diff --git a/TabPFN_Demo_Local.ipynb b/TabPFN_Demo_Local.ipynb
index 57fb795ab..3d15b0fc7 100644
--- a/TabPFN_Demo_Local.ipynb
+++ b/TabPFN_Demo_Local.ipynb
@@ -1,9340 +1,6818 @@
 {
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "tisgLOuqzrfo"
-      },
-      "source": [
-        "# TabPFN Hands-On-Demo\n",
-        "\n",
-        "**Welcome to this enhanced and educational walkthrough of TabPFN!**\n",
-        "\n",
-        "TabPFN is a novel machine learning model that is exceptionally fast and requires no hyperparameter tuning. It is particularly powerful for tabular data, which is a common data format in many real-world applications. This notebook will not only demonstrate how to use TabPFN but also provide clear explanations of the underlying concepts.\n",
-        "\n",
-        "**What you will learn:**\n",
-        "\n",
-        "* What TabPFN is and why it's a game-changer for tabular data.\n",
-        "* How to set up and run TabPFN on your local machine or using the client API.\n",
-        "* How to use TabPFN for both classification and regression tasks.\n",
-        "* A comparison of TabPFN's performance against other popular models like XGBoost and RandomForest.\n",
-        "* Advanced features of TabPFN, including handling text data, unsupervised learning, and model interpretability.\n",
-        "\n",
-        "Let's get started!\n",
-        "\n",
-        "\n",
-        "\n",
-        "## Table of Contents\n",
-        "\n",
-        "1.  [Installation](#installation)\n",
-        "2.  [Backend Selection](#backend-selection)\n",
-        "3.  [**Classification with TabPFN**](#classification)\n",
-        "4.  [**Regression with TabPFN**](#regression)\n",
-        "5.  [Handling Text Data](#text-data)\n",
-        "6.  [Unsupervised Learning with TabPFN](#unsupervised-learning)\n",
-        "   - Data Imputation\n",
-        "   - Anomaly Detection\n",
-        "   - Clustering Applications\n",
-        "7.  [Model Interpretability](#interpretability)\n",
-        "   - Feature Importance Analysis\n",
-        "   - Explaining Predictions with SHAP\n",
-        "   - Extracting and Visualizing Embeddings\n",
-        "8.  [Predictive Behavior](#behavior)\n",
-        "9.  [**Time Series Prediction with TabPFN**](#timeseries)\n",
-        "9.  [Using TabPFN to estimate the effect of causal interventions](#causal)\n"
-      ]
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tisgLOuqzrfo"
+   },
+   "source": [
+    "# TabPFN Hands-On-Demo\n",
+    "\n",
+    "**Welcome to this enhanced and educational walkthrough of TabPFN!**\n",
+    "\n",
+    "TabPFN is a novel machine learning model that is exceptionally fast and requires no hyperparameter tuning. It is particularly powerful for tabular data, which is a common data format in many real-world applications. This notebook will not only demonstrate how to use TabPFN but also provide clear explanations of the underlying concepts.\n",
+    "\n",
+    "**What you will learn:**\n",
+    "\n",
+    "* What TabPFN is and why it's a game-changer for tabular data.\n",
+    "* How to set up and run TabPFN on your local machine or using the client API.\n",
+    "* How to use TabPFN for both classification and regression tasks.\n",
+    "* A comparison of TabPFN's performance against other popular models like XGBoost and RandomForest.\n",
+    "* Advanced features of TabPFN, including handling text data, unsupervised learning, and model interpretability.\n",
+    "\n",
+    "Let's get started!\n",
+    "\n",
+    "\n",
+    "\n",
+    "## Table of Contents\n",
+    "\n",
+    "1.  [Installation](#installation)\n",
+    "2.  [Backend Selection](#backend-selection)\n",
+    "3.  [**Classification with TabPFN**](#classification)\n",
+    "4.  [**Regression with TabPFN**](#regression)\n",
+    "5.  [Handling Text Data](#text-data)\n",
+    "6.  [Unsupervised Learning with TabPFN](#unsupervised-learning)\n",
+    "   - Data Imputation\n",
+    "   - Anomaly Detection\n",
+    "   - Clustering Applications\n",
+    "7.  [Model Interpretability](#interpretability)\n",
+    "   - Feature Importance Analysis\n",
+    "   - Explaining Predictions with SHAP\n",
+    "   - Extracting and Visualizing Embeddings\n",
+    "8.  [Predictive Behavior](#behavior)\n",
+    "9.  [**Time Series Prediction with TabPFN**](#timeseries)\n",
+    "9.  [Using TabPFN to estimate the effect of causal interventions](#causal)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "o03aOVAw0Etg"
+   },
+   "source": [
+    "# Installation [Running this cell required!] <a name=\"installation\"></a>\n",
+    "\n",
+    "First, we need to install the necessary libraries. This includes TabPFN itself, as well as other libraries for data manipulation and baseline model comparisons. If you are asked to restart the runtime after installation, please do so.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "collapsed": true,
+    "id": "agAt8X7T0N6P",
+    "jupyter": {
+     "outputs_hidden": true
+    },
+    "outputId": "27bf5620-2f8d-43af-b7e3-9882c3db8a66"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "o03aOVAw0Etg"
-      },
-      "source": [
-        "# Installation [Running this cell required!] <a name=\"installation\"></a>\n",
-        "\n",
-        "First, we need to install the necessary libraries. This includes TabPFN itself, as well as other libraries for data manipulation and baseline model comparisons. If you are asked to restart the runtime after installation, please do so.\n"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
+      "\u001b[2K\u001b[2mResolved \u001b[1m21 packages\u001b[0m \u001b[2min 203ms\u001b[0m\u001b[0m\n",
+      "\u001b[2K\u001b[2mPrepared \u001b[1m1 package\u001b[0m \u001b[2min 1.31s\u001b[0m\u001b[0m\n",
+      "\u001b[2K\u001b[2mInstalled \u001b[1m1 package\u001b[0m \u001b[2min 5ms\u001b[0m\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mcatboost\u001b[0m\u001b[2m==1.2.8\u001b[0m\n",
+      "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
+      "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 102ms\u001b[0m\u001b[0m\n",
+      "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
+      "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 140ms\u001b[0m\u001b[0m\n",
+      "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
+      "\u001b[2K\u001b[2mResolved \u001b[1m34 packages\u001b[0m \u001b[2min 746ms\u001b[0m\u001b[0m\n",
+      "\u001b[2K\u001b[2mPrepared \u001b[1m4 packages\u001b[0m \u001b[2min 78ms\u001b[0m\u001b[0m\n",
+      "\u001b[2K\u001b[2mInstalled \u001b[1m4 packages\u001b[0m \u001b[2min 6ms\u001b[0m\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mbackoff\u001b[0m\u001b[2m==2.2.1\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mpassword-strength\u001b[0m\u001b[2m==0.0.3.post2\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1msseclient-py\u001b[0m\u001b[2m==1.8.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mtabpfn-client\u001b[0m\u001b[2m==0.2.8\u001b[0m\n",
+      "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
+      "\u001b[2K\u001b[2mResolved \u001b[1m91 packages\u001b[0m \u001b[2min 1.47s\u001b[0m\u001b[0m\n",
+      "\u001b[2K\u001b[2mPrepared \u001b[1m18 packages\u001b[0m \u001b[2min 1.07s\u001b[0m\u001b[0m\n",
+      "\u001b[2mUninstalled \u001b[1m1 package\u001b[0m \u001b[2min 4ms\u001b[0m\u001b[0m\n",
+      "\u001b[2K\u001b[2mInstalled \u001b[1m18 packages\u001b[0m \u001b[2min 152ms\u001b[0m\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mautogluon-common\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mautogluon-core\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mautogluon-features\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mautogluon-tabular\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mboto3\u001b[0m\u001b[2m==1.40.67\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mbotocore\u001b[0m\u001b[2m==1.40.67\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1meval-type-backport\u001b[0m\u001b[2m==0.2.2\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mgalois\u001b[0m\u001b[2m==0.4.6\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mjmespath\u001b[0m\u001b[2m==1.0.1\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mkditransform\u001b[0m\u001b[2m==1.2.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mposthog\u001b[0m\u001b[2m==6.9.0\u001b[0m\n",
+      " \u001b[31m-\u001b[39m \u001b[1mrequests\u001b[0m\u001b[2m==2.32.4\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mrequests\u001b[0m\u001b[2m==2.32.5\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1ms3transfer\u001b[0m\u001b[2m==0.14.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mshapiq\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1msparse-transform\u001b[0m\u001b[2m==0.2.1\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mtabpfn\u001b[0m\u001b[2m==6.0.4\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mtabpfn-common-utils\u001b[0m\u001b[2m==0.2.7\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mtabpfn-extensions\u001b[0m\u001b[2m==0.2.0\u001b[0m\n",
+      "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
+      "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 168ms\u001b[0m\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "## Base library Installation\n",
+    "# Install Baselines for model comparison\n",
+    "!uv pip install catboost xgboost\n",
+    "\n",
+    "# Install the datasets library for loading example data\n",
+    "!uv pip install datasets\n",
+    "\n",
+    "# Install rich for better and more readable printing\n",
+    "!uv pip install rich\n",
+    "\n",
+    "## TabPFN Installation optimized for Google Colab\n",
+    "# Install the TabPFN Client library\n",
+    "!uv pip install tabpfn-client\n",
+    "\n",
+    "# Install TabPFN extensions for additional functionalities\n",
+    "!uv pip install 'tabpfn-extensions[all]'\n",
+    "\n",
+    "# Install tabpfn\n",
+    "!uv pip install tabpfn"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "p8RTKDLrJAAr"
+   },
+   "source": [
+    "***Note: remember to restart the runtime after the installation.***"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "iro4vB3w4rgE"
+   },
+   "source": [
+    "# Necessary Imports for the Notebook [Running this cell required!]\n",
+    "\n",
+    "Now that the libraries are installed, let's import all the necessary modules for this notebook.\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "id": "uVEqqRwQ4W1H"
+   },
+   "outputs": [],
+   "source": [
+    "# Standard Library Imports\n",
+    "\n",
+    "# TabPFN and Extensions\n",
+    "\n",
+    "try:\n",
+    "    from tabpfn_extensions.post_hoc_ensembles.sklearn_interface import (\n",
+    "        AutoTabPFNClassifier,\n",
+    "    )\n",
+    "\n",
+    "    from tabpfn import TabPFNClassifier, TabPFNRegressor\n",
+    "except ImportError:\n",
+    "    raise ImportError(\n",
+    "        \"Warning: Could not import TabPFN / TabPFN extensions. Please run installation above and restart the session afterwards (Runtime > Restart Session).\"\n",
+    "    )\n",
+    "\n",
+    "# Data Science & Visualization\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import torch\n",
+    "\n",
+    "# Other ML Models\n",
+    "from catboost import CatBoostClassifier, CatBoostRegressor\n",
+    "\n",
+    "# Notebook UI/Display\n",
+    "from IPython.display import Markdown, display\n",
+    "from rich.console import Console\n",
+    "from rich.panel import Panel\n",
+    "from rich.prompt import Prompt\n",
+    "from rich.rule import Rule\n",
+    "from sklearn.compose import make_column_selector, make_column_transformer\n",
+    "\n",
+    "# Scikit-Learn: Data & Preprocessing\n",
+    "from sklearn.datasets import fetch_openml, load_breast_cancer\n",
+    "\n",
+    "# Scikit-Learn: Models\n",
+    "from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor\n",
+    "from sklearn.metrics import mean_squared_error, roc_auc_score\n",
+    "from sklearn.model_selection import (\n",
+    "    KFold,\n",
+    "    StratifiedKFold,\n",
+    "    cross_val_score,\n",
+    "    train_test_split,\n",
+    ")\n",
+    "from sklearn.pipeline import make_pipeline\n",
+    "from sklearn.preprocessing import LabelEncoder, OrdinalEncoder\n",
+    "from xgboost import XGBClassifier, XGBRegressor\n",
+    "\n",
+    "# This transformer will be used to handle categorical features for the baseline models\n",
+    "column_transformer = make_column_transformer(\n",
+    "    (\n",
+    "        OrdinalEncoder(handle_unknown=\"use_encoded_value\", unknown_value=-1),\n",
+    "        make_column_selector(dtype_include=[\"object\", \"category\"]),\n",
+    "    ),\n",
+    "    remainder=\"passthrough\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "4I4uUwflTY3i"
+   },
+   "source": [
+    "# Backend Selection [Running this cell required!] <a name=\"backend-selection\"></a>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "QUq82Au7UdXk"
+   },
+   "source": [
+    "\n",
+    "TabPFN can be run in two ways: locally on your machine (if you have a GPU) or by using the TabPFN client, which sends the data to a server for computation.\n",
+    "In your project you would either use the **local** version (which requires a GPU) with:\n",
+    "```python\n",
+    "# Simple import for TabPFN\n",
+    "from tabpfn import TabPFNClassifier\n",
+    "\n",
+    "# Now you can use it like any other sklearn classifier\n",
+    "# model = TabPFNClassifier()\n",
+    "print(\"TabPFNClassifier imported successfully.\")\n",
+    "```\n",
+    "\n",
+    "or the **client** API (which uses a remote server):\n",
+    "\n",
+    "```python\n",
+    "# Simple import for TabPFN\n",
+    "from tabpfn_client import TabPFNClassifier\n",
+    "\n",
+    "# Now you can use it like any other sklearn classifier\n",
+    "# model = TabPFNClassifier()\n",
+    "print(\"TabPFNClassifier imported successfully.\")\n",
+    "```\n",
+    "\n",
+    "If you select **local** and it's your first time using the model, you'll need to accept the license agreement and log into Hugging Face.\n",
+    "You'll be prompted with instructions on how to do this the first time you fit the model.\n",
+    "\n",
+    "For demonstration purposes, the cell below provides an interactive way to switch between local mode and the client:\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 694,
+     "referenced_widgets": [
+      "0b0d8924f58949a2ba8c5de2dc99d9b2",
+      "80873b8fc8734802a2422304e627a233"
+     ]
     },
+    "id": "pJVAXg2YoDdF",
+    "outputId": "0857a1f6-4dcf-47b3-e156-3ff23157363f"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 1,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "collapsed": true,
-        "id": "agAt8X7T0N6P",
-        "outputId": "4061bfcd-8a83-45ba-fd87-7e4b76c8aeb1"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2K\u001b[2mResolved \u001b[1m21 packages\u001b[0m \u001b[2min 287ms\u001b[0m\u001b[0m\n",
-            "\u001b[2K\u001b[2mPrepared \u001b[1m1 package\u001b[0m \u001b[2min 1.66s\u001b[0m\u001b[0m\n",
-            "\u001b[2K\u001b[2mInstalled \u001b[1m1 package\u001b[0m \u001b[2min 11ms\u001b[0m\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mcatboost\u001b[0m\u001b[2m==1.2.8\u001b[0m\n",
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 242ms\u001b[0m\u001b[0m\n",
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 179ms\u001b[0m\u001b[0m\n",
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2K\u001b[2mResolved \u001b[1m34 packages\u001b[0m \u001b[2min 268ms\u001b[0m\u001b[0m\n",
-            "\u001b[2K\u001b[2mPrepared \u001b[1m4 packages\u001b[0m \u001b[2min 112ms\u001b[0m\u001b[0m\n",
-            "\u001b[2K\u001b[2mInstalled \u001b[1m4 packages\u001b[0m \u001b[2min 11ms\u001b[0m\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mbackoff\u001b[0m\u001b[2m==2.2.1\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mpassword-strength\u001b[0m\u001b[2m==0.0.3.post2\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1msseclient-py\u001b[0m\u001b[2m==1.8.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mtabpfn-client\u001b[0m\u001b[2m==0.2.8\u001b[0m\n",
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2K\u001b[2mResolved \u001b[1m91 packages\u001b[0m \u001b[2min 1.01s\u001b[0m\u001b[0m\n",
-            "\u001b[2K\u001b[2mPrepared \u001b[1m18 packages\u001b[0m \u001b[2min 1.62s\u001b[0m\u001b[0m\n",
-            "\u001b[2mUninstalled \u001b[1m1 package\u001b[0m \u001b[2min 2ms\u001b[0m\u001b[0m\n",
-            "\u001b[2K\u001b[2mInstalled \u001b[1m18 packages\u001b[0m \u001b[2min 237ms\u001b[0m\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mautogluon-common\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mautogluon-core\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mautogluon-features\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mautogluon-tabular\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mboto3\u001b[0m\u001b[2m==1.40.67\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mbotocore\u001b[0m\u001b[2m==1.40.67\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1meval-type-backport\u001b[0m\u001b[2m==0.2.2\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mgalois\u001b[0m\u001b[2m==0.4.6\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mjmespath\u001b[0m\u001b[2m==1.0.1\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mkditransform\u001b[0m\u001b[2m==1.2.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mposthog\u001b[0m\u001b[2m==6.9.0\u001b[0m\n",
-            " \u001b[31m-\u001b[39m \u001b[1mrequests\u001b[0m\u001b[2m==2.32.4\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mrequests\u001b[0m\u001b[2m==2.32.5\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1ms3transfer\u001b[0m\u001b[2m==0.14.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mshapiq\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1msparse-transform\u001b[0m\u001b[2m==0.2.1\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mtabpfn\u001b[0m\u001b[2m==6.0.3\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mtabpfn-common-utils\u001b[0m\u001b[2m==0.2.6\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mtabpfn-extensions\u001b[0m\u001b[2m==0.2.0\u001b[0m\n",
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 241ms\u001b[0m\u001b[0m\n"
-          ]
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">╭────────────────────────────────╮\n",
+       "│ <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">TabPFN Demo: Backend Selection</span> │\n",
+       "╰────────────────────────────────╯\n",
+       "</pre>\n"
       ],
-      "source": [
-        "## Base library Installation\n",
-        "# Install Baselines for model comparison\n",
-        "!uv pip install catboost xgboost\n",
-        "\n",
-        "# Install the datasets library for loading example data\n",
-        "!uv pip install datasets\n",
-        "\n",
-        "# Install rich for better and more readable printing\n",
-        "!uv pip install rich\n",
-        "\n",
-        "## TabPFN Installation optimized for Google Colab\n",
-        "# Install the TabPFN Client library\n",
-        "!uv pip install tabpfn-client\n",
-        "\n",
-        "# Install TabPFN extensions for additional functionalities\n",
-        "!uv pip install tabpfn-extensions[all]\n",
-        "\n",
-        "# Install tabpfn\n",
-        "!uv pip install tabpfn"
+      "text/plain": [
+       "╭────────────────────────────────╮\n",
+       "│ \u001b[1;35mTabPFN Demo: Backend Selection\u001b[0m │\n",
+       "╰────────────────────────────────╯\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "p8RTKDLrJAAr"
-      },
-      "source": [
-        "***Note: remember to restart the runtime after the installation.***"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "This script can run TabPFN using one of two backends:\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "This script can run TabPFN using one of two backends:\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "iro4vB3w4rgE"
-      },
-      "source": [
-        "# Necessary Imports for the Notebook [Running this cell required!]\n",
-        "\n",
-        "Now that the libraries are installed, let's import all the necessary modules for this notebook.\n",
-        "\n",
-        "\n"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span><span style=\"font-weight: bold\">. local:</span> Uses a local GPU <span style=\"font-weight: bold\">(</span>NVIDIA<span style=\"font-weight: bold\">)</span>. Requires CUDA.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "  \u001b[1;36m1\u001b[0m\u001b[1m. local:\u001b[0m Uses a local GPU \u001b[1m(\u001b[0mNVIDIA\u001b[1m)\u001b[0m. Requires CUDA.\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 2,
-      "metadata": {
-        "id": "uVEqqRwQ4W1H"
-      },
-      "outputs": [],
-      "source": [
-        "# Standard Library Imports\n",
-        "\n",
-        "# TabPFN and Extensions\n",
-        "\n",
-        "try:\n",
-        "    from tabpfn_extensions.post_hoc_ensembles.sklearn_interface import (\n",
-        "        AutoTabPFNClassifier,\n",
-        "    )\n",
-        "\n",
-        "    from tabpfn import TabPFNClassifier, TabPFNRegressor\n",
-        "except ImportError:\n",
-        "    raise ImportError(\n",
-        "        \"Warning: Could not import TabPFN / TabPFN extensions. Please run installation above and restart the session afterwards (Runtime > Restart Session).\"\n",
-        "    )\n",
-        "\n",
-        "# Data Science & Visualization\n",
-        "import matplotlib.pyplot as plt\n",
-        "import numpy as np\n",
-        "import pandas as pd\n",
-        "import torch\n",
-        "\n",
-        "# Other ML Models\n",
-        "from catboost import CatBoostClassifier, CatBoostRegressor\n",
-        "\n",
-        "# Notebook UI/Display\n",
-        "from IPython.display import Markdown, display\n",
-        "from rich.console import Console\n",
-        "from rich.panel import Panel\n",
-        "from rich.prompt import Prompt\n",
-        "from rich.rule import Rule\n",
-        "from sklearn.compose import make_column_selector, make_column_transformer\n",
-        "\n",
-        "# Scikit-Learn: Data & Preprocessing\n",
-        "from sklearn.datasets import fetch_openml, load_breast_cancer\n",
-        "\n",
-        "# Scikit-Learn: Models\n",
-        "from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor\n",
-        "from sklearn.metrics import mean_squared_error, roc_auc_score\n",
-        "from sklearn.model_selection import (\n",
-        "    KFold,\n",
-        "    StratifiedKFold,\n",
-        "    cross_val_score,\n",
-        "    train_test_split,\n",
-        ")\n",
-        "from sklearn.pipeline import make_pipeline\n",
-        "from sklearn.preprocessing import LabelEncoder, OrdinalEncoder\n",
-        "from xgboost import XGBClassifier, XGBRegressor\n",
-        "\n",
-        "# This transformer will be used to handle categorical features for the baseline models\n",
-        "column_transformer = make_column_transformer(\n",
-        "    (\n",
-        "        OrdinalEncoder(handle_unknown=\"use_encoded_value\", unknown_value=-1),\n",
-        "        make_column_selector(dtype_include=[\"object\", \"category\"]),\n",
-        "    ),\n",
-        "    remainder=\"passthrough\",\n",
-        ")"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span><span style=\"font-weight: bold\">. client:</span> Uses the TabPFN API. Requires an internet connection and a free account.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "  \u001b[1;36m2\u001b[0m\u001b[1m. client:\u001b[0m Uses the TabPFN API. Requires an internet connection and a free account.\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "4I4uUwflTY3i"
-      },
-      "source": [
-        "# Backend Selection [Running this cell required!] <a name=\"backend-selection\"></a>"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<span style=\"font-weight: bold\">Choose your backend</span> - If not field to enter is shown restart the cell. <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">[client/local]</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">(client)</span>: </pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "\u001b[1mChoose your backend\u001b[0m - If not field to enter is shown restart the cell. \u001b[1;35m[client/local]\u001b[0m \u001b[1;36m(client)\u001b[0m: "
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "QUq82Au7UdXk"
-      },
-      "source": [
-        "\n",
-        "TabPFN can be run in two ways: locally on your machine (if you have a GPU) or by using the TabPFN client, which sends the data to a server for computation.\n",
-        "In your project you would either use the local version (which requires a GPU) with :\n",
-        "```python\n",
-        "# Simple import for TabPFN\n",
-        "from tabpfn import TabPFNClassifier\n",
-        "\n",
-        "# Now you can use it like any other sklearn classifier\n",
-        "# model = TabPFNClassifier()\n",
-        "print(\"TabPFNClassifier imported successfully.\")\n",
-        "```\n",
-        "\n",
-        "or the **client** API (which uses a remote server):\n",
-        "\n",
-        "```python\n",
-        "# Simple import for TabPFN\n",
-        "from tabpfn_client import TabPFNClassifier\n",
-        "\n",
-        "# Now you can use it like any other sklearn classifier\n",
-        "# model = TabPFNClassifier()\n",
-        "print(\"TabPFNClassifier imported successfully.\")\n",
-        "```\n",
-        "\n",
-        "\n",
-        "For demonstration purposes, the cell below provides an interactive way to switch between those:\n"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "client\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 5,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 269,
-          "referenced_widgets": [
-            "c8ebb291f21c453ca4a320acba3b8411",
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-            "d3f75ae0f8b547f7bcc16acee7811bd3",
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-            "f4ff55a5dd534f26af360e693a41d71d",
-            "57a47265175f4d2ea7cf38b89de152ed",
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-            "dbb5f30af0ea4aac9fe0fb446ea8f44a",
-            "c569e8946f954d569ab61a2d0ca82f72",
-            "b459baa1c9a948a2bb23a9f52a484f87",
-            "9e3a6817cc2947c68cf4b05f5fddc5a2",
-            "12ccb93856a14d68ab532f54627a3032",
-            "c0232f349cb64d5b9da0b469eb3fd79b",
-            "86499ee4ec064f38aab981eb69d5fbe9",
-            "c4259046e97447c0b83be4391e4bebd0",
-            "2c970ec9eeed45f5b9c9405d5a5b818d",
-            "e36a97b9286a4c81b86d3b9ca9778669",
-            "76812559c3ed4220a567014135b88777",
-            "66384a1bee794f159243a0fe1fa98eee"
-          ]
-        },
-        "id": "pJVAXg2YoDdF",
-        "outputId": "ba7fec4b-b622-48a2-dccc-2843ef9f9bf8"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "╭────────────────────────────────╮\n",
-              "│ \u001b[1;35mTabPFN Demo: Backend Selection\u001b[0m │\n",
-              "╰────────────────────────────────╯\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">╭────────────────────────────────╮\n",
-              "│ <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">TabPFN Demo: Backend Selection</span> │\n",
-              "╰────────────────────────────────╯\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\n",
-              "This script can run TabPFN using one of two backends:\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-              "This script can run TabPFN using one of two backends:\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "  \u001b[1;36m1\u001b[0m\u001b[1m. local:\u001b[0m Uses a local GPU \u001b[1m(\u001b[0mNVIDIA\u001b[1m)\u001b[0m. Requires CUDA.\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span><span style=\"font-weight: bold\">. local:</span> Uses a local GPU <span style=\"font-weight: bold\">(</span>NVIDIA<span style=\"font-weight: bold\">)</span>. Requires CUDA.\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "  \u001b[1;36m2\u001b[0m\u001b[1m. client:\u001b[0m Uses the TabPFN API. Requires an internet connection and a free account.\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span><span style=\"font-weight: bold\">. client:</span> Uses the TabPFN API. Requires an internet connection and a free account.\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\n",
-              "\u001b[1mChoose your backend\u001b[0m - If not field to enter is shown restart the cell. \u001b[1;35m[client/local]\u001b[0m \u001b[1;36m(client)\u001b[0m: "
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-              "<span style=\"font-weight: bold\">Choose your backend</span> - If not field to enter is shown restart the cell. <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">[client/local]</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">(client)</span>: </pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "local\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\n",
-              "✅ You have selected the \u001b[32m'\u001b[0m\u001b[1;32mlocal\u001b[0m\u001b[32m'\u001b[0m backend.\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-              "✅ You have selected the <span style=\"color: #008000; text-decoration-color: #008000\">'</span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">local</span><span style=\"color: #008000; text-decoration-color: #008000\">'</span> backend.\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\u001b[92m──────────────────────────────────────────── \u001b[0m\u001b[1mSetting up \u001b[0m\u001b[1;36mlocal\u001b[0m\u001b[1m backend\u001b[0m\u001b[92m ─────────────────────────────────────────────\u001b[0m\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">──────────────────────────────────────────── </span><span style=\"font-weight: bold\">Setting up </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">local</span><span style=\"font-weight: bold\"> backend</span><span style=\"color: #00ff00; text-decoration-color: #00ff00\"> ─────────────────────────────────────────────</span>\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 84ms\u001b[0m\u001b[0m\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "Attempting local backend setup\u001b[33m...\u001b[0m\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Attempting local backend setup<span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\u001b[1;32m✅ GPU is available.\u001b[0m Importing local TabPFN library\u001b[33m...\u001b[0m\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">✅ GPU is available.</span> Importing local TabPFN library<span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
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-          "data": {
-            "text/plain": [
-              "\u001b[1;32m✅ TabPFN \u001b[0m\u001b[1;32m(\u001b[0m\u001b[1;32mlocal\u001b[0m\u001b[1;32m)\u001b[0m\u001b[1;32m imported successfully.\u001b[0m\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">✅ TabPFN (local) imported successfully.</span>\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "✅ You have selected the <span style=\"color: #008000; text-decoration-color: #008000\">'</span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">client</span><span style=\"color: #008000; text-decoration-color: #008000\">'</span> backend.\n",
+       "</pre>\n"
       ],
-      "source": [
-        "console = Console()\n",
-        "\n",
-        "console.print(Panel.fit(\"[bold magenta]TabPFN Demo: Backend Selection[/bold magenta]\"))\n",
-        "console.print(\"\\nThis script can run TabPFN using one of two backends:\")\n",
-        "console.print(\"  [bold]1. local:[/bold] Uses a local GPU (NVIDIA). Requires CUDA.\")\n",
-        "console.print(\n",
-        "    \"  [bold]2. client:[/bold] Uses the TabPFN API. Requires an internet connection and a free account.\"\n",
-        ")\n",
-        "\n",
-        "backend = Prompt.ask(\n",
-        "    \"\\n[bold]Choose your backend[/bold] - If not field to enter is shown restart the cell.\",\n",
-        "    choices=[\"client\", \"local\"],\n",
-        "    default=\"client\",\n",
-        ")\n",
-        "\n",
-        "console.print(\n",
-        "    f\"\\n✅ You have selected the '[bold green]{backend}[/bold green]' backend.\"\n",
-        ")\n",
-        "\n",
-        "console.print(Rule(f\"[bold]Setting up [cyan]{backend}[/cyan] backend[/bold]\"))\n",
-        "\n",
-        "if backend == \"local\":\n",
-        "    !uv pip install huggingface_hub\n",
-        "\n",
-        "    console.print(\"Attempting local backend setup...\")\n",
-        "    import torch\n",
-        "\n",
-        "    if not torch.cuda.is_available():\n",
-        "        console.print(\n",
-        "            \"[bold red]Error:[/bold red] GPU device not found. For fast training, please enable GPU.\",\n",
-        "            style=\"red\",\n",
-        "        )\n",
-        "        console.print(\n",
-        "            \"In Colab: Go to [bold]Runtime -> Change runtime type -> Hardware accelerator -> GPU.[/bold]\",\n",
-        "            style=\"yellow\",\n",
-        "        )\n",
-        "        raise SystemError(\"GPU device not found.\")\n",
-        "    console.print(\n",
-        "        \"[bold green]✅ GPU is available.[/bold green] Importing local TabPFN library...\"\n",
-        "    )\n",
-        "\n",
-        "    from huggingface_hub import login\n",
-        "    login()\n",
-        "\n",
-        "    from tabpfn import TabPFNClassifier, TabPFNRegressor\n",
-        "\n",
-        "    console.print(\"[bold green]✅ TabPFN (local) imported successfully.[/bold green]\")\n",
-        "elif backend == \"client\":\n",
-        "    console.print(\"Attempting client backend setup...\")\n",
-        "    console.print(\"Importing TabPFN client library...\")\n",
-        "    from tabpfn_client import TabPFNClassifier, TabPFNRegressor, init\n",
-        "\n",
-        "    init()\n",
-        "    console.print(\"[bold green]✅ TabPFN (client) initialized.[/bold green]\")"
+      "text/plain": [
+       "\n",
+       "✅ You have selected the \u001b[32m'\u001b[0m\u001b[1;32mclient\u001b[0m\u001b[32m'\u001b[0m backend.\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "c8iQ9KEd1h9R"
-      },
-      "source": [
-        "# Classification with TabPFN <a name=\"classification\"></a>\n",
-        "\n",
-        "Now, let's dive into a practical example of using TabPFN for a classification task. We will use the well-known Parkinson's Disease dataset. The goal is to predict the presence of Parkinson's disease based on various voice measurements.\n",
-        "\n",
-        "We will compare TabPFN's performance against other popular machine learning models: RandomForest, XGBoost, and CatBoost. The performance metric we will use is the [ROC AUC](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html) score.\n"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">──────────────────────────────────────────── </span><span style=\"font-weight: bold\">Setting up </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">client</span><span style=\"font-weight: bold\"> backend</span><span style=\"color: #00ff00; text-decoration-color: #00ff00\"> ────────────────────────────────────────────</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[92m──────────────────────────────────────────── \u001b[0m\u001b[1mSetting up \u001b[0m\u001b[1;36mclient\u001b[0m\u001b[1m backend\u001b[0m\u001b[92m ────────────────────────────────────────────\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "source": [
-        "### **Loading Parkinson’s Disease Dataset**\n",
-        "\n",
-        "**Source:**  \n",
-        "The dataset was created by _Max Little_ of the **University of Oxford**, in collaboration with the **National Centre for Voice and Speech**, Denver, Colorado. The dataset consists of biomedical voice measurements collected from individuals, and the original study published the feature extraction methods for general voice disorders.\n",
-        "\n",
-        "### **Dataset Overview**\n",
-        "\n",
-        "-   **Number of subjects:** 31\n",
-        "    \n",
-        "-   **Number of Parkinson’s disease (PD) patients:** 23\n",
-        "    \n",
-        "-   **Total recordings:** 195 voice samples\n",
-        "    \n",
-        "-   **Goal:** To discriminate healthy individuals (status = 0) from those with Parkinson’s disease (status = 1).\n",
-        "    \n",
-        "-   **Identifier column:** `name` (subject name and recording number)\n",
-        "    \n",
-        "\n",
-        "<details>\n",
-        "If you use this dataset, please cite:\n",
-        "\n",
-        "> Max A. Little, Patrick E. McSharry, Eric J. Hunter, Lorraine O. Ramig (2008).  \n",
-        "> _Suitability of dysphonia measurements for telemonitoring of Parkinson's disease._  \n",
-        "> IEEE Transactions on Biomedical Engineering.\n",
-        "\n",
-        "* * *\n",
-        "\n",
-        "\n",
-        "\n",
-        "* * *\n",
-        "\n",
-        "### **Attribute Information**\n",
-        "\n",
-        "Each row corresponds to a voice recording, and each column represents a distinct biomedical voice measure.\n",
-        "\n",
-        "**Feature Name**\n",
-        "\n",
-        "**Description**\n",
-        "\n",
-        "`name`\n",
-        "\n",
-        "ASCII subject name and recording number\n",
-        "\n",
-        "`MDVP:Fo(Hz)`\n",
-        "\n",
-        "Average vocal fundamental frequency\n",
-        "\n",
-        "`MDVP:Fhi(Hz)`\n",
-        "\n",
-        "Maximum vocal fundamental frequency\n",
-        "\n",
-        "`MDVP:Flo(Hz)`\n",
-        "\n",
-        "Minimum vocal fundamental frequency\n",
-        "\n",
-        "`MDVP:Jitter(%)`, `MDVP:Jitter(Abs)`, `MDVP:RAP`, `MDVP:PPQ`, `Jitter:DDP`\n",
-        "\n",
-        "Measures of variation in fundamental frequency\n",
-        "\n",
-        "`MDVP:Shimmer`, `MDVP:Shimmer(dB)`, `Shimmer:APQ3`, `Shimmer:APQ5`, `MDVP:APQ`, `Shimmer:DDA`\n",
-        "\n",
-        "Measures of variation in amplitude\n",
-        "\n",
-        "`NHR`, `HNR`\n",
-        "\n",
-        "Ratios of noise to tonal components in the voice\n",
-        "\n",
-        "`status`\n",
-        "\n",
-        "Health status of the subject (`0` = healthy, `1` = Parkinson’s disease)\n",
-        "\n",
-        "`RPDE`, `D2`\n",
-        "\n",
-        "Nonlinear dynamical complexity measures\n",
-        "\n",
-        "`DFA`\n",
-        "\n",
-        "Signal fractal scaling exponent\n",
-        "\n",
-        "`spread1`, `spread2`, `PPE`\n",
-        "\n",
-        "Nonlinear measures of fundamental frequency variation\n",
-        "</details>\n"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Attempting client backend setup<span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
+       "</pre>\n"
       ],
-      "metadata": {
-        "id": "PNtRCHyLG1D5"
-      }
+      "text/plain": [
+       "Attempting client backend setup\u001b[33m...\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 6,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 423
-        },
-        "id": "tTQe5IprKLV5",
-        "outputId": "257f73da-f6d0-48a3-8340-31c7cde14191"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "     MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
-              "0        119.992       157.302        74.997         0.00784   \n",
-              "1        122.400       148.650       113.819         0.00968   \n",
-              "2        116.682       131.111       111.555         0.01050   \n",
-              "3        116.676       137.871       111.366         0.00997   \n",
-              "4        116.014       141.781       110.655         0.01284   \n",
-              "..           ...           ...           ...             ...   \n",
-              "190      174.188       230.978        94.261         0.00459   \n",
-              "191      209.516       253.017        89.488         0.00564   \n",
-              "192      174.688       240.005        74.287         0.01360   \n",
-              "193      198.764       396.961        74.904         0.00740   \n",
-              "194      214.289       260.277        77.973         0.00567   \n",
-              "\n",
-              "     MDVP:Jitter(Abs)  MDVP:RAP  MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  \\\n",
-              "0             0.00007   0.00370   0.00554     0.01109       0.04374   \n",
-              "1             0.00008   0.00465   0.00696     0.01394       0.06134   \n",
-              "2             0.00009   0.00544   0.00781     0.01633       0.05233   \n",
-              "3             0.00009   0.00502   0.00698     0.01505       0.05492   \n",
-              "4             0.00011   0.00655   0.00908     0.01966       0.06425   \n",
-              "..                ...       ...       ...         ...           ...   \n",
-              "190           0.00003   0.00263   0.00259     0.00790       0.04087   \n",
-              "191           0.00003   0.00331   0.00292     0.00994       0.02751   \n",
-              "192           0.00008   0.00624   0.00564     0.01873       0.02308   \n",
-              "193           0.00004   0.00370   0.00390     0.01109       0.02296   \n",
-              "194           0.00003   0.00295   0.00317     0.00885       0.01884   \n",
-              "\n",
-              "     MDVP:Shimmer(dB)  ...  MDVP:APQ  Shimmer:DDA      NHR     HNR      RPDE  \\\n",
-              "0               0.426  ...   0.02971      0.06545  0.02211  21.033  0.414783   \n",
-              "1               0.626  ...   0.04368      0.09403  0.01929  19.085  0.458359   \n",
-              "2               0.482  ...   0.03590      0.08270  0.01309  20.651  0.429895   \n",
-              "3               0.517  ...   0.03772      0.08771  0.01353  20.644  0.434969   \n",
-              "4               0.584  ...   0.04465      0.10470  0.01767  19.649  0.417356   \n",
-              "..                ...  ...       ...          ...      ...     ...       ...   \n",
-              "190             0.405  ...   0.02745      0.07008  0.02764  19.517  0.448439   \n",
-              "191             0.263  ...   0.01879      0.04812  0.01810  19.147  0.431674   \n",
-              "192             0.256  ...   0.01667      0.03804  0.10715  17.883  0.407567   \n",
-              "193             0.241  ...   0.01588      0.03794  0.07223  19.020  0.451221   \n",
-              "194             0.190  ...   0.01373      0.03078  0.04398  21.209  0.462803   \n",
-              "\n",
-              "          DFA   spread1   spread2        D2       PPE  \n",
-              "0    0.815285 -4.813031  0.266482  2.301442  0.284654  \n",
-              "1    0.819521 -4.075192  0.335590  2.486855  0.368674  \n",
-              "2    0.825288 -4.443179  0.311173  2.342259  0.332634  \n",
-              "3    0.819235 -4.117501  0.334147  2.405554  0.368975  \n",
-              "4    0.823484 -3.747787  0.234513  2.332180  0.410335  \n",
-              "..        ...       ...       ...       ...       ...  \n",
-              "190  0.657899 -6.538586  0.121952  2.657476  0.133050  \n",
-              "191  0.683244 -6.195325  0.129303  2.784312  0.168895  \n",
-              "192  0.655683 -6.787197  0.158453  2.679772  0.131728  \n",
-              "193  0.643956 -6.744577  0.207454  2.138608  0.123306  \n",
-              "194  0.664357 -5.724056  0.190667  2.555477  0.148569  \n",
-              "\n",
-              "[195 rows x 22 columns]"
-            ],
-            "text/html": [
-              "\n",
-              "  <div id=\"df-8c51f1e7-e80e-416b-adca-2c8c56205e3e\" class=\"colab-df-container\">\n",
-              "    <div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>MDVP:Fo(Hz)</th>\n",
-              "      <th>MDVP:Fhi(Hz)</th>\n",
-              "      <th>MDVP:Flo(Hz)</th>\n",
-              "      <th>MDVP:Jitter(%)</th>\n",
-              "      <th>MDVP:Jitter(Abs)</th>\n",
-              "      <th>MDVP:RAP</th>\n",
-              "      <th>MDVP:PPQ</th>\n",
-              "      <th>Jitter:DDP</th>\n",
-              "      <th>MDVP:Shimmer</th>\n",
-              "      <th>MDVP:Shimmer(dB)</th>\n",
-              "      <th>...</th>\n",
-              "      <th>MDVP:APQ</th>\n",
-              "      <th>Shimmer:DDA</th>\n",
-              "      <th>NHR</th>\n",
-              "      <th>HNR</th>\n",
-              "      <th>RPDE</th>\n",
-              "      <th>DFA</th>\n",
-              "      <th>spread1</th>\n",
-              "      <th>spread2</th>\n",
-              "      <th>D2</th>\n",
-              "      <th>PPE</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>119.992</td>\n",
-              "      <td>157.302</td>\n",
-              "      <td>74.997</td>\n",
-              "      <td>0.00784</td>\n",
-              "      <td>0.00007</td>\n",
-              "      <td>0.00370</td>\n",
-              "      <td>0.00554</td>\n",
-              "      <td>0.01109</td>\n",
-              "      <td>0.04374</td>\n",
-              "      <td>0.426</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.02971</td>\n",
-              "      <td>0.06545</td>\n",
-              "      <td>0.02211</td>\n",
-              "      <td>21.033</td>\n",
-              "      <td>0.414783</td>\n",
-              "      <td>0.815285</td>\n",
-              "      <td>-4.813031</td>\n",
-              "      <td>0.266482</td>\n",
-              "      <td>2.301442</td>\n",
-              "      <td>0.284654</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>122.400</td>\n",
-              "      <td>148.650</td>\n",
-              "      <td>113.819</td>\n",
-              "      <td>0.00968</td>\n",
-              "      <td>0.00008</td>\n",
-              "      <td>0.00465</td>\n",
-              "      <td>0.00696</td>\n",
-              "      <td>0.01394</td>\n",
-              "      <td>0.06134</td>\n",
-              "      <td>0.626</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.04368</td>\n",
-              "      <td>0.09403</td>\n",
-              "      <td>0.01929</td>\n",
-              "      <td>19.085</td>\n",
-              "      <td>0.458359</td>\n",
-              "      <td>0.819521</td>\n",
-              "      <td>-4.075192</td>\n",
-              "      <td>0.335590</td>\n",
-              "      <td>2.486855</td>\n",
-              "      <td>0.368674</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>116.682</td>\n",
-              "      <td>131.111</td>\n",
-              "      <td>111.555</td>\n",
-              "      <td>0.01050</td>\n",
-              "      <td>0.00009</td>\n",
-              "      <td>0.00544</td>\n",
-              "      <td>0.00781</td>\n",
-              "      <td>0.01633</td>\n",
-              "      <td>0.05233</td>\n",
-              "      <td>0.482</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.03590</td>\n",
-              "      <td>0.08270</td>\n",
-              "      <td>0.01309</td>\n",
-              "      <td>20.651</td>\n",
-              "      <td>0.429895</td>\n",
-              "      <td>0.825288</td>\n",
-              "      <td>-4.443179</td>\n",
-              "      <td>0.311173</td>\n",
-              "      <td>2.342259</td>\n",
-              "      <td>0.332634</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>116.676</td>\n",
-              "      <td>137.871</td>\n",
-              "      <td>111.366</td>\n",
-              "      <td>0.00997</td>\n",
-              "      <td>0.00009</td>\n",
-              "      <td>0.00502</td>\n",
-              "      <td>0.00698</td>\n",
-              "      <td>0.01505</td>\n",
-              "      <td>0.05492</td>\n",
-              "      <td>0.517</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.03772</td>\n",
-              "      <td>0.08771</td>\n",
-              "      <td>0.01353</td>\n",
-              "      <td>20.644</td>\n",
-              "      <td>0.434969</td>\n",
-              "      <td>0.819235</td>\n",
-              "      <td>-4.117501</td>\n",
-              "      <td>0.334147</td>\n",
-              "      <td>2.405554</td>\n",
-              "      <td>0.368975</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>116.014</td>\n",
-              "      <td>141.781</td>\n",
-              "      <td>110.655</td>\n",
-              "      <td>0.01284</td>\n",
-              "      <td>0.00011</td>\n",
-              "      <td>0.00655</td>\n",
-              "      <td>0.00908</td>\n",
-              "      <td>0.01966</td>\n",
-              "      <td>0.06425</td>\n",
-              "      <td>0.584</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.04465</td>\n",
-              "      <td>0.10470</td>\n",
-              "      <td>0.01767</td>\n",
-              "      <td>19.649</td>\n",
-              "      <td>0.417356</td>\n",
-              "      <td>0.823484</td>\n",
-              "      <td>-3.747787</td>\n",
-              "      <td>0.234513</td>\n",
-              "      <td>2.332180</td>\n",
-              "      <td>0.410335</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>190</th>\n",
-              "      <td>174.188</td>\n",
-              "      <td>230.978</td>\n",
-              "      <td>94.261</td>\n",
-              "      <td>0.00459</td>\n",
-              "      <td>0.00003</td>\n",
-              "      <td>0.00263</td>\n",
-              "      <td>0.00259</td>\n",
-              "      <td>0.00790</td>\n",
-              "      <td>0.04087</td>\n",
-              "      <td>0.405</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.02745</td>\n",
-              "      <td>0.07008</td>\n",
-              "      <td>0.02764</td>\n",
-              "      <td>19.517</td>\n",
-              "      <td>0.448439</td>\n",
-              "      <td>0.657899</td>\n",
-              "      <td>-6.538586</td>\n",
-              "      <td>0.121952</td>\n",
-              "      <td>2.657476</td>\n",
-              "      <td>0.133050</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>191</th>\n",
-              "      <td>209.516</td>\n",
-              "      <td>253.017</td>\n",
-              "      <td>89.488</td>\n",
-              "      <td>0.00564</td>\n",
-              "      <td>0.00003</td>\n",
-              "      <td>0.00331</td>\n",
-              "      <td>0.00292</td>\n",
-              "      <td>0.00994</td>\n",
-              "      <td>0.02751</td>\n",
-              "      <td>0.263</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.01879</td>\n",
-              "      <td>0.04812</td>\n",
-              "      <td>0.01810</td>\n",
-              "      <td>19.147</td>\n",
-              "      <td>0.431674</td>\n",
-              "      <td>0.683244</td>\n",
-              "      <td>-6.195325</td>\n",
-              "      <td>0.129303</td>\n",
-              "      <td>2.784312</td>\n",
-              "      <td>0.168895</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>192</th>\n",
-              "      <td>174.688</td>\n",
-              "      <td>240.005</td>\n",
-              "      <td>74.287</td>\n",
-              "      <td>0.01360</td>\n",
-              "      <td>0.00008</td>\n",
-              "      <td>0.00624</td>\n",
-              "      <td>0.00564</td>\n",
-              "      <td>0.01873</td>\n",
-              "      <td>0.02308</td>\n",
-              "      <td>0.256</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.01667</td>\n",
-              "      <td>0.03804</td>\n",
-              "      <td>0.10715</td>\n",
-              "      <td>17.883</td>\n",
-              "      <td>0.407567</td>\n",
-              "      <td>0.655683</td>\n",
-              "      <td>-6.787197</td>\n",
-              "      <td>0.158453</td>\n",
-              "      <td>2.679772</td>\n",
-              "      <td>0.131728</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>193</th>\n",
-              "      <td>198.764</td>\n",
-              "      <td>396.961</td>\n",
-              "      <td>74.904</td>\n",
-              "      <td>0.00740</td>\n",
-              "      <td>0.00004</td>\n",
-              "      <td>0.00370</td>\n",
-              "      <td>0.00390</td>\n",
-              "      <td>0.01109</td>\n",
-              "      <td>0.02296</td>\n",
-              "      <td>0.241</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.01588</td>\n",
-              "      <td>0.03794</td>\n",
-              "      <td>0.07223</td>\n",
-              "      <td>19.020</td>\n",
-              "      <td>0.451221</td>\n",
-              "      <td>0.643956</td>\n",
-              "      <td>-6.744577</td>\n",
-              "      <td>0.207454</td>\n",
-              "      <td>2.138608</td>\n",
-              "      <td>0.123306</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>194</th>\n",
-              "      <td>214.289</td>\n",
-              "      <td>260.277</td>\n",
-              "      <td>77.973</td>\n",
-              "      <td>0.00567</td>\n",
-              "      <td>0.00003</td>\n",
-              "      <td>0.00295</td>\n",
-              "      <td>0.00317</td>\n",
-              "      <td>0.00885</td>\n",
-              "      <td>0.01884</td>\n",
-              "      <td>0.190</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.01373</td>\n",
-              "      <td>0.03078</td>\n",
-              "      <td>0.04398</td>\n",
-              "      <td>21.209</td>\n",
-              "      <td>0.462803</td>\n",
-              "      <td>0.664357</td>\n",
-              "      <td>-5.724056</td>\n",
-              "      <td>0.190667</td>\n",
-              "      <td>2.555477</td>\n",
-              "      <td>0.148569</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>195 rows × 22 columns</p>\n",
-              "</div>\n",
-              "    <div class=\"colab-df-buttons\">\n",
-              "\n",
-              "  <div class=\"colab-df-container\">\n",
-              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8c51f1e7-e80e-416b-adca-2c8c56205e3e')\"\n",
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-              "  </svg>\n",
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-              "\n",
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-              "    .colab-df-container {\n",
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-              "\n",
-              "    .colab-df-buttons div {\n",
-              "      margin-bottom: 4px;\n",
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-              "\n",
-              "    [theme=dark] .colab-df-convert {\n",
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-              "\n",
-              "    [theme=dark] .colab-df-convert:hover {\n",
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-              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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-              "        document.querySelector('#df-8c51f1e7-e80e-416b-adca-2c8c56205e3e button.colab-df-convert');\n",
-              "      buttonEl.style.display =\n",
-              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
-              "\n",
-              "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-8c51f1e7-e80e-416b-adca-2c8c56205e3e');\n",
-              "        const dataTable =\n",
-              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
-              "                                                    [key], {});\n",
-              "        if (!dataTable) return;\n",
-              "\n",
-              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
-              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
-              "          + ' to learn more about interactive tables.';\n",
-              "        element.innerHTML = '';\n",
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-              "\n",
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-              "                title=\"Suggest charts\"\n",
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-              "\n",
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-              "</svg>\n",
-              "      </button>\n",
-              "\n",
-              "<style>\n",
-              "  .colab-df-quickchart {\n",
-              "      --bg-color: #E8F0FE;\n",
-              "      --fill-color: #1967D2;\n",
-              "      --hover-bg-color: #E2EBFA;\n",
-              "      --hover-fill-color: #174EA6;\n",
-              "      --disabled-fill-color: #AAA;\n",
-              "      --disabled-bg-color: #DDD;\n",
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-              "\n",
-              "  [theme=dark] .colab-df-quickchart {\n",
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-              "      --fill-color: #D2E3FC;\n",
-              "      --hover-bg-color: #434B5C;\n",
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-              "      --disabled-bg-color: #3B4455;\n",
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-              "\n",
-              "  .colab-df-quickchart {\n",
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-              "    border: none;\n",
-              "    border-radius: 50%;\n",
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-              "    padding: 0;\n",
-              "    width: 32px;\n",
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-              "\n",
-              "  .colab-df-quickchart:hover {\n",
-              "    background-color: var(--hover-bg-color);\n",
-              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
-              "    fill: var(--button-hover-fill-color);\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart-complete:disabled,\n",
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-              "    background-color: var(--disabled-bg-color);\n",
-              "    fill: var(--disabled-fill-color);\n",
-              "    box-shadow: none;\n",
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-              "\n",
-              "  .colab-df-spinner {\n",
-              "    border: 2px solid var(--fill-color);\n",
-              "    border-color: transparent;\n",
-              "    border-bottom-color: var(--fill-color);\n",
-              "    animation:\n",
-              "      spin 1s steps(1) infinite;\n",
-              "  }\n",
-              "\n",
-              "  @keyframes spin {\n",
-              "    0% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
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-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "      border-right-color: var(--fill-color);\n",
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-              "    40% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
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-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    80% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "    90% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "  }\n",
-              "</style>\n",
-              "\n",
-              "      <script>\n",
-              "        async function quickchart(key) {\n",
-              "          const quickchartButtonEl =\n",
-              "            document.querySelector('#' + key + ' button');\n",
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-              "            const charts = await google.colab.kernel.invokeFunction(\n",
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-              "\n",
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-              "\n",
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-              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('X')\"\n",
-              "            title=\"Generate code using this dataframe.\"\n",
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-              "\n",
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-            "application/vnd.google.colaboratory.intrinsic+json": {
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-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Importing TabPFN client library<span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
+       "</pre>\n"
       ],
-      "source": [
-        "# Load Parkinsons dataset described above\n",
-        "\n",
-        "import pandas as pd, io, zipfile, requests\n",
-        "\n",
-        "url_zip = \"https://archive.ics.uci.edu/static/public/174/parkinsons.zip\"\n",
-        "with requests.get(url_zip) as r:\n",
-        "    r.raise_for_status()\n",
-        "    zf = zipfile.ZipFile(io.BytesIO(r.content))\n",
-        "    df = pd.read_csv(zf.open(\"parkinsons.data\"))\n",
-        "X, y = df.drop([\"status\", \"name\"], axis=1), df[\"status\"]\n",
-        "\n",
-        "display(X)"
+      "text/plain": [
+       "Importing TabPFN client library\u001b[33m...\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 7,
-      "metadata": {
-        "id": "KAXhoOc2U2vJ"
-      },
-      "outputs": [],
-      "source": [
-        "# Alternative datasets (commented for reference):\n",
-        "\n",
-        "# Cholesterol dataset: Predict cholesterol levels\n",
-        "# Features: Patient characteristics, medical measurements\n",
-        "# Samples: 303 patients\n",
-        "# Target: Cholesterol levels in mg/dl\n",
-        "# df = fetch_openml('cholesterol', version=2, as_frame=True)\n",
-        "\n",
-        "# Heart Disease dataset (Statlog): Predict presence of heart disease\n",
-        "# Features: Clinical and test measurements\n",
-        "# Samples: 270 patients\n",
-        "# Target: Binary heart disease diagnosis\n",
-        "# df = fetch_openml(\"heart-statlog\", version=1)\n",
-        "\n",
-        "# Diabetes dataset: Predict diabetes presence\n",
-        "# Features: Medical measurements, patient history\n",
-        "# Samples: 768 patients\n",
-        "# Target: Binary diabetes diagnosis\n",
-        "# df = fetch_openml(\"diabetes\", version=1)"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">########  ########   ###  #########  #########       ###         #####     ########  ########</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">     ###        ##   ###  ###   ###        ###       ###        ###  ###   ##   ###  ###     </span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">########  #######    ###  ###   ###  #######         ###        ########   ######    ########</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">###       ###   ##   ###  ###   ###  ###   ###       ###        ###  ###   ##   ###       ###</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">###       ###   ##   ###  #########  ###   ###       ########   ###  ###   ########  ########                      </span>\n",
+       "\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "\u001b[1;34m########  ########   ###  #########  #########       ###         #####     ########  ########\u001b[0m\n",
+       "\u001b[1;34m     ###        ##   ###  ###   ###        ###       ###        ###  ###   ##   ###  ###     \u001b[0m\n",
+       "\u001b[1;34m########  #######    ###  ###   ###  #######         ###        ########   ######    ########\u001b[0m\n",
+       "\u001b[1;34m###       ###   ##   ###  ###   ###  ###   ###       ###        ###  ###   ##   ###       ###\u001b[0m\n",
+       "\u001b[1;34m###       ###   ##   ###  #########  ###   ###       ########   ###  ###   ########  ########                      \u001b[0m\n",
+       "\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 7,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 0,
-          "referenced_widgets": [
-            "b30ee01485d34573826cb3f230e7adc9",
-            "3a317e1783f34146a59efab8dddce055",
-            "2ee156d35f204bec99b9ee0b8f1a8bf2",
-            "1c91deb2188942c5be9247a7141bf809",
-            "a00a874d0491494b82d6f79e38710991",
-            "6bb024c1725a47c3b04e4443b5f0a5ae",
-            "fe4e99c718614d6fb36b7a13c77937ff",
-            "c0b2e071a7424279bd94603c6af4084e",
-            "ebf32e3765d94172a009dd7ce26a483c",
-            "9fa4f151143548179254843fe97c72b5",
-            "2c533f77b75e4512a384e00038564755",
-            "685956e02a614623b44834afda9ffc87",
-            "aebbe55445184de2a02b5d082884b42d",
-            "b25aba14f90049daa1f7a1b0f25049fe",
-            "0f9ab1f340fe47deb7ad8fe948c18833",
-            "d2a9043880474366a790019f1d9be003",
-            "90f2e6589a194b19b50e6069a39e7f6d",
-            "8e662a0751bb4ed6905e1da717463f01",
-            "22a12af56fdf4c7c85031d923320050f",
-            "d880ef9056334388920649327d967afa",
-            "9a192b54ffd146d4bd6a3cb6fcc1b6dc",
-            "44ab539ab5ed45a288f07a12f13c6225"
-          ]
-        },
-        "id": "zTHzDedu3DKR",
-        "outputId": "250b8218-b919-44ee-bb56-7c1b257941f3"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "tabpfn-v2.5-classifier-v2.5_default.ckpt:   0%|          | 0.00/42.9M [00:00<?, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "b30ee01485d34573826cb3f230e7adc9"
-            }
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "config.json:   0%|          | 0.00/35.0 [00:00<?, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "685956e02a614623b44834afda9ffc87"
-            }
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "TabPFN ROC AUC Score: 0.9732\n"
-          ]
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">Thanks for being part of the journey</span>\n",
+       "\n",
+       "</pre>\n"
       ],
-      "source": [
-        "# Split the data into training and testing sets\n",
-        "X_train, X_test, y_train, y_test = train_test_split(\n",
-        "    X, y, test_size=0.20, random_state=42\n",
-        ")\n",
-        "\n",
-        "# Train and evaluate the TabPFN classifier\n",
-        "tabpfn_classifier = TabPFNClassifier(random_state=42)\n",
-        "tabpfn_classifier.fit(X_train, y_train)\n",
-        "y_pred_proba = tabpfn_classifier.predict_proba(X_test)\n",
-        "\n",
-        "# Calculate the ROC AUC score\n",
-        "roc_auc = roc_auc_score(y_test, y_pred_proba[:, 1])\n",
-        "print(f\"TabPFN ROC AUC Score: {roc_auc:.4f}\")"
+      "text/plain": [
+       "\u001b[2mThanks for being part of the journey\u001b[0m\n",
+       "\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "ZVs_HfxbVCs3"
-      },
-      "source": [
-        "### Comparing TabPFN with Other Classifiers\n",
-        "\n",
-        "To get a better sense of TabPFN's performance, let's compare it with other popular classification models using cross-validation. This will give us a more robust estimate of each model's performance.\n"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  TabPFN is under active development, please help us improve and report any bugs/ideas you find.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "  TabPFN is under active development, please help us improve and report any bugs/ideas you find.\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 8,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 0
-        },
-        "id": "ITuXXhqE7Fps",
-        "outputId": "81e1f6f0-31d5-4a99-9911-358f78bbc0d7"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    2.0s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.5s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.1s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    8.6s finished\n"
-          ]
-        },
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "Text(0.5, 1.0, 'Model Comparison - 3-fold Cross-validation')"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 8
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 1000x600 with 1 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #000080; text-decoration-color: #000080\">Report issues: </span><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">https://github.com/priorlabs/tabpfn-client/issues</span>\n",
+       "</pre>\n"
       ],
-      "source": [
-        "# Compare different machine learning models by training each one multiple times\n",
-        "# on different parts of the data and averaging their performance scores for a\n",
-        "# more reliable performance estimate\n",
-        "\n",
-        "# Encode target labels to classes for baselines\n",
-        "le = LabelEncoder()\n",
-        "y = le.fit_transform(y)\n",
-        "\n",
-        "# Define models\n",
-        "models = [\n",
-        "    (\"TabPFN\", TabPFNClassifier(random_state=42)),\n",
-        "    (\n",
-        "        \"RandomForest\",\n",
-        "        make_pipeline(\n",
-        "            column_transformer,  # string data needs to be encoded for model\n",
-        "            RandomForestClassifier(random_state=42),\n",
-        "        ),\n",
-        "    ),\n",
-        "    (\n",
-        "        \"XGBoost\",\n",
-        "        make_pipeline(\n",
-        "            column_transformer,  # string data needs to be encoded for model\n",
-        "            XGBClassifier(random_state=42),\n",
-        "        ),\n",
-        "    ),\n",
-        "    (\n",
-        "        \"CatBoost\",\n",
-        "        make_pipeline(\n",
-        "            column_transformer,  # string data needs to be encoded for model\n",
-        "            CatBoostClassifier(random_state=42, verbose=0),\n",
-        "        ),\n",
-        "    ),\n",
-        "]\n",
-        "\n",
-        "# Calculate scores\n",
-        "n_splits = 3\n",
-        "cv = StratifiedKFold(n_splits=n_splits, random_state=42, shuffle=True)\n",
-        "scoring = \"roc_auc_ovr\" if len(np.unique(y)) > 2 else \"roc_auc\"\n",
-        "scores = {\n",
-        "    name: cross_val_score(model, X, y, cv=cv, scoring=scoring, n_jobs=1, verbose=1)\n",
-        "    for name, model in models\n",
-        "}\n",
-        "\n",
-        "# Plot results\n",
-        "df = pd.DataFrame(\n",
-        "    [(k, v.mean()) for (k, v) in scores.items()], columns=[\"Model\", \"ROC AUC\"]\n",
-        ")\n",
-        "ax = df.plot(x=\"Model\", y=\"ROC AUC\", kind=\"bar\", figsize=(10, 6))\n",
-        "ax.set_ylim(df[\"ROC AUC\"].min() * 0.995, min(1.0, df[\"ROC AUC\"].max() * 1.005))\n",
-        "ax.set_title(f\"Model Comparison - {n_splits}-fold Cross-validation\")"
+      "text/plain": [
+       "  \u001b[34mReport issues: \u001b[0m\u001b[4;34mhttps://github.com/priorlabs/tabpfn-client/issues\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "ipG2Cpb7Jrc7"
-      },
-      "source": [
-        "# Regression with TabPFN <a name=\"regression\"></a>\n",
-        "\n",
-        "Next, we'll explore how to use TabPFN for regression tasks. We will use the Boston Housing dataset, where the goal is to predict the median value of owner-occupied homes.\n",
-        "\n",
-        "We will measure performance using the [Root Mean Squared Error](https://scikit-learn.org/1.5/modules/generated/sklearn.metrics.root_mean_squared_error.html), and again, we will compare TabPFN with other popular regression models."
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #000080; text-decoration-color: #000080\">Press Ctrl+C anytime to exit</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "  \u001b[34mPress Ctrl+C anytime to exit\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "source": [
-        "### **Loading Boston Housing Dataset**\n",
-        "\n",
-        "### **Dataset Overview**\n",
-        "\n",
-        "-   **Objective:** Predict the **median value of owner-occupied homes** in the Boston area based on various socioeconomic and environmental attributes.\n",
-        "    \n",
-        "-   **Number of Instances:** 506\n",
-        "    \n",
-        "-   **Number of Attributes:** 14 (13 numeric features + 1 target variable)\n",
-        "    \n",
-        "-   **Target Variable:** `MEDV` — Median value of owner-occupied homes (in $1000s)\n",
-        "    \n",
-        "-   **Class Type:** Numeric\n",
-        "    \n",
-        "-   **Class Index:** Last\n",
-        "    \n",
-        "\n",
-        "* * *\n",
-        "\n",
-        "<details>\n",
-        "\n",
-        "\n",
-        "**Citation:**\n",
-        "\n",
-        "> Harrison, D. and Rubinfeld, D.L. (1978).  \n",
-        "> _Hedonic prices and the demand for clean air._  \n",
-        "> _Journal of Environmental Economics & Management_, 5, 81–102.  \n",
-        "> Used in Belsley, Kuh & Welsch, _Regression Diagnostics: Identifying Influential Data and Sources of Collinearity_, Wiley, 1980.\n",
-        "\n",
-        "\n",
-        "### **Attribute Information**\n",
-        "\n",
-        "**Feature**\n",
-        "\n",
-        "**Description**\n",
-        "\n",
-        "`CRIM`\n",
-        "\n",
-        "Per capita crime rate by town\n",
-        "\n",
-        "`ZN`\n",
-        "\n",
-        "Proportion of residential land zoned for lots over 25,000 sq.ft.\n",
-        "\n",
-        "`INDUS`\n",
-        "\n",
-        "Proportion of non-retail business acres per town\n",
-        "\n",
-        "`CHAS`\n",
-        "\n",
-        "Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)\n",
-        "\n",
-        "`NOX`\n",
-        "\n",
-        "Nitric oxides concentration (parts per 10 million)\n",
-        "\n",
-        "`RM`\n",
-        "\n",
-        "Average number of rooms per dwelling\n",
-        "\n",
-        "`AGE`\n",
-        "\n",
-        "Proportion of owner-occupied units built prior to 1940\n",
-        "\n",
-        "`DIS`\n",
-        "\n",
-        "Weighted distances to five Boston employment centres\n",
-        "\n",
-        "`RAD`\n",
-        "\n",
-        "Index of accessibility to radial highways\n",
-        "\n",
-        "`TAX`\n",
-        "\n",
-        "Full-value property-tax rate per $10,000\n",
-        "\n",
-        "`PTRATIO`\n",
-        "\n",
-        "Pupil–teacher ratio by town\n",
-        "\n",
-        "`B`\n",
-        "\n",
-        "1000(Bk − 0.63)², where Bk is the proportion of Blacks by town\n",
-        "\n",
-        "`LSTAT`\n",
-        "\n",
-        "Percentage of lower status population\n",
-        "\n",
-        "`MEDV`\n",
-        "\n",
-        "Median value of owner-occupied homes (in $1000s)\n",
-        "\n",
-        "</details>"
-      ],
-      "metadata": {
-        "id": "Qzrj9m0fI32f"
-      }
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Opening browser for login. Please complete the login/registration process in your browser and return here.\n",
+      "\n",
+      "\n",
+      "Could not open browser automatically. Falling back to command-line login...\n",
+      "\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "source": [
-        "# Load the Boston Housing dataset\n",
-        "\n",
-        "import pandas as pd, requests\n",
-        "from IPython.display import display, Markdown\n",
-        "\n",
-        "cols = [\"CRIM\",\"ZN\",\"INDUS\",\"CHAS\",\"NOX\",\"RM\",\"AGE\",\"DIS\",\"RAD\",\"TAX\",\"PTRATIO\",\"B\",\"LSTAT\",\"MEDV\"]\n",
-        "df_boston = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data\",\n",
-        "                        delim_whitespace=True, header=None, names=cols)\n",
-        "X, y = df_boston.drop(columns=[\"MEDV\"]), df_boston[\"MEDV\"]\n",
-        "\n",
-        "display(X.head())\n"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
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-          "text": [
-            "/tmp/ipython-input-378995386.py:7: FutureWarning: The 'delim_whitespace' keyword in pd.read_csv is deprecated and will be removed in a future version. Use ``sep='\\s+'`` instead\n",
-            "  df_boston = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data\",\n"
-          ]
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-              "      CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
-              "0  0.00632  18.0   2.31     0  0.538  6.575  65.2  4.0900    1  296.0   \n",
-              "1  0.02731   0.0   7.07     0  0.469  6.421  78.9  4.9671    2  242.0   \n",
-              "2  0.02729   0.0   7.07     0  0.469  7.185  61.1  4.9671    2  242.0   \n",
-              "3  0.03237   0.0   2.18     0  0.458  6.998  45.8  6.0622    3  222.0   \n",
-              "4  0.06905   0.0   2.18     0  0.458  7.147  54.2  6.0622    3  222.0   \n",
-              "\n",
-              "   PTRATIO       B  LSTAT  \n",
-              "0     15.3  396.90   4.98  \n",
-              "1     17.8  396.90   9.14  \n",
-              "2     17.8  392.83   4.03  \n",
-              "3     18.7  394.63   2.94  \n",
-              "4     18.7  396.90   5.33  "
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-              "      <td>2.94</td>\n",
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-            }
-          },
-          "metadata": {}
-        }
+      "text/plain": [
+       "\n",
+       "\n"
       ]
+     },
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+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 10,
-      "metadata": {
-        "id": "YaA7WBuEVdQy"
-      },
-      "outputs": [],
-      "source": [
-        "# Alternative datasets (commented for reference):\n",
-        "\n",
-        "# Liver Disorders dataset\n",
-        "# Classification task: Predict liver disorder presence\n",
-        "# Features: Blood test results, alcohol consumption\n",
-        "# Samples: 345 patients\n",
-        "# Target: Binary liver disorder diagnosis\n",
-        "# df = fetch_openml(\"liver-disorders\", version=1)\n",
-        "\n",
-        "# Grid Stability dataset\n",
-        "# Regression task: Predict electrical grid stability\n",
-        "# Features: Power system measurements, grid parameters\n",
-        "# Samples: 10,000 simulations\n",
-        "# Target: Grid stability score\n",
-        "# df = fetch_openml(data_id=44973, as_frame=True)\n",
-        "\n",
-        "# Concrete Compressive Strength dataset\n",
-        "# Regression task: Predict concrete strength\n",
-        "# Features: Concrete components (cement, water, aggregates)\n",
-        "# Samples: 1,030 concrete samples\n",
-        "# Target: Compressive strength in MPa\n",
-        "# df = fetch_openml(data_id=44959, as_frame=True)"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">[1]    </span> Create a TabPFN account     \n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">[2]    </span> Login to your TabPFN account\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">[q]    </span> Quit                        \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;34m[1]   \u001b[0m\u001b[1;34m \u001b[0m Create a TabPFN account     \n",
+       "\u001b[1;34m[2]   \u001b[0m\u001b[1;34m \u001b[0m Login to your TabPFN account\n",
+       "\u001b[1;34m[q]   \u001b[0m\u001b[1;34m \u001b[0m Quit                        \n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 11,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 0,
-          "referenced_widgets": [
-            "32a2b737742b406887e8a6e078922b01",
-            "7d12f4927a1c4b418697813349b3d512",
-            "0df8b18da346497c835542ca3273d1de",
-            "ef478cd34d4c4e7b93b2f976df9cf0aa",
-            "d3e165a844f64c6284344e0a25978607",
-            "073d6915cf3d4a33bb98425f3431fcf8",
-            "d504601435584d72a44816b57c53bdbd",
-            "319d093f756748b7994edd02321b978d",
-            "1caddc4636ae4a9eb81d426b6cb8c95a",
-            "fe0193e4450c4762b76e672ab749e807",
-            "266e7f2275d1499eb828d2ff42dc3181",
-            "ef0bd01494074f3789cc86b43c50f93b",
-            "34c01ecf372d40ce8ebe78b3517e6735",
-            "45da61d443a04a0da4a6841464bb3bde",
-            "94a1568298f74d56bc53cebf91c8c3d5",
-            "8986a96f12c04e3b91782089e4af8d75",
-            "338703c876984c08899cafd92b8154ba",
-            "c48dbfcb14ff4739aa5a289d167dfeeb",
-            "66802619c84d4852bf53d419a2bba226",
-            "4ad890c87f4e4774906d1bd5bce01f75",
-            "af3622d7ad5441c6a84a24f391e5beca",
-            "3d981bc2a5e64318ba5438b024960ff8"
-          ]
-        },
-        "id": "rWqC16PL7R_T",
-        "outputId": "21cd4312-d533-47e0-a07a-eb646d080116"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "tabpfn-v2.5-regressor-v2.5_default.ckpt:   0%|          | 0.00/40.8M [00:00<?, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "32a2b737742b406887e8a6e078922b01"
-            }
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "config.json:   0%|          | 0.00/35.0 [00:00<?, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "ef0bd01494074f3789cc86b43c50f93b"
-            }
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "TabPFN RMSE: 2.6538\n"
-          ]
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">→</span> Choose <span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/q<span style=\"font-weight: bold\">)</span>: </pre>\n"
       ],
-      "source": [
-        "# Split the data\n",
-        "X_train, X_test, y_train, y_test = train_test_split(\n",
-        "    X, y, test_size=0.33, random_state=42\n",
-        ")\n",
-        "\n",
-        "# Train and evaluate the TabPFN regressor\n",
-        "tabpfn_regressor = TabPFNRegressor(random_state=42)\n",
-        "tabpfn_regressor.fit(X_train, y_train)\n",
-        "y_pred = tabpfn_regressor.predict(X_test)\n",
-        "\n",
-        "# Calculate the Root Mean Squared Error\n",
-        "rmse = np.sqrt(mean_squared_error(y_test, y_pred))\n",
-        "print(f\"TabPFN RMSE: {rmse:.4f}\")"
+      "text/plain": [
+       "\n",
+       "\u001b[1;34m→\u001b[0m Choose \u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m/\u001b[1;36m2\u001b[0m/q\u001b[1m)\u001b[0m: "
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "Itu5-vVRWEMA"
-      },
-      "source": [
-        "### Comparing TabPFN with Other Regressors\n",
-        "\n",
-        "Now, let's see how TabPFN's regression performance stacks up against other models using cross-validation.\n"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 12,
-      "metadata": {
-        "id": "0XLxgbqSPe55",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 0
-        },
-        "outputId": "4728bee7-eb16-44d6-af06-602b3d59cbb6"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    1.8s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    1.1s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.4s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    5.9s finished\n"
-          ]
-        },
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "Text(0.5, 1.0, 'Model Comparison - 3-fold Cross-validation \\n (Variance Explained - Larger is better)')"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 12
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 1000x600 with 1 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<span style=\"font-weight: bold\">Login</span>\n",
+       "</pre>\n"
       ],
-      "source": [
-        "# Compare different machine learning models by training each one multiple times\n",
-        "# on different parts of the data and averaging their performance scores for a\n",
-        "# more reliable performance estimate\n",
-        "\n",
-        "# Define models\n",
-        "models = [\n",
-        "    (\"TabPFN\", TabPFNRegressor(random_state=42)),\n",
-        "    (\n",
-        "        \"RandomForest\",\n",
-        "        make_pipeline(\n",
-        "            column_transformer,  # string data needs to be encoded for model\n",
-        "            RandomForestRegressor(random_state=42),\n",
-        "        ),\n",
-        "    ),\n",
-        "    (\n",
-        "        \"XGBoost\",\n",
-        "        make_pipeline(\n",
-        "            column_transformer,  # string data needs to be encoded for model\n",
-        "            XGBRegressor(random_state=42),\n",
-        "        ),\n",
-        "    ),\n",
-        "    (\n",
-        "        \"CatBoost\",\n",
-        "        make_pipeline(\n",
-        "            column_transformer,  # string data needs to be encoded for model\n",
-        "            CatBoostRegressor(random_state=42, verbose=0),\n",
-        "        ),\n",
-        "    ),\n",
-        "]\n",
-        "\n",
-        "# Calculate scores\n",
-        "scoring = \"r2\"\n",
-        "n_splits = 3\n",
-        "cv = KFold(n_splits=n_splits, random_state=42, shuffle=True)\n",
-        "scores = {\n",
-        "    name: cross_val_score(model, X, y, cv=cv, scoring=scoring, n_jobs=1, verbose=1)\n",
-        "    for name, model in models\n",
-        "}\n",
-        "\n",
-        "\n",
-        "# Plot results\n",
-        "df = pd.DataFrame([(k, v.mean()) for (k, v) in scores.items()], columns=[\"Model\", \"R2\"])\n",
-        "ax = df.plot(x=\"Model\", y=\"R2\", kind=\"bar\", figsize=(10, 6))\n",
-        "ax.set_ylim(df[\"R2\"].min() * 0.99, df[\"R2\"].max() * 1.01)\n",
-        "ax.set_title(\n",
-        "    f\"Model Comparison - {n_splits}-fold Cross-validation \\n (Variance Explained - Larger is better)\"\n",
-        ")"
+      "text/plain": [
+       "\n",
+       "\u001b[1mLogin\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "3uGfjIdjsCg-"
-      },
-      "source": [
-        "# Handling Text Data <a name=\"text-data\"></a>\n",
-        "\n",
-        "A powerful feature of the TabPFN server is its ability to handle text data directly, without the need for manual feature engineering. This simplifies the process of working with datasets that contain a mix of numerical and textual features.\n",
-        "\n",
-        "**Note:** This feature is only available when using the 'client' backend."
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Email: </pre>\n"
+      ],
+      "text/plain": [
+       "Email: "
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "vYBdSZnor-at"
-      },
-      "outputs": [],
-      "source": [
-        "if backend != \"client\":\n",
-        "    console.print(\n",
-        "        Panel(\n",
-        "            \"[bold yellow]Text data can only be processed through the TabPFN server. Please restart the notebook and select the 'client' backend to run this section.[/bold yellow]\",\n",
-        "            title=\"[bold yellow]Warning\",\n",
-        "            border_style=\"yellow\",\n",
-        "        )\n",
-        "    )\n",
-        "else:\n",
-        "    # We will use gdown to download the dataset\n",
-        "    !gdown --fuzzy \"17bJekFGIAxbrdcBeBIvcyZjneweY581E\"\n",
-        "\n",
-        "    # Load the clothing review dataset\n",
-        "    # We restrict to 500 rows to make the example faster\n",
-        "    df_text = pd.read_csv(\"cloth.csv\", index_col=0).dropna()[:500]\n",
-        "\n",
-        "    # Define features and target\n",
-        "    y_text = df_text[\"Rating\"]\n",
-        "    X_text = df_text.drop(columns=[\"Rating\"])\n",
-        "\n",
-        "    print(\"Text dataset loaded successfully!\")\n",
-        "    display(X_text.head())"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "noah@priorlabs.ai\n",
+      "Password: ··········\n"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "iQkFQD_rWi1v"
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0b0d8924f58949a2ba8c5de2dc99d9b2",
+       "version_major": 2,
+       "version_minor": 0
       },
-      "source": [
-        "### Comparing Text Handling\n",
-        "\n",
-        "Now, let's compare how TabPFN handles text natively versus how a baseline model like RandomForest needs a specific text processing pipeline.\n",
-        "\n",
-        "For baselines, we will create a pipeline that converts strings to ordinal features.\n",
-        "\n",
-        "For TabPFN, we simply pass the raw data with the text column directly to the classifier."
+      "text/plain": [
+       "Output()"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "ktXNMVFCsEHZ"
-      },
-      "outputs": [],
-      "source": [
-        "if backend == \"client\":\n",
-        "    # Encode target labels to classes for baselines\n",
-        "    le = LabelEncoder()\n",
-        "    y_text = le.fit_transform(y_text)\n",
-        "\n",
-        "    # Define models\n",
-        "    models = [\n",
-        "        (\"TabPFN-Text\", TabPFNClassifier(random_state=42)),\n",
-        "        (\n",
-        "            \"TabPFN\",\n",
-        "            make_pipeline(\n",
-        "                column_transformer,  # string data needs to be encoded for model\n",
-        "                TabPFNClassifier(random_state=42),\n",
-        "            ),\n",
-        "        ),\n",
-        "        (\n",
-        "            \"RandomForest\",\n",
-        "            make_pipeline(\n",
-        "                column_transformer,  # string data needs to be encoded for model\n",
-        "                RandomForestClassifier(random_state=42),\n",
-        "            ),\n",
-        "        ),\n",
-        "        (\n",
-        "            \"XGBoost\",\n",
-        "            make_pipeline(\n",
-        "                column_transformer,  # string data needs to be encoded for model\n",
-        "                XGBClassifier(random_state=42),\n",
-        "            ),\n",
-        "        ),\n",
-        "        (\n",
-        "            \"CatBoost\",\n",
-        "            make_pipeline(\n",
-        "                column_transformer,  # string data needs to be encoded for model\n",
-        "                CatBoostClassifier(random_state=42, verbose=0),\n",
-        "            ),\n",
-        "        ),\n",
-        "    ]\n",
-        "\n",
-        "    # Calculate scores\n",
-        "    cv = StratifiedKFold(n_splits=3, random_state=42, shuffle=True)\n",
-        "    scoring = \"roc_auc_ovr\" if len(np.unique(y_text)) > 2 else \"roc_auc\"\n",
-        "    scores = {\n",
-        "        name: cross_val_score(\n",
-        "            model, X_text, y_text, cv=cv, scoring=scoring, n_jobs=1, verbose=1\n",
-        "        ).mean()\n",
-        "        for name, model in models\n",
-        "    }\n",
-        "\n",
-        "    # Plot results\n",
-        "    df = pd.DataFrame(list(scores.items()), columns=[\"Model\", \"ROC AUC\"])\n",
-        "    ax = df.plot(x=\"Model\", y=\"ROC AUC\", kind=\"bar\", figsize=(10, 6))\n",
-        "    ax.set_ylim(df[\"ROC AUC\"].min() * 0.995, min(1.0, df[\"ROC AUC\"].max() * 1.005))\n",
-        "    ax.set_title(\"Model Comparison - 5-fold Cross-validation\")"
-      ]
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "mTnMbG9vXHkL"
-      },
-      "source": [
-        "# Unsupervised Learning with TabPFN <a name=\"unsupervised-learning\"></a>\n",
-        "\n",
-        "TabPFN can also be used for unsupervised learning tasks like outlier detection and synthetic data generation. These features are available through the `tabpfn-extensions` library.\n"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Login successful!</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;32mLogin successful!\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "ghZddJXFa4zE"
-      },
-      "source": [
-        "### Data Generation"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">✅ TabPFN (client) initialized.</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;32m✅ TabPFN \u001b[0m\u001b[1;32m(\u001b[0m\u001b[1;32mclient\u001b[0m\u001b[1;32m)\u001b[0m\u001b[1;32m initialized.\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "console = Console()\n",
+    "\n",
+    "console.print(Panel.fit(\"[bold magenta]TabPFN Demo: Backend Selection[/bold magenta]\"))\n",
+    "console.print(\"\\nThis script can run TabPFN using one of two backends:\")\n",
+    "console.print(\"  [bold]local:[/bold] Uses a local GPU (NVIDIA). Requires CUDA.\")\n",
+    "console.print(\n",
+    "    \"  [bold]client:[/bold] Uses the TabPFN API. Requires an internet connection and a free account.\"\n",
+    ")\n",
+    "\n",
+    "backend = Prompt.ask(\n",
+    "    \"\\n[bold]Choose your backend[/bold] - If not field to enter is shown restart the cell.\",\n",
+    "    choices=[\"client\", \"local\"],\n",
+    "    default=\"client\",\n",
+    ")\n",
+    "\n",
+    "console.print(\n",
+    "    f\"\\n✅ You have selected the '[bold green]{backend}[/bold green]' backend.\"\n",
+    ")\n",
+    "\n",
+    "console.print(Rule(f\"[bold]Setting up [cyan]{backend}[/cyan] backend[/bold]\"))\n",
+    "\n",
+    "if backend == \"local\":\n",
+    "    !uv pip install huggingface_hub\n",
+    "\n",
+    "    console.print(\"Attempting local backend setup...\")\n",
+    "    import torch\n",
+    "\n",
+    "    if not torch.cuda.is_available():\n",
+    "        console.print(\n",
+    "            \"[bold red]Error:[/bold red] GPU device not found. For fast training, please enable GPU.\",\n",
+    "            style=\"red\",\n",
+    "        )\n",
+    "        console.print(\n",
+    "            \"In Colab: Go to [bold]Runtime -> Change runtime type -> Hardware accelerator -> GPU.[/bold]\",\n",
+    "            style=\"yellow\",\n",
+    "        )\n",
+    "        raise SystemError(\"GPU device not found.\")\n",
+    "    console.print(\n",
+    "        \"[bold green]✅ GPU is available.[/bold green] Importing local TabPFN library...\"\n",
+    "    )\n",
+    "\n",
+    "    from tabpfn import TabPFNClassifier, TabPFNRegressor\n",
+    "\n",
+    "    console.print(\"[bold green]✅ TabPFN (local) imported successfully.[/bold green]\")\n",
+    "elif backend == \"client\":\n",
+    "    console.print(\"Attempting client backend setup...\")\n",
+    "    console.print(\"Importing TabPFN client library...\")\n",
+    "    from tabpfn_client import TabPFNClassifier, TabPFNRegressor, init\n",
+    "\n",
+    "    init()\n",
+    "    console.print(\"[bold green]✅ TabPFN (client) initialized.[/bold green]\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "c8iQ9KEd1h9R"
+   },
+   "source": [
+    "# Classification with TabPFN <a name=\"classification\"></a>\n",
+    "\n",
+    "Now, let's dive into a practical example of using TabPFN for a classification task. We will use the well-known Parkinson's Disease dataset. The goal is to predict the presence of Parkinson's disease based on various voice measurements.\n",
+    "\n",
+    "We will compare TabPFN's performance against other popular machine learning models: RandomForest, XGBoost, and CatBoost. The performance metric we will use is the [ROC AUC](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html) score.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "PNtRCHyLG1D5"
+   },
+   "source": [
+    "### **Loading Parkinson’s Disease Dataset**\n",
+    "\n",
+    "**Source:**  \n",
+    "The dataset was created by _Max Little_ of the **University of Oxford**, in collaboration with the **National Centre for Voice and Speech**, Denver, Colorado. The dataset consists of biomedical voice measurements collected from individuals, and the original study published the feature extraction methods for general voice disorders.\n",
+    "\n",
+    "### **Dataset Overview**\n",
+    "\n",
+    "-   **Number of subjects:** 31\n",
+    "    \n",
+    "-   **Number of Parkinson’s disease (PD) patients:** 23\n",
+    "    \n",
+    "-   **Total recordings:** 195 voice samples\n",
+    "    \n",
+    "-   **Goal:** To discriminate healthy individuals (status = 0) from those with Parkinson’s disease (status = 1).\n",
+    "    \n",
+    "-   **Identifier column:** `name` (subject name and recording number)\n",
+    "    \n",
+    "\n",
+    "<details>\n",
+    "If you use this dataset, please cite:\n",
+    "\n",
+    "> Max A. Little, Patrick E. McSharry, Eric J. Hunter, Lorraine O. Ramig (2008).  \n",
+    "> _Suitability of dysphonia measurements for telemonitoring of Parkinson's disease._  \n",
+    "> IEEE Transactions on Biomedical Engineering.\n",
+    "\n",
+    "* * *\n",
+    "\n",
+    "\n",
+    "\n",
+    "* * *\n",
+    "\n",
+    "### **Attribute Information**\n",
+    "\n",
+    "Each row corresponds to a voice recording, and each column represents a distinct biomedical voice measure.\n",
+    "\n",
+    "**Feature Name**\n",
+    "\n",
+    "**Description**\n",
+    "\n",
+    "`name`\n",
+    "\n",
+    "ASCII subject name and recording number\n",
+    "\n",
+    "`MDVP:Fo(Hz)`\n",
+    "\n",
+    "Average vocal fundamental frequency\n",
+    "\n",
+    "`MDVP:Fhi(Hz)`\n",
+    "\n",
+    "Maximum vocal fundamental frequency\n",
+    "\n",
+    "`MDVP:Flo(Hz)`\n",
+    "\n",
+    "Minimum vocal fundamental frequency\n",
+    "\n",
+    "`MDVP:Jitter(%)`, `MDVP:Jitter(Abs)`, `MDVP:RAP`, `MDVP:PPQ`, `Jitter:DDP`\n",
+    "\n",
+    "Measures of variation in fundamental frequency\n",
+    "\n",
+    "`MDVP:Shimmer`, `MDVP:Shimmer(dB)`, `Shimmer:APQ3`, `Shimmer:APQ5`, `MDVP:APQ`, `Shimmer:DDA`\n",
+    "\n",
+    "Measures of variation in amplitude\n",
+    "\n",
+    "`NHR`, `HNR`\n",
+    "\n",
+    "Ratios of noise to tonal components in the voice\n",
+    "\n",
+    "`status`\n",
+    "\n",
+    "Health status of the subject (`0` = healthy, `1` = Parkinson’s disease)\n",
+    "\n",
+    "`RPDE`, `D2`\n",
+    "\n",
+    "Nonlinear dynamical complexity measures\n",
+    "\n",
+    "`DFA`\n",
+    "\n",
+    "Signal fractal scaling exponent\n",
+    "\n",
+    "`spread1`, `spread2`, `PPE`\n",
+    "\n",
+    "Nonlinear measures of fundamental frequency variation\n",
+    "</details>\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 423
     },
+    "id": "tTQe5IprKLV5",
+    "outputId": "2289a6e5-6cac-4c72-8203-f638f2acb520"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 13,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 0
-        },
-        "id": "npJnFdtTa_nS",
-        "outputId": "c2fbe9fd-e7c6-4e14-c2b2-198e2fea703e"
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "type": "dataframe",
+       "variable_name": "X"
       },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "100%|██████████| 3/3 [00:05<00:00,  1.85s/it]\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 935.75x750 with 12 Axes>"
-            ],
-            "image/png": 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fW7sXV3QeldbDyzb02Ils6T3hvro72znQFYZ/y+GhU+v21hMZaZ/oZgtxTvnFB/vZ29LHD1YWEBM+9VMIhLhQuFw+/s8rpSSGW/jWVdOmujlCCCEm0LgDT6fTyUMPPcQf//hHAPbv309GRgYPPfQQiYmJfPvb3x7X/m699VY6Ojp4/PHHaW1tZdasWaxatWok4VB9ff1IrypAc3MzRUVFI/efeuopnnrqKZYtW8bHH3883pdz3ikvL6fUHYPffLjQdou2g5iQCDKyc0aWldW1AyfPPmiPSyGjYO7I/T1bN4DfOaFtFuJcU97az876XtoGhqcm8Az4z+nhtsfwe8E1ACEnHkUhxMn0ubw0tbZh9IdOdVOEEEJMsHEHno899hilpaV8/PHHXHHFFSPLV6xYwfe///1xB54ADz744HGH1h4dTKalpREMjm+o54UWkEbHJYwKMm1bd01ha4T47Pn362bQ3udiWqL97D95Vw3sfRnyV0J0zsnXnwwtu9Scu7hTnLdfswYat0LxPWCLmdy2ifOPqx+at0NCEbGhVp7N3oTV1Q6NFkiae/LthRBCfCaMO/B89dVXef7555k/fz6aI5IBTJ8+nerq6gltnBBCTAWHzYzDNkVDbPUmsDrUv1PlwDrQaE898IxIB78bTGGT2y5xfuquhbqNYAqHhFlEZs6D9n1gsE51y4QQQkygcQeeHR0dxMQce0V7aGhoVCAqLhxjJSEqLS3F7w+fwlYJ8RkVnghzvzS1bZhx06gsoyflyFQ3IU5H7HQw2iAiVX3v8q9WNyGEEOeVcQeec+fO5a233uKhhx4CGAk2f/vb37JgwYKJbZ34TBgrCVHpuq3EZReSPYXtEkKcplAZLntWVX8Egx1QcONna27vRNHpz96Fi8Yt0F4BM64HY8jZeU4hhBDAaQSe//Ef/8GVV15JWVkZPp+Pn//855SVlbFhwwbWrFkzGW0UnwFHJyFqrimfwtYIIc5VwWBQRscczT0I7n4YZ/6CC9UZfYc8w+DqUQm8hBBCnFXak68y2uLFi9m5cyc+n4+CggLee+89YmJi2LhxI3PmzJmMNgohhDgPvLOnmb9/Wk9AagGPNu1zUPxl1fMnTmhnQw+/WVtN16D79HaQsRTmPwBmmY8shBBn22n9lcvMzOTZZ5+d6LYIIYSYSMEgdJRDaBxYIk5tm/YKGGiB9CUTPuzTatDjMUvQOaYjevCae52EmAyEWwxT2KApFAzC/lWg0UPWJXBESTWjTkuo2YBeewa95tpTu+bePejGHwwSHSq1fIUQYiKcVuAZCASoqqqivb2dQCAw6rGlS5dOSMOEEEKcmd+89QmFba8zf/ElkHvlqW3UsQ8690Pi7AnvFVqWK3NHT2bA5eWFrY2kO0JYOStxqpszNfoaYOffVHbntIUjczEPdA7yv2uruSQ/hnCrcdKb8faeFgZdPv5lWaYMDxdCiAkw7sBz06ZNfOELX6Curu6YepoajQa/X+ZNCCHEVPP7/XzYqMUVMpf5ieOohZh9KaQulKGIU8Rm0rMoy4HDNvmB1TkrLBHm/QuExI5KANTY42RHfS/J9hCYOfnNmJsWiccXkKBTCCEmyLgDz/vvv38ks218fLz8IAshzl99jaqeZVjCVLdk3HQ6HT+9dQ563RywWU59Q2OIZPucQhqNhrlpkVPdjKnT3wzBAKQtPuahxdkx/P5LxSTbz059z7w4ufgihBATadyBZ2VlJS+++CJZWVmT0R5xlvj9Pura+/hkVy0ATZ39+BNHD5sOBIIMDfRTX183sqx/YAC7Zdw5qYT4bNrzMujNMO++qW7JaUmIGEfAechQF3RWqqG2Wv0pz4cT4owFAlD2Ovi9sOihMVfJjAk9dqHPA03bwZENIVGT3EghhBCna9yB57x586iqqpLA8zNuoLuTLd44rE3qyvquARsxTs+odQZdHgKBFmjZNbLM2dWMNUbmaYkLRPalKsHJhaR1N9RvBKMVaj5WAegYvU9CTKjaT6B5B6QuBtM4ezT7mqDmI/C5IHP5pDRPCCHEmRv3GdVDDz3EN7/5TVpbWykoKMBgGJ11r7CwcMIaJyZXeFQMGdk5ANi27hpzHZvZQErs4WyYVvPpZVn0eT2UlpYes7y4uBizWTIGinNQcyk0bIIZN41/2546sMWA4TR6HKdacrHKghsWD+YI0E/isEZXP/TWgT0V2sshboYKeMWFR28FnxcOrIVp157aNt21Kth05ML068GePPZ6fh+0l0FkOpjG6DEVQghxVow78LzxxhsBuOeee0aWaTSakYLOklxIjKW9oYbynm4qPIfnLjXVlPMNYMmSJVPXMCFOJBg4+TpHKG/p47W1W7iRD8mafZHqMT2R9n3QsBnyV4L1FMudTDZjCMTkqf/P+eLkPlfTdtW7GlcIrbtAb4SEWRP/PANt0LYXUuZLYHsuaiuD+g0qm61ZBYY/e6+CQY+P714zXa3TuE19P+IKDm9XswacHbAo+/B3dizdtVD+lsqQm75sEl+IEEKIExl34FlbWzsZ7RCfYWPNBe3u7ibyqKyY0UkZZBSMI7umEFMpYaa6jUND9zCr6wPMzC0kK3bayTfwOMHZBX7Pydc9HyXMVNlzHbkQkaL+nQxdldDwKUSkQVTGhO76r5sO0Nrn5uuXZKPXy3zY0+J1qnmdmcvVUFubg7LWLfQ5vfj9fnRaLdStA1P46MAz5zI1v1N3klOZyDTIvgwcx04RGnT5+MXq/eTFh3HD7KQJfVlCCCFGG3fgmZqaOhntEJ9hY80F7W+tQRtyjvTgCHGWXDo9jnSHlXRHCOh0J98gaY7q4dOewrqnaeuBLlIiQ4gJOweHtFsiIPHg78SRAcVESyqB8GSwp0z4rpt6hqnrcuIJBNAjgedpSZoLCUWg1VHfOUh/Xy8/vqEQnz+A7tBxNPMLKtnVkU4127TOoI61MQx7fNR2DmG3nt40EiGEEKfutLJmVFZW8tFHH9He3k4gMHoo2uOPPz4hDROfLUfPBQ2zmqawNUJMnazYcZZgmMSgs6Z9kJ+8u5+S9Ei+ednJexN31XdT3zPMNTMTJ61NU0JvhIjJuWj6yKW5eHwBrMYLLAnVRDt4HPxu/QG21/XwrcuzWZwbd/hxW/SkPG10mJmf3joLi37yjkMhhBDKuP9SPvvss3z1q1/F4XAQFxc3qo6nRqORwFMIcWHxe2Hn31Tvy8nmdB4pGIRJroOcFGnl2lkJ5MWdWkKV/11bQ2ljH9MTwkmPtk1q284XRr0WowyxnRgtpXxJ9y7DYbP47boDowPPSRR6mknzhBBCjM+4A88f/vCH/OhHP+Jb3/rWZLRHCCE+gzQHb6fI2QM7/wJJxSrhzSQx6rV8Yd6p9/TdOCeR2akRxwadPjfop3gUg7Pn3EnAJCZNepiee9wb6Ys+yXHh86iebK8Lgn6VFEsIIcQ5bdyBZ09PDzfffPNktEUIIT57dAaYc+f4ttFqwRgKuiOCue5aaNoGWZeouY8HeTx+dDoOz3Ub7oF9b6r/Zyyb0HmLF+fHH7uwuRQq36U59VpqvZEsyp6cIY8n1L4P9r4K+Z9TJVfEeckTNQNjeAp5u18AXwXbd0QTk5pHUuRRmYgHWmH7X1TJIveAuuZTcAtUvgspCyc8gZQQQoiJMe7xQTfffDPvvffeZLRFCCEuDOZwmPsllVioYYsKOoc6oLNK1bY8yOPxc8+ftvB/Xjqizq7PDX3NqsZox/7Jb6spFELjeX1vN7/4sIrmbufJt/G6IDCBpbUsURCdA1bHsY8N98KGX0L9pol7PnHWff/13dz22020t7eBPY2O7h4+3LabF7c1HF7J51FD23UmVb9z7yvg7oPoXHW/vxlcfVP3IoQQQpzQKfV4/uIXvxj5f1ZWFt/97nfZtGkTBQUFGAyj50Y8/PDDE9tCcVwul4stW7aMWlZVVUUgGJyiFh12dImVscqrCHHBcw/i2/8+lf44zEU3k74gT5UXOUing+hQE3aL8fA2oXGw5BFVhsUSeew+J1pUBkRlsLCxl4TEIeLsJ8mO63HC5t+o0hV510xMG0JjYMaNYz+m0YAhBLTGsR8XnwmRVhPx4WZCOnbAYB0Ri+8jq9pLfmK4WiEYhO1/YDBo4ZOQFSxJXIQtLB6mXQ8hB4+DRV+f+iHhQgghjuuUAs+f/exno+7bbDbWrFnDmjVrRi3XaDQSeJ5FW7ZsofSFnzAz83AChqYdG3EnlUxhq5SjS6xIeRXxWRAIBFld3obDZqIo5Sx8X82h9OXdzIayQXJ6XKRHHzGM1dmDruoDfnbpXIhMH72d3nTqpSR2v6D+LTizKRKFSXYKk+wnX1FngIh0sB2RGKZ9HzTvhLyrVG/vRDKHQ/HdE7tPcdY9nNcHIVsg8yoa+2ezoz7IJTPiDyf+0WhAo8fTUU1d/ywyC+eSk3fR6J0cCjpbStUogtwrJRAVQohzyCkFnrW1tZPdDnGaZmbGsaTw8EnpS2v3UD2F7TnSkSVWpLyK+CzwBgLUdAzh8gaOCTzruoYIBiHNcepJTFweHy9u2s/CwDYyps9Tw0WPEpWYzQ12D6Hmo36O3X3QVa2CuKMDz/HQGhhX4qMzpTOo11nzMYQlQli8Gg7b3wxeN5yD5UQnjasfDFbQSamVk6lsH0JXW41BW0q5rYSazgGW6naBuw1mfl4lEorKJGK4h5unOYhyHJGp2eMEjRYMB79c/a3QVaOG30rgKYQQ54xxz/H893//d5zOY+f4DA8P8+///u8T0ighhJgKJr2OOxekccWMg711HieUvw09B/iovJ33ylrHtb/2fhc7qhtoq9mtEqIcR0SIEb3uqJ/jiDRY8IAqfH8mc9emXwfTrz35esEgVLwDB9af3vOMtb9DUubDwgfVkNnJNNSlStt01Yxa3NjtZEdd9+Q+99GG+2Dzs1D1/tl93s+iwQ6aGw5Q2a+nrLKKfpePezP7CO/cRY/Tze7GHrVeXAEaazRRw42Htw0GYdsfYfeLh5dlr4D5/zLxvetCCCHOyLgDzyeeeILBwcFjljudTp544okJaZQQQkwVi1GH4VAQONyjhu311HFJfgyXTz+2rmBV+yA9Q54x95XisHHvlQuYdsNjkLb4hM+7vbqVTbvLCR4ZsJlDwTMIO/4MlWMEMD6PGsLqOYWEPycTDKjhiX2No5f7veqkfjzJe2LyYcHXVG8nqGGSZ6PnyTMIfQ3HBOl/2FjLf75bQVvf8OS34RCDRfX8hiefvef8rOpvJo8DhGbMI3HJF1icHY3V3QF6A6/3ZfPqR+voGnRB9Ud4dr1Ed1PV4W01GpVc6MhRAVodNG5TmZADgbP+coQQQoxt3ON/gsEgmjGKnpeWlhIZeRYSXQghxNkSngjFXwFLBMk6PX6/n/a+YWLCLQB0Dbl5o7SZvPhQrpwxRikSIC/uFJJq9TZg2f8mdNQTyPgWuhD74ceMNkhbAiGxx27XWaF6KX0eSDnDud1aHcy9R/17pIAP+lvUkNFzXUQqLHxYBX1HuDQ/ltzYMKJDz+KwS71RlX8RJxdfyFBiK7rS90hIjSPS2QlpyyB9OcvW/YMBfQURukshaQ67OzR8OpDPXW4fIaaDpzBZFx+7T2cnDLarCyrjv8YuhBBiEpzyr3FERASRkZFoNBpycnKIjIwcuYWHh3PppZdyyy23nFYjfvWrX5GWlobZbGbevHls3rz5uOvu3buXG2+8kbS0NDQaDU8//fQx6zz55JMUFxcTGhpKTEwM1113HRUVFafVNiHEBc4WPTJH7z9XVXD7bz9ld2MvAJFWIxfnxTA7+QwTEZW/SY6hnRkll6Az20Y/ptFA6kJwZKr7g22qpAqAIwdyLoe46eq+swcGO06/HQYz+D1Qt4mu7i62HOjGqzXB/Psh54rT3+/ZdFTQCTAvw8HNc5PRaiUAOSdpNKTlF1M47yIiDX5Vp7a9DDor2RXM5Pc9haytG4aINOKKrmDZtAQVdA52qHJER5TuOdA5SFlzH0y7Tl00kvm1QghxzjjlX+Snn36aYDDIPffcwxNPPEF4+OG5E0ajkbS0NBYsWDDuBjz//PM8+uijPPPMM8ybN4+nn36ayy+/nIqKCmJijp0P5HQ6ycjI4Oabb+Yb3/jGmPtcs2YNDzzwAMXFxfh8Pr7zne9w2WWXUVZWRkjIqScGEUKII6VEhpAbF0qEVWXa1Gg0zEy2n9rG7kFo2gZxhWA9KlDNugxdMIAuOvvE+xjsgM2/hfiZEFeghr9mrQDjwd+1fa+r4HPRw3C6QVZnJdR8RHPIMM0dg+TUNRBecjtYJmi+3GCbqst5KCBo3QPWqMPDck9kuE8FlnopnXK+0Q60YAmLhvhCtaBuE+x7lSWmRLY77ibBMADEkhhhJfHQ4dO0DZp3qAzP4YkAbK9pRd+xj+yLl2OwhI75XCc01Km+j2OM7BJCCHFmTjnwvOuuuwBIT09n4cKFx9TvPF0//elPuffee7n7bpUO/5lnnuGtt97iueee49vf/vYx6xcXF1NcXAww5uMAq1atGnX/D3/4AzExMWzbto2lS5dOSLuFEBeeOxakcseC1NPbuK8e6jaA3nLssNhDvZknYw6H4W41vNYaqeZkugcgJEo9njgHfMOnH3QCxEwDnYGM0HSiarYRNtgITFBt4J4DsPPvkL5EzXkd7oV9b4AjGwpuOvG27gHY8ls1b1KGsJ5/dv5NZXFe9h3o3A9DHRA7gwhLBN9PdkH9C+C4cyTABCB1gUrCdURpoYsdPWg7d2DojIPk4vG1oaMC9rysevcTiybmdQkhhBgx7jEoy5Ytw+/389JLL7Fv3z4Apk+fzsqVK9HpdCfZejSPx8O2bdt47LHHRpZptVpWrFjBxo0bx9u04+rrU4kmjjcH1e1243a7R+739/dP2HMLIc7MeXN8OvKgwAQRKae/D70RHLmqV9KRC3GFPLelnXBLIzfOSYK4Gae/b1c/+H0QEgmx0wkBQmYsAZac/j6P0N7vwmawY40vBPvB4N1iV1l3LVEn34HeArHTITzpxOt11UB3DaQvlZ7Rs2DCjs+8q9SFFL8Lhrtg7p0Qmal6HnsOAEGwRNA3MEhwqBN7XBqYw3m1fICO8hq+vDgdrVaLPWk69OwD/WnU7QmJURdeQo9NIiaEEOLMjfuyeFVVFfn5+dx55528/PLLvPzyy9xxxx1Mnz6d6urxVZDs7OzE7/cTGzs6aUZsbCytreMrW3A8gUCARx55hEWLFjFjxtgnZU8++STh4eEjt+RkyUIoxLnirB2f/c0qic5R3ixt5GfvV+Dx+MfYaBy0WtWzqTvD0SIl98LlP4SQKDw6K5trutl5cM7pmHweld2zaceJ97vvddj+R5XFdoJ1Dbr41ku7+J/1bZB3NdiP+Axj8k+tzIpOD7lXnDy47qyExi2nX37mXNF9QGVVPsed6fH5wpZ6/uejSkhbBLPvgNQSlSAqKksFna4+dUEkPAn2r+Kjd19i/T9/SqC7DoBd9X1sPtCNy3cwe23AB4Ot0H0aFa2tEar00KkM+/Z5oL1ctU0IIcQpGXfg+fDDD5OZmUlDQwPbt29n+/bt1NfXk56ezsMPPzwZbTwjDzzwAHv27OEf//jHcdd57LHH6OvrG7k1NDScxRYKIU5kwo9Pz5AqQeI7qgTK7hfVsM+jvLu3jVd2NNHUd7BkyUDbsSeb3mGV8Gf/+2rfJzHo8vG/a6rZXNOpAt69r6m5mafiiNIkRr2WHy028K/FxybUGeH3QE8tDB4bVI8SVwjJJacdGHcPeqhs68XjC+D1jy5hEWLUMzvZTm6s7ThbT6CMZSo7ry168p9rsjh7oPTvUPPxVLfkpM70+Ny+r5r6si0MHthO8KP/xF3+rkpydUjtOtj9AnTX0lm/jw6NA3PqHLRD7TDUxcMrsvnBtTOwGg8O4DKHwZy7IfuyY55rb2MPHs/YpY/GrXUX7H1FJUESQghxSsY91HbNmjVs2rRp1LDVqKgofvzjH7No0aJx7cvhcKDT6Whraxu1vK2tjbi4Mx/q8uCDD/Lmm2+ydu1akpKOPzzLZDJhMp3FNPtCiFM24cdn6x6o/lAFWLHTDy/PWgGaY6cLfP2SbJr7XKRHhx4xR3GxKnEC0LgVPv1fNbRzsEOV9EiYdcImNPc6+ai8nUAgSImpX528xkw7NunQyfg8RNWvUnPcEo4zT9Rkg3n3g26MYafDPWqIbUTq4aQup8o7rObkReeCzsDD/9hGecsAX5yfSnyEhVvmHh5SbDbqeWhFzvj2f7oM5tGBy4kMdam5sudaIhmLXX0fPwNDPs/0+Px2xGo0unpsO9bjaS6lpbmFkMRlRIce/AwTZ0NINMQV0Nw6yN4WKwvn5ELVB5AwC3vulcfudIyLDi9uqed7r5exLDea/7ljzmm3d4QjB3wuiMw4830JIcQFYtyBp8lkYmBg4Jjlg4ODGI3jm09jNBqZM2cOq1ev5rrrrgPU0NjVq1fz4IMPjrdpI4LBIA899BCvvPIKH3/8Menp6SffSEyqQCDI0EA/9fV1I8va2lpxu09hiJ0QEyl2ugo6o7IOLwsG1ZDPMQKQrNgwsmIP1uK0OlRQGXHkb0oQTGFgcah5l0cGs8eRExfG96+dTqLdAiY9QXsKAUsU45slj5rDOOMmMJ6gxxPGLDGCexC2/F6dPC944HDW2q4acHZB0twTB2Qtu1QAr9FA7HQSwi14vEFSI61EhZ7G/LqzraMS9ryoesaSjg1EOvpdVLQPMDc1ErNh3J/MmdFoxp8Y5zMqPDYdIhwQEo/Tnku/NhmH8fCpiS8kFn1YPFR9yIy6v/G9hAVE9GghYTYkz1Mr9TXD/rcg93Ps6jdj0GrJTxhdPzfBbiIrNoSkiAn6bprDVIIsIYQQp2zcgec111zDfffdx+9+9ztKSlRmxk8//ZT777+flStXjrsBjz76KHfddRdz586lpKSEp59+mqGhoZEst3feeSeJiYk8+eSTgEpIVFZWNvL/pqYmdu7cic1mIytLnUg+8MAD/O1vf+O1114jNDR0ZL5oeHg4FstJTtDEpBh0eQgEWtTJ6kFdB/ZSXm5kxYoVU9gycb6r6xwk0W5Grz/4c2eyqV6UI23/swreCm4evTwQGJ0h1mSDo3tYkopVb2XDZqherUoxmDIPb9+8A8ISIWx071Ve3OET41U1HtoH6rh9Xgp63fFnQDT3Ohlw+cmNO6JMxJEZcVv3qOA47OQ9Zf1NZYQNtUF8kTqJPqRpqxqaG5OvXu/xxE4DNCoBDPBfN8866XOOxeX1Y9Bp0WlPo9exdh14nZBz7LDKkwpxqM/tOPP5KjsG2VLbQ5LdSppDynBNmpIvM+jy0T/QT4JhLfb2Mtp7S2gKhhJnM7Dukw9JS0pketdmtAkz0SbMxKvxYUgqOTxCoG497HkFLFFs6pqJ1aQ7JvBcmB3La9mxYzTgLOttgPqNkHEx2BxT3RohhDirxh14/uIXv+Cuu+5iwYIFIyVVfD4fK1eu5Oc///m4G3DrrbfS0dHB448/TmtrK7NmzWLVqlUjCYfq6+tHFf1ubm6mqOhwmvOnnnqKp556imXLlvHxxx8D8Otf/xqA5cuXj3qu3//+93zpS18adxvFxLCZDaTEHh5K2HRALgKIybW2vI1vvriLy6bF8qMbTjCU1BymsqYG/KqMQ2gcDLSqYbUZy1UvZ0eFGtJqDlMBJaig1NkDW59TJUGyVqiste1lai5oTD5UvqdqboZdc9ynD7MY8AWCaE8y5HNDdReN3cOkRlmP7YUb7qV/x8t82GlHW3gjieEWGnqGWDkzcdRvKMCOum7++yMPX8q7iqUFC2nqGybKasRs1EPWpeAZPHHQCWAKPbYszDi5vH7+uOEAaY4QLp9+/GDZ5/PxX+/uZ3pCKNcWHZG8pq9BJZ8JBsc/XPZQIpnjmJMaQZLdQnKkdXz7FePTVMq2j9+htmOQW1MHsEQm8Wmjh+ruVu7MDxLf9jH7e7IIWI3Y3V7e37+N7VHXcJnPycqig1N+8q4BcwSkLeIGt5ZTvYYRCAR4eXsTOXGhFCbZJ+0ljuLsVkPUE+ZI4CmEuOCMO/C02+289tprVFZWsm/fPjQaDfn5+SO9jafjwQcfPO7Q2kPB5CFpaWkEgyeuKXeyx4UQF4aYcBN5caEU2t1q/uWRc78CATjwCdhiVC9mcynUfqJ6IwpuAUuEuhnM0NeoEokkzlG9a3teBI8T5n5JPR6ZoW6HMq62V0BXleoNnXHjSRPdLMo66vHmnapmZ+ToaQJLsqPxdVRh3v4cgdwr2dJtIS7cTGpUCFjsDGddw87uPqZ7/byzt4U9jf0syHAQG374Ik9pYy8bqrtIcdgxxsVS2+Xiu6/tZXG2g/uXZ+EzhlPZpyU3LHBMwDqKswf2vqxe46H5oXtfVUHrrNtPKRDUazUkR1qICT3xHMGd9b38fXM9c9MiRgeeM26EYGBS5mia9DpSoqSnc9Lt/Cuz6l4jOv0W9CGRsP89Ls63MytzMWWlW/hoMAtnRD5mmwtz8kyagxo2V3Uz7A2wINOBtmEzUf27YdYdYLTgON6Mn7YyVUd32nUjAV9dp5MXtjUyNzXi7AWeCTMhKvPkF3aEEOI8NO7A85Ds7OyRYFNzriVmEEIIIC/ezp+/Mh/W/zfs3QHz7mNzTSevl7bwpbnRZDVsPpwcpHq1yuwaP1MFiuYwFViCSsBjtoPtYK+c2Q4GC92DHv77wxpmpRRzbdwRCcxyLgfvUnVyGX1UUh1XH3jdxy8h4nFCxSpVcsTVBzH5NPb72VDdybLcGBLDDNDiZMjlYWO1k5y4UBV4ArHZs3k8sQets5v6tFRap7lGBZ0AG6o6WVvZyf+7Op+CJDt9Tg+zU+wjQ3/f2tPC3z6t5ytL0rl02vF7Ifudwwx1dhEf41IlWHQGNec0YDrlQFCv03JVQcJJ15ub4eDbV+aRHzd6+KTU6TwPzLwNl9OPu6+HVnsmUdY43I3b6GrtRd/XiocZ5MTbWe59g+6BBP7fLXeS/2klafEx/Hx1JfGDTfxLrhn9odIrQ10QNUbCH78XvEMQPFwWKT3GxiMrskmOOMu92hJ0CiEuUKcVeP7pT3/iJz/5CZWVlQDk5OTwb//2b3zxi1+c0MYJIcSEyFgKWvVzZ2zZSlZXBb3e21TZBaMFdCbI/5wKQo3qJLRr0M1/vbuP/LhQMo19LBjqRu8+WBvy4JxCV5+Thh4niUcnLDFaR/ZzjI3/o3o0r/xPiEw79nGjFWbdRnd9GZbdb2Ap1DKkSae138Wwx6+yyEbnEgrcpmnGFho+anNt/QZo2UVK8ZdJcRwb3H6+JIWStEgKDvbwhFuNPHp53sjj0+JCWZgZNXoeqcepgslDSYr2vkrZvlqeG1jCD3Tr8R7Yizf/JtJzr1KPH1gP9ZtU8D79BgiJGvu9GIfb56ed8T7GEggEaOx2kuKQYOCsq3iHHq+e5y23snzo7+gr3sQ57Up0le9iMwwSnP1VnFVGwsPsfNJViL96O2bNs9zo74KWSPxRaeyPm4d+Wqj6ru17S5U5Kf6yGslwhMHIfNZ2RrPcFMWRR+aCTBnuKoQQZ8u4A8+f/vSnfPe73+XBBx8cKZ+ybt067r//fjo7O/nGN74x4Y0UQogzEj9z5L+zIjzk54ApxT5SDxM4PEz2oLa+YXbU9VLb7qRn2MN3L76OpdEx8OlvVDbNhJkkhFv5xeeLMOvHURI5bqYq22I8/jBOT2gKL3YOkG/UssSRQ27AS2bsPvRaA3Bw+O1wH3Hlf1XzSPOPmD+aUASWKJXkaAx2q5E5aWpuXMeAi1d3NrMgI4oZiSqAzY4L4+tH9yyW/h3QQPE96r7BQlKsg4Wx0VhCs3hhRxdt3Qf4wfUFarhy0zbVwzTUqeqInsPeKG3mb5sbePDiLJZkf4Zrf37WBIPQ28DuejemfgPxaalETJvOYFgWbT29BA0W3q7T0NzRwzT/C8SbhunTDGCzZYE2FNyDlKRH4avZT8Wba8ld8WVILFLf+zG++//zcTV/3ljHA8uzuP+i058aJIQQ4vSNO/D87//+b379619z5513jixbuXIl06dP5/vf/74EnkKIc1ve1ZgCvtFB5ximxYXwy1sLaOjzsK91gGlZKaBxQtCn5hUeZDWO/hl9bUcDr5e28vWLMylMiTx6t5B/lbqdgFGvZX5uMjZT+sE5pp3oO8rAFnl43qfRqoYGRySP3jgsAULjjxnueqC+nrbmOuaZGsA3BHkr0WrsmPVa9EdlY9lcVo2l/EXy7EEMc78EUdnQtlf1YqbMh5zLScqBLwGQRQpNFIUcHPY63AN6syrRggZ0o9+fXqeHv26qZ0FmJLNTx3h/JlLTDmjeQV/WtbxX7aQwyT66JxfIiLExO8VOcsQZJjvzecA3rObmipPTaGDOl4hM7Kdo73tEhJroy72ZH72+E7v5Sr4eU84Nfdu5PC+GrPY69PpowmddAlodFN7MXzY3YO82Eq/twhISBiarGmabOFutc0jHfqhZw4rEhdRmO5iXcTAo7W1Q2XATi0dnhj7P7WrspbJtgCsL4o/57RJCiMk27l+dlpYWFi5ceMzyhQsX0tLSMiGNEkKIybKjsY9ep4eL8saev1jfPcS6yg6u87+Pps9DW8RVPHjxoXmaZkicC537VTmRQ8Fr215VyiTvKtoHPNR1DdHr8p1ag/pbYN/rkLEMog8PeR2V7CQ8CUr+BSzhPPVeOeXNAzx5wwyicy8/dn8BP2z/kyoXkv+5kcXr338Zd9MuMmalEh3sgqhsouJn8cW4RujdA9GXjcyZ7KwrI6d1G25dMgYCkLZIDWHsPqACT8Dl8dE96CEh0srKWYmHnz/vGhWY68b+81LXNcTayg7MBu3kB54BL3iH8fm8tA+4GXR7j1mlINFOQaL9zJ9r/yrorIR5/yJz+E6V3siMJAc1xmv4ze42rqr4hHt7fofPnoa7ppMhl5XdviHsM2/F0ltNYlc1BHy4PNfx0b4OEiIs/CC9H3xBlRyseQfkXX042dVwL1S9D64BZueF8+uCI2rsOruheg20l6vP7Dhldc43Ay4fHQNuvL4gyBRpIcRZNu7AMysri3/+85985zvfGbX8+eefJzs7e8IaJoQQk+G/P6yioXuY2amRhFuOPfNaV9nB6ztbmJ0fyXsNHezY/QnzvFvQeQZIK1wCrl4YaFYZcVMXqXmP+95UwWjmJdy7NJNbipOP3XcwCI1b1TDAI5Kf/OeqfaQ1V3NZ9DwiolHZdn3Dxw7FDVFBms/rYbp3F5qBCAgba8igRm2rH92DF5m7mJbQVCwXXwHuVnWivfdlqN8MobGQtkQFnr0NLE814fLmYFt4t+pBBZh7z6iepKff2kpPRzP3fO4ScuOP6OXTaoHjDz2emRzBE9dOJ+VslClJLoHkEqKA+5YGMJygRuoZi0gDnVH19opx+fDjD7DXr8GXFk6KxUVQ14XT7WTQnEkvGbywd4j0oJtYm5XKQQPLZ7r50XKryoIbehls+jX01EPmxaqs0SHuAXANQOZydfHmSAkzYeFD0F09uo7teW5hZhQl6ZGTeywIIcRxjDvwfOKJJ7j11ltZu3btyBzP9evXs3r1av75z39OeAOFEGIiXTsznuGhQcJ3/k4FkQU3g+NwAHd1QQIJdisZmfMwBKq4ueUDKnduZdgHcck5mLMvVSe5u16AsCSIyYOobHxReQTMkRhhzIAW7zDUfAj21FGBZ4/ewa6Q67kk5mBvZ916qF2HK6EYc87FBwM5wOuCPS/x7ZwYsLbDYCUwRuCp1ULhLer/HqcqceLs4Mo5d8HiuWq57eBw3YQiiEiFmBlgORg87vwb1uFerIvug6gjyrkclSwpe3Ar3t69RGrnAeMbXpp39BzSEwn4VQ3VrioIT1bz+A45VDrrFLLoTvqJdnzh4Z42cer2vsotrpfoi7ET1bcDTV89jdGLGe7cRollHXO8H1Ka/hUaHF9kXfsgewZ6udw3RNyB11WQGX0jOHJVD3/KvNH71mjUsXBUWaIRcdPU7VwTDKrbicoZnSaNRoNBJ5UIhBBTY9yB54033sinn37Kz372M1599VUA8vPz2bx5M0VFRSfeWAghzpbyt8DrVIHlEa4tSgb3IGzzQX+TCj4PKXudcL+b5Qe3+eryHPAk8dFbf8fRvhVzRLQ6mdXowJGjbgD51/DPrU3odjRya3HK2O0xWlV9S8Ponswf33BUsBISTZ/TSd/a32H0GogrWKaWB/2qraHxMOvzEHL8RDgVLX28VtrMF+OaiG/eDuYI1e6O/VD9IUxbqfYTk3/sxvFFKvgd6hgdeB7lqitXEuibQ0jMycuhHK26fYCXtjdy7cyE0b2lY+mshN0vgs8FycHRgeeOv6pe2kOB9tkQ8INn6PR6yXwedQHCIvNAR3iHCdO4CTMO4vN48MXkY9P7KEu6mrSh99G7DjA7MZTFM1MPbxMMQvByurtbqP37EySFBIjNmj16v8Eg7Pqn+u6PVV7laK5+MNr4eH8nOxp6+MqSDELNBvV5u/rBGjGxr/tEyl5TQ4HnfGlSgk8hhJgqpzWzfM6cOfzlL3+Z6LaIC4w/EKSqqopPPvlk1PLi4mLMZhmuJs6Q33v8jKomG8z/GnTVqJqdhxzqaTiSVs9F4a1qPuehoHHWbQcf06ogZMtvmeOLpyPhohO36ejhfmOJycM3/WYsbT/CVv8B6PrAEgHpS2DeV1WtQpNN1c08Usd+qN8IuVdzoMtLoKkUQ/sqiLBDyZdV0pu2PdBSqoLW3nqYeevhobSH5FyqeoECftjzEmRcfPik2zushpJWvI3FbIfMRSd/PWOo7XKyra6XgsTwkweeEamQdQnY046tfWoOO7Vant5hKH9b9WwfkeH4tNSuhcYtMOcesB2nFEfDFuitg/yVo9tX+a76nObdB6bQsbe90BTcrBL97HsdjTmcoN5EVLCXa6cV0bsvjv6I6URYjgryvcOw6x8QtFDb48OTtITYtOLR62g0kH0p6I7zt6T6IzUH1DMIsTOg6j1IWcDe5gS2Hejh+iK3CjzrNqjyQHPuPPZYGS+fR83njkiFpOLjr2cKVReapEa6EOI8c9opzdrb22lvbycQCIxaXlgoQ43EqekdcmFv+gS2O0eWlVa3Av/GkiVLpq5h4vww/brjP9ZWBhXvqF69lHkw/fqD21wLfh9s+Z3qLZ35BVWDsvA2MJoh7GASHYNFnfx6nKA1QFgiufZUcpOjVeA62Aa2WHXiGPCDz338up5jiEovhEu+Dl210FtPW1cXVb58FsQH0W57DhJmq5PqI/jdQwx2NhOe5ebyGYnMNGbjaG9VPZi2WLVSSJwadmgKBbNdte1oGo0KkBu3qyApvkgFni27VPA240boqYMQ57HbnsD+1j6+93oZxWmRPHpZLlnRNtIcxy8pQ18THFgHGRep5EZjmbbypM/r9PjYUdFEQWslYRORcTY0XvV0n+jzdHaq3vSAl1EZXCLSVD1Z/Rlm0D2f6A6+H14XuqhsLIPtEJ8PtWuw6314+/fgrdfyUWAa6Q4raQ7bwd7/HiKjY5l767+QYguqz2OgHWo+guRiVZM3ruCYp3t+cx0vb2/ih6n7yA71gd8F0dPUZ2qL58uL07h+VgIJkVaae500dluZ6cjDZJqAeaABr/penCz5VNYlZ/5cQghxDhp34Llt2zbuuusu9u3bR/CongGNRoPfP8aJjBDHkRoTzpLC4w/nE2JS6M2q1qUjF+KPPTlluBf6GtQwz5AocGTS0e+ifH87i7IcaLVaKP0HBHxQci8U3KQCJb9XzUfc9wbkXqUSmOxfBR3lYI2GnCvY1KFlVoIds/kEP7/eYRjuhtR5EJ7E1t2tHGjoZU5SPOaYGar37yi/LLfyftl8vp1hYLGpn7jYWMh5ZPRKjkxY9HU11DgkBkr/BlmXjR6+ekhikRqiaLGr++ZwiEhR/xZ/WQ03Pp6Af3RJi0CAAZePhm4nGQeDzRMGnaBef3eNCrKP7ukch54hD5tbA5jSvsjczAnIXBqTp24nkn05ZF5ybG9sXMGYwdAFz5EDCTMZ0IWi0/ShtyViDEuG/ib2N3ay3p+IV9sLQJrFrb5fK38BWgNpniHY/Fv1vkZmqOzL9ZvU9zwy7Zin6hr0UNs1xK7Zl5M9OxkIqtEMgSLQaDBrNCREqmOzrsvJpu5QEuZcRpJpApJhGUPUqAWtlDERQlyYxv3rd88995CTk8Pvfvc7YmNj0chQkLPG5XKxZcuWkftbt25FV900ap2mzn78iYGjNxVCHCkqQ/U8HKpLeUjHfujYB/Pvh8EO3qnX4muv5HOa9WzvjOStRgsxrnByC0tUbctgQPX+NW6B9nKGkxfzSX8sM225xB7qHQ1NgNbdUPp3Stu93LspkVvnJvP/Pjcdjy9AZXs/+XFhKpg9xD0A7XtVz6oji4tmJOH2BjBbjJB/tVrH54HdL4A9BdKXkBYVQmp0KPEmN3zyK5WM6KLvqADwyB4WvUnNjRzsgMjUw4Hl0TQafMYw3t/dQly4maKUVDVE8GjdtWr+5aH5okNdsP3PkDpfvbd1G6HxU+YU3cWbDy3CHnKKw+jjCiAi/YxLk5gNOqJsRqIjws9svtxwr/o8TlL/FVDPo5VaFaekfhP+ug109jkZskYS2teBff3P8YVGQ1QONXFX0GWcxVdKUggzG2DHH+jp7WFz5LUs0ezEmlSojufQWDUkfeYXoLVUBXk9B9RFnCPmMn/t4mxuLUkmynb4e1je0kdg2x/JTIrHNOvwnPDitEgyY2zEhE7g1I9TGRouhBDnqXEHnjU1Nbz00ktkZY2Vxl9Mpi1btlD6wk+YmanqD254dSNNxhQqrYdr4e0asBHjPM68NiHEYdYoiEilus+HrWU7sbHxKhjtKIeUBeDsJHGogzZrFriczIoKJ8+1kYR2HTizIX2x2s/+96CjEmJyGQ5No6LBS1j6UmItdjXENrFIZWMNTyW6q4cHMjuIT1L1BF/f2cQL2xr52vIslgW3q17W2beDLQaK7wPPAOx5GWv6Mqwhhwrf16uhs8Ggmp/mcwNwbVESOTEhaLc9Q9DfhSYyBRo+haZtMON6iM6jd8iDLxDEkVyihhQH/eDuH/2++NxQ9jpEZuCLnUV9t/PEU81q1qihpY4cFeRqdWCNVEEagMEK5kjQarGPd+72GEHns59Us6W2h+9dk09i5El6TVF1C7sHPQy4z2A0jqtf9arF5I6qjSomQHs5mrbdhHp66NBGMxS1ELu/Er9Wx9Cwl4JkMyX9bxPdtUxdzEieR6ehh87OTvz+/eBqV8erqx82P8Fb2iW83ZfLD7PCiah5Rw17j8oaNSf6yKAToGvIi99rIUVn5cjLCnqddmKDTiGEuMCNO/C85JJLKC0tlcBzCrjdbuDI4c1B7NExZGTnjCyxbd111ts1kdxeH+Wlpccsl4RDYqJ1hWTyre2DxFtqudn7GrGFs9X8xYTZKuvovrcpZAhmXQGabGI3PQMdayHl7tEZLiOzoG4dRGaztdVLe0MlnwYymdH1HjZ/H5Tcp5LQTL+WhG1/4v6ZJshXF4sKEsNo6XOQG6mBD/+mkqwkF6shutYIFWR2VEB0HjRtB4MRDmxQPYmZF6l9H4oKfR6G1/ycvuEB7DMWEzG4Hzqr1PBDkx2Ad/a0UN81SEu/my+UpFLS8jfVM3Rkwh3/wXlolnDMBh13LUw7cSmSnMvZVNHAbJ+f32+oZV1VJ9/73HVkxR6cE5cwU90mSPegh6YeJ4Ne3ymtn+YI4d6lGYSYzmB4o8GqemBD41TvdVQ2GOT36IwNtINnCFdnHd7UpYQOOXEabPja9uNPKMHauZPAUAcGTx99Q8288sFWPtIUsyLJyIz0BELj71O96711KukWQXqCoTiG9jPsyiIiqVgNKz86EddRFmRE4U65B4vxBMPHhRBCnLFx/yX+7W9/y1133cWePXuYMWMGBsPoH/SVK0+e7EGcnvLycl6q0VNhViet52PvZnl9B909/wD/4QBaEg6JCeH3qn8PnoQGAgGcHj9au42EktsgKlYNy+urB388tO5QGTEDfpWEKDROlTHJu+rwPve9oXo7m0shKoeYLriu900aQy6nz5GELdQOGhW0vb6vhyj9HBZ1fwD1nzKQtIR1VV0szY0mjnYgqIbRhsVD9wE1Py1hphpKq9FC+Zsq4EmZD9EHLzZ5hlTg2LQDmraSF6yhK2kuEakFsO4DiJkOOZepANYcyor+V9jkiuKVmnjmpERRMuv2kfaNOJTx9+A8NLNBp3pBXc4xS0r8x9oufru+g8837CPebkGv8bPtQPfhwHOCfevKfB5YnoltrFqpx3FGQSeoBDi5l/PRx6tx7nqVkktvJTp/8Znt80IXDKo5xsYwBkJSCO+pIGGonT2pd9JgnYHBlEh0rAHi5mKqeJlgTzmzzUYatNMIbn+R9fszKLp8pupZz7pEHac5l/P53kb8lq0YPbUqg/NQpxp1oDv8HdjV0IMvEGR2qvpbqtVqPlNB53t7W3lhWyMPX5JFQaJ9qpsjhBCnbNx/jTdu3Mj69et55513jnlMkgtNvui4hJEezs967+bx5CdHScIhMWEaO7qIsYVg3PciXq+btuzPkxRpJTrMwt/uWzB65ZqP2b3hXeoiFnKNJRLCkqCrlqo96wlz1qEJBIg2vqeCveg8dfIcFg+X/RAi05g10AqeXeQlhhMyS2Wd3Vzdxr7mPrY19GPVa1hUsgyisqjpGOS9sjZ8/iAz50WrEicGq5oT2bILYqfxn/tj6O/t5hs3r8Ax9ytgCjk8x7C/BXb8CdKXqjmhngGss27AmrJA9cpZ7CoJUeNWNZd1xo1EO6IJ19i4fV4qX1yYdvw37Yh5aI3dTrT73yLB0wAlXzmmfmVhYhhFyeEUJIZz27w0/t8rLn74djn+IHxh/gme4wyMJ+gcl4E2lan4OPVLnWFpdMQuJug4SXIhcXIaDaQuYU9FBREBCBgtaCMzSfDWY9QPcsBrRO8zkFy/Gl90Ju6uBtLcZXw3N4HtWgedQR097iBWQygmvVl9Zz1OdOEadLmXqaHf+oPZp3WjT3WeeKOMAbeX976xfEpe+pky6XXYLXqMUuNTCPEZM+7A86GHHuKOO+7gu9/9LrGxsZPRJiGEmBDba9opffknJCensGLuDOobmmj64FmMC64kJjnn2A38PoY66/lkeAFXfu5mdAfWMPjaN2l2x/JC+PUkeauZGRJkoGY1PcZ9zEiOYHDQybSCaWh1OlWm5IofEXIo42v1R1jXvoi3L4qVl32VrJhQcKh5izND4dtX5JIRbQOLUZXa6KxU9TpdA9BRQe5AHT0t+/B3Z0NsvBpW6HFC4c2qfEREhsqWmzQP0pcdDkobt6iEKo4sNQTRaFNDbqNzKBjyMD0QgOadaq5o2BGZXgMBqHgbQhwjSZee/aSGop56ropoxBjw85U/bMHt9/PnL6vHrylK4ZqilJFdLMqKomfIw5zUg72jvfVgDB2zt/ScU/W+yk686OtjDqW9enYmzM6ckKf6tKaTv22u5855qcxJj5qQfX7WlLcP0rH3YzzWeAZNoSS5q7EMt2AcaiZfvwW93013eD5V/VYChgISY+MINmwnpquJ5NS5vN4cQUxCAVceulBS9hoMtsKCB9XIhpjcMZ+3JC0Cj/+zm4RvWW40y3KjT76imDw7/qIuFM64YapbIsRnyrgDz66uLr7xjW9I0CmEOOc5wiyYYzMIcSRA5kWEGfZh6P47EVrXqPXueW4z0zUH+GZOG/mz5hOVMQedtwmGBzBkLsbe5WNmlIX32xfxeqWL2xxe9A2b6bBp2dujwzHoJi7cqmpfanVqiKzHCY2bSQkFX2Ius6bFqx5S94AKUIGi1EiVeXPvB6oHNeADWxwUfR4G27h6dhBP635CEjNUQNReBoYQlRTIHK4C0EO0R6RF8Q2DRsf2Vb+nvK6J9Kv/lQUHe30iQoww1A27nsdjjUO/6EEVNIN6/p4Dh4clAxflxWBoyUNviwK9Ebffj8d38KS9vQLqNkD+NWBTJ8JXFiRyZUEi1e0DdPd0Ebn1OdUbNf9r+Axh+AIBzK4O2Pe66q2NyVdDefe+qoLvlHmn9uF6XSecZ+nxBfjbp3XkxdmYn3mKJ+lpS9Tncxbmb+5vHWTrgR5K0qMuyMCztXeY325u54FQH5E2LUF/D3RV4Yyeg99RgHmgDq3egNHTxVB3H+2mVMKtyXg9pbRpEgiNWsACQyehtjDwOwAY6mnFr9ETdoJyJa7uRh6dPoghee7ZeqnifGSwyjxvIU7DuAPPG264gY8++ojMzIm56iuEEJMlxRFKyhe/OnI/OiUf4r8DBjOBQIA/bqgjwW4mxKRjur8O9rxFeEIR4aF+iCiB+FmYvMMUbv5fCmOGyMyfTUvFZhbGxmPMW05T5Dw0HosKOgEaNoLOqAJPVy8Eg4QV3cKszGUMdTRQue0DcrXNWApXQsw0FaT6/SoBSsCvypIMNFE1ZOSdPUPcMS+ViLyDZVkcmbD8O2oIre4kP90zboJgkKGBd+nutZOtP2r9kEiGQlLZuKuM9sBevrC8UC0P+CC2AOKmjay6PCcacq8euX+opxMAv0u9zsDhQBWgZ9DD918vIy8uhP+bPA1X0x5+99L7lGkyMOi0/NflMRj9HhWIw8F5tO2n3ivaUQl7X4Jp1x4uleH3qiHFURkQlkhrr5NVe1vpHIw4tcCztwGad0DGslNrwxn64sI05qTamXaBztHTajREGQNEueqwdTXiDkulNHolVVGLuNa8iyFbAobOHQSNoWxyXMPCrDjyYwbYFfEIm3bsY7YlmWX9b4PTDx/9A8KS2XBggA7s3LDQj9l47DESCAR4463XiXVWsfT2NJU9eqINdkLdJ5C8AMLiJn7/4twgPZ1CnJZxB545OTk89thjrFu3joKCgmOSCz388MMT1jhxfvP7fdS19/HJrtqRZVVNXURkRp5gKyFOzyf7O4gJM5IbFw6oMhu7q+qwRHv4789fAu4M2BkCdZugbj1EpKieOr0R5n4FjBZygdzmZmhrhkCQRKuDxCMDlcLb1L/dByA8ifqMz9Pr8lNYv5m6T16kub6eQO48Zu9+EbIvhbTFKqBMWwZdFZB7JThyeOWDA7xa2kxcuImbs3UqiVHmJRCeCJt/QyAqi96EZUTaTCozaF8DJBSxpa4bR4iJ9JhQ0GhYctGVHC8ll3/adTT0ZBIedsTx1lML9RvUlfyQaDXkd8efVUAalgTTrxtdCzN+JsQVcnS9lVCznovzY0iKsEDejQxFFLD2rQ4ibUGSHRb04fGw8KHDGxitMO+rKhA/FaYQCE8a6TkGVAKoA+vUnL6wRFIcNv7f1fnEnmo5jIFWaN8HcTNVPchRb5b3pJlRT8eFGnQCxISbeezumxjaoaF/7xsYDVryujcSY/ExaEkk3tgORV8kNDDMYynJ0FoGq5/FnPsvNA7ruazqVZizhH2BJOKb/4Fdb8Y7+x6i+uoxb/8t5F6hetCPoNVq6Yubh1k7/dig0+9T378zrU3u7ID2cojMlMBTCCGOclpZbW02G2vWrGHNmjWjHtNoNBJ4ilM20N3JFm8c1qbDJ74beuxEtvROXaPEeWlvcy+/X72TZFuQr1y9iOTIEMKtRr6fWoql9n2oD4G0RTD7TuiuhqFOfrm6ks21XTxx7QxcXh2a6nfICx5Qw1s1euiphqOTzIREQeseFShmX8Z/b9IR0ryO2Og9JIaE05a5EF3h9eAtVSe+NR9D9DTVazjQqoa5dtfy+XmXEWe3cOX0OHC3HexRDKgTY0sEBwY0vLaxjuuLEknr3AItu+jWO/jpB83kx4Xx+Oemn/Q9CYuK4+6VR50YR+fBdL3KqAtQ8xE0bIL4Ihju4shyTnsbe3h1ZzNWg5Z7l2VjMx/+c6LXa7l70eEEPVEp+fzhyzkYdaDTHQ4ue50e2gdc5MSGnbwXd1TjE6DojmOXzfz8qIBixngCu6S5qt7j0b2u/c2w8++QebHKjiomTH2Pi086E7lcqyO0bi266HxszZ+wQ3MHDn8bBu8m+sxx/HHvDqbHGrkkJJoch4n/yKrANNDNkCWOf3+ri3jt57kpMpvGHhf3zYiDim2He9OP8LdNB3BERfO52XNGP+Adhq3PqWAx94oze1Ex+RASCyFyAVUIIY427sCztrb25CsJcYrCo0bXIS2rawf6j7+BEKchOyaM++IrMQ82YDeUjCwPy1pIl99PTauf3sEWcg2tpMy4AULjCVn1Ka1ddjoHXLyztw1Du5eHCuOwhUSzs3WYqq5Urk6IoLdmNzGBTnQZS1VgaE+B5BKIzKAkrZ82TzSNiZcxJ9rARe17IMILnjTY/wG4e1UPS+ZySF2gAr2QWJIiQ/jighAAegKx+AruJVrTB2hg1ucJaW2kwOjH4a6HkBiYfh2Rni6+F7MBT+4YQ8D8XjUXMzKDQXM87+xuYVGynoTBfZA0R80XBdX+IxOyRGWpXtysFeoxrY7y1n5KG3rZXtfFRxWd6DUaEiIt3FqcdsLPYKxyFb9fV8uWum7+68ZCkiJDjr+xe1CVeTlk90uqVzbv6tHrHQqYT4dGM/ZQX51J9f4aT9A+cVrMRh16ezwbm3NZGOfDaLFh07aS5auk0xUkXOvCFRHHhu5w6q2J2JNupyhlPiZzGAylUd/lJMMRQl5cPM9saWVHfS8LMuZRMO9+CAbU9770ebAn4UtZzK/X1BAdauS62SmjG6LVg9VxTMbm0yZBpxBCjOkMi5uB3+9n9+7dpKamEhHxGchaKIS4YPQNe3h2bTWLMh0syE2DThdYLOrBzioYbONDVx7WshfoSriYTEMFWJyQexVfjK7h6rmXEZPhQKOFztYAtubfgLeboZjbcA4NsHvbGg7s+JBMq4s5iUVq/qU5TNUVBG7OHcbd/Cmm6GWqREfDBnD2QOUqqN/E0Pxv8npLAjMMfRQk2dVQ26O8vacFw2ArN2tXo4nMAu8wsQPN6Jw+9q2rwxeaQMaCG7D01pBk1zMYOkapEWcXHXs+xJY5yEYM/OaTagy5A1xnLoWeOjXkNzr72O1ip6nbEYY9fuhv5vq8KOJNPtxaK5fnRYPPM6oMy6koTo/AZtbjsJmOv1Lrbtj3JhTcooYlg5pbOtaQSM8Q7HlFBc9JxeNqy3GFRMGcOydmX+KwwU56tq7C5IpG78jGU7eW0EAfwb4mEmgkGFeAsaOM8I4KHki8Hqu+EvvuTez39ZJ38R2w9ifENayiJOFLXJoMsWGJzEuLoiA5Anb8DbyDUHQn9DeCKQS9Xs+XF6UTMla9Tp0BZt569t8DIYS4wIw78HzkkUcoKCjgy1/+Mn6/n6VLl7Jx40asVitvvvkmy5cvn4RmCiHE+O2o6+GVHc30D/tYkK9RwYrfq8qO9NZBWxlLsy+i37aIT9zx7OtpI9XQi85kQ582jxibmh+4ra4PW9NW3P52TOHJLMpyMF+7j/7SVVg1LTjsaeDspttvUfMuQSXMad2LyWRSwYuzSwW75W/A9BsgfQmemPk4OxsJHBzC6vMH2FTbRUqElZQo1cOm18C6Zj8lmXmkGQ1qKLAjl+79uyn3xlPtX8DMN/9Ajr4Vf9Ji1uxzcn9MAIPu8FzMrV0Gnjkwi1ziWTpDS4TVSJM5E7JiYNfzanjqWIHnGIrizRRWr0HXa2S+zaXmfTasVmVTSu4bHXz2HFABafTBUQ19TaDRjpRwWZwdw+LskyR4sURAZPro+Zyzbh973YAfXD3gGT6l1yKmUEc5rRXbiQkJo8TSiD8yEvoaGUqYj8k3gLGvnoApjJ2mEv7RlsBDoWswuLvZ3TpAmseHOWUxEUNdrOh+AetHDVxW8hUuW3YpNO1QGZaDUeDuV0NutQYY7ORL07Vq7rYQQogpMe7A88UXX+SOO9TcmjfeeIMDBw5QXl7On//8Z/7v//2/rF+/fsIbKYQQ4+Zzs9xax/cvSyY/LRHs0yHjIjVEMxiElAXgGiS2+gViFz7Mx6Vu9tnmcdGMRbzTZOOioWoiKeXpUh3hmn4WuDaijYwDawSuvg5WdznIT1rBjMw+6K5h9a5afri1jn+9LIerZyZCwxYoe1kFdY5c6KxQCXqiMlUgZjAT4XNz4+wkjHotDHUzXLMR14Fe3MYBuORu0JtIjrJiNlsZSL0Y4kLBngEhdnKmX0v5zkZqtzeRnrCcxkAzTQfa0cfuwdDmhLp1qpfQFk1yhJW45AzqB3009Xh49NIcMqNtUPuaCgxDE1W9z8r3IWG2Gi6s0Y5OJAS8vKMBh9XI0qxLVEmXvnqwRKq6n8EgB7qGSYs1su1ANy9sa+SRiHXE6V0Q9Yja1+4XVRmCefee+ucYngQzbxv7seFe1ct8iDkM5j9wTLvFOaarRg0rT5xNnLsSN2Y8rkGcfhtufTQJA/W47BkcCESzwTONr4evITIxm27/MNbuCt7ZWsH1UT2UD9sx1G0jxJFK3GAXtOyEqtXqOE+dr47zvKto9YWy45U/kG3uJ+u670gZDCGEmCLjDjw7OzuJi1MJKd5++21uvvlmcnJyuOeee/j5z38+4Q0UQojT0l0L1au5NH0pRObQ2j/MltoeFmVGEVm3Cva/q7LJugegbR/3zl9AlzOCH69pprSxgeC0Ihalh/DC8y3MijVwt80NBjt01hAM30PTcApRjmwysmJBZ8RX1kFudANptII3EuzJh2tzarSgM8PSb4I9SbWvrwnPtj/z16Z0+iIL+E5uG6Fl/2B+/AJMWqgo28nWoRiunZ3MvHQHm/ZU0r7nOWJctWoOadYKVppKufjSFEKqy/jEm42xfh/JwXrQZkEgALUfQ8pCYsMT+cF1hXxa20242UB+wsG5bHojGE0QkazmUXZVq97IynfxhcSjL7hu5O1s7B7iidfLSHeEsPSBxQeXHqy5GRrLXzbW8cwbW/nGpTk4bGaa+4ZpzV1KXHzI4UAw+9JTz1x7pIp3VPKloi8eTkLUUa6G1eZfA3EFh9eVoPPc19cAzm6WZZfA5pcZ7qzHE5GHITSG4aFO9kauYMbQp6RrXFzGEJEdm3GkJBER6ocQIxt3vcmusEFMZhudIdl43W7iOvdBfIE6NsIS1EWJ+k+hbj0G7OzSTsMWYyRLgk4hhJgy4w48Y2NjKSsrIz4+nlWrVvHrX/8aAKfTOSpboRBCTKmoLMj/HERmANA54GH1vlbe29vKD/MDhLv7IToLHBng7ML38lcx6kLxOldSnJbM0rmZWANDPJy0nhTTEL6QRPQRSVD/KZa6D/nyRd9F9+mvoCwOZn2ey1M1XB7ihAPrYc2bqtTIoofV0N6hDqh6HxJmqcCzZRcE/OjCk4jxRBMdZYOQAH0h6RhdvRiikrFVv0V4xJUEg0l4fAEqO104fEZicq6A+EIYaIH2vdgiUiB2BksTZsLii9UwYpMNtEbY+zJNfjtv9A5z4+wk5idZoPcAeDNU8pW0pSpb66HkQvO/BgYL+ysr2bCjgqbKTfzfG1TdzqTIEK4pjCPaNvaJe7rDwsykcJIjLZSkO1iQGaV6co901HxRjy9AIBAYs+biKFqDSvJz5LxOcyQ4slVSGPHZYouB5GKIm04gMget1oxjuIWgMQzDQCOe0HQ0CTMx9Teid4dQm/dVHMXXoCt9nvA9q4nWFvKT7iUUJ5r4yhf+Bat/QO03LAHW/VzVZHVkqmNusJ2o/Gv4xsVXHPt9HEswqC5qhMaP7k0XQghxxsYdeN59993ccsstxMfHo9FoWLFiBQCffvopeXl5J9l6bL/61a/4yU9+QmtrKzNnzuS///u/KSkpGXPdvXv38vjjj7Nt2zbq6ur42c9+xiOPPHJG+xRCnIcaNoEhRNWIBGYkhqPTaFhd0cbaacV87vpLRzKl9tftoW3IgMno5ZErZxIRFYtRryVY/iFX+z6gp7mRD3O+yqKUEkIIMmDL4J0dzVwRMZ0wZxM0bIbWvdBTAxGpoA9RcxM1GtWraI2CaSvVibHfB5XvQkgMujl3cTNA5Qc4Kyt4byiDkvLfk1pyHYlFl5OYNAf0qn7kTYumYfSng8Wm9huepIbEhjhUQHtQWXMfNR1NXOVag9YcxnpPBh9VtDMvYoDotldguEe1R29U8ybnPzCybZfPSMDjxRtdQM7210mOsgHzRx7/0fUzj/t2L8qOYdER8zVP5ST/R2+X4fYG+PGNhSdeMXvFsctCY6DgppM+hzgHxeSrm8dJh9+MxedD399CMFyPLjyB9JY38Xda6OzpJy4xl7yiG1Vm4Tl3EhtfiL8phMR99cRVvUqb/30MkalELb6Hjp5hUrIvAb1F1bw1hqv5nmHxnHLaq4EW2PuqOqbGSPZ1UsM90LgVEueAVbLbCiHEkcYdeH7/+99nxowZNDQ0cPPNN6vEGajabN/+9rfH3YDnn3+eRx99lGeeeYZ58+bx9NNPc/nll1NRUUFMzLFJJ5xOJxkZGdx888184xvfmJB9CiHOM4EANG0DS9So2ov/enked0XtozDwERyIgdBYcPWxbyCCHbbPUeYM5+IWP9fFqqBJkzgXc0mAnr072dejIduQSPiMe/jL5gbKa6vJzPExR9tPZdkOovMXY/e7YbATFtwC5jDaewZw736VhO5N6ApvhdiD9TULb1VDbw+1ta2M8poGNuivo6j4q2DXq97BIxL12IZbaF7zHJ0xiyiYfwkajUYFnX6fyvwalQHmcD7cVUdM1T8ZnBFDWOpsrklMJTs2gpl2N/gyVFkQVz/ozWrO6RFDUx97ZTcmVzdPL/Shm5YOWWmT+jElhlvwBgKT+hzi3OTxBXhpZwcLtBZMGiNDscV4dGZsfVX4LJF4w9NpNRhp1Vho3riHBFsZxWHdYAzlc54Gllx5C75du6jt8tGBjo1v72VTdTe/vKOI3OiDPfgJBy9oeIZOvRyOLU4NCbennt4L661XgWdIjASeQghxlNMqp3LTTcdeZb7rrrtOqwE//elPuffee7n77rsBeOaZZ3jrrbd47rnnxgxki4uLKS5WafKPF+iOd59CiPOMVguz71L1+YCqtn6eeKOM4rRIHo4zQ2cl9DUR8HsZ7GnHNByCoa4bTfIdDLu8eL1eDAYDhMagz7mM3I4a0kMq6W/eyBfXGok3evhqShMF7iZ2GmfwyFaY1unify69GCreguZSyFhCbWMLjvL38Jtc6LzDvPnhxzRp4vmXi46olRn0g07HVlccu4e8ZOUMwSfPQk8tHUUP0u30kRsXCiYbnYZ4aodNTAsE0esODjvtOQD7V0HaQkhfxsqiBLyaBPrCcwhLX4wVKEo9eAI850sAdA26sfs70fXWqcD14LzJpY5B4vrL0dXUMOz106lPo6WqhX6Xn0umJ6pgF2DPy6onOeeKM/qY7luWOfYDjduhaz9MuxYMljN6DnFuqm9uRPvp/2LW70Hv7cBjicVi9oHRRjA0gX7CcOKn3R1KoPFT4pMN4Neriy1DXdi7dwKDBAxDxOdfRVjZamzRGWiOvo7RVgY7/w6mMJj7JdUDeiJaLSTNPf0XFlsAZjuEJ5/+PoQQ4jx1xnU8z4TH42Hbtm089thjI8u0Wi0rVqxg48aNZ22fbrcbt9s9cr+/v/+0nlsIMfFO+/g8Yn5Wz5CH/W0DxIeZ4ZLrVVF5ZxetFVvwdVRiTV1O6qKbMFqS+MumA+yuquU/Vk6DbX/Am7wI07wvYdr+R4KdpSwNTWaOpZUiQw/a0Hhyy37HjxML2JuYCzv/Am17weuC9MUU5Gawsecr7OvvoqDPh3v763RFXwJNw+B1Q8pcVUOw+F4uyxhiqV8DuhiVfCU6l0013VR1DBEfZibMGkHuZV8mKxBEf0SpFKwOyL1KlRwBUmId/DH0St7d2sa/2dsoSnWMSujT2O3khW2NrLTsItNbCRHpKqHQQCt38C5kTYOIGyit6WDvAT95rf8LxhgC076KTgP4/dC+Tw0lPlpfo1p+qr1Lx+Pqg4E23txeS1F2GomR1jPbn5g0p3t8ZgWbsEd2UqVbhDk4QLynHmvQg6GzDNyDGCO0LOheiyd6OjW5cxg0WSm3OgiGJRDuXEtoUxmhBTcRozdDiIO+zc9j1TjQao+YBxwMHhxaHql6PYO+iX75x9Jq1XB7IYQQx5jSwLOzsxO/309sbOyo5bGxsZSXl5+1fT755JM88cQTp/V8QojJNRHHZ3GGg5e/toDY0IPDW4c6wOfCm3ste0J7yM3MYIbZBPvX8q9hVYT1NeGvuYLBve/Tf6ACZ9IS9oVfyVzva3wrvw+GnWCKod1nJkIL880NzM/oI7jXg8aRC7F5oNEQCMDbzTa21Pt51B5JYnIqy6w74a1fqky3l/6AQEQqvdtfIS4uk3f60qgNieDKS78PwLx+F9mxoYRZ1TxPk/6oBG4d+2HPSyqJkjns4LDd3SyK0jLb9hbZ+4LQlQWFt7CxfohP9ndy56J0CuMshDgWgHHOSE1N+hrBM6iGH2csJTVqmLBBF+2DaYTaHejcfSrBT28d9DSompzuwZF5sgx2wvY/Q1wh5F99Rp8Xmcv5Z2cy//lOOV8vX8ud11yqytCIc85pH5/uARwRdvzOLqzduzFrNWicnQTjZqLT6olsXI0/YQ763iaSA9vY3aWlxZxGeEw/mUMNGGwWQr0uVarI1Ut6dCift/bhiA1jqGo9/fpI4u0hULsWkor5R3cm3t0uvrhwjLYE/OB1jq4VK4QQYsJNaeB5rnjsscd49NFHR+739/eTnCzDZIQ4F5zx8en3QsBHYoQN2svBM6Ay3bbuJnXmMlItb0Pvp3jK32Wu3oYtLpc97SH8aVsX0eHXMGdwLTH1b9OSmcRweCYkJkHDZvwpC3i50sJFkV3k9q1jqGk3uwN5hGbOY3pePgDf/vs6SgK7uf2Ki5mWn4evWYOtZy8YAzDUCSGRvLmjjsID27Ds+SvTcr5ES8S1I01v6nXyyw+rub7QwTWRjap3MjyJQZePB/+6lRnhbv41JxOsB3sf+xpw7X6D9IQCdJYu8BqgbgPYYnhnhw1nw05KYy7ncs1maHBDyVcAGPb4scRMgzl3jcxDjQ+3EB9uIS7885iG22DTMyoTriUcpl0H5pDDQSeoHua0RSrh0ZnSaJidFs1VWfUUaQ6oMi8SeJ6TTvf4LK+uxbOnjISEWPQ+FfQFQ6IIoifo7CFgT8PlC2D1DaJLmUePDjL0A1j1vcTlL8I61EDN+uep63gOe8GlFGk8WIN9KtHXGw8TjJhB302/JjzzYojM4K/vlOPxB/jiwvRjG1P7CTRugTl3g02yJAshxGSZ0sDT4XCg0+loa2sbtbytrW2kVujZ2KfJZBpJkiSEOLec8fG591UYbIV5X4WmrdDfqgKupLkQEglR2VD1Iei0dFiz6Cn8Fyo/fht7dznNpmRmpCwiPncWy7troG4d9MaDZwhdwU3cqn8dXXwMQ4FUuqp2EmZNxF79KqQngSmUBWHdFNe8Qs6gBgzTafIZMAd16AtvgZh8drcM8ZNPm/hmwlyujtORa4fc+OBI03udHuq7nXgGuqBvHbgGIDyJH7+9h/oeF2ajDQpvAcDp8VEzZGNVcw6JpjQ+v/hRVcvQ64SIFO7KqcbtqSan9XeQOg8sCQDUVZfxYdUQS4ry6fNl8NGHddy/LAubWf15iLSZwBChspASUL1CWWNkmdXpIX3p6X9OR8mKC+cHd1wMg4WqN/dU+L1q6LI4a073+HRGTSMm5lNsQw340eIJiYGWvWjiE9Fr/Pj9GozOdgwmK8MBH9fe8ShDH/wEff3HmAoehZkr2d/wPwxZerF3VbFJ52DW4q+wtryB6PDFmJNnEx9iAZuqNXv3Ihd+f3DsxoTGgSNrJAO2EEKIyXFagWcgEKCqqor29nYCR2UkXLr01E88jEYjc+bMYfXq1Vx33XUj+169ejUPPvjg6TRtUvYphPgM8w6Dx6lKkOReDX73yPxPrz9A3Y61pLTuxWWK5iPPNL5MJ03OCnZELyNL20rk0F6oG1J1/eypYLJDej7oTUTQD4EAHdYkVhkWUFFRxjx7L7doDbDtD9ye5Kcn/i7KLdkM1nbxyUefcpNuLdGOrfzNcBMR0XHcMT+F+OhUDM3tUPMxDPcyWHA7q2p8LM6O4cWvLiDcYoQex0jNSk9AQ5hJwyMlFjVMUKvjVx9VUd7aR4ZjOvbICHAkjHobMmcmQIRJJe1JXaiG2HqHiax6mcx+G+/sDqO6fYjV5e2kRlm5ee4RPZemUJh+LU6Pj/WVncx3eQk1jzPA69gPrbsg5/KTD2l0D6p5ro7cU++Bai5VdRtn3qZKzYhz2uz8HDoOhOENRhAIBrF27CNoj8Ef9KCv34A/oYQeYxw9Wj3vtCZwcfkuMh2JoJ2nauTqTaQY+tCmxjHUUMo2dwaDGz8hw+rhb457+VJR+uFkWMANc07QCxuTp24n4fEFWLu/g9kpEUTaTrlAixBCiIPGHXhu2rSJL3zhC9TV1REMjr56qNFo8Pv949rfo48+yl133cXcuXMpKSnh6aefZmhoaCQj7Z133kliYiJPPvkkoJIHlZWVjfy/qamJnTt3YrPZyMrKOqV9CiEuICYbuEPUMNGDQ1JdLh/6gQMMdzexajCLnIQvU26aSc2AnkBLKZHBXioGLFx27Z2EDZdC9Yeq123618HmYENVB76aPuYFdPS0dxASHgH6UDpC8xiO18COP0H1xxCVyb7wa6jYX4cuMZbI1OkMWCKp6R3g2a29xNg93FSUyIZGL3NTFqIzhEBvI/0b/oi30cea4B3cWpKhem3rNsKihxmu387nnB9im7OEvObXwTIEKSVkx9gw6DR8bXn2SA3N3iEXr5U2c3VhAg6bGTIWQ9oC4OAJucFCaMHn+PiDBl5YW8sTn8sjKdLKlTMSxnwrt+3Zw/bte+kfXsKNc8c5pHaoHbqrVZKXkwWejVugfhPM/DxEpqllPo/qzTwimBjFGAK22MNlasQ5zW1x8I/wewhoO/i873VCNB6C7iE0g1V0Z9/E+85cpjk3MBiaxNV9f0f/Ti+l6ddTYOhFW/EWrw1O59PhedyabCCxYwtZVh0FYf3Eavp5/OobRjI1H6Ntr5qr7Mg6eSODQQj4RnrRN1V38uwnNVxTGM8XF6RN3JshhBAXiHEHnvfffz9z587lrbfeIj4+ftQVxdNx66230tHRweOPP05rayuzZs1i1apVI8mB6uvr0R5RZ665uZmiosN1+Z566imeeuopli1bxscff3xK+xRCXEDyV6qTx6oPobsaV/6t3PrXfdxq3cYX4tr4QmIS7um3YB+E9e9VstGdyNKLbuPbbivaQC9kLoPUBarsScUq8LnZWzpMm0tPevwA3pbdfOK7hRcq6nk4rZ7PBWqhohrCEmDWF5ndsBWHZh8NPgfLWv8HvyEUvS6F6wty6PYYaelzU9/rxLv8YnSaAAx24IhLYZbFT/z0RPUahnuguxZcfbQNBtnX6WcwRE9RwZyRbLbXFSVBVw1s/Q3kXQX2FJ5bf4Dfrz9AS4+Lb189TfWObvkdhETDjOvVvm3RXJXdQ2hcHCtnJaHXH//PwuxgJXbzLmKTLx7/55CyEOJnjZ4XejxxM8FghfCDr3+oC9b8l+qpXvA1MIcfu40j69SCCXFOMHn7ye7bQI63nKi+rXiDWgzpi6GjAm/bfqbFxRDj8RKm7cVkNjFkTGFVbxLTw6vQVn5AxtAmNvXks6prId+65EHiHDnqu7X3VVVeKP8a2P+emtM9/QZ1wSIYVMvM4af2Xan9RNUDnvMlsEZQlBrB9UUJLM46SUkWIYQQYxp34FlZWcmLL7440rs4ER588MHjDoM9FEwekpaWdkxP63j3KYS4gOj06ta4FTrL0acuJtJqpD6sGBKbiOyqBJue53e2kmrXkWHoxV+zA31TNaURF+O76IsM9HSQ0fIGpsZPCfQ1cqM9jyZ7PtGaXvA0EJ7gIqptPWavjb7K9fSlXIQt92oiHVmYbdHkZC0lu3ErmlYL+tQSchKL+D/JxaDR4PEF8PgCmI16iM6DA59gNNvInzMLQg7OnZt7NxTcDCYbabGQF5JPz5Cbh7Z1cL/NwPRDsVxfPTg7IRigpn2A9n4XV8yI5arCg/PbNdqDhe3th9+fuvXMdVUxd8nX4ARBJ0BI/goKUmeDI370A36fOuEPjYX0JWNvrNWeWtAJau5tyLwjPkODarPfpzL3is++oS4yutcRHxpEM9SJJmUJmtZdaHUmzCYj/t5mzLnLcVWsJxBwURm5hJULl6GvqQNXP0lmL1c4y0iZvhysoaoXXadXJVMCXvUc3iE1L/oQjQYKbgLtcYaJ9zWCZxiis9V994Ba5h4CawShZgO3lUipFCGEOF3jDjznzZtHVVXVhAaeQggx6RY9DENt6CMz+f3dGlXLs2mnSsCz9xWqD8SyYvgDIkwQaN5CuM5Cbb+WDZ/UcNXwawy49tFujafLkkimI4qCklvhwCfg6cUcnYrDsp0/dabQF3MLIW01mNwfMa97G8TOgMzlaDQ6VU9Qo1dZWuNngsGCUafB6O4FHGpuYt5V0F0Hn/4vxBVAzpWgN40K2pZmOdi96V1SgEAwQy0M+FVwHZ4CEWms33SAT6q6uH1eCoWJdjXEsP5TVXrFdkSPTfpyVQLFcmwvotcfQKfRHK6NaI04nEH3SMEAODvAMM5hrsGgev/H2ueRzGGw/DG1/hmOshHnAL8Xqt4jMtSEtrcKf+oSAl21BC2haPvq8WFnvW0u0e4h/MEgfdnXc8mcFWAyQMTd4O4lIuBjmd+rhmDvfh1yr4SEWWp49iHTrx/1nfH4AhjtY8z1DPjVrWo1DLbD4kfUxY6wBHXT6Y7dRgghxLiNO/B86KGH+OY3v0lraysFBQUYDKOvHBYWFk5Y44QQYsKYQ9VtoB1cfSpZUHwA2itoaaqjJDGdBdZ8XuiMIjEynaWhjUQGkpiWHk6UayG/+jSZukAW+YlRZCxI5blV7xEImPnKyp9B7wGmJ0XwqKOT8O49dOiDhDjSwBIBBgsAbmsMG5p1FLi34xjuUSe6AE3bofI91aPpyILURTT5owgddhPWU8e+nRvYs+Etwmddx2UrLlPbuAcocJeSlZ9Fr+1gr6hWp8qc6FXSk1tnJxNtM7I40wH734G69RASq4YdH8kapXp1BjtGBaQeX4A/bzpAot3CFTOO6uE8mt4IJfepHtXxaNwKVR+Mnst5IhJ0nh80Wjz6UHThCWhdLWgIUGErIdtfhcGejksbQ7ZhGFPVe8Sa/RhNfTT1urHt+yPhucugfY8KKBd8DVz9KllW5BhlUmDkO3Ogc4jXS5u4bFocYRY9YRYjNtPBU6Cy11Xm65wrR2dGTixSF3+ON19UCCHEuIz71/TGG28E4J577hlZptFoCAaDp5VcSIiTcXt9lJeWjlpWXFyM2SxJRMQp8gxB1Yd4YgvZ/slbpPoaiI+0wYwbwOfGu+YPJMVZsOYsIS/chl9XQH9qIg1/eY7wlo0k3fqvDFRHkmk1cs/8BOyNa1nc8zodRIB5JcRMR6e3krD2v/D17qcn+Qv0JF5JdF42bP8TDLbitKbhKd9FWe4lLJ22XGXaNQG2GFXGoa0cItP5eH87z37STaQxj6SwPML0Afr90Wg6gxwMOwmaw3AVfJ7d+2twvvc7QlbcRliEAxxZvLGzidLGvext6mN+ZhRXzEhQ2XAT5+JKvxJ0BkaOnIYt0N+g6pvGz4S8q0feMp1WQ2yomQjrybN3Dnv8GHVqm3EJjVXZRMfobRXnMa2O/699Lh3Vfn4QXoH+wCai8m/HW92CJjyaGF8DvqE+fOHJuF3NVHd52VvxAhm6HnSdr/MR89DpDdw6fZiYsDDIWAbA+soOPqns4MvzYoluXadq0h6cy2k16ogPMwNBnt/SSG5cKFcVHLygEhKNJ6DBaE9RQ8KPJEGnEEJMmHH/otbW1k5GO4Q4rvL6Dl7qKqfCEwlAU0053wCWLDnOXDIhjrC9rpvhsneZ3/wn3FnX8E5vKjfbBoj3u6CjEnrr0eVfg6HbiXbDL5hvj4XOCvb13ENejIVpfTWY3c18b0UCH23cROPeeqK7V5FucZJitqig1hhCQG+hz6dHP/chNg7PY0GI43APnddJhLOOxSGN6JOtNGx7i/q9n5Jx1SPEt34CDdtgz8vQtIUdfQspbQxy5fRY/rmngznJdvzRV3JtTgIvbK5ndXkbVxbEUdft5poIPyZDJzaNe+T1VnUMUtM5SI/TS6/ToxamqPmSX/z1BqwmHX+85+D8ye4aGGiDvGsgfPQQRJ1WwzUzx85ue6TmnmEe+Ps2ChPDeeLagvF9OPYUdRMXnFnxFgb7AtT600iKNRJf/hc08YXgHiJoiSBZ249muINgMEiry4S7u5HBCDPmrkrKw65kY7OX7PRyrpiRNNJTX9vpZFdTH329RqI7y1lVPcy7wwM8eW0BMWFmbi5Oob5rgD2NvXQOONm8r4ZHs9rojyzga2ugpH4f/++a6VP8zgghxPlr3IFnaqpMrBdnX3RSBhkFc6e6GeIzaFNNN7UtUUxPWobdbOBrBRBRXQ0eO4P9XdC4By92ovs6aA93EO7VER4zndUNGnzmVK6eeSkYbYQ3rufSwTfRuc2QtQyD34tBb1ZlPIB9dU04G9qIca6lZ8hNy/79FN34FTUEtq8ZCr9ASGgchITT7tQygJWG/iDxffWAH6JnwGAbt2QGyc4pYHFWFO0DHqo6Bvjjl0pIjg7l/7ywkw01XSzKdpAaFUJM3jJsMxaqHlP3IJhsfC2zB3p/j3/5V7CmjQ4Eo0ONdA15+OGbe/h/18wARzZ4nSr4O1jbdLxMBi3xYRYiDyVCEuIUXJkTxqdbtmP1tdATmoTZkYNBZ0DbU4nfHU3QYMFlchAsuJVF3h62atMI8XUTG5XPd+dm8mkbXDL8KpRZoeReqF3H52NhxbQ5xIVbIOF+Xvh7GXtaOmkbdJFqVnOkazqH2N7Qw3R/GNGuZjzmPYRYY0iwm4kMUb373311N+Ut/Tx960wSI08xIZYQQoiTOu0xJGVlZdTX1+PxeEYtX7ly5Rk3SgghJsrs5DCmafWEer3QXEps9DBMv5ru0Eycq36Atr+J3uxlpLnfZachG+O0zzMvN4lFDT3EtqzGG5aCNjQRXXgLIbYIiC2g2piLrvZj0hyHT0qTsmeyv+NW7O3vsUjXQZjZoeaKaQ2qfuXOP4LfA7ZYZjkC9Du1RKTYIOpmsKdBzwHIWkFiaBx09+INRPGDa6fT5/KSHK3qXn7nqjyum5XAwuwY9aRdNerf4Z6DcyVvw+TpgcAwBIbA2QMd+9T8zfxreHB5Jv/60m68voPb9DdS29BEma+Oq+fbx/W+flzezqs7m3hgXjj/s9QHiRln/FmJC0hIJP7YQtobPVgMDpKHStFoNfiicukNy8Y/1E+bMZE0WxzGt7/PwtB4iC2AoQ4o/wM3xM+AmBKVXKh9H7SXodPqea0+juZ+F9+9ahrfW1lA56CbVLuBvevfZj/JXL+ogGfv0JMYYcEXKMBhWgZWB8/kHR5i6/X5cXn9+E+eQF8IIcQ4jDvwrKmp4frrr2f37t0jczuBkXqeMsdTCHGuKGvp44k39lEQb6NgeglR6WYo/RtEptNrSWG7tpi0lFkkBtux2+0UGjvZtv5ZNvjuZMmMTDyt/fxzTS07dkUyPy2Oy8JzCPN78H7wA2x6D8OeLCwAbWWE+zwUX3wDtGSxPCSKGk8ke4b9zIjOU0GlP6CSoIQnobPYiUiaqzLVWsJVYpTuWgiLx136T/r2bMXtmEHRitvAcTjjqz3EzMLsI+Y2738b0KqMnhHp0LwDtEbIuQKcXbDlNxCeqkqsBPxMS4rg7a8vPfjmvAFte3mmfwHv726jKHeQhIhT793xBYN4/AFMHbthqExl/xwrY6gQY+lvJnNoJwNhFoz+NvzhyWjbywiY7HS2t6Bz5BDWsB79opuh4DZwdqs52Vt/r0rqNG6BhNkw0Ap1G+CS70NEMmnvvU3McD8BppHisJHisEFHJeUb32RTcBqzstOYm+E4oiHHfud/fNOss/UuCCHEBWXcgefXv/510tPTWb16Nenp6WzevJmuri6++c1v8tRTT01GG4UQ4rQkhFtYMT2WhdYWIju2qmDMlgCmMDLKf09onoMQZzNWQwjUdBAaaGFhUE9/hZsd/ReR6+6h35ZJ1FANNR1GXFF2wixaQuOz0QacWEId0NMIO/6qsmImz4fEWWBPYeeWarz97eT730UXEgF5KyHqYOZNzyBs/xNN7R285F/EdUVJpFT8HqKyMc28DV9tA6Z9L9EVFULUnOuhZYcqeWIOh6EuOLAeUuaruZloICIVItJgy7Pgc+Mc6GWXN5nc+Bwi8i8FnXEk2+2IpDkQGk9xSDQJia5xBZ0AK/JjWZEfC+4c6M9XpWCEOBXNpVDzEVED+7Bbo9H2NKI12QjaYtCaI0kYHqbFaKMz8zrSNR51cabmI5VlNiSawa56NNYIQqo/ojt2PvsG46j4tIm7rs7m8iQfuHygOyLRVVQmjvm3keGKID0mdOpetxBCXODGHXhu3LiRDz/8EIfDgVarRavVsnjxYp588kkefvhhduzYMRntFEKIcbNbjXzzsjxwJ0LNgEriEz8Lqj+E6tVEO3IhcS6kLVS1JP1evO0H0BnC0bbvJWAaZGXgfcoGDeRevpCY+FsBSCy8GbzDsOFXUL8BEudAxdvQsEnNt4zM4uqaH+GPyEAX9EHVR6pH8FDgueNvUL8JrzaRltZ61kfHEmfPYvtABBF7tqDN/xydYflkZhaqBEC160BvVcHiYBu074XIVJWJ9hCNBmbfBcEgH326m/9c38+tISk8cLD+p8cXYNDlJfJQ+ZWDNQpvOl4nZTCohjWGRB9TxiQYDOIPBNHrtGAKhWg5mRfjoNWBKRR9SBTanlr84cloPEMEtXo0Q21YtQbSfFX4kxZA/Xpo2gGefgh6oeReNn3wJv6WWmampVFqKOGxlljihg1Mq+tmfsFNqq6s3wsEVQ1crZZpM0tYcoJ5yD5/QH2fhRBCTJpxB55+v5/QUHWS4XA4aG5uJjc3l9TUVCoqKia8gRcCl8vFli1bjlkuJUOEmCCmUMj7HPS34+qpY9htwGx2oO1vw1SUD7HT2dlr4u/b23mnKpOn5vazLKQCkyMHW+sWogsuRR8by0vbGphmbKeyfYiNPWE8HB+Hb/dH9HkMWOJmkDljEcRNB78XU3g8RCVC/rVQsQrSDg5x7axWJ8ahsXSl30WyQ8eK4mzau+w0rXsPQ3c1c+YawN4JWg04poHOBFEH51DGTlMlWKxRx7zM36xvIKzhYy5ztHPfvGu4eObhXsj1VZ2UNvRyx4JUHLZTSATUugvK34ZpK1VZiiOsr+6krLmfz5ekEGoeXcv51R2NbD3QzdcvySE6TH6/xBjiZkDcDBp6nUS638fg8xIMeHEZ7AQDXvwh8QQ7m7Abd9IRs5CANZPY5FDIvQbc/cR66vnYmMufG6dxX0YU/3a5mWFPgOIEs8oybbHD9r+AzwUlX6GmY5DXdjazLCea2akRxzSnpW+Yl7Y1sSzHQUGS/ay/HUIIcaEYd+A5Y8YMSktLSU9PZ968efzXf/0XRqOR3/zmN2RkSHKJ07FlyxZ+9vz7JGbkjSyTkiFCTDCNBuxJ7NlbQeeAllmGOCzR6ZgMZtjyO3LLP+AuErgoM4VcZxemnItU0pL0ZbRm3ESwa5CXtzcRa3wHz5CfdzuXUuT3M7O/Dw9WNg1nk5k4C5p3qmyxV/zo8HMXfUH96xmCunXg9+HNvYbmhi7m9W8jur4aLJEYooepi/kc3bYIIvsbgKCqIxiTO/q1hDgYy//P3n3HV1Xfjx9/3ZG7cpObvXcIJBBI2BtEUHDhqIh721q1rVJtta3602qto9TWUVpb9/arUq0KIoLsDWElgSSE7L3nzR2/Pw4mhARIQm5uCO/n43Ef5n7uGe9z5dx73+d8Pu9PXXMbjXYzHsZmbpwcDQZj+2vR/iYcTidehh5+7HuFQXAymEO6vqTX4u+pw6ObO0T1LTYqGqy0Ohw924845xTXNPPiqkxCdRNI9ahmvDMdg84LD0crDpUdZ3MVbQEJ2FQeZKTvwbOtCi8fNSZHG6g0jB4xnFZ1MnlHdOi0Kq6bEktLm52sNW8QTAWes39Fgc2fIBN4Av5mPSPDvAn3NXYbj06jJtBLh6dO5uwUQghX6vWn7B/+8AcaGxsBePLJJ7n00kuZOXMm/v7+fPTRR/0e4LkiPC6x03QhdrudtLS0TstkZWXhcJ57ZfbabHYqq6rJyzsKQGlpCa2tQW6OSgx6dUXgsClThRzdpBQnCR5FeMv/8Le14Bcciq45XylW0tqAR/leoqN9iSz/Bp2zmYZMFYa6bFq9Y/nNN/nMTgjkgQsS8LN6oq5q5K+N1YRb6yku98Lg6c3F08ZBVS4c+hbaGpVusBlf0RacQoEumlgz8MOz0NoIE27FozyTsLIt1AamUm2O5697tYz0v4zcCgO+Zd/gFxEKrfWQsRIiJ4KnX/fHaW1UChMFJXHlMA1etZsx5WRDxGiIP699sbhAM3GBvRjHaQ6EkZd1+1JKpC8pkV3vHAHcNDWG6yZGodX2sdtiVa7SPdI7tG/ri0FvU1YF6w6V8HTQGoY5cjG2ZqGxREBjFU6dGZtWj2ddNnatnmC7L1bPQAz+nsq/i/xtcHQTEyz5TAgwguclQCC1zW0caAvD6ROEqbKWFbWRjPYLZgZgMXowP7wNnBVA17HI/mY9iyfKfLJCCOFqvU4858+f3/73sGHDyMjIoKqqCl9f3/bKtuLMVVSUk5X1KSn2ve1thbs30xoxyY1RucfR0hqs9hwo9gGgMvcAGRk65s2b597AxOCW/pUyR+WMXymVL8sOQl0BoSMmg0oLOj1krFCK7niF0BYxHXXJfpymIFra9JSXlGHXhxLiHc1Uox+eejV6tZra/d8SXLadgKgkvCJHYXM4sNirCfX3hrISyN8K3qHY/EdgrSrk3QNqlh0p4R+LRzHZMwhqd8Ohb9lR702Rzzgmx0eC1ki9tQ2b3g+P1ha0DXVQ2wYttcp4VGstqLXgFaJUxj1e0S5lDKjag3h/A1hMYBkDASO6f19OpeoItNYpSbO1SRmv2gd9TjrtNtj/CXgGwfhb+rYNMehdnhqKytFKQuEWfKtsqLHgRHuseFYJeo9mHAZ/bJVHMJlUeDRbUduPJYaRk3DaWlE1lCljqjU6CEkm2NvArNlzsehAs3UZVxl8MIdfC3nblOJb6V+ASg1Tfu7egxdCiHNYn/uVZGVlkZ2dzaxZs/Dz82ufVkX0n2HhfswcE9v+/NN1+8l2YzwDwW63cbSslvV7j7S3FVbU4RWuIypYucNSmNt9dykhOok/XylGAhA/FyoOQ0U2NrUeTfZKnHMewxE8Eu3RTeATiU1roilqDhoV5BsT2VFpYq53Hqa6I0Tq8nl2jZNRPlYeC6kmyFGCzhaCOnIqicM8oTIL9n+mJLQA5mBy0ndxtCWGYu9kzgvLI7ekDB+rNyNiZ4HeG45sQeeViP/+N6ivq+ORGUsIGhFDUU0T5tyxoLFB3PnK+EpLhFK8SKPrepzBo0FjUKZk0epgwTNKe2MVHFoJERPBdOxuqd2m/FdzLM66IshaDXHnKVOhHN2otOm8lAQwfp5S0MjVcjeCzgxhKTDiEvCQc3wo02q1RFJGRe4+/MwtOE3+qGqOgsEHjP7Y1TpadBaKg+bg8B3OqBHDoLUZdrxOIx407V+JM/FSglKvB7/49u0GmLRKxVz/OIK9w6CtCrJXQ1gqDLuwS5EsIYQQA6vXiWdlZSXXXHMNa9asQaVScfjwYeLi4rjjjjvw9fXlL3/5iyviFOeI+qoKtreFYCrs6Fa4t95MUJPVjVGJs47TCTgpsPvz93fW8TPzOuKdhTDqSgoO7yFQH0jR/q18pr6AJf6l2GtL0Fek4/Dwp2D4zTSGzGBYxXtos9dQ7xNIqMcOJsddwCWNy/H2smDwSEFdlQ0qJw1qMw6bFu/6YghJpTT2Epq9xhJU8T/UNDF9znwMO79kf0MBHupWMEWCZwAT4kMgOoWmbz6kQRNMZfoWgixmwkKSIfWKjmOJm6WMNTUHQ+zszsfZ2qDMxxmc2HW6lOpcJVnVeUPMVKVtz/uAs+NuorUZ6ouV6V0AEuYr3YT1FvCJBmP33Wn7ld2mzMnoGagknn6xSndkMaTFGhqxeapoNYai14PKYMHhHQlNlXi01aEtLyI4eAJ+jZtoq7fgcWQt1OTh4R2FWuVA01wKxXVK9dqGUoidAbUFcHglREzouGCS/BPwClbupjbXQksdGLzdeuxCCHGu6nXi+cADD+Dh4UFeXh5JSUnt7YsXL2bJkiWSeIozZvEPIi5hePtz8469p1haiG5UH4V9n1BgG4ZnWQH68u9gzHlUH9lFUUERnqET0JVmERvWjKYmDwp20RowklJdDOuL1ZgKVpLq0cRu3Xi8vOPQV2fx55H7MOmSyD20iz9WzOa80TdxuSWCFTvzaazTcl3qddjKDrNqy17sxWZuGRWIz4iR0FwMYRMZYwlXEjyfSCg9qIzfLN2HPnYKBdoJ1B1YRUZQHIkhyR3HUZkDR9aB0U9JJG0t0KqCPe9C0Cj+fsDE2MosZvrFdH0PPP2VyretdR1tJ46bDIiH6fd3JK3mQCBQ+Tvl2v77/3EqGq0yDcyPd2EPrYSKQzD5bkkQhrAAVS1WayHo2sChg9p8HE4VDrUWp2ckWlMI3m3VNLZpee2ggSuCxxLjHU5GhY1nmxcQUGTgJ2N8mFW3k9X7svh+tzdPX5EMSZeC5bg5ggI7vkvY864yLdHE2wb+gIUQQvQ+8fz2229ZuXIlERGdB+gnJCRw9OjRfgtMCCH6zDsUYqYzpaEcs8MX3/rRUH4YjVNPtXcKuqb9GDXNTFanszvoKvSOKGwNVXjSQLxHLmmVKtTRXkxcdCf66iyMe7ZjKthI28irKNeE0qbzpMWgJGjjfJrwPfR3PDaa0cXMZlKsHz6NX8MBoDwRbFbs9eUUt6jRegURMnwitU4TzY0QEuaPxjuE2CMHKPH1xuBs4bv9BcSH+BCra4DCXRzIOcJeSxyLZv4MrckbGsqhphAsUbRoAtgVej0zY7sZz2mJhJGXgyVKucuj84SEC7oud+KdUncwHXdnNTBR6Yqs83RfPML14s9Ht+9THKUHcAYMx2nyx+kVjLahhLbmClA5ofoozeGzSFAV4l+wHuw1eJjGcaklizB1NSrV5RAwnPV5OnIqGrE7nWhCRnfZ1dqMMjZkl3Nf/Gh8zPLvSggh3KXXFSAaGxsxmboWnKiqqkKv78HccEII4WpaPYRPgJo8kiN88Jz+U2hrwmyrZ6K5Ei/fQDwcTVCezoacah4rnsbOiOvRj5iHyWyhLnAsWaZUrFX5bMsuRd1UCRETyfKZzk79ZG52/Bev4g0AxHmBr6oZp95CsT6W4YljCAqJUsaV6rwhZhYtOh+ymr3Y5DEVoqfxTkEIz1fNJCvgfEi8mJAxF5A6Ih5z3WH+b2sOX+zOU+78laez2/sC1pSZaFEf+9y1NipFfwxe/OaiJH6VWA3F3fQKUKuVIkGONtj6D8jdMID/A85AUCIMOx/UGndHIlzJ5Icz5QasIROwVebT5hkC9jYcbW04nFBjiqcidCbftY5msm8DXlonDL+EpEX/j5+EVjBbe5CZjt2w6SUejj7MspvGo9F0/28mr6qRzKIGynxTB2bMshBCiG71+o7nzJkzefvtt/njH/8IgEqlwuFw8NxzzzFnzpx+D1AIIfpEZ4JJd4JGr3RrXfA86tpcgpw2ntlnJlrlR4kmnqQEfxYVfEBY6VFs+S0EOuxE+6bir4umrUCLwTBKGSPWWMEwLxsN5ipiGtMIqrZhty1GEzgcwseRVmbD/tXTePob8I4aDcPng2cAdrWO9dZk6kOszLWUQEstM2PNjKSVCK9j1/7CUyF4JH7WJhZmNTHaowiKCyFkDFcnTOEymwPzj/Nv+sXAhNvAFKCMjzy6RZnXM3TMSd4Hs1Lh1kumJxGDy592OrjQEUBSyBgMpXtQeehp841DW5yGWWvA3lzNXH8NzQcOUutpwhI3C9QadLOXQGEa5G+GuNkYQkdiMJ78zv31k6K5ZEwo/mbDAB6dEEKIE/U68XzuueeYO3cuO3bswGq18pvf/IYDBw5QVVXFxo0bXRGjEEL0jd6LnLJ6Wja8Rl2LDf/zf0F8kDfBaf8lvGYXMUkhTLamofFoBjxx6rzR1ObTYnOS7RHPyJY05oyOAdvPofIQHsW7mWiuxGo204yD7I9/x/BgM4SmoLM1Ud9QTYOvN/qAJPQmP9DqaWuzk1fVRIKPGr/CNVATQIq1GaiA+hgwjVJi1epQN5RycaI/X+9rolY3huTY6Rh0Wgwn/qb2Cun4e9xNHeMju6Mzwagr+vNdFeKM2drsLHJ8Q0zjftTqQBwRE1E3lKC11tLsm4DByx+9VoVH2Q6q/CfTOO4WChwRlH+7nGmmQnQmC0RMUgoJmU5dBEurVUvSKYQQg0CvE8/k5GQOHTrEyy+/jJeXFw0NDVx11VXce++9hIbKFXUhxCDRUguHvuPA/hI2V0fQ2Gpj2ncfETg6jGSyCYyOxdNYA7XlFLVqocmJX1s+du9wdnmdz8a0Nm4LNZGqMylFeKqzYesyCElBFzUew6GtBBiLIc8Jk37KqJEh7Cu4iPcPlHC+OZhxrfWgUmPw0HPz1Bg8NGoomAtlB2gpP0yz2hvftjZI/5Jcn6lsPpjNJa0rMcRMIHN/Pflmb5JP8YPa4XCiVquUIkJCnGXe23KEaWoPNBoV1BXi4RWOo7EMVWstNk0AeUHTsLQdJmD2tcRGTSfn0D4Oprdiz9pDS2AlutgJOOLnotacYsTQvk+Vgl7D53e+WCOEEMIt+jSPp8Vi4fe//31/xyKEEP3nwH+heDfjA2LI8h+Po7aJCcY1WIqPMsyoxaOhlMYjuRSqjezyX0C+TscEdSZxY2Yy3O5DbcnXlGbt5kPLLMzly7kguAF97HmQsggMvgSFfA5tTRA9vf1Hrb2xiuqGZhx1JWRteZdhY2dD8CgMHiZQe0HGl9grDpNjSKGwrJbUohwsed9S71nMuuIRTIwIZlhzOTf553Ko2ZvffBzKkwuTMRg6f1RnltTz3cFSFqaGEuknxVLE2cevrZDCJg8i9b54OKuwNtegMgXjCBmNurmV+qJMWlTgDBjP9v151G78nFHJY9HNuAjvEaOoc+h48tO9NLS08fjCZEJ9js39Wl+szKdrDgSNB1Rmw653Yeo9yt1/IYQQbtOnxLOlpYW9e/dSVlaGw+Ho9NrChQv7JTAhhDgjoSmAE01BDkHaQlL9bWwpDyLXL5FQ+yEia3fibTLjqEon2jKKifGx/PvIdC6tbmZ8yxqsQWYsGh2R1d+htpaiLS4D/3iy8wtYX9XI4rjRGDOWQ2MxkACZK0nc/TE/N8WzMmssxcVBXDHCh+Q974E5DIISKQ2YTG69P4aAOIIbN+JjNlHcDNbC77luxkTivOOhaDcB465i+1efYG5Yx9HqWBKCvVCrO+7s6LUqfDw98ND2uj6cEIPC3IljsLWsw1Gswqk1om6pRtXaiKapBK0pgMi2VrK9J9Kw5q/ENDfzb/MCLuQg/kX/hYREtBo1ZXWtpBfXkVFc15F4pn2sVESedCeMXKiMb26uBA+jew9YCCFE7xPPFStWcPPNN1NRUdHlNZVKhd1u75fAhDgZu81GVlYW69ev79Q+ceJEDAYZxyOOCUsBrxCaWjfQWKnHM+2fpOi02DSplBXnoI+YQnh9GiqjF8n2A5SnH0DVdD7eHIRgPybNuwb22KAiHWbeBA4H+0oaWZuvZ8OREiZFDWdk6DiwtoDDAfXFGIxGIoxtTPHS8D/DhUSOiIdKDRRshe//iC7lLvKirmRWjJHgABUEDeew31zKqSRuz7uoL78HoqeCRsfkEZHEaQJotjn42Tu7WDwxgnkjlTurMQFmYgLMbn6Dheg7k5cvDfYmdA35tIRMRN9cglqjxm6KpLmpmTqtH0d0CUSbC6iw1WP0icPisR88vMlrUJNWWMKzV4/hYFEtc5KCOzYcfx5ojhsUHXTcVENVuWDyk/lhhRDCTXqdeP7iF79g0aJFPPbYYwQHB59+BSH6WVVFGbmV3ti357e3FeZk8ABK1WUh2nkFs1U7gRZTK61jbyHZfgCTly9l9Q20VOyn1KHGPvqnhGe8QaMxkWBvPfFNe8E5E7yDweTL/rYgilevIs5Qy9dlkew1+/LQ/OGMDNLB18uVuyux02H01ZB8JajUjNKZGaVSQfYPULoPQsaCrQ3f+Mks8goEexukZ0BLNT5JF/Huf3/guhArGH3a56/0m3UXfsDBolosRi16ubsphhh7TRFODxP21gZUTRWAncaGWip0kXhay5ltKcMy5ze89PYOivNqybvqNuJCLDz36SF+OFTOC9eMYf6osM4bDU3pfmcN5ZD2AYSMhqRLXX5sQgghuup14llaWsqSJUsk6RRu5RMSRdzoCe4OQwx2lTlc5J1PY+wowvIq4chhKGsmKCyGjFo4GLSQxOLV2D08CdXUc53zO9STf0aWJhaPtW8RHT+KvDJfggvewsNpJDFiLH7BQUyI8Ye2ZoiaQr7dj8CSTAwGT6jKUqZuGbMYHHZoLAUPA0SOg7jpSky2Vr7PKIViHWPGJhBoMeAZHE11/AQw+VG16W0OVjmJnnY1kX6ejAyz8MI1qW59G4XoV631kLWWRpsGvTkYc00GjsARONChcqoJbGukMXIygRMXo9VpuWBkCBuzKyirbSSu5Gtujo7H7BHAZM0RaDKyp8LJJzsKWDwpijERPt3v0+QHceeBT+RAHqkQQojj9PoS+tVXX83atWv7NYhXXnmFmJgYDAYDkydPZtu2badc/pNPPiExMRGDwcDo0aP5+uuvO73e0NDAfffdR0REBEajkZEjR7Js2bJ+jVkIcRYo3oMubyMh1EHJXghKBnsLZSV5FFq9+HB3MbbGKjTNFZg9vfFuLaF56+uUpn1H2dEMiisqmDbrQoZf9Sh+17zE5dfcyl0jbbDhZTiymXWqsdyxzsSe7z/BceQHsDZDeSbkrIXqPKWwid+wjvFl9aW0rf8b5tzvqCvMxNpYQ5S/mZevn8DiSdHKMk47HionapXKbW+bEC5Vk0fp4W00e4Wjaa0Hcxjq6lxsGg201KBrLKTS4YX1yEbI38bMBH/m6A+z/+ABrHVlTGpax59Tq/ApXgcle6lttpNX1Ux9c9vJ96nWKN3YLREDd5xCCCE66fUdz5dffplFixaxfv16Ro8ejYeHR6fXf/nLX/Zqex999BFLlixh2bJlTJ48mRdffJH58+eTmZlJUFBQl+U3bdrEddddxzPPPMOll17K+++/zxVXXMGuXbtITk4GYMmSJXz//fe8++67xMTE8O2333LPPfcQFhYmxY+EOFfUFlLcpOarilgu//pJAq2FMGEsLPw767/6H5WHd3DRuEmUlRkZXlcM7ARzEM7mBtDq0M++j08O1xHqqGCRIw0K18H0X0LGN7D7bfAMZqJvHNNib2WXdgGB1WlYi7JRqTxJbCiFmJnKNA6NVbDmTxAzC0JHU4w/dSovUs//CWFJkzrHrFLhN/02JrvlDRNigAQmka4bRUT5KtRqNar6fPAMQttShyN0JOqKDALr09FV+NLkYeL7Mh3xFRuJooWy4VcRoa6C2nww+kL4eGbrzUyM9cWk61O9RCGEEAOk15/SH3zwAd9++y0Gg4G1a9eiOu6qvEql6nXiuXTpUu666y5uu+02AJYtW8ZXX33F66+/zsMPP9xl+b/97W8sWLCAhx56CIA//vGPrFq1ipdffrn9ruamTZu45ZZbOO+88wD46U9/yj//+U+2bdt21iSedlsbWYWVrN97pL2tsKIOe7jjFGsJIQA49C0c/hbvslyimiKpNJkJDE6C0LHgHcaU1NEUDh/HpPETWPlNLc2e5dgCh1PZaCXQupVJATY0UWHsLrJyqKQee+knqJoq+U/reYz2mcmUVCdUHsaqMjMz2heVyhfsbWQezsbcXELU2BF8sCmP8TGxpFZthcojSuJpsOAz7ioSv/sruqbhoD91gaCaRisWjzZURWkQkixFUcTQoFYzZeJ0bA1roagUp08keJhQNZRiKGqgWmXmdetMaiojGOUZzPgRAWg95uAs2K4UDkq9EfZ/pmzr2DkkSacQQgx+vf6k/v3vf88TTzzBww8/3Km8f19YrVZ27tzJI4880t6mVquZN28emzdv7nadzZs3s2TJkk5t8+fPZ/ny5e3Pp02bxhdffMHtt99OWFgYa9eu5dChQ/z1r3/tdputra20tra2P6+rqzuDo+ofVcX55Fb7YC/0a2/bW28mqMnqxqiEGHh9Oj89DBA8Cs+E+ezbWMHn2mH8Y+FE5bX8nYRnvEN4ax1oFzJLn8fuUUvYk12EV9VeLvSOJVhlp6mhmlRNNlFhkTj9F1JXUcTKvcVURFuYcvkvYP8ntG39CF+P7xljqkIbMw3TzPmYMj6jrL6Fbw+2YLU7SJ18HaRcpxQOAry9fdhpmcR3GQ6ujaphdHdj0mryOdpq5rO95VwaXElC5Q/KnISRE8/8DRWiH/Xp/LTbMNQe4qj/OGxWDyLq9qP18kCl8UDtFYbBO4qSIl8qKmo5WOngpmlxqIuqKPfzZWW5J7MydxKVfJULj0oIIYQr9DrxtFqtLF68+IyTToCKigrsdnuXQkXBwcFkZGR0u05JSUm3y5eUlLQ/f+mll/jpT39KREQEWq0WtVrNa6+9xqxZs7rd5jPPPMMTTzxxhkfT/3wCQ4hLGN7+3LxjrxujGTwcDieN9XXk5R1tbystLaG1tWvXbHH269P5GTtLedSX8uspO8DPBPnbIGQMR7YuJ6y2AL29gTatkS9z7DSWbGOyTxNGVRa76oMY03YEsh7EVlXPfs85vGIbxXNX/YSnjd8QbNsFh2qgMA2/mFS84hLRtlSCOYTQwBgIX4IFeMS7SpnyxFYNB5cr8QQlgUqFIWYyPvZKQryPm/7H6QSVSpnyIe0DAkKnMDxkBJ7hIRBiAb/40x93eQZkrlSq6/pE9e49E6IP+nJ+NjfWcmjrWgJaj+LpbAUcWNHRHDwFv+z/YqjO4TybFa1Rx9G4a5XfGyMvRV3fxLg9qwjIrYDYJNCZTr+zg/+F5joYd6NyfgkhhHCbXmePt9xyCx999JErYuk3L730Elu2bOGLL75g586d/OUvf+Hee+/lu+++63b5Rx55hNra2vZHfn5+t8uJwaGhxUpbTTEU721/VObuP+nFCnF2O6Pzs7ZAKSp08L+w4e+w9d/U19dTpQ0ED0/s1kbqzLEsyH2WhLLvqG1uJb/OicPhQO3hQU3wRPY4E5iuy8Yn82NGjEjCJ3YC+U5fvitw8EO5AX3sVCXRCxzeadepUX74mHSAA2wtUJkF+z+HqiNMHRbIQ/MTCfwx8WyshE1/U5Jjr2CInIRnWCKXjA4jzM8bgkaCVn/641V5gIcJ1NLtUAyMvpyf/zvUyKrGGHS0YalKQ2sOQNNcgao6T7nAotIw2tJAU8BofjH32HnlFYp/WDwjZyzENG5Rz5JOUM4bD5nfWQghBoNe/zqx2+0899xzrFy5kjFjxnQpLrR06dIebysgIACNRkNpaWmn9tLSUkJCQrpdJyQk5JTLNzc387vf/Y7PP/+cSy65BIAxY8awZ88eXnjhBebNm9dlm3q9Hr2+Bz/qxKBhNngQFezb/rww1+jGaIQrndH5GTZWqWKZvQ6y10DeBsI9TOjtjeATjaGlguvmXk6TehaEpZAaMwO/kgIidXUQNQl/rwgiKxrwr1Tzw4b11GLg1vMuxFpaxyHVbhIdtcqdyhM5HLD3Q6X4ScwMCE6BrJWg1imJpV9s5+XVatD7HPuRbKTQfyoaJ4Qc3QRGPwhK7NnxBsQrDyEGSF/Oz3mJIXxXl4y2ZBvOkDFY21qxGwLw0TTjbKjC6RlErLaKhOmJvLkph4PZR7l7djw2hwMfvxCCAsNOv5MfDV/QyyMSQgjhKr1OPPft28fYsWMB2L9/f6fXVL3sxqLT6Rg/fjyrV6/miiuuAMDhcLB69Wruu+++bteZOnUqq1ev5v77729vW7VqFVOnTgWgra2Ntra2Ll2BNRoNDocU5hHinFOwnYbig2R4zsRgCSHZUAlNFdBcBRXZlMSZuSnnSlLafPhHVA0j/PVQXAjZ36ObcCvDQ7zZ0pjCsxVOpvq0gb2NeG8n99z181Pv19YKDZXKXc7GMhh+EQQMB3M3XcKNvjDh1vanX6YV46+3s8i6Ueky29PEU4izgK9Zx6LzJ0OBBvvWf2ItO0qe90RaqotI8vWirakBq11FQFsLxWUNxB/9BN1WT3YVWCkbeRv3zE/t2Ji9DVoboLkG/GNPtkshhBCDQK8TzzVr1vRrAEuWLOGWW25hwoQJTJo0iRdffJHGxsb2Krc333wz4eHhPPPMMwD86le/Yvbs2fzlL3/hkksu4cMPP2THjh3861//AsDb25vZs2fz0EMPYTQaiY6O5ocffuDtt9/u1d1YIcQQULKflgNfgbWFPZXxtKmD8G/IpFAVxhh1K7qICYRkvsuVkZFYfUM5uG8jEU2ZeA+bBq11UJYBQYlMiQ/gjVsnEOlvhsPfQek+mHRXe8GgLtRq5bX0/4F3GMTPhbjux5h3Z05iEB5qFZhuBq3czRdDk83upLG6Ch124loO0qZtoynhBuxlhzGGJNF68CvuSpxLc/hFhJhUhHo1Eh53XG+oqlzY94nSvby1Dqb8/OTnpBBCCLdz+0CgxYsXU15ezmOPPUZJSQmpqamsWLGivYBQXl5ep7uX06ZN4/333+cPf/gDv/vd70hISGD58uXtc3gCfPjhhzzyyCPccMMNVFVVER0dzdNPP83dd9894McnhHATaxN129+jtSQbqyGQhYEl6EeMoyqtiRwPCzGp17C71oTmyJfcff4cHOZgWj/9AQ9PM5h8ob4EGkrb7zYmhftAeSYUbgW/EcqP3ZPuuxFMAUrCqdZC9LRehT4ixOvYX6eebkWIs5kq40vsek/sjSUYVHYM1nIo3gK2RjBP5quDfuwoa+SRxZeg1aqZPuqEDXgYwRysjK9W68BgcctxCCGE6Bm3J54A991330m71q5du7ZL26JFi1i0aNFJtxcSEsIbb7zRX+EJIc5GOhPagDiO1LRR7pPCLOtmdBU7MAf64uXnycelYThxku6xkGSfBIKMQMxo8AxUilbFzoaoKR3ba6oGVGAKhLiZoNWdfN/52yFvM4y5Vrr/CXESGks4xupCrAYfWhwetOlDaG5wEGaxQEUWTQmXEtpoRXuyMohewTD+5gGNWQghRN8NisRTCCFcwTTtp6RMddBWcQSP3Yc53KTHZlVjq89EX1fOlDAP7k4OQFNthaJqGHsjlO6Hgp3gHap0mQXlTuf+zyDxYph6T6d9NDRb+XJvMXOTggjyPtYtNmQMaA3gE9H7oNuaIet7ZeoV/7gzfAeEGIQcDkj7EHyjMXqY8MhcAXGzKcrYhW9DPrXNKo42eDEnLo2AmRcrVaF7WsVWCCHEoCWJ5yDQ2tpKaWkJWkvHvJR19fX4GM98rlQhzmkqFag0HKyw4mtK4u0SXzyayhnup8KkqSHaxwNNTQ5Y66GuGPZ+DE4b2O3U29V8ve0oC0aHYjH6Q+AI8AxSqtg2lCpd/FQq/ptWxKtrsympa+aBC44VAfL0A88pp47tZFpqoWSf8kNbEk8xVDkdgIMaYyjNHuE01TtRo0bbUo2toYxWWwhp2yuYGxoP6V9A0iUQMtrdUQshhDgDkngOAhkZGVTm7ifcq2NahqbKIkxB3VS/FEL0mMPhZOum77Ed/IrmEXP5WXQRxf5TOHr4ICM8aygLu5Q//JDP9Fgzi0bPgLQPlPGd5mC+OFjPq5tL0TQUcXWiCZKvAsBemEbNni/xHHMZhsgU5iYFU1rfwmVjejHFw6l4hcCkn4LBu3+2J8Rgo1ZD3Hmw7jlU+jA01dloGyrZSwKaiBnoaeOgPZILUuPB0wC+0eQ16bE0tWExeZx280IIIQYnSTwHCX8vY6d5KU0G+XIV4kxtyang3T11jHX6MVuvJay5nIgQPaOdBnQ7t1JeOpywNiuxRw6APg6iJinz/qlUzKxooLhFw1zdZtiXA1oTBCVQ3KyhtTCTOp9EYiNTCLEYWXJBolLt9mgOjL355BPW528DjR7CUk4Zt9Pk2+vpqYQ4q9haoLEcb/9EWs0mfCsPEqjJYVf5RN6rGoFPlInE2CgAyuKv5NMteYxqruTCUUpVW6fT2fUcaa6B3e9C+HiInjrABySEEOJ0pC+nEGLIGhZoxjswmn/VTuaZgxbeUl3BfmsQBo0KdeAI6lthUWQ9E8aOA6cdHHZQqXhj4xF25NXw4PwkbCoNDUd34zjwGdisBIZGoEs4j8CI+M470+qVSreqk3ysOp1KwaGi3aeMObu8gVfXZHO0srGf3gUhBqGAYXD1G9i9gimubcHmFY6HWoPNFMh8zS7G6Ev523eHqG9pI8BTz/mJgYyN9IG2Zo7k5vCPtdnkV51wjqjUoDOD5hSFv4QQQriN3PEUQgxZQRYjS+ZGElO3hRbfZIwmE77N+VC8E0LH8cm2RqJq9xE74SFlPKVKhdXmYGtOJYHeBq4aF0Gabhz6ECexfnE4aq1E+fsQOeeOrjuLnQnMPHkwKhWk3gTqU9/J9FCrsJi06E5aylOIIaD0ADRVoY2eTOH27VQ2VzNizr1szfDiaNsOrJU+NJVXsnBMGPUeNrz1WgK9DZD+Fb45O4nwuxKt5oRzxOANE251y+EIIYQ4PUk8hRBDWhC13D2sFuJ0EB0NrQ3gmAZ6b0bHVFKnu0uZ/2/TSxA9HV3EeP7fZaPQaTUATBmTROPweH77f/vw2bOTF8dXQthY8OvDNCmefqddJMrfkxv9PXu/bSHOItbCvThKDmAw+zHjomuVytERyVzvq2VNcybDEn2JiIwlKsDMXW/voLS2hY9+NhVjUBI+HkYWxiaBRn7CCCHE2UQ+tYUQQ1vAMBh3s1KFFkBvhuEXws63uNSzAsZNPq6LnjK2OsTH2L66Wa/lle+zyK1q5JaRWig/pBQA6kviKYQA4KnDsQQ2tnJnUhvGtiaoyoGwFCJ1Bm4OOgIGHwhQqtiOi7RQE2DCqNMoPROk2rMQQpyVJPEUQ4Ld4SQrK4v169d3ap84cSIGw0kKvYhzhyW8a9uIi6HiEGx/Tfl74u0nXT3c18jIUG/mTkkEUwrovZQXmmuUsZsm35OuK4ToytfXlzz1WDTjk0FlBWMABA5XzidLBJRnQNxs0Jv5+ZwEd4crhBCiH0jiKYaEmsYWfArXw66m9ra07BLgIWbOPMW4O3HuMgcqdzprjkJFFlQfUSradlOR9sYp0dw4JbrrNvZ/Cm3NMO2+AQhYiKHjgQtHKH9Ym+G7J5SEc9aDynkZPhbqCkErFw2FEGIokcRTDBnRQRZmjpHuj6KrJquNhhYbQa15SvXaoCTlBU9/UGshdx2YgyB29smnQulO2Hhwtrkm6J4oS4eiPZB4sTJOVYiziNXmoO5oGgFlByEwCYw+yguhKcrjR631ULIfQseA7tj457JMKNoJIy4Co/Q4EEKIs4EknkKIIW37kQp+yCgls7SRl3zex6A3wEV/7lggehqN5jjUQQkYTUryVtNk5ckvDzImwsKt009xMSM81bXBn05zDdQWQFuLJJ7irPPe1lz25th4LGgq25qCyVhzhMUTw6ioayM58rhksjwTctaCztSRkLbWQG0h2FrdEboQQog+kMRTDFmtbTYy0tK6tMu4z3PHpzvzeGz5QabE+TEu0oJGHw+ePp2WaTGF8ubOFiJqG7h8bEfyptOq0Zxm6pOeePG7TLz0Htwx0wUFUaKmQPg4ZQ5RIc4yjS02aqxqnEZfaqps7G+oYWduJQeK63nr1okdyWfIGPAwQsDwjpUjJ0NISu96KAghhHArSTzFkJWRV05V9Ydg39veJuM+zy3RviaGh5oZFuTJvfNGACPaX1u5v5j1hyv42XlxpERa8PPsmHTex6Tjzz8Zc8b7dzgc5Fc1ddp2v1KpJOkUZ63KJitxQd5YZv2MktWH8SitI8TbgNXuJMDbo2NBrQ6CR3XdgCSdQghxVpHE08VaWlrYvn17pza54zZwkiL9ZdznOWyCuZLPZxTDiBQo3guVWUoFWw8D1U1WSmpbqG9qo6yutWty2FwDDeUQ2PeKmmq1mqevGI1arT79wkKcQxwOB02tdsI86jj8xQvcmHwextljMemO/Swp2Qf5h5UxnB7GU29MCCHEWUESTxfbvn07f/1oFeFxiQAU5mTwAMgdNyEGQlM5VOdC/haoK4WGUrC1QGs9144P54rUcFraHKw9VEGozwk/bo9uVJLVcbeCJbTPIRh08jErxIl+vChTcGg3+m9XYlKVYAwIAV2kskB9KVQdUcZwSuIphBBDgvwiGgDhcYnEjZ7g7jCGNLvdxtGyWtbvPdLellVYiW+8nxujEm4XPR2CkmH7v8ErBKb8HJqrYdfbED0dQ9wsDDq4c2YcHhqV8iO3qRK8w5SKtc3VsPdDGHezUgFXCNFvtFo1MSPHY6u9Gm3a+7D9dbjgceXF+PMheppSUEgIIcSQIImnGBLqqyrY3haCqbAj0dxU7YNfcY37ghLup1KByQfG3aiMhfzxR6xPFNhbYN+nYG9Bl3qD0p67AfK3KYmmJVwpalK0BzTyUSlEv2qugbytULofbdAo5ZxsqQGbFTQeoFZL0imEEEOM/JoSQ4bFP4i4hI6qhwePlgF1nZaRSrfnKK8Q5b8VWeBoU4qSFO6C1gZQawBlrk+DfwJqAM8AZfnQMcqjMgf2vA+Jlyg/kIUQZ6b0ABRsU5JM/1iapv8GY+lOVN//CayNMPMBsIS5O0ohhBD9SBJPcU6RSrfnuJw1YG2CsTcpUzGU7getjppGK+9sOUpKhA+zRsztup7TAQ4bOJ0DH7MQQ1HYWDD6QGAiRXWtfJJWwKWWMOJtB6GlEqqPSuIphBBDjCSeYsg62bjPifF+Uun2XOB0QuY3yo/b6GlKW+Il4LBDYzk0lkHSQlCrMbTZiQ3wJND7JFOTBAyDgF8MWOhCDHk6U/sUKZ56Dy6xrca/yQnz/wQVh8B/mJsDFEII0d8k8exH3U2dkpaWht3eMSm93W4n7YSunllZWTjkTkq/627c54YKL+objhIV3nElPS27mMRRre4IUbiSww7VOdCmdLNtamrjX1vrWTAqhMTKLVCVq9x10ZsxeGi4NEXurggxUD7edhStVs1V4yKxGD2wWDOhsR4093Q/Z6cQQoizniSe/Wj79u2kffI8KfEh7W1Z6w5QMewn/DgTYEVFOVlZn5JyXFfPwt2baY2YNMDRnhtOHPe5acdetjd1Tkb355Tzk4wM5s2b544QhatotDDhzvYxnO9sO8qra7M5XFrHK4sWQFsT6M29325dEaAC775PsSLEue4f63LQqdVcNUwDqGDOI+CQC7BCCDGUSeLZz1LiQzp140zLLqbouNfttjbgxC9XJ3anYyDCE3RNRvNLqvjhhx86LXPjjTfi4+MzwJGJfufRUTDq0jFhZJbWc/GoYNB7KY++2P8pqD1gyt39FKQQ554FySEYtSo48Dmo1MpUR0IIIYY0STwHWFVxPrnVPtiPu+O2t95MUJPVjVGd2/ILCqhrbEa1Jx2A7BxlTOh9993nzrBEPwv3M7F08dgz39CweWBrA7tNplkRoo9+uyBJ+aPMqUx7dDybVSnmJdOpCCHEkCK/mvpRa2srGdnFndoy88qp8K8kL+8oAHX19fgEBHe642besRfhXiGhYUydPN7dYYizgSUStv4L6vIg8VJ3RyPE2S0oqWvbwf9CfYnSq0DjMfAxCSGEcAlJPPtRRkYGn+ZoyTR03M38Ng9MLYehWGlrqizCFBTkrhCFEGdKq4fABPCOcHckQgxNvtFg8AK1/EQRQoihRO3uAABeeeUVYmJiMBgMTJ48mW3btp1y+U8++YTExEQMBgOjR4/m66+/7rJMeno6CxcuxGKx4OnpycSJE8nLy3PVIbQLDAkjLmF4+8Ps44fZ4EFUsC9Rwb6YDHL1VoizUtb3sP0/ypyeSZdBWKq7IxJiaKgthE0vQZky3IHISTB8QdcuuEIIIc5qbk88P/roI5YsWcLjjz/Orl27SElJYf78+ZSVlXW7/KZNm7juuuu444472L17N1dccQVXXHEF+/fvb18mOzubGTNmkJiYyNq1a9m7dy+PPvooBoOh220KIcRpqdXH7sDIj2Eh+pVKrRTsUrn9J4kQQggXcns/lqVLl3LXXXdx2223AbBs2TK++uorXn/9dR5++OEuy//tb39jwYIFPPTQQwD88Y9/ZNWqVbz88sssW7YMgN///vdcfPHFPPfcc+3rxcfHD8DRiKHAam3rUuUWula67W7eVoCJEye2X+ToyTIDYbDEcVaLO8/dEQgxNHmHSpVoIYQ4B7g18bRarezcuZNHHnmkvU2tVjNv3jw2b97c7TqbN29myZIlndrmz5/P8uXLAXA4HHz11Vf85je/Yf78+ezevZvY2FgeeeQRrrjiim632draSmtra/vzurq6MzswcVY7scotdF/pdvv27fz1o1WExyW2txXmZPAAMHPmzB4vMxAGSxx9IeenEIOXnJ9CCCF6yq2JZ0VFBXa7neDg4E7twcHBZGRkdLtOSUlJt8uXlJQAUFZWRkNDA3/+85956qmnePbZZ1mxYgVXXXUVa9asYfbs2V22+cwzz/DEE0/0Kvbu7iBlZWXhcMoE2ENBT6rctra2ovX0QWsJbG/TepZ0+hEGEB6XSNzoCS6JszcGSxy91ZfzUwgxMOT8FEII0VNDbkCFw+EA4PLLL+eBBx4gNTWVhx9+mEsvvbS9K+6JHnnkEWpra9sf+fn5p93P9u3bSfvkedj1TvujcPdqWltaT7uuGBoyMjKozN0PxXvbH5W5+0960UT0TV/OTyHEwJDzUwghRE+59Y5nQEAAGo2G0tLSTu2lpaWEhIR0u05ISMgplw8ICECr1TJy5MhOyyQlJbFhw4Zut6nX69Hr9b2OPyU+hJljYtuff7puP9m93oo4m/l7GYkK9m1/npflQVZWFuvXrwcgLS0Nu93SaR1bm5W0tLQu25Lxlt3r6/kphHA9OT+FEEL0lFsTT51Ox/jx41m9enX7+EuHw8Hq1as7jaU73tSpU1m9ejX3339/e9uqVauYOnVq+zYnTpxIZmZmp/UOHTpEdHS0S45DiB9VVZSRW+mNfbty1T9tww5CEsaQcNwyZfk5ZFRXkWntmO/1bBlvKYQQQgghRF+4vartkiVLuOWWW5gwYQKTJk3ixRdfpLGxsb3K7c0330x4eDjPPPMMAL/61a+YPXs2f/nLX7jkkkv48MMP2bFjB//617/at/nQQw+xePFiZs2axZw5c1ixYgVffvkla9eudcchiiGgu0q3P/zwA3ZzQKc2h8OJxrtj3KdKZ6KiopK8vKPty1RUVKDx9D3t2FCpRCuEEEIIIYYKtyeeixcvpry8nMcee4ySkhJSU1NZsWJFewGhvLw81OqOoajTpk3j/fff5w9/+AO/+93vSEhIYPny5SQnJ7cvc+WVV7Js2TKeeeYZfvnLXzJixAg+/fRTZsyYMeDHJ4aG7irdbks/QtQwXaflGlqsOBzFyphPoCzvMAZvXyjuuLvZXVtl7gEyMnTMmzevve3HccQp8R3dztOyS4CH5M6oEEIIIYQ4q7g98QRlioqTda3t7i7lokWLWLRo0Sm3efvtt3P77bf3KR7nscq0pyoL39jYyFdr9rIzs6C9bffhIqq9PdmwuWO8S3lZKbqGZjZs3tHt8zNpG6zbGrKxmryxOzqqFjtxUlxU1M1yzeTlKKN9G+uqaLPZ2p+frK26rJjvvvuOlpaW9racnBw0RWXYbLb2tuyiKg5+8AFbt26lN3Jycthf6aSgsOPfa2XBES4Zeflppz/w8vJCpVL1an+u1JPzU4hzyWA6R+X8FKKzwXR+CuFuKqdT5v84UUFBAZGRke4OQ4hBoba2Fm9vb3eH0U7OTyE6G0znqJyfQnQ2mM5PIdxNEs9uOBwOioqK5CpVD9XV1REZGUl+fr58uPajwfK+DrbzoLfn52B5H89m8h6eOVe+h4PpHD3Z+Sn/hlxP3uOB0dv3eTCdn0K426DoajvYqNVqIiIi3B3GWcfb21u+7FxA3tfO+np+yvt45uQ9PHND/T083fk51I9/MJD3eGDI+yxE76lPv4gQQgghhBBCCNF3kngKIYQQQgghhHApSTzFGdPr9Tz++OPo9frTLyx6TN7X/iHv45mT9/DMnevv4bl+/ANB3uOBIe+zEH0nxYWEEEIIIYQQQriU3PEUQgghhBBCCOFSkngKIYQQQgghhHApSTyFEEIIIYQQQriUJJ5CCCGEEEIIIVxKEk8hhBBCCCGEEC4liacQQgghhBBCCJeSxFMIIYQQQgghhEtJ4imEEEIIIYQQwqUk8RRCCCGEEEII4VKSeAohhBBCCCGEcClJPIUQQgghhBBCuJQknkIIIYQQQgghXEoSz244nU7q6upwOp3uDkUIcQI5P4UYvOT8FEIIcTKSeHajvr4ei8VCfX29u0MRQpxAzk8hBi85P4UQQpyMJJ5CCCGEEEIIIVxKEk8hhBBCCCGEEC4liacQQgghhBBCCJeSxFMIIYQQQgghhEtJ4imEEEIIIYQQwqUk8RRCCCGEEEII4VKSeAohhBBCCCGEcClJPIUQQgghhBBCuJQknmJoyN0IO9+GtmZ3R9IjDoeDFqvN3WEIIYTohtXmwGZznHyBqiOw9TWoyR+4oIQQ4iyndXcAQvQLRxvYmsDp7PdN7yuoIaO0nouSQzHr++eUeX3jEbYeqeKPlycTYjH2yzbFmbnvgYcor6nv1Bbo48XLf33eTREJIdzlsf/up6XNzvzkEC5KDu26gMMObU3gkAuIQgjRU5J4iqEh7jzl4QKNrXYq61ux209x9buXAsx6wi1GDB6aftumODPlNfVMuX5Jp7Yt7y91UzRCCHcKseipaGilusGK0+lEpVJ1XiBgGMz4lXuCE0KIs5QknkKcxpR4fybE+KLV9F/P9CvGRnDF2Ih+254QQoj+c/+8ETgcSg+aLkmnEEKIPpHEU4ge6M+kUwghxOCnVkvCKYQQ/Ul+TQvRGw3lsOsdqMxxdyRCCCF6q3A37PkArE3ujkQIIc45kngK0Ru2ZqgvAWv96ZcVQggxuLTUQEOZUpBOCCHEgJKutsItrFY7Ot1ZWFjHJwqm/wq0OndHIoQQ56Qz+v6IOw9iZoDGo19jEkIIcXpyx1MMuL9+e4ifLNtEelGtu0PpG0k6hRDCLV7fkMMV/9jAxqyyvm1ApZKkUwgh3EQSTzHgLEYNwd569Fr55yeEEKLnvAxagrwMmHTSYUsIIc42Z8Un9yuvvMLzzz9PSUkJKSkpvPTSS0yaNOm063344Ydcd911XH755Sxfvtz1gYoeuX1mPLfPjHd3GEJ0sj9tNzWen3RqK0jb7aZohBDdWTQhikUTotwdhhBCiD4Y9LecPvroI5YsWcLjjz/Orl27SElJYf78+ZSVnbqbTW5uLg8++CAzZ84coEhFv6nJh/LD7o5CnGPsba0sSAnt9LC3tbo7LCGEOzVXQ1EaOOzujkQIIc56gz7xXLp0KXfddRe33XYbI0eOZNmyZZhMJl5//fWTrmO327nhhht44okniIuLG8BoRb/I/h7Sl4Pd5u5IhBBCnMsKd0Hm18oFUSGEEGdkUHe1tVqt7Ny5k0ceeaS9Ta1WM2/ePDZv3nzS9Z588kmCgoK44447WL9+/Wn309raSmtrx52Nurq6MwtcnJlhc8HaDJpB/c9TDBA5P4UYvIb8+Rk+DkwB4BPp7kiEEOKsN6jveFZUVGC32wkODu7UHhwcTElJSbfrbNiwgf/85z+89tprPd7PM888g8ViaX9ERsoXjFtZIiAwwd1RiEFCzk8hBq8hf34afSEsBdRn4fRfQggxyAzqxLO36uvruemmm3jttdcICAjo8XqPPPIItbW17Y/8fOlSI8RgIeenEIOXnJ9CCCF6alD3ZQwICECj0VBaWtqpvbS0lJCQkC7LZ2dnk5uby2WXXdbe5nA4ANBqtWRmZhIf37Waql6vR6/X93P0YtCoK4Ki3RAzEwze7o5G9JKcn0IMXoPi/Dy6CTR6iBjv3jiEEEKc0qC+46nT6Rg/fjyrV69ub3M4HKxevZqpU6d2WT4xMZF9+/axZ8+e9sfChQuZM2cOe/bsGXpdgETPVOdB8V5oKHd3JEIIIfqT06kUACrd7+5IhBBCnMagvuMJsGTJEm655RYmTJjApEmTePHFF2lsbOS2224D4OabbyY8PJxnnnkGg8FAcnJyp/V9fHwAurSLQaq1AdI+gKAkiJnRP9uMnAh+seAVfPplhRBCnD1UKhh7E6gH9XV0RVsz7Hkf/BMgbpa7oxFCiAE36BPPxYsXU15ezmOPPUZJSQmpqamsWLGiveBQXl4e6rPhC0f0jEoFKjWg6r9tqjWSdAohxFBltLg7gp7r7+83IYQ4iwz6xBPgvvvu47777uv2tbVr155y3TfffLP/AxKuo/OEiXe4OwoxhP1uyb00VZd1aa+trXZDNEKIc4aHESbc5u4ohBDCbc6KxFOcw+xtkPU9+EZC0Eh3RyOGgKbqMl68eVyX9o9WbXFDNEIIt6k6AqUHIX4O6EzujkYIIYY86aMqBjdrE5Tshcocd0cihBBiKKnJU75fWmrdHYkQQpwT5I6nGNyMFph4p9IF14UKqprYcbSKBaNCMOjktBBCiCEvejoEJ7PyiJUov1qSws6isaJCCHEWkjueYvAz+YJW59JdrNhfzAfb8tlbWOPS/QghhBgkNFoKWg28vjGX5bsL3R2NEEIMeXJrRwjg4jGhhPkaSY30c3coQgghBkiEnyc/mxVHpK/R3aEIIcSQJ4mnEECYj4kwHykuIYQQ55rzk2S6LSGEGAiSeIrBp6ECnG3gFeruSMQ5rqyyisW33d2lPdDHi5f/+rwbIhJCuETlEfAKcnk9ASGEOJdJ4incpqnVSnnmZqJjhoP3cUlmxv+guRpm3A8qmWhbuI9D7cGU65d0ad/y/lI3RCOEOK3WBijZB6Fjep5E1uTD3g8hYiIkzHNtfP2gxWoju7yBUeE+7g5FCCF6RYoLCbf5dvtBtn37Ebl71nR+IWoyxJ8vSacQQojeqTgEOWuh4nDP1/EKgdiZEJzssrD60/I9hTz5v3Q2Hi5zdyhCCNErcsdTuE1sTAzZjdfgExsIh1ZC9DTQe0FQkrtDE0IIcTaxNkHuBggcDiMXQsDwnq+r8YCYGa6LrZ+lRPhQ2WAlIdjb3aEIIUSvSOIpBkb1UdCZwdO/vSklwoeUiPPg6GYo3AV+w5TEUwghhOiNxjIo3AkeBoid1fv1q3LBYFGm7xrkksIsMueoEOKsJImncL22ZmX8jCUKUq/r+nrERPCJAkv4wMcmhBDi7OcbA+NvAc/A3q/b2gBpH4J/PIxZ1O+hCSGEUEjiKVzPwwjDLgSjT/eva7SSdAohhDgz3mF9W0/nCQkXduqRI4QQov9J4ikGRvjYft9kVUMrX+4tYmKMHyOl25EQQpzzvtxThN5DzYWjQnq+kkoFEeNcF5QQQghAEk9xFnM4oc3uxO5wujsUIYQQg4DV7kCtloroQggxGEniKc5aAV567pwZ5+4whBBCDBI/GR/h7hCEEEKchMzjKdyj8gjUFbs7CiGEEGeTllooPQAOh7sjEUII0UuSeIqBU1+mzNfZWAn7/w8Or3J3REIIIc4m+dvh4BdQm+fuSLrXXA2ZK6Cxyt2RCCHEoCNdbcXAqTmqzNfpEw1Jl4KHyd0RCSGEOJuEjQOjL1gi3R1J92oLoWg3mIPB08/d0QghxKAiiacYOOHjwDsUvMOVKoK90NBi4397C5kS509MgNlFAQohhBjUPP36lNAVVDex/nAZFyeHYTHpXBDYMcGjlKnDvPo4tYsQQgxh0tVWDBy1BiwRvU46AfbmV/P57iLWZJS5IDAhhBBD2YbD5SzfXcz23GrX7kilUr7n1PLzSgghTiR3PMVZYVKsPz+b5WBM5AnzddYVQmMFhKa4JzAhhBADp7UBytIhJBk8jD1e7aLkUALMBmYM83dhcEIIIU7FJZfkcnJyXLFZcQ7TatWcnxRMgNnQ+YWjmyHja2iudU9gQgghBk5ZOmR9BxWHe7WaxaRj3shgDDq53i6EEO7iksRz2LBhzJkzh3fffZeWlhZX7EIIRex5kPwTMFpOt6QQQoizXchoSLwEAhPdHYkQQoheckniuWvXLsaMGcOSJUsICQnhZz/7Gdu2bXPFrsS5zhwAgcPdHYUQQoiB4GGA0DGgdWGBICGEEC7hksQzNTWVv/3tbxQVFfH6669TXFzMjBkzSE5OZunSpZSXl7tit0IIIYQQQgghBiGXll3TarVcddVVfPLJJzz77LNkZWXx4IMPEhkZyc0330xxcbErdy/OVrWFYG1sf+pwOKlqaHVjQEIIIYaUpmporHR3FAOuze6gtsnq7jCEEOcolyaeO3bs4J577iE0NJSlS5fy4IMPkp2dzapVqygqKuLyyy935e7FWcTpdALQUluKc9dbkLO2/bU9+TW8tfkouRWNJ1n75KoarLzyfRZ78ntQQv/wd7D/UzgWixBCCPdadbCEtzYewb73Mzi0sv82vP//YO8H7U+d3XzuO51OWtrs/bfPQWD9oQre3JwrF3OFEG7hkvJuS5cu5Y033iAzM5OLL76Yt99+m4svvhj1sXmtYmNjefPNN4mJiXHF7sVZ6JOdBTgcDqobmplrTGF48Kj210J8DCSGeuHr2fsxPUcrG1h3uByTTk1qpO+pF7Y2QEudknj2Ya5RIYQQ/WvbkSoOl9SzaGQNJnU/XhSMmAQOJancfqSKPfk1XDMhAoup43tmV141G7MquGZCJCGWnk/dMphF+5uwO514GqS6rxBi4Lnkk+cf//gHt99+O7feeiuhoaHdLhMUFMR//vMfV+xeDGIOh4MmqwPzCV96njotTpwYPDQ4QmeCr3f7a2HaZsJ0+4BJgE+v9jc22o/HF44kxt/z9AuPukKSTiGEcJP6lja8DB6d2u6eHUddUxumwEl922hDORTvgagpoPfqaA/rmPtZ56HGbNCgVnf+7Pc16ojwNWH0GDpJWnyQmfggs7vDEEKco1zyabpq1SqioqLa73D+yOl0kp+fT1RUFDqdjltuucUVuxeD2Osbj7Apu5Inr0gmwsfU3n7JmO4vUABQcxQKd4J3GBh9er3PkaG9mGpFkk4hhBhw+wtrePabTK4cF85V4yLa2/3NBvxPnL+5N6pyoGAHWKIgaES3i6RE+JAS4dOlPS7ITJwkaUII0W9cknjGx8dTXFxMUFBQp/aqqipiY2Ox24fWmAnRc8FeBmL9PTFpe/FPL3QMePqDd8TplxVCCHHWMeu1xAZ4Emju52lSwseDdyhYIvt3u0IIIXrNJYlnd4P0ARoaGjAYzuDKpTjrXZYazmWp4b1bSa0Bn6jTL9fWAjV54D8M1C6tmyWEEKIfxQSYefKK5P7ZWFUuGCxg8gWNtmffH0IIIVyuXxPPJUuWAKBSqXjssccwmTq6UtrtdrZu3Upqamqvt/vKK6/w/PPPU1JSQkpKCi+99BKTJnU/3uOzzz7jT3/6E1lZWbS1tZGQkMCvf/1rbrrppj4dkzgDDgdkfg2eAcr4Glcr3AFH1kPyTyBweEd76UForRuYGIQQQriGwwF5m8AzGPSecGQdxM5W7mj+qLkW0j5QvgOSf+K+WIUQQnTRr4nn7t27AeWO5759+9DpOrrM6HQ6UlJSePDBB3u1zY8++oglS5awbNkyJk+ezIsvvsj8+fPJzMzs0pUXwM/Pj9///vckJiai0+n43//+x2233UZQUBDz588/swMUirpi0OiU7q+n4rBBdS7Yj80ZVp0LFYchdhZo9f0fV9CxSrgnXt0u2gX1pRA2DrT93I1LCCHEwGhrhKMbwS8egkdB1REIGa20+URD5EQweMOwC8Ac6O5ohRBCnKBfE881a9YAcNttt/G3v/0Nb2/v06xxekuXLuWuu+7itttuA2DZsmV89dVXvP766zz88MNdlj/vvPM6Pf/Vr37FW2+9xYYNGyTx7A8OO+z5AEx+MOHWUy+r1cHEO0F97J9ZxWGlyEPIGPAK7v/YTL4QM6Nre+KlYLNK0imEEGczvReMuwV0nsrflkhoqYdd7yhVaiMnKgXiIie4O1IhhBDdcMkYzzfeeKNftmO1Wtm5cyePPPJIe5tarWbevHls3rz5tOs7nU6+//57MjMzefbZZ0+6XGtrK62tHZMp19XVnVngQ5laA/Hng0cPx+oev1zsLOXqtCuSzlM5sRJuWTqodRAQP7BxiD6R81OIwWvAz0+vEOW/tQXQWKl8p0z7JfiEuXa/Qgghzli/JZ5XXXUVb775Jt7e3lx11VWnXPazzz7r0TYrKiqw2+0EB3dOVIKDg8nIyDjperW1tYSHh9Pa2opGo+HVV1/lggsuOOnyzzzzDE888USPYhJAeGrf1tPqO340uIvTCYdWKlfLJfE8K8j5KcTg5bbz8+hmqMwCvzhImDvw+xdCCNFr/Vb602KxoDo2B6K3tzcWi+WkD1fz8vJiz549bN++naeffpolS5awdu3aky7/yCOPUFtb2/7Iz893eYxDmsMBLWdw1dvphKOblDuTp1om63so2Nm7batUkHwVjLi47/GJASXnpxCDl9vOz7g5MPoaMHidejlbK1ibBiamnqgrggNfQFP1yZcp2Q/5WwcuJiGEGCD9dsfz+O61b775Zr9sMyAgAI1GQ2lpaaf20tJSQkJOfudMrVYzbNgwAFJTU0lPT+eZZ57pMv7zR3q9Hr3eBcVuzlV5m5RiD2Nv7lxtEMDepoz5PHaRolu2FsjdqBQJCkrqfhmHDUr2Kd12I8b3Lj4prX9WkfNTiMHLbeenOUB5ANhtoFJ3P43W/s+guQom/3xwTLNVXwJlByAoUalL0J2i3dBYAeETlOEtQggxRLjkU/ipp57iyJEjZ7wdnU7H+PHjWb16dXubw+Fg9erVTJ06tcfbcTgcncagCBczh4J/AujNyvOydKUSbnMtbH4Zcn449foeRhh3M4y46OTLaDxgwm0w8vL+i1sIIcTZxd4G2/8N6V90/7pGpwzxGAxJJ0DYWJj0085Tfp0o6TIYe6MknUKIIccln8SffPIJw4YNY9q0abz66qtUVFT0eVtLlizhtdde46233iI9PZ2f//znNDY2tle5vfnmmzsVH3rmmWdYtWoVOTk5pKen85e//IV33nmHG2+88YyPS/RQQLzSnVXvpVQcPLAcctcryaI5RJnY+zivrcvmma8PYrfbOxq9gpWy+Kdi8FaSVCGEEOcmlQbMwWBUpvd6d8tRnvhiP81WO1gboeKQkpwOFirV6aciM/rIdDBCiCHJJVVt09LSOHDgAO+99x4vvPAC999/PxdccAE33HADV1xxBSaTqcfbWrx4MeXl5Tz22GOUlJSQmprKihUr2gsO5eXloT7uSmZjYyP33HMPBQUFGI1GEhMTeffdd1m8eHG/H6foAYMXjLoCDD6gM0HqdV0W2Xm0mrzKJu6ZMwyLsR+u8FqblKvcGpf88xZnubW7MllcXt6lvaHV4YZohBBnRK2G5Cvbn+48Wklafh23TmsmOsB87PunF7UlWupPP25UCCFEn6icTqfT1TvZuHEj77//Pp988gktLS2DfjqEuro6LBYLtbW1/TIX6ZBRlKbMhXmycZd93Wx1M/VWKyOCT/hx0NZy0mlbWlpsGAzdJJatDbD9NQhIUObvFEPOmZ6fiaNT+dkvf9ml/Q+/f5ynnu5cnfOJJ57m8Te+6bLslveX8tEby3q9byGGun7//uzme+Ckn/9AWV0zFfWtjAz3UYZ52KzKHJ89UZEF+z6BxIshtIfrCCGE6LEBGfTg6emJ0WhEp9PR1jaIuryInnM4YM97sP115e9Taa1XxnT2UJivsWvSWXkENr6oFBA6wb6Cai5+eT2//7zra2j14BcPXuGn3unRzXBkXY9jFEII4WJN1dBwXG+EmnzY9Hco2NXelFFcwyWvrOfhT9OUhvztkL22/fUgb6OSdALkbYXs70//nfUjgwX848F0rCtswXbY/saZVWkXQgjRzmV9EY8cOcL777/P+++/T2ZmJrNnz+aJJ57g6quvdtUuhSup1RCaCi01p1/28CqoPAyT74H6QrA2Q/jY3u2vrlC5Uu3h2eUlvVZNoJceb3033XI1HjBy4em3X54J9haIndW7uM6UwwGNZcqYpFNV9hWD2v603dx/26Iu7SbfIP609BU3RCTEEHDwv8p3zPRfKZ+PHp5giVDGPB6j12oJMuuJ0zco1WwrDilVa2NndRQQKj2ojOv0DARLaM8LC5kDYcw1Hc/tNrA1K9N3CSGEOGMuSTynTJnC9u3bGTNmDLfddhvXXXcd4eGnuQMlBr+x13d+XpkDRTth2AWdfhgQkqIkVjpP5YpzUyWEjuldhb7mKmX9bgosDA+x8NHPpvXtGH40ZpF7fkwUp8GhFUo13uCRA79/0S/sba28ePO4Lu33v72rm6WFED0SMV6Zd/PHi3KefpDa+XsnNtDMB9eEw573Ic+hFLJz2JR5L1tqYfh8yNsC1gZlihWDT9/jiZ6qPIQQQvQLlySec+fO5fXXX2fkSPlhPaQ1lfPt+k0U5IVw+yUzO9oD4pUHQOJl4GjtedJZnglGP+XHQ+wspTKuK+i63kkdEJYIJQn3Cj39skIIcS4JGd1tc15FI3/830HmJAZw/ZRY8AyAsFTwjemobF6br8yR6RUMCQtAowYPk0xJIoQQg4hLEs+nn37aFZsVg4G9DZqrwRxEqVcyf2+8EN0RuN3a2H0y5+nX82031yiTfQckwOirlfGaQ405EBIvcXcUoofarG2s+O8nXdpra6vdEI0Q56atRyr44XA5KhVK4qnz7DzPc30pxM2FmlzIXAHD5kHkRLfFK4QQonsuG+NZUFDAF198QV5eHlartdNrS5cuddVuhavlblC6MY2/hWCfMH5xUQqxzQdh88uQeiNYzqBLtdEHki7tKOwghNs5WZDS9e703uUy9YoQA2XRxGgAJscGdH2xOhd2vQMNJZByvZJ09nPldSGEEP3DJYnn6tWrWbhwIXFxcWRkZJCcnExubi5Op5Nx47qOixIDpPoopH+hdEMy+kLBNoiaAqZe3JX0iwVbi7I+MD85DCqaobBSmafzTJ2kq5UQQohz14/JZxemAAhOBnMQmEM6hnmcKH+bcuHUL06Z21MIIcSAc0ni+cgjj/Dggw/yxBNP4OXlxaeffkpQUBA33HADCxYscMUuRU+o1KD2UMa81OYrhW58Y3qXePrGKI/jHT+mUwghhBgoejMkX3n65Yp2Q00eBAx3fUxCCCG65ZLEMz09nQ8++EDZgVZLc3MzZrOZJ598kssvv5yf//znrtitOB2fSJhyt/K3w6EUYRjoIje2VqjMUr78NR4Du++ecNgBVc/L7wshhHAPhwNwdhQQqjqiFBTyCu667JhrQYUyV6cQQgi3cMmva09Pz/ZxnaGhoWRnZ7e/VlFR4Ypdit4oPwyN5eAdNvBzSZbsg4NfQNnBgd1vT9htsO01SP/S3ZEIIYToTmUO1BUrfx/8L+x4XblgaLPCvv+Dw992v57RIkmnEEK4mcvm8dywYQNJSUlcfPHF/PrXv2bfvn189tlnTJkyxRW7FD1lbYT9n4JvNKReN/D7DxyhJHj+CWe0mZY2O7XNbQR7G7q+2NqgzOt2/NyiPaFSK+OETL5nFJsQQggXsNtoTfsEmzEQz6m3K5/xKpXy2a3VKJVuPUzKtCqeQdJzRQghBhmXfCovXbqUyZMnA/DEE08wd+5cPvroI2JiYvjPf/7jil2KntJ5wsjLIHbm6ZcFpWLg3k+g6fTTR9Q0Wfk+vRSrrXPFz3WZZXy8Iw+Hw6HMyxk95YwLEW3MquD9rXlUNLR2ffHActj55rFus73hVOaE08tVcSGEcAerzcE7m3PZnFXO9+ml1Le0KS+01MLBzznIML5qGEGrzQ7xc5RCQT/23AlJVorf7XhDqWHwo+Ya5Xuh+ugAH40QQojjueSOZ1xcXPvfnp6eLFu2zBW7EX0VPKrnyzZWQWW2Mifaae4Efr2viP/uKUatUnFeYlB7+/eZ5WSXNjB/ZAgWk66vUXcyLMiMTqPGYuxmnGhwMljrez9xuK0VStOVLlthKf0SpxBCiJ4rqGriq73FRPoZyatqpryhhcUTo8HaBFU5BPhNoNU7EZ3mJNfNvUIhdAxYIjraWmqgLB28Q5XePkIIIdzCJYnn9u3bcTgc7Xc9f7R161Y0Gg0TJkxwxW6FK0SMg8DhSuXA05iVEIRKBWOjfDq13zkzltpmq5J01pdC1nfKHVefqG63U1DVxLtbcrlgZAjjY7qvuBvt70m0v2f3gYSnnjbWbulMMOlO0HbTfVcIIYTLxfmoeCExA3XISH6oDWVmQqDygncoTLmXSJ0nkcfucP74XXHhqBDGRR/7rjD5QuIlnTfqGwOT75YxnkII4WYu6Wp77733kp+f36W9sLCQe++91xW7FK7Ug6QTIMLPxHWTYrrc1YzwNTEqzEd5Ym1UpnJpqTvpdkrqmtmTX0tORSMAX+wp5Kn/HaCmydqn8HvF4A3a/rkrK4QQopdsViJUVYR5tHLdpBjCfI4blqE3g0qFw+Hgr99m8unOfPbk13Lk2HfFKZl8ZcynEEK4mUvueB48eJBx48Z1aR87diwHDw7CaqbCNZzOLlVzK/VhWKb8Eq3h5GM8J8T4s3RRCiE+yp3H0roWcioaaWqz4cNpkkKHA7K/V4oEhY4540M4XrPVjodGhfZkXbyEEEKcGZMvTLsPNMd91lcdgdKDEH8eTg8Tdc02jlQ2EmYxdPquOC2nk9rmNjRqNWaDS37+CCGEOAWXfPLq9XpKS0s7jfUEKC4uRquVD/uzXk0eeAYqhXhOpvwwZH4FIy8Hv1gAcisaeHT5AWYPD+DOWfFdVmlpsfHI8r2E+5h4cEFie/sdM2K5dlIUXoYezPtpa1GKSvjF9Wvi2dJm5+3NuUT7m1iQPMBznwohxLlEq+/8vCYfSvZC+Fi2FbSw5Uglv75wOKEWEzrtcRcCm6uVMfrdzeOZ8Q2OukKezhlNVlUbv5k/ginxga49DiGEEJ245NbNhRdeyCOPPEJtbW17W01NDb/73e+44IILXLFLMVBqC2D3e3B006mX02iVCrrqjgsNxdUtWG12nE5Ht6vUtrSxLbeavQU1ndrVanWPks5//ZDFR3sqYOIdSln9E7XUQmv9abfTHa1aRbS/iRBL38Z//pBewi8/2EV6UU2f1hdCiHPVIf0oniqfwQ/5Ng4czmbjoXIyius6J50AGV/B7nfB3tZ1Ix4G1DpPHKjJLGkgvahv3wVCCCH6ziW3H1944QVmzZpFdHQ0Y8eOBWDPnj0EBwfzzjvvuGKXYqB4BkH01NPPw+kXC5Pu6tRU1tBCc2MNAQ6AE9Z32An2hGU3jsPX1IM7myew2RykFdQR4KWDSd0XLWLXu0oyPOHWXm9fq1Gf0Z3ONYcrWJNRxphwC0k/jncVQgjRPXubMlxDq2NDdi0fHWhkpOM7wirTaG08j6MVgcp0XyZ/ZZougPDx0FoHmm6+Q+LnAPDnZBtX51YzZZjc7RRCiIHmksQzPDycvXv38t5775GWlobRaOS2227juuuuw8Oj90mFGES0Oog7r0+rXj42gimtmwis+gGOaiD6uKrHmV9DZTajJ/20T3N8arVq/nh5Mh5a1ckXCkt1W+Gg++cOY3SYhctTpZuuEEKc1p73oOIwTL2Xm6dF4efpwXlBUejrQgg1jCU5UA07X4eQ0ZB0qbJOUNJpN6vVaiXpFEIIN3HZgEtPT09++tOfumrzYrBrrIKc7yFyMvhEtjcHD58EmzZDeXrnxNMrVLm6rTld8SD7Sefn9DOfZt2Y6T2Nvt/5eBr4yYTI0y8ohBAC9N5KFfTyTLTxYVwxPhLytoFWRUpsMOCEuFlgOUkPFyGEEIOOyxLPw4cPs2bNGsrKynA4Oo/pe+yxx1y1WzFIWBur0JQdQuMX3ynxXF/hScCIe0gKD+i8QkQP5nbN3QAFO2DcLUrlQyGEEENT8lVK11nzsUJBzTWw4z/gGQDxc5XeK9GdLybuzquiocXGzOFBXTbX0GKTSrZCCOFmLvkUfu211/j5z39OQEAAISEhqI6bUkOlUknieQ54aksLXs65PBSW2t7WZLXxr3U5RPkZeTrhhMSxrUWpSGv0OflGW+qgvhjamoFeJp6HViqVERMvBUdbp2RYCCHEIFSeCYdXwbiblUJ1waMhMAEcNtj/PwhMhOCR7Yt/tL2AotpmJsb4YdB1/Lw5VFLHn75J56JRoSw+WQ2AljqlN43O09VHJYQQ5yyXJJ5PPfUUTz/9NL/97W9dsXnRjxpabLy2PpvkcAsXjAzpt+2GWwzYHPpO83iadFp+OjsOL4OW3UereOabDGYnBHLv3AQ49A1U5sCUu7v/4q8rUZJOg3eXuUELq5uwO5xE+Z/iB4NWr0z/kv0d1BXCtF+eejoYIYQQA6q2qY3s8np+yCxjdKQv8/R60BogbzP4xYPTBrWFyoXKymww+HRKPBdPjKCh1d4p6QQw6bVE+Xri76VM07Lk4920tDl49YbxygJOJ+x6RylSNP7mgTpcIYQ457gk8ayurmbRokWu2LToZ7VNVnYdrcFDo+5b4mlrBZW6SxXBn80e1u3iMxOUog7rD5VRVNNMdnkDj36+j9+Oi8Gs81J+ZHSn7CA0lMGoRco40LL09kISqzNKaW518LPzus4N2u7HgkiVOUqXLUk6hRBiUNmVV822nErSCmvRaTXMO3821BXDzjc5VFDGupIYFqREEuHpB1PvAa0Rmqqhvgh8ohkb6dvlwiRAhK+JJ69Ibn9e2WClqdXesYBKBaGjle0JIYRwGZcknosWLeLbb7/l7rvvdsXmRT8K9zPx7KLR+BhPU5inrVn57/EJm8MBO95QrjqnXtve/Mn2PNZklvHghSOIC/LqdnMzhwfxv19M57kVGaw/XMGNU8YxInrsyfcfPRX84sA3Gg5+oSSinoHgGUBxVROt3U8N2pV/XA8XFEIIMZBSI30IMOu4cWoU/p567HY7j64qZ6RpKk06f97KKSMwIYgI6OgZk7cZctcrdyuHXQCRE7vddkltA3/+5hDzRgTwz+vHd10gdlbXNqdT6YJrtPTbMQohxLnMJYnnsGHDePTRR9myZQujR4/uMoXKL3/5S1fsVvRRmKX76UvsdjsazbEKsrvfU8bYHD8HplqtJII6c6f1jlY2k17cQENVGeiqwaf7MTU+ngZ+PT+Ja6saGRF6mi92DyO1hjCMdie6qCngF6PM3wasPlRBY4uNxy4b1ZPD7T/2NijYCQHDwdNvYPcthBBDjK+nDl9PHRTvBYeZZq9oMkvrqbd485dFI0mNC2VS7AmF6cLGQmujMnb/2HdCd/67u4Qv0oqpamjj0rFdv5M6fd/9KH8rZK+Fsdef9HtMCNFZbm4usbGx7N69m9TUVHeHM2DefPNN7r//fmpqavp927feeis1NTUsX76837c90FySeP7rX//CbDbzww8/8MMPP3R6TaVSSeI5mNUWQGs9H+WaeHPTUZZcMJwLRoVAQAKg7rr8iIu6ND1wwTBumBJFaO7nkJZ/0vGU36QV8MamPK4aF8YYP7tSWKi7ib+B8roWfvvZXqZGe3PXnETwCm5/7bqJEVhtzr4ecd/VFEDOGqUoUvx5A79/IYQYamxWOLQCvEIxjovjXzdPQK9RodNplKTT6eTBj3ficKpZeu04aCiFqizlu+jEHi3WRuUCoc6TKR7ZXJnkRcqwrslpbkUDD3y0h0mxfjxycceYUczBEDgcDHLHUwjRISYmhvvvv5/777+/X7d7sqT9b3/7G06nG37nuoBLEs8jR464YrNiIOT8ADX5+PhdQ6CXHpPuWLIZN7vHm9BoNIT6GCFyCgQmsbOwmc3ZBdw9Oxatsw1KD0DQSHbn17Ajr5ppQa3QtAWipp40gTPqtMwNqGN8+ZdQfpPyY+CY22acYmynK/lGw6grwRLhnv0LIcRQo9XBmGugvgSqc/H3jen8es46ko9+zmrPYxc9/eMhdoby3xMd/K9SG2D4AkIrNzHOYxhWR1iXxXQaDf6eerxOnG7FL1Z5CHGOsFqt6HSnGXrlZmdDjP3NYhk6F7+6uYXVv5xO55DJ0s8FDZGz2ew5m2kjInn7jslMT+g6H1qPafWgVvPmphze33aUL/cUQFmGUh6/PIPfXZrMC1eP5p4F4yA0RUnkjmdt4mDOUUpqmjEbtNwwMxHvgHCaqgog63tljGlLHRTtAbvtjI67T9RqCEoEvfn0ywohhDit+pY2sERC5jew5wN251ZS39JGVV0TR/ZuAI2WOeNG8fCcSKW6rd4LYmaypaCFD7bkcqCwhi3ZFcrGAkcqXXH94vFLnEFleQnrDuR12WeYr5F/3zqR+84f3uU1IYay8847j/vuu4/777+fgIAA5s+fz/79+7noooswm80EBwdz0003UVFR0b7OihUrmDFjBj4+Pvj7+3PppZeSnZ3d5xh++OEHJk2ahF6vJzQ0lIcffhibreM3XXcxnorT6eT//b//R1RUFHq9nrCwsPaelk8++STJycld1klNTeXRRx8FlG6tV1xxBS+88AKhoaH4+/tz77330tbW1h7P0aNHeeCBB1CpVJ2mjARYuXIlSUlJmM1mFixYQHFxcafX//3vf5OUlITBYCAxMZFXX321/bXYWOVC19ixY1GpVJx33nmdYvqRw+HgueeeY9iwYej1eqKionj66adP+b4MFi5LPN9++21Gjx6N0WjEaDQyZswY3nnnHVftTpyBZqsdq02pzrOmQMWLu2F1emnPVnbYlUd38jZBxtdYVK04nYBapZS+T7wYgpTuTFeNj0LnaVHaTriynLHmfTZ88Dz/+D4dgN01Jn6dlcLu9Gwo3AltTVC8R/mBUpXTl0MXQggxSHy5p5Cfv7OT3fm14BtHaU09b63Zw6c7C1i9eRs7v32foup6omdey6jyr5Quuce8ujabZ1ZksHxXIa+syabJaoPwVKUnjdYDrc7ITEs5143qftqtuuY2uUguzklvvfUWOp2OjRs38uc//5nzzz+fsWPHsmPHDlasWEFpaSnXXHNN+/KNjY0sWbKEHTt2sHr1atRqNVdeeSUOR0+rPHYoLCzk4osvZuLEiaSlpfGPf/yD//znPzz11FMnjXHZsmWn3Oann37KX//6V/75z39y+PBhli9fzujRowG4/fbbSU9PZ/v27e3L7969m71793Lbbbe1t61Zs4bs7GzWrFnDW2+9xZtvvsmbb74JwGeffUZERARPPvkkxcXFnRLLpqYmXnjhBd555x3WrVtHXl4eDz74YPvr7733Ho899hhPP/006enp/OlPf+LRRx/lrbfeAmDbtm0AfPfddxQXF/PZZ591e4yPPPIIf/7zn3n00Uc5ePAg77//PsHBwd0uO9i4pKvt0qVLefTRR7nvvvuYPn06ABs2bODuu++moqKCBx54wBW7FX1gszt4d2sugWY9V4yNYPqwQFraHMxICDj9ygCbXoHWevCLhoT5YA7seM0vAZpqmDsyEJ2nlTkjgpW7oKEpJ99eW7PyYyJgOLqQEWgiVCSF+QCQoMrjIcsavEdeDuGhyp3G0FTQeSkVb4UQQpy1Ar10xAWaicn9GBpyMKVczch8fybF+tHS4km5+jJ8wuKhLBNCU2kzh9JSno9X2Q6uT45nVJg3cxICmDwsAJNOC/VlsPsdZQ5Qaz1jL74DAkd02W9+VSP/t7OQ2cMDGBctheLEuSUhIYHnnnsOgKeeeoqxY8fypz/9qf31119/ncjISA4dOsTw4cP5yU9+0mn9119/ncDAQA4ePNjt3cRTefXVV4mMjOTll19GpVKRmJhIUVERv/3tb3nsscdQq9VdYjydvLw8QkJCmDdvHh4eHkRFRTFp0iQAIiIimD9/Pm+88QYTJyoVsN944w1mz55NXFzH70hfX19efvllNBoNiYmJXHLJJaxevZq77roLPz8/NBoNXl5ehIR0noawra2NZcuWER+vdP2/7777ePLJJ9tff/zxx/nLX/7CVVddBSh3OA8ePMg///lPbrnlFgIDld/Q/v7+Xbb9o/r6ev72t7/x8ssvc8sttwAQHx/PjBkzevT+uJtL7ni+9NJL/OMf/+DZZ59l4cKFLFy4kOeee45XX32Vv//9767YpegjjVrFsEAzEb5KZVs/s45FEyMJMHc/n2ZNk5WduVUdDY3l0FgGdUXKHcjj2RpprSultKyCKcMC8PFUtvnWphyueGUD/92Z33UHbS1QkQV1xcSlzOSOW+7g2inKh4FZ78G4KB+Ghfh3VJE1eEP4WNC45BpKn1htDj7YdpQ9+dXuDkUIIc4aU+IDefLyUTRVFlJRW4NXSAI/nR3Pl3uL+NPKwwQMm4ip+hBkrYKQZL6vDuD7HQdoLTrAglgPfnvRSCYNC2Je0rEr/x568AoBFVBf3KUC+4+8DTqGBZkJ9NKfMj6Hw8H2IxU0tLhhaIcQLjJ+fMf0QmlpaaxZswaz2dz+SExMBGjvTnv48GGuu+464uLi8Pb2JiYmBlASvt5KT09n6tSpnbqrTp8+nYaGBgoKCrqN8XQWLVpEc3MzcXFx3HXXXXz++eeduu7eddddfPDBB7S0tGC1Wnn//fe5/fbbO21j1KhRnapch4aGUlZWdtp9m0ym9qTzxPUaGxvJzs7mjjvu6PT+PvXUU73qqpyenk5raytz587t8TqDiUt+rRcXFzNt2rQu7dOmTevS17knXnnlFZ5//nlKSkpISUnhpZdear96caLXXnuNt99+m/379wPKP9Y//elPJ13+XKdSqZiT2MPb89VHyVrxLsubk/GYO50xzVsgZjoEJSlf7lrlS3tzVjlvbsrltqnDGD81iYD8NsJ9OqraltW2cri0gZK6lq770HnC+NvA5Nv1teBRymOQy61sYPnuIoprW0iN7OY4xIC474GHKK+p79JeXt21rbfqm60s/svKLu2Z+VXdLC2E6DGViqVNl2A0annK5AvWRqrqmskqa6C83spH1eGUl9i4SeNPlF8LheqxqCMngLmbXjoGC4y9Qfnb1goaHaR9oPSSSbq0fTFLQxaXadLBvOCUoW3MquDlNdksTAnlhikx/XjQQriPp2dH9/OGhgYuu+wynn322S7LhYaGAnDZZZcRHR3Na6+9RlhYGA6Hg+TkZKxW64DEeDqRkZFkZmby3XffsWrVKu655x6ef/55fvjhBzw8PLjsssvQ6/V8/vnn6HQ62trauPrqqztt48RpIFUqVY+6Ene33o9d+BsaGgAlT5k8eXKn5bpM5XQKRmPXWSLOJi6bx/Pjjz/md7/7Xaf2jz76iISEhF5t66OPPmLJkiUsW7aMyZMn8+KLLzJ//nwyMzMJCupa+Gbt2rVcd911TJs2DYPBwLPPPsuFF17IgQMHCA8PP6PjEhDpb2Cyhx9x/gbYtlfp4npCUaAVB0pYk1lOqI+RKQnJzEvqvI2HLkri6vHhxAZ5d93Bgc+hqRIm/6yjrb4UKrMgctJJp1vpjVUHS1h/qIKfzo5rv9Pbn4YHe/PrCxOI8u35B6Xof+U19Uy5fkmX9pWrVp3xtp0aHVMuv7lLe5r06BDijN0xN4mmVhuf//dTxjVt5OnUufz8/JnEBHhzw2tH2XHUg1Fjq5iTGEJS6AnfIw4H1BWCd7hSAO5HWj20j+E8YSxnfSlUZoO1CXQn/05ICvPmgqQgJsVId1wxNI0bN45PP/2UmJgYtNquKUJlZSWZmZm89tprzJw5E1CG0vVVUlISn376KU6ns/2u58aNG/Hy8iIiou8zBhiNRi677DIuu+wy7r33XhITE9m3bx/jxo1Dq9Vyyy238MYbb6DT6bj22mt7nczpdDrs9pPUNzmJ4OBgwsLCyMnJ4YYbbjjpdoFTbjshIQGj0cjq1au58847exXDYOCSxPOJJ55g8eLFrFu3rn2M58aNG1m9ejUff/xxr7a1dOlS7rrrrvZBv8uWLeOrr77i9ddf5+GHH+6y/Hvvvdfp+b///W8+/fRTVq9ezc03d/2hKHrBN5rgC3/NZaBcPdYaj/si77DkgkQifIxcM/G4hNTaCEfWQ8hoUKmJPfo15KkhZhYEHFcG3xKhzOepOu4HQ8k+KNiudOuNmQmeJ58kvIumamiu7jS/W2VDK3nVjTS1uq67VJdJzoUQQvTIyFALBRU1VBVuxNOzEm1NITG174PmIh6aP5z04nrmJHY//onSfZDxtdIbxye684VRlQpSruu6TuwsiBivVMg9hQCzgTtnuWn6LjG4ZH4DWgPEz3F3JP3q3nvv5bXXXuO6667jN7/5DX5+fmRlZfHhhx/y73//G19fX/z9/fnXv/5FaGgoeXl53f4W76l77rmHF198kV/84hfcd999ZGZm8vjjj7NkyZL28Z299eabb2K325k8eTImk4l3330Xo9FIdHTHZ8Gdd95JUpJyV2Tjxo293kdMTAzr1q3j2muvRa/XExDQs998TzzxBL/85S+xWCwsWLCA1tZWduzYQXV1NUuWLCEoKAij0ciKFSuIiIjAYDB0mUrFYDDw29/+lt/85jfodDqmT59OeXk5Bw4c4I477uj1sQw0l4zx/MlPfsLWrVsJCAhg+fLlLF++nICAALZt28aVV17Z4+1YrVZ27tzJvHnzOgJWq5k3bx6bN2/u0Taamppoa2vDz+/kVyhbW1upq6vr9BCnodFB1CQa/ZI4dGA3Ow/lt1fGtZg8uGv2MCym4+5ONpYryWNZJrbmOg6lp1GalwlNSt/3ivpWqhutyo+F4fOVHwg/ip6qPMoOQtn+3sWZ8z3s/Qiaa9qbrp0YxbKUowyv7f2HjRh4cn4KMXj15/lZU1fP/75bw8H8KiICfJh1yQ34hw+Dlmo4/C31WRsJ9fHkqhFG6r9firNgT/u6tc1tbMquoMEYDuHjlKm79n4M9rbT71itPm3SKUQndYVQ1/uhY4NdWFgYGzduxG63c+GFFzJ69Gjuv/9+fHx8UKvVqNVqPvzwQ3bu3ElycjIPPPAAzz//fJ/3Fx4eztdff822bdtISUnh7rvv5o477uAPf/hDn7fp4+PDa6+9xvTp0xkzZgzfffcdX375Jf7+HTctEhISmDZtGomJiV26vfbEk08+SW5uLvHx8e0FgXrizjvv5N///jdvvPEGo0ePZvbs2bz55pvt06hotVr+/ve/889//pOwsDAuv/zybrfz6KOP8utf/5rHHnuMpKQkFi9e3KMxqIOByyqyjB8/nnffffeMtlFRUYHdbu9SIjg4OJiMjIwebeO3v/0tYWFhnZLXEz3zzDM88cQTZxTrUGW1OahushLsfUKxIZUKYqazb1caDVvepCkwlaCARUT6naR7aVWucufRWke5YQovOq9hlMmTeyNTAfh8dyFGnZobuxs3o/NU7ox6hYNPD7peNFTA0U0QNQUiJ4NPrDLW5zgGlRXsJxmP4HCAreWUXa7EwJHzU4jBq9/OT4eDqsx1NO/5ijyVg5F2AwZbK/jHQ8IFkHwlqw5ZqdhdyGzPXEz7VmIz+OEbkQpAbkUDW3OqsBiDGTV8PlTmgLWhfXiG0+mkpK6FIC8DGrXqFIEI0QPjbkGpWnV2W7t2bZe2hISEk07jATBv3jwOHjzYqe34qYhiYmJ6NTXR7Nmz26cR6WmMp3LFFVd0mvOyO06nk6KiIu65554ur/04bcrxXnzxxU7Pp0yZQlpaWqe2W2+9lVtvvbVLLCe+F9dffz3XX3/9SWO78847u3ShPTEmtVrN73//e37/+9+fdDuDlUvueH799desXNm18MbKlSv55ptvXLHLbv35z3/mww8/5PPPP8dg6L5KKyjz4dTW1rY/8vO7qbY6lGWvgfT/dfvS1pxK3t+aR0ltc7evR8fEYhk5l/CRk089XrLsIHgYITSFUIuJe+Yls2haUvudzUlxfoyP8lO65O7/XLla/aO6Yjj4udIF16MH/fAbSynJ2kHG4cNK192IcZ3voKpUMPZGGNn9lSSOboDNrygJrHC7c/78FGIQ65fzs/ww/PAscQ37mTh9HnFxw6nNWAt5m6EmD5x2CBzOZO8qLtftILw1B+eYazGO7CgGNDLMwuUpYdjtTjZnV+L0i4XQMe2vHypt4MNt+ewvrDnzgxZC4zGoqumLnisvL+fll1+mpKSk09ydYmC4JPF8+OGHux0Y63Q6e9UXPCAgAI1GQ2lpaaf20tLSk85v86MXXniBP//5z3z77beMGTPmlMvq9Xq8vb07PYa0gh2w610lyQNoKFdKzXdzhSou0JOxkT74mHTdbirUz5u9miSqCzJR7XyDjNdu5+lXX2PH4YLOC6ZcBzMfBD+lO0FyuA9Bx91FTQm3kBTmrRR3qDwMDcf+n9cVUrf+n1RueR9H5ZGeHV/wKHYGX836+uC+TQjuGQh+MeBx8osVgDJ/6XFdeIVrnHPnpxBnkX45P+uLlfH43mFkGVP49GA9a80Xw5Sfw+hFyoVIaxPhjhKCrUep27eCNZllvLO3oX0THho1cUFmDpXVk5Zfjc3hVD6j0/8HNfmEWAykRFg6LpBWZMP2/3TtLtlcA5tfhbytfXtDqo/C1tegOrdv6wsxhNx9992dpg45/nH33Xf3aZvvvffeSbc5atTpZz4ICgriySef5F//+he+vjLzwEBzyeWaw4cPM3LkyC7tiYmJZGVl9Xg7Op2O8ePHs3r16vbb5g6Hg9WrV3PfffeddL3nnnuOp59+mpUrVzJhwoRexz/ktTUpY2Ycx4rrjP6JknSqunYbCfc1EX6ayq8Lhnli2bIeHHo0ahWjPEoISX8TIu5T7lJC1+lRHI6OioMHlivdcMfdAuZA5cdGcw3s/QR03hQU5FLnEUeoKhBNVROf7y7k0tEhxAaalS68lrD2qVx+dH5QE05bDSrVsN6+OxAwAloboKUG9GYl1sos8InqnIwe+C80V8LUX3SuniiEEKLnDD6gN1FpSeTfq8sYFmRmSpQJDnyh9HLZ9zEMm6dUPA9KptGnlqIqP0JrctnyzRamzL4Ycn6A6GlclByKze7AQ6OGukqlOJ3JF0t0JOcnHTdsx2FVElPHCWNAVSrl+0Tdx59HDofyHduDqReEGOqefPJJHnzwwW5f6+tF5IULF550XOaJ05l0p083JES/cUniabFYyMnJaZ9U9kdZWVm9mosHYMmSJdxyyy1MmDCBSZMm8eKLL9LY2Nh+e/zmm28mPDycZ555BoBnn32Wxx57jPfff5+YmBhKSkoA2q+GCJQKfoFJHZNpq3s+fxDAztwqNmVX8PPZcWi1WsKDg8DiT5Xah4Q7/kRC8V6oONwlGaQyB6qylTnU8rZA6vXgFaSM4XTaOxJfvZdS2j5nDZhDsFz0ByqavIiOCmblgRI2ZFUQ5W8iVlOuFA6Kma4c03GM1ZlK8ji8c/uJcsrqabTaGR3h09HYXANZ30HQSKWrbsVhOPCZso+Y6R3LBY+CtkZJOoUQ4kxYIiBiIv6hcdx7voMWqw2P7E8h538QkqIUnDP4QcUh2PshCTFTeOTau/jkwzcpK91JgcmBaufrmCeUY5n1047t+sZA8qLuawMEJUFgYtcLrgYLTDyDypD+sTDjV31fX4ghJCgoqNupD8+El5cXXl5SDOxs5ZLE8/LLL+f+++/n888/Jz5eKT2elZXFr3/9axYuXNirbS1evJjy8nIee+wxSkpKSE1NZcWKFe0Fh/Ly8jqVXP7HP/6B1WrtMhns448/zv/7f//vzA5sqKgtgF3vdJuw9cTrG46w7nA5Mf4mLotogZw1HGoL5Ll0H6Zpc7h9xhhoqYWyTAhP7Vix4hAU7VH2afTpmJMz4YKuOwlLheRroK2B8IhYwo8lxxckBRFmMZAU4g3OVoiepiTR0FG9UOMByT8B57ErzulfQlONMpH4CUnin1dkcrSqkY9/NhWL8Vh3Yk8/GHNtx11a3yiInakkoscLH9vr906ce3635F6aqrtWmzP5BvGnpa+4ISIhBhlPP0i8BIBpcXZ+8o/N3OJt50rfaDBZQO0BjmNTeAUlQpQyf+DMC67C0TKXV9ceIc54EVv2h/PrEbWMCD5WTK6hDA58CuHjIaGbAoPd9PIRQgjhOi5JPJ977jkWLFhAYmJi+wSwBQUFzJw5kxdeeKHX27vvvvtO2rX2xGpXubm5vd7+Ocfoq8yn6RPV61VbWmzMHRlITICJCxJDYN+bcGQdnuEXowuIJTbABA47FO4EU0DnxDN+jlLm3hwEMdNOv7Nh53VpUqvVx92dNELc7I4X936szC868Xali2z7Sh7goev2R8bMYQEMr/fqSDp/5B/b8beHEWJmnD5eIbrRVF3GizeP69J+/9u73BCNEIObRqPh/KQgfGwR0HyICocXAZlfKxf+pv8CanKVabJ8wgnxDwG8uXiSns92e2FyOAjwPG44hN5b+a7zjXHT0QghhDiey7rabtq0iVWrVpGWlobRaGTMmDHMmtX7u2vCBXSekHTp6Zdz2JWqgl5h4B8HDjtPr0jnf3uL+O2CRJpsdgwjLoH4uYT7RPPqjOPuJo6/tesYGa1eSTp7y9baqdtuZkktP2RWcNX4cALMx/3I8A7rfoqUEQu6th1z07SY3scjxEnU1FRz/22LOrXt37sb6Jp4CiGO47DD0Y1gieL2qRGUN4bz910jWJFWzq/GDGP+xNHgHaqMy/SJAq1BWUetYVpCENMSuvlu8TBA4sUDfyxCCCG65bJa0CqVigsvvJALL7zQVbsQfdVYqXRDNXed9Paut7YD8Nr1ydDWAkc2KFea1RrY93/M9EnFFNOCIfd71jKbqybFdb8Pow/Ul0DJXvCNA+9TVyE+qYJdkP0dLaOuJbvVQkKwFztyq1mdUcaoMC8CEo5LPOPn9G0fQvQTldPR5e7mnF9u6XbZ//t2IytGp3ZpNxv17NjWx4qaQpytmmsgdyOottBUWsgBr3nU2GMpqLOS55GgVF+3toBXiDI/c2k6FGylMPZqMPl1FMFrrACTf5ceLg99vIfs8gaW3TiBIMtpKpYLIYRwCZmE6Fx04DMlqZz+iy4vqVQwhizY9D0EjlCKPsSfp0y9YvLnwthYLgxOpyQrH2u4vuu2QbkKvX4pVOcpYyrjz4eRC7HZnXyZVsjIMG9GhB4bg+N0KvOImvyUqVasTcpV7R+V7gVrI4erbHx3tBS1WsWV4yJIDPFmbJQP5KxT5ggdfY0yTkiIs4RdpeFnv/xll/Z//v3vbohGCPey6n1Zb7yQUcYKfIr3M8azkvOSx3NjYA4x4TWQuRKK05TvJKMPtDSA3os1h6oZ1ryK8CgLBI1Svt+CRip3RsNSISQZAJUaNGp1b2vpCSGE6EeSeJ6LoqZAN/OsAvxrfBE0tYBHFFibwdoAHiYweMOEW5WFLOGERE0BT3/lecY30FgGwy+CvE0QPkEZ34kK/IdB8W7wjSZLHUfentVE5lTCeQshMEHpGlucBpZwpfhQ9RGYcu9xYzRVEDySuOgo5hjqiQv0RK/VMDzEi/zs/USnf6pc3RZCCHHWyi6uoHTPSuwRw7hw4YtElWfCnv9gRgPVrTDiIuzNddTpA/BVO6A5D8zBnBdtwHK4DPZ/B1PDlKrpR35QqtP6d/TIee7qVOWPgl1wOB1GXaEMOxFCDAkqlYrPP/+8ffrFs8Wtt95KTU0Ny5cvd3coA0ISz3NRyOiTv2ZrVpK+MYuUecicDtB0M1ZTo1PGfxoDaLar0Km1aOqLlKq1PjEw8TYcDgfpObkEe7USYA4h0dsbVYKJqNKNcMAOsx7E6tBiT7kVo7MBstdBxCTY939gtMCoK2HsTWBrwdPeSGpUx1ygb27K5eCRSp4YM4ugEVPlbqcQQpzFRgR7oY804RvkpDF3G55BsVgDk7F5BmEKTaRFa+E1vYmWnE3c6p9OYEst1BUQUfo9JF8K1SMhIAEChkNJGoSmKD1pTmRtULrj2m0Df5BCDAGbN29mxowZLFiwgK+++qpX68bExHD//fdz//33uyY4MehJ4ik6S7mWlhYbWzJKOS8xGDiuYFBdMdhalC6xbc1wZD3NnpH8u3YCSWFjmdecrvTVNfoAsO5wBf9YU0JNUwiP+2mY5g0jZi6CqgngaCO7oonnv82gvrmNty9QoanNg4ix0FIDHseuRKvVkPmN0p12xv1YNZ78bfUhtGoVKfGRmEbPBIP8MxZCiLOZWmck7pL7+eSLL7Ae+Jw5cy8irdFC6+oPSJl6IW+UxLLuUDlTwkfgMTwcag+AxqDUIagvhdkPKRXI4dTj/eNmKdNwnXhB9TgFVQ0UVLcwJT6gn49SiLPff/7zH37xi1/wn//8h6KiIsLCwtwdkjiLqE+/SN84HA4OHTrEhg0bWLduXaeHcKPmGig9oIytPIkXVmXyu8/S+N1ne6lpbOl44dBK2P+pMg7zwGcQNApN4gISQ72J9DWBd7gyf2d1Lq02O36eHoyL8mVCjB+hPxZzUKmU7k+BI9h8+P+zd9/xVZbn48c/Z4+cmb33niRhha1MwQGK4gStrXt32rqq32p/ttplbe23frW27j1QHCgo20CAQEhC9t7z5OTs8/vjgUBMUFAiaO/365WX5n7GuZ8nJOdcz33f19VGlMJGcICa4bBJMOkSMMdKdUabd0LDoQQrXjf01kNfIy6Pj7rOITw+P9fNS8Yggk5BEITvDZslDX18AYFl/2Zyzd/wmGKpUcTjdHtJCg1g6eRkLCovuJ1gTYbAeIgsAMUxcg6M53DQ2VsPm/4EnRWjNt/3dhk3PVfCgea+k3ZdgvB9YLPZePHFF7n++utZtmwZTz/99Jh93n77baZMmYJWqyU4OJgVK1YAMG/ePOrr67n99tuRyWTIDiUAu++++5g0adKoc/zxj38kPj5+5PvPP/+chQsXEhwcjNlsZu7cuezadWIlyV555RVycnLQ6XQEBQWxYMEChoaGjvv8MpmMJ554grPPPhu9Xk9GRgZbt26lqqqKefPmERAQwIwZM6iurh455vC1PfHEE8TExKDX67nooovo7+8/Zj99Ph8PPfQQCQkJ6HQ68vLyeOWVV0a29/b2ctlllxESEoJOpyMlJYWnnnrqhO7FqTQhgee2bdtITk4mIyODOXPmMG/evJGvM84QmUdPqcYdUPYW9DeONO1v7mdnfc/I91MSrCSEGHl3byv/3t4gHXPwA0iYA2lLpSwNvY1U7tnMb989QFFiEGnhRnANgscFfh/FdT2sP9DJhYXR/GZ5JgmhxjFdWRbYzFWa9UwLHKKsbUiqtSZXSGnyvS5pShTwZoOKXepCsMZj0Cr5fyvzuHV+6oTfKkEQBOFb4vNB9UZmqatQBcaCQoFLrqNKmUJeWjLbanvoHnIzJy1MyiOQsgi6DkDdFmjbD1UfQu2n4LSNObXN6eFnL+/m3jdLR2+QK6UcBnLVqObJcVZmpgQRYRHZb4XTm8PtZW9THw73+Hk7TraXXnqJ9PR00tLSuPzyy/m///s//EcNZKxdu5YVK1awdOlSSkpKWL9+PVOnTgXgtddeIzo6mvvvv5/W1lZaW1uP+3UHBwdZs2YNmzZtYtu2baSkpLB06VIGBweP6/jW1lYuueQSfvCDH3DgwAE2bNjA+eefP9L34z3/Aw88wOrVq9m9ezfp6elceumlXHvttdx5550UFxfj9/u56aabRh1TVVXFSy+9xNtvv826desoKSnhhhtuOGZfH3roIZ555hn+/ve/s3//fm6//XYuv/xyNm7cCMDdd99NWVkZ7733HgcOHOBvf/sbwcHfndkZEzJcdN111zF58mTWrl1LRETEyFMN4TQQNVlKxmOKGmna29zHwLCb/BgrcrmMxdmRRJi1vLyzmRXpBqj9APBD4plHnhQnn0HZvhfY72qntW+IlHCzFDCGpUNoBikYeb2kif9962N+FrMfa8EKCM0Y1RVrZDJG3yAFAcnERh7KcqvSwdQfSR9C5HK6+h10lm/FpVdToJbS5R9zlNPr+dLpU4IgCMJpyO2AnU9BfzOx5nhc2ReilMfxyNtVbO8J4BKnh0umxGA8HB8aQ6UvlRY8bhhohrZ90gNLrQUickedvq3fQUljHwr5Fz6LmKNg2o9goAW6qiE4CYDr5qVM/DULwklQ2T7I+gMdAORGWyb89Z588kkuv/xyAJYsWUJ/fz8bN25k3rx5APzmN7/h4osv5te//vXIMXl5eQAEBgaiUCgwGo2Eh59Yib0zzzxz1Pf/+Mc/sGy0V1cAAQAASURBVFgsbNy4kbPP/uq69K2trXg8Hs4//3zi4uIAyMk5ku/keM9/1VVXcdFFFwHw85//nKKiIu6++24WL14MwK233spVV1016lwOh4NnnnmGqCjpc/df/vIXli1bxiOPPDLmPjidTh588EE++ugjioqKAEhMTGTTpk088cQTzJ07l4aGBvLz85k8eTLAqJHh74IJ+ZR+8OBBXnnlFZKTkyfi9MKJGmyXRjkTZknB3xcS8SzNicTr9SGXy6QRy4EWcqPjyI0JhIMfgaMXci4cHdTFTGPyqmTCbUhBJ0BYJq81mzA0yliUpSUhyECHMwClIUQKSo/m98NAK8rIbNKt46wPkMmgZTfBxkjSF67BolON3edo/c2w5wVIni+l0B+P2wE+z1EZcwVBEIRTaqgHeqqlgNEcgyZ5PlkqHWAmMMJLns6BSeHmOsNm6G8Ax62gNbOzrod9TRouNUWiCs+ExDOkmTyBY2tLJ4UEcO/ZGQQc66Fl1XoYbIWZt4FSPZFXKwgnVWqYcdR/J1JFRQU7duzg9ddfB0CpVLJq1SqefPLJkcBz9+7d/OhHPzrpr93e3s5dd93Fhg0b6OjowOv1YrfbaWhoOK7j8/LymD9/Pjk5OSxevJhFixaxcuVKrFbrCZ0/N/fIQ62wsDBgdAAbFhaGw+FgYGAAk8kEQGxs7EjQCVBUVITP56OiomJM4FlVVYXdbmfhwoWj2l0uF/n5+QBcf/31XHDBBezatYtFixaxfPlyZsyYcVz34XQwIYHntGnTqKqqEoHnacMnZav1jZ/Fz3x0UNf0uTRdKXulVO4kqlDKDBicwjt7mnl/fxs/XZRGbLCB6N7tRPt9wDkAeDw+3i1tJdigYVFWODeemQKMfnLcbXPy6tYDzE+1klTzkfSEWa6SSqnEzZAy5jpt0vrO0hch9Sxm5a/46ktUaCAg+EhSovHsfwPsHTDthlFB9MPvHUCnVnLz/PGfcjtaDqBtK4b0s0FvHXcf4fSzb08JfQEvj2l3u92noDeCIIyr+XNo3gWh6dBcwsZmP/b+DhZGw10p4di6W9n78VbybZ+i0xmwOTwYtPBuaTM7a3ooSuki1dQBIekQMv4SDJlMxqzUsGP3IXGetLRDBJ3Cd4xWpfhWRjpBGu30eDyjkgn5/X40Gg2PPfYYZrMZnU53wueVy+WjpuvC2PfpNWvW0N3dzZ/+9Cfi4uLQaDQUFRXhcrmO6zUUCgUffvghW7Zs4YMPPuAvf/kLv/rVr9i+fTsJCQnHfX6V6sjn5cOzOcdr8/l8x38DjmKzSUsF1q5dOypYBdBopHXsZ511FvX19bz77rt8+OGHzJ8/nxtvvJHf//73X+s1v20TEnjefPPN/PjHP6atrY2cnJxRPxQY/cRA+BYYI2DmLdKIX9lbUltErrSm8ovUJogqkKYgAeitDCtN/OWDSlr7htlQ0cn8tFBigw3Q3wItJaCzQvwslEo5v1ichqVzh1RWZZyRxy0H6lEU/5Pq/kkkzb8YNGbpHI3bpZqflhg48BZUb4CA0DHTcw+r67IRbNAemXZrCIbCNV9+H4KSwBDCFyuI21wejvUnorZzkGffLmauah+zUxYeYy/hdOR1O1mSFzGmfdNLx06sJQjCtyxmmjRltnwdNO0gXtdB9aCSNpef6DgHDc2drOuKJzAkhzCdjwee20ByRi5KuZy6PgfbtbNIdX8oJc07XLfT7ZBmzQx1SXWiE+Ycc6ZLQ5eNQEMEBotYpiEIx+LxeHjmmWd45JFHWLRo0ahty5cv5/nnn+e6664jNzeX9evXj5luepharcb7hTryISEhtLW14ff7RwK33bt3j9pn8+bNPP744yxduhSAxsZGurq6TugaZDIZM2fOZObMmdxzzz3ExcXx+uuvc8cdd5yU8x9LQ0PDqOy/27ZtQy6Xk5aWNmbfzMxMNBoNDQ0NzJ0795jnDAkJYc2aNaxZs4bZs2fz05/+9L878LzgggsA+MEPfjDSJpPJRv5RffEfnfAtcdmhqwo6y6WyKEcFnpsPdtDS3s4FrreQh2WCWs9Tm2rY09jHxVOieWt3C1PjrfxuZQ5Lcg4FpTIVuO00dvQiM9uJ9rWRXPkGeJ3gDAdDGJhGf/BfkB1LaddUEpPSAaU0xWmoA0IyQGMCnxd3WzmdPjOqzDWEhI4dhaztGORXb+5jZlLwoVHV4xQzZdzm+887dl1TjVJJoy6Dg7FTmW08sTUJgiAIwlfQWQAltO6FwCRUySuQbVuHc7iXocF+4ovOJ63ZRKRqJ/KKt5mlDmBLSyRn5EWRHZXFWdnhlB7U0l+7i+mul1DmroTdz4JMAQoV1G2C0MxxA8/mHju/fH0fUxKs3LpA+hBY2zFIZYeNhZlhyOUTlvhfEL5T3nnnHXp7e7n66qsxm82jtl1wwQU8+eSTXHfdddx7773Mnz+fpKQkLr74YjweD++++y4///nPAWk94qeffsrFF1+MRqMhODiYefPm0dnZycMPP8zKlStZt24d77333shUVYCUlBT+/e9/M3nyZAYGBvjpT396QqOr27dvZ/369SxatIjQ0FC2b99OZ2cnGRkZJ+X8X0ar1bJmzRp+//vfMzAwwC233MJFF1007jpXo9HIT37yE26//XZ8Ph+zZs2iv7+fzZs3YzKZWLNmDffccw+FhYVkZWXhdDp55513Rq7ju2BC/qrW1taO+aqpqRn5r3CKBATC1B/C3J9D0gKwdUFTMbiGeWNXPS/sqKdHHQmWeKjeQGlDO9trelCrFNx/bha3LUw9EnQC6C04fHJe3dvJu5uKcdR8hhuFNCXV75Pe/D2jpynodFqmFhQS3PU57PwnlL4CA03QfRA+eRB66igLOYvHBubwbpMS7L2w+zkpYAZwDhJsUDE9MYicqNF//CZCpFXHE6sn84N5Y59MCYIgCCeBcwCi8mHSZUT6WskJdKJ0DdDW04feM8BlcQOYOj7HYA5luqmDBZ1PUVrXyzmBLTgGu/nPPjcHahtpb6nFPtgjrfO0xklJ6oKSpJk047Aa1BQlBZETZRlpe213C/+3uY6qjrHZcQXhv9WTTz7JggULxgSdIAWexcXF7N27l3nz5vHyyy/z1ltvMWnSJM4880x27Ngxsu/9999PXV0dSUlJhISEAJCRkcHjjz/OX//6V/Ly8tixYwc/+clPxrx+b28vBQUFXHHFFdxyyy2EhoYed/9NJhOffvopS5cuJTU1lbvuuotHHnmEs84666Sc/8skJydz/vnns3TpUhYtWkRubi6PP/74Mfd/4IEHuPvuu3nooYfIyMhgyZIlrF27loSEBEAaNb7zzjvJzc1lzpw5KBQKXnjhhZPS12/DhIx4Hs4YJUwQnxcG28AUKU0nOhFak/QFsO5X+DoP4I+dye2hZpqCgwh2t0mlU2o/ZX7wlQzFJJAeYUavVkpJIOy9oLfyZkkTsYpE8iavJqY7lnSqWb+1mJ6E87giIgcUaqm8ynhrZuQKaXvcTEhehE+uQF7ynLSvzkpKThxFinamxAeCu0eq6xmcKr1+8ZMYowqYGp/LgEOMnAuCIHznhWeDOkD6W7/vVSyBybjdwRgMGpxyDXsPVBPvUhESn0tk5ToCLEPMSe7GVfI2r/VnExg0naJwOb7BLjY/9yADyStYaq5F57VB7kXgGBh3fb5erRwza+b8SZFkR5pIDhVJ6AThsLfffvuY26ZOnTpqjeb555/P+eefP+6+06dPZ8+ePWPar7vuOq677rpRbb/85S9H/j8/P5/PP/981PaVK1eO+v6L60SPlpGRwbp16465/eucPz4+fkzbvHnzxu3H9ddfz/XXXz/ua3+xFqpMJuPWW2/l1ltvHXf/u+66i7vuumvcbd8FE7qooaysjIaGhjGLc88999yJfNnvv+ZdUPURZK+QEip8HT4fuOx0KiP4sC6A6FAT86bkwMFWqRh3QBh2VzYJCj9Ktw2qt0D7HtCHYMu9kld3NnOxbiv5kQ4umDEZjzyWz/stqEwh4PNRWllB+aAeX2sDC9JDKG+z0dBjZ9WUGOQh6VK//X56yz/jwI53CVGoiFtwDUN+A1aZm3Nyww+txYyCGbdIa4DcwxCcDKYIPtrcgLmvlDlRS9FavvBUyuuW1rKaoyF22je+3YIgCMIEssQw4JFTV15JcN4NRPbvJULWgdsSxYYtm3m5M4HMlAu5LScbjKGYHf101O/CVb6J2KRkLPZisqfNpaq2ltSeV2mv/g9NuctICQ6D6o3g6IaiW+Crps427ybBOUBC9pxv57oFQRD+y0xI4FlTU8OKFSsoLS0dWdsJR7I9iTWe35AlDiLzpaRBX5dcDlOuoqHJzqZyJYV6K/Oc/eDoB60ZplzJhYf37a6Ftj1giYWwbP6zrY6MSCO5OctBJ5UnUQJXLjq0htIxSOmW97GpgohP6UA51EN/l563ezOYnxlGqPFQaZXuavRlL2Ic7KVp8m08tWWYpvZNPJa8E1NsFqRJi7xRHdpfpYMsKcPtFZm7UZXVoO2rhC8Gnj6PVJdNdXLm5wvC8RocdrHqkfdHtVV1H1/WPUH4r9ZVjbO9gv7YfCJjZ4CtG8X+l8lr2IvCciYJU+ZL71sRk2DrX/FqQtgTeTHbalxks40nNHHMm7qUGF8j2v5BQqYtA4VCSnTnHv7qoBOgYz8MdUoZ1kVNaEEQhJNuQv6y3nrrrSQkJLB+/XoSEhLYsWMH3d3d/PjHP/7OZF06rRlDIW3JNz9PRC5TImDK4Zw7fr9UjqRirTRNNmaq1B6UAFN+APpgkCtoKd6H1+MjOib+yLmcg1IyB7Ve+so4j5DuUhLa1hOQM4uijBhiLRlHgk6AoU401hhypl0N0QXs/7gSj9uIMiQRDF8eVMel5EJgwPhrd1Q6mHYtyMUHB+Hb5VeomX7e6lFtn+6+9xT1RhC+O0wpRUwKiUVliYYtfwGZHHncbDr9cfSpMjDUfsDbn9rJzptCgnOQiIQCgiNy8W3fx2BgAZvbtEx2eNHMvJEwn1cKOn0+Kc+A9TiX/2Qtl2bMiKBTEIST4L777uO+++471d04rUzIX9etW7fy8ccfExwcjFwuRy6XM2vWLB566CFuueUWSkpKJuJlhWMZaJMCw5AUcA1JqeaH++DgOikR0OE3ZZlMCmr1wdJ6m6MZjtRAu2tp5pF2v1/62vk0aK1QcDk0buNSw07eGQriQK0bpS6ZhOBArO0fQPDSI9kFXTZQa6V+ATedebgG2/jZZ0eRy0eOw2mDvnp6dIlsqe1lXlooBu2htaU+n3RdJ7oWVhAEQfj2KFSoguKl/884G/a9CqYoss65jSyfj5p3f0dgRydlOisJIekglzGt5d9ksofq2J9z8YKsI+W1DrN3QfV6CM+RciJ8lS++7wmCIAgn1YQEnl6vF6PRCEBwcDAtLS2kpaURFxdHRUXFRLzkd8tQt7RGM3b68T+J/SZqPoHeepqzfsjA7rdIU3chTz8bGCcYc9khfhYEJeKo3kxDXRWmwvMJtxhHdlErD01Zcg7Czn9BeC6E5UojnQDmGBxBmWxttpCeEkK0UQGDHdDXCB7nkcAzfjYkzJWSCjn6pSBxnAQQI2xdoLPQ7/SjVsrRqQ/V42zZCXVbKFHO4d9lchQKGWdlR0jTq4qfkrIapi7+5vdREARBmFAtPTbk8mDCg1LxN36Op/gplIGJxMrs9Km1lPUM0JM3F/emP2Olnw5FKHv27SM5NWvsyQyhkHMhBASPNHl9frZVdxNh0ZIYIhIICYIgfJsmJPDMzs5mz549JCQkMG3aNB5++GHUajX/+Mc/SExMnIiX/G5xDkJPrZSp9dsIPBPmQEQ/r5X20tto4sq8cGJD0yE8c+y+Bz+UnhLPup2h3na6Wmqxx3SwvqydnmEfNye0QVcFTLqMjQe7mCwPIEClPTItF6B1L2qdAb0lmP6GPWx48z0WrroZim44su6ypw5KX5LWcYZnw/43wdFz7AQQ/U2w69+4YmbwbGMUkRYty/OjpW3huaDUk2dK4+KAfuYEDcCejZB4JugCQT3Ohwuf91DyIkEQBOF04HK5WP10MQl6L/8b/glOp50en5kApxezoxtD6kXkNZXR0D8FdVcbfqULpTWCczqextBfANpxatkFJ4/6dsjhobihh1SnUQSegiAI37IJCTzvuusuhoaGAKlmz9lnn83s2bMJCgrixRdfnIiX/G4JjIcZN41b0PpkcHl8fFLRQaxVT0akCcxRYI7ibNkg+4O1RGZFHTvRQtIZ4HHQ7/SxzzCDmLlTiKt7iaZWIzv8k3HF+sEr54E3S3m7rI+zsgt4aHrekeP9frC1IVebWJGdQcXBSiyh4ey0h+BrGmZKwqHAU6WTkiMdntoUkQdu+7H7pbNCeC6qwDhy/QFY9OrR22KmEAysKDBJtUn76sHngkkXjz1Xb51UPzRtKYSNE3wLwinU0d3DqqtGp5UPsRh57A+/O0U9EoSJ4fH62F7bTbRVT1xQAGq1miizlmi9nb7m/aiVCvbLC9BZpzIr0EZqSBJYFLjiwtg+6Uacla9xsNNPpPUMZpmOL9meSa/i0qmxGDSqCb46QRAE4YsmJPBcvPjItMbk5GTKy8vp6enBarWOZLb9rzdBQSeAw+Olqt2GQiaTAk+A6k9IaN5FglwJrtWg/MKU1oFmaNgGCfPAGkdTSz+7GgcITLeiCEllYXwkRnsEv1pfTXZUPB9U9pMQEsDM5ODR55HJoOBK8DjI1BjInJkPwz282N6PR65hSkKgtJ8xDAquOHJcZB5jNBXjqN3Ce4p5zMxOITRjGTJglrtMqmPqmzc2UHXapFqj+Vcce02PzytN++2tFYGncNrxyVVMv/SOUW3bnnv0FPVGECbOoMPD57W92Jxe4kwKGGjiX4W10FvPfoowONoYsk7lieowknNnEr7rDyCTozZFUqhqZIs2llZXAN0Rc5nlccHn/yfVhw5N+9LXDTk6yZ0gCILwrZnQ1G1VVVVUV1czZ84cAgMDv7S4q3DymLQq1syMR6s8Kigb7pfWPFoTxp9iauuEzkoIy4GAIGo6B1HI/GRGBYP8HDSAsbaLWZ7tJPki+MGMc8mNsVCUHAKAw+3F4fJiCVDDYCvseQ4SF4ys+zw7JRBV2UtQkyMlemjbA1GTpT4d/ADiZ4I1Huo2QW8D5KwEmZLyTif/qWuk0a7llgWHkg91VkB3Fe2WPIKsVpSKo66zuQS2PS7V8Jx0KcQVjb3WgGBp+pXGdHJuuCAIgnDCrAFqLpkWg1Grgr3PQ83HeF3D+Ia6SNAE4h1oJFiTTKAhDn3Pfuiphqhp4LKh9/QybdmVFMi0BGiVYG8/lCvgSPmid/Y009Bt54YzU07hVQqCIAiHTUjg2d3dzUUXXcQnn3yCTCbj4MGDJCYmcvXVV2O1WnnkkUcm4mWFoxg0X/jRZp0Hmeceeypr5CQp8NNZAHh2eyPlrf2cNymKuGBpdLYgIZiCS28EhYpsc/Sow7ftO4ivdjNT5i7BOFgvBboypGmtoekEBASA1iglEqrfIq0l1VqlmqEDTdIHBpACUWc/2HugbS+xeWcyyxjA2blHTaNKW0JTRzcvl3QzMxmmJgQd2RaVD5lnQ18LeBzjX6vWDEU3iUy3giAIp1iY6dDyC68DkNHv8FIfdh7GvkosBhmTsrKYFeiDmkPZ8OVyKUfCtGswKo6aLmuKhFm3jfq7/vyOBkqb+1mUFUZymHjQKAjCyRcfH89tt93Gbbfddqq7ckLuu+8+3njjDXbv3v2tvu5xVFQ+cbfffjsqlYqGhgb0ev1I+6pVq1i3bt1EvKTwVWQy6Q17uFfKqrv/TTj40eh9DgWdAFfNiOO2+WkjQScgrd+09wKH3vj3vyklSgIS9UMk+GrR2dvYX9dC3bAOglMgegrIlKDUQOFqKZMvMlCopem2vbVSRtwIaartcNyZ+KceqsFp7yFQ7eX2hekkytuhegMdfUOUd7uxBoeTF20hLugL6e81Bph8Ncy/S1qv+mX3QxAEQTj1Osrxxc6kJf583EHpmLAzPPl6grIXYnD3QvHTeIZ68C28H99AKx1lG9ld1ykdO9Qtva/BmL/rV82M5/b5qSLoFISTpK2tjVtvvZXk5GS0Wi1hYWHMnDmTv/3tb9jt9lPdveMWHx/PH//4x1Pdjf9KEzLi+cEHH/D+++8THT16VCwlJYX6+vqJeMn/Tp0VoDGOWsv48YF2TFolk48eBTzE5/Mh3/cGuAZBYwaf+8hGew8MtEBYFshkLM6OZH9zH797fRuJyg4uWLZMmo778QPS6GjyAug4ANGTQWMkNq0QomIgIIR9LVYCDAU4+/wYOjuJcjdBwmxp9NMcC8lnQkyhVBu08sORfnQNOnl+RwOF8VZmJAXDzKMy3HYegI4y9vRHsK9bxtWzEjgzI/TY9+bwBxBHP1Sth8h8CEz4Zvf7ZGovk/oYOk4WRkEQhP8Wbgfsf51hl5f1/jOYFHEmOa4SnmnoxtS4nhC9HGd/F4MBkfgrdxPldVAbs5wBp1wqwbX736CxwOQrpfO57NJ7U1gmCzKPzJTx+XzIjzXjRxCEr1RTU8PMmTOxWCw8+OCD5OTkoNFoKC0t5R//+AdRUVGce+65p6x/fr8fr9eLUjmhqwiFb2hC/goPDQ2NGuk8rKenB41GMxEv+d/HZYd9r0PNhpEmh8vD01vreGVX85jd//lpNb98aTu2gBhp3WPqYlDqYbhP2qFxBxx4W0oydMg7e5qx1ezAXrpWSsZjCIH0pRBbhC20kFdUS2lwm4+8iCEUZDJWTkngrIIkntxUx2+r4nhTtYQhWz9UvAdNO0ClBaVWqumZtwrSloG9F51aQbJFTlLbOmgrHT0tOGk+FF5JXnIcZ+WEY9IdZ0ZCx4C0dtXWPtL0wDv7+e17B47v+IlS8wnUbDy1fRAEQTiFSpv6eObzVj7xTaK6tQdlWwkhMSm4Cq7mwwPt/FGxhg6fAYdMRZ08kaDO7ShdgxSkJ7LAvw2aPofQrNHJhDoOSHkDOo/UDH+5uIHr/rOLui7bKbhKQfh+uOGGG1AqlRQXF3PRRReRkZFBYmIi5513HmvXruWcc84Z2bevr48f/vCHhISEYDKZOPPMM9mzZ8/I9vvuu49Jkybx73//m/j4eMxmMxdffDGDg4Mj+/h8Ph566CESEhLQ6XTk5eXxyiuvjGzfsGEDMpmM9957j8LCQjQaDZs2baK6uprzzjuPsLAwDAYDU6ZM4aOPjszwmzdvHvX19dx+++3IZLJRSU83bdrE7Nmz0el0xMTEcMstt4xU6QDo6OjgnHPOQafTkZCQwLPPPvuV923Dhg1MnTqVgIAALBYLM2fOHBmE+6q+gjQ6+z//8z+sXr0ag8FAXFwcb731Fp2dnZx33nkYDAZyc3MpLi4eOebpp5/GYrHwxhtvkJKSglarZfHixTQ2Nn5pX//5z3+SkZGBVqslPT2dxx9/fGSby+XipptuIiIiAq1WS1xcHA899NBXXv8XTUjgOXv2bJ555pmR72UyGT6fj4cffpgzzviS6Y/Cl+upheoN4HXjVepoiVqEO27OyGatWskNc5O4YnrsmEONGiWz2I2yZQcEpUJPFZS+AE07pR2ip0LaWWCURk9/9dpeqjpsWNOmEV54jpSQR66AqT+C1EW8X9bJHzZ18vyOBl7b1cQbJUcCVoVchkIuY2lOBDnxoXT6AvAEhEPG2VK9T9cQG//zIH/+25/ZeLAHyl6D0pcI0Cg5KyOQMG+7NH3qaGo9GMIIVQ6THqTmuFliYPr1EDMN+pvB1kV52yAVbYNffexEyj4fspaf2j4IgiCcQh6fn8aufg5UllMhT8ImM6Db/STqfS9xn/k9lsWDM2IaDqWZoPhsmlKuYEPa3cgjcpH1NUB/I7SWQl8j7+9v5dlt9XhDM6UZNsojyzB0KiWBAWqUCjl7G3u58G+beXjdKX74KAgng3tYSqroHp7Ql+nu7uaDDz7gxhtvlHJ2jOPoAO7CCy+ko6OD9957j507d1JQUMD8+fPp6ekZ2ae6upo33niDd955h3feeYeNGzfy29/+dmT7Qw89xDPPPMPf//539u/fz+23387ll1/Oxo2jH9r/4he/4Le//S0HDhwgNzcXm83G0qVLWb9+PSUlJSxZsoRzzjmHhoYGAF577TWio6O5//77aW1tpbW1daQ/S5Ys4YILLmDv3r28+OKLbNq0iZtuumnkta688koaGxv55JNPeOWVV3j88cfp6Og45n3zeDwsX76cuXPnsnfvXrZu3co111wzcq++qq+H/eEPf2DmzJmUlJSwbNkyrrjiClavXs3ll1/Orl27SEpKYvXq1aOSuNrtdn7zm9/wzDPPsHnzZvr6+rj44nFKDB7y7LPPcs899/Cb3/yGAwcO8OCDD3L33Xfzr3/9C4A///nPvPXWW7z00ktUVFTw7LPPEh8ff8zzHcuEjEc//PDDzJ8/n+LiYlwuFz/72c/Yv38/PT09bN68eSJe8r9DxwFo3QNh2ZQPqPig3sAZ2gAmHVUZZXpiEBvWr+Un7/o4Y2ohy/KiYKiHVfKPIM4PYTOldZCBiRCSDgolDPWAWgcqPXRXQUgqbq+H/a2DDLn03JbTCPteg8LVuDw+DnYMsCArjA6bgwUZYVR1DCE/6g/Oxop2GnqGWTUllnlpR6bDejWZ2FxezEoF/cYUet1qPH4g5tC6z65qKfGPKRJXTyO+CBtavbTG1Ofzs7e6kfjqf2OJzZESJR0vnRm8HtjzAgSE8OeLVyHnFK/xNB5fzTlBEITvq/xYK+lWORv+/SzTfC0EqPwMDYVR5rUSoXIzbNYTYMghOjYG4qax/J978TgOkuirJzbnItZ+sgFrwz6i505Gq1QQoFEiU2ql97TazyDgWggI5Oy8SM7Okx6qtvcP02t3Mez0nuKrF4SToKMcKg/lTonKn7CXqaqqwu/3k5Y2ulRRcHAwDoeUyPHGG2/k//2//8emTZvYsWMHHR0dI7Mcf//73/PGG2/wyiuvcM011wDSiObTTz+N0WgE4IorrmD9+vX85je/wel08uCDD/LRRx9RVCRVJ0hMTGTTpk088cQTzJ07d6QP999/PwsXLhz5PjAwkLy8IyX6HnjgAV5//XXeeustbrrpJgIDA1EoFBiNRsLDw0f2e+ihh7jssstGkgSlpKTw5z//mblz5/K3v/2NhoYG3nvvPXbs2MGUKVMAePLJJ8nIOPaSqYGBAfr7+zn77LNJSkoCGLV/Xl7el/b1sKVLl3LttdcCcM899/C3v/2NKVOmcOGFFwLw85//nKKiItrb20euye1289hjjzFt2jQA/vWvf5GRkcGOHTuYOnXqmL7ee++9PPLII5x//vkAJCQkUFZWxhNPPMGaNWtoaGggJSWFWbNmIZPJiIuLO+Z1f5kJCTyzs7OprKzksccew2g0YrPZOP/887nxxhuJiBAfuI/F7/fj8flRHS4P0t8E+iBQSVn/KgMKkcWkkGIIJt7Vyox4AwkhRwIzP6BwDmBs/pRshx5lM6x121liewuFxwax0yDx0C+rrROsSYAMip+EkDR279qK0dWBZskDPHxhAfe+sYdum5sOrIT2VkBfI8UlJWyt6Wfq7MVcP09KUZ9iBuo+g4FJIJOTUPk0MvNUZLLRI6/3v1PGzrpeHrusgHNzwji3rx5SraAMl6bEbv0rBCXjd9no3/UWw7WlxJ7zS9BZsDk8bKobAnUKk2RKGGiF4ywYDkgBdvJ8UAUQZDiJ071dQ6Ae5+lfX4NUruWohE2CIAjCaDqjmbiYOAz7XsMfkUul30Scax8N2gzWVwxwhuM1wpUN1O/9jBmh89A7Bwg7+CGe9gjcnkxaFZEktO1i7tR4MMfArn8DPkg6U/r7a+uCxu0QNwP0Vgrjg1h362yxDkz4fghNP/TfU5MvYseOHfh8Pi677DKcTicAe/bswWazERQ0OtfI8PAw1dXVI9/Hx8ePBJ0AERERI6OHVVVV2O32UQElSNM98/NHB9iTJ08e9b3NZuO+++5j7dq1tLa24vF4GB4eHjOK+EV79uxh7969o6bP+v1+fD4ftbW1VFZWolQqKSwsHNmenp6OxWI55jkDAwO58sorWbx4MQsXLmTBggVcdNFFI7HQ8fY1Nzd35P/DwsIAyMnJGdPW0dExEngqlcqRAPnovh44cGBM4Dk0NER1dTVXX301P/rRj0baPR4PZrO0pO7KK69k4cKFpKWlsWTJEs4++2wWLVr0JXd0fBP2l9dsNvOrX/1qok7/vbS9todd9b1cMjUWq69HegONKpDWYwLbm4ZxuBWkhLcTsOdppkVPBp30S/npjh04nG4Wz5lJ4Tk3MKlpF9t3bOStDjWFeVl4dUGownM4PP7oad2DvfJTVIFx6BKmgdZCszadmIFmuvZ8SETY5bQNuOgbdrPFFs5yTTMMdJDsrkZtdBIZelS2265qKP4XhGyDnIuIDTYRa+ynr3w92tQz0aqkuqHhJi1xwQFSzTatBewlUpKdqHzQmqSpvgHByAJCcPQ6sPSUQv02SF+CSa/i/ClxmGShsOsf4LFLtT5PROSkb/YD+qL2/VD2FmRfACGpR9qH+6HkOQhJkbYJgiAIx6TBjiMsj3p1Jg5FIJa6lwjW7yE5YDs+nRlkBpT99czxv8MWRQH7LQUo2g4yw1BMUE4cCvcAeFx4vD6Uap300C9WesrPQDO07YXAeNBL04NE0Cl8b6h0EzrSeVhycjIymYyKiopR7YmJiQDodLqRNpvNRkREBBs2bBhznqODNJVqdK6Ow8vyDp8DYO3atURFRY3a74u5Yr449fcnP/kJH374Ib///e9JTk5Gp9OxcuVKXC4XX8Zms3Httddyyy23jNkWGxtLZWXllx5/LE899RS33HIL69at48UXX+Suu+7iww8/ZPr06cfd16Pv1eFpuuO1Hb5/J+rw/f7f//3fkRHSwxQK6TN8QUEBtbW1vPfee3z00UdcdNFFLFiwYNS62+MxYX99HQ4He/fupaOjY8yNOJVZr05nJq2SEKMGlVIOyiCILYKgxJHtS3Mi8Pn8oJVJAWlQ8si2+O5NeD0uZLJZoDWj8LtJm76IFcosdLGh3PJ8CQkh1dx3bhYA9WEL2dwWi90lZ75dQejB9zhr1koGDwzg8/XicnsZHrajVmhYMGsGdOig4i1CNWZCrS7o34vfPI2qThtR2mD0Ogs+tYnBD/4HfVgiTnSU1ezHpchlXnoY2Dq5fmoQBBwq5K3MlRIN2Y6aG39UYBiz4DopmPV7jmy26AG9tDZSNzZr77dOa5Ey5Wq+kKpfa4KkeVLWXkE4QW6Xm3VvvjyqrWlPySnqjSBMML+fMMUgPmsCth4Xoa4d9CUsQ+ZzYnR3Y/DakamNhBhAHRBIhLOCDm8Y3f12YvwDKMxGKFhNjyaKFz+rZXL8mUw5Oqt7RK5UuutYf4+PNWtFEIQRQUFBLFy4kMcee4ybb775mOs8QQpQ2traUCqVX2sNIEBmZiYajYaGhoZR02qPx+bNm7nyyitZsWIFIAVVdXV1o/ZRq9V4vaOn2xcUFFBWVkZycjLjSU9Px+PxsHPnzpGRxIqKCvr6+r6yT/n5+eTn53PnnXdSVFTEc889x/Tp04+rr1+Xx+OhuLh4ZHTzcF/HmxocFhZGZGQkNTU1XHbZZcc8p8lkYtWqVaxatYqVK1eyZMkSenp6CAwMPO5+TUjguW7dOlavXk1XV9eYbTKZbMwP+6v89a9/5Xe/+x1tbW3k5eXxl7/8Zdz5yQD79+/nnnvuYefOndTX1/OHP/zhO1PUNTPSTGbkUVlik+aN2j4yRdTnHRkFPSx+5oXgPxTgD/dCbx1B7mGCAjvwaS/j4mQ34apm8Eojc3ERYbQNK+js6maweRN7WjUk17YyKWeZ9FS4Zh1/S67EM/VaDDo1WOOkQLezQqrdued5Or06Pq6GjLgIHKn3UtLQxWTvABkOH2F9BwmKL0J/eGR0z/PSGtKIXGmk0Bgu1fgMyYQN/w/Cc6SMuYcpVDDlB+PX2zzeKSXuYXrLN9BnTCUhPulIu3MQKtZBeO7obIgnyhwFeeMs1JbJDtUrFYSvw8+SvNHTyJ/Y6DxFfRGECdTXCOVrqepXo/HYSdMPEGBQ4x2upVmfxW5HOJaEXAr7PkavM6IvuAz6arHue58Go4rGgEwCLVEgk6EvfYap/kDC+kwwVCglpFNppb/HxvDxX7+nTlr7n7r4Wxk1EoTvsscff5yZM2cyefJk7rvvPnJzc5HL5Xz++eeUl5ePTEFdsGABRUVFLF++nIcffpjU1FRaWlpYu3YtK1asGDM1djxGo5Gf/OQn3H777fh8PmbNmkV/fz+bN2/GZDKxZs2aYx6bkpLCa6+9xjnnnINMJuPuu+8eMwAWHx/Pp59+ysUXX4xGoyE4OJif//znTJ8+nZtuuokf/vCHBAQEUFZWxocffshjjz02MsX02muv5W9/+xtKpZLbbrtt1GjvF9XW1vKPf/yDc889l8jISCoqKjh48CCrV68+7r5+XSqViptvvpk///nPKJVKbrrpJqZPn37M+OnXv/41t9xyC2azmSVLluB0OikuLqa3t5c77riDRx99lIiICPLz85HL5bz88suEh4d/6VTj8UxIVtubb76ZCy+8kNbWVnw+36ivEw06X3zxRe644w7uvfdedu3aRV5eHosXLz5mFim73U5iYiK//e1vRy0a/t7oroVNf4DO8tHtlliwxkPtJuirZ2fEhbzZn0S3JhK5XM5ZlmaC2z7js5f/RP9n/0COj5d2NtHT3kCcrxlTSCzJNc/AgbekTIEtewho+xxz46fS+U3hUHAFzPkpGKMAP0F7/5fz3WvJijTzn2217CmrwBZWgCYoCYVrgLSwAGICDz0Vi50GagMMdcFQp9TP0ldh/X1w8COo/mTstcrl4weeh3QOOKjrGjrmdtrL6Nz/KWV7ihl2HfXvzm2XaoraO4/jhguCIAgTonYTFD9NjGaAYH8POr8d+UAzSkcfka5azJ4egvY/x1BHDY6uWtj6F2jehdoUiEKhRBeVCxF54HWj9QxSqO8i2rYPdvwDqj786tfXGEdNwRUE4diSkpIoKSlhwYIF3HnnneTl5TF58mT+8pe/8JOf/IQHHngAkAaY3n33XebMmcNVV11FamoqF198MfX19SNrEY/HAw88wN13381DDz1ERkYGS5YsYe3atSQkfHlN9kcffRSr1cqMGTM455xzWLx4MQUFBaP2uf/++6mrqyMpKYmQkBBAWke5ceNGKisrmT17Nvn5+dxzzz1ERkaOHPfUU08RGRnJ3LlzOf/887nmmmsIDT12TXm9Xk95eTkXXHABqampXHPNNdx4440jiYKOp69fl16v5+c//zmXXnopM2fOxGAw8OKLLx5z/x/+8If885//5KmnniInJ4e5c+fy9NNPj9xvo9HIww8/zOTJk5kyZQp1dXW8++67J1wfWeY/OvfuSWIymSgpKRnJ4PRNTJs2jSlTpvDYY48B0vzlmJgYbr75Zn7xi1986bHx8fHcdtttXzni6XQ6RxZFg5SFKiYmhv7+fkwm05cceQoMtEDlB9JoqDV+1Ka739hLZttbhCgdDIYW8n5nENcvyiEvxgodB6h+/3Fq3MHodHqsFiufa6ai0eq4JF0uTRvd8hgEp0oJGao/g/pPIaYIks+QEjPoLJTU9xDjqSO483PsB97HiwLj8t9RvHM7+roPyYyNwJe/hn5tDFbjUfPwu6qg9GVpxNPjAEsi9NVB624pk23iGWOeOHs8Hl7/rIS5shJCcxdK01qP8nJxI819w1w3PRRt42aIzANztLTR7YAtf8GGlvbUS0mKCGLI6eGVnY1khBmYGqOXRmC/JLAVTg9f9/czPWcS146zVuOuX93L//zm18fVfiL7Hqv94V/fS+u/bxizb8QVj/Oze4/vHE/8+c+Ul+4es68gnGrf6P1z36tQ/DSEZeEaHkDRUoJXbWAoIBY/fgLaS+i1ZKHCg9w9CAGhNBgnccAyl3mJJsLNWkAuPRj1+8HRB/YeGg6W0uANZMq0mWiUiom8fEEQhNPO008/zW233XZc04C/bRMy1XblypVs2LDhGweeLpeLnTt3cuedd460yeVyFixYwNatW79pN0c89NBD/PrXYz8AnpZMkTD5ynE3KeRyNqjnsti/lez6/zB/2kpMkVIaaqwJJE09B5PNibf4KYyDw2TOT8bW34l3fwuvKpdS2rWAG/JziNC44MBaCMsFS7RUwiUomZZhNf9vXQX5sRb83iKsch2z5KVkOgaYnDsJwlVgiefFKjnv7t/NXUvTqe4ewqRVMSspEbJXSqONFe9CUApkr4DsFdR22Vhf1s65RgehJu3I9byzp5VXd1RhMBzgrPSiMdc7IymIQYcHratHSh6htxwJPJUaSJyDQWPBECqt95HJINTbQXTZc2BYAWGZo09o64KeGmn9rOL7nXzC4/Hw7I4GzkgNJTbY8NUHnELfqd9PQfgv841+PzNXSLWjB1rxdVXh7axCrg9CPtSJTRuKTq6gR5/ItoAzcLSWEznQSH3nAG0xEOPYSV/tWzRr09gUuIJFmWEU9b8LFe9hS1xDqSuSHLdPBJ6CIAinkQn5dP3YY49x4YUX8tlnn5GTkzMmc9V4GaPG09XVhdfrHTM0HxYWRnl5+TGOOnF33nknd9xxx8j3h5/Yftfcd242APVb2jA3t2DsOyDV/ozIlda66MyENLwH5gBcAQmU96uobXCi8ARQaqsiqusztpV4WDF/DuReBMPdkDAXvC4whhPq8bEsJ4z4ID1ba3spJp0Vy85FFmiROnBovWRa+w6Mpr2YVCl021zoHJ1wYDPEz5GSC1liQW/l6S21uL1+LFoVHx7oID7YwILMI4HnvPQQdjfnYEqeBeFjfx5RVv2h/zPBlKul0jOHyWQQMzozl16t5Ky8WKiMAqWWMVpLoKlYenpuiR27/Xvk+R2N/P79SvY3D/DwhZNOdXe+1Pfl91MQvo++0e+nXA5xRVD9CUPt9ahkSpR+Oa3mSfytfzo3h5roaa1BH5lCxtxz2VHfj8PjRzc8SEDLJpQqDXXGPF7Z2Uj/sIuiwhgISSU4OJihai/lrQNMSzwNEtEJgiAIwAQFns8//zwffPABWq2WDRs2jKT5BWnu9/EGnt8WjUYzJj3z6c7l8bG9povC+ED0OGnasx6NUkmIq5G4pDn0WILp9vsJVuqgq5pKTwgRfg1GazzkXMRbG3egqdhLvLeOzvB5/DB8AJ2jFLM5AzxOqpVJ9BFCodYMcumJsVIpZ0NFJ22DTn68MIWfLUiE2k/BFw/BKSN9KzD1UxDWAzofl06JRla+G9oPSEmBAgJH1tNUtQ8y7Pbxm+XZxAXrKIgZnRXLEqAdCaa/TF2XjRc/72ZprpqcKMuX72yKkEaMvR6oeE8aIQ0/VAspZppUB878/Q9qzkgPYX/LAMtyT/+6ut/F389vy023/5TOvsEx7SEWI4/94XenoEfCf5uT8ftZqUyB2CWEl/0TlUqBwjfMhab9bBlOYnKQj2RtFfKKGiKiprG/ZZCY/Kl4Pg9lf/cgCdGR3BBoIsyswRWfhzr5DPRODznOLmLMKvC6pWR1zkEpkVBYthTsCoIgfE9deeWVXHnllae6G+OakMDzV7/6Fb/+9a/5xS9+ccKLTo8WHByMQqGgvb19VHt7e/v3M3HQCfjoQBtrd5RjPFhFaHQCOzd9gCk8gTMSDdBcTOWuElxOJ7PiA+iXmXmw9QyuNWyiSNcMQ13kuFuxm5LISZkDw11Q9iZo/BAcD2Vv0Fe8laZBSFZcgDl5Ovi9oNQSa5ZT0+5koL8P2tvgs0fBFAUr/ykFc/telTIITrkG9FYU+16D4qegYDW4h6UR2ENZaX9xViZ+/GjVSqYmBH/1RXvd0F0DQUmjpsI29g6zq6GPjAjTVweeh3mGpRqiPs+RwFNrkr7+C0QHGvjtyrxT3Q3hG+rsG2T6pXeMad/23KOnoDeCcIKGemje+TYlVT3kySpRewaRDwyR4Kok1u0k3DwF61AjareWEk88MYPvkdpRiTc+FmfyIhRtzxAna2fAEsbzOxrRKJUsy43EoFGyOCscdv0Haj3HXJ4iCIIgfLsmJPB0uVysWrXqGwWdINXZKSwsZP369SxfvhyQkgutX7+em2666ST09LtrSlwg3p4AgrqbqKjXE5g2A3/cbMiKoaOtCeWAmai2jcjlCnTJMykKCMNgmgcmO8hkpIUOQXeVVNusZZdU/iMgWBr1a9tLWKYCrcOLOTIZ9r8O9i6IyOd857ssy46lYHAzaFYDiiN1LP1eGO6RMgXqrVKyB2sCxM+C6Kmw/zVp7aU1AVRaDGoZNO0CaxzFXQo2V3Vz7ewktNpj/LOs3QQ7/g75qyFj2Ujz7JQQ4qw6ogP14x83Ho0Rpv4QlMdOgy0IJ8PgsItVj7w/pt3mPDkp0wXhO8s5QJC9lpTgcGL6B1DYhnFGTUHbXQ7B4ZgGuvFbE3AN96EJMGHInIZB7UTX9DbMvAGSfw6GMDQDbnqHXBTGWqVyY7uegYBQ6SGoc1Aq22KJgak/OtVXLAiC8F9tQgLPNWvW8OKLL/LLX/7yG5/rjjvuYM2aNUyePJmpU6fyxz/+kaGhIa666ioAVq9eTVRUFA899BAgBb1lZWUj/9/c3Mzu3bsxGAzHLAp72vD5oOoD0IdAdOH4+wz3wkArIaEZnDN3Gg5bOt7itwl31aBNOAu318dLZQ7O7txCTAAQloVWLuPaOYnQZgNtGAx1SGVZWneDrROssVIgZzqUMjoij+jIfKLlCqo6bJjkIYQGWaCvkSRNP+0GLf0tLVh76yFhJpttobz5wuf86rw8zFOvAdmhBw5lb0sjlHkXgz6IcvMcDNVvEl31IWScA7Z2qF4Ppih2lqv4v4MWEoL1nJt/aKprbz10HYSE2VLAaokGS7wUIH/BqAQ5w33Shw3LV0yZ1Zq/fLsgnAR+hZrp560e0/7OjntPQW8E4TQSGI/CFE747nfxBsfg05hw2W1oglJQqHQEeDpoDZuNYrCO3P696OKvBq0HDrwLa38Cyx4Bv59oq56rZiVK5/T5pIzlSg2kLJCm1+55Dopulmp7CoIgCKfMhASeXq+Xhx9+mPfff5/c3NwxyYUeffT4p4GtWrWKzs5O7rnnHtra2pg0aRLr1q0bSTjU0NAwamS1paWF/PwjZTl+//vf8/vf/565c+eyYcOGb3ZhE83nho5yMA8dO/Cs3wJt+6SSJ6ZItAYz8VOXgb0H9FZU7mEWRTmw+EJBJo1u0lzMHm8sQfteJToxnS6bE2d/J5HWWGSuISi4HFSHRv78ftj5NGjM+NV6Osob2B5xFpcF9cPOf6F32VkvPxflcA6XW+LoaG/B37qTNE8XDlc2Zp1amk6rC4K6T6GnFgZbwBrProMywod6iZ4eD8CL5W6sshkskjWwVF9B5KzZLEw5qp5a10Fo+hzCsqS1mcEpsOTBkTWnx1T1kVS+pehG0Bq/6U9FEARBmCBufThetwN1fw1K1wBarxtv9wAyYyh+p4eAipexK4wMhSag0wfiSFxMf00pFk8tmpbd0L5feg8zHlp+I5dD3ipwDUnvlZGTpSzqIugUBEE45SYk8CwtLR0J/vbt2zdqm+xr1E286aabjjm19ovBZHx8PBNQmvTbodTAlB+CQj3+dq9HWpeoPFS7DKQRy+FeCEmVvt/yGKmdB2DuL8AYTv+wh5auXj4t3sdM1zDRYTnU9jdQoc1mRWECATKnFHS6hsDjkqbfdldDwhxkfi8ZYXoS0sPA68cbN5O97hi06mQi03JRhoTRMmjC0+NleWI0Qe5mGNDD/jekdZNxMyA8T8o229/ENN92+g1BECyNPO9s6MPpNrJo2tnEaDYQ8/kfoPJi6UMESCOd4dlHPlDAVwedAFGF0min5qhRUFunNBIbIDIcCoIgnC5KTbOpjlexsOc5rFo9Ho8Clc4EHjuuwDT6B4bwh+ZgjI6AroO0a1N5X7WMuQndpGmUUhZy5TjJjVp2Scszsi849oNcQRAE4Vs1IYHnJ598MhGn/c7zeHy8U9pCRoSRtPBjTPPUfElNxeZi0AeDzA87n4Lci6H8Lan+5NyfSolxdGYwx0qJeLQmSps6+bzOy7nWBkLrSqGtlFxXDXu70/jhS27+sGoS4QCb/gTdByHrIikJ0FA3hKRiNUaCSQPyRLw5lzD48as4lUHkxsdCXxP729wcdGczvWM9lD0DM26B1MVSwiFjGLgdYGtjYHiYhNAQ5LNvB7+Pl196hlhdMhctKgCdFsJypJFN97AUYCuU0ocJ45ckkeprBEPo2A8dgQnS11E6Nj+DRqvDPPeG4/pZCcLppKO7h1VXXTemvWTPXqZfOnb/fXtKuO2qC8e0662hPPjoXyeii4LwtSgHGpjT9AQ+SyS+nmq0pkiGfBpsGjNuvwKzXkNEsBq2/QmUGmLPe4wLrFWYBqvBY5RKaVW+D4GJ0oPKnlqQK6X3FIUWrPGn+hIFQRCEQyYk8BTGV9Vl4/kdjUxLDDx24DkenxcOfggN26SRzYS50LJbWqNo75GS+8iVULcZQjJBY4EDb4E1jkkxVoICNMTLF6Lw1oBKiyZzGbs/GqK334bdPgxmPQQmQeM2sLdJwV5HGQw0Sa+vNoA+ELWjj0x5Mz2Eo9zxNg3NB+kIvp7SViUDzjqcbgdma7xUMqX6Y2nKa8d+uofcfDIUh8UXwJkqDfKmEuLbP2LQ7CXUNEN6jeBkKQlRVxV4HKD4kgAcoLcOdj8vjaomzv3SXfvtLv7VEk24Rc8Vx3/XBeG04ZOrxs1eu7348nH397qd/HF1wZj2257ZddL7JgjfRGFSFEP1qVT2KzEaItAM96D1+Rly+gmwetDr1NDXLCWlcw8jq9pAkHsQIvLAHAUH3pbeNxQaKfAsexPUAVIioZgpp/ryBEEQhKOIwPNblB5u4to5iSSHfUVQ9UWuIWltpypAeoprCIWMZThcHuSTr0Vt74TNf5GyyhpCIH0phKSBUoNBoSQjwgRdndIbd0g6zXYZ56d6yI3YRlC3DSLOh6hCBrxyurVxxOddgsxpk0qN2Lug8wB0VcK06wg+40YWdVYz0JTJjgYv3U4Zj10+mQNlMnAOMDfgUC3O5hLorICQNFRBcXxcGk6TzceUul2Ya9eRF20iq2CSlAiou0r6EJG6BBKdXz7qe5ghTMrAe1T90GMxapXEZhURYdae2H0XhNOE2+Vm3Zsvj2kf6Ov79jsjCN/UUA9UvgeRhaBQETDzOiI++AO2QQd+UyxOrw+/UY3W0YRiaFBanznvJzDYIS2jCAiTlk10VUq5AIJTpSUoPh+kn318SzIEQRCEb50IPL9lZ2aEndgBnZXSmktThDSFqOI98DjwRRVy1xulWPRq7pobIWWmjS4EYyQv7ekmvOp9ZqXuRj55jXSejgPQWgpyFbLOLnTDGhQpSdJ5B9vhvZ8wqM/gDXMeP7A2oqz5hICcpdITZL8f3E4pEN3/OvoDb6PPWoGj8AaWhxmICTIQMWM2fpCmyQ73SUGh1wX5l2EyhnNP8jDddidmVQd4pqIOy0QdkgF1n0kjtRqTNJqrUH3JzThK10FplPRwJt4vIZfLWTU19sTuuyCcVvwsyYsY07r9De8JnWXDrooxU3ZDLEYe+8PvvlHvBOGEeOww0Ax+oGItICM8IAS724TM1ozOOYg7MIUuZTjBSfPZErCAul39XKrbhcocBYZDmc1D0mDyVdKD2cZtEDlpJIeAIAiCcPoRgefprqcW2vdCzsWATyoxEpSMXC4nOlCPUaMCTQBknitNLwI2VpaT0K8nRx2G1eeV3pD1QeDz0G+zET71fEx+BYbwQwmJXMOQdAZmYwJnh0dQ37SP3Zv34uiIJyiojalNT1HT5yOya5CUnk0Qlg2Jc7k8KEEKSnvrUBoiQKWB6k+hYSsUrpGmOR1afxnet5Pw4T5IW3okEZLfz25XNH7DLPKDkqTESR1lkHbWyLUAbK3q5J29rVw9K4HEUCO47FD+rhRsTxpngdvXNdwPu/8jJSeKnX7yzisIE+RYI6H9/b3j7u/wycdM2d323PFnGReEk8IcDTNvBccgNGzH11eLz9YBmkAGdTGojDKG+7txhWQiM4bxXq2X3o5BluVFEKwx0bn1WUIMGshZKS0NSVkkLbvQiRJZgiAIpzMReJ7uks6A6CnSukkYlTTntgw7Q60HcOzoQ6uUSUGY38f9CfsoI5/P/HGE7z/IlK5PkflldPQNsKnfgUrRxzmq7bDzfyE8F1IXwcxbMXicpMiVtO7eTnRYGBUBoaTaNqPz2PCpw9A3bAKTGjLOBuSHMur2we5nwTkkpbBHBl4nOGyjRyMH26W6nT43uF2gMULVR8g+e421+vNpULSQNHSQbF+tlJDoqMBze203Gyo7mZpglQJPtR5yL5LWnh7m90ulY76BZ3fUY6nuY3awH9M3OpMgfFvGHwnd+4bvFPRFEE6Ayw5b/47HBzJlAPQ24FMHoVQp0bUVMxC9kPDeXSgH9/Cz/Guxa/ejTriQ1996jeEhG8mxEUzNOXQujeH4lmgIgiAIp5QIPE83Lju4bNI6TgClGpSB4+7qHOzk420lmGIymWtoht3PQdYKgnpLsfoGeKfVwBnmTjorN6JMPwt/6iK0e0vJdWyB+o3S9FatBZyDMNQJFe9C9kqCzAGkNnxOjn2YkL69uBwDOMLmom7bCxEF/HaHh8zWR0lMziI4yEp4yy6pTtrBdaA0gFzFroMNbCmF6+cloVAoIPM8aQ1q7WfQUiKVjfF50br70PeW09KfgNxSQHbWAlAH4PX5kQFyuYxr56YwJT6QmSmhRy4+KFFa+9pUDAEhsP91KUiPyPvat768V0bxwCwyLdki8BQEQZhIMmCwGe9gO6qOUtxxZ8BAByaNBrlKQZSjBo9MhluppbmhmvjwONp7+rC3VtAQNJvo1IXjn3ewTXpfU4k1/YIgCKcbEXiebg5+CF3lMO16qTzKl1ClnIm+bpiQ7m2QOgv0gVLgOtxLssnIbXNTqapwcdAXgWPAyPyMcJaenSGlmE+eBHFF0onUeih+SkryM9hGT8oqqvZWEdfTRkjkJOzqELaXOvFZ5tI2kMTObgUBpslEObpwDwERuZC5QlrTuf91SJ7P08UWdjU0siQ7nOQwk1QeBaW0ptRlk2qHpiwkVG7lTELIDdNAyx7wz8bv9/P8jgYMGiXLc8PQDTYyMylu7A1oL5My58bNlILoY9U/PU53L82k3+EixKT7RucRhFNtcNjFqkfeH9Pe2Ts4Ia930+0/pbNv7LnF+lHhmHRWmHU7vZ89jQWQ9daiksnw2tzIlFq8Mj/Dk66it6aYHZVN/H1gNpcVxZO98k6WhIURpHJJOQIiJkkzaECaVVP8FEQVSGW9BEEQhNOKCDxPN6EZoDVT3u3h/QMVXD49niDDOMWx7b3Im3aQGhfBoC8OZ1cdmuRo6Ulv6mK00YVEmHUEJYVTXp9EtnkQynbgzbkIRUeZVC8zfialNS18vnsny0ydhPm8UPYG4Uumozj/ZxiVgE6HZctfuCq8jtp+eLktm1XTAomydxJj20VI1FJatQu4+6NeFqZYWBU3Ayxx3HBGBEMNpSQru8DBkSA6LEv6AvD7sXq7sPq7oFUp1SkNyUDWu4Nc9yB2YxZ88hsY6oLp1x05DqDzIAw2Q/JC6G+QpuaGZpzYvXYMQPk7EJ4D4Tmo1QpC1CLoFL77/Ao1089bPab9/d2/mZDX6+wbHLfci1g/KnyZLswMdLdgMIeh9wzh1wXictpxBmXg72+G2k8JN4fiSJ6LsrGSloNdrEzXA1robobaTaA2QeShmS5aq7Q0JSjplF6XIAiCMD4ReJ5uQlIhJJW33zvAG3taiLTouHDyOBlZ+xugeRc28yzWe/Kw1a8jO2oYfbj10FpLwO9H7R0mNzYEempx2nr4sMpOdsps4jVDtLz3Oxyd3UzxDNDjCSEspQiGe8HnISQo6Mhr5V1MXPoAprYG7mj3cob8ffplw5hldmTbHkenMOPvWky/3AeFJghOJR0/VG6j47M+Om1uss64GKLyAfD5fPh8oPQOQelLIFNK9UeDkiEoAWo+IVevgIRgGAgFcxxYpHuwoaKD2q4hVgfVouisgOhpsP0JKbDNvWjUOk+vz8/W6i4iLToSQ8ZZ/+N1w0ArWMYZTRUEYVzjjW6W7NnL9JOY50v477Cn3U2g3YZKYwPHIDKfH9VQB26FHp9zCPlAE3K5m5kZISyUbyNB30Z3mY2uIBspkxchVxsgMPHICZVqSFlw6i5IEARB+FIi8DxVfD4oewv0VkicO2bzZdPjiQ7Uc3Zu1PjHG6OpksVQ5gymHy8/b5nLX1o6yK65X0oWpDFD+z7Y/Tws+DVkX8hQZxO2DiMyayjoXfR6tSj8HhTD3QSFR0JwGkQXSG/eRzNFwtpH0bTuJ4VQeuPzCQ2LotMUjarrAOamT/hlajaBoZFS7U6A+NkQGE9z2XtU+8OJVVo4NBmK/3y0naDmT5g/vRBtZCFETgbvsDQNFyD/MkAm9aPo+lFd2V7TTWlTP2ddMJ3w2Cmgs0Dhammk9wvJhYYcHnY29DLo9IwfeAYEwYybj7+EiyB8x42XBbdpT8kJnWO80c3txZd/474J/2UG2tDv/ich4dHI2zchM4bhN4Qit3fjG+7FGZyN3+9jty+DF7d38sszV1Jmd1Pp7qbXHkiMX47+cIZ0QRAE4TtBBJ6nit8HQ+1SgoVxRFp1XDJt7Ehcc/V+Kre8RW5iJMGVrzA9vJbFsmHyZq4k3bsX+uqhuw766hi2D+KxDdBQ30xWUS6BAYFcHA/4vOCRkZpVyP49PhoMmcSZhqVEPXUbITBJmro61MXumhZ2+NK5JrUQ+VAfGmUIZjXQ30ybLJla3RkszjCTpFYx4LEzED0PU+N6WpQxyP0WooKMOGKWYgxLAFsX+FyEqZ2Y/b0oXTYpAA9JAUMItJXCgbchZbEUdPp84BkeleH26tkJ9Ay5CA88av1rwuxx76FJr+LSqbEYNF8SWH4xyBaE77WxWXCf2Og8RX0R/qv5PcR7awjx9CC3xuBzDyOz9+G3xuNXGdH3VzBgSEGbvZA5Dh3hIVZ63vsbgaYMzpg+Fb360MeXgWZo2A4Jc6WHiYIgCMJpSwSe31R3jTTSdlSZk+OiUEqZXb8YeToG6Oloxhwag0I7dpRuQ1kLqtY6OhWDpCcUYnH1Qf0WzombDImXSwGtXAE9NQxveAyHV4urpZwN7/SQN2cFTX12csoeAZkcldpApyGN/9lj5raYCFZG9tL59t24ApuIik2GrirCelrxexXYMu6gzhHMphZYmJRDks5BekAISZ01aDojcTptPF+to71Hzz3zf8QHuwcxujyckzGXTpuZHTU9TO1dC7ZO0obkVKjDKFemkD1zudRfgP4m6KyEhDngHoLip8HRL41KHvpAEWzQEuxogvLNkHzmSJ3QYwkxisyGgiAIpx1zNLbk8wja8WtcgRmgUqHrOQiGEFRDXSgjCgmT+ZDt+wv7vUW0ayJJM9hJDxlG7agH46HRTlunNNMmLEcEnoIgCKc5+anuwHdexVqoXAed5VJW1hMhV4BcDh6nVA8T6Cj9kK53f0P3h7+X0sKDVKOy7G2o/YwzZ8/Ck38lkeEh0lrO2BlSNteucjAEs71Tzk/fbWQ3yQQWrcFqNpLcvpb4fX/h3+99wo3/2Ul/VxPOtnIamlvpUYQwX1fJkBswhWNDR50/HLJWgjoAc2wuS1b+EEP1O+hL/0VfUxmVAwqwd6Eqfwd91VrcLSV80OCnQpPNlGg1NGxjWayL6ZOy8aSdQ48vALffJ63hDAiiQxmOp78V5d4XwGk7cj+SF8K0a0Brlq7d3i0FlpXvQ3/zkfvRWwtte6XkQCDdP0f/N/oxCoIgCN+uT52p1IcuROG1o5H5ITBeyjNgioaWbXibP0fn7qHapmB425MM9rShHmiCvS9CxXvSSSLyYNp10swZQRAE4bQmRjy/qfSzpRHPqk/A0SeVFpEdY/7ssRz8ADrKYdq16OKn0D8whM6kApVeqlW5699S0BWeQ0SCjkvnZENNNzX9oFVFE2mJA2Mk+5t62VbTRb/dhcvtBb0VnSWMzqAcqtudhKmc/CysGE/CIoYr32HI3sP01AGygupITT8TtIFEZM4gLLwASl/Abk6C+CJqen307yslPdDApSmTiE3UwccvS8Fy9ko+qRniL81BTIqVcZamDLb9LyFRhRA7DfQhXJligtAEqNkPg23UyGZhyYwlPbRTCiwdA1C9AaImjSQRIiQdZtwEQ91w4C1o3CEF9zkXQuI8iCyEgEP1TcvfhZ5aKfOtWg/A3oYeHt9Yw4pJUSzOiRjnpguCIAin0pXzMnE+XYHKa0dmH8Tv8+IzRuHXBuId7sU33E+7Kpp47RD+oEn4EiZDXAZdJW/TXLqXvJTF0sNbvfVUX4ogCIJwHETg+XW17JECzIhc6fuMs8HnOfGgE3CYEiipGyDG5ic6JBbj/KPKILjsoNRC0nw80VM52NJPhq4Xd/MeXjjYRo0uj39e8X8gV/Difz5mV1MfD51hImdwPbR1gj6Y4Mmr8bWoyHdUkmqWU1FTzGbVOUw7cx67O53sdLqZ02VigXYQrUIOwy14Oiop1xRQpwukor2LeX4VdJQRG3MQPBmgNkBgMoP2QfK8ZVyWWEBu4SQwB0FOH9h7oX0/tO4FfRDkXggqPb78K9i+rpNodzVpXSUkqPRw4C0GfRrWVTjILTKTFmGW7qMxXDrWejM4B6X1mAFBIFPA0WVPAhOl/hw17bZ5wMH+ln6mxFvx+fyUtw0SadFi0Ys1nYIgCKcDhUKBzxSHxzOA3D2Mz+tGoQ5AaWvCrg9HpQrAOlhBhqOPAVkgKdOjwRTJg80FbK/t5O79rSzJOUYCPkEQBOG0IwLPr6t+E8hVRwJPQ8jo7a17oL0MMs4BzTgZVQ+p67Lxu08cVHZEscTfwI8neaUpqRoDVH0sJSAquALkCh58ax+b91fzm2keJhdcSpyniYs8n0GTB+KKuFjzKQuj5KTIE+Dgp9LoocaMrLuKhRGJ0DEMqky29Sp4o9FAaK+fzJgQOu055MZaaXa7qfDlMUkNFnyEBCh4ub6PHQdbWBVWhzpmmpQxt78FnDZsA+V8EnAWk03RrPHuZVdHIOtbtczvq4Sugwy6/QzpYiB8Fj2ff0xqYgLK6Mn8ZK6GR9cP0UEgCcP9MNBGX9hc3m+MIqTfSVqwE0r+w94uN7K+BnIWrpZGQE3LpClW9h5wDkDSQikL7+Eabkc5KzuSvCgzkdYAmnvtvL+/jbxoC2dmhJ7MfwXfDq9bZN4VBOF75YkNB6mtq+HHKg/63gpkzkHkhihwDSDrb4T4RdC8A2dYEZ9oliLzusg0xaMDFudGEaDTMD1RrOkUBEH4LhGB59eVcxHHTEkL0prDwTYpaPgSexr72Ns8QF6MmYUhfdi3v4o+Ogeyz5fWLrrs0hpPICXUgL57CGN7Kf/eqGZFWAeGjX+Cod20+syoGzejteaglfvo6W5DFj0Pa/J02P0c7H4BfG56ZBbcuuUMez3sauxjbWk795+XjXq4iw3F+ylxRBKdmUhg5nxi5HKWVvcSb9+Hy6OhKWIe0RqDdL64Gcg0wSR2D6GMWwA1bzKw522GFEF0xIQjj4ykpsfFC7ZJhHWF0zhg5XprKln1WzCWbyDMm45reFAKIFc+SczBj3hUuxtTahHUbYLajXTaonE77OTINdhdHv76SRWLlJAXGiKVT9FZRu5jXZeND/a3s2pqDGadNKoZaZWy4UaYdSzMDCPKovvi7T/9dVXD/tcg8xwp+BYEQfge2NPYy52eZ7Bo1cg0Fvz6YPD78ZqS8WsC8brstMWcxzvqZdh6e1kW0osOJ6BhcXYki7MjT/UlCIIgCCdIBJ5f1xdHOL8ofjbETIehTmiug8hJ407DPS8/GmuAmvxoMx9t2UFQdwd6xR6wxEH6WaP2vWR6PEyJ5k+vWni1XIHalMmi/GvQxBRg0Sip1CQxrI6jw61kk24BPX0p/DA4maHgHIY62zGbgjnQbCNL/ibPF+WxTRXFQbkLfetWHJ89jm4whE7tuXxcCqnTQ6B+C1MCosldPId9JSrkEdNBawVk0FMD9r0Ela2nSf4bQtPOIkNZgmL7X2nzpHNDz6Xkx5i5fkkyJq2S8tYgMuJDoMuGwhrDipoX8YTkQO5FoDXh1AahMimkexSUCJMuhcoejG2fs62qldDEID7Y105XXBp58yeNuY+v7Gzk9ZIWzDolq6aOLkMjL3+bbLkCopad0I+Y4T4p0dHXmD590qh1YAiV1vsKwgTo6+vltqsuHNOut4by4KN/PQU9Ev4b3LkwAfOrrXgDolEodTDcjdecgMthQ91Zhj44DV1PB7ctmYtcEwg1e6Xa1wEhkLb4VHdfEARB+BpE4DlRZDJpTWLTDmjbB34PRORLZVS+YE6qNP0zN3cSivifUWfr4ZV9es4x9pMWbh69s0JJuzycVaaNyPsieFyzAk2TnBUhkQTPvpaw6ucJqi8m15RJT6gSajbQrk9ja0gk+enJDKhLKGz5D8a2bczRVLBssA7ZwQg0AWoyrSE4vO3k9XyKp2km7cXvUNqvZThjJevaE7ksXkaqUo0vZhpNn/2LAWMKBlM8oeX/hvT7CMucg7O7hDpPNDFomRIG6aEGHC4fB9sHibJoSYtIJ0ChIqX+I0hNB680qrvelkBtn4erPT605mgwRzM/boC7/89DxXY7zxUGMDnewuCwi/5hF+ae/dDfCGlngULFRYUxWHRqloyXSMg5IGX+PR72XqkWqioA9r0CqUsgKv9Ef/onjykSCtecutcXvvdsdgetnZ1j2jd/sBl7b8eY9n17Gph+6bfRM+F7a6ibtq0v0GssxIWFXG0FCls7CkcXOls73rAsZE4bspgp/GyLijCrhqXpK8kq/X9SEj/PsLSM5XApLkEQBOE7QQSeEy1+LsiVcPAjUGrpM6Xx6IeV5EaZWTk5ZtSuSaFGCJ3E3zdU8XpFPWERvVLgaeuC2k+k0inmKC6IGcTU9AE2/5lEpJ3JvqZeNNXvkxAciDzjDBwDbdg/ew17WwfVQQYSzQpCjHEYIgo5+GkFXa2N2LLPYtBmI0OpQ50wG5/DhrmxlOXxSlSqfH5XbkFnvBwP7SR7XSz2fIJ7h4c6xbnUD6dQ7p3KQL+JRep+MuWN4BqGkBQ0U1Yz2RjJs45+2PM81A5QXG/jmS0yKtoHeXRVPgw0STXXvG5Y+1OwJlCgiSUwcgHq2o8hPEsKuLQmIuJSmd/yGspGDUq5ha4hDz4vMNgMPdXSdGSFithgAz+cc4y1tJMuO/6fV9Pn0LwTMs6FkNSvHtkG9jf1MuT0MjUp+PhfRxBOE36FmunnrR7T/unue/nj6oIx7em3HPw2uiV8n7WVEtexHqVaR4CyDWX9Z/jCc/DrgpC7h/F6Pew2nsEL/UWofMMElj3Jxv4isuZdA03FUs1nn0cEnoIgCN8xIvCcaAGBkDAX9MEQmITL4aNjwEF/4Nj1ho++X4HH5+Pm+alkB8mYGimHtv1SDcuuGuhtgNB0Yp1tOAMsKJKnkZ8SSrxFRdP7+xi2x5Myfw3qrmraGr182mkAm5H/yYGKhkFsa58l3VdHc9ol1A/qmWN7H2doGGqvk56GCpoUCZgsRaQmJRLYVkzu8B6mXHQxfP5P3O512HxWmjpy+dc2G0vDdWhrt1CVNI28OVdC6KFi3mFZ9NtdvL27gbnqOGLcdgrcJVyTVUBK9qHsg5EF0hrN3ibQBEBQIuFBSYQbvfDpm9BdCUU3AnB2QSJebSrorDywIhuv14tCoYCUJZB4BqgDvvpncCJTZaOnSNl0QzOkAPg43L/2AG39TtbeMhuDVvxKCYIgfKmIXOyWVOTuYUw9u/CH5yJTavApNPhVevoD4mjrtTNbW0JY/iLU5eFoEsKhfZ+UWmHKj0ZlMS9r6cPj8ZEbG3jqrkkQBEH4SuJT8kTy+8HeJQWdcUUAhKrhz5cUoFbKx+zu8vnwev3o1ApmeXbA+2+COVJa7xmWDbYWcA2h6K1Gbgwlpv0T2Lqftl4tQ9owQmML4dNHkHuGWRRuwB1/BpbGD2jYupNe41Q295iwDodQmL+Q/I5igg92omqspMpnZMicR1z3ZvprVdQYQrg6vBZ2vE77HjMfd8aywuvDGp2ERjPEL5TP0ePKojUqjayu93jx7TYG0vX8aG4yAK/ubOSN/QM486ZydZAfvTmGNX4f1DwHqqkQlc/jn9to75Vz26KfYI1IAKdNenodkirdr0OeK+mipDGLR/ITiEZKv4/XI42ammNP4EfhZ/2BDsw6FVMSvuTDid56wjXhpiUE0W93iaBTEAThOLS6dLyoOJtL5B8gk8vwBoSgatyKTGcBt4NApZY0k4HtNj/63a9zVtgAtL8FyWdKa96VGun9daAFjBE8vK6CniEXr98wQ3qPEARBEE5L4pPyRGrfDwfelmp8hueMNI8XdAL84qyMI9+47dI6w/h5eNtLGS59A6UpHO3k1by/5SADXhPnKnsxtXxElt+NX65CP2jAW/UxDdYi1NlnMq/rU2T9H6PqLkOnluMInkP3UDiKrjJiB0uQKQNwOof5vN/CpjYNfzC14K44yG53CGqLj2hTFG6FjnqfGVv4VIbNWbS4zGQVLYe4GTh7m+jcWUd1bxD9nYO8+Hk9y7IjqWtpIzHEwMUJdih+FnTB0jrJxs+h/QA07mByRy0K9yCalkUQFgs7n5ICzhk3S9Nndz8PgQkszU0nI8JE5NEZaVt3w8EPIfNcCDu+UUmvz09d9xChBs1X73yC7liUdtLPKQiC8H21paqLijYb4YZ9yAyhqIZ7DwWUOrAkIB9qB4UPZ+wcMgZeptmhQmlNICxmGn5jOJVtg0S7qgmofg9SlzA3LYRhl1cEnYIgCKc5EXhOAIfby4HWAdJMwehDs8AQ/uUHuOxSltiQdOg8ALZO6KkCrwOCU3AXP40dA8MaNXEqDbGhVoz9lZT0GgkNOYPJzp3gHKC/bg+vm37Izg4Vwfvh6t6NhNsa8YdmYzaYmKpppWewGVNVN15LJNqeSjxR0wn3DRNpDEFOIBa9iyB3M/UVTRhkHqJVdm5J87N9q5PNrnjKB9SEm0KYVLebac5tGH1DyCPzsarVPPVZLam1z3OHr5qh6T/mtWoXKbYw4lz9BKTEYlryW/jgl9C0g6mTzwWVDkLSQCaH0CzQGKVpsX4v2LvBEEJusoXcaMvo+6XUSfVTzdFH2tr2SUmBUhaNW/NSqZBz+fQ4FPJTmKFWEARB4IIsE+adnyD3OpAN9YFCK/3d1hjw2rqQu4cICugnpukNZDmz+LC0CqU2g8sVGrqqd/FRtYqCSANFkflgieWqmSdez9M27KJ7yEVc8LHrbAuCIAgnlwg8J0BVh40NFZ3I0kKYlHUuAI09Q+hUSgYdHuwuD1nqdqj6SBq1622A2o3SVNP2Q9lasy+EivdguBvNOX+gr9fHR7XDpDfKmKVpYDDUSoUtngCDDPq6wRiBZ7CdDOV+ClUd2EJWUGHLItDqQz/cRrMsi52tPqb5u7AMlOFQuPHHTEHfXcokXQ+Bky9AuR+U7j6y7dvpbj9AU+Ak6mqaKAsoYqdnGnKFmVVTgijZXcw5fX9AqzfiVRtYlhPO/s9eZ7nVCPYuVM5GogLkNNtVHGQOcVo/mY5AiqKCaY4/n+qyYjzuLM6clAM+n5TMJywbjFJ2X9QBMP368RNH2HvhwFtSoNrfJN2v2CIp6Owoh/hZoDCPPQ7QqsTTcEEQhFNOpSMhOQtntw2dyYmsvxnkCmRyFXKXDb8hFP1QHVPtBzB1DLMo1IJ56EVa1m+iuaufzuF09uvnUTR7ydfuwsMfVLDpYDePX5pPeuT47xmCIAjCySUCzwmQGmZEBiSFSk9SnR4vr5c0E2HW4fX56LK5SQ/dj6KnWsoGG5ohZb4NTAR7L93N1XT1y0kzR4HWjCwwjt62al7Z2cKV8Z3Yql6nLXgGzfEXsUz9Ea7OKmR+MOosFAx+hio4mU8VOgbtTjxaQCajbNCIXgPmjoMQmIzZEoXPMwQyBdb4KVgTo6BvEuBhWJeINyGSXmUU4R1byHTbmTN/CQExGSCD7NZ6DG4jCmMEJC8kTtaGx11BtTYTdfYKtJ4s8Hv52aJkaja9QM2BvQQmXwMuHRv8+fy2TsfKIBlnAr7BNtqL30IXX4hl0nlHbuKxshVqzZA4B0xRUL8FBloharI00hk/S9ouCIIgnL6UakL796KveQ9/1GT8rmHQmfD7/aDRI7O1Yw8qpNsSjEEBkamzsO98nh1datpUBTS6w8nWfbNlE6lhJoacHkJM2pN0UYIgCMJXEYHnBFAr5WRZfVC7HtQBaGKnMz89DINWiV6twOXxoWjaLU3BLX8HIifRF17E9leeJNc0yKYWGZ+3NPKbhFZcqmqe3zPEvIG13JOTjSZhBnXeSyixWZg88D7VPgMWcy5arweZW40vYg6a1h0kd/4ee/AkTF41Q1ELebM6izSzmwXmYFDIwdGBPCAMoqdC5jlga4eAEDoizqChfCexripmh/bijQjBLxtEufMPYF9GqSOY8hYHRnUYwQmz6epro2xPKckqO/nTUiB1BnSFwq6nkeuDGNLm0aa3k3/gBZzlw0Qn38afL55EUYKUQGhPr5oSfxEJsmTOAHAPg60DrHFSwiF1wOistHI5WBNArob0s8HjkuqlwjFHOgVBEITTi9oYhM8UAxoTMu8wMnsv4MfvsuM3ReL3uhh2DtGefBZxiXPQh6RgbfSRFWTiunDTN379y6fHcfn0uG9+IYIgCMJxE4HnRGnZBWVvgtoAwakkhVh5fEM1iSEBLM+PBtN54BiEmk/A42T3ru2UtNiwu/UosxYTP+xFZR2gT25kV7Ob9MA45iWaQF5O9+xLobGBXEcxPYlncW9XHorhHooigznL/QFaZxcqYwSKvgMMxxfwmW4OZ5mKydF0Up14O+3DPqb2vovSOQT48DbvQtG0HWQKygYjSbXtQ20KgqBkFFkroLMS6j+F/mbSfPUM5J+LPPEaMOjwdg8QVvsL9L5eqa6mzytNmdUHgb2XrPBuwmZOI6jpfRqaOvjXpmqunpOE9lAG2P/saGRrtYon49uhrAwUamjZDSmLpSm1aYulqbSH+byw+wXQB8LkK0/FT1YQ/isMDrtY9cj7Y9o7ewdPQW+E7xtNZC6ug+tQ2HuQdVZDaBoyuQpkPeAcQmUMJ2awAmvAWSCTUW4zoNa6SDkJQacgCIJwaojA82TrrZPWIUZPlkYRLbEQEIxj2M2B1gH8h/dTqKQanzkXwLa/M1vmpKVwGXPdHxDY/P/oi1tEcek+mt21nFV4FdMCPLD7P+AeIsgYSZDOCjI5AQEBzJFtoF8OUbYWeiveRxGbjaq3Cm9wPs0OBf27nyUjVIOpu4pdDhMHh01EzriS+Mp/45SrGCx5G7O7HVVQPJbMS/msKp4zYvygsMPBD6QgT22g3jwZRd0mZqa5wBoIA82E2SoIK5gHXifoAqVEQWVvgx+YejXKvS8RHhAE065BldTPwlbIjTlSrmRxVgSRZh2JmlroqgJjNKj0oDKArQ1660cHnnIFJM+XEhMJgjBh/Ao1089bPab9nR33se7Nl0e1DfT1jXuOkl27WHXVdWPaQyxGHvvD705KP4XvoJ56hkvfQq0xgToAf1gW9NWC1oosIAKfsw+f04YiNBVldD4Az+5ooKbTRlaECZNefYovQBAEQfg6ROB5sjVsg546aTSutx6G+6BpJ5a8VTx8QR469TilVDLPQ2Fr59Lq98Hbh8cvY2/J5+zRTkahkZGuhNIDZaSrA9HLVbjaK1HgQjHYhk0fz2B7HQWBHhI8fhyWMCoUyaRafShUanqaKumVh2GQDaD3DDC1712mWuIwVOyF/Cvo3/8JQxYNRrcKnINMClYyKfcC+Og+vPZeCAhBETMNIvL4+asdmDwFPB4+SfqH01EBVeulLLTmGCnBj88jZejta5TKwUy7TpouK1cQFWPlkpjRl74oK5xFWeHgTYak2VD2FmhNEBgL6edQ6gyht7KDOamhMNTNlr1l7BgK5bo5iYyszOmukUqsJC+QjhUEYQL5WZIXMapl+xvecfd0+WD6pXeMad/23KMT0jPhO6K3hkGni+DBJvA5pVJa+lD8QUnQVY3c40BnCUDWuRfK17JLkU1OhJU5KcGYunZBexnkXgQakZFWEAThu0QEnidb8kJwDoJCA9kXgKMf2kpBpsRqOPSU1t4njRAaw6TvTYc+xMlVkL0CmSUe74Emcmo/Y4qqmt6qckoHtAQaAojyddMmC8avUBCXmEZYbCZTlHGkHniMAF0MfcGRHGxrYiAuDY2rH9ukH6BzmQkzVdLWEMKgX0dk3048VdtRWuMZrPyUcsscwqInQUQ2tO2WMuzqAinuDcDW1s78mGZIX8a0ZD9DDitKtQbcDjBFQ/5lUhFv1zC07+GF9dvwa1dyySIrGELGvUX+rmqayzahSF1ERPiha1coQWGAvFVSYXCFEjKW8dD/bmPIUSEFnnWfIdv/GR3acxh0xKFVH/rna2uDroMQM00EnoIgCKe5d/vieX9oOb+JUKHzuZF1loHPjVcfiFytRe534RtsRZk8H3rqcB7cArpUFq65DeqrwOfC5/Oxu76XcIuWSLOYASMIgvBdMM7w2+nnr3/9K/Hx8Wi1WqZNm8aOHTu+dP+XX36Z9PR0tFotOTk5vPvuu99KP6//TzG3vt0gBZLFT0nrPGOmwJQfgMsGti5pGu4Hv4JPfitNxT3MFEF1ylWs7Q7D3VmJxt7Of5qDKZclEKHzM0nfQ4RJhTwkA5dch82SAZN/AFH55OdPJSAwGnrqCAhJQB6SRoM6kTCDgjPjdKxJlxHQupWe/iEG6/fSFbsE37w7wRSOJW0OuRY3eoMFWndCxwFw9II+kMqwsxlMWAQxReBxcXtsI3fN0Ev9bdwO+1+VpsWmLICYKbiiZvF0qYNX9/eyf/DQfn0N0N9MfV0VBzuktWHDfe00VpVR31A/9ibKFVLQecgFBVFcPDVW+ia2iPxFl3HbOdNGZyKMmS6NrJqjTuJPUxAEQZgImXEh2DVBuJzD+JyD+E1R+KMKUAz14lVbsVnSUfnd6JQKKLiCsNAIZqiqoKNMyl4+7Tr6vBo2Vnayp7HvVF+OIAiCcJxO+8DzxRdf5I477uDee+9l165d5OXlsXjxYjo6Osbdf8uWLVxyySVcffXVlJSUsHz5cpYvX86+ffsmvK913Xbqu21SgpyYyRCaKW1w2mDPC1C9HlRaBgKzGArKBM3oLKxtAw5qu4bw1G8lw3+QWTFa4uWdKHw+qsIX80DzVAZbDpBs8ZNVtAyi8qUpR9v+Lq3DNEcxMDhASMt6hn0y1rZb+fOWDikgcw6SNbydnLRUUoINqBu2gK2DoDNvIiZzqpQMaLANglOlsi4tu7lC+SHLY9zSWtT+Rtj+V9j3qtTZkHSIKwJjOP/8tJpLX6ilXJ/LzQuzyI42sauhF4b7oeRZ2PG/VK17nKc+2o3d5UGfVETS7IvI6/sIWvd+6T29oDCGS6YdyjxoDEMbW0DoF9Pfy+WgExltBUEQvgvigw0YXd3Yh+zI7R1g70Jm70XuHUbVVYrbOUxX8GRsFR+DvZvExdcTXXAWGCNHzhFo0LAiP4oZicGn8EoEQRCEE3HaB56PPvooP/rRj7jqqqvIzMzk73//O3q9nv/7v/8bd/8//elPLFmyhJ/+9KdkZGTwwAMPUFBQwGOPPTbhff3HZYU8fkmhVP4jYQ5E5EpB575XISgRYqfjU2j4ef00/qd9GqiOCqDa9tF7cDsfl7ezQ15IqTeWudZOglRu7I5Bgvf9i9ShYmka6mAr7D2U3GPvS7D3OWktaex0dvnT6FGGYo3J4D+2Aox1H8LBD8EYgUqhJsA7KGWLtcSCyw6V70vJerKXQ0QOjuEhBl1eBlVWhmu2StOEQVrDmbkcEuaC51AiofjZoNLS1Genst1Gx6CLZXlR3HxmKmfnRkrTXpPOgOSF2MKn0eVS43T5QCYjNCIOXUQaBASd2E0ebIPNf5Iy3wqCIAjfSasLg/FrTfhNkcg8w/g1RvwBIcicdjRKBc8P5LA3/DwIz5WWbWScDXrrqHPEBwdg1qtO0RUIgiAIJ+q0XuPpcrnYuXMnd95550ibXC5nwYIFbN26ddxjtm7dyh13jE5msXjxYt54441jvo7T6cTpdI58PzAw8LX6GxMcMLbR75OCT2MkGEK5+/VSVAoZ0xIDR+/XsI2A1joaeuZQvmcP6fJmhuddS4d1ARWb3iRL3cIFxgYCkheCZxgCQrn/rX3M7oFUbSrmgmtok4dR3t2CJyqK+E4bJq0SuSJICgDn/Bh0Zlo+fYah6JmkFN0AdRvBcCRJiC9jOf/85CAelCj86bgVOdxSWCT9I1GqoXANDHXD5r+AewhCsyB3JXctzeDqmQnEBEmJHoIMUmHvhi4b/7fbyHmTIjjr7CLmuTyY9Wo625vZ89HzRGTNIct0gtNjZUrQmNlY3c/azbv55dJ0LAGiAPj32cn6/RQE4eT7ur+fk9QtdMk8eHsbISgVWWclblMU3rACdvQGEGzop6atnz0byukclrM4M5TS5gFWTo7BIrLaCoIgfCed1oFnV1cXXq+XsLCwUe1hYWGUl5ePe0xbW9u4+7e1tR3zdR566CF+/etff/MOg5TptfMApCwCtV4K+iZfBdv+Bs4BttZKAeefLy0YfVzWCs7I8HLBxk62VzmJTM3izMwMXAOdBPaU4Hf3EBAWDwmzoWErtO8nCj2tfcPUBZ3J0l0vYI2bQYghiZn+vZhsrcSaLDQE5EHiPGgrpV8RyPMBl1IzmMxfNQGQtnRUF7r9Rj5u8pEcomZeWjSDjmiU5tH3EqUazNHgGgSDNMVJqVSOBJ0A+HzQeYA9dXI+LGvDqleSHxuIWil9WKho7qKxsY7egGSyJp3g/TUEw5SreOHfn7O5uo1zcyOYlSYCz++zk/r7KUwIt8s9psQKHLvMyon45R03Yu8du7RCbw3lwUf/+o3PL3wzX+v3s7sGug7gD0rG4+pF3lOD0xCFTxuC3W5D7egiyGTH4ejh04p2Oh0KNAoZuxr7yYsxMyVBTK8VBEH4LjqtA89vy5133jlqlHRgYICYmJgvOeJLDLZCVyXEzZQCTwClFiLzwRDKjxccYy3ioSmnN5xpoTghiFlpUkZYtUZLXEQoKONgxtVgiZFKlgQmcbXegn2wmd6IOMKCkiEkjIvD4qBjLhz8kMKugxTmnimdv+sg5uFm5kzKY1ZgslTupPZTSJoPpnAAQkxa/mdFDoE6NeGWY2QJ1Bhh0sXjb2v6XMpua42FsrdYGlmI5pwcpiWOnk47qyAPt+ZOcuOO8eHB7ZCmAwcmQXThuLv8eFEaS1sHmJUWNu524fvjpP5+ChNkbIkVOHaZlRNh7+3gj6sLxrTf9syub3xu4Zv7Wr+fKj0YIwiR9+BxDUhLQVQalJ4BvF4n2qQzKZx9Jfi8JA+66Rt2MyUxiMq2QQrjA7/83IIgCMJp67QOPIODg1EoFLS3t49qb29vJzw8fNxjwsPDT2h/AI1Gg0aj+eYdBmlEMqpgdFkPuRySpQBw2bG7AYBZr2Z+1lE7aYwYlt4vBWOHE+gEJkhfTcXozeHo4zIhad6RY0IzoHkXxARDRJ7UlnYWdFYypeJdUCvAGSIlDHINjXr9zIhvkKSnowIcfRBbBCmLUAQmsugLa3IOOyPrS6bY+txSiRbd+McCJIeZSA4TpVP+G5zU30/hW3WskdCdH77PqquuG9UWYjHy2B9+9211TThJvtbvpylcmnGz50WUCUWQtgRKX4XOciyBSUwunAqB0tKVqKOeT4qgUxAE4bvttA481Wo1hYWFrF+/nuXLlwPg8/lYv349N91007jHFBUVsX79em677baRtg8//JCioqJvocdI5UBOdi1JpUb6+iKvCyzRUvKFL8q7ZPT3Kh2EZUrHBCVLSRoCE6X2kyX7fGk0Vqk65kjlcdEYYfoNoBBJIwThu+1YI6Fypl86ei3+tuce/bY6JZwOLDEw69Yjf+cdA9L73JyfgXnsvxlBEAThu++0DjwB7rjjDtasWcPkyZOZOnUqf/zjHxkaGuKqq64CYPXq1URFRfHQQw8BcOuttzJ37lweeeQRli1bxgsvvEBxcTH/+Mc/TuVlTIy4GRAzTQp2v0g+TsJihUqqK3rYyQw64cjU4pNBKZJHCMJ/k317SrjtqgvHtL/24WZaOzvHtG8uqYRx9hdrP79Djn64mL0CMs8d//1MEARB+F447QPPVatW0dnZyT333ENbWxuTJk1i3bp1IwmEGhoakB8VZM2YMYPnnnuOu+66i1/+8pekpKTwxhtvkJ2dfaouYWKJN2lBEL4HvG7nuGs5X/xwG9PPWz2m/dPd94q1n9834v1MEAThe+20DzwBbrrppmNOrd2wYcOYtgsvvJALLxz7JFwQBEE49cZb+9nU2sqqR94fs6/N6Tuhc+8qGTtyuml/A0lZ+WP2FetKBUEQBOHb850IPAVBEITvk7FrPze9pB53ZPOdHfee0JkV3rEjp+m3HByzphTEulJBEARB+DaNsxBQEARBEARBEARBEE4eMeIpCIIg/Fc6VkKj8RIU/fKOG7H3dhzXvsdy0+0/pbNvcEx7+f5S0rNyxrSLqcCCIAjC94kIPAVBEITvjapu15i1os3tXePWE61vqKM1cmx274pdFTz4hbZ3139GWszYOpIff7Cd6t7/z96fx8dZ1ov//2v2JbNn37emTds0bbrvpaUslZ2KgCCIHM9RKyro0cPPhaOfoyDnK+I5Iiog6lEQWZRFoEAthUJbuu9Nm7Zp9j2Zycxk9vv3x92mDU33ZpKW95PHPErumdz3e+7MNTPv+7qu9xU/bvv+nZuZO75gwLaVW+v4l5/+33GPffsLV5M1Pf+47TtWvXLcNiGEEOJCJYmnEEKIi0ZMe/xc0dc+emDQ9URPNK/0H/9xP+UTJg3Y1tjaxZ1f/cZxj33to/+kJ+X4pLGx5Q0e/en1A7Zl3fHRoAlwOBIaNL7frAoft00IIYS4UEniOQhFUQDw+XzDHIkQw89ut6PRaIY7jH6n2z4TiQTxWGzQ+85k+8W0j5Ee35k8VgHC4eMTM+V87Ftn5F++8pUB2x544P+dYB8Kl41PP27r1r8njo9PSQz62NV/VQbddyKROK3PoZHURuXzU4iBRlL7FGK4aZQjnxKiX0NDA/n5x1/BFuKTyOv14nA4hjuMftI+hRhoJLVRaZ9CDDSS2qcQw00Sz0EkEgmamprkKtVp8vl85OfnU19fL2+u59FIOa8jrR2cafscKefxQibn8NwN5TkcSW30RO1TXkNDT85xcpzpeR5J7VOI4SZDbQeh1WrJy8sb7jAuOA6HQz7shoCc14HOtn3KeTx3cg7P3cV+Dk/VPi/25z8SyDlODjnPQpw5WcdTCCGEEEIIIcSQksRTCCGEEEIIIcSQksRTnDOTycQDDzyAyWQa7lAuKnJezw85j+dOzuG5+6Sfw0/6808GOcfJIedZiLMnxYWEEEIIIYQQQgwp6fEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEchKIo+Hw+FEUZ7lCEEB8j7VOIkUvapxBCiBORxHMQvb29OJ1Oent7hzsUIcTHSPsUYuSS9imEEOJEJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkJPEUQgghhBBCCDGkLvjE86GHHkKj0fCNb3yjf1soFGLZsmWkpqZis9lYunQpra2twxekEEIIIYQQQnyCXdCJ5/r16/nNb35DZWXlgO333nsvr776Ks8//zyrVq2iqamJG2+8cZiiFMfxNcPmP4O3YbgjEUKcjqYtsO2vEO0b7kiEEEIIcYG6YBNPv9/PbbfdxhNPPIHb7e7f7vV6eeqpp3jkkUdYtGgRU6ZM4emnn+bDDz9k7dq1wxix6Bf2g7cewrLAuBAXhGAX9DRALDLckYiLlKIoeL1eFEUZ7lCEEEIMkQs28Vy2bBlXXXUVixcvHrB948aNRKPRAdvLy8spKChgzZo1g+4rHA7j8/kG3MQQSi+DOV+HjLHDHYm4AEj7HAFKF8LsZWBxDnckYoQ5X+3T5/NR/+IPpH0LIcRF7IJMPP/yl7+wadMmHnzwwePua2lpwWg04nK5BmzPzMykpaVl0P09+OCDOJ3O/lt+fv5QhC2OZbAMdwTiAiHtcwTQaEBvGu4oxAh0Ptunw2o+j5EJIYQYaS64xLO+vp6vf/3r/PnPf8ZsPj8fUvfffz9er7f/Vl9ff172K4Q4d9I+hRi5pH0KIYQ4XfrhDuBMbdy4kba2NiZPnty/LR6P89577/HLX/6S5cuXE4lE6OnpGdDr2draSlZW1qD7NJlMmExyNV+IkUjapxAj1/lon/3zO5H5nUIIcTG74BLPSy+9lO3btw/Ydtddd1FeXs53vvMd8vPzMRgMrFixgqVLlwJQXV1NXV0ds2bNGo6QhRBCCHECPp+Pxld+QqpDhtoKIcTF7IJLPO12OxUVFQO2paSkkJqa2r/97rvv5r777sPj8eBwOLjnnnuYNWsWM2fOHI6QhRBCCHESdpnfKYQQF70LLvE8HT//+c/RarUsXbqUcDjMFVdcwa9+9avhDksIIYQQQgghPpEuisTz3XffHfCz2Wzmscce47HHHhuegIQQQgghhBBC9LvgqtoKIYQQQgghhLiwSOIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCCCGEEGJISeIphBBCiGGjKAq9wTCKogx3KEIIIYaQJJ5CCCGEGDY+n4+nDjjx90WGOxQhhBBDSBJPIYQQQgwro8k83CEIIYQYYpJ4CiGEEEIIIYQYUpJ4CiGEEEIIIYQYUpJ4CiGEEEIIIYQYUpJ4CiGEEEIIIYQYUpJ4CiGEEEIIIYQYUpJ4CiGEEEIIIYQYUpJ4CiGEEEIIIYQYUpJ4CiGEEGLYKYqC1+tFUZThDkUIIcQQkMRTCCGEEMMuEIrQ/vqD+Hy+4Q5FCCHEEJDEUwghhBAjgt1qGu4QhBBCDBFJPIUQQgghhBBCDKkhTzyj0SilpaXs3r17qA8lhBBCCCGEEGIEGvLE02AwEAqFhvowQgghhBBCCCFGqKQMtV22bBk//elPicVi57yvxx9/nMrKShwOBw6Hg1mzZvHGG2/03x8KhVi2bBmpqanYbDaWLl1Ka2vrOR9XCCGEEEIIIcTZ0SfjIOvXr2fFihW89dZbTJgwgZSUlAH3v/TSS6e9r7y8PB566CHKyspQFIU//OEPXHfddWzevJnx48dz77338o9//IPnn38ep9PJV7/6VW688UY++OCD8/20hBBCCCGEEEKchqQkni6Xi6VLl56XfV1zzTUDfv7xj3/M448/ztq1a8nLy+Opp57imWeeYdGiRQA8/fTTjB07lrVr1zJz5szzEoMQQgghhBBCiNOXlMTz6aefHpL9xuNxnn/+eQKBALNmzWLjxo1Eo1EWL17c/5jy8nIKCgpYs2bNCRPPcDhMOBzu/1nWEBNi5JD2KcTIJe1TCCHE6Urqcirt7e2sXr2a1atX097eftb72b59OzabDZPJxJe+9CX+9re/MW7cOFpaWjAajbhcrgGPz8zMpKWl5YT7e/DBB3E6nf23/Pz8s45NCHF+SfsUYuSS9imEEOJ0JSXxDAQCfOELXyA7O5v58+czf/58cnJyuPvuuwkGg2e8vzFjxrBlyxbWrVvHl7/8Ze6880527dp11vHdf//9eL3e/lt9ff1Z70sIcX5J+xRi5JL2KYQQ4nQlZajtfffdx6pVq3j11VeZM2cOAKtXr+ZrX/sa3/zmN3n88cfPaH9Go5FRo0YBMGXKFNavX88vfvELbr75ZiKRCD09PQN6PVtbW8nKyjrh/kwmEyaT6cyfmBBiyEn7FGLkOtf2qSiKDM8VQohPiKT0eL744os89dRTLFmypH8ZlE996lM88cQTvPDCC+e8/0QiQTgcZsqUKRgMBlasWNF/X3V1NXV1dcyaNeucjyOEEEKI88fn89H8xs9IJBIoikJvMIyiKMMdlhBCiCGQlB7PYDBIZmbmcdszMjLOeKjt/fffz5IlSygoKKC3t5dnnnmGd999l+XLl+N0Orn77ru577778Hg8OBwO7rnnHmbNmiUVbYUQQogRyGYxAxAIRXmmKZPv+XzH1WoQQghx4UtK4jlr1iweeOAB/vjHP2I2qx8wfX19/PCHPzzjnsi2tjbuuOMOmpubcTqdVFZWsnz5ci677DIAfv7zn6PValm6dCnhcJgrrriCX/3qV+f9OQkhhBDi/DKZzMMdghBCiCGSlMTz0Ucf5corryQvL4+JEycCsHXrVsxmM8uXLz+jfT311FMnvd9sNvPYY4/x2GOPnXW8QgghhBBCCCHOn6QknhMmTGDfvn38+c9/Zs+ePQDceuut3HbbbVgslmSEIIQQQgghhBBimAx54hmNRikvL+e1117ji1/84lAfTgghhBBCCCHECDPkVW0NBgOhUGioDyOEEEIIIYQQYoRKynIqy5Yt46c//SmxWCwZhxNCCCGEEEIIMYIkZY7n+vXrWbFiBW+99RYTJkwgJSVlwP0vvfRSMsIQQgghhBBCCDEMkpJ4ulwuli5dmoxDCSGEEEIIIYQYYYY88YzFYixcuJDLL7+crKysoT6cEEIIIYQQQogRZsjneOr1er70pS8RDoeH+lBCCCGEEEIIIUagpBQXmj59Ops3b07GoYQQQgghhBBCjDBJmeP5la98hW9+85s0NDQwZcqU44oLVVZWJiMMIYQQQgghhBDDICmJ5y233ALA1772tf5tGo0GRVHQaDTE4/FkhCGEEEIIIYQQYhgkJfE8ePBgMg4jhBBCCCGEEGIESkriWVhYmIzDCCGEEEIIIYQYgZJSXAjg//7v/5gzZw45OTkcOnQIgEcffZSXX345WSEIIYQQQgghhBgGSUk8H3/8ce677z4+9alP0dPT0z+n0+Vy8eijjyYjBCGEEEIIIYQQwyQpief//u//8sQTT/Dd734XnU7Xv33q1Kls3749GSEIIYQQQgghhBgmSUk8Dx48SFVV1XHbTSYTgUAgGSEIIYQQYoRRFAV/XxgFZbhDEUIIMcSSkngWFxezZcuW47a/+eabjB07NhkhCCGEEGKE8fl8/F+tk0g0RiAUGe5whBBCDKGkVLW97777WLZsGaFQCEVR+Oijj3j22Wd58MEHefLJJ5MRghBCCCFGIIPRRDgS5oXmDDyexHCHI4QQYogkJfH8l3/5FywWC9/73vcIBoN89rOfJScnh1/84hfccsstyQhBCCGEECOY0WQc7hCEEEIMoaQkngC33XYbt912G8FgEL/fT0ZGRrIOLYQQQgghhBBiGCVtHc8jrFarJJ1CCCGEOI6iKPh8PrxeL4oiBYeEEOJikvTEUwghhBBiMJFImKfeP8jPXtuMz+cb7nCEEEKcR5J4CiGEEGLEMFltmFPswx2GEEKI80wSTyGEEEIIIYQQQ2rIE89oNMqll17Kvn37hvpQQgghhBBCCCFGoCFPPA0GA9u2bRvqwwghhBDigqcQjoSJhENSXEgIIS4ySRlqe/vtt/PUU08l41BCCCGEuEBFY3ESDZsI7V8rxYWEEOIik5R1PGOxGL/73e945513mDJlCikpKQPuf+SRR5IRhhBCCCFGOKNeh9mYtGXGhRBCJElS3tl37NjB5MmTAdi7d++A+zQaTTJCEEIIIYQQQggxTJKSeK5cuTIZhxEXKX84xoF2P2OzHRh0UohZCHFm4gmFXU1eCjwpOK2G4Q5HCCGE+ERK6rf4mpoali9fTl9fH4AUDhCnZVeTlxW726jtDAx3KEKIC1Bjd5B3drexpb57uEMRQgghPrGS0uPZ2dnJZz7zGVauXIlGo2Hfvn2UlJRw991343a7+dnPfpaMMMQFanyOE6tRT1FqyqkfLIQQH5PrtnL5uEzyPNbhDkUIIYT4xEpKj+e9996LwWCgrq4Oq/XoB//NN9/Mm2++mYwQxAUsxaSnItcpw2yFEGdFp9UwPteJ0yLDbIUQQojhkpQez7feeovly5eTl5c3YHtZWRmHDh1KRghCCCGEGCEURcHn88mSKUII8QmSlMQzEAgM6Ok8oqurC5PJlIwQhBBCCDFC+Hw+fvbaZnq7u4jFE8MdjhBCiCRIytjFefPm8cc//rH/Z41GQyKR4OGHH2bhwoXJCEEIIYQQI4g5xY4pRebuCyHEJ0VSEs+HH36Y3/72tyxZsoRIJMK3v/1tKioqeO+99/jpT396Rvt68MEHmTZtGna7nYyMDK6//nqqq6sHPCYUCrFs2TJSU1Ox2WwsXbqU1tbW8/mUhBBCCCGEEEKcpqQknhUVFezdu5e5c+dy3XXXEQgEuPHGG9m8eTOlpaVntK9Vq1axbNky1q5dy9tvv000GuXyyy8nEDi61Ma9997Lq6++yvPPP8+qVatoamrixhtvPN9PSwghhBBD4MgcUFl2TQghLh4aJQnv6nV1deTn56PRaAa9r6Cg4Kz33d7eTkZGBqtWrWL+/Pl4vV7S09N55pln+PSnPw3Anj17GDt2LGvWrGHmzJmn3KfP58PpdOL1enE4HGcdmxDi/JP2KcTIdbrt0+v18tjKGnzdHTRvXkE8Eeu/LzszE62SoNOYy//3pWtxuVxJiFwIIcRQS0qPZ3FxMe3t7cdt7+zspLi4+Jz27fV6AfB4PABs3LiRaDTK4sWL+x9TXl5OQUEBa9asGXQf4XC4v7qeVNkTYmSR9inEyDVU7TMSi5No3yPtXQghLiJJSTwVRRm0t9Pv92M2m896v4lEgm984xvMmTOHiooKAFpaWjAajcddIc3MzKSlpWXQ/Tz44IM4nc7+W35+/lnHJIQ4v6R9CjFyDWX7NOqTUnhfCCFEkgzpu/p9990HqFVsv//97w9YUiUej7Nu3TomTZp01vtftmwZO3bsYPXq1ecU5/33398fK6hDheTLrRAjg7RPIUYuaZ9CCCFO15Amnps3bwbUHs/t27djNBr77zMajUycOJFvfetbZ7Xvr371q7z22mu899575OXl9W/PysoiEonQ09MzoNeztbWVrKysQfdlMplkPVEhRihpn0KMXNI+hRBCnK4hTTxXrlwJwF133cUvfvGL81IIRFEU7rnnHv72t7/x7rvvHjdHdMqUKRgMBlasWMHSpUsBqK6upq6ujlmzZp3z8YUQQgghhBBCnJmkTKB4+umnAaipqWH//v3Mnz8fi8VywrmfJ7Ns2TKeeeYZXn75Zex2e/+8TafTicViwel0cvfdd3Pffffh8XhwOBzcc889zJo167Qq2gohhBBCCCGEOL+SUlyoq6uLSy+9lNGjR/OpT32K5uZmAO6++26++c1vntG+Hn/8cbxeL5dccgnZ2dn9t+eee67/MT//+c+5+uqrWbp0KfPnzycrK4uXXnrpvD4nce7afSHe3tlCLJYY7lCEEOKUGrqDvLunjURC3rOEEEKIM5WUxPMb3/gGBoOBurq6AQWGbr75Zt58880z2peiKIPePv/5z/c/xmw289hjj9HV1UUgEOCll1464fxOMXxe3dbEk6sPsv5Q13CHIoQQp/TSpgYeX7Wf3S2yxIcQQghxppIy1Patt95i+fLlA4oAAZSVlXHo0KFkhCBGoEXlGdhMeibmu4Y7FCGEOKUrxmeS57IwJuPc6xUIIYQQnzRJSTwDgcCAns4jurq6pBreJ1hRmo2iNNtwhyGEEKdlTJaTMVnO4Q5DCCGEuCAlZajtvHnz+OMf/9j/s0ajIZFI8PDDD7Nw4cJkhCCEEEIIIYQQYpgkpcfz4Ycf5tJLL2XDhg1EIhG+/e1vs3PnTrq6uvjggw+SEYIQQgghRghFUYiEQ4RDERSU4Q5HCCFEEiSlx7OiooK9e/cyd+5crrvuOgKBADfeeCObN2+mtLQ0GSEIIYQQYoTw+XyE9q8lXLeJRCI+3OEIIYRIgqT0eIK6zuZ3v/vdZB1OCCGEECOY2agnbNANdxhCCCGSJGmJZygUYtu2bbS1Hb8G2rXXXpusMIQQQgghhBBCJFlSEs8333yTO+64g46OjuPu02g0xOMyzEZ8TFctGFPAlj7ckQghRqqeetDqwJEz3JEIIYQQ4hSSMsfznnvu4aabbqK5uZlEIjHgJkmnOE60D7b+BWreHu5IhBAj2c6XYPc/hjsKIYQQQpyGpPR4tra2ct9995GZmZmMw4kLncEC5UvA7BruSIQQI1nZ5aBJ2owRIYQQQpyDpHxif/rTn+bdd9+VCrbi9GVPHO4IhBAjXcbY4Y5ACCGEEKcpKYnnL3/5S2666Sbef/99JkyYgMFgGHD/1772tWSEIYQQQgghhBBiGCQl8Xz22Wd56623MJvNvPvuu2g0mv77NBqNJJ5CCCGEEEIIcRFLSuL53e9+lx/+8If8x3/8B1ptUuoZCSGEEEIIIYQYIZKSBUYiEW6++WZJOoUQQgghhBDiEygpmeCdd97Jc889l4xDCSGEEOIioCgKPp8PRVGGOxQhhBDnQVKG2sbjcR5++GGWL19OZWXlccWFHnnkkWSEIS42iTigAelJF+KTKZEAFNDqhjsSMQQikTC/emsHD+bn43Q6hzscIYQQ5ygpief27dupqqoCYMeOHQPuO7bQkBAAdNWCxaXeTiQegw1PgS0Txl+fnLiEECPLzpcg5IOpd8FI+iwJdkPIC56i4Y7kgmeypAx3CEIIIc6TpCSeK1euTMZhxMUg0Albn4WM8TD+2hM/TqOFlAywuJMXmxBiZLF4QGcaWUknwIF/QvtemPkVsEhPnRBCCAFJSjyFOG0WN5ReCs6ckz9Oq4WKG5ITkxBiZBq1aLgjGFzuVHAWgtkx3JFc8BRFwev14nA4ZISUEEJc4IYs8bzxxhv5/e9/j8Ph4MYbbzzpY1966aWhCkNcaLRaKJg+3FEIIcTZcxeqN3HOIqEgj7y6nh/e7pR5nkIIcYEbssTT6XT2X52UDwshhBBCnA2zxTbcIQghhDgPhizxfPrppwF1mMwPf/hD0tPTsVgsQ3U4IYQQQgghhBAj1JCvQ6EoCqNGjaKhoWGoDyWEEEIIIYQQYgQa8sRTq9VSVlZGZ2fnUB9KCCGEEEIIIcQINOSJJ8BDDz3Ev//7vx+3hqe4yHQdhM4DJ74/3AsNGyAWTl5MQogzF49B0xbo6xnuSJIn5Dv8/hQZ7kiEEEKIi1JSllO54447CAaDTJw4EaPReNxcz66urmSEIYba3jchEYPZ9wx+f8tOOLASDBbIHJ/c2IQQp6+nDqrfgIJZUHrJcEeTHC3b4OD7YLRBRvlwRyOEEEJcdJKSeD766KPJOIwYbmOWgKKc+P7sSjBaIG108mISQpw5dyGM+RR4ioY7kuTJngQmB6SOGu5IhBBCiItSUhLPO++8MxmHEcPNXXTy+41WyJ6YlFCEEOdAq4OcT1hbNdnUi2NCCCGEGBJJmeMJsH//fr73ve9x66230tbWBsAbb7zBzp07kxWCEEIIIYQQQohhkJTEc9WqVUyYMIF169bx0ksv4ff7Adi6dSsPPPBAMkIQQgghhBBCCDFMkpJ4/sd//Af/9V//xdtvv43RaOzfvmjRItauXZuMEIQQQghxQVEIRyKcpHKAEEKIC0hSEs/t27dzww03HLc9IyODjo6OZIQgLnYHV8OGpyHaN9yRCCHEuYn2qe9nB1cPdyTDKhqLE27YQiQsS9wIIcTFICmJp8vlorm5+bjtmzdvJjc3NxkhiIudklCXcjlZVV0hhLgQKIq8nx1m0CelBqIQQogkSEriecstt/Cd73yHlpYWNBoNiUSCDz74gG9961vccccdyQhBXOxK5sP0L6qVc4UQ4kJmtKrvZyXzhjsSIYQQ4rxJSuL5k5/8hPLycvLz8/H7/YwbN4758+cze/Zsvve97yUjBHGevLO7lf98ZSctPTKkVYhPmj1NPn7w9x1srusa7lCEEEIIcYFJyhgWo9HIE088wfe//3127NiB3++nqqqKsrKyZBxenEct3hD72/z0hmJkDXcwQoik6gqE2dfWS0evzLkTQgghxJlJ2jqeAAUFBSxZsoSbbrrprJPO9957j2uuuYacnBw0Gg1///vfB9yvKAo/+MEPyM7OxmKxsHjxYvbt23ceohcAn52ezy8/W0VZln24QxFCJNnssnR+ffsULhsvl52EEEIIcWaSlng+9dRTVFRUYDabMZvNVFRU8OSTT57xfgKBABMnTuSxxx4b9P6HH36Y//mf/+HXv/4169atIyUlhSuuuIJQKHSuT0EAWq0Wp9V46geei2A39LYO7TGEEGdlyNv/xSzkA1/TcEdxwVEUBa/XiyLFloQQ4oKWlKG2P/jBD3jkkUe45557mDVrFgBr1qzh3nvvpa6ujh/96Eenva8lS5awZMmSQe9TFIVHH32U733ve1x33XUA/PGPfyQzM5O///3v3HLLLef+ZD6pgt0Qj4DJBsaUITtMW28IT/Ur6Ps6YfbXQCcVDYW4IPjbwWAG0xCNhgj51Pcere6Mf7XV14cnxYRBl9RBPsereQc69sGML4HFObyxXEAioSCPvLqeH97uxOmU8yaEEBeqpHyrf/zxx3niiSe49dZb+7dde+21VFZWcs8995xR4nkyBw8epKWlhcWLF/dvczqdzJgxgzVr1pww8QyHw4TD4f6ffT7feYnnorLtL9C+F1JLYMaXhyQhbPWFeGZdHZd4yqgqHjdiks6tDd3savJxdWUOdrNhuMP5xJH2eQGI9sHG34OrACbefP7372+DjU9D3gwoveSMfrWhK8jzGxuYUeJhdmna+Y/tTGRPAlvmSZPzcCzOK1ubyHdbmVmSmrzYzlKy2qfZYhuS/QohhEiepFz+jUajTJ069bjtU6ZMIRaLnbfjtLS0AJCZmTlge2ZmZv99g3nwwQdxOp39t/z8/PMW00UjbxrkTYf08rPqcTgdLquBSfku0oonqscbISJRBX8oTiJx/vb5zu5WfvFONf7Q+Xv9X6ykfV4A9GYomAlZE4Zm/0YbpI0BR84Z/2qqzcTEPBdFqSNgqaXUEiiaA9oTf/QqCmw+1M37e9uSGNjZk/YphBDidCUl8fzc5z7H448/ftz23/72t9x2223JCOGk7r//frxeb/+tvr5+uEMaVr9ffYAbf7Wad3Y0H92YNxWqboWyy0CjOfEvt++Fvp6zOq5Jr2NheQb5nqEbyns2phV7+Jd5xTit56+3c3ezjw21PXiDUh30VKR9nj97W7zc9OsPeej1XSd/oKJAe7U6vPV0aDRQPA8yx517kIMxWmH89ZA++ox/1WLUsWhsBjmuEZB4ngazQUcwGqPDf2G8N0j7FEIIcbqSNpbxqaee4q233mLmzJkArFu3jrq6Ou644w7uu+++/sc98sgjZ32MrCy10mJrayvZ2dn921tbW5k0adIJf89kMmEymc76uBebvmicTn+EwJn2Rve2wI4XIbsSyq866+Pva/Hx5OqDXDUhm/ljMs58B5Eg6Izndaiu5mTJ9lm4e24xN07OJfcC+TI8nKR9nrmNtV08t6Gez84oYFK+u397OJagOxAmEImffAfeBtjxEuROgdGXD3G0Z2AI2vZI9P2rxqFJbtH5sybtUwghxOlKyqf3jh07mDx5MgD79+8HIC0tjbS0NHbs2NH/uHP9cl9cXExWVhYrVqzoTzR9Ph/r1q3jy1/+8jnt+5PkywvL+OK8YvT6wy+PSADq1kJmBdgzT/yLKRkwajE4z22oVTieoL03jD98FsNQw35Y/wSklUH51ecUx1CyGvVYjRf3l2cxDOo/AoOFYDSLNl+Yvo8lmBPy3Lz59XlH2/aJ2LOh9FLwFA9hsGco7IePnlB7Pc/hwtaFINVmHu4QhBBCiPMuKd98V65ced725ff7qamp6f/54MGDbNmyBY/HQ0FBAd/4xjf4r//6L8rKyiguLub73/8+OTk5XH/99ecthotNIqGg0QxM/DUaDZsPdVFV6AFfi/qFVm8+eeKp1UL+CeZmnqriZaATQl5ILaEiK4Xf3joBvdly5k9GbwJPKdhzz/x3hbiQJRJQ+yFY3cybciezilPR64/vNTtl0glqj2LB9FMcTkGrVd8z9jR5SXeYSbWZDg/T3QOOXDA7zuqpDEpvgtRSsJ/5PM9z5m1QiwLpDOp5joXU4b8iSRTC4Uj/ciqKouDz+XA4HOd9NIoQQoihc2GM5TnGhg0bqKqqoqqqCoD77ruPqqoqfvCDHwDw7W9/m3vuuYd//dd/Zdq0afj9ft58803MZrmCPJh4QuHP6w7x5s7mAdufeP8AX312M298tBNCPVB5M+Qf80U0kYD970LL9lMfJBpSK17uef2EDzm0/lVaVv8BQr2w/UX0W/6ofoE9UzoDjLsWcqvO6NdisQRNPcEzP54QI4VWC1W3qa9/GJh0+hqhZccJfvEMNGyE2g/4oKaDJ1cfoDcU5VCHn688s5kf/+PwvFFvA+z8uzpK4nw6y7bt7Yvyzq5W2n1nuZZz50HY9H9Qv079ufZ9WPOYerEM8IdidPplneihFI5E8R/4qL9irs/n48fPvS8VroUQ4gJzwY31u+SSS066iLRGo+FHP/rReVui5WKnAZxWAzbjwMI5E/Nc1JQGmKDZD/t2wqRb1S9+R8TD0LhRXT7hVJUs9SYonAXWEy8NsJFyXI4cssx2cOaCxXXSIkahSAzzeRyq+tcN9byyrYnvfmosE/Jc522/QiSVLb3/fxOJBLEEGPVaqP0AOveDu0hdi/dste6AsI+U3LG4rQb0Wi0ZDgtzy1IZnXm4d9ORow65dxed01M5X9p7w2xv9JJqM5LuOIsLkPYMtbiap1T9OSVdHYJsUPf1i3f2UtsV5OefmYTNfMF9pF4wDPqB1dTNKbK8ihBCXGjkU/ITTqvVcO3E44elzjLUMGtcKxTPB18JOAsGPsBggalfUJPKU9FooGjuSR9y6YwpaDVALAzBrqNfWhUFGtarc85c6tzRhp4gP3plJ3NK07hzzvmZg1aSbqUq30W6TYpkiGES8qqjAnImQcbYc97dr1cdYEdTDz+5oRJX8QJ1DclIEKpfV9vjWSxNQsWNkEgwyeJkUqGnf/OPrjvm4pNWd+Ih98NgVIaNz87IJ/1s500aU9Rq3kdkjhtQvbc824ErxYA1UA/tnZA35eSVv4UQQohPqAtuqK1IjobGOnZX71K/dGVVDL7unNV93uY5OS0G7GaDmni27YTeRvWOvh7Yuxy2/kUdsgtY9FqynBZcKedveZOZpel8Z8lYslxnMa9UXPBavH08u+7QccV4kioaUoephrznZXfuFCPZDgt6rVadm50+Wh0237lfvbhz0lj64MC70PuxtSRNdrA4z0t8yZTpsKCN+iF+/tfNXTolj2ULy9A2bYSatyHce96PIYQQQlwMpMdTDOqRulJ2NXr4RXuIMdlD0wvY6u0jNcUwsNhJIg46E3B4WJXVDenl6hA/fwu4i0i1mfnRdRVDEpP4ZPrzulpe2tSEVgM3Ty8cniDsmTD7ntMbRXAabp1ecPzG9NHqMU413NbXDIfWgEarDjU9Q63ePjKdI+giTrAb1j8J2ROHbnmY0kvVIbnns6CSEEIIcRGRHk8xKJfVTEmGmy113Rxo95+/HUeCEOji3T0tXPvL1fzXP3YPuPuZDa3sCKf3D6sFYOw1MOUucA1TQvBxva1qgiwuGldX5vDpKbksLD+LdWPPJ4N5wDDNh9/czb1/2UTsBGvqbm3o5h/bmojEEqd/jCNJZ7Svv0DOcTzFMPFWyJ9x+vs97Kdv7OKq/1nNy1vqB2yPxWL8csU+1u5vP+N9njOjFdLHqPPHh4rVffbzWiMBNTkWQgghLmKSeIpBHegIsK89QHWbn55gRN3obYD1T0HXwbPaZ5svxKvPP8nuf/ycdHOcknQbWc6j864auvw8vLKW/3egbMAcKgxm8BSNjHlTHTWw4XdqdU9x0RiT5eTey8rJcIygXjpge4OXDYe66Q4Mnni2+yLUdwWJxs8g8Txi31vqazk0SGVQjUZtcx/vfa1bC5v+pCatJ5DlNFOaYSPDNvBcrqhu4/FV+/n5O/uInUmifD7oTWpF3MzxyT3u6dr1ilr5OxYZ7khGIIVYVM6LEEJcDGSo7cXE2widNVAwC/TG4+/3NUPNO1CyQK1GexIP3lhJhz9EpsOMty+Goiho4jF1/lk8ekZhPbZyH2trOvnywhL2U4DHlc2cgmye/deBvQ95HhtfuWQUOSeYZ/n3TQ1U5joo8RjVdfQsLgD++41dhOMJvnd1Eobf2tIhq3Jgj6wQZ6P+I3XO5EkKCT14YwW+vhjpzsEL4ywsz2BuWRpmg27Q+08qbQwY7eo87hOo6wyQYtKr63OCmnCGfaCoieOLq7bw6t4An55WSG1ngPquPv7fdeO4c3bJcfu6dEwGl45JV6vsnkz9euiuhXHXDf4+dp5FYgl2NfVQmedCO9hc9mTIGKcWe9Kdv3nrF4toLE60cSdmpw2v10tPT8/hZVTOYrktIYQQw0oSz4tJ2261AmzqqOOGlCUSCcJ9vVh8TRD2q+v61X4AxZfQqXESSyhkOszc/6eVWJUQ3//cErJdFt7d08bm+h4+MzWPXE8RzL23v+fxodd3sa/Nz0+XTiDNEAOzvf94u3dswd7wLnkzl9LU3cee1l5iMYWv3XrtSb/c/euCUYNuX76jie+/vINLRqfzv5PqoPMAzPwSGFN4e087gVDs/CSeXbVgckCKZ/D7zU4Ye9W5H0d8ssWjULtaXZrjJIlnnsdGLJY44fJBOq0Gnfb0ks5frdzHBzUdfP/qsZRnuyCjHDLKue+5zTR09/Hbz03GlXI0we2LxHlpUyN5HgufnnL4QkvpQii5RC0C1llL6u4/MDpURM3ubv7ZbmdXi5+rK7OpzHfz/r4OFoxJV4uGAXq9nv+ZeIiE1oBWf3gtzkgAehogrUwtYKYocPA96OuG8k8BQ594vry5kRc2NfDlBaVcMlxDrXMmDs9xLxAGvYZoLE7dqz/lz1mfIxGPopUkXQghLjiSeF5MiuaoxUMGmcf0m1UH2FLv48fXfIk0txNatqvVLbMnsfxAH96+KP82v5TJ4fWY/Y0QvQQMFipyndjNejKPrH93zHDX2s4Ae1t7iTdshoa3YPKdkKoub/LWzibKelrImx7jh9eO40sLSshPPft116qyzFw5Pou5o1Ih1QgGG+jVmO6cVUjoBHPgzkjYD1ufVRP3ypvOfX9CnIjOAJNuO3GPXjSk9ioarfzvP/exv8PPQzdOPKd1Inc3+9je6GV/m19NPE/BYtSxeFwmTssgx9z0B9AZmTdvIRN9XlprV1NYcR11Y0cxb0wmL22s57kNDQBcPfGYZVtiIbTH7q5+PdStgcpb1PcOJaEOi80cf9Ke2NOmKOroCMOJh1BPynfS7g9TnmU/4WPE8DuyfrfJakOJx4iEQ8MckRBCiDMlieeFyNcMDRugeC5Y3Ee3GyxHh9AefF/tlShbDEC63USe24LJYlW/jBntMO1fwJbO1EQv4WgcrVbDTTfcpA6nPfxFLc1uIs0+eJXN/++mKvxdzWQG9kJvM/TUql8euw5yTbaP7on/CvEo+rZd5NvSgLNIPBNxqFtLxsH3+e+FSyE9H8iHrKPrBt42s+jM9zsYkw1GXwnWE/R2CnGufM1Q+z4UzQdH1okft+NFde7lzC+R5jARjsVPPkTV1wRag9peGtar63Ra3QMe8u0rRnN1ZTaXjh143Edurjr6Q7BbTdRsmRBooyJ3kBg1msNrgGrQjb0ad28b7pwyyvOmgk79SLlkTCYAc8vSBv7upM8O/DlrgppoHrlYptWp70un6sXtqDncW1qnFkA6UeXd2vehbp1anMyWNuhDyrIclGVJJdqRLhoJ80xdKvm5kVMP1xZCCDEiSeJ5IfI1qcuLpI8ZmHgeq/sQdNWoX+zsmXx66jFzErtr1Z69gplgW8jozGOu9HvUHsufLd9DXXeQn15fiflIL0vDerWX8XDSZzPrsdW/AdGAmrB5SiCRgM1/oiTQCdlpsGW1+kU2dzJUfmZgjLGwOtzQVQjdB9XncyRx9jVBoEOdU7bnNXW7KQk9ErlVp36MEGfryDqaFo96seZErzdPsfra12j43DEXVp5dW8s/q9v5zpVjGJV5OFlKJNR1bi0eyK5U3xs8xXBwFbTtUYeGZ00gP9VOfuop2lD162rbK5oDB1ZBxY1qu/y4WBi6DqjDbv3NgNKfdAJ4bEZunHIa86BTUiFl1sBtho/NZ42FoXmbOgS+txkKZ6vvCZGgmgS7C06ceFrTwF14/D7FBcloHpqlvYQQQiSHJJ4XopwqtbiN7STzkQpmq8lcy3Z1fcBj2bOhaDakjiEUjWPu2QcaA6SV9j9ka30PjZ29dPl7yDGnqV9uaz8As2tAbyN50wHl6BfokA/6vJBaAgUzwGACow3sORwn2KkWWAl2qUWRNLqjieehD6FjH1TcpPbeFM1V51eeqe5a6G1Re0VGQlVc8ckU8sLOl9XCVLO+Crv+Dk1biGeMI6E1YNB9rAencPagu9nS4GXdwU72tfUeTTy1Whh1Kegt6jBxnenoxalQr7oW54nEIqDEjw5FzZumFg9y5qvzLG2Z6giJhvVqEpd6uGhQViXYs9ThsM3b1GVZ8qefuqfybHQdUIuiWVzQ16MmwuOuU49lsKhxnUjmuIEVssVFRVEUvF4vDocDjby/CyHEiCeJ54VIqz150gnqkNdJtx2fdII6tC13GrVNTby6v5fbE6/idrgGJJ4/ubEC7c6XyKneA+4vHZ2TdswErYN7dxKNw+ixx/baKOAphOxJag+luxii4cHjcOTA5DsgJU1NPo8d4lq8QE1w00ept9ORSKhfTI8tDNS4CdqrIX0stO9Wk+CsJFS/FeJYiYTa2xnrUxO9/BlgTOHVHe10+COMzkxhQpoet8N+dN5nJACH1vSPWgD4/tXjuWFyLjNLPpZsZR9TnKazBtp2QellYE09efvZ9TL4W2DGl9Uey/TRR+8rP1xEK9wL+1eqSeeRxDN99NHHjrsW4vGhSToBHLlqAaa8maBEwZF98sfHY2rM1hOMBhEXDZ/Pxy/f3MZ3b56H03kWFyaFEEIklUyUGImUcywTH/aDv139kniiAh0H3iV19zOU2ULEx12vVpCMhQk27GT59nqcVhM5hWMgbdTRZFOjfrFMJBL87v0a7Cv/g9TV/4mSOGZNPrMTKj6tLukCsO8d2PU3NSHc+hdo3Xn0sdE+OPQBGz9azbO7I2rv7O5X1XlqtvTBh/h9TFNPkMiRNQEbNsBHv4Gtf8W74a/Ud/qhdBFU3aaeh0NroGnzmZ1LIc7EYG3X364mZbPvgcJZ6jDR3a+CLYN0uwmrQcfu+naCH/waqv+h/k48Ci271J7Gxi2w+U/QXYvNrD8+6Tz2UC0H+Gd9gi2ORdC5F3a9pA5VHUywWx0RYE0dNGnsDUXZ0+IjYbDB2KvV95W23f33d/kjLN/ZQkibcuIq0KcSC8OWv6jrg55I2x71uH3t4Mpn3YEOfrOqhkgkPvjjD6yE9b9Ve2HPQSSWoKknOHCjr1n9W/TUn9O+xfljTjn7onVCCCGSS3o8R5r9/4S2aphyJxitZ7ePvW+oy4LM+srxiWewG7b/FZxF2EfP58qMTIiH1OIedR9R/8HfWBecTF9sFh5rMW29OXz6yBCmbc+Czky4cD4H6lvwWgrJzUpHc+zyKJ0HYdtfILsK+jrVngqLW+2F8DbSoHjQkk6OIQg6I/ga2VTj5dkOLdct7MBa90+wZkDhjOOfVyKhJo7OPLBn0tAV5PmNDUwvdjNnVDo4c9T18CIBDtQ185G/mX9dMArN4fU+qbpd1skTQ2ff2+qw0Ml3Hp1TGAvDpj+qvfuTblW35UxWh7PqDMwpcjK77Xl6nBnYM8aB/nCbP7QGDq2GUZepw9t3blZ78U5GUVDWP0ne7nXUFCylYuFl6ONBdYTDYEJedR61VqeOOEhJHXD3pkPdbKrrIWWKjnxrqprIHRPDGzuaeGVrMyaddtBlSHY09uCyGslzH35OkSD0tvZXvgbUi0x9nRBOVe/Xm44mwd4GdQ54wUwouxzS1B7WFzY28OH+TiYXuplWlMpxnAXqeT/HqrgbD3Wx9kAXSyfnUpCacvQ5eBtO/bcQQgghxHEk8RxpdCZ1iOrJ5mWdSuYEsGWpc75OxJaO11PB/hVPkq/pIP3yb0HGGHKqrqTKl8HsIiv/814TB9oDXDYuE6fVqA4P7PNh2fUC91VUoi38MWYCVLd42dvioycYZ8kYO2k5k9RelJYtkF1JdSyTDTu6uWHql3j2+TdYsOYBckrT1XlsM7/CAvOHXNK2HWvxNdDXCKGP9VQ0bAA0anK87y21gEr5VaTZTVQVuChJP3zF25mn3hQFT14vixTNwHk/tnT132gfVL+prh0ow27F+aI3q0O5j227OqOaOB1bBOzYOYeJGJr6Nbg9JZA3nd6D63i3K4spOVnk5Eymz1NOQDGSNucbR5PZkPdwO6hSRyQcodFgr7yWZl8IS8cOevrmkJZdcvT+9n3q+r3F89TkzlME42+Eg++qBcJI5YN9bYSiCS4dl0VlnguHxUB3IEJzzMD0OV8bsPzL2JwUDrTbmZh3fMGiTn+In7y+m7HZDr5/9Xh1Y90adU531e3qHHVQL67N+JLaJj/6jZpcHhni29ejXkDzlKpt/nACfdecIqYXewZPOgEyxqi3c1ScnkI4liDdblbnwu5+VS1UdOzfQiSZQjgShoSGcxwXJIQQYhhI4jnSFM1Rbx8X8qpffo4kTx/zytZGrEY9i8dmqgvDU37cY/x9EQJRM5kz/g2ASG+IWksFzjTo7IxS2xngyooFXLP3Ldj+Ov824za6E3lq0gmQNxXiUT6o9bKr3sUXrFtg65/p1lTS0hZheWgsXcESvn7plVC/DsbdABlj+N8/b2TV3nZcVgNV5SWkerugsACyJ0AixujOFeBvBO0N6pfQY3slFQUaNqqFgfKmqFU2D89vNUd7uKT7BXBfChzzRVOjoTD9Y8sjJBLq3FhQ10jsOgBmBzBI4hmLwL7l6vxUSUw/ceLxOC2+ELnuM+wxK5438OdIQB2eOkh73tXk5aODXXx6Sj62ed9Se+cSMRJth+gOQsCSDYWjWbm9iZo2P5+fU4zjSLOIBNXXryN3QOK5sbaLpp585kxcgrtmFd4P/4hlVBUp029XH9C2G9p3qcXJLM7D7ylBdZ714XmTv35vP5Piu1jQ1o175hdxF7h5fkMdHb0RJhe4B3xg/GVdI2/saKEk3aYuaRQLq72+qaW408Zw3cRcct3HJGgZ49XE1fax+d5anZpUekqPFiFr26UOA55wkzpCo68bRl8OwLgcF+NyXGf0pzkbWQ4LWY7DF+8iIfDWgynlzJLOY993xDmLxuIkGjYRVhKQXYnP5wNJQYUQ4oIhieeFYver4G9T54l9bLhoLJbg5c2NpNlMauJ5Ag+8sos9Lb387vNTyXRaSLebuX7RPLRaDV9/ZgP17V4yvNuYnOeC1FJy0tzk6E3ql+eW7Wqvg7+d8MEPccVTqA8lKDLZGUUXblcIq9vGrMoctbLtzpfVqpct27huwnRcFh2zjPvx1D4P4z8NpQvUoBIJdRidxQ3+VmjcqPZ4tO6B1l3ql2OjBUoXqtUz3YXqnFNfs1o0aPdraq/S4R6Obn8Et8048Ik3b4OaFepyLs5ctejI9C+euEc42gfte9XjSOL5ifPI2/t4fXszD3+6kmnFJ+hVA+g8oP6bWjL4/fvegfY9UDgHgh3q6/pw2129r4MVe9qIRKNsro/wzcuLGRWrwZnwcvtYDVpzLzTsZXTGaBxmAynGY96qHdkwc1l/RdmA3o3Omc0/tjcT6apn7txUDmjyWN0VZXKnkYVbnlGXPXEXQscetciRRqv2Jm76I6SWwYJ/B50Bh0nPWN9uundsI338dWB2cmVFNrG4gv7YyrstO7hltAatJpsFo9PUJNF7uJJuIoY2Yyw3Ty8YeD4cWSdeu1RnUIsUHdG0BQ68p1bPzZuqVuuNRY72uHYfUpd+Kbvi6Plv2gabnobxS9U1js8nYwrM/MqA4mqnFPbDxt9DZgWUXnJ+4/kEM+p16NDii0RpfuNnRFJvGe6QhBBCnCZJPC8EiqIOv7V4Bp2jqNdr+fcryjHp1GGlsViM1Qc6uWT04STU3w67X2WRO4fZ8XrcB1th0qcB0GrV39HrtLhDdWRW/xP8hXDZD4/OterYCwfeVZcuCHYxjgO028fQHrESGf0pRo+ZgKu7kf0bduN/9xew6BZ2tfaS1tFMauKfzF08lg8O6vjb2n3cYezBkIgeDT4eVm/+VvXf7lq8vX72b91KsXIId0YR+Brwrn6aQx095FVdhkcfU4sUTfsiLPyumhADb+1s4XcfHORrC0cxu8AMSkItdqQ3q/PktMecu+p/qNV2p37++PNtcaqJqeEs59iKC1pRmpVxOXbS7adYM3Dvm4ACs5YNfn9mhXp/xx4IB9R5nVF1PvVnpuUzqcDJSxsbWV3TyRXjvIyaNAFMDrRWD+x+DV/LfgzZC5iraYYDOWpyV3EDWFw0BrW89NZabmp4kHZDLhuzPsPcnGw69r7GB6sL2eL5FNpiKCsJQdNbsOVZsOdBV51ayKdzP2RPJFC8hJ3NXdibexmb5+GW6YVs2vNp5o+7sb831W4e+J6jRIJEd7zC5LQiJn/6s+rGLa9AT5061LjroPqedZLlLdp9Id7a1cKl5ZlkuQa5AOTIAXeRev7KLoOOGvjgUXUZlfQx6vZEbGAxp7AXvI1qYj0U9MZTP+ZYWp36vmM4yZQHcU5sFhnyLIQQFxJJPIeLv/1wNcnTGIbV16P2/p2oymssQnmsGlxlAPz8nX08+1E9d84u5OuLx6g9G/tXclXmOJhYrg4B7DoINW9DySLWel18flYxodFacmMJMLth218htVRdmy+zAvQmGqMO/lFr4IppX6GtehddB9bjiWoZPX46yvbnyW9vQ6PTE4pDV8KKsXMP2oIJvL0nRE+flhbdRG5ZNA9toJl1+1opjtSQ3fGhmhjGQurQ3NJLqa5pon7HGpTRlUypuhUaNhFpPECbwUxPopQ1m/dxXfF4yq2uAcMY0+1GxmTaSbUZYfuL6vOcvWzg0g+gFknpOgju0oHnMR6Dzf+nDgUs/9QZ/TnFhaGxO8i+Nj8zS1IxGwZZ/iMS4KaCIDdNnnzqtln+qaOJTzymvqY8RUcvDqWVQvMmtaDO9C9C42a1Su2UO3GlpJPp3cHVZVlURDtIPfQqVHwOWrapa3AG2vmox0pk+5M4JozGXWRX52EePt7+hhb8e1ayP3MSeU4TV9Q9wkeBa1gRHs8VJjMZ3Ru4/srLMaa4+UdHgtmBlbjTLBDqgu0vqEsXhXxEJ3yePX16piciAMwbnYG7t5p3//FXyubHGVM177invb6xj9r4bBZlltBfX3fUZYeHFvvUC0jHJp193epw+dzJ/UsmfVTbxStbm7EaddwwOR869qvVfsdeqxYfKpwDaWOOLp1itKrrDx+5GOQuUkd/HKEo6lDnvKnga1FHSpzNur/nk8ECk28f3hiEEEKIEUQSz+HQUQPbn1e/rOVP7d8ciSXwhaKk2T7W02J1Q8VSNVH9uIb16lDS3mbi4QA9WTOpyLWT4zZj0unUpHX/O5AziVbPFHZGclkQ/ie6xs1w8D2CfUF+uW8G+TaFB6wvgdUB+bPgwAraFQcJRx+ZTgvozOx64f9jc2AC8Uwz48KHyMvKoMTmhWgAg8nCGGec91oMfLRyEzOzRxN3OnEZu1jU8UcqJ9/DKKeCqXUb4dZqarQ2NDYt2c5cKF5EdPMzaGrfQ191O1O63qRgfCH2vDyoW8u7gWK2+W18YZqTtgPb6TJk0pVZeLRHtq8bOmqoyplIVcHhobHxisGXkVAU2PqsOpQvb9rA+zQadf6W7gx7Ns5EtE/tQU4fe+Y9KOKc7W8LsLmuh/IsO1nOQXqiGjbAoQ+h8uZBh9D2BEKYdXrMZv3hHrnD2nbCntfVYeN5U45uL16ozm08+D6YHGqBLkMKdB9iyz+fx+pOZ3LfPuIpWcT6guzbuYUcSxS6azFmXE973I65eBQ4M2D80aGoqaYEVdZ28owaMnr2YMktZm7FVPya3Uw78D+kFU/EEijikS2Z/P7DTsZnz+bbo0ZRNcanJmXp5bD3LVx7X+AOYwoc0kDWF8GYQtiaRcAzjo3dFiwdAdLDBzFEetAXzASdnjSbiZbMMsyaABx8T00SbenAMfPPfU3qcPjcyWpPaMN6SEkHq4cOf4i9Lb0sqcjksnGHE0utVk0qjyT7OsPRpNPXos5rnfy5wf+owW71glH+dHWe6La/qBfLxl1z6heEEEIIIZJGEs/hkJKqfjFy5gzY/GFNB5vre7h9ZoFaSfFYx/bYHcvfpiZeBbP4yVYLy1/4gP+5tYqn7pyOPd6pVm/NnQYtW/Ftfom3lesZk96LXWPHkTcTa8TPZfngbdjD3mCUiqwg2h0v4J/6FT7/+52M2ryGX8zwgaeUykwjzr5adhZ8lgWzbiDatBNlx4v43v0lDqMG45Tb2fj2fnZ0OKmKbaNq/FgwjiOzaRuZvWtJ1Gxnn7GcrIrPsKR+G13N+/lFezqFgXZ0mtno4yaW9HWjq3mLrOxKiHbDwZ3sSzj46ICP29L2U+Lbwo8X3sSjmzoIRWIsGp0GjRugfoM6rC21VP3ymjd10NPlC8ew2vPQ23Og+2Nr8Wl1MPHWE/7ZEgmlf2jyWWvZATXvAJr+IcIieWaUehiTbSPTMTDp7AmE2N3US6ahmLwiA0Zn3nG/29LTx+1PreOGzDaWTTKoczaPXDzwlKi972mjqK5rIa31fVJLpqjJq5KA9mq6XeVYWrdg3vIMXPoArolLcDS8h8Fsw1L5KZoO7cLrDxIIatH0xCnxHGD+kpth72sowSa2JApJtRopMAUp7/onWZd+muqP3sDk92MZN5nUFAvzCqxodIuxjJvF6x3ZTMl3cHB0Og6TAbfDBkW3wobfqa/D3iYI6tVK2mWXgdYIiQRTxpZR59ex/J/vEGk7yNze13EYE2QsSYOMckrSbWol6V2vQutOVnZn8Kt1nSydnMstM4rU81G/QU3G3YVqlW2ziw3dVtI7eukNxVh3sIsrxmdiMx/+CPIUw4wvDv5H27+CRNchnlSuoTArlSsqBr5votWqSb3OpF6cK1l4tGruqQS7weIa2EN7imHC51OHr480hwzFFUII8ckgiedwsLiPvxrf28rElhexuybjsJQO/ntHJBJQ/ToRkwfj6CvVYX716ym1zaUwNQW31Uimwwy1dVD3IUz5PMQjRHs7+cjbRzS+i2DNcozTb8HcUc0tqRt5L15PwGAmEY+i1YClbQsemw19tJmm6s3kTM0iMyOTzNY9TM/rAE0JBkcGrWGFsL8TfaoH68H3GVs6F+2BWtb3ZXEwUMGNVRPVXqCNv6cuoONH1W4+3fgKld6VmFOLMdbvpsusZcLEaXi6t4O+CJY8DFan+kUyFuZWQypLJoZJjdZB5ya2Nnj5/Yft7Gz0MTe+HmPHLqKll7P1w7cxa9+k4hp1CF44Fmf5jhbGWHsY49bhSynlD2tqGZczi0tnjTvtNT0/rGkjx2Vl5Z52ClOtLDpJAadTOrKURtoJLiSIIWXS68jU9ML6Z9TlfDLGAvCjV3fT2tZMVkYGN88Yw3S9US2StXe5WuAmYwxmg4Z8j4V8Qy+0NEBqKaG08Szf2cK4lF7KSmbR6A3zp+XvM6Pvfa5OzVQTz9r3iGmNvNFTxLy+TeTHQrDjRWbN+gIbd2Xz2y09pNam84XU3YxO1NDqnEqt/QrG9bxD5FAuxqrPEQj4OLRpE57eFTBhPrp4mFSnDeOcZXQHG8kytMHWP1MQC8HYhbTsWkVT0yb2ZS5h2cLRlGcfHnaaSIA1DRwW4oEOdPGwOiQ1YyxUvwGBVihawMLIh+TZPyLDHyZePJ+IPQ2vJZ9/+82HVLgifK9wj9qbmVtF/I2XGN0bYWvDZdxyZPnd4nnqaz1FHYxbE3Hzjb+upzgthSsqsvnJDRXkeVKIxROs2NNGWbyGkuxMSC87/o9WPJ+9mgb+92+NTC0KHp94mp1H52rHo+rFANPxS7wc58jIk9FXQm6Vum33a9DbDFPuAt3Qfjw+v6GOX66o4RuXjeaGycdf6BAnpigK0WgYRaegAF6vF4fDMXD5LCGEECOOJJ4jhRLHrY8yJd8G+kHmnqEuyG7QaRmTZqaroZqtPhsFhiJK7dnQsJ7POrby2TvvUivgthpY16IQa1IYP9WOa8G32Rf5J19sqcZpNGJwTcBUMB1ifkw5k5iTNxNN02b07dugZQc6nYkvWSL44hacU5eCO0v9Uhb1w4F/QtMmAo078LqnEYzryNG1QdNmrp06iYO7XqQdD12HYvw97OWKqlIskz6LLqeLEkOQHE0z5qgNh9tNVsVU/lCXyaJYO0XxA+rc1ww1KdvZ0M2jy6u5PesQCwpSwJkPKEzMtbNkrIK9Zzft0Uw0ZPD/VkaZpWjxmHX9C6RE4wre7jZS9z4FngysmRUsUbowJsZD+qzT+rNsr+vm2y9sZ+6oVKaVpGI1nWOTMaZA/rRTP04MHSWuVhyNHy1yNdUTxNO+nMzsSynJnKhWrO3Yo/YMtuyEBd/ClWLj6btmQGwSrP451K+jusdIb1MLhuA7oL+Cj/bFGd3xDtHR89Uht4kE6EzoM8Yw3lZI3Ph1qH2evgNrObD/AD2jPkdxphtd2yYMeWl4Fn4dZ/M2Wup7WJlyORu2mJii7eGq9ie5si+Arnc/dBeBPRP6ehnbvpnXu7IJ5WQzrngRphQ3BLtI8+5ioT6Fzp4ifrE8wuOfPzwXWquFiht4fXMtnY17mFNopyRyQK3WarZDIgrbn8MV8TNtzmXQXcfOrLkkPPmY0dAdiNBnTQDq80JvYXGZm6xUGL1g7NFz3HMITE7Y+zYYTLgSVr7oWEON7RIcZj1FaTa0Wg194Si9HY0kOt6BaMngiacrn/JJ+dzjraEix3H8/cfq3K9eLCgOQtEpKttaPOq8+cPLMwFq+zQ5k9LjmWYzUpZpJ8P+yRtyrygKPp8P5djiUGcgEosTqt9GtChCJByh4eUfw3XfJT8/X5JPIYQYwSTxHCkcOTDna6DR0O4PkWo1DRjWmYjH+fDtv6FN8TDmpuuIT7kb4/aPiG7+Cx+0NRHLncl4VyZpnfvUapu2bHy2q9jgvpEyWz70ebku9DKkHJ736MpQ19HMngCAFcCdCw0Z0LKNQHcL5uaDuEwG2N4DM79ArOpONm3dSmHfTjITXfTG9dR5ozSmjGGUx4PNkQeeUorHTia3q47dHTtJ2b+RvQft5FUuIH/fS/zQXagOUdzXQjgSoljbyhSXGSV3JpSNpUfjwhZPoNdpafeH0ffU4gq9A2QSsB5k24FuHM4Wri9QiHg3k9ruJl77IVekfZ7RNhO5FUeLodhMej4zMQ3DehfkVKEPdjIqth/aOyA66fhqk95GdV7oMXP7itNTWDIhm6p8F5+q/FhPyxnqCYRwpUgVxmRq6gnyq5X7mTMqlSUTDv/9HNkw52v8fWsjxvYmJuW52NQY4jPZhVSNGwtWAxzYrPaIGW1w8F21uFfBdPX3dUYCKXmY/U1Edj1N6qilFHjywZ7FxLFm9nmnUFU5Dtb+Wk1sDq2FcA8Tp+ZA1hRI/1eUiIJl/d/JKOtB6fZT2P4eafUWiFdC+jhih7bwYbiU1xr7yMhpJ97XgSZ1NIbx18DWv6iVWzPGEoiZsLfW01LdyJbsS7jrlkUQ7kU/7S5Ku+u5cd97hDODsHo9FM/j2YZU2npDvFfdjsk4k0vDq6Bjp1ohtnQhdB1epgQN+BqJxSPsOtSKzZtgSUU2r90zB4PBACxiy7p38f/jD1RccTcVU8YD8PjKfVQfauJ7qStJs6dA0ybIqSKtZD5XFWsxzyjB5jnajiytm7gu+g6aKVcOWJP0iI21nYzNcGC1GvjXBcfff5zUUhjzKfXfY4V71bVPM8Yf7clM8ajrAh+rdOGpj3GeLCzPYmH5CZaXucj5fD4ee3MTzmj8rPdh0B8t/qXRaHnk1fX88HYnTucwF5USQghxQpJ4DoeGjdC8BSZ8GsxOvH0R/rT2EIvHZmDQ6Xh5SxOXjEmnqsDd/ytaJcZljjoUu9pLk24zkp7YxIFEHI23njpNIati5ViIM8n5GYKddbgOvcB3PvsdtE3/hN2vQyygfvFq2gwa1HXyIgHo64JAuzr3sGQRhIM0+RU+cl9Fob6HjqiLBRY3z605QOqBDTjMQTKv+w665lq8r/6BvIwurPEuAtEEKbmTYOw1GDc/g8PciaanE22Kjb1hD9NT0tFp9axst1PdNYEbe/5IkV7Llfo2LH2VtFuK+fOaWqYUuZlXls4l5VnEA9NwtHZDQSHx/R8SMdhRdr3GpHHTUMpyMfvroWQm15eXqOsmRjtgTzXYsiFvMiZPPiz6nlo0KJFQn2e0b/AlDva9ra63OPfe/sJFNouR71417pz/5P/7zl7+/FE937liNDdMOc35Z+KchSNxWrwhvH2Hezd3v0pjcxu70y7lrZ2dpBh1XDk+k2W2f5IarqetdRKu7nqMgQ4Co2+kJWqkNH00dOxlebOF7MAOCkwhfJtfwpE9irLpVzPGauDQ+jr+uPFdUsfM4auTStje2cGWRgOz8vOwk1BfW2Y3JBIkGjewtS+NWP5VTLT08g9HMblKFomeXeDKQ6fRktf4D67L7qbyii9waVo361e7MJnsjPc2YowF1fmkxQvJ6KhmgbKFdq2Co3c9BC7noN9Arq8VY2c1ZdmpkKiB3VshJZ0n38/BatLT0Rvmc7OyyCmYDlsPQmcNpJWBrx5yp4ACZI5HnzmWBYoDx/pfwIchDIt/wL8/v5loLMElOSn0KHnkKnZch893QoHOiI7gmGvAlaIOt82dwpo2PT/cFWBRuIFvj1oDOZPVeZ3OXAw5lZA19rgqtH/bWMd3X97JFeOy+PktVaf3B9cZIGfi8dubNkHth6C3Dt6rKpLObLZBpP2sf19RFHqDYcJadcit2WI7j9EJIYQYCpJ4DodETF0+5PAwo3/uauWZdXX09kX58sIyxuY4KO5dD5s7oPIm9cuUohCP9rG7oYtos5cx2U6YeAuGXoUeislJK2RNbZj1tV2Y8n1o43qirkpqvHHMa14kLXQQv3scW5rNTHOPw507Bf+6PxAyeYjWbSK9YAz6kE9NQhvWUWiwkaEtItx5gPGTPwddB5jV8BQui7pkwks7O7lm2jTy0/6OPt7JXm0x6/scjAvlMMqlQCiKKz2ftyzzsbsy+O7KBNdP+hJXjsqiesWzFPftRHGlkdK7m4mWMJHqF6gt/zIpBoVCc1//YvErtx+grXU3xTTiaN1A5YIf4jDoeHJbH/hjfH5SOabxn1KXssiZAlkVsP4Jmrt8/HQ13FHkpUtxMKpsDEVpNnWI4omULlT/LtrBhzqfC5dNT77bgtMqTS6ZrCY9aTYjjiNrUYZ66dn6MjtNfXzjhtsxG/RodTqKJ8zBd3A9L2xs4JJUL+MSNWzc08y2Lj2L588jr2Mnbx1ysMhwkIBRoS/nOpqto5mbXsWqPc2MzllIT8CItX4bbaEaDnldPFg/nidG+xhnskHuNIJGN81v/wpnwkumtQBtXzf6njhzS6oIfBCGvjoC7amkNKwnv7SSWLSbaal1bNy2HZc2gnvXExgC44hO+Td+U5fNgtZOJjSsxtK4iYLxN2LNns9z62t5tdrPfc42JpdO5R+RibDnH0xPrSJ97DV8vq+TYDhGeY6DeWXpEMlUh9mmlsDB1fDhL6DyFnWY8cF2yJtMhskMVjv0eMHXTHWLn1Aswf930zy6qiaQ4VB78SOROFUFTr6ctg1tZzOU/htklAPg8HXjslvJtUagfZ86wsNTDM489TaI4vQUJuQ6KctIOefXwW5NCX5jhGmeonPelxgZopEwf6x1Y7JuIFoUGe5whBBCnAb5FjwcCmaot8OunJCDNxxn0eg0nBYDV47PguotEAyCorCn2YcOhc2aCt5uj3JZQw+l6XY+bDdTmGrDMGo+4/NclI2F1dv3s3DnL9C6C8i85Vd0/OPHxIKt7Mu5ih5TPr29IeIpVhLoaPSF6TVqaLYtYIo7mxx7lrpkgc6EUadjmqUUXYuXjIMvcKDajsl3AL/WSKOxmOKaP6FtCzIxJUhAZ2db/QEKbemMrn2Gzd1GSuq34XeM5kB3CteGt3FXyUwWhF7E3DOHMaYODHoXUXOISOolhNoP4Ov28/wHO5jl/QdpDY20FV2OtWUDS8zFbBxzG/WeNto79fzpwwh6mxt9wM/lyh5Wtszj0rEKhpbt0LZbHQ458bO0bnyfYGcDQd8qGhJZdPYpFE30DLpERj934ZD9yT83s4TPzTzJsZPsn7tbeHh5NVdVZHPP4ou30NGBTj+b67qxGnXqUOkJn8bS2sVVXfWMskfB5lIvAFlcGAwGppqb8fgb6Nbr0dvTiQYUXm5NY+GoO9mxaQO3ZHZSU9uJsbwYc81y9jlT2L/3EJVlOm5Ob6Blxyo0GaXMK8/CU1nEuIYnofsQifyZ1Pq0mONR2vKvIK91JUaThh2HWqg7+Bpp+XMJ1W0noLhIyczG3NtKpGsP4fYqsnq3QXcDxpLZaIqnsFdTwF/W76emwMkS/ThmOvw400bzwa4DFFf/H1elLqS5+GaYWIh/YzN+JZWu/Lm8uKaFaDxBkVNHeM1v6YrNJs23l5DWzL0fWCjRhflqWiUWk0ud59jbol7QCXvBkq6uf7v+KR678jqCtkJe297EBzUdfH3xaPLcVv64rpanP6jloakG5mVmQ9setWiRTs/4PDd/+dfD86pDladV/GdSQSrP/dts9YdYBHa8qCapxcevLXoqL+7wsaPRxi8qYmQ6T6+omBj5jCbjgCG3J3JkTikgRYiEEGIYSeKZLO3V6pc5x/FzeixGHZ+fXcRHBzpo9oWYUZIGY66EzoMQj/A/b1czz7CDa6aNJrWilEvHZbFiSw0PvH6A8hwnT1TsRnPQAFW38dlpeewI30hXzERs8zvkRpqIG8M0aIyMa3+NdHqJVwfZ0baITJNCqrGHdLOZHHOMuHsGvobdBDPmU9OrZe7uhwj19RHV6kgxePA5R2EwGNFHrZQmqlGaGoljwKbVUm7O5Q+9E6ioeYPxjmzq02fwlG8m96e/TFrbhxTPGoM1bIbwHsri64mZXeh0FrBlE22N4kjL4nZqMcRDmG1uett2Y2pcy2hrEx90p7D10C42Z15PSOOk0rsWfyiGO9tKr9WIVqOBUZeqRXssLji0hkn7Hue/ixdgqfoipoZuxobWwzYvzLmHV3b3sGJ3K/cuHq32gh7W5uuj1RdmQp5r4B8okVC/gLvyQP+xNVYvVBrQaTTqubuIWQ16Ku29ZOsMKG170TRvpqRyDux+HaV+PaGQny6vD423nrRwE1bPPOrDaaxuNWAvmcLO3gC3sRPPIS8/L2sjv2UTJSWjsXb9H1pDlBbzQgrSahhVuwatZwzhyWXod72Ipi2LgtExYrVr0aR4iOx8Fa2xFGtfIzpNmF69m962eoyuILMja8jo1hMyp7EmUkyabzea3k52Zl5HT3QsxfMvI7zpr6R2/hMyCnDt/RlP5RnRmJyYuqrRBA+Cv4WqzAwcLQlcjm4KLDWwdQ03OzOguIfqYAcvbtJhiXawLHsfoWCApvZu0owJvMZsNtb20OvWEbTGsWx7FoxWmPVV8DVA01ZILaWl4SDdcSM5Ez3kpzvZXd9JfrQWTTgbsDKl0M2+Vj+p46ZAZCfseQ3QQss2sKWq1a0BzEcLBP3fmlqi8QRfmHuqizKKWmXYGjyr18HNU/NZMDqsrkksPnF8Ph8/e20zAN+8ukrmgQohxDCRxPNchXsBDZhOMr8k7IcdL6lDyybeMvA+X5O6vIrBwrPr64nEE8woSeODDdvofP+3VM64hKVV0ync/za2rhiXOv2sensjbVvf4LOZk1gVGENLVw8WVw7Gg+uoff95mkmjyPsR/lo9kfwcNGE/2R1rcAYPkEjx0Osowx1qxtG2FW3GKNJSUqC9l4OxVPq2vITNqKNC10ci7CWaOZWO5kPECy8hz2Wka+ubmPUewopCwpKPJsWNNtiCSacwxdpKMAQeHYzrWct37Z2k9uxCY8tEX/sumFMgo5x4vA9ddyfdaVPwHaohJ+6nr2kjBVEfppJ54GvEkeLAbytCpygsMFbjsIAh24DH4CPHG0CXkoZm0hcZn2JCpz18/o/8DXRmsKTitLsgu5xpjb+HvmaaC66GPi3GRJC54dWYvHri7vHE42A06vjv5dVsqO3m17dPYUz2MdUz969UF6WvvAXKLj3mb9cIh9ZA0bzjhvAGIzHMei1a7amvxg+HReVZLPoEFDYpTTUzM7CC0CE3GztCjI3uwJQzAX93K/rdb9HnKCHa08729KuY7duE4lvDa2lfZlzfX2FfPVWWUia0vkI8HMRgdWOI9mCI+dAHmknkTsG+50VswQ56tBYSoQgJJYbdlkXIWkhs9+v4NClYlQR+91gyjSmYFQfalpUEQwkiaQWsYgbXmtZhbV2NzpxBjrWFtqiO7N4GYnof5mgXrdur+em+Er6f46XCNQrb7hVYo2ES0Swc8Wa0Y6+EYBcFqW5Iz8flcdBa8wFN4QRuVyNul4eSnFHM7jZwdd97TOp6m+byz2HPzYeGfbgLs/nJ9elkWBO4d7xGTGdEH2hDCfeSSCjoEhEYfTk1DREO+jRcZvBg767jesdecK+DDe/B3HupKsinqsCjnvhQBWgN4M6Dbc/A/lbIngi2ge1kV7OP8OkUmNGbYMa/nnW12bIsB2UX/8v9gqEoCuFIBBNnV9X2bJhTTmOJHSGEEENKEs9zteVZdU7gtLsHbq9fr66vWTRLTYjGXQcWF1sOdQIwqTAV/G2w8Q9gdtJhG02P38J8ax3f+UM32VaY5zIQadnNpYkmqFpE076NuDb/jInWbDTpxQRsGRR2dtHXvAd/rx9L3RbcwQPYlIOk2Iw0WSsImMzYrQdIsdpJKG5iBhv2hlUYMqvQZI9HiYVp94cwBxrJ6gvQXDILHRHM7evQaWwk2ms4lHstW+q0zD20EcUznUhcYUygjqitAGP9B0Rs2Rz0zGC2rQ+lpg2daRSJ1FIckSCK3kLIlk9PVEumPQV99yHabeNxd24Co5VQwkTYmMAS6kQbD6k9lmEvlqLp/K05jamB9yi3dmBKzUMX2Ytxx6t0OkZjzZnFq+vq1WVOilOPnvdoCLr2QXaFOr+sYz8UzSOaM5kXdlvI6G3n5sIE9Pih9T1+u/Eg6wJZPHjjBKYXebAYdeS6DleeTSTU5Sf0RnWerf1jVW27DsGOF/n7zm5e8E/g95+fil6vp6EnyH++vJM5pWncNbd46F574pS8YYVY1iR8MSMfKnry89xo9r2CMa2MmKcErc6G2xlhdnwDFoOePJ2PLwafIJhqY0PQyjXaD3BFmonbs+kLh4jmzUEbaEGv0aKLx7D0tRMwZ2Ls2IE+1oVRq0Ex2qmLW8mK7COeUUmgdRs62rF7d6ON+tAWLkLnrSel5T3K88r4bdds7srUYDHoqYoc4oBjNjm+HYw1ttFT93es2hgT3FdTn305cb9CrjEbhzlEg6kUu7YPXc4E8NZDx14YfTk0bUEX7UXbUUd7Xwb+jmayPKP54fWX4V/1PomAE12gBZNpOlR+hs5tKzH16tBMvoE/xi7F39vN7TMK+Ki3EH1TG/NTC9Fr9cxdciujfSF+9MpW/iP2a/IcBii/BoKd6rF3vwqTPssbNUE2HurmK5dMwmM2wuS7oKMaTMdczAl2w/53WJRZwIedNrzBCE7rKZYVuch75z9JfD4fgdqNpKSnDXcoQgghkkgSz3OVOR40H+vVioVh23PgbQBXLrgK1OqOwL8/+S4Ab993idrTWTALmjbRsX8zCW8Rju730SVGUV7ioqR9JVrDROhJh94mNP4EOlsarlAb8+N1zDfsJWC3YIz2EG/ZRcSaTrsli5xYHTolSlHfVqJhK7HO/eg0BhKBDiJp47AGWtCHvWjD3UTthZiDTWisTgw9tdi7mgmlT0SnxIjrTNgtWsZ1v09VvAWdzkRfaw12Tzb6jj0k7FmQXo4pHqY8tJVoEIw6A20RIzVMYmrwdRR7FvrWbXRlX8XOYCYLiixEwvtBZyalYwfWmBVNsBZtWiGKr5O+WBSLxUN4x8tckZFHPFxKoGUXf++twNKn4VJ9DA+NmNreY2rOHRSmRPD2RVESCq4UI7TuVJPN0svg0PvQ14F/7GdYvqOF8TkGJljaYOdrkD8TGjczQXeQd4M2/uef+/mvGyZwU7AbundDn0udUzbmCnU9wLypx1fCTRsNBXNoqEsjnkgQi4FeD1a9njyXBY9N5pINq5bttK19l+Km9yiyplHp6KOvU4fenYu+fTvoLCRMVjRGJwSaATDF/TjDTcQtaWRa2jFHu0FrRNO2G3uKB01zNbHsacRsqWi7a1EMdiyBBrSeIhKWVDStG9GEusmONWCwpRJpWo/Bnko81kfEko4u5EUfbEHT147G4ibHEOSL5uU4Q71oowYMwWayohDTW9F119BScjeVjhA/nnAprH+SnS1aEs4cHB0foC28ns9tn09JdToP3ng97HgBDDbIGEuaspOE3sqeLhNKX5BtByNcNQZeNV5Br6sQ84EPGO//O1Nu/i5pvbswh8KYHNfwjm0M+4J+3glksK62lenFVWymnfb11Vw5sxKTXku2M4U+7SQ6XW7qbXOYNM4DDRtAZwSNhrrOIPvb/QQjUTwYIX2UejtWyAsdNcTCZg51aeiLxpHBj58set35L+ImhBBiZJPE81wVzTl+m96kLlsSDfHxU1yZYyd+ZHSRzgCll0D+NMoVhVlrmom0BLkqUoNP4yFhzyYaDtMeN5FusWAqHo1hy1bQ2yDYDoYUrKYEobQxhON6MFpJ69qNweWBkA+zwYq1aweJnAnEtSaMvQq63gYwpGAgCoko2mATEZ0Nbdd+tI4sUqMB4rEGjB07wVFAxOTEYwihD/SgpORjNZuJdR8gXHgJSkKLPhaCUCdGoxOdv42wpxx75xZK2E9b5mw8wRosKIwKbiEnFGGT9RacljwsWgdadyFtlvF0+lvRxWPkKO3YqpejJMLEzWlYOw+Ar4mQrQBTdzXOKZ9Bm+GDrr0Y977CPGLQDJsTpbi6t+Caf4dazCQehuxKcOYS6m6gq6sT+6G3yE9NIb1yNrHUchLu0Rgducza/ldCxmbq0krUHs6dL4G3SZ2PZvWow3Y1msGXX7GlwZyv8tU58NVjNntsRv7zuorz9AITZyWRgF2vUNT6IWFPKg5tF6ambZhMTuLuIkgdhSYWReerR4mFUBIJNLEocUcGOo0eXUcNtpRUtEqUhMZILKMCnTYBaEGrwdi8BQxWdEYjGu9BFH89YVcJMZ0FxTMKb1SP27cffVopxkAjGo2GsGIEvQl/KILOOQpLz16K44eI4EefYoNAD0pKGppwiDUpC0iYEpS3r0aXcNPd00m7bTKezhWkdG0HTxl+QyrtYQ0loL5GJ9xEfV0t8XA9RZ0vkzH6CqaXptGx50Pa0/OhbTdXhldSU76IDSYXWbl+1r75DO78GxgT2AzhHu69fAwAv3m3hg5/hLn5Ova98md8iVR6J43DaTXy3WsqgAq++9I2Gqr38fjtU7DmTVUvzgB6XQeXjE4nz3OSarSeIpj1VS7TWZkdjZ+6t7P6DbXYUdXnjq7DecqXQIKXtzQyKtPOhFzXaf2OuPAdKSTkcKg97D6fD0VJ3pBeIYQQJyaJ59nyNQEadTH6Y21+hnjTZhryryE7T4dxwxNgtEPlzTRp3ASiCilGHct3tnDF2PSjvaURP3dOtKOtfQWlaz9rNJ+h21IERhPZbZuJtUXpNTWQwI7LZKErYympnRvB24QhEkXjyUcf6kHrsENPHXFLGgTawGBGG+7FpI+ieEahhAMotmzobUBjSUUT9qJJsRMzuTD5G9BoEuh6myB7CorJBo1bibiK0Ttz0SSixF0laIMdaGJB4uEgSrAN3AVE43qiBWMx9NRiMBtB0eKr+4AUYxDcBcQs6dg1reQ1vEowYcBBJ4mQjSldz9IZs9LknkpXznwM+j6smgjG1l0o1lSCzlIChZcyq+QyCq1h2l9+A2/aJMxjrscYaoe8aZQ278XU9j40V6pVL3e/pq7pWXkLtetepcUyGn1vI/hbwdDKN/bPILa1hV/fWgnF81mYOgqcueBthI59oDNB7fsw5U6wpZ/4NRDshngU7Bln/vpp3qq+frIrz/x3xalt+hPsXY7Tlk1Qb0QXDUFOFQTa0cRjxG0Z6PzNYLSisedDIgIaAzri6jqvFicJzygI9aBJxDAoYTTedhIp6eiaNoO7EE3HXrB4IGs8mkAPRouTeLyPcKgPW6gXXYqTWNhPXxSMhNDrTGhNNixxL5rOJqKKQszbCrE+6OtAazDi1+bit7nRanVMS2whxWDgta4K2ld8iCFrLEuyK3BEm8DqYcbM+fxzzjFv4dEQ3g+fJKRzkl9+DbrUUjwbfoenr4nR0WI4pMOt+JhW6GRaRTldm1+hoXoTh/SFjDEGoKumv2fy7ioHny2LYa/+C9bxFeSnTzsuOfzUhGy8fVGsxoEfI5MLPZzW1GazHT3gNJxGz5fWoLbLMxhue6gjyF/WNzC10C2J50VMURT8fRGUw13mPp+P+hd/QP7SHwFQ/+IPcCz+5oDHe71eqW4rhBDDQBLPs7XjRfXL0MwvDdze10VfZz3vG81My6tizMF3oW0XsaAX/fjP4TJDsX8jusZMqPtA7SXQGqBjD3W9JvI0eowWB/nRg0QyJlDs1KM90ASJPuyaMPG0MYSbPyQlnkCJ9KGxuNGSwNC4kYS7CKW7jrizEI3OSNRVgsbiwtC8ESUSAL0VY1c1JELQ143iyEVjy0Ef6cUY6wNiKEYXCZ0Zwj0oTZsJFyxkT5+LCYG1aFw5KJ0HMBlNJPwtaBwFaJQQ0T4vEZ0D2vdiDLei1WrQuMZiSzEDGnq8PmzRMPpAI2m5s6Gvhy5dJWalD4PWhCG1gFFd7xPU2nC4HNC5D308AZYS6tojvLlPw79P0sDBjwh5xuBr3o9XM5E9tXGmTJjFqGCnumh88UIwmNWlGmJhcGRhGXcFpXVrabaY6M66GjIMuFrM6PSH526WLDj6t+vcr/ZCl8yHUI9a2fNkdr0MfT0w52sM+KYdj6o9NM58yD3Bwve1H6hzgyXxHBqeInAXEtcY0MRi6Lv3g6cMlARaUwo0bwaDEY1WB30d4G9B4yqGqF+tnhrqQZuSiaLVoench96qFgDTBDvQGCwQCxFLSUerxNH0tkCwC224h5jJhcFiw9K8hkThPCyhLra7Z+KJdWOLtmML1hFLLUOrMdBiLCScMYHM9nUYHW5CbfvxRTSYbFomaQ9grllFJLMSm8VHVnQv5YYebMWLIVwH6aOP7/nTmyisuoyw0YVOH4Ktz6tVaTMrwVUIzZsgdwrY1YtlnspPUeGejMeTBpqxYD462FW/+wXsvhbw1uGsuhPnqON78OeUDX5RpqrAfd7+jP3KFp/xrxRn2PjqolHku6WS7cUsGgnzTF0qGe6ja3k6rOZB/x/UxPSXb27juzfPk+q2QgiRZJJ4nq1RiwfO7WzcArEgzFqGvuoLVLSHKUgzgeUu4tXL6dq7Bn/EykNLvoB/9euYQzugaRNkVkDBJLB4aF6zGmsogdvgJFXjJRxtJXrwIJqgF33Uh8EURx/vw5iSjsZbj6LVo1hd6Dtr1B6Ylq10uysxmVOwtGzAGA+jaVxD3FlMHDAmwiipo1As6WhR1P96aol6SjFGAygGO4neZmrSFhOz2ijQp2HqrqEyrRSNfSzGtp0oxAlkTob2vehCXnRhP17bOEK6FNK1jQSMJZjjvWh7atGkjkIx23jHNpvJPW+Sm+rG1L4LnVZLkyGbjGg7unAQQ7Qakz0Vg7sUnacYbFmgN0PbNszOUizGAvyBXtZs2k19xmVUZW6gpPZFfOlLCGrsoNHRETfz2Bt7uWFeFZUL7+8vDFQ48RJItZGv0UPuJAD+a9Txf05A/UKeUwX5M05epfiI/Olq79jHu3diYejaryaWnCDxnHATIFfbh0zJfEgvJ/7qvRja9qo94YFmlJRsNN21ag+3rwnFYoVAJxp7rjpEO5FAcZUS1+vQBdrReOtIZE5AFw6ghLtQjE40KICesL0Yc8QLvQdRMiqImhzoew6ia9+JklaGrq8T7fhrKAlDaNMHHMj9FI6YCXtXO4dKb6a2sY05hVNwZ7kgFkGxZdDZEkIbaCErRYe3ZCntUTM1TZ2MGj0Rp1IPWmDRd/GFojQ2+xiTaUerPfw60miwj1mAHdQ1bbMnQu5k9bXcWQ0TPq3ONz9Cp6e8KO/wDwO/nFMwBwLtauGgC/jiyLwTJMfi4mI0n94yV0eG4ZpTTjIMXAghxJCRxPNsZYwd+HPLNrWXrGAWZouVSQVW2PMGtGxDM+treE3vUB1JY/2uIPW+uYx3BFkybwGMvVatCNm8mamzL6dzm4IlKxN/eyuGFDc2Y5xeFEJkYAq1o490ghInZrLTasghL7gfxZqKotGjpJXjIIK2ZRdxRx76iB+NRkfImgm+Jox6LUqfj15HKWa7Bk1vK73mXJr7XJTHGtGYXQQco/BGdaS3raHVlUeBvhOjv4FEsIe4LQu/1sJa7SwWaPdBoJ2wo5AOQwaujk2ELBYi7iLMxgT2tm30avUcCJpwZ6ez3nU3DbE25mj/TrznEE7aqXVMpSrPgcZXh4EIZI+DqttBiUPLTtgUoKx0IWXjrqInGKE6fQnjbH1UlV8BkS3MK8uDnBTYsZ9gsJdd3X6me/uozHcPTAYPzz07pfQy9Xa6DheMOo7JBtP/7eRrfp5sCO+xeuqg+k0ou0xdjkecvp0voO/cT8yRhTYRRmP2qD35Vg8ajR5N+jiU3kZw5IAhBSXsR9PXDBrQRoMoeivxtPEcsE1nlOYj0BkIaMxY27bQlzEJc+ceNDoNfVlTaKvbhym9EKfRiTkeQZ8+Hlq3QF8Pzil30Rm3sFczkVkWPSn+asaE9mDJLSOnuBI04+G9n2Gq/gcTbdmw8D602WPBaMfUeIB1m5ppcGfCBCM41cRxU203m+t7sJv05HkG6ZnPGHv0Papxs9ozb8s8/XVocyaelz+BEMmhEI6E6enpAcAXDOFQlOOG0oaDAR57cxdOT+Yg+xBCCDHUJPE8X8Zfz9Pv1dC3ch9fWTRa7QlrrwaDFW2KG+eUG/nTs5vxWNvpDVsxuHNZMn4MdR1+3v7gENdpW0hL78J23f8PXvoSWfEYzPg2JOI4VvyIoMmBduxijH0d9FW/QzihpSuRQoYjCyUcIGjKQeerxxZqJp4xDl/CTCylGHvPHnb3aImkTGceW4kHOiASxNtSiz5zFDVePTWZVzCqtw1LsBVLXIPTmU/clkV9yMr2lGu5xFaPPrGP9t4Y6+xzieMhmDCiuMrpjJkYlWlnQ28Z+2yzuesydR1O2qt4pz4FQ+d6UlK7KRu9ALNhPKv3pFDbuQGLXseNk6qwtm6A8sUwatExJ1Or9k4e7qEEcFmNfHVML7TtAs9MuO2vRx8+798pMJh4qFdHcfpp9FQmw6mG6Z6uxOE5h4nTWOtQDKQA2RUEwhrMvQdJmO3oAl6MOrM617NhDYnsqWi7alDMbhKeQrTBNtAaCTuyiCfi9IXjOAIHiB/aQHPWQuon3MPc+b38badChe5tRkd2U9OjsGn0d5mSrSfX3A07/wq5E6F0ntpzb0ujeMFtFCQU9LoJEA5A3Ro8jmzQawGtOoKi+yDatNGQVtI/7DU7fxSlPSkEInF1TczDJua7cKcYyHadxjDS3KoTD/kW4iIQjcWJHdhAxxsriMTg6Von31vsG3Qordk8Qj4jhBDiE0gSz/PF7ODpLT1YjX418Ty8jdRRoDOQYTdw32VlpKYYyfOkYNKrBTU2Hurmd9UGyotcpHVUw+jLYNSl6jzB3a+ANQ3NlQ+RYrSBLZVA3VZW7ekmyxxncqGb7uxb+OiDd8iKdpM/7loCZVfgysqn96M3WL6jAVvaIjxF41lSVQrNW2DD00QjBrZlXEUifQLPNbZTUTIG7awfodnxAma9gXGVn8EbCNJe28JvNhqpcIcpcXkpnTiNwqxJ7I9nEWv9AjW7NpFtDmBWwmSVVBLwTAZXPoR90NfNIt0eYuMKSR0zCrLV9draHAtYE8pl4eh0rKMzIK1AHfZ4Okrmq0OTU1IHbj9c3KfYPMjvXOg8xTD368MdxYUppwp9IkZquJceTyFbO3XsjIwmainkhtS9ZFtc9BlcmHMmo+k8QJfGg889jx6di51KMRP9a8iIHOSAcxTbR32bp5sL+ZzBg6aokjuLAObSV7OaomAPVZVXqMcMdAJxyJsC4V6oeQsyx6JxFaDXHe59MaUcP2cxf6p6G8SSCdnHbXOnGHGnnKISrBCfIAa9FofVRDgGJtPF+GEghBAXvos68Xzsscf47//+b1paWpg4cSL/+7//y/Tp04fseHfPKcKgP/zl0mCBaV8YcP/04uMXy752Ug4uq4GJWRPBdLi6Y+VN6r9tu9UeE09h/+MNWRWsdMF0awOTi1NxF8zkioKxsPNldS5WVj4AOVWXs7AgwKh0G3rd4WGnuVXociaRodFwOfDhvjbi9QcYk23H7DCBOUWdt5hWijMN5hZO4G/TI9gipeBvh5xJGDUaxgIUXk9W5UKIx8GUwii9if6pk70t0NeNM6sMKm4Ai6s//gynmR9cc0yhkowxp3+CLW71JsTpKJwFKNB1EFfBHCaZMln33gE6AhG2aBQKMuMYKpaq67FGwzgjITq2reXPdZlMKcqgyg7RVhdZU6+l05iNrbWXOWUDKxhbRs1lQJ9jSipMuln9/84D6tBYg/SwCJFsxy6pIoQQYmTQKBfpAlfPPfccd9xxB7/+9a+ZMWMGjz76KM8//zzV1dVkZJx8+QufTx2ic6Tk+idGNKTOATvXEvNHhoeeToEeIc7QeWmfp/sajfYNvoarEGJQp9M+6+rq+OHPf4XH4yYWjdLe1TXg/uzMzEG3n+w+g9HEPaN7CMfg9/VpfDarkeKl/wkfPgazl/GnTe2EAn56uzsxWVO4f+nME1a1PXYtUFlyRQghzp/TWW3tgvTII4/wxS9+kbvuuotx48bx61//GqvVyu9+97vhDm3kMpjPPekEtZqrJJ1iJDvd16gknUJcEKKRML+vz+T/6lKJxuKkmI34fD61eruiEAmHiERCnM6Vdp/Px4+fex+fzzfkcQshxCfJRTnUNhKJsHHjRu6///7+bVqtlsWLF7NmzZrjHh8OhwmHw/0/y4eNECOHtE8hRq6R1D5NZgs6XZRQIEggFMH/1s8IW80YfT5C+9cSDvURcY3CZLH298ge6dE8tpcTwJwiF0+FEOJ8uyh7PDs6OojH42RmDiyZnpmZSUtLy3GPf/DBB3E6nf23/Pz8ZIUqhDgFaZ9CjFwjuX1qNBp+U+PE7/djNuoxGdRr7ZG+II+8un5Akiy9nEIIMfQuysTzTN1///14vd7+W319/XCHJIQ4TNqnECPXSG+fJpMZv9+P0j/IViEciWA0p9DT00N3dzc9PT309PSg0Ru4SMteCCHEiHBRDrVNS0tDp9PR2to6YHtraytZWVnHPd5kMmEynebC6kKIpJL2KcTINRLbp6Io+PsipJgNRKJxGt/+FTHPHBRFIRAIoLRXQ9EUHnrhQy73v8Z7GTcT7gsSad5JfX0ODoeDRCJBfX09drsdrVbbv99TFR062WPOV9EiKX4khLhQXZQ9nkajkSlTprBixYr+bYlEghUrVjBr1qxhjEwIIYQQQykaCfNsUyaBUJRIJMzr3blEonEisTihxp3otBCOhIlEIzzXlEqiZQe0V5NIxDn0ykP86E8r6Gpv5eHf/oFdu3bh9Xr7k70jw3EVRenv5T22l9Tn81H/4g8GHbJ7svuOdWTfJ+p9PZdhwafatzg1OYdCnL2LMvEEuO+++3jiiSf4wx/+wO7du/nyl79MIBDgrrvuGu7QhBBCCDGEjMf0whpNxv7/N+g1RGNx/LVb8NduQW/QY9TrMBnUdbQ1Gg2J9j2EI1FMJgvh1Y/hfeMn/UnekaJDPp8P7xs/GXDfEQ6r+YRxney+I04nQT3b4kcyl/Xcne4FBCHE8S7KobYAN998M+3t7fzgBz+gpaWFSZMm8eabbx5XcGgwR65iyZuKEGC320fUcC5pn0IMNJLa6Om0z97eXnr9AbQ6HbFYFL8/OOD+HrNv0O1ncp8hEqcp0UNvr4NYPHHC3wsf+3vBME2JHkJBN9GuTnS9vXR5/WjQ0LR7NwAdbS3sPvz/xp5eAJp278Zut/c/t3BzB6Zjth37vE9033GP8/rxn+Bxvb29/XGcbD8n2rc/4D+r3xWqI38fp893Wu1uJLVPIYabRpGxAsdpaGgYUZX5hBhOJ1sIfjhI+xRioJHURqV9CjHQSGqfQgw3STwHkUgkaGpqkqtUp8nn85Gfn099fb28uZ5HI+W8jrR2cKbtc6ScxwuZnMNzN5TncCS10RO1T3kNDT05x8lxpud5JLVPIYbbRTvU9lxotVry8vKGO4wLjsPhkA+7ISDndaCzbZ9yHs+dnMNzd7Gfw1O1z4v9+Y8Eco6TQ86zEGfuoi0uJIQQQgghhBBiZJDEUwghhBBCCCHEkJLEU5wzk8nEAw88MOIWEb/QyXk9P+Q8njs5h+fuk34OP+nPPxnkHCeHnGchzp4UFxJCCCGEEEIIMaSkx1MIIYQQQgghxJCSxFMIIYQQQgghxJCSxFMIIYQQQgghxJCSxFMIIYQQQgghxJCSxFMc57HHHqOoqAiz2cyMGTP46KOPTvjYnTt3snTpUoqKitBoNDz66KPnvM+L2fk+t//5n/+JRqMZcCsvLx/CZzAynenr6/nnn6e8vByz2cyECRN4/fXXkxTpyHUm5/CJJ55g3rx5uN1u3G43ixcv/sS26WOd7fvcX/7yFzQaDddff/3QBjiM5DPg/HnwwQeZNm0adrudjIwMrr/+eqqrqwc8JhQKsWzZMlJTU7HZbCxdupTW1tZhivjC99BDD6HRaPjGN77Rv03OsRBnThJPMcBzzz3HfffdxwMPPMCmTZuYOHEiV1xxBW1tbYM+PhgMUlJSwkMPPURWVtZ52efFaijOLcD48eNpbm7uv61evXqonsKIdKbn9cMPP+TWW2/l7rvvZvPmzVx//fVcf/317NixI8mRjxxneg7fffddbr31VlauXMmaNWvIz8/n8ssvp7GxMcmRjxxn+z5XW1vLt771LebNm5ekSJNPPgPOr1WrVrFs2TLWrl3L22+/TTQa5fLLLycQCPQ/5t577+XVV1/l+eefZ9WqVTQ1NXHjjTcOY9QXrvXr1/Ob3/yGysrKAdvlHAtxFhQhjjF9+nRl2bJl/T/H43ElJydHefDBB0/5u4WFhcrPf/7z87rPi8lQnNsHHnhAmThx4nmM8sJzpuf1M5/5jHLVVVcN2DZjxgzl3/7t34Y0zpHsXNtoLBZT7Ha78oc//GGoQhzxzuYcxmIxZfbs2cqTTz6p3Hnnncp1112XhEiTTz4DhlZbW5sCKKtWrVIURVF6enoUg8GgPP/88/2P2b17twIoa9asGa4wL0i9vb1KWVmZ8vbbbysLFixQvv71ryuKIudYiLMlPZ6iXyQSYePGjSxevLh/m1arZfHixaxZs2bE7PNCNJTnYd++feTk5FBSUsJtt91GXV3duYZ7wTib87pmzZoBjwe44oorPlGvx2Odj9dmMBgkGo3i8XiGKswR7WzP4Y9+9CMyMjK4++67kxHmsJDPgKHn9f7/27vzqKiuOw7gXxgcVnEQdASVQQPIsFlQQ5CQ0aCxmBBMiodDCIt1yQIRGkmtbaJWkmjjEo0mWjCF9rgQIngal6CIQXQ0VMGx0OAMIIhJsIpLCsgBnfn1D48vjgyyhBGB3+cczmHecu/v/rz3vXd9bx4/AYAw/kpKSnD79m29nHt4eMDZ2Zlz3k0JCQl4/vnn250zOMeM9QxPPJmgoaEBWq0WUqlUb7lUKsXly5cfmzL7I2PlISAgAJmZmcjLy8PWrVtRU1OD4OBgNDY2/tKQ+4We5PXy5cuDvj/erzf65tKlS+Hk5NTu4myw6EkOT5w4gc8//xzp6emPIsQ+w+cA49LpdEhOTkZQUBC8vb0B3D3GicViSCQSvW05592TlZWF0tJSrF69ut06zjFjPWPW1wEwxnouNDRU+N3X1xcBAQGQyWTIzs4e0HdR2ONjzZo1yMrKQmFhISwsLPo6nH6hsbERMTExSE9Ph4ODQ1+Hw/qxhIQElJeXD7rv9hvbpUuXkJSUhPz8fD6uMdaLeOLJBA4ODhCJRO3eyvbf//73oS+3edRl9kePKg8SiQTu7u6oqqrqtTIfZz3J66hRowZ9f7zfL+mb69atw5o1a3DkyJF2L94YTLqbw+rqatTW1iIsLExYptPpAABmZmZQq9V44oknjBv0I8LnAONJTEzE/v37UVRUhDFjxgjLR40ahba2Nty8eVPvjhznvOtKSkpw5coV+Pv7C8u0Wi2KioqwZcsWHDp0iHPMWA/wo7ZMIBaLMWnSJBQUFAjLdDodCgoKEBgY+NiU2R89qjw0NTWhuroajo6OvVbm46wneQ0MDNTbHgDy8/MHVX+8X0/75kcffYTU1FTk5eVh8uTJjyLUx1Z3c+jh4YGysjKoVCrh58UXX8T06dOhUqkwduzYRxm+UfE5oPcRERITE7F3714cPXoU48aN01s/adIkDBkyRC/narUadXV1nPMuCgkJaTdGJ0+ejOjoaOF3zjFjPdDXbzdij5esrCwyNzenzMxM+u6772jRokUkkUjo8uXLREQUExNDf/jDH4TtW1tb6ezZs3T27FlydHSklJQUOnv2LFVWVna5zMHCGLldsmQJFRYWUk1NDSmVSpoxYwY5ODjQlStXHnn7+kp386pUKsnMzIzWrVtHFRUVtGLFChoyZAiVlZX1VRP6XHdzuGbNGhKLxbRnzx6qr68XfhobG/uqCX2uuzl80EB+qy2fA3rXG2+8QcOGDaPCwkK98Xfr1i1hm9dff52cnZ3p6NGjdObMGQoMDKTAwMA+jLr/u/+ttkScY8Z6gieerJ3NmzeTs7MzicVievLJJ+nbb78V1ikUCoqLixM+19TUEIB2PwqFostlDia9ndvIyEhydHQksVhMo0ePpsjISKqqqnqELXo8dCevRETZ2dnk7u5OYrGYvLy86MCBA4844sdPd3Iok8kM9s0VK1Y8+sAfI93th/cbyBNPIj4H9CZDYw8AZWRkCNu0tLTQm2++SXZ2dmRlZUUvvfQS1dfX913QA8CDE0/OMWPdZ0JE9EhvsTLGGGOMMcYYG1T4O56MMcYYY4wxxoyKJ56MMcYYY4wxxoyKJ56MMcYYY4wxxoyKJ56MMcYYY4wxxoyKJ56MMcYYY4wxxoyKJ56MMcYYY4wxxoyKJ56MMcYYY4wxxoyKJ56MMcYYY4wxxoyKJ55sUHNxccHGjRv7OgzGWC+Kj4/HnDlz+joMxgBwf2SMsXt44skGhczMTEgkkr4OgzH2CGzatAmZmZnC52nTpiE5ObnP4mGD24P90Vi4nzPGHndmfR0AY4wx1puGDRvW1yEwBq1WCxMTk37XH9va2iAWi3ulrNu3b2PIkCG9Un5vxsUY6xt8x7MfmDZtGt566y0kJyfDzs4OUqkU6enpaG5uxrx58zB06FC4urri66+/1tuvvLwcoaGhsLGxgVQqRUxMDBoaGoT1eXl5ePrppyGRSGBvb48XXngB1dXVwvra2lqYmJggNzcX06dPh5WVFSZOnIhTp051GCsRYeXKlXB2doa5uTmcnJywePFiYb2Liwvef/99xMbGwsbGBjKZDF999RWuXr2K8PBw2NjYwNfXF2fOnNErNycnB15eXjA3N4eLiwvWr1+vt/7GjRuIjY2FnZ0drKysEBoaisrKSgBAYWEh5s2bh59++gkmJiYwMTHBypUrhX1v3bqF3/72txg6dCicnZ2RlpbW7RycOHECwcHBsLS0xNixY7F48WI0NzcL6z/77DO4ubnBwsICUqkUERERwro9e/bAx8cHlpaWsLe3x4wZM/T2Zf1bfxq/AHDz5k289tprkEqlsLCwgLe3N/bv3y+s72wsuri44MMPP+xwTAHA999/j6ioKAwfPhzW1taYPHkyiouLAQDV1dUIDw+HVCqFjY0NpkyZgiNHjgj7/vGPf0RAQEC7uCdOnIhVq1YB0H+0MT4+HseOHcOmTZuE8V9TUwNXV1esW7dOrwyVSgUTExNUVVU9NEds4Jk2bRoSExORmJiIYcOGwcHBAe+99x6ISNimtbUVKSkpGD16NKytrREQEIDCwkJh/b0na7766it4enrC3NwcdXV17R61NcYxwVA/r62t7XS/+9uenJwMBwcHzJo1q8M8bd++HXK5HBYWFvDw8MBnn30mrLt3zPniiy+gUChgYWGBnTt3Cu3/4IMP4OTkhAkTJgAAysrK8OyzzwrnvkWLFqGpqUkor6P9GGP9GLHHnkKhoKFDh1JqaippNBpKTU0lkUhEoaGhlJaWRhqNht544w2yt7en5uZmIiK6ceMGjRgxgpYtW0YVFRVUWlpKM2fOpOnTpwvl7tmzh3JycqiyspLOnj1LYWFh5OPjQ1qtloiIampqCAB5eHjQ/v37Sa1WU0REBMlkMrp9+7bBWL/88kuytbWlgwcP0sWLF6m4uJjS0tKE9TKZjIYPH07btm0T4ra1taVf//rXlJ2dTWq1mubMmUNyuZx0Oh0REZ05c4ZMTU1p1apVpFarKSMjgywtLSkjI0Mo98UXXyS5XE5FRUWkUqlo1qxZ5OrqSm1tbdTa2kobN24kW1tbqq+vp/r6empsbNSL59NPP6XKykpavXo1mZqa0vnz57ucg6qqKrK2tqaPP/6YNBoNKZVK8vPzo/j4eCIiOn36NIlEItq1axfV1tZSaWkpbdq0iYiIfvzxRzIzM6MNGzZQTU0N/fvf/6ZPP/1UiI/1f/1p/Gq1WnrqqafIy8uLDh8+TNXV1bRv3z46ePAgEXVtLHY2phobG2n8+PEUHBxMx48fp8rKSvriiy/o5MmTRESkUqlo27ZtVFZWRhqNht59912ysLCgixcvEhFReXk5AaCqqiqhznvLKisriYgoLi6OwsPDiYjo5s2bFBgYSAsXLhTG/507d+iDDz4gT09PvfYvXryYnnnmmR79O7P+TaFQkI2NDSUlJdH58+dpx44dZGVlpXf+WrBgAU2dOpWKioqoqqqK1q5dS+bm5qTRaIiIKCMjg4YMGUJTp04lpVJJ58+fp+bmZr3+eK+u3j4mdNTPu3Isudf2d955h86fPy+M1Qft2LGDHB0dKScnhy5cuEA5OTk0fPhwyszMJKKfjzkuLi7CNj/++CPFxcWRjY0NxcTEUHl5OZWXl1NTUxM5OjrSyy+/TGVlZVRQUEDjxo2juLg4oT5D+zHG+jeeePYDCoWCnn76aeHznTt3yNrammJiYoRl9fX1BIBOnTpFRESpqan03HPP6ZVz6dIlAkBqtdpgPVevXiUAVFZWRkQ/n0S2b98ubPOf//yHAFBFRYXBMtavX0/u7u7U1tZmcL1MJqNXX321XdzvvfeesOzUqVMEgOrr64mI6JVXXqGZM2fqlfPOO+8IF40ajYYAkFKpFNY3NDSQpaUlZWdnE9HdC4Jhw4Z1Go9Op6ORI0fS1q1bu5yD+fPn06JFi/TKPX78OJmamlJLSwvl5OSQra0t/e9//2tXf0lJCQGg2tpag/li/V9/Gr+HDh0iU1PTDuvobCwSdT6m/vrXv9LQoUPp2rVrBuswxMvLizZv3ix8njhxIq1atUr4vGzZMgoICBA+G7rQT0pK0ivzhx9+IJFIRMXFxURE1NbWRg4ODsJFNBtcFAqF3n94EhEtXbqU5HI5ERFdvHiRRCIR/fDDD3r7hYSE0LJly4jo7nkGAKlUKr1tDPVHYxwTDPXzru7n5+f38AQR0RNPPEG7du1qV35gYCAR/XzM2bhxY7v2S6VSam1tFZalpaWRnZ0dNTU1CcsOHDhApqamdPny5Q73Y4z1b/yobT/h6+sr/C4SiWBvbw8fHx9hmVQqBQBcuXIFAHDu3Dl88803sLGxEX48PDwAQHgcr7KyElFRURg/fjxsbW3h4uICAKirq+uwbkdHR716HjR37ly0tLRg/PjxWLhwIfbu3Ys7d+50WN69uB/WloqKCgQFBemVERQUhMrKSmi1WlRUVMDMzEzv8Tt7e3tMmDABFRUVBuPsKB4TExOMGjWqXfseloNz584hMzNTL9ezZs2CTqdDTU0NZs6cCZlMhvHjxyMmJgY7d+7ErVu3ANx9PDAkJAQ+Pj6YO3cu0tPTcePGjU5jZv1Lfxm/KpUKY8aMgbu7u8H1nY1FQ3U+OKZUKhX8/PwwfPhwg3U0NTUhJSUFcrkcEokENjY2qKio0GtXdHQ0du3aBeDu4/27d+9GdHS0wfI64uTkhOeffx5/+9vfAAD79u1Da2sr5s6d261y2MDx1FNPwcTERPgcGBgo9O2ysjJotVq4u7vrjctjx47pPeIuFov1+n9HjHFMMKSr+02aNOmh8TY3N6O6uhrz58/XK+v9999vV//kyZPb7e/j46P3/cyKigpMnDgR1tbWwrKgoCDodDqo1eoO92OM9W/8cqF+4sEv55uYmOgtu3ey1Ol0AO5evIWFheEvf/lLu7LuXXyGhYVBJpMhPT0dTk5O0Ol08Pb2RltbW4d1P1jPg8aOHQu1Wo0jR44gPz8fb775JtauXYtjx44J5Rgqrzt19DZDuX2w7s5y/dprr+l9l/UeZ2dniMVilJaWorCwEIcPH8by5cuxcuVKnD59GhKJBPn5+Th58iQOHz6MzZs3409/+hOKi4sxbty43m4q6yP9ZfxaWlp2t2kGPWxMdVZHSkoK8vPzsW7dOri6usLS0hIRERF67YqKisLSpUtRWlqKlpYWXLp0CZGRkd2Oc8GCBYiJicHHH3+MjIwMREZGwsrKqtvlsIGvqakJIpEIJSUlEIlEeutsbGyE3y0tLfUmrx0xxjGho7i7st/9E8COygGA9PT0dt+xfjAfhsrqrPyO9HQ/xtjjiSeeA5S/vz9ycnLg4uICM7P2/8zXrl2DWq1Geno6goODAdx9QU5vsLS0RFhYGMLCwpCQkAAPDw+UlZXB39+/R+XJ5XIolUq9ZUqlEu7u7hCJRJDL5bhz5w6Ki4sxdepUAD+3z9PTE8Dd/4W+/45Mb/L398d3330HV1fXDrcxMzPDjBkzMGPGDKxYsQISiQRHjx7Fyy+/DBMTEwQFBSEoKAjLly+HTCbD3r178fbbbxslXvb466vx6+vri++//x4ajcbgXc/OxmJX69i+fTuuX79u8K6nUqlEfHw8XnrpJQB3L3jvvSTlnjFjxkChUGDnzp1oaWnBzJkzMXLkyA7r7Gj8z549G9bW1ti6dSvy8vJQVFTUpTawgeneC67u+fbbb+Hm5gaRSAQ/Pz9otVpcuXJFGHOPUmfHBMBwP+/Kfl0hlUrh5OSECxcudPvpAkPkcjkyMzPR3NwsTC6VSiVMTU35JUKMDWD8qO0AlZCQgOvXryMqKgqnT59GdXU1Dh06hHnz5kGr1cLOzg729vZIS0tDVVUVjh492isTnczMTHz++ecoLy/HhQsXsGPHDlhaWkImk/W4zCVLlqCgoACpqanQaDT4+9//ji1btiAlJQUA4ObmhvDwcCxcuBAnTpzAuXPn8Oqrr2L06NEIDw8HcPdNm01NTSgoKEBDQ4PwqGtvWLp0KU6ePInExESoVCpUVlbin//8JxITEwEA+/fvxyeffAKVSoWLFy/iH//4B3Q6HSZMmIDi4mJ8+OGHOHPmDOrq6pCbm4urV69CLpf3Wnys/+mr8atQKPDMM8/gN7/5DfLz81FTU4Ovv/4aeXl5ADofi10RFRWFUaNGYc6cOVAqlbhw4QJycnKEt+26ubkhNzcXKpUK586dwyuvvGLwDm10dDSysrLw5Zdfdnoh7OLiguLiYtTW1qKhoUEoTyQSIT4+HsuWLYObmxsCAwO73A428NTV1eHtt9+GWq3G7t27sXnzZiQlJQEA3N3dER0djdjYWOTm5qKmpgb/+te/sHr1ahw4cMDosXV2TAAM9/Ou7NdVf/7zn7F69Wp88skn0Gg0KCsrQ0ZGBjZs2NDt9kRHR8PCwgJxcXEoLy/HN998g7feegsxMTHCY8aMsYGHJ54DlJOTE5RKJbRaLZ577jn4+PggOTkZEokEpqamMDU1RVZWFkpKSuDt7Y3f/e53WLt27S+uVyKRID09HUFBQfD19cWRI0ewb98+2Nvb97hMf39/ZGdnIysrC97e3li+fDlWrVqF+Ph4YZuMjAxMmjQJL7zwAgIDA0FEOHjwoPDo0tSpU/H6668jMjISI0aMwEcfffRLmyrw9fXFsWPHoNFoEBwcDD8/PyxfvhxOTk4A7uYkNzcXzz77LORyObZt24bdu3fDy8sLtra2KCoqwuzZs+Hu7o53330X69evR2jWe2iuAAABzUlEQVRoaK/Fx/qfvhq/wN0/lzJlyhRERUXB09MTv//974UL1K6Mxc6IxWIcPnwYI0eOxOzZs+Hj44M1a9YId0w3bNgAOzs7TJ06FWFhYZg1a5bBpyUiIiJw7do13Lp1S+9PVRiSkpICkUgET09PjBgxQu/7ovPnz0dbWxvmzZvX5TawgSk2NhYtLS148sknkZCQgKSkJCxatEhYn5GRgdjYWCxZsgQTJkzAnDlzcPr0aTg7Oxs9ts6OCYDhft6V/bpqwYIF2L59OzIyMuDj4wOFQoHMzMwefS3EysoKhw4dwvXr1zFlyhREREQgJCQEW7Zs6XZZjLH+w4Tovj9SxRhjjA0ix48fR0hICC5dusR3WgaxadOm4Ve/+hU2btzY16EwxtiAxd/xZIwxNui0trbi6tWrWLlyJebOncuTTsYYY8zI+FFbxhhjg87u3bshk8lw8+bNXn30njHGGGOG8aO2jDHGGGOMMcaMiu94MsYYY4wxxhgzKp54MsYYY4wxxhgzKp54MsYYY4wxxhgzKp54MsYYY4wxxhgzKp54MsYYY4wxxhgzKp54MsYYY4wxxhgzKp54MsYYY4wxxhgzKp54MsYYY4wxxhgzqv8DkbIrXWmhMboAAAAASUVORK5CYII=\n"
-          },
-          "metadata": {}
-        }
+      "text/html": [
+       "\n",
+       "  <div id=\"df-d52120d9-7d31-4822-867b-72c4af95f0a7\" class=\"colab-df-container\">\n",
+       "    <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>MDVP:Fo(Hz)</th>\n",
+       "      <th>MDVP:Fhi(Hz)</th>\n",
+       "      <th>MDVP:Flo(Hz)</th>\n",
+       "      <th>MDVP:Jitter(%)</th>\n",
+       "      <th>MDVP:Jitter(Abs)</th>\n",
+       "      <th>MDVP:RAP</th>\n",
+       "      <th>MDVP:PPQ</th>\n",
+       "      <th>Jitter:DDP</th>\n",
+       "      <th>MDVP:Shimmer</th>\n",
+       "      <th>MDVP:Shimmer(dB)</th>\n",
+       "      <th>...</th>\n",
+       "      <th>MDVP:APQ</th>\n",
+       "      <th>Shimmer:DDA</th>\n",
+       "      <th>NHR</th>\n",
+       "      <th>HNR</th>\n",
+       "      <th>RPDE</th>\n",
+       "      <th>DFA</th>\n",
+       "      <th>spread1</th>\n",
+       "      <th>spread2</th>\n",
+       "      <th>D2</th>\n",
+       "      <th>PPE</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>119.992</td>\n",
+       "      <td>157.302</td>\n",
+       "      <td>74.997</td>\n",
+       "      <td>0.00784</td>\n",
+       "      <td>0.00007</td>\n",
+       "      <td>0.00370</td>\n",
+       "      <td>0.00554</td>\n",
+       "      <td>0.01109</td>\n",
+       "      <td>0.04374</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.02971</td>\n",
+       "      <td>0.06545</td>\n",
+       "      <td>0.02211</td>\n",
+       "      <td>21.033</td>\n",
+       "      <td>0.414783</td>\n",
+       "      <td>0.815285</td>\n",
+       "      <td>-4.813031</td>\n",
+       "      <td>0.266482</td>\n",
+       "      <td>2.301442</td>\n",
+       "      <td>0.284654</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>122.400</td>\n",
+       "      <td>148.650</td>\n",
+       "      <td>113.819</td>\n",
+       "      <td>0.00968</td>\n",
+       "      <td>0.00008</td>\n",
+       "      <td>0.00465</td>\n",
+       "      <td>0.00696</td>\n",
+       "      <td>0.01394</td>\n",
+       "      <td>0.06134</td>\n",
+       "      <td>0.626</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.04368</td>\n",
+       "      <td>0.09403</td>\n",
+       "      <td>0.01929</td>\n",
+       "      <td>19.085</td>\n",
+       "      <td>0.458359</td>\n",
+       "      <td>0.819521</td>\n",
+       "      <td>-4.075192</td>\n",
+       "      <td>0.335590</td>\n",
+       "      <td>2.486855</td>\n",
+       "      <td>0.368674</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>116.682</td>\n",
+       "      <td>131.111</td>\n",
+       "      <td>111.555</td>\n",
+       "      <td>0.01050</td>\n",
+       "      <td>0.00009</td>\n",
+       "      <td>0.00544</td>\n",
+       "      <td>0.00781</td>\n",
+       "      <td>0.01633</td>\n",
+       "      <td>0.05233</td>\n",
+       "      <td>0.482</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.03590</td>\n",
+       "      <td>0.08270</td>\n",
+       "      <td>0.01309</td>\n",
+       "      <td>20.651</td>\n",
+       "      <td>0.429895</td>\n",
+       "      <td>0.825288</td>\n",
+       "      <td>-4.443179</td>\n",
+       "      <td>0.311173</td>\n",
+       "      <td>2.342259</td>\n",
+       "      <td>0.332634</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>116.676</td>\n",
+       "      <td>137.871</td>\n",
+       "      <td>111.366</td>\n",
+       "      <td>0.00997</td>\n",
+       "      <td>0.00009</td>\n",
+       "      <td>0.00502</td>\n",
+       "      <td>0.00698</td>\n",
+       "      <td>0.01505</td>\n",
+       "      <td>0.05492</td>\n",
+       "      <td>0.517</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.03772</td>\n",
+       "      <td>0.08771</td>\n",
+       "      <td>0.01353</td>\n",
+       "      <td>20.644</td>\n",
+       "      <td>0.434969</td>\n",
+       "      <td>0.819235</td>\n",
+       "      <td>-4.117501</td>\n",
+       "      <td>0.334147</td>\n",
+       "      <td>2.405554</td>\n",
+       "      <td>0.368975</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>116.014</td>\n",
+       "      <td>141.781</td>\n",
+       "      <td>110.655</td>\n",
+       "      <td>0.01284</td>\n",
+       "      <td>0.00011</td>\n",
+       "      <td>0.00655</td>\n",
+       "      <td>0.00908</td>\n",
+       "      <td>0.01966</td>\n",
+       "      <td>0.06425</td>\n",
+       "      <td>0.584</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.04465</td>\n",
+       "      <td>0.10470</td>\n",
+       "      <td>0.01767</td>\n",
+       "      <td>19.649</td>\n",
+       "      <td>0.417356</td>\n",
+       "      <td>0.823484</td>\n",
+       "      <td>-3.747787</td>\n",
+       "      <td>0.234513</td>\n",
+       "      <td>2.332180</td>\n",
+       "      <td>0.410335</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>190</th>\n",
+       "      <td>174.188</td>\n",
+       "      <td>230.978</td>\n",
+       "      <td>94.261</td>\n",
+       "      <td>0.00459</td>\n",
+       "      <td>0.00003</td>\n",
+       "      <td>0.00263</td>\n",
+       "      <td>0.00259</td>\n",
+       "      <td>0.00790</td>\n",
+       "      <td>0.04087</td>\n",
+       "      <td>0.405</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.02745</td>\n",
+       "      <td>0.07008</td>\n",
+       "      <td>0.02764</td>\n",
+       "      <td>19.517</td>\n",
+       "      <td>0.448439</td>\n",
+       "      <td>0.657899</td>\n",
+       "      <td>-6.538586</td>\n",
+       "      <td>0.121952</td>\n",
+       "      <td>2.657476</td>\n",
+       "      <td>0.133050</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>191</th>\n",
+       "      <td>209.516</td>\n",
+       "      <td>253.017</td>\n",
+       "      <td>89.488</td>\n",
+       "      <td>0.00564</td>\n",
+       "      <td>0.00003</td>\n",
+       "      <td>0.00331</td>\n",
+       "      <td>0.00292</td>\n",
+       "      <td>0.00994</td>\n",
+       "      <td>0.02751</td>\n",
+       "      <td>0.263</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.01879</td>\n",
+       "      <td>0.04812</td>\n",
+       "      <td>0.01810</td>\n",
+       "      <td>19.147</td>\n",
+       "      <td>0.431674</td>\n",
+       "      <td>0.683244</td>\n",
+       "      <td>-6.195325</td>\n",
+       "      <td>0.129303</td>\n",
+       "      <td>2.784312</td>\n",
+       "      <td>0.168895</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>192</th>\n",
+       "      <td>174.688</td>\n",
+       "      <td>240.005</td>\n",
+       "      <td>74.287</td>\n",
+       "      <td>0.01360</td>\n",
+       "      <td>0.00008</td>\n",
+       "      <td>0.00624</td>\n",
+       "      <td>0.00564</td>\n",
+       "      <td>0.01873</td>\n",
+       "      <td>0.02308</td>\n",
+       "      <td>0.256</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.01667</td>\n",
+       "      <td>0.03804</td>\n",
+       "      <td>0.10715</td>\n",
+       "      <td>17.883</td>\n",
+       "      <td>0.407567</td>\n",
+       "      <td>0.655683</td>\n",
+       "      <td>-6.787197</td>\n",
+       "      <td>0.158453</td>\n",
+       "      <td>2.679772</td>\n",
+       "      <td>0.131728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>193</th>\n",
+       "      <td>198.764</td>\n",
+       "      <td>396.961</td>\n",
+       "      <td>74.904</td>\n",
+       "      <td>0.00740</td>\n",
+       "      <td>0.00004</td>\n",
+       "      <td>0.00370</td>\n",
+       "      <td>0.00390</td>\n",
+       "      <td>0.01109</td>\n",
+       "      <td>0.02296</td>\n",
+       "      <td>0.241</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.01588</td>\n",
+       "      <td>0.03794</td>\n",
+       "      <td>0.07223</td>\n",
+       "      <td>19.020</td>\n",
+       "      <td>0.451221</td>\n",
+       "      <td>0.643956</td>\n",
+       "      <td>-6.744577</td>\n",
+       "      <td>0.207454</td>\n",
+       "      <td>2.138608</td>\n",
+       "      <td>0.123306</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>194</th>\n",
+       "      <td>214.289</td>\n",
+       "      <td>260.277</td>\n",
+       "      <td>77.973</td>\n",
+       "      <td>0.00567</td>\n",
+       "      <td>0.00003</td>\n",
+       "      <td>0.00295</td>\n",
+       "      <td>0.00317</td>\n",
+       "      <td>0.00885</td>\n",
+       "      <td>0.01884</td>\n",
+       "      <td>0.190</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.01373</td>\n",
+       "      <td>0.03078</td>\n",
+       "      <td>0.04398</td>\n",
+       "      <td>21.209</td>\n",
+       "      <td>0.462803</td>\n",
+       "      <td>0.664357</td>\n",
+       "      <td>-5.724056</td>\n",
+       "      <td>0.190667</td>\n",
+       "      <td>2.555477</td>\n",
+       "      <td>0.148569</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>195 rows × 22 columns</p>\n",
+       "</div>\n",
+       "    <div class=\"colab-df-buttons\">\n",
+       "\n",
+       "  <div class=\"colab-df-container\">\n",
+       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d52120d9-7d31-4822-867b-72c4af95f0a7')\"\n",
+       "            title=\"Convert this dataframe to an interactive table.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+       "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+       "  </svg>\n",
+       "    </button>\n",
+       "\n",
+       "  <style>\n",
+       "    .colab-df-container {\n",
+       "      display:flex;\n",
+       "      gap: 12px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert {\n",
+       "      background-color: #E8F0FE;\n",
+       "      border: none;\n",
+       "      border-radius: 50%;\n",
+       "      cursor: pointer;\n",
+       "      display: none;\n",
+       "      fill: #1967D2;\n",
+       "      height: 32px;\n",
+       "      padding: 0 0 0 0;\n",
+       "      width: 32px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert:hover {\n",
+       "      background-color: #E2EBFA;\n",
+       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "      fill: #174EA6;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-buttons div {\n",
+       "      margin-bottom: 4px;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert {\n",
+       "      background-color: #3B4455;\n",
+       "      fill: #D2E3FC;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert:hover {\n",
+       "      background-color: #434B5C;\n",
+       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "      fill: #FFFFFF;\n",
+       "    }\n",
+       "  </style>\n",
+       "\n",
+       "    <script>\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#df-d52120d9-7d31-4822-867b-72c4af95f0a7 button.colab-df-convert');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      async function convertToInteractive(key) {\n",
+       "        const element = document.querySelector('#df-d52120d9-7d31-4822-867b-72c4af95f0a7');\n",
+       "        const dataTable =\n",
+       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+       "                                                    [key], {});\n",
+       "        if (!dataTable) return;\n",
+       "\n",
+       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+       "          + ' to learn more about interactive tables.';\n",
+       "        element.innerHTML = '';\n",
+       "        dataTable['output_type'] = 'display_data';\n",
+       "        await google.colab.output.renderOutput(dataTable, element);\n",
+       "        const docLink = document.createElement('div');\n",
+       "        docLink.innerHTML = docLinkHtml;\n",
+       "        element.appendChild(docLink);\n",
+       "      }\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "\n",
+       "    <div id=\"df-8d8cc699-bdc3-415f-a51f-a5dd44058db1\">\n",
+       "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8d8cc699-bdc3-415f-a51f-a5dd44058db1')\"\n",
+       "                title=\"Suggest charts\"\n",
+       "                style=\"display:none;\">\n",
+       "\n",
+       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "     width=\"24px\">\n",
+       "    <g>\n",
+       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+       "    </g>\n",
+       "</svg>\n",
+       "      </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
+       "      --hover-fill-color: #174EA6;\n",
+       "      --disabled-fill-color: #AAA;\n",
+       "      --disabled-bg-color: #DDD;\n",
+       "  }\n",
+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
+       "      --hover-bg-color: #434B5C;\n",
+       "      --hover-fill-color: #FFFFFF;\n",
+       "      --disabled-bg-color: #3B4455;\n",
+       "      --disabled-fill-color: #666;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart {\n",
+       "    background-color: var(--bg-color);\n",
+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
+       "    display: none;\n",
+       "    fill: var(--fill-color);\n",
+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    30% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "      <script>\n",
+       "        async function quickchart(key) {\n",
+       "          const quickchartButtonEl =\n",
+       "            document.querySelector('#' + key + ' button');\n",
+       "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "          try {\n",
+       "            const charts = await google.colab.kernel.invokeFunction(\n",
+       "                'suggestCharts', [key], {});\n",
+       "          } catch (error) {\n",
+       "            console.error('Error during call to suggestCharts:', error);\n",
+       "          }\n",
+       "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "        }\n",
+       "        (() => {\n",
+       "          let quickchartButtonEl =\n",
+       "            document.querySelector('#df-8d8cc699-bdc3-415f-a51f-a5dd44058db1 button');\n",
+       "          quickchartButtonEl.style.display =\n",
+       "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "        })();\n",
+       "      </script>\n",
+       "    </div>\n",
+       "\n",
+       "  <div id=\"id_eabe92fa-3f6c-4501-a1ec-d0b82f79e203\">\n",
+       "    <style>\n",
+       "      .colab-df-generate {\n",
+       "        background-color: #E8F0FE;\n",
+       "        border: none;\n",
+       "        border-radius: 50%;\n",
+       "        cursor: pointer;\n",
+       "        display: none;\n",
+       "        fill: #1967D2;\n",
+       "        height: 32px;\n",
+       "        padding: 0 0 0 0;\n",
+       "        width: 32px;\n",
+       "      }\n",
+       "\n",
+       "      .colab-df-generate:hover {\n",
+       "        background-color: #E2EBFA;\n",
+       "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "        fill: #174EA6;\n",
+       "      }\n",
+       "\n",
+       "      [theme=dark] .colab-df-generate {\n",
+       "        background-color: #3B4455;\n",
+       "        fill: #D2E3FC;\n",
+       "      }\n",
+       "\n",
+       "      [theme=dark] .colab-df-generate:hover {\n",
+       "        background-color: #434B5C;\n",
+       "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "        fill: #FFFFFF;\n",
+       "      }\n",
+       "    </style>\n",
+       "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('X')\"\n",
+       "            title=\"Generate code using this dataframe.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "       width=\"24px\">\n",
+       "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+       "  </svg>\n",
+       "    </button>\n",
+       "    <script>\n",
+       "      (() => {\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#id_eabe92fa-3f6c-4501-a1ec-d0b82f79e203 button.colab-df-generate');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      buttonEl.onclick = () => {\n",
+       "        google.colab.notebook.generateWithVariable('X');\n",
+       "      }\n",
+       "      })();\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
       ],
-      "source": [
-        "from tabpfn_extensions import unsupervised\n",
-        "from tabpfn_extensions.unsupervised import experiments\n",
-        "\n",
-        "# Load and prepare breast cancer dataset\n",
-        "df = load_breast_cancer(return_X_y=False)\n",
-        "X, y = df[\"data\"], df[\"target\"]\n",
-        "feature_names = df[\"feature_names\"]\n",
-        "\n",
-        "# Initialize TabPFN models\n",
-        "model_unsupervised = unsupervised.TabPFNUnsupervisedModel(\n",
-        "    tabpfn_clf=TabPFNClassifier(), tabpfn_reg=TabPFNRegressor()\n",
-        ")\n",
-        "\n",
-        "# Select features for synthetic data generation\n",
-        "# Example features: [mean texture, mean area, mean concavity]\n",
-        "feature_indices = [4, 6, 12]\n",
-        "\n",
-        "# Run synthetic data generation experiment\n",
-        "experiment = unsupervised.experiments.GenerateSyntheticDataExperiment(\n",
-        "    task_type=\"unsupervised\"\n",
-        ")\n",
-        "\n",
-        "results = experiment.run(\n",
-        "    tabpfn=model_unsupervised,\n",
-        "    X=torch.tensor(X),\n",
-        "    y=torch.tensor(y),\n",
-        "    attribute_names=feature_names,\n",
-        "    temp=1.0,  # Temperature parameter for sampling\n",
-        "    n_samples=X.shape[0] * 2,  # Generate twice as many samples as original data\n",
-        "    indices=feature_indices,\n",
-        ")"
+      "text/plain": [
+       "     MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
+       "0        119.992       157.302        74.997         0.00784   \n",
+       "1        122.400       148.650       113.819         0.00968   \n",
+       "2        116.682       131.111       111.555         0.01050   \n",
+       "3        116.676       137.871       111.366         0.00997   \n",
+       "4        116.014       141.781       110.655         0.01284   \n",
+       "..           ...           ...           ...             ...   \n",
+       "190      174.188       230.978        94.261         0.00459   \n",
+       "191      209.516       253.017        89.488         0.00564   \n",
+       "192      174.688       240.005        74.287         0.01360   \n",
+       "193      198.764       396.961        74.904         0.00740   \n",
+       "194      214.289       260.277        77.973         0.00567   \n",
+       "\n",
+       "     MDVP:Jitter(Abs)  MDVP:RAP  MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  \\\n",
+       "0             0.00007   0.00370   0.00554     0.01109       0.04374   \n",
+       "1             0.00008   0.00465   0.00696     0.01394       0.06134   \n",
+       "2             0.00009   0.00544   0.00781     0.01633       0.05233   \n",
+       "3             0.00009   0.00502   0.00698     0.01505       0.05492   \n",
+       "4             0.00011   0.00655   0.00908     0.01966       0.06425   \n",
+       "..                ...       ...       ...         ...           ...   \n",
+       "190           0.00003   0.00263   0.00259     0.00790       0.04087   \n",
+       "191           0.00003   0.00331   0.00292     0.00994       0.02751   \n",
+       "192           0.00008   0.00624   0.00564     0.01873       0.02308   \n",
+       "193           0.00004   0.00370   0.00390     0.01109       0.02296   \n",
+       "194           0.00003   0.00295   0.00317     0.00885       0.01884   \n",
+       "\n",
+       "     MDVP:Shimmer(dB)  ...  MDVP:APQ  Shimmer:DDA      NHR     HNR      RPDE  \\\n",
+       "0               0.426  ...   0.02971      0.06545  0.02211  21.033  0.414783   \n",
+       "1               0.626  ...   0.04368      0.09403  0.01929  19.085  0.458359   \n",
+       "2               0.482  ...   0.03590      0.08270  0.01309  20.651  0.429895   \n",
+       "3               0.517  ...   0.03772      0.08771  0.01353  20.644  0.434969   \n",
+       "4               0.584  ...   0.04465      0.10470  0.01767  19.649  0.417356   \n",
+       "..                ...  ...       ...          ...      ...     ...       ...   \n",
+       "190             0.405  ...   0.02745      0.07008  0.02764  19.517  0.448439   \n",
+       "191             0.263  ...   0.01879      0.04812  0.01810  19.147  0.431674   \n",
+       "192             0.256  ...   0.01667      0.03804  0.10715  17.883  0.407567   \n",
+       "193             0.241  ...   0.01588      0.03794  0.07223  19.020  0.451221   \n",
+       "194             0.190  ...   0.01373      0.03078  0.04398  21.209  0.462803   \n",
+       "\n",
+       "          DFA   spread1   spread2        D2       PPE  \n",
+       "0    0.815285 -4.813031  0.266482  2.301442  0.284654  \n",
+       "1    0.819521 -4.075192  0.335590  2.486855  0.368674  \n",
+       "2    0.825288 -4.443179  0.311173  2.342259  0.332634  \n",
+       "3    0.819235 -4.117501  0.334147  2.405554  0.368975  \n",
+       "4    0.823484 -3.747787  0.234513  2.332180  0.410335  \n",
+       "..        ...       ...       ...       ...       ...  \n",
+       "190  0.657899 -6.538586  0.121952  2.657476  0.133050  \n",
+       "191  0.683244 -6.195325  0.129303  2.784312  0.168895  \n",
+       "192  0.655683 -6.787197  0.158453  2.679772  0.131728  \n",
+       "193  0.643956 -6.744577  0.207454  2.138608  0.123306  \n",
+       "194  0.664357 -5.724056  0.190667  2.555477  0.148569  \n",
+       "\n",
+       "[195 rows x 22 columns]"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Load Parkinsons dataset described above\n",
+    "\n",
+    "import pandas as pd, io, zipfile, requests\n",
+    "\n",
+    "url_zip = \"https://archive.ics.uci.edu/static/public/174/parkinsons.zip\"\n",
+    "with requests.get(url_zip) as r:\n",
+    "    r.raise_for_status()\n",
+    "    zf = zipfile.ZipFile(io.BytesIO(r.content))\n",
+    "    df = pd.read_csv(zf.open(\"parkinsons.data\"))\n",
+    "X, y = df.drop([\"status\", \"name\"], axis=1), df[\"status\"]\n",
+    "\n",
+    "display(X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "id": "KAXhoOc2U2vJ"
+   },
+   "outputs": [],
+   "source": [
+    "# Alternative datasets (commented for reference):\n",
+    "\n",
+    "# Cholesterol dataset: Predict cholesterol levels\n",
+    "# Features: Patient characteristics, medical measurements\n",
+    "# Samples: 303 patients\n",
+    "# Target: Cholesterol levels in mg/dl\n",
+    "# df = fetch_openml('cholesterol', version=2, as_frame=True)\n",
+    "\n",
+    "# Heart Disease dataset (Statlog): Predict presence of heart disease\n",
+    "# Features: Clinical and test measurements\n",
+    "# Samples: 270 patients\n",
+    "# Target: Binary heart disease diagnosis\n",
+    "# df = fetch_openml(\"heart-statlog\", version=1)\n",
+    "\n",
+    "# Diabetes dataset: Predict diabetes presence\n",
+    "# Features: Medical measurements, patient history\n",
+    "# Samples: 768 patients\n",
+    "# Target: Binary diabetes diagnosis\n",
+    "# df = fetch_openml(\"diabetes\", version=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "zTHzDedu3DKR",
+    "outputId": "b8f79392-66bf-4884-bcbd-1a7cb51ab676"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_aoNg2_K4k6E"
-      },
-      "source": [
-        "### Outlier detection"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing: 100%|██████████| [00:02<00:00]\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 14,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 0
-        },
-        "id": "ezircAHiZSKG",
-        "outputId": "4c93610c-33a5-4dd1-ba43-6ba118c06942"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 600x600 with 3 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
-      ],
-      "source": [
-        "import torch\n",
-        "from sklearn.datasets import load_breast_cancer\n",
-        "from tabpfn_extensions import unsupervised\n",
-        "from tabpfn_extensions.unsupervised import experiments\n",
-        "\n",
-        "# Load data\n",
-        "df = load_breast_cancer(return_X_y=False)\n",
-        "X, y = df[\"data\"], df[\"target\"]\n",
-        "attribute_names = df[\"feature_names\"]\n",
-        "\n",
-        "# Initialize models\n",
-        "clf = TabPFNClassifier(n_estimators=4)\n",
-        "reg = TabPFNRegressor(n_estimators=4)\n",
-        "model_unsupervised = unsupervised.TabPFNUnsupervisedModel(\n",
-        "    tabpfn_clf=clf, tabpfn_reg=reg\n",
-        ")\n",
-        "\n",
-        "# Run outlier detection\n",
-        "exp_outlier = unsupervised.experiments.OutlierDetectionUnsupervisedExperiment(\n",
-        "    task_type=\"unsupervised\"\n",
-        ")\n",
-        "results = exp_outlier.run(\n",
-        "    tabpfn=model_unsupervised,\n",
-        "    X=torch.tensor(X, dtype=torch.float32),\n",
-        "    y=torch.tensor(y),\n",
-        "    attribute_names=attribute_names,\n",
-        "    indices=[4, 12],  # Analyze features 4 and 12\n",
-        ")"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "TabPFN ROC AUC Score: 0.9732\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Split the data into training and testing sets\n",
+    "X_train, X_test, y_train, y_test = train_test_split(\n",
+    "    X, y, test_size=0.20, random_state=42\n",
+    ")\n",
+    "\n",
+    "# Train and evaluate the TabPFN classifier\n",
+    "tabpfn_classifier = TabPFNClassifier(random_state=42)\n",
+    "tabpfn_classifier.fit(X_train, y_train)\n",
+    "y_pred_proba = tabpfn_classifier.predict_proba(X_test)\n",
+    "\n",
+    "# Calculate the ROC AUC score\n",
+    "roc_auc = roc_auc_score(y_test, y_pred_proba[:, 1])\n",
+    "print(f\"TabPFN ROC AUC Score: {roc_auc:.4f}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ZVs_HfxbVCs3"
+   },
+   "source": [
+    "### Comparing TabPFN with Other Classifiers\n",
+    "\n",
+    "To get a better sense of TabPFN's performance, let's compare it with other popular classification models using cross-validation. This will give us a more robust estimate of each model's performance.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 789
     },
+    "id": "ITuXXhqE7Fps",
+    "outputId": "f7cc728b-2b9e-4d1f-ce3a-db8bd165c371"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "Qk6OxtxmJsr9"
-      },
-      "source": [
-        "### Missing value imputation"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing: 100%|██████████| [00:01<00:00]\n",
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "Processing: 100%|██████████| [00:02<00:00]\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:   12.8s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.7s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.2s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    8.9s finished\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 15,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "9hgAlgghJuF3",
-        "outputId": "bc78fafc-f40e-4dfb-a2e8-9e3f7487d691"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Introduced 168 missing values into the test set.\n",
-            "       0      1       2\n",
-            "0    NaN  18.60   81.09\n",
-            "1  18.94    NaN  123.60\n",
-            "2  15.46  19.48  101.70\n",
-            "3  12.40    NaN   81.47\n",
-            "4    NaN  14.44     NaN\n",
-            "Fitting the unsupervised model on the training data...\n",
-            "Imputing missing values...\n",
-            "\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "100%|██████████| 3/3 [00:11<00:00,  3.88s/it]"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "\n",
-            "------------------------\n",
-            "\n",
-            "Number of missing values after imputation: 0\n",
-            "           0          1           2\n",
-            "0  12.515228  18.600000   81.089996\n",
-            "1  18.940001  21.109259  123.599998\n",
-            "2  15.460000  19.480000  101.699997\n",
-            "3  12.400000  17.477161   81.470001\n",
-            "4  11.358663  14.440000   74.500938\n",
-            "Mean Squared Error of imputed values vs. original values: 0.4940\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "\n"
-          ]
-        }
-      ],
-      "source": [
-        "# --- 1. Load and Prepare Data ---\n",
-        "# Load the breast cancer dataset\n",
-        "df = load_breast_cancer(return_X_y=False)\n",
-        "X, y = df[\"data\"], df[\"target\"]\n",
-        "\n",
-        "# Split the data into training and testing sets\n",
-        "X_train, X_test = train_test_split(\n",
-        "    X,\n",
-        "    test_size=0.33,\n",
-        "    random_state=42,\n",
-        ")\n",
-        "\n",
-        "# --- 2. Introduce Missing Values ---\n",
-        "# Create a copy of the test set to introduce missing values (NaNs)\n",
-        "X_test_missing = X_test.copy()\n",
-        "n_samples, n_features = X_test_missing.shape\n",
-        "\n",
-        "# Introduce missing values in the first three columns for demonstration\n",
-        "missing_fraction = 0.3\n",
-        "n_missing = int(n_samples * missing_fraction)\n",
-        "\n",
-        "for col_idx in range(3):\n",
-        "    # Choose random rows to set to NaN\n",
-        "    missing_indices = np.random.choice(n_samples, n_missing, replace=False)\n",
-        "    X_test_missing[missing_indices, col_idx] = np.nan\n",
-        "\n",
-        "print(f\"Introduced {np.isnan(X_test_missing).sum()} missing values into the test set.\")\n",
-        "print(pd.DataFrame(X_test_missing[:, 0:3]).head())\n",
-        "\n",
-        "# --- 3. Initialize the Unsupervised Model ---\n",
-        "# Initialize TabPFN models for regression and classification tasks.\n",
-        "# The unsupervised model uses these to model the data distribution.\n",
-        "clf = TabPFNClassifier(n_estimators=3)\n",
-        "reg = TabPFNRegressor(n_estimators=3)\n",
-        "\n",
-        "# Initialize the main unsupervised model\n",
-        "model_unsupervised = unsupervised.TabPFNUnsupervisedModel(\n",
-        "    tabpfn_clf=clf,\n",
-        "    tabpfn_reg=reg,\n",
-        ")\n",
-        "\n",
-        "# --- 4. Fit and Impute ---\n",
-        "# Fit the model on the complete training data (without missing values)\n",
-        "print(\"Fitting the unsupervised model on the training data...\")\n",
-        "model_unsupervised.fit(X_train)\n",
-        "\n",
-        "# Perform imputation on the test set\n",
-        "print(\"Imputing missing values...\\n\")\n",
-        "X_imputed_tensor = model_unsupervised.impute(\n",
-        "    X_test_missing,\n",
-        "    n_permutations=5,  # Fewer permutations for a quicker example\n",
-        ")\n",
-        "\n",
-        "print(\"\\n------------------------\")\n",
-        "\n",
-        "# --- 5. Verify Results ---\n",
-        "# Check that the imputed data no longer contains any NaN values\n",
-        "n_missing_after = torch.isnan(X_imputed_tensor).sum().item()\n",
-        "\n",
-        "print(f\"\\nNumber of missing values after imputation: {n_missing_after}\")\n",
-        "print(pd.DataFrame(X_imputed_tensor[:, 0:3]).head())\n",
-        "\n",
-        "# Optional: Calculate the Mean Squared Error for the imputed values,\n",
-        "# since we know the original ground truth values.\n",
-        "original_nan_mask = np.isnan(X_test_missing)\n",
-        "imputed_values = X_imputed_tensor.numpy()[original_nan_mask]\n",
-        "original_values = X_test[original_nan_mask]\n",
-        "\n",
-        "mse = np.mean((imputed_values - original_values) ** 2)\n",
-        "print(f\"Mean Squared Error of imputed values vs. original values: {mse:.4f}\")"
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Model Comparison - 3-fold Cross-validation')"
       ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "MqZlQ09WfCe9"
-      },
-      "source": [
-        "# Model Interpretability <a name=\"interpretability\"></a>\n",
-        "\n",
-        "Understanding *why* a model makes certain predictions is crucial for building trust and for debugging. The `tabpfn-extensions` library provides tools for model interpretability. We'll look at SHAP (SHapley Additive exPlanations) values, which show the impact of each feature on a specific prediction."
+     "data": {
+      "image/png": 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bNk2fffaZgoKC1LBhQ7300ktKTk6292/UqJFat26tiRMnyt/fXy1bttSCBQuUlZVl73P+/HmH43sjILVr105Xr17VmjVrJP369/3000/Vpk0bh8/KDz/8oFatWsnX11c+Pj4KCAhQp06dJOV+T9+Ms8ffmc9SfuT3uN9gtVoVEBDg0FayZMmbfkYA3HkEJgB/2NNPP63PPvtM8+bNU5MmTRyuwS9INptNktSpUyetX78+z6lBgwZOrTMyMlIHDx5Udnb2Ha/3xv0Y+W03fjcQRl5+H8COHDmiRx99VBcuXND06dO1du1arV+/XoMHD5b0v2N2w29/Qb+Zhg0b6siRI5o/f77uv/9+/fvf/9YDDzygf//73/laPi+3s9+vvPKKgoOD7VPt2rWd3q6Hh4datGihVatW6erVq5Kkf/7znw7rvdk9SK50YyCS//73v04tl9+/c14GDRqkgwcPaurUqbJarRo7dqwqV66sXbt2Sfr1PfjBBx9oy5Yt6t+/v30Qlpo1a9qDUe3atR2O7yuvvCJJqlu3rsLCwrRixQpJ0scff6yrV6+qXbt29u2npqaqUaNG2rNnjyZNmqSPP/5Y69evt9/r9vv39J3i7GepIJh9RgAULgZ9APCHtWrVSr169dLWrVu1fPly037lypXThg0bdOnSJYezTDcuqSlXrpz9nzabTUeOHHH4JfbAgQMO67sxgl5OTo5iY2PvyL40b95cW7Zs0cqVKx0utzLbnxt1hYeH29uzs7N17NixO1bTbx06dMjhbMHhw4dls9nsAyp8/PHHysrK0po1axzO4Hz55Zd/eNv33HOP4uPjFR8fr8uXL6thw4aaMGGCevTo4XAsfm///v3y9/dX8eLF/3ANnTt3Nr1UyxlXr16VYRi6dOmSvLy89Oqrrzr8ah8SEnLT5cuVK6e9e/fKZrM5nGX6/Xv59wICAuTl5ZXnpY15Hbvfu++++1SpUiV99NFHmjlzpry9vW+5jFn9N7b5j3/8I1cdv68/IiJCQ4cO1dChQ3Xo0CFFR0fr1Vdf1ZIlS+x96tatq7p162rKlClatmyZOnbsqPfee089evTQ0qVL7eFUksPnpW3btpo5c6bS09O1fPlyhYWFqW7duvb5Gzdu1MWLF7Vq1So1bNjQ3n7s2DGn99uZ4+/MZ+n3P1yYcfa4A/hz4AwTgD/M29tbc+fO1YQJE9S8eXPTfk2bNlVOTo5mz57t0D5jxgxZLBb7SHs3/vn7UfYSEhIcXru7u6t169ZauXKlvv/++1zby+/lWr/Vu3dvBQcHa+jQoTp48GCu+efOndPkyZMlSbGxsfLw8NBrr73mcFbk7bffVlpaWp6j+v1Rc+bMcXg9a9YsSf87Zjd+kf5tPWlpaVqwYMEf2u7FixcdXnt7e6tChQr2y66Cg4MVHR2tRYsWOQzX/f333+vzzz9X06ZN/9D2bwgPD1dsbKx9utUZxLwuyUxNTdXKlSsVGhqqwMBASVLNmjUd1nur5y41bdpUycnJDj8QXL9+XbNmzZK3t7caNWqU53Lu7u6Ki4vT6tWrdfLkSXv7jz/+qHXr1t10mzdMnDhRFy9eVI8ePfK8D+vzzz/XJ598ctN11KpVS4GBgZo3b57DpXOfffaZfvzxR/t798qVK7mGrY+IiFCJEiXsy/3yyy+5zgpGR0dLkr1PgwYNHI7vbwNTu3btlJWVpUWLFikxMVFt27Z1WFde7+ns7Gy9/vrrN93HvDhz/J35LBUvXvyWw9RL+T/uAP5cOMME4I7o0qXLLfs0b95cjzzyiEaPHq3jx48rKipKn3/+uT766CMNGjTIfs9SdHS0OnTooNdff11paWmqX7++kpKSdPjw4VzrfPHFF/Xll18qJiZGPXv2VJUqVfTzzz9r586d2rBhg37++Wen9qNkyZL68MMP1bRpU0VHR6tTp06qWbOmJGnnzp169913Va9ePUm//lo9atQoTZw4UY0bN1aLFi104MABvf7666pdu7b9Hos76dixY2rRooUaN26sLVu22Idej4qKkiQ9/vjj8vDwUPPmzdWrVy9dvnxZb731lgIDA3X27Nnb3m6VKlX08MMPq2bNmrrnnnv03Xff6YMPPlD//v3tfV5++WU1adJE9erVU/fu3e3Divv6+uZ6Dk5hadKkie69917FxMQoMDBQJ0+e1IIFC3TmzJmbng29lWeeeUZvvPGGunbtqh07digsLEwffPCBNm/erISEhJsOyjBx4kQlJibqoYceUt++fe1Bq2rVqg73hZlp166d/vvf/2rKlCnatWuXOnTooHLlyunixYtKTExUUlKSli1bdtN1FC1aVNOmTVN8fLwaNWqkDh062Ie3DgsLs192dvDgQT366KNq27atqlSpoiJFiujDDz9USkqKfQCTRYsW6fXXX1erVq0UERGhS5cu6a233pKPj0++gvIDDzygChUqaPTo0crKynK4HE+S6tevr5IlS6pLly4aOHCgLBaLFi9enK9LVvOS3+PvzGepZs2amjt3riZPnqwKFSooMDAw1xkkKf/HHcCfjGsG5wPwV/bbYcVvJq/hmC9dumQMHjzYCAkJMYoWLWpUrFjRePnllw2bzebQ7+rVq8bAgQONUqVKGcWLFzeaN29unDp1KtcQwYZhGCkpKUa/fv2M0NBQo2jRokbp0qWNRx991HjzzTftffI7rPgNZ86cMQYPHmzcd999htVqNYoVK2bUrFnTmDJlipGWlubQd/bs2UZkZKRRtGhRIygoyOjTp4/xyy+/OPRp1KiRUbVq1XwdI8P4dSjkfv362V/fGIp73759xlNPPWWUKFHCKFmypNG/f/9cw2OvWbPGqF69umG1Wo2wsDBj2rRpxvz58w1JxrFjx2657Rvzfjus+OTJk406deoYfn5+hpeXlxEZGWlMmTLFyM7Odlhuw4YNRoMGDQwvLy/Dx8fHaN68ubFv3z6HPjf25fz58w7tN95Xv63xj5o9e7bx4IMPGv7+/kaRIkWMgIAAo3nz5g5DVt+K2XFKSUkx4uPjDX9/f8PDw8OoVq1anu+vvN6zX331lVGzZk3Dw8PDCA8PN+bNm2c/LvmVlJRktGzZ0ggMDHTYt48++sje58aw1u+//36e61i+fLlRo0YNw9PT07jnnnuMjh07Gj/99JN9/oULF4x+/foZkZGRRvHixQ1fX18jJibGWLFihb3Pzp07jQ4dOhhly5Y1PD09jcDAQOOJJ54wvvvuu3zvy+jRow1JRoUKFfKcv3nzZqNu3bqGl5eXERISYowYMcI+/P6NIbsNI3/DihtG/o9/fj9LycnJRrNmzYwSJUoYkuxDjP9+WPEbbnXcb+xL8eLFcx0LZ98nAP44i2Hc5k80AIBCc+MBuefPn5e/v7+rywEA4K7BPUwAAAAAYILABAAAAAAmCEwAAAAAYIJ7mAAAAADABGeYAAAAAMDEXfMcJpvNpjNnzqhEiRL5fiI3AAAAgL8fwzB06dIlhYSEyM3t5ueQ7prAdObMGYWGhrq6DAAAAAB/EqdOndK999570z53TWC68dT1U6dOycfHx8XVAAAAAHCV9PR0hYaG2jPCzdw1genGZXg+Pj4EJgAAAAD5ulWHQR8AAAAAwASBCQAAAABMEJgAAAAAwMRdcw8TAAAA4KycnBxdu3bN1WXgNnh4eNxyyPD8IDABAAAAv2MYhpKTk5WamurqUnCb3NzcVL58eXl4ePyh9RCYAAAAgN+5EZYCAwNVrFixfI2mhj8Pm82mM2fO6OzZsypbtuwf+vsRmAAAAIDfyMnJsYelUqVKuboc3KaAgACdOXNG169fV9GiRW97PQz6AAAAAPzGjXuWihUr5uJK8EfcuBQvJyfnD62HwAQAAADkgcvw/tru1N+PwAQAAAAAJghMAAAAAGCCQR8AAACAfAobubZQt3f8xWaFuj3kxhkmAAAA4G+ia9euslgsslgsKlq0qMqXL68RI0YoMzMzV99PPvlEjRo1UokSJVSsWDHVrl1bCxcuzHO9K1eu1MMPPyxfX195e3urevXqmjRpkn7++edb1tSrVy+5u7vr/fffz7PeJ598Mlf7xo0bZbFYHJ6DlZ2drZdeeklRUVEqVqyY/P391aBBAy1YsKBAHy5MYAIAAAD+Rho3bqyzZ8/q6NGjmjFjht544w2NHz/eoc+sWbPUsmVLNWjQQNu2bdPevXvVvn179e7dW8OGDXPoO3r0aLVr1061a9fWZ599pu+//16vvvqq9uzZo8WLF9+0litXrui9997TiBEjNH/+/Nvep+zsbMXFxenFF1/UM888o2+++Ubbt29Xv379NGvWLP3www+3ve5b4ZI8AAAA4G/E09NTpUuXliSFhoYqNjZW69ev17Rp0yRJp06d0tChQzVo0CC98MIL9uWGDh0qDw8PDRw4UG3atFFMTIy2b9+uF154QQkJCXr22WftfcPCwvTYY485nAHKy/vvv68qVapo5MiRCgkJ0alTpxQaGur0PiUkJOjrr7/Wd999pxo1atjbw8PD1aZNG2VnZzu9zvziDBMAAADwN/X999/rm2++sT+TSJI++OADXbt2LdeZJOnXy+e8vb317rvvSpKWLl0qb29v9e3bN8/1+/n53XT7b7/9tjp16iRfX181adLE9JK/W1m6dKliY2MdwtINRYsWVfHixW9rvflBYAIAAAD+Rj755BN5e3vLarWqWrVqOnfunIYPH26ff/DgQfn6+io4ODjXsh4eHgoPD9fBgwclSYcOHVJ4eLiKFi3qdB2HDh3S1q1b1a5dO0lSp06dtGDBAhmGcVvrioyMdHq5O4HABAAAAPyNPPLII9q9e7e2bdumLl26KD4+Xq1bt76tdd1OuLlh/vz5iouLk7+/vySpadOmSktL0xdffFGodfxRBCYAAADgb6R48eKqUKGCoqKiNH/+fG3btk1vv/22ff59992ntLQ0nTlzJtey2dnZOnLkiO677z5736NHjzo9Cl1OTo4WLVqktWvXqkiRIipSpIiKFSumn3/+2WHwBx8fH6WlpeVaPjU1Ve7u7vZL7e677z7t37/fqRruFAITAAAA8Dfl5uam5557TmPGjNHVq1clSa1bt1bRokX16quv5uo/b948ZWRkqEOHDpKkp59+WpcvX9brr7+e5/rNBn349NNPdenSJe3atUu7d++2T++++65WrVplX65SpUr64YcflJWV5bD8zp07Vb58efulgE8//bQ2bNigXbt25drWtWvXlJGRka/jcTsITAAAAMDfWJs2beTu7q45c+ZIksqWLauXXnpJCQkJGj16tPbv368jR45o+vTpGjFihIYOHaqYmBhJUkxMjL1txIgR2rJli06cOKGkpCS1adNGixYtynObb7/9tpo1a6aoqCjdf//99qlt27by8/PT0qVLJUkdO3aUxWJR586dtWPHDh0+fFjz589XQkKChg4dal/foEGD1KBBAz366KOaM2eO9uzZo6NHj2rFihWqW7euDh06VGDHz2K48oLAQpSeni5fX1+lpaXJx8fH1eUAAADgTyozM1PHjh1T+fLlZbVaXV2OU7p27arU1FStXr3aof3FF1/U9OnTdezYMftlbmvWrNErr7yinTt3KicnR1WrVlW/fv0UHx+fa70rVqzQnDlztGvXLtlsNkVEROipp57SgAEDco2Ul5KSonvvvVfLli1TmzZtcq2rb9++2rp1q3bu3Cnp10EoRo4cqW3btiktLU0VKlRQ//791b17d1ksFvtyWVlZmjFjhpYtW6ZDhw6pWLFiqly5snr27KmOHTuqSBHHJybd7O/oTDYgMAEAAAC/8VcOTPifOxWYuCQPAAAAAEzcVmCaM2eOwsLCZLVa7U8ANnPt2jVNmjRJERERslqtioqKUmJiokOfS5cuadCgQSpXrpy8vLxUv359ffvttw59DMPQuHHjFBwcLC8vL8XGxhbotYoAAAAA4HRgWr58uYYMGaLx48dr586dioqKUlxcnM6dO5dn/zFjxuiNN97QrFmztG/fPvXu3VutWrVyGOGiR48eWr9+vRYvXqz//ve/evzxxxUbG6vTp0/b+7z00kt67bXXNG/ePG3btk3FixdXXFycMjMzb2O3AQAAAODWnL6HKSYmRrVr19bs2bMlSTabTaGhoRowYIBGjhyZq39ISIhGjx6tfv362dtat24tLy8vLVmyRFevXlWJEiX00UcfqVmzZvY+NWvWVJMmTTR58mQZhqGQkBANHTpUw4YNkySlpaUpKChICxcuVPv27XNtNysry2F4wvT0dIWGhnIPEwAAAG6Ke5j+HlxyD1N2drZ27Nih2NjY/63AzU2xsbHasmVLnstkZWXlKtDLy0ubNm2SJF2/fl05OTk37XPs2DElJyc7bNfX11cxMTGm2506dap8fX3tU2hoqDO7CgAAgLvcXTI22t/Wnfr7ORWYLly4oJycHAUFBTm0BwUFKTk5Oc9l4uLiNH36dB06dEg2m03r16/XqlWrdPbsWUlSiRIlVK9ePT3//PM6c+aMcnJytGTJEm3ZssXe58a6ndnuqFGjlJaWZp9OnTrlzK4CAADgLnXjYalXrlxxcSX4I7KzsyVJ7u7uf2g9RW7d5Y+ZOXOmevbsqcjISFksFkVERCg+Pl7z58+391m8eLG6deumMmXKyN3dXQ888IA6dOigHTt23PZ2PT095enpeSd2AQAAAHcRd3d3+fn52e/RL1asmMPzgPDnZ7PZdP78eRUrVizX85mc5dTS/v7+cnd3V0pKikN7SkqKSpcunecyAQEBWr16tTIzM3Xx4kWFhIRo5MiRCg8Pt/eJiIjQV199pYyMDKWnpys4OFjt2rWz97mx7pSUFAUHBztsNzo62pldAAAAAG7pxvdPs4HN8Ofn5uamsmXL/uGw61Rg8vDwUM2aNZWUlKQnn3xS0q/pLSkpSf3797/pslarVWXKlNG1a9e0cuVKtW3bNlef4sWLq3jx4vrll1+0bt06vfTSS5Kk8uXLq3Tp0kpKSrIHpPT0dG3btk19+vRxZhcAAACAW7JYLAoODlZgYKCuXbvm6nJwGzw8POTm9scfO+v0+akhQ4aoS5cuqlWrlurUqaOEhARlZGQoPj5ektS5c2eVKVNGU6dOlSRt27ZNp0+fVnR0tE6fPq0JEybIZrNpxIgR9nWuW7dOhmGoUqVKOnz4sIYPH67IyEj7Oi0WiwYNGqTJkyerYsWKKl++vMaOHauQkBB7cAMAAADuNHd39z98Dwz+2pwOTO3atdP58+c1btw4JScnKzo6WomJifYBGU6ePOmQ5DIzMzVmzBgdPXpU3t7eatq0qRYvXiw/Pz97n7S0NI0aNUo//fST7rnnHrVu3VpTpkyx33AnSSNGjFBGRoaeeeYZpaam6sEHH1RiYiJDPQIAAAAoME4/h+mvypmx1gEAAAD8fRXYc5gAAAAA4G5CYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBRxNUFwDlhI9e6uoS73vEXm7m6BAAAABQSzjABAAAAgAkCEwAAAACYIDABAAAAgAkCEwAAAACYIDABAAAAgAkCEwAAAACYIDABAAAAgAkCEwAAAACYIDABAAAAgAkCEwAAAACYIDABAAAAgAkCEwAAAACYIDABAAAAgAkCEwAAAACYIDABAAAAgAkCEwAAAACYIDABAAAAgAkCEwAAAACYIDABAAAAgAkCEwAAAACYIDABAAAAgAkCEwAAAACYIDABAAAAgAkCEwAAAACYIDABAAAAgAkCEwAAAACYuK3ANGfOHIWFhclqtSomJkbbt2837Xvt2jVNmjRJERERslqtioqKUmJiokOfnJwcjR07VuXLl5eXl5ciIiL0/PPPyzAMe5+uXbvKYrE4TI0bN76d8gEAAAAgX4o4u8Dy5cs1ZMgQzZs3TzExMUpISFBcXJwOHDigwMDAXP3HjBmjJUuW6K233lJkZKTWrVunVq1a6ZtvvlGNGjUkSdOmTdPcuXO1aNEiVa1aVd99953i4+Pl6+urgQMH2tfVuHFjLViwwP7a09PzdvYZAAAAAPLFYvz2NE4+xMTEqHbt2po9e7YkyWazKTQ0VAMGDNDIkSNz9Q8JCdHo0aPVr18/e1vr1q3l5eWlJUuWSJKeeOIJBQUF6e233zbt07VrV6Wmpmr16tX5qjMrK0tZWVn21+np6QoNDVVaWpp8fHyc2eU/lbCRa11dwl3v+IvNXF0CAAAA/oD09HT5+vrmKxs4dUledna2duzYodjY2P+twM1NsbGx2rJlS57LZGVlyWq1OrR5eXlp06ZN9tf169dXUlKSDh48KEnas2ePNm3apCZNmjgst3HjRgUGBqpSpUrq06ePLl68aFrr1KlT5evra59CQ0Od2VUAAAAAcC4wXbhwQTk5OQoKCnJoDwoKUnJycp7LxMXFafr06Tp06JBsNpvWr1+vVatW6ezZs/Y+I0eOVPv27RUZGamiRYuqRo0aGjRokDp27Gjv07hxY73zzjtKSkrStGnT9NVXX6lJkybKycnJc7ujRo1SWlqafTp16pQzuwoAAAAAzt/D5KyZM2eqZ8+eioyMlMViUUREhOLj4zV//nx7nxUrVmjp0qVatmyZqlatqt27d2vQoEEKCQlRly5dJEnt27e3969WrZqqV6+uiIgIbdy4UY8++miu7Xp6enKPEwAAAIA/xKkzTP7+/nJ3d1dKSopDe0pKikqXLp3nMgEBAVq9erUyMjJ04sQJ7d+/X97e3goPD7f3GT58uP0sU7Vq1fR///d/Gjx4sKZOnWpaS3h4uPz9/XX48GFndgEAAAAA8s2pwOTh4aGaNWsqKSnJ3maz2ZSUlKR69erddFmr1aoyZcro+vXrWrlypVq2bGmfd+XKFbm5OZbi7u4um81mur6ffvpJFy9eVHBwsDO7AAAAAAD55vQleUOGDFGXLl1Uq1Yt1alTRwkJCcrIyFB8fLwkqXPnzipTpoz97NC2bdt0+vRpRUdH6/Tp05owYYJsNptGjBhhX2fz5s01ZcoUlS1bVlWrVtWuXbs0ffp0devWTZJ0+fJlTZw4Ua1bt1bp0qV15MgRjRgxQhUqVFBcXNydOA4AAAAAkIvTgaldu3Y6f/68xo0bp+TkZEVHRysxMdE+EMTJkycdzhZlZmZqzJgxOnr0qLy9vdW0aVMtXrxYfn5+9j6zZs3S2LFj1bdvX507d04hISHq1auXxo0bJ+nXs0179+7VokWLlJqaqpCQED3++ON6/vnnuU8JAAAAQIFx+jlMf1XOjLX+Z8ZzmFyP5zABAAD8tRXYc5gAAAAA4G5CYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBBYAIAAAAAEwQmAAAAADBxW4Fpzpw5CgsLk9VqVUxMjLZv327a99q1a5o0aZIiIiJktVoVFRWlxMREhz45OTkaO3asypcvLy8vL0VEROj555+XYRj2PoZhaNy4cQoODpaXl5diY2N16NCh2ykfAAAAAPLF6cC0fPlyDRkyROPHj9fOnTsVFRWluLg4nTt3Ls/+Y8aM0RtvvKFZs2Zp37596t27t1q1aqVdu3bZ+0ybNk1z587V7Nmz9eOPP2ratGl66aWXNGvWLHufl156Sa+99prmzZunbdu2qXjx4oqLi1NmZuZt7DYAAAAA3JrF+O1pnHyIiYlR7dq1NXv2bEmSzWZTaGioBgwYoJEjR+bqHxISotGjR6tfv372ttatW8vLy0tLliyRJD3xxBMKCgrS22+/nWcfwzAUEhKioUOHatiwYZKktLQ0BQUFaeHChWrfvv0t605PT5evr6/S0tLk4+PjzC7/qYSNXOvqEu56x19s5uoSAAAA8Ac4kw2cOsOUnZ2tHTt2KDY29n8rcHNTbGystmzZkucyWVlZslqtDm1eXl7atGmT/XX9+vWVlJSkgwcPSpL27NmjTZs2qUmTJpKkY8eOKTk52WG7vr6+iomJuel209PTHSYAAAAAcEYRZzpfuHBBOTk5CgoKcmgPCgrS/v3781wmLi5O06dPV8OGDRUREaGkpCStWrVKOTk59j4jR45Uenq6IiMj5e7urpycHE2ZMkUdO3aUJCUnJ9u38/vt3pj3e1OnTtXEiROd2T0AAAAAcFDgo+TNnDlTFStWVGRkpDw8PNS/f3/Fx8fLze1/m16xYoWWLl2qZcuWaefOnVq0aJFeeeUVLVq06La3O2rUKKWlpdmnU6dO3YndAQAAAHAXceoMk7+/v9zd3ZWSkuLQnpKSotKlS+e5TEBAgFavXq3MzExdvHhRISEhGjlypMLDw+19hg8frpEjR9rvRapWrZpOnDihqVOnqkuXLvZ1p6SkKDg42GG70dHReW7X09NTnp6ezuweAAAAADhw6gyTh4eHatasqaSkJHubzWZTUlKS6tWrd9NlrVarypQpo+vXr2vlypVq2bKlfd6VK1cczjhJkru7u2w2mySpfPnyKl26tMN209PTtW3btltuFwAAAABul1NnmCRpyJAh6tKli2rVqqU6deooISFBGRkZio+PlyR17txZZcqU0dSpUyVJ27Zt0+nTpxUdHa3Tp09rwoQJstlsGjFihH2dzZs315QpU1S2bFlVrVpVu3bt0vTp09WtWzdJksVi0aBBgzR58mRVrFhR5cuX19ixYxUSEqInn3zyDhwGAAAAAMjN6cDUrl07nT9/XuPGjVNycrKio6OVmJhoH5Dh5MmTDmeLMjMzNWbMGB09elTe3t5q2rSpFi9eLD8/P3ufWbNmaezYserbt6/OnTunkJAQ9erVS+PGjbP3GTFihDIyMvTMM88oNTVVDz74oBITE3ONwAcAAAAAd4rTz2H6q+I5TLhTeA4TAADAX1uBPYcJAAAAAO4mBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMHFbgWnOnDkKCwuT1WpVTEyMtm/fbtr32rVrmjRpkiIiImS1WhUVFaXExESHPmFhYbJYLLmmfv362fs8/PDDueb37t37dsoHAAAAgHxxOjAtX75cQ4YM0fjx47Vz505FRUUpLi5O586dy7P/mDFj9MYbb2jWrFnat2+fevfurVatWmnXrl32Pt9++63Onj1rn9avXy9JatOmjcO6evbs6dDvpZdecrZ8AAAAAMg3pwPT9OnT1bNnT8XHx6tKlSqaN2+eihUrpvnz5+fZf/HixXruuefUtGlThYeHq0+fPmratKleffVVe5+AgACVLl3aPn3yySeKiIhQo0aNHNZVrFgxh34+Pj7Olg8AAAAA+eZUYMrOztaOHTsUGxv7vxW4uSk2NlZbtmzJc5msrCxZrVaHNi8vL23atMl0G0uWLFG3bt1ksVgc5i1dulT+/v66//77NWrUKF25csW01qysLKWnpztMAAAAAOCMIs50vnDhgnJychQUFOTQHhQUpP379+e5TFxcnKZPn66GDRsqIiJCSUlJWrVqlXJycvLsv3r1aqWmpqpr164O7U8//bTKlSunkJAQ7d27V//617904MABrVq1Ks/1TJ06VRMnTnRm9wAAAADAgVOB6XbMnDlTPXv2VGRkpCwWiyIiIhQfH296Cd/bb7+tJk2aKCQkxKH9mWeesf97tWrVFBwcrEcffVRHjhxRRERErvWMGjVKQ4YMsb9OT09XaGjoHdorAAAAAHcDpy7J8/f3l7u7u1JSUhzaU1JSVLp06TyXCQgI0OrVq5WRkaETJ05o//798vb2Vnh4eK6+J06c0IYNG9SjR49b1hITEyNJOnz4cJ7zPT095ePj4zABAAAAgDOcCkweHh6qWbOmkpKS7G02m01JSUmqV6/eTZe1Wq0qU6aMrl+/rpUrV6ply5a5+ixYsECBgYFq1qzZLWvZvXu3JCk4ONiZXQAAAACAfHP6krwhQ4aoS5cuqlWrlurUqaOEhARlZGQoPj5ektS5c2eVKVNGU6dOlSRt27ZNp0+fVnR0tE6fPq0JEybIZrNpxIgRDuu12WxasGCBunTpoiJFHMs6cuSIli1bpqZNm6pUqVLau3evBg8erIYNG6p69eq3u+8AAAAAcFNOB6Z27drp/PnzGjdunJKTkxUdHa3ExET7QBAnT56Um9v/TlxlZmZqzJgxOnr0qLy9vdW0aVMtXrxYfn5+DuvdsGGDTp48qW7duuXapoeHhzZs2GAPZ6GhoWrdurXGjBnjbPkAAAAAkG8WwzAMVxdRGNLT0+Xr66u0tLS/9P1MYSPXurqEu97xF299ySgAAAD+vJzJBk4/uBYAAAAA7hYEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABMEJgAAAAAwQWACAAAAABNFXF0AAAAA4KywkWtdXcJd7/iLzVxdQqHgDBMAAAAAmCAwAQAAAICJ2wpMc+bMUVhYmKxWq2JiYrR9+3bTvteuXdOkSZMUEREhq9WqqKgoJSYmOvQJCwuTxWLJNfXr18/eJzMzU/369VOpUqXk7e2t1q1bKyUl5XbKBwAAAIB8cTowLV++XEOGDNH48eO1c+dORUVFKS4uTufOncuz/5gxY/TGG29o1qxZ2rdvn3r37q1WrVpp165d9j7ffvutzp49a5/Wr18vSWrTpo29z+DBg/Xxxx/r/fff11dffaUzZ87on//8p7PlAwAAAEC+WQzDMJxZICYmRrVr19bs2bMlSTabTaGhoRowYIBGjhyZq39ISIhGjx7tcLaodevW8vLy0pIlS/LcxqBBg/TJJ5/o0KFDslgsSktLU0BAgJYtW6annnpKkrR//35VrlxZW7ZsUd26dW9Zd3p6unx9fZWWliYfHx9ndvlPhRscXe9uucERAIA/M74Tud5f+TuRM9nAqTNM2dnZ2rFjh2JjY/+3Ajc3xcbGasuWLXkuk5WVJavV6tDm5eWlTZs2mW5jyZIl6tatmywWiyRpx44dunbtmsN2IyMjVbZs2ZtuNz093WECAAAAAGc4FZguXLignJwcBQUFObQHBQUpOTk5z2Xi4uI0ffp0HTp0SDabTevXr9eqVat09uzZPPuvXr1aqamp6tq1q70tOTlZHh4e8vPzy/d2p06dKl9fX/sUGhqa/x0FAAAAABXCKHkzZ85UxYoVFRkZKQ8PD/Xv31/x8fFyc8t702+//baaNGmikJCQP7TdUaNGKS0tzT6dOnXqD60PAAAAwN3HqcDk7+8vd3f3XKPTpaSkqHTp0nkuExAQoNWrVysjI0MnTpzQ/v375e3trfDw8Fx9T5w4oQ0bNqhHjx4O7aVLl1Z2drZSU1PzvV1PT0/5+Pg4TAAAAADgDKcCk4eHh2rWrKmkpCR7m81mU1JSkurVq3fTZa1Wq8qUKaPr169r5cqVatmyZa4+CxYsUGBgoJo1c7yBrGbNmipatKjDdg8cOKCTJ0/ecrsAAAAAcLuKOLvAkCFD1KVLF9WqVUt16tRRQkKCMjIyFB8fL0nq3LmzypQpo6lTp0qStm3bptOnTys6OlqnT5/WhAkTZLPZNGLECIf12mw2LViwQF26dFGRIo5l+fr6qnv37hoyZIjuuece+fj4aMCAAapXr16+RsgDAAAAgNvhdGBq166dzp8/r3Hjxik5OVnR0dFKTEy0DwRx8uRJh/uTMjMzNWbMGB09elTe3t5q2rSpFi9enGsAhw0bNujkyZPq1q1bntudMWOG3Nzc1Lp1a2VlZSkuLk6vv/66s+UDAAAAQL45/Rymvyqew4Q75a/8zAEAAP4u+E7ken/l70QF9hwmAAAAALibEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwMRtBaY5c+YoLCxMVqtVMTEx2r59u2nfa9euadKkSYqIiJDValVUVJQSExNz9Tt9+rQ6deqkUqVKycvLS9WqVdN3331nn9+1a1dZLBaHqXHjxrdTPgAAAADkSxFnF1i+fLmGDBmiefPmKSYmRgkJCYqLi9OBAwcUGBiYq/+YMWO0ZMkSvfXWW4qMjNS6devUqlUrffPNN6pRo4Yk6ZdfflGDBg30yCOP6LPPPlNAQIAOHTqkkiVLOqyrcePGWrBggf21p6ens+UDAAAAQL45HZimT5+unj17Kj4+XpI0b948rV27VvPnz9fIkSNz9V+8eLFGjx6tpk2bSpL69OmjDRs26NVXX9WSJUskSdOmTVNoaKhDGCpfvnyudXl6eqp06dLOlgwAAAAAt8WpS/Kys7O1Y8cOxcbG/m8Fbm6KjY3Vli1b8lwmKytLVqvVoc3Ly0ubNm2yv16zZo1q1aqlNm3aKDAwUDVq1NBbb72Va10bN25UYGCgKlWqpD59+ujixYumtWZlZSk9Pd1hAgAAAABnOBWYLly4oJycHAUFBTm0BwUFKTk5Oc9l4uLiNH36dB06dEg2m03r16/XqlWrdPbsWXufo0ePau7cuapYsaLWrVunPn36aODAgVq0aJG9T+PGjfXOO+8oKSlJ06ZN01dffaUmTZooJycnz+1OnTpVvr6+9ik0NNSZXQUAAAAA5y/Jc9bMmTPVs2dPRUZGymKxKCIiQvHx8Zo/f769j81mU61atfTCCy9IkmrUqKHvv/9e8+bNU5cuXSRJ7du3t/evVq2aqlevroiICG3cuFGPPvporu2OGjVKQ4YMsb9OT08nNAEAAABwilNnmPz9/eXu7q6UlBSH9pSUFNN7iwICArR69WplZGToxIkT2r9/v7y9vRUeHm7vExwcrCpVqjgsV7lyZZ08edK0lvDwcPn7++vw4cN5zvf09JSPj4/DBAAAAADOcCoweXh4qGbNmkpKSrK32Ww2JSUlqV69ejdd1mq1qkyZMrp+/bpWrlypli1b2uc1aNBABw4ccOh/8OBBlStXznR9P/30ky5evKjg4GBndgEAAAAA8s3p5zANGTJEb731lhYtWqQff/xRffr0UUZGhn3UvM6dO2vUqFH2/tu2bdOqVat09OhR/ec//1Hjxo1ls9k0YsQIe5/Bgwdr69ateuGFF3T48GEtW7ZMb775pvr16ydJunz5soYPH66tW7fq+PHjSkpKUsuWLVWhQgXFxcX90WMAAAAAAHly+h6mdu3a6fz58xo3bpySk5MVHR2txMRE+0AQJ0+elJvb/3JYZmamxowZo6NHj8rb21tNmzbV4sWL5efnZ+9Tu3Ztffjhhxo1apQmTZqk8uXLKyEhQR07dpQkubu7a+/evVq0aJFSU1MVEhKixx9/XM8//zzPYgIAAABQYCyGYRiuLqIwpKeny9fXV2lpaX/p+5nCRq51dQl3veMvNnN1CQAA3PX4TuR6f+XvRM5kA6cvyQMAAACAuwWBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABMEJgAAAAAwASBCQAAAABM3FZgmjNnjsLCwmS1WhUTE6Pt27eb9r127ZomTZqkiIgIWa1WRUVFKTExMVe/06dPq1OnTipVqpS8vLxUrVo1fffdd/b5hmFo3LhxCg4OlpeXl2JjY3Xo0KHbKR8AAAAA8sXpwLR8+XINGTJE48eP186dOxUVFaW4uDidO3cuz/5jxozRG2+8oVmzZmnfvn3q3bu3WrVqpV27dtn7/PLLL2rQoIGKFi2qzz77TPv27dOrr76qkiVL2vu89NJLeu211zRv3jxt27ZNxYsXV1xcnDIzM29jtwEAAADg1iyGYRjOLBATE6PatWtr9uzZkiSbzabQ0FANGDBAI0eOzNU/JCREo0ePVr9+/extrVu3lpeXl5YsWSJJGjlypDZv3qz//Oc/eW7TMAyFhIRo6NChGjZsmCQpLS1NQUFBWrhwodq3b3/LutPT0+Xr66u0tDT5+Pg4s8t/KmEj17q6hLve8RebuboEAADuenwncr2/8nciZ7KBU2eYsrOztWPHDsXGxv5vBW5uio2N1ZYtW/JcJisrS1ar1aHNy8tLmzZtsr9es2aNatWqpTZt2igwMFA1atTQW2+9ZZ9/7NgxJScnO2zX19dXMTExN91uenq6wwQAAAAAznAqMF24cEE5OTkKCgpyaA8KClJycnKey8TFxWn69Ok6dOiQbDab1q9fr1WrVuns2bP2PkePHtXcuXNVsWJFrVu3Tn369NHAgQO1aNEiSbKv25ntTp06Vb6+vvYpNDTUmV0FAAAAgIIfJW/mzJmqWLGiIiMj5eHhof79+ys+Pl5ubv/btM1m0wMPPKAXXnhBNWrU0DPPPKOePXtq3rx5t73dUaNGKS0tzT6dOnXqTuwOAAAAgLuIU4HJ399f7u7uSklJcWhPSUlR6dKl81wmICBAq1evVkZGhk6cOKH9+/fL29tb4eHh9j7BwcGqUqWKw3KVK1fWyZMnJcm+bme26+npKR8fH4cJAAAAAJzhVGDy8PBQzZo1lZSUZG+z2WxKSkpSvXr1brqs1WpVmTJldP36da1cuVItW7a0z2vQoIEOHDjg0P/gwYMqV66cJKl8+fIqXbq0w3bT09O1bdu2W24XAAAAAG5XEWcXGDJkiLp06aJatWqpTp06SkhIUEZGhuLj4yVJnTt3VpkyZTR16lRJ0rZt23T69GlFR0fr9OnTmjBhgmw2m0aMGGFf5+DBg1W/fn298MILatu2rbZv364333xTb775piTJYrFo0KBBmjx5sipWrKjy5ctr7NixCgkJ0ZNPPnkHDgMAAAAA5OZ0YGrXrp3Onz+vcePGKTk5WdHR0UpMTLQPyHDy5EmH+5MyMzM1ZswYHT16VN7e3mratKkWL14sPz8/e5/atWvrww8/1KhRozRp0iSVL19eCQkJ6tixo73PiBEjlJGRoWeeeUapqal68MEHlZiYmGsEPgAAAAC4U5x+DtNfFc9hwp3yV37mAAAAfxd8J3K9v/J3ogJ7DhMAAAAA3E0ITAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABgooirCwAAAM4JG7nW1SXc9Y6/2MzVJQAoJJxhAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMMGw4gD+chhS2bUYThkAcDfhDBMAAAAAmCAwAQAAAIAJAhMAAAAAmCAwAQAAAIAJAhMAAAAAmCAwAQAAAIAJAhMAAAAAmCAwAQAAAIAJAhMAAAAAmCAwAQAAAIAJAhMAAAAAmCAwAQAAAIAJAhMAAAAAmCAwAQAAAIAJAhMAAAAAmCAwAQAAAICJ2wpMc+bMUVhYmKxWq2JiYrR9+3bTvteuXdOkSZMUEREhq9WqqKgoJSYmOvSZMGGCLBaLwxQZGenQ5+GHH87Vp3fv3rdTPgAAAADkSxFnF1i+fLmGDBmiefPmKSYmRgkJCYqLi9OBAwcUGBiYq/+YMWO0ZMkSvfXWW4qMjNS6devUqlUrffPNN6pRo4a9X9WqVbVhw4b/FVYkd2k9e/bUpEmT7K+LFSvmbPkAAAAAkG9On2GaPn26evbsqfj4eFWpUkXz5s1TsWLFNH/+/Dz7L168WM8995yaNm2q8PBw9enTR02bNtWrr77q0K9IkSIqXbq0ffL398+1rmLFijn08fHxcbZ8AAAAAMg3pwJTdna2duzYodjY2P+twM1NsbGx2rJlS57LZGVlyWq1OrR5eXlp06ZNDm2HDh1SSEiIwsPD1bFjR508eTLXupYuXSp/f3/df//9GjVqlK5cuWJaa1ZWltLT0x0mAAAAAHCGU4HpwoULysnJUVBQkEN7UFCQkpOT81wmLi5O06dP16FDh2Sz2bR+/XqtWrVKZ8+etfeJiYnRwoULlZiYqLlz5+rYsWN66KGHdOnSJXufp59+WkuWLNGXX36pUaNGafHixerUqZNprVOnTpWvr699Cg0NdWZXAQAAAMD5e5icNXPmTPXs2VORkZGyWCyKiIhQfHy8wyV8TZo0sf979erVFRMTo3LlymnFihXq3r27JOmZZ56x96lWrZqCg4P16KOP6siRI4qIiMi13VGjRmnIkCH21+np6YQmAAAAAE5x6gyTv7+/3N3dlZKS4tCekpKi0qVL57lMQECAVq9erYyMDJ04cUL79++Xt7e3wsPDTbfj5+en++67T4cPHzbtExMTI0mmfTw9PeXj4+MwAQAAAIAznApMHh4eqlmzppKSkuxtNptNSUlJqlev3k2XtVqtKlOmjK5fv66VK1eqZcuWpn0vX76sI0eOKDg42LTP7t27JemmfQAAAADgj3D6krwhQ4aoS5cuqlWrlurUqaOEhARlZGQoPj5ektS5c2eVKVNGU6dOlSRt27ZNp0+fVnR0tE6fPq0JEybIZrNpxIgR9nUOGzZMzZs3V7ly5XTmzBmNHz9e7u7u6tChgyTpyJEjWrZsmZo2bapSpUpp7969Gjx4sBo2bKjq1avfieMAAAAAALk4HZjatWun8+fPa9y4cUpOTlZ0dLQSExPtA0GcPHlSbm7/O3GVmZmpMWPG6OjRo/L29lbTpk21ePFi+fn52fv89NNP6tChgy5evKiAgAA9+OCD2rp1qwICAiT9emZrw4YN9nAWGhqq1q1ba8yYMX9w9wEAAADA3G0N+tC/f3/1798/z3kbN250eN2oUSPt27fvput77733bjo/NDRUX331lVM1AgAAAMAf5fSDawEAAADgbkFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAAAAAMFHE1QUUFsMwJEnp6ekuruSPsWVdcXUJd72/+nvo74DPgWvxGXA9PgOux+fA9fgcuN5f+XNwo/YbGeFmLEZ+ev0N/PTTTwoNDXV1GQAAAAD+JE6dOqV77733pn3umsBks9l05swZlShRQhaLxdXl3JXS09MVGhqqU6dOycfHx9XlAC7B5wDgcwDwGXA9wzB06dIlhYSEyM3t5ncp3TWX5Lm5ud0yPaJw+Pj48B8H3PX4HAB8DgA+A67l6+ubr34M+gAAAAAAJghMAAAAAGCCwIRC4+npqfHjx8vT09PVpQAuw+cA4HMA8Bn4a7lrBn0AAAAAAGdxhgkAAAAATBCYAAAAAMAEgQkAAAAATBCYAAAAAMAEgQkAAAAATBCYAAAAAMBEEVcXgL+fkydP5qtf2bJlC7gSAMCfwcmTJxUaGiqLxeLQbhiGTp06xf8PcFf4xz/+oVWrVsnPz8+hPT09XU8++aS++OIL1xSGW+I5TLjj3Nzccv1PUfr1f4w32i0Wi65fv17YpQEuER4erm+//ValSpVyaE9NTdUDDzygo0ePuqgyoHC4u7vr7NmzCgwMdGi/ePGiAgMDlZOT46LKgMLj5uam5OTkXJ+Dc+fOqUyZMrp27ZqLKsOtcIYJd9yuXbvybDcMQ++9955ee+01eXt7F3JVgOscP348zy+EWVlZOn36tAsqAgrXb38w+63Lly/LarW6oCKg8Ozdu9f+7/v27VNycrL9dU5OjhITE1WmTBlXlIZ8IjDhjouKisrVtmHDBo0cOVIHDx7UiBEjNHToUBdUBhSuNWvW2P993bp18vX1tb/OyclRUlKSwsLCXFAZUDiGDBki6derCsaOHatixYrZ5+Xk5Gjbtm2Kjo52UXVA4YiOjpbFYpHFYtE//vGPXPO9vLw0a9YsF1SG/CIwoUDt3LlT//rXv/Sf//xHPXr00KeffprrVDTwd/Xkk09K+vXLYpcuXRzmFS1aVGFhYXr11VddUBlQOG5ccWAYhv773//Kw8PDPs/Dw0NRUVEaNmyYq8oDCsWxY8dkGIbCw8O1fft2BQQE2Od5eHgoMDBQ7u7uLqwQt8I9TCgQR44c0XPPPaeVK1eqbdu2mjx5ssLDw11dFuAS5cuX17fffit/f39XlwK4RHx8vGbOnCkfHx9XlwIATmNYcdxxffv2VZUqVZSWlqbvvvtOy5YtIyzhrnbs2LFcYSk1NdU1xQAusGDBAoewlJ6ertWrV2v//v0urAooXIsWLdLatWvtr0eMGCE/Pz/Vr19fJ06ccGFluBXOMOGOc3Nzk9VqVWRk5E377dy5s5AqAlxr2rRpCgsLU7t27SRJbdq00cqVKxUcHKxPP/00z/v+gL+Ttm3bqmHDhurfv7+uXr2qqKgoHT9+3D4YUOvWrV1dIlDgKlWqpLlz5+of//iHtmzZokcffVQJCQn65JNPVKRIEa1atcrVJcIE9zDhjhs3blyeoyEBd6t58+Zp6dKlkqT169drw4YNSkxM1IoVKzR8+HB9/vnnLq4QKFhff/21Ro8eLUn68MMPZRiGUlNTtWjRIk2ePJnAhLvCqVOnVKFCBUnS6tWr9dRTT+mZZ55RgwYN9PDDD7u2ONwUgQl33IQJE1xdAvCnkpycrNDQUEnSJ598orZt2+rxxx9XWFiYYmJiXFwdUPDS0tJ0zz33SJISExPVunVrFStWTM2aNdPw4cNdXB1QOLy9vXXx4kWVLVtWn3/+uX0USavVqqtXr7q4OtwM9zDhjvviiy94KC3wGyVLltSpU6ck/fplMTY2VtKvI4fxwE7cDUJDQ7VlyxZlZGQoMTFRjz/+uCTpl19+4TlMuGs89thj6tGjh3r06KGDBw+qadOmkqQffviBR0z8yRGYcMc99thj+vnnn+2v69aty8M5cVf75z//qaefflqPPfaYLl68qCZNmkj6dcjlG5dnAH9ngwYNUseOHXXvvfcqJCTEfvnR119/rWrVqrm2OKCQzJkzR/Xq1dP58+e1cuVKlSpVSpK0Y8cOdejQwcXV4WYY9AF3nJubm5KTk+3PWypRooT27NnDSHm4a127dk0zZ87UqVOn1LVrV9WoUUOSNGPGDJUoUUI9evRwcYVAwfvuu+906tQpPfbYY/L29pYkrV27Vn5+fmrQoIGLqwMAcwQm3HEEJgCAmRtfOxgcCHej1NRUvf322/rxxx8lSVWrVlW3bt3k6+vr4spwM1yShzvOYrE4/I/w96+Bu9HixYv14IMPKiQkxP68jYSEBH300UcurgwoHO+8846qVasmLy8veXl5qXr16lq8eLGrywIKzXfffaeIiAjNmDFDP//8s37++WdNnz5dERERPGrlT45R8nDHGYahRx99VEWK/Pr2unLlipo3by4PDw+HfvzHAXeLuXPnaty4cRo0aJCmTJliH+jBz89PCQkJatmypYsrBArW9OnTNXbsWPXv399++d2mTZvUu3dvXbhwQYMHD3ZxhUDBGzx4sFq0aKG33nrL/h3p+vXr6tGjhwYNGqSvv/7axRXCDJfk4Y6bOHFivvqNHz++gCsB/hyqVKmiF154QU8++aTDJarff/+9Hn74YV24cMHVJQIFqnz58po4caI6d+7s0L5o0SJNmDBBx44dc1FlQOHx8vLSrl27FBkZ6dC+b98+1apVS1euXHFRZbgVzjDhjiMIAY6OHTtmH+jhtzw9PZWRkeGCioDCdfbsWdWvXz9Xe/369XX27FkXVAQUPh8fH508eTJXYDp16pRKlCjhoqqQH9zDhAKxdetWjR49WsOHD1diYqKrywFcqnz58tq9e3eu9sTERFWuXLnwCwIKWYUKFbRixYpc7cuXL1fFihVdUBFQ+Nq1a6fu3btr+fLlOnXqlE6dOqX33ntPPXr0YFjxPznOMOGO++CDD9SuXTt5eXmpaNGimj59uqZNm6Zhw4a5ujTAJYYMGaJ+/fopMzNThmFo+/btevfddzV16lT9+9//dnV5QIGbOHGi2rVrp6+//tp+D9PmzZuVlJSUZ5AC/o5eeeUVWSwWde7cWdevX5ckFS1aVH369NGLL77o4upwM9zDhDuuZs2aql27tubMmSN3d3dNnTpVL7/8ssPDbIG7zdKlSzVhwgQdOXJEkhQSEqKJEyeqe/fuLq4MKBw7duzQjBkz7MMpV65cWUOHDs3zclXg7+zKlSv2/xdERESoWLFiLq4It0Jgwh3n7e2t3bt3q0KFCpKk7OxsFS9eXKdPn7Y/mwm4W1y/fl3Lli1TXFycgoKCdOXKFV2+fJnPAgDcxX766SdJ0r333uviSpAf3MOEO+7KlSvy8fGxv/bw8JDVatXly5ddWBXgGkWKFFHv3r2VmZkpSSpWrBhhCXelnJwcrVy5UpMnT9bkyZP14Ycf2ofYB+4GNptNkyZNkq+vr8qVK6dy5crJz89Pzz//vGw2m6vLw01wDxMKxL///W95e3vbX1+/fl0LFy6Uv7+/vW3gwIGuKA0odHXq1NGuXbtUrlw5V5cCuMThw4fVrFkz/fTTT6pUqZIkaerUqQoNDdXatWsVERHh4gqBgjd69Gi9/fbbevHFFx2eRzZhwgRlZmZqypQpLq4QZrgkD3dcWFiYLBbLTftYLBYdPXq0kCoCXGvFihUaNWqUBg8erJo1a6p48eIO86tXr+6iyoDC0bRpUxmGoaVLl+qee+6RJF28eFGdOnWSm5ub1q5d6+IKgYIXEhKiefPmqUWLFg7tH330kfr27avTp0+7qDLcCoEJAAqYm1vuq58tFosMw5DFYuGyJPztFS9eXFu3blW1atUc2vfs2aMGDRpwyTbuClarVXv37tV9993n0H7gwAFFR0fr6tWrLqoMt8IleQBQwI4dO+bqEgCX8vT01KVLl3K1X758WR4eHi6oCCh8UVFRmj17tl577TWH9tmzZysqKspFVSE/OMOEApWUlJRrGNlBgwYpNjbWxZUBAApL586dtXPnTr399tuqU6eOJGnbtm3q2bOnatasqYULF7q2QKAQfPXVV2rWrJnKli2revXqSZK2bNmiU6dO6dNPP9VDDz3k4gphhsCEAvP666/r2Wef1VNPPWX/D8PWrVv1wQcfaMaMGerXr5+LKwQKz5EjR5SQkGD/8aBKlSp69tlnudkdd4XU1FR16dJFH3/8sYoWLSrp18GAWrRooYULF8rX19fFFQKF48yZM5ozZ472798v6dcfkvv27auQkBAXV4abITChwNx7770aOXKk+vfv79A+Z84cvfDCC9zciLvGunXr1KJFC0VHR9tHRtq8ebP27Nmjjz/+WI899piLKwQKx+HDhx2uOLjxvD4A+DMjMKHA/P4BtjccOnRINWrU4CZf3DVq1KihuLg4vfjiiw7tI0eO1Oeff66dO3e6qDIAgCtkZGRo+fLlunr1qh5//HFVrFjR1SXhJnhwLQpMixYt9OGHH+Zq/+ijj/TEE0+4oCLANX788Ud17949V3u3bt20b98+F1QEFJ5Dhw5p5cqV9sFP1q5dq4YNG6p27dqaMmWK+N0Wf3cnT55Uo0aNVKJECT322GM6efKkHnjgAfXo0UMDBgxQdHS0vv76a1eXiZtglDzcUb8d+aVKlSqaMmWKNm7c6HAP0+bNmzV06FBXlQgUuoCAAO3evTvXL4i7d+9WYGCgi6oCCt6HH36otm3bys3NTRaLRW+++aZ69eqlhx9+WD4+PpowYYKKFCmif/3rX64uFSgww4YNU3Z2tubNm6cVK1YoLi5OFStW1Ndffy03Nzf16dNHEyZM0BdffOHqUmGCS/JwR5UvXz5f/XhwLe4mkyZN0owZMzRy5EjVr19f0q/3ME2bNk1DhgzR2LFjXVwhUDBq1aqluLg4TZ48WQsXLlS/fv30wgsvaNCgQZKkN99802EkVeDvqHTp0lqzZo3q1Kmjn3/+Wf7+/tq8ebP9x+Q9e/bo0Ucf1YULF1xcKcwQmACggBmGoYSEBL366qs6c+aMpF+f+D58+HANHDhQFovFxRUCBaNEiRLavXu3IiIiZLPZ5OHhod27d+v++++XJB0/flxVqlTRlStXXFwpUHDc3Nx09uxZBQUFSfr1Hu+9e/cqPDxckpSSkqKQkBAeYv4nxiV5AFDALBaLBg8erMGDB9sf3lmiRAkXVwUUvIyMDPt73c3NTV5eXipWrJh9vpeXl7KyslxVHlBofvvDGD+S/fUQmFCgfvrpJ61Zs0YnT55Udna2w7zp06e7qCqgcDRs2FBr1qyRn5+fJGnNmjV67LHH5OXl5drCgEJisVhyfVHkyyLuRuPGjbP/WJCdna0pU6bYnz/GGdY/Py7JQ4FJSkpSixYtFB4erv379+v+++/X8ePHZRiGHnjgAW5uxN+em5ubkpOT7QM7+Pj4aPfu3fbLMIC/Ozc3N/n6+tpDUmpqqnx8fOTm9usgvYZhKD09nUuR8Lf28MMP5+uHgi+//LIQqsHt4AwTCsyoUaM0bNgwTZw4USVKlNDKlSsVGBiojh07qnHjxq4uDyh0/D6Fu82CBQtcXQLgchs3bnR1CfiDOMOEAvPbm31LliypTZs2qWrVqtqzZ49atmyp48ePu7pEoED9/gxTiRIltGfPHs4wAcBdaNKkSRo2bJjDfXySdPXqVb388ssaN26ciyrDrXCGCQWmePHi9vuWgoODdeTIEVWtWlWSGDoTd41169bZr1O32WxKSkrS999/79CnRYsWrigNKHSXLl1yONPq5uYmb29vF1YEFJ6JEyeqd+/euQLTlStXNHHiRALTnxiBCXfcpEmTNHToUNWtW1ebNm1S5cqV1bRpUw0dOlT//e9/tWrVKtWtW9fVZQKFokuXLg6ve/Xq5fDaYrFw/wb+tnbv3q3nnntOn376qaRfh9P/7Q3uFotFW7ZsUe3atV1VIlBoDMPI816mPXv26J577nFBRcgvLsnDHefu7q6zZ8/q8uXLunz5sqpXr66MjAwNHTpU33zzjSpWrKjp06erXLlyri4VAFCAunfvroiICD333HOSfr0s9Y033lCZMmVkGIbmz58vwzC0ePFiF1cKFJySJUvKYrEoLS1NPj4+DqEpJydHly9fVu/evTVnzhwXVombITDhjvv9fRsAgLtT5cqVtWzZMtWoUUNS7vv4tm3bprZt2+rEiROuLBMoUIsWLZJhGOrWrZsSEhLsl2lLkoeHh8LCwlSvXj0XVohb4ZI8FAieswE4OnPmjDZt2qRz587JZrM5zBs4cKCLqgIK1okTJxQQEGB/PWnSJPn7+9tfBwcHKyUlxRWlAYXmxqXZ5cuXV/369VW0aFEXVwRncYYJd9zvn7th5ueffy6kigDXWrhwoXr16iUPDw+VKlUq14M8jx496sLqgIJzzz336OOPP1aDBg3ynL9582Y1b96c/x/grpOZmWkfGOsGHx8fF1WDW+EMEwrExIkTHU45A3ezsWPHaty4cRo1apT9gZ3A3aBGjRpavXq1aWBatWqV/XI94O/uypUrGjFihFasWKGLFy/mms8AQH9eBCYUiPbt23MPE/D/XblyRe3btycs4a7Tt29ftW/fXmFhYerTp4/9M5CTk6PXX39ds2bN0rJly1xcJVA4hg8fri+//FJz587V//3f/2nOnDk6ffq03njjDb344ouuLg83wSV5uONujJJHYAJ+NWLECN1zzz0aOXKkq0sBCt2//vUvvfzyyypRooR9sIejR4/q8uXLGjJkiF5++WUXVwgUjrJly+qdd97Rww8/LB8fH+3cuVMVKlTQ4sWL9e6779qH38efD4EJdxyj5AGOcnJy9MQTT+jq1auqVq1arht+p0+f7qLKgMKxdetWvfvuuzp06JAkqWLFiurQoQPP5MNdxdvbW/v27VPZsmV17733atWqVapTp46OHTumatWq6fLly64uESa4JA933O9HAAPudlOnTtW6detUqVIlSco16APwdzV27FiNHz9edevWzTMcnTx5Ut27d9f69etdUB1QuMLDw3Xs2DGVLVtWkZGRWrFiherUqaOPP/5Yfn5+ri4PN8EZJgAoYCVLltSMGTPUtWtXV5cCFKqyZcuqVKlSWrx4se6//36HeW+88YaGDx+uBg0a6LPPPnNRhUDhmTFjhtzd3TVw4EBt2LBBzZs3l2EYys7O1owZM/Tss8+6ukSYIDABQAErXbq0/vOf/6hixYquLgUoVOnp6erfv79WrFih8ePH61//+pd++ukndevWTd9++61efvllPfPMM64uE3CJEydOaMeOHapYsaKqVavm6nJwEwzZBAAF7Nlnn9WsWbNcXQZQ6Hx8fPTOO+9o+fLlmjlzph544AFVq1ZNFotFe/fuJSzhrvDFF1+oSpUqSk9Pd2gvV66cHn30UbVv317/+c9/XFQd8oMzTABQwFq1aqUvvvhCpUqVUtWqVXMN+rBq1SoXVQYUjpSUFHXq1ElJSUkqXry4PvnkEzVq1MjVZQGFokWLFnrkkUc0ePDgPOe/9tpr+vLLL/Xhhx8WcmXIL84wAUAB8/Pz0z//+U81atRI/v7+8vX1dZiAv7N3331XVapUkc1m048//qg+ffro8ccf1+DBg5WZmenq8oACt2fPHjVu3Nh0/uOPP64dO3YUYkVwFmeYAABAgWjdurXWrVunqVOnasCAAfb2b775RvHx8ZKkhQsXql69eq4qEShwVqtV33//vSpUqJDn/MOHD6tatWq6evVqIVeG/GJYcQAoJOfPn9eBAwckSZUqVVJAQICLKwIKVnJysnbt2pVrwJP69etr9+7dGjlypBo1aqTs7GwXVQgUvDJlytw0MO3du1fBwcGFXBWcwRkmAChgGRkZGjBggN555x37c8rc3d3VuXNnzZo1S8WKFXNxhUDBsNlscnO7+dX/X3/9tRo2bFhIFQGFb8CAAdq4caO+/fZbWa1Wh3lXr15VnTp19Mgjj+i1115zUYW4FQITABSwXr16acOGDZo9e7YaNGggSdq0aZMGDhyoxx57THPnznVxhQCAgpKSkqIHHnhA7u7u6t+/v/0h5vv379ecOXOUk5OjnTt3KigoyMWVwgyBCQAKmL+/vz744AM9/PDDDu1ffvml2rZtq/Pnz7umMABAoThx4oT69OmjdevW6cZXb4vFori4OM2ZM0fly5d3cYW4Ge5hAoACduXKlTx/OQwMDNSVK1dcUBEAoDCVK1dOn376qX755RcdPnxYhmGoYsWKKlmypKtLQz5whgkACtijjz6qUqVK6Z133rFfv3716lV16dJFP//8szZs2ODiCgEAgBkCEwAUsO+//15xcXHKyspSVFSUpF+fy2G1WrVu3TpVrVrVxRUCAAAzBCYAKARXrlzR0qVLtX//fklS5cqV1bFjR3l5ebm4MgAAcDMEJgAAAAAwwaAPAFAA1qxZk+++LVq0KMBKAADAH8EZJgAoAL9/WKfFYtHv/3NrsVgkSTk5OYVWFwAAcM7NH78NALgtNpvNPn3++eeKjo7WZ599ptTUVKWmpuqzzz7TAw88oMTERFeXCgAAboIzTABQwO6//37NmzdPDz74oEP7f/7zHz3zzDP68ccfXVQZAAC4Fc4wAUABO3LkiPz8/HK1+/r66vjx44VeDwAAyD/OMAFAAWvYsKGsVqsWL16soKAgSVJKSoo6d+6szMxMffXVVy6uEAAAmCEwAUABO3z4sFq1aqWDBw8qNDRUknTq1ClVrFhRq1evVoUKFVxcIQAAMENgAoBCYBiG1q9f7/Dg2tjYWPtIeQAA4M+JwAQAAAAAJnhwLQAUgqSkJCUlJencuXOy2WwO8+bPn++iqgAAwK0QmACggE2cOFGTJk1SrVq1FBwczGV4AAD8hXBJHgAUsODgYL300kv6v//7P1eXAgAAnMRzmACggGVnZ6t+/fquLgMAANwGAhMAFLAePXpo2bJlri4DAADcBu5hAoAClpmZqTfffFMbNmxQ9erVVbRoUYf506dPd1FlAADgVriHCQAK2COPPGI6z2Kx6IsvvijEagAAgDMITAAAAABggnuYAAAAAMAE9zABQCH47rvvtGLFCp08eVLZ2dkO81atWuWiqgAAwK1whgkACth7772n+vXr68cff9SHH36oa9eu6YcfftAXX3whX19fV5cHAABugsAEAAXshRde0IwZM/Txxx/Lw8NDM2fO1P79+9W2bVuVLVvW1eUBAICbIDABQAE7cuSImjVrJkny8PBQRkaGLBaLBg8erDfffNPF1QEAgJshMAFAAStZsqQuXbokSSpTpoy+//57SVJqaqquXLniytIAAMAtMOgDABSwhg0bav369apWrZratGmjZ599Vl988YXWr1+vf/zjH64uDwAA3ATPYQKAAvbzzz8rMzNTISEhstlseumll/TNN9+oYsWKGjZsmIKDg11dIgAAMEFgAgAXyMzM1Jw5c/Tyyy8rOTnZ1eUAAAAT3MMEAAUkKytLo0aNUq1atVS/fn2tXr1akrRgwQJFRERo5syZGjx4sGuLBAAAN8UZJgAoIP/617/0xhtvKDY2Vt98843Onz+v+Ph4bd26Vc8995zatGkjd3d3V5cJAABugkEfAKCAvP/++3rnnXfUokULff/996pevbquX7+uPXv2yGKxuLo8AACQD5xhAoAC4uHhoWPHjqlMmTKSJC8vL23fvl3VqlVzcWUAACC/uIcJAApITk6OPDw87K+LFCkib29vF1YEAACcxSV5AFBADMNQ165d5enpKenXkfF69+6t4sWLO/RbtWqVK8oDAAD5QGACgALSpUsXh9edOnVyUSUAAOB2cQ8TAAAAAJjgHiYAAAAAMEFgAgAAAAATBCYAAAAAMEFgAgAAAAATBCYAwF1v48aNslgsSk1NzfcyYWFhSkhIKLCaAAB/DgQmAMCfXteuXWWxWNS7d+9c8/r16yeLxaKuXbsWfmEAgL89AhMA4C8hNDRU7733nq5evWpvy8zM1LJly1S2bFkXVgYA+DsjMAEA/hIeeOABhYaGatWqVfa2VatWqWzZsqpRo4a9LSsrSwMHDlRgYKCsVqsefPBBffvttw7r+vTTT3XffffJy8tLjzzyiI4fP55re5s2bdJDDz0kLy8vhYaGauDAgcrIyCiw/QMA/DkRmAAAfxndunXTggUL7K/nz5+v+Ph4hz4jRozQypUrtWjRIu3cuVMVKlRQXFycfv75Z0nSqVOn9M9//lPNmzfX7t271aNHD40cOdJhHUeOHFHjxo3VunVr7d27V8uXL9emTZvUv3//gt9JAMCfCoEJAPCX0alTJ23atEknTpzQiRMntHnzZnXq1Mk+PyMjQ3PnztXLL7+sJk2aqEqVKnrrrbfk5eWlt99+W5I0d+5cRURE6NVXX1WlSpXUsWPHXPc/TZ06VR07dtSgQYNUsWJF1a9fX6+99preeecdZWZmFuYuAwBcrIirCwAAIL8CAgLUrFkzLVy4UIZhqFmzZvL397fPP3LkiK5du6YGDRrY24oWLao6deroxx9/lCT9+OOPiomJcVhvvXr1HF7v2bNHe/fu1dKlS+1thmHIZrPp2LFjqly5ckHsHgDgT4jABAD4S+nWrZv90rg5c+YUyDYuX76sXr16aeDAgbnmMcAEANxdCEwAgL+Uxo0bKzs7WxaLRXFxcQ7zIiIi5OHhoc2bN6tcuXKSpGvXrunbb7/VoEGDJEmVK1fWmjVrHJbbunWrw+sHHnhA+/btU4UKFQpuRwAAfwncwwQA+Etxd3fXjz/+qH379snd3d1hXvHixdWnTx8NHz5ciYmJ2rdvn3r27KkrV66oe/fukqTevXvr0KFDGj58uA4cOKBly5Zp4cKFDuv517/+pW+++Ub9+/fX7t27dejQIX300UcM+gAAdyECEwDgL8fHx0c+Pj55znvxxRfVunVr/d///Z8eeOABHT58WOvWrVPJkiUl/XpJ3cqVK7V69WpFRUVp3rx5euGFFxzWUb16dX311Vc6ePCgHnroIdWoUUPjxo1TSEhIge8bAODPxWIYhuHqIgAAAADgz4gzTAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABggsAEAAAAACYITAAAAABg4v8BTsaQW22N+HgAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Compare different machine learning models by training each one multiple times\n",
+    "# on different parts of the data and averaging their performance scores for a\n",
+    "# more reliable performance estimate\n",
+    "\n",
+    "# Encode target labels to classes for baselines\n",
+    "le = LabelEncoder()\n",
+    "y = le.fit_transform(y)\n",
+    "\n",
+    "# Define models\n",
+    "models = [\n",
+    "    (\"TabPFN\", TabPFNClassifier(random_state=42)),\n",
+    "    (\n",
+    "        \"RandomForest\",\n",
+    "        make_pipeline(\n",
+    "            column_transformer,  # string data needs to be encoded for model\n",
+    "            RandomForestClassifier(random_state=42),\n",
+    "        ),\n",
+    "    ),\n",
+    "    (\n",
+    "        \"XGBoost\",\n",
+    "        make_pipeline(\n",
+    "            column_transformer,  # string data needs to be encoded for model\n",
+    "            XGBClassifier(random_state=42),\n",
+    "        ),\n",
+    "    ),\n",
+    "    (\n",
+    "        \"CatBoost\",\n",
+    "        make_pipeline(\n",
+    "            column_transformer,  # string data needs to be encoded for model\n",
+    "            CatBoostClassifier(random_state=42, verbose=0),\n",
+    "        ),\n",
+    "    ),\n",
+    "]\n",
+    "\n",
+    "# Calculate scores\n",
+    "n_splits = 3\n",
+    "cv = StratifiedKFold(n_splits=n_splits, random_state=42, shuffle=True)\n",
+    "scoring = \"roc_auc_ovr\" if len(np.unique(y)) > 2 else \"roc_auc\"\n",
+    "scores = {\n",
+    "    name: cross_val_score(model, X, y, cv=cv, scoring=scoring, n_jobs=1, verbose=1)\n",
+    "    for name, model in models\n",
+    "}\n",
+    "\n",
+    "# Plot results\n",
+    "df = pd.DataFrame(\n",
+    "    [(k, v.mean()) for (k, v) in scores.items()], columns=[\"Model\", \"ROC AUC\"]\n",
+    ")\n",
+    "ax = df.plot(x=\"Model\", y=\"ROC AUC\", kind=\"bar\", figsize=(10, 6))\n",
+    "ax.set_ylim(df[\"ROC AUC\"].min() * 0.995, min(1.0, df[\"ROC AUC\"].max() * 1.005))\n",
+    "ax.set_title(f\"Model Comparison - {n_splits}-fold Cross-validation\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ipG2Cpb7Jrc7"
+   },
+   "source": [
+    "# Regression with TabPFN <a name=\"regression\"></a>\n",
+    "\n",
+    "Next, we'll explore how to use TabPFN for regression tasks. We will use the Boston Housing dataset, where the goal is to predict the median value of owner-occupied homes.\n",
+    "\n",
+    "We will measure performance using the [Root Mean Squared Error](https://scikit-learn.org/1.5/modules/generated/sklearn.metrics.root_mean_squared_error.html), and again, we will compare TabPFN with other popular regression models."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Qzrj9m0fI32f"
+   },
+   "source": [
+    "### **Loading Boston Housing Dataset**\n",
+    "\n",
+    "### **Dataset Overview**\n",
+    "\n",
+    "-   **Objective:** Predict the **median value of owner-occupied homes** in the Boston area based on various socioeconomic and environmental attributes.\n",
+    "    \n",
+    "-   **Number of Instances:** 506\n",
+    "    \n",
+    "-   **Number of Attributes:** 14 (13 numeric features + 1 target variable)\n",
+    "    \n",
+    "-   **Target Variable:** `MEDV` — Median value of owner-occupied homes (in $1000s)\n",
+    "    \n",
+    "-   **Class Type:** Numeric\n",
+    "    \n",
+    "-   **Class Index:** Last\n",
+    "    \n",
+    "\n",
+    "* * *\n",
+    "\n",
+    "<details>\n",
+    "\n",
+    "\n",
+    "**Citation:**\n",
+    "\n",
+    "> Harrison, D. and Rubinfeld, D.L. (1978).  \n",
+    "> _Hedonic prices and the demand for clean air._  \n",
+    "> _Journal of Environmental Economics & Management_, 5, 81–102.  \n",
+    "> Used in Belsley, Kuh & Welsch, _Regression Diagnostics: Identifying Influential Data and Sources of Collinearity_, Wiley, 1980.\n",
+    "\n",
+    "\n",
+    "### **Attribute Information**\n",
+    "\n",
+    "**Feature**\n",
+    "\n",
+    "**Description**\n",
+    "\n",
+    "`CRIM`\n",
+    "\n",
+    "Per capita crime rate by town\n",
+    "\n",
+    "`ZN`\n",
+    "\n",
+    "Proportion of residential land zoned for lots over 25,000 sq.ft.\n",
+    "\n",
+    "`INDUS`\n",
+    "\n",
+    "Proportion of non-retail business acres per town\n",
+    "\n",
+    "`CHAS`\n",
+    "\n",
+    "Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)\n",
+    "\n",
+    "`NOX`\n",
+    "\n",
+    "Nitric oxides concentration (parts per 10 million)\n",
+    "\n",
+    "`RM`\n",
+    "\n",
+    "Average number of rooms per dwelling\n",
+    "\n",
+    "`AGE`\n",
+    "\n",
+    "Proportion of owner-occupied units built prior to 1940\n",
+    "\n",
+    "`DIS`\n",
+    "\n",
+    "Weighted distances to five Boston employment centres\n",
+    "\n",
+    "`RAD`\n",
+    "\n",
+    "Index of accessibility to radial highways\n",
+    "\n",
+    "`TAX`\n",
+    "\n",
+    "Full-value property-tax rate per $10,000\n",
+    "\n",
+    "`PTRATIO`\n",
+    "\n",
+    "Pupil–teacher ratio by town\n",
+    "\n",
+    "`B`\n",
+    "\n",
+    "1000(Bk − 0.63)², where Bk is the proportion of Blacks by town\n",
+    "\n",
+    "`LSTAT`\n",
+    "\n",
+    "Percentage of lower status population\n",
+    "\n",
+    "`MEDV`\n",
+    "\n",
+    "Median value of owner-occupied homes (in $1000s)\n",
+    "\n",
+    "</details>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 240
     },
+    "id": "4vbEBAKKIRaM",
+    "outputId": "d55a593d-d65f-4fdf-ac5c-6d9d32be2bf9"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "6RYILEoPXaMZ"
-      },
-      "source": [
-        "### Shapley Values\n",
-        "\n",
-        "Next, we'll use SHAP to understand our model's predictions. SHAP values break down a prediction to show the contribution of each feature, helping us see which factors are most influential for a given data point.\n"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipython-input-378995386.py:7: FutureWarning: The 'delim_whitespace' keyword in pd.read_csv is deprecated and will be removed in a future version. Use ``sep='\\s+'`` instead\n",
+      "  df_boston = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data\",\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 16,
-      "metadata": {
-        "id": "8CJtLwWUe-KV",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "outputId": "d743c96e-c69b-401d-8571-9ceb8e9ba2b9"
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "summary": "{\n  \"name\": \"display(X\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"CRIM\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.02277820712874479,\n        \"min\": 0.00632,\n        \"max\": 0.06905,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.02731,\n          0.06905,\n          0.02729\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ZN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8.049844718999244,\n        \"min\": 0.0,\n        \"max\": 18.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0.0,\n          18.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDUS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.6551591289412393,\n        \"min\": 2.18,\n        \"max\": 7.07,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          2.31,\n          7.07\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CHAS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"NOX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.03376832835661252,\n        \"min\": 0.458,\n        \"max\": 0.538,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.538\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"RM\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3467163105479751,\n        \"min\": 6.421,\n        \"max\": 7.185,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          6.421\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AGE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 12.402943199095933,\n        \"min\": 45.8,\n        \"max\": 78.9,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          78.9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DIS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.8400812621407525,\n        \"min\": 4.09,\n        \"max\": 6.0622,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          4.09\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"RAD\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 3,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"TAX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.31831129861952,\n        \"min\": 222.0,\n        \"max\": 296.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          296.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"PTRATIO\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.393915348936225,\n        \"min\": 15.3,\n        \"max\": 18.7,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          15.3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"B\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.8492349769566823,\n        \"min\": 392.83,\n        \"max\": 396.9,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          396.9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"LSTAT\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.346812732196585,\n        \"min\": 2.94,\n        \"max\": 9.14,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          9.14\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
+       "type": "dataframe"
       },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "PermutationExplainer explainer: 26it [02:02,  5.10s/it]\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 800x650 with 1 Axes>"
-            ],
-            "image/png": 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FadGiBYsXL7b6P+5GD+J9JXdG0yBF5LF07do1pk2bRt26ddm/f78lvWrVqnz66afExcVZplodPHiQAgUKkDNnTqtzlChRwurxwYMHM0xPT8voP+PAwECrx3v27MEwDPr27Uvfvn0zbPuJEycoWLAgBw8etPoj/1btAti2bRsffvghy5Yts/xxle7G9S63snv3bv7++2+rwPLmNt2p3bt3A1j+8LmZl5eX5d+nT59m4MCBTJs2zaaurLT/btz83OzevRvDMChZsmSG+W/8o+pO3BiQwfU/OgsVKpRh+s1/GDk4OFCsWDGrtKCgIADL2pGDBw/i7++Pp6enVb4yZcpYjt/o5r7fzp0+Pzf3OVeuXIC5b15eXuzduxcHB4dMA8asvn5cXFz4+OOP6dmzJ/ny5aNatWo0bdqUdu3akT9//v/cr5MnT5KcnJzptLIb3Xxt0699qVKlrNKdnZ0pVqyY5XhgYCBvv/02I0aMYMqUKTz99NM0b96cl156yfLaaNOmDd9++y2vvvoq7733HvXr1+fZZ5+lVatWNkHvnbrdc3a/3h9ZPW9Wrs/d1H0nn3uffPIJ8+fP548//mDq1Kn4+flZHU/fEXf06NHs37/fKmDKkyePzfnv5LMhLS2Ns2fPWp0no2sWFBTExYsXOXnyZIav/wfxvpI7o2BNRB5Ly5Yt459//mHatGlMmzbN5viUKVMswdr9dOM394Dl2/BevXrRsGHDDMtkFIxl5syZM9SuXRsvLy8GDRpE8eLFcXV1ZfPmzbz77rtZ+gY+LS2NkJAQRowYkeHxm/94yIr0eidNmpThf+45clz/LyoyMpK1a9fSu3dvypcvj4eHB2lpaYSHh2ep/bfagfFW3y5Dxs+NyWRi4cKFViMj6W4cTb0TGZ0rs3Tjpg1B7oeb+347d/r83Iu+3cnrp3v37jRr1ox58+axePFi+vbtS0xMDMuWLeOpp566Z/3Kiju9tjf69NNPiYqKYv78+SxZsoS33nqLmJgY1q9fT0BAAG5ubqxatYrly5ezYMECFi1axPTp06lXrx5Lliy55XXPits9Z/fr/XEn573d9bmbuu/kc2/Lli2WAO6vv/6ibdu2VseHDh1K37596dixIx999BG5c+fGwcGB7t2739H75H5+NjyI95XcGQVrIvJYmjJlCn5+fnz11Vc2x+bMmcPcuXMZM2YMbm5uFClShOXLl3Px4kWr0bWb78mWfv+sjO7VltX7t6WPkDg5OREWFpZp3iJFimSprhUrVnDq1CnmzJlDrVq1LOk3jiimu1VQU7x4cbZu3Ur9+vXv2dbz6Qv7/fz8Mu1rUlIScXFxDBw40GoBffo3wDe6VdvSRwFu3l3v5hGl27XXMAwCAwMtI1f2IC0tjX379lm1adeuXQCWRf5FihRh6dKlnDt3zmp0LX0KbFbu/Xara3snz09WFS9enLS0NLZv3241zffmPHD718+N+Xv27EnPnj3ZvXs35cuX59NPP2Xy5MkZ5s9qv3x9ffHy8iI+Pj6LvbOWfu137txpNUKakpLC/v37bfoWEhJCSEgIH374IWvXriU0NJQxY8YwePBgwDzSWr9+ferXr8+IESMYOnQoH3zwAcuXL8/0Ov3X9/V/fX9k9tlzJ+e93fW5k37eyefehQsX6NChA8HBwdSoUYNhw4bRsmVLq82qZs2aRd26dRk/frxV2TNnzlg2VbmXMnoP7tq1i5w5c95ytPB+v6/kzmnNmog8di5dusScOXNo2rQprVq1svnp2rUr586ds2yV37BhQ65evcq4ceMs50hLS7MJ9Pz9/SlXrhw//PAD58+ft6SvXLmSv/76K0tt8/Pzo06dOowdO5Z//vnH5viNuxo2bNiQdevW8ccff1jSTp8+bXP7gfRvYW/81jUlJYXRo0fbnN/d3T3DaWuRkZEcOXLE6hqku3Tp0l3dL6phw4Z4eXkxdOhQrl69anM8va8ZtR/I8Obd7u7ugG1Q5uXlRd68eW22rc7oGtzKs88+i6OjIwMHDrRpi2EYGW7n/qB8+eWXVm358ssvcXJyon79+gA0btyYa9euWeUD+OyzzzCZTDRq1Oi2daR/UXHztb2T5yerIiIicHBwYNCgQTYjDun1ZPX1c/HiRZv7xBUvXhxPT89MbzuR1X45ODgQERHB//3f//H777/bnOd2ox1hYWE4OzvzxRdfWOUdP348Z8+epUmTJgAkJyfbrEkKCQnBwcHB0o/Tp0/bnD892L3dLTbc3d3/0w2p/+v741bv3ayeNyvXJ72erPbzTj733n33XQ4dOsT333/PiBEjKFq0KO3bt7eq29HR0aYPM2fOtKxDvtfWrVtnNf3+8OHDzJ8/nwYNGtxydO5+v6/kzmlkTUQeOz/99BPnzp2jefPmGR6vVq2a5QbZbdq0ISIigipVqtCzZ0/27NlD6dKl+emnnyx/GN34jevQoUNp0aIFoaGhdOjQgaSkJL788kvKlStnFcBl5quvvqJmzZqEhITQqVMnihUrxvHjx1m3bh0JCQmWe/K88847TJ48mWeeeYY333zTsnV/4cKFOX36tKVdNWrUIFeuXLRv35633noLk8nEpEmTMvwjsmLFikyfPp23336bypUr4+HhQbNmzXj55ZeZMWMGr7/+OsuXLyc0NJRr166xY8cOZsyYweLFizPcXCEzXl5efP3117z88stUqFCB559/Hl9fXw4dOsSCBQsIDQ3lyy+/xMvLi1q1ajFs2DCuXr1KwYIFWbJkSYYjg+mL6T/44AOef/55nJycaNasGe7u7rz66qv873//49VXX6VSpUqsWrXKMgKVFcWLF2fw4MH06dOHAwcOEBERgaenJ/v372fu3LlER0fTq1evO7oG94KrqyuLFi2iffv2VK1alYULF7JgwQLef/99y7fnzZo1o27dunzwwQccOHCAJ598kiVLljB//ny6d++e6fbl6dzc3AgODmb69OkEBQWRO3duypUrR7ly5bL8/GRViRIl+OCDD/joo494+umnefbZZ3FxcWHjxo34+/sTExOT5dfPrl27qF+/PpGRkQQHB5MjRw7mzp3L8ePHef7552/Zhjt53Q0dOpQlS5ZQu3Ztyxbv//zzDzNnzmT16tWZ3tLB19eXPn36MHDgQMLDw2nevDk7d+5k9OjRVK5cmZdeegkwT93u2rUrrVu3JigoiNTUVCZNmoSjoyPPPfccAIMGDWLVqlU0adKEIkWKcOLECUaPHk1AQIDVvQIzUrFiRZYuXcqIESPw9/cnMDDQsqlNVvzX98et3rtZPW9Wrs+d9jOrn3vLli1j9OjR9O/fnwoVKgDm27LUqVOHvn37MmzYMACaNm3KoEGD6NChAzVq1OCvv/5iypQpNmtO75Vy5crRsGFDq637wXxbjFu53+8ruQsPZM9JERE70qxZM8PV1dW4cOHCLfNERUUZTk5ORmJiomEY5m3LX3jhBcPT09Pw9vY2oqKijDVr1hiAMW3aNKuy06ZNM0qXLm24uLgY5cqVM3766SfjueeeM0qXLm3Jk76V/K22Pd67d6/Rrl07I3/+/IaTk5NRsGBBo2nTpsasWbOs8m3ZssV4+umnDRcXFyMgIMCIiYkxvvjiCwMwjh07Zsm3Zs0ao1q1aoabm5vh7+9vvPPOO5atpm/cCv78+fPGCy+8YPj4+NjcbiAlJcX4+OOPjbJlyxouLi5Grly5jIoVKxoDBw40zp49m+k1z2jr/nTLly83GjZsaHh7exuurq5G8eLFjaioKKstpxMSEoyWLVsaPj4+hre3t9G6dWvj6NGjGW4l/9FHHxkFCxY0HBwcrLakvnjxovHKK68Y3t7ehqenpxEZGWmcOHHillv332r789mzZxs1a9Y03N3dDXd3d6N06dJGly5djJ07d2Z6DW61dX+TJk1s8gJGly5drNIyes20b9/ecHd3N/bu3Ws0aNDAyJkzp5EvXz6jf//+NluEnzt3zujRo4fh7+9vODk5GSVLljSGDx9u2Vo+s7rTrV271qhYsaLh7Oxsdd2y+vzc6tpmdG0MwzC+++4746mnnrK83mrXrm251Ua6271+EhMTjS5duhilS5c23N3dDW9vb6Nq1arGjBkzMuzjje7kdXfw4EGjXbt2hq+vr+Hi4mIUK1bM6NKli3HlyhWrPma0vb9hmLfqL126tOHk5GTky5fP6Ny5s5GUlGQ5vm/fPqNjx45G8eLFDVdXVyN37txG3bp1jaVLl1ryxMXFGS1atDD8/f0NZ2dnw9/f32jbtq2xa9eu2/Z1x44dRq1atQw3NzcDsGxvf6fP2d2+Pwzj1u/drJw3K9cns37eyu0+95KTk40iRYoYFSpUMK5evWpVtkePHoaDg4Oxbt06wzDMW/f37NnTKFCggOHm5maEhoYa69atM2rXrm3Url3bUi596/6bb0Nwq9dQRs9R+vt48uTJRsmSJQ0XFxfjqaeesvq8v/GcNz+P9/N9JXfGZBgPYKWyiMgjaN68ebRs2ZLVq1cTGhqaad7y5cvj6+tLbGzsfW9X9+7dGTt2LOfPn/9PGwqI/YuKimLWrFlZHrUVkceDyWSiS5cuNlOf5eGjNWsiIllw6dIlq8fXrl1j1KhReHl5Waa9AFy9etVm3cSKFSvYunUrderUue/tOnXqFJMmTaJmzZoK1ERERB5yWrMmIpIFb775JpcuXaJ69epcuXKFOXPmsHbtWoYOHWq1FfeRI0cICwvjpZdewt/fnx07djBmzBjy589vc1PZe6F69erUqVOHMmXKcPz4ccaPH09ycvIt79EmIiIiDw8FayIiWVCvXj0+/fRTfv75Zy5fvkyJEiUYNWoUXbt2tcqXK1cuKlasyLfffsvJkydxd3enSZMm/O9//8vwpqf/VePGjZk1axbffPMNJpOJChUqMH78eKst+kVEROThpDVrIiIiIiIidkhr1kREREREROyQgjURERERERE7pGBN5BFjGAbJyckZ3vBYRERERB4eCtZEHjHnzp3D29ubc+fOZXdTREREROQ/ULAmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2KEc2d0AEblP/jkN51OzuxUiIo8Wdxfwds/uVojIY0LBmsijqus4OJyc3a0QEXl0BPrB+C4K1kTkgVGwJvKoOpAIe05mdytERERE5C5pzZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJih7R1v4iIiEh2O3MB3vkB5v4GF69AlZLwaXuoUPz2ZTfshonL4Lfd8OdBSL0Gxpz732YRue80siZyB8LDwzGZTNndDBEReZSkpUGTwTD1V+jaCIa1gxNnoU4/2H309uV/2QTfxoHJBMXy3f/2isgDo2DtPouJieGdd97J7maInYiPjyc6Oprly5dnd1NERORBqdMXokbd+visdbB2J0zsCv3bQJdGsGIQODpA/+m3P3/ncDg7CX4fDs88ee/aLSLZTsHafTZ16lQmTJiQ3c2Qe2T+/PmcO3fursvv2LGDcePGsX79+nvYKhEReajNWgf5fODZatfTfL0hsgbM3wBXrmZePp8PuLnczxaKSDZRsHaHzp07R0pKSnY3Q7KJi4sLHh4e2d0MERF5lGzZDxWKgcNNf5ZVKWlev7YrC1MhReSR9NAFa9u2bcNkMtGpUyer9IoVK2Iymejdu7dVelBQEAULFrRKW7VqFaGhoXh4eODk5ERAQADdu3fn6lXrb67S1ycdOnSIRo0a4e3tjbe3N7t27QJg2LBhlCxZkpw5c+Li4oKfnx9hYWEcOnQIAF9fX+Lj40lMTMRkMll+Zs2addt+zpw5kypVqlja6OfnR5MmTUhISLDkSUlJoVu3bgQEBODk5ISHhwehoaGsXr3a6lzx8fGYTCaio6P57rvvKFGiBE5OTvj4+PDiiy9mGHxu2bKFRo0akTt3bnLkyEGuXLmoXr06S5cuteSZMmUKderUwc/PD2dnZ3LmzEmFChWYPXu21bnq1KlDjhw5OHLkiE09GzduxGQyERkZaZX+xRdfEBwcjKurKy4uLgQFBfHVV1/d9roBzJo1C5PJRExMDH369KFAgQI4OTlRoEAB+vTpk2GZuXPn8tRTT5EzZ06cnZ0pVqwYgwcPtsmX0Zq19LSTJ08SERGBl5cXTk5OlClThoULF1ryxcTE0Lp1awDef/99y+shJCQEgGvXrvHOO+9QpEgRXF1dcXNzw9/fnyZNmnDlypUs9V1ERB5C/yRBgVy26elpR08/2PaIiN146HaDLFu2LH5+fqxdu9aSdunSJUtAsmrVKkt6YmIie/fupUWLFpa02NhYmjZtiqOjI23atCF//vwsXryYkSNHEh8fbxWMpKtduza5c+emS5cuXLhwAR8fH4YNG8a7775LcHAw3bp1w83NjUOHDrFixQoSEhIoXLgwQ4YMYeDAgZw7d45+/fpZzlexYsVM+zhgwAAGDRpErly5iIyMpGjRohw8eJBly5axe/duAgICAGjQoAErV67kqaee4uWXX+bYsWNMnz6dsLAwfvnlF+rVq2d13uXLlzNt2jQiIyPx9/dnwYIFTJ06lVy5cvHll19aXaMWLVpw7do1mjVrRrly5Th16hRr164lLi6OsLAwAMaPH8/Zs2eJiIigUKFCJCQkMGvWLCIjI5k9ezYREREAREVFsXLlSr766iuGDh1q1abRo0cD8Prrr1vSOnbsyIQJE6hYsSJvvfUWjo6OLFiwgK5du/LPP/9kGERl5NtvvyUpKYnIyEg8PT2ZN28e//vf/zh9+jRjx4615Bs/fjzR0dF4e3vTrl07PD09mT9/Pn379mXv3r1ZnsZas2ZNfHx86Nq1K6dOnWLSpElERkZy4MAB8uTJQ+PGjdm1axcTJ06kWbNm1KpVCwB/f38AunbtypgxY6hatSrt2rXD0dGRffv2sWzZMi5evIiLi6a4iIjYvaupcPaibdqVq5CYbJ2e28M8mnYpBVwy+JPM1dn8+5Jm9Ig8rkyGYRjZ3Yg71bRpUxYtWsTp06fx8vJi7ty5PPvss4SFhbF69WrOnj2Ls7Mz48eP59VXX+Wrr77ijTfeAKBMmTLs2rWL5cuXW/5YTktLo27duqxatYpp06bRpk0bwDxisnjxYurXr28TxNWsWZNNmzZZ6rqVkJAQjh07xsmTJ7PUt507d1KuXDny5cvHpk2byJfPelena9eu4ejoyNSpU3nxxRepXbs2y5Ytw+HfqRMrV66kXr16lC5dmm3btgHmkbWQkBCcnZ3ZtGkT5cqVs/S7aNGiJCcnc+bMGau0f/75h7i4OMs1url+gDNnzuDj42N1fP/+/TzxxBOULl2ajRs3AnD16lV8fX3x9fVl9+7dlrxpaWn4+fnh7u7OwYMHASzBYPv27Zk4caLVuWvUqMGWLVtISEggT548t7yGs2bNonXr1ri4uLB161ZKlSoFmIP6J554gn379rF9+3ZKlSrF1atXKVCgABcvXuTPP/+kRIkSlrwVKlRg586d/P7771SoUAG4/pq48W2TnhYREcHcuXMt6V9++SVvvvkm/fv3Z8CAAVZtGzp0qM0oX7FixUhJSbEaPb0bycnJeHt7c7ZENF57sva6ExGRLChVEJYNBP/crF+/nsqVK1v+T9y+fTsFChQg19YjULffbU5ktmlWJyo+1wg8XoA2oax95Slq1KhhOb5jxBRK95wNi/pCw6eu15HLPOKWkJBAWloahQsXBsyf/1dfG02eaRssW/evXbvW6pw3P75lPzKp49ChQ5a/JVSH6lAd/62O23nopkEC1K9fn2vXrvHTTz8BsHDhQry8vHjnnXe4fPkysbGxgHmEyGQyWUZ4Dh48yI4dO6hevbpVEOLg4MCgQYMAmDFjhk19H3zwgU2ap6cnKSkpTJw4kbS0tHvWt2+//ZbU1FTeeecdm0ANsLxYZs6cCcCgQYMsgRqYRwGrVavG9u3bLdMx0z399NNWLx4HBweqVKnC2bNnSUpKAmDFihUcPnyYJk2a2ARqN9YPWAVqSUlJHDlyxDL97++//7Ycc3JyonHjxuzZs4cNGzZY0mfPns2pU6do1aqVVf9NJhNdunQhISHB6qdJkyZcvnyZRYsWZX4R/9WwYUNLoAbg5ubGG2+8QVpaGlOmTAHMweGpU6do3ry5JVBLz9ujRw8Mw2Dy5MlZqq9v375Wj1u2bAlgmTZ7Ox4eHpw+fZr58+dnKb+IiGSfatWqWf2fGBwcbP4D7smiENvf+ueJItCgvE16xSb1zYUL5IJ/kmz+gCvt/e/fAf65rev4V0BAgOWPRAAvLy+bLzNvPufNj2/Zj0zquPFvCdWhOlTHf6vjdh7KYC09+Fq8eDEAa9asoUKFCtSrVw93d3d++eUXAH777TeKFClimWa2fft2AKs/4NNVqVLFsj7tZhlNWxwyZAh58+bltddew9vbm5o1a/LRRx9x6tSp/9S3PXv2ALd/Ig8fPozJZKJq1ao2x9L7l97fdEWKFLHJmzu3+T+Ao0fNi5fj4+MBeOqpp27b1j/++IO6devi7u5O7ty5CQgIoFChQmzcuJGLF62ngKSPbKZPewT47rvvcHBwoEuXLpa0PXv2YBgGVapUoVChQlY/H374IUCGa98yUrp0aZu09BGyvXv3AtcDqZvfWACVK1cGzKOFWZG+9ixd+lrJ9ED4dmJiYnByciIiIoLcuXMTFhbGiBEjuHTpUpbKi4iIHcjlAWFPWv/k8jAHZDenp09zLF8UNu8z32/tRr/thpwuEOT/wLshIvbhoVuzBhAYGEhAQADr1q0jOTmZXbt2ERkZiaOjI08++SSrV6/myJEjHDx40DKl8b/w8vKySatQoQL79+9nxowZLF68mI0bN9KvXz8+++wzli1bRvny5f9zvffajd8M3OxOZ8MmJSVRr149Ll++zEsvvUT58uXx9vbGwcGB//3vf/z5559W+WvWrEnRokX5+eefSUtL4/z586xYsYIKFSpQrFgxq3aYTCZ++OGHW7a3SpUqd9TWB8XJySnD9Kxe2yZNmnDgwAF+/PFH4uLi2LBhA3FxcYwYMYINGzZYvnQQEZFHTKvq5u3756yHVv9+WZuYDDPXQrNK4HLD/y97j5l/F8//4NspIg/cQxmsAVStWpU5c+YwceJEUlNTLZuI1K5dm+HDh/Pjjz9iGAYNGjSwlAkODgbM68JutnHjRgzDsBrKvJ2cOXMSFRVFVFQUABMnTqRDhw4MGjSIOXPMc8Vv3jnwdkqWLAmY57NWqlTplvkKFy7Mpk2b+O2332ymK6aPFqX3906kjw798ccfmeabOXMmSUlJDBkyhPfff9/qWPr6rJu1bt2a4cOHM2vWLA4fPszly5d5+eWXrfIEBgayadMmSpQoQbVq1TI8T1bt2LHDJm3z5s0AFC9eHLg+Cpk+onij33//3dKme+V2r4dcuXLxxhtvWEYi+/bty+DBgxk+fDifffbZPWuHiIjYkVbVoVoQdPgStidAXk8YvQiupcHA563z1u9v/n3g+kZZHDwBk1aa//27eYYOg83LJSjiCy/Xua/NF5H756GcBgkQFhaGYRgMGzaMPHnyWEaymjVrRmpqKiNHjsTBwYHmzZtbyhQpUoTSpUuzbt061qxZY0lPS0uzBBg3byF/KxltApEeNKVv1gHmtU8XLlzI8rq2V155hRw5cjB8+HASExNtjqefJ32d14ABA6zOvWbNGtatW0dwcPAdBZ7pateuTaFChfj555+tdty8uf4cOcxx/s2jRlOmTLnlGq0uXbrg4ODAd999x9SpU3Fzc6Njx45WeV599VUAevbsaXMrBcj6lEQwT5O9MTC/dOkSo0ePxsHBgRdeeAGAevXqkSdPHv7v//6Pffv2WfJeuXKFzz//HJPJxEsvvZTlOm/H29sbIMPpshm9pqpXrw7A6dPatllE5JHl6Ai/fAhtQuGLBdD7B8jrZd7MpFTB25fffwL6/mj++e3fjbzSH4+Pu79tF5H76qEdWYuIiOCNN97gyJEjhIeHW9KrV6+Ot7c3CQkJBAUF2Sy0/eKLL2jatCkNGjSw2rp/8+bN1K9fP8vTJmvVqoWnpydVqlShcOHCJCUlWe7v1a5dO0u+SpUqsWHDBlq1akVoaCiOjo60bNkyw/VjYB7p6dOnD4MHD6Z06dK0aNGCokWLkpCQQGxsLOPHj6du3bq88MILfPPNNyxfvpzKlSvTsGFDy9b9Tk5OjBo16i6uqnnTkXHjxhEREUHdunVp3rw55cqVIykpibVr11K/fn1iYmJo0qQJ3t7eDB06lP3791OoUCH++OMPFi5cSOHChTNc+1ekSBEqV67MihUruHr1Kk2aNLG5wXTDhg2Jjo7mm2++oXjx4jRu3JiCBQty9OhRtm7dyoYNG0hNTc1SXwoWLEj16tVp06YNnp6ezJ07lz179vDKK69Y1rM5OTnx8ccfEx0dTeXKlS3b/M+fP59du3YRFRVlWed2L1StWhVXV1cmT56Mu7s7uXLlwt/fn8jISIKDgylTpgwVK1a09Hn69OnkyJHDJqgVEZGHyIqPbp8nlwd828X8k5kbR9TS1Sln2f1RRB4tD22wlj9/fgIDA9m3bx9169a1OlapUiXi4uIy3KTjmWeeYcmSJfTp04cZM2Zw5coV/Pz86NatG8OHD89y/VFRUcydO5eZM2dy/vx5PDw8KFmyJJ9++qnlxsdg3jTiwIEDxMXFMW/ePAzDICAg4JbBGph3eCxVqhSffPIJP/74I1evXiVXrlxUqVKFoKAgS74lS5bQu3dvZs2axfDhw3FxceHJJ59k2LBh1KxZM8t9uVnDhg1ZtWoVffr0ITY2lrlz5+Lp6UmZMmUs91jLly8fP/30Ez169ODHH3/k2rVrlCxZkmnTpjFmzJgMgzWAdu3a8dtvvwHXR9FuNnbsWKpVq8aXX37J5MmTuXLlCl5eXgQGBma4M+etvPrqqyQnJzNx4kQSExPJmzcv77zzDh9//LFVvldeeQUfHx8GDx5smVYbEBDARx99ZNnU5F7x9PTk66+/ZtCgQQwdOpTU1FTKlStHZGQkUVFRxMXFMXnyZC5duoSXlxdly5alf//+1K5d+562Q0RERETs30N5nzWRzGR2L7PHge6zJiJyn9xwnzURkQfhoV2zJiIiIiIi8ihTsCYiIiIiImKHFKyJiIiIiIjYoYd2gxGRW2nVqtUd3+RbRERERMTeaGRNRERERETEDilYExERERERsUMK1kREREREROyQ1qyJPKqK5gVH5+xuhYjIoyPQL7tbICKPGQVrIo+qLzuBp1d2t0JE5NHi7pLdLRCRx4iCNZFHVYHc4KVgTURERORhpTVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYoRzZ3QARuU/+OQ3nU7O7FfIocHcBb/fsboWIiMhjR8GayKOq6zg4nJzdrZCHXaAfjO+iYE1ERCQbKFgTeVQdSIQ9J7O7FSIiIiJyl7RmTURERERExA4pWBMREREREbFDCtZERERERETskII1ERERERERO6RgTURERERExA4pWBMRkexz5gJEfw2+UeDeFur2g817s17+7wQIHwQeL0DudvDySDh5NvMyU1aC6VlzGRERETumYE3kDsTHx2MymYiOjs7upog8/NLSoMlgmPordG0Ew9rBibNQpx/sPnr78gmJUOtD2HMMhr4IvZrDgk3wzEBIuZpxmfOX4J1J4O56b/siIiJyHyhYE3nAYmJieOedd7K7GSL3X52+EDXq1sdnrYO1O2FiV+jfBro0ghWDwNEB+k+//fmHzoYLl2HZQHirCbzfCmb0hK0HYOLyjMsMngWebhBR5a66JCIi8iApWBO5A8HBwZw7d44vv/zyrs8xdepUJkyYcA9bJfKQmrUO8vnAs9Wup/l6Q2QNmL8BrtxidCzd7PXQtBIU9r2eFvYkBPnDjLW2+Xcfhc/+D0ZEQQ7He9EDERGR+0rBmsgdcHBwwMPDA2dn5+xuisjDb8t+qFAMHG76r6hKSbh4BXZlMhXyyCnzlMlKxW2PVSkJW/bZpnf/DuqWg8YV/1u7RUREHpCHLliLiYnBZDIxffp0Xn/9dfLmzYuzszNBQUH88ssvAMyePZvg4GBcXFzw8fGhc+fOGZ4rNjaW0NBQPD09cXJywt/fny5dupCSkmKVb9GiRYSHh1OgQAFcXFxwdXWlTJkyjBkzxuac4eHhmEwmTp48SUREBF5eXjg5OVGmTBkWLlyY5X4mJibSoUMHChYsiJOTEx4eHgQHB/P5559b5Vu1ahWhoaF4eHjg5OREQEAA3bt35+pV62+k77RdaWlpDBo0iKCgIFxdXXF1daVw4cK8+uqrljynTp2iY8eOBAUFWa5h/vz5adeuHcnJyZZ869evx2Qy8fzzz2fY13r16pEjRw4OHTpkSdu7dy8RERHkzZuXHDlykCtXLpo1a8bBgwezdP1CQkLw9fVl69atVK9enZw5c+Lm5kZoaChbt261yX/mzBnat29Pvnz5cHJywsfHhwYNGrBt2zarfBmtWbsx7bvvvqNEiRKWc7z44otWrydfX1/i4+NJTEzEZDJZfmbNmgXA2rVrqVWrFrlz57ac44knntBInDya/kmCArls09PTjp7OvOyNeW8uf/q89cjcgt9hyVYY0eHu2ysiIvKA5cjuBtytDz74gLS0NKKiokhJSWHixIk899xzjBw5krfffpvnnnuOVq1aMW/ePMaMGUPx4sXp1auXpfyECROIjo4mf/78REVFkSdPHtavX8/XX3/NX3/9xapVqyx5f/zxR/bv30+jRo0oWrQoiYmJzJ49m86dO3Px4kXefvttm/bVrFkTHx8funbtyqlTp5g0aRKRkZEcOHCAPHnyZNq348ePU7lyZQ4fPszTTz9Nu3btSE1NZevWrfz88890794dMAebTZs2xdHRkTZt2pA/f34WL17MyJEjiY+PZ+nSpXfdrgYNGhAXF0dQUBCdOnUiV65c7Nixg0WLFlny7N27lzlz5lCvXj1atmyJk5MTv/76K5MnT2bbtm1s2rQJgGrVqlGiRAkWLVrE1atXcXJyspwjMTGRNWvWULlyZQoXLgzA33//TWhoKKmpqURERFCiRAl2797NrFmzqFatGn/++Se+vjdMe7qFK1euUL9+fYKDg+nZsye7du1izpw51K5dm82bN1OsWDFLvho1avD333/z9NNPU7t2bUve0NBQfvvtN0qVKnXb+pYvX860adOIjIzE39+fBQsWMHXqVHLlymWZNjlkyBAGDhzIuXPn6Nevn6VsxYoVOXLkCI0aNQIgMjKSokWLcvLkSbZs2cKaNWvo0EF/ZIodu5oKZy/apl25ConJ1um5PcyjaZdSwCWD/4Zc/x25vpRieyxd+jEXJ9tjrk7X87g4mTcb6TEBXm8AwYWy1h8RERE78NAGa2lpaWzbtg03NzfAPJISHR1N586dWbRoEc888wwAffr0oUCBAowbN84SrJ0/f54ePXoQFBTEli1brKa09e7dm08++YRZs2bRqlUrAEaOHImPj49V/YMHD6Z06dKMGDEiw2AtODiYuXPnWh6HhITw5ptvMmrUKAYMGJBp315//XUOHz7MgAED6N+/v9Wxa9euWf791ltvkZqaSmxsLLVq1QLMwUDdunWJi4tj+vTptGnT5o7b9cUXXxAXF0dYWBiLFi3C0fH62o4b6w8JCeH48eO4uLhY1fHKK6/w3XffWUYkAdq0acOQIUOYMmUKUVFRlrxjxowhJSWFdu3aWdI6duxIamoqGzdutAqS2rVrR3h4OB988AHffPNNptcQ4Ny5c7Ru3ZoZM2ZY1de5c2d69OjB/PnzAfj444/5+++/efHFF5k8ebIl74QJE+jYsSNdu3YlNjb2tvUdOnSITZs2Ua5cOQAGDBhA0aJFmTx5siVYi46OZtSoUaSkpFh9eQAwbtw4kpOTGTlyJG+99dZt6xOxK2t2mLfdv9nanTBttXXa/jFQ1A/cnOFKqm2Zy/8GYm6ZTDdOP5bRurbLV63zfPZ/kHgOBmY8ui8iImKvHrppkOmioqIsgRpAs2bNAChVqpQlUANwc3OjTJkyHD16fe3D9OnTOXv2LC+++CInTpwgISHB8hMZGQnAzz//bMl/Y6CWnJzMkSNHSE5OpkqVKhw5coTExESb9vXt29fqccuWLQHYtWtXpv26du0asbGxFCxY0CZQAyyB08GDB9mxYwfVq1e3BGpgXlM1aNAgAKsg5U7a9eOPPwLwzTffWAVqN9YP5mubHqilpKRw7NgxEhISaNy4MQArV6605H3jjTfIkSMH33//vdX5pk2bhru7uyWAO3nyJL/99htPP/007u7uVs9NmTJlyJ8/v9Wo5+3873//s3r8+uuv4+/vb9W2//u//8NkMvHJJ59Y5e3QoQNFixZl9erVVkHqrTz99NOWQA3Mz0WVKlU4e/YsSUlJty2fO3duABYuXJjha0oku23fvt3qtZyQkHB9+vKTRbkwrzf7v2kPsf3NP08UIalK0euPY/uz7fPWkN/HXKZALpL+3m/1/tq+fTsX9hwxP/DPbV0H5s/g+Pj469Mf/0li7VrrzURO/LnLPHrn4gRnL3Bt0HTSXqkPyZfgwAl2x64h5XQyGAYcOMHRP/7OuI4b3FzHzY/Xr19v049bXivVoTpUh+pQHaoji0yGYRh3VCKbxcTE8P777zNt2jSbUSOTyURYWJjNKEh4eDiLFy8mvavdu3dn5MiRmdbTuHFjFixYAJgDo65du7Jq1SqrtVjptm/fTpkyZazqSklJsZrul96+8PDwTNeuHTx4kKJFi1K3bl2WLVt2y3wLFy6kcePGdOzYkfHjx1sdu3TpEu7u7lSsWJGNGzfecbsCAgK4cOFClgKMvn378sMPP3D48GFufim99tprVuv6atasyYYNGzh69Ch58+YlPj6eJ554goiICObMmQOY1wemTwW8FT8/P44fP55pnpCQEPbt28eFCxdsjoWGhrJ27VqSkpLw8fGhYMGCXL58mVOnTtnkDQsLIy4ujgMHDlCkSBHi4+MJCQmhU6dOltG99LSMnovo6GjGjRtHfHw8ZcuWtbTt2LFjnDx50qa+hg0bsmTJEhwdHSlZsiQ1a9akY8eOVK9ePdP+3ig5ORlvb2/OlojGa49tHSJ3pFRB89b4/rnvvGydvuYRtIlvZny89XD49W84+q31JiPRX8OUVXD6h4ynOabzi4I65WCG9Sg1pbpCQB6IGwgHTkDg65m3s0UVmPdelrokIiLyID200yBvHvG5XfqN0oOKHj16ULly5QzzFC1aFDBPt6xTpw4JCQm0adOGKlWqkDt3bhwdHRk/fjxxcXEZjrrcHBDdXHd2uZft6tWrF59++ikVKlTg1VdfpVChQri4uHDo0CHee+890tLSrPK3a9eONWvW8PXXX9O3b1+++uorDMOw2qwjvR1hYWF07Ngxw3rd3d3vuK0PQmavvaxe38WLF7NmzRpmzZrFunXrmDRpEt999x3vvvsuQ4cOvVdNFbEPraqbt++fsx5a1TCnJSbDzLXQrJJ1oLb3mPl38fzX056rDt8vh8OJUCivOS3uT/Mukj3Msy3w84a579rW/cUCWLcLfuyR8SYlIiIiduChDdb+i9KlSwPg4eFB27ZtM83766+/cuDAAV599VXGjRtndSwr66buVEBAAO7u7uzevTvTfMHBwQDs3LnT5tjGjRsxDMOyYcedKly4MOvWrWP//v0EBgbeMt/s2bPx9fVlw4YNVoHKpEmTMszfvn17evXqxbRp0+jbty/z5s3D39/fsq4N4IknnsBkMnH16tXbPje3c/HiRfbt22fZSCTdgQMH8PLyskxvLViwIL///jvHjx8nX758Vnn37duHm5sbAQEB/6ktNzKZTJkeDw0NJTQ0FDBvNvPUU08xYsQIBg8ejMPNW5yLPMxaVYdqQdDhS9ieAHk9YfQiuJZmu76s/r/Twg+MvZ72/nPmwK5uP+jWBM5fhuHzIaQIdKhnzpPTBSKq2tY9bwNs2JPxMRERETvxWP7l17ZtW7y8vBg9erTVWrZ0586ds0yJy5HDHM/ePDKyZs0aVq9ebVP2v3J0dKRBgwYkJCQwePBgm+Ppo1VFihShdOnSrFu3jjVr1lgdT98oJH393Z164YUXAPP6rptHDW8cLUsP0G5MS0lJYdiwYRme18XFhfDwcP7++29GjBjBsWPHeO6556zyFCxYkMqVK/Prr79absVwc/03zg2+nffes57aNGbMGI4ePUrt2rUtaU2bNsUwDHr37m2V9/vvv2f//v2EhoZmacQ2q9zc3Lhw4YLNyOPRo0dtrne+fPkoUKAAKSkpGU7pFHmoOTrCLx9Cm1DzSFfvHyCvl3naZamCty9fKC+s/Mg82vbeZBg2DxpXMK+Py2z6pIiIyEPisRxZ8/Hx4auvvqJjx46ULl2aFi1aULJkSZKSkti1axcrVqzg+++/p1WrVlSpUoVChQrx/fffc/HiRUqXLs3OnTuZM2cORYoUYe/evfe8faNHj+a3336jb9++LF261LJe6Y8//rDs/gjmXRubNm1KgwYNrLbu37x5M/Xr17dZ05dVXbt2Zfbs2SxZsoSyZcvSoEEDcufOzc6dO1mzZo0lWGrcuDGjRo2iatWqNGvWjLNnzzJ//vxMA5vXXnuNmTNn8uGHH2IymejSpYtNnu+//56aNWvSvHlzGjZsyFNPPcW1a9fYt28fy5cvJyIiIkujmp6enixbtozatWtTq1Yty3b83t7efPbZZ5Z87777LtOmTWPSpEkcPnyYmjVrsnv3bmbPno23tzejRo26i6t4a5UqVWLDhg20atXKEgi2bNmSr776iu+++4569epRokQJnJ2dWbVqFZs3b6Z27dp4enre03aI3HcrPrp9nlwe8G0X809mbhxRu1HZwrA4g10ob2fim7deSyciImInHstgDeCll14iMDCQ/v37s2DBApKTk3F3d6dAgQK0a9eOGjXM6yecnJxYuHAhnTt35ueff2b27NkULlyYzz77jM2bN9+XYC1//vxs3ryZnj17snTpUlavXo2rqytFihThtddes+R75plnWLJkCX369GHGjBlcuXIFPz8/unXrxvDhw/9TG5YuXUr//v2ZOnUqY8eOxWQykS9fPqvNPz799FMMw2DmzJkMHToUb29vwsPD6dq16y03xKhfvz6FChXi8OHDlC9fPsP7l5UuXZo//viDd999l2XLlrFkyRKcnJzImzcvderUyfL9xlxcXFi6dCmvv/46n3zyCYZhUKlSJUaPHk3x4sWt8q1du5Zu3bqxcOFCfv31V3LmzEmdOnX4/PPPLdNm75WYmBgOHDhAXFwc8+bNwzAMAgICaNSoEVu3bmXVqlXMnz8fBwcH8uXLx9tvv81HH2Xhj14REREReaQ8dLtBimRFZjsuPuq0G6TcU/9lN0gRERH5Tx7LNWsiIiIiIiL2TsGaiIiIiIiIHVKwJiIiIiIiYoce2w1G5NH2119/ZXcTRERERET+E42siYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJih7TBiMijqmhecHTO7lbIwy7QL7tbICIi8thSsCbyqPqyE3h6ZXcr5FHg7pLdLRAREXksKVgTeVQVyA1eCtZEREREHlZasyYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB3Kkd0NEJH75J/TcD41u1shDzt3F/B2z+5WiIiIPJYUrIk8qrqOg8PJ2d0KeZgF+sH4LgrWREREsomCNZFH1YFE2HMyu1shIiIiIndJa9ZERERERETskII1ERERERERO6RgTURERERExA4pWBMREREREbFDCtZERERERETskII1ERF58M5cgOivwTcK3NtC3X6weW/Wy/+dAOGDwOMFyN0OXh4JJ89mXmbKSjA9ay4jIiLyEFCwJnIfREdHYzKZiI+Pz+6miNiftDRoMhim/gpdG8GwdnDiLNTpB7uP3r58QiLU+hD2HIOhL0Kv5rBgEzwzEFKuZlzm/CV4ZxK4u97bvoiIiNxHCtZEHpBZs2YRHR3N8ePHs7spIvdXnb4QNerWx2etg7U7YWJX6N8GujSCFYPA0QH6T7/9+YfOhguXYdlAeKsJvN8KZvSErQdg4vKMywyeBZ5uEFHlrrokIiKSHRSsidwHX375JefOnSM4ONiStmTJEsaNG8fJk7pRtTzmZq2DfD7wbLXrab7eEFkD5m+AK7cYHUs3ez00rQSFfa+nhT0JQf4wY61t/t1H4bP/gxFRkMPxXvRARETkgVCwJnIfODs74+HhgYOD3mIiNrbshwrF4Ob3R5WScPEK7MpkKuSRU+Ypk5WK2x6rUhK27LNN7/4d1C0HjSv+t3aLiIg8YPpLMhvExMRgMpmYPn06r7/+Onnz5sXZ2ZmgoCB++eUXAGbPnk1wcDAuLi74+PjQuXPnDM8VGxtLaGgonp6eODk54e/vT5cuXUhJSbHKt2jRIsLDwylQoAAuLi64urpSpkwZxowZY3PO8PBwTCYTJ0+eJCIiAi8vL5ycnChTpgwLFy7Mcj8TExPp0KEDBQsWxMnJCQ8PD4KDg/n888+t8q1atYrQ0FA8PDxwcnIiICCA7t27c/Wq9bfrd9qutLQ0Bg0aRFBQEK6urri6ulK4cGFeffVVS55Tp07RsWNHgoKCLNcwf/78tGvXjuTkZEu+9evXYzKZeP755zPsa7169ciRIweHDh0CbNeshYeHM27cOABCQkIwmUyYTCaio6Pp3bs3JpOJqVOn2pz34sWLeHh48OSTT2bhios8JP5JggK5bNPT046ezrzsjXlvLn/6vPXI3ILfYclWGNHh7tsrIiKSTXJkdwMeZx988AFpaWlERUWRkpLCxIkTee655xg5ciRvv/02zz33HK1atWLevHmMGTOG4sWL06tXL0v5CRMmEB0dTf78+YmKiiJPnjysX7+er7/+mr/++otVq1ZZ8v7444/s37+fRo0aUbRoURITE5k9ezadO3fm4sWLvP322zbtq1mzJj4+PnTt2pVTp04xadIkIiMjOXDgAHny5Mm0b8ePH6dy5cocPnyYp59+mnbt2pGamsrWrVv5+eef6d69O2AONps2bYqjoyNt2rQhf/78LF68mJEjRxIfH8/SpUvvul0NGjQgLi6OoKAgOnXqRK5cudixYweLFi2y5Nm7dy9z5syhXr16tGzZEicnJ3799VcmT57Mtm3b2LRpEwDVqlWjRIkSLFq0iKtXr+Lk5GQ5R2JiImvWrKFy5coULlw4w+vx5ptvcv78edasWUPv3r3x8/MDoEqVKhQvXpzPP/+cb7/9lhdesN6l7ptvvuHChQu0b98+0+stkm2upsLZi7ZpV65CYrJ1em4P82japRRwyeC/H1dn8+9LKbbH0qUfc3GyPebqdD2Pi5N5s5EeE+D1BhBcKGv9ERERsSMK1rJRWloa27Ztw83NDTCPuERHR9O5c2cWLVrEM888A0CfPn0oUKAA48aNswRr58+fp0ePHgQFBbFlyxacnZ0t5+3duzeffPIJs2bNolWrVgCMHDkSHx8fq/oHDx5M6dKlGTFiRIbBWnBwMHPnzrU8DgkJ4c0332TUqFEMGDAg0769/vrrHD58mAEDBtC/f3+rY9euXbP8+6233iI1NZXY2Fhq1aoFwJAhQ6hbty5xcXFMnz6dNm3a3HG7vvjiC+Li4ggLC2PRokU4Ol5fp3Jj/SEhIRw/fhwXFxerOl555RW+++47y4gkQJs2bRgyZAhTpkwhKirKknfMmDGkpKTQrl27W16PJk2aMH/+fNasWUO7du0oV66c1fGnn36aX3/9laNHj+Lv729J//7773F3dyc6OvqW5xbJVmt2mLfdv9nanTBttXXa/jFQ1A/cnOFKqm2Zy/8GYm7OtsfSpR/LaF3b5avWeT77P0g8BwMzHhEXERGxd5oGmY2ioqIsgRpAs2bNAChVqpQlUANwc3OjTJkyHD16fR3H9OnTOXv2LC+++CInTpwgISHB8hMZGQnAzz//bMl/Y6CWnJzMkSNHSE5OpkqVKhw5coTExESb9vXt29fqccuWLQHYtWtXpv26du0asbGxFCxY0CZQAyyB08GDB9mxYwfVq1e3BGoADg4ODBo0CIAZM2bcVbt+/PFHwDwydWOgdmP9YL626YFaSkoKx44dIyEhgcaNGwOwcuVKS9433niDHDly8P3331udb9q0abi7u1sFcHfqjTfeIDU1lVGjru+gFx8fz9atWwkPD8fDw+Ouzy3yXxiGYfn39u3bSUpKsjxOSEjgcJ4cENsfYvtzYV5v9n/THp4oAg3KQ2x/tn3e2nKc/D6sXbvWPF3x3+mM69evv/4Fyr9pZz1yWNWRPr0Y4JyHk1VewHzO9LTcHqzdtBHOXjDvANkpjC0r13Jt7z9w4AScv0Ra2jXObt0NJ85kWEdycrLNbTcsddzisVU/bnGtVIfqUB2qQ3Wojpsf347JuPF/YnkgYmJieP/995k2bZrNqJHJZCIsLIzY2Fir9PDwcBYvXmz5w6l79+6MHDky03oaN27MggULAHNg1LVrV1atWmW1Fivd9u3bKVOmjFVdKSkpVtP90tsXHh6e6dq1gwcPUrRoUerWrcuyZctumW/hwoU0btyYjh07Mn78eKtjly5dwt3dnYoVK7Jx48Y7bldAQAAXLlywekPdSt++ffnhhx84fPgwN78dXnvtNat1fTVr1mTDhg0cPXqUvHnzEh8fzxNPPEFERARz5syx5IuOjmbcuHH89ddfllG0jNJu5O/vj4uLC/v37wegU6dOfPvtt6xYsYLatWvfth/pkpOT8fb25myJaLz2aOdJ+Q9KFTRvj++f+87K1elrHkGb+GbGx1sPh1//hqPfWm8yEv01TFkFp3/IeJpjOr8oqFMOZvSyTi/VFQLyQNxAc2AW+Hrm7WxRBea9l6UuiYiIZAdNg8xGN4/43C79RulBRY8ePahcuXKGeYoWLQqYp1vWqVOHhIQE2rRpQ5UqVcidOzeOjo6MHz+euLg4q28N0t0cEN1cd3a5l+3q1asXn376KRUqVODVV1+lUKFCuLi4cOjQId577z3S0tKs8rdr1441a9bw9ddf07dvX7766isMw7gn0xSff/55PvvsM5YuXUrdunWZO3cuxYsXv6NATeSh0Kq6efv+OeuhVQ1zWmIyzFwLzSpZB2p7j5l/F89/Pe256vD9cjicCIXymtPi/jTvItnDPEMBP2+Y+65t3V8sgHW74MceGW9SIiIiYkcUrD2kSpcuDYCHhwdt27bNNO+vv/7KgQMHePXVVy07Eqb75ptv7nnbAgICcHd3Z/fu3ZnmS78H2c6dO22Obdy4EcMwbrlhx+0ULlyYdevWsX//fgIDA2+Zb/bs2fj6+rJhwwarIHnSpEkZ5m/fvj29evVi2rRp9O3bl3nz5uHv729Z15YZk8mU6fG3336bUaNG8dVXX3Hs2DFOnTpFly5dbntekYdOq+pQLQg6fAnbEyCvJ4xeBNfSbNeX1f93KvWBsdfT3n/OHNjV7QfdmsD5yzB8PoQUgQ71zHlyukBEVdu6522ADXsyPiYiImJntGbtIdW2bVu8vLwYPXq01Vq2dOfOnePUqVMA5MhhjslvHnlas2YNq1evtin7Xzk6OtKgQQMSEhIYPHiwzfH00aoiRYpQunRp1q1bx5o1a6yOp28Ukr7+7k6l76r4+uuv24wa3jhalh6g3ZiWkpLCsGHDMjyvi4sL4eHh/P3334wYMYJjx47x3HPPZalN6evOjh8/nuHxgIAAQkNDWbx4MaNGjcLZ2Zk337zFNDKRh5mjI/zyIbQJNY909f4B8nqZp1yWKnj78oXywsqPzKNt702GYfOgcQXzurjMpk+KiIg8ZDSy9pDy8fHhq6++omPHjpQuXZoWLVpQsmRJkpKS2LVrFytWrOD777+nVatWVKlShUKFCvH9999z8eJFSpcuzc6dO5kzZw5FihRh796997x9o0eP5rfffqNv374sXbqU6tWrA/DHH39Ydn8E866NTZs2pUGDBlZb92/evJn69evbrOnLqq5duzJ79myWLFlC2bJladCgAblz52bnzp2sWbPGshi0cePGjBo1iqpVq9KsWTPOnj3L/PnzM52K+tprrzFz5kw+/PBDTCZTlke/ateuzYgRI+jVqxeRkZG4ublRuXJlQkNDLXk6d+7MypUr2bBhAw0bNiRv3rx31X+RbLXio9vnyeUB33Yx/2TmxhG1G5UtDIsz2IXydia+eeu1dCIiInZGwdpD7KWXXiIwMJD+/fuzYMECkpOTcXd3p0CBArRr144aNcxrQZycnFi4cCGdO3fm559/Zvbs2RQuXJjPPvuMzZs335dgLX/+/GzevJmePXuydOlSVq9ejaurK0WKFOG1116z5HvmmWdYsmQJffr0YcaMGVy5cgU/Pz+6devG8OHD/1Mbli5dSv/+/Zk6dSpjx47FZDKRL18+GjVqZMnz6aefYhgGM2fOZOjQoXh7exMeHk7Xrl0tAebN6tevT6FChTh8+DDly5enVKlSWWpP8+bN6datG1OnTuXDDz8kLS2NTp06WQVrrVu3pnv37hw7dozXX7/N5ggiIiIi8kjTbpAidqZQoUKkpaVx5MiRuyqv3SDlnrnb3SBFRETkntCaNRE7MmPGDBISEnj+ed3EV0RERORxp2mQInZgxowZ7Nixgy+//BJPT0/69OmT3U0SERERkWymYE3EDnz00Uds376dgIAAvvnmG20sIiIiIiIK1kTswV9//ZXdTRARERERO6M1ayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2CFtMCLyqCqaFxyds7sV8jAL9MvuFoiIiDzWFKyJPKq+7ASeXtndCnnYubtkdwtEREQeWwrWRB5VBXKDl4I1ERERkYeV1qyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHcmR3A0TkPvnnNJxPze5WSEbcXcDbPbtbISIiInZOwZrIo6rrODicnN2tkJsF+sH4LgrWRERE5LYUrIk8qg4kwp6T2d0KEREREblLWrMmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJih7QbpIjIo+LMBXjnB5j7G1y8AlVKwqftoULxrJX/OwF6fAerd4BzDmhSEUZEga/39TxHT5vr2LjH/G9HBwjyhy6NoF0dMJnuR89EREQeSwrWREQeBWlp0GQwbD0IvVtAXi8YvQjq9INNw6Gkf+blExKh1ofgnROGvgjnL8EnP8FfB2HDx+DsZM6XmAwJp6BVdSicF65eg9itEDUKdh6BoS/d/76KiIg8JhSsySMtJiaGpKQkhg0blt1NEflv6vSFon4w8c2Mj89aB2t3wsxe0KqGOS2yBgR1hf7TYWqPzM8/dDZcuGwO7Ar7mtOqlIRnBsLE5RDdwJz2RFFY8ZF12a6NodlQ+OIX+KgtODredTdFRETkOq1Zk0fa1KlTmTBhQnY3Q+T+m7UO8vnAs9Wup/l6mwO2+RvgytXMy89eD00rXQ/UAMKeNE9xnLH29vUX9TVPvUxJvavmi4iIiC0Fa/JQOXfuHCkpKdndjEydOnUqu5sgj6Mt+6FCMXC46WO9SklzELXr6K3LHjkFJ85CpQzWtlUpCVv22aZfumKeEnngBHy/HCYsh+pB4Oby3/ohIiIiFgrW5I5s27YNk8lEp06drNIrVqyIyWSid+/eVulBQUEULFjQKm3VqlWEhobi4eGBk5MTAQEBdO/enatXrb/5Dw8Px2QycejQIRo1aoS3tzfe3t7s2rULgGHDhlGyZEly5syJi4sLfn5+hIWFcejQIQB8fX2Jj48nMTERk8lk+Zk1a1amffziiy+oVq0aefPmxcnJCU9PT2rUqMGqVats8vr6+hISEsKyZcuoWLEiOXPmpEyZMpbjmzdv5plnnsHHx4ccOXLg6+vLiy++yJkzZ6zOs2HDBlq2bEmhQoVwdXXFxcWF4sWL89FHN003E7mVf5KgQC7b9PS0o6czL3tj3pvLnz5vOzI3cgH4RkHg6+b1atWCYFrPu2q6iIiIZExr1uSOlC1bFj8/P9auvT4t6tKlS8THx2MymawCmsTERPbu3UuLFi0sabGxsTRt2hRHR0fatGlD/vz5Wbx4MSNHjiQ+Pp6lS5fa1Fm7dm1y585Nly5duHDhAj4+PgwbNox3332X4OBgunXrhpubG4cOHWLFihUkJCRQuHBhhgwZwsCBAzl37hz9+vWznK9ixYqZ9nHs2LF4e3sTGRlJgQIF2LNnD7Nnz6ZBgwasXbuWChUqWOU/fvw4zZo1o169ejRv3pxz584BsHTpUpo3b07OnDmJjIwkICCArVu3MmPGDDZt2sTWrVtxcTGPQixYsIBNmzZRp04dihUrxvnz5/n555/p168fJ06cYNSoUXfwLMlD72oqnL1om3blqnk060a5PcyjaZdSwCWDj3RXZ/PvS5mMSKcfc3HKoLzT9Tw3Hm9b0zwSdzIZfv4djp/NvA4RERG5YwrW5I5VrlyZRYsWkZycjJeXF4sWLSIlJYWwsDBWr15NSkoKzs7OzJ8/n7S0NMLCwixl33rrLVJTU4mNjaVWrVoADBkyhLp16xIXF8f06dNp06aNVX3Fixe3CeJ++uknXF1d2bJlC87Ozhm2Mzo6mlGjRpGSkkKvXr2y3L81a9bg4+Njlda5c2eefvppPvroI+bOnWt17OTJkwwaNIi+fftapb/66qvkypWLP//8kzx58ljSx4wZQ+fOnRkxYgR9+vQBoEePHgwcONCq/LBhwyhfvjzjx4/nk08+sQR28hhYswPq9rNNX7sTpq22Tts/xrzxiJszXMlgvdjlfwMot4zfJ1bHMlrXdvlqxuWL+Jl/ANo+DdFfQ9gA2DlKUyFFRETuEU2DlDtWv359rl27xk8//QTAwoUL8fLy4p133uHy5cvExsYC5lE0k8lEREQEAAcPHmTHjh1Ur17dEqgBODg4MGjQIABmzJhhU98HH3xgk+bp6UlKSgoTJ04kLS3tnvYvPVBLS0sjMTGRhIQEAgIC8Pf3588//7TJ7+7uznvvvWeVtnr1ag4ePEizZs24dOkSCQkJlp/GjRvj4uJiuU431glw/vx5jhw5wj///EPt2rW5dOkSGzduvKd9lOx17do1jh69voYsOTmZ+Pj46xmeLMq2z1tDbH/Lz4USvtCgvOXx9pGRXFvUF/L7AHAljztXD52wnCIhIcE8JfjfKY7nvZyt64DrI+T/Tn88sP4Pq+Pr168n7egp8+idixPbt28nKSnJtg4wb+V/OJEDP/yScR23eLx+/XquXbtmeZxpHRldK9WhOlSH6lAdquMhruN2TIZhGHdUQh57+/fvp1ixYrz00ktMmjTJMjVy6dKleHt70759e7766isCAwMt+cEc1DVu3JiOHTsyfvx4q3NeunQJd3d3KlasaAlMwsPDWbx4MWfPnsXLy8sq/+bNm2nUqBEnTpzAw8ODJ598koYNG/LGG29YjWKFhIRw7NgxTp48meX+LVu2jD59+rB161auXLlidczX15cTJ05YPfbx8WH37t1W+b744gu6deuWaT1PPPEEW7duBSApKYkuXbqwZMmSDDcomTNnDi1btsxS+5OTk/H29uZsiWi89mS93/KAlCoIywaCf+47K3e7rftbD4df/4aj31pvMhL9NUxZBad/yHiaYzq/KKhTDmbcNApdqisE5IG4gRkWs5i/ASL+B9N7QmRolrokIiIimdM0SLljgYGBBAQEsG7dOpKTk9m1axeRkZE4Ojry5JNPsnr1ao4cOcLBgwdtpjTejZsDNYAKFSqwf/9+ZsyYweLFi9m4cSP9+vXjs88+Y9myZZQvX/6u6vr7779p3LgxOXPm5LXXXqNs2bJ4eHhgMpl49913uXTpkk0ZV1fXW56vbdu2NGvWLMNjvr7Xt0hv1KgRGzZsoFmzZtSuXRs/Pz8cHR2ZP38+06dPt/pWRyRDraqbt++fs/76fdYSk2HmWmhWyTpQ23vM/Lt4/utpz1U37+p4OBEK5TWnxf1p3kWyxw2v4ZNnzbcEuNn4pWAymXekFBERkXtCwZrclapVqzJnzhwmTpxIamqqZROR2rVrM3z4cH788UcMw6BBgwaWMsHBwQDs3LnT5nwbN27EMAwKFy6c5TbkzJmTqKgooqKiAJg4cSIdOnRg0KBBzJkzBwCTyXRH/Zo4cSJXrlxh0qRJtG7d2upY586dcXLKZGTiBmXLlgXA0dGRtm3bZpr3+PHjbNiwgWeeeYb58+dbHVu4cOEdtF4ea62qm3dk7PAlbE+AvJ4wehFcS4OBz1vnrd/f/PvA2Otp7z9nDuzq9oNuTeD8ZRg+H0KKQId61/MNmWVeUxf+lPmebKfPme/RtnEPvNkYShS4/30VERF5TGjNmtyVsLAwDMNg2LBh5MmTxzKS1axZM1JTUxk5ciQODg40b97cUqZIkSKULl2adevWsWbNGkt6WloaAwYMACAyMjJL9SckJNikpa+Du3FbfDc3Ny5cuJDldW2Ojo4A3Dw7eNCgQZw9ezZL5wCoW7cuhQoVYvbs2ZapjjdKSUmxrFnKkSNHhnXu3bvXZjMTkVtydIRfPoQ2ofDFAuj9A+T1Mk+5LFXw9uUL5YWVH5lH296bDMPmQeMK5jVyN47KNakI+XPBd8ugyzgYMhucc8CErjDylfvWPRERkceR1qzJXTl27Bj+/v4YhkF4eLjVCJCPjw9nz54lKCjIZhQtfev+HDlyWG3dv3nzZurXr2+162P6mrWMXqLFihXD09OTKlWqULhwYZKSkpg1axYJCQl89913ltG2Ll26MHr0aFq2bEloaCiOjo60bNmSIkWKZNivP/74g6pVq+Lu7s6LL75I7ty5Wbt2LevWrcPDw4Nr165ZrX/z9fUlf/78/PXXXzbnWr58uSV4bdasGWXLluXChQvs3buXZcuW8e6771p2g6xYsSJbtmyhadOmVK5cmQMHDjBz5kz8/PzYu3cvM2fOpFWrVll6brRmzc7d7Zo1EREReexoGqTclfz58xMYGMi+ffuoW7eu1bFKlSoRFxdHjRo1bMo988wzLFmyhD59+jBjxgyuXLmCn58f3bp1Y/jw4VmuPyoqirlz5zJz5kzOnz+Ph4cHJUuW5NNPP7WavhgTE8OBAweIi4tj3rx5GIZBQEDALYO18uXLM23aND744APGjRuHg4MD5cqVY/Hixbz++uscO3Ysy22sW7cuv/32G++//z4rVqxg7ty5uLq6ki9fPlq0aGG1Ycj8+fN57bXX+PXXX1m4cCEFChSgV69eODk58f7772e5ThERERF5dGhkTeQRo5E1O6eRNREREckirVkTERERERGxQwrWRERERERE7JCCNRERERERETukYE1ERERERMQOKVgTERERERGxQwrWRERERERE7JCCNRERERERETukYE1ERERERMQO5cjuBojIfVI0Lzg6Z3cr5GaBftndAhEREXlIKFgTeVR92Qk8vbK7FZIRd5fsboGIiIg8BBSsiTyqCuQGLwVrIiIiIg8rrVkTERERERGxQwrWRERERERE7JCCNRERERERETukYE1ERERERMQOKVgTERERERGxQwrWRERERERE7JCCNRERERERETukYE1ERERERMQOKVgTERERERGxQwrWRERERERE7JCCNRERERERETukYE1ERERERMQO5cjuBojIffLPaTifmt2teDy4u4C3e3a3QkRERB4xCtZEHlVdx8Hh5OxuxaMv0A/Gd1GwJiIiIvecgjWRR9WBRNhzMrtbISIiIiJ3SWvWRERERERE7JCCNRERERERETukYE1ERERERMQOKVgTERERERGxQwrWRERERERE7JB2gxQRsVdnLsA7P8Dc3+DiFahSEj5tDxWKZ6383wnQ4ztYvQOcc0CTijAiCny9r+c5etpcx8Y95n87OkCQP3RpBO3qgMl0P3omIiIiWaBgTeQu+fr6kj9/fv76669M00TuSloaNBkMWw9C7xaQ1wtGL4I6/WDTcCjpn3n5hESo9SF454ShL8L5S/DJT/DXQdjwMTg7mfMlJkPCKWhVHQrnhavXIHYrRI2CnUdg6Ev3v68iIiKSIQVrYvdiYmJISkpi2LBh2d0UkXunTl8o6gcT38z4+Kx1sHYnzOwFrWqY0yJrQFBX6D8dpvbI/PxDZ8OFy+bArrCvOa1KSXhmIExcDtENzGlPFIUVH1mX7doYmg2FL36Bj9qCo+Ndd1NERETuntasid2bOnUqEyZMyO5mZMnBgwfZsGFDdjdDHgWz1kE+H3i22vU0X29zwDZ/A1y5mnn52euhaaXrgRpA2JPmKY4z1t6+/qK+5qmXKal31XwRERH57xSsyQN37tw5UlJSHni9p06duu915MyZEzc3t/tejzwGtuyHCsXA4aaP6SolzUHUrqO3LnvkFJw4C5UyWNtWpSRs2WebfumKeUrkgRPw/XKYsByqB4Gby3/rh4iIiNw1BWuPoW3btmEymejUqZNVesWKFTGZTPTu3dsqPSgoiIIFC1qlrVq1itDQUDw8PHByciIgIIDu3btz9ar1t/3h4eGYTCYOHTpEo0aN8Pb2xtvbm127dgEwbNgwSpYsSc6cOXFxccHPz4+wsDAOHToEmNeAxcfHk5iYiMlksvzMmjUr0z6aTCbCw8OZPn06wcHBuLq6UqdOHQD27NlD27ZtCQwMxN3d3dL+bt262bQfYMeOHdSuXdsSiFWtWpU//vgjw3p9fX0JCQnJsC03i4mJsenL0aNHadOmDfny5cPJyQkPDw+KFy9Ojx63mfImj55/kqBALtv09LSjpzMve2Pem8ufPm87MjdyAfhGQeDr5vVq1YJgWs+7arqIiIjcG1qz9hgqW7Ysfn5+rF17fSrUpUuXiI+Px2QysWrVKkt6YmIie/fupUWLFpa02NhYmjZtiqOjI23atCF//vwsXryYkSNHEh8fz9KlS23qrF27Nrlz56ZLly5cuHABHx8fhg0bxrvvvktwcDDdunXDzc2NQ4cOsWLFChISEihcuDBDhgxh4MCBnDt3jn79+lnOV7Fixdv2c/v27bRv356IiAief/55S/q6deuIi4ujXr16lChRgpSUFOLi4vjiiy/Yv38/P/30kyXv8ePHqVWrFqdOnSIiIoLg4GB+/fVXwsLC7svoYKNGjYiPj6dly5Y88cQTXLp0ib///ps1a9bc87rkAbqaCmcv2qZduWoezbpRbg/zaNqlFHDJ4CPa1dn8+1Imr7/0Yy5OGZR3up7nxuNta5pH4k4mw8+/w/GzmdchIiIi952CtcdU5cqVWbRoEcnJyXh5ebFo0SJSUlIICwtj9erVpKSk4OzszPz580lLSyMsLMxS9q233iI1NZXY2Fhq1aoFwJAhQ6hbty5xcXFMnz6dNm3aWNVXvHhxmyDup59+wtXVlS1btuDs7JxhO6Ojoxk1ahQpKSn06tXrjvp4+PBhpk6dStu2ba3SIyIiePHFF3G4aXrZM888w88//8zevXspXtw8fezdd9/l5MmTDBkyhPfff9+SNzIykpkzZ95Re27n5MmT/Pnnn0RERNx25FAeMmt2QN1+tulrd8K01dZp+8eYNx5xc4YrGawXu/xvAOWW8XvG6lhG69ouX824fBE/8w9A26ch+msIGwA7R2kqpIiISDbRNMjHVP369bl27ZplFGnhwoV4eXnxzjvvcPnyZWJjYwHzKJrJZCIiIgIwb6CxY8cOqlevbgnUABwcHBg0aBAAM2bMsKnvgw8+sEnz9PQkJSWFiRMnkpaWdq+7SNGiRW0CtfR60wO1S5cucfToURISEmjYsCGGYbBixQpL3qVLl+Lt7W0zNTQmJuaet9fDw4McOXLw559/Eh8ff8/PL/fPzaOs69ev59q1a5bHO1yucG5OT4jtD7H9OTm1Cyll/KFBeYjtz4V5vdn/TXvz8fw+AFzK5Xp9OiNcHwn/N23ryQSrOrZv305SkvX0x6S/91uOJycnm19X/ySZR+9cnKxG163qAPNW/ocTubb8+mvRqg4gISHBMmXZqo5bnTODxzdfK9WhOlSH6lAdquNxquN2TIZhGHdUQh4J+/fvp1ixYrz00ktMmjTJMjUyPThp3749X331FYGBgZb8YA7qGjduTMeOHRk/frzVOS9duoS7uzsVK1Zk48aNgHnN2uLFizl79ixeXl5W+Tdv3kyjRo04ceIEHh4ePPnkkzRs2JA33niDPHnyWPKFhIRw7NgxTp48meX+mUwmatWqxcqVK22OpaSk0L17d+bOncvx48e5+S3w8ccf88477wDg5OREUFAQ27ZtszmPu7s7xYoVu+191kwmEw0bNmTRokVW5WNiYnj//feZOXMmrVq1AqB///4MHTqU1NRUAgICqFq1Kq1bt7YZqcxMcnIy3t7enC0RjdeerF8zuUulCsKygeCf+87K3W7r/tbD4de/4ei31puMRH8NU1bB6R8ynuaYzi8K6pSDGTeNSJfqCgF5IG5g5u2bvwEi/gfTe0JkaJa6JCIiIveWRtYeU4GBgQQEBLBu3TqSk5PZtWsXderUwdHRkSeffJLVq1dz5MgRDh48SLVq1W5/wtu4OVADqFChAvv372fChAk0bdqUY8eO0a9fP0qWLHnLDTzuxK12ZXzxxRf5+uuvKV26NDExMUycOJGpU6fSrVs3AKtvUO6n1FTbKW4DBw5kx44dDBo0iNKlS7N06VKef/556tat+0DaJHakVXU4fgbmrL+elpgMM9dCs0rWgdreY+afGz1X3bz27HDi9bS4P827SLaucT3t5NmM6x+/FEwm846UIiIiki20Zu0xVrVqVebMmcPEiRNJTU21bCJSu3Zthg8fzo8//ohhGDRo0MBSJjg4GICdO3fanG/jxo0YhkHhwoWz3IacOXMSFRVFVFQUABMnTqRDhw4MGjSIOXPmAOaRqXvpl19+oWzZsixfvtwqfceOHTZ58+XLx5EjR7h69SpOTtf/ON67dy8XL160yZ8Rd3d3zpw5Y5O+d+/eDPMXL16cvn37AnD16lUaNmzI8uXLWbx4MQ0bNsxSnfIIaFXdvCNjhy9hewLk9YTRi+BaGgx83jpv/f7m3wfGXk97/zlzYFe3H3RrAucvw/D5EFIEOtS7nm/ILPOauvCnzPdkO33OfI+2jXvgzcZQosD976uIiIhkSCNrj7GwsDAMw2DYsGHkyZOH8uXLA9CsWTNSU1MZOXIkDg4ONG/e3FKmSJEilC5dmnXr1lntUJiWlsaAAQMA8+YbWZGQkGCTlr4O7sbgxs3NjQsXLtyzdW0ODg42Ux/PnDnDuHHjbPLWr1+fs2fPMnz4cKv0Pn36ZLm+ggULsn37dpKTr+/6d+zYMebNm2eVLzk52SoPmKdhlitXDuCOpoHKI8DREX75ENqEwhcLoPcPkNfLPOWyVMHbly+UF1Z+BMXzw3uTYdg8aFzBvC7uxlG5JhUhfy74bhl0GQdDZoNzDpjQFUa+ct+6JyIiIrenkbXHWEREBG+88QZHjhyxug9Y9erV8fb2JiEhgaCgIKv1YwBffPEFTZs2pUGDBlZb92/evJn69etneX1VrVq18PT0pEqVKhQuXJikpCRmzZqFyWSiXbt2lnyVKlViw4YNtGrVitDQUBwdHWnZsiVFihS5q37Xq1ePn376iTp16lCvXj2OHTvGrFmzMpyq+fHHH7NgwQL69u3Lpk2bKFu2LKtWrSI+Ph5PT88s1RcdHU2vXr2oXLkyrVu3JikpiRkzZpAvXz7Onr0+BW3Tpk00adKEWrVqERwcTO7cudm+fTuzZ8/G19fXKmiWR8CKj26fJ5cHfNvF/JOZG0fUblS2MCzOYBfKGz1T3vwjIiIidkfB2mMsf/78BAYGsm/fPps1UZUqVSIuLo4aNWrYlHvmmWdYsmQJffr0YcaMGVy5cgU/Pz+6detmMwKVmaioKObOncvMmTM5f/48Hh4elCxZkk8//ZTWrVtb8sXExHDgwAHi4uKYN28ehmEQEBBw18HapEmT6Ny5M4sXL2bNmjXkzZuX559/ntDQUKv7sYH5Gv36669ER0fzyy+/8Msvv/DEE0+wdOlSnnnmmSzV17NnTxISEpg0aRIff/wxfn5+dO/eHQcHB6vbAQQFBdGsWTM2bNjAqlWrSE1NJXfu3LRo0YKYmJgMg0kREREReXRpN0iRR4x2g3zA7nY3SBEREZHb0Jo1ERERERERO6RgTURERERExA4pWBMREREREbFDCtZERERERETskII1ERERERERO6RgTURERERExA4pWBMREREREbFDuim2yKOqaF5wdM7uVjz6Av2yuwUiIiLyiFKwJvKo+rITeHpldyseD+4u2d0CEREReQQpWBN5VBXIDV4K1kREREQeVlqzJiIiIiIiYocUrImIiIiIiNghBWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYocUrImIiIiIiNghBWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYocUrImIiIiIiNghBWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYodyZHcDROQ++ec0nE/N7lY8utxdwNs9u1shIiIijzAFayKPqq7j4HBydrfi0RToB+O7KFgTERGR+0rBmsij6kAi7DmZ3a0QERERkbukNWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYocUrImIiIiIiNghBWsiIiIiIiJ2SLtBiojYmzMX4J0fYO5vcPEKVCkJn7aHCsWzVv7vBOjxHazeAc45oElFGBEFvt7X8xw9ba5j4x7zvx0dIMgfujSCdnXAZLofPRMREZE7oGBNHgkhISEcO3aMkye1Vb085NLSoMlg2HoQereAvF4wehHU6QebhkNJ/8zLJyRCrQ/BOycMfRHOX4JPfoK/DsKGj8HZyZwvMRkSTkGr6lA4L1y9BrFbIWoU7DwCQ1+6/30VERGRTClYk1uKiYkhKSmJYcOGZXdTHgrHjx+nb9++NGjQgFatWmV3c8Re1ekLRf1g4psZH5+1DtbuhJm9oFUNc1pkDQjqCv2nw9QemZ9/6Gy4cNkc2BX2NadVKQnPDISJyyG6gTntiaKw4iPrsl0bQ7Oh8MUv8FFbcHS8626KiIjIf6c1a3JLU6dOZcKECdndjCzZsGEDBw8ezNY2nDx5knHjxrFkyZJsbYc85Gatg3w+8Gy162m+3uaAbf4GuHI18/Kz10PTStcDNYCwJ81THGesvX39RX3NUy9TUu+q+SIiInLvKFh7jJw7d46UlJTsbsY9c/XqVZKTkwFwc3MjZ86c2dyi++vUqVPZ3QR5ELbshwrFwOGmj+cqJc1B1K6jty575BScOAuVMljbVqUkbNlnm37pinlK5IET8P1ymLAcqgeBm8t/64eIiIj8ZwrWHqBt27ZhMpno1KmTVXrFihUxmUz07t3bKj0oKIiCBQtapa1atYrQ0FA8PDxwcnIiICCA7t27c/Wq9bft4eHhmEwmDh06RKNGjfD29sbb25tdu3YBMGzYMEqWLEnOnDlxcXHBz8+PsLAwDh06BICvry/x8fEkJiZiMpksP7Nmzcq0jyaTifDwcH788UdKlSqFi4sLPj4+REZGkpSUZJP/5MmTvPzyy+TPnx8nJye8vLyoV68eW7dutcoXExODyWTixx9/pHPnzuTLlw9XV1e++uorwLxmzdfX16pMelp8fDyhoaHkzJkTd3d3wsPDSUpK4tq1a3Tt2hU/Pz+cnJwoVqwYP/30k00b09LS6NevH8WLF8fFxQVXV1eeeOIJZs6cackza9YsQkJCABg3bpzlet3cpi+++ILg4GBcXV1xcXEhKCjI0oeMruP06dMt+evUqZPptZdHxD9JUCCXbXp62tHTmZe9Me/N5U+ftx2ZG7kAfKMg8HXzerVqQTCt5101XURERO4trVl7gMqWLYufnx9r116finTp0iXi4+MxmUysWrXKkp6YmMjevXtp0aKFJS02NpamTZvi6OhImzZtyJ8/P4sXL2bkyJHEx8ezdOlSmzpr165N7ty56dKlCxcuXMDHx4dhw4bx7rvvEhwcTLdu3XBzc+PQoUOsWLGChIQEChcuzJAhQxg4cCDnzp2jX79+lvNVrFjxtv38+++/6dChAy1atCAyMpKVK1cyc+ZMdu7cyebNm3H8dx3MyZMnqVChAidPnqR58+aULVuWo0ePMm3aNJ5++mnWrVtH2bJlrc79/vvvk5qaSps2bfD29uaJJ57ItC1XrlyhXr16VKxYkd69e/P777/zyy+/8Oyzz5IrVy7+/PNP2rVrx9WrV5kwYQIvvPACBw8eJE+ePJZzNGjQgGXLllGrVi3atGnDlStXmDt3Ls8//zxnzpyhU6dOlvMPHz6c0NBQIiIiAPDy8rKcp2PHjkyYMIGKFSvy1ltv4ejoyIIFC+jatSv//PMPgwcPtmr79u3bad++PRERETz//PO3ve5ih66mwtmLtmlXrppHs26U28M8mnYpBVwy+Gh2dTb/vpTJ6Hj6MRenDMo7Xc9z4/G2Nc0jcSeT4eff4fjZzOsQERGRB0bB2gNWuXJlFi1aRHJyMl5eXixatIiUlBTCwsJYvXo1KSkpODs7M3/+fNLS0ggLC7OUfeutt0hNTSU2NpZatWoBMGTIEOrWrUtcXBzTp0+nTZs2VvUVL17cJoj76aefcHV1ZcuWLTg7O2fYzujoaEaNGkVKSgq9evW6oz4eOnSIsWPHEh0dbUmLjIxk5syZjBo1iu7duwPQpUsXjh8/TmxsLLVr17bqZ6VKlejZsyeLFi2yOveVK1fYsWOHVRCUmXPnzvHKK6/w2WefWdJq1qzJypUrKVasGNu2bcPFxTzdq1y5cpZ+DxgwAIAxY8YQFxfHgAED6N+/v+UcMTExBAcH88EHH/DKK68QGBhIu3btGD58OMHBwTbXLC4ujgkTJtC+fXsmTpxodZ4aNWrw6aef0qNHD6sg8fDhw0ydOpW2bdtmqa9ih9bsgLr9bNPX7oRpq63T9o8xbzzi5gxXMlgvdvnfAMot4/es1bGM1rVdvppx+SJ+5h+Atk9D9NcQNgB2jtJUSBERkWymaZAPWP369bl27Zplut3ChQvx8vLinXfe4fLly8TGxgLmUTSTyWQZoTl48CA7duygevXqlkANwMHBgUGDBgEwY8YMm/o++OADmzRPT09SUlKYOHEiaWlp97qL+Pv7WwVqYA5KAObNmweYpxYuXLiQkJAQihcvTkJCguXH29ubMmXK8Ntvv9mc+6WXXspyoAbm6/PRR9Y73lWvXh3DMGjfvr0lUANo1qwZgGWqKMDkyZNxdXUlKirKqo0nTpygfv36nDx5ks2bN9+2Hd9++y0mk4kuXbpYnSchIYEmTZpw+fJlm8C0aNGiCtQeEjeOlgOsX7+ea9euwZNFIbY/B7+N4tycnhDbH54owuVapTk+pbP5cWx/LszrzbZTR8yFC+SCf5Jszrnn19/N//DPbV3Hv7Zv384Zt38/0v9JIiEhwTKtGSDl0HFSvd2sRtVurmPt2rXmrfwPJ8Kq7RnWceN05pvrSE5OJj4+PtNrc8trpTpUh+pQHapDdTyGddyOyTAM445KyH+yf/9+ihUrxksvvcSkSZMsUyOXLl2Kt7c37du356uvviIwMNCSH8xBXePGjenYsSPjx4+3OuelS5dwd3enYsWKbNy4ETCvWVu8eDFnz561CW42b95Mo0aNOHHiBB4eHjz55JM0bNiQN954w2pk527uXWYymahRowZr1qyxOebu7k6BAgXYs2cPBw8epGjRorc9V3owGRMTw/vvv8+ECROIioqyyZtRW0NCQjh69KjNxhzp55o2bZrNSGT6WrGFCxcCEBAQwJEjRzJt59y5c4mIiCA+Pp6QkBA6derEN998Y5WncuXK/P7775me5+OPP+add96xtKNWrVqsXLky0zIZSU5Oxtvbm7MlovHao/vO3RelCsKygZbA6Y7cbuv+1sPh17/h6LfWm4xEfw1TVsHpHzKe5pjOLwrqlIMZN42Il+oKAXkgbmDm7Zu/ASL+B9N7QmRolrokIiIi94emQT5ggYGBBAQEsG7dOpKTk9m1axeRkZE4Ojry5JNPsnr1ao4cOcLBgwdtAom7kdEoVIUKFdi/fz8zZsxg8eLFbNy4kX79+vHZZ5+xbNkyypcv/5/rvZ30IKx8+fKWACUrPDw87qgeh5t31LuB4y3uIXXj9xeGYeDp6cnYsWNveZ5q1ard8tiN5zGZTPzwww+3rLdKlSpWj93c3G57XnkEtapu3r5/zvrr91lLTIaZa6FZJetAbe8x8+/i+a+nPVfdvKvj4UQolNecFveneRfJHs2u5zt51nxLgJuNXwomk3lHShEREclWCtayQdWqVZkzZw4TJ04kNTXVsolI7dq1GT58OD/++COGYdCgQQNLmeDgYAB27txpc76NGzdiGAaFCxfOchty5sxJVFSUZZRq4sSJdOjQgUGDBjFnzhzAPLpzNw4cOGCTtnfvXi5evEhAQAAAhQsXJmfOnFy4cMGup/oVKlSIDRs2EB4eTq5cGeywd4PMrldgYCCbNm2iRIkSWQru5DHWqrp5R8YOX8L2BMjrCaMXwbU0GHjTRjP1/11HeeCGLxPef84c2NXtB92awPnLMHw+hBSBDvWu5xsyy7ymLvwp8z3ZTp8z36Nt4x54szGUKHD/+yoiIiKZ0pq1bBAWFoZhGAwbNow8efJYRrKaNWtGamoqI0eOxMHBgebNm1vKFClShNKlS7Nu3TqrKYZpaWmWzTAiIyOzVH9CQoJNWvo6uDNnzljS3NzcuHDhwh2vazt69KjNNMA+ffoAWAJTR0dHwsPD2b17d4Zb1wPZfpNrgJdffhnDMGxut5AufZoqgI+PD0CGtyh49dVXAejZs6fNbRZuPo885hwd4ZcPoU0ofLEAev8Aeb3M0y5LFbx9+UJ5YeVH5tG29ybDsHnQuIJ5fdyNo3JNKkL+XPDdMugyDobMBuccMKErjHzlvnVPREREsk4ja9kgIiKCN954gyNHjhAeHm5Jr169Ot7e3iQkJBAUFGS1fgzM9+hq2rQpDRo0sNq6f/PmzdSvXz/L0yZr1aqFp6cnVapUoXDhwiQlJTFr1ixMJhPt2rWz5KtUqRIbNmygVatWhIaG4ujoSMuWLSlSpEim5y9cuDBvvfUWcXFxBAUFsXLlSn799VfKlSvHW2+9Zck3ZswYNm/ezJtvvsmsWbOoXLkyLi4uHDhwgJUrVxIcHGyz6caD1qVLF37++Wdmz55NmTJlCAsLw9fXl8OHD7Np0ybLZiMABQsWtDwn7777LgUKFMDT05NXXnmFhg0bEh0dzTfffEPx4sVp3LgxBQsW5OjRo2zdupUNGzaQmprBDoDy6Fnx0e3z5PKAb7uYfzJz4BbTc8sWhsUZ7EJ5o2fKm39ERETEbilYywb58+cnMDCQffv2UbduXatjlSpVIi4ujho1atiUe+aZZ1iyZAl9+vRhxowZXLlyBT8/P7p168bw4cOzXH9UVBRz585l5syZnD9/Hg8PD0qWLMmnn35K69atLfliYmI4cOAAcXFxzJs3D8MwCAgIuG2wVqZMGf73v//Rv39/5s6di5ubG8899xxjx461Wq/l6+vL1q1beffdd1mwYAFr1qzBwcGBPHny8NRTT9Gly23+UH1AFi5cyLBhw/j+++/59ttvSU1NxcfHh1KlSvHhhx9a5Z0wYQI9evTg888/JyUlhbx58/LKK+ZRirFjx1KtWjW+/PJLJk+ezJUrV/Dy8iIwMDDDXTtFRERE5PGm3SDlnjKZTDRs2DDbR8QeZ9oN8gH4L7tBioiIiGSR1qyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB3SBiNyT2kJpIiIiIjIvaGRNRERERERETukYE1ERERERMQOKVgTERERERGxQ1qzJvKoKpoXHJ2zuxWPpkC/7G6BiIiIPAYUrIk8qr7sBJ5e2d2KR5e7S3a3QERERB5xCtZEHlUFcoOXgjURERGRh5XWrImIiIiIiNghBWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYocUrImIiIiIiNghBWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYocUrImIiIiIiNghBWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYodyZHcDROQ++ec0nE/N7lY8nNxdwNs9u1shIiIijzkFayKPqq7j4HBydrfi4RPoB+O7KFgTERGRbKdgTeRRdSAR9pzM7laIiIiIyF3SmjURERERERE7pGBNRERERETEDilYExERERERsUMK1kREREREROyQgjURERERERE7pGBNRERERETEDmnrfhGRB+XMBXjnB5j7G1y8AlVKwqftoULxrJX/OwF6fAerd4BzDmhSEUZEga/39Tw7EuC7ZbDkD9h7DDxcoUIxGPg8VCpxP3olIiIi94lG1kREHoS0NGgyGKb+yv+3d9/xNd1/HMdfV2TJFEmsIKgd1dqjLVp7tVZUB6qaUlraomhKYxZVpdWFWkWJ+WvtUVVbUUXs2dgzQRDk/P64zeW6SSTkyo2+n4/HfST3e77nfMeNI598x6FLfRjWBs7EQI2+sP/E/c+PPgfPhcOBUzD4VejeBBZsgdoREH/zTr5xy2HsMihfGEa0gw+awN4TULkXLN9ut+aJiIhI+lOwJhlqyJAh9OzZM03nhIWF8cMPP9ipRrZ++OEHwsLCHll5kknV+ATafZX88VnrYd1emNgF+rWCzvVhVX9wygL9Ztz/+oNnw9XrsDIC3msIfVrAzA9h+xGY+NudfK2fhX9+gHGdIawO9HgJNg4FP0/4NBXliIiIiMNQsCYZatq0aUyYMCFN54wdO5Y5c+bYqUa25syZw9ixYx9ZefKYmrUecvpCs8p30gJ8ILQqzN8EN24meyoAszdAo/KQP+BOWq0yUDQPzFx3J61cYfB0tz43hxc8W9I8jVJEREQyDQVrkq4uX75MfHx8Rlcj00hISODixYsZXQ15FLYdNq8dy3LPbbdiEfP6tX0pTIU8ft48ZbJ8EmvbKhaBbYfuX/6pi+DvnbY6i4iISIZSsPaY2bVrFyaTibfeessqvVy5cphMJnr06GGVXrRoUfLmzWuVtnr1aqpVq4anpyfOzs4EBQXRrVs3bt60/st/vXr1MJlMHDt2jPr16+Pj44OPjw/79u0DYNiwYRQpUoRs2bLh6upKYGAgtWrV4tixYwAEBASwc+dOzp07h8lksrxmzZqVZNt27tyJyWQCYMmSJVbn3G369OmULVuWbNmy4ezsTIECBejXr59Vnho1apAlSxabsn766SeyZMlCnTp1AChdujRLliwBsCpvyJAhluMBAQHcK7Gud0+fnDVrluXc8PBwgoKCcHV15aOPPrLkGT16NCVLlsTNzQ1XV1eKFi3KmDFjkuwPyWROXoTc2W3TE9NOXEj53Lvz3nv+hSspj8z9EQXr90Graqmvr4iIiGQ47Qb5mClVqhSBgYGsW3dnWtS1a9cswcPq1ast6efOnePgwYO8+OKLlrRly5bRqFEjnJycaNWqFbly5WLJkiWMGjWKnTt3snz5cpsyq1evjp+fH507d+bq1av4+voybNgwPvroI0qWLEnXrl1xd3fn2LFjrFq1iujoaPLnz8+gQYOIiIjg8uXL9O3b13K9cuXKJdm2oKAghg8fTo8ePShZsiRvvPGGTZ6IiAgiIiIoWrQob7/9Np6enqxcuZL+/ftz4MABpk6dCkBkZCSlSpUiLCyMypUrExQUxKFDh+jcuTM5c+Zkxgzz2p7evXszaNAgoqKiGD58uKWc2rVrp/YjsfHDDz8QGxtLy5YtyZ07N8HBwQC0b9+eCRMmUK5cOd577z2cnJxYsGABXbp04eTJkwwcOPCBy5R0dvMWxMTZpt24CedirdP9PM2jadfiwTWJW66bi/nrtRRGpBOPuToncb7znTxJHT9zCV4ZCQUDoedLyZchIiIiDkfB2mOoQoUKLF68mNjYWLy9vVm8eDHx8fHUqlWLNWvWEB8fj4uLC/PnzychIYFatWpZzn3vvfe4desWy5Yt47nnngNg0KBB1KxZkxUrVjBjxgxatWplVV7hwoVtgrj//e9/uLm5sW3bNlxcXJKsZ1hYGF999RXx8fF07979vu3y9fWle/fu9OjRg3z58tmcc/DgQQYOHEiNGjVYuXKlJX3AgAGEhoYyffp0evbsSZkyZQgICGDSpEk0btyY5s2bs27dOpo3b05cXBxz5swhe3bzCMYrr7zC5MmTiYqKSlUdU+Ps2bPs2rWLAgUKWNJWrFjBhAkTaNu2LRMnTrSkDxkyhKpVqzJixAjef/99cuTIkS51kIe0dg/U7Gubvm4v/LzGOu3wdxAcCO4ucOOW7TnX/w3E3JP+d2J1LKnRs+s3kz//6nVoNBguX4M1g2zXsomIiIhD0zTIx9ALL7zA7du3+d///gfAokWL8Pb2pmfPnly/fp1ly5YB5lE0k8nESy+9BMDRo0fZs2cPVapUsQRqAFmyZKF///4AzJw506a8jz/+2CbNy8uL+Ph4Jk6cSEJCQno3MUnjxo3j1q1bvP3220RHR1u9mjZtimEYzJs3z5K/fv36dOnShU2bNlG6dGn++usvunXrxgsvvGDXejZo0MAqUEusu8lkonPnzjZ1b9iwIdevX2fx4sV2rZfccev2bcv3sbGx7Ny50+r4xutnYFk/y2vXly3hyQJQ5ylY1o+oUaHcXvyJ+XguX6Kiorid09synTE6OtoyHTgxbf9V62mQd4+OW6Y/nryzvnHDhg3cvn3bnObnSdTB/VbrH6MPHeFagwj4+yjM701s/uw27bAqI4n3ljL+FRUVZV3G3e1Ipq9UhspQGSpDZagMlZH8+/sxGYZhpOkMcXiHDx+mUKFCvPbaa0yZMsUyNXL58uX4+PjQtm1bxowZQ8GCBS35wRzUNWjQgPbt2zN+/Hira167dg0PDw/KlSvH5s2bAfOatSVLlhATE4O3t/XGBVu3bqV+/fqcOXMGT09PypQpQ926dXnnnXesRodKly7NqVOnOHv2bKrbZzKZqFu3rk3w0rRpU6tgLCkdO3bk22+/tbxPSEigdOnSREVFUbZsWTZv3kyWezaASGxnUv9Ukqv/zp07KV26NG+99ZblMQOzZs2iZcuWhIeHM2DAAKv8FSpU4M8//0yx7kOHDk3VYw5iY2Px8fEh5okwvA+kvl/lX8XymrfHz+OXtvNqfGIeQZv4btLHWw6HP3bDiXHWm4yEfQtTV8OFyUlPY0wU2A5qhMDMe0Z4i3WBoBywIuJOWkKCeerjrPXm/HfvQCkiIiKZhqZBPoYKFixIUFAQ69evJzY2ln379hEaGoqTkxNlypRhzZo1HD9+nKNHj9pMaXwQ9wZqAGXLluXw4cPMnDmTJUuWsHnzZvr27cvIkSNZuXIlTz311EOXe6/EYGro0KHky5cvyTwlS5a0er9z505LsBodHc3FixfTNNXw3s1NEt27GcvdsmXLZpNmGAYmk4nJkyfj5OSU5HkVK1ZMdb3EAbWoYg6e5myAFlXNaediIXIdNC5vHagdPGX+WjjXnbTmVWDSb/DPOcjnb05b8bd5F8n3G1uX9e44mLEWvu+oQE1ERCQTU7D2mKpUqRJz5sxh4sSJ3Lp1y7KJSPXq1Rk+fDjTp0/HMAzLrodwJ5DZu3evzfU2b96MYRjkz58/1XXIli0b7dq1o127dgBMnDiRN954g/79+1uek5ZcsPMgnnjiCQBy5sxJ69at75s/Pj6eli1bkpCQQK9evRg6dCitWrWyWX+XUh29vb3Zv3+/TXpUVFSa6l6wYEG2bNnCE088QeXK+uX6sdSiClQuCm98DVHR4O8F3yyG2wkQ8bJ13hf+3b30yPd30vo0Nwd2NftC14Zw5ToMnw+lC8Abz9/J9+Uv5utWKQbZXOGn362v3bQSeLjZp40iIiKSrrRm7TFVq1YtDMNg2LBh5MiRwzKS1bhxY27dusWoUaPIkiULTZo0sZxToEABihcvzvr161m7dq0lPSEhgU8//RSA0NDQVJUfHW378N3EdXCXLl2ypLm7u3P16tU0rWtzdXW1ukait956i6xZszJw4EAuX75sc/zs2bPExd3Zwa9Dhw7s27ePfv36MWTIEFq3bs2KFSsYOnSo1XkeHh4AnDhh+xyswoUL26wnu337NiNHjkx1exLrAvDhhx8mOSqXOPonmZiTEywMN2+fP3oB9Jhsfu7Zygjz1Mv7yecPvw8wj7b1+gmGzYMGZc3r4u4elfvriPnr+r3w+ijb19nYpK4uIiIiDkhr1h5Tp06dIk+ePBiGQb169Vi0aJHlmK+vLzExMRQtWtRmFC1x6/6sWbNabd2/detWXnjhBatRp5TWchUqVAgvLy8qVqxI/vz5uXjxIrNmzSI6Opoff/zRMtrWuXNnvvnmG5o2bUq1atVwcnKiadOmNhtw3O3pp58mKiqKjh07EhwcjMlkolu3bgAMHjyY8PBwcuTIQZMmTQgODubMmTPs2rWLtWvXsmXLFkJCQpg2bRqvvfYazz//vKVNN27cICQkhH/++Yd169ZRtmxZAEaMGEH37t2pUaMG9evXx8XFheeff54nn3ySv//+m7Jly+Lt7U2bNm1wcXHh119/5fbt2+zbty/JNWuDBw+md+/eNu16++23+eGHH8iXLx8NGjQgb968nDhxgu3bt7Np0yZu3UpiJ8EkaM3aQ3rQNWsiIiIi6UzTIB9TuXLlomDBghw6dIiaNWtaHStfvjwrVqygatWqNufVrl2bpUuX0rt3b2bOnMmNGzcIDAyka9euVs8Zu5927doxd+5cIiMjuXLlCp6enhQpUoQRI0bQsmVLS74hQ4Zw5MgRVqxYwbx58zAMg6CgoBSDtfHjx9OhQwd++OEHrl+/DmAJ1vr06UNISAhDhw4lMjKSuLg4vLy8yJcvH126dCE4OJijR4/yzjvvEBgYaHmeGphH7CIjI6lSpQqhoaHs2LEDd3d3unXrxpYtW1i8eDG///47hmEwePBgnnzySZ588knGjRtHREQEY8aMwdPTk0aNGvHee++leY3Z999/T+XKlfn666/56aefuHHjBt7e3hQsWDDJHTdFRERE5PGmkTWRx4xG1h6SRtZERETEQWjNmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiIiIiDkjBmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4ID0UW+RxFewPTi4ZXYvMp2BgRtdAREREBFCwJvL4+vot8PLO6FpkTh6uGV0DEREREQVrIo+t3H7grWBNREREJLPSmjUREREREREHpGBNRERERETEASlYExERERERcUAK1kRERERERByQgjUREREREREHpGBNRERERETEASlYExERERERcUAK1kRERERERByQgjUREREREREHpGBNRERERETEASlYExERERERcUAK1kRERERERBxQ1oyugIjYyckLcOVWRtfCfjxcwccjo2shIiIiYjcK1kQeV13Gwj+xGV0L+ygYCOM7K1gTERGRx5qCNZHH1ZFzcOBsRtdCRERERB6Q1qyJiIiIiIg4IAVrIiIiIiIiDkjBmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiIiIiDkhb94uI3OvSVeg5GeZuhLgbULEIjGgLZQun7vzd0fD+j7BmD7hkhYbl4It2EOBzJ8+eaPhxJSz9Cw6eAk83KFsIIl6G8k/Yo1UiIiKSyWhkTUTkbgkJ0HAgTPsDutSHYW3gTAzU6Av7T9z//Ohz8Fw4HDgFg1+F7k1gwRaoHQHxN+/kG7ccxi6D8oVhRDv4oAnsPQGVe8Hy7XZrnoiIiGQeGlkTG0OGDOHixYsMGzYso6uS6fTs2ZPs2bPTu3fvjK6KJKfGJxAcCBPfTfr4rPWwbi9EdocWVc1poVWhaBfoNwOmvZ/y9QfPhqvXYctwyB9gTqtYxBysTfwNwuqY01o/C5+2Ak/3O+e2fwFKvAufzoBaZR6unSIiIpLpaWRNbEybNo0JEyZkdDUypQkTJjBt2rSMroY8jFnrIacvNKt8Jy3Axxywzd8EN24meyoAszdAo/J3AjUwB15F88DMdXfSyhW2DtQAcnjBsyXN0yhFRETkP0/B2n/A5cuXiY+Pz+hqSBLOnz+f0VWQe207bF47luWe22PFIub1a/tSmAp5/Lx5ymT5JNa2VSwC2w7dv/xTF8HfO211FhERkceSgrVHYNeuXZhMJt566y2r9HLlymEymejRo4dVetGiRcmbN69V2urVq6lWrRqenp44OzsTFBREt27duHnT+q/89erVw2QycezYMerXr4+Pjw8+Pj7s27cPgGHDhlGkSBGyZcuGq6srgYGB1KpVi2PHjgEQEBDAzp07OXfuHCaTyfKaNWtWim2cMGECISEheHl54eLigr+/P8888wx//vknAKGhoZhMJrZu3Wpz7sGDB3FycqJ+/fqWNJPJRL169Zg5cybFihXD1dUVPz8/unbtCsCpU6do2LAh3t7euLq6UqlSJQ4cOGB13bCwMEwmE+vXryc0NBRfX19cXV0pU6YMmzdvBuDbb7+lUKFCuLi4EBAQQERERJLtmz59OmXLliVbtmw4OztToEAB+vXrZ5XHZDJx7tw5du7cadV3O3futPRt6dKlWblyJeXKlSNbtmyUKFGC7777DpPJRP/+/ZMsO1++fOTKlYuEhIQUPwNJJycvQu7stumJaScupHzu3XnvPf/ClZRH5v6IgvX7oFW11NdXREREHltas/YIlCpVisDAQNatuzMF6tq1a5Zf6levXm1JP3fuHAcPHuTFF1+0pC1btoxGjRrh5OREq1atyJUrF0uWLGHUqFHs3LmT5cuX25RZvXp1/Pz86Ny5M1evXsXX15dhw4bx0UcfUbJkSbp27Yq7uzvHjh1j1apVREdHkz9/fgYNGkRERASXL1+mb9++luuVK1cu2fbNnj2bN998k/z58xMWFkb27Nk5fvw4f/zxBzt37qR8+fJ07dqVyMhIRo0axaRJk6zOHzVqFAkJCbzzzjtW6Xv27KF9+/Y0b96cVq1aMW/ePEaPHo2bmxuRkZHkyZOHrl27sn//fiIjI2nRogV//fWXTf1ef/11smXLRqdOnTh79ixTpkyhQYMG9OjRg8GDB/Pyyy/j5+fH9OnT+fTTT3nqqaes+j8iIoKIiAiKFi3K22+/jaenJytXrqR///4cOHCAqVOnAjB8+HD69++Pl5cX779/Z11TUFCQ5fvTp0/TuHFjnn/+eZo0acLly5dp3749vXr1YurUqVZ9DrBw4UKio6Pp3LkzWe4d6ZH7u3kLYuJs027chHOx1ul+nubRtGvx4JrErdHNxfz1Wgqj1InHXJ2TON/5Tp6kjp+5BK+MhIKB0POl5MsQERGR/w5DHomGDRsaTk5ORkxMjGEYhjFnzhwDMGrVqmW4ubkZN27cMAzDMMaNG2cAxpgxYyznFi9e3MiSJYvx+++/W9Ju375tPPfccwZg/Pzzz5b0unXrGoDxwgsv2NShWrVqVmUlJyQkxPD3909121q1amUAxpEjR1LMV6xYMcPX19eIj4+3Ss+VK5eRN29eqzTAMJlMxsKFCy1pcXFxho+Pj2EymYwWLVokWYdNmzZZ0t566y0DMCpWrGjcvn3bkt6rVy8DMNzc3Izdu3db0o8ePWpkzZrVqFmzpiXtwIEDNmmJWrZsaZhMJuOvv/6ypPn7+xshISFJtt/f398AjP79+9sca9u2rQEY69ats0pv2LChkSVLFmP//v1JXjMpMTExBmDEPBFmGDR9PF/FuhjG8fP374zfdqT+modPm8/xaG0Y7b+2vdaCP835Fm9NvrzN+815Jv9me6zHJPOx6/G2x65cM4wKPQzD51XD2JHyvyMRERH579Cf6h+RF154gdu3b/O///0PgEWLFuHt7U3Pnj25fv06y5YtA8yjaCaTiZdeegmAo0ePsmfPHqpUqcJzzz1nuV6WLFks0+ZmzpxpU97HH39sk+bl5UV8fDwTJ05M1yl1Pj7mZ0eNHz8+xbVxbdu25dKlS0yePNmSNnfuXE6dOkWrVq1s8hcrVsxqaqS7uzslSpTAMAz69OljlbdGjRoA7Nixw+Y6Xbt2tRqVql27NgDVqlWjePHilvT8+fOTN29ey5RQgHHjxnHr1i3efvttoqOjrV5NmzbFMAzmzZuXbJvv5eHhQa9evWzSP/jgA0wmE6NHj7akXbp0iRUrVlC+fHmeeELP3UrKlStXLNNME909gk2ZYHZ92RKW9bO8rj4RgFG7jOX90XHtuDznQ8jlC8DNAC+uHbqzLi02NtZcRuIUxzx+1mXcXea/0x+PbtzO7du3LcejoqK4cfSUefTO1Zno6Og7P2fxN7nVZDAJ24/A/N4QUsC2HUm837Bhg00ZFy9etLy3KuPudqRwTZWhMlSGylAZKkNlPNoy7sdkGIaRpjPkgRw+fJhChQrx2muvMWXKFMvUyOXLl+Pj40Pbtm0ZM2YMBQsWtOQHc1DXoEED2rdvz/jx462uee3aNTw8PChXrpxlDVa9evVYsmQJMTExeHtbb1KwdetW6tevz5kzZ/D09KRMmTLUrVuXd955hxw5cljylS5dmlOnTnH27NlUte348eM8++yzHD58GDc3N0JCQqhVqxadOnUif/78lnyXL18mZ86cPPXUU5Yf1Lp167Jy5UoOHjxolddkMlGrVi1LEJsosX3x8fE4O9+ZSjZr1ixatmzJZ599xkcffQSY16yNHTuWbdu28dRTT1ny7ty5k9KlSyfZp6VLl+b06dOcOXMGgKZNm943GOvYsSPffvstYF6XlitXriSDxoCAAHx9fdm/f3+S1ylbtiwHDhzg7NmzuLq6MnjwYD7++GO+//57wsLCUqzD3WJjY/Hx8SHmiTC8D6TuM8x0iuWFlRGQxy/t595v6/6Ww+GP3XBinPUmI2HfwtTVcGFy0tMYEwW2gxohMLP7PXXuAkE5YMVd6yITEsxTH2etN+e/ewdKERER+c/TyNojUrBgQYKCgli/fj2xsbHs27ePGjVq4OTkRJkyZVizZg3Hjx/n6NGjVK788L+w3RuogTkYOHz4MBMmTKBRo0acOnWKvn37UqRIkSTXeqVW3rx52bt3L5GRkbz88svExcUxdOhQSpQowYIFCyz5vLy8qF+/Phs3buTw4cOcO3eOVatWUaVKFatALZGTk1OyZd4dqN0tqRHDrFmTXpqZ3PXv/vtF4vdDhw5l2rRpSb46duyYbD3v5ebmluyxN998k8uXL1sCyJ9++gkfHx/atWuX6utLOmhRBU5fgjkb7qSdi4XIddC4vHWgdvCU+XW35lXg1z/hn3N30lb8bd5FsmVV67zvjoMZa+GbMAVqIiIiYkMbjDxClSpVYs6cOUycOJFbt25ZNrGoXr06w4cPZ/r06RiGQZ06dSznlCxZEoC9e/faXG/z5s0YhpFkoJOcbNmy0a5dO0sAMHHiRN544w369+/PnDlzAPOoVlo5OzvTokULWrRoAZh3r6xZsyYRERE0bNjQkq9r167MmTOHUaNG4evrS3x8vM0umY4kcfphzpw5ad269X3zP0jfJerQoQN9+vRhwoQJVKhQgd27d/P666/j4uLywNeUB9CiClQuCm98DVHR4O8F3yyG2wkQ8bJ13hf+3RH0yPd30vo0Nwd2NftC14Zw5ToMnw+lC8Abz9/J9+Uv5utWKQbZXOGn362v3bQSeCQf3IuIiMjjTyNrj1CtWrUwDINhw4aRI0cOy9S8xo0bc+vWLUaNGkWWLFlo0qSJ5ZwCBQpQvHhx1q9fz9q1ay3pCQkJfPrpp4B5W/zUiI62fdBu4jq4S5cuWdLc3d25evVqqte1JXXdChUq4OLiQkxMjE15RYoUITIykqlTp5IjRw5eeeWVVJWTEd566y2yZs3KwIEDuXz5ss3xs2fPEhd3Z7dBNzc3YmNjbfKlhqurK02aNGHLli2WqZzdunV7oGvJQ3BygoXh5u3zRy+AHpPNzz1bGWGefnk/+fzh9wFQOBf0+gmGzYMGZc1r5O4elfvriPnr+r3w+ijb19kH+zkSERGRx4dG1h6hl156iXfeeYfjx49Tr149S3qVKlXw8fEhOjqaokWLWq0fAxg9ejSNGjWiTp06Vlv3b926lRdeeCHJzTmS8txzz+Hl5UXFihXJnz8/Fy9eZNasWZhMJtq0aWPJV758eTZt2kSLFi2oVq0aTk5ONG3alAIFCiR53VatWnH69GmeffZZgoODiYuLY/78+Vy/fj3JurVp04ZPPvkEMAdDKU13zGjFihUjIiKC8PBwChUqRJMmTQgODubMmTPs2rWLtWvXsmXLFkJCQgB48sknWbhwIW+++SalSpUiS5YstGvXDl9f31SV98EHHzB16lR+++03QkJCKFu2rB1b9x+1asD982T3hHGdza+U3D2idrdS+WFJ36SPJZr4bvLr5kRERERQsPZI5cqVi4IFC3Lo0CFq1qxpdax8+fKsWLGCqlWr2pxXu3Ztli5dSu/evZk5cyY3btwgMDCQrl27Mnz48FSX365dO+bOnUtkZCRXrlzB09OTIkWKMGLECFq2bGnJN2TIEI4cOcKKFSuYN28ehmEQFBSUbLD22muvMWnSJObPn8/ly5dxd3cnf/78jBkzxubZaQBdunRh8ODBXL9+3fKQa0fWp08fQkJCGDp0KJGRkcTFxeHl5UW+fPno0qULwcHBlrxjxozh1VdfZcaMGcTFxWEYBrVq1Up1sPb0009TunRp/v77b15//XX7NEhEREREMgXtBimPXFxcHIGBgRQrVowtW7ZkdHUcToUKFYiKiuLUqVN4eXml+XztBikiIiLyeNCaNXnkRo4cydWrV3nzzTczuioOZ9u2bWzZsoX69es/UKAmIiIiIo8PTYOUR2b8+PEcPHiQr776iqCgIIfeBfJRW7RoEX/99Rdjx44la9asls1jREREROS/S8GaPDK9evXi4sWLFC5cmAkTJiT7rLT/olGjRrF06VICAwMZNWqUZcMSEREREfnvUrAmj8zZs4/p+ql0sHjx4oyugoiIiIg4GK1ZExERERERcUAK1kRERERERByQgjUREREREREHpDVrIo+rYH9wcsnoWthHwcCMroGIiIiI3SlYE3lcff0WeHlndC3sx8M1o2sgIiIiYlcK1kQeV7n9wPsxDtZEREREHnNasyYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiIiIiDkjBmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiIiIiDkjBmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiIiIiDkjBmoiIiIiIiAPKmtEVEBE7OXkBrtzK6Fo8PA9X8PHI6FqIiIiIPHIK1kQeV13Gwj+xGV2Lh1MwEMZ3VrAmIiIi/0kK1kQeV0fOwYGzGV0LEREREXlAWrMmIiIiIiLigBSsiYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOCAFayLy33XpKoR9CwHtwKM11OwLWw+m/vzd0VCvP3i+An5t4PVRcDbGNt+gWdBkMOR8A0zN4NOf060JIiIi8vhSsCbyAIYMGYLJZGLWrFkppokDS0iAhgNh2h/QpT4MawNnYqBGX9h/4v7nR5+D58LhwCkY/Cp0bwILtkDtCIi/aZ03fBpsPgBPF7RPW0REROSxpIdii8jjqcYnEBwIE99N+vis9bBuL0R2hxZVzWmhVaFoF+g3A6a9n/L1B8+Gq9dhy3DIH2BOq1jEHKxN/A3C6tzJe/g7c13OxZpH8URERERSQSNrIumke/fuXL58maZNm2Z0VSQ1Zq2HnL7QrPKdtAAfc8A2fxPcuJnsqQDM3gCNyt8J1ABqlYGieWDmOuu8wYHpVm0RERH571CwJv8JN27c4MqVK3Ytw9nZGU9PT5ycnOxajqSTbYehbCHIcs9tsGIRiLsB+1KYCnn8vHnKZPnCtscqFoFth9K3riIiIvKfpGDtPyZxXdWMGTPo2LEj/v7+uLi4ULRoURYuXAjA7NmzKVmyJK6urvj6+tKpU6ckr7Vs2TKqVauGl5cXzs7O5MmTh86dOxMfH2+Vb/HixdSrV4/cuXPj6uqKm5sbJUqU4LvvvrO5Zr169TCZTJw9e5aXXnoJb29vnJ2dKVGiBIsWLUpVG8PCwjCZTKxbt46XX34ZPz8/3N3dWbx4MQCjR4+mcuXK+Pv74+zsjJeXF1WrVmX16tVJXq9///7kzZsXZ2dncuXKRc+ePTEMI9m+vXvNWmJddu7caZM/ICCA0qVLW6VNmDCBkJAQvLy8cHFxwd/fn2eeeYY///wzVW2XNDh5EXJnt01PTDtxIeVz78577/kXrtx/ZE5ERETkPrRm7T/q448/JiEhgXbt2hEfH8/EiRNp3rw5o0aN4oMPPqB58+a0aNGCefPm8d1331G4cGG6d+9uOX/ChAmEhYWRK1cu2rVrR44cOdiwYQPffvstO3bssAp8pk+fzuHDh6lfvz7BwcGcO3eO2bNn06lTJ+Li4vjggw9s6vfMM8/g6+tLly5dOH/+PFOmTCE0NJQjR46QI0eOVLXx1VdfxcXFhTfffBOTyUSBAgUA+P777/Hx8SE0NJTcuXNz4MABZs+eTZ06dVi3bh1ly5a1XKNnz54MHz6c4OBg3nvvPeLi4hg3bhy+vr4P2PPJmz17Nm+++Sb58+cnLCyM7Nmzc/z4cf744w927txJ+fLl073Mx8bNWxATZ5t246Z5ndjd/DzNo2nX4sE1iVugm4v567V422OJEo+5OidxvvOdPEkdFxEREUklBWv/UQkJCezatQt3d3cASpcuTVhYGJ06dWLx4sXUrl0bgN69e5M7d27Gjh1rCdauXLnC+++/T9GiRdm2bRsuLi6W6/bo0YPPP/+cWbNm0aJFCwBGjRplE9wMHDiQ4sWL88UXXyQZrJUsWZK5c+da3pcuXZp3332Xr776ik8//TRVbfT09GTLli1W9QNYu3atTX06derEs88+y4ABAyzlnj59mlGjRpE3b162b9+Ot7c3AN26daNMmTKpqkNaREZGYhgGv//+uyWwlFRau8e87f691u2Fn9dYpyVu9uHuAjdu2Z5z/d9AzN3F9liixGNJjZ5dv3n/80VERERSQdMg/6PatWtnCdQAGjduDECxYsUsgRqAu7s7JUqU4MSJO+t3ZsyYQUxMDK+++ipnzpwhOjra8goNDQXg119/teS/OzCKjY3l+PHjxMbGUrFiRY4fP865c+ds6vfJJ59YvU/ctGPfvn2pbuO7775rE6jdXZ+EhATOnTtHdHQ0QUFB5MmTh7///tuqnfHx8bRr184SqIG5j+rUqXPvZR+aj48PAOPHj7eZSvpflpCQYPk+OjqaY8eOWd7Hxsaap5iWCYZl/WBZP3Z92dL8/ZMFoM5Td97/+9p4dB+3b982T1c8eZGoqCguXrxoueaFqH/Xm+Xxsy7jLn8e//dZbP9Oh1y37q4NRU5e5Ka3G7ez3rm93ltGbGxs0u24i9U1k3i/YcMGczuSKSPZvlIZKkNlqAyVoTJUhsOUcT8mI6nFN/LYGjJkCH369OHnn3+mVatWVsdMJhO1atVi2bJlVun16tVjyZIllnVa3bp1Y9SoUSmW06BBAxYsWADA0aNH6dKlC6tXryY2NtYmb1RUFCVKlLAqKz4+Hmdn6ylkJpOJevXq3XftWlhYGGPHjmXdunVUqVLF5vjKlSvp3bs327dv58aNG1bHAgICOHPmDADvvfceX331VZJ99dFHHzFs2DAiIyMtI4iJfXt3WmJdduzYQUhIiE1ZuXLlYseOHQAcP36cZ599lsOHD+Pm5kZISAi1atWiU6dO5M+fP8U23y02NhYfHx9ingjD+8DZVJ/nkIrlhZURlsApTe63dX/L4fDHbjgxznqTkbBvYepquDA55WmMge2gRgjM7G6dXqwLBOWAFRG25yRu3d8vFD59Oa0tEhERkf8YTYP8j0pux8LU7GSYGLS9//77VKhQIck8wcHBgHlUpEaNGkRHR9OqVSsqVqyIn58fTk5OjB8/nhUrVlj9xSLRvYHavWWnhpeXl03a7t27adCgAdmyZePtt9+mVKlSeHp6YjKZ+Oijj7h27Vqqr58aJpMp2WP3tjtv3rzs3buX+fPns2DBAjZt2sTQoUMZPXo0M2fOpGHDhulat/+8FlXM2/fP2XDnOWvnYiFyHTQubx2oHTxl/lo415205lVg0m/wzznI529OW/G3eRfJ9xs/mjaIiIjIY03BmqRZ8eLFAfOasNatW6eY948//uDIkSN06NCBsWPHWh374Ycf7FbH5EycOJEbN24wZcoUWrZsaXWsU6dOVkHiE088AcCOHTtsRtZ2796dqvL8/MwjQqdPn7YaWbty5QqXLl0ib968VvmdnZ1p0aKFZWRu9erV1KxZk4iICAVr6a1FFahcFN74GqKiwd8LvlkMtxMg4p5Rrxf6mb8e+f5OWp/m5sCuZl/o2hCuXIfh86F0AXjjeevzp6yCo2fNjwQAWB0FAyPN379eHQroOWwiIiJiS2vWJM1at26Nt7c333zzjdVatkSXL1/m/PnzAGTNav57wL0jYmvXrmXNmjU259pb4sjhvfXp378/MTExVmmhoaG4uLgwceJEq+mbe/fuZenSpakqr1SpUgD88ssvVum9e/e2qUN0dLTN+RUqVMDFxcWmbpIOnJxgYTi0qgajF0CPyeDvbZ52WSzv/c/P5w+/DzCPtvX6CYbNgwZlzWvj7p0+OX4FfDIdhswxv/9tp/n9J9Ph8Jl0b5qIiIg8HjSyJmnm6+vLmDFjaN++PcWLF+fFF1+kSJEiXLx4kX379rFq1SomTZpEixYtqFixIvny5WPSpEnExcVRvHhx9u7dy5w5cyhQoAAHDx58pHUPDQ1lxIgRdOzYkT/++AM/Pz/WrVvH+vXryZkzp9XUxFy5ctGlSxe++OILypQpQ/PmzYmLi+Pnn38mT548HD58+L7ltWrVio8++ogxY8Zw/vx5ChUqxNq1a9m5c6fNNM1WrVpx+vRpnn32WYKDg4mLi2P+/Plcv37dZmRPUmHVgPvnye4J4zqbXym5e0TtbqXyw5IkdqF8kLqIiIiI3EPBmjyQ1157jYIFC9KvXz8WLFhAbGwsHh4e5M6dmzZt2lC1qnkNkLOzM4sWLaJTp078+uuvzJ49m/z58zNy5Ei2bt36yIO1p556ip9//pmPP/6YsWPHkiVLFkJCQliyZAkdO3bk1KlTVvlHjBiBl5cXP/zwA6NGjSJHjhx06NABX19fPv744/uW5+zszPz583n77beZOXMmTk5OVKhQgT/++MPSR4lee+01Jk2axPz587l8+TLu7u7kz5+fMWPG8M4776RrP4iIiIiI49NukCKPGe0GKSIiIvJ40Jo1ERERERERB6RgTURERERExAEpWBMREREREXFACtZEREREREQckII1ERERERERB6RgTURERERExAEpWBMREREREXFAeii2yOMq2B+cXDK6Fg+nYGBG10BEREQkwyhYE3lcff0WeHlndC0enodrRtdAREREJEMoWBN5XOX2A+/HIFgTERER+Y/SmjUREREREREHpGBNRERERETEASlYExERERERcUAK1kRERERERByQgjUREREREREHpGBNRERERETEASlYExERERERcUAK1kRERERERByQgjUREREREREHpGBNRERERETEASlYExERERERcUAK1kRERERERBxQ1oyugIjYyckLcOVWRtdCREREJG08XMHHI6Nr4RAUrIk8rrqMhX9iM7oWIiIiIqlXMBDGd1aw9i8FayKPqyPn4MDZjK6FiIiIiDwgrVkTERERERFxQArWREREREREHJCCNREREREREQekYE1ERERERMQBKVgTERERERFxQArWREREREREHJC27hcRERERkcffpavQczLM3QhxN6BiERjRFsoWvv+5m/bDxJWwcT/8fRRu3QZjTvL5T1+CvtPh1y1w/jLk8oUXnjQ/Qy4NNLKWhL///puqVavi7e2NyWSiXr16GV0luyhdujQBAQEZXQ2L27dvExYWRmBgIE5OTphMpoyukoiIiIg8DhISoOFAmPYHdKkPw9rAmRio0Rf2n7j/+Qu3wLgVYDJBoZwp5/3nHFToCYu2Qcc68E0YdKgFZ2PSXO00B2vbt2+ncePG5M2bF1dXVzw8PMibNy9169YlMjIyzRVwRK+88grbt2+nQ4cODB8+nHfffTfZvH/++ScdOnSgWLFieHt74+bmRsGCBencuTOXLl2yyb948WJatmxJiRIlcHNzw2QyMWTIELu1ZciQIfTs2dNu109PQ4cOZezYsVSoUIHBgwczfPhwu5Y3a9YswsLCOH36tF3LERERERE7q/EJtPsq+eOz1sO6vTCxC/RrBZ3rw6r+4JQF+s24//U71YOYKfDncKhdJuW8b38HWZ1g2wj4JBTavwDhLeF/fdLWJtI4DXLZsmU0atQIJycnGjZsSKlSpYiLi+PAgQOsX7+en3/+mZYtW6a5Eo4kLi6OqKgomjdvzhdffHHf/KNHj2bmzJk888wzNGvWDBcXF37//Xe++eYbFixYwI4dO/Dy8rLknzNnDrNnzyZv3rwULFiQPXv22LM5TJs2jVOnTjFs2DC7lpMeli9fjru7O7/88gtZsth/0Hfp0qWMHTuW9957j5w57/MXEhERERHJvGath5y+0KzynbQAHwitCj+thhs3wdU5+fNz+qaunD3RsGireTQthxdcjzcHhM4PtvosTWeFh4cTHx/PqlWrqF69us3xQ4cOPVAlHMnRo0cxDIPs2bOnKv/rr7/OiBEjbKYTtm/fngkTJjBkyBAGDx5sSe/duzfDhg3D19eXMWPG0KVLl3Stv6NKSEggJiYmxX49f/48Hh4ejyRQexTOnz9Pjhw5MroaIiIiIrLtMJQtBPf+nlmxCPywDPadgNIFHr6c5X+bv+b0hRf6wcod5mCtdhn49m0IDkzT5dL0W3F0dDSenp5JBmoAhQoVsny/c+dOTCYTYWFhNvnCwsIwmUzs3LnTklavXj1MJhPHjx+nXr16eHl54ebmRtWqVS1BYEREBHnz5sXZ2Zm8efPyww8/pKnuzZo1I0eOHGTNmpUcOXLQrFkzjh8/blWHkiVLAjB27FhMJhMmk4lZs2Yle93atWsnue6rffv2AOzatcsqvWDBgvj6+qa63smZO3cuTz/9NNmyZcPFxYVChQoxcOBAqzwBAQHs3LmTc+fOWdqSVHsOHDjA888/j4eHB66urpQrV44///zTpsy4uDi6dOlCvnz5cHZ2Jlu2bFSqVImVK1da5Zs1a5Zlemd4eDhBQUG4urry0UcfJdmWxPx///23VV3vXiu4detWateuja+vL1mzZiUgIIBXX33VZqrppk2baNq0Kfny5cPNzQ1XV1cKFy7MgAEDrPLVq1ePsWPHAua1e4llJv68Jv48JuXeut39sz569GgKFy6Mi4sLr776qiXP9OnTKVu2LNmyZcPZ2ZkCBQrQr18/m2v/8ssvlC9fHl9fX5ydnfHz86NChQosXLgwybqIiIiISCqcvAi5kxg0SEw7cSF9ytl/0vw17FtwyQozPoTPXoM1u6HWp+aNTdIgTSNrefPm5cSJE3z77bd06tQpTQWlVvXq1cmZMyfdunVj//79REZGUr9+fRo0aGCZZunm5sbEiRPp1KkTlStX5sknn0zxmmfPnqVChQqcPn2a+vXrU7ZsWbZt28a8efPYuHEjf//9Nzly5ODdd9/lySefZPjw4VSrVo2XXnoJgHLlyqW5HQcPHgQgMDBt0XNqjB8/nrCwMHx8fGjTpg1eXl7Mnz+fTz75hIMHDzJhwgQABg0aREREBJcvX6Zv376W8+9uz40bN3jmmWcICQnhww8/5NChQ8yYMYMXX3yRI0eO4OzsbMlXuXJldu/eTZ06dXjjjTe4dOkSM2bMoH79+vz666/Url3bqp4//PADsbGxtGzZkty5cxMcHJxke8qVK8fw4cMZOXKkVV1LlCgBmKdHNmnShGzZshEaGkpQUBDbt29n5syZbNmyhe3bt+Pq6grAggUL2LJlCzVq1KBQoUJcuXKFX3/9lb59+3LmzBm++so8l/ndd9/lypUrrF27lh49elg+p4oVKz7w57Js2TKmTZtGy5YtrYLyiIgIIiIiKFq0KG+//Taenp6sXLmS/v37c+DAAaZOnQrA5s2badGiBb6+vrz++uvkypWLU6dOsXHjRjZt2kSDBg0euG4iIiIij42btyAmzjbtxk04F2ud7udpHk27Fg+uSYQ+bi7mr9fi06duV66bv+byhQUf3xnJC/KH1l/AtNXQoXayp98rTcFav379ePHFF3nnnXfo378/Tz31FBUqVKBBgwZUrlz5/hdIhSeffJI5c6y3wZwxYwbnz59nz549+Pv7A9CoUSOqV6/OiBEjmDRpUorX7NmzJ6dOnSI8PNxqhCU8PJxBgwbRs2dPxo8fT8OGDSlQoADDhw+nZMmSdO/e/YHacPPmTYYMGUKWLFmSHFl8GDdv3uSjjz7C1dWVTZs28cQTTwDQv39/ypYty6RJk3j33XcpW7YsYWFhfPXVV8THxyfblsuXL9O+fXu+/PJLS1pAQABffvklM2bM4LXXXgPMfbVjxw6mTJliSQPo27cvxYsX54MPPmDHjh1W1z579iy7du2iQIGUh5QLFixI9+7dmTRpUpJ17dChA9mzZ7cE1Ym+++47OnXqxBdffEHv3r0BeP/994mIiLA6f9iwYTz11FOMHz+ezz//HFdXVxo2bMj8+fNZu3Ytbdq0ISQkJMU6psaxY8dYu3at1b+FgwcPMnDgQGrUqGE1AjlgwABCQ0OZPn06PXv2pEyZMsyZM4f4+HgmTZr02O5AKiIiIvLQ1u6Bmn1t09fthZ/XWKcd/s489dDdBW7csj3n+r9BmrtL+tQt8Tqh1aynXLasAq87meuYhmAtTdMgGzZsyKpVq6hbty5xcXEsXryYAQMGUKVKFUqVKsX27dvTcrkkhYeHW72vUaMGAE2aNLEEagDPPfcc7u7uqVont2zZMry8vPjkk0+s0vv27YuXlxfLli176HrfrXXr1uzdu5d33nmHChUqpOu1V6xYwfnz52nSpIklUANwd3fn/fffxzAMfvrpp1Rfz2Qy2UyfbNiwIQBRUVGWtDlz5pAnTx5q1KhBdHS05XX9+nUqVapEVFQUly9ftrpOgwYN7huo3c+aNWs4evQojRs35tq1a1ZlN2jQAFdXV6vP7+4ppleuXOH48eOcPHmS6tWrc+3aNTZv3vxQ9UlJpUqVbP5oMW7cOG7dusXbb79tVffo6GiaNm2KYRjMmzfPqu4zZszgypUrdquniIiIiKPbtm2b1ft169bdeVMmmKhRodxe/Aks6wfL+nG9aC5u1ixleX92WmdOT+1kHuECbuf04fK+Y7bXPHnR/CaPn3UZwIYNG7h9+7blfVRUFBcvXrS8j46O5tixO9eMjY3ltNO/wV9OH+t6OzlBDi/OH7Suw/2keVuSZ555hsWLFwPm9VgLFixg0qRJREVF0bhxY/bu3Yu7u3taL2tRunRpq/eJAdrd6+ESeXh4EBNz/+cVnDlzhiJFiuDiYh0xu7i4EBQUZJmymB7efPNNZs+eTePGjS1T7tLTvn37AJIcCUoMDA8fPpzq62XPnh1PT0+rtFy5cgHmDTISRUdHEx8fT758+ZK91vHjxylevLjlfbFixVJdj+Rs3boVgO+//57vv/8+yTx31/PixYt07tyZpUuXWqUnOnv27EPXKTlJ/Ywm7vb58ssvJ3veqVOnAPPUzJ9//pmJEycybdo0ihcvTo0aNQgLC6NUqVL2qbSIiIiIA3r66aet3letWvXOm+yelHzP+ncrt9w5IH8g1DJvq3/vjhJOZQvh9cdu8/PW/h3xqlq1Kkz8FrK5QtE8VHW1HmS494/wiXtbJAoKCrJ67+3tjXeDqjB6BRy/YF3vePMUzRxN0jaQ82B7SP6rVKlSlCpViu7duxMSEsLu3btZunQpL774YooPNL51K4khyH8lrpG6l5OTU5LphmGkrdJ2FBYWxo8//ki9evUsoyWOLqWdF+/uW8MwyJ8/P5999lmy+e/9gc2WLdvDV/BfrVu3pnHjxkkeu3uDl/r167Np0yYaN25M9erVLQ/Ynj9/PjNmzLD660hKkvv5jY9Pfj5zUu1N7MOhQ4cmG+gm/sPPli0b27ZtY/HixcyfP58NGzbwzTff8O233zJ69Gg6duyYqrqLiIiIyD1aVDFv3z9nA7T4N4A6FwuR66Bxeett+w+a/5BO4VxpL6dGCAT6wNTV0Kf5nTVxE3+D2wn3f0bbPR4qWEuUJUsWypQpw+7duzl69ChwZ3Tm7qHCREeOHEmPYlMtZ86c/PPPP8THx1uNrsXHxxMdHZ0uz9gKCwtj7Nix1K1bl19//dVu288njlbdvZNmosQdHAsWLGhJSyloTovcuXMTExNDaGhosoGzPSSOKDk5OdG6desU854+fZpNmzZRu3Zt5s+fb3Vs0aJFNvlT6pvEKYknTpwgT548lvS///47tVUHsExVzZkz533rn6hevXqWNWt79uyhQoUKDBo0SMGaiIiIyINqUQUqF4U3voaoaPD3gm8WmwOoiHtmQL3w747dR+6a1XX0DEz53fz9nwfMXwdGmr8WCIDXa5i/d3WG4W2g7VfwXDi8Xh2OnYNRC+DZktCsUpqqnaaIYtq0aUmOLFy+fJm1a9cCULZsWQBy5MiBj48PGzduJCEhwZJ3+/btlryPSq1atbh8+TKDBg2ySh84cCCXL1+22cUwrTp27MjYsWOpXbs2CxYssGsw8/zzz5MjRw5++eUXq/V6N27c4Msvv8RkMlltAOLu7s7Vq1etPoMH0bx5c2JiYujRo0eSx9My9TItatasSb58+Zg9e3aSayLj4+M5ceIEAFmzmv/2cO9o68GDB5k7d67NuYnTP0+fPm1zLDEovvcxB/37909T/d966y2yZs1q+Vm719mzZ4mLM+9mFB0dbXO8aNGieHt7J3muiIiIiKSSkxMsDIdW1WD0AugxGfy9YWUEFMt7//MPn4FPpptfG/eb0xLfj19hnbdNTZj+AcTfMpcz5Xd4u7Z5d8g0xglpGlnr1asX77zzDs899xwhISF4eHhw7NgxfvnlF06ePEmdOnV45plnLPlfffVVvvnmGypUqECjRo04fvw4M2fOJH/+/Bw4cCBNFX0Yw4YNs2yGsnXrVp5++mm2bdvGggULyJMnD8OGDXvga4eHh/P999+TI0cOatWqxciRI62O58mTh1deecXyfteuXYwZMwa4s55pwYIF/PPPPwB07tw5xfVJzs7ODB06lLCwMCpUqEBoaKhl6/59+/bRrl07S8AMUL58eTZt2kSLFi2oVq0aTk5ONG3aNM0bfwwZMoTff/+dkSNH8scff/Dss8/i4+PD0aNHWbt2La6urmkedUqNLFmyMGnSJBo3bkylSpVo3LgxpUqV4urVqxw8eJCVK1fy0Ucf0bt3b3LkyMHTTz9t2eq/QoUKHDlyhMjISHLmzGmzaUf16tX54osv6N69O6Ghobi7u1OhQgWqVatGly5d+Pzzz+nVqxdRUVH4+fmxYsUKm+e63U+xYsWIiIggPDycQoUK0aRJE4KDgzlz5gy7du1i7dq1bNmyhZCQED744APWrVtneeyAYRgsWrSIEydOWAXgIiIiInKPVQPunye7J4zrbH6l5EgS+yTUCAFjjm16cl5+xvx6SGkK1oYMGcLs2bPZunUrv/32G3Fxcbi7u1OoUCE6d+5Mr169rPKPHDmSmJgYfv31VwYPHky+fPkYOXIkGzdufKTBWkBAABs3bqRr1678/vvvLFy4EB8fH1566SVGjx5ttR18WiVOPTx//nySD30OCQmxCtZ2797Nt99+a5Vn7dq1ltHG559//r6bSbz55pv4+voycOBAJk6cyK1btwgKCmLAgAE2u2kOGTKEI0eOsGLFCubNm4dhGAQFBaU5WHN1dWX9+vX069ePyMhIS8Dp5+dHqVKleOONN9J0vbSoWbMmGzdupE+fPqxatYq5c+fi5uZGzpw5efHFF2natKkl7/z583n77bf5448/WLRoEblz56Z79+44OzvTp08fq+s2adKErl27Mm3aNMLDw0lISOCtt96iWrVq+Pv7ExkZyQcffMD48eNxc3OjRo0a/O9//7NM8U2tPn36EBISwtChQ4mMjCQuLg4vLy/y5ctHly5dLM+fCw0N5cyZMyxZsoSYmBhcXFzIkycP/fv35+OPP37ofhQRERGRzMVkONIOHSLy0GJjY/Hx8SHmiTC8D9hv90sRERGRdFcsr3lqYh6/jK6JQ7DPLhgiIiIiIiLyUBSsiYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOCAFayIiIiIiIg4oTQ/FFpFMJNgfnFwyuhYiIiIiqVcwMKNr4FAUrIk8rr5+C7y8M7oWIiIiImnj4ZrRNXAYCtZEHle5/cBbwZqIiIhIZqU1ayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOKCsGV0BEUlfhmEAEBsbm8E1EREREZGUeHl5YTKZkj2uYE3kMXP+/HkA8uXLl8E1EREREZGUxMTE4O3tnexxBWsijxk/Pz8Ajh07ho+PTwbXxrHExsaSL18+/vnnnxRvjP9V6p/kqW9Spv5JnvomZeqf5KlvUva49I+Xl1eKxxWsiTxmsmQxL0X18fHJ1Dcve/L29lbfpED9kzz1TcrUP8lT36RM/ZM89U3KHvf+0QYjIiIiIiIiDkjBmoiIiIiIiANSsCbymHF1daVfv364urpmdFUcjvomZeqf5KlvUqb+SZ76JmXqn+Spb1L2X+kfk5G4z7eIiIiIiIg4DI2siYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAm4qD27NlD7dq18fDwIFeuXPTs2ZP4+Pj7nmcYBp999hn58+fH3d2dKlWqsGHDBpt8J06coHnz5nh5eeHn50eHDh2IjY21R1PSnT37Zvny5bz88ssEBweTLVs2SpYsyfDhw7l586a9mpPu7P2zkyghIYFy5cphMpmYNWtWejbBbh5F3yxYsICqVavi4eFB9uzZqVmzJtHR0endFLuwd/+sWbOGmjVrkj17dvz9/alfvz5//fWXHVqS/h60b7755hsaNWpEQEBAiv9WMvM9GezbP5n9vmzvn51EmfGeDI+mfzLzfRlDRBzOhQsXjNy5cxvPPfecsXjxYmP8+PGGj4+P0blz5/ueO2TIEMPFxcX44osvjOXLlxtNmzY1vLy8jIMHD1ryxMfHGyEhIUZISIjxv//9z/j555+NoKAgo2HDhvZsVrqwd9+0aNHCaNCggTFp0iTjt99+M4YMGWK4u7sb7dq1s2ez0o29++du33zzjZEzZ04DMCIjI9O7KenuUfTNlClTDBcXF6N3797GypUrjfnz5xvdu3c39u/fb69mpRt798+ePXsMd3d3o2HDhsaiRYuMefPmGRUrVjT8/PyMkydP2rNpD+1h+qZSpUpGpUqVjDZt2iT7byUz35MNw/79k5nvy/bum7tltnuyYTya/snM92XDMAwFayIOaPDgwYaHh4dx/vx5S9r3339vODk5GcePH0/2vGvXrhne3t5G7969LWk3btwwChQoYHTq1MmSNm3aNMNkMhl79uyxpC1ZssQAjI0bN6Zza9KXvfvm7NmzNucOGjTIMJlMSR5zNPbun0Rnz541/Pz8jB9//DHT/GJg7745f/684e3tbXzzzTf2aYCd2bt/hgwZYri5uRlxcXGWtEOHDhmAMXny5HRuTfp60L4xDMO4ffu2YRiGcfjw4WT/rWTme7Jh2L9/MvN92d59kygz3pMNw/79k9nvy4ZhGJoGKeKAFi1aRK1atfDz87OkhYaGkpCQwNKlS5M9b926dcTGxhIaGmpJc3FxoVmzZixcuNDq+k8++STFihWzpNWuXRs/Pz+rfI7I3n3j7+9vc+7TTz+NYRicPHkynVphP/bun0S9e/emZs2a1KxZM30bYEf27puZM2dy+/Zt3nzzTfs0wM7s3T83b97E1dUVNzc3S5qPjw9gnkbpyB60bwCyZLn/r1qZ+Z4M9u+fzHxftnffJMqM92Swf/9k9vsyaM2aiEPas2cPxYsXt0rz9fUld+7c7NmzJ8XzAJtzS5QowbFjx7h27Vqy1zeZTBQvXjzF6zsCe/dNUtasWYOrqysFCxZ8iJo/Go+ifzZt2sS0adP4/PPP07Hm9mfvvtmwYQPFixdn0qRJFChQgKxZs/LUU0+xaNGidG6Jfdi7f15++WVu3bpFeHg458+f58SJE7z//vvky5ePF198MZ1bk74etG8e5vqZ5Z4M9u+fpGSW+/Kj6JvMek8G+/dPZr8vg4I1EYd08eJFfH19bdKzZ8/OhQsXUjzv3r9cJ55nGAYXL158qOs7Anv3zb3279/PqFGj6NixI56eng9V90fB3v2TkJBA586d+fDDDwkODk7Pqtudvfvm1KlT7N27l08++YQBAwawaNEigoODadKkCbt27UrXttiDvfunSJEirFixgvHjx+Pv70/evHlZvXo1y5cvt4ywOSp73zMz8z0ZHn39M9N92d59k5nvyWD//sns92VQsCYikqzY2FiaNWtGwYIFGTRoUEZXxyGMGzeOU6dO0atXr4yuisNJSEjgypUr/PDDD7Rp04batWsTGRlJUFAQQ4cOzejqZbh9+/bRvHlz6tSpw7Jly/jll18oUKAA9evX5/Tp0xldPckkdF+2pntyyh6H+7KCNREHlD17dmJiYmzSL168aDWvO6nzbty4wfXr123OM5lMZM+e/aGu7wjs3TeJ4uPjadq0KRcvXmThwoV4eHikTwPszJ79c+XKFfr06UN4eDjx8fFcunTJsrV4XFycw28z/ij+XQE8//zzljzOzs4899xzmeIvuPbunz59+pArVy4mT55MrVq1aNSoEb/++isXL15k1KhR6duYdGbve2ZmvifDo6t/Zrwv27NvMvs9GR7Nvy3IvPdlULAm4pCSWqcQExPDyZMnbeZ233sewN69e63S9+zZY3n+UXLXNwyDvXv3pnh9R2DvvgHzX+JeffVVtmzZwqJFi8iXL186tsC+7Nk/586d4/z583Ts2JHs2bOTPXt2ypQpA0Dbtm0pWrRoOrcmfdn7Z6dUqVLJXuPeQMYR2bt/oqKiLD8viTw9PXniiSc4ePBgejTBbh60bx7m+pnlngz27x/IvPdle/ZNZr8ng/1/djL7fRkUrIk4pPr167N8+XIuXbpkSYuMjCRLlizUqVMn2fOqVq2Kt7c3kZGRlrSbN28yZ84cGjRoYHX97du3s3//fkvaihUrOH/+vFU+R2TvvgHo3Lkzv/zyC/Pnz6d06dLp3gZ7smf/5MqVi99++83qNX36dAA+/fRT5syZY59GpRN7/+w0atQIMD/AN1F8fDy///475cqVS8eW2Ie9+6dAgQJs27bNaufH2NhY9u/f7/BrbR60b9Jy/cx6Twb79w9k3vuyPfsms9+Twf4/O5n9vgzoodgijijxIZHVq1c3lixZYvz444+Gr6+vzUMin3/+eaNw4cJWaUOGDDFcXV2NL7/80lixYoXRvHnzZB+KXbp0aeOXX34xZsyYYeTLly9TPIDV3n0zaNAgAzB69OhhrF+/3uoVExPzSNr4MOzdP/dKzfN/HMWj6JvmzZsbAQEBxvjx442FCxcaDRs2NNzc3Iy///7b7u17WPbun3nz5hmA0bp1a2PRokXG3LlzjWeeecZwd3c39u3b90ja+KAepm82b95sREZGGt98840BGB9++KERGRlprFq1ypInM9+TDcP+/ZOZ78v27pt7ZaZ7smE8mv7JzPdlw9BDsUUcVlRUlPHCCy8Y7u7uRmBgoNG9e3fjxo0bVnmqV69uFChQwCotISHBGDx4sBEUFGS4uroalSpVMtatW2dz/ejoaKNZs2aGp6en4evra7Rv397h/9NLZM++qV69ugEk+frtt9/s3LL0Ye+fnbtltl8M7N03V65cMd59910jICDAcHV1NapWrWqsWbPGnk1KV/bun5kzZxoVKlQwvL29DX9/f6N27drGhg0b7NmkdPOgfdO2bdsk7yfVq1e3ypeZ78mGYd/+yez3ZXv/7Nwts92TDcP+/ZPZ78smw3DwJ1GKiIiIiIj8B2nNmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiIiIiDkjBmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiYuXMmTP4+PgwduxYq/R27doRHBycMZV6THz66aeYTCaOHDnySMqbOHGiTXnXrl0jT548REREPJI6iMiDU7AmIiIiVsLDwwkICOCNN95IVf5Tp07RvXt3QkJC8PLywtvbmyJFivDyyy8zZ84cq7w1atTA09Mz2WslBjN//vlnkscvXryIu7s7JpOJKVOmJHud4OBgTCaT5eXi4kJwcDAdOnTgn3/+SVW7Hlfu7u706tWL4cOHc/LkyYyujoikQMGaiIiIWERHR/Pjjz/y7rvvkjVr1vvmP3r0KGXKlGHMmDFUrlyZzz77jCFDhtCoUSP27NnDhAkT0rV+U6dO5caNGxQsWJAff/wxxbxBQUFMmTKFKVOmMGrUKCpVqsSPP/5IpUqVOHfuXLrWK7N58803MZlMfPHFFxldFRFJwf3vwiIiIvKf8f3332MymWjdunWq8n/++eecOXOGefPm8eKLL9ocP3XqVLrWb/z48dSsWZMXX3yRbt26cejQIQoVKpRkXh8fH1577TXL+06dOhEYGMjXX3/NhAkT6NGjR7rWLTPx8PCgWbNmTJw4kYEDB+Lq6prRVRKRJGhkTURE5CEkrglasWIF/fv3p0CBAri7u1OpUiU2bNgAwO+//84zzzyDh4cHuXPnZsCAAUle688//6Rp06b4+/vj6upKsWLFGDRoELdu3bLKt2nTJtq1a0fRokXJli0bXl5eVKtWjblz59pcs127dphMJmJiYizBipubG9WqVWPjxo02+SMjIylfvjyBgYGpav/+/fsBeOGFF5I8nitXrlRdJzW2bt3KX3/9Rdu2bXnllVfImjXrfUfX7lW3bl0ADhw4kGyeRYsWYTKZGD16dJLHq1SpQkBAADdv3gTS9nkkJfEzSorJZKJdu3Y26TNmzOCZZ57By8uLbNmyUalSJWbNmpWq8hLVr1+fc+fO8dtvv6XpPBF5dBSsiYiIpINevXoxb948unbtSr9+/Th06BB16tRh3rx5NGvWjGeffZbPP/+c4sWL07dvX3766Ser8xcsWEC1atXYt28fH374IaNHj6ZKlSr07dvXZpRr7ty57Nmzh9DQUEaNGsXHH3/MhQsXaNasGdOmTUuyfnXr1iU6Opq+ffvSu3dvdu7cScOGDbl8+bIlz+nTp9m7dy8VK1ZMdbsLFy4MwNixYzEMI9XnnTt3LslXXFxcsueMHz8eT09Pmjdvjr+/P40aNWLSpEkkJCSkutzE4NLf3z/ZPHXq1CFXrlxMnjw5yfM3bNjAK6+8grOzM/Bgn8fDCA8P5+WXX8bLy4sBAwbw2WefkS1bNlq2bMmYMWNSfZ0qVaoAsGrVqnSvo4ikE0NEREQe2IQJEwzAePrpp40bN25Y0ufPn28ARtasWY3Nmzdb0m/cuGHkypXLqFy5siXt2rVrRs6cOY1nn33WuHnzptX1v/jiCwMwfvvtN0valStXbOpx9epVo2jRokaJEiWs0tu2bWsARqdOnazSZ86caQDGd999Z0lbuXKlARijRo1Ksq1t27Y1ChQoYJV28OBBw9vb2wCMfPnyGa+88ooxcuRI488//0zyGtWrVzeA+77u7rPEPvL19TXatm1rSZs3b54BGAsXLrQpp0CBAkbx4sWNs2fPGmfPnjUOHTpk/Pjjj4aPj4+RNWtWY8eOHUnWL1H37t0NwNi1a5dVenh4uAEYW7ZssaSl5fPo16+fARiHDx+2pCV+RkkBrNq8ZcsWAzB69+5tk/fFF180vLy8jNjYWEta4s/n3eXdLWvWrEajRo2SPCYiGU8jayIiIumgU6dOuLi4WN4/++yzAFSqVIny5ctb0l1cXKhYsaJlhAdg2bJlnD59mjfeeINLly5ZjTQ1aNAAgKVLl1rye3h4WL6Pi4vj/PnzxMXF8fzzz7N7925iY2Nt6vf+++9bvX/++ecBrOpx9uxZAPz8/FLd7kKFCrF9+3Y6d+4MwLRp03j//fcpX748Tz75JFu2bLE5x83NjWXLliX5ev3115MsZ86cOVy6dIm2bdta0ho0aEBAQECyUyH37NlDQEAAAQEBFCpUiPbt2+Pv78/8+fMJCQlJsV2J5dw9umYYBj/99BMhISGULVvWkv4gn8eDmjp1KiaTibZt29qMSjZp0oTLly+zfv36VF/Pz8+PM2fOpFv9RCR9aYMRERGRdHDvJhfZs2cHoGDBgjZ5s2fPzvnz5y3vd+/eDUD79u2Tvf7p06ct3585c4bw8HDmz5+f5C/aly5dwtvbO8X65ciRA8CqHonrpow0TGcE8zb5X3/9NV9//TUnT55kzZo1TJkyhV9++YVGjRqxa9cuqwDQycmJWrVqJXmtNWvWJJk+fvx4AgICCAoKslpvVqdOHSIjIzl37pzN1Mbg4GDLs+JcXFzIkycPTzzxRKralBiQTZ06lcGDB5MlSxZWr17NkSNHGDZsmFXeB/k8HtTu3bsxDIPixYsnm+fun5X7MQwj2fVyIpLxFKyJiIikAycnpzSl3y0xOBo+fDhPPfVUknny5MljyVunTh12795N165dKV++PD4+Pjg5OTFhwgSmTZuW5Bqu5Opxd2AWEBAAwIULF+5b5+Tkzp2bli1b0rJlS1599VWmTZvGwoULrXZlTKvDhw/z22+/YRgGRYsWTTLPTz/9RLdu3azSPDw8kg0KU6NNmzZ069aNlStXUqtWLSZPnoyTk5NVWx7087hbcsHSvRvLJJZnMplYtGhRsp9pqVKlUt3GixcvWj53EXE8CtZEREQyWJEiRYDUBRd///0327dvp2/fvkRERFgdGzdu3EPVI/GX/LunRj6MypUrM23aNI4fP/5Q15kwYQKGYTB27Fh8fX1tjoeHh/Pjjz/aBGsP65VXXqFHjx5MnjyZatWqMWvWLGrXrk3u3LktedLj80gcdbxw4YLVCOShQ4ds8hYpUoTFixeTP39+SpQo8SDNsjhy5Ai3bt2675RQEck4WrMmIiKSwerWrUtgYCCfffZZkqNa165ds+zamDiacu9UxZ07d6Z6q/jkBAQEUKpUKcsjB1Jj1apVXLt2zSY9ISGBX375BYCSJUs+cJ0SEhKYOHEipUuXpkOHDrRo0cLm1bp1a3bs2MHmzZsfuJykBAQEUL9+febMmcPUqVOJjY21WjMH6fN5JI4WLl++3Cp9xIgRNnkT1/T16dOH27dv2xxPyxTIxM+5evXqqT5HRB4tjayJiIhkMA8PDyZPnsxLL71EsWLFaN++PU888QSXLl1iz549zJkzh7lz51KjRg1KlChBqVKlGDZsGHFxcRQrVox9+/bx/fffU7p06SQ39EiLli1bMmDAAE6ePGk1gpSczz//nLVr19K4cWPKli2Lj48Pp06dYvbs2WzZsoWaNWvSsGHDB67P0qVL+eeff3jzzTeTzdO8eXM+/fRTxo8fT4UKFR64rKS0bduW//3vf3z44Yf4+Pjw0ksvWR1Pj8+jdevW9OnTh7CwMPbs2YOfnx+LFy/m3LlzNnkrVKjAp59+yqeffspTTz1Fy5YtyZMnDydPnmTLli0sXLiQ+Pj4VLVt4cKF+Pv7U7NmzVTlF5FHT8GaiIiIA6hbty6bN2/ms88+46effuLs2bNkz56dwoUL88EHH/Dkk08C5pGcBQsW0L17dyZNmsTVq1cJCQlh0qRJbN++/aGDtbfeeouBAwcybdo0Pvzww/vmDw8PJzIyktWrV7NkyRIuXLiAh4cHJUqUYMSIEXTu3JksWR58Is/48eMBaNasWbJ5QkJCKFq0KD///DMjR47E3d39gcu7V6NGjfDz8+PChQt06NABNzc3q+Pp8Xl4e3uzcOFCPvjgAwYPHoynpyfNmjXjp59+smxUc7d+/fpRvnx5Ro8ezZdffsnVq1cJDAwkJCQk2Qd53+vq1avMmTOHTp064erqmrrOEJFHzmSkdcsnEREReax17NiRpUuXsnfvXsuDnwHatWvHqlWrOHLkSMZVTtJk4sSJvPHGGxw+fJjg4GBLeuLDu/fv35+qEVQRyRhasyYiIiJW+vfvz/nz55kwYUJGV0Xs4Nq1a3z22Wf06NFDgZqIg9M0SBEREbESGBhITExMRldD7MTd3Z2TJ09mdDVEJBU0siYiIiIiIuKAtGZNRERERETEAWlkTURERERExAEpWBMREREREXFACtZEREREREQckII1ERERERERB6RgTURERERExAEpWBMREREREXFACtZEREREREQckII1ERERERERB6RgTURERERExAH9Hw2pk9gaHMmXAAAAAElFTkSuQmCC\n"
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "/usr/local/lib/python3.12/dist-packages/tabpfn_extensions/interpretability/shap.py:137: FutureWarning: The NumPy global RNG was seeded by calling `np.random.seed`. In a future version this function will no longer use the global RNG. Pass `rng` explicitly to opt-in to the new behaviour and silence this warning.\n",
-            "  shap.summary_plot(shap_values=shap_values, show=False)\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 800x950 with 2 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 750x500 with 3 Axes>"
-            ],
-            "image/png": 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\n"
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+       "  <thead>\n",
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+       "      <th></th>\n",
+       "      <th>CRIM</th>\n",
+       "      <th>ZN</th>\n",
+       "      <th>INDUS</th>\n",
+       "      <th>CHAS</th>\n",
+       "      <th>NOX</th>\n",
+       "      <th>RM</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>DIS</th>\n",
+       "      <th>RAD</th>\n",
+       "      <th>TAX</th>\n",
+       "      <th>PTRATIO</th>\n",
+       "      <th>B</th>\n",
+       "      <th>LSTAT</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.00632</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0.538</td>\n",
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+       "      <td>0</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>2.18</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>3</td>\n",
+       "      <td>222.0</td>\n",
+       "      <td>18.7</td>\n",
+       "      <td>394.63</td>\n",
+       "      <td>2.94</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.06905</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2.18</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.458</td>\n",
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+       "      <td>6.0622</td>\n",
+       "      <td>3</td>\n",
+       "      <td>222.0</td>\n",
+       "      <td>18.7</td>\n",
+       "      <td>396.90</td>\n",
+       "      <td>5.33</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
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+       "\n",
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+       "  </svg>\n",
+       "    </button>\n",
+       "\n",
+       "  <style>\n",
+       "    .colab-df-container {\n",
+       "      display:flex;\n",
+       "      gap: 12px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert {\n",
+       "      background-color: #E8F0FE;\n",
+       "      border: none;\n",
+       "      border-radius: 50%;\n",
+       "      cursor: pointer;\n",
+       "      display: none;\n",
+       "      fill: #1967D2;\n",
+       "      height: 32px;\n",
+       "      padding: 0 0 0 0;\n",
+       "      width: 32px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert:hover {\n",
+       "      background-color: #E2EBFA;\n",
+       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "      fill: #174EA6;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-buttons div {\n",
+       "      margin-bottom: 4px;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert {\n",
+       "      background-color: #3B4455;\n",
+       "      fill: #D2E3FC;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert:hover {\n",
+       "      background-color: #434B5C;\n",
+       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "      fill: #FFFFFF;\n",
+       "    }\n",
+       "  </style>\n",
+       "\n",
+       "    <script>\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#df-4590d6cd-2eaa-4ea3-b5f5-7a56b39dda16 button.colab-df-convert');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      async function convertToInteractive(key) {\n",
+       "        const element = document.querySelector('#df-4590d6cd-2eaa-4ea3-b5f5-7a56b39dda16');\n",
+       "        const dataTable =\n",
+       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+       "                                                    [key], {});\n",
+       "        if (!dataTable) return;\n",
+       "\n",
+       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+       "          + ' to learn more about interactive tables.';\n",
+       "        element.innerHTML = '';\n",
+       "        dataTable['output_type'] = 'display_data';\n",
+       "        await google.colab.output.renderOutput(dataTable, element);\n",
+       "        const docLink = document.createElement('div');\n",
+       "        docLink.innerHTML = docLinkHtml;\n",
+       "        element.appendChild(docLink);\n",
+       "      }\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "\n",
+       "    <div id=\"df-c0acb8e2-3622-4d87-aaad-fe39e89d60bc\">\n",
+       "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c0acb8e2-3622-4d87-aaad-fe39e89d60bc')\"\n",
+       "                title=\"Suggest charts\"\n",
+       "                style=\"display:none;\">\n",
+       "\n",
+       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "     width=\"24px\">\n",
+       "    <g>\n",
+       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+       "    </g>\n",
+       "</svg>\n",
+       "      </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
+       "      --hover-fill-color: #174EA6;\n",
+       "      --disabled-fill-color: #AAA;\n",
+       "      --disabled-bg-color: #DDD;\n",
+       "  }\n",
+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
+       "      --hover-bg-color: #434B5C;\n",
+       "      --hover-fill-color: #FFFFFF;\n",
+       "      --disabled-bg-color: #3B4455;\n",
+       "      --disabled-fill-color: #666;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart {\n",
+       "    background-color: var(--bg-color);\n",
+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
+       "    display: none;\n",
+       "    fill: var(--fill-color);\n",
+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    30% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "      <script>\n",
+       "        async function quickchart(key) {\n",
+       "          const quickchartButtonEl =\n",
+       "            document.querySelector('#' + key + ' button');\n",
+       "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "          try {\n",
+       "            const charts = await google.colab.kernel.invokeFunction(\n",
+       "                'suggestCharts', [key], {});\n",
+       "          } catch (error) {\n",
+       "            console.error('Error during call to suggestCharts:', error);\n",
+       "          }\n",
+       "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "        }\n",
+       "        (() => {\n",
+       "          let quickchartButtonEl =\n",
+       "            document.querySelector('#df-c0acb8e2-3622-4d87-aaad-fe39e89d60bc button');\n",
+       "          quickchartButtonEl.style.display =\n",
+       "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "        })();\n",
+       "      </script>\n",
+       "    </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
       ],
-      "source": [
-        "from tabpfn_extensions import interpretability\n",
-        "\n",
-        "# Load example dataset\n",
-        "data = load_breast_cancer()\n",
-        "X, y = data.data, data.target\n",
-        "feature_names = data.feature_names\n",
-        "n_samples_test, n_samples_train = 25, 50\n",
-        "\n",
-        "# Split data\n",
-        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5)\n",
-        "\n",
-        "# Initialize and train model\n",
-        "clf = TabPFNClassifier()\n",
-        "clf.fit(X_train[:n_samples_train], y_train[:n_samples_train])\n",
-        "\n",
-        "# Calculate SHAP values\n",
-        "shap_values = interpretability.shap.get_shap_values(\n",
-        "    estimator=clf,\n",
-        "    test_x=X_test[:n_samples_test],\n",
-        "    attribute_names=feature_names,\n",
-        "    algorithm=\"permutation\",\n",
-        ")\n",
-        "\n",
-        "# Create visualization\n",
-        "fig = interpretability.shap.plot_shap(shap_values)"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "Zt05caATl2Cc"
-      },
-      "source": [
-        "### Embeddings\n",
-        "\n",
-        "This example demonstrates how to extract embeddings from TabPFN models and use them\n",
-        "for classification and regression tasks.\n",
-        "\n",
-        "NOTE: This example requires the full TabPFN implementation (pip install tabpfn).\n",
-        "It will not work with the TabPFN client (pip install tabpfn-client) because\n",
-        "the embedding functionality is not available in the client version.\n"
+      "text/plain": [
+       "      CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
+       "0  0.00632  18.0   2.31     0  0.538  6.575  65.2  4.0900    1  296.0   \n",
+       "1  0.02731   0.0   7.07     0  0.469  6.421  78.9  4.9671    2  242.0   \n",
+       "2  0.02729   0.0   7.07     0  0.469  7.185  61.1  4.9671    2  242.0   \n",
+       "3  0.03237   0.0   2.18     0  0.458  6.998  45.8  6.0622    3  222.0   \n",
+       "4  0.06905   0.0   2.18     0  0.458  7.147  54.2  6.0622    3  222.0   \n",
+       "\n",
+       "   PTRATIO       B  LSTAT  \n",
+       "0     15.3  396.90   4.98  \n",
+       "1     17.8  396.90   9.14  \n",
+       "2     17.8  392.83   4.03  \n",
+       "3     18.7  394.63   2.94  \n",
+       "4     18.7  396.90   5.33  "
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Load the Boston Housing dataset\n",
+    "\n",
+    "import pandas as pd, requests\n",
+    "from IPython.display import display, Markdown\n",
+    "\n",
+    "cols = [\"CRIM\",\"ZN\",\"INDUS\",\"CHAS\",\"NOX\",\"RM\",\"AGE\",\"DIS\",\"RAD\",\"TAX\",\"PTRATIO\",\"B\",\"LSTAT\",\"MEDV\"]\n",
+    "df_boston = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data\",\n",
+    "                        delim_whitespace=True, header=None, names=cols)\n",
+    "X, y = df_boston.drop(columns=[\"MEDV\"]), df_boston[\"MEDV\"]\n",
+    "\n",
+    "display(X.head())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "id": "YaA7WBuEVdQy"
+   },
+   "outputs": [],
+   "source": [
+    "# Alternative datasets (commented for reference):\n",
+    "\n",
+    "# Liver Disorders dataset\n",
+    "# Classification task: Predict liver disorder presence\n",
+    "# Features: Blood test results, alcohol consumption\n",
+    "# Samples: 345 patients\n",
+    "# Target: Binary liver disorder diagnosis\n",
+    "# df = fetch_openml(\"liver-disorders\", version=1)\n",
+    "\n",
+    "# Grid Stability dataset\n",
+    "# Regression task: Predict electrical grid stability\n",
+    "# Features: Power system measurements, grid parameters\n",
+    "# Samples: 10,000 simulations\n",
+    "# Target: Grid stability score\n",
+    "# df = fetch_openml(data_id=44973, as_frame=True)\n",
+    "\n",
+    "# Concrete Compressive Strength dataset\n",
+    "# Regression task: Predict concrete strength\n",
+    "# Features: Concrete components (cement, water, aggregates)\n",
+    "# Samples: 1,030 concrete samples\n",
+    "# Target: Compressive strength in MPa\n",
+    "# df = fetch_openml(data_id=44959, as_frame=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "rWqC16PL7R_T",
+    "outputId": "01d8b6c2-7421-4a10-8a93-984ddeaafb99"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "nj8XPK35l4z1"
-      },
-      "outputs": [],
-      "source": [
-        "if backend == \"client\":\n",
-        "    console.print(\n",
-        "        Panel(\n",
-        "            \"[bold yellow]Text data can only be processed through the TabPFN server. Please restart the notebook and select the 'client' backend to run this section.[/bold yellow]\",\n",
-        "            title=\"[bold yellow]Warning\",\n",
-        "            border_style=\"yellow\",\n",
-        "        )\n",
-        "    )\n",
-        "else:\n",
-        "    import matplotlib.pyplot as plt\n",
-        "    import numpy as np\n",
-        "    import pandas as pd\n",
-        "    import seaborn as sns\n",
-        "    from sklearn.datasets import load_breast_cancer, load_diabetes\n",
-        "    from sklearn.linear_model import LinearRegression, LogisticRegression\n",
-        "    from sklearn.manifold import TSNE\n",
-        "    from sklearn.metrics import accuracy_score, r2_score\n",
-        "    from sklearn.model_selection import train_test_split\n",
-        "    from tabpfn_extensions import TabPFNClassifier, TabPFNRegressor\n",
-        "    from tabpfn_extensions.embedding import TabPFNEmbedding\n",
-        "\n",
-        "    # Load and evaluate classification dataset\n",
-        "    print(\"Loading classification dataset (breast cancer)...\")\n",
-        "    df = load_breast_cancer(return_X_y=False)\n",
-        "    X, y = df[\"data\"], df[\"target\"]\n",
-        "    attribute_names = df[\"feature_names\"]\n",
-        "\n",
-        "    # Split the data\n",
-        "    X_train, X_test, y_train, y_test = train_test_split(\n",
-        "        X,\n",
-        "        y,\n",
-        "        test_size=0.5,\n",
-        "        random_state=42,\n",
-        "    )\n",
-        "\n",
-        "    # Train and evaluate vanilla logistic regression\n",
-        "    model = LogisticRegression(\n",
-        "        max_iter=10000,\n",
-        "        random_state=42,\n",
-        "    )\n",
-        "    model.fit(X_train, y_train)\n",
-        "    print(\n",
-        "        f\"Baseline Logistic Regression Accuracy: {accuracy_score(y_test, model.predict(X_test)):.4f}\",\n",
-        "    )\n",
-        "\n",
-        "    # Train and evaluate TabPFN embeddings (vanilla)\n",
-        "    clf = TabPFNClassifier(n_estimators=1, random_state=42)\n",
-        "    embedding_extractor = TabPFNEmbedding(tabpfn_clf=clf, n_fold=0)\n",
-        "    train_embeddings = embedding_extractor.get_embeddings(\n",
-        "        X_train,\n",
-        "        y_train,\n",
-        "        X_test,\n",
-        "        data_source=\"train\",\n",
-        "    )\n",
-        "    test_embeddings = embedding_extractor.get_embeddings(\n",
-        "        X_train,\n",
-        "        y_train,\n",
-        "        X_test,\n",
-        "        data_source=\"test\",\n",
-        "    )\n",
-        "\n",
-        "    model = LogisticRegression(\n",
-        "        max_iter=10000,\n",
-        "        random_state=42,\n",
-        "    )\n",
-        "    model.fit(train_embeddings[0], y_train)\n",
-        "    y_pred = model.predict(test_embeddings[0])\n",
-        "    print(\n",
-        "        f\"Logistic Regression with TabPFN (Vanilla) Accuracy: {accuracy_score(y_test, y_pred):.4f}\",\n",
-        "    )\n",
-        "\n",
-        "    # Note: Using test_embeddings and y_test from your original script.\n",
-        "    # The embeddings have shape (n_splits, n_samples, n_features), so we use the first split [0].\n",
-        "    test_only_embeddings = test_embeddings[0]\n",
-        "\n",
-        "    # Apply t-SNE to reduce the TEST embeddings to 2 dimensions.\n",
-        "    # The number of samples in the test set is len(y_test). Perplexity must be less than that.\n",
-        "    # We'll set perplexity to 30, which is suitable for this dataset size.\n",
-        "    print(\"\\nApplying t-SNE for visualization on the TEST SET only...\")\n",
-        "    tsne = TSNE(n_components=2, random_state=42, perplexity=10)\n",
-        "    embeddings_2d = tsne.fit_transform(test_only_embeddings)\n",
-        "\n",
-        "    # Create a DataFrame for easy plotting\n",
-        "    df_plot = pd.DataFrame(\n",
-        "        {\n",
-        "            \"t-SNE-1\": embeddings_2d[:, 0],\n",
-        "            \"t-SNE-2\": embeddings_2d[:, 1],\n",
-        "            \"label\": y_test,\n",
-        "        }\n",
-        "    )\n",
-        "\n",
-        "    # Plot the 2D embeddings for the test set\n",
-        "    plt.figure(figsize=(9, 7))\n",
-        "    sns.scatterplot(\n",
-        "        data=df_plot,\n",
-        "        x=\"t-SNE-1\",\n",
-        "        y=\"t-SNE-2\",\n",
-        "        hue=\"label\",  # Color points by their class label\n",
-        "        palette=\"viridis\",\n",
-        "        alpha=0.9,\n",
-        "        s=80,\n",
-        "    )\n",
-        "\n",
-        "    plt.title(\"t-SNE Visualization of TabPFN Embeddings (Test Set Only)\")\n",
-        "    plt.xlabel(\"t-SNE Dimension 1\")\n",
-        "    plt.ylabel(\"t-SNE Dimension 2\")\n",
-        "    plt.legend(title=\"Class\")\n",
-        "    plt.grid(True, linestyle=\"--\", alpha=0.6)\n",
-        "    plt.show()"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing: 100%|██████████| [00:03<00:00]\n"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "PkphS4vSFNvg"
-      },
-      "source": [
-        "### Feature selection\n",
-        "\n",
-        "Feature selection is the process of selecting a subset of relevant features for use in model construction. It's useful for reducing model complexity, improving performance by removing noise, and decreasing training time. Here, we'll use Sequential Forward Selection (SFS), which starts with no features and iteratively adds the feature that most improves the model's performance.\n",
-        "\n",
-        "The goal is to see if we can create a simpler, faster model with fewer features without a significant drop in accuracy.\n"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "TabPFN RMSE: 2.6528\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Split the data\n",
+    "X_train, X_test, y_train, y_test = train_test_split(\n",
+    "    X, y, test_size=0.33, random_state=42\n",
+    ")\n",
+    "\n",
+    "# Train and evaluate the TabPFN regressor\n",
+    "tabpfn_regressor = TabPFNRegressor(random_state=42)\n",
+    "tabpfn_regressor.fit(X_train, y_train)\n",
+    "y_pred = tabpfn_regressor.predict(X_test)\n",
+    "\n",
+    "# Calculate the Root Mean Squared Error\n",
+    "rmse = np.sqrt(mean_squared_error(y_test, y_pred))\n",
+    "print(f\"TabPFN RMSE: {rmse:.4f}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Itu5-vVRWEMA"
+   },
+   "source": [
+    "### Comparing TabPFN with Other Regressors\n",
+    "\n",
+    "Now, let's see how TabPFN's regression performance stacks up against other models using cross-validation.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 810
     },
+    "id": "0XLxgbqSPe55",
+    "outputId": "930f9733-d5af-40c0-dd95-7f35d8ad61e1"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "GPJtNDLnFPPW"
-      },
-      "outputs": [],
-      "source": [
-        "from tabpfn_extensions import interpretability\n",
-        "\n",
-        "# Load data\n",
-        "data = load_breast_cancer()\n",
-        "X, y = data.data, data.target\n",
-        "feature_names = data.feature_names\n",
-        "\n",
-        "# Initialize model\n",
-        "clf = TabPFNClassifier(n_estimators=1)\n",
-        "\n",
-        "# Feature selection\n",
-        "sfs = interpretability.feature_selection.feature_selection(\n",
-        "    estimator=clf, X=X, y=y, n_features_to_select=4, feature_names=feature_names\n",
-        ")\n",
-        "\n",
-        "# Print selected features\n",
-        "selected_features = [\n",
-        "    feature_names[i] for i in range(len(feature_names)) if sfs.get_support()[i]\n",
-        "]\n",
-        "print(\"\\nSelected features:\")\n",
-        "for feature in selected_features:\n",
-        "    print(f\"- {feature}\")"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    8.9s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    1.1s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.4s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    6.4s finished\n"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "lmPJW5NSK7ut"
-      },
-      "source": [
-        "# Predictive Behavior of TabPFN <a name=\"behavior\"></a>\n",
-        "\n",
-        "In this section, we explore the behavior of predictions from TabPFN on various toy functions."
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Model Comparison - 3-fold Cross-validation \\n (Variance Explained - Larger is better)')"
       ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "ZBeID4YeMQ9L"
-      },
-      "source": [
-        "## Decision Boundary during Classification\n",
-        "\n",
-        "First, let us inspect the decision boundary for different classifiers.\n",
-        "The decision bounds show how smoothly a model learns to transition between classes and how well it fits the data.\n",
-        "\n",
-        "In the first cell, we create the data and code to plot the decision boundary. The second cell then generates the plot."
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Compare different machine learning models by training each one multiple times\n",
+    "# on different parts of the data and averaging their performance scores for a\n",
+    "# more reliable performance estimate\n",
+    "\n",
+    "# Define models\n",
+    "models = [\n",
+    "    (\"TabPFN\", TabPFNRegressor(random_state=42)),\n",
+    "    (\n",
+    "        \"RandomForest\",\n",
+    "        make_pipeline(\n",
+    "            column_transformer,  # string data needs to be encoded for model\n",
+    "            RandomForestRegressor(random_state=42),\n",
+    "        ),\n",
+    "    ),\n",
+    "    (\n",
+    "        \"XGBoost\",\n",
+    "        make_pipeline(\n",
+    "            column_transformer,  # string data needs to be encoded for model\n",
+    "            XGBRegressor(random_state=42),\n",
+    "        ),\n",
+    "    ),\n",
+    "    (\n",
+    "        \"CatBoost\",\n",
+    "        make_pipeline(\n",
+    "            column_transformer,  # string data needs to be encoded for model\n",
+    "            CatBoostRegressor(random_state=42, verbose=0),\n",
+    "        ),\n",
+    "    ),\n",
+    "]\n",
+    "\n",
+    "# Calculate scores\n",
+    "scoring = \"r2\"\n",
+    "n_splits = 3\n",
+    "cv = KFold(n_splits=n_splits, random_state=42, shuffle=True)\n",
+    "scores = {\n",
+    "    name: cross_val_score(model, X, y, cv=cv, scoring=scoring, n_jobs=1, verbose=1)\n",
+    "    for name, model in models\n",
+    "}\n",
+    "\n",
+    "\n",
+    "# Plot results\n",
+    "df = pd.DataFrame([(k, v.mean()) for (k, v) in scores.items()], columns=[\"Model\", \"R2\"])\n",
+    "ax = df.plot(x=\"Model\", y=\"R2\", kind=\"bar\", figsize=(10, 6))\n",
+    "ax.set_ylim(df[\"R2\"].min() * 0.99, df[\"R2\"].max() * 1.01)\n",
+    "ax.set_title(\n",
+    "    f\"Model Comparison - {n_splits}-fold Cross-validation \\n (Variance Explained - Larger is better)\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "3uGfjIdjsCg-"
+   },
+   "source": [
+    "# Handling Text Data <a name=\"text-data\"></a>\n",
+    "\n",
+    "A powerful feature of the TabPFN server is its ability to handle text data directly, without the need for manual feature engineering. This simplifies the process of working with datasets that contain a mix of numerical and textual features.\n",
+    "\n",
+    "**Note:** This feature is only available when using the 'client' backend."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 292
     },
+    "id": "vYBdSZnor-at",
+    "outputId": "13fd1b18-776d-43d2-ee0c-e1ed688071f0"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 18,
-      "metadata": {
-        "id": "B5a_ia0OLOxG"
-      },
-      "outputs": [],
-      "source": [
-        "from matplotlib.colors import ListedColormap\n",
-        "from sklearn.inspection import DecisionBoundaryDisplay\n",
-        "\n",
-        "\n",
-        "# Toy functions that generate the data\n",
-        "def generate_circle(n_datapoints, radius, noise_factor):\n",
-        "    angles = np.linspace(0, 2 * np.pi, n_datapoints).T\n",
-        "    x = radius * np.cos(angles) + np.random.randn(n_datapoints) * noise_factor\n",
-        "    y = radius * np.sin(angles) + np.random.randn(n_datapoints) * noise_factor\n",
-        "\n",
-        "    return np.stack([x, y]).T\n",
-        "\n",
-        "\n",
-        "def generate_concentric_cirlces(radii, num_points_per_circle, noise_factor=1 / 15):\n",
-        "    circles = []\n",
-        "    for r, num_points in zip(radii, num_points_per_circle):\n",
-        "        circles.append(generate_circle(num_points, r, noise_factor))\n",
-        "\n",
-        "    return np.vstack(circles)\n",
-        "\n",
-        "\n",
-        "def generate_circle_data(num_points_per_circle, radii, noise_factor):\n",
-        "    radii = np.array(radii)\n",
-        "    circles_1 = generate_concentric_cirlces(radii, num_points_per_circle, noise_factor)\n",
-        "    circles_1 = np.hstack([circles_1, np.zeros((sum(num_points_per_circle), 1))])\n",
-        "\n",
-        "    circles_2 = generate_concentric_cirlces(\n",
-        "        radii + 0.3, num_points_per_circle, noise_factor\n",
-        "    )\n",
-        "    circles_2 = np.hstack([circles_2, np.ones((sum(num_points_per_circle), 1))])\n",
-        "\n",
-        "    circles = np.vstack([circles_1, circles_2])\n",
-        "    X, y = circles[:, :2], circles[:, 2]\n",
-        "    return X, y\n",
-        "\n",
-        "\n",
-        "# Generate the data\n",
-        "X_train, y_train = generate_circle_data(\n",
-        "    num_points_per_circle=[50, 100, 200], radii=[1, 2, 4], noise_factor=0.1\n",
-        ")\n",
-        "\n",
-        "\n",
-        "# Function for plotting\n",
-        "def plot_decision_boundary(ax, model, model_name):\n",
-        "    cmap = ListedColormap([\"#FF0000\", \"#0000FF\"])\n",
-        "    ax.set_title(model_name)\n",
-        "    DecisionBoundaryDisplay.from_estimator(\n",
-        "        model,\n",
-        "        X_train[:, :2],\n",
-        "        alpha=0.6,\n",
-        "        ax=ax,\n",
-        "        eps=0.2,\n",
-        "        grid_resolution=50,\n",
-        "        response_method=\"predict_proba\",\n",
-        "        cmap=plt.cm.RdBu,\n",
-        "    )\n",
-        "    ax.scatter(X_train[:, 0], X_train[:, 1], c=y_train > 0, cmap=cmap)"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading...\n",
+      "From: https://drive.google.com/uc?id=17bJekFGIAxbrdcBeBIvcyZjneweY581E\n",
+      "To: /content/cloth.csv\n",
+      "100% 8.48M/8.48M [00:00<00:00, 21.0MB/s]\n",
+      "Text dataset loaded successfully!\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 19,
-      "metadata": {
-        "id": "wzrSEZR5LYlf",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 707
-        },
-        "outputId": "3ba2abe5-4fe4-465e-daea-c86d239f79ea"
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "summary": "{\n  \"name\": \"    display(X_text\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"Clothing ID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 119,\n        \"min\": 847,\n        \"max\": 1080,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          1049,\n          858,\n          847\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7,\n        \"min\": 39,\n        \"max\": 60,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          50,\n          39,\n          47\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"My favorite buy!\",\n          \"Cagrcoal shimmer fun\",\n          \"Flattering shirt\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Review Text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"I love, love, love this jumpsuit. it's fun, flirty, and fabulous! every time i wear it, i get nothing but great compliments!\",\n          \"I aded this in my basket at hte last mintue to see what it would look like in person. (store pick up). i went with teh darkler color only because i am so pale :-) hte color is really gorgeous, and turns out it mathced everythiing i was trying on with it prefectly. it is a little baggy on me and hte xs is hte msallet size (bummer, no petite). i decided to jkeep it though, because as i said, it matvehd everything. my ejans, pants, and the 3 skirts i waas trying on (of which i ]kept all ) oops.\",\n          \"This shirt is very flattering to all due to the adjustable front tie. it is the perfect length to wear with leggings and it is sleeveless so it pairs well with any cardigan. love this shirt!!!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Recommended IND\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Positive Feedback Count\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 0,\n        \"max\": 6,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          6,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Division Name\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"General Petite\",\n          \"General\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Department Name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Dresses\",\n          \"Bottoms\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Class Name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Pants\",\n          \"Knits\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
+       "type": "dataframe"
       },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 700x700 with 4 Axes>"
-            ],
-            "image/png": 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+       "      <td>Some major design flaws</td>\n",
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+       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-295fed73-1ab6-47f1-b06d-cd3041b3a409')\"\n",
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+       "      display:flex;\n",
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+       "\n",
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+       "      background-color: #E8F0FE;\n",
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+       "          + ' to learn more about interactive tables.';\n",
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+       "     width=\"24px\">\n",
+       "    <g>\n",
+       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+       "    </g>\n",
+       "</svg>\n",
+       "      </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
+       "      --hover-fill-color: #174EA6;\n",
+       "      --disabled-fill-color: #AAA;\n",
+       "      --disabled-bg-color: #DDD;\n",
+       "  }\n",
+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
+       "      --hover-bg-color: #434B5C;\n",
+       "      --hover-fill-color: #FFFFFF;\n",
+       "      --disabled-bg-color: #3B4455;\n",
+       "      --disabled-fill-color: #666;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart {\n",
+       "    background-color: var(--bg-color);\n",
+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
+       "    display: none;\n",
+       "    fill: var(--fill-color);\n",
+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    30% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "      <script>\n",
+       "        async function quickchart(key) {\n",
+       "          const quickchartButtonEl =\n",
+       "            document.querySelector('#' + key + ' button');\n",
+       "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "          try {\n",
+       "            const charts = await google.colab.kernel.invokeFunction(\n",
+       "                'suggestCharts', [key], {});\n",
+       "          } catch (error) {\n",
+       "            console.error('Error during call to suggestCharts:', error);\n",
+       "          }\n",
+       "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "        }\n",
+       "        (() => {\n",
+       "          let quickchartButtonEl =\n",
+       "            document.querySelector('#df-9afbc783-e193-4d88-938f-00ca40f23fd1 button');\n",
+       "          quickchartButtonEl.style.display =\n",
+       "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "        })();\n",
+       "      </script>\n",
+       "    </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
       ],
-      "source": [
-        "rf = RandomForestClassifier().fit(X_train[:, :2], y_train)\n",
-        "xgb = XGBClassifier().fit(X_train[:, :2], y_train)\n",
-        "tabpfn = TabPFNClassifier().fit(X_train[:, :2], y_train)\n",
-        "\n",
-        "# Create a 2x2 subplot layout\n",
-        "fig, axes = plt.subplots(2, 2, figsize=(7, 7))\n",
-        "\n",
-        "# Plot Train Points\n",
-        "ax_points = axes[0, 0]\n",
-        "ax_points.set_title(\"Train points\")\n",
-        "ax_points.scatter(\n",
-        "    X_train[:, 0], X_train[:, 1], c=y_train, cmap=ListedColormap([\"#FF0000\", \"#0000FF\"])\n",
-        ")\n",
-        "\n",
-        "# Plot Random Forest\n",
-        "ax_rf = axes[0, 1]\n",
-        "plot_decision_boundary(ax_rf, rf, \"Random Forest\")\n",
-        "\n",
-        "# Plot XGBoost\n",
-        "ax_xgb = axes[1, 0]\n",
-        "plot_decision_boundary(ax_xgb, xgb, \"XGBoost\")\n",
-        "\n",
-        "# Plot TabPFN\n",
-        "ax_tabpfn = axes[1, 1]\n",
-        "plot_decision_boundary(ax_tabpfn, tabpfn, \"TabPFN\")\n",
-        "\n",
-        "# Adjust layout for better spacing\n",
-        "plt.tight_layout()\n",
-        "plt.show()"
+      "text/plain": [
+       "   Clothing ID  Age                    Title  \\\n",
+       "2         1077   60  Some major design flaws   \n",
+       "3         1049   50         My favorite buy!   \n",
+       "4          847   47         Flattering shirt   \n",
+       "5         1080   49  Not for the very petite   \n",
+       "6          858   39     Cagrcoal shimmer fun   \n",
+       "\n",
+       "                                         Review Text  Recommended IND  \\\n",
+       "2  I had such high hopes for this dress and reall...                0   \n",
+       "3  I love, love, love this jumpsuit. it's fun, fl...                1   \n",
+       "4  This shirt is very flattering to all due to th...                1   \n",
+       "5  I love tracy reese dresses, but this one is no...                0   \n",
+       "6  I aded this in my basket at hte last mintue to...                1   \n",
+       "\n",
+       "   Positive Feedback Count   Division Name Department Name Class Name  \n",
+       "2                        0         General         Dresses    Dresses  \n",
+       "3                        0  General Petite         Bottoms      Pants  \n",
+       "4                        6         General            Tops    Blouses  \n",
+       "5                        4         General         Dresses    Dresses  \n",
+       "6                        1  General Petite            Tops      Knits  "
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "if backend != \"client\":\n",
+    "    console.print(\n",
+    "        Panel(\n",
+    "            \"[bold yellow]Text data can only be processed through the TabPFN server. Please restart the notebook and select the 'client' backend to run this section.[/bold yellow]\",\n",
+    "            title=\"[bold yellow]Warning\",\n",
+    "            border_style=\"yellow\",\n",
+    "        )\n",
+    "    )\n",
+    "else:\n",
+    "    # We will use gdown to download the dataset\n",
+    "    !gdown --fuzzy \"17bJekFGIAxbrdcBeBIvcyZjneweY581E\"\n",
+    "\n",
+    "    # Load the clothing review dataset\n",
+    "    # We restrict to 500 rows to make the example faster\n",
+    "    df_text = pd.read_csv(\"cloth.csv\", index_col=0).dropna()[:500]\n",
+    "\n",
+    "    # Define features and target\n",
+    "    y_text = df_text[\"Rating\"]\n",
+    "    X_text = df_text.drop(columns=[\"Rating\"])\n",
+    "\n",
+    "    print(\"Text dataset loaded successfully!\")\n",
+    "    display(X_text.head())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "iQkFQD_rWi1v"
+   },
+   "source": [
+    "### Comparing Text Handling\n",
+    "\n",
+    "Now, let's compare how TabPFN handles text natively versus how a baseline model like RandomForest needs a specific text processing pipeline.\n",
+    "\n",
+    "For baselines, we will create a pipeline that converts strings to ordinal features.\n",
+    "\n",
+    "For TabPFN, we simply pass the raw data with the text column directly to the classifier."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 841
     },
+    "id": "ktXNMVFCsEHZ",
+    "outputId": "fa5bd253-55d1-48a6-a91b-670b78326586"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "8tvOmmiOOT4o"
-      },
-      "source": [
-        "## Sin Curve Fitting with Regression\n",
-        "\n",
-        "Next, we investigate the curve-fitting behavior of the different models on a sin curve."
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing: 100%|██████████| [00:01<00:00]\n",
+      "Processing: 100%|██████████| [00:01<00:00]\n",
+      "Processing: 100%|██████████| [00:01<00:00]\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:   18.4s finished\n",
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    8.4s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    2.0s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.8s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    9.2s finished\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 20,
-      "metadata": {
-        "id": "f_6wB1N2OrYu",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 0
-        },
-        "outputId": "f91662b0-c1cb-42b1-d4c0-5562492d4090"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 1400x1200 with 4 Axes>"
-            ],
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54DCTksWhrJSkgLaLJiRtAQAIhf27/WqWpX193nUsXlUGAABA5HG0NvjVzhnTfm/6KVp3z0U+J4mymE0qLeq9vi13msWn/DEZPpP6JnVeGMgfkxHKboUESVsAAEIhebhfzRqV3uddx+JVZQAAAESeFz884le7tqRhemzOFN05fbxfk0MV5tlUPmeKMoYk+GzHnWbxp2tSv/uZ5HxdWpQbc5OQSSRtAQAIjVHTZKRme61Y6zCkXUamqhw5fu8ylq8qAwAAILJU1tTr/72TrF1GhrwNdHXGtJde/jWfo2s9Kcyz6cdXTPSrLXeaxRdnUt+a5j5YxdpL6Y1oNyDcHQAAIC6YLTIVLpaeL5bDcJ+MzBn0lnXcJIef11Nj/aoyAAAAIofdYaisolYOmVXWUazyhCVyGPIa096cntyv97Gmxm/9UvhWmGfTjFyrquqa1NjapqyUzsErsfy3ECNtAQAIldxZMl27VO2DrW6LG5Spko4FWuXI93tXsX5VGQAAAJGjqq5J9c2do1tXOfJV0rFADXK/28sZ076Xcn6/7wTrrX6p1Jko/vLA4X7tH9HH7jC0cftevbzlc1XVNSl/TIZmTx6hgnGZMZ2wlRhpCwBAaOXO0qCcy2XfsV7bP9muRiNdppOmqdhi0WX72zVsSKJkkvb4eB4PV5UBAAAQObqXI1jlyNfq9qnKN29VlvapUemqcuTIIbMeO447wZz1S0uWVXtt4zCkec9Uq9zMAIZYV1lTr7KKWtcFA6mzPFxpUW5c/NuTtAUAINTMFlnGnq/xY8/X+HD3BQAAAOjFsOTEHsscMmuTI9dt2femjz/uZFphnk2Pfv0MzX92s9fauZJUVlGrGblWBjLEqMqaepUsq1b3U6ChuU0ly6rj4q5DyiMAAAAAAADAo8qaet39/JZe21lTEzX/opMD8p5DhyT6TNgakuqb21RV1xSQ90NkcdZQ9nQKOJeVVdTK7uskiQEkbQEAAAAAANCDc7RjQ0u71zamo4/7Z00M2KjX7uUYvGloPhSQ90Nk6VpD2ZN4SdqTtAUAAAAAAIAbX6MduwrGBLlZKUl+tXvwlQ9UWVMfsPdFZPA3ae9vu2hF0hYAAAAAAABuehvt6PTz/zo94LVF88dkyJaWpN7G7X554LBKllWTuI0x/ibt/W0XrZiIDACAOGE/ckRb31qlQ19+rsT0bLVknaU9B49o2JBEySTt2d/uet7Y0qamA4eVkZyorORj67NSkpQ/JoMJHwAAAGKcv6MY9xzwXjqhvyxmk0qLclWyrNptuVkO5Zu3Kkv71Kh0VTlyZMjMpGQxxpm0b2hu8zjS26TOEd75YzJC3bWQImkLAEAc2LzqKWVvLNNE7XUt22VkaGlHsVY58vu0L1takkqLcmN+tlYAAIB4Fu7RjoV5NpXPmaIfLn9fTQc6NNNcpdKEpco2HatjusvIUFlHsVY156uqrkkF4zKD0heEVtekvUlyS9w60/KlRbkxn6SnPAIAADFu86qndPqGO3SCsddtuVVNKk9Yopnmqj7tr6G5jdvQAAAAYlxvJQpM6ryYH8zRjoV5Nv34iomaaa5SecISWeU+8VTXeDbW65vGG2fS3prmflEgGDWUIxUjbQEAiGH2I0eUvbFMktT9QrTZJDkMqTThaa1unyqHn9dyDXUG6dyGBgAAENuuP+sk/erVD3ssD+VoR2tygkoTlkryHc/uHDIvqP1A6BXm2TQj16qquiY1trbFXak2krYAAMSwrW+t6iyJ4CWuMZukbO1VvnmrNjly/d6vIam+uY3b0AAAAGJQZU29yipqvU5EZg1huax8y1ZZTE1e1zvj2eGWrZKygt4fhJbFbIrbvzdI2gIAEMMOffm5X+2ytK9f++c2NAAAgNhSWVOvkmXVHieAkqTvTT9F8y86JWSjHS0HGgPaDogW1LQFACCGDRo6wq92jUrv1/6DNfEEAAAAQs/uMFRWUes1YWuS9Nzbn4WyS1Ly8MC2A6IESVsAAGJYztkztVuZcniJvB2GtMvIVJUjp0/7DcXEEwAAAAitqromryURJPcSWSEzapqUmi1v9b4MmdQ+2Cb7yILQ9QkIAZK2AADEMMuAAdpVUCpJPRK3ztdlHTf5PQmZFNqJJwAAABA6/pa+CmmJLLNFKlx89IV77OkwJMMwdMe+63Tew2+osqY+dP0CgoykLQAAMe6MmXP1r2m/1hcm9wL+DcpUSccCrXLk92l/1rQklc+ZEpKJJwAAABA6/pa+CnmJrNxZ0rVLpVT3+LNrPNvQ3KaSZdUkbhEzmIgMAIA4cMbMubJffKP+/dYqHfrycyWmZ6sl6yxddvCIiockSiZpz/52DTv6vLGlTU0HDisjOVFZycfWZ6V0lkRghC0AAEDsyR+TIVtakhqa2zzWtTWp8wJ+WEpk5c6Sffxl+u7iRzXgQKMala4qR47rjjHjaP/KKmo1I9dKvBrF7A5DVXVNamxti+u/P0jaAgAQJywDBmjiuZeHuxsAAACIUBazSaVFuSpZVi2T5Ja4jYQSWVU7m/X31pMlnexxfdeauwXjMj22QWSrrKlXWUWtW21lW1qSSoty4+5OP8ojAAAAAAAAQJJUmGdT+Zwpsqa5l0CIhBJZEVlzFwFTWVOvkmXVPSbDi9fSF4y0BQAAAAAAgEthnk0zcq0Rd4t6xNbcxXGzOwyVVdR6LMsRr6UvSNoCAAAAAADAjcVsirgSAxFdcxfHpaquqccI267isfQF5REAAAAAAAAgu8PQxu179fKWz7Vx+17ZHZ5So+HjrLkrHaux6xQJNXfRf5S+6ImRtgAAAAAAAHEuWiaActbc7d7XoUMSdNXkEUobNFB2h0HiNspQ+qInRtoCAAAAAADEsWibAKowz6Z191ykZ289R988d7QyhgxU04EO/Xn9Dt3wx006b/FrEddn+OYsfeEt1W5S50WEeCp9QdIWAAAAAAAgTvU2AZTUOQFUJJZKaD50WE+s36GmA4fd1kVqshneUfqiJ5K2AAAAAAAAcaovE0BFkmhNNsM7Z+kLa5p7CQRrWpLK50yJqDIdoUBNWwAAAAAAgDgVrRNA9SXZXDAuM3Qdw3EpzLNpRq5VVXVNamxtU1ZKZ0mEeBph60TSFgAAAAAAIE5F6wRQ0ZpsRu8sZhOJdlEeAQAAAAAAIG5F6wRQ0ZpsBvxF0hYAAAAAACBOResEUL0lmyUpY0iCzhw1NGR9AgKJpC0AAAAAAEAci8YJoHwlm52aDnTogodfV2VNfeg6BgSIyTCMmJpGr6WlRWlpaWpublZqamq4uwMAAIAAiac4L54+KwAgctgdRtRNAFVZU6+yilqvk5I5ex+pyWfEH3/jPCYiAwAAAAAAiFPRmKjtqjDPpotyhuucRWvUdOBwj/WGOhO3ZRW1mpFrjarPFk+i/TwMBpK2AAAAAAAAccjTKFVbWpJKi3KjalTquzu/9JiwdTIk1Te3qaquSQXjMkPXMfglVs7DQCNpCwBAfzjssu9Yr+2fbFejkS7TSdMki0V79rdr2JBEySSfz7l6DAAAgHCqrKnXvGXv6CzzVp1l3qdGpavKkaOG5jaVLKuOqnICja2eSyP0tx1Cp7KmXiXLqtW9dms0noeBRtIWAIC+ql2hQxU/0KBDDRovabykXesyVNZRrFWOfL93w9VjBISXCwiNLW1qOnBYGcmJykrm4gEAADjG7jC09qXH9c/EPynb1ORavsvojGn/4ciPqnICWSlJvTfqQzuEht1hqKyiVoYksxzKN29Vlo5dQDBkjqrzMNBI2gIA0Be1K2Q8X6xEw3CbptaqJpUnLFFJxwK/E7dcPcZxC8AFBC4eAAAQfz5+4xn9tONnPZa7xbTN+VFTTiB/TIZsaUlqaG7rMWJT6gzbrWmdF6sROarqmlTf3KaZ5iqVJiz1eAEhms7DQDOHuwMAAEQNh11G5T0yZKj7hV7n69KEp2WWw6/dOQPKsopa2R2ewkvAB+cFhIMNboudf2zNNFf5tRvnxYPKmvpg9BIAAEQah10nvVUmSb3GtNFSTsBiNqm0KFeS27gKt9elRblxOVozkjW2diZsyxOWyKomt3VdY9poOQ8DjaQtAAD+2rlBppZdXn95mk1Stmmv8s1b/d5l10kRAL8F8AICFw8AAIgzOzdoUNvuHjGEU9eYNprKCRTm2VQ+Z4qsae59tqYlcWdbhMoakqDShKWSfF9AyBqSEOKeRYagJm0XLVqks846SykpKcrKytKVV16pbdu29brdCy+8oJycHCUlJWnSpEn6+9//HsxuAgDgn/27/WqWpX193nW8Xj1GPwX4AgIXD7wjngUAxBw/Y9rxgw9EXTmBwjyb1t1zkZ699Rw9cv1kPXvrOVp3z0UkbCNUvmWrsk1NvV9AsPg/KCaWBDVp+8Ybb2jevHnatGmTVq9erY6ODl1yySU6cOCA1202bNigG264Qbfccos2b96sK6+8UldeeaVqamqC2VUAAHqXPNyvZo1K7/Ouo2kUAyJAkC4gcPGgJ+JZAEDM8TOmvWLa5KgsJ2Axm1QwLlOzJ49QwbjMqPwM8cLkZ0xrOdAY5J5EJpNhGCG7D+6LL75QVlaW3njjDZ1//vke21x33XU6cOCAVq5c6Vp2zjnnaPLkyXrsscd6fY+WlhalpaWpublZqampAes7AABy2GUsyZPhZYSjw5AalKnz2h+Rw8/ros5JEdbdcxEBJfxX90/pqSt6bXb94R9pkyPX790+e+s5ET3JQyTEeaGIZ6XI+KwAgBjlsEtL8qSWesnDtF0OSe2DrBr0g1rJbAl59xAfKmvqteLl5/W7jvt6bzx3pTTmK8HvVIj4G+eFtKZtc3OzJCkjw/vw+o0bN2r69Oluy2bOnKmNGzd6bN/e3q6Wlha3BwAAQWG2yFS4WCaZ1L30p/N1WcdNfUrYSkyKgH4YNU1GarbXirUOQ9plZKrKkePX7kySbMyo7JdgxLMSMS0AIITMFqlw8dEX7jGoIZNMMmlQ0cMkbBE0lTX1nRPhto7VLiOjx99Wx5ik1BHSqGmh7F7ECFnS1uFwaMGCBTr33HOVl5fntV1DQ4OGD3cfqj98+HA1NDR4bL9o0SKlpaW5HiNHjgxovwEAcJM7S6Zrl6p9sNVtcYMyVdKxQKsc+X7vikkR0G8BvIDAxQP/BSuelYhpAQAhljtLunaplOoeh5pSs2W6dmnn+hhgdxjauH2vXt7yuTZu38ukqxHA7jBUVlErQ5JDZpV1FEtSj5jWcEaphQ/F7QWEAaF6o3nz5qmmpkbr1q0L6H4XLlyou+66y/W6paWFIBcAEFy5szQo53LZd6zX9k+2q9FIl+mkaSq2WHTZ/nYNG5IomaQ9Pp5npXSOaiRJhn47egGhreIHGnToWDKwQZkq67jJ7wsI1rQklRblcvHAD8GKZyViWgBAaNkdhqoSz1XjV1fp5IPva0LKQZlTrJ0jGmMkQVZZU6+yilrVNx+r2W8j7gm7qromt3+TVY58lXQsUGnCUmXr2KS4hwdblXjFz2LmAkJ/hCRpO3/+fK1cuVJvvvmmTjzxRJ9trVardu92L0S8e/duWa1Wj+0TExOVmJgYsL4CAOAXs0WWsedr/NjzNT7cfUH88nEBobClTU0HDisjOVFZyVw8OF7BjGclYloAQOh4TmZmqLToZBXGUMK2ZFl1j4q9Dc1tKllWzd1uYeRp4ttVjnytbp+qfPNWZWmfGpWuG2Zfp9m5J4Whh5EjqElbwzD03e9+V8uXL9fatWs1ZsyYXrcpKCjQmjVrtGDBAtey1atXq6CgIIg9BQAAiFJcQAgq4lkAQCyJh2Rm19vvuzPUWRqqrKJWM3KtXLgOg6yUJI/LHTK7TaB7Z+qQUHUpYgW1pu28efO0bNkyPfPMM0pJSVFDQ4MaGhp06NAhV5vi4mItXLjQ9frOO+9UZWWlfvGLX2jr1q26//779c4772j+/PnB7CoAAADQA/EsACBW9JbMlDqTmdFe97X77ffdGZLqm9tUVdfktQ2CJ39MhmxpSfKWLmeC3GOCmrQtLy9Xc3OzLrzwQtlsNtfjr3/9q6vNp59+qvr6etfradOm6ZlnntEf/vAHnX766frf//1fvfTSSz4newAAAACCgXgWABAr4iWZ6en2++Nph8CymE0qLeocUds9ccsEue6CXh6hN2vXru2x7JprrtE111wThB4BAAAA/iOeBQDEinhJZnq7/b6/7RB4hXk2lc+Z0qO2MhPkugvJRGQAAAAAAAAIn3hJZjpvv29obvNYCsKkzuQgt9+HV2GeTTNyraqqa1JjaxsT5HoQ1PIIAAAAAAAACL94qSXq6/Z7qbMMxPVnjQxpn+CZxWxSwbhMzZ48QgXjMknYdkPSFgAAAAAAIMbFUy1R5+331jTPo4Z/9epHOm/xa6qsqfe4HogEJG0BAAAAAADigLdkpjUtSeVzpsRULdHCPJvW3XORvjd9vMf1Dc1tKllWTeIWEYuatgAAAAAAAHEi3mqJPvf2px6XG+ocYVxWUasZudaY/fyIXiRtAQAAAAAA4oizlmisq6prUn1zm9f1hqT65jZV1TXFxfFAdKE8AgAAAAAAAGJOY6v3hG1/2gGhxEhbAAAAAACAGGd3GHFTEsEpK8XzRGT9bYfjF4/nYX+RtAUAAL1z2KWdG+RobdAHrYP18eBJGpY8WDJJe/a3a9iQxF6fE5QBAACER2VNvcoqat1KBdjSklRalBtTk491lz8mQ7a0JDU0t8kkh/LNW5WlfWpUuqocOTJkljWtM0ZF8MXredhfJG0BAIBvtSukynukll0yS5ooaaiRobKOYq1y5PdpVwRlAAAAoVVZU6+SZdUyui1vaG5TybJqlc+ZErOxmcVsUmlRrl565jHdl7BU2aYm17pdRoYe6CjWlUXfYVBBCMTzedhf1LQFAADe1a6Qni+W0bLLbbFVTSpPWKKZ5qo+7c4ZlFXW1AeylwAAAPDA7jBUVlHbI1EmybWsrKJWdoenFrGh0Py2ygc+ImuXhK0kWU1NKh/4iArNb4epZ/GD87B/SNoCAADPHHap8h4ZMtR97IFzMEJpwtMyy+H3LgnKAAAAQqeqrsntVvTuDEn1zW2qqmvy2iaqHY1nTTJ6JMDMUmeMW3lvZzsETdyfh/1E0hYAAHi2c4PUsqtHwtbJbJKyTXuVb97ap90SlAEAAIRGY6v3RFl/2kWdo/Gsd4bU8nlnOwRN3J+H/UTSFgAAeLZ/t1/NsrSvX7snKAMAAAiurJSkgLaLOn7Gs47WhiB3JL7F/XnYTyRtAQCAZ8nD/WrWqPR+7Z6gDAAAILjyx2TIlpbk9c4pkzonis0fkxHKboWOn/Hs/IpdzLkQRHF/HvYTSVsAAODZqGlSaraHiradHIa0y8hUlSOnT7slKAMAoCe7w9DG7Xv18pbPtXH7Xmq/IyAsZpNKi3IlqUdE53xdWpQri9lbOi3KHY1ne376Ts54dlXrWCbLDaK4Pw/7iaQtAADwzGyRChfLJPVI3Dr/jizruEmOPoQTBGUAAPRUWVOv8xa/phv+uEl3PrdFN/xxk85b/Jr+/t4uErk4boV5NpXPmSJrmvtdTta0JJXPmaLCPFuYehYCR+NZyXc8az8azzJZbvDE9XnYTybDMGLqbGxpaVFaWpqam5uVmpoa7u4AABD9aldIlfe4TeKwy8hUWcdNWuXI79OubGlJKi3KJShDv8RTnBdPnxWId5U19SpZVi1//jDn9yiOh91hqKquSY2tbcpK6bzrKW4uoteuUPvKHyjx4LHatd7i2WdvPUcF4zJD3cOY5zz/GpoPqenAYWUkJ8qaGmfn4VH+xnkDQtgnAAAQjXJnSTmXSzs3yNHaoA9aB+vjwZNUnDxYxSZpz/52DRuSKPXyPO7+OAAAoBd2h6Gyilq/EraS1NDcppJl1YxKg9/iOlHbVe4sVbZP1rMv/FVZ2qdGpavKkePxjjEmyw28ypp6lVXUqr752LF1XoSKy/PRTyRtAQBA78wWacxXZJY08egDAAAcn02f7HVLYvTGUGepobKKWs3ItZLsgE++EmXxmPTPSh2iTY7c3tsxWW5AebubgItQvaOmLQAAAAAAIVZZU695f6nu83aGpPrmNlXVNQW+U4gZzkRZ94sCzkRZPE64lT8mQ7a0JC9TkjFZbjD4upvAuYw6wt6RtAUAAAAAIETsDkOPvPqRvrOsWvsOdfR7Pw3NhwLYK8QSEmWeWcwmlRZ1jrTtnrhlstzgqKpr8nk3ARehfKM8AoDo47DLvmO9tn+yXY1GukwnTZMsFv/qarYe1NgD72ngoUZ9oaGubRtb2lzF0LOSqccJAACAwKusqdf9K/6txpZDOse8tdfamp6Y5VC+eauqKqo0Yt8Zyr+wqLOMEXBUXxJl8TbhVmGeTeVzpvQoG2GN47IRweRvfWDqCHtG0hZAdKldoUMVP9CgQw0aL2m8pF3rMlTWUdzrLPYzzVUqTViqbFPnVbxT+7CtUzzXgAIAAED/OW9Xv8RcpdLEYzGpJO0y+hHPGpLelA69bdWgooc7Jw4FRKKsN4V5Ns3ItTJBWwj4Wx+YOsKeUR4BQPSoXSHj+WIlHmxwW2xVk8oTlmimucrrpjPNVSpPWCKr3G+78GfbruK5BhQAAAD6x3m7+iXHEZN6i2cTDzXIeL5Yql0RlL4j+pAo653FbFLBuEzNnjxCBeMySdgGCXWEjw9JWwDRwWGXUXmPDBnq/vvU+bo04WmZ5eixqVkOlSYsdWvr77bdxXMNKAAAAPRPVV2Tdjcf7HdM6jOelWTI0KGKH0gOe6C7jihEoqxv7A5DG7fv1ctbPtfG7Xv5Oy+AqCN8fEjaAogOOzfI1LLL65eW2SRlm/Yq37y1x7p881Zlm5p6BLj+bOsJxdIBAADQFw0tbccVk/a6raRBhxpUtbYicJ1G1CJR5r/Kmnqdt/g13fDHTbrzuS264Y+bdN7i17izMoCcdYStae4ju61pSSqfM4XSgz5Q0xZAdNi/269mWdrn1zJ/t/UlXmtAAQAAwH+VNfV6cOW/dV4fYtLvTT9Fo4cN0Z7Wdj34ygd+x6krN2zRmRfOJhkHJtzyg7POdPdxtc6SeCQUA4c6wv1D0hZAdEge7lezRqX7tczfbX2J5xpQAAAA6F3XpFCjOd2vbeZMP0v5F42X1Hnb9p/W1amx1b9tPzw4RJu279W5pwzrX4cRU0iUeeesM+2pEIKhzhHJZRW1mpFr5XgFiLOOMPxHeQQA0WHUNBmp2V6rzjoMaZeRqSpHTo91VY4c7TIy5K00ka9tPaEGFAAAAHpz+IhDP1xe40oK9RaTGpKM1BHKv7DItcx5m/vbfYhn5z3DpLk4hgm3PKuqa3IbgdwdJfEQCUjaAogOZotMhYtlkqlHsOp8XdZxkxwevtYcMquso9itrb/bdkcNKAAAAPSmsqZe5yx6VU0HDruW+YpJDZk6/yt8SDJb3NYV5tn06Jyp+qXlmx637R7P7jvUoZJlJG4BX/wtdUdJPIQTSVsA0SN3lkzXLlX7YKvb4gZlqqRjgVY58r1uusqRr5KOBWqQ++hYf7btimLpAAAA8MVZEqHpQEePdd5iUlNqtnTtUil3lsd9FubZ9NMf/rf+n+X7fsezZRW1snsbmgvEOX9L3VESD+FETVsA0SV3lgblXC77jvXa/sl2NRrpMp00TcUWiy7b365hQxIlk7TH4/Oz9XbrLRp74D0NPNSoLzTUtW1hS5uaDhxWRnKispI974MaUAAAAPDFV51Mp1WOfK1un6p881ZlaZ++ffk0TSwo7DHCtruBA8ya/rVv6SvLJuuso9s2Kl1Vjpwed4w5b+2mvi3gWf6YDNnSktTQ3Obx59WkzgE7lMRDOJG0BRB9zBZZxp6v8WPP1/h+7eAkSdKpgewTAAAA4l5vdTKdHDLrLUeurGlJ+lXBRZKfgwKcpRLu/VuiNh3qOZK3u3nPVOuhqydxlxjQjbNedMmyapkkt8QtJfEQKSiPAAAAAABAAPS1/mV/kkKFeTY9euMUv9pS3xbwrjDPpvI5U2RNcy+BQEk8RApG2gIAAAAAEAD+1r/MHDJQ/3NVXr+TQueMzfR5a3d3ZRW1mpFrZdQg0E1hnk0zcq2qqmtSY2sbJfEQUUjaAgAAAAAQAL3VyZSkjCEJ2rjwYg0c0P8bX7ve2t0bZ33bqromFYzL7Pd7InrYHQZJyD6wmE38bCAikbQFAAAAACAA/KmT+dOrJh1XwtbJeWv3vX97X/v8qG/b19INiE6VNfUqq6h1q61sS0tSaVEut/sDUYaatgAAAAAABEgo62T2pb6tv6UbEL0qa+pVsqy6x2R4Dc1t1DYGohAjbQEAAAAACKBQ1snsrb6tSZ0J4/wxGQF/b0QOu8NQWUWtx3PAUOd5QG1jILow0hYAAAAAgABz1smcPXmECsZlBi1R5izJIB0rweDkfF1alEuiLsZV1TX1GGHbVdfaxgCiA0lbAAAAAAACwO4wtHH7Xr285XNt3L5Xdoe36cgCK5QlGRCZ/K1ZTG1jIHpQHgEAAAAAgOMU7gmgQlmSAZHH35rF1Db2ze4w+BlCxCBpCwAAAADAcXBOANV9XK1zAqhQjXZ1lmRA/Mkfk0Ft4+MU7gsvQHeURwAAAAAAoJ96mwBK6pwAKlSlEpzCVaoB4UFt4+PjvPDSvS6w88JLZU19mHoW3fgeOj6MtAUAAAAAoJ/6MgFUqEbBMmIwPjlrG3f/t7fyb+9TbxdeTOq88DIj10rSuw/4Hjp+JG0BAAAAAOinSJsAKlJKNSA8qG3cd5F44SXa8T0UGJRHAAAAAACgnyJpAqhILdWA0HLWNp49eYQKxmWSsO1FpF14iXZ8DwUOSVsAAAAAAPrpzFFDlTFkoNf1JnXeEhyKCaD6MmIQQKdIuvASC/geChzKIwAAAAAA0A/Omo1NBw57XB/qCaAYMRi/7A6Dkgj9lD8mQ7a0JDU0t3kcHWpSZ13gUFx4iQV8DwUOSVsAAAAAAPrIW83GrkI9AZS/IwGHDUkMck8QSkz4dHwsZpNKi3JVsqxaJsntZzrUF15iASOXA4fyCAAAAAAA9IGvmo1OGUMS9MYPvhrSpJlzxGBvqaW7X/iXKmvqQ9InBJfz4kH329GdEz7x7+yfwjybyudMkTXNPZGYNihBC6afohm51jD1LPr09j0UypIx0Y6kLQAAAAAAfdBbzUZJajrQoXd3fhmiHnVyjhiU5DNxu7uFhF4sYMKnwCrMs2ndPRfpe9PHK31QgiRp36EO/erVj3Te4tf4efGTr+8hRi73DeURAADxzWGXfcd6bf9kuxqNdJlOmiZZLNqzv73z1kGTfD6nZhgAAPEnkms2OkcM3r/i32poaffYxlBn8qSsolYzcq3EMVHKefHALIfyzVuVpX1qVLqqHDlyyOw24VPBuMxwdzcqrK5t0JJXP+yRCHeOXC6fM4WSE35wfg91L9sR6pIx0Y6kLQAgftWu0KGKH2jQoQaNlzRe0q51GSrrKNYqR77fu6FmGAAA8SXSazYW5tmUkpSgG//0ltc2JPSiX2Nrm2aaq1SasFTZpibX8l2GezzLhE/+6W3kMhc6+qYwz6YZuVYmyDsOJG0BwB+Mxow9tStkPF+sRMNwu2/HqiaVJyxRSccCvxO3XHkHACC+RMNs83v29xxl62lEZkPzoTD0DoGQ8+VaFSUs6bG8ezzLhE/+6a3sCRc6+s5iNnGsjgNJWwDoDaMxY4/DLqPyHhky1D2PbjZJDkMqTXhaq9unyuFH+XeuvAMAEH+uP+sk/erVD3ssj5Sajd0Tdd5GZP5y5Tc1aOC3iFGjjcOu8Zt/IsPUc7KirvFsTeK5TPjkp0gue4L4xERkAOCLczTmwQa3xc6r1zPNVX7vihlcI8jODTK17PL6S9BskrJNe5Vv3ur3LrteeQcAALGrsqZe5y1+zWPCVuocYRsJd990ncF9prlK5QlLZJV7nGJVk35m/7leeuYxYtRo42c8+6tzDjKgwE+RXvYkWtgdhjZu36uXt3yujdv3MhHecWCkLYDwcNilnRvkaG3QB62D9fHgSRqWPFgySY0tbWo6cFgZyYnKSg5juQFGY8au/bv9apalfX3eNVfeAQCIXZU19SpZVu0qidC93MC0r16heRfnRESc55zBfd6yd1SasFSSvMa09yU8rWtWnEuMGk38jGfzTzgS5I7EjmgoexLpKmvqe0w+xh2n/UfSFkDo1a6QKu+Rjl4ZnihpqBGB5QaOXr32FraaTVK2OkdjbnLk+rVL6iBFiOThfjVrVHqfd82VdwAAYlP3SYo8lRvYvb5cyv6VNHF2eDrZTWGeTc9eYlf2m97vBHLGtCP3/0tVdWcSo0YLP+NZv9vBdaGjZFm1TJJb4jZSyp5Esu4XtZyY/6P/gloe4c0331RRUZGys7NlMpn00ksv+Wy/du1amUymHo+Ghgaf2wGIIrUrpOeLZbTsclsckeUGGI0Zu0ZNk5GaLYeX1Q5D2mVkqsqR4/cuTeq8kMCVdyD2ENMCkNwnKfJWbuAEY6/ML8ztjHkjhL8jLbO0jxg1moyaJqVmS16HmJik1BGd7eC3wjybyudMkaK5xUYAAHxdSURBVDXNfSBGpJQ9iVTdL2p15VxWVlFLqYQ+CupI2wMHDuj000/XN7/5TX3ta1/ze7tt27YpNTXV9TorKysY3QMQag67dLTcQPfQIiLLDTAaM3aZLTIVLpaeL5bDcC9/4Ywjyjpu8us8lLjyDsQ6YloA0rGL7mY5fJYbMCSp8l4p53LJbAltJz3pQ0xLjBpFzBapcLGM54slmWTyNC608KHIOAejTGGeTTNyraqqa1Jja1toSvNFua4XtTzhjtP+CWrS9tJLL9Wll17a5+2ysrKUnp7uV9v29na1t7e7Xre0tPT5/QCEyM4NUjSVGzg6GtPwUuDfYUgN6vtoTOogRYjcWTJdu1RtFT/QoEPHRr81KFNlHTf1qVSHlTpNQEwjpgUgHbvonm/e6lYSoTuTDKnl887Yd8xXQtU97/yMaT9LPp0YNcpUOs7S2gE/0B0df3I7Jw8NGq5BRQ9LubPC2LvoZjGbSC72gb+j9BnN3zcRWdN28uTJam9vV15enu6//36de+65XtsuWrRIZWVlIewdgH6LtnIDjMaMfbmzNCjnctl3rNf2T7ar0UiX6aRpKrZYdFm3ye+8PefKOwLCYe9xHspi8XnucR5GPmJaILY4JynKat3n3wZ+xr5B50dM+0DHTfrxNZP4PRJFjtUPnazn9Wu3CfHebsvRo46pKgx3JxE3nBe1uk/OWOXIcft7mdH8fRNRSVubzabHHntMU6dOVXt7u/70pz/pwgsv1FtvvaUpU6Z43GbhwoW66667XK9bWlo0cuTIUHUZQF9EY7kBRmPGPrNFlrHna/zY8zU+3H1BfKpdoUNHv2PGSxovade6CJycEX4jpgVik3OSoiefqfZvg0iaAMpHTPvrhFt05TXf5PdHFOleP9Qhs9udikEtIReH7A6DUgm9yB+ToeuTt/QY9b3r6ITj/3Dkc8dpP5gMwwhJFWCTyaTly5fryiuv7NN2F1xwgU466SQ9/fTTfrVvaWlRWlqampub3WqIAYgADru0JE9GS323mktHVx+9Neu89kf6NHrVmpakdfdcFNxfnIyCAxAMtStkPF8sw8vIp5KOBX4nbp2bx/IkGZEQ5xHTAqh8/z8642/nd0465jG0M3VOELXg/cirJ+ojpiVejR4bt+/VDX/c1Gu7Z289h1v8j1NlTb3KKmrd6rVyodyDXmLa2zsW6Mqvf4djdpS/cV5EjbT1JD8/X+vWrQt3NwAEwtFi+abni2V0K5Yf8eUGGI0JINAcdhlHJ2f0NJFNxE3OiONCTAvEjsJJJ8pu/pVML8w9+t0bRRNAdYlpP6mpV9mLNSSjohD1Q0PjWAkKdw3NbSpZVh3TF8r75OiE4yYZMnmKaSX9Ku05Dcq9Lyzdi2b+ZUbCaMuWLbLZ+CEAYkbuLOnapTKluv9cNyizTyPKpM4RtvyiBBC1dm6QycukMNLRyRlNnZMz+qvr5IyILMS0QGyxTJwtk4eYVqnZ0rVLI34CKGcyqvts785kVGVNfZh6Bn/4WxqO+qH9170ERVfOZWUVtbI7QnLzemQ7OuG4N2apsyzLzg2h61OMCOpI2/379+vjjz92va6rq9OWLVuUkZGhk046SQsXLtTnn3+upUuXSpKWLFmiMWPGaOLEiWpra9Of/vQnvfbaa/rHP/4RzG4CCLXcWVLO5dLODXK0NuiD1sH6ePAkFScPVrFJamxpU9OBw8pITlRWMuUGAMSoaJucMY4R0wLwqEtMq/27O2vYjpoWmSNsu+gtGcVdG5HPOSleQ3Obx39HZwk56of2X1VdU4+LGl11vVAe9yUo/J10MVImZ4wiQU3avvPOO/rqV7/qeu2cXGHu3Ll68sknVV9fr08//dS1/vDhw7r77rv1+eefa/DgwTrttNP06quvuu0DQIwwW6QxX5FZ0sSjDwCIK9E4OWOcIqYF4NXRmDaakIyKfs5J8UqWVcskeSrQEZoScjGMEhR94O+ki5E0OWOUCNlEZKHCpA0AACAqOOwyluTJ8FIiIaInZwyTeIrz4umzAgitl7d8rjuf29Jru0eun6zZk0cEv0PoNybJCh4me+uDoxOOq6Ve8jb2O1InZwyTmJmIDAAAICaZLTIVLpaeL5bDy0y7ETs5IwDEIbvDUFVdkxpb26K6VBf1UGNHYZ5NM3KtMXFeRhpKUPTB0QnH9Xyx5G3sd6ROzhjhSNoCAIDgcdhdtf7sQ7JUZc9R44EOtxrVzufe6lnH9B8gubNkunap2ip+0DlBw1ENylRZx019npyRkTUAEByxNKKRZFRssZhNjPQMgu4lKExyKN+8VVnap0al621HDhfKuzo64bgq73GflCw1uzNhG+GTM0YqyiMAAIDgqF3RI3DbZWSorKO4T8lIKXr/MPabwy77jvXa/sl2NRrpMp00TbJYekzC6O15TCe2u4inOC+ePisQ6Spr6lWyrLpHgtP5jVs+Z0rU/X5yfibJcz3UaPxMQDBU1tRr7UuP646OPynb1ORafmiQVYOKHiYZ2V2XARvRMjljOPgb55G0BQAAgVe74ugtUu5hhvO2/5KOBX1K3PJHJKT4ivPi6bMCkczuMHTe4te8TtwVzbXEY2n0MBA0tStkHI1p3X/Cj766dimJW/QZNW0BAEB4OOydI2w93HRpNnUmbksTntbq9ql+12s11Bkal1XUakauNer+MAYARKequiavCVup8/dTfXObquqaou4WdeqhAr04GtOaPBYSORqdVt4r5VzOaFIEhX9/KQEAAPhr5wb3WlbdmE1Stmmv8s1b+7Tbrn8YAwAQCo2t3hO2/WkXaZz1UK84LVuStPK9Xdq4fa/sjpi6IRfon15iWsmQWj7vbAcEASNtAQBAYO3f7VezLO3r1+6j9Q9jAED0yUpJCmi7SESZBMALP2Nav9sBfUTSFgAABFbycL+aNSq9X7uP5j+MAQDRJX9MhmxpSWpobvN4g7Szpm3+mIxQdy0gvE2y1tDcppJl1dSSj1B2h0FZi1DwM6b1u12M6XoexuMEuaFA0hYAAATWqGlSarbUUi9PdW0dhtSgTFU5cvq022j/wxgAEJ2uP+sk/erVD3ssd6YjSotyozI5YXcYKquo9VWtk1ryEYiR0SHUS0wrmTrXj5oW6p6FnafzsCvOycCgpi0AAAgss0UqXHz0hfsfec4SeWUdN/k9CVnXvUTrH8YAgOhTWVOv8xa/5jFhK3VeSIzmkah9mWQNkcE5Mrr7v5tzZHRlTX2YehajfMS0xtHpyewzF8XdJGTezsOuOCcDg6QtAAAIvNxZ0rVLpVT3P2QblKmSjgVa5cjv0+6i/Q9jAEB06S0p8b3pp2jdPRdF9e+lWJ9kLdb0NjJa6hwZzSRyAeYlpq03MvSdw3fqvBXJcZWY9HUedsU5GRiURwAAAMGRO0vKubxzRt39u2UfkqWd9hxddqBDxV3qXjlrYDW2tKnpwGFlJCcqK5m6WACA8OgtKWGS9Nzbn2n+RaeEslsBFw+TrMWSvoyMLhiXGbqOxYPcWaq0T9GTzz6rLO1To9JV5ciRQ2aZ4qz+c2/nYVeck8ePpC0AAAges0Ua8xVJkkVSQXh7AwBAr+IlORbrk6zFGkZGh4/dYahs5TbVO3J7rIu3+s/9Ob84J/uP8ggAAAAAABwVL8kxi9mk0qLOJFT3NBO15CMPI6PDh/rPx/Tn/OKc7D+StgAAAAAAHBVPybHCPJvK50yRNc39s1BLPvI4R0Z7S6GbJNkYGR0U8XIhxx+9nYddcU4eP8ojAAAAAABwVLyVDSjMs2lGrlVVdU1qbG2jlnyEco6MLllWLZPkdm4yMjq44ulCTm98nYddcU4GBiNtAQAAAAA4Kh7LBljMJhWMy9TsySOUPyZDVXVNennL59q4fS8zv0cQRkaHB6Oc3Xk7D7vinAwMk2EYMfUN3NLSorS0NDU3Nys1NTXc3QEAAECAxFOcF0+fFYhUlTX1KquodatlaUtLUmlRbswmIuLxM0cju8NgZHSIVdbUq2RZtSTPo5zjMUHZ9TwcNiRRMkl79rdzTvrB3ziPpC0AAACiQjzFefH0WYFIFk/JMWdSqnuCIJ6TUkBXXNRAoPgb51HTFgAAAAAAD5xlA2Kd3WGorKLWY31KQ52J27KKWs3ItcZs0hroDfWfEWokbQEAAAAAiGNVdU1uowe7MyTVN7epqq4pLpLYkSieRn1Hsni5kIPIQNIWAAAAAIA41tjqPWHbn3YILG7LB+KTOdwdAAAAAAAA4ZOV4n0W+P60Q+A4aw13Hwnd0NymkmXVqqypD1PPYHcY2rh9r17e8rk2bt8ruyOmpoxCBGCkLQAAAAAAXcTbrej5YzJkS0tSQ3Obx7q2JknWtM7jgNCh1nDkYvQzQoGkLQAAAAAAR8VjMsZiNqm0KFcly6plktyShM5UYGlRLonBEKPWcGRyjn7unkx3jn4unzMlZr8rEFqURwAAAAAAQPF9K3phnk3lc6bImuZeAsGalkQSKkyoNRx5ehv9LHWOfqZUAgKBkbYAAAAAgLjHreididsZuda4Kg0Ryag1HHniffRzvJWOCTeStgAAAACAuBfvyRgni9kU058vmlBrOPLE8+jneCwdE26URwAAAAAAxL14TsYgMjlrDUvHags7UWs4POJ19HM8l44JJ5K2AAAAAIC4F6/JGEQ2ag1HFufoZ29pcpM6R5/G0uhn6viGD+URAAAAAABxj1vRe6J+ZWSg1nDkcI5+LllWLZPk9l0Rq6OfKR0TPiRtAQAAAABxLx6TMb5QvzKyUGs4cjhHP3f/+Rg6JEFXTR6htEEDZXcYMfNdQemY8KE8AgAAAAAA4lZ0J+pXAr4V5tm07p6L9Oyt5+ib545WxpCBajrQoT+v36Eb/rhJ5y1+LWZ+TigdEz6MtAUAAAAQNbhdG8EW77ei91a/0qTO+pUzcv9/e3cfHldd5///dWaaJr1LQlLSSbCUwgIhLbbcpaTcqFBMpNuC634RVgisyH7N4krFr1vwq8YsvxXrzVpv2OqyKpSuYPn9FBrxSrdQ0aVNCdJWCaFoSyjaZBrb0Ex6kzSdc35/TE6aSWYmZ5LMzJmZ5+O6el3N5MyZz5ycmXnP+3w+77cva44JEInXY6jnxEn9eNvbo14v9gWOTLjYQ+mY1CFpCwAAACAtOF2uTWIXE5XNS9GpXwk4ky0XOCgdkzokbQEAAAC4nr1cO9pspkf+7hKdMSNXW9r8emZ3h7qPnRzahjqcgHPUrwScyaYLHNHq+Pr4fE0okrbZxgxK+7fL7PXrjd7p2jv9Ys2eOV0ypENH+zV7Ru6Y/2e2AgAAAJJp5Gwmj0xVevaoREfUpUK1mOW698ldsiJNd1JmLVNF4jBDO4T6lYAz2XaBI9tLx6QCSdts0rZJalotBTrkkbRA0hlWkRoGarXZrIxrV8xWAAAAQLIMn81U7WlRfc56lRndQ7/vsGNaK3JMm0nLVJEYTktvZAPqVwLOZOMFjmwuHZMKnlQPAEnStknaWCsr0BF2s0/dWpezVtWelrh2R9dQAAAAJIs/cDphuy5nrXzqDvu9k5jWXqa6Y9/hRA4VacguvTFymXO2fuex61dKp+tV2qhfCZxmX+CI9kowFLr4wwUOjBdJ22xgBqWm1bJkjXozsT9n63OekEem413aV1wbGtsUNKOsQwMAAAAmqKm1Uw/94nV5ZKo+Z72k0zGsLZ6Y9t6fZF8SDtGN1UhIys7vPHb9Sl9B+AxBX0EeZUaAQVzgQKJRHiEb7N8uBTqiXv3xGFKZDqvSs0c7zArHu82kotoAAABwn+HNx6707AkriTCS05j2yIkB6ttiSDY1EooX9StTjzrL7keDLiQSSdtscPSgo81KdGRcu8+UotpAwphBBd/epn1v7VOXVSjj7KWS16uuQJ+6j51U0cxclcyk8R8AAMONnAHpNFZ1sp0l6fM/f03Xlc/R1CksPsxm2dZIKF7D61cGT53SnuZf6sS7BzTtjLNUvqRa3imkFBKFOsvpI9MvcHDxIHV4h80GM+c42qxLhePafSYV1QYmXdsmnWj8nKad8OsCSRdI6ngpvgaABGcAgGw0cgak01jV6XbdxwZ05cMv6CsfXshnbBbLxkZC47Fr8+Mqa27QAp2uCX1wS7E6qup1SfWdKRxZZhq+ymA4u84yKwXcJ1MbdHHxILW4rJwN5i2V8ssiVLQNMS2pwypWi1ke124pqg2MoW2TrI21yj3uD7s53gaA2doEAwCQ3ezmY7YWs1wdVpGilRYdT0zbfewkn7FZjkZCY9u1+XEt2v5pnWmFN/E70zqsRds/rV2bH0/RyDITdZbTX9C01LzvsJ7dfUDN+w6n7d+KJo2px0zbbODxSjVrZGyslSVDxrC3f/u9o2HgDplj5PA9MlXp2aMSHVGXCtViluuWy9+jHW8dHrWk2/7/8OXfvnym0SOLmEFZgw0AIzVLMa1Qs5Qt/ZeP+dqzFPrC0NDYphsqfLyGAAAZz24+NpwpjxoGarUuZ61MK7wZ2URi2lfMcj5js5jdSKhuw04ZUliijEZCoZIIZc0NkiI3ADQtqbS5QcHrP0aphElCneX0likzU8e6eMD30+TgXTVbVKyUblkvo2m1FOgYutmvYjUM3DHmMu1qT4vqc9aHNX/osIrU8KtaffsFZ0u8pfR8swLGZf92GZPYAJDgDACQLaItC5akzWal6gZWheJSnY5L7Zj2lWlX6e7FZ+m68jn67NO/08FAX9h+osa0vbVqaV/MZ2yWopFQdHte3hwqiRAlqPUYkk+H9frLm7XgquXJHVyGos5y+sqkshY73jrMxQMXIGmbTSpWSuXLpf3bZfb69UbvdO2dfrFqZ05XbYQGSPb/c/7wC13R8m1pxFuPvcS7bmCV49qcnWn4ZgWMS4IaABKcAQAyWayZPbbNZqWe779cV3j2aPVVhZpaWKa90y/WXfkz9O/DVnV9eWVo9qSt2tOidTlrR+3Pjml/++Z86by7JvcJIW1keiOh8Trx7oFJ3Q5jo85yesqkmalNrZ164P97zdG2fD9NLJK22cbjleZfI4+kBYP/YjKD0qY1siJUxI13ifdw6fJmBYxbghoAEpwBADLZWMuCbYUz8nTXh2/XJYOTACLFtPbsyc///DUdOdav+pz1kqIv8V7U+lWp5o5QvIyslKmNhCZi2hlnTep2GJtdZ9nf0xcxAWgoNAs8m+ssu1GmlLWItdolEr6fJhaNyBDb/u3SWEu8jdASb6eGv1kBGWveUln5ZTKj/DreZik0wQAAZAOnM3a+sPwiR6u2ahaWaseDy3T99L0qM7pHJWxtHkPKPd4Zin2RVTKlYVCilC+p1kEVx2wA6FexypdUJ3dgGcyusyyNrkpBnWX3yoSyFk5Wu9j4fpocJG0RW4KWeEvufrMCJszjlVGzRoaMUUFuPM1SJIIzAED2mD0z19F2voJpjvc5dYpHn7p8pqNtf/eG84kISH9NrZ26es1W3fboDt331G7d9ugOXb1mKx3Rh/FOmaKOqnpJihrTdlbV04RsktkrBXwF4bMYfQV5lBp0qUwoa+F0tYuN76eJxzsrYkvQEm/J3W9WwKSoWCnjlvXqa/ycpp3wD93stAGgjSYYAIBs0NTaqS9vej3mNuNdFrzoonKpZeztfrDruL5bY/ElNAtkUsOgRLuk+k7tklTW3KA5Ojx0e5dRrM6qel1SfWfqBpeBgqallvZu9Z8y9Y2/XTTUc4Y6y+6WCWUtnE6sK5yeo6/+zcW8RyYBSVvENm+plF8mK9ApI8Jbj70cxukSbyk93qzgkBkc1dhu9szpo5rZxfp/xgcfFSs1rXy5gm9v07639qnLKpRx9lLVer2qCfSp+9hJFc3MVcnMLD0+AADIWQ29Ca08mbdU/dN9yjnmj1giwY5pm3rPdX29QUzcyCXAHpmq9OxRiY6oS4V6xSynB8cIl1TfqeD1H9PrL2/WiXcPaNoZZ6l8SbV8zLCdVE2tnWpobAub7Vg6OIGD9yV3s8ta1G3YKUMj27iHfr71irkpGJlzTifWPXLbpbrq/NkJHg0kkrYYi8cr1ayRsbFWloywxG28S7yHYxp9BmjbJDWtlgIdQ43tzrCK1DBQ63gGqa0002eSerzynnutLjj3Wl2Q6rEAAOAyTmvoTWjlicer3y18UJe/fJ9MK7wZ2ciY1t9zIv79I60MXwJc7WlRfc56lRmn+210WEVq6K1VS/tiEmXDeKdM0YKrlqd6GBmL2d/pzy5rMTLxbvvW83/UU6/8ybXffZ3OFr6S98WkoaYtxlaxUrplvYz88DcVv4pVN7AqrgRdKTV4MkPbJmljraxAR9jNPnVrXc5aVXscrD8cxg5EqB8GAED2cVpD7xt/u2hCMWTwwhWqG1glv8JXe42MaR967g1ikgxnLwGu9rRoXc5a+RTeINmOab1vNqZieMhCsS5e2bc1NLbRKC8N1Cws1Uurr9NnlkWeruPm7740wXMfZtrCmYqVUvnyUUvha2dOV22M5e9dw5Z/+/JZ5p0RzKDUtFqWrFFv5B4jNFulPucJbem/3PEMbEuhDwGWoQEAkH2c1tA7dKx/Qo9TOb9I98+6Vtf0XK4rhi2FbzHLw2KWd4+dZFZbhiuZlSePTNXnrJekUSUz7Jh2UetXpZo7QqsPEcauu9rV20c5r0kw1sUrS1JnTx/lW9LIU6+8E/F2t3/3jTZbmD4rqUHSFs55vNL8a4aWwi9I9XiQGvu3S4GOUQlbm8eQynRYlZ492mFWON4tgQgAANkpWR23h9cbjBWjuP0LNSaucn6Rama9pbKB7qjbeAwp93hnKPadf00SR+d+sequktAZH6cXr5xuh9RK9yR8zcJS3VDh48KMC5C0BRCfowcdbVaiI+PaPYEIgLRmBkc1HpTXG3UVyvAmhATEyFbJ7LhtzyD6/M9fU/exgajbuf0LNSbG6zH0vy+ZLjmp6OUw9s0W1F1NjGRdvEJypH0S3gzKu3+7qo4flArmhBrUE5+mBElbAPGZOcfRZl0qHNfuCUQApK22TTrR+DlNO+HXBZIukNTxUnwNGpmphGx16xVn61vP/2HU7YmooVezsFQnBkx95qe7x9zWtV+oMWGLLip3lrR1GPtmg7HqrjJDffySefEKiZfWSfhhDceH5JdJNWtCZTORVCRtAcRn3lIpv0xWoFNGhJDCtEINPVrM8rh2SyACYBQzOKqW+uyZ00fVT4/1/6TNXm3bJGtjrXItK6xzg93MxmnjTmYqIdtEWmY9XKJq6Pny0/gLNSbHGDGtZIQSFfOWJn1obpXuS77dbHj5FkMKOyNpAJV+RibhPTJVOayW+itmuUoKprvvu+9gw3GNfE8MdIZuv2U9idskS2jS9je/+Y2+/vWv69VXX1VnZ6d+/vOf6+abb455nxdffFH333+/Xn/9dc2dO1df+MIXdNdddyVymADi4fFKNWtkbKyVJSMsyLWbmTYM3OG4CZlEIAIggmFX+e1a6mdY8c1atSV89qoZlDXYoDFaMxunDRqZqeROxLSJEW2Zte0zy87Xp647PyGvA2a1YXhMq2hpspqv0oRsmLRf8u1yNIDKHMOT8DWeFn0pZ73KjNM1tDusIh289MvuivMGG46PSthKGopQmx4INajnfTFpnGdVxuHYsWNatGiRHnnkEUfbt7e3a/ny5frABz6g3bt3a9WqVfrEJz6hzZs3J3KYAOJVsVK6Zb2M/PDAwa9ix7PJhvMV5DGrDMBpg1f5reHLsnR61mq1x8l61tPs2atNrZ2TOcrT9m+XMZhcjsRjSGVGqEGjE8NnKsEdiGknX6xl1lIoZfbUK39K2OPbX6jtxxr52BIXk7PCYEyrETGt8suYURZBWi/5ThM1C0v10urr9OQ9V+rbty7Wk/dcqZdWX8f3pDRUs7BUP/vAIa2bulY+hcd0pca7uqT5vlDM6xaDDcejs6TAgdB2SJqEzrT90Ic+pA996EOOt//+97+v+fPn65vf/KYk6aKLLtJLL72kb33rW6quro54n/7+fvX39w/9HAgEJjZoAM5UrAxdZRuxdLl25nTVunHpMjKbg+ZPnIdpYvAqvyVrVCIl3lmrtoTPXk1Qg0ZmKrkHMe3kc8Mya2a1QVJYTKujB0M1bOctZSZZBMxQT7DBslDeowdVNXOO9F7Ow7RmBnXJ618NlUcYEXoabpy56rTpIs0Zk8pVNW2bm5u1bNmysNuqq6u1atWqqPd5+OGH1dDQkOCRAYjI45XmXzO0dHlBqseD7DQJzZ8kGkC5xuBV/mhpVY8hlSk0a3WHWeF4twlNACWoQSMzldIXMe3Y3LLMumZhqW6o8KmlvVtdvX1cxMtWgzEtYqPuagLR/CnzjBHThs1cdcP7j9OmizRnTCpXJW39fr/mzAk/AebMmaNAIKATJ05o2rRpo+7z4IMP6v777x/6ORAIaO7cuQkfa8qlU3MWAEiUSWr+JNEAyjUSNGvVlpAE0LylsvLLZEUpkRBvg0ZmKqU/YtqxlczKG9WYpcUsHzWDPhkXL7weg6ZJgEPMUE8Amj9lpnSbuToYz4rmjK7iqqTteOTm5io3NzfVw0iudGrOAgCJMonNnyQaQLlGgmat2hKSAPJ4ZdSskTbWyrTCz8d4GzQyUyl7ZVtMW9n3kprzPqM5Ojx0W8eweDZVFy+CpsWsW2AMzFCfRDR/ylwOY9qWv0xRfFmcxGhq69KLx2/XV6yvRSjpQHPGVEloI7J4+Xw+HTwYfpXh4MGDys/PjzgjISulW3MWAEiUSW7+JNEAyhXmLZXyyyJUtA0xLanDcj5r1WYodKEyYQmgipUyblmv/um+sJvjbdBIY8bMQEw7hrZN8j59p0qGJWyl0/FszWA8m+yLF02tnbp6zVbd9ugO3ffUbt326A5dvWYrcTIQgT1D/abFZ6nqvGIStuNF86fMNRjTjm53GWLHtLf9tzflnzNNrZ2q27BTTx1drLqBVfIrPF4+MW0OM75TxFUzbauqqvTLX/4y7LYtW7aoqqoqRSNymXRszgIAiZLAZfQ0gEohj1eqWSNjY60sGWHLs+KdtWpL2uzVipWaVr58VFO8Wq9XNw4rUdQV6FP3sZMqmpmrkpmULcpExLQxDJtVFi2e/fLUJ3TzR+5J6sUL+wvryLlulM4BxsYM9QlItyX0cG4wprU21oZmrg771ciYNpX5mKBpqaGxbejzb7NZqS39l4eVL/rT1EX6TfkNYo5t8iU0aXv06FHt3bt36Of29nbt3r1bRUVFOvvss/Xggw/qwIEDWr9+vSTpk5/8pL73ve/pn//5n/Xxj39cW7du1caNG/Xcc88lcpjpIx2bswBAoiRwGT0NoFKsYqV0y3oZIxpy+FWshoE74i4FlNQ6ex6vvOdeqwvOvVYXJP7RkCTEtJNojFllHkPy6bBqZrZLek9ShjTyC+twTHAAYmtq7RxV35YSfHGg+VNmq1ipP7zvEc168QsqM06v5BsZ06YyH9PS3h32+pUkU57wnFJggHxRiiQ0afvb3/5WH/jAB4Z+tpsr3HnnnXrsscfU2dmpd955Z+j38+fP13PPPafPfOYz+va3v633vOc9+s///E9VV1cncpjpIx2bswBAokxy8yeJBlCuUrEyVL9tRNPN2pnTVUvTTSQZMe0kcuGsskhfWIdjgkPmYWbo5GCG+iSYt1QnpvmUe8IfZQ0RzZ/S3Z4z3q/P9H9nzMabqcrHOH1c8kWpkdCk7fvf/35ZVqRr1iGPPfZYxPvs2rUrgaNKY+nYnAUAEmUSmz9JNIByJY9Xmn/NUNPNBakeD7IWMe0kcuGsMr6wZhdmhk4OZqhPjqa2Lj3Tc6v+PWetTGlUPGsYkkHzp7RWMitv9MzVKNulgtPHJV+UGq5qRIYxpGtzFgBIlElq/iTRAAoAkiE4t0oHVTx0cW0ke5VEcG7y6v/yhTV72DNDR86spjlz/OKZoY7I7MR3k1kZsfmTX8V6cMrnFCxfkaIRYjJUzi9SaUFe1DKXqc7HuH182c5VjcgwhnRuzgIAieKw+RNL6AEg9Vr29+ixk3doXc5amdboWWWSVH/yDt21vydppQjsL6z+nr6IswYpnZMZmBk6uZihPnHDE9+Rmj+1mOUy+z26idIsac3rMVS/okJ1G3bKkMLeg9ySj7n1irP1ref/MOp2t4wvm5G0TTfp3JwFABKF5k8AkBa6evu0eXBWWX3OepUpcmOWG5OY6EmHL9SYOGoXTy5mqE/cyIR2tCX0JL7TX83CUq27/dJRpVlSnY+JVC5muFSPDyRt0xPNWQAAAJCGZs/MlRRjVtngirFkJ3qifaE+Y0aOPrz4LBVMm6qgaRE3pzFmhk4uZqhPHInv7FKzsFQ3VPiGmiAOz8007zuc9NxMtEaCts8sO1+fuu58PvdSjKRtuqI5CwAAANJIU2unvrzp9aGfI80qS2WiZ/gX6i1tfj2zu0Pdx07qh9ve1g+3vU2zqjRHgmxyMUN94kh8Zx+vx1DVecVqau3U//l/f5eyhoixysVIoXPvqVf+pE9dd37Cx4LYaEQGAAAAIKHsGT3+QH/UbdyQ6PF6DPWcOKkfb3tb3cdOhv2OZlXpjWY7k8+eoe4rCE9009zVGTvxLWnUeemG90MkhhsaItJIMH0w0xYAAABAwow1o8fmhtp5NKvKXMwMTYyRS74pwRcft9Y6RWK45TOGcjHpg6QtAAAAgIQZa0aP7Rt/u0hXnT87CSOKjmZVmY0EWWLYS74xPiS+s4dbPmMoF5M+SNoCAAAASBinM3UOHYteOiFZmH2U+UiQwY1IfGcHt3zGUE85fZC0BQAAAJAw6TSjJ53GivEjQZY4QdMiIQ5E4ZbPGK/H0BeXV+gff7Jz1O8oF+MuJG0BAAAAJEw6zehJp7EiPiQTE6+ptXNU6YlSSk8AQ9zyGdPU2qmHnmuL+DvKxbiLJ9UDAAAAAJC50qlDejqNFc41tXbq6jVbddujO3TfU7t126M7dPWarUnp0p4tmlo7Vbdh56h6nf6ePtVt2MmxjiBoWmred1jP7j6g5n2HFTTHateIdBfrM0YK1bS99Yq5CR1DtNeq7YvLLyJh6yKGZVkZ9c4QCARUUFCgnp4e5efnp3o4AAAAmCTZFOdl4nNNp1l46TRWxGYnKEZ+6bUTJutuv5S/6QQFTUtXr9kaNQlkzx58afV1XPAYxHtMdov09x8uUecCr1X3cBrnkbQFAABAWsimOC9Tn2s6LVFPp7EiMhIUydG877Bue3THmNs9ec+V1BIWFxIQEjQtfW/rXn3r+T+M+l2izgVeq+7hNM6jpi0AAACAhEnX5CfNqtJfS3t31IStFFqK3NnTp5b2bv7WE+C0073T7TJZ0LTU0NgWsZ6ppVCyrqGxTTdU+NLifRIT89Qr70S8PVHnAq/V9EPSFslhBhV8e5v2vbVPXVahjLOXSl6vDh3t1+wZuZKhmP9PpwAfAAAAIZmyBDhoWmrZ9xcF396mEuOIzjv3PHnPuUryeFM9NMRAgiI5nHa6d7pdJuNCAmypOBd4raYfkrZIvLZNOtH4OU074dcFki6Q1PFSkRoGarXZrHS8m3QM8AEAALJVtCXAdmOidFkC3NTaqRef+ZE+PfCfKjO6Qze+JJ2Y5tO0FV+XKlamdoCIigRFclTOL1JpQZ78PX0RZ5DaZSgq5xcle2iuw4UE2FJxLvBaTT+eVA8AGa5tk6yNtco97g+72adurctZq2pPi+Nd0XkUAAAgPYy1BFgKLft0e7f0ptZOPfOT7+srA1+TT91hv8s97pe1sVZq25Si0WEsdoIi2lo9Q6GJISQoJsbrMVS/okKSRh1r++f6FRWsmhQXEnBaKs4FXqvph6QtEscMympaLUuWRr7m7Z/rc56QR6aj3aVTgA8AAJDN4ln26VZB09JDm17Tl3LWS1LEeNaSJavpAckMpmCEGAsJiuSpWViqdbdfKl9BeILJV5CXNrPqk4ELCbCl6lzgtZpeKI+AxNm/XUagI+qbkMeQynRYlZ492mFWONolNX4AAADcLxOWALe0d2vu0d+pbGr0xLJHkgIHpP3bpfnXJG1scM5OUIysreyj9Nqkq1lYqhsqfGnZeDBZ7AsJdRt2ypDCViNwISG7xDoXNPjzF5dfNKnngt0YtP+UqW/87SJ6CKUBkrZInKMHHW1WoiNx79rNAT4AAEC2y4QlwF29fc7jVIdxL1KDZGLyeD0Gk2vGwIUE2KKdC7aHnntDHo8xKedErMagvGbdi6QtEmfmHEebdakw7l27OcAHALiAGZT2b5fZ69cbvdO1d/rFmj1z+tCMgtkzciVD6gr0qfvYSRXNzFXJzNBth3qP69xjv9fUE136i86QcfZSyesNu1+s/5MMADKj2UnJrDzncarDuBepQzIRbsKFBNhqFpbKNKV//MnOUb/r6jmux36yQaVXF2rRReXSvKWSx+tsx4OxsI4eVMtfpuje//YqOKJCaro1Bs1GJG2ROPOWysovkxXoiFg82bQkv4rVYpY73mU6BPgAgBRr2yQ1rZYGP38WSDrDKlLDQK02m5Ux71rtaVF9zvqhDvEXSup4ydl9hytltgyyXCYsAa6cX6Q/zVykjv4i+dQ9qqatJJmSjPyzZMxbmvTxAUhvXEiANFg//bm2UbeHxaQtCv3LL5Nq1kgVK2PvdFgsLEmVkv4nd3Q8ayn0mdzQ2KYbKnyu/kzOVjQiQ+J4vDJq1siQoZF9w+yfGwbukOnwNEyXAB8AkEJtm6SNtbIGg1SbT91al7NW1Z6WqHet9rRoXc7aUR3indx3JHvmQlNrZ3zjBzJIujc78XoMfXHlxfqXgVpJihjPGpLM6oedz3wCAGCYSI07o8WkCnRKG2tD8W40g7GwHMbC6dAYNJuRtEViVayUcct69U/3hd3sV7HqBlbFNWspXQJ8AECKmEGpabUsWaOaYNrX+upznpBH5qi7emSqPkaH+Fj3jcTO7TQ0tik4MtMDZJGahaV6afV1evKeK/XtWxfryXuu1Eurr0ubeK5mYalu/rtP6vM5/yy/wld6+VWsT55cpas3zeQCDRBB0LTUvO+wnt19QM37DvN5CEQwsl9PrJh0KMJseiAU9440GAuPbms2djxL3yB3ojwCEq9ipaaVL1fw7W3a99Y+dVmFMs5eqlqvVzdSHxAAMFn2b5cCHaMStjaPIZXpsCo9e7TDrAj7XaVnz1BJhHjvG83wmQssf0Q2S/clwKHak5/XIy98RNt/1agSHVGXCtVilsuURwY1AYFRYjU94nUCnDayX89YMalkSYEDobh3/jXhvxqMhaOJFc/SN8idSNoiOTxeec+9Vhece60uSPVYAACZyWH39kjd4J12iHfcSX4YZi4AmeHJ3x5QZ4SLNtQEBMI1tXaqbsPOUXP9aHoEjDaycafjWDNS3DuOWJi+Qe5GeQQAAJAZHHZvj9QN3mmHeMed5Idh5gKQ/iLVHByOmoBASNC01NDYFmFxNqWDgEjsxp1SKIHqONaMFPeOMxamb5B7kbQFAACZYd5SKb8sQkXbENOSOqxitZjlo37XYparwyoa1WjIyX2jMRRaCsrMBSD9OZ0xz8x6ZDsucADxsxt3zsnPHTsmlWTlnxWKe0eKMxYunJ7DzHeXI2kLAAAyg8cr1ayRIY0KVu3At2HgDpkRwh9THjXE6BAf676R2I/OzAVkq0xrQOR0xjwz65HtuMABjE/NwlJ985bFY8eklrRn0f8Nxb3DBE1Lze1HtHH2p2TJchTPPnIbCVu3o6YtAADIHBUrpVvWy2haHdaIwa9iNQzcoc1mZdS7bjYrVTewSvU561Wm7rjuO5KPZivIYpnYgGhkzcGRqAnoTkHTUkt7t7p6+2hsnCRc4ADG79DRfkljx6Qvv3SmvjqnUzdU+NTS3q0tbX49s7tD3cdOSjpHL3hix7P2Z9aVadwkNFsYlmWl92XvEQKBgAoKCtTT06P8/PxUDwcAAKSCGZT2b5fZ69cbvdO1d/rFmj1zumSEAuLZM3IlQ+oK9Kn72EkVzcxVyczQbYd6j+vcY7/X1BNd+ovOkHH2UsnrDbtfrP+TGEicbIrz0vW5RmtAZL8a0nkZpv3cJIU9v0x4bpkoEy8epIOgaenqNVvHvMDx0urrsvJzkgsJiKV532Hd9uiOoZ89MlXp2aMSHVGXCtViloet+pqZO0VH+09F3Fe0+/KZ5Q5O4zyStgAAAEgL2RTnpeNztZM10epZZkKyhkRgesjkiwfpgAsckfH+gbGMddFjMhTPmKp//fBCzrkUcxrnUdMWAAAAwIRlQwOimoWlemn1dXryniv17VsX68l7rtRLq6/jy6+LBE1LDY1tERMe9m0NjW1pX2fZzeymSr6C8BIIvoK8rE7Y1m3YOeo90t/Tp7oNO9XU2pmikcFNvB5D9SsqEvoYX1h+UVa+BtMVNW0BAAAATFi2NCDyegxVUQfQteK5eMDfMXFqFpYO1dvM9lIAY11IMBS6kHBDhS8rjw/C2Rc9Hvj/XtOREwOTvn9fwbRJ3ycSh6QtALhY8NQp7Xl5s068e0C5hWUKlFyhQ8dPOaqrSY1NAEAy0YAIbpAtFw/SwdAFjsE683r9oDRzjjRvqUZ2vs9kXEhAvGoWlmpWXo4+9p8vT9o+aZiZnkjaAoBL7dr8uMqaG7RAh4du67CKtH6gNq4u9jZqZgEAEqlyfpFKC/LGbECUSV8YaSrkPlw8cJm2TVLTainQcfq2/DKpZo1UsTJ140oiLiRgPK48tzjmZ2o87E+l+hUVfEalGWraAoAL7dr8uBZt/7TOtA6H3e5Tt9blrFW1pyXufVIzCwCQSMNr8Y38SpiJXxibWjt19Zqtuu3RHbrvqd267dEdunrNVj5nU8y+eBDtLDMUupCdSRcPXKttk7SxNjxhK0mBztDtbZtSM64k40ICxmMy69tmcz3pdEfSFgBcJnjqlMqaGyRJI7/X2j/X5zwhj8y49kvzDQBAomVLAyKaCrlXtl08cC0zGJphG6slXNMDoe0yHBcSMF5Dn6n5uXHft2hGju6+6hwaZqY5yiMAgMvseXlzqCRClMjOY0hlOqxKzx7tMOO7+krNLABAomV6AyKaCrmfnehoaGwLS6z7KBWVPPu3j55hG8aSAgdC282/JmnDSgX7QkLdhp0yFJ7G5kICxmJ/pn5v61596/k/xNy2aEaOPrz4LC2r8GXU5242I2kLAC5z4t0DjrYr0ZFxPwY1swAAiTTUgCgD0VQoPWT6xQPXO3pwcrdLc1xIwER4PYbuW3a+LvTNHHUOkajNbCRtAcBlpp1xlqPtulQ47segZhYAAONDU6H0kckXD1xv5hxHm7X8ZYrib6+bnriQgIniHMo+JG0BwGXKl1Tr4JZinWkdHlXTVpJMS/KrWC1medz7zsTO3QAAJBNNhQAH5i2VlV8mK9ARsZGOHc9+Zsd0/eb9VtYknbiQgIniHMouNCIDAJfxTpmijqp6SaGAdjj754aBO2TG+RZOzSwAACaOpkKAAx6v/nDJFyQrdjx7IDCglvbu5I8PANIASVsAcKFLqu/U75Z+R38xwq+i+lWsuoFV2mzGv5As0zp3AwCQCnZTIWl0z1AukAKn7Tnj/aobWCW/wi9gjIxnKSUCAJFRHgEAXOqS6jsVvP5jev3lzTrx7gHlFpYpUHKFbjx+SrUzciVDOnS0X7Md/J96RwAATB6aCgFjK5mVp81mpbb0X65Kzx6V6Ii6VKgWszxsxRilRAAgMpK2AOBi3ilTtOCq5akeBgAAYwqaVlY1R6EhDBCbXUrE39OnHWbFqN/TawEAYiNpCwAAAGBCmlo7R806Lc2CWac0hAGis0uJ1G3YKUPS8NK2lBIBgLFR0xYAAADAuDW1dqpuw86whK0k+Xv6VLdhp5paO1M0MgCpZpcS8RWEl0A4Y0aOPn7VOSqYNlXBkZ3KAACSmGkLAAAAYJyCpqWGxjZFSrlYCs2ma2hs0w0VPmbTAVlqeCmRLW1+PbO7Q93HTuqH297WD7e9nRWz8gFgPJhpCwAAAGBcWtq7R82wHc6S1NnTp5b27uQNCoDreD2Gek6c1I+3va3uYyfDfpfps/KDpqXmfYf17O4Dat53mJnFABxjpm0qmUFp/3aZvX690Ttde6dfrNkzp9MRHgAAAGmhK3BMV3raonaFH9quN3piN1NkWyM2IB7ZOis/W+t9A5gcJG1TpW2T1LRaCnTII2mBpDOsIjUM1GqzWRnXrnjTBwAAQNK1bVLNls/ppqn+oZs6osSzJbPyRt47o5CYcQ+S5+4Uz6z8TGnuZ9f7HpmotmcWr7v9Ut4fAMREeYRUaNskbayVFegIu9mnbq3LWatqT0tcu8v05SQAAABwmcF4dupxf9jNI+NZQ6HkZeX8ohQMMjloxOYeTa2dunrNVt326A7d99Ru3fboDl29Zit/AxdwOts+U2bljzWzWArNLKZUAoBYSNommxmUmlbLkqWR13vtC8D1OU/II9PxLnnTBwAAQNIMxrMaI571Dsaz9SsqMnamI4kZ9yB57m5OZ9tnyqx86n0DmAwkbZNt/3Yp0DEqwLV5DKnMOKxKz564dsubPgAAAJJiMJ6Nxo5nq2e9lfHLf0nMuAPJc/ernF+k0oK8qN+DM21WfrbNLAaQGCRtk+3oQUeblejIuHbPmz4AAAASymE8+70VZRmdsJVIzLgFyXP383oM1a+okKRRiVv750yalZ9tM4sBJAZJ22SbOcfRZl0qHNfuedMHAABAQjmMZz2zfAkeSOqRmHEHkufpoWZhqdbdfql8BeGvB19BXsbNys+2mcUAEmNKqgeQdeYtlfLLZAU6ZURYwGNakl/FajHL49qtodCHHW/6AAAASKjBeFaBTinignQj9Pt5S5M9sqSzEzP+nr5oR4IYPQlInqePmoWluqHCp5b2bnX19qlkVuj1kSkzbG32zOK6DTtlKPydMhNnFgNIjITPtH3kkUd0zjnnKC8vT0uWLFFLS0vUbR977DEZhhH2Ly8vwz5YPV6pZs3gG3f4G7RdYqlh4A6ZcfxpeNPHhJhBqf1/pNf+XwXf+o2a/9ilZ3cf0LY/HtK2vYf0851/1g//5y39fNfp24b//tndB9S87zA1wgAAGY2YdpjBeDYkykLnmq+Gtstw2bbk260q5xfprPwcXelp00rPdl3paQtr7MysRnfxegxVnVesmxafparzijP29ZFNM4sBJEZCZ9r+9Kc/1f3336/vf//7WrJkidauXavq6mq9+eabKikpiXif/Px8vfnmm0M/G0YGvoFXrJRuWS+jaXVYEwe/itUwcIc2m5Vx7c5XkKf6FRW86SN+bZtC3Z8Hz0OvpHlWkR4bqI37PCzlPMREmUFp/3aZvX690Ttde6dfrNkzp0uGdOhov2bPyB3z/5k6WwNAahHTRjAYz2pEPKv8slDCtmJl6saWZHZipqGxLayu6hkzcvThxWepYNpUBU2Lz6YE8u5p1PPez2naVP/QbR1WkRoGavXfgzEtyXMkjRlU8O1t2vfWPs20CvWNv1kqeb3EqgDiZliWlbDpcUuWLNEVV1yh733ve5Ik0zQ1d+5c/dM//ZMeeOCBUds/9thjWrVqlY4cOeL4Mfr7+9Xf3z/0cyAQ0Ny5c9XT06P8/PwJP4eEIkGBVGrbJG2s1chljfaE2bqBVXElbu0zkKvGGJcRFxCk01+2uIAAwBYIBFRQUJD0OI+YNobBeFZHD4Zq3c5bmhUzbCMJmpZa2ru1pc2vZ3Z3qPvYyaHf8dmUQGPEtJ/P+We9/+aPc+yRHG2bdKLxc5p2IvwCwndyPsF5CGCI05g2YTNtT548qVdffVUPPvjg0G0ej0fLli1Tc3Nz1PsdPXpU8+bNk2mauvTSS/WVr3xFCxYsiLr9ww8/rIaGhkkde9J4vNL8a+SRtGDwH5AUZjCUIItQfc1jhILc+pwntKX/cselOiyFErcNjW26ocLHhQQ4N/hlyxpRNManbq3LWRv3BQR/T5/qNuzkAgKASUFMO4bBeBahJd89J07qx9veHhVh8dmUIGPEtJYMPTz9v2RUjL64Aky6tk2yNtYq17LC6qX41K2vDHxN//iTk9LffZL3AACOJaym7aFDhxQMBjVnTnh32Tlz5sjv90e8z4UXXqgf/ehHevbZZ7VhwwaZpqmlS5fqz3/+c9THefDBB9XT0zP0709/+tOkPg8gI+3fHr6UcQSPIZUZh1Xp2RPXbi1JnT19amnvnuAAkTUGv2yNTNhKofNQCl1AGF6Xbiz217aGxjZqLQOYMGJaOBU0LTU0tkVsSMZnU4KMEdMasmQEDoS2g+sETUvN+w5nRo8MMyhrMKYdOXfF/vlLOU/ooU2vpffzBJBUCa1pG6+qqipVVVUN/bx06VJddNFF+sEPfqCHHnoo4n1yc3OVm5ubrCECmeHoQUeblejIuHbf1ds39kaANPRlK9q8bI8hlSl0AWGHWeF4t8MvIFSdVzwpQwUAp7IpprVLAmRyF3inWtq7w2rajsRnUwI4jGkdb4ekaWrtHFUHOq3LiOzfLsNBTDv36O/U0n4Z7wEAHElY0nb27Nnyer06eDD8A/LgwYPy+XyO9pGTk6NLLrlEe/fuTcQQgew1c87Y20jqUuG4dl8yK4M6ZCOxuIAAwOWIaaPLuKTLBDn9zOGzaRI5jGkdb4ekaGrtVN2GnZlVRiSOmJb3AABOJaw8wtSpU3XZZZfphRdeGLrNNE298MILYTMPYgkGg3rttddUWppmb9iA281bGuruHOVasGlJHVaxWszyuHZrKPRlrXJ+0cTHiOzABQQALkdMG5mddBk5s9ROujS1dqZoZKnj9DOHz6ZJNBjTji6yZDOk/LNC28EVMraMSBwxLe8BAJxKWNJWku6//349+uijevzxx/XGG2+orq5Ox44d09///d9Lkmpra8OaOvzLv/yL/vu//1tvvfWWdu7cqdtvv1379+/XJz7xiUQOE8g+Hq9Us2bwh/Ag146PGgbucNyEbPhe6ldUZO2ySIzDGF+2uIAAwA2IacNlbNJlgirnF6m0IC9W+pDPpsnm8WrXggckWRp5ug3FFjVfDcW+cIV4yoiklXlLZeWXRe3CYMe0f5q5iPcAAI4lNGn70Y9+VN/4xjf0pS99SYsXL9bu3bvV1NQ01MjhnXfeUWfn6avw7777ru655x5ddNFFuvHGGxUIBLR9+3ZVVDivYwjAoYqV0i3rpfzwWT9+FatuYJU2m5Vx7c5XkJeeS5mQWoMXEAxpVOKWCwgA3IKYNlzGJl0myOsxVL8i9Dce+enDZ1NiNLV26m9+NVufPLlKfoUnwjqtIu2q+nYo5oVrZGwZEY9XRs0aGTJGXUCwf/6XgTv0xZUX8x4AwDHDsqyMugQeCARUUFCgnp4e5efnp3o4gPuZwVAzqKMHFZxRopZgubqODWj2jFzJkLoCfeo+dlJFM3NVMjN026Gj/UO/P3S0P+sbj2AStG2SmlaHdYDusIrVMHBH3BcQsrmeIpDpsinOc/NzfXb3Ad331O4xt/v2rYt10+KzEj8gl6HWb3IETUtXr9k6dJw9MlXp2ROqGapCvWKWq6Rgul5afR0xqos07zus2x7dMeZ2T95zZXo262rbpBONn9O0E/6hmzqsYn0n5269/+aP8x4AQJLzOC9hjcgApAmPV5p/jSTJK8lZdT5gklWslMqXS/u3y+z1643e6do7/WLVzpyu2ggXCqL9nwsIAJB41G6NrWZhqW6o8KmlvVtdvX18NiXIyBnfpjzaYYbPZrdnfKdl8i9D2WVE/D19EUusGAqt4EvbEgIVKzWtfLmCb2/Tvrf2qcsqlPecq/Sv553JewCAuJG0BQC4w+AFBI+kBYP/AADuk/FJl0ng9RgkChMsY5fZZzi7jEjdhp2D5bFOy5gyIh6vvOdeqwvOvVYXpHosANJaQmvaAgAAAMgs1G6FGzDjO33VLCzVutsvla8g/G9zxowcffyqc1QwbWraNjIMmpaa9x3Ws7sPqHnf4bR9HgDcgZm2AAAAAOJiJ11G1m71UbsVScKM7/Q2vIzIlja/ntndoe5jJ/XDbW/rh9veTss60NSzBjDZSNoCAAAAiBu1W5FKWbHMPsN5PYZ6TpzUj7e9PSrx7u/pU92GnVp3+6VpkfBsau1U3Yadaf88ALgLSVu4nxkMK+RunL1U8nqjNiPqCvSp+9hJFc3MlS+fLw8AAACJQu1Wh8ygtH+7dPSgNHOONG9pqJY7JoQZ3+ktaFpqaGyLOFPaUij53tDYphsqfK7+PpcpzwOA+5C0hbu1bdKJxs9p2gm/LpB0gaSOl4rUMFCrzWalo12wJAUAAACpEDQt7f31T3T2yw2a1nfw9C/yy6SaNVLFytQNLkMw4zt9tbR3hyXbR7Ikdfb0qaW929UXhzLleQBwHxqRwb3aNsnaWKvc4/6wm33q1rqctar2tDjaTefgkpSm1s5EjBIAAAAYpam1U//3K1/R+S/+o3JPHAz/ZaBT2lgrtW1KzeAyjD3j+6bFZ6nqvGIStmmiqzd6onM826VKpjwPAO5D0hbuZAZlNa2WJUsjYy775/qcJ+SR6XiXDY1tdO8EAABAwjW1dureDb/Vpwf+U5JGxbNDFVibHgiVTgCyUMmsvEndLlUy5XkAcB+StnCn/dtlBDqinqAeQyozDqvSs8fR7oYvSQEAAMD4BU1LzfsO69ndB9S87zAXxUew61te4dmjMqM7QsLWZkmBA6Fat0AWqpxfpNKCPEV7iRgKlbqrnF+UzGHFLVOeBwD3oaYt3OnowbG3kVSiI3HtliUpAAAA49fU2jmq6RP9A8LZ9S2v8BxxdgeHcS/CBU2LOrZpzusxVL+iQnUbdsqQwhp52X/J+hUVrv+7ZsrzAOA+zLSFO82c42izLhXGtVuWpAAAAIxPU2un6jbsHNVwx0//gDD2JAHHcarDuBenNbV26uo1W3Xbozt031O7ddujO3T1mq2cg2moZmGp1t1+qXwF4d/TfAV5Wnf7pWlzMShTngcAd2GmLdxp3lJZ+WWyopRIMC3Jr2K1mOWOdmco9IHJkhQAAID42Uv+IxVCsBSKtRoa23RDhS/rZ5PZkwRazHJ1WEXyKXKJBEuGjPwyad7SJI8wvdkXD0aei/bFAxJk6admYaluqPCl7cxpe9Z3/ylT3/jbRZIhHTran3bPA4D7kLSFO3m8MmrWSBtrZVrhzcjssmkNA3fIjGOyOEtSAAAAxsde8h/N8P4BVecVJ29gLmTXt/T39KlhoFbrctbKtMKbkZkaXDZd81XJ403RSNMPFw8yl9djpOV7R6ySMen4fAC4C+UR4F4VK2Xcsl79031hN/tVrLqBVdpsVjraTSlLUgAAACbEaV8A+gecrm8pSf9tVqpuYJX8Cl/tdWzqHJn/63GpYmUqhpi24rl4gPSVLs0OKRkDINGYaQt3q1ipaeXLFXx7m/a9tU9dVqGMs5eq1uvVjUf7NXtG7tDyE/v/XYE+dR87qaKZufLlsyQFAABgopz2BaB/QIhd37KhsU2beyq1pf9yVXr2qERH1KVCtfSVa86m6aq3OplYEAcuHmS+dGl2yKxvAMlA0hbu5/HKe+61uuDca3VBqscCAACQhYYv+Y+UpKB/wGh2nc7vbd2rbz3/B+0wK8J+Tw3W+HHxILOlU71iSsYASAaStgCQqcygtH+7dPSggjNK1BIsl7/35NBM9JKZo2eqj/w/DRQAANLpJf91G3bKkMKSKvYnBP0DInvqlXci3s5svPhx8SBzRZu56pE5NEt907N7dUP5vfJOSX0ag1nfAJIh9e92AIDJ17ZJalotBTokSV5J86wiPTZQ67getM2NS9IAAMk3fMn/8BlmPj4nomI23uTi4kHmivRaqfa0qD5nvcqMwRrFA1L/v/27vH/99ZTXg2bWN4BkIGkLAJmmbZO0sVYaMVfBp26ty1kbVyM/yZ1L0gAAqWEv+W9p71ZXbx8rMsbAbLzJx8WDzDTyNVDtadG6nLWjtpt6/GAozr1lfUoTt8z6BpAMJG0BIJOYwdAM2wjho8eQTEuqz3lCW/ovlymPo12yfBMAMJzXYzAr1CFm4yUGFw8yz/DXgEem6nPWh/4/4k9q2JFp0wNS+XLJ403iKE9j1jeAZHD2jR0AkB72bx8qiRCJx5DKjMOq9OyJa7fDl28CAABn7Nl40dI2hkJliJiNFz/74sFNi89S1XnFJMfS3PDXSqVnj8qM7lEJ29MsKXAgFPemkD3r21cQftHFV5DHCjUAk4KZtgCQSY4edLRZiY6Ma/cs3wQAwDlm4wHODH+tOI5THca9icSsbwCJxExbAMgkM+c42qxLhePaPcs3AQCID7PxAGfs18qpGSXO7uAw7k00Zn0DSBRm2gJAJpm3VMovkwKdilTX1rQkv4rVYpbHtVuaKQBAdguaFjPJJoDZeIAzNQtLdUP5ver92vc0o78rYokE05L6p/s0bd7S5A8QAJKIpC0AZBKPV6pZE+qqO2Ihpjn434aBOxw3IZNYvgkA2a6ptVMNjW3q7DldIqe0IE/1KyqYJRoHGrgBDnm8+lfzLn1FX5NphTcjOx3P1upf5VFq2pABQHJQHgEAMk3FSumW9VJ++Bdpv4pVN7BKm83KuHbH8k0AyF5NrZ2q27AzLGErSf6ePtVt2Kmm1s4UjQxApmpp79ZTRxerbmCV/Apf5WXHs08dXUyDXAAZj5m2AJCJKlZK5ctDXXWPHlRwRon2B8tV03tSlcdOqmhmrkpm5kqGdOhov2bPiPx/lm8CQPYKmpYaGtsiFNsJreMwJDU0tumGCh+fEwAmjd34drNZqS39l6vSs0clOqIuFarFLB9aMUaDXACZjqQtAGQqj1eaf40kySupKrWjAQCkmZb27lEzbIezJHX29KmlvZtl/3GiRvD4cewy3/DGt6Y82mFWRNxu9ozcZA1pFM5DAMlA0hYAAADAKE5nsTHbLT7UCB4/jl12qJxfpNKCPPl7+iLO9Ld99unf6csrk/+35zwEkCzUtAUAAAAwyvDZbpOxHagRPBEcu+zh9RiqXxGaXRtr7urBQHL/9kHT0ref/6M+yXkIIElI2gIAAAAYxZ7tFi1pYig0u6xyflGULTDcWDWCpVCN4KAZa25hduLYZZ+ahaVad/ulmpMfvQRCMv/2Ta2duuqrL+hbz/8h5WMBkD1I2gIAAAAYJdZsN/vn+hUV1HF0KJ4awQjHsctONQtL9c1bFsfcJhl/e3uWtz/Qn/KxAMguJG0BAAAARGTPdvMVhJdA8BXkad3tl1K/MQ7UCB4/jl32OnQ0dqLUlqi/faxZ3skeC4DsQyMyAMDkMYPS/u0ye/16o3e69k6/WLNnTpeMUNA9e0bumP+nAy8AuEvNwlLdUOGjU/oEUSN4/Dh22Stlf/vBmHbfvr2a13tIB1Uu0+GcN85DAJOFpC0AYHK0bZKaVkuBDnkkLZB0hlWkhoFabTYr49oVHXgBwF28HkNV5xWnehhpza4R7O/pizhrz1BoBjM1gkfj2GWvlPzth8W0F0h6aqrU4SCm5TwEMNkojwAAmLi2TdLGWlmBjrCbferWupy1qva0xLU7OvACADINNYLHj2OXvWL97aVQHdlbr5g7eQ84GNNqnDEt5yGAyUTSFgAwMWZQalotS9aoYNqOWetznpBHpuNd0oEXAJCJqBE8fhy77BXtb2/71vN/1NVrtk78Yv9gTKsIc3rHimlLOQ8BJADlEQAAE7N/uxToiDj7QQoFuWU6rErPHu0wKxzvdngHXpbkAgAyBTWCx49jl73sv/33tu7Vt57/w6jf26u0JpQ4HYxpo4kW035m2fn61HXncx4CmHQkbQEAE3P0oKPNSnRkXLunAy8AINMMrxEcNC2SkHGgvnJ2e+qVdyLebilUPqGhsU03VPjG9xqKM6alBwOARCNpCwCYmJlzHG3WpcJx7Z4OvACATNXU2qmGxjZ19py+QEkiCIispb077LUy0oRXacUR0xbNyNGvP/cBTZ1CxUkAicM7DABgYuYtlfLLIlS0DTEtqcMqVotZHtduDYW+uNKBFwCQiZpaO1W3YeeoJBTNOIHInK6+GvcqrThi2u5jA3p1/7vjexwAcIiZtgCAqIYv2Zw9I1cypENH+0f9v2jxF1T+m3uHlqbZ7B5iDQN3yIzjOiGdoAEg9Vi2nzhB01JDY1uEdkeTtMw7w3AuQnK++mrcq7Q8XqlmjbSxVqZ1uvmYFDmmpYQXgEQjaQsAGM0MquXFRv1i+2794fgMtZjlYyRdC1XtuU/1OetVZnQP3epXsRoG7tBmszKuh/exNBQAUopl+4mV8GXeGYRzEbbK+UUqLciTv6cv4gUPSSqakaPL5p0R+sEMhpqLHT0YKn0wb2koMRtLxUr94X2PaNaLX1CZYse0lPACkGgkbQEA4do26UTj51R5wq9KSZoqdVhFahiojZl83WxWakv/5ar07FGJjqhLhUPJ3lXX/5Xmnzkz5mxd+//MoAGA1LKX7Y9MikxKd3ZISsIy7wzBuYjhvB5D9SsqVLdhpwwpYuK2+9iA3vf1X+nfL/2zLnn9q1Kg4/Qv88tCM2krVsZ8nL9639/p2uYzNffo70bFtFJoJryPEl4AkoCkLQDgtLZNsjbWKndEGOxTt9blrFXdwKqYiVtTHu0wK8JuMyT99Ld/1kurryMRCwAux7L95Ej4Mu8MwLmISGoWlmrd7ZeOmn093KLe32jR9rWyjPCyXQp0ShtrpVvWj5m4vaVyvr71/MCo2ynhBSCZaEQGAAgxg1LTaknWqA8HOyatz3lCHplx7Xb4Ek8AgLvFs2wf42cv846W8qEZJ+cioqtZWKpff+4DKpoxddTvPDL1pZz1khTh9TV4CaDpgVDcG0FTa6euXrNV33r+DxF/7yvIY4Y3gKQhaQsACNm/XQp0RP0C6TGkMuOwKj17xrX7bF/iCQDpgGX7yWEv85ZGJ5aYyRfCuYhYXt3/rrqPnRx1e6Vnj8qMbkV/6VhS4EAo7h3BLscR7WLBZ5adr5dWX0fCFkDSkLQFAIQcPehosxIdGdfus3mJJwCkC5btJ4+9zNtXEH4smckXwrmIWKIl6x3HqSPi3ljlOKTQxZSnXvmT4/EBwGSgpi0AIGTmHEebdakwrt3SrAEA0sdY3dl5T59cNQtLdUOFTy3t3erq7aMZ5zCci4glWrLecZw6Iu6NpxxH1XnFDkcJABPDTFsAQMi8paGuulEKJJiW1GEVq8Usd7xLlngCQHph2X7yeT2Gqs4r1k2Lz1LVecUc20Gci4glWl3oFrNcHVaRzGhTZmVI+WeF4t5hKMcBwI1I2gIAQjxeqWbN4A/hIbAd+DYM3CEzjo8OlngCQPph2T7cgnMR0QxP6g9nyqOGgdrQ/0ckbi0ZsiS9ecn/1bO/96t532EFBzeaPTPX0eNSjgNAMhmWZUW9BpWOAoGACgoK1NPTo/z8/FQPBwDST9smqWm1FOgYuun4NJ/2X/4ldc+r1qGj/Zo9I1cyFPP/LPEEMNmyKc5zw3MNmhbL9uEKnIuIpqm1U5//+WvqPjYQdnu1p0X1OetVZnQP3dZhFetrukvP9F82dFtpQZ5WLirVs7s75A/0R30cuxzHS6uv49wDMGFO4zyStgCA0cxgqKvu0YOhml/zloZm4gJACmVTnJdNzxWIhEQtnDp5ytSVD7+g7mMnw273yFSlZ49KdERdKlSLWR7XijGbfdYxuxvAZHEa59GIDAAwmscrzb8m1aMAACQZibLU4viHNLV2qqGxLawxVGlBnupXVJA0wyhTp3j0lQ8vVN2GnWFN60x5tMMcXUIhXj7OPQApQtIWAAAAAImyFOP4hzS1do5KvkmSv6dPdRt2MtsREdn1jyOVSpiob/ztIl11/uxJ3ScAOEEjMgAAACDL2Ymy4QlD6XSirKm1M0Ujyw4c/5CgaamhsW1UwlbS0G0NjW1DzaOA4WoWluqLf71g0vd76Fj0WrcAkEjMtJ2g4KlT2vPyZp1494ByC8sUKLlCh46fctSkh4Y9AAAASLWgaemhTa9piadtVO1HS6F6jg2NbbqhwkesmgBjJSqz6fi3tHePSlwPZ0nq7OlTS3u3qs4rTt7AkDZ8+XmTvs+SWZO/TwBwgqTtBOza/LjKmhu0QIeHbuuwirR+oFabzcq495eNy58AAACQWnt//RM93f8FlU0d3mW9SA2DMS2JssQiUXlaV2/04zCe7ZB9KucXqbQgL+ZryilDoXq2lfOLJj4wABiHhJdHeOSRR3TOOecoLy9PS5YsUUtLS8ztn376aZWXlysvL08XX3yxfvnLXyZ6iOOya/PjWrT90zrTOhx2u0/dWpezVtWe2M8zkmxb/gQAAJAuMjWmVdsmXfDre+VTd9jNkWJaEmWJQaLyNKczGpn5iGi8HkP1KybefMxWv6Ii42e4A3CvhCZtf/rTn+r+++9XfX29du7cqUWLFqm6ulpdXV0Rt9++fbtuu+023X333dq1a5duvvlm3XzzzWptbU3kMOMWPHVKZc0NkqSR79/2z/U5T8gjM679UqcJAADAfTI1ppUZlJpWS7IcxbQkyhLD6XGdPSM3wSNJPXuWZLQUmaHQ6kRmPiKWmoWl+v7tl6pwes6491E4PYemdwBSzrAsK2HZwSVLluiKK67Q9773PUmSaZqaO3eu/umf/kkPPPDAqO0/+tGP6tixY/rFL34xdNuVV16pxYsX6/vf/37Ex+jv71d//+nC4IFAQHPnzlVPT4/y8/Mn+RmFvL7tOS3Y8ndjbnfryS9ohzm+q3xP3nNlxi9/AgAAiEcgEFBBQUFC47xIMjWmVfv/SI//9Zib3XryC9o/61K9tPo6ZpwlQNC0dPWarfL39EWsa2vz5efpyyszv5Sa3ZRNUtjxsM88EmlwKmha+t7WvfrxtnYdOTEQ133/6+4luur82QkaGYBs5zSmTVhN25MnT+rVV1/Vgw8+OHSbx+PRsmXL1NzcHPE+zc3Nuv/++8Nuq66u1jPPPBP1cR5++GE1NDRMypidOvHuAUfblejIuB8jG5Y/YZKZQWn/dpm9fr3RO117p1+s2TOn0xAPAIAJyOSYVkcPOtqsREd0F0uEE8Zezl23YacMKWri9mAgVEoto5OWZlA1M/bqmWs79INdx9XUe67MwcWhPvp/IE5ej6H7lp2vT133V2pp71ZXb59mz8jVZ5/+nQ4GIl8ksevYXskEKgAukLCk7aFDhxQMBjVnzpyw2+fMmaM9e/ZEvI/f74+4vd/vj/o4Dz74YFhQbM9KSKRpZ5zlaLsuFY77MVh+hri0bQotbwx0yCNpgaQzhjUQiQcN8QAAOC2TY1rNnDP2NpJuX3aFKokLEqpmYanW3X6pvrzpdfkD/RG3sRRKKDU0tumGCl/mJdGHxbOLJP27pP4in3638EEFL1zBxAKMm9djhK1i/fLKyBdJ7LOLOrYA3CLhjcgSLTc3V/n5+WH/Eq18SbUOqljRys6altRhFavFLI9739RpQtzaNkkba2UFOsJuHm9TPBriAQCQfKmIaTVvqZRfJkWpIGrJkJV/lirfvyLxY4FqFpbqm7csjrmNJamzp08t7d0xt0s7g/GsRsSzuccPqrJllar6t5FEw6SxL5L4CsInSvkK8jJ7JjuAtJOwmbazZ8+W1+vVwYPhy64OHjwon88X8T4+ny+u7VPFO2WKOqrqdeb2T8u0wpuR2YnchoE7hpbyOMWVPcRtsIGIJWvU1y2PETof63Oe0Jb+yx2fjxk/iwMAgDhkckwrj1eqWRNKlkWYc2ZIUs1XQ9shKQ4djTzLdqSMKqU2rCHeaIORadMDUvlyzkVMmpqFpbqhwjdUNoEycQDcKGEzbadOnarLLrtML7zwwtBtpmnqhRdeUFVVVcT7VFVVhW0vSVu2bIm6fSpdUn2nfrf0O/qLEV7rxq9i1Q2sintJusSVPYzD/u1SoCNqh12PIZUZh1Xpibx8M5qMncUBAECcMj2mVcVK6Zb1Uv6I+DO/LHR7xcrUjCtLOS2RllGl1Abj2egsKXAgtB0wieyyCTctPktV5xWTsAXgOgmbaStJ999/v+68805dfvnlqqys1Nq1a3Xs2DH9/d//vSSptrZWZ511lh5++GFJ0n333af3ve99+uY3v6nly5frqaee0m9/+1v9x3/8RyKHOW6XVN+p4PUf0+svb9aJdw8ot7BMgZIrdOPxU6p10PSJBlCYsDgaiIxHRs3iAABgnDI9plXFytAsxv3bQ7HFzDmh0gnMaky6yvlFKi3Ik78ndpOkjCql5jCedbwdAAAZIqFJ249+9KP6y1/+oi996Uvy+/1avHixmpqahhozvPPOO/J4Tk/2Xbp0qX7yk5/oC1/4gj7/+c/r/PPP1zPPPKOFCxcmcpgT4p0yRQuuWp7qYSCK4KlT2jMiqX7o+KnMSaQ7bCAy3qZ4GTWLAwCAccqGmDYoj1rMCnUFz1WJmadKeUTKNvm8HkP1K8KbJHlkqtKzRyU6oi4Vaunlf53qYU4uh/Gs4+0AAMgQhmVZUdpppadAIKCCggL19PQkp4EDXGvX5sdV1tygOTo8dFuHVaSGgVrH5StKC/JUv6LCvSUrzKC0dqGsQKeMCPMxTCtUsuPq/m/HVWPZnsXx0urr3J20BgBklWyK85L5XJtaO9XQ2KbOntMrbFwfA2U4+2/y3t7fqD5nvcqM0yWrOqwifSfnE3r/zR/PjL+PGdSJr1co97hfkcJO05L6p/s07XNtzP4GAGQEp3FewmraAqm0a/PjWrT90zrTOhx2u0/dWpezVtWeFkf78ff0qW7DTjW1diZimBM32EAkNBMjPModb1M8GuIBAJA9mlo7VbdhZ1jCVkqDGCjD1Sws1Usrj+r7U9fKp/AeAz516ysDX9MzP/l+Rvx9gvKoYaBW0un41XY6nq1VkK+uAIAswycfMk7w1CmVNTdI0qir9fbP9TlPyCNzzH3ZcWNDY5uCI6NItxhsIGKMaCAy3qZ4NMQDACA7BE1LDY1tEWunpkUMlMnMoDybHwiVR4gSz34p5wk9tOm1tP/7tLR366mji1U3sEp+hdfqtePZp44upkEuACDrJLSmLZAKe17erAU6LEWZJOoxpDIdVqVnj3aYFWPuz5LU2dOnlvZuVZ1XPLmDnSzDGoiYvX690Ttde6dfrNqZ01VLQzwAABBBS3v3qBm2w6VFDJSp9m+XEeiIFs4OxbNzj/5OLe2XpfXfx258u9ms1Jb+y8Pq97aY5UMrxmiQCwDINiRtkXFOvHvA0XYlOhLXfl0fKHq80vxr5JG0YPAfAABANE5jG9fHQJno6EFHm5XoSNr/fYY3vjXliTqpgga5AIBsQ3kEZJxpZ5zlaLsuFca1XwJFAACQSZzGNsRAKTBzjqPNulSY9n+fyvlFKi3Iizqr2FCoMV7l/KIoWwAAkJlI2iLjlC+p1kEVj2pkYDMtqcMqVotZ7mh/BIoAACATkSxzsXlLZeWXRe3AYMezf5q5KO3/Pl6PofoVodm1I89FGuQCALIZSVtkHO+UKeqoqpcUqwPtHUP1sWIhUAQAAJmKZJmLebwyatbIkBE1nv2XgTv0xZUXZ8Tfp2Zhqdbdfql8BeGzhmmQCwDIZoZlWendbnSEQCCggoIC9fT0KD8/P9XDQQrt2vy4ypobNEeHh27rsIrVMHCHNpuVjvZRWpCn+hUVBIoAALhANsV5yXyuTa2damhsC2tKRgzkEm2bdKLxc5p2wj90U4dVrO/k3K333/zxjPv7BE1LLe3d6urto0EuACBjOY3zSNoiowVPndKelzfrxLsHlFtYpkDJFTp0/JRmz8iVDOnQ0f6o/ydQBADAXbIpzkv2cyVZ5mJmUMG3t2nfW/vUZRXKe85VqjzvTP4+AACkKadx3pQkjglIOu+UKVpw1fJUDwMAAMDVvB5DVecVp3oYiMTjlffca3XBudfqglSPJQG4YAAAQGQkbQEAAAAASUdpDgAAoqMRGQAAAACkiaBpqXnfYT27+4Ca9x1WcGSnsjTR1Nqpug07wxK2kuTv6VPdhp1qau1M0cgAAHAHZtoCAAAAQBrIlJmpQdNSQ2ObIqWbLUmGpIbGNt1Q4aNUAgAgazHTFgAAAABcLpNmpra0d496HsNZkjp7+tTS3p28QQEA4DIkbQEAAADAxcaamSqFZqamS6mErt7oCdvxbAcAQCYiaQsAAAAALpZpM1NLZuVN6nYAAGQikrYAAAAA4GKZNjO1cn6RSgvyFK1araFQrd7K+UXJHBYAAK5C0hYAAAAAXCwTZ6beesXZEcs92Inc+hUVNCEDAGS1KakeAAAAAAAgOntmqr+nL2qi05cmM1ObWjvV0NgWtdyDryBP9SsqVLOwNMkjAwDAXZhpCwAAAAAu5vUYql9RIUmjSgqk08zUptZO1W3YGTVh+5ll5+ul1deRsAUAQCRtAQAAAMD1ahaWat3tl8pXEF4C4YwZOfr4VeeoYNpUBc1I83DdIWhaamhsizhTWAoln5965U/JHBIAAK5GeQQAAAAASAM1C0t1Q4VPLe3d2tLm1zO7O9R97KR+uO1t/XDb2yp1cWmBlvbuqDNsJcmS1NnTp5b2blWdV5y8gQEA4FLMtAUAAACANOH1GOo5cVI/3va2uo+dDPudv6dPdRt2qqm1M0Wji66rN3rCdjzbAQCQ6UjaAgAAAECaiFVmwL6tobHNdaUSSmbljb1RHNsBAJDpSNoCAAAAQJqIp8yAm1TOL1JpQd6oRmo2Q1JpQZ4q5xclc1gAALgWSVsAAAAASBPpWmbA6zFUv6JCkkYlbu2f61dUyOuJltYFACC7kLQFAAAAgDSRzmUGahaWat3tl8pXED42X0Ge1t1+qSsbqAEAkCpTUj0AAAAAAIAzdpkBf09fxLq2hkJJULeWGahZWKobKnxqae9WV2+fSmaFxsoMWwAAwpG0BQAAAIA0YZcZqNuwU4YUlrhNlzIDXo+hqvOKUz0MAABcjfIIAAAAAJBGKDMAAEDmY6YtAAAAAKQZygwAAJDZSNoCAAAAQBpKpzIDQdMiwQwAQBxI2gIAAAAAEqaptVMNjW3q7Okbuq20IE/1Kyoo5QAAQBTUtAUAAACANBc0LTXvO6xndx9Q877DCprW2HdKgqbWTtVt2BmWsJUkf0+f6jbsVFNrZ4pGBgCAuzHTFgAAAADSmFtnsgZNSw2NbYqUPrYkGZIaGtt0Q4WPUgkAAIzATFsAAAAASFNunsna0t49alzDWZI6e/rU0t6dvEEBAJAmSNoCAAAAQBoaayarFJrJmqpSCf5A9ITtcF29zrYDACCbkLQFAAAAgDTk5pmsTa2deugXrzvatmRWXoJHAwBA+iFpCwAAAABpyOkM1S1t/gSPJJxdsqH72EDM7QyFau9Wzi9KzsAAAEgjJG0BAAAAIA05naH6o21vJ622baySDcPZbcfqV1TQhAwAgAhI2gIAAABAGqqcX6TSgrETt4aSV9t2rJINtqIZU7Xu9ktVs7A04WMCACAdkbQFAAAAgDTk9RiqX1Ex5nbJrG3rtGTDF5ZfRMIWAIAYSNoCAAAAQJqqWViqu686x9G2ThOqE+G0ZIOvYFqCRwIAQHojaQsAAAAAaWxZhc/RdrNn5CZ4JKdLNkSrUkvzMQAAnJmS6gEAGMYMSvu3S0cPKjijRC3BcnUdGwgF2IZ06Gj/0P+7An3qPnZSRTNzVTLz9O9LZoWCYBo6AAAAZAc7Uerv6YvZAOyzT/9OX15ZkdCyBF6Z+vaSXm14/hV1qVAtZrnMwblCNB8DAMA5krZAJGZQwbe3ad9b+9RlFco4e6nk9YYlTaMlUH3540yatm2SmlZLgQ5JklfSPKtIjw3UarNZGdeuSgvyVL8isQE5AAAA3MGubVu3YacMaShx65GpSs8eleiIulSoVwLlqtuwM3ENwAbj2cpAhyqnhm7qsIrUMBjP+ohRAQBwzLAsK/EtRJMoEAiooKBAPT09ys/PT/VwkI7aNulE4+c07YR/6KbhwaYTcSdN2zZJG2ulEXMj7Aa/dQOr4krc2uliOvICADJJNsV52fRcMXmaWjv15U2vyx/oV7WnRfU561VmnG4+1mEV6V8GavW7WdfqpdXXTe5s18F41pIVVhrB/ukP73tEf/W+v2OGLQAg6zmN86hpCwzXtknWxlrlHveH3exTt9blrFW1p8XRbjp7+lS3YaeaWjvH3tgMhmbYRljMZse09TlPyCPT0WNr2J4aGtsUNDPqugwAAACiqFlYqm/esljVnhaty1krn7rDfu9Tt/49Z63e2/sbtbR3R9nLOAzGsyMTtpJkDEamF+76V3njiGcBAMh2JG0BmxmUNRhsjpwAMN7kqaOk6f7tQyURIvEYUplxWJWePY4fVwolbjt7+iY3IAcAAICrHeo9rvqc9ZIUM6btChybvAcdjGejNx+zpMCB0HYAAMARkraAbf92GYGOqC+KeJOnjpOmRw862l+JjjjabqSu3r5x3Q8AAADp56+Ov6Yyo3tUwtZmx7R/dfy1SXtMs9c/9kZxbAcAAEjaAqclKHk6ZtJ05hxn+1FhXI9rK5mVN677AQAAIP1cNOu4o+0unDF5M21fD0xztN0bvdMn7TEBAMh0JG0BW4KSp2MmTectlfLLpCgLykxL6rCK1WKWx/W4hkIN0SrnF8V1PwAAAKQvzyyfo+0+/Vyns/4LY2hq7dSdz3vVYRUpWlUwO57dO/3iCT8eAADZgqQtYJu3VFZ+WdSKtfEmTx0nTT1eqWbNsHuFP6YkNQzcITOOl6u9l/oVFXToBQAAyCaDEwJGtwQLsWPazb3nOm+cG0VTa6fqNuxUd5+phoHaof2PfDwpFM+W5M8Y92MBAJBtSNoCNo9XRs0aGTJiBpvxJE8dJ00rVkq3rJfyS8Nu9qtYdQOrtNmsdPyYkuQryNO62y9VzcLSsTcGAABA5hicEGBIoxK3w2PaoDyyJH3+56/p5CnnjXZtQdNSQ2Ob7LB5s1mpuoFV8it8woJfxfrHgVX6/axrWQEGAEAcDMuyxmhtn14CgYAKCgrU09Oj/Pz8VA8H6ahtk040fk7TTpxulNBhFath4A7HydPSgjzVr6iIP2lqBkNddY8eVHBGiVqC5eo6NqDZM3IlQzp0tH/o/12BPnUfO6mimbkqmXn69yWzQrN7mWELAMg02RTnZdNzRYK0bVL/Lz6n3ONjx7RFM6bqKx9eGFfs2rzvsG57dMeo2z0yVenZoxIdUZcK1WKWy5KHCQUAAAxyGudNSeKYgPRQsVLTypcr+PY27Xtrn7qsQhlnL1Wt16sbhyVNoyVQffkTSJp6vNL8ayRJXklVk/vMAAAAkC0qVqqpf7GefPqnYQnUSKvGuo+dVN2GnXElVqM12zXl0Q6zYujnwuk5+urfXEzCFgCAOJG0BSLxeOU991pdcO61uiDVYwEAAADGoSR/RlgCNRa7VMJ15XM0dUr0cmBB01JLe7fjWriP3Haprjp/tqNtAQDAaSRtAQAAACADVc4vUmlBnvw9fXJSE6/72ICufPiFUaUS7ETtlja/ntndoe5jJ8fcl6FQn4Urzyse/xMAACCL0YgMAAAAADKQ12OofoWzmbY2u1SCPZO2qbVTV6/Zqtse3aEfbXvbUcLW5rgpLwAAGCVhSdvu7m597GMfU35+vgoLC3X33Xfr6NGjMe/z/ve/X4ZhhP375Cc/maghAgAAADER0yLd1Sws1brbL1XRjBzH97FLJTT+rkN1G3aqsydy/dpYVi27gDq2AABMQMKSth/72Mf0+uuva8uWLfrFL36h3/zmN/qHf/iHMe93zz33qLOzc+jf1772tUQNEQAAAIiJmBaZoGZhqXY8uExFM6Y6vk/3sQF9+sldjsoqRHLO7OnjvCcAAJASVNP2jTfeUFNTk1555RVdfvnlkqTvfve7uvHGG/WNb3xDZWVlUe87ffp0+Xw+x4/V39+v/v7+oZ8DgcD4Bw4AAAAMIqZFJpk6xaOvfHih6jbsdJyIHW/CVpJKZuVN4N4AACAhM22bm5tVWFg4FNxK0rJly+TxePTyyy/HvO9//dd/afbs2Vq4cKEefPBBHT9+POb2Dz/8sAoKCob+zZ07d1KeAzBewVOn9Pq25/TbX/yHXnvpF9r2h4N6dvcBbfvjIW3be8jx/5v3HVbQnEioDAAAJoKYFpkmnlIJHpm60tOmlZ7tutLTJo9MR49hSCotyFPl/KIJjhYAgOyWkJm2fr9fJSUl4Q80ZYqKiork9/uj3u/v/u7vNG/ePJWVlen3v/+9Vq9erTfffFM/+9nPot7nwQcf1P333z/0cyAQIMhFyuza/LjKmhu0QIeHbuuwirR+oFabzcq491dakKf6FRXUAwMAIAWIaZGJahaW6rryObry4ReiNhWr9rSoPme9yozuods6rCI1jBHT2i3HaEAGAMDExZW0feCBB7RmzZqY27zxxhvjHszw+mAXX3yxSktLdf3112vfvn0677zzIt4nNzdXubm5435MYLLs2vy4Fm3/dOiHYTGqT91al7NWdQOr4k7c+nv6VLdhp9bdfimJWwAAJgkxLbJdrFIJ1Z4WrctZO+o+TmJaHxMOAACYNHElbT/72c/qrrvuirnNueeeK5/Pp66urrDbT506pe7u7rhqey1ZskSStHfv3qgBLuAGwVOnVNbcIEkaOanAY0imJdXnPKEt/ZfLjKMqiaVQ/rehsU03VPiYsQAAwCQgpgVOl0r4/M9fU/exAUmhkgj1OetD/3cY0xbNyNGHF5+lZRU+Vc4vIl4FAGCSxJW0PfPMM3XmmWeOuV1VVZWOHDmiV199VZdddpkkaevWrTJNcyhodWL37t2SpNJSrtTC3fa8vDlUEiFKjOoxpDIdVqVnj3aYFXHt25LU2dOnlvZuVZ1XPPHBAgCQ5YhpgZCRpRIqPXvCSiKMZMe078/7o+ZfVk2iFgCABEpII7KLLrpINTU1uueee9TS0qJt27bpU5/6lG699dahLrsHDhxQeXm5WlpaJEn79u3TQw89pFdffVVvv/22Nm3apNraWl177bV673vfm4hhApPmxLsHHG1XoiPjfoyu3r5x3xcAAMSPmBbZwC6VYMh5rPofN79HX1yxQFXnFZOwBQAgQRKStJVCHXPLy8t1/fXX68Ybb9TVV1+t//iP/xj6/cDAgN58882hTrpTp07V888/rw9+8IMqLy/XZz/7WX3kIx9RY2NjooYITJppZ5zlaLsuFY77MUpm5Y37vgAAYHyIaZEN7FIJp2aUjL2xpCkFzBoHACDRDMuyRtaeT2uBQEAFBQXq6elRfn5+qoeDLBE8dUqH/p8LdKZ1eFT9LylU/8uvYl3d/+24atpKoYoLvoI8vbT6OmYyAACyWjbFedn0XOEewVOndOrfFmjqcX/Eql+WDBn5ZdKq1ySPN+njAwAgEziN8xI20xbIJt4pU9RRVS8plKAdzv65YeCOcSVsJal+RQUJWwAAACSUd8oU5f7112XIkDUibWvJCN1S81UStgAAJAFJW2CSXFJ9p3639Dv6ixHeLMy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-          },
-          "metadata": {}
-        }
-      ],
-      "source": [
-        "# Toy function to generate data\n",
-        "def generate_sinx_plus_x(N):\n",
-        "    x = np.linspace(0, 20, N)\n",
-        "    y = np.sin(x) + x / 10\n",
-        "\n",
-        "    return x.reshape(-1, 1), y\n",
-        "\n",
-        "\n",
-        "# Utility function for plotting\n",
-        "def plot_predictions(ax, model, model_name):\n",
-        "    X_test = np.linspace(0, 20, 200).reshape(\n",
-        "        -1, 1\n",
-        "    )  # Predict for 200 points  between 0 and 20\n",
-        "    y_preds = model.predict(X_test)\n",
-        "    ax.set_title(model_name)\n",
-        "    ax.scatter(X_test, y_preds, label=\"Predictions\")\n",
-        "    ax.scatter(X_train, y_train, label=\"Train points\")\n",
-        "    ax.legend()\n",
-        "\n",
-        "\n",
-        "# Generate data\n",
-        "X_train, y_train = generate_sinx_plus_x(N=40)\n",
-        "\n",
-        "# Fit Models\n",
-        "rf = RandomForestRegressor(random_state=42).fit(X_train, y_train)\n",
-        "xgb = XGBRegressor(random_state=42).fit(X_train, y_train)\n",
-        "tabpfn = TabPFNRegressor()\n",
-        "tabpfn.fit(X_train, y_train)\n",
-        "\n",
-        "# Create a 2x2 subplot layout\n",
-        "fig, axs = plt.subplots(2, 2, figsize=(14, 12))\n",
-        "\n",
-        "# Plot train points\n",
-        "ax_points = axs[0, 0]\n",
-        "ax_points.set_title(\"Train points\")\n",
-        "ax_points.scatter(X_train, y_train, label=\"Train points\")\n",
-        "ax_points.legend()\n",
-        "\n",
-        "# Plot predictions for Random Forest\n",
-        "ax_rf = axs[0, 1]\n",
-        "plot_predictions(ax_rf, rf, \"Random Forest\")\n",
-        "\n",
-        "# Plot predictions for XGBoost\n",
-        "ax_xgb = axs[1, 0]\n",
-        "plot_predictions(ax_xgb, xgb, \"XGBoost\")\n",
-        "\n",
-        "# Plot predictions for TabPFN\n",
-        "ax_tabpfn = axs[1, 1]\n",
-        "plot_predictions(ax_tabpfn, tabpfn, \"TabPFN\")\n",
-        "\n",
-        "# Adjust layout for better spacing\n",
-        "plt.tight_layout()\n",
-        "plt.show()"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "if backend == \"client\":\n",
+    "    # Encode target labels to classes for baselines\n",
+    "    le = LabelEncoder()\n",
+    "    y_text = le.fit_transform(y_text)\n",
+    "\n",
+    "    # Define models\n",
+    "    models = [\n",
+    "        (\"TabPFN-Text\", TabPFNClassifier(random_state=42)),\n",
+    "        (\n",
+    "            \"TabPFN\",\n",
+    "            make_pipeline(\n",
+    "                column_transformer,  # string data needs to be encoded for model\n",
+    "                TabPFNClassifier(random_state=42),\n",
+    "            ),\n",
+    "        ),\n",
+    "        (\n",
+    "            \"RandomForest\",\n",
+    "            make_pipeline(\n",
+    "                column_transformer,  # string data needs to be encoded for model\n",
+    "                RandomForestClassifier(random_state=42),\n",
+    "            ),\n",
+    "        ),\n",
+    "        (\n",
+    "            \"XGBoost\",\n",
+    "            make_pipeline(\n",
+    "                column_transformer,  # string data needs to be encoded for model\n",
+    "                XGBClassifier(random_state=42),\n",
+    "            ),\n",
+    "        ),\n",
+    "        (\n",
+    "            \"CatBoost\",\n",
+    "            make_pipeline(\n",
+    "                column_transformer,  # string data needs to be encoded for model\n",
+    "                CatBoostClassifier(random_state=42, verbose=0),\n",
+    "            ),\n",
+    "        ),\n",
+    "    ]\n",
+    "\n",
+    "    # Calculate scores\n",
+    "    cv = StratifiedKFold(n_splits=3, random_state=42, shuffle=True)\n",
+    "    scoring = \"roc_auc_ovr\" if len(np.unique(y_text)) > 2 else \"roc_auc\"\n",
+    "    scores = {\n",
+    "        name: cross_val_score(\n",
+    "            model, X_text, y_text, cv=cv, scoring=scoring, n_jobs=1, verbose=1\n",
+    "        ).mean()\n",
+    "        for name, model in models\n",
+    "    }\n",
+    "\n",
+    "    # Plot results\n",
+    "    df = pd.DataFrame(list(scores.items()), columns=[\"Model\", \"ROC AUC\"])\n",
+    "    ax = df.plot(x=\"Model\", y=\"ROC AUC\", kind=\"bar\", figsize=(10, 6))\n",
+    "    ax.set_ylim(df[\"ROC AUC\"].min() * 0.995, min(1.0, df[\"ROC AUC\"].max() * 1.005))\n",
+    "    ax.set_title(\"Model Comparison - 5-fold Cross-validation\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "mTnMbG9vXHkL"
+   },
+   "source": [
+    "# Unsupervised Learning with TabPFN <a name=\"unsupervised-learning\"></a>\n",
+    "\n",
+    "TabPFN can also be used for unsupervised learning tasks like outlier detection and synthetic data generation. These features are available through the `tabpfn-extensions` library.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ghZddJXFa4zE"
+   },
+   "source": [
+    "### Data Generation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "npJnFdtTa_nS",
+    "outputId": "c2fbe9fd-e7c6-4e14-c2b2-198e2fea703e"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "XcYaJKT_Pw6T"
-      },
-      "source": [
-        "## Uncertainty of TabPFN / Quantile Regresison\n",
-        "\n",
-        "---\n",
-        "\n",
-        "\n",
-        "\n",
-        "TabPFN is trained to predict the distribution of the target variable and not just a single point. This is also the case for regression.\n",
-        "\n",
-        "As a result, we natively obtain uncertainty for the predictions of TabPFN (without the need for a new model or repeating models for different quantiles).\n",
-        "\n",
-        "In the following, we plot the uncertainty of TabPFN for a toy function with noise."
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 3/3 [00:05<00:00,  1.85s/it]\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 21,
-      "metadata": {
-        "id": "r5q1UBos4W1O"
-      },
-      "outputs": [],
-      "source": [
-        "### Code to generate the plot (feel free to ignore)\n",
-        "def plot_regression_uncertainty(ax, x, y_line, y_noisy, x_test, color_multiplier=5):\n",
-        "    all_quantiles = preds[\"quantiles\"]\n",
-        "    y = np.array(all_quantiles)  # shape of y: (9, number of samples)\n",
-        "\n",
-        "    # Calculate the maximum and minimum values in y\n",
-        "    y_max = np.max(y, axis=0)\n",
-        "    y_min = np.min(y, axis=0)\n",
-        "\n",
-        "    # Calculate the widths of each quantile bin\n",
-        "    quantile_bin_widths = np.diff(\n",
-        "        y, axis=0\n",
-        "    )  # shape of quantile_bin_widths: (8, number of samples)\n",
-        "\n",
-        "    # Normalize the bin widths for a given x\n",
-        "    per_x_normalized_bin_widths = (quantile_bin_widths) / (y_max - y_min)\n",
-        "\n",
-        "    # Plotting\n",
-        "    num_bins, num_data_points = (\n",
-        "        per_x_normalized_bin_widths.shape[0],\n",
-        "        per_x_normalized_bin_widths.shape[1],\n",
-        "    )\n",
-        "    rect_width = (\n",
-        "        x_test[1] - x_test[0]\n",
-        "    ).squeeze()  # assuming the x query points are equally spaced out\n",
-        "\n",
-        "    for i in range(num_data_points):\n",
-        "        for j in range(num_bins):\n",
-        "            quantile_bin_widths[j, i]\n",
-        "            rect = plt.Rectangle(\n",
-        "                xy=(x_test[i][0] - rect_width / 2, y[j, i]),\n",
-        "                width=rect_width,\n",
-        "                height=quantile_bin_widths[j, i],\n",
-        "                facecolor=plt.cm.viridis(\n",
-        "                    per_x_normalized_bin_widths[j, i] * color_multiplier\n",
-        "                ),\n",
-        "                edgecolor=\"none\",\n",
-        "            )\n",
-        "            ax.add_patch(rect)\n",
-        "\n",
-        "    # Set limits and labels\n",
-        "    ax.plot(x, y_line, label=\"True line\", color=\"blue\")\n",
-        "    ax.set_xlim(min(x_test) - 1, max(x_test) + 1)\n",
-        "    ax.set_ylim(np.min(y_noisy) - 1, np.max(y_noisy) + 1)\n",
-        "    ax.set_xlabel(\"X\")\n",
-        "    ax.set_ylabel(\"Y\")\n",
-        "\n",
-        "    # ax.plot(x, y, label='True line', color='blue')\n",
-        "    ax.scatter(x, y_noisy, label=\"Noisy data\", color=\"red\", s=10)\n",
-        "\n",
-        "    plt.title(\"TabPFN Regression Uncertainty\")\n",
-        "    plt.show()\n",
-        "\n",
-        "\n",
-        "# Generate Data\n",
-        "def generate_line_with_heteroscedastic_noise(\n",
-        "    m=0.8, num_points=200, x_start=0, x_end=100, noise_factor=0.1\n",
-        "):\n",
-        "    x = np.linspace(x_start, x_end, num_points)\n",
-        "    noise = np.random.randn(num_points)\n",
-        "    y = m * x\n",
-        "    y_noisy = y + (noise * noise_factor * x)\n",
-        "\n",
-        "    return x.reshape(-1, 1), y, y_noisy\n",
-        "\n",
-        "\n",
-        "def generate_line_with_heteroscedastic_noise_with_gap(\n",
-        "    m=0.8, num_points=200, x_start=0, x_end=100, noise_factor=0.1\n",
-        "):\n",
-        "    extra_points = num_points // 3\n",
-        "    x, y, y_noisy = generate_line_with_heteroscedastic_noise(\n",
-        "        m, num_points + extra_points, x_start, x_end, noise_factor\n",
-        "    )\n",
-        "    a = np.arange(num_points + extra_points)\n",
-        "    idx = np.where((a < num_points / 3) | (a > num_points / 3 + extra_points))\n",
-        "    return x[idx], y[idx], y_noisy[idx]\n",
-        "\n",
-        "\n",
-        "x, y_line, y_noisy = generate_line_with_heteroscedastic_noise_with_gap(0.8)\n",
-        "x_test = np.linspace(0, 100, 200).reshape(-1, 1)"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 935.75x750 with 12 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from tabpfn_extensions import unsupervised\n",
+    "from tabpfn_extensions.unsupervised import experiments\n",
+    "\n",
+    "# Load and prepare breast cancer dataset\n",
+    "df = load_breast_cancer(return_X_y=False)\n",
+    "X, y = df[\"data\"], df[\"target\"]\n",
+    "feature_names = df[\"feature_names\"]\n",
+    "\n",
+    "# Initialize TabPFN models\n",
+    "model_unsupervised = unsupervised.TabPFNUnsupervisedModel(\n",
+    "    tabpfn_clf=TabPFNClassifier(), tabpfn_reg=TabPFNRegressor()\n",
+    ")\n",
+    "\n",
+    "# Select features for synthetic data generation\n",
+    "# Example features: [mean texture, mean area, mean concavity]\n",
+    "feature_indices = [4, 6, 12]\n",
+    "\n",
+    "# Run synthetic data generation experiment\n",
+    "experiment = unsupervised.experiments.GenerateSyntheticDataExperiment(\n",
+    "    task_type=\"unsupervised\"\n",
+    ")\n",
+    "\n",
+    "results = experiment.run(\n",
+    "    tabpfn=model_unsupervised,\n",
+    "    X=torch.tensor(X),\n",
+    "    y=torch.tensor(y),\n",
+    "    attribute_names=feature_names,\n",
+    "    temp=1.0,  # Temperature parameter for sampling\n",
+    "    n_samples=X.shape[0] * 2,  # Generate twice as many samples as original data\n",
+    "    indices=feature_indices,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_aoNg2_K4k6E"
+   },
+   "source": [
+    "### Outlier detection"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "ezircAHiZSKG",
+    "outputId": "4c93610c-33a5-4dd1-ba43-6ba118c06942"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 22,
-      "metadata": {
-        "id": "xpvqsL1f4W1O"
-      },
-      "outputs": [],
-      "source": [
-        "reg = TabPFNRegressor()\n",
-        "reg.fit(x, y_noisy)\n",
-        "preds = reg.predict(x_test, output_type=\"full\")"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x600 with 3 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "from sklearn.datasets import load_breast_cancer\n",
+    "from tabpfn_extensions import unsupervised\n",
+    "from tabpfn_extensions.unsupervised import experiments\n",
+    "\n",
+    "# Load data\n",
+    "df = load_breast_cancer(return_X_y=False)\n",
+    "X, y = df[\"data\"], df[\"target\"]\n",
+    "attribute_names = df[\"feature_names\"]\n",
+    "\n",
+    "# Initialize models\n",
+    "clf = TabPFNClassifier(n_estimators=4)\n",
+    "reg = TabPFNRegressor(n_estimators=4)\n",
+    "model_unsupervised = unsupervised.TabPFNUnsupervisedModel(\n",
+    "    tabpfn_clf=clf, tabpfn_reg=reg\n",
+    ")\n",
+    "\n",
+    "# Run outlier detection\n",
+    "exp_outlier = unsupervised.experiments.OutlierDetectionUnsupervisedExperiment(\n",
+    "    task_type=\"unsupervised\"\n",
+    ")\n",
+    "results = exp_outlier.run(\n",
+    "    tabpfn=model_unsupervised,\n",
+    "    X=torch.tensor(X, dtype=torch.float32),\n",
+    "    y=torch.tensor(y),\n",
+    "    attribute_names=attribute_names,\n",
+    "    indices=[4, 12],  # Analyze features 4 and 12\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Qk6OxtxmJsr9"
+   },
+   "source": [
+    "### Missing value imputation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "9hgAlgghJuF3",
+    "outputId": "bc78fafc-f40e-4dfb-a2e8-9e3f7487d691"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 23,
-      "metadata": {
-        "id": "GwSCwFm-4W1O",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 0
-        },
-        "outputId": "05fa4741-b689-4438-8000-40e7ae886f4f"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 1200x600 with 2 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
-      ],
-      "source": [
-        "fig = plt.figure(figsize=(12, 6))\n",
-        "\n",
-        "# Plot the original data\n",
-        "ax = fig.add_subplot(121)\n",
-        "ax.plot(x, y_line, label=\"True line\", color=\"blue\")\n",
-        "ax.scatter(x, y_noisy, label=\"Noisy data\", color=\"red\", s=10)\n",
-        "ax.set_xlabel(\"X\")\n",
-        "ax.set_ylabel(\"Y\")\n",
-        "ax.set_xlim(min(x) - 1, max(x) + 1)\n",
-        "ax.set_ylim(np.min(y_noisy) - 1, np.max(y_noisy) + 1)\n",
-        "ax.set_title(\"Heteroscedastic Noise along a Sloping Line\")\n",
-        "ax.legend()\n",
-        "\n",
-        "# plot the uncertainty estimates obtained from TabPFN\n",
-        "ax = fig.add_subplot(122)\n",
-        "plot_regression_uncertainty(ax, x, y_line, y_noisy, x_test, color_multiplier=5)"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Introduced 168 missing values into the test set.\n",
+      "       0      1       2\n",
+      "0    NaN  18.60   81.09\n",
+      "1  18.94    NaN  123.60\n",
+      "2  15.46  19.48  101.70\n",
+      "3  12.40    NaN   81.47\n",
+      "4    NaN  14.44     NaN\n",
+      "Fitting the unsupervised model on the training data...\n",
+      "Imputing missing values...\n",
+      "\n"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "VJMcv-KvPYIh"
-      },
-      "source": [
-        "# Time Series Forecasting <a name=\"timeseries\"></a>\n",
-        "\n",
-        "TabPFN can be used for time series prediction, following the work of Hoo et al. (Zero-Shot Time Series Forecasting with TabPFNv2; https://arxiv.org/abs/2501.02945v3).\n",
-        "\n",
-        "In this demo, we will use the time series dataset from [Chronos Dataset](https://huggingface.co/datasets/autogluon/chronos_datasets) on HuggingFace. Also, we'll keep it short and work with just 2 time series from the dataset.\n",
-        "\n",
-        "Feel free to explore other datasets by using the dataset names from Chronos Dataset on HuggingFace or even use time series data of your own problem.\n"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 3/3 [00:11<00:00,  3.88s/it]"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "Z3wiT00Uf0dF"
-      },
-      "source": [
-        "## *Installation*"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "------------------------\n",
+      "\n",
+      "Number of missing values after imputation: 0\n",
+      "           0          1           2\n",
+      "0  12.515228  18.600000   81.089996\n",
+      "1  18.940001  21.109259  123.599998\n",
+      "2  15.460000  19.480000  101.699997\n",
+      "3  12.400000  17.477161   81.470001\n",
+      "4  11.358663  14.440000   74.500938\n",
+      "Mean Squared Error of imputed values vs. original values: 0.4940\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "J0cUKia3fzrz"
-      },
-      "outputs": [],
-      "source": [
-        "!uv pip install tabpfn-time-series\n",
-        "raise ValueError(\n",
-        "    \"Make sure to restart the session before proceeding, otherwise errors will follow (Runtime > Restart Session)\"\n",
-        ")"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# --- 1. Load and Prepare Data ---\n",
+    "# Load the breast cancer dataset\n",
+    "df = load_breast_cancer(return_X_y=False)\n",
+    "X, y = df[\"data\"], df[\"target\"]\n",
+    "\n",
+    "# Split the data into training and testing sets\n",
+    "X_train, X_test = train_test_split(\n",
+    "    X,\n",
+    "    test_size=0.33,\n",
+    "    random_state=42,\n",
+    ")\n",
+    "\n",
+    "# --- 2. Introduce Missing Values ---\n",
+    "# Create a copy of the test set to introduce missing values (NaNs)\n",
+    "X_test_missing = X_test.copy()\n",
+    "n_samples, n_features = X_test_missing.shape\n",
+    "\n",
+    "# Introduce missing values in the first three columns for demonstration\n",
+    "missing_fraction = 0.3\n",
+    "n_missing = int(n_samples * missing_fraction)\n",
+    "\n",
+    "for col_idx in range(3):\n",
+    "    # Choose random rows to set to NaN\n",
+    "    missing_indices = np.random.choice(n_samples, n_missing, replace=False)\n",
+    "    X_test_missing[missing_indices, col_idx] = np.nan\n",
+    "\n",
+    "print(f\"Introduced {np.isnan(X_test_missing).sum()} missing values into the test set.\")\n",
+    "print(pd.DataFrame(X_test_missing[:, 0:3]).head())\n",
+    "\n",
+    "# --- 3. Initialize the Unsupervised Model ---\n",
+    "# Initialize TabPFN models for regression and classification tasks.\n",
+    "# The unsupervised model uses these to model the data distribution.\n",
+    "clf = TabPFNClassifier(n_estimators=3)\n",
+    "reg = TabPFNRegressor(n_estimators=3)\n",
+    "\n",
+    "# Initialize the main unsupervised model\n",
+    "model_unsupervised = unsupervised.TabPFNUnsupervisedModel(\n",
+    "    tabpfn_clf=clf,\n",
+    "    tabpfn_reg=reg,\n",
+    ")\n",
+    "\n",
+    "# --- 4. Fit and Impute ---\n",
+    "# Fit the model on the complete training data (without missing values)\n",
+    "print(\"Fitting the unsupervised model on the training data...\")\n",
+    "model_unsupervised.fit(X_train)\n",
+    "\n",
+    "# Perform imputation on the test set\n",
+    "print(\"Imputing missing values...\\n\")\n",
+    "X_imputed_tensor = model_unsupervised.impute(\n",
+    "    X_test_missing,\n",
+    "    n_permutations=5,  # Fewer permutations for a quicker example\n",
+    ")\n",
+    "\n",
+    "print(\"\\n------------------------\")\n",
+    "\n",
+    "# --- 5. Verify Results ---\n",
+    "# Check that the imputed data no longer contains any NaN values\n",
+    "n_missing_after = torch.isnan(X_imputed_tensor).sum().item()\n",
+    "\n",
+    "print(f\"\\nNumber of missing values after imputation: {n_missing_after}\")\n",
+    "print(pd.DataFrame(X_imputed_tensor[:, 0:3]).head())\n",
+    "\n",
+    "# Optional: Calculate the Mean Squared Error for the imputed values,\n",
+    "# since we know the original ground truth values.\n",
+    "original_nan_mask = np.isnan(X_test_missing)\n",
+    "imputed_values = X_imputed_tensor.numpy()[original_nan_mask]\n",
+    "original_values = X_test[original_nan_mask]\n",
+    "\n",
+    "mse = np.mean((imputed_values - original_values) ** 2)\n",
+    "print(f\"Mean Squared Error of imputed values vs. original values: {mse:.4f}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "MqZlQ09WfCe9"
+   },
+   "source": [
+    "# Model Interpretability <a name=\"interpretability\"></a>\n",
+    "\n",
+    "Understanding *why* a model makes certain predictions is crucial for building trust and for debugging. The `tabpfn-extensions` library provides tools for model interpretability. We'll look at SHAP (SHapley Additive exPlanations) values, which show the impact of each feature on a specific prediction."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "6RYILEoPXaMZ"
+   },
+   "source": [
+    "### Shapley Values\n",
+    "\n",
+    "Next, we'll use SHAP to understand our model's predictions. SHAP values break down a prediction to show the contribution of each feature, helping us see which factors are most influential for a given data point.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
     },
+    "id": "8CJtLwWUe-KV",
+    "outputId": "d743c96e-c69b-401d-8571-9ceb8e9ba2b9"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "kNOAk5sPHS_3"
-      },
-      "source": [
-        "## Load Time Series Data\n",
-        "\n",
-        "In this demo, we will use the time series dataset from [Chronos Dataset](https://huggingface.co/datasets/autogluon/chronos_datasets) on HuggingFace. Also, we'll keep it short and work with just 2 time series from the dataset.\n",
-        "\n",
-        "Feel free to explore other datasets by using the dataset names from Chronos Dataset on HuggingFace or even use time series data of your own problem."
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "PermutationExplainer explainer: 26it [02:02,  5.10s/it]\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 2,
-      "metadata": {
-        "id": "qgHudyQdHS_3"
-      },
-      "outputs": [],
-      "source": [
-        "dataset_metadata = {\n",
-        "    \"monash_tourism_monthly\": {\"prediction_length\": 24},\n",
-        "    \"m4_hourly\": {\"prediction_length\": 48},\n",
-        "}\n",
-        "\n",
-        "dataset_choice = \"monash_tourism_monthly\"\n",
-        "num_time_series_subset = 2"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x650 with 1 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 3,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 217,
-          "referenced_widgets": [
-            "6dc16349db2d4cc9beee99bdfd46d874",
-            "6ebc8ffbacd346fb804aa6811ee4599b",
-            "db879755a85f4cc2ad57893cd549e0ca",
-            "1ca71883c8684d3a8ef8ad820d700d8f",
-            "1cfb7fbd035a46bea01e1a33ddb8fb7c",
-            "7975212fe0eb47e18dd0db5c070e1282",
-            "154d619b579a4609a283930f74112d9a",
-            "0101e1e211f346b783d1cace07b9cd53",
-            "9d340085bd084fad84734b7a2cad54b9",
-            "5185c09ee6cd4f37adeb0a59de8c035e",
-            "bcd4e162cddc4536b19efaae88c3c868",
-            "339530ea26ba473dbf7f4e959a577144",
-            "43e20dc7b73d46f798eaadbfb5a639a1",
-            "845678766c52402a91c0aabd163a59bb",
-            "c6063827653640bf8662e7bbcef18542",
-            "db42d7e1f1df4d8f95882eb9171f57ba",
-            "2a3561603bdc4c47b58612d2e0530e7f",
-            "981b7347a33d4cb2af30bd297756c7ef",
-            "cd181b91c64d45c6ace03aef2f2474b4",
-            "98d751e6894d489ea004dc8fe1785523",
-            "2b0544f342c640c9bcc0ceaa238e758a",
-            "2420ee8b5ba74b1ba474e3026e022e02",
-            "acfb3598c0814c21baf3b153b702852e",
-            "c583f6a2d57f4558acd8e449ff6c31bc",
-            "6aa1d039909c4165821894d381fd7e3e",
-            "e647eca6c6984f839265de01d1bee27b",
-            "02713e014c734f408e44ae0dff0b43cf",
-            "0f854e4d18994152b7563989b25f452c",
-            "bacabb7b43c44622b673f225ae9d2d06",
-            "3e42aeb0377842099c33985a84a5dd6c",
-            "50e7ca77a17e445786e00b58ae3a728b",
-            "9f953f9d80f44464b3950e16430dc6e2",
-            "7a9e4423a7e94dcf81c0f56b0da6b565"
-          ]
-        },
-        "id": "Qc1mHevjHS_4",
-        "outputId": "b4b08d1f-e172-43e5-85d7-ccc35310d634"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
-            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
-            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
-            "You will be able to reuse this secret in all of your notebooks.\n",
-            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
-            "  warnings.warn(\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "README.md: 0.00B [00:00, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "6dc16349db2d4cc9beee99bdfd46d874"
-            }
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "monash_tourism_monthly/train-00000-of-00(…):   0%|          | 0.00/335k [00:00<?, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "339530ea26ba473dbf7f4e959a577144"
-            }
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "Generating train split:   0%|          | 0/366 [00:00<?, ? examples/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "acfb3598c0814c21baf3b153b702852e"
-            }
-          },
-          "metadata": {}
-        }
-      ],
-      "source": [
-        "from datasets import load_dataset\n",
-        "from tabpfn_time_series import TimeSeriesDataFrame\n",
-        "from tabpfn_time_series.data_preparation import generate_test_X, to_gluonts_univariate\n",
-        "\n",
-        "prediction_length = dataset_metadata[dataset_choice][\"prediction_length\"]\n",
-        "dataset = load_dataset(\"autogluon/chronos_datasets\", dataset_choice)\n",
-        "\n",
-        "tsdf = TimeSeriesDataFrame(to_gluonts_univariate(dataset[\"train\"]))\n",
-        "tsdf = tsdf[\n",
-        "    tsdf.index.get_level_values(\"item_id\").isin(tsdf.item_ids[:num_time_series_subset])\n",
-        "]\n",
-        "train_tsdf, test_tsdf_ground_truth = tsdf.train_test_split(\n",
-        "    prediction_length=prediction_length\n",
-        ")\n",
-        "test_tsdf = generate_test_X(train_tsdf, prediction_length)"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/lib/python3.12/dist-packages/tabpfn_extensions/interpretability/shap.py:137: FutureWarning: The NumPy global RNG was seeded by calling `np.random.seed`. In a future version this function will no longer use the global RNG. Pass `rng` explicitly to opt-in to the new behaviour and silence this warning.\n",
+      "  shap.summary_plot(shap_values=shap_values, show=False)\n"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "cKH8WtXdHS_4"
-      },
-      "source": [
-        "Let's take a look at the time series data."
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x950 with 2 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 4,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 607
-        },
-        "id": "jOm8_GLEHS_4",
-        "outputId": "b8aa5e8c-f23f-4cad-c6be-76e8489a6205"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 1000x600 with 2 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
-      ],
-      "source": [
-        "from tabpfn_time_series.plot import plot_actual_ts\n",
-        "\n",
-        "plot_actual_ts(train_tsdf, test_tsdf_ground_truth)"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 750x500 with 3 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from tabpfn_extensions import interpretability\n",
+    "\n",
+    "# Load example dataset\n",
+    "data = load_breast_cancer()\n",
+    "X, y = data.data, data.target\n",
+    "feature_names = data.feature_names\n",
+    "n_samples_test, n_samples_train = 25, 50\n",
+    "\n",
+    "# Split data\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5)\n",
+    "\n",
+    "# Initialize and train model\n",
+    "clf = TabPFNClassifier()\n",
+    "clf.fit(X_train[:n_samples_train], y_train[:n_samples_train])\n",
+    "\n",
+    "# Calculate SHAP values\n",
+    "shap_values = interpretability.shap.get_shap_values(\n",
+    "    estimator=clf,\n",
+    "    test_x=X_test[:n_samples_test],\n",
+    "    attribute_names=feature_names,\n",
+    "    algorithm=\"permutation\",\n",
+    ")\n",
+    "\n",
+    "# Create visualization\n",
+    "fig = interpretability.shap.plot_shap(shap_values)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Zt05caATl2Cc"
+   },
+   "source": [
+    "### Embeddings\n",
+    "\n",
+    "This example demonstrates how to extract embeddings from TabPFN models and use them\n",
+    "for classification and regression tasks.\n",
+    "\n",
+    "NOTE: This example requires the full TabPFN implementation (pip install tabpfn).\n",
+    "It will not work with the TabPFN client (pip install tabpfn-client) because\n",
+    "the embedding functionality is not available in the client version.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "nj8XPK35l4z1"
+   },
+   "outputs": [],
+   "source": [
+    "if backend == \"client\":\n",
+    "    console.print(\n",
+    "        Panel(\n",
+    "            \"[bold yellow]Text data can only be processed through the TabPFN server. Please restart the notebook and select the 'client' backend to run this section.[/bold yellow]\",\n",
+    "            title=\"[bold yellow]Warning\",\n",
+    "            border_style=\"yellow\",\n",
+    "        )\n",
+    "    )\n",
+    "else:\n",
+    "    import matplotlib.pyplot as plt\n",
+    "    import numpy as np\n",
+    "    import pandas as pd\n",
+    "    import seaborn as sns\n",
+    "    from sklearn.datasets import load_breast_cancer, load_diabetes\n",
+    "    from sklearn.linear_model import LinearRegression, LogisticRegression\n",
+    "    from sklearn.manifold import TSNE\n",
+    "    from sklearn.metrics import accuracy_score, r2_score\n",
+    "    from sklearn.model_selection import train_test_split\n",
+    "    from tabpfn_extensions import TabPFNClassifier, TabPFNRegressor\n",
+    "    from tabpfn_extensions.embedding import TabPFNEmbedding\n",
+    "\n",
+    "    # Load and evaluate classification dataset\n",
+    "    print(\"Loading classification dataset (breast cancer)...\")\n",
+    "    df = load_breast_cancer(return_X_y=False)\n",
+    "    X, y = df[\"data\"], df[\"target\"]\n",
+    "    attribute_names = df[\"feature_names\"]\n",
+    "\n",
+    "    # Split the data\n",
+    "    X_train, X_test, y_train, y_test = train_test_split(\n",
+    "        X,\n",
+    "        y,\n",
+    "        test_size=0.5,\n",
+    "        random_state=42,\n",
+    "    )\n",
+    "\n",
+    "    # Train and evaluate vanilla logistic regression\n",
+    "    model = LogisticRegression(\n",
+    "        max_iter=10000,\n",
+    "        random_state=42,\n",
+    "    )\n",
+    "    model.fit(X_train, y_train)\n",
+    "    print(\n",
+    "        f\"Baseline Logistic Regression Accuracy: {accuracy_score(y_test, model.predict(X_test)):.4f}\",\n",
+    "    )\n",
+    "\n",
+    "    # Train and evaluate TabPFN embeddings (vanilla)\n",
+    "    clf = TabPFNClassifier(n_estimators=1, random_state=42)\n",
+    "    embedding_extractor = TabPFNEmbedding(tabpfn_clf=clf, n_fold=0)\n",
+    "    train_embeddings = embedding_extractor.get_embeddings(\n",
+    "        X_train,\n",
+    "        y_train,\n",
+    "        X_test,\n",
+    "        data_source=\"train\",\n",
+    "    )\n",
+    "    test_embeddings = embedding_extractor.get_embeddings(\n",
+    "        X_train,\n",
+    "        y_train,\n",
+    "        X_test,\n",
+    "        data_source=\"test\",\n",
+    "    )\n",
+    "\n",
+    "    model = LogisticRegression(\n",
+    "        max_iter=10000,\n",
+    "        random_state=42,\n",
+    "    )\n",
+    "    model.fit(train_embeddings[0], y_train)\n",
+    "    y_pred = model.predict(test_embeddings[0])\n",
+    "    print(\n",
+    "        f\"Logistic Regression with TabPFN (Vanilla) Accuracy: {accuracy_score(y_test, y_pred):.4f}\",\n",
+    "    )\n",
+    "\n",
+    "    # Note: Using test_embeddings and y_test from your original script.\n",
+    "    # The embeddings have shape (n_splits, n_samples, n_features), so we use the first split [0].\n",
+    "    test_only_embeddings = test_embeddings[0]\n",
+    "\n",
+    "    # Apply t-SNE to reduce the TEST embeddings to 2 dimensions.\n",
+    "    # The number of samples in the test set is len(y_test). Perplexity must be less than that.\n",
+    "    # We'll set perplexity to 30, which is suitable for this dataset size.\n",
+    "    print(\"\\nApplying t-SNE for visualization on the TEST SET only...\")\n",
+    "    tsne = TSNE(n_components=2, random_state=42, perplexity=10)\n",
+    "    embeddings_2d = tsne.fit_transform(test_only_embeddings)\n",
+    "\n",
+    "    # Create a DataFrame for easy plotting\n",
+    "    df_plot = pd.DataFrame(\n",
+    "        {\n",
+    "            \"t-SNE-1\": embeddings_2d[:, 0],\n",
+    "            \"t-SNE-2\": embeddings_2d[:, 1],\n",
+    "            \"label\": y_test,\n",
+    "        }\n",
+    "    )\n",
+    "\n",
+    "    # Plot the 2D embeddings for the test set\n",
+    "    plt.figure(figsize=(9, 7))\n",
+    "    sns.scatterplot(\n",
+    "        data=df_plot,\n",
+    "        x=\"t-SNE-1\",\n",
+    "        y=\"t-SNE-2\",\n",
+    "        hue=\"label\",  # Color points by their class label\n",
+    "        palette=\"viridis\",\n",
+    "        alpha=0.9,\n",
+    "        s=80,\n",
+    "    )\n",
+    "\n",
+    "    plt.title(\"t-SNE Visualization of TabPFN Embeddings (Test Set Only)\")\n",
+    "    plt.xlabel(\"t-SNE Dimension 1\")\n",
+    "    plt.ylabel(\"t-SNE Dimension 2\")\n",
+    "    plt.legend(title=\"Class\")\n",
+    "    plt.grid(True, linestyle=\"--\", alpha=0.6)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "PkphS4vSFNvg"
+   },
+   "source": [
+    "### Feature selection\n",
+    "\n",
+    "Feature selection is the process of selecting a subset of relevant features for use in model construction. It's useful for reducing model complexity, improving performance by removing noise, and decreasing training time. Here, we'll use Sequential Forward Selection (SFS), which starts with no features and iteratively adds the feature that most improves the model's performance.\n",
+    "\n",
+    "The goal is to see if we can create a simpler, faster model with fewer features without a significant drop in accuracy.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "GPJtNDLnFPPW"
+   },
+   "outputs": [],
+   "source": [
+    "from tabpfn_extensions import interpretability\n",
+    "\n",
+    "# Load data\n",
+    "data = load_breast_cancer()\n",
+    "X, y = data.data, data.target\n",
+    "feature_names = data.feature_names\n",
+    "\n",
+    "# Initialize model\n",
+    "clf = TabPFNClassifier(n_estimators=1)\n",
+    "\n",
+    "# Feature selection\n",
+    "sfs = interpretability.feature_selection.feature_selection(\n",
+    "    estimator=clf, X=X, y=y, n_features_to_select=4, feature_names=feature_names\n",
+    ")\n",
+    "\n",
+    "# Print selected features\n",
+    "selected_features = [\n",
+    "    feature_names[i] for i in range(len(feature_names)) if sfs.get_support()[i]\n",
+    "]\n",
+    "print(\"\\nSelected features:\")\n",
+    "for feature in selected_features:\n",
+    "    print(f\"- {feature}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "lmPJW5NSK7ut"
+   },
+   "source": [
+    "# Predictive Behavior of TabPFN <a name=\"behavior\"></a>\n",
+    "\n",
+    "In this section, we explore the behavior of predictions from TabPFN on various toy functions."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ZBeID4YeMQ9L"
+   },
+   "source": [
+    "## Decision Boundary during Classification\n",
+    "\n",
+    "First, let us inspect the decision boundary for different classifiers.\n",
+    "The decision bounds show how smoothly a model learns to transition between classes and how well it fits the data.\n",
+    "\n",
+    "In the first cell, we create the data and code to plot the decision boundary. The second cell then generates the plot."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "B5a_ia0OLOxG"
+   },
+   "outputs": [],
+   "source": [
+    "from matplotlib.colors import ListedColormap\n",
+    "from sklearn.inspection import DecisionBoundaryDisplay\n",
+    "\n",
+    "\n",
+    "# Toy functions that generate the data\n",
+    "def generate_circle(n_datapoints, radius, noise_factor):\n",
+    "    angles = np.linspace(0, 2 * np.pi, n_datapoints).T\n",
+    "    x = radius * np.cos(angles) + np.random.randn(n_datapoints) * noise_factor\n",
+    "    y = radius * np.sin(angles) + np.random.randn(n_datapoints) * noise_factor\n",
+    "\n",
+    "    return np.stack([x, y]).T\n",
+    "\n",
+    "\n",
+    "def generate_concentric_cirlces(radii, num_points_per_circle, noise_factor=1 / 15):\n",
+    "    circles = []\n",
+    "    for r, num_points in zip(radii, num_points_per_circle):\n",
+    "        circles.append(generate_circle(num_points, r, noise_factor))\n",
+    "\n",
+    "    return np.vstack(circles)\n",
+    "\n",
+    "\n",
+    "def generate_circle_data(num_points_per_circle, radii, noise_factor):\n",
+    "    radii = np.array(radii)\n",
+    "    circles_1 = generate_concentric_cirlces(radii, num_points_per_circle, noise_factor)\n",
+    "    circles_1 = np.hstack([circles_1, np.zeros((sum(num_points_per_circle), 1))])\n",
+    "\n",
+    "    circles_2 = generate_concentric_cirlces(\n",
+    "        radii + 0.3, num_points_per_circle, noise_factor\n",
+    "    )\n",
+    "    circles_2 = np.hstack([circles_2, np.ones((sum(num_points_per_circle), 1))])\n",
+    "\n",
+    "    circles = np.vstack([circles_1, circles_2])\n",
+    "    X, y = circles[:, :2], circles[:, 2]\n",
+    "    return X, y\n",
+    "\n",
+    "\n",
+    "# Generate the data\n",
+    "X_train, y_train = generate_circle_data(\n",
+    "    num_points_per_circle=[50, 100, 200], radii=[1, 2, 4], noise_factor=0.1\n",
+    ")\n",
+    "\n",
+    "\n",
+    "# Function for plotting\n",
+    "def plot_decision_boundary(ax, model, model_name):\n",
+    "    cmap = ListedColormap([\"#FF0000\", \"#0000FF\"])\n",
+    "    ax.set_title(model_name)\n",
+    "    DecisionBoundaryDisplay.from_estimator(\n",
+    "        model,\n",
+    "        X_train[:, :2],\n",
+    "        alpha=0.6,\n",
+    "        ax=ax,\n",
+    "        eps=0.2,\n",
+    "        grid_resolution=50,\n",
+    "        response_method=\"predict_proba\",\n",
+    "        cmap=plt.cm.RdBu,\n",
+    "    )\n",
+    "    ax.scatter(X_train[:, 0], X_train[:, 1], c=y_train > 0, cmap=cmap)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 707
     },
+    "id": "wzrSEZR5LYlf",
+    "outputId": "3ba2abe5-4fe4-465e-daea-c86d239f79ea"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "UWmQq17tHS_4"
-      },
-      "source": [
-        "## Adding Features\n",
-        "\n",
-        "In our paper, we propose adding `Running Index`, `Calendar Features`, and `Auto Seasonal Features` to the table.\n",
-        "\n",
-        "**Feel free to experiment with your own features!**\n",
-        "\n",
-        "To do that, simply define your own feature functions and pass them to the `FeatureTransformer`."
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 700x700 with 4 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "rf = RandomForestClassifier().fit(X_train[:, :2], y_train)\n",
+    "xgb = XGBClassifier().fit(X_train[:, :2], y_train)\n",
+    "tabpfn = TabPFNClassifier().fit(X_train[:, :2], y_train)\n",
+    "\n",
+    "# Create a 2x2 subplot layout\n",
+    "fig, axes = plt.subplots(2, 2, figsize=(7, 7))\n",
+    "\n",
+    "# Plot Train Points\n",
+    "ax_points = axes[0, 0]\n",
+    "ax_points.set_title(\"Train points\")\n",
+    "ax_points.scatter(\n",
+    "    X_train[:, 0], X_train[:, 1], c=y_train, cmap=ListedColormap([\"#FF0000\", \"#0000FF\"])\n",
+    ")\n",
+    "\n",
+    "# Plot Random Forest\n",
+    "ax_rf = axes[0, 1]\n",
+    "plot_decision_boundary(ax_rf, rf, \"Random Forest\")\n",
+    "\n",
+    "# Plot XGBoost\n",
+    "ax_xgb = axes[1, 0]\n",
+    "plot_decision_boundary(ax_xgb, xgb, \"XGBoost\")\n",
+    "\n",
+    "# Plot TabPFN\n",
+    "ax_tabpfn = axes[1, 1]\n",
+    "plot_decision_boundary(ax_tabpfn, tabpfn, \"TabPFN\")\n",
+    "\n",
+    "# Adjust layout for better spacing\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "8tvOmmiOOT4o"
+   },
+   "source": [
+    "## Sin Curve Fitting with Regression\n",
+    "\n",
+    "Next, we investigate the curve-fitting behavior of the different models on a sin curve."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "f_6wB1N2OrYu",
+    "outputId": "f91662b0-c1cb-42b1-d4c0-5562492d4090"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 5,
-      "metadata": {
-        "id": "jKWF7CrmHS_5"
-      },
-      "outputs": [],
-      "source": [
-        "from tabpfn_time_series import FeatureTransformer\n",
-        "from tabpfn_time_series.features import (\n",
-        "    AutoSeasonalFeature,\n",
-        "    CalendarFeature,\n",
-        "    RunningIndexFeature,\n",
-        ")\n",
-        "\n",
-        "selected_features = [\n",
-        "    RunningIndexFeature(),\n",
-        "    CalendarFeature(),\n",
-        "    AutoSeasonalFeature(),\n",
-        "]\n",
-        "\n",
-        "feature_transformer = FeatureTransformer(selected_features)\n",
-        "\n",
-        "train_tsdf, test_tsdf = feature_transformer.transform(train_tsdf, test_tsdf)"
+     "data": {
+      "image/png": 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FSNoCAAAAAAAAgIv8/2jftpytr8p2AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1400x1200 with 4 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Toy function to generate data\n",
+    "def generate_sinx_plus_x(N):\n",
+    "    x = np.linspace(0, 20, N)\n",
+    "    y = np.sin(x) + x / 10\n",
+    "\n",
+    "    return x.reshape(-1, 1), y\n",
+    "\n",
+    "\n",
+    "# Utility function for plotting\n",
+    "def plot_predictions(ax, model, model_name):\n",
+    "    X_test = np.linspace(0, 20, 200).reshape(\n",
+    "        -1, 1\n",
+    "    )  # Predict for 200 points  between 0 and 20\n",
+    "    y_preds = model.predict(X_test)\n",
+    "    ax.set_title(model_name)\n",
+    "    ax.scatter(X_test, y_preds, label=\"Predictions\")\n",
+    "    ax.scatter(X_train, y_train, label=\"Train points\")\n",
+    "    ax.legend()\n",
+    "\n",
+    "\n",
+    "# Generate data\n",
+    "X_train, y_train = generate_sinx_plus_x(N=40)\n",
+    "\n",
+    "# Fit Models\n",
+    "rf = RandomForestRegressor(random_state=42).fit(X_train, y_train)\n",
+    "xgb = XGBRegressor(random_state=42).fit(X_train, y_train)\n",
+    "tabpfn = TabPFNRegressor()\n",
+    "tabpfn.fit(X_train, y_train)\n",
+    "\n",
+    "# Create a 2x2 subplot layout\n",
+    "fig, axs = plt.subplots(2, 2, figsize=(14, 12))\n",
+    "\n",
+    "# Plot train points\n",
+    "ax_points = axs[0, 0]\n",
+    "ax_points.set_title(\"Train points\")\n",
+    "ax_points.scatter(X_train, y_train, label=\"Train points\")\n",
+    "ax_points.legend()\n",
+    "\n",
+    "# Plot predictions for Random Forest\n",
+    "ax_rf = axs[0, 1]\n",
+    "plot_predictions(ax_rf, rf, \"Random Forest\")\n",
+    "\n",
+    "# Plot predictions for XGBoost\n",
+    "ax_xgb = axs[1, 0]\n",
+    "plot_predictions(ax_xgb, xgb, \"XGBoost\")\n",
+    "\n",
+    "# Plot predictions for TabPFN\n",
+    "ax_tabpfn = axs[1, 1]\n",
+    "plot_predictions(ax_tabpfn, tabpfn, \"TabPFN\")\n",
+    "\n",
+    "# Adjust layout for better spacing\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "XcYaJKT_Pw6T"
+   },
+   "source": [
+    "## Uncertainty of TabPFN / Quantile Regresison\n",
+    "\n",
+    "---\n",
+    "\n",
+    "\n",
+    "\n",
+    "TabPFN is trained to predict the distribution of the target variable and not just a single point. This is also the case for regression.\n",
+    "\n",
+    "As a result, we natively obtain uncertainty for the predictions of TabPFN (without the need for a new model or repeating models for different quantiles).\n",
+    "\n",
+    "In the following, we plot the uncertainty of TabPFN for a toy function with noise."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "r5q1UBos4W1O"
+   },
+   "outputs": [],
+   "source": [
+    "### Code to generate the plot (feel free to ignore)\n",
+    "def plot_regression_uncertainty(ax, x, y_line, y_noisy, x_test, color_multiplier=5):\n",
+    "    all_quantiles = preds[\"quantiles\"]\n",
+    "    y = np.array(all_quantiles)  # shape of y: (9, number of samples)\n",
+    "\n",
+    "    # Calculate the maximum and minimum values in y\n",
+    "    y_max = np.max(y, axis=0)\n",
+    "    y_min = np.min(y, axis=0)\n",
+    "\n",
+    "    # Calculate the widths of each quantile bin\n",
+    "    quantile_bin_widths = np.diff(\n",
+    "        y, axis=0\n",
+    "    )  # shape of quantile_bin_widths: (8, number of samples)\n",
+    "\n",
+    "    # Normalize the bin widths for a given x\n",
+    "    per_x_normalized_bin_widths = (quantile_bin_widths) / (y_max - y_min)\n",
+    "\n",
+    "    # Plotting\n",
+    "    num_bins, num_data_points = (\n",
+    "        per_x_normalized_bin_widths.shape[0],\n",
+    "        per_x_normalized_bin_widths.shape[1],\n",
+    "    )\n",
+    "    rect_width = (\n",
+    "        x_test[1] - x_test[0]\n",
+    "    ).squeeze()  # assuming the x query points are equally spaced out\n",
+    "\n",
+    "    for i in range(num_data_points):\n",
+    "        for j in range(num_bins):\n",
+    "            quantile_bin_widths[j, i]\n",
+    "            rect = plt.Rectangle(\n",
+    "                xy=(x_test[i][0] - rect_width / 2, y[j, i]),\n",
+    "                width=rect_width,\n",
+    "                height=quantile_bin_widths[j, i],\n",
+    "                facecolor=plt.cm.viridis(\n",
+    "                    per_x_normalized_bin_widths[j, i] * color_multiplier\n",
+    "                ),\n",
+    "                edgecolor=\"none\",\n",
+    "            )\n",
+    "            ax.add_patch(rect)\n",
+    "\n",
+    "    # Set limits and labels\n",
+    "    ax.plot(x, y_line, label=\"True line\", color=\"blue\")\n",
+    "    ax.set_xlim(min(x_test) - 1, max(x_test) + 1)\n",
+    "    ax.set_ylim(np.min(y_noisy) - 1, np.max(y_noisy) + 1)\n",
+    "    ax.set_xlabel(\"X\")\n",
+    "    ax.set_ylabel(\"Y\")\n",
+    "\n",
+    "    # ax.plot(x, y, label='True line', color='blue')\n",
+    "    ax.scatter(x, y_noisy, label=\"Noisy data\", color=\"red\", s=10)\n",
+    "\n",
+    "    plt.title(\"TabPFN Regression Uncertainty\")\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "# Generate Data\n",
+    "def generate_line_with_heteroscedastic_noise(\n",
+    "    m=0.8, num_points=200, x_start=0, x_end=100, noise_factor=0.1\n",
+    "):\n",
+    "    x = np.linspace(x_start, x_end, num_points)\n",
+    "    noise = np.random.randn(num_points)\n",
+    "    y = m * x\n",
+    "    y_noisy = y + (noise * noise_factor * x)\n",
+    "\n",
+    "    return x.reshape(-1, 1), y, y_noisy\n",
+    "\n",
+    "\n",
+    "def generate_line_with_heteroscedastic_noise_with_gap(\n",
+    "    m=0.8, num_points=200, x_start=0, x_end=100, noise_factor=0.1\n",
+    "):\n",
+    "    extra_points = num_points // 3\n",
+    "    x, y, y_noisy = generate_line_with_heteroscedastic_noise(\n",
+    "        m, num_points + extra_points, x_start, x_end, noise_factor\n",
+    "    )\n",
+    "    a = np.arange(num_points + extra_points)\n",
+    "    idx = np.where((a < num_points / 3) | (a > num_points / 3 + extra_points))\n",
+    "    return x[idx], y[idx], y_noisy[idx]\n",
+    "\n",
+    "\n",
+    "x, y_line, y_noisy = generate_line_with_heteroscedastic_noise_with_gap(0.8)\n",
+    "x_test = np.linspace(0, 100, 200).reshape(-1, 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "xpvqsL1f4W1O"
+   },
+   "outputs": [],
+   "source": [
+    "reg = TabPFNRegressor()\n",
+    "reg.fit(x, y_noisy)\n",
+    "preds = reg.predict(x_test, output_type=\"full\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "GwSCwFm-4W1O",
+    "outputId": "05fa4741-b689-4438-8000-40e7ae886f4f"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "N9WZ46ywJylH"
-      },
-      "source": [
-        "Let's take a look at the tables (train and test) before we proceed to do predictions.\n",
-        "\n",
-        "✅ Realize that we have added some features into the tables."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 6,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 0
-        },
-        "id": "tnKwZbngJx0X",
-        "outputId": "c17364a2-867f-4ae1-edf3-ab32703e423d"
-      },
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "                       target  running_index  year  second_of_minute_sin  \\\n",
-              "item_id timestamp                                                          \n",
-              "0       1979-01-31  1149.8700              0  1979                   0.0   \n",
-              "        1979-02-28  1053.8002              1  1979                   0.0   \n",
-              "        1979-03-31  1388.8798              2  1979                   0.0   \n",
-              "        1979-04-30  1783.3702              3  1979                   0.0   \n",
-              "        1979-05-31  1921.0252              4  1979                   0.0   \n",
-              "\n",
-              "                    second_of_minute_cos  minute_of_hour_sin  \\\n",
-              "item_id timestamp                                              \n",
-              "0       1979-01-31                   1.0                 0.0   \n",
-              "        1979-02-28                   1.0                 0.0   \n",
-              "        1979-03-31                   1.0                 0.0   \n",
-              "        1979-04-30                   1.0                 0.0   \n",
-              "        1979-05-31                   1.0                 0.0   \n",
-              "\n",
-              "                    minute_of_hour_cos  hour_of_day_sin  hour_of_day_cos  \\\n",
-              "item_id timestamp                                                          \n",
-              "0       1979-01-31                 1.0              0.0              1.0   \n",
-              "        1979-02-28                 1.0              0.0              1.0   \n",
-              "        1979-03-31                 1.0              0.0              1.0   \n",
-              "        1979-04-30                 1.0              0.0              1.0   \n",
-              "        1979-05-31                 1.0              0.0              1.0   \n",
-              "\n",
-              "                    day_of_week_sin  ...    sin_#0        cos_#0  \\\n",
-              "item_id timestamp                    ...                           \n",
-              "0       1979-01-31     8.660254e-01  ...  0.000000  1.000000e+00   \n",
-              "        1979-02-28     8.660254e-01  ...  0.500000  8.660254e-01   \n",
-              "        1979-03-31    -8.660254e-01  ...  0.866025  5.000000e-01   \n",
-              "        1979-04-30     0.000000e+00  ...  1.000000  6.123234e-17   \n",
-              "        1979-05-31     1.224647e-16  ...  0.866025 -5.000000e-01   \n",
-              "\n",
-              "                          sin_#1  cos_#1        sin_#2        cos_#2  \\\n",
-              "item_id timestamp                                                      \n",
-              "0       1979-01-31  0.000000e+00     1.0  0.000000e+00  1.000000e+00   \n",
-              "        1979-02-28  8.660254e-01     0.5  1.000000e+00  6.123234e-17   \n",
-              "        1979-03-31  8.660254e-01    -0.5  1.224647e-16 -1.000000e+00   \n",
-              "        1979-04-30  1.224647e-16    -1.0 -1.000000e+00 -1.836970e-16   \n",
-              "        1979-05-31 -8.660254e-01    -0.5 -2.449294e-16  1.000000e+00   \n",
-              "\n",
-              "                          sin_#3  cos_#3        sin_#4  cos_#4  \n",
-              "item_id timestamp                                               \n",
-              "0       1979-01-31  0.000000e+00     1.0  0.000000e+00     1.0  \n",
-              "        1979-02-28  1.224647e-16    -1.0  8.660254e-01    -0.5  \n",
-              "        1979-03-31 -2.449294e-16     1.0 -8.660254e-01    -0.5  \n",
-              "        1979-04-30  3.673940e-16    -1.0 -2.449294e-16     1.0  \n",
-              "        1979-05-31 -4.898587e-16     1.0  8.660254e-01    -0.5  \n",
-              "\n",
-              "[5 rows x 29 columns]"
-            ],
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-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th>target</th>\n",
-              "      <th>running_index</th>\n",
-              "      <th>year</th>\n",
-              "      <th>second_of_minute_sin</th>\n",
-              "      <th>second_of_minute_cos</th>\n",
-              "      <th>minute_of_hour_sin</th>\n",
-              "      <th>minute_of_hour_cos</th>\n",
-              "      <th>hour_of_day_sin</th>\n",
-              "      <th>hour_of_day_cos</th>\n",
-              "      <th>day_of_week_sin</th>\n",
-              "      <th>...</th>\n",
-              "      <th>sin_#0</th>\n",
-              "      <th>cos_#0</th>\n",
-              "      <th>sin_#1</th>\n",
-              "      <th>cos_#1</th>\n",
-              "      <th>sin_#2</th>\n",
-              "      <th>cos_#2</th>\n",
-              "      <th>sin_#3</th>\n",
-              "      <th>cos_#3</th>\n",
-              "      <th>sin_#4</th>\n",
-              "      <th>cos_#4</th>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>item_id</th>\n",
-              "      <th>timestamp</th>\n",
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-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
-              "      <th>1979-01-31</th>\n",
-              "      <td>1149.8700</td>\n",
-              "      <td>0</td>\n",
-              "      <td>1979</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.000000</td>\n",
-              "      <td>1.000000e+00</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>1.000000e+00</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>1.0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1979-02-28</th>\n",
-              "      <td>1053.8002</td>\n",
-              "      <td>1</td>\n",
-              "      <td>1979</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.500000</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>1.000000e+00</td>\n",
-              "      <td>6.123234e-17</td>\n",
-              "      <td>1.224647e-16</td>\n",
-              "      <td>-1.0</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1979-03-31</th>\n",
-              "      <td>1388.8798</td>\n",
-              "      <td>2</td>\n",
-              "      <td>1979</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.866025</td>\n",
-              "      <td>5.000000e-01</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "      <td>1.224647e-16</td>\n",
-              "      <td>-1.000000e+00</td>\n",
-              "      <td>-2.449294e-16</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1979-04-30</th>\n",
-              "      <td>1783.3702</td>\n",
-              "      <td>3</td>\n",
-              "      <td>1979</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>...</td>\n",
-              "      <td>1.000000</td>\n",
-              "      <td>6.123234e-17</td>\n",
-              "      <td>1.224647e-16</td>\n",
-              "      <td>-1.0</td>\n",
-              "      <td>-1.000000e+00</td>\n",
-              "      <td>-1.836970e-16</td>\n",
-              "      <td>3.673940e-16</td>\n",
-              "      <td>-1.0</td>\n",
-              "      <td>-2.449294e-16</td>\n",
-              "      <td>1.0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1979-05-31</th>\n",
-              "      <td>1921.0252</td>\n",
-              "      <td>4</td>\n",
-              "      <td>1979</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>1.224647e-16</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.866025</td>\n",
-              "      <td>-5.000000e-01</td>\n",
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-              "      <td>-0.5</td>\n",
-              "      <td>-2.449294e-16</td>\n",
-              "      <td>1.000000e+00</td>\n",
-              "      <td>-4.898587e-16</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
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-              "        if (!dataTable) return;\n",
-              "\n",
-              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
-              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
-              "          + ' to learn more about interactive tables.';\n",
-              "        element.innerHTML = '';\n",
-              "        dataTable['output_type'] = 'display_data';\n",
-              "        await google.colab.output.renderOutput(dataTable, element);\n",
-              "        const docLink = document.createElement('div');\n",
-              "        docLink.innerHTML = docLinkHtml;\n",
-              "        element.appendChild(docLink);\n",
-              "      }\n",
-              "    </script>\n",
-              "  </div>\n",
-              "\n",
-              "\n",
-              "    <div id=\"df-4e9c9c90-1671-4cf3-8c51-32cb9ad8db61\">\n",
-              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4e9c9c90-1671-4cf3-8c51-32cb9ad8db61')\"\n",
-              "                title=\"Suggest charts\"\n",
-              "                style=\"display:none;\">\n",
-              "\n",
-              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
-              "     width=\"24px\">\n",
-              "    <g>\n",
-              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
-              "    </g>\n",
-              "</svg>\n",
-              "      </button>\n",
-              "\n",
-              "<style>\n",
-              "  .colab-df-quickchart {\n",
-              "      --bg-color: #E8F0FE;\n",
-              "      --fill-color: #1967D2;\n",
-              "      --hover-bg-color: #E2EBFA;\n",
-              "      --hover-fill-color: #174EA6;\n",
-              "      --disabled-fill-color: #AAA;\n",
-              "      --disabled-bg-color: #DDD;\n",
-              "  }\n",
-              "\n",
-              "  [theme=dark] .colab-df-quickchart {\n",
-              "      --bg-color: #3B4455;\n",
-              "      --fill-color: #D2E3FC;\n",
-              "      --hover-bg-color: #434B5C;\n",
-              "      --hover-fill-color: #FFFFFF;\n",
-              "      --disabled-bg-color: #3B4455;\n",
-              "      --disabled-fill-color: #666;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart {\n",
-              "    background-color: var(--bg-color);\n",
-              "    border: none;\n",
-              "    border-radius: 50%;\n",
-              "    cursor: pointer;\n",
-              "    display: none;\n",
-              "    fill: var(--fill-color);\n",
-              "    height: 32px;\n",
-              "    padding: 0;\n",
-              "    width: 32px;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart:hover {\n",
-              "    background-color: var(--hover-bg-color);\n",
-              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
-              "    fill: var(--button-hover-fill-color);\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart-complete:disabled,\n",
-              "  .colab-df-quickchart-complete:disabled:hover {\n",
-              "    background-color: var(--disabled-bg-color);\n",
-              "    fill: var(--disabled-fill-color);\n",
-              "    box-shadow: none;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-spinner {\n",
-              "    border: 2px solid var(--fill-color);\n",
-              "    border-color: transparent;\n",
-              "    border-bottom-color: var(--fill-color);\n",
-              "    animation:\n",
-              "      spin 1s steps(1) infinite;\n",
-              "  }\n",
-              "\n",
-              "  @keyframes spin {\n",
-              "    0% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "      border-left-color: var(--fill-color);\n",
-              "    }\n",
-              "    20% {\n",
-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "    }\n",
-              "    30% {\n",
-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    40% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "    }\n",
-              "    60% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    80% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "    90% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "  }\n",
-              "</style>\n",
-              "\n",
-              "      <script>\n",
-              "        async function quickchart(key) {\n",
-              "          const quickchartButtonEl =\n",
-              "            document.querySelector('#' + key + ' button');\n",
-              "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
-              "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
-              "          try {\n",
-              "            const charts = await google.colab.kernel.invokeFunction(\n",
-              "                'suggestCharts', [key], {});\n",
-              "          } catch (error) {\n",
-              "            console.error('Error during call to suggestCharts:', error);\n",
-              "          }\n",
-              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
-              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
-              "        }\n",
-              "        (() => {\n",
-              "          let quickchartButtonEl =\n",
-              "            document.querySelector('#df-4e9c9c90-1671-4cf3-8c51-32cb9ad8db61 button');\n",
-              "          quickchartButtonEl.style.display =\n",
-              "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
-              "        })();\n",
-              "      </script>\n",
-              "    </div>\n",
-              "\n",
-              "    </div>\n",
-              "  </div>\n"
-            ],
-            "application/vnd.google.colaboratory.intrinsic+json": {
-              "type": "dataframe",
-              "variable_name": "train_tsdf"
-            }
-          },
-          "metadata": {},
-          "execution_count": 6
-        }
-      ],
-      "source": [
-        "train_tsdf.head()"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x600 with 2 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(12, 6))\n",
+    "\n",
+    "# Plot the original data\n",
+    "ax = fig.add_subplot(121)\n",
+    "ax.plot(x, y_line, label=\"True line\", color=\"blue\")\n",
+    "ax.scatter(x, y_noisy, label=\"Noisy data\", color=\"red\", s=10)\n",
+    "ax.set_xlabel(\"X\")\n",
+    "ax.set_ylabel(\"Y\")\n",
+    "ax.set_xlim(min(x) - 1, max(x) + 1)\n",
+    "ax.set_ylim(np.min(y_noisy) - 1, np.max(y_noisy) + 1)\n",
+    "ax.set_title(\"Heteroscedastic Noise along a Sloping Line\")\n",
+    "ax.legend()\n",
+    "\n",
+    "# plot the uncertainty estimates obtained from TabPFN\n",
+    "ax = fig.add_subplot(122)\n",
+    "plot_regression_uncertainty(ax, x, y_line, y_noisy, x_test, color_multiplier=5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "VJMcv-KvPYIh"
+   },
+   "source": [
+    "# Time Series Forecasting <a name=\"timeseries\"></a>\n",
+    "\n",
+    "TabPFN can be used for time series prediction, following the work of Hoo et al. (Zero-Shot Time Series Forecasting with TabPFNv2; https://arxiv.org/abs/2501.02945v3).\n",
+    "\n",
+    "In this demo, we will use the time series dataset from [Chronos Dataset](https://huggingface.co/datasets/autogluon/chronos_datasets) on HuggingFace. Also, we'll keep it short and work with just 2 time series from the dataset.\n",
+    "\n",
+    "Feel free to explore other datasets by using the dataset names from Chronos Dataset on HuggingFace or even use time series data of your own problem.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Z3wiT00Uf0dF"
+   },
+   "source": [
+    "## *Installation*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "J0cUKia3fzrz"
+   },
+   "outputs": [],
+   "source": [
+    "!uv pip install tabpfn-time-series\n",
+    "raise ValueError(\n",
+    "    \"Make sure to restart the session before proceeding, otherwise errors will follow (Runtime > Restart Session)\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "kNOAk5sPHS_3"
+   },
+   "source": [
+    "## Load Time Series Data\n",
+    "\n",
+    "In this demo, we will use the time series dataset from [Chronos Dataset](https://huggingface.co/datasets/autogluon/chronos_datasets) on HuggingFace. Also, we'll keep it short and work with just 2 time series from the dataset.\n",
+    "\n",
+    "Feel free to explore other datasets by using the dataset names from Chronos Dataset on HuggingFace or even use time series data of your own problem."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "qgHudyQdHS_3"
+   },
+   "outputs": [],
+   "source": [
+    "dataset_metadata = {\n",
+    "    \"monash_tourism_monthly\": {\"prediction_length\": 24},\n",
+    "    \"m4_hourly\": {\"prediction_length\": 48},\n",
+    "}\n",
+    "\n",
+    "dataset_choice = \"monash_tourism_monthly\"\n",
+    "num_time_series_subset = 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 217,
+     "referenced_widgets": [
+      "8af3e44759a84b24923e15c7722b8518",
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+      "0ef1661193d44ef99f7e281cb79c40b5",
+      "38d0e7f682cd45b193066630854b3329",
+      "30bea92a5ae940428e1f3f534611309e",
+      "a1292ad49a5b49c582f15ade36b78282",
+      "5029e0c3a04c418c9f2284c505cfa52e",
+      "41ef74f05a894e2ab10dde4e6d4c49da",
+      "b15054c98fd8457095b01a54ad491056",
+      "e4a2681db14a43a6836f0fd3ab154509",
+      "e0ce26fdeefc4061879dbd285a3ec436",
+      "7e13c9b09413417b9d2cb7af278a46fe",
+      "12a2a205bd944f8e8a3643f977c38b56",
+      "758dc947f2dc4db1b28f427add34f4c6",
+      "b7227f27d0c341419b87360437ea2132",
+      "769284272f1545a5b3dafa71d2b9439d",
+      "0c458dab93ee415f839fd216d33b43d9",
+      "96db2596e70f4e809832e39642b8af99",
+      "614ab8ceb45245cf8d11dcb576b3e27d",
+      "bcd4f57966ce4cd594bce97f564dfbfc",
+      "73584ad402334131a9b7f96d13a086a4",
+      "e369aa70fe3d4923ae127eab8a8d1490",
+      "f42b869e3b994141b0c81dcffc39c042",
+      "498eb04a0a594e87af9c566e2878e515",
+      "a93d570f7c4547288f6257d8221593be",
+      "78a9d6c24bf0436fb7184a1ac46f8593",
+      "769f504e490449dd952edf304ea53a76",
+      "92834505829e49cd99d1ad420bddf0d1",
+      "88b6a04a2d974027a9936cb9bb84eac0",
+      "5975c2b92d634044b794d793aeb4d52f",
+      "894db0aa656e4882b2117d1ac8398be5",
+      "1d7a439caf5a462e81e67f8cc9b2a998"
+     ]
     },
+    "id": "Qc1mHevjHS_4",
+    "outputId": "395ee836-630b-45dd-ba5f-5024aa43cc73"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 7,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 0
-        },
-        "id": "yKaNq3RAKMH9",
-        "outputId": "44f52c0f-8370-4725-f07d-b7083a95b348"
-      },
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "                    target  running_index  year  second_of_minute_sin  \\\n",
-              "item_id timestamp                                                       \n",
-              "0       1992-08-31     NaN            163  1992                   0.0   \n",
-              "        1992-09-30     NaN            164  1992                   0.0   \n",
-              "        1992-10-31     NaN            165  1992                   0.0   \n",
-              "        1992-11-30     NaN            166  1992                   0.0   \n",
-              "        1992-12-31     NaN            167  1992                   0.0   \n",
-              "\n",
-              "                    second_of_minute_cos  minute_of_hour_sin  \\\n",
-              "item_id timestamp                                              \n",
-              "0       1992-08-31                   1.0                 0.0   \n",
-              "        1992-09-30                   1.0                 0.0   \n",
-              "        1992-10-31                   1.0                 0.0   \n",
-              "        1992-11-30                   1.0                 0.0   \n",
-              "        1992-12-31                   1.0                 0.0   \n",
-              "\n",
-              "                    minute_of_hour_cos  hour_of_day_sin  hour_of_day_cos  \\\n",
-              "item_id timestamp                                                          \n",
-              "0       1992-08-31                 1.0              0.0              1.0   \n",
-              "        1992-09-30                 1.0              0.0              1.0   \n",
-              "        1992-10-31                 1.0              0.0              1.0   \n",
-              "        1992-11-30                 1.0              0.0              1.0   \n",
-              "        1992-12-31                 1.0              0.0              1.0   \n",
-              "\n",
-              "                    day_of_week_sin  ...    sin_#0        cos_#0  \\\n",
-              "item_id timestamp                    ...                           \n",
-              "0       1992-08-31     0.000000e+00  ... -0.500000 -8.660254e-01   \n",
-              "        1992-09-30     8.660254e-01  ... -0.866025 -5.000000e-01   \n",
-              "        1992-10-31    -8.660254e-01  ... -1.000000 -1.224956e-14   \n",
-              "        1992-11-30     0.000000e+00  ... -0.866025  5.000000e-01   \n",
-              "        1992-12-31     1.224647e-16  ... -0.500000  8.660254e-01   \n",
-              "\n",
-              "                          sin_#1  cos_#1        sin_#2        cos_#2  \\\n",
-              "item_id timestamp                                                      \n",
-              "0       1992-08-31  8.660254e-01     0.5 -1.000000e+00 -2.596808e-14   \n",
-              "        1992-09-30  8.660254e-01    -0.5 -3.135839e-14  1.000000e+00   \n",
-              "        1992-10-31  2.449913e-14    -1.0  1.000000e+00  3.674869e-14   \n",
-              "        1992-11-30 -8.660254e-01    -0.5 -1.470443e-14 -1.000000e+00   \n",
-              "        1992-12-31 -8.660254e-01     0.5 -1.000000e+00  9.314124e-15   \n",
-              "\n",
-              "                          sin_#3  cos_#3        sin_#4  cos_#4  \n",
-              "item_id timestamp                                               \n",
-              "0       1992-08-31  5.193617e-14    -1.0  8.660254e-01    -0.5  \n",
-              "        1992-09-30 -6.271677e-14     1.0 -8.660254e-01    -0.5  \n",
-              "        1992-10-31  7.349738e-14    -1.0 -4.899825e-14     1.0  \n",
-              "        1992-11-30  2.940885e-14     1.0  8.660254e-01    -0.5  \n",
-              "        1992-12-31 -1.862825e-14    -1.0 -8.660254e-01    -0.5  \n",
-              "\n",
-              "[5 rows x 29 columns]"
-            ],
-            "text/html": [
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-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th>target</th>\n",
-              "      <th>running_index</th>\n",
-              "      <th>year</th>\n",
-              "      <th>second_of_minute_sin</th>\n",
-              "      <th>second_of_minute_cos</th>\n",
-              "      <th>minute_of_hour_sin</th>\n",
-              "      <th>minute_of_hour_cos</th>\n",
-              "      <th>hour_of_day_sin</th>\n",
-              "      <th>hour_of_day_cos</th>\n",
-              "      <th>day_of_week_sin</th>\n",
-              "      <th>...</th>\n",
-              "      <th>sin_#0</th>\n",
-              "      <th>cos_#0</th>\n",
-              "      <th>sin_#1</th>\n",
-              "      <th>cos_#1</th>\n",
-              "      <th>sin_#2</th>\n",
-              "      <th>cos_#2</th>\n",
-              "      <th>sin_#3</th>\n",
-              "      <th>cos_#3</th>\n",
-              "      <th>sin_#4</th>\n",
-              "      <th>cos_#4</th>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>item_id</th>\n",
-              "      <th>timestamp</th>\n",
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-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
-              "      <th>1992-08-31</th>\n",
-              "      <td>NaN</td>\n",
-              "      <td>163</td>\n",
-              "      <td>1992</td>\n",
-              "      <td>0.0</td>\n",
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-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>...</td>\n",
-              "      <td>-0.500000</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>-1.000000e+00</td>\n",
-              "      <td>-2.596808e-14</td>\n",
-              "      <td>5.193617e-14</td>\n",
-              "      <td>-1.0</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1992-09-30</th>\n",
-              "      <td>NaN</td>\n",
-              "      <td>164</td>\n",
-              "      <td>1992</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>...</td>\n",
-              "      <td>-0.866025</td>\n",
-              "      <td>-5.000000e-01</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "      <td>-3.135839e-14</td>\n",
-              "      <td>1.000000e+00</td>\n",
-              "      <td>-6.271677e-14</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1992-10-31</th>\n",
-              "      <td>NaN</td>\n",
-              "      <td>165</td>\n",
-              "      <td>1992</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>...</td>\n",
-              "      <td>-1.000000</td>\n",
-              "      <td>-1.224956e-14</td>\n",
-              "      <td>2.449913e-14</td>\n",
-              "      <td>-1.0</td>\n",
-              "      <td>1.000000e+00</td>\n",
-              "      <td>3.674869e-14</td>\n",
-              "      <td>7.349738e-14</td>\n",
-              "      <td>-1.0</td>\n",
-              "      <td>-4.899825e-14</td>\n",
-              "      <td>1.0</td>\n",
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-              "      <th>1992-11-30</th>\n",
-              "      <td>NaN</td>\n",
-              "      <td>166</td>\n",
-              "      <td>1992</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>...</td>\n",
-              "      <td>-0.866025</td>\n",
-              "      <td>5.000000e-01</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "      <td>-1.470443e-14</td>\n",
-              "      <td>-1.000000e+00</td>\n",
-              "      <td>2.940885e-14</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1992-12-31</th>\n",
-              "      <td>NaN</td>\n",
-              "      <td>167</td>\n",
-              "      <td>1992</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>1.224647e-16</td>\n",
-              "      <td>...</td>\n",
-              "      <td>-0.500000</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>-1.000000e+00</td>\n",
-              "      <td>9.314124e-15</td>\n",
-              "      <td>-1.862825e-14</td>\n",
-              "      <td>-1.0</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>5 rows × 29 columns</p>\n",
-              "</div>\n",
-              "    <div class=\"colab-df-buttons\">\n",
-              "\n",
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-              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-416fb540-8db5-46d5-9e39-43632a5c9afa')\"\n",
-              "            title=\"Convert this dataframe to an interactive table.\"\n",
-              "            style=\"display:none;\">\n",
-              "\n",
-              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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-              "\n",
-              "  <style>\n",
-              "    .colab-df-container {\n",
-              "      display:flex;\n",
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-              "\n",
-              "    .colab-df-convert {\n",
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-              "      border-radius: 50%;\n",
-              "      cursor: pointer;\n",
-              "      display: none;\n",
-              "      fill: #1967D2;\n",
-              "      height: 32px;\n",
-              "      padding: 0 0 0 0;\n",
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-              "\n",
-              "    .colab-df-convert:hover {\n",
-              "      background-color: #E2EBFA;\n",
-              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
-              "      fill: #174EA6;\n",
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-              "\n",
-              "    .colab-df-buttons div {\n",
-              "      margin-bottom: 4px;\n",
-              "    }\n",
-              "\n",
-              "    [theme=dark] .colab-df-convert {\n",
-              "      background-color: #3B4455;\n",
-              "      fill: #D2E3FC;\n",
-              "    }\n",
-              "\n",
-              "    [theme=dark] .colab-df-convert:hover {\n",
-              "      background-color: #434B5C;\n",
-              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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-              "      buttonEl.style.display =\n",
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-              "                                                    [key], {});\n",
-              "        if (!dataTable) return;\n",
-              "\n",
-              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
-              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
-              "          + ' to learn more about interactive tables.';\n",
-              "        element.innerHTML = '';\n",
-              "        dataTable['output_type'] = 'display_data';\n",
-              "        await google.colab.output.renderOutput(dataTable, element);\n",
-              "        const docLink = document.createElement('div');\n",
-              "        docLink.innerHTML = docLinkHtml;\n",
-              "        element.appendChild(docLink);\n",
-              "      }\n",
-              "    </script>\n",
-              "  </div>\n",
-              "\n",
-              "\n",
-              "    <div id=\"df-8b1788eb-1bd2-4277-871c-9044bad7da16\">\n",
-              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8b1788eb-1bd2-4277-871c-9044bad7da16')\"\n",
-              "                title=\"Suggest charts\"\n",
-              "                style=\"display:none;\">\n",
-              "\n",
-              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
-              "     width=\"24px\">\n",
-              "    <g>\n",
-              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
-              "    </g>\n",
-              "</svg>\n",
-              "      </button>\n",
-              "\n",
-              "<style>\n",
-              "  .colab-df-quickchart {\n",
-              "      --bg-color: #E8F0FE;\n",
-              "      --fill-color: #1967D2;\n",
-              "      --hover-bg-color: #E2EBFA;\n",
-              "      --hover-fill-color: #174EA6;\n",
-              "      --disabled-fill-color: #AAA;\n",
-              "      --disabled-bg-color: #DDD;\n",
-              "  }\n",
-              "\n",
-              "  [theme=dark] .colab-df-quickchart {\n",
-              "      --bg-color: #3B4455;\n",
-              "      --fill-color: #D2E3FC;\n",
-              "      --hover-bg-color: #434B5C;\n",
-              "      --hover-fill-color: #FFFFFF;\n",
-              "      --disabled-bg-color: #3B4455;\n",
-              "      --disabled-fill-color: #666;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart {\n",
-              "    background-color: var(--bg-color);\n",
-              "    border: none;\n",
-              "    border-radius: 50%;\n",
-              "    cursor: pointer;\n",
-              "    display: none;\n",
-              "    fill: var(--fill-color);\n",
-              "    height: 32px;\n",
-              "    padding: 0;\n",
-              "    width: 32px;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart:hover {\n",
-              "    background-color: var(--hover-bg-color);\n",
-              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
-              "    fill: var(--button-hover-fill-color);\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart-complete:disabled,\n",
-              "  .colab-df-quickchart-complete:disabled:hover {\n",
-              "    background-color: var(--disabled-bg-color);\n",
-              "    fill: var(--disabled-fill-color);\n",
-              "    box-shadow: none;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-spinner {\n",
-              "    border: 2px solid var(--fill-color);\n",
-              "    border-color: transparent;\n",
-              "    border-bottom-color: var(--fill-color);\n",
-              "    animation:\n",
-              "      spin 1s steps(1) infinite;\n",
-              "  }\n",
-              "\n",
-              "  @keyframes spin {\n",
-              "    0% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "      border-left-color: var(--fill-color);\n",
-              "    }\n",
-              "    20% {\n",
-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "    }\n",
-              "    30% {\n",
-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    40% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "    }\n",
-              "    60% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    80% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "    90% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "  }\n",
-              "</style>\n",
-              "\n",
-              "      <script>\n",
-              "        async function quickchart(key) {\n",
-              "          const quickchartButtonEl =\n",
-              "            document.querySelector('#' + key + ' button');\n",
-              "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
-              "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
-              "          try {\n",
-              "            const charts = await google.colab.kernel.invokeFunction(\n",
-              "                'suggestCharts', [key], {});\n",
-              "          } catch (error) {\n",
-              "            console.error('Error during call to suggestCharts:', error);\n",
-              "          }\n",
-              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
-              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
-              "        }\n",
-              "        (() => {\n",
-              "          let quickchartButtonEl =\n",
-              "            document.querySelector('#df-8b1788eb-1bd2-4277-871c-9044bad7da16 button');\n",
-              "          quickchartButtonEl.style.display =\n",
-              "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
-              "        })();\n",
-              "      </script>\n",
-              "    </div>\n",
-              "\n",
-              "    </div>\n",
-              "  </div>\n"
-            ],
-            "application/vnd.google.colaboratory.intrinsic+json": {
-              "type": "dataframe",
-              "variable_name": "test_tsdf"
-            }
-          },
-          "metadata": {},
-          "execution_count": 7
-        }
-      ],
-      "source": [
-        "test_tsdf.head()"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
+      "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
+      "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
+      "You will be able to reuse this secret in all of your notebooks.\n",
+      "Please note that authentication is recommended but still optional to access public models or datasets.\n",
+      "  warnings.warn(\n"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "CqNGS6a0HS_5"
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8af3e44759a84b24923e15c7722b8518",
+       "version_major": 2,
+       "version_minor": 0
       },
-      "source": [
-        "## Prediction"
+      "text/plain": [
+       "README.md: 0.00B [00:00, ?B/s]"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "iAh9dvY5HS_5"
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e0ce26fdeefc4061879dbd285a3ec436",
+       "version_major": 2,
+       "version_minor": 0
       },
-      "source": [
-        "Now, let's perform prediction.\n",
-        "\n",
-        "We provide two options, `TabPFNMode.LOCAL` and `TabPFNMode.CLIENT`, as the backend for TabPFN.\n",
-        "\n",
-        "- `TabPFNMode.LOCAL` uses your local machine to run TabPFN.\n",
-        "- `TabPFNMode.CLIENT` uses TabPFN's inference service provided by [tabpfn-client](https://github.com/automl/tabpfn-client)\n",
-        "\n",
-        "For this demo, we'll use `TabPFNMode.CLIENT` to perform prediction. If you have not use the client before, you'll be prompted to create an account.\n",
-        "\n",
-        "Note: if your machine doesn't have a GPU, using `TabPFNMode.CLIENT` is recommended -- must faster 😉.\n"
+      "text/plain": [
+       "monash_tourism_monthly/train-00000-of-00(…):   0%|          | 0.00/335k [00:00<?, ?B/s]"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 8,
-      "metadata": {
-        "id": "v_gi5gDFHS_5",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 98,
-          "referenced_widgets": [
-            "73d2588763f942d7ad03a74a4d9d4751",
-            "532a400be5354241bf672103c94acf96",
-            "7f1e814ce5c84e298ab7fb552e898146",
-            "7588e1686607416ea734e566d42de33c",
-            "0ecacdc21e114ab9babf55260145a6e2",
-            "829982ccd1d748cd89ff08707cd2e616",
-            "f481ffacd4114f25b0a8d7fcf475f148",
-            "61069c92812743dca890bab4c19f79e5",
-            "f3206138775d4d1aae38f67ae4b38168",
-            "f5a0c6afd48f4bf0b64e5f49bdb79298",
-            "e7c4c642419b4aa6a32b4948bf7fec66",
-            "ee1642c77a2c4c2f9318bfb8a8c09409",
-            "6d37921372dc432a9a4a05d1c5c47144",
-            "e39edfff68dd4b0dbb6afa9ea3f935a0",
-            "5be7af29968a4757a434e9a141cd18fd",
-            "33b37f665fd34a93a4f3d46a656b772b",
-            "5c9e3aacac05461190192145c9ca992d",
-            "11ee51dab89149f3b1bfc481cfc5bb29",
-            "058fc385f12d4ffa88193d52d3276304",
-            "28d72184e91245e4abf0ff88ac955de2",
-            "8305015058ef402cb67c3ee76a7a42e7",
-            "91e599083d8b4ba8aff5cd061da0648b"
-          ]
-        },
-        "collapsed": true,
-        "outputId": "fdfb26be-38fb-47f4-da65-53e96f4107e8"
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e369aa70fe3d4923ae127eab8a8d1490",
+       "version_major": 2,
+       "version_minor": 0
       },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "tabpfn-v2-regressor-2noar4o2.ckpt:   0%|          | 0.00/44.4M [00:00<?, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "73d2588763f942d7ad03a74a4d9d4751"
-            }
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "config.json:   0%|          | 0.00/37.0 [00:00<?, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "ee1642c77a2c4c2f9318bfb8a8c09409"
-            }
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "GPU 0:: 100%|██████████| 2/2 [00:04<00:00,  2.38s/it]\n"
-          ]
-        }
-      ],
-      "source": [
-        "from tabpfn_time_series import TabPFNMode, TabPFNTimeSeriesPredictor\n",
-        "\n",
-        "predictor = TabPFNTimeSeriesPredictor(\n",
-        "    tabpfn_mode=TabPFNMode.LOCAL,  # adapt this to TabPFNMode.CLIENT if using API\n",
-        ")\n",
-        "\n",
-        "pred = predictor.predict(train_tsdf, test_tsdf)"
+      "text/plain": [
+       "Generating train split:   0%|          | 0/366 [00:00<?, ? examples/s]"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from datasets import load_dataset\n",
+    "from tabpfn_time_series import TimeSeriesDataFrame\n",
+    "from tabpfn_time_series.data_preparation import generate_test_X, to_gluonts_univariate\n",
+    "\n",
+    "prediction_length = dataset_metadata[dataset_choice][\"prediction_length\"]\n",
+    "dataset = load_dataset(\"autogluon/chronos_datasets\", dataset_choice)\n",
+    "\n",
+    "tsdf = TimeSeriesDataFrame(to_gluonts_univariate(dataset[\"train\"]))\n",
+    "tsdf = tsdf[\n",
+    "    tsdf.index.get_level_values(\"item_id\").isin(tsdf.item_ids[:num_time_series_subset])\n",
+    "]\n",
+    "train_tsdf, test_tsdf_ground_truth = tsdf.train_test_split(\n",
+    "    prediction_length=prediction_length\n",
+    ")\n",
+    "test_tsdf = generate_test_X(train_tsdf, prediction_length)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "cKH8WtXdHS_4"
+   },
+   "source": [
+    "Let's take a look at the time series data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 607
     },
+    "id": "jOm8_GLEHS_4",
+    "outputId": "cbffcec8-67f1-40e1-8d66-1aab471e9f32"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "toHiW8LeHS_5"
-      },
-      "source": [
-        "## Visualize the Results\n",
-        "\n",
-        "Let's visualize the forecasting results.\n",
-        "\n",
-        "Also, note that we provide both **point prediction** and **quantile prediction**, how amazing! 😄"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x600 with 2 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from tabpfn_time_series.plot import plot_actual_ts\n",
+    "\n",
+    "plot_actual_ts(train_tsdf, test_tsdf_ground_truth)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "UWmQq17tHS_4"
+   },
+   "source": [
+    "## Adding Features\n",
+    "\n",
+    "In our paper, we propose adding `Running Index`, `Calendar Features`, and `Auto Seasonal Features` to the table.\n",
+    "\n",
+    "**Feel free to experiment with your own features!**\n",
+    "\n",
+    "To do that, simply define your own feature functions and pass them to the `FeatureTransformer`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "jKWF7CrmHS_5"
+   },
+   "outputs": [],
+   "source": [
+    "from tabpfn_time_series import FeatureTransformer\n",
+    "from tabpfn_time_series.features import (\n",
+    "    AutoSeasonalFeature,\n",
+    "    CalendarFeature,\n",
+    "    RunningIndexFeature,\n",
+    ")\n",
+    "\n",
+    "selected_features = [\n",
+    "    RunningIndexFeature(),\n",
+    "    CalendarFeature(),\n",
+    "    AutoSeasonalFeature(),\n",
+    "]\n",
+    "\n",
+    "feature_transformer = FeatureTransformer(selected_features)\n",
+    "\n",
+    "train_tsdf, test_tsdf = feature_transformer.transform(train_tsdf, test_tsdf)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "N9WZ46ywJylH"
+   },
+   "source": [
+    "Let's take a look at the tables (train and test) before we proceed to do predictions.\n",
+    "\n",
+    "✅ Realize that we have added some features into the tables."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "tnKwZbngJx0X",
+    "outputId": "1ea42799-8360-42d5-e1f6-648340baabca"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 9,
-      "metadata": {
-        "id": "FCxt23reHS_5",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 607
-        },
-        "outputId": "24f262d9-fa1e-497f-df3c-86787a9a6194"
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "type": "dataframe",
+       "variable_name": "train_tsdf"
       },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 1000x600 with 2 Axes>"
-            ],
-            "image/png": 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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>target</th>\n",
+       "      <th>running_index</th>\n",
+       "      <th>year</th>\n",
+       "      <th>second_of_minute_sin</th>\n",
+       "      <th>second_of_minute_cos</th>\n",
+       "      <th>minute_of_hour_sin</th>\n",
+       "      <th>minute_of_hour_cos</th>\n",
+       "      <th>hour_of_day_sin</th>\n",
+       "      <th>hour_of_day_cos</th>\n",
+       "      <th>day_of_week_sin</th>\n",
+       "      <th>...</th>\n",
+       "      <th>sin_#0</th>\n",
+       "      <th>cos_#0</th>\n",
+       "      <th>sin_#1</th>\n",
+       "      <th>cos_#1</th>\n",
+       "      <th>sin_#2</th>\n",
+       "      <th>cos_#2</th>\n",
+       "      <th>sin_#3</th>\n",
+       "      <th>cos_#3</th>\n",
+       "      <th>sin_#4</th>\n",
+       "      <th>cos_#4</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>item_id</th>\n",
+       "      <th>timestamp</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
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+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
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+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
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+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
+       "      <th>1979-01-31</th>\n",
+       "      <td>1149.8700</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
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+       "      <td>0.000000</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1979-02-28</th>\n",
+       "      <td>1053.8002</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>6.123234e-17</td>\n",
+       "      <td>1.224647e-16</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1979-03-31</th>\n",
+       "      <td>1388.8798</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.866025</td>\n",
+       "      <td>5.000000e-01</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>1.224647e-16</td>\n",
+       "      <td>-1.000000e+00</td>\n",
+       "      <td>-2.449294e-16</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1979-04-30</th>\n",
+       "      <td>1783.3702</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000000e+00</td>\n",
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+       "      <td>1.000000</td>\n",
+       "      <td>6.123234e-17</td>\n",
+       "      <td>1.224647e-16</td>\n",
+       "      <td>-1.0</td>\n",
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+       "      <td>-1.836970e-16</td>\n",
+       "      <td>3.673940e-16</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-2.449294e-16</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1979-05-31</th>\n",
+       "      <td>1921.0252</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.224647e-16</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.866025</td>\n",
+       "      <td>-5.000000e-01</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>-2.449294e-16</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>-4.898587e-16</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 29 columns</p>\n",
+       "</div>\n",
+       "    <div class=\"colab-df-buttons\">\n",
+       "\n",
+       "  <div class=\"colab-df-container\">\n",
+       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-99cec216-cf7f-44bf-ae5a-72a21d117994')\"\n",
+       "            title=\"Convert this dataframe to an interactive table.\"\n",
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+       "\n",
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+       "  </svg>\n",
+       "    </button>\n",
+       "\n",
+       "  <style>\n",
+       "    .colab-df-container {\n",
+       "      display:flex;\n",
+       "      gap: 12px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert {\n",
+       "      background-color: #E8F0FE;\n",
+       "      border: none;\n",
+       "      border-radius: 50%;\n",
+       "      cursor: pointer;\n",
+       "      display: none;\n",
+       "      fill: #1967D2;\n",
+       "      height: 32px;\n",
+       "      padding: 0 0 0 0;\n",
+       "      width: 32px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert:hover {\n",
+       "      background-color: #E2EBFA;\n",
+       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "      fill: #174EA6;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-buttons div {\n",
+       "      margin-bottom: 4px;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert {\n",
+       "      background-color: #3B4455;\n",
+       "      fill: #D2E3FC;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert:hover {\n",
+       "      background-color: #434B5C;\n",
+       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "      fill: #FFFFFF;\n",
+       "    }\n",
+       "  </style>\n",
+       "\n",
+       "    <script>\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#df-99cec216-cf7f-44bf-ae5a-72a21d117994 button.colab-df-convert');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      async function convertToInteractive(key) {\n",
+       "        const element = document.querySelector('#df-99cec216-cf7f-44bf-ae5a-72a21d117994');\n",
+       "        const dataTable =\n",
+       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+       "                                                    [key], {});\n",
+       "        if (!dataTable) return;\n",
+       "\n",
+       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+       "          + ' to learn more about interactive tables.';\n",
+       "        element.innerHTML = '';\n",
+       "        dataTable['output_type'] = 'display_data';\n",
+       "        await google.colab.output.renderOutput(dataTable, element);\n",
+       "        const docLink = document.createElement('div');\n",
+       "        docLink.innerHTML = docLinkHtml;\n",
+       "        element.appendChild(docLink);\n",
+       "      }\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "\n",
+       "    <div id=\"df-7fe1f8e8-4e45-46b1-9769-44b88ccd2a71\">\n",
+       "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7fe1f8e8-4e45-46b1-9769-44b88ccd2a71')\"\n",
+       "                title=\"Suggest charts\"\n",
+       "                style=\"display:none;\">\n",
+       "\n",
+       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "     width=\"24px\">\n",
+       "    <g>\n",
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+       "    </g>\n",
+       "</svg>\n",
+       "      </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
+       "      --hover-fill-color: #174EA6;\n",
+       "      --disabled-fill-color: #AAA;\n",
+       "      --disabled-bg-color: #DDD;\n",
+       "  }\n",
+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
+       "      --hover-bg-color: #434B5C;\n",
+       "      --hover-fill-color: #FFFFFF;\n",
+       "      --disabled-bg-color: #3B4455;\n",
+       "      --disabled-fill-color: #666;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart {\n",
+       "    background-color: var(--bg-color);\n",
+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
+       "    display: none;\n",
+       "    fill: var(--fill-color);\n",
+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    30% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "      <script>\n",
+       "        async function quickchart(key) {\n",
+       "          const quickchartButtonEl =\n",
+       "            document.querySelector('#' + key + ' button');\n",
+       "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "          try {\n",
+       "            const charts = await google.colab.kernel.invokeFunction(\n",
+       "                'suggestCharts', [key], {});\n",
+       "          } catch (error) {\n",
+       "            console.error('Error during call to suggestCharts:', error);\n",
+       "          }\n",
+       "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "        }\n",
+       "        (() => {\n",
+       "          let quickchartButtonEl =\n",
+       "            document.querySelector('#df-7fe1f8e8-4e45-46b1-9769-44b88ccd2a71 button');\n",
+       "          quickchartButtonEl.style.display =\n",
+       "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "        })();\n",
+       "      </script>\n",
+       "    </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
       ],
-      "source": [
-        "from tabpfn_time_series.plot import plot_pred_and_actual_ts\n",
-        "\n",
-        "plot_pred_and_actual_ts(\n",
-        "    train=train_tsdf,\n",
-        "    test=test_tsdf_ground_truth,\n",
-        "    pred=pred,\n",
-        ")"
+      "text/plain": [
+       "                       target  running_index  year  second_of_minute_sin  \\\n",
+       "item_id timestamp                                                          \n",
+       "0       1979-01-31  1149.8700              0  1979                   0.0   \n",
+       "        1979-02-28  1053.8002              1  1979                   0.0   \n",
+       "        1979-03-31  1388.8798              2  1979                   0.0   \n",
+       "        1979-04-30  1783.3702              3  1979                   0.0   \n",
+       "        1979-05-31  1921.0252              4  1979                   0.0   \n",
+       "\n",
+       "                    second_of_minute_cos  minute_of_hour_sin  \\\n",
+       "item_id timestamp                                              \n",
+       "0       1979-01-31                   1.0                 0.0   \n",
+       "        1979-02-28                   1.0                 0.0   \n",
+       "        1979-03-31                   1.0                 0.0   \n",
+       "        1979-04-30                   1.0                 0.0   \n",
+       "        1979-05-31                   1.0                 0.0   \n",
+       "\n",
+       "                    minute_of_hour_cos  hour_of_day_sin  hour_of_day_cos  \\\n",
+       "item_id timestamp                                                          \n",
+       "0       1979-01-31                 1.0              0.0              1.0   \n",
+       "        1979-02-28                 1.0              0.0              1.0   \n",
+       "        1979-03-31                 1.0              0.0              1.0   \n",
+       "        1979-04-30                 1.0              0.0              1.0   \n",
+       "        1979-05-31                 1.0              0.0              1.0   \n",
+       "\n",
+       "                    day_of_week_sin  ...    sin_#0        cos_#0  \\\n",
+       "item_id timestamp                    ...                           \n",
+       "0       1979-01-31     8.660254e-01  ...  0.000000  1.000000e+00   \n",
+       "        1979-02-28     8.660254e-01  ...  0.500000  8.660254e-01   \n",
+       "        1979-03-31    -8.660254e-01  ...  0.866025  5.000000e-01   \n",
+       "        1979-04-30     0.000000e+00  ...  1.000000  6.123234e-17   \n",
+       "        1979-05-31     1.224647e-16  ...  0.866025 -5.000000e-01   \n",
+       "\n",
+       "                          sin_#1  cos_#1        sin_#2        cos_#2  \\\n",
+       "item_id timestamp                                                      \n",
+       "0       1979-01-31  0.000000e+00     1.0  0.000000e+00  1.000000e+00   \n",
+       "        1979-02-28  8.660254e-01     0.5  1.000000e+00  6.123234e-17   \n",
+       "        1979-03-31  8.660254e-01    -0.5  1.224647e-16 -1.000000e+00   \n",
+       "        1979-04-30  1.224647e-16    -1.0 -1.000000e+00 -1.836970e-16   \n",
+       "        1979-05-31 -8.660254e-01    -0.5 -2.449294e-16  1.000000e+00   \n",
+       "\n",
+       "                          sin_#3  cos_#3        sin_#4  cos_#4  \n",
+       "item_id timestamp                                               \n",
+       "0       1979-01-31  0.000000e+00     1.0  0.000000e+00     1.0  \n",
+       "        1979-02-28  1.224647e-16    -1.0  8.660254e-01    -0.5  \n",
+       "        1979-03-31 -2.449294e-16     1.0 -8.660254e-01    -0.5  \n",
+       "        1979-04-30  3.673940e-16    -1.0 -2.449294e-16     1.0  \n",
+       "        1979-05-31 -4.898587e-16     1.0  8.660254e-01    -0.5  \n",
+       "\n",
+       "[5 rows x 29 columns]"
       ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_tsdf.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "yKaNq3RAKMH9",
+    "outputId": "73791141-2b67-4019-bf3d-d4bf1bde5738"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 10,
-      "metadata": {
-        "id": "_EJU0ILwHS_5",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 237
-        },
-        "outputId": "96bb92f7-51e5-4dea-a90d-2687652c1c71"
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "type": "dataframe",
+       "variable_name": "test_tsdf"
       },
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "                         target          0.1          0.2          0.3  \\\n",
-              "item_id timestamp                                                        \n",
-              "0       1992-08-31  6429.405762  6035.002930  6181.089355  6277.288086   \n",
-              "        1992-09-30  4152.457520  3882.526855  3975.224365  4042.564697   \n",
-              "        1992-10-31  3016.685791  2787.193359  2869.374023  2925.949463   \n",
-              "        1992-11-30  1970.703613  1770.288208  1839.468140  1888.747070   \n",
-              "        1992-12-31  2334.847168  2095.349854  2180.212891  2239.671631   \n",
-              "\n",
-              "                            0.4          0.5          0.6          0.7  \\\n",
-              "item_id timestamp                                                        \n",
-              "0       1992-08-31  6355.530273  6429.405762  6507.368652  6598.672852   \n",
-              "        1992-09-30  4099.373535  4152.457520  4206.895508  4267.668945   \n",
-              "        1992-10-31  2973.139160  3016.685791  3059.930908  3108.218262   \n",
-              "        1992-11-30  1931.135254  1970.703613  2011.075439  2055.861328   \n",
-              "        1992-12-31  2289.326172  2334.847168  2379.584961  2426.927002   \n",
-              "\n",
-              "                            0.8          0.9  \n",
-              "item_id timestamp                             \n",
-              "0       1992-08-31  6720.195312  6920.027832  \n",
-              "        1992-09-30  4346.391113  4473.317871  \n",
-              "        1992-10-31  3167.230713  3256.193604  \n",
-              "        1992-11-30  2110.589111  2191.478760  \n",
-              "        1992-12-31  2482.097412  2556.839600  "
-            ],
-            "text/html": [
-              "\n",
-              "  <div id=\"df-93509c66-ff2e-4b0c-b2f4-2496c0c62bbd\" class=\"colab-df-container\">\n",
-              "    <div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
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-              "    <tr>\n",
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-              "      <th>timestamp</th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
-              "      <th>1992-08-31</th>\n",
-              "      <td>6429.405762</td>\n",
-              "      <td>6035.002930</td>\n",
-              "      <td>6181.089355</td>\n",
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-              "    <tr>\n",
-              "      <th>1992-09-30</th>\n",
-              "      <td>4152.457520</td>\n",
-              "      <td>3882.526855</td>\n",
-              "      <td>3975.224365</td>\n",
-              "      <td>4042.564697</td>\n",
-              "      <td>4099.373535</td>\n",
-              "      <td>4152.457520</td>\n",
-              "      <td>4206.895508</td>\n",
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-              "      <td>4346.391113</td>\n",
-              "      <td>4473.317871</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1992-10-31</th>\n",
-              "      <td>3016.685791</td>\n",
-              "      <td>2787.193359</td>\n",
-              "      <td>2869.374023</td>\n",
-              "      <td>2925.949463</td>\n",
-              "      <td>2973.139160</td>\n",
-              "      <td>3016.685791</td>\n",
-              "      <td>3059.930908</td>\n",
-              "      <td>3108.218262</td>\n",
-              "      <td>3167.230713</td>\n",
-              "      <td>3256.193604</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1992-11-30</th>\n",
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-              "      <td>1770.288208</td>\n",
-              "      <td>1839.468140</td>\n",
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-              "      <td>1970.703613</td>\n",
-              "      <td>2011.075439</td>\n",
-              "      <td>2055.861328</td>\n",
-              "      <td>2110.589111</td>\n",
-              "      <td>2191.478760</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1992-12-31</th>\n",
-              "      <td>2334.847168</td>\n",
-              "      <td>2095.349854</td>\n",
-              "      <td>2180.212891</td>\n",
-              "      <td>2239.671631</td>\n",
-              "      <td>2289.326172</td>\n",
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-              "        if (!dataTable) return;\n",
-              "\n",
-              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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-              "    fill: var(--button-hover-fill-color);\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart-complete:disabled,\n",
-              "  .colab-df-quickchart-complete:disabled:hover {\n",
-              "    background-color: var(--disabled-bg-color);\n",
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-              "    box-shadow: none;\n",
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-              "  .colab-df-spinner {\n",
-              "    border: 2px solid var(--fill-color);\n",
-              "    border-color: transparent;\n",
-              "    border-bottom-color: var(--fill-color);\n",
-              "    animation:\n",
-              "      spin 1s steps(1) infinite;\n",
-              "  }\n",
-              "\n",
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-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "      border-left-color: var(--fill-color);\n",
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-              "\n",
-              "      <script>\n",
-              "        async function quickchart(key) {\n",
-              "          const quickchartButtonEl =\n",
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-              "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
-              "          try {\n",
-              "            const charts = await google.colab.kernel.invokeFunction(\n",
-              "                'suggestCharts', [key], {});\n",
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-              "            console.error('Error during call to suggestCharts:', error);\n",
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-              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
-              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
-              "        }\n",
-              "        (() => {\n",
-              "          let quickchartButtonEl =\n",
-              "            document.querySelector('#df-49ab1a91-419e-49b1-908d-854823a1286f button');\n",
-              "          quickchartButtonEl.style.display =\n",
-              "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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-            }
-          },
-          "metadata": {},
-          "execution_count": 10
-        }
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+       "      <td>1992</td>\n",
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+       "      <td>5.000000e-01</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
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+       "      <td>1.0</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
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+       "      <td>1992</td>\n",
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+       "      <td>1.0</td>\n",
+       "      <td>1.224647e-16</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>8.660254e-01</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>0.5</td>\n",
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+       "      <td>9.314124e-15</td>\n",
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+       "      <td>-1.0</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 29 columns</p>\n",
+       "</div>\n",
+       "    <div class=\"colab-df-buttons\">\n",
+       "\n",
+       "  <div class=\"colab-df-container\">\n",
+       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-80d21b08-9078-44d7-b5b6-5046e14b7c8a')\"\n",
+       "            title=\"Convert this dataframe to an interactive table.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+       "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+       "  </svg>\n",
+       "    </button>\n",
+       "\n",
+       "  <style>\n",
+       "    .colab-df-container {\n",
+       "      display:flex;\n",
+       "      gap: 12px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert {\n",
+       "      background-color: #E8F0FE;\n",
+       "      border: none;\n",
+       "      border-radius: 50%;\n",
+       "      cursor: pointer;\n",
+       "      display: none;\n",
+       "      fill: #1967D2;\n",
+       "      height: 32px;\n",
+       "      padding: 0 0 0 0;\n",
+       "      width: 32px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert:hover {\n",
+       "      background-color: #E2EBFA;\n",
+       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "      fill: #174EA6;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-buttons div {\n",
+       "      margin-bottom: 4px;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert {\n",
+       "      background-color: #3B4455;\n",
+       "      fill: #D2E3FC;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert:hover {\n",
+       "      background-color: #434B5C;\n",
+       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "      fill: #FFFFFF;\n",
+       "    }\n",
+       "  </style>\n",
+       "\n",
+       "    <script>\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#df-80d21b08-9078-44d7-b5b6-5046e14b7c8a button.colab-df-convert');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      async function convertToInteractive(key) {\n",
+       "        const element = document.querySelector('#df-80d21b08-9078-44d7-b5b6-5046e14b7c8a');\n",
+       "        const dataTable =\n",
+       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+       "                                                    [key], {});\n",
+       "        if (!dataTable) return;\n",
+       "\n",
+       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+       "          + ' to learn more about interactive tables.';\n",
+       "        element.innerHTML = '';\n",
+       "        dataTable['output_type'] = 'display_data';\n",
+       "        await google.colab.output.renderOutput(dataTable, element);\n",
+       "        const docLink = document.createElement('div');\n",
+       "        docLink.innerHTML = docLinkHtml;\n",
+       "        element.appendChild(docLink);\n",
+       "      }\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "\n",
+       "    <div id=\"df-628d6697-813b-467d-b311-55143ccd38c1\">\n",
+       "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-628d6697-813b-467d-b311-55143ccd38c1')\"\n",
+       "                title=\"Suggest charts\"\n",
+       "                style=\"display:none;\">\n",
+       "\n",
+       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "     width=\"24px\">\n",
+       "    <g>\n",
+       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+       "    </g>\n",
+       "</svg>\n",
+       "      </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
+       "      --hover-fill-color: #174EA6;\n",
+       "      --disabled-fill-color: #AAA;\n",
+       "      --disabled-bg-color: #DDD;\n",
+       "  }\n",
+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
+       "      --hover-bg-color: #434B5C;\n",
+       "      --hover-fill-color: #FFFFFF;\n",
+       "      --disabled-bg-color: #3B4455;\n",
+       "      --disabled-fill-color: #666;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart {\n",
+       "    background-color: var(--bg-color);\n",
+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
+       "    display: none;\n",
+       "    fill: var(--fill-color);\n",
+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    30% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "      <script>\n",
+       "        async function quickchart(key) {\n",
+       "          const quickchartButtonEl =\n",
+       "            document.querySelector('#' + key + ' button');\n",
+       "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "          try {\n",
+       "            const charts = await google.colab.kernel.invokeFunction(\n",
+       "                'suggestCharts', [key], {});\n",
+       "          } catch (error) {\n",
+       "            console.error('Error during call to suggestCharts:', error);\n",
+       "          }\n",
+       "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "        }\n",
+       "        (() => {\n",
+       "          let quickchartButtonEl =\n",
+       "            document.querySelector('#df-628d6697-813b-467d-b311-55143ccd38c1 button');\n",
+       "          quickchartButtonEl.style.display =\n",
+       "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "        })();\n",
+       "      </script>\n",
+       "    </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
       ],
-      "source": [
-        "pred.head()"
+      "text/plain": [
+       "                    target  running_index  year  second_of_minute_sin  \\\n",
+       "item_id timestamp                                                       \n",
+       "0       1992-08-31     NaN            163  1992                   0.0   \n",
+       "        1992-09-30     NaN            164  1992                   0.0   \n",
+       "        1992-10-31     NaN            165  1992                   0.0   \n",
+       "        1992-11-30     NaN            166  1992                   0.0   \n",
+       "        1992-12-31     NaN            167  1992                   0.0   \n",
+       "\n",
+       "                    second_of_minute_cos  minute_of_hour_sin  \\\n",
+       "item_id timestamp                                              \n",
+       "0       1992-08-31                   1.0                 0.0   \n",
+       "        1992-09-30                   1.0                 0.0   \n",
+       "        1992-10-31                   1.0                 0.0   \n",
+       "        1992-11-30                   1.0                 0.0   \n",
+       "        1992-12-31                   1.0                 0.0   \n",
+       "\n",
+       "                    minute_of_hour_cos  hour_of_day_sin  hour_of_day_cos  \\\n",
+       "item_id timestamp                                                          \n",
+       "0       1992-08-31                 1.0              0.0              1.0   \n",
+       "        1992-09-30                 1.0              0.0              1.0   \n",
+       "        1992-10-31                 1.0              0.0              1.0   \n",
+       "        1992-11-30                 1.0              0.0              1.0   \n",
+       "        1992-12-31                 1.0              0.0              1.0   \n",
+       "\n",
+       "                    day_of_week_sin  ...    sin_#0        cos_#0  \\\n",
+       "item_id timestamp                    ...                           \n",
+       "0       1992-08-31     0.000000e+00  ... -0.500000 -8.660254e-01   \n",
+       "        1992-09-30     8.660254e-01  ... -0.866025 -5.000000e-01   \n",
+       "        1992-10-31    -8.660254e-01  ... -1.000000 -1.224956e-14   \n",
+       "        1992-11-30     0.000000e+00  ... -0.866025  5.000000e-01   \n",
+       "        1992-12-31     1.224647e-16  ... -0.500000  8.660254e-01   \n",
+       "\n",
+       "                          sin_#1  cos_#1        sin_#2        cos_#2  \\\n",
+       "item_id timestamp                                                      \n",
+       "0       1992-08-31  8.660254e-01     0.5 -1.000000e+00 -2.596808e-14   \n",
+       "        1992-09-30  8.660254e-01    -0.5 -3.135839e-14  1.000000e+00   \n",
+       "        1992-10-31  2.449913e-14    -1.0  1.000000e+00  3.674869e-14   \n",
+       "        1992-11-30 -8.660254e-01    -0.5 -1.470443e-14 -1.000000e+00   \n",
+       "        1992-12-31 -8.660254e-01     0.5 -1.000000e+00  9.314124e-15   \n",
+       "\n",
+       "                          sin_#3  cos_#3        sin_#4  cos_#4  \n",
+       "item_id timestamp                                               \n",
+       "0       1992-08-31  5.193617e-14    -1.0  8.660254e-01    -0.5  \n",
+       "        1992-09-30 -6.271677e-14     1.0 -8.660254e-01    -0.5  \n",
+       "        1992-10-31  7.349738e-14    -1.0 -4.899825e-14     1.0  \n",
+       "        1992-11-30  2.940885e-14     1.0  8.660254e-01    -0.5  \n",
+       "        1992-12-31 -1.862825e-14    -1.0 -8.660254e-01    -0.5  \n",
+       "\n",
+       "[5 rows x 29 columns]"
       ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_tsdf.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "CqNGS6a0HS_5"
+   },
+   "source": [
+    "## Prediction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "iAh9dvY5HS_5"
+   },
+   "source": [
+    "Now, let's perform prediction.\n",
+    "\n",
+    "We provide two options, `TabPFNMode.LOCAL` and `TabPFNMode.CLIENT`, as the backend for TabPFN.\n",
+    "\n",
+    "- `TabPFNMode.LOCAL` uses your local machine to run TabPFN.\n",
+    "- `TabPFNMode.CLIENT` uses TabPFN's inference service provided by [tabpfn-client](https://github.com/automl/tabpfn-client)\n",
+    "\n",
+    "For this demo, we'll use `TabPFNMode.CLIENT` to perform prediction. If you have not used the client before, you'll be prompted to create an account.\n",
+    "\n",
+    "Note: if your machine doesn't have a GPU, using `TabPFNMode.CLIENT` is recommended -- much faster 😉.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 721
+    },
+    "collapsed": true,
+    "id": "v_gi5gDFHS_5",
+    "jupyter": {
+     "outputs_hidden": true
     },
+    "outputId": "7c0a617b-7fbb-4534-c392-92ea999c146a"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "source": [
-        "# Using TabPFN as a Base Model for Causal Inference <a name=\"causal\"></a>\n",
-        "\n",
-        "Often decisions hinge on **what changes because of an action**, not just what correlates with it. Causal effect estimation turns data into these counterfactual answers—e.g., _If we treat someone like xxx, how much does the expected outcome change?_\n",
-        "\n",
-        "Below we show how to use TabPFN to estimation the effect of these causal intervations.\n",
-        "\n",
-        "*In depth explanation:*\n",
-        "\n",
-        "To estimate it most methods build two ingredients: an **outcome model** (predict yyy under T\\=1T{=}1T\\=1 and T\\=0T{=}0T\\=0) and often a **propensity model** (estimate Pr⁡(T\\=1∣X)\\\\Pr(T{=}1\\\\mid X)Pr(T\\=1∣X)) to reduce selection bias. You can treat this as AutoML, or take a strong default: **TabPFN**, a pretrained transformer for tabular data that frequently works **out of the box** as the base learner inside CATE pipelines—cutting tuning time while staying competitive.\n",
-        "\n",
-        "\n",
-        "Many causal inference methods require selection of base models to fit either propensity or outcome models. While recent studies have framed this as an AutoML model selection problem ([Vandershueren et al, 2025](https://openreview.net/forum?id=QbOoz74GNO)), other studies ([Zhang et al, 2025](https://arxiv.org/pdf/2505.20003)) have shown TabPFN to be a strong choice \"out of the box\" in various CATE estimation methods. In parallel, there is a growing body of research pre-training PFNs specifically for the conditional average treatment effect (CATE) estimation task ([Robertson et al.](https://arxiv.org/pdf/2506.06039)), defined as:\n",
-        "\n",
-        "$$CATE : \\tau = E[y | do(1), x] - E[y | do(0), x]$$\n",
-        "\n",
-        "\n",
-        "**NOTE:** Current CATE estimators only work when *unconfoundedness* $(Y_0, Y_1) \\perp \\kern-1.8ex \\perp T$ $|$ $X$ is satisfied. We are working on pre-training a foundation model called \"Do-PFN\" ([Robertson et al.](https://arxiv.org/pdf/2506.06039)) that is designed to offer strong out-of-the box performance in **all** identifiable scenarios (including front-door and instrumental variable settings)."
-      ],
-      "metadata": {
-        "id": "0bBYgouXsh2A"
-      }
+     "ename": "AttributeError",
+     "evalue": "'list' object has no attribute 'exists'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "\u001b[0;32m/tmp/ipython-input-1981978721.py\u001b[0m in \u001b[0;36m<cell line: 0>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mtabpfn_time_series\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mTabPFNMode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mTabPFNTimeSeriesPredictor\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m predictor = TabPFNTimeSeriesPredictor(\n\u001b[0m\u001b[1;32m      4\u001b[0m     \u001b[0mtabpfn_mode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mTabPFNMode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLOCAL\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0;31m# adapt this to TabPFNMode.CLIENT if using API\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m )\n",
+      "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/tabpfn_time_series/predictor.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, tabpfn_mode, config)\u001b[0m\n\u001b[1;32m     37\u001b[0m         }\n\u001b[1;32m     38\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtabpfn_mode\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtabpfn_mode\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 39\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtabpfn_worker\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mworker_mapping\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mtabpfn_mode\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     40\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     41\u001b[0m     def predict(\n",
+      "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/tabpfn_time_series/predictor.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     33\u001b[0m         worker_mapping = {\n\u001b[1;32m     34\u001b[0m             \u001b[0mTabPFNMode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCLIENT\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mlambda\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mTabPFNClient\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 35\u001b[0;31m             \u001b[0mTabPFNMode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLOCAL\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mlambda\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mLocalTabPFN\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     36\u001b[0m             \u001b[0mTabPFNMode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mMOCK\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mlambda\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mMockTabPFN\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     37\u001b[0m         }\n",
+      "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/tabpfn_time_series/tabpfn_worker.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, config, num_workers_per_gpu)\u001b[0m\n\u001b[1;32m    240\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    241\u001b[0m         \u001b[0;31m# Download the model specified in the config\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 242\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_download_model\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"tabpfn_internal\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"model_path\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    243\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    244\u001b[0m     def predict(\n",
+      "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/tabpfn_time_series/tabpfn_worker.py\u001b[0m in \u001b[0;36m_download_model\u001b[0;34m(model_name)\u001b[0m\n\u001b[1;32m    288\u001b[0m         )\n\u001b[1;32m    289\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 290\u001b[0;31m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mmodel_path\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexists\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    291\u001b[0m             download_model(\n\u001b[1;32m    292\u001b[0m                 \u001b[0mto\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmodel_path\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mAttributeError\u001b[0m: 'list' object has no attribute 'exists'"
+     ]
+    }
+   ],
+   "source": [
+    "from tabpfn_time_series import TabPFNMode, TabPFNTimeSeriesPredictor\n",
+    "\n",
+    "predictor = TabPFNTimeSeriesPredictor(\n",
+    "    tabpfn_mode=TabPFNMode.LOCAL,  # adapt this to TabPFNMode.CLIENT if using API\n",
+    ")\n",
+    "\n",
+    "pred = predictor.predict(train_tsdf, test_tsdf)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "toHiW8LeHS_5"
+   },
+   "source": [
+    "## Visualize the Results\n",
+    "\n",
+    "Let's visualize the forecasting results.\n",
+    "\n",
+    "Also, note that we provide both **point prediction** and **quantile prediction**."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "FCxt23reHS_5"
+   },
+   "outputs": [],
+   "source": [
+    "from tabpfn_time_series.plot import plot_pred_and_actual_ts\n",
+    "\n",
+    "plot_pred_and_actual_ts(\n",
+    "    train=train_tsdf,\n",
+    "    test=test_tsdf_ground_truth,\n",
+    "    pred=pred,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "_EJU0ILwHS_5"
+   },
+   "outputs": [],
+   "source": [
+    "pred.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "0bBYgouXsh2A"
+   },
+   "source": [
+    "# Using TabPFN as a Base Model for Causal Inference <a name=\"causal\"></a>\n",
+    "\n",
+    "Often decisions hinge on **what changes because of an action**, not just what correlates with it. Causal effect estimation turns data into these counterfactual answers—e.g., _If we treat ($T=1$) someone like $X$, how much does the expected outcome change?_\n",
+    "\n",
+    "Below we show how to use TabPFN to estimation the effect of these causal intervations.\n",
+    "\n",
+    "*In depth explanation:*\n",
+    "\n",
+    "To estimate it most methods build two ingredients: an **outcome model** (predict $y$ under $T=1$ and $T=0$) and often a **propensity model** (estimate $Pr⁡(T=1∣X)$) to reduce selection bias. You can treat this as AutoML, or take a strong default: **TabPFN**, a pretrained transformer for tabular data that frequently works **out of the box** as the base learner inside CATE pipelines—cutting tuning time while staying competitive.\n",
+    "\n",
+    "\n",
+    "Many causal inference methods require selection of base models to fit either propensity or outcome models. While recent studies have framed this as an AutoML model selection problem ([Vandershueren et al, 2025](https://openreview.net/forum?id=QbOoz74GNO)), other studies ([Zhang et al, 2025](https://arxiv.org/pdf/2505.20003)) have shown TabPFN to be a strong choice \"out of the box\" in various CATE estimation methods. In parallel, there is a growing body of research pre-training PFNs specifically for the conditional average treatment effect (CATE) estimation task ([Robertson et al.](https://arxiv.org/pdf/2506.06039)), defined as:\n",
+    "\n",
+    "$$CATE : \\tau = E[y | do(1), x] - E[y | do(0), x]$$\n",
+    "\n",
+    "\n",
+    "**NOTE:** Current CATE estimators only work when *unconfoundedness* $(Y_0, Y_1) \\perp \\kern-1.8ex \\perp T$ $|$ $X$ is satisfied. We are working on pre-training a foundation model called \"Do-PFN\" ([Robertson et al.](https://arxiv.org/pdf/2506.06039)) that is designed to offer strong out-of-the box performance in **all** identifiable scenarios (including front-door and instrumental variable settings)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "yn_gs71ksBfH"
+   },
+   "source": [
+    "### 1) Install the required packages\n",
+    "\n",
+    "Note: you will need to restart the notebook (Runtime -> Restart Session)\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "QNU2S_pwrSq1",
+    "outputId": "94a9eebb-71a1-487f-b5b2-df81930d1182"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "source": [
-        "### 1) Install the required packages\n",
-        "\n",
-        "Note: you will need to restart the notebook (Runtime -> Restart Session)\n",
-        "\n",
-        "\n",
-        "\n"
-      ],
-      "metadata": {
-        "id": "yn_gs71ksBfH"
-      }
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: tabpfn in /usr/local/lib/python3.12/dist-packages (6.0.3)\n",
+      "Requirement already satisfied: torch<3,>=2.1 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (2.8.0+cu126)\n",
+      "Requirement already satisfied: numpy<3,>=1.21.6 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (2.0.2)\n",
+      "Requirement already satisfied: scikit-learn<1.8,>=1.2.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (1.6.1)\n",
+      "Requirement already satisfied: typing_extensions>=4.12.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (4.15.0)\n",
+      "Requirement already satisfied: scipy<2,>=1.11.1 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (1.16.3)\n",
+      "Requirement already satisfied: pandas<3,>=1.4.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (2.2.2)\n",
+      "Requirement already satisfied: einops<0.9,>=0.2.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (0.8.1)\n",
+      "Requirement already satisfied: huggingface-hub<2,>=0.25.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (0.36.0)\n",
+      "Requirement already satisfied: pydantic>=2.8.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (2.11.10)\n",
+      "Requirement already satisfied: pydantic-settings>=2.10.1 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (2.11.0)\n",
+      "Requirement already satisfied: eval-type-backport>=0.2.2 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (0.2.2)\n",
+      "Requirement already satisfied: joblib>=1.2.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (1.5.2)\n",
+      "Requirement already satisfied: tabpfn-common-utils>=0.1.8 in /usr/local/lib/python3.12/dist-packages (from tabpfn-common-utils[telemetry-interactive]>=0.1.8->tabpfn) (0.2.2)\n",
+      "Requirement already satisfied: kditransform>=1.2 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (1.2.0)\n",
+      "Requirement already satisfied: filelock in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (3.20.0)\n",
+      "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (2025.3.0)\n",
+      "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (25.0)\n",
+      "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (6.0.3)\n",
+      "Requirement already satisfied: requests in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (2.32.5)\n",
+      "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (4.67.1)\n",
+      "Requirement already satisfied: hf-xet<2.0.0,>=1.1.3 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (1.2.0)\n",
+      "Requirement already satisfied: numba>=0.48 in /usr/local/lib/python3.12/dist-packages (from kditransform>=1.2->tabpfn) (0.60.0)\n",
+      "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.12/dist-packages (from pandas<3,>=1.4.0->tabpfn) (2.9.0.post0)\n",
+      "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.12/dist-packages (from pandas<3,>=1.4.0->tabpfn) (2025.2)\n",
+      "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.12/dist-packages (from pandas<3,>=1.4.0->tabpfn) (2025.2)\n",
+      "Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.12/dist-packages (from pydantic>=2.8.0->tabpfn) (0.7.0)\n",
+      "Requirement already satisfied: pydantic-core==2.33.2 in /usr/local/lib/python3.12/dist-packages (from pydantic>=2.8.0->tabpfn) (2.33.2)\n",
+      "Requirement already satisfied: typing-inspection>=0.4.0 in /usr/local/lib/python3.12/dist-packages (from pydantic>=2.8.0->tabpfn) (0.4.2)\n",
+      "Requirement already satisfied: python-dotenv>=0.21.0 in /usr/local/lib/python3.12/dist-packages (from pydantic-settings>=2.10.1->tabpfn) (1.2.1)\n",
+      "Requirement already satisfied: threadpoolctl>=3.1.0 in /usr/local/lib/python3.12/dist-packages (from scikit-learn<1.8,>=1.2.0->tabpfn) (3.6.0)\n",
+      "Requirement already satisfied: platformdirs>=4.4.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn-common-utils>=0.1.8->tabpfn-common-utils[telemetry-interactive]>=0.1.8->tabpfn) (4.5.0)\n",
+      "Requirement already satisfied: posthog~=6.7 in /usr/local/lib/python3.12/dist-packages (from tabpfn-common-utils>=0.1.8->tabpfn-common-utils[telemetry-interactive]>=0.1.8->tabpfn) (6.8.0)\n",
+      "Requirement already satisfied: setuptools in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (75.2.0)\n",
+      "Requirement already satisfied: sympy>=1.13.3 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (1.13.3)\n",
+      "Requirement already satisfied: networkx in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (3.5)\n",
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+      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.6.77 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (12.6.77)\n",
+      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.6.80 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (12.6.80)\n",
+      "Requirement already satisfied: nvidia-cudnn-cu12==9.10.2.21 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (9.10.2.21)\n",
+      "Requirement already satisfied: nvidia-cublas-cu12==12.6.4.1 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (12.6.4.1)\n",
+      "Requirement already satisfied: nvidia-cufft-cu12==11.3.0.4 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (11.3.0.4)\n",
+      "Requirement already satisfied: nvidia-curand-cu12==10.3.7.77 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (10.3.7.77)\n",
+      "Requirement already satisfied: nvidia-cusolver-cu12==11.7.1.2 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (11.7.1.2)\n",
+      "Requirement already satisfied: nvidia-cusparse-cu12==12.5.4.2 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (12.5.4.2)\n",
+      "Requirement already satisfied: nvidia-cusparselt-cu12==0.7.1 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (0.7.1)\n",
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+      "Requirement already satisfied: nvidia-nvjitlink-cu12==12.6.85 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (12.6.85)\n",
+      "Requirement already satisfied: nvidia-cufile-cu12==1.11.1.6 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (1.11.1.6)\n",
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+      "Requirement already satisfied: distro>=1.5.0 in /usr/local/lib/python3.12/dist-packages (from posthog~=6.7->tabpfn-common-utils>=0.1.8->tabpfn-common-utils[telemetry-interactive]>=0.1.8->tabpfn) (1.9.0)\n",
+      "Requirement already satisfied: charset_normalizer<4,>=2 in /usr/local/lib/python3.12/dist-packages (from requests->huggingface-hub<2,>=0.25.0->tabpfn) (3.4.4)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.12/dist-packages (from requests->huggingface-hub<2,>=0.25.0->tabpfn) (3.11)\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.12/dist-packages (from requests->huggingface-hub<2,>=0.25.0->tabpfn) (2.5.0)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.12/dist-packages (from requests->huggingface-hub<2,>=0.25.0->tabpfn) (2025.10.5)\n",
+      "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.12/dist-packages (from sympy>=1.13.3->torch<3,>=2.1->tabpfn) (1.3.0)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.12/dist-packages (from jinja2->torch<3,>=2.1->tabpfn) (3.0.3)\n",
+      "Collecting econml\n",
+      "  Downloading econml-0.16.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (37 kB)\n",
+      "Requirement already satisfied: numpy in /usr/local/lib/python3.12/dist-packages (from econml) (2.0.2)\n",
+      "Requirement already satisfied: scipy>1.4.0 in /usr/local/lib/python3.12/dist-packages (from econml) (1.16.3)\n",
+      "Requirement already satisfied: scikit-learn<1.7,>=1.0 in /usr/local/lib/python3.12/dist-packages (from econml) (1.6.1)\n",
+      "Collecting sparse (from econml)\n",
+      "  Downloading sparse-0.17.0-py2.py3-none-any.whl.metadata (5.3 kB)\n",
+      "Requirement already satisfied: joblib>=0.13.0 in /usr/local/lib/python3.12/dist-packages (from econml) (1.5.2)\n",
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+      "Collecting shap<0.49.0,>=0.38.1 (from econml)\n",
+      "  Downloading shap-0.48.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (25 kB)\n",
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+      "Requirement already satisfied: tqdm>=4.27.0 in /usr/local/lib/python3.12/dist-packages (from shap<0.49.0,>=0.38.1->econml) (4.67.1)\n",
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+      "Requirement already satisfied: llvmlite<0.44,>=0.43.0dev0 in /usr/local/lib/python3.12/dist-packages (from numba>=0.54->shap<0.49.0,>=0.38.1->econml) (0.43.0)\n",
+      "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.12/dist-packages (from python-dateutil>=2.8.2->pandas>1.0->econml) (1.17.0)\n",
+      "Downloading econml-0.16.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.4 MB)\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.4/5.4 MB\u001b[0m \u001b[31m77.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hDownloading shap-0.48.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.0 MB)\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.0/1.0 MB\u001b[0m \u001b[31m62.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hDownloading sparse-0.17.0-py2.py3-none-any.whl (259 kB)\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m259.4/259.4 kB\u001b[0m \u001b[31m26.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hInstalling collected packages: sparse, shap, econml\n",
+      "  Attempting uninstall: shap\n",
+      "    Found existing installation: shap 0.49.1\n",
+      "    Uninstalling shap-0.49.1:\n",
+      "      Successfully uninstalled shap-0.49.1\n",
+      "Successfully installed econml-0.16.0 shap-0.48.0 sparse-0.17.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install tabpfn\n",
+    "!pip install econml\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "4wlBhyRpy1wy"
+   },
+   "source": [
+    "### 2) Generate a synthetic CATE dataset\n",
+    "\n",
+    "The dataset $D = (T, X, Y, \\tau)$ below represents an observed confounder scenario $G = \\{X \\rightarrow Y, T \\rightarrow Y, X \\rightarrow T\\}$ and thus satisfies the unconfoundedness assumption: $(Y_0, Y_1) \\perp \\kern-1.8ex \\perp T$ $|$ $X$. We divide the dataset into train and test splits $(D_{train}, D_{test})$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "pFK2RGwpzIWz",
+    "outputId": "8d0fe6aa-8080-41dc-b16f-ebc04bbdefea"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 8,
-      "metadata": {
-        "id": "QNU2S_pwrSq1",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "94a9eebb-71a1-487f-b5b2-df81930d1182"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
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-            "Requirement already satisfied: slicer==0.0.8 in /usr/local/lib/python3.12/dist-packages (from shap<0.49.0,>=0.38.1->econml) (0.0.8)\n",
-            "Requirement already satisfied: numba>=0.54 in /usr/local/lib/python3.12/dist-packages (from shap<0.49.0,>=0.38.1->econml) (0.60.0)\n",
-            "Requirement already satisfied: cloudpickle in /usr/local/lib/python3.12/dist-packages (from shap<0.49.0,>=0.38.1->econml) (3.1.1)\n",
-            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.12/dist-packages (from shap<0.49.0,>=0.38.1->econml) (4.15.0)\n",
-            "Requirement already satisfied: patsy>=0.5.6 in /usr/local/lib/python3.12/dist-packages (from statsmodels>=0.10->econml) (1.0.2)\n",
-            "Requirement already satisfied: llvmlite<0.44,>=0.43.0dev0 in /usr/local/lib/python3.12/dist-packages (from numba>=0.54->shap<0.49.0,>=0.38.1->econml) (0.43.0)\n",
-            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.12/dist-packages (from python-dateutil>=2.8.2->pandas>1.0->econml) (1.17.0)\n",
-            "Downloading econml-0.16.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.4 MB)\n",
-            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.4/5.4 MB\u001b[0m \u001b[31m77.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25hDownloading shap-0.48.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.0 MB)\n",
-            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.0/1.0 MB\u001b[0m \u001b[31m62.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25hDownloading sparse-0.17.0-py2.py3-none-any.whl (259 kB)\n",
-            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m259.4/259.4 kB\u001b[0m \u001b[31m26.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25hInstalling collected packages: sparse, shap, econml\n",
-            "  Attempting uninstall: shap\n",
-            "    Found existing installation: shap 0.49.1\n",
-            "    Uninstalling shap-0.49.1:\n",
-            "      Successfully uninstalled shap-0.49.1\n",
-            "Successfully installed econml-0.16.0 shap-0.48.0 sparse-0.17.0\n"
-          ]
-        }
-      ],
-      "source": [
-        "!pip install tabpfn\n",
-        "!pip install econml\n"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import networkx as nx\n",
+    "\n",
+    "edges = [[\"X\", \"Y\"], [\"T\", \"Y\"], [\"X\", \"T\"]]\n",
+    "graph = nx.DiGraph(edges)\n",
+    "nx.draw(graph, with_labels=True, node_size=2000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "gadFg7JusQ6l"
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "num_samples, num_features, train_test_split = 500, 5, 75\n",
+    "\n",
+    "noise_scale = 0.01\n",
+    "exogenous_scale = 0.1\n",
+    "heterogeneity_scale = 2\n",
+    "\n",
+    "X = np.random.normal(loc=0, scale=exogenous_scale, size=(num_samples, num_features)).astype(np.float32)\n",
+    "prop_eps = np.random.normal(loc=0, scale=noise_scale, size=(num_samples)).astype(np.float32)\n",
+    "Y_eps = np.random.normal(loc=0, scale=noise_scale, size=(num_samples)).astype(np.float32)\n",
+    "\n",
+    "w_X_Y = np.random.uniform(size=num_features)\n",
+    "w_X_T = np.random.uniform(size=num_features)\n",
+    "w_X_T_effect = np.random.uniform(size=num_features)\n",
+    "\n",
+    "T_0 = np.zeros(shape=num_samples).astype(np.float32)\n",
+    "T_1 = np.ones(shape=num_samples).astype(np.float32)\n",
+    "\n",
+    "base_X_Y = np.sum(w_X_Y * X, axis=1)\n",
+    "base_X_T = np.sum(w_X_T * X, axis=1)\n",
+    "heterogeneity_term = np.sum(w_X_T_effect * X, axis=1)\n",
+    "\n",
+    "propensity = np.sin(base_X_T) + prop_eps\n",
+    "T = (propensity > propensity.mean()).astype(np.float32)\n",
+    "\n",
+    "Y_0 = np.cos(base_X_Y) + np.sin(0.3 * T_0) + Y_eps\n",
+    "Y_1 = np.cos(base_X_Y) + np.sin(0.3 * T_1 + heterogeneity_scale * heterogeneity_term) + Y_eps\n",
+    "\n",
+    "Y = Y_0 * (1 - T) + Y_1 * T\n",
+    "tau = Y_1 - Y_0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "VnBaoFhLBiKq",
+    "outputId": "92c452fd-d8ca-45ec-daed-77f04730713a"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "source": [
-        "### 2) Generate a synthetic CATE dataset\n",
-        "\n",
-        "The dataset $D = (T, X, Y, \\tau)$ below represents an observed confounder scenario $G = \\{X \\rightarrow Y, T \\rightarrow Y, X \\rightarrow T\\}$ and thus satisfies the unconfoundedness assumption: $(Y_0, Y_1) \\perp \\kern-1.8ex \\perp T$ $|$ $X$. We divide the dataset into train and test splits $(D_{train}, D_{test})$."
-      ],
-      "metadata": {
-        "id": "4wlBhyRpy1wy"
-      }
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x300 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "df = pd.DataFrame({**{f\"X{i}\": X[:, i] for i in range(num_features)}, \"T\": T, \"Y\": Y, \"Y_0\": Y_0, \"Y_1\": Y_1, \"tau\": tau})\n",
+    "fig, axes = plt.subplots(ncols=2, figsize=(6, 3))\n",
+    "sns.scatterplot(data=df, x=\"X0\", y=\"tau\", hue=\"T\", ax=axes[0], edgecolor=\"black\", palette=\"Set1\")\n",
+    "sns.scatterplot(data=df, x=\"X1\", y=\"tau\", hue=\"T\", ax=axes[1], edgecolor=\"black\", palette=\"Set1\")\n",
+    "fig.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "3KJJwIwSySzk"
+   },
+   "outputs": [],
+   "source": [
+    "perm = np.random.permutation(num_samples)\n",
+    "train_idx, test_idx = perm[:train_test_split], perm[train_test_split:]\n",
+    "X_train, X_test = X[train_idx], X[test_idx]\n",
+    "Y_train, Y_test = Y[train_idx], Y[test_idx]\n",
+    "T_train, T_test = T[train_idx], T[test_idx]\n",
+    "tau_test = tau[test_idx]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "STYhNc224Zmz"
+   },
+   "source": [
+    "### Run CATE estimators with TabPFN as a base model\n",
+    "\n",
+    "We fit three CATE estimators to our synthetic datasets with different choices of base models\n",
+    "\n",
+    "\n",
+    "\n",
+    "*   `s_tabpfn`: TabPFN applied as an `SLearner`\n",
+    "*   `cfdml_tabpfn`: TabPFN applied as a propensity and outcome in `CausalForestDML`\n",
+    "*   `cfdml_default`: `CausalForestDML` with default propensity and outcome models\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "-3id6xmIrajj"
+   },
+   "outputs": [],
+   "source": [
+    "from econml.metalearners import SLearner\n",
+    "from econml.dml import CausalForestDML\n",
+    "from tabpfn import TabPFNClassifier, TabPFNRegressor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "xuZ1kxQP1ZN6",
+    "outputId": "8741fedd-5b6e-4900-d856-5774a3348399"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "source": [
-        "import networkx as nx\n",
-        "\n",
-        "edges = [[\"X\", \"Y\"], [\"T\", \"Y\"], [\"X\", \"T\"]]\n",
-        "graph = nx.DiGraph(edges)\n",
-        "nx.draw(graph, with_labels=True, node_size=2000)"
-      ],
-      "metadata": {
-        "id": "pFK2RGwpzIWz",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 0
-        },
-        "outputId": "8d0fe6aa-8080-41dc-b16f-ebc04bbdefea"
-      },
-      "execution_count": 9,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 640x480 with 1 Axes>"
-            ],
-            "image/png": 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1ra/SPL8bRSxglqbyvWYKpSMqWhGVaimifOW/jBAqSYOGXKdt27Zp2rRpxy/h+P3+03oMHACg8IYln6s6sdFyhNgpHYcl1asUrWHJ55qOghAUMIUyMsxHF5RyOuR0OtWnTx+tWrVKS5cu1b/+9S916tTJdDQACCulI516vn+8TvFJn0HD75ee7x/P6iSKRcBseUdFhHehjPrTX/C2bduqbdu2htIAQHhrXi9WQzs00PglP4TE1rdlSdd3aKDEuuZ24hDaAqbFRZcKmG5rRBl+YgSAgHJHSqOQ2Po+ttV9e7dGpqMghAVMoawdW0aRziD/W3uGIp2W6sSWMR0DAPA7pSOdGnN5vCzLUrB+d7J09IEPbHWjuAVMoYx0OtS4eng+z7pJ9Qo8/goAAlBi3Vi9fEWC6RiFMnZAAlvdKHYB1WLi68QowsDeQvWrnlLN614t8deVjj7LO75OjJHXBgD8s57Naujpvi7TMc7I031dcjdl5iSKX0AVyma1KpbIs7wDSYHPr6a1KpqOAQD4G/2T6mh0X9fRLWTTYf7BsYyj+7rUP6mO6TgIEwF1EyZci1WzMP1zA0Aw6Z9UR+WiIjT8gzT5/f6AvP3tsI6emRw7IIGVSZSogFqhbFi1XNiND4qKcKhh1XKmYwAATkHPZjX0vxvaBOTtb8uS6sRG6383tKFMosQFVHuLdDp0kauGnIH2t7SYOB2WesfV5EIOAASRxLqxmj2io65r30CWZLxYOqyjW9zXd2ig2SM6cgEHRlh+f2A9CyAjc78ufnWp6Rgl5rNh7eSqHWM6BgDgDKzdlqU7PkxXZtZhI1vgliXVjY3WmMvjKZIwKuCWxuLqxOj8GhWM/8RX3ByWdEHNCpRJAAhizesdXa0c1vlclY86ei3BKubvX8e+P5aPitAtnc9lVRIBIeBWKCXpf2szdfdUj+kYxe7Zy+J0WfPapmMAAIpATr5X0z079fayrfpqZ7acDkveIly2PPb5mtasoEFtz1YvVw2GlSNgBGShzMn3KunxeTqYW2A6SrEpHxWh1fd344sBAISgjMz9mrRymz7L2KncAp+ko3OHT2c03u8/3imf+jSvq6tb12NnCwEpIAulJD035zu9smhzQI5lKCzLkm7pfK7u7H6e6SgAgGJU4PVp056DWr/jgDbsOKD0zP36Zne28r0n/+YW6bTUpHoFxdeJUdNaFTV+9IPK+WmLUr9cVHLBgdMUsIUyJ9+rHi+kGjvoXFwcllS3UrRm3daR1UkACEMFXp8ys47oSL5Xufle5Xl9KuV0KCrSqTKRTtWJLfOH6R///e9/dcstt2jv3r2qWJG5xQhMAVsopaO35y777zIFbMAzYEmadlNbDlADAE7J1q1bdfbZZ2vatGnq06eP6TjACQV0oZSkJ2Z+o/FLfgiNVUq/X0fSpqu5M1OJiYlq0qSJmjRposaNGys6Otp0OgBAgGrSpInat2+vN954w3QU4IQCvlCGyta3w5KifYf11bNXSd58OZ1Oeb3e4++//vrr9dprrxlMCAAIVLfffrv+97//KTMzU1ZxzyUCzkDAzaH8s9KRTo25PF6WZSlY/wpZOvps1QlDO6lW9aqS9IcyKUnnnHOOgWQAgGDgdru1Y8cOffXVV6ajACcU8IVSOvqYq5evSDAdo1DGDkhQy3Oq6umnn/7L+5KSknTnnXcaSAUACAYdO3ZUmTJl9MUXX5iOApxQUBRKSerZrIae7usyHeOMPN3XJXfTGpKkK664Qo0bN5bD4ZBlWXI4HNqwYYMmTJigAD99AAAwpHTp0kpOTtasWbNMRwFOKGgKpST1T6qj0X1dR7eQTYf5B8cyju7rUv+kOsd/3el06qmnnpLP55Pf79d7772na665Rtdff70uu+wy7du3z1hmAEDgcrvdWrx4sX799VfTUYC/CPhLOScyc/0uDf8gTX6/PyAv6jiso2cmxw5IOL4y+Xt+v1+9evXSBRdcoNGjR0uSpk2bpqFDhyo6OlqTJk1S586dSzg1ACCQbd68WQ0bNtSnn36q3r17m44D/EFQFkpJWrc9S7dPSQ+429+WJdWNjdaYy+NPe9ZkZmamrr76aqWmpuree+/VQw89pMjIyGJKCgAINg0bNlS3bt00btw401GAPwjaQikdHSn0/NyNemPxD7IsGS2WDkvy+6XrOzbQ7d0anfFTcLxer55++mk9+OCDSkpK0uTJk9WgQYMiTgsACEbDhw/X9OnTtWXLFsYHIaAE1RnKPysd6dR9PZto6o1tVSc2Wg5Df7csS6oTG61pN7XVve4mhXqkotPp1H333aelS5dqz549io+P16RJk4owLQAgWLndbm3btk3fffed6SjAHwR1oTymeb1YzR7RUcM6n6vyURGSjpa84nSsvJaPitAtnc/V7BEdi/Rxiq1atVJ6erouvvhiXX311Ro4cKCys7OL7PMDAIJP586dFRUVxfggBJyg3vI+kZx8r6Z7durtZVv11c5sOR2WvEW4F37s8zWtWUGD2p6tXq4ahVqRPBWTJk3SzTffrMqVK2vy5Mlq3bp1sb4eACBw9ejRQ5I0e/Zsw0mA/xdyhfL3MjL3a9LKbfosY6dyC3ySpAiHpYLTKJi///ioCId6x9XU1a3ryVU7pjgin9QPP/ygK6+8UmvWrNHDDz+se+65R05n8RZZAEDgeeGFF3TPPfdo3759io6ONh0HkBTihfKYAq9Pm/Yc1PodB7RhxwGlZ+7XN7uzle89+R890mmpSfUKiq8To6a1KqpZrYpqWLWcIpzmTgnk5+fr4Ycf1hNPPKEOHTpo0qRJqlOnzj//RgBAyPj222/VpEkTff755+rZs6fpOICkMCmUJ1Lg9Skz64iO5HuVm+9VntenUk6HoiKdKhPpVJ3YMkbL49/58ssvNXDgQB06dEhvvPGG+vbtazoSAKCE+P1+NWjQQL169dLLL79sOg4gKYwLZbDbt2+fhg4dqo8++khDhw7VmDFjVLZsWdOxAAAl4Oabb9acOXO0efNm01EASSFyyzscVapUSVOnTtUbb7yh9957T82bN1daWprpWACAEmDbtr7//nsKJQIGhTKIWZal6667TmvXrlWZMmXUunVrjRkzRj6fz3Q0AEAx6tKliyIjIxkfhIBBoQwBjRs31ooVK3TLLbfojjvuUM+ePbV7927TsQAAxaRcuXLq0KGDZs2aZToKIIlCGTKioqL03HPPadasWUpPT5fL5dLMmTNNxwIAFBO3262FCxcqJyfHdBSAQhlqevToIY/HoxYtWujCCy/UiBEj+GIDACHItm0dOXJEqamppqMAFMpQVLVqVc2YMUMvvviixo0bp1atWunrr782HQsAUIQuuOAC1a5dm3OUCAgUyhBlWZZuvfVWrV69Wvn5+WrevLn++9//iilRABAaLMuS2+2mUCIgUChDnMvl0po1azRo0CDddNNN6tOnj/bu3Ws6FgCgCNi2re+++05btmwxHQVhjkIZBqKjozVu3Dh9/PHHSk1Nlcvl0oIFC0zHAgAUUteuXRUREcFtbxhHoQwjl1xyiTwej8477zx169ZN9957r/Lz803HAgCcoYoVK6pt27YUShhHoQwztWrV0ty5c/Xkk0/q2WefVbt27XjSAgAEMbfbrfnz5ys3N9d0FIQxCmUYcjqdGjlypJYtW6Z9+/YpISFBEydO5MIOAAQh27Z16NAhLV261HQUhDEKZRhr0aKF0tLS1LdvXw0aNEhXXnmlDhw4YDoWAOA0xMXFqUaNGtz2hlEUyjBXvnx5vf3225o8ebJmzpyp+Ph4LVu2zHQsAMApsixLtm1TKGEUhRKSpAEDBigjI0M1a9ZUx44d9cgjj6igoMB0LADAKbBtW1999ZUyMzNNR0GYolDiuPr16+vLL7/U/fffr4cffljJycnavn276VgAgH+QkpIih8PBbW8YQ6HEH0REROjhhx/WokWLtG3bNrlcLv3vf/8zHQsA8DdiY2PVunVrCiWMoVDihDp06KCMjAx1795d/fv315AhQ3Tw4EHTsQAAJ+F2uzVv3jzmC8MICiVOKjY2VlOmTNGECRM0ZcoUNW/eXGvXrjUdCwBwArZtKzs7W8uXLzcdBWGIQom/ZVmWBg8erHXr1qlcuXJq06aNnn32Wfl8PtPRAAC/k5iYqKpVq3LbG0ZQKHFKGjVqpOXLl2vEiBG6++671aNHD+3atct0LADAbxwOh3r06EGhhBEUSpyyUqVKafTo0ZozZ442bNggl8ulGTNmmI4FAPiNbdvKyMjQzp07TUdBmKFQ4rSlpKTI4/GodevWuuiiizR8+HAdOXLEdCwACHvdu3eXZVmaPXu26SgIMxRKnJEqVaros88+09ixY/XGG2+oZcuW2rBhg+lYABDWKleurBYtWjA+CCWOQokzZlmWhg0bpjVr1sjv9yspKUmvvPKK/H6/6WgAELbcbrfmzJnD085QoiiUKLSmTZtq9erVuu6663TLLbfo4osv1i+//GI6FgCEJdu2tX//fq1atcp0FIQRCiWKRJkyZTR27Fh99tlnWrZsmVwul+bNm2c6FgCEnRYtWuiss87itjdKFIUSReqiiy6Sx+PRBRdcoJSUFP373/9WXl6e6VgAEDacTqe6d+9OoUSJolCiyNWsWVOzZ8/W6NGjNWbMGLVt21YbN240HQsAwoZt21q7dq327NljOgrCBIUSxcLhcOjuu+/W8uXLlZ2drcTERL311ltc2AGAEtCjRw9JYnwQSgyFEsUqKSlJ69at0+WXX65//etfuuKKK7R//37TsQAgpFWrVk2JiYmMD0KJoVCi2JUrV05vvvmmpkyZotmzZysuLk5LliwxHQsAQprb7dbs2bPl9XpNR0EYoFCixPTv318ZGRmqU6eOOnXqpIceeog5aQBQTGzb1t69e7V27VrTURAGKJQoUfXq1dOiRYs0atQoPfroo+rUqZO2bt1qOhYAhJzWrVsrJiaG294oERRKlLiIiAg9+OCDSk1N1Y4dOxQXF6cPPvjAdCwACCkRERFKSUmhUKJEUChhTLt27ZSenq6ePXtqwIABGjx4sH799VfTsQAgZNi2rVWrVmnv3r2moyDEUShhVExMjCZPnqyJEydq6tSpSkxM1OrVq03HAoCQYNu2/H6/5syZYzoKQhyFEsZZlqVrrrlGaWlpiomJUdu2bTV69Gj5fD7T0QAgqNWsWVMul4vxQSh2FEoEjHPPPVdLly7VXXfdpXvuuUcpKSnasWOH6VgAENTcbrdmzZrFD+koVhRKBJRSpUrpySef1Ny5c/Xtt98qLi5On376qelYABC0bNvWnj17lJ6ebjoKQhiFEgGpa9euysjIUPv27XXJJZfo5ptv1uHDh03HAoCg065dO5UvX57b3ihWFEoErMqVK+vjjz/WuHHj9NZbb6lFixbyeDymYwFAUImMjFS3bt0olChWFEoENMuydOONN2rNmjVyOp1q2bKlXn75Zfn9ftPRACBo2Lat5cuXKysry3QUhCgKJYLCBRdcoFWrVumGG27Qrbfeql69emnPnj2mYwFAULBtWz6fT/PmzTMdBSGKQomgUbp0ab344ouaMWOGVq9eLZfLpdmzZ5uOBQABr27dujr//PMZH4RiQ6FE0Lnwwgvl8XgUFxcn27Z15513Kjc313QsAAhox8YHcWQIxYFCiaBUvXp1ffHFF3ruuef08ssvq02bNvruu+9MxwKAgGXbtnbu3Kn169ebjoIQRKFE0HI4HLrjjju0cuVKHT58WImJiRo/fjw/fQPACXTo0EFly5bltjeKBYUSQS8hIUFr167VVVddpaFDh6pfv37at2+f6VgAEFCioqLUpUsXCiWKBYUSIaFs2bJ6/fXXNXXqVC1YsEBxcXFKTU01HQsAAopt21q6dKmys7NNR0GIoVAipPTt21cZGRlq0KCBkpOT9cADDyg/P990LAAICLZtq6CgQPPnzzcdBSGGQomQU6dOHS1YsECPPPKInnzySXXs2FE//PCD6VgAYFyDBg3UqFEjxgehyFEoEZKcTqfuv/9+LVmyRD/99JPi4+M1efJk07EAwDi3260vvviCC4woUhRKhLTWrVsrPT1dvXv31lVXXaVrrrmGs0MAwppt28rMzNQ333xjOgpCCIUSIa9ChQqaNGmS3n33XX388cdKSEjQqlWrTMcCACM6deqk0qVLc9sbRYpCibAxcOBApaenq3LlymrXrp2efPJJeb1e07EAoESVKVNGycnJFEoUKQolwso555yjJUuW6N///rfuv/9+devWTT/++KPpWABQomzb1uLFi3Xw4EHTURAiKJQIO5GRkXr88ce1YMECbdq0SS6XSx9//LHpWABQYtxut/Ly8rRw4ULTURAiKJQIW507d5bH41FycrL69OmjG2+8UYcPHzYdCwCK3bnnnqsGDRowPghFhkKJsFapUiVNnTpVr7/+ut555x01b95c6enppmMBQLGyLIvxQShSFEqEPcuyNHToUK1du1ZRUVFq1aqVXnjhBfl8PtPRAKDY2LatLVu2aOPGjaajIARQKIHfNGnSRCtXrtSwYcN0++2368ILL9RPP/1kOhYAFIvk5GSVKlWKbW8UCcvPWjfwF7NmzdK1114rSZo4caJs2zacCACKXvfu3eVwOCiVKDRWKIETsG1bHo9HzZs3l9vt1u23367c3FzTsQCgSNm2rS+//FJHjhwxHQVBjkIJnES1atU0Y8YMvfDCC3r11VfVqlUrHlUGIKS43W7l5ORo0aJFpqMgyFEogb/hcDh02223adWqVcrLy1Pz5s31+uuvcysSQEho3Lix6taty5Y3Co1CCZyCuLg4rVmzRtdee61uuOEG9e3bV3v37jUdCwAK5ffjg4DCoFACpyg6Olrjxo3Txx9/rC+//FJxcXE8ZQJA0LNtW5s2bdL3339vOgqCGIUSOE2XXHKJMjIy1LBhQ3Xt2lX33Xef8vPzTccCgDPStWtXRUZGsu2NQmFsEHCGvF6vnnnmGT3wwANKTEzU5MmTdc4555iOBQCnrUuXLoqOjtaMGTNMR0GQYoUSOENOp1P33HOPli5dqr179yo+Pl7vvvuu6VgAcNps29bChQuVk5NjOgqCFIUSKKSWLVsqLS1Nffr00TXXXKOBAwfqwIEDpmMBwClzu906fPiwFi9ebDoKghSFEigC5cuX18SJE/Xee+9p+vTpSkhI0PLly03HAoBT0rRpU9WqVYtzlDhjFEqgCF155ZVKT09XtWrV1KFDBz322GPyer2mYwHA37IsS7ZtMz4IZ4xCCRSxs88+W4sXL9Z9992nUaNGKTk5Wdu3bzcdCwD+lm3b+uabb7Rt2zbTURCEKJRAMYiIiNAjjzyihQsXauvWrYqLi9PUqVNNxwKAk+rWrZucTifb3jgjFEqgGHXs2FEZGRnq1q2b+vXrp6FDh+rQoUOmYwHAX8TExKht27Zse+OMUCiBYhYbG6sPP/xQ48eP1+TJk5WYmKh169aZjgUAf2HbtubPn6+8vDzTURBkKJRACbAsS0OGDNG6detUtmxZtW7dWs8995x8Pp/paABwnNvt1sGDB7V06VLTURBkKJRACTrvvPO0fPly3Xbbbbrrrrvkdru1e/du07EAQJIUFxenatWqcY4Sp41CCZSwqKgoPfPMM5ozZ448Ho9cLpc+//xz07EAQA6Hg/FBOCMUSsCQlJQUeTwetWzZUr169dKtt97KY88AGGfbttavX68ff/zRdBQEEQolYFCVKlU0ffp0vfzyy3r99dfVsmVLffXVV6ZjAQhj3bt3l8Ph0OzZs01HQRChUAKGWZalW265RatXr5bP51NSUpLGjRsnv99vOhqAMFSpUiW1atWKbW+cFgolECCaNWum1atXa8iQIbr55pt1ySWX6JdffjEdC0AYsm1bc+fOVX5+vukoCBIUSiCAlClTRmPHjtWnn36qpUuXyuVyaf78+aZjAQgzbrdb2dnZWrFihekoCBIUSiAA9e7dWx6PR+eff75SUlJ0zz33MGgYQIlp3ry5KleuzPggnDIKJRCgatasqTlz5ujpp5/Wc889p3bt2mnTpk2mYwEIAw6HQz169OAcJU4ZhRIIYA6HQ3fffbeWL1+u/fv3KyEhQRMnTuTCDoBiZ9u20tLSePgCTgmFEggCSUlJSktLU//+/TVo0CBdeeWV2r9/v+lYAEJYjx49ZFkW44NwSiiUQJAoV66cJkyYoA8++EBffPGF4uPjed4ugGJTpUoVJSUlse2NU0KhBILM5ZdfrvT0dNWuXVsdO3bUI488ooKCAtOxAIQg27Y1Z84ceb1e01EQ4CiUQBCqX7++Fi1apAcffFAPP/ywkpOTtW3bNtOxAIQYt9utrKwsrVq1ynQUBDgKJRCkIiIiNGrUKKWmpiozM1NxcXH68MMPTccCEEJatmyp2NhYxgfhH1EogSDXrl07paeny7ZtXX755frXv/6lgwcPmo4FIAQ4nU51796dc5T4RxRKIATExMTo/fff11tvvaUPP/xQiYmJWrt2relYAEKAbdtas2aNfv75Z9NREMAolECIsCxLgwYNUlpamipWrKg2bdromWeekc/nMx0NQBCzbVt+v19z5swxHQUBjEIJhJiGDRtq6dKluuOOOzRy5Eh1795dO3fuNB0LQJCqXr26EhIS2PbG36JQAiGoVKlSeuqppzR37lx9/fXXcrlcmj59uulYAIKUbduaPXs2Ox44KQolEMK6du0qj8ejdu3aqXfv3rrlllt05MgR07EABBm3261ffvmFs9k4KQolEOIqV66sTz75RK+++qrefPNNtWjRQuvXrzcdC0AQad26tSpUqMD4IJwUhRIIA5Zl6aabbtKaNWvkcDjUokULjR07Vn6/33Q0AEEgMjJSKSkpnKPESVEogTBywQUXaNWqVbr++us1fPhw9e7dm1EgAE6JbdtauXKl9u3bZzoKAhCFEggzpUuX1ksvvaQZM2ZoxYoVcrlcmjt3rulYAAKcbdvy+Xx8vcAJUSiBMHXhhRfK4/GoWbNm6t69u+6++27l5eWZjgUgQNWuXVvNmjVj2xsnRKEEwliNGjU0a9YsPfvss3rxxRfVpk0bbdy40XQsAAHKtm3NmjWL8UH4CwolEOYcDofuvPNOrVixQgcPHlRCQoImTJjAhR0Af+F2u/XTTz8pIyPDdBQEGAolAElSYmKi1q1bpwEDBmjIkCG6/PLLlZWVZToWgADSrl07lStXjvFB+AvLzzIEgD/53//+p+uvv14VKlTQpEmT1KFDB9ORAASISy65RPv27VNqaqrpKAggrFAC+It+/fopIyND9erVU+fOnTVq1CgVFBSYjgUgANi2rWXLlmn//v2moyCAUCgBnFDdunW1cOFCPfzww3r88cfVsWNHbdmyxXQsAIa53W55vV7Nnz/fdBQEEAolgJNyOp36z3/+o8WLF2vXrl2Kj4/X+++/bzoWAIPq1aunJk2aMD4If0ChBPCP2rRpo/T0dPXq1UtXXnmlBg0apF9//dV0LACGHBsfxDUMHEOhBHBKKlasqEmTJumdd97RtGnTlJCQoFWrVpmOBcAAt9utHTt2aMOGDaajIEBQKAGcMsuydPXVVys9PV1nnXWW2rVrp6eeekper9d0NAAlqEOHDoqOjmZ8EI6jUAI4beecc46WLFmif//737rvvvuUkpKiHTt2mI4FoISULl1aycnJnKPEcRRKAGckMjJSjz/+uObPn6+NGzfK5XLpk08+MR0LQAlxu91asmQJ56khiUIJoJCSk5OVkZGhjh076tJLL9VNN92kw4cPm44FoJjZtq38/HwtWLDAdBQEAAolgEI766yz9NFHH+m1117TxIkTlZSUxLN+gRB3zjnnqGHDhmx7QxKFEkARsSxL119/vdauXatSpUqpZcuWeumllxgrAoQwxgfhGAolgCLVpEkTrVixQjfffLNuu+029erVS3v27DEdC0AxcLvd2rZtm7799lvTUWAYhRJAkStdurTGjBmjmTNnas2aNXK5XJo9e7bpWACKWKdOnRQVFcX4IFAoARQft9stj8ejhIQE2batO++8U7m5uaZjASgi0dHR6ty5M+coQaEEULyqVaumzz//XGPGjNHYsWPVunVrtseAEOJ2u/Xll1/q0KFDpqPAIAolgGLncDg0YsQIrVy5Ujk5OWrevLnGjx/PQX4gBNi2rby8PC1atMh0FBhEoQRQYuLj47V27VoNHDhQQ4cOVb9+/bRv3z7TsQAUQqNGjXT22Wez7R3mKJQASlR0dLRee+01TZs2TQsWLFBcXJy+/PJL07EAnCHLso6PD0L4olACMKJPnz7yeDw699xzlZycrP/85z/Kz883HQvAGXC73fr++++1adMm01FgCIUSgDG1a9fWvHnz9Pjjj+upp55Sx44d9cMPP5iOBeA0JScnq1SpUqxShjEKJQCjnE6n7r33Xi1dulR79uxRfHy83nvvPdOxAJyGcuXKqUOHDpyjDGMUSgABoVWrVkpLS9Mll1yigQMH6uqrr1Z2drbpWABOkdvt1sKFC3XkyBHTUWAAhRJAwKhQoYLeeecdTZo0SZ9++qni4+O1YsUK07EAnALbtpWTk6PU1FTTUWAAhRJAwLnqqquUnp6uatWqqX379nr88cfl9XpNxwLwN84//3zVqVOHbe8wRaEEEJAaNGig1NRU3XvvvXrggQfUtWtXZWZmmo4F4CQYHxTeKJQAAlZkZKQeffRRLVy4UN9//73i4uL00UcfmY4F4CTcbre+++47bdmyxXQUlDAKJYCA16lTJ2VkZKhLly7q27evrr/+ep4bDASgrl27KiIiglXKMGT5eZgugCDh9/v15ptv6rbbblPdunX1/vvvKz4+3nQsAL/TuXNnVahQQZ999pnpKChBrFACCBqWZem6667T2rVrVaZMGbVq1UpjxoyRz+czHQ3Ab9xutxYsWKDc3FzTUVCCKJQAgk7jxo21fPlyDR8+XHfccYd69uyp3bt3m44FQEfHBx06dEhLliwxHQUliEIJIChFRUXp2Wef1axZs5Senq64uDjNnDnTdCwg7LlcLtWoUYPxQWGGQgkgqPXo0UMej0dJSUm68MILNWLECOXk5JiOBYQtxgeFJwolgKBXtWpVzZgxQy+99JL++9//qnXr1vr6669NxwLCltvt1ldffcXs2DBCoQQQEizL0vDhw7Vq1Srl5+crKSlJr732mhhkAZS8bt26yeFwsEoZRiiUAEKKy+XS6tWrNWjQIN14443q06eP9u7dazoWEFZiY2PVpk0bzlGGEQolgJATHR2tV199VZ988olSU1Plcrm0cOFC07GAsOJ2uzVv3jzl5eWZjoISQKEEELIuvvhieTweNW7cWF27dtV9992n/Px807GAsGDbtn799VctX77cdBSUAAolgJBWq1YtzZ07V0899ZSeeeYZtWvXTps3bzYdCwh5CQkJqlq1KtveYYJCCSDkORwO/fvf/9ayZcuUlZWlhIQEvfPOO1zYAYqRw+FQjx49KJRhgkIJIGy0aNFC69at02WXXaZrr71WV111lQ4cOGA6FhCy3G63PB6Pdu7caToKihmFEkBYKV++vN566y29//77+vzzzxUfH88ZL6CYpKSkyLIszZ4923QUFDMKJYCwdMUVVygjI0M1a9ZUhw4d9Oijj8rr9ZqOBYSUypUrq2XLlmx7hwEKJYCwVb9+fX355Zf6z3/+o4ceekjJycnavn276VhASHG73Zo7d64KCgpMR0ExolACCGsRERF66KGH9OWXX2rbtm2Ki4vT1KlTTccCQoZt29q/f79WrlxpOgqKEYUSACS1b99eGRkZ6t69u/r166frrrtOhw4dMh0LCHpJSUk666yz2PYOcRRKAPhNTEyMPvjgA02YMEEffPCBEhMTtW7dOtOxgKDmdDrVvXt3nusd4iiUAPA7lmVp8ODBWrduncqXL6/WrVvr2Weflc/nMx0NCFput1tr167VTz/9ZDoKigmFEgBOoFGjRlq2bJlGjBihu+++W7Zta9euXaZjAUGpe/fukqQ5c+YYToLiQqEEgJMoVaqURo8erblz52rDhg1yuVyaMWOG6VhA0KlWrZqaN2/OOcoQRqEEgH/QrVs3ZWRkqE2bNrrooos0fPhw5eTkmI4FBBW3263Zs2cz7zVEUSgB4BRUqVJFn376qV555RWNHz9eLVq00IYNG0zHAoKGbdvat2+f1qxZYzoKigGFEgBOkWVZuvnmm7V69WpJR58N/uqrr8rv9xtOBgS+Vq1aKSYmhm3vEEWhBIDT1LRpU61atUrXXXedhg0bposvvli//PKL6VhAQIuIiFBKSgrjg0IUhRIAzkCZMmX08ssva/r06Vq+fLlcLpfmz59vOhYQ0Nxut1atWsUPYCGIQgkAhdCrVy95PB41bdpUKSkpGjlypPLy8kzHAgJSjx495Pf7NXfuXNNRUMQolABQSDVq1NCsWbM0evRojRkzRm3bttXGjRtNxwICTs2aNRUXF8c5yhBEoQSAIuBwOHTXXXdp+fLlys7OVmJiot566y0u7AB/4na7NWvWLJ4+FWIolABQhJo3b65169bpiiuu0L/+9S8NGDBA+/fvNx0LCBi2bevnn39WWlqa6SgoQhRKAChi5cqV0/jx4/Xhhx9q9uzZiouL05IlS0zHAgJC27ZtVb58eba9QwyFEgCKSb9+/ZSRkaG6deuqU6dOeuihh1RQUGA6FmBUZGSkunXrxvigEEOhBIBiVLduXS1cuFAPPfSQHnvsMXXu3Fnbtm0zHQswyu12a/ny5crKyjIdBUWEQgkAxSwiIkIPPPCAUlNTtWPHDsXFxWnKlCmmYwHG2LYtn8/H+KAQQqEEgBLStm1bpaeny+1264orrtDgwYP166+/mo4FlLg6deroggsuYNs7hFAoAaAEVaxYUZMnT9bEiRM1depUJSYmHn82OBBOjo0PYrRWaKBQAkAJsyxL11xzjdLS0hQTE6O2bdtq9OjRzOVDWLFtW7t27ZLH4zEdBUWAQgkAhpx77rlaunSp7rrrLt1zzz3q3r27du7caToWUCLat2+vsmXLMj4oRFh+1poBwLgFCxbo6quvVm5uriZMmKDevXubjgQUu969eys7O1uLFi0yHQWFxAolAASALl26yOPxqH379rr44os1bNgwHTlyxHQsoFi53W4tXbpU2dnZpqOgkCiUABAgzjrrLH388ccaN26cJkyYoKSkJM6XIaTZtq2CggLNmzfPdBQUEoUSAAKIZVm68cYbtXbtWkVERKhly5Z6+eWXuQmLkHT22WfrvPPOY3xQCKBQAkAAOv/887Vy5UrdeOONuvXWW3XRRRfp559/Nh0LKHJut1tffPEFPzQFOQolAASo0qVL64UXXtDnn3+uVatWyeVyac6cOaZjAUXKtm39+OOP+vrrr01HQSFQKAEgwPXs2VMej0cul0s9evTQXXfdpdzcXNOxgCLRqVMnlSlThvFBQY6xQQAQJHw+n1588UWNHDlSTZs21fvvv6/zzjvPdCyg0Hr27Km8vDwu5wQxVigBIEg4HA7dfvvtWrlypQ4fPqzExES9+eabnD1D0HO73Vq8eLEOHjxoOgrOEIUSAIJMQkKC1q5dq6uuukrXXXed+vfvr6ysLNOxgDNm27by8vK0YMEC01FwhiiUABCEypYtq9dff11Tp07V/PnzFRcXp9TUVNOxgDPSsGFDnXPOOYwPCmIUSgAIYn379lVGRoYaNGig5ORkPfDAAyooKDAdCzhtjA8KbhRKAAhyderU0fz58/XII4/oySefVMeOHbVlyxbTsYDTYtu2tm7dqo0bN5qOgjNAoQSAEOB0OnX//fdryZIl2r17t+Lj4zV58mTTsYBT1rlzZ0VFRTE+KEhRKAEghLRu3Vrp6em66KKLdNVVV+maa65Rdna26VjAPypbtqw6duzIOcogRaEEgBBToUIFTZo0Se+++64++eQTJSQkaNWqVaZjAf/I7XZr0aJFOnz4sOkoOE0USgAIUQMHDlRaWpqqVKmidu3a6cknn5TX6zUdCzgp27aVm5urRYsWmY6C00ShBIAQds4552jx4sUaOXKk7r//fqWkpOjHH380HQs4ocaNG6tevXpsewchCiUAhLjIyEg99thjWrhwoTZt2qS4uDh9/PHHpmMBf2FZ1vHxQQguFEoACBOdOnVSRkaGOnfurD59+ujGG2/krBoCjm3b2rx5szZv3mw6Ck4DhRIAwkilSpU0depUvf7663rnnXeUlJSkjIwM07GA47p06aLIyEi2vYMMhRIAwoxlWRo6dKjWrVunqKgotWzZUi+++CJPKEFAKF++vNq3b0+hDDIUSgAIU40bN9aKFSs0bNgwjRgxQhdeeKF++ukn07EAud1uLViwQDk5Oaaj4BRRKAEgjEVFRen555/XF198obVr18rlcrEyBONs29aRI0eUmppqOgpOEYUSACDbtuXxeNS8eXO53W7dfvvtys3NNR0LYapp06aqVasWP9wEEQolAECSVK1aNX3++ed68cUX9eqrr6pVq1b65ptvTMdCGGJ8UPChUAIAjrMsS7feeqtWrVqlvLw8NW/eXK+//joXdlDibNvWt99+q61bt5qOglNAoQQA/EVcXJzWrFmja6+9VjfccIP69u2rvXv3mo6FMNKtWzc5nU62vYOE5efHTgDA3/jkk080ZMgQlSlTRpMmTVLnzp1NR0KY6NixoypVqqRPPvnEdBT8A1YoAQB/65JLLpHH41GjRo3UpUsX3X///crPzzcdC2HA7XZr/vz5ysvLMx0F/4BCCQD4R7Vq1dLcuXP1xBNPaPTo0Wrfvr2+//5707EQ4txutw4ePKglS5aYjoJ/QKEEAJwSp9Ope+65R0uXLtXevXsVHx+vd99913QshLC4uDhVr16dc5RBgEIJADgtLVu2VFpamvr06aNrrrlGAwcOVHZ2tulYCEGWZcm2bcYHBQEKJQDgtJUvX14TJ07Ue++9p+nTpys+Pl4rVqwwHQshyLZtbdiwQT/++KPpKPgbFEoAwBm78sorlZ6erurVq6t9+/Z67LHH5PV6TcdCCElJSZHD4WDbO8BRKAEAhXL22WcrNTVV9913n0aNGqUuXbooMzPTdCyEiEqVKqlVq1YUygBHoQQAFFpERIQeeeQRLVy4UFu2bJHL5dK0adNMx0KIcLvdmjt3LuOqAhiFEgBQZDp27KiMjAx169ZNl112ma6//nodOnTIdCwEObfbrezsbC1fvtx0FJwEhRIAUKRiY2P14Ycfavz48XrvvffUvHlzpaWlmY6FIJaYmKgqVaqw7R3AKJQAgCJnWZaGDBmidevWKTo6Wq1atdLzzz8vn89nOhqCkMPhUI8ePRgfFMAolACAYnPeeedp+fLluu2223TnnXfK7XZr9+7dpmMhCNm2rfT0dO3atct0FJwAhRIAUKyioqL0zDPPaM6cOfJ4PHK5XPr8889Nx0KQ6d69uyzL0uzZs01HwQlQKAEAJSIlJUUej0ctW7ZUr169dNtttyknJ8d0LASJKlWqKCkpiXOUAYpCCQAoMVWqVNH06dP18ssv67XXXlPLli311VdfmY6FIOF2uzVnzhwVFBSYjoI/oVACAEqUZVm65ZZbtHr1avl8PiUlJWncuHHy+/2moyHAud1uZWVladWqVaaj4E8olAAAI5o1a6bVq1dryJAhuvnmm3XppZfql19+MR0LAaxFixaqVKkS294BiEIJADCmTJkyGjt2rD799FMtWbJEcXFxWrBggelYCFBOp1Pdu3dnfFAAolACAIzr3bu3PB6PmjRpom7duumee+5RXl6e6VgIQLZta82aNdqzZ4/pKPgdCiUAICDUrFlTc+bM0dNPP63nnntO7dq106ZNm0zHQoDp0aOHJGnOnDmGk+D3KJQAgIDhcDh09913a/ny5dq/f78SEhI0ceJELuzguOrVqyshIYFzlAGGQgkACDhJSUlKS0tT//79NWjQIF155ZXav3+/6VgIEG63W7Nnz+ZRngGEQgkACEjlypXThAkT9MEHH+iLL75QfHy8li1bZjoWAoDb7dYvv/yiNWvWmI6C31AoAQAB7fLLL1d6erpq166tDh066JFHHmGwdZhr3bq1KlasyLZ3AKFQAgACXv369bVo0SI9+OCDevjhh5WcnKxt27aZjgVDIiIilJKSwvigAEKhBAAEhYiICI0aNUqpqanKzMxUXFycPvzwQ9OxYIht21q1apX27t1rOgpEoQQABJl27dopPT1dtm3r8ssv15AhQ3Tw4EHTsVDCbNuWz+fT3LlzTUeBKJQAgCAUExOj999/X2+99ZamTJmixMRErV271nQslKBatWqpWbNmnKMMEBRKAEBQsixLgwYNUlpamipWrKg2bdromWeeYZRMGHG73Zo1axb/nwcACiUAIKg1bNhQS5cu1R133KGRI0eqR48e2rVrl+lYKAFut1s//fST0tPTTUcJexRKAEDQK1WqlJ566inNnTtXX331lVwul6ZPn246FopZ27ZtVa5cOba9AwCFEgAQMrp27SqPx6O2bduqd+/euuWWW3TkyBHTsVBMSpUqpW7dujE+KABQKAEAIaVy5cr65JNP9Oqrr+rNN99UixYttH79etOxUExs2z7+7HeYQ6EEAIQcy7J00003ac2aNXI4HGrRooXGjh0rv99vOhqKmG3b8nq9mjdvnukoYY1CCQAIWRdccIFWrVql66+/XsOHD1fv3r31888/m46FIlSvXj01adKEbW/DKJQAgJBWunRpvfTSS5o+fbpWrFghl8vFMOwQc2x8ECvQ5lAoAQBhoVevXvJ4PGrWrJm6d++uu+++W3l5eaZjoQi43W7t3LmTs7IGUSgBAGGjRo0amjVrlp599lm9+OKLatOmjTZu3Gg6FgqpQ4cOio6OZnyQQRRKAEBYcTgcuvPOO7VixQodPHhQCQkJmjBhAtulQSwqKkpdunThHKVBFEoAQFg69vzvAQMGaMiQIbriiiuUlZVlOhbOkG3bWrJkiX799VfTUcIShRIAELbKlSun8ePH68MPP9ScOXMUHx+vxYsXm46FM+B2u1VQUKD58+ebjhKWKJQAgLDXr18/ZWRkqF69eurcubNGjRqlgoIC07FwGho0aKCGDRuy7W0IhRIAAEl169bVwoUL9dBDD+nxxx9Xp06dtHXrVtOxcBoYH2QOhRIAgN84nU498MADSk1N1c6dOxUXF6cPPvjAdCycIrfbre3bt+ubb74xHSXsUCgBAPiTtm3bKj09XRdeeKEGDBigQYMGcdkjCHTq1EmlS5dmfJABlp91YQAATsjv92vSpEm6+eabVa1aNb3//vtq0aKF6Vj4G8cu5/A0pJLFCiUAACdhWZauvvpqpaen66yzzlLbtm319NNPy+fzmY6Gk7BtW6mpqTp06JDpKGGFQgkAwD8455xztGTJEt1999269957lZKSoh07dpiOhRNwu93Ky8vTwoULTUcJKxRKAABOQWRkpJ544gnNnz9f3333nVwulz755BPTsfAnDRs21Nlnn834oBJGoQQA4DQkJycrIyNDHTt21KWXXqqbbrpJhw8fNh0Lv7EsS263W1988QXjg0oQhRIAgNN01lln6aOPPtJ///tfTZw4US1atJDH4zEdC79xu93asmWLNm3aZDpK2KBQAgBwBizL0g033KA1a9YoIiJCLVu21EsvvcSqWABITk5WqVKlGB9UgiiUAAAUwvnnn6+VK1fqpptu0m233aZevXppz549pmOFtbJly6pjx46coyxBFEoAAAqpdOnSGjNmjGbOnKk1a9bI5XJp9uzZpmOFNdu2tWjRIh05csR0lLBAoQQAoIi43W55PB7Fx8fLtm3deeedys3NNR0rLLndbuXk5OjLL780HSUsUCgBAChC1apV08yZMzVmzBiNHTtWrVu31rfffms6Vthp0qSJ6tSpw7Z3CaFQAgBQxBwOh0aMGKEVK1YoJydHzZs31/jx47mwU4KOjQ/iYk7JoFACAFBMEhIStGbNGg0cOFBDhw5Vv379tG/fPtOxwobb7dbGjRv1ww8/mI4S8iiUAAAUo7Jly+q1117TtGnTtGDBAsXFxXGur4R06dJFERERrFKWAAolAAAloE+fPvJ4PDrnnHOUnJysBx54QPn5+aZjhbQKFSqoffv2nKMsARRKAABKSO3atTV//nw99thjevLJJ9WxY0e2Y4uZbdtasGABt+2LGYUSAIAS5HQ6dd9992np0qXas2eP4uPj9d5775mOFbLcbrcOHz6sxYsXm44S0iiUAAAY0KpVK6WlpemSSy7RwIEDdfXVVys7O9t0rJDTrFkz1axZk23vYkahBADAkAoVKuidd97RpEmT9OmnnyohIUErV640HSukWJYl27a5mFPMKJQAABh21VVXKT09XVWqVFG7du30xBNPyOv1mo4VMtxut77++mtt377ddJSQRaEEACAANGjQQIsXL9a9996r//znP+ratasyMzNNxwoJ3bp1k9PpZJWyGFEoAQAIEJGRkXr00Ue1cOFCff/994qLi9NHH31kOlbQi4mJUZs2bThHWYwolAAABJhOnTopIyNDycnJ6tu3r2644QYdOnTIdKygZtu25s+fr7y8PNNRQhKFEgCAAFSpUiVNnTpVb7zxhiZNmqSkpCSlp6ebjhW03G63fv31Vy1btsx0lJBEoQQAIEBZlqXrrrtOa9euVenSpdWqVSuNGTNGPp/PdLSgEx8fr2rVqrHtXUwolAAABLjGjRtrxYoVGj58uO644w717NlTu3fvNh0rqDgcDvXo0YOLOcWEQgkAQBCIiorSs88+q1mzZik9PV1xcXGstp0mt9stj8ejHTt2mI4SciiUAAAEkR49esjj8SgpKUk9e/bUiBEjlJOTYzpWUEhJSZHD4dDs2bNNRwk5FEoAAIJM1apVNWPGDL344osaN26cWrdura+//tp0rIB31llnqWXLlqzsFgMKJQAAQciyLN16661avXq18vPzlZSUpNdee01+v990tIBm27bmzp2rgoIC01FCCoUSAIAg5nK5tHr1al177bW68cYb1adPH+3du9d0rIDldrt14MABrVixwnSUkEKhBAAgyEVHR2vcuHH6+OOPlZqaqri4OC1cuNB0rICUlJSkypUrs+1dxCiUAACEiEsuuUQej0eNGjVS165ddd999yk/P990rIDicDjUvXt3xgcVMQolAAAhpFatWpo7d66efPJJPfPMM2rXrp02b95sOlZAcbvdWrduHbM8ixCFEgCAEON0OjVy5EgtW7ZM+/btU0JCgt555x0u7Pyme/fukqQ5c+YYThI6KJQAAISoFi1aKC0tTX379tW1116rgQMH6sCBA6ZjGVe1alUlJSVxjrIIUSgBAAhh5cuX19tvv63JkydrxowZio+P1/Lly03HMs62bc2ZM0der9d0lJBAoQQAIAwMGDBAGRkZqlmzpjp06KBHH300rMuU2+3Wvn37tHr1atNRQgKFEgCAMFG/fn19+eWXuv/++/XQQw8pOTlZ27dvNx3LiJYtWyo2NpZt7yJCoQQAIIxERETo4Ycf1qJFi7R161bFxcVp6tSppmOVuIiICKWkpDA+qIhQKAEACEMdOnRQRkaGUlJS1K9fP1133XU6dOiQ6Vglyu12a/Xq1fr5559NRwl6FEoAAMJUbGyspkyZogkTJuiDDz5QYmKi1q1bZzpWienRo4f8fr/mzp1rOkrQo1ACABDGLMvS4MGDtW7dOpUrV06tW7fWc889J5/PZzpasatRo4bi4+M5R1kEKJQAAECNGjXS8uXLNWLECN11112ybVu7du0yHavY2bat2bNnh0WBLk4USgAAIEkqVaqURo8erTlz5mj9+vVyuVyaMWOG6VjFyu126+effw6rrf7iQKEEAAB/kJKSIo/Ho9atW+uiiy7S8OHDlZOTYzpWsWjTpo0qVKjAtnchUSgBAMBfVKlSRZ999pnGjh2rN954Qy1atNCGDRtMxypykZGR6tatG+ODColCCQAATsiyLA0bNkxr1qyR3+9XixYt9Oqrr8rv95uOVqTcbrdWrFihffv2mY4StCiUAADgbzVt2lSrV6/WkCFDNGzYMF1yySX65ZdfTMcqMrZty+fzad68eaajBC0KJQAA+EdlypTR2LFj9dlnn2np0qVyuVyaP3++6VhFonbt2mratCnnKAuBQgkAAE7ZRRddJI/HowsuuEApKSkaOXKk8vLyTMcqNNu2NWvWrJDbzi8pFEoAAHBaatasqdmzZ+vpp5/W888/r7Zt22rTpk2mYxWK2+3W7t27lZGRYTpKUKJQAgCA0+ZwOHT33Xdr+fLlys7OVkJCgt5+++2gXeFr3769ypYty7b3GaJQAgCAM5aUlKR169bp8ssv1+DBgzVgwADt37/fdKzTVqpUKXXt2pXxQWeIQgkAAAqlXLlyevPNNzVlyhTNmjVLcXFxWrJkielYp83tdmvp0qU6cOCA6ShBh0IJAACKRP/+/ZWRkaE6deqoU6dOeuihh1RQUGA61imzbVterzdkbq+XJAolAAAoMvXq1dOiRYs0atQoPfroo+rcubO2bdtmOtYpqV+/vho3bsw5yjNAoQQAAEUqIiJCDz74oFJTU/Xjjz8qLi5OU6ZMMR3rlNi2rS+++CJoLxeZQqEEAADFol27dkpPT5fb7dYVV1yhwYMH69dffzUd62+53W7t2LFDX331lekoQcXyU8EBAEAx8vv9eueddzRs2DDVqFFD77//vpKSkkzHOqGcnBzFxsZqyJAhqlSpkpYsWaJnnnlGzZs3Nx0toFEoAQBAidi0aZOuvPJKpaen6/HHH9ddd90lhyMwNkt9Pp8mT56s6dOna9q0afJ6vXI4HPL5fProo4906aWXmo4Y0CiUAACgxOTl5WnUqFF6+umn1aVLF73zzjuqWbOm6VhKT09XQkKCLMv6y/nJLVu2qH79+maCBYnA+LEAAACEhVKlSunJJ5/U3Llz9c0338jlcumzzz4zHUtxcXG64447/lImy5cvr3r16hlKFTwolAAAoMR17dpVGRkZateunS6++GINGzZMR44cMZbHsiw988wzuvrqq2VZ1vFfP7Zqib9HoQQAAEZUrlxZn3zyiV599VVNmDBBSUlJWr9+vbE8DodDb775pmzbPl4iExMTjeUJJhRKAABgjGVZuummm7RmzRo5nU61aNFCY8eONTYHMjIyUlOnTlWjRo0kSTVq1PjD+/O9Pm355ZC+2nlA67ZnaeWWvVq3PUtf7TygLb8cUr7XZyK2cVzKAQAAASEnJ0cjR47USy+9pAsvvFBvvfWWqlSpYiTLrl271OeyfnrspfHa6y+r9TsOKD1zv77dna1878mrU6TTUuPqFRRfJ0bNalVU01oV1bBqOUU6Q3sNj0IJAAACyueff67BgwfL6XRq4sSJ6t69e4m+fkbmfr27Yqume3Ypt+DoimOEw1KB79Qr0+8/PirCoYtcNXRNm/py1Y4pjsjGUSgBAEDA2bVrlwYNGqQ5c+bozjvv1BNPPKFSpUoV2+vl5Hv1WcZOvb1sq77elS2nw5L3NArkPzn2+S6oWUGD2tbXRa6aKh3pLLLPbxqFEgAABCSfz6cXXnhB99xzj5o1a6bJkyfrvPPOK9LXyMn3auzCzXp72VYdzC2Qw5KKsEf+xbHPXy4qQoPb1tew5HNDolhSKAEAQEBLS0vTgAEDlJmZqZdeekn/+te/imSUz9ptWbrjw3RlZh0u1hJ5Mg5LqhMbrTGXxyuxbmzJByhCFEoAABDwDh06pBEjRmj8+PG67LLL9Prrrys29sxKWE6+V8/P3ag3Fv8gq5hXJP+Jw5L8fmlohwa6I6VR0K5WUigBAEDQmDp1qoYOHary5cvrvffeU4cOHU7r96/bnqXbp5hblTwZy5LqBvFqZWjfYQcAACHlsssuk8fj0dlnn63OnTvrwQcfVEFBwSn93pnrd6nfa8sDrkxKR1cpM7MOq99ryzVz/S7TcU4bK5QAACDoeL1ePfXUUxo1apRatmyp9957T2efffZJP37K6u2656OjT+EJ5OJz7GTo031d6p9Ux2iW08EKJQAACDpOp1P333+/Fi9erF27dik+Pl6TJ08+4cdOWb1dIz9aL78Cu0xKOp7x39M8+nBNpuk4p4xCCQAAglabNm2Unp6uXr166aqrrtI111yjX3/99fj7Z67fdXxlMtiMnOYJmu1vtrwBAEBImDRpkm666SZVq1ZNkydPVkT1hur32nL5fP6AX5k8EUuSw2Hpfze0CfiLOhRKAAAQMr7//ntdeeWVWufZoAvufE/ZvsiAu4BzOo7Nqpw9omNAjxSiUAIAgJCSn5+vi0e9ra99NY7O4wlyliVd36GB7nU3MR3lpDhDCQAAQopn50F9468ZEmVSOjpS6PXUH7Rue5bpKCdFoQQAACEjJ9+rOz5MlyM0uuRxliXdPiVdOfle01FOiEIJAABCxisLNysz67C8IXagz+eXtmcd1isLN5uOckIUSgAAEBJy8r16a9nWoL6E83f8funtZVsDcpWSQgkAAELCdM9OHcw9tccwBqtfcws0wxN4sykplAAAICS8tXRryJ2d/DOHJb21bIvpGH9BoQQAAEEvI3O/vt6VHbLb3cf4/NJXO7OVkbnfdJQ/oFACAICg9+6KrXKG+vLkb5wOS5NWbjMd4w8olAAAIKjle32a7tklb6gvT/7G6/Prs4ydKvD6TEc5jkIJAACC2qY9B5VbEDjlqiTkFvi0ac9B0zGOizAdAAAAoDA27DhQIq+z7alep/Rx1QY8odL1XMWcRlq/44Ca1KhQ7K9zKiiUAAAgqK3fcUARDksFxbzlfVavO//wz4c2LFDO1rS//Hpk5TrFmkOSIhyWNuw4oP5Jxf9ap4JCCQAAglp65v5iL5OSVK5p8h/+OW/nt8rZmvaXXy8JBT6/0gPopjdnKAEAQNDK9/r07e5s0zGM+GZ3dsBczKFQAgCAoPVj1hHlh9qDu09RvtevzKwjpmNIolACAIAgdjgvtB+1+E+OBMhzvSmUAAAgaIXbuKA/y6VQAgAAFE5+gJwhNCUvQP78FEoAABC0Ip3hXWVKBcifPzBSAAAAnIGoiPCuMlGRTtMRJFEoAQBAEIsuFd4jtctQKAEAAAqndmwZRTot0zGMiHRaqhNbxnQMSRRKAAAQxCKdDjWuHhjPsy5pTapXUARnKAEAAAovvk6MIhwlv0pZqftNqnfPjBJ/Xenos7zj68QYee0ToVACAICg1qxWxRJ5lncgKfD51bRWRdMxjqNQAgCAoBZIxaokNQugPzeFEgAABLWGVcuF3figqAiHGlYtZzrGceH1bx8AAIScSKdDF7lqyGngHKUJToel3nE1A+ZCjkShBAAAIeDq1vXlDZNzlF6fX1e3rmc6xh9QKAEAQNCLqxOj82tUUKgvUjos6YKaFeSqHWM6yh9QKAEAQEgY3K6+Qn2R0ueXBrc923SMv6BQAgCAkHCRq6bKRYX2oxjLR0Wol6uG6Rh/QaEEAAAhoXSkU4Pb1g/ZbW/Lkga1ra/SAfL87t+jUAIAgJAxLPlc1YmNDrlS6bCkepWiNSz5XNNRTohCCQAAQkbpSKee7x8vf4idpfT7pef7xwfk6qREoQQAACGmeb1YDe3QIGRWKS1Lur5jAyXWjTUd5aQolAAAIOTckdIoJLa+j211396tkekof4tCCQAAQk7pSKfGXB4vy7IUrJ3SkmRZVkBvdR9DoQQAACEpsW6sXr4iwXSMQhk7ICGgt7qPoVACAICQ1bNZDT3d12U6xhl5uq9L7qaBN3PyRCiUAAAgpPVPqqPRfV1Ht5BNh/kHxzKO7utS/6Q6puOcMsvvD7WL9QAAAH81c/0uDf8gTX6/PyAf0eiwjp6ZHDsgIWhWJo+hUAIAgLCxbnuWbp+SrsyswwFVKi1LqhsbrTGXxwfFmck/o1ACAICwkpPv1fNzN+qNxT/IsmS0WDqso0PLr+/YQLd3axTwt7lPhkIJAADC0tptWbrjQ3OrlcG+Kvl7FEoAABC2cvK9emXhZr29bKt+zS2Q9duKYXFx/LYiWj4qQoPa1tew5HODdlXy9yiUAAAg7OXkezXds1NvL9uqr3Zmy+mw5C3CZctjn69pzQoa1PZs9XLVCIkieQyFEgAA4HcyMvdr0spt+ixjp3ILfJKkCIelgtMomL//+KgIh3rH1dTVrevJVTumOCIbR6EEAAA4gQKvT5v2HNT6HQe0YccBpWfu1ze7s5XvPXl1inRaalK9guLrxKhprYpqVquiGlYtpwhnaI/+plACAACcogKvT5lZR3Qk36vcfK/yvD6VcjoUFelUmUin6sSWCfnyeCIUSgAAABRK+FVoAAAAFCkKJQAAAAqFQgkAAIBCoVACAACgUCiUAAAAKBQKJQAAAAqFQgkAAIBCoVACAACgUCiUAAAAKBQKJQAAAAqFQgkAAIBCoVACAACgUCiUAAAAKBQKJQAAAAqFQgkAAIBCoVACAACgUCiUAAAAKBQKJQAAAArl/wB5dm5Tb60RHwAAAABJRU5ErkJggg==\n"
-          },
-          "metadata": {}
-        }
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/lib/python3.12/dist-packages/sklearn/utils/deprecation.py:151: FutureWarning: 'force_all_finite' was renamed to 'ensure_all_finite' in 1.6 and will be removed in 1.8.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "s_tabpfn = SLearner(overall_model=TabPFNRegressor())\n",
+    "\n",
+    "s_tabpfn.fit(Y=Y_train, X=X_train, T=T_train)\n",
+    "s_tabpfn_cate = s_tabpfn.effect(X=X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1eUVnX-r1waQ"
+   },
+   "outputs": [],
+   "source": [
+    "cfdml_tabpfn = CausalForestDML(model_y=TabPFNRegressor(), model_t=TabPFNClassifier(), discrete_treatment=True)\n",
+    "\n",
+    "cfdml_tabpfn.fit(Y=Y_train, X=X_train, T=T_train)\n",
+    "cfdml_tabpfn_cate = cfdml_tabpfn.effect(X=X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "R_QEm9P12tlH"
+   },
+   "outputs": [],
+   "source": [
+    "cfdml_default = CausalForestDML(discrete_treatment=True)\n",
+    "\n",
+    "cfdml_default.fit(Y=Y_train, X=X_train, T=T_train)\n",
+    "cfdml_default_cate = cfdml_default.effect(X=X_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "nbsS1tvf7GS1"
+   },
+   "source": [
+    "### Evaluate performance in CATE estimation\n",
+    "\n",
+    "We assess how close our predicted individual effects $\\hat{\\tau}(x)$ are to the true effects $\\tau(x)$ using **PEHE** (Precision in Estimation of Heterogeneous Effects).\n",
+    "PEHE is defined as the root-mean-squared-error (RMSE) between predicted and ground truth CATE values.\n",
+    "\n",
+    "$$\\text{PEHE} = \\sqrt{\\frac{1}{n} \\sum [\\widehat{\\tau}(x_i) - \\tau(x_i) ]^2}$$\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "LQYrBYLB7F2v",
+    "outputId": "48ceaeb6-81d5-4d74-8541-ee3656097969"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "source": [
-        "import numpy as np\n",
-        "\n",
-        "num_samples, num_features, train_test_split = 500, 5, 75\n",
-        "\n",
-        "noise_scale = 0.01\n",
-        "exogenous_scale = 0.1\n",
-        "heterogeneity_scale = 2\n",
-        "\n",
-        "X = np.random.normal(loc=0, scale=exogenous_scale, size=(num_samples, num_features)).astype(np.float32)\n",
-        "prop_eps = np.random.normal(loc=0, scale=noise_scale, size=(num_samples)).astype(np.float32)\n",
-        "Y_eps = np.random.normal(loc=0, scale=noise_scale, size=(num_samples)).astype(np.float32)\n",
-        "\n",
-        "w_X_Y = np.random.uniform(size=num_features)\n",
-        "w_X_T = np.random.uniform(size=num_features)\n",
-        "w_X_T_effect = np.random.uniform(size=num_features)\n",
-        "\n",
-        "T_0 = np.zeros(shape=num_samples).astype(np.float32)\n",
-        "T_1 = np.ones(shape=num_samples).astype(np.float32)\n",
-        "\n",
-        "base_X_Y = np.sum(w_X_Y * X, axis=1)\n",
-        "base_X_T = np.sum(w_X_T * X, axis=1)\n",
-        "heterogeneity_term = np.sum(w_X_T_effect * X, axis=1)\n",
-        "\n",
-        "propensity = np.sin(base_X_T) + prop_eps\n",
-        "T = (propensity > propensity.mean()).astype(np.float32)\n",
-        "\n",
-        "Y_0 = np.cos(base_X_Y) + np.sin(0.3 * T_0) + Y_eps\n",
-        "Y_1 = np.cos(base_X_Y) + np.sin(0.3 * T_1 + heterogeneity_scale * heterogeneity_term) + Y_eps\n",
-        "\n",
-        "Y = Y_0 * (1 - T) + Y_1 * T\n",
-        "tau = Y_1 - Y_0"
-      ],
-      "metadata": {
-        "id": "gadFg7JusQ6l"
-      },
-      "execution_count": 10,
-      "outputs": []
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "s_tabpfn PEHE: 0.09701367904551404\n",
+      "cfdml_tabpfn PEHE: 0.22240085005502397\n",
+      "cfdml_default PEHE: 0.2537058237154443\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import root_mean_squared_error\n",
+    "\n",
+    "s_tabpfn_pehe = root_mean_squared_error(tau_test, s_tabpfn_cate)\n",
+    "cfdml_tabpfn_pehe = root_mean_squared_error(tau_test, cfdml_tabpfn_cate)\n",
+    "cfdml_default_pehe = root_mean_squared_error(tau_test, cfdml_default_cate)\n",
+    "\n",
+    "print(f\"s_tabpfn PEHE: {s_tabpfn_pehe}\")\n",
+    "print(f\"cfdml_tabpfn PEHE: {cfdml_tabpfn_pehe}\")\n",
+    "print(f\"cfdml_default PEHE: {cfdml_default_pehe}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 307
     },
+    "id": "-Jlg79mU_Ehg",
+    "outputId": "dd26be1d-37b0-4357-c32b-fe5d3697f85f"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "source": [
-        "import pandas as pd\n",
-        "import seaborn as sns\n",
-        "import matplotlib.pyplot as plt\n",
-        "\n",
-        "df = pd.DataFrame({**{f\"X{i}\": X[:, i] for i in range(num_features)}, \"T\": T, \"Y\": Y, \"Y_0\": Y_0, \"Y_1\": Y_1, \"tau\": tau})\n",
-        "fig, axes = plt.subplots(ncols=2, figsize=(6, 3))\n",
-        "sns.scatterplot(data=df, x=\"X0\", y=\"tau\", hue=\"T\", ax=axes[0], edgecolor=\"black\", palette=\"Set1\")\n",
-        "sns.scatterplot(data=df, x=\"X1\", y=\"tau\", hue=\"T\", ax=axes[1], edgecolor=\"black\", palette=\"Set1\")\n",
-        "fig.tight_layout()"
-      ],
-      "metadata": {
-        "id": "VnBaoFhLBiKq",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 0
-        },
-        "outputId": "92c452fd-d8ca-45ec-daed-77f04730713a"
-      },
-      "execution_count": 11,
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 900x300 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df_test = pd.DataFrame({\"T\": T_test, \"Y\": Y_test, \"tau\": tau_test, **{f\"X{i}\": X_test[:, i] for i in range(num_features)}})\n",
+    "df_test[\"s_tabpfn_pred\"], df_test[\"cfdml_tabpfn_pred\"], df_test[\"cfdml_default_pred\"] = s_tabpfn_cate, cfdml_tabpfn_cate, cfdml_default_cate\n",
+    "\n",
+    "fig, axes = plt.subplots(ncols=3, figsize=(9, 3))\n",
+    "sns.scatterplot(data=df_test, x=\"tau\", y=\"s_tabpfn_pred\", hue=\"T\", ax=axes[0], edgecolor=\"black\", palette=\"Set1\")\n",
+    "sns.scatterplot(data=df_test, x=\"tau\", y=\"cfdml_tabpfn_pred\", hue=\"T\", ax=axes[1], edgecolor=\"black\", palette=\"Set1\")\n",
+    "sns.scatterplot(data=df_test, x=\"tau\", y=\"cfdml_default_pred\", hue=\"T\", ax=axes[2], edgecolor=\"black\", palette=\"Set1\")\n",
+    "fig.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "SlKBzRphHS_6"
+   },
+   "source": [
+    "# Feedback\n",
+    "\n",
+    "Let us know what you think!\n",
+    "\n",
+    "Write us at Discord: https://discord.gg/qK7AaXPN or just simply create an issue on [GitHub](https://github.com/PriorLabs/tabpfn).\n",
+    "\n",
+    "Thank you for trying out our method! 🎉\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "collapsed_sections": [
+    "tisgLOuqzrfo",
+    "o03aOVAw0Etg",
+    "iro4vB3w4rgE",
+    "c8iQ9KEd1h9R",
+    "ZVs_HfxbVCs3",
+    "ipG2Cpb7Jrc7",
+    "3uGfjIdjsCg-",
+    "mTnMbG9vXHkL",
+    "6RYILEoPXaMZ",
+    "PkphS4vSFNvg",
+    "ZBeID4YeMQ9L",
+    "8tvOmmiOOT4o",
+    "XcYaJKT_Pw6T"
+   ],
+   "gpuType": "T4",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.9"
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "0b0d8924f58949a2ba8c5de2dc99d9b2": {
+     "model_module": "@jupyter-widgets/output",
+     "model_module_version": "1.0.0",
+     "model_name": "OutputModel",
+     "state": {
+      "_dom_classes": [],
+      "_model_module": "@jupyter-widgets/output",
+      "_model_module_version": "1.0.0",
+      "_model_name": "OutputModel",
+      "_view_count": null,
+      "_view_module": "@jupyter-widgets/output",
+      "_view_module_version": "1.0.0",
+      "_view_name": "OutputView",
+      "layout": "IPY_MODEL_80873b8fc8734802a2422304e627a233",
+      "msg_id": "",
       "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 600x300 with 2 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
+       {
+        "data": {
+         "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">⠇</span> <span style=\"font-weight: bold\">Authenticating</span>\n</pre>\n",
+         "text/plain": "\u001b[32m⠇\u001b[0m \u001b[1mAuthenticating\u001b[0m\n"
+        },
+        "metadata": {},
+        "output_type": "display_data"
+       }
       ]
+     }
     },
-    {
-      "cell_type": "code",
-      "source": [
-        "perm = np.random.permutation(num_samples)\n",
-        "train_idx, test_idx = perm[:train_test_split], perm[train_test_split:]\n",
-        "X_train, X_test = X[train_idx], X[test_idx]\n",
-        "Y_train, Y_test = Y[train_idx], Y[test_idx]\n",
-        "T_train, T_test = T[train_idx], T[test_idx]\n",
-        "tau_test = tau[test_idx]"
-      ],
-      "metadata": {
-        "id": "3KJJwIwSySzk"
-      },
-      "execution_count": 12,
-      "outputs": []
+    "0c458dab93ee415f839fd216d33b43d9": {
+     "model_module": "@jupyter-widgets/controls",
+     "model_module_version": "1.5.0",
+     "model_name": "DescriptionStyleModel",
+     "state": {
+      "_model_module": "@jupyter-widgets/controls",
+      "_model_module_version": "1.5.0",
+      "_model_name": "DescriptionStyleModel",
+      "_view_count": null,
+      "_view_module": "@jupyter-widgets/base",
+      "_view_module_version": "1.2.0",
+      "_view_name": "StyleView",
+      "description_width": ""
+     }
     },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "### Run CATE estimators with TabPFN as a base model\n",
-        "\n",
-        "We fit three CATE estimators to our synthetic datasets with different choices of base models\n",
-        "\n",
-        "\n",
-        "\n",
-        "*   `s_tabpfn`: TabPFN applied as an `SLearner`\n",
-        "*   `cfdml_tabpfn`: TabPFN applied as a propensity and outcome in `CausalForestDML`\n",
-        "*   `cfdml_default`: `CausalForestDML` with default propensity and outcome models\n",
-        "\n"
-      ],
-      "metadata": {
-        "id": "STYhNc224Zmz"
-      }
+    "0ef1661193d44ef99f7e281cb79c40b5": {
+     "model_module": "@jupyter-widgets/controls",
+     "model_module_version": "1.5.0",
+     "model_name": "HTMLModel",
+     "state": {
+      "_dom_classes": [],
+      "_model_module": "@jupyter-widgets/controls",
+      "_model_module_version": "1.5.0",
+      "_model_name": "HTMLModel",
+      "_view_count": null,
+      "_view_module": "@jupyter-widgets/controls",
+      "_view_module_version": "1.5.0",
+      "_view_name": "HTMLView",
+      "description": "",
+      "description_tooltip": null,
+      "layout": "IPY_MODEL_b15054c98fd8457095b01a54ad491056",
+      "placeholder": "​",
+      "style": "IPY_MODEL_e4a2681db14a43a6836f0fd3ab154509",
+      "value": " 44.3k/? [00:00&lt;00:00, 932kB/s]"
+     }
     },
-    {
-      "cell_type": "code",
-      "source": [
-        "from econml.metalearners import SLearner\n",
-        "from econml.dml import CausalForestDML\n",
-        "from tabpfn import TabPFNClassifier, TabPFNRegressor"
-      ],
-      "metadata": {
-        "id": "-3id6xmIrajj"
-      },
-      "execution_count": 13,
-      "outputs": []
+    "12a2a205bd944f8e8a3643f977c38b56": {
+     "model_module": "@jupyter-widgets/controls",
+     "model_module_version": "1.5.0",
+     "model_name": "FloatProgressModel",
+     "state": {
+      "_dom_classes": [],
+      "_model_module": "@jupyter-widgets/controls",
+      "_model_module_version": "1.5.0",
+      "_model_name": "FloatProgressModel",
+      "_view_count": null,
+      "_view_module": "@jupyter-widgets/controls",
+      "_view_module_version": "1.5.0",
+      "_view_name": "ProgressView",
+      "bar_style": "success",
+      "description": "",
+      "description_tooltip": null,
+      "layout": "IPY_MODEL_96db2596e70f4e809832e39642b8af99",
+      "max": 334951,
+      "min": 0,
+      "orientation": "horizontal",
+      "style": "IPY_MODEL_614ab8ceb45245cf8d11dcb576b3e27d",
+      "value": 334951
+     }
     },
-    {
-      "cell_type": "code",
-      "source": [
-        "s_tabpfn = SLearner(overall_model=TabPFNRegressor())\n",
-        "\n",
-        "s_tabpfn.fit(Y=Y_train, X=X_train, T=T_train)\n",
-        "s_tabpfn_cate = s_tabpfn.effect(X=X_test)"
-      ],
-      "metadata": {
-        "id": "xuZ1kxQP1ZN6",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "8741fedd-5b6e-4900-d856-5774a3348399"
-      },
-      "execution_count": 14,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "/usr/local/lib/python3.12/dist-packages/sklearn/utils/deprecation.py:151: FutureWarning: 'force_all_finite' was renamed to 'ensure_all_finite' in 1.6 and will be removed in 1.8.\n",
-            "  warnings.warn(\n"
-          ]
-        }
-      ]
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-      "cell_type": "code",
-      "source": [
-        "cfdml_tabpfn = CausalForestDML(model_y=TabPFNRegressor(), model_t=TabPFNClassifier(), discrete_treatment=True)\n",
-        "\n",
-        "cfdml_tabpfn.fit(Y=Y_train, X=X_train, T=T_train)\n",
-        "cfdml_tabpfn_cate = cfdml_tabpfn.effect(X=X_test)"
-      ],
-      "metadata": {
-        "id": "1eUVnX-r1waQ"
-      },
-      "execution_count": 15,
-      "outputs": []
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-      "cell_type": "code",
-      "source": [
-        "cfdml_default = CausalForestDML(discrete_treatment=True)\n",
-        "\n",
-        "cfdml_default.fit(Y=Y_train, X=X_train, T=T_train)\n",
-        "cfdml_default_cate = cfdml_default.effect(X=X_test)"
-      ],
-      "metadata": {
-        "id": "R_QEm9P12tlH"
-      },
-      "execution_count": 16,
-      "outputs": []
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-    {
-      "cell_type": "markdown",
-      "source": [
-        "### Evaluate performance in CATE estimation\n",
-        "\n",
-        "We assess how close our predicted individual effects $\\hat{\\tau}(x)$ are to the true effects $\\tau(x)$ using **PEHE** (Precision in Estimation of Heterogeneous Effects).\n",
-        "PEHE is defined as the root-mean-squared-error (RMSE) between predicted and ground truth CATE values.\n",
-        "\n",
-        "$$\\text{PEHE} = \\sqrt{\\frac{1}{n} \\sum [\\widehat{\\tau}(x_i) - \\tau(x_i) ]^2}$$\n"
-      ],
-      "metadata": {
-        "id": "nbsS1tvf7GS1"
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-    {
-      "cell_type": "code",
-      "source": [
-        "from sklearn.metrics import root_mean_squared_error\n",
-        "\n",
-        "s_tabpfn_pehe = root_mean_squared_error(tau_test, s_tabpfn_cate)\n",
-        "cfdml_tabpfn_pehe = root_mean_squared_error(tau_test, cfdml_tabpfn_cate)\n",
-        "cfdml_default_pehe = root_mean_squared_error(tau_test, cfdml_default_cate)\n",
-        "\n",
-        "print(f\"s_tabpfn PEHE: {s_tabpfn_pehe}\")\n",
-        "print(f\"cfdml_tabpfn PEHE: {cfdml_tabpfn_pehe}\")\n",
-        "print(f\"cfdml_default PEHE: {cfdml_default_pehe}\")"
-      ],
-      "metadata": {
-        "id": "LQYrBYLB7F2v",
-        "colab": {
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-      },
-      "execution_count": 17,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "s_tabpfn PEHE: 0.09701367904551404\n",
-            "cfdml_tabpfn PEHE: 0.22240085005502397\n",
-            "cfdml_default PEHE: 0.2537058237154443\n"
-          ]
-        }
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-        "df_test = pd.DataFrame({\"T\": T_test, \"Y\": Y_test, \"tau\": tau_test, **{f\"X{i}\": X_test[:, i] for i in range(num_features)}})\n",
-        "df_test[\"s_tabpfn_pred\"], df_test[\"cfdml_tabpfn_pred\"], df_test[\"cfdml_default_pred\"] = s_tabpfn_cate, cfdml_tabpfn_cate, cfdml_default_cate\n",
-        "\n",
-        "fig, axes = plt.subplots(ncols=3, figsize=(9, 3))\n",
-        "sns.scatterplot(data=df_test, x=\"tau\", y=\"s_tabpfn_pred\", hue=\"T\", ax=axes[0], edgecolor=\"black\", palette=\"Set1\")\n",
-        "sns.scatterplot(data=df_test, x=\"tau\", y=\"cfdml_tabpfn_pred\", hue=\"T\", ax=axes[1], edgecolor=\"black\", palette=\"Set1\")\n",
-        "sns.scatterplot(data=df_test, x=\"tau\", y=\"cfdml_default_pred\", hue=\"T\", ax=axes[2], edgecolor=\"black\", palette=\"Set1\")\n",
-        "fig.tight_layout()"
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-        "# Feedback\n",
-        "\n",
-        "Let us know what you think!\n",
-        "\n",
-        "Write us at Discord: https://discord.gg/qK7AaXPN or just simply create an issue on [GitHub](https://github.com/PriorLabs/tabpfn).\n",
-        "\n",
-        "Thank you for trying out our method! 🎉\n"
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+}
diff --git a/examples/notebooks/TabPFN_Demo_Local.ipynb b/examples/notebooks/TabPFN_Demo_Local.ipynb
index fe05858e2..3d15b0fc7 100644
--- a/examples/notebooks/TabPFN_Demo_Local.ipynb
+++ b/examples/notebooks/TabPFN_Demo_Local.ipynb
@@ -1,6802 +1,6818 @@
 {
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "tisgLOuqzrfo"
-      },
-      "source": [
-        "# TabPFN Hands-On-Demo\n",
-        "\n",
-        "**Welcome to this enhanced and educational walkthrough of TabPFN!**\n",
-        "\n",
-        "TabPFN is a novel machine learning model that is exceptionally fast and requires no hyperparameter tuning. It is particularly powerful for tabular data, which is a common data format in many real-world applications. This notebook will not only demonstrate how to use TabPFN but also provide clear explanations of the underlying concepts.\n",
-        "\n",
-        "**What you will learn:**\n",
-        "\n",
-        "* What TabPFN is and why it's a game-changer for tabular data.\n",
-        "* How to set up and run TabPFN on your local machine or using the client API.\n",
-        "* How to use TabPFN for both classification and regression tasks.\n",
-        "* A comparison of TabPFN's performance against other popular models like XGBoost and RandomForest.\n",
-        "* Advanced features of TabPFN, including handling text data, unsupervised learning, and model interpretability.\n",
-        "\n",
-        "Let's get started!\n",
-        "\n",
-        "\n",
-        "\n",
-        "## Table of Contents\n",
-        "\n",
-        "1.  [Installation](#installation)\n",
-        "2.  [Backend Selection](#backend-selection)\n",
-        "3.  [**Classification with TabPFN**](#classification)\n",
-        "4.  [**Regression with TabPFN**](#regression)\n",
-        "5.  [Handling Text Data](#text-data)\n",
-        "6.  [Unsupervised Learning with TabPFN](#unsupervised-learning)\n",
-        "   - Data Imputation\n",
-        "   - Anomaly Detection\n",
-        "   - Clustering Applications\n",
-        "7.  [Model Interpretability](#interpretability)\n",
-        "   - Feature Importance Analysis\n",
-        "   - Explaining Predictions with SHAP\n",
-        "   - Extracting and Visualizing Embeddings\n",
-        "8.  [Predictive Behavior](#behavior)\n",
-        "9.  [**Time Series Prediction with TabPFN**](#timeseries)\n",
-        "9.  [Using TabPFN to estimate the effect of causal interventions](#causal)\n"
-      ]
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tisgLOuqzrfo"
+   },
+   "source": [
+    "# TabPFN Hands-On-Demo\n",
+    "\n",
+    "**Welcome to this enhanced and educational walkthrough of TabPFN!**\n",
+    "\n",
+    "TabPFN is a novel machine learning model that is exceptionally fast and requires no hyperparameter tuning. It is particularly powerful for tabular data, which is a common data format in many real-world applications. This notebook will not only demonstrate how to use TabPFN but also provide clear explanations of the underlying concepts.\n",
+    "\n",
+    "**What you will learn:**\n",
+    "\n",
+    "* What TabPFN is and why it's a game-changer for tabular data.\n",
+    "* How to set up and run TabPFN on your local machine or using the client API.\n",
+    "* How to use TabPFN for both classification and regression tasks.\n",
+    "* A comparison of TabPFN's performance against other popular models like XGBoost and RandomForest.\n",
+    "* Advanced features of TabPFN, including handling text data, unsupervised learning, and model interpretability.\n",
+    "\n",
+    "Let's get started!\n",
+    "\n",
+    "\n",
+    "\n",
+    "## Table of Contents\n",
+    "\n",
+    "1.  [Installation](#installation)\n",
+    "2.  [Backend Selection](#backend-selection)\n",
+    "3.  [**Classification with TabPFN**](#classification)\n",
+    "4.  [**Regression with TabPFN**](#regression)\n",
+    "5.  [Handling Text Data](#text-data)\n",
+    "6.  [Unsupervised Learning with TabPFN](#unsupervised-learning)\n",
+    "   - Data Imputation\n",
+    "   - Anomaly Detection\n",
+    "   - Clustering Applications\n",
+    "7.  [Model Interpretability](#interpretability)\n",
+    "   - Feature Importance Analysis\n",
+    "   - Explaining Predictions with SHAP\n",
+    "   - Extracting and Visualizing Embeddings\n",
+    "8.  [Predictive Behavior](#behavior)\n",
+    "9.  [**Time Series Prediction with TabPFN**](#timeseries)\n",
+    "9.  [Using TabPFN to estimate the effect of causal interventions](#causal)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "o03aOVAw0Etg"
+   },
+   "source": [
+    "# Installation [Running this cell required!] <a name=\"installation\"></a>\n",
+    "\n",
+    "First, we need to install the necessary libraries. This includes TabPFN itself, as well as other libraries for data manipulation and baseline model comparisons. If you are asked to restart the runtime after installation, please do so.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "collapsed": true,
+    "id": "agAt8X7T0N6P",
+    "jupyter": {
+     "outputs_hidden": true
+    },
+    "outputId": "27bf5620-2f8d-43af-b7e3-9882c3db8a66"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "o03aOVAw0Etg"
-      },
-      "source": [
-        "# Installation [Running this cell required!] <a name=\"installation\"></a>\n",
-        "\n",
-        "First, we need to install the necessary libraries. This includes TabPFN itself, as well as other libraries for data manipulation and baseline model comparisons. If you are asked to restart the runtime after installation, please do so.\n"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
+      "\u001b[2K\u001b[2mResolved \u001b[1m21 packages\u001b[0m \u001b[2min 203ms\u001b[0m\u001b[0m\n",
+      "\u001b[2K\u001b[2mPrepared \u001b[1m1 package\u001b[0m \u001b[2min 1.31s\u001b[0m\u001b[0m\n",
+      "\u001b[2K\u001b[2mInstalled \u001b[1m1 package\u001b[0m \u001b[2min 5ms\u001b[0m\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mcatboost\u001b[0m\u001b[2m==1.2.8\u001b[0m\n",
+      "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
+      "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 102ms\u001b[0m\u001b[0m\n",
+      "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
+      "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 140ms\u001b[0m\u001b[0m\n",
+      "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
+      "\u001b[2K\u001b[2mResolved \u001b[1m34 packages\u001b[0m \u001b[2min 746ms\u001b[0m\u001b[0m\n",
+      "\u001b[2K\u001b[2mPrepared \u001b[1m4 packages\u001b[0m \u001b[2min 78ms\u001b[0m\u001b[0m\n",
+      "\u001b[2K\u001b[2mInstalled \u001b[1m4 packages\u001b[0m \u001b[2min 6ms\u001b[0m\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mbackoff\u001b[0m\u001b[2m==2.2.1\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mpassword-strength\u001b[0m\u001b[2m==0.0.3.post2\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1msseclient-py\u001b[0m\u001b[2m==1.8.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mtabpfn-client\u001b[0m\u001b[2m==0.2.8\u001b[0m\n",
+      "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
+      "\u001b[2K\u001b[2mResolved \u001b[1m91 packages\u001b[0m \u001b[2min 1.47s\u001b[0m\u001b[0m\n",
+      "\u001b[2K\u001b[2mPrepared \u001b[1m18 packages\u001b[0m \u001b[2min 1.07s\u001b[0m\u001b[0m\n",
+      "\u001b[2mUninstalled \u001b[1m1 package\u001b[0m \u001b[2min 4ms\u001b[0m\u001b[0m\n",
+      "\u001b[2K\u001b[2mInstalled \u001b[1m18 packages\u001b[0m \u001b[2min 152ms\u001b[0m\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mautogluon-common\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mautogluon-core\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mautogluon-features\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mautogluon-tabular\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mboto3\u001b[0m\u001b[2m==1.40.67\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mbotocore\u001b[0m\u001b[2m==1.40.67\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1meval-type-backport\u001b[0m\u001b[2m==0.2.2\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mgalois\u001b[0m\u001b[2m==0.4.6\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mjmespath\u001b[0m\u001b[2m==1.0.1\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mkditransform\u001b[0m\u001b[2m==1.2.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mposthog\u001b[0m\u001b[2m==6.9.0\u001b[0m\n",
+      " \u001b[31m-\u001b[39m \u001b[1mrequests\u001b[0m\u001b[2m==2.32.4\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mrequests\u001b[0m\u001b[2m==2.32.5\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1ms3transfer\u001b[0m\u001b[2m==0.14.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mshapiq\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1msparse-transform\u001b[0m\u001b[2m==0.2.1\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mtabpfn\u001b[0m\u001b[2m==6.0.4\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mtabpfn-common-utils\u001b[0m\u001b[2m==0.2.7\u001b[0m\n",
+      " \u001b[32m+\u001b[39m \u001b[1mtabpfn-extensions\u001b[0m\u001b[2m==0.2.0\u001b[0m\n",
+      "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
+      "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 168ms\u001b[0m\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "## Base library Installation\n",
+    "# Install Baselines for model comparison\n",
+    "!uv pip install catboost xgboost\n",
+    "\n",
+    "# Install the datasets library for loading example data\n",
+    "!uv pip install datasets\n",
+    "\n",
+    "# Install rich for better and more readable printing\n",
+    "!uv pip install rich\n",
+    "\n",
+    "## TabPFN Installation optimized for Google Colab\n",
+    "# Install the TabPFN Client library\n",
+    "!uv pip install tabpfn-client\n",
+    "\n",
+    "# Install TabPFN extensions for additional functionalities\n",
+    "!uv pip install 'tabpfn-extensions[all]'\n",
+    "\n",
+    "# Install tabpfn\n",
+    "!uv pip install tabpfn"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "p8RTKDLrJAAr"
+   },
+   "source": [
+    "***Note: remember to restart the runtime after the installation.***"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "iro4vB3w4rgE"
+   },
+   "source": [
+    "# Necessary Imports for the Notebook [Running this cell required!]\n",
+    "\n",
+    "Now that the libraries are installed, let's import all the necessary modules for this notebook.\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "id": "uVEqqRwQ4W1H"
+   },
+   "outputs": [],
+   "source": [
+    "# Standard Library Imports\n",
+    "\n",
+    "# TabPFN and Extensions\n",
+    "\n",
+    "try:\n",
+    "    from tabpfn_extensions.post_hoc_ensembles.sklearn_interface import (\n",
+    "        AutoTabPFNClassifier,\n",
+    "    )\n",
+    "\n",
+    "    from tabpfn import TabPFNClassifier, TabPFNRegressor\n",
+    "except ImportError:\n",
+    "    raise ImportError(\n",
+    "        \"Warning: Could not import TabPFN / TabPFN extensions. Please run installation above and restart the session afterwards (Runtime > Restart Session).\"\n",
+    "    )\n",
+    "\n",
+    "# Data Science & Visualization\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import torch\n",
+    "\n",
+    "# Other ML Models\n",
+    "from catboost import CatBoostClassifier, CatBoostRegressor\n",
+    "\n",
+    "# Notebook UI/Display\n",
+    "from IPython.display import Markdown, display\n",
+    "from rich.console import Console\n",
+    "from rich.panel import Panel\n",
+    "from rich.prompt import Prompt\n",
+    "from rich.rule import Rule\n",
+    "from sklearn.compose import make_column_selector, make_column_transformer\n",
+    "\n",
+    "# Scikit-Learn: Data & Preprocessing\n",
+    "from sklearn.datasets import fetch_openml, load_breast_cancer\n",
+    "\n",
+    "# Scikit-Learn: Models\n",
+    "from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor\n",
+    "from sklearn.metrics import mean_squared_error, roc_auc_score\n",
+    "from sklearn.model_selection import (\n",
+    "    KFold,\n",
+    "    StratifiedKFold,\n",
+    "    cross_val_score,\n",
+    "    train_test_split,\n",
+    ")\n",
+    "from sklearn.pipeline import make_pipeline\n",
+    "from sklearn.preprocessing import LabelEncoder, OrdinalEncoder\n",
+    "from xgboost import XGBClassifier, XGBRegressor\n",
+    "\n",
+    "# This transformer will be used to handle categorical features for the baseline models\n",
+    "column_transformer = make_column_transformer(\n",
+    "    (\n",
+    "        OrdinalEncoder(handle_unknown=\"use_encoded_value\", unknown_value=-1),\n",
+    "        make_column_selector(dtype_include=[\"object\", \"category\"]),\n",
+    "    ),\n",
+    "    remainder=\"passthrough\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "4I4uUwflTY3i"
+   },
+   "source": [
+    "# Backend Selection [Running this cell required!] <a name=\"backend-selection\"></a>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "QUq82Au7UdXk"
+   },
+   "source": [
+    "\n",
+    "TabPFN can be run in two ways: locally on your machine (if you have a GPU) or by using the TabPFN client, which sends the data to a server for computation.\n",
+    "In your project you would either use the **local** version (which requires a GPU) with:\n",
+    "```python\n",
+    "# Simple import for TabPFN\n",
+    "from tabpfn import TabPFNClassifier\n",
+    "\n",
+    "# Now you can use it like any other sklearn classifier\n",
+    "# model = TabPFNClassifier()\n",
+    "print(\"TabPFNClassifier imported successfully.\")\n",
+    "```\n",
+    "\n",
+    "or the **client** API (which uses a remote server):\n",
+    "\n",
+    "```python\n",
+    "# Simple import for TabPFN\n",
+    "from tabpfn_client import TabPFNClassifier\n",
+    "\n",
+    "# Now you can use it like any other sklearn classifier\n",
+    "# model = TabPFNClassifier()\n",
+    "print(\"TabPFNClassifier imported successfully.\")\n",
+    "```\n",
+    "\n",
+    "If you select **local** and it's your first time using the model, you'll need to accept the license agreement and log into Hugging Face.\n",
+    "You'll be prompted with instructions on how to do this the first time you fit the model.\n",
+    "\n",
+    "For demonstration purposes, the cell below provides an interactive way to switch between local mode and the client:\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 694,
+     "referenced_widgets": [
+      "0b0d8924f58949a2ba8c5de2dc99d9b2",
+      "80873b8fc8734802a2422304e627a233"
+     ]
     },
+    "id": "pJVAXg2YoDdF",
+    "outputId": "0857a1f6-4dcf-47b3-e156-3ff23157363f"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 1,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "collapsed": true,
-        "id": "agAt8X7T0N6P",
-        "outputId": "27bf5620-2f8d-43af-b7e3-9882c3db8a66"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2K\u001b[2mResolved \u001b[1m21 packages\u001b[0m \u001b[2min 203ms\u001b[0m\u001b[0m\n",
-            "\u001b[2K\u001b[2mPrepared \u001b[1m1 package\u001b[0m \u001b[2min 1.31s\u001b[0m\u001b[0m\n",
-            "\u001b[2K\u001b[2mInstalled \u001b[1m1 package\u001b[0m \u001b[2min 5ms\u001b[0m\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mcatboost\u001b[0m\u001b[2m==1.2.8\u001b[0m\n",
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 102ms\u001b[0m\u001b[0m\n",
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 140ms\u001b[0m\u001b[0m\n",
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2K\u001b[2mResolved \u001b[1m34 packages\u001b[0m \u001b[2min 746ms\u001b[0m\u001b[0m\n",
-            "\u001b[2K\u001b[2mPrepared \u001b[1m4 packages\u001b[0m \u001b[2min 78ms\u001b[0m\u001b[0m\n",
-            "\u001b[2K\u001b[2mInstalled \u001b[1m4 packages\u001b[0m \u001b[2min 6ms\u001b[0m\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mbackoff\u001b[0m\u001b[2m==2.2.1\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mpassword-strength\u001b[0m\u001b[2m==0.0.3.post2\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1msseclient-py\u001b[0m\u001b[2m==1.8.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mtabpfn-client\u001b[0m\u001b[2m==0.2.8\u001b[0m\n",
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2K\u001b[2mResolved \u001b[1m91 packages\u001b[0m \u001b[2min 1.47s\u001b[0m\u001b[0m\n",
-            "\u001b[2K\u001b[2mPrepared \u001b[1m18 packages\u001b[0m \u001b[2min 1.07s\u001b[0m\u001b[0m\n",
-            "\u001b[2mUninstalled \u001b[1m1 package\u001b[0m \u001b[2min 4ms\u001b[0m\u001b[0m\n",
-            "\u001b[2K\u001b[2mInstalled \u001b[1m18 packages\u001b[0m \u001b[2min 152ms\u001b[0m\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mautogluon-common\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mautogluon-core\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mautogluon-features\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mautogluon-tabular\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mboto3\u001b[0m\u001b[2m==1.40.67\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mbotocore\u001b[0m\u001b[2m==1.40.67\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1meval-type-backport\u001b[0m\u001b[2m==0.2.2\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mgalois\u001b[0m\u001b[2m==0.4.6\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mjmespath\u001b[0m\u001b[2m==1.0.1\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mkditransform\u001b[0m\u001b[2m==1.2.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mposthog\u001b[0m\u001b[2m==6.9.0\u001b[0m\n",
-            " \u001b[31m-\u001b[39m \u001b[1mrequests\u001b[0m\u001b[2m==2.32.4\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mrequests\u001b[0m\u001b[2m==2.32.5\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1ms3transfer\u001b[0m\u001b[2m==0.14.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mshapiq\u001b[0m\u001b[2m==1.4.0\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1msparse-transform\u001b[0m\u001b[2m==0.2.1\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mtabpfn\u001b[0m\u001b[2m==6.0.4\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mtabpfn-common-utils\u001b[0m\u001b[2m==0.2.7\u001b[0m\n",
-            " \u001b[32m+\u001b[39m \u001b[1mtabpfn-extensions\u001b[0m\u001b[2m==0.2.0\u001b[0m\n",
-            "\u001b[2mUsing Python 3.12.12 environment at: /usr\u001b[0m\n",
-            "\u001b[2mAudited \u001b[1m1 package\u001b[0m \u001b[2min 168ms\u001b[0m\u001b[0m\n"
-          ]
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">╭────────────────────────────────╮\n",
+       "│ <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">TabPFN Demo: Backend Selection</span> │\n",
+       "╰────────────────────────────────╯\n",
+       "</pre>\n"
       ],
-      "source": [
-        "## Base library Installation\n",
-        "# Install Baselines for model comparison\n",
-        "!uv pip install catboost xgboost\n",
-        "\n",
-        "# Install the datasets library for loading example data\n",
-        "!uv pip install datasets\n",
-        "\n",
-        "# Install rich for better and more readable printing\n",
-        "!uv pip install rich\n",
-        "\n",
-        "## TabPFN Installation optimized for Google Colab\n",
-        "# Install the TabPFN Client library\n",
-        "!uv pip install tabpfn-client\n",
-        "\n",
-        "# Install TabPFN extensions for additional functionalities\n",
-        "!uv pip install tabpfn-extensions[all]\n",
-        "\n",
-        "# Install tabpfn\n",
-        "!uv pip install tabpfn"
+      "text/plain": [
+       "╭────────────────────────────────╮\n",
+       "│ \u001b[1;35mTabPFN Demo: Backend Selection\u001b[0m │\n",
+       "╰────────────────────────────────╯\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "p8RTKDLrJAAr"
-      },
-      "source": [
-        "***Note: remember to restart the runtime after the installation.***"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "This script can run TabPFN using one of two backends:\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "This script can run TabPFN using one of two backends:\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "iro4vB3w4rgE"
-      },
-      "source": [
-        "# Necessary Imports for the Notebook [Running this cell required!]\n",
-        "\n",
-        "Now that the libraries are installed, let's import all the necessary modules for this notebook.\n",
-        "\n",
-        "\n"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span><span style=\"font-weight: bold\">. local:</span> Uses a local GPU <span style=\"font-weight: bold\">(</span>NVIDIA<span style=\"font-weight: bold\">)</span>. Requires CUDA.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "  \u001b[1;36m1\u001b[0m\u001b[1m. local:\u001b[0m Uses a local GPU \u001b[1m(\u001b[0mNVIDIA\u001b[1m)\u001b[0m. Requires CUDA.\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 2,
-      "metadata": {
-        "id": "uVEqqRwQ4W1H"
-      },
-      "outputs": [],
-      "source": [
-        "# Standard Library Imports\n",
-        "\n",
-        "# TabPFN and Extensions\n",
-        "\n",
-        "try:\n",
-        "    from tabpfn_extensions.post_hoc_ensembles.sklearn_interface import (\n",
-        "        AutoTabPFNClassifier,\n",
-        "    )\n",
-        "\n",
-        "    from tabpfn import TabPFNClassifier, TabPFNRegressor\n",
-        "except ImportError:\n",
-        "    raise ImportError(\n",
-        "        \"Warning: Could not import TabPFN / TabPFN extensions. Please run installation above and restart the session afterwards (Runtime > Restart Session).\"\n",
-        "    )\n",
-        "\n",
-        "# Data Science & Visualization\n",
-        "import matplotlib.pyplot as plt\n",
-        "import numpy as np\n",
-        "import pandas as pd\n",
-        "import torch\n",
-        "\n",
-        "# Other ML Models\n",
-        "from catboost import CatBoostClassifier, CatBoostRegressor\n",
-        "\n",
-        "# Notebook UI/Display\n",
-        "from IPython.display import Markdown, display\n",
-        "from rich.console import Console\n",
-        "from rich.panel import Panel\n",
-        "from rich.prompt import Prompt\n",
-        "from rich.rule import Rule\n",
-        "from sklearn.compose import make_column_selector, make_column_transformer\n",
-        "\n",
-        "# Scikit-Learn: Data & Preprocessing\n",
-        "from sklearn.datasets import fetch_openml, load_breast_cancer\n",
-        "\n",
-        "# Scikit-Learn: Models\n",
-        "from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor\n",
-        "from sklearn.metrics import mean_squared_error, roc_auc_score\n",
-        "from sklearn.model_selection import (\n",
-        "    KFold,\n",
-        "    StratifiedKFold,\n",
-        "    cross_val_score,\n",
-        "    train_test_split,\n",
-        ")\n",
-        "from sklearn.pipeline import make_pipeline\n",
-        "from sklearn.preprocessing import LabelEncoder, OrdinalEncoder\n",
-        "from xgboost import XGBClassifier, XGBRegressor\n",
-        "\n",
-        "# This transformer will be used to handle categorical features for the baseline models\n",
-        "column_transformer = make_column_transformer(\n",
-        "    (\n",
-        "        OrdinalEncoder(handle_unknown=\"use_encoded_value\", unknown_value=-1),\n",
-        "        make_column_selector(dtype_include=[\"object\", \"category\"]),\n",
-        "    ),\n",
-        "    remainder=\"passthrough\",\n",
-        ")"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span><span style=\"font-weight: bold\">. client:</span> Uses the TabPFN API. Requires an internet connection and a free account.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "  \u001b[1;36m2\u001b[0m\u001b[1m. client:\u001b[0m Uses the TabPFN API. Requires an internet connection and a free account.\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "4I4uUwflTY3i"
-      },
-      "source": [
-        "# Backend Selection [Running this cell required!] <a name=\"backend-selection\"></a>"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<span style=\"font-weight: bold\">Choose your backend</span> - If not field to enter is shown restart the cell. <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">[client/local]</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">(client)</span>: </pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "\u001b[1mChoose your backend\u001b[0m - If not field to enter is shown restart the cell. \u001b[1;35m[client/local]\u001b[0m \u001b[1;36m(client)\u001b[0m: "
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "QUq82Au7UdXk"
-      },
-      "source": [
-        "\n",
-        "TabPFN can be run in two ways: locally on your machine (if you have a GPU) or by using the TabPFN client, which sends the data to a server for computation.\n",
-        "In your project you would either use the **local** version (which requires a GPU) with:\n",
-        "```python\n",
-        "# Simple import for TabPFN\n",
-        "from tabpfn import TabPFNClassifier\n",
-        "\n",
-        "# Now you can use it like any other sklearn classifier\n",
-        "# model = TabPFNClassifier()\n",
-        "print(\"TabPFNClassifier imported successfully.\")\n",
-        "```\n",
-        "\n",
-        "or the **client** API (which uses a remote server):\n",
-        "\n",
-        "```python\n",
-        "# Simple import for TabPFN\n",
-        "from tabpfn_client import TabPFNClassifier\n",
-        "\n",
-        "# Now you can use it like any other sklearn classifier\n",
-        "# model = TabPFNClassifier()\n",
-        "print(\"TabPFNClassifier imported successfully.\")\n",
-        "```\n",
-        "\n",
-        "If you select **local** and it's your first time using the model, you'll need to accept the license agreement and log into Hugging Face.\n",
-        "You'll be prompted with instructions on how to do this the first time you fit the model.\n",
-        "\n",
-        "For demonstration purposes, the cell below provides an interactive way to switch between local mode and the client:\n"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "client\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 4,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 694,
-          "referenced_widgets": [
-            "0b0d8924f58949a2ba8c5de2dc99d9b2",
-            "80873b8fc8734802a2422304e627a233"
-          ]
-        },
-        "id": "pJVAXg2YoDdF",
-        "outputId": "0857a1f6-4dcf-47b3-e156-3ff23157363f"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "╭────────────────────────────────╮\n",
-              "│ \u001b[1;35mTabPFN Demo: Backend Selection\u001b[0m │\n",
-              "╰────────────────────────────────╯\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">╭────────────────────────────────╮\n",
-              "│ <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">TabPFN Demo: Backend Selection</span> │\n",
-              "╰────────────────────────────────╯\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\n",
-              "This script can run TabPFN using one of two backends:\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-              "This script can run TabPFN using one of two backends:\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "  \u001b[1;36m1\u001b[0m\u001b[1m. local:\u001b[0m Uses a local GPU \u001b[1m(\u001b[0mNVIDIA\u001b[1m)\u001b[0m. Requires CUDA.\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span><span style=\"font-weight: bold\">. local:</span> Uses a local GPU <span style=\"font-weight: bold\">(</span>NVIDIA<span style=\"font-weight: bold\">)</span>. Requires CUDA.\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "  \u001b[1;36m2\u001b[0m\u001b[1m. client:\u001b[0m Uses the TabPFN API. Requires an internet connection and a free account.\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span><span style=\"font-weight: bold\">. client:</span> Uses the TabPFN API. Requires an internet connection and a free account.\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\n",
-              "\u001b[1mChoose your backend\u001b[0m - If not field to enter is shown restart the cell. \u001b[1;35m[client/local]\u001b[0m \u001b[1;36m(client)\u001b[0m: "
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-              "<span style=\"font-weight: bold\">Choose your backend</span> - If not field to enter is shown restart the cell. <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">[client/local]</span> <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">(client)</span>: </pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "client\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\n",
-              "✅ You have selected the \u001b[32m'\u001b[0m\u001b[1;32mclient\u001b[0m\u001b[32m'\u001b[0m backend.\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-              "✅ You have selected the <span style=\"color: #008000; text-decoration-color: #008000\">'</span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">client</span><span style=\"color: #008000; text-decoration-color: #008000\">'</span> backend.\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\u001b[92m──────────────────────────────────────────── \u001b[0m\u001b[1mSetting up \u001b[0m\u001b[1;36mclient\u001b[0m\u001b[1m backend\u001b[0m\u001b[92m ────────────────────────────────────────────\u001b[0m\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">──────────────────────────────────────────── </span><span style=\"font-weight: bold\">Setting up </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">client</span><span style=\"font-weight: bold\"> backend</span><span style=\"color: #00ff00; text-decoration-color: #00ff00\"> ────────────────────────────────────────────</span>\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "Attempting client backend setup\u001b[33m...\u001b[0m\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Attempting client backend setup<span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "Importing TabPFN client library\u001b[33m...\u001b[0m\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Importing TabPFN client library<span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\n",
-              "\u001b[1;34m########  ########   ###  #########  #########       ###         #####     ########  ########\u001b[0m\n",
-              "\u001b[1;34m     ###        ##   ###  ###   ###        ###       ###        ###  ###   ##   ###  ###     \u001b[0m\n",
-              "\u001b[1;34m########  #######    ###  ###   ###  #######         ###        ########   ######    ########\u001b[0m\n",
-              "\u001b[1;34m###       ###   ##   ###  ###   ###  ###   ###       ###        ###  ###   ##   ###       ###\u001b[0m\n",
-              "\u001b[1;34m###       ###   ##   ###  #########  ###   ###       ########   ###  ###   ########  ########                      \u001b[0m\n",
-              "\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-              "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">########  ########   ###  #########  #########       ###         #####     ########  ########</span>\n",
-              "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">     ###        ##   ###  ###   ###        ###       ###        ###  ###   ##   ###  ###     </span>\n",
-              "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">########  #######    ###  ###   ###  #######         ###        ########   ######    ########</span>\n",
-              "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">###       ###   ##   ###  ###   ###  ###   ###       ###        ###  ###   ##   ###       ###</span>\n",
-              "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">###       ###   ##   ###  #########  ###   ###       ########   ###  ###   ########  ########                      </span>\n",
-              "\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\u001b[2mThanks for being part of the journey\u001b[0m\n",
-              "\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">Thanks for being part of the journey</span>\n",
-              "\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "  TabPFN is under active development, please help us improve and report any bugs/ideas you find.\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  TabPFN is under active development, please help us improve and report any bugs/ideas you find.\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "  \u001b[34mReport issues: \u001b[0m\u001b[4;34mhttps://github.com/priorlabs/tabpfn-client/issues\u001b[0m\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #000080; text-decoration-color: #000080\">Report issues: </span><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">https://github.com/priorlabs/tabpfn-client/issues</span>\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "  \u001b[34mPress Ctrl+C anytime to exit\u001b[0m\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #000080; text-decoration-color: #000080\">Press Ctrl+C anytime to exit</span>\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "\n",
-            "Opening browser for login. Please complete the login/registration process in your browser and return here.\n",
-            "\n",
-            "\n",
-            "Could not open browser automatically. Falling back to command-line login...\n",
-            "\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\n",
-              "\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-              "\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\u001b[1;34m[1]   \u001b[0m\u001b[1;34m \u001b[0m Create a TabPFN account     \n",
-              "\u001b[1;34m[2]   \u001b[0m\u001b[1;34m \u001b[0m Login to your TabPFN account\n",
-              "\u001b[1;34m[q]   \u001b[0m\u001b[1;34m \u001b[0m Quit                        \n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">[1]    </span> Create a TabPFN account     \n",
-              "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">[2]    </span> Login to your TabPFN account\n",
-              "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">[q]    </span> Quit                        \n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\n",
-              "\u001b[1;34m→\u001b[0m Choose \u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m/\u001b[1;36m2\u001b[0m/q\u001b[1m)\u001b[0m: "
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-              "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">→</span> Choose <span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/q<span style=\"font-weight: bold\">)</span>: </pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "2\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\n",
-              "\u001b[1mLogin\u001b[0m\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
-              "<span style=\"font-weight: bold\">Login</span>\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "Email: "
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Email: </pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "noah@priorlabs.ai\n",
-            "Password: ··········\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "Output()"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "0b0d8924f58949a2ba8c5de2dc99d9b2"
-            }
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\u001b[1;32mLogin successful!\u001b[0m\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Login successful!</span>\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "\u001b[1;32m✅ TabPFN \u001b[0m\u001b[1;32m(\u001b[0m\u001b[1;32mclient\u001b[0m\u001b[1;32m)\u001b[0m\u001b[1;32m initialized.\u001b[0m\n"
-            ],
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">✅ TabPFN (client) initialized.</span>\n",
-              "</pre>\n"
-            ]
-          },
-          "metadata": {}
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "✅ You have selected the <span style=\"color: #008000; text-decoration-color: #008000\">'</span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">client</span><span style=\"color: #008000; text-decoration-color: #008000\">'</span> backend.\n",
+       "</pre>\n"
       ],
-      "source": [
-        "console = Console()\n",
-        "\n",
-        "console.print(Panel.fit(\"[bold magenta]TabPFN Demo: Backend Selection[/bold magenta]\"))\n",
-        "console.print(\"\\nThis script can run TabPFN using one of two backends:\")\n",
-        "console.print(\"  [bold]1. local:[/bold] Uses a local GPU (NVIDIA). Requires CUDA.\")\n",
-        "console.print(\n",
-        "    \"  [bold]2. client:[/bold] Uses the TabPFN API. Requires an internet connection and a free account.\"\n",
-        ")\n",
-        "\n",
-        "backend = Prompt.ask(\n",
-        "    \"\\n[bold]Choose your backend[/bold] - If not field to enter is shown restart the cell.\",\n",
-        "    choices=[\"client\", \"local\"],\n",
-        "    default=\"client\",\n",
-        ")\n",
-        "\n",
-        "console.print(\n",
-        "    f\"\\n✅ You have selected the '[bold green]{backend}[/bold green]' backend.\"\n",
-        ")\n",
-        "\n",
-        "console.print(Rule(f\"[bold]Setting up [cyan]{backend}[/cyan] backend[/bold]\"))\n",
-        "\n",
-        "if backend == \"local\":\n",
-        "    !uv pip install huggingface_hub\n",
-        "\n",
-        "    console.print(\"Attempting local backend setup...\")\n",
-        "    import torch\n",
-        "\n",
-        "    if not torch.cuda.is_available():\n",
-        "        console.print(\n",
-        "            \"[bold red]Error:[/bold red] GPU device not found. For fast training, please enable GPU.\",\n",
-        "            style=\"red\",\n",
-        "        )\n",
-        "        console.print(\n",
-        "            \"In Colab: Go to [bold]Runtime -> Change runtime type -> Hardware accelerator -> GPU.[/bold]\",\n",
-        "            style=\"yellow\",\n",
-        "        )\n",
-        "        raise SystemError(\"GPU device not found.\")\n",
-        "    console.print(\n",
-        "        \"[bold green]✅ GPU is available.[/bold green] Importing local TabPFN library...\"\n",
-        "    )\n",
-        "\n",
-        "    from tabpfn import TabPFNClassifier, TabPFNRegressor\n",
-        "\n",
-        "    console.print(\"[bold green]✅ TabPFN (local) imported successfully.[/bold green]\")\n",
-        "elif backend == \"client\":\n",
-        "    console.print(\"Attempting client backend setup...\")\n",
-        "    console.print(\"Importing TabPFN client library...\")\n",
-        "    from tabpfn_client import TabPFNClassifier, TabPFNRegressor, init\n",
-        "\n",
-        "    init()\n",
-        "    console.print(\"[bold green]✅ TabPFN (client) initialized.[/bold green]\")"
+      "text/plain": [
+       "\n",
+       "✅ You have selected the \u001b[32m'\u001b[0m\u001b[1;32mclient\u001b[0m\u001b[32m'\u001b[0m backend.\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "c8iQ9KEd1h9R"
-      },
-      "source": [
-        "# Classification with TabPFN <a name=\"classification\"></a>\n",
-        "\n",
-        "Now, let's dive into a practical example of using TabPFN for a classification task. We will use the well-known Parkinson's Disease dataset. The goal is to predict the presence of Parkinson's disease based on various voice measurements.\n",
-        "\n",
-        "We will compare TabPFN's performance against other popular machine learning models: RandomForest, XGBoost, and CatBoost. The performance metric we will use is the [ROC AUC](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html) score.\n"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">──────────────────────────────────────────── </span><span style=\"font-weight: bold\">Setting up </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">client</span><span style=\"font-weight: bold\"> backend</span><span style=\"color: #00ff00; text-decoration-color: #00ff00\"> ────────────────────────────────────────────</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[92m──────────────────────────────────────────── \u001b[0m\u001b[1mSetting up \u001b[0m\u001b[1;36mclient\u001b[0m\u001b[1m backend\u001b[0m\u001b[92m ────────────────────────────────────────────\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "source": [
-        "### **Loading Parkinson’s Disease Dataset**\n",
-        "\n",
-        "**Source:**  \n",
-        "The dataset was created by _Max Little_ of the **University of Oxford**, in collaboration with the **National Centre for Voice and Speech**, Denver, Colorado. The dataset consists of biomedical voice measurements collected from individuals, and the original study published the feature extraction methods for general voice disorders.\n",
-        "\n",
-        "### **Dataset Overview**\n",
-        "\n",
-        "-   **Number of subjects:** 31\n",
-        "    \n",
-        "-   **Number of Parkinson’s disease (PD) patients:** 23\n",
-        "    \n",
-        "-   **Total recordings:** 195 voice samples\n",
-        "    \n",
-        "-   **Goal:** To discriminate healthy individuals (status = 0) from those with Parkinson’s disease (status = 1).\n",
-        "    \n",
-        "-   **Identifier column:** `name` (subject name and recording number)\n",
-        "    \n",
-        "\n",
-        "<details>\n",
-        "If you use this dataset, please cite:\n",
-        "\n",
-        "> Max A. Little, Patrick E. McSharry, Eric J. Hunter, Lorraine O. Ramig (2008).  \n",
-        "> _Suitability of dysphonia measurements for telemonitoring of Parkinson's disease._  \n",
-        "> IEEE Transactions on Biomedical Engineering.\n",
-        "\n",
-        "* * *\n",
-        "\n",
-        "\n",
-        "\n",
-        "* * *\n",
-        "\n",
-        "### **Attribute Information**\n",
-        "\n",
-        "Each row corresponds to a voice recording, and each column represents a distinct biomedical voice measure.\n",
-        "\n",
-        "**Feature Name**\n",
-        "\n",
-        "**Description**\n",
-        "\n",
-        "`name`\n",
-        "\n",
-        "ASCII subject name and recording number\n",
-        "\n",
-        "`MDVP:Fo(Hz)`\n",
-        "\n",
-        "Average vocal fundamental frequency\n",
-        "\n",
-        "`MDVP:Fhi(Hz)`\n",
-        "\n",
-        "Maximum vocal fundamental frequency\n",
-        "\n",
-        "`MDVP:Flo(Hz)`\n",
-        "\n",
-        "Minimum vocal fundamental frequency\n",
-        "\n",
-        "`MDVP:Jitter(%)`, `MDVP:Jitter(Abs)`, `MDVP:RAP`, `MDVP:PPQ`, `Jitter:DDP`\n",
-        "\n",
-        "Measures of variation in fundamental frequency\n",
-        "\n",
-        "`MDVP:Shimmer`, `MDVP:Shimmer(dB)`, `Shimmer:APQ3`, `Shimmer:APQ5`, `MDVP:APQ`, `Shimmer:DDA`\n",
-        "\n",
-        "Measures of variation in amplitude\n",
-        "\n",
-        "`NHR`, `HNR`\n",
-        "\n",
-        "Ratios of noise to tonal components in the voice\n",
-        "\n",
-        "`status`\n",
-        "\n",
-        "Health status of the subject (`0` = healthy, `1` = Parkinson’s disease)\n",
-        "\n",
-        "`RPDE`, `D2`\n",
-        "\n",
-        "Nonlinear dynamical complexity measures\n",
-        "\n",
-        "`DFA`\n",
-        "\n",
-        "Signal fractal scaling exponent\n",
-        "\n",
-        "`spread1`, `spread2`, `PPE`\n",
-        "\n",
-        "Nonlinear measures of fundamental frequency variation\n",
-        "</details>\n"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Attempting client backend setup<span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
+       "</pre>\n"
       ],
-      "metadata": {
-        "id": "PNtRCHyLG1D5"
-      }
+      "text/plain": [
+       "Attempting client backend setup\u001b[33m...\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 5,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 423
-        },
-        "id": "tTQe5IprKLV5",
-        "outputId": "2289a6e5-6cac-4c72-8203-f638f2acb520"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "     MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
-              "0        119.992       157.302        74.997         0.00784   \n",
-              "1        122.400       148.650       113.819         0.00968   \n",
-              "2        116.682       131.111       111.555         0.01050   \n",
-              "3        116.676       137.871       111.366         0.00997   \n",
-              "4        116.014       141.781       110.655         0.01284   \n",
-              "..           ...           ...           ...             ...   \n",
-              "190      174.188       230.978        94.261         0.00459   \n",
-              "191      209.516       253.017        89.488         0.00564   \n",
-              "192      174.688       240.005        74.287         0.01360   \n",
-              "193      198.764       396.961        74.904         0.00740   \n",
-              "194      214.289       260.277        77.973         0.00567   \n",
-              "\n",
-              "     MDVP:Jitter(Abs)  MDVP:RAP  MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  \\\n",
-              "0             0.00007   0.00370   0.00554     0.01109       0.04374   \n",
-              "1             0.00008   0.00465   0.00696     0.01394       0.06134   \n",
-              "2             0.00009   0.00544   0.00781     0.01633       0.05233   \n",
-              "3             0.00009   0.00502   0.00698     0.01505       0.05492   \n",
-              "4             0.00011   0.00655   0.00908     0.01966       0.06425   \n",
-              "..                ...       ...       ...         ...           ...   \n",
-              "190           0.00003   0.00263   0.00259     0.00790       0.04087   \n",
-              "191           0.00003   0.00331   0.00292     0.00994       0.02751   \n",
-              "192           0.00008   0.00624   0.00564     0.01873       0.02308   \n",
-              "193           0.00004   0.00370   0.00390     0.01109       0.02296   \n",
-              "194           0.00003   0.00295   0.00317     0.00885       0.01884   \n",
-              "\n",
-              "     MDVP:Shimmer(dB)  ...  MDVP:APQ  Shimmer:DDA      NHR     HNR      RPDE  \\\n",
-              "0               0.426  ...   0.02971      0.06545  0.02211  21.033  0.414783   \n",
-              "1               0.626  ...   0.04368      0.09403  0.01929  19.085  0.458359   \n",
-              "2               0.482  ...   0.03590      0.08270  0.01309  20.651  0.429895   \n",
-              "3               0.517  ...   0.03772      0.08771  0.01353  20.644  0.434969   \n",
-              "4               0.584  ...   0.04465      0.10470  0.01767  19.649  0.417356   \n",
-              "..                ...  ...       ...          ...      ...     ...       ...   \n",
-              "190             0.405  ...   0.02745      0.07008  0.02764  19.517  0.448439   \n",
-              "191             0.263  ...   0.01879      0.04812  0.01810  19.147  0.431674   \n",
-              "192             0.256  ...   0.01667      0.03804  0.10715  17.883  0.407567   \n",
-              "193             0.241  ...   0.01588      0.03794  0.07223  19.020  0.451221   \n",
-              "194             0.190  ...   0.01373      0.03078  0.04398  21.209  0.462803   \n",
-              "\n",
-              "          DFA   spread1   spread2        D2       PPE  \n",
-              "0    0.815285 -4.813031  0.266482  2.301442  0.284654  \n",
-              "1    0.819521 -4.075192  0.335590  2.486855  0.368674  \n",
-              "2    0.825288 -4.443179  0.311173  2.342259  0.332634  \n",
-              "3    0.819235 -4.117501  0.334147  2.405554  0.368975  \n",
-              "4    0.823484 -3.747787  0.234513  2.332180  0.410335  \n",
-              "..        ...       ...       ...       ...       ...  \n",
-              "190  0.657899 -6.538586  0.121952  2.657476  0.133050  \n",
-              "191  0.683244 -6.195325  0.129303  2.784312  0.168895  \n",
-              "192  0.655683 -6.787197  0.158453  2.679772  0.131728  \n",
-              "193  0.643956 -6.744577  0.207454  2.138608  0.123306  \n",
-              "194  0.664357 -5.724056  0.190667  2.555477  0.148569  \n",
-              "\n",
-              "[195 rows x 22 columns]"
-            ],
-            "text/html": [
-              "\n",
-              "  <div id=\"df-d52120d9-7d31-4822-867b-72c4af95f0a7\" class=\"colab-df-container\">\n",
-              "    <div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>MDVP:Fo(Hz)</th>\n",
-              "      <th>MDVP:Fhi(Hz)</th>\n",
-              "      <th>MDVP:Flo(Hz)</th>\n",
-              "      <th>MDVP:Jitter(%)</th>\n",
-              "      <th>MDVP:Jitter(Abs)</th>\n",
-              "      <th>MDVP:RAP</th>\n",
-              "      <th>MDVP:PPQ</th>\n",
-              "      <th>Jitter:DDP</th>\n",
-              "      <th>MDVP:Shimmer</th>\n",
-              "      <th>MDVP:Shimmer(dB)</th>\n",
-              "      <th>...</th>\n",
-              "      <th>MDVP:APQ</th>\n",
-              "      <th>Shimmer:DDA</th>\n",
-              "      <th>NHR</th>\n",
-              "      <th>HNR</th>\n",
-              "      <th>RPDE</th>\n",
-              "      <th>DFA</th>\n",
-              "      <th>spread1</th>\n",
-              "      <th>spread2</th>\n",
-              "      <th>D2</th>\n",
-              "      <th>PPE</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>119.992</td>\n",
-              "      <td>157.302</td>\n",
-              "      <td>74.997</td>\n",
-              "      <td>0.00784</td>\n",
-              "      <td>0.00007</td>\n",
-              "      <td>0.00370</td>\n",
-              "      <td>0.00554</td>\n",
-              "      <td>0.01109</td>\n",
-              "      <td>0.04374</td>\n",
-              "      <td>0.426</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.02971</td>\n",
-              "      <td>0.06545</td>\n",
-              "      <td>0.02211</td>\n",
-              "      <td>21.033</td>\n",
-              "      <td>0.414783</td>\n",
-              "      <td>0.815285</td>\n",
-              "      <td>-4.813031</td>\n",
-              "      <td>0.266482</td>\n",
-              "      <td>2.301442</td>\n",
-              "      <td>0.284654</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>122.400</td>\n",
-              "      <td>148.650</td>\n",
-              "      <td>113.819</td>\n",
-              "      <td>0.00968</td>\n",
-              "      <td>0.00008</td>\n",
-              "      <td>0.00465</td>\n",
-              "      <td>0.00696</td>\n",
-              "      <td>0.01394</td>\n",
-              "      <td>0.06134</td>\n",
-              "      <td>0.626</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.04368</td>\n",
-              "      <td>0.09403</td>\n",
-              "      <td>0.01929</td>\n",
-              "      <td>19.085</td>\n",
-              "      <td>0.458359</td>\n",
-              "      <td>0.819521</td>\n",
-              "      <td>-4.075192</td>\n",
-              "      <td>0.335590</td>\n",
-              "      <td>2.486855</td>\n",
-              "      <td>0.368674</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>116.682</td>\n",
-              "      <td>131.111</td>\n",
-              "      <td>111.555</td>\n",
-              "      <td>0.01050</td>\n",
-              "      <td>0.00009</td>\n",
-              "      <td>0.00544</td>\n",
-              "      <td>0.00781</td>\n",
-              "      <td>0.01633</td>\n",
-              "      <td>0.05233</td>\n",
-              "      <td>0.482</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.03590</td>\n",
-              "      <td>0.08270</td>\n",
-              "      <td>0.01309</td>\n",
-              "      <td>20.651</td>\n",
-              "      <td>0.429895</td>\n",
-              "      <td>0.825288</td>\n",
-              "      <td>-4.443179</td>\n",
-              "      <td>0.311173</td>\n",
-              "      <td>2.342259</td>\n",
-              "      <td>0.332634</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>116.676</td>\n",
-              "      <td>137.871</td>\n",
-              "      <td>111.366</td>\n",
-              "      <td>0.00997</td>\n",
-              "      <td>0.00009</td>\n",
-              "      <td>0.00502</td>\n",
-              "      <td>0.00698</td>\n",
-              "      <td>0.01505</td>\n",
-              "      <td>0.05492</td>\n",
-              "      <td>0.517</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.03772</td>\n",
-              "      <td>0.08771</td>\n",
-              "      <td>0.01353</td>\n",
-              "      <td>20.644</td>\n",
-              "      <td>0.434969</td>\n",
-              "      <td>0.819235</td>\n",
-              "      <td>-4.117501</td>\n",
-              "      <td>0.334147</td>\n",
-              "      <td>2.405554</td>\n",
-              "      <td>0.368975</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>116.014</td>\n",
-              "      <td>141.781</td>\n",
-              "      <td>110.655</td>\n",
-              "      <td>0.01284</td>\n",
-              "      <td>0.00011</td>\n",
-              "      <td>0.00655</td>\n",
-              "      <td>0.00908</td>\n",
-              "      <td>0.01966</td>\n",
-              "      <td>0.06425</td>\n",
-              "      <td>0.584</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.04465</td>\n",
-              "      <td>0.10470</td>\n",
-              "      <td>0.01767</td>\n",
-              "      <td>19.649</td>\n",
-              "      <td>0.417356</td>\n",
-              "      <td>0.823484</td>\n",
-              "      <td>-3.747787</td>\n",
-              "      <td>0.234513</td>\n",
-              "      <td>2.332180</td>\n",
-              "      <td>0.410335</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>190</th>\n",
-              "      <td>174.188</td>\n",
-              "      <td>230.978</td>\n",
-              "      <td>94.261</td>\n",
-              "      <td>0.00459</td>\n",
-              "      <td>0.00003</td>\n",
-              "      <td>0.00263</td>\n",
-              "      <td>0.00259</td>\n",
-              "      <td>0.00790</td>\n",
-              "      <td>0.04087</td>\n",
-              "      <td>0.405</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.02745</td>\n",
-              "      <td>0.07008</td>\n",
-              "      <td>0.02764</td>\n",
-              "      <td>19.517</td>\n",
-              "      <td>0.448439</td>\n",
-              "      <td>0.657899</td>\n",
-              "      <td>-6.538586</td>\n",
-              "      <td>0.121952</td>\n",
-              "      <td>2.657476</td>\n",
-              "      <td>0.133050</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>191</th>\n",
-              "      <td>209.516</td>\n",
-              "      <td>253.017</td>\n",
-              "      <td>89.488</td>\n",
-              "      <td>0.00564</td>\n",
-              "      <td>0.00003</td>\n",
-              "      <td>0.00331</td>\n",
-              "      <td>0.00292</td>\n",
-              "      <td>0.00994</td>\n",
-              "      <td>0.02751</td>\n",
-              "      <td>0.263</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.01879</td>\n",
-              "      <td>0.04812</td>\n",
-              "      <td>0.01810</td>\n",
-              "      <td>19.147</td>\n",
-              "      <td>0.431674</td>\n",
-              "      <td>0.683244</td>\n",
-              "      <td>-6.195325</td>\n",
-              "      <td>0.129303</td>\n",
-              "      <td>2.784312</td>\n",
-              "      <td>0.168895</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>192</th>\n",
-              "      <td>174.688</td>\n",
-              "      <td>240.005</td>\n",
-              "      <td>74.287</td>\n",
-              "      <td>0.01360</td>\n",
-              "      <td>0.00008</td>\n",
-              "      <td>0.00624</td>\n",
-              "      <td>0.00564</td>\n",
-              "      <td>0.01873</td>\n",
-              "      <td>0.02308</td>\n",
-              "      <td>0.256</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.01667</td>\n",
-              "      <td>0.03804</td>\n",
-              "      <td>0.10715</td>\n",
-              "      <td>17.883</td>\n",
-              "      <td>0.407567</td>\n",
-              "      <td>0.655683</td>\n",
-              "      <td>-6.787197</td>\n",
-              "      <td>0.158453</td>\n",
-              "      <td>2.679772</td>\n",
-              "      <td>0.131728</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>193</th>\n",
-              "      <td>198.764</td>\n",
-              "      <td>396.961</td>\n",
-              "      <td>74.904</td>\n",
-              "      <td>0.00740</td>\n",
-              "      <td>0.00004</td>\n",
-              "      <td>0.00370</td>\n",
-              "      <td>0.00390</td>\n",
-              "      <td>0.01109</td>\n",
-              "      <td>0.02296</td>\n",
-              "      <td>0.241</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.01588</td>\n",
-              "      <td>0.03794</td>\n",
-              "      <td>0.07223</td>\n",
-              "      <td>19.020</td>\n",
-              "      <td>0.451221</td>\n",
-              "      <td>0.643956</td>\n",
-              "      <td>-6.744577</td>\n",
-              "      <td>0.207454</td>\n",
-              "      <td>2.138608</td>\n",
-              "      <td>0.123306</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>194</th>\n",
-              "      <td>214.289</td>\n",
-              "      <td>260.277</td>\n",
-              "      <td>77.973</td>\n",
-              "      <td>0.00567</td>\n",
-              "      <td>0.00003</td>\n",
-              "      <td>0.00295</td>\n",
-              "      <td>0.00317</td>\n",
-              "      <td>0.00885</td>\n",
-              "      <td>0.01884</td>\n",
-              "      <td>0.190</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.01373</td>\n",
-              "      <td>0.03078</td>\n",
-              "      <td>0.04398</td>\n",
-              "      <td>21.209</td>\n",
-              "      <td>0.462803</td>\n",
-              "      <td>0.664357</td>\n",
-              "      <td>-5.724056</td>\n",
-              "      <td>0.190667</td>\n",
-              "      <td>2.555477</td>\n",
-              "      <td>0.148569</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>195 rows × 22 columns</p>\n",
-              "</div>\n",
-              "    <div class=\"colab-df-buttons\">\n",
-              "\n",
-              "  <div class=\"colab-df-container\">\n",
-              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d52120d9-7d31-4822-867b-72c4af95f0a7')\"\n",
-              "            title=\"Convert this dataframe to an interactive table.\"\n",
-              "            style=\"display:none;\">\n",
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-              "variable_name": "X"
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-          },
-          "metadata": {}
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Importing TabPFN client library<span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
+       "</pre>\n"
       ],
-      "source": [
-        "# Load Parkinsons dataset described above\n",
-        "\n",
-        "import pandas as pd, io, zipfile, requests\n",
-        "\n",
-        "url_zip = \"https://archive.ics.uci.edu/static/public/174/parkinsons.zip\"\n",
-        "with requests.get(url_zip) as r:\n",
-        "    r.raise_for_status()\n",
-        "    zf = zipfile.ZipFile(io.BytesIO(r.content))\n",
-        "    df = pd.read_csv(zf.open(\"parkinsons.data\"))\n",
-        "X, y = df.drop([\"status\", \"name\"], axis=1), df[\"status\"]\n",
-        "\n",
-        "display(X)"
+      "text/plain": [
+       "Importing TabPFN client library\u001b[33m...\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 6,
-      "metadata": {
-        "id": "KAXhoOc2U2vJ"
-      },
-      "outputs": [],
-      "source": [
-        "# Alternative datasets (commented for reference):\n",
-        "\n",
-        "# Cholesterol dataset: Predict cholesterol levels\n",
-        "# Features: Patient characteristics, medical measurements\n",
-        "# Samples: 303 patients\n",
-        "# Target: Cholesterol levels in mg/dl\n",
-        "# df = fetch_openml('cholesterol', version=2, as_frame=True)\n",
-        "\n",
-        "# Heart Disease dataset (Statlog): Predict presence of heart disease\n",
-        "# Features: Clinical and test measurements\n",
-        "# Samples: 270 patients\n",
-        "# Target: Binary heart disease diagnosis\n",
-        "# df = fetch_openml(\"heart-statlog\", version=1)\n",
-        "\n",
-        "# Diabetes dataset: Predict diabetes presence\n",
-        "# Features: Medical measurements, patient history\n",
-        "# Samples: 768 patients\n",
-        "# Target: Binary diabetes diagnosis\n",
-        "# df = fetch_openml(\"diabetes\", version=1)"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">########  ########   ###  #########  #########       ###         #####     ########  ########</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">     ###        ##   ###  ###   ###        ###       ###        ###  ###   ##   ###  ###     </span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">########  #######    ###  ###   ###  #######         ###        ########   ######    ########</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">###       ###   ##   ###  ###   ###  ###   ###       ###        ###  ###   ##   ###       ###</span>\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">###       ###   ##   ###  #########  ###   ###       ########   ###  ###   ########  ########                      </span>\n",
+       "\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "\u001b[1;34m########  ########   ###  #########  #########       ###         #####     ########  ########\u001b[0m\n",
+       "\u001b[1;34m     ###        ##   ###  ###   ###        ###       ###        ###  ###   ##   ###  ###     \u001b[0m\n",
+       "\u001b[1;34m########  #######    ###  ###   ###  #######         ###        ########   ######    ########\u001b[0m\n",
+       "\u001b[1;34m###       ###   ##   ###  ###   ###  ###   ###       ###        ###  ###   ##   ###       ###\u001b[0m\n",
+       "\u001b[1;34m###       ###   ##   ###  #########  ###   ###       ########   ###  ###   ########  ########                      \u001b[0m\n",
+       "\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 7,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "zTHzDedu3DKR",
-        "outputId": "b8f79392-66bf-4884-bcbd-1a7cb51ab676"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "Processing: 100%|██████████| [00:02<00:00]\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "TabPFN ROC AUC Score: 0.9732\n"
-          ]
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">Thanks for being part of the journey</span>\n",
+       "\n",
+       "</pre>\n"
       ],
-      "source": [
-        "# Split the data into training and testing sets\n",
-        "X_train, X_test, y_train, y_test = train_test_split(\n",
-        "    X, y, test_size=0.20, random_state=42\n",
-        ")\n",
-        "\n",
-        "# Train and evaluate the TabPFN classifier\n",
-        "tabpfn_classifier = TabPFNClassifier(random_state=42)\n",
-        "tabpfn_classifier.fit(X_train, y_train)\n",
-        "y_pred_proba = tabpfn_classifier.predict_proba(X_test)\n",
-        "\n",
-        "# Calculate the ROC AUC score\n",
-        "roc_auc = roc_auc_score(y_test, y_pred_proba[:, 1])\n",
-        "print(f\"TabPFN ROC AUC Score: {roc_auc:.4f}\")"
+      "text/plain": [
+       "\u001b[2mThanks for being part of the journey\u001b[0m\n",
+       "\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "ZVs_HfxbVCs3"
-      },
-      "source": [
-        "### Comparing TabPFN with Other Classifiers\n",
-        "\n",
-        "To get a better sense of TabPFN's performance, let's compare it with other popular classification models using cross-validation. This will give us a more robust estimate of each model's performance.\n"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  TabPFN is under active development, please help us improve and report any bugs/ideas you find.\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "  TabPFN is under active development, please help us improve and report any bugs/ideas you find.\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 8,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 789
-        },
-        "id": "ITuXXhqE7Fps",
-        "outputId": "f7cc728b-2b9e-4d1f-ce3a-db8bd165c371"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "Processing: 100%|██████████| [00:01<00:00]\n",
-            "Processing: 100%|██████████| [00:00<00:00]\n",
-            "Processing: 100%|██████████| [00:02<00:00]\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:   12.8s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.7s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.2s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    8.9s finished\n"
-          ]
-        },
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "Text(0.5, 1.0, 'Model Comparison - 3-fold Cross-validation')"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 8
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 1000x600 with 1 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #000080; text-decoration-color: #000080\">Report issues: </span><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">https://github.com/priorlabs/tabpfn-client/issues</span>\n",
+       "</pre>\n"
       ],
-      "source": [
-        "# Compare different machine learning models by training each one multiple times\n",
-        "# on different parts of the data and averaging their performance scores for a\n",
-        "# more reliable performance estimate\n",
-        "\n",
-        "# Encode target labels to classes for baselines\n",
-        "le = LabelEncoder()\n",
-        "y = le.fit_transform(y)\n",
-        "\n",
-        "# Define models\n",
-        "models = [\n",
-        "    (\"TabPFN\", TabPFNClassifier(random_state=42)),\n",
-        "    (\n",
-        "        \"RandomForest\",\n",
-        "        make_pipeline(\n",
-        "            column_transformer,  # string data needs to be encoded for model\n",
-        "            RandomForestClassifier(random_state=42),\n",
-        "        ),\n",
-        "    ),\n",
-        "    (\n",
-        "        \"XGBoost\",\n",
-        "        make_pipeline(\n",
-        "            column_transformer,  # string data needs to be encoded for model\n",
-        "            XGBClassifier(random_state=42),\n",
-        "        ),\n",
-        "    ),\n",
-        "    (\n",
-        "        \"CatBoost\",\n",
-        "        make_pipeline(\n",
-        "            column_transformer,  # string data needs to be encoded for model\n",
-        "            CatBoostClassifier(random_state=42, verbose=0),\n",
-        "        ),\n",
-        "    ),\n",
-        "]\n",
-        "\n",
-        "# Calculate scores\n",
-        "n_splits = 3\n",
-        "cv = StratifiedKFold(n_splits=n_splits, random_state=42, shuffle=True)\n",
-        "scoring = \"roc_auc_ovr\" if len(np.unique(y)) > 2 else \"roc_auc\"\n",
-        "scores = {\n",
-        "    name: cross_val_score(model, X, y, cv=cv, scoring=scoring, n_jobs=1, verbose=1)\n",
-        "    for name, model in models\n",
-        "}\n",
-        "\n",
-        "# Plot results\n",
-        "df = pd.DataFrame(\n",
-        "    [(k, v.mean()) for (k, v) in scores.items()], columns=[\"Model\", \"ROC AUC\"]\n",
-        ")\n",
-        "ax = df.plot(x=\"Model\", y=\"ROC AUC\", kind=\"bar\", figsize=(10, 6))\n",
-        "ax.set_ylim(df[\"ROC AUC\"].min() * 0.995, min(1.0, df[\"ROC AUC\"].max() * 1.005))\n",
-        "ax.set_title(f\"Model Comparison - {n_splits}-fold Cross-validation\")"
+      "text/plain": [
+       "  \u001b[34mReport issues: \u001b[0m\u001b[4;34mhttps://github.com/priorlabs/tabpfn-client/issues\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "ipG2Cpb7Jrc7"
-      },
-      "source": [
-        "# Regression with TabPFN <a name=\"regression\"></a>\n",
-        "\n",
-        "Next, we'll explore how to use TabPFN for regression tasks. We will use the Boston Housing dataset, where the goal is to predict the median value of owner-occupied homes.\n",
-        "\n",
-        "We will measure performance using the [Root Mean Squared Error](https://scikit-learn.org/1.5/modules/generated/sklearn.metrics.root_mean_squared_error.html), and again, we will compare TabPFN with other popular regression models."
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">  <span style=\"color: #000080; text-decoration-color: #000080\">Press Ctrl+C anytime to exit</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "  \u001b[34mPress Ctrl+C anytime to exit\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "source": [
-        "### **Loading Boston Housing Dataset**\n",
-        "\n",
-        "### **Dataset Overview**\n",
-        "\n",
-        "-   **Objective:** Predict the **median value of owner-occupied homes** in the Boston area based on various socioeconomic and environmental attributes.\n",
-        "    \n",
-        "-   **Number of Instances:** 506\n",
-        "    \n",
-        "-   **Number of Attributes:** 14 (13 numeric features + 1 target variable)\n",
-        "    \n",
-        "-   **Target Variable:** `MEDV` — Median value of owner-occupied homes (in $1000s)\n",
-        "    \n",
-        "-   **Class Type:** Numeric\n",
-        "    \n",
-        "-   **Class Index:** Last\n",
-        "    \n",
-        "\n",
-        "* * *\n",
-        "\n",
-        "<details>\n",
-        "\n",
-        "\n",
-        "**Citation:**\n",
-        "\n",
-        "> Harrison, D. and Rubinfeld, D.L. (1978).  \n",
-        "> _Hedonic prices and the demand for clean air._  \n",
-        "> _Journal of Environmental Economics & Management_, 5, 81–102.  \n",
-        "> Used in Belsley, Kuh & Welsch, _Regression Diagnostics: Identifying Influential Data and Sources of Collinearity_, Wiley, 1980.\n",
-        "\n",
-        "\n",
-        "### **Attribute Information**\n",
-        "\n",
-        "**Feature**\n",
-        "\n",
-        "**Description**\n",
-        "\n",
-        "`CRIM`\n",
-        "\n",
-        "Per capita crime rate by town\n",
-        "\n",
-        "`ZN`\n",
-        "\n",
-        "Proportion of residential land zoned for lots over 25,000 sq.ft.\n",
-        "\n",
-        "`INDUS`\n",
-        "\n",
-        "Proportion of non-retail business acres per town\n",
-        "\n",
-        "`CHAS`\n",
-        "\n",
-        "Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)\n",
-        "\n",
-        "`NOX`\n",
-        "\n",
-        "Nitric oxides concentration (parts per 10 million)\n",
-        "\n",
-        "`RM`\n",
-        "\n",
-        "Average number of rooms per dwelling\n",
-        "\n",
-        "`AGE`\n",
-        "\n",
-        "Proportion of owner-occupied units built prior to 1940\n",
-        "\n",
-        "`DIS`\n",
-        "\n",
-        "Weighted distances to five Boston employment centres\n",
-        "\n",
-        "`RAD`\n",
-        "\n",
-        "Index of accessibility to radial highways\n",
-        "\n",
-        "`TAX`\n",
-        "\n",
-        "Full-value property-tax rate per $10,000\n",
-        "\n",
-        "`PTRATIO`\n",
-        "\n",
-        "Pupil–teacher ratio by town\n",
-        "\n",
-        "`B`\n",
-        "\n",
-        "1000(Bk − 0.63)², where Bk is the proportion of Blacks by town\n",
-        "\n",
-        "`LSTAT`\n",
-        "\n",
-        "Percentage of lower status population\n",
-        "\n",
-        "`MEDV`\n",
-        "\n",
-        "Median value of owner-occupied homes (in $1000s)\n",
-        "\n",
-        "</details>"
-      ],
-      "metadata": {
-        "id": "Qzrj9m0fI32f"
-      }
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Opening browser for login. Please complete the login/registration process in your browser and return here.\n",
+      "\n",
+      "\n",
+      "Could not open browser automatically. Falling back to command-line login...\n",
+      "\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "source": [
-        "# Load the Boston Housing dataset\n",
-        "\n",
-        "import pandas as pd, requests\n",
-        "from IPython.display import display, Markdown\n",
-        "\n",
-        "cols = [\"CRIM\",\"ZN\",\"INDUS\",\"CHAS\",\"NOX\",\"RM\",\"AGE\",\"DIS\",\"RAD\",\"TAX\",\"PTRATIO\",\"B\",\"LSTAT\",\"MEDV\"]\n",
-        "df_boston = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data\",\n",
-        "                        delim_whitespace=True, header=None, names=cols)\n",
-        "X, y = df_boston.drop(columns=[\"MEDV\"]), df_boston[\"MEDV\"]\n",
-        "\n",
-        "display(X.head())\n"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "\n",
+       "</pre>\n"
       ],
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 240
-        },
-        "id": "4vbEBAKKIRaM",
-        "outputId": "d55a593d-d65f-4fdf-ac5c-6d9d32be2bf9"
-      },
-      "execution_count": 9,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "/tmp/ipython-input-378995386.py:7: FutureWarning: The 'delim_whitespace' keyword in pd.read_csv is deprecated and will be removed in a future version. Use ``sep='\\s+'`` instead\n",
-            "  df_boston = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data\",\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "      CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
-              "0  0.00632  18.0   2.31     0  0.538  6.575  65.2  4.0900    1  296.0   \n",
-              "1  0.02731   0.0   7.07     0  0.469  6.421  78.9  4.9671    2  242.0   \n",
-              "2  0.02729   0.0   7.07     0  0.469  7.185  61.1  4.9671    2  242.0   \n",
-              "3  0.03237   0.0   2.18     0  0.458  6.998  45.8  6.0622    3  222.0   \n",
-              "4  0.06905   0.0   2.18     0  0.458  7.147  54.2  6.0622    3  222.0   \n",
-              "\n",
-              "   PTRATIO       B  LSTAT  \n",
-              "0     15.3  396.90   4.98  \n",
-              "1     17.8  396.90   9.14  \n",
-              "2     17.8  392.83   4.03  \n",
-              "3     18.7  394.63   2.94  \n",
-              "4     18.7  396.90   5.33  "
-            ],
-            "text/html": [
-              "\n",
-              "  <div id=\"df-4590d6cd-2eaa-4ea3-b5f5-7a56b39dda16\" class=\"colab-df-container\">\n",
-              "    <div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>CRIM</th>\n",
-              "      <th>ZN</th>\n",
-              "      <th>INDUS</th>\n",
-              "      <th>CHAS</th>\n",
-              "      <th>NOX</th>\n",
-              "      <th>RM</th>\n",
-              "      <th>AGE</th>\n",
-              "      <th>DIS</th>\n",
-              "      <th>RAD</th>\n",
-              "      <th>TAX</th>\n",
-              "      <th>PTRATIO</th>\n",
-              "      <th>B</th>\n",
-              "      <th>LSTAT</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>0.00632</td>\n",
-              "      <td>18.0</td>\n",
-              "      <td>2.31</td>\n",
-              "      <td>0</td>\n",
-              "      <td>0.538</td>\n",
-              "      <td>6.575</td>\n",
-              "      <td>65.2</td>\n",
-              "      <td>4.0900</td>\n",
-              "      <td>1</td>\n",
-              "      <td>296.0</td>\n",
-              "      <td>15.3</td>\n",
-              "      <td>396.90</td>\n",
-              "      <td>4.98</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>0.02731</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>7.07</td>\n",
-              "      <td>0</td>\n",
-              "      <td>0.469</td>\n",
-              "      <td>6.421</td>\n",
-              "      <td>78.9</td>\n",
-              "      <td>4.9671</td>\n",
-              "      <td>2</td>\n",
-              "      <td>242.0</td>\n",
-              "      <td>17.8</td>\n",
-              "      <td>396.90</td>\n",
-              "      <td>9.14</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>0.02729</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>7.07</td>\n",
-              "      <td>0</td>\n",
-              "      <td>0.469</td>\n",
-              "      <td>7.185</td>\n",
-              "      <td>61.1</td>\n",
-              "      <td>4.9671</td>\n",
-              "      <td>2</td>\n",
-              "      <td>242.0</td>\n",
-              "      <td>17.8</td>\n",
-              "      <td>392.83</td>\n",
-              "      <td>4.03</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>0.03237</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>2.18</td>\n",
-              "      <td>0</td>\n",
-              "      <td>0.458</td>\n",
-              "      <td>6.998</td>\n",
-              "      <td>45.8</td>\n",
-              "      <td>6.0622</td>\n",
-              "      <td>3</td>\n",
-              "      <td>222.0</td>\n",
-              "      <td>18.7</td>\n",
-              "      <td>394.63</td>\n",
-              "      <td>2.94</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>0.06905</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>2.18</td>\n",
-              "      <td>0</td>\n",
-              "      <td>0.458</td>\n",
-              "      <td>7.147</td>\n",
-              "      <td>54.2</td>\n",
-              "      <td>6.0622</td>\n",
-              "      <td>3</td>\n",
-              "      <td>222.0</td>\n",
-              "      <td>18.7</td>\n",
-              "      <td>396.90</td>\n",
-              "      <td>5.33</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>\n",
-              "    <div class=\"colab-df-buttons\">\n",
-              "\n",
-              "  <div class=\"colab-df-container\">\n",
-              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4590d6cd-2eaa-4ea3-b5f5-7a56b39dda16')\"\n",
-              "            title=\"Convert this dataframe to an interactive table.\"\n",
-              "            style=\"display:none;\">\n",
-              "\n",
-              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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-              "  </svg>\n",
-              "    </button>\n",
-              "\n",
-              "  <style>\n",
-              "    .colab-df-container {\n",
-              "      display:flex;\n",
-              "      gap: 12px;\n",
-              "    }\n",
-              "\n",
-              "    .colab-df-convert {\n",
-              "      background-color: #E8F0FE;\n",
-              "      border: none;\n",
-              "      border-radius: 50%;\n",
-              "      cursor: pointer;\n",
-              "      display: none;\n",
-              "      fill: #1967D2;\n",
-              "      height: 32px;\n",
-              "      padding: 0 0 0 0;\n",
-              "      width: 32px;\n",
-              "    }\n",
-              "\n",
-              "    .colab-df-convert:hover {\n",
-              "      background-color: #E2EBFA;\n",
-              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
-              "      fill: #174EA6;\n",
-              "    }\n",
-              "\n",
-              "    .colab-df-buttons div {\n",
-              "      margin-bottom: 4px;\n",
-              "    }\n",
-              "\n",
-              "    [theme=dark] .colab-df-convert {\n",
-              "      background-color: #3B4455;\n",
-              "      fill: #D2E3FC;\n",
-              "    }\n",
-              "\n",
-              "    [theme=dark] .colab-df-convert:hover {\n",
-              "      background-color: #434B5C;\n",
-              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
-              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
-              "      fill: #FFFFFF;\n",
-              "    }\n",
-              "  </style>\n",
-              "\n",
-              "    <script>\n",
-              "      const buttonEl =\n",
-              "        document.querySelector('#df-4590d6cd-2eaa-4ea3-b5f5-7a56b39dda16 button.colab-df-convert');\n",
-              "      buttonEl.style.display =\n",
-              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
-              "\n",
-              "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-4590d6cd-2eaa-4ea3-b5f5-7a56b39dda16');\n",
-              "        const dataTable =\n",
-              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
-              "                                                    [key], {});\n",
-              "        if (!dataTable) return;\n",
-              "\n",
-              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
-              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
-              "          + ' to learn more about interactive tables.';\n",
-              "        element.innerHTML = '';\n",
-              "        dataTable['output_type'] = 'display_data';\n",
-              "        await google.colab.output.renderOutput(dataTable, element);\n",
-              "        const docLink = document.createElement('div');\n",
-              "        docLink.innerHTML = docLinkHtml;\n",
-              "        element.appendChild(docLink);\n",
-              "      }\n",
-              "    </script>\n",
-              "  </div>\n",
-              "\n",
-              "\n",
-              "    <div id=\"df-c0acb8e2-3622-4d87-aaad-fe39e89d60bc\">\n",
-              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c0acb8e2-3622-4d87-aaad-fe39e89d60bc')\"\n",
-              "                title=\"Suggest charts\"\n",
-              "                style=\"display:none;\">\n",
-              "\n",
-              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
-              "     width=\"24px\">\n",
-              "    <g>\n",
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-              "    </g>\n",
-              "</svg>\n",
-              "      </button>\n",
-              "\n",
-              "<style>\n",
-              "  .colab-df-quickchart {\n",
-              "      --bg-color: #E8F0FE;\n",
-              "      --fill-color: #1967D2;\n",
-              "      --hover-bg-color: #E2EBFA;\n",
-              "      --hover-fill-color: #174EA6;\n",
-              "      --disabled-fill-color: #AAA;\n",
-              "      --disabled-bg-color: #DDD;\n",
-              "  }\n",
-              "\n",
-              "  [theme=dark] .colab-df-quickchart {\n",
-              "      --bg-color: #3B4455;\n",
-              "      --fill-color: #D2E3FC;\n",
-              "      --hover-bg-color: #434B5C;\n",
-              "      --hover-fill-color: #FFFFFF;\n",
-              "      --disabled-bg-color: #3B4455;\n",
-              "      --disabled-fill-color: #666;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart {\n",
-              "    background-color: var(--bg-color);\n",
-              "    border: none;\n",
-              "    border-radius: 50%;\n",
-              "    cursor: pointer;\n",
-              "    display: none;\n",
-              "    fill: var(--fill-color);\n",
-              "    height: 32px;\n",
-              "    padding: 0;\n",
-              "    width: 32px;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart:hover {\n",
-              "    background-color: var(--hover-bg-color);\n",
-              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
-              "    fill: var(--button-hover-fill-color);\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart-complete:disabled,\n",
-              "  .colab-df-quickchart-complete:disabled:hover {\n",
-              "    background-color: var(--disabled-bg-color);\n",
-              "    fill: var(--disabled-fill-color);\n",
-              "    box-shadow: none;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-spinner {\n",
-              "    border: 2px solid var(--fill-color);\n",
-              "    border-color: transparent;\n",
-              "    border-bottom-color: var(--fill-color);\n",
-              "    animation:\n",
-              "      spin 1s steps(1) infinite;\n",
-              "  }\n",
-              "\n",
-              "  @keyframes spin {\n",
-              "    0% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "      border-left-color: var(--fill-color);\n",
-              "    }\n",
-              "    20% {\n",
-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "    }\n",
-              "    30% {\n",
-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    40% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "    }\n",
-              "    60% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    80% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "    90% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "  }\n",
-              "</style>\n",
-              "\n",
-              "      <script>\n",
-              "        async function quickchart(key) {\n",
-              "          const quickchartButtonEl =\n",
-              "            document.querySelector('#' + key + ' button');\n",
-              "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
-              "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
-              "          try {\n",
-              "            const charts = await google.colab.kernel.invokeFunction(\n",
-              "                'suggestCharts', [key], {});\n",
-              "          } catch (error) {\n",
-              "            console.error('Error during call to suggestCharts:', error);\n",
-              "          }\n",
-              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
-              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
-              "        }\n",
-              "        (() => {\n",
-              "          let quickchartButtonEl =\n",
-              "            document.querySelector('#df-c0acb8e2-3622-4d87-aaad-fe39e89d60bc button');\n",
-              "          quickchartButtonEl.style.display =\n",
-              "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
-              "        })();\n",
-              "      </script>\n",
-              "    </div>\n",
-              "\n",
-              "    </div>\n",
-              "  </div>\n"
-            ],
-            "application/vnd.google.colaboratory.intrinsic+json": {
-              "type": "dataframe",
-              "summary": "{\n  \"name\": \"display(X\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"CRIM\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.02277820712874479,\n        \"min\": 0.00632,\n        \"max\": 0.06905,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.02731,\n          0.06905,\n          0.02729\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ZN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8.049844718999244,\n        \"min\": 0.0,\n        \"max\": 18.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0.0,\n          18.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDUS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.6551591289412393,\n        \"min\": 2.18,\n        \"max\": 7.07,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          2.31,\n          7.07\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CHAS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"NOX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.03376832835661252,\n        \"min\": 0.458,\n        \"max\": 0.538,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.538\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"RM\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3467163105479751,\n        \"min\": 6.421,\n        \"max\": 7.185,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          6.421\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AGE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 12.402943199095933,\n        \"min\": 45.8,\n        \"max\": 78.9,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          78.9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DIS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.8400812621407525,\n        \"min\": 4.09,\n        \"max\": 6.0622,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          4.09\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"RAD\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 3,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"TAX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.31831129861952,\n        \"min\": 222.0,\n        \"max\": 296.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          296.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"PTRATIO\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.393915348936225,\n        \"min\": 15.3,\n        \"max\": 18.7,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          15.3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"B\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.8492349769566823,\n        \"min\": 392.83,\n        \"max\": 396.9,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          396.9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"LSTAT\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.346812732196585,\n        \"min\": 2.94,\n        \"max\": 9.14,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          9.14\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
-            }
-          },
-          "metadata": {}
-        }
+      "text/plain": [
+       "\n",
+       "\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 10,
-      "metadata": {
-        "id": "YaA7WBuEVdQy"
-      },
-      "outputs": [],
-      "source": [
-        "# Alternative datasets (commented for reference):\n",
-        "\n",
-        "# Liver Disorders dataset\n",
-        "# Classification task: Predict liver disorder presence\n",
-        "# Features: Blood test results, alcohol consumption\n",
-        "# Samples: 345 patients\n",
-        "# Target: Binary liver disorder diagnosis\n",
-        "# df = fetch_openml(\"liver-disorders\", version=1)\n",
-        "\n",
-        "# Grid Stability dataset\n",
-        "# Regression task: Predict electrical grid stability\n",
-        "# Features: Power system measurements, grid parameters\n",
-        "# Samples: 10,000 simulations\n",
-        "# Target: Grid stability score\n",
-        "# df = fetch_openml(data_id=44973, as_frame=True)\n",
-        "\n",
-        "# Concrete Compressive Strength dataset\n",
-        "# Regression task: Predict concrete strength\n",
-        "# Features: Concrete components (cement, water, aggregates)\n",
-        "# Samples: 1,030 concrete samples\n",
-        "# Target: Compressive strength in MPa\n",
-        "# df = fetch_openml(data_id=44959, as_frame=True)"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">[1]    </span> Create a TabPFN account     \n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">[2]    </span> Login to your TabPFN account\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">[q]    </span> Quit                        \n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;34m[1]   \u001b[0m\u001b[1;34m \u001b[0m Create a TabPFN account     \n",
+       "\u001b[1;34m[2]   \u001b[0m\u001b[1;34m \u001b[0m Login to your TabPFN account\n",
+       "\u001b[1;34m[q]   \u001b[0m\u001b[1;34m \u001b[0m Quit                        \n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 11,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "rWqC16PL7R_T",
-        "outputId": "01d8b6c2-7421-4a10-8a93-984ddeaafb99"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "Processing: 100%|██████████| [00:03<00:00]\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "TabPFN RMSE: 2.6528\n"
-          ]
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">→</span> Choose <span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span>/<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>/q<span style=\"font-weight: bold\">)</span>: </pre>\n"
       ],
-      "source": [
-        "# Split the data\n",
-        "X_train, X_test, y_train, y_test = train_test_split(\n",
-        "    X, y, test_size=0.33, random_state=42\n",
-        ")\n",
-        "\n",
-        "# Train and evaluate the TabPFN regressor\n",
-        "tabpfn_regressor = TabPFNRegressor(random_state=42)\n",
-        "tabpfn_regressor.fit(X_train, y_train)\n",
-        "y_pred = tabpfn_regressor.predict(X_test)\n",
-        "\n",
-        "# Calculate the Root Mean Squared Error\n",
-        "rmse = np.sqrt(mean_squared_error(y_test, y_pred))\n",
-        "print(f\"TabPFN RMSE: {rmse:.4f}\")"
+      "text/plain": [
+       "\n",
+       "\u001b[1;34m→\u001b[0m Choose \u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m/\u001b[1;36m2\u001b[0m/q\u001b[1m)\u001b[0m: "
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "Itu5-vVRWEMA"
-      },
-      "source": [
-        "### Comparing TabPFN with Other Regressors\n",
-        "\n",
-        "Now, let's see how TabPFN's regression performance stacks up against other models using cross-validation.\n"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 12,
-      "metadata": {
-        "id": "0XLxgbqSPe55",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 810
-        },
-        "outputId": "930f9733-d5af-40c0-dd95-7f35d8ad61e1"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "Processing: 100%|██████████| [00:00<00:00]\n",
-            "Processing: 100%|██████████| [00:00<00:00]\n",
-            "Processing: 100%|██████████| [00:00<00:00]\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    8.9s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    1.1s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.4s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    6.4s finished\n"
-          ]
-        },
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "Text(0.5, 1.0, 'Model Comparison - 3-fold Cross-validation \\n (Variance Explained - Larger is better)')"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 12
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 1000x600 with 1 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
+       "<span style=\"font-weight: bold\">Login</span>\n",
+       "</pre>\n"
       ],
-      "source": [
-        "# Compare different machine learning models by training each one multiple times\n",
-        "# on different parts of the data and averaging their performance scores for a\n",
-        "# more reliable performance estimate\n",
-        "\n",
-        "# Define models\n",
-        "models = [\n",
-        "    (\"TabPFN\", TabPFNRegressor(random_state=42)),\n",
-        "    (\n",
-        "        \"RandomForest\",\n",
-        "        make_pipeline(\n",
-        "            column_transformer,  # string data needs to be encoded for model\n",
-        "            RandomForestRegressor(random_state=42),\n",
-        "        ),\n",
-        "    ),\n",
-        "    (\n",
-        "        \"XGBoost\",\n",
-        "        make_pipeline(\n",
-        "            column_transformer,  # string data needs to be encoded for model\n",
-        "            XGBRegressor(random_state=42),\n",
-        "        ),\n",
-        "    ),\n",
-        "    (\n",
-        "        \"CatBoost\",\n",
-        "        make_pipeline(\n",
-        "            column_transformer,  # string data needs to be encoded for model\n",
-        "            CatBoostRegressor(random_state=42, verbose=0),\n",
-        "        ),\n",
-        "    ),\n",
-        "]\n",
-        "\n",
-        "# Calculate scores\n",
-        "scoring = \"r2\"\n",
-        "n_splits = 3\n",
-        "cv = KFold(n_splits=n_splits, random_state=42, shuffle=True)\n",
-        "scores = {\n",
-        "    name: cross_val_score(model, X, y, cv=cv, scoring=scoring, n_jobs=1, verbose=1)\n",
-        "    for name, model in models\n",
-        "}\n",
-        "\n",
-        "\n",
-        "# Plot results\n",
-        "df = pd.DataFrame([(k, v.mean()) for (k, v) in scores.items()], columns=[\"Model\", \"R2\"])\n",
-        "ax = df.plot(x=\"Model\", y=\"R2\", kind=\"bar\", figsize=(10, 6))\n",
-        "ax.set_ylim(df[\"R2\"].min() * 0.99, df[\"R2\"].max() * 1.01)\n",
-        "ax.set_title(\n",
-        "    f\"Model Comparison - {n_splits}-fold Cross-validation \\n (Variance Explained - Larger is better)\"\n",
-        ")"
+      "text/plain": [
+       "\n",
+       "\u001b[1mLogin\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "3uGfjIdjsCg-"
-      },
-      "source": [
-        "# Handling Text Data <a name=\"text-data\"></a>\n",
-        "\n",
-        "A powerful feature of the TabPFN server is its ability to handle text data directly, without the need for manual feature engineering. This simplifies the process of working with datasets that contain a mix of numerical and textual features.\n",
-        "\n",
-        "**Note:** This feature is only available when using the 'client' backend."
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Email: </pre>\n"
+      ],
+      "text/plain": [
+       "Email: "
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 13,
-      "metadata": {
-        "id": "vYBdSZnor-at",
-        "outputId": "13fd1b18-776d-43d2-ee0c-e1ed688071f0",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 292
-        }
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Downloading...\n",
-            "From: https://drive.google.com/uc?id=17bJekFGIAxbrdcBeBIvcyZjneweY581E\n",
-            "To: /content/cloth.csv\n",
-            "100% 8.48M/8.48M [00:00<00:00, 21.0MB/s]\n",
-            "Text dataset loaded successfully!\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "   Clothing ID  Age                    Title  \\\n",
-              "2         1077   60  Some major design flaws   \n",
-              "3         1049   50         My favorite buy!   \n",
-              "4          847   47         Flattering shirt   \n",
-              "5         1080   49  Not for the very petite   \n",
-              "6          858   39     Cagrcoal shimmer fun   \n",
-              "\n",
-              "                                         Review Text  Recommended IND  \\\n",
-              "2  I had such high hopes for this dress and reall...                0   \n",
-              "3  I love, love, love this jumpsuit. it's fun, fl...                1   \n",
-              "4  This shirt is very flattering to all due to th...                1   \n",
-              "5  I love tracy reese dresses, but this one is no...                0   \n",
-              "6  I aded this in my basket at hte last mintue to...                1   \n",
-              "\n",
-              "   Positive Feedback Count   Division Name Department Name Class Name  \n",
-              "2                        0         General         Dresses    Dresses  \n",
-              "3                        0  General Petite         Bottoms      Pants  \n",
-              "4                        6         General            Tops    Blouses  \n",
-              "5                        4         General         Dresses    Dresses  \n",
-              "6                        1  General Petite            Tops      Knits  "
-            ],
-            "text/html": [
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-              "    <div>\n",
-              "<style scoped>\n",
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-              "      <th>Clothing ID</th>\n",
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-              "      <th>Title</th>\n",
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-              "\n",
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-              "\n",
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-            ],
-            "application/vnd.google.colaboratory.intrinsic+json": {
-              "type": "dataframe",
-              "summary": "{\n  \"name\": \"    display(X_text\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"Clothing ID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 119,\n        \"min\": 847,\n        \"max\": 1080,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          1049,\n          858,\n          847\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7,\n        \"min\": 39,\n        \"max\": 60,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          50,\n          39,\n          47\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"My favorite buy!\",\n          \"Cagrcoal shimmer fun\",\n          \"Flattering shirt\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Review Text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"I love, love, love this jumpsuit. it's fun, flirty, and fabulous! every time i wear it, i get nothing but great compliments!\",\n          \"I aded this in my basket at hte last mintue to see what it would look like in person. (store pick up). i went with teh darkler color only because i am so pale :-) hte color is really gorgeous, and turns out it mathced everythiing i was trying on with it prefectly. it is a little baggy on me and hte xs is hte msallet size (bummer, no petite). i decided to jkeep it though, because as i said, it matvehd everything. my ejans, pants, and the 3 skirts i waas trying on (of which i ]kept all ) oops.\",\n          \"This shirt is very flattering to all due to the adjustable front tie. it is the perfect length to wear with leggings and it is sleeveless so it pairs well with any cardigan. love this shirt!!!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Recommended IND\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Positive Feedback Count\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 0,\n        \"max\": 6,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          6,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Division Name\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"General Petite\",\n          \"General\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Department Name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Dresses\",\n          \"Bottoms\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Class Name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Pants\",\n          \"Knits\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
-            }
-          },
-          "metadata": {}
-        }
-      ],
-      "source": [
-        "if backend != \"client\":\n",
-        "    console.print(\n",
-        "        Panel(\n",
-        "            \"[bold yellow]Text data can only be processed through the TabPFN server. Please restart the notebook and select the 'client' backend to run this section.[/bold yellow]\",\n",
-        "            title=\"[bold yellow]Warning\",\n",
-        "            border_style=\"yellow\",\n",
-        "        )\n",
-        "    )\n",
-        "else:\n",
-        "    # We will use gdown to download the dataset\n",
-        "    !gdown --fuzzy \"17bJekFGIAxbrdcBeBIvcyZjneweY581E\"\n",
-        "\n",
-        "    # Load the clothing review dataset\n",
-        "    # We restrict to 500 rows to make the example faster\n",
-        "    df_text = pd.read_csv(\"cloth.csv\", index_col=0).dropna()[:500]\n",
-        "\n",
-        "    # Define features and target\n",
-        "    y_text = df_text[\"Rating\"]\n",
-        "    X_text = df_text.drop(columns=[\"Rating\"])\n",
-        "\n",
-        "    print(\"Text dataset loaded successfully!\")\n",
-        "    display(X_text.head())"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "noah@priorlabs.ai\n",
+      "Password: ··········\n"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "iQkFQD_rWi1v"
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0b0d8924f58949a2ba8c5de2dc99d9b2",
+       "version_major": 2,
+       "version_minor": 0
       },
-      "source": [
-        "### Comparing Text Handling\n",
-        "\n",
-        "Now, let's compare how TabPFN handles text natively versus how a baseline model like RandomForest needs a specific text processing pipeline.\n",
-        "\n",
-        "For baselines, we will create a pipeline that converts strings to ordinal features.\n",
-        "\n",
-        "For TabPFN, we simply pass the raw data with the text column directly to the classifier."
+      "text/plain": [
+       "Output()"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 14,
-      "metadata": {
-        "id": "ktXNMVFCsEHZ",
-        "outputId": "fa5bd253-55d1-48a6-a91b-670b78326586",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 841
-        }
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "Processing: 100%|██████████| [00:01<00:00]\n",
-            "Processing: 100%|██████████| [00:01<00:00]\n",
-            "Processing: 100%|██████████| [00:01<00:00]\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:   18.4s finished\n",
-            "Processing: 100%|██████████| [00:00<00:00]\n",
-            "Processing: 100%|██████████| [00:00<00:00]\n",
-            "Processing: 100%|██████████| [00:00<00:00]\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    8.4s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    2.0s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.8s finished\n",
-            "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    9.2s finished\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 1000x600 with 1 Axes>"
-            ],
-            "image/png": 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bNkyS0nxz/89vvu+mcePGOnbsmObPn6/q1avro48+Up06dfTRRx9laP30ZGW/33nnHZUoUcL6qF+/fpZe29vbW5cvX7Y+r1+/vs1233nnnSxt90FLndTjt99+y9R6Gf05p2f69Onau3evRo0apcTERA0ZMkSPP/64dUITd3d3ff/999q0aZO6d++uvXv3qmPHjmrWrJl1wop/vrclSpTQ8uXLJUnBwcHy8PDQihUrJEkrVqyQk5OT2rdvb339zB7T2eWHH35Q27Zt5ebmplmzZmndunXauHGjunTpkqHfzexwP38bAGQfptYGcFfPP/+8XnrpJe3YscP6ISc9ZcuW1aZNm3T16lWb0aGDBw9al6f+NyUlRceOHbP5BvXQoUM220udaS45OVlBQUHZsi/BwcHavn27Vq5cqc6dO9+1b2q9hw4dspkVKykpSSdOnMi2mv7pyJEjNt/yHz16VCkpKfLx8ZEkffnll7px44bWrFljM/Ly7bff3vdrFyxYUL1791bv3r117do1NW7cWBMmTFDfvn1t3ot/O3jwoAoXLpwt0zn36NHD5tS0rH7IP378uIoUKWJ9vmTJEutohaQ7znKWqmzZsnfc19Tld1pPUrqnG6a3vX9r1KiRChQooGXLlmnUqFFZnrY5s8eur6+vfH19NWbMGOukGHPmzNGbb74pSXJyclLTpk3VtGlThYeHa8qUKRo9erS+/fZbBQUFpZl18PHHH5ck5cmTR88884w+/fRThYeHa/ny5XriiSdUsmRJa9/sPKYz8/6vXLlSbm5u2rBhg81U8wsWLEizbnqz+t3t9R/m3wwA94+RIQB3lTdvXs2ePVsTJkxQcHDwHfu1bt1aycnJev/9923aZ8yYIYvFolatWkmS9b/vvvuuTb9/zw7n7Oysdu3aaeXKldq3b1+a18vKKVQDBgxQiRIlNHz4cB0+fDjN8gsXLlg/AAYFBcnFxUXvvvuuzTe18+bNU2xsbLqz392vf8+e9d5770n633uW+uH4n/XExsam+wEuM/766y+b53nz5lXFihV148YNSbe/+a9Vq5YWLVpkM0Xwvn379M0336h169b39fqpypcvr6CgIOvjXiN/6R0D69at065du9SyZUtrW2BgoM127xWGWrdurZ07d1pP75JuTxv/wQcfyMfH547X//zzffr31NR3us7onzw8PPT666/rwIEDev3119MdIfjvf/+rnTt33nU7GT124+LidOvWLZt1fX195eTkZP3Z/3OELVXqrISpff753gYFBalEiRLWvh07dtSff/6pjz76SHv27Elzilx2HtOZef+dnZ1lsVhspmM/efKkPv/88zTbzZMnT5qpsdNjj78ZAO4fI0MA7qlnz5737BMcHKynnnpKo0eP1smTJ1WzZk198803+uKLLzR06FDrNUK1atVS586dNWvWLMXGxiogIEBRUVE6evRomm1OnTpV3377rfz9/dWvXz9Vq1ZNly9fVnR0tDZt2pTuB7W7KVCggFavXq3WrVurVq1a6tatm+rWrStJio6O1rJly9SwYUNJt0emRo4cqYkTJ6ply5Zq27atDh06pFmzZql+/fo2Fz5nlxMnTqht27Zq2bKltm/frv/+97/q0qWLatasKUlq3ry5XFxcFBwcrJdeeknXrl3Thx9+qKJFi+rcuXNZft1q1aqpSZMmqlu3rgoWLKhffvlFn332mQYPHmzt8/bbb6tVq1Zq2LChXnzxRSUmJuq9996Tl5eXJkyYcL+7niUBAQGqXbu26tWrJy8vL0VHR2v+/Pny9va+531w7iY0NFTLli1Tq1atNGTIEBUsWFCLFi3SiRMntHLlSpuL4/8tLCxMbdq0UaNGjdSnTx9dvnxZ7733nh5//PF7XqskSSNGjNDvv/+u6dOn69tvv9ULL7yg4sWL6/z58/r888+1c+dObdu27a7byOixu3nzZg0ePFjt27fXY489plu3bmnx4sXWLyKk29eTff/992rTpo3Kli2rCxcuaNasWSpdurTNKN6dtG7dWvny5dOrr75qs91U2X1MZ/T9b9OmjcLDw9WyZUt16dJFFy5cUGRkpCpWrGhzvZwk1a1bV5s2bVJ4eLhKliypcuXK2UyKktn3HcAjxh5T2AF4dP1zau27+ffU2oZxe/rhYcOGGSVLljRy585tVKpUyXj77beNlJQUm36JiYnGkCFDjEKFChl58uQxgoODjTNnzqSZWtswDCMmJsYYNGiQ4e3tbeTOndsoXry40bRpU+ODDz6w9sno1Nqp/vzzT2PYsGHGY489Zri5uRkeHh5G3bp1jcmTJxuxsbE2fd9//32jSpUqRu7cuY1ixYoZL7/8svH333/b9HnyySeNxx9/PEPvkWGknc45dTrq/fv3Gy+88IKRL18+o0CBAsbgwYONxMREm3XXrFlj1KhRw3BzczN8fHyMadOmGfPnz7eZ4vdur5267J9TBb/55puGn5+fkT9/fsPd3d2oUqWKMXnyZCMpKclmvU2bNhmBgYGGu7u74enpaQQHBxv79++36ZO6L/+eivnf0xBnh9GjRxu1atUyvLy8jNy5cxtlypQxXn75ZeP8+fMZ3sa/fxapjh07ZrzwwgtG/vz5DTc3N8PPz8/46quvbPrc6bhbuXKlUbVqVcPV1dWoVq2asWrVKqNnz573nFr7nz777DOjefPmRsGCBY1cuXIZJUqUMDp27Ghs2bLF2udev6v3OnaPHz9u9OnTx6hQoYLh5uZmFCxY0HjqqaeMTZs2WftERUUZzz77rFGyZEnDxcXFKFmypNG5c2fj8OHDGd6Xrl27GpKMoKCgdJdn9JjOyNTahpHx93/evHlGpUqVDFdXV6NKlSrGggULrMfvPx08eNBo3Lix4e7ubkiy/u7c6Zi+n78ZmT1OANw/i2FwpR4A2FPqTU8vXryowoUL27scAABMg2uGAAAAAJgSYQgAAACAKRGGAAAAAJgS1wwBAAAAMCVGhgAAAACYksPcZyglJUV//vmn8uXLl+G7RQMAAABwPIZh6OrVqypZsuRd7w/nMGHozz//lLe3t73LAAAAAPCIOHPmjEqXLn3H5Q4ThvLlyyfp9g57enrauRoAAAAA9hIXFydvb29rRrgThwlDqafGeXp6EoYAAAAA3PPyGSZQAAAAAGBKhCEAAAAApkQYAgAAAGBKDnPNEAAAAJAZKSkpSkpKsncZyILcuXPL2dn5vrdDGAIAAIDpJCUl6cSJE0pJSbF3Kcii/Pnzq3jx4vd1j1HCEAAAAEzFMAydO3dOzs7O8vb2vutNOfHoMQxDCQkJunDhgiSpRIkSWd4WYQgAAACmcuvWLSUkJKhkyZLy8PCwdznIAnd3d0nShQsXVLRo0SyfMkcMBgAAgKkkJydLklxcXOxcCe5HapC9efNmlrdBGAIAAIAp3c+1JrC/7Pj5EYYAAAAAmBJhCAAAAIApMYECAAAAIMkndO1Dfb2TU9s81NdDWowMAQAAADlAr169ZLFYZLFYlDt3bpUrV06vvfaarl+/nqbvV199pSeffFL58uWTh4eH6tevr4ULF6a73ZUrV6pJkyby8vJS3rx5VaNGDU2aNEmXL1++Z00vvfSSnJ2d9emnn6Zb73PPPZemfcuWLbJYLLpy5Yq1LSkpSW+99ZZq1qwpDw8PFS5cWIGBgVqwYMF9TZBwL4QhAAAAIIdo2bKlzp07p+PHj2vGjBmaO3euxo8fb9Pnvffe07PPPqvAwED99NNP2rt3rzp16qQBAwbo1Vdftek7evRodezYUfXr19fXX3+tffv2afr06dqzZ48WL15811oSEhL0ySef6LXXXtP8+fOzvE9JSUlq0aKFpk6dqv79+2vbtm3auXOnBg0apPfee0+///57lrd9L5wm9xA87CFXR8HQMQAAgC1XV1cVL15ckuTt7a2goCBt3LhR06ZNkySdOXNGw4cP19ChQzVlyhTresOHD5eLi4uGDBmi9u3by9/fXzt37tSUKVMUERGhV155xdrXx8dHzZo1sxm5Sc+nn36qatWqKTQ0VCVLltSZM2fk7e2d6X2KiIjQ999/r19++UW1a9e2tpcvX17t27dXUlJSpreZUYwMAQAAADnQvn37tG3bNpv7JX322We6efNmmhEg6fYpbXnz5tWyZcskSUuWLFHevHk1cODAdLefP3/+u77+vHnz1K1bN3l5ealVq1Z3PA3vXpYsWaKgoCCbIJQqd+7cypMnT5a2mxGEIQAAACCH+Oqrr5Q3b165ubnJ19dXFy5c0IgRI6zLDx8+LC8vL5UoUSLNui4uLipfvrwOHz4sSTpy5IjKly+v3LlzZ7qOI0eOaMeOHerYsaMkqVu3blqwYIEMw8jStqpUqZLp9bIDYQgAAADIIZ566int3r1bP/30k3r27KnevXurXbt2WdpWVoJLqvnz56tFixYqXLiwJKl169aKjY3V5s2bH2od94swBAAAAOQQefLkUcWKFVWzZk3Nnz9fP/30k+bNm2dd/thjjyk2NlZ//vlnmnWTkpJ07NgxPfbYY9a+x48fz/RsbcnJyVq0aJHWrl2rXLlyKVeuXPLw8NDly5dtJlLw9PRUbGxsmvWvXLkiZ2dn6+lvjz32mA4ePJipGrILYQgAAADIgZycnDRq1CiNGTNGiYmJkqR27dopd+7cmj59epr+c+bMUXx8vDp37ixJ6tKli65du6ZZs2alu/07TaCwbt06Xb16Vb/++qt2795tfSxbtkyrVq2yrle5cmX9/vvvunHjhs360dHRKleunPX0vC5dumjTpk369ddf07zWzZs3FR8fn6H3IysIQwAAAEAO1b59ezk7OysyMlKSVKZMGb311luKiIjQ6NGjdfDgQR07dkzh4eF67bXXNHz4cPn7+0uS/P39rW2vvfaatm/frlOnTikqKkrt27fXokWL0n3NefPmqU2bNqpZs6aqV69ufXTo0EH58+fXkiVLJEldu3aVxWJRjx49tGvXLh09elTz589XRESEhg8fbt3e0KFDFRgYqKZNmyoyMlJ79uzR8ePHtWLFCjVo0EBHjhx5YO8fU2sDAAAAypm39ciVK5cGDx6st956Sy+//LLy5MmjoUOHqnz58nrnnXc0c+ZMJScn6/HHH9fs2bPVu3dvm/WnTZumunXrKjIyUnPmzFFKSooqVKigF154QT179kzzejExMVq7dq2WLl2aZpmTk5Oef/55zZs3T4MGDVL+/Pn1ww8/KDQ0VG3btlVsbKwqVqyo8PBwvfjii9b1XF1dtXHjRut9k1599VV5eHioatWqGjJkiKpXr579b9z/ZzHsecVSNoqLi5OXl5diY2Pl6elp73JscJ+hrMmJf5AAAMCj7/r16zpx4oTKlSsnNzc3e5eDLLrbzzGj2YDT5AAAAACYEmEIAAAAgCkRhgAAAACYEmEIAAAAgCkRhgAAAGBKDjKPmGllx8+PMAQAAABTcXZ2liQlJSXZuRLcj4SEBEmy3rw1K7jPEAAAAEwlV65c8vDw0MWLF5U7d245OTE+kJMYhqGEhARduHBB+fPnt4bbrCAMAQAAwFQsFotKlCihEydO6NSpU/YuB1mUP39+FS9e/L62QRgCAACA6bi4uKhSpUqcKpdD5c6d+75GhFIRhgAAAGBKTk5OcnNzs3cZsCNOkAQAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKaUpTAUGRkpHx8fubm5yd/fXzt37rxr/4iICFWuXFnu7u7y9vbWsGHDdP36devy5ORkjR07VuXKlZO7u7sqVKigN954Q4ZhZKU8AAAAALinXJldYfny5QoJCdGcOXPk7++viIgItWjRQocOHVLRokXT9F+6dKlCQ0M1f/58BQQE6PDhw+rVq5csFovCw8MlSdOmTdPs2bO1aNEiPf744/rll1/Uu3dveXl5aciQIfe/lwAAAADwL5kOQ+Hh4erXr5969+4tSZozZ47Wrl2r+fPnKzQ0NE3/bdu2KTAwUF26dJEk+fj4qHPnzvrpp59s+jz77LNq06aNtc+yZcvuOuJ048YN3bhxw/o8Li4us7sCAAAAwMQydZpcUlKSdu3apaCgoP9twMlJQUFB2r59e7rrBAQEaNeuXdZgc/z4ca1bt06tW7e26RMVFaXDhw9Lkvbs2aOtW7eqVatWd6wlLCxMXl5e1oe3t3dmdgUAAACAyWVqZOjSpUtKTk5WsWLFbNqLFSumgwcPprtOly5ddOnSJTVq1EiGYejWrVsaMGCARo0aZe0TGhqquLg4ValSRc7OzkpOTtbkyZPVtWvXO9YycuRIhYSEWJ/HxcURiAAAAABk2AOfTW7Lli2aMmWKZs2apejoaK1atUpr167VG2+8Ye2zYsUKLVmyREuXLlV0dLQWLVqkd955R4sWLbrjdl1dXeXp6WnzAAAAAICMytTIUOHCheXs7KyYmBib9piYGBUvXjzddcaOHavu3burb9++kiRfX1/Fx8erf//+Gj16tJycnDRixAiFhoaqU6dO1j6nTp1SWFiYevbsmZX9AgAAAIC7ytTIkIuLi+rWrauoqChrW0pKiqKiotSwYcN010lISJCTk+3LODs7S5J16uw79UlJSclMeQAAAACQYZmeTS4kJEQ9e/ZUvXr15Ofnp4iICMXHx1tnl+vRo4dKlSqlsLAwSVJwcLDCw8NVu3Zt+fv76+jRoxo7dqyCg4OtoSg4OFiTJ09WmTJl9Pjjj+vXX39VeHi4+vTpk427CgAAAAD/k+kw1LFjR128eFHjxo3T+fPnVatWLa1fv946qcLp06dtRnnGjBkji8WiMWPG6OzZsypSpIg1/KR67733NHbsWA0cOFAXLlxQyZIl9dJLL2ncuHHZsIsAAAAAkJbFSD1XLYeLi4uTl5eXYmNjH7nJFHxC19q7hBzp5NQ29i4BAAAAOVBGs8EDn00OAAAAAB5FhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKhCEAAAAApkQYAgAAAGBKWQpDkZGR8vHxkZubm/z9/bVz58679o+IiFDlypXl7u4ub29vDRs2TNevX7fpc/bsWXXr1k2FChWSu7u7fH199csvv2SlPAAAAAC4p1yZXWH58uUKCQnRnDlz5O/vr4iICLVo0UKHDh1S0aJF0/RfunSpQkNDNX/+fAUEBOjw4cPq1auXLBaLwsPDJUl///23AgMD9dRTT+nrr79WkSJFdOTIERUoUOD+9xAAAAAA0pHpMBQeHq5+/fqpd+/ekqQ5c+Zo7dq1mj9/vkJDQ9P037ZtmwIDA9WlSxdJko+Pjzp37qyffvrJ2mfatGny9vbWggULrG3lypXL9M4AAAAAQEZl6jS5pKQk7dq1S0FBQf/bgJOTgoKCtH379nTXCQgI0K5du6yn0h0/flzr1q1T69atrX3WrFmjevXqqX379ipatKhq166tDz/88K613LhxQ3FxcTYPAAAAAMioTIWhS5cuKTk5WcWKFbNpL1asmM6fP5/uOl26dNGkSZPUqFEj5c6dWxUqVFCTJk00atQoa5/jx49r9uzZqlSpkjZs2KCXX35ZQ4YM0aJFi+5YS1hYmLy8vKwPb2/vzOwKAAAAAJN74LPJbdmyRVOmTNGsWbMUHR2tVatWae3atXrjjTesfVJSUlSnTh1NmTJFtWvXVv/+/dWvXz/NmTPnjtsdOXKkYmNjrY8zZ8486F0BAAAA4EAydc1Q4cKF5ezsrJiYGJv2mJgYFS9ePN11xo4dq+7du6tv376SJF9fX8XHx6t///4aPXq0nJycVKJECVWrVs1mvapVq2rlypV3rMXV1VWurq6ZKR8AAAAArDI1MuTi4qK6desqKirK2paSkqKoqCg1bNgw3XUSEhLk5GT7Ms7OzpIkwzAkSYGBgTp06JBNn8OHD6ts2bKZKQ8AAAAAMizTs8mFhISoZ8+eqlevnvz8/BQREaH4+Hjr7HI9evRQqVKlFBYWJkkKDg5WeHi4ateuLX9/fx09elRjx45VcHCwNRQNGzZMAQEBmjJlijp06KCdO3fqgw8+0AcffJCNuwoAAAAA/5PpMNSxY0ddvHhR48aN0/nz51WrVi2tX7/eOqnC6dOnbUaCxowZI4vFojFjxujs2bMqUqSIgoODNXnyZGuf+vXra/Xq1Ro5cqQmTZqkcuXKKSIiQl27ds2GXQQAAACAtCxG6rlqOVxcXJy8vLwUGxsrT09Pe5djwyd0rb1LyJFOTm1j7xIAAACQA2U0Gzzw2eQAAAAA4FFEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSlkKQ5GRkfLx8ZGbm5v8/f21c+fOu/aPiIhQ5cqV5e7uLm9vbw0bNkzXr19Pt+/UqVNlsVg0dOjQrJQGAAAAABmS6TC0fPlyhYSEaPz48YqOjlbNmjXVokULXbhwId3+S5cuVWhoqMaPH68DBw5o3rx5Wr58uUaNGpWm788//6y5c+eqRo0amd8TAAAAAMiETIeh8PBw9evXT71791a1atU0Z84ceXh4aP78+en237ZtmwIDA9WlSxf5+PioefPm6ty5c5rRpGvXrqlr16768MMPVaBAgaztDQAAAABkUKbCUFJSknbt2qWgoKD/bcDJSUFBQdq+fXu66wQEBGjXrl3W8HP8+HGtW7dOrVu3tuk3aNAgtWnTxmbbd3Pjxg3FxcXZPAAAAAAgo3JlpvOlS5eUnJysYsWK2bQXK1ZMBw8eTHedLl266NKlS2rUqJEMw9CtW7c0YMAAm9PkPvnkE0VHR+vnn3/OcC1hYWGaOHFiZsoHAAAAAKsHPpvcli1bNGXKFM2aNUvR0dFatWqV1q5dqzfeeEOSdObMGb3yyitasmSJ3NzcMrzdkSNHKjY21vo4c+bMg9oFAAAAAA4oUyNDhQsXlrOzs2JiYmzaY2JiVLx48XTXGTt2rLp3766+fftKknx9fRUfH6/+/ftr9OjR2rVrly5cuKA6depY10lOTtb333+v999/Xzdu3JCzs3Oa7bq6usrV1TUz5QMAAACAVaZGhlxcXFS3bl1FRUVZ21JSUhQVFaWGDRumu05CQoKcnGxfJjXcGIahpk2b6rffftPu3butj3r16qlr167avXt3ukEIAAAAAO5XpkaGJCkkJEQ9e/ZUvXr15Ofnp4iICMXHx6t3796SpB49eqhUqVIKCwuTJAUHBys8PFy1a9eWv7+/jh49qrFjxyo4OFjOzs7Kly+fqlevbvMaefLkUaFChdK0AwAAAEB2yXQY6tixoy5evKhx48bp/PnzqlWrltavX2+dVOH06dM2I0FjxoyRxWLRmDFjdPbsWRUpUkTBwcGaPHly9u0FAAAAAGSSxTAMw95FZIe4uDh5eXkpNjZWnp6e9i7Hhk/oWnuXkCOdnNrG3iUAAAAgB8poNnjgs8kBAAAAwKOIMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlAhDAAAAAEyJMAQAAADAlLIUhiIjI+Xj4yM3Nzf5+/tr586dd+0fERGhypUry93dXd7e3ho2bJiuX79uXR4WFqb69esrX758Klq0qJ577jkdOnQoK6UBAAAAQIZkOgwtX75cISEhGj9+vKKjo1WzZk21aNFCFy5cSLf/0qVLFRoaqvHjx+vAgQOaN2+eli9frlGjRln7fPfddxo0aJB27NihjRs36ubNm2revLni4+OzvmcAAAAAcBcWwzCMzKzg7++v+vXr6/3335ckpaSkyNvbW//5z38UGhqapv/gwYN14MABRUVFWduGDx+un376SVu3bk33NS5evKiiRYvqu+++U+PGjdPtc+PGDd24ccP6PC4uTt7e3oqNjZWnp2dmdumB8wlda+8ScqSTU9vYuwQAAADkQHFxcfLy8rpnNsjUyFBSUpJ27dqloKCg/23AyUlBQUHavn17uusEBARo165d1lPpjh8/rnXr1ql169Z3fJ3Y2FhJUsGCBe/YJywsTF5eXtaHt7d3ZnYFAAAAgMnlykznS5cuKTk5WcWKFbNpL1asmA4ePJjuOl26dNGlS5fUqFEjGYahW7duacCAATanyf1TSkqKhg4dqsDAQFWvXv2OtYwcOVIhISHW56kjQwAAAACQEQ98NrktW7ZoypQpmjVrlqKjo7Vq1SqtXbtWb7zxRrr9Bw0apH379umTTz6563ZdXV3l6elp8wAAAACAjMrUyFDhwoXl7OysmJgYm/aYmBgVL1483XXGjh2r7t27q2/fvpIkX19fxcfHq3///ho9erScnP6XxwYPHqyvvvpK33//vUqXLp3ZfQEAAACADMvUyJCLi4vq1q1rMxlCSkqKoqKi1LBhw3TXSUhIsAk8kuTs7CxJSp27wTAMDR48WKtXr9bmzZtVrly5TO0EAAAAAGRWpkaGJCkkJEQ9e/ZUvXr15Ofnp4iICMXHx6t3796SpB49eqhUqVIKCwuTJAUHBys8PFy1a9eWv7+/jh49qrFjxyo4ONgaigYNGqSlS5fqiy++UL58+XT+/HlJkpeXl9zd3bNrXwEAAADAKtNhqGPHjrp48aLGjRun8+fPq1atWlq/fr11UoXTp0/bjASNGTNGFotFY8aM0dmzZ1WkSBEFBwdr8uTJ1j6zZ8+WJDVp0sTmtRYsWKBevXplYbcAAAAA4O4yfZ+hR1VG5xK3B+4zlDXcZwgAAABZ8UDuMwQAAAAAjoIwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATClLYSgyMlI+Pj5yc3OTv7+/du7cedf+ERERqly5stzd3eXt7a1hw4bp+vXr97VNAAAAALgfmQ5Dy5cvV0hIiMaPH6/o6GjVrFlTLVq00IULF9Ltv3TpUoWGhmr8+PE6cOCA5s2bp+XLl2vUqFFZ3iYAAAAA3K9Mh6Hw8HD169dPvXv3VrVq1TRnzhx5eHho/vz56fbftm2bAgMD1aVLF/n4+Kh58+bq3LmzzchPZrcJAAAAAPcrU2EoKSlJu3btUlBQ0P824OSkoKAgbd++Pd11AgICtGvXLmv4OX78uNatW6fWrVtneZuSdOPGDcXFxdk8AAAAACCjcmWm86VLl5ScnKxixYrZtBcrVkwHDx5Md50uXbro0qVLatSokQzD0K1btzRgwADraXJZ2aYkhYWFaeLEiZkpHwAAAACsHvhsclu2bNGUKVM0a9YsRUdHa9WqVVq7dq3eeOON+9ruyJEjFRsba32cOXMmmyoGAAAAYAaZGhkqXLiwnJ2dFRMTY9MeExOj4sWLp7vO2LFj1b17d/Xt21eS5Ovrq/j4ePXv31+jR4/O0jYlydXVVa6urpkpHwAAAACsMjUy5OLiorp16yoqKsralpKSoqioKDVs2DDddRISEuTkZPsyzs7OkiTDMLK0TQAAAAC4X5kaGZKkkJAQ9ezZU/Xq1ZOfn58iIiIUHx+v3r17S5J69OihUqVKKSwsTJIUHBys8PBw1a5dW/7+/jp69KjGjh2r4OBgayi61zYBAAAAILtlOgx17NhRFy9e1Lhx43T+/HnVqlVL69evt06AcPr0aZuRoDFjxshisWjMmDE6e/asihQpouDgYE2ePDnD2wQAAACA7GYxDMOwdxHZIS4uTl5eXoqNjZWnp6e9y7HhE7rW3iXkSCentrF3CQAAAMiBMpoNHvhscgAAAADwKCIMAQAAADAlwhAAAAAAUyIMAQAAADAlwhAAAAAAUyIMAQAAADAlwhAAAAAAUyIMAQAAADAlwhAAAAAAUyIMAQAAADAlwhAAAAAAUyIMAQAAADAlwhAAAAAAUyIMAQAAADAlwhAAAAAAUyIMAQAAADAlwhAAAAAAUyIMAQAAADAlwhAAAAAAU8pl7wIAADmPT+hae5eQI52c2sbeJQAA/oGRIQAAAACmRBgCAAAAYEqEIQAAAACmRBgCAAAAYEqEIQAAAACmRBgCAAAAYEpMrQ04EKY7zhqmOwYAwJwYGQIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSoQhAAAAAKZEGAIAAABgSlkKQ5GRkfLx8ZGbm5v8/f21c+fOO/Zt0qSJLBZLmkebNm2sfa5du6bBgwerdOnScnd3V7Vq1TRnzpyslAYAAAAAGZLpMLR8+XKFhIRo/Pjxio6OVs2aNdWiRQtduHAh3f6rVq3SuXPnrI99+/bJ2dlZ7du3t/YJCQnR+vXr9d///lcHDhzQ0KFDNXjwYK1ZsybrewYAAAAAd5ErsyuEh4erX79+6t27tyRpzpw5Wrt2rebPn6/Q0NA0/QsWLGjz/JNPPpGHh4dNGNq2bZt69uypJk2aSJL69++vuXPnaufOnWrbtm1mSwQAAAAyxSd0rb1LyJFOTm1z706PsEyNDCUlJWnXrl0KCgr63wacnBQUFKTt27dnaBvz5s1Tp06dlCdPHmtbQECA1qxZo7Nnz8owDH377bc6fPiwmjdvfsft3LhxQ3FxcTYPAAAAAMioTIWhS5cuKTk5WcWKFbNpL1asmM6fP3/P9Xfu3Kl9+/apb9++Nu3vvfeeqlWrptKlS8vFxUUtW7ZUZGSkGjdufMdthYWFycvLy/rw9vbOzK4AAAAAMLmHOpvcvHnz5OvrKz8/P5v29957Tzt27NCaNWu0a9cuTZ8+XYMGDdKmTZvuuK2RI0cqNjbW+jhz5syDLh8AAACAA8nUNUOFCxeWs7OzYmJibNpjYmJUvHjxu64bHx+vTz75RJMmTbJpT0xM1KhRo7R69WrrDHM1atTQ7t279c4779ickvdPrq6ucnV1zUz5AAAAAGCVqZEhFxcX1a1bV1FRUda2lJQURUVFqWHDhndd99NPP9WNGzfUrVs3m/abN2/q5s2bcnKyLcXZ2VkpKSmZKQ8AAAAAMizTs8mFhISoZ8+eqlevnvz8/BQREaH4+Hjr7HI9evRQqVKlFBYWZrPevHnz9Nxzz6lQoUI27Z6ennryySc1YsQIubu7q2zZsvruu+/08ccfKzw8/D52DQAAAADuLNNhqGPHjrp48aLGjRun8+fPq1atWlq/fr11UoXTp0+nGeU5dOiQtm7dqm+++SbdbX7yyScaOXKkunbtqsuXL6ts2bKaPHmyBgwYkIVdAgAAAIB7y3QYkqTBgwdr8ODB6S7bsmVLmrbKlSvLMIw7bq948eJasGBBVkoBAAAAgCx5qLPJAQAAAMCjgjAEAAAAwJQIQwAAAABMiTAEAAAAwJQIQwAAAABMiTAEAAAAwJQIQwAAAABMiTAEAAAAwJQIQwAAAABMiTAEAAAAwJQIQwAAAABMiTAEAAAAwJQIQwAAAABMiTAEAAAAwJQIQwAAAABMiTAEAAAAwJRy2bsAAACAO/EJXWvvEnKkk1Pb2LsEIEdgZAgAAACAKRGGAAAAAJgSYQgAAACAKRGGAAAAAJgSYQgAAACAKRGGAAAAAJgSYQgAAACAKRGGAAAAAJgSYQgAAACAKRGGAAAAAJgSYQgAAACAKRGGAAAAAJhSLnsXkF0Mw5AkxcXF2bmStFJuJNi7hBzpUfxZPuo41rKGYy3zONayhmMt8zjWsoZjLfM41rLmUT3WUutKzQh3YjHu1SOH+OOPP+Tt7W3vMgAAAAA8Is6cOaPSpUvfcbnDhKGUlBT9+eefypcvnywWi73LyRHi4uLk7e2tM2fOyNPT097lwIFxrOFh4VjDw8KxhoeFYy1rDMPQ1atXVbJkSTk53fnKIIc5Tc7JyemuqQ935unpyS8XHgqONTwsHGt4WDjW8LBwrGWel5fXPfswgQIAAAAAUyIMAQAAADAlwpCJubq6avz48XJ1dbV3KXBwHGt4WDjW8LBwrOFh4Vh7sBxmAgUAAAAAyAxGhgAAAACYEmEIAAAAgCkRhgAAAACYEmEIAAAAgCkRhgAAAACYEmHIRMqXL6+//vorTfuVK1dUvnx5O1QEAAAA2E8uexeAh+fkyZNKTk5O037jxg2dPXvWDhXB0Zw+fTpD/cqUKfOAKwGA7Hf69Gl5e3vLYrHYtBuGoTNnzvC3Ddnm6aef1qpVq5Q/f36b9ri4OD333HPavHmzfQpzQIQhE1izZo313xs2bJCXl5f1eXJysqKiouTj42OHyuBofHx80nxIkG5/UEhtt1gsunXr1sMuDQ6sfPny+vnnn1WoUCGb9itXrqhOnTo6fvy4nSqDoylXrpzOnTunokWL2rRfvnxZ5cqVS/cLRyArtmzZoqSkpDTt169f1w8//GCHihwXYcgEnnvuOUm3P4T27NnTZlnu3Lnl4+Oj6dOn26EyOJpff/013XbDMPTJJ5/o3XffVd68eR9yVXB0jHrjYfnnFzv/dO3aNbm5udmhIjiavXv3Wv+9f/9+nT9/3vo8OTlZ69evV6lSpexRmsMiDJlASkqKpNvfaP38888qXLiwnSuCo6pZs2aatk2bNik0NFSHDx/Wa6+9puHDh9uhMjgiRr3xsISEhEi6/aXi2LFj5eHhYV2WnJysn376SbVq1bJTdXAktWrVksVikcVi0dNPP51mubu7u9577z07VOa4CEMmcvz48XS/0ZKkhIQEmz/uwP2Kjo7W66+/rh9++EF9+/bVunXr0pxaAtwPRr3xsKSOehuGod9++00uLi7WZS4uLqpZs6ZeffVVe5UHB3LixAkZhqHy5ctr586dKlKkiHWZi4uLihYtKmdnZztW6HgshmEY9i4CD0fTpk318ccfpxle/emnn9S9e3cdPnzYTpXBkRw7dkyjRo3SypUr1aFDB7355pvMVogHilFvPCy9e/fWzJkz5enpae9SAGQTptY2ETc3N9WoUUPLly+XdPv0uQkTJuiJJ55Q69at7VwdHMHAgQNVrVo1xcbG6pdfftHSpUsJQnjgTpw4kSYIXblyxT7FwKEtWLDAJgjFxcXp888/18GDB+1YFRzRokWLtHbtWuvz1157Tfnz51dAQIBOnTplx8ocDyNDJhMZGanXXntNzz77rE6ePKlTp05pwYIFat68ub1LgwNwcnKSm5ubqlSpctd+0dHRD6kimMG0adPk4+Ojjh07SpLat2+vlStXqkSJElq3bl2617IBWdGhQwc1btxYgwcPVmJiomrWrKmTJ09aJ4lp166dvUuEg6hcubJmz56tp59+Wtu3b1fTpk0VERGhr776Srly5dKqVavsXaLD4Johkxk0aJD++OMPTZs2Tbly5dKWLVsUEBBg77LgIMaNG3fH69KAB2XOnDlasmSJJGnjxo3atGmT1q9frxUrVmjEiBH65ptv7FwhHMX333+v0aNHS5JWr14twzB05coVLVq0SG+++SZhCNnmzJkzqlixoiTp888/1wsvvKD+/fsrMDBQTZo0sW9xDoYwZCJ///23+vbtq6ioKM2dO1ffffedmjdvrrfeeksDBw60d3lwABMmTLB3CTCh8+fPy9vbW5L01VdfqUOHDmrevLl8fHzk7+9v5+rgSGJjY1WwYEFJ0vr169WuXTt5eHioTZs2GjFihJ2rgyPJmzev/vrrL5UpU0bffPONdUZDNzc3JSYm2rk6x8I1QyZSvXp1xcTE6Ndff1W/fv303//+V/PmzdPYsWPVpk0be5cHB7B582ZuqIqHrkCBAjpz5oyk2x9Qg4KCJN2e+YubYCI7eXt7a/v27YqPj9f69eutp5j//fff3GcI2apZs2bq27ev+vbtq8OHD1uv7f7999+5ZUA2IwyZyIABA/T999+rXLly1raOHTtqz5496d7lGMisZs2a6fLly9bnDRo04KaXeOD+7//+T126dFGzZs30119/qVWrVpJuT4ecepoJkB2GDh2qrl27qnTp0ipZsqT1dKXvv/9evr6+9i0ODiUyMlINGzbUxYsXtXLlShUqVEiStGvXLnXu3NnO1TkWJlAwqevXr/MtFrKdk5OTzp8/b72fUL58+bRnzx5mlMMDdfPmTc2cOVNnzpxRr169VLt2bUnSjBkzlC9fPvXt29fOFcKR/PLLLzpz5oyaNWumvHnzSpLWrl2r/PnzKzAw0M7VAcgswpCJpKSkaPLkyZozZ45iYmJ0+PBhlS9fXmPHjpWPj49efPFFe5eIHI4wBMAsUj8+MWkMHpQrV65o3rx5OnDggCTp8ccfV58+feTl5WXnyhwLp8mZyJtvvqmFCxfqrbfesrl7dvXq1fXRRx/ZsTI4CovFYvPB4N/PgQdl8eLFatSokUqWLGm9B0dERIS++OILO1cGR/Pxxx/L19dX7u7ucnd3V40aNbR48WJ7lwUH88svv6hChQqaMWOGLl++rMuXLys8PFwVKlTg9hTZjJEhE6lYsaLmzp2rpk2b2nxjf/DgQTVs2FB///23vUtEDufk5KTq1asrV67bE1Xu3btXVapUsQnfEvcZQvaaPXu2xo0bp6FDh2ry5Mnat2+fypcvr4ULF2rRokX69ttv7V0iHER4eLjGjh2rwYMHW0+J27p1qyIjI/Xmm29q2LBhdq4QjuKJJ55QxYoV9eGHH1r/n3rr1i317dtXx48f1/fff2/nCh0HYchE3N3ddfDgQZUtW9YmDO3fv19+fn66du2avUtEDjdx4sQM9Rs/fvwDrgRmUq1aNU2ZMkXPPfeczd+2ffv2qUmTJrp06ZK9S4SDKFeunCZOnKgePXrYtC9atEgTJkzQiRMn7FQZHI27u7t+/fXXNDcx379/v+rVq6eEhAQ7VeZ4uM+QiVSrVk0//PCDypYta9P+2WefWS84Bu4HIQf2cOLEiXT/hrm6uio+Pt4OFcFRnTt3Lt0blQcEBOjcuXN2qAiOytPTU6dPn04Ths6cOaN8+fLZqSrHRBgygT59+mjmzJkaN26cevbsqbNnzyolJUWrVq3SoUOH9PHHH+urr76yd5lwEDt27NCXX36ppKQkNW3aVC1btrR3SXBw5cqV0+7du9N80bN+/XpVrVrVTlXBEVWsWFErVqzQqFGjbNqXL1+uSpUq2akqOKKOHTvqxRdf1DvvvGMN4D/++KNGjBjB1NrZjNPkTMDZ2Vnnzp1T0aJF9cMPP2jSpEnas2ePrl27pjp16mjcuHHWG8cB9+Ozzz5Tx44d5e7urty5cysuLk7Tpk3Tq6++au/S4MA++ugjTZgwQdOnT9eLL76ojz76SMeOHVNYWJg++ugjderUyd4lwkGsXLlSHTt2VFBQkPWaoR9//FFRUVFasWKFnn/+eTtXCEeRlJSkESNGaM6cOdabmefOnVsvv/yypk6dKldXVztX6DgIQybw7+mOgQelbt26ql+/viIjI+Xs7KywsDC9/fbbNjdiBR6EJUuWaMKECTp27JgkqWTJkpo4cSK3DEC227Vrl2bMmGGd7rhq1aoaPnw4p5vjgUhISLD+XatQoYI8PDzsXJHjIQyZgJOTk44cOaIiRYrctZ+np+dDqgiOKm/evNq9e7cqVqwo6fY3W3ny5NHZs2cJ43ggbt26paVLl6pFixYqVqyYEhISdO3aNY43AA7jjz/+kCSVLl3azpU4JsKQCTg5Od31Xi+GYchisSg5OfkhVgVHlN4oJDdexYPm4eGhAwcOpLlmCHgQkpOT9fnnn9vcCLNt27Zydna2c2VwJCkpKXrzzTc1ffp062y/+fLl0/DhwzV69Gg5OXGr0OzCBAom8dlnn6lgwYL2LgMm8NFHHylv3rzW57du3dLChQtVuHBha9uQIUPsURoclJ+fn3799VfCEB64o0ePqk2bNvrjjz9UuXJlSVJYWJi8vb21du1aVahQwc4VwlGMHj1a8+bN09SpU23uaTVhwgRdv35dkydPtnOFjoORIRPgmiE8LD4+PncdhZQki8Wi48ePP6SKYAYrVqzQyJEjNWzYMNWtW1d58uSxWV6jRg07VQZH07p1axmGoSVLlli/YPzrr7/UrVs3OTk5ae3atXauEI6iZMmSmjNnjtq2bWvT/sUXX2jgwIE6e/asnSpzPIQhEyAMAXBk6Z0uYrFYOAUY2S5PnjzasWOHfH19bdr37NmjwMBAbl6ObOPm5qa9e/fqscces2k/dOiQatWqpcTERDtV5ng4Tc4EypYtm+Zc5jZt2uijjz5SiRIl7FQVAGSPEydO2LsEmISrq6uuXr2apv3atWtycXGxQ0VwVDVr1tT777+vd99916b9/fffV82aNe1UlWNiZMikuKgdD1pUVFSa6WeHDh2qoKAgO1cGAFnTo0cPRUdHa968efLz85Mk/fTTT+rXr5/q1q2rhQsX2rdAOIzvvvtObdq0UZkyZdSwYUNJ0vbt23XmzBmtW7dOTzzxhJ0rdBxMRQEg282aNUstW7ZUvnz59Morr+iVV16Rp6enWrdurcjISHuXBwd07Ngx/ec//1FQUJCCgoI0ZMgQ6705gOzy7rvvqkKFCmrYsKHc3Nzk5uamwMBAVaxYUTNnzrR3eXAgTz75pA4fPqznn39eV65c0ZUrV/R///d/OnToEEEomzEyZFLVq1fX119/LW9vb3uXAgdUunRphYaGavDgwTbtkZGRmjJlChd+Iltt2LBBbdu2Va1atayzLv3444/as2ePvvzySzVr1szOFcLRHD161GbUO/XeagByHsIQgGz375uvpjpy5Ihq167NRcbIVrVr11aLFi00depUm/bQ0FB98803io6OtlNlAHD/4uPjtXz5ciUmJqp58+aqVKmSvUtyKIQhEzh9+nSG+pUpU+YBVwKz6NKli2rXrq0RI0bYtL/zzjv65Zdf9Mknn9ipMjgiNzc3/fbbb2k+IBw+fFg1atTQ9evX7VQZHMmRI0e0d+9e1alTR+XKldPatWs1bdo0JSYm6rnnntOoUaPueWsB4F5Onz6t7t27Kzo6Wg0aNNC8efPUrFkzHTlyRJLk7u6ur7/+Wo0bN7ZzpY6D2eRM4E73fkmddla6PQ3trVu3HnZpcCD/nPGmWrVqmjx5srZs2WK98HPHjh368ccfNXz4cHuVCAdVpEgR7d69O00Y2r17N7cUQLZYvXq1OnToICcnJ1ksFn3wwQd66aWX1KRJE3l6emrChAnKlSuXXn/9dXuXihzu1VdfVVJSkubMmaMVK1aoRYsWqlSpkr7//ns5OTnp5Zdf1oQJE7R582Z7l+owGBkygT179qTbbhiGPvnkE7377rvKmzevLly48JArgyMpV65chvpx01Vkt0mTJmnGjBkKDQ1VQECApNvXDE2bNk0hISEaO3asnStETlevXj21aNFCb775phYuXKhBgwZpypQpGjp0qCTpgw8+sJk9E8iq4sWLa82aNfLz89Ply5dVuHBh/fjjj9YvFvfs2aOmTZvq0qVLdq7UcRCGTGrTpk0KDQ3V4cOHFRISouHDhytfvnz2LgsAMs0wDEVERGj69On6888/Jd2+e/uIESM0ZMgQTl3CfcuXL592796tChUqKCUlRS4uLtq9e7eqV68uSTp58qSqVaumhIQEO1eKnM7JyUnnzp1TsWLFJN2+Bnfv3r3WW6HExMSoZMmS3Ew6G3GanMlER0fr9ddf1w8//KC+fftq3bp1nEYCIEezWCwaNmyYhg0bZr0hJl/uIDvFx8dbjyknJye5u7vLw8PDutzd3V03btywV3lwMP/8Aocvcx48wpBJHDt2TKNGjdLKlSvVoUMH7d+/nxuu4oH6448/tGbNGp0+fVpJSUk2y8LDw+1UFRxJ48aNtWbNGuXPn1+StGbNGjVr1kzu7u72LQwOx2KxpPmAyodUPCjjxo2zhu2kpCRNnjxZXl5eksTo4wPAaXImMHDgQM2bN09PPfWUpk6dqlq1atm7JDi4qKgotW3bVuXLl9fBgwdVvXp1nTx5UoZhqE6dOlz4iWzh5OSk8+fPW0e3PT09tXv3br7oQbZzcnKSl5eXNQBduXJFnp6ecnK6fe96wzAUFxfHqUu4b02aNMlQ0P72228fQjXmQBgyAScnJ7m5ualKlSp37ce9OJBd/Pz81KpVK02cOFH58uXTnj17VLRoUXXt2lUtW7bUyy+/bO8S4QD+HYZSjzXCELLbokWLMtSvZ8+eD7gSANmN0+RMYNy4cQzn46E6cOCAli1bJknKlSuXEhMTlTdvXk2aNEnPPvssYQhAjkLIwcM2adIkvfrqqzbXpklSYmKi3n77bY0bN85OlTkeRoYAZLvixYvr22+/VdWqVVWtWjVNnTpVbdu21Z49exQYGKhr167Zu0Q4ACcnJy1atMh6Ln3nzp0VERFhnYUpVdu2be1RHhzY1atX9c+PT05OTsqbN68dK4KjcXZ21rlz59JMcvXXX3+paNGinJKZjRgZMoHNmzercePGypWLHzcerEmTJmn48OFq0KCBtm7dqqpVq6p169YaPny4fvvtN61atUoNGjSwd5lwIP/+xv6ll16yeW6xWPjQgPu2e/dujRo1SuvWrZN0e+r2f17IbrFYtH37dtWvX99eJcLBGIaR7lk9e/bsUcGCBe1QkeNiZMgE/v3tQoMGDbRy5UqVKlXKzpXB0aQea9euXdO1a9dUo0YNxcfHa/jw4dq2bZsqVaqk8PBwlS1b1t6lAkCGvfjii6pQoYJGjRol6fb1aXPnzlWpUqVkGIbmz58vwzC0ePFiO1eKnK5AgQKyWCyKjY2Vp6enTSBKTk7WtWvXNGDAAEVGRtqxSsfCUIEJ/Dvv/v7779wPAQ9E6rH2zwvY8+TJozlz5tirJAC4b9u2bdPgwYNt2ho0aGD9W+fu7q4OHTrYozQ4mIiICBmGoT59+mjixInW04AlycXFRT4+PmrYsKEdK3Q8hCEA2YrJOmAPf/75p7Zu3aoLFy4oJSXFZtmQIUPsVBUcxalTp1SkSBHr80mTJqlw4cLW5yVKlFBMTIw9SoODST31t1y5cgoICFDu3LntXJHjIwyZADeLw8P02GOP3fP4unz58kOqBmawcOFCvfTSS3JxcVGhQoXS/L0jDOF+ubm56dSpUypdurQkadiwYTbLz5w5k2bWL+B+PPnkk9Z/X79+Pc3Nyz09PR92SQ6LMGQChmGoadOm1gkUEhISFBwcLBcXF5t+3GcI2eHfw/rAgzZ27FiNGzdOI0eOtN4EE8hOtWvX1ueff67AwMB0l69atUq1a9d+yFXBkSUkJOi1117TihUr9Ndff6VZzsQw2YcwZALjx4+3ef7ss8/aqRKYQadOndJMBQo8SAkJCerUqRNBCA/MwIED1alTJ/n4+Ojll1+2HmvJycmaNWuW3nvvPS1dutTOVcKRjBgxQt9++61mz56t7t27KzIyUmfPntXcuXM1depUe5fnUJhNDkC2udN9EYAH6bXXXlPBggUVGhpq71LgwF5//XW9/fbbypcvn3XihOPHj+vatWsKCQnR22+/becK4UjKlCmjjz/+WE2aNJGnp6eio6NVsWJFLV68WMuWLbNO8477RxgyiR07dujLL79UUlKSmjZtqpYtW9q7JDggJycnnT9/njCEhyo5OVnPPPOMEhMT5evrm+aC4/DwcDtVBkezY8cOLVu2TEeOHJEkVapUSZ07d+b+ach2efPm1f79+1WmTBmVLl1aq1atkp+fn06cOCFfX19uXp6NOE3OBD777DN17NhR7u7uyp07t8LDwzVt2jS9+uqr9i4NDubfs3gBD0NYWJg2bNigypUrS1KaCRSA+zV27FiNHz9eDRo0SDf4nD59Wi+++KI2btxoh+rgiMqXL68TJ06oTJkyqlKlilasWCE/Pz99+eWXyp8/v73LcyiMDJlA3bp1Vb9+fUVGRsrZ2VlhYWF6++23mdELgEMoUKCAZsyYoV69etm7FDioMmXKqFChQlq8eLGqV69us2zu3LkaMWKEAgMD9fXXX9upQjiaGTNmyNnZWUOGDNGmTZsUHBwswzCUlJSkGTNm6JVXXrF3iQ6DMGQCefPm1e7du1WxYkVJUlJSkvLkyaOzZ89yOhOAHK948eL64YcfVKlSJXuXAgcVFxenwYMHa8WKFRo/frxef/11/fHHH+rTp49+/vlnvf322+rfv7+9y4QDO3XqlHbt2qVKlSrJ19fX3uU4FKbeMYGEhASb+ehdXFzk5ubG+aYAHMIrr7yi9957z95lwIF5enrq448/1vLlyzVz5kzVqVNHvr6+slgs2rt3L0EI2Wbz5s2qVq2a4uLibNrLli2rpk2bqlOnTvrhhx/sVJ1j4pohk/joo4+UN29e6/Nbt25p4cKFNnfQ5saEAHKinTt3avPmzfrqq6/0+OOPp5lAYdWqVXaqDI6mQYMG8vX1VVRUlPLkyaMxY8aobNmy9i4LDiQiIkL9+vVL96aqXl5eeumllxQeHq4nnnjCDtU5Jk6TMwEfH597XkRssVh0/Pjxh1QRAGSf3r1733X5ggULHlIlcGTLli3T4MGDVatWLc2aNUvz5s3TzJkzNXDgQIWFhcnNzc3eJcIBlC1bVuvXr1fVqlXTXX7w4EE1b95cp0+ffsiVOS7CEAAAwF20a9dOGzZsUFhYmP7zn/9Y27dt22YN4wsXLlTDhg3tVSIchJubm/bt22e9zvvfjh49Kl9fXyUmJj7kyhwXp8kBABzCxYsXdejQIUlS5cqVVaRIETtXBEdx/vx5/frrr2km6QgICNDu3bsVGhqqJ598UklJSXaqEI6iVKlSdw1De/fuVYkSJR5yVY6NCRRMJioqSs8884wqVKigChUq6JlnntGmTZvsXRYAZFl8fLz69OmjEiVKqHHjxmrcuLFKliypF198UQkJCfYuDw7gbrMVuru7a+bMmfy/FNmidevWGjt2rK5fv55mWWJiosaPH69nnnnGDpU5Lk6TM5FZs2bplVde0QsvvGAdyt+xY4c+++wzzZgxQ4MGDbJzhQCQeS+99JI2bdqk999/X4GBgZKkrVu3asiQIWrWrJlmz55t5woBIGNiYmJUp04dOTs7a/DgwdabSR88eFCRkZFKTk5WdHS0ihUrZudKHQdhyERKly6t0NBQDR482KY9MjJSU6ZM0dmzZ+1UGQBkXeHChfXZZ5+pSZMmNu3ffvutOnTooIsXL9qnMADIglOnTunll1/Whg0blPox3WKxqEWLFoqMjFS5cuXsXKFjIQyZyL9vvprqyJEjql27NvcdApAjeXh4aNeuXWlmX/r999/l5+en+Ph4O1UGAFn3999/6+jRozIMQ5UqVVKBAgXsXZJD4pohE2nbtq1Wr16dpv2LL77g/FMAOVbDhg01fvx4m3PsExMTNXHiRGb3ApBjFShQQPXr15efnx9B6AFiNjkH9+6771r/Xa1aNU2ePFlbtmyxuWboxx9/1PDhw+1VIgDcl5kzZ6pFixYqXbq0atasKUnas2eP3NzctGHDBjtXBwB4lHGanIPL6Hml3HQVQE6WkJCgJUuW6ODBg5KkqlWrqmvXrnJ3d7dzZQCARxlhCAAAAIApcZocACDHWbNmTYb7tm3b9gFWAgDIyRgZMpk//vhDa9as0enTp9PcKTs8PNxOVQFA5jg52c7/Y7FY9O//nVksFklScnLyQ6sLAJCzMDJkIlFRUWrbtq3Kly+vgwcPqnr16jp58qQMw1CdOnXsXR4AZFhKSor135s2bdLrr7+uKVOmWCeH2b59u8aMGaMpU6bYq0QAQA7AyJCJ+Pn5qVWrVpo4caLy5cunPXv2qGjRouratatatmypl19+2d4lAkCmVa9eXXPmzFGjRo1s2n/44Qf1799fBw4csFNlAIBHHfcZMpEDBw6oR48ekqRcuXIpMTFRefPm1aRJkzRt2jQ7VwcAWXPs2DHlz58/TbuXl5dOnjz50OsBAOQchCETyZMnj/U6oRIlSujYsWPWZZcuXbJXWQBwX+rXr6+QkBDFxMRY22JiYjRixAj5+fnZsTIAwKOOMGQCkyZNUnx8vBo0aKCtW7dKklq3bq3hw4dr8uTJ6tOnjxo0aGDnKgEga+bPn69z586pTJkyqlixoipWrKgyZcro7Nmzmjdvnr3LAwA8wrhmyAScnZ117tw5Xbt2TdeuXVONGjUUHx+v4cOHa9u2bapUqZLCw8NVtmxZe5cKAFliGIY2btxoc9PVoKAg64xyAACkhzBkAk5OTjp//ryKFi1q71IAAACARwZTa5sE344CcGRRUVGKiorShQsXbKbdlm6fRgcAQHoIQybx2GOP3TMQXb58+SFVAwDZZ+LEiZo0aZLq1aunEiVK8OUPACDDCEMmMXHiRHl5edm7DADIdnPmzNHChQvVvXt3e5cCAMhhuGbIBLhmCIAjK1SokHbu3KkKFSrYuxQAQA7D1NomwCkjABxZ3759tXTpUnuXAQDIgThNzgQY/APgyK5fv64PPvhAmzZtUo0aNZQ7d26b5eHh4XaqDADwqOM0OQBAjvbUU0/dcZnFYtHmzZsfYjUAgJyEMAQAAADAlLhmCAAAAIApcc0QACDH++WXX7RixQqdPn1aSUlJNstWrVplp6oAAI86RoYAADnaJ598ooCAAB04cECrV6/WzZs39fvvv2vz5s3cXw0AcFeEIQBAjjZlyhTNmDFDX375pVxcXDRz5kwdPHhQHTp0UJkyZexdHgDgEUYYAgDkaMeOHVObNm0kSS4uLoqPj5fFYtGwYcP0wQcf2Lk6AMCjjDAEAMjRChQooKtXr0qSSpUqpX379kmSrly5ooSEBHuWBgB4xDGBAgAgR2vcuLE2btwoX19ftW/fXq+88oo2b96sjRs36umnn7Z3eQCARxj3GQIA5GiXL1/W9evXVbJkSaWkpOitt97Stm3bVKlSJb366qsqUaKEvUsEADyiCEMAAIdz/fp1RUZG6u2339b58+ftXQ4A4BHFNUMAgBzpxo0bGjlypOrVq6eAgAB9/vnnkqQFCxaoQoUKmjlzpoYNG2bfIgEAjzRGhgAAOdLrr7+uuXPnKigoSNu2bdPFixfVu3dv7dixQ6NGjVL79u3l7Oxs7zIBAI8wJlAAAORIn376qT7++GO1bdtW+/btU40aNXTr1i3t2bNHFovF3uUBAHIARoYAADmSi4uLTpw4oVKlSkmS3N3dtXPnTvn6+tq5MgBATsE1QwCAHCk5OVkuLi7W57ly5VLevHntWBEAIKfhNDkAQI5kGIZ69eolV1dXSbdnkBswYIDy5Mlj02/VqlX2KA8AkAMQhgAAOVLPnj1tnnfr1s1OlQAAciquGQIAAABgSlwzBAAAAMCUCEMAAAAATIkwBAAAAMCUCEMAAAAATIkwBABweFu2bJHFYtGVK1cyvI6Pj48iIiIeWE0AAPsjDAEA7K5Xr16yWCwaMGBAmmWDBg2SxWJRr169Hn5hAACHRhgCADwSvL299cknnygxMdHadv36dS1dulRlypSxY2UAAEdFGAIAPBLq1Kkjb29vrVq1ytq2atUqlSlTRrVr17a23bhxQ0OGDFHRokXl5uamRo0a6eeff7bZ1rp16/TYY4/J3d1dTz31lE6ePJnm9bZu3aonnnhC7u7u8vb21pAhQxQfH//A9g8A8OghDAEAHhl9+vTRggULrM/nz5+v3r172/R57bXXtHLlSi1atEjR0dGqWLGiWrRoocuXL0uSzpw5o//7v/9TcHCwdu/erb59+yo0NNRmG8eOHVPLli3Vrl077d27V8uXL9fWrVs1ePDgB7+TAIBHBmEIAPDI6Natm7Zu3apTp07p1KlT+vHHH9WtWzfr8vj4eM2ePVtvv/22WrVqpWrVqunDDz+Uu7u75s2bJ0maPXu2KlSooOnTp6ty5crq2rVrmuuNwsLC1LVrVw0dOlSVKlVSQECA3n33XX388ce6fv36w9xlAIAd5bJ3AQAApCpSpIjatGmjhQsXyjAMtWnTRoULF7YuP3bsmG7evKnAwEBrW+7cueXn56cDBw5Ikg4cOCB/f3+b7TZs2NDm+Z49e7R3714tWbLE2mYYhlJSUnTixAlVrVr1QeweAOARQxgCADxS+vTpYz1dLTIy8oG8xrVr1/TSSy9pyJAhaZYxWQMAmAdhCADwSGnZsqWSkpJksVjUokULm2UVKlSQi4uLfvzxR5UtW1aSdPPmTf38888aOnSoJKlq1apas2aNzXo7duyweV6nTh3t379fFStWfHA7AgB45HHNEADgkeLs7KwDBw5o//79cnZ2tlmWJ08evfzyyxoxYoTWr1+v/fv3q1+/fkpISNCLL74oSRowYICOHDmiESNG6NChQ1q6dKkWLlxos53XX39d27Zt0+DBg7V7924dOXJEX3zxBRMoAIDJEIYAAI8cT09PeXp6prts6tSpateunbp37646dero6NGj2rBhgwoUKCDp9mluK1eu1Oeff66aNWtqzpw5mjJlis02atSooe+++06HDx/WE088odq1a2vcuHEqWbLkA983AMCjw2IYhmHvIgAAAADgYWNkCAAAAIApEYYAAAAAmBJhCAAAAIApEYYAAAAAmBJhCAAAAIApEYYAAAAAmBJhCAAAAIApEYYAAAAAmBJhCAAAAIApEYYAAAAAmBJhCAAAAIAp/T9N/d7kNrqGIAAAAABJRU5ErkJggg==\n"
-          },
-          "metadata": {}
-        }
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
       ],
-      "source": [
-        "if backend == \"client\":\n",
-        "    # Encode target labels to classes for baselines\n",
-        "    le = LabelEncoder()\n",
-        "    y_text = le.fit_transform(y_text)\n",
-        "\n",
-        "    # Define models\n",
-        "    models = [\n",
-        "        (\"TabPFN-Text\", TabPFNClassifier(random_state=42)),\n",
-        "        (\n",
-        "            \"TabPFN\",\n",
-        "            make_pipeline(\n",
-        "                column_transformer,  # string data needs to be encoded for model\n",
-        "                TabPFNClassifier(random_state=42),\n",
-        "            ),\n",
-        "        ),\n",
-        "        (\n",
-        "            \"RandomForest\",\n",
-        "            make_pipeline(\n",
-        "                column_transformer,  # string data needs to be encoded for model\n",
-        "                RandomForestClassifier(random_state=42),\n",
-        "            ),\n",
-        "        ),\n",
-        "        (\n",
-        "            \"XGBoost\",\n",
-        "            make_pipeline(\n",
-        "                column_transformer,  # string data needs to be encoded for model\n",
-        "                XGBClassifier(random_state=42),\n",
-        "            ),\n",
-        "        ),\n",
-        "        (\n",
-        "            \"CatBoost\",\n",
-        "            make_pipeline(\n",
-        "                column_transformer,  # string data needs to be encoded for model\n",
-        "                CatBoostClassifier(random_state=42, verbose=0),\n",
-        "            ),\n",
-        "        ),\n",
-        "    ]\n",
-        "\n",
-        "    # Calculate scores\n",
-        "    cv = StratifiedKFold(n_splits=3, random_state=42, shuffle=True)\n",
-        "    scoring = \"roc_auc_ovr\" if len(np.unique(y_text)) > 2 else \"roc_auc\"\n",
-        "    scores = {\n",
-        "        name: cross_val_score(\n",
-        "            model, X_text, y_text, cv=cv, scoring=scoring, n_jobs=1, verbose=1\n",
-        "        ).mean()\n",
-        "        for name, model in models\n",
-        "    }\n",
-        "\n",
-        "    # Plot results\n",
-        "    df = pd.DataFrame(list(scores.items()), columns=[\"Model\", \"ROC AUC\"])\n",
-        "    ax = df.plot(x=\"Model\", y=\"ROC AUC\", kind=\"bar\", figsize=(10, 6))\n",
-        "    ax.set_ylim(df[\"ROC AUC\"].min() * 0.995, min(1.0, df[\"ROC AUC\"].max() * 1.005))\n",
-        "    ax.set_title(\"Model Comparison - 5-fold Cross-validation\")"
-      ]
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "mTnMbG9vXHkL"
-      },
-      "source": [
-        "# Unsupervised Learning with TabPFN <a name=\"unsupervised-learning\"></a>\n",
-        "\n",
-        "TabPFN can also be used for unsupervised learning tasks like outlier detection and synthetic data generation. These features are available through the `tabpfn-extensions` library.\n"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Login successful!</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;32mLogin successful!\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "ghZddJXFa4zE"
-      },
-      "source": [
-        "### Data Generation"
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">✅ TabPFN (client) initialized.</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;32m✅ TabPFN \u001b[0m\u001b[1;32m(\u001b[0m\u001b[1;32mclient\u001b[0m\u001b[1;32m)\u001b[0m\u001b[1;32m initialized.\u001b[0m\n"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "console = Console()\n",
+    "\n",
+    "console.print(Panel.fit(\"[bold magenta]TabPFN Demo: Backend Selection[/bold magenta]\"))\n",
+    "console.print(\"\\nThis script can run TabPFN using one of two backends:\")\n",
+    "console.print(\"  [bold]local:[/bold] Uses a local GPU (NVIDIA). Requires CUDA.\")\n",
+    "console.print(\n",
+    "    \"  [bold]client:[/bold] Uses the TabPFN API. Requires an internet connection and a free account.\"\n",
+    ")\n",
+    "\n",
+    "backend = Prompt.ask(\n",
+    "    \"\\n[bold]Choose your backend[/bold] - If not field to enter is shown restart the cell.\",\n",
+    "    choices=[\"client\", \"local\"],\n",
+    "    default=\"client\",\n",
+    ")\n",
+    "\n",
+    "console.print(\n",
+    "    f\"\\n✅ You have selected the '[bold green]{backend}[/bold green]' backend.\"\n",
+    ")\n",
+    "\n",
+    "console.print(Rule(f\"[bold]Setting up [cyan]{backend}[/cyan] backend[/bold]\"))\n",
+    "\n",
+    "if backend == \"local\":\n",
+    "    !uv pip install huggingface_hub\n",
+    "\n",
+    "    console.print(\"Attempting local backend setup...\")\n",
+    "    import torch\n",
+    "\n",
+    "    if not torch.cuda.is_available():\n",
+    "        console.print(\n",
+    "            \"[bold red]Error:[/bold red] GPU device not found. For fast training, please enable GPU.\",\n",
+    "            style=\"red\",\n",
+    "        )\n",
+    "        console.print(\n",
+    "            \"In Colab: Go to [bold]Runtime -> Change runtime type -> Hardware accelerator -> GPU.[/bold]\",\n",
+    "            style=\"yellow\",\n",
+    "        )\n",
+    "        raise SystemError(\"GPU device not found.\")\n",
+    "    console.print(\n",
+    "        \"[bold green]✅ GPU is available.[/bold green] Importing local TabPFN library...\"\n",
+    "    )\n",
+    "\n",
+    "    from tabpfn import TabPFNClassifier, TabPFNRegressor\n",
+    "\n",
+    "    console.print(\"[bold green]✅ TabPFN (local) imported successfully.[/bold green]\")\n",
+    "elif backend == \"client\":\n",
+    "    console.print(\"Attempting client backend setup...\")\n",
+    "    console.print(\"Importing TabPFN client library...\")\n",
+    "    from tabpfn_client import TabPFNClassifier, TabPFNRegressor, init\n",
+    "\n",
+    "    init()\n",
+    "    console.print(\"[bold green]✅ TabPFN (client) initialized.[/bold green]\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "c8iQ9KEd1h9R"
+   },
+   "source": [
+    "# Classification with TabPFN <a name=\"classification\"></a>\n",
+    "\n",
+    "Now, let's dive into a practical example of using TabPFN for a classification task. We will use the well-known Parkinson's Disease dataset. The goal is to predict the presence of Parkinson's disease based on various voice measurements.\n",
+    "\n",
+    "We will compare TabPFN's performance against other popular machine learning models: RandomForest, XGBoost, and CatBoost. The performance metric we will use is the [ROC AUC](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html) score.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "PNtRCHyLG1D5"
+   },
+   "source": [
+    "### **Loading Parkinson’s Disease Dataset**\n",
+    "\n",
+    "**Source:**  \n",
+    "The dataset was created by _Max Little_ of the **University of Oxford**, in collaboration with the **National Centre for Voice and Speech**, Denver, Colorado. The dataset consists of biomedical voice measurements collected from individuals, and the original study published the feature extraction methods for general voice disorders.\n",
+    "\n",
+    "### **Dataset Overview**\n",
+    "\n",
+    "-   **Number of subjects:** 31\n",
+    "    \n",
+    "-   **Number of Parkinson’s disease (PD) patients:** 23\n",
+    "    \n",
+    "-   **Total recordings:** 195 voice samples\n",
+    "    \n",
+    "-   **Goal:** To discriminate healthy individuals (status = 0) from those with Parkinson’s disease (status = 1).\n",
+    "    \n",
+    "-   **Identifier column:** `name` (subject name and recording number)\n",
+    "    \n",
+    "\n",
+    "<details>\n",
+    "If you use this dataset, please cite:\n",
+    "\n",
+    "> Max A. Little, Patrick E. McSharry, Eric J. Hunter, Lorraine O. Ramig (2008).  \n",
+    "> _Suitability of dysphonia measurements for telemonitoring of Parkinson's disease._  \n",
+    "> IEEE Transactions on Biomedical Engineering.\n",
+    "\n",
+    "* * *\n",
+    "\n",
+    "\n",
+    "\n",
+    "* * *\n",
+    "\n",
+    "### **Attribute Information**\n",
+    "\n",
+    "Each row corresponds to a voice recording, and each column represents a distinct biomedical voice measure.\n",
+    "\n",
+    "**Feature Name**\n",
+    "\n",
+    "**Description**\n",
+    "\n",
+    "`name`\n",
+    "\n",
+    "ASCII subject name and recording number\n",
+    "\n",
+    "`MDVP:Fo(Hz)`\n",
+    "\n",
+    "Average vocal fundamental frequency\n",
+    "\n",
+    "`MDVP:Fhi(Hz)`\n",
+    "\n",
+    "Maximum vocal fundamental frequency\n",
+    "\n",
+    "`MDVP:Flo(Hz)`\n",
+    "\n",
+    "Minimum vocal fundamental frequency\n",
+    "\n",
+    "`MDVP:Jitter(%)`, `MDVP:Jitter(Abs)`, `MDVP:RAP`, `MDVP:PPQ`, `Jitter:DDP`\n",
+    "\n",
+    "Measures of variation in fundamental frequency\n",
+    "\n",
+    "`MDVP:Shimmer`, `MDVP:Shimmer(dB)`, `Shimmer:APQ3`, `Shimmer:APQ5`, `MDVP:APQ`, `Shimmer:DDA`\n",
+    "\n",
+    "Measures of variation in amplitude\n",
+    "\n",
+    "`NHR`, `HNR`\n",
+    "\n",
+    "Ratios of noise to tonal components in the voice\n",
+    "\n",
+    "`status`\n",
+    "\n",
+    "Health status of the subject (`0` = healthy, `1` = Parkinson’s disease)\n",
+    "\n",
+    "`RPDE`, `D2`\n",
+    "\n",
+    "Nonlinear dynamical complexity measures\n",
+    "\n",
+    "`DFA`\n",
+    "\n",
+    "Signal fractal scaling exponent\n",
+    "\n",
+    "`spread1`, `spread2`, `PPE`\n",
+    "\n",
+    "Nonlinear measures of fundamental frequency variation\n",
+    "</details>\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 423
     },
+    "id": "tTQe5IprKLV5",
+    "outputId": "2289a6e5-6cac-4c72-8203-f638f2acb520"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "npJnFdtTa_nS",
-        "outputId": "c2fbe9fd-e7c6-4e14-c2b2-198e2fea703e"
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "type": "dataframe",
+       "variable_name": "X"
       },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "100%|██████████| 3/3 [00:05<00:00,  1.85s/it]\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 935.75x750 with 12 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
+      "text/html": [
+       "\n",
+       "  <div id=\"df-d52120d9-7d31-4822-867b-72c4af95f0a7\" class=\"colab-df-container\">\n",
+       "    <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>MDVP:Fo(Hz)</th>\n",
+       "      <th>MDVP:Fhi(Hz)</th>\n",
+       "      <th>MDVP:Flo(Hz)</th>\n",
+       "      <th>MDVP:Jitter(%)</th>\n",
+       "      <th>MDVP:Jitter(Abs)</th>\n",
+       "      <th>MDVP:RAP</th>\n",
+       "      <th>MDVP:PPQ</th>\n",
+       "      <th>Jitter:DDP</th>\n",
+       "      <th>MDVP:Shimmer</th>\n",
+       "      <th>MDVP:Shimmer(dB)</th>\n",
+       "      <th>...</th>\n",
+       "      <th>MDVP:APQ</th>\n",
+       "      <th>Shimmer:DDA</th>\n",
+       "      <th>NHR</th>\n",
+       "      <th>HNR</th>\n",
+       "      <th>RPDE</th>\n",
+       "      <th>DFA</th>\n",
+       "      <th>spread1</th>\n",
+       "      <th>spread2</th>\n",
+       "      <th>D2</th>\n",
+       "      <th>PPE</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>119.992</td>\n",
+       "      <td>157.302</td>\n",
+       "      <td>74.997</td>\n",
+       "      <td>0.00784</td>\n",
+       "      <td>0.00007</td>\n",
+       "      <td>0.00370</td>\n",
+       "      <td>0.00554</td>\n",
+       "      <td>0.01109</td>\n",
+       "      <td>0.04374</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.02971</td>\n",
+       "      <td>0.06545</td>\n",
+       "      <td>0.02211</td>\n",
+       "      <td>21.033</td>\n",
+       "      <td>0.414783</td>\n",
+       "      <td>0.815285</td>\n",
+       "      <td>-4.813031</td>\n",
+       "      <td>0.266482</td>\n",
+       "      <td>2.301442</td>\n",
+       "      <td>0.284654</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>122.400</td>\n",
+       "      <td>148.650</td>\n",
+       "      <td>113.819</td>\n",
+       "      <td>0.00968</td>\n",
+       "      <td>0.00008</td>\n",
+       "      <td>0.00465</td>\n",
+       "      <td>0.00696</td>\n",
+       "      <td>0.01394</td>\n",
+       "      <td>0.06134</td>\n",
+       "      <td>0.626</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.04368</td>\n",
+       "      <td>0.09403</td>\n",
+       "      <td>0.01929</td>\n",
+       "      <td>19.085</td>\n",
+       "      <td>0.458359</td>\n",
+       "      <td>0.819521</td>\n",
+       "      <td>-4.075192</td>\n",
+       "      <td>0.335590</td>\n",
+       "      <td>2.486855</td>\n",
+       "      <td>0.368674</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>116.682</td>\n",
+       "      <td>131.111</td>\n",
+       "      <td>111.555</td>\n",
+       "      <td>0.01050</td>\n",
+       "      <td>0.00009</td>\n",
+       "      <td>0.00544</td>\n",
+       "      <td>0.00781</td>\n",
+       "      <td>0.01633</td>\n",
+       "      <td>0.05233</td>\n",
+       "      <td>0.482</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.03590</td>\n",
+       "      <td>0.08270</td>\n",
+       "      <td>0.01309</td>\n",
+       "      <td>20.651</td>\n",
+       "      <td>0.429895</td>\n",
+       "      <td>0.825288</td>\n",
+       "      <td>-4.443179</td>\n",
+       "      <td>0.311173</td>\n",
+       "      <td>2.342259</td>\n",
+       "      <td>0.332634</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>116.676</td>\n",
+       "      <td>137.871</td>\n",
+       "      <td>111.366</td>\n",
+       "      <td>0.00997</td>\n",
+       "      <td>0.00009</td>\n",
+       "      <td>0.00502</td>\n",
+       "      <td>0.00698</td>\n",
+       "      <td>0.01505</td>\n",
+       "      <td>0.05492</td>\n",
+       "      <td>0.517</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.03772</td>\n",
+       "      <td>0.08771</td>\n",
+       "      <td>0.01353</td>\n",
+       "      <td>20.644</td>\n",
+       "      <td>0.434969</td>\n",
+       "      <td>0.819235</td>\n",
+       "      <td>-4.117501</td>\n",
+       "      <td>0.334147</td>\n",
+       "      <td>2.405554</td>\n",
+       "      <td>0.368975</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>116.014</td>\n",
+       "      <td>141.781</td>\n",
+       "      <td>110.655</td>\n",
+       "      <td>0.01284</td>\n",
+       "      <td>0.00011</td>\n",
+       "      <td>0.00655</td>\n",
+       "      <td>0.00908</td>\n",
+       "      <td>0.01966</td>\n",
+       "      <td>0.06425</td>\n",
+       "      <td>0.584</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.04465</td>\n",
+       "      <td>0.10470</td>\n",
+       "      <td>0.01767</td>\n",
+       "      <td>19.649</td>\n",
+       "      <td>0.417356</td>\n",
+       "      <td>0.823484</td>\n",
+       "      <td>-3.747787</td>\n",
+       "      <td>0.234513</td>\n",
+       "      <td>2.332180</td>\n",
+       "      <td>0.410335</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>190</th>\n",
+       "      <td>174.188</td>\n",
+       "      <td>230.978</td>\n",
+       "      <td>94.261</td>\n",
+       "      <td>0.00459</td>\n",
+       "      <td>0.00003</td>\n",
+       "      <td>0.00263</td>\n",
+       "      <td>0.00259</td>\n",
+       "      <td>0.00790</td>\n",
+       "      <td>0.04087</td>\n",
+       "      <td>0.405</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.02745</td>\n",
+       "      <td>0.07008</td>\n",
+       "      <td>0.02764</td>\n",
+       "      <td>19.517</td>\n",
+       "      <td>0.448439</td>\n",
+       "      <td>0.657899</td>\n",
+       "      <td>-6.538586</td>\n",
+       "      <td>0.121952</td>\n",
+       "      <td>2.657476</td>\n",
+       "      <td>0.133050</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>191</th>\n",
+       "      <td>209.516</td>\n",
+       "      <td>253.017</td>\n",
+       "      <td>89.488</td>\n",
+       "      <td>0.00564</td>\n",
+       "      <td>0.00003</td>\n",
+       "      <td>0.00331</td>\n",
+       "      <td>0.00292</td>\n",
+       "      <td>0.00994</td>\n",
+       "      <td>0.02751</td>\n",
+       "      <td>0.263</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.01879</td>\n",
+       "      <td>0.04812</td>\n",
+       "      <td>0.01810</td>\n",
+       "      <td>19.147</td>\n",
+       "      <td>0.431674</td>\n",
+       "      <td>0.683244</td>\n",
+       "      <td>-6.195325</td>\n",
+       "      <td>0.129303</td>\n",
+       "      <td>2.784312</td>\n",
+       "      <td>0.168895</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>192</th>\n",
+       "      <td>174.688</td>\n",
+       "      <td>240.005</td>\n",
+       "      <td>74.287</td>\n",
+       "      <td>0.01360</td>\n",
+       "      <td>0.00008</td>\n",
+       "      <td>0.00624</td>\n",
+       "      <td>0.00564</td>\n",
+       "      <td>0.01873</td>\n",
+       "      <td>0.02308</td>\n",
+       "      <td>0.256</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.01667</td>\n",
+       "      <td>0.03804</td>\n",
+       "      <td>0.10715</td>\n",
+       "      <td>17.883</td>\n",
+       "      <td>0.407567</td>\n",
+       "      <td>0.655683</td>\n",
+       "      <td>-6.787197</td>\n",
+       "      <td>0.158453</td>\n",
+       "      <td>2.679772</td>\n",
+       "      <td>0.131728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>193</th>\n",
+       "      <td>198.764</td>\n",
+       "      <td>396.961</td>\n",
+       "      <td>74.904</td>\n",
+       "      <td>0.00740</td>\n",
+       "      <td>0.00004</td>\n",
+       "      <td>0.00370</td>\n",
+       "      <td>0.00390</td>\n",
+       "      <td>0.01109</td>\n",
+       "      <td>0.02296</td>\n",
+       "      <td>0.241</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.01588</td>\n",
+       "      <td>0.03794</td>\n",
+       "      <td>0.07223</td>\n",
+       "      <td>19.020</td>\n",
+       "      <td>0.451221</td>\n",
+       "      <td>0.643956</td>\n",
+       "      <td>-6.744577</td>\n",
+       "      <td>0.207454</td>\n",
+       "      <td>2.138608</td>\n",
+       "      <td>0.123306</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>194</th>\n",
+       "      <td>214.289</td>\n",
+       "      <td>260.277</td>\n",
+       "      <td>77.973</td>\n",
+       "      <td>0.00567</td>\n",
+       "      <td>0.00003</td>\n",
+       "      <td>0.00295</td>\n",
+       "      <td>0.00317</td>\n",
+       "      <td>0.00885</td>\n",
+       "      <td>0.01884</td>\n",
+       "      <td>0.190</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.01373</td>\n",
+       "      <td>0.03078</td>\n",
+       "      <td>0.04398</td>\n",
+       "      <td>21.209</td>\n",
+       "      <td>0.462803</td>\n",
+       "      <td>0.664357</td>\n",
+       "      <td>-5.724056</td>\n",
+       "      <td>0.190667</td>\n",
+       "      <td>2.555477</td>\n",
+       "      <td>0.148569</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>195 rows × 22 columns</p>\n",
+       "</div>\n",
+       "    <div class=\"colab-df-buttons\">\n",
+       "\n",
+       "  <div class=\"colab-df-container\">\n",
+       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d52120d9-7d31-4822-867b-72c4af95f0a7')\"\n",
+       "            title=\"Convert this dataframe to an interactive table.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+       "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+       "  </svg>\n",
+       "    </button>\n",
+       "\n",
+       "  <style>\n",
+       "    .colab-df-container {\n",
+       "      display:flex;\n",
+       "      gap: 12px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert {\n",
+       "      background-color: #E8F0FE;\n",
+       "      border: none;\n",
+       "      border-radius: 50%;\n",
+       "      cursor: pointer;\n",
+       "      display: none;\n",
+       "      fill: #1967D2;\n",
+       "      height: 32px;\n",
+       "      padding: 0 0 0 0;\n",
+       "      width: 32px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert:hover {\n",
+       "      background-color: #E2EBFA;\n",
+       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "      fill: #174EA6;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-buttons div {\n",
+       "      margin-bottom: 4px;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert {\n",
+       "      background-color: #3B4455;\n",
+       "      fill: #D2E3FC;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert:hover {\n",
+       "      background-color: #434B5C;\n",
+       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "      fill: #FFFFFF;\n",
+       "    }\n",
+       "  </style>\n",
+       "\n",
+       "    <script>\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#df-d52120d9-7d31-4822-867b-72c4af95f0a7 button.colab-df-convert');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      async function convertToInteractive(key) {\n",
+       "        const element = document.querySelector('#df-d52120d9-7d31-4822-867b-72c4af95f0a7');\n",
+       "        const dataTable =\n",
+       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+       "                                                    [key], {});\n",
+       "        if (!dataTable) return;\n",
+       "\n",
+       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+       "          + ' to learn more about interactive tables.';\n",
+       "        element.innerHTML = '';\n",
+       "        dataTable['output_type'] = 'display_data';\n",
+       "        await google.colab.output.renderOutput(dataTable, element);\n",
+       "        const docLink = document.createElement('div');\n",
+       "        docLink.innerHTML = docLinkHtml;\n",
+       "        element.appendChild(docLink);\n",
+       "      }\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "\n",
+       "    <div id=\"df-8d8cc699-bdc3-415f-a51f-a5dd44058db1\">\n",
+       "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8d8cc699-bdc3-415f-a51f-a5dd44058db1')\"\n",
+       "                title=\"Suggest charts\"\n",
+       "                style=\"display:none;\">\n",
+       "\n",
+       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "     width=\"24px\">\n",
+       "    <g>\n",
+       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+       "    </g>\n",
+       "</svg>\n",
+       "      </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
+       "      --hover-fill-color: #174EA6;\n",
+       "      --disabled-fill-color: #AAA;\n",
+       "      --disabled-bg-color: #DDD;\n",
+       "  }\n",
+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
+       "      --hover-bg-color: #434B5C;\n",
+       "      --hover-fill-color: #FFFFFF;\n",
+       "      --disabled-bg-color: #3B4455;\n",
+       "      --disabled-fill-color: #666;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart {\n",
+       "    background-color: var(--bg-color);\n",
+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
+       "    display: none;\n",
+       "    fill: var(--fill-color);\n",
+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    30% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "      <script>\n",
+       "        async function quickchart(key) {\n",
+       "          const quickchartButtonEl =\n",
+       "            document.querySelector('#' + key + ' button');\n",
+       "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "          try {\n",
+       "            const charts = await google.colab.kernel.invokeFunction(\n",
+       "                'suggestCharts', [key], {});\n",
+       "          } catch (error) {\n",
+       "            console.error('Error during call to suggestCharts:', error);\n",
+       "          }\n",
+       "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "        }\n",
+       "        (() => {\n",
+       "          let quickchartButtonEl =\n",
+       "            document.querySelector('#df-8d8cc699-bdc3-415f-a51f-a5dd44058db1 button');\n",
+       "          quickchartButtonEl.style.display =\n",
+       "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "        })();\n",
+       "      </script>\n",
+       "    </div>\n",
+       "\n",
+       "  <div id=\"id_eabe92fa-3f6c-4501-a1ec-d0b82f79e203\">\n",
+       "    <style>\n",
+       "      .colab-df-generate {\n",
+       "        background-color: #E8F0FE;\n",
+       "        border: none;\n",
+       "        border-radius: 50%;\n",
+       "        cursor: pointer;\n",
+       "        display: none;\n",
+       "        fill: #1967D2;\n",
+       "        height: 32px;\n",
+       "        padding: 0 0 0 0;\n",
+       "        width: 32px;\n",
+       "      }\n",
+       "\n",
+       "      .colab-df-generate:hover {\n",
+       "        background-color: #E2EBFA;\n",
+       "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "        fill: #174EA6;\n",
+       "      }\n",
+       "\n",
+       "      [theme=dark] .colab-df-generate {\n",
+       "        background-color: #3B4455;\n",
+       "        fill: #D2E3FC;\n",
+       "      }\n",
+       "\n",
+       "      [theme=dark] .colab-df-generate:hover {\n",
+       "        background-color: #434B5C;\n",
+       "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "        fill: #FFFFFF;\n",
+       "      }\n",
+       "    </style>\n",
+       "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('X')\"\n",
+       "            title=\"Generate code using this dataframe.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "       width=\"24px\">\n",
+       "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+       "  </svg>\n",
+       "    </button>\n",
+       "    <script>\n",
+       "      (() => {\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#id_eabe92fa-3f6c-4501-a1ec-d0b82f79e203 button.colab-df-generate');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      buttonEl.onclick = () => {\n",
+       "        google.colab.notebook.generateWithVariable('X');\n",
+       "      }\n",
+       "      })();\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
       ],
-      "source": [
-        "from tabpfn_extensions import unsupervised\n",
-        "from tabpfn_extensions.unsupervised import experiments\n",
-        "\n",
-        "# Load and prepare breast cancer dataset\n",
-        "df = load_breast_cancer(return_X_y=False)\n",
-        "X, y = df[\"data\"], df[\"target\"]\n",
-        "feature_names = df[\"feature_names\"]\n",
-        "\n",
-        "# Initialize TabPFN models\n",
-        "model_unsupervised = unsupervised.TabPFNUnsupervisedModel(\n",
-        "    tabpfn_clf=TabPFNClassifier(), tabpfn_reg=TabPFNRegressor()\n",
-        ")\n",
-        "\n",
-        "# Select features for synthetic data generation\n",
-        "# Example features: [mean texture, mean area, mean concavity]\n",
-        "feature_indices = [4, 6, 12]\n",
-        "\n",
-        "# Run synthetic data generation experiment\n",
-        "experiment = unsupervised.experiments.GenerateSyntheticDataExperiment(\n",
-        "    task_type=\"unsupervised\"\n",
-        ")\n",
-        "\n",
-        "results = experiment.run(\n",
-        "    tabpfn=model_unsupervised,\n",
-        "    X=torch.tensor(X),\n",
-        "    y=torch.tensor(y),\n",
-        "    attribute_names=feature_names,\n",
-        "    temp=1.0,  # Temperature parameter for sampling\n",
-        "    n_samples=X.shape[0] * 2,  # Generate twice as many samples as original data\n",
-        "    indices=feature_indices,\n",
-        ")"
+      "text/plain": [
+       "     MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
+       "0        119.992       157.302        74.997         0.00784   \n",
+       "1        122.400       148.650       113.819         0.00968   \n",
+       "2        116.682       131.111       111.555         0.01050   \n",
+       "3        116.676       137.871       111.366         0.00997   \n",
+       "4        116.014       141.781       110.655         0.01284   \n",
+       "..           ...           ...           ...             ...   \n",
+       "190      174.188       230.978        94.261         0.00459   \n",
+       "191      209.516       253.017        89.488         0.00564   \n",
+       "192      174.688       240.005        74.287         0.01360   \n",
+       "193      198.764       396.961        74.904         0.00740   \n",
+       "194      214.289       260.277        77.973         0.00567   \n",
+       "\n",
+       "     MDVP:Jitter(Abs)  MDVP:RAP  MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  \\\n",
+       "0             0.00007   0.00370   0.00554     0.01109       0.04374   \n",
+       "1             0.00008   0.00465   0.00696     0.01394       0.06134   \n",
+       "2             0.00009   0.00544   0.00781     0.01633       0.05233   \n",
+       "3             0.00009   0.00502   0.00698     0.01505       0.05492   \n",
+       "4             0.00011   0.00655   0.00908     0.01966       0.06425   \n",
+       "..                ...       ...       ...         ...           ...   \n",
+       "190           0.00003   0.00263   0.00259     0.00790       0.04087   \n",
+       "191           0.00003   0.00331   0.00292     0.00994       0.02751   \n",
+       "192           0.00008   0.00624   0.00564     0.01873       0.02308   \n",
+       "193           0.00004   0.00370   0.00390     0.01109       0.02296   \n",
+       "194           0.00003   0.00295   0.00317     0.00885       0.01884   \n",
+       "\n",
+       "     MDVP:Shimmer(dB)  ...  MDVP:APQ  Shimmer:DDA      NHR     HNR      RPDE  \\\n",
+       "0               0.426  ...   0.02971      0.06545  0.02211  21.033  0.414783   \n",
+       "1               0.626  ...   0.04368      0.09403  0.01929  19.085  0.458359   \n",
+       "2               0.482  ...   0.03590      0.08270  0.01309  20.651  0.429895   \n",
+       "3               0.517  ...   0.03772      0.08771  0.01353  20.644  0.434969   \n",
+       "4               0.584  ...   0.04465      0.10470  0.01767  19.649  0.417356   \n",
+       "..                ...  ...       ...          ...      ...     ...       ...   \n",
+       "190             0.405  ...   0.02745      0.07008  0.02764  19.517  0.448439   \n",
+       "191             0.263  ...   0.01879      0.04812  0.01810  19.147  0.431674   \n",
+       "192             0.256  ...   0.01667      0.03804  0.10715  17.883  0.407567   \n",
+       "193             0.241  ...   0.01588      0.03794  0.07223  19.020  0.451221   \n",
+       "194             0.190  ...   0.01373      0.03078  0.04398  21.209  0.462803   \n",
+       "\n",
+       "          DFA   spread1   spread2        D2       PPE  \n",
+       "0    0.815285 -4.813031  0.266482  2.301442  0.284654  \n",
+       "1    0.819521 -4.075192  0.335590  2.486855  0.368674  \n",
+       "2    0.825288 -4.443179  0.311173  2.342259  0.332634  \n",
+       "3    0.819235 -4.117501  0.334147  2.405554  0.368975  \n",
+       "4    0.823484 -3.747787  0.234513  2.332180  0.410335  \n",
+       "..        ...       ...       ...       ...       ...  \n",
+       "190  0.657899 -6.538586  0.121952  2.657476  0.133050  \n",
+       "191  0.683244 -6.195325  0.129303  2.784312  0.168895  \n",
+       "192  0.655683 -6.787197  0.158453  2.679772  0.131728  \n",
+       "193  0.643956 -6.744577  0.207454  2.138608  0.123306  \n",
+       "194  0.664357 -5.724056  0.190667  2.555477  0.148569  \n",
+       "\n",
+       "[195 rows x 22 columns]"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Load Parkinsons dataset described above\n",
+    "\n",
+    "import pandas as pd, io, zipfile, requests\n",
+    "\n",
+    "url_zip = \"https://archive.ics.uci.edu/static/public/174/parkinsons.zip\"\n",
+    "with requests.get(url_zip) as r:\n",
+    "    r.raise_for_status()\n",
+    "    zf = zipfile.ZipFile(io.BytesIO(r.content))\n",
+    "    df = pd.read_csv(zf.open(\"parkinsons.data\"))\n",
+    "X, y = df.drop([\"status\", \"name\"], axis=1), df[\"status\"]\n",
+    "\n",
+    "display(X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "id": "KAXhoOc2U2vJ"
+   },
+   "outputs": [],
+   "source": [
+    "# Alternative datasets (commented for reference):\n",
+    "\n",
+    "# Cholesterol dataset: Predict cholesterol levels\n",
+    "# Features: Patient characteristics, medical measurements\n",
+    "# Samples: 303 patients\n",
+    "# Target: Cholesterol levels in mg/dl\n",
+    "# df = fetch_openml('cholesterol', version=2, as_frame=True)\n",
+    "\n",
+    "# Heart Disease dataset (Statlog): Predict presence of heart disease\n",
+    "# Features: Clinical and test measurements\n",
+    "# Samples: 270 patients\n",
+    "# Target: Binary heart disease diagnosis\n",
+    "# df = fetch_openml(\"heart-statlog\", version=1)\n",
+    "\n",
+    "# Diabetes dataset: Predict diabetes presence\n",
+    "# Features: Medical measurements, patient history\n",
+    "# Samples: 768 patients\n",
+    "# Target: Binary diabetes diagnosis\n",
+    "# df = fetch_openml(\"diabetes\", version=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "zTHzDedu3DKR",
+    "outputId": "b8f79392-66bf-4884-bcbd-1a7cb51ab676"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_aoNg2_K4k6E"
-      },
-      "source": [
-        "### Outlier detection"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing: 100%|██████████| [00:02<00:00]\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "ezircAHiZSKG",
-        "outputId": "4c93610c-33a5-4dd1-ba43-6ba118c06942"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 600x600 with 3 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
-      ],
-      "source": [
-        "import torch\n",
-        "from sklearn.datasets import load_breast_cancer\n",
-        "from tabpfn_extensions import unsupervised\n",
-        "from tabpfn_extensions.unsupervised import experiments\n",
-        "\n",
-        "# Load data\n",
-        "df = load_breast_cancer(return_X_y=False)\n",
-        "X, y = df[\"data\"], df[\"target\"]\n",
-        "attribute_names = df[\"feature_names\"]\n",
-        "\n",
-        "# Initialize models\n",
-        "clf = TabPFNClassifier(n_estimators=4)\n",
-        "reg = TabPFNRegressor(n_estimators=4)\n",
-        "model_unsupervised = unsupervised.TabPFNUnsupervisedModel(\n",
-        "    tabpfn_clf=clf, tabpfn_reg=reg\n",
-        ")\n",
-        "\n",
-        "# Run outlier detection\n",
-        "exp_outlier = unsupervised.experiments.OutlierDetectionUnsupervisedExperiment(\n",
-        "    task_type=\"unsupervised\"\n",
-        ")\n",
-        "results = exp_outlier.run(\n",
-        "    tabpfn=model_unsupervised,\n",
-        "    X=torch.tensor(X, dtype=torch.float32),\n",
-        "    y=torch.tensor(y),\n",
-        "    attribute_names=attribute_names,\n",
-        "    indices=[4, 12],  # Analyze features 4 and 12\n",
-        ")"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "TabPFN ROC AUC Score: 0.9732\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Split the data into training and testing sets\n",
+    "X_train, X_test, y_train, y_test = train_test_split(\n",
+    "    X, y, test_size=0.20, random_state=42\n",
+    ")\n",
+    "\n",
+    "# Train and evaluate the TabPFN classifier\n",
+    "tabpfn_classifier = TabPFNClassifier(random_state=42)\n",
+    "tabpfn_classifier.fit(X_train, y_train)\n",
+    "y_pred_proba = tabpfn_classifier.predict_proba(X_test)\n",
+    "\n",
+    "# Calculate the ROC AUC score\n",
+    "roc_auc = roc_auc_score(y_test, y_pred_proba[:, 1])\n",
+    "print(f\"TabPFN ROC AUC Score: {roc_auc:.4f}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ZVs_HfxbVCs3"
+   },
+   "source": [
+    "### Comparing TabPFN with Other Classifiers\n",
+    "\n",
+    "To get a better sense of TabPFN's performance, let's compare it with other popular classification models using cross-validation. This will give us a more robust estimate of each model's performance.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 789
     },
+    "id": "ITuXXhqE7Fps",
+    "outputId": "f7cc728b-2b9e-4d1f-ce3a-db8bd165c371"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "Qk6OxtxmJsr9"
-      },
-      "source": [
-        "### Missing value imputation"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing: 100%|██████████| [00:01<00:00]\n",
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "Processing: 100%|██████████| [00:02<00:00]\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:   12.8s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.7s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.2s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    8.9s finished\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "9hgAlgghJuF3",
-        "outputId": "bc78fafc-f40e-4dfb-a2e8-9e3f7487d691"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Introduced 168 missing values into the test set.\n",
-            "       0      1       2\n",
-            "0    NaN  18.60   81.09\n",
-            "1  18.94    NaN  123.60\n",
-            "2  15.46  19.48  101.70\n",
-            "3  12.40    NaN   81.47\n",
-            "4    NaN  14.44     NaN\n",
-            "Fitting the unsupervised model on the training data...\n",
-            "Imputing missing values...\n",
-            "\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "100%|██████████| 3/3 [00:11<00:00,  3.88s/it]"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "\n",
-            "------------------------\n",
-            "\n",
-            "Number of missing values after imputation: 0\n",
-            "           0          1           2\n",
-            "0  12.515228  18.600000   81.089996\n",
-            "1  18.940001  21.109259  123.599998\n",
-            "2  15.460000  19.480000  101.699997\n",
-            "3  12.400000  17.477161   81.470001\n",
-            "4  11.358663  14.440000   74.500938\n",
-            "Mean Squared Error of imputed values vs. original values: 0.4940\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "\n"
-          ]
-        }
-      ],
-      "source": [
-        "# --- 1. Load and Prepare Data ---\n",
-        "# Load the breast cancer dataset\n",
-        "df = load_breast_cancer(return_X_y=False)\n",
-        "X, y = df[\"data\"], df[\"target\"]\n",
-        "\n",
-        "# Split the data into training and testing sets\n",
-        "X_train, X_test = train_test_split(\n",
-        "    X,\n",
-        "    test_size=0.33,\n",
-        "    random_state=42,\n",
-        ")\n",
-        "\n",
-        "# --- 2. Introduce Missing Values ---\n",
-        "# Create a copy of the test set to introduce missing values (NaNs)\n",
-        "X_test_missing = X_test.copy()\n",
-        "n_samples, n_features = X_test_missing.shape\n",
-        "\n",
-        "# Introduce missing values in the first three columns for demonstration\n",
-        "missing_fraction = 0.3\n",
-        "n_missing = int(n_samples * missing_fraction)\n",
-        "\n",
-        "for col_idx in range(3):\n",
-        "    # Choose random rows to set to NaN\n",
-        "    missing_indices = np.random.choice(n_samples, n_missing, replace=False)\n",
-        "    X_test_missing[missing_indices, col_idx] = np.nan\n",
-        "\n",
-        "print(f\"Introduced {np.isnan(X_test_missing).sum()} missing values into the test set.\")\n",
-        "print(pd.DataFrame(X_test_missing[:, 0:3]).head())\n",
-        "\n",
-        "# --- 3. Initialize the Unsupervised Model ---\n",
-        "# Initialize TabPFN models for regression and classification tasks.\n",
-        "# The unsupervised model uses these to model the data distribution.\n",
-        "clf = TabPFNClassifier(n_estimators=3)\n",
-        "reg = TabPFNRegressor(n_estimators=3)\n",
-        "\n",
-        "# Initialize the main unsupervised model\n",
-        "model_unsupervised = unsupervised.TabPFNUnsupervisedModel(\n",
-        "    tabpfn_clf=clf,\n",
-        "    tabpfn_reg=reg,\n",
-        ")\n",
-        "\n",
-        "# --- 4. Fit and Impute ---\n",
-        "# Fit the model on the complete training data (without missing values)\n",
-        "print(\"Fitting the unsupervised model on the training data...\")\n",
-        "model_unsupervised.fit(X_train)\n",
-        "\n",
-        "# Perform imputation on the test set\n",
-        "print(\"Imputing missing values...\\n\")\n",
-        "X_imputed_tensor = model_unsupervised.impute(\n",
-        "    X_test_missing,\n",
-        "    n_permutations=5,  # Fewer permutations for a quicker example\n",
-        ")\n",
-        "\n",
-        "print(\"\\n------------------------\")\n",
-        "\n",
-        "# --- 5. Verify Results ---\n",
-        "# Check that the imputed data no longer contains any NaN values\n",
-        "n_missing_after = torch.isnan(X_imputed_tensor).sum().item()\n",
-        "\n",
-        "print(f\"\\nNumber of missing values after imputation: {n_missing_after}\")\n",
-        "print(pd.DataFrame(X_imputed_tensor[:, 0:3]).head())\n",
-        "\n",
-        "# Optional: Calculate the Mean Squared Error for the imputed values,\n",
-        "# since we know the original ground truth values.\n",
-        "original_nan_mask = np.isnan(X_test_missing)\n",
-        "imputed_values = X_imputed_tensor.numpy()[original_nan_mask]\n",
-        "original_values = X_test[original_nan_mask]\n",
-        "\n",
-        "mse = np.mean((imputed_values - original_values) ** 2)\n",
-        "print(f\"Mean Squared Error of imputed values vs. original values: {mse:.4f}\")"
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Model Comparison - 3-fold Cross-validation')"
       ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "MqZlQ09WfCe9"
-      },
-      "source": [
-        "# Model Interpretability <a name=\"interpretability\"></a>\n",
-        "\n",
-        "Understanding *why* a model makes certain predictions is crucial for building trust and for debugging. The `tabpfn-extensions` library provides tools for model interpretability. We'll look at SHAP (SHapley Additive exPlanations) values, which show the impact of each feature on a specific prediction."
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Compare different machine learning models by training each one multiple times\n",
+    "# on different parts of the data and averaging their performance scores for a\n",
+    "# more reliable performance estimate\n",
+    "\n",
+    "# Encode target labels to classes for baselines\n",
+    "le = LabelEncoder()\n",
+    "y = le.fit_transform(y)\n",
+    "\n",
+    "# Define models\n",
+    "models = [\n",
+    "    (\"TabPFN\", TabPFNClassifier(random_state=42)),\n",
+    "    (\n",
+    "        \"RandomForest\",\n",
+    "        make_pipeline(\n",
+    "            column_transformer,  # string data needs to be encoded for model\n",
+    "            RandomForestClassifier(random_state=42),\n",
+    "        ),\n",
+    "    ),\n",
+    "    (\n",
+    "        \"XGBoost\",\n",
+    "        make_pipeline(\n",
+    "            column_transformer,  # string data needs to be encoded for model\n",
+    "            XGBClassifier(random_state=42),\n",
+    "        ),\n",
+    "    ),\n",
+    "    (\n",
+    "        \"CatBoost\",\n",
+    "        make_pipeline(\n",
+    "            column_transformer,  # string data needs to be encoded for model\n",
+    "            CatBoostClassifier(random_state=42, verbose=0),\n",
+    "        ),\n",
+    "    ),\n",
+    "]\n",
+    "\n",
+    "# Calculate scores\n",
+    "n_splits = 3\n",
+    "cv = StratifiedKFold(n_splits=n_splits, random_state=42, shuffle=True)\n",
+    "scoring = \"roc_auc_ovr\" if len(np.unique(y)) > 2 else \"roc_auc\"\n",
+    "scores = {\n",
+    "    name: cross_val_score(model, X, y, cv=cv, scoring=scoring, n_jobs=1, verbose=1)\n",
+    "    for name, model in models\n",
+    "}\n",
+    "\n",
+    "# Plot results\n",
+    "df = pd.DataFrame(\n",
+    "    [(k, v.mean()) for (k, v) in scores.items()], columns=[\"Model\", \"ROC AUC\"]\n",
+    ")\n",
+    "ax = df.plot(x=\"Model\", y=\"ROC AUC\", kind=\"bar\", figsize=(10, 6))\n",
+    "ax.set_ylim(df[\"ROC AUC\"].min() * 0.995, min(1.0, df[\"ROC AUC\"].max() * 1.005))\n",
+    "ax.set_title(f\"Model Comparison - {n_splits}-fold Cross-validation\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ipG2Cpb7Jrc7"
+   },
+   "source": [
+    "# Regression with TabPFN <a name=\"regression\"></a>\n",
+    "\n",
+    "Next, we'll explore how to use TabPFN for regression tasks. We will use the Boston Housing dataset, where the goal is to predict the median value of owner-occupied homes.\n",
+    "\n",
+    "We will measure performance using the [Root Mean Squared Error](https://scikit-learn.org/1.5/modules/generated/sklearn.metrics.root_mean_squared_error.html), and again, we will compare TabPFN with other popular regression models."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Qzrj9m0fI32f"
+   },
+   "source": [
+    "### **Loading Boston Housing Dataset**\n",
+    "\n",
+    "### **Dataset Overview**\n",
+    "\n",
+    "-   **Objective:** Predict the **median value of owner-occupied homes** in the Boston area based on various socioeconomic and environmental attributes.\n",
+    "    \n",
+    "-   **Number of Instances:** 506\n",
+    "    \n",
+    "-   **Number of Attributes:** 14 (13 numeric features + 1 target variable)\n",
+    "    \n",
+    "-   **Target Variable:** `MEDV` — Median value of owner-occupied homes (in $1000s)\n",
+    "    \n",
+    "-   **Class Type:** Numeric\n",
+    "    \n",
+    "-   **Class Index:** Last\n",
+    "    \n",
+    "\n",
+    "* * *\n",
+    "\n",
+    "<details>\n",
+    "\n",
+    "\n",
+    "**Citation:**\n",
+    "\n",
+    "> Harrison, D. and Rubinfeld, D.L. (1978).  \n",
+    "> _Hedonic prices and the demand for clean air._  \n",
+    "> _Journal of Environmental Economics & Management_, 5, 81–102.  \n",
+    "> Used in Belsley, Kuh & Welsch, _Regression Diagnostics: Identifying Influential Data and Sources of Collinearity_, Wiley, 1980.\n",
+    "\n",
+    "\n",
+    "### **Attribute Information**\n",
+    "\n",
+    "**Feature**\n",
+    "\n",
+    "**Description**\n",
+    "\n",
+    "`CRIM`\n",
+    "\n",
+    "Per capita crime rate by town\n",
+    "\n",
+    "`ZN`\n",
+    "\n",
+    "Proportion of residential land zoned for lots over 25,000 sq.ft.\n",
+    "\n",
+    "`INDUS`\n",
+    "\n",
+    "Proportion of non-retail business acres per town\n",
+    "\n",
+    "`CHAS`\n",
+    "\n",
+    "Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)\n",
+    "\n",
+    "`NOX`\n",
+    "\n",
+    "Nitric oxides concentration (parts per 10 million)\n",
+    "\n",
+    "`RM`\n",
+    "\n",
+    "Average number of rooms per dwelling\n",
+    "\n",
+    "`AGE`\n",
+    "\n",
+    "Proportion of owner-occupied units built prior to 1940\n",
+    "\n",
+    "`DIS`\n",
+    "\n",
+    "Weighted distances to five Boston employment centres\n",
+    "\n",
+    "`RAD`\n",
+    "\n",
+    "Index of accessibility to radial highways\n",
+    "\n",
+    "`TAX`\n",
+    "\n",
+    "Full-value property-tax rate per $10,000\n",
+    "\n",
+    "`PTRATIO`\n",
+    "\n",
+    "Pupil–teacher ratio by town\n",
+    "\n",
+    "`B`\n",
+    "\n",
+    "1000(Bk − 0.63)², where Bk is the proportion of Blacks by town\n",
+    "\n",
+    "`LSTAT`\n",
+    "\n",
+    "Percentage of lower status population\n",
+    "\n",
+    "`MEDV`\n",
+    "\n",
+    "Median value of owner-occupied homes (in $1000s)\n",
+    "\n",
+    "</details>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 240
     },
+    "id": "4vbEBAKKIRaM",
+    "outputId": "d55a593d-d65f-4fdf-ac5c-6d9d32be2bf9"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "6RYILEoPXaMZ"
-      },
-      "source": [
-        "### Shapley Values\n",
-        "\n",
-        "Next, we'll use SHAP to understand our model's predictions. SHAP values break down a prediction to show the contribution of each feature, helping us see which factors are most influential for a given data point.\n"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipython-input-378995386.py:7: FutureWarning: The 'delim_whitespace' keyword in pd.read_csv is deprecated and will be removed in a future version. Use ``sep='\\s+'`` instead\n",
+      "  df_boston = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data\",\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "8CJtLwWUe-KV",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "outputId": "d743c96e-c69b-401d-8571-9ceb8e9ba2b9"
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "summary": "{\n  \"name\": \"display(X\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"CRIM\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.02277820712874479,\n        \"min\": 0.00632,\n        \"max\": 0.06905,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.02731,\n          0.06905,\n          0.02729\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ZN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8.049844718999244,\n        \"min\": 0.0,\n        \"max\": 18.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0.0,\n          18.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDUS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.6551591289412393,\n        \"min\": 2.18,\n        \"max\": 7.07,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          2.31,\n          7.07\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CHAS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"NOX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.03376832835661252,\n        \"min\": 0.458,\n        \"max\": 0.538,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0.538\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"RM\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3467163105479751,\n        \"min\": 6.421,\n        \"max\": 7.185,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          6.421\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AGE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 12.402943199095933,\n        \"min\": 45.8,\n        \"max\": 78.9,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          78.9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DIS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.8400812621407525,\n        \"min\": 4.09,\n        \"max\": 6.0622,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          4.09\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"RAD\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 3,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"TAX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30.31831129861952,\n        \"min\": 222.0,\n        \"max\": 296.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          296.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"PTRATIO\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.393915348936225,\n        \"min\": 15.3,\n        \"max\": 18.7,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          15.3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"B\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.8492349769566823,\n        \"min\": 392.83,\n        \"max\": 396.9,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          396.9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"LSTAT\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.346812732196585,\n        \"min\": 2.94,\n        \"max\": 9.14,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          9.14\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
+       "type": "dataframe"
       },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "PermutationExplainer explainer: 26it [02:02,  5.10s/it]\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 800x650 with 1 Axes>"
-            ],
-            "image/png": 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FadGiBYsXL7b6P+5GD+J9JXdG0yBF5LF07do1pk2bRt26ddm/f78lvWrVqnz66afExcVZplodPHiQAgUKkDNnTqtzlChRwurxwYMHM0xPT8voP+PAwECrx3v27MEwDPr27Uvfvn0zbPuJEycoWLAgBw8etPoj/1btAti2bRsffvghy5Yts/xxle7G9S63snv3bv7++2+rwPLmNt2p3bt3A1j+8LmZl5eX5d+nT59m4MCBTJs2zaaurLT/btz83OzevRvDMChZsmSG+W/8o+pO3BiQwfU/OgsVKpRh+s1/GDk4OFCsWDGrtKCgIADL2pGDBw/i7++Pp6enVb4yZcpYjt/o5r7fzp0+Pzf3OVeuXIC5b15eXuzduxcHB4dMA8asvn5cXFz4+OOP6dmzJ/ny5aNatWo0bdqUdu3akT9//v/cr5MnT5KcnJzptLIb3Xxt0699qVKlrNKdnZ0pVqyY5XhgYCBvv/02I0aMYMqUKTz99NM0b96cl156yfLaaNOmDd9++y2vvvoq7733HvXr1+fZZ5+lVatWNkHvnbrdc3a/3h9ZPW9Wrs/d1H0nn3uffPIJ8+fP548//mDq1Kn4+flZHU/fEXf06NHs37/fKmDKkyePzfnv5LMhLS2Ns2fPWp0no2sWFBTExYsXOXnyZIav/wfxvpI7o2BNRB5Ly5Yt459//mHatGlMmzbN5viUKVMswdr9dOM394Dl2/BevXrRsGHDDMtkFIxl5syZM9SuXRsvLy8GDRpE8eLFcXV1ZfPmzbz77rtZ+gY+LS2NkJAQRowYkeHxm/94yIr0eidNmpThf+45clz/LyoyMpK1a9fSu3dvypcvj4eHB2lpaYSHh2ep/bfagfFW3y5Dxs+NyWRi4cKFViMj6W4cTb0TGZ0rs3Tjpg1B7oeb+347d/r83Iu+3cnrp3v37jRr1ox58+axePFi+vbtS0xMDMuWLeOpp566Z/3Kiju9tjf69NNPiYqKYv78+SxZsoS33nqLmJgY1q9fT0BAAG5ubqxatYrly5ezYMECFi1axPTp06lXrx5Lliy55XXPits9Z/fr/XEn573d9bmbuu/kc2/Lli2WAO6vv/6ibdu2VseHDh1K37596dixIx999BG5c+fGwcGB7t2739H75H5+NjyI95XcGQVrIvJYmjJlCn5+fnz11Vc2x+bMmcPcuXMZM2YMbm5uFClShOXLl3Px4kWr0bWb78mWfv+sjO7VltX7t6WPkDg5OREWFpZp3iJFimSprhUrVnDq1CnmzJlDrVq1LOk3jiimu1VQU7x4cbZu3Ur9+vXv2dbz6Qv7/fz8Mu1rUlIScXFxDBw40GoBffo3wDe6VdvSRwFu3l3v5hGl27XXMAwCAwMtI1f2IC0tjX379lm1adeuXQCWRf5FihRh6dKlnDt3zmp0LX0KbFbu/Xara3snz09WFS9enLS0NLZv3241zffmPHD718+N+Xv27EnPnj3ZvXs35cuX59NPP2Xy5MkZ5s9qv3x9ffHy8iI+Pj6LvbOWfu137txpNUKakpLC/v37bfoWEhJCSEgIH374IWvXriU0NJQxY8YwePBgwDzSWr9+ferXr8+IESMYOnQoH3zwAcuXL8/0Ov3X9/V/fX9k9tlzJ+e93fW5k37eyefehQsX6NChA8HBwdSoUYNhw4bRsmVLq82qZs2aRd26dRk/frxV2TNnzlg2VbmXMnoP7tq1i5w5c95ytPB+v6/kzmnNmog8di5dusScOXNo2rQprVq1svnp2rUr586ds2yV37BhQ65evcq4ceMs50hLS7MJ9Pz9/SlXrhw//PAD58+ft6SvXLmSv/76K0tt8/Pzo06dOowdO5Z//vnH5viNuxo2bNiQdevW8ccff1jSTp8+bXP7gfRvYW/81jUlJYXRo0fbnN/d3T3DaWuRkZEcOXLE6hqku3Tp0l3dL6phw4Z4eXkxdOhQrl69anM8va8ZtR/I8Obd7u7ugG1Q5uXlRd68eW22rc7oGtzKs88+i6OjIwMHDrRpi2EYGW7n/qB8+eWXVm358ssvcXJyon79+gA0btyYa9euWeUD+OyzzzCZTDRq1Oi2daR/UXHztb2T5yerIiIicHBwYNCgQTYjDun1ZPX1c/HiRZv7xBUvXhxPT89MbzuR1X45ODgQERHB//3f//H777/bnOd2ox1hYWE4OzvzxRdfWOUdP348Z8+epUmTJgAkJyfbrEkKCQnBwcHB0o/Tp0/bnD892L3dLTbc3d3/0w2p/+v741bv3ayeNyvXJ72erPbzTj733n33XQ4dOsT333/PiBEjKFq0KO3bt7eq29HR0aYPM2fOtKxDvtfWrVtnNf3+8OHDzJ8/nwYNGtxydO5+v6/kzmlkTUQeOz/99BPnzp2jefPmGR6vVq2a5QbZbdq0ISIigipVqtCzZ0/27NlD6dKl+emnnyx/GN34jevQoUNp0aIFoaGhdOjQgaSkJL788kvKlStnFcBl5quvvqJmzZqEhITQqVMnihUrxvHjx1m3bh0JCQmWe/K88847TJ48mWeeeYY333zTsnV/4cKFOX36tKVdNWrUIFeuXLRv35633noLk8nEpEmTMvwjsmLFikyfPp23336bypUr4+HhQbNmzXj55ZeZMWMGr7/+OsuXLyc0NJRr166xY8cOZsyYweLFizPcXCEzXl5efP3117z88stUqFCB559/Hl9fXw4dOsSCBQsIDQ3lyy+/xMvLi1q1ajFs2DCuXr1KwYIFWbJkSYYjg+mL6T/44AOef/55nJycaNasGe7u7rz66qv873//49VXX6VSpUqsWrXKMgKVFcWLF2fw4MH06dOHAwcOEBERgaenJ/v372fu3LlER0fTq1evO7oG94KrqyuLFi2iffv2VK1alYULF7JgwQLef/99y7fnzZo1o27dunzwwQccOHCAJ598kiVLljB//ny6d++e6fbl6dzc3AgODmb69OkEBQWRO3duypUrR7ly5bL8/GRViRIl+OCDD/joo494+umnefbZZ3FxcWHjxo34+/sTExOT5dfPrl27qF+/PpGRkQQHB5MjRw7mzp3L8ePHef7552/Zhjt53Q0dOpQlS5ZQu3Ztyxbv//zzDzNnzmT16tWZ3tLB19eXPn36MHDgQMLDw2nevDk7d+5k9OjRVK5cmZdeegkwT93u2rUrrVu3JigoiNTUVCZNmoSjoyPPPfccAIMGDWLVqlU0adKEIkWKcOLECUaPHk1AQIDVvQIzUrFiRZYuXcqIESPw9/cnMDDQsqlNVvzX98et3rtZPW9Wrs+d9jOrn3vLli1j9OjR9O/fnwoVKgDm27LUqVOHvn37MmzYMACaNm3KoEGD6NChAzVq1OCvv/5iypQpNmtO75Vy5crRsGFDq637wXxbjFu53+8ruQsPZM9JERE70qxZM8PV1dW4cOHCLfNERUUZTk5ORmJiomEY5m3LX3jhBcPT09Pw9vY2oqKijDVr1hiAMW3aNKuy06ZNM0qXLm24uLgY5cqVM3766SfjueeeM0qXLm3Jk76V/K22Pd67d6/Rrl07I3/+/IaTk5NRsGBBo2nTpsasWbOs8m3ZssV4+umnDRcXFyMgIMCIiYkxvvjiCwMwjh07Zsm3Zs0ao1q1aoabm5vh7+9vvPPOO5atpm/cCv78+fPGCy+8YPj4+NjcbiAlJcX4+OOPjbJlyxouLi5Grly5jIoVKxoDBw40zp49m+k1z2jr/nTLly83GjZsaHh7exuurq5G8eLFjaioKKstpxMSEoyWLVsaPj4+hre3t9G6dWvj6NGjGW4l/9FHHxkFCxY0HBwcrLakvnjxovHKK68Y3t7ehqenpxEZGWmcOHHillv332r789mzZxs1a9Y03N3dDXd3d6N06dJGly5djJ07d2Z6DW61dX+TJk1s8gJGly5drNIyes20b9/ecHd3N/bu3Ws0aNDAyJkzp5EvXz6jf//+NluEnzt3zujRo4fh7+9vODk5GSVLljSGDx9u2Vo+s7rTrV271qhYsaLh7Oxsdd2y+vzc6tpmdG0MwzC+++4746mnnrK83mrXrm251Ua6271+EhMTjS5duhilS5c23N3dDW9vb6Nq1arGjBkzMuzjje7kdXfw4EGjXbt2hq+vr+Hi4mIUK1bM6NKli3HlyhWrPma0vb9hmLfqL126tOHk5GTky5fP6Ny5s5GUlGQ5vm/fPqNjx45G8eLFDVdXVyN37txG3bp1jaVLl1ryxMXFGS1atDD8/f0NZ2dnw9/f32jbtq2xa9eu2/Z1x44dRq1atQw3NzcDsGxvf6fP2d2+Pwzj1u/drJw3K9cns37eyu0+95KTk40iRYoYFSpUMK5evWpVtkePHoaDg4Oxbt06wzDMW/f37NnTKFCggOHm5maEhoYa69atM2rXrm3Url3bUi596/6bb0Nwq9dQRs9R+vt48uTJRsmSJQ0XFxfjqaeesvq8v/GcNz+P9/N9JXfGZBgPYKWyiMgjaN68ebRs2ZLVq1cTGhqaad7y5cvj6+tLbGzsfW9X9+7dGTt2LOfPn/9PGwqI/YuKimLWrFlZHrUVkceDyWSiS5cuNlOf5eGjNWsiIllw6dIlq8fXrl1j1KhReHl5Waa9AFy9etVm3cSKFSvYunUrderUue/tOnXqFJMmTaJmzZoK1ERERB5yWrMmIpIFb775JpcuXaJ69epcuXKFOXPmsHbtWoYOHWq1FfeRI0cICwvjpZdewt/fnx07djBmzBjy589vc1PZe6F69erUqVOHMmXKcPz4ccaPH09ycvIt79EmIiIiDw8FayIiWVCvXj0+/fRTfv75Zy5fvkyJEiUYNWoUXbt2tcqXK1cuKlasyLfffsvJkydxd3enSZMm/O9//8vwpqf/VePGjZk1axbffPMNJpOJChUqMH78eKst+kVEROThpDVrIiIiIiIidkhr1kREREREROyQgjURERERERE7pGBN5BFjGAbJyckZ3vBYRERERB4eCtZEHjHnzp3D29ubc+fOZXdTREREROQ/ULAmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2KEc2d0AEblP/jkN51OzuxUiIo8Wdxfwds/uVojIY0LBmsijqus4OJyc3a0QEXl0BPrB+C4K1kTkgVGwJvKoOpAIe05mdytERERE5C5pzZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJih7R1v4iIiEh2O3MB3vkB5v4GF69AlZLwaXuoUPz2ZTfshonL4Lfd8OdBSL0Gxpz732YRue80siZyB8LDwzGZTNndDBEReZSkpUGTwTD1V+jaCIa1gxNnoU4/2H309uV/2QTfxoHJBMXy3f/2isgDo2DtPouJieGdd97J7maInYiPjyc6Oprly5dnd1NERORBqdMXokbd+visdbB2J0zsCv3bQJdGsGIQODpA/+m3P3/ncDg7CX4fDs88ee/aLSLZTsHafTZ16lQmTJiQ3c2Qe2T+/PmcO3fursvv2LGDcePGsX79+nvYKhEReajNWgf5fODZatfTfL0hsgbM3wBXrmZePp8PuLnczxaKSDZRsHaHzp07R0pKSnY3Q7KJi4sLHh4e2d0MERF5lGzZDxWKgcNNf5ZVKWlev7YrC1MhReSR9NAFa9u2bcNkMtGpUyer9IoVK2Iymejdu7dVelBQEAULFrRKW7VqFaGhoXh4eODk5ERAQADdu3fn6lXrb67S1ycdOnSIRo0a4e3tjbe3N7t27QJg2LBhlCxZkpw5c+Li4oKfnx9hYWEcOnQIAF9fX+Lj40lMTMRkMll+Zs2addt+zpw5kypVqlja6OfnR5MmTUhISLDkSUlJoVu3bgQEBODk5ISHhwehoaGsXr3a6lzx8fGYTCaio6P57rvvKFGiBE5OTvj4+PDiiy9mGHxu2bKFRo0akTt3bnLkyEGuXLmoXr06S5cuteSZMmUKderUwc/PD2dnZ3LmzEmFChWYPXu21bnq1KlDjhw5OHLkiE09GzduxGQyERkZaZX+xRdfEBwcjKurKy4uLgQFBfHVV1/d9roBzJo1C5PJRExMDH369KFAgQI4OTlRoEAB+vTpk2GZuXPn8tRTT5EzZ06cnZ0pVqwYgwcPtsmX0Zq19LSTJ08SERGBl5cXTk5OlClThoULF1ryxcTE0Lp1awDef/99y+shJCQEgGvXrvHOO+9QpEgRXF1dcXNzw9/fnyZNmnDlypUs9V1ERB5C/yRBgVy26elpR08/2PaIiN146HaDLFu2LH5+fqxdu9aSdunSJUtAsmrVKkt6YmIie/fupUWLFpa02NhYmjZtiqOjI23atCF//vwsXryYkSNHEh8fbxWMpKtduza5c+emS5cuXLhwAR8fH4YNG8a7775LcHAw3bp1w83NjUOHDrFixQoSEhIoXLgwQ4YMYeDAgZw7d45+/fpZzlexYsVM+zhgwAAGDRpErly5iIyMpGjRohw8eJBly5axe/duAgICAGjQoAErV67kqaee4uWXX+bYsWNMnz6dsLAwfvnlF+rVq2d13uXLlzNt2jQiIyPx9/dnwYIFTJ06lVy5cvHll19aXaMWLVpw7do1mjVrRrly5Th16hRr164lLi6OsLAwAMaPH8/Zs2eJiIigUKFCJCQkMGvWLCIjI5k9ezYREREAREVFsXLlSr766iuGDh1q1abRo0cD8Prrr1vSOnbsyIQJE6hYsSJvvfUWjo6OLFiwgK5du/LPP/9kGERl5NtvvyUpKYnIyEg8PT2ZN28e//vf/zh9+jRjx4615Bs/fjzR0dF4e3vTrl07PD09mT9/Pn379mXv3r1ZnsZas2ZNfHx86Nq1K6dOnWLSpElERkZy4MAB8uTJQ+PGjdm1axcTJ06kWbNm1KpVCwB/f38AunbtypgxY6hatSrt2rXD0dGRffv2sWzZMi5evIiLi6a4iIjYvaupcPaibdqVq5CYbJ2e28M8mnYpBVwy+JPM1dn8+5Jm9Ig8rkyGYRjZ3Yg71bRpUxYtWsTp06fx8vJi7ty5PPvss4SFhbF69WrOnj2Ls7Mz48eP59VXX+Wrr77ijTfeAKBMmTLs2rWL5cuXW/5YTktLo27duqxatYpp06bRpk0bwDxisnjxYurXr28TxNWsWZNNmzZZ6rqVkJAQjh07xsmTJ7PUt507d1KuXDny5cvHpk2byJfPelena9eu4ejoyNSpU3nxxRepXbs2y5Ytw+HfqRMrV66kXr16lC5dmm3btgHmkbWQkBCcnZ3ZtGkT5cqVs/S7aNGiJCcnc+bMGau0f/75h7i4OMs1url+gDNnzuDj42N1fP/+/TzxxBOULl2ajRs3AnD16lV8fX3x9fVl9+7dlrxpaWn4+fnh7u7OwYMHASzBYPv27Zk4caLVuWvUqMGWLVtISEggT548t7yGs2bNonXr1ri4uLB161ZKlSoFmIP6J554gn379rF9+3ZKlSrF1atXKVCgABcvXuTPP/+kRIkSlrwVKlRg586d/P7771SoUAG4/pq48W2TnhYREcHcuXMt6V9++SVvvvkm/fv3Z8CAAVZtGzp0qM0oX7FixUhJSbEaPb0bycnJeHt7c7ZENF57sva6ExGRLChVEJYNBP/crF+/nsqVK1v+T9y+fTsFChQg19YjULffbU5ktmlWJyo+1wg8XoA2oax95Slq1KhhOb5jxBRK95wNi/pCw6eu15HLPOKWkJBAWloahQsXBsyf/1dfG02eaRssW/evXbvW6pw3P75lPzKp49ChQ5a/JVSH6lAd/62O23nopkEC1K9fn2vXrvHTTz8BsHDhQry8vHjnnXe4fPkysbGxgHmEyGQyWUZ4Dh48yI4dO6hevbpVEOLg4MCgQYMAmDFjhk19H3zwgU2ap6cnKSkpTJw4kbS0tHvWt2+//ZbU1FTeeecdm0ANsLxYZs6cCcCgQYMsgRqYRwGrVavG9u3bLdMx0z399NNWLx4HBweqVKnC2bNnSUpKAmDFihUcPnyYJk2a2ARqN9YPWAVqSUlJHDlyxDL97++//7Ycc3JyonHjxuzZs4cNGzZY0mfPns2pU6do1aqVVf9NJhNdunQhISHB6qdJkyZcvnyZRYsWZX4R/9WwYUNLoAbg5ubGG2+8QVpaGlOmTAHMweGpU6do3ry5JVBLz9ujRw8Mw2Dy5MlZqq9v375Wj1u2bAlgmTZ7Ox4eHpw+fZr58+dnKb+IiGSfatWqWf2fGBwcbP4D7smiENvf+ueJItCgvE16xSb1zYUL5IJ/kmz+gCvt/e/fAf65rev4V0BAgOWPRAAvLy+bLzNvPufNj2/Zj0zquPFvCdWhOlTHf6vjdh7KYC09+Fq8eDEAa9asoUKFCtSrVw93d3d++eUXAH777TeKFClimWa2fft2AKs/4NNVqVLFsj7tZhlNWxwyZAh58+bltddew9vbm5o1a/LRRx9x6tSp/9S3PXv2ALd/Ig8fPozJZKJq1ao2x9L7l97fdEWKFLHJmzu3+T+Ao0fNi5fj4+MBeOqpp27b1j/++IO6devi7u5O7ty5CQgIoFChQmzcuJGLF62ngKSPbKZPewT47rvvcHBwoEuXLpa0PXv2YBgGVapUoVChQlY/H374IUCGa98yUrp0aZu09BGyvXv3AtcDqZvfWACVK1cGzKOFWZG+9ixd+lrJ9ED4dmJiYnByciIiIoLcuXMTFhbGiBEjuHTpUpbKi4iIHcjlAWFPWv/k8jAHZDenp09zLF8UNu8z32/tRr/thpwuEOT/wLshIvbhoVuzBhAYGEhAQADr1q0jOTmZXbt2ERkZiaOjI08++SSrV6/myJEjHDx40DKl8b/w8vKySatQoQL79+9nxowZLF68mI0bN9KvXz8+++wzli1bRvny5f9zvffajd8M3OxOZ8MmJSVRr149Ll++zEsvvUT58uXx9vbGwcGB//3vf/z5559W+WvWrEnRokX5+eefSUtL4/z586xYsYIKFSpQrFgxq3aYTCZ++OGHW7a3SpUqd9TWB8XJySnD9Kxe2yZNmnDgwAF+/PFH4uLi2LBhA3FxcYwYMYINGzZYvnQQEZFHTKvq5u3756yHVv9+WZuYDDPXQrNK4HLD/y97j5l/F8//4NspIg/cQxmsAVStWpU5c+YwceJEUlNTLZuI1K5dm+HDh/Pjjz9iGAYNGjSwlAkODgbM68JutnHjRgzDsBrKvJ2cOXMSFRVFVFQUABMnTqRDhw4MGjSIOXPMc8Vv3jnwdkqWLAmY57NWqlTplvkKFy7Mpk2b+O2332ymK6aPFqX3906kjw798ccfmeabOXMmSUlJDBkyhPfff9/qWPr6rJu1bt2a4cOHM2vWLA4fPszly5d5+eWXrfIEBgayadMmSpQoQbVq1TI8T1bt2LHDJm3z5s0AFC9eHLg+Cpk+onij33//3dKme+V2r4dcuXLxxhtvWEYi+/bty+DBgxk+fDifffbZPWuHiIjYkVbVoVoQdPgStidAXk8YvQiupcHA563z1u9v/n3g+kZZHDwBk1aa//27eYYOg83LJSjiCy/Xua/NF5H756GcBgkQFhaGYRgMGzaMPHnyWEaymjVrRmpqKiNHjsTBwYHmzZtbyhQpUoTSpUuzbt061qxZY0lPS0uzBBg3byF/KxltApEeNKVv1gHmtU8XLlzI8rq2V155hRw5cjB8+HASExNtjqefJ32d14ABA6zOvWbNGtatW0dwcPAdBZ7pateuTaFChfj555+tdty8uf4cOcxx/s2jRlOmTLnlGq0uXbrg4ODAd999x9SpU3Fzc6Njx45WeV599VUAevbsaXMrBcj6lEQwT5O9MTC/dOkSo0ePxsHBgRdeeAGAevXqkSdPHv7v//6Pffv2WfJeuXKFzz//HJPJxEsvvZTlOm/H29sbIMPpshm9pqpXrw7A6dPatllE5JHl6Ai/fAhtQuGLBdD7B8jrZd7MpFTB25fffwL6/mj++e3fjbzSH4+Pu79tF5H76qEdWYuIiOCNN97gyJEjhIeHW9KrV6+Ot7c3CQkJBAUF2Sy0/eKLL2jatCkNGjSw2rp/8+bN1K9fP8vTJmvVqoWnpydVqlShcOHCJCUlWe7v1a5dO0u+SpUqsWHDBlq1akVoaCiOjo60bNkyw/VjYB7p6dOnD4MHD6Z06dK0aNGCokWLkpCQQGxsLOPHj6du3bq88MILfPPNNyxfvpzKlSvTsGFDy9b9Tk5OjBo16i6uqnnTkXHjxhEREUHdunVp3rw55cqVIykpibVr11K/fn1iYmJo0qQJ3t7eDB06lP3791OoUCH++OMPFi5cSOHChTNc+1ekSBEqV67MihUruHr1Kk2aNLG5wXTDhg2Jjo7mm2++oXjx4jRu3JiCBQty9OhRtm7dyoYNG0hNTc1SXwoWLEj16tVp06YNnp6ezJ07lz179vDKK69Y1rM5OTnx8ccfEx0dTeXKlS3b/M+fP59du3YRFRVlWed2L1StWhVXV1cmT56Mu7s7uXLlwt/fn8jISIKDgylTpgwVK1a09Hn69OnkyJHDJqgVEZGHyIqPbp8nlwd828X8k5kbR9TS1Sln2f1RRB4tD22wlj9/fgIDA9m3bx9169a1OlapUiXi4uIy3KTjmWeeYcmSJfTp04cZM2Zw5coV/Pz86NatG8OHD89y/VFRUcydO5eZM2dy/vx5PDw8KFmyJJ9++qnlxsdg3jTiwIEDxMXFMW/ePAzDICAg4JbBGph3eCxVqhSffPIJP/74I1evXiVXrlxUqVKFoKAgS74lS5bQu3dvZs2axfDhw3FxceHJJ59k2LBh1KxZM8t9uVnDhg1ZtWoVffr0ITY2lrlz5+Lp6UmZMmUs91jLly8fP/30Ez169ODHH3/k2rVrlCxZkmnTpjFmzJgMgzWAdu3a8dtvvwHXR9FuNnbsWKpVq8aXX37J5MmTuXLlCl5eXgQGBma4M+etvPrqqyQnJzNx4kQSExPJmzcv77zzDh9//LFVvldeeQUfHx8GDx5smVYbEBDARx99ZNnU5F7x9PTk66+/ZtCgQQwdOpTU1FTKlStHZGQkUVFRxMXFMXnyZC5duoSXlxdly5alf//+1K5d+562Q0RERETs30N5nzWRzGR2L7PHge6zJiJyn9xwnzURkQfhoV2zJiIiIiIi8ihTsCYiIiIiImKHFKyJiIiIiIjYoYd2gxGRW2nVqtUd3+RbRERERMTeaGRNRERERETEDilYExERERERsUMK1kREREREROyQ1qyJPKqK5gVH5+xuhYjIoyPQL7tbICKPGQVrIo+qLzuBp1d2t0JE5NHi7pLdLRCRx4iCNZFHVYHc4KVgTURERORhpTVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYoRzZ3QARuU/+OQ3nU7O7FfIocHcBb/fsboWIiMhjR8GayKOq6zg4nJzdrZCHXaAfjO+iYE1ERCQbKFgTeVQdSIQ9J7O7FSIiIiJyl7RmTURERERExA4pWBMREREREbFDCtZERERERETskII1ERERERERO6RgTURERERExA4pWBMRkexz5gJEfw2+UeDeFur2g817s17+7wQIHwQeL0DudvDySDh5NvMyU1aC6VlzGRERETumYE3kDsTHx2MymYiOjs7upog8/NLSoMlgmPordG0Ew9rBibNQpx/sPnr78gmJUOtD2HMMhr4IvZrDgk3wzEBIuZpxmfOX4J1J4O56b/siIiJyHyhYE3nAYmJieOedd7K7GSL3X52+EDXq1sdnrYO1O2FiV+jfBro0ghWDwNEB+k+//fmHzoYLl2HZQHirCbzfCmb0hK0HYOLyjMsMngWebhBR5a66JCIi8iApWBO5A8HBwZw7d44vv/zyrs8xdepUJkyYcA9bJfKQmrUO8vnAs9Wup/l6Q2QNmL8BrtxidCzd7PXQtBIU9r2eFvYkBPnDjLW2+Xcfhc/+D0ZEQQ7He9EDERGR+0rBmsgdcHBwwMPDA2dn5+xuisjDb8t+qFAMHG76r6hKSbh4BXZlMhXyyCnzlMlKxW2PVSkJW/bZpnf/DuqWg8YV/1u7RUREHpCHLliLiYnBZDIxffp0Xn/9dfLmzYuzszNBQUH88ssvAMyePZvg4GBcXFzw8fGhc+fOGZ4rNjaW0NBQPD09cXJywt/fny5dupCSkmKVb9GiRYSHh1OgQAFcXFxwdXWlTJkyjBkzxuac4eHhmEwmTp48SUREBF5eXjg5OVGmTBkWLlyY5X4mJibSoUMHChYsiJOTEx4eHgQHB/P5559b5Vu1ahWhoaF4eHjg5OREQEAA3bt35+pV62+k77RdaWlpDBo0iKCgIFxdXXF1daVw4cK8+uqrljynTp2iY8eOBAUFWa5h/vz5adeuHcnJyZZ869evx2Qy8fzzz2fY13r16pEjRw4OHTpkSdu7dy8RERHkzZuXHDlykCtXLpo1a8bBgwezdP1CQkLw9fVl69atVK9enZw5c+Lm5kZoaChbt261yX/mzBnat29Pvnz5cHJywsfHhwYNGrBt2zarfBmtWbsx7bvvvqNEiRKWc7z44otWrydfX1/i4+NJTEzEZDJZfmbNmgXA2rVrqVWrFrlz57ac44knntBInDya/kmCArls09PTjp7OvOyNeW8uf/q89cjcgt9hyVYY0eHu2ysiIvKA5cjuBtytDz74gLS0NKKiokhJSWHixIk899xzjBw5krfffpvnnnuOVq1aMW/ePMaMGUPx4sXp1auXpfyECROIjo4mf/78REVFkSdPHtavX8/XX3/NX3/9xapVqyx5f/zxR/bv30+jRo0oWrQoiYmJzJ49m86dO3Px4kXefvttm/bVrFkTHx8funbtyqlTp5g0aRKRkZEcOHCAPHnyZNq348ePU7lyZQ4fPszTTz9Nu3btSE1NZevWrfz88890794dMAebTZs2xdHRkTZt2pA/f34WL17MyJEjiY+PZ+nSpXfdrgYNGhAXF0dQUBCdOnUiV65c7Nixg0WLFlny7N27lzlz5lCvXj1atmyJk5MTv/76K5MnT2bbtm1s2rQJgGrVqlGiRAkWLVrE1atXcXJyspwjMTGRNWvWULlyZQoXLgzA33//TWhoKKmpqURERFCiRAl2797NrFmzqFatGn/++Se+vjdMe7qFK1euUL9+fYKDg+nZsye7du1izpw51K5dm82bN1OsWDFLvho1avD333/z9NNPU7t2bUve0NBQfvvtN0qVKnXb+pYvX860adOIjIzE39+fBQsWMHXqVHLlymWZNjlkyBAGDhzIuXPn6Nevn6VsxYoVOXLkCI0aNQIgMjKSokWLcvLkSbZs2cKaNWvo0EF/ZIodu5oKZy/apl25ConJ1um5PcyjaZdSwCWD/4Zc/x25vpRieyxd+jEXJ9tjrk7X87g4mTcb6TEBXm8AwYWy1h8RERE78NAGa2lpaWzbtg03NzfAPJISHR1N586dWbRoEc888wwAffr0oUCBAowbN84SrJ0/f54ePXoQFBTEli1brKa09e7dm08++YRZs2bRqlUrAEaOHImPj49V/YMHD6Z06dKMGDEiw2AtODiYuXPnWh6HhITw5ptvMmrUKAYMGJBp315//XUOHz7MgAED6N+/v9Wxa9euWf791ltvkZqaSmxsLLVq1QLMwUDdunWJi4tj+vTptGnT5o7b9cUXXxAXF0dYWBiLFi3C0fH62o4b6w8JCeH48eO4uLhY1fHKK6/w3XffWUYkAdq0acOQIUOYMmUKUVFRlrxjxowhJSWFdu3aWdI6duxIamoqGzdutAqS2rVrR3h4OB988AHffPNNptcQ4Ny5c7Ru3ZoZM2ZY1de5c2d69OjB/PnzAfj444/5+++/efHFF5k8ebIl74QJE+jYsSNdu3YlNjb2tvUdOnSITZs2Ua5cOQAGDBhA0aJFmTx5siVYi46OZtSoUaSkpFh9eQAwbtw4kpOTGTlyJG+99dZt6xOxK2t2mLfdv9nanTBttXXa/jFQ1A/cnOFKqm2Zy/8GYm6ZTDdOP5bRurbLV63zfPZ/kHgOBmY8ui8iImKvHrppkOmioqIsgRpAs2bNAChVqpQlUANwc3OjTJkyHD16fe3D9OnTOXv2LC+++CInTpwgISHB8hMZGQnAzz//bMl/Y6CWnJzMkSNHSE5OpkqVKhw5coTExESb9vXt29fqccuWLQHYtWtXpv26du0asbGxFCxY0CZQAyyB08GDB9mxYwfVq1e3BGpgXlM1aNAgAKsg5U7a9eOPPwLwzTffWAVqN9YP5mubHqilpKRw7NgxEhISaNy4MQArV6605H3jjTfIkSMH33//vdX5pk2bhru7uyWAO3nyJL/99htPP/007u7uVs9NmTJlyJ8/v9Wo5+3873//s3r8+uuv4+/vb9W2//u//8NkMvHJJ59Y5e3QoQNFixZl9erVVkHqrTz99NOWQA3Mz0WVKlU4e/YsSUlJty2fO3duABYuXJjha0oku23fvt3qtZyQkHB9+vKTRbkwrzf7v2kPsf3NP08UIalK0euPY/uz7fPWkN/HXKZALpL+3m/1/tq+fTsX9hwxP/DPbV0H5s/g+Pj469Mf/0li7VrrzURO/LnLPHrn4gRnL3Bt0HTSXqkPyZfgwAl2x64h5XQyGAYcOMHRP/7OuI4b3FzHzY/Xr19v049bXivVoTpUh+pQHaoji0yGYRh3VCKbxcTE8P777zNt2jSbUSOTyURYWJjNKEh4eDiLFy8mvavdu3dn5MiRmdbTuHFjFixYAJgDo65du7Jq1SqrtVjptm/fTpkyZazqSklJsZrul96+8PDwTNeuHTx4kKJFi1K3bl2WLVt2y3wLFy6kcePGdOzYkfHjx1sdu3TpEu7u7lSsWJGNGzfecbsCAgK4cOFClgKMvn378sMPP3D48GFufim99tprVuv6atasyYYNGzh69Ch58+YlPj6eJ554goiICObMmQOY1wemTwW8FT8/P44fP55pnpCQEPbt28eFCxdsjoWGhrJ27VqSkpLw8fGhYMGCXL58mVOnTtnkDQsLIy4ujgMHDlCkSBHi4+MJCQmhU6dOltG99LSMnovo6GjGjRtHfHw8ZcuWtbTt2LFjnDx50qa+hg0bsmTJEhwdHSlZsiQ1a9akY8eOVK9ePdP+3ig5ORlvb2/OlojGa49tHSJ3pFRB89b4/rnvvGydvuYRtIlvZny89XD49W84+q31JiPRX8OUVXD6h4ynOabzi4I65WCG9Sg1pbpCQB6IGwgHTkDg65m3s0UVmPdelrokIiLyID200yBvHvG5XfqN0oOKHj16ULly5QzzFC1aFDBPt6xTpw4JCQm0adOGKlWqkDt3bhwdHRk/fjxxcXEZjrrcHBDdXHd2uZft6tWrF59++ikVKlTg1VdfpVChQri4uHDo0CHee+890tLSrPK3a9eONWvW8PXXX9O3b1+++uorDMOw2qwjvR1hYWF07Ngxw3rd3d3vuK0PQmavvaxe38WLF7NmzRpmzZrFunXrmDRpEt999x3vvvsuQ4cOvVdNFbEPraqbt++fsx5a1TCnJSbDzLXQrJJ1oLb3mPl38fzX056rDt8vh8OJUCivOS3uT/Mukj3Msy3w84a579rW/cUCWLcLfuyR8SYlIiIiduChDdb+i9KlSwPg4eFB27ZtM83766+/cuDAAV599VXGjRtndSwr66buVEBAAO7u7uzevTvTfMHBwQDs3LnT5tjGjRsxDMOyYcedKly4MOvWrWP//v0EBgbeMt/s2bPx9fVlw4YNVoHKpEmTMszfvn17evXqxbRp0+jbty/z5s3D39/fsq4N4IknnsBkMnH16tXbPje3c/HiRfbt22fZSCTdgQMH8PLyskxvLViwIL///jvHjx8nX758Vnn37duHm5sbAQEB/6ktNzKZTJkeDw0NJTQ0FDBvNvPUU08xYsQIBg8ejMPNW5yLPMxaVYdqQdDhS9ieAHk9YfQiuJZmu76s/r/Twg+MvZ72/nPmwK5uP+jWBM5fhuHzIaQIdKhnzpPTBSKq2tY9bwNs2JPxMRERETvxWP7l17ZtW7y8vBg9erTVWrZ0586ds0yJy5HDHM/ePDKyZs0aVq9ebVP2v3J0dKRBgwYkJCQwePBgm+Ppo1VFihShdOnSrFu3jjVr1lgdT98oJH393Z164YUXAPP6rptHDW8cLUsP0G5MS0lJYdiwYRme18XFhfDwcP7++29GjBjBsWPHeO6556zyFCxYkMqVK/Prr79absVwc/03zg2+nffes57aNGbMGI4ePUrt2rUtaU2bNsUwDHr37m2V9/vvv2f//v2EhoZmacQ2q9zc3Lhw4YLNyOPRo0dtrne+fPkoUKAAKSkpGU7pFHmoOTrCLx9Cm1DzSFfvHyCvl3naZamCty9fKC+s/Mg82vbeZBg2DxpXMK+Py2z6pIiIyEPisRxZ8/Hx4auvvqJjx46ULl2aFi1aULJkSZKSkti1axcrVqzg+++/p1WrVlSpUoVChQrx/fffc/HiRUqXLs3OnTuZM2cORYoUYe/evfe8faNHj+a3336jb9++LF261LJe6Y8//rDs/gjmXRubNm1KgwYNrLbu37x5M/Xr17dZ05dVXbt2Zfbs2SxZsoSyZcvSoEEDcufOzc6dO1mzZo0lWGrcuDGjRo2iatWqNGvWjLNnzzJ//vxMA5vXXnuNmTNn8uGHH2IymejSpYtNnu+//56aNWvSvHlzGjZsyFNPPcW1a9fYt28fy5cvJyIiIkujmp6enixbtozatWtTq1Yty3b83t7efPbZZ5Z87777LtOmTWPSpEkcPnyYmjVrsnv3bmbPno23tzejRo26i6t4a5UqVWLDhg20atXKEgi2bNmSr776iu+++4569epRokQJnJ2dWbVqFZs3b6Z27dp4enre03aI3HcrPrp9nlwe8G0X809mbhxRu1HZwrA4g10ob2fim7deSyciImInHstgDeCll14iMDCQ/v37s2DBApKTk3F3d6dAgQK0a9eOGjXM6yecnJxYuHAhnTt35ueff2b27NkULlyYzz77jM2bN9+XYC1//vxs3ryZnj17snTpUlavXo2rqytFihThtddes+R75plnWLJkCX369GHGjBlcuXIFPz8/unXrxvDhw/9TG5YuXUr//v2ZOnUqY8eOxWQykS9fPqvNPz799FMMw2DmzJkMHToUb29vwsPD6dq16y03xKhfvz6FChXi8OHDlC9fPsP7l5UuXZo//viDd999l2XLlrFkyRKcnJzImzcvderUyfL9xlxcXFi6dCmvv/46n3zyCYZhUKlSJUaPHk3x4sWt8q1du5Zu3bqxcOFCfv31V3LmzEmdOnX4/PPPLdNm75WYmBgOHDhAXFwc8+bNwzAMAgICaNSoEVu3bmXVqlXMnz8fBwcH8uXLx9tvv81HH2Xhj14REREReaQ8dLtBimRFZjsuPuq0G6TcU/9lN0gRERH5Tx7LNWsiIiIiIiL2TsGaiIiIiIiIHVKwJiIiIiIiYoce2w1G5NH2119/ZXcTRERERET+E42siYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJih7TBiMijqmhecHTO7lbIwy7QL7tbICIi8thSsCbyqPqyE3h6ZXcr5FHg7pLdLRAREXksKVgTeVQVyA1eCtZEREREHlZasyYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB3Kkd0NEJH75J/TcD41u1shDzt3F/B2z+5WiIiIPJYUrIk8qrqOg8PJ2d0KeZgF+sH4LgrWREREsomCNZFH1YFE2HMyu1shIiIiIndJa9ZERERERETskII1ERERERERO6RgTURERERExA4pWBMREREREbFDCtZERERERETskII1ERF58M5cgOivwTcK3NtC3X6weW/Wy/+dAOGDwOMFyN0OXh4JJ89mXmbKSjA9ay4jIiLyEFCwJnIfREdHYzKZiI+Pz+6miNiftDRoMhim/gpdG8GwdnDiLNTpB7uP3r58QiLU+hD2HIOhL0Kv5rBgEzwzEFKuZlzm/CV4ZxK4u97bvoiIiNxHCtZEHpBZs2YRHR3N8ePHs7spIvdXnb4QNerWx2etg7U7YWJX6N8GujSCFYPA0QH6T7/9+YfOhguXYdlAeKsJvN8KZvSErQdg4vKMywyeBZ5uEFHlrrokIiKSHRSsidwHX375JefOnSM4ONiStmTJEsaNG8fJk7pRtTzmZq2DfD7wbLXrab7eEFkD5m+AK7cYHUs3ez00rQSFfa+nhT0JQf4wY61t/t1H4bP/gxFRkMPxXvRARETkgVCwJnIfODs74+HhgYOD3mIiNrbshwrF4Ob3R5WScPEK7MpkKuSRU+Ypk5WK2x6rUhK27LNN7/4d1C0HjSv+t3aLiIg8YPpLMhvExMRgMpmYPn06r7/+Onnz5sXZ2ZmgoCB++eUXAGbPnk1wcDAuLi74+PjQuXPnDM8VGxtLaGgonp6eODk54e/vT5cuXUhJSbHKt2jRIsLDwylQoAAuLi64urpSpkwZxowZY3PO8PBwTCYTJ0+eJCIiAi8vL5ycnChTpgwLFy7Mcj8TExPp0KEDBQsWxMnJCQ8PD4KDg/n888+t8q1atYrQ0FA8PDxwcnIiICCA7t27c/Wq9bfrd9qutLQ0Bg0aRFBQEK6urri6ulK4cGFeffVVS55Tp07RsWNHgoKCLNcwf/78tGvXjuTkZEu+9evXYzKZeP755zPsa7169ciRIweHDh0CbNeshYeHM27cOABCQkIwmUyYTCaio6Pp3bs3JpOJqVOn2pz34sWLeHh48OSTT2bhios8JP5JggK5bNPT046ezrzsjXlvLn/6vPXI3ILfYclWGNHh7tsrIiKSTXJkdwMeZx988AFpaWlERUWRkpLCxIkTee655xg5ciRvv/02zz33HK1atWLevHmMGTOG4sWL06tXL0v5CRMmEB0dTf78+YmKiiJPnjysX7+er7/+mr/++otVq1ZZ8v7444/s37+fRo0aUbRoURITE5k9ezadO3fm4sWLvP322zbtq1mzJj4+PnTt2pVTp04xadIkIiMjOXDgAHny5Mm0b8ePH6dy5cocPnyYp59+mnbt2pGamsrWrVv5+eef6d69O2AONps2bYqjoyNt2rQhf/78LF68mJEjRxIfH8/SpUvvul0NGjQgLi6OoKAgOnXqRK5cudixYweLFi2y5Nm7dy9z5syhXr16tGzZEicnJ3799VcmT57Mtm3b2LRpEwDVqlWjRIkSLFq0iKtXr+Lk5GQ5R2JiImvWrKFy5coULlw4w+vx5ptvcv78edasWUPv3r3x8/MDoEqVKhQvXpzPP/+cb7/9lhdesN6l7ptvvuHChQu0b98+0+stkm2upsLZi7ZpV65CYrJ1em4P82japRRwyeC/H1dn8+9LKbbH0qUfc3GyPebqdD2Pi5N5s5EeE+D1BhBcKGv9ERERsSMK1rJRWloa27Ztw83NDTCPuERHR9O5c2cWLVrEM888A0CfPn0oUKAA48aNswRr58+fp0ePHgQFBbFlyxacnZ0t5+3duzeffPIJs2bNolWrVgCMHDkSHx8fq/oHDx5M6dKlGTFiRIbBWnBwMHPnzrU8DgkJ4c0332TUqFEMGDAg0769/vrrHD58mAEDBtC/f3+rY9euXbP8+6233iI1NZXY2Fhq1aoFwJAhQ6hbty5xcXFMnz6dNm3a3HG7vvjiC+Li4ggLC2PRokU4Ol5fp3Jj/SEhIRw/fhwXFxerOl555RW+++47y4gkQJs2bRgyZAhTpkwhKirKknfMmDGkpKTQrl27W16PJk2aMH/+fNasWUO7du0oV66c1fGnn36aX3/9laNHj+Lv729J//7773F3dyc6OvqW5xbJVmt2mLfdv9nanTBttXXa/jFQ1A/cnOFKqm2Zy/8GYm7OtsfSpR/LaF3b5avWeT77P0g8BwMzHhEXERGxd5oGmY2ioqIsgRpAs2bNAChVqpQlUANwc3OjTJkyHD16fR3H9OnTOXv2LC+++CInTpwgISHB8hMZGQnAzz//bMl/Y6CWnJzMkSNHSE5OpkqVKhw5coTExESb9vXt29fqccuWLQHYtWtXpv26du0asbGxFCxY0CZQAyyB08GDB9mxYwfVq1e3BGoADg4ODBo0CIAZM2bcVbt+/PFHwDwydWOgdmP9YL626YFaSkoKx44dIyEhgcaNGwOwcuVKS9433niDHDly8P3331udb9q0abi7u1sFcHfqjTfeIDU1lVGjru+gFx8fz9atWwkPD8fDw+Ouzy3yXxiGYfn39u3bSUpKsjxOSEjgcJ4cENsfYvtzYV5v9n/THp4oAg3KQ2x/tn3e2nKc/D6sXbvWPF3x3+mM69evv/4Fyr9pZz1yWNWRPr0Y4JyHk1VewHzO9LTcHqzdtBHOXjDvANkpjC0r13Jt7z9w4AScv0Ra2jXObt0NJ85kWEdycrLNbTcsddzisVU/bnGtVIfqUB2qQ3Wojpsf347JuPF/YnkgYmJieP/995k2bZrNqJHJZCIsLIzY2Fir9PDwcBYvXmz5w6l79+6MHDky03oaN27MggULAHNg1LVrV1atWmW1Fivd9u3bKVOmjFVdKSkpVtP90tsXHh6e6dq1gwcPUrRoUerWrcuyZctumW/hwoU0btyYjh07Mn78eKtjly5dwt3dnYoVK7Jx48Y7bldAQAAXLlywekPdSt++ffnhhx84fPgwN78dXnvtNat1fTVr1mTDhg0cPXqUvHnzEh8fzxNPPEFERARz5syx5IuOjmbcuHH89ddfllG0jNJu5O/vj4uLC/v37wegU6dOfPvtt6xYsYLatWvfth/pkpOT8fb25myJaLz2aOdJ+Q9KFTRvj++f+87K1elrHkGb+GbGx1sPh1//hqPfWm8yEv01TFkFp3/IeJpjOr8oqFMOZvSyTi/VFQLyQNxAc2AW+Hrm7WxRBea9l6UuiYiIZAdNg8xGN4/43C79RulBRY8ePahcuXKGeYoWLQqYp1vWqVOHhIQE2rRpQ5UqVcidOzeOjo6MHz+euLg4q28N0t0cEN1cd3a5l+3q1asXn376KRUqVODVV1+lUKFCuLi4cOjQId577z3S0tKs8rdr1441a9bw9ddf07dvX7766isMw7gn0xSff/55PvvsM5YuXUrdunWZO3cuxYsXv6NATeSh0Kq6efv+OeuhVQ1zWmIyzFwLzSpZB2p7j5l/F89/Pe256vD9cjicCIXymtPi/jTvItnDPEMBP2+Y+65t3V8sgHW74MceGW9SIiIiYkcUrD2kSpcuDYCHhwdt27bNNO+vv/7KgQMHePXVVy07Eqb75ptv7nnbAgICcHd3Z/fu3ZnmS78H2c6dO22Obdy4EcMwbrlhx+0ULlyYdevWsX//fgIDA2+Zb/bs2fj6+rJhwwarIHnSpEkZ5m/fvj29evVi2rRp9O3bl3nz5uHv729Z15YZk8mU6fG3336bUaNG8dVXX3Hs2DFOnTpFly5dbntekYdOq+pQLQg6fAnbEyCvJ4xeBNfSbNeX1f93KvWBsdfT3n/OHNjV7QfdmsD5yzB8PoQUgQ71zHlyukBEVdu6522ADXsyPiYiImJntGbtIdW2bVu8vLwYPXq01Vq2dOfOnePUqVMA5MhhjslvHnlas2YNq1evtin7Xzk6OtKgQQMSEhIYPHiwzfH00aoiRYpQunRp1q1bx5o1a6yOp28Ukr7+7k6l76r4+uuv24wa3jhalh6g3ZiWkpLCsGHDMjyvi4sL4eHh/P3334wYMYJjx47x3HPPZalN6evOjh8/nuHxgIAAQkNDWbx4MaNGjcLZ2Zk337zFNDKRh5mjI/zyIbQJNY909f4B8nqZp1yWKnj78oXywsqPzKNt702GYfOgcQXzurjMpk+KiIg8ZDSy9pDy8fHhq6++omPHjpQuXZoWLVpQsmRJkpKS2LVrFytWrOD777+nVatWVKlShUKFCvH9999z8eJFSpcuzc6dO5kzZw5FihRh796997x9o0eP5rfffqNv374sXbqU6tWrA/DHH39Ydn8E866NTZs2pUGDBlZb92/evJn69evbrOnLqq5duzJ79myWLFlC2bJladCgAblz52bnzp2sWbPGshi0cePGjBo1iqpVq9KsWTPOnj3L/PnzM52K+tprrzFz5kw+/PBDTCZTlke/ateuzYgRI+jVqxeRkZG4ublRuXJlQkNDLXk6d+7MypUr2bBhAw0bNiRv3rx31X+RbLXio9vnyeUB33Yx/2TmxhG1G5UtDIsz2IXydia+eeu1dCIiInZGwdpD7KWXXiIwMJD+/fuzYMECkpOTcXd3p0CBArRr144aNcxrQZycnFi4cCGdO3fm559/Zvbs2RQuXJjPPvuMzZs335dgLX/+/GzevJmePXuydOlSVq9ejaurK0WKFOG1116z5HvmmWdYsmQJffr0YcaMGVy5cgU/Pz+6devG8OHD/1Mbli5dSv/+/Zk6dSpjx47FZDKRL18+GjVqZMnz6aefYhgGM2fOZOjQoXh7exMeHk7Xrl0tAebN6tevT6FChTh8+DDly5enVKlSWWpP8+bN6datG1OnTuXDDz8kLS2NTp06WQVrrVu3pnv37hw7dozXX7/N5ggiIiIi8kjTbpAidqZQoUKkpaVx5MiRuyqv3SDlnrnb3SBFRETkntCaNRE7MmPGDBISEnj+ed3EV0RERORxp2mQInZgxowZ7Nixgy+//BJPT0/69OmT3U0SERERkWymYE3EDnz00Uds376dgIAAvvnmG20sIiIiIiIK1kTswV9//ZXdTRARERERO6M1ayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJihxSsiYiIiIiI2CFtMCLyqCqaFxyds7sV8jAL9MvuFoiIiDzWFKyJPKq+7ASeXtndCnnYubtkdwtEREQeWwrWRB5VBXKDl4I1ERERkYeV1qyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHFKyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB1SsCYiIiIiImKHcmR3A0TkPvnnNJxPze5WSEbcXcDbPbtbISIiInZOwZrIo6rrODicnN2tkJsF+sH4LgrWRERE5LYUrIk8qg4kwp6T2d0KEREREblLWrMmIiIiIiJihxSsiYiIiIiI2CEFayIiIiIiInZIwZqIiIiIiIgdUrAmIiIiIiJih7QbpIjIo+LMBXjnB5j7G1y8AlVKwqftoULxrJX/OwF6fAerd4BzDmhSEUZEga/39TxHT5vr2LjH/G9HBwjyhy6NoF0dMJnuR89EREQeSwrWREQeBWlp0GQwbD0IvVtAXi8YvQjq9INNw6Gkf+blExKh1ofgnROGvgjnL8EnP8FfB2HDx+DsZM6XmAwJp6BVdSicF65eg9itEDUKdh6BoS/d/76KiIg8JhSsySMtJiaGpKQkhg0blt1NEflv6vSFon4w8c2Mj89aB2t3wsxe0KqGOS2yBgR1hf7TYWqPzM8/dDZcuGwO7Ar7mtOqlIRnBsLE5RDdwJz2RFFY8ZF12a6NodlQ+OIX+KgtODredTdFRETkOq1Zk0fa1KlTmTBhQnY3Q+T+m7UO8vnAs9Wup/l6mwO2+RvgytXMy89eD00rXQ/UAMKeNE9xnLH29vUX9TVPvUxJvavmi4iIiC0Fa/JQOXfuHCkpKdndjEydOnUqu5sgj6Mt+6FCMXC46WO9SklzELXr6K3LHjkFJ85CpQzWtlUpCVv22aZfumKeEnngBHy/HCYsh+pB4Oby3/ohIiIiFgrW5I5s27YNk8lEp06drNIrVqyIyWSid+/eVulBQUEULFjQKm3VqlWEhobi4eGBk5MTAQEBdO/enatXrb/5Dw8Px2QycejQIRo1aoS3tzfe3t7s2rULgGHDhlGyZEly5syJi4sLfn5+hIWFcejQIQB8fX2Jj48nMTERk8lk+Zk1a1amffziiy+oVq0aefPmxcnJCU9PT2rUqMGqVats8vr6+hISEsKyZcuoWLEiOXPmpEyZMpbjmzdv5plnnsHHx4ccOXLg6+vLiy++yJkzZ6zOs2HDBlq2bEmhQoVwdXXFxcWF4sWL89FHN003E7mVf5KgQC7b9PS0o6czL3tj3pvLnz5vOzI3cgH4RkHg6+b1atWCYFrPu2q6iIiIZExr1uSOlC1bFj8/P9auvT4t6tKlS8THx2MymawCmsTERPbu3UuLFi0sabGxsTRt2hRHR0fatGlD/vz5Wbx4MSNHjiQ+Pp6lS5fa1Fm7dm1y585Nly5duHDhAj4+PgwbNox3332X4OBgunXrhpubG4cOHWLFihUkJCRQuHBhhgwZwsCBAzl37hz9+vWznK9ixYqZ9nHs2LF4e3sTGRlJgQIF2LNnD7Nnz6ZBgwasXbuWChUqWOU/fvw4zZo1o169ejRv3pxz584BsHTpUpo3b07OnDmJjIwkICCArVu3MmPGDDZt2sTWrVtxcTGPQixYsIBNmzZRp04dihUrxvnz5/n555/p168fJ06cYNSoUXfwLMlD72oqnL1om3blqnk060a5PcyjaZdSwCWDj3RXZ/PvS5mMSKcfc3HKoLzT9Tw3Hm9b0zwSdzIZfv4djp/NvA4RERG5YwrW5I5VrlyZRYsWkZycjJeXF4sWLSIlJYWwsDBWr15NSkoKzs7OzJ8/n7S0NMLCwixl33rrLVJTU4mNjaVWrVoADBkyhLp16xIXF8f06dNp06aNVX3Fixe3CeJ++uknXF1d2bJlC87Ozhm2Mzo6mlGjRpGSkkKvXr2y3L81a9bg4+Njlda5c2eefvppPvroI+bOnWt17OTJkwwaNIi+fftapb/66qvkypWLP//8kzx58ljSx4wZQ+fOnRkxYgR9+vQBoEePHgwcONCq/LBhwyhfvjzjx4/nk08+sQR28hhYswPq9rNNX7sTpq22Tts/xrzxiJszXMlgvdjlfwMot4zfJ1bHMlrXdvlqxuWL+Jl/ANo+DdFfQ9gA2DlKUyFFRETuEU2DlDtWv359rl27xk8//QTAwoUL8fLy4p133uHy5cvExsYC5lE0k8lEREQEAAcPHmTHjh1Ur17dEqgBODg4MGjQIABmzJhhU98HH3xgk+bp6UlKSgoTJ04kLS3tnvYvPVBLS0sjMTGRhIQEAgIC8Pf3588//7TJ7+7uznvvvWeVtnr1ag4ePEizZs24dOkSCQkJlp/GjRvj4uJiuU431glw/vx5jhw5wj///EPt2rW5dOkSGzduvKd9lOx17do1jh69voYsOTmZ+Pj46xmeLMq2z1tDbH/Lz4USvtCgvOXx9pGRXFvUF/L7AHAljztXD52wnCIhIcE8JfjfKY7nvZyt64DrI+T/Tn88sP4Pq+Pr168n7egp8+idixPbt28nKSnJtg4wb+V/OJEDP/yScR23eLx+/XquXbtmeZxpHRldK9WhOlSH6lAdquMhruN2TIZhGHdUQh57+/fvp1ixYrz00ktMmjTJMjVy6dKleHt70759e7766isCAwMt+cEc1DVu3JiOHTsyfvx4q3NeunQJd3d3KlasaAlMwsPDWbx4MWfPnsXLy8sq/+bNm2nUqBEnTpzAw8ODJ598koYNG/LGG29YjWKFhIRw7NgxTp48meX+LVu2jD59+rB161auXLlidczX15cTJ05YPfbx8WH37t1W+b744gu6deuWaT1PPPEEW7duBSApKYkuXbqwZMmSDDcomTNnDi1btsxS+5OTk/H29uZsiWi89mS93/KAlCoIywaCf+47K3e7rftbD4df/4aj31pvMhL9NUxZBad/yHiaYzq/KKhTDmbcNApdqisE5IG4gRkWs5i/ASL+B9N7QmRolrokIiIimdM0SLljgYGBBAQEsG7dOpKTk9m1axeRkZE4Ojry5JNPsnr1ao4cOcLBgwdtpjTejZsDNYAKFSqwf/9+ZsyYweLFi9m4cSP9+vXjs88+Y9myZZQvX/6u6vr7779p3LgxOXPm5LXXXqNs2bJ4eHhgMpl49913uXTpkk0ZV1fXW56vbdu2NGvWLMNjvr7Xt0hv1KgRGzZsoFmzZtSuXRs/Pz8cHR2ZP38+06dPt/pWRyRDraqbt++fs/76fdYSk2HmWmhWyTpQ23vM/Lt4/utpz1U37+p4OBEK5TWnxf1p3kWyxw2v4ZNnzbcEuNn4pWAymXekFBERkXtCwZrclapVqzJnzhwmTpxIamqqZROR2rVrM3z4cH788UcMw6BBgwaWMsHBwQDs3LnT5nwbN27EMAwKFy6c5TbkzJmTqKgooqKiAJg4cSIdOnRg0KBBzJkzBwCTyXRH/Zo4cSJXrlxh0qRJtG7d2upY586dcXLKZGTiBmXLlgXA0dGRtm3bZpr3+PHjbNiwgWeeeYb58+dbHVu4cOEdtF4ea62qm3dk7PAlbE+AvJ4wehFcS4OBz1vnrd/f/PvA2Otp7z9nDuzq9oNuTeD8ZRg+H0KKQId61/MNmWVeUxf+lPmebKfPme/RtnEPvNkYShS4/30VERF5TGjNmtyVsLAwDMNg2LBh5MmTxzKS1axZM1JTUxk5ciQODg40b97cUqZIkSKULl2adevWsWbNGkt6WloaAwYMACAyMjJL9SckJNikpa+Du3FbfDc3Ny5cuJDldW2Ojo4A3Dw7eNCgQZw9ezZL5wCoW7cuhQoVYvbs2ZapjjdKSUmxrFnKkSNHhnXu3bvXZjMTkVtydIRfPoQ2ofDFAuj9A+T1Mk+5LFXw9uUL5YWVH5lH296bDMPmQeMK5jVyN47KNakI+XPBd8ugyzgYMhucc8CErjDylfvWPRERkceR1qzJXTl27Bj+/v4YhkF4eLjVCJCPjw9nz54lKCjIZhQtfev+HDlyWG3dv3nzZurXr2+162P6mrWMXqLFihXD09OTKlWqULhwYZKSkpg1axYJCQl89913ltG2Ll26MHr0aFq2bEloaCiOjo60bNmSIkWKZNivP/74g6pVq+Lu7s6LL75I7ty5Wbt2LevWrcPDw4Nr165ZrX/z9fUlf/78/PXXXzbnWr58uSV4bdasGWXLluXChQvs3buXZcuW8e6771p2g6xYsSJbtmyhadOmVK5cmQMHDjBz5kz8/PzYu3cvM2fOpFWrVll6brRmzc7d7Zo1EREReexoGqTclfz58xMYGMi+ffuoW7eu1bFKlSoRFxdHjRo1bMo988wzLFmyhD59+jBjxgyuXLmCn58f3bp1Y/jw4VmuPyoqirlz5zJz5kzOnz+Ph4cHJUuW5NNPP7WavhgTE8OBAweIi4tj3rx5GIZBQEDALYO18uXLM23aND744APGjRuHg4MD5cqVY/Hixbz++uscO3Ysy22sW7cuv/32G++//z4rVqxg7ty5uLq6ki9fPlq0aGG1Ycj8+fN57bXX+PXXX1m4cCEFChSgV69eODk58f7772e5ThERERF5dGhkTeQRo5E1O6eRNREREckirVkTERERERGxQwrWRERERERE7JCCNRERERERETukYE1ERERERMQOKVgTERERERGxQwrWRERERERE7JCCNRERERERETukYE1ERERERMQO5cjuBojIfVI0Lzg6Z3cr5GaBftndAhEREXlIKFgTeVR92Qk8vbK7FZIRd5fsboGIiIg8BBSsiTyqCuQGLwVrIiIiIg8rrVkTERERERGxQwrWRERERERE7JCCNRERERERETukYE1ERERERMQOKVgTERERERGxQwrWRERERERE7JCCNRERERERETukYE1ERERERMQOKVgTERERERGxQwrWRERERERE7JCCNRERERERETukYE1ERERERMQO5cjuBojIffLPaTifmt2teDy4u4C3e3a3QkRERB4xCtZEHlVdx8Hh5OxuxaMv0A/Gd1GwJiIiIvecgjWRR9WBRNhzMrtbISIiIiJ3SWvWRERERERE7JCCNRERERERETukYE1ERERERMQOKVgTERERERGxQwrWRERERERE7JB2gxQRsVdnLsA7P8Dc3+DiFahSEj5tDxWKZ6383wnQ4ztYvQOcc0CTijAiCny9r+c5etpcx8Y95n87OkCQP3RpBO3qgMl0P3omIiIiWaBgTeQu+fr6kj9/fv76669M00TuSloaNBkMWw9C7xaQ1wtGL4I6/WDTcCjpn3n5hESo9SF454ShL8L5S/DJT/DXQdjwMTg7mfMlJkPCKWhVHQrnhavXIHYrRI2CnUdg6Ev3v68iIiKSIQVrYvdiYmJISkpi2LBh2d0UkXunTl8o6gcT38z4+Kx1sHYnzOwFrWqY0yJrQFBX6D8dpvbI/PxDZ8OFy+bArrCvOa1KSXhmIExcDtENzGlPFIUVH1mX7doYmg2FL36Bj9qCo+Ndd1NERETuntasid2bOnUqEyZMyO5mZMnBgwfZsGFDdjdDHgWz1kE+H3i22vU0X29zwDZ/A1y5mnn52euhaaXrgRpA2JPmKY4z1t6+/qK+5qmXKal31XwRERH57xSsyQN37tw5UlJSHni9p06duu915MyZEzc3t/tejzwGtuyHCsXA4aaP6SolzUHUrqO3LnvkFJw4C5UyWNtWpSRs2WebfumKeUrkgRPw/XKYsByqB4Gby3/rh4iIiNw1BWuPoW3btmEymejUqZNVesWKFTGZTPTu3dsqPSgoiIIFC1qlrVq1itDQUDw8PHByciIgIIDu3btz9ar1t/3h4eGYTCYOHTpEo0aN8Pb2xtvbm127dgEwbNgwSpYsSc6cOXFxccHPz4+wsDAOHToEmNeAxcfHk5iYiMlksvzMmjUr0z6aTCbCw8OZPn06wcHBuLq6UqdOHQD27NlD27ZtCQwMxN3d3dL+bt262bQfYMeOHdSuXdsSiFWtWpU//vgjw3p9fX0JCQnJsC03i4mJsenL0aNHadOmDfny5cPJyQkPDw+KFy9Ojx63mfImj55/kqBALtv09LSjpzMve2Pem8ufPm87MjdyAfhGQeDr5vVq1YJgWs+7arqIiIjcG1qz9hgqW7Ysfn5+rF17fSrUpUuXiI+Px2QysWrVKkt6YmIie/fupUWLFpa02NhYmjZtiqOjI23atCF//vwsXryYkSNHEh8fz9KlS23qrF27Nrlz56ZLly5cuHABHx8fhg0bxrvvvktwcDDdunXDzc2NQ4cOsWLFChISEihcuDBDhgxh4MCBnDt3jn79+lnOV7Fixdv2c/v27bRv356IiAief/55S/q6deuIi4ujXr16lChRgpSUFOLi4vjiiy/Yv38/P/30kyXv8ePHqVWrFqdOnSIiIoLg4GB+/fVXwsLC7svoYKNGjYiPj6dly5Y88cQTXLp0ib///ps1a9bc87rkAbqaCmcv2qZduWoezbpRbg/zaNqlFHDJ4CPa1dn8+1Imr7/0Yy5OGZR3up7nxuNta5pH4k4mw8+/w/GzmdchIiIi952CtcdU5cqVWbRoEcnJyXh5ebFo0SJSUlIICwtj9erVpKSk4OzszPz580lLSyMsLMxS9q233iI1NZXY2Fhq1aoFwJAhQ6hbty5xcXFMnz6dNm3aWNVXvHhxmyDup59+wtXVlS1btuDs7JxhO6Ojoxk1ahQpKSn06tXrjvp4+PBhpk6dStu2ba3SIyIiePHFF3G4aXrZM888w88//8zevXspXtw8fezdd9/l5MmTDBkyhPfff9+SNzIykpkzZ95Re27n5MmT/Pnnn0RERNx25FAeMmt2QN1+tulrd8K01dZp+8eYNx5xc4YrGawXu/xvAOWW8XvG6lhG69ouX824fBE/8w9A26ch+msIGwA7R2kqpIiISDbRNMjHVP369bl27ZplFGnhwoV4eXnxzjvvcPnyZWJjYwHzKJrJZCIiIgIwb6CxY8cOqlevbgnUABwcHBg0aBAAM2bMsKnvgw8+sEnz9PQkJSWFiRMnkpaWdq+7SNGiRW0CtfR60wO1S5cucfToURISEmjYsCGGYbBixQpL3qVLl+Lt7W0zNTQmJuaet9fDw4McOXLw559/Eh8ff8/PL/fPzaOs69ev59q1a5bHO1yucG5OT4jtD7H9OTm1Cyll/KFBeYjtz4V5vdn/TXvz8fw+AFzK5Xp9OiNcHwn/N23ryQSrOrZv305SkvX0x6S/91uOJycnm19X/ySZR+9cnKxG163qAPNW/ocTubb8+mvRqg4gISHBMmXZqo5bnTODxzdfK9WhOlSH6lAdquNxquN2TIZhGHdUQh4J+/fvp1ixYrz00ktMmjTJMjUyPThp3749X331FYGBgZb8YA7qGjduTMeOHRk/frzVOS9duoS7uzsVK1Zk48aNgHnN2uLFizl79ixeXl5W+Tdv3kyjRo04ceIEHh4ePPnkkzRs2JA33niDPHnyWPKFhIRw7NgxTp48meX+mUwmatWqxcqVK22OpaSk0L17d+bOncvx48e5+S3w8ccf88477wDg5OREUFAQ27ZtszmPu7s7xYoVu+191kwmEw0bNmTRokVW5WNiYnj//feZOXMmrVq1AqB///4MHTqU1NRUAgICqFq1Kq1bt7YZqcxMcnIy3t7enC0RjdeerF8zuUulCsKygeCf+87K3W7r/tbD4de/4ei31puMRH8NU1bB6R8ynuaYzi8K6pSDGTeNSJfqCgF5IG5g5u2bvwEi/gfTe0JkaJa6JCIiIveWRtYeU4GBgQQEBLBu3TqSk5PZtWsXderUwdHRkSeffJLVq1dz5MgRDh48SLVq1W5/wtu4OVADqFChAvv372fChAk0bdqUY8eO0a9fP0qWLHnLDTzuxK12ZXzxxRf5+uuvKV26NDExMUycOJGpU6fSrVs3AKtvUO6n1FTbKW4DBw5kx44dDBo0iNKlS7N06VKef/556tat+0DaJHakVXU4fgbmrL+elpgMM9dCs0rWgdreY+afGz1X3bz27HDi9bS4P827SLaucT3t5NmM6x+/FEwm846UIiIiki20Zu0xVrVqVebMmcPEiRNJTU21bCJSu3Zthg8fzo8//ohhGDRo0MBSJjg4GICdO3fanG/jxo0YhkHhwoWz3IacOXMSFRVFVFQUABMnTqRDhw4MGjSIOXPmAOaRqXvpl19+oWzZsixfvtwqfceOHTZ58+XLx5EjR7h69SpOTtf/ON67dy8XL160yZ8Rd3d3zpw5Y5O+d+/eDPMXL16cvn37AnD16lUaNmzI8uXLWbx4MQ0bNsxSnfIIaFXdvCNjhy9hewLk9YTRi+BaGgx83jpv/f7m3wfGXk97/zlzYFe3H3RrAucvw/D5EFIEOtS7nm/ILPOauvCnzPdkO33OfI+2jXvgzcZQosD976uIiIhkSCNrj7GwsDAMw2DYsGHkyZOH8uXLA9CsWTNSU1MZOXIkDg4ONG/e3FKmSJEilC5dmnXr1lntUJiWlsaAAQMA8+YbWZGQkGCTlr4O7sbgxs3NjQsXLtyzdW0ODg42Ux/PnDnDuHHjbPLWr1+fs2fPMnz4cKv0Pn36ZLm+ggULsn37dpKTr+/6d+zYMebNm2eVLzk52SoPmKdhlitXDuCOpoHKI8DREX75ENqEwhcLoPcPkNfLPOWyVMHbly+UF1Z+BMXzw3uTYdg8aFzBvC7uxlG5JhUhfy74bhl0GQdDZoNzDpjQFUa+ct+6JyIiIrenkbXHWEREBG+88QZHjhyxug9Y9erV8fb2JiEhgaCgIKv1YwBffPEFTZs2pUGDBlZb92/evJn69etneX1VrVq18PT0pEqVKhQuXJikpCRmzZqFyWSiXbt2lnyVKlViw4YNtGrVitDQUBwdHWnZsiVFihS5q37Xq1ePn376iTp16lCvXj2OHTvGrFmzMpyq+fHHH7NgwQL69u3Lpk2bKFu2LKtWrSI+Ph5PT88s1RcdHU2vXr2oXLkyrVu3JikpiRkzZpAvXz7Onr0+BW3Tpk00adKEWrVqERwcTO7cudm+fTuzZ8/G19fXKmiWR8CKj26fJ5cHfNvF/JOZG0fUblS2MCzOYBfKGz1T3vwjIiIidkfB2mMsf/78BAYGsm/fPps1UZUqVSIuLo4aNWrYlHvmmWdYsmQJffr0YcaMGVy5cgU/Pz+6detmMwKVmaioKObOncvMmTM5f/48Hh4elCxZkk8//ZTWrVtb8sXExHDgwAHi4uKYN28ehmEQEBBw18HapEmT6Ny5M4sXL2bNmjXkzZuX559/ntDQUKv7sYH5Gv36669ER0fzyy+/8Msvv/DEE0+wdOlSnnnmmSzV17NnTxISEpg0aRIff/wxfn5+dO/eHQcHB6vbAQQFBdGsWTM2bNjAqlWrSE1NJXfu3LRo0YKYmJgMg0kREREReXRpN0iRR4x2g3zA7nY3SBEREZHb0Jo1ERERERERO6RgTURERERExA4pWBMREREREbFDCtZERERERETskII1ERERERERO6RgTURERERExA4pWBMREREREbFDuim2yKOqaF5wdM7uVjz6Av2yuwUiIiLyiFKwJvKo+rITeHpldyseD+4u2d0CEREReQQpWBN5VBXIDV4K1kREREQeVlqzJiIiIiIiYocUrImIiIiIiNghBWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYocUrImIiIiIiNghBWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYocUrImIiIiIiNghBWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYodyZHcDROQ++ec0nE/N7lY8utxdwNs9u1shIiIijzAFayKPqq7j4HBydrfi0RToB+O7KFgTERGR+0rBmsij6kAi7DmZ3a0QERERkbukNWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYocUrImIiIiIiNghBWsiIiIiIiJ2SLtBiojYmzMX4J0fYO5vcPEKVCkJn7aHCsWzVv7vBOjxHazeAc45oElFGBEFvt7X8xw9ba5j4x7zvx0dIMgfujSCdnXAZLofPRMREZE7oGBNHgkhISEcO3aMkye1Vb085NLSoMlg2HoQereAvF4wehHU6QebhkNJ/8zLJyRCrQ/BOycMfRHOX4JPfoK/DsKGj8HZyZwvMRkSTkGr6lA4L1y9BrFbIWoU7DwCQ1+6/30VERGRTClYk1uKiYkhKSmJYcOGZXdTHgrHjx+nb9++NGjQgFatWmV3c8Re1ekLRf1g4psZH5+1DtbuhJm9oFUNc1pkDQjqCv2nw9QemZ9/6Gy4cNkc2BX2NadVKQnPDISJyyG6gTntiaKw4iPrsl0bQ7Oh8MUv8FFbcHS8626KiIjIf6c1a3JLU6dOZcKECdndjCzZsGEDBw8ezNY2nDx5knHjxrFkyZJsbYc85Gatg3w+8Gy162m+3uaAbf4GuHI18/Kz10PTStcDNYCwJ81THGesvX39RX3NUy9TUu+q+SIiInLvKFh7jJw7d46UlJTsbsY9c/XqVZKTkwFwc3MjZ86c2dyi++vUqVPZ3QR5ELbshwrFwOGmj+cqJc1B1K6jty575BScOAuVMljbVqUkbNlnm37pinlK5IET8P1ymLAcqgeBm8t/64eIiIj8ZwrWHqBt27ZhMpno1KmTVXrFihUxmUz07t3bKj0oKIiCBQtapa1atYrQ0FA8PDxwcnIiICCA7t27c/Wq9bft4eHhmEwmDh06RKNGjfD29sbb25tdu3YBMGzYMEqWLEnOnDlxcXHBz8+PsLAwDh06BICvry/x8fEkJiZiMpksP7Nmzcq0jyaTifDwcH788UdKlSqFi4sLPj4+REZGkpSUZJP/5MmTvPzyy+TPnx8nJye8vLyoV68eW7dutcoXExODyWTixx9/pHPnzuTLlw9XV1e++uorwLxmzdfX16pMelp8fDyhoaHkzJkTd3d3wsPDSUpK4tq1a3Tt2hU/Pz+cnJwoVqwYP/30k00b09LS6NevH8WLF8fFxQVXV1eeeOIJZs6cackza9YsQkJCABg3bpzlet3cpi+++ILg4GBcXV1xcXEhKCjI0oeMruP06dMt+evUqZPptZdHxD9JUCCXbXp62tHTmZe9Me/N5U+ftx2ZG7kAfKMg8HXzerVqQTCt5101XURERO4trVl7gMqWLYufnx9r116finTp0iXi4+MxmUysWrXKkp6YmMjevXtp0aKFJS02NpamTZvi6OhImzZtyJ8/P4sXL2bkyJHEx8ezdOlSmzpr165N7ty56dKlCxcuXMDHx4dhw4bx7rvvEhwcTLdu3XBzc+PQoUOsWLGChIQEChcuzJAhQxg4cCDnzp2jX79+lvNVrFjxtv38+++/6dChAy1atCAyMpKVK1cyc+ZMdu7cyebNm3H8dx3MyZMnqVChAidPnqR58+aULVuWo0ePMm3aNJ5++mnWrVtH2bJlrc79/vvvk5qaSps2bfD29uaJJ57ItC1XrlyhXr16VKxYkd69e/P777/zyy+/8Oyzz5IrVy7+/PNP2rVrx9WrV5kwYQIvvPACBw8eJE+ePJZzNGjQgGXLllGrVi3atGnDlStXmDt3Ls8//zxnzpyhU6dOlvMPHz6c0NBQIiIiAPDy8rKcp2PHjkyYMIGKFSvy1ltv4ejoyIIFC+jatSv//PMPgwcPtmr79u3bad++PRERETz//PO3ve5ih66mwtmLtmlXrppHs26U28M8mnYpBVwy+Gh2dTb/vpTJ6Hj6MRenDMo7Xc9z4/G2Nc0jcSeT4eff4fjZzOsQERGRB0bB2gNWuXJlFi1aRHJyMl5eXixatIiUlBTCwsJYvXo1KSkpODs7M3/+fNLS0ggLC7OUfeutt0hNTSU2NpZatWoBMGTIEOrWrUtcXBzTp0+nTZs2VvUVL17cJoj76aefcHV1ZcuWLTg7O2fYzujoaEaNGkVKSgq9evW6oz4eOnSIsWPHEh0dbUmLjIxk5syZjBo1iu7duwPQpUsXjh8/TmxsLLVr17bqZ6VKlejZsyeLFi2yOveVK1fYsWOHVRCUmXPnzvHKK6/w2WefWdJq1qzJypUrKVasGNu2bcPFxTzdq1y5cpZ+DxgwAIAxY8YQFxfHgAED6N+/v+UcMTExBAcH88EHH/DKK68QGBhIu3btGD58OMHBwTbXLC4ujgkTJtC+fXsmTpxodZ4aNWrw6aef0qNHD6sg8fDhw0ydOpW2bdtmqa9ih9bsgLr9bNPX7oRpq63T9o8xbzzi5gxXMlgvdvnfAMot4/es1bGM1rVdvppx+SJ+5h+Atk9D9NcQNgB2jtJUSBERkWymaZAPWP369bl27Zplut3ChQvx8vLinXfe4fLly8TGxgLmUTSTyWQZoTl48CA7duygevXqlkANwMHBgUGDBgEwY8YMm/o++OADmzRPT09SUlKYOHEiaWlp97qL+Pv7WwVqYA5KAObNmweYpxYuXLiQkJAQihcvTkJCguXH29ubMmXK8Ntvv9mc+6WXXspyoAbm6/PRR9Y73lWvXh3DMGjfvr0lUANo1qwZgGWqKMDkyZNxdXUlKirKqo0nTpygfv36nDx5ks2bN9+2Hd9++y0mk4kuXbpYnSchIYEmTZpw+fJlm8C0aNGiCtQeEjeOlgOsX7+ea9euwZNFIbY/B7+N4tycnhDbH54owuVapTk+pbP5cWx/LszrzbZTR8yFC+SCf5Jszrnn19/N//DPbV3Hv7Zv384Zt38/0v9JIiEhwTKtGSDl0HFSvd2sRtVurmPt2rXmrfwPJ8Kq7RnWceN05pvrSE5OJj4+PtNrc8trpTpUh+pQHapDdTyGddyOyTAM445KyH+yf/9+ihUrxksvvcSkSZMsUyOXLl2Kt7c37du356uvviIwMNCSH8xBXePGjenYsSPjx4+3OuelS5dwd3enYsWKbNy4ETCvWVu8eDFnz561CW42b95Mo0aNOHHiBB4eHjz55JM0bNiQN954w2pk527uXWYymahRowZr1qyxOebu7k6BAgXYs2cPBw8epGjRorc9V3owGRMTw/vvv8+ECROIioqyyZtRW0NCQjh69KjNxhzp55o2bZrNSGT6WrGFCxcCEBAQwJEjRzJt59y5c4mIiCA+Pp6QkBA6derEN998Y5WncuXK/P7775me5+OPP+add96xtKNWrVqsXLky0zIZSU5Oxtvbm7MlovHao/vO3RelCsKygZbA6Y7cbuv+1sPh17/h6LfWm4xEfw1TVsHpHzKe5pjOLwrqlIMZN42Il+oKAXkgbmDm7Zu/ASL+B9N7QmRolrokIiIi94emQT5ggYGBBAQEsG7dOpKTk9m1axeRkZE4Ojry5JNPsnr1ao4cOcLBgwdtAom7kdEoVIUKFdi/fz8zZsxg8eLFbNy4kX79+vHZZ5+xbNkyypcv/5/rvZ30IKx8+fKWACUrPDw87qgeh5t31LuB4y3uIXXj9xeGYeDp6cnYsWNveZ5q1ard8tiN5zGZTPzwww+3rLdKlSpWj93c3G57XnkEtapu3r5/zvrr91lLTIaZa6FZJetAbe8x8+/i+a+nPVfdvKvj4UQolNecFveneRfJHs2u5zt51nxLgJuNXwomk3lHShEREclWCtayQdWqVZkzZw4TJ04kNTXVsolI7dq1GT58OD/++COGYdCgQQNLmeDgYAB27txpc76NGzdiGAaFCxfOchty5sxJVFSUZZRq4sSJdOjQgUGDBjFnzhzAPLpzNw4cOGCTtnfvXi5evEhAQAAAhQsXJmfOnFy4cMGup/oVKlSIDRs2EB4eTq5cGeywd4PMrldgYCCbNm2iRIkSWQru5DHWqrp5R8YOX8L2BMjrCaMXwbU0GHjTRjP1/11HeeCGLxPef84c2NXtB92awPnLMHw+hBSBDvWu5xsyy7ymLvwp8z3ZTp8z36Nt4x54szGUKHD/+yoiIiKZ0pq1bBAWFoZhGAwbNow8efJYRrKaNWtGamoqI0eOxMHBgebNm1vKFClShNKlS7Nu3TqrKYZpaWmWzTAiIyOzVH9CQoJNWvo6uDNnzljS3NzcuHDhwh2vazt69KjNNMA+ffoAWAJTR0dHwsPD2b17d4Zb1wPZfpNrgJdffhnDMGxut5AufZoqgI+PD0CGtyh49dVXAejZs6fNbRZuPo885hwd4ZcPoU0ofLEAev8Aeb3M0y5LFbx9+UJ5YeVH5tG29ybDsHnQuIJ5fdyNo3JNKkL+XPDdMugyDobMBuccMKErjHzlvnVPREREsk4ja9kgIiKCN954gyNHjhAeHm5Jr169Ot7e3iQkJBAUFGS1fgzM9+hq2rQpDRo0sNq6f/PmzdSvXz/L0yZr1aqFp6cnVapUoXDhwiQlJTFr1ixMJhPt2rWz5KtUqRIbNmygVatWhIaG4ujoSMuWLSlSpEim5y9cuDBvvfUWcXFxBAUFsXLlSn799VfKlSvHW2+9Zck3ZswYNm/ezJtvvsmsWbOoXLkyLi4uHDhwgJUrVxIcHGyz6caD1qVLF37++Wdmz55NmTJlCAsLw9fXl8OHD7Np0ybLZiMABQsWtDwn7777LgUKFMDT05NXXnmFhg0bEh0dzTfffEPx4sVp3LgxBQsW5OjRo2zdupUNGzaQmprBDoDy6Fnx0e3z5PKAb7uYfzJz4BbTc8sWhsUZ7EJ5o2fKm39ERETEbilYywb58+cnMDCQffv2UbduXatjlSpVIi4ujho1atiUe+aZZ1iyZAl9+vRhxowZXLlyBT8/P7p168bw4cOzXH9UVBRz585l5syZnD9/Hg8PD0qWLMmnn35K69atLfliYmI4cOAAcXFxzJs3D8MwCAgIuG2wVqZMGf73v//Rv39/5s6di5ubG8899xxjx461Wq/l6+vL1q1beffdd1mwYAFr1qzBwcGBPHny8NRTT9Gly23+UH1AFi5cyLBhw/j+++/59ttvSU1NxcfHh1KlSvHhhx9a5Z0wYQI9evTg888/JyUlhbx58/LKK+ZRirFjx1KtWjW+/PJLJk+ezJUrV/Dy8iIwMDDDXTtFRERE5PGm3SDlnjKZTDRs2DDbR8QeZ9oN8gH4L7tBioiIiGSR1qyJiIiIiIjYIQVrIiIiIiIidkjBmoiIiIiIiB3SBiNyT2kJpIiIiIjIvaGRNRERERERETukYE1ERERERMQOKVgTERERERGxQ1qzJvKoKpoXHJ2zuxWPpkC/7G6BiIiIPAYUrIk8qr7sBJ5e2d2KR5e7S3a3QERERB5xCtZEHlUFcoOXgjURERGRh5XWrImIiIiIiNghBWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYocUrImIiIiIiNghBWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYocUrImIiIiIiNghBWsiIiIiIiJ2SMGaiIiIiIiIHVKwJiIiIiIiYodyZHcDROQ++ec0nE/N7lY8nNxdwNs9u1shIiIijzkFayKPqq7j4HBydrfi4RPoB+O7KFgTERGRbKdgTeRRdSAR9pzM7laIiIiIyF3SmjURERERERE7pGBNRERERETEDilYExERERERsUMK1kREREREROyQgjURERERERE7pGBNRERERETEDmnrfhGRB+XMBXjnB5j7G1y8AlVKwqftoULxrJX/OwF6fAerd4BzDmhSEUZEga/39Tw7EuC7ZbDkD9h7DDxcoUIxGPg8VCpxP3olIiIi94lG1kREHoS0NGgyGKb+yv+3d9/xNd1/HMdfV2TJFEmsIKgd1dqjLVp7tVZUB6qaUlraomhKYxZVpdWFWkWJ+WvtUVVbUUXs2dgzQRDk/P64zeW6SSTkyo2+n4/HfST3e77nfMeNI598x6FLfRjWBs7EQI2+sP/E/c+PPgfPhcOBUzD4VejeBBZsgdoREH/zTr5xy2HsMihfGEa0gw+awN4TULkXLN9ut+aJiIhI+lOwJhlqyJAh9OzZM03nhIWF8cMPP9ipRrZ++OEHwsLCHll5kknV+ATafZX88VnrYd1emNgF+rWCzvVhVX9wygL9Ztz/+oNnw9XrsDIC3msIfVrAzA9h+xGY+NudfK2fhX9+gHGdIawO9HgJNg4FP0/4NBXliIiIiMNQsCYZatq0aUyYMCFN54wdO5Y5c+bYqUa25syZw9ixYx9ZefKYmrUecvpCs8p30gJ8ILQqzN8EN24meyoAszdAo/KQP+BOWq0yUDQPzFx3J61cYfB0tz43hxc8W9I8jVJEREQyDQVrkq4uX75MfHx8Rlcj00hISODixYsZXQ15FLYdNq8dy3LPbbdiEfP6tX0pTIU8ft48ZbJ8EmvbKhaBbYfuX/6pi+DvnbY6i4iISIZSsPaY2bVrFyaTibfeessqvVy5cphMJnr06GGVXrRoUfLmzWuVtnr1aqpVq4anpyfOzs4EBQXRrVs3bt60/st/vXr1MJlMHDt2jPr16+Pj44OPjw/79u0DYNiwYRQpUoRs2bLh6upKYGAgtWrV4tixYwAEBASwc+dOzp07h8lksrxmzZqVZNt27tyJyWQCYMmSJVbn3G369OmULVuWbNmy4ezsTIECBejXr59Vnho1apAlSxabsn766SeyZMlCnTp1AChdujRLliwBsCpvyJAhluMBAQHcK7Gud0+fnDVrluXc8PBwgoKCcHV15aOPPrLkGT16NCVLlsTNzQ1XV1eKFi3KmDFjkuwPyWROXoTc2W3TE9NOXEj53Lvz3nv+hSspj8z9EQXr90Graqmvr4iIiGQ47Qb5mClVqhSBgYGsW3dnWtS1a9cswcPq1ast6efOnePgwYO8+OKLlrRly5bRqFEjnJycaNWqFbly5WLJkiWMGjWKnTt3snz5cpsyq1evjp+fH507d+bq1av4+voybNgwPvroI0qWLEnXrl1xd3fn2LFjrFq1iujoaPLnz8+gQYOIiIjg8uXL9O3b13K9cuXKJdm2oKAghg8fTo8ePShZsiRvvPGGTZ6IiAgiIiIoWrQob7/9Np6enqxcuZL+/ftz4MABpk6dCkBkZCSlSpUiLCyMypUrExQUxKFDh+jcuTM5c+Zkxgzz2p7evXszaNAgoqKiGD58uKWc2rVrp/YjsfHDDz8QGxtLy5YtyZ07N8HBwQC0b9+eCRMmUK5cOd577z2cnJxYsGABXbp04eTJkwwcOPCBy5R0dvMWxMTZpt24CedirdP9PM2jadfiwTWJW66bi/nrtRRGpBOPuToncb7znTxJHT9zCV4ZCQUDoedLyZchIiIiDkfB2mOoQoUKLF68mNjYWLy9vVm8eDHx8fHUqlWLNWvWEB8fj4uLC/PnzychIYFatWpZzn3vvfe4desWy5Yt47nnngNg0KBB1KxZkxUrVjBjxgxatWplVV7hwoVtgrj//e9/uLm5sW3bNlxcXJKsZ1hYGF999RXx8fF07979vu3y9fWle/fu9OjRg3z58tmcc/DgQQYOHEiNGjVYuXKlJX3AgAGEhoYyffp0evbsSZkyZQgICGDSpEk0btyY5s2bs27dOpo3b05cXBxz5swhe3bzCMYrr7zC5MmTiYqKSlUdU+Ps2bPs2rWLAgUKWNJWrFjBhAkTaNu2LRMnTrSkDxkyhKpVqzJixAjef/99cuTIkS51kIe0dg/U7Gubvm4v/LzGOu3wdxAcCO4ucOOW7TnX/w3E3JP+d2J1LKnRs+s3kz//6nVoNBguX4M1g2zXsomIiIhD0zTIx9ALL7zA7du3+d///gfAokWL8Pb2pmfPnly/fp1ly5YB5lE0k8nESy+9BMDRo0fZs2cPVapUsQRqAFmyZKF///4AzJw506a8jz/+2CbNy8uL+Ph4Jk6cSEJCQno3MUnjxo3j1q1bvP3220RHR1u9mjZtimEYzJs3z5K/fv36dOnShU2bNlG6dGn++usvunXrxgsvvGDXejZo0MAqUEusu8lkonPnzjZ1b9iwIdevX2fx4sV2rZfccev2bcv3sbGx7Ny50+r4xutnYFk/y2vXly3hyQJQ5ylY1o+oUaHcXvyJ+XguX6Kiorid09synTE6OtoyHTgxbf9V62mQd4+OW6Y/nryzvnHDhg3cvn3bnObnSdTB/VbrH6MPHeFagwj4+yjM701s/uw27bAqI4n3ljL+FRUVZV3G3e1Ipq9UhspQGSpDZagMlZH8+/sxGYZhpOkMcXiHDx+mUKFCvPbaa0yZMsUyNXL58uX4+PjQtm1bxowZQ8GCBS35wRzUNWjQgPbt2zN+/Hira167dg0PDw/KlSvH5s2bAfOatSVLlhATE4O3t/XGBVu3bqV+/fqcOXMGT09PypQpQ926dXnnnXesRodKly7NqVOnOHv2bKrbZzKZqFu3rk3w0rRpU6tgLCkdO3bk22+/tbxPSEigdOnSREVFUbZsWTZv3kyWezaASGxnUv9Ukqv/zp07KV26NG+99ZblMQOzZs2iZcuWhIeHM2DAAKv8FSpU4M8//0yx7kOHDk3VYw5iY2Px8fEh5okwvA+kvl/lX8XymrfHz+OXtvNqfGIeQZv4btLHWw6HP3bDiXHWm4yEfQtTV8OFyUlPY0wU2A5qhMDMe0Z4i3WBoBywIuJOWkKCeerjrPXm/HfvQCkiIiKZhqZBPoYKFixIUFAQ69evJzY2ln379hEaGoqTkxNlypRhzZo1HD9+nKNHj9pMaXwQ9wZqAGXLluXw4cPMnDmTJUuWsHnzZvr27cvIkSNZuXIlTz311EOXe6/EYGro0KHky5cvyTwlS5a0er9z505LsBodHc3FixfTNNXw3s1NEt27GcvdsmXLZpNmGAYmk4nJkyfj5OSU5HkVK1ZMdb3EAbWoYg6e5myAFlXNaediIXIdNC5vHagdPGX+WjjXnbTmVWDSb/DPOcjnb05b8bd5F8n3G1uX9e44mLEWvu+oQE1ERCQTU7D2mKpUqRJz5sxh4sSJ3Lp1y7KJSPXq1Rk+fDjTp0/HMAzLrodwJ5DZu3evzfU2b96MYRjkz58/1XXIli0b7dq1o127dgBMnDiRN954g/79+1uek5ZcsPMgnnjiCQBy5sxJ69at75s/Pj6eli1bkpCQQK9evRg6dCitWrWyWX+XUh29vb3Zv3+/TXpUVFSa6l6wYEG2bNnCE088QeXK+uX6sdSiClQuCm98DVHR4O8F3yyG2wkQ8bJ13hf+3b30yPd30vo0Nwd2NftC14Zw5ToMnw+lC8Abz9/J9+Uv5utWKQbZXOGn362v3bQSeLjZp40iIiKSrrRm7TFVq1YtDMNg2LBh5MiRwzKS1bhxY27dusWoUaPIkiULTZo0sZxToEABihcvzvr161m7dq0lPSEhgU8//RSA0NDQVJUfHW378N3EdXCXLl2ypLm7u3P16tU0rWtzdXW1ukait956i6xZszJw4EAuX75sc/zs2bPExd3Zwa9Dhw7s27ePfv36MWTIEFq3bs2KFSsYOnSo1XkeHh4AnDhh+xyswoUL26wnu337NiNHjkx1exLrAvDhhx8mOSqXOPonmZiTEywMN2+fP3oB9Jhsfu7Zygjz1Mv7yecPvw8wj7b1+gmGzYMGZc3r4u4elfvriPnr+r3w+ijb19nYpK4uIiIiDkhr1h5Tp06dIk+ePBiGQb169Vi0aJHlmK+vLzExMRQtWtRmFC1x6/6sWbNabd2/detWXnjhBatRp5TWchUqVAgvLy8qVqxI/vz5uXjxIrNmzSI6Opoff/zRMtrWuXNnvvnmG5o2bUq1atVwcnKiadOmNhtw3O3pp58mKiqKjh07EhwcjMlkolu3bgAMHjyY8PBwcuTIQZMmTQgODubMmTPs2rWLtWvXsmXLFkJCQpg2bRqvvfYazz//vKVNN27cICQkhH/++Yd169ZRtmxZAEaMGEH37t2pUaMG9evXx8XFheeff54nn3ySv//+m7Jly+Lt7U2bNm1wcXHh119/5fbt2+zbty/JNWuDBw+md+/eNu16++23+eGHH8iXLx8NGjQgb968nDhxgu3bt7Np0yZu3UpiJ8EkaM3aQ3rQNWsiIiIi6UzTIB9TuXLlomDBghw6dIiaNWtaHStfvjwrVqygatWqNufVrl2bpUuX0rt3b2bOnMmNGzcIDAyka9euVs8Zu5927doxd+5cIiMjuXLlCp6enhQpUoQRI0bQsmVLS74hQ4Zw5MgRVqxYwbx58zAMg6CgoBSDtfHjx9OhQwd++OEHrl+/DmAJ1vr06UNISAhDhw4lMjKSuLg4vLy8yJcvH126dCE4OJijR4/yzjvvEBgYaHmeGphH7CIjI6lSpQqhoaHs2LEDd3d3unXrxpYtW1i8eDG///47hmEwePBgnnzySZ588knGjRtHREQEY8aMwdPTk0aNGvHee++leY3Z999/T+XKlfn666/56aefuHHjBt7e3hQsWDDJHTdFRERE5PGmkTWRx4xG1h6SRtZERETEQWjNmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiIiIiDkjBmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4ID0UW+RxFewPTi4ZXYvMp2BgRtdAREREBFCwJvL4+vot8PLO6FpkTh6uGV0DEREREQVrIo+t3H7grWBNREREJLPSmjUREREREREHpGBNRERERETEASlYExERERERcUAK1kRERERERByQgjUREREREREHpGBNRERERETEASlYExERERERcUAK1kRERERERByQgjUREREREREHpGBNRERERETEASlYExERERERcUAK1kRERERERBxQ1oyugIjYyckLcOVWRtfCfjxcwccjo2shIiIiYjcK1kQeV13Gwj+xGV0L+ygYCOM7K1gTERGRx5qCNZHH1ZFzcOBsRtdCRERERB6Q1qyJiIiIiIg4IAVrIiIiIiIiDkjBmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiIiIiDkhb94uI3OvSVeg5GeZuhLgbULEIjGgLZQun7vzd0fD+j7BmD7hkhYbl4It2EOBzJ8+eaPhxJSz9Cw6eAk83KFsIIl6G8k/Yo1UiIiKSyWhkTUTkbgkJ0HAgTPsDutSHYW3gTAzU6Av7T9z//Ohz8Fw4HDgFg1+F7k1gwRaoHQHxN+/kG7ccxi6D8oVhRDv4oAnsPQGVe8Hy7XZrnoiIiGQeGlkTG0OGDOHixYsMGzYso6uS6fTs2ZPs2bPTu3fvjK6KJKfGJxAcCBPfTfr4rPWwbi9EdocWVc1poVWhaBfoNwOmvZ/y9QfPhqvXYctwyB9gTqtYxBysTfwNwuqY01o/C5+2Ak/3O+e2fwFKvAufzoBaZR6unSIiIpLpaWRNbEybNo0JEyZkdDUypQkTJjBt2rSMroY8jFnrIacvNKt8Jy3Axxywzd8EN24meyoAszdAo/J3AjUwB15F88DMdXfSyhW2DtQAcnjBsyXN0yhFRETkP0/B2n/A5cuXiY+Pz+hqSBLOnz+f0VWQe207bF47luWe22PFIub1a/tSmAp5/Lx5ymT5JNa2VSwC2w7dv/xTF8HfO211FhERkceSgrVHYNeuXZhMJt566y2r9HLlymEymejRo4dVetGiRcmbN69V2urVq6lWrRqenp44OzsTFBREt27duHnT+q/89erVw2QycezYMerXr4+Pjw8+Pj7s27cPgGHDhlGkSBGyZcuGq6srgYGB1KpVi2PHjgEQEBDAzp07OXfuHCaTyfKaNWtWim2cMGECISEheHl54eLigr+/P8888wx//vknAKGhoZhMJrZu3Wpz7sGDB3FycqJ+/fqWNJPJRL169Zg5cybFihXD1dUVPz8/unbtCsCpU6do2LAh3t7euLq6UqlSJQ4cOGB13bCwMEwmE+vXryc0NBRfX19cXV0pU6YMmzdvBuDbb7+lUKFCuLi4EBAQQERERJLtmz59OmXLliVbtmw4OztToEAB+vXrZ5XHZDJx7tw5du7cadV3O3futPRt6dKlWblyJeXKlSNbtmyUKFGC7777DpPJRP/+/ZMsO1++fOTKlYuEhIQUPwNJJycvQu7stumJaScupHzu3XnvPf/ClZRH5v6IgvX7oFW11NdXREREHltas/YIlCpVisDAQNatuzMF6tq1a5Zf6levXm1JP3fuHAcPHuTFF1+0pC1btoxGjRrh5OREq1atyJUrF0uWLGHUqFHs3LmT5cuX25RZvXp1/Pz86Ny5M1evXsXX15dhw4bx0UcfUbJkSbp27Yq7uzvHjh1j1apVREdHkz9/fgYNGkRERASXL1+mb9++luuVK1cu2fbNnj2bN998k/z58xMWFkb27Nk5fvw4f/zxBzt37qR8+fJ07dqVyMhIRo0axaRJk6zOHzVqFAkJCbzzzjtW6Xv27KF9+/Y0b96cVq1aMW/ePEaPHo2bmxuRkZHkyZOHrl27sn//fiIjI2nRogV//fWXTf1ef/11smXLRqdOnTh79ixTpkyhQYMG9OjRg8GDB/Pyyy/j5+fH9OnT+fTTT3nqqaes+j8iIoKIiAiKFi3K22+/jaenJytXrqR///4cOHCAqVOnAjB8+HD69++Pl5cX779/Z11TUFCQ5fvTp0/TuHFjnn/+eZo0acLly5dp3749vXr1YurUqVZ9DrBw4UKio6Pp3LkzWe4d6ZH7u3kLYuJs027chHOx1ul+nubRtGvx4JrErdHNxfz1Wgqj1InHXJ2TON/5Tp6kjp+5BK+MhIKB0POl5MsQERGR/w5DHomGDRsaTk5ORkxMjGEYhjFnzhwDMGrVqmW4ubkZN27cMAzDMMaNG2cAxpgxYyznFi9e3MiSJYvx+++/W9Ju375tPPfccwZg/Pzzz5b0unXrGoDxwgsv2NShWrVqVmUlJyQkxPD3909121q1amUAxpEjR1LMV6xYMcPX19eIj4+3Ss+VK5eRN29eqzTAMJlMxsKFCy1pcXFxho+Pj2EymYwWLVokWYdNmzZZ0t566y0DMCpWrGjcvn3bkt6rVy8DMNzc3Izdu3db0o8ePWpkzZrVqFmzpiXtwIEDNmmJWrZsaZhMJuOvv/6ypPn7+xshISFJtt/f398AjP79+9sca9u2rQEY69ats0pv2LChkSVLFmP//v1JXjMpMTExBmDEPBFmGDR9PF/FuhjG8fP374zfdqT+modPm8/xaG0Y7b+2vdaCP835Fm9NvrzN+815Jv9me6zHJPOx6/G2x65cM4wKPQzD51XD2JHyvyMRERH579Cf6h+RF154gdu3b/O///0PgEWLFuHt7U3Pnj25fv06y5YtA8yjaCaTiZdeegmAo0ePsmfPHqpUqcJzzz1nuV6WLFks0+ZmzpxpU97HH39sk+bl5UV8fDwTJ05M1yl1Pj7mZ0eNHz8+xbVxbdu25dKlS0yePNmSNnfuXE6dOkWrVq1s8hcrVsxqaqS7uzslSpTAMAz69OljlbdGjRoA7Nixw+Y6Xbt2tRqVql27NgDVqlWjePHilvT8+fOTN29ey5RQgHHjxnHr1i3efvttoqOjrV5NmzbFMAzmzZuXbJvv5eHhQa9evWzSP/jgA0wmE6NHj7akXbp0iRUrVlC+fHmeeELP3UrKlStXLNNME909gk2ZYHZ92RKW9bO8rj4RgFG7jOX90XHtuDznQ8jlC8DNAC+uHbqzLi02NtZcRuIUxzx+1mXcXea/0x+PbtzO7du3LcejoqK4cfSUefTO1Zno6Og7P2fxN7nVZDAJ24/A/N4QUsC2HUm837Bhg00ZFy9etLy3KuPudqRwTZWhMlSGylAZKkNlPNoy7sdkGIaRpjPkgRw+fJhChQrx2muvMWXKFMvUyOXLl+Pj40Pbtm0ZM2YMBQsWtOQHc1DXoEED2rdvz/jx462uee3aNTw8PChXrpxlDVa9evVYsmQJMTExeHtbb1KwdetW6tevz5kzZ/D09KRMmTLUrVuXd955hxw5cljylS5dmlOnTnH27NlUte348eM8++yzHD58GDc3N0JCQqhVqxadOnUif/78lnyXL18mZ86cPPXUU5Yf1Lp167Jy5UoOHjxolddkMlGrVi1LEJsosX3x8fE4O9+ZSjZr1ixatmzJZ599xkcffQSY16yNHTuWbdu28dRTT1ny7ty5k9KlSyfZp6VLl+b06dOcOXMGgKZNm943GOvYsSPffvstYF6XlitXriSDxoCAAHx9fdm/f3+S1ylbtiwHDhzg7NmzuLq6MnjwYD7++GO+//57wsLCUqzD3WJjY/Hx8SHmiTC8D6TuM8x0iuWFlRGQxy/t595v6/6Ww+GP3XBinPUmI2HfwtTVcGFy0tMYEwW2gxohMLP7PXXuAkE5YMVd6yITEsxTH2etN+e/ewdKERER+c/TyNojUrBgQYKCgli/fj2xsbHs27ePGjVq4OTkRJkyZVizZg3Hjx/n6NGjVK788L+w3RuogTkYOHz4MBMmTKBRo0acOnWKvn37UqRIkSTXeqVW3rx52bt3L5GRkbz88svExcUxdOhQSpQowYIFCyz5vLy8qF+/Phs3buTw4cOcO3eOVatWUaVKFatALZGTk1OyZd4dqN0tqRHDrFmTXpqZ3PXv/vtF4vdDhw5l2rRpSb46duyYbD3v5ebmluyxN998k8uXL1sCyJ9++gkfHx/atWuX6utLOmhRBU5fgjkb7qSdi4XIddC4vHWgdvCU+XW35lXg1z/hn3N30lb8bd5FsmVV67zvjoMZa+GbMAVqIiIiYkMbjDxClSpVYs6cOUycOJFbt25ZNrGoXr06w4cPZ/r06RiGQZ06dSznlCxZEoC9e/faXG/z5s0YhpFkoJOcbNmy0a5dO0sAMHHiRN544w369+/PnDlzAPOoVlo5OzvTokULWrRoAZh3r6xZsyYRERE0bNjQkq9r167MmTOHUaNG4evrS3x8vM0umY4kcfphzpw5ad269X3zP0jfJerQoQN9+vRhwoQJVKhQgd27d/P666/j4uLywNeUB9CiClQuCm98DVHR4O8F3yyG2wkQ8bJ13hf+3RH0yPd30vo0Nwd2NftC14Zw5ToMnw+lC8Abz9/J9+Uv5utWKQbZXOGn362v3bQSeCQf3IuIiMjjTyNrj1CtWrUwDINhw4aRI0cOy9S8xo0bc+vWLUaNGkWWLFlo0qSJ5ZwCBQpQvHhx1q9fz9q1ay3pCQkJfPrpp4B5W/zUiI62fdBu4jq4S5cuWdLc3d25evVqqte1JXXdChUq4OLiQkxMjE15RYoUITIykqlTp5IjRw5eeeWVVJWTEd566y2yZs3KwIEDuXz5ss3xs2fPEhd3Z7dBNzc3YmNjbfKlhqurK02aNGHLli2WqZzdunV7oGvJQ3BygoXh5u3zRy+AHpPNzz1bGWGefnk/+fzh9wFQOBf0+gmGzYMGZc1r5O4elfvriPnr+r3w+ijb19kH+zkSERGRx4dG1h6hl156iXfeeYfjx49Tr149S3qVKlXw8fEhOjqaokWLWq0fAxg9ejSNGjWiTp06Vlv3b926lRdeeCHJzTmS8txzz+Hl5UXFihXJnz8/Fy9eZNasWZhMJtq0aWPJV758eTZt2kSLFi2oVq0aTk5ONG3alAIFCiR53VatWnH69GmeffZZgoODiYuLY/78+Vy/fj3JurVp04ZPPvkEMAdDKU13zGjFihUjIiKC8PBwChUqRJMmTQgODubMmTPs2rWLtWvXsmXLFkJCQgB48sknWbhwIW+++SalSpUiS5YstGvXDl9f31SV98EHHzB16lR+++03QkJCKFu2rB1b9x+1asD982T3hHGdza+U3D2idrdS+WFJ36SPJZr4bvLr5kRERERQsPZI5cqVi4IFC3Lo0CFq1qxpdax8+fKsWLGCqlWr2pxXu3Ztli5dSu/evZk5cyY3btwgMDCQrl27Mnz48FSX365dO+bOnUtkZCRXrlzB09OTIkWKMGLECFq2bGnJN2TIEI4cOcKKFSuYN28ehmEQFBSUbLD22muvMWnSJObPn8/ly5dxd3cnf/78jBkzxubZaQBdunRh8ODBXL9+3fKQa0fWp08fQkJCGDp0KJGRkcTFxeHl5UW+fPno0qULwcHBlrxjxozh1VdfZcaMGcTFxWEYBrVq1Up1sPb0009TunRp/v77b15//XX7NEhEREREMgXtBimPXFxcHIGBgRQrVowtW7ZkdHUcToUKFYiKiuLUqVN4eXml+XztBikiIiLyeNCaNXnkRo4cydWrV3nzzTczuioOZ9u2bWzZsoX69es/UKAmIiIiIo8PTYOUR2b8+PEcPHiQr776iqCgIIfeBfJRW7RoEX/99Rdjx44la9asls1jREREROS/S8GaPDK9evXi4sWLFC5cmAkTJiT7rLT/olGjRrF06VICAwMZNWqUZcMSEREREfnvUrAmj8zZs4/p+ql0sHjx4oyugoiIiIg4GK1ZExERERERcUAK1kRERERERByQgjUREREREREHpDVrIo+rYH9wcsnoWthHwcCMroGIiIiI3SlYE3lcff0WeHlndC3sx8M1o2sgIiIiYlcK1kQeV7n9wPsxDtZEREREHnNasyYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiIiIiDkjBmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiIiIiDkjBmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiIiIiDkjBmoiIiIiIiAPKmtEVEBE7OXkBrtzK6Fo8PA9X8PHI6FqIiIiIPHIK1kQeV13Gwj+xGV2Lh1MwEMZ3VrAmIiIi/0kK1kQeV0fOwYGzGV0LEREREXlAWrMmIiIiIiLigBSsiYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOCAFayLy33XpKoR9CwHtwKM11OwLWw+m/vzd0VCvP3i+An5t4PVRcDbGNt+gWdBkMOR8A0zN4NOf060JIiIi8vhSsCbyAIYMGYLJZGLWrFkppokDS0iAhgNh2h/QpT4MawNnYqBGX9h/4v7nR5+D58LhwCkY/Cp0bwILtkDtCIi/aZ03fBpsPgBPF7RPW0REROSxpIdii8jjqcYnEBwIE99N+vis9bBuL0R2hxZVzWmhVaFoF+g3A6a9n/L1B8+Gq9dhy3DIH2BOq1jEHKxN/A3C6tzJe/g7c13OxZpH8URERERSQSNrIumke/fuXL58maZNm2Z0VSQ1Zq2HnL7QrPKdtAAfc8A2fxPcuJnsqQDM3gCNyt8J1ABqlYGieWDmOuu8wYHpVm0RERH571CwJv8JN27c4MqVK3Ytw9nZGU9PT5ycnOxajqSTbYehbCHIcs9tsGIRiLsB+1KYCnn8vHnKZPnCtscqFoFth9K3riIiIvKfpGDtPyZxXdWMGTPo2LEj/v7+uLi4ULRoURYuXAjA7NmzKVmyJK6urvj6+tKpU6ckr7Vs2TKqVauGl5cXzs7O5MmTh86dOxMfH2+Vb/HixdSrV4/cuXPj6uqKm5sbJUqU4LvvvrO5Zr169TCZTJw9e5aXXnoJb29vnJ2dKVGiBIsWLUpVG8PCwjCZTKxbt46XX34ZPz8/3N3dWbx4MQCjR4+mcuXK+Pv74+zsjJeXF1WrVmX16tVJXq9///7kzZsXZ2dncuXKRc+ePTEMI9m+vXvNWmJddu7caZM/ICCA0qVLW6VNmDCBkJAQvLy8cHFxwd/fn2eeeYY///wzVW2XNDh5EXJnt01PTDtxIeVz78577/kXrtx/ZE5ERETkPrRm7T/q448/JiEhgXbt2hEfH8/EiRNp3rw5o0aN4oMPPqB58+a0aNGCefPm8d1331G4cGG6d+9uOX/ChAmEhYWRK1cu2rVrR44cOdiwYQPffvstO3bssAp8pk+fzuHDh6lfvz7BwcGcO3eO2bNn06lTJ+Li4vjggw9s6vfMM8/g6+tLly5dOH/+PFOmTCE0NJQjR46QI0eOVLXx1VdfxcXFhTfffBOTyUSBAgUA+P777/Hx8SE0NJTcuXNz4MABZs+eTZ06dVi3bh1ly5a1XKNnz54MHz6c4OBg3nvvPeLi4hg3bhy+vr4P2PPJmz17Nm+++Sb58+cnLCyM7Nmzc/z4cf744w927txJ+fLl073Mx8bNWxATZ5t246Z5ndjd/DzNo2nX4sE1iVugm4v567V422OJEo+5OidxvvOdPEkdFxEREUklBWv/UQkJCezatQt3d3cASpcuTVhYGJ06dWLx4sXUrl0bgN69e5M7d27Gjh1rCdauXLnC+++/T9GiRdm2bRsuLi6W6/bo0YPPP/+cWbNm0aJFCwBGjRplE9wMHDiQ4sWL88UXXyQZrJUsWZK5c+da3pcuXZp3332Xr776ik8//TRVbfT09GTLli1W9QNYu3atTX06derEs88+y4ABAyzlnj59mlGjRpE3b162b9+Ot7c3AN26daNMmTKpqkNaREZGYhgGv//+uyWwlFRau8e87f691u2Fn9dYpyVu9uHuAjdu2Z5z/d9AzN3F9liixGNJjZ5dv3n/80VERERSQdMg/6PatWtnCdQAGjduDECxYsUsgRqAu7s7JUqU4MSJO+t3ZsyYQUxMDK+++ipnzpwhOjra8goNDQXg119/teS/OzCKjY3l+PHjxMbGUrFiRY4fP865c+ds6vfJJ59YvU/ctGPfvn2pbuO7775rE6jdXZ+EhATOnTtHdHQ0QUFB5MmTh7///tuqnfHx8bRr184SqIG5j+rUqXPvZR+aj48PAOPHj7eZSvpflpCQYPk+OjqaY8eOWd7Hxsaap5iWCYZl/WBZP3Z92dL8/ZMFoM5Td97/+9p4dB+3b982T1c8eZGoqCguXrxoueaFqH/Xm+Xxsy7jLn8e//dZbP9Oh1y37q4NRU5e5Ka3G7ez3rm93ltGbGxs0u24i9U1k3i/YcMGczuSKSPZvlIZKkNlqAyVoTJUhsOUcT8mI6nFN/LYGjJkCH369OHnn3+mVatWVsdMJhO1atVi2bJlVun16tVjyZIllnVa3bp1Y9SoUSmW06BBAxYsWADA0aNH6dKlC6tXryY2NtYmb1RUFCVKlLAqKz4+Hmdn6ylkJpOJevXq3XftWlhYGGPHjmXdunVUqVLF5vjKlSvp3bs327dv58aNG1bHAgICOHPmDADvvfceX331VZJ99dFHHzFs2DAiIyMtI4iJfXt3WmJdduzYQUhIiE1ZuXLlYseOHQAcP36cZ599lsOHD+Pm5kZISAi1atWiU6dO5M+fP8U23y02NhYfHx9ingjD+8DZVJ/nkIrlhZURlsApTe63dX/L4fDHbjgxznqTkbBvYepquDA55WmMge2gRgjM7G6dXqwLBOWAFRG25yRu3d8vFD59Oa0tEhERkf8YTYP8j0pux8LU7GSYGLS9//77VKhQIck8wcHBgHlUpEaNGkRHR9OqVSsqVqyIn58fTk5OjB8/nhUrVlj9xSLRvYHavWWnhpeXl03a7t27adCgAdmyZePtt9+mVKlSeHp6YjKZ+Oijj7h27Vqqr58aJpMp2WP3tjtv3rzs3buX+fPns2DBAjZt2sTQoUMZPXo0M2fOpGHDhulat/+8FlXM2/fP2XDnOWvnYiFyHTQubx2oHTxl/lo415205lVg0m/wzznI529OW/G3eRfJ9xs/mjaIiIjIY03BmqRZ8eLFAfOasNatW6eY948//uDIkSN06NCBsWPHWh374Ycf7FbH5EycOJEbN24wZcoUWrZsaXWsU6dOVkHiE088AcCOHTtsRtZ2796dqvL8/MwjQqdPn7YaWbty5QqXLl0ib968VvmdnZ1p0aKFZWRu9erV1KxZk4iICAVr6a1FFahcFN74GqKiwd8LvlkMtxMg4p5Rrxf6mb8e+f5OWp/m5sCuZl/o2hCuXIfh86F0AXjjeevzp6yCo2fNjwQAWB0FAyPN379eHQroOWwiIiJiS2vWJM1at26Nt7c333zzjdVatkSXL1/m/PnzAGTNav57wL0jYmvXrmXNmjU259pb4sjhvfXp378/MTExVmmhoaG4uLgwceJEq+mbe/fuZenSpakqr1SpUgD88ssvVum9e/e2qUN0dLTN+RUqVMDFxcWmbpIOnJxgYTi0qgajF0CPyeDvbZ52WSzv/c/P5w+/DzCPtvX6CYbNgwZlzWvj7p0+OX4FfDIdhswxv/9tp/n9J9Ph8Jl0b5qIiIg8HjSyJmnm6+vLmDFjaN++PcWLF+fFF1+kSJEiXLx4kX379rFq1SomTZpEixYtqFixIvny5WPSpEnExcVRvHhx9u7dy5w5cyhQoAAHDx58pHUPDQ1lxIgRdOzYkT/++AM/Pz/WrVvH+vXryZkzp9XUxFy5ctGlSxe++OILypQpQ/PmzYmLi+Pnn38mT548HD58+L7ltWrVio8++ogxY8Zw/vx5ChUqxNq1a9m5c6fNNM1WrVpx+vRpnn32WYKDg4mLi2P+/Plcv37dZmRPUmHVgPvnye4J4zqbXym5e0TtbqXyw5IkdqF8kLqIiIiI3EPBmjyQ1157jYIFC9KvXz8WLFhAbGwsHh4e5M6dmzZt2lC1qnkNkLOzM4sWLaJTp078+uuvzJ49m/z58zNy5Ei2bt36yIO1p556ip9//pmPP/6YsWPHkiVLFkJCQliyZAkdO3bk1KlTVvlHjBiBl5cXP/zwA6NGjSJHjhx06NABX19fPv744/uW5+zszPz583n77beZOXMmTk5OVKhQgT/++MPSR4lee+01Jk2axPz587l8+TLu7u7kz5+fMWPG8M4776RrP4iIiIiI49NukCKPGe0GKSIiIvJ40Jo1ERERERERB6RgTURERERExAEpWBMREREREXFACtZEREREREQckII1ERERERERB6RgTURERERExAEpWBMREREREXFAeii2yOMq2B+cXDK6Fg+nYGBG10BEREQkwyhYE3lcff0WeHlndC0enodrRtdAREREJEMoWBN5XOX2A+/HIFgTERER+Y/SmjUREREREREHpGBNRERERETEASlYExERERERcUAK1kRERERERByQgjUREREREREHpGBNRERERETEASlYExERERERcUAK1kRERERERByQgjUREREREREHpGBNRERERETEASlYExERERERcUAK1kRERERERBxQ1oyugIjYyckLcOVWRtdCREREJG08XMHHI6Nr4RAUrIk8rrqMhX9iM7oWIiIiIqlXMBDGd1aw9i8FayKPqyPn4MDZjK6FiIiIiDwgrVkTERERERFxQArWREREREREHJCCNREREREREQekYE1ERERERMQBKVgTERERERFxQArWREREREREHJC27hcRERERkcffpavQczLM3QhxN6BiERjRFsoWvv+5m/bDxJWwcT/8fRRu3QZjTvL5T1+CvtPh1y1w/jLk8oUXnjQ/Qy4NNLKWhL///puqVavi7e2NyWSiXr16GV0luyhdujQBAQEZXQ2L27dvExYWRmBgIE5OTphMpoyukoiIiIg8DhISoOFAmPYHdKkPw9rAmRio0Rf2n7j/+Qu3wLgVYDJBoZwp5/3nHFToCYu2Qcc68E0YdKgFZ2PSXO00B2vbt2+ncePG5M2bF1dXVzw8PMibNy9169YlMjIyzRVwRK+88grbt2+nQ4cODB8+nHfffTfZvH/++ScdOnSgWLFieHt74+bmRsGCBencuTOXLl2yyb948WJatmxJiRIlcHNzw2QyMWTIELu1ZciQIfTs2dNu109PQ4cOZezYsVSoUIHBgwczfPhwu5Y3a9YswsLCOH36tF3LERERERE7q/EJtPsq+eOz1sO6vTCxC/RrBZ3rw6r+4JQF+s24//U71YOYKfDncKhdJuW8b38HWZ1g2wj4JBTavwDhLeF/fdLWJtI4DXLZsmU0atQIJycnGjZsSKlSpYiLi+PAgQOsX7+en3/+mZYtW6a5Eo4kLi6OqKgomjdvzhdffHHf/KNHj2bmzJk888wzNGvWDBcXF37//Xe++eYbFixYwI4dO/Dy8rLknzNnDrNnzyZv3rwULFiQPXv22LM5TJs2jVOnTjFs2DC7lpMeli9fjru7O7/88gtZsth/0Hfp0qWMHTuW9957j5w57/MXEhERERHJvGath5y+0KzynbQAHwitCj+thhs3wdU5+fNz+qaunD3RsGireTQthxdcjzcHhM4PtvosTWeFh4cTHx/PqlWrqF69us3xQ4cOPVAlHMnRo0cxDIPs2bOnKv/rr7/OiBEjbKYTtm/fngkTJjBkyBAGDx5sSe/duzfDhg3D19eXMWPG0KVLl3Stv6NKSEggJiYmxX49f/48Hh4ejyRQexTOnz9Pjhw5MroaIiIiIrLtMJQtBPf+nlmxCPywDPadgNIFHr6c5X+bv+b0hRf6wcod5mCtdhn49m0IDkzT5dL0W3F0dDSenp5JBmoAhQoVsny/c+dOTCYTYWFhNvnCwsIwmUzs3LnTklavXj1MJhPHjx+nXr16eHl54ebmRtWqVS1BYEREBHnz5sXZ2Zm8efPyww8/pKnuzZo1I0eOHGTNmpUcOXLQrFkzjh8/blWHkiVLAjB27FhMJhMmk4lZs2Yle93atWsnue6rffv2AOzatcsqvWDBgvj6+qa63smZO3cuTz/9NNmyZcPFxYVChQoxcOBAqzwBAQHs3LmTc+fOWdqSVHsOHDjA888/j4eHB66urpQrV44///zTpsy4uDi6dOlCvnz5cHZ2Jlu2bFSqVImVK1da5Zs1a5Zlemd4eDhBQUG4urry0UcfJdmWxPx///23VV3vXiu4detWateuja+vL1mzZiUgIIBXX33VZqrppk2baNq0Kfny5cPNzQ1XV1cKFy7MgAEDrPLVq1ePsWPHAua1e4llJv68Jv48JuXeut39sz569GgKFy6Mi4sLr776qiXP9OnTKVu2LNmyZcPZ2ZkCBQrQr18/m2v/8ssvlC9fHl9fX5ydnfHz86NChQosXLgwybqIiIiISCqcvAi5kxg0SEw7cSF9ytl/0vw17FtwyQozPoTPXoM1u6HWp+aNTdIgTSNrefPm5cSJE3z77bd06tQpTQWlVvXq1cmZMyfdunVj//79REZGUr9+fRo0aGCZZunm5sbEiRPp1KkTlStX5sknn0zxmmfPnqVChQqcPn2a+vXrU7ZsWbZt28a8efPYuHEjf//9Nzly5ODdd9/lySefZPjw4VSrVo2XXnoJgHLlyqW5HQcPHgQgMDBt0XNqjB8/nrCwMHx8fGjTpg1eXl7Mnz+fTz75hIMHDzJhwgQABg0aREREBJcvX6Zv376W8+9uz40bN3jmmWcICQnhww8/5NChQ8yYMYMXX3yRI0eO4OzsbMlXuXJldu/eTZ06dXjjjTe4dOkSM2bMoH79+vz666/Url3bqp4//PADsbGxtGzZkty5cxMcHJxke8qVK8fw4cMZOXKkVV1LlCgBmKdHNmnShGzZshEaGkpQUBDbt29n5syZbNmyhe3bt+Pq6grAggUL2LJlCzVq1KBQoUJcuXKFX3/9lb59+3LmzBm++so8l/ndd9/lypUrrF27lh49elg+p4oVKz7w57Js2TKmTZtGy5YtrYLyiIgIIiIiKFq0KG+//Taenp6sXLmS/v37c+DAAaZOnQrA5s2badGiBb6+vrz++uvkypWLU6dOsXHjRjZt2kSDBg0euG4iIiIij42btyAmzjbtxk04F2ud7udpHk27Fg+uSYQ+bi7mr9fi06duV66bv+byhQUf3xnJC/KH1l/AtNXQoXayp98rTcFav379ePHFF3nnnXfo378/Tz31FBUqVKBBgwZUrlz5/hdIhSeffJI5c6y3wZwxYwbnz59nz549+Pv7A9CoUSOqV6/OiBEjmDRpUorX7NmzJ6dOnSI8PNxqhCU8PJxBgwbRs2dPxo8fT8OGDSlQoADDhw+nZMmSdO/e/YHacPPmTYYMGUKWLFmSHFl8GDdv3uSjjz7C1dWVTZs28cQTTwDQv39/ypYty6RJk3j33XcpW7YsYWFhfPXVV8THxyfblsuXL9O+fXu+/PJLS1pAQABffvklM2bM4LXXXgPMfbVjxw6mTJliSQPo27cvxYsX54MPPmDHjh1W1z579iy7du2iQIGUh5QLFixI9+7dmTRpUpJ17dChA9mzZ7cE1Ym+++47OnXqxBdffEHv3r0BeP/994mIiLA6f9iwYTz11FOMHz+ezz//HFdXVxo2bMj8+fNZu3Ytbdq0ISQkJMU6psaxY8dYu3at1b+FgwcPMnDgQGrUqGE1AjlgwABCQ0OZPn06PXv2pEyZMsyZM4f4+HgmTZr02O5AKiIiIvLQ1u6Bmn1t09fthZ/XWKcd/s489dDdBW7csj3n+r9BmrtL+tQt8Tqh1aynXLasAq87meuYhmAtTdMgGzZsyKpVq6hbty5xcXEsXryYAQMGUKVKFUqVKsX27dvTcrkkhYeHW72vUaMGAE2aNLEEagDPPfcc7u7uqVont2zZMry8vPjkk0+s0vv27YuXlxfLli176HrfrXXr1uzdu5d33nmHChUqpOu1V6xYwfnz52nSpIklUANwd3fn/fffxzAMfvrpp1Rfz2Qy2UyfbNiwIQBRUVGWtDlz5pAnTx5q1KhBdHS05XX9+nUqVapEVFQUly9ftrpOgwYN7huo3c+aNWs4evQojRs35tq1a1ZlN2jQAFdXV6vP7+4ppleuXOH48eOcPHmS6tWrc+3aNTZv3vxQ9UlJpUqVbP5oMW7cOG7dusXbb79tVffo6GiaNm2KYRjMmzfPqu4zZszgypUrdquniIiIiKPbtm2b1ft169bdeVMmmKhRodxe/Aks6wfL+nG9aC5u1ixleX92WmdOT+1kHuECbuf04fK+Y7bXPHnR/CaPn3UZwIYNG7h9+7blfVRUFBcvXrS8j46O5tixO9eMjY3ltNO/wV9OH+t6OzlBDi/OH7Suw/2keVuSZ555hsWLFwPm9VgLFixg0qRJREVF0bhxY/bu3Yu7u3taL2tRunRpq/eJAdrd6+ESeXh4EBNz/+cVnDlzhiJFiuDiYh0xu7i4EBQUZJmymB7efPNNZs+eTePGjS1T7tLTvn37AJIcCUoMDA8fPpzq62XPnh1PT0+rtFy5cgHmDTISRUdHEx8fT758+ZK91vHjxylevLjlfbFixVJdj+Rs3boVgO+//57vv/8+yTx31/PixYt07tyZpUuXWqUnOnv27EPXKTlJ/Ywm7vb58ssvJ3veqVOnAPPUzJ9//pmJEycybdo0ihcvTo0aNQgLC6NUqVL2qbSIiIiIA3r66aet3letWvXOm+yelHzP+ncrt9w5IH8g1DJvq3/vjhJOZQvh9cdu8/PW/h3xqlq1Kkz8FrK5QtE8VHW1HmS494/wiXtbJAoKCrJ67+3tjXeDqjB6BRy/YF3vePMUzRxN0jaQ82B7SP6rVKlSlCpViu7duxMSEsLu3btZunQpL774YooPNL51K4khyH8lrpG6l5OTU5LphmGkrdJ2FBYWxo8//ki9evUsoyWOLqWdF+/uW8MwyJ8/P5999lmy+e/9gc2WLdvDV/BfrVu3pnHjxkkeu3uDl/r167Np0yYaN25M9erVLQ/Ynj9/PjNmzLD660hKkvv5jY9Pfj5zUu1N7MOhQ4cmG+gm/sPPli0b27ZtY/HixcyfP58NGzbwzTff8O233zJ69Gg6duyYqrqLiIiIyD1aVDFv3z9nA7T4N4A6FwuR66Bxeett+w+a/5BO4VxpL6dGCAT6wNTV0Kf5nTVxE3+D2wn3f0bbPR4qWEuUJUsWypQpw+7duzl69ChwZ3Tm7qHCREeOHEmPYlMtZ86c/PPPP8THx1uNrsXHxxMdHZ0uz9gKCwtj7Nix1K1bl19//dVu288njlbdvZNmosQdHAsWLGhJSyloTovcuXMTExNDaGhosoGzPSSOKDk5OdG6desU854+fZpNmzZRu3Zt5s+fb3Vs0aJFNvlT6pvEKYknTpwgT548lvS///47tVUHsExVzZkz533rn6hevXqWNWt79uyhQoUKDBo0SMGaiIiIyINqUQUqF4U3voaoaPD3gm8WmwOoiHtmQL3w747dR+6a1XX0DEz53fz9nwfMXwdGmr8WCIDXa5i/d3WG4W2g7VfwXDi8Xh2OnYNRC+DZktCsUpqqnaaIYtq0aUmOLFy+fJm1a9cCULZsWQBy5MiBj48PGzduJCEhwZJ3+/btlryPSq1atbh8+TKDBg2ySh84cCCXL1+22cUwrTp27MjYsWOpXbs2CxYssGsw8/zzz5MjRw5++eUXq/V6N27c4Msvv8RkMlltAOLu7s7Vq1etPoMH0bx5c2JiYujRo0eSx9My9TItatasSb58+Zg9e3aSayLj4+M5ceIEAFmzmv/2cO9o68GDB5k7d67NuYnTP0+fPm1zLDEovvcxB/37909T/d966y2yZs1q+Vm719mzZ4mLM+9mFB0dbXO8aNGieHt7J3muiIiIiKSSkxMsDIdW1WD0AugxGfy9YWUEFMt7//MPn4FPpptfG/eb0xLfj19hnbdNTZj+AcTfMpcz5Xd4u7Z5d8g0xglpGlnr1asX77zzDs899xwhISF4eHhw7NgxfvnlF06ePEmdOnV45plnLPlfffVVvvnmGypUqECjRo04fvw4M2fOJH/+/Bw4cCBNFX0Yw4YNs2yGsnXrVp5++mm2bdvGggULyJMnD8OGDXvga4eHh/P999+TI0cOatWqxciRI62O58mTh1deecXyfteuXYwZMwa4s55pwYIF/PPPPwB07tw5xfVJzs7ODB06lLCwMCpUqEBoaKhl6/59+/bRrl07S8AMUL58eTZt2kSLFi2oVq0aTk5ONG3aNM0bfwwZMoTff/+dkSNH8scff/Dss8/i4+PD0aNHWbt2La6urmkedUqNLFmyMGnSJBo3bkylSpVo3LgxpUqV4urVqxw8eJCVK1fy0Ucf0bt3b3LkyMHTTz9t2eq/QoUKHDlyhMjISHLmzGmzaUf16tX54osv6N69O6Ghobi7u1OhQgWqVatGly5d+Pzzz+nVqxdRUVH4+fmxYsUKm+e63U+xYsWIiIggPDycQoUK0aRJE4KDgzlz5gy7du1i7dq1bNmyhZCQED744APWrVtneeyAYRgsWrSIEydOWAXgIiIiInKPVQPunye7J4zrbH6l5EgS+yTUCAFjjm16cl5+xvx6SGkK1oYMGcLs2bPZunUrv/32G3Fxcbi7u1OoUCE6d+5Mr169rPKPHDmSmJgYfv31VwYPHky+fPkYOXIkGzdufKTBWkBAABs3bqRr1678/vvvLFy4EB8fH1566SVGjx5ttR18WiVOPTx//nySD30OCQmxCtZ2797Nt99+a5Vn7dq1ltHG559//r6bSbz55pv4+voycOBAJk6cyK1btwgKCmLAgAE2u2kOGTKEI0eOsGLFCubNm4dhGAQFBaU5WHN1dWX9+vX069ePyMhIS8Dp5+dHqVKleOONN9J0vbSoWbMmGzdupE+fPqxatYq5c+fi5uZGzpw5efHFF2natKkl7/z583n77bf5448/WLRoEblz56Z79+44OzvTp08fq+s2adKErl27Mm3aNMLDw0lISOCtt96iWrVq+Pv7ExkZyQcffMD48eNxc3OjRo0a/O9//7NM8U2tPn36EBISwtChQ4mMjCQuLg4vLy/y5ctHly5dLM+fCw0N5cyZMyxZsoSYmBhcXFzIkycP/fv35+OPP37ofhQRERGRzMVkONIOHSLy0GJjY/Hx8SHmiTC8D9hv90sRERGRdFcsr3lqYh6/jK6JQ7DPLhgiIiIiIiLyUBSsiYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOCAFayIiIiIiIg4oTQ/FFpFMJNgfnFwyuhYiIiIiqVcwMKNr4FAUrIk8rr5+C7y8M7oWIiIiImnj4ZrRNXAYCtZEHle5/cBbwZqIiIhIZqU1ayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAmIiIiIiLigBSsiYiIiIiIOKCsGV0BEUlfhmEAEBsbm8E1EREREZGUeHl5YTKZkj2uYE3kMXP+/HkA8uXLl8E1EREREZGUxMTE4O3tnexxBWsijxk/Pz8Ajh07ho+PTwbXxrHExsaSL18+/vnnnxRvjP9V6p/kqW9Spv5JnvomZeqf5KlvUva49I+Xl1eKxxWsiTxmsmQxL0X18fHJ1Dcve/L29lbfpED9kzz1TcrUP8lT36RM/ZM89U3KHvf+0QYjIiIiIiIiDkjBmoiIiIiIiANSsCbymHF1daVfv364urpmdFUcjvomZeqf5KlvUqb+SZ76JmXqn+Spb1L2X+kfk5G4z7eIiIiIiIg4DI2siYiIiIiIOCAFayIiIiIiIg5IwZqIiIiIiIgDUrAm4qD27NlD7dq18fDwIFeuXPTs2ZP4+Pj7nmcYBp999hn58+fH3d2dKlWqsGHDBpt8J06coHnz5nh5eeHn50eHDh2IjY21R1PSnT37Zvny5bz88ssEBweTLVs2SpYsyfDhw7l586a9mpPu7P2zkyghIYFy5cphMpmYNWtWejbBbh5F3yxYsICqVavi4eFB9uzZqVmzJtHR0endFLuwd/+sWbOGmjVrkj17dvz9/alfvz5//fWXHVqS/h60b7755hsaNWpEQEBAiv9WMvM9GezbP5n9vmzvn51EmfGeDI+mfzLzfRlDRBzOhQsXjNy5cxvPPfecsXjxYmP8+PGGj4+P0blz5/ueO2TIEMPFxcX44osvjOXLlxtNmzY1vLy8jIMHD1ryxMfHGyEhIUZISIjxv//9z/j555+NoKAgo2HDhvZsVrqwd9+0aNHCaNCggTFp0iTjt99+M4YMGWK4u7sb7dq1s2ez0o29++du33zzjZEzZ04DMCIjI9O7KenuUfTNlClTDBcXF6N3797GypUrjfnz5xvdu3c39u/fb69mpRt798+ePXsMd3d3o2HDhsaiRYuMefPmGRUrVjT8/PyMkydP2rNpD+1h+qZSpUpGpUqVjDZt2iT7byUz35MNw/79k5nvy/bum7tltnuyYTya/snM92XDMAwFayIOaPDgwYaHh4dx/vx5S9r3339vODk5GcePH0/2vGvXrhne3t5G7969LWk3btwwChQoYHTq1MmSNm3aNMNkMhl79uyxpC1ZssQAjI0bN6Zza9KXvfvm7NmzNucOGjTIMJlMSR5zNPbun0Rnz541/Pz8jB9//DHT/GJg7745f/684e3tbXzzzTf2aYCd2bt/hgwZYri5uRlxcXGWtEOHDhmAMXny5HRuTfp60L4xDMO4ffu2YRiGcfjw4WT/rWTme7Jh2L9/MvN92d59kygz3pMNw/79k9nvy4ZhGJoGKeKAFi1aRK1atfDz87OkhYaGkpCQwNKlS5M9b926dcTGxhIaGmpJc3FxoVmzZixcuNDq+k8++STFihWzpNWuXRs/Pz+rfI7I3n3j7+9vc+7TTz+NYRicPHkynVphP/bun0S9e/emZs2a1KxZM30bYEf27puZM2dy+/Zt3nzzTfs0wM7s3T83b97E1dUVNzc3S5qPjw9gnkbpyB60bwCyZLn/r1qZ+Z4M9u+fzHxftnffJMqM92Swf/9k9vsyaM2aiEPas2cPxYsXt0rz9fUld+7c7NmzJ8XzAJtzS5QowbFjx7h27Vqy1zeZTBQvXjzF6zsCe/dNUtasWYOrqysFCxZ8iJo/Go+ifzZt2sS0adP4/PPP07Hm9mfvvtmwYQPFixdn0qRJFChQgKxZs/LUU0+xaNGidG6Jfdi7f15++WVu3bpFeHg458+f58SJE7z//vvky5ePF198MZ1bk74etG8e5vqZ5Z4M9u+fpGSW+/Kj6JvMek8G+/dPZr8vg4I1EYd08eJFfH19bdKzZ8/OhQsXUjzv3r9cJ55nGAYXL158qOs7Anv3zb3279/PqFGj6NixI56eng9V90fB3v2TkJBA586d+fDDDwkODk7Pqtudvfvm1KlT7N27l08++YQBAwawaNEigoODadKkCbt27UrXttiDvfunSJEirFixgvHjx+Pv70/evHlZvXo1y5cvt4ywOSp73zMz8z0ZHn39M9N92d59k5nvyWD//sns92VQsCYikqzY2FiaNWtGwYIFGTRoUEZXxyGMGzeOU6dO0atXr4yuisNJSEjgypUr/PDDD7Rp04batWsTGRlJUFAQQ4cOzejqZbh9+/bRvHlz6tSpw7Jly/jll18oUKAA9evX5/Tp0xldPckkdF+2pntyyh6H+7KCNREHlD17dmJiYmzSL168aDWvO6nzbty4wfXr123OM5lMZM+e/aGu7wjs3TeJ4uPjadq0KRcvXmThwoV4eHikTwPszJ79c+XKFfr06UN4eDjx8fFcunTJsrV4XFycw28z/ij+XQE8//zzljzOzs4899xzmeIvuPbunz59+pArVy4mT55MrVq1aNSoEb/++isXL15k1KhR6duYdGbve2ZmvifDo6t/Zrwv27NvMvs9GR7Nvy3IvPdlULAm4pCSWqcQExPDyZMnbeZ233sewN69e63S9+zZY3n+UXLXNwyDvXv3pnh9R2DvvgHzX+JeffVVtmzZwqJFi8iXL186tsC+7Nk/586d4/z583Ts2JHs2bOTPXt2ypQpA0Dbtm0pWrRoOrcmfdn7Z6dUqVLJXuPeQMYR2bt/oqKiLD8viTw9PXniiSc4ePBgejTBbh60bx7m+pnlngz27x/IvPdle/ZNZr8ng/1/djL7fRkUrIk4pPr167N8+XIuXbpkSYuMjCRLlizUqVMn2fOqVq2Kt7c3kZGRlrSbN28yZ84cGjRoYHX97du3s3//fkvaihUrOH/+vFU+R2TvvgHo3Lkzv/zyC/Pnz6d06dLp3gZ7smf/5MqVi99++83qNX36dAA+/fRT5syZY59GpRN7/+w0atQIMD/AN1F8fDy///475cqVS8eW2Ie9+6dAgQJs27bNaufH2NhY9u/f7/BrbR60b9Jy/cx6Twb79w9k3vuyPfsms9+Twf4/O5n9vgzoodgijijxIZHVq1c3lixZYvz444+Gr6+vzUMin3/+eaNw4cJWaUOGDDFcXV2NL7/80lixYoXRvHnzZB+KXbp0aeOXX34xZsyYYeTLly9TPIDV3n0zaNAgAzB69OhhrF+/3uoVExPzSNr4MOzdP/dKzfN/HMWj6JvmzZsbAQEBxvjx442FCxcaDRs2NNzc3Iy///7b7u17WPbun3nz5hmA0bp1a2PRokXG3LlzjWeeecZwd3c39u3b90ja+KAepm82b95sREZGGt98840BGB9++KERGRlprFq1ypInM9+TDcP+/ZOZ78v27pt7ZaZ7smE8mv7JzPdlw9BDsUUcVlRUlPHCCy8Y7u7uRmBgoNG9e3fjxo0bVnmqV69uFChQwCotISHBGDx4sBEUFGS4uroalSpVMtatW2dz/ejoaKNZs2aGp6en4evra7Rv397h/9NLZM++qV69ugEk+frtt9/s3LL0Ye+fnbtltl8M7N03V65cMd59910jICDAcHV1NapWrWqsWbPGnk1KV/bun5kzZxoVKlQwvL29DX9/f6N27drGhg0b7NmkdPOgfdO2bdsk7yfVq1e3ypeZ78mGYd/+yez3ZXv/7Nwts92TDcP+/ZPZ78smw3DwJ1GKiIiIiIj8B2nNmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiIiIiDkjBmoiIiIiIiANSsCYiIiIiIuKAFKyJiIiIiIg4IAVrIiIiYuXMmTP4+PgwduxYq/R27doRHBycMZV6THz66aeYTCaOHDnySMqbOHGiTXnXrl0jT548REREPJI6iMiDU7AmIiIiVsLDwwkICOCNN95IVf5Tp07RvXt3QkJC8PLywtvbmyJFivDyyy8zZ84cq7w1atTA09Mz2WslBjN//vlnkscvXryIu7s7JpOJKVOmJHud4OBgTCaT5eXi4kJwcDAdOnTgn3/+SVW7Hlfu7u706tWL4cOHc/LkyYyujoikQMGaiIiIWERHR/Pjjz/y7rvvkjVr1vvmP3r0KGXKlGHMmDFUrlyZzz77jCFDhtCoUSP27NnDhAkT0rV+U6dO5caNGxQsWJAff/wxxbxBQUFMmTKFKVOmMGrUKCpVqsSPP/5IpUqVOHfuXLrWK7N58803MZlMfPHFFxldFRFJwf3vwiIiIvKf8f3332MymWjdunWq8n/++eecOXOGefPm8eKLL9ocP3XqVLrWb/z48dSsWZMXX3yRbt26cejQIQoVKpRkXh8fH1577TXL+06dOhEYGMjXX3/NhAkT6NGjR7rWLTPx8PCgWbNmTJw4kYEDB+Lq6prRVRKRJGhkTURE5CEkrglasWIF/fv3p0CBAri7u1OpUiU2bNgAwO+//84zzzyDh4cHuXPnZsCAAUle688//6Rp06b4+/vj6upKsWLFGDRoELdu3bLKt2nTJtq1a0fRokXJli0bXl5eVKtWjblz59pcs127dphMJmJiYizBipubG9WqVWPjxo02+SMjIylfvjyBgYGpav/+/fsBeOGFF5I8nitXrlRdJzW2bt3KX3/9Rdu2bXnllVfImjXrfUfX7lW3bl0ADhw4kGyeRYsWYTKZGD16dJLHq1SpQkBAADdv3gTS9nkkJfEzSorJZKJdu3Y26TNmzOCZZ57By8uLbNmyUalSJWbNmpWq8hLVr1+fc+fO8dtvv6XpPBF5dBSsiYiIpINevXoxb948unbtSr9+/Th06BB16tRh3rx5NGvWjGeffZbPP/+c4sWL07dvX3766Ser8xcsWEC1atXYt28fH374IaNHj6ZKlSr07dvXZpRr7ty57Nmzh9DQUEaNGsXHH3/MhQsXaNasGdOmTUuyfnXr1iU6Opq+ffvSu3dvdu7cScOGDbl8+bIlz+nTp9m7dy8VK1ZMdbsLFy4MwNixYzEMI9XnnTt3LslXXFxcsueMHz8eT09Pmjdvjr+/P40aNWLSpEkkJCSkutzE4NLf3z/ZPHXq1CFXrlxMnjw5yfM3bNjAK6+8grOzM/Bgn8fDCA8P5+WXX8bLy4sBAwbw2WefkS1bNlq2bMmYMWNSfZ0qVaoAsGrVqnSvo4ikE0NEREQe2IQJEwzAePrpp40bN25Y0ufPn28ARtasWY3Nmzdb0m/cuGHkypXLqFy5siXt2rVrRs6cOY1nn33WuHnzptX1v/jiCwMwfvvtN0valStXbOpx9epVo2jRokaJEiWs0tu2bWsARqdOnazSZ86caQDGd999Z0lbuXKlARijRo1Ksq1t27Y1ChQoYJV28OBBw9vb2wCMfPnyGa+88ooxcuRI488//0zyGtWrVzeA+77u7rPEPvL19TXatm1rSZs3b54BGAsXLrQpp0CBAkbx4sWNs2fPGmfPnjUOHTpk/Pjjj4aPj4+RNWtWY8eOHUnWL1H37t0NwNi1a5dVenh4uAEYW7ZssaSl5fPo16+fARiHDx+2pCV+RkkBrNq8ZcsWAzB69+5tk/fFF180vLy8jNjYWEta4s/n3eXdLWvWrEajRo2SPCYiGU8jayIiIumgU6dOuLi4WN4/++yzAFSqVIny5ctb0l1cXKhYsaJlhAdg2bJlnD59mjfeeINLly5ZjTQ1aNAAgKVLl1rye3h4WL6Pi4vj/PnzxMXF8fzzz7N7925iY2Nt6vf+++9bvX/++ecBrOpx9uxZAPz8/FLd7kKFCrF9+3Y6d+4MwLRp03j//fcpX748Tz75JFu2bLE5x83NjWXLliX5ev3115MsZ86cOVy6dIm2bdta0ho0aEBAQECyUyH37NlDQEAAAQEBFCpUiPbt2+Pv78/8+fMJCQlJsV2J5dw9umYYBj/99BMhISGULVvWkv4gn8eDmjp1KiaTibZt29qMSjZp0oTLly+zfv36VF/Pz8+PM2fOpFv9RCR9aYMRERGRdHDvJhfZs2cHoGDBgjZ5s2fPzvnz5y3vd+/eDUD79u2Tvf7p06ct3585c4bw8HDmz5+f5C/aly5dwtvbO8X65ciRA8CqHonrpow0TGcE8zb5X3/9NV9//TUnT55kzZo1TJkyhV9++YVGjRqxa9cuqwDQycmJWrVqJXmtNWvWJJk+fvx4AgICCAoKslpvVqdOHSIjIzl37pzN1Mbg4GDLs+JcXFzIkycPTzzxRKralBiQTZ06lcGDB5MlSxZWr17NkSNHGDZsmFXeB/k8HtTu3bsxDIPixYsnm+fun5X7MQwj2fVyIpLxFKyJiIikAycnpzSl3y0xOBo+fDhPPfVUknny5MljyVunTh12795N165dKV++PD4+Pjg5OTFhwgSmTZuW5Bqu5Opxd2AWEBAAwIULF+5b5+Tkzp2bli1b0rJlS1599VWmTZvGwoULrXZlTKvDhw/z22+/YRgGRYsWTTLPTz/9RLdu3azSPDw8kg0KU6NNmzZ069aNlStXUqtWLSZPnoyTk5NVWx7087hbcsHSvRvLJJZnMplYtGhRsp9pqVKlUt3GixcvWj53EXE8CtZEREQyWJEiRYDUBRd///0327dvp2/fvkRERFgdGzdu3EPVI/GX/LunRj6MypUrM23aNI4fP/5Q15kwYQKGYTB27Fh8fX1tjoeHh/Pjjz/aBGsP65VXXqFHjx5MnjyZatWqMWvWLGrXrk3u3LktedLj80gcdbxw4YLVCOShQ4ds8hYpUoTFixeTP39+SpQo8SDNsjhy5Ai3bt2675RQEck4WrMmIiKSwerWrUtgYCCfffZZkqNa165ds+zamDiacu9UxZ07d6Z6q/jkBAQEUKpUKcsjB1Jj1apVXLt2zSY9ISGBX375BYCSJUs+cJ0SEhKYOHEipUuXpkOHDrRo0cLm1bp1a3bs2MHmzZsfuJykBAQEUL9+febMmcPUqVOJjY21WjMH6fN5JI4WLl++3Cp9xIgRNnkT1/T16dOH27dv2xxPyxTIxM+5evXqqT5HRB4tjayJiIhkMA8PDyZPnsxLL71EsWLFaN++PU888QSXLl1iz549zJkzh7lz51KjRg1KlChBqVKlGDZsGHFxcRQrVox9+/bx/fffU7p06SQ39EiLli1bMmDAAE6ePGk1gpSczz//nLVr19K4cWPKli2Lj48Pp06dYvbs2WzZsoWaNWvSsGHDB67P0qVL+eeff3jzzTeTzdO8eXM+/fRTxo8fT4UKFR64rKS0bduW//3vf3z44Yf4+Pjw0ksvWR1Pj8+jdevW9OnTh7CwMPbs2YOfnx+LFy/m3LlzNnkrVKjAp59+yqeffspTTz1Fy5YtyZMnDydPnmTLli0sXLiQ+Pj4VLVt4cKF+Pv7U7NmzVTlF5FHT8GaiIiIA6hbty6bN2/ms88+46effuLs2bNkz56dwoUL88EHH/Dkk08C5pGcBQsW0L17dyZNmsTVq1cJCQlh0qRJbN++/aGDtbfeeouBAwcybdo0Pvzww/vmDw8PJzIyktWrV7NkyRIuXLiAh4cHJUqUYMSIEXTu3JksWR58Is/48eMBaNasWbJ5QkJCKFq0KD///DMjR47E3d39gcu7V6NGjfDz8+PChQt06NABNzc3q+Pp8Xl4e3uzcOFCPvjgAwYPHoynpyfNmjXjp59+smxUc7d+/fpRvnx5Ro8ezZdffsnVq1cJDAwkJCQk2Qd53+vq1avMmTOHTp064erqmrrOEJFHzmSkdcsnEREReax17NiRpUuXsnfvXsuDnwHatWvHqlWrOHLkSMZVTtJk4sSJvPHGGxw+fJjg4GBLeuLDu/fv35+qEVQRyRhasyYiIiJW+vfvz/nz55kwYUJGV0Xs4Nq1a3z22Wf06NFDgZqIg9M0SBEREbESGBhITExMRldD7MTd3Z2TJ09mdDVEJBU0siYiIiIiIuKAtGZNRERERETEAWlkTURERERExAEpWBMREREREXFACtZEREREREQckII1ERERERERB6RgTURERERExAEpWBMREREREXFACtZEREREREQckII1ERERERERB6RgTURERERExAH9Hw2pk9gaHMmXAAAAAElFTkSuQmCC\n"
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "/usr/local/lib/python3.12/dist-packages/tabpfn_extensions/interpretability/shap.py:137: FutureWarning: The NumPy global RNG was seeded by calling `np.random.seed`. In a future version this function will no longer use the global RNG. Pass `rng` explicitly to opt-in to the new behaviour and silence this warning.\n",
-            "  shap.summary_plot(shap_values=shap_values, show=False)\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 800x950 with 2 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 750x500 with 3 Axes>"
-            ],
-            "image/png": 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\n"
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+       "  <thead>\n",
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+       "      <th></th>\n",
+       "      <th>CRIM</th>\n",
+       "      <th>ZN</th>\n",
+       "      <th>INDUS</th>\n",
+       "      <th>CHAS</th>\n",
+       "      <th>NOX</th>\n",
+       "      <th>RM</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>DIS</th>\n",
+       "      <th>RAD</th>\n",
+       "      <th>TAX</th>\n",
+       "      <th>PTRATIO</th>\n",
+       "      <th>B</th>\n",
+       "      <th>LSTAT</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.00632</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0.538</td>\n",
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+       "      <td>0</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>2.18</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>3</td>\n",
+       "      <td>222.0</td>\n",
+       "      <td>18.7</td>\n",
+       "      <td>394.63</td>\n",
+       "      <td>2.94</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.06905</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2.18</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.458</td>\n",
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+       "      <td>6.0622</td>\n",
+       "      <td>3</td>\n",
+       "      <td>222.0</td>\n",
+       "      <td>18.7</td>\n",
+       "      <td>396.90</td>\n",
+       "      <td>5.33</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
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+       "\n",
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+       "  </svg>\n",
+       "    </button>\n",
+       "\n",
+       "  <style>\n",
+       "    .colab-df-container {\n",
+       "      display:flex;\n",
+       "      gap: 12px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert {\n",
+       "      background-color: #E8F0FE;\n",
+       "      border: none;\n",
+       "      border-radius: 50%;\n",
+       "      cursor: pointer;\n",
+       "      display: none;\n",
+       "      fill: #1967D2;\n",
+       "      height: 32px;\n",
+       "      padding: 0 0 0 0;\n",
+       "      width: 32px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert:hover {\n",
+       "      background-color: #E2EBFA;\n",
+       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "      fill: #174EA6;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-buttons div {\n",
+       "      margin-bottom: 4px;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert {\n",
+       "      background-color: #3B4455;\n",
+       "      fill: #D2E3FC;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert:hover {\n",
+       "      background-color: #434B5C;\n",
+       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "      fill: #FFFFFF;\n",
+       "    }\n",
+       "  </style>\n",
+       "\n",
+       "    <script>\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#df-4590d6cd-2eaa-4ea3-b5f5-7a56b39dda16 button.colab-df-convert');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      async function convertToInteractive(key) {\n",
+       "        const element = document.querySelector('#df-4590d6cd-2eaa-4ea3-b5f5-7a56b39dda16');\n",
+       "        const dataTable =\n",
+       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+       "                                                    [key], {});\n",
+       "        if (!dataTable) return;\n",
+       "\n",
+       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+       "          + ' to learn more about interactive tables.';\n",
+       "        element.innerHTML = '';\n",
+       "        dataTable['output_type'] = 'display_data';\n",
+       "        await google.colab.output.renderOutput(dataTable, element);\n",
+       "        const docLink = document.createElement('div');\n",
+       "        docLink.innerHTML = docLinkHtml;\n",
+       "        element.appendChild(docLink);\n",
+       "      }\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "\n",
+       "    <div id=\"df-c0acb8e2-3622-4d87-aaad-fe39e89d60bc\">\n",
+       "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c0acb8e2-3622-4d87-aaad-fe39e89d60bc')\"\n",
+       "                title=\"Suggest charts\"\n",
+       "                style=\"display:none;\">\n",
+       "\n",
+       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "     width=\"24px\">\n",
+       "    <g>\n",
+       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+       "    </g>\n",
+       "</svg>\n",
+       "      </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
+       "      --hover-fill-color: #174EA6;\n",
+       "      --disabled-fill-color: #AAA;\n",
+       "      --disabled-bg-color: #DDD;\n",
+       "  }\n",
+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
+       "      --hover-bg-color: #434B5C;\n",
+       "      --hover-fill-color: #FFFFFF;\n",
+       "      --disabled-bg-color: #3B4455;\n",
+       "      --disabled-fill-color: #666;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart {\n",
+       "    background-color: var(--bg-color);\n",
+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
+       "    display: none;\n",
+       "    fill: var(--fill-color);\n",
+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    30% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "      <script>\n",
+       "        async function quickchart(key) {\n",
+       "          const quickchartButtonEl =\n",
+       "            document.querySelector('#' + key + ' button');\n",
+       "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "          try {\n",
+       "            const charts = await google.colab.kernel.invokeFunction(\n",
+       "                'suggestCharts', [key], {});\n",
+       "          } catch (error) {\n",
+       "            console.error('Error during call to suggestCharts:', error);\n",
+       "          }\n",
+       "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "        }\n",
+       "        (() => {\n",
+       "          let quickchartButtonEl =\n",
+       "            document.querySelector('#df-c0acb8e2-3622-4d87-aaad-fe39e89d60bc button');\n",
+       "          quickchartButtonEl.style.display =\n",
+       "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "        })();\n",
+       "      </script>\n",
+       "    </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
       ],
-      "source": [
-        "from tabpfn_extensions import interpretability\n",
-        "\n",
-        "# Load example dataset\n",
-        "data = load_breast_cancer()\n",
-        "X, y = data.data, data.target\n",
-        "feature_names = data.feature_names\n",
-        "n_samples_test, n_samples_train = 25, 50\n",
-        "\n",
-        "# Split data\n",
-        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5)\n",
-        "\n",
-        "# Initialize and train model\n",
-        "clf = TabPFNClassifier()\n",
-        "clf.fit(X_train[:n_samples_train], y_train[:n_samples_train])\n",
-        "\n",
-        "# Calculate SHAP values\n",
-        "shap_values = interpretability.shap.get_shap_values(\n",
-        "    estimator=clf,\n",
-        "    test_x=X_test[:n_samples_test],\n",
-        "    attribute_names=feature_names,\n",
-        "    algorithm=\"permutation\",\n",
-        ")\n",
-        "\n",
-        "# Create visualization\n",
-        "fig = interpretability.shap.plot_shap(shap_values)"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "Zt05caATl2Cc"
-      },
-      "source": [
-        "### Embeddings\n",
-        "\n",
-        "This example demonstrates how to extract embeddings from TabPFN models and use them\n",
-        "for classification and regression tasks.\n",
-        "\n",
-        "NOTE: This example requires the full TabPFN implementation (pip install tabpfn).\n",
-        "It will not work with the TabPFN client (pip install tabpfn-client) because\n",
-        "the embedding functionality is not available in the client version.\n"
+      "text/plain": [
+       "      CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
+       "0  0.00632  18.0   2.31     0  0.538  6.575  65.2  4.0900    1  296.0   \n",
+       "1  0.02731   0.0   7.07     0  0.469  6.421  78.9  4.9671    2  242.0   \n",
+       "2  0.02729   0.0   7.07     0  0.469  7.185  61.1  4.9671    2  242.0   \n",
+       "3  0.03237   0.0   2.18     0  0.458  6.998  45.8  6.0622    3  222.0   \n",
+       "4  0.06905   0.0   2.18     0  0.458  7.147  54.2  6.0622    3  222.0   \n",
+       "\n",
+       "   PTRATIO       B  LSTAT  \n",
+       "0     15.3  396.90   4.98  \n",
+       "1     17.8  396.90   9.14  \n",
+       "2     17.8  392.83   4.03  \n",
+       "3     18.7  394.63   2.94  \n",
+       "4     18.7  396.90   5.33  "
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Load the Boston Housing dataset\n",
+    "\n",
+    "import pandas as pd, requests\n",
+    "from IPython.display import display, Markdown\n",
+    "\n",
+    "cols = [\"CRIM\",\"ZN\",\"INDUS\",\"CHAS\",\"NOX\",\"RM\",\"AGE\",\"DIS\",\"RAD\",\"TAX\",\"PTRATIO\",\"B\",\"LSTAT\",\"MEDV\"]\n",
+    "df_boston = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data\",\n",
+    "                        delim_whitespace=True, header=None, names=cols)\n",
+    "X, y = df_boston.drop(columns=[\"MEDV\"]), df_boston[\"MEDV\"]\n",
+    "\n",
+    "display(X.head())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "id": "YaA7WBuEVdQy"
+   },
+   "outputs": [],
+   "source": [
+    "# Alternative datasets (commented for reference):\n",
+    "\n",
+    "# Liver Disorders dataset\n",
+    "# Classification task: Predict liver disorder presence\n",
+    "# Features: Blood test results, alcohol consumption\n",
+    "# Samples: 345 patients\n",
+    "# Target: Binary liver disorder diagnosis\n",
+    "# df = fetch_openml(\"liver-disorders\", version=1)\n",
+    "\n",
+    "# Grid Stability dataset\n",
+    "# Regression task: Predict electrical grid stability\n",
+    "# Features: Power system measurements, grid parameters\n",
+    "# Samples: 10,000 simulations\n",
+    "# Target: Grid stability score\n",
+    "# df = fetch_openml(data_id=44973, as_frame=True)\n",
+    "\n",
+    "# Concrete Compressive Strength dataset\n",
+    "# Regression task: Predict concrete strength\n",
+    "# Features: Concrete components (cement, water, aggregates)\n",
+    "# Samples: 1,030 concrete samples\n",
+    "# Target: Compressive strength in MPa\n",
+    "# df = fetch_openml(data_id=44959, as_frame=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "rWqC16PL7R_T",
+    "outputId": "01d8b6c2-7421-4a10-8a93-984ddeaafb99"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "nj8XPK35l4z1"
-      },
-      "outputs": [],
-      "source": [
-        "if backend == \"client\":\n",
-        "    console.print(\n",
-        "        Panel(\n",
-        "            \"[bold yellow]Text data can only be processed through the TabPFN server. Please restart the notebook and select the 'client' backend to run this section.[/bold yellow]\",\n",
-        "            title=\"[bold yellow]Warning\",\n",
-        "            border_style=\"yellow\",\n",
-        "        )\n",
-        "    )\n",
-        "else:\n",
-        "    import matplotlib.pyplot as plt\n",
-        "    import numpy as np\n",
-        "    import pandas as pd\n",
-        "    import seaborn as sns\n",
-        "    from sklearn.datasets import load_breast_cancer, load_diabetes\n",
-        "    from sklearn.linear_model import LinearRegression, LogisticRegression\n",
-        "    from sklearn.manifold import TSNE\n",
-        "    from sklearn.metrics import accuracy_score, r2_score\n",
-        "    from sklearn.model_selection import train_test_split\n",
-        "    from tabpfn_extensions import TabPFNClassifier, TabPFNRegressor\n",
-        "    from tabpfn_extensions.embedding import TabPFNEmbedding\n",
-        "\n",
-        "    # Load and evaluate classification dataset\n",
-        "    print(\"Loading classification dataset (breast cancer)...\")\n",
-        "    df = load_breast_cancer(return_X_y=False)\n",
-        "    X, y = df[\"data\"], df[\"target\"]\n",
-        "    attribute_names = df[\"feature_names\"]\n",
-        "\n",
-        "    # Split the data\n",
-        "    X_train, X_test, y_train, y_test = train_test_split(\n",
-        "        X,\n",
-        "        y,\n",
-        "        test_size=0.5,\n",
-        "        random_state=42,\n",
-        "    )\n",
-        "\n",
-        "    # Train and evaluate vanilla logistic regression\n",
-        "    model = LogisticRegression(\n",
-        "        max_iter=10000,\n",
-        "        random_state=42,\n",
-        "    )\n",
-        "    model.fit(X_train, y_train)\n",
-        "    print(\n",
-        "        f\"Baseline Logistic Regression Accuracy: {accuracy_score(y_test, model.predict(X_test)):.4f}\",\n",
-        "    )\n",
-        "\n",
-        "    # Train and evaluate TabPFN embeddings (vanilla)\n",
-        "    clf = TabPFNClassifier(n_estimators=1, random_state=42)\n",
-        "    embedding_extractor = TabPFNEmbedding(tabpfn_clf=clf, n_fold=0)\n",
-        "    train_embeddings = embedding_extractor.get_embeddings(\n",
-        "        X_train,\n",
-        "        y_train,\n",
-        "        X_test,\n",
-        "        data_source=\"train\",\n",
-        "    )\n",
-        "    test_embeddings = embedding_extractor.get_embeddings(\n",
-        "        X_train,\n",
-        "        y_train,\n",
-        "        X_test,\n",
-        "        data_source=\"test\",\n",
-        "    )\n",
-        "\n",
-        "    model = LogisticRegression(\n",
-        "        max_iter=10000,\n",
-        "        random_state=42,\n",
-        "    )\n",
-        "    model.fit(train_embeddings[0], y_train)\n",
-        "    y_pred = model.predict(test_embeddings[0])\n",
-        "    print(\n",
-        "        f\"Logistic Regression with TabPFN (Vanilla) Accuracy: {accuracy_score(y_test, y_pred):.4f}\",\n",
-        "    )\n",
-        "\n",
-        "    # Note: Using test_embeddings and y_test from your original script.\n",
-        "    # The embeddings have shape (n_splits, n_samples, n_features), so we use the first split [0].\n",
-        "    test_only_embeddings = test_embeddings[0]\n",
-        "\n",
-        "    # Apply t-SNE to reduce the TEST embeddings to 2 dimensions.\n",
-        "    # The number of samples in the test set is len(y_test). Perplexity must be less than that.\n",
-        "    # We'll set perplexity to 30, which is suitable for this dataset size.\n",
-        "    print(\"\\nApplying t-SNE for visualization on the TEST SET only...\")\n",
-        "    tsne = TSNE(n_components=2, random_state=42, perplexity=10)\n",
-        "    embeddings_2d = tsne.fit_transform(test_only_embeddings)\n",
-        "\n",
-        "    # Create a DataFrame for easy plotting\n",
-        "    df_plot = pd.DataFrame(\n",
-        "        {\n",
-        "            \"t-SNE-1\": embeddings_2d[:, 0],\n",
-        "            \"t-SNE-2\": embeddings_2d[:, 1],\n",
-        "            \"label\": y_test,\n",
-        "        }\n",
-        "    )\n",
-        "\n",
-        "    # Plot the 2D embeddings for the test set\n",
-        "    plt.figure(figsize=(9, 7))\n",
-        "    sns.scatterplot(\n",
-        "        data=df_plot,\n",
-        "        x=\"t-SNE-1\",\n",
-        "        y=\"t-SNE-2\",\n",
-        "        hue=\"label\",  # Color points by their class label\n",
-        "        palette=\"viridis\",\n",
-        "        alpha=0.9,\n",
-        "        s=80,\n",
-        "    )\n",
-        "\n",
-        "    plt.title(\"t-SNE Visualization of TabPFN Embeddings (Test Set Only)\")\n",
-        "    plt.xlabel(\"t-SNE Dimension 1\")\n",
-        "    plt.ylabel(\"t-SNE Dimension 2\")\n",
-        "    plt.legend(title=\"Class\")\n",
-        "    plt.grid(True, linestyle=\"--\", alpha=0.6)\n",
-        "    plt.show()"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing: 100%|██████████| [00:03<00:00]\n"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "PkphS4vSFNvg"
-      },
-      "source": [
-        "### Feature selection\n",
-        "\n",
-        "Feature selection is the process of selecting a subset of relevant features for use in model construction. It's useful for reducing model complexity, improving performance by removing noise, and decreasing training time. Here, we'll use Sequential Forward Selection (SFS), which starts with no features and iteratively adds the feature that most improves the model's performance.\n",
-        "\n",
-        "The goal is to see if we can create a simpler, faster model with fewer features without a significant drop in accuracy.\n"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "TabPFN RMSE: 2.6528\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Split the data\n",
+    "X_train, X_test, y_train, y_test = train_test_split(\n",
+    "    X, y, test_size=0.33, random_state=42\n",
+    ")\n",
+    "\n",
+    "# Train and evaluate the TabPFN regressor\n",
+    "tabpfn_regressor = TabPFNRegressor(random_state=42)\n",
+    "tabpfn_regressor.fit(X_train, y_train)\n",
+    "y_pred = tabpfn_regressor.predict(X_test)\n",
+    "\n",
+    "# Calculate the Root Mean Squared Error\n",
+    "rmse = np.sqrt(mean_squared_error(y_test, y_pred))\n",
+    "print(f\"TabPFN RMSE: {rmse:.4f}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Itu5-vVRWEMA"
+   },
+   "source": [
+    "### Comparing TabPFN with Other Regressors\n",
+    "\n",
+    "Now, let's see how TabPFN's regression performance stacks up against other models using cross-validation.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 810
     },
+    "id": "0XLxgbqSPe55",
+    "outputId": "930f9733-d5af-40c0-dd95-7f35d8ad61e1"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "GPJtNDLnFPPW"
-      },
-      "outputs": [],
-      "source": [
-        "from tabpfn_extensions import interpretability\n",
-        "\n",
-        "# Load data\n",
-        "data = load_breast_cancer()\n",
-        "X, y = data.data, data.target\n",
-        "feature_names = data.feature_names\n",
-        "\n",
-        "# Initialize model\n",
-        "clf = TabPFNClassifier(n_estimators=1)\n",
-        "\n",
-        "# Feature selection\n",
-        "sfs = interpretability.feature_selection.feature_selection(\n",
-        "    estimator=clf, X=X, y=y, n_features_to_select=4, feature_names=feature_names\n",
-        ")\n",
-        "\n",
-        "# Print selected features\n",
-        "selected_features = [\n",
-        "    feature_names[i] for i in range(len(feature_names)) if sfs.get_support()[i]\n",
-        "]\n",
-        "print(\"\\nSelected features:\")\n",
-        "for feature in selected_features:\n",
-        "    print(f\"- {feature}\")"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    8.9s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    1.1s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.4s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    6.4s finished\n"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "lmPJW5NSK7ut"
-      },
-      "source": [
-        "# Predictive Behavior of TabPFN <a name=\"behavior\"></a>\n",
-        "\n",
-        "In this section, we explore the behavior of predictions from TabPFN on various toy functions."
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Model Comparison - 3-fold Cross-validation \\n (Variance Explained - Larger is better)')"
       ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "ZBeID4YeMQ9L"
-      },
-      "source": [
-        "## Decision Boundary during Classification\n",
-        "\n",
-        "First, let us inspect the decision boundary for different classifiers.\n",
-        "The decision bounds show how smoothly a model learns to transition between classes and how well it fits the data.\n",
-        "\n",
-        "In the first cell, we create the data and code to plot the decision boundary. The second cell then generates the plot."
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Compare different machine learning models by training each one multiple times\n",
+    "# on different parts of the data and averaging their performance scores for a\n",
+    "# more reliable performance estimate\n",
+    "\n",
+    "# Define models\n",
+    "models = [\n",
+    "    (\"TabPFN\", TabPFNRegressor(random_state=42)),\n",
+    "    (\n",
+    "        \"RandomForest\",\n",
+    "        make_pipeline(\n",
+    "            column_transformer,  # string data needs to be encoded for model\n",
+    "            RandomForestRegressor(random_state=42),\n",
+    "        ),\n",
+    "    ),\n",
+    "    (\n",
+    "        \"XGBoost\",\n",
+    "        make_pipeline(\n",
+    "            column_transformer,  # string data needs to be encoded for model\n",
+    "            XGBRegressor(random_state=42),\n",
+    "        ),\n",
+    "    ),\n",
+    "    (\n",
+    "        \"CatBoost\",\n",
+    "        make_pipeline(\n",
+    "            column_transformer,  # string data needs to be encoded for model\n",
+    "            CatBoostRegressor(random_state=42, verbose=0),\n",
+    "        ),\n",
+    "    ),\n",
+    "]\n",
+    "\n",
+    "# Calculate scores\n",
+    "scoring = \"r2\"\n",
+    "n_splits = 3\n",
+    "cv = KFold(n_splits=n_splits, random_state=42, shuffle=True)\n",
+    "scores = {\n",
+    "    name: cross_val_score(model, X, y, cv=cv, scoring=scoring, n_jobs=1, verbose=1)\n",
+    "    for name, model in models\n",
+    "}\n",
+    "\n",
+    "\n",
+    "# Plot results\n",
+    "df = pd.DataFrame([(k, v.mean()) for (k, v) in scores.items()], columns=[\"Model\", \"R2\"])\n",
+    "ax = df.plot(x=\"Model\", y=\"R2\", kind=\"bar\", figsize=(10, 6))\n",
+    "ax.set_ylim(df[\"R2\"].min() * 0.99, df[\"R2\"].max() * 1.01)\n",
+    "ax.set_title(\n",
+    "    f\"Model Comparison - {n_splits}-fold Cross-validation \\n (Variance Explained - Larger is better)\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "3uGfjIdjsCg-"
+   },
+   "source": [
+    "# Handling Text Data <a name=\"text-data\"></a>\n",
+    "\n",
+    "A powerful feature of the TabPFN server is its ability to handle text data directly, without the need for manual feature engineering. This simplifies the process of working with datasets that contain a mix of numerical and textual features.\n",
+    "\n",
+    "**Note:** This feature is only available when using the 'client' backend."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 292
     },
+    "id": "vYBdSZnor-at",
+    "outputId": "13fd1b18-776d-43d2-ee0c-e1ed688071f0"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "B5a_ia0OLOxG"
-      },
-      "outputs": [],
-      "source": [
-        "from matplotlib.colors import ListedColormap\n",
-        "from sklearn.inspection import DecisionBoundaryDisplay\n",
-        "\n",
-        "\n",
-        "# Toy functions that generate the data\n",
-        "def generate_circle(n_datapoints, radius, noise_factor):\n",
-        "    angles = np.linspace(0, 2 * np.pi, n_datapoints).T\n",
-        "    x = radius * np.cos(angles) + np.random.randn(n_datapoints) * noise_factor\n",
-        "    y = radius * np.sin(angles) + np.random.randn(n_datapoints) * noise_factor\n",
-        "\n",
-        "    return np.stack([x, y]).T\n",
-        "\n",
-        "\n",
-        "def generate_concentric_cirlces(radii, num_points_per_circle, noise_factor=1 / 15):\n",
-        "    circles = []\n",
-        "    for r, num_points in zip(radii, num_points_per_circle):\n",
-        "        circles.append(generate_circle(num_points, r, noise_factor))\n",
-        "\n",
-        "    return np.vstack(circles)\n",
-        "\n",
-        "\n",
-        "def generate_circle_data(num_points_per_circle, radii, noise_factor):\n",
-        "    radii = np.array(radii)\n",
-        "    circles_1 = generate_concentric_cirlces(radii, num_points_per_circle, noise_factor)\n",
-        "    circles_1 = np.hstack([circles_1, np.zeros((sum(num_points_per_circle), 1))])\n",
-        "\n",
-        "    circles_2 = generate_concentric_cirlces(\n",
-        "        radii + 0.3, num_points_per_circle, noise_factor\n",
-        "    )\n",
-        "    circles_2 = np.hstack([circles_2, np.ones((sum(num_points_per_circle), 1))])\n",
-        "\n",
-        "    circles = np.vstack([circles_1, circles_2])\n",
-        "    X, y = circles[:, :2], circles[:, 2]\n",
-        "    return X, y\n",
-        "\n",
-        "\n",
-        "# Generate the data\n",
-        "X_train, y_train = generate_circle_data(\n",
-        "    num_points_per_circle=[50, 100, 200], radii=[1, 2, 4], noise_factor=0.1\n",
-        ")\n",
-        "\n",
-        "\n",
-        "# Function for plotting\n",
-        "def plot_decision_boundary(ax, model, model_name):\n",
-        "    cmap = ListedColormap([\"#FF0000\", \"#0000FF\"])\n",
-        "    ax.set_title(model_name)\n",
-        "    DecisionBoundaryDisplay.from_estimator(\n",
-        "        model,\n",
-        "        X_train[:, :2],\n",
-        "        alpha=0.6,\n",
-        "        ax=ax,\n",
-        "        eps=0.2,\n",
-        "        grid_resolution=50,\n",
-        "        response_method=\"predict_proba\",\n",
-        "        cmap=plt.cm.RdBu,\n",
-        "    )\n",
-        "    ax.scatter(X_train[:, 0], X_train[:, 1], c=y_train > 0, cmap=cmap)"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading...\n",
+      "From: https://drive.google.com/uc?id=17bJekFGIAxbrdcBeBIvcyZjneweY581E\n",
+      "To: /content/cloth.csv\n",
+      "100% 8.48M/8.48M [00:00<00:00, 21.0MB/s]\n",
+      "Text dataset loaded successfully!\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "wzrSEZR5LYlf",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 707
-        },
-        "outputId": "3ba2abe5-4fe4-465e-daea-c86d239f79ea"
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "summary": "{\n  \"name\": \"    display(X_text\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"Clothing ID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 119,\n        \"min\": 847,\n        \"max\": 1080,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          1049,\n          858,\n          847\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7,\n        \"min\": 39,\n        \"max\": 60,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          50,\n          39,\n          47\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"My favorite buy!\",\n          \"Cagrcoal shimmer fun\",\n          \"Flattering shirt\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Review Text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"I love, love, love this jumpsuit. it's fun, flirty, and fabulous! every time i wear it, i get nothing but great compliments!\",\n          \"I aded this in my basket at hte last mintue to see what it would look like in person. (store pick up). i went with teh darkler color only because i am so pale :-) hte color is really gorgeous, and turns out it mathced everythiing i was trying on with it prefectly. it is a little baggy on me and hte xs is hte msallet size (bummer, no petite). i decided to jkeep it though, because as i said, it matvehd everything. my ejans, pants, and the 3 skirts i waas trying on (of which i ]kept all ) oops.\",\n          \"This shirt is very flattering to all due to the adjustable front tie. it is the perfect length to wear with leggings and it is sleeveless so it pairs well with any cardigan. love this shirt!!!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Recommended IND\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Positive Feedback Count\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 0,\n        \"max\": 6,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          6,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Division Name\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"General Petite\",\n          \"General\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Department Name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Dresses\",\n          \"Bottoms\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Class Name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Pants\",\n          \"Knits\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
+       "type": "dataframe"
       },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 700x700 with 4 Axes>"
-            ],
-            "image/png": 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+       "      <td>Some major design flaws</td>\n",
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+       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-295fed73-1ab6-47f1-b06d-cd3041b3a409')\"\n",
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+       "      display:flex;\n",
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+       "\n",
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+       "      background-color: #E8F0FE;\n",
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+       "          + ' to learn more about interactive tables.';\n",
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+       "     width=\"24px\">\n",
+       "    <g>\n",
+       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+       "    </g>\n",
+       "</svg>\n",
+       "      </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
+       "      --hover-fill-color: #174EA6;\n",
+       "      --disabled-fill-color: #AAA;\n",
+       "      --disabled-bg-color: #DDD;\n",
+       "  }\n",
+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
+       "      --hover-bg-color: #434B5C;\n",
+       "      --hover-fill-color: #FFFFFF;\n",
+       "      --disabled-bg-color: #3B4455;\n",
+       "      --disabled-fill-color: #666;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart {\n",
+       "    background-color: var(--bg-color);\n",
+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
+       "    display: none;\n",
+       "    fill: var(--fill-color);\n",
+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    30% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "      <script>\n",
+       "        async function quickchart(key) {\n",
+       "          const quickchartButtonEl =\n",
+       "            document.querySelector('#' + key + ' button');\n",
+       "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "          try {\n",
+       "            const charts = await google.colab.kernel.invokeFunction(\n",
+       "                'suggestCharts', [key], {});\n",
+       "          } catch (error) {\n",
+       "            console.error('Error during call to suggestCharts:', error);\n",
+       "          }\n",
+       "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "        }\n",
+       "        (() => {\n",
+       "          let quickchartButtonEl =\n",
+       "            document.querySelector('#df-9afbc783-e193-4d88-938f-00ca40f23fd1 button');\n",
+       "          quickchartButtonEl.style.display =\n",
+       "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "        })();\n",
+       "      </script>\n",
+       "    </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
       ],
-      "source": [
-        "rf = RandomForestClassifier().fit(X_train[:, :2], y_train)\n",
-        "xgb = XGBClassifier().fit(X_train[:, :2], y_train)\n",
-        "tabpfn = TabPFNClassifier().fit(X_train[:, :2], y_train)\n",
-        "\n",
-        "# Create a 2x2 subplot layout\n",
-        "fig, axes = plt.subplots(2, 2, figsize=(7, 7))\n",
-        "\n",
-        "# Plot Train Points\n",
-        "ax_points = axes[0, 0]\n",
-        "ax_points.set_title(\"Train points\")\n",
-        "ax_points.scatter(\n",
-        "    X_train[:, 0], X_train[:, 1], c=y_train, cmap=ListedColormap([\"#FF0000\", \"#0000FF\"])\n",
-        ")\n",
-        "\n",
-        "# Plot Random Forest\n",
-        "ax_rf = axes[0, 1]\n",
-        "plot_decision_boundary(ax_rf, rf, \"Random Forest\")\n",
-        "\n",
-        "# Plot XGBoost\n",
-        "ax_xgb = axes[1, 0]\n",
-        "plot_decision_boundary(ax_xgb, xgb, \"XGBoost\")\n",
-        "\n",
-        "# Plot TabPFN\n",
-        "ax_tabpfn = axes[1, 1]\n",
-        "plot_decision_boundary(ax_tabpfn, tabpfn, \"TabPFN\")\n",
-        "\n",
-        "# Adjust layout for better spacing\n",
-        "plt.tight_layout()\n",
-        "plt.show()"
+      "text/plain": [
+       "   Clothing ID  Age                    Title  \\\n",
+       "2         1077   60  Some major design flaws   \n",
+       "3         1049   50         My favorite buy!   \n",
+       "4          847   47         Flattering shirt   \n",
+       "5         1080   49  Not for the very petite   \n",
+       "6          858   39     Cagrcoal shimmer fun   \n",
+       "\n",
+       "                                         Review Text  Recommended IND  \\\n",
+       "2  I had such high hopes for this dress and reall...                0   \n",
+       "3  I love, love, love this jumpsuit. it's fun, fl...                1   \n",
+       "4  This shirt is very flattering to all due to th...                1   \n",
+       "5  I love tracy reese dresses, but this one is no...                0   \n",
+       "6  I aded this in my basket at hte last mintue to...                1   \n",
+       "\n",
+       "   Positive Feedback Count   Division Name Department Name Class Name  \n",
+       "2                        0         General         Dresses    Dresses  \n",
+       "3                        0  General Petite         Bottoms      Pants  \n",
+       "4                        6         General            Tops    Blouses  \n",
+       "5                        4         General         Dresses    Dresses  \n",
+       "6                        1  General Petite            Tops      Knits  "
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "if backend != \"client\":\n",
+    "    console.print(\n",
+    "        Panel(\n",
+    "            \"[bold yellow]Text data can only be processed through the TabPFN server. Please restart the notebook and select the 'client' backend to run this section.[/bold yellow]\",\n",
+    "            title=\"[bold yellow]Warning\",\n",
+    "            border_style=\"yellow\",\n",
+    "        )\n",
+    "    )\n",
+    "else:\n",
+    "    # We will use gdown to download the dataset\n",
+    "    !gdown --fuzzy \"17bJekFGIAxbrdcBeBIvcyZjneweY581E\"\n",
+    "\n",
+    "    # Load the clothing review dataset\n",
+    "    # We restrict to 500 rows to make the example faster\n",
+    "    df_text = pd.read_csv(\"cloth.csv\", index_col=0).dropna()[:500]\n",
+    "\n",
+    "    # Define features and target\n",
+    "    y_text = df_text[\"Rating\"]\n",
+    "    X_text = df_text.drop(columns=[\"Rating\"])\n",
+    "\n",
+    "    print(\"Text dataset loaded successfully!\")\n",
+    "    display(X_text.head())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "iQkFQD_rWi1v"
+   },
+   "source": [
+    "### Comparing Text Handling\n",
+    "\n",
+    "Now, let's compare how TabPFN handles text natively versus how a baseline model like RandomForest needs a specific text processing pipeline.\n",
+    "\n",
+    "For baselines, we will create a pipeline that converts strings to ordinal features.\n",
+    "\n",
+    "For TabPFN, we simply pass the raw data with the text column directly to the classifier."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 841
     },
+    "id": "ktXNMVFCsEHZ",
+    "outputId": "fa5bd253-55d1-48a6-a91b-670b78326586"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "8tvOmmiOOT4o"
-      },
-      "source": [
-        "## Sin Curve Fitting with Regression\n",
-        "\n",
-        "Next, we investigate the curve-fitting behavior of the different models on a sin curve."
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing: 100%|██████████| [00:01<00:00]\n",
+      "Processing: 100%|██████████| [00:01<00:00]\n",
+      "Processing: 100%|██████████| [00:01<00:00]\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:   18.4s finished\n",
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "Processing: 100%|██████████| [00:00<00:00]\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    8.4s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    2.0s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.8s finished\n",
+      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    9.2s finished\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "f_6wB1N2OrYu",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "f91662b0-c1cb-42b1-d4c0-5562492d4090"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 1400x1200 with 4 Axes>"
-            ],
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-          },
-          "metadata": {}
-        }
-      ],
-      "source": [
-        "# Toy function to generate data\n",
-        "def generate_sinx_plus_x(N):\n",
-        "    x = np.linspace(0, 20, N)\n",
-        "    y = np.sin(x) + x / 10\n",
-        "\n",
-        "    return x.reshape(-1, 1), y\n",
-        "\n",
-        "\n",
-        "# Utility function for plotting\n",
-        "def plot_predictions(ax, model, model_name):\n",
-        "    X_test = np.linspace(0, 20, 200).reshape(\n",
-        "        -1, 1\n",
-        "    )  # Predict for 200 points  between 0 and 20\n",
-        "    y_preds = model.predict(X_test)\n",
-        "    ax.set_title(model_name)\n",
-        "    ax.scatter(X_test, y_preds, label=\"Predictions\")\n",
-        "    ax.scatter(X_train, y_train, label=\"Train points\")\n",
-        "    ax.legend()\n",
-        "\n",
-        "\n",
-        "# Generate data\n",
-        "X_train, y_train = generate_sinx_plus_x(N=40)\n",
-        "\n",
-        "# Fit Models\n",
-        "rf = RandomForestRegressor(random_state=42).fit(X_train, y_train)\n",
-        "xgb = XGBRegressor(random_state=42).fit(X_train, y_train)\n",
-        "tabpfn = TabPFNRegressor()\n",
-        "tabpfn.fit(X_train, y_train)\n",
-        "\n",
-        "# Create a 2x2 subplot layout\n",
-        "fig, axs = plt.subplots(2, 2, figsize=(14, 12))\n",
-        "\n",
-        "# Plot train points\n",
-        "ax_points = axs[0, 0]\n",
-        "ax_points.set_title(\"Train points\")\n",
-        "ax_points.scatter(X_train, y_train, label=\"Train points\")\n",
-        "ax_points.legend()\n",
-        "\n",
-        "# Plot predictions for Random Forest\n",
-        "ax_rf = axs[0, 1]\n",
-        "plot_predictions(ax_rf, rf, \"Random Forest\")\n",
-        "\n",
-        "# Plot predictions for XGBoost\n",
-        "ax_xgb = axs[1, 0]\n",
-        "plot_predictions(ax_xgb, xgb, \"XGBoost\")\n",
-        "\n",
-        "# Plot predictions for TabPFN\n",
-        "ax_tabpfn = axs[1, 1]\n",
-        "plot_predictions(ax_tabpfn, tabpfn, \"TabPFN\")\n",
-        "\n",
-        "# Adjust layout for better spacing\n",
-        "plt.tight_layout()\n",
-        "plt.show()"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "if backend == \"client\":\n",
+    "    # Encode target labels to classes for baselines\n",
+    "    le = LabelEncoder()\n",
+    "    y_text = le.fit_transform(y_text)\n",
+    "\n",
+    "    # Define models\n",
+    "    models = [\n",
+    "        (\"TabPFN-Text\", TabPFNClassifier(random_state=42)),\n",
+    "        (\n",
+    "            \"TabPFN\",\n",
+    "            make_pipeline(\n",
+    "                column_transformer,  # string data needs to be encoded for model\n",
+    "                TabPFNClassifier(random_state=42),\n",
+    "            ),\n",
+    "        ),\n",
+    "        (\n",
+    "            \"RandomForest\",\n",
+    "            make_pipeline(\n",
+    "                column_transformer,  # string data needs to be encoded for model\n",
+    "                RandomForestClassifier(random_state=42),\n",
+    "            ),\n",
+    "        ),\n",
+    "        (\n",
+    "            \"XGBoost\",\n",
+    "            make_pipeline(\n",
+    "                column_transformer,  # string data needs to be encoded for model\n",
+    "                XGBClassifier(random_state=42),\n",
+    "            ),\n",
+    "        ),\n",
+    "        (\n",
+    "            \"CatBoost\",\n",
+    "            make_pipeline(\n",
+    "                column_transformer,  # string data needs to be encoded for model\n",
+    "                CatBoostClassifier(random_state=42, verbose=0),\n",
+    "            ),\n",
+    "        ),\n",
+    "    ]\n",
+    "\n",
+    "    # Calculate scores\n",
+    "    cv = StratifiedKFold(n_splits=3, random_state=42, shuffle=True)\n",
+    "    scoring = \"roc_auc_ovr\" if len(np.unique(y_text)) > 2 else \"roc_auc\"\n",
+    "    scores = {\n",
+    "        name: cross_val_score(\n",
+    "            model, X_text, y_text, cv=cv, scoring=scoring, n_jobs=1, verbose=1\n",
+    "        ).mean()\n",
+    "        for name, model in models\n",
+    "    }\n",
+    "\n",
+    "    # Plot results\n",
+    "    df = pd.DataFrame(list(scores.items()), columns=[\"Model\", \"ROC AUC\"])\n",
+    "    ax = df.plot(x=\"Model\", y=\"ROC AUC\", kind=\"bar\", figsize=(10, 6))\n",
+    "    ax.set_ylim(df[\"ROC AUC\"].min() * 0.995, min(1.0, df[\"ROC AUC\"].max() * 1.005))\n",
+    "    ax.set_title(\"Model Comparison - 5-fold Cross-validation\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "mTnMbG9vXHkL"
+   },
+   "source": [
+    "# Unsupervised Learning with TabPFN <a name=\"unsupervised-learning\"></a>\n",
+    "\n",
+    "TabPFN can also be used for unsupervised learning tasks like outlier detection and synthetic data generation. These features are available through the `tabpfn-extensions` library.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ghZddJXFa4zE"
+   },
+   "source": [
+    "### Data Generation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "npJnFdtTa_nS",
+    "outputId": "c2fbe9fd-e7c6-4e14-c2b2-198e2fea703e"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "XcYaJKT_Pw6T"
-      },
-      "source": [
-        "## Uncertainty of TabPFN / Quantile Regresison\n",
-        "\n",
-        "---\n",
-        "\n",
-        "\n",
-        "\n",
-        "TabPFN is trained to predict the distribution of the target variable and not just a single point. This is also the case for regression.\n",
-        "\n",
-        "As a result, we natively obtain uncertainty for the predictions of TabPFN (without the need for a new model or repeating models for different quantiles).\n",
-        "\n",
-        "In the following, we plot the uncertainty of TabPFN for a toy function with noise."
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 3/3 [00:05<00:00,  1.85s/it]\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "r5q1UBos4W1O"
-      },
-      "outputs": [],
-      "source": [
-        "### Code to generate the plot (feel free to ignore)\n",
-        "def plot_regression_uncertainty(ax, x, y_line, y_noisy, x_test, color_multiplier=5):\n",
-        "    all_quantiles = preds[\"quantiles\"]\n",
-        "    y = np.array(all_quantiles)  # shape of y: (9, number of samples)\n",
-        "\n",
-        "    # Calculate the maximum and minimum values in y\n",
-        "    y_max = np.max(y, axis=0)\n",
-        "    y_min = np.min(y, axis=0)\n",
-        "\n",
-        "    # Calculate the widths of each quantile bin\n",
-        "    quantile_bin_widths = np.diff(\n",
-        "        y, axis=0\n",
-        "    )  # shape of quantile_bin_widths: (8, number of samples)\n",
-        "\n",
-        "    # Normalize the bin widths for a given x\n",
-        "    per_x_normalized_bin_widths = (quantile_bin_widths) / (y_max - y_min)\n",
-        "\n",
-        "    # Plotting\n",
-        "    num_bins, num_data_points = (\n",
-        "        per_x_normalized_bin_widths.shape[0],\n",
-        "        per_x_normalized_bin_widths.shape[1],\n",
-        "    )\n",
-        "    rect_width = (\n",
-        "        x_test[1] - x_test[0]\n",
-        "    ).squeeze()  # assuming the x query points are equally spaced out\n",
-        "\n",
-        "    for i in range(num_data_points):\n",
-        "        for j in range(num_bins):\n",
-        "            quantile_bin_widths[j, i]\n",
-        "            rect = plt.Rectangle(\n",
-        "                xy=(x_test[i][0] - rect_width / 2, y[j, i]),\n",
-        "                width=rect_width,\n",
-        "                height=quantile_bin_widths[j, i],\n",
-        "                facecolor=plt.cm.viridis(\n",
-        "                    per_x_normalized_bin_widths[j, i] * color_multiplier\n",
-        "                ),\n",
-        "                edgecolor=\"none\",\n",
-        "            )\n",
-        "            ax.add_patch(rect)\n",
-        "\n",
-        "    # Set limits and labels\n",
-        "    ax.plot(x, y_line, label=\"True line\", color=\"blue\")\n",
-        "    ax.set_xlim(min(x_test) - 1, max(x_test) + 1)\n",
-        "    ax.set_ylim(np.min(y_noisy) - 1, np.max(y_noisy) + 1)\n",
-        "    ax.set_xlabel(\"X\")\n",
-        "    ax.set_ylabel(\"Y\")\n",
-        "\n",
-        "    # ax.plot(x, y, label='True line', color='blue')\n",
-        "    ax.scatter(x, y_noisy, label=\"Noisy data\", color=\"red\", s=10)\n",
-        "\n",
-        "    plt.title(\"TabPFN Regression Uncertainty\")\n",
-        "    plt.show()\n",
-        "\n",
-        "\n",
-        "# Generate Data\n",
-        "def generate_line_with_heteroscedastic_noise(\n",
-        "    m=0.8, num_points=200, x_start=0, x_end=100, noise_factor=0.1\n",
-        "):\n",
-        "    x = np.linspace(x_start, x_end, num_points)\n",
-        "    noise = np.random.randn(num_points)\n",
-        "    y = m * x\n",
-        "    y_noisy = y + (noise * noise_factor * x)\n",
-        "\n",
-        "    return x.reshape(-1, 1), y, y_noisy\n",
-        "\n",
-        "\n",
-        "def generate_line_with_heteroscedastic_noise_with_gap(\n",
-        "    m=0.8, num_points=200, x_start=0, x_end=100, noise_factor=0.1\n",
-        "):\n",
-        "    extra_points = num_points // 3\n",
-        "    x, y, y_noisy = generate_line_with_heteroscedastic_noise(\n",
-        "        m, num_points + extra_points, x_start, x_end, noise_factor\n",
-        "    )\n",
-        "    a = np.arange(num_points + extra_points)\n",
-        "    idx = np.where((a < num_points / 3) | (a > num_points / 3 + extra_points))\n",
-        "    return x[idx], y[idx], y_noisy[idx]\n",
-        "\n",
-        "\n",
-        "x, y_line, y_noisy = generate_line_with_heteroscedastic_noise_with_gap(0.8)\n",
-        "x_test = np.linspace(0, 100, 200).reshape(-1, 1)"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 935.75x750 with 12 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from tabpfn_extensions import unsupervised\n",
+    "from tabpfn_extensions.unsupervised import experiments\n",
+    "\n",
+    "# Load and prepare breast cancer dataset\n",
+    "df = load_breast_cancer(return_X_y=False)\n",
+    "X, y = df[\"data\"], df[\"target\"]\n",
+    "feature_names = df[\"feature_names\"]\n",
+    "\n",
+    "# Initialize TabPFN models\n",
+    "model_unsupervised = unsupervised.TabPFNUnsupervisedModel(\n",
+    "    tabpfn_clf=TabPFNClassifier(), tabpfn_reg=TabPFNRegressor()\n",
+    ")\n",
+    "\n",
+    "# Select features for synthetic data generation\n",
+    "# Example features: [mean texture, mean area, mean concavity]\n",
+    "feature_indices = [4, 6, 12]\n",
+    "\n",
+    "# Run synthetic data generation experiment\n",
+    "experiment = unsupervised.experiments.GenerateSyntheticDataExperiment(\n",
+    "    task_type=\"unsupervised\"\n",
+    ")\n",
+    "\n",
+    "results = experiment.run(\n",
+    "    tabpfn=model_unsupervised,\n",
+    "    X=torch.tensor(X),\n",
+    "    y=torch.tensor(y),\n",
+    "    attribute_names=feature_names,\n",
+    "    temp=1.0,  # Temperature parameter for sampling\n",
+    "    n_samples=X.shape[0] * 2,  # Generate twice as many samples as original data\n",
+    "    indices=feature_indices,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_aoNg2_K4k6E"
+   },
+   "source": [
+    "### Outlier detection"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "ezircAHiZSKG",
+    "outputId": "4c93610c-33a5-4dd1-ba43-6ba118c06942"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "xpvqsL1f4W1O"
-      },
-      "outputs": [],
-      "source": [
-        "reg = TabPFNRegressor()\n",
-        "reg.fit(x, y_noisy)\n",
-        "preds = reg.predict(x_test, output_type=\"full\")"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x600 with 3 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "from sklearn.datasets import load_breast_cancer\n",
+    "from tabpfn_extensions import unsupervised\n",
+    "from tabpfn_extensions.unsupervised import experiments\n",
+    "\n",
+    "# Load data\n",
+    "df = load_breast_cancer(return_X_y=False)\n",
+    "X, y = df[\"data\"], df[\"target\"]\n",
+    "attribute_names = df[\"feature_names\"]\n",
+    "\n",
+    "# Initialize models\n",
+    "clf = TabPFNClassifier(n_estimators=4)\n",
+    "reg = TabPFNRegressor(n_estimators=4)\n",
+    "model_unsupervised = unsupervised.TabPFNUnsupervisedModel(\n",
+    "    tabpfn_clf=clf, tabpfn_reg=reg\n",
+    ")\n",
+    "\n",
+    "# Run outlier detection\n",
+    "exp_outlier = unsupervised.experiments.OutlierDetectionUnsupervisedExperiment(\n",
+    "    task_type=\"unsupervised\"\n",
+    ")\n",
+    "results = exp_outlier.run(\n",
+    "    tabpfn=model_unsupervised,\n",
+    "    X=torch.tensor(X, dtype=torch.float32),\n",
+    "    y=torch.tensor(y),\n",
+    "    attribute_names=attribute_names,\n",
+    "    indices=[4, 12],  # Analyze features 4 and 12\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Qk6OxtxmJsr9"
+   },
+   "source": [
+    "### Missing value imputation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "9hgAlgghJuF3",
+    "outputId": "bc78fafc-f40e-4dfb-a2e8-9e3f7487d691"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "GwSCwFm-4W1O",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "05fa4741-b689-4438-8000-40e7ae886f4f"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 1200x600 with 2 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
-      ],
-      "source": [
-        "fig = plt.figure(figsize=(12, 6))\n",
-        "\n",
-        "# Plot the original data\n",
-        "ax = fig.add_subplot(121)\n",
-        "ax.plot(x, y_line, label=\"True line\", color=\"blue\")\n",
-        "ax.scatter(x, y_noisy, label=\"Noisy data\", color=\"red\", s=10)\n",
-        "ax.set_xlabel(\"X\")\n",
-        "ax.set_ylabel(\"Y\")\n",
-        "ax.set_xlim(min(x) - 1, max(x) + 1)\n",
-        "ax.set_ylim(np.min(y_noisy) - 1, np.max(y_noisy) + 1)\n",
-        "ax.set_title(\"Heteroscedastic Noise along a Sloping Line\")\n",
-        "ax.legend()\n",
-        "\n",
-        "# plot the uncertainty estimates obtained from TabPFN\n",
-        "ax = fig.add_subplot(122)\n",
-        "plot_regression_uncertainty(ax, x, y_line, y_noisy, x_test, color_multiplier=5)"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Introduced 168 missing values into the test set.\n",
+      "       0      1       2\n",
+      "0    NaN  18.60   81.09\n",
+      "1  18.94    NaN  123.60\n",
+      "2  15.46  19.48  101.70\n",
+      "3  12.40    NaN   81.47\n",
+      "4    NaN  14.44     NaN\n",
+      "Fitting the unsupervised model on the training data...\n",
+      "Imputing missing values...\n",
+      "\n"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "VJMcv-KvPYIh"
-      },
-      "source": [
-        "# Time Series Forecasting <a name=\"timeseries\"></a>\n",
-        "\n",
-        "TabPFN can be used for time series prediction, following the work of Hoo et al. (Zero-Shot Time Series Forecasting with TabPFNv2; https://arxiv.org/abs/2501.02945v3).\n",
-        "\n",
-        "In this demo, we will use the time series dataset from [Chronos Dataset](https://huggingface.co/datasets/autogluon/chronos_datasets) on HuggingFace. Also, we'll keep it short and work with just 2 time series from the dataset.\n",
-        "\n",
-        "Feel free to explore other datasets by using the dataset names from Chronos Dataset on HuggingFace or even use time series data of your own problem.\n"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 3/3 [00:11<00:00,  3.88s/it]"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "Z3wiT00Uf0dF"
-      },
-      "source": [
-        "## *Installation*"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "------------------------\n",
+      "\n",
+      "Number of missing values after imputation: 0\n",
+      "           0          1           2\n",
+      "0  12.515228  18.600000   81.089996\n",
+      "1  18.940001  21.109259  123.599998\n",
+      "2  15.460000  19.480000  101.699997\n",
+      "3  12.400000  17.477161   81.470001\n",
+      "4  11.358663  14.440000   74.500938\n",
+      "Mean Squared Error of imputed values vs. original values: 0.4940\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "J0cUKia3fzrz"
-      },
-      "outputs": [],
-      "source": [
-        "!uv pip install tabpfn-time-series\n",
-        "raise ValueError(\n",
-        "    \"Make sure to restart the session before proceeding, otherwise errors will follow (Runtime > Restart Session)\"\n",
-        ")"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# --- 1. Load and Prepare Data ---\n",
+    "# Load the breast cancer dataset\n",
+    "df = load_breast_cancer(return_X_y=False)\n",
+    "X, y = df[\"data\"], df[\"target\"]\n",
+    "\n",
+    "# Split the data into training and testing sets\n",
+    "X_train, X_test = train_test_split(\n",
+    "    X,\n",
+    "    test_size=0.33,\n",
+    "    random_state=42,\n",
+    ")\n",
+    "\n",
+    "# --- 2. Introduce Missing Values ---\n",
+    "# Create a copy of the test set to introduce missing values (NaNs)\n",
+    "X_test_missing = X_test.copy()\n",
+    "n_samples, n_features = X_test_missing.shape\n",
+    "\n",
+    "# Introduce missing values in the first three columns for demonstration\n",
+    "missing_fraction = 0.3\n",
+    "n_missing = int(n_samples * missing_fraction)\n",
+    "\n",
+    "for col_idx in range(3):\n",
+    "    # Choose random rows to set to NaN\n",
+    "    missing_indices = np.random.choice(n_samples, n_missing, replace=False)\n",
+    "    X_test_missing[missing_indices, col_idx] = np.nan\n",
+    "\n",
+    "print(f\"Introduced {np.isnan(X_test_missing).sum()} missing values into the test set.\")\n",
+    "print(pd.DataFrame(X_test_missing[:, 0:3]).head())\n",
+    "\n",
+    "# --- 3. Initialize the Unsupervised Model ---\n",
+    "# Initialize TabPFN models for regression and classification tasks.\n",
+    "# The unsupervised model uses these to model the data distribution.\n",
+    "clf = TabPFNClassifier(n_estimators=3)\n",
+    "reg = TabPFNRegressor(n_estimators=3)\n",
+    "\n",
+    "# Initialize the main unsupervised model\n",
+    "model_unsupervised = unsupervised.TabPFNUnsupervisedModel(\n",
+    "    tabpfn_clf=clf,\n",
+    "    tabpfn_reg=reg,\n",
+    ")\n",
+    "\n",
+    "# --- 4. Fit and Impute ---\n",
+    "# Fit the model on the complete training data (without missing values)\n",
+    "print(\"Fitting the unsupervised model on the training data...\")\n",
+    "model_unsupervised.fit(X_train)\n",
+    "\n",
+    "# Perform imputation on the test set\n",
+    "print(\"Imputing missing values...\\n\")\n",
+    "X_imputed_tensor = model_unsupervised.impute(\n",
+    "    X_test_missing,\n",
+    "    n_permutations=5,  # Fewer permutations for a quicker example\n",
+    ")\n",
+    "\n",
+    "print(\"\\n------------------------\")\n",
+    "\n",
+    "# --- 5. Verify Results ---\n",
+    "# Check that the imputed data no longer contains any NaN values\n",
+    "n_missing_after = torch.isnan(X_imputed_tensor).sum().item()\n",
+    "\n",
+    "print(f\"\\nNumber of missing values after imputation: {n_missing_after}\")\n",
+    "print(pd.DataFrame(X_imputed_tensor[:, 0:3]).head())\n",
+    "\n",
+    "# Optional: Calculate the Mean Squared Error for the imputed values,\n",
+    "# since we know the original ground truth values.\n",
+    "original_nan_mask = np.isnan(X_test_missing)\n",
+    "imputed_values = X_imputed_tensor.numpy()[original_nan_mask]\n",
+    "original_values = X_test[original_nan_mask]\n",
+    "\n",
+    "mse = np.mean((imputed_values - original_values) ** 2)\n",
+    "print(f\"Mean Squared Error of imputed values vs. original values: {mse:.4f}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "MqZlQ09WfCe9"
+   },
+   "source": [
+    "# Model Interpretability <a name=\"interpretability\"></a>\n",
+    "\n",
+    "Understanding *why* a model makes certain predictions is crucial for building trust and for debugging. The `tabpfn-extensions` library provides tools for model interpretability. We'll look at SHAP (SHapley Additive exPlanations) values, which show the impact of each feature on a specific prediction."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "6RYILEoPXaMZ"
+   },
+   "source": [
+    "### Shapley Values\n",
+    "\n",
+    "Next, we'll use SHAP to understand our model's predictions. SHAP values break down a prediction to show the contribution of each feature, helping us see which factors are most influential for a given data point.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
     },
+    "id": "8CJtLwWUe-KV",
+    "outputId": "d743c96e-c69b-401d-8571-9ceb8e9ba2b9"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "kNOAk5sPHS_3"
-      },
-      "source": [
-        "## Load Time Series Data\n",
-        "\n",
-        "In this demo, we will use the time series dataset from [Chronos Dataset](https://huggingface.co/datasets/autogluon/chronos_datasets) on HuggingFace. Also, we'll keep it short and work with just 2 time series from the dataset.\n",
-        "\n",
-        "Feel free to explore other datasets by using the dataset names from Chronos Dataset on HuggingFace or even use time series data of your own problem."
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "PermutationExplainer explainer: 26it [02:02,  5.10s/it]\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "qgHudyQdHS_3"
-      },
-      "outputs": [],
-      "source": [
-        "dataset_metadata = {\n",
-        "    \"monash_tourism_monthly\": {\"prediction_length\": 24},\n",
-        "    \"m4_hourly\": {\"prediction_length\": 48},\n",
-        "}\n",
-        "\n",
-        "dataset_choice = \"monash_tourism_monthly\"\n",
-        "num_time_series_subset = 2"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x650 with 1 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 217,
-          "referenced_widgets": [
-            "8af3e44759a84b24923e15c7722b8518",
-            "879a16d4635a447b85a81ae72df23f67",
-            "6387bc83be594ddcb9869a991df66659",
-            "0ef1661193d44ef99f7e281cb79c40b5",
-            "38d0e7f682cd45b193066630854b3329",
-            "30bea92a5ae940428e1f3f534611309e",
-            "a1292ad49a5b49c582f15ade36b78282",
-            "5029e0c3a04c418c9f2284c505cfa52e",
-            "41ef74f05a894e2ab10dde4e6d4c49da",
-            "b15054c98fd8457095b01a54ad491056",
-            "e4a2681db14a43a6836f0fd3ab154509",
-            "e0ce26fdeefc4061879dbd285a3ec436",
-            "7e13c9b09413417b9d2cb7af278a46fe",
-            "12a2a205bd944f8e8a3643f977c38b56",
-            "758dc947f2dc4db1b28f427add34f4c6",
-            "b7227f27d0c341419b87360437ea2132",
-            "769284272f1545a5b3dafa71d2b9439d",
-            "0c458dab93ee415f839fd216d33b43d9",
-            "96db2596e70f4e809832e39642b8af99",
-            "614ab8ceb45245cf8d11dcb576b3e27d",
-            "bcd4f57966ce4cd594bce97f564dfbfc",
-            "73584ad402334131a9b7f96d13a086a4",
-            "e369aa70fe3d4923ae127eab8a8d1490",
-            "f42b869e3b994141b0c81dcffc39c042",
-            "498eb04a0a594e87af9c566e2878e515",
-            "a93d570f7c4547288f6257d8221593be",
-            "78a9d6c24bf0436fb7184a1ac46f8593",
-            "769f504e490449dd952edf304ea53a76",
-            "92834505829e49cd99d1ad420bddf0d1",
-            "88b6a04a2d974027a9936cb9bb84eac0",
-            "5975c2b92d634044b794d793aeb4d52f",
-            "894db0aa656e4882b2117d1ac8398be5",
-            "1d7a439caf5a462e81e67f8cc9b2a998"
-          ]
-        },
-        "id": "Qc1mHevjHS_4",
-        "outputId": "395ee836-630b-45dd-ba5f-5024aa43cc73"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
-            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
-            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
-            "You will be able to reuse this secret in all of your notebooks.\n",
-            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
-            "  warnings.warn(\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "README.md: 0.00B [00:00, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "8af3e44759a84b24923e15c7722b8518"
-            }
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "monash_tourism_monthly/train-00000-of-00(…):   0%|          | 0.00/335k [00:00<?, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "e0ce26fdeefc4061879dbd285a3ec436"
-            }
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "Generating train split:   0%|          | 0/366 [00:00<?, ? examples/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "e369aa70fe3d4923ae127eab8a8d1490"
-            }
-          },
-          "metadata": {}
-        }
-      ],
-      "source": [
-        "from datasets import load_dataset\n",
-        "from tabpfn_time_series import TimeSeriesDataFrame\n",
-        "from tabpfn_time_series.data_preparation import generate_test_X, to_gluonts_univariate\n",
-        "\n",
-        "prediction_length = dataset_metadata[dataset_choice][\"prediction_length\"]\n",
-        "dataset = load_dataset(\"autogluon/chronos_datasets\", dataset_choice)\n",
-        "\n",
-        "tsdf = TimeSeriesDataFrame(to_gluonts_univariate(dataset[\"train\"]))\n",
-        "tsdf = tsdf[\n",
-        "    tsdf.index.get_level_values(\"item_id\").isin(tsdf.item_ids[:num_time_series_subset])\n",
-        "]\n",
-        "train_tsdf, test_tsdf_ground_truth = tsdf.train_test_split(\n",
-        "    prediction_length=prediction_length\n",
-        ")\n",
-        "test_tsdf = generate_test_X(train_tsdf, prediction_length)"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/lib/python3.12/dist-packages/tabpfn_extensions/interpretability/shap.py:137: FutureWarning: The NumPy global RNG was seeded by calling `np.random.seed`. In a future version this function will no longer use the global RNG. Pass `rng` explicitly to opt-in to the new behaviour and silence this warning.\n",
+      "  shap.summary_plot(shap_values=shap_values, show=False)\n"
+     ]
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "cKH8WtXdHS_4"
-      },
-      "source": [
-        "Let's take a look at the time series data."
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x950 with 2 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 607
-        },
-        "id": "jOm8_GLEHS_4",
-        "outputId": "cbffcec8-67f1-40e1-8d66-1aab471e9f32"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 1000x600 with 2 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
-      ],
-      "source": [
-        "from tabpfn_time_series.plot import plot_actual_ts\n",
-        "\n",
-        "plot_actual_ts(train_tsdf, test_tsdf_ground_truth)"
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 750x500 with 3 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from tabpfn_extensions import interpretability\n",
+    "\n",
+    "# Load example dataset\n",
+    "data = load_breast_cancer()\n",
+    "X, y = data.data, data.target\n",
+    "feature_names = data.feature_names\n",
+    "n_samples_test, n_samples_train = 25, 50\n",
+    "\n",
+    "# Split data\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5)\n",
+    "\n",
+    "# Initialize and train model\n",
+    "clf = TabPFNClassifier()\n",
+    "clf.fit(X_train[:n_samples_train], y_train[:n_samples_train])\n",
+    "\n",
+    "# Calculate SHAP values\n",
+    "shap_values = interpretability.shap.get_shap_values(\n",
+    "    estimator=clf,\n",
+    "    test_x=X_test[:n_samples_test],\n",
+    "    attribute_names=feature_names,\n",
+    "    algorithm=\"permutation\",\n",
+    ")\n",
+    "\n",
+    "# Create visualization\n",
+    "fig = interpretability.shap.plot_shap(shap_values)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Zt05caATl2Cc"
+   },
+   "source": [
+    "### Embeddings\n",
+    "\n",
+    "This example demonstrates how to extract embeddings from TabPFN models and use them\n",
+    "for classification and regression tasks.\n",
+    "\n",
+    "NOTE: This example requires the full TabPFN implementation (pip install tabpfn).\n",
+    "It will not work with the TabPFN client (pip install tabpfn-client) because\n",
+    "the embedding functionality is not available in the client version.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "nj8XPK35l4z1"
+   },
+   "outputs": [],
+   "source": [
+    "if backend == \"client\":\n",
+    "    console.print(\n",
+    "        Panel(\n",
+    "            \"[bold yellow]Text data can only be processed through the TabPFN server. Please restart the notebook and select the 'client' backend to run this section.[/bold yellow]\",\n",
+    "            title=\"[bold yellow]Warning\",\n",
+    "            border_style=\"yellow\",\n",
+    "        )\n",
+    "    )\n",
+    "else:\n",
+    "    import matplotlib.pyplot as plt\n",
+    "    import numpy as np\n",
+    "    import pandas as pd\n",
+    "    import seaborn as sns\n",
+    "    from sklearn.datasets import load_breast_cancer, load_diabetes\n",
+    "    from sklearn.linear_model import LinearRegression, LogisticRegression\n",
+    "    from sklearn.manifold import TSNE\n",
+    "    from sklearn.metrics import accuracy_score, r2_score\n",
+    "    from sklearn.model_selection import train_test_split\n",
+    "    from tabpfn_extensions import TabPFNClassifier, TabPFNRegressor\n",
+    "    from tabpfn_extensions.embedding import TabPFNEmbedding\n",
+    "\n",
+    "    # Load and evaluate classification dataset\n",
+    "    print(\"Loading classification dataset (breast cancer)...\")\n",
+    "    df = load_breast_cancer(return_X_y=False)\n",
+    "    X, y = df[\"data\"], df[\"target\"]\n",
+    "    attribute_names = df[\"feature_names\"]\n",
+    "\n",
+    "    # Split the data\n",
+    "    X_train, X_test, y_train, y_test = train_test_split(\n",
+    "        X,\n",
+    "        y,\n",
+    "        test_size=0.5,\n",
+    "        random_state=42,\n",
+    "    )\n",
+    "\n",
+    "    # Train and evaluate vanilla logistic regression\n",
+    "    model = LogisticRegression(\n",
+    "        max_iter=10000,\n",
+    "        random_state=42,\n",
+    "    )\n",
+    "    model.fit(X_train, y_train)\n",
+    "    print(\n",
+    "        f\"Baseline Logistic Regression Accuracy: {accuracy_score(y_test, model.predict(X_test)):.4f}\",\n",
+    "    )\n",
+    "\n",
+    "    # Train and evaluate TabPFN embeddings (vanilla)\n",
+    "    clf = TabPFNClassifier(n_estimators=1, random_state=42)\n",
+    "    embedding_extractor = TabPFNEmbedding(tabpfn_clf=clf, n_fold=0)\n",
+    "    train_embeddings = embedding_extractor.get_embeddings(\n",
+    "        X_train,\n",
+    "        y_train,\n",
+    "        X_test,\n",
+    "        data_source=\"train\",\n",
+    "    )\n",
+    "    test_embeddings = embedding_extractor.get_embeddings(\n",
+    "        X_train,\n",
+    "        y_train,\n",
+    "        X_test,\n",
+    "        data_source=\"test\",\n",
+    "    )\n",
+    "\n",
+    "    model = LogisticRegression(\n",
+    "        max_iter=10000,\n",
+    "        random_state=42,\n",
+    "    )\n",
+    "    model.fit(train_embeddings[0], y_train)\n",
+    "    y_pred = model.predict(test_embeddings[0])\n",
+    "    print(\n",
+    "        f\"Logistic Regression with TabPFN (Vanilla) Accuracy: {accuracy_score(y_test, y_pred):.4f}\",\n",
+    "    )\n",
+    "\n",
+    "    # Note: Using test_embeddings and y_test from your original script.\n",
+    "    # The embeddings have shape (n_splits, n_samples, n_features), so we use the first split [0].\n",
+    "    test_only_embeddings = test_embeddings[0]\n",
+    "\n",
+    "    # Apply t-SNE to reduce the TEST embeddings to 2 dimensions.\n",
+    "    # The number of samples in the test set is len(y_test). Perplexity must be less than that.\n",
+    "    # We'll set perplexity to 30, which is suitable for this dataset size.\n",
+    "    print(\"\\nApplying t-SNE for visualization on the TEST SET only...\")\n",
+    "    tsne = TSNE(n_components=2, random_state=42, perplexity=10)\n",
+    "    embeddings_2d = tsne.fit_transform(test_only_embeddings)\n",
+    "\n",
+    "    # Create a DataFrame for easy plotting\n",
+    "    df_plot = pd.DataFrame(\n",
+    "        {\n",
+    "            \"t-SNE-1\": embeddings_2d[:, 0],\n",
+    "            \"t-SNE-2\": embeddings_2d[:, 1],\n",
+    "            \"label\": y_test,\n",
+    "        }\n",
+    "    )\n",
+    "\n",
+    "    # Plot the 2D embeddings for the test set\n",
+    "    plt.figure(figsize=(9, 7))\n",
+    "    sns.scatterplot(\n",
+    "        data=df_plot,\n",
+    "        x=\"t-SNE-1\",\n",
+    "        y=\"t-SNE-2\",\n",
+    "        hue=\"label\",  # Color points by their class label\n",
+    "        palette=\"viridis\",\n",
+    "        alpha=0.9,\n",
+    "        s=80,\n",
+    "    )\n",
+    "\n",
+    "    plt.title(\"t-SNE Visualization of TabPFN Embeddings (Test Set Only)\")\n",
+    "    plt.xlabel(\"t-SNE Dimension 1\")\n",
+    "    plt.ylabel(\"t-SNE Dimension 2\")\n",
+    "    plt.legend(title=\"Class\")\n",
+    "    plt.grid(True, linestyle=\"--\", alpha=0.6)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "PkphS4vSFNvg"
+   },
+   "source": [
+    "### Feature selection\n",
+    "\n",
+    "Feature selection is the process of selecting a subset of relevant features for use in model construction. It's useful for reducing model complexity, improving performance by removing noise, and decreasing training time. Here, we'll use Sequential Forward Selection (SFS), which starts with no features and iteratively adds the feature that most improves the model's performance.\n",
+    "\n",
+    "The goal is to see if we can create a simpler, faster model with fewer features without a significant drop in accuracy.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "GPJtNDLnFPPW"
+   },
+   "outputs": [],
+   "source": [
+    "from tabpfn_extensions import interpretability\n",
+    "\n",
+    "# Load data\n",
+    "data = load_breast_cancer()\n",
+    "X, y = data.data, data.target\n",
+    "feature_names = data.feature_names\n",
+    "\n",
+    "# Initialize model\n",
+    "clf = TabPFNClassifier(n_estimators=1)\n",
+    "\n",
+    "# Feature selection\n",
+    "sfs = interpretability.feature_selection.feature_selection(\n",
+    "    estimator=clf, X=X, y=y, n_features_to_select=4, feature_names=feature_names\n",
+    ")\n",
+    "\n",
+    "# Print selected features\n",
+    "selected_features = [\n",
+    "    feature_names[i] for i in range(len(feature_names)) if sfs.get_support()[i]\n",
+    "]\n",
+    "print(\"\\nSelected features:\")\n",
+    "for feature in selected_features:\n",
+    "    print(f\"- {feature}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "lmPJW5NSK7ut"
+   },
+   "source": [
+    "# Predictive Behavior of TabPFN <a name=\"behavior\"></a>\n",
+    "\n",
+    "In this section, we explore the behavior of predictions from TabPFN on various toy functions."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ZBeID4YeMQ9L"
+   },
+   "source": [
+    "## Decision Boundary during Classification\n",
+    "\n",
+    "First, let us inspect the decision boundary for different classifiers.\n",
+    "The decision bounds show how smoothly a model learns to transition between classes and how well it fits the data.\n",
+    "\n",
+    "In the first cell, we create the data and code to plot the decision boundary. The second cell then generates the plot."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "B5a_ia0OLOxG"
+   },
+   "outputs": [],
+   "source": [
+    "from matplotlib.colors import ListedColormap\n",
+    "from sklearn.inspection import DecisionBoundaryDisplay\n",
+    "\n",
+    "\n",
+    "# Toy functions that generate the data\n",
+    "def generate_circle(n_datapoints, radius, noise_factor):\n",
+    "    angles = np.linspace(0, 2 * np.pi, n_datapoints).T\n",
+    "    x = radius * np.cos(angles) + np.random.randn(n_datapoints) * noise_factor\n",
+    "    y = radius * np.sin(angles) + np.random.randn(n_datapoints) * noise_factor\n",
+    "\n",
+    "    return np.stack([x, y]).T\n",
+    "\n",
+    "\n",
+    "def generate_concentric_cirlces(radii, num_points_per_circle, noise_factor=1 / 15):\n",
+    "    circles = []\n",
+    "    for r, num_points in zip(radii, num_points_per_circle):\n",
+    "        circles.append(generate_circle(num_points, r, noise_factor))\n",
+    "\n",
+    "    return np.vstack(circles)\n",
+    "\n",
+    "\n",
+    "def generate_circle_data(num_points_per_circle, radii, noise_factor):\n",
+    "    radii = np.array(radii)\n",
+    "    circles_1 = generate_concentric_cirlces(radii, num_points_per_circle, noise_factor)\n",
+    "    circles_1 = np.hstack([circles_1, np.zeros((sum(num_points_per_circle), 1))])\n",
+    "\n",
+    "    circles_2 = generate_concentric_cirlces(\n",
+    "        radii + 0.3, num_points_per_circle, noise_factor\n",
+    "    )\n",
+    "    circles_2 = np.hstack([circles_2, np.ones((sum(num_points_per_circle), 1))])\n",
+    "\n",
+    "    circles = np.vstack([circles_1, circles_2])\n",
+    "    X, y = circles[:, :2], circles[:, 2]\n",
+    "    return X, y\n",
+    "\n",
+    "\n",
+    "# Generate the data\n",
+    "X_train, y_train = generate_circle_data(\n",
+    "    num_points_per_circle=[50, 100, 200], radii=[1, 2, 4], noise_factor=0.1\n",
+    ")\n",
+    "\n",
+    "\n",
+    "# Function for plotting\n",
+    "def plot_decision_boundary(ax, model, model_name):\n",
+    "    cmap = ListedColormap([\"#FF0000\", \"#0000FF\"])\n",
+    "    ax.set_title(model_name)\n",
+    "    DecisionBoundaryDisplay.from_estimator(\n",
+    "        model,\n",
+    "        X_train[:, :2],\n",
+    "        alpha=0.6,\n",
+    "        ax=ax,\n",
+    "        eps=0.2,\n",
+    "        grid_resolution=50,\n",
+    "        response_method=\"predict_proba\",\n",
+    "        cmap=plt.cm.RdBu,\n",
+    "    )\n",
+    "    ax.scatter(X_train[:, 0], X_train[:, 1], c=y_train > 0, cmap=cmap)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 707
     },
+    "id": "wzrSEZR5LYlf",
+    "outputId": "3ba2abe5-4fe4-465e-daea-c86d239f79ea"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "UWmQq17tHS_4"
-      },
-      "source": [
-        "## Adding Features\n",
-        "\n",
-        "In our paper, we propose adding `Running Index`, `Calendar Features`, and `Auto Seasonal Features` to the table.\n",
-        "\n",
-        "**Feel free to experiment with your own features!**\n",
-        "\n",
-        "To do that, simply define your own feature functions and pass them to the `FeatureTransformer`."
+     "data": {
+      "image/png": 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qB465Zu3atcVes9vtokGDBqJBgwbCZrMJTdPEa6+9JurUqSMsFou4+OKLxU8//VTm+e+HH34QzZo1ExaLRTRv3lzMnj27WJ9CCJGZmSkefvhhkZSUJEwmk2jUqJF46623hKZpxY4xevRot22+xrRs2bKg0lX5u06uLFmyRHTp0kWEhoaKqKgocc0114jt27e7tXGk2Dp9+rTXPn744QfRtWtXER4eLsLDw0XTpk3F6NGjxa5du4QQQuzfv1+MGDFCNGjQQISEhIgqVaqInj17iiVLlrj1s3PnTtG9e3cRGhoqAD3d1jlGEaISRcPo6FQgU6dOZfjw4axdu7ZCShzq6Ojo6OjonD10n1gdHR0dHR0dHZ3zDl3E6ujo6Ojo6OjonHfoIlZHR0dHR0dHR+e8Q/eJ1dHR0dHR0dHROe/QLbE6Ojo6Ojo6OjrnHbqI1dHR0dHR0dHROe+o1MUONE3j2LFjREZG6qXedHR0Kh1CCGfJzqioqPNmntLnVh0dncqMY25NSkpCVX3bWyu1iD127Bi1atU618PQ0dHRCUh6ejpRUVHnehhBoc+tOjo65wOHDx+mZs2aPl+v1CI2MjISkCdxvtwcdHR0/jtkZGRQq1YtDh8+7JyvzgccYx35+ndYQsLO8Wh0LnRys0wc2FqFgnyVmMQ8ajdJxY9xTec8Y/uJTK7s3sRt26/Ld9G8WunnxPy8HKY8dUPAebVSi1jHMldUVJQuYnV0dCot55MrARTNrZaQMCyh4ed4NDoXKpodlsxoyOa/qiM0BUUBIRQiYvLpN2wndZqlnesh6pQDphA7oeGRHtvKZ24JNK9WahGro6Ojo6OjU4S1QKUgz0BouBXVcK5HU4Rmh0O7YslKNRMeZcUSZmX+J83JTLUAUog4Enpmp5v5fkIrbn58I0n1Ms/doHXOe3QRq6Ojo6OjU8k5+W8EK3+uzb5N8QihYLbYaNX1BB37HSIswnZOx7Z7QzxLZjQkO93istWRgr64JU0IBTRY8WNdbnhoy1kZo86FiS5idXR0dHR0KjGHdsTw/YRWCFEoAIGCfCMbltVg76Y4bn3yH8KjrCXutyBPZdOfSWxaXp3MVAsh4VZadT7JxT2Peu1PCNi3OY6Ny6uTcjwMc6idhJpZbF9d1ccRfC8FC6FwcHssuVlGQs+xCNc5f9FFrI6Ojo6OTiXFblf46bNmCE1xClgHQlPISLHwx+z69Bu2y7k9P9fA5r+qs3VVVXIyzETH5XFRt+M0v/QkRpO0kOZlG/n27dYkHw8vXOZXyEozsHphbTb/VY2bn9hIbEKes09NgwWfN2XH2qooqobQVEBw+ojD79FTsAbjI66Ql23SRaxOqdFFrI6Ojo6OTiVl3+Yq5GSafb4uNJUdfydy+ZC9hITZyUw1881bbchIDilsoZCTZeL4wUg2/1WdIWM2Yw6xs3RWA5JPhHsVxtmZJuZOasHwF9Y7t69bUpMdaxOdx3T0XRZUVSM8uqBMfeRlG9m8oho71yaSn2skrno2bbofp17LFM6jWEudUqKLWB0dwGaD+fNhxgxITYVGjeDuu6FNm3M9Mh0dnf8yZ46Fo6oamuY7J5VmV0k/E0pI7Sxmvtu6UMC6KLhCoXriYCTLvq9PtwEH2PF3IkLzofKEypljEXz/QUsG3LcN1SBYt8R3rs7SoCiCpu1OYzBpJB8Pw26TYzGYNGITc50puIQGB7fHcupIBAajRv1WKVSpmgtAyslQZrzdmuxMc6ELrkJ6soV9m+NpfukJ+g7bpafyusDRRazOf56DB6FHDzh0iMIUMLBsGUyaBA8/DO+8g/5Er6Ojc04wmbVi1lJvGM12VvxYh9RTvvP+CqGwdWU16rdM8SuKHRzYVoVfpzeiU/9/PYK2yorAEmYjPLqAj57oSG6Wu6U5PCqf9lceoUbDdOZ/3JyMlBAUVQOhsOy7hjRsfZq+Q3cxe2JLcrJMTpEORVbi7Wuqklgrm/ZXHCnHcetUNnQRq1NhFBTAvHmwezdERsKAAVC79rkd04EDMGUK/PUXGAxQpYocoyP1i+O3rdBFa/x4qF8f7r//3IxXR0fnv4PdrpCTYcJg0pwZBxq2OcPv3zfws5cgJiGXqCp5/L04sLVUs6uknQ4J2E6isG1VNVp1PhFk++CIT8omMjaftYtr4s0lITvDzO/f10dRhdNaLFxE974t8cx4J5TUk/4LdaxbUpO2vY7o1tgLGF3E6lQIP/8MQ4dCcjIYjTIoYMwYuOsu+PBDMPt28fLLhg2wbp3c/4oroEYN321tNli5ElJSoF492LpVjgnAbg/+mG+8AffdJ0Wvjo6OTrAU5Kns3xpHXo6RmPg8ajf1XqnKWqCyekFtNi5PIi/bBEC1Ohl07PsvcdVzqNsimYPbquDdB1Wh89WHOLi9CraC4G7pcdVyMFtsFOQHbq8ocPxgFBHR+WSlm32MIRCisC9Bh6v+pUb9TGZPbOXvqHIvH+4OQlM4fTQCRdEQwpdCVchKszD3oxa07HyChhclV6q8ujrlgy5idcqdP/+E666TwhWKrJoAn30mLbRTp7rvk5wMixZBTg60agUdOrgv4e/ZA7fcIgWsA1WFW2+FyZMhzOOBfOpUeOYZOH687Odz5Ajs2gXNm5e9Lx0dnQsfIeDvRbVY9XMdrAUGpIhTiIzNo8/tu6nXItXZ1lqgMvPdizhxMMrNbeDEv5HMndzS+beiCIQARdGcla9QoPvA/bToeIpNy6sHOzrSw49Qq0MI+/5sREBRqgiOJtuo0WEvuxb7mgRFgH4ULBF5dL3vD8zhBfw5vUMAARoEigjKzWLf5jj2bY4nIiaPyJh8MlJDCAmz0aLjSS7qdpzQcD0zQmnYejzD+f9+Pc/dzVEXsTrlzgsvyN+OpXlXNA2+/BL+9z8ZPGW1wuOPS/9Tq0tawpYtYdo0aN1aCtEuXWTAlWdf06fDiRNSADtE70cfwahR5XtOBWULoOX4cfj1V9nPJZdA27blMy4dHZ3Kx+oFtfnrx3ouW+TklJlm4YcPWzFkzCZqN0kHYMPSGsUELODm5wmO/LAC1SCo1yKF6vUyadnpJBExBWw9nkEKwbsIdG/XnKuvtPP52Cw2/+m/Nr3QVLpeFk3dDmnMtmWweVk0BmzYMQIaKgIjNqwYED4khRErV/A7N8UcZX/bLqyeEls2AQvOQK7AyDZZaSFkpcnqYdnpZv6cW48NS2tw0+PuqcR0vOMqWh34E6/9ejZnwbLttKweVZHD0kWsTvly+rQMivKHwQAzZ8Kzz8KQITB3bvE2O3ZAt26wfj188ol0CfDmAqBpsHgxPP88vPwyZGXBY4+Vy6k4CQ+XgtsfQkhrss0GiYk4lwxzc6U/7Zdfuo+/bVspwJs0Kd+x6ujonFtys42s/LmO9xeFghCCRV83pvfNe9m6siq7/0nw+sDvHQW7TWXfljiqtNnDwdxkkIH63DYink3fa1jzFQKJu7QsKw13/MbkKqt4IPFJ1p9q5n0fRRAarlG7bTqDLknihgkp7L/odqZod7OdZsSQzs18Sywp3MXnPo9nw8SYrDe5/H/LSLnxFmbGf0Hq8UDW22ApST+K87cQkJ1pYt7kFgx9dn2pg3e9ibuKFm5nk8picfWFLmJ1ypW0tMBtVFW2+/JL7wIWpODLzYXXXoOffgrsw/rKKxAVBVWrSpeE8kJVoU8fuOMOWL1aimSLBRo2lCm4br4Z5syB11+HzZvlPjVqwAMPyMwGgwfDwoVFrhUONm6U1uVNm/z79eroBOL111/n6aef5qGHHuK9994718P5z7Pnn3g0u/+l9bTTYXz/wUWABpTUIqkgNNjyw6W88sMhzCFFCrjbdeksnRXrZ19B1YgsXh/ZGlOBVL9zWcKl/M0pqmJzkQSqQfY7bkIuPdpWxa5pmA8f5GptPlcz361XOyrzuZYfuRbhdj4aoDCCz7kcad2oMvMb7kxowaPK00GId38CVXH57bvErd/eNZXTRyL4c42Rrh1s7NkYz+Y/q5N2JoSwSCstO56keceTmMxasX39ibsFy7Y7/3++ClrH+ZVVuG49nlGh10AXsTrlSvXqMujK3/K7zSazFNx3n/++bDb45ht3NwN/PPkkPPqoDCSzlZObU1wczJ5dlHrLwenTsGoVPPUUnDqFW7DG0aPw9NMy68GqVd77tdulkH/3XZnCS0enNKxdu5YpU6Zw0UUXneuhlBpPS1ZluOm7jsl1PPm5BtKTQzBb7ETH53m13h04qrlF1funtEvqCrlZKut/i6BT/0wAUnOtdBt6klW/RJKbacCboFMQjMl6BaPDfAvU5Bhrac/zvMg0bie/0C2he+cCnn08k66diiZzJdZ7ZJQBje+4gTd5gg94kFNULez7KI/xNg8wwW00w0+/ybshd3PcGo/dh+BXsWFAw4oRf9dJVQRJMZnkCxOn00J9tvO5vypIPhjHl8urcGZfYqHvsULaacGxfVGsW1KTmx7b6FaG15vAEwIO7bBwZI+FKqZLado+h5gEe4UKWm9WYFdKe7zyErAOl4KKRBexOsVIT5c5UyMiZFS/t4naapUuAZ98ItNWJSTIyP/hw2UA1rRpvoWk2Sz7zs31/rorBQVSGAcToKWq0g2hJJkH/NGlC6xYIf/vy2Jw6pT87WlpFUIKWFUt/poDu136AnfqBNdeW/qMDTr/TbKysrj11lv55JNPeOWVV871cEqF581ywbLt5W65Kclyrzfr2oJl28nPMnNq5UVsX1MVzS4FVVxSNl2uOUiTS8647dfh0qbsXlrxiaUVFXZvNdH08iJxNfiSJJp9n8vdN4STnQVaoZBWVYGmKQxgLo/xTjF5m8RxPuUe3uNhjvcaQuRrDxJfpXACT3NpeOIQokoMpKQV68OEjf/xGk/wJgepi4pGXQ5ioPgEGEM6v+d15Noaa9h+NB53i6v8/8Vs5AuGcSW/coIkn9dBEwppqQqv8gQP8QEltsYCWnIdkvdL8e70TS78nXo6hJ8+bUaLm/8CwJprIiq7EzvXhjLxZ4V6LfJo2DqX2RPjObrX4hy/ogja98nkxkdaYLaIMn+2fQlWX0LTcTxv+BtDWQRsam7RZzE21OTWZ0U9nOoiVsfJ8ePSsvjtt0XWz1at4KWXZI5XBzk50LcvLF9eJNKOHJHprx57TIozGUXrLv4cf7//PmzfXvx1bxiNctn+5ZcDt9U0OR6zGfLzS3UJABl49e67MGJEcGMMNCZ/5OXBDTdATIz8nZoqj9etm3woiIkp/bF1LmxGjx5N//796d2793kpYr3dLCvKcuN6jED9e968u7VpxUtDE8nPCHELRko+HsaPU1rQvP9m6rTPcO6Xn5PNrPGCgryKFbIGFRpWDWdg6yTshRONXdNo2hI2b7YzZbLKjG8EWdkKTRvbGGX9gBvWPY0R30/5EWTT8I+vyDpzGbkpReeqpGUQMu5DjJt3IhTFr0w0YaMRewOOvwH7WXnFQ2yceoRl9GQvDVDRaMA+rmAJnViFArRhEwuphj9rrIV8OrKG0vjYCk3h350Wn5kOhKby765YbqvbmrxslUlPVCcvR3UGlu1aH4rQYl2MPYXpwYTC2l8jyUozcO/rJ8r02S6NsPTWNthAq9IK2IGt5cPGnE3H3PqqSGusLmJ1ABnhf+mlUsi6WlC3boWBA+Hjj6WYBLls/5d8KHWKNIfQ87f037SpFMSDB8v0V8GIQ7NZ+pZOnw779vlvq6qyeMGLL0ox7omChiBw0MOisavIb9iJ/fsDj6+8SEuTVm3HRDh7tgx8+/FH6Nnz7I1D5/xgxowZbNiwgbVr1wbVPj8/n3yXJ7uMDP/LkGcLXzfL8rLcbD2eUewYvqKmfVmtfvkyloKsUJ/ZA7YvaMkdIyOh0OJoCRNcP/oMM95JpGRBR26dB9zPZlPofFmBU8A2SwhHpJ+WL5pzGPuQjZcH7ZGRqSYjhv5TUPwIWAeKzU7OyYyipSGbnSrPv47hiBQmisvE7fyfoqAIUeKzVQryuYzlXMZyn22u5UcW0QdftwsjVgYwh/aspTUb2cRFBOumYTAIqtQo4PS/AaqRKYKtK8P4dVos+XmqR4Uw6ZPrTQQLTWH76nD2bQ5hd8qGoMbki7Iu7Z+NTAHnAr2OhQ4AY8cWF7BQJDRHjYLffpN+rJMmBbYwejJ0qBTEgwfLv/v2DX7fGNJYee9X1I5OB59TmbQADx4MTzwB7960hijS3V6vxnH8TbEqNrryJ/HXdkY8/kTwAyxHhCj6ycmB/v1lWVwdHQeHDx/moYceYvr06YSEBJdWady4cURHRzt/atWqVcGj9I83cemgvCKgA/kLur7uy9JlzVdY80uk/0AtofLKHbX4dVoM21aHYc1X6HJtJp0GJlPa6PtbmUYDy78+XzcaBY0aWLnzqgyamnNoas5xCljD9g0oQ2/HXKcRxva9MbTqAtfdgt1a4Gf2LMIeHQmmoqVgy/qNmP49guJl0lcK/7E2rM/+fr2xh1gQ+JulixCKwsm8wEtmtzGNBE5joLh/moIm/Xx5HwWYyY3Ek4zqJtaLRqSqRUUXQFC9hsYVvYMYLHBgWyj5uaoPX2c/9xWDYO2vMo3ZuRCRC5Ztr3AB62qF9UZFHvusidjXX38dRVEYM2bM2TqkTpDk5MhMAf6CoWw26N1bWmRLKmBB9v/NN0V/d+0qrab+EdRnP8TGkvj4UH5K74oJK4oXHyuDAdq0keJYUeDhiE85YajJHAbwGSNYRg+OUIs+/OJ1MgQNgcrzvARA0rdvU8d4lOCm44pB06RP8EcfSYE+Z470nW3TBvr1g1mzgg9607lwWL9+PadOneKSSy7BaDRiNBr5448/+OCDDzAajdi9OIU//fTTpKenO38OHz58DkYuCSQug+0jmH4CCeVA6YMy0wwU5AW+TWalGZn/SRyTn6zOMwPr8PP0CCZ9YKJmbc0pnILBiJUeLGMad7A3vw4P8j6Ac86T4guSqtuZ981pzBlHMaQdw5B2jIJ1v2GdNx31mpsxLVyGUhhdq9g1DNv3YDgQ+D0XwOkmjTixeh0nVq3lxKq1KPMX+Z0FFQHKkaMca9yJtcMe4ED3K8iNqeJXzApF4XSTlpyu3iLgDBtJFkvoRSIyAMGADRU7Choh5DGb62nJNgCasJtNtOZR3iE+MheDQVCrhp0XX9SY/o2N/v0FTZsJWrez07OPlVMnVL753OHH6u/CKKSeMpTKtUyzw9495ZgypwQ4lvErWsCeS86KO8GFEEF7PnPypFyKj4yURQQ8A7VOnJC+mcFQGgHr4M034bbb5P8VBT79FK6/3nd7BcG9OUWh+63YygL6MYRZpFIFk2pHqAZsNmjfXmYDcJaGVVVClTwGMM+tz1ncyA18x6/0wYgVBYENIxby+YS7uYIlcncEY+xv8wjvBpjegkntIooq7JQQux1++EHmy/3tN3l+dru0av/yiwwKW7hQphfzx+bN8Mcf0sLbvbsUwjrnJ7169WLLli1u24YPH07Tpk158sknMXipj2yxWLBYAiyZnkWCsbb6cinwtKAGauNvDP6CXwBCwjRK6hKQl21g4cdVaRCTy8RpWdx7YyQnTsh5QggFo1Fgs3mmhRKoaCRxjK+4w9nX+4xhJFOYzEi20IpwYwHXhy3gxpRvCL80GRFiwXp5ZwoG9YOkqpjf/gQlM9ttyd9xBCiySXo7GwHkRUZxsk5LMo3VnTcKS3LxIC5P1AJpGLCHhHLsko4cu6QjxuwsLvruS8LSUpzHFIVuB5nVarDv8r5oJjNpNeoQc/SQ32O0ZBt7lYb8IAaxkKuwYeRS1jCMqVTBvQpOEsd5kyd54eVctCb1Mbfr5Xxt0BWgRCfw1psqzz7rGknr35Jat3keqSeNftv53h9Co3PKPaArEGdDwDrwZ4WtaCtwhYvYCyGC9nzl0CHpTzpvXpH4bNhQ+ozecktRu+joszOeLVuk76cjWGnAAFk2dvr04m0N2LmE9YzwSKDdm984Sg2+ZzD/KO2xPHAP1wwOoVMnF3Gel+czz1YUmSziKtbSjh8YRBYRNGMHtzKdGA/3gwfEB6yjLdO5jeJTv7wd1OMgKcSSjr/cjDKxdjwnOVOYeqYknDghM0BAUeYFx++//4Z775VWbrsd5s+XpX3//ReSkqTl9ttvZSlgRxowTZOZF2bMgJo1SzwcnXNMZGQkLVu2dNsWHh5OXFxcse3nirJaW30Fg/jKZuCgZfWoEgXBOI7jq21WugGjSWCzQkkFzJTxITwzxsjmlSeYPjOU2T+GkpGl0Kq5jVuH5LBpTS6ffhHBsVMmEjjFnXzOKCYVE2XN2cEHjJEzkBVEukuG1Lx8TAv/wPjbSjLuuQPzzj1+x+Q5g7mKW4DQzAxaf/cVeZHR/NvpMk41bYU5O9tvnwKwe3lAsoVH8M/t91Jl3y6qbtuIJTOD/MhITjVvQ3LDpojCh61/u/QkZtZUv+LaFhKKPSqa205P53YxLeB48mOiyYqrShhQsO43Qhs2A8Aek0T6Pzt5dWxTwHu6MGd2gULrd9XwNMLz89l/qholfaAB0OwK1VseLZWfd3mkuqrIzADBWGErunKXIkRZYq8DM3ToUKpUqcL48ePp0aMHbdq0CTohd0ZGBtHR0aSnpxMVyNSk48bhw9Cunawi5bq66Ii2/+ADmZDfQa9e8PvvZbO0BkNKCsS66D27HcaNk9kAHGVlQywaI/I/4g2eJAL/EyhffikrETj4/XcYNEgeqBwQKMy/+Hkm/tOJtbQnjxCMWKnLQe7hE4YxlWd4lUmMwo7Jb18D+IG5XE9JJkGDQb5f/t4XVYVdu6S/8pIlRdZaf+m9jEaZq3fjRmmh1ykdlWWOKu3c+uB7P2MJDS/38fjzeQ0WT0tSMDd0xz5lPbYQcPCw4PPHapF2ylysBGwwKGh80G4q9/wvErVFXa+5CpWp36K+Nr6Y5bTE41UVbGYLpiCW1ARwqnlr8sMjsGRmUGXvLoy2Aq8C99Cl3amzxnfQlaNtRvVabLlxWKnHX2XvThovnIPBZnOWLnCMJz88km0Dbyb8zCmaLJwbcCwoCvuvvpKs2jWp1qk9YXFhAIQqoaivvcv05fW5A/9CGKAp27mXyRixcz8fUhorrOPxwBIqaHX9WhIanSom5oSA00fDKcg1EpOQ6ywj7KA8fMQ9Hwj9pZgL9ngOAevNCjtn0zG3FFulEbH5udl8MKZ/wLm1Qi2xF0oE7fnI8897L9XqmCsfeUSWfK1aaBgcOxZ69KjYMTVuXDxllMEAzz6j8fjl/7BpvQ1btZq0zF5D1PD7A3eoKFKlO9i5UzrF+qu0UEIUVeHanBlcy4s+21zOMibwkO8+0GjMbh7lXeYyqETHDybnraZJa6yj3K9jH3/C12aT1t2pU90fZnTOT37//fdzPQQn5SFgofhyf7CW1bIgBCz9MYy/ZlXhzJGyuV8YsXFi/XHMA+9E69YRbeJbEFoUiJe7dwfGvCxCy8GOpGgiKAELcknfbrbwb5fLafjrjxjstmLyzPF3rbV/BdVnVtXqwQ/WCykNm/L3yEeJ37mVuH27MOdkkxcdy5nGzUip3wRhMJBTJYG4vbuI27vDbYye4xZCELPtALbwME6sWku1Tu2JyEjG8MhLkJdPCu1RsaP5tMRKPuQBerGUNvyDiuanvZTcderbObRf9RiZ/H9BHvwzswMd7/qDrWQgNIhIrcOG32twdG80+blGZ1+R1dJpfPlOho1MCP4CBsAzxVxZV0r8CdizTYWJWEcE7eLFi0sUQfvii77Fgk5wZGXJ5eVAgVq1a8PVV8ul5dtvl0Fbd91VumNW4ygnqIG/5ZZHHvFijJgxA555BsuBA3RwbAsc8SURAurWLfr7nXdkpJM/9dahg1RvycnBmZ01LaC/xdX8RB0OcoSa2L18pQQqj/E2XVjJvUxiMqMItCzlsKY2bAh7A6dc5I8/Sh9wp4tYnfKiPIK2XAm03B8svpKwezJrUgx/zYpzBlCVBRtGksRRAJQVaxBjniTv8Xvd2mQ2bkKI0YhSDiUGhaIgFAU1wESgCEFeVDSqtYDEXVtRhe/2ihDkRscSkp7qt/jrmcZlf2jRTGZOtbqEU60u8d5AVTlySUfiC0WsLxQg9sAeYv7dz74B/Tixai3NFi2FfGltrsOhgAKWwnYAO2gWoL1CkxY2ho/O56lR3lc1hFAQQlCwvy0dLkvh7QeqkH3GsQTm+llTyDwRw/pvOnJ8TT7Dnj9J9brlGzjlK3+sr9d8URkELFRgdoLzPYL2fObkyeCMkQUFMh/pY49BjRqygtb117uXUA2EASudWMlxajKTGzBRAC7ZAxyRucN7/cvdNRbIcmAOPvkEbr65yOHTQbCuAFWqyBxUDhyOob5QFKnct2+H//0vcCUBo1H6ZPTp478ZdhbQjziSC/2otMLtcvIZzQTu5DMUYBKjmcD91KYofU5srPRR7tZNXntVlRXQoPil8UVp7oFCFFUc09EpL8orRVZ59edpNfLlx7dts8pfs+KA0gVhemLExo3MBKSl1LhsFXm7j5KTnENOcg55Ow8TNXkqaFq55UBJr1k3YF9CVTnVtBWmnGzUAEs9QlHIjk+U//fxenpSLTKrnx3n+oTd29CUwDcoVQhUu50aS1diSU7FvPeA02WjHwuI5zR4yXIDMvtBF/6iITIxeSj+S0uqqqBpQ5Wlv5j8ZqLQ7Aob/wjngzFJ5KZEuLzi/bN2bJ+Z8aNrcPpoxcff9+vZvMRuBP4Y2DrprGUtqDAR64ig3bhxo/OnXbt23HrrrWzcuNFnBG1UVJTbj07JKWmVJyGkAfOBB6QmbNFC6j2H1dRb2VmQIi2WNKYyDIAhfM9+GvA0r9OAvVTnGL21RczjWj77rQ7qNf2hWjUYM0ZaQsuabq1jR1i0qKhEWE6ANCZCQEYGxMfLqgupqbB/vxS2nqiqHOusWTLJbQCas4OdNONtHqMDf9OM7Qzme37nMibwYFEgBnA/EzlAPfYuOciuXfKhY/p0WQHNZoMXXsAZzRzIncBohDp1Ag7PKwYDNGhQun11dDwpbytseeApYH0J2dRcK+t+icFgLL8QkRd5gThcHsiFIG/uzwCYNm0l/pFnsfyzBTStWIBVaUahCMH+Hn041ayV1z4cfx/s2gtbWDg2S0jA4yhCkJ1Qjd1XDUAYjLJEq6qiFVo6MqrXZMe1N/q+SZQzptwclCCvjiIE4SlnsBxOc9tuxspH3FdY9sZdyBqwYaaAD3jQuW0w3zkNEt7QNIUBAzSMdmPA1TBrgULqSaOzHHCAMyA/R+XXaf6Chs8ulcmNwEGFSfzzIYL2QmXlytLtpyiCt1+3sXa9ga+nq3z2GRw9KqPcb7hBFkP4cnIOaflhRJHOcL7gMd6mJkedfdTkKK/xP17jf94PkpcHEybIAKxAotMfqgqLF8OCBVKJvf56cPt5RjHVqwe7d8O0aTBliqwsEBcnhes99xS5Ntxyi3uiWy/ENqvGI3sm8IhtvP8xGAyol15Kg1513bcXFJD34We8++JtgP9oK8fkW0WkcOhQvP/j+cBuh0aN5G8vz5Q6OiWmvK2w5YHnDde1NKara4HtdCR2W/BiTEFwJYvYT3320Ni5PZYUxjKWB5hQbJ98Iklf+ictvvwWhPDqi+oq0YKNhReKQkq9RuRWiWdPnwGcat6aBr8tIDQtpShAypFxoHlrQKbDSq3bkJhD+1B9+OUqQnC6SQvyYuNIqduQxJ1bCDtzGs1s5kzDptICe5YErDyHKARK0EIWwJhf3JI6mB+YzzU8wZtsp4VzexdWMJ6HuYR/nNse5V2mcTsaajG3AoNBULumnYG9T7FtQySLDBG+DQ+KwGAQJfqMaZrCusURDHn4NCZz4PZng8okYEEvO3tBsXWrtOiND6ChfCGEwo49Jo41uYx7Hx/AvasfLKZu3jtzDwXf/oBJyytlLRqk8+amTf7D5125+Wbp6/Dzz9JU6QjXd+x78KAUnMHQtm3xbRYL3Hmn/PHFZ59JtTdzpvfXH3gArrtOVoQIhKLImrKurFwJ117L6uRWpHNfwC6SOMoY3ucV+zOBj+eHTz6RRvFZs4reaiGkgXr6dJlf1mKBa66RribmSjKR6uiUhTmbjmE9E8bva8KwWRVi62UTHiFQVOGjIlMRBoPAblcYzCy+5RZUNDZwCXtpSDTp9GQZFor7cylAdmI1qm7aAHbNr48pwP5uvVFtNqpt3YAlM8PttSKLrYKKIKN6LXb3uc7ZR3qtemwYNhpTdiahaanYTSayE6oVE5z/dryMmH/3S7HsIWQFcLJ5a/JipYuFPSSU4206cC451bw1tdaVzEqTlZiELcSC0aM6WH8W0I8FbKUlZ4inNv/SgOK1xpuxk5+4mkH8QAZRGAuL5dgw0bBOHj99tofwvAJG3FGLdz6MKLa/E0GhgC3ZndNmVcnLNmAyBxHlW8HEhpqYs+lYpRKyZ1XEVqYI2guJvDxpOJw1K3hd6I+s4xnw6KOwZo20Pro6ydasiVm1+XInCp6SDHTAAPjnH5kE1ZvFwG4vys8ViNatgx6iGyEhMgjthRdg8mSZoNVgkKXH7r67aF3+scfg7bf992WzyQSub70lXSr27IErroCcHPIJJiJa8DwvU5WTpBM4CC48HPylepwzR1YFGzpUpjp7913pdeHKN99IAfvUU/KjoXv66HjSsnpUuQRhVTSZGTB9bA12rY6UAVwKCC2OuAQNPzFOgCA8HDp1Ety380GuOzIJQ+FE2JYNtGWDnz0hOz6RzGo1aLx4TlAyxhYSxqkWrTl2SUcSd2ym2tYNmDMzsYWEUBAeid1oxBYWzqmmLUmvVc+rRdQaHok13PeqTla1JLYNvIXGC+diyc5COHIwKgrHW7XlwGVXBjHSs0dulXiOXtKRGhtWB9XebjRhqxHOyfYXU+PP4vsoQEu2Ov/vi978xjGS+JabWUt7TG2a0Gd0Da7slu58+G8Utp+3m8zh0Z33omJDoyjjgPsRS4aiCIymcy9gKyu6JfYC4O674fvv5f/LKmDN5FOPA3IimzlTmt+GDClqcPnl8MYbZTsIlGygbdrAk08GDtoymfxHtMXFBWcp9UezZvD++75fD1Yk22yyEkVioqxEUJhariVbUQpL4PpGoQ0b2UiboA41aBB89ZX/NuPHS2+K7dt9vzUFBdKV+Msvpf+uN1diHZ3KjKbB6NvC2L1eKg8hFKfGSE1RUBSBIuwuAkRiUAWhYbBuvY169cBU7Ruv5a99oQAHuvaCwopVwSBUKXg0k4kTF7XlxEVeVpGASOsxIm3HyTSVzjqWXqsea+98iNhD+whLOYPNbCGlfmOs4X6siueQA916UxAeQc21KzDl+Q66EsCpS1qhmU0Y7xlKVtVEwmf/VGyCExYLSn6+905cCCOHO81fM3xQGkr0alieizhSG3FtX4iKRB3/EQ/vmkZDFvA6T7GKzgBEk04GUQHmdN8IAfM/iWfIw2dKtX8wlDQ7QWWyxuoi9jzHsexbHiUrjFi5hW+KKlcZDDBpkhSxOTlSwK5ZU/YDOfpu2FBm6feFqsJll8kEswGqxiAEVK8uy5T54s03K349fOlSn9XCiqEoMkHvyZNOgV6To1zLPH7iaq/FEwxYack22rOWMwTnC3vmTFHKLm843AeCNY4fPgwDB8K6dWfVHU5Hp8ysWGbkn7Xeb3uaXcGAnRjSSCa+MNMKWDETp51iTsxoGr4Th3bXXYiqiZCaQkkycYlCp8bMGklYUtMDFKqW4tIfkdZjAFTr1J4Tq4LLxe4TVSW1XiNS6zUqWz9nA0XhaNtOHGvTgcjjR6i29R8Sdm6BwhRjjoeEo5d0JLldM6p1ag9A9oB+5PbsSsiqtagpqWhRUeR1agcGA/EPPu1z8hOACA0lf/gNmFZtwPjtD85qY4qmwbj3yLv3NkK+nokiBNcyn2uZTwaRFGBmCDNZxuUBTsqf97PCyp+i6D8ihfDo8qtG5K0iXjArKbGhpoCZBzz9zSsSXcSe58ydW1SFq2S4f2kM2KjBUV7nqaImdrt0tLXbpTV0j/+ShiXCbpfBWMuWyfJhnqiqrMTweWHZ2RYtpMXSlxIzGqF7d1ns4KGH4PTpotdiY6WAHTGi/MbvC00L/s0QQl5To/vXcBKj2cjFxfLOGrESSSbfcAsKcAWLSeQkp0jAW6IRVYXmzeVlDEZsBmsc1zTYsEE+z3TsGNw+OjqVgQVzjE6fVm/YMZJDGJO5h300xIaRjqzmOuZiOWJFfAyGjz9G69K5xCkECgotm2datyB+q/9cp+k161IQ4d0NwCFeAadAq9apPaxaW2pr7PmE6/ln1KxDRs06HOjWm8SdWzBnZVIQHsHpJi2xhGQ5r48DLTqKnKt6Fesz9/JuhP623KuVXAEybh2MZeU/GDZL4ae43IdEgZWQD74oJkGjyASk72xgNwL/r9ttCrs3hHJxzwDGnCBwFa+eVbQqY4aRQOgi9jwkPV3mDw0Ph8zMkriXSuH6KG+xjRYs4ioEKuFkMZwveI6XSeS0+y4REdLZNpCALYmSNhigc2cZLTRgAIwaJSshLFsmA7hiYqSPxCOPyDRXINv486m22WTZqs6dYfBgmXrr6FG5/1VXyeiks0HnzoHX7j2pUcPNgpzEcdbRjnd5hCmMJIU4IshkGFN5jLepU5hj1oSNCTzAjcwq5oKgqgJVVfjgAxm49cUX5XJ2TgwG+XboIlanMpKbrSA0BeGRdSMtVfEpYJ37Esq9fMzl/MZMbiSeoqqAjj3VFSvRqibCmWQ3QeMNoSjkVE3AFJ6HyXqMKn17k2k2E/nFN15LveZFRLH92hsBd8Hmiqc4c+Bo70vMeusvkPD1NQZflFVIBzqe49xPrFpb1NYMR9t2cu5vIatEx8y8bQhKQQGhy1chVFXezzQNFIWsG67D2KYxIZ9+7XXfQPK0I6tZSWevhXBA+rwGk5d4x9pQqlSzUbtpvr4C5oIuYs8jTp2SrqHffFPk+pmUFGyie4GFfD7gQe7hEwAyiCSTSOI54zWaFlWFm26SlbACdi9kBL/FIiN/Tp6UFkZHDlfPPidPLgqHb9JEZh4A3/meBg2S+82c6d6fQzw//LAUkCB9Y6++OohrUgHccot8kzIygnuyMBql+H7mGbfziifZmaqsABMmrF4nyyF8h5HreZR3OEjR8mPTpgoTJkDPnjIHcP3ELP49ZSm0CpQdTXO68erouFGewV2uVqNAfQoB65dE8NuMGI7slQ+tibUKWDcghVeeCkNVoWYd4dcSK5Gv/UF3+rCINVyKEXehKgDFbEHr2wd1wUK5rOxtTIoCChzr3MFNeOb26o6tZhIRs+Zi2rMfhECLiOB0kwacbH8x4coZHKlJfQlWT7yJu0xTUjFR6NqfmxAM0G/QlNW1Ichj+juPEo/ZaCDjnqFkX91HuhtkZaHWro7t8s5QJYbQ+b8jDIaADyzeGMkU3uFRfLkMSAEbOJnaqp+jWfVzNDUa5nPHM6dIalC68uqO75Gj/KynNfZ8QxGiPLwpK4aMjAyio6NJT0//zxc+OH1aVkw9csRdtBYZQDV8LSk3aQKjBx7lltdaEkta8Ac1m2XN006dpFUzED/8IAPBrFaYNw/++ksOoHFjKW7NZujRQ1oeS4PdLnPMvvdekeWyaVN4/HEYPrzyOGj++ae0/ubn+w9GMxqlv/Hnn8vsBH/9VWrnZg2FNWpnTsU3p9btPbi4jUC5qo8s7LBoEfuuGk0vlnCIus664dJ6W/KULw7atoW1ayvPZT8XnK9zlGPcD773M5ZQ76UyS8vW4xnlImIdArZl9SjnMqe/fn/8uAqLp8d6WLbk92nAjVZeGp/HulUqIwaVLGBpDgMYwDyvrxVs3QphYSh//Iay/E8Ms+eipBctydqqVyNjxC1YmzX2un9F4uonG6yoO7FqbckF4AVGWFyY8/+hDZsBoL76Lsq070pdHvgLhnEnn2HA7jQkqAaBZle4Y2Qe+3YbWL3cGHCVAOQqmzlU48lPjxCfVPZyxZ6+scF8d1NzrX4Duzx9Yhcs215isZyfm80HY/oHnFt1EXue8OCDMsbKtyYSheLE3YeyuiWFNQ99S/WrWsvArJLQvDls2yZLr65fH7j9xo2lT2FVEjRNWnoNBlmftTKqqIMHYeJE+PprOVZPjEYZiLZ6tTSn5+bCq6/KN9mRLiwqSj4ArFsX+HhRUfJBwdUX2GSCkSNhxQrYtIk8zcR33MA8riOHMJbRkzxCy3SaS5ZAr+IuZv8Zztc5qqJFLJSt8IGrgA2m3wPbLLw7yn/p047draxfZcRqDX6+MGBjED8wk5u8vm795x9EC5ksX6SfBqsV48L5kJZOnmJFa1KfnJTiEfSuQgkgJ7nkhV88+yhtPxc6JbnWjrYO8epA+XY26guvB51ZwhuruZTxPMwv9MVutHCpupaHtPFcXXcL/1x9P9fOGsXJE4agqnmpBsGlV2VyyxOnA7YNhpJkJwgkYEEXsU7O1xtEeVNQIAtH+Q/Q16jJEY5QE1AJJYdhTOUFXqQqp2STiAjIKoGvULduMpfS11/DHXf4b1ujhjQT6xRn7VqZm2rBAinAw8Jg2DB47rkin18HBQXSymw2yxxWdrusK3vihHf3BFWVqQJ+/VVmkPB8yvHhqywAtYwV241GuO228ve3PZ84X+eoihSx4G6N9RYFHehm6eum50vIfvVqIut/i0DzaclyfNZL/sDbm19ZTJ/iPUZGYj16VOaQdmxLl6LCkCaXtnP37nCKJk8x5RBKuXvdg7x8iSxf+ztw9BOMkA2LC/tPCF5PUep6rV3P35v11Y2sbAydr4K8vIAZKYKpsiZU1emCIgqNMKebdeP9vr8w5asQkk+7Fir3jtGs8fYvBzCcZafQyiZidZ/YSkZ2ttQxMTFFBsYzZwJnmAKFI9SmJod5m0e5jh8JwcNpsSQCVlVl4BXIJe+XX/Yd3KUosmyrjnfat5eFGjIzpa9sfLzvQDOzWdaCdWA0ysC6K66Qbhquy1mqKt0pQkKkJdebmd5XOUmgGsc5QfVSn5bNJmtQrFolA7wqo0Fc59zhzZrq+povIevvhudwLfDcf8dG4UfAQmldZoxYacTeYtuFqqLdfbebgAVQohOcQhYcgmiHx9/uuG7L3bvDq4XV177eX98RlBC+0IWsN6uq+zWU18mX9dWNiHC0cc+hPvwsguLlgkuKqw+1w7qbsGsFL3V8gBeOTmb4MAMzZipofrzRbAUqBXkqoRGyr8O7zexcF4Zmh7ot8ml8cW65z8mBUmudC0qXfVen3PnlF5khKiJCWl3r1JGFn6xWiIx0L5rlHflpPUYSd/A1W2jlvVlo4fKxt+ApB6oqDzp8uPzbYpH5lLp3L942Lk5aAXv0CDRAnchIabEuaaaELl2kO8dttxXtW7WqtOT++aesdFEKX617+BgDZfOp2rRJxtM1by49I3R0HDhE5tbjGc4fx9+B8NXGlyU2PsFEiXNeOfG9nw0TdxcGwjpaCkB07Ij9+eeL95TuvrzraWUNFm/iMpi+ArW5kEVrSfBmkQ107UT/K9G+nAiJ/vNzl1Y3KnY76tdfIw7toUYNgRqgI1OIRg75HD6mMf6BJN68uxbzP6nCgi+q8OHDSbx6Ry1OHCyfQN7UXKtTwAZb5OBsCV5dxFYCJk6Efv2k66KDw4fhiSdkdVKLRcZWBZXrEwN2DLzAi94b5ObCJ5/I5ezmzWWnjo4d/4+OlsI03uXLGhsLf/whs+K/+64sv7p8uTQTl7UKlk5gmjWT6/a5ubLO8IkTslCCwVDqNAEP8T51OISB4pONogjatAnm4Umye7fMhLDBd+VNnf8IrgK0X8/mzh/X1/y5E3i29ey3X8/mCAFnjhs5cdBEQb5Cm8uyy2B1ckSHuyKtWw/xHhezEQBhNCKaNME+fjy2hQulW5AXHK4EDnKSc4ISSp7uAI79gt3f9XiBXnft80LF1/l5c7sI9lqITu2xf/8FWmSE0w3A7XXAWre218eiYB6xFKsVZedubu+5D5vN9wfaYBAMudXKNS2S+OGF+hzcJlcEhKY4VyROHzHx3oM1yEj2Y7AKgKd4DVbAns1qXrpP7Dnm0CGoX993NiZFkfE/x0qWqg8FjdMkEEdK8RcXLYIrC2tinzwpU2OtXCmXrnv3lv6vF+j1vuCw2+VDR2B/E6+cJJH7mMQ8BqAhJ7tIMniY8TzYeBGd0n7hQEqU3wnVgcEgP1YLFpRqKOcl5+scdT5lJ6iuVGXLXjvm8AJuvKkm6xZHsPCrWE4dlhWwLKEa7a/MZMOyCHIzVS85N/17KaqKnXriACeoRjYyc0FNDvMkbzCaiVLiWiwUHNoDBgNKdILXfrz5w4J338vS+rP6W/ouiU/sfwVfPrH+3C0CuW0A5C3/HdM7n2LZXlRxUgsNIaf/lWRffSURM+cQtmhpYfCBKudpowFs9oCWWq1bR5RV63jI9g4TeADPz67BIIiNE8xclM2av4w884Dv4FxFFfS5LZX+d6YGPCdPSmp59cTVL1b3ib2A+eQT/xZWIUouYEHmKkihSnERqyjSquegalWZo1Tn/MRgkJXIPvqoVC4FVTnFbAZzlCQ2cxEWCujIKsLIhT0KK0RDHqr/E9/92yGgkLXbYeFCmSAhwft9XkcnaJolXMxnr4aTfizWuW3Ttzay0o24Rtfk56qsmB9FbKKNnAxvVif/n1tNGHiLx+nDInbTGDMFNGEXhkJrrDAYEAP6Ycg8iT0mqZjLgCverLCef4fFhZG7d0fQwsp7f3IfT8GlC1h3XH1eXbf5w/W98fU6SVVJe+ZhDCdOYTx6DGE2U9CkobOsedatN5DT7wosa9ajZmVjj4/DVqcWcc+95vfYAlD+XI0CvMcYqnGCN3mCdGIAUBD0an2ahz40E5cIC+aEoKrCZ0YDoSmsXhhB51tOObcFUw62rAL2bKKL2HOMo6preWPESlU8UjsZDNCnD9SqVf4H1Dl3PPUUfPedtKqXcmGlBseogcfTkhAkcIZv9nfkva8W8uDPffjhB/9aWYgiEbttm3xI27lTBioOGSLdY4z6rHPBUl5lKw9stfD+QzWKrVBlpReKVA9rq9AUUk4YA1Q/Km6RNWCjLeu5hvkYsdOGTe57qCqEh6GNHCrbp5XCouCBq5B1/F2WPkIbNiu17+1/AXl9g7vW3h4yfPcJ9mqJ2Kslem2jxcaQ61Hi1taqKcYtO3326/rpVBE8wzge4V1W0IVcQmnONupvOIj2an9sM2eSlqIETMllyzU5xeicTceK+ap6itrzScCC7hN7zgkL8x9jVRqMWBnCTGftZkAeJC4OPvywfA+mc+5JSpIpAtpXUJJyg4HE6ePp0iVwETJFgcREePZZaNlS+nsvWiRjzwYNgksu8Z42V+fCoTxcCb57Px5Nk+LUHf83bP/lO+VrKnaUQitrP35mIVcVq8jlQGtQm5w3n4ZaJSvQUhJR6SsbQXnv81/FMyODv2sX7HUt7fW3XuklODoAIeTTi6Vczc/U5yAAyoIFGJ57jouaqxgMvg0XiiqoVado0vbm1+otAOt8EbCgW2LPOllZ8oa+f7+MlerWDb79tiw9ulsXDFiJIoOXcYmctVikn+tzz+lW2AuVunVleoArr4TffitukTUY5FJXbvHE6wGx22HdOm4asYxHRDe3ghqeh+jfX2YTe/VVuc1htXWsNmzfLtParlihp+S6UClr2dnjB0wc3h0SuGExAn+g6nCARxiPERu9WUxjL+mzQObuzL+4FemPjCqVYPFnHfXu1xo4f6ln/96O52gfbK5Zb8f0166y4m/83vyPS5vGzNHG0UdJrOhhcWGIuJig2/tDEQImf0x235ew231XoBMaDBlawJxNxVcQ/LkVONqfD2JWF7EVhKZJLfHddzI9aJMmMv7muedkDI7JVHRjj4qS6UNLioJGFOmkE+v8uxdL+ZD7qc8B2WjqVLjxxmL5DHUuQBRFKsiHHpKlbF3X/du3lwF877wjXzMYigIOhAjshpCcTMKNl/Oi+j/+J14p9rLBID9ir74qRaqPGgvY7dJo/PffcOmlZTxfnUqHa4nY0pJysixpgXwHcRmwcQPf84DyIQj/uT4VIVDySpb1wx6T5OZu4MgR663YgTcRWoT/vLK+cPWxLblIKy64S3Lsc4mv8/U1/vI4r5IKWcf4zNcNQLw5BSUtvUzH11C4Pvdrfpwdju/PvKBOy1xEk8NB+cE6cLRNzbUyZ9OxSi9kdRFbAaSkSIvU6tXS/8+xBOu6FGt1seCXRsACGLCzk6Ycoi6ZRNKIPdTh36IGCQlwyy1SMev8NwgJgSlTZHGKJUtk+q1LLikqB/zZZ9KH9ttvITlZWnDT02VFsSD8aZ/WXiWKNMYylmSKUrBdEraDjyfaiIhoxV7vxi0nRiP8/LMuYnW8ExFduiABg0Eg7BoCBeHhKaegYcTGvXyEIgT2sDAMOb7Fh1BVtJjgo6ntMUnO355+swGrQXkQrMhyHNMVQ9qxYgFjnv257ucYq69jejtGWTCkHSvXPl3P1x+OY5aHT7ODYIWsp+Vde+geDC++VaZjz+AmfmRggFYKtzx6hoTo0sm82FBTqYWsN8tvRaGL2HJGCLj+ellpFEoVMO6tV7w9aT3Hy1TjFNUcZWUdOMxgEyboAva/SmKifIDxRqNG4JqoPSUFxo2TpeICoAD3M5F7+JjldCeDKBqxh1bZ2+FOA7s//wvo4L8PJahD6fxHqd00n7jqVpKPGwk+dbzAqNgZz/08wngKMKMVClkVDTMFzOZ6GnCAzMHXolithM9f5FY5yRVF08jr2jGoIzsEkme1LnB3KygPC6CrAPRM9SXST7uJNX/i1bFvoMcFX+nEHOw47Tu1X7OE4qnb7EH0GSyu5wvFBarn+QZq77mPP1zFvz/Lt6ON27hvvQGbZsLw+ltFAiHAyoAnH/AAAQvcKoINyyJIqh9cei1vbkCuQtZBsILWNb1WRaKL2HJm7VpZE6B8cf+gRpPK87zMw4z33rxuXblsPDDQk5qODrJEXOvWRU9eQWDGSm9+K9pQqAXqjB1OZORWMjN9T65Wa8XFoOmce1pWjyqTX6yiwIBRyXz2XDWCq0QPigo/3/k9l3/6KQPtc/mMO1lGTwB68Dt38SnVCrO1WBs3wFajOqF/rETNyCwmZIWiUNC8MQUtgxedrsLMu1tBcXwJJn/WSn8C0PGap1jzt28wgtKfUDX4qIZi17Ri+zVLCHc7nr9+feEqjF378nbOnufm+bcvAR/omjiOFciK7Qt7bA14cDTaqAdQvvoc4wcTUY6WzHIpK3IG+F4ISD3pW+J5E5e+hKyD0grakuaILQm6iC1n5s+Xy6Ult8D6m6wFtTjMGzxJNOlczlJC8OOv9c03spi9jk6wtG4ty22VJd+bpvHqviGuOTGK4checO21pT+MTuWmPNJstemezdDnTjJrfDy5WQYCzY/Vq8FlXawoU+xU4yT/4zX+h/ecnKb9hzDv3kdur26YN2zGfKDIBUsoCnmdO5Ax/BZnuTpHiiZvYsWbcPKXR9ZzP2+CqaTWSocYdAg8VzHr7Rie7QP17Uuo+sNzH7sPi3dJ+95xOtvruEtj3S2tRTjY9ziYY2sjhmE/cgzDpMkoPuZeh5OXa125EPLJwXdAl2OPDcsiiEuy0ee2VAw+1J6rwAz03XVYZisTuogtZ3JzSxt17aeiDBr3Mpmb1VmBcxyBvlarU3LuvBM+/bRMXUxlKC/zgt82qgqzZ+teLhc6ZU2ztWNtKMtnRxUKWPBvdVIwmQX27p0whIej+Khe5xAAkTNmI1SlUBcr5HbtSEHjBmAyUdCyKVpsTInGWhYxVNb+HCLTl0gMtG8wQlYnMK6ZKAJZZg1px9ytwAOvgIkf+XxMUwARHobIy0ex2xGKwmDxPZ9wdzHfb09sBSq/TI3l6F4zd7500q2MuOM7Guxyv6t4rUzBXnqe2HKmdWv3oK3gEBiwoXqpYW/ESjVOMJIpPmt1u+9ghOZlz9Oo8x/j0kvh7rtLvbuGwrO8HLCdokDTpqU+jE4lp7RWWNca7WsXRzDpseoc3BFcRhVVETSsmy+LEjx+v9c2DoHgEAmKJmQGAk0j5K/VGE+cIq9bxxIL2HOJ53K8599KdIJPQRyMBbS0VtiKwq5plUJ0+7LCOoK7cvfuKPbjicMVwZB2DGrVQBv3HCgKwiVpvHD9nZ3jXCVThGAM72HE6tLK34AVNv8ZweY/w9i5NpT1v0VwYKvFGcfbr2dzp6D19vDp+t30lmf2XKNbYsuZwYNlhqP09OCMpiAn1k+5kxnczCKuQkFDQaBhoA3/MIsbZfnYDz6H11+Hffu8L/saDHDTTRAfX/w1HR1/KApMngwNG8Lbb8uyWyVgKy05SuAcxDYbrFsn09nqXJiU1ArrauE5fsbOt28WLocHqETkQBMK92wdg7nlHESrZtiH34zy/XzUzKyg9leAsEW/kd3/CkR0+fjuectSUJ44BKtDZAZrjfUmfCuDMCwvRPrpcgsc84ev99ZblgJfFcBc+xDXX429QT147hWMO2R6F+cDl5fjNGMn87mWgcwhl1AfrYpQFMHUl6pitxU9lCTULKBVl2z2bAwl+ZiJsKjaKIcy6TogncgY989SZROurlSex6wLhNBQmDGjKA1nMIzquZ1hfMVC+rKdZnzAg7zLI/xNe9ZyKfUKq3SQkgL33ScP4lm7U1WhQQMY7yPYS0cnEKoKTzwBR4/CWyVLAZNN8DfCzz+HU6cCt9M5v9h6PKPUAtZh4dnyexTWAlebqX9U7PRgGdef+RTl5CmUZX9h+OJbbL26kPr4/dijIoMLDdM0QtZtLNHYfRFIRNljksoktDwFrLfX/OEqfAMd43ykrP6qJSV37w6/KbZcLbT++sgNV1Fs0l0gGPrwK8epzgQeIAT/uWqFULDb3Ps9fcTE0pkxHN5lISfTwJmjJn75MpbXh9fi9BGpL1JzrVzVKInffzXy82wj2zappa1sXmHoIrYCCAmBzp2DL2PfuneC05G2GTu5n4k8xAe0Z517w8ceg4cflmW/YmOlmAWoVk1WUVizRrfC6pQdkwlGj5ZVOIKkIXsxeHGH8cZ338nUtYcOlXaAOpWNsgRzuVp5ovNiUYNcH7SQz0imsIB+zrKxjuAY89xFGA/+iyEjMzg5rKgo2cFXXzpX+BOwpV369yVYy9uVwPU4lc1VoaLxJ2Qd23KOp2HYc0BW4wqSaDK4n4k0Y6ezlLJvvJVwdn9gFJpCVrqBT5+vRnK2leUzqtDjokgeGBrGU6PDuOmqCG64Ipztm4N/7/r1bF4uwZ6++O98is4SU6bAZZfJsprBfhbD6ybC1VdL822wJCfL3+vWwfHjMHYsxMSUdLg6Ot4JDYVXilfm8kUCZ7iB7yHgRCrdbE6ehOHDYdcuWLQI1q8P/vuiUzkpjRXWc5kyPAKUID4HM9q8zHGqMonRhJJX7HWhKIT+uTrosSiahj2xchgAdpzOLlVaq9JwtoRkeR3nfLYQB7TWlmH+u41ppd/ZA82ucGyfhZ/HJ7FkaiI52e7id88OlaEDwtm7q3LIx8oxiguEPXtg1Cj5/2BTbBkVG1c8eymkpkKNGnJjMF94TZNZCJ55pnSD1dEJxP33S/cUh8U/AO/wKNU5TjCzsc0Gy5bJIK+rroJ27aQ77v33Q7duULu23DZxoizTrHNh4U3AAlzR34rd7tt2asBON+VPhmx8nhh8l+5UhMB4IjifFQHYLGby27YOqn1ZCNaVwKCqTjF7Pgu38sQhhANdj7PhE1sa/JUCDosLA4sZa82koN0JHAhgBJ9Tg6OFwV7eWpQMRRWsXRLp9TVNU7AWwIdvWoLqa8Gy7RWaJ1YXseXI5MnB+8GC9Oe6W3xMwoG/YeVK+PdfeSfv2DG4jux2+PVXOHb2Srzp/IdQFBgzRrqwBDGxJnGcf7iEkUz2MZn6Z/9+KVpXrIDDh2Xa2gcegLZtpeXWwfr10q/WUTlX59xSUl9Yhx/siWMK0z8zMWW8mQVzDeTmajRsZqPHlVZUtfiNV0FDQ+EFMZZgvGYFkBNTBX+1kBxHOdKjKyfKySfWQWnKq7ousxtU1fnjELNlsWgGu39Fi+aynEcgIXs2BKwSnVDsvfVXscuVQOm3cvr19ulOIDx/K4rT3zuGdJbTnebIdFkGbBhwWNJKnvMz0KqY3a6wbKGRDN/PkWcNPTtBObJ6dXAWWKNiwyaMDGQ243lYbnRElh44IC2yJcn7d+wYJFXe6EGd85wFC4Je66/KKSYziitYzGBml+pwjkM5fu/bB3fcAe++C7ffDv/8U9TWZJKxjm+/reeerUz4S4hut8H2mfUZO92EQD6v220KsbGCF8baiY2zY1as5GFGQUPFjoaBUHL5lLvoxdKAxxeKQkb1mhy+tDst5n6DEN5v5fmR0ezt1Y+0ug2JtPo3BniLMAfvEfHeEuIHErXl5UJQmowDnvtUZn/V0ubFrShcSwuXlbxunTDtPUDY0j8RquqsJidUFWEykn1VL8w792A4kwJR4aj/HnNmKqrHQTbShhV0YTndAbiU1VzHPLLxblX1iVBQDQLNT+0bTVNIS1GIij63fmC6iC1HLEFY180GG3fbJ3MHX9GetcUnVrsd/vxT+scGWz0pMbGkQ9XRCZ684j6HgejFUkLIJY/gXBH8YbPJBYfOnYu7FlitMGECnDkD06eX+VA6JcSfFdZXWp7nHwlh7gwTQsjZz16oR1JTYcxDBlTVgFaYXktBYMfEdczla24nkiDTZgnB0badSKtTn20Dbqb+soWEpaU4Xy8IC+dwh64cb9PBbb8Tq9ZSrVPxmsg5yTlerW3+SsR6HVcAS2FZxWNpBN7ZEoUOi/KFQoWkUVMUMoffQv4lFxG2+A+Mhw4jzGbyO1xCTu/L0OKrkA2gaSQ89WIx44ICdGUFXVnh3PYWTzCKj4IegmoQxFa1knLCv1VANQhi4859IIMuYsuRq6+GP/7wbUQ1YuU2+5d8yAP+Owp2QlFV6NJFOhDq6FQU7drB3r0lqqUcQzr38hHvMyZgVZlgycry/tUQQlZafvxxaNOmXA6lUwa2bVZZNbc64zdGoGlwSQc7t91dQM3aGgt/NDHnWxN+ahM5BSyAhgx2nccA1nApvfnN77Edy6snOlxCSoMmAKTVacCGoaOIOHEMS1YG1rBwMpJqubnIBLLC+louDiRggxG4Z0PYBXOMko5jzib/18zXQ0xZhHpODiDAEhq8xbks19dX/94s7Y7PiK9csYEIiwuT+yoKBW1aUdCmlc+25k3bUI+d9Pm6AwHcx2SmRj/E3+lNCMa1oGrtAoY+d5I37vKd99tgEFze10Zkxbm6Bo0uYkuBEPDXX/DllzKlZlISDB0qf156CTIzBJpw/7A40l88xAfBHcRoDCwaVFUWP9DRqUhGjYJpJY9+fYOnOEwtfuAGjFixYcKADXsppx1/z3ZGI3z1lS5izwULlm13WmP/XhTBtHGJKKqMcgb4/VeFZYtMEFTGVu+vG7DyHmMCilhrg7pk3nEjSoN6RK5a6/5ivEJBfDQAkbbjxfb1ZoF1FR+urgSu4jRQ+VhfCfhdxVVphZ2rkHSIRl8WT3/HCHR8b4I1NtS3pS411+rcx1XMOo5TkA9//mbk5AmFuARB9142Qn3oPCFg4TwjX3xkYcdm+VDToImdoSMLEEOyURTvYrOs19euaT4FsON4Dmus47ORu3eH3wAuX5TUJcG8bSfCYHCmlPOF49t0Z8Z4/mayn5aCkHCNGx46w8U9ssnSCuh+YzJ/fFs8Y4dqEFhC4P7H84Meb0Wii9gSUlAAN98s6787dKbRKANNWrQAs8lVwEpTu4KGCRvfcjMXsSXwQYxGGdHir3BB1arS/NS5c9lPSkfHH506wfPPyyc0VzcXVZXKsk0b2L1bmklMJmfdZTNWvmMIK+jClwzlKElU5zjL6MEB6lOecaVCuAd/6ZwdHFHHC5ZtJzsljD8/vBwhQLhkGBDO+bDkASYO7Jj4k25+2wgg/42nMIeHYca7KA2ENwESjHj1JnYcQsdfO09x5U0serNouraLDTU5RaOrkHW4CPg7hr9KTJ5j8SdaPXG09SZm539v4vXnLGSkqTKfmlCwhNm5YvhpOlyTVqyvxV/E8+fMKLdgv/27VZ5/JJTNGww8/2ae87o2Swgvl4cDf/s6xG2zBGmNdXUrCBS45eyj8HPk6Y7gtMYGQCmh+8etYhpP8xrpahXsXivhKdz65GnaXJbt9Gef8I6ZqQ3z+Pg9C1mZRfs0bWHnxXfyqN84+DFsPZ5RYRkKdBHrg3//lffliAi5muookPXEEzB3rvy/w1Dq+L1tm/e+WrGFhVxFdYK4yzpKx779tkw2//rrkJ9fJBgiIuQg/ve/kqVC0NEpCy++CBdfLD+XK1dK1dihAzzyiKy1LAQsXAj9+7vt5s1HayF96MsvBGeZK0qf7M/ooChQs2bJT0unfGhZPYrvf61R6KNXMfOS6icHsQBE906Etm4LeLeI+fJrdcWbCAlGuHoKHn9WPH+i0lMouopAVzzbOf52FYy+juNNYDr2CTQefwgBB7ZZOLzLgsEEzdrnkH4mhKWzotm5NpRXhEKVpAJO7A/BGWNf+ICTn2Pgp4nVCLcY6HpdUWL8A9ss/DlTWgNd3UwcD0bfTzPTs4+N7r3lTdhXMQhvVuHS4vqA4HArKIl/rC8Xk5JYYwsaNyDs12XBDRgIJ4ef1WvoY/yNLFuI81oaDAK7XaH7TWeo0yGN1Fz3azR8VAE3Dy9g7Uoj2dlQr4FGkxbBidfUXCuxoSb69WzOgmXbgx5rSVGEqLwpxjMyMoiOjiY9PZ2oElQPKgv798tclQsXFvlMV6sGAwZIYfvLL6VLyv4T/enPgsAN27WDJUsgWi57kZoK8+bJkrP16kmRYDaXfAA6Fc6RIzB/vgw+at4c+vQpWf2K8waHmvQ8ueuvlxcgCN/ZwXzHDwwiGBHbsqU0Bn/xhf+ut2+HZsEZQsqNczFHlQeOcT/43s9YQksWye6Laa9fzPEDFWVtsTKQOczixmKPPgIgrgoFy5dCYpHI9BQVvrILeMNTaAQrXr32pWle25VWLHri6s4B7qV8XY8TaPnfFV9tHRb3jGMxKAaNuLrJmEKtZJ6KYOP3bck6FVVoXXXsoaCoAqG5rk76/s6HRth5dc5BTIW3uK9eTWT9bxFO1xRPVFXQpYeNSdNzvb7uzWJdVhzX1a5pTmu7wz82kJB1fK5cXU28fU4DWmNtNuIfegY1MxNFC06QCKOR4wNGMKXhW8yZH0pegZGGLa3cPMzKxR2CDCIvAXM2HXN+jkqTKzY/N5sPxvQPOLfqllgX/v0XLi2sO+AqVE+ckDlgS4sBK5O517+INRplua9bbpF1ax3ExsKwYaU/uE6pyMiQomnaNBn53rAhjBwJAwcW1275+fLB5/PP5edGVaXOq1lTRsx3735uzqHC8KXM164NOvjrQT7gBwb7bRMaKjMP3HKL/E7Onw+nT3u3yI4adfYFrI47crk3OOu6dxyTbvH97Ri4p+VSzlxyJ1XWrkTZIS1WwmhEG3w9tmefRmlUJOQc1jFXQhu69Bcg4KokPqy+Apxcl/a9tfUmFL1ZrHxlf3Bt6/h/v57Ni1llPY/l2tbfWISAb6cd4/SeRDS7Skh0Dln7uvDvzirONgajRtP2J9m7MZ6C/MJ5wSMeRLgtX/v/bORmGZj2eTKJjU5yek8im/+s6VPAgrTO/rNRcXOl8HfuZXlYcO3bYel2BJe5WmQduIpTT/HqiqcVVz5oBRCyRiNpj44mdtx7kJ8fnHuB3U6Vqnk8d+dunnm0aDw7Tls5n0sG6CLWhRdegLS04DNbBYsdE9to4b/RLbfAiBHle2CdoNm/X1rZ8/Nlmt4nnpAJ90FO5ocPSwN5//7SH9rVGD5sGMyaVRR45Pj8HDsGV14p8wf/JwKOSrBC0I0/uYT1bKY1Nh/T0EcfyWBJkIJ21Sq45x5YvLioTVSUzEqgF64799RtkcKx/VGlWqlSVEHb9la2rAOr3eDMSmDEhh0Db3WdSetmBjI7dSfqow/g8GGUzExE3boQHV28KryLWHBYyYIJxvJFoGVqX24A3oSVPyunp7Vq6/GMYpZWf21dCVfNbFkRRupJExExdi7qms3v67YC0v3DW78OMtNUPnuuGvs2N0BRNRRA01Q8qz/ZbSrbVlUr/Kv0Ps+uhGUnsGpSK9LPhBYez/+DUUiIHJPn9S4PweoL12O5ClkH3h6ivH3mvGU5gOCErK1+HZJff56wJX8QsnotaloGWK1er5TjXdMKSyu7poaLsYUz7n07y34xkZ8PLdrYuXmYlTbt5Y3M10pCZUEXsYXk5Mg4qRJkESoBGtF+SiRiMMB771XEgXU82L5dJs3/4QeZ/rRpU2kEX7dO+lU6rKieOLb98ot0D331Vfn3li0wY4b3Y2ma/Dy9/LI83gXPwIHycxzEU6ACzOcaevEbO2nmdPl2BEs++6wscOBK3boyX+yBA7B1qxS2XboEXRVXp4K5qOtx1iysjd2qugRzBULQZVAyrz2rcvGYG8iw7+IT7uJn+mPFRBf+YjSTaLZiJ6w2kPDJJMTY2linT0Vr2gQoAC/R/57CwHPJ1vMTWtpKTwNbJ/n0WfW2dF0aYVWSamgO1iyM4Pv348nLMaCqAk2DmeZ46nXN57ohvmMzThwysXJ+FKsWRJKXI4WL0FQX6eorNVr5sfrXGtjzHdLEf9+qKmjTQ+YOLg9/12BwfW995dg9W6VvtbhYsm4cQNaNA1Cysqky9g0Mp84Us8zK5HUQ9sK7FKzagOHK3ii1GrDKchnX3FqN7Gyj00/2yCGVBbPN3DMmn1GPSzeNyixkdRFbyJkzMvNARaAiuJlvfbyownffSbcBnVIjBBw8KAVQYqJ0A5gyBQ4dgrg4adFr3lxWfLLbix5WNm507yOQ/tI0WRr12WelePr4Y/91Kex2GQiYnQ3h5eN6WHkZPVpeHE0LynE8ieNsojVzvsriu3lm0tLke3TPPdIP1hf16skfncpFRLSV60dvZfbEltgKHDc8x+3T8f8iFFWQWCefd980U23eNCL/WEokMJYXGcuL7p0Lir60R49iGjAY+4KZUCUGKC5Kwb9/oudSr680WA48o94rM//8Hs60cVVxXHeHOLEVKOxZ2pSFedHEJ+VwKjeb1BYGYhPtmDIyWPKhie8XNfDwYT2LKIKQMI28bF95hD2aKwKjWdDyCu+1px2BRecD5VE4QUSEk/LCE0R8+wOhy1cVX50onJPNC3+Hhb+TSzgDlSNkI9BEkUC1F7pvfPyehaYtbYy+w1ypP/u6iC0kJqYoAUDpKb7sYVDsxBkzuHNwLjR8DmbOlGkPjEYYNAgee0wGc+mQnAzp6TKQLiy4UtQIAZ9+KpM47N8vt3mKyowMmR1KiNIF5XmSni59Xb/+GpYvD9xe0+QYLngRW6+edFwdMKAwKzn+L7iiYG7dghtvN3Pj7UWbhYC//4alS+W169YNunZ1y02vU0mp0zSNZn03s2XexfjzcVVVQb+BVp5+tQBLiEbcV5+7ldn0h2K3I1JTUb6bixg5DAgcUOMPx76OKcOfmK3MFimQ35d5k+PwtwS/dWV1Z/DVCwvgmqTlXHl8Ft9rEwFPH9aKwn18iiI/K2FRGnnZ/q5v0XwihEJBnsKUB+tx2wgbh6ML+GWuiXWrjShKQ8Lrp9DzumwiYypPiVpv+HIpKA0iMgKtSqz7s6MPpnMraSLKZzEaVRV8NcXC6Dsqbew/oItYJ1FRcM018NNPJfeJTUiA6+v/w6I10RykPiakSdeKmbriAD9Zrybu211Qp45UU7feKhWzflcGYMUKGDtW+pyCLN97++1y2T7JxwqRQ+g8/7xcYnbF2/tX3lUV7703+LahodIa/J+gd2/pQPzll7BsGSxaJJc4vIlZIWDzZnjtNWl+DQ/nSHIogwbJ99Y1tVbLljBnjgyw06m8CAH7/2rkzP/pDdUgmLc8i1p1i76oYXt3lSz3pSbghx/J7XUpEHx+Tn84/AQdgsJTzJ4P1tgjuy0kHw/C+lj43ggBPx3tyhLaAhpnI8BHQXNmUHdQtY6VgaPOMGt8Av6tsIXqzEWk5WYa+PQDlU8/kD75jqlG+SOB36fHM3LcCZq09Z69oDSk5lrPmutCaTDt2osShO78nR6oaNh9vOeaprBpnQFbxfhYlhu6iHVh7Fh5zxUiONFjMEij0/d3LYS+fdFQWEQf/uAyALqznKtYiNOj6NAhua6dmgoPPVRh53E+sWABXHedu8bJz4epU+VrX30lRWCDBrK+A8CWjXZuvV1hy9ZzYxFRlOAfdIxGGfj1n8qKFhsLY8bIn3/+gV69ZMSkNyGraTLn8f/+R7YSQY/QXRzKrw4obtd4506Z5WHLlv/QA8F5yJlj4WQnR/hto9nhn79VatW10ywhHHFoD+SWTGQogMjKdeZ+LUm1I/Atep1WWR8uBg4hW1mtsdmZJR+XhoEc/L9nZUdaXlVsGNCYyY00ZjdHqUEip1j/zkfkxidSrW4BqSeNbjlhi/dD8QwIwqFqXXPJgjUfJj5Wnb7DUugxKIPQiMptlS0vgskRIlACGWsRQuGLLxQmTongyEEDUTGCawZbuXFYAfEJlcNCq4tYF9q0kZHP11wj77n+UBRo3Lgw9dbN74DBgGq305eF9GWh/50ff1xaY+OLl3T7L1FQIIN37Pbi+sZmk9H9vXvLv1UVru1yhocL3uTaNc+QRQTnIi2IopTMJUHTYNMm6fbcty98/70sihEeLr1JWvkuj31hcPHFsH69/LIEeKKfJm5hf041hJfp12aTFbk++QSeeqqiBqtTVrYfChxYoKqQnqpKAZt+GsMXX0llWwKEqmKrJa1hwVQ4ciWYOvau0duueFpifaXXKg88sw14sn5PHtXURCyhNuKqy2sQV63yWs0SOMVoJnIXn1IDed1aINN9Wad+yMLRz3Fx3xS2rfLndxXISlt8m9AECz6vwtIZMdz35gnqt8or9Tk48MyE4ItAlntv5XLLSkHLZph37gl4o+rOcmYxxOfrqioID4f7RxsKXS0VMjMUPn7PzMwvTXw5N4d6Dc/9Q0HlfJw8h1SvLn0e/ZGQICPc16yB+Dghl01L4oNgt0unyv84P/4o/WCDEYWaBvP/jKbPmhfJIhz7WXn+ElBYJcigyN/NmpXMC0TT5OdkyBDpdz18OLz/vsxucNFF8oEpM7P8R16pCDJ/7HRuxZ8jl6ZJy/x/nXHjxtG+fXsiIyNJTExkwIAB7Nq161wPC4DQmMCCUtMUOrQwFSWI/3paQP89TxRNI7fXZaUZYlD4yyPraYUNNnhoYOukEifb95aZ4MxxI0d/68nSd67kmzcv5osX2/PZC+05vq06ibWs1GuRi6KW1EpWsVY1IzaG8iUv8JJTwLpyyW9zub5pHE/cFc01NxRQlFrLdXzC6TtbMhRAIT9PZdLj1UlPLlsFmmDfb9e0bN5+PAmUuzhYcnt0QTMYAr6jtzGNSDJRvYZFyu9pVhaA4mYZ1zSFjDSFMXeGlkuMSVnRRawHn30WuJqr0ShXSiMjkctgJXWiNRhkKP1/nJ07i8r5BoMdE3mEYKfiI04N2EjgFG3YSF32c7mylO+m5fPYYyUPDnN8PBy/rdYiTffzz9C6tVwmv2AJUqUnE4fA/w0mOVnmc27bVvrJ3n23e4aJ/wJ//PEHo0ePZvXq1SxevBir1cqVV15Jdva59dfcejyDsNhcGrbJdatz746gShVB366ngMLl+9Nngk7S5JA2uZd1puCikqeeCosLC+g/6ysxvacbQUVaYT05ddjEgi9i+erVRF4bVovNf4a7Lamnngxl43ftWPlTJDeMOYPBKPy8B8VRECg+xIwDE/koPkv/avgTwjZM3MlnPl835OQQ9tuvaELjxXdzePzFXKomFfVXNUnQrrMNpQyKRWgKBfkKK+aXb1U5R9EDV3zlFfbE0c5XMGEwqwaunFi1luPbd7H92pvQjEaEi8XF892JIpOfuJpQcjFQZGQwIh+0TCbhM1We3a6wf7eBdavOfUlK3Z3Agz2BrfAcPy6Xws1mZI6lkqJp/znHvuxs2LVL6vcWLaR4jYgoTcBVxQfDGSngFr7hHR4jnsL0LRpw9A1S7noCs7n80rEJIfOeXnQR3HST9AW2WMqn70pDo0ZBNWvMLnbTGJuPhxRVlanwXn216IFg1y6ZnWL8ePlg+V9g4UJ3d6WpU6eSmJjI+vXr6X6WysOdPhrGpuVJnDkWhjnETuNLzpAXl0dMbluy0gzISpgeEeiFAmiS6UFC3zXB9X0gMR5hMUNeflDfbHtCHDl9e5Pb+7IKDYz1JmBdCaaUa0lx1Jh3LWJgt8HMdxNY9XOUzPfqNFAWS6AEwMy34ph+z1t8O3M4bz2j8vcO1/Pw7ynZkq1soyWytIEUX0ZVw6Tl8Rkj6MVvXMmvbOEiZzEKKBI9tfiXf6njtkomg7hU/scrNMX3aoEAam1cibJwDuryP2mjqLzasxf/3vAw4qKLqFkTVq9W6NmjbO+50BQ2Lg+j37DUMvXjj2AFrK8csw5CGzYrka/3iVVrAcg0JUFtWD9sNNW2bCD2wF6MebmEZKQV+wR04y920IzJ3MtsrieXENqzjp6G5Yy2TvA/foNg2UIjC+eZWLbIiLUAWl5s55YRVrpeXiSKS1NytiRUqIgdN24cs2fPZufOnYSGhtK5c2feeOMNmjRpUpGHLRPR0YFTbVksYHLMXR99VPKD2O1w882lGt/5Rk6OjNv55BMpZEHmcX3sMRg8GB555NyOz5NQcjhMLeJIKf7i++9T5fHHeeQRhTfeKJ90Xa7MmiWzZEyZUr79nnO6dZNpBfbv9/vFGsnHzOV6n69rmtQtrl04LNoPPywt2j17ltegzx/SC/2fqlSpEqBl+bBifh1W/lQXRdUQmgqKYN/meFAau1gHi+f4acE23uBJ+p38BTFehY8/Jee1JzA0qIdlw+aAx019+F4KLr4o8FJZGfDnB1taNwJ/CAEHt1tY9XMUyceNZBaEEHpZCjlxB+nfqzk/TIhj1YJIAD/BTkVoqMz4uAmzp9ZmcEEBBwwNOGKvjqLArWIax6jhUSFPyprneYkneJMPuZ9JjOIQdQkni5urLeOxY4/ShD0A/EU33uFRJjGKU1TFgI0BzOUpXqche/kfr/I5I8hFWhDrcIinjG9zj22S33ErgGHCJDAYUAqfUI3fzaD+jG+wvTUO7ao+dP3kTbop97FSdCqTO5m1QHG6dXirtOZKSd/jYAWs5z5l9Y11E7CFFERE8W+nHvzbqQcAMYf20/Sn7zBa3S0wtTjCqzzLqzzr3DbYPivgMTUB0z8zFwY6y8/mqj8U/lpq4o6R+TQYUKZTChpFiIrzarjqqqu46aabaN++PTabjWeeeYatW7eyfft2woNImpmRkUF0dDTp6elERVWckndl8WJZKtQXRqOsEPvll4UbTKaSlflSFLjzTqnqLlBSU+X1Wb1augufOeNdu4wYIfX811+Xfwqs0mDEyt18wiRG+260ejX2dpfy5BOC995XEEJal202+VvTynYuBoPMUFW9eun7qJSsWCGzFNhsPt1vBHAz3zKLIcVyFyqK76UtkN/LPn1kijxHdhHDWVjpOhdzlCuapnHttdeSlpbGX3/95bNdfn4++fn5zr8zMjKoVasWD773M5bQ4G+gO/5O4KfPfC3j+7L0CapxnF00IYqsoq2qihYVSfq9w6jy+vt+jytMJk5PegsRGhL0WL3hz52gJG4EgcSNrzRMrvtqdvjmrQTW/BKFahBodgUUDYRKTK0UHnojg5dvryO3lwALuaQSSyj5btuPU42HeY8flMHYhPxyJMXn8iwvce+Z1+W5F7bVUFAROIL+PUcggCwiCCEPE+73vyzC2UtDLOTTWNmDtd1FWNb+49MG7DubsMvrCXGQkkaqPYrrmMdfdCu0AAs0xYiCwC4MTsuvLwwGGV3/8nt5Pt1BHO9boPfZ9T12taiWNHOFXdOcIlakn3bLeeywxPoLXvQmYL1hzM2hw5R3AvqQHqEGdTjkZm33jW/r/p0vnaDNZdmltsTm52bzwZj+AefWCvWJXbhwIcOGDaNFixa0bt2aqVOn8u+//7J+/fqKPGxAhJA5Sa+/HurXl0u5L78sUzp9+qnvm5+KDaMtlyfX3SAjTDStZLmTDAYYNQom+X8qPZ/58UeoUUNaWGfNglOnfIu6zz+HgWlfcNOVcsnegM05MflCxYaZPAx4C5AQtGUdd+L9AUHFjoKGSvGHDgM2QsnlMd72f4JvvomhVhJvv6vyb3gz3uk2lyfuzWDKFJl5oKxi3G6XQuyCo0sXWLlSPiH6WAZWgGncxks8TxxnnNujSaO6OIZfnzub/E7fcguEhEhR27ChdDPIz/e523nP6NGj2bp1KzN81T4uZNy4cURHRzt/atWqVeJjCQGrF9bGdxJKXzJE4QTVeYR33LdqGoa0dNSsbArq1vb57gog5/JuZRKwYXFhfv0L/QnY8sQ1uGvxNzGs+aXQyuoQqoWVk9KOxPDZC9VKLGAB8gnlby4ttr06J5jBTRwV1Vge2Ze1Na5mz1VDuX1CDbIGXeP27jnSQvp6qxUgkiyngHVtFkE2bdhEU3aiomGrVSNgTgG/Z6kocDoZxW6nCqkspzvL6cb9fMhQvuItw1OcEIks4kras9ZfT9jtCjcNk5bIga2TvP6UhfJOvVaS/MeRVv8+2lUO7AlK8M1hYJBH9C1gFVWwbFZ0kP2UjbMa2HW2l728IYSsjnnFFbK40IEDMqjmhRegf3+ZCsnTUORweE/gDIvoQ/Ods2W+19tv918f05XnnoMjR+DDD118Ec4/srJgwgSZOalaNRlg89FH0m1g40aZNiovL9jqWIJR865g+sJ4dtCM53iZ+/mQTqzCWyFJBTsqgm+5mb4sdAsyiFHSeE35H3/TgU+5h4+5mwROue3fhF0soC/XMB+Qotbh0F6HQ/xOD+pzwP+Q586VTtFAUsZOxvw1mFe+qc/dzVdw7bQhNGeb00esNKhqUbGrC45LLpFPiqdOwY4d8M47xQStETvP8irHSGIjrdnAxaygMyeoFrD7/Hz5/XX4K+/fD48+CldddWEK2fvvv5+ffvqJZcuWUbNmTb9tn376adLT050/hw8fLvHxcrNMnDka4bOIgX8UvmYoqcS4bRUGA+Zde0kfcy9aXBW3mHTH74Kmjci6cUApjukuXkMbNvMqCgIJ2IoI5jqdbmPpzBh8yjehcmRPCKXNGpCHb8GfyBm6ZS6k7dGfCf3me0LveZqQ1evcgoBc8fduC0XBWjMJERaKUIryjgpVBVUl4+47ECEW+XcpUYR70j0F6cs5nkf4lLt52PYWcUoqV7KYNXTkGV4FcAtWcvx/4E0FrF9jZNZXJk4eD/w59pVN4mwXPPD3AFatU3uqdWoP+BeyqtUa1KcpnWhUnwF8wSE0hYPbQ85K9oKzFtilaRpjxoyhS5cutPQh/LwteZU3X3xR5Mbq6gXguNheCwthoAVbWE9bLFhxvr/ffCNzJv39t/+DhofL5JbB1lKtpJw6BT16yKwCIK/VqVPyoWDyZHC4Ogf/wVU4Rk220ZwWbOcFXgLAipExvMcURqJhQDXIJ+gEQypT7bfTV1nE9WIuh6nJVloSSi6dxGosLstnd/Mpw5jKH1xGMnHU4wDtWYsCXMWv7KYRC+hHPhYuYQO9WBrcF9fT1Gq3y6TCvXqh2O3MZx09+J0jSFEhUDEq9sLlu8AVcTRNBr5d0MTHy5/ERHjySa/uOGastEb6ST6IY6k58E3H23d6+XJ46y149lnv+5xvCCF44IEHmDNnDr///jv16tULuI/FYsFSxojBYHwy/VGAhY20oSe/u3aKkp2DFl+F5NeeJfSPFYT8uQo1Mxt7Qjy5vbqR17E9GEvmG+J60/dnzfIlYB14s6yV1Rd2YOskPpiRQk5moHMKJmV9cRQ0WrI1iHaAJlCzczBkZgVq7nV0KJA54hZsNaoTunwV5o1bwa5ha1SPnJ7d0BLjyftqBpEV6S/mIb5f5Vnas5bxPMwKuqAgaMM/HIhtw5wZZlRVIAS8+jRcd6OV/72Wh8WL5h/YOqlcHlr89eEQwv78Yh0BXmFxYX7dCqp1as+JVWuJtB4r5loQaT0GMWpQn6bG7PYZXOuO/96Us1SU9KyJWMeylz+/rXHjxvHiiy9W2BiEkDezkiasB9hGK2ZxI7czrWijqsK6ddIkeeKE9x1VFUaOPO8FLMBddxXP3uD4/7Zt8qek2cZAsJCrnEmvAUzYmMj9PMsrzOM6MuxRNA47Sv+7kzCpzWC8jM6uxRFqccRnzyZs9OY3r681Zg+NHeLIYIAWLaVJvjSPjna788Trc4CttOQr7uBbbiaNGJqL7dzMNyzlciZzn8+gBFWVlYkvv7zkQzgv+e23oPzJZzEkSP8s72iaXAB5+umz4ydb0YwePZpvvvmGefPmERkZyYnCuSc6OprQ0NAKO25YZAHh0flkp5spbZYQzwdFRQhCVv6NtUlDcnt1J6ffFeT0u6L0Y3SxugbCn4AtS1UuT+udXdOK9dW5ToIPpydXXIPjgrveRqz05yevuVh9HiUIgelLTtsTE7A2rA+qSk7f3uT07e187cSqtbDvAErdOthMZgzWAh8e04XjCHrE3jpxn7cHMI8BzEMA22hOB9aSl1boi6wVldydO8NEVqbCu5+UX1laV/xlsXB8TjyzFNhjktz8YiH4TAUOiyyrirtVRF5/NbZVazGcOo2i+b7PXcc8qpBMKrF+/Yv9oaqCJm3PzpLiWXEnCHbZqzyWvPyRliatiKUzcQsmcL/7Jk2TwmfePJkvynPSUxTo0AFeeqmUI648HDggfTV9aQ4XHVciVDQK8O5XXJ0T3MsUnuAtBuR8g+nD8dJpuTQ3F4OhqG6tY3/H75YtZVRQSZLW+iGKTO5nIivoyjZa8p1yI9czlw95kB00JZETxXx6DdgwGGTF1q5dZbooh8X7giXINf4cyv4AePIknD5d5m4qBR999BHp6en06NGD6tWrO39mzpxZocdVVWh7+dFSq40IMmnHumLbFSDyi2+Iv/8JEu57jJhX38Xy93rQtIC+rK5UtIANJqDLgedSs2cqpUZN7ajGYG5Ejovt2dazGICcQ5I45j8w1QfFe/M+Cs9txhOnMG9xF1cnVq11CzbKCKvNge5XeMlXId0RhKq6uSJ4G5ffsQmBMJu8tlGQltkCLF4DQ4VQWPyTiZ1+SpiXtECFJyWx3PtaEQD5uQ72u+AQsw5Xg2qd2oOikH7fCDCairl3uF47CwV8wXBUND95gf2jaQqX3xSgalQ5UaEiVgjB/fffz5w5c1i6dGnAZS+LxUJUVJTbT+VBYQsXeX8pPl6K2fvvhypVpM9r48YyqmTpUulOcJ6zalX5p5QCWbe7AwHcMRzY7TJxfmmWpqKiZIT81KnQubM0eV56qRTFq1ZB8+YlyzJRElwuXCP2sZGLuZcphFHoc4cNFQ2rFTZskMP58EM5pA8/rJghVQratAmqWUu2+qwqUxIulPy7QgivP8OGDavwY7e74gj1WqQgQ9ZdJgTFkeze+yShYOc+JhGOb+uMIS0DNTML8649xHzwCVGTPge7/K4HunlXBguss387LP/NyKwvTSyab6BO4fzvKmSjY+Ga661BVqCSoU+OthaLYPBgwS23aIQZZAnVWFJ4lHdYRzuSOF7yQStKqZ5NhKoS8ndRoLareHVd0j7Z6hJ29bmOgvAIt/1zqsSzddDt7Oo/yClmXfvGoJJ9XV/5t7fjKwqpDeuTdctgr23y1BC+ZzD2ACs5H71TNDkIARvWGJj6kZmsNXU5dagEwdtngZIKWVdsDeqS/PJT5F3a1ilkhdkMVeV3QRgNCKORa5jPb/SiNv8GcaSi773BIKuq9bv3JInNyt8d1BsVmmJr1KhRzmUv19ywwS57lXf6GiGkMNi1q3SCLIZUUvEISlMUaT574w3pMtCkiQxgORvOIGeRGTPKP7WtARv12c8umlR8CYPGjaVp09f7kpUlLbUVEVXlOKbHh86KkSPUpB1rSSPW55L5b79dwC4GnTtLn3I/Zvxp3OruxlNCVBXat5cp38qbc51iq7Q4xl3SFFsgU0NtXVWNf35PIuVEGEazRmLzI1x9o5lp46qSkWzEsQCtqgJNU7g6Yik/ZF2FuQRBjwLIv+cWjI8/TO7eHX79AYOpxOXAHpPk0+LlT8QGY4nd+Ec4M96NJzut6BpERApefFGj142ycp1BVSnIh3tvDWPtCsd3PoB/IRpv8Tg3RC8i9uZemB8YgdKoOcKuYRt6D6GzviqzRep0w6Yk7N2JpqioIjhDgVAU8ttfTPqD9zi3nXBZyi6W9knTiDp2GFNeLnlR0WQnVHPOj3HJu4jbuoOII8cxRYRT0KIJOZd3R0uMJ2TFGqI+mw4FBQhVlcFeQnC6cXOy6lenzuLfnfllXW3XyUo8CSLQEowgLkHw++Ys9u9ReeTuUPbtMkjfWWSQUtP2OQx77iTh0fK6eAZ2OR5QPD87/j4zDgvvwNZJxdJsAcVcChwE+i4ETYGV8BAQEeGENm0Jm7ahLvwNduxGXSkNS9toRksXVz9vKIogLl5QNUlwUVs7N95RQIMmmvPcz+sUW+dq2csXikKpyoYCGLByPT8Uf0EISEmR9S9vvRXatZMWpnXFl83OZ7p1K48c4y659LARRQbfM/gs1OACdu8GP/7YRETABx/I/3sKXYPBvxkv0AOLj1QNJmz8ypWkUMWvz+fTT/vv/rzmq6/k6oUfZ9Wb+ZZBfFeGpS145pnSDlDHk5xMM+lnQrDmG7CE2aheN4P4hqdp2i6PsTMOMeiJY3TuYaNJCzs9+liZO8/GnObPlEjAOjDPXUTu7m3lc9OuYLauDOOz56uSneYuTLMyFR59xMBvM2U6Lbum8dmH5sKSnQETTDmJIIva6duI+ORDzJdfidiyAcWgYrm0NUoQRhOfKcxUldy4WI5d0Yktg24jpX4jCiIjyIuNxm7yvkzvRFGwVXfPHOI3Wl5VyahZh+SGTclOrO6cOyOtxyiIikQ8OprM8a+Q8vLTZN10PVpiPAB5XS7l9MQ3OdKzK8cuvpR/L+3Ozj4DyKmSQJ1FS1Hsdq9XMlqkBpEtRiH5tMKpEwrDBoZxcK+80Wmagij0n929PpQPH03CXoLFukBBYZ7iNlAJ2pLi6tbhFbOJbM0EJiO5+3ZCm5aIxHiUVWud73kTdhOO/7LhQsDdY/KZsTCbZ17No0ET93m6X8/mbD1ecVbZCncnOFfLXr4YMUKmagV3F0j/c4BM7fQw7wV3kG3boHt32By4Ck1l4O+/ZX7NuDhpVL7mGplz05UaNWSqz+ApzDOIoEcPwciR0CguDRMFJHCKh3ifTbTmIraU23n4xWCAP//03+bOO2Vy24YNi7YpCvTuDevXyw8PFH1wHL8vuwwSErwLMVWVTwA+MnIs4koC3cQchkqbTVY5vuiiorK9t98Omzb5P61KTcOG8M8/8MAD0uUD5G9HtQeDAYMKM7mJN3iSYFMOKYp8O1QV3nsPrr22Qkb/n+P4wUg+e6E9axbWJvVUGNnpFg7uiGXDtx2Y/kYCBiO0vjyDKd/mMvPXTN79NIe+fQV07lDiNEsKoJ5KRkk7O8uSZUEImDMprvA+4v37/MLzKnXCw7Fa4ZvPzU6BFCxX8isAil2DM8mYRo1GpJ9G69gWJYBlRgCohQFNjmXkwh8tNoasZx8FVUWrZuHoVV3ZcceNpE94g5yB/f3fHIUgt0dnry+5CllfqZ9cX/O2/O12qNAQUpo34XSTFiTs3kbTRXOpvfoPVI8UXA4UwISduhwk0LyhKPDtF2bSUxVn9SlXNE3hyB4Lm/8sWrUIJnNBsP6wwbqwBGuFPbFqrdMKHkjMOvqzfvQxhnHvuaU0M2JnDO/7cecSmC1w1XUFJJ9RSE8N6jTKlbOaJ7YyoCjSz3D6dOlaEBsr3SOff14GLsXEuLcFCDfZmatcT0u2BXcQu10mq3zuuXIff3nz+efQsaPMr5mSIoPfFi6UeXRffrmo3eLF/g2ZxVFYp7YnHzPLjjRm8sO72H2mCgXD7+WUUo13eMxvZgGfGI1ywBZLkWk4WNeNYNrdcIP0N9m0Cf74Aw4dkhekRQv47DNpYR85Uir9O+6QJcmWLpWJ/C+5xL0vVYUBA+DgQZ9RWilUIRhLzO+/y+Ic994LW7fKj1h2tnTzaN8efv458KlVWmrUkP7jaWky2Cs9HY4dgzVr4LbbADCg8Thv04C9BHNDGjBAWrD374eHHqrwM7jgObA1lpnjWzFt3MUU5BncgmSEJr+Ha36JZOV892U/xxKpfejtoKpBPoJ4EMQNPic5p0R15subI3vMnDps9ltVLitL4ZcFCuG54aSlBH/rNWDjemZTj4PObYrdjrpmPYb1KxGNG6F164jwsZohgJyqCSS/OZbUJx8kv21rbDWqY23cgMyhN5H8+vNoCfHO9q6W1Jw+l2OrWxuhup+Xw3c168YBbvt64s0q6xCukdZj7oFHQWBOS6fVd18RmioL5AQz8w/jC7+vK4qgTTs78783+U0jpyiCNQulNd1TnJZ3kYOy4OnOEYyYzTmdhWXabK/fz6d4nTZsdMu7Cw7/V7h+oGDIlZH0aBVJ1+ZRDO4dzi9zz1riq7OXYquyUFAg468+/VTe7FRVlkmdOFGWSj11SuazX7gQrFaZXOB2+3SiH15QsgPZ7bKaQnKyNHFWQnbtkl4QQrjHNDn+//zz0ojYo4dMc1uS1GQKGrW0Q7Kiy4ED0lq5fbt0tShNjjMoEqETJkDt2lKBr1ol38TFi6Wq84XdDj17Bn+ci3wE8bVtK388adhQmkw3bJDi688/ZSDZ7Nl+D1UzSCH/2WdFJVVdsdnkcIcMkTUYziO3zOIoinsFvH37pLuBy0mPZiKPMN5nFwaDLFoS4LLrlICVP9Vhxfy6hYFFfmSDAotnRPO/x7y43tSsgfbuK6hjnpGeosGkdVIUtJrVEdGRkFIxKZDKi6w0/4FDIEXQqdMKxqCyEuAsodqR1XzOCO9ttu/C0KAu2jsvYxj+AGzbiVAUFCGcvq2nmrbiRM92VKtWFXu1qhS08l422KuQtJhJ/d/DhM/9hdCly1Fz5Ptgq5lE9nV9ye/YLqhzcc1h6vNYQVB1/SZUmy2g5dmV+5nI6zxNFuF4s9sJoXDHyAKeedB/nI4QCtvWhPHjx1XoPyKl2OslLU3s2tZb4QRvqbYC4asErePvSOsxTqxaW+z6G/89gnoq2WufEWTzB5fxBk/yEfeRjHxouaxLPrl5CjNnmt3uS7t3qDxxXxg9b4vj+rsrfhXlPyNirVZZEvXJJ+W9EXDWWAepNa+7Tlq8brhB/jg52Q8eM5Q8et1RDaCSitjJk6X+83U/MRrh/fehZk2pzYLFgI3eLCGRQod6u13mN/r8c2lZe+SRwJ3ExsqnC6NRihurFSIjZYGJdoUT51NPFbV/+WVZds3b5GY0SvF8afFSjOVOq1Yyq/7ChUE1H8QPTOf2gO1++8237hcCcnNh2rQiV5nznowMmZjY46RH8AUv8TzpRCO8+BHb7TIZSIcO8mNzxRXScF6KKqs6wJE90ayYXxfAr5VRNlBIOWYmPTWfmCpF75ujHrzo24sc86so3/2CZaNcTlByc1EKrF5FiSIEBYP7gaIETPQebMS2IzOBN8qSmSAmMfC9QQiFmjUFtWtDvXqCAwfA30NBT5byCOO5ioUYfPmDm03ynGKS4LsvsE6bjnHpSgoOHiE/OoqU5o3Jrl7NbRXK27Xydm0d7ay2cI7ffCdht91KVM4pMBkRcbEYFKVY8rtAyfjLhN1OzO59QQedOYgmg/lcQz8WUIDZmafbgA07RmJiNd5+MQRVDSJjrVBY/E0M6WcMXP1w2QshxIaavKbwUqITnAFeJaVYMJ3Ha96ErJLnP91hBNm8zPOMZSzJxKHcPZD5DZ7kzqfqF2vrcJNZNi2BSy/Po0aDglKdR7D8J0TsoUPyZrZnj+82jtibF14o7g9K1aqyLNUHH5TMgqgosipRJeWvv/zrcptNGhPPnPHdxhMVO0ZsvIJHeSRNg2+/lZF1TzwB48Z578Dh73HvvXLpft48qdBatYIbb/RdNOLpp6UP8vffS3Oc3V40cdeqJU1zZyNjxKRJUsAG+Tm5hp+IIZU0YvA1eUZHy2chfwghfT/79IEGDUo04srJjBnyffcgmgwWcRVX8iuZRKKhAgoGg4yCVxTp1uxIdrB+vSxw8sMPcPXVZ/cULgQ2LEtCUTWny0AwPPNACHfcm8tQ8x+o06ahHP4XEmMR11+DVjuJnOG3OENFDMdPEvvqu6hpMqekgvTZVDSN7L690a7o5laxCIoLpWDTawVKreWPQJa16nWt1GqSx5E9Fq++rooiiIuDrl0FL45VOXUSfH3fjVhpyVaWcIX/kq9mE7Y+RR9qe0JtTMOHktutAwCHf/oDkOLRXwUz12vrSl5CS8Z9VJ1PZyaQmWVAUQRXdM3gmdHH6dLIV4WvinPpyD2cjFrKyl89+IOdNOUj7mM215NOFGfURBQhSEtVSUsFRQ2yQppQ+HtRFJdcnQytSzUcn3hW7vK0xsr3zr9frLeKXa6vQfEHCnvVRKcF3x8GNBI4jfLJx3wU9wSKInw+3KoGwYofoxjycAkERCm44EWszSYFrHzq9Y/dLi1eZ87I1K9uvP22tAZ+9FFR1IjVT9SjY12zklphIbjqRUaj1IDBegA0YB+fM4J2rC/+Ylqa/P3KK9Kn9fXXIS+v6HWHi0CvXvLvDh3kTzAYjTBzJvzyi4x+2rVLXvtbb5XRT5GRwfVTViZMKFFzI3bG8zDDmeqzTb16sHFj4L727pWeDsuX+/aGOG/YuVO+p16+Yx1Yyz4a8AXDmc815BsjaHxjG76ZYSiWqctul89PgwbJj0Tdumdn+BcKx/ZHlUjAAqz8w8ifS6NIYQWPG+ag2O0IgwF1/iJCLr2YnHtHyFzagL16VZLfHEvIX6sJWbMeJTcPW60a5Pa+DFPHomBIh/DyJrjKmhvWQVlSawEMfvAM7z9UAwXh5lvpuNG//oaNa642sH694uF7KcWTw32gLgeZzzX+BayiYB92B8TEOM9JpJ/GHpOEuV0SBet+o/7Vl7ntE9qwGfaYpGIhOuZ2xQVPSqpCj37x7DtgdAY6CaHw28ooflsZxYwvUrmmb16x/bz1VVacIs6+DRFiCWg19EVtDvMaz/A/XqW28RhCUz18u4M3cqgGwT+Lo5nTqLgrgL+ArwXL3NNV9etZ5NrhWbnLnzXW18qEw23DG/5cObTYaPIvboVl49aArj6Oq7QluQbeQ+oK+7QrHNtf8Tl2L3gR++OP/i2w3nj9dXjyURsJq36UqtZul/ks335b+iPMnCn9D7Zu9R5RYzBI375XXimfk6gg+vWTxk5fKTqNRujbV7p6xsQIUlPB+5OqIIQ85nM1vVjq/WNtMMjgKJA+DC+8AA8/LK9ferr0Kb388lLl8crLkz6jkyerHDzYn5iY/txxh/R9dgS5nxXy84t8VUrAML4kjxAe5y2yiMCAvTA5t4KqBp99QAiZ7va22+Q+53Wq4ogIv09NcaTwGO/wGO+ADUYt+QEYiLfPpxDyM/7RRzKds07wqIaS+647RM+TvElX+190ZpUzh6fx741ExMwh6/YhzvYiLJTcK3uSe6W7z7qJ4gLVVczi5XV/+MsN64uS+DbWb5nP8Df+ZeXUmuzYUmQhqFcPXn/dxo4dihcBC66f2fd4kJF8TAj+hZp2TX+0d99HMZtdxh9Gs4RwRPppzO16OcWfQ8DbkdfA83xdLX8OXnxOZd8BtVikvt0uiy4MGxXLko3pONK9u/axdy9MmqTy4zyV/Hxo105w3yiNK64QJZ6THMIcILQJiBsHwrTvnJ+nEvVV+Hu6chtptgg/AiywRVZokJ/uW6C5fmY8hasjZ6pr2ilffrHg3RobKIjR0xobjC9y5u1DMO3Zj5qdE1DI5mP2WWmzCIEltHSW85JwwYvY+fOlGPs/e+cdHkXVtvHfmdlNr5BACL13UBARG6IggoKgIthFRexiL6+9V2yvFXsBURRBRWwUUZDee++BUNLb7sz5/jjZZDfZmZ1Nggbe776uvSC7U860M/d5zv3cTzhy1lfGSt4bW8RP8mVOcZVWk3r3XaXlnDoV7rlHfScljB2r9JjZ2eUb6NRJsarOnWvuQI4ARo1SL/WiouC6WClVrtQFF4AmJMFE8b7owTvcQF9mWO/MMJREwB8JCdWuoJCXpyLt8+eXtzkvTx3Xe++pqGR75++56sHlshcZ2+AG3uUKPuM7hvAU/2E97ZCIsDdlGKp43MKFzoPYtRIXXRRojxEC3+/rgWHz4jEMpfL4fxLrHFKCK8LAyUs9GFx4eINbOZl5Zd8JKYmZ8Qf5Fw5Cxlgn0oTSuIZDXkMVN4DgUVgnFkoV0bRjIf1fLuTb8W4OHRSc1lPntqv3EZmayu2367bPs0CSR3xIAuu9cwzms8+z9kAB4Clru2GapdPRqQHkD/zIa4Xj9a3jj8JC+PjjxKBWU6Aisvl5kt9+iGTIcDVT4tvG3NkuxlwdW1qGXK3/888wbZqLy68v4q5HisIksuo+aJ8aiwEY99xHxE+/I/dnhn1H+pb/Q56Gholhac4UestCg/g6oYm0E6N/K10sVD8aG04inZmawqEnHyTu2++JmrsA4bU+vimcj3RgbtX+xCPv73zMk9iiIttiQEFhSkE+0QxkGlu9zalDqfnZ4cNw9tnKB7ZpUxXquusupZedOVMlo7RpA8cfX/MHcgTQoIHKeD/vvEAiq+vq0G65ReksAUwZ/IZtyjZe5F4uClYIwgchVHhwwICaPQCUFHbhwspBO8NQl+vCC9Xlqthx5ufDZ5+VO1I0awbXX6+Wd1X1qdB1dYzTp4d/0wGxFHAcy1hH8OzhcLBixVFOYrt0UTZm06Y5Opf7Ca09P1JVhY9V7NqYyME9caEXtIAXN39yaqXvhcdL7DffY9RPxWhQn5KO7YLOwIRDVK0QKpEL7AlsOHXvC3I1Pn64MVuWxpbZD/3yveD1V+vz4ceSvXvtyZFAsibEsy8Bc8ydpQRWtd3XVl/lJ3VcMWXRUX/yOnVlRsjjOLDLTXFRku0ymgum/1mAbFdOsApzNV4a2QqvJzAJ0EdmP38vipKUg3Q63d48v2JEMuCY2nSk5JcfcY+6CRYuspgXVBB+f/svJ6pm9BYA0xD07F/5OKoy8KmIirpYqHo0FsJLqDNT6pBz/VXkXDmCpDsfIjIn+LVaT1t0PBjYPR+Cxm2ObFIX/A/4xEZEVM3NyUQnl3g+YqTfl6ZiexUL2kdFKfIyfPhRQ2B96NNHRe4GD1YuBE2aKM//TZuU1MBudl/D4Co+sSewAC+/DB9/XOPz27m5KuBtxXEMA9auVdFYf2RkKEvXm25SEdwtW5Ql7IgRcM45QfOJnOP++6sUifXhB86r5MdXFTio6lz7MX680ryA7Y24nC6UYFNRrRQ+U4v/hzOsmNMATbO7l0N3rC6Leznm5xnEf/YVyc+/Tsod/8G9Zn0VW2mNqupgwyWwnhLIzdJ46940ti5XkUPDEHi9qr87eEjjogv1UosyawgkcVglTJUWJ+jdG9LSLNuua1rZ92sz8wOIuu/75Gi37Sc1yUGyhAkJ8QIjK5rZH9fnzdEteP26lniKhWWij9AkC6bUCbn/ycv3BJBB/7YDiA7H4f1rLsbrryNLK4pJXUe6StvduQPy2suRbVshU+tWIrq9mV0q17JCqPta0u3MXJq2r5o21w7BrmlVKnj5iGtVHSEiNm7GnZdneSYSyXYUic3zeDDDj+eEhWM6EltYqDxfqwoJ/Eo/7mJs+ZeGoZhTTIzK/ho2rKxTORrx+efKgqiwUEUgTVNNw2dnKy2sHR8z0ZjPSfY7SE1V2tcjgLVrQxNOXVdEtbdfjsNllyni6j+48RHhmTNVdNcXgQ4bp56qQrxXXVWlaGwh0VUur+qD261cCo56xMUp+c6KFcq0eMqUoIstJohvbxAc1ZHpfwEHM2IwbZO6BHZSAxceBhLcX1tA2QOoHcoi+YXXOfTIvXhbNK1Okyvvx0ZGUF0Cu2N9BL98lsyKv2Jtk4JMU2AUe2nEbvaQbhm98uLmAjEZZOWzKgHq1MH7/vuW+/HXVfonCfmO87PZ+9jwRwqZO91ExZp065NPk3aViVhSqkGj1sXs3mRdvME0BXGJBk9f0RjT8Nf5WhNAaQq2r4nCNCuPSQtyNeb9GM/8n+MpyNZJalDC8oFZdOqdw0XdyiOz/lFK84YbMC+5BG38eMSyxcjoaMwB56C1bVgaMLkdMf4btEefCziXlzKe+3mOLBIxg1Ig25Q6GjQv4cr/7OdwoadS1Hho1/RqRWMN0wyqUf4nEbF4OUmvvgMWldAAhjKZMbYVTNUd/P6dzYhJMGjQ1aTNRfuIiKp5RntMR2K/+UbN8FcdGp5gHc7hw8oiaswYFb68775qRd/+aXg8Ktv99ddV4n5BgXqfeDzlvOvrryWGN1SWosQdqi71ESyX5GTa3+cF/PrrqkJbdLQqsGU1tewj8bk2M15ebwh+etllytetXbvKv+m6cmaIigq66nEswxtSMG8NIZT0uJK7xtGMtm2V0NkCkSE0hD54vdXtD/63EBXjCRk9tHrh+wZit/DfoL8HLCslmJK4b74P+L46FbicyAis4ITArl0YzdibGoUksD54cZGByjINNkjV8dJdW8LJJ+aR8eCj5PXpW0YHZUQE5tVX41m4EJo2DSDgTkn3xE/cvHRZK6a8XZd50xKY8VUSL45uxFv3pFFcULn9A0ceKiWwQfx7NUnLLoVMej0Fr6diolqIhCgJM75KxOv32ji418WzIxsz5Z267N0SQfZBFzvWRPPNC+l89p/GFJeaIAR1j0hMxLzxRox338d89Q3kSSdiJDcs/71Z40otiqWAHzmXWArQ/GYK9FDvMpQWtkXnInIquKZICetXa/z+k4ttq6JrNPpYVb9YwLbcbDBEzl9M0itv2xJYgMbsYhTjLAIugUOwghydzX+2YvyLx1FS5CDKHyaOaRK7dm2Zk0uVoOPlVCxqrXo8ivEYBrzwwlFRYtYwlPNCw4ZK9WDHL01TYJhayAf7HGxM/Vu0UEQ/TOTnq4pq/fsrU4jRo4MXW+jUKTRZM02le739dnU/FFV2hamEwsLK+5NSmVL07KnuKbdbBV0tI/0NGyr3ii++gFNOUXZfzZsrucGWLcrHLchBnccPpLHXpla1Pbp3VyYaxwwKC+H005VLiAX68hsuBy+gMWOU5fONN/4/mXWC9idmOpRiSfzJjo4XF14mMpz2rAtYygrCNIlYvgpRWnXPSX34ULDzg61OIpenBD5+oj6GNzxbJg8RTGQ4MRQgMHFTUnbfduoOY5e3Zvt30zhw651sH/8Nq1dvpWT9ejz79mG8955lxQ5/AhtsGv63H108dX80pqGm+k1DlLV77YIYnh/ViMK8wPPR+ZQCRty1H92lLMJ0lyxzqmjStpitq6NQNQfCl4hNfacu797fQJ0/CR88Wp+cQ75SxqV2XqXt27o8htvvDv1s+1DxmsuTTkCmp5WVyfXhJOaznrY8wpN0YTmt2cBFTKKRtsd24CZNQVpbdQ/5orDLFuoM6xfLRX3jGHNNDB/e3ZRHLm7Kwl+qrieviHArd1UF2oFDJL71AeDsqr7BrVzDhwhMdGHgdplYPuVScGB3LH//1KTG2uvDMU1i4+KqHiAVmGiYjGKcsxVeeolSD6paCSnhmmvgwQdV8Swn0MqsnirfmDpe6nCIKxKmBk//HzRIzePHhjc1smWLipiOGqUqyc6bpwht9+6qRoL/SzUiQhlGWEltdV0ZIKxbF/x3OzzwQKC38L33Ks3sokXqbynh779h6FB4/HGLjeg6XHqpqipx4IA6uKeegvR0dV6OP75SMQwXBl9xMREUOyJmFXHllYGVW0tKFPm+/341I79gQdU04v8KCgoUgV2wwHax+uznKj5xRPyLimDcOKUFLzjyibNHNdr12E9iamiBuBDQNCmD0/iDU5nD/TzHJlpxAZMDlwu1HUDLC7woVYnGWkVhayKRa9rMNXzyThYFOTrhEThJOru5kMlkkMa7jGY073K7eJ0fBr7AZ98XUCcl8ME0kpLUwNdhHxqs7VLCWy9H2hAzQeauCJ4f1ZCC3MDzcsrgXJ76ZhtDbjzIqWdlcknHWUxoeQsH1xulkcaq5DgoIr1ucTRzvktk+9pIdq6PwrRxQlj4YzKFpbeFrmkhI+kiMbX8HtA0zOceAV2rRGQbkMGjPMFyjmMDbZnApTzQ8TvL/lFokthELx1Pyy0jsCuW6FxzYQwb1waeu+wDOp8+XZ9VUztjeI+M12F0q/aOK9U52t7MOSEjsP6IwMP7jGKj1pbH235E756+6Uvra7nsjwaWrhdVxTFNYocODUeWWH7nuvCgYfIFl9GI3c5WLylR+r1aitmzK5WhDwkdg4H8hIZZlmwkMBFIEhMFP3+ZRfz+zbBmDezapSpyjR+v2N/UqWHPaRuGyuPZUzro9LXVNxB58UXlHuB/Te+7D66+Wv3fJy/wlQ+MjJRVjrjNn6+irjt2qCCgL7rpPyjyteOxx8otvsLG6NGVqk6cxp8sogcjmIAbld2ZQmbA1JcVevUq//8ffyi1y4gRygnu2WfVMfXu7Xwg86/ixRdVyS0HeINbGcBPgHUykQ+GAUuXqrLL/w9ruCNMRty5PHRCkgZ9W25jtn4mczidp3iYJuwMe39S1zETy4uSVCcaa6WFrS6BBYguSEHYJrxVhobJjbwNqBKeo3ifN7iNF7mHU8Rcy4F4RcIWisBBYDQ2Y7dg41rdUtvqw8E9bj57pl6loE9cksmVrX7i19nN+HRlXzI26+Sb0TgjsPb3zexvEtm8Iqq0UpY1Soo0xn1/yMH+AuEjsrJXD4zx7yFP7GbbMgHcsPIWruqiZsh0P49kTZPExMBlT+zCFVH+/UuPRZYWVAnm/SvZuaQZb/+nO9kHQiee1iTClREARKzfhDDDj3C0YAv3dPyWZskZuF326xcXuCnMrcb0eBAc0yS2XTtlN+kEMaKIOhykHvu4kk9YQjeGMcn5zjStvCJVLcS4cc4qdPnDg5uLmMQmWnE3L3EGMzmbX3gt9Sm2bNfpPryV0neCmj4fMUL5vlaxLNLPP6uqSnZWSJMnB9rNaprKs5szBy67xOTkZns4L/I3hjGRgoKqhxxNUwXWH31UmVHY6W9dLnjzzSru6I471PmqsIOOrOEzrqKIKAqIZj/1uEb/NKBjrdiGE04oz8Bfu1bJMQ4eVH97POXndc4cVVuiUnnl2gTDUCfV4agrmiK+ZxCz6M1V2mdlVebs8P8kNjQS6pTQ7czdtkTWNATDOiwOaUBvdyWlplF00glIC624U1h5wjohf07hijBLp9KdQcdLF5YHT4TRNDwNrPW7wZJ8/Im4YcCyP2IZ91B9xt6UzqQXGtAov3HZY1MYRO8aHIJVc2N56vLGZO4q74tiMzM47/5R6MVFaNJkNmc43F6I51YKDuxxk1/s7ET2aZOCYZoBFa3sUOkeOL4L5ufv4P1EddRWZ0VD8tGKE5iiDeGs+itpUN+gcTODa28tYcofedx0YR2SMprw2N1RjLkmiqULXUEIbFkrACjMjuarV7tUKwJpp/EOhqq4EkhNq5L5mDBNClLrExvldbS+y12z+UPHNIkFpYcMFRDUdTg5bgUHSWEfaXzAKLqwMrwdmWatLlq/YUN4yfICkzjyuJivaM42nuMBZnIm0xnArdqbJCZWvS0HDyqSdaBCSeVffnGmYX7/fTWF79PWCwGnnuTl48Pn89f2RnxbOKC0s3Vye1s/dl6vCiwvXGhPrL3ecplB2EhOhrlz1WgryChDQxJNEQJ42RjDcdpKBDKAVGiaMoGYOLG82MMLL6h2WfX5OTmqSESYVXL/ORw4EHa4WAC9+YP3k+6mdWt7/iulyr37f4TGif13EhNfYhF9lFwU9x39P7s15AvMKn9dahoyJpq8CwdVq52hXvRWZWWtKiVVRFmJ0PTtOH11xpDPrbzBH/QmjspEWhgGSaOvcUzO2qfGli2bkw3v39mUDx5OY+VfsWxdHc2q2Qlcc2Es99wQjdcLaY1MIqOcU5ODe928cls6ew8YHC700Oqbz9G8HrSwNUgipLxH0yXXXhwTUlccnyBp2VZ1wO1TY6uVvS+WrkTq9tdOAIPNKUzf141d9Y7nx18zuPneQgwvDOkdy21Xx/DdRDczf3YYUZQaWZkxbFpetRL0PkIe7P62kxSk9eoRFpkt6dTeduRvdQdIIG7qdM7rtR2v1/rcCiFp1CqLqNiaNew+5klsTAy89pr9MoYB12vW1iUhIYSy2TrnnKpv4wijbhjPj6/zeZ/riKXClJ4QqqBDFbBqlfKjTU1Vutd69VShBV9Z1XBI9mOPKWveskSt999XJWyl5CB12E99h1uy70BLSpy5IFTLl7VePSXFWLrUthNJIJc5np68wS10ZA0JMR6aNVPR4j//VAO2+vUhPl7Z8jox97/9dqUGqXWozgmNiSGlrhly5iEpqeq7+F9CXGIJl963jMZtsgO+d0ea3FTvM77IHw6EnmCWQlDSugVmclL5d0BJp3Yceuw+zHrVt9SoiqdmOBjYpwPDRzQmLsnJi1iynSa8wp3EB/F/lYDZvj2ygyLHTomsDw/dHs2ejSpy7SOCPm3pL9+7ePvlSGJi4PyLnbhMKJimIO+QC2N1E4Z2TeeEVfPQ/Np1On/YrO07KriSTyzsqxR0XdK7n4d2nb0cd4LXcoZJCMmIkcVERgWPSocLUVSk9C9OljUMxKpVtJ/yJR4PXD8ihp3bSiudeYOVD7bZlmayZUXol7CV5jfUfV0T2tjCM05BRkRU0g6XtcFiPQG49mTQy5hLk3QrpxiJlHDSgB3VbmdFHPMkFpSVa58+wf3SNWHSl18Ymv2xs41V3Iimqc/771ej1NORx6WXOl+2F/P4hbMZzleVf5RS6TjDxOLFSo85bVp5hExKVdyqV69yDaonjFymmTPhiSdK//ALKTq1XAKz9GMNIeD88+2lGJqm9NfVxubNIafPoyniZt5iJZ3J9sax9YfV3HabauNTT4WvddV1ePvtarT5SCEhQSV1hauBAdi1i0taLbIdFOm6SoL7fzhDUkoRw+9YwXVPLOC4YYvofsl83n15Om/uv4oI6awqj5ASUVzCgdee4eDj93H4/jEcePUZsu69DSMtdMU1O4Q73VpdNG5bTGhTfEEC1qJ8AYh169BHjw6boO3cJpj5s9syiimlYPwHERQVwq33FZPW0DlBlhJ+nOxSpLo4sC+9mo+JocAmyip4mTv5gGtpy7qgyalCKELz2O3ZtE+NZfIkSfPm6nsf2faR2lP6eBl9pU4KNeOdKlu3RIRZuk8bN46Z091s36JXXRIgRdAopU9n7QQBCWt+qInKdgAyIZ6su25SBSREeV0zJ8MfKQRLZpSwY4+V9lc5TxQX1TxH+p8gsW63CtLdcktggCcm2uQ2+TrfMzhkMkgZunQJjJaddJLK/Dn33JptdA3j4oudFMySNGY7f3IafbG2NLIt42WBUaNUf1iRWBiG+v6661TSVjgRY9OEt96CokKp9AmlBDCRHE7hz5CVr5qxDbtHQNdVcP3OO5X0N+ggSFMuGKNGOW+3JcKpaOYzwH3lFR56SB1+VZw4vF7lslAr8eCDVSoYga7TfeE7tvxXSlVm+P9hj6J8Fzs3JLJ7cwJejyC5fiENOu7l6htSaLtyFmYYfYEEZHQUaBrels0p6dQOM6VOjbXVrrBBTSH7gM7EsSmsXxhDqNhzDPm4Q/RBQkr0zz9HrFoFOI/GzpvtghDR1bxcwarlgvgkgy+n59GwiYEzSiIoydfpsG0NUdu3BKyRTBZTGUwkxQH9q4+sPspj3MkruDD4lX60ZmPZ77ow0IQkwi35/JUtnNxqOzI7kwaxmcz/LYM3Xsqm14kltGnl4dSTiunVy2TuLBcndHfTuJGL887VWTgrC5mdWfYJhYqkT/bvg0xMsIw2VjoTUiJ27mTJrGjLaLFT1GscGI3v1CDBclm7e9ZqwFYT0VhPh7YcHPsk+RcOoqB+Krn1GnCgtbMy6B9s6o8eosLf/OnBbeKqg9obOqxhREcrWcGTT5bP2h7/8wvEP/+Q8xelzzLp559VNn5KiqrTWsshZfkx2wf6BA1x4Ed35ZUqbNqihaP9L1um9m8F01RSg9WrlalB797O69xnZ8OGFYV00bSA6/gfnmZgabZ6RQhMmrOVdbTlRt7hQ66pVELPF2B//HFo2lRFkAcPVkUQfP2faSo7qzZtVNGIvn2VjVmVCw2cfLKK5js9eK+X/G+m82GQwUE4iPxnE2edo39/lZF4443qZAuhPqHOj2Hw7spetve6aSr3htata7bJxwqKC3Vmft2S1X/XxzTUsxEZ7aX7WbuIP14RLmEYYZeSLu7kPGrk9KXsJAprpYcNB6v/juajx+pTXKRBiGx/HS+Xi89D8UwApMuFNn487Z95hrWZ+Y6IrNcor5dmhyfvUl6lnbtIXnvF5PXXJH/8EaLSmi5p3yQb1znnQImn0lJnMpM1dOBtbmQK51PkiuMk75/czJuc5uer3phdrKQz0xjI9wwir9uJdO7m5ZK+m6mbUELhJgBloZbQqj2jB8PowbB2UxSnDu9Afn75lL2UghkzYPasuvz00QZO75kX8rqLxNTKRDcyEnPsk2ij70SaEuFk0BAfR+Hug5hGXctzZg+Jpkk6n5zhaGn/amsVEfSYUNHY6hQH8YeZlEj+kIFk1FeDwjytPkk7t+IusrbbE1KyorgdRogKf/t3xSFNx4oORzimI7F79ypvzDZtlDVnv34qI/u009RMZfy2MJO3DEMxmnr1oFu3o4LAFhUp7ejJJ4eO1GkY9MSBV5SUYaV2r3dYFv3FF5VEYOzY8IiVftMNlVjcAKbzDqPR8aLjRcNbFi3owgr+4hTcGLzNjdzMm6W/ybJpsgYN4KefoEepLr53b9i5U6kWhg1T51PXVRR50SLlafvAA8rWcfZs520PQGqqGiCEMYW+tahByNK7dtA0Rc5rLa67Tg0Yn35aOV9cc03o507X+SJnUMj7/YUXaq6ZxxI8JRpfPH8cK+emlRFYgOJCF3N/aMrK745DStjfrjNamKMnrSC8m9XpVOmR1MLmZ2u8PqYB79yXTnGhAwIrDGIo4B75ovOdlOqA/GUFdhKDTsd7Q9pmgWTLFtiyRfDjD4KLLnTRvp3Bk3HPYkfGvIZgdMJnkJ+vqqkFQTO28zz3s6L1uaxvfRZfckkAgfVBx2QQP/Aeo/k4ayjXdZ1BtCeLok17kV9OQ3wwCdeseRSuWa5ImGFw62NNyM8XlabuDUPgNQTX3Nc8rFmnStHY00/G+OpDvD2PDxmRlQAHD9L1z7fRbKVnkohIX9GP8nMmNBMhYMDIdcTEB0orVu0NLjUJVxt9JJHrTkfqOru797JO7BKCou5diYxxMKySgm3rkmu0jcdsJHbpUjjjDJWp7bsn9u9XJHbECPj8c9Dj48OOJNCnT4239UhASiXTvesu+xKq/jDRnRV3MAzFNh3CqZPBpEnw7bcq0NayJcj8ArZk2EVjJGmJhbRdMj7or6N5j0F8z4dcw2r38cR6DnMB39Kfn9FLOyQ3Xt7gNh7iKaYymNy0NrR781b6nx+FLkxYs05VjWrVioTERG6+Wd0CXbuq+8q/jzdNZaB/7rmwaZPK9Qsbr70GGzcqH6zQoXOiNaf638rQNJUEds01Vd7EP4P69VW1Bh9efllVn7Dq7A2DbC30NPXmzSpxz784xP86pITv3urIwb2xBCc6gj0rG7Hyr71M3ziIu/TN5BhxtGU9N/AOw5mIy0IvKYCI1TUTLXIK/xKtVrCr1GV44c27G7Brk29UHfp90VRu4ysuphWbnTVSSmXoXIpQ+tj2qbHQNZ8OXbysX22l0wyMtHpLDffffc/Ne2xmGBOZxDAkwm85ExBc6R5Pv2UvO9InuXbsovDUXqUeo/bLu7fuIOnZVynp0JaY3/9Qxy0EwjQxI9yQlMDW/YnMtjlvpinYvjuS2fPj6dNrDwb2Axhf5NJISg+setW5A0WP3E7BrkPUefIlXDt2WdztIL0G1/EeT/Og9X4EjHmwEN0FEz6MZNtmHU2XpLTeR9/BGTRsGZywljleVIDVPVCdErTVwa4TTiYy+zANVi3FFBqaNJFCIKQkv349CkZfTbcp+/l7fahZEcm+bXE071BzhaGOSRJ76JCq9FkxQuULGkycCCeeCN3bjmKitzPZJNKajYzko9Am3T/8ACNHHpmG1yAeegieecbp0gag8yiP0RGHQvMwyP8ZZ6hM8FA2uqZZ3m9u2wYpWiHt2MYG2lhmut4V/TauHNNyAJjOXh7iaeh4nNI1WKA++xnF+7BPwEuT4cDVqkavr2xXZKQ6kKgo3ph/FRiDkbJyxNQ01X03blwVKxHHxcGMGcoQ9403FJm1QYuClbRlHRtoU0kS4Q+3Ww0OSt8bgBpc/PRTNeQP/xZGjVIzAdu2VZYW6Dr07EnKfjeHN9lvxjCUq8OZZx6xlh51WDoznW1rQwwAhMlHj9XHMATSVCL2g9ThT07jCy7jO4YQYVFtThj/XJQpHC2sVaGD1X/HsHODM+9agcn1vMtb3IyGtJmwrwDTxLjiCsdtBYgvjqVDV4N1q30VFf0NzPyJaeU2vsKdLKcLJ7CYV7iDDBoA0Ijd3MXL3OZ5HSM/xVHbteIS9rt1mjsgvMI0ce/ei2v33vJtlw7StRIPcv9BNnKCg71Kxn5Qn3Yti6iXFHppSyILEB1F4ak9iR+/y3p9oDG7eYubGM176Hgxyt5HJgI4u1cOj9wdy6asfC69xsukJXuoG+vmp1lrOAw0xFr/6g8nUdhgJWgLN62tkVLNlhCCzX3PY1/nbtRftZSo7Cw80TFktuuEt2EMaTHRDOi+lbd+PC7kprasrsNJA8MvhmKFY05OUFKipnrtplilVFO/ve/sznuM5ktG8CQP05ytvMA91iu6XGpqs5ZjzZpwCKzSLn3G5TzG485W0HWlzXCIyEi47DLn7QFFMDI9SZzPlLKIhm+q3ycLuJpPuDPrEWeG+CtXOgu5Salq3Y4erUiSD8XFSgs9ZQrfZ/TAG4TA+mCa8NFHahagSnC5lGbhjz9CptAL4GGetCSwujAYMKB8Rv6885R84PXX1eH17FnFNv6bSEhQ5P6sswK/1zQYPhymT+f03s4GWT57t/+Hmq6dN61p6AWlhtcjAjLjfYPMn+nP0/zHYjWNkjataqStPlTVG9Ypls6MC1lRyh/dWIrPMt7pMN+4+QZk3fjQC5Zi3jxB1y4uvv0iotRSq3wa1+3G1k5LorGWDuQRz728yE4as4mWbKYF22jGGF5DQ+Jt2shx8tOh1DZsO+XM0u3bw47YCyAeJ9OGgumzE+l4diduvy+Bhx/SmPS1oMTGJMMuWqvn5jmScF3POH6hH72ZVfZdU3bwEnfz7TXf4ipQUdL1a+GX9+vx5n31ODjvDJpGn8DK3Tms2lv+8cfhwsABX22Lwvojr346m886l9UXXMaGAUM53Lx1WVSkW9M9pGgHsL8LBHu2JJKfU3NVu465SOzXXzvTYPqcQ7wVTsF9vEBDdnMZQaaoDUNNbdZy+Ny+nOYHjeVOLuJbZwsLoR54hzZbBQWKj02bpjhGOHIfE43vGMIyjuNLRjCBSzhIHdqygVGM4wxmISIToSj0tjAMuPlmFd10atxtsVzFeyYYtm6Fxo3h7ruVrKBLF1VNK1z1CklJ6nzbaA8vYzy7aMSDPIMoe4FKvLg51TWfCRNOJjERbr1Vybl9hSa2bVPtOiqRlqb82TZtUoMOXVfC5YYNAbjyUi8ffBD6Ok2cqIqm/T8gY1s8BblOtRXBb2QTnTe4lf/wdOVorGlS2K+3o62Hk2ldnQpddlICgIJcLaQZvw8aJufxQ6Xvg8VJAWRiAuboq+G6y9Xf2Zkhtb0FBTB0iE5BQcVSp+r/Ho9A06TjLs6FQUu2VGrv3rp1aRFiIxIoiYunMLkuu3qcQmFyHdr9YF/lMtSZ7Ml8GrCHvTQIsbQgN1/n3Q9jS991gpQUyWefG5x5poXnbGKqmnOsEMk04+Mdv5j68Rv9+I0iIvHgJo48BOCNegevhM/GxvPyyzq6LjEM9c5b8HM8zTr048YX9hITbzJt5ppKRNZpwY1gUdgjBc3jof66JdTdtA6Xp5i8lDQyOnejIDU4B0r46RdGmnm8yH2225Um/Da+FZ4SNXBo1DqbzqdkEJsQhr+mH445EvvBB46khJYQmDzFQ1zK+MqPkNvtvI7tv4iNG50TWIDjWeZsQV1Xn0mTHCe1jR6tuAZUxQJKkEUy0RQxko8ZyceVF2neXIXTQl3wBg3gpZdUePTDD8NtSAB6MZcfGIQX+9FkVpaSdfjQtavSYnfqFMbOdF31hCESaO7jBUbwJR9yDZtoRSLZDGcipyevRyRm8PXXSgVTUKAGOFIq54XzzlN1FuLiwmjTv4WMDHXtVqxQdiPnn68OoFXl6N5pc54hjWvJoKHtJufPV/doYaFK/rzqKmhfM7aLRx08JTUzMXeYOmyiFR1KM899xC1/yEC8TRrZrlvbkNrIg7ZIlhURsIKGwbV8QDp7K/3mn+5S1ON4Sjq2w92+GRHnngeRatCgZ+0JGVWW2ZlM/CKaw4eTsJYLSFsTfoFBO9aTRJbNMuD1xrD9pNNp+vcfltFTAew64ZQy78GDrdpTUCeVmEOZlvQzlMTChcETPKKkXY4gyt51hw7B+YN1/vrLS5euztaOqRtD0UndiZvwjeUywdocRTFRFKs0rrrJ0L0r4z6O4eWXFTHz6ZR977wd6yL5+Il63PRihqUO1g7/dBRWz9hP2y++wZ2vBoMCiNu7h/QVi9jeqzc7e54euIJpEv3LTM7lcEgSC7BhaflgbduaOsz7sSnn37CGFp0Ohd3WY05OsGNH1QksqOmWdbRnK80r//jQQ1Cn5nwNjxQSE50luLvw0I+fK43EKyEyUlk83HWXCnMPclYecudO+OKLUOTV+mJpeMt8Bi0RExNa1CmEisK63WqUc9ZZVQiJluM23ghJYINh1SrljLElxOkOQN++jitANGUHj/MYX3A5b3EzvfW/EGf2YdYsNcteUKCeDY+nfJDz008q6b/W4+OP1cDp4YfVdMvnn6sKE507V5b4FBcjXnuVC/kWJ76YH3ygygu//LKqJHfjjdWzLDtaUTetIKT3qELoZfwzuX0kTj/g/AVVXX2fb0rWME1bnaEvAlZxSteHk8/LDUFg1bkYwQRe5zbLpXxb8HTpQFHf3hhd2pcRWCfwkZi5fxi47PyPS/dkVYxAonMXL9sSSQkI02DnSb1Zf/ZgDFdgX2eWrr37+J7s7RqoYa34d0U46XWv4wNe4i5EiEI0FWGaAtOEF1+0PkH+BQN8zhdmnWQKBpxleVfbx4OBw9mYv87h+bExWD0bpilYuyCWvVurPo1uFYWtcT2sYZD0whu4CwoC1NWaVNej6bzZ1N0QmDtzYMYc9JxcWrPJwXUTAR9ZWgjiu7c7cjjTmf7cH8cciU1Pr5IXfyUUEqTs5VEiIBw+PPRLWGBSn328j41LvxDKJqCgQJHX55+HZs0ct2P6dCcDCusuwsTFDYSw8srPh7lz1YUPunmh5vH954yvv75aI50+zOKRMv2w8+0YhgoEP/98GDvr31+ZmValcpVhwObNPP6IgaYFP2TDULmKdj6+/zpmzVIWCh5Pefafj4Vv2qTOkf8Nv3IlHD5Md5Y42rxhqI9vk+++61cJ7n8I8ckltOx0EGFjWK67DOxf65IG7KEVgVl1Aoj8a354U0QQ0vtSz9pjGaVqnxobQGatYEdk01uU0PdSXyZ14AMkMGnAHhbSnS+4gkhCVC4TAvfaDbaLBDsW33d61h5EcZGjEVYC2aVEVrXZl0dwI29yDfYzUQLIq6+SvTI7dOXvm+5lzcALyWzdnsNNWpDRpTtLLx3F1t5nVwoG7Ot4HDkNm1TS0/rOnKlpjnrMuxhL81DBlSDwegXffisq3Wah5CV5Iy4g//yBSLcroL0VEfR702T9mM/ZnRGB3bMhNMnqv62dJwzTDKqH/aejsJHLVuLan2lpryYRNPtrBok7tyG83lIbLkW6GrCXlmwmzDMIUg1Als0Kv/LeMUdiR46sWuUif0RTUFrNyQ+apkI2RwEGDlS8zZr3SK5jHEvoZu/GIKXyIcpwZtJcEcUFhsPRdOVlNAzO5meGM9F6NZdLRYhbtVLRuGefLdNEAkpPev/9yg4sxk9jN3SomtsPdoIcjoAe5zEuwF7/FQxeL3z2WRiRPl1XguIGDcrN/sPA4UWbmTVHt92fy6WCm7UWzz5rfV28XpXJeM895WL40oPtz/QQ3o7BIaWKyubXXKGnowZ9L91ETJynEpEVQuJyG4y4azkJDbLQrGrdI7mTsUFttjQpEYVOBOwKNRVdckpkh3ZN53ChJ4DMHt6vE5dk0KFnPsl6dtn3ceQyhlfZQFtOcDhYAmzHvMEibf4EluJizlo01laTr2HQjUWsoz2P8RidtDU0ZzPn8T2/0I83ucV2CGIKQU79dPLrNfDbqMahNh1Yf+5FrL7gMracOYD8esH9A6XLxeqhl7LrhJPxRJZH1YoSk9h41rls7Dco6GkIdlpa2JIha3i9oiznxTRh1vICMnYLVu8rf6D9pRsxdWNA08gfNpjM/75AXlq9soh2RVjJKkpk6AirALwVxjmHCz2O9LD/pBY2YuVapGYnSZFEZx+m8zef0f69cRTO2U2Gtx6e5k15hgfZRGvs0/eCQ5oam5aHb5VzzJHYSy6B448Pzk+EUBLKunWt34k6XkbyEbFU6EBNU4lNjwJs3Kgsxnyz7Bpe3KVRgnR2M49evMcN1MPhCK9C/WynOG7Gy7a2T6AiBA/wLCl+bUkki/t5jqkMtvScBBSB8dV7FUIR1l27FOnetg327VM2DbEVRrdut6pOcHqprkfXFZMDdYP07Oko8nkcy6lKJ1tYqILboK7Vb78p9y/L4HCrVoqovflm2OW18qSzBJlQ9mf/GoqL1bUKxfpfeYXd7c7kp+Me4Pd1DSmISeEuxlq+jEIhP18FgP/XkFCnmCseXELX0/bicqtzLjSTtifs54oHl5DeIpduIxaSXN8LyDL5gS/SdyWfcCdjg25bCsHe5avDblNNVCJyQmShPCp7IM/D16+m8OjFTZnydl3WLYrhsJFINAU8zsPsoz5juYs4whjpSImnrdJvFxwsCHlcAQQWED/9zrB9b1GfDMuS2iY69/AS9dnPQ9ozLBdd2EIrJnMh/fjNPoYuBN7oGDYMGOr8mIK1weVm+ylnsmDUHSy66iYWjryFxVffwr7O3chs34U1548gP6Ve+X79/vXvAq/hY6pSISshQeJywaMvemjZWqN/j0TOOTGRAT0TeO01DTOuXI9ZsZiGdLmI3Z+Js3hxOdrI9URhX8jDNAV/Tk1g6Sx7H+CA9lQjCpsxbyEZ8xaGv6JhbVnpw27SGcmHNCjZxdmLP6DfJ2M5ufB3nrJwJnG8a2/41/uYS+yKioLff1eFfiZPLicGQihroQ8+UIRh4MDAWUlQBLYt6y0tYqoltv0HYJoqA/2tt3zJOxIdAwMXnVnKIzzBYL63J4YVkZQUGN10im3bOGXq/bTnPDbQxs9Xrxw6Hi7kG57hIR7XnmSd2RoTjbasJ4oQxFkINWLp27fyb04cJFJTlR/r0qXKOsvrVebBffsqhnnVVarygq/+bJBp0IuYxCM8GXpfFRAZCQsWqGpyc+eWf9+2raoiFbSCVnw8HHecKsEWBuqxnzhyycPawsfrhU8+UU4FN9wQ1uaPPDyekM9dBvW5iTeZwhDM5TpcDbGuneQTvr7KH9WphHY0Iz65hH6XbuLM4ZvJPRzBtjXJbF9bhz8mN0fUOcjVt0ZyXv+dLPo1jr9/icXtjeS4tZMZzbucyQxL2lEcGw96eHGTgoMFNVITHhSR9ZV1tbPeGto1nVE3evl7SkJZdS5Z2mUWEs2jPEknVnMBkwPWs0takoDUdUrCKLsLgRE4MfUnIjUPP5kDOIvfyCYJEw0Q6HgwcHM/z5bNXkkpMSIiEUaRbbsAPDFx7OvYlT3HnYgntmayPKXLRVFy3UrfH27emsPNWhGVdQhXcTHF8QkgBPVWL6PBysVE5mQjgAv5hhP5mwWciPN4myQnR5Ca6qK4yB1gN7Zvj+DeewWLFws+eg38wxQxdWMoOFiAlp+PMMN/z8eTx8joCbxXMtKi+IRC9gEXHz6axiX37Ofk85xVIbKLwtZUqVl/eFo1I3qmtT/5btLpwUIySQ3IDVmc0Txk0MoOQjNJtygKYYdjLhILkJwM33yjbI7efVdpRJs3V9aSZ54J69ap0qAXXlgegKvLAR7gWeZyMklkB99wLfcjeuopRWBBERPDEGXkcQVd+Zte4RFYIVTd1aq8zSdNQmiCLxlBHHllkRofNLw0ZQevcTsAbjx0ZhVdWRGawNatq0SLn35arQQtQIXt779fJe2dfbYirHFx6gZat04JWB99VGWoPfVUgPa2PesYxpcEk0PYobhYceW//w78fsMGGDJE2T4Fxe7dYe0HIJISruUDdBudIyjefuONyj+2ViE21tYJ4xDJnMxcvmcwpt9rKd8bRVWi5P4Iy0XiGMThfdGMf+F4fv2iDRuWprB5RV02zWrDwxc15aPH6yMRXPrYbr7+LY+JdW7kLBsCK4HCtMqEJhRCEdhQGf1Vwacz97FgarJFeVkBmNzPsxQHSe4s7tgWIKjHqjAM6t77GPEffkFMfOC6RlJ60GPx/14czkaYJsezjAWcSFeWlVnqGbjpwQIGMq3sGggpyWtsf34EsHLYVSy4/g62n3JmjRHYkBCCouS65KWl44mNwxMTy+4ep7D23GFli0Tg4VfOZgQTEAHvrTKFbbANA1BcVDr4CLiGAqRg4pcaP86pVynBK6ZuDGZsbJm+MxxITeOJnl/Rro23lDjbpYlJvn41hcJ8Z+8uq3ujYttrCkUn9cCIiLCsrnwfz1UisEC1CCwoOUG3PuG/445JEuuDris53ddfq4zwQ4eUO88tt6jSoQcOqKTng/PWk0kqT/IIidiMBAYM+MfaHi4KCpSDlBUkGq8yhm8YSknFztflKmfzAStJNdfdsGG5T5ZTHD4Muk4XVjKFwSSShf+DLYAz+b3c6sU0lf7BKkIihIqeLlwIe/Yo0lmVZKdw0LatMnp96CG49FL4z3+UXMHPDeETRnJxmW5XVvjYo+LMpi/gePPNBDfurlIdW3iYJ2hQz3DE9++5pxpFGo4EhIDbbrMcrLzKGHbQxMItomoDHF1XSpN27aq0+jEBT4nGV692oSDXje/lX55NDKvnxTDx5RReGNGKyeMj8UTHhrA4h4J6qaT16uFo/zF1Y4ipG0N0q/aVpnx9KCN3Nt6qazPzAz5gXwBh8vI9rJ0bHyKvQmMjbYmhkGF8xVKOQ+o6MrUu2WNu5NADYyjp0DagFyg7e6ZJ9Mw/iRr7HtGt2geS1MRURGJqWVt9f/uO1WzTFqnrLKQ7nVnFUroHEIdFnMAZzOIbLiiPsI4ZTX6D+kFJtQQOtmuNTNWJ9+wJ+3Mk4CopDnhqE8hlApezkyZMYATjuYStNGc8l9CCrVXci+T60Rrvf1WfbJeaZSwjg+lJFPU8ARlmdniBGcX9nqfYsMlVSpztPQ28HsEP7yunI3+v4ooJaBXvgWBk1orIpvXq4fh5C0BkBDl334zUdUwReB6ySGQiI6rkzmMFn/7+1MFbadQq/EiskLL2zpHn5OSQmJhIdnY2CQnOyrb5o08fVVbSKiHW5yd78gnFTF+UQjwh3t6bN0OLFmG345/A9OnOOXYKmTzDg4zSP1KmmJ9+quaxv/wy+ApCKB3p0qXKg8gJPvoIrr2WWfI0zuL30ihZ4IMtMDmXH5nKYPXL+PGqQpV//Vnf/kFN7w8Z4mz/RxIpKXDwYMBX62jLN1xINgm0YiO7acyL3EMhVRsh16sH992nCG2ZDNY01ZTCjh2Ot7NPT+f82F+Zn9PBsX/yDTfA229XqdlHBiUlyg/2t9/U334HkcZe9lE1ch8Muq5mcubNC2o/WwnV7aP+LfjafdurPxIZXVmjt+LPNH7+rA2hBwJqEv1rLuIi7L02C886ndyRl4Zsm+9lHIq8QmUCGywL3UnVLn8i8deEevz8STJOBkEuPGiY/NDweno91RWZlkrBwQIS3v6QqHmLEDZsuGTmL8hOHcuOwS6Dvn1qLGLWLDLOvobWbKCYKIv2SWLJJ4M0YiI8ZH74OhSXEPfNVKJ/n4NWmt9gJMZTMKAfBQP7VsnOp0paSwdIXreRJr//4WjZB3iaF7kHo0qESvUhqanw41eZdOnkRc/aQ+GmtYjdGcTc+giiuKTS9ZMAotyJTuo6HkOjT+P1zN/dDMNhYQyQuCIkL07bSq63PLnLyqGgbK0KOml/+KQFNZUQqWfsg08mkrBpG+5CZbe1nC6luSB2sBLW+A/pyr8TmqTfJRvpenpgAnlxYT6vjzk3ZN96zGlifVi9OnRihu9dOH+Jmxt5i8+xL/HJ0qW1lsSGM9N8gFSuZxwlDVpy8y9Xqcz3Pn3UPHYwliOlIlCvvab0GU4wbBgHb3mUgQU/BSWwoKLDPzCIGZzJWcxQpb3S01XkbcWK8gVbt4axY+Hcc50f5JFEkCyodqznPwTW+l1AD6bTn0D1lTPs36+iolOnqgFKVBTqZTN2rOOCG17hpp/4jbX5KqTodLj62WdKVuCuucF29RARoXzA3npLNWyrisBIcEBgQ9mrByI+XlX7dUJgj2VsWVUn0KXfEgIhJI/IJ7iQb6zPtKYhQthrVYe8Ao4ircHgI7DJ0eqG37gkGqf3jBc3mpBcUvghO05chrFjDTEJEUT9vdiWwEqXC23St5innBGy7YZpqt87nMDrzcdRvNWKwAII8ollAiO4psnv6qvICPIuvYi8Cwfj2pMBuoa3YYNqzWRVKcLnABFRUeCQxGaRjIYMRyDnB3X+Dh6SnHtxKmsWZBCflE50KygECl9+iKhX3kffuK1sDRkdjTnobMThLPhzgYqO1UlifNsnmPtH87D37y0RrPwzluP75DN5+Z4yIrs2M9+SyIrEVGR2Ztmz4E9mo1u1p3DT2jJ9byhYSRB86xpp9ck4vRe7T+9Fg9/nk7puFYlWUstKR2cgA957wQis72/Jir8aVCKxTnHMkVgpYfFieCeEvag/DFPjSy7hRe6lAVU7kf82fEGqcHB/1n1cnSCIBfjuO/uFvV5VqcspiY2L48NBkymcaP9CEJh8zNWc1XSzkjT07q0y71auVFP39etDt27V177WJNLSHI0aVLSk6i8K01Q67pde8qv8deGF8NVXiuj7W5+lpCjbsLlzyzTM34vBrPSGX34qP18lR55zTpWbXvOIiIAxY9Tn++9hsIreJ3GYLJJtVxWYjvVa2dkqz+9/sWrXwYxolsxoyMalKRTmux1LiqUUrKUD62hLeyxqfpsmnmaB2uZgL9FgBDYUeYWqEdiK5BUg55DO1tXhJQSaUnDwkM6U35IYNrA9hUsXIkJ66ElETn5A9FXXtKBlcH3kRkqYsK8/oQi2hslqOsLV9Suc4xhITwLAeZkFa9SowX4pSjq1w4yJQSsIve0WbMGoRv8KYBqCzEzJlz/WY9TwfRh+RLbg9SeILtEQm7ZCbDSy14mIOfMQdzyk3FJME/Yf4P19HdEwAjT5jiBM5vyRxfF91P1Xkcj6UJHQ+p4BH5l1SmSdPG8V103r1YOMeQvJadOI1HWraMZ2jmMpK+hiebwCSV9+5Xf6YaIjhKygTQ6ENDUytiWwb2cs9RuH72t4TJHYxYuVJ7p/EM8pDFzM4TQuxsIwU9ehV6/qNfAIoagoNAcNhrw8wZRhn3Npw9lKNBwqVBem1dZ3O7sT6k0o0dhBEzVv7oMQKomutibSjRqlEstC2PUcz1LmcFq19EOmCf/9LzzwgF/gZNgw5XU7Y4Yi02lp6sfzzgto0yRzKDreoM4QobBvX5WbfORxzjmUFkxnJB/xOrfaTCkKjmMxS1GVhDQttI/0uHGKK/8vYcvKOkx+uyNSqpeKQnhKs2wSg34vARkZQdEpPQNepFYRV3841b1WN/rqw84NkUjHU8LlcAsvq+/6mhFjHiTO7UZqmm0kFgmZKcqL1df2YG06XOgp+35Qx3QKC0K3TSKIbZCA9+ohRBceDLl81VE5M77axNbtJm/4EBI+Gl/pp4pzKlfyKQ/yjA15dDYLIwRM/0lw/fXlUc7oFibk5kFUFLKDStZj/Sa02x8EwyjfqpTsoGn4BBYQCFyRHsBNcrQ7wJ/Yd0/4ovDBIrP+UVkrIusPJ8+bb11/pPXqQZQsNyt8kocZxA8EO78aBlfyKR9xDYf0FDYNvIbn2tzG5JdDOxxl7oqrEok9ZhK7Vq9WyRirw7chLINpdTp0vXyquxYiMzNs5yVAWYrt/WkpvP9+uVG8FTQtbFKpAoKhNXWNUopVtt3RgttuU5XLgiXD+WE071Y7UgCKUB44UPrH9u3w5JNw003KYqNnT+jXT1X5UJYUZevlEl/l/TeqzSXuc3LKhO538TLJZAX1zdQwGMA0FtODA9Rl6+lXUa9epcUCICXs3XskGl17UZjnYsq7HTAN4UdgIRwZho63rHy1P/WVmga6Rs5N1yJjAqsgFm5aW2MWQaH8X51C06qWImJKiPHmIKRElJSAadoPAUyTwxdX1gdXJNXxLjdF+RpSqu4mKTn0cUo0Bo07G/0IEdhg163gYEGNRWYLzzqdnKtGYJYmA/gnpfkny9VnP89zn98v5RCa9JP6hgikyPLiCOTk4H7kIfSe/XCdcBZ6l9PQbr4XVq1F+3g8yMrO0/XYH3aJXB/qt6vezK/d4K4iqveslR/1efzIx1xFNAUITNyUlPW/l/MZ76B8GpPlIVqJTSz/PfjgtiJc7qqdw2MmEvvIIypQWNWa5wKTk6jgeeTLhDn++PD0Cf8wEhNxnLTjDwMXDXD4xvaZ0Frg8GHlNbp4sZr5HTgQuneH5ctDRb4EV31wOkRXz9PzH0VyMvz1l/KkmjIl0IzY7yK0YSNjuZM7eDUgIupbLCLCwoUgCCIjJDz0sCreoGnl8opnnlF+XXsqT0O2ZT0/MSCsSLAQaqx2xhmOV/nnERtbFlJtyB7+5FQuZTxL8EX+BTperuRT3uRmBFCXQ0w/3MFR8bkGDUIvcyxh5dw0DK/yGw0O+4iWCw/nM4VU1EjLt6QpBNktmmFeNQJvcyUlCDbF6f9yrRgt8kWYDKxf2E79X/3hm7atGP1s1qEYd4SJpyS8+I6Bi/OZUva3T05sdebMu++mZfcOlZK5Dhd6SI52s3VVJL98nszqv2OQUpBSzyTz6hKGDPfw6bsRmDbTsyf1KOb4njqFi2reQ9SHIyEl8EdhvzMoPK0XkUtXoGfnYLpcJHw6EUwz4HzeySuksp/HeYzNKCG7pks6npbDsJsPs3tzJBNeTCHnoAure1jXJSecIJHbN+I+dwhi0+ayKLowTfh9NvqMORAVGTS6fjUfs4RuNkdT+S4QQtL51L1EJ4aOPjlJ9AqGcJ81UEQ32LXdnZdHAuVHcRWfcgHfMpHhbKIViWQzjK9pxebylYTgr+iz2LIstG2b7jJp1v5wyOWC4ZhwJ8jOhjp1ql5uVsfLufzIFIYE/tCunUoRv+SSsCsl/dM491yl5QuHxMeRSwZplauT+cPHuC65BD7/PGgm63ffKQeqoqJyfuX1QqOUInYdsCenxx8PixZVKUG2dmDXLpXwt22bitAGwU+cwwvcyyz6AMq5a8wYuPpqZQrx6KPWm9c0FWyde/GrcMcdYTVtA61pi32tdn/4ePE33yi1Qq3GkCEq2cvvhl9MN5bQjUiK6cevAfp2KTS61NvLqn32oVghlAb5zjudNeNYcCf46eMebFyeYuGLag8XHupwiPn0pBnby76XQrCrWy8OnaRelE4SgZwkdtW0rAAqE9lv3qjL7G8SbXV8/tDxMoBpfM/5lX6rmM4i6yZj3DEG8577QYiyNudkQ0624M89e8hYlciHj9ZXjrRl0gaJJqBL5FoOFMWxh3TMIDGoBmlels/NJNnYbUlIjkbEfvUdsd//jLCgKyawsl4fNj74Imn92jBzp8pZSI52s3hGLB8/bpUAKtF1WLtoPy3euB/tk08RRmUiIUvfg8HuiDxi6cYSttC8kqxJ6UHV/zVdaUOlKeh08l7OvmwjazOzGdinQ5mUwL8ErW92IRSJtXIqsLv2waQGVu4GPieKhj/Ppe7mdZbXoFLbhGDYoANM/iHZ7z4OuiTd++7izGFbAr79n3InOHAgXALrGxmpUV1rNvA+1wUu4nbDiBGKaRwFePRR+OUXq1+DxwNe4F57AgvljGvUKNA0cnOVI9eECSr6mpamXCB859+fRGcc0P0Sb0wqqlc6dFAWaEctgQU1796okZJDlOo0K2IA0xnAdEpwYzRvTfSMX8ukKQ8/rAYBK1cGt4IzTXjwHg9c/3TYTWvDRp7kIR7mqUrZokIoxwP/OhbNm8Mrr1hUDKtt+M9/4McfA6Lf3VlC92B17DWNfZFNQxJYUAXqrrsu5GLHFITm0IigAlyUMIIveZqHaMLOgN+kEOiGh1x3OvGePWTMWxiSyPqqcxVuWhuUyOpZe8oy0YORWV9ENlwiO7RrOpOX7ymLgnY7M5eNS6PZvTmyLClFaLJUKyvRMBClBY29uDmDmXzB5UG3LYC8tHp4rr6UiHrxmK2bE92uMzLnACIxlXWrdN5+KYo/flP+opreplSXTIWSyQJTwoqittzG62yhBVMZhK9PdWteLr+0mDdezCYyb88/SmCPlN2WP1rPW2hLnjSg6/6ZdLmjBzvf/pCh519Qdk2bn5TFyedFM/eHRL/rqCKwpgnvvJpFk+RctPETghJYoGzfwd6kceQzm95czufM4Cz8hy7tehRy0e2ZfDM+m8LDMTRK1Wl7wn4SU4pYsrGEvqd1RpaWg/MnsD7YEVgrOJENVL437AlsrjudjX3PIzIni/j9e5FCIKQMej58vxkPP8jO3+NDEFiF3hdU1fP3GCGxKSlKtuo8Cqk6o0SyeZJHGMlHlWtgmybE1FwVjCOJiRPhuecCSZCmqbKDSEk8OeSQVPZbKvt5lge4lg/tN3reeQHnYNs2ZR6ws/R9JSWsXWstY/DiJotk7uJFFnIif3AaoNGczdxzj+CG51vUKtOBamHnTmtD4lJE4IGta+DUU2HjRtB1hFBc7OyzYdUqxYMNw3f94NVX4byUv/1EseHhIZ6mBVt4hgdZjSpBlZysJLUPPqg05Lt3q2do+3ZFYm+9VfknXnONqr4bG34/euTRo4fyH7v8clXFxO0uzxj2h66D24133EdY8IwyCKHMH46igGqNoGn7w2xYkhJ6QT9oeLmd13iJe4P+LkyTgjqKaNY4kU1KR2Zn2hLZgHUckNqhXdN557uDvP1SA/Zu9ps9EpBQx0taq0L+s+5OTsv+hc+5smwKdTgTOZm5tuph0+ViR24uaZ3aEeOno//rL8FVg+PwessrS5mGbzgRfIsmOp9xBRmksZcGrKALkRTTS1uI66G/0POKAkiMHcGsik1WsO3luo98rogpnVEVISWNb7qWNSedHCAZ6X/zXhp2ymP9L/VZs0JHd8G5AyW3jzHp2b4QfeESRJF94rKdqKYBGfxOX9bQnpl3TyYjtTE5dTJIaVxCcrSbG++NZdrMNZiGYMOSDiye0ZD87EhmjoWU9BJOv+wAQ7qUz4aF8osF6ygshC/3sFved32NqChWXHw1KRvXUH/1MiLycimJjcd0u0nctRXdqwiYkZ6G5/IhaLfeRPJyiabL0vs6OGITPOh61QUBxwSJTUyECy5QXvjhENlcEriISZUJLKgNHQUhqccfh8ceqxzNNE04rpPBt6ta0YztzKcn22hGXQ5yBrNwB0mECUDTpgEEVkp1OvbsCSStoWYWNAx20JTZnIGBhkTg0iRMbQ3F/RUrHjw4ZJJUrUdqqmUkthK2boVp02DQIEBpMJcuVWT222+VxVWHDioi2KQJMD38jE1/XMoELuFL9gy5ieKWHWiUUkTEeWdDTCd69ICOHZWGefbs8nV27FD65scfV22rlTmNAwYoBv7tt2oEEBOjfJynT1dWYxERMGgQ8oYb2bC1GdHR9hWUpazlWuAjhA4n7mPOd80pLnA5nkI3cfEFlwclsRIwXW4y25XX7fURWSdwSmStUPHlX9HGKhh2bBV8fE8zKjo7SVOQc0inTV0vlxd+ikYJD/OUo+MAdS4yW3Ss9L1pwjUjdTwegkSq7K/BQVI4QAqN2UVjdqn9eIEz+2EkxBHRows5PXuSsXaDJcH0DSqqgn+CtFZETqOmxBzMRJMOplxNkzqff8zBu+4HyiPtj9weD7cXBBDEMiJYAzkZEmhXZy9tjLfIm70VGRPLLx1P5UDvfkhdp/9pHXjvwTTWzA8Mjh3YE8G3L6bj2VrCM29UIUP7CCHY/SFdLjLbdyGzfWCSt+b1UOfQRkxdp+7ZfXAlxjPlq2g2r9NsCazQJJ1Orl5y21HOHMrxxBPw00/qJeWUyJroLKdrZW9YXYfzz1dT6bUYy5YpAgvB5RTLVrmYyyk0ZzsnMZ+TmO9sw/Xrw4knBnw1e7aa8g4XJhpFqA5C92Vwmig3hC1blHl9kyaKwR3NxeqvuAI++MDRoqvpwOT7csj7S/mRDhsG0dHKZODcc4Pw+fbtq5a55weBpOF3b6qNmyY8cJcK/06YwL2P1OEPC3/x/fuVbnnPniNf5bdKiIpSgmyvV2V2xsQoGVB2NkRFkV0SzeDBqoCBXUBO05Su3mEdiWMKEVEmw25bwVevdaG40FVeligEMqkcCZWlUwgb+g/GiKheHoGTogeh4NQ/9t1XIikqJLi9lhQsmpbMmpQT6XTgT8f7loCp6+zveBwxHAr4bfZfEWzbVvVpqCgqkx2xJwPXHtDXb6buxB/IHnAWuc2Dn6t/g4hWB3u7dKfB8oWOTLNW0Yl3PuvK+tXRJNWRnHehBxkNn/y+n9Map5GSZrKWctsqIykdXUqMJg3Rdu6xlC0IoKRtK9wbNgddRgAcykJ//U0STRM0jeGTvuRA8zZMffkTZsxvUUpggx/B95MiOKGXl/NHlFRJRnAkYHmfmCZR2SoRqygxGeH1UkgdomQWeYVuLnn6bBauS/Zz+wiS3KaZRMV66XZmGJWaguCYIbHt2il95ahRsDCMAWYkflMIPk1C374q1b6W49137YN/miZ5M/IeLiuaEB4BGjeuUnGBGTOcBxr9oWPQBQvjXk+pL97u3api2Lp1ULdueDuoLTj9dBXO/Okny3OdTwxX8BmTuQB9rYG2SZ2C0aMhLk5VstU0peJ44AE46aTSFZs2VYTzt9+Cj9B0XVl+RUUpfYedQNz/Av7+O1n9hjFu1W+2Ebj9+1Wy0333WS7y72H+fHj2WVUAwTSVFsA0IS8PE8GZ8etYmtsaEJanxeVSaoRvv631+ZtHDGnN8hj11AJWzU1j07K6HMyIoTDPjR1lSKsw+Jcos/qdLZtzsGlgeWqnUViwriTkj1DWQuEUPygphmnfuTFsIkaaJvmgxWOMPdzfQSEDBSkEq4dehhEZBZ7A3zZsdIU0gQ8GHS+9mEdShcpJAepZKcHjofmPv3LwmvZ4YmoHIaoOCuuksLHvIFr/OtXa8QHBbbzGm9yKvs+LOV1H0+GbLyKIjGlNcYHOS4A7QjJwaAmvvwhpacprFSHgrpsRtz8YdP9S0yjp0oHsm64laexbRKzbWNYO//YIKO+jS/+ts2Mz5z4wikfNUMREMvbJKAYPd2hZ82/ANGm0aC7pSxcQUaieMUPX0UwTISUmgjO+uoOFJSmliwecGfz1winpBQy+fg1xidU73qM5paYSunaFBQuUrdM774Qu8pRAVqCt1g03wN9/KyISF9oW4t/G8uX2pNI0BatlB+cENj5epaaXTnP7o6pBQIlgFOPsFzIMpWv80EajW9shhKpo1ru35SKXMp6pKImKgV7G4YuLFYEFxb+mTVOy2W+/9Vv57bdVqLBimNblUsxrwgQ1iuvZ03mbDYMlSyQlJaFfpE4Ltf2jmDwZTjlFuRT4GGpODuTl4UXnHH5iSW4bgucUK+g6XH+9epZOO+0fanctRXSslx79dnHJPcsZcuNq7AisjjfguZZpaeRNHkfWvbeRnx48EzwcDWZVo7BrM/PLkrucJnjl5gq8nhDPgIC5sZ3wpqQig0xJ+Oy0pBCY0VEUntqTtVdejKwf3N4uNjZ8AgsSAxf/IXSSp5ASzfBSf9XSMPdRe7G/Y1c29htkeVe+yD28ifIbN1DSGMOrli4uKL8XPCWCHyZF0PMkvcxyz0hKRw7sR9H1lyKFUB9NUzMLqAhsdqnXcdaY0RgJ8WXbC3UVNcOg/vpV7NtqPygEQXaWxvrVtXHKC5CSdtO+oencmWUEFtTxCSkx0LiQScwp6YVdWWSA829cxVUPLaZOfRt9l0McUyTWhy5dVHTriiuspxAFJnfwKtG+aZmGDeGNNxQJOEqyjSIc1A4slm4+OGs8BUQHX0AI9SZ/5RU1BXvBBUEXO/XUcKOwilS8yc00ZYeDxU348stwdlC7IKUaQVlIUJZyHFM531H1LK9XnY4rrlCXBFDWAUuWwLXXKu0BKAI7bJiaeujRQw0GFi8Ouf2dNGISF/INF3BIOIt8B7Gh/XeRk6OSukwzaHT6ee7jV/qF3IxhwD33QOvWR6KRRy8atsyhbff9ICqPXl14aMIObuUNQOnkzL59IOqfCWOHisKG606QkCDRdHutpWnAti2JvHX73+Q1aVW5Tb6PlOQPGUjODSNJ6acs9YJFoQf0K8LttosMyAr/l+h4eY9RnMPPIY/Jt1ry9s2hlzsKIAyDuhvXEL9nZ1AXjWIieJ57CUWefDAMQeY+waOP6gH3k2foOeR/+gr5Fw2i6JQTKezbm0OP3E3Wg3eUFeuInvUXWm5eSPK6hwZMYTA/cC6ZWiruiuF4C+zbUzv5R93N60jZtK7Scfv+fpfRfFfRpjQoBJ4ivcZo1hEnsW+++SbNmjUjKiqKnj17smDBgiO9yzK8/baahQXV8YIs/RdG8hEP86T6UdNU2dOjhLyC8mTd4MACtLhYcN3vI2jBFlZROcGgLMT6/fe2x9+vH7RqFY4uUnAz/+UGwgjh5eY6X7Y2Yf9+Nfd/xhmq+lkQvMg9hGNiJKXSd3/+ud+XjRqpKYbDh1VZqZwcGD9eZYGBcpTwWHeUB6nDhUyiKdsZxiQu4htGyAmO2hVtMQb61/DFF+oEBZki8ODiVcbgtHuzS/aqzTiSfasQcO616+jRbxdud/noVWAygJ/4i1Oow2F155gmxnXXWG4rXCmBk/KYNYlFf+t+rgDWyNwZyZgHm9Jj5w/swjoiHPvtj1Ah071iFLpuHcnNN5uIIIMEhUB7LQ2TrixnFMH7F6stCCeJULUcsZkZnPDRG7T/8RvS1iwPSh6/5zwOE54UzTAEX3whAl470a3aI1PqkH/+QHJGX03ulcPxtGkV8G6M/uNv26nJQyQzggk0ZidDmMIgfqCRuZMEt7P3W52U2mndn7ZicUD1NH9I4BXC8zGvKRxREjtx4kTuvPNOHn30UZYsWULXrl3p378/+/fvPyL7KyyEjz+G/v1VXtINNygboRkz4KpTNjGI77mecSyiOx9wXXmiUVKSSjCqV08RkYkTq1766x/Cl1+GUx5TcIAU+vIbeQTRRxmGOkm7rQXWmqaKU9Wp48zXVSD5iQHOaZvLBZ07O1269sA0lRZ2Sak/aZD7ZiWdmMjwsDet62qauxIiI5VBb0VmuWuX5SgjnxjOYCZTOB/p99g7iQyDqnVRq7B8uaWjxXraciBI0lEwxMQoyfHRhiPRt+YejuCv75sy9b32/PRxW7auqsPpQ7dw00t/M2bQV3ytXcgW0YKpnE8DMtS0uhCYA/rjGnMHMTc/ROKr7xC/fWell3xV7JwqIpyErnDwxnORpRzFfqrXl/S12duUc5mGabG8VlxM5PJVIff79DMm112niKxKgLHuLU10lnACy+gacrs+SCHITm/iePnaCHdBPp0mfUZEfh5A0ISqAqK5lf9WafueEsHu3Sq67/T+0nJzLe+UfGLozSwmcRGmny93CZHsKwxlYydp2Miga3dZySauNiDm0AHLpLccEthEa5xRSkmj1tmhF3OII0pix44dy6hRoxg5ciQdOnTgnXfeISYmhg+PgPZx926liR05UuW/LFyoZIKnn6446Xt/tGfqjy7ePGV8uSG674V/6BBkZEBmpkpjHjFCTavbRLX+bVgUz7KEgYt91GcCNmxk3z7bbXTooHxFH39c8X47SDS20JKDTkfHXq8yLz3a8NtvagrfRmvxIneX/i/8SH9UOM4viYmW7fiYq1lNJwvSGrpdV10VRjv+CURHW0ZD7DSw/hBCeeEeJXbQAajpvnXprHTefeAk5v3YlA1LUlk9vx6T3+rEJ091p6RYx31efabefi6Zl5/L7jadKOzQiaLmLUBK9B9/Qlu2Cn3LDiIXL6fFD7/Q/vuvAhKgwrFzsjJrt/LErA4ydgtWLnVuLQbK/3oFXZnBmUF/l4CWF5qEuFzw3zdNpv6Zy3kXegj9HEoWcGKIZcrbIBFkdO7uaPnairSVS3CVFNsWOpjAJWRgVZErNML1hTYS4y2HGx9yjWU/G7pfEpw50Ot4Qjgc4l0T8EZGWR63jtOgn6RV1wMk1rX35A0HR4zElpSUsHjxYvr27Vu+M02jb9++zJs3L+g6xcXF5OTkBHycQEpVhXJradEHX46H733+7rvwyCOwtf1AzD/+VEysTp3g0Vb/6fUXXnC0/38DmZnhl9kVSH7kXIsfhaOi8amp8NBDcNllKqM7FDSCNNL/KfX9f/RoODP4S6FW49tvbT1uJTCJYQGjcqfwepXTm2NYPFcAH3Bt2Pv3xxGaPKk6Bg+2JOxtWU8CoUf6DRrAk0/WdMOOPGq6b928sg6/TWitSmL6PqZ6NRzcG8M3b3RCSjiQmMr86+7k82c/QhgGUZs2VtbHlfafdbZsoMm8WUB4dk5OTNrt6sVDeblOJ8jJqZqEzEUJP3Be0N8EYKQ4n9o+u0c0513kJENbVNJV+qZ3pV9EQwoBQrDhnPMpTkxy3I7aiJQNq0NmFX/FMESw90wIaJqkczdvWB7YIjcPPfOg5e+VKn+GASEk2Vnl92NtiMb6S4Ey23aylBzGkU83FhNKkhMd5+GcK52XQneCI0ZiDxw4gGEY1K9fP+D7+vXrk5ER3Nz22WefJTExsezTuHFjR/uaNw8WLbJPPHr6aeWD3rw5vHHTWuThLPuNSqkkBuF6Sv1DaN06/PoA0s+zNQC6rsTDDkisD2eeaR+oFhh0YiXJHA78oW1bxYR9aNlS6Tzffvuo0iSXIT/ftpOVCAoJP9SnaSpB0TGv37FDVbCywB7SA2QE4aLWPQZnnAHduwedjojAQ2N2Yt+hSk4+OfSMQm1ETfetf09rYqnNlKbG/p3xvHrbqcx+7Uymf5JMm68mE7mhcoKHPwSQvnwRmqdq9jlVjcaWeX+apiMyW7+BWaVqQQIopnIimwSMpERKOoen6+3czUtMrH07BCZ9+a18X7oGUZHkXD6M4i4dMOPjMBITONS2FcsuvY4DbY9i3+1S6CUlIeOXOSQElNR2BlVy9sa7wysuED3zT0SJx7JNu2hU5X5WaGCU9rPhJidWhBObulCoKAHK6NwNT1SMZa/ajnXYzyZIkusXEB1Xsy+TWuVO8MADD5CdnV322emrbxoCv/7qnNDt2CG5bfaF3Cj/G1qvuX+/qrVaC3HddVXxbPVyAosq/2AYMDw8zebgwUpLaJXoJdG5R7yMqPgwrl+vzmtsrNIlrF+vorBHI4EFpbGwrektacXGsCMFpglZWUrm6gi//mrbjnT2VClaAerS9Ki+pLFm4avX26ZN0J/zsTYVL90Av/wS/mzG0QqrvrW4SGfPlsQQ0+kSb4lOweEYpn2czE1f3cpm2TzkPnVPCXH7yoX7TiUF1Y3Gtk+NdUxmE5Pg7EHesImsBzfH+2RpFVAw4KyAwVWuOz3ksUfHwKXXlFgOJnQMhjORRmJXeXKNpkFhEQmff03kqnUUH9+FQ0/cz66zTic/terT67UJ+Sn1LJOJQA0aOrGqLGHbein//6u/IyKhqCC8907UgsW2/WwaGVXuZ00Dup4QODvsJBpbUVJwpBIjvdExrBx2JSUWvsNZJGIfOBClfU3NtuuIkdiUlBR0XWdfBZ3lvn37SEsL/oBFRkaSkJAQ8HGC8HKw1E37LjcyBwfGkNUcER0p9O+vqgs5534SCdaerXfeCXl5jvfvcik73dTUwDb4BhP3nLmYK+Sn1iwhPx8efVRZex3NGDky5D1ySxWTDvbsgaFDHXr0htBvX4uzamIV4XKpNjRqVKXVjyzq11fFDoKMpCIJHQHMyVFjt6PNFKMm+1bD46R/Kzcsl6bggKzLMCY5Str0yQuqUiGqutpYp2T2jv8UkZgs/aoLhYJJPLlcxvigv8ZO/hHtwCEy5i0M67hvuqeYswepyISPVPv+7dXLy9tjloI7AiFVX47HW35lvF6i/vybOg8/izvnKLuhbZDRpbutHlYAo3kPL3baNuFnFVdmhoanBO6+Poa//nJOZEWxfWS4qv2sEJKIaJNBF5X3406isaHs5moahXVSWHXB5UF/0zEQoXoFKfh9YssabdMRY2gRERF0796d33//vew70zT5/fff6dWrV43u66STwo9KuvDwLqPtF2rcWFVCqoUQQiWuPfywCmo6WIOHeMraszUrS9kWhYH27VWRrVdfVT6yXbuqCqDzPt3IC7NODH1DgxIrh0Geax3S0uCtt9T/LcLSN/AOp/MHWgXxe8W/K8LrVTljf/9tu5hCiFDp1XxMB1ajO/Qq9KFVq1pa6MCHhASVnVWhwx/CdyHPL6j6FG3bOrOrqy2oyb41KtZDTEJ4U/5e3CzjeP7mJNvlTF0nL7W+7TJWcBKNdYqKZLYiGjSSTJiWT/tTcoP64laGYDyXEEvlNgoU0Yn5bTagNIVOLcbcbnjxnUI++jafcy/00L2Xh77neZj8nZdfb/ySxNdegpKS8v1U3LdpouXlk/6nw/LiRwEON2tFRoeufvFTBf//n8Bi7kHlrwRGQf3WCjLTIKVACHjuWec0yNu0cYD+uCKu431asjlEZLhSS9BckhEP7yauvIaCIzlMKH34kUBhSj1y0hpWerv35XdHA9ulMxvx+bPHkX2gZnylj2iY8c4772TcuHF88sknrF27lhtvvJH8/HxGjhxZo/vp319pXcMJmnpxs4YO9gvddVetjcSCipI9/riq0eAEHVlj/aOmwZw5jve9e7cqQ9q+Pdx/vzJ4uPZaRXhOmvWc8/NWUGCr5TwqMGqUKrPlTyCio8tC1JGUMJ1zeIQnSKU8Q6ot60JuWtdh5kwHbeje3ZbIxlLAbM7gfKY6nu668UZVvyEllDPMv42nn1aDTb977ibeKk0qDN2t7tsHAwbUele9ANRU36ppcPwZu238Si3Ww8tcTrb8XQrBvvZdMKKqZjAcStOnZ+0J+wVuR2TTG0u+/Ap6nJuFFlJaIGz7UiElkfMXBWgK7SzGfFPGBQXw/dduPvuugK7dDF4ZV8TzbxUwcIBJxPMvlu45RMtMk8RtO3DnHyPRWCHY1G8Qm/sMoMgvSc0bFR3wZD/PfXzISNpQPhptwF5atTyIsImwG4bg11+F4zhKQd/eCBtymUAucziNvvxuuUwgJE3aF3Pz21u5Z2RSebtK9+G7Z+1QcWbCagajJrH5rIGYbneA48KVfEoszpLR9m6PZ/yLx1OQF2ZiTxAcUYY2fPhwXnrpJR555BGOO+44li1bxvTp0yslJFQXug7ffReeVY7AJKli0pE/BgyAW2+tdtv+CdSr52y5SklWFeFQm7B6tUo6evll5VVbWAhr18Ltt6t8m7zpf4YXGv/vf5Wm82gWKA4YoAYBvkIE338foAOIophHeYI9pLOTRuwnlQnJt4TcrBBhlPwdP962GkVdDvENF7E9qh3jximDjmCLaxqcey68+aaqRFzrkZqqZAVDh5Z91YSdXMgkR6ubJmzZoiS2Rwtqsm898eydNGyVTTjFOEBY2upIIK9OKttOD10xzQ5HQttnR2QBujRz9hIJVX1JFKuIqT95DVbIwUdgp06MpE+XeP5zexSzvkjhyQeiOPP4ON58IYrN85ahrV5tO60esG8pidsfPMHvqIQQZHQ9gcVX38L8UXcwf9QdrBl0cYVyEDCSj1lLe3aTznaasC22A0mtRMjXmpSCfIdGAJ52rcnvd4btMmnsY5p+HovOGcP5Y/aSUMcblEgLzSQu2eCGZzNIaVT5fgpFYGV2pqW0piZnMoIhPzWN5SOuIbd+eTJ4Etnci0NHJ6mRnx3BstnVtwg74mHGW265he3bt1NcXMz8+fPpGU5t9zDQpYvyP48MI0I9gonBf9A0xQxrcRTWH2edFTrLOoVMejPbegHTVAw0BKRUFrrZ2YGRKynVZ9EiuO/wffzBafxCP/bgwPFgwQLljnDyyXDQ2r7kqEBSkpIYnHkmdKpsSeLCoBG7SeUAfx3uQCji4PXCaQ6k2wDMnRs6nKjrND6jJX37KjvkirJzl0sFlidNOspy7XJzKzVYaRadHYTbrSx/jybUVN/qckuG3b6Cpu0P45TImugBmfIVkd2kOUbEkS9DW5XpVDsie0ofb2n1ruAQmLRjLQ2xLgwjhcDbpGHZ3xWjsEZSeoCW8dfvI3jkzmgK8kv3YAiQAq9HMO61KN5+t47DIytHxylf0vmrT0javiXsdWsthMATG4cnNo7c9Mbk1UurlPQlgHT20pidRORn02zDeswQXWJioqRuGMW+vC2bhV5IStKPS6D7Odnc9c4uGrZUvqhCk2WR/pg6+dz+2h7ikwMbWFtkBKGSEQvq1mPTWedi6HpZrzGY7x1vX0pY9Vf1ExCrH8utJcjKUtW6XC4oDuGj68JDI3ZxGRYaUNOEZctquIVHDlFR8NhjMGaM9TJP8AgRVtEDIaBuXUdlmWbOtNcPGga8VTiSt1BlKDUMBjOFN7mFdCxKjPmI1+LFKpo2e/ZRxqCC4PHHYZV11Z4tNOdWXseOZGmaMj9wRGLfeUfN/4eCYfBB+5e4vqU6xf6cNyEBfvghDNJcW7B1q5JSZGUFfD2QaTRlG7to5Kgy2dEkJ6hpuNySXgO3s2N9EqpSqfV9qePlDGbRidVBfxdAfIY1yasp6Fl7qmz23j41Nmjm9wm9DNp3NtiwRsMIQmYlGvfznL3vhZQU9j0jZBvWZuYj0Hj1mSjU4CH4Vt+Z1AI3L7KdZsSTy0VM4hyml1ectEDC3p10nPwFG/qfT2b7LiHbczTBVVRIQUIysRYRZ4EqRTtp68nYDcw0XTJqlInL5Wz4FrFiDQnjPgu9oKax74LLmPXfOiyYmkxelup/omNNWnYp4oyLsmh9fBFCwOHC8KOwEDzBsaalBJaJiaZJyxnTaLBqKSYCX9Hm41jO8SxmBV0d9LmCgjwHZvMhcHSEGkPgwAHo2ROeeQZH0wImGp1Zaa+J3bTpqJrevu02eO45FYkWQkWWhJBEUcRL3MWNvGO9cny80nQ60GMsWGA7Y12K8s7YROcHBnESf5NJCHGl16um5OcfxYkJWVlw9dWKxNrgPa4Pmfim6zB5sgM+P2uWMwILzGlwMaNe7YhpViZt+fkwbJjS5h1VuOuuylMDgI7JVAYRQwGhXlEej5oI+F9Efo6br1/rzJcvH19a5KDiDScD/m3CDj7nMsvtSSA669CRaGqNon1qbKWolxDwxicFNG6mvvc5Fuia+vtB8QxX8mnQ7fnSiApPPYni7s7Kw65dqbF7R7BzXg6PR+NV7uBbLuBzLuc8fuRE5ofsT33yg9a//YBeVOioPUcD9KJCun75Iambrb2KJfAgzyAwsD63ksZNTe69z9l7PnLhUpJeeD2gEp0VSq67gdseaMHMz1LKCCxAQZ7Gyr9iWfFnbEC/PrSrIouGaVZLRgBHXkoA0HTeLNJWLQWUjSSUn+UPuZYoihzkXkgS6lS/ctcxQWLvugs2bw4eSfEROijPXDTR+YkBnMTffMKVwTean68igkcJhFCJVnv3quSqhx6C994T7N1tctcHHcnpdyHz217J0qQ+eCuOkFJTHYehXK4wNJql8OJmD+m8VFZ+NcQOpkwJbwe1BWvWqFT3Tz4JuehiuoUcqWqacgcIiZdecmyU/JLnNstBiGGoJKeJFiqbWon9+9X9EkSD7cHFozxBLgnYkVhdV4/ARRcdwXbWUnhKNL58uSvb1yUF+VUiNJOYxGJc7nIysJUW9GARHxO8FrEA3IUFRNVyImvlwVm/geSb3/N5/q0C+vT30vNULxdf7WXKB8u56+LVZbWgpduN1MqZiIyKpOCcM8kZdYXjmaScbGfLmehItDIrqeV0ZSiTQ0YPBSAMg3rrVjraT21HyvpVdP/kLaKzD9tqhDfSmlV0DlkE4YJLi0lMdLDjkhIS3gs+eAmGt/IvYM7v7sr+y6V/z/4mia2ryuU2k5crUqprWpW8Yf1RE4UOfAjmrKEXF5O+dL7l0KAFWxgivkM4eAa6nm4xOxsGjnoSe+iQspqy4mBSllto+lfS8KIy667hQ7ZgYdy9w8KOqhYjORn69FGS3uJiWL4xhtHzr6H+nEmctP4TumXNoDE7eJXbyzvArVuVhnP58pDbP/vsqgWoDVy8wS0s4AT7jlcIlSl2tMHjgXPOUdMCDuDGG3KkGhHhYENSws8/O0qkk0Jj+uGeIRc9mhKc2L7d8oZ8hgeZgq9ub/CuTteVkcTUqeHp6Y8VrFtUj0MZMWVlZgOhfGFLCtyVptZ30YiRfMyr3G657aQdW2u4tTUHH1Gw8uKMiISBQ728+mEh739dwINPF9FiYHN2vPwmn3+1nxeeLebVru+z2uyALNUEihIPsdNnkPjKO2VWWKHQqEnVZvsM3PzFqcwntA5aahoxh5z1S7UZjefPod1Pk3EXho40HiY55DK6Czwe4Yg0Ri1ahlZY6FBhD5/OPy6E77DJxPfUtU+Orjylbtcmn546GJGtyWRIK0eNxF3b0C1eIvnE0JtZfClHYNoUUBGaJLVRPp1P+X8Sy/r1IX3ebSAQSN7hhuA/33+/IghHCQ4fVpW0WreGm25S5gpnnAHvvQdFftX1MkjjDl7ldl5VX5im6nQfeSTkPnylUENLCiqjkFh6spBuLGENFg+bx0PQue7ajilTYOfOkAzfRPAs9zOT3rblCV0uOP98y5/LIaXzUUVUFB4z9IVbvNjZ5moFLDIaS3DzOreFLAE5bJiSLp9kb3l6zGLtgtSQuW9ejxaE5KqV7uN5DlkQBnf+kfV/rqoeNhSBBRUZ+/LvvfznuXwevSuKJ+6N4suP3VxyTjxXDo7ngQdd3L3oMjqzin7GdDJJLbNeily+ivhPnE1nNG4m6X6S14GtV2UIDG7lDaYxACPEfW64nYyIay+iDx2g6bxZgLNUzVQyQwYJDK+gafPK5z26VftK0Ux97z6kg5eeFAKzcWM270vENO1aqpG9N3gI2Hdfrs3MtySzdkQWqhaNtVqnYjRWsyFcr3NbSD2s0Ew69NzHiLuWERFZfcnmUU9iqxs9MXAxDwuD8IwMGDhQ2T/Vcng8yi932jT1t88tIDjUw/UGt7OMUu2WYShbqMMhbLhQ082dO6v/+57rcPKwVtKZ05jDDhoHX+CNN1Rmv8Oyw7UCM2Y4mtK/i5d5kGcpwlr35DuXd97pYL+aBt26hXbS0HXE1Ck0ahT6Qm3fHjjoqdVo1UrdjBVuwA204RD2Kccul/I5btr0SDawdqMgJyKoEXw5gtnql8ODmwlUTggVQNP5f9D65ymIMCvRBLOismxdFSsWhSKwW5bH8PJlrZj6WhrfTXTzzXg3Tz8QzbpVaj1TapilU9Wz6c1Z/EYR6mUkpCR6zjy0w9mO2vLgM0VERWHrZxoMEo0ldONcptGBNZYzipppEpGfS2R26L69tiJt5RJMhy+Z97mWLqwo9TANfk6FkMQnSPr0d3ZvyphoZ8ECITCef5rokPbIksLDcUybqfyGk6PdZZICUPenP5kNuisLIuv02YmpGxPw8X3nD1801p/IFqRYe3q+zY2YdrRSmBx3+h4GXr2eqJiaCVQd9SS2Sxdo4MDFyRoydHWNMWPCF4L+w5g8GRYuDC+A6cLDB1xb/oWUjohjSopK8Pr6axX5Pe005SvqFAYuckjgZe6yXmjTJqVdCLcU278FBx3cBlrzKnfYLuPTcH/5JRx/vMVCixerMPvQoTB6tJIxhNp/qc4k3UHwSkq1/1oL01QzJFdcAf36KcPbCs+no2pxHP0mGNVFfJ2isAsd+MOFlx00sfy93tqVtJwxrcrbr2mszcwPSWAP7HLz+cONKC5UCVemIfxstyrfMF7crKILXzOs7DthmkSstCku44c27U2++DGflt3y8SddocvgijIivYUWnMXvFBIVdMnUdUpLWvcfMMI/Eog5mInm4B38JcMZxfvkE4vVAMx3vz/6UiGRwU9XJRT1sOqMyyEBz3tvIS8aQfPWBvbJpALDo5O1216Q65TIVoQvmmz3iW7VvtInGPyJbLxnDwUp9chJa1TJ3sxAYydNsI2VS0FeVs3qto56iy2XCx54QGXnVw0Cw078bZoqYWf5cjjuuKru5Ijjs89UMC4cvaoXN5tpEfjlqaeqqOIJJ9iu63arRBhfMozPP3bqVGdt8OLmY0byGmMsFvCqmrY//uhwXv1fxskn29Zn3UwLruN9BGZIGcG2bRYDM8NQJq4ffaQW9HrL/w2FAwfg119JSzsn9LKoMUStREGBuh9++01NA1iM2tqwgRQyOYB1pM7rdWSNfEyjY6/97N5U9VC0F51UrD0rBZL6a5azs+fpUHP5JlVCKO2jLxK29IcUTENUTsqxgYbB51zOFXwOKPri3ryVotOdlQFu1dbkyqf2oOVHcTjTRVyiwdwfEvhtQhLSdlpawYubbTTjS4ZzNSqxtGIxAEyTttO+ZckVN1CUHDhL4bQ0rqXl0hGGERmJFMI2mctE8CDPACZ28bn6LYp57EmDU/pYR3y0rTuJn/wL+u4MZHQU8qxeGMd3xLXE2jYRQFu/gdWZ+aQ3dlapbufiJnC5feRJ1zQM02RtZr6lc4GRlF7JsaCq+tiYujGVHA7S27UmeuafMHcBQkoK4usSnxF4LTRMoimg0OZBF5okMrpmpYJHfSQW4JZb4N571f9dLhVd8c3snniibynrm38OvVlLO/ud7HH2kP9b2L8//IQrHS91qZBBnJurolv79wdfyQJCqAS7IGXsLZFDAl67AYTLpUqxHQ24+OKg9VkNNG7iv7RmI39yakCZvmDweLCeinr8cWWGDOXE1WmkWgjYuJGzznK2uKOM3X8DN91UXofXZtrBjZfbec1SF6fryoP31FPLv7OX4BybaH3cARq1zgoajRVCEhntwa7vlOjk2UhjSjdEw/XzbUuvhouq6mHtorCgpnWXzoq1LXgQDCY6+ymfZhVAzO9/EPfZRJAyqN4wmMVXYopBs/bFpKR76X/FYZq2Ky69NqFvTE3ApMRry/ZfEQIldWi6dHZZVM33SevVw9Gn4nrhoKrrARxo1c6WwO4nhbt5ka20IBStOeWCQ9YEVkq0V94m9qb/EP37HCLXrCdyyQqiX3gHff3mELFV0D8bD0C9+ta+v/7wFIX2SXVSgtbKMzbYJxQqEtiIFatJufNhYif/SFzGfmL3ZZKyqXLJdAGMYILtzLY0Ndr1CI9bhMIxQWKFgOefV6VP77gDLrwQrr1WOWTNmwdxcWB3Q7nw8BEj7XfiDn2z/Zto3jz8ZCsDF5cwofIPWVnQty88+STsdm5aHhUF48bB5Zc7Wz6FTFwWpStVA42jR5wZFRXUWut+nuUdbkSilUZg7Tu2yEjf/VoB+fnwyitVZ1lSQnw8o0c7u5X9KrjWHuzdC59/7lgzcz/PcQHfAKBXSJwxDDXB0q8fvPCCisi63coRol8/+Omnmm587YSuSy66bSVdTtuD7ionVLrLpMtpexhyk6+ggfV99wL3kYN1fWIJaCXOsm//CT1sKHiKw38tuvDQisrTF7E/zyRm+u9A+JGxyGjJra/uYfD1h4hJCH3Pm1KQV+QOWYghOfNgJXLqFBXXqUhq/QlqsO+tyHCoT0nTRIqSEoPeha8whkbs5lWrWT3/4xeSovzy61vJJ/i7aWhvfaj+X/pbGXnOd+BOcFC5QAy6yH7wpyCJTbZ3WuoW9pwAAQAASURBVAhFYK0qdxVuWkvBwYKgn3AIrXbwMEmvvA1eb8Agwkopfy8v4saDFuS9LoRJ/aY5NGtfs9rso15O4I927dQLyR9FRZAXIknWRGM7IabUHnxQEbtaKqK79trw/D11vPRkPv2xcF9YuVKlbT/2GLz2mgp3O0BeHnz1VejlNA2uj/0Scm0WkhIaNrRZoIrYvh3efx9Wr4bYWKWDGDRIRX5371bSkYgIlbK+aJGq3hYZqYS/Taz1fxXZ5yGSeZ3bQ2bI++BywWWXWeSHzZ0b+ka2gQRm5p3In88pkjbNQqYoBAwf7tCf9p/G77+HJfp2YfAVw/mRTxnb7Uv+WBxbabZixgy1WX8pzsyZSq3wzDNKqnSswx1hcvZlmzh96FYytisymtYkj6hYLzmHIgk18CoiiklcxDV8FPR3TUqkcFoA+MjAiY2SDw1alLB9baSjaXwfvLi5jvcrfS+B2K+n4PEWwfmD4YTjHG8TICJS0vvCbH75Igm7ql6gBiSdIjZAKP94WTNFfIKR34x5CwOIrBVBrkpUPr9ePaKeCHzBf8oV3MkrjrchpSA5LXBAVUYQpUR752NL2UKou0ECxKhtNW0hSWlcwoGdETZrChoetwtsNOUB7bNAxShsKHIaGGm1XzZ6xh9gGLZRcH+0Yz2/cDbD+JoMGuBySQxDnXcpNfZtT+Cz547nhLN24SnRWf5HOjkHo4iK89CpVwZdT99LdGx4eTDHFIkNhshIFSSzC+gJTOpy0H5DixbBH39A794128AaQt++KgL9zTehllQd4QB+4jOusC9d6JtfvfVWaNQIhgwJ2Y6tW50FT+Pj4Y4Ov8K8EAv+/bcinAMH4igrKRRef12F64VQrEXTVHSvTRto2VIlDPnYjBDq+DVN/XvzzTBiBFx1lWLq+/ap8zJypNKtVNAB/MQASnAmYtd1xacffNBigVC1lG2wgdYM4TvW3tohKEH2jct8uuYPP6zyro4sHHpv+kNDMijqN95MDH4dfH2zP7n18WTfuLVHzc2C12pExRg0a58V8F1+dmhrJh2DPVg/mxKot2wlhw4dxqxj7d8ZThQ2HDix1PJH76HZfLK6vuPtC0wuYhJn80uQ35R/bMTEHxATf0B2bIcx/jMII4q87I9YCvNCT7MZhmDUKcuR0+0Jl7e+dXZ5dZHephVR8xcj8vIwU+pSVFCoMvtVA9GycpBuFzIhHlFQiGub8mL3NmtSvpwFtApVx0wEj/AEoci9D0JIYpMM7hppoZXKyEBs2RZyO3aQ9eqxY6vGxrUueg05xLR36mN4CNI+SaNuO7j4YkVgDxd6yqp2+RCqepdVFBacV+3yXy6YFjZy+WqEGd7s36n8xXaa8u0He/jP88ls2aDhf43274jnxw87qO8EIAWF+S7+nNKcZbPTueTuZSSmOH/fHfMkVgjFTVYHL/MNKOPoy/jCfkMulyosX0tJrE+TeuWVoTLLBVEUMoFLiMNhdEIIFZZyQGJDW4uozd14I6R8U1lXUwl//aU+mqbKub75ZlnFnLDx/fdwewVzdh9j2bBBffwRjOFMmKA+/olV776rNBTjxkFamrJmA/KIw2kH26GD4tItW1os0KVLOakOAwepw+n8wYFSuyl/Ca2uK+3rRRepilXDh5dbp9VKVIVN6jo7LryDn78Iv6tzueCtt1Qe3f8qYhJCDxwMdNLYa3mnC0DzGkT/Pof8YYNruom2CJfAAnQ7K48Vf8WwdKZvZsX6+Y2kkHt5kUd4wn4av6xBG3BfMBzv0mWO+7G9WyPQXRLDa9+P3HSTQac6kYjp1stIQDt0CNfW7Rj1UpGxNZRtZ5rEfTGJmF9K9eqaBqZB/GdfkTt8CFp+ATG/zUbLVbNJRnwcWkFhWQlX6XZT2OdUcocPwb15G+6NW0DTKOnYDm8LNUsqowIHosvpynaaOWqez77s/DF7cbksSKy3eglHO2nMtZlf8NupCaXfxOBym0TEFFFSUP5i1N0GPfruIqnHCqBD0G05KT8L4Udh7RCU+FahspEUAnebpngMjS0bKg++yhMmhZ/iQiAl5GVH8P24Dlz+wFLH+zvmSeyaNUora4cIt+REz3z7hYSoVjTsSGPuXHj77fKcFzsUEc162tKdJc42LqXy79q/X5UCs0HLlqry6oYN1nxLSuWOxFdhdBqmqUKE+/crMloVPPNM+BYOVqiYWPXFF9C4MfznPypyDbRjHU4I7LffqvGBrVKlSRM47zwl1gzDduw9rieT1DIrHn8YhrIFPu44Naio9ejcGU45RQndnVxDXYfmzdl4wX2EGqMGg9erJgL+l5FYt5jouBIK89xY3csul8mFUT+DjdpFSEnUgsX/OIn1wTBNx0RW0+Dqh/cTm2Dw55Qk22UTyeERnrDX9vtBmCZi8xa0SZMwS5MHfG0b2jW9zCHBv4pTRKR0pAC4404T8Z9Ntln8AojYuYe6Dz+L1HWKTjqBvEsvxExMCLq8U8R9OZmYn2eU3yG+4IDHQ8LnX1dqk5abF+ie4PEQ/ctMomb9hVZSgtRU9E5MlJS0bkH2baPxtGyOkRCPnqM0aCpI4AxN2hbT5+r9tOhaACgS66+HldmZ0CANWScZcSh8zeZ+UjmZuezLDrSV8Xo0hDeK9ifmE9F4HbrboG7zA7gire8XJwRWZmcGTeYC51FYJ8hKTCAlhCtEJUiJedUI3hoXi9MgTtmqpsbebQlkbI8juZ6zINsxkdgVDDk5KnDXuXPo912JR7Aooa/9Qh6PjXHnvwcp4Z571Lv9yy/VDLcTuPs7TFP3h4NysELAww9bE1hdV/LTDh2A0093VCAgAD/8AHPmOF9+6VLFmBMTFSOpCQIbDFIqqcJVV8EDDyCB+ZwUVODug66r6eqhQx1Krd95R0kqKmbw+WqnBsHnXG5vPo3i39nZyoCj6tXv/iF88omzaHRsrBpMzJ/PIaPqVgtVDfofK9i3M5bCPDtdH3TsYJKU6gr5qhJVkIPYwW461Yf2qbFlhKBiEk8wHC70kJ+tMffHBPZujQzpobuf+mwW4QnIpRCI8V+Utc/XNsM0y6aUDxd6yj7NemTbVn8SQtKqnUGjhEz1ADvM2xCGQdTcBdR55FlEjl1yQojt5OYR8/PvltdfQiUSZBmxL71HhGmWTWO7N28j+ZmxYBjkDy03JG/FppBVuQAuuXc/176yjRZdC8rOb7CEKT1vP+blwyr5n5Ydh815HcsdZJCGVwaPPK5dEEvfvvUZeWNdBp/TloF9OjCwj4rCHi4Mr9N1ct/XFA52bg9SOnLdlkK5c3tPPxHvtaNZttK+37CEkOze7LzPPiZJbHGxSl75/HPnnCWv2G398GuaIkHDh9dcI2sIn30GL72k/u80QJeWBh2+f16doHjrrOIAJCU51qRedplyi9A0xa9crnKuesYZareASharSjGDRx91ttzXX6sp6C+/VKOaIwyZn8+Cj1bz4ynPMHp4FvfxfNAIKJRP5b/1Vhg7SE9XhQ7uu6/czisxEVq0CDrA8KKTSSp2HYmUiucnJakcutRUNSjKygqjXf8kDh92RmKHDlVuDnXqkGwtw7SFrqtiHv+LKCnSmD+9MV++dByhsqxXr3VT3K4jUrd+nUgh8DSxqNBXBVhFoazghMgO6ZLOrPF1+c8FzZg4NoUtK6Mc3WrG+C+QMdG2JMcfQkpETnYZGalItId2TQ/43DCkLqf39ViWppVS8OSjUr2+2jUPS3IkpEQ7eJi4L791vI4PB3+ZifnGe8Q88RIY1ue1ugl9wjTR9+4j6u9FFPbtTd5Fg5GaRq6Ipwk7sK3KVddD296Hys4lVCaw/qSw4KyeGF3bIwkkrVLTwO3C26aCr3rp3j/gOttSq5ou+fsn63etf9uqIiOAckeCmkLGvIUUJyex7ZQ+tsv5DOC8jdIpHnMtRffeBJpWrTpF4RRgOSZJ7IQJqqKU80RmyfTiPmSTqIisf2fkY2ATJ0LMv+zWXQFSwosvhm+YcNttMOkbwRuHLmPK1ZMpIYTnkhBwww1h2Yzde68y7X/0UbjkElVY6s03VSnVTF+f0b27cj6A8PzBli0LvczevYpNm+Y/UvXrW4bQhO30vP0kzjsPxk20H0k2aqRyBVu3DnNHKSnw9NPqJHq96gbYuDFgERPBS9xFY3aSSegkjgK/fi87W3G/U06ppUTWqV+z3zkJYt8bEpqmorCjR4e/7tGOogKdL144njnfNaekSCcUDfF4BLnEIeyIjJQU9vt38wlCkYOP345gxqepSnsqfcUO7I5dkpYmadanAcYPE5Dnnu2oHVIT0FS5rsjszAAyC+VRWX/C/fxbhZx4snqh6S6J7pJomkTXJWNfMRjaV3lvyqHngtvlsF6dggCi5/wdUhOaMW+h+sxdAK+8TftPJ5K2YCkxGQ6n/6oDIYj6awEIQf6QgUwf8zHd9BXsojHBrpGmS3QXjH27hAu7lQdfrAhsGSmMcHNwzM3kjrwUb6N0pNuFGRdL4Wkn4Umrj2vDlqDn1q6oCoBpwJ4tEYx/IZW370tjwoupbFkVGbZj4j8Vhc2YtxBQxS0iCuyn9X1n/9DD9+Dp35voth0BCDMfrBxS0LRdluPFj0lN7AcfhCt9FLzGbfwoB/Jn7DmkiIPKzigiAoYNU6Gprl2PZJOrhKws5YLlBL48pJNPVhwoP993js6irraP/8qbGSGDeMaCSip66KGw29e4sVrt3XeVU5e/1OG009T37W+7TVUHu+660OJlHxzIGvjgA0q9PcJutxVKcLOetggkbVmPGy8SuJ73eJ/rCCfmsGuXqpZaLeh6+SCgFBK4jvdD+x7bwDBg/XplE/zyy9VsY03DKev3C7+2qBw8sYRvQBgbq4rF1YQhxtGGWZNacnBvrOOKVREUIX76DbNeXbT9BwNUcL7/H+jUDqNz8CQWfxRuWntEHAr8EUwfW1gA74wNsxymgNvHmGr83bgh5stPIJaugN177ZO8TIkxYmgZcTKS0pHZmYjE1EpE25eYFh0Lb0/IY8VinUW/x5CbI2jVSnLFlSZpaSCzFRErPLAH/YGbiX7qdaQpy6bxQykThZTkTPmRgnT7Gu657nTSl/xN/cXL1RcyVPmWmsF+mcrbu67lqwcuIq/Qzf7sGDyGjhl075K0BiYvvVdI5+Mrk4CK59h3HcqSolw6hWedTuFZp5duTpL81FjcO5Vnuv8eV9GR97geNyV4sHfy2Loqmu1rozANgaZL5v6QwPFn5DL4bmde7JUItx+qk9BlBV91trh99vczlGqt16yDxieXfefSoSTMXDmhmTRtl0XdBgUUO3jNwzFKYnfsCF/6aOBiE60Yk/8kn7uuUV9eeqmydwq3isA/BKfHKIRK3jnllEDO41v/oJnEJYwnkkKG8l35ArqubKWeeUa91auAF16A+++v/P2cOdCxowrwPn1ZIslOCSwoPUQoLFjg/AT5ypdajHw8uHiGB3md2zhUmuWfQia38xo5xPM+o3BSUccfhqEqwVarMpZhVLLdmE1vPuKaamy0fNPjxqlLH1mzpa6rh/btISEhtDzk2mvL/hsfr8hoqCBu166K8J5xhpI219qqZUcQRfkuVv9dPwyPVEkJkTRhJ6/tv50rui2ArduJOpwNQEHdVHZ3O4nC1qmkhZgyKjhYELSyle3eS8mfU7RPjQ3qGTt3touCfGfHrOsSwxAMON9DUpJGr74pbNxYn7hYg+FtJjFm96U0Y3vltqJe9iVD+6N16Vi+vaw9ZUQWAos4VCRcHQbAiAEme/fChx9oDLtIx1vs5eSeCdxw4UGaALmt21H4xIOIj8eTtGkrmlOimQO5Te1HbcIwaLzgTydbK0N4qT2V8Qv9OJ/vKMqOhmwcbE1w+JBGy7aBfXnFqfpgyVHBpuPdm7cSsX5jpe8f41Ee5zFcePDixv5I1fe+SnC+f5fNjiO6bioXdQ9xSKWwk9FUbLsvmgrh+fL6rwdguNzOrmEFOVFKfZM9O0NxJ7VlISRSClIaFHDuteER8mOSxDZoADt3hh+EM3AxkRG84r2TVA6oJJK2bYOzsFqAOnWUG8CWLfbHKqWaul6+3GoJgcDkXl5gCN+V36yRkUpCkJdXJRK7f799AFdKlav02/hU5ur1STEqT0t50fmTUzlACk3ZzgksQjiZ43W5nIXjIyKUwe7w4YqxLVgQ8LOBxjC+5nsGBehbD5DKwzxBuSInvG5a06o2zV1pIz4CXor3uN6vU7VGdLTSjtudntxc5RbWNEQdkH8cTz9d5gARFFFRauRWaoEmhHqEb7vNepXYWGUDnVC9JO2jHgf2xmAa4ajM1H1fSDTXM446Sy7kQlaQl1Kf7SefweEWbRyXGQ2XwPrIX00gJ9vZ8xuXYNLtRINhV5Qw/sMIbrxBR9N0TFOQV6Dz30O9+NC1ht+8venBIsCvZ4hwUzTyYjznn40DJ0JLzJolGDpEp6iI0oSvCJatcPPf9zpx3XkRPD96Ie5ubfB8IsLqlSL0gpDXSuzz4C5yGCIDTEqtQLHuISXwF6fwJcPJJolWbGIkH9GEnUxgOJeWVZV0fjSFBYKd2zTadggvmhXUK3XRcqSuBchlvuBSHucxAL++1ja1LfgvUrDg+2Ryn8kjvpb2Pfs7dKHOji22y0jA3a0dUX6zKMf38LJnp12VSokrwiS5XiGxCSV06LmPtt0zcbnDI27HpCZ2ZNVnUvHiZjWlo2Qp4ZFHlP+QNQP81yAE3HWXc7Jul3ku0dhEa5bQrfzLggIYO1ZpV3fuDLt948eH5pBSwpbsutxjPFPpt8+4nCbsoA+zGMYkTmQhHVwbmNXhpvKF8vPVnHfjxorUCaGI3cKF9jsXQtlWvfuukh6cfz7Mn6+KHfhFjL5jCFMYYpGgVbXHR9dV3lG1I31CwDnnBMwUrKV9SAKbmKg4oBPHoSoG4I8sBg5U5fmsUFKizG9POUUlgqEe4QsuUD/7BwR1XY1jvv76/wksKL1l1SAQGDzMk6pK1YF9dPj+K5K2bQZCR4J8BDYcKYGRlB526dm1mflBrbYaN3VGdvJyBOs3GSxd4OLvOS5ABDgHGIagwIxmSMIMilu1QtZNxkipQ8mZJ1Pw0kO47h5DdOtAWYWPiIvE1JDHs28fFQisglkq/Xj/h7a0vPxSZsyII3njFsfWSFLTqDvyokrlaCuWmY0rzHC0PVCJUTktm7HzzNMwI1Q0T+pawJxVLnGczS+cxp+8yw1MYARP8jDN2coYxnI5X2Bd5NQeEaHrdAQMgnz3XsXBlHLV8EvyAp7lAYQDWzWVjGffdm+JxuK/ncUTwxm0VaWssG89fxxo2wlPZJTlXKMESjq1R9ZJCvj+kmsDz1swnDJoG1c/vJhht6+k40n7wyawcIyS2CuuUBZOwVUAoU9SpH/dPo9Hzased5zSxtagxrImMHq0KnBQU8isKFCXUoXjrr8+7G3t3OlMiWGgM57LyKKc1X3ANVzJZ+wlUKO1wWhFvwsT+OMPVBbSqaeq67JrV2Bxgl271P+tpjClVCVmR45UBPjP0imybdsCrvE7jEan5hLDdF0FuB9/PMwVMzKUFcUHHyg7AR/uvTeArNflYMjOtW5dJfW2y3fTNMUBqx0trmls3KgcJzZVrlNfBt/5WLxYJfehAvNffaUKF3Trpq5BYqKSDSxeDAMG/ANtPwpQr1Ee0XFVs8KS6KylQ6luHJCSNr9NsR1MxtSNqRKBrQrsSs92P8kguUGJg6xowb7tkXz8rttScmGYgr058fywqQvi4GH0A4dwz5hL7G2Pog8bCTtU32QkpZcR8VDkdW1mPmsz83nhv14KKxBY/7YBZGULLnp5MAvkCUG3dZgkXuM2LmYiI5jAOK4lb+jFyKSEsuvh+8TlHSZ+3Rqif55Bk4gIkrp2CnF+FLKvv4rMt1+i+PH7ibzmMg68/TI5o67ESE4KWO5yPmMmKvvdixsDNwYuTHRe4w6qorgVQpLe2KRpC/uBSbBzXpHIxtSNQXRoETDbtY/6rKYT0sJ5xteGtiflMmyMs0Qsj4NHLtQ9Eu5MhmMIwYphVyE1vRJ78lH0iHUbiXz9I9i7r+ye7nScwcVXlRCMcwlNktoon+N6h+cyEgzHJImNiYFZs1TAJtzM/TocpDuLA7/03cAvvaQid7UImgYff6wy/2sCTYNouTAMmD4dbrpJiQbr1YM+fWDSJNsXVGqqc1lqCZFsRCXtFBLFXbxMsGkYUwpMUxXemn7pp0xd3pSdsqH1hn2ENNiN4Luuhw9D//6wdSsyv4AskcxhkpCoyKaddUq46NixXA/sCIWFimg3aqRGK9ddp1jYiSeqihKnn66KQOg6K0UXcolHhnis9+9Xl+70060HGVIqv99ah1tuUYOXEI4T+cSw1WhM1k9zyxIGdV15Ry9apEojZ2WpMUEnZ+/l/wnoLkmPfruwHuyHHsTnoELaAojIy6fLu5+Q+N/3cW0PnM3xJ6//FIG1KnggBAwZk4HQgFBEVgpMr/0z5qaEBfQs673Kep8Va9AvGY1R4g6LvPra/vcfbgeFD5SzwpM8UumXX+hHY3ZyB6/wDRfyNRdxPeNoPuNzVrrOIeKEs9T1KIK4e58j9oYHiHnqdRI++4rkV96mzjNjMWNjlMNCEPisqeImTSX2x1/QDh1WhDg9Cf2049EPHCo7F2tpx1SG2PSvMmRfFnQtKbju1mJHM01QObpZkci6R14FsTFlllteB+8DoUGDRgatujqowY6kXWfnGVDBorE1/fyk9epRJi3Ri4tpNncmmllaXa10Gf+3s/B6cf88G33olbB9R9l2/vNMEWdfl0lETHlgUHcZdDl1L5fcvYyIyOr7th+TJBZUBGnqVNi8GT79VAWxtm2D4cMFumZ14iT38CIR2My7P/fckTPMryKEUDZWYVRWrAQNLz2YT3tsSsG++y5s3arsnebMUeG8Sy+19DK75JLwTtVljOdNbuJbLiCbJKymIkxTuWwNmHYr58vvaMp2zuc7MlD1zk0Ev9CP17iN97mWfamd7EOKpoksKuajG+bT6bXrSJaHqMNhOrKag9Ql3KStinjwQeWNu3Chane3biFXUfjtNxUl/vjjyud4yRIVhd6zB66+mtkT9tBDW8xiuhNqCicvT43HVqwor+Tqcin5sxAqSvnRR4rX1yps3w6//GLrnbedJlzFRyRxmBZsJZlDnHthJIsXW67y/6iAE8/eSdfT9gKglfaVoqzPtL+3dLw0Z2vAd8I0iVywhDqPPEfEyjVA1eQDVUFFEmiFycv30LxrAbe/vpsGzatflEEicAWZwRGmCQcP4vp8ovri0CE1ZRWkEIR/u31tVzwidGTGkBrTGEgO5d6kG2nFYKZSSDQSDRMdEyWJyMrROHdYCgc9qZi7DqNfej2UXqtKx5BfAKYsraoV5Hcp0Q8dJubHX0l58Em0zdsVMfbqAS2fwvkhZrmcJxeCLPPRPW34AS663FkBAd8gwoirh/h5BtqDT6Hd8ygxfy4jOrUh0a3aY6S3xPvum6BpSF2nAXtJZb/tdk1DUK9xCUu2LKdOswMIEfxFqOmS9icWsihLORTommY7YxCufKbakJL2UydSZ6tKbPMXdlS8OsI0ISsb1wPliTCaBqdedIg+d/3KFQ8u5tJ7l3LzS/M4+7KNREZXr8yvD8dkYpc/mjdXHx/efx8yMzVmzACXLvEa4MKLFzfnosqZvsIYBjKNtmyovMHt29WUZtu2/9AROENysjJm//5763e8EMHVEAIDN15e53b7nfgzUt9OvvpKRQXvvLPS4k2bKu3l6687O4ZNtORW3qARu9AwLAsFVIREddin8BdvcCs38jY7aFq6DQ1XppfreY9XGYM7SKcpgdvMsfz3lxEB04lraYeTcZ7VeQV49VUVNQ4bH34YkGFfCYahXoBjx+J97iVG3FYPj8RB/Zry1XNz4eBBVcjsm28UuW3fHi6/nCoXCDii2Fg5Q9gfm2lBT/7mEHX8pvo0pq1tzi8nqTFB73/XqvSogNDg7Ms30uXUvaz4qwFZB6KIifPQtnsm0z5qhacoImiETMfDUL5TSbEVt2maSCFIevN98j5/3TF5rU7ilhPy6o/kaDfJnYoZetNB3rrbyX6t9Y5e3JzNL0F/E4aB9u67iDlz0EplTDI+HvPaazEefJC1Hrdlu7v1NFi6SHfkHiHRyBANSJCqGtd/uQUD3aIEtSArW3LbPSbt/txJZNHdnMXv9GJeZbJCqfl/k0bIPRmIkpKyM+G/rDBNZGERMc+8idG3H1mxzVnNaQgkx7OUbBIxaiCO1vUEg+S6kuKYXM4ckkdaMw/frfCUFRDwx9rM/EqOD2LvQVz9z0bbm6GOS4CY8hO89CbecW/DgHTkxZfhbd6GHQ//l4dmDOJAqUtNcKiz8dUrqaS2PpE+g/Yw/dN4CnIjAq+bMEmsa3DJPfaE+N9Eg62LSdodZHa2AiSwhG7sMhqR+msm3bbvhJg6ZWWUNV2S1simLnU1IKSsZSJPP+Tk5JCYmEh2djYJ1cy68M2IL1yook5166pE9AM/LyZm70bmcgq7aIyOF4nARGcQU/iMK0mkgp3PihWqnm0tw9q1ik8WFgYnslFRasBfOToq6cBqttICA52T+JvbeY2hTHY2Fm7cWIW5g3S6hqGmpZ9/PgxLMMwqTSMJDDRk2fWruM2r+CSo/dQM+nAWM8Lenw89e6qcMN/hm6ZSXHz7rdKVho29e1XSmZMiDcnJfPfhIYYOrcJ+SvHbb3BWFaoQ/2NYu1Y9czt2KA2wBfrzE79wNlYDj4QEpRypzoxFRdRkH/VPwtfu2179kcho59l7v8+KZsmXJygiI8tPpI6HuhxiASfSlB3WGwCMFx9HDhkYcl/+CU9VgVUSVzBMXr6H5GhFHvNzNP4ztJkqelAFuPDQkdUs5XjbfHV0HeHXUUtdR7ZujfePP1jrcQdt+56dggG94hxHZN2UMJyveITHOYvf2UkTm6UV+XLhQSIwcNGdRUxmKI3ZhQcX3zGEPzkVgeQM/Q8GjqqL+90PbBPIConivnMW8/6sdhQWqWOKIZ+G7GIj1QsGDRxawnNvFiEEZYQJCEpgK1XD8nrRn3wS7bn/Y++8w6Ooujj8zsxuKikk9N470qUrRQSpoiIqqKjYe+/dz16wd0HsFQtFQMVKFQHpRemhhJBed2fu98fNJrubLbObDQSY93nyJNmdcmfLzG/OPed3nvQ5fqEAqoZz8WJEt26s+C+fyaMS2L1DRddNOhEoBjabYNzV69mzJZm1f9ajINdOXIKD+l13MPU2OzWSDTILHaa7dvmyBoPId+wCsP3veWpu2oYaIIflZwZzHa+wkfKCxQa18rntSchrtJuasXbmLtpAp/qhnR+LC/N56aZRQc+tx30kFuTM61lnySCqzSZFhmFAmzaCezLe4AaeJZ/SbiluL8lcRjGa2fzKqZTVVCYkQKvQemUfKdq3l/VJV14pRZWLlBRprbp5sz8hqbCBjri+fL8zkN84lVNYxCzOIoWswDvevVsWHvlwhtc06Vx1zTUyR3nt2uDOV+EIWLmehu4nOiJQmcEl3MlTtGMzDmx8yzjmMIqfGBpS5NebBx6QHvxz5shcy65d4fTTKyGWXnjBvOLPzGTNaoHNpoTVmEzT5GelWorYbdvg0ktl6koQdtMooIAFaS07Y4bcpEV4DB1UiD16CRmrurNtjTSKslPCuXzK6SzkFa7DQGUAfzCG77F5FRkKmw1l0xYEgUVsZQVsZYhPNOg9IpclcxN8RjxVTdCsQxFZ6TYO73d3ApHnnqbs4DvGUEAcsRTiWY9fnpykeEUaFF2HrVvRnngCbnvAZ1OGBo0FT71ayO1Xx5ZO/wQWsg6i+EQ5n+/EWLRAaXJyBAAe7iZr6MKp/MqHTOYcvmQfDbAjUx9e1G+i2RvbmcfvtGOzzy060RilzOXX+e0w3G56CohnK22CjEeQUktw+JCKqgq3Yjb5Ct5wg8EldxRgCNAU1adwdVGh3bAQaFOmoH7+uX9nVyGFrPrCC+gzZ/Lp9Gh2bVf9FNWVreW1HxXdKfjt6xZcfN9KThm/HSHk7N26fTnUSA7eAORoohWXoAQRsMNYUOHamXYojlumKky4O4FTRpjJCw6f4zYn1sWOHbIGyVWs7nSW64MtWxSmlLxNDok+k8t1bPzBQBYyrPzBAQOkyWY1pUsXOT28bp2MBP74o6y+3rgxWBtedwsR+bH4jcHU4wBfc1bwHefmwltvSUX3yiuyesiNRo2kS9kff0DfvmEcmGn8n2BsOPiY89lOM9qzkQl8yYdMZjeNwxawdruMfrduDTfdJP1IR4wIU8AuXiyrrZ55xrSIPVy7LctXhCdgXdiq463snj3yg7J4sanFZVFg8Bf9o48qOa4TlKICjVW/NGDRFy04vDOVBgOX8L9ZO/h0/P9YSm+W04eL+YAXuZGXuZ6zmEVztrMar06HQkBU4O4ZR1PAujjr2kM0ay8vvmUpRooARZBS18GhNDtZ6d5fHOmIasNJV9ZQg3ziKOBS3mErrSos6QtF11HfeYf2SVJIVhBfwIhxTq59bQeN2rn8WgNPpupCI1dNoCAuuSxv1CxO7GynGcNYyMHSFtYOosq6U+2mEYP4hUySfa7/BRNYJAZ7CNhygkeSe/Vz8sI7BXTtpWO3C6JjBGPGCn5epPPMswYd6pS36vWFq31v+9rxHtFN5Zdf0AII2LLlnDrqt98C8NWH0WGVwwihkL6nBgd315DbDC/Ab4rKOBS41lUzs4n5cxkxvy8lqlEDvwMWwNW8Vnrt9Jl0wqzn6qNXcdf36nj5iijTpkm7U7MCzhspfC5guCu/af586NZNFtTUri3LnS+/vNq19+nYsbwC/s8/w3cGc2DnXD5jMf04mRUVF1AUWTTVtat0z7fZ5It9881S0T3ySNmXQFHk9Pq558KSJcF12l13SXezjIzwxu6NE41HeYBHub/sHQ/mqRoITZN2bhGxofrpJ6l+Q3ij1nASQ3P/5PC88Her69WwgAtkAWVWVuAvrlsycjzm8q0OH47A2E4w/vmjHj9+0grdqaJqMiK2dVE7dv9SyEuZ6xjDbA64CRwX+6jPEH5mPR2pj/QXVXQd3dXO0weRFLCu7lzBUgrcUwlcRMcJbngxjZU/JfDn9wlkHrCTkOKkzxm5ZOyzseiLZD95qQqbKc/3LSaGGVzCB1zI89zCNbyOGiRzXcnNhQMHaN+4sd8in6vOTKVu8138+2dN5k6vSfqewKaowlAoLgi/82QBcfi6TurYOUgdZjCFm5kGSAuvmVzEck7mJ4agoAe0o/KHqkFyCpw2yslpo6QS8jXV7nqf3SPX7qK2wtS8EKgvvYTwSufwS3ExCEH6gfD8al0cPhBL3SZVkxcKskgy3PazcalxUFhEynszsf2yBMUIfh1aRTe2EMCvGwVnicLi2YlQhfLouI/EfvSRudRCfzixcRi3JveGIUOKBw/Klp933ikFnCvUWw2pXJGOgoLgWW73/bQQ0q2gqEj+7XDI18jphMcek7kEXgwbFlzAJifDQw/Je4W5c2XztOefr8xxyGORP2pYKQuua6Hrd+/enm18K5CXJ1uSDR8OAwfKllFebWIB+WJceqn8beakChQTxRnMI6soJuwbFE2TsxRdugRf9ohiGHLeP9AXV9M8bB46sxYzLhLVNBOo2rJlVSrzP2iL7pSddwxdLU0WlL3gx+z9hDQaoPu4GdSxkUMib3AVUFpDnlAD2rb0ua/qEIF1x2aH3iNyueXVNB79cid3vLWXU8bnsHy+7zQDfwhUnNi5gVfoFrWefWoAS0AXcXEoK1bQ8dP3SH73DaK2+igyBlr2z+T+D3cz/pqKxXS+aNdL5kwqqvt3Jdj3JlDXJbn2Z5wLwBxG0og93MwLfMZEDlAvLAELssL/9NHlKRCBckVdj7sir67HPJYXAnXGDOzt26PNmWNKwApFwWjXnve/KUGtZPd5M9X4wfJhI43LDzi2eRvin3zDp4AVXr9d7MHE5xj46VsRcj5sKBz3kdhgLdaDYcNJC7xarrmrBpex/gUXyL6V1ZD27WWDo82bw4vIOrHzDePC64H9+OOyPL9GDY/xDB8uUx18nUcURQZyo0tnHV1G9EJIh6UFC8J1OQv9LlrT5NDvv1+mZ7hqrqZOlRFlv11hNm2CIUNkrrBr8EuXwssvw9NPywYNLhYtkkVLIfAl57APc5XbPXtKb1SbTepCV05yx47w2Wch7fbIUFAgO7EFo06dsj/v4ClTm77wwnAHdeIhBPz5XbPy5MAw0LHxCefzMA/JCcbcPNSb7oPsbJS8fETbVhjnnw09QruTEtnSRN6M4HWJmkAR2cxCKZa8I7IV9isgLyucy6Z8/dY52nCGmMMqulXIlYXS4q7u3bGNGoX6998IVaWhEChCkDNoCLtefgtqyWMe36UBs9akkVXkIK6uuVawA8/MpveIXBZ9kcSuTTEoiiA6zqC4QEWE+R6Dyt/0IIlMckksPSrVpPNAWYawx6OKKjipm06vfvIC4Z0uILLTK7z3roisPxGoPfgg2pNPlvm9msEhNCYpn/HlxBomGmH4xxZTQm7iLtbtq3jhcn32zOD63Psi1Cisu82d8tOvqMv/9rmcTAwAERuDUlie35qCuWkt3VG1MvO4F7EtWoQv3kAKuKm8E2Qhpyw+Wbu2WroWKAo88QSVqmB3EIWODZuih/ZiFhTAvHnSU9aNjz6SxU9//y2Foq6Xi6zzz4d77/V9HF9/LW273n8/lAh76PLbNZZatWQkuHt32eLXFCUl8uAOHvR8rVwDvuMOadE2dqz8P1D3KT8sYjA2HEHTITZskDcwS5fKlOVt22Sh3wUXyM+DmdaMR5y4OPlTEKDSVlGgfXv+WW3w+76WvM7VBHuPo6JkcaGFObLSYziUViP4gkFe91w3r1IA5adfpY2RALb+h+3beRgXTYT7bgXFs9+cS6j4unhrWWkVetP5EjYuvKfmXaLWVRA0a02ah6DwJWgVBeITdfJzwgvLCaHyD12Yp45ilDHb8zkAXUfZvAnySyOmbuIt4fdfaXHeeLbN/hFR+sV1jb2gNcx6WlCQ7/+9sMcY1O2YQ1SMoGX/TOlwoMC6XxP58qnwrcxAuOXJhn6u1ewC3SEL5hRFQXcqdOul8+J7hRjCKNO57WvHe3wORNZBlOV/oc6eg+IUiA4daD9pElBRxCrr1qE9+aT8O4Tr10M8xFfrZXpIIJGvKCLg82MuzWHI6f6n3gMVpblwHbs/ZwIgJHeCgoyCMiGrfD0naHqFUaMGBcOHEP/NXBSgB38R/P0W1KiTa3pM4XDci9irr5YFN6Ej35ybeIHOrAu+uKLI5NNqKGIBzjxTCr9rr5Wz3K7UVTPfZwWDVmyT5t3h3AxkZVV4KDVVCqtvvpGNKA4elFO9U6dKL09/N8uxsdLr93//k+tedZWZAYR2Uk1OllHWU0+Fs88ujwibZtYs6dgQiIsukm4OTqfcYYgYJtMhGjeWr2XfvlVdUBdBVFV2KXvzTb93KtucTbnox0dYss/81FtJicyJdQvgWgSgpKjylwcNJx0oN80v+ya6aqVKL5rqzM8QbVshzj3T4yLtfkn1dfH2fszXJdglbL0FrXt0T1M9q9u9Ba07XU/PYvHXKSGlFLhjw8HX0RMZVTgboWlgGB7CSsnxfdFXdJ249Wvp8McCjIkTPY4hOgamXF3Ea8/G4Pt8J7j8uhIm9q5f4ZlxnWHfcgeLf7GFGY1V/PwdGE0TNGpmMGNWPr/Mt7N1k0pUtGDICAedu+vyPrX0PRPZ6YhsKdC0rDTIzkG9+jbUFasQttLCIl1Hu+su9DfewJg82WNf6vTp5nNgSykglle4PmjqmaIIho9z0LiJwXuvyuIvRQOhS8/lERdlMvjc7KD781ecBpEXsN4oBw8FfG0UQM3NRWvdpOwdvp5XzGyZRl2DXAsryXEvYq+4Aj79VNoIBZqCVjBQEGVV6vXZx508xQ2YdOoXIrIGlFXARRdJUfbVV7LxVkqKFI7nny87eQa6q7qel8PfsZ9ERLtdBmi9grSmqFtXWol99RX8/LPpVNKguKLW5sSxHxYsKA/l+iM72/Wim/rcuDwa5zMcJzYc2AK2P1QU6NDBI4vj2OL222W4Pienwhd3H/XoH72SjPWh545Vs2Z71ZrE1CIU1UAY4Z/XdGxcw2tBlxMAr70LE8Z53MH6umiD59Spe+OECqI2uUGFKK6SVDskQevNwPsVJvwmyMwggF+ofwQKJUVgtG+Psm9f2XnAzJaEqqK8Px0xYgjtosqPB+C5x8DmMHj5JRVVLU8bMgw4/9ISpt5YhO7j86+oMO29fN6aFsOnM6LIza7K65gorcdU6N7byROvFlAzVTD+AtmWVL4v5VFu9/dOy0qT77sQxN7xOMqG0i5STjev3ZIStMsuw0iKQ5wysHy369eFJGABVtCLXILlcgpuuLuYqddL27FJlzuYN8vOn+vyqVtX0GNoHgk1/e/X3R8WfBShUbUCVq63kfgGdWHtBr+vkQBEak2cvbqQb09ks6MF73EpwaKwcYk6yY0yIejrGD7HvYiNiYGFC+HBB2XnKIePm2sVJ8lk8QuDKCCeaIrpxLoKHodBGTw4MoOuQuLjpZh1Z+dOKdo+/VRB9nxyncQMFGAYC7iKN9hBU3JJoAm7KjaA8IWqygTSKmyT9OijMqXUl/esoshI5N69wUWu67o5ZoyMBlcKpzO0lIsgymorrTidBeyguZsRuXyP/FX+CuGzidqxwaxZMnfDRwQf4AVuJqM4PtRvJw0aWFHYUIiNd9KuRzqbVtY2KWTdb4IFCoJz+ILxzAq6pgJoe/eTt3wJIlVWonp39XIXrq6LdlxqXIVcwFBErRlB602tOoKZ3+Vz342x/L2s/BLq6WXqH4FCJ7EWdePGkCffFcNA3b+v7Ljcj0cBnr4Prr5Q4+MvYtm3X6NeXZ0LJhTSopkeNH/4lWfgucd01q/TGTDAZkKghzZ6VRWccorgzPGCUwYadOwE4GkJ5S9txP09dixdR8I63760rvxN2933ISadjbLvACIxEUU45Q1ACHexuomCNEWBGgmi7DOTWktl8uUlTMbOrDVpJATJsQ5GIAHrIhINDsTZY1Dn/uh/AUVhc/+JPP7ROXyuT8WBjeDTsgoFOTZZDFqFHPciFqRwe/bZ8iniIi/vXQMbfVlCBzai+bI/sdlg9Gj47jvfgkPTZKVS69ZVcwBVTFKStCI79NcOftrWpOyjaUNnAl8wgc85meWsphsgzc0v4GOe4O4y65wKaJpUlu++W6UR6t69ZcrtxRdLJwP3/Nprr5Vpp6edFnw7rVrJ+rMrr4yAb2rv3jJHIlxUFV21873zDN7icn5kGM7SE6pnDqyOQEXTRNkFx3X8l18uZ+SPOb74Qn5RAxRfvMelPn2dg3HHHdV+sqTacerZ/7F7SzJ5OXbw6fUpUdBJJpvMUieXRuzhRl7kZl4oK2AyI3kKMwowiPYpTn1drL0f87UelAtbj1SFEAWtOw0aw3tf5/HvFpVNazXsUdLTdMbr0bz/ekyAozXQ0LmE6T63GwyhqjhTEikqO8aNFcR+qyR4wPtGPMt3qoU3UUC3VjB+TDKzvo8NKGRd5xrTYxfw8is6revK11z4mGH3Fmu+blyU7+YhFMVvbqsiBMqWbYgHnwJVle+CYQSJGcp3q5goVtCLEqJowF7slHjYxlU8JoVO3fzPuGUWOvwWC7qnq/gqXIPA4jWSHboK6iURP6g/yq+LK7yuQlVYV2cgA+c9Q16BDb3sRs3cDYwIY7YiFE4IEQsyODZhgu9ILMjuXNO4iVvx4eOkaTIn4ayzZJWPmz8lAJ06wcyZVTPwI0B6OvTpA3t2N0W4fTB1ND7hAj7hAlS3U6CDKD5iEj8zhOWcTD0OVNzowIHSmcCViGkYssKuuFgqxgjOc592mizunz9f7iIxUUZUXVG3d9+Vog7kSdcVtW3SRLYibt5cRuwjxuTJ0nqtoCCs+ev8ex9n1Mxz+XVn8yAFAxqaJujYUSEvT7Yb7tpVdkcbNapqTbWrBIcDrrtO/u3nAiWADEI35h03rnzTFuZJqFnChff8zW/fNGP90no+XQo0HDRiL3/RgyJiMVBpxJ7SFtD+6s89EYCRkoxRUxpKukda3f8Phi9RC/KC7y323KOZvvBX5e5eAd++Nowuay0dRb8X4YbLHYwba2PPHs8j13BioPIOU6lDutsz5lEMg7y+vSlxK8rxdWy+CCSIvLlnaiaz57VHCCpEl1VV0K97Ln/8FWiKuFzEa6pANxSeeTSH1nXzTY/F31S56nAGFLEuXOLVfUT4WE8oCkLAE9zFM9xGVumNmA0HjdnFLpr6vGnWNEG7zjrtO+tlzgihEiyV4EhQsD+bpL9Xouw/CJqKcOpu8ymgGIIrDj9PnlNzE7BmENSs60SLilCunx9OGBE7Z05gFyOBwvPczE1M84zGahr06CGVnksBu38JVFW2bPKnjo8B/vc/WYfkfdddntAuKnS0cmJnH/V5gEd4S71anizuv18K/dq1oWGph5wQshLr8cdl+zSQ1VmXXCIfi1CTCE2Tlee+qs8vuUQK3XfegdWrpWAdMwbOOSfC4tVFYqJM1h07ttw3NwRu2HItv5d2dwlWaKHrCrt3Hycm/gsXVuj05o0C1GMf+6lYoOKNqkKzZrKJ3IUXWlHYcKmRXMLIKVsYMHY7nzzbjZwMz+KhKEp4nauo5cNyx7VU3rgziPv1T5ScPL9TugXDh4Cq+uw6FJcaZ1rIuq8fTNwF8qb1J0o0VQ0oWLS68OlCmNZ3Kd9nnUoxssNjN1byFHfRjyXM5EK+Zjx5JNCZtVzBW7RnU8CxCgWKe3XHdmoPbKV3qGbEazh0blvIvBlbuPDmFuzZH4WmibLT2HmjD/P6Yzs49bx2rNschzNIpG3gybncdvl+hp+SQ7AO5u74M+8vSqkZUlqACwUQpdduoWnSCcMp+D1xNE9wFwuze+P+uXZiZydNsSkGhms2ofR8rKqyJe4zbxQG/DwEsmyrGStTDlxC1v3mSEmqHdBOK2IUFVPzyRexb5M2ot7vpAKsoyNLS3qEtfmhE7MIYJgREU4YEfvHH7KQyL/WVEijEevpwEnubgS6Lrty9esn56u9MQzZVmr2bFi+XPZXPYZwOGSkMpyOZk7sfMCFvHDSTOLvu1lWjXnzwAOy6YE7hYXw+uvw4Ydw3nkyTNqzZ9jHYIbGjeHhh6t0F560bSuF/H//+V1EAL8wiNmMpoQourGKIfU2MPOr+JB0r3d6zDHL3r2mFruct3mcewKmFCxbJu8tLSKDEPDDzHbkHq5Y/V5CNBP4kr/pThu2+lxfGTGQwqF9iLv3GUR+QZkIEaqCYgic/XvCpDHEafJm2bc4C1zEEop4Bf8C1l2Q+POWDeQ5m3FI4fJz49iaNaJsBsuGg7/ozRtcxVTeZTstUNEx0PiVU5nGzTzBXdzlx+9YxMVSMm4YjknjQVGqTLy6M6BnHtt++YcFvyexfksssbE6owZn06yRLGL6+o1tnDa5Lf/tii4r1rJpAqeucOm5h5h2/y7sNhHxttZRkycgFi+XdmShrqwoOK+/HiUxkRf/7MTjf40lI9t/G3mjtAqh/2AnaXtU9u9VqZkiGDexhIkXO0ipJcWt9+dh1hrzUW/X+r5SV/TkBgGj1qHc3Pki4fNvsP+7PeDruJFQP2vyNWnXq4AB43KY/3vYwzPFCSNizU6t3sDL/MLg8jnnqVNlmDItLbDSO3hQJlV+9VVkBnyEOHxYWm6FSxGx7P/yD1r6asKzZUtFAetCCFl5/s470sD0ggtklyZ75RLhqwWFhfKmZ7+ffGFkhf0oZrOKHthwoCBwYCcuw4nTGUqxhMxmOS6oW9fUYjfyIjOYwl4aVpghUBT5UerVqyoGeOKyZ2sSOzem+HxOx0Yx0TzN7bzDFRWeF6pKdM+TIaEGRm4J6pvvI/buk+eAxAT0sSNQ7riB2OjApsWuyJx7ikGowhXMRV+DtaoNxG1XxvLfFrm+4ZXL/gXnlrWd9X7ubp6kNVs5m68Rqoro0RXjhsshyg4d2qLFxFAmt/ILUL7/AeXvf0BVEX17IkYMDcMPMDCaBmcMyuaMQRUTWBvXd7Bq9gY++T6Fz2ankJWt0aZFEVecl87Ak/OqLJ1JxMeRe+XFJL4+XaYVhHLHr2kciornefvdPLOoYsTf5/6Ewub1Gte/X941zYyva7DGGcEIFo2tTJtZAKWwiNhf/gialhFPKGkSguQUQe+z0jnj/Dy0I6AwTxgRO3gwPPNM8OV+ZRBr1S507hUjRel557Gu7lBe0N/gO8ZRQhQ9WMkNvMQ4vi2/g9F1aVy6bx/UDz7VWV1ISPBd2R8Kif5So955J/jGXc998oksHzfzJlVn0tLglFN8R+1LcaJxGgvZQtvS/8tPdgUhdjcxDNn84bjg0KGK+eZeGCg8yV3soWFpukt57l1UlDQ1eOSRYzAfuJqzcUUdVNXA8ONS4JqVeZsrPKI6QlURwwdDTDTqJdejLllR9o4JQMnKRpv5GWL2fPTXng3aucslVN3FbChRyWDR11DFq3fEbd+/0fy1OFCuqFLhxsuFis5T3MlZMXMQ556Jcft1vvOdlv+NdtWtkJsnVSagfvU94skX0V97Brp2PmJfgLhYg8vOPcRl55prexspivqdjJKbR/w3c9FyzUdhFKeTjPrtefEe/9FXX6QfUBECUuLsZBY6yt53X2J21pq0SgvYsvEm1UYntHxms9j2pqGUBE+DHMQvJJJNDv5T/2JiBbP/zKVWHfmRnLUmE812ZAJSJ4yIHT5cFvIE6+6paTD70dV0vlv+/+23cE76fKBcbPzGKSxiCFfzKq9yXflJ2zDg11/lFPkxQlyczA+dPTs8r9X27WUKrE9WrzavjoWAV16B++6LWJ5sRCkpkYnV27bJ5gRnnin/fukl+OUXedEYOlR2btu5M+CmvmcMG/AXPjV38XFdo845ByZNMnsQ1ZjHHpM51UG4n0d5ltvw9TqVlEhv3EhPX1pAUX5wI/wSYpjPcEYgz5dC0yA+DuPW61CfmIaybCVQ/s55bO1wFtol16F/+yE0bwp4Flx5X8TDmU4PV8AGmhr2Fisr/0lEUUVYjRAMNFZwMulL15LUsGKRj5aVBrv3ol12A5SUyNfP/aR96DC2cy9DxMdJEXz5hVA79CLI6oavKfOY35eS8OEXAcV6ITG8w1Te4Cq205xkMplk/5R164ZQUhzaGGJr6KTEyffa9Z67xKx3k4xQ8ZcX646/tAL5PQjPpUAo5m7Y4ijkTp7iXh73tyUuvrqYukcpdnfCnO5VVWokV6fPQMu5cgwPHoSJE2WVvnvXDlcu3utcyyn8znm4NaC/9FJZ7t67d6QPocp44AFpUyUrUUNbt53/TnqmcxzLKCqSgnDcOPm/rsNnn8Grr8LGjdIrbfhwOOMM6NIFMjJkpwPDgP79/bf6WrlS9qvNz4d69eDAAfj+eznt37279OIaPtz/CfG77+Cyy2SksLTDDlddJX+7NzX4+GNTL+BXnI2GMyybKBctW8pOdFdddRwULP33nykBu6lmX57IvJtAQv+++2Q6wTH/mlQzklKLZJ/YgEJWcAnT2U1jNMVA9DsZ4/5b0Zu0RvviOw4byfxHC2qQRzs2VejzJIpLUN/9COOxe8ofP1IFLiHiL9JmGKWTCZXYtiMmAbysHl0CRv3oC3A4UIyKeyi7OcgvgPc/Rf1uLgXPP4CoU+uI5NBGimDWavYt/5L41vsghN+p8DziGcLP/IWstRCoFBLH886bUT8SKCoIk9c6VRX0HuHZRc1fN7fxXRqUdXszG40N5FBgptFBuDibNMSIi0UtKAy67Nl8yVecxd/IAi9VlZ9zVyONK28uApNdJCPNCSNiAYYMkYXxhQHeM4dDit30dLmswyH8tp1TcTKNmzxFbEmJVMq7d1fTxvQV6d5dOodNmiT1ndmWtJoGTZsGWCAzM/TBuO4gXJ5o33xTnpKQmSmr0N59t3x5V2sap1OG4WbNgjZt5HM5OXIbrg5aru26c/CgDENfc418472F7E8/wfjx5S+GK/Lh+t99eybvAPJIKGtWEA59+8oOx8fNlLn7++mHIqIZovwctAXkzp3ynsXKiY0snfvvZ/mCJkGWUthPfd65YymXXCDKHEr2fbaYux3v8yXnlM1mtWEzD/Ogx7lTMQz4/gdwE7GRRMtKK/OGdY/GuuyRdMPwGY31N2Xsi9SW+Rh6apgjFDRoACk1Db/Tx8rcH1F8td3yXs4wIDMH+3PvUvLUnWWCJ5iYDWTXVVnRFGjffoVrcQlqbi4iLg4RF0v0spUkvfKOFLB+tiWAO3mSv+le4XxhCBWjxPwthqYJ4hMEPcYdIrPQ89rhLy/WXciC/xueyvjEVrrVbImDxLdnohQUBvVv/oxzmcyHpUvJJYUQCAG3PVzIpMtKKpVDXllOKBEbHy8Daq+/Hnjq/PBhaTgQTMgZ2FhBL88Pga5LYTRrlgzjHiMMHSp195w5sH69FPCvvw7//uv/NdD1II0EwhHxXbvK388/L3M5IHhOrev5zZtlPuratVCrlnRLWLRIPuevBazr8ddek9Fz73Zm994rf4fSgSsIHVjPbHWMzxaQwVAUWf903AhYkGknfthFY1bTlV85lX2Hzfmhubr5WkSOlHqFdOi9nw3L6gVcTtMEG9SO0FDewO4vqM2AB0ZxAJtH7vdWWnM+n3KIWlzHq+UbKCiEVf9At5Oq5DjMCFkInhvrT8CIk+CXt3V271DDaknbp2ch9pwAU9JZ5j/cimEQ9c96cjbtwqhdy6MRRGyr9hSuXYVSXIJIiC/LrXW1IfVHUNEkBJQ45PZs5bm//ppQAFBYhH3REsTKdYCCo30b1DYtqTF7ATFLlqM4dYSikNugHglp+wMKWIA8avAelwWY6TLTiUwu17y1wbNvFNKybeBWf96fG9fnw13M+sI7Cmu2yQEEfi/2L1lR9ne9vhXv6JNefovoVWt9vhLuemYTbbmAjzFQcX/dZGqR4LmHYxkwyKBF66PXz/uEErEgU+9++w3WrQusjQK1vXdH89UHxW6HJUuOKRELcthnnil/AFJSAnd9ioqCAQPK/3c6ZTZAerq0tOo/8BSUPR+bS7bVNNkgoW1bufyLL4YuHHVd7vzNN2HYMPgxQBs9X1x1Fbz8skxLuPpqGb1dtiy0bZhgas81PLkyPBUqhMyDPa5ISKjwUBr1uZI3mcMoD79iMznDe/bIz/D69TK9+rzz5M1rzZoRHfUJx8nDdwcVsboOUVGCTSVxtK8dz6N3qxzIjsHp9b653tNbeJ7z+JRaZJQ9p11wBcY7L8Ko8ZE/CMqFrDeuqdxAUdlgKApMe7eQKePjyMl2bxQQ/LOrKNCmle9zZeG2jaAb1DBRiOOxTcC2J42S2rXKRE/Cvt1w39PUWLkOBTDiYilp35biLh2wN2qI2LVH+oYqKiWd2lF0cnefrjG2XXuIXfQH2r4DiLhYREw09o1bsKVnIICSTu3JHzMcR8d2fgWXfcs2kp99FaWgsCwHKGbxchJKXxBXuoAiBAl795UdUyA20p4iQivc8qZLLye33FdEt14iYMDAO4LqT8wGQjcMjzSCykRf3cVrrr0BCY40j8cAGtWrS8yqtQHHJADHe69wzkMXYOzy135XQUHwyfQo7n386Pk8nnAiNilJTsVOmyYjjQGKyIOiojOMhb6/VMdBdcnAgYGfdzql5rvvPtmw7I47ZDqCixYN3+J1fT+nszDwhjRNVoe99578f9++8N8Yw5AtX7OzPfNVzVBYCH/9BatWyQ/II4+EN4YgNH35Nu76TuGJJyqaNyhKeZTV+ybLZpPpG8ediL3kEpn7XEoGKfRjMXvLHAhcBBew9erJzbm/9atWwXPPyRustm0jO/QTiVr1C0iqVUj2oYpese4890gc876J4ubr4YMP1IBm+DoaHzKZm3gRSrcqdAP1zodhRJAChkqgZaWh49tmK9SorDct2xp8vSifT96L4rsv7eTlKNStb/DfVn9ioJz6CbJhhK/pdSU7h4Qwqm8Pb/2PGqWR7ejlK4l9+R0pEEufVwsKiVm5mpiVq4HSOKQqp45jf19CjU+/JvOOG9Aby/SQ/YuXU3/JClJXrS3rnOXuOEHp31HrNxG1biN7Bg8k6rKK1adqRibJT72M4ipS8+qu5Z3vava2X1OFd0pxSKganNRNp0tPHcO95RwV/Vx9FWGFchPkvi1/ud++Wu964y1eff0NkOBIQ//yu4C3VK738an3mrB+V3Kg4aPrCot/Cf65rkqqJJFhx44dXHbZZTRv3pzY2FhatmzJgw8+SElJSVXsLmRq1JDCa88es1rTd0TQQGMEP1R8wuGA00+v1BirA++9VzbL5BPDkLPw06fDxRd7CliA7WkxjFR+4EeGer7Q7re2SUmyzdbUqbJIKyOD3EIbt/E0DdiLhpNUDnEzz7Mbk40ksrKk+W24c+66Ln/uvz+iFUIGCtNi7qLZOT154gn5mPvm69SBhx6SrXCTk+Vjdnv5S9eunXyJImwFefQZNqz8gIFp3MQeGnlMP5tBUcqteb1TldPTYfToylnJnegoKvQbvRP/l7/yS+OmdRqXX26jpDjwd1BD5z9aeO5HCJQD6aiLfq38oIPgTzi0rx1f9qMbhk8j+kDUriu49s5C5q/I4c/N2Xz9Sy7deztQFP+zS6oqmHBGZgXRUiZcgvjo+sIZFc2BJl3Zv2QFSmERiW+WFkQFOB4F2WrUtYyalUPSI89w8Jc/2b9kBXGbD1CnNJJXFil1W7dsO6XPNfrlDw79+Av7l6zw+DFmfioFrI8Zt3CzpQTQ2VhDrYRKRAYFdGtv9/gMuMSq63Pg/pg33ssGI1AU1j366kvAul7LXHuDsp9A5NobQKH/dIxDpPI14/mIC3hm6RDMvBMRzLQLiyoJF27atAnDMHjzzTdp1aoV69at4/LLLyc/P59nn322KnYZNuZ0ju+FVHR+4xSu55XyB202aN06SLLoscHWrcE/oPv2wc03+35OCDAUlZubf8s/XS5E+fWXciuqG2+USbjXXiudAubOBcPg0yt+Zooyg2JuL9vOYVJ5met5n4v5jVPoxHr/A1JVaNVKKr5wPMPc2K00YXetbtRK30gbw7MlZAl2MkglkRziKT+5FBNFFCUVPjECuIx3mVE0BfaWP+sSW6NGyTRq16zdvHlypmDXLml2MXGifNmOy6r74mKP9+odpobl3JCQIGv5fKHr0hFt/nxpbmERHp36HqAg185vs1qU3tsLhHB9KMs/14ZJiymBQk0qFoAKVUVJOyhlcalXJkTeL9NXJNadQO1lg+GKxLnEzHV3FXHpWTXwl1pQs6Ygqm5dYlPL78B27N/Nmm0pRNkM+nU+gLNLB7R/NgY1qKd0L+ldOxIv0qnXtxcxP/2GUlzx3BQMRQhshUWkbN7Koc4daLL8V5OJPeWtXtt8/i2OGvEY/XtTOHgARkpNUmfNMXUcIY0V0O68hhvtJTzwv2g/tnDu8eKKaBqcd17l7nZd0fxAeEdhfQlYM4VbwYSrN0XJKRXev0JiuJEXmc4l5cEDE5OYqio4ub/Oovk2Pp9pZ/tWjcQkQZO+KQwZl09cQtVHDapExI4YMYIRI0aU/d+iRQs2b97M66+/Xq1ErEtPLVwYSO/4/6oaaPzMkPKNCSHbzs6de1yojaSk4L0KbLbAhTRCwLrt8fSu9TXbkLYm/fLh9j+XM+iuCzyq/j9kEheKD3xuR8dGDolM5DPW0cn/u+Kyvxo1SuY3hBH9/4fO3Mpz/KgPg9LochdW8zR3cBL/8Cj3M51LKCQOFZ0RzKUh+/iWcRykLrEUcgEfcSdPEU0xbyjX8Lk4m39p7Xefc+ZILd+9u7SIWrKk/DlFkcHlk0+unha6lWbJEsiVFjYCOIC5zl0uFEW+NsHSl+12mVJgidjKcfLpe+jQ+yDrl9Rl7eK6ZB6II3B0Fr/PO7FzHp9WfMIwPLqouKy2grXhNIuvnFhvItG9y3396Cg1oEVZxmGVN96L57YbGrAnTeXaW5JZ8HOPMiEWEyO4alA7nlzT2++NMgCqimIYFA49BfXi86inqsSlxhGdkS4VWpg397UOHSa6RVOiQ2gu4MJeUIi9oBDx7VziZy8g69ZrZAFYFeA8fxLXNYtl/b+CTz9R0DSBriuoqsAwFFq1NUg/qJCXg1fxnZR2N99fSGpq+SyQdxti3TD8+rn6WicQ/rZRWSeIQOzv3I3Gy8t7wRoojOVbfmao30Yc/jAE7N2tcMOUuLLXOW2PYNP62iydlcKNL4ZosxkGR0xpZWdnk5Liu22hi+LiYnJycjx+qprbbqtcwO4wKVyYMps1fa6UHarWr4dmzSI2vqPJuecGTim12aBbN3PR7BUrpENWVhbMnSsYfOfJ3CmeKDvx5hHPlbxR+p/vDerY2EBH/mCAz+dRFOjYUYYwO3YM0IXBP//QmX4sZhGDPR5fS2eG8wMdWcdbXEEhsluQgcZcRvM2l3OwVHwVEst05VLasJmm7OQJcWdAAQvy2vLii7JQboVnHj5CSKexM84ILcX3mMHN804BUt2KfHxTHr2pUUPOBMyYYW5XR3vqq7JUl1StGkkl9B6xG5s9WEwusK9sMpm0Y1PFp+x2jFGjPLdUGjU1I0ADEajtrItICVh3vv7Yjqb5/wAKA15/P57DztoMHl2XH3/1jCQWFSm8OL8Lk7qtQ9ijEIqCsNkQrnyjWqk4+/XAMX44BfffgHJyZxK2byMuXgqTNba+TNZnUp806pPG+XzMEvqYGrsCKMUl4Az9YumRYmAIcDpJfv41nI3qIyL4+gpFYUWzszj3gR6kptj49BOVuHiDFm0MuvRwMniEk+ffLuDzhfl8Mi+fgUOdHukdDZsIHn+pkAsuK2Fjen7Zj6aqZT9Q/pkIJlTD/exU2j4rCCUJSeTXLf/sz2c4P3J6yAIWoGcfJ8t+l58/1w2BEApCKORmarx1b33OGNSBdfuqTssdkeqjbdu28fLLLweNwj7xxBM8/PDDR2JIZQwdKmt4brop9DogicKnh0/n0xUjmXWPwmhz7ZiPCYYOhX79ZITLW+irqny9LrigougKjvywP82dnMxyzuZrPudcCggU0SndLzp/0ZOTWc5B6lCDPGqSJaM2ycnyJqISfXRv4CWKiKkwnS2/4ILDpPoYY8UxGyK0E5iuS6epvDzfQ9d1GbD8/ntpW3tMoeuwfLkM2bduLTs1uNOpk0e72UuYzvPcEtAi5+23Zb+LDh2kdZ6uS1vSQP01HA4YNCgiR3TUqG6pWja7TvDKe/8lJFnU5A8GMJA/yh4VikL6pVewT8Ti7SwaqYhspARsKB2aVm1ohK4HymtVOJCm8tBTDvbutflMyRBC4atVrflo5nbOP/gJysaNEBeHftogRN/eKFu2Yr/ueqK+mle2TnZsHS5s+BPfb5uM+3vxBRP4lPN5gZvKCuv8ITQV2rVAr1MLIyYGtSj8nFNFCAyHk8KU+tiMjSGJkEBx/QViGGN2f46xWyl77QryVf7dImjSzODVDwpIKnUoadxUcN+TRYw9VyMvB9p1Mmjb0SidQA3+vnsXeLlTmRQUF1UlYAESivcQnZNX9q2dzhQ0HOgh1SAIGjcz2LZZ89vJz9AV9u+IYusqc9aI4RLSlfauu+5CUZSAP5s2ed5V7927lxEjRjBhwgQuv/zygNu/++67yc7OLvvZvXt36EcUBjfeKK1Fr7gCUsPwqXZiR3cKJk4UnlPrxcUyteDDD6UCOcbCQKoq+wAMKc2Y0LTynM3UVJm3edVVHjU5ISJ4htsA2EYr33ZlXhgofMc4aikZNGE3KWQyqEcui4Y8Kiv1ICwBW0AsT3IHvzIoiL9g1Rm0FhYGHrqmSReIY4p335X9nvv1k6HkVq3kB2qj23RZ06byudIqwpt5gVocQvXzeWhYu4TJk2VDg/jS2ThNkxFZf7MCmgYtWsjGbMcyI0aMYPr06Zx++um0aNGCsWPHctttt/H1118flfG07ppRKc9iDQe/ciqG3Y5QVYSicPjiqRy8/1E0VfWIiLlQkmrLPNnkBh4/Zgi2nBkBO2tNWtkPSDN7Uz8pAlUNfA2Ijtf5+uOogDnFmib4ZFYqk9ZdS8+1rzNk07M8sW0EhXvysI8cB2vLv1vZJHJy4a98v60j3ucu13nuZqaxjJMDjkvRDdSrpxJXPxnnqMGIMN/0fOJ4lPtoKPaS8vMCYpRiJvA5f9MNgLV0YipvUY991CKdMXzHt4zhFa6hD4tpHb+XkQm/8Q3j0FUbuqIxTx3J1bzKOG0ODqOiP6+hK+zeofLyU1JM7dqucM3kWIb1qMEtU+N44JY4br08lvnfhRbTc30+/T0XDqGkEXhbZ5klNuMw9sLCsk/DHhqFJGA1TZCYLLjj4WKyDgc+TlUTbFtTObuzYIT0rt16661MmTIl4DItWpRXmqalpTF48GD69evHW2+9FXT70dHRRB+l0utOnWR3006dZK1RqHpToFJQIPjgA7juWiE39sADnl2r2rSBt96SPqTHCDVryoZXq1dLQVtUJPsRjBtXLmiff1522w0dhWX0YSstSSaLwBbWLlR+1wZ5RIb/WB3P0JXX8Ql/MpHPQxuCqvKP0ZFhLOQggQ2tqxJXG79A6Hp59f0xwXPPyXwdb377TbYdW7FCRmYB3ngD+vSBffuoL/bzP+5hKr47eaUdiuLKK+H99z0fv+km2a3rk088U/9UVXoef/99YLeNYxWzqVrFxeUN4yOVqtV5wD6WzW9McaEGIc4+gBRSH9e+jpYnN+bUrgfIHXcWjsblncG8i6PccY+mRjJfNhDuwjVUeg7LY+VPFT2RXaiqoOuwbBZ/Hfi91HWFebOicBelvy20M83ekIV6W3oa5eLmQR5mK20IdPNtw8FLXM9HXFjhOVGaX6tffQnKn8uI37wNZ2EBRv06qGkHTPhUlJNHPKfyC6vpVjZ1rQuNb9Sz+MY4kzt4iqe5E6CsuGgeI5jNGGQJoEDkq+zQ6vMDA2kYfYisknjy9VgURSACWbnpCt98ZmfilGIuOSuevBzFI4K4e6fKHVfHkZNdyMSLQ8vVDZYfGypVGYUFULxSQhqxJ0gkVpRObirExQvGnlvCJVeXUFRUdQGdUFCEqJrw4N69exk8eDA9evTgww8/RAvj6pGTk0NSUhLZ2dkkuiX5VyU5OXJasqAgnICeoF07hTVTXiDqrlsqPq2q8ir666/yIn4c8cEHcPvtFW22giOIoYj3uIRJfBy0rag/FAxiKWQ/9UjAfOFBDgm0SkzncK4NXRwdhaNp8mahZk1ZQe/vG2mzyS66H398ZMcXFocOQYMGcg7fF5omO6q5+cOyfz88+SS88go99SWsorvfPC1Fke4Z3pkJhiGL5F5/HTZskFkmF1wgHdxq1YrQsblxNM5R7mzbto0ePXrw7LPPBpzpeuihh3ymat0wbQ7RsZW7AP/5l8KKD3vjKIwqLUcP7eKm4sTARq9+Tl6ZWUCcj+F4G8K7cLfIMitgg+XEehfyeOOeQhCKmDV0ePGGBmzfEIPwirSqmiA23uDq17bz+nXNyM8KJ9NPkEg2/9KKWmRQSAx1OEge/oWzi4bsYQ+NK465b1+MkzqhTZ8BDmfp3bYUQmYdClzcwVMB0oQMXOb55q8BoY4A+g92sORX36kaAFHRgkVrckkMoYDW+7PpyqMNZT2XO4FZRwIXrmisGYeCBIf83GpFRXSc8UlZ++J5jGAk8/yup2Jw/T3FXHyVA5utPNjicMDQbjXIzAh8rNe9kMa/2SvpVD+082NxYT4v3TQq6Lm1Sgq79u7dy6BBg2jSpAnPPvss6enp7N+/n/3HQBgpMRG++koKBg9rUxNT3aCwaZPgwnsqngyA8hapd9wRkbFWJy68UM7mL1woRdY775hdU6GEKK7iTS7kA5Ovc0UEKoXE8jw3cydPcgEfcSPT+IsePpcvJpofGM5NXX7hUG70URGwrpNB06byvuaaawIv73TKzlPHBJ98ErhiUtflFy0rq/yxevVg2jSWLCpkJb0CFhqoqlzd1+Njxsgsnh074J9/4K67qkbARpJjOVUrqWE2T8zay/m3p9OuZ+hRJKNU1KxcovLInRXz53wJWJGdXnbhd/2YxbW8axve+PIFdWd8lwZlnZgyCx0B24q6o2pw1dP76Ny/VCQroqywqG6TEi59dieJtZycf6GOGqAAzD8KOSTyHnJabDeNTQlYuarCN0mTGVv3T3q2z2XsyBK++KiA4gcfRXvrHShxSP9eXa8QyTPDXurzKtcGSNWSbU1DC2KEHglcHEDAAjhK4IdvQo+yR5K4VPOFNa6WsgmONBJK9lJ701pO+vQ9+r7yJL3feJaWP82h1sENZQK2Xt9e1B48kKLePcuK6oYzn9OZ7yd9S5AYW8LZkxzY7Z6zhXY7XHh5iV/vY1UT1GtWQptuhT6fjxRVEomdMWMGl/jpVxrK7o5mlGPDBlnw9eWXUFQk6Fiyilw9jm20MuVhuZxe9OIv/wts337cuBj4Qgg46STZ3tcMCgYvcx2rkwbzTvY5hHOCUtARaNhwIErv6p3YmcBnfMBFRNeIQuTl8QrX8aD6KJlGcsj7iCSTJsko4fDhMjCZny9TR9evr6j/FEUWdH35Zfg9HI4od9whv0D+IrEuunaVCdbjx2NMupA7HkvkueeCb95ul7t47LFIDDZ8InWOSk9PJyMjsCtDixYtiIqShUFpaWkMGjSIPn36MGPGDNQQc/Bc465sJHbdvhxGDu5Q9n9aus7T57VCd4YXH1FVwYK/8qhbX6AUFJAy8z1SZr5L1O5dkJiIMWkS+g03IJLjIm61FSwy6y+6Fk5kNn2PjY0r4tCdCk3bFdO8UxFZRQ7Gd2lAxiGFCcPiyTio+BBcwaKPgi6sYjU92E0jmmDmZkVQt77gwD61zCbJ9Xtg8j/MyRlIghF6+okACojjJl5kBhfhJPRmDZFCUQQ16zk4vC/wGGx2wUVXlnDzvcUBl3PH102WmWisr0gsmPeH9cAwiHr4GWr+u72sixrIIkmhKmTfdh0lncu/p0p2DrUeexZlfzqKEORQg/ZsJI2GVPx8CUaMc/L064UVrj1OJ9xxdSwLZ9tRNYGhK4AABZJSdW58cS+1GzmZu2jDsRWJnTJlCkIInz/HCh06yPTVw4ehYG8WK5TevMDNpgSsDQczuSjwQsdAVLoyKIrs5GU2xVlVYdmYx3k78xwmT1bCstl13cU7saNjK8ur+opzuKnB55CezjO3HeQGXo6YgHXPkgml0/Azz8h6v5Ejy7cRHy8jspMmeW4rPl4Ktk8/PUYELEh7MzPedatXw08/wXXX8Wj913juOXPnCIdDppgfL9SuXZt27doF/HEJWNdMV48ePZg+fXrIAjYSrNuXU0HAZhY6iK1hMOZsZ0ArqUAYhsIP39pR83JpPv4M6j1yH1Hb/0NxOlEOH0Z9/XXs3bujrDV5dxwE9yhuoMgs+O/AFE5ktnYjJ6eMz2HwhGxadC4XsACptQQffpdP996e359A3b7clmIN3biIGdQinc78AyZmtw4ekCcWV1GU6/firA5cY7xsYr+eCE2jZOgwRnbZw3tcYlLAVp0+EEKh/znBrPtkykdyzWNHp7iI/ek3kv/dDni261WEQDEESS++hVJY7igR26Ie+S8+hJh6ISIqilmcRRqN8H2DJL+TvtrL2mzw7JuFvDSjgH6nOmnUxKB9Z4PhUw9yz4zd1G5U9Z6Qx74j/5Hggw9A1zmDH3gOP+2p3DBQgxu2168focFVX3r2lLU7w4YFX1ZRVdSUZFAU5s8P1yHLj9UHGu8cHMuWXTE88HLo3rGBGD5cOlts2iSr4886SwYXoaKotdngzDNh8WLf9U4gnR7efx/S0mRB3c8/yzzjJ58sL6Q7JjjvvJCqI3OpwdNF12MmAq8osjvXOedUYnzHKNUhVcvl+eguYF2M79KAm+8rpkFjo8KUuGqmBRDw8pPR7LtlOrHr1sqLsNtzitMJBQXYL7404EmicNtGvz++CCZmzbQSdYnZ8V0alIlZM6LW1/MNGgumf13At7/lcfYdaVz60H4GT8gKuJ1yFD5iMpcynQd4BAL6f5ZG7PxMsevY+IQL2Ec9ioliJ004hKeFj/e3XGgaxMYya8Rb/LamZgj+o5G8QxeAQFGlI8RZ1x3i9HMKaNW1ECWAQ4QQMGJs1TRhqDKEIO6Hn/w+rQiBUlREzOLlHo/HduuF4/EnKNn9Ly82f8avGwxIR4KvPvZ9I6KqMHi4k9c/KmTesjw+X5BP/7Mzj0i3LrBErDnWrnWz/5lGAoGnVlQMGhLAsDImRvpmngB07izFWM+egZuYOZ3lnXoLqyCFxulUePLJsBp4+cVul16lnTpB27bw9NMyT3PVKpmLefXVUsBPmACffy6LBWfNMlfTV7u2XHfw4HIbqWMGl43C2WebDh0vZBgFBD9Q12fonXcg7jjyZDbLwoUL2bZtGz/99BONGjWifv36ZT9HEl8C1kVKLcGHs/O49RaD5GQpGOyawTi+DXihdOFwwMXfX4Lu5xqo6DrK7r0of1Y8h7qEqqvXvK+fQDZG3mLWHVeubCAh68Jd0IJvoeq9vC9atDZ46OYaNOuTRb8xuZgVegYan3I+HVnPC/bbURUDl7DzlJ3BbQN1bFzGu9TiEM3YSW0OMZDfWMhpckuJ5Xm3O2nC3Q1m0KPRAa54pKnJ6DF+xlY5mrYvZvRlh3nky50MniC9L0dfdhhF8R3VVhTBeVMc1G9U+TG4PieBfiKFUliE7UB64HdRVbFv2opt1x7Uw+WOSRmHFe5/tj6rd9QOeLOh6wo7/w1PLoaTShAKlog1g9vVUgEu5220AFEFJ3amMMP/9oqKZDust9+O3BirOffc4z9wommypmfCBPn/SSdVTdfe9HTzU/5mtJdh+PfI7dwZXnpJCvjPP5fHdkxFUsNBCJmD06SJ7AP75ZfyMRNvptnOQa1bw/z58utzInKspGol1RQ89j+DffudpB9ykLlmG18pEzibL4NGZA1DYS8NmcMov8sITYO1G3w+FwmLomD5tqGIEH8CNVTqNnHQf2w2ZoWephq8MfZzTt94M/OW51OjTGuGHvGcz3CPIrHF9GU48/lIu4iSZX9QsmAOsx78izb27TybNolVm+LIzVX8GuGX496+wPVTLmal2BQeRXCBj18u16ZHITe9vJfTJ2eRlFp+49TypCKueHw/NZLlY9K3V6BqgguvKOGOR8Jv4uCN66Yn0A9UPh/WVNczwyBmyQpS73mM2jfcTeytj7J/4Sb6D6vN88+rQd8nRREkp1Svc4wLS8T6QQiZg9i/P8S9+TzJznSmMJ01nMTtPENdDmDD9911TAx8fPr77LP5cSlwce21MGqUNH+/9loZvjtOGT8eHnlE/u3h+qBIITh/fnn+7HXXhd1wKyCdOpnryKYo0L279OUPdH4wjHLhbQE8/jhceaXMhXBHiIB3BXtoyMvcYGoXDz1kLj3FouroVD+RuYt8C0hvVFU6vsS8+wYoCq9xLU3ZGXQ9OyUso7f/BYSocFcYigAwYyrvcjDwJhxPUFeKQWU596ZDDJuUZcq9QNEUMmq3wYivwfatKnm54Tdr8Y7SGdgQwOXqu2RH1WZHs2Gc90R3HE6lQrMB//grUpOPJdV2cOo52Vz54g5GXH6Qth0N6tQ3pBj3ELXl1EjSGX35Ya5+ah82P0GDjn0KePTLnVzx+D7GXpXBebelc9tH27j9oeKQ6hrAv/XbESUmmpJWzQNKe+93XtuwlVuvsbN7T8XmEL4QAkafXT3TLCwR6wMhpHn/+efLlquFxRrZJPMRk+jJXyyhL0voy2n8iPS386SoCJ5beBJdnH+xhdb+d+RwyLZXixbJCFaXLnDffcdcZy+z3H+/NKOfMkWKxAEDpB/+1q0y+upi4kSZUimnfQJvU9OgWzePhk8+l+ncWfrYRgWoL9A0OX3vdMJff0n/ffA9BkWRdlfNmwce3wnD3r2yuYcvhPD7mRbAAzxCscnK5RdeCHN8Fkccd79V9bPPUAyDWmQwi+B9kwVKwNkuxTAQA8pFbiidjkKOdPkQshBaNNaFt5DNLHSEFKlVNRh7xWEe/XIHmi3wdUJ3QuNmcpkd/6khTO27E2gdlWKnxmdz6/D2Wyq6jonIqzuBl01K0Tn7ugw6dTXod1YmXyzM56e/8/jln1zufLiYZi0N7HZBbKKTAeOyuP2t3fzvm52cPinLr4B1odmgc/8Chk7Mpv+Y3LLI7JHG32fLLPuXrGD/khXsbd0yYOMJbw5Sh684G90w0WJXEzRtYTBinCVijxlmzoQZM+Tf7gXWsupd43w+IVZzME8dzVhldmm+kSe6UDlMTc7jk8A7c13cXSHC//1PFpIdp3TvLrMoVq6E33+XxVA1a3ouo6qycv+VVzzN7OvW9Yzi2mzSomrRInjzTZmS4C1kbTaoUQM++kh2bXJFg71RVbns00+XR1+HDoUvvoCkUuNru728s9bll8Nrr1XutTiumDkzZOuEPOIZxRymcylmT0XLl3t2rLWonlSwF8ovF7SdWUcztqP4CAC4cGJnBPN9Pue6KGtX3wabtpY9XhWdjvylFYQbjYXg+bFmSEwx6DMyJ2BE1maD0WfLIoDNh7NCFJhgppmAzSa/j7N/ECFEYF3bDoSC0+G5PZeVWXQMTL68hO9+z+fvXbnc/fk2Jt6SQZO2JVWShuYPs1HYYELVPZUgFPYvWYFWVEzcpv1oh0s41LKt3F/pedg9UcObDXQw4bQkt9C5u857XxUQW01rECwR64Np0/xPIwtUHEQxveuLHLz/ZeaqYzD8tFvUsbOKHqygp/mdK4osRT9Oo7Fm0TRp/r9lC2RnQ16erBU6eFAGr+fMkcG/mTOlyGzcWArjG2+U05cAsbEyov733zISCzIa+/LLFYVzu3bSCaCn11t11lmwb59s4HDffTJyvHOnFM3HfY6rGfbuLTdUDpGLeZ8FnB7yejuDz0ZbVCPS0+G/ZoMoVGQPdRXBXTzp19heVQVtOzppfUknoKLcKbso7z+ANvkqipYvCWtcoYgGf2kFoUZjIylkR07JJDGlYmMEV8T1zkeLSCo9z7Xtkxs0clsRc9PMxaojxPQvQUJNvTQf1TeqJmjWodyrNZw2v+4EcokINRoeDJe7hbvLhT/7Nm/M3ojtX7yc2qvW0mHGJ7T6aQ6NVvxB6r+bMRSV3LoNKI6LD/jufYE5a5ep1xfxwXcF1KlXffVIOL3tjmsMA9asCawhhaKyvNm5dB8AwZqXKBisCNb4wGPjQt7a7tsn23ae4ChKuSgFKT5HjPC9bN26UmQ+84x0AoiLq3gzoigy5/byy2UENytLRnt79vQfSIyJkaklFm7oOtxyiwyXuwjhSraJtnzN2WHturp33zoRcOXFersUzFqTViYIlv9hZ8qzCqtX2IBviCOfS3mPh3iIK3iLLbTheW7FhqPU01lG/gxDYfN6G+NSXuGBsS0Z8d2dPseg6AYiJ5fYu5+E7FziUCjp3J6C4UNwNm8acPwFGQXEpcaVCdnYVu39LqtlpaEnN0Bkp/tsiOASsmZajUK5kHV/rcxQQYTFOZg6bQcL3q3Nul8TS43mpaPBNbcXc/ro8nSMuESDPmce5s8vUzBlY6cKElOdJNctYdeGOL8WXE6nwrDRDooKFf7drPmNxiqKoFH7Qk4enUWnbg4y9tt55Wb/x27oCgPPzPZ93F6M79LAo+GEv2WAoMuZxV8XORe+Ivjen6FwUwn2L1lB6rqNNHCzzFJKP4OKMEjcvzdgnHsdHXmda03tS+ZRV28sEeuFokjhE8inXVVlFC5QfqULgUIUYfg6Bet0ZOEXVZUpBIGIjvYvhi1M4Apphzlj8C3j0HCaah7iQlGgRQvo4buTsMVRwF3I1oy1lwmOOV/buPu6WI8bwwLieZ2r+YERLKUPz3Eb5/Epz3ELXynn4kT1CLsu/1NjrHEz85jPafzsc/+KEKi70spkWcziFcT8uZycqZMpOrV/wLG7ol7uYtaFt6h1iRLXZcElRFxCZmN6fthitrLLXjwEsrNy2btLJS4emrYwKtyQj+/SgLHT4MqSTJZ9X1M+rwiELkt+FEWUphvIbkspqYJ3vygm/aDCFRPBV2qBpgmGDhWcNSSGjg3h0+m+lwOZK/vkM4KTutdg1po06tQsZOC50fz+eSqKKspEsqoKDEPh9KkHiW+UT2ahudfKW6T6W97Ma+4vuu56X3097+4w4A/3myH3x8B8UeL+JStQdJ26y1cHXM6f9Cwimpt5HgXDRItfha8+iuLa20tCciaI1I2CWSwR64WiyOrnhQv9C1ldlwKoVy8ZJcwJaBsr6MbfoQ2iTh1o2DC0dSwsjhQHDoQnYBWlbJ0CQk+wEkLmLB8zXcuOczrVTyxrfOBOXi48dFtsaT2f55ulY2M7zXmYB3mJGzmpRRYHovohtqrgFcUzDBUQTOF9dtIUzU8OrUczBMNAAInvfIijVQv0hsH9c73Fg7eodRe03kIkkJh1J5CwNZOSEEwYJyVDUrJRvj2vr6amqmgavPOmjenn/MvaXxNpGJVEg8YGzVrozJ0Vxab1GnHxgmGjnIw9t4TEJGjZFp58tZAHb42luEig2UAY0jf0tNMEH30sL5Jt28I77+hMnaqhqgKnU74rrva1dz1axEnd5bIuITn+RfhpRAEfvBXF6hUaigon99O5+Kpi+g2KAfwLTn83DJVNC3Bt11euq3uhovvzZgSsi7KboeTQx7l/yQoA1AMO7EWhm6nvoClD+JnttDC9jsMBvyy0cebE0IJqlU3/CAVLxPrg9tvhhx98P6dp0oj+3HNlzuXNN8tiIf/Xc5XeLGcCX/Ay11OLjPKye18nL1WV892hen1YWBwpvvnGXEtZb0q/JGvpxGbamIrCunRvSorMXDjrrNB3a3FkefzlAoqLEvAXD9Kx8U7sdVy2aATpWj1+PTnBb9GRgcZeGrGA0zkDPydlL1xOo3z4BftPqdhZpF7fXgHXdxe1LkHrLWSBgGLWG3cB5ItABUJmhLH38+7bc63vWv6SYXVgGEB5zmnfU/37o44c76T/kGzmzYoia280NeJh/FkG3bq5psTlsU+aLOjc2cmrr2ksXCAvb137OLjg0mI6d9fxVYIz9AwnQ89wll0/A92guh9j+9rxYUW/zW7bF74eDzclwF30es8CuMSqN7b8fGK2Z5K0d1fI+9NRGc58dhPE9tMLRYU/N+Yg1mSaukE40lFYsESsT4YMgddfl9atiiKv164vV2qqjNLGyhoF7r8fduyQrUI1zXVt95xS0bHxBRNYQxeWagNIvOlS6YTvbj3k2sHQoXCn7xwwC4tqQVaW/LCbMd11YyPtuJT3WIqJlmXIzmYTJ8reCSNHlvsIW1QfvHNja8baObQnCs0GzgDBm8JClX1KfdJ2BjdaV9HZQhvTIhZkmkFs2iFy7Z4X3gRHWplICCZmIXDurLeY9ZUv66IyXqJmhXEw8eVa3p/gCxQRrpEAD9xqx2UpKQuVKPvbxUldavPmm+43uAoQU0GIe48hFPHq/bcvMRtKdDtQ9DUQruP2FYX1VTQYKO/adeO0f8mKCp9ZDIPmv/9Ig9XLQUDIJhPAXEayhbYhrycMhSZN5esTKFXD9dyRjMC6sESsH666SqYVvPmmrHqPiYExY2DSJNm33YWmwfTpssXoY4/B7NngKwKhY2Mz7Xij8f8487kXeF95mN2iEbU5yIV8QNd6B2V49447ypNthZAtn15/Xba+TUyUBqpTp0o1bWFxNGjePGQB+x/N6c+f5GC+/eDw4dJtwuLYIirGQJio8YuLg/j44CkpBiqJQVp9+0L4UEYugeASs2aFLPiOyoL/fNlwCSaIXYQqutyjl5qqBozeBhsfVBRvviLT/rYdLDLta+xmnvM35e+LQMv6Ow7v5wMJWO+Ifrg0++MnGqxaVqYqXHa//gzQfFlr/cAItwJKcyiKoEayTofeBWhuxrveYvZoCliwRGxAWraUOXjBUBTo3VvqSpvN//XdQOGeHZdzJ1eDEKgYqBg8z62cv+8jZrx4CVGvvipL4adNk3kN773nHuKVXb2ee06W1nfsGLFjtbAIyuHD8MQTsjFHiDzKfeSSYLqQy2aTDhMWxx59Tivk10/8h4tUVdClp05KLcGi3XtJqt2S7HQb/tIPbDg43cszNpAHJkgBm9mspZ9nw8MVlfWHK1+2OuMSsu7/h4Mv8RZKvmdVdbkKZbtmPV79CdlAebCR8iy2F+TTcNVyv33NvIVs2S2hoiAUpcy1oIQoRAjd2hRFFvhdcGc6mo9Ttns01uUOkVnoOCpC1vKJjSA7dwYLUCluF3EFA63szugzzuMWnpcb+PhjaWz63ntyUff8Q8OQYmLUqPDyEi0swiEjA/r0kS2zAlcyenCAOjzNbczk4pCiALoOTQO7JFlUUxq1KqFN71w/PqACIeCqW2Q+pqrCmKmHCWT75CSKtmzhRqaRQUr5E6rq00pIIG0Q93cObGNhJgrrTmWiaaFS2U5OwQin29iJhtliraokddsmAk1reH9ryv4XAuw2hALZJCIUFR0/LS3lCrhXAzbrWMT1z6fRqa+nGPdnd+bufxwJD+RQsERsBKlbN/x1DTTe5EoOkSqv4N79593RdamYZe6ChUXVc++98N9/pm+cBPA4d9OIPdzFkxV6rwfDbpeZMxbHJhPuSuOU0+QdvaYJbHbZ6z4mFp54pZB+p+pl05C9R+Rx9vWH0GxyGSl+PS+q+dTgVa6lN8s4RCrOZ57AePguKWTd0gaEoiBUlY2jz6E4Kdnn2BIcaSELWBeB8hqPNaoqGnqsE4rbQFWjFReFbMeilP6sKunE2MRFJJPFu+KyoOuNuOgwd76zm4c/38ktr6bRuptnsZ9LnAayL4tk0wizWOkEEeSMM+Czz8Jf34mdeZzBhXwYfGG7HX79FcaNC3+HFhZmyMuTlYshRP5f52ru5fGwd/nkk9KRwOLYJDpW8PL7hWzeUMzC2Xby86B5K4OR4x3UcKspcE0/Djonm17Dcln6Qw2+f6tWaf1QRXuuHUpz7jltGa8vvpX8b3/hD2M4JUTRRf2HJjWzKOx3MrtqJuNM8DKKNgxS/ttCatpmUFXsNZNxtG0VUb+26p5KcKTQstLQqXxucHXBbI5yVVCUnIIShhf3bwzkdLEAZ7Z7mk6gz7pCk3YlNGrt29M+mID1tfyRSi2wRGwEad68slsQFBIbiaFYWESOnTuhyL8FjzcObDzMg2HtqlEjaVl3ySVhrW5RzWjbwaCtW/tQF76seOKTDGokCXQn+LXnEhozFjZiPbezgs9xIItgFcNgZMZc3phzNe1iMiju1pndDQ9RWLsWsQfTaTb3R6LyCzBUBQUF5a/VOJo1IeuWqzFSavrclztmUwkiUdR1LOTWnigctfdCCJJ3/kvqlvVypkGYz2g1ULiImTiwhzQDlnPY97KhClgzHdQiiZVOEEFqV/pmTaEza80t6nDAKadUdocWFsEx05rOjSX05SCh5daMGQNLl0q7OkvAnhj4itTs32n3WUjijoNoFtOvTMACCFTmM5z+xh8cLogjZslftP7ye5rlF9Bq9gLsBdIcXjVEWbGLbdceaj7+ApRELodPWk+Fns/qa71wt+W+rq/1rTQC//h7vc2+D76stUJFdTroOOtjOn3zCbW3bUIJUcB+wnnspFnIKVyJKf5n2o5GmoBZrEhsBGnXDjp1gvXrQ29mpOGkHZvow1L5gFt3I59ER0tPWQuLqsQw4K67zC9vs5HrTAi+XCnx8XDbbfDAA7LIx+L4Z9aaNL9TjdGxBoaprJWKl3UndvbSkGncxGPG/bJz1/ufgoLPKVnFMLDtP0jM8r8pGtA74N6COROAZyFQOCW37usH2lagaK93S1N/HrbhClmzYu5YSynw1QrW/X/319Hfa+DLWisc2v70Ncm7twO+P7e+MFB4iRt4nlvYTZOQ9xmXoNOu17FpB2OJ2AiiKNKBaOzY4BrUYz0M4snnQybLU7PNJqvEMjL8T+M6HHJnj4efd2hhEZQPPoCvv/b7dAYpzORiNsV2o0atGM7ps4fWF4+G0cE3/fjjcP31UKNG8GUtjk18TSsGypXrMjCfOe+G74GtY+NtLucx7pcWREKU+Wr6QigKMUv/CipiXfjyifVFJAuDPAStmxermeUDCdlQCeSNGmidqhCywXxcfS3rjWtdM8flnVbgvWxlBKz8PG2kIKOA+h3akvLaeyHlwQrgImbyMRf4dOsww7irMrCHNuFWbbBEbIQZPVo6ZF19tWxs5O0bWy5upcObgsEkPuJBHqYV/8qF+vSBCy+EK6/0vyPDkE0QHnzQamVkUTV8+23Auf33uISreR0ndjSHgtin8PwXMCQDunWDNWv8d1Zu0UIGeCNYV2NRzQgUcfVHvWYO/Nu4m+MgdU1vQRECxaQhsZlobFXjS2jpyQ1MCbDKCMpwBGwkBbT3WLwbTEBFQRsouup9M2DmuFzRZX+EKmB9vW9RG7eEXMg1m9F8xOSQ1nERl6Az7qoM+o3ODWv96oAlYquA886DM8+UGmD7dlllPXq07Oz14ouQng6gkJgIN9ygcud5p1Bj2T1S7fbtKz1i775bOhA4AuRrZWXJJMK2obeTs7AIyH//wYQJfqcT5nIGl/EeLsFhuN2o/fyz/81qmvxYz5hhCdjjmcpUJitqQGvMoKRyqIIBvN+mCKqKs2H9kLZvNhobDt45lZGK+kZCUIYTXa7qSLB361/vfQcaVyB8tRk2s55Z/BWLKWH4977G1WiKE12Yl3NdhmbRe2gh7XoVHLMRWBeWiK0iYmJk33cXCxfKqmv3z2hOjpxSnTu3Kb/8cqlHO1tKSgILWBchFt1YWJji9dd9h1FLeYQHUNFDLh4YMgSeekpGai2ODzrVT2Tuog2MHNyh0ttSFGjTvZCtf8diGKHf5Wg4uZT3zO/PMCgcPND08q5orD+REw7ewtW7za2Lyu7LjKD0N/VeGfF2JCLBkRKX7mkB/toM+1snEqgZmaaXdfkjr7d3Qy8JJuUEqiq/X4MvSmfclGM38uqNJWKPAEVFMjrrcFQMbBmGnHZ9+GF49tnSB0tKYNYscxtftkx6e2VlSR/PlBQrxGVhji1b4Mcf5eemTx/o5WYAP3++X1/Yg9RmGX1C3p2qyvbMloC1CMTQiVls/iv0aXsVnVoc4mZeAEBoKiQmImrXgi3b/EZjbfsP4Gxhvj2cL5EZjsAMlkfp/niogtbfsu6C0h9VYfRvZr9mtlGVeL8foaSPRKLNrH39Jmp8NivwzIGilFbACmjSGGPyBBI+ToJ/A65FSqrgkmtL0NrvpnGD46uC1hKxR4CvvpKdYv2h67Id/fDhcOgQNNj4OwO27wwe41IUmXbw9NOwapV8rHlzuOkmuPZaOXebmyuN6mfOlIViLVvKXNszz5TPW5x4HD4sc67nzi2/4RECevSQ3TpatgwYhc0nvMpmw5BpBI8+GtbqFicI7U8uZNxVGXz7RiqqJjB0V5d4F74v1n1YygdcSD3lgOwTn5iI/t5LaNfd6XdfAqjx0RcU9e4R8vnQW8yaFbLuAtOs+Km4XPDon79oYiTEYLDoo6/XItT9uqbcKzNef+P0Hl+gG4qqTB9xoWTnkvTm+/JvH88LYA6jeM1+I2uTB5CQAOeOOszlI9OZ4HDy6NP+T9mKApdeV8LFV5Uwa43O8easaonYI8CaNcHTW3Nz4fTTXf8NpRE7mMZNnI3/ynCEkDmxu3aVP7ZjhxSxf/whQ7uDBsnHXMvv3ClzG0aOlNFeKx3hxMLhkHdLrpse96mBNWtg4ED5+9RTYeNGn2fGGAoJt/gm0/xsmcUxwrp9ORVSCVwG6eHmxp52fhbtehbw+zdJ7NgYjT1K0LFvPiWFKkvmJJKfIwWnPdqgZY88nrh6H/2WfkGt9U0R0W3Qh5yCMqwfbP0XZe8+v/tRAC07l6j1myg5qWNYYy0XPsGjspGyYQpF/IYqsgNhRoBHKg3Cn3g1kzccfJy+Uzi8OSLFfBmHibv+QdTDvk+OBgqX8h7vMwXNoaMf1OAgPPZKA16cUZcH7swlKgqKiwVCeJ6TNU2QnCI48zzfnbiOBywRewSIiQndN3YPDZnAF3zBhMBCFjyFhmtHX3whhcru3Z47d00R//ADPPSQZdF1ojFrFvz1l+/nnE44cEDmwyqK31v7NXQlHAGrKNDU/KytxQlOo9YlnH+75/Rzfo5KbqbGXz8moDsVHMUqezfHsnxXE5rd/RDJdeQsgauCXUnPMLUvNSu70uP1FrNQLrDCib5Gisrm8YY69sqkQZgZg/s+vLfvbxyhPBfquCq7LfWpl1AO+f+cvsY1vM/FgOxY50I3FLJyNG65tyaaJjwu84oqEIZC/UaCVz8oICk5vLFlFjqqdaMDsETsEWHMmHCmUFUEBjcxjTP5Bo0QqxYVBbZt8/+8YcCrr8L990Os1er2hOHDD2VOlb+5J8OAN9+ENP9TeOb7x1QkkGucxfFHJHuoF+apTLuuIQd32z2KvnIzbDxxr519exXenOa5jrCb27fZ5czgT2CZFTv7l6wAoF7fXkGWDH9MwaKXvtatzH7d9x2JbQV6LNLIfUQ2paDMdzY7B+X7+X5ttQTwPLegIPycd+Vjuu75nDAUzplcwn1PFh33WYOWiD0C9OoFgwfDb7/5rZXxg8oeGnMBH/EY99OaAKLUGzOh35wcGDcO7rxTlo1bBWHHPwcPBsx3BaQHnLfBcSkCiKUAG06cIZw+NA26dIGpU0Mcr8UxS6R7qC/6MokDu+2ICq4F8v8Zr8Vw05UO2ru0hhBoL74ZNPFFALF/LKW4by9wOlGzcxEx0Yj4yk0jhyOwXALW++9QBa2/db2jsu5UtSA80hHo6oKWth/7L5vRHd9hGzAAMbBPef71zt0oPs6zLg5Ql+20CGOvgl8W2Lj3ifDGfCxhidgjxJdfSq/YJUukPjAMqTPNaM0vmcCXTOAVruNq3vB4LpNkZjCF+QzHgZ1+LOYK3qIxe8wN7OefZY7sxIkySmezPhLHNS1awMqVPgUqIG9koqIgP7/CU3M5g1t5jk0Ejkioqvxx7SI6Gi66SKZoxx1dr3iLY5g/vk30IWDL0TTBM6/oTDrLRubhOrRIW0/vDZuDzhsoQNSa9SS8NZOYZStRi4sBKO7YlvwzR+Fo30YuWFRM7O9LiP19CWp2LnqtVAoH96eoT8+InDf3L1lBrt3P1O2SFaaFrEvA5tobkOCoeBNxoorJI41SUEjiG9OJ+fsfhKqAoqK8/yWiQT0c770NPRpAbEzgbYTdg0vh0EGFTetUOnWVQYtI3lBWJyzFcoRISZG1Vj//LNNVc3KkVpg5M/i6Li/Oa3id1rYd9D1ZJ7ZDc5a9s5YzmEsOiaUfdZVfOZUnuYuZXMT5fBp8467Q8OefQ5s20szWovqSmSkjpbVrQ82a5tbZswfeeQeWL4d9+8rUZTaJTOcSvmACuSRwEmu4WrxJ/1Z5sHatR8T2W8YynsC2b65Aftu2sGCB3K3TCZ06QXJyOAdrcSwTyYum7oTcw4EvV7oOn8+I5qO3XbJ1GJ1Zw5tcSV+WBlxXAWJ/X+IxrRu1YQtRG7aQff1UHG1bU/Ox59D2HShbXj2cSdTmrcT+/DuZd9wAMVXXOTHX3gBMpBm4C1j3xyKZmmDhSVxqXMUbAyFIev41orbILpyKISjrL7b/IPazJuL4+Qf0Hv3RGtaHvfv8uhJUpoNdcZFcL5zueccKlog9gqgqnHaa/AF50l20SF7szURkFUUw3JiHsRhqrBGUUIIDDeFmmaFjAwwm8yHt2EQ3VpsbnBDw0kvSssvKka1+rF8P990H330nxaWqytD+//4HCQkwezYUFsJJJ8kPmFr6mfjoI5gyRa7jJko30ZbBLOJAaYtOUNlIez7iQm6qs57zjEvYQ2Nqk04flnA1rwN4fNbcsduha1e49FIZdY2Lg0aNqvIFsTgWiNSFU9WkE4GjOJA9kFLBAWY9HRjMIv5gAD1ZGXAf3nmJihAIIPGtmThaNEM7kO4hJVzL27f9R8LHX5J76STzBxQGrshqMFHqLmD9RWMjRVXk7x5LxLZq7zM1I2r9ZqI3bfW5jmIYiOJitLdm4LzzZigu9itRV4dZRAtyZqJ5K+O4FrBgidijiqbJNrRnny2jWMGErBBK2TJ5+QoQhe8PuIqKgxe5kRlcYn5A2dmwerVsfevN5s0y3WD/fmjQQCqVli3Nb9sifFatktZXRUXlQtQwpHCdM6f8MVWVd0Z168oE1I0bpTuFF040zmAe6dTyEKVO5Ilu2sKOTGN52eOppJNB4E47Dge8/bbcrcWJR6Q6dvlDUaDXsDyWzkso9Y01h4ENJ3AHT/Ezp4W+X4CiYqI3bPa/jCGI/W0JeRPPRMSH56HsnsMaCHchC57iMWA6QhXgEfX1Mf4TSdh6R2NjlqxAqKrfNrKKrqN+8gk2mw0y/Ttj2FRBqDXdIAVsh4E5/Lp333EtYOF4c709Bhk/XubLhhe18n8yd2JnNqPLH0hNNbdJVyLj/v3wxhvwxBPSV7RdO/n3jBky+teqFdxyS/AiIYvKc9llUsB6VwUahnzMlVztev7AATmf70PAgjTN3kFzdMyd3DKoZWo5d7tiixOHTvUTKzxWM9Ye8Yvn0POzsEcJFNXX3b7/CICOjUUM5SWup4gwpvyV4JmJitNJwoxPse3eG/r2SzErQHPtDcqWdQnJYCLYrEgOFdc4XGNyH9uxzP4lKzxes4KMAtONEwCUgoKgUSmlsBD1gw9QAlR79zSWERsVrP281wyCKkis7eCMqw4e9wIWLBFbLTjrLNmPINL2Qw53kXL//cFXiImBDh3gxhulqr7mGrj3XimIQIokp7NcLL3wAjz5ZGQHbeHJ6tUyEhuarUVAfmYIdkIxvzYX+aodXlt0CwtT1Gnk4IZpadSsI2+0VVWgKKUXcBMf0Rt5iQakMZcRQEXZW4KdLziHx7iXF7mBXTSWTwhzpnIxy/4i9e5HSZr2pmwdXsW4BKOvPFjv5Y4GVSWcwyGUsYQ7bvemCHqdWkHdfkStWiiFhT6fW8bJnMnXpHKYwhI7fm/SFEFyXQeaXQaT4hJ0hp6XxZ1v7aVx/cjIu+peEGalE1QTVBUaN47c9jSc9GWJ/CcmRiYrPv20f/9PRZG5kw88IM3uzXZneOopuPlmK4+2qtiyJeKbNFAr5fXqi2bN4OSTI7pJC4sKNGlXzIOf7GLzylj2bJWdvIoKFOa8m2Jq/WySGMd3LK4zlh49nBgTxqFOe4M5a5sxRcwgg1rYcGCgcjMvcAnTeY1riDZx0yeLdyB65WoS35pJznUnrp9cVefiVjWhjj+2VXsKt6wnYfcOnFt2YSQkeKQS7KcuX3IOh6hFU3ZytvI1RWdPpM6br1bY1izOZAJfAKKsqLscWeTlambQqksRVz2xD3uMwFGsEBUjIuqUWTPWXtZ9zyxHOgfXErHVhDfekHU7kULHxvW8jAB+G/c8751byI60j6nLfi7kQ0Yy17OBghCyUGjMmNDai+XkwK+/wogRAQZTOuVt2XcFRwhYsQL+/BPy8uDddyO+i34s5hWuj+g2n3mmvJbM4sTCV9vZqkRVoX2vQtr3klGsglyV+TNr4nQEv3obaKCqTE78jtaGTuy3gnatTuHxfzqU3dg53WawZjAFBzZmMsX0+BQhiF36F/lnj0GvXze0gwuR6ioUExxp1S4nNqhLg2EQvXINzWfPR8stwoi1YzgcFPXpBVF2cDgh4zDUiJe+ge4s/5sadz6MsifNw0vAQOFunuA5bkWgoKHjxMZ1vModjYq5veNvxG5cXyZ4c0hgMh+WBhrcT6jln+2Ueg6adSji5OF5tO9VgFqqc6Njw7XjCs6sNWnVtnOXpSqqASUlctY+fMq/Nio6Bho9WU4ecUxM/IEvPhuOTdFxcioaTr5gIgP5jdmMIp4CKWY1TaYGmKkw86bAj+/g999LdfPHH3KbPXrIPNrzz7caK7j47z+ZY5yWBrVqSWurNWvCex+AdGrxK6eio9GTFeykGa9zNWvpRCK5TOQzJvEh8eSRTzzhVr6688EHcM45ld6MhUVYxCUYjLw0k+/eNJf3bxgKW7bZ2LLNVtq87iT82RgZaHzAxdzH/2hNebV5sG+NUBWiV6yiYKz/m3s1IxM1Lw89OcnUuP1Rr2+vajV1f0xS4iB52utE/7MBoSjSmUIB5a2ZxH2/AEfr5sQuW4lSXIKwaYgRp2FccgHKzt2wbiPq+5+CkELU/bPxAI/wNHeUPeqKrBaIWB66P46vmi5ipyFl2GB+pgXbKSTWrwsMKJQUKVx838Ey8VrVhBONPZJYIrYa8PPPcPhwuGsLOto2s9PZkHziMdDQcLKGrpzHF5AjhZCztOeyXvqW/84AkslCoNGWTUzRp5O0WpBHf9qwkZHMxY7/TiIeTJ8ufWb79pWuBTVrwuOPS2WuaeVibNUqmDRJdnx46aUTW8iWlMCoUfDjj76fD1HAFhDLjbzIDKa4RZLkhVnDWfq+C1bSg2e4ncl8wJtcVZkjACA+HiZPrvRmLCwqxWnnZ+FQnCz6oBZF+Wau7qWiwvD83xcaTj5jIvfzGACOxg2xByvgUlSU0qYJ3ti3bKPGZ98QtVl2YBSKQnTTRmwbOIrCVPOJ5dU1CnssUuPzWUStlYVbLus0V7q1bd9+bPv2l31CFKcOcxagzZ6Pgn8X18PU5Blu9/OsfGztzpSyv+cwGid2lCB2BHlZNvKyNRJTIlcnEYyasfZqG421RGw1IBQB6+r25eqIdOWVCk/dXY9OXaAw20BHRcdG+cfb38lZLUsV30xb7uZJyAMNHR0bdTjADKZwBj8EH9S8eVJ0ff453HMPPPpoeWjZvSDJdcV45RUYORLOOMP8gR9vDBokxXwEKCCGk1nGBjr6nILSy77mCgYah0jlB0YQRTElBO4YEwibTd6TWFgcbRQFRp6fR8+RWaye2ZzZX9kRIjI3ySoGmZQ3Fsm84wZq33xvwHahiq6jN6gHgH39JuLn/kjU+o2gl7ZqdLuBV4Qgcddeun76DmsmXkpBLfMpCO7T4wmOtOPCGSDSuKzH/Il+paCQuJ9/r+ATXPa8r8fclvX3KfueMZQQFWR05Wu7gg/+o7Dl2KOqLnUgEMGE7NHwpLWy2KoBzZubW27GDLj2Wjj3XGkgsG6dzKX9aE4ye3MS3MRKqChlP65tpFOLsXzHH/QPvrqul/fRLSiAW28Nvs7UqVRwJq9KCgulBUT4Ie/w2LJFtvVdtao8uvrzzxETsL9xCvXYz3o6mzr5AejY2UlzLrg4/A5Dqio7zt1yS9ibsLCIOPYoQZNhJltum8SJjRb8hwD0hvWIbVkPx6A+fm23BCDi41CH9yfpjz9IeWIaUWs3oDh1tyifly2SYaA6dVr+HDxokOBIq5BzGijXsyoitsdK+oL3OH2N27Z9J0pJ5K9FWSSjhmPyGgBFFbToXEhsjSNvbVld7bosEVsN6NMHWrf2XxijqtC+vZypnzYNPvlE9qHv2FE+/9lnkR+TQEOgcF/pFJoHWgSScdLSzIndynLwoLQKS02VdwupqTBkiOxktXGjp5DevVu6M4waJTtQTJ/uP983GCtWQL9+sgfr6adD9+7Sa/e77+CGGyJyaFtozQjmkUtFn85gqCok11R45ZWK3WvbtZPZHjNmyM/agAHycZtNduYCaae1YIE8PAuLakNuDB/e1zjsjvO+iKKESXwk/7n8Ymjckb0F9cmiYi6ra7/GnTcQG1WD6Dfleu6V6v4id4oQJKXtIiYzw+9YXII01KKpqiiyChb1rUqh6+3jGmj/7l62vsalpe2rghFCS/714S5QGaQjwemTsyK4TfOYzYs90vmzVjpBNUBR4K23YNgw+b97/wBVlZrxjTf8p5Dm5IRVAxQUHRu/Moj91KWectDtiQjl4rzxhhSNtcyZ6YfMgQPQu7fs6+s+5kWL5A9IUXvDDdCwYblRr67LF/7rr2VaxE8/ybsIF4YhH1u+XCq700+Hbt3Kn1+xAk45paJX5NatMG5cxHKBn9dux0EMhNDByIVhQG6ujOxPnSqDw1lZ0KKFtMpyH+J558Fff8HcuVBcLOvzxowpF7QWFtWFmY/VJfewDXymErhOkv6+L57ZjQoGApVp3ERNstjd7Qwe/vc+PuweS7HjcxQMhjOfh3iI3qUd7hSQnZrWbULZ8m95F70QiMnOpKhmxSK1BEcaCEGjunWw/bEUER1NSef2iJjwU4KqCrMtcsPBXYT6a3vrzzs311af+v+tIHrej9QoLAKnEy09w29eayhkkEI6tanDQVLIZAQ/UJMMMjHZaCggAhQ475aDdOwTZmAlAgTLiR3fpcER95W1RGw1YdAg+OUXuP12z5nmPn1k1NVXJ1gXHTvK1IIAKVqV4jAp1BMHIr9hhwPmz49sYmVmJrz/vhSSy5bJ6GqgrmIZGfDQQxXvAlzrHDwIp50G27ZJL9y1a2V3im3bpIAVAu66C049VeYE16kjcz1KSiru17WPSNxxtGzJZ4cuw5kd/mSKS2NHRwdPT+7ZU/5YWFRX9m23s21NIL9qVxmOLwSqYqAIo6yTXTx52HHwDLfzd+ppfLt7PBn/qOilN40ClYUMYyGn8SI30pRd1GM/PYyVKN/OQ7RrG7Abkz/0qIqiNMGRRqN6dUh8833se8pFgoiKIn/McPLHnSGF3BFoPWu2vW1VCFlf4tS7Da/7Mkm7/qPZHz8Tm3kIBBhRUUQV5GMoKqoIb0p+M214j0vZQTNSyeBklvEV5zCHUQhUVHTG8i2PcT+38wz3EJmGQJ36FNB/bG5EthUqljuBhSn694fFi+Hff2XX1/r1ZWQsGFddJWfHqwaDP+lHS/4NavjtREMtdbgzjZ+OJWU4HPDttzJn4tAhaNNGhg6bNZMR1pQUaNpULjt7NkycKLepKOZb4gYSlbouUx8GDZIh8ZUry+8W3O8a/vxTit3p0yOW7+qT6GjZuOK55yhIrlw2UFUFwC0sjgY7NpiJSJYKWYWyaK2qCRDw/NtFDN38No+/1JhPis6mkFjySCSTVP7LaOG2fjku14/reK3ssWb8R5/iZWTvaEIUBxnNHM7nE+IJHEETgGG30W7OF9hKiilMSmFfl54Utq5Ng2ZNSHngyQqRCqWkhPivvkcpLCTvgurncxdJIes3ulr6v7uYzbXVp/UP31B301qPKKtwSjEWjoAVwJ08xTPcUdYQQ0HwOtcABq7sTAON7xnLQk5nPqcTTSHFVK4ZkKJAyy5FldpGZamOzgRwBERscXExvXv3Zs2aNaxatYquXbtW9S6PeVq2lD9m6d8frrtOFv1XBVfwDs9wBw/zAHVIpzfLqEE+IIXrW1zBy1zPJtqj4WQUs7mTp+mHCTF3663S0WDUKLjpJujSpfy59HSZY7FmjRSQug6//y5zL9x9VDt3hpNOkgmcQpT/RJIVKwJv0+mUUdp+/SKyux00ZR2diI1T6X9JG3Z2OIPfNtdBNGvBwBHxtI+Ven79+vAOVVGgSZOIDNXColpg1jfz1HOy2bIylv07orDZBScNzGfoeVnkNMzn0X8n8HlRQ4CyiKwk0GSz53M7aM4OmkO2gorOt5zJ/TzKTwylAxsDbkV1OIl25AEQf+gArX6aQ8meViglJVBS4tesKW7ujxQMG2zq+CtDOHmu/oSsv235ErvBWut6P1d/5VLqbloLeL474aQMCCCPeC5lOl8yAfBsiCHxDCjo2ChS47mh6fdM7pzGe9+38OOW4X3y9rGMItBsgj5n5IQx+soTThQ2s9BxxArBqlzE3nHHHTRo0IA1a9ZU9a5OWBRFFuJ06iSjssGIi5P1Si5dGBj55dxKay7gU0BOs13HKzzIQ5zH53zP6LKldWzMZRSzGcMHXMgFfBJ48zmlX8wPP5Su+R9/LO0XQEZV160r3bDu+dtdua1dK3+qEpNK8Z+StnzOuWSTRGu2MpkPSSGzwnJ/x/Tj9aIprKQ78RRwJt9wCdPJJYGrkj9jflZv2UGoAGxvegVgbpG1aZMnw913h3c4mgYXXBDeuhYW1ZE23QtQFBHQWssebTDq0sOcc73wdroisxAWf5WCqgoMozIZkuXrugp70qnNafzIv7QklqJy6SK7LZSupvi0boravC2o+FKA+P89BxPG+Xy+MpFQb7HpLhYVp5OEA2kohkF+7bo4Y3xHHN2FrL9tAT6X8bcshkHNnf8SnZONMzaWw81bY9ijwDBo/udPEclzBfiPFgxK+Is9uckhracbCn9vT+W2V+38V+xk0Xx72WfL1TY2MdVJzfoOFFUQ5YxhywbN4/PnmiWY8sBBaiQfeUcCl4ANJQp7pPNiq1TEzps3jwULFvDVV18xb968qtzVCY+iyLqke+4J7CKlabK77DnnyFl618z7ihWwa1fAPZT9lU8NnuIOflBH8Y/h7U3quks1mMIMTuNH6pAe/ABcKm3yZJkAnJFRXnx1DLCDJkzgS/6iFxpOVAyc2LidZ3iF67icd8qW/Z/9Qe4reggbTpzYkCkb/fkf96DGxpCVG1fWAhN85zr/9pt8vwYNkl1/3TMnXEHqqCip+X3dqDz8sEzftbCoDEe65WwgatbR6T4kj78X1UD4EKGKIug1KositYSiwnLLINeF2jBg75aYiPnLuqNjYx8N+IxzuZiZcn+JCeh1auGsV5e4P5b6vVE2O5rYQ4dJWL+H3O6NPB4vE39+iqDcCUVANl7+Ow1XLcNW2tTBUFUOt2jDwXadKU5IIr9OvbK7hIR9e6j3z18k7E/DsNnJaNWW/Z264x3QNJvPm/LvZlr9NIeogvwysarb7ezqfQqFySmoZlPJgqCjMDLmR9LykwlXEivZcTz3Th7LfrPz9SdRrNvkpEZNnf4j82jSMwubXQo/w8hnztd2Pn7XzpYNGvYoGDLCQaPBe6nfspgKL1YVEo549cfIwR2Yu2gDneqH7qJjhioTsQcOHODyyy/nm2++IS4urqp2Y+HF5Mnw6qv+I6y6Luuoxo6FCRPKH9+2Tdp8mUdljdE54PNObDzGfbzEjT6XyKUGixhMIbGcxD+0Z5NUbDffLC2pzIWKI04WSczkIv6kPyoGQ/nJb05bEdHcyIu8zeVlYt692UQJUVzB2/zGKfRgJTEUcp/jIYBSAQuuxhNZSgqi0NyJ0umUudPXXguDB8tUkoOlBhIdOsibmZNOkpH5P/8sX692bXjwQek6ZmFRGfwJWH/Tj0dievG829LJPGjjv7WxZdEuV2Rr0OlOnnvBhj1KXpjdo0VSRMDDVTg2FZ15yiguFlLEajm5qHn52LdtL2t1Wlka/r2UtK4n+/Rr9BcN9bVcQISg9YLvqLNprYesUw2DWts2UWvbJgAKk5LZ2W8IcYfTabLs97JiKoFMlWi4cinrzppEXr2GHpuPzs6i9pb12AoLKE5MJr1tR5yx5Roiece/tP/+87L/XWPQHA6a//ETOXXrBx6/SQQwt/edbFlm0sjdDzGx8u3oO8jBgCHyyuD92QO5zJhzHIw5x/v7k8qsNWmVKq4y+91z30dlBeyRSilQhIi8OZMQgpEjR9K/f3/uu+8+duzYQfPmzYPmxBYXF1Ps1qovJyeHxo0bk52dTWJi1aj4442dO2VaaV5eRf2nadIeafHiilavmzdLf9DIIu+Rh/IjnzGRVGSIWEflfh5lGjdRSPnJaQC/8x6X0pptsmArO7tKRewG2vMct/AlEygihg5sYDA/8xZXUkAcCgIFgY5GKof4gTPoyUqPozuTb/ie0YigfoACFQOjLGpd+WiPokit/9dfUtSmpcnoa926ntOkmzbJnguJiTJ/2rLGihw5OTkkJSUdc+co17hvmDaH6Nj4kNcPFIHNLHRUuAAGml4MdKFzXVT9LePrwq7rsGV5DQ4ur0v6QYUGjQTjzy+hz0Ddrxe3iynj41i1QsMIw7YuGAoG4/iOWYz3eDyY8VeorLjkOoqTagZfMAQUp5PaW9aTvGs79vxcau7eEXSdYNP5QlFwRsew4rIbytIAWvzyA/X/WQmKIoW9IRCqyo6BQ0nr1huEoNuHbxKXcQjFTwGxUXpDEMrr6VH8pSigQPY1l/FA2k288V17HM7wi2jnzHVy2mmCjen5aG4fQF/dr/TSCLIW7IMaAqFO7ZsRr7pbpNvfWN27d4UTiS0uzOelm0YFPbeGFIm96667eOqppwIus3HjRhYsWEBubi53h5iw98QTT/Dww1V5L3z807SptOo6+2z4779yFyhdl8XzH3/su1dBs2aQnCy9QiOHPC38wqmMZC6L6YeGwVW8wbtcViENYQl96Mdi/qY7SqbCz2IUOhq9WRawIML8cMqLwRZyGmP4Hh2tLEl/DSexmq5lY3c/RWZRk2EsZCutqYU0I/+DAXyH7xw0HzuPsPG1PBRX9NVm81+o1a5dVdygWJyorNvnv8DEl4AF/xfGYBEm13qBLsQ+t90duCqI84kPplxdwsqlVTNzKFDYRz1W0ZVurC57PPJyOTi2wgLqrl9N4r49CEUhq0kLDrbrjCIEtuJCHLHxGKV3u3HpB+g062OiCvLKBKKZfFN3QzN/rVttRYW0//4LDJtGbOZhYjMz5LJClHc3M3Ra/LoAZ3QM+Sm1ic8InJ6mlo7PDGXLaRp6XCzY7RR3P4mCYYPQG9ZH/7LyYtItLoduGGWiz5+Adf87EmI2Uq4CuleKRvva8WxMzzc91nX7cqokpSCkSGx6ejoZGf67iQC0aNGCc889l++//x7FLRyk6zqapjFp0iTef/99n+takdjI4fLjX7FCRufOOKO8w5c/7r0XnnzSvDNVqDzCfTRiL5cy3e8yGg5asJ1/aekh+gaxiA+4kIbsZRm9mc4l7KYR9TjARczkVH71fVJ1pSS4Cdg84mnIXvKoEZKwVNF5gru5g2cAuJI3eI9LfVSqHhlUVUZWf/vtqOzegqMbia2M80u4kViXgPWXRlBdbXhC4c0Xonjl6RhMxBIpl2rBJJ1cRsOBjp0reYPreYlYimjOdo+trKUT07iRbzmTYqLowd9cz8ucxddBR2PYbBTXSARV5XCzVuzr0rNCVLbm9q20m/MlqlPHvTpeqCqKYaAAhqpxqGVbcho0ptmSX9AcJRFJd/A3bheB2lA4YmLRHA40PbAhuoCy872/7ek2G/uiGrJXa0zNU1uRPLIjGUotVv0nCwW6tThIo2YaX//WlClPnBLaAXmxYaOjzG3IOxpbNp7Si2772uXfxY3p0gEoklHZcPA1Nm/8jbUy0VizkdgqSSfYtWsXOTnld+tpaWkMHz6cL7/8kt69e9OoUaMAa5dzrE7VHasUFUmx++uv8v/IfjI8Jmwwd3Eox4aDBuzlZJbzJediw4ETe9nvkczhS84hFi8vvZNPlp213HiLy7mKNypEgs0cQ1+WsFgZAJ07c2biT3z7R2qQY6laZs6ECy88ars/4Tma56gbb7yRrVu3Mm/evGojYqH6+kmGwl+LVS45u0bAZVRV0Lm7zq7tKpkZnueSYC4J7ue4NmzmHh7nIuUDvhejOZuvgHIbJw0nOjYu5y3e5MqAQg88p8WForBp9AQcjeWxRGdm0ebTWWVi1feIfP9fHdhNQxYwnGKi6cYq+rDU5xgPtG/P8o0t+YZxFBFLV1YzhRnU4hCrY3tyT8cvmb+ySdl7VLdmARk5MTh1+T7abTrnD/2PJ1+qQfeBdUg/pKL7dKzwH2vWNEGPPk7e+jy//LEAgtQ70hls+Ujimunw9931NTZvfAlYkKlAcxdtAKgSEVslhV1NvOY1a9SQX6CWLVuaFrAWR56YGNlAa/p0eO012SU1WC8Cd7vWIEv6+TvYshIndnbRhF00Lfvf/fcPjOAGXuJtrpAhyoED4Ycf4LvvpFWXGyvohYaOM2QRq1AQlQxPPAtXXknDO+KxLY1cpzTXaxlKPVubNpHZt8WxxdFyfulUP5F1+3LKLkruYtYVcXG/IPpKA6gZaz8qHYBCEdfdehtERQtKigOcqxSIa5zDDQ8dZNvKeHIzbMQn63SomcrMt+xs3Rjo8lq+3S20Zgrvs77Babx84Hx0p+pxg62XXqbf5gpO4Tcm47uzjfdIlVK/7Hazv2DTheeSOmwQCdM/RvGxrM/1A4w+FCIhhg+TzKW8x/eMLWsyIFDpxFo+4Xw6sb5sX3viWnF63p9soiY2HAgUPuU87uV/3Nf5U57ecj5Fq2weNxkHMmM9Rulwany4sBVrJuk8+VYB106uQWGhKMuVdt2k9Oyrs261hqNElHVyAylgayQKHni6uEIerD98fT6PlFWV6zvpvT/XmEIV0+4C1sUx505gcWwSFSWtuq68Uv7/1FOyq6o/hID33oNbbol0Pq0v/H+RDDRmMIXHoh+j7hXj5MBjYiAhocKyUZRgPmvKk/VGB1L/14EWn8iOtpURsO43ADab/HnlFXj5ZdnfIRiaJpuU9e4d/hgsjj2OtvOL62LkErPeUVnvC6KvoqwjZYTuTqiCoPOQeqxakOS3yMvQFQaOzKdWgp1ag0qAEjILHQjyaH1qTbZtqmPSrkue157Ze6EUR34kn4LO09xeQcR6xwILiaGIGJLIlr4nwqDVoXSKU+OIWfUPSlXli/nB+2i20opFDEag0J8/ywSoLwqJ4SEe5Hlu9Ujbcr1GG2nPQH5jJhfRhF20YxPDE5eyNS0Z8GxKYKDy4NoLS615g0t2w1BY85eNfXs0rnr9X5Z9V5O1vyRSUqhSu2kxJ4/OpNMpufTZE8UvH9Viw58JGLqCZjM4aUgOgy7I4O9cB397nct9ffZ9CchAy1cFvvZjVnT7u1mF8Iq6QuGIiNhmzZpRBVkLFkeAm26Czz+HVasqRlxVVRaLXXSRbK51991Vl09rBid2fnx5I5Mulxd2IWARQ3jV9g2rnJ2IJ59z+IraHEAnKrx9OKUPbyAvXrP07y+dA2JipG/vddfJTm2XXio9fMePD7y+qkJ+fuBlLI4vhBBMmTKFq666ip49e7Jjxw5T6/mqN6gs7lFZX0K2uhHqmEZflM2G3xMoLlAriB5FEXQbnEfjNp6tuF37iFI0z8omU4iAs1oCjbV0YRgLeJEby4pdXSP7g/48zj38wAgEKrU5yDW8xu3iGeLn/IQtz4ES4fOzv3zWXGrwEZP4hUEIFAbyOyOZzfW8wlxG4y69T+UXPmISDfEUQsVEMZz5/EF/v+4vOjayqMlYZgOQFFdM9v5oP6OVIwzlGqUogjffFFz6jJOJ12Ux8bosryXspLYTtH00neLCQxTmqcQlyii+63lfeM9kROL74tpmZfE1u+KNt+j2t1ykxhQIKxJrEZC//pL2TL5Orv37S7GlaVKAffGFFLvhu2IZ4HeyyxwltnIBe9NN8NJL0djU0ThLT4Lr6YiZYgwFI4ycWfM89JD0a/W5bwVGjJBB5Nxc/9twOoMX61kcGxyrzi+uCIuv9AJvjsQFLdL0uHA7a77uRu6BpLLHFNWgcY+d1O63nrmLfKvOjIJUhBFqC2pz571FDKYvS1hGb9qxGQF8yTmcx6ce56106vAo9zOXkSxiMHF//AnR0TjUKOxGSeCdhDBi4SrgLr1ILKYPo5lDFsllHi+fM4EbeRFfOaR/0p+B/M4qupFE+c3Vu1zGHwwwcR4u31Z2QXjBCX8IoXBgNyxZujWs9V1G/77oVD8xot+JSEQ73VOFvDEjbt0JJw82HKqksCtSWIVdR5esLGm9lZvr/+514UIZjQXpTXv//fDOO/LvULFTgiPMCKmLFSugZ09Z8HTxxf6WCiRgBbXiC2neIZYVKyJf1tCkCdx3H0yd6unl6oubb5apBb5uChQF4uNh/3752+LoEKlz1NFyfgnXJ9Yf3oVf3hfEqr6gVQVCwP6dCaTvicdmN2jW8TBxNYJUyAt498FeZB6MARHKzbC5DFINByOZx3eMI5tE6rOPImJ8Cj4NJ9fxMhoG73EpWdSkJoe5jHe5jWepi/Tp01FZSh8yqUkrttGOzf5HWepk4BKwLueC/dSlDVvIJw4jhBiZgsGz3MYtvFD2CnRiLRvoUKXBhOADEzRonsOkO1eHvKq7Fd2x+Ll3x5+tXrCb1soc91F1J4gUlog9urz0koxm+vuEaBoMGwbedSUFBdKj9vHHZXQ2UN7oU09JYVdcDFOmBB+Te6txX3TuLJs59OsH69eHn97gcMjjSEoKvqxZPvoIzjvPZzMdn2RlyWj35s2eQlbT5HvyxRdw1lmRG59F6Bzpc1SknV8iLWKhvBHCkYrEVFcO7onn02e7UFKsIQzXl968HVdwBI3ZDTaV3c6GAddRMFAxyorEQIrbOhxkCX35iSHcz2OkUd49qx9/8hrX0IV/KmyvsEMnnPXqU+PXn1HcTk6PcD+P8IDHfsygYNCJdaxSu+O02fngyoe4+vXbcDoj660demsJwemTt9Bl4P4Ij+P4IFDTkyMlYq10Agu/LFoU+Hldh59/rvh4XBx06gT/+58UuLm5FaOJqgpjxsDtt8uo4owZ5sYUTMSuXStbqq5da257/hBCFrlFAk2T0erzzw8efXUnOVkK8scfhzfflA3MFEVu6777YMCAyIzP4tjhWHB+cZ8mPVEFLECdRvlcfP9KVv7YiPVL61JUaDORIytQNYFRdr4MdMJQ2E0TcAaPQwlUdK+Ipo6NdGozjAVspS3eg1tGb/rzJ0vpQyfWY6gaB5q15v1nPsQRH89td5zvIWABZjE+ZAHrGt8B6rJiwEh+O20ih+o2wh6j48yLtIiFUNPVWp4UeIbE4uhydF10Lao1hhHcPivQ882bSyP+9u3l/y4Bp2myeOnTT8sfq2myS6IZN4CPPza3LV+oKvTqJVuzxsRIoeirw5k/XMdjt5evN24cfPllaALWRVKSjFYfOiRTB3JypHOYJWAtLKo/SanFDJn4L9e/sJjb3/iNTv32E0zJDjrnX9p0D9yVypPw6wic2EsFrGs75ejYKCKGu3gSgcL2/kOZ/dJH1KiVDEBWfsW82iJiwhoHCEpqJfBws6fZ6GxLVnoM9ZrloijhThQLPF9nAYqgSbssBp2zDc2m+1jGN/+uqRXmGI5/Ip3XGw5WJNbCL/37Swsnf5FPTZPT9oHo3Bn++QeWLpW2UTExMHw41K/vudzpp0NiohRp/khKktHIYOi6zOXdtSv0dALDkLmoLu68U0aMzaAoMie4c2dYt05GpMeOjUzLV5sN6tat/HYsji+qq/PLiRyBDcQp47fz7z+pFOXbK9hvKapBcq0iThqwn7Y90tm6uhbCp8H+kUPHxlxGct4VH5DbIBH+2svIwUnUjLWzu8dA9vwXj0PYaMcmUsikC6vYTNuw8lizDsXxw0zXyTKU5ji+UKjbJJcDu2uAUEhMKab7kL10H7wXzSY4acB+/vqxIYtnNw+4FVUTZGeEK8xPHLwdSo6ksLVErIVfLr1UVtEXFfmOuOq6p+Dzh6JA377yxx+xsfDww4G3N2UKvPhi8P0BnH02PPec7+dcKQnuTQVsNhnlvfFGmbfqYvRoeOYZmfbgWsYb1+MTJ8IDD8jtnnOOuXFaWFicOMTVcNCp337++rERCE+RVqdxHuOvXo89ysAeZdDrtD0sX9CYyrUKqHyrAYFKTJ22NK2fz7p9Ocz5eQM7lzXn9t+ep0hINxg7JUzgM1bSM6xOiIFbLYQ2fkU1qNskj0l3rkIIBd2pYI8yPGbComN1upyyP6iIFYZCTPyRb8xxLOGy2vP1+JHAErEWfqlVC776Cs48U4o+l4Bziba77pJT5ZHixhtlgddDD8nfmib3ExcHTz8Nl1winQ+CeaPa7dKz1uGQxWnu4lNVZcR35kz4/Xf4+msp0nv0kDZhp51Wcdr/tttg5EiZl7pqFURHQ4MGstlBZqbsmjV1qu91LSwsLEAGAhZ81Jp//vCahiq1/LNH6cQllAumU8ZvR1FhxcJGbg0Xgp9gFEVmwAqhoJQVc4XW5tubuBpyXJ3qJ/LLVy3YuKAx7lPxDqL4hAuCCtgmsXtIc9bH6XDP0YrESbO8YKtpuyxGT91YWkAr0DTfMxU1kkpo1DqLvduS/DalEEC7nqGkdlgcaSwRaxGQM86QU+OvvgrffCPFZZ8+UvANHRrZfSmKnL6/8kopLvfvh4YNZQW+q/HWvffCPfcE3sYll0BqKkybJkX2q6/C6tVSDE+YAFdcAfXqyTSBp582N7YOHcxHgS0sLCy82ftvIv/84a/1rcKercmsX1qXkwbISnhFlUK21+m72bY6lfwcO39+3xxDDywU2/Y8iM0mqFf7MBkbbKza1roSoxZEx5ZPP2Xsi2PFgsZlY/ZcUiNQjqmiCOI727l20hL27Uhg+fzG7NyU7ObcUBkUThqYRo8he6nVoMD0WgPH7eDT57vIcVcQsoJup6aRmFLsa1WLaoIlYi2C0rq1FITTph2Z/SUny1QGX9x1Fxw44F9QDhgAL7wg/1YUGDJE/lhYWFgcTdb8Xh9VNTD8iTYFVv/aoEzEuoiNd9K5/wEA8nOiWbWooc/IoaIaNG6dzZipm8oee2HeAIJFYVPrFZCx35/NmkJxoY0Zj/bg4vv+5p8/66GoRgDh6X9fQihkH4ohKkanabssVixsFBEB68olPn3S1pBnwhq1zuasa9Yx7/22FORGoagCYYCiCroPSmPQOf9WenwWVYslYi2OKRRFiunrr5cpA3/+KaPD7drJx846S6YTWFhYWFQnMvfH+RewAEIhKz024DZOGb+dQ3vj2bW5JooipJhVBAhIrl3EqMs2lm9OgNMRXCTWqFlExoE4H5FIFwpF+XZ+/ao5hqH6nXoPhqIIj3SJhOTiwKK+AhWb3CqqIDpWZ9xV68NO5WrR+TBXPbWU/9amkHkwlugYnVZdDxGfaOXCHgtYItbimKRlS/j886M9CgsLCwtzxMQ7yoWnH9yn7n1hjzKYcOM/bPm7Nmv+qE92egxxiSV06nuADn0OEBVdbseiKJBav4CMfXH4i5Aqamkef1CDC4VNK2vTofdBVEVghCFkhVDo0PtA2f+d+h0IkF7hewxdT93Lnq1JZB+KJSrWScc+B+g+eC8JNSvXRlfTBK27Wn6wxyKWiLWwsLCwsKhi2p98kO3rU/0+r6jCQ+T5Q9WgXa902vUKXnDUbfBefvzYf06sEFLo7tyYEtQTHKHSsGU2G5bWC7RQ6W9v+zBBnca5tHITig1a5NC+1wE2rqhTYXlvFEXQrMNhTjtvG4rlbm/hhvVxsLCwsLCwqGLa9kgnpV4+ilrRvFpRDaJjnXQblBbRfZ40YD/NOx2WKQdu4VZXE4GhE7dRp1F+cAFbSpM22TRpl+mzCYGiGtijdFLrl9rHuO2zRacMzr1xrYdTgKLAyEs20XvEbmxR7p2/PMeqagYnDdzHmVevtwSsRQWsSKyFhYWFhUUVY7MLJt7yD9++0YG0/5JQVIGCwDBUklKLOfPqddRIrty0uDeaJhh/zXr+/rkhK39uSO5hadzfsFU2vUfspkWnw5QUaSz8uHVp/qy/iKggtX4BNesWMv7qdfwwsy2bV9YGRYpRYciGAmOv2EDdJnns35FA2vZEVFXQtH0mKXULfW5V1WSeb58zdrL33yR0p0qdxnkYusL+nQmoqqBRmyziapho1WhxQmKJWAsLCwsLiyNAjaQSJt25mn07Eti5oSaGodCgRQ5N22VWWZRR0wS9hu2h52l7KC7U0GwCe1R5NDgqRmfIxG0s+LAtvj1j5WMDxu5AUSAqxmDsFRvJSt/Of+tScDqk8GzaNqvsGOo3z6V+81zTY4yKMWjeMdPjseTaRWEdr8WJhSViLSwsLCwsjiD1m+VSv5l5kRcJFAVi4nSfz3UZuB+b3WDhx61xFLvLAoGqGZx23r+06X7IY53k2kV0HxzZ9AcLi1CxRKyFhYWFhcUJTsc+B+lw8kG2rUll25pUFE1Qt3E+7U8+4Ff8Wlgcbaq1iBWl2eY5ORX78lpYWFgcbVznppycHBISElCOkb7DrnNrcZH57kYWJwZN2uXTpN0uj8eKfae0WlgA4CgqoDA/1+P/4kItwBrBcZ2bRJCqQ0UEW+IosmfPHho3bhx8QQsLC4ujTHZ2NomJiUd7GKawzq0WFhbHArt376ZRo0Z+n6/WItYwDNLS0qo8wpGTk0Pjxo3ZvXv3MXMRqiwn2jGfaMcL1jEfiWMWQpCbm0tCQgKJiYnHTCQ2kufWE/Fz5o51/NbxW8cf+eN3nVsbNGiAqvqveqzW6QSqqgZU4JEmMTHxhPsQnmjHfKIdL1jHXNUkJSUdkf1Ekqo4t56InzN3rOO3jt86/sgev5lzq2UdbGFhYWFhYWFhccxhiVgLCwsLCwsLC4tjDkvEAtHR0Tz44INER0cf7aEcMU60Yz7RjhesY7Y4Mpzor7l1/NbxW8d/9I6/Whd2WVhYWFhYWFhYWPjCisRaWFhYWFhYWFgcc1gi1sLCwsLCwsLC4pjDErEWFhYWFhYWFhbHHJaI9UNxcTFdu3ZFURRWr159tIdTZezYsYPLLruM5s2bExsbS8uWLXnwwQcpKSk52kOLKK+++irNmjUjJiaG3r17s3z58qM9pCrjiSeeoFevXiQkJFCnTh3OPPNMNm/efLSHdcR48sknURSFm2666WgP5YTlRDl/unOinEvdOZHOq96c6OdZd47mOdcSsX644447/s/eeYdJVZ59+D5nyvbeG8tSl947AgoCAhbsLaKJHVtiTGI0JiYmaqKJnzEqaiyxoaKIFBGUJr2XpS+wLNt7L1PO+/0xO7Mzu1O3gpz7uuaCPfWdmTPP+Z3nfQqJiYndPYxO59ixYyiKwqJFizh8+DD/+te/ePPNN/n973/f3UPrMD777DN+9atf8cc//pG9e/cybNgwZs2aRVFRUXcPrVPYuHEjCxcuZPv27axduxaj0cjMmTOpra3t7qF1Ort27WLRokUMHTq0u4dyUXOx2E97LgZbas/FZldbcjHbWXu63eYKlVasWrVKpKeni8OHDwtA7Nu3r7uH1KX8/e9/F2lpad09jA5j7NixYuHChba/zWazSExMFM8//3w3jqrrKCoqEoDYuHFjdw+lU6murhZ9+/YVa9euFVOnThWPPvpodw/pouRit5/2/NRsqT0Xu11tycViZ+05H2yu6oltQWFhIffccw8ffvghgYGB3T2cbqGyspLIyMjuHkaHYDAY2LNnDzNmzLAtk2WZGTNmsG3btm4cWddRWVkJ8JP5Tl2xcOFC5s6d6/Bdq3Qtqv105KdkS+1R7WprLhY7a8/5YHO13Xbm8xAhBHfeeSf3338/o0ePJisrq7uH1OVkZmby73//m5deeqm7h9IhlJSUYDabiYuLc1geFxfHsWPHumlUXYeiKDz22GNMmjSJwYMHd/dwOo3Fixezd+9edu3a1d1DuWhR7acjPzVbas/FbldbcrHYWXvOF5t7UXhif/e73yFJktvXsWPH+Pe//011dTVPPvlkdw+53Xj7nu3Jzc1l9uzZ3HDDDdxzzz3dNHKVjmThwoVkZGSwePHi7h5Kp3Hu3DkeffRRPv74Y/z9/bt7OD85Lkb7aY9qS1U8cTHYWXvOJ5t7UXTsKi4uprS01O02vXr14sYbb2T58uVIkmRbbjab0Wg03HbbbXzwwQedPdQOw9v3rNfrAcjLy2PatGmMHz+e999/H1n+aTzfGAwGAgMDWbJkCddcc41t+YIFC6ioqGDZsmXdN7hO5qGHHmLZsmVs2rSJtLS07h5Op/H1118zf/58NBqNbZnZbEaSJGRZprGx0WGdim9cjPbTHtWWtuZitqstuVjsrD3nk829KESst2RnZ1NVVWX7Oy8vj1mzZrFkyRLGjRtHcnJyN46u88jNzeXSSy9l1KhRfPTRRz+5G/64ceMYO3Ys//73vwHL1E+PHj146KGH+N3vftfNo+t4hBA8/PDDLF26lA0bNtC3b9/uHlKnUl1dzdmzZx2W3XXXXaSnp/Pb3/72opne624uVvtpz0/dltpzsdnVllxsdtae88nmqjGxdvTo0cPh7+DgYAB69+79kzXAubm5TJs2jdTUVF566SWKi4tt6+Lj47txZB3Hr371KxYsWMDo0aMZO3Ysr7zyCrW1tdx1113dPbROYeHChXzyyScsW7aMkJAQCgoKAAgLCyMgIKCbR9fxhISEtDKaQUFBREVFqQK2C7kY7ac9F4Mttedis6studjsrD3nk81VRexFztq1a8nMzCQzM7PVjean4qS/6aabKC4u5plnnqGgoIDhw4ezevXqVkkJPxXeeOMNAKZNm+aw/L333uPOO+/s+gGpqFwEXAy21J6Lza62RLWz5wdqOIGKioqKioqKisoFx08v4lxFRUVFRUVFReUnjypiVVRUVFRUVFRULjhUEauioqKioqKionLBoYpYFRUVFRUVFRWVCw5VxKqoqKioqKioqFxwqCJWRUVFRUVFRUXlgkMVsSoqKioqKioqKhccqohVUVFRUVFRUVG54FBFrIqKioqKioqKygWHKmJVVFRUVFRUVFQuOFQRq6KioqKioqKicsGhilgVFRUVFRUVFZULDlXEqqioqKioqKioXHCoIlZFRUVFRUVFReWCQxWxKioqKioqKioqFxyqiFVRUVFRUVFRUbngUEWsioqKioqKiorKBYcqYlVUVFRUVFRa0bNnT+bNm9fdw1BRcYkqYlW6jNtvvx1/f39OnDjRat0LL7yAJEmsWLHCtqyxsZF///vfTJ48mYiICPR6PYmJiVx11VV8+umnmM1m27ZZWVlIkuTwCg0NZfjw4bz22msO23YXr7/+Ou+//353D0NFReUnTEs76Oq1YcOGDjvnhg0bHI6t0+no1asXd9xxB6dPn7Zt58xOW1/jx4+3bXfnnXciSRJDhw5FCOH0PT700EMdNn6VCxdtdw9A5eLhn//8J6tWreL+++9n3bp1tuVnzpzhz3/+M9ddd53tqb+4uJgrrriCPXv2MGvWLJ5++mkiIyMpKCjg+++/59ZbbyUzM5M//OEPDue45ZZbmDNnDgCVlZWsWrWKhx9+mLNnz/KPf/yj696sE15//XWio6O58847u3UcKioqP10+/PBDh7//97//sXbt2lbLBwwY0OHnfuSRRxgzZgxGo5G9e/fy1ltvsXLlSg4dOkRiYqJtO3s7bSUmJqbV8Q4dOsRXX33Fdddd1+FjVfmJIFRUupC33npLAOL999+3LZs9e7YIDQ0VOTk5tmWzZs0SsiyLL7/80ulxdu3aJT766CPb32fOnBGA+Mc//uGwnaIoYsyYMSIxMbGD34nvDBo0SEydOrW7h6GionIRsXDhQtHWW31qaqqYO3eux+3Wr18vAPHFF184LH/11VcFIP72t78JIVzb6ZYsWLBABAQEiH79+omhQ4cKRVEc1gNi4cKFPr4blZ8iajiBSpdy9913M2nSJH79619TWlrK4sWLWb16Nc899xxJSUkAbNu2je+++457772Xa6+91ulxRo8ezW233ebxfJIkERcXh1bbetLh9ddfZ9CgQfj5+ZGYmMjChQupqKhotd0XX3zBqFGjCAgIIDo6mttvv53c3FyHbQoKCrjrrrtITk7Gz8+PhIQErr76arKysgBLbNnhw4fZuHGjbfps2rRpHsevoqKi0tG89957XHbZZcTGxuLn58fAgQN54403XG6/Zs0ahg8fjr+/PwMHDuSrr77y6jyXXXYZYJlt8xVZlnn66ac5ePAgS5cu9Xl/lYsDVcSqdCmSJLFo0SIqKyt54IEH+OUvf8no0aNZuHChbZvly5cDlhhaX6mrq6OkpISSkhJOnz7Nf/7zH1avXs2CBQsctvvTn/7EwoULSUxM5OWXX+a6665j0aJFzJw5E6PRaNvu/fff58Ybb0Sj0fD8889zzz338NVXXzF58mQHwXvdddexdOlS7rrrLl5//XUeeeQRqquryc7OBuCVV14hOTmZ9PR0PvzwQz788EOeeuopn9+fioqKSnt54403SE1N5fe//z0vv/wyKSkpPPjgg/znP/9pte3Jkye56aabuOKKK3j++efRarXccMMNrF271uN5Tp06BUBUVJTDcns7bX3Z210rt956K3379uXPf/6z09hYFRU1nEClW3jyyScFIDQajdizZ4/Duvnz5wtAVFRUOCyvr68XxcXFtld5ebltnXWaytnrgQcecJiOKioqEnq9XsycOVOYzWbb8tdee00A4t133xVCCGEwGERsbKwYPHiwqK+vt223YsUKAYhnnnlGCCFEeXm5V1NkajiBiopKV+MsnKCurq7VdrNmzRK9evVyWJaamioAh7CuyspKkZCQIEaMGGFbZg0nePfdd0VxcbHIy8sTK1euFD179hSSJIldu3YJIdzb6fXr19uOt2DBAhEUFCSEEOKDDz4QgPjqq69s61HDCVSaUD2xKt1CdHQ0AImJiQwePNhhXVVVFQDBwcEOy998801iYmJsr8mTJ7c67r333svatWtZu3YtX375JQsXLmTRokX86le/sm3z/fffYzAYeOyxx5Dl5p/APffcQ2hoKCtXrgRg9+7dFBUV8eCDD+Lv72/bbu7cuaSnp9u2CwgIQK/Xs2HDBsrLy9vzsaioqKh0OgEBAbb/V1ZWUlJSwtSpUzl9+jSVlZUO2yYmJjJ//nzb36Ghodxxxx3s27ePgoICh21//vOfExMTQ2JiInPnzqW2tpYPPviA0aNHO2xnb6etr2HDhjkd62233aZ6Y1VcolYnUOlyzp07xx//+EcGDx5MRkYGf//733n66adt60NCQgCoqakhLCzMtvy6666zCd7HH3/cadmsvn37MmPGDNvf1157LZIk8corr/Dzn/+cIUOGcPbsWQD69+/vsK9er6dXr1629a62A0hPT2fz5s0A+Pn58eKLL/L4448TFxfH+PHjmTdvHnfccQfx8fG+f0AqKioqnciWLVv44x//yLZt26irq3NYV1lZ6WB3+/TpgyRJDtv069cPsJTMsrdxzzzzDJdccgkajYbo6GgGDBjgNB+hpZ12h0aj4emnn2bBggV8/fXXDoJaRUX1xKp0Odb6ft9++y033HADf/3rXx1qCaanpwOQkZHhsF9KSgozZsxgxowZREREeH2+6dOnA7Bp06b2Dt0ljz32GCdOnOD555/H39+fP/zhDwwYMIB9+/Z12jlVVFRUfOXUqVNMnz6dkpIS/vnPf7Jy5UrWrl3LL3/5SwAURWnzsYcMGcKMGTO49NJLGTJkiFMB2xZuu+02+vTpo3pjVVqhiliVLmXp0qV88803/OUvfyE5OZlXXnkFvV7vkNhlrRX78ccfd8g5TSYTYPHsAqSmpgJw/Phxh+0MBgNnzpyxrXe1nXWZdb2V3r178/jjj7NmzRoyMjIwGAy8/PLLtvUtvRkqKioqXc3y5ctpbGzkm2++4b777mPOnDnMmDHDIcTAnszMzFbC0dqwpmfPnp09XKDZG7t//36WLVvWJedUuTBQRaxKl1FdXc0jjzzCiBEjePjhhwFLvNVf/vIXVq9ezRdffAHApEmTuPzyy3nrrbdcGixfnsat1Q6sMVczZsxAr9fz6quvOhznv//9L5WVlcydOxewlPGKjY3lzTffpLGx0bbdt99+y9GjR23b1dXV0dDQ4HDO3r17ExIS4rBfUFCQ0xJeKioqKl2FRqMBHG1oZWUl7733ntPt8/LyHEpcVVVV8b///Y/hw4d3abjU7bffTp8+fXj22We77Jwq5z9qTKxKl/H000+Tl5fHV199ZTOkAAsXLuSDDz7gscceY/bs2YSEhPDRRx8xe/ZsrrnmGq644gpbCIG1Y9emTZu44oorWp1j7969fPTRR4BFNP/www98+eWXTJw4kZkzZwKWzjBPPvkkzz77LLNnz+aqq67i+PHjvP7664wZM8ZW2kun0/Hiiy9y1113MXXqVG655RYKCwv5v//7P3r27Gmbfjtx4gTTp0/nxhtvZODAgWi1WpYuXUphYSE333yzbWyjRo3ijTfe4LnnnqNPnz7Exsba6iiqqKiodAUzZ85Er9dz5ZVXct9991FTU8Pbb79NbGws+fn5rbbv168fv/jFL9i1axdxcXG8++67FBYWuhS9nYVGo+Gpp57irrvu6tLzqpzndGdpBJWLh927dwuNRiMeeughp+t37twpZFkWjzzyiG1ZfX29eOWVV8SECRNEaGio0Gq1Ij4+XsybN098/PHHwmQy2bZ1VrpFq9WKXr16iSeeeEJUV1e3Oudrr70m0tPThU6nE3FxceKBBx5wKNtl5bPPPhMjRowQfn5+IjIyUtx2220O3cVKSkrEwoULRXp6uggKChJhYWFi3Lhx4vPPP3c4TkFBgZg7d64ICQkRgFpuS0VFpdNxVmLrm2++EUOHDhX+/v6iZ8+e4sUXXxTvvvuuAMSZM2ds21k7dn333Xdi6NChws/PT6Snp7fqzOWqY1dLfOnYZS2xZY/RaBS9e/dWS2yp2JCEUKOkVVRUVFRUVFRULizUmFgVFRUVFRUVFZULDlXEqqioqKioqKioXHCoIlZFRUVFRUVFReWCQxWxKioqKioqKioqFxyqiFVRUVFRUVFRUbngUEWsioqKioqKiorKBYcqYlVUVFRUVFRUVC44zuuOXYqikJeXR0hIiNp3XkVF5bxDCEF1dTWJiYnI8oXjE1Btq4qKyvmMt7b1vBaxeXl5pKSkdPcwVFRUVNxy7tw5kpOTu3sYXqPaVhUVlQsBT7b1vBaxISEhANz3whf4+Qd282hUfiocKahm5pT+DsvWbDyOJj+NAz8mUJIbhFan0GdYKcOn5hIZ19BNI1U532lsqGPR726w2aoLBet4/7zkR/wDg7t5ND9N1mw6bvv/wPgL6/roSKrK/Ni/MZETe6MxNGqIiK1n6KQC0scWodF0f8PQIwXVDn+3vDeodA8NdTU8c/0lHm3reS1irdNcfv6B+AUEdfNoVH4q6PzNBAQ1/zBqqyV2fTiTyrwIQAASJgMc3h7J0Z19mb8wg7SB5d02XpXznwttSt46Xv/AYIffgkr7WbX+CAA6/0AGJ4R282i6l0Nb41jzUT8UswRYrrmSXMEPnyVy6lA51y7MQKPtXiE7Iq1ZW2TkV7F+5znb33MuHdgdQ1Kxw5NtPa9FrMqFidEgc2xXDIXZIcgaQa8hpaSmV3A+3OeLc4M4tKIn299IRCgQm2Lk1EF/zCbr4JoHKRQZsxAse3MQD7y4Db8Ac/cMWkVF5YLAKmA7S7wW5wZxbFcMDXVawmMaGDiukKBQY6ecyxdMRonD2+M4uDmB6nI/AkOMCCEoyQ3B6hiwIoTl/2ePRrD92x5MuvJs9wzaCfbfW0Z+le37VMXs+YsqYlU6lKyj4XyzaCCN9VpkjQABe35IJia5huseOkRIhKHNxy4tCODskQgURSKxVxUJadVuhXFjvYbs4+GYDDIxybUUnQtm1XvpIAmEYgkUryjWYm9gWyEkjI0yh7fHMfLSvDaPXUVF5aeLVexA5whYk1Fi5bvpnNgbiyQrSBIIRWLTV2lMu+E0oy7LbdexTx2MoqrMn4BgI32Hl7h9YBcCCrODKS8MQO9vJj61mi//M5jCsyEWUyokaiv1dns4t69CSOzbkMj4OdnnRVhBS6zfoypmz29UEavSYZTkBfLVa0NsU0eWf5vXff7KUO58Zk8rg1VaEED+6VAkWdCjf0UroVtfo2Xlu+mcORwFkrDYSSERm1LNVfceISLWMWZVMcOPX6exd30SJqPGbk3TeYV9pqNn97AkC/Kz1ClXFRWVZjpbuNrz3Yf9OLkvBrDMEFktqBAS6z7rQ2CIgQFjih32MRklso5EUletIzSykR7p5bRM8j6yI5bvF/ehsU6HJAmEgLW6vkyYe5Zxs8+1chIUnA1m9f/6U5zTHEctaxQUpSlcwGbavZt2q6/RU13mR3jM+Zt3oIrZ8xtVxKp0GLvWJqMozdNF9ghFpqwgiMz9UfQfVQJAdbmeVe+nk30swradJAn6jSpm1u0n8AswYzZJfP7KUIpzm4ymkGx2signiE/+Ppy7/riHwJDmKbXVH/bn8PY4cDIOb41rS2S5YzwFpQUBFOcEo9Up9Ohfgd5fDVFQUblQsBeu0PniFaCixJ8jO+JwbbsEW5b3JH10sU107t+YwKav02is09m2Cg5rZMatJ+k7vBSAE3ujWfnuAKzK02q3TUYNP37dC0mCcbOb40OLc4P49KXhdqFXFhRz+0rLyR3ghTUZJbKPR2Bo0BARV0dcSm27j9kSZ2LWiipquw9VxKp0GMd3x9qm6Z0hSYIT+2LoP6qEhjoNHz4/ssW0k8WQntgTQ3WZH7f8ej8n9kVTdM6FF1TI1FXrWfluf657KANZA4Xngji8Ld7VCNr0voQitzuxq7zYn9Uf9CfnZLhtmVZnZtT0XCZffaaVh0RFReX8orPjXV2RuT/KEj7gUutJlBcGUl4YQGR8PbvWJrFhSZ9WW9VU6vn6zUFctzCDtMFlbPyqFy3jVe358euepPSrILGXJXv/x2U9MZsktzbeNwThMfWERDS2/QjC4jzZviqVxvpmORObUs3sO04Q16OmIwbqQMvvXxW13YsqYlU6BCHAaHRv3IQAQ4Nlen/luwOorfRzsZ1E3ukwMg9Ec2RHXNM0lysBapkyW/rGIOY/cJjD2+KRZQWlAw1tSEQjwZGNrP2kDyV5QdTX6AgMNhCTXMuQSQXEptRSXuzPnu+TObIzFkODhvDoBoZPzWPYlHwaarV88uII6msdf24mo4Ydq1Ooq9Ixe8GJDhqviopKR9KVYQPOMDRqPNjA5u0qSvzZ8GVvF1tYlPD6Jb0IDDVQURzg9nhCyHz60nBufOwg0Um1nDoY5WJ2q61IjLwsl/0bE8k6GkFlieV+EB7dQK8hZQwYW4RWq3B4Rxx71yVRnBuERiPoM6yE0ZfnEJ9aw9YVqWxd0bPVkYtzgvn0H8O5/cm9RCfWdeCYW+NJ1KqCtnNRRaxKhyBJEBlXT1lBAK6e7CVZEJ1QS+6pUE4fivJwPEHGtjjqqnUejTdInD4UxcEtCdRW6b3Y3nv8g4zEJNfw6d9H0Oy1EJQSxLmT4exdn0yf4cVkHYnAbJJtXoryogDWL+nN8T0xxCTXUF+rdeHBkDi0NYFRM3KJSer4KTAVFZW20d3i1UpUQp3Hh3JZVgiPbuDTl4Z5EJoSZQVBFHgZ46+YJZa/PYAbHzvQgQLWYkfTRxeyeVmazbFhpTgnmJP7o9n0VRpxqdVkHYmyiXjFDMf2xHBsTyyX33acbatSnZ9BSJhMEj8u68n8B4443aazUCscdC3qJKaKTwgBuadCWfd5b779oB87VqdQU2mJuxoxzX2GrFAkhl6Sz551SdhlALg4j0RNhR8RMfVIsuJ5YBLsXZdEUKgBSWpvjJVl/z7Dixk4tshOcLcsw2X5N3N/NCaDpoVIlUBI5J8J5dCWBPdhFrJg53cpNNZrXG6joqLSddiHDnSVgG2o07B3XSKr/9eP7z/tw5nDEQgF+gwtJSDEAC7smiQrpI8porZaR0med40rvI9Dlait8qMgO8Tl+X1DoNObmXPXEU4dsjQ/sNjR1q/6Wh1ZRyIte9kJaKHICAXWftwf4ebWIBSZzAPR5J8JdhOK0bnYXz+r1h9pFXag0n5UT6wKWUci2Ls+kbzToWi0lumakZflEhVf77BdY72Gr98cRPaxCGRZsUg9IfHjsjRS+lag8zMTFGqgtkqPvTfW+hQ95dozRMQ2kHMiDFfeWnv8g4wMmVTA0V1xnt+EkCjND2TOz4+y54f2tf8Miq6h/4yjRPYsZd1LM70Yq+v1QkgIs/v9hSJxZEccx3bHMGh8IaMvP0fxuWDMZpn41OpOnw5TUVGx0JFxr3U1Wg5sTOTw9jgaanWEx9QzbEoeA8cVtSrwf3xvNKveTcdklG1JpPs2JBES2UBcSg0RsfU01GgRknCoriLJCsHhBqZed4YzGZFejy0hrYrw5DIqcsLx5MuSZIWTWRKx/QopPhGLEG30fUmCtPGnSZuUyfGdaRgNskevsWtnh4RQhOcwCyHx0QujiEqoZdK8LAJDjVQU++MfZKLnwHJ0ei8cJB2AWuGg81BF7EXOpqVp7FjdA0lWbN7CAz8mcHBzAlffd4Q+w0pt2y5/ZwDnToQDOE5vCcg+bul2ZcmOlZAkxWbsYlNqGDc721aVwFv8A030SK8gfXQhx3bH4klMylqFEl0+ScOzyd2f0mp7GTMKnr2d9z2YQ9r0KA5tSeF7U9d5RxWzzKEt8RzaEo/92JP6VDLnrmOER5+/ZWhUVC5UOiNsoLwwgE9fGkZdtb7JCyjRUKcl/3+WyinXPZxhE1B5p0NY/vbAJq+i1FSuykJ1mT/VZS1zByzT8Vq9mcETCpg47yxBoUYfZqAEucZi7nkmnn8tDMfksVeCRK/ekfS9uYa3HgWzQUHxWcgKeiUVc+cfGkFO5bUlPbwMT/DgAPAyxKE0P5Bv3h7ksEzvb2LivLOMnpHTZY141AoHHY8aTnARc3J/FDtW9wBwmO4Wioxilli2aCC1VToMjTKHtsRxJiMKobh/crYaFSFkZI3CNQ8e4o6n9joI2B7p3mT6C6oMBg4XVJF6xS7i+7tvNCBrBMOn1DHn0oE88bKRa8ftIABHD+Y4dqDFfbOFUCp59i9j6PvxO1TUdORTuvfTdy0Nd97pED55cTi1VTrnu6ioqPiM/fRuR4YNCAFfvzmQuhprPL/VJlr+f+5EOD8u6wlAWaEldl4I11UCHKfZLaT0L+OBF7dy+a2Zto5dKf0q8M7OSAzq25+QHrX84h9Z6P08hHYpEg/e4c89V0byv6XVDNE6iq8wKpjCBmRMLo8ho3Bvzss88ch85ido8Jc6wpb5ojxbb2to0LJhSW92rE7pgLH4hvV6cxZuoIYc+Ibqib2I2fNDEpIsXAhTSxD9B8+NpLFei8ng+6WimGW+WTSI23+3z6HUyagZORzd6a7uISAJ4kUB73z5LDEnDqM0KgzgKGdJdeJNtXQGGzu/hPJ6i0H/i/5Z3pO2skFMpQF/hnKQdI7zEP/mDR5w6pGVUHiclwkWtcx66wXiB5/kc5b4/L5d4+5G5WYvRaauRs+eH5KZMv8MAPW1WnJOhiEUifie1YRGtr1MjYrKxURnJ2zlngr1EJsqsef7ZM5kRFBW4F0Mq/2+AOeOR7Dm4/5cdc9R25qw6EaCoqupLQnBnZ2RJMF9296j14r30BXkM0H8jDv5wOm2Glkwd3YDswda7PeA0BPcbLyUfQznBP0IpYpLWU8+CQziMI1IrWyrBhOhVPEL/ot/ZimDRg9i4rCD5J3rj8nkyR62zWb6wtYVPRk+JR//IBNCQEFWCFVlfgQEm0juU4HcBZNxrpLBQPXQeqLLROwLL7zAk08+yaOPPsorr7zSVadVcUPe6TCPnlVLGay2GxFFga0rezhkiCak1hLRo4zy7EjXxxYy72bcTQIHmkYCPzCdWXzHSfqh1SgIJBQF9H7w4uv1TL+iueJBkp8gRFRxFcsdDvtPfkUxMXzOTWgxoiAjo2BCx70s4mmes207NONLpgVs40fDeMxu41qtHlt3Exvu4rs8IxSJQ1vimTgvi/Vf9Obg5oTmIuOSoM/QUmbefuK86KOu0rWottU7uqrOa+6pMDfOASuWKgFtR+L47liKrsgmNtlS1SQjv4rh1+9ly5tTXe6lkRXmSN/S/+2/Nh0FFvA/ckjiD/zFYsFkCUkCk1lmyrB83vjFRgy7LV5W+eQZ9MAI9jOC/bbjppHFKuZwNcuoJgS5ySaa0RJJGd9yBdFYQtMko5GHd/+cxWz16n16XC8JZFm0uemC2SRxfG80EbH1rP2kr8P3EhTayJRrzzB4QmGbjt0W1OoGvtElInbXrl0sWrSIoUOHdsXpLmrMZonM/VGc3B+NySATnVTH0Mn5Tj113sVQtfMpWMicOhCNoUFG728xbBn5VQy5Zj873r6UxgZaxUZJKNzMpwxvErBW0sjiCANZzjxWaK+jaM71DBguuPIGI6FhArPd7H/DgEGErltrUdF26DHyGTfza17iQ35GIXEkk8OdvM8QMlq98/fqb2Zi6GEKa4IcYtWsyJhIIhcdBk7T1+PH8YTfC7zc+GuUNvz06qp1fP3GILKORDrGggmJU4ci+fQfw/nZ7/c69D2vKvOjqsyPwBAjkXH11FTq2L8hicM7Ymms1xIRW8+IqXkMGFd0XvYvV3GPals901HitaLEn0Ob4ynND0Tnb6bfiBJ6Dylt5amTJOHl82o7baukcHRnLLHJZ8jIrwLg5ltSMOaWs3N5RKvjy7JApxh4lqdanfkpnud2PuZd7iIjehz6OD2z+u5ieHwmxevA2tBWbjQwSJaQldZvcBobySGZj7idzUxGRuEy1nEziwnAMZ5/Att4Svs3/mr6PRIKooUDwLrser5gCdfbljpFSEQpxUwN2sKS2vlefHCOyLIg/0wI33/SF6XFvai2Ss+376ejmCWGTi6wLTcZJYpzgxEKRCfWofMzc/pQJHvWJVGYHYJGq9B3eAmjLsslskWCtC/YX7OqmHVOp4vYmpoabrvtNt5++22ee+45zzuotJmqMj8+f2Uo5YWBTYlaEpkHYfuqHlx2UyYjL3WMK01NL+dURqRDtmtnIITEwbMN+IdaDNmcSwdSXm9kcPpZlvw9gaIsf9u2skZwH4t4xfyo02NpMTOfZcxvXIbpeg3KDTcAdvFVVVXIL/8dzWcfISmuY1rHsJsx7PY49lSy2Zs8l5dC/sg7O0ZSSTgWz6tMJKXcz5v8in+yn+HM4Ae3x9JgJqGxkFiKKSDB47lb4h9o5Mxh5/V1hSJTURzAgU0JjJ2VQ+G5IDZ80bsp4c5CZHwtNRV+GA0am5eo8KyWbz9I5/COOK576BBanSpkLxRU2+qZjhKwu9Yms2FJLyQZhGIpi3dkezzRiTXc8NhBgsOaZ0BS0ys6tFa1KyQJ8ooFGflVTBhveYAurzfyxn9k/pPayEdv+2FotM4ASaQFF/BB1XWMaOEcsI2bbP7EszQYItkzfSEANSTa1ofmnCVxzw4kxfUkfwg1PMCbPMCb7scOPGd6ipRRBj7aM50tTEI0HVFC4VLW82te5gpWM4Yd7Gas2+PViUCuqv2SJfguYhVF4uzRCMt31up7s3x+65f0ZsDYIjRahe3f9mDP98k0NLX01erMhMfWU5Ib7DRBev6Dh+k1uMzncbVkcEKo6pl1QqeL2IULFzJ37lxmzJjh0dA2NjbS2NjsMayqqurs4f1kEAoseXUIFcX+TX/LtuUAPyzua+uEYmX05bmcOhTd6WPT6hUumdYDrd4ikMrrjcwfloh5iMI9VzVwaK+Rk8c0+PsLZvhtZOx9D3o8ptBoYPtWxMxpzQvLy9FdeS3SyUwHD6y9wbVKNG9vMRIQW3yYF/SP8BKHMaFBi9n2r5X+HHfqUbDHjJa+nORu3uY5/uDDKCzenaAwI40NrpomWBJKDmxOIHVABZ/8fXirEIiygkC7d2XdxxpjF862lalcck2W12NS6V5U2+qajox7Pb43mg1LLF2wrPbU+hBYWhDIV68N4We/32vLcI/rUUNSnwpyM70rJegaT/GgEv2HBDJhfF+uGtLcantATBCv/7GYvz0m8d0P/lRkHKdfSiXT/7sQbdUpt2eUgICKMiSTCaFtlgdxh/bS54eVCElCarKiHRGtennAZu7jWRRr8huW48t2ruwR7Gc/IzDhPBlMwkwfMrmK5ehpxIDzTpCu0GgVqsrcdS+TMNRryTwQxamDURzd6Vgpx2TUUJJriW1umSAtJMGyRQO5/4XtBAS5TnzzFrVUV2s6VcQuXryYvXv3smvXLq+2f/7553n22Wc7c0g/Wc4ciaQ0312MlWDtJ3247Xf7bF6DHv0r6D8zg+NrBuG7ObKYMFlSmqZgnO+v0QiuudHItaMca72aFYV0TTXyD+sYvHkrCIGYMN77YSgK5rJcDLubvZ9+/3oH6WRmKw+s/SGNQYFoGxrArHh1KiFJmCLCkYrLEGATrvYCFiCZXGazmjVcjtmJsZUwE0cRs1nNGHbxJg9QSpQT0dv61iDJCiERjej8zB76lltimH9Y3AezWXYSk+e+nu2+DUlMmHtW9cZeAKi21TUdHfu649seLuuRCkWmMDuEnWuSGTuzuVTTVfce4f0/j6a+RkdnCVkJ+M1DeuKiw0jXN1diEZV1aI7uI/y9/3FzaTkiIowq/UhMJeUuZGDLM0oIudnO+FWW02fdKkt9BLuuAfajUiSJhrAIiwD24d0Z/S0P1s2itbXtuZe3eJt73RxF4gHeIIwqnuY5nuEvTrZx9jlalg2dnM++De5ri0uSICczrCkh2QeEhMkok7E1njGX5/i2rxtUMdtMp4nYc+fO8eijj7J27Vr8/f097wA8+eST/OpXv7L9XVVVRUpK15e/uBA5dTASWVbctCeUqCoL4M3fTiAorJGkPlWEDzlJr4ln0Nb34PDmEJ/aCsooPMOz/FL8k5ukL1gtrmi1jUYriImBfzwnkxgThKgstq2TTpxEe+sdyGezEZIEQiC9+TZCo/HqCV8Sgpr0AZhKLcZbqqkl+IctbkMIALJnTKUyNJXe678lPOesx/cpCUFBShLhJzLxdEt8hccYz3aqCHEQshpMSAje5edom8Tsj1zCtXzFUQbaYpOFkAiNNlJbpcVssH6PgtCESmSNmcLsSNz7PwT+gUZyT4V5fF/OaKzXUl4UqLa/Pc9RbatzOqPqQF21jsJsTy1aBZu+6s22lamEx9QzcFwRQycVcOtv9vHfZ9xPgzsjlEpO0ZsdjOV6vqQBfxx/8xYb8Mxvq5kUmYNybG9z4UAh0H+wBM3nKyw1AppEZ/QHSzD5+Xm0rQIo79kb7ERs/KG9bscrkKiOT+LQjXeSvGsLybu3ojU02o3U+XkaQ0Kp6Nnb7bEBRrOHR3iFV3kMayiXFRkzU9jEXbwHwNM8hwktz/MkRnS28A+9H/iHGqgq1tv2DQ43ExBbwuFd7lugg8U2F2UHOYQL+ELuqVDGXO7zbh5RxWwnitg9e/ZQVFTEyJEjbcvMZjObNm3itddeo7GxEY3GMSLez88PPz/fpgJULJhN3v2wLO1c/Tm+Rw+7Y5lycwkvvyy45QpBVQUesvAtaDGSRC6P8iqh1LJKzOE97uJP/JFzWHpZy5LgqtE5vDzqQ5L/U4oYPhR5VDr1Z05AdQ1B9/4OqbIacHy6x2y25fG7lmpQmxhPTkERFBQBEJhXQKzZ7GKPpv0kCU2Zkfq0GDKuvwP/ijKiTh4lZedmNEZD6+d0SaI6LpFzAyZhMAcSci7P7Q2gHyfZxRie5Hm+4lrMTT+vyWzmOZ5mMlts26ZznMMMYkPaArbc9ira4CDSRtSRPthMQ53Ma4srMZskzh0IZvPXEQ7NI1whSZA6oJyMrb7H21qxdgtSOX9RbWtrOqvygNljCSiwWipjo5binGA25gaz5/tkbn5iPxPmZrNtZaqL/Zxbub/yFNGUMpdvyaQPj/IvlnKtLRk0KaySJ8d8w4KMD6m4o5rKPmkYgy2zcDF7D5K4zbl3XtvY6JWXNGf0RIe/I86ecrTRLZAQBBcXgCSRM3YyuSPHE3Yui6Q92wnPOeP0XQOcnjYbY2AQJp0erdF9/e5/8Uv6cZJ/8ARn6QlAOOU8wBs8w5/RY2waCzzLn3iEV/n8Fysoih1ESrKZa+Y2cE4XwPHDDXy9uQpDo8Sat+IoyYyzm7FyfdfR+ZkwGeQ2CViJzrerF7OY7TQRO336dA4dOuSw7K677iI9PZ3f/va3rYysSvsIiWxwmj3vkiZBtGlxNNdMK2PL6mIe+5U/azeH2qbNIiMUoiLMnDytQ2oqmSKQGcNOFnML4VQClh/pz3mPO3mf/QyjlmD6ipPEby9EbAdkGUlRUGIikZ96hMrPVxFcUeXUXLT2N7T+26zTYVa0RG85RMHQkdRHxhBQ7UUJFCFQNM2XfEN4JLljJpE/bAy9Nn5H7JEDyE3GWpFlitKHcGbaLIRWS/GAoaT9+D2y2eRWXCeHFvNZ1U2UE0E+CURSRgIFzneQZSaNKmbsXefQhloSsKSwGI4W1/Lrn4fw0rvVbP46vGno7o2nLCkERzZSUeKdZ87Z6IPCDETEqi1uz3dU2+pIZ5bOCgwxoNObMHpdJ1sCAbXVOpb+ZzB3PrObgGAjm5enYKhrfoiISW2gskiHoV5j6yQYRA1/5SkW8h/bdknksYSbKCSWk/QlkDqGVR5A/l5BSBJBQOLWneQPHcWZSdMZtOegu5HZbGjLPAHrsrqwSJL2bMO/qoLifoMQWi1+VVWeZ8fsWl4JrZaKtD5UpPUhPCuTXutXE1jZ3OCmISyC09NmUZ5mSUbLHTWeHts3uT2+DNzr9y4PNL7BKXpjQksvTuPnonlNhFzB7TP3QWgmAPqg6aRTB30lfjMwmDnT/KitbBly5XoEQyYVsH9DIu7dK84RwuJc6AouRjHbaSI2JCSEwYMHOywLCgoiKiqq1XKV9lFdrmf/hqQ27SvLgi//I3H3cytY8ns9ZwuDOJ4dRpC/iSlzo9HrBUdO+rPx2vegwcBkNjvUB3Q4FoKRLdZJYEuykkrL8X/ir8gh3hX4Nvn5IZkVtCYjQpIs2atCQWM0ElaQQ2hhLkn7d3Jm8nT0tdVepEFAZWLrKVRFryfz8ivJmjydkIJcAKrjkzAFBNq2Mfv5ceKK+aSv+MJldJXZz59jM+cz9MsPiRTlROLacImm16mAYJJPWKYD9aOnIyqLSTfXU/Lfzyh6cSIa4p3G2LZkhliDX3UDK0qv8ritK/wCTBRmh5CQVt3mY6h0PqpttdAVdV93rE71QcA2IxSZ0vwgDv5Qi9/go0zqfYS0yGEY6mViUgwsuDyKhvoG9j6zmfpP1hFPAVfxDcE4D+WJo4g4ihyW2XtHEw7sRl9dZZvGd4XVbtWHRxJYYUnyVTQaNGYzAgiqLCOwspyoMydJ2fEjR668CV2j+xJRltAA5yFMFT37sPfOhQQX5qOvrcYQFExNXKKD6M0dPZGIrFOEFOS6iFqFvKGjQZKIP7ibviLT/XgkibL0vuRu2kv8hDEERgXacicGBCez91efk5/5httjWImihPs1b/CPdb9p8iC3Ib5ZguoyP0xGqcvyDS4mMat27LqAqSj2Z92aCAoOJ1BX3bYEAkWR2HYolMCbH6Zh+hRirp1HTK9iAqMCMWcXUQ+kSTBEfgOJtte7A5AUgSxMaGvqvClhja6xkW33P4GQJEZ+tAh9jaP31mrE0zb/QFlqL0vmrJtpLwBjkGsBbQoItHkHnFHaJ52DN91Fj63rCT+X1ezJkCSK+w/i7IRpNIZFkD9kFAkHd7v12AIUDB6JMSCA0ys20mveVAy7fyCgUUJz50MkVVSyg3KPArYfx1jJPPQY6GnIclsdofUoHL0QZYUBfPL34Vz7UAZpg5oFuGKGwuxgju6KpTgnGK1OofewUgaOLbTV/lVR6Uo6U8A219qO8j2Rxw4tRiYv2c6dR1ZieO4v1I5zFHrDw+oYOXg/WukVj3bLExIQdfqkV9sqkkR5Wl/2TZ5O7NED9P1+JdAcaWqtPuBXVcmAld51LKyNdFPlRpKoiU90uVrR6si4/mck7tlO0p5t6OyEeGNIKOfGTaFw0HD8qiqIO7wfYTK6vX8YgoLJGTKRGl0iNIVWxI8bRcRnS9CvXMduFnqsJAPwAr/hl7zCQvNrKMgetm/p47azr0Ji+7ep5J4O4/qHD6HRNn/X9TUaTh6I5tSBKBrrdUTG1zHsknyHDpft4WIQs10qYjds2NCVp/vJIgRsXtaT7Q5Zs+0rdiLVNxC4cg3aU2eo+O0j1JU6TivrU1PQH2+d+e/zeYRAYzJ6PSkjNBoizmbiX13pehtJIqC8zLOA1fthtPOutoXqhGQOX/czJLMZbWM9KAom/0CHcjRnps4kND/HEifmhoSDu4k5nkHW3BmcXrGRhMEDCH7iGaixfPZaN73ILQiSyKMPp3iNhV6N//rbG9i2WyH3mJOSMkJGQbDy3XQeeHE79bU6dnybwoFNiZjNMvYG+nRGJN9/2ocRU/OYMDebwBC1U1h3crHY1s72vpYVBPDF/w2lqszfy2Ywnkk5th9uuArjJ/9DXDbNYZ1R34iunQK2Ge+PI2QZIcsk7d3h0hbLQiGwvASTTofW6P73XZXkKu7XOxStjpxxl5AzdjKywYDG2IjQaDH5B9i8to1hERyddwODvv7E7bF0NdUM/+w9CgcMJXPGPIKVQsS/30a3ax/gjV21MImt6DHyBTe6LO9lRe9vZup1maz9uH/TEsdPVAiJ7GPhHPgxgZGX5nF8TzTbVqVSnGN1qli+hXMnwjiwKZHwmDpm3JJJz4Hl9k7rNvNTFrOqJ/YCZN/6RLZ/azEa7S2qrcHERLZaSpwI0B89geGDxZQN7O+wnRIUSEI7BawVSQiPAlZgEYyKTkdE1ikUWUZ2cX5JCAKqKlBkDShml9mwBcNGO2Tdtgeh0WAMdO7VFZKEvsZ1HU778WkNjfRavoY9d9yP+YPFYOelvoJVLOYWlwZURuEKvgWgliBkFMwevAsLrqph6eIoXD5CCIn6Gj2HtsazdUUqdVV6u2vM8V+hwN71SRzZEcdNjx+wtb9UUekMOlvAGhpkFv9zWNOsVvttqwkdU9mIpFjiV7UPPkTtB/8CTfNvtC44Ap2/H9oG75Ku3CEkmcagIPxqqt3HlwpBec/e6GtrCCwrcXtMRZapi4olpDDPqZNAYLGFRQOGtG/wViQJxc8PxUUSor9dbK0rrJ9u7NGDGAMCyZ4wjZj9GbbPZAbfe/TChlLBKPYAUI+7GrIWEnpWUVkc6LHd8L4NSdTX6Ni6oieODx2OtrWiOJAlrw5l+NRcZtyS2SFCFlqL2Z+CkFVF7AWGYoYfV7SlNI7z520zWh7nZbslEuGHT3F22KUAhGWfIX3lF+ga3cda+TKKhrBwKpNSiTu8v+mMrZFozpKVFMUrJ8OpS2c3F+S2M7hCkqiNjiVnzKR2j98b/Kor0dd7lyAlCYFsMpJwcA/B2Y4d1X7JK3zCbbQsKwOW0jLB1NhKywzkiK0agis0soJych9mk/taL7KssHttEnXVOg83csu6hnotX702mIkPfY/soXVtZ/etV/np0RWxrwBHdsZRW6mn/SX8LaEE6RxjCpuApgf30nKK3/yU6tRkUBRSV68j9szZDjibBVko5I0YS+rWjWjMzr2NAqiLjqUyuSd+1d41vKiJjUc2mwgqKWplVxGCk5dfidnfs9DrCEILciyeWS+81xKQeGAXVQnJaOw8yX04xVV8zUrmObWZEgqP8qqtVW46xzjEYATOEyYlSUEKr6AkP8ytgLWGbFkErHWE7tm/MYm4HjUOLW87gp9S96/O7Teq0uFs3StjqPU9A11CQbIr0K9tKknyDM9yNd/YbScIqLQE/Ifkn2PwVx+hdSJgXZem9kz+0NFkzphH9rhLLIbQDquv9czk6ZT1tniDq+OTkIRrL7AA6sMiKBw8gozrbqcyuXlqy+jnT87oiRy6YQFmfReVGPLxsVkSguiTR5GNjrFeI9nH/7gDLWY0tikwgYyZIGpZxRyiKQXgCr4lgTxknJcZ08gKV0/OJinGs7gWQqK8KND7cjJCorrcn6Ljccy5dKDLF2Dr8a6i4g1dJWABTu6L9lG/Ctvvsvl3pyChEE8By7i6VXUVUStRrU2g59drCXcjYK2Jn+CdjRVYbF3+sLHsu+2eVjGq1mM0hEdw+OqbQZJoDA7BEOiuQQ7IikJVUg8O3bCAnNETMfo133sqk1LJuO52itM7yAvrBUKS8TyP14xsNtuSde35gDsZ3dR23PodWu+JN/EZz/Bn27YP8RruG8XIpIw6S73SAB5CUCRJIPlUbkuwa22yN5rdZwYnhNp+V/Y1li80VE/sBYbZ6Fv5HAmF2/iYF/gdi7iPr5hPA/6MZRcP8RoT2dZqH5PeYqj6rl7WdAxnx216qo+Mxq+mGo3RYGlY4GYsQpKoiU2gYOgokCTOTZhG7qiJJBzcTURWJghBbUy8rWyWleL0wfT88XuntVyt5I0YB5JEZUoalSlpaBobkU0GjAFBHRZC4C2NIWHUh4XjX1nhtbmVTUaqUpIJKC9FthPst/EJk9nMIu5jCxPRYWIW3/Fz3iWK5hbCWsx8zG3MZjVmhIOHQSMrxIbV8YfrfyQ+oI6+yZVk5oa69LJaDKaPQlxWCDX3hSZR7Yw5lw68oI2lStfSlQIWwGjQeN3wRZIU/EUDW5nAOXrwJvdzjP5EUMHtfMRdvEcYjg9sEmDy8ycs+wxh+e67NwlJojE0DL+aauSmygEuBW+TZzLz8nkIrZaGyGj23fEAIXnZxB/ci19lBWZ/f0r6DaSk78Dm+H1ZJn/YGHps3+g8VECSMPoHUNpnAEKj4eykyzg7YRq6+loUrR5zN9QdruiRRtyRAz7tY3Qi1MOpZDOTWc6VfMjtFBFHL07zC/7LFBzLfd3FeyxlPt8xCwUZ6zchSwJFSFy2oIhpVyaQEAafH3Zzr5GsoQa+2FaJsoIgGuu0+HdA21pn2HtlL0SPrCpiz2OMBpkDmxLYvymRqhJ/NH5GxkxvetrzwtjqdQoPGf/JCzyJDhN/5o/8mT+63UcARQOG4F9e6lDbzxkSoDEa2P7gb9A21NN3zTdEnj7h9Cdq1ukpGDyCsxOnoWibYzwVvZ7c0RPJbVFg22FfvR/H5t3AwG8WIxTFVsvVGjZQ2mcA+UNHOe7j59ctRhYASSJ31ET6rFvl1eaKJFETk0D+0NHEHW1d5zGVbP7GUx6Pcykb2MpE/swfWMGVKGgI0Bq4cepJHp+/h9hwS3WJx+dt5/43Z7k4Shsf+YVEB4VMq6h0uoAtyApm9/fJnDoYhdksEZ9ag87PDJJiq6Htjv7BObxfexPDlYMM5yBXssLjPopGQ1laX9K9yPiXheDMlJmU9e5P9LEMem1cg76+OebcXtRWxyVyduI0Knv0cjhGdWIPqhN7uD1PzuiJhORlE3H2NNgdU0gSikbL0StvRNjXHZZljEGeOph1HiV9BtAz6Af0dTVeV3SoTEmjvEcvwrJPO0w9azEzn6+Zz9duHxK0mFnG1bzM47zKI+RjqbQwpFcZT/xOYvAMM+jjuSIdfnynkqKiICdhCqLJtHZU8EjHciELWVXEnqcYGmQ+++cwCrJDbBe/uc6PbSv1yDIIxXkHJ1kWREXBK6+YmVn4IdG/esLrcwpA0WrJHzaaoJJij9sDaBsscUMm/wCOXnUTfpXlhOVmA1CVkGyJBTObaQiPRNF507nbORWpvdh32z0k7ttJ9MkjyCYztVEx5A8fQ3H/wV3ubfVEwZCRBJYVk7h/l8fSX7IQ5A8bTU1CEtljJ9Nj52aXxcg9mcBR7OVr+TpqlQDyL5uH//wJ6ANl8NNTsG0XCMGCXW/QwCqe4B+Y0aDBjEBqSiATtCXKSAiJM4f9Ucwge5gsyMivUmNjVVzS2QL26K4YVv53AJIkbG26806HeGwoAjB6TjmP3m3m1ntGIVe7T4qyRwC5I8Zh9vPHr8p1pRV7dE1x9SXpgyntO4Dw7DPNtVZj4tHX1WLyD6AxtG1tpsGSlHX0qpuJPXqQhAO7CSgvwazTU9J/EHnDx9IQHtnmY3cGQqvl8PxbGfzlh7bPx5VNVCSJ2th4amPjyZw+l2GfvYe2rsbBunlbJUeHid/xIk/wD/KDe1H32F0kDI2AwEBkZTRafQTSgd3sKHuUK1nKAYajxYiEwEjbyl82jxCKcoLo0d+766atXKhCVhWx5yk/fp1G4bmQVh5XRZGQJTOyUBAotlaEYCkdotcKlv5xD6MvS0ReXNbysB6piYnHGBSCsca7OnUtY6oawyIoCovw+bzeUB8Zw6npczk1fW6nHL9DkSROT5tNcf/BxB/cQ3j2afxqa5yK07xho6lItXhRsideSm1MHEl7thFaYEn0MgQGUZmSRkBpEcGlxS4FsQDQyBj690ETEU6v3avQrPsMgOrkRORxlxHUWIz/ngM8ygFu4VM+5GecphcCeIOFtCdMPueEP/s3BjHyMtdVCtSQAhV3dLaAranQs+q9dIRw7ILXUsBqMNm8aZaaohJzJ+Xz/B+K6NcnFszu26S2RAJKm2L8jYFBUOHZNjeEhjePT6OhPK2Pw3pjcMd4RIVGQ+HgERQOHtEhx+ts6qJj2XPnQmKPHiTmWAbBhflIQnGQiYokYdb7cWLW1QA0hoWz77a7Sd69jbiMfWiNBhRZpjYmnsrEZJL37XR7ToHleyvv2ZuwqhKSnnsKCVCCgzDOm47hhrkE/ulVkpVs9jGCdVzGSuZiQM9eRrCTsV41rWmNxX2x5uN+/OLZXR1WpcAVLWNkLwQxq4rY84yM/CpMjRr2b453memoCA2g4VqW8D2XU0UYOgzczKf83vA86Q8dR/wpCuXGq30+v1mvB6A2Nh5DYBD6Ovdlk/JGjvP5HBcT1QnJVCckgxBEnzhC0p5thBTlA1AbHUveyPEUDRjqkAxW2ncgpX0HIpksMVDWGLaYY4fov/prl+eSgOPXziPtwGH8t+5yyOANys1n8JcfUR2bYPMMx1LM4/wTgHVc2iRi3eHebyHJgi3LQ92KWBUVV3RFDOzBzQlu4xIlTPThFDGUsBVLNZM+ZPIYr3DflkXIExRM40ZQFR5OWGW1j00KLOfMHzqKsLxzLrcSWMKv7BNULyRCjJaH72qd6wYH7cXs50/+8LHkDx+LvqaK5N1biTu8H43RiFmrpWjAMHJGT6QxLNy2jzEohDNTZ3JmyuXIRqNlZrApnjj61An8qitdxgaX9u5P0YChDGjRsVGuqUX/2XLE6g1oKppjoKezjumsA2Aim9soYK1IlBcGknc6lKTeXZMYeyF5ZVURex5hzdwenjaEtUbPX833zODX/IM7eZ94CtHZF3EuKUXz+rsocdFIxWVeNimQqEru2fRfiVPTZjNg1ZcupUtDSBiFg0d6cVwVJImS/oMo6T8I2WQEgcfwCvsGCgDF/QcTeeo40SePWg5p3a5JlGZNnEZodi66k6daJcnKQiCAkKJ8p99lJN547d27AYQiUZzTHmOtcrHSVUlc+VkhbjO9BVpO0o90jrGGGYxjJyE41l3V7thHiF7nVZknKya9nrroWMDykFq/bRP+lWVO26wCZE6fc96FSFmxilRnxE8YAzS1QG/qltWROBPGhuBQTk+bzemps9AYDJh1OvefnSShNDlrrH8fv2I+g7/8EMlstuVcgMWjawwKJmvSZQz/5B0QrSvMSkLgV+FaXMZQgozJYda0LVQU+3eZiIULR8iqIrabqC7Xc2RHHNXlfgSGGBk4rhCoYs6lA8k95d0xqgjjTzzLZ9zEj0whggrbOtuTYmEJxrgYtIXFDstbYomH1VAwaLhtWWm/gZwwGuizbhWS2eywbXV8EhnX3u4Y9K/iFfaJbT4hSRy/4lqqEneTtG8H/lUVANTEJpAzeiKlfdIZ884rLnOzrHG1zhjGAfpygkz6uC4ELnlKThBUlmr5860pjJpew+RrqgiLcl7yS42LVbHSkQJWUeDM4UjOHo0AAUl9KukzvBRNU/1ijUZx/0MAQOJb5rCCK3mHu/l5Uy3m5rUgG03UxCYQXJSPkGSHiiItEUjkDx1te2gVGg0Hbr6LQV9/SkihoyBUNFoyp8+hpAvLVoFzYWovGFuut4hV93izjc84Eca2cUpSm5N5qxOSOXDLL0jeuZnoE0eRhYJZp6Nw0HDOjZlM5JmTbqvjuHu8v42P+QY3s6JeJmr/sLgPR3fGMmJaHr2GlHV6aAFcGEJWEqIzKpB1DFVVVYSFhfHIKyvxC3Bfz+5CQQjYsrwn21dZskYl2dI2VijQY0wWj7+oIAQ8c0MqVWUavAkI12DiLt7lbe5rfT5ZpmRwOg1RUYQezyKwrARdQz0KkqVLFxZPnpA1HLnqRipSe7c6hmwyEnXiCCEFuZj1fuQPHY2hHckEKh2AEGgaG0CWbfVvNY0NTHjjH20+5FKu4VqW4qy5AkC/sdWc2BmM+0chyzpJFgQEKTz8Sh7JfVrHD65af+QnIWIb62t59bG5VFZWEhp64bwfq239+6p9BHRjtnlHCtiywgC+/PcQKooDkDUWUamYZYLCGrl2YQbxqTUc2JTAmo/74mXTa2QUTtOLVLJbr5UkDl7/M2KPHbbEvFdX2ma8JJpnSMpSe1uy/LWtfUaBpUVEH8tA19BAZVIKJf0H+1xn2hdceVGdCc6CFoKxU0RpB9BynNC+UAbJZEJjNGDy87d5dNM2riHhwC6XXSOtOJu1NKJlPNs5wLBWVQtkWRAYaqah0Yyp3rMAl2QFocgMuySPy2872SVCFppnibtSyNbXVvObOSM82lbVE9vF7PkhiW0rm2OdhLn5Ksze1ZPlb1eQOqCRoDAzVWXefT1mtHzIHbzEE61qE6Io6GpqOX7ZdTDMsii4II+EA7sIzTuH0Ggo7dWPgiGjHOKHHA6h1VE8cBjFA4f59F5VOhFJatUlR9Fovc62dbbdfL7mY25lIf+hggg0koJZSOg1Zh6Zuo2bnwjiqnuHU5gHZrOzszQvE4pEfa3MW0/G88dPs9GolkalBR0pYBvrNSx+ubllrGK2a+1arePzfw3jukcOUlYYgKwRKGbw/EuRkBC8xb38ladbrxUCs96fU9PnAKAxNBJ79CCxRw6iq6+jPjySgiEjKO2d7nJ6uy4qluxJl7XlLXtNW7yovmzXEQRGBVJX6l2Xw5a0HGfBtl2t3rMvolZotZhaPHAoWq1X1QedXVE6TKzlcm7jY1ZzhaUxhiyjKBKpYfk8duMa1mmms+x1z504rQ1oDvyYSEJaNUMmdWwnL1eczx5Z9dbShZhNEttWuQvWl/h+cTgIyceuHtCIP0cZwHh2tDikREOgY5mUmvhETsb7nvSlcn4jtFrKU3sTkX3aY8KJq9v3rXzKtXzFMq4iS9uXWGMeVyvfELG+AmmdwvcTb+XGsHfJyPBr6hPu+mhCkSgv0pGxLZBhl7TtBqXy06SjY2AztsW7bBkrFJnGBolPXhyBJNOU2GXfE8u1mDWjZTejXa432T1ImvV+5A8bQ/6w7vdY2ou489GDGhgV6HJZW8WsFafvt53e2tLe6aTs2uLVts4cBJGU8y1zOEo6a7kco9Aznq1MqNyJvMjMPcGhLLzsaz7aPBWjQbILMXBxbUqCXd8nd5mIhfNXyKoitgvJPRVGQ62HeMim2JjWlQk8+9j8aN0eVhLCUkdV5aIgZ+xkIs6e8toj6wx/GrmJLxDGpmPY6eH0HZ+xfdBRvlq6jvXf+/Pef9y3QJY1gqP79PQYbalxGBFguf6tpbZ+CiEFKr7RGUlcx3fHuN9AWIRrs121L3TnGgkz/jQ4OZxEdUIShpDz7/q1CtjuEK/OxKkrAvoMaLWsPvNoh4lZe9rrra2JT6Q8pSfhOWd9rEjhyACOMYBjzZddU3SCf00V/103ncm/e5sflCvZtDSMnEy968tTSJTmBWFolNH7dV2XmfNRyKoitgsxNLQnCcptQ1cSyGcIhxyXShKVSakXbKkWFd+pSurB8Svm0++7ZW4rUnjyQbkSwZLZTNDBfdxsWEPsglmeRawE/eKDmT9Mx6dbC1j9eQRblodSWaJB659C8aRCRs/IISTCt7qbKhcmnVWFoLHBm/wBdw20XafszGvRjcv62zk74VJfhtiptDVkoC14EqrOxKm3WPe1F7P2dJSwdSdqXYnZY3NvYODyzwjLzfZwxfiOJYYarvz4b+S+NZHTGf7kndY3hb242a/pZNnHw9i1NoWzRyJQBCSkVTN6eg79RpZ0eNzs+SZkVRHbhUTFd9aUqsRveREtZgdxUtq7PydnXtWpiQIq5x8l/QdTkZLGyP+9ga6h3uWt2x1uH5lkGfnDD5jy38n07BnK2bOWjl3OMJkkxkw0UlIiWPRIKmV5+qbKRBLGej171iVxeFs8t/xmH1Hx9d69QZULks4soxWTVEtpfqAtZtB3WssSDSaiKeFWPnHYwuQfwMnLr6QypWc7RtwxtDdswBfPqT2uhKo5PBEPusvL47tac9Tp0o4KQXAnZs3+/hy6/g56bNtAj52bnR5HSJLlOhHCqQ11K36FIObcaW7Ul3NgcBjKKte/E0kSxPWoRqdX2Lchke8/7WtL+gLIPx3CN6cGMfKyHC678VSnCdnzAVXEdiIVxf4c2hJPWWEgfgEm0kcXk9S3grxToS6MrXeTwFqMmNCixYQJHb/knzzCqwhJoio+mZL+Aynv2ee8axmo0nWYAoM4dOOdDFnyIbo6S/c1CVCaygHlDxmJpCjEH97v0BbXU4tcAElRkE+eQLt8Ob+mkofEb5xup9EIeveGu67z484FGioKpFZiVygyDfWw/O2BLHh6j/q89ROlIwWs2SyRuT+KUwejMBllYlNq6D+qmKM749p4RAkJBQnFVrVFQSaGYtZyOUFYBNLZCdOoj4qmLK1ft5cW9Fa8dobX1J1QlcI8hHV4gagsxhzeLCA1Fc3v1VMIArRP0HoUs5JE9oRpyGYzyXu22eypxWJKmPz8ybxsDn2/X4FsNDqUXvM2CMHv0H7+VfYFm6XfUSKiWlU0AIvTYOysc5QWBPD9pxbFb68prB3o9q5LpueAcnoP9b17pycGJ4SeF95YVcR2ALVVOg5uTiDrcASKkEjpW4lilti1NhlJBoTlyenQlgRik6uRNQpmpyLWU8xrAx9xKyu4ijIi6cVpfsF/GUKGZQMhyB09gbKm9oYqFzf1kdHsueMB4o4cIPrEYTSGRuqiYikYOsoWYlKZnErivh0EFxWAJFHeoxeBpcX41VS5DTXgeCa6u+/nAUkmg2De5MGmhysdEgIkiI9TWPpRCcWnBUuWxLmoaGAxvsU5weRnhZCYVt0pn4VK99Ae8SoUyDoWwaHN8VSV+hMUZqDnwDJ2rU2hsiQASVZASJzYG4MkC1L6l3HueCTOnQGuHQQazDzIa8RRxC7GoMfAFXzLTXxGIPUILK1Oc8Zd4vN76Gh8Fa/tmdq3F5L2OBOqR4ubuvRZ//WCATHOy2baH7+loLXHKm7t32NHxdQ6fLZ2SWHVukSQJLIumUFp7/4kHNhNUHEBik5PSd8BFA4ajikgkJq4RJL2biP2yEG0RoOldXhSD2JOOvck25P660dBCL4T65jOD5QTgYIMSEiSGSE0TJh7lv6jSlj3We+mBFsXHehkhb3rkzpFxFrpbiGrith2cvZYOF/9ZzBmo2ybJs07HWqXoGXZzuqBKs4LxvtnsmY0mPgZH3I9S7mepa3WC0miMTgtXxR2AAEAAElEQVSEsrS+bXwnKj9FzP7+5I0c57I9cPGAoRQPGNrcfUiSSNy3g7SNa1we095cykLhdRZyC4t5k/vJYDBhVHKTZgk/m15LUNAvWLcrErM53sNIBQWqiP1J0R4BazZJfPPWQDIPRNumSSVJkHkgGqv9dPA8meHc8QjcRHO7OJMCCH7Fv0jlrMs9c0eM9/k9dCS+hA34KmB9EatgJ1hboPGxw9iJ0nrMHuquDohx7dm1eoOdeWo7MkHMlXe2OjGF6kTnZbEaw8I5fekVnL70CksHDllGMpkIzz6DtrHBvbvKZEIChnGQE/TjXX7OV1xLLUGMEHuZF7Wc7XHjgPHknQlxG0IjFJn8M51XB/p8iI9VRWw7qKnU2wlYu8tSuE4WcNe32xlSU/riMA7wMo873UZIlmmMI1fffN62KlQ5z7Gbxy8YPJLULevQmExudrDbFZjCj0zhx+aFJhAfSZiO70Fc9zfA8+yARtt1WbYqnUt7wwd+/DqNzINRQLNYbbax7hK0PNFsl7UYUZB5nzvpydlWW1pbfuQNHUXRwKE+voP242uyljvx6kqoWvFFsDoTq0sPuG5Fa8/8YY7jcCd8zYri9PxWD651zN0lZr0u0dX0HoVWS8GQkaTs3up2c/urO5Jyfs3L/JqXbcuUUomr31/OkzyHVjcMT2GIsrZz+1l1d3ysKmJd4E1bzIM/JrQWsDbaF9wXRTENBJDKWe5jEXfzDoG0TnwRkkT2mMkUDBuNMSi4XedUUQFQdDoag0MJrGjfFJQkBLqd+xk6aS3B/tOpadC72RjSBpW363wq5xdtFbCGBpl9GxO9asXpiOftA6hHiwktJuawkl/yCqPY22o7ATRERHF66kxLF8Nu6KIF3iVr2ceDWsWbM9HqbbxqS+HoycNqFbDW8nmuKK83OojdloK2Jc7O21LYDogJaiVmoXWoQUfHzfosZJuoiU9q83mtyAgQCvd++w4rBl0JJ1x3z5Rkhb7DStp9Tm/oLm+sKmKdYH2q8CRkzxyOcJmV3V6WcxXjpR3gIsvRiiQE5b36qQJWpUOpTkjCv7LCbU94bzBKOh5+fxY1DTpcewwE6aOLCY1sXedY5cLD6oVtK/lnQjEZOj5xSoOJiWzhe2Z6lULbEBZORU+XafLtoiNKYnkSr+5Eq6uQACveClfwLF6dbddS0IJnUetsXI6C1vJ+nSWGdXTcbFuFbE1MW5MPHZGFQll+JJnF1hbKzuPAJWDkZbkdck53dKc3VhWxLbDvEbxq/RG3QlZxkajiDRJmBK0NtYyZ3pxiPNubr0tPswHtKL6souKM/KFjiDt6yPOGHviV+Adfls/EnWSIjK9j1u3H230ule6nI6oQKG12DLiXpma03MvbDmWQ3B+uc+xqe5sReCte2ytU7WkpOL0Vrq5wtr+rkAR34tb6Huw9tPZxtPaC1lkimLVkV1vEbFuEbGNYBOU9ehF+7ky7miacoSfT2IDZZP0cnSUywry7jxKT1HXdErvDG6uKWCdYvwTrv64Mc1KfKgrPBftUm1CSBMFyDXVmfwSg2AlZGTMyCm9yHxJQO3cmQStdJ9gAmHU66qLaX9ZERcWemoQkzo6fSur2jV6V3XJGIbG8zkI8NepQzBK6Luw6o9K5tLeMVlxKjUPNS19I5wgn6O9gV8FiW6fzPfP5ivqwCAyBwYTln3N9XUuSy6Sd9tBWAduyVJa9ELOKNGfi1ddkK3AtJtsrXD3h6vie4m3nD0t0IWaDHLzRrmJn2+OZbYuQzZwxj6GfvYe+rqbNQvb/eJRG3DWasdhcxUXVgs6gu7yxqoi1IyO/yulThCuv7PCpeexdl4S39V0BJA0s0dxIgLmGx3mJXTRnjY9iNy/xBJfwI3XRkWSmJjMwNRntuTyn3ZeEJFEweCSK3k2soYpKGzk3fgq1MXEk7dlOaF62z1Hey7mylZhojURFcSC1VXqCw9SuXRcy7Q0jsBIYYmTAmCKO7opzWTqoNYJxqcdYe3Ysz/In3uR+arGEWAVRw/28yXM8jQ4zx6fNQhKC8GWLXRzJ0tCjYPDIDnk/0Dbx6k64QmvxCs0Ctj3JV50tVn3F3Xjcxdk6i51155m1itnOFrKNoWHsv/VukvZuJy5jH7rG1m2NPfExt+JZcwiyj4czYEyxz8e/kFBT2Zvw9ARhFbf220XG1TPrZ8dbN5h3wxX3FjBdt4VL2MxOxnOcfmxgKsfpx07G2zK8DQGhVOuTyLxkAiZ/P9sUGFjEK0BVYgpnJ50/rQ9VfnqU9e7PoRsXsO+Wu33et4pQJC9/F/lngtWomAuYju7GNf3mTKITa2mSlB62FvgHKXx253KCpTpe4gkKiWMLE9nCRAqJ4yWewB9LzLVZ70d5Wl+yx04GQLFL2lIkGSHLHJtzXYflGfgiYAOjAm0vsAgs68uKOTzRqff1aHEtGlm2CdilB/IcXhEBOq9eFxItx219r4DDZ2H9fKSwmOZEsBbJb9bP2P7z9xbrd+suSc8eY1AwWZfMYMcDT1DSq5/tnu4NAqjDu/GV5AbRUNe1jTk66mHWW1RPrB2eYjnsPbJWDHEN9BijJz8jCWOdn8dzXD4qjJrMyYT+sAbJbKYfJ+nHyVbb6WqqmfDv55EUhYboCExDBqI7ew4qKqkLi6Jg6CiK04d0e+cYlYuDuth46iKiCCgv9RAc0BzGnc4xhFfPyYKv3xhCv5FFzPvFMTSdXBJGpXPoyHayfgFmLrnmNDu+TSX3lKfjSoSGSCRMG4H0rOXaCaKOiWxrtaUiy/Rf9RV+tdWY9H6U9O6PxmAgqLQIIcuU9upP/vDR1Ed2TIiWtwLWWZyrPS0Fl7vQgbYkXf0UsH+v1s/AdaiBe6+shaM+eWVt33FTcwRvwwuKBwwh+vQJl+vtbaq1QGc/TrCfEbj3xlpq1i96cjzXLswgpV+lV+NpD90RUqCKWBeU1xudGgB7obtrTTAf/ysWxZdm0bJC8T0PErbmW6errbfvQDuxEFBShlRcSt3USZwc1J9qffvLdKio+IQkkTV5OgOXf+42eEZotbZi3bP4jgRyySfRzR7Y1p3YF8PGrwxcduOpjh27ygVFfa2Wr14bTN7pMGTZu1jpkDCBGDwIZfRwpL0HnYdfYWmZbO1Gp2tsIPL0CRS9nkPX30FtjKeGHL7hjYD1tjwWOA8bAMfQAW/LXf3UiQjQOYQaOBOz9glgrstz+Z745Wt4QVmv/lTHJhBcXOA0RlYCzJKELITN9i7kde7hbS9GI2Fs1LDk30O4+887CYnompCtrkzwUkUsrUMJyuuNtn9dGYOT+/z58G+xti5d3qDVKNxc+TWRQX6Ynvot2r++iNDISGaLwbVevi2PZr2wAzduIdxPR/VAVcSqdD1lvftzbPZ8eq//1mUcl2zXIEGDwv9YwGy+ber/7eF3IiT2bUikrlpLflYoGlnQa0gZw6flIcuCs0fDMZtlEnpWE9ejpgPfmUp7WLX+SId5YYWAr98YRH6WpcuQ4kVylywLrk49hPa9ZTRcOxN9di6aIkscYMviQy2vQFkIJIOB9BVL2HPnwg6rB+uLgHWXpGWPp4QtVcA6Yv0crGLWGi9rH2IArhPAAAL6tC1W1hchKzQaDl97G/1WLyUy65RTHaCxE7AAC/iAz7iB77kcT1GhQkiYjTLffdiPhloddTU6wqIbGHZJPn2GFXPueAQVpf4EBJroNaQUvX/7kmy72huritgmWj41zB+WyNIDeS6F7JqPIpospHdGT8bMXeZ3iHvsfgBEYACGudMxV9SgP3YCudRS6N3tVK0kEX3gCOcGdn8Pb5WLk5L0wVQlJjPm3X979eg2gx/YzCX8jufZiOf4bcUsc3RXLAiLYS4rCmT398l2D4sWUx7fs4p5vzhKRKzvSREq5y/5WSHknAz3ensJgUYx8tCa+WjWZBEI1MZGUz16OEHniggsK0Y2Gpu2dXEMIQioLCfsXBaVPdLa/R68FbCeErW86ZZ1sYYO+IIzryxYPkt3zROs4QZdIWRN/gEcueZW+q1eSsyxDI+Nk3WYWMFV/I0neYVfUoXrhgdgEbJnDkfajlRV6k/2sQg0GgWzWcZqV7V6MxPnnmXsrHPtfp7rKm+sKmJbYPXCgmsha2yUOLYnwIOAtVwUGlnBrMhMZSOv8EvbWqmuHv3KH6i5eg6lyUnElFV4LLchCUFAcdd031BRcUXMyaMWj5WXmVjj2cEGLuMt7uY+b6bARPON2pKd3tqXVpgdzCf/GMGCp3cTFGok+3g4+zYkUpgdgk5vpt/IEoZPySM4XK140Jl0dBJH5v5oZFnxygOrwYwGE19wA2lk2ZYHFpeir67j0LW3M/zTd7x62BKSRHBhXrtFrCcB64331Z3H1VmFgQtBvPp6nbQUP+7290YoOYuXBcdqBs7Kc3WlkEVRiDp13OsqMH4YeJZneZq/0otT5NDDwx7NR7Y2aTKbHe2qyaBh09JeKIrEhDnZ1NVoOfhjAsd2xdLYoCUqoZYRU/PoNaTMrcjtSm+sKmKdYH9h2wtZsPwYTEbJKw9sRIRgkrSVn5f/k6vEMjS0dtMHLV+NHB7qdb040Ya6fyoqHYm+prpNtWOnsKmNZ2z9WxOKTH2Njr3rkjEZZPasS3aoLbp9VSB7fkjihscOkphW3cbzqnhDRyZ0mYyyV9FZ/XtWcW3Wa9zPm/TgnMM6SQi0DfWkbtuA7CQ21hXtTZJtr4D1tjzW+SJafRWm3l4nGflVrY7tal/rtr54/DyFGbhKAOtsIasxGtEYjS7Xu0KHiclsYQkJmPD12nD+Y9u2MpUe/ctZ+sZgGmp0tpmw6nI9ZzKiGDiugCvuPI4nOdIV3tiLXsTaPy3Ye2HtsV7kVjErZAiJMlJd6jrOT5bg9yH/5tfZj7ofgKKgMXiXGSYkidJe/b3aVkWlszAEBrWpSHc6J7iUdfzIJW0wtq0RisT+jYk01mub/rbz4ApLQsOX/x7C/S9sR6dXmyl0NJ1RSicmqcZjJ8QQfT0H8pLww3VctCQE4dmnvT6vJATl7Wgx607A+uJ9PV/DBZx91x358NLW41q3tY7PVzHrKswAHBPAukLImnU6FI0W2Wxyut4VAniI11jMLT7t5w6zSWLp64NpqNPavLbQbGOP7IgjNqWWMZfnuDxGV3ljL3oRC44XvvVCNts9wVsvansPbdl9Zl59QYvz1vIKWmHkzuxnPZ5byDKNwaHoa91377CuyRs53uMxVVQ6k5L+g+m5ZZ3L9e6qF7zHXUxkK4XENSV7ebOXaxrrNUiScDC0tiMKiYZaLcd2xTBkUqHPx1bxTEcLmfQxxaz7vA+GRo3T2S4NJu43vOpWwNq2NZlQJBnZuZG2IYDytD7UR0a3acyuBKw37WHPN/Hq7sGks0RrR2AVTL6K2ZZeWWgdMwt0aGiBS2SZogFDiD28H9nbmVksVnMSW/kjf+JZ/oQGk822umpv7wlJgvoa902Udn+fxKjpOR69sZ2NOjftBLOiMCAmiH6RQexYGcz1MwIZnhzCmF4h/OaBAI4clLn15wb69DMjoWBfjFuDEQnLzTqaMo/nkhSF8p59HJoZ2GMr9S1B9oyp1MR7V3tORaUjCDHmtSrg3RgaRu7I8c6vV0mCFtey/f9TyWYvI3mCfxBDERIKsRTSlxPI+DqVZjHhzgSsFUkWnPMhUUjFO9rrhS0vDGDNx335v0cn8dL9U3jnD2PY/X0SkiS47KaTSEIg4eiRkjEzjAP8gee8OofRz5/CwcNdFpK3XpfVCckcnzW/Te/Dk4C1NiqwNiiwFts/Zgh0KmDti/V3VfOBVeuP2F5gEYTOXuc79uO0fz/e4K5hgvV7sm+SYN8YwRfiJ4xx2xDh3JhJmPV+Dg04rAjArG1xPdht9yee5Ruu5BJ+RIsRLUZGs9un8dnOJSQkyd3Dn0RNhT/VZZ5r43d28wPVE9tEy1ACsxluv13DV19KyLKlB7G5HtYs1/LdN1pCQgWVFS2fARQuZy1P8oKt85YnhCyTP2w0tTFxpK9cAkLYPLJWI1vaqx+FU0ZiCgpq57tUUfEed8Y265IZKDodSXu2obErq1UfHsmJmVfTGBpGaG42uvo6emzbgK6h3uZnjaOI5/k9z/N7mydhI1OYxkafxudtblnXdQ+/uGirsMk9FcrnrwzFbJJs05PlRQGsX9Kb7d/2oL5Gh+Vba7avURTzMK/xOC8TTOus/ZYISaJw8Aiyx08loKyU8Nyztjhu6zVn8vPn1GVXUNJvUJtKa3kjYL1J2uoOr6u3MacXItb30hGeWWt9WUtYQcckewEuwwoawyI4dOMC+q1eRnBxgW25ImvIHzqKrMnTCSnIxa+mivCsU8QdO+Sw/5Ws4EpWOJTpmsIGNjMF4bUlFMgaYbGtnuyrh0N2RUjBRS1iD+ZUU5wZx6aKUKRAA4//IsTmhV20SGbpV5b+GPa5AZZsPkFlhbNvT2YWa7wWsABnJ0zDFBBIWe/+7FnwIAkH9xBx9hQogsqUVPKHjqY+KsbrdnYqKh2B/Q3aaSyXJJE9YRq5oyYQfvYUGoOB+ogoqhOSbYKgtN9Aeq9bha6xwXV5o6Z/p7CJXyd/zEs5t3k1PlkWRCcZ0eoE+Wf0Lr2xQpFJ6Vfh1TFVvMMbz0p5sT/Zx8IRikRirypiUyzizWyW+PrNQZiNcovvTAKBnYBtRoORQOp5iNe8FrCGoGByR45H0enIuO52ojKPEZ+xD7+qSgxBwRQNGkZxv0GW5hxtwJmAbRn76inutavF609ZuDrD/v21Rcy2TPzqKCHrKT62LiqW/bfdQ1BhPkElRShaLRWpvTD5BwBQlZyKvqaKft8tc3kO+1/Qp9Jt9NadodHgRa3upke84VNz2bsu2e12IRGNhEY0ejhe5yMJcf52LK+qqiIsLIxHXlmJX0DHeiGP7Y5h9ce9La1iJQFCQuenMO1yEznZMicOazCbwVc/TiC1FBLn0dgaAwI5O34qBUNHufUCqOL1wqK4NoyVx8dTVBtOVGAVc/rtICHEc1hJV1GtS/T6moqfMMZmnFvGcnnTiUYymxn/xt8dPLWuEEApkcRQjMcoJ0kw8tIabni0hGO7AvnguTjnm8kCrb+BhS/u7LTErsb6Wl59bC6VlZWEhl44osBqW/++ah8BQSE+7euuuUFDrZZvP+hP5oEou6USMcnVRMbXc/ZIBA11vgs2GTN/4k8eQwkEUJ7am8wZczGEuK+d2R5CjHkuBaw3ca+d2ZjA1UPGhSxahQJnjkRaHoyA5D6V9B5SiuxDuKfVI+hL8pd1hnb+sERbfOyAGIsWEZWWhhqaijzqM33v7FWwbZfXrWlbkrxrC6lb13uVYCskiYXiNd6U7kcI97Y1JKKBqdedpv+oYv77zFgqS/0cEmbtjsqlN5xi9Ixcr8abkV/lc5WC+tpqfjNnhEfbelF6YjMPRLH8bbtC000eAWOjzNoVetqaZAJQRxDLuJrb+MTpegEYgwI5+rObQCMTYsp3eiHbC41e86a2aSwq7WP38Sje+HoAP+xNQAiYPKSQB685xqQhRa22FQJe+GQof/9kCEKARiNQFInXdlzLg1cf5a/37PE5AL6lQfQ1/qrlsaxP/9AsUL0hMCqQXvOm2sZjfxy3JWMMjV4JWLD82qIp40pWsEqah9mFsZVlwe/ePUdCmuXmMmpGDZlHtWz5MgqNRtjqHkqywD9QYcQtO9Dpz9vn9J8UZrPEF/83hMJzIbS0n8U5wRTnBLda7i0KMv/l5x5F7NG511HWt3NL+ngjYD15XztKvHZl1YCOwtAgc3BzAgc3J1BT4UdgiIEhkwoYNiUP/8DWlXrKCwP48rXBlBcFImssQnL32hRCIhq4dmGGzcvvCfvkr7Z6ZF2V39KPTsSw+4c2hRa0BX1NlddlDiUhuIe3eUM86HobSdB/dBHzfn4Mqcn0XvvQIRa/PJy6ap0tMcdaxnDQhEJGXeadgLXSWeW2LjoRKwRsWNKr6S9Pk5y+I2OmiFiX6yWg4dp5xE8e17zQScai1UgGRgUi9xuJNjSizWNS8Ux9PaxY7U9OnoaYaIWKKoknngpDowGTyXI9fLujB8u3pvK3P1byq4ccDedri4J4/qNmz49ip93+8/UAQnun8MffeVev1Nq729q3256Wnh7vj3fU6cOQt8ezHgOwCVrPJWP0KLLsU63Ov/J7fhAzaJADUJTWv8Mr7iy3CViAigYjs+4p5he3+rP4fT279wj8AwQjptYycV4Vmw9WAuf3Tf1Cwp0X9uS+aArOuvqs2xuZLFFC61asVgRg0vt1iYB1RksB29neV3vxer6L1pK8QM4ei0AoEJ1Yy7ovelOaH2QTRo31Gn78Oo0DPyZw6xP7HRqUNNZrWPzyMGqrLZ+ZYm7+PGsq/fjsn8O460+7CA7zLim0LSW5nIUWNIvZQAbEBCEqi9GPnt5lQtYYEOhTmcMR7Ocu3uV97moVGyvJCgHBJi69/rRNwAJExdfz8z/t4tCWeI7uisVQryUqsZYRU/LoOajcpzDyzoyNvehEbNG5YMqL2u7R8oSChmSc104TgBIVgXTTHAI1su1Cd1dbUD96OsdqJDAEdNqYLyaKCiQWv+fHyi/1VFdJJKea6TtQYf23OupqJWSNQLE5AyTsHYmmJi/f758NI3GEzPAxlg2NBvjLS+6mZCX++Z9g5t1rJijY/fgGxATZenfrR7cWh2bgmMG36ze9yVPgDG+PZz2GderM6p09vWKjSyErtFpK+g0i+vhhj2WOrAzhMD8ymdvTt3H0SHPma2i4wsSbipl1S+vSSpYbi5kxE+tZeiDvvCkGf7FxeHucy3Jn7UchiVyXc2QScOrS2Z1w3mZcxcF2lYA9n4WrEJYZzr3rkyjICkGjEaQOLKOiKMDyYCNZpJPl2mj5LUoIAVVlfqx8L52bfnnQtiZjWzw1lXqcfetCkWis13JgUyKTrjzr03h99cq2FLKuasl2lZAtTh9C6nbfmscs0i4kdEAcizLn0FDf/Hmm9Ktk1s9OOO1uGBBkYuzMHMbOdF0P1hc6wxt70YnYuuqOuMG5MqWCMCqZZ8sObPrBWrNie6YiPniNgMR4mxBoNb7SutYCVh/AN4cKWm2r0owQYDJIaHQCQ73M/rVh7P8hlLoqDVFJBsbMqSAy0cB7v+1BQ62mqZ0pnDii4cQRLdY0TE+F1gFkjeClfync+KTlO8ncG0hlRbjbfRobJF79Xy2DLnHtjb1qSLzt6d4T3l4PVw2J90qkujueIgTXDE0AQ30rMetJyGaPu4SoU8cRJqPXnoOR7GPxN6WczAol67RMSIhg9AQzK4+VI0mqQD1fqa3SdZKABRnLlKiQZSRFaZU0nTXpMkoGDO2Uc4P7RC6rgD1mCITi2g4Vr+dDMpZitlTn0eoEeWdC2Lc+kdzTYWg1Cn2GlzJsSh671qSwb0MSkixstvXYLrsZSWFfds91Emb2sQjKCgKIjK8H4MgO1953sIjio7tifRax0DYhCzjUk7V+11a7na6v81rIxk8YA22Mi20IjyRv6CgSDu7xeo5DKwy8NO1bbvxkFHv2BLPlZCXZ5UcJj60nPLrzr6u2hHN4w0UnYkPanE1nX7QCQMExAcUibG+fs5W3b1zBrMEJhH38Af7HjhASHoJy9dUoU8aDzvJDCHDZHOYo+tHTgSajqLcIjG3bT7Zx3N5hf1F1dl23jsTYoCVrWy+yd/fEUOuHJCtIGgXFaI34l6go0nJqbzCyzoRilGnpBXD81zOKWeLkXj3rVudwanMfcvYlebXf4UPFVOkcW2RaP/fyeqPPDyoRATqPPcVbHtO++1zLY7nCOjaLIIZ0fZ1DZq47IdsQEcXBG+6g3+qvCSor8RhtLmQZMWUKIiCQ/oMU+g9y9ODmnNRTdE5HQLBCn+H1bo6k0tG4CyUACItqoOhcsItEEPdYZkCceelAI5npGZjHJdPK2Jr2WyLPniI68ygag4G6yGgKBo+gMazzwq3cCVgHW03HeF/PF49r9vFwdqxOIetoBAiJgCAD9bV6JEmxJQiVrQlk19pk2zS/UJzZVt/IPR1KflYIu9amNMVRu8dQ3/Z2wW2Nk4XWYtasKBwz+CZk28PpabNRdHoS9+9ENps92lbJrMAlIxkVrxB0uYkplwfxzaFkNm45zr4zdYRUpWA2ScQm1xIR1zm2tTPCCi46ERudWEdcahVF2SE+eg0kBoypZcy0Cmauepl/HL6DAwy3rU3hHC9Iv+PWVZ+i/OBH+XU3UfjI4/QZOQBTUxajleaYx2as2Y3W9dane3ujaF//riVtNXbuLqiuMKC5p0LZ/X0SZw5HIoSlHM/o6Tn0Huo+o18okJ8Vwor/DqCyxB/rz1cocpMhtftumwyuYuy4y10ry+x4eyoN9Rqvb9pD0wVJdp+p/Wfv6UZXXm9skzfHvu6hq3XeHKO83mgz1NYSM2CJBazPPOq2G01tbAL7fnY/Ifm5BJYWkrJzM/rqKqc1CCRFgZ07iX73Lcp/cZ+tcsfh/TKvP9STglP+tm0Dgs1Mu72Ea4a2qcynSgczdFIBJ/a6zgdwiiQIizQzcEoVcxI2UPpWDotMd1PfNBuhwcR1Ygmv1y4kamUZtVEx5I6awImZV3fpl+6LgD0fxKuhQcO+jYkc/DGB6nI9AcEmBk8oYORluQSFuo8fra/VsueHJLatTLXESDbdJ+trLR2c7DPchWL1sLY9Gbolu7dEUJJpCU3xhCQLohLbJxLb0+2rZYhBW4Ssu7wCt8gyWZfM4NyYSURmZRKSl0PiQQ/NDf78d4z1laTPuYljhkDmDIhnzbsxbP0qHMXU/DDQI72c2T87Tlh055TQ6khv7EVZYiv3VCifvTwMRWnZ7cf5D1GSBX3H1HD7s7nM++dTDFv7NbJQOMgQsuhJNCWMZzuy3YSJ0GohOBjjqmWIvn0chKu9YLVif5EHRgVaQgmajKMzT6wzz6mvhs9dyZG2HtMXDm6O57sP+zVNQVkMozX7cdzsbKbMP9NqHyHg0JZ4tq3qQVVp98QJS7JCYLCRuhqdVwJWkgQRcXX8/E+7bfddb0uO2IvP9sTTldcbHdom+3qjte5vraMsKotblZbxtmSMrraGQV9/QnBxYav5DXuMUdEoIaHsSr+Jy9f/hUaj3MLTY+Hh3zZw72MG2/uyf0+evIft5WIpseWNPRAKfP3mIDIPRjlpGevMtgokCe57NYsh/se4f+E1SEYj1SKYbUzAhJaR7CWeAtue1qPkDR/D6amzOl3IuqpE0JECtqM9r/W1Wj79x3BKCwKb2z1isUMBIUZufWIfEbENrfarKvNjw5e9OLE3xunvrCtoS0z1Vfcdpv/Ikg45f3vLcEFzy/p0veWebtj9A+C6/FZ7Sm21JP7AbnpvWG3rAtPqFydJoNVAXBwiNpYbxYd8uX9gq9+r9R53x9N7CQ5rHSvbXry5/6klttyQ1LuKmx4/wMr/plPpIIRafJFNP6j+A8ws+q9CVKNg4PdfIzUlqQzlEENx7Jhh29dkQlRXo1v4MDV/+7XDOm+nFwbEBNmSBNx94XMuHciq9UfIyK/y2Qi6Oq79MaHjxWxZYQDffdQPkBwMplUU7ljdg30bElDMMpHxdYycksMNAV+xc0US3xVMxRLO0R1YbqO1VZ7b7QGWGsSSIK5HDXmnQ0nsVcXhgipqSwM5ddCfsGgT0YnOy1C1NI5tTVpy5oWdPyyxVUhBW/F1uswYFMz+W+5m1Puv4V9V6dJ/oystgdISXsiahBHhsuPMGy/7ccPPjEREWQx3W73WKu7xZAMkGa669wjrl/Ri34akFjdGx1ABSVJAkrj6sQIS+zZy46dfIpnNSEIQSjWzWOP8HE3/Ju7fRWnv/lSmpLX7fbmiZSWCzhSwHWlf133Wm7LCgFbCRAiJ+mod7/9lFAgJrV6h38hiLhu5n7H7v+PhH/9AhRLuQ2enjkWSBSFRRmrKdF7kJlh+6+HR9dRU6Gmo0+AfaMbQKFOSGwQSxCTV+lwfui1eWVceWeuMlSePbHtiY1tSMGw0ik5HvzXfOF0vCYEwmpByctmbE8eXDHK6nVBk6mr07FqbzKXXn273uDqTi1LEAgSFGagq98fdNMjQQUZ++VAt115Zj14PmqWbLdOdXiKZzbDvII37T2JOcR032XIatte8qRh2/9BkLL3LRPdVyLYMI7AKHXsDbP0Bt1Ugu2P/xkQPT90CQ4NlLEU5waz+OJ1aLuFHpjSt9z3uzncc/YSSJJBkwfBpuez9IcW7/Zsur+O7Yzi6M46QuEokSVBVEI41tzRtUD3zF5aSNqh56qalgLVf3haB1vI47T1eewkoLyWgqtLjdsVEs4orEG6+b7MZvl2m5dafGztUnKtY8MWbrdEKTAaNi5bAFiGr0SkkjzzLHQ9r0UXXcdWQeMLuWGGxl16iSDIJB3Z3mohtGQfb0QK2s2a66qp1HN0V63KGSAgJk8Fy2zcZNWRsjuP4j5exHz8qCcPcZkngeziBhAmBFllWUBSZ4aPNFOZpqPIiuRYkJEmhssyfdZ/1YdNXvUjpX0HOiXCMBsu0uN7fxIhpeUy6MguN1vsJ55Zta9sqZH2tWtDmsIKWYzlz0m0NWeun+wEL0GLEhPNrVigShzYnMO26050y4dFRIQVdoQTOSw7+mND0P+ffjkYjiApt4Lbppwioy0NTkYd0dJ/HVsLOqF2/mYJtu1y+qnWJthfA6RWOPeTnD0t06k1rifWC8BQ43XLKxP7Yzs7j7XF9Ie90iIepePuYVkuM62YmI+H9ja49yJiRUbiVj5nEZiawhasGb+Duv+ykRz/P4qsZS394pem9VheGUlXg2Eko64g///dwEgc2W26MrgSsKyHaVjr6eL6gr/OuQHkhcW4FLIBGC8UFMgW5El99omPninCyj3npKVdxi69Jng21Wg5vj3MzHS1hNmq47g69TcACaL14oLFHFgpBxYU+7eMt3ghYjSyjkWWWHsizzZB4I2BXrT/SqaFaxTlBPiXWKUKDER0buMylmPEO71WOBhMDOcx8vmYMO5mnW8Nn75WweYPAu6jBpihcITe9VwmTUeZMRqRNwAIYGrTs+C6Fz18ZisnguwprWVPWE86+/6PFtbbGF9brx1lVIuu11hEdOv1qq72qBJNHImbcJ8U11msxGSXOZESwd30iR3fG0NiORDorHXntX7Se2LzToW7jfsxmiZ37AhziVwOXLm/TREutf6zXT1gt24LahxR4g7ce2ZZPQPZT1p68stD+i1CjEfj69G6Z5uqaqa5h7Ofv/JYZ/NB0bsjPieduw1sYw8qRtQMcAuFb466iZYsthYTZDO88lUCv4bXMuruIB6+LcrKv77R8KDErikOyoHUbb27A1lgvazxse2gM9q7VaSxFSCgePbFbNmr472vBTZ59f1YgkdKvgQV/0LHn1IHzrq7mhUBbfusleUEOBemdIgmOHtIxrpflRjtg51qkhtYxmu4QgKLr+BkEbwUsnD/eV3tkje9uFsWDkOlIAqjjbt7hBX5HIE0Z8I1gangJc+0t3HxVCM+/HOy00Ukz3tlVAIREzslw/vPEBMbOzGHc7GyfWtX62hwhIkDXKqygpUfW2jimpUfWmhzbXo9sQ3AYwVKex9rcCeSjwYzJjW3V6s28/dS4pvA5yz1NqzMz/opsxs/JPi8Sai9aT6wsK+DBr6qRzdSV1lFXWodh7wk0Wb4X/DVrdVQk92zbINuIux+aqzACK/OHJdoEbXu9skaDzMHN8Sx9fRBf/N8QNi1NY+cRIxn5VQT2zGuDHu0aEbuK2exltE3AWs+cWF7A9WG1TJmWxoybqyzxri5p2zhPHwjk3V/3JGN/x/00WyYcmO1CYrzxxtpfB9a+4eCYoOiqMoErGiKiqIpPtCQauCGWYmbxHRpct68VChw7pLELTbH8m5vpx78eSqLB2/hllVb4Krgk2TsRpdFYag+n6+vQLHrH43XQ+kQSJX0HeN7OB7wNIbCnuwRsUU4Q33/ah89fGcI3bw3g+J5ozGaJ+J7V6P29a/XclciYuZw1FBLHqzzaLGCbkF78PzQVedw//xTBQQKNk+vIUq2gbXnohgYdm7/pyYr/DnAS5uIZX72y1gcc+zqyVo+spTzhALce2fZQNGi4V81l7uB/7r3vksBkkKmt1lsXAJYwlM3fpLF1RWq7xjk4IbRDynl2qoh9/vnnGTNmDCEhIcTGxnLNNddw/Pjxzjyl16QNLnerMzSywoxh2ba/dScyff75CCB31HgUvd7jth2Jpxg2Z15Ys6LYXtZl1jCGlmLWXsi2fB3Kq2LvqXo275J44/ej+e7DfmQeiCLrSCQ7Viez8f+mE1o1njsfDsA/QPGqjIr3CNqT8CWhkMZpl0klApi/YQkAE28pZNTsCsDi/ZBk0SYvSOuTSBgM8OffdE7lBXsR6guuxK69N8FX78GZqbMQkuxRwPyN36PDiOxSyLasMmJBUSTqq2WytvfqtJaH3cH5bFfjelTjF+gh9ElI3HNzoC17W/7xR59aaApJwqT3o2DwyPYM1QFntWDBUkIOsAmQll5Yb+goAWsyStRW6Vi/JI0P/jKa/ZsSOHs0kuN7YvjmrUF8+NeRGBo0TT3tfbNFEgrubaewe/mOgoYFfEAIrTvuAWiyztGwYR1hlYdY9pfVRIRbfutajUDbZFf1etC0y2kscXxPLGcyItu0t7dCtmUdWWdCFnArZNsTVlDRI43SXv08JuiNYTc382nTd++ILIvme7OLvJXt3/agvqb7J/M7VcRu3LiRhQsXsn37dtauXYvRaGTmzJnU1no/Pd5eFAUKs4PJyQyltqr5qSOpTwWy1uzCmyYQAh4YusZZdoJbBJakA4CCIaPIHjfF/Q5diCcvrFXgOPPUuRKy1v/PnjKQoLLx7HprNj/8fTbb3plCY7W1fqv1R2CJX/rsnzGc3VbN7c/lEBjk/RO2hJlAap2KGQmBBjM38hmDOORiGzMSiksxJJB5kucdSqU57g/hWzZydf9I7ijax9JpH7Dmr9+y4O565s43suA+A0t+qCE0vH2VE4QicfSQhuOHz9+JEmdl4nylOiGZQ9f/jNoox648LT/9EexnPZeSjqNQC6WK4T2LnRphK4oiUXQ4DaHAmSMR7NuYwNFdHRPX1V10hV31xkNSW6UjJzOUwuxg7B0/vYeW4ur3LEsKM4ZmkxZdDjSVHzJ593tRmh52jP6BZFx7O0ZPPZx9xF03Lmd48sJ2VPxrSV4gy99J5/8emczrT0xk99oeAHaxr5bPpTg3iC9e6E3Y8P0MmWax9RqN9bN1b1+t4TrOf0uCXpzmbt7GlaNAxowrkavBSArZXM8St2NQth+i8XAW484u5fhtj/LGXd9y82WnuO2aUt56tZxnf1+FD3nVTpFkhf22fBjfaa+QBcsDkfW66hQhK0kcm3s9eSPGYtY0i0xnV8D/uINHeQU/HMN50oMybfHGrlDMEsf3xlBdrufQljj2b0qgIMv332R7vbFdWie2uLiY2NhYNm7cyJQpnsVde+rECmGpQ7p1RSo1FZYC6ZIs6DmwjMY6DXmnw+23bvpXQoMJCcEHLOBWPqU+OpLs6VMQskz6p195PK8hIJDCwSMoGjCU+shon8ZsJcSYR695U221Yq0JBL5MXbU0ms7q39nX/gRHL13L/t9LD+RhMkJ9XjBmMySkGfAPbGrVqsD/notlzw/BTQnInqcGk8jm8KV3Uxzek2UrIvneOBUjOg4xhFKiXQacv8m9fM01rGaO7bsyoSNRV8TnpmuZJLZQRgTXs4T1XIYWIxICI3rCKWcR9/Eyj7OTcU2ZmVq0mDCh40npef4qfu++o1RwEOj1SGXltmWmiEjy/vhXym+4GUwm3nqwgDdXDUAR7RNK/3qnjhlzHQW3L9eBfW1Y++/Y2XfrqWOX9Tqxr31o9cK2u86hEASVFOJXVUlAWQmp2zYgKYqTqqKwizGcpC+hVHEp6+hDJoW4vylJkkAf3EBjdQAdHdd1PtSJ9dWuguc6se5mc6rK/Fj/eW9O7o+2ecBDIxtI6FVF1pEIGuvsryXL563BhBkt49jOamYT5t+AuOtWaudOxf+Bp9Cey/UYgFOa1oeS/oMp6TPAUoe7g/AURiCFxfj8m/FVvFaV+VFV5kdgsJGIuHrbNZmfFcLil4dhNkleJ2y9G3g36ZcbqcnQ8MmpSzhDT0xo2cIlTrfXYCSVbP7K77mPt6giDB0GzGgQSNzD27zGQ+gw8Qm3cA9vU08AWowoaDCj5Vq+ZDbf8iBvIJAwIyOjoKAlhWy+Zwb9cN91sj4yggA7uwpgGj2UhsfvRYSHUnGmmn4P3U2DoqU9/rfI+Fp+8ayHpgAe8LaerLMastY629Dc+Kg+s3WMrDVEqz22VdPYSEj+OWSDgeR9OwjNdx4SWU4467mUBvwZxn62MYF7+K/bY8uyQlRiLSW51lwEy289rkc1835x1NY62BOuasael3ViKystGaiRkc7d+Y2NjTQ2NpcZqqpq+xTg9m97sHlZGvbPH0KRXEwlWL4AP+p4hH/zMK+RguXL9i8tp/dXq9h/692YNRo0bsrACKAypSdnJ13W5nF3Bq4ELDiKG1FZbJvusArao8W1mM1QurEnb/1HS32V5ZLR6RXGz63mqntLObw9kD0/NN0IvXwkyqUH+9Y3MJW3eRx4nBcBOEcyl7GOTPoiy8LSs1s2Y1I0PMVz3Mvb3MfbHGIQq5hLA/6MYB9XGFeha6pcEEk565jOLkbzDVdRTwBDOcgNfEEADVzHl3zHLBZzM5WE0YdM7uYdesSUIBW5HrMApJpaBI4eL015GT0ee4BEcx3yokW8cCKPLfxIBoMdStb4Wsg7JKxjny+t36mvyYItaW9SVyskidqYeGpj4qF3fxSNlt6bWod0SMBYdjEWi3F/jzspJN7DwS2zKoYaa6cvx7gus1lm8lVZHfZWugNPdhV8s63uPCM1FXo+emEEddU6h2vZIsKcdeuy2NbBHOTP/Ik5rEKLGRqAN97DL+ccpXExxJ/LdXlOK1mXXN5mx4ArXAnYgD4DMIPD9K83AtZX8VqcG8T6L3px9mjzdxeTXMPU+afpOaiclf9Nx2yUfbAbgmfrniJrWS8EcDnv2da8yG/4HS+ikcyYhQZZUlCERCL5rJauoK84ydV8w5dcRyZ9CKOS+dJSUsVZ2wPGrXzKlSznU27hOP0JoZob+IJBWN73XFbxNvewjxH40chcVnBl6PeEV3luqe3fQsACaPYcQvPg01T0603yzr28zTbu4APkpoci+/dtwXN9Wf/A9scMe9s+tWXpLcAh0cscnoimIq8pbMVRyHZEopfZz4+KnpYe9+W9+jHmnVfQN7QWlxFUcC1LLfsgM5O1Ho+tKFJTW2DHXISinCA++cdwFjy9h5CIjm+U0JIuE7GKovDYY48xadIkBg8e7HSb559/nmeffbbd56ou17P5m55Nf7W8qF2XfmkkkO+Yxd94qnmpEMgmEyk7fyRv+FiS92xzcwQoGjCsXWPvLJw96bTswAQ4CFmA9OggbrpDYdnnegcPq9Egs3lZKGeP+qHRiaauW765tN7iPqbxo8OyFHI4xBC+4Ho+j36ASn00/ZLK+dn0o6Sv+RLlgA6N0cgQDjOEw7b9nMm9MexmDLtbrdegMIdvmcO3tnUmP39qdXEIStx7YnF+RQlA85vfgBCEoLCJKfyN37OI+6ggAoDJiacZkLuWD7mDegKcHKmZyGiFkeO6ppzY+Ub0qWMoePa1vMojTZULPHu8XYmAHatTGHlZDoHB518yjDd4Y1fBd9vqSoRtXZlqEbCtvILuf/sHGIEWk0XA2u2hX/49lTddQ+zeg8gu5ooFUBMb37UC1i6MwP6Bz10sbFsE7McvjsBkdPwsS3KDWPLaECbNy6K8yLs64c1InCWNTHrTh1MOa37L37mKZbypfYhdQRMICdcxZ1oh14euIma1QJwAfxq4nY+bdxKtbWsINdzL207Pnkg+f+TP9ruT23scEfvci1iXtVyEwL+8goQdewC4nY9III+/8Ac2Mg2AME01N+u+ZHfDYPYw2s3RLAwc58ZT4QPWxCRvKhbYC9mWFQs6W8haCSnIdSpgW7Ka2eThuq69BdefsVBkGuq07P7B+0YJ7akZ22VBdwsXLiQjI4PFixe73ObJJ5+ksrLS9jp37lybzpWxNb7NU4QHGc5yrnRYJguFmOOHyRs+lsagEKeCSQAVKT0p79m7bSc+T9m6VWLZZ35OQwSEIpF93I+c435talN4gv5Ol/vTyO18zPKiyWzKSeedHRMY/c5vqEpJQjY5FxtWIekOIbdOIrLuc+rSKwguznd7K3ZXG0HC0tzC2gwjlGpe4EmKiCWXRErlaDZWDONN6UEKieNmPnU71oVPNNKyglBbOnbZx2RZb8be3pS7i8CSIq8MUwaDvRCw7itaKGaJ43tiXK4/3/HGrkLH2FaTUeLwtjif6pBasHz+v+LlVr9RIUn4ny0ja/IMp3tauqZKZF1yua/DdUmIMc/WTtadgG0ZRuCupFZbYl9/WNwbk1FqZTuFkEDAzu960NZEqkz6OF0+gOP8n/FhtlaM5rusYTz00RzkHT9SpdeBJPlSvMqGIjvPIhCSRG1MHIagYI/vwrv+XBams44NXEo54eSQRLE5kjcb7mI3Y1jLdEKoclpPXJIVQqMaGDTes1fYW7zNsLePkXWV6GWlZYxsR1QsAAgsLfbqajrAMLR4qkvv/o4rFJmMrZ5mySy0N+GxS0TsQw89xIoVK1i/fj3Jyckut/Pz8yM0NNTh1RYqS/2R2vjjl1D4gAWtlsuKArLMwZvvojLZsbSEkCSKBg7lyFU3cV4UTmsHLX9U770nN9V0dYEAk8n39yyhEE6Fm/WOBBaX0mu5+0Q7172/QNFqOTz/VioTezisq4+I4uiVN1KSPtjNEdqODhOJ5BOplCLV1iIJQQg1fMJt/IWn0dOIhIIOAxIKetnIyLEm/vN3P8b2DuGmWYEsXaxjyV7fxaar4tvgmGjgSRhbax+CY1KCPR1RpNuKWeddNQ897Z+qkmVBfbV35zvf8NauQsfY1voaHSZjW+O8JY4zgIMMdVgqEOhra8kbMZZT02Zj8nMsh9YYEsbhq2+hMqVnG8/riLMqBM4E7DFDIEeLa9HIMt8cKuhwAVtZ4se5ExFuHgikpsL9bbNJoXgXiqcxmUjYsYfII8fdVohwtUZIEnkjxpE9YSpGP3/bckXWUDhwGIeuv6MpfrntttXVY2g4lSSRh1Yy25wTM1jHXkbZwhu0GG3l+YKDavAPNPL6ExN57fEJrP2kD2UF7a8C46uQBfeJXp2FWa/36lvwpwHFK2no/mgNtdo2lTPzlU4NJxBC8PDDD7N06VI2bNhAWlrntAhsiX9Q26cGBTL5ThJFBBB+9jTFA4eScf0dBJQVE1KQh5BlKlLSOjxT1kp74xfby6lTlsYPrpGaMpN9b1xwiwdvpMNZhEA2ee5a1vo8Fo7PvIbKlDQqU9LwqyzHv6oSY0AAdVGxtgePipSeRJ4+6VWNvfYiAU/zVx7gDb7gBgqIp14K5N88woE9frbP/OghDc/8UkO/sck8+LxjhyJ7w+lqKsZZ8W1fygS5m+axtlC0Tnl1FCX9B5G0d7vHsktX8zVfcGO7Og0pikRopG+F9rub7rKrfgFN1Vx8iOtuSRGOcbOSgNC8bLQN9eQPH0PB4BFEnD2FtqGextBwi8OgAxwD9g9ZngSsFBYDTQK2o8WrlcpSf88beR3n6bhPInmMY4dP43EVytFyNFKL/9dGRnF2wjSEVkvOqIkEFxUgCYXaqBjM/haBWJmc6tGp5HvT2pYHaD5+H05xkKH8yCVsYgoCWM+lrK+eTnW1JVDJaNCwf1MCh7bEc93DGaSmV7Tn7F6HFgBO4mObqgI1hRUAbtvTtpXynn1QZNnjdz2PFTzOP9t9vuBwQ5f49DrVE7tw4UI++ugjPvnkE0JCQigoKKCgoID6eu+y1trKgLGFtjafviJjpCdnnK7rv2YZPbauJ+7QXoKLCihL60tx+pBOE7Dtwde6mM6mNQCioyzeKu9wFWjhiBYjvTjtk4iFthk5CUCSCM89a1vWGBZBZUpP6qLjHG6QeSPHuxSwnqokeioSJgDhp0doHK/LKMq4n0U8yfO8J+6kQdE7PDSI/yfvrMPsqq42/tvnyri7RSbuSlxJIAQSILg7RQuFQqnS0lKjWKFYKa4BgidASAgx4u7JJJOMu8/cuXb298eZe+e6TCYh4Xuf5z7JHN3H1n732mu9q6Pk7sGNMSx7P9HruEOz4p0GNBRvgGe1rkAJKr6O5xhQnUiPQfmIsah6Q1D92Ad4AvAnCxQa9EaV/qNrurz/j4ETaVcDvUPGSDt9htWGXNDAF/JwD2MQQHRdDcM/eJ303dtI37cTW2QUVYNHaN7XbiSwruEDEDiE4EQSWAjV0dKV4i6CP/MwujC/iVCm+4XH3xKIrqtDb9beO6nX05ydS1NODyeBBWhLzaAht6dTIs3XuY/nKQvprYgqgGms5vf8lQSaWMHMjjUu9k8q2G0Knzw/BIu5e6hQONJbgfRjPXG82rEAtqhoykecEfRZ9+cQC/g4YIGZYBBCMmJqeZf3DwcnlMS+8MILNDY2MmPGDLKyspy/hQsXnsjTkpHXyoAxVX6E9APTDRUDN/Oq13LHR9tj4xr6Ll/MgK8/ZdzLT9F75VKOW7yum9HVAGlfuOIKNUgJQAc6x+h6vfaDTnFqAxZnnM0Q9rCCmV5VW0JBl4islGTs2Y5iDezJbcrpweEZc9y0fkGbMlN1eo5NnAHC26cghdA6Wz+xYVojBG3TJ4MqfW6zSFxCNekByqsKvn0nEbUj1MvTWLrqF3qucw0HcMCfFzaQtqUrAXZ0+q7xW90VUmCOT2TXRddg7egIVUXB8Qq63rvRbGMhl3UxrEA70sxLDmOMPL0S6E60XQ1EzCbPP4YQMuwiJQI749jgpfUL2vcZVV9L/2Vf0nf5YoZ/+Aaj33yB2Irje58csa/gHVf4YxJYgLScVpIy2ggn5lXRSXR6R1EV7Sewd4YiYeYJ7vfZfwWFD7sWdBc0fe7M3duDbntg7kW0Jya79b4OUlvfqw+NWbk+B61SCMwBYmolAmtkFPV5vfy6UP7NvQTKZrCadWxf2XXtWAe6oiHr6VQIph97vDa2cOpsKoeMBDr6tY4+y5MVvcH1TOf7jr/C/NYVlYQ0E6PPDL/CaVdwwsMJfiyce+N+DEY7u9dnggShaIlIxhgz1nY90u596QKVeXzJbJb5PKbw+FdRVbK3bUBnbqfg7PNPyHVoqgHhZqhqCKRlV3Ekgodfj2TVcj0Kgknj2rnzViPTJ1c7txEJaZx1tiQ+UaWpIRSvgCApso1z++9BZqUz9pIUJs+yseF7Qdnz69Fv3sBZLGMqq7s88rbr9Ojs3iPEYKN5nc1KRFMDppTASTzlI8fRlNODzB1biC8rRuoU6nr3o2LYaCxxCbRkZJG/cinR9bWdbcrMoPmaS1Gamon/7xtIIZwJXo7EFMuwQZhHDydi20701Z37Otq9gfEdmfb+x5XmNh3lRw3k9LHS3hTBsQ29Wb4jD6vJSFRCG3ljjtFj7DH0Ee6kzFf54FDg6c13LYLR7TJbHmjJymHTzfeSWrCPlNIDWpJIZiapURFEL1+F0qJ5hC/iU0rJoReFtBBHqMOcuGQzUy8oZMiE7slUPpn4Me1qRo8WLr13J4tfGURLY0SHKok2hotPaaexxjvGUCAxYOMp7vN7XE/bGtVQx7CP3mDHlTdrIT9hwh95BXcC6zy/SxKXA4Fixf0RWKtFYfe6DHauzqKpLpLoWCtDJ1UwYmq5m/dVCBh8RiVrvww9FGRWj30kJ9vpPymda24EuWc1nyyKo27JHnpaDnMl75GMt0xVSJASVW9A2G0o4bxfUpJQdYwGa5CEZiMUXDqPpEOHSdp/CKXdRntCEhXDRlOX3x/FZqX3yqVk7N2J0jFS1+Jqh1M0YTpDPn2PmNoqtxAjVSggBAfmXEBy4SESS445wwocWzWSwBGCJ1vvXZ/JuLNLkRIKdqSwZXkO5YXxCEXSe0gdY2eXktMn+OymQ3orWGiBQ7HAAVe1Ale4hhV0i1KBolBw1nxKx0wk7cBuDG1tmOPiMSWmkLl7K0lFmppALC18y1k8yu/5I38JctDO3lcokv6japh1RQGR0eE5B7qqUHBSix2Ei+MpdgDa+3x4ZzIHtmrEpd/wGsyZhcwcN5Q3H01n74Zop/ROVKTKrWPX8K81szEGzczzxpbrbseU3D1Zzo7M2eiUaGfBg893Bc+oDDVzfeWSKBY9loWidMa76nUSm13wl/tL+PUdFdgTs5ESLr02icVLI0PWKYylmSZdEsJuRx06FOtr/4VeWiKcMac3wtL1ZBwpBKWjJ2CLiCR301r01s5jhTIltenGuzEnJHX5/J0nk8RUVWBsbcYQ0Y4pLYXMSeMAaF70OelbdxJ3rAQBmONiqRk+hPakRPIXa4lpru10fHx38BwvcUfQqzj/Z7UMn9rKU3fn0NasuGQ2S4SAzF4WfvFsGdFxGuF0Fdt2I6EecbHBih0AnD8s0ynHZtm8HNDKznaHKHcocHohVJWkvQfIW/mD825dwgcs4hKC3r/bdhOXZCGrZzOiG+ahToViB12Bv2IHwUpWO9DWomPzt3k0VEeRkGpi1Iwy4pMt7NmQxrKF+VhaO2M+Bw618bL1FqYceCOsNkohqOk7iAPnXRzWfuEQ2O70wppNOhY+NZzKY477qc3fCQFxSWaufHA78cmaVm9ZYRzvPTayY5YruG1VsPOE8iD3yqdBp8NyzQIaZp0JQmD/z//IWr/5uKbkVUWhYMG55KzdSExF58AumF2VikL7pHE03X4D4J1ZD/iM7fQVQ99syEbfbnJ64Fsys7F1zMYoFgs5W9eRtXMLxrZWVKFQ028QpWMm0GvNdySWHPWKoZdAM7Ek0Bz44gGdXuW+/6xmxYd92LI8103TWygqUhWcc91Bhk0OTdnAn4C/KzyL0fgrggDu9/BE2tuIhnoGLv6I2OoKBNBIHIlBkwS1kKzhUypIy20hNqHrThPXe3ZKFjs4magsimXJ6wOoKe2MVz24JY0e4yOYO0Pl8j8V09Kgo6cti16R7YwU35JQWYhxTfgPQBUK6ft2nbAiBwONbTAs02vqwRWf7Cij3mQNSmSPFMKif2UhpXvClq3j/394MpeJo1uZPr6MDdtj+PKb0D8UgUpvChEdBSHEvn0Y512AfclCiI9DpiZBWWVQHVbtWB7LhcASE0vp6AlYY2IpGzWexOJCdBYzEsHArz8JeMy25FTM8YkhX0tACEFrRhatHQmAcdayTsPScwwVPceAqhLZWE/m7m2k7txDRHMz2uSXx6E62jeCnYQiNNPQJHn1TxmYWhQPaR6BlFB5zMjHz6Vwza+rfRJYR6KgI8FrwYhs57sD/sms4xiunoKTSWBdz5Gz+Qd6rPnBbd39PMUiLvW/s5Ck9KrBmlVI9nFKuvxUEQqBVVVY/WlvtizPwW7rVCoo3JPC3Bv2M2R8NWruYYZkjaKiSrJgSgLzhregv74SeUhxzlCEAiElqQX7OGSxoBpDU5AIRGAd8Iw57C4v7IoP+1BV7DkboH2XzQ1GvvzfIK761XYA1nzWq8MahEY9VXTkqwVagpTNRsTrH2IrKKJmxFAiknuQTfAKVIHSxCrGj8aUmUHL43/GVFyKobgUaTAQufIHInbu8fvchKrCjHE+vdud8C5R7fl8nB7GyGwafMhUqkYjxROmUzx+GorVStLRArJ2bmb4R2+i8xMmJoB4WkiijnqS/Fy5BrtNoWB7CluWayofrk4bTUFC8s1b/cnr30BiWmiJoKF4Y0MpgmAq2Nf9HlkfMLQ2M2zRm0Q0NznvVALNTGUlq5mK/+hTJWRP9YnAqVucvYswm3Ss/yqPt/8xkppSd++tzarjyJq+vPOUVh3lqqlpTJ7czKzpFuKibbTEJWNKTgxfnEuAoa37FASaDdlOcuA6bWtXVefPE44Pwd/Ucb3JSr3JyqbFiSiio9E+oFdUnn4uClPBPt56S6DXhRfvezsvOv8v7HaoqsH24suYCvZhOTc4ybdGx1A1aLibzJIE6nvks+PyG51JdKrBQF1+f6oHDqNm4FDqevbxmwgkgOJxU0+Y/FmzIdv5cyCmupKR771Cztb1RDY3IXwQWNf2XcBnQc8jhKbVWXY4AtWPYoSqCjZ9G0dppTaQ8CSwsrG6Mxu2411aMCLb7f1x/Fzh8BQATi/sySSwDkTVVdN7zXKv5RNZx3S+R/GZjKB90XMulRxYNpD3/9uL9Ut60Fx/ekpr/RiQUvMevvvYSDZ+k+dGYAFqymJ4//GRbNhl57xZg0no3cKA8a30Hai9e5YxA8IisA4IKdGbQyMNwQhsdEq0G8myJ2b7rMjlD4FiHU2tevasz/Crly1VhdLDCVSVxNDWoufYvuSQtbUFKulUMrejOIsDGZu20SLSqc0fgDUiMmjSaU3fgTRnuMd+WqKiKZk+iepRw533zZ6XgzJ/BrpzJmO/7kKQvuP4pU6H7N0D5a5fYhw7C+PYWdgTs71+jnXGsbOI6jvIGe/p+EFn0p1rHLM/9FnxFYOWLCKhtMgvgXXFGWwk2GAhIsrKtpXZCMXfOypAwPZVodm6UONjHfCU3AICym45nlV3Shvmr1yKsaXZ6079mT92/M/73ghFktOngbrKKL59ty/L3+/D4Z3JXU4TCvV+ueIn44mVEjZ9m8vaz3u5VEDx9eIKNn6RxB9+rQNUBsZKZ6eMEJRNHk/+l0uRPjIe/UFIiTnuxHh3TAX7MI7NdhIIBzw9B/68aq5kZMGIbD46HB1QMsumKqzdlU5bbRtV1bqQdd502BjLZm7yTCqQEt3SNTROn06VMNA3JYnIugafUz8Neb3Zs+AqUBQOnzmX+NJiFLuN1tQMzAmJAc9/4NyLGPT5BySWHkNVlM7jS8nRKbM6dGBPDoTdzuDPF6KzWoLKRDmQTQVTWMUapuLP4Or0MKZfFOuClK9VbYL2HT246i6LF4EFOoisZig9vbIOuL5HvrywR75cCZxcAguQuXOrFnPscV8F8AkLuIiP+Z6Z6LEikNiEAWMEpOebePexdBRdGlJKircK1nzei8nzjzLh3KLTXd75uBGo82isieCzl4ZQWRTndxupCqwWhYJV/eBSLczn/GGdYue28SOx9O+D4dCRkL8J0OIibVHBtTxDIbCu8KV1HAr8eWEri2JR7cF8QpKyw/H0CEPOSRPtF7zI7Rg8Bmh6s4XE4kLqe/fjyMxzGPD1p17T/xKQio49F15BY498AKJrq4isr8MeEYmapidzyngy8b5HUX0HQd9BqLoolAf/iLTaQNHiUIXNhszvjfWDd0GvdxIvX3KQjr7L4WEEMI7VPI0OLyPgJtfnz8uY0aFgAYT8Hj3Cn1jKOX7XCyEZNqWCnauzAhbykKpg/+Y0xs4uDmnKPNTStK4SiA7JLZHgHh97oqt5GdpaST20z+c9ncFK3uVqbuYV2olEjw1VKNilntTsFqrLYvj6jYEoOhUkbF2RS1J6G5fcsytkrzWEfr888ZMhsVtX5LByUWjVsnQ6yZeLjPz7N3VOT6dzarRHLvvmX0af75YQ0dIZSxMwNkjKE1Jutq22jeiUaHQNZV51vH2RWlci4klCHNCFolVut1CxbhNJ5lyQ+UE3j6SNm3mVf/BrIjG7rROArKvX7q3RwPZLbyF/1VLS9u9y6tXZIiIoHTWB4nFTNCMJqAajz2klv02OiGT3JdcSX1pE6sG96C3tmBJTqBwyAktcQsjH6Q4kHzlIRGvwOCxPPM19TGYtFgw+K1HNn6dSUaaENLB4+q+RHNij8OgzbQzN9I61crxPnuEFDri+M66ef+eAj5NPYAEtVsvPDUiige84kw2M5yMupjWlJwMfvpjv1tj44qMOpQN75xSuBNZ83pvoOCsjpp0cOZhTGb4IWnubjvceH0lLY3CvtVQVKvfmUtV4kMvO0AY+A40dna5Ox4Hpk8gQkaQd3BsSAVGFoGrgUFR9aLH+4XhgAZ/Eq6sV7II4cZ0QiiQm3oKiqCHJQA5nF//kIeaw1Od6h5e6euAw7HoDvdYsJ7qhzrm+KacHR2bMoTWtc0DRlpKOLl4jxL4qlrnCnpgNV10P58xHt/BDxO49EJuAOm8ecu5c9te1gwXwUUQFcJZY1aCdwzGg1ry03mTW+Rw9Z3qkJGfr+qD3zBPj2eCMmfdMnBVCxRhpJzHVRChZ+M11Ebzy8DguvXcn2fmh2fhAYQWejibAjcjacZ+N9dSP7S4iG1VXE/CbvJL3OZclvM017GUwhVOmUZ5pZtcno5yDN9dBXENNJAufHMFNj2zCYDyx6k0/CRJrtSis+bxXyNtLCTs26WhrE8QBtJkwHCggLyWJ0ooq6vL7U9erLwklR4lsakQCvdYsR29u95m5WTJ2UlBP4fEgkNfA18jXl5ySg5RMmmFjxxadX9ksnaIya3QFGRPOYLww8upW/6xXwc6VvMcL3EEcLT63kYqC0q8X+fOmA5oHr2LmWKonDiOytg6pKJjSUpB6PXH2CnxUCwwKKWFz6QC+PzoSs81A/9QSzu2/nlhjOxG0EmE9ucUiUkr3hyQq7YkxbOU7zuRmXmE/nZ2JIiSqFHzyiQ6CllntxFefGeg/JILH/ui+PBwv1Cc7ytw8aj827AZjwAGlQOu0xrMB6gTFO3/D/YseDeC5lvywuCfDppSHTET+P2HnmiyaG3yXnfYFu01QvDcS+xjt3RcHD2Fb8w0iJQnVaOTg3Is4OnU2CcVHEaoktrKU7J1bvI6jCoE9IpLi8dOCntORCOsLvhKNwFsXO1gFu2DTnJk9m9Ab7dgsgb5PQY+BDUgJ6XktVByLxV9Enx4rq5nCBDYGPK8pIdn5/7q+A6nrM4CYmkr07Sba4xMxJyT5naJ32GQHjGNneZnfWmsab7+tcOhQBnFxDzP6ujaGjerYqk4j0K73zrPvcR0MgyupjQ6JzLoSNMVqdVOFCRUCeIdryKaMF7kDC51V4SQCs8nAsvf6O5cEDj3QJLk+enYYt/99PcbIwDY+VLUCz4I0rggUHwt0S7EZ1bPGuQ8k0MSdPI8A6g7mMrVhCaoqfNpWqSo01UWwf1N6yMlwXcVPgsQe25eExRT6pagqrF9toMfgDP425Gvu3v5zZ9Z8gkFP2YhxFE2cQWOPfBo79mnM60Xf5UucEhQA1sgoSs6YTOnoCd15OU44PAh2tDKI+CCsvgyILyPsWBc9Socxoi/mdl9T0hpZuvH8Qi5//HxW7chCQfVZgk6PlRxKeYr7/BJY0AL/xU3XOj9AT8N5vKiqj+TSP85k26FUZ/yu3S54ev0V/O9Xa5g3Kfwa8ccL5VgxYpd3MkMomMQ69jKYDYznO2byiPJnbLKLn6mEd16O4NqfNTEsK81tOs+zLrwrPDuiz3dVOImscewspze2uxMLQkFt34EkHS0IuI3zrZaSr1+pDiL7LmhpiKCqKJbMXv7f458yAhG0veszwpSJlLz+657sfr2WRfIyjAe+w+HD7ZueRsGMeTRn51I9SCs/WzV4OO2JKeRtXIOhvbNjbsztxeEz53aLcyBQHKxjBgu0974rCV0AxkiVUdPL2LQs1yfhF4pK/tA6qopiWfLaQJeQN0/SpFWU+hcPBiSwUgjaklJoyfT4/oRwel3jrGUYrZoWt68iD6B9z267u9ybvzxl5R+/12O3g07RWmp/Mo7JM6w88bIJ1xo/rjbD9R66LneQNAccZBY076wdLcwAHN5Hrb848uVK4qxltCpdV/8xYuXf3Mcf+TPLmcW/lftYq070MzgLTGSlFJjb9OzdmMHIEGZwgk2TB/PGeoYV+COyrNvUZXvckpaJOSYWY2tLEArf0eaaciqrspHS/8hfCDi4NTUsEhtO5TMHfhIktr0t3MvQHkVLq8I9G2/EwAZu5yUAdFYbuZvXEVNTxd7zL3fOE5kTkthz0dVENNYTXVeDqjfQlJ2HDGl+Pjy4jppdvWb+Eg/8GRBXOJcnW7n84WIW/jkPi1k6PbI6nURKePnvR3lm8QTW7tIMti8Cq2DnIj7maX5BGv6rHUkhUM85G9ulWpyrw0B1F+x2uHh2KnuOaNdmc5nOMFl0XPu36axYXMO4Mb7jl1QVVv1g5HChnsR4lTmzzMTGHp/inGXzcsTEkYgvfU//hQKHN/Gv/A67KlCD6jn490vWVAnKivTo9a3OOFjAJ4H19x45DKyrQT1RGbLBUD1gCD3Wr9SMbQhT0vsZENJxrQE9aD99+CNoplYD4ZUY0bbdvj+eGbzMNkaR0CHRE11dw7CP3mD3xdfSlNOjY3NB2ejxlI8YS1x5CTqrRVMSCVEKL5gX1lcYgQOhhhGEKjs29cJC6iqjOLwztUOWSXFKNaXltjJqRhmLnh3WEQ7k+57mUcxfeJjredPvebQ4V4WC2fP8Jqv6ihH2R17d1Bk6/l3xjZ5HH+pkqTaXkeC61Xquu1pwzZ9Lncs8+52mOh0HNkdhswpy+5nJ62/x66UN5p3Nn6fN4MXIapoys4mrLA8rrtoVydTTh8OsVSf52cKhFxOYyAoBxQcTQyKxDoRKzjy9sZ5hBQ4i6wtdtseKQvG4qfRd8VXwbdHyPhoIHKYnpcDSfuLt6k+CxB5v7fPf8Ddu5DUiOir/CCTJRwtILjxEXR/3TtCckNQ9WqNB4Gp89lui+XRnOUqA7JNQNWKTogz0GdXGz/9XQOu2PFYt12O3wdlT2rn1+lZaWmP45iH/L6fAzlB2s5ArAp5HApX3P0Tlz+8HW9dr2wfC6uV6duz2HauneZklf3w6gade8dYp3LRWz59+GUVpcedHFhklufnn7dxyj7lLiT4DjW1a5zB6JvK1D+GINmUaLiRQSwqLOS9g8YNQXWRS4pY04ElgQxkEgdbpDzR2Jhn8GERWNRjZdfG1DP3kHS3Ux0eSlyu2MppQpMuSMk5sKezTFdFxFloajIRHZMGGgaP04lVu4j6eBjoTcfp8t4Rt19zmRsCkTkdTbs/uarbfRC7PONjjDSNwhU4vWXDHHgr3JrNjdSaNNZHEJlgYMrGS/qNq+OylwWjfrP9v+gXu4DwCEwlTYjIH5y6gJcP3NxeIwDrIqy/i6qqR+8Jfe7lppbpCtQsOboyjrSyGnD7uut9Ws+CjZ1JY/1W8m4JKjwHtXP+HKtLztAFxvcnqk9T6I7P5aES2buRA4r/uWtyyg5a+yXXosWLDn60L8V0Pw7SH4o11DfuDTm+sA46wAjgxiV4Vw8dgbG0mb+Ma7dvs+F593Y0D9McelD5KUnNOfCjfT4LElhYkEJrcvW80kMy3nMU8FjuXqUKQuWurF4k9WXAUOnBAESIkohqK0bWZdahlZ7DxSx3NtXoMRkl+fyPWiAi++EJBr5fYbH6kYtCxkxGUkUU2vkehEqjN6cXLZ10P+8OPYQoVn72biaKTfuWm7HbB90sNfLK9wi2hrXhfJK882BPpEQDWbhI891gUu0tamXWdfw+zL6hScuFwTb5moLENy/vvYrzgYmSpZnTCmbQSQDVpQQisv6O6IybBxtamEvLpzH6F8IodOLZ3eAc0QqB5ArojHitctCelsOX6u0guPEjW9k1apR4/2MD4IEeTxCRYiE3oehGOnypMrXrqK6Ppql0FrXylg8SCRmRjaquJqa6gNf34Sn0G8sKCbz1Y8CawxxNG4InSI/Fs/z6LI7tTkFJgs7RhajGgqnB4V0rA2GI9Vj7jwqAk9tDZ80MmsA7yqvQfjT5ec744QtNcSasDSVEGGqp1lB+OJBAURbJjtTuJlRJe/VMGe9ZFe5HfkoIInrwrh1+/Ukximt3rfruSWlcyC5o9VfqP7vDIQvm40WRt3OrXfvpa7rqsnCyfM4zhQErI7dcYfEMXhDNV7ssb61nNC7o50UsIiibNpHLISDL27iB763r0fiTMvmRe0AqTIOg5qIsV5MLAaU9ibVbBpm/zOB5DCxppcIUiJQklR5nw/GOoej01fQdRNmoc7Ukpx3WecBGKFxZCr+dtNul47R/DaKmMd2a5Wy2Crz818O2XMGOOBUTwTOS2IKVwFw2Zxbr1h4IeB7SyuF3RhysriUVV4wkYv6QK1q09gmKw01CSiKkhmiNrslBt/j0iqxemMOeyFuKSQs8yqzdZ+XxXBQtGZGudRNZABu3eg+6BB1BeecVb+kZRwKAHs++qY+lUIbD7VCkIFUJIZl7aiM7lKw81htoVDi/B+cMyfRrT443H6gqkTkdt30EoVmtAEmsl+Luckuntqf//gqWrDmCI9P0t7/4hE6s12ExAgG8PhSp8l4wduuhthJSYklIoHzGWqoHDQk/xJ7A+ZihyWr5mITwRrk3asz6dJa8PdPNg1ldFsfz9vuzYHB80OU4iAtpViZbY2JyZ67XO9X54EliHM2S/Rfvbk7x6fv+W9uDPQSLZf6AOVuzD0mag7lgKzZVxFPzgu7Kmahe0NQleedzOoHO876uD2HmSWbuqst8SzcB4sDmILNCSm03Pr77DYGpzt6sdHkRVKCjShQS6bJNFeUeuR9dsqxASQ4SdweMru7R/ICLr6o11nT2D0MMKjtexYE5IonjcVFIP7EHXUOfzC28nEgU79iCDAUeFuhOJ057ElhfGYw4jqcsfeuLdESo2GwIbWMxk7tpC5p5t7LngShp79D7u84WDUL2wgep5H9iSRlVRLCWH42muiMWz87HbBVJKfvhaYgsigRdDCzmU+h3xNsclUTT/UoYaA4/mAbcpFtf2t7fpsNsUomKtfvu25nwrFXtEgFkdSWyimURTDt++0q/DqxQcUoWtK2KYfpHv6Z+KowaO7Y9Ab4B+o0zEJ9vdgvOdo+iYGOwvvIB61VXo/v53xLJl2vHj45BXXoR62/VQVIooKkH57aOIls6plxTqmMdiljAXu99pr8AYMKGFMQu8R++uCDUMJRBOtifWgYRjR+i/9POAVGoou9nFsIAdltmk4/uP8uk3qobs/Kb/d5qx/uxGwfaUIFOmjvhB3zdMwU4vCn2uM3RIQ8VWldN/6eekHtzLvvmXhZRjEE5VrkByWg4cjxe2ujSGA5vTaGk0svsHLQnOPdlFuzc1BenE6ZpptnvbXgckgiHsCThDc3TymV5k3/V+uBL4qL6DnNfvILCfbKugrVGHMUohM8X3vU5Ms2GMULGYA2umTpgUT9HWaaxfEo/dOXPn/32QUqF8R08uvbHEbbkje99uVegVM5rWJh3GZBOL1DIuHuVOZBk7i3ygrbKKA6nJJOwoJGvHZgztWjhQY04PisdNoSUjh4TSYyQdOUTm7q1uLbqB1/k3v/B7bYEhEYrkort2ExEVvpROoLACRx9yvGEFxwthtzP047eJ8kNgAUawI2i/JIRk+8os0vNaGTy+ksjoLkgPhYDTnsTabKGO3n1/XAKVXEqYwfc+1nVCkRJpVxn0xQdsuvUX2I0RXtufiijck8QXLw/GbNIhFNlRJcZ/tacWSyRRtNJOlM+pAh02buIVjIoFOzp0aueLKYD65Axevu8JrCEQWF84vDOZ9V/1oOyIFpcbHWdh1Iwyxs0pQm9w71GHTa5g7Ze9/Ha0QkD+0Do+fHpYwOIA3jtC+VFvD15dhZ63/pZOwY5O8XVFJxk/p5lLfhEgwW3qVGxTpyJLC9FVFEJiAug7Pr0hA5FDBsJfn4QW9w72r/yO5czCjAgh/sgb595eySWj/XtHHcUxwiGysrHaTbfQgZOtUpBcsI9BixcFTfD4Oc9yC/8LuE1VSSzVJbFs+jaP3L4NXHjnHqJifFX++v8FLYM+2HcToOgGOn7Gy27LPK2w4/klHS0gZ8sPlIybGlLbQk3mgsByWl2F1aKw+NWBHNqW1pHE5bgq3/dDIImwt9NKtJ8BlURB5SZexW4woLdavcxa8bipVIwY67bMQWBdVV8cnlenqg3Q0qjw4O9sbPm6HxaTDoRk8Lg2zrmunt5D3b1lxkjJ+HObWftZvG8pRiGJjFLZvDyGQ9ujPTzMgd8Xs0mP1SwwRHRe3ZDMeLauyGHVpz2xmTttUVKmhcJ7KnjgxsROIuvIO9i8nPRJw6kwGCgaPw1DuwlVr3frl+vy+6NvN5G1e6tbG0ayg+t5nTe5LoSQLW/0G1VNXv/wQglChadSQahhBd0FncXM0EVvEVtZHvBJzuUrciihnExUP32TlLBnfSa71gq+/yifOdceZMiEqm5v82lPYtOyW/0GoLvD22sgsCPQgukVF5PhfyQs0VktpO3fTcXwMcff+BOMyuIYPn5uqFPgPZQyhwYszGMxn7AAiepGnhShkpdYy6zrJFdFvEn/nGRGbfiWvKP7sev0HBgyjn3DJ6LqukC4Zg7mhX+2sXfJMITofBZtzUbWftGTg1tTuPrX2zAYO9fFJlqYfeUhvn2nv9c7IIQkNbtVKwUZQAbEF6QKaz9LoK1R4ZrfVmOMkDQ3KDx5Vw7N9e4dkGoXrP86jvpqPVc8UhT4wLGxkOo7HEWeNQPe+1gr1duBYexmFdO4hZfZzmjn8khMmIkIaIAVneTyKe5TuZXlgo/eNrLyWz02G4w6w07axAiSBgcWoao3Wd3K17rix/DCJh49zKAvPwopgOgGXucrzuFjLgZwuWeOr1z7LhxvVemReD55fihXPrD9/51H1hOZvZqpLI4NWMVIg7fF1GFjAuu5infdlgfS983etomSsZMDhhWEownb1apcoeCr1wdQsD0VIIT7o713NaQxiTWsZ6IbkVWEHSkV/tL/WSqHn8OhnB7EVpaTdmA3+nYT5vhEKgeP8JIbcyWwrl5X6CSvAO+tqeZ/9/WgriKusw+Qgr0botm3MZrrfl/J2NnuA+jzbqrjwOYoakoNbkRWUbQStJm9LBza5jt0IBhe+PVEzr91H70Ga/GSm77N9VmoqKHSwFt/yENnKKLXMFNnqJbFxMAOIpt5BrBpH83Rvp91fc98n8mf/+MWsijn39yLySWEI1icp1AkSR5VqKQKR3Yns2NNFg1VUUTFWRkyvpJB46p8Cv2HEhsbjjcWvGNjoQtKBarK4E/fC0pgAXSofMBlzGYZVqRHklynbXXkq9htCkteH0hsgoWegxpCb1MIOO3lvWMTLfQdWUNoqYLuj2YIe/mKuZzHkgBbuUMKQVx5SYAtTh1s/DoPLSwo9N5YRWEYu1jFNObyFUqH/HWiaGDKxTXc+XYbxRfNpzk6HnNkNOunX8CH1z/Ex9f8kj2jpoZFYHeXN3XGQlXp2PuVVhrWe0AiqC6N49U/jqOt2d1rOHJaORf/fBfZfTqnaGJi2pk8bBe15VFeNd5DQ4dM0KpY3vmH5sVZtSiBpjqdzyQyqQr2b4qmcHuAeLYgo2f1ustBp2gxXS4Yw1a2MYatjGIhl/EV57CZMQENrU4nOXuejWiX5mxcq2Pe5Fj++7SRfbt0HNqnY9E7Bp67oxfL3k0M2DZPeMZhnVQvrJT0Xv1tyJvrUFnIFTzHXQzggOMg/g+vKpQWJHQki/7/xsjp5SERNNCImAORmLiNl/iGORjp9CoFs9BGUysRzf4zuEMhsMG8sN2BuoooDmxJD292By28Yiln8wh/JNMlKfaMhN08seBNppzboCk0CEFLZjaF08/m0JwLKJo4PSCBNY6d5RY24CCwn++q4PNdFSx/I5X6CqMPJ4ZASnjjLxms/sw9bCImXuWXL5Qy87JGImMcz1YyfGAFQ/pUcnRv12baACwmPYv+M5Sq4hjMJh1r/RQqklIgVfjutQxAI3Y6RQFjFPtbBMaxs4jOSCfzjEF+Y6StMXFUDhruZVf12Pk7v6WSDD5nPh9wKfsYyFUpS9DpAtuHwRM6Y2HtNsGnLw7h4+eGcWRXMrXlMZQcSuCbt/rz2p/H0tIQfriW58yY58yB5zvt+c5D4FAbf0guPERCWXHIbGES69jCGK4W72JUXGeufLsABfDDku5TIHHgtCexALOvPIQxykYoRHYxc/mW2exkGDsZztmE3iFqEFpSzikOKeHgtrSwvZB29MznCyayni84n2biqCaVGpnC5XO2EBV7YkrIrVsSPAO4qS6CD/89DE+HYP7QOq56cDuP3fs/NvWYRmNrDMadVQRRuQ8KqQq2fhdHVbGBdUviA3qyFZ1k+7LAxMfXNLwTvXuivvA4REQ4VQpd3+ZRbOcyPmQO3zCEfVx/xhYQ3u+7opMYI+Bn95mwqyp2VaWmRnL3ddGYzbh5VewdHvrPXkrhuQeyaKwJnfA7yjSf7DCC6NpqYmqrw0rj1KFyBy+yj8GU/rAXh5fAHxRF5eC21ONt6mmPtJxWpl10OPiGQjI1bwcrdGeyghlUkMlz3E0M7p6hUJ6ZP9saSiJXIE1YcC9scDw4uC3V57cXCDqsnMdiYjDxe/5KKTnUkEITcXyRfjVn9AzhPnfAk8CCb/IKEI2RHcsS/FZodHwLHzyZxq617oPw6DiVC++o5bFFB/l6wYPURGby3N6L2X0ok+NJpJZSI88bl+ZxaFuqS+EH39se3RuJrU4L4fpkR5l2bR5EFvy/I0fOnEt9T83T62lX42hhPl9yKR8xgAP83vYI0RF2P0RWkjv6GCmZnXJ8P3zZk4Kd2uyac8AntXvaWB3Fy78fz571vpMbgyUOeiYdesZze77j/qrThYr0vTtRw5x+GsR+XtPfQvE1dzBxQS1CCTAAkIKSg4m0t3Wvduypz8ZCQGyClbnXHSCID5XYJBtnxm9iNssZxm6/8hyBzJMiVRp65B9Xe8PFghHZXhU9gkG1C7daxqFAh41ZLGMkO5zLojGRSi06VKQg7Ha4or1NR/HBBEoK4rFa3NtW4SMG1RuCquI43nq6P5sPmNld3uT8qevX84tn72BU8VoqyOQ7Znc5+9TtjIpk+8oYWhoCH0u1C5pqNS+0XVXdpn5CjWGS0yZhX/0l6m/vg7wc3+3p+Pd/m8Zxf847RBjcYzfz+6m8+nEL502KomdMDMamGJa9H4u5nYAkfP+mKP51W25YRPbHgMHU9QQGGR2FGh+ah9VqPrXvw8nC+DklJGe2EtAqSsGw/BKm21cwg5XO4gbhQKLpn1pi47zWBUrkCkRgg3lhA8WDByIYVrOOQOmk3tAy4X/FY84lCpIU6ogVraFW9AV8E9h95mgO7VPY/IOB17/RJA2TogxafGWl3svW+sNrj2SwbYVHiICqMu+Ruzj70ydIaa/idW5ATyh9QOD7I1WF/R0JcYGIjwNLlxU7rwnwIrL586b79ciqegN7L7iCnZdeT+XgEX5bJ4ABjZv5XpnO4MRSt3V6g8qUS+sYct4upISWBiM15VFsXZETUHXCZtWx5LVBrF/Sw215sITB7vDGQuDBnyeMbS0oXSkiYbVh7duHvPjYkEKwutu2/iRILEC/UbWkZLUiFP/ut5vS3iOiJbBuWSAfjSoE5th4avsO7HpDTyBcsx51eklsUihFICSiw2U5jo18yKU+tgBrRibTz+laeV2zScc3b/Xj+Qcn8f4TI3nvX6P4zwMTOPjdAOwdHCwiUg05BrHqQCYbXzuTAT0HM3FCPyaO78sD37+GTqropEo5x6c/6QqhSBqatAFQIMOs6CTDBxq84kYdBDagF9YViQnIG68CW+DEIj0qj5dcR6U1hbd7PMijj9bw1hfNfLismUmDI7nzToXMDD2DBxn46191Xt5rbwia63V8+Uqy21JHZ+7pFXCQh3CMZHfA7IPkhAIJYLORbK0gITHwzVClICXrxIt0ny6YesFR/CYsCUmkwcQD+38dtK6cBL/V5wRQMnYSnkYgHCUCt+N5dPKeXthA0loO+CMayZltIYcSCOwYsPEW1zKFtd4bSEljXmhqN74I7H8Xx3PRzDgunR3PLZfG8PRNfXj9wZ4UHdCcAsao0EmJ1azw6p8y+fCFBOpNVupNVlJXLqP3uhXOmNIysgMUCfBE4O9Mqgr1simkXI2IuHanLfJHZAOGFghBU04PGvN6BezjBTC65Qe21/ZggxjP/67+hn++0Mp3O5o5++ZqspSxvPTwKF54aCKv/WkclvbQwudWf9aLxhrvZPBwZdzC8cY6vplQbXR7fCKq6BolzKg4Sn5/e9B+JiLKRnR81x1hvvCTIbFCwII7dxMTb+2Y6umoNtExypsf8TmPH7oZEbw3x96ROe54oI6j2aJi2H3RVSek1OzxwleQ+MhpZQQPsRDkUsxSzmINU0iiwedW1bfeAR7X7UqaXb2ijh9oWbwLnxzBrh+ysLsoSdjMBg6v7scbj6YjJYyY1hqSMXO0ub1Jx7pXerJgRDZX6mvJLDzg1AXMJPRazcG8CqpNcNaEKK6+3hZQxlK1C+ZfqmX5Orywjkz+kAmsAxYrorwyhLxwSQJNXFX6FD9ffiXDRttJsscweZKe119TMJtDzxp2XMOmpXF8/vUBlqzY69VpOODoQLsSd3W8aE9KoSkz1yvGLRgEgNWG8dXXuP126ZY86A6JokiGTOiaBuRPEf1H1zBhriZBqLg4CYSQROjNfGedRY/K/QGP4XhatsjIDnuqLXHY2JLRE6gcMtJtn2AE1tf0qb8wAlcE00cOVma2/+iakLyHAA/yL4rJ42qPBDfo6FMiIqgeMCTocXwR2GcWJXDvjTEcLXA3TIV7Inn67hyKDhhJSreR09dMOOWlVr2fSm9LHgtGZDN37edu/V0W5SF4YiWJNKAEJLGSxDQbN9wejzHSf9uEkOT2bWDcYO1ZHReRBa1kfAghJQqSM+RGbnp3LvcN30F8gmT1B8m8/kgmLdXhD6SFArvWujtXQimi4TrYOtGxsZVDRrpp64YKAehefpX5M6vR6/3PZQshGT61PGDMsQPhkPufDIkFSEpv58Y/bmLmJYfJ6NlMYnob+UNr+dP4Z/jEvACDDG0EoLPZODh7HhXDRtOUlUtDXm8Oz5zLluvvxJTc/YkCJwp9htcRCnmZzkrOYpmbQoMrBBC1fSt2a2fJQAdpdhDWc2cO9vrtLm9i6ZJEKotifRNUKdi2Io6tGwxkDW8kOz90Y2u3Czas0VN4GHRF7hq/uZQygxXoCOTNlDzFvVzHG36NshCSuFjJ3Rc18YfbGuiZZ0fv4wMUQjJrrpUxE+xuYQRdhl4X1kBJ2O3Er1jGoLoSfv97HeXljnjX8GG3CdqbohiaFe/TyHoazsyJZ5x0b+yRGWcjFe8kuKDDNSnRffAhycm+kgc70WNAA1Gx/z8ktgZnhtYhT73wKFc+uI0BY6tJSm8jLbeFKecUsE8MZgLrQ65l356UwqGz5lPfM5+mzByqBg9n+xU3cXTaWV5eWAjeCQfzwoZboS6UztNgVEnPbQm6HUj+zm/JwL+skGK3E1MdeMAUZy0j84xBbgR2V0s0f/ttFFJ6v8tSFdhsgkXPpCIEzL2+nnBiWHU6yXuva7NKcSXH3BRTrueNIJ5YST6H+Zo5Ac8pBIydV0dEtOSC22ud+7pvow0oZ1xyBOgkfcdDZO0GY8jvqgBQFJQn/kXJMYVlr2nvVbgJfY5Lq6+K8rnK3zsXqvSh68Atqu8gr8FdqDa6Ma8XNX0HhhUo44TVyuDN3xHtt/vTVC2GTAjuYAqnQh78xEgsQGS0nbGzS7nut9u49S+buOiuPdx78FG/BM0frDGxHDlzLjsvv5E9F19DxYix2CNOD21YAFWF0oJQXgZJL44FvTuJiz8n9X8vusl+uBJWXzh35mDq9/cPeFxFJ6nakImig6sfLSIuJTzy0HbIRq7JW6P1nzyEDrtTXcETj/I7fsEz/I3fkU0ZOg8i6/A4PXfPavR7lxFTsIylf/uEs88ocfPiGSMkE6fbiIiU/POBeF54QaGpyb+eakhQFGyTx4aVQCiFoHnxGha+L7pMYB0Y2qMz89ghBwO4la31NJYnk8i2ZOaw65LraEnLdFuuhkD8bQ0tPPF44FKJRfsTaWs57dUHux25fZuYd/N+bvnLJm74wxbuzHiNnpbCkOmRABSrlaohI9m74Cp2XnETBWfNpyXTO/47WElZf17Y4yGwDgTrRJvrjR2zSsFnuQJVNBJoJHbwZ++j+KgwE2ctI85aRv686URnpLslca1Zoaehzr+Or1QFR3ZHUV2iZ8S0Vi76eTXBMz402O2Cw7sEA3XN0Nbmtsdk1rKART7tqoKddCr5gcmMZxP/5CHnXXDbTpEMGWFnwgX11JusTFvQxNUPVRGX7L5dYrqJ/qOr2bwsl2Xv9aW8MI4hmUGIrCU6IJGt7TswZBILmoNAWf4d378vwiko530cITuSz90RLmED95kFf3Hfvr6PoDZaCA7MvYjSMROx6zu/kZBmvXQ63l2aQlODv2ANAVKrAtjdOO0ttd0uKNiRwt4N6bQ1G0lMNTF8SgW5/Rq1gb2UJNTXhJ1L2ZZ8amQnD0qL8VllJhAaqiP58JlhNFRFE6w0JAjGsTH4/ZGS7Feep+bWOwDNGxvKSLGuwhDw/KpdcGifwsyjPUiOhjufL+TVB3pSXWwM0m4NMYU70D/2kNdVjmMTy5jNrbzMATpjmBOo5xH+xD08A0AGVWxkHH/kEd7getrRRsujMg9x+xmfM7zxAEe+7Dzuq7cXUXtHL3aZzqC8Pp6/PR7HD98bnFMkCxcKfv9bwQdvGjlreNDm+4Xl0vPQr93sU+PQJ4TgWHU0VmvXCawQkqz8JmITLUG31Ub/+4hOiT7uModdQXNWLjuuuoXo2ioimhqxRkaTuWsL6ft2+Z0Sk0KwIX0eVcWB75GqKuxel8m4s04PKb0ThYaaSHauzqL0cDyKTtJ7SB3DJlU4vdTJtRWoinvBk0CQQGuq70xtV4Q6IAqkRtAVAhssjEBKWLekh19JKFcIJMPYicHPINq5nZQYzO2kHthL1ZARzuWeRQw8S8dWlOhD0kff8l0sablWBoxu5+pfV/HOP9O1CwkSwRxttKBcfSXimPsslwDe4yp+yeO8zM+w0OnYmcYqXuNGp+f5AZ6gJ8d4lN+zE+3aEuJVbr2+lYtvbyUqMYNPd5ZTb7IyYGYdfzm7mSO7Ilm1tozKvVmU78mloTpSS5wSkm3f59BvVDXzbt7H/ppGp9aqo0DA57sqOH9YplYUYewslKZ6MkHTke1QUTElp1LTdxAph/eHTmYtFg4V6AnxNfcJVVUYONZ/gm8w3VgHPIsf+IKvcrQOGx1MO1bqdBydOpui8dOIqyhBqCrWqBhGvRe4YIyw2/no8JhOOX7fW7FjdRYzLz0S8Fjh4rQmse2tej54ehiVRfE4yFp5YRx7N2QyaFwl596wH0UnaI+KJsoUGhGUgGowYI5PPIEtDx2hysIsWbEXm1nHms97sn5JTxfj5t9Y6YRKlizlXA+dXF8QAKVl6KsqWTAiJ6TECICYBDtmU+D664f26Xnwdu1VjI7px3W3mdm/8yjfL+sVsP0xkVamvftzMFt8bjWVNexjEOuZwOYeZ5FftIVZLCcS9wo1GVTxInfwBPdzNLY/xy6+kPgkzVA04/HBb9pH5sRYJiavY/RvLqKhSbs2V+9nmwkuuiqZbYvL6duza7Wj1b69aLj/DhL+8z8waQl6AYciqkpcfZBiC0CnhfE8mjbdM3n+0bDb+mOiLSWdthSNGFUiydy7I+D2TbMvgNeCHVVyZEfy/2sSu2d9Okte7xj8Sa1nKjqQyLrFPbnknl3k9GmiLSYOEUYMnQDnswqGcL2w4O2V8rSbx1NiufhgAsve70NNaWjhFxLBL3g6pG1VoRBfXuxGYqHzHkT1HeRWfUunKBS01CFlcHm7xa90FlfpNbida35dxbKnFSpM/sPiFCG5IGsVhmU+EtGACCz8h3t4hD/yXdS5tCWkMb7iKwY6dZg7cSkfcQkfUUYWDXfdTuacPiQMGtAx6GjjwuFanOjnuyposlrpNwoK9+azfY+WYOouWwUF21NZvrAvc6455CxX65fIxtPhkcWNyB6ccwH9v1ZJPXygIzZbBqb00VHEb16BjrOChlJocD+aUCQ5+Y30GNDgcy9HKVpfRDYpyuBV+MATIiENO8GTh8NxNqhGI40uKkz1PXqTWHzUJ/GXAEkJNBlTAyo1gKZM0NJoIDah+5K7TttwAinh/SeHU1nkMCrazXO89Ps2prOuQ1j33SG38zK38DZXU0lgIyoAndVKTFXoyUEnGsEI45IVe7Ga9Gx7YxrrlvQklAGmDisxsoWPxcXowhFUDWEk6Irx5zQHSYJwf+nbWgUvPhnB4KJ9Hd5S3+cSqNwx7GviC/YEHFELYCLrmZu/kfNY4kVgXRGDicEtO5j52TPoW1tI27eTEe/9j0n//isTn/07A778iPjCIqK/Wsb7f2+hrl7vc+peVQVWm+C5N0PrsP3BMmIo1f95jKZbr8OWmxVwIlACfV79A8PZ4TV95w7BzHOsCKHVANd1BOLrI2zMv2UfvUKspuIwmN1Zs/t40ZyZQ8XQUT7vkxQCtV9v+v1sMqFMA1cc65oKwk8Bh3cmseS1gR2zzy6DYSmwmnV89MwwTK16Ng2exYfyUl7mFr5nul/lAQckkFB6LOA2wbywoWjC+kvkCoRAsbC71mbw/hMjqCmNDXoc0RGHfx1vcD1vBN2+YyefU7aOa3W9PgcxHzC+BUNE4MQpTxzbH8GifyfzoWkB0bT4tBM6bMQpLdzS+FTQcKZk6jkvegkXRi5yKSTiDQFkU86Q5/6I4aMvaF+zCnHT9Rj7DmZ4XgoDJ47k5tULGbj6Gwa88Azfvx6F3zAJKdi1NpOWRoMzbt9naAH4DS1QDQb2z7+MrVf/jPIRY/zcrU4otfVcUvVCQAIrFJWeg+qIjtPImaJTnf1er0F1LLhrd0D1nWBhBZ4JXuHOzh4vCqefjV1v8J2HIATtd11Hj7zQeMGhbd2bV3TaemK/facf1SWBOhrBpmU5FOxMoapounOpHis38hrPcE9AQhPZ3EBrRvdJNR0v1q0/FHB99boR1FbEBB0JgUYA7+Y57uVpesnAnYoDUoDs04d+g3uzryZ04jLlwkZWfhyPqVnnY+rLf4HfFw6ewwHuoY5k3uZa9FiRCERHibtb+B9/sj4fUhtUBHGV5bTHxRPR3BQkuAIiGhsYsfA1opoaOqfz7SqpBftI7Zim+ZKfd/gufR/Nbhcs/DKZJ39ffHzlSyOMtE+fRBGSIW99AO1mfxFHCODPPMyFfIave6sIlcuvhIf+1UZZkY6n/mdCsRhIy7VQJbYwsGfXktJ+jNKzPiEEBbPOw5SYTM6WdRg7NGXtej11g/oT+cgv6J1aTXJSLnX1geNnrRYdUtWyiv8/oaEmks9ecmTLe79pUgos7Tq+fGUgRQcTUDnfua43R3iVm5jBSp/HFkBkY2CJQwgvmctTE7arcbDgm0g01UXwzdsDOv4K9iFr+QWP8gcu5/2Q8zAUVaXBRWbLNR7Y4YUVCWnQcW2f7CgjMgbOvKKBb95I9nVIn22VqsBiUniVm1jKHObxJY0kdKgISOwYSKKOJfZzySguDqrkI4Do2nqODB5DwtHioNsCxL21ELnwE4TV5jy+segYWX/9E5cC34kZNMvAov1SVSjYnsrI6VrVM1cie+7Mwe4e2RbhXaK2wyPblpbBkZlzsUVG0WPDav/nA85jCSPYxm6GYvcgswp2EJA3YxcXD1Mo2J5CdUksOoNKn+G1pOeGTjj9eWPrTdagHllXaN/Ivm5zMrSlpLPjipvovepbko4ddj5PU2oK5puuQj/5DOZGV/DJl8Hl4mrKjq8ogydOSxJbcTSWHauDP0xru4HqYvdLtGHgFW6minQ+YYFfs2SN7N4b3R3wN1ozm3Qs/SEjZImqKEw8zX1hnVtIUG+6EtlUAx21pl3jYn0VQWg6Gss7/0inrcn1GbhOufhvr4LK+1zJW1zH/TzJm1xHBZnkUMoNvM4Q9mCxDPC7v1vbkejNJoomTKf/t18E3V6RkqimBm1fFy+va2vbiCbYREZ1nYEx8wfz5pNH6N/LjMEgu0xoVb0e4YfAuuICPudlbuFu/oMFI3psqB1qlZckfMuLL55JYTPk9ZL865FI/re4hhidgcojmtJEII+Ao4iDbGzDVOBuIE925S6/EILSsZMoGzWe6NoqhCppS04lRtSQH6UlrJ0zo5V3P4kjWKz4vs3pDB7nP7P8p4hl7/XtSFoK/KYd3ZPitewYPTmbpaxmKuPZ6LVeAtaorqt3RKdEB1Qj8CSwDhxPGMHONVkOd1PQbXXYuZvnuIr3gODZCKBpj1ti4qjro9kyT0+0g6Q7wso+2VGG3Q6r38hk1See36rjjAEG11LHO1zNC9xBCbm8w9WsZioCyUxWcAXvE0U7loi8kNoP0JSVhykhkYimxuBi+RKER/iX6/8tMrTk6WXv96WlMYJJ5x5FIrym5OtNVi1+1BjF/haTk8jmz0vnyJfaIMvVZqmIgOo8OlSWMocL+ZR1TEKPFYHEipEEGrnvpg2sy7Ch08UzYEwNeQMaaK6LxBgZeiBtsLAC1z7W4Y11qOGEE1JAFystmlLS2LvgKowtzUQ0N2KNjMIQayZz+BD0wNwZjYSSg3NwaxqzryjoNgfBaUlit6/KDimoHXzLYajo+IwLWcdEJrHOfXvAEhNLU3ZedzX3hKO+Kgq7LTRJJgU7g9kTdDunOezwRFounIN5ZD8cdbUWjMjmkx1lzg/Lc4R4cJ/CFfdGY/NKNAoY+e3Szs6iBaPYzii2e7VP6vWocbEozYHlbiSC9vgkqoaMxGBqo9fa70AGjoMKhrFsZgcjggp/7zoQxeh5Q5BSYDSoXDK3ngd+VsGwAaaA+/m4iJDbewuvcAkf8S5XcYh+JNLAZXzAgEwVW+RuZBO895qeV/8TSUWZ1hEaI3LIGnEU65kHGNW7cwDnkE87nkptJwPGlmai6muxG4y0pGcidTpa011mUlya/8uKX/EuLwY5omTrd9nk5DfS0hhBdLyFpLRQioecvmiqi6BwdzLB3zTf61W0Sla/5a8s5yyf21QN9p/tGEppWVf40oQNt6BBMFQWxYYUngVaye4hLrY1cOqUBltkNHsWaNrjrrq4DsLu6oV1XM9Xz2SzcWmc16ybEFr8pZQQKFTZQgSNJJBONT/jZX7Gy15tq87KJPtYYO8qaP1De2ISuy++lsGfvkdMnbdSjFsbgxxvKLsRqMggDgKpKqxb3IN1i3sAgqT0NkbPLEXfvzOsweG5tBujgDaMY2dh2byc/HnTOfLlys4kJylBEaAGftDpVLOWyaxjIl8yDzMRjGIbl/ARy3s9TdKUs/ho0VHK1wzj0LY0J/fI6NHM1AsK6T00+CyEg8j6Qzje2G6BqhJbVY7OaqUtOQVrTByW2DhnZT2DyzebWbqdsylnKecQ6Em3NRs5sieJ6DgbSEjNacVg7HqN+NOSxNaUxXRNq80Feqy8yXVuJNZB3I5OmcVx6WmcZOj0ob8AKjru5jmf61x9pFJRaI+Lpzkrj8bBPYm/aB7RLm5Eu6oG/Jie+1cEqk348Q4H9hZo7VTIpNzvegHIkjLKRg0jd9U6v9uBJlxdOXQkAKVjJyFUlZ4/rAi4TzDcwQu8xO0hbCmQHb2gxarwweJkFn2dxOcvH+LMSc0B94xOiaattk2brtcptKUmE1Vb7zcG2PWOJtLInbzQuU6nQz3jcmRjNW8/lcETT+hwHUxYzApFm3tTX5yMuPEH9Ea7T69sqCV0TxYimhrIX/ENyYUHnddujomjaMI0KoeNdtu2rbYN5eBiRq97iVx+Swk9vA/ohKDiaDz//V1nlbqs3o3MuOQIuX3DL6t6OqCu0n8sojsCePrQ8x2zKSeTLJeiIxKtrGz1gKEBjxxqZS5/YQSeOB4vLGjlRkMZdyvYyaWEs/jW53rX3W0RkVqWfL/BVA4egT0yMmBhB9drayuLYeM3vmdLpNSIWDDSbcRMAo1+1wugMbUXqbH7MbY0+30jVKAuvz+26BhswLZrb2fic/9E50MuzNlGAr9huZQyny9YwrkhVAbrPFJ9VRTLF/al95BkvmQd82YPcpuC32+JZqDRD5HNykUJMc9DAJNY584bhKCgxwDqy/T88PIUbO0GN35SWRzLR88OY/6t+wIqFARDMG9st0JKMnduIW/jaiJaNSeRFILa/P4cmTEHS1yC2+ZttW1E/fsFbhCDWSrnBjs4n704xOl4M0bYGDG9nCnnF6I3hK9Se/owNRcYI2za/PZxwI6OKh9JXjZjBDX9g1dQOZWQktVGbGI7wT2cKufzGdfwts+1js+uKTObH+7+DVtu/DkHz7mQyh6jnHGPtqZ6Bhrd42zsqur2q6+XfP+N76SnznNJFOHfcKgoXMdbAa9G39bO0VGzODZ+mk8FRMffpaPG05aa4VwerEJOKG/WCHbyN34T4h6d98FmF1itgivu6eNRUasTDnkUz+n6mpFDQyKwPltgt0OfPPbs03cQWLz2kKqguSKB6NrxQGdFNk8vrGXzcuf/f8x4WGNzEyPef5Xko4fcrsTY2ky/5YvJ3bjGbfuKdZswrNqA1OsZzi5EsLKYHre64mg8C58YwbH9id1zAacYjscb4olqvJM3KoaOQjUcH6l0RSA1gu7wwgLkD60NIc9AxYiFt7km4JS0APZccCUb7niQnZffSNno8dgjOzWZHQTWNaHLcY2Oa9u0NA4lQMUjjTz5b68eK1fzNhH4l9GTgLGtlZ2XXu/0uHmeUQXsEZEcnTrb5SIFNf0Gdbl0qQPPcydZlAf9Pt2hXXfh3mSObezFkhV7nQMYx7vgUHdwyJU55Mvqe/ahPT7Brx5qIHVdCVhycjHFJfDpCynYzUak9Lj+jvfnm7f7Y7WEdm/CLUcLHSEFAcrQhoO8Davou+IrjK2ds5xCSpKPHGTE+69haHV3wAhTO7pNO+gnD4Z0fNeZY4tZz+Zvc/n4uaFuMmZLV/lPFnTFaUli+4+pCcIbgos66zpGzq4QgN5iJvlIaDfvZMNXadfd5U3srWxiwrlFBDJekZj4F79iEYHVCAQQV1GG3uw9ddpW24Z6cCsAA41tTtIKmp6t45cqolGDxOfqsKGXVj9VtST38RS98J90JtFKWCIExROns/n6u2jKci9HaomJ5fD0ORROc5/aNCckUdNvsF+jJfBf490Vv+Ef/IFHCH2iX4MqBfWNet5/0zvo3pPAVrjELxUNmUZ5h3fRte2hkG4JKI88xhuPlPqsOubcTsLqz+K9ClmcP8xdpNrpIebHi4ftsWEVelObF7F33Jme6753GltHG221TSAl5/NZMGEdvEi+FEgpWPp2/5CnmE8nZPVqIiY+mCRc8AsXqGT5mEXJ3LPde2TQgXBDCVxxorywAAPPqCY20YxQ/NlMLZZ0PROYyho/22hQhUJSUWgamb5ifwFqqoJPe3eczWuJDhuxtPB7/hpwT4FmW80JSWy6+V6OTpyBNarzGUigvnd/dlx5M+2J7ollpaMnaGoLPo4rhQjJUuZQxmbGkkRdCFt7ngTKN/dxvmaOd8AxCHAQWdf7G2evYO/8y7EZI3z2CY4lvq5JAMbSEuY89CA7V8cE6PcEFpOeQ9uD6893pQCCL/h7h4IhoqmRHutXAd49myIlxrYW8jwcBMJkQgAj2U4aVQS2E74TRo/tS+bAFm3QFs49OC3DCQaPq2T9kh60NBo7deSckCg6ydCJ5excmwWeo6IO2DBwE696LZdAfGkxtf2CCw+fLDgIRKBSifp+B+g9WVC4th96rNjRocOODQMTWMcS5pIUYArJFQIwtLVii3LvPCrWbdK8BZuXYxw7y80jKxs7/5/a2oCe/tgCvF4qCvfwNKuYxmbGOZfH0syveIzfBTG0CEHVoE5dRXNSMrsuvxGduZ2oulotJjI13W9YyKGz56M3t5NUdARVURBS0xpQpKRq4FDS9u8OKbHBVwJLKDDo7Ow6koypYKvXOlcC6wYhOHzmudT36kve1tXElmpEIZSOwTEjWrC6GlvAXANBfaUeKfFKQnMkdbm27ccisMJmI33fzsCJJFIy8p3/0dijN+XDx0CajgazmUi7ynZGEDisxY9XRgoaqqMoLUggt19o39PpAkUHE+cdY9m7/qrsSdIHllN3ONNHrLsGHTbOZQlpuMdGCiC6vhad2ezmfXRFuKEEbuc9QeFfBqPKpb/YwYdPD6elIRIdNlQUBBIddv7HzVznZ2bLE0JKjC3eoSiuagSBCPuCEdlU2vezR45CDeB/iqaV+3iSp7mfVjqnmseymVe5iXwKA7bTrjdQ16tfR6MFJeOnUjJuClH1tejN7bTHJ2CN8a0M1JaWwf7zLmHAVx+j2GwghNOuWmLiaI+LI76iLGihgXSqyaaMOsItOiRorI1CtercNGSd8bGq6kyCgn3OsAJdop1t195O5s7NZO3cgqHd5HHUAGeUEvuBxiCDYq0KZEO173c/VHjqxvoKKbAnZgdM8AqW3JW+b4dm/P08IyElWTs2E1tVTnOfXMTwIajxccjICA639+x45/zdC/+9qhAq21dlM2hceCEXpyWJNUaqXP7LHSx6Zhj1VdEoOm3UqdoVomKtLLhzD5WyishdSViao7xGRwKVm3iVkezwfYJTxM2iayhjYGK2c/ToC6oKyabxrPgogbLDEShCJVcWk0sJ/SjgSt5jFsvDKrurZRG7n7PZkO3mLbF0EFlHOx0wFewj8R/PczH3soiL/cY1CbSKLo/zIFuNYzlg6UscLZzJd8QQWBZEFQq2qCinV9IV9ohIWrK8y1h6HcNgZM+Cq4gvKybtwG70JhPtCYlUDhlJe1IKDT3y6fvtl9rd8OPpAxjHRnRYvWRXgp5fChRbO221bRwqS+SD1f2pqI8mLcHEpVMOklSyFPBBEoWgrs8AFJuNgaUfh3VOISVJlip0iopd9Z8IqOgkNWV60nLcveSepXR/TEUCg6kNxR4881dpa+f7/QNZsn86DUnZ9Okzk4l8wovc1bFF12LrG2oif3IkFmDktHJMLQZ++KIX4JoopDB0UgU5s7YSXTeBT55LxbND0mEjknb+7gyz8YHj0ptzOYyfcpugTR93hxe2viqSjUvz2LshA5tFRxyN9KSI3hxhIuu5mVdIp7PDDTbolUJgjQmuNRvVd5BXCV2AiIMHuGvl9TzHPj97auECN/Eqj/Iwv+afLDfOxWTRMYQ9DGN30HMDFI2fimo0ui8UAlOIVSzr+gxg0y2/IH3vDmIry5CKjvqefajtOxCdzcqQT94lrrLMmTTs776dxTJ2M5TwJ4wlQ3Nj2V3azKalsRzaHoXZqrJtaCsP3RnFvupWBhrxio+NiGimaOIM0g7sQd9uCssyJIimoJMUqiporI7EbhfOCo/dDZGQ5pW34MitCBURTY1BK0UKoLrcyKvl8zi0oSexE3pzxeif84cfLqadQAoT/u+qlEqXSP5pSWIBktLauemRTRTuSebY3iRUVZCS3UpaTgsl7fXEJFu4+/kyvngmg4MbY52B1nE0cR9P8TB/9nlcAbQnJJ68C/ED7aXbh3Gsf6KgqvD239PZtDQO0REjrEqFYvI4Ri+u5W3OYllY51WFoKFnH2zR/oPF22rbiE6JdouNdEDUN6JfvZE/8zBfMZdWYrD7eM1+x1+diR9jLJsZzeYQVBi159OWksr+eZcGbGNIEIKmnB405Xgn+FQNHkFDXm8yd28ltrIcVaejPSGJ+NIi4is7iVwaNVzD27zB9YRjbO2qwuZtOm7YM4KvD01A5zJd+fzikVw4KIt7z1qO3k/oR0LpMVRFCTkhwYEreJ931GsCt80u+MvVPTjvrkrGzWtwejAAr3KGPxbsERFBDW0hvTmLbzlCH/RYUesFbFZ4iitRsKEeh/mLijm11Rq6CiFg0nlFDJtUwd4NGTTWRhIVayGrVzOVtnpUm8Ko+TWoeitr3s2gtrrzqx3HRl7gDobgHc8nAbvBiD0iNAmlUHGiRN8rjsXy/hMjsFkV52xfMwnsYxB2dLzOjSTjnm0eLF1VkSqVLrNH4B5GESxsIunNV0nRHeJO+394nru8zqTHShL1PMQ/AYjRmzmfzxAETrRy/l+no2j8VErHTgrYDl9t94IOykZP8Fps0+vZcfmNJB0t0Mii2YQ5LgHFaiXl8AH01s5Y3Tt4gX9zT0doV6iUUmKIsLP2i57sXJOFqdnojCHeujSRb/5n48W3TQw6RyN7jhKtDiKb1HSEqBC0jD3RVx5iuH4Pu9TBAaUud6/LouJYHJfdt5OY+MA2JNRStIHgqwStA/5K0FqjooMS8kf5HQ/zZxRUpFWgrFZ5jX8dV1tBOktaAwzOjAuJvZy2JBa0meI+w+pIzmzj+4/y2b4y20lWc/uaSbqmivc/klSWN2EqiyHqo7eY8vZdxBBY3sgXqTkV4EiwcXgZtiyPZdPSjsB7l+QDh1fwDl7gLL6lN0fdjuPP0Eo0b11EcxNp+3ZqmcQe03TOkAIXuI7yWj5YTB9VpT+HWMtkbuW/rKfTKEbRyu95lN/wj3AuHbteT/G4KTTm9qI5K7fbPDqBYImLp2jiDK/lxsYGRr3zX/QWTbf1Ge5lH4PYyARCU4fUsObYcOcUlN0jLOazfVNIiGzlluk/+N65iwP5uXzF6Kyj7Kjs4XXOzmNrU4Bf/ieT1FwLjPC92Y8JuzGC2vz+JB856DOkwIKB2SyjGE0qz31GQCKDmj7/zzEi2krPQeF3dKcT4pIsjJtTzLbvs9nwdQ/WL+kFgCFCpXF3I3//i+D39zXRuNNGS3k9/e+8kEF2/8koAjAl+Rbmd51ODwZfHsruTuiSKnz+38FuBNZ5fvQcpD8P8C9e5Rb3/YRAKgpSVb3eSQmoOj0Z+3ZQFhHhFkvqeu0OL6wvRG/dhLDbeZZ7yKCKx3iQVjqn9UewjYVcQS6l2gLVjtojD+VoScDCBc09c2nM703JgPHYI6P8budJWgM9s4p1m/ySJBSF+vz+1Oe7h60ctlnJ3biWvI2rEUA/CniHa7iatzvCJ1yfhf8wIKtZx4avOvtw1SXB2NSi446rYsn4vokZw7Wwgqi+2uA8c+IZ1Cxf5feaAkII/pj3IpccfSZg2wBqy2P49MUhXP2r7X4PF0xqyxWhhBR4emMDlaCtHjCUvM1++h3gDa7jDzyqnafjmaiEJvEZEAKGTKgMe7fTMrHLFfXVkbz9t9Ec3pniRuRKCoy8+6c8RuXF8adfRlNpamfmgpigBNau6Nwy2X8s+BqVJ0UZ3KbJVi5KCFjSVSK4nIW8ybWY0Nz0UlFo7pFD4eQzsRncp4wc493oumoGfPMZg778UMtqBy8NQ9AMblTfQUSnRDt/WZM7p/gV7E4S4Ui2MxHNo/yBRVzs3K4pI5ua/kMCZoeWnDGFknFTac7OOykENhAsCYm0ZGY7zVQ8zaxiOq9xAxP4gTQq6ccB5vAVoqPUgC/WqWkh+rtmwbs7ZlNTaSfOWub1s2TFhe2FlYA9IYHbrjhGUlJo6WDLXknvzO5tEc4QEtcyjj8WisdPA0Xx+d58zEUUku8nnCVUn79vTDn/aJekYE43fL8on+Xv96OlodNOWM0KG79IZNbIRM4Zk8Cy7yMYnbyFAWnVAcdVEqjN9xdr6x+BvJPdldDlmQl+bH8SjTVRPvItNNjR8wbX8yv+wR46PWVCSvafcyEtme7hTI63SWe3kbljM6PeeomE4qNu23hep0hIY191q7PIAYA0GjuOJaknkTZicNhVgcoWxnEbL9HUQWyFKmk++8yAiVYyJpr2395H3eD+ROvcB2aeNgc0++/4BYJjveu+waDqDVQOdh8xX8FCdjGcO3iRXIpIp5wZLCfPmfTrK4lbuPw8rlkVtLXCi09Esqtce38cg4bolGhSz5yKOT6uSz6C4ZcPYNpsa4ffx39yuZSCssMJFB3ongQuT3gO8sJN8GpLy6BqwBCfMb4S+At/wF85+NDgfV+EohKXZGbYZP+ymv5w2pPY7z/Kx9yu82FwhPPfDWv13H5lLC+/EROCGJJ3DOSPBePYWQFjv0oOGQNOXUgUNjOW63mTHEpZqsxBJiVQMmMKTSN7s+nme7WMTI/9HFO0yUcOkr11vU8Caxw7C3tiNvbEbIxjZ3X+zp2LjI1hN4MZzk5KyXUc1fkzEcXlLOQHJgLQnpFIxfQxtGRrCWwOUuL4t3LISIrHTQnjzp14RDW4G/wILNzAG6xjClVkcpCBfM25HKIvsXRtytOq6lnw3qM8tOlPtPSc7daBRF51CfaE+KD1zR2QQCsxnBm7ntuemk5dg+Kyxh8EJYciKDsYodUjN0Y5iaxnPfIfA63pmey+6BrMsVpn4NptfMF8P8oX4cD1iBKdXmXGJYcZNePHJe8nA9WlMWz+1jEA9bQxHR6lWsG//h3LrF/MpbZOH3RoEO6gywFHJ3wiE7pcs6Eri2ODSjiq6HmSXzKUPVzGQkxEcmzidOr6DWbn5TdSdMZkN91tBxQpUVQ7g778AMVl6hzcY2F9VR9rPuscpFC4kE94mvs7SIb2cxQHWMGZXMYHgOawME8eT+PPfwZ6vUZaofPfmGjqH7oXGRPjRTod3nHPXzhw3SdUMhtXUer1Hg1mH89zF8X0pJJsVjCbw/TjLv7TsUV4Tg0pBZ+8F8GcsfH8+7UMVNWF6AlB9ahhAdOSvJYpCouSb2TwE3exermhIwcnWAiE5Fu/CZTB0V0Scv6eyaGzL6Bi2Cjnu+JAAX05TF+6Th2lx/+1v9PzWrjyge1ERnfmOeytCKyj7sBpTWJbmwwc3pHqd8TsgIPo/fzzuRTq+gbcVlFVjG3+SYcvr5ivEWt3YV91q0YgPPDFt/sD6rA64DBujSQwny/Z9O+l5F15HgDZRzY7p8T9IXfbelBVLwK7v0Ww3xLt9hMJadgz87Hedhtz+KYjrMH3tIoEZwJIxPgxpE+fRNvf/0D9r++lfcp4zCOGYDpzKgcvvYDKGWOIs4U/QjuhCFQSxwXxNNNMPF1NIALBss3ZnPuniyhpy+z0emfE0/7oAxAdiVRc5LYcXhu9Nl3uNBlxcdw+ZgPry7Ws484ptmDtEmz6TEvoOBWJbFNODzbf9HN2L7iaqkGdnU87kQEzuP3D1ci6dERCYjDaGTy+8seeCDgp2Lk6M4CsVCfsdsGR8jgesvwl8IZCENESWqfkgC8vbKDiBl3p2H3pcdaVR4WgDYsz1n8RF3NZ1mJtZgBAStIOBgitkBKd2Uze3rVudtWzxKwnQa+/4lrej7iez7nQcSSvY6vo+IZz2Moo1NgYEALz2JFU//tvtFx6AZZRwzCPGUHzjVdR89RfseX3dO57PIQ1EDzJbCCIEO2qARsSgSFAvG8w1FYLHvqVjvt+k+A2QKodMpCKISMBLUcE6CT/DvtKp6XY1ftsrqx/GZuNoNKSnRDUVcRQX+k/fAN8v5++ZhocIQXOo/vQjPVEoGcsdToOzzqPjbfcS8Gs87BERiHR7GpwBJPXEh7/l/QZXktCSjB5P984LWNiVVWb8jm2LzGsyl2KkLxsv4m/81u/20i0gge+EErsliMWyIFwM7j9feTr1h9y+1tf2jckQ+uAig67kPz708G8dLMWyK78uxBVESh+dAc1qa02sgf2I9KDwGKMcpJrR+KP9hFF88OoP1JG4KkSiY4lnEs7Eeimju7ssKaPwTZ9jHO7LDo1Sf3GWP0IaMrOI+Lg3qBSMcYAouKhwq4qtJoN/G7hHD5730U7cSxYzjwf3Vtvo3z6BaKtDXXIYOw3Xg+qHf1v/oBSeBSA8uYY3t8yEHsXyPT2VVHc8LBWLebzXRWcPyzTrR555hnApn0/3rMRgoae+TTm9iTl8AF0Fgsj2MGnXIC/8pVamIeKig6dUFGFcBkM+7hHUsFsEuxcncXE84pO3LX8yGiuN3J0bzLHDiQGdQ44YFcV3uEanuSXJPqR8ZNCYIsIP/M40FSoLy9sV1QJXL2wUoWje33H7vqDio4vy8/kqvqd5CXVobOYgyYHSUUhuqLKOVfgKDEbSInGnpLCX7OeJohCFgp2FnExA8d83Xm+hHjazj8niO7LiYWz7wwgz9ecGVxZxgEjlq6mBnRA+85fejWG665sYxgdAychKJg9j5p+g8jasYWY2krshghq+g+mauAweqxfSdrBPU51lP8WXYCU0rvIQVBICnamcMZZJT7XhhMXe6JgjYmjcthoFJuN/JXf0JtComjDRKAkRO2+6rGiKhrFDEzuBZu+6cEZs0swRoY/W3Pakdije5P46s3+tNRHEm52i13q2M5Iv+ulENT36O1TxzDU5APXbTwJbajInzcdpb+3fJSrsV34fiZCyLBIvN0uWPRZJG/ELUfX2oi9oQHhzKn1j6jUWK2Ky9hZmpE1al45Rxk8Tw/Id1+latNxQdqmoqPt3AuJn+g/VMBUsI/olGhnIPqpQmQbh/Ym/cCeoNsl0MQZbGALY48r+N1uFyz9LoLy1jSyXS8/IQ31z39D/fPfnIvE4sXoL77Ybf/VTMPexfOrdsWZKXvKElk074E5Np7ouhpu5hX+zMMEim99ivuJoZXvlTNZOWQyTWXpNNb494xICXs3pv8kSazVovDtO/3YuyGjw6aEZ1stRHCQ/ozDd7KIoqo+K+X5s6ueXlhfCV3HC19errLCeFoaw1dQUISd7StjmRn9upc8oU94CDG7es1cnQOusNthb6FvfVa3Q6OFDpnOnhla408yXG05uJPZ9qQU6vN6k1ByDCWIV3YuX/E09x13e3Q6yWtvR/Ofx2c5FXfibOU09OpLQ6/OmVthszHs47eIKy91c158bZ3dNdsqJHZr1yfDXfViHfCX4KUNBvf5lNoKpU81JSUjgFhauZHXeInbfKoOKdhJo5rFnMu7XE3hoLM4mNyLPasDO7WsFh1H9ybTf3RNwO184bQKJygpiOejZ4fS0uAwMuF5lRTsRPsZizpeSeeUkAu6Ol16PNMz+vikgEa7rdkQFoF1wGJVEK+9jfLBpxjWbw2YtSoBW1YmMinBLT7XQWAdpf1cf6BpS4bSslR9PdH/8S115oDDE+MgstD159FdiLOW0ZaZQfMVCwDc4lJ9df2/4R8BCKz/BACvLaXg2DHh+APxww/ofvtbdA88gPLmm2Aygc2G/vbbtfUuz7arBBYkqdl+/DfGTsIXneFdwvnHgCM8JocyXubWDlH6zthYhwd2Pl9wJ89zM6/ylv0azpryDaYWf+EvnXtb2k+7cX9QSAmfvTjYhcBCV8JfojD5TSCq69mHlozwBjjhJKR0VRvWszKQ9g6ED520YzhaQebeHeRtWRf0q1akRDd7GtEp0c7r3G+JdnqXHaL2rlBDnGqXKOSfmYwtL3Sv5slGoBCDQ3POxxIX5xaP6etezmYZQ9mFPmBIQXDbarcLDhd32rKs4YNJ2bWX/O+/oce674muqQIgY+8O4spKvGbfbF21rVIhLbcl6GbhhBS4IpRBX6i8xDXE8q/8joHs98o50GPFiIUPuIwxbONx5Ve80u/PZPXzrv7pCxZz1+7jaWWRV33SW/PudYG8geb5O5/PnX+7Bt7bIiI5OOcCLfvdAw6hf1/yUv7gT74i2IjH8UF3FhPwPapPSG2ntjw65Ck/DSo9KUJPZ/C0r+QDXJa1zjsbxREX1FjtbE+9ycq5MwdjbhNsXRFLeaERVW9j0KRmbrg4mhVvBc8Av+M+BeuBDT5NkMOwOzTujny5EvhxBfYdcLThSArEXHguuUWlGPcdBKGRfsNhbb7PcQcW8CmP8QAP8RiKok2/CkUiVUFypo38YSa2rYjDbgv+XicZ6pCHKzFcdyPKpi1a7KsQYLWiu/9+bLffiqj0likZz4YuX2/G6AK3vx3hIwONbdiatGlTx/P5sWGOjcfY0owAbuR1elPIY/yKb5iDio5+HOIenuE2XnL7DrZuHxuUoApFJSXrxOiS/pgoPphA4Z6U4ziCSh4lDGGP8513tSu1+QM4OOeCblMVcc3Y727EJ4fW4XrCipGB7Hf+HTClRwisMdGYR48kGt8JawDlBRE8+3UEpjbo01/l7PPNTJ8uWbWKAA4MiVFvZ95Vp4eOsa8ZNktsPNuuupWsnVvI2LMNY1sr5pg4dOZ2jKY2571VkCzhXGaxnEP0d85MKopEVQWZQ0pRm+KpKg7svVZ0EmOHPqn+m5WkPfcGWG2ac0JCjw2rqek7kKh632Vwp7GK98j1W9jHF4SQxCRY6D00cGndUyGkAMAc23kPE2nkBybxJPfzIrdTSSZGzFzO+zzEY5060ULQIJJZ9V5otiU5o2vBLqcNiW2qi6C0IDGELX3TMh02sih3Zm46trDr9RyaPY/avoOcyTC+EAqR9SSuXSVcR75cSf686QG3GT65gsM7wivJpyC5i+fclvnqdBwi8q3nnUX7tIlEo1XlchjbBSOy+WRHGTtWxfDW39IxmwSKXjvIyvdS2TWxhcGppeyryUT6HKVK8rIs3DVpMYDXFEd0SrSTvDriYeHUILCuaDZkQw4cyMki8/47QEqSf/1n8CHC/yBPcAGf8V/9z9kw/mYi4w0kDq1m8OQW0hL0XHB7HQ9f2tOv2oQQksH9TAxKPor+4uthvxYjLWydo2HZ3Iz+8ad8TqD34QjnsIRlnBXA2LruqbW/36gackcWO0MJADcCqx7cekoNMCqHjiKuotT59wxWMoOV2FGwoSfCI0ZZFYKyvIHs2TaMYN5HqSqMnP7TUybYuyEDRVFRAw6IAw13FX7HX72qAtb2GcCxyWcGrPTUbMiGMJwD3YUlK/b6rM+elttKak4LtWUxIc90CVTiaeJiFvlcryJQkM67Y4uKpOnhB4nO6CQGIiENqlv5ZEcZkaqR53+Vwb4NMeh0EqGAzQr/fDiSe+YeZKUc4Kcl2hmeunUlMZHHq8xx8uCLyNojoygZN4WSDlWa5IL9DP7yQ6998yhhN0NZxEW81+937IvvTY8+NibPb2JzwQ4AyleMZvsq/yXoVbvgnAstKN8sJeLpV5xW0HUmK+XwAb+BST/nP7zF9QGu0H1PoajodJL5t+71VxXdC/4KH/gKKTgRaMzthTkmFmNrCwItYflPPMIfeQQzERixeH3/wm7ntYifYWkPdpGSlKw2snqHl/jpwGlDYkOb5nG8LJ2TOTps2DGQSwlLOZso3EfaOpuNhp59AhJYB1yJbKBtjgee5V39oc+wWnoPreXonmQ/xtb9w1GwM54N3O2UJXGHABqy81BUlbaUNJoG9cCUkUZmh/ekZvchPinsyzcbotDrBHW6FFa8ndpxmwWqi81cvy6SiWyjF+0U0htPuZGhvetZ+vjX0NqMLyEIV1J7qhJYB1zfiajqGjJK/aso9KeAxy33Ijc8yNF/P0/T+Rfz+a5m6k1WklJh1uUNLHsvEW9TKUHCw1duwLpwMYY9+30cnYAlHAFe4yamsIZCendUwVFAaKEfEXEmohLbqC/SCEdSuonRZ5YycnoZe10cu+cPywSLCVv7qUdgAaoGDiNz52ZiqyvdBhI6VHQ+kuwUKXl35m+xvmH0WucOSVpuC/1G1HZzi398mFoMIWRVe65X0WHHjoHf8xd+xn/d1kpFwRIbH3Kp0lMFQsBZVxaw8KnhoHp6PL2JvK4jS/51bvDqWxwwJyRijYrGbjDSmp+F8ZrLkFFa3kVU30Fs3aXnuYV26mqjaTakUrwrhsK92nq7XeCYMGhvU/nXor78jJf4L7chsLs5CXSK5B83rObiyQVebTjVEUh8HyBjz3a/FfqMWLmChVx5cCFHRk3kw8ueISY1iXPzBrNkxV7Gn1PMvo3pWMzCy0mgKJLMPu1MnWVDN+8JpCIQPhKdhfQfIncGm3mKX3AfT6PH6nQS6HQSux0Gj2/j0E4DVpMRRacycGwV488p9h+m5QF/3lhHTkp3IGhcrKJwZMY5DFz8kVsfI4AIvBWOpE6HzM/nu4rhIUXLzb3+gNdEzU+uYldsoplASRoa3OO5tBFyMy9wOwv4FKOPiWuJJrIcKk6Fzrql0cCOVdk0VkeiN9qxWnTOEAudzs5M+3IqyGQ3wwFIoo47eIHf8Ve/hhagcMYcWtOznH87yPS3qxO48d/n0NxqQKfX7pndloa/52FHzxqmsoLpHGQA73IVNaTQh8PcelUZ066Jw1TXFtBoueJUuOeB4GifwRTaSFJYLPS64xasaTEw8Rw+31VBvcnK/Fu1qaXvFiYipVYszW4XxEVb+c3k1xlQs5H25auIClBuNRCRzaSSLYzhZW7lv1H3UGHIJTLJytT5zUw6r4nlG/ag2gSDMhLQG1SqSmJY9XE+ZdWS9sNRjJjdAMNgYKzEsvnUI7CgSYvtvuha+qz4irSDe5z3yXV4ixDaT0rKf/UbsiZfAG8EP/agcVWI0yqLIDTEJZmdU7ChQ2EBH/F3fktfDnuvlmA3dC2+NFx0l2amlFC4O5lt32cTGW3DbNJht3WSxD7RZQxo2853zKS9I6xqGiv5E48wjdV+j2uOjWX3pTd06m1HRWplu60KN/9qMB9+Eo1Orw1UVZnidzZGoqBgo5BebGMkz3EnGzkDHSrz477j8n+mkRLfNZmiUwGZE8+AdZt82pPIpoaASjCOO9Z72zqu/fUNvPLvD0iK0XJniszVXPHADj57cTAN1dEIoWoau1LQf4yJC39VQlSlGWXX7oDtCzQX8Qv+zRls4t/cy3fxF6Lq9UyYZid3RinDR9lZ/N1eBqQkojeo2KwK+zams2V5LkKR9B5SR59htShBQkKPtwytv+SuYAMIB2r7DWL/vEvovfJbIpvdVUhc7apQVWSvnti++gr7Te4OLF/Q6dUue2HhNCKxMfFW8ofVUbgnKeQ4UIlCPcnkUeKbwApBfY981JNkbI8Xu8ubaCyPZ+MbY7GbOxO7hKIipaDnoDruznyE+79/FiEllWTQTiTZlPm8fk9Yo2Pd/m42ZFP89VGuXngzFpuCRGBzm6Xy/3LqsfIl83mcB/kZLwMaz7atyaG4aQiW2FhISTqlCNDxwhoVE3yjDghA9+vfM3DdNBiWyac7y2m0WJl2fSUj51djPJqLsdlGrn0HQxvfxRqVRjPZ2O36oCPbQCYjgSZ+KZ7k3ssrKbjxLr7fU0lTZi4R0YmcO1PzXOytaGLnJ6Oo2JuN42Sl22HFW6mot7fwl/OXU7j41COwDtgjIzk4dwGF084irrwEhKApM4fYmiqyDmxGZ7GgHzoILpxFwtQ5JBaZ0OtjsQWMSRbk9PnxY9NOBIZNrmDb9+ElAemwUUeybwILKFKltl94lYL8IRRlgnCSunwlykgJS9/ux8412c54daBDH1jylyfa+eWDA9DTiolIKsgkjmZSCeyZl4A5LtH5t6su7G/fO4tFn2oJRaHEw4PmIPiWOeRzKS9zW+eKZmhadRH2Xj2w9u2F9KGwc7rAl1fQEh1LdF1NUElDAWQf2kPv7etomDzDadPSc1u55c+bOHYgkYqjcVS3mbjoqjiyelupN6korcFj3SWBM+En8wOTxDosy9dytFFFjY7ho8YIwIgQYIxQObYvkU9fHIKlvZOx7liVTXS8mSt+uZ2UTN9OplMlNra27yBq+wwkvqwYQ1sLlph49NHt9GgzYSgqQRcXhXLhfGwXXc5eWzxpGWpApSKhSLLzj++6ThsSCzD9oiMUHxyFzUrIRFaHjdVMZRLr3JY7PoWSU6wSlD+cO3Mwdhv88fKe2MyK20vhuBfH9iWxVZ7hjMnMJPQ6xE0ZOVhivQPg3905C6tdQQ1TA08gacb9eEKCoaiU/CItZrE5PYsjM8+hOSvX1yFOOzRn5dAen0BEU2Noud0FhRxYVYPMH8S5A7L4+qAmrXPN9HQGXWJANjZg2XyUI19anUMQU3Kqi0vRGxKwGYzorRa/bRBSony9lEGvv82gju33n3MR62+5n3NnDuafv9BTsdfhkXc/yjMvxmEqPYO7eqw8JQmsK6wxsdT1Hej8uyEmloae+U5ZpxaTgd/fGsmHK9MCFg4RikpypuknS2IzerQwfEoZO9dkEaoqgWO2xRekEDTk9Q5bjeBkwjMedufqLHau0drr5gmVApsVHvtTJPdIPXoginZ6czSk8wigfIR3vG9T4jBe+SANtYtJyq3EEE+n90oC8e9/rP3faKTtrOm0XHoBhBAmdyrBn1ewavBwkoqDCOS6oPdnX/Nu4plkpbvGokKvQQ30GtTA7vImth2FrN6aZ9OanYOMiECY/XuyBWDX6VHsNp9fiQTUtBSMk2cwwKKFLt3Wqx9bbrqXc2eewwcfHuOHF4d1DFjcj9DWFMEbfxnLHY+tIyrG7n1wP3CoWDjiYh1FD1xltrodQtCU08P5Z5y1jCMx0WSef45zgLbsuxjueiiO8pLA7mWpCsbMKg24TTCcVm94anYbVz+0nWXv9aXkUGLI+7kWTpOKAqqKqtdzcM4Fbg/jVMfO1TE01gR+ZItL5wWUzfKEdmcEh2fN9bl+2eEx2MNSQNBgR8cADgTcJra6gmEfvsnOS6+nJevUlYMJGUJQOO0sBn35UcDAFwk8y895jF9RerFG4GPj4xk6UyUq3sYPTdGkJ+g4d2YkZ6e5H6VyyEjyNvifukQISsdMJPnoIeIqytza4NompaLKuVxvtTB4yYfkbl3Hfx/9nJLtgZKcJC9/MYALr0km/hQPd4ytLCN9304MrS1YomKwxMYTW1OJYrPStm4nF1d/xs6STB8x5Z13SghJVIyNC2/b85Ou1HXW1YeISzaz+ds8zCaHjQkcvuWwq04ZJKGgSJWGvF7sP+9iv/u5wlf8v69KXQ74qtR1vJASNi3Lxd/1SlVQVyN4Z8CD3FzwR4Q9NJIhQZMWy8z20sP9emVCSBUXfSGBBlJx19N0PZKwWIhesgxdRTWNv7it21QhfkzU9BtMztYNxFRXIgJMRR2kHw/xDz7fcAHqBo1AJfWIxTS+gbryaMwmPckZJoZNLqfYWs2SFXuZOKEfIj6BuosuI/mDd30+XwnYjREUnHkuA77+xOtNcbRIqapxW556rIC5D9/N9/c9wmPrr/NJYB2w2xQ+/+9gLr9vVzi3JigcWrHdBZ3FTNq+XcSXFQGCtuRUYtqqMS75Fn12Fovzbuayhcl4O81d7KqiIlWFsbOL6XuceQanFYkFSMtp5coHdlBfFUlteTSLXx0UUBrHjp4z+a7z72EDaBs9imN6HY0xvU5Ci7sPh3dGdgSL+/Wx0dScyJ7e0xhctNZZUcQVnh+fNSqavfMvc4uFdUW7LVjCiy9IdNi5jjcDbqVNDankr/yGnVfc1IXznHqo7TuI/XMXMOCrT3yul8CdPMeL3ImrO7WlSWH9Z0mA1ufodPDmm8n0zZnPM2fuJK5DpcQcn0jhtLPIX/UtEuE+QBOC5owsysZOpGzMBPJXLiVj9za3SHFn5q1HuxS7nfjyEhr/swPksABXqO35383zeeCcb0O8KycXwm6n39LPSD+wB1UozlKWjuu3oudqvmAHvt95x5YR0TZGzyxj1IxSYuJPD8mirkJRYNJ5RYw7u5jywnj2bkzXPLN++IIOKzNZAXSqvJSNHEdt30G0ZIbngfWlTBBupa7jQXubnvrKwAUK9HrJd9lXcMuB3/tc74vUVA0aTsHseW4k0qEL27ozKexiNaDNLN7KyxgIrD4gpCRyy3ZKP/yM2MsuDOscpyKkXs/ui69hyMdvE1flXYYdYB8Dmcg6Wohx0+WuL0rh+6JUhFABAQLWfdWDaQsKiRmuFaz5ZEcZFz30e5LWfA+lpW6OINnx/A6dPZ/avoOwRsfQb+nnRLZ0zsy42lZXKB1Mbuqzf6FC95CPLVwhKNqfRHubjsjo0L2xgSAS0jqkMbsH8aVFDP7sfXQWszOvwHVicENhJldyPb7T4Dq3zOvfwNjZpeQPrTvuMdZpm6aQlN5O3xF1jJ1dos1T+4AeKxNYx1i2OJdZLj0P06xpqMaukLMfGdo7ExSL7/4HbUkpWilNP9s0ZOex/bIb2Piz+2nxoY3rQP+UEhQRyLPrIauBHRA8z51B48VAM7bxFaVE1YVfqeNURW2fgdTn9vS5bh0TOwgseBs0jV5KKZzxmYXlcdzxxf3YXLzhZaMnsO+8S2hNy3Aus0ZEUjJ2Ersvvg5Vb0A1GImq977/geyFotpJ2OW/5rsrtpf3CWm7HwO9Vi8jraOamiJVN9IugLt4nm+YE/ggAhLTTEw5/+hPnsC6Qm+Q5PVvZPqCQowRdoQf22rHwC95AtAsQFtKGsemzAqLwIaiwnIiKnV5IpQ+VEqoj8/Det+92t8+jqGF8hgonDid9Xf8ikNzLkDqvKdT7YnZDBlkC4HAup9FwUY/DvI7/hpCizX5uOS9B0JOoD1VkDnxDJ/vhi0ikv1zL/Lbp/2cZ2khFruXhKB2n6VUkLJDoUAKLWl1V7YzntqWlo71my+xzp2Bqu98bo05Pdl18bXUdgyspKK4EVj3s/iGYldRLaHQLUF5YeDqVp7wVRjjRMxYRDQ1MuSTd9F1hKq5KjYIYD8DmcH32AjErTRrPO7sEvoMO34CCyfBE/vcc8/xr3/9i4qKCkaMGMGzzz7LuHHjuu34E889Rk1ZDAe3pnXIaemdRKoXR/mISwBtNCWT4mnO691t5z7ZUHTBahBr+N1DE/h67HrerxlPBu6jMMfeiWXF6Gy2oFNNlw/7ji1l/nQJXY+oQY+d17mGq3g/aDtdYWxpOu3keDwR2VBH3obVpB3Yg6LafY7Mn+HnXtI4gWBXFY41ZPLDkQFM67vPuby23yBq+w3C0NqCYrdhiYlz6zCja6tIKA1cHrWdCN7nCl7nBirJoBdHGWvZ7KPV3jDousdT0N3QtZvI2rnF7xUU0If/cWvwA0lBQ60xaDKFtf3Hq0Z/Im1rZIyNi+/ezUfPDsNmEc668A4Jocf5JbNZ7ty+Yqh3mexQcLL1YX1BKCo6g72jBKifqV674OvPjAzt/xR/HJDAlQe8Kw0KQLHZSSksoNRH5UfXMImU0Xp69bFTdFRBDTCz5opJrONzzieRRj/bu0OREl2Lt6zcaQcpydiznZwt64j2MTAHKKQXy5kd3nGFpOSHgSwe+h2TJvbTlqWlYr77Bvbn5mG2xGM3GrF5lBHO2r4JtSN0xh/2MJjnuZOVTEeHnbNZSpK+gRpr8AFZVypxukKnKNjDCCkMFZk7N2vxwH48aX/jN1hDLPjQ0tB9TsQTSmIXLlzI/fffz4svvsj48eN5+umnmTNnDgcOHCA9vetlKqXUih9YzTrik9s5/9a9HNmTTMGSKCxHrKRSzbW8zdW8QwxtzukA8/WXYNyzn7r9h2jLHd5dl3lS0FSnY9XHCQSXGdMyXVdv6MFE1rOB8aTh7eVUhUL29o009ghM6mf32crFkw+yaG2/jtmDIOdGRyH5wS7HC56G4nRDdG0Vwxe+jmK1Oo2b550qIYePuShkAuuATthZ40FiHbDGxPrYA+IqAnu5aknmTJazkxEoqKjoOEQ/vmYuwd8xyfi8/SHV3D7ZSCwuRFH9E+x3uco52A0IIcnIIaikjam1mWX/6EpLjw8nyrZa2hWa6iIxRNjJ6dvILX/eyM5VGdQvM4PZzkTWcRfPM4rtgOYcaEnNoC05laTCQ5jjEmhLPTVKEIeKtV/0xm7zT2BdcegQXC0foZoG7uUZr/WKVImvKCWmuoLWtEzA3eOsVWHUfAf/eM7EdRdGY4MARLYT2xiF0YfWsT9IIbBGx/xoBSW6BVLS57slZO3aGlCU5c/8oQvHFtSWx9DeGOW9Sq/HqG+j2ZDotS6hrCgggf0fN/Mz/osOu1Mzdo8cgrQF98QKoZLRw7fc1NCs+OOW2fKFCj+yZp5IKdjvl8BaMLCQK1BDpJSxid03uDqhJPbJJ5/k1ltv5cYbbwTgxRdfZPHixbz66qv8+te/7tIxD25NZe2XPakp1TpvvcHO4AmVTL2wkD4P1aH8sIYHVr1JauFB5z4yJRlhtxP51CtEAUlAL/1yykeM5dikmT6nfE41rF8Sh9Y3h5g9LHUU0YO/8jue5j6v9YpUNfmhIFCE5Hcj/sWUUTfz/FdjOHQ48EhLReF1rud3/C2kdkq0jPvW1Iyg257K6Lf0cxSrxRkD5Qs/55mwShM6IAGLLbxPVQbxsN/A6+xhCJqasvb+ByV2ztbAndfUEmKC9kmFYgscK1hDKgoqQf3IEibO67p24YlGd9vWthY9az7rzZ51Gdis2vuQmtPC5HnHmHR+MfpzzEx48xnO3f4teqvWAUlFwRIdRXRdNSM+fMN5rOb0TI7MmEtz9qmvOmK1KOxck+lXAsgTjkH8AzzOlbxHOt7xhhKIrShzklhw9zg7qnMdpITbnzWy/qNUNi+LC0pkW4llMedxGd6Vq3xBSEnV4NPLWeOJxGNHyNq1FfDf8+1kGK/T9ZwKuw9yGUg7NZBt3cwYfsZ/kSjYXKI17eg7YgEDOwj6DK87ZcOXFLt/29pCLNaAYQQOSKLjrfQcWN997eq2I3nAYrGwZcsWZs/udPErisLs2bNZt25dgD39Y/vKLD57aQg1ZZ3yETarjl1rs3jnn6MwtejZ2Xs477+2mP8+9zFHn30JtU8flJpaqG9we3V0Nis5W9YzYMmi0AJNf2QUH4wIex87el7hZqx+yIkMIUGi2ZCNIiQ3n3eIPV/tYNiQYB+YoI7QaiU77nrh1NmndQZtTHUFcZXlAQlsOZl8zgXILn1ygn5pvpMZ/MEcE+fXc1FAH75kvo/Ysc7zBWqLIiRpCaaw2nOy4Bon7As9OYYtKFmXZPayMO7sU5PEdrdtNbXqefefo9i5JtNJYAFqymL47KUhbPs+G5sxghfPu40n31vN4XcXYfvZLaCqRLS0ovNIII2trmTYR28GHCSHEg97MtBYE4nVHL4vR0XhDT+lRgWh2VaAfv0l1/62mlv+Esr3Lan1sK2dtSk9thSCpqxcavMHnDL3uivI2rkZNUjf8BK3oQ9BB90XjBE2osKxZVJiM/rX4P0396DzO0T2r0zQcXDiU7pmV33FxYYKfzHInmhJz/L7LOJpIpZg9lIj8GdeWhC0sEM4OGEktqamBrvdTkaGe6eSkZFBRYXvD9ZsNtPU1OT2c6Ct2cDyhX21PzxGzVIVNFRF8fnLgyja3IO9u3VMumgWKe+9jThyBPD96ggkqYcPkFgUuv7cjwW9QYbqhHVDC3Fehg+0cIK63v3DOpYQ0K+PDZ3OP1lTsNMb9/sphcAeG4MaoRFxx97W6Bj2z7uU+t79wmrHqYbo2uDZn3sZ7JYxGzokilA5d8i2sPbquW6l33Urmd6FdnRClQpVDd5TcKcC2lIzaMrM8Wtsr+FtP5mz7vjZ3yowRp6ag9vutq3rl/SgoSbKW3u7w84ue78PG77OpXx3Nk26BGREBLr//s9v+4SUCKnSe+U3Aa/jVJjeDmTLAkHBzmF8JzdKoMElTKvZkB00uSotJxQSJrxsqwBMicnO8zr+re0zkD0XXqnJTnBq3OuuIKa6MqBzALQwi67McAlFMnxqOTqDe2hAVN9BzvhlT3KXUHyUmHr/ScjfcnaX2qJB0tYcvrPqZKF8xFi/z0KPnbMIrlbTY0Adg8Z1n1qCdu5TCH//+9955JFHfK7bsz7Dbzk+DYKi/cmwP4k9XwrWPtvExwdK8e+P0qAKQcaebTT0DD+O82RiyIQ2Ni/zLkYQDAp2YmlxW6aNhyTlI8M3bDde08bHn/snMCoKP+OlznMJgdTrsfbvgxobg4yJob61lcakntT37OM0sqcz7CGULY4mlAQgz8KG2t83j15MUnTo2abRtVXEV/j3goVC4gJBIEmKM3fR93HicXDOBYz44HWEqc3rSluJIZTR4IEtUaTlnJqe2K7An2212wU712QFtq1SYdUn+YBgzxcqhry1/CFIYoumOlJGVF3NcSVs6hrKtDTdE6RQkJhmIiHVRGNNJOF5CQSJNHgtlWiappa4hLDakdnLSs+B7RQdjPD5LAQqmVQ4iYLsKGhjSk6kOSOHxrxetMclYIuJpSG3F+aExLDOf6oilNLFMbQiUIPMcnmLoEXHWhg/p5gjfkyrr5ACzTPs/90/HtuqKBAde+om4jXm9aZ09ARytq73uV6HjcDhEoKqEt85HMeDE8YgUlNT0el0VFa6V42qrKwkMzPT5z6/+c1vaGxsdP6Ki4ud6+qrohBKKKNm7QbuORjDFNZQSeAkA0VKIppCy/b8MTFiegtJGVaUMDwHCjbOYzGxeH+lKiJgjIs/zJ5h5qx5Fp+yZooimZBxiKuTvuic5pISYbUSsW0XUWs2EPPVMtK279a8Bz8BAgvQ2KM39iCVcc5gE+lhVFDTIFAUyctb5rGyIPQSnlF1gaXNprAmzHZ0QqeTnDmmjJQ43+URTwW0J6Ww7apbsRm9vRrVhEKGBF8v1LP4u70sWRH4t3RV4IIeJwLdaVvbW/UBdbY7odlVq1nhTwU38U/5q5DaavQhRXQqQSgwYa4m2h4ObBi4wq8Ci9qlELVLf1GDTi+9+jlFkQgheG7Q4widcNpVgMi6BtL37yZz9zZ6/bCCiKYGzPHhEehTGTX9BweN77+IjwOu75SJc7+vbc1GPn5+CHZL6DNk0TVVAQdvM1nR5dAGVVUYPL4q+IY/FoSgcOpsisZO8rm6mXiCfUftrQbqKrt3Fu+EsQij0ciYMWNYvrxThkVVVZYvX87EiRN97hMREUF8fLzbz7ku0uZXeNsX7FJHNWk8y88DbieFwOInw/tUwYIR2bTYrdz9ZDkJKQ7i6S8aqhMC+AN/8blckSr9v/40bGMrBPz9uTZuv89CpEt5vKgoye03tfLFZc8Q3VAFQjgjgJyach2yH8bmFoYtehvFeqr68sKD3RhB6egJAZ+GHju/DZTsJjy9sBpUVdM2fPTri2k1hzbVZDcEDrAfyAFm823YxlYIiaLA767dEdZ+PwYscfGUjp3k9UxyCK3EYWNJMiXfjqVPXDJDs+L9/gZnhj87crzoTttqiLATlmHtwJ95mAaCkyVrVPjlL9tq2zAVeCtxnCgMm1zBhLnHtD8CamI7ILmATxmJ93cggLRD+0kp2O93733VrT4LNvQcZOa+Z8vIH+Y+QBw2TPL568Wc3/6R04a66nNq4RuaD7DHhtVkdiRCAV6Vwk43VAwbg91o9ElkHW/tNbxNJhXofNgzraCE8y/XNUgpqDgaz5G1oWte2yMiAn4t93QxeVcISd8RNWT26p7ZH0f52W6HEJSMn+pz9rEHRSH1Ke/8YxRH9yV2W5NOqCvs/vvv5+WXX+aNN95g37593HHHHbS2tjozasPBgLHVqGGWP7Wj5zUCn0tISfWg0yODMz3Xyh/eLubqhyo78qACB4nP53POYLPPtQKIrq8NSaHAE3o9ZJ9dyIPvFfDO4lZe/7SZ4hIbT961j5TnXtC8rwHIsZASY0sTaQd2h33uUxVFE6ZTPnwMoA2MVEXxMrz38Ay/4W8degA29FidH71BD/6ep0TBbDOwdH9o72ljbk+fXkhXvMW19KYQgUqoJCYpRfLFB7WMHXB8ZQJPFiqGjsJujHCb4sullNl8CwQjK5LdP2Ty+l/G0lhz6sWpdZdtNUao9B5ah1DC05U0E8EnLPC7XgKtyaldkttyVLU6WRACpl54lBv/uIns3s2E8j38h7v8rpNo084OeMZVDkqL8avj2WOgmV88U8Yf3z/GTY8f4/PVLbyxpIlzlv8OpajUTWDe37nzNqyGE6AT+mPAGhPLrouuxdohwagqCqrHACCOFr7jTHLQ7rMeC3qsCFSMesd98GNbpaBoUy8CqPK5oab/kIDrJ7GOp9EKYuiVUA6qOaOGTKxg/q17uy2/2a6qDEoLfwAZClSDkdIx3k6bG3ktBAIvaG8z8OHTI1j7he+CQOHihJLYyy+/nMcff5yHH36YkSNHsn37dr7++muvhIRQkNmzhfxhNYTrNfCV1OSAhI4MzvASnH5MGCIkI6a1BdVr1WH3GUbgiegwK2Wt/sHIvTfE8Mj8/vx1QX8e/1ME1ZUKsbGge+sdIPSJuUDeitMOisKRM89l8/V3UnzGZKoGDad43BQsEZ2ZrAL4G7/jMH34HX/lKt7lHvEsH575GFZrkOepqBypDe27kXo9xeOmBNwmk0q2MIZnuIfcHs3ojQHIrJAk55hZtq2JGVNO3ZgtT9iiY9h90TXYIiPdruxxHgjhHdXmEFqbDHzxcvfqMnYHutO2TjqvwwsZhm1VsPsNzXAc5ejUs05Z1RFfRSxSs9vI6t0cQsiWwIz/DHWBNu3simDeUFOr4Ju3EvnDpT34+Yx8Hv9ZLvvXxRIdI1GaGhELP0TYgxNTAUS0NhNTHW7o0qmL1owsNt10D/vPWUDlkJFUDhlF+dBRbtsM5AAF9OVDLuFGXuda3uIlbuO8uU1BM+EtbRG0NYcWUlAxZKSTUPvDvTzDemUCV+StISUt2DMTnHfTfuZef1BL3j5NUDR+GpVDRrotm8B6prAq5GP88GUvju5NOu62nPCgxLvvvptjx45hNpvZsGED48eP7/Kx5t+yj7wB4eiLqX6nDyWgGgzsueDK0y42MyJaJSo2+CjPM5PVF0IJnHfgpXfTOOuCVNZ8p8du1SrN7Nii48HbYnjglwpi63a3mtOBIICYqgqyt65Hb/rxqh51N9qTUiiaNJOCs+ZTNHEGlcPHeHlke3OUR/gTb3ADT8hfMirtmJ+jdUICEfrQp/9Lx0zEFJ8YkJbE0cLdPMd9/9jBIwuLSM22ecU6C0ViiLJwzSMlp9tnAkBLZjabbr6H5swc570YwU76cDik/aWqUH40nsqiUy/kqLtsa3Z+Mwvu3BNizoEGOwbyKPa5TgCloydQ37tvl9pzohFILD4htT1oVUQjZjIJLIllD6OseWujwhO357L41WQaqvQgBa1NOtZ/ksz5M6IoX1mOYjaHfDyAvE1ryTy65bSQj/SELyUHqddTM3Aoh2edx+FZ53J0ymwvfXcDNi5hEf/lNl7lZm5M+IhIYSFACKsTrgQyUCiLPTKKfedeHHS4N07Zwusz/sfy7U3MvV0bUCgu35cjTnfs7GIGjfs/9s46PK4yff+f94wlE3dp6pbUnbbUC0VaCsXdHZZlYRdYYdlddmFxWWTxxZ3iXlraUndvamnTSOMuM3PO+/vj5ExmJqNpCi3f331duZLMHJfnvd9H7ie8PNhg3QOrm53MG/4zNp5RFHafeBpbTzvX/ZEAbuPRsDchFI21P3Q7/EM57C38DNhWWs+Wkjryq2sYfP5PxKSEF/JRkFznUSnvCQGYnE6i6mu69Fh/DigKTJxT5/VS+EJD4QpeCbodzWSiumd4A82ug/H85m89AL2i2b2NNoP/1FMmPq2ezG76sIXBNBJ8tioBa1MDvRd/z7gXHidt+6awjuNYQ/HwMbhsUUGf1iXvNhAqx1nVTEzuG77nOv7gfqLqaoKHHhVB0/CRNCanUX3IzMAxTcSm1WGx6VWmUTFORs88yKTrF5Oac4zmL0tJ5pb12HyuxcW8gUK4hY2Soj2R9TM/1tB3aBVzr9kW5tKSeGo5g48DfAvRNVUhtxJKdgpATcw+YsoE/jBo3KGgdtWMkwt5i5ggaiOS0GFnT7z/ZCrlBy1tqgTetrWlwcQtDwyhlji2MJj99Ai5PQkk79lJv4+/JO+7RYiGI5AbeYQRqoOUGhXFwVHjg2+jTrDi08bgUUuh0W9EM1Ex3ky3qTLA/ZWSXssXBd0vgHC52D/rDBrqwWSWDBzdRFyyCyE0hKKR3beOuddtZdrZeyMKVnR1t67DQXRVOek7NnuNWiewgOiwlHh0B0HR7sMvQjwmSOysKQM5dfogZhw3GHvlBGwWI5QT2NiYhMZAdnI9/w26bUtjQ9Dvj1accEENSRkuP6Ev/f+/8E96B2mpJIHiEeNQowKHxTzx0hcDgnrihJBcvPXP9GcPQ9lCGuXcxFNUk+h/efePRGgqA775hIRjQK83ElgaGxjy8dtYWgILWBeSw9W81Paff2umCI3BmQcYlh3aYwuQkr+NoR++HnI5oUkO3HQH7/wzm4evz2H5F/E0lMfhaushP3j8IaadtZeo+KNXiSAopKT/t5/S+8dvsTa1D+QSuI7niKMBJXTvLoCIvJTHIor3xbFzbRqKKVSOtC6h8wS/JRr/z4UAogP0uDdwtLUrNhAd62L62YaX3vs6mHCSTBX/4K8B15fohZ4lw8YAoZs61NcorF8YG9D7q2mCnftiSaOCoWyhF/sZyVo+Y07AbRqFuwCWPQUkPvrsMemRDYbMTWvpvnpZ0Cf1T/JfFMhgpF+CFEw8t9yvF9N3kmVqbWXYOy+TUFwYMi9ZG9CfBaYTmTEyjs+fymDX+mjqq81IqRAd6+TEC/MZOKriqMm2CbfhgYGYshJGvP2y3orW4/NYGvgdj7XVWoSG8KNyFCmOCRIL+sv+8HU5zH86hapDZkJ2vrA2MYHlHAgxc40rCa9a+WhDbKLGbc8UMWpGgxeRTU5o5nH77/k796AhvF5yT19f6dBRFBw/I+z9rdmZ4uWB9YWUgiZXewFMM3ae4zomsZRagnux9Bo1QffVnZd+Otpgratl+DsvuXPjAl25F7im7a/A19ZmcnD/3LfCMnixpUXkfvVRiC3q0JKT+fOieWz/Sa+w11QBUnGL3q9dkMPqb4O3Dj2auwElFewmY/umDn1yBHpO8DfMItYcDkEX9MqtOSLHeDRg/aJs3vz3KPLXpaGp+gQmEJE1mTSGKlvQEDQHyAuVoEcB1DCrZSKEb1HUvOHZVDd3XaRg1IxiZl+5nYTU9mdDCMnUtDWsYDw5oqjD1fFs4LLlrItxxIXnuc/fbgrZbhakV0vPTQxnLp/xCpeH3L7QNKz5u7Hs2hvW8fzSCOmd1zS6r1xCvx++1B0gARarI47/cTlaUCl8wfRza+g3KrDn0HOyNfDrj4g7FNreCWDHGbdz82VxOFv090nThPs+NzdYefex4bQ0Hf3t7gOh/3efo7icHZofCODv/JULTe+2fRKkMZKiF5UeLo6qZgfB8PZDaXrIRfoOR7qByezloLrMTEujgkBS3RrLa1zKy1zFg/yBP/Bwh21KIHX3dgonHF4Ho18K8ckqaccvYvoIK8N6DcZilXTr68Asr+arZX2J2bGV3PQYotevI27FUkSLbpRdVhvOaDtC00K2RzQkWmxLDA9N8IYTnlAxs5OBPMzvuTeI9wJ0xYLEwgJMjlbUEJX1RztyVi2l57KFYRW4rWGM3lc7CByqmSR7eCGabmuWIxEoYaTblMb25eN3rUHDbSu/6cHUQR1zxOwp9qD9xY8GZG5aG1CYvJpEfscT1Lli6Nhkoh1C0eg9uJqkjKOzze7hoqzIzvdv6ylF3uov7Q03cvrXcHBXEgoqqmpiK3lcxcvcx59ZyHS6461wIgChqiQV7Kaq78DDPkZZW+5OKchLizky0kE+GHRcGXnjyigvimFnUQunzckhPiWdz/e9wNn7ViJqa0mpL8f87XdQWOS+Ws1JKV4FWPWW7IATvXnDs3l8Szg1Hj6ye5gAyY08w5l8RALBtXilScG2ZgPOAeFLSf0SMGxJIC+9rbaawfPfwl5TFXIk2slAWgiuRyoUSWxCeB5De2UZyft2h7UswDNrJqK68GtbpSZorrewdUUmo2cce060mLISYssD54S/y/m8p56Fdw853+sg0aRg9MzDP/9jwhNbfcjM5qUxAUMuUgpK9llpbdZnPUbnDkPu4Q4e4gtO7bCegGOi0cH8jcUkRXsXYBli6wDWGAebCzezautOvvh+J7X1UTy56zxO/+ZxejxxLyMXPcsDLbdQh+5xMzta6b76JwZ9+m7YUiwnjzvYqdCHipmnuZEWrGHVPgtX5A0Yjiakb91ArzAJLICN1pChF4spTI+WlKTszQ8qxu1e1GTiy143hPQCtTRaqCnyriD9OeWPDgcxleUBr8V5vMsqjIpxX18tGAY4PaeRU6/4Falo+GDT4uzgqRJCcnCXfv+Ntsn6b8F+enI6n/h9rw1v7OHCVHNkPP2nTh8UtFAGdGGF1OxGohL0CYyUsKpwIJM/+y29n72f5Jee5KzCJ1lGu/h7fHEhQz94lYRC/6lRpppiZG17283sAS1hFen6OTpasPECV4e1rHAcG6oigQiscLkY+uEbRLXlWoeyr1bCO1+joMtXksp3cp60d1fIpgsGpMnER5tzg0YuAfLXdb6T3S+JYM10ljGBS3gdJ0a03NO26tdaKBIh4JRLd5LVBbq4xwSJLdxpI/RjKwK2TjTh4kH8d5hRnE6yNq4+pnT1DPI6JCueNGc2+R9O4PsHTmbR4yfw/QMn85ezc/jmtURqK8w4NCt76cOfuY/jWEElep9tISVJB/aGrdV60aw9JMTLAL3Gg9PTalJIppobeZoS/HcUAnDZbLhs4eXoHpWQkh4rFoctVLSIqeylT9BWhWaTxpRe4TcXEGEIHkoAIWgaN5lQ9w7A2dwe9hIJaaiJ3gPN0ZpSoFr9T5w2MozvmBXEAy4xWzTmXL2Ni+5cT3TMsT2xCoaiPfHu9BG/kAqBnhEXFtYziiVM7vCdQM/Ntld2rgPRz9nswB9UVbDiq+78987xLHrsRP58Zi/+eHpP3ri7O3vWx9DSaqKBOD7jNCazhP9yHdDeeKD/t5955aH6i1iomsa5Y7OYMK+KzjScAIU/8AgjWcu7nBt4MVVFTQ0sNXk0IFREJ3XXNqLqasIiLLXE8wlz2wo3A19XqQkGHRdeKoGiqmGRWCkE2tln0uQIFeQWVJcdm2OdFkR540H+gAkV/9RSv369B1dx1T9WMWRi18jAHRMkVhxm6oiKmcVMxUXHDQkkfRZ+Td7n7x/1RNbwvhrdggrzE3jzgZHs3ZoCbWELTVXQXCa8b62Chold9OdmnnJ/KoGsjf6bIfgiOc7BFx9UkpDQlowtjAzb8IxvM3Ze5BrGsIZC/OdZmltbGfXGcyQW6IUVRys5CgR7ZRlR9bVheWGf4Qams4itDCLwBE2iaYJLRnwX3gEIQVNKWsiyHITA9cKzDJvTK8i+21G0qXvA747mbkDlAwb71Sn9gtltfb4DQeBymsjs0YDJ/OsqiPFFsEr8dgSZZOHke07w+11cyUFGvPUi8UUHIjomf5Xhnt7LIw1NhY+fHcSST3rTWNc+YDfWthETjxCxCwsShRt5hu3kAjqRjaqvJaGwAPDvXfT0+k05v5IJs3WPlLvpRFidw3RsYjjn8y738he/3wsg9v2PiXvpDWiJTKrr50SwYr+U3TuDTvYNVJDCOFbxd/7mjhj4g6JIBo1vJLNXeLnUjWkZKGHwAzW3L65//4usnFDOBEljrQ2n4yip7IoANd174/LTFVICXzI7aMMDoWjYol0kpXddsfAxQWJ7D24JQ4A6tDHW/Jyu4exO3ptP5pb1nTq+nwOe3lfQ+fYXL+eiqf480P5fDBUL73MOh0h3L2WvDH9wGD3CSf4uF3f9s5nc8Q0MntDEhNl1AffnCxcWykjnVh4PuEx0dSWDP3mb7N0rgWOLyCrO8Dx2OxngnkyoAV54ISRmM7xwx1KGZgRRbdA0YspKiCsuxNzcRPGIcSH3r3XLQptzKqNGhUNgJBW7MtC0I9jKsIthrywjsWAPdZndcFk7tolsxYYSRvWsy3VMmMfDQs+8moi7dXlD4grg0VbQC4tyv/jgsIq8/KUUBOp41RXYtjKDvZtT28hqeLbNhMqz3OD+X9JRoSFQO13FBKf8ppjf//cgOaMOkNrvEIOOKyO1W0NY1dtGmsdfuZct+Jf2EqpG9I8/kfTgk+A6MgV3nUXp8tUh1SoUl8OnTNk/buEJ9tAnAIFtd7r0HNTCZX/xjhL4TpQsjQ3EFRdiLz9EVa9+OOwxIY/Acf5ciI2hW8/QTQ5AsHFxVojljh6YHK0kFBYQV3LQ7zijoXgVIPqDlKJN/abrcEwUdsUmqow7qZ6VX8f5TxkQMiSHzaQYa4i+vlkbVlHa1jr0aIRBYAH2b0+ivjrycISKmQ2M4CS+BcDkdJC9djnFo8aH1V0nLg7Ou9xB9OhSkqItSAmlB83s32IPo8pWJ7IfcwYlZJBFx3CCURfdY+VaKs89g9KVayM9xV8MLUnJaIoScsb+H25GQUMNOIeUdOuhseTzclIOFrD3c3+LSDI3r6P7qiXYGnQvjhQK5X0H6vcxgKSOAEwHi1HXrWd73+MhgASa5xqq00x95dFvKuKLDtBn0dfEenQr8ncVRrAhpLG1WFUS036dxVyeGHZ8CZuWDkQGKL7QEfi9dmGlH7sCfi+kxNrUSPK+XVT2yz3s44UjX9y1flE2QsiQXRE94cLCcia4/xdAzpqfqOnRm5Yk71C+qaa4TdjNjqppzBuezfyNxfTMa+WOR+DLhasYkhXPgZ0JvPfYcEIX1LZtV7j4r3IjT6n+W+IKTWLN30PUqrW0TAw92T2a0JSaQdKBfUHbmReTwXucFyRNSL+GZ95cztSz6vxKRppqihGHKuj55fckFBxw7685IZHG5DQSmwI/dxKwfvot6o23k5kd3iSraE8CY044uh01wuWi108/kLl5Laa2mhV/JVsmNAaxle3kueuSOmwLyOjRtbKmx4Sr4dvFO4kbsZSk7m0zW+EdcknMqUIxqwRjsqVk8w2zAn4vaGvBeozo6VWV2jutsWbxIPMC6LPke/r8+E2ntiUEXPDXIo6fZnghQ6cYaJjYTf/A25QSc3nlMSMLY8AVFU1Nv94Bz/5TTuN4lvI0vwmhSCCorRZkZerPtz8Nvx4rFtPvhy+xNrQnxgupkbp7e1BDD3relrJ8JVHRkJAYShfUP6L75WFPsQc8vp8b8Qf3M+TD14mp6JiD6Tv8n8ZnZFISUCNWKJKhk0qwWI/u9KKuQGJ6C3Ov3YZikl4FXkKRKCbJwNHlhNKN/S83BF1CU5SAbVAD5UL681r+XCkFlaX2iAisDonFp5jIVl/HiHdeIqrNI2ucq3FeuVbvtAlfmbAeA2uZe+02rFHGcxr8PVWlmc3W0cHvlhBELTz6pAxD2Y/SISMDjs3lpHI7D9Of3SGVXkBiMrc36fTtdNWyfCn2W//mRWABomprSDpYEHTLAjBt3gnAoOHheLslVtvR5RXvAE0j77P3yF6/yk1god2m+r4lt/BkkI3pNmbo8SVdeojHBIkdlBnHiJ4xXHHnVs64YQt9h1aR3r2evkOrOOOGLVz1xy0MmRC8gMCEi0e5Legy4VYfHg2w2NRO8e1Y6jmOlR0+z96wmtjiQr+GwnOg8R1IqpudRMVoPPNGMw891xS2goE9jK4eSpUuP/NLE6RQiHMWu39Kjj8OLcbeYSB5iN9zOp+ygvBag5qDdAO21VbTfaXeo9r3cof1QkvpXvGUM5x+tuK1MLb4JuJSjuLiJinpu/ArhCY7EHh/Z2ZG5X3OwUYrJq9Quj4Bi4p2Eh3joKFWvwl1VTa2LMtg09JMyoti/Gzx2Eb/EZVc889VHHfSAbJ615LVu45xswq5+t5VnHTJzhB5s4LVjGMVgT17QtPQTB3rESJpeBBKpaArtWIttsgnLwoas/nS6zMBmBwO+vz4DQ1KBtCe7+tYs8C9nOGN9YcBoyq48aHlZPYMrqQAelOUWDV4Tr6QElPF4WtzdiXCyatvSUph36SZHT4vIZOxrOYJfksT4bWG9s1z90xNsb3+EaKuISw74hdt6806zdmWAhn83ek+8PDVkXyf+0CpNs27twfuRBYAyft2kbx/T1ipHABX8yJn8DECzcvJZvzdM7ea8oOxSE3PPd+3JYkNi7PYuTYVp6NzdPTojxF6QDHpBrf/iI4SD421wcODKmYWMS3g94ZbPKaslMaMoz9Ppe+wSoQiAyoy+INA42ae8tsyUQIj3vsfTlsUpUNHUTR6Aq5ou5fOoammuENlOuA2wN9/YUFRCCEtIumW0syIyg0hj1eLjyNzcO6R0yLVNN2V3AWTF09DrC5dgeLhRd5OLnfwkL7LMF45xSSZflK7YTI8ngYytm0MmjIQCgLQBg4A4I5/tPLh22acrYGrJ/tM3IuiHL2mIqb8EDER5HYDTOIn1pjHc+/Al5i/ZwytLUb+o0ZLs5lln/dm2ee9SclupKI4xquYJ7tvLXOu2k5CytFbJBMp4pNbmXxGQQedgUMHYn30YzvChItFTOM4Vvn9XgBxxgQ5gndNH3C3/+ySbnljyli3KDu4aoMHFFSiaeZqXuzwnZCS5II9HP+f+2jIzsQZHUXTiKHudzrX2sQOR/AW3XWVUZTuD908QZOCeckLkKXBSkVBizvCEzEpQdXA3NGmlC5f3eli0IasjgXBv+MxiugWhgdWhxCQN05PE/Ikf3lpMcjiCswLlyM6mW8tAdL1ehOLBaacX8GiNwO1TNbbeueO6Zx6hy98J0GehYOHg4wtG9CE6NDUIBBMaLzPObzI1TzR/ym251uAttQcobF/exL7tqYQm9iCqgqa620Y7Mtqc3H83AJGzyyKaEg+ekemI4Bg1Y1GLuaA7z5l/UXXdgmxOZKIiXcyYkox6xd1I9Q8UaAhUTiH9wO2TDS2YGltIWftctLyt7LxvCtxxvif3Rp5XAY0DRZ8aQ6pjQeCP93VjPJnM9LhCGpsXT2Cd4vqFKQkffsmstevJLb8EBJBTY9eFI2eSE2P3sSWFpOWvxVzawvNCUm0xsWTsicfW0MdrbHxlA0eTlWvfu54lNEMwusMXarXeT3HdZhxBq3a9DhAAC68SidI0f3yOoRVY2sOLxxTRxwv/DCcV/4dS8khje4DWtm33Yp0GYOO8TborWe7j9sHQdI/fmnY6jvnzcjTtvLw2d+hHBzGWy9Z0c9bwVNatqKo4/Nfsi+Otx8awaV/WYsfB+P/SYSqHE8p2E3y3vwuaX5wpDFqZhGblmbhcobKi5UINGJo5Atmk0FwQhJTXIp4+GnqLzwbLpmLY80CrGNmeuX4Vjc7OXX6ILcKDUD++tSwHBbZWSrnXGBCPBr8/JpVze0Y6Ep1EVNZOfYvviNq6QqUVgdqXCzNM6ZQkJqMFIKk/N1kVDZj+nEZjelp2OrqSK5ry+ePj8MyuJGqpMB2RnF6exzLSOMDzg6bwCI0Rs1oJDmjPao0b3g2qqbpEcby8pA65aFa/SyLmsbTv83kpxWSJtVJbHotDWUJeGePSixRKmffssWtU3ukIGvLD0trOaquOmwCa8CExrX2N5j29j8YOTmdZsNnJhW0tk011Hg2NNKvi6PVzML3+yGlYOyJ3g1UguFXQ2Kz+9SyZ1NgLTwFlcksCboNISUxFWXEHiqhIfPo7O3tienn7sXlMLF5WRbBkv8lCs9zNVfzUlhhESEltvo6+iz6hp2zzwrrWFxOcLlCbV0yeLDkqrMq4E5XyGNJ+tejqDnZNMfH0TAwA3m4jEFK+n33GZnbNroHXYEkobCApAP7aExKJaa6Ak1RQJPutoYSgUASU1ZC6p4d1Gbn0JCeTcaOjZhaWtHe+pDm6ZNoOmk6MiYGZ88czAcK3Z17NjI8DAKrC0ALReO8P5fQL7cjeTI84rZePWDX3k55YgvoyVR+pPCFHm2XxEzNIQtSE6RmNyAEOFpMpGQ3MnJqCb2HVLE1cHOWowLO6E56HaRk74R5vDvHILBhrqYpNNTY2LCoG6NnHv3NUg4HKVmNmK0qLkfgd0/FzBQWB92OJgSZm9ZGTGJ9vbGe3bu6AltK6rwKZgESU1s459ZNzH96MM2NgSN8AslA8lnKJFIIHaI3nrC4tz6gYvggbMP6uYks2Jk7NJNPN7e/bMaxOVtNeqFZiGf07kdaiFkavJuVAOIKi+j+xY80pqZTVVuHI0E//8MhtOb9hST98xFEq8PtyTTVNxDz6VcMjI5CcThRXC69Q6SUpG7Z7nWcGYogfe1GykcOJaq0Wm8HLwQ13XtRNHoCtT16o8SrXuvsZGBYBNYo0kvuWcUFv9fTMnxzYQFMNIVZQucf/+Bu7tnzD0wFElVVABNgw2RRyepVT321DYtVY8CocoZPKSY2Ifz0l0CNObqy3bI/OOyx2KsqQtZZeEIqCtrZ83jmtVRaW8D/FQ18lZd+2ovhk8N31BwTObHhwOUMTnA0TFw3b2dY24quruiKQzriMJkksy7Jx2RRCarlKFQ2MyyibQspSd29HUtjeyWhp0fQyOMyDIHVRltFZrBeyTBvnkSUHgorZGM+WIxt5Vp6fbuQkW88h7U+dF5YMKTs2k7mNr1xgGeOjzHTtLfdd0XTUDyGDGNZY7n44oNkb1iFuaVVz3urriFm/hck3/1vlNo65JmzvFpPxtCICFBE5D4GE8y5uop7Pygkb2LH6s3MCWPdPy0Txwa9foHugATmMZ9iuiGlcHuZjE54FSUxDBhdzrX3reKsm7fSZ2jV0R6QAKA+qxstcQkRladJIdCuvpoftvVE7US6r5SCzcsCN+74tUDTDAm/wE9VdmoDY1Pzg25HkdJvyke9JTvsdCFfj9LhymydOn1QwO+69a1j7EmFBBXLR2kjUpENo1II7AuWeOUnehZ5Gd5Y0MlLcmZTSOUXq00yfIwLUV6F37J7DyiaRlLBbnLWLCf3jfeJ26zr+JYuX9251C0pSXjqRS8Ca0BIibmpGcWlOy0UTXPbUc8zMvLZM9ZtIr64EEVqKJpK0oG9DP3oDXqv+ZaUWdNxDB/ibpUeTl0FSOK7VTP2kuWMu3Q5Nrv0In6qprmvfXNFMfXdu3WqNuZzZnMP/9C36XWvBJpLoawwlsv+spYr7lnD8aftj4jAGgj0vHqS8c6+E4FkzsoGDYuQwAqw2VBvvI7X3xABu6wGg8thYvfG8Jtz/CpIbFmhnbULQoeeW61xYW1P8yPke7Rh14YU3n5oOI/eNBk1BIFXUSgePRvM5ogGeiGlrtiAtwB5oHyb869wIEI8UZdfoSETEkLv2/hpe4GiqysZ8tEbncsDlRJzcxPd1q0IaqDCfd38qUfqBROVJL79Plr/3mg36+0gpSKYy6cBJUdAz4GdcGodsy6uIT7ZP9n1HGBcfXrRMnKo33ORQoCi+L3PSzmeDYwMqOuJFKxdkIMa0qN+lEEI9k05IUR5WtuPEDqBvfQi1Mcfp7So8+faXB9OesixC6dD4Yf3+rY9D0EmySaQsbEhm2yoQTr9RIpANuhwPVMNtVYWfdiHp26fwOKP+oZcXqJQNuKEiO2qtnmb+39Pcj53aPvEyCAtA0eXtykU+N+LokiGzajBHgPV0XEhSSwYNkyfqPdZ/B2W/XVuEhMRkXU6sa3egLkksGMiXLVdfxXvhv3vtnQlpsIi6q64AJkQhzSZGMEGMigl2ERDCLj9sTouvTqd2TPbSaCRRoBDz491rFlA06EyDo0bpdsIP0csAU0x+bW7j3B7wAYqUgocLSa2Ls8Iev5dha7KhwWo6D+IhtT0kM+3cU1kUiLOj95F9u1LfV3nbKsQkqYIbOsxTWKbG8y89/hQXv3nWBwtRq9e/7AIJz/t6YEWHVxbVTVbqO7Rp4uPtGuxeH5vPn52CEV7EsIqPlAUyB6TQdPj96CmRdZ+UDOHn3Fy/hUtDB2pdqhmNv5/6GGNnPhyTFYnrqG57hl1OBCAvbqS5D3hedMBkJK07ZsY+cZzjH/uEeJLiyKaVUYKoWmYl60lOj4N7bfXoT5xHyv6XMDf+SvteaY+6wiJokimnR06LG14rUpXrCF/3ChaJoxtJ2Zt11JLSqRl9HC/6//IVMwhtJJbGi2UH7RzqDCGssKYY4bQVvbLw2np2NjAgDGQusYMQ/3xU+RffotsqqGuNtwh1heS2KRfT2GXL7auSOeZP0xg89JQaVWCA4diOTQkhM60EJQP9C/EDxESpwAIVOEfCkaotro8ilf/OZo13+fQ3GAQ7hD1BkJS+erTqNdfG7YHTwLSbKJ0+WovKTFfbyzoRHZnZQ2nXL6jrQbVp2peaCRluph5WQUmRaHmjLNC5nX6gyGxGC6RVSqqMN/3KGlX30rik891qmluJJCKQvxPy4ga2B3n4h8oveAKbjY929a4x/91F4pk7Kx6ktLbHQPGdTUIbG6sdBPY0tXbOdR9BNtOvwCnXS+20wmt/ruqV39a7TEdxhAJLGFy8NQGAQfyE6mrslFaEEt99eFP6HxTIlRN8yKw4ebDBrvX0mymePjYkA4ChKDpnt/R+OpjyDGj2eGwe9UWRAIpBXER2NZjIid2W2k9lihvD5WmCpa/OIn60tBVmwCalMSuWY2WlYjS7D/JTwIHx0wI2hv4l8b+HYms/NrIZwzPaKqq4JLzm9BaerL1nNPp+fUCEvbuDzl0O6LtNKRnEau1azx6CnW7t982A4+Khh8XSB58QOP55xUqK/U9jBwpufMuldNPl8g2rua49Cyi77wfKUTYxFIC3datoCpM0fReSxeQs3b5ETewnhCaxqbvqtie0J+augu4o7gHLYpAbxDlecX1o7JGSa66tzTs9ofGIBNHMfkjh2Lp24scRUE4HKjpacR8+BlRazZ0uLcqCiVkh9W68Z3HhuNs0WfCUTFOcsbuZdyYo1s/2dLUiMUZ3PBJQBwspbmxmmh0j1d6hpECEyGRFUSUt3UsYdeGFL58JY9wmh0YSPzmG7ToaJTm5o6DvBC4bFGUDvXfSMZTASVSqJqGKYLJsC+MIiqAL1/OpbnBHLbii1Ak0050kZiqoN57D+qF52GdekJY9uxQP32iWbp8NX3mTPVSfjFyY6ubnSRF6++hI3Mf59/uYtkXPdi/PRnQG3JkjzjA9X8Gp01l/sZi5o6bQN2U6cQt/TGiKvuo+josjfU4Y+Law8oBir+qvl5A/w8+w9Ta6j7XIz3VFZpG87YSvq84ld27FBbUPM13msXPntuf2aETGznv9vbUQIPAGt5ug8AClK7e7j7vmp59WHX1rSQX7Ca6qgLVagNNpe8i/1rqh0gPbVclFO5K4Lk/jnd/1CO3mqln7iWz5+GL/4dKIwglrxW05e+e4KlCAkDT0FKTiB44OETiXChIbHYXfYdVhp3mdUyQ2FlTBhId450KsOHHGOpKEsPehoqVBcxgYck3TEppJaqqBqCdRElJ0ajxFB43pQuPvOuxbmE2QtHCln9BSE4/10FyssYrL/bn4CYzffsN5dq9vwu56sGxx+vFVAHeD88Xx3MG+Le/a/zlbo3SUoiKgrJDsP+AYPVqwah+erq7OmQgNb+7gYTnX0XUN4RNI+yV4eUrx5UcJGftcghzu12BzQzhQt5ky988848DnZn+2SV/KiVvbOSdodxkNr6YfQDEkPnTShIOFnegyi9yNfdyN4X0CGPL0k1gQffM7l40gPed9Zz5XsSH+TMiNHEQgGj0NuRxCZETWKFoJGc2M3xy8bHSGyVsSKlHeiIh9mac/Nv5e36vPkqMXWBtbNSLI9FzIFtj49h2+vk47Ycf5jQm0SIhrUs7d5UXxVC8N3SakxtCw2yB3NMLWfpDOt+XZRBriuaMGWeR/sOHAYmsBJz2GMpzh6JabG7y3rx7O9Yx2W7JLUP9xVOtoCa2kHNvraWlyYSjxYzZolJ2MJYP32/mzLMzcUW1YDKZ2P/iawz6460oH33kTr8K504m7t9L+aD2KI4xuTBksQyPXZ9FP3kR2CMNDcGf+CeP77uN1ktCdanUI14ZPVu55l8dG2y4Cay1yU1g937+Y0cSpyhU9RkAfQZgam1h3POPubdu4ADduY1Hmc88d+vfYGhp8A6RF+Yn8taDIzj/9o1k96kPsJb/oi5/aTO+XthwEE4ExNzaEpY1UErKUROz9cLL8kbssZL62khsq76XmeftxmyRvy4S6w9rvo+NWCd1M8OYxXc8U3k9F2V+hmqx0RofT0tCMuW5Q2mNj8CI/QLYUlJHaUF82ATWZHEx4YwaVDWOASMz0LQMFDEOTSr823Y2H7SezijWdSA9AigaMY7ikYGF+T0HEH85OGYzHDwouPW3CuvXtx9vrx7pPPCHJk7pB+YTjqM8bwDxd9zjnlQEgwDCjVFkblqLJhSUMJcP1+fkwEIR3bDiIJt2wvg/LuUqXvKjAxt4i4pJsvmnGIZPCTxD1r0zergxqLdKSlK2bO+wt3/yF/7KvQSciXSAf8K97ad4fvyuiSknOvx8/8vDaY8NT88wJRHA7fXKGxrOdWk34ULRyB1Tzszzd2ON0mg9xjvTbiutZ2Tv9ve3othOVWlkZNOFhQe4kw+1s1goTyS6WwquqGha4xKozempk4EQ3tJ6SzYE0BANpRfr64319GCGi0MHwhPKNxCfWccpFzh44+7u1FdaUBSJpiVys+ldbrI+y0OOW7HI9lHYeIJcUdFsOetiVFu7xNDez3+kz5ypHkoFeLWj9SSyABarxoovu7H+x2y3asTatzSGTq2n+cZSzpuYzpYnXyRvyvFYfvd7Xf8wDAit47vjSWQBHE3RxB08Ms1nKkihlgSyKMGO/mI1YmciP7GJ4V5azcEhOLTfRlWpmeRM/R5UNzu9CKyrTm+ks/fzH0NuLW3HFhTVW02niGyOYyUVpIZBYP2PLlITaFLhmzcGcPnda4Nm4/gr6jJSCQJ5YcOV1grVdKQpNY2EksKQ27GOHIkKbl4Ql95KfW10WMcAEJ/SwrSz9jJwdGSF9ccEif128U4sUd6C0IX7E5BaZIbHyFm5mac5pfRreooCpKKw49SzjnoCCzAkK55l5vAG3W59a+k7ezVlq8ezbKXVXSWotRmCA44sppiW8JN9GiPqdQOlCYWGzCx2zziVpjT/ldfG4O/pAfH82yC0K1cKTjzBhG96VsEBE+f9ph/Hj87g4asWMSL/R2xVNWF5CiTQmJIexpIQU3EoJIE1cnmElLhsUZicDpAduz5JoJlo/sWfeZYbqEYP5w1hE3/mPuw0cQX/C+u4PKGp0NzgPbh/uXAbE8brWok7HHZ3nlwo+RvR2Ii5xTucfoDu3MPf2v7zRyL0oVUfgAXBvG9CkXzwhuWoJbEIQW33XiQe2Bf0WXKcPovofnlub17/vEbiEzTqaoORLMFJl+wkLrGV9B4NxMQfWVmbXxKtTZ0rVlMxs5t+/KXpHl5svhYhJTXde7H/+OlhFRp1Fr7eWF/96nBw6vRBvPhkTVjLWmwuJpy6H2dKMR88OQmtLXZq2FeXKnhSu5GWbtk8W3y2O6TvsMdyaMhICsdNQnrUGRgk0ZPI5o6ZyQ6H3YvIGthcXMfuT8aze2OqF6mTmsKmhfFsXRrHuivK+ecdZsR9D+r2LMzr0JKU7PdzT5KTVLUrrG3peaS6E6ElLh5bm7KMv2NZzGTu4W8sYgYAUTRzCa/zR+7jTD5iEyPCPANvNDUoJKMTWK3NphsEVstf5yawoUicvboSqShe6Rl/4x4qSA0pnWjIewWClIKKoljKCmPJ6NExraCzXlhPAuurM24g3Dz0A+OnkLl5XcDnSALE2lGnnOj+zKQojDyxluJdUQR05AiNnnnVjJ5RTHSsk6ye9SELw/3hmCjsGpQZx5CseK+fnO5OhBKMpASpWETyPLqhFapK7hcfEF11bMhq9RteGeK8AQTF+xJY/doEdiyP8ytzoUkTraqVxxtu9FhLYqurJXnfLszNTe5WquDdNcrQaTQpitcP6IR2e3kjN94CLhd+9q3//9PaWKb8dg4L3nUGLQgpIZNNDKWCFARQO6Sv13EFghqkyMd9DcwWygcMIn/WXFZfcysbz7uS2t492ist25ZrxcaJfMe/uctNYAG2MZgLeIcLecvr3MKFYoLUbjrL/3LhNrenBfDSi1QGjMKeYg/6E52Z0KGw5H9cjn+dAgMChKTfiGYs0a1Bj19qgq3b27flr3PbL438E+ciFf9eEQloUTZkTDSo7VlbFgtcfYuDgPZCSHoPrmTYpFJ6D6n+VRNY0L0hnYWKmTe4hFqp1ykkHNxP3x++Cnv9SOS2QoVLI1UpSOldEYZdBWericXz+7L502FIzX9dgpSC5w+eToHWVruAHpKNPVRMfPGBDssbJMogVa66avfk1SCyhje2b9xodm9IC+CVFKhOwTfPp3P5rGa0Q1UBQ/4OLGwjjx0MxIVCa1wsMi10SFwNU7mnISOLkpHjWHvJ9ay9/GYKJs3EEdNRHegT5jKdhSyhPY2vhWhe4QpGsY4NjAxrf75QTJKkdJebwJ4xLKtTBBbAZbV6mYdmoniDS0IQWEl0rIPeQzp2F/WHmvLAaRKReGF93wuDwAbKhw3n/J0xcRwaNCJo0axr+CAoKXF3n5u/sZipc5qwx2v4jwLqDpNJc/fTd2gV2b07R2DhGCGx/jB0UkmIsHrgAVnFxIa22Z1ATxof8PV80nZs7lRl58+JkdOL9Gp/EZyiSU3QXBPToZrVEypm3pYXuHUOhZTYGhvouWwRo19/BmttnVubFHCH8wLloRlk9sBeM1vWm0NoxAlcLji/5CkaZMfw5QqOYwbfk00Jw9lEOmXMifuB/dOvdR9PnLOYpNo99F3+JaNf/Q/jn32A4/77MCPefB5ndPAwhkRQl51DyfCxlOUNI0aWoyRL9p9yAq3XXeTlk3yam1jB+A5hI+P/RmKJlMCCXpzoTF3vJq+G6LpnKHSHw445PonofnnBfwYNR86Y7NUQYh+9CdnzWgq6n7CYqPgWgueVSqLjdPJnTGKi++V1aIn7S0KNjqZoxFg0j0mI5xkJhxP7v57CNOtsxJ697uf4susdjJ1doy/TRmSM35k96plz1Y6f6xR+ccQnt9IzrwqhBHoWgj9PDmzsauvuJtq64/Vc+n1EToJARNYYkH3DpHlpMV6DeWdUCmyxDoYdXxrUXurQIxYNZfFB7ZuCxjuc717DpLpI2r+HoR+9SY9lCzss70lktfx1AF5EFnRivvzLOBRTiIkpgm17s3mQOzp868DCX/k7mZQyuI3G9uQAD457Aw2l3TkgJYn795D7ybuMfeExxj/zIGNffJzMjatxWW0dtusJKQSlg0ZwYNwkmlPSkCYTRWMmsuPis3BGta/bgo0reAWJ6FDZ78JCDUlB9xMIikkyfEoDDkvrYRNY0JVPPKN6ZaTTQvDxRTFJcseUM2JKeMWfNntH3hGowYEvfNP5fN8PfwQ2UjWQ0mGjaE5IapcqbPvcUG4wL1+HdeRxZDzybz7dpJ9zdIxkxAVLiY5RvdYSQiIUOPXyHWT3DpwLHC6OWRKb3bue4ZOL8W9UgxsiBY1o2pPZBBBbVsrArz9m3AuPkbh/T5cea1ciKa2FeTdtxWwxqqpDkNkQNtmBjSa8iYgAzC2t9Fuy3GsDnt43k6IEDNsdKglTakYKGonlLS70+nwh05jCYhYztX1ZFL5unMqp/ziLbQeSyZwwlu6pKeS99SGZK9cSXV2DudWBpaWZ2PJDpOzZCQj/Wqr6NyQe2Mfw9/7HmNeeIqqiij5zptJnzlSsG3Z4eYef5ia00CIjEUBfvs+kXcSmNbijC77wzPNTE7PbfyyJqFWtqGqU1+euO/RByzjn5DC6CCkmicmqMnpyRUgePnyGLi3RVcU0XQnF6WDIB6+Rs26F34ppY7IKQFEJlnnnoDQ2YFIUPtlczGm/OcTv/3uQnJGF9BhYzYCRFZxxwxYuunM9UTFH98S2qzHj3D1YrKofz2R4uZVRtHtzBZCzZjmjX3uWgV98gOIK7iENRCyCVVYHQqTe2Iwp68P0nIWWZVPQqCC1w1oAPVYtJWlfx7C8J5E1io4MImsQ86pSS8jGB6Dby6e5yasRgwsTp/MJ/+LPXhGlYrL564K5PLjldqSEuNaDDPj6Y4bMf4uUffnYGhswOVqxNdSTtms7ZkcI+SMp6b/wK4574TF6/vSDOyfXXl6BxSPl6SPOpJrkIBrakcvfKSaJPU5l2mVlfgms8Rz5fc6kxFpfh622GuERrWlMz6Syd3+3XU2gFhHiXZBSEB3rpGdeNbbo4PYjOtZB9wH+JRZ9vbC+jRq89uknjaCzigSeSMnfxvB3XyGqrrbDHRHok1WhaQgpyXz0AcZ89pbbEZOQVce1963khAt202doFT3zqjju5ANc+6+VDB4fvE1zuDhmSSzAiRfuYuqZe7HHtefpmS0qKakNAYWHQfegzeVTr8+MG2NubWXQJ+8QU3b0yuf0HlTN9fevICbBQfCXPLQBSKCGGDqSEqFpWPYfxLp5GwmLF2N77EXMd/0FZe1mkNJNYOdvLO7ws74i/IfTpGisFu35nhqCK3kZFVOH2bmqKbQ4zPzpjamIpmbiH3gK0doapPZfuuml5tEAQPj8ttXUMuCzrxElZXphRbPDTYQ0BPvoQ/BXJdyMXh1RCc0MnrORMy8u9ktefbHDYUckpCEanZjv+AvWgUOwHTcJW+5QLOdchLIlX/eOTp+F64MPIC6OZmzEi7qQIa+EVBdFG7qTO/oQsQkOvyFVvRrfxYgT6joQa2hPNemsTFJXoMfyH4k7VOLXyPpCqCqUHiLxo/fdnyVFW+iZ18qQ0zZx3m2bmHvtdvqPqCRAdsKvGqnZTVx053p65VXj+dwmZzYR/FnX6MF+BrPV61NjjdTdO+j/zSdhHUM4niLf0Kk/b2y4RPbU6YMwWTTOvGkrU+aF48QIPnFVMdGT/X6/04Qge90K4g/up8+ib+j33Wd0W7scc1Ojm1g0HSrzIrJGWkFUgjOIl9wbh8iklPbahnc4n685xU8hkv7WvLM4lz2Jp9OnvJLUnVvc3/j7De1eOE14x3uMZRRVJWf1T/Re8j1xzmJS+/X22utOBgYdp8ND+56FIhk+uZFrHt9PQobDL4EN9Fyl7djMyNf/y7iXnmDsK08x7vlH6bFsoXvStfOUM6nqrUcYismiB/sJ9gxITVBTHkVlSQwT5xQEPYNJcwsw+XjXg3lhPSMNhhc2UBqBP0TihbU0NTLw649BSi9vdLD82MlvPYtwufhy4TaGZMVjjVIZOa2Ys27ewrm3bmbyGQXEJ3edxvYxUdgVCEKBcScdZPQJRVQU29FUhZTMJqrLonnj/pFtM0Bv8mHCSTYlnIt/vSCBRErIWf0TO2ef/TOcRecQHesio0cD+7ZYgySOBxfGMOHiGl4ImDcpgcSHn9a9sSYTsAzTS6/Qb8Qo7Hf9B1uW/w4kiYM0Mns5KC3wp+PnDVUqLBcTeYfzOVN+yE8cTwG9Ay+vKazYlk7/m6+lznEraZRxDS/wOx4jlXYvSitW6ognQdZSMzKXqPJK4gNU1QopkS2t2H7cxBe2y3mj5kWKcZFDIZfzCgpqiArUUAIkksnzapk4ux6zRbJ2z0aEAls95IqDklkpER99hPnyy6GlxZukLVmC+YQTcH3wAXL2bOTs2RStLeSkqS62FScHOTb9nleXman+fCi7f3Bx0sX5LP+yJ+UHY90DpdQEcRl1/PaJWoQ9sPfBU4Ln54bicuqFByHCDvvpwX+5nm+ZhSpNTHhiN9aUClK769975iT/X0dqdhNn37KFhhordVU2omNcJGU089rjAyjfkYEm/U3qFP7MvwLaEyElabu2c6CynOaUtID7DqYb27xbVynw1FWFjgVe0LkiLyGg16AaFs8PuaSe0hXA9ppQPXLlvaFISWJhAUmFBboUmdSvTc+ffmDPjFM5NGQkrN5OnznpHRQLrr/ayq3Lw/dOPsatXM9z9GMPz3J9UFumKBrXPjmTmoZTEUimsYjbeYRT+Nq9jARqSAQkUXEa5XkjyNq4GnOr/1xqAWRvWEV+31G8UX8OqzgLgcYMFlJAT9QwpKmCwWKT3PBAMVExGskZLhxW/ykEngTW0wNpbmlmwFcfkbx/r9dTa2ltofvqn0g4uJ8tZ16MZrWyfe55fL+kG/9Ye22bJzZQMay+pR2r09m2MpO8caVMOn0vyz7vhaYKFJNEUwUms8bkMwoYMdW/wyxYW2R/CCeNwEC4Xtj0rRsQMngcUkXhE07nJa5iPz3JrCnB8vddaFN+Hh/pMU1iDZhMkozu7QYso0cDc6/bxmcv5qG69OpMk3ThwkIORXzFybQQhRkXFj8zQUVKUnfvIF9VvXIMITxvU7gPyOFiyIRS9m4O0oFLQFKPCqr3p3b4yoSTHIq4gweD70Rre4A9coXtmzdy/l+vZ/7zH/ktyhICzrihkufuykTK4ARPSsEOkccF8m2yKOZK8UpbCkNwQ13XlkBeTjoPcCdvcDHLmEgTdv7Jn3mbC3FiJYpmLt72Hne33k1ckK02azZOf/1Svn81BZOShIqCiTG8z7lBj6PtjIN+O2RqHWffUuku0p7dq6NxCkigXC6G3HEzpnff9WsuharqOUlXXYVz/36w2bjoqlh2HvLnO4F2oyva/wVam8189epArvr7amoroziYnwhC0n1ALVXRB0nOGES1j5yUYTSNAeLneu59EVVbjdkZXDXhc2ZzJh/iwoxsGzg3lgyDawQX3VVGVdQqIMRk4v8gYhMdxCa2X9thZ6xn/7fTyF9rx2SWSJeGQEPFwt38gwt4i3piiaXB/9RJCFJ3baMwZaqfb9vhT3KrqbIJe4rdTWRB90AZOdqHC0PGanB3SMrQnSH+SarEGuVClaC2+naK1B0nD3Cn16Q6EBTPkLAm6f/95zhi4nDl2P0qFkw6wcGIMVY2rDWFkJzSX+zHxG08Iv/AzfyHfAYGnYxrmkJVQ7T7fBYxjQWcwL+5kz/wEC9yNY9wO/kMBGBI/SZuX/MYl2lLglrAz5nNOR89gRMTWptTaQlTwkrCEkKv//BX/2Kxadz+zEG69dO9pYGKuAIR2LjiQobMfxOTU1+/g22VkvjiQrI2r6V45HHk74/h72uvA3DbkPa1PON8+mdGzvT2VRmMnXWQmx5azs51qTTW2ohNbGXg6HJs0R1bAwTywgZKJThSXliAuLKSoDmJzUQxl0/5nhMRaEgUtjIYFgvS9tYz8LZNnU7H2lYaXr7sr4LE+sLlFPTMq+b6f69g6/JMdu6wMX3XT0xu/YGNDGcMa2kiBhstXMib/Jn76Mter20IKVFUF6oHiY1zFoeUOgLcnU48Ee4AH+csps+c4AbeQP8RFXTrW0vx3vgO3lihaMQlt+Kqi8WfTl0GpTzM7TzBb3FhZhyrmMunmD36bQQyTEJV6Za/mW7rV1A0aoLfZQaPb+Kqe0t584F0muuDz7aNl71MyeQRcTuEkfPlCRUzxWRzEW+ynpE0YXeH0VuI5n+tFzKfU1nBBPrhP1R4C0/ygzZN316bwVTdofjQpHra2TUs+TgB1aVHCKQGtii44+8tWIaXUNtKUO1Kz1m3Z2vEzEcfQHlPjxoEvB9SQlUVyqefsmHAOSxe3InUBylwOUxsXJLFpLn7yenXbkirPRwFRmtDWRt5juKRghYi5r+fHpzJhzix4n3++nV689/pTLw2nuP9N5T6/2iDMZbd8EAJm9ebadySRdOWgwxe+w6ZHOI1LuFe/grAILZyG49yJS97h6CFwOwIX6atNACRBQJ6Y307eEWqG7u1tI6Z5+7mg6eG0vHd1/9P7FVB2Y4sfEPKAvgtj2DByR94kBQqOZ936OWTWhAoBUoKQfdVS9jU+wrinMXu83XViT0kzQAArhRJREFUVZMbDzuw89QbDfzjDzF8+1mwVuttRErq78ZT3EyctQlCXvr27RnpXHfxACs4jo850ysXdBuDuUJ7ha0M4iE/RWQAu+nL2fIDnNLklfuqk+nQdjWrby0tDRaqSmPa5Kr0Y+yZ28J1D5QQl6h5d+JyNHdoZAAdx19zUyOD57+F4gydbpK1cQ31Q7rzXsFdmBTNPT54I3ha3/qF2Uw4dT/DJ/vvFuqLQF5Yf6kEcGS8sNBmW4UISGRv52EWoEcK2u+vfi3KD8by8X/zOP/2zWHvrzP4VZHYgu16S9YDO/SqxoTUZkbPLOL0ifO5Y8ujjGcFVSS7CU4rUbzOpXzEWSxhMkPZ4t6WM9ruJScSSb6fL9EtXb464nxB65iZ7s4XgaCY4OxbNvPdm/3YvibDo/GDpFdeNfXVNipL7fh7wYrJ4Rw+xIwTgcSJlXRK+ZCzmMSykMenmkz0WfJdQBILMHxyE0MmFPDeY6ks+zy+7V0IFILRyaMqbO5wSyRwYeFHpmJCDVDpmsg1PM/CthfOwCHS2U1fXuWyIF6K0Mcyck4l488tw1rQnZoqQVaOxsxTXETbAdpFy8MdTOcNz0ZrbCD9pWfD6owjzWbYvJ4Fu2ejKMErpwNuQwp2rU9l0lz/uXxHC4SqkrZzC5mb12Grq8EVFY3TFoW5tcXvnfov1/khsF5bZN93Izh+9IYjd9BHMbaU1AX1QLc0mVj9bXc2LM6mpdHCggclI6c1MP6cg9xX+hvuF5O5VT6B4jEB3k4uV/MSKzmO57iuPadS02hO9K9H6gvfjlGeCNcbG2lKgeGNbUzZz5k3Cr57uz/1Ve3yR9GxTgYdd4i1C7obZ9RhG49zGwKJGScqJv7IfVzG/3iRa72cBP4gpCS+5CDm5iYwt5N4e/46GDNT7+gVZ+fB/zZy2XVmrrvURkOVhdCEUNCo2iNuEASg4OJjzgTwQ0ThYf7A6XzCJH5yf+fAwn568m/uRMWbwHoeU1AIjaS0Fk75/UYO7kpg3UYriiI54/x4uvXV2XgHAuvRSjaYCkHm1g2YXM6Qll0AUTVVZI7JZfGLvQIQ2NBwOU0c2JlI/xHBvfPhKhIYiMQLGw6iqyrI2ria5L27EFKjJTY+4PhTTSIvcE3QwrzC/CQqS6JIyeq8dF8o/GpI7IbFWXz35gCvwpTaiih+eLcvyyzX8D0nUUmKX4LTQCyX8DrrGenOcikdPKJDqDwsL6wfdHa9cKrArVEqs6/aydSz9lG4KwGpCbL71NFQa+Xth0YGWVM/N8/CnzIymcxSLuNVHuF2UkJUt5vDaFdkMsMFf6jghAtqWPZ5PEs+iae1KYghkGCPU2moMREOefRGR6kWAyoWFjGDXfSjP7v5iYnczT86kNrOwGZXuXhaGlYbMNk75KNqusqAZ/edYETWMMqm3bvo9sj9iIYwlQA0FaGotFY3AJ0PiTud/ol8dbOTecOzUTXNbTgP12B2BorTweD5b5FQXOhuGW1t1EXCAz0t8zkzyLc6Sgvi0bQjqst/VGLWlIEsXBW4G09zo5m3HhxB9SG7O9qjqYK1C2JZuyCWn6wPsEEO0T/3mAQa4dYXuJa5fMocvtC1ehWF8oFDwj4+f/mx3mkFXa9ZbBDZ5rQCrvtXFYW7EqmrshET56BHXg0fPDEUhAZ+8oKNAV0icNIuJ/UqV/IVp/Ic13G6+CzkxFRxuaiPbj/3psomaMuPNVrTDh7pYvF6jX8/V8aaz5LZuzm47JOmCmx2DWeLP/3uIOthJhhJNuPkWW5gEj/Rgo1/8Wee5iYvBYTOQCBIzW5ECKiNK6TvJMND6Z/A9tOqcKwJLqElVJWUXdvJXrcitHRPG6TNij0zA1U7vPxd1RmecQmVC+urShCuFzZUylfK7u0M/PKjtiIu/dpYGnTbKhH4yjWu5DhchNINFqz+tgcnX5YfYjlvRELmfxUmu67Kxvdv6ZWD3rkzen5Ki9PGbgYEIThmNjKCtbTHE2MqyrDV1pC0bxeZ+9aQOWbEkTuBIPANjQVCbKKDvLHlDDqujMS0FgrzE8MS7+4IwWtcxnHKaioInG+raBr1md0Y9/LjXHbOZK6bNZSLLj6REe++hKWpI/FKy3Fx+vVVxCUaCfGB92+xSU68qAbFJBFCYjKHlhILF49xK7/nQabyo5eEV2chFMn5l7rwlE7UyavmDvcY/88bnu0WLjd+OkBKrvv6ZfImjyHx05DVJW44NTN3H7iefz+X2SkvLLTJ02SEJ87tmQ/7c6LX0gXElxwE8JLSMiafoHeew+P/2jBIvZSC2vLwWyT+X8Hi+b2pLov2UzyqX/UNjsFB1zfh4hnaG6ooUhJdWU78wf0k7dtFVE1oGTh/8H3uPD1SgdpwRgKDSGw9VEdd/AHotYvGlP0oiqRwV6JfAhsKZWQwj094St4YdDmnLYqY8lIGzX+TIc+/RuqVt5DwnxdQduzpIL2lmDXu/k0co+eEdx1PuqSKlCzd7igmGUJz1kBwL68LC4uZwlPcyASWcx9/OmwCCxKhSIZMLHUTGt+UK01K5g7NJNfaRD+tKqQGbFR1JaP/9zS5X8/H0twUnqaMEKwceTkn3n0eDmfn7KqB9O4dO3J5Ihhx8x0r/LV6PxyngrW+loFffoTQNK/W3UaRpmhT+vEciV1hFuVVlHROS3zWlIFhLfer8MRuWpoVYonwHr7NDGUMaxFAcsFukl75j3tN19cLaJ43m6bZs/wWMx0pdNogHwbnkwgKZE/u4e88zc1+N62azAz56HXstdXu4oTEwgKOf/bf9P/yA1576HVa4hI6rJvWq5mqQ+aA6QKKIsno08LkSw4x7axa1i2Mpb7aRHSsymfPp3SaoBl4lhsJXFUaDLIt17V9HUWR9MvVuObWZlSP2+Qpe5JrBZGQxvaSWkRlBVp0tFdek2+oc9SX75H+n4cAvNocBoMGXKS8xYdv9g/a4jDkdlRBj7FHbyqBqbWFzC3rA3qxjDOvGJBH6q7t7ueyO4WUkkWo++2ndfz/abQ2m9i6PKPTTWVAdxB4NpbRpGTYB6+haO1h9ZqcXuyZcQrNyR0LUMF/kZcBX29sMJWCSPJioaNH7PDVK/Rr9Tse50w+ohsdq9KlEDQlpzL403fRhHATCmXVOli5lpZbr8IBXh5ZVdO4YFYC798f+ggGHdfMzPNr2bk2mr2boxAKlBZY2bg4JkgKVyibIjlId37DU2Es23Fd3/0IoSGlYMhpG9lbr5Nz4154eV9payNbdAC5dTV7l64HRfFLYBWXkyEfvoG1sT6sMzKObI0czYzV/8EhQz07HetO3GelaHTrV0dyZuDIpT+i7gsjEubeo4cubKjOXKEKugx1l0DXRUPQlJaOFIpe7AWMYl3QbRo40jrbvwoSW1YYE25kICg8GyD4Uhxzq4O4d+aj1NXTcGF40ludlRzyrUjtDHL614YYfIJDlSZeEVfyIHcSI9sHBeMyK0BMjXdbQ4EECemFe7nq3ccofOK/7u8Mj3L6bxSuXxbYhGia4He3KExsG3iGz27PpbE0xPPRW5bDJLKBqvYDw2SSDButEhcvWbLAjJSChCSNcy91cPmNLYzp7a3V51X01NCA8s/7Gfbq64iaWv2jiZM4dMvvaZg81W2MTYoCqsqAK1+ImF7/wEw+0II/k0ZRRLduUFQkUBTpvo5GntyJF1Uz9/JMt77f0YaY8kMoavCcQgk4MuLRCiwora24MFEfVJdChzXKRWLqkcvbOtrhLy+2pjwa1XX4QrmedlUB0LzvYXzRfoa9+wobLrya1oSkgNsJWeSFPmHsqgIvf9haWkdiThU1B5Mjzi01IBG8zFX8RfzLy34afyW0RRo8PWJC6p6wqCdepnHIQBx4pxb0GeBi2CgXWzeaUP2QUUWR5AxodeeS5o1tJm+sfl/Ki8xs/skesI1uaERuUz3X7T52H4e2Z+Fo0HOPk3tXcMFvXAwcFQ94k1dPIpe38ltMDz6CbYWuLDLYZqVk6Biaxqag2ry7iqXu3EZUQ2T5pgK94NepKkGb3QhFAwnWKA1Hq+I17gpFIzrGxSmX7gy5v0AE1kjlMqAX1rZHHsIlsMFSCRKKDgRNcVGQRNXVUnD8DGJ/0PW4d9OfcOQlew+uDvL94eNXQWItVi1YAV1YsNLKLL51/x/otsR8+T0HkpNwJIQ3yEcqOxTnLHZLq/giULjBH+HI6V9LSlYjVaXRyE6EvgCaZTTFqUPo59qOqGnftwBEkM47QlVJ+vhDYv75F0QfPSRgeEeOm6xx3XUqzz1naiNWxuxb//uaa1TGTXaiau2zbQMn/b2JijI7i761YjJLVPcE70h5xnXva7ceGg8/38ikQXaam100llaQmCAxhCsM0urbLYWmZux3/Atl30Evr2rMyuX0uWAe6ssvo110EaBfn6gd27AWF0V8lC9xJWacQRobSGxWjUfur+eic5r4ckk69z8Em9frr3+3AS3MuqCWkdOOvk5cnYXatxemHbt4S7uQHYTSW5QMn1Lclrbyfw9GDqgvzNbgE4ZwYMLFObwfdBlFSnA46LHiR3addIbfZcLRjgXvIi9V09xENtyc9GAwrlPvCXtZ924QacMQEEh2MpDG1HRiyg95x4XayGpA9QJAfPgt8pZL3RqyudYmREIa9zzSxOWnx9LUiBeRVRSJNVrj4rv8N6FJ6+biuvtKeeEvmThbcSsAHEkYxbtn/aaCaWdraFoRzQ0KZovEFt3+HvqSV4PADvrsTcw3/MYrKmpudZCzdjlJBbvZfO7lqB45Xsn78v3mdQbDTgawgsCFywZ65tYw7ew9RNldrP6uO5t/ysTRYsYa5WLo8aWMm1XoJVPni3DTCPzlwnYFgTUQmo5CY2q6HlFBBNRB9lxDUSSDx4enyNBZ/CpIbN/hlexYk97p9QUaN/I0yYSeMUghiMkvoXJibqf3FwyBjPWE8f0DGt9AYa7BZ69gw1tTqa8SbsMUaXVqbMV+ZIoJFEVvLRfmesLlQmzZgkzRc6NyPfK/H7+3ieED7Tz+Hxv5+/Q8xH49W/ntb1q46pKmwNkaVvjqjSaWrbTy5nvR/LDYxoFCE12QAtcB0dEa2VkaV17cxNWXNZIQL5G1jUQBUcl0COP4oqmyiZj3PkbZV4jwiVMLVUUCpuuuQz1+LCQkkCtUlJjOeb320jdEZy6B1SK59rTdqFHZnHW2ZNDURpxO3QP8+baOodZQFeu/BBrSs1DNFkzBJlBAVWYPvo25gjXbnHzAWYSTOhKb0HUdZH4tSE5vJiG1mdqKKDpDahRUomnmRp4JvazUSNu5lT0zTkWz+C8WCaYdC96SW4Y3tquJLEBGXimzLq7m2zeSfJRUAoeUPSGQxFKPvbzMrw8zaMWAlLBuo/u8DSIra8uZPQTe+gpeeMLGV/OtOJ0Cs0UyZGodUy+sICrTCQHsRO7YZv7x/n5Wfh1H/rooti6PDXEVIo0X6esoJrBFawwY2cy0c2rpN1yPfigKxMS3G3JP8ubpfc21NkFtLebf/E5vAuPjuRJSElNZTs6qpeyfNFO3tYqC4nJFRGABDtAj9EJC0ndoJWnddBI549w9TD9nD6pLYDLLkJmHwdII/Hqf27ywng6TriCwNT16E19cGNATqAmFmh69OWDJ5P3YR1jXkEsROSG2KjCZVWxRkU2GI1Vo+FWQ2AEjy1ma2ovaSltYCfd6qzs9/8OFhYt5gwe5M6x9SQS2+sgu8uEg19oEQzP5dHPg2UywPJpTZxXyw8cxbPwhHlqt5PV1Yo/W+PLb4EUsCi6OYxVZlCIrOzcvd+3ZhBrjn3BcnAcXPQ1V9Vaaq5rp1tOEEOBcG3q7Y80w9kJ4J7M31z40qRNHFgySPj1a2fH9FrcBas7fHlBe0TAgHVJHNI3B3yzsQGANCEA6HFhHjIXmFoSUaH37IE0mr77d4SCdQ5hwBSxcBEhJ0rdphF3z0tLaQq4dlw3kmfuloVmtlAwfQ7d1K/yGvjQhWJE2k7O+e4nS6hjMwoVLhqdyUV8dFXKZXzt8Jy5CgYmz9/PVq+FM2HVSY0Z/312YSaSGT5lLDwKrH3hC0TQsTU20JgSveA5Xcqurunh5wng3TrumityxTSz+KIH9222YrZL+I5pZvyiW5gaFUIVQ5/CBu1gmssx8kIrifQ3WLCC6Xx5qYjYnDmig+2Maf76/maYGE3HxEluUANLcBB78a1bHxGvMOLeW6efU8rfzbVSVBtOhxSuSFh4El/zpEGNOCF7gFMj7ahSzyYfvgyDyWEJKuq1ZRtbGNZidDjSTmaakZLeaSbhIpSL0QlIQHes9xgkBZkv4+wk3DzZQGoE/REJgAUqHjCJn9U9tZL8jpJT8QbufV988HZOieZR5Bb//TocZp8OENUIie+r0QTQ3/h9qdmC2SM793Sbef3woNeV2Al1cM07y2MYcPqeIHDI4xCW87qUPG45Rcdo7VgYeCXi2HOz0NiytPPLPFFSthVyrniSvVBfz4rup/P6+7jQ1+/P+6Z037uHvQOcIrGoxs3tPMfKAHsIyDG6gPOF97bfAvazhYQk005yVt4Ok2DHUNlr9tsEUSGxWFy2OSLwugj+dv5qWPQXuT/zt3995eBoMS2MD5tbg3j0ByKbmdm/M3n16ODGAsTU++YnjeYFr2MlAUqikD3uDElhFkVx2ZhgGOQLoHq/t2FPsP6tCQemQkSQV7Camstz9rhrX5ZC1G7NrPqTepU/QXDJ882azH9nig6MdgSYuQyYeor7GxtJPenl86j/YfRf3UU46GgqTWcJ5vIs9SJ2BL6QQuKKCT66DSW5BuzfWl8h65sd2ttDLgEE6+o9oof8I7zzqEy+u4d1HUtmx2r8+twknY1nDDH7oXMBeCCp66/s3iKz+/m0HtrenF7RNUgEvmT/Ai8x6wrgeQsC0s2v56OmUAAXCEmHSkGr4aWpCaNhTGhk+JTCBDUVejQ5cpp17QhJSBV2OD0BRXdgryglW7Wy00/0fl/MZp9GCjbGspicFHKBHQC1Us1Wl77DwFF180Vk1glBpBJESWNB18QvHHk+PlUvau3TSfsX+kvoYr+6ZCxCRVq5QNMyWw09LCoZfBYkFSExt4aq/ryZ/fQqLPuhLfXU0+AxzWRTzJbPJIXDeoTPajqWlOeALokiNsryhXX8CfhDdLy+ENHZ4mL+xmLlDM9nhsJNrbUJLyubK6+Hci8s4/6Rmvs/vg4IeblExEU0Lz3EdJ/EtZaSxm37E0MhQNgfsi+4JCVQMHYy0mDt4TDInjA34kvl2RAtFjqKsKi/f+i0XPHgqTlf7yyWEXmA2ZchBBves5LmvhgV98cyKhioFVrPGfdeu4dzpBV7f+yNqnufh71w0S3gDpFcYse2Zk36IrDSZ0KTgeu0ZXuQadw6s0Qs9imacwobqQ+bNZklaGlx9g8lLT9MY4Px5pfyRmaRoS4fnKLpf3s+mFWtytNLvu89J3aUfmychMn6/0noxdcS4W1uGD0HumPLQi/0fxYRTDzBo3CF++qwnW1dm4t0WWv/7fu7kriAtrDWbFdEaOC9QE4KqPgM7FOT4QyC1AsMb69vJKxC6otDLF6lZLm56uJR1C+28+7d4mrC3Rf50rerjWcZHnIlEsImhNBJDf3aRFobXTwqBZrZwaMhInJYYr0YQnukFxrjhVkZpS6swMHdoZoeiN19iO/SUCnZtiGLz0hiPJjW0yR7CZXeX8b9/pKOpwVKgZFv6mkL3AQ6uva8Sz0wRX6LmS149PY+eDQyyquuJ8pq+hobS5js0rqPb1rZ9tk4ZzYnat9SQ2PaZwmrGtclIBVazOX5OAdaozuezdVaNALquK1fy3nz6ff851qZGL8ZkSBfWY+epiivpTPrIwNHlhGioeNj41ZBY0DtY9R1WzfqFrT7hQYGCShXJFJPtl8RKIajq3Z99k09gxFsv6t08fIisBMpyh9KUmnFkT6QNamJ2p9QJPEnIqdMHUd3s5NPNpW4CYszqHC5I71eLKb89FB1NI7fzKNNYyLm8y0ec6f6uJwX8nXu4jNe89ud+8NvyZluPGw03XEmm2f/TaxBAw6NieFc8ByXDs2Ig0As7IbeEBf/6gOe+Hsony/vR5DDTL6uGK07YygVTd1LXbOXTlX0pqYrxQ2QlYwZWcPzQMnpkNHDJFVaSEkxAnp89tZM141g8vcue5wKgWm3UdO9FwsH9EYWwAN0VkpaGlBJRXs5ay3E83fMBvqyayKEq/V4YObCGwLwDK7HxUFcLCD1VRkrBwMEqDzzbREVcFGkJ+n03CKyRomIM5MZz45sLOyQrni8XbuPU6YO8nqNcD29s5oSxEEJMu9OQkkGfvEN8cWFQM/oB53SCwEryxpaRnBG6ccf/ZSSktjJgVCXbVmXoiVg+j/RmhqIhAk5yq+65A/sPS4j+/scO91AKgVRMHBg/JaJj8gypezdACF7kBYefVuAPxvtz6vRBCARJ0Q00Nce421ePYg1PcROfcDp/5x4O0BPQ09vO5gMe5TayPWS3vFwwbQR26xkXuCOBvh3N2m1ku1fWkPkzYFwP3zQLL5UUY9k/HqTvggRWfpJE2QErVqtk+NRGZpxbQ1ZvJzXl1Xz0VCq+BE8IickiGTernvhklbxxzfQe0kJNi5Nqn9fMk6h1SBtoK5j17cBVMmAM6Ru2ECmMI2xMzSCmvJRGYngt6WZej7uZVYXZbQ1128/fs87AGuXC0WJ2p1CYLSoTT9vP2FkHIz4OCO2FDUeNwB8iVURK3L+XvM/ec+fC+svRXsJUGoiLaLugRwDHn3IgonUizYeFXxmJBVj+RU+K9iTgO2vQMNFCNPOYz356+m3/p1qstCSlsPmcSxnw1XxiqtvDBJoQlA4fw77JJx7pU+gAf/mwwXIWDRKypaTOTT48iez28kYa6uGSOXEc2JeC6nGtmonhn/yZR7kNB1avMPV+enA5r1JGOn/gYaDNO5CegpqQgJqWSvPUiTjzBnhVjYrGRuxmDZkQT1OL/rL4I4C+MAaj5t3bvUitL6Htm1XLg1cs5cErlnbYRvdeCgse/4bbnh7Hlyu6uz0K8XEubr/qEHfdUNLWpckEbc+E4cXxnPUax6LDO5Tj5RHyMCKF4yaTUFgQcd6bkBJZUcGmAxX87z9mHn8gDmWvDCotpmGirhYee7GRqgoFlwrDR6kMHmHM5JWA5BUCE1hPfLlwGxPG928nsg2C3DEz3YPMkUJSwW4SikIbwwZiCV8BUqcHA0eXcfJloeVv/q+judHMZy/ktRWFdixDeouLmM4iruYlv+tHpcdTf+l5NFRWkbpxK4qmue9Cc0ISu046naa08J0DkXTy8pcba6CrvLGe9vj5R+vZ/ElffJn+RkYwhrU4sAHtHjYVMx9yFsuYyGrGkkGZm7jWpWehWq3U9OzLocEjcEV7TO41DUeTnRi1jNJlq8icOM7rOhheWfd+2tIsoL3Q1rddr+d1OmtUNmeNAv7gYP7GAq/lqpthxJwKVLOTha+nUVfZPk70GdrCub+rILtPe2etmrasC4Oc+RJXX6LmFTI/VEbpav3veks2ZElquvUkoTi4LJQ/aIpCfe9s8u+8h7MevpCC0jj0eu7gElrZvWsZPrWE+qooouOc9BtWGXGep4FwNGGhc2oEEJkXttfSBXqBXJBlGgk3fbK9sNEa5eKsm7e4C94iQajr4otfFYl1OQUbfswOmGyuYqaYbnzOHM7gE6/vhJTU9OyD4nKSsWU90bU1Hb43NzURVVtFc7L/Pt1HEstX7PL6P5zK8SFZ8X6J7Lzh2bz7ipX9e5UAxEihye+Dq89S/8j9XKy8RZZWjJwwBvnco7Qe3Afota/GkKDs2Y/1tQ8xr96oEzNFIWrSWGrnnoqaqQ9Y/gTM7Sl2L+Pr+bcvoQ0HfY7rxcfHlVFUWs2W/GiibJLjRjQQZfM2gL4hSH8hSVNNsTuM7i9n15Oca5lWDpw4jR6LliKdekgxXDIrLRZWLLby+AP6fQhHG1coki+WNjLl/CosQD6Qv9H/sr7eVwj+TBnP0vIVu7yILDTpedttRDbOWdyl3tg4ZzHZ21aFVZQxnI3so3dQqbHoOAfJGc2kZTcy7uRCElL+vypBONiyLBOXK1jBksbj3NqBxEqA7ExkVjqWpRuIK6twN6EwtmRyOokpP0R9RvZh9/31zI8Fb2+sL7raGzskKx5Hq8L3Xw/FX/hZxYzq7nLkfZ4uLBSTzT/5C0+K3yIVwfY551Ldu3/HHWkaOWuXk71+Jda27ogt8QlUbNlO5ZA8EILMCWPdhL4d7X8bNtWXhvlLQfDMp+2IYkaeWMvBndG0NCqkZDtI6aZPDHwVBsCbmHkSV1nb5EXSQL+XflPPhGD7aeeQ99n7JBbtj8hJIKQkpmcW17x6KYXl0WGtKTWFA/lJnP3bLV3W5yhSTdhwCWwkiKquJLY8tPzVYLaGtb307g3ExDvIG1dG3tiyI55GYOBXRWLrKqNobQ51SpL3OMeLxEpFwRVlo6VnAoM+ecdvCFgAaflbSd2znT2nn0pTln+vwREJp7ahM5JH/ojs/I3FvPZy305LU0kErw64l9vvNqHNnIGp/pCPpxJYtxHTbfeC6mpvD6ppmJesImXZWpwnTKJxxAgcgwd6eW19Cawvgn0XCt0ynXTL7FjQ4ElWAw147mXdx6H/DkVmo6RELl6OwH/Vp4Hd9OUbTsKBldHKWpLHxfDQQ0QkiSYE2BRzUM+Sp+cpHO+rJ4xnyRigPt1cCm1tH0Fv0mGE/Az4esvCfT8817NbLGF5XG7kGT7gnCBLCGZfvpPeQ46s+PavEaX740JkIZrYyhDqiCWe9uIdAajXXopp43ZiH3gSf0bH2lhP3x++JPHAXnacelbYRDaSTl7QMaWgq+A5Edy1PhVnazCyH/hdVjHziriKf8z9HteMCbjyd3ecFGoauV98QMoe7+iBra6WnMXLSdy2l9qBvShvbkaNbi+S63iNtnv9dpPaNm9tIDLrCzfhGtX+mZFf60nGPD2uoE8ufNMFDPjaEH82Q09fa7+WgYisAwtfMJu99CGZKs6QH7Px+DtZ935kjpDONrbwxZaSuqAE1oBxvTy90xCcwEaaSmBpDo8MD2I7x7OUFYz3W0AsFI307g1c+qf1Ee2/q/CrIrEirD7Q8B7n8Rf+RZ7YoVeDx8dSe+dvif/xJxILCwJvH0DV6LNwKRVP3Off2HaiMvBIwyAf0O6B08M/nXsxTRaFvVMuQ56jQW05amK2V+gdKTHd+XdwuTq0ThVSIl0uLF8vIunrRTi7ZVFz+01o6akdPKz+wvpdjUgIrLGM9DjnYMVN1vWbiH/mZX29ANurJZ7L+B+fMA+BhkCiaSa67aqlpNwekfHUVEGZcydfLvQuEvE0mp4E9nB0YD09LSIhDatPWoEvefUthAsGY11j4NW2bHfnWwfDNBZxM//hKX6D97Cm/z18cjG9jnD3mGMZhkKBv+dCUSQICUEllSQ38QyvcynSbEa4XLiuvQouOAvbCWcEDFsan6Xs3kHGto0cGjIyouMO1Mmrefd2rGN0UpbnUa3vicNVKjBgXLO6yiivbniRolHaqTrvYmK1Kq/aAWM8Sd21ndQ9HdNfjL3FVhwipuIQWctXc2D8VA6OPV6f3fq8e771B4YNMybnvmQWOubR+oOn19bX6wrepMzTXvhKFQYdPzWNIR++QUzFIa9z98WHnMl1PEclqW0ShCZuEM8x7F2JyST9djbzByEkmb3qD9sLG44aQUcvbLuHOhwPbCS8wxEbfp7ri1zNeFZQT7xX3YFQNCw2jVO6ICUrGMEPhl8ViU1MaSEhpZnaymDi3AIpBA+kPsDLQx9FO3kWLX1TsNmjsb75GW9wEZ9wOo3EMIxNXMML9GWvx9pgqq7BumELjlHD/O7haCKw4P/lscdqNNZ1zt+vqpCS3G6QOpDMNRsQBYG1IT3vjLnkEMn/epTKf/+Vpkq8ijP8kdfDqYb358U19uGZLwbtZNUf/DU68DUw1o1bSHzi+aDTBBWF2XzBCsYDID3KYooOxUdSfIuiSFKynVx8ZTqKEl7jj8NpaODpNfCtmgXvd8AoPgkXngUrqBqxsTEhCSzAF8zmC05t+6/9ytviWug/LZ8TZ9d0WTjw/xp6D65i28pQOauCN7mYP46YT8bgeOJvug6tf0/Eho3sLYznBW5nO3nEUc9ZfMgZfIwV78hI1oZVEZFY3+ImAwaR9ZTcAvsR8cZ6kv/oWOdhtcUWQhJndxJt0xVRfItgMzetDdl5SqBHvXotW4jLFkXp8DF+30fPorh2tHtoDe3ZUHm07jV9VBD0dbyLtHxtp+e+S8MoDFUcDvI+fy9kGPwbZnl1ijM8iK3SyurlkeXRSikYM7NzBVwGwsmD9ST/nqkW4Yx5nWlxrzidtNpjsDY1Bh2n6onlfu6iwVf5RUhyx5Rz/NwCktJ+uZbdvyoSKxQ47uRCvn1zQNDlNGniw+Y53Pb6ZF0qqKaYHT8dYO72j9lHT7ds0bfM4kHu4DF+x2950r2+FALLrr0dSGxnHqSfC74vz7iT6/nxg4ROGVxNE5w7uzIgybSsWB72gyU0DaWyCsfr72K59jKfClv/6ExOUMf8MG8YHghoJ7R+PcDVNbSuX4OWGA/xcTQdqse2bgNxm3cgNA1H/z5o9mgSnwxOYAG+5BR+IkCzBmkEb0NnfAlFEhWrcc0/SwNGYj1JZ1K0xT3wRkJkfSdDnm2Bg3kKOjOpq7dkI1SVoZ+8gv1gScDljKvzqZjLGXK+3yVa66OwxrT+fwJ7GBgwqpyFH/ShqS6EBJaAP4x/lvvu1pfLS4jh3/9N5x52eMjCuXiP88hlGws4wV2RL4CYijI95SACohmIyIJ3WoG/Ll7Qdd7YLSV1DBhlYcE7/TpNZKcc30rC8dNwrFnglvbzzLOPrSiJqPNUjxU/cmjISKSp3WHhfh89xitfQttuL73TDaBjHq0BTxUET3Rox01H8oqm4WyKJkpU0RKfCIqCrbaajG0bsdXX4Yy2U9E/jz4/fktcSWhCeScP6FEt/DlqwvXAakipMHJaEQO7QIKvM2kExrULJ40gEjubuH8vgz5+CxEgOmLY1VYszOJbVjO2YyqBhOqyaOISD7+uoDOqBAZ+VSQWYNjkElZ83Z26yuCi2S0eUh+OuGzm/bk/B9S2Ipq2B9+4abfyBP3YzWy+1FeQkpgvv8OZ2x/H8MFA5x6knwOBHo7p59Sw8utYWhpMfgxucOIkhCRvoAtq2z/zJIjO4koi7X8Ut7uIgrZr6NY9jBLIzxdhLixC2qy0jhmBs39fdw6tqG9AaWxEi49H2oPcb03DsS4fXE7UzAyU2jqiVq5FNDejZqQjZk/pUADhmyag7D2A9dUPMK/eSEybjqsjbwD24lJMNbVIkwISon78KexzfltchAkVVQbyiAcP3QIkpKocd3I9U+bVkpDqPbz402EE3AN2JETW05PguV3D0wJdP4nrtnY5cQdLAl4FCWiJCbRkdeOy/NeRqm/lPBgqBPt+GMnmAV8ztNvR1Ur3aIS/58Fskcw8dw+fvRg83CcUaG1R3IV/j73o4J4PRwOesnC6Xd1Nf+bwGWsZ4yXtk/fZe+ycfRaaOXxS6Y/IdlAroL1TnT+P7OEoFRjvkj3OybiTClnxVc9ObEUyaKi+fyM9xzPfPnPCWMR//xfRFq3NTcSVHKQux+N4pCT2UDEpu7ZjcjrQEiyUt7SiRukTj8xxo2jdvh+pKGjJSdjTYgMXiCWmQ2ExxMVCTjbi24Woy5cjLWZc40aiDezjVfPgj7ymbdhM6sbt7iK1VnsMzSlpJBQWgBAYNCtn7fKwzjmf/mxkRETXyReKopEzoJZR04voN7zysCbA4RC0Dq11oUOhmy+C6ZQHg+JwkPvpuwEJLLTZ1gG9eaT5t6wonBBgKUFpQTw71qQzZMKhsPcfCJ1JJYBfIYkVAgaMqmDt9zlBWuJJbDEqb7xg46S5gtqtLnYXJQTcpgkX9/NHN4kVgFRVEh55mvzz5tGanAgceQLr+TJEEgb2fDjcBCTOyduftfD766PZtd3Upn8X3vYEbTNE4T+kHltXF1nFKGBubfEaiBJ27yN94RJwOMFkAqkR8+X3SCFw2qxoViu2unr9XghBTd/elI4fjSPB47pIScqW7WSs3YilsS2sJYzUPqF7e1QV3nifuisupGWK/rIaA59xPuY9BST/8xFQ1fYiNSmxbmvPAxJq5FVy5TLFo1o5UuhX9zcv7sEaJdGggwYj4Leq2NPzFEmLWU8C6+mF9fS0dNk7oGl0W7s86DMkAC0qinlRX1CjBnsfBNVlFqoOpLBFqTysXOBfO4I9Dz3zqhGKhgzSOERTBVUFUexaEwNDFF58Mipge1IXFtYzmkVMYzqL3J8nF+ym74Iv2XXS6REdezAiayBQfmxXKRVsKalj0twCFJNk5dc9UF1K2O1ZFROIGIc7lck6ZqabyNhT7DQXVWGKsCU1gNnR7ikztbaQ+8UHJB3Yh9ZG4oWmkb1kBarJjCsmGvMLr2N26PJYrXGxlI8aRuXgXLfqAYCprJyE9+djWrG+vXFAm4KIYjKBlNje/hTHwH7U3Ho9Mi4W8CFe5iwGfvURqfnez5u1qRFbG6HV86g9mr4QelypICXia+QNycgZRcw4Z2/oRUMgVBqBUQDnLTXWFLCpga+joDP2Nm3nFkxq8EJjBVgz+xb++uQtBLvqQkg2L83sEhLbWfzqSCzA8MklrPmue9BlmhtMPPIPE4/eG8XQQU7MJg1XgDZ6KmZ+YhKN2IlBf6B0MXlI2LKPPTNnd/UpdIDnS2B4zwwEGpR9Z4Adk8c1PlzQyMa1JrZuVLBYoKRI8NJ/bAEJrSIk44Y3IoT/0BC0ETq9zUtY56YJhaaUVEB/KeOLDtDz24XthSAehltIibWlFdnS2u69kZKEPQXEFhaz8fwraUnSjVjPpQvIWbPcK/gmZPs6xnal00nC869SWVRMfa8e3gcnJQPema8XqflRrOgsJNDbXIhZ03AFJAWhTfa8EVlYQzc56pCr5o/IhnqOfNtCGh6DcIsOIoG1qQFLa+g8q+WlA/iutFdY28zL6UsZlYeVC/x/GdGxLnLHlLNjTVoQIivZuCSW9Yvi+OxJBzVlwSdpZpx8yaleJFZISfr2TeyfOB1HXGT3KZB+rB5daU8VMojskfDGCgWOP20/o2ceZPfGVFqbzcQltvD1a7lB1XM0VTBynNZGsPWueGpiNtH92lRQYjo3XDcnJrv/zv3iQ3fxsuJjE8yqC3Odd796a30DOT8uQ9S6qDh+KKXLV2Otq6f/+59ganV420Rjgu9hry35e4j967/Zdc5ct0fWIF7Je3aSlt9xwhRq4hoKPShEIAmufhpkH0JiNkfYoCYIwkkjAP9NDfwR2MN1FISTjgFw25sntQ2Rga+jlIK66kjjrt7obEGXga7XGzkKkJzRzJR5+ixKCH8Po0Bq+o+mCjZutqKFMcF14J30o0iNtF3biHMWe/383DicfBIhYMQYlYuucnLupU4uu87ZRor8v8SaFFx+udPLA2tPsbt/AFzdssImsKBfx9Kho93/91qpV61GYswUqWFytNJ34VcARFdV0H3NspDbMb6XQOaytZgLG4iqqAJ0YyGrBNFV1ZF33QoDF11YFYTAGkfmH4pJMnq8KyICm5cW49WDGzoa0kAwjIxvK8QjpRwhA4gMujDxLucyk+/pzR7O5CME4XnB41JUnM1mDm3PZMfqNKpKg6cc/X90xLSz9xKb4EAovte8Xehca6v6rikPTQYFsoNdNZBUsLvTx+kvtaV593b382qQBc9n2Zjch/tOhEKUXWXIhEOMnlHEgFGVjJhaTOBqTUlskpPjJqluYr3DYUckpKEmZmMdM5OokWOQceEKz+ue0YbMdMxxulc1trSYpAN7I7JlhgXqtmEVVGjUW7JJXbkFxZfA4t9aCSmxl1eQuG4PpuJmmrR2L2nmprVoRyBRPTsvlvETmzEFVCsyag0CfCsVeg+uOuzjCIecGfbUk8D6SyPo6nRFf1d9L735PQ+RxzZ6so8lZXkBlvSEJDahFSmhtCCW7avS2Ls5GZfz5ytA+FV6YkEv8EpMb2blVz04dCC0lIQW9GZp9OQAidR0+MYkdH1MaBdn9m1B2hXwDfF1ptmBIYsUKmx28tw+fPKe/wFICMn786O5/IOZADQdLOX1j1N465MUyss0+ner44rpPTjbPB/F5QiZ1SmAkiEj0TIsxDmLES4XcQcOdmoOrUhJ0oF9ekHA1g1oQkGR4REcAdirqxj86bsANKRmsGfGKUTV1XTiSIJDAurQgUz8y3QuVxt59S17h3CjokgURZ8L+JOC0VTBlTcF7kXvCZOidPDEGojU6zR/Y7F3q8i21rNdDWe0ndaYWKyNDe5noZkoTuNTFnAiCq623MpwAoyS+BSVbcvtLPpoFprLxLq2b7oPqObky/JJTP3lqmuPJcQmOLjkT+tY/kVPNi/LxOUwEfAeuIsTA98fJ1bGsKbjF0KguFydOsaw8mMDFHoZEYrOemSDRTVGzyxk9bc5AYu+GqrNPPlONT0GNTNveDYb1wn++qrGjg1ZWM0u5pwcx41nXEvOm0+EVOuQioK0WWm59XooLNLbeuevDqtpiD9oQiFz01qaklJI3bUjom1IoOcKXftVNZspHTqagkkzsVdVoBwB58CuB5/k9hgXF86WaK2+Gq8h6j0UjbRujeT0rw24TDgI5VgKNFHybWpwJGptqvoMIHPbRq/PvuBUzuQjVEx+tWCDocfAGv5372gqimLdn9nsTibO3s/omUVB84kPxwFn4Ih4YgsKCrjqqqvo3bs30dHR9O3bl3vuuQeHI7xBt6swcFQFl/55HfNu2hzG0sGkvAVX8lKHR18qCnJwrrty055ip8+cqW7D2RnPbLDlh2TFu3/ChbGsQYKToi1Bf1xO+O7rwGLdUgoW/BjF55tiOViXxsjTh3HrP3qwamMMe4vj+X5dN85/8BTOHrIVJ2akT7jO8wprKUkUTR5P2ZSR7nyrzJHDcGHmC07lea7hE+bSGsBTEwjRNVVE1VYjwiSw/hBTWcbQD17D0lAfeuFIIQRNM8/gla/6Yo+WTJwoiYltvzIWi+T0c5289mkjyWm618CIKBjehd/f08KUEyIb5LeXN4al9RgIvoN6OLq6nYYQ7B8/zesp/BP3sZAZQHtxUHgBRkFKlpMf3k9Ac3l7eA/uTuCtB0bQUBvZM/ZL4WiwrTHxTk64YDe3PPYTWb1DDfbB7CpE0+glheReS0oaI2hD6wtj0Pf0yPqmvOhpBbpn80h6ZA3sXJseRLVAoJhg9ce6p/J3f2rh4tlxfPGhlfx8wZZtFh56IpbcDx5mUc+L/dpV4ypLRaF1zAiq/n4Xak62blcnjCUuNYV9og+vcDkvcwU7Ca7i4wlFatirKrA11EVsVz3P2ORykb1hFbmfv4/LZotERTAsaFYbT+/uxpPPOxg6oZHoRG97l5zZxOnXb2HcSXobayOiYNjXxNQWzrzp8DpzhZMHC/69sEeawIJOYl3W9mtfQiZn8SFOLBETWHu8g9Xf5VBZ7B0haG2ysPD9fqz4skeANdtxOKkEcIQ8sTt27EDTNJ577jn69evHli1buOaaa2hsbOThhx8+ErsMjjCS6nUESF5G0khsx881Ddd116ElZmMdoz9oRkWppyxKpES2z5ypeivPLoIvkQ320LSUxtBUF/yxUBTJsh8t3HOb4GCRycuLaHgNP9nYl3vPXc/fD16LWKZXlcr4eOTZp9E4KhdUDcvaTaQvWknGzj24enRDzU7h/u3n8Rg1Xm1vE6niQe7kGl4M63xViw1XVDRSKJ0msoanIS1/Ky6r1V3o0BX4Wp7E+S/+k7oGExYLaBJUl6DvABe//ZODUce5SEjUl/38pwa+mm9hwVdmmpsEuUNUzrnESZ/+kZ2Xpzf2SHQtirQVcDhoyGw33g3E8DzXBpDMCQZJv+HN7N7o//ikptDUYGX1dzlMP/vwCzmONI4m22oyS5wOE+El7PiHCwvNRBNFe/GRFIKWhCTquoUeAIMhkPSWpzfWMz+2Kz2y/vKuC7YmBV1HUwXbV9op3RzP96/oWs+eURhVFbS0wtyyV9h7VTqp772AqNUnEeqQATjmzkLrlYNSWIxlwU8kP/YMMjqKptEj2TnsFK5Y/QpbtB543o8T+I7XuJQsguuuSsBlteGyHX4KjpCSlH27KB00gpjK8ohSz9qTVjqiUYllbtJ3/PC7wW5yKjWBYtIYNeMgQyaUkZqt13MMGFlJ7tgyNi3JoqI4BpvdRe7ocgaMKsdsOXxqHU4agS885bSOqNqRolCflkFikU7kX+AaXJiREfs0JckZTRTtSQhYuLjs854Mn1qMPbZzUZVwcERI7Mknn8zJJ5/s/r9Pnz7s3LmTZ5999hchsUkZh1d0IlF4hSt4gLv0/9uKlqrPPp/CU84Dh34Dc61NXtIonhp/ncEOR9cSA8/0gkAYlBlaaFwCS9c3s3VjYIMmpeDJbwYxd/2XZDW7qCxqJb2bRnK6CevWbVjOOBtq69zFWzXlkqlrLmUbg/H13NSQzLW8gEB26M3ue1yuGDukQPnAwWRuObw2eOvkSD4pO53KtO6ML/+Bs/mAaPSwswsT33Ei++hNCpXM5gtiaWQvvVjLaCxWwVTn9yTJGvf2WrDxI1M4XfkctUn3djs9nD37dpu4716F658s5qxR2TQ2wBcfWlj4rZnWFsGgYTqB7dW38x7mI4FgXcsOBz02LnGHP9cz0mtiEw4URWK1q6Rku9i7RbpzNX0hNcHmpZnHBIk92mxrSmYTlSX2oIoFweDCzPucw7W8AIAmBNJsYcepZ9IVwr6+RNZTrcBohAAETS2IFIEUHnQvbPBzcrkk7z5rDtj1S9MEjU3wvwH/5oZNN1OwqQGzq47eeRasikT52wMob32INJkQqooE3ts7k2vev6at0Ml7mwuZxhQWs45RxHm0C/aHioGDccTFU5eVQ1xpUafrBOqJ5W3OZ1PRcaSYSjjH9S5D2Or+/gDd+Y4TcWFmHKsYyQacmFnENKpMafRR8xkt1nulipWLNC41v87CsuMAvJ5HTYU13/Ugp18dad10z2zp/lg2Lc2issROlN1F7pgy+o+sOGwCGyoP1rMdr6cX1rMr15GW67Q01pNYdMD9JPzA9Ig9sCAZc8JB1nyfQ7BnWpOCHavTGTW943t0uAVdBn62nNja2lqSk5NDL3gEkJLZTHafWkr2xYcldeIP5aS6+4K3Dsil8pobqL7gErfBUzWNHQ67XyJ7OOhqr1moVIQNBZtQzFkdwq6ekJrAjAmhyKBtUetqFU4cHU9tdZuUi5AcP83Bc5v/QV59g9sIaghmy8/YhvFA+9/mnTzApbzWocuPAQE0n38mplYHSrSDmm49SCgqjEgcHKCaRM7hfRZwAmaciErBM1zBLTzJm1yICwvX8RylZCHQkChE00gPCslngD6jdYBNcXCNeJ452qe8yDV8IebQLKN116ufc9Q0QekeXZ7ouYMV/O+uHjRUm9qEHgTrVpp4/Xkrd97bwkVXRR7qDJYbGwpGXrUntpc3BhQ4P1zEOYuxVddEPFAqikQoumc7Id3J9fcf4stXkkIWbrY2W1BVEaQY5OjFL2lbh08pYefa8DrE+YOCxibLSHCCZjJRPaAv+8ad4FYY6Qr488gaXQFBTysQCWluIuuJw2mE4OuNzepdT8G25IBjkBCS7N71FO1LDWpXpYT77xf88a4ebk9tSrLKXZN+5LZPP9K31aYQ8DUnczUvEihzUMXCHvryCldwC//xu4wmBI64BCr65WGrraFo9Hhyv/gwIhlFA+9wHlfzIk3YMde60ISJf3A3Z/Ihz3ADt/Af3uecNq+gvode7KWWBKpJcXdaGGDZzYOO29jGIN7gErbJwRAwWCYQQrLs8570G17Jog/6sOb77m65OCEkuzemkpzZyHm3bSI2oXNRt0jyYH2bGhhOgJ9Dbz6qtsbrvoV3DyWKqW28FzD2hELyjitjzffBVaAURdJ4hFO1fhYSu3v3bv7zn/+E9BS0trbS2toeVqqrO/ykXwMnXrSLtx4cgcupdNJroJBhqeasixz89m4X0T5OUoMgGBp/XeWd6opOMpFgRK8YKiaVsuHHbL/GVlEkad2dJGe6QmS76aitbt+GlIKlC62M5UtWMIGhbAHge05gVVvr1WCoIoVvmcUcvnAbUGl4axQF54mTsC9fyZBtuwBQTSakIhBaZOGq0/mEZUwE2gTa23hfHQmcxmdeYRfj72Zi2Emu17ZaNStPcRNPcXP7xoFQqgP5SxPIX2+nsVYP1Ro8zhiw/v2XaHr31TiUFLi1LwQIWbVNijw9TKF0Yg0PvgHf4i4DmRPGQhitI0PBSL+xZGUgS0oRmmQk67HTGNIbe/bFrSQmQ3NqOX1HNZISYyE+RQ054bJFu45JAvtL29YeA2sYMrGELcsM3eDIaI2KmaedN7C42xncc8lq+tV/ioVWurrMzpfI+hZ5+RLZw5Xe8tdIZNikElZ81QMZQLZISsGomUUUvxgf0q5WV3l7VSurTPzh0+ls53le5Br3N3/jb3735YuXudKLxEqAtihIa1ICNdm9Gfvyk27N2daYWGyNwT23viR3ATO4kLfavlNwYnXbxI85nR+ZQg1JHvZVX7uAPh22ne/oyxl8Eta5gX5tywrjWPFVdzfxMniAMc5Vl0Xz8TODueiu9REHASLJgzVgSBQ61uhqPHs/14vfjrTevGrxJpXTWchipgRM1VJwkdq9mT5DqoiOdZI7tpzYBAeNdRZCFcppmiDGz6SgKwq62o8vAtx1110IIYL+7Nixw2udoqIiTj75ZM455xyuueaaoNu///77SUhIcP907x6c5UeC9JxGLr5rPX2HVrWLhUaIFqeZt1+N4voL7Th/pjoKf0TkSGPKvL1k9KyngxSJ0IiO07j6H6X0H94SZmtF32UETcRwPc+6P/mQs1AIL2fmEBnUEcdC60l8N/YPVF5xC+q9f8P1739i+WYxph173MuaVDV0Fa/P/z8ylSVM8Rte0VDQMKHLb4f76kRmDaUGhwqt1FaYA5IuoUgeeCB0kd78jcV+w6HGZ56DcrjFgv4GciMkGwksjQ1kbF5H9roVJO3bpbcapZ3A9pkzFTlzgnsCEksj1/EcSoCmlyZcjB7Twt0POMg5uYD+Y3QCC+BK3Rh04ioUydBJgVvb/hw42mxruIOMEHDyJflu6a3OYmtROuc+MIct0Wd2ehuh4FnsZUTIPGW3PNEVhV4GoTGuZVySg9lX7kAoeEmUGX+Pmn6QASMryOlXG0Aa0r0GAQSteJmrWcQ0QC/YWcVxAZZth0ShFH0SsoVBfJV6PmsnX0PrOXOouu1GEAqZWzd4NU2whiCwxlF64m/8zR258oWGmUrSIghrh07N8IcNi7oRyPUiNYWSgniK90amTRwpgfXU2O5yAislCQf2kr1uBZmb1mKt7/geN6Wm05yQ5L4K1/ACFpwBpQo1zMw4dw+TzyhgzAlF7vc8Jt5J78FVfuT22qEoktyxZX6/64pUAojQE3v77bdz+eWXB12mT5/2WVNxcTHTp09n4sSJPP/88yG3/8c//pHbbrvN/X9dXV2XEtnU7Cbm3biVpgYzX7ycy/4goZ1A0KTCupWCzz+0MO+CdqNm3ZVPzIJvUazorfaGdpw9dhZdXSUbCtYojfNv38jmpZlsWJxNbWUUUXYX6UMO0HPcPjJ79UVKJzn9WineZw2YaxgYgmVMYicDGEg+9cSFHfB/b/jd3Lz9OVocZlgNtk2SS89v4dF3cjBL2emGBE7MfMSZ/J6HCD67PML6dwJcDhEwJw70dI69G+1oqt7lJxAMwmmQVs8JkfFduN26fDF/YzFzh2a6Iw/hQqgqvRd/S9amtXpc1PD2xMZxcOYkGnKy3ZJ1yi13oH30HWLvPoSqch9/YgMj3AoF7ZComElM0/hgXTEmk/f5JXaDvLGH2L4mvUORp1A0omNdjD0xPAHwI4WjybZG0sUNQCgw9sSDjJ55kIJtSXz4n2Fhr2tAw4SQGn94aQqfnz+fOGcx9ZZshMtFyt6dRNVU44qKprLvQJwxHYtsw4VnMwR/bWlDpRVECl+PbO6YcpLSm1nzfTf2bE5BUxWyetUxakZ7e9MxJxzkwM7gRWCBIfkv1zGdRdQTWlrSWCcx08ZwSzmbClOhAlgCuT1qeKjP48yu7qiTHa4VlIrCXq0Xj3AbS5kc8jiOpH1VTBoNtcGFtYWisW9rEt36hjeJC0VgDfwcBDa2pIjcrz4iqq7GXbfTVwjK8oaye8ZspLmN7gnB/gnTyP16PgBZlPIhZ3EGH+Pymhzo98NscqEEiFJNnrePwvxEVOm/K93E2fuPaFEXREhi09LSSEsLT1anqKiI6dOnM3r0aF555RWUMHI7bTYbNlsY6u2HCXusi2HHl1KwtXN5VwLJe6/pJFaprSHn5muJ//4bXfZECMyqiuyRg3LHdZB4BGWIjiAsVo1RM4oZNcPbcG8p0WfjQsBV/yzlid90o7bC1BbyFrT1dA1rH09wC0/yWwayM4zUBInJLPluU0+vl6W1VfDSaza2yU/4gRkB82WDoW7O2Zz21W9ZrE5qm40eYaIaBFKCy1yNJIS8kBRoWnASa8CXzPp6U8P1wvrqDYN3Xmw4CgV9F3xBxraN7Ve4bXC0NtbT+7NvaH70r2jgVudwffc9rrlnYN+0ARutdOeAH2+OvrUFX1tQkjOYe22VFwkbkhVP3hU7iU10sG5hNqpHvndOv1pOviz/sLyIXYGjzbaG6uLmD4oCvQdXk5TRRPWhaCKOQqBQUh3L7vjTGdjwMSm7ttHv+y+wtLagtSmN9F34NUUjx1Ewaaa+w06g3pINPoVezbu3Yx3TnlYAeBV5GeiMWoEnkQUY0gNmX7kz4PJ9h1UxcU4Byz7v5dPmN1htPu7vvuEktjKIXhQQRTMthFYU2FWW2OGznYUJnH7gbj5ltbvleriQAMnJzE+7ivN3/hM1rMjVkbO7QtHoN6yC/PXB87eF8NWVDYxwCGyHPFhHM1i7nsBGV5Yz9MPXUNpyod2TDilJ374Zk8PBjjnnuJevyB3CntZmev/4LULT6MtuOo7Aou24TXzw5FCuvncVMfHe42tG90bOv30jX782gIpi/zqxvujKVAI4QjqxRUVFTJs2jR49evDwww9TXl5OaWkppaXBZTx+TvQbUUlKdiNC+HOFh6JTCts2mdi2AXpddDZxC78HdMktd8u9omLsd9yHUl7RtQf+C2NIVrybIKRmufjjK4WcfkMl3fo6SEp30mdIc9jbepYbOZ1PuITXCG7A9PuhuhS/sz1NKvzEJN7h/EhOBakoqElJXBXzCkvl8W17+mWa2Bnhw+ln7yG5dyXBlMGEkGT3acUcYaq0kWbQGfgjM54DvFEk4wnfTnYp5dvJ9CSwHhBSfwJsb853E9gdDjvbLQns+vIH9s7/kjUDZvEmFwe+R1Lww3txfPrNTvcxG8dtMkmmnb2Xmx5ezhk3bOG0q7dx1d9Xcf7tm46pRgc/t22NdMARAiafvo/DISRPfT6C6H3F5H7xIea21sOK1NvRCKnRbd0Kei/5vtPbB500GEU0RmqBZzevYPqxncGp0wd1SC8IhuNP288Fv9/AgFEVxCe3kJTeRFpOeBrPtSQwhjWs5Dgu5bUQqVoSi0WfS/pGfqQUSAQ38kzAZkDBRsqVF9zDeXsfwInFQ9c5GI5MTrpQNOKSWpl+7h5s9uBODk1VyOodWhs8XAI7b3h2e/2Ao5ncWHlEcmC7r16KUDW/hbBCSlJ37yDmkHfKVMOgblQ8+Tcc553Gf2x/IFCKhpQCZ6uJTUuz/O47q3c9l/91LZf8cS1zrt7GWb/ZzI0PLmfMCYEbHXRVKgEcocKu7777jt27d7N7925ycnK8vpNHoENHZ2AySYZd8BPr3h5LbXESJrMuQOJyCSw4cWFCBtGk1DS4cl40G1qq6OcnT0+oGrKllZivFlB/6XmdPs7OVpMHgj8D6klQIh207HEaM8+rZeZ5ul6hlPC383tQVWomHP3IrziFj5nHI+L3/E4+hl5F5Y+kGL5a/9tUUHmOa8mihI85gybsDGELl/M/UtBbCHrKzkgEq+2TWXrNs3z0SEyY+b1HDnGZtfSdvIuoQaV0a7KQvyAXzeW/6YSUMO3s2sPepzEZ8adpGQ6MlAJfGOFaX3m5mPlfIBUlYJ6y0DRMazah1tayIzrLqwhNRvVmweg3UfODmyzVaSaxMYdePav9fm+LVuk/ojLkuR2t+Dlta6RpBQYGjq7ghAvzWfBuX9AUhAmEKlFleBPEJVu78fj+c3iarwJkfkL2hlUcHDPxsFILAC/pLQhfP7azk8EOXtkg711O/1qvzlHbVqXzxUsdJ4sdoeDAytl8wAaG8R0nsp8efoik/rw4g7QIlSgcoCcfczq76c928oilgbP4kKn82L5c23stzWZqXLF8O+VPvLDvOtQARWz+0fU22GxVGTqxlIlz9mOPczJyajErv+7h1xkihCQ2sZU+Q4Pbh87kwPojsF3WQlZVSc3fFrQ7pSYU0nduYV+GTkQNGx3dtxfVJ13NG19n4GoN/H5KCXs2pjDh1AP+j0FAZq8GMnuFzpXuagh5tLBKP6irqyMhIYFbHv8CW3RkGpHhYEtJHadMG8SGNWYoyCDObGHs4kdoWpfPtWEI65uEyhXyZV7g2oDLaPZoyp9/LKLjsqfYUQaMwhyfxA6HnU83l7J8xa6IthEI/l4834HKWKazubgrP03ki2cyCM8oaXRXivh27GX8t8+feHPpJCoKozq1XwsOnFgx4wAEGgpmXLworuHMoZtpGnsc9vVr+aFlIreX/YVdFYeT6uFLqDuRzyUkA8bVc/mfKolLbDdA1c1Odq6M4e1/6CTFyDk2KuyHz6xl3u0lnY2meiEp2tIh9O4PnobbeC7mDs30Ms6+ngXfJh/ZS5aTsmUHSoiJmTrrROotdppGjab2vIspdqRy6XlmineFJ7Q++sKVzJj683hXW5sbefLW2dTW1hIfH/lE4JeCYVsf/HI90TGBcycjTSnwxLo9zSS1jqbogIlEUcPDH53KyXxLId0J9a4INAroRQ/8K3BIYO/0kykZ3nkdbvCecBnpMNH98lATs91pBUZ+rK+yx+GqxhjvXbjX1+UU/Peu8TQ3WAjX1jyT9nt6nRjNQ9U3s+ib9LBD5b4w4UIiUNqKf1xYOJ6lfMpc4u+8lqZVa3FUNnFH/T28WTgTRxCJxiMOoXc4PPOmLfQYWOOl/epyCt5/chgH8xMMeRt9FUXDYtU473cbAxIxTwfP0UJgAUwtzUz4b3B1EikETUkpNCel4Iq209Avi4xrz+Ol5dO464HutDog1DOVltPA5XevPaxjjUQbtrmxnjtOHRnStv5sOrFHK4SAXkOamXtBC3mpCub+T9FKGY9zK9vJC+qNVaWJN7iY57k2cBlQc8fB1LMVoj9kThiLPX8dtIVVNSmZML5/p42mJxn1R0wnjO/vd3l/MkrhYM5gEGUOPv/ARmhyp1Codaf8lflckSApvkvw0VvSq1NNeJA4aatG92hT60BwmfwfGWcuYupNufyw2Mq8c1M4fAe39/FlZGnExsOenZ7Pi79zb89rm3myi/ufgq93tVLtkYUxb3g26lCNM46v540XbCz82oLDIRg4WOWCK1uZdZpEUTp6QCPFp5tLqW52uu9/IELbGQLr+zdAfWI3UrXgsnMSUL79jgQg4YtPSLz/QWanFnGoPLyJjRCS+Mw6tpS0dJp8/X94o7Oe+lF9o9lSsoILzxxE1jefMoidPMCdXMjbIddV0HiX8/gD/gdnqSiYW8JPXQqEoNJbeBd6GR7Zw+3mZSASryyA2SI5+zebeefR4ThbQ3dKM5kl7039C2ddV8mM8mYWfd3pQ0VF35+nDNMKxnN63Pf85+beqJrgpotiWb3F1LVRLaGR0aOBmjI7rc2edCWwbbXaVOZeu43egztGY8wWybm/3cTmnzJZ/2M2NWXRWKNU8saVMXrmQRJSWjusA5Hlv3qOm7nWpg45sF0toaVabbgsVsxBJJOElNirKrBX6emNmVvW8791Q/ndgUvD2odQNLL7dG0ua1fh/zyJ9YRYsgTlQCHRwEJmMJTNlIUosGkhmhai3J2cPCEBR2xMB9Ia8iFevtpdoZ1rbeKMYVluwtEZdJaMer2IEeL9Z5r4ap6Nm25PoKQ0tMEdEtOE3Sr58au4ThBYgmxfQREqD3yay/hxC7j11rloGp1ueuEPr7/u4qxZZSgK7NpjYu0GKy6X5INPovn6u2iUtoRPTRPExcGZZ2qcelEjAwfr19c3JG9c99OGN3DaU4HDM4anKBCCqQbscNjd+zUpintQNoy05+AKwQmskVMY6rkuyx1Kr6ULgur2+t6V913z2FcaHoFSTJKhExs58/Q+HTQ6/z86h86mFPhi/OdvoSkKF2jvsIc+3M2/gi6voFFBauDvNY2WhM5W8HsjlGIB0CG1oCuJLBD285rZq4Gr/7GaVd/msHZBcOUeTZPsL6ngy4XbKVzbI5Lurj7w74hQMbO0fhTPfFhAXYWFlUsTu2S7AAidNJ1x/TZi4p24nIIDO5JobjRTX2Nj9bfdaWm0gNDc3tS0nEZGTi1i0PgyLNbA453JLBkxtYQRU0PL6nXa+4p/Hdgj1Ub20JCRZG9YFbQ5jOeV1hDcc+AGwo0gSk1hxNTI1Tk80dUFXQb+P4n1gNiyxd3mMp1yLud/PMLtQbXrkqkkKog0tys6GkeTndaExIiPx7FmgbvIZe7QzA6VsoGIqWcXMc/fnSGj0F7wEGnzhhOS4fHrcv5fe+cdH0Wd///nzLb03hNSCL33olJUVAQb9t7rWX965+k19cr3Tk/v9Lyi19SzcociNhRsgApIh9ADhIT03rfO5/fHZje7ydZkUyDzfDyiZHbKZzYz73nN+/MuXPXUmd73LSvMHV+Fdt/nmAGj6boejdHXzWgTGr7cnsFXG2M4VBLbw/17J0w0oWuyf0djEiEnx/49XfkwFF4VzZotmZgtMrPmRzH//OigwgAcBtAVRxKVnyZUXv9u+hlnO68FKdb+cHZcX46pUteHqz8BWxFggwNreATHTz+LvA2fBxx88V+uQsbmtRC3A0kWJKRaufLhGuf4VSE7eEg6ctAZRnIff+FJnsSGd/FnRUuOVOw110dIErLV6izTFgq6tqbt2gxhbLJ7eIFDtISiIU0wXtmoODNnXnGU4oPxVJdGeq0GIxSZOXNbyEqPwRwRQYH/EjBe8P79yhrBse9jKTui91kWMNj9ImRMbTpnNrxWJxg+sc758cxFJyjcnUhDVTiGcCsjp9Z0y5zvDYGIVxgEAraDEzNOI7FwP/qWZmQXIevNzm5nGsXk+N2vJNlLZ515RSEpASYW+iKUCV0OhqyI7fpWoJFlym0aslwugFv5N8/wY6/7kDWC68dvQdrt+WKRgIjqGqa89Q/2XHETbUmBt2c8+tE6N2/sAXOER9HqyKJ14PAWuH7u6pHzJIqAgDqMufZ1DpQRikRu3BhKGlOwie5CxKbIXJ3zDkc/KmD4BQuYmFPNpn3J2ILqqibQyAKbHwO6d6PnosuekBAd9t6/UY6q2EJ7Yee+HZ7Jio1bkIGb53XG21m3BzwEJ46penAkSzn+ToG/VLiOyVFtVB41DS0wRu8uZh1e//hwXUAC1h/xxw6TuW0TsaXH7WOJS0BrMqJvt4/Jl6Ddyzj/AlYSLLyuhjkX1ROT0LmuKmRDR0+/Q0c1k1sMYRha7VnfcTRyBStYweX2jnge0GsVrtKtRBglz94lIRj5+UdEVZZx5KwlvRayrt5Y8OCR9dDVq6tXFnoXJ+ttFgS6i1pJgjmLi/nwn55FgSQrpA5rIXOEPTEsOas14NKHnfh/1RRCcLiwntpjSQELWHvZMMe63jyxgvAo76JUoxWMnhb6yj+BilcITMC2VVZRsWV/nwhYbVsrmTs2k1qwA317GxZDGMa4BMIb6pz3jLe/yGFGBHAEQUJaG2dfXUjOmIZejbWvvLAwhEWsK62NGl57Sc+hbTeQJulYJlZyLmsYzSF+yO95lh9120aSBGFhIF+wgINL/8DI5x5DMnePSZGEQGs2MXr1exyfuxB9WyumqGgacvIRGs8PZ1eDqmkowxaX0U2sOnAIVMfUsut6orEa0djm5pFziJnu2AWR6+feBEqwN+TvL32Lh969mdLGRGRJQRESsiQQAh468xMmj6ijmQyOfrSOizNb+LbgnoD3LWNjbEox+6p8vVUK4iNaiA+wvXxMWBuZ0VUsHbWRv2xeRrvVWzymICmikeRj73L0ePcXDOf3FEAMtCuevnfX2D1f2/rah4OjH61zxl2b6UhkoXPKtKuQhc6QB08C1tf1MGzzenI2rnPOcACEN9qLp7dHxxLW7L3KwivczHHyvH7uIDZe8MLTBt7frVDfrrgJiVBNhw9levodCgElh2LZuyGbayLfY3b9p9wq/kU6FfyGn7KGc2gktotH1i6cZk1tY9fZT3Pae78k7FBht307Hs7pe7bTmpRqt6WSRGNmNsa4AG90Dzi8sdAzIdvb8ALwn3zrELRjZlbTUHOUDe/nOZM+Jdle5zQxrY1l9xY4tX3WyEbiU9toqAoPKpRKH2bFbPQuE4QiMXqUhYPNVlprPBe871gTWSOIijUzbHQDOoONXesyvIc4CBg3uzLgcfaWnohXcA/Vc3UYecsTCBX65kYmL38FfWuL067qTEa0ZhNWnQGN1QyK4rHOTzthPMbvAjiKxNSFpb0WsA76wgsLQ1jEOvrBb1kbxZu/S0axSciyAYnb+Dt3MZmdfMpinuFRMinltzzeLT7WaIQXfhvG33X3scL8GefzmcdjSUIQWVvNuI/+53y3tYRHcGTBedSMmeB1jI6yL/oZnm8Cxw2jaShzTi13jZMMNBTAm7gNxQ2YFtPI6zf+mfWFY1l/ZCxmq5a8xCoumriVtJhOEdOsy+Cc/G1cNe8gyzeMdk5leEOWbEQZTDyyaDV3Lb8Ti81znTtZElw6+XvGp58gLaaeiqY4j+uBICasnffv+D06jf0bbZESeembc72MQOL207+i3eA7ycrXd+gqTNPmzvQpDD3ux4dY9XbcrvF/DlzLCnnqUGQ30p3Xiet4PRFVXkrORrshd/WmOcWsDwFrQ+Zn/JpAvEENdTK/+Wsz489w94Sp4nXgMLZqee8vEyg9EossK5SIHD4Wc3mSJ3iBB/kBf2Mzc3iAP7GaxbiW1ZMlwcYd0Zy95QYuCE9jORcR4SVkSwAjvlrt9nvd8FEcPudCrOH+m2+40tUbCwMnZLviLXZ2zvkljJ5eze4N6dRWRKA32Bg1vZoRk2rdGqFIElx4+37eeW4yFrPcpQ2z53ts1rklIMGWNcO82GGBzqAwdmYVWp3C8f2+Xx4WXnbUWfy+vUXL4e1JtLXourWElmSF2EQTY2cFPnPWE4IRrg68eV+7CthA8wR6ysjPP3ITsA7sTjP7veLNar7FNQGFEoBg25eZTFlQ3quJjr70wkIfNTs4WagtSuT136Rgs0oIIWGzSViFXdfvZTyL+RRF1vKg5s/sYyzxhlZnUXohJBSbfbt2s8wlrGI/Y/we03EtaNvbGPPpShIP9+5B6xCproW6veHdC9v36DQ2zh5dwFNL/sdvL3qbO0//wk3AOmjRZ/Djic/yhzu+ZnRmZwxUbkojkV1ieqdmFfHSVX9nZEoFj5+zEgm7sO1EIEkK49JOcM30b5Elwf3zVzs/c8duyO85Y41TwAJcO/0bbpv7BVrZioRAI9sAgV5j4cGFH7N0/I7efC006zLcero7lgW7vaefYPDUP763pO/egiL5qD3oZXkpGSxmNWVkElDkrCTY9lGCRwHr2vBApecsOXNcUA+j918aR9kx+/euKDJCyChosKLjXv7K+/LF5GmO8wlLeTTCtQShhCIkrFb73/2T9rO4h795PY6nEK6EY4eZ8N4bSNaetbvs+mLmsJvthfvRNJShaSjrmOWyN0UYmxyJTVGwKYpT3PRVq3BPDRPiU4wsuOwYl967lwtuP8CoqbUeO/mlZrdw40+3MfG0CrQ6u43Th1mISTTiejeGRVpYcNkR5l96jLlLiknOanE+9xxIsoIkw5Jb9qMPUxgzo5rUnCYk2UOxfVkhPqWdiad3NuQIj7JyzQ93kZDW3rGOcG6bmt3C1Y/sRG8IfY101x9HA4qeCFjH33tsciRj9G3dBGywYXfBENZQR/zxo16TuDy7cuy8ws3cx599rOG+p/rKSEoLe59H0ldeWBjCnliAoxtGdEQ+dn/QWtGxiyl8tvA3TJ9YzV91D1D/bAQei8+jQUHhTzzA3/hBQMd2xNjnrV9L7YixfmO6XNshOn7vikOI+Ev4GezIkuDaBQe5dsFBjGYNGlmg0yqUfLOdTTWzaLfoyUmoISO2s4TKOWP2kBTVzBtb5rHl+AgEEgkRLVw6+Xuunv4tBq39gTZ/xAF+uXQ5z3+1lLq2zvqYMWHt3HPGGi6Y4B60Kklw8+x1LJv0PV8fHk9dWxQp0Y0sHLGPSIPnciw9oS+D/gcEIYguL/VZgNvTFV9OGrPZTDlBlBATEiUH7S1Vg629qRJ6yo9FU3LIe+UACYWfRz/LyHlhHJ06j7/86S6v6ypoeIMb+A0/I4vuLSw97l8IoqorST60l6pxk4MauydvLHT1yI51hnl58sr2pUcWehfrHZ9i5LwbDnPudYexWGR0egVJgsYaA7UVkej0NtLzmpy1VfVhNq754U6+XzOMnesyaG/RgyQYPr6O2eeXkJlvF9MareDKh3bz2X9Gc2hnklv8bc6YBpbccgB9mPuTKT61nVt+sZUTh2PtQkkSZI9pID23OVS5et1evHoqplzzAjx5XzUNZc7Zzp44I4Ihsqpn3fl+y2P8hN8STHafJAkqi6Pcmm4EQ197YWEIi1irRaLmSDK+3ki0WsH7Ix4h89Fm1l4b1ak8Pe0PHe9yWcAilo4jhzU3EV1+guYM7+VSHAbTgeuNE8j6JzNh+k7Dp9PYmJJ13Ou6U7OKmJpVhMmqxWzVEmkw2ctbdeHMkfuYl3+AbcXDqWqJISGilVk5hW4e2K7Ehrdz8aStvTuZQYrjwdxrhCD5wB4yd2wmsqqSnqRCP8UTVJIaYJvKThSsqoDtYxziyd/3W7grEVlWULwkZwpkChpHsOq231FbrqW10fffWkHmE5ZwJ/8IeKxCkkjZtytoEQsd4sMlNtaBLyEL7mW4XCsXQO8bI3Slt0mLkoybpzM2yURskueXcn2YwhkXHef0C45jatei1dvcGgg4CIuwcfHd+2isNVByKA4EZOY3EZ/qvZ6vJMGwUY0MG9X7DoQQOtHqiltiK53i1RFa5Zos3VdxsIbGejK3byJl/260HnJv/HGCzI7wLAimKY8QoNH2ziPel15YGMIi1ualpacrQkBFvQ2NLFNabQbhO8bKSM86Tenbgi9d4W/6ty+mhweSYKZnDFqr0/PqDa2sMDu3e8LIUMD1Id01LrYrAU+LCsGItR+Stm+XPYmrQ8D6imjt+pkRA69xo9eMdW/IssKYabWqeB0kWMyagJ6Ta74uZFKu/5cnGSVo2yoJgb61dyWBKrwIWTt2r1t4R5K3t1a1rl5ZCK2Y7e/qG5IMYZH+QzRiE03Ezh2YpCwIrWjyJmDB3fvqGqoXagEbWVXOxBWvI1vMzvJZwfaHfJWbnTY5WPIm1PlfyQP94YWFIRwTqw+zERVrwpe3SBEwcozdO5c+wois8b6ujJXJ7OrRWEzRgRsg0Vh9ygnUQDnlptwHOQ5vUiAkHdpL2j779e+WxIXnO0x0+T9ANckYCS4Zx7EHR8KISt8SSGxscmars1WyN/RhVgzRJvaWFniMo3RFQcMkdrstE/j28wtJwhjT81g+f7bGNU4W3HMSHBViHNPOyyZnuMXKdv3pDa4xsq4/QwHXcw02vtUfjr/NsskZnZVZXGJfPQnYQOtlB4UQjPn4XTcBC74FrKd74xh5QYtYSRKMnlHttYtZIPS1FxaGsCdWkmDqmaVsWJXnxRoKdFq48EozIDFzaQObP/CefamgJZJW1nAOi/gc2VFntOMp7jm3E9rjE2lJSQ/BGamoDBwZO7a4ldFypauQdU08EJKEEAJkmRipFWyB+Bg6aiBK9lrNF96xj+TM3hfiVgkNo2dU8eV/8zEbPXfqk2TB5HnlTB4WRUF5E1Pmt7BrQ5RH4SuhEE0zm5jNWPaTSlXHct8iVhKCyglTe30unryxDjyFF4A9J8G19jLg9Mp2JZRdvxwEUmf2ZMKbKO8rgeS1fSzdq/30dbJ0bEkR4Y3d2+e60tnIvPP/SoctFloNCIi2NXe0Dva/J3tVIJlhoxtYfMPBHo27P1+khqyIBZix6AQF22NpKEnoqFdnvww0GoGiwMsv24hPsD9UU3LMXHJPDe//LclZk8+Oo6iw4AvO4jMWM5mdfML5ZFBB1eQJJO8s6Ob+tx9O4siZ54es44yKykARVV3ut+Whx27nQtBkiGd57o/40rgQjuNlzU5yx9V3JKA0M/H0CiKi+yYTXMUz/mJj9QaFpbce4P2XxgHCrYSSJAmSM1s47QJ7bPuE9BhM0zcSd+BMGqq03QrmCyRaieSn/B8/59c8z0P8QH4Ja3oqFouF8OrabtedkCQas3KozR/dq/P0luTlSlchC7jFynYNL+hKX4Qb+Ksz25XBJHD7W7C64q36QNccFE8Ctq+qEURVlXt1Djjw9ELn8Npun3g9r7Zcxv9K5yLafE28C2KT2knObCM8ysLYWVVkj27okTRx9Y73B0NaxGp1gpk3bMJQNYev34uhuVaHJAlmnWHllz+XmD9fsN+lCMDZVzeSmmPh87fjOLIr3GVPEgIJK3rAXp7rPOlzNt3zLO2HjtGclkFkdRUaW2c8UVtiMkcXnkfjMA/F3IVAsnS0VFRROQlQZA2yzXddDE/2cB0LWWZaSePBWBeD6T2KNjbJyBUP7unFSFX6gxGTa7nu0Z1sWp3Nkd2JCCERHmVmyoIyZp1bgj6sM1nEEG1i6g1fIp2YxbcfxtDeoqHzRUZytv1W0HAffyElS8OSB2KRPt2A9bvv0ba1O68YRaOhYvxUiuYvwlN/Z8lqBUny2mjGE768seAuZIGAvLKuuCaB9WVFA294Erh9LWx9eer6S/w4CKT2q2v4AHgWsH0R7iY0moDyY7taTBN6buQ1/rvj6g6nm/99LLq6kOETfXt9/dHfAhaGuIgF0OgUzr2+gRmXVnNufgY6HWj1irNkSleDM2FuGxPmtvH3n6Syd1OkxykwKzoKxHjWvm1FWx/JP/grhxhFArVcx1tcnPoF5pHD0JpMSDab06CG1deStfU7Ug4UINusKG/+D8uSM+FHD8EpUm1A5dRDNptpSs8ivuSYT49BVw4zgiV8ghk9IAXwziZhtQzZMP5BRSCVCtLzmln2g73YrPa/m95gw1PZYEfjGUZ/w7TYaL59aSHeXmRkSfBr00+Y+8Op/JO7+IA/YMLAbDZxl/YfZE4QmOIS0Lc0d3buEoLUvTvJ2LGZyFq7KGnIzKF0xlzq80b6PE/XTnn+hCzgUcx68sqCZzHbV0lgvvAXjhCMoA10Grm/haonunbeAvfWsV27XUL38IG+LqfVmpDUo4Ss+3mRFVwB4DJr7AuJthZ90MdxZSAELKgi1okkwdqjZR1TCb7XVWywd2Okn17RCpfVv9rR993uVZBQ2MhpPFtZxFeVZzKWYixh4RxedAGmmFgm/u8/yFaLcypAbm1D/+5q2LgD22efQJduXCoqA4rZQsY3m0jYewiN1f5ACCZr9k88gBVtxz2icqqi0Qo0Wt9eeodQ+m5bTpdwLXcUIbG7Mo1hOKb57esdYhSvWG/j/3Y+xmM8jQTU5I/m8DkXMXzdZ6Tsd08Miy0rJm7VcY7OP4eyaXN8ji2QsAIHXcVsVyHr6pX1FGLQ1SsL/SdmHbiKEE/xtYFuO5jprfcV+lbAxpw4Tt76tURXlQe9bTlp/Jtbg7argXhrvTFQAhZUEQvYb9QlZ45zezNzTP0A3dpv2qySHwEL9pQE2flvsNdHBChhGJfxLluYidbYztiP/oc5MhqN1dK9jZyiIMor0f70F9j+u6JnJ6iiEgTeZiHcsNqIe/bP6Pcf6laNwB8FjOd1buCf3B5UOS1ZVhg2siHg9VX6nlCXd7KYZSQEwu+V5P654zr6Cb9jCrs4n09JPHqIiOX/JqK+tvvWHdds3vq11Ofm057g20HgrXasN4IpxeXA9X7zJGYd9KeoPVlEqT+6foeuSXZdva/gvXxWV/pCwMYWH2XCyrcJts52O2Es5yr+xW0BJHF1x9G4IlgGUsCCKmKdU1kOIbtyV5kzsFsjy27Fql1jh8Ji0jE2heH9se3dCFvRsY0ZbGQup7ERARham72uL9lsyB9+jK2qCgzBR1q3F+4POouyT8qFqAxqNA1l2MCtMxy4Z+k6CPt+G4Z9wWWuWtFwNy/xL25HiwVrsA0NFFktpTWIcIQUhJKkjFavTRICQYOV53iE8/kUSQgi6mt9J8ZIEmm7t3Ns4Xk9PqYvfDVIGJvceZ95E7RdKxoMpIf2ZMRTyIAD1+97oKoPdEMIRnzxsT0vJggRu5lZLOUjaklCJjiXqiQrZI9ucLYA7gkD+bKjBpjhHvMTH65j5a4yrwLW0Yt92PCWXh1Tg5WvOBMIsIuxzYZ04ECvjqmiEirCv9yACDJ19af8mn9zK+DwnAW2vSzbjfKZVxSSMdz7y57KwBDKcjqjptXQk05vDmxoWccCtzrEPjO7hSAqiDaePclC91VTtrPbV6TzB3Bmx3d9efRUc1alO67fjet35vq9Or5vVwHbXrh/4AQsEFNWQnhjQ1ACtox0zmEt9cRjnwH2XNquOwIke7Lsklt6pi0GQ03iIe+JdcXhjQW8ClgHiemtHN6Z1ONjBTZl1oWwnnUEO9noOnWneoUHH5qqmqCSuBqJ4U886AypCZTwKDM5Y+uZdmZZj6e7VPqOUHtjtTqF4HoRdcfVrgZScVjRBvYYDCY2tivdKxjYl7u2rQX7LIhDyAJeE8FcvYp91dr2ZCNQr6vj+3X93gMNH+hrDE0NQW/zV35AGxFBtOoWaLSC+NQ2Jp5WwcTTKzCE+45Z98VAh5yoIrYDZ4Ysno1B17gvb32mA8WKjnlscP7uLyFGJCWhDM/q1TFVVLzhWucyEIRWG1QS1+fSORhFuP8VcRTbljjjomPMXVoc8JhUBo5QxcZKEkTEmGlr6lmmtAYrp/FdZzMNx359bNPberKB4i3py0EgghZ8l+hyMNQEbddELQcni3h1oGiCk2RCknhXXOYsQ+cPSVaIjLFw/WPbiY4392SITgaDFxbUcAI3JqTHdPMqeCsjM3p6dYfXIHg0WBhPAfNZD9hrwYnEeJ8TCMrpc0GnG7ItZ1X6jmCNt/aLb9FUVftdT8gyouOBWzgysIQYgNTsZi66a68qYE8SQu2JmXxGOZLUs5ACG1r+H390/i7R0RXOw7qi47P6vBEB779Zl9Hrwvau4QWu2e+ahjLnD7iHG0BnyIGnMAMYeqEGrq17Xc8dcPuOHN+b6/epaSjDvPWLQSVgNSYT2ZvX+26n7PjR2O2qLS6exoTsgPavM9iYurCMG36yLWQCdqC9sKB6YnuMIdzG/EuP8eXyEXT3o3rzUdkvwRSqWckyu4HVaCAinPZ7byLil897PZ78wUdIuwsg23vrW0+c7EldfdUJZajjKdu6vXA/+hkOb1AENkVxS+oSjdXQ0EDY8/8EvHu3Gonms9grqDrtPDTh5dguGEO9GAe3+R/XjT/ZSmqO2kL2ZCRU3tjpZ59g7+YUmusNbt2+7PiyrRKP838s433nktoJY9E0thNXUtRtC8dehn/9GfsvuiqoMfqrG+sPT15ZV5zNEly8s46ES4dH0bWCjr9Qg66cLJ5aX0LcUxvfYDyvMDjEq4PsjV8TUVvto9ULbGcau8dcTPS4XMYs0KBcdA4x1yhUfi+8V0ySFEZOruGiO/cjh7Ca4WAQsKCK2F4x/axS9AYbG97PpbXJ4FxuiLBiatMhSQpCdHY0jjCYecjwJx5u+h2J1CEkCWX+GYhH70X30j/tHWY8vGEDoJHR/PPfiF/+0G2xa2HtQOmtAe4v+rqQ9FDHVcg6YvYc2dOOMlsOxiZHIg4cQX/O+UhWz/FTNmR+zq/4I/8PY2M4rLYvH1Zg5PrHq8kebaTksMFjDVBJUsgc0aQK2JOUUMbGhkdZue7HO1nz5kiO7E6EDhuq0VkRiozi4fKbFrePZ5of4mzb5wAosdG0nn8O4vRZxD3wuPcaMkKQcPQQhsYGTLFxAY0v0AYIgdC9FJdvMetaOcRVzPpqoOAJT+J2oIWtN8Hq7RwcdPVKexOvELqqA6F2rqTv2EzGzu+9Xqc7mczNvMoupsAB4ACErRbM+b6WmRfUc3BTtPedC5npZ5eFTMAOljACB6qI7SUTT69g/JwKyo7GYmzTEpfcTmJ6G6VHovnu41xqSyOxKApjp9uYe0U1YcMvoC5sHvX1dWRPGYuINtinkHbuQ/ImYAHJakP++mts/NDj557e5l3fOB04br7BLmR7k0ShEhyu14KrN9ZRyxJA1JShu+xqqPQeRnAvf+Hv3NkteevEYQPP3JmJVue5iL0kK2jDLCy+MbiSXSqnLlGxZi79wV6a6gxUn4hEoxVk5DciFImtn2dyYEsqLS0y+kgTi682M+YsLdstvyZH+zCKBDmzxsGu9ejWbPSbgCgBMWXFVAcoYiH09slT61pXXNvYuuIaN+tLzHbFV+ku6F9B6yshyxvehCv4Fq8QOu9rqJwrSQcLyF+3xuvnBxjNPDbQjntOgbFd4us3E4lNinVZ2jlT4cgtmHlOCcNGNYZkrIMpjMCBKmJDgKyBrJGdF0lrk47P3x5F9YkokBQQMrs3CHZ+HcUtPzBh/JkJRSiQHAmOG86HgHWiuBvj7m+V3Q2gpxvWlwEebNP3qhe2b+nqVXL1xjoYmxyJ9J/lyIcLve7nAKN5mbs9fiaEhM0CNreWsR1d7GSFYdOKOf+yCmISepcsqTKwBNKKNlhiEkxu18Wu9els/DgXJHs7TXObgRV/gpg347npt8W8nR3LRRPTQNeGPGoamk07AjtQkOXiIPgGCP7w1rrWla45Ea6itmvdWec2fgQtdA9B6I9atL0Vr/6EK/SNeA1puJ0QZG9c5zNJ9imewEiYl+QticYardvvDuJT25i7pJixs6pCMtTBKGBBFbF9wqqXx1FTFmH/RdgNiGKzX1yv/NVAVo7CZde7PLAbGpHrGnxeyAKgpRVa2yAywrnc9cbs+jbvC18GeLAIx8EyjlMdVyE7/IIFHV59+wNybHIyorEazYcfI2TZ62zBG1yPBquPLNmuV3ZHFztFZuF5taqAVfFL8cE41rw5yv6LsxCs/Tpqqdfwn59k88C/j/DBngqYmMaYGMAY2L71LT2vPxzqWS13sdVpyz2FjHmLnfXknXVuE6CX1iFm+0LIeqsm4AlvwhX6z+vqINROnvD6GiIa6rx+3koEK7jcT2dDD6pBUohLNjJudmgErIPBJmBBFbEhp6IoitLCOB9rCP71ZwPLru18aMt/+ze0tfssAyMBorUV6b2PYHgO0hfrMVRVIlLTMJ4+G9EhbB03baS1Fc3+IxjaLFhGj0CJi/V4AzqWpc2dOei8sCr9g2y1EL2nmMxdm9H/9d8QHoa4ZAm2B/8fTLV7d6SGWp/hLifI7FGrQ0lW2LUhnXOvO9zj8asMLkLditbB959lIcmKh2QvUBS7R+r45jhGzKvn/d3lXJapY/xzLwa078xtG6kePYHkgwWE19di0xuoGTmW5vQsNy+tZLMRe6IIXXsbpqgYmjKzibaW91l4ViDeWfAvZl1x9dKCd1HrqXRXKPElYIMNF4C+Fa+uBONciaosI2PbJhKPHkSyKbQlpVA2ZRZV4yaBJKEx+64gUUdCUK25nQiZowUJNNfrT6lKBJ5QRWyIObo3AUn2HPtnR6KsROKHd0Ry5JBMtCGJi49M4m6xjiz8t9SUf/8iUrsRodGgA3SKjei336Px7psxzZ6O1NhEzD9ex7BzDxIQjr3UUf3I4cjzT6MxMse5L8fN6PDCuS5TGRrIFjMT3n2D6Ar7tScBtLXD8vfRv78a65o1iNF5MCIP8c1mJJvnpK4G4vA+j+AdocjUlkf4X1HlpMARUhBqISsUKNqX4JIo6wmFr1fEsn5lLE0NMh9rjvBT21Iu5ANkPx2Q9O1tzPz3n+zH6hCtmTs205CVw/4Lr8RmCCNl3y5yN3yOvr1TIBmjYzly1vnU540EF4dAqPEkZh24ilpfiWAOugrbrqLWuS8vrW9DhacyYQ48iW9v4hX6p01ssGEEiYf2MWb1ewgkZGE/18jqSkat/YC44iMcWrwMY2wcQpKRhOfvIp46/FeR94KQaKgO75WIHewCFlQRG3IUq2wPqPZz0X21RtshdDXs5xH+yH18whIWdNSO9YQEiHb7/JirmBAWC7F//if1ERHEvPa2vZuS63aKQvyhI2hazOy57AZ7FQQXVOE6dMneuI7oyrLuk/02G8JoRHvllZi3bcR66ZXo//Wm1/3U0LPudZIkMERYe7StyuAk1F28AITAj4AFkCg+aHD+u0EaxSXifZbxLsu5Gh2+rzNHAphrIlhsaTFjPn6XmtHjGbn2w25S2NDcyLgPlrP34mtoyM23L3SZ0Qq1oO0q0rx5aB1x7a7Cz0FXYetJMIJ3cRsqvB3XFV/CFfpPvEJwz0ltWyujP30fhHB7gXJULE4+uJfGYXlUTphKS0oqUZXlHhVDARPoTQc7fXjPbKtrBYLBLGBBFbFuFJQ39foPlpbbjGLzH0jv6qm1ocWIxAV8RDHZxNPgdTtPl7OjoHf0G/9FU1ntMRtXEoLY0mISjx6idsSYAM5E5VRHtlpI27Pda/a2pChQVoa8fhOaXz6FkCSP6wqgNTwZ2oMfgxASY6b7b5ygcnIR6iQvWQPJmS1Ul0U642A90/mZIuzhLe+zjN/wU57kqaCPKwlBfPFRostPePSHSYAQgrz1a9iRczdIkscZrr6qBOMrftZbYxxvDUYDFbfB4klI25e3uR3T23rezmOwCliA1L07kYTiU35m7NiMJTyC6Mpyj58LoLaHzgEQxCYaSckM/kXkZPC+uqKK2BAzfGItUfFGWhsMXjwHnqcGFDS0EMkr3MzDPB/0cSVFQVvq+WZwPXLq7m32Nos9yMZVObUIa6xHa/E91SR0OuQVK5D3+vCsSRL5cbXsNvkouO3hupdkhfhkI6OmqSL2VCWUYQXTzy7l0/+M8rGG52tPIPMCD/AYvyWM4KdWFSSf94kERNbVEFVRSkt6Z2vw/hSzEHz8rCvevLahwFeXSVuA64HnkpGDUcACRFeV4yuCRQIia6vJ3uS9MoEE5HEs6GM7tj7j4iKkIHqynmzi1YEqYkOMLMMld+3jv3+chMUiuyQhBNLFW+aHPMcm5vIYv2ManeVhAtna/2QbJBQfZea/XqBsyizKps62dwxTGZIogVS/VhSkwkKEVotk7T411UY4/xVXQnk5vv0OdiS5o/uXIpOS1cql9xag1fWsxajK4CbUYQUT5lZw/EAc+79PddbABDrKGEr4soANJDCcYzzCc9zHnzF0iNnAog1FQOtNXv4KtfmjKZk1j9bUdOfyrmK2r+tz+4qfdcVTLK0ngm2oE0h1nM4xBL59f3bX6m2OiCJrEBL46p4sgKjqSq+f72IS73EZieGN1LbH4L1Tnd0nJcl2J4JGFiy84khQlQlOVgELqojtE9Lzmrnp59vY9kUm+75PxWzUEJtkpKEqHD91txHIrGQZK1nGh1zIYj5DRISjTJ6EvHkLO5RJPMsjrORSTBgYz17u50Vu4RU0He+1/oytvqWZ3G++JK74KPsuvkYVskMUY1wCxpg4DE0N3Zomg/06kmw2mmPiifaQhPE+F3Mj/6GZaLRY8CYJJFmQO9bIgssaWf9FMykxevIm1JGZ36ROCJzihDKsQJJh6S0HyBtfx/avMqkqiUKjVYhPbqe6NMqvbS0njUd5hk84n09YigEzyohc5OJSzGaJl7mLv3AvhYwgklauYjmP8ByjORhQVKIEJBw9RMKxw+y7+GoacvLdPncKoi5VYPon1MCdrgLXX6Mc+768J5R5Xt833kT2QLWC7Vqdpze5IvV5I0g5WNBtucNCKpJEW3oKUWXdRWwzUVzN23zCBWiwItq7bt2BZM+8Off6g7S36Glv0RGTaGTsrCrCIwOPhT2ZBSyAJIS/W3/gaGpqIjY2lgee/xhDeGjic/zRNS42lHFd7zw3iZLDsc7asb6QUIgOs/Dl77/DOnEGOQlNbJ5yH5cr/wVwlt2QsCGQuZhV/I/L0XmNeOqOAI4tOJeyqbN7dD4qA4fGaCSmvARJCJpT07FE+mg76EJYQx0ZO7eQWLgf2WIv76IzGRHAO1zNH3mIbcxAg41FfMG9Yz9h2tIY0v7wO7cSW99yGgtYh4LcrUOXq7HVGRROW9rERXfVoQ8TIS+GP9CY2lv500NLaWxsJCbm5Dkvh2195pMdhAd47fQUhze2r/7uJwpjePv3UwNeX0Lhgcv3M+9sMyMmZZL9f7dz8cc/5BvOAHBez1osaLHwGYuZx4aObf0jAGtYON/f/hBC69tP5Np0ZqA6KEYkeq4O4k8EB7puoGMYCPHaTbhq04msqsDQ3IglIrJbiTWvKArJh/aSvmsr4XU1CEBrNiEJQQnDeI5HeI2baCSODEq5g79z508U0v/wLJKxs5ixABbzKV9wtoea2+4iNmVYMwsuO0ru2Iaenv6gFrDtrc08umSqX9uqemL7kZnnnKDkUHxA6wpkmowGZtx/JgAaTRRCvItdRsgu69m9qB9wEX/jBzzAi0EV5EjfuUUVsScRktVK3oa1pBXsQO6oUCEkiZqRYzmycDHRlWXEHT+KJARN6VnUjhjjfJDGFh9j/Kp3QLEhd7y7io6fH/BXXuIeZGwoaFDQsIZzWL3/fB5dXMFkUUQFqaRTzsWs4lf8vGN7Ty9k9qvvmh9VMe2sFsIiBu17sko/0Fdltxxk5jeRnNVCTVmExxqyXRFIvLBiHC+ssF+ncTEraUTqdi1b0aEgcxnvcoIsDJgDsq0SoDO2k3jkIDWjx/tct7/jZj3hKh4DFZOhFpwDESoA7t7WmBPHmfrlS0TW1TiXGaNiKJq/iKaMbFL277aL2/AIqsZMxBifCNhnq8Z++F8Sigrdrg8B7GU881lPE9HYOhxPZWTyK+kJ3lpu4/dnRHD8iwokobCAdRgJYw3neRm5PT4hPaeJJbccJCGtB5m0LgxmARsMqojtR/In1XHaBUV891Gusx2tbzpvCZvNcWt4N6Ev8CD382KXLb0jAeGN9faWtx4KXmvb20jdt8uemStJNGQPp3r0BBS93s+eVfoEIRj74X+JLz7qViVAEoKkQ/tILDyArCgoHX/LjF1bsOgNtCcmE1FbjcZsb7DhVn4NWMklvMQ9gD3B0IHDE/DMH1OBN50duaJoooVofF1hskZQVaJTBawK0DdltxxIElxyz17eeXYyzQ2GjniYwLMHGppkr+sraKghmfe4lGt4J+AxKbJMRG0V4EHECkFMaTEpB/aga2vFFB1L5fjJtKZ0xNEOkJiFgZvK72v8hQrEnDjOhPfeQOrS2t3Q0sSYT97ruKQkZ4WW7M0baE5OQ2syom9tdjoUul5FV7HcTcA6UITM4SMSlxx5HKnDNSWQyaIEDZZu6zsREuVFMUTF9a6BgYOTXcCCKmL7ndMvPE7O2Ho+X5VG9aF0P2t7btXpCYHMUfJpIYoouY32eXPRVlaiO3jEawklsBtbx3SJxmwi8fABDC2N6NpaSS3Y2XFz2iVx0uH95H77JXuXXUtLqlpbtr+JLyok4fgRj59JYH8ZAWSXaX+d2YS2/ITPR/qL3B9Qy1jH5y0E5k0ztrm/GJ1qoQQqwdNX3ti4JCM3/2Ire75NZ9PqbIytWgKfj/K9ng4zW5nBNbyDBBw6eymjvvjY9x6FQNF2CpHIynLiio8iW63EFxUSU1mG0lHkXkgyGbu2UDFhKoVnLekWOztQYQanCoEkaQ1f9xmSEM46rg7cXEdCuD1Lo6orfF4533Ea+zy9xHTZu+sMwAmyvK3stp3ZJKMPCzx0sCuhKCc6WFBF7ACQNaKJmx9p4qUnImiu8JZ12DN0WEAIlJRE2qZMIO5Aodd1hSTRlJcNkkTa7m3krV+LbLW41QPtHJn9d63JyPj33mTbLfdhDQsP2bhV/JNasNOnhz3Y5Q62MsOHgO0ZQoGUYb5bKqoMLfo6rCAswsbMc06QkNbGe3+eGLL9CiT0HdUMFFmmatxksnZsJryuxvs9JwS1+aPRtTYz9qMVxHTMZiE62+A4ujg5ujWlFuzAFB1Dyez5QPdEMFXMBoe3sIGuRNRU+awS4A1/dnUb053hWaHbK+jDrIRH9bxBjGsjg1MBVcR64JOv9vXp9BdAU50BxeJ9GitYNFiZx3rCMHVEh89DkxiHePlVJKOp2/qO90nbjVczbMN6cr5c5/zMl+dWEgKtyUTq3p2UTp8bkrGrBEZYQ10IX3c6MWCiOaR7FCAJmiK28clXndNeqhdWpa/tqhBQXxlur23kt8NXYFjRsZSPEUDDyOFEK5U0Dc8kwiV20m0MQF3eSEyxcUx58x+ENdQBvu0q2J8Emds2cWL6aW4JYf1d1eBkpWvIAARWYUDfElrr58CAyW/nzmCRZMHkeeVoND0L0zpV4mBdUUVsFyakx1BQ3tSnGbXGNg1v/34KbQ2eYkt71ifZhpYf8wwCMF9+JZ/qbmXtLw9hMf6VmWzhOt4kpotUEVGR6KeMZNif/x7kUQUJRw6qIraPkS1mYkqLka1WwpoaiKwNvO5fMFzEKl7hVi9JWsFiv5LGL93NtBFhQFgI9qlyqtFX3tgdX2Xw1f88FB/toV3VYmEqOziNb0Grperm/8d/d82idMc+4qnhWt5mJlvdtpGA+tx8kg7uI6K+NrjjmU3ElJ+gcVhut89cBZlrIhgMHUHrSag6CKYkVkRNFeENtQgBWVu/DcXQurGYT0O8R0F8Shtzlhzv0danooAFVcR6pK89Rrs2ZNBc762jlz9DazfG9mkKGRkbAolreYtIWtg3YjFLtr1J8QotWqYD03mVm/kRv+d/XMH5HTeWBEjNLUR8sxO5ui6o8UuA7KHwvQN9SxNpu7eRdHg/GouFluQ0yifPoCFnuNopzAuSzUbi4X2ENTbQlphEVFUFmTs2o7F0TskH++6tIFFELla05FKEGT1vcS3rmY+E4Ey+4mre4SFe4N/cGqoz4eyrDjHtrIYQ7U/lVKOvwgosZpkNq/K8fCoRSMsYR2y44/+pVHAr/6KWJF5a9hlP/GQqMgJJTAbgeR7mQj7gHa4moqPvsgDSd2/DHBnltVWzLySbl1hHIUg4eoj03duIqK3GptdTPXo8FROnn9KCtrf1W8Praog/eghkmbaEZHI2fuXW6rUnPs0GYiknnQTqSKWKHUzhNW6igjQyKONmXmUSe5jPOtZxZg+O0BVBXHI71z66k7CI4GNhT1UBC6qIHRD2bkz1U5jbm7EVSDLcMfxd6gpt7GYix8jHgp43uYE3uQFNkaAjxMpZSxaglXAu4CPGsp8wjJzJV9yl+SfmrSaamUUuRaQSmKdPQcIUHUP6ju8RGg31ufmYYuIAiC4/wfj33kRjtTiNt661mcRjhyibNJ2jZ56vCllXhCDnmy/I3L7JWfYKPPuNAv3WBPB37uRpfswxhgMQTRMWdJgwIHdkw77B9TzK03zCUk5jI99xWhBH8c6oacF5n1SGHn0RVnBsbzxmo69HmqPDV/dQA0kS5GRUsqTifxTYJlDAROpIopRh3MPL3Cv9DeV/9pkKm/013rntRyxlJIdJooZMSrmZVzm79nMKrKOIE9FMoAAN3ZuFeEIAEXXVRNTV0B4XT33uCHvlGEVh1GerSDlYgCJJTluRvWk9GTu+Z8/lN9CWlHrSemh9eVihZ40HDPW1THj/bcIa693KXnUlGIt3lDx+ym9YweXO52sq5VSSjhZLh2NJ4Y88zG38k6d5lDn4PrdAkCRB9uiGoJoYODiVBSyoInZAaGvW4a8EjDbMjNWos5eGkwRCkdGFWZh4yU5Kxuip+jCVQ9u6twG0Wb3tV4OCYC8TANjBVJ61/RC+kjqOqHAhH/AHHiGfoz7HLyNIOnKQxCOHcJiF6tHjObrwPMa9/zYai9nt7BwGN2P3NlpSM6kaP9nn/ocSI9Z8QNr+3d2W91RKCknibvE3/s5dztItAM3E4JDGNpcHcAMJnCN9ztPxP+e7utN7eNSOMUuCjPzGkJV/UTn1CaU3tr3FS1miLoSFWzG26ZBlBSEkhJDIn1zD0lsKsTZOYsdvptNqcg+DUYSMt5AEgYYyMigjkwLGs5olSCiIxo5Sd5TyGL/jPv7s8752pNLmrV8LHR5cU2QUhYsuJLyumuSODlByl/J6WmM741a9w9Zb7j8pQg56GrsaDPqmRqb/5yUk4d4Mu8d2FTjIKGbzPa1EuiXCVpIGdDqNHIlc/+ZWIsNaGGsrYL9lHPQiXEsImbGzgg8nO9UFLKgidkCITTLS3qrzmnggyQq5o5s466pCDu9IwmzUkpDaxogpNWh1gtamRD7dMaMHR+48nv1Gc/X8yXzMBXzDPL5nllPIupptBftt6FjmWo4k+eBeEo4VojV3TyLrPAbkblhL1diJHuvSDjXCa6tJ9SBge0qRnMf1+uV8a7Q/rLrHuHa/3mxoaBLRfHjxE0w81MKe7yI9XJddH96eHub2a+GMi4p6fgIqQ4pQhxXEJHq3Pa5c8f920VwXRnVpJFqdwohJtc7C8d+syqfFEuGziYdn7J8pHY9U1+3LyOABXuQ4OTzLjzxu3Tn31vGvDqGqb21h3Kq37aLWx5HDmpvI2LGZMpc8BV+CNhB6K3q9HS/UgtUTYz9c7qz+0FsU4E8Rj/Djtl9j9hjj7/kvI5D5q3I/l967h4MvglBElxDCrjOunmdgJUkwbHQDw0Y1BjXuoSBgQRWxA8LkeeVUFHlv9SgUmUnzyolNNDFjUWm3zw9uTfYSTxss7vuwoaWRGH7M06zgCuct5Sj0bI6MwtDa4jHGSwKfAtaxjt7Yzsg1H3B48SUhGH8AdBQWTyvYQVhDHZaISKrHTKA2fwxC0730iWSzEVN6HK3JRHt8Am1Jqb06fER1JRk7vyfh2GEkRaEpfRhlU2fSmD2ckWtWhSx3tZQMZuu3U22K7dH2uzZEMuHqtbSIMZRszcNqtn83sqwwdnYV0xaWYjZpiIgys+ubDLZ/lQFIzlmC8Egri286SPbo4AytytAmlEI2Z0w9UbEmWhr1eBIWkiRIzmohLbuVtOxWRk7pHvayZ2NaQF2/gsM+luf4ITfzKhPY67SpkhCYw8LRGds92gJHJK+/uFoB5H77JQ25+bQlpnT7PFjhGIjo1RhNJOw/RPTxEiRFoS0thdrxYzDHdv4dXY8b1lBHZE0V8ZpWGjNzetU0R7JaSd23i7SC7RgaG7CGh1M1djLlk6YjWa09KpnlCQH8n/xzft72yx5tbzVrsFo1XP3ILr54ZwSVxZ3P/bjkds64uIjoePtzUyjwyatjaKoNR5IFCBBCYsSUGpbcfCCoKLyhImBBFbEDwrjZlez5No3yYzHdxagkyJ9Yy/Dx3pOtWpv0yLJAsYVKAnViQ8f7XEINiSTRaeSN0VHoWtuDTlLwROqBPZTOmNtrgegXRWHUmg9IObAHRZKRhYIAEo8ewqrT056QRFPGMMonTccYl0D6ri1kb1qPztjZzq85NZ3Cs5d2dtPpgr2uruxRECcd2svo1SsRSE6vQHxRIYnHDlE883Siqip6fYoOn+gvs/5KbXlsD19uJNqaZGSt4PKbSjFfVU7F8RgUm0RKdjMRXWoSnn3VEWYvLubwziTM7VriU9rJn1SLRqt251IJnlAJWVmGc647zMq/jUfC3eslSQJJFiy6xnvdbMUG5va+eyRqsfAvbuMPPOwsnq9IEsbYeHRGI95SjAK5ox3NTrK/+5oDF17Z67H6E73R5ScYs/J/aMxm6CgkFVleSfKOPRhj4mhPSKJ6zARaRqSgb2thxOcfEV98zLm9TaujdNpsiucs8DwrpyjIViuKTtcth0I2m5nw3htEV9gdPBL2+uXZm9aRtnsrNSPGhMw5UK7L5knbk73ah9Uik5nfxI0/3U5NWQTNdQbCoy2kZrd0E6Z3/vp7ig7EU1UShVanMHxCLfEpxqCON5QELKgidkDQ6gRXPLibde8NZ8+3adisdgGkM1iZuqCMMy4uQvLhDIiKN6EofZccZUNLsZRDkugUsYam5pAZBkWSSdm3m6L554Roj+5ojO3o21pI2beb5AN7AJfC4o51LGaiK8uIqionY8dm6vJGkXjsULd9RVVVMOm/r7Hr6ltpS+rwcAhBasEOMnZsdvbZbszM5sSM06jPGwmAvrmRUZ++D0IguzycHOPI3tL7si6OvZb87Ne8/oeLXFoTB7+ndrPZKSD0YQrZoxt8bhEVa2HqgnKf66ioBIrjgdvbrm4jJtdy+f17+GpFPrVlkc7labnNnHnFETLzvRd6lzUQFmnB2BpYbG2wWNFylOHd8gWiK8tCsn8J+wu6xtiOrS8a0QhBWGM9GmM741e+1ZH74BKfi90mhTc1ENbUQEJRIcPiN6A1GdG2u7ez1VgtDPv+G/QtzRSee5FzeVh9LVlbviXlYAGyzYbFEEblhKmcmHEa1vAIAHK/+YLoyrLusa5CoGtrI+VAQQ8LqrmcKmAels1zl21F/Kl3T76w8E4nQFJGG0kZ3lv7SjLkjasnb1x9j4411AQsqCJ2wNCHKZxzbSHzlx2jqiQKSYKU7Gb0Bv9xPGOmV/Pl8hFBeGKDv6VjhftN5JzWCmovnpEQ6FsDLzCtb25E196GOTIaS2SU1/XC6mvJ+e4rkgoPBFRYHDqn6TwJWMfnks1KzrdfUjTvbGSLlcxt35F8yD2zOqashPGr3uHYvEWUTp9L2p7tHW0MPeOILw6Grt+/JT2Dd+/5BbvHnkl7W2/+MhKyrHpRVQYe16oFPRWzeePryR23lZqySNqadETHm5wxr/6YdHo5Wz4fhugDJ4EGG2F0H4dr8a/eIgmBrr0tIBErWa1E1NcgJJm2hCTveQpCkL57K5lbvyOs2S6SvD0LpC7/D++ok+tt3bR9u6gaOwmbwYC+uYkxn76PZLU6X/Z1JiOZ2zeRdHgfu666FUWrJW3vDq/2XRYKssnYq+9TyDL1l1zOSzc8yrevaEAW0IvrwWrtn/yPoShgQRWxA44h3BZ0wHZ4lJV5lxxj3bv5fTQqmMc3/Ijf8yAvOD2JXW9jKxo+ZTGHGUkcDVzEByTiv+asECApCkkH92KKjqU5PdNj2a2Y0mJyv/2CmLIT9u2A+uzhNGdkYWhuQkgyDTl51A0fTVhjPZOX/xvZbO5RyIMvgS4LQcKxwyQeO+x1e8cx8zZ8jikyivTd23yOw54gJzn/Gwi2UXmIW28DvYHi9BG8HTMSodGQqtWg0QoflSn8IYiP73kfbhWVUBKK8AJJguTMVsgMbrsZ55xg35YUWhv1AcbGBv5qb0PL/7iSNiJ5lh8yGs8vzgDHyWY152PCwDS2cwbfBHQUAUSXlRBZW01jZrbTe+mKZLWSvWkd6bu3OfMYzBGRVI8aj5BldMZ2TNExVI6bjCk2nuFffUrG7q1uwjBQSxNI1fOJ777ultrUrbSgEBiamxj+5Wqs4eHI3uro+tiHr89tEZFsWXQJVfljUTRaiqbMoTkplXXfHqSuORJhi/NzFr7R6UOTYOaLgvKmISdeHUhChCDI0Qcmk4nZs2eza9cuduzYwZQpUwLetqmpidjYWB54/mMM4ZH+Nxhi7FyXzlf/y8dqCaQ3sz0mrNMwB3arj2Uv49nHSA5zG/9iOEdBklgtFnMb/6KCdGfjBT1mHuYP/JqfBVwXEaA9LoHCs86nMXu4c1nc8aOMf/9t+7i71E8FeykpsAtMm0YDSMg2a5+0ZQ2GYAy9TatBY7XRSjhlZBJNM2lUOvdTH5bES8MfY4txHkpMDLMWx5GcbuA/K6M4fMxGTLKV+Re0MGleK28+ncK2L6J6GCctOOvKI0w/u3sSoYpvTO2t/OmhpTQ2NhIT079tdUNhW5/5ZAfhkd6TTAeSvuya6IumOgOf/mckx/cn+l5RUjCE2TA542gDb6igw8JCviKZGi7gIy7hffRYaCaSO/kHy7mqYy8CBQ1j2cc7XM0k9njdb9cjK7JM5bjJHFtwnj22FHvi6vj33yL2xHGPL9kCEJKM1OEJteoN6Pwk7PaGYGb3/H+znetZoiLRtrRSRibthDOMEntL9o7P11z7PG8Xn8XeqkiknBhyZpioPxbBlnX2vSfm1bBoSS0C+OfPZvf4DMIiLdzz9Ea0ur6RWaey97W9tZlHl0z1a1v73BP76KOPkpGRwa5du/r6UEOOKQvKqa8OZ9sXWX6nvy75QQGHtydTtD8eoYAhwkpDVYRL0wXPpfX3M54DjEFG8Dse4wmeZH7WYS4qeR1HBT5HXTwzBp7mx1jQeS0lA91v+7CGOiasfIujFy2mJSujIyFrJXSp8ec6SlcDLNtsAy5eHVjR8h9u4CXu5jCjiKGR63mT+/gzGbh0idHIVExfxJOtP+aNgjkYsU//zeVbnuQpovOiuaD6Ter2GZAlUAR8sBPshYMFCB3VJYLCrVEMn9DOFQ/WsHtDJGYTHq4F4Yyx7vqZJCmER1sZP7f3SWYq/cupblv7qrOXP2ISTCz7wT6ev3+ez/UkCYZPqCNzRBO7N6TT3KDH0FGD1h5X61l22dBiQ8OnnI8GK69zI3kc5dPwi7nX9iJfmc9wluhy7OEQo1jAOnYwlVyOdxuLpyPJikLa3p2EN9ZTsOw6kGWSD+whtqTIZ7kuyaU0VV8KWMfxAuUgo3mBB1nJMszomcp2HuBFLuKDbvGx/132D36/fAq7zfZa6jE0cjv/4Cfy77h3zrcsf2s0skag2EAqhC1r3QPmmitj+dem4Vxw+34mzy9l1/oMD6N1rd/j+UxmLy7uEwHrEK9wagrYYOhTEbt69WrWrFnDu+++y+rVq/vyUEOWrBGNbF07zMcagsgYM/kT6hg52X2qv6VRx2u/mtHRfMHXHjQ4JnCe5JfkyyaErPEonAUyz/MQj/Ac6VR0+cyOJ2EqgNzdBbTddTWa7QXoW70Hv3clFAI2FIkAa1nELbxCGZn27GhkGonjGR7lJe5mHQuYiL1geZUtidOL3uNETTiuEnyzNJfzxGdEVAhMJns1XqWrDezIunZ8/0f3Gnjjz4LpN3zDrvem0loT7TwjWSM4/cImpp/dzD9/lk5LowZJVjq2l4mON3PZ/Xt61MpQZeAYKrbVVchC/3lldXqFpIwWaso91U22IxSJYaMamTy/nKkLy1yWwzcf5rDpk1wfR7Dv09ZRIL+IHM7gG6rNnkvk2dDSQhTP8Qgv8oCPPXZZJgRxJUXEFxVSP3wU6bu3Edoo3L6nlgR+zNO8wi0IJKfAX8dCvmQRd/M3/soP7Gel0fCHvBf44evXIEmd59hELC9ID/OPmAdo/q6jKYHNYUcda3V+g0Kxp6x9+M+x3PzzregMCtu/zESxdVZKj0s2svimA+zdmMaeb9ORZMUZICYUmHVeCTPPORHy7+NU9r72hD4TsZWVldxxxx28//77RER0j8vxhMlkwmTqfPNravKeSapiJ39iLdEJRloaDJ69sRJMO6sU2UPEQVSspWMqLDj5duS4wefnNjTcx4v8m9uIpfNv6DhKM1G8zTXsZTyRtLKMlcwUW9EcKyH8442ItNQe9RzvKdUkUUEaKVSRShWtRPBPbucf3EEpmaRQya28wl28TBzd45dbiGQZ7/E55+IwcK6Rrvb6u7GcxnecwTcM5yhFE8/lxL7wbhUFHJ2B2trtAjYghEzZniwuvv4Ep/16O6VHYqgpjUSrVzAlHccQZeZgLZx2/y4q9qZTX5JAYqSO7DENjJxc4/HaUBm8DDXb6lq5oD+9sjMWneDT/4zx+JkkCfRhNsbO6l6PVJLtibv28K3A7mGBhur2WHvdZS+i2YqOl7iL63iTOWz2uM5WpvMel9JKJOPYxzW8TTTNjPjiEw6ERRDWUOdWUaAvsaLhMCMQSIygED1WtjCD53mQNZyHQGI+63iIF5jPBo/7WMVFXMU7mJxNBtztKsBL3MNG5jCcY0xLLOKJoz8A6PY92oRMc4O/bpmu2CXprg0ZnH3VEeYsLuZoQQJmk4bEtDaGjWpEkmDYyCZmnlvCvk2ptDXriYozMWFuBbFJofViq+LVM30SEyuEYMmSJZx++un87Gc/o6ioiLy8PL9xW08++SRPPfVUt+VqTKxvqkoiWf6HyZjatc4b12EMR0yp5uI793kVKn/54VzamntedNozHRn/1LKWc5jKTucnK7iMm3iNdsLRYkUgYUXHItaygsuJkZoRqanIFaGd3vbkBd7NRB7nt6zmfOfb/UK+pIRhHCW/Yzu5478KORxnA/PIxL0kzpUs510udXbr8YckKQjhL2kkeN/wRXftZfS0mqC2Uekd/R0TG2rbOphjYj3Rn3GyQsDaN0eya0MGkqw48wkkWUGjEVz+wB6vSbm7NqSx5o1RBHcPBxr1CXfxN/7Kvc6k20ZiuIL/sZZz0WJBQmBFSzjtvMrNXM4KJMDS0VghVAhcOzjasSHze37E8zzkbMmaRDWn8y0fcBEabM4WrVosWNHxDD/iRzzrtu9dTGIGW7GiwXctF0fisXBxHoQuwCw+tY3bfxlct7NQ4Ro2AENLwAYaExtU7YfHHnsMSZJ8/hw4cIAXX3yR5uZmHn/88aAG/fjjj9PY2Oj8KSkpCWr7oUrKsFZueXIrc5YUE5fcTniUmcwRjVx4+z4uvsu7gAUYN6fSOb0cOuwmrYE4zuMzWrF7i9Yzj6tYTjvhCGQs6J3G7CvOZBkrEULwVeV4nuBJnuIXfM2CXvsNOsN+Ow3bNqYxh018xnluLSK/ZiFHGIG9uqtjuYSChhKGcSP/cdtvIXms4PKABSwQgIC1HzNoTp4ZQpUuqLY1MBwP8a4P975AkuzNEy69dw85YxqIiDYTk2Bkxtml3PLkVp9VZUZOrUHWBHtDBn7Pv8zdvMCDgL1c36W8x5ecBdCRNqZHINNOOFfzDuuZTzVJvGS8lZ/ya/7CD6glIcjxuaNgT7CVXFriCuB6Xucn/J9TwALUkMwqLkYgO22+Y6wAj/J7vuU053IB/JH/1/GbP3tpf97Y7XXosyP6aULQSUF5k/MH7Ne840elO0F5Yqurq6mt7d6qz5Xhw4dz5ZVX8uGHHyK5iAabzYZGo+G6667jtddeC+h4anWCvqepzsCrv5yO2aTtk9qIILiLl1jI17zI/WxmjnMayBO5HKWI4WixAHYjN4E9rOJihnOMXUzib9zDZmYRjpGLWcVt/Mutu5j9qNjrHgqBiAxH6tJtbDpb2cVkn2Pxxn7GMJJDKLKGJ9Oe5rdlD+G513pvCNITKwnu+r/NxCT0bSKGijuh8sQOlG092Tyxrji8stD/FQwCYd27eXy/Zhh9IaxAkEgtf+Qh6kjkIV7wuqaMlVyKKCYHBbnDE6pFi5WneILH+B3thPMW1/IW11BLEmPZz538nTP5ym30rr5iS5gBndHd3qxmMUsIPkZbi4XLeJd3uMbu3R09moSj22i0DOxzX5IVJp5WwXk3eC+vGCrUZC13AvXE9kk4QXFxsVvMVVlZGeeddx4rVqxg9uzZZGVlBbQfVcT2D1UnIln10ngaqsM7ps0CjccMRGgFV0TFkRDlihYLaVRwB3/nCX7lnIJyTPNH08wazmUW9ikfIUmY8kdSd831JI3NQX/tTW7728UkptDzjO5XuJlL4j7mjbue4t0j57HuveF99AIQOJn5jVz76M4BHcNQpL/DCUJtW09mEetgsIpZRYH1K4ez9fNMhLB7K+1P274RtT3d75P8gte5kSPkI6Eg0Dht7I28xivcgoxwCljL4oVY50xF/+HnaHbsRVI6Z/IuYSUfsdSZsBYMGZRyQhpG7fU3U/qrp5k9JgmTMdTfVeAhG471b/zZNlKHtYZ4HJ2o4tUzA1piKzs72+33qCh7l6X8/PyAjaxK/5GS1crtv/ye4wfiqSiKprI4kkM7UvxsJcjMb6T0SJyf9YIzQp48mlZ0nCCLJ/iV83fHvhU0NBPF+XzCMfKIpoXKvNHUffgplphYTGtWk9dlf4cZGdSYuvLdokvZf9mNCFlDiqkl5AJWkgSJ6a3UlEW5xeJ5R/RBSIjKYES1rd1xffAPJkEry7DwsqPMPKeEQ9uTaWvWsvXzLMxGH8m0kkJ6bgvVJyIDrP/de34lPWGPnVAkREe5RIeNfZ0bmEABP9T8ERQF6wvPIa65yh6luny1m4AF2M/YHglYAGKi2P/5bpRh2WiA5Lx2Sg+Gh86+SgJJEkREW2hr1ge4XwlbH3bcUpO1eo/asUsFsGfU5o6rJ7ejZ/O/n4yktjwCT8ZWkhVGTK7lkrv38eqvplFdGuW1DE1o8extUNBSRyIvp/6IGdfLbJp/Adbj7UA716Sld1s/joZejeGNTYsJ22MlIbWNpjpDkN7r7vsDkDUCIexlr0ZOqWHJrQc4cSiW79cOo/hAXMe63qs7niiMQ1G8d45UURkKdK1kAAMvZiNjLM4SXGk5zbz3l0neVxYy515/iJZ6Pe/+2cd63ei5/bUJjdd4eoHEc/KPuPGyKhpuux3jhIlgtn+Wl5ZF9MHDSEpneb546uhRU21JUGOJYvbiMSRlmdBoBfXlgQpNzyMHyV72SgLFJmMIt3LhbftJy21m2xdZ7FiXjrHVd1KzJCscK0ggIy/wNumBoHpfQ0e/iNjc3Fz6uDGYSoi55O69vPH0VExt7l4DSRLEJJhYdI09Rmj2eSV89K9Q3IT+psP8G7M/JN7O1OhtLImzT4/Wt1t4rjAHY+TrFLVmEE89V/FfTmcDGiw99hi0t+hpb9FRX+noT96zuouSLBg/p4LM/CZqKyIwhNkYNa2apAx7jdy8CfXkTajng3+M5dC2ZN8JBkLqqEyh3mdDCdW2emYwilmA4RPrmbLwBDu/zsLV5jlmXBZefoSUrFaSM1qJS26nsTZsgEOVJCqVFH599hOkCDPssVeNMbVLVBseo1R5ECNhTGM7d/J3RnGIzczxsT9Pdl6AAHO7BnM7tNR1lSXBhwBIMiy7Zw/lRTFYzTLJWS2Mnl7tbDxwxsVFjJ1dyb+fmOX77CV62AXRM6p4DT2qJ1alG0KBrV9kYWpzdJ3pNDwxiUaufmQnUbH2xKsxM6spOVRmL0Pjo8ahL2SsHV2/fAlZPyJXgpgwuyj95Kt9CAHmA/P4cnkcsmxPaJCxspLLiKbR2WXMF51T+a7H9lbCJbhSOpIESRmtnHXlEQzhvhsNpOc2c3Bbso+BCpLSW9EEnQ2tonJqM9jEbFVJFAe2pODe7cle0/S0C4qcxfElGS65Zy9vPzsZszGYpFt3OylhRYTgMb9zZzHR5XZvZHNVFLvfmUdT3ShnDsPXLORZHsG3HewoheVWYjAQgRq4bZVkBSEkzr/pAPmT6sifVOd13dhEI4Zwq0vb4O4oNpm03N57YVXx2neok48q3dj8aTa71jum4d2nyZtqw1i/crjzd0cZmovv2kvWyAZ0BiuyRsG3R1DYW6d2MCH8QEdfaz+GTPKxTwHpefZC6BPSYyjZmsOXy+MAUDpiSh1lsJqJ9VlNQCNZufjOPYycUkvKsCYkOZTiUBCbaGTesmNc++gOvwIWYMJpFWi1Pr5TAdPPLg3hGFVUTi1cSxS5li/qT4ytWv77x0kuDWZcfgRsWp1NTVln84rkzFZu+cVWZp5TQmSsCa02kK56nTY0QtPGbMM2/NpiP+gMVmaOl5mQHsOYpFi2vD6H5np7OSuHHbWhRaDxW+Zq9qzDzF1aTEZ+I9EJjnq1ofB0CmSNwsgpNVz7o52Mn1PldwutTjBlQZlbZy9XJEkQFW8kf6LvqiG+8FQqSyW0qJ5YFTesFonv12bhzbAIIbF/SwoLLj1KdLw9OEqSYNS0GkZ1FNo/sjuB9/4y0ftBJJh38VHGzqpGZ7BRfCCe3f8I876+/cg+4m7t3ofNn2UxamoNsYlGjnwzAr/eWy/YhJaIWCsX37WPyuIo/vOb6UHvwxOSrDDtzDLOuvJIUNuFR1q58I79rHppHALRWXS9w/M9bnYlE08LbXMIFZVTkYFMAivYmIqxXevFjkkIIdj+VSbnXtdZzik63syCS4+x4NJjCAGv/Xo61aXeWuEK9OE2bn3iexRFJjLGzKu/nAF+9Jw+zIrZJIPH+tUCi0nDxtXZzLvoOAe3JWNqDvewXmCUNSRz9W27Of3C47z3l/E01/mz++5j8WbPZVlwz9ObiIi2BDWeuUuPU3okhhOHHe1+O8M7dHqFZXfvDbqjoep17V9UT6yKGxVFMR1hBD4QcGyv90LZeRPqyB5T7/ENV5IV4pPbmbqwnNhEExFRVmrLI5D9ZtdLZAxv8PoZgLFFz9vPTaKmPBxjo+ektEBxxkH58v4GgSQrGMJszFjUs17aIybXcsNPtzN+TiWGcAtanY30vCaW3rafJTcfRFLvZBWVoOhv72zhriSfjk+hyBzekeT1c0mCs648giThwbbaBd7Cy44QHW8hNrEjOaoqHH92MGVYM5LXuH67p3jTx7ns+TaNY3sTvHou/SM5Z8Uc5xM8no4tmHnuiaAFLIBOr3DFg7tZdE0hSRmtaHU2wqPMTDuzjJt/vpW03JaA9uOtQYFK36N6YlXcsFkDsyxWi3fVJMtw6b0FfLk8n4Lv0lwMl2D4hDrOu+GQ2zS6PswWUCytxazFt3dVoqU+nKMFiQGdg9fxaxSSs+x1AZPS2wiLtGBsDTwJzB7z5Wj/a/deJ6S2c9Gd+3rVjCAlq5XzbzrE+Tcd6vE+VFRU3Okv76zdtvq2c/7sb/boBi6/fw9r3xpBQ3Vn6EFEtIUFlx5lwmmVzmWSBFq9gtXs3ZUoyY6eMP7rfX/3UTbpvcjSl2RB5vDOLmfZYxoo3BWcrXacj30Wyl7VZda5JZxxUVGPx6XVCaYuLHNWkAgG1es68KgiVsWNpMxWJFn4SSSQSM32/Yaq0yucd8Nh5l1SxInDsSiKRHpuE7FJ3UXcyCk1fL1iuIe9OA4nSEhto6Y0kkCaK5Qfi0ZrsGA1BV99QJIF42ZXEh5pBUCjFUw/+wTffpAbwLHtHpLpi0qZuqCMY3sTsFkl0nKbycxv6qHnQUVFpb/oS0GblttMeVG017rPkqyQmuPf85c7rp7bf7WFsqMxNNUaCI+2MGxUo8fEztHTq9m3OcXrMYUiERFjDiApV6KpLpxR02t6WP/EvtXk+eXOJePnVPDNqlwsJo1/ES0JNFqFW5/6nqriaBprwgiLsJI/udZpq/sTVbwOHtRJSBU3ImMsjJ5W5bV4viQrJGW2kDE8sKm3iGgLo6bVMGZGtUcBCxCXbGTc7Erv01RC4vQLiwJOsFJsMtkzfKwvCSRZdPncXoUhObOlW8zqnMXFjJ5Rbd/U+b0Il5/O6b2csfXMu/gYcclGpi4sY8aiUrJGqAJWReVkI9ThBlPml/t0DghFZtqZgSVoShJk5jcxdlY1uWMbvFYmmXVuCbLsKfygw5ZntJCU3hqwMB0+oRaNryRTl327/VuCxTceJC7Z6FweFmHjsvv3oNXbfIYoSLJAoxFccvc+YhPMjJxSy4xFpUw4rXJABawaMjA4UD2xKt0466ojVBRH01gd7vaG7IjrvPD2/SEXZefdcAibTebg1pTOAtWKhCwLzrqqkDEzaijYWM+xggT8ldpKzmwlZtohaMriaEFH4kDHeciyQB8muPWpCo4WhLF5dTRN9RKxiSamzC9n0rxydHp3AS9r4MLb9zNxbgW7vkmnvjIcfbiV2AQTdZXhGFt1xCYbmXxGOaOmVQedCKCiojJ4CZV3NjG9jbOvKuSL5SPdZrscXtApC0oZMbnnmfCeSMpo47L79rDq7+MwtenslWOEvWJLSlYrl963h5YGA9984GMmrANZo5CW08KFt+9n1cvjwEOS6fg5FYyeXs32rzIpOxqDJNtDyGacfcJjfGnWiCZu/9X37PkmncO7ErFZZeKT27EpEnXlkcgahfyJdUxZUOYmgPubri8wqngdPEhiEFfKdvT3fuD5jzGERw70cIYUxlYt277MZNeGdFobDRjCrYyfW8HMc070Kq7THzVlERzYmoypXWv30M6qJDzK/rZdfDCO5X+Y7GcPgjv/bzMl5mrOOX0cGz+OYcPKWGrKtRjCBTPPaWbh5Y0kpne+wX/y1b5BUQhd5eTD1N7Knx5a6re/92DDYVuf+WQH4ZHRAz2ck47eiNmi/XFsXZtF0f54hJBIy2lmxtknGDOzus9mbCxmmUPbk6g8Ho1GqzB8Yh1ZIxudx3vrmcmUHonFVzvciadVsvhGezx+VUkkWz/PonBXEjarRHJWC9POKmPsjKpTJslUFa4DS3trM48umerXtqoiVsUvQmHQGKbtX2bwxfIRHb+5Glx7wtc51x5iyoJyCsqbAjY6qohV6SmqiB3a9EbMOp68gyHUqLVJxxu/m0pTbTjdk2cFcSntXP/jHU6HwqmIp3ARVbgOHIGKWDWcQMUvg0XAAkw7q4zsMfV8/s5Iyo7EYLPa5+6zRjYyd0kxuePqB3iEKioqQ4XehBoMBvHqIDLGwm1PbWHbl5ls/yKLlkY9IKEPszJ1YSmzzishLCKQZgsnB97im1XROnhoaA/shWlQi1iHk9hkbBvgkagMJqLjW1l2Tw1C2KfJNBqBRttxrXQ0gbEY22hvDawcjMXYhqldDWRVCR6HbRrEE1oecYzX2BZYHUwV/5w5a5jz32vWH3T7bFzayeHtnjL/IFPmH0SxgdUqo9MrTrHtsK0nG/sqPD8Hzp0/utuyQJ8ZKn1LQ7sVU4dt8mdbB3U4wYkTJxg2bJj/FVVUVFQGkJKSErKysgZ6GAGj2lYVFZWTAX+2dVCLWEVRKCsrIzo6GqmXcy9NTU0MGzaMkpKSkyp2LVSo56+ev3r+oT9/IQTNzc1kZGQgy4Mo7sYPqm0NHer5q+evnv/A2dZBHU4gy3LIvRsxMTFD8kJzoJ6/ev7q+Yf2/GNjY/2vNMhQbWvoUc9fPX/1/Pvftp48rgMVFRUVFRUVFRWVDlQRq6KioqKioqKictIxZESswWDgiSeewGAwDPRQBgT1/NXzV89/6J5/XzLUv1v1/NXzV89/4M5/UCd2qaioqKioqKioqHhiyHhiVVRUVFRUVFRUTh1UEauioqKioqKionLSoYpYFRUVFRUVFRWVkw5VxKqoqKioqKioqJx0DHkRazKZmDJlCpIksXPnzoEeTr9QVFTEbbfdRl5eHuHh4eTn5/PEE09gNpsHemh9xl/+8hdyc3MJCwtj9uzZfP/99wM9pH7ht7/9LTNnziQ6OpqUlBQuueQSDh486H/DU5Tf/e53SJLEQw89NNBDOaVR7apqV091VNvayUDa1SEvYh999FEyMjIGehj9yoEDB1AUhZdffpm9e/fyxz/+kZdeeomf/OQnAz20PmH58uU8/PDDPPHEE2zfvp3Jkydz3nnnUVVVNdBD63PWrVvHvffey6ZNm1i7di0Wi4Vzzz2X1tbWgR5av7NlyxZefvllJk2aNNBDOeVR7apqV091VNtqZ8DtqhjCfPLJJ2LMmDFi7969AhA7duwY6CENGM8884zIy8sb6GH0CbNmzRL33nuv83ebzSYyMjLEb3/72wEc1cBQVVUlALFu3bqBHkq/0tzcLEaOHCnWrl0rFixYIB588MGBHtIpi2pXO1Ht6tBhKNrWwWBXh6wntrKykjvuuIPXX3+diIiIgR7OgNPY2EhCQsJADyPkmM1mtm3bxqJFi5zLZFlm0aJFbNy4cQBHNjA0NjYCnJJ/a1/ce++9LF261O06UAk9ql11R7WrQ4ehaFsHg13VDtiRBxAhBDfffDN33303M2bMoKioaKCHNKAUFhby4osv8uyzzw70UEJOTU0NNpuN1NRUt+WpqakcOHBggEY1MCiKwkMPPcTpp5/OhAkTBno4/cY777zD9u3b2bJly0AP5ZRGtavuqHZ16DAUbetgsaunlCf2scceQ5Iknz8HDhzgxRdfpLm5mccff3yghxxSAj1/V0pLS1m8eDFXXHEFd9xxxwCNXKU/uPfeeykoKOCdd94Z6KH0GyUlJTz44IO8+eabhIWFDfRwTkpUu6raVRXfDDXbOpjs6inVdra6upra2lqf6wwfPpwrr7ySDz/8EEmSnMttNhsajYbrrruO1157ra+H2icEev56vR6AsrIyFi5cyJw5c3j11VeR5VPqnQawT3tFRESwYsUKLrnkEufym266iYaGBlatWjVwg+tH7rvvPlatWsX69evJy8sb6OH0G++//z7Lli1Do9E4l9lsNiRJQpZlTCaT22cq3VHtqmpXu6La1U6Gom0dTHb1lBKxgVJcXExTU5Pz97KyMs477zxWrFjB7NmzycrKGsDR9Q+lpaWceeaZTJ8+nTfeeOOUfpDPnj2bWbNm8eKLLwL2qZ/s7Gzuu+8+HnvssQEeXd8ihOD+++9n5cqVfP3114wcOXKgh9SvNDc3c/z4cbdlt9xyC2PGjOHHP/7xkJn66w9Uu6ra1aFiV2Fo29bBZFeHZExsdna22+9RUVEA5OfnDxlDu3DhQnJycnj22Weprq52fpaWljaAI+sbHn74YW666SZmzJjBrFmzeP7552ltbeWWW24Z6KH1Offeey9vvfUWq1atIjo6moqKCgBiY2MJDw8f4NH1PdHR0d0MamRkJImJiaqADTGqXVXt6lCxqzC0betgsqtDUsQOddauXUthYSGFhYXdHi6nomP+qquuorq6ml/84hdUVFQwZcoUPv30025JCacif/vb3wBYuHCh2/JXXnmFm2++uf8HpKJyiqLa1aFjV0G1rYOFIRlOoKKioqKioqKicnJz6kWcq6ioqKioqKionPKoIlZFRUVFRUVFReWkQxWxKioqKioqKioqJx2qiFVRUVFRUVFRUTnpUEWsioqKioqKiorKSYcqYlVUVFRUVFRUVE46VBGroqKioqKioqJy0qGKWBUVFRUVFRUVlZMOVcSqqKioqKioqKicdKgiVkVFRUVFRUVF5aRDFbEqKioqKioqKionHaqIVVFRUVFRUVFROen4/yydBTYNWMDXAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 700x700 with 4 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "rf = RandomForestClassifier().fit(X_train[:, :2], y_train)\n",
+    "xgb = XGBClassifier().fit(X_train[:, :2], y_train)\n",
+    "tabpfn = TabPFNClassifier().fit(X_train[:, :2], y_train)\n",
+    "\n",
+    "# Create a 2x2 subplot layout\n",
+    "fig, axes = plt.subplots(2, 2, figsize=(7, 7))\n",
+    "\n",
+    "# Plot Train Points\n",
+    "ax_points = axes[0, 0]\n",
+    "ax_points.set_title(\"Train points\")\n",
+    "ax_points.scatter(\n",
+    "    X_train[:, 0], X_train[:, 1], c=y_train, cmap=ListedColormap([\"#FF0000\", \"#0000FF\"])\n",
+    ")\n",
+    "\n",
+    "# Plot Random Forest\n",
+    "ax_rf = axes[0, 1]\n",
+    "plot_decision_boundary(ax_rf, rf, \"Random Forest\")\n",
+    "\n",
+    "# Plot XGBoost\n",
+    "ax_xgb = axes[1, 0]\n",
+    "plot_decision_boundary(ax_xgb, xgb, \"XGBoost\")\n",
+    "\n",
+    "# Plot TabPFN\n",
+    "ax_tabpfn = axes[1, 1]\n",
+    "plot_decision_boundary(ax_tabpfn, tabpfn, \"TabPFN\")\n",
+    "\n",
+    "# Adjust layout for better spacing\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "8tvOmmiOOT4o"
+   },
+   "source": [
+    "## Sin Curve Fitting with Regression\n",
+    "\n",
+    "Next, we investigate the curve-fitting behavior of the different models on a sin curve."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "f_6wB1N2OrYu",
+    "outputId": "f91662b0-c1cb-42b1-d4c0-5562492d4090"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "jKWF7CrmHS_5"
-      },
-      "outputs": [],
-      "source": [
-        "from tabpfn_time_series import FeatureTransformer\n",
-        "from tabpfn_time_series.features import (\n",
-        "    AutoSeasonalFeature,\n",
-        "    CalendarFeature,\n",
-        "    RunningIndexFeature,\n",
-        ")\n",
-        "\n",
-        "selected_features = [\n",
-        "    RunningIndexFeature(),\n",
-        "    CalendarFeature(),\n",
-        "    AutoSeasonalFeature(),\n",
-        "]\n",
-        "\n",
-        "feature_transformer = FeatureTransformer(selected_features)\n",
-        "\n",
-        "train_tsdf, test_tsdf = feature_transformer.transform(train_tsdf, test_tsdf)"
+     "data": {
+      "image/png": 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FSNoCAAAAAAAAgIv8/2jftpytr8p2AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1400x1200 with 4 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Toy function to generate data\n",
+    "def generate_sinx_plus_x(N):\n",
+    "    x = np.linspace(0, 20, N)\n",
+    "    y = np.sin(x) + x / 10\n",
+    "\n",
+    "    return x.reshape(-1, 1), y\n",
+    "\n",
+    "\n",
+    "# Utility function for plotting\n",
+    "def plot_predictions(ax, model, model_name):\n",
+    "    X_test = np.linspace(0, 20, 200).reshape(\n",
+    "        -1, 1\n",
+    "    )  # Predict for 200 points  between 0 and 20\n",
+    "    y_preds = model.predict(X_test)\n",
+    "    ax.set_title(model_name)\n",
+    "    ax.scatter(X_test, y_preds, label=\"Predictions\")\n",
+    "    ax.scatter(X_train, y_train, label=\"Train points\")\n",
+    "    ax.legend()\n",
+    "\n",
+    "\n",
+    "# Generate data\n",
+    "X_train, y_train = generate_sinx_plus_x(N=40)\n",
+    "\n",
+    "# Fit Models\n",
+    "rf = RandomForestRegressor(random_state=42).fit(X_train, y_train)\n",
+    "xgb = XGBRegressor(random_state=42).fit(X_train, y_train)\n",
+    "tabpfn = TabPFNRegressor()\n",
+    "tabpfn.fit(X_train, y_train)\n",
+    "\n",
+    "# Create a 2x2 subplot layout\n",
+    "fig, axs = plt.subplots(2, 2, figsize=(14, 12))\n",
+    "\n",
+    "# Plot train points\n",
+    "ax_points = axs[0, 0]\n",
+    "ax_points.set_title(\"Train points\")\n",
+    "ax_points.scatter(X_train, y_train, label=\"Train points\")\n",
+    "ax_points.legend()\n",
+    "\n",
+    "# Plot predictions for Random Forest\n",
+    "ax_rf = axs[0, 1]\n",
+    "plot_predictions(ax_rf, rf, \"Random Forest\")\n",
+    "\n",
+    "# Plot predictions for XGBoost\n",
+    "ax_xgb = axs[1, 0]\n",
+    "plot_predictions(ax_xgb, xgb, \"XGBoost\")\n",
+    "\n",
+    "# Plot predictions for TabPFN\n",
+    "ax_tabpfn = axs[1, 1]\n",
+    "plot_predictions(ax_tabpfn, tabpfn, \"TabPFN\")\n",
+    "\n",
+    "# Adjust layout for better spacing\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "XcYaJKT_Pw6T"
+   },
+   "source": [
+    "## Uncertainty of TabPFN / Quantile Regresison\n",
+    "\n",
+    "---\n",
+    "\n",
+    "\n",
+    "\n",
+    "TabPFN is trained to predict the distribution of the target variable and not just a single point. This is also the case for regression.\n",
+    "\n",
+    "As a result, we natively obtain uncertainty for the predictions of TabPFN (without the need for a new model or repeating models for different quantiles).\n",
+    "\n",
+    "In the following, we plot the uncertainty of TabPFN for a toy function with noise."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "r5q1UBos4W1O"
+   },
+   "outputs": [],
+   "source": [
+    "### Code to generate the plot (feel free to ignore)\n",
+    "def plot_regression_uncertainty(ax, x, y_line, y_noisy, x_test, color_multiplier=5):\n",
+    "    all_quantiles = preds[\"quantiles\"]\n",
+    "    y = np.array(all_quantiles)  # shape of y: (9, number of samples)\n",
+    "\n",
+    "    # Calculate the maximum and minimum values in y\n",
+    "    y_max = np.max(y, axis=0)\n",
+    "    y_min = np.min(y, axis=0)\n",
+    "\n",
+    "    # Calculate the widths of each quantile bin\n",
+    "    quantile_bin_widths = np.diff(\n",
+    "        y, axis=0\n",
+    "    )  # shape of quantile_bin_widths: (8, number of samples)\n",
+    "\n",
+    "    # Normalize the bin widths for a given x\n",
+    "    per_x_normalized_bin_widths = (quantile_bin_widths) / (y_max - y_min)\n",
+    "\n",
+    "    # Plotting\n",
+    "    num_bins, num_data_points = (\n",
+    "        per_x_normalized_bin_widths.shape[0],\n",
+    "        per_x_normalized_bin_widths.shape[1],\n",
+    "    )\n",
+    "    rect_width = (\n",
+    "        x_test[1] - x_test[0]\n",
+    "    ).squeeze()  # assuming the x query points are equally spaced out\n",
+    "\n",
+    "    for i in range(num_data_points):\n",
+    "        for j in range(num_bins):\n",
+    "            quantile_bin_widths[j, i]\n",
+    "            rect = plt.Rectangle(\n",
+    "                xy=(x_test[i][0] - rect_width / 2, y[j, i]),\n",
+    "                width=rect_width,\n",
+    "                height=quantile_bin_widths[j, i],\n",
+    "                facecolor=plt.cm.viridis(\n",
+    "                    per_x_normalized_bin_widths[j, i] * color_multiplier\n",
+    "                ),\n",
+    "                edgecolor=\"none\",\n",
+    "            )\n",
+    "            ax.add_patch(rect)\n",
+    "\n",
+    "    # Set limits and labels\n",
+    "    ax.plot(x, y_line, label=\"True line\", color=\"blue\")\n",
+    "    ax.set_xlim(min(x_test) - 1, max(x_test) + 1)\n",
+    "    ax.set_ylim(np.min(y_noisy) - 1, np.max(y_noisy) + 1)\n",
+    "    ax.set_xlabel(\"X\")\n",
+    "    ax.set_ylabel(\"Y\")\n",
+    "\n",
+    "    # ax.plot(x, y, label='True line', color='blue')\n",
+    "    ax.scatter(x, y_noisy, label=\"Noisy data\", color=\"red\", s=10)\n",
+    "\n",
+    "    plt.title(\"TabPFN Regression Uncertainty\")\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "# Generate Data\n",
+    "def generate_line_with_heteroscedastic_noise(\n",
+    "    m=0.8, num_points=200, x_start=0, x_end=100, noise_factor=0.1\n",
+    "):\n",
+    "    x = np.linspace(x_start, x_end, num_points)\n",
+    "    noise = np.random.randn(num_points)\n",
+    "    y = m * x\n",
+    "    y_noisy = y + (noise * noise_factor * x)\n",
+    "\n",
+    "    return x.reshape(-1, 1), y, y_noisy\n",
+    "\n",
+    "\n",
+    "def generate_line_with_heteroscedastic_noise_with_gap(\n",
+    "    m=0.8, num_points=200, x_start=0, x_end=100, noise_factor=0.1\n",
+    "):\n",
+    "    extra_points = num_points // 3\n",
+    "    x, y, y_noisy = generate_line_with_heteroscedastic_noise(\n",
+    "        m, num_points + extra_points, x_start, x_end, noise_factor\n",
+    "    )\n",
+    "    a = np.arange(num_points + extra_points)\n",
+    "    idx = np.where((a < num_points / 3) | (a > num_points / 3 + extra_points))\n",
+    "    return x[idx], y[idx], y_noisy[idx]\n",
+    "\n",
+    "\n",
+    "x, y_line, y_noisy = generate_line_with_heteroscedastic_noise_with_gap(0.8)\n",
+    "x_test = np.linspace(0, 100, 200).reshape(-1, 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "xpvqsL1f4W1O"
+   },
+   "outputs": [],
+   "source": [
+    "reg = TabPFNRegressor()\n",
+    "reg.fit(x, y_noisy)\n",
+    "preds = reg.predict(x_test, output_type=\"full\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "GwSCwFm-4W1O",
+    "outputId": "05fa4741-b689-4438-8000-40e7ae886f4f"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "N9WZ46ywJylH"
-      },
-      "source": [
-        "Let's take a look at the tables (train and test) before we proceed to do predictions.\n",
-        "\n",
-        "✅ Realize that we have added some features into the tables."
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x600 with 2 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(12, 6))\n",
+    "\n",
+    "# Plot the original data\n",
+    "ax = fig.add_subplot(121)\n",
+    "ax.plot(x, y_line, label=\"True line\", color=\"blue\")\n",
+    "ax.scatter(x, y_noisy, label=\"Noisy data\", color=\"red\", s=10)\n",
+    "ax.set_xlabel(\"X\")\n",
+    "ax.set_ylabel(\"Y\")\n",
+    "ax.set_xlim(min(x) - 1, max(x) + 1)\n",
+    "ax.set_ylim(np.min(y_noisy) - 1, np.max(y_noisy) + 1)\n",
+    "ax.set_title(\"Heteroscedastic Noise along a Sloping Line\")\n",
+    "ax.legend()\n",
+    "\n",
+    "# plot the uncertainty estimates obtained from TabPFN\n",
+    "ax = fig.add_subplot(122)\n",
+    "plot_regression_uncertainty(ax, x, y_line, y_noisy, x_test, color_multiplier=5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "VJMcv-KvPYIh"
+   },
+   "source": [
+    "# Time Series Forecasting <a name=\"timeseries\"></a>\n",
+    "\n",
+    "TabPFN can be used for time series prediction, following the work of Hoo et al. (Zero-Shot Time Series Forecasting with TabPFNv2; https://arxiv.org/abs/2501.02945v3).\n",
+    "\n",
+    "In this demo, we will use the time series dataset from [Chronos Dataset](https://huggingface.co/datasets/autogluon/chronos_datasets) on HuggingFace. Also, we'll keep it short and work with just 2 time series from the dataset.\n",
+    "\n",
+    "Feel free to explore other datasets by using the dataset names from Chronos Dataset on HuggingFace or even use time series data of your own problem.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Z3wiT00Uf0dF"
+   },
+   "source": [
+    "## *Installation*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "J0cUKia3fzrz"
+   },
+   "outputs": [],
+   "source": [
+    "!uv pip install tabpfn-time-series\n",
+    "raise ValueError(\n",
+    "    \"Make sure to restart the session before proceeding, otherwise errors will follow (Runtime > Restart Session)\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "kNOAk5sPHS_3"
+   },
+   "source": [
+    "## Load Time Series Data\n",
+    "\n",
+    "In this demo, we will use the time series dataset from [Chronos Dataset](https://huggingface.co/datasets/autogluon/chronos_datasets) on HuggingFace. Also, we'll keep it short and work with just 2 time series from the dataset.\n",
+    "\n",
+    "Feel free to explore other datasets by using the dataset names from Chronos Dataset on HuggingFace or even use time series data of your own problem."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "qgHudyQdHS_3"
+   },
+   "outputs": [],
+   "source": [
+    "dataset_metadata = {\n",
+    "    \"monash_tourism_monthly\": {\"prediction_length\": 24},\n",
+    "    \"m4_hourly\": {\"prediction_length\": 48},\n",
+    "}\n",
+    "\n",
+    "dataset_choice = \"monash_tourism_monthly\"\n",
+    "num_time_series_subset = 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 217,
+     "referenced_widgets": [
+      "8af3e44759a84b24923e15c7722b8518",
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+      "0ef1661193d44ef99f7e281cb79c40b5",
+      "38d0e7f682cd45b193066630854b3329",
+      "30bea92a5ae940428e1f3f534611309e",
+      "a1292ad49a5b49c582f15ade36b78282",
+      "5029e0c3a04c418c9f2284c505cfa52e",
+      "41ef74f05a894e2ab10dde4e6d4c49da",
+      "b15054c98fd8457095b01a54ad491056",
+      "e4a2681db14a43a6836f0fd3ab154509",
+      "e0ce26fdeefc4061879dbd285a3ec436",
+      "7e13c9b09413417b9d2cb7af278a46fe",
+      "12a2a205bd944f8e8a3643f977c38b56",
+      "758dc947f2dc4db1b28f427add34f4c6",
+      "b7227f27d0c341419b87360437ea2132",
+      "769284272f1545a5b3dafa71d2b9439d",
+      "0c458dab93ee415f839fd216d33b43d9",
+      "96db2596e70f4e809832e39642b8af99",
+      "614ab8ceb45245cf8d11dcb576b3e27d",
+      "bcd4f57966ce4cd594bce97f564dfbfc",
+      "73584ad402334131a9b7f96d13a086a4",
+      "e369aa70fe3d4923ae127eab8a8d1490",
+      "f42b869e3b994141b0c81dcffc39c042",
+      "498eb04a0a594e87af9c566e2878e515",
+      "a93d570f7c4547288f6257d8221593be",
+      "78a9d6c24bf0436fb7184a1ac46f8593",
+      "769f504e490449dd952edf304ea53a76",
+      "92834505829e49cd99d1ad420bddf0d1",
+      "88b6a04a2d974027a9936cb9bb84eac0",
+      "5975c2b92d634044b794d793aeb4d52f",
+      "894db0aa656e4882b2117d1ac8398be5",
+      "1d7a439caf5a462e81e67f8cc9b2a998"
+     ]
     },
+    "id": "Qc1mHevjHS_4",
+    "outputId": "395ee836-630b-45dd-ba5f-5024aa43cc73"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "tnKwZbngJx0X",
-        "outputId": "1ea42799-8360-42d5-e1f6-648340baabca"
-      },
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "                       target  running_index  year  second_of_minute_sin  \\\n",
-              "item_id timestamp                                                          \n",
-              "0       1979-01-31  1149.8700              0  1979                   0.0   \n",
-              "        1979-02-28  1053.8002              1  1979                   0.0   \n",
-              "        1979-03-31  1388.8798              2  1979                   0.0   \n",
-              "        1979-04-30  1783.3702              3  1979                   0.0   \n",
-              "        1979-05-31  1921.0252              4  1979                   0.0   \n",
-              "\n",
-              "                    second_of_minute_cos  minute_of_hour_sin  \\\n",
-              "item_id timestamp                                              \n",
-              "0       1979-01-31                   1.0                 0.0   \n",
-              "        1979-02-28                   1.0                 0.0   \n",
-              "        1979-03-31                   1.0                 0.0   \n",
-              "        1979-04-30                   1.0                 0.0   \n",
-              "        1979-05-31                   1.0                 0.0   \n",
-              "\n",
-              "                    minute_of_hour_cos  hour_of_day_sin  hour_of_day_cos  \\\n",
-              "item_id timestamp                                                          \n",
-              "0       1979-01-31                 1.0              0.0              1.0   \n",
-              "        1979-02-28                 1.0              0.0              1.0   \n",
-              "        1979-03-31                 1.0              0.0              1.0   \n",
-              "        1979-04-30                 1.0              0.0              1.0   \n",
-              "        1979-05-31                 1.0              0.0              1.0   \n",
-              "\n",
-              "                    day_of_week_sin  ...    sin_#0        cos_#0  \\\n",
-              "item_id timestamp                    ...                           \n",
-              "0       1979-01-31     8.660254e-01  ...  0.000000  1.000000e+00   \n",
-              "        1979-02-28     8.660254e-01  ...  0.500000  8.660254e-01   \n",
-              "        1979-03-31    -8.660254e-01  ...  0.866025  5.000000e-01   \n",
-              "        1979-04-30     0.000000e+00  ...  1.000000  6.123234e-17   \n",
-              "        1979-05-31     1.224647e-16  ...  0.866025 -5.000000e-01   \n",
-              "\n",
-              "                          sin_#1  cos_#1        sin_#2        cos_#2  \\\n",
-              "item_id timestamp                                                      \n",
-              "0       1979-01-31  0.000000e+00     1.0  0.000000e+00  1.000000e+00   \n",
-              "        1979-02-28  8.660254e-01     0.5  1.000000e+00  6.123234e-17   \n",
-              "        1979-03-31  8.660254e-01    -0.5  1.224647e-16 -1.000000e+00   \n",
-              "        1979-04-30  1.224647e-16    -1.0 -1.000000e+00 -1.836970e-16   \n",
-              "        1979-05-31 -8.660254e-01    -0.5 -2.449294e-16  1.000000e+00   \n",
-              "\n",
-              "                          sin_#3  cos_#3        sin_#4  cos_#4  \n",
-              "item_id timestamp                                               \n",
-              "0       1979-01-31  0.000000e+00     1.0  0.000000e+00     1.0  \n",
-              "        1979-02-28  1.224647e-16    -1.0  8.660254e-01    -0.5  \n",
-              "        1979-03-31 -2.449294e-16     1.0 -8.660254e-01    -0.5  \n",
-              "        1979-04-30  3.673940e-16    -1.0 -2.449294e-16     1.0  \n",
-              "        1979-05-31 -4.898587e-16     1.0  8.660254e-01    -0.5  \n",
-              "\n",
-              "[5 rows x 29 columns]"
-            ],
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-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th>target</th>\n",
-              "      <th>running_index</th>\n",
-              "      <th>year</th>\n",
-              "      <th>second_of_minute_sin</th>\n",
-              "      <th>second_of_minute_cos</th>\n",
-              "      <th>minute_of_hour_sin</th>\n",
-              "      <th>minute_of_hour_cos</th>\n",
-              "      <th>hour_of_day_sin</th>\n",
-              "      <th>hour_of_day_cos</th>\n",
-              "      <th>day_of_week_sin</th>\n",
-              "      <th>...</th>\n",
-              "      <th>sin_#0</th>\n",
-              "      <th>cos_#0</th>\n",
-              "      <th>sin_#1</th>\n",
-              "      <th>cos_#1</th>\n",
-              "      <th>sin_#2</th>\n",
-              "      <th>cos_#2</th>\n",
-              "      <th>sin_#3</th>\n",
-              "      <th>cos_#3</th>\n",
-              "      <th>sin_#4</th>\n",
-              "      <th>cos_#4</th>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>item_id</th>\n",
-              "      <th>timestamp</th>\n",
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-              "      <th></th>\n",
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-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
-              "      <th>1979-01-31</th>\n",
-              "      <td>1149.8700</td>\n",
-              "      <td>0</td>\n",
-              "      <td>1979</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.000000</td>\n",
-              "      <td>1.000000e+00</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>1.000000e+00</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>1.0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1979-02-28</th>\n",
-              "      <td>1053.8002</td>\n",
-              "      <td>1</td>\n",
-              "      <td>1979</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.500000</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>1.000000e+00</td>\n",
-              "      <td>6.123234e-17</td>\n",
-              "      <td>1.224647e-16</td>\n",
-              "      <td>-1.0</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1979-03-31</th>\n",
-              "      <td>1388.8798</td>\n",
-              "      <td>2</td>\n",
-              "      <td>1979</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.866025</td>\n",
-              "      <td>5.000000e-01</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "      <td>1.224647e-16</td>\n",
-              "      <td>-1.000000e+00</td>\n",
-              "      <td>-2.449294e-16</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1979-04-30</th>\n",
-              "      <td>1783.3702</td>\n",
-              "      <td>3</td>\n",
-              "      <td>1979</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>...</td>\n",
-              "      <td>1.000000</td>\n",
-              "      <td>6.123234e-17</td>\n",
-              "      <td>1.224647e-16</td>\n",
-              "      <td>-1.0</td>\n",
-              "      <td>-1.000000e+00</td>\n",
-              "      <td>-1.836970e-16</td>\n",
-              "      <td>3.673940e-16</td>\n",
-              "      <td>-1.0</td>\n",
-              "      <td>-2.449294e-16</td>\n",
-              "      <td>1.0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1979-05-31</th>\n",
-              "      <td>1921.0252</td>\n",
-              "      <td>4</td>\n",
-              "      <td>1979</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>1.224647e-16</td>\n",
-              "      <td>...</td>\n",
-              "      <td>0.866025</td>\n",
-              "      <td>-5.000000e-01</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "      <td>-2.449294e-16</td>\n",
-              "      <td>1.000000e+00</td>\n",
-              "      <td>-4.898587e-16</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>5 rows × 29 columns</p>\n",
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-              "\n",
-              "    [theme=dark] .colab-df-convert {\n",
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-              "    [theme=dark] .colab-df-convert:hover {\n",
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-              "\n",
-              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
-              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
-              "          + ' to learn more about interactive tables.';\n",
-              "        element.innerHTML = '';\n",
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-              "        await google.colab.output.renderOutput(dataTable, element);\n",
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-              "  [theme=dark] .colab-df-quickchart {\n",
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-              "variable_name": "train_tsdf"
-            }
-          },
-          "metadata": {},
-          "execution_count": 5
-        }
-      ],
-      "source": [
-        "train_tsdf.head()"
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
+      "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
+      "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
+      "You will be able to reuse this secret in all of your notebooks.\n",
+      "Please note that authentication is recommended but still optional to access public models or datasets.\n",
+      "  warnings.warn(\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "yKaNq3RAKMH9",
-        "outputId": "73791141-2b67-4019-bf3d-d4bf1bde5738"
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8af3e44759a84b24923e15c7722b8518",
+       "version_major": 2,
+       "version_minor": 0
       },
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "                    target  running_index  year  second_of_minute_sin  \\\n",
-              "item_id timestamp                                                       \n",
-              "0       1992-08-31     NaN            163  1992                   0.0   \n",
-              "        1992-09-30     NaN            164  1992                   0.0   \n",
-              "        1992-10-31     NaN            165  1992                   0.0   \n",
-              "        1992-11-30     NaN            166  1992                   0.0   \n",
-              "        1992-12-31     NaN            167  1992                   0.0   \n",
-              "\n",
-              "                    second_of_minute_cos  minute_of_hour_sin  \\\n",
-              "item_id timestamp                                              \n",
-              "0       1992-08-31                   1.0                 0.0   \n",
-              "        1992-09-30                   1.0                 0.0   \n",
-              "        1992-10-31                   1.0                 0.0   \n",
-              "        1992-11-30                   1.0                 0.0   \n",
-              "        1992-12-31                   1.0                 0.0   \n",
-              "\n",
-              "                    minute_of_hour_cos  hour_of_day_sin  hour_of_day_cos  \\\n",
-              "item_id timestamp                                                          \n",
-              "0       1992-08-31                 1.0              0.0              1.0   \n",
-              "        1992-09-30                 1.0              0.0              1.0   \n",
-              "        1992-10-31                 1.0              0.0              1.0   \n",
-              "        1992-11-30                 1.0              0.0              1.0   \n",
-              "        1992-12-31                 1.0              0.0              1.0   \n",
-              "\n",
-              "                    day_of_week_sin  ...    sin_#0        cos_#0  \\\n",
-              "item_id timestamp                    ...                           \n",
-              "0       1992-08-31     0.000000e+00  ... -0.500000 -8.660254e-01   \n",
-              "        1992-09-30     8.660254e-01  ... -0.866025 -5.000000e-01   \n",
-              "        1992-10-31    -8.660254e-01  ... -1.000000 -1.224956e-14   \n",
-              "        1992-11-30     0.000000e+00  ... -0.866025  5.000000e-01   \n",
-              "        1992-12-31     1.224647e-16  ... -0.500000  8.660254e-01   \n",
-              "\n",
-              "                          sin_#1  cos_#1        sin_#2        cos_#2  \\\n",
-              "item_id timestamp                                                      \n",
-              "0       1992-08-31  8.660254e-01     0.5 -1.000000e+00 -2.596808e-14   \n",
-              "        1992-09-30  8.660254e-01    -0.5 -3.135839e-14  1.000000e+00   \n",
-              "        1992-10-31  2.449913e-14    -1.0  1.000000e+00  3.674869e-14   \n",
-              "        1992-11-30 -8.660254e-01    -0.5 -1.470443e-14 -1.000000e+00   \n",
-              "        1992-12-31 -8.660254e-01     0.5 -1.000000e+00  9.314124e-15   \n",
-              "\n",
-              "                          sin_#3  cos_#3        sin_#4  cos_#4  \n",
-              "item_id timestamp                                               \n",
-              "0       1992-08-31  5.193617e-14    -1.0  8.660254e-01    -0.5  \n",
-              "        1992-09-30 -6.271677e-14     1.0 -8.660254e-01    -0.5  \n",
-              "        1992-10-31  7.349738e-14    -1.0 -4.899825e-14     1.0  \n",
-              "        1992-11-30  2.940885e-14     1.0  8.660254e-01    -0.5  \n",
-              "        1992-12-31 -1.862825e-14    -1.0 -8.660254e-01    -0.5  \n",
-              "\n",
-              "[5 rows x 29 columns]"
-            ],
-            "text/html": [
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-              "  <thead>\n",
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-              "      <th></th>\n",
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-              "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
-              "      <th>1992-08-31</th>\n",
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-              "      <td>8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1992-09-30</th>\n",
-              "      <td>NaN</td>\n",
-              "      <td>164</td>\n",
-              "      <td>1992</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>...</td>\n",
-              "      <td>-0.866025</td>\n",
-              "      <td>-5.000000e-01</td>\n",
-              "      <td>8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "      <td>-3.135839e-14</td>\n",
-              "      <td>1.000000e+00</td>\n",
-              "      <td>-6.271677e-14</td>\n",
-              "      <td>1.0</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
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-              "      <th>1992-10-31</th>\n",
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-              "      <td>1.0</td>\n",
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-              "      <td>...</td>\n",
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-              "      <td>2.449913e-14</td>\n",
-              "      <td>-1.0</td>\n",
-              "      <td>1.000000e+00</td>\n",
-              "      <td>3.674869e-14</td>\n",
-              "      <td>7.349738e-14</td>\n",
-              "      <td>-1.0</td>\n",
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-              "      <td>166</td>\n",
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-              "      <td>0.0</td>\n",
-              "      <td>1.0</td>\n",
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-              "      <td>1.0</td>\n",
-              "      <td>0.000000e+00</td>\n",
-              "      <td>...</td>\n",
-              "      <td>-0.866025</td>\n",
-              "      <td>5.000000e-01</td>\n",
-              "      <td>-8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "      <td>-1.470443e-14</td>\n",
-              "      <td>-1.000000e+00</td>\n",
-              "      <td>2.940885e-14</td>\n",
-              "      <td>1.0</td>\n",
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-              "    <tr>\n",
-              "      <th>1992-12-31</th>\n",
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-              "      <td>-8.660254e-01</td>\n",
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-              "      <td>-8.660254e-01</td>\n",
-              "      <td>-0.5</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>5 rows × 29 columns</p>\n",
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-              "    .colab-df-convert:hover {\n",
-              "      background-color: #E2EBFA;\n",
-              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
-              "      fill: #174EA6;\n",
-              "    }\n",
-              "\n",
-              "    .colab-df-buttons div {\n",
-              "      margin-bottom: 4px;\n",
-              "    }\n",
-              "\n",
-              "    [theme=dark] .colab-df-convert {\n",
-              "      background-color: #3B4455;\n",
-              "      fill: #D2E3FC;\n",
-              "    }\n",
-              "\n",
-              "    [theme=dark] .colab-df-convert:hover {\n",
-              "      background-color: #434B5C;\n",
-              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
-              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
-              "      fill: #FFFFFF;\n",
-              "    }\n",
-              "  </style>\n",
-              "\n",
-              "    <script>\n",
-              "      const buttonEl =\n",
-              "        document.querySelector('#df-80d21b08-9078-44d7-b5b6-5046e14b7c8a button.colab-df-convert');\n",
-              "      buttonEl.style.display =\n",
-              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
-              "\n",
-              "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-80d21b08-9078-44d7-b5b6-5046e14b7c8a');\n",
-              "        const dataTable =\n",
-              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
-              "                                                    [key], {});\n",
-              "        if (!dataTable) return;\n",
-              "\n",
-              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
-              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
-              "          + ' to learn more about interactive tables.';\n",
-              "        element.innerHTML = '';\n",
-              "        dataTable['output_type'] = 'display_data';\n",
-              "        await google.colab.output.renderOutput(dataTable, element);\n",
-              "        const docLink = document.createElement('div');\n",
-              "        docLink.innerHTML = docLinkHtml;\n",
-              "        element.appendChild(docLink);\n",
-              "      }\n",
-              "    </script>\n",
-              "  </div>\n",
-              "\n",
-              "\n",
-              "    <div id=\"df-628d6697-813b-467d-b311-55143ccd38c1\">\n",
-              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-628d6697-813b-467d-b311-55143ccd38c1')\"\n",
-              "                title=\"Suggest charts\"\n",
-              "                style=\"display:none;\">\n",
-              "\n",
-              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
-              "     width=\"24px\">\n",
-              "    <g>\n",
-              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
-              "    </g>\n",
-              "</svg>\n",
-              "      </button>\n",
-              "\n",
-              "<style>\n",
-              "  .colab-df-quickchart {\n",
-              "      --bg-color: #E8F0FE;\n",
-              "      --fill-color: #1967D2;\n",
-              "      --hover-bg-color: #E2EBFA;\n",
-              "      --hover-fill-color: #174EA6;\n",
-              "      --disabled-fill-color: #AAA;\n",
-              "      --disabled-bg-color: #DDD;\n",
-              "  }\n",
-              "\n",
-              "  [theme=dark] .colab-df-quickchart {\n",
-              "      --bg-color: #3B4455;\n",
-              "      --fill-color: #D2E3FC;\n",
-              "      --hover-bg-color: #434B5C;\n",
-              "      --hover-fill-color: #FFFFFF;\n",
-              "      --disabled-bg-color: #3B4455;\n",
-              "      --disabled-fill-color: #666;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart {\n",
-              "    background-color: var(--bg-color);\n",
-              "    border: none;\n",
-              "    border-radius: 50%;\n",
-              "    cursor: pointer;\n",
-              "    display: none;\n",
-              "    fill: var(--fill-color);\n",
-              "    height: 32px;\n",
-              "    padding: 0;\n",
-              "    width: 32px;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart:hover {\n",
-              "    background-color: var(--hover-bg-color);\n",
-              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
-              "    fill: var(--button-hover-fill-color);\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart-complete:disabled,\n",
-              "  .colab-df-quickchart-complete:disabled:hover {\n",
-              "    background-color: var(--disabled-bg-color);\n",
-              "    fill: var(--disabled-fill-color);\n",
-              "    box-shadow: none;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-spinner {\n",
-              "    border: 2px solid var(--fill-color);\n",
-              "    border-color: transparent;\n",
-              "    border-bottom-color: var(--fill-color);\n",
-              "    animation:\n",
-              "      spin 1s steps(1) infinite;\n",
-              "  }\n",
-              "\n",
-              "  @keyframes spin {\n",
-              "    0% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "      border-left-color: var(--fill-color);\n",
-              "    }\n",
-              "    20% {\n",
-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "    }\n",
-              "    30% {\n",
-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    40% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "    }\n",
-              "    60% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    80% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "    90% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "  }\n",
-              "</style>\n",
-              "\n",
-              "      <script>\n",
-              "        async function quickchart(key) {\n",
-              "          const quickchartButtonEl =\n",
-              "            document.querySelector('#' + key + ' button');\n",
-              "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
-              "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
-              "          try {\n",
-              "            const charts = await google.colab.kernel.invokeFunction(\n",
-              "                'suggestCharts', [key], {});\n",
-              "          } catch (error) {\n",
-              "            console.error('Error during call to suggestCharts:', error);\n",
-              "          }\n",
-              "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
-              "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
-              "        }\n",
-              "        (() => {\n",
-              "          let quickchartButtonEl =\n",
-              "            document.querySelector('#df-628d6697-813b-467d-b311-55143ccd38c1 button');\n",
-              "          quickchartButtonEl.style.display =\n",
-              "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
-              "        })();\n",
-              "      </script>\n",
-              "    </div>\n",
-              "\n",
-              "    </div>\n",
-              "  </div>\n"
-            ],
-            "application/vnd.google.colaboratory.intrinsic+json": {
-              "type": "dataframe",
-              "variable_name": "test_tsdf"
-            }
-          },
-          "metadata": {},
-          "execution_count": 6
-        }
-      ],
-      "source": [
-        "test_tsdf.head()"
+      "text/plain": [
+       "README.md: 0.00B [00:00, ?B/s]"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "CqNGS6a0HS_5"
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e0ce26fdeefc4061879dbd285a3ec436",
+       "version_major": 2,
+       "version_minor": 0
       },
-      "source": [
-        "## Prediction"
+      "text/plain": [
+       "monash_tourism_monthly/train-00000-of-00(…):   0%|          | 0.00/335k [00:00<?, ?B/s]"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "iAh9dvY5HS_5"
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e369aa70fe3d4923ae127eab8a8d1490",
+       "version_major": 2,
+       "version_minor": 0
       },
-      "source": [
-        "Now, let's perform prediction.\n",
-        "\n",
-        "We provide two options, `TabPFNMode.LOCAL` and `TabPFNMode.CLIENT`, as the backend for TabPFN.\n",
-        "\n",
-        "- `TabPFNMode.LOCAL` uses your local machine to run TabPFN.\n",
-        "- `TabPFNMode.CLIENT` uses TabPFN's inference service provided by [tabpfn-client](https://github.com/automl/tabpfn-client)\n",
-        "\n",
-        "For this demo, we'll use `TabPFNMode.CLIENT` to perform prediction. If you have not use the client before, you'll be prompted to create an account.\n",
-        "\n",
-        "Note: if your machine doesn't have a GPU, using `TabPFNMode.CLIENT` is recommended -- must faster 😉.\n"
+      "text/plain": [
+       "Generating train split:   0%|          | 0/366 [00:00<?, ? examples/s]"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from datasets import load_dataset\n",
+    "from tabpfn_time_series import TimeSeriesDataFrame\n",
+    "from tabpfn_time_series.data_preparation import generate_test_X, to_gluonts_univariate\n",
+    "\n",
+    "prediction_length = dataset_metadata[dataset_choice][\"prediction_length\"]\n",
+    "dataset = load_dataset(\"autogluon/chronos_datasets\", dataset_choice)\n",
+    "\n",
+    "tsdf = TimeSeriesDataFrame(to_gluonts_univariate(dataset[\"train\"]))\n",
+    "tsdf = tsdf[\n",
+    "    tsdf.index.get_level_values(\"item_id\").isin(tsdf.item_ids[:num_time_series_subset])\n",
+    "]\n",
+    "train_tsdf, test_tsdf_ground_truth = tsdf.train_test_split(\n",
+    "    prediction_length=prediction_length\n",
+    ")\n",
+    "test_tsdf = generate_test_X(train_tsdf, prediction_length)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "cKH8WtXdHS_4"
+   },
+   "source": [
+    "Let's take a look at the time series data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 607
     },
+    "id": "jOm8_GLEHS_4",
+    "outputId": "cbffcec8-67f1-40e1-8d66-1aab471e9f32"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "v_gi5gDFHS_5",
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 721
-        },
-        "collapsed": true,
-        "outputId": "7c0a617b-7fbb-4534-c392-92ea999c146a"
-      },
-      "outputs": [
-        {
-          "output_type": "error",
-          "ename": "AttributeError",
-          "evalue": "'list' object has no attribute 'exists'",
-          "traceback": [
-            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
-            "\u001b[0;32m/tmp/ipython-input-1981978721.py\u001b[0m in \u001b[0;36m<cell line: 0>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mtabpfn_time_series\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mTabPFNMode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mTabPFNTimeSeriesPredictor\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m predictor = TabPFNTimeSeriesPredictor(\n\u001b[0m\u001b[1;32m      4\u001b[0m     \u001b[0mtabpfn_mode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mTabPFNMode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLOCAL\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0;31m# adapt this to TabPFNMode.CLIENT if using API\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m )\n",
-            "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/tabpfn_time_series/predictor.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, tabpfn_mode, config)\u001b[0m\n\u001b[1;32m     37\u001b[0m         }\n\u001b[1;32m     38\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtabpfn_mode\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtabpfn_mode\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 39\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtabpfn_worker\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mworker_mapping\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mtabpfn_mode\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     40\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     41\u001b[0m     def predict(\n",
-            "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/tabpfn_time_series/predictor.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     33\u001b[0m         worker_mapping = {\n\u001b[1;32m     34\u001b[0m             \u001b[0mTabPFNMode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCLIENT\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mlambda\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mTabPFNClient\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 35\u001b[0;31m             \u001b[0mTabPFNMode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLOCAL\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mlambda\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mLocalTabPFN\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     36\u001b[0m             \u001b[0mTabPFNMode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mMOCK\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mlambda\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mMockTabPFN\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     37\u001b[0m         }\n",
-            "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/tabpfn_time_series/tabpfn_worker.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, config, num_workers_per_gpu)\u001b[0m\n\u001b[1;32m    240\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    241\u001b[0m         \u001b[0;31m# Download the model specified in the config\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 242\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_download_model\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"tabpfn_internal\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"model_path\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    243\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    244\u001b[0m     def predict(\n",
-            "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/tabpfn_time_series/tabpfn_worker.py\u001b[0m in \u001b[0;36m_download_model\u001b[0;34m(model_name)\u001b[0m\n\u001b[1;32m    288\u001b[0m         )\n\u001b[1;32m    289\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 290\u001b[0;31m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mmodel_path\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexists\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    291\u001b[0m             download_model(\n\u001b[1;32m    292\u001b[0m                 \u001b[0mto\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmodel_path\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-            "\u001b[0;31mAttributeError\u001b[0m: 'list' object has no attribute 'exists'"
-          ]
-        }
-      ],
-      "source": [
-        "from tabpfn_time_series import TabPFNMode, TabPFNTimeSeriesPredictor\n",
-        "\n",
-        "predictor = TabPFNTimeSeriesPredictor(\n",
-        "    tabpfn_mode=TabPFNMode.LOCAL,  # adapt this to TabPFNMode.CLIENT if using API\n",
-        ")\n",
-        "\n",
-        "pred = predictor.predict(train_tsdf, test_tsdf)"
+     "data": {
+      "image/png": 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dhEWLFuGCCy6gxwqCgGeffRYXXnghCgoK8NBDDwEAnn32WQwZMgQmkwnDhw/Hyy+/TH9n//79EAQBGzdupM+1t7dDEASsWLECQLiKvGzZMkyePBn5+fk47bTTsGPHjohzffTRR1FVVYXCwkLceOONcLvdcddltVpRXV1NH3q9HoWFhfTvV155JW677TbccccdKC8vR319fdJz3b9/P2bMmAEAKCkpgSAIEddRMBjEPffcg9LSUlRXV2Pu3LkpvhscDofD4XA4HE7m2NLQCbvHD39QxHEHm5V9py9U8eZSc04sRFGE0+tX5SGKoqJzbGtrw8cff4zZs2ejoCD2TLxoSfbcuXNx8cUXY/PmzfjpT3+Kt99+G7fffjt+/etf47vvvsMtt9yCG264AcuXL0/5/9nvfvc7PP744/j6669hMBgiFBBvvPEG5s6di4cffhhff/01ampqIpQP6fDSSy/BZDJh1apVWLBgQdLj+/fvj//9738AJK+Bo0eP4umnn454vYKCAnz55Zf405/+hHnz5mHp0qU9OkcOh8PhcDgcDiddvjlwnP7Z7vGreCbp4yau5r2o4t17/Nk1gMsXwKj7l6jyb2+dV498U/K3c/fu3RBFEcOHD494vry8nFaTZ8+ejf/3//4f/dlPfvIT3HDDDfTvP/7xj3H99dfjF7/4BQDgzjvvxNq1a/HYY4/R6rBSHnroIZxxxhkAgN/85jeYNWsW3G43LBYLnnrqKdx444248cYbAQB//OMf8cknnySseifjpJNOwp/+9Cf69/379yc8Xq/Xo7S0FABQWVnZbb78uHHj8Ic//IG+9t/+9jcsW7YMZ511VtrnyOFwOBwOh8PhpMuGQ+30zw5PQL0T6QFO4mrOK96c3sZXX32FjRs3YvTo0fB4PBE/mzx5csTft23bhmnTpkU8N23aNGzbti3lf3fcuHH0zzU1NQBA3eq3bduGKVOmRByfyJVeCZMmTerR70cjP39AWoPcbZ/D4XA4HA6Hw8klG2QVbwejFW+Xj1e8OQnIM+qxdZ465m1K+x+GDh0KQRC69VIPHjxYep0YM87jSdLjoQvNRZTL330+X8xj5UZtROIeDAZT+vdSIXotqZxrLKKN5gRByOr5czgcDofD4XA48WjscKOhI6wOZVVqTuZ48x5vTkwEQUC+yaDKQ+morLKyMpx11ln429/+BofDkdY6R44ciVWrVkU8t2rVKjpDvaKiAgBw9OhR+nO5eVkq/86XX34Z8dzatWtTfp1EKDlX4nweCLAp1eFwOBwOR8uIoohHPtyG37/znWLPGg6HE5sNB49H/J31indvcjXnFe8TkGeeeQbTpk3D5MmTMXfuXIwbNw46nQ7r1q3D9u3bk8qx7777blxxxRU4+eSTMXPmTLz//vt466238MknnwCQquZTp07Fo48+itraWjQ3N+O+++5L+Txvv/12XH/99Zg8eTKmTZuGV199FVu2bKHV+Uyg5FwHDhwIQRDwwQcf4LzzzkNeXh6sVmvGzoHD4XA4nBOZf605gOdW7gUA/Hz6EPQp7q6+43AygsUCfPVV+M+9kG+iAm9WK95OXvHm9AaGDBmCDRs2YObMmbj33nsxfvx4TJ48GX/9619x11134cEHH0z4+z/84Q/x9NNP47HHHsPo0aPx3HPP4cUXX8T06dPpMf/85z/h9/sxadIk3HHHHfjjH/+Y8nn+6Ec/wu9//3vcc889mDRpEg4cOICf//znKb9OMpKda9++ffHAAw/gN7/5DaqqqnDbbbdl/Bw4HA6Hw4nFF7tacd0/v8Jdb27C/OW78cG3DfjuSAf8gd7R1rS9sRMPLQ57xLBaneMwgl4PnHKK9NBLAZ3d48dF81fhkQ9T9yrSIt8cbAcAWM1SfZVVczU37fHuPXViQeSanrh0dnaiqKgIHR0dsNlsET9zu93Yt28famtrYemlGTOOOvBri8PhcDiE6/75FVbubOn2/IzhFXjxhlNVOKPM4fYFcNHfVmFHUxd97p3Z0zChf7F6J8U54ViypRG3vLweFYVmrPvdTLVPp0d4/UGMmbsEXn8QZ42qwtKtTbj59MH47Xkj1T61lDn9T8tx8JgT//t5HSYNLFX7dOKSKF6Mhle8ORwOh8PhcDQKqQDPGluDSyb2xdi+RQCAjbJxQazyyOJt2NHUhXKrGTVFUqLZySvenGzi9QJ//rP08HoBAN8ebgfQO9QWW492wusPoiTfiFE1UhDIqtSc9ngbe0/FmwfeHA6Hw+FwOBqF9DlePrkfnrhiAhZcI/mwsLqZJizb1oSX1hwAADx2+ThUhwJvh5dNWSyHEXw+4J57pEdois2mQx0ApM9aMMi2EPib0BixkweUoNBCpOZs3iuoq3kvMlfjgTeHw+FwOByORnFF9TlaQ//1BUR4/GwGqc1dbtz9328BADd+rxbTh1eiwMR2kHCi0OX24eU1+9HpVj56VcsEgyKteAOAw8v29bchpISZOKAYBWZ2P1OiKPbKOd488OZwOBwOh8PRKM5QIEA2nwXm8CaUVdOk/64/jGMOL0ZUF+Kec4YDCK+P9cCnt/Poh9vx+3e34OWQWoF19rc50OkOX3OsK0lIxXvigBIaeLO4Jm8giEBIfWDhruYcDofD4XA4nGxD5JZk82nQ62AxSts3FitZAHDcIfXWnjGsAmYDSShIQYKT0WTCiUAwKOLjrU0AgKZOt8pnkxk2yardALufKQBo7nTjSLsLOgEY178Y1lCSjsUEndsbntrAK94cDofD4XA4nKwTS25JxgR1udkMEpwxejd5xVv7bD7SgZYuDwA2q6ixIP3dBDuDQSqBjBEbVlUIq9lA21NY/Ew5fdI5G3QCjPreE672npVwOBwOh8Ph9CJ8gSB8AUluKQ+8ae8mgxtqIBx4x1qTk5uraZZPtjXRP9sZTfpE05sq3hsOhmTmA0sAyOd4s7em3misBvDAm8PhcDgcTi/G7WM3kHPJzl3e50iMyFitOpK+9TxTeEwQ62s6EfhkWzP9M6tJHzlefxBbGjoBAGUFJgBsX3/fhALvk/sXA5Al6Bis4lNVTC/q7wZ44M3hcDgcDqeX8ubXhzDi9x9h0bdH1T6VtCBVH50AmA3hLZuV8TFBtOItTyaE+lH5HG9tcqTdhW1HO+nfmZVkWyzA8uXA8uXY2eGD1x9EUZ4Ro/qEZl4zWsn3BYL49rAkmycVb/KZcnj9EEW2xqS5e6GjOcADb06GGDRoEJ566im1T0N1Fi5ciOLiYvr3uXPnYsKECaqdD4fD4ZzIPP/5PgDAuv3HVD6T9AhLsg0QBIE+z7KEFAgnFOQO7eF+VEYDul7OpyGZOUkA2VkdJ6bXA9OnA9OnY2NDFwBgXL+i8GeK0Ur+tqOd8ISSCIPLCwCE7xOiyF4LhzPKVLK3wAPvEwxBEBI+5s6dm9brrlu3DjfffHPKv3fgwAHk5eWhvLw84Xldf/31aZ0XoDwpsGnTJlx44YWorKyExWLBoEGD8KMf/QjNzc1Jfzced911F5YtW0b/fv311+OHP/xh2q/H4XA4HGVsO9qJHU3Sxpr1ADW6z7Gg15iryaTmpOLNaODT2yEy85mjqgCwKV+OZlNo5vWE/sVMj94CgA0hY7WTBxTTJF2eUQ9dKF/H2j2wN87wBgBD8kM4vYmjR8Nyu//85z+4//77sWPHDvqc1WqlfxZFEYFAAAZD8sukoqIirfN59913MWPGDLz00ksIBKQP2erVq3HppZdix44dsNkk6U9eXl5ar6+UlpYW/OAHP8D555+PJUuWoLi4GPv378d7770Hh8OR9utardaI/6ccDofDyQ3vbDxC/8xqFcsVcvaN7nNkeUwQEHtTTSvejK6pN2P3+LFmTxsA4IcT+mLRt0eZDVDh8wF//zsAYItrJABgXL9idLlbAbAXoBIaOlwAgKEV4T2nIAgoMBnQ5fHD7vGjUq2TSwOXTO3Tm+AV7xOM6upq+igqKoIgCPTv27dvR2FhIT788ENMmjQJZrMZX3zxBfbs2YOLLroIVVVVsFqtOOWUU/DJJ59EvG50VVkQBDz//PO4+OKLkZ+fj5NOOgnvvfdet/N59913ceGFF6KiooKeR2lpKQCgsrKSPrdixQpMnDgRFosFgwcPxgMPPAC/X7o5iqKIuXPnYsCAATCbzejTpw9+9atfAQCmT5+OAwcOYM6cObR6HotVq1aho6MDzz//PE4++WTU1tZixowZePLJJ1FbWwsAWLFiBQRBwKJFizBu3DhYLBZMnToV3333Xdz/33Kp+dy5c/HSSy/h3XffpeeyYsUKRe8bh8PhcJQTDIp4f2MD/TvrleHoqg/rslhqrhajx5vVwKc388WuFngDQQwsy8f4/kUA2OwbBgB4vcBttwG33Yb9RyUzsvH9imTXH5uJH6eHtG9EBqqsGqyR5ByXmnOS43DEf7jdyo91uZQdm2F+85vf4NFHH8W2bdswbtw42O12nHfeeVi2bBk2bNiAc845BxdccAEOHjyY8HUeeOABXHHFFfj2229x3nnn4aqrrsKxY+E+u/b2dnzxxRe48MILE77O559/jmuvvRa33347tm7diueeew4LFy7EQw89BAD43//+hyeffBLPPfccdu3ahXfeeQdjx44FALz11lvo168f5s2bh6NHj0ZU/OVUV1fD7/fj7bffTvpFcvfdd+Pxxx/HunXrUFFRgQsuuAA+X/Jep7vuugtXXHEFzjnnHHoup512WtLf43A4HE5qrNt/DA0d4e9bVoO5WPOuATAvi405TszEx4lpFSIz/8GIKqb7hqMRRaBPkQWVNgusZiMAdpN0JAkn902Q/521e0W8pCPr8MA7G1it8R+XXhp5bGVl/GPPPTfy2EGDYh+XYebNm4ezzjoLQ4YMQWlpKcaPH49bbrkFY8aMwUknnYQHH3wQQ4YMiVnBlnP99dfjxz/+MYYOHYqHH34YdrsdX331Ff354sWLMW7cOPTp0yfh6zzwwAP4zW9+g+uuuw6DBw/GWWedhQcffBDPPfccAODgwYOorq7GzJkzMWDAAJx66qm46aabAAClpaXQ6/UoLCyk1fNYTJ06Fb/97W/xk5/8BOXl5Tj33HPx5z//GU1NTd2O/cMf/oCzzjoLY8eOxUsvvYSmpia8/fbbCdcASLLzvLw8mM1mei4mkynp73E4HA4nNd7dJFW7+5dKbUqsbToJxNm3u9Q8FHgzGCSIohhhGkeQOzBztEMgKGL59lB/98jKiL5hVj9Xcsb1KwYgb99gc02k4p0XJc1m1YjRFUMV0xvggTenG5MnT474u91ux1133YWRI0eiuLgYVqsV27ZtS1rxHjduHP1zQUEBbDZbhFEZkZknY9OmTZg3bx7tl7Zarbjppptw9OhROJ1OXH755XC5XBg8eDBuuukmvP3221SGngoPPfQQGhsbsWDBAowePRoLFizAiBEjsHnz5ojj6urq6J9LS0sxfPhwbNu2LeV/j8PhcDiZx+sPYvFmSd3041MHAGBPZkmIV/UpYHQzDQDeQBCBoKQsy4vR4+1k9L3qrWw81I42hxeFFgNOqS2V+oYZV1zIGR8985rRxA+teMe7VzC2LiI1j1b7sI5qgfeRI0dw9dVXo6ysDHl5eRg7diy+/vpr+nNRFHH//fejpqYGeXl5mDlzJnbt2hXxGseOHcNVV10Fm82G4uJi3HjjjbDb7RHHfPvtt/j+978Pi8WC/v37409/+lP2F2e3x3/873+RxzY3xz/2ww8jj92/P/ZxGaagoCDi73fddRfefvttPPzww/j888+xceNGjB07Fl6vN+HrGI3GiL8LgoBgMAgA8Hq9+OijjxQF3na7HQ888AA2btxIH5s3b8auXbvo+7pjxw4888wzyMvLwy9+8QucfvrpiuTf0ZSVleHyyy/HY489hm3btqFPnz547LHHUn4dDofDYY3vjnRgwco98PqDap9Kj/hsZwvanT5UFppx1kjJgbmL0dFHsdy/AVnFm8HAxyWTJ8eSmnsDQeavwd7EJ6ExYtOHV8Kol8KGQoYVF9GM7yf1rLOeTIilIgHYXVe8NhvWUcUq7vjx45g2bRpmzJiBDz/8EBUVFdi1axdKSkroMX/605/wl7/8BS+99BJqa2vx+9//HvX19di6dSssFgsA4KqrrsLRo0exdOlS+Hw+3HDDDbj55pvx2muvAQA6Oztx9tlnY+bMmViwYAE2b96Mn/70pyguLk5r9JViogJXVY7NIKtWrcL111+Piy++GIAUCO/fv79Hr7lixQqUlJRg/PjxSY+dOHEiduzYgaFDh8Y9Ji8vDxdccAEuuOACzJ49m1aqJ06cCJPJRB3TU8FkMmHIkCHdXM3Xrl2LAQOkKsrx48exc+dOjBw5UvFrpnMuHA6Hk21+/+532HCwHcOqrDhzRJXap5M2xM38gvF9YMuTEsAObwCiKMY12NQqYal5ZJ2EZXM1sqE26XU0kAOAfFlvqtPrh8nAfivWF7ta8fHWRvxu1kiYDWwGEMtCgffMkWFPbJYVF3IEARgTCrxZlWQTyHlH93izui5y78vvZVJzVQLv//f//h/69++PF198kT5HnKMBqdr91FNP4b777sNFF10EAPjXv/6FqqoqvPPOO7jyyiuxbds2fPTRR1i3bh2VRv/1r3/Feeedh8ceewx9+vTBq6++Cq/Xi3/+858wmUwYPXo0Nm7ciCeeeCK7gXcv46STTsJbb72FCy64AIIg4Pe//z2tXKfLe++9p6jaDQD3338/zj//fAwYMACXXXYZdDodNm3ahO+++w5//OMfsXDhQgQCAUyZMgX5+fl45ZVXkJeXh4EDBwKQHNc/++wzXHnllTCbzSgvL+/2b3zwwQd4/fXXceWVV2LYsGEQRRHvv/8+Fi9eHHGdAlIPfFlZGaqqqvC73/0O5eXlimdzDxo0CEuWLMGOHTtQVlaGoqKibsoADofDyTW+QBBbGjoBAG32xGomLWP3+GmF7ocT+tIAIRAU4fYFmaueEPfveFUsFiX08SpZRr0OJoMOXn8QDm8AxflqnF3mcHr9+OW/v8Fxpw/fG1qOs0fH9pjRMu1OL3Y2ScrK6cO6B96sVVGjGVxeAJtF2oOx7JsAJKp4E3M1tu4VvbXirYrU/L333sPkyZNx+eWXo7KyEieffDL+8Y9/0J/v27cPjY2NmDlzJn2uqKgIU6ZMwZo1awAAa9asQXFxcUQ/8syZM6HT6fDll1/SY04//fQIA6v6+nrs2LEDx48f73ZeHo8HnZ2dEQ8O8MQTT6CkpASnnXYaLrjgAtTX12PixIk9es1UAu/6+np88MEH+Pjjj3HKKadg6tSpePLJJ2lgXVxcjH/84x+YNm0axo0bh08++QTvv/8+ysrKAEiB8v79+zFkyJC488ZHjRqF/Px8/PrXv8aECRMwdepUvPHGG3j++edxzTXXRBz76KOP4vbbb8ekSZPQ2NiI999/X7FJ2k033YThw4dj8uTJqKiowKpVqxT9HofD4WSTPS12Ku9lrTIi5+MtjXD7ghhcXoAxfW3IN+ohMGwEFd/VXPo7iw7MrgRuxaQ/1cngexXNG+sO4bhTanFod7LZ6tDpIokfPYryw0WCQgvDgbfZjHcefA43XPYHjBgULsSwnkxwxnM1p94JbK3L1UsDb1Uq3nv37sWzzz6LO++8E7/97W+xbt06/OpXv4LJZMJ1112HxsZGAEBVVaTUraqqiv6ssbERlZWRo+ANBgNKS0sjjpFX0uWv2djYGCFtB4BHHnkEDzzwQOYWqnGuv/56XH/99fTv06dPjzlKa9CgQfj0008jnps9e3bE36Ol57Fep729HQDwzTffoLOzE2eccUbM84p1HvX19aivr495/A9/+MOEFeepU6di06ZNcX8OAIMHD8bf//73hMcQvve978Wd3R39/3Tu3LmYO3cu/XtFRQU+/vhjRf8Oh8Ph5IotR8KJZgfDI4LeCc3uvmhCXwiCAEGQNp52jx92jx8VhWaVzzA14sktWZWPArIZ3jE21PkmA447fUxfg4CkIPnH5/vo3zsZ9RggQWi3KqqJ3esPBgM+6D8Ry+19MXdAGX063L7BZlsKUb8UxFPHMNaW4ooz0YF1VKl4B4NBTJw4EQ8//DBOPvlk3HzzzbjpppuwYMECNU6Hcu+996Kjo4M+Dh06pOr59Fb8fj/++te/cok1h8PhaAQiMwfYrvis2t0KALhoQnhMJdtBauyqD1mTyxegDuGs4PQlqHibe0fF+4NvG3Ck3UX/zqIyAQgnSazRfcOhincXo+9Tu1Nqp6kustDnyLUXCIrwMGbuFwyKNFCNNwGBNal5ImUMy6gSeNfU1GDUqFERz40cOZKOpyKzlqNnKDc1NdGfVVdXR4ymAqSA7tixYxHHxHoN+b8hx2w2w2azRTw4mefUU0/tJt/mcDgcjnpsaeigf2YxQAWAYw4vAkERJoMOg8rDZqQsy7LjS83DVS3WKllkXFi+sbvoknW5LyAp/has2AsgLMlm8doDwu+D/HoD2E5mwedD3efv47LNn8CqCyet5JVi1q4/EnQDsd4rNueTk3ufhVe8e860adOwY8eOiOd27txJe3Zra2tRXV2NZcuW0Z93dnbiyy+/pDOU6+rq0N7ejvXr19NjPv30UwSDQUyZMoUe89lnn0WMlVq6dCmGDx/eTWbO4SSDSOCLi4vVPhUOh8PJGKIoYutR9ive5LxtlqiNZ8g8ibWNJxC/6mM26GDQSVJY1sygEknNaT8qw1Lz5TuasaOpC1azAT+ZIk1AYXWcXTz5MtNGZF4vfv3vR/HY4qdg1YUr2zqdQD0GWFsXSb7pBOneIIfVZBZtszGp0hWdNVQJvOfMmYO1a9fi4Ycfxu7du/Haa6/h73//O+0bFgQBd9xxB/74xz/ivffew+bNm3HttdeiT58+tJd35MiROOecc3DTTTfhq6++wqpVq3DbbbfhyiuvRJ8+ksTsJz/5CUwmE2688UZs2bIF//nPf/D000/jzjvvVGPZHA6Hw+FojkPHXBEVORYDVCBcVbTGq/gwVhkG4vc5CoLA7EineJJY+XMsvlcEUu3+yZQB6FecB4DdircjnmEXo/LlaOL1Q7MWpDplCZLo3nRW7xNU7dPLKt6qpBFOOeUUvP3227j33nsxb9481NbW4qmnnsJVV11Fj7nnnnvgcDhw8803o729Hd/73vfw0Ucf0RneAPDqq6/itttuww9+8APodDpceuml+Mtf/kJ/XlRUhI8//hizZ8/GpEmTUF5ejvvvv5+PEuNwOBwOJ4RcZg6wOaIKCFepCi2R/iFkc81i8BOWmnffrlnNBnS4fOwFCXHGHgHhIMHJ6DW4/sAxfLX/GEx6HW78Xi3W7GkDAHR5WK14x5OasylfjiaWhL65y8PcukiCJN/cPUhltS2AJh17WY+3avX7888/H+eff37cnwuCgHnz5mHevHlxjyktLcVrr72W8N8ZN24cPv/887TPMxk9nWfN4UTDrykOh5NLiLFaudWEVruXuUCOQJyju1W8LWxuPAHARed4J9pQsxWkOhOYJrFe8X42VO2++OS+qLJZmO/xpoF3tNSc4XFivkAQJDXXWxzAyWcqej3y51hTJ/BxYpwITCYTdDodGhoaUFFRAZPJxNzoAY62EEURXq8XLS0t0Ol0imeDczgcTk8gFe9Ta0uxeHMjkwEqEA4CCqN7vBmVjwKJR+oQ+S9r61KWTGBrTQCwr9WBT7Y1QRCAm88YDCC8HmYDbxLQRSWzwsEce+tyePwoDv25u4SefKbYClLJ56W3VLz9gSC8AakIFT1KkXV44J0mOp0OtbW1OHr0KBoaGtQ+HU4vIj8/HwMGDIBOp4oFA4fDOcH4LlTxPnUQ24E37fHuRYF3PFdzgOF+1ARrIvJzFud472iUPkfj+hVjSIUVQLjtgV1ztcTjxFi79oDIwNugj9xnWc3S+8WauVri9g3pvSOjB/U67RcJ5S7tvOLNoZhMJgwYMAB+vx+BAHtfEhztodfrYTB0N8fgcDicbNDc5UZLlweCAEweVAqAzc00EN4s26J7vBl2YE40y7aQUQl9ojWxPMebJH5K8sPXH+tSczutpPaecWKJkjqs9q6HWwLiJ+gASUIffX/UIiTwFmK4tLMOD7x7iCAIMBqNMBq1fyFzOBwOhyOH9HcPLi9ARaEZgLQxFUWRuQRgV5webxqgMta36QsE4Q9Kc4ZjzrxmVO7roOPEuq+J5Yp3LFd9EuR4/EF4/UGYGAsiqFt2tNScUbUFAHSJevziot+g3GrCPLM54mesrotWvM3dP1Nk9KA/KMLhYSTwljmas/Y9lAweeHM4HA6Hc4KyNRR4j+5TRDedgaAIjz8IC2O9dV1xerxZdTWXz7K2mLoHbKyPCYrVu0kr3owlSYDYHgPytocutw9lVnO339MydJxYVCW1UHbtsZakcwSAxSO+h5E1NsDQOyr58d4nIDx6sMPlY2ZdiUYOsg5bqTcOh8PhcDgZgxirje5jiwiEWKv4AAl6vBmXZOt1Akz67ts1VnvXE0rNGXVgBsLvg7zirdcJNBhiLfEDhNcUr+IdFCP7cVkgXt86wLCruSd+jzcgv1ew8V6R5BxryV8l8MCbw+FwOJwTlC2yirdOFiSwFqQC8ed4sxqgkqpvfhy5ZW+Uxeb3gh7v6OsvbLDG3ppIQBfdvpFv0oNckqx5Jzgcbpy3/QtM/3Yl4I88d1Zd6GnFO0YyAQgnuVj5XLkTJOdYh0vNORwOh8M5Ael0+3CgzQlAqngDUjDn8AaY23gCQJdH6vEujGsExUa1h0AqiZY4m09mK/kJZKSk4u1kssc7vsdAYyebzubUXC3qvRIEAVaTAV0eP+wePyrVOLk0cdudeObdR6W//PlXEXJzVqXmySrerCXpnLIe794Gr3hzOBwOh3MCsi1U7e5TZEFJgQkAuxtPQF7xji2LZS3wSSTJBuQOzGwFqaSSn2g2OWtSX0AmNbd0D7wBoJPBZBZ5H6KTCYDcY4Ct6y+RcR+7a4qdICFYGZPQk+RcbxslBvDAm8PhcDicExIiMx/Vp4g+x2qPIxC/xzvsai65tbNCsqoPq67mzgQJBVKxczIW+ACyxE+3ije7s7zjuZoD4c8ZUZqwQqJ7G0n8sPqZKohb8SbrYuNz5eIVbw6Hw+FwOIQtDR34at8xtU+jR4T7u230OdY2aHLCruax53gTt3ZWSFb1YbF3XRRFWSU/fhXVG5DGb7GEPc71x+osb68/CG9Aeg9iBXTMVocTfF5YqwwTyJry4/R4szYBIdyO0vs6onngzeFwOBxOCrh9AVz597W4+oUv0e70qn06aSN3NCewKjX3+AM0UOtmBCWrmrAU/CSVmjPY4+2VzSaPlVCQr5W1kWLJFBcsXXtA5HUVy7SrkCZ+GKt4J0gUkPeONcO4ZBVv1u7rVO3DpeYcDofD4ZzYrNnThi63H15/EC1dHrVPJy3cvgB2NdsBAGP6xpCaM7JBI8g3ytGBt04nMLfxBORS895hmASEkwlA7ISCUa+DySBtTRP14mqR+OZqbErNSdXXbNDBEGOcHavqmIRSc0bbN5L1eLN2r3Al8IFgHR54czgcDoeTAp9ub6Z/ZtEwCQB2NdkRCIooyTeipshCn2dtg0Yg1cQCkx56XazRW+z1biqVmjs8fmZ610kywagXYIwRzAGgI+1YGX0ESBL6sNQ8KvBmdURVgv5uALCajaHj2FpXIv8A8pny+IPwB9hpdUjUiw+wV/FONPmAdXjgzeFwOByOQkRRjAi8WQrk5DR0uAAAA8sKImZEs7ZBI8TrryWw2A/tks3xjgXZZAfF8EZV6ygZE0T6OlmqeLt8AYQU9DHHiQFsXXtA+HzjzYYmrvqsybLbAwLuOu8OfPfHpwCTKeJn8sCVpd71pBVvE1sTEMh9wsIr3hwOh8PhnLjsarbjSLuL/p01+SiBVN+K8qKMyKjUko0NGqGTyHwtiSs+LAUJyfoc5QE5K0EdkZrHq8wBbCZ/yHWlE7oHPyQZ1MnYvYL02Md3ymYzodDpB/47diY6r7wKMEbe/0wGHUwhJYadEY8BURTDPd5xPlesvVe84s3hcDgcjgIOtjnx8toDTMn0UkFe7QbYCuTkdLqkIKD7zGtSGWFrXfFmeBOoERkjm2kg8dgtILp3nY1ECZ3hnWBDnc/gNUhaTqxmQ4SCBGDfXC2ufJnRSj5ZV6zZ5AB7BmsefxCBkNwi6RxvRt4rFzdX43A4HA4nOX9ash2/f+c7/HPVPrVPJSuQwJv0EbO2mSZ0uWNLs1nboBHirYdAqnYsvV9uX3JZNmuJEqeCShZ5r5wMSc0TtTqwaq5m72V9wwSXy4MZe9ah4rNPAH/3c2fND8IZYVjYuyre3FyNw+FwOJwENHW6AQCvrzvEjOGTUjqcPqw/cBwA8L2h5QDCs6NZgwQBtrzoijdbGzQCDXySVLFYChKUjNRh7f2iI9LiOLUD4aCcJXWC3R2/ispqxZuoE6xxe7zZuvYASZbtc7rx4n8fQM1VlwOe7lMpSOKHlXsFeZ8sRl1MY0lANq2Ckc8UHyfG4XA4HI4CyOZyb4uDBqm9hc92tSAQFDG00opRodnXrFWxCOR9ssWreDOyQSOQ9yGu1JzBICEsNU/eD82KLJYEM0qSCYncp7UGmWUd6/qz0Yo3G+8RgXxWeksVFYiUZceDtUp+shneAJhrSXHzHm8Oh8PhcJIj31y+vu6QimeSeZaHZOZnjqhkLuCJpjNOoFrA2AaN0JWsb5PBIIFKzU3xt2qsJUqUmCaxJvUFwve9WOZ+5DPm8gXgY8j7ImkvNGMBKqDsmmItoUD+/+fHUSYAMhUJI2viruYcDofD4ShAXgFe9O1RZivC0QSCIlbsbAEAzBheCRuj8lFCVxwzMhaDHkBBjzeDiRJqRJZAls1akKBIPk97vNlYEyALvGMEqfJgnKXrLzzHO4nUnKk1JT9X1tpSUql4szKf3KVA7cMqPPDmcDgcTkYQRZEGAOVWE1y+AN7fdFTls8oMmw6345jDi0KLAZMHldAAj5WAJxra491LzNXsCSqOAHuVYSC5qznA3vulZE0szvEOm6t1v/6Meh0sRmm7zVKiztELpeZKztVqYmtd4fcpefuGdLz2P1fcXC3DzJ07F4IgRDxGjBhBf+52uzF79myUlZXBarXi0ksvRVNTU8RrHDx4ELNmzUJ+fj4qKytx9913wx/lTrhixQpMnDgRZrMZQ4cOxcKFC3OxPA6HwzkhcXoDIO1z19YNAgD85+veITcnMvPTT6qAUa+jAQ+rFf3OOBVi2l/rDSCYpBdSSyjv8db+ppMQlporkGUzEtC5ksyGBsJrcjIS+ADhIC2eLJvFWd4Ob7I1hQNUVow0lQSdBYzdK5LN8AbYm0/uUpCgYxXVKt6jR4/G0aNH6eOLL76gP5szZw7ef/99vPnmm1i5ciUaGhpwySWX0J8HAgHMmjULXq8Xq1evxksvvYSFCxfi/vvvp8fs27cPs2bNwowZM7Bx40bccccd+NnPfoYlS5bkdJ0cDodzokCqOQadgJ9MGQCDTsCmQ+3Y3tip8pn1HDJGbMaISgDsOhUT4gWq8k02S9XhZK7mYak5O4EPlWUnqPpYzUR5wVaQkHCON4MV72StDizeLxxJxomR54Mi4PZpX74MKJSaMzaij9ynkwWprIweDAZFWvHmPd4ZxGAwoLq6mj7Ky6XRLB0dHXjhhRfwxBNP4Mwzz8SkSZPw4osvYvXq1Vi7di0A4OOPP8bWrVvxyiuvYMKECTj33HPx4IMPYv78+fB6vQCABQsWoLa2Fo8//jhGjhyJ2267DZdddhmefPJJtZbM4XA4vRri7Gu1GFBuNWPmyCoAwH8YN1lr6nRjS0MnBAGYPrwCQFjSzOo4MVLxtuVFBgpmgw6G0EgaFiSJBKWBD0trUlL1YS1IULImVgIEOSSRlazizZJChvz/L4jzXuXLgiJWZNl2jx8+vQH/vPLXwN/+BphM3Y4pYK19w5O8xxtgpzXA4w8ncXjFO4Ps2rULffr0weDBg3HVVVfh4MGDAID169fD5/Nh5syZ9NgRI0ZgwIABWLNmDQBgzZo1GDt2LKqqqugx9fX16OzsxJYtW+gx8tcgx5DX4HB6MyxJRNPFHwjiuMOr9mlwZHRGGXb96NT+AIC3NxyBx89OwBPNyh2Sqdq4fsUot5oByEcEsbORJrh9AXhDm5voircgCMxs0OQkcpUG2Nl0EkRRhNOX3GCIrosRdUK44p1gTQxWvKnUPM71Z7Owdf0B4XONV/HW6QTmpgU4PH749Qasqv8RMHs2YOyeqLMy9l7RincCV3OAHT8Iuakir3hniClTpmDhwoX46KOP8Oyzz2Lfvn34/ve/j66uLjQ2NsJkMqG4uDjid6qqqtDY2AgAaGxsjAi6yc/JzxId09nZCZfLFfO8PB4POjs7Ix4cDmus3tOKcQ98jJfXHlD7VLLG8u3NOOvJzzD5oU/w3ZEOtU+HEyLs7CttZk4/qQI1RRa0O334eEtTol/VNPvaHACAk/sX0+fIJsbtCzI1IggIv0+CEDYSksPKBk1Ob5vj7QuIdN5wIqk5c9U5kkxIsKZ8Fnu8SdIxST80S1JzJb3DrKkTkiUTAPbuFU6FDuCs3CuIzNxs0EEfUl/1JlQJvM8991xcfvnlGDduHOrr67F48WK0t7fjjTfeUON0KI888giKioroo3///qqeD4eTDmv2tMHu8eOhRVtx+LhT7dPJKPtaHfjpwnW4YeE67Gt1IBAUsb2xS+3TyhiiKKKh3cWMUU009qiKt14n4PJJ/QAAbzBsstbulIK64vxwdYTVEUFApCxWF2Njw9pmWu6mHy/wkW+mWfh8uWTV3kT90KyNdCLBdEKpOR0nxl7FO26rg5k9hQyVmieopIZNJtm4/hyeAHTBAMbs2gCsWAEEul9jVHHByP1Pias5wI5pnEuBDwTLaGKcWHFxMYYNG4bdu3ejuroaXq8X7e3tEcc0NTWhuroaAFBdXd3N5Zz8PdkxNpsNeXl5Mc/j3nvvRUdHB30cOsTuRpFz4kI2AG5fEA9+sFXls8kMgaCIP320HWc/uRKfbm+GUS+gslCS/Ha42NnIJOLQMSeuev5LnPbop3jtq4Nqn05a0KqjLPg5d2wNAGDToXY1TikjdIausSJZP7R8RBArlREC7e9ONvOakXXJ3fTjBT4kURIIihE9hFrF6QsbFZoM8bdqrFbnFDm1M7ImIHmrA4sVb4cCB3rW1DEOrx9mvw83/+FGYMYMwO3udgyL9z8geY83K34QLgWqGJbRROBtt9uxZ88e1NTUYNKkSTAajVi2bBn9+Y4dO3Dw4EHU1dUBAOrq6rB582Y0NzfTY5YuXQqbzYZRo0bRY+SvQY4hrxELs9kMm80W8eBwWEN+U12ypQnLdzQnOJoNvtp3DM+s2ANfQMQZwyrw0R2n4+zRUitJJ+OBtyiKePXLAzjnqc+wek8bAGBrA5ttLrFm2ZIESafbDz9jkmxCR4zAG2BzRBCgXJbNiqs5ue70OoEmQ6KRb+JYCH5cChzNAZl8lJH3ypVC37qTkTUBys3VOhm49gDJQ4U4lcdbExBONLBy/Sma402TCdquDBNoxTtJj3cBI/PJSSLBwivemeOuu+7CypUrsX//fqxevRoXX3wx9Ho9fvzjH6OoqAg33ngj7rzzTixfvhzr16/HDTfcgLq6OkydOhUAcPbZZ2PUqFG45pprsGnTJixZsgT33XcfZs+eDbNZ2uTdeuut2Lt3L+655x5s374dzzzzDN544w3MmTNHjSVzODmDGNKUWyW3zgfe28K0sRUAtDk8AIBJA0uw8IZTMKTCSqt1rAU9co60u3DtP7/C797+Dg5vgAZCrFbxY82GLsozQgipmdsZXVfcwJsxmS+hK1nF28SGJJEgTyQIQuyeQLkRlNYrPoCyyjDAXpDgVDD6iATlvoBITQC1TESrQ9KKNxv3QLmxXaKAjtwrWEhmAQrHiVnYuU8AyiverPV490ZHc0ClwPvw4cP48Y9/jOHDh+OKK65AWVkZ1q5di4oKaUzLk08+ifPPPx+XXnopTj/9dFRXV+Ott96iv6/X6/HBBx9Ar9ejrq4OV199Na699lrMmzePHlNbW4tFixZh6dKlGD9+PB5//HE8//zzqK+vz/l6OZxcQm6qs2cMRWWhGfvbnPjHZ3tVPque0emS1lSSb6IbazIGidUg1RcI4qp/rMXnu1phMerw+/NH4Q8XjAbA7prsMeSWBr2OBqysutCT90Pe4w2wKR8Fkle8WdmgEcKmfsk2nuxImJVuPumaGLkGnQrGicl/xkLV2+ULtzrEuwatjN0ryP93o16A2ZC8x5uVe4WS86SfKS8bfhBK53iz8l4pVfuwSuJvqSzx+uuvJ/y5xWLB/PnzMX/+/LjHDBw4EIsXL074OtOnT8eGDRvSOkcOh1XITbXKZsHvZo3E7a9vxN+W78ZFE/qif2m+ymeXHqSqbcsL37JIMEeCctZos3uxv80JvU7A4l99H4MrrFi2TfKlYDXwjhfQleSb0O704RjjgXc8qTkLgZwc8pmJLzVnoxeQkGyGN8FqNqAJHibeL7L5TDZOh5h2eQNBeP3BhP3gWsClwIHZqNfBZNDB6w/C4Q2gWONfWyTpoRPiBz821ireCty/AfZGb6UiNRdFKVGU7P+B2tA53kkTj2womVwKRg6yjLbv0BwOJ2XsspvwheP7YEptKfNGa2SzIpfGUqk5o0EqTSZYDBhcYQUQrqiyG3jHdpYuCa3ruJO9wDsYFGWJn8jALuzoy9b7FU6Q9A5ztWSO5gSWHMCVVIaBSMdprSdKvP4g/GREWrJ1mdhJ/nTKFBfxWh3IZ42VijfdRyiUL7Nyr1DSkpFn1IMMe2Dh+lNa8Sb3Cq2rSMjIwbw4fh2s0ztXxeGcwJAvCqtZD0EQ8OAPx0AnAB9vbUJzZ3cHTxYgFTqbJUbFm7GghxCrikr+TMZXsUa8kTqlBZLfwHEG19Xl8YOoDbtXvA30GJagruZ5vUVqnlg6T2DJiMzlI5vpxGsy6HUwG9hw15ePSFM6+oiFazDZKDHpZ4xJzRWMEgPYSmYByq4nQRCYMSIDlM1bB9gxV3MrnEvOKr1zVRzOCUzYvEb6eA+rKkSZ1YyWLg9a7B5U2ixqnl5axKo4kqCB2Yq3q/uaivKkALXT7UMwKMacsaxl4jn7luRL62JRak7eJ4tR163XkbW+TUJnkoo3a4ZdyUY5EVgavaXUXA2Q1uXxezWfUHDI+oaN+sR1H5ZmedsVeAyEK95sfF/ZlUrNGUpmAdK6/Ho9Gn83D9VFFsAYf/xgl8fPxD0w1TneWk9mpXLvYxEeeHNOaDYeaseLq/bBqNeh0GJAocUIm8WA6cMrMbTSqvbppYXd030TUJRnREuXh1kJMw1SY0jNWV1Tooq3KEpV1OgKq9bpopWfyK8WWvFmMPCO198NsLeZJoR7ohNXvFkIUIHk6yGwVJ1LxWDIajGgzeHV/LqcKawpnyGfAbsnlHBMcP0V0rFbAQSCIvQaT6oqmeENsNM3THB4/PDpjXDfcSdQXhD3OLKuLo+27+3+QBCekPN/8jnebCRUnSG1DzdX43B6Ic8s342PtzZ1e/61rw7i019Pz/0J9RD57M2CqMAbADoYlPoCsTfWZE0ObwD+QBCGJBUUrRErmWAy6JBn1MPlC6DD6WMv8I5jclUSCryPMdjjnTDwZiiQkxPLM0EOq+ZqVnMSczWGxgS5FPZ4A+xISJUYqxFYqngrSfzIf2ZnIKnqoF4xSqXm2t9bBIMiHZOm1IhM+0GqsrFvADtTHdwp3PtYhAfenBMa0kt70YQ+6FOch6ZON9765giOtrPZCy2fvSn/wixifPRWLKm5fCPT6fbTqiorxOuzLc43wtURYPK9ssfZgFJztV5X8WZUap7E1Zy1ijepOCrt8WahJ58aDCmUmgMMBAkKTaDkx7BwDSoZZ2c26KlTe5db+0lVxa7mjFx7QPgzpQsGULh5A2DUAxMnAvru1yMryUfiaG7QCTAlKT6w0hbgVDjRgVV44M05oSFf6pdM7IczhlXguMOLt745ApcvAF8gmLQPTWuQL4no2ZvFrAfe1FwtvFkx6HWwmg2we/zodPmYC7w7YvR4A1KAd7TDjXYXW0GqLxCks4djjRMDgGMMKi4SBd5WRs3VujyJe7xZMiEDUpeaa30zDaQmNS9gJUggs8mTVOaA8HuldQdmQG6ulvj6s1kMaLV7mUjU0cA7mXyZoXFiZE15AR8s0+qkJ+12oKC75JwVFYnc0Tyeoz6BlR5vso/orRVvtqIKDifDRPdDy3u0WJOPAt2N1Qg21gPvGHO8gbDLOYvO5rGk5gC76gT55yW6SkKSIu0MS82jEyQAeyOCCOR8i+K4mrNUxQKUBz4smaulJDVnpJJP12RMXvMJ93hr/xqM5asSC5buF0ol2VZG5MuAcsM4gJ22FKUzvOXH+AIiPH7tfq5SSTqyCA+8OSc00V+YRr0OFiMbo1liQQxOojcAdEwVY8EcIPWtE+lRdIWO5YRCvEoqqyPFyOclz6jvphShPd69VGpu17gBjxxRFOP24hNYk5p3Ku3xZsgIKiw1T76hLmQlSEjBrTjc463tNQHxvS2iCbemaP9+IR9Lmgh5FVUkcxc1Slg+r1xxofV7YCrtGwWyY7Sc0HKl0GbDIjzw5pzQ0MBbVikhX54sVlHjfbEU57MboMqrA9EVLRJ4Eyk6S8TqWwfYrXh3JpilXBqSmne5/fAFgjk9r56ixFyNhQoWwRlyVQbiV4itoaDH6w8y8X7ZU5zjzYIRVEpScxMbgbcrpR7vsAu41lFa8bYydL8ga0pmhEfW5A+K1F1bq9gVyucBdpKPSmd4A1J7Hiksaflekcr0AxbhgTfnhMXrD8Ib+qKQf2HSKhYDX47RxJNSFdEAVfsbzmhIQJdv6l5JZXmkWLhvvbu5mvRzttZkTzBL2ZZnBJmec5wxubmScWJ2t/arPQSy6dfrhLgbG3niTssbNIIScytAXhnWfjDn8qVQyWIkSHCkUvFmpG8dCFewk82RZ6niTYKfZJ8peRCr+evPQzwGFEjNGemHdqSQzALYqOS7aY9377Qh44E354RFfkOVS3BYrGIRnHFmb7IqXwZiG6sRaEKBgY1MNL1Nap5IbqnXCXRdxx1sratTgbmaPyjSMX5aJzxKzBDXjMeg18FsYKflhpxjvPFoBFYCVCA1WTYrQYIzjb51FpIkdJqDwh7vTgb2Fkr7oXU6ge6ftF6sUCqfB8J7Qq1ff7THW2GQyoLBWvje1ztD1N65Kg5HAfKeVPkMaGqAwlDfJsEeZ/Ymq/JlIBwoxJKRErM11qrDQAKpeUiWzdp7RZ2y42zUWO3zJgmQWIF3gUkPEruycr8ItwQo64fW+sZT7gGRrOLIkhFUKuZqrDhLu+KYf8aCrJuFHu9YLWuxYGn8IAnMlDjQs5LQUiqfB9hZE614K6jiA2y4tdMebwUmjCzSO1fF4SggXkaXSnEY+HKMJt7sTZZ7vOMFqAC7UvNAUJQ5S8epeDM2TizeDG9Cab4Je+Fgztk8kdRcEARYzQZ0uf3ocvtRWZjrs0udToWjtwrMBrQ5vJreoAGRiYHkPbah1oCQEVSy8TtqEt589p7AJ5XezQKGeryVm6sRV3Ptf18plZoDUsKhucuj6SoqIBsnlm8B/vAH6Ulj7PeskJFkFlWRKOyHZiGh6kpB7cMiPPDmnLDEG0FTSEdUafuGG4uwlCqOCZnbh2BQhE6n3Q1nNPF6oQG51Jyt98qewDAurE5ga02dSfpsacW7FwXegJT86XL7mUnUkSBBqSxb65tpkpgzG3QwGRKL+IgSKBAygrJo2LwnNak5G7JYlze2IisWpNLq1Pj1B8h6vJMEqTaGKt6pGJGx0DcMhO9lloI8YO7chMeycv9LRZkgP06r6xJFkc/x5nB6K2SjHL0JoIZJGr0xJSKZuZoosvGlLydhxZtRCT1Zk8Wog9kQ5UDPqBFeOJEVO6AjzubHGZKaB4Mifa/iBd4sORUD4esq+cxrbW/QCMmuOzksGUGFpeYKZLGMuJqHkwm9Z02iKCqeI89KFRVIbfQWC/JlQN6K13uk5tTVPNUeb422cHgDQTp1Q8uJ0Z7AA2/OCUu8ESBWhpxHowkbbUTesMwGPZX3sRekxt/UsOrWnqiKGjZXYydABRL34gPyHm923qsujx/ErDxW4gdgy6kYUC6LZWXjGa7gJ994smIEJa/6pCI179L4e0VmkyuRxYYDBI1X8X0BhOIEBa76bEjNg0ExpTFVrHgMUEWgUQC2bJEewdimmKwYFqZa8aYmpxo1b3V7w+9Hb614c6k554QlHHhHbkBZkoNFY/fGrngD0g3X5QuwF3i7iAtzrB5v0hbQe9ZE+vEd3gB8gWC3EWpaJVmPd0k++cJnJ6FA3ieLURc3+04Db41v0AjU1TxP2cxrrW887R5lo5wIVosBDm9A00GCvOqjRGoeHpOm3TUBqc3xJpVWrZurkfueTki+LlbM1UiCBFDY483KvSJ0LRXBD4wZE3rSDhQUdDuWFVf9VCveNTYLAKCpw521c+oJztAYRYNOYGbvkyq9c1UcjgLijZbojeZqALumXYmk5kWMzrxWMhtafhwLdCULvBl0NU/W3w0AVlrFYuN+odjVnBFzq2TXXTQsVPJdsv/nqYzecnoDCAa1O0+eBDFKkglEYu8LiPD6tTuqr0umnEtm1lfIyL2C7CN0AuhYwUSEe7y1fa8IV4eVJxO8gSA8fu2uK9U53tVFUuB9tFObgXdvN1YDeODNOYEhX37RlRJWvhxjEc9cDWB3pFiiOd7kuU6X5FLMComSCXqdQIMIlt4r+nkyJ+7xZklCryTwpn2bjNwvlEqzWQhQAfl1pyzwLmSgOkdk5kqrPvK1a7V3E4DMNEn5ODFA21Vvpa0b0jFsKLTkCXwlzv8FjBQr6P5IkcdA+PrTctXbmULfOgDUFOUBAI62u7J2Tj0hlckHrMIDb45iutw+NGpUnpIO8arDrElH5ZAviFjZzyJGR4olnuMtrckbCMLt025VJJpETu1AWG7ertE+rFh0JTEYYtHVXFHgTc3V2HivlFaI6cxrjW+mUwl8ADYSCqk4mgNSVVIfmlSh6SAhheqcUR92qdfye2VPIfFTKLv2WFAmKE1msWPEGNofKeiHNuh1sBil60/L60q34q3Vvby7lzuaA7zHm6MQXyCI+ic/Q0OHG4PLC3D6sAp8/6RyTB1cpjjTpjWoE2kvMlcjN+FeVfEmFboYwU+BSQ+9TkAg5D7NijwpWUBXlGfEIbiYktDTkTrx5ngXEFdzdtaUUsVbw5szObTHu5eME6M93oqDBO2/X2FHc2X3MzJPvsPlC/3/sGTx7NIn1YSC1WzAMb+X/p4WScVjgCSHRFH6rlaaLMo15LOh9Ppj4TMFxG8vjIfVbIDb59X0ulIxwQPCgXeXx48ut09z1yBZT291NAd4xZujkOYuDxpCGbK9rQ4sXL0fN770NU5+cCk+3d6k8tmlR1ecijfL5mpKerw7GKqiAnIjsu5rEgSBPs9SQiGR1BwAivOkIJWlNZHNSbwqPpGa2z1+TffMySH//+O9TwCL48ROXFdzgA0Pj1Qk2QQW+mxdKRpBkcBPy8mfVDwGLEYdDCFlgpbvF84ECfxYsHKvoIqLXrQuRxpJEnKtNmmwz7u3z/AGeODNUUhrlwcAUFFoxoKrJ+GqKQNQZTPD6w9i2bZmlc8uPeL1Q5MeVbuHrb5hIP6INCA8H5qlYA5IHqSyOFJMScUbYKcfWhTFpJLfQosBoT0nMxJ6ZRXvkCeEhjdncpKNfSNQp2IN99cCMqlvCq7mgLaDuXSqPlaNtzx4/UH4U3BqB8IBupYr3ql4DAiCwISzuT1BAj8WrKh+6LqMytZVnK99Q9BUXc0BoIYYrGlQbs7N1XLAo48+CkEQcMcdd9Dn3G43Zs+ejbKyMlitVlx66aVoaoqsqh48eBCzZs1Cfn4+Kisrcffdd8Pvj/zQr1ixAhMnToTZbMbQoUOxcOHCHKyod9JqlwLvapsF54ypxkMXj8Uvpg8FoO2bUiLi9WaRL5FAMDxLlQX8sj7nmBVvBnu8g0Ex3BIQZ2NNAnKtG9bISTRODAivqcOl7Y0MweUL0PFH8TagOp2AEgY2MnKUuZprO+CJpitB64acAgYqqEC4FSXVHm8tJ0pSGbtFqLSZAWi3dzNVp3Yg3Iur5SRJsu+naFiY5R32ikmtMqzl9ylif2TNA+66S3oY4983qgqlz1RzqPCkNURRDPd4K5TPAzKDNQ3eK8ieO09hcoRFVA28161bh+eeew7jxo2LeH7OnDl4//338eabb2LlypVoaGjAJZdcQn8eCAQwa9YseL1erF69Gi+99BIWLlyI+++/nx6zb98+zJo1CzNmzMDGjRtxxx134Gc/+xmWLFmSs/X1Jtrs0ka5zGqiz5E/tzGyiY6GVoejvjDzTXpamdOyHDEa+ezNmOZqDFa87V4/iOggbpBqYW9dYQlzEnM1Rka/KZ1lSwzWWJnl3dtczQNBMakJHqGAgaAHSL/HW8vrcqbY4w2Eq1haDbzJfF6jXvl83gKT9lUXiVRmsWCh4h2WmitUJjDQbiMfi1hQmA/8+c/Sw2SK+zskmdWsQUk2ALh9Qbo/Sqvi3a69daXqA8EiqgXedrsdV111Ff7xj3+gpKSEPt/R0YEXXngBTzzxBM4880xMmjQJL774IlavXo21a9cCAD7++GNs3boVr7zyCiZMmIBzzz0XDz74IObPnw+vV9rQLViwALW1tXj88ccxcuRI3Hbbbbjsssvw5JNPqrJe1mkJVbzLrWb6HDFLarNrMxuYjHhfmMSoBghXU1iAbCQNOiHm7E0blS+zE6CSyrDJoIsruwxLzdl5rxIZxgHsJUk6ZeqRRONnSJ83KwZrnYpczdkZPyiXgiqWmms4QAVSn+PNghEUqfqkIjUnVawGjQbedIZ3CmsKJ3+0q7pI1VWfhZFi1FxNYTKB3NfbHB7NtueR+5hJ5pafjKpCKUBt7tTmHleekErlc0WdzTu1N1KMuppzc7XMM3v2bMyaNQszZ86MeH79+vXw+XwRz48YMQIDBgzAmjVrAABr1qzB2LFjUVVVRY+pr69HZ2cntmzZQo+Jfu36+nr6GrHweDzo7OyMeHAkWmME3mUF0p9ZkY1Gk2jmNQtysGiSzd5kscc70QxvAqkas7WuxFLzYsb61sNyy8Sbz5IC6eesjBRLpeLNwr2CnKPZoIPZkHhjw0KACqQu9WVBQp+qqzkg79vU3mYakK9JeWWOVrw1fA2mXvEOe8holUR7o1iQQM7tC2o2sR/eH+mBYBDYv196BOOPIa2ySetq6tJmMsspGx+r0yWft07Qco83UVvwineGef311/HNN9/gkUce6fazxsZGmEwmFBcXRzxfVVWFxsZGeow86CY/Jz9LdExnZydcrthfTI888giKioroo3///mmtrzdCpOblMqk5qXi3u3y0v5Ml4knNAXbMQuTYk8zeZNGELDz6KP4GwMbgupSbq7GxJqWGXeGRYr0v8HZ4A5q/Dyp1NAciK95arWIBqVccWajkpyU1L5Yq3pqVmqfRt05aU7TczpZsjGI0LEjNHSkadlmMepSF3qsGjSZ+IgzjXC6gtlZ6xIkHAKAiJDVv0njFO5VkFgBUF2n3XsGl5lng0KFDuP322/Hqq6/CYtHWrMl7770XHR0d9HHo0CG1T0kzxKp4l+QbIQjSTEpWejYJHn8AvoC0mYxlRMbCl2M0ycZKkOChy+OHPxA/y6slqHFSgsCHVI21LN2T4/YF4PFL//97i9TcrlDu25vN1QDtJ+qUJLII5L4YFEFNibRIPJPMeLA0Tiw1qbm0n2po12bgQzxIUtlQkzUd0eiaANm9T+H1Z2NATRdRHVZITbF2+4aBcLuC0vsEEJaat2i14u1N/X0CtF3x5lLzLLB+/Xo0Nzdj4sSJMBgMMBgMWLlyJf7yl7/AYDCgqqoKXq8X7e3tEb/X1NSE6upqAEB1dXU3l3Py92TH2Gw25OXlxTw3s9kMm80W8eBIxAq8DXodlcSSijgryDddsbK6VA6m4c1ZNIlmeAORQR4rveuJZngTbIwFqSRBIAjxN2tF1FyNjTUprTqSwJuFRF0wKCoKvM0GPe0Z1H7gnTyRRcg36UE6VrS6LrcvAG8oiai4x5sBNVNPpOadbr8mq/mpzvAGgL6hKv5RLQfeCZRzsWAhqZ9sLxEL6pStUSOyVEekAWFztVa7Fz4NFitSdZ8nkNaADpePBu9agVe8s8APfvADbN68GRs3bqSPyZMn46qrrqJ/NhqNWLZsGf2dHTt24ODBg6irqwMA1NXVYfPmzWhuDs+PXrp0KWw2G0aNGkWPkb8GOYa8Bic1YrmaAzKDNYc2pTjxsMuqw/oYvTFhczU2Ah8gLDuKl9E16nX0Z6wFqYlGH7FmrkblvmZD3L4secVbyzJfAnmfklUTwq7m2r/+ujwyR/0kgWohdfXV9rq6PMor3oIgaL7HltzHBUF5QEc+W1pO/jjTkJAWWoz086fFSlY6G2oin2/QaBUVSL/VQduBdyhJklLgTSre2kySpJNMKM03wRD6jm7VoIkwrXinGKTaZPcKrcnN+RzvLFBYWIgxY8ZEPAoKClBWVoYxY8agqKgIN954I+68804sX74c69evxw033IC6ujpMnToVAHD22Wdj1KhRuOaaa7Bp0yYsWbIE9913H2bPng2zWcpQ3Xrrrdi7dy/uuecebN++Hc888wzeeOMNzJkzJ9dLZh5/IEjNkOQVb4Bdg7VkhigsZKWjsdMvy/g3LNYkzHTmcKKKt6X3JROKQ5Vhrz+oaZkvQanBVWnIXI2FHm+itjAncNQnsDJSLNzjrdSITFq3VqvD5P5gNcVPYkVTGZrN6/QGNLsuV+gzn4pTMaDtkWLpzCbvE5IvN3e5NVlxBGQ93goDOjIqUst7JkcaAZ2WZ0MD8sKE8jXpdAK9X2ixz7sn1eFqjcrNw3O8eeCdU5588kmcf/75uPTSS3H66aejuroab731Fv25Xq/HBx98AL1ej7q6Olx99dW49tprMW/ePHpMbW0tFi1ahKVLl2L8+PF4/PHH8fzzz6O+vl6NJTHNMacXoihVFUiFm0Aq4Fr+EolFsr5AFuSI0SjJ6IZHirHxfiVz/wZkFW+NVxsJHQrWVCBTYrCQUKABUC/q8Sb/38lGORFWRhJ11ATPrKw6V6BxIzK7wutOToHZQBUKTRqVxbrSdPalFWINGlylEySUF5hh0usQFLX5XomimLKrPh37ptHKMJBedZgkSbS6Lio1T1GWXUGczTV4/aVqgidHq33e6bTZsEbq71YWWLFiRcTfLRYL5s+fj/nz58f9nYEDB2Lx4sUJX3f69OnYsGFDJk7xhIbIzEvzTd1k2SQQb2Wsx5tmP+N8WbJggBKNU8EXC2sjxZRUh1lzNVcyG1oQBBTnGdHm8KLD5aPZaa1ip8qExAEddTVnIPGjpL+bQGd5azRAJVAFSV5qRmQOjfUBEpS66UdTaTOjq8WPpk43hlRYs3FqPSIdV3MAqLFp1+DKkcaadDoB1UUWHDzmREO7G/1K8rN1emnh8gVABhkorXj3LZEC7yPtLoiiGHP0p9qkY0Sm+Yp3GskEAKgKVbybuzRY8abz1tOoeNuIOkY7iZIOpw+HjjsBpGYsyRqarHhztEUsYzUCGSFxjLEe764kFW+Wx4kl+mJhbaRYeI53Iql5OOgJanycEyCr4icJfooYUieQ3uGkruah+4XTG6DupVollcA7XPHW9ueqkwaqCiveJm3PvO5K0jIUj8qQW3GzBuWjgKw6nKrUPFR1bOzUzmaa4Epz9BGppGpxPjlJOOoE5QkFYhjn9AY0Oy4y2YSUWMjbHLT4PRyRTDAYgF/8QnoYEl+PZJZ3M694ZxWHx4/rF36Fpk4PKgrNmDiwRO1TyhqaqHhztA0JvKON1YBwBYsF6aicZOYhLBigROPwJO9hYq3HW0mgQAJYUZQ24koCJTUhjvLJzpMlt/ZkiSxCodkAg06APyjiuNNLqyRaJKWKNys93grHvhG0LjVP1diKUGUjVSxtbDqjcacxeguQjxTT3rrSTSb0KQpXiLWGPPGjtHJtMepRbjWj1e7B4eMumozUCqIoJjVqjUWVzQJBALwhT6BYhRo1iXA1N5uBBIpaOeEebw1+pnpS8dbQLG+3L4CbX/4aGw62oyjPiJdvPDWpeo5leMWbkxQiNY9Z8Q49x9w4MVKhi1vxJn3D2txwxsLuTS6lomOqNJppj0aJNNZs0MNilG5lLFTylfStA+HeYhZGiikNgARBoMZxxx3aXhftxVcQeIdbU7R9v+hS2BJAIEk8rQbedmJslaLUvIr2bWq74p2y1FxDm+lo0u3d7ENHimlvTekmfsJyc2fGz6mnuH1BKp9PRZZtMujoHlGL75WSwkQsaMVbg1Lz3lDx9geC+NW/N2DV7jbkm/RYeMMpGFHdu0c588Cbk5QWBVLzNsYq3qQylazibde4dFSOQ0GPN6sV72SBAkvrUhrQsdQWkIqzL3U217iEPiWpOblfaDRAJZBrKdWKt1bXpWTqQSwqNWyYBMirw+nJsrVsrpZu4K1F065kJq3x6BcKvA8f1+CaZJ/11NUJ2r3+Iireogi0tEiPJOM6K2xadjVPvSWAEG5LUe8eKIoi7vnft/h4axNMBh2ev24yTh7QeyXmBB54c5LS2hV7hjcAlLLqak76feJs2FgcJ+ZMocebhQAVkPdDJ5FlU4WC9tdFzjFZQMeSEV4qzr6sOJunIzXX+vXXlWKPt1XjUvNkYyHjQaXmGtxMA+lLzYl8tMvt11yyxOkjgXdq71UNTSZoL0lClHOpKi76FWtXPi+fDa10RB+BGqxpcF0R5mpOJ1BZKT2ciVUHVSE/iBYNtqWkM2+dUGOT3qtjDq9qfitbj3birW+OQK8T8MxPJuK0IeWqnEeu4YE3JyltIeO0ihgVb7lLcUCDhhrxoF+YcW5YJJDT2uYlEeGMbvIebxbky6IoKu5JZcnZvCNlczXtr6krhd5hVpzN0zNX0/b9IlVX83DFW5vmamSaBmlfUAqVmmtwMy2KYtqVLKvZQD+DWnIrBtKb4w2Ezci0WPFO5b4npy8DFe+0grlibciXY5GOUzsQTtK12r2amyXfk4q3Lc9AFQ1qtaZsP9oFADhlUAlmjqpS5RzUgAfenKRQV/PCGBXv0IZHFNlwXyYkuwmTjbTTG4BfYzfbeCgxRCF9wywEqC5fgCZzlErNiQu6liHn2FvM1QJBkcpIlVRSSxgxZFQy9o1A1q19czVlrRsErZur7WySNm5DKgpS+j1SxWrqdENMIjXNNR5/uMc21Yo3oF2DtXTmeAPh9XS4fJq7DpWaSkZDkglHNBh496SKSozwtKlOSC+hUJJvgiFU+W/RWJ93T3q8BUFQvc97d4sdADC0UnsjHbMJD7w5SaFS84LuFW+DXkeDOZb6vJONoZE/z0rVW8mcSpak5iRA1euEpBld0uPJxLoUBj+kiqd1dYI82FSyAS0J3S+Oa/x+kdoc71DF26Pd98oXCMLtk5KISit0WpbQB4IidjVLgffwFM14KkNVLLcvqLnZ63LZZ6o9toB2DdbCPd6pBQmFFiO9DrU2UiyVFhs5ZB65FqXmDm9y5Vw8qulIMe2uK1VzNZ1OoM7mWjNY64mrOSB7v1QaP7i7ORR4V/DAm8OhiKJIpeblhbHHQxDpKEvO5smCVJNBB7NB+nhoXT5KoJnqXmKuFg5Qk49qoRVvDQYI0aRqrqb194r8PzcbdDAZkn+lkB7v4xqX0Pe2cWJdKSZIAKAidM/XWqUHAA4dc8LtC8Js0GFAaX5Kv2sx6mmyTmvzeUmAatQLMOpT36LVaNTgqiey2PBIMW29V+l6DBCpeYfLR30XtIISk9Z4UHM/jb1PgLLCRDwqNGrG6OxBxRsIB95qVbz3kMC7slCVf18teODNSUinyw9fQNK9lcWZN1nGiHRUjl1Bb1YhIyOCAKn64/IRiVjyHm+nNwCvX9sS+rADs4JxToz0eIuiqFjCzEpbQLjqo0y+zHu81YFs8AtMehgUBnRhSbb2Au/tjVK1+6QqK/QpmkAB2h0plu68a4LWK97pyOdJQKc10650x4lZzQZ6X9Fa1bsnASq59po63Zry/PH4A3Qfm866qjRa8e6JOgEIJ7TUuFd4/UEcOCYZ23GpOYcjg4wSKzQbYImzESAS9GMObd2UEqGk34dURFiQmpMbMJB4TYUWI0jxWOuV1FSMoIhsW+trsnv8tH9Tad+61r0TUjUYYqHHOxhUniABZEk6Dd8rSOtGKkECkWS3OTyaMxYi/d3Dq9Kb+Vql0SqWK01JNkGrLuDpzvEGtDtSLN2KNxAeKaa1Pu+e9HhXFpqhEwB/UKTeQFrAITOHTKc6TGd5a+xeQSbZpHuvqFbRD2J/mwOBoAir2UAN7E4UeODNSUibPbHMHAiPFGtlSGqu5AszXMXSdjAHhLPUBp1AJfKx0OsE2o+q9SA1FSOosNRcu4EPED4/k14HizHx7VcuNQ9qqHoQDZkQoDTwJoaMWu7xtntlCZIU5nh7/UF4/Np0AA+PElO+SSsNGQuJIjS1kQaAHY2kvzu9akmlRufzkrm6qfYNE2o02Gfb3OWGP/SBSidI7VOsTak5+UylOk4MkBmsaSyZ4PCk1wsNSJ4/JEjVUpKErCnPqJfUMQYDcN110sOQ/L0jPd5aStLZPX54Q8nQdKXmNSr2eJP+7iEVBUlbCXsbPPDmJIQE0+UxZngTWJOai6KoKPBmaZY3+WLJN+mT90Pnk4BO2+8XneGtSGrOSDJBNkpMad96UJQCQa2SasWbSM2PabiS3+EM963HU/rIiTBj1Oj9opMqSJRXvCOMhTQWoO4IVbyHVaXXH6jViveKHc0AgCmDS9P6/fAsZe2s68PNjQCACf2LU5ZlAzKpuYaSCYCsZS2NZIJWR4rZaS9+z4I5LY0U66ZwNJuBhQulhzl5tZVWvDUkNV/ynfSZqi0vUDweMpqwGV7u3yvS3z3kBJOZAzzw5iSBVDliOZoTShkLvD3+IO0/SpSptlKnYm1upOWkMqOyOE96vzQfpKYQ0LHS492RQjLBYtRT9UKHho3IUh2pQ3rX3b4glZ9qjVT6uwFJSULvF5oNvFOveANApQYDVI8/gH2tDgDAiBQdzQnhvk3trEsURSzfLgXeZ46oTOs1SODT5fFrRq31/qYGAMAF4/uk9fskmaClKioQnuSi9D4hhzqbayzwJvevdKTmgCzxo6HAm+xN06niA9pUx7y94QgA4OKT+6ZdMSbvVavdm3Ol1ok6SgzggTcnCW0JZngTyqzhPkAWkG+M8xNUs8LmatrYvCQiFUMU1tyylVToSCCrdVfzToWO5oTifO2/V6kaDFnNBhj10kZBqwZrqQbeQDjxoFVPiHSNoKjMUkPVnj3NUn+gzZJ+f2Al7dvUzrp2NHWhocMNs0GHusHlab1GgdlA/Um0YLDW0O7C1weOQxCAWWNr0noNIstu6NDO3HWPP4ADbVLyJ52qHVnTYY0lEzYdagcgSYDTgVa8NbSuRZuPAgDG9y+WnhBFwOGQHgqup8pCbfV4N3a4sWpPKwAp8E6XknwjnUSS6/vgiTpKDOCBNycJLVRqHn9zU8bYODGHTGauS+CGy8KIIIISszgCDbw1XEUFwmZQqfR4azlABZSPEiOwsC7a56iwQiIIAh0pplWVDPn/TRIfStDyzGsg/D7ZUqx4a9FYiBirjai2pV3tIQF7k4Yq3p+Gqt3Thpan5f5NoBViDQTei76Vgp5TBpVSaWuqVNksEATJQ6FNI/eMfa0OBEXpc1+ZwAMnHmFzNWemTy1tjjm82Hq0EwBQN6QsrdeoKdZWxdvp9eO9jZLi4keT+4eedAJWq/RwJv//X0VNJr2aMJl8Z+MRiCJwyqAS9E9xlKIcQRBUaQ0IBkXs4RVvDic2VGqeIPBmTWqu1Im0UOPSUTnE1VxJ8EOCvnYNB3OAvOKtfE1un3bNrYCwfF5pJZWFwJt8nlIJ6Mg9Qyub6GjSqnhrPFGXjqs5IAtQNRR40/7uNI3VgHAVq6nTo5kqKpGZz0hTZk4gzuZaMFh7/9ueycwBwGTQoSK0B9FK7/quJilwOKnSmlbyh1S8W+1euH3a+M5as6cNoggMq7LSz0eq9NHYHPnFmxth9/gxoDQfUwenl0woCZlMAkCLysofURTx9jeSzPySif16/HrhwDt379eRdhfcviBMeh0G9CBxwCo88OYkhEjNKxSYqx13ejXtvkwIV4cTVxRYkprbPcpHtbAgXwZSm+NdaDbQMWkkwNAiYcM4ZUFqUagfv13D6gTa451C4F2tQTminFSVCYD8fqHN6y8dV3NAJsnWkNScOpqnaawGhPs2vf6gJu6F7U4v1h84DiD9/m5CuCda3SB1f6sD3x7ugF4n4Nwx1T16rT4acwHfFUr+nFSZ3jVYnG9EQej7WitrIvLlaUPTa3MAZBVvjSRI/rPuIADgR6f0T6hwTESEyaTK98GtRzuxo6kLJoMO56XZuiFHjZ580t89qDwfBv2JF4aeeCvmpESrAqk5mcsbFLVfRQXCFSlrkoDOytAcb2cK80RZqKICsjneCgIFnWxMmlalvkBvlZqnXknV6igdQjoV77BCRpvvVSqfJznhUToaDLzTNFYDALNBj5JQElILa1u5swVBUUomkM9HutSo6FYs54NQtfu0IWUJ9xBKIM7mWjFY2xXqUT2pKj3VhSAI1NlcKwZrq3eHAu8h6QfepOLd3OWGX2VZ9p4WO9btPw6dAFzaw+qwVkwmSbV75sjKtEz9olHD2Zw4mp+IMnOAB96cJCiRmhv1OnoDaNPYrNdY2BXOqQz3bGo/8E7HXE3rDuCpmKvJj9NykErWpPQLk6gT2jU8+i2dSqrWqlfRpBN4h0faafN+0eVJvYoPaK/Hu8vto9fNsDSDHoKWRop9miGZORAOvNWW+76/Serv7onMnNCHVua0cc8IB97pqy6owZoGAu/Dx53Y3+aEXiekPcoOkPaKBp2AoKh+dfiNdYcAADOGV6btL0AIj1VU717hDwTxbmhCwMUn91xmDqgjNT+RjdUAHnhzEuD0+uEMjftJNMcbkBmsabRnU47iHu9QBU+rPZtyiNQ8lcBby/JlIDVzNflxWk4opDKbHGAjSZLqODEgbCyklepVNOkE3iSI00pgEM0xR2rXHoGsq83hhdevvrHQzlBvbZXNjOL8xN9LydCKjD4QFLFyZwuAnsvMgbB8VM2K986mLuxo6oJRL6B+dM9k5kBYwqy2fB6Q2hP2h8bZndSDqh0dKdauvsHa6t1tAIBx/YrSmrVO0OsETdwLfYEg/vfNYQDAFaf07/HraWGW9xe7W9HS5UFJvhFnDKvIyGtW21SoeLecuDO8AR54cxJAXMrNBl3STTVLBmtKHcDDc7y1G/QQaMVbSY83A5VhIPW5wzRI1XCihCQTeqO5WiqbNa1XvDvTCLy1LJ/3+oNpy/tK8o10/FurBhRNxNG8JzJzQlhGr24wt+HgcbQ7fSjKM2LigOIevx4xV1PTWfqDUGXujGGZkcT2LdZGFR8ADrQ54A+KsJoNtGKYDlqSmpP+7u/1oL+bEG4LUO/6W7atGa12L8qt5owks7RgMklmd184vg8dA9ZTVOnxDn0XDTlBK96pNXtxTihayAxvqzmpa2eZlZ2KNwlSC5ME3jaNuxTLIa7mSireLEiy3b4Ara4pl5oTqa9215WKUzsgk5prWJ2QjtScBKmNHW4EgiL0aZreZIt0Kt5a2kRHs7OpC95AEEV5Rqo2UIogCKgstOBIuwtNnW6aNFGLsLFazzdtZDOttoyeyMxPH1aREbMhEgzaPX50un0pqxx6iiiKeP9bIjPvuQEUEE7WaUEls0uWxEp3nB2gHam5KIpYvUeqeJ/Wg/5ughTMHVe14v3G15LM/NJJfWGM/kzp9cBll4X/rAA6y1ulirfd48eSLY0AgIsz4GZOIEm6FrsHXn8wYwF9PNrsHhx3+iAIJ27grUrF+9lnn8W4ceNgs9lgs9lQV1eHDz/8kP7c7XZj9uzZKCsrg9VqxaWXXoqmpqaI1zh48CBmzZqF/Px8VFZW4u6774bfHxkgrVixAhMnToTZbMbQoUOxcOHCXCyv19BGjdWSy/lKC0JzDjVQEUkGkcYmrXhbwuPEtDJuJh6ONMzVtGyER94jQUieICGwIMvuSFFqrvUkiSiKsoq38sC7stAMvU6ALyCqPp4lFukE3v2pbNSlufvF5iMdAICxfYvSChQqbdoxWCOB97Ae9NYSwj3e6q6LBN5njsiMfDTfZKDXrhpy8y0NndjX6oDFqMPMkVUZeU1SmWvu8qg+S3kndTTvWeBAk3UqJxN2NdvR0uWBxajDxIHFPX69GpUr3o0dbqzYIX2m6OxuORYL8Oab0sOiTLGg9j3w5TUH4PYFMbi8AOP7FWXsdcsKTLAYdRDF3LQGkGp33+I85ClQaPZGVAm8+/Xrh0cffRTr16/H119/jTPPPBMXXXQRtmzZAgCYM2cO3n//fbz55ptYuXIlGhoacMkll9DfDwQCmDVrFrxeL1avXo2XXnoJCxcuxP3330+P2bdvH2bNmoUZM2Zg48aNuOOOO/Czn/0MS5Ysyfl6WaVVVvFORhlDUnMapCYJFIh01h8U4fap39uYCEcKPd6kiur1BzUzPzQaUhm2mg2KR4Cw1OOt2FxN4/34Hn8QvoAUZKbS423Q62hvmdqbzlikE3hXF1mgE6T/J2QahFYggfeYvult2KpotUf9/loS9IzIiNQ8FHiruK6Gdhe2N3ZBJ0iy7ExBDdZU+Hyt3StVT783tELRd5ISygpMMBmkAEFtt/aeOpoTiPqkqdOtqn/CF7skmfkpg0phNvQ8GFLbCO8/6w4hKAKnDirF4AxVVWnFWwV1zObDHXhi6Q4AwC1nDO6RyiIaQRCo10AulBdklNiJ6mgOqBR4X3DBBTjvvPNw0kknYdiwYXjooYdgtVqxdu1adHR04IUXXsATTzyBM888E5MmTcKLL76I1atXY+3atQCAjz/+GFu3bsUrr7yCCRMm4Nxzz8WDDz6I+fPnw+uVNjwLFixAbW0tHn/8cYwcORK33XYbLrvsMjz55JNqLJlJWruIo7mSijc7UnO7Qql5gUlPZ0Nrvc9b6WxyQAqQiLRXq5XUVE3IgHB1WKvjxHyBIBwhs0Kl8nmS9GqxexAMaquKCkQqEwpMqW2wtdoTHQyKafV4G/U6WkHV2po2Hw5XvNMhLMlWtzLc0uVBm8MLQcjMxk0L61oeqsydPKCEfo9mAjVHiu0LGY+NqO65KoGg0wmqJhPk7A4Z/KU7w5tQXmCGyaBDUOVkwuoMzO+Wo8aIKkKHy4d/rtoHALhq6oCMvS65V7Q5vDlVXDg8fvzq9Q3wBUScM7oaV8Sq4PcQkgA6fDz7Jn8nuqM5oAFztUAggNdffx0OhwN1dXVYv349fD4fZs6cSY8ZMWIEBgwYgDVr1gAA1qxZg7Fjx6KqKixhqq+vR2dnJ62ar1mzJuI1yDHkNTjJIUG0oop3KDg/prFKTyyUmqsJghA2WNN4n3cqPd6CIND+da0G3uHZ0MqDubDUXJvvlfwaUrouUkX1+oPUc0FLdKWhTCD01aiz+ZF2F4IiYDLoEo5RjEW4Z1N9l2KC1x+k8ux0A2+tzLAl1e6BpfkZkSmGnYrdqrUHrN17DAAy5lJMoC7gKgbeteUFGX3dPioYQUXjDwSxtzUzFW+dTgjfM1RyNvcHgvQa7Mn8bjnkfVLj2nvh873ocPlwUqUV54+LM8bO4ZCyxYIg/VkBJfkmajKZy/aoP7y3BftaHagpsuDRS8dmtNpNIIH3oWO5k5rzircKbN68GVarFWazGbfeeivefvttjBo1Co2NjTCZTCguLo44vqqqCo2NkrFAY2NjRNBNfk5+luiYzs5OuFyxLy6Px4POzs6Ix4lMi4IZ3oSyUI83C1JzpePEgHDFVesGa1RqrrDqqPWRYqnO8AbCqgst9gwD4Sp+gUnf3ewlDka9jpoKHTqmnWCOQBzklfbhyyHOt1ozIyNSuMHlBSmbvmnRYE1urNa/ND1jNOr+rfJnixqrZaiSWhFaly8g4rhK98ItoTaA8f2LM/q6NXRMUO6vRRJ4D8pw4E16h9VUlBw45oQvICLfpKcBZk/op/I9Y9PhDtg9fhTlGTGqT8/bN4Dw+9QaMuzKFW12D174Qqp233nWsIyadup0AiqsuXU2f3fjEfx3/WHoBOCpH03o8fjEeISl5tnfY6Q7XaM3oVrgPXz4cGzcuBFffvklfv7zn+O6667D1q1b1TodAMAjjzyCoqIi+ujfP/OSDpYgUnNl5mpEaq7NoEeOPYW5w8xUvFNIJgBAUegGrtWKd6ozvAHtGNXEgxqrpThah5h2HdJQFZWwK1SB7F+an/LvasmlWM6eHow60aJ8vqfGaoCsMqxyxTvsaJ6ZwNuo11F/EjWq+Q6PH/vapCB1dIaCHgKpeOe6OuzyBui/OTjDgXffYnV7h4HwPW9opTVllU8s1L5nrN4tycxPG1KWsUBV3o+fy8/VgpV74PAGMKavDeeM6fns+GgqczjL+9AxJ+57+zsAwG1nnoQpg8uy9m+FpebZvQYdHj9VQfDAWwVMJhOGDh2KSZMm4ZFHHsH48ePx9NNPo7q6Gl6vF+3t7RHHNzU1obpa+iBVV1d3czknf092jM1mQ15e7Czlvffei46ODvo4dOhQJpbKLERqXpGC1Py406fJXlQ5Ss3VgLAkuEujfcMAEAiKcPmIuZoy+aXW50PTincKUvN+sk2Z2q63sSBrSnWmLalSHmzTTjBH+O5I+r3Dam8447GnhQTeqQcNWqx499RYDZC7f6sceIeCnmEZ7B1WU0a/7WgnRFHqH1XS0pUKpB8614H3/lAioTjfiJIM9qwD8mSdetfhrqbMVuzUHilG5neflqH+bkBqZ8t1P35Tpxv/WnMAAPDrs4dnRZJNlD+5SED+5q1v0eXxY/LAEvzqzKFZ/bdyZa62t0W6N5RbTVmr3rOA6j3ehGAwCI/Hg0mTJsFoNGLZsmX0Zzt27MDBgwdRV1cHAKirq8PmzZvR3NxMj1m6dClsNhtGjRpFj5G/BjmGvEYszGYzHXFGHicyrSlIzUtCH6JAUNRsMEfoUtjjDcgCb492K96kvxtQtiZALjXXZmtAVxpS83KrGSa9+kY18Uh1lBhByxXv7xqkdpx0gjrNBt7N0uZgSBobay2uqafGakB4w3nc6YPHr84khEBQpD3emap4A+oarG0JfX5G98nceCACTZbk+F5IZeZlma12A+o6tROoo3kPjdUI/UrVS9b5AkF8c7AdgFTxziRkakWuEj9/+3Q3PP4gJg0swfQM+yUQqnJU8fbJ+u4fvXQcDApb09KFuut3ubN6f9/dIt2/M+U0zyqqBN733nsvPvvsM+zfvx+bN2/GvffeixUrVuCqq65CUVERbrzxRtx5551Yvnw51q9fjxtuuAF1dXWYOnUqAODss8/GqFGjcM0112DTpk1YsmQJ7rvvPsyePRtms/Qleuutt2Lv3r245557sH37djzzzDN44403MGfOHDWWzBy+QJD2/yqRmpsMOlqd1LKzuSiKtOKtpC/VGgqStCw1d4b6u/U6AWaDso90aWikmFbfq7DUXHnFW6cTwn3DGgp8CHRNean1QxMZt9Z6vANBEVt7EHiT6lWX268pJ/rdLelLzdXu14wmE8ZqgFS9NIU2f2p5KOxtscPpDSDfpM/oxo2MSlOj4r2lQUqKZFpmDoSdpbs8fvqdlwtI4J1pmTkQTmxpIfAe1kNjNULfYun+rsZ31p4WO7z+IArNhsy3BeSw9evQMSdeX3cQAHBXlqrdQDhJl+17xaFjTgSCko9AOsqrVImY5Z1FNQk3VpNQJfBubm7Gtddei+HDh+MHP/gB1q1bhyVLluCss84CADz55JM4//zzcemll+L0009HdXU13nrrLfr7er0eH3zwAfR6Perq6nD11Vfj2muvxbx58+gxtbW1WLRoEZYuXYrx48fj8ccfx/PPP4/6+vqcr5dFiEmaTghXs5NBKuNtGnRfJrh8ARAlfCpScy2bq1GXdpNe8ReOFiWxctIxVwO0va5010QCb7WkiPHY02KHyxdAgUmf1qatwGygM+W10ud9zOGl977B6UjNQ5voLo9fE8qfTBirAZJ0tJJuOtW5v2881A4AGNOnKKOmSbTirUJCIVzxznzgbTUbqOdHYw6TCtlyNAfCfeudbj/93sslgaBIW1EyVfGWT3cI5LhNb9tR6fobUVOY8WA1l4ZdTy/bBV9AxPeGlqMuw5V7OZU0SZfdewVp1xhYVpC1JIKcXM3yJkngE3mUGACkbkWbAV544YWEP7dYLJg/fz7mz58f95iBAwdi8eLFCV9n+vTp2LBhQ1rneKJDqhqlBWbFBiKlBSbsa3Vo2tmcfFnrBCDPmLwfutCs/R7vVI3VAG3Ll4GwA3gq48QAoF9xPoA2zQWpQA+k5qXh3nWvPwiTQlVDtiES5tF9itI2GepbnId2pw9Hjrswolr91p69oU113+I85Kc4lxwA8kx6lBWY0Obw4shxV8r9/Jkm3N9t6/EGrspmweHjLtUM1r49TNy/MyvLVqvH2+sPUul8NqTmgJRUsLf40dThTkvBkQ408M5Cpc5qNsBmMaDT7cfRdhdOymDLgRIOHnPC6w/CYtTRgLmnVBWaodcJ8AdFNHe5UZMBp3SlbDsqXX8jazJ/7+2foxFVrXYP3vrmMADgrvrhyn5JrwfOOy/8Z4VU5Wg++f5WaV82qCx109J06VeSh93N9qwlSpxeP74IGfmdMqg0K/8GK2hjB8fRHKS/W4nMnFBGnc01HHi7w/3dSjaiYXM17Va8HSn0rBNyZaaRLmRMVapBaljepr2EAklmKVWQECqsZliMUu+6VirDQGZMu7TmbE6kcOn0dxP6UodY9a/BTLxHBGospJLUfNPhdgDAuH7FGX1d2gud43Xtau6CLyDCZjHQFoVMQ+TmalS8s9HjDYTvGWpIs4mj+ZAKa8ZUFwa9jvau51qpRSre2Qi8c1Xx3tHYhaAoKSwmKB3JZ7EAixZJD4tF8b/VTyafF8XsqRNIxTvT4/gSkW1n8xU7WuD2BdG/NA9j+qqfZFcTHnhzYtJmDzmaFyp3WiXO5ixUvJVWhwvJHG8Nm6uRc8tPpeIdqqK2dHng9qljlhQPURSxP7R5I9JCpWjR3IqwvVHa5KTaGyiXgWlJoUAdzful/yUafr+0YYbXE0dzgpauQaJKGNe3uMevpaazuccfoEGC4s21QnLpVCxHbqyWvZ7U3BpcdTh99Ps/G1JzIBx459qtHZD3d2e20q5GMkEUwx4do7JR8S4NrymbEvq9WfQUiIbc2+1ZbiWiqpEsJa9ike1EyeLNRwEA542pyYl8XsvwwJsTE+ponsI4EDrLW8M93qkG3uQ4LZk/ReP0SoGzVeEoMUByNSdr01rVu6XLgzaHFzohdfdirfZ4+wNB7AyNoUmnupAr2Z5SAkGRBg5jeiCT1VKQCgB7QuNOemL+Qtek8jWYKWM1gpo93tuPStXhknxjxqvDcqfiXI7C3HIke8ZqBFJJzVWyhMwkr7KZU1JgpQIx0FRDJZMtc6h+KoxJi/iezeB4PkK1zQKDToAvIGb1+tsXumen48mRKhajno79y+a+qbdVvN2+AD7dLk2hOm9sTcZfnzV44M2JSVhqrrziXVoQMlfTcsXbnZosm5qrMVDxLkihJ1WqooaCOQ1VUQFgS6iyVVtegDyT8mQCIHe9dWtqnvzeVge8/iAKTHoMKE29b4v8jlbeq32tkrFaTx2m5cZCWoBKzTOwJrWTCZkyViMQ9+/mrtxXGuUy80xXS8qtJgiClEzK5XcXrXhnUXZJRjrlarzivlbp85MtmTkA2gOd7c9Xl9uHVbtbIwoJu5qlRNZJGQ68wxXv3N3ft8q+Zy0K/G5SxaDXoSaUJMlmkLo3dM3VlqfwnjgcQEGB9HA4Uvr3si3J9vqDNGmb2x7v7LUfrtzZAqc3gL7FeRjXLzt+FiyhirkaR/vsC5k7pFJdKGdAak5mXis17bIy1OOdirkaIN1otzd2aa7iTSSlo9KopNYUWaDXCfAGgmixe2g1S23C7rG2tIzItDZSjPQOj6qx9ajXsY9GqsOAlJUniY0eBd4aqeJn0lgNkFe8VQi8DxFjteKMv7ZBr0O51YyWLg+au9wptVelSzAo0ntCtozVgNy3B5B9Qzarj+Tzlc2xRwAw7/2teHO9ZNo1qsaG751UThNzmTZ166NCxTubxmqE/iX5OHTMhUPHnDi1NjuGWmm76DvT+y7tW5KHjYfasybJPnTciaAoTanJxb2IED3L22zIXDKGyMzPHVN9wsvMAV7x5sSBjsxI4QuGSM21HHjTirfC6rCNzvHWrtTcQXu8U7tR9tOQCZQc0nc2sib1zY1Br6NVHi0lFLYeTX9NQDgbrZnA+3D687vlkE10U5cbvkCwx+fVE/a3OSCK0uz4VEwlo9FKu0MmjdWASEl2riEV7/FZqpbQkWI5ktHvb3PA4Q3AbNBltTc11+Zq2RwlRiDy+YaO7H6+vtp/jP5569FO/P2zvXD7pKkS6aiWEqGGfD6c4M5u4A1kT6nl8Qfod2Iu5l0DkQZr2YD42+RqlBihrMCEPKM+47O83b4Alm2TZObncpk5AB54c2Lg8QdwoC31XkcSeLdqusc71A+tsOLNxhxvaU2p9tTR+dAa6Rsm0A1Bmpl4rVQc5fS0ukCkwoc0kkygxmo9DOrKCkwwGXQQxdzJYeMh79/syYanX2iWd5vDC5dXPeNCYqyWif5uICw1b3f6cmrIaPf4aSI4047mBLK2XAWoRGY+osYGgz572zCShGzp8sCfg8TWvnRkvykiN1fLVjuR0+vHwVBA99Ed38fTV07AFZP7YXBFAW6YNiijc+SB7AdzsdiaRUdzQrZl2YeO5b46TPrxs7WmXCSvYiFvP8zk2r7Y1Qq7x4+aIgtOzoJiiUW41JzTjX2tDgRFKeisTOFmRgKeVru04Uy1PzcX2D1S5TpVczWHN4BAUMz4F24mcIbk89YU5w5rseLt8gboF0/agXdJHrBf/YqjnJ6ObSFJkmMOLxwef9aMi5QQDIrY0kAczXsW1Ol0AvoW52FfqwNH2l10nWqwp1m67no679iWZ0Ch2YAujx9H2l0ZN2JSQqaN1QBpXSaDDl5/EC1dnpy9V5sPd0AUpe+XbG2u+xTn9l4YdjTP7lidMqs0IzoQFNFq99IKeDYQRZEaXdWWZ+/aqC6yQBCka7zN4c3KNbGryQ5RlNrnRlTbMKLahosm9M34v0Mgfetdbj863b6Ux2imitsXwN5QMisbjuaEbLdI7aXGaj1LlqZCtkexHmiT/l8NzGF/N6FfSR52ZXiW9+LvJJn5OWOq02qz643wijenG+lWforyjLRCrBUTqGhI5Vpx4C2rjGvVYM2exhxvQC4D006AuqNJmslZbjWlvaHqq4JRTSJaujxo6fJAEIARabrH2ixGFOdLmzG1P1t7WyWZrMWo63GQCoRllmonSugosR4GyoIgqD7Le1ezZKxWaDFkTBYrCAKVZOeyz5vKzPtnrxea/D86mCP1D0lcZTvw1usEmjzPdjW/xe6BwxuATkBWkzJGvY6u6WiW5OY7QvO6Mz02LB4FZgO9v+dCbr4z9D1bWmBKqbiSKkSpla0gda8K1eFwK1F27u1qOJoTMp1U8PgDWLq1CQB3M5fDA29ON3aFxh4NTXFTLQgCzdIdbNNG0BNNqlJzs0EPk0H6mGi1zzttc7XQlyKpomqBcH93+oZQ2Za3pQqpdg8qK0B+iqoEOTRRonJrwHcZMlYj9CnShrM5TThmIJmgdrvDzlDgMLI6M8ZqhLCzee7aib6VOZpniwHkeysHHgry+cnZNFYjVFFn8+xei6Ta3a8kP6PGTLEIm5FlKfAOqUWyMWYrHn2zvCY522SeI9msFJPvrKMdrqx4eIQVFjkMvEPvU2dInZBp1JKaA5lXQa7e3YYutx+VhWZMGlCSkdfsDfDAm9ON3dRYLfUNKKkcHNCICVQ0RGqeSnXYpnFnc0comZCquZrNYkRRnpRl11qQ2hP5m1bMrQjbemisRiDVg1wEB4nIVH83QQvjt4JBkY6l6WnFG1D/GtzRKK1lWHVmZe65dskGwo7m2RxDQyvebamNFkqHpk5pfrJeJ6StgEmFXI0UIwFDLip1fehIseysiSSuhueo4g3kdsID8RzJpswckMbRmgw6BDNs2EUg9+yUXfR1OuCMM6SHLrUwqMBsoH5GmX6vPP4ATbxkcyRfPDJd8SZu5lxmHgkPvDnd2COTmqfKgFLpZqEV9+VoSJBamELgXRjqt9Kq1JyMSEun71drfd6ZMHyRVxtFUf1Z3jTwru7ZJqe/RpzNM+2W3UcDZngNHS7JsVivQ/8URijGQysV70wHDqT9oylH7t+tdg+OtLsgCJlL9MSCSKOPO31ZqWLJITLzIRXZmZ8cTdjZPLvv2b5Q0iKbLu0E0p5ytBdWvLOVTJCTC2M1QPLwIHuMbLRIkWTP4FTN/PLygBUrpEde6vf7vlkyWJObxfVkska6ZFIt6AsE8TGXmceEB96cCPyBIDWsOKky9S8dWvHOQeUgHbrS6Ie2harCbXZtjklLV2oOaEuWHQyK2J6BESckkHN6A2h3qt8ekKl5qf2IC72KSRLJWE16j3pqrEbop4HAm8jMB5XnZ8RlWv2Kd3Z6VOlIsRxVvInMfEiFlSZAs4HVHB4hl+02qS05lJkDuVMp5FL2S6XmWZDPH3d4aStFpud1JyJXUnNRFHts9pkK2UoYd7h8aA3tyWpzNEqM0C9Lfd77W6XXG1Se21FihOhZ3j3h28Pt6HD5UJJvxCmDsjPDnVV44M2J4NBxF7yBICxGHf0iSAXS461VqXk6QWp/jVWFo6HjxNLoH9ZKFRWQJNQObwCmHs62tRj1KLdKlTm1R4p5/AFq2jWyh0ZK5DpUs8d7f5sDdo8fFqMuI73QQGS/ploKhT0tmXE0J6hZ8baH3NSBbATeoXnXOerx3hiSmY/PYn83IdsOzIRcGasRyNzr3iQ1r6G+EJlfEzFW61eSl1YyO11ypfw5fNyFLrcfRr2QsftdIrKV3CfXW2WhOafvE5C9ireaxmqAZLaXqVneq3e3AQDqhpRpchqQmvDAmxPBrtCXzpAKa1o9GQNks6GzNWOzJ6Tqag7IkgkaNYxz0Cp+6rJFLVW8SRZ+eFVhj6uOWpHQ72qywx8UYbMY0KeHo3zIZ+vQcadqASqRmY/M4PzhmpBs1O0L4phDHVUJdTTPVOBNKged7qyYCiWC3MMrC80oKcisXDHXPd7f5sDRnDAwR/4kpOLdE1VPKuTiPQsERfr9mAupeTarw6RNIxf993KIfD7bFW/yPTu0spAax2aT/rLvrUwSnhmfxvXmcAAVFdLDkbo6M9vJhFoV+ruB+LO8HR4/fvnvDXjhi32KX2v1HhJ4l2f2JHsBPPDmRECM1dKdPVtTZIFBJ8AbCGZ9fEk60Iq3QldzQD5qRnuBt93jh8snVbzTmf2ZrS/FdNiaAWM1Ql+NJBS2yaTzPZWO9S3JgyBIEvo2lQLUr/YdAwCMyaBM1mzQ097hbFSwlEB8LYZUZmbDU14QNhXKdqUxGtrfnYXAoZL2eGd/TaIoYtOhdgC5qXjn4j7fZvfQe9LomtxIzcM93u6sJewa2iWlnEmvo5XbbEKSdS12D7z+zCa2tmepTSMZuUrW5cpYjZBIVbe7uQv//upgWtelfIZ3WrS2So806BtaU6bVCaTircYMb0KsosWzK/bg/U0N+H8fblfkgeH2BbD+4HEAwLQhZdk5UYbhgTcngp6O1DHodfSDq7VANRgUYfemITXXcOC9/oB0c+tXkpdWdSvTLpY9IVPu34A2+oaBzPV3A1KASsY5qdEacPi4E29+fRgAcNaoqoy+ttpmZKTiPbQiM5ttnU6g12Cuk1rE0Twdj45kVIaqp51uP1zenvUAJuPwcReOO30w6gWMyMA9IRkDQlWmbPZ4/+8b6fMzuo8NRfnZ61mXQ1zNnd4A9TjJNKRSN7AsPyey0rICE0wGHUQx80mgnSoYqwGhZJ1eStZlM7GVye9ZJSSqDv/q3xtx71ubsWRLY8qvu7c1d2Z+0WRLUUd6vNUYJUaI3hMeaXfhH5/vBQB4A0Es29aU9DXWHzgOrz+IaptF1bVoFR54cyIggXc6o8QINFDVmDTb6QuAJFZTk5pLN47Dx50IaEw+/9U+Sc4zpTa9rCL5AulwZd/NNxlbqQSz55Ugtc2tCJk2sSEjxQ6psK4nPt4JbyCI04aU4fsnZVY+pmbg3e70UpOelMfSJECtazBc8c58/6bNYoDFKG0bmruyW/XeFJKZj6yxZX0uNJD9incgKOLltQcAANdMHZiVfyMWeSY9HYnZlCX1RS77uwFJEktadzJ5zxBFkfZ45zrw1ukEWsnP5j0jk8oyJZD9YHOXB25fOFl36JiTnsuakCw5FcIV79wHduTeftzpoyrKnuL2BahZoFo93kD3pMKfP9oOjz8IQyihtujb5EmS1XskJcFpQ8pUMYnTOjzw5lBEUQxXvHswy5bIZLRWISY3SL1OoJtHJVTbLDDqBfgCoubk80T6O6U2PddI+UzKwyqadrU7vWgIbQozUd3KlvlJKoiiiG2Nmd3kqGWGt6WhA29vPAIAuPfckRn/MiUbmWz3N8aCGKvVFFnSGskXD7WSCSRwyIZUVhAEamyV7c/W5sPZn98thwTeR9pd8GdB6rtyZzMOHXPBZjHgogl9M/76iSBy86NZDrxzWX0kkvajGXQ2P9rhRpfbD4NOSH1EVQbom0W3dgDocvvoviwXjuYAUJJvRIFJSpzJ7xnyyulX+4+n9JrBoIj9rblz0Y/GZjHSZFb0/f3QMSeuWLAGS7cmrwxH/54oSqNuyzLszZEK8or3pkPteGdjAwQBePTScQCAz3a1oCtJkSbc381l5rHggTeH0tDhhtMbgEEn0CpvOgzIkUlNqnSFjNUKTPqUAge9TqABj5bGpLl9AWwKuf5OGZz+uAYtGJGRzHf/0ry0etWjodVGFaXmjZ1utDt90OuEHiWy5PRXaaTYox9uhygCF47vk7ExYnJo9UqFRMnavdImIVPvEYEG3jlc03GHFy1ZHoU0LKSGImqObEHuCbkau1VZaIbZoEMgKGbFa+Cl1VK1+0en9EeeKfsVfDnEYC1TiWPinE8eZHxdLoOg8DSEzL1XJGk1uKIgJ8Zj0WRjTXLI+1RTZMm48WI8JMOu7t9bn2xrpn/e3tiJDpdyxV1Tlxsun7RXJd+JuYasKfr+/uKq/fhq/zH8v4+2p9S7Tts1yvNVrRLL567/cdFWAMDFJ/fFpRP7YnBFAbz+IJbJ3rtoutw+fBtKmp42lBurxYIH3hxKeJZtAYw9cCweUEp65bQTpAJSVRVAWvNgczVqJhU2HGyHNxBElc1Mkx3pQKuoKlaHM234QoKeDpcP9iz1NSaDBCZDKgpgMWZmo62G38Dnu1rw+a5WGPUC7q4fnpV/g5jVHG7P7eer0+3D3z+T+tcuPjmzVUg1kj87czAKaUS19BklJlTZQBTFcOtJjipzOtkmPtOfr32tDqzc2QJBAK7OocycQPq8MyE139tix6QHl2Lao5/Sx5pQ8iqXElmSrMukSmaHSsZqhD5ZVmqtCo14ylW1mxDdItXp9tGEp81igCgC3xxQXvUmMvMBpfk92qv2hL5xChbLd0hB6e5mO3Y22RW/HpkKMEglR3MCneXd6cG6/cdhMepwd/1wCIKAWWNrAACLNh+N+/tf7TuGQFDEoLL8tEYSnwjwwJtDof3dPaz8aFVq/mVIlp3Olw6t4muob/1LWX93TzKkmqh4N2S2F7rQYkRRnpRgUavPO5PGaoRcz/IOBkU8+uF2AMA1UwdlrbpAR/a15nZU2vOf7UWHy4eTKq0Zl/+qITWn/d1ZDBzI9by9MXsV7+YuD9ocXuh1Qk57bcMjxTKbNH4l1Ns9fVhFj9Rk6SJ3Nu8pn25vhscfhE4AzAYdTKHH6D62nLjPE/rEGSnm9Qdx71ub8eqXB1J+TWKslutRYoS+WRwptmRLI55ethMAcOaIyoy/fiJoxTu0J1y5owX+oIihlVacPboaAPDV/mOKX29vT2XmOh0webL00KUXBsUyjdvX6qCVawD44NsGxa+3r0096bwcMsubcPP3B9P2ovNCgffKnfHl5nyMWHJ44M2h7G6WvnR6Krkkm/PjTvUNu+R8sUsyfEjHGEqLyQTS331qmv3dhH60mq9mxTvz1a1w4KPOe7Y1w8ZqQPiz1dDuyonR33ubGrCloROFZgNuO3No1v6dAaX5EASgy+PP2ai0NruHziW986xhGXdjlvet58qUkfZ3ZzFwIG7IO5vsWemFBsKJuEyqRZSQqOL99f5j+NNH2+Hxp+bm7vT68cbXhwAA1542qMfnmA6JZnk3d7lTuj7JJI17zhmBHX88FztDj0W/+n5OJfQ1cWTZH29txL+/OogH3tuaknwZyK4/ghL6Fofv79E0dbrTVtx9ubcNv/z3BgRF4EeT++OqKQN6dJ6pEh2kkv7uH4ysxKmDpP3L16kE3i09mOENAHl5wLp10iMvvaosTSbI3qtPt0vVbuIhtOjbo4oTyaRnXe2Kt3yWd0WhGbecMYT+bER1IQaXS3JzstZoSOB9Gu/vjgsPvDmUTBirAZJjeLlV6h/SirO50+vH1wekG3s6gbfWpOZefxDfhOYkTu1BfzegfsXb6w9iV3Pmq8Nqz/LOtKM5IG2gjXoB/qCYUVOhWPgCQfx5yQ4AwK3Th1ATvmxgMerRJ5RV39+amxaVBSv3wOENYExfG84ZU53x168pyoPZoIMvIObsvrEzNEosmxXv/iX5yDfp4fUH6dzZTJNr52UCTbDG+N76v/99i2dW7KEj9ZTyzoYGdLn9GFiWjzNOqsjIeaZKdZwe7+Xbm3HqQ8vw0KJtil5HFEV8HQq8Jw0syexJpgitDkfdBz/cLLkuewPBlMZU+QNB7ArtgXLtaE7oI6t4ywM2jz+Ai/62Cuf95XMcTzExue1oJ372r6/h9Qdx1qgqPHTxmJz3ENP903EnfIFw0HbWyCqcEiocbDrUEeF6nghq5pfuDO8MEMvAdXloXbeeMQQmgw57Wx30XpYMGniXqzfDmzC+fzEA4P/OGRFhOCoIAq16L/q2u9z8mMNL9z3cWC0+qgTejzzyCE455RQUFhaisrISP/zhD7Fjx46IY9xuN2bPno2ysjJYrVZceumlaGqKdAk8ePAgZs2ahfz8fFRWVuLuu++G3x/Zz7lixQpMnDgRZrMZQ4cOxcKFC7O9PCYRRZF+6WTCZEhrs6+/3HcMvoCIvsV5aWVJtWYYt/lIO9y+IMoKTBjSwy+f/jIXy1zKfAlfH5DeG5vFQJMAmUANcyvC3hY79rY4oBOAMX0yFzzodWGjmmwrFHY0duFIuwuFFgN+Oq02q/8WEN5w7MtB4N3U6ca/1khS1F+fPTwrG1G9TqCfTZLUzCbyUUg9GQeZDJ1M/k3aKTJNeLRgbgPveCPFDh1zUvf7VNyKRVHEv9bsByCNENPlYMZ1LKjUvMMT8fxLoXN75csDigK6w8ddaOnywKgXMLZvbkzv4kHkr11uP5W9uryBiErcexuVS30PHHPC6w8iz6in34m5hsjnHd5ARLX+i12taOyUHNdJi5kSDh1z4tp/foUutx+nDCrBX398Mgwq9ETLp3F8vf84Ot1+lBaYcPKAEgwqy0e51QxvIEhNuZKxT0VHc0K/qHGRdk/4vblgfB/MGC4l2WIFqNFIo8SkpJjaFW8AmHvhaHzwy+/hskn9uv2MBN4rdrZ0888hffsjqgtRbjVn/0QZRZXAe+XKlZg9ezbWrl2LpUuXwufz4eyzz4bDEd5wzZkzB++//z7efPNNrFy5Eg0NDbjkkkvozwOBAGbNmgWv14vVq1fjpZdewsKFC3H//ffTY/bt24dZs2ZhxowZ2LhxI+644w787Gc/w5IlS3K6XhZoc3jR7vRBENDjQA6Q9cpppOJNZObfG1qe1iabbMjanb6U5WvZYO3esMy8p0ED+QKxe/yqrI30P54/vk9GAyBayVfB2fzN9VJV7IxhFSjL8BcQdR3NchKImGeN6VOUEwkp2XBkq4oq56+f7oLHH8TkgSWYPix7VUgSAO/KQeDd3OVBh8sHXYbu4YkgBmvZcjYPV7xzG9zRwLst0mtg5c4W+uc1e9oUGzau238c2xu7YDHqcPmk/pk92RQggXebwwNfqD2gpcuDz0Pfi15/EK+vO5T0dYjKanSfopy2AMSiwGygPh5kTNqKHc1w+QJUnbN6T6viefNhYzWragkSi1FP1YJybwi5mVUqM6/vfGMjWro8GF5ViOevPUW196xfaXju9XubpLGUM4ZXQq8TIAgCTq2V1BPrFMjNPf4A/e4bku4Mb6cTGDRIejjT+x4l38Otdmk++Re7WuELiBhYlo/B5QU4f1wfAMAHCuTmJNFXaDFkVVmmFKvZgDFxEmsjawpRW07czSOTkKt2S/cTXu1OjCqB90cffYTrr78eo0ePxvjx47Fw4UIcPHgQ69evBwB0dHTghRdewBNPPIEzzzwTkyZNwosvvojVq1dj7dq1AICPP/4YW7duxSuvvIIJEybg3HPPxYMPPoj58+fD65UytwsWLEBtbS0ef/xxjBw5Erfddhsuu+wyPPnkk2osW9OQikz/kvyM3JzjVQ7UgvZ3D0vP8KFAJp/Xgtw8U/3dAPmyl4LDXMuyj3a4sGSLdPO+ti6zbr/RGelc4Q8E8b9Q4P2jUzK/2SZZ/j2t2Q3mtoeCn0zMVVcCWVe2K94H25x4/SspyLirPjvVbsLQChJ4Z88BnEACh0Hl2e+LJn3e2XA2t3v89BoYmaNrj0CUWl0eP9qd4SSkPPD2BoJYuaOl2+/G4r/rpevsovF9UZTf8zGJ6VKab4JRL0AUpQQNIBk/BYIiHZv1ytoDSXu912tEZk7oE2VgSALUyyb1w8kDihEUgcUKKo5A+POjlsycED1SzOMPYOmWcIBDku7JcHj89P167ppJql5/NpnZ6dsbpMD7rFFhg7dTQn3eZF+TiEPHnAiK0ljYisI0k9qiCBw4ID3SVPkV5Rnp5Igj7S6sCLmZzxheCUEQcOaISliMOhw85sR3RxInKFeHAtbBFVZVR4kpQZKbS61ZpK2DsIb2d3NjtURoose7o0OSl5SWSh++9evXw+fzYebMmfSYESNGYMCAAVizZg0AYM2aNRg7diyqqqroMfX19ejs7MSWLVvoMfLXIMeQ14jG4/Ggs7Mz4nGikEmZOQAMCFWvDmbYHTYdmjrd2NHUBUEApvXghqCVZII/EKRGJFNqM5NZpOM+cry2f395EIGgiFNrS2kVLVMQo5pcz/JeubMFzV0elBWYcOaIquS/kCJk6sDuFEaVpAMJqkZm+H2JRzjwzu41+PSyXfAHRXz/pHJMHZzdzDypeOdCap4LR3MCdTbPQsWbvGa1zZJxtUgyLEY9qmzSv0nairz+IN0YTxsqXS9LtybvHfb6gzSp+MMMj6pLFZ1OQGUhkZtL90MSAP36rGEoyTfiSLurWwUrGs0F3qFK/tF2N9y+sMz8vLE1uHC8VHF8d5MyuflOlY3VCMTr4kjIc+WLXa3o8vhpJXRHUxfa7J64v0/47kgHgiJQZTPndMxbPMgew+0LwqTX4fsyvwMSeH9z4HjS5A9p+aitKFA1SBUEgbazHTrmpGPEiGN8gdmAH4S+/xO5m/sCQfzjc8nkM5a0W4sQufnyHc3oCCUoj3a4sLdVaq/LREGoN6N64B0MBnHHHXdg2rRpGDNmDACgsbERJpMJxcXFEcdWVVWhsbGRHiMPusnPyc8SHdPZ2QmXq/tm/JFHHkFRURF99O+vnjQs1+zJ0CgxglaCVCBc7R7btwglPZDxaGVNW492wuENwGYxZCw730/W550rvP4gXgtVHq+rG5Tx1yfmai1dHsWmLZmAOBhffHJfWk3KJEMrpfc82/JlMi4qVxUgsjk80ObImteA2xegm6A5Zw3Lyr8hh7xXu5vtWfdPyGXgQK6Jhg433XhlCiozz3F/N2FgKUkaS/f5rw8cg8MbQLnVhDtmStfMp9ubqWQ7Hqv2tKLD5UO51ayJjai8z3t3sx3fHu6AQSfgskn98KNTJJdr4nsQC4fHT1sLNBN4y0aKrdjRAqc3gL7FeRjfrwizxtVAJwAbDrYrMnndQUeJqXPdEeg0hJB8nlTxLxzfh445+1JBZZj0S+dyxFsi+hWH++brhpRFmHaNrLHBajagy+NPOqaQvE+Dy9UzViMQVd3SrU1o6vQg36THFJnZ7axxUoCaSG7+7sYGHGl3odxqxuWMBN6jamwYVJYPjz+Ikx/8GD94fAV+8eo3AKR9NlE3cGKjeuA9e/ZsfPfdd3j99dfVPhXce++96OjooI9Dh5L3PPUWiBRySIYCb+IO29DuTrpByTZf7A73d/cErczy/lLW352pEUh0PnQOnc0//O4oWu0eVNnMOHt05ivDJflGOo8yG3NRY9HS5cGybVLm+/LJ2UnckSrqoeNOuLzZSSi0dHnQavdCEHJXAepfkg+dADi9ASqHzTTrDxyHxx9Elc2Mk0POrdlkYFk+jHoBTm/YPCdb7GjKnSOzzWKk1Z5Mz/Omxmo5djQnRE+wIDLz00+qwMQBJSgrMKHT7U8qiyWmSueNrc74qLp0kDubvxOqdhMPiqunDoBOkL4rd8dpi9h0qB1BUTKtJOPJ1KZG5gL+4XfS/+9zx1RDEKQKP5G8vp9knnKHy0e9JYZVqxvQyeXzcpn5rHE1VKFDTKwSsfFwO4CwQ7XakIo3AMwcFfl9r9cJmBhK5qxL8LnyBYJ4/auDALTRR0wCb6IemTa0HGZDuM1nxvBK5Jv0ONLuwsZD7d1+PxgUsWDlHgDAjd+rVd03QSmCIGDOWcNQVmBCUJRUCBsOtgOQ/h9wEqNq4H3bbbfhgw8+wPLly9GvXzjTU11dDa/Xi/b29ojjm5qaUF1dTY+Jdjknf092jM1mQ16M2X1msxk2my3icSLQ3OmmPSiZkppXFpphNugQCIo5C3piIYoiNZD5XhpjxOQQ+bzaPd5fZrC/m6BGxZtUV35y6kAYs+C0KggCTQDlwikbAN7ZcAT+oIjx/YuzFgCVW80oLTBBFIE9LdmpepNgqrasIGezeU0GHb0Os/V+fUElw+mZLKaKUa+jpnG7mrLX5x0MivT1c5UoIf3XmTZYIxXv0WpVvMtIglW6Bkk/9xnDK6DXCfjBSElKmsjdXJKZS8q7WSFZptqQYLmxw4V3NkqBApHA9yvJx8yRUjAUr+qtNZk5EJ5csa/NQROe540L//8mcvNk7ub//GIfgqLUplGhshszGZN25LiLysyrbGZMGlBCA28lBmvfksBbIxVvktACgJkjK7v9/NRBxGDteNzXeG9jAxo63Ci3mnGxyu0bQFid4AwlwInMnJBn0tPPVSx384+3NmF3sx2FFgOunprb2eo95aIJffH1fTPx1e9+gH/99FT89rwRuPWMIbjp+4PVPjXNo0rgLYoibrvtNrz99tv49NNPUVsbOapm0qRJMBqNWLZsGX1ux44dOHjwIOrq6gAAdXV12Lx5M5qbw6Mjli5dCpvNhlGjRtFj5K9BjiGvwZHm7l31/JfocPkwqCw/Y5sdQRA0USHe3tiFVrsHeUZ9jzcMWpCaB4Midf7MVH83kPse7++OdGD9geMw6AT8+NTstXSQ4DcbJlDRiKKI/4Rk5j/KUrWbQBJk2TLt2h4aE5UrYzUCkZtna5b3qgypX1IhF33eR9pdcHoDMOl1GFSWm1FIRJKbyc+WPxCkr6eW1Fx+n2/scGN7o+QPQnpSzxolJfaXbm2KKx/9YncLutx+VBaaMXmQ+jJzAKgukgLKD79rxOHjLljNBpwlqzxed9ogAMD/1h+m47nkrD+ovcCbVIc3HGyH3eNHTZEFE2SBZv2Yapj0Ouxo6oqrzGh3evHPL6Qe29tnnqS6uRXxJmlod1GZ+bljaqDTCZgSSrbvarajNUGfd5vdQ8dNju2n7tg3AlGwTBxQTEfByaEGa/uPxfxcabE63C9q7NyM4d0TCkRuvmjzUQRl/euiKOLZFbsBSMayhRb25NlEWXL6sArcfPoQ/ObcET1q5zxRUCXwnj17Nl555RW89tprKCwsRGNjIxobG2nfdVFREW688UbceeedWL58OdavX48bbrgBdXV1mDp1KgDg7LPPxqhRo3DNNddg06ZNWLJkCe677z7Mnj0bZrP0BXPrrbdi7969uOeee7B9+3Y888wzeOONNzBnzhw1lq05Olw+XPPCl9jVbEe1zYKXb5wSIZPpKbRyoGKgSvq7pwwu7fHayHqOtLtUk8/vaOpCh8uHApM+oxWhfjme5f1yqKpy7tgaVGZRtpiN4CAeGw61Y3ezHRajDuePz26Vi3gx7MySwdq20CY11/2OtUShkIWRYu1OLzYfkfoecymHk/d5Zwva91hRkLM5vcRgbVsGP1t7Wx3w+oOwmg2qzVLuLxsp9llIZj6uXzE1t/re0HJYjDocaXfR6nw0H1CZeY0mZOZAuOJNVE3njqmOCF5OG1KGoZVWOLwBOpWBEAyK+EaDFe+aosjvDhKgEoryjJgemqccr+r9j8/3osvjx8gaG84ZXZ29k1VIn1DFu7nLQ2XmxMyqpMAU7vNO4G7+beg+N7i8QDP9tpMHleJfPz0Vz1w1KebPx/cvhlEvoKXLE7NYs2x7M3Y121FoNuCqnlaHBQEYNUp69CDRQhQXgJRYqC7qvpc5Y1gFCs0GHO1w47Z/f0P9ZlbvacOmwx2wGHW4YVptt9/j9F5UCbyfffZZdHR0YPr06aipqaGP//znP/SYJ598Eueffz4uvfRSnH766aiursZbb71Ff67X6/HBBx9Ar9ejrq4OV199Na699lrMmzePHlNbW4tFixZh6dKlGD9+PB5//HE8//zzqK+vz+l6tYjT68dPF67DloZOlBWY8MrPpkRIgTJBdK+cGny2S9o4ZaLCVWENy+ePtme3XzMe/w71N00eVJrRDXbf4jwY9QJcvkDW5ebtTi/eDc3yzPQIsWhIxTYb7svRvBmqdp83pga2LGeviZx4V5YCb1rxzvFonWxWvNfsaYMoSkmLXPaohtUJ2Qu8dzbnfhQS+WztbOxK6kSslC0NUsAwsqZQtVnKJMF6tNONj0Ny8jNks97zTHpa/Y4lN4/uy9UK1VHXfLRUVxAEXBe6H/9rzYGI6tyeFjs63X7kGfU5vyckospmgfwyIWOO5Fw4ISQ339TQLal8zOHFi6v2AwDmzDxJtWtOTmmBCRaj9N3e5QmpJmTJDtLbvGZva9zX2BTqJx6nkWo34fRhFTGDU0CaKDAupFb4KmqetyiKeCZUHb66bmDPv1/z84EtW6RHfvr7XtLjDQAzRlTEPMZi1OPhS8bCqBeweHMjfvT3tWjucmP+cmk9V54ygI5z5ZwYqCY1j/W4/vrr6TEWiwXz58/HsWPH4HA48NZbb9HebcLAgQOxePFiOJ1OtLS04LHHHoPBYIg4Zvr06diwYQM8Hg/27NkT8W+cqLh9Adz0r6+x/sBx2CwGvHzjlIz1dssZWBrZK5dr3L4ANcA5fVjsm2Iq6HQCTSYcUGFM2o7GLryyVqoU33rGkIy+tsmgw0mhyly8Kk6mePPrw3D7ghhZY4vYUGQDMgprb6sjq87mTq8f72+SqlxXZGF2dzR0pFgWpOb+QJBWZ0fm2OAqHHhnPlkn7+/OJeH3KvPO5h1OH/7x2V68tHo/gNyOQhpUVgCzQQeXL9Ct/ebzXS1YvFnZ/GQ5ahurAUBZgQn5Jj1EEfh0uxRAk6opgUi0YwXen++M7MvVCvKAp6bIEnOU3sUT+8FqNmBvqwP/+yZc9Sb93RP6F+dMUaEEo15Hx6RV2yyYGOP/9w9GVKHApMfh4y6s2Bk5f/25lXvg9AYwpq8tQnavJoIgUAk9IFW75QmBsMFagoo3cTTXiLGaUuLN8/5q3zFsONgOk0GHG6YNUuHMYlNaYEJhyJ090ejQC8b3wSs3TkFxvhGbDrXjvKe/wOo9bTDoBNx0Ou+JPtHQzh2UkzP+tWY/Vu1uQ4FJj5d+emrWeukGlJFeOXXM1eQOxpkakzZQpT5vURTx4AdbERSBc0ZXZ8XRk1wHZPObLYj77FVTBmS9n67KZkZRnhGBoJhVqe/izY2we/wYWJZP+/CyydBQ3/CBY86MJxT2tTrgDUhyX7mULhfUhozI9rc5IipumUCN/m5Amk+uE6TWnhYF83eVsK/VgXvf+hZTHvkEDy3ehqZOD0oLTDkNHvQ6IeyhIEvWbW3oxPUvrsMvXv0Gq/fEr8rFQu1RYkCkP0lQlOTK0QZVPxhRCZ0AbGnoxJEo81DSlxsdMKmNXOVx4YQ+Mc/NajZg9oyhAIA/LtqGltB0AS0aqxGINPucMdUx15Rn0tOq960vr8dH30mmdy1dHry0Zj8A4M6zhqne2y2nb1TgLWdKbSkEQUrkNXd1V96JoiireBdn8zQzztTQKK7/fXMYj3y4DV6/1NL3bKi3+/JJ/WiiRQsIgoDHrhiP+88fhYkDihMeO2VwGd7+xTTUlhfQ/vyLJvTN+XcsR3144H0CQtwVf3PuCJycxYz8ADIPNYtzeRPxyTapGpFJB+P+KgXen2xrxhe7W2HS6/Db80Zm5d8gVaZsVrztHj82hbLx0VWkbCAIApVGZrPP++0NUnXoson9crKBq7CaUZxvzIqzOenZHV6de7lvv5I8GHQCPP4gGjsz185x6JgT+9uc0OuEiDmrucBi1GNgKKGwO0ZrwLJtTSk5g9s9fly+YDX+/dUhuH1BjKguxKOXjMWq/zszpxVvINyKQM4/EBTxm7e+pdLzP36wTbEMXRRFWcVbXYnsAFnb1fdPKu/Wp11mNdMg9BNZ1dvtC9Aq+PkakpkD0nU4qCwfep2ASyfGnxf8s+/XYlSNDR0uH+a+vwWANo3VCJdN6o8hFQUJ25Z+f/4o/GBEJTz+IH7+6nq8uGofFqzcA7cviAn9i2OaYqlJn5D5WLTMHACK801UyRWrz/tIuwttDi8MOkG1yQDpcsawClw9dQBEEXhu5V5c8uwqfPBtA1bsaIFOAG7OVHXY6QRGj5Yezp7t5epHV+On36tV9L1fW16At39xGqYPr0C1zYJfnjm0R/82h0144H2CcaTdhU2HOyAIwDljsrsx6FeSB0EAHN4Ajjm8Wf23ojnm8OI/66Se20xugAbIjHdyhccfwEOLtgIAbvx+LVUSZJpcVLzX7TuGQFDEwLL8bo6g2YLIpXdkeN4w4WiHC6tD411+mKMRJ4IgREiYMwmpXqrRy2nQ62hyK5N93qTyOqF/sSrusUMqYvd5f73/GG586Wtc88JXig0bv95/DK12LyoKzfjPzVPx4e3fx5WnDsjZ2Dc5xHyPJGteXLUP3x7uQKHFgEKLAVuPdkZIlhPR2OnGcacPBp1AneDVQh54nxGnTYmoCxas3IOX1+yH3ePHZztbqLv2yf21F6S+eMOp+O+tdQkTNEa9Dn+6bBz0OgGLvj2KN74+hL0t0mfx5CRVPTX4yZQBWPbr6RhcEf+ayTcZ8Nw1k3DVFCmoe+D9rXhxleRkrrVqNxB2Ir9kYr+Yyc9E87w3HZIS28OrCzXh/J0KgiDgjz8ciwVXT0JxvhHfHenEba9tAADMGteHJjB7jCgCW7dKjxwXhYrzTVh4w6lY/ZszaWsV58SCB94nGEtCMqtTBpWiojC7hg4Wo54auuTa2fyfX+yD0xvA6D62jGazB5blvuL90ur92N/mREWhmcoAswEJUI+0u9Dh7D5OJhOQAOi0LEjl45Htive7GxsgisCpg0ozblCYiJNCm+edGZ4PTf4/qWWiNCgLzuZf7JY2qLnu7ybEGyn2RsiQr9XuoVL4ZJD+xzOGVWDK4DJVgwZyz9je2IlDx5x4/OOdAIB7zx2JX515EgDgsSU74PD4k74WSfgNrbSqHjAMLEseeP9wQl9UFppxtMON37+7BXUPL8PDi7cB0J7MnFBbXqBI5TambxGdx/vbtzYDkN6X4nx2RwUZ9Dr88YdjcM85wwFIbQSTB5bg+yepc09IxJWn9Mcbt9ThrrOHxfx52GCte+BN53cz1t8t55wx1fjo9tMxbWh4n3DrGb2rF1qL9wdObuCB9wnGR1ukwDtXYzPUqBB3uHzUbOiXZw7N6MZUvp5cyOdbujz46zLJ/fLu+uGwmg1JfiN9ivKM1KUzW3JzUhmuG5K7zc4IMvboaHYC73c2SA7tuap2E0jFO9PO5rTirZLBVaadzYNBEatV6u8mnBRj7rrT66dtP4DkuqyEL0OB96k58BJIBknOHDrmwl1vboLLF8CptaW48pT+uPa0gRhQmo/mLg+e+2xv0tfSgrEaYVQfqeJ48oDiuOMOK20WfPLrMzD3glEYXF6ALo8f+0Pfc1pyM0+XO2aehNryAvhDrQJaMopLF0EQ8IvpQ/HXH5+MM4ZV4I8Xj9FctRuQkgSn1safXHLqIKnPe2+LA81RLTkbQ/3d4zXmaJ4q1UUWvPzTKXjiivF45qqJGN2H7fVwOAQeeJ9AtHR5sC40pqF+TG4CbyL/2pYlmW8sFq7ajy6PH8OrCnH2qMyuk1Q0uzx+tGepKizniaU70OXxY2zfIlyWoC8vU2Szz/u4w0tfty6Go262GFZlhSBIVUViFpQptjZ0YntjF0x6HWaNze1mm7jQZ3JMVYfTh4YOaSOXy9FUcgaHAu99GXI2397YhTaHF/kmPSaoVAUaGqMt4MPNjXB4A8gPScQ/3tKU1CjP5Q3QitbU2tx9huJRUmCiqqYv9x2DyaDDI5eMhU4nwGzQ495zRwAA/v7ZHhztSGyyqQVjNcKkgSWhmcMTEx5nsxhx/bRafHLnGfjXT0/FeWOrcV3dQJz8/9k77/Aoyu2Pf2c3W9J7IRBC6EVqqGIBRQMqggXFjpcregUbdq8iYsELNrx6Ldef2PCqeBURuShSRBDpoQmRFkJLL5u6dX5/zL6zuyFlNzuzMxPO53nmIdl9d/IOszs75z3f8z0azjYyzAY95l/bX/xdjfXdbWXiwHR8/JfhYqmE1oiNMIjf1d5Zb6eLx75T2nQ0bwqdjsO1QzqdZTBHEFqGAu9ziNV/FIHnhd6OoXJSZF/W24413/pCSqob7PjQXbs185Lukst5zAY9UmMEib7ccnOrw4lv3dnUv1/ZJyTSJDnrvLccE/oo90yNkr3MwZsIYxi6uGvD8iSWmzNTtUv7pCA2IrS1wz2Zs3mZdK3SDroXyDrGhcvei7w5xIy3RFJzJuEekZUAY5gyX3msxru0xoYKt9/F1zuE986Mi7oiPdaMGqsD6w4Wt7ifXQUVsDt5dIg1IyNBHW64rJ83ANx/SXfxWAFBMjq8SwIa7C4sXJXX7D5Kqj1SezUE3oDQgrJDrH//xzodh4t6JuNft2TjuUnqzKK2hZFdE/FoTi8M6RyHy/upo90WIcAWr7/ecVJU3x0pqUGtzYlwgx7dW6h5JwhCOSjwPodgMvOcEMnMAWBYFyHw3nuqStY+yoxPfz+Oqno7uiZHypaB7Cz28pY38N59ogoNdhcSI40haVEFyJvxFmXmIcx2Mzx13tIdl9PF47tcQR4capk5ACRHmxBjDoOLF9pLSQGr7+7TQZlsNwBxkaSgrM5vR+yW2HREmf7d3kR6tWY7XFKDE+V12Hy0DBwHXJ/dCRMHCu2Ovt/Tstz8dy+ZuVqCO+ac3Cs1GjMu6ubzHMdxePoqoQvDN7tOidn6xsxdvh+WBgf6pcdgeBflJfSEh5lju+Obe0drur67PTJ1eAaMYTr8eqgUn/5+HADENmL9O8aqqt86QRAe6JN5jlBVbxfrHCeESGYOCEFqSrQJdicv1h7JRZ3NgQ9+dWe7x3Q/qwWMVLA2aSdkDryZY+nIEBoo9eso1FEdLq4We2hKhRL13QzRfVnCOu/fjpSiuNqKuAiDIu1oOI6T3GDNY6ymXNYxPS4cRr0ONqcLpxv1SLY6nAF5K9gcLrHlzgUKmygxg7VDRTX4ZqegZDm/WyI6xUeIgfeaA8Wobmi+hGWL+5owQgUyc8ado7Mw46KueP/27CYVBQM6xeFa98LUg1/mwtLo+H7cX4gf9p6BXsfhH9cNoICBIPyge0q0WMrx4g8HcKioGrvdC1sDNF7fLTscB2RmCptKFjCJcwf6hjtHWHuwCA4Xj56pUS223ZAajuMwzJ2tlVtu/vmWApTX2tA5IQKTBqXL9ndCZRi32R2ojgyhA3h6rBmx4QbYnbyPEVSwFFsacLi4BhwHjAxxH2XAU6+cVyRdxvtbd/B01YAOikmYezbjlt1WmCKgt4IZb72OE1vmeWfyV+07g/7P/oSFPzYvWW7Mtvxy1NudSIoyoleIe1w3hkk//yyqxtc7BTfz67MF34Z+6THomhQJq8Ml9oFujNXhxC734mWoe5G3RFKUCU9d0afFVj9PXtEHHWLNOFpSiwf+s0tUMlTV2/HMsn0ABMn9eR0pYCAIf5l2fhdc3DMZVocL93+Ri+35Qr/19lDfLSsREUB+vrBFhK4TCUEAFHifM/xvb2jdzL0Z5q7z3povX+BdY3WIzrn3jukma9akc6IgGZWqBrUpGuxO7CgQvkRDKc3mOM4jN5ewzpsZwPRLj1FEssik038W1cDhZ7/klqizOcTSjWsUkJkzujODNQmczV0uXqyBV9p0iMnN2WfscHE1Zn+1GzanCx9sPHaWk29zsB7S4/qkKi7NZhnv5btP40R5PaJMYWLZD8dxYta7OXfz3SeqYHO4kBRlEg3otEJytAnv3zYUpjAd1uWViIsn81ceQHG1FV2TIvHApT0UniVBaAuO47BwygAkRBpx4IxFVCwN7BSn7MQIgmgWCrzPAepsDvzyZwmA0LmZe8My3juPV0gS9DTFiz8cQEm1FRkJ4bhWZvfvvh2ErMzuk5Wy1a3vKqiEzeFCcrQJ3ZJDe5MtGqxJWOfNsvfnKyAzB4CM+AhEGPWwOVySLJj8tL8IdTYnMhMjMETBNjusTdWfEqgTTlTUoc7mhClMJ/bSVoqsJE/Gu8bqwN2f7kCdTfis2Rwu/N/GY63uo8bqEBccpwyVvyNAa7BFknK3udqV/TsgwuhpD3i1W6Wz8VCpOMYbj8xcPfXdgdC/UywWXD8AAPDuL0cwd/l+fLFNyPy/fN0AxXt3E4QWSYk24x/XDRB/j48wqMZ4kSCIs6HA+xzgl7wSWB0udE6IUKRHau+0GESbwlBrc4orslKyLq8Y/9laAAD4x3UDZJf99kyNQmqMCQ12lyjtkhol6rsZcmS8PfXdytSm6nScKDeXos77G9a7e1BHRYOgnm759PGyOlgdwS0Csf+XHqlRitfZdhFbitXisa9340hJLdJizGLg9tnvx1FZd3Zw6s3KPWdQb3eia3KkoosjDNZSjNF4MaBbchT6pcfA4eLxv31n0BimGFKTzDxQJg3qiHsuFgzYPvotHwBw28hMVfQkJwitclnfVNwyojMAIDtTmwtzIaW+Hhg2TNjqW25zSBBSQ4H3OQCTxI4/L02RC7Jex2EIk5s3UeftdPFnGe74S2WdDY9/vQcAcOfoLiHJqHIch4t6JAMANhwqkeVvMGm2Eg7g3hnvQIysmuNEeR0KyusQpuMwTEHHYiafbuxsfri4GrsK/F9AOVNVj43u866kzBwAUmNMiDaFwenikR9k32vWyqqPCnrbZrml5hv+LMHKvYUw6Dm8fcsQTMnuhN5p0ai1OfHxb8db3Adr13V9didV3IjGhhuQ4m6j1yUxosm+yKLcPNdXbm53urDjuPAe1XqQ+mhOL1zSWzAj7BBrxmPjeyk8I4LQPnMm9sWC6wbguUn9lJ6K+nG5gO3bhc0ljwqTIJqDAu92TnWDHT/tF8x6xisgM2ewm8Xtx88OvB//7x5kP78a29tQA/7s8v1CjWByJB4f3zvoefrLRT2FwPuXPOkD7wa7E7kFlQCUyRB3S46CUa9DdYMDJyuCXw1miwgDM+IQZQprZbR8sDrvg14Z798Ol+KKRRtxzb9+E13/W+Obnafg4oX3dBeFa205jkP3VI9pFwDwPI8dxyvwzc6TsPtZ2nG4uAZfu+uhbxyWIc9kA4D9v7JuYnOu6ovszHhwHIeZY7sDABb/dgy1VkeTr88vrcXW/HLoOODawcrLzBm93WqS5hYDWOC9Nb8chVWeOva9p6pQZ3MiLsKAninKmsQFi17H4c2bBmP2ZT3xf3cMQ7RC/eIJoj1hCtPjhmEZYttCgiDUCQXe7Zzvdwtyy27JkRisoNMly3RuPVbhk0Xdd6oKX+84CbuTx2ur/wxonyv3nsF3uaeh44BXpwwMaY3gBd2TwHFAXlG1zw2yFOw8XgGb04XUGJMitbbGMJ1oBLW/kdzc0mD3O5hjeOq7lW2B5Ml4CwHqvlNVmPHpDtjcx/Po13tQ00wgx+B5Hl9tF+pSbxiqfIAKQAzEdhVU4tPfj2PCol9x3Tu/YfZXuzHr851+SdBf+TEPThePcX1SMVQFfZTTYswwG4Svp2sGd8StIzPF567o3wFdEiNQWWcXS0waw0zVLuyRjLRYs/wT9pOnruiNh8b1xF8v7Nrk8x3jwjE0Mx48Dzz3/X643CsPTCk0rEsCdDK1SQwlUaYw3H9pD1FdQxAEQRDnAhR4t3O+3CbcmE4d1llRueWATrEw6nUorbEi36sNl3ew/duRMuz0U/JbUm3F0+42NPeO6Y7BIa7hjI80YoDbOVRqubm3zFypcybWeXsZrK07WIzhL/6MCYt+bdL8qSl4nsdvR4RMshKyeW9YjfepynrsO1WFaYu3ocbqwIisBHSKD8epynrMX3mgxX1sPVaO42V1iDTqcUV/5RQk3rBFkg83HcMzy/bhYGE1TGE6GPU6/Li/CPd8uqNFE8CdBRVYtb8QOg6qkf3qdByeGN8bU7I74aVr+vt8DvQ6Dn8bI9QJv7/h6FkLC04Xj/+6ZeZqMFXzpndaDB4Y16PFRcLHxveGQc/hf/sK8aL7/ehtrEYQBEEQhDahwLsd88dpC3afrIJBz+GaIcrWopoNegzoJLiBs37eOwsqsPZgMfQ6Dhd0F2qz/7XuiF/7e2f9EZTX2tCnQwzuV6gNzcU9hDlv+FPiwFthIzLAq87bnfFe/UcRZny6HQ12Fw4X1+DuT7f7lUn9375CFFmsiDTqxTp/pYgNNyDdnf286f3fUVpjRZ8OMfj3HUNF064lWwqw8VDzkvOvtgsB3cSB6T6O1Eri3bO1W3Ik5lzVF1ufGof/mzYUZoPQvmn6x9tQZzs7m8/zPF7+30EAgvy5p8K9rr2ZNjoLC6cMRLjx7CD1msGd0CHWjOJqK/6745TPc78dKcXpqgbEmMMwrk9qqKYrGcOzEvDKlIEAgP/beAz/3nBUNHEcqfDiFUEQBEEQbYcC73YMk8Re1jcVSVEmhWfjaSu2zV3L/dpPQrb7uiEdMW9SP3Ac8POBorPMrxpTZ3Ng6Q7h2B4b30t2F/PmuLiXUOf966FSOF3Bm5ABwrHtPlkJQNmbbJbxPnDGgv/tPYO/fbYDdiePsb2SEW0Kw7b8Cjz+9Z4WzddsDhcWrBKCur9e2FUV7YJYjW211YGMhHB8fOcwxJgNOL9bEm5zy5kf/+8eVDdh9lfdYMfKvYLb9BSVyMwBQX7879uH4ssZI/Hz7IvxlwuyEBthwIU9kvHRncMRadRj0+Ey3PHh1rOOa31eCbYeK4cxTIcHx/VU6AgCxximw11uufY7vxxGaY1VfI6Zqk0a1FEV77m2MGlQRzwxQfCseHHlAVRbHYg2haGPAl0pCIIgCIKQBgq82ykNdie+cdc5Th3WWeHZCAzv4gm8fz9aho2HS2HQc7jvkh7omhyFK/p3ANB61vv73adR3eBA54QIXOx2F1eCgZ3iEG0OQ1W9HXvcwXKw7DheAbuTR3qsGZ0TlOul3Med8T5VWY9Z/9kFh4vHpEHp+PftQ/HOrdkI03FYlnsab/x8qNl9/GdrAfLL6pAUZcJdFzVd0xpq2IJCYqQRn/xlBFJiPPW/T0zojYwEQXL+0sqDZ732B5/2VHGhmrJfXNY3FSOaKE0Y2TURn0wfgWizsFgyYdGv+Oz342iwO+F08fiHe2HkzvO7IF1jpjw3De+MxEgjTpTXY+zC9Xh/wxGU1lixap96encHw90XdcXtozy17UO7xEPfDuq7CYIgFCcpSdgIIsRQ4N1O+XF/ISwNDnSMCxdl3EozJDMeHAfkl9Vh7vL9AIRFgQx3gHmvu25zxZ7TyC+tbXIfPM/jk81CG6FbR3ZW1GgoTK8T/283/OmfI3ZrMJn5yG7K1XcDQIzZgIwEIRBzunhcO6QjXrthkHDMPZLwwuTzAACL1hzCt7tOnvX66gY73lwjBOUPjOuhqJu5N7efn4m/XpCF/8wYiaxGjuSRpjAsuE6Q+P5nawF+/qPI53lvUzU1tKfyl+zMePznrpFIjjbhZEU9nl62DxctWIeHv8rFwcJqxJjDxJppLRFu1OOjO4ejX3oMqq0OvLTyIMYuXA+rw4VeqdHo3zFW6SkGBcdxeHZiP+T0E+Ty4/pqTzZPEAShOiIjgZISYYtUtjMJce5BgbfGqaqz487FW3G4uNrnceb2e8PQDNW44MaGG9DLXUN6sLAaxjCd2BoIAPqlx2Jsr2S4eODdX5rOeu86UYn9py0whekwJVt5uS9rKyaVwZqS/bsbM7yLMIcbhnbCwusH+mTbpg7vjHsuFoK1x77eg9WNgtT3NxxFWa0NXZMiMVUF7akYKdFmPH1V32ZrmUd1S8Qd7izj35bsEGXLh4ursbOgEnodh2sV7t3dFs7rGIsNj47FsxP7irXRy9y9ov82pjviIowKz7Bt9O8Ui+WzLsCC6wcgOdqEarcrvVp6dweLXsfhnVuy8b8HLsRNKlEuEQRBEATRNtSRhiLazIsr/8C6vBJsy6/AGzcOwri+qThWWovfj5aD49QntxyelSC2c7ptZOZZrX5mju2OdXkl+O/Ok3hgXA90iPWVv37mznZPHJiO+EjlgwUWeO8qqEBVnR2xEZ6etDVWByKNer8DgFqrA3tOVgFQh4nS3Kv7YurwDGR3jm9y8eaxnF44UV6HH/aewYxPt+PJCb1x14VdUVxtxQe/HhPGjO8Ng15b63tPXtEHZbU2rNhzBo8s3Y380lqx5djYXsk+8nQtEW7U487RWbhlRCaW7TqFDzYeRaQpDNPO76L01IJCr+Nww9AMXNG/A/694ShOVNThphHtJ0jV6Tiq7SYIgiCIdoAid8QbNmzAxIkTkZ6eDo7jsGzZMp/neZ7HnDlz0KFDB4SHh2PcuHE4dMi3lrS8vBy33HILYmJiEBcXh+nTp6OmpsZnzJ49e3DhhRfCbDYjIyMDCxYskPvQQs7j43tjeFYCaqwO3PXpdry19hC+3CZIYi/umay6uk3WzzvcoG9S3jq0SwJGZCXA7uTPqvUudwdDAEQjLKXpGBeO7ilRcPHAJnfbrPJaGx7/eg/Oe/ZH3P9Frt/Ga9/vPg2ni0en+HBRfq8k0WZDi32DdToOb0wdhFtHdgbPAy+tPIjH/7sHC3/MQ73diezMeFEmqyXMBj3enDoYs9xqjLfWHca/fz0KQF2mam3FGKbDDcMy8NNDF+Pbe0c36RquRaJMYXjosp547YZBqiltIAiCIFRGfT0wZoyw1dcrPRviHEORwLu2thYDBw7E22+/3eTzCxYswJtvvol3330XW7ZsQWRkJHJyctDQ0CCOueWWW7B//36sXr0aK1aswIYNGzBjxgzxeYvFgssvvxyZmZnYsWMHFi5ciLlz5+L999+X/fhCSWKUCUv+OgK3j8oEzwOv/PQn3tsgBKxqkvgycvql4Y5RmXjthoHNOq3PukQIeD79/Tj+tf6w+PhX20/A5nRhQKdYnxZKSnOR2+Dtl7wSfLmtAJe+uh5fuuuBv999Gs+v+KNF928AqKq3Y+GPeQCgqQykQa/D85POw9yJfaHjhHZbTJ795ITempX76nQcHsnphQXXD0CYjgPPA0lRRlzSO0XpqREEQRAE0VZcLuCXX4TN5VJ6NsQ5Bse3FhHIPQGOw7fffovJkycDELLd6enpePjhh/HII48AAKqqqpCamoqPPvoIU6dOxYEDB9C3b19s27YNQ4cOBQCsWrUKV1xxBU6ePIn09HS88847+Pvf/47CwkIYjYIk+YknnsCyZctw8ODZjsVNYbFYEBsbi6qqKsTEqF/q95+tBZjz3T7YnTySooz47YlLFWu1FSyvrf5TNOe6/9IeeODSHhjzyjqcKK/HgusH4AYVZR7X5xVj2uJtPo/1So3GlQM64LXVQsu0p6/sg79e2Lyz99zl+/HRb/nonhKF/z1woebk2QCwLq8Y932+CzVWBy7vm4r3bx+q9JQk4bcjpXhhxQHcOjITN7cjCTNBEARBnHPU1gJRUcLPNTVksEYETSDxouru7o8dO4bCwkKMGzdOfCw2NhYjRozA5s2bAQCbN29GXFycGHQDwLhx46DT6bBlyxZxzEUXXSQG3QCQk5ODvLw8VFRUhOhoQstNwzvjP3eNxJDOcXhsfG/NBt0AMPuynnh8vNDH9s01hzBt8VacKK9HbLgBEwekKzw7X0Z2TYTJ/X8dYdTj71f0wYr7L8D9l/bA36/oAwB44YcD+H736SZfn1dYjU9/F2rXn53YV5NBNwCM7ZWCZTNH4+HLeuLl6wYoPR3JOL9bElY+cCEF3QRBEARBEESbUV0hXGGh0IM1NdW3NjQ1NVV8rrCwECkpvpLPsLAwJCQk+IzJyso6ax/sufj4+LP+ttVqhdVqFX+3WCxBHk3oGdolAd/cO1rpaUjC38Z0Q7hBh7nf/4FfDwn101OyO6muJtVs0GPB9QOw+0QV/nphlk9d/V8vzMKpynp89Fs+Hv5qN1KiTRjhZZzG8zyeXb4PThePnH6puFDBvuRS0D0lCvdd2kPpaRAEQRAEQRCEqtBmak0m5s+fj9jYWHHLyFCPnPlcZdroLMy/tj84DtBxwC0qMVVrzKRBHTFnYt+zzOw4jsMzV/VFTr9U2Jwu/PXj7fhw4zHYHEJd0Q97z+D3o+Uwhenw9JV9lZg6QRAEQRAEQRAyo7rAOy0tDQBQVOTbF7ioqEh8Li0tDcXFxT7POxwOlJeX+4xpah/ef6MxTz75JKqqqsTtxIkTwR8QETRMQv/JX0YgK0l7tTh6HYdFUwdjeJcEVFsdmLfiD4x77Rd8s/MkXvrhAADgnou7qcLJnCAIgiAIgiAI6VFd4J2VlYW0tDSsWbNGfMxisWDLli0YNWoUAGDUqFGorKzEjh07xDFr166Fy+XCiBEjxDEbNmyA3W4Xx6xevRq9evVqUmYOACaTCTExMT4boQ5Gdk3EBT2SlJ5GmzEb9Pj8rhF46Zr+SI42oaC8DrO/2o3TVQ3oGBfeZGs1giAIgiAIQmIiIoSNIEKMIoF3TU0NcnNzkZubC0AwVMvNzUVBQQE4jsODDz6IF154AcuXL8fevXtx++23Iz09XXQ+79OnD8aPH4+77roLW7duxaZNmzBr1ixMnToV6emC8dbNN98Mo9GI6dOnY//+/fjyyy+xaNEizJ49W4lDJgiE6XW4eURn/PLoGMy+rCci3bXqcyb2hdmgrrp1giAIgiCIdkdkpOBsXltLjuZEyFGkndj69esxduzYsx6/44478NFHHwmGU88+i/fffx+VlZW44IIL8K9//Qs9e/YUx5aXl2PWrFn4/vvvodPpcN111+HNN99EFGsRAGDPnj2YOXMmtm3bhqSkJNx33314/PHH/Z6n1tqJEdqiotaGkhoreqZGKz0VgiAIgiAIgiACJJB4UfE+3mqGAm+CIAiCIAiCIAiiKTTdx5sgCIIgCIIgCEJyGhqAK68UtoYGpWdDnGOoro83QRAEQRAEQRCE5DidwMqVnp8JIoRQxpsgCIIgCIIgCIIgZIQCb4IgCIIgCIIgCIKQEQq8CYIgCIIgCIIgCEJGKPAmCIIgCIIgCIIgCBmhwJsgCIIgCIIgCIIgZIRczVuAtTi3WCwKz4QgCIIgCIIgiKCorfX8bLGQszkRNCxOZHFjS1Dg3QLV1dUAgIyMDIVnQhAEQRAEQRCEZKSnKz0Doh1RXV2N2NjYFsdwvD/h+TmKy+XC6dOnER0dDY7jlJ5Ou8VisSAjIwMnTpxATEyM0tMhWoDOlTag86Qd6FxpAzpP2oHOlTag86Qd6Fy1DM/zqK6uRnp6OnS6lqu4KePdAjqdDp06dVJ6GucMMTEx9IHWCHSutAGdJ+1A50ob0HnSDnSutAGdJ+1A56p5Wst0M8hcjSAIgiAIgiAIgiBkhAJvgiAIgiAIgiAIgpARCrwJxTGZTHj22WdhMpmUngrRCnSutAGdJ+1A50ob0HnSDnSutAGdJ+1A50o6yFyNIAiCIAiCIAiCIGSEMt4EQRAEQRAEQRAEISMUeBMEQRAEQRAEQRCEjFDgTRAEQRAEQRAEQRAyQoE3IQkbNmzAxIkTkZ6eDo7jsGzZMp/ni4qKMG3aNKSnpyMiIgLjx4/HoUOHfMYUFhbitttuQ1paGiIjIzFkyBD897//9RlTXl6OW265BTExMYiLi8P06dNRU1Mj9+G1K0JxrvLz8zF9+nRkZWUhPDwc3bp1w7PPPgubzRaKQ2wXhOozxbBarRg0aBA4jkNubq5MR9U+CeW5+uGHHzBixAiEh4cjPj4ekydPlvHI2hehOk9//vknJk2ahKSkJMTExOCCCy7AunXr5D68doUU5+rIkSO45pprkJycjJiYGNxwww0oKiryGUP3FMERivNE9xPSEKrPFIPuKZqGAm9CEmprazFw4EC8/fbbZz3H8zwmT56Mo0eP4rvvvsOuXbuQmZmJcePGoba2Vhx3++23Iy8vD8uXL8fevXtx7bXX4oYbbsCuXbvEMbfccgv279+P1atXY8WKFdiwYQNmzJgRkmNsL4TiXB08eBAulwvvvfce9u/fj9dffx3vvvsunnrqqZAdp9YJ1WeK8dhjjyE9PV3WY2qvhOpc/fe//8Vtt92GO++8E7t378amTZtw8803h+QY2wOhOk9XXXUVHA4H1q5dix07dmDgwIG46qqrUFhYGJLjbA8Ee65qa2tx+eWXg+M4rF27Fps2bYLNZsPEiRPhcrnEfdE9RXCE4jzR/YQ0hOozxaB7imbgCUJiAPDffvut+HteXh4PgN+3b5/4mNPp5JOTk/l///vf4mORkZH8J5984rOvhIQEccwff/zBA+C3bdsmPv+///2P5ziOP3XqlExH076R61w1xYIFC/isrCzpJn8OIfd5WrlyJd+7d29+//79PAB+165dshzHuYBc58put/MdO3bkP/jgA3kP4BxBrvNUUlLCA+A3bNggPm+xWHgA/OrVq2U6mvZNW87Vjz/+yOt0Or6qqkocU1lZyXMcJ54HuqeQFrnOU1PQ/URwyH2u6J6ieSjjTciO1WoFAJjNZvExnU4Hk8mEjRs3io+df/75+PLLL1FeXg6Xy4UvvvgCDQ0NGDNmDABg8+bNiIuLw9ChQ8XXjBs3DjqdDlu2bAnNwbRzpDpXTVFVVYWEhATZ5n4uIeV5Kioqwl133YVPP/0UERERITuGcwWpztXOnTtx6tQp6HQ6DB48GB06dMCECROwb9++kB5Pe0Wq85SYmIhevXrhk08+QW1tLRwOB9577z2kpKQgOzs7pMfUXvHnXFmtVnAc59N32Gw2Q6fTiWPonkJepDpPTUH3E9Ii5bmie4qWocCbkJ3evXujc+fOePLJJ1FRUQGbzYZ//OMfOHnyJM6cOSOO++qrr2C325GYmAiTyYS7774b3377Lbp37w5AqK1LSUnx2XdYWBgSEhJIwicRUp2rxhw+fBj//Oc/cffdd4fqUNo1Up0nnucxbdo03HPPPT43n4R0SHWujh49CgCYO3cunn76aaxYsQLx8fEYM2YMysvLFTm29oRU54njOPz888/YtWsXoqOjYTab8dprr2HVqlWIj49X6vDaFf6cq5EjRyIyMhKPP/446urqUFtbi0ceeQROp1McQ/cU8iLVeWoM3U9Ij1Tniu4pWocCb0J2DAYDvvnmG/z5559ISEhAREQE1q1bhwkTJkCn87wFn3nmGVRWVuLnn3/G9u3bMXv2bNxwww3Yu3evgrM/t5DjXJ06dQrjx4/HlClTcNddd4XycNotUp2nf/7zn6iursaTTz6p1KG0e6Q6V6yG7u9//zuuu+46ZGdnY/HixeA4DkuXLlXk2NoTUp0nnucxc+ZMpKSk4Ndff8XWrVsxefJkTJw4sdlAgggMf85VcnIyli5diu+//x5RUVGIjY1FZWUlhgwZ4nM+CfmQ4zzR/YQ8SHWu6J7CDxSWuhPtEDSqHfGmsrKSLy4u5nme54cPH87fe++9PM/z/OHDh8+qL+F5nr/00kv5u+++m+d5nv+///s/Pi4uzud5u93O6/V6/ptvvpH4KM4N5DpXjFOnTvE9evTgb7vtNt7pdEp/AOcIcp2nSZMm8Tqdjtfr9eIGgNfr9fztt98u3wG1Y+Q6V2vXruUB8L/++qvPmOHDh/NPPfWUxEfR/pHrPP38889n1UHyPM93796dnz9/vsRHcW7QlnPlTUlJCV9RUcHzPM+npqbyCxYs4Hme7imkRq7zxKD7CemQ61zRPUXr0LIfEVJiY2ORnJyMQ4cOYfv27Zg0aRIAoK6uDgDOWuHU6/VipmfUqFGorKzEjh07xOfXrl0Ll8uFESNGhOgIzh2COVeAsDI9ZswYMTNHWQZ5COY8vfnmm9i9ezdyc3ORm5uLlStXAgC+/PJLvPjiiyE8inODYM5VdnY2TCYT8vLyxOftdjvy8/ORmZkZoiM4NwjmPDU3RqfTNen8SwRHc+fKm6SkJMTFxWHt2rUoLi7G1VdfDYDuKUJJMOcJoPuJUBLMuaJ7Cj9QOvIn2gfV1dX8rl27+F27dvEA+Ndee43ftWsXf/z4cZ7nef6rr77i161bxx85coRftmwZn5mZyV977bXi6202G9+9e3f+wgsv5Lds2cIfPnyYf+WVV3iO4/gffvhBHDd+/Hh+8ODB/JYtW/iNGzfyPXr04G+66aaQH6+WCcW5OnnyJN+9e3f+0ksv5U+ePMmfOXNG3Aj/CNVnyptjx46RA2kbCNW5euCBB/iOHTvyP/74I3/w4EF++vTpfEpKCl9eXh7yY9YioThPJSUlfGJiIn/ttdfyubm5fF5eHv/II4/wBoOBz83NVeS4tUiw54rnef7DDz/kN2/ezB8+fJj/9NNP+YSEBH727Nk+Y+ieIjhCcZ7ofkIaQvWZ8obuKc6GAm9CEtatW8cDOGu74447eJ7n+UWLFvGdOnXiDQYD37lzZ/7pp5/mrVarzz7+/PNP/tprr+VTUlL4iIgIfsCAAWe1bSkrK+NvuukmPioqio+JieHvvPNOvrq6OlSH2S4IxblavHhxk3+D1vr8J1SfKW/oS7JthOpc2Ww2/uGHH+ZTUlL46Ohofty4cWfJnonmCdV52rZtG3/55ZfzCQkJfHR0ND9y5Eh+5cqVoTrMdoEU5+rxxx/nU1NTeYPBwPfo0YN/9dVXeZfL5TOG7imCIxTnie4npCFUnylv6J7ibDie5/ng8+YEQRAEQRAEQRAEQTQFFUkQBEEQBEEQBEEQhIxQ4E0QBEEQBEEQBEEQMkKBN0EQBEEQBEEQBEHICAXeBEEQBEEQBEEQBCEjFHgTBEEQBEEQBEEQhIxQ4E0QBEEQBEEQBEEQMkKBN0EQBEEQBEEQBEHICAXeBEEQBEEQBEEQBCEjFHgTBEEQBEEQBEEQhIxQ4E0QBEEQBEEQBEEQMkKBN0EQBEEQBEEQBEHICAXeBEEQBEEQBEEQBCEjFHgTBEEQBEEQBEEQhIxQ4E0QBEEQBEEQBEEQMkKBN0EQBEEQBEEQBEHICAXeBEEQBEEQBEEQBCEjFHgTBEEQBEEQBEEQhIxQ4E0QBEEQBEEQBEEQMkKBN0EQBEGoiI8++ggcx2H79u3iYytXrsTcuXOVm1QzrF+/HhzH4euvvxYfY/Nnm9lsRnp6OnJycvDmm2+iuro6qL955swZPPHEExg7diyio6PBcRzWr18f5JEQBEEQhLxQ4E0QBEEQKmflypV47rnnlJ5GQMybNw+ffvop3nnnHdx3330AgAcffBD9+/fHnj172rzfvLw8/OMf/8CpU6fQv39/qaZLEARBELISpvQECIIgCIJof0yYMAFDhw4Vf3/yySexdu1aXHXVVbj66qtx4MABhIeHB7zf7OxslJWVISEhAV9//TWmTJki5bQJgiAIQhYo400QBEEQKmbatGl4++23AcBHws1wuVx444030K9fP5jNZqSmpuLuu+9GRUWFz366dOmCq666CuvXr8fQoUMRHh6O/v37izLtb775Bv3794fZbEZ2djZ27dol+bFccskleOaZZ3D8+HF89tln4uN2ux0HDx7EmTNnWt1HdHQ0EhISJJ8bQRAEQcgJBd4EQRAEoWLuvvtuXHbZZQCATz/9VNy8n3/00UcxevRoLFq0CHfeeSeWLFmCnJwc2O12n30dPnwYN998MyZOnIj58+ejoqICEydOxJIlS/DQQw/h1ltvxXPPPYcjR47ghhtugMvlkvx4brvtNgDATz/9JD526tQp9OnTB08++aTkf48gCIIg1ABJzQmCIAhCxYwaNQo9e/bE6tWrceutt/o8t3HjRnzwwQdYsmQJbr75ZvHxsWPHYvz48Vi6dKnP43l5efjtt98watQoAEDfvn2Rk5ODu+66CwcPHkTnzp0BAPHx8bj77ruxYcMGjBkzRtLj6dSpE2JjY3HkyBFJ90sQBEEQaoYy3gRBEAShUZYuXYrY2FhcdtllKC0tFbfs7GxERUVh3bp1PuP79u0rBt0AMGLECACCBJwF3d6PHz16VJZ5R0VF+bibd+nSBTzP46OPPpLl7xEEQRCE0lDGmyAIgiA0yqFDh1BVVYWUlJQmny8uLvb53Tu4BoDY2FgAQEZGRpOPN64Tl4qamppm50wQBEEQ7REKvAmCIAhCo7hcLqSkpGDJkiVNPp+cnOzzu16vb3Jcc4/zPB/cBJvg5MmTqKqqQvfu3SXfN0EQBEGoFQq8CYIgCELleLuYe9OtWzf8/PPPGD16dJtacykBM4bLyclReCYEQRAEETqoxpsgCIIgVE5kZCQAoLKy0ufxG264AU6nE88///xZr3E4HGeNV5q1a9fi+eefR1ZWFm655Rbx8UDaiREEQRCEFqGMN0EQBEGonOzsbADA/fffj5ycHOj1ekydOhUXX3wx7r77bsyfPx+5ubm4/PLLYTAYcOjQISxduhSLFi3C9ddfr8ic//e//+HgwYNwOBwoKirC2rVrsXr1amRmZmL58uUwm83iWNZO7I477vDLYO2FF14AAOzfvx+AkEXfuHEjAODpp5+W/mAIgiAIIkgo8CYIgiAIlXPttdfivvvuwxdffIHPPvsMPM9j6tSpAIB3330X2dnZeO+99/DUU08hLCwMXbp0wa233orRo0crNuc5c+YAAIxGIxISEtC/f3+88cYbuPPOOxEdHR3Uvp955hmf3z/88EPxZwq8CYIgCDXC8XI4pxAEQRAEQRAEQRAEAYBqvAmCIAiCIAiCIAhCVijwJgiCIAiCIAiCIAgZocCbIAiCIAiCIAiCIGSEAm+CIAiCIAiCIAiCkBEKvAmCIAiCIAiCIAhCRijwJgiCIAiCIAiCIAgZocCbIAiCIAiCIAiCIGQkTOkJqBmXy4XTp08jOjoaHMcpPR2CIAiCIAiCIAhCJfA8j+rqaqSnp0OnayWnzQfASy+9xA8dOpSPiorik5OT+UmTJvEHDx4Uny8rK+NnzZrF9+zZkzebzXxGRgZ/33338ZWVlT77AXDW9p///MdnzLp16/jBgwfzRqOR79atG7948eKz5vPWW2/xmZmZvMlk4ocPH85v2bLF5/n6+nr+3nvv5RMSEvjIyEj+2muv5QsLC/0+3hMnTjQ5V9poo4022mijjTbaaKONNtpoA8CfOHGi1dgyoIz3L7/8gpkzZ2LYsGFwOBx46qmncPnll+OPP/5AZGQkTp8+jdOnT+OVV15B3759cfz4cdxzzz04ffo0vv76a599LV68GOPHjxd/j4uLE38+duwYrrzyStxzzz1YsmQJ1qxZg7/+9a/o0KEDcnJyAABffvklZs+ejXfffRcjRozAG2+8gZycHOTl5SElJQUA8NBDD+GHH37A0qVLERsbi1mzZuHaa6/Fpk2b/Dre6OhoAMCJEycQExMTyH8VQRAEQRAEQRAE0Y6xWCzIyMgQ48aW4NwZ6DZRUlKClJQU/PLLL7jooouaHLN06VLceuutqK2tRViYEOdzHIdvv/0WkydPbvI1jz/+OH744Qfs27dPfGzq1KmorKzEqlWrAAAjRozAsGHD8NZbbwEQZOEZGRm477778MQTT6CqqgrJycn4/PPPcf311wMADh48iD59+mDz5s0YOXJkq8dnsVgQGxuLqqoqCrwJgiAIgiAIQsvYbMDf/y78/OKLgNGo7HwIzRNIvBiUuVpVVRUAICEhocUxMTExYtDNmDlzJpKSkjB8+HB8+OGH8I7/N2/ejHHjxvmMz8nJwebNmwEANpsNO3bs8Bmj0+kwbtw4ccyOHTtgt9t9xvTu3RudO3cWxxAEQRAEQRAEcY5gtwOvvCJsdrvSsyHOMdpsruZyufDggw9i9OjROO+885ocU1paiueffx4zZszweXzevHm45JJLEBERgZ9++gn33nsvampqcP/99wMACgsLkZqa6vOa1NRUWCwW1NfXo6KiAk6ns8kxBw8eFPdhNBp9JOxsTGFhYZPztVqtsFqt4u8Wi6X1/wiCIAiCIAiCIAiCaIE2B94zZ87Evn37sHHjxiaft1gsuPLKK9G3b1/MnTvX57lnnnlG/Hnw4MGora3FwoULxcBbKebPn4/nnntO0TkQBEEQBEEQBEEQ7Ys2Bd6zZs3CihUrsGHDBnTq1Oms56urqzF+/HhER0fj22+/hcFgaHF/I0aMwPPPPw+r1QqTyYS0tDQUFRX5jCkqKkJMTAzCw8Oh1+uh1+ubHJOWlgYASEtLg81mQ2VlpU/W23tMY5588knMnj1b/J0Vy7eG0+mEneQqhAQYDAbo9Xqlp0EQBEEQBEEQhIQEFHjzPI/77rsP3377LdavX4+srKyzxlgsFuTk5MBkMmH58uUwm82t7jc3Nxfx8fEwmUwAgFGjRmHlypU+Y1avXo1Ro0YBAIxGI7Kzs7FmzRrRoM3lcmHNmjWYNWsWACA7OxsGgwFr1qzBddddBwDIy8tDQUGBuJ/GmEwmcQ7+wPM8CgsLUVlZ6fdrCKI14uLikJaWRr3jCYIgCIIgCKKdEFDgPXPmTHz++ef47rvvEB0dLdZKx8bGIjw8HBaLBZdffjnq6urw2WefwWKxiHXSycnJ0Ov1+P7771FUVISRI0fCbDZj9erVeOmll/DII4+If+eee+7BW2+9hcceewx/+ctfsHbtWnz11Vf44YcfxDGzZ8/GHXfcgaFDh2L48OF44403UFtbizvvvFOc0/Tp0zF79mwkJCQgJiYG9913H0aNGuWXo7k/sKA7JSUFERERFCgRQcHzPOrq6lBcXAwA6NChg8IzIgiCIAiCIAhCCgIKvN955x0AwJgxY3weX7x4MaZNm4adO3diy5YtAIDu3bv7jDl27Bi6dOkCg8GAt99+Gw899BB4nkf37t3x2muv4a677hLHZmVl4YcffsBDDz2ERYsWoVOnTvjggw/EHt4AcOONN6KkpARz5sxBYWEhBg0ahFWrVvkYrr3++uvQ6XS47rrrYLVakZOTg3/961+BHHKzOJ1OMehOTEyUZJ8EER4eDgAoLi5GSkoKyc4JgiAIH3iex4If83BeeiyuHEALtARBEFohqD7e7Z2W+rI1NDSIiwksWCIIKaivr0d+fj6ysrL8KtUgCIIgzh32narCVf/ciNQYE7Y8Na71FxAE4cHlAg4cEH7u0wfQBdVZmSAC6uPdZldzQoDk5YTU0HuKIAiCaI7i6gYAQEm1FU4XD72OvjMIwm90OqBfP6VnQZyj0DIPoSnmzp2LQYMGKT0NAELJxYMPPqj0NAiCIIhziNIaGwDAxQOVdTaFZ0MQBEH4CwXe5yiFhYV44IEH0L17d5jNZqSmpmL06NF45513UFdXp/T02sTcuXPBcVyLW1tYv349OI4j93qCIAhCccprPcE2C8IJgvATmw2YO1fYbPT5IUILSc3PQY4ePYrRo0cjLi4OL730Evr37w+TyYS9e/fi/fffR8eOHXH11Vc3+Vq73d5qX3aleOSRR3DPPfeIvw8bNgwzZszwMe7zxmazwWg0hmp6BEEQBBE03oF3WY0VQLRykyEIrWG3A889J/z86KMA3QcSIYQy3ucg9957L8LCwrB9+3bccMMN6NOnD7p27YpJkybhhx9+wMSJE8WxHMfhnXfewdVXX43IyEi8+OKLAASH+27dusFoNKJXr1749NNPxdfk5+eD4zjk5uaKj1VWVoLjOKxfvx6AJ4u8Zs0aDB06FBERETj//PORl5fnM9eXX34ZqampiI6OxvTp09HQ0NDscUVFRSEtLU3c9Ho9oqOjxd+nTp2KWbNm4cEHH0RSUhJycnJanWt+fj7Gjh0LAIiPjwfHcZg2bZo41uVy4bHHHkNCQgLS0tIwd+7cAM8GQRAEQfhPaY1V/LnE62eCIAhC3VDgLSE8z6PO5lBk89ecvqysDD/99BNmzpyJyMjIJsc0lmTPnTsX11xzDfbu3Yu//OUv+Pbbb/HAAw/g4Ycfxr59+3D33XfjzjvvxLp16wL+P/v73/+OV199Fdu3b0dYWBj+8pe/iM999dVXmDt3Ll566SVs374dHTp0CLod3Mcffwyj0YhNmzbh3XffbXV8RkYG/vvf/wIA8vLycObMGSxatMhnf5GRkdiyZQsWLFiAefPmYfXq1UHNkSAIgiCawzfjTVJZgiAIrUBScwmptzvRd86PivztP+blIMLY+uk8fPgweJ5Hr169fB5PSkoSs8kzZ87EP/7xD/G5m2++GXfeeaf4+0033YRp06bh3nvvBQDMnj0bv//+O1555RUxO+wvL774Ii6++GIAwBNPPIErr7wSDQ0NMJvNeOONNzB9+nRMnz4dAPDCCy/g559/bjHr3Ro9evTAggULxN/z8/NbHK/X65GQkAAASElJQVxcnM/zAwYMwLPPPivu+6233sKaNWtw2WWXtXmOBEEQBNEc3sF2KWW8CYIgNANlvAkAwNatW5Gbm4t+/frBavX9Ih86dKjP7wcOHMDo0aN9Hhs9ejQOsL6IATBgwADx5w4dOgAAiouLxb8zYsQIn/GjRo0K+G94k52dHdTrG+M9f0A4BjZ/giAIgpAayngTBEFoE8p4S0i4QY8/5uUo9rf9oXv37uA47qxa6q5duwr7CQ8/6zXNSdKbQ6cT1nO85e92u73Jsd5GbUzi7nK5Avp7gdD4WAKZa1M0NprjOE7W+RMEQRDnLjzPo6zWszhOGW+CIAjtQBlvCeE4DhHGMEU2f1tlJSYm4rLLLsNbb72F2traNh1nnz59sGnTJp/HNm3ahL59+wIAkpOTAQBnzpwRn/c2Lwvk72zZssXnsd9//z3g/bSEP3NlzudOp1PSv00QBEEQgVBnc6LB7lncLa2ljDdBEIRWoIz3Oci//vUvjB49GkOHDsXcuXMxYMAA6HQ6bNu2DQcPHmxVjv3oo4/ihhtuwODBgzFu3Dh8//33+Oabb/Dzzz8DELLmI0eOxMsvv4ysrCwUFxfj6aefDnieDzzwAKZNm4ahQ4di9OjRWLJkCfbv3y9m56XAn7lmZmaC4zisWLECV1xxBcLDwxEVFSXZHAiCIAjCH8obBdql1ZTxJoiAMJuBrVs9PxNECKGM9zlIt27dsGvXLowbNw5PPvkkBg4ciKFDh+Kf//wnHnnkETz//PMtvn7y5MlYtGgRXnnlFfTr1w/vvfceFi9ejDFjxohjPvzwQzgcDmRnZ+PBBx/ECy+8EPA8b7zxRjzzzDN47LHHkJ2djePHj+Nvf/tbwPtpjdbm2rFjRzz33HN44oknkJqailmzZkk+B4IgCIJoDSYt1+sElVtZrdXvriYEQQDQ64Fhw4RN71+ZJkFIBcfTFbtZLBYLYmNjUVVVhZiYGJ/nGhoacOzYMWRlZcFMK2aEhNB7iyAIgmiKNQeKMP3j7eieEoXDxTUAgH3P5SDKRAJGgiAIJWgpXmwMZbwJgiAIgiA0QJlbat4pPlw0VS0jgzWC8B+bDVi4UNhs5JFAhBYKvAmCIAiCIDQAax+WEGlEUrRg/EnO5gQRAHY78NhjwhZAFxuCkAIKvAmCIAiCIDRAubuVWFKUCYmRJgBAKfXyJgiC0AQUeBMEQRAEQWgAn4x3FAu8KeNNEAShBciNgyAIgiCIdsG7vxwBANx9UVdwHKfwbKSH1XgnRhqR7Jaal1HGmyAIQhNQ4E0QBEEQhOapqLXh5f8dBCAYjj11RZ92F3yzPt6JUUYvqTllvAmCILQASc0JgiAIgtA8LBsMAP/+9Rj+tf6IgrORB+ZgnhBpQlIUZbwJgiC0RECB9/z58zFs2DBER0cjJSUFkydPRl5ens+YhoYGzJw5E4mJiYiKisJ1112HoqIinzEFBQW48sorERERgZSUFDz66KNwOBw+Y9avX48hQ4bAZDKhe/fu+Oijj86az9tvv40uXbrAbDZjxIgR2Lp1a8BzIQiCIAhC+1TVCwFomE7Ici/8MQ+f/n5cySlJCs/zPlLzRHeNdwllvAmCIDRBQIH3L7/8gpkzZ+L333/H6tWrYbfbcfnll6O2tlYc89BDD+H777/H0qVL8csvv+D06dO49tprxeedTieuvPJK2Gw2/Pbbb/j444/x0UcfYc6cOeKYY8eO4corr8TYsWORm5uLBx98EH/961/x448/imO+/PJLzJ49G88++yx27tyJgQMHIicnB8XFxX7PhSAIgiCI9kFlndAaqG96DO6/pDsAYM53+/Bd7iklpyUZtTYnrA4XAEFqzszVqI83QQSA2QysWydsZrPSsyHONfggKC4u5gHwv/zyC8/zPF9ZWckbDAZ+6dKl4pgDBw7wAPjNmzfzPM/zK1eu5HU6HV9YWCiOeeedd/iYmBjearXyPM/zjz32GN+vXz+fv3XjjTfyOTk54u/Dhw/nZ86cKf7udDr59PR0fv78+X7PpTWqqqp4AHxVVdVZz9XX1/N//PEHX19f79e+2juZmZn866+/rvQ0FGfx4sV8bGys+Puzzz7LDxw4MKB90HuLIAgicL7efoLPfHwFf+sHv/Mul4ufs2wvn/n4Cr7rkz/wW4+VKT29oDleWstnPr6C7/30/3ie5/k/Cy185uMr+AFzf1R4ZgRBEOcuLcWLjQmqxruqqgoAkJCQAADYsWMH7HY7xo0bJ47p3bs3OnfujM2bNwMANm/ejP79+yM1NVUck5OTA4vFgv3794tjvPfBxrB92Gw27Nixw2eMTqfDuHHjxDH+zKUxVqsVFovFZ2tvcBzX4jZ37tw27Xfbtm2YMWNGwK87fvw4wsPDkZSU1OK8pk2b1qZ5AUCXLl3wxhtvtDpu9+7duPrqq5GSkgKz2YwuXbrgxhtv9FFRBMojjzyCNWvWiL9PmzYNkydPbvP+CIIgiKaprBcy3nERRnAch2cn9sNlfVPhdPFYnnta4dkFT2ktq+8WartZxruq3g6bOxNOEATRXmiwO1FkaYDD2X6ub212NXe5XHjwwQcxevRonHfeeQCAwsJCGI1GxMXF+YxNTU1FYWGhOMY76GbPs+daGmOxWFBfX4+Kigo4nc4mxxw8eNDvuTRm/vz5eO655/z8H9AmZ86cEX/+8ssvMWfOHJ86/aioKPFnnufhdDoRFtb62yQ5OblN8/nuu+8wduxYfPzxx3A6nQCA3377Dddddx3y8vIQExMDAAgPD2/T/v2lpKQEl156Ka666ir8+OOPiIuLQ35+PpYvX+5TShEoUVFRPv+nBEEQhDxU1Qn1z3HhBgCATsfhkt4pWP1HEU5U1Ck5NUkor/E4mgNAbLgBeh0Hp4tHea0NabHals1WN9hhd/LiwgJByILdDrz/vvDzjBmAwaDsfIhm2Xm8Ajd/sAU9U6Pw00MXKz0dSWhzxnvmzJnYt28fvvjiCynnoyhPPvkkqqqqxO3EiRNKT0ly0tLSxC02NhYcx4m/Hzx4ENHR0fjf//6H7OxsmEwmbNy4EUeOHMGkSZOQmpqKqKgoDBs2DD///LPPfhtnlTmOwwcffIBrrrkGERER6NGjB5YvX37WfL777jtcffXVSE5OFufBFBQpKSniY8xsz2w2o2vXrnjuuedEQz6e5zF37lx07twZJpMJ6enpuP/++wEAY8aMwfHjx/HQQw+J2fOm2LRpE6qqqvDBBx9g8ODByMrKwtixY/H6668jKysLgGD4x3EcfvjhBwwYMABmsxkjR47Evn37mv3/njt3LgYNGiT+/PHHH+O7774T57J+/Xq/zhtBEATRMp6Mt+dGOiM+AgBworwdBN5exmqAsLDAftZ6SzGe53H1W5sw9pX1qLc5lZ4O0Z6x2YBZs4TNRh0B1ExxtXBdY+qe9kCbAu9Zs2ZhxYoVWLduHTp16iQ+npaWBpvNhsrKSp/xRUVFSEtLE8c0dhZnv7c2JiYmRpQl6/X6Jsd476O1uTTGZDIhJibGZ2sTtbXNbw0N/o+tr/dvrMQ88cQTePnll3HgwAEMGDAANTU1uOKKK7BmzRrs2rUL48ePx8SJE1FQUNDifp577jnccMMN2LNnD6644grccsstKC8vF5+vrKzExo0bcfXVV7e4n19//RW33347HnjgAfzxxx9477338NFHH+HFF18EAPz3v//F66+/jvfeew+HDh3CsmXL0L9/fwDAN998g06dOmHevHk4c+aMT8bfm7S0NDgcDnz77bfgeb7F+Tz66KN49dVXsW3bNiQnJ2PixImw2+0tvgYQZOc33HADxo8fL87l/PPPb/V1BEEQROtUuQPv2HCvwDtBUEudrKhv9dqudjxSc89NKHM213rgXW114FhpLarq7ThVqf1FEoIggqe4WoiZUqLP0cCb53nMmjUL3377LdauXStmAhnZ2dkwGAw+Na15eXkoKCjAqFGjAACjRo3C3r17fepmV69ejZiYGPTt21cc470PNobtw2g0Ijs722eMy+XCmjVrxDH+zEU2oqKa3667zndsSkrzYydM8B3bpUvT4yRm3rx5uOyyy9CtWzckJCRg4MCBuPvuu3HeeeehR48eeP7559GtW7cmM9jeTJs2DTfddBO6d++Ol156CTU1NT4t31auXIkBAwYgPT29xf0899xzeOKJJ3DHHXega9euuOyyy/D888/jvffeAyC0p0tLS8O4cePQuXNnDB8+HHfddRcAwX9Ar9cjOjpazJ43xciRI/HUU0/h5ptvRlJSEiZMmICFCxc22X7u2WefxWWXXYb+/fvj448/RlFREb799tsWjwEQZOfh4eEwmUziXIxGktQRBEFIAXM1j4vwXFfT48Kh4wCrw4WSam0Hp42l5gDEXt6lGu/lXVTlSUpQX3KCIACg2CJcs1NitF1G401AgffMmTPx2Wef4fPPP0d0dDQKCwtRWFiIendmNjY2FtOnT8fs2bOxbt067NixA3feeSdGjRqFkSNHAgAuv/xy9O3bF7fddht2796NH3/8EU8//TRmzpwJk0lY0bjnnntw9OhRPPbYYzh48CD+9a9/4auvvsJDDz0kzmX27Nn497//jY8//hgHDhzA3/72N9TW1uLOO+/0ey5E0wwdOtTn95qaGjzyyCPo06cP4uLiEBUVhQMHDrSa8R4wYID4c2RkJGJiYnwWXJjMvDV2796NefPmifXSUVFRuOuuu3DmzBnU1dVhypQpqK+vR9euXXHXXXfh22+/PasvvD+8+OKLKCwsxLvvvot+/frh3XffRe/evbF3716fcd4LNwkJCejVqxcOHDgQ8N8jCIIgpEOUmntlvA16HTrECllvrdd5lzWSmgNoNy3Fiiye+TNJPUEQ5zZMat6eMt4Bmau98847AIS6WW8WL14suk6//vrr0Ol0uO6662C1WpGTk4N//etf4li9Xo8VK1bgb3/7G0aNGoXIyEjccccdmDdvnjgmKysLP/zwAx566CEsWrQInTp1wgcffICcnBxxzI033oiSkhLMmTMHhYWFGDRoEFatWuVjuNbaXGSjpqb55/R6399bcszWNVoXyc9v85QCITIy0uf3Rx55BKtXr8Yrr7yC7t27Izw8HNdffz1srdTGGBoZVnAcB5dLcCa02WxYtWoVnnrqqVbnU1NTg+eee67JHuxmsxkZGRnIy8vDzz//jNWrV+Pee+/FwoUL8csvv5w1h9ZITEzElClTMGXKFLz00ksYPHgwXnnlFXz88ccB7YcgCIIILaK5WoTvdb9TfDhOVdbjRHk9sjOVmJk0sMA7IbKpjLfWA2+vjDcF3gRBwCM1Tz5XA29/6qPMZjPefvttvP32282OyczMxMqVK1vcz5gxY7Br164Wx8yaNQuzZs0Kai6y0ChwVWSshGzatAnTpk3DNddcA0AIhPODXARYv3494uPjMXDgwFbHDhkyBHl5eejevXuzY8LDwzFx4kRMnDgRM2fOFDPVQ4YMgdFoFB3TA8FoNKJbt25nuZr//vvv6Ny5MwCgoqICf/75J/r06eP3PtsyF4IgCKJlmjJXA4CMhAhsOVaueYO18tqzjYY8GW9tB6tF1SQ1JwjClxIx491+pOZtbidGnDv06NED33zzDSZOnAiO4/DMM8+Imeu2snz5cr9k5gAwZ84cXHXVVejcuTOuv/566HQ67N69G/v27cMLL7yAjz76CE6nEyNGjEBERAQ+++wzhIeHIzNTSG106dIFGzZswNSpU2EymZCUlHTW31ixYgW++OILTJ06FT179gTP8/j++++xcuVKLF682GfsvHnzkJiYiNTUVPz9739HUlKS3725u3Tpgh9//BF5eXlITExEbGxswFl5giAIwheXi/cyV/P1zhCdzbUuNa85O+PNzNVKtJ7x9qrxZgsMBEGc2zCpeXvKeLe5nRhx7vDaa68hPj4e559/PiZOnIicnBwMGTIkqH0GEnjn5ORgxYoV+OmnnzBs2DCMHDkSr7/+uhhYx8XF4d///jdGjx6NAQMG4Oeff8b333+PxMREAEKgnJ+fj27dujXbb7xv376IiIjAww8/jEGDBmHkyJH46quv8MEHH+C2227zGfvyyy/jgQceQHZ2NgoLC/H999/7bZJ21113oVevXhg6dCiSk5OxadMmv15HEARBNE91gwNMlOftag54nM1PlNc3fplm4Hm+Ram51rPE3jXeJDUnZMVkAlasEDZT+wno2hsNdieqGwS/ppSY9nOeOF7r/TVkxGKxIDY2FlVVVWe1FmtoaMCxY8eQlZUFs7n9SCBCwc6dO3HJJZegpKREU9ne9evXY+zYsaioqEBcXJxsf4feWwRBEIFxvKwWFy9cj0ijHvvnjfd5bnt+Oa5/dzM6xYdj4+OXKDTD4KhusKP/3J8AAH/My0GEURAs7jtVhav+uREp0SZs/fs4JacYFNf8axN2FVQCAM7vlojP7yITXII4lykoq8NFC9fBbNDhwLzx4DhO6Sk1S0vxYmMo402EHIfDgX/+85+aCroJgiAI9dJUKzFGRoIgNT9T1QCHM7gyKaVgTt/hBr0YdAOeGu/yWhtcLu3mUXyl5pTxJohzHU8Pb7Oqg+5AoRpvIuQMHz4cw4cPV3oaBEEQRDuhUqzvPntBNznKBGOYDjaHC2eqGsRAXEuIrcSifBcWmOzc4a5xj4/0r+xJTbhcvFjLCZDUnJAZux1YskT4+ZZbAEoCqZL22EoMoIw3QfjNmDFjwPO8rDJzgiAIInAqm2klBgA6HYdO8azOW5sGa6yGO7FRYG0M04mLDWUaNSUrr7PB4ZWtr6i1+dVFhyDahM0G3HmnsLXSFpdQjpJ2aKwGUOBNEARBEITGqWqmlRhD687mzOk7oYmMNsuCl1RrM4hgPbxjzIII0+HiYal3KDklgiAUxiM1p8CbIAiCIPzmRHkdqhvsSk+DaMewGu+mpOaAx9m8QKMZ71KW8Y46+yZU7OWt0Yw3C7wzEiIQZRKCb60eC0EQ0lDs7nSQEtO+TIYp8A4SkkMRUkPvKaI9UWRpwKWv/oLb/m+r0lMh2jGewLvpGmcx463RlmLMcKyx1BzwtBQrrdZmsMpaiaXFmMWMPhmsEcS5TXvs4Q1Q4N1mmCN3XZ02V88J9cLeU+T6TrQH/jhtgc3pwoEzFlpUImSjsr75Gm/A42yuXan52T28GZ6MtzaDVZbxTvEKvLV6LAShFiwNdsxfeQDz/3dAk9+97dVcjVzN24her0dcXByKi4sBABEREe3K7p4IPTzPo66uDsXFxYiLi4Ner1d6SgQRNEzaa3W4UGtzilJSQlmcLh5fbjuBDnFmXNwjGTqdtr+/qlg7seak5hrPeJfWCDehTUnNEyNNPmO0Bgu8U2NMKLZQxpsgguWn/YV45rt9oprkmsEd0Tut5f7SaqPEq51Ye4LugIIgLS0NAMTgmyCkIC4uTnxvEYTW8XaRLquxUuCtErYeK8dT3+4FAHRNjsRfRmfhuiGdEG7U5oJfZWvmau4a79IaK+ptTs0dZ4tS82i31LxGm8EqCw5SY8w4FSksjJRpdBGBIJSk2NKAud/vx8q9hT6PbzlarqnA2+F0iaqX9iY1pzugIOA4Dh06dEBKSgrsdjIOIoLHYDBQpptoV3hLe0trrMhMjFRwNgSj0OLJ/B4tqcXTy/bhlZ/ycNPwzrg+uxO6JUcpOLvAYe3Emqvxjg03INoUhmqrAycr6tAjNTqU0wsasZ1YVPNSc61nvNNizEiIIqk5ITMmE/DVV56f2wl/FlXjund+Q3WDA3odh7sv6godx+GtdYex5VgZ7ji/i9JT9JuyWht4HtDruCYXG7UMBd4SoNfrKVgiCIJoggIvaa9WM3JN8fmWAlTU2TBzbHelp9ImymuFxeJLe6dgdPckLP7tGE6U1+Od9Ufwzvoj6N8xFpMGpeOqAelIi1W/1K+1dmIcx6FTQgQOnLHghMYCb57nW6nxdgerGv18FYnuxSbxJpuk5oRshIUBU6YoPQvJ+XrHSVQ3ONAzNQpv3DgYfdNjsC2/HG+tO4ytx8rB87xmSmKZo3lSlFHzZVCNIXM1giAIQhZ4nsfJct+Md3ugtMaKvy/bi4U/5vlI6bVEhTuw6Rgfjr9ckIX1j4zFu7dm45LeKQjTcdh7qgov/HAAo15eg482HVN4ti3D87zoat5c4A0AGfGC3Fxrdd41VgdsThcATz23N1rOeNudLrF1WGqMGQnu46PAmyACg33+rxncCX3TBVn5gE6xMIXpUFpjw5GSGiWnFxDF7bS+G6DAmyAIgpCJqno7qq0O8XetZuQas+5gMZhJ7MkKbQVxjAq3NDs+Qsgw6nUcxp+Xhg+nDcOWpy7F85PPQ/+OseB54Ie9Z5ScaqvU2pxwuIQTEteM1BzwcjbX2GIJ+9xEGPVN1qYzw7U6mxN1NsdZz6uZkmoreB4w6DkkRBjFjHd7uVYQKsThAJYuFTaHtj4vLdGUD4QpTI8hneMBAJuPlisyr7bQXh3NAQq8CYIgCJkoaBTgtBfDpLUHPYaa3rXSWoIF3k1JlxOjTLhtZCZemHwegLPPo9pg9d3GMB3MhuZva8SMt8ZaipW1IDMHgEijXjxurQWsYiuxaDN0Ok6sYaeMNyEbVitwww3CZm0f30mA57Pf+DoxsmsiAGDL0bKQz6mtMKl5ezNWAyjwJgiCIGSisaS3PdR4Wx1ObPizRPz9TFWDgrNpOxW1rUuzO7szxEUWKxrszpDMqy1UerUSa6mG0ZPx1tZiSVkLrcQAoX6dSdBLNLa45V3fDXiChvJamyZ7DxOEUogZ70YGjCO6JgAAtrjrvLVASQ1bkKPAmyAIgiD8gmUWTWHCV40Wa1Abs/VYOWptniD0TKVGA+8WMt6MuAjBCRwATqo4S9yasRpDDLxVfCxN0VIrMQYLXFmmSCuIPbzdtZxsAcHmdKHG2n5kwAQhJzzPi9+vjX0gBmXEwRimQ0m1FUdLa5WYXsCIGe8YqvHGhg0bMHHiRKSnp4PjOCxbtszneY7jmtwWLlwojunSpctZz7/88ss++6olzzsAAK8USURBVNmzZw8uvPBCmM1mZGRkYMGCBWfNZenSpejduzfMZjP69++PlStX+jzP8zzmzJmDDh06IDw8HOPGjcOhQ4cCPWSCIAiiDTCJcv+OsQDaR4ugNQcEmXm4Qai11WrGmwVzrMa7KTiOE4NVNcvNPRnvltvOdHJLzasbHKiq004L0Nak5gDQwe08X1ilrWy+2ErMPf9wo178bJHcXJ38cdqCaYu34nBxtdJTIdzU2ZywOtwGjI0y3maDHoMz4gAI/by1ANV4e1FbW4uBAwfi7bffbvL5M2fO+GwffvghOI7Ddddd5zNu3rx5PuPuu+8+8TmLxYLLL78cmZmZ2LFjBxYuXIi5c+fi/fffF8f89ttvuOmmmzB9+nTs2rULkydPxuTJk7Fv3z5xzIIFC/Dmm2/i3XffxZYtWxAZGYmcnBw0NGjzRokgCEJLMBOrQe4vfa1nvHmex5qDRQCAyYPTAQBnNBboAL4u4PGt9EhlcvOCMhUH3vXuHt6tZLwjjGGiA7iWst4t9fBmdIgVFhW0thDUWGoOeBYY2sNCXXvkn2sPYX1eCZZsKVB6KoQbdo0whekQ0YQB4whW531MG3XeJe048A64j/eECRMwYcKEZp9PS0vz+f27777D2LFj0bVrV5/Ho6OjzxrLWLJkCWw2Gz788EMYjUb069cPubm5eO211zBjxgwAwKJFizB+/Hg8+uijAIDnn38eq1evxltvvYV3330XPM/jjTfewNNPP41JkyYBAD755BOkpqZi2bJlmDp1aqCHThAEQQQAc/we3DkewDFU1tlhd7pg0GuzyulQcQ1OlNfDGKbD9dmd8J+tJ1CosUAHEFzAWXuqhBYy3gDQOVEIvI9rIuPdcuANABkJ4SitseJEeR3Ocysx1E55LZOQtp7x1l7g7Ss1B4QFhlOV9ShvB54Q7Q2ni8dvR4Tg7XSl9hYdG7M+rwh7KpzYd6oKh4prcEX/NDya01vpaQUMa8mXFGVq0udiZNcEvLkG+P1omer7efM87wm8SWoeGEVFRfjhhx8wffr0s557+eWXkZiYiMGDB2PhwoVweFn6b968GRdddBGMRs+XTE5ODvLy8lBRUSGOGTdunM8+c3JysHnzZgDAsWPHUFhY6DMmNjYWI0aMEMcQBEEQ8uB08TjlDrwHdIqFzv09X6HhLBaTmZ/fLRHdkqMACFk5NRuPNQU7B6YwXZPtqbzprIEWXP7WeANARrz26rxLmqnd9CZNDLy1FQyJgbfXDba3wRqhLvadqhI/b1pb5GmKv322C6+t/hM//VGEY6W1+Pevx2BzS7a1RHOO5owhneNh1OtQZLHiuIrVS4CwkMoWhpNaUPlolYAz3oHw8ccfIzo6Gtdee63P4/fffz+GDBmChIQE/Pbbb3jyySdx5swZvPbaawCAwsJCZGVl+bwmNTVVfC4+Ph6FhYXiY95jCgsLxXHer2tqTGOsViusXq0FLBZLoIdMEARBQLihtjldCNNxSI8LR0KkCaU1VpTUWDW7ir3mgCAzv7R3CmLDDTAbdGiwu1BkaUBmYqTCs/Mff4zVGJ01UeMtHE9cK9l7QMh4A9pyNmcLWOlx4c2O0a7UnNV4ny01L63VdmlKe2Tj4VLx59MaNZaE0Yi3bnsK+WV16JASg0FZyeibHoO31h1GZZ0d+09XuVVa2qE5R3OG2aDHwIxYbMuvwJZjZeiSpN7vK7bQGBdhgCms5YVhLSJr4P3hhx/illtugdnse5M1e/Zs8ecBAwbAaDTi7rvvxvz582EyKafnnz9/Pp577jnF/j5BEER7gWVIO8aHQ6/jkBRlRGmNVXN9hhnltTbsLBAUV5f0SQXHcUiPDcfR0lqcqdJW4O2PsRrDO/BWq0SRSc1j/ZGaayzj7XLxYoDDzOGagknNiywNcLl46HTqO0+Nqbc5YWkQ1I7ei3FMUk9Sc/Wx8ZAn8C6tscLqcGovODIY8HX/ccgvq8OXNwwR659/O1KGtQeLsbOgUnOBN1ukamkxdWTXRGzLr8DvR8tx47DOoZpawDBH8/ZY3w3IKDX/9ddfkZeXh7/+9a+tjh0xYgQcDgfy8/MBCHXiRUVFPmPY76wuvLkx3s97v66pMY158sknUVVVJW4nTpxode4EQRDE2ZxwZ+lYoMNMrbRqsLY+rxguHuidFo2O7syjVuW9HmO11gPV9Lhw6Digwe5SbY/oykCk5hqQzntTWmuFzemCjvO835oiJdoEHQfYnbxmMsUs2x1u0Itt6wAgwS2pJ6m5uqi3ObHjeIXPY1r0uAA8xn2JUZ7gbkjnOADAroKKpl6iatgiVVJU88HqiCy3wZq7zlutFFezHt7aVMa1hmyB9//93/8hOzsbAwcObHVsbm4udDodUlJSAACjRo3Chg0bYLd72n2sXr0avXr1Qnx8vDhmzZo1PvtZvXo1Ro0aBQDIyspCWlqazxiLxYItW7aIYxpjMpkQExPjsxEEQRCBw6TJTNrLJHBazXivOSjUd4/r4ylfStOooVUgGW9jmE6UMas1WLXU+9dODPAsBJ2sqFf1zSeDycxTY8wtmhKG6XXijapWgiHvVmLeSopEcjVXJdvyy2FzupAea0YXt+miFuXmtgYbhu7fjLFHtiHR5PlMDXFnuXcVVCo0s7ZT7kfLwSGZcQjTcThd1SAan6qR9txKDGhD4F1TU4Pc3Fzk5uYCEEzMcnNzUVDgaStgsViwdOnSJrPdmzdvxhtvvIHdu3fj6NGjWLJkCR566CHceuutYlB98803w2g0Yvr06di/fz++/PJLLFq0yEei/sADD2DVqlV49dVXcfDgQcydOxfbt2/HrFmzAAj9Rx988EG88MILWL58Ofbu3Yvbb78d6enpmDx5cqCHTRAEQQTASTHwFm7QmDGUVrJx3tgcLmzIKwEAXNInRXw8ndXVauzmM5Aab0D9dd6iq7kfGe+0WDN0HGB1qDeD780pt3N0xxbquxlaWwgqauYGm8zV1Amr776gR5LoN6A1tQ8AVFRUY/HXz2Hx188hVucxUhuYEQcdJ3zm2KKQVihlGfwWrukRxjAMdLf2fOzrPViXVwyXS32Lj0xqnkyBt8D27dsxePBgDB48GIBQrz148GDMmTNHHPPFF1+A53ncdNNNZ73eZDLhiy++wMUXX4x+/frhxRdfxEMPPeTTozs2NhY//fQTjh07huzsbDz88MOYM2eO2EoMAM4//3x8/vnneP/99zFw4EB8/fXXWLZsGc477zxxzGOPPYb77rsPM2bMwLBhw1BTU4NVq1adVXNOEARBSAuroRWl5tFuw6Rq7d1Mb88vR7XVgcRIIwZ1ihMf11qgw6gIwIwM8O7lrc6bbLGPtx813sYwHdLc9cRqzvowWMa7Ywv13Yz0OPf7USNtnoqqznY0B4CEqPYTeL+97jAuXrhOkwFqY1h99+juSZo18wN831feXgiRpjD0ShOUrjuPa0tuLrYcbMUF/PZRmQCAzUfLcOfibRjzynq8v+EIqursLb4ulDCpeXsNvAM2VxszZkyr8qwZM2b4BMneDBkyBL///nurf2fAgAH49ddfWxwzZcoUTJkypdnnOY7DvHnzMG/evFb/HkEQBCEdBY0y3knujHeZBjPe2/KFm7CLeib73KixQKfQoq2b6opa4SYrwY8MMeDp5a3GjHeD3YkGu5C18ifjDQCd4iNEueUQlZsoBZTxjnEHQxrJ1nlaifneYHuk5tq7VnjD8zwWbzqG0hobthwtx+TBHZWeUpsprbHijzNCp5/R3ZNwuLgGgOf9qSVaamk5pHMcDpyxYGdBBSb07xDCWQUHK+FqqeUgAEwa1BHndYzFkt8LsHTHCRSU1+GllQfxxbYTWPvwmBDMtHXacw9vQOY+3gRBEMS5R4PdiSK3XIxlS1nGW4s13ixD3KGRuZUY6GhMai7WePspNVezIRnrKazXcYgy+ZdLYO7gJzXgbB5Ixpu9P7XyfmRS88YZb2Z41WB3oc7mCPm8pOJISS1K3dc7lsXTKr8dKQMA9OkQg6Qok0dqrsHAu7yupcBbWIjbqaE6b57nRT8Ef8qHuiVHYc7Evtjy1KV4YbKgEj5aUot6m1PWefpLCdV4EwRBEIT/sCxIpFGPeHcWUqzx1kBdbWOqmnHNZoFOWa0NDXZ13LT4A1tI8MdcDfAsnhwvr5VtTm1FrO8ON/jd6swTeKs/aAgk490hTpvmao0D70ijHsYw4fZUiwt1jK3HysWfWTChVTa5ZeYXdBecsTtotMwGaLlN3ZBMIfDee6oKNoer2XFqosbqEOfamtTcmwhjGG4Z0RlGt2ljSwsSoYTM1QiCIAgiALxl5iwY8nY114KbtDcs8G5cQxwXYYDZIHyNasmMp63makUWq+oWGCrdxxLrp8wcADoleJzN1Q7LeLfUw5shBkMaKX1oLvDmOM7Ty1vDdd5bjpWJP2s58OZ53stYLRkAxIz3aQ1mvCtaCDC7JEYgIdIIm8OF/aerQjirtsM+I+EGPSKMgVUQcxznMTNUwSJXnc2BGqugciGpOUEQBEH4AXM07+Q2VgM8/UVtThcsDdqSj4rBXaN2VRzHac5kiOd5VATgAg4A8REGUcatNnm22MPbD2M1hlak5lX1dlS7b0LT/XI1F8YUVjWo0q3YG57nm63xBrTvbM7zPLYc9WS8izUceOeX1eFUZT2Meh2GdREywmyRx9LgCZS0Qktt6jiOw2C387dW5OasnCGQbLc3CSryVGCO5uEGPSKNeoVnIw8UeBMEQaiEwqoGvPZTnqayp01xwp2lY5lSADAb9GLwVqYxuXllMxlvwFtyqY3MT53NKcoS/c14cxyn2pZiVeIigv83ncxp/5TKe3mzbHdCpNGvTFZKtAk6DrA7edX3wLY0OERTvMYZb8A7GFD3cTTHifJ6FHpdx7Wc8d54SGilOCQzTnwfRpsNiDYLP2utzrvEyuOZy+7BloefA4xnXzeY3HxngTaczcv9aCXWEmpa5BJl5jEmv0uHtAYF3gRBECph8aZjeHPtYfzfxmNKTyUoCsqY1Nw3SyfKzVXwBR8IlmZqvAHttRRjN1emMB3CDf5nFDwtxdQVeLNWYoFkvH16eas4IAqkvhsADHqd2IJH7XXexe6gNDbcAHMT70PR2Vxji3QMJjNnHhda6BnfHExmfqFbZs5IdyssTqv8vdaYkgYXPh1yFUpvvwswnH3dGNw5DgCwSyMtxdhnhJkSBoqaAu/2bqwGUOBNEAShGvLLBPOqI+5WLVqlcQ9vBpObl6o42GkMz/MeA68mAm+W8VZ7oMNgxxIfYQwoo+BpKaau7BY7nkBqvA16nVgicELFdd6n3J8jfwNvAOJxnVa5AqOwBZk5ACS4zRjVEAy0hS1uY7Xx5wktqSrr7LA61OWP4A9OFy86mo/unuTzXAeN9Y1niBniZqTZAzvFQccJCwpauK4H4mjeFGoKvJn7f0p0+6zvBijwJgiCUA3M7IkF4FqFtZ1iwRqDZbFKVfAF7y91Nicc7nrZpqXmzGRI/TdogMe51t9WYowMlUrNWyoDaImOGqjzFjPefhirMbSyEMTaDTYlMwe0q45hsIz35f1SYdALC1ylKjCvCpSSaiuqGxzQ6zj07xjr81wHjWa8K6rrMbJgDzrlbgGcZy+GRJrC0DstBoA25OZlEtV4qyPwFq4LyZTxJgiCIOSGBd4nyuvhVLk5UnNU1dlF87TGTsxJ7i9TLclHWWBn1DctzRYDHY04SVeI2ZHAAtXOKu3lXVUXuLkaoI2WYoFKzQFP6YPaM97Mx6K5zJaagoFAOV1ZjxPl9dBxwLAuCUh2K33UXNbQHJYG4fMVYw6DXuerkEln7zUNZbztThcaquvwxX+eQqfrrgQaml40GJIZBwDYqQG5ebnbFK1d1HhbKPAmCIIgQoClwS62rbI5XZox62oMk5knRZ1tCJXEMt4aCrxZYBfTTJ9o0dVcIxlv1konEDMyAD7mamoyJBNrvAM8Hua4r+rAuyLwjHe6l7O5mjlaIqh6MhupYhhaNldj/bvP6xiLKFOYGEQUa9A0s9odeEebz17YYk77WvquaqmVmDdDOmvHYM0jNW9bsKqm1n0eqTkF3gRBEISMnGoUABxXmYmVv5zw6uHdGGb+UqYhyaUnsGs6o8oy3mW1NtX1uG4KMeMdYKDaMS4cHAfU252qksy2pcYb0EZLsWAy3mo3+ztcIvhYdE+JavJ5TzCgnUU6BqvvHpGVAABIdmf1tWiwZqkX1Esx4We76ntqvNX9XvPG3+8eFnjvO2VRfW1+e5Kai0qYdtrDG6DAmyAIQhU0zrxptc6b1QA3NlYDPOZqWgq8La3UEMdFGGA2CF+lTCanZipEc7XAAlVjmE7MphaUq+e9WRmk1LzxgpdaaPBa4GhcstESWmhvx/O8aCDZo5nAWwwGNHStYLD67uFZiQA8slktS82jTU1kvL2M/NSkgmkJf4PLzMQIJEYaYXO6sPN4pbyTCpIyiaTmSqtLHE4X8kuF+4euSZGKzkVOKPAmCIJQAY0zb5rNeDNH84SzgwW2Iq8lqXlrgR3HcZpxkgbabq4GeM6pmgzWquoD7+MNeBaGTlbWw6VCPwWW7Y406gMyjuvgzo4XVVlVeVyA4GheYxUMuzITm77BTnTLZmttTk0oSRgl1VYcLakFxwHDu7CMt1tqrsnAu/mMN1NXNNhd4oKe2vE3uOQ4Dpf2SQEAfLmtQM4pBQXP814u7cG1E6uqt8PhdEk2t0A5Xl4Hm9OFcIM+IJWP1qDAmyAIQgWwjHekUTDwyi9VT1YxENhxNJ3x1l7gXeWHa3ZajDacpAFvc7XAA29PL291LDDYnS7UWIXAINCMd4dYM/Q6DjaHS5XvR+/67kDavqVEm8Bxgk+E0hms5jjsznZnJkbAGNb0bWhMeBjC3GZeapDA+gur7+6dFiOWP6RoOOPdUo232aAXr+laMVgrD+CzfuvITADAyr2FqjUEtTQ4YHcKC2xtzXjHRRjBLjFKLqAcKnKrYFKjoNP5f83TGhR4EwRBqACW8R7ZVZAnajXjzYJPlg3xhknNLQ0O1dfNMcR2VS1Is1mtoxYy3hV1bcsQA74Ga2qALYoAgvldIITpdeKCyQkV1nm3pb4bEHqUMxdttS4EiTfYzcjMASHjqKbaU39hMnNW3w1oXGrOarybCLwBL3NJlb7XGhPIe2lApzgM7BQLm9OFr7aflHFWbYcdT6RRD3MTXTf8Qa/jxIVLJT9rh4qqATTv+9BeoMCbIAhCBbBM8ejuSQCA4+W1qpWKtkShpfnAO8Zs0FwWy5+Mt1Z6JwNtN1cDPIZ5amkpxsoAmmp15A9qbinWFkdzRgeVu023ZqzGUEvtaSBsbWSsBmg88GbtxJqQmgPa8BTwpqzWBodejw1/fRRYsAAwtLxgd4s7671ky3FVtvhk5oMJbTRWY6hhkeuQ6PsQrdgcQgEF3gRBECqA3fyP6JoAvY5Dg92luZrABrtTDIbSmnAl1ek8WSytGKz50ydarPFWubsvz/NeNd6BZYgBiPW46sl4t62VGEPNLcU8Ge+m2221RIcYdTubM6l5a4E384RQq8y3MRW1NhwsFLJ2w7wCb2+puVZMyBjV7hrvpqTmgKelmNqvfYyyGhvsegPy/3Iv8OijgLHla8fEAemIDTfgZEU9NvxZEqJZ+g8zYExsYysxBnu9OgJvyngTBEEQMlLt1cM7MzESGe4sl9aczVkrEFOYrtkMMZOba6W1TpU/UnOW8baoL4Dzpt7uhM0hmOfEByE1L7Q0qMLwSjS+C9ChnaHmlmLBZby1EXi3ltlifYk3Hi5VZbaxMXtOVQEAuiZHitc5wHPNszldonRbK7CuDjHmljPemqnxDtDjItyox/XZnQAAn/5+XLZ5tRXRWK2N9d0MthCrVPs+p4vHEbcSpmcqZbwJgiAIGWHZrfgIA6JMYWJm8bjGAm/v+u7mDKE8WSxtZLzFPt7hzd/YpGlEas5u0oxhOkQYA68HZO9PQB3BqtjDO8D6boaqpeZtrPEGvEsf1HdcZTVW8X3YNbnllkGX9U0FAHyz8xTu+mS7KHtWK6VuhVLjc2Y2eJzpi6vVfY1oTEvmaoAn460dqbkVOpcTnY/sB7ZtA5ytLyDeMqIzAGBdXrFqymwYTA3S1h7eDLbIpVRZR0F5HWwOF8wGXZsWG7VEwIH3hg0bMHHiRKSnp4PjOCxbtszn+WnTpoHjOJ9t/PjxPmPKy8txyy23ICYmBnFxcZg+fTpqamp8xuzZswcXXnghzGYzMjIysGDBgrPmsnTpUvTu3Rtmsxn9+/fHypUrfZ7neR5z5sxBhw4dEB4ejnHjxuHQoUOBHjJBEISsnCwXblqY9LVLovBvvsYM1lh9d2oTMnNGstjLW1sZ75bMu1g/29Iam6pN4yq9engH4pTN4DhOXGRQQ8/yyja2EmOoVWrucLrEz1IgPbwZaWJ7O/UFeSzb3TEuHBHGprOojKsHpmPR1EEwhemw9mAxrnl7E46puNtDBSvjaOL9qNU675baiQFAOjOW1IjUvLzWBpPDjgHXXg4MHw40tD7vrslRuKB7Enge+HyrulqLlYkZ/GCl5sJ7tkKhwJsZq3VLjmqTX4eWCDjwrq2txcCBA/H22283O2b8+PE4c+aMuP3nP//xef6WW27B/v37sXr1aqxYsQIbNmzAjBkzxOctFgsuv/xyZGZmYseOHVi4cCHmzp2L999/Xxzz22+/4aabbsL06dOxa9cuTJ48GZMnT8a+ffvEMQsWLMCbb76Jd999F1u2bEFkZCRycnLQ4McHjSAIIlSw7CG7ydZqxptJzZuq72ZorZe3P3LmuAgDTO62SEVV6j0ulmlsi8ycwUzZ1NC3t6qOqRGCy3ifqlBXL+9CSwOcLh5GL4fyQEhXsQKDGav1SPWvjnPSoI5Yes8opMWYcaSkFpPe2oiNh0rlnGKb8QTeZ78fkzVWYsNgGe/WXM2L3O9ZNeNwusTFukBhrcW+2nZCVYurTDmWJJG5mlIZ73OlvhtoQ+A9YcIEvPDCC7jmmmuaHWMymZCWliZu8fHx4nMHDhzAqlWr8MEHH2DEiBG44IIL8M9//hNffPEFTp8+DQBYsmQJbDYbPvzwQ/Tr1w9Tp07F/fffj9dee03cz6JFizB+/Hg8+uij6NOnD55//nkMGTIEb731FgAh2/3GG2/g6aefxqRJkzBgwAB88sknOH369FlZeoIgCCVhGTcWCHRJcme8SzWW8XYHnU05mjMSxYy3+qXmThcvmgu1JGfmOM5jMqRiySULDNrSw5sh1gLWKX/+2BzaKjUXe3k7XaoKiFh9d4c4c5v62XqXPqhpQQHwMlZL9v8Ge0CnOCyfNRpDOsfB0uDAg1/uUqVJGVuMim/i85USI1z31KAUCYTW2omlRJug4wCHi1d9Nr+izo62vm3G9UlBWowZZbU2rNpXKO3EgiDQmvXmUNrVXPR9aOf13YBMNd7r169HSkoKevXqhb/97W8oKysTn9u8eTPi4uIwdOhQ8bFx48ZBp9Nhy5Yt4piLLroIRi+3wZycHOTl5aGiokIcM27cOJ+/m5OTg82bNwMAjh07hsLCQp8xsbGxGDFihDiGIAhCDXgCbyHg9s54q/EGszmK/JCaM6OhUg20CLJ4ZUdaC+5Yll+NWUZGhRQZb4Ulid6wm7XMxMCdvwGhlzerh1ZDzTojmPpuQPj8cZxg5qWGBRJvPDfYgWW2UmLMWDxtOABW0uGSfG7B0tLnS4sZb7vThXq3iWJ0M+ZqYXqdeO1T86Ij4Akq22LGGKbX4abhQq33f3eeknRewVAq1ngHJzVXOvD+0y01p4x3Gxg/fjw++eQTrFmzBv/4xz/wyy+/YMKECXC6DQwKCwuRkpLi85qwsDAkJCSgsLBQHJOamuozhv3e2hjv571f19SYxlitVlgsFp+NIAhCbk5W+krNO8WHQ8cBtTan2C5ECxQGIjVXeXYE8NR3Rxr1MOhb/rpkTtJb88tln1dbKRczcm3LEAOeemql+7DzPC+2burTIabN+2GfuRPl6gkaREfzNgbeBi+JutoWgvxtJdYUUV7BX61Vfe7gotS8ieyjFmu8mdoHaD7wBrz6xqu8zruM9bxuYxeEkV2FFnEnVWSwJpWruZKBt9PFU8Y7GKZOnYqrr74a/fv3x+TJk7FixQps27YN69evl/pPSc78+fMRGxsrbhkZGUpPiSCIc4CTjVoHmcL0onRZS3XeYo13bPOr70mie6r6b0ADMe+6ZnBHAMB/thZgm0qD70omNZekxlvZwLvIYkVlnR06rm1BHMNjsKaem2kx4x2Eu68a2zxVN9jFFmfdkwO/wdbrOIQbBDf+Opt66mwZFbUe88LGiFJzDbmas/ruCKMeYS0sPLL3mtqdzcuDNCJLUtniCc/znsBbohrvijpbyFV2pyrqYXW4YAzTiS0r2zOytxPr2rUrkpKScPjwYQBAWloaiouLfcY4HA6Ul5cjLS1NHFNUVOQzhv3e2hjv571f19SYxjz55JOoqqoStxMnTgR8vARBEIFQ3WAXDby8M1xd3HJzrTib8zwv1i+2KDWP9rQTU1v9aWP8cTRnXNgjGVOyO4Hngce+3oN6FQYGHqllMDXe6sh4HygUFGldk6NgNgTeGo2hxpZiwUrNAY/pFVOhqIEjJcIiYnK0CbFtzDpGmoRzXaPmjHeTUnPhmqiWoM0fWqvvZoj+FirPeIvmkm3MDjPVQrXVgQa78td3S70DDvd3qFQ13nYnLzrZh4pDxeeOozkQgsD75MmTKCsrQ4cOHQAAo0aNQmVlJXbs2CGOWbt2LVwuF0aMGCGO2bBhA+x2T33d6tWr0atXL9GobdSoUVizZo3P31q9ejVGjRoFAMjKykJaWprPGIvFgi1btohjGmMymRATE+OzEQRByAm7yY6LMPj0SmV1q1rJeJfX2mBzCnWXKdHNB97sC97h4lXfl7cyQNfsp6/qi9QYE46V1uK11XlyTq1NSGGuluCWqVcq7Gp+8Ixws9Y7LThpohpbip2qCD7jnSZmIdUTDLXFWK0xke4+8nU2dQXePM972vW1G6k56+Hdctu3dBWqK5qClW3FxkQAzz4rbAb/F4CiTWEwurtXqOE8lrpVY9GmMJjC2r74CAi95iONwj5C7d/xZ9G542gOtCHwrqmpQW5uLnJzcwEIJma5ubkoKChATU0NHn30Ufz+++/Iz8/HmjVrMGnSJHTv3h05OTkAgD59+mD8+PG46667sHXrVmzatAmzZs3C1KlTkZ6eDgC4+eabYTQaMX36dOzfvx9ffvklFi1ahNmzZ4vzeOCBB7Bq1Sq8+uqrOHjwIObOnYvt27dj1qxZAASX2QcffBAvvPACli9fjr179+L2229Heno6Jk+eHOR/G0EQSrNq3xnc/el2VKmgrVEweHp4+95ks4y3mvvWesMya0lRRvHmpClMYXrEuG/k1F6/zszV/HXNjg03YP61/QEAH2w8hh3H1SU5F6Wwwbiaq6TGO8+d8Q6mvhvwznirQ1nC87y4GNcpru2yS1H+q6JgKJj6bgbr/V1rVT7j6E2tzSkuPDZVypHiDrwr6uywqdAYrinYwmhrih9W431KRe+1pih3B6rxcZHA3LnCZvT/WshxnKpM8kTpfJAyc0a8Qi3FWMabAu9m2L59OwYPHozBgwcDAGbPno3Bgwdjzpw50Ov12LNnD66++mr07NkT06dPR3Z2Nn799VeYTJ6aiiVLlqB379649NJLccUVV+CCCy7w6dEdGxuLn376CceOHUN2djYefvhhzJkzx6fX9/nnn4/PP/8c77//PgYOHIivv/4ay5Ytw3nnnSeOeeyxx3DfffdhxowZGDZsGGpqarBq1SqYzc1nYwiC0AZv/HwIP+4vwk9/qKe1R1sQe3g3usn2ZLzVERC0hj+O5gzmbL7lWFkrI5XFnx7ejbmkdyquHdIRPA88+vUeVUgSGS31GfaXeJXUeDNjteAz3p6gQQ2lD8yxm+NabsvXGh3E9nZqyni7b7ADdDT3hmXl1GauxrKEpjAdwo1nZx9jww0w6AUZbakKgjZ/YJLj1jLeWUnCIvHeU1X422c7UKyi8gZvpGi9xZQLajAHLWOO5kHKzBmJCpURtbXTgVZp+dPUBGPGjGmx8P7HH39sdR8JCQn4/PPPWxwzYMAA/Prrry2OmTJlCqZMmdLs8xzHYd68eZg3b16rcyIIQjs02J045L5YayUj3BxidqtxxjuJ1XgLLcU4Tt21T2IPbz8C7wn90/D2uiOY891+JEQYMaF/B7mn1yaqAsx4M569qh82HirF0ZJavL76Tzx5RR85phcw5RK0E2NZkTqbEw12Z1D11W3F5nCJN2u9g8x4p8UIvbztTh7F1daggl0pYAtxqdHmFpUjrZGqQmmzlFLzWpV5KLRU3w0AOh2HpCgTzlQ1oKTaKtZFqxmm+GmtxrtnajRmX9YTi9Ycwv/2FWLj4VI8MaE3bhrWuU196OWirIaZSxqA/fuFB/v0AXT+f86SVJTxLgvSLK4xSrSKdJ1jjuZACGq8CYIgpOZgYTWc7uyU1gNvTw9v3xsx5u5Z3eBAhQbk9ExqnupH4PLwZb1w7ZCOcLp43PefXfhpvzpVC8zVPFAjqNgIA16YLKivFv+WL75XlaTe5hR7HwcjNY8xh4kGOEplvY+U1MDh4hFtDhPrS9uK2np5H3LXO3ZLiQxqPynuBbAilWQfG+xOFLjbMAUjNWfmamqr8a5oob6bweTmxSpaDGkJ1k4sJrz1HN39l/bA97MuwMBOsahucODv3+7Dje9vVpUygS08JuudwHnnCVt9YPJ4NdXqs4WEJImk5glix5HQXddPVdajzuaEQc8h8xxwNAco8CYIQoPsO1Ul/tx+Am/fLx2zQS8GBPkaMFgrqmq9hzdDp+Ow8PqBmDQoHQ4Xj5mf78Tag0Wtvi7UtDXjDQBjeqUAELKzNSF2iW2KcneQbNTrRLluW+A4ziM3r1VmQeggq+9Oi5FECSL28lZB4P3HGc+xBQML8upsTlU4gB8rrYWLFxZuWPDSFtRa411R23oZh5qCNn+wiOZq/l3/+qbH4Jt7R+PZiX0RYdRjW34Fvt11Ss4pBkSwruaAl9RcBRlvKaTz3jDjzPIQtvpk2e6uSVEttqxrT5wbR0kQRLti/2mL+HN+Wa0qajPbCsuyNeVgrCVnc5bx9ifwBoSevK9OGYgrB3SA3cnjnk93YuOhUjmnGDDMuC8uPPAbG2OYTuw5zAJ4JREDg0hD0MEqu0FTKuMtOpp3kEaamM5ab1UpfzPNFhWCldBHmsIQ5ZZlq6Hm1ttYLZj3n2prvOtaD+q0FniLGW8/A29AuK7fOToL1wzuCEA92X2nixcXH5syv/OXZHd2WQ3nkAX/0gXeoc94H5LA90FrUOBNEITm2H/ak/FusLtU1as2EGqsHhl5U4G32Mu7VPlMXGsUBSA1Z4TpdXjjxkEY3y8NNqdLdS24gsl4e79ODW3TWqtBDQSlnc0PiMZq0rT8TIxix6PszTTP85KZxgGerHeRRfkggXly9EgJ7rg8Nd4qC7z9yngL18biam18X7Ea79bM1ZqCXSMqFTZhZFTW2cDsqaTIeKsh8GbXX1Z3HiyJCtR4e1qJnRv13QAF3gRBaAy70yVmvFj2I1+jcnPWrzc23NBkViHTHXi3x4w3w6DXYebY7gDU146mst7dx7uNLuAs8FZDxlsKYzWG0s7mB8+wrLA0N2uJ7hvXMoXb2xVaGlBZZ4dex0mSAUqJYTXFygd6RyRoJQZ49fFWm9TcvYDaUjZVTUGbP/jbTqwp2DVTLf4k7PonuMu3PfTxSM2VX1AQzeIkynjHK+BqfugcczQHKPAmCEJjHC6ugc3pQrQpDMOzEgAARzUaeIutxJrIdgNAF7fUPF/lLcUa7E6x9VaggTfgezOjprIBdkxtzXgzUyI1BN7sWKS4SVPiBo1RVmMV5au9JHLBZZmeUoV7k7MFxW7JkTCFBe8Wn+LOsKoh0JOihzcARLgXW2tUlvFmMua4lgJvFTli+0O1n+3EmkJtGW8mnw629Zboal5tbbHDUygQj0kyc7XQ9vHmeR6Hi86tHt4ABd4EQWgMZqzWNz0GXd1tabRqsNacozlDKxlvJjM3G3R+OeA2JjHKCI7zrcNTmga7xwU8UFdzhig1V0HgzYLktmbvvWE13pUKZLPy3FLszMQIMfsZLElixlvZgEg0VguyvpuhFhftOptDvEZLl/FWV+DNAsyWFrZEBYIKpP/+IGa8A6jxZsQreI1oCqmMyNi1ot7uVLSlncvFi4qjRInaiYVaan6mqgG1NifCdJzYPvVcQJpvLYIgiBDBjNXO6xiLLNbrWrOBN8t4N91Gg5mrVdTZUVVnb3MAKDeFXo7mbTFOMuh1SIgwoqzWhpJqq2Q1a8HAstQ6Dogytu2rkt2wqiHjXeFHYOAvStZ4H5CwBpqRoGAG35uDEteus0BP6ZZiK/acgc3pQmZiRLOLjP4SaVRnH+9yt8N/Swtb3hlvnuclceSXE4+5WuDXvziFy1EaU+ZtRGYwAI88IjxhCOw7NdIUhkijHrU2J0qrraKBYag5XVUPp4uHQc9Jl/F276fW5kSD3QmzIXjVTUv86c52ZyVFBiX/1xrnzpESBNEuYMZq/dJj0NUdeLfXjHekydN653i5eo9R7OHdBpk5I1kl2TmGt7GaTte2G+QYVZmrufsMS1DjzQJVJW6qxfpuiYJTwCPVLKuxKSoflbp2nX0elc6wfr6lAAAwdVjnoIPNCJX28a70w7yQXeNsDhcsKmgx2BI8z3v18W5DxluUmit/7QO8ZdkmwGgEFi4UNmPg18OkaOVLBg65TcmkDFqjTWEw6IXPZygWIQ+fg/XdAAXeBEFoCJeLxx9eGW8mTyoor4PD6VJyam2iuR7e3mihzptl1NICcDRvjNqMh4Kt7wY8N6yqyHh7tRMLFiUz3lK6fjOYVNPmdKFaIQlzg90pelX0lUhq7lnMUi7j/cdpC3JPVCJMx+H67E5B7y9SpX28/ZEymw16MXtcogLDu5aosznhdPtttK3GW7jO1FgdsDmU/24ul6jGG/BSLij4XZXnzhb3lMjnAgA4jgvptZ0tHnQ/hxzNAQq8CYLQEPlltai1OWE26NA1KRJpMWaYDTo4XLwYxGoJsYd3XPPyS7HOW8VZfdb/uC3GaowUlbXaETPeQWSIPTXeyme3WM9XSVzNFWg7AwgeAEyeGGyfa2/CjXqxQ4JSzuaHi2vgdPGIjzCItdnBIn6mFMx4f7FNyHZf3i9VXAgIhkiT+vp419s8fhCteSioTdnTHEylE6bjEN4GyXGM2QAmFGLdIZSkzHthxOUC8vOFzRX4ooDHDFS5c/inDIE3ENqyG9bDuydlvAmCINTJvtMemWmYXgedjhN7XWtNbl7bSg9vhpYy3lJIzdWT8fa0n2kramknxvM8TpQL75+MhObVFf7CWiaF2ggvv6wWVocL4QY9OktwHN4kKNzL+w8vCb1Utb+sxrva6kC9AjXR9TYnvt15CgBw8/BMSfbJMt51KqrxZiUXBj3Xas2vmpzmW8Lb0bwt70edjhOvf2qQm5fXeDmA19cDWVnCVh/4gn2SCjLeLFssddAaqsCb53nxGM6lHt4ABd4EQWiI/W5H8/M6erJdWRqt82bzTYg0thjcacHZvFBCqblaMkEsWI4LRmpuVkc7sbJaG2ptTnBc834CgcDk6g12V0gDOtZuq2daNPRtrLtvDiY3V6o/Lzs2qRzNAaFmk2UrlVCSrNhzGtVWBzonROD8bomS7JPVeNfaHIq3c2J4OgYYWw1S1bbA2BysE0Nb6rsZTF0TamVMU5TVepmrBYnS59Dl4r3qo+XJeMvdUqzIYkW11QG9jkOXJGkXUdUOBd4EcQ7w6NLduO3/tqii1ioYREfz9FjxMa0H3lmttNFgGX01Z7yZq3kwGe8Uld2QioF3EE7ysSoxVzvufu90iDFL0h86ysuEJ5QGawcL3e22JKzvZiR5GawpATs2qYzVAKFmU2xhpcDn6j9b3aZqwzPabFDYGJZR5nmhpZMaYBndBD/KOJQO2vwlmB7eDNaFo0INGW+xxjv4cgeW8VZKan6yoh71dieMeh0yJVb+hKqlGJOZZyZGSPKdpCWonRhBtHNOV9Zj6Y6TAAQ546CMOGUn1EZ4nsc+0dHcE3h30Wjgne9n4N3ZLTUvrbGixupQrH1Jc7hcvJhNa0/mat6u5m0lRiV9vJnMnL2XgoXjOMRFGFFSbUV5rQ3pLXgUSMmBM9IbqzHYDbkSvbx5nscB1sNbQrd2QFjQOl5WF/KWYgcLLdhZIJ2pGsMcpgfHCYF3rdWJiDa2+pMSVnLhzyIdW2D8ZPNx/Li/ENFmA6JMYejdIRpPX9lXciVHWwmmhzfD42yubMZb6HktHI/QwSC4BRulv6tYfXfX5EiESdyGKz5EGW9RKn+OycwByngTRLtn85Ey8ec8d1ZFi5yqrEdlnR1hOg490zx1TVptKeZvxjs23CDKv9QoNy+vs8Hu5MFxCMoUSm0Zbylczb3N1ZSUxbKMt5R10QkK9On1ZIWlDU4BT4233DecTVFcbUVFnR06TvrWOkoZrP3H3ULssr6p4hykQKfjEGFQV0sxFlj6I2POzoyHXseh3u5Eflkd9p6qwuajZVi8KR+5JyrknqrfWMQe3m2//sWpJONdVW8XHdqlMJdUPPAulsdYDfBkvOX2umAZ73OtlRhAGW+CaPdsOlIq/sxa8WgRJjPvmRrtI01igevpqno02J0wt8GBVQmO+hl4A4Icq7zWhuNldT7ZfjXAZOaJkaag+omym5kaqwN1NofimSwpM942pwsNdhfCjcq8NwvcGW/mFyAFrM47VC3FGuxOsXNBjxTpb9YSQ5TpaQpmrNY1OUry65cSUvN6mxPf7HKbqo3oLPn+I0xhqLU5UaMSZ3PvGu/WGNolAdv+Pg5FlgbUWB2oaXDgH6sO4mBhNU5W1CNbGg+6oGEqnWCk5mrJeLPPdLQ5DMYwHRDkR4GVpZTW2MDzvGRmiP4il7EaACS4lT9yX9c9rcTOvcCbMt4E0Y7heb5RxlvDgfcpJjP3zXYlRBoRbQ4Dz3sCDC3gb8Yb8K7zVl/G29PDO7jauSgvIyg1ZL0rxRrvtmdIIo16UTqqpMFaQbnwvpE04x3JbqpDc1xMLh9tCpPEIKkxrG5TCam5HMZqDE/GO3RS8zUHi1Dd4EBGQjhGd0uSfP+s3EYtzubsMxDvpx9EQqQRfTrEYFiXBIztnYK+7u80NbXEZDXewZmrsYy3soE3Wxxmn/FgYfuxOV2KtIpkUnOpjdWA0Lia8zyPQ8XnpqM5QIE3QbRr8svqcKbKc8Ol5cCbtRI7r6NvxpfjOFFufrREfYFpU1TU2sRArIsfWchMd23u8VL1LSyIjuZBGKsBwnlUk7O5RYKMN8dxqjBYk0NqzrJZocp4i8eQGCFLhilRQXO1A2IrMelvQlMU+EyxhYQLeyRLZqrmTYRRXb28y2v9l5o3RSe3R8KpSvUE3ux6FUzGO04sR1FWar7juCDh78/uHcLCgHvvFbawwI/PbNCLHStKakLrneD0cjSXQ2oeisC7pNqKqnqhtKZrsnQqLK1AgTdBtGM2HRZk5gMz4sBxguRKDdnEtrD/9NmtxBhaM1hjMvMOsWa/5MeqznhL4GjOUFOdd2UAhkktoXRLsXqbUwy6MiUyVwM8N2ihymYdF+Xy8rSeEc3VFOjjLbq1S+hozmCfy1C2E2PX4a5+qHnaAuvlXWtVR8a7os5/qXlTMHPC0yoKvKslqPFWi9R8a76g+huWlSA8YDIBb78tbKa2ZcGTxO+q0B5bQXkdrA4XTGE6SRdSGaKSyasuXmpYtjszMVIzpYFSEnDgvWHDBkycOBHp6engOA7Lli0Tn7Pb7Xj88cfRv39/REZGIj09HbfffjtOnz7ts48uXbqA4zif7eWXX/YZs2fPHlx44YUwm83IyMjAggULzprL0qVL0bt3b5jNZvTv3x8rV670eZ7necyZMwcdOnRAeHg4xo0bh0OHDgV6yAShWZjM/NLeKWLbCS1mvYurG1BksYLjgN5NuP4yuXa+RgLvQGTmgFfGW4UtxaTKeAPKm9YwXC5ekhpv79cr5Wx+osIt0TaHBX0s3sSFOONdUMbk8vIEcyzjXV5rg0umG86msDqcOOJW6sgiNVegxjsQ/4q2EOnVy1sNVIjmam37fHWMd2e8VSQ1l6bGW3lzNZvDJWa8R7DAWwKS3XLzkhCXpjCZefeUKFkc8Nk543n5FkwOeR3DuUjAgXdtbS0GDhyIt99++6zn6urqsHPnTjzzzDPYuXMnvvnmG+Tl5eHqq68+a+y8efNw5swZcbvvvvvE5ywWCy6//HJkZmZix44dWLhwIebOnYv3339fHPPbb7/hpptuwvTp07Fr1y5MnjwZkydPxr59+8QxCxYswJtvvol3330XW7ZsQWRkJHJyctDQEFppCEEogcvFY/NRIfA+v1sierlljAc16GzOpItZSZGIbKKdltZ6eR8rFVZ8/b0xZRnvQksD6lVS18godLslpwbRSozhkcUqe42usTnAYq9gg1VWI6lUxpst1mRKLNFmQUZ7yXiz7JyL99T3h4JDRTVwunjEhhskWbxqDPtMVdbZ0RCCvtc8z/vdKrGtRLAab5VIzStqg/OD6OglNVey+4E31aydWBDXvzgVZLz3na5Cg92F+AgDuie7Az2eB0pKhK2N/99KLRKzoFUOmTkAhOl14neeXIuqh4rlM4fTAgEvZU2YMAETJkxo8rnY2FisXr3a57G33noLw4cPR0FBATp39rhbRkdHIy0trcn9LFmyBDabDR9++CGMRiP69euH3NxcvPbaa5gxYwYAYNGiRRg/fjweffRRAMDzzz+P1atX46233sK7774Lnufxxhtv4Omnn8akSZMAAJ988glSU1OxbNkyTJ06NdBDJwhNkVdUjfJaGyKMegzoFIdeaTH4cX+RJjPezDQtq5l6aHaDd1QjgXe+u1bb3xvTuAgDYsxhsDQ4UFBeJy6iqAEmNW9PGe8qd4bGFKYLWgqndC9v0dFc4kyxp8Y7NMdVIEOdujfGMOGGs6rejrIaqywGbk3BOk30TouWpXY9NtwAY5gONocLJdVWZMj0/8coslhRb3dCr+Nk+1uRrMZbJYuQYsY7SKl5nc2Jqnp7UIaOUsHaiQWV8XYvzlXW2RVx/waArcfKAQDDuiR4/Abq6oCUFOHnmhogMvBrIzNYKw15xtttSiZj0JoYaRSug7U29JBh/8zR/Fw0VgNCUONdVVUFjuMQFxfn8/jLL7+MxMREDB48GAsXLoTD4Vm53Lx5My666CIYjZ6LT05ODvLy8lBRUSGOGTdunM8+c3JysHnzZgDAsWPHUFhY6DMmNjYWI0aMEMc0xmq1wmKx+GwEoVVYffewLgkwhulE4568Iu0F3kwu29yNHKvxLq2xiiv1aiZQKSbHcR45vcrqvEWpuSQZb1aPqnDgLTqaBy/NjhUz3spk55hEW+ogyONqLn82y+nixWuAXIE34JGbl4bQYG3PyUoA8sjMAeHaEUqDtaNuNU/nhIig2gu2RIRY4618xrvB7hTd1dvaI9ps0IstqtTibC5mvCWo8Xa4eFQrdK5Y4D1cQpk5oNwiMZOa95QxaJXTYI3nebEPOUnNZaChoQGPP/44brrpJsTEeL5U7r//fnzxxRdYt24d7r77brz00kt47LHHxOcLCwuRmprqsy/2e2FhYYtjvJ/3fl1TYxozf/58xMbGiltGRkZbDpsgVAGr7x7dPREAxCzpn0XVsplmyMXJcuFmpJO7Fq4xMWaDeOOSr0Lnb29crrZJMVkP5uMqCrwb7E4xSJXCXE01GW+J6rsBz42rYlJzmSTa3q7mcstjz1TVw+7kYdBzYnZQDhJD4OjrTXWDHd+6+11f0F36tlsMMfAOQUsxVu7TRaaSAEBd7cRYKzG9jgsqO9xRZc7mrE1WMIG32aCH2SCEGZUhUsZ443Tx2JYvBN4jshIl3Tf7rgplxtvhdImdW+SSmgOeY5PjelFWa0NlnR0cB3RLpsBbUux2O2644QbwPI933nnH57nZs2djzJgxGDBgAO655x68+uqr+Oc//wmrVdmbrSeffBJVVVXiduLECUXnQxBtxeF0YYt7pfd8dx/VLomRMIXp0GB3iT1xtUJrGW/Aq85bRYFpUxRVN7RJisluZPNVZLDG+qOGe7VXCQa1tBNjN9Nx4cFLPpVuJ8ak5lJniuPdQarV4UK9zLXD7Bg6xUfIYijECLWz+RdbT6C6wYGuyZG4pHeKbH8nlEoSz6KifDfVESb1tBMTHc3DDUG1TlOTs7nd6flMx4QHd12PF1uKhb7OO6+wGtUNDkQa9ZJ3DBDN1UL4XXW8vA42pwvhBn2zSQgpYOo15t8iJUxm3jkhwq+OLu0RWQJvFnQfP34cq1ev9sl2N8WIESPgcDiQn58PAEhLS0NRUZHPGPY7qwtvboz3896va2pMY0wmE2JiYnw2gtAie05VocbqQGy4QZQw6nWcWBd0UGN13myhICPej8Bb5b28WUYoUCmmGjPe291usZ0TpDHuYpm5shqroqoMlp0OxliIwW5clch4O128qBaROvCONOphdL9/5c4Qy13fzQil1NzmcOH/Nh4DANx9UVdZ+l0zPM7moct4Z8nYn1dsJ6YCV/MKidoOihlvFUjNWSsxwKMuaCtxCgbeW48Jqr/sLgkIk7jsQQl1lrcbuJzXiw4s8K6S/r14yC0z73GOyswBGQJvFnQfOnQIP//8MxITW5d35ObmQqfTIcVtdjBq1Chs2LABdrvnRmX16tXo1asX4uPjxTFr1qzx2c/q1asxatQoAEBWVhbS0tJ8xlgsFmzZskUcQxDtFSYzH9k1wSdD1CtVCMK1ZLBWY3WI7UgyEppf5fX08q4JybzaSlulmF2S3BlvFUnpP/39OABg0uB0SfaXEGkExwnO0kr0U2ZU1ktzMw0o206syNIAm9OFMB0n3kxJBcdxonlShcwyUrkdzRmJUZ6FH7lZvvs0Ci0NSI42YfLgjrL+LbGXtwwZrMYclbmHNwCxs4Ua+niz936wZnxiSzEVZLzZtSrSqA86YGXtqSoVaCm2VZSZS1vfDXjM1cpC2H4wr1B+YzXAc704UyX9Qh3LeHc/R43VgDYE3jU1NcjNzUVubi4AwcQsNzcXBQUFsNvtuP7667F9+3YsWbIETqcThYWFKCwshM0m3Mhs3rwZb7zxBnbv3o2jR49iyZIleOihh3DrrbeKQfXNN98Mo9GI6dOnY//+/fjyyy+xaNEizJ49W5zHAw88gFWrVuHVV1/FwYMHMXfuXGzfvh2zZs0CINwUPPjgg3jhhRewfPly7N27F7fffjvS09MxefLkIP/biPZMsaVBEwZdLfHbEcFYbXSjukGPwZp2jANZtjsuwoDoFurNWDZMLeY0zcEy8oFKMVnG+3RVPawO5W8495ysxO4TlTDqdbhxqDR+GGF6nSj3VbLOu73UeLNWYp3iwyXP+AChk5GGLOPtDp7KZM54u1w83t9wBADwl9FZMIXJK7lk2bkimT9TDqdLPFdd5Ay83RLVOlVlvIMLvNUkNa8WHc2Dv/4pJTXneV42YzXAo45xuviQHRszJZOzvhsAOsQK78VCGWq8KePdhnZi27dvx9ixY8XfWTB8xx13YO7cuVi+fDkAYNCgQT6vW7duHcaMGQOTyYQvvvgCc+fOhdVqRVZWFh566CGfoDo2NhY//fQTZs6ciezsbCQlJWHOnDliKzEAOP/88/H555/j6aefxlNPPYUePXpg2bJlOO+888Qxjz32GGprazFjxgxUVlbiggsuwKpVq2A2S98rk2gfnKqsR87rG9AzNQrf3Dta6em0iQa7E9vzBQnw+d18FSeeXt7ayXj7IzMHPF8WcqzSSklbpZiJkUZEmcJQY3XgRHmd4ivGn24Wst1XDuggZgqlIDnahNIaK4qrregn2V4Do0qs8ZYu4+0t3wwVBeXusoZm2vAFC8vyyX3jedx9HJkyHQeD3UzLLZ1f/2cx/iyqQZQpDLeM7Nz6C4IkVOZqpyrr4XDxMIXp0EGGnuSMCFVlvINrJcZQk7maRezhHbxvB1MNVYQ44320tBalNTYYw3QY0CnW98mwMOCOOzw/twGDXoeESCPKa20oqbFK+h3YHJ4e3vIGrUwddaaqQfI2cIfFHt7nbsY74HfcmDFjWnQwbc3ddMiQIfj9999b/TsDBgzAr7/+2uKYKVOmYMqUKc0+z3Ec5s2bh3nz5rX69wgCAH7cV4gaqwM7CypRY3UEXd+kBDsLKmB1uJAcbTrLNZJlvPNLa9FgdwbdozgUnHBnsFuSmQNAepzwZVFkaYDTxctqwhQMzPwtUCkmx3HITIzA/tMW5JcqG3hX1tmwfPdpAMCtIzMl3XdKtAkHzqgk4y1pO7HQZ7w9xmryGPF4O5vLBc/zYuZedqm5W21RKnOZw7u/HAUA3DKic1Cu0f7CpKNyf6a82yTKWYPq6eOthoy3e5EuMrjzyMyySmtsin83S9FKjMGuEaFoO+gNy3YPzog7W1FiMgEffRT030iKEgLv0mob0LR1lGTYnS5x0V7uoJV5QtgcLlTW2UUjzWApr7WJ/hndUuRdRFUzsvfxJggtsfZgsfjzIQ32uwaAnW7Dq5FdE89aqUyONiE+wgAX71l5VDv+ZryTo0zQcULP0FDUaLaFYKWYXRLV0ct76faTsDpc6NshBkM6x0m6bzW0FGP1iJJIzd37qLE64HC6gt5fU5TVWLHmQNFZC99iwJogz02Op8Zbvpvqyjq7qBZo7RoQLKwloZxS850FFdh6rBwGPYc7R2fJ9ne8EU0La22wOeR5DwLeZTTy3lSrqsa7TpqMd2y4ARHuBQWl5easlVgw7dEYSmW8WeAtR303Q/yuqpFfZZdfWgu7k0ekUS+qI+TCFObpKy+lgpDdU3eKD0eEUXtJLamgwJsg3FQ32LHF7YIJCP2utQjLcjVVQ8NxnLhaqhW5+Ul3K7FOrdR3hul1YmbntErl5icrgpNisozfcQVbirlcPD7bIsjMbx+VKakMDfAECarIeEtS4+25wZBLbv7SyoOY/vF2fOKW/zPYtSCQtnWBwIKNchmzWcxYLSXaJHv7GSYXraq3wy7TIsn77mz35EEdxbY9chMfYUSYOwMtZ99h0ThS7sDbyPp4qyHjLbz344MMvDmOU43c3CM1137Ge1hTgTfPA7W1wtaKSrclQtlSLI85mqdGS/6d2xTsXqrQIt178ZA72XMu13cDFHgThMjGQ6WwOz0XYeYgqTVOtiLNFg3WCrVhsHbC3Q4pw4++lWkytsGQgmNBSjHVkPH+9XApjpfVIdochqsHSeNm7o2nl7dyiycs8A7WMAkQFoSYNFYuuTlbJPxg41GfNmwFMruBx4s13vJls1j7PLll5oC7F7P7YylHFv9MVT1+/KMQADDjoq6S7785dDrO63MlX5DArktyZ7xZH+86mzNkjtLNwd4nUshxRWdzhQ1CLQ3SZbxFVUwIA++TFXU4VVkPvY7DkM7xZw+oqwOiooStru2L2MzZPBTtB38/KiSF+ncMTZtj7zpvqfDUqJ+79d0ABd5EEBwursFfP96m2cxwY9a4ZeZMYqPV42KBd6dmZJm90oQLtxYy3jzP40SF/1m79FjmDKvOjLd34N0W1JDx/nRzPgDg+uxOssjFUqJDU4/aElJmvL33Y5GpWwK7OTpRXo/V7sCuqt4uSublcgMXzdVklJqfEOvU5a8J1Ok48ZjkuJn+9c9S8DwwKCMOPUJ885kithST79p4tET+VmKAJ+MNAHV2ZeXmbNEpXgI/CLU4m0tZ4y328Za55aA329xtxM7rGCuWJchBqMqieJ7H+rwSAMDYXimy/i2GJ4khzfXC5nBhbZ5wj81Mfs9VKPAm2szb6w7j5wPF+L9fjyk9laBxuXiscwferO4uT4OBt9PFi1/anZrJEPcSM97qP77yWhvqbMKNlT91TWniKq26M95tlWKy152sqJO1VrM5TpTXiQtUUpuqMZSu8T5ZUYcaq5DxCbY3LyNGRoM1m8Pl0/P8/zYK12PmJZAUZZTt5jMU5mqhMlZjMIM1OfrI/3pYaPN4YY+kVkZKT4rMLcUa7E6cdl935c54mw06UZlQZ1VWbi5pxtv9HXdSaal5vfTtxEIpNd96TPC5Gd6liWy3hITqu+pISQ1OVtTDGKbDqEadauRCbCkmUeD9xbYCnCivR3K0CePPk9mJTuVQ4E20CZ7nsdF9E6HFALUxu09WoqzWhmhTGG4ZIbR3Kam2yt5WRmoKLQ1wuHgY9JyYOWwMC7yLq62yZqqkgDmap8aY/HJ5lUMeJSXBZrxTok0wG3Rw8crUAX694yR4Hrige9JZjvlSkRICSWxLsDZpo7snSpbxljPwLq5uAM8DYToOBj2HbfkV2H2i0svRXL6ANRQ9eo/LLJdvTKJMBmsuF49N7u/MC7orF3iXyJTxPl5WB54X5MlSLVg1B8dxYta71qZcxtvudKHaHfgHW+MNeBbLlZaaV0vYTowpAWptzpAtFu85WQkATcvMJcQjNZf3u2rdQSHbPbJrYshMyTw13sFfL2qtDry55jAA4P5Le5zTxmoABd5EGzlUXCOu8h0qqm61jZzaYW7mF/VMRlyEUfwC1Jrc/KT7JjU9LrzZdlpRpjDx+NQuN/fX0ZzBpHpqD7zbKsXkOE7ROm/2ebi0j3xyN5ZFqLM5URvibFat1YH/bC0AAPxFQsdpUWpeL/3xsIxEWqwZEwcKNff/t/GY2Pta1sBbdDW3y/YdwDL3ch6HNx6pubQ303+csaC81oYIox6DZQ4ImoItxMq1oOV9bQuF+ROr8w71NcIbtuDEcdKUpYhSc4UVW6wkRoqMd4zZ45sQiqx3g90pqvkGZMTJ+rdClfFe55Zoj+2VLOvf8UbKJMbiTcdQWmNFZmIEpg7LCHp/WocCb6JNsJV7QFjJVNqFM1jWHBAubJf0FgKKXu76O621FBON1VoJVLVisMbqu/296Za6LklKpJJisswfa90TStjqN5OhyUGkKUw0Iwt11vubnSdhaXCgS2KEpLV0rFZSjoy355yYMf0CYbHgh71nsOWoUOfYOVE+2S8LUm1OlyyZxwa7Uzy+TBmPwxuWxZJa7cQUYiO7JsIYFvpbr1R3b94imTLewap5AsXTUix0gXdeYbWP6aN328HmFroDgUnNz1Q2+JgkhhrWfSFGAnM1nY4TFyUqZTKX9ObAGQscLh6JkUaky9w1gAXe5XU22VpFVjfYxZr1UNV3A9LdS1XU2vCeu5PDw5f3gkFPYSf9DxBtwjvwBrSXGfbmTFU9/jhjAccBY9wrij1ZYKqx4/IYq7UcGPVLjwUA5J6olHtKQcEczVtrJcZg5mqFFmVvXJpCKilmjxThvanEZ847uyonStR5u1w8Fv+WDwCYdn6XNrnON4ec5mqecxKOfumxGNU1EU4Xj1/+FOSJmTJmisMNepjcQaQcZStM8RJtCpPEvMofEiPlkZpvPKSczBwAUmLkLeE4Vip0AZG7lRjD01IsNFLzw8XVuPLNXzHprU2iB4RY3y2BzBwQ5L16HQeHi1e0q4OUGW/AqyQlBKVte05WAQAGdIqVXXkRH2GEjhM6kpXJdGybDpfB7uSRlRQZss8WAKS5peY1VodYetAW3vnlCKqtDvTtEIOr+neQanqahgJvImAcThd+d2dTuiULFwKttt4CPDLzwRlxYh9XlvH+U2PHxTLErQXe2ZmC1HH78QrZ5xQMrIe3P63EACFg0+s4OF287HVXgcJuTIOVYvbuoEwfdqeLF2/aO4Qo8A7lzecvh0pwtKQW0aYwXD9UWjkcq5WUJePNAm93YMWy3ozOMtZGc5zHBVyOOm9mrJaREBES+TLg6eUtpblag92Jre6slRLGakDopOahynhHuFUxNSHKeH+z8xQcLh5nqhrw5ppDALx7eEsToOp1nBjwKOlszjLesRLUeANAXARrKSZ/xpsF3v07xTU/SK8Hrr9e2PSte8c0uxsdJ9ZCy6X6XO+WmY8JocwcEBQlTPHQVpXM6cp6fORezH5sfC9JF7O1DAXeRMDsPlmFGqsDcREGTB7UEYC2M95r3TLzS/ukio+xPoN5GqtfPykG3i3fbA/uHAcdJ2TI5ZIeSoFY4+1n1k6v45DqDtqUbsnSmKMS3ZiyMoE/i6pD2sO2tMYKp4uHXseJcly5UKKl2IduN/Abh2UgSmIXcE+Nt/Q3nmcsnow3IJTLeL/H5Mx4A552QXIYUYbaWA2ALO3EtuWXw+ZwITXGhO4p8pgStgbLeJfWWGWRxR4rFc5V16TQHB+TmtfZWg+8nS5e/C5pCzzP47vc0+LvH248hkNF1V6txKQzk2O9vE8qZLDG87wYeEud8Q5FjTczVhvQMbb5QWYzsHSpsJmDW0T2tPiUvvSL53mv+u7QycwZaUHWeS/6+RBsDhdGZCXg4p6hXThQMxR4EwHDZObnd0tE7w5CT2gttKZqinqbU6y9Y/XdANA1ORI6TshQKeWu3Bb8lZpHmw1iP+/t+erMejtdvLiK7G/gDai3zjtfDLyDuzHtkhgJY5gOdTanqHAIBez/M8WtKpCT5BA7mx8qqsavh0qh44A7zu8i+f5jZXQ1Z+eFqRB0Og5/Gd0FgNB2if1fykUCM1iT4aa6wH0zK2fWvjFJUdIvJHhk5skhy9w3JjHSJJss1tJgFxVGXZJCc648Nd6tS83nrzyACxesE4OYQNlZUIFTlfWINOpxcc9kOFw8nl2+X3yPSNFKjMHqvJXyzamzOcUyLSn6eANevbxlznjXWh04XCIoywZ0aiHwlhDR7LRU+u/iA2eqUWSxItygx/CsBMn33xpsMbctgXd5rQ1f7zwJAHh8Qm/FrntqhAJvImBYoDq6e5IoyT5cUiObuYScbD5aCqvDhfRYs5hJBACzQS/W02hlUcHhdIkXSH8C1aGi3Lxc1nm1lSJLA+xOoTUak9/5QwfRGVZdgbenh3dwN6Zheh16uLNmB86E7r3J3lupAZyLthLqGm9W231Z39SAFnn8hd3AypHxLmzivFyfnYEr+3fA/Zf2CEmdIwCU10p/bGLGOyF0tY2i1FzCUpVfDynXv5uh13GiKSJbBJQKtr+kKJNkWdLWYAaM/mS8d7m9TJjhYKCwbHfOeWl4YfJ5MIXp8NuRMvx3hxBYSOk/wAJvpRRbrL47TMfBbJAmRGD/P3JnvPeftoDnhfrklBB8TwEeTwM5uoywhaLR3RP9aqcqNR1i2p7E2HqsHE4Xj16p0bK3ddMaFHgTAVFnc2BXgZAhvaB7EjrFhyP8/9s78/A2quv9vyPJlizb8r7vjp2NxFmcxAkkECAkJAECCTtlDVsLtCWltLR8gUL7o6VlJ20KlKVAgQQohSQEskFWsjv74jW2432VLdta5/fH6I4kW7ZlezSSnPN5Hj0Eayzd8ZVm7rnnPe8JUsJksYmLpECC1XdfNi6+1wJVrPMOEBk9MxQLVioQ54EUeFqmcDE84Kd13hUetEZzh+Nm4V9Sc0e7neFLMccmyq80qdO7Zla9iZwZ79ZOE76w78xL2ULMmQgtM1eTth7VZuPdzktIsBIrb5uKn83NkfT93MGk2d5YVFf4QGrO+ngbTFZ0SWDc1dhhxIkaoXvERT4yVmOM9ZJp6HDbJA4F1gu4w4OMNyvBKq4fvGeL2WrDuiM1AIAlk1OQFq3FT+eOAuAoH5I04+3jXt6s5aEuJEiyTbsoL/pAOCPKzAfKdhsMQg84jhP+PQwy7dem8qa+17/6bvOQSh0c9d3yy8yB4UnN95YJm1y+yNT7OxR4E4Nib1kzzFYeKZEhSI/WQqHgMDpBCCTOBEhm2JmiOuFGPD2z98VBrPMOkPNiDuApUSEemVgwg7Xj1XqPsgZyM9ge3gx/zHgLUkxh0SGFFJMtoE/J2A5Ozox3vIwZ76+P1KDbbMP4JJ3XFgneaifWaDDCYuPBcfC6pLwvWL3/2X4WnkPBauNRZb+mydXDGxAc1IPtLW+kMFhjpVljE8N9NkcMZswotVJGbmM1AAhTe5bxNlqs4gZecf3gz3tncSOaDCbEhAbjolExAIAHLxmFtGhHOZeUNd7JMkvNe3rYMAdrKVqJMeQyV3N2NJcL1uawvxrvn7y9B5e9+P2gMsdtnWYxKSK3sRqDbeYOxQeItUCbToF3LyjwJgYFW0TMzokVd0OdjcgCDXZDdidlHpMYWBnvKg8dzRkpkSFI1GlgtfE4XNnmzaENiUrWkzzas/NhJPthjTeTYsaFSyPFZAvokZ7xbpDB1XyX/Zq2aGKi12TZzuZqUpo11rUJ16+4MLXP+qMW2BdW24oaJC03qtV3w2S1IUjJicGIHDg7tUtR573DD2TmDKaUkXrDTgy842TMeHtY413T2g32lato7kS3eXAqBiYzvyovCSr7d0wTpMTTV10gHuMNqfm5lq5+rxXdZiu+OFg1rM+oxWrDPe/tw8JXt4sb3VK3EgPkM1dzZLwjvfo+zjA1Tmun2e35GYwWHKlqg9nKD6p967aiBth4YHRC2IBmud4iYYgZ7/ZuM45XC2vKGW6SWuc7FHgTg2JHcRMA4CKnRUSgBagMnnfINN1l8UaLUvMOWd2jh4rDWM2zizTHccgX5eb+V+dd1eyZQ3tPRHmUH7maiwvTGGkWpuw7V9ZkkEQO6wk1dum+t3t4Aw5X8yaDyaveETYbj92lwjVt1ijvBUasnZjFxkvad5jNiRybIX2RnxGFSG0QWjvNOFjRKtnrsgxSapTW62Z+PWFy88H28t5yqg4f7Tkr1ufyPC96oszJ9b2r7zinDbu+7mkN7UYUDeJebrbaxA3ATImub57gaY23szu4jR9cLW6XyYpvj9cCAK6xd3BhzBufgOvzUxEdGixpDSsLvA0mqyj7dscneyuwYvVhsbXZUPjP3gpsPd2AkzV63Pr2j6hp6xIdzXUStRID5Ml4t3WaRbn3xP4czSVGG6wSFVruVD9FTuUNg1Fc+NLNnJEUMbSyvYMVrbDxglJJjvVCoEGBN+ExjR1GnLTXql1ol1wBgSfJZnQYLeIimLVacSYzRotgpQJdZqvPHEYHg6eO5s5M8+N+3syxe7BmVyw7VtduFN1ZfU1pg7RSzLgwNWJCg8HzQNEQ5JNDoU7ftzpEaqJDg73mwOzMiRo9WjvNCFOrMMmL8sSQICWClELwKKXcvL+NQ7lQKRXi4nDTyTrJXpe5BMspM2cwg7XGQRisrT9ag3ve24/f//cYLvzzFix+bTueXXsCNW3dCFYp/KLW0ZOOCHe9uxeLXtuO0oaB66G3nqrHgle24VRtOxQcMN7e5UQOHDXe/Qfe51pdz3Mwdd6bTtah02RFWnQIpqZH9nr+r9fnYf/v50lq5BUSrBQVF1WtfZdvnLaXyQ3V1KvFYMKL350BIGxiVDZ34ba394j3qnB1YGW8j54TMqxp0SGS1tx7Qn8Ga84lmGfqPPvsma02fH+6AQBwiY9k5gCQpBPWUi2d5kEpRfaWCZvZ7ko4CQq8iUGwu0T4Mo1NDHfp48sC7/KmThgt8mTfpIAtWsM1KvEm7oxKqcAou3t0IGwqVA5Sag4A0zKEC+PBsy1+l9VnNetpgzgfQKg5VSk4WG28rH2g+0NqKSbHcWLW+5QMzuY8z8ua8VYqODHr7U13X3ZNm5EVLcpIvQHHcQ65ebd0gXdNm3zy//6YNy4BALDphDSBd1OHEW9sETJ542QM5hix9oW7p5s+R6pasWJ1IQBBespxgnfGuzvLAQDTM6N84krcE5VSIXqyuKvzrtd343i1HmYrj80n+269VVzfjjvf2Yu739uH0gYDYkKD8eKNk2Rt++bo493/mqNnP+wiD4MfwCEzXzIpxW0ZCsdxHvmpDBaHs3nfEl9WWlavH9o97pVNZ9DWZcaYhHCs/8UcJEdoUNpgwOv27503Mt6tndKW2jhz5FwrAHll5gzRYM1NSzHnEswiDzd9tp1pQLPBhNiwYJ8Gr7oQFULs163BlO7tKxMSOTOyyM3cHYNeaWzbtg1XX301kpOTwXEcvvzyS5fneZ7HU089haSkJISEhGDevHkoKnKVwjQ3N+O2226DTqdDZGQkli9fjo4O1w/kkSNHMGfOHGg0GqSlpeGFF17oNZY1a9Zg7Nix0Gg0mDhxItavXz/osRCe41zf7UyCTg2dRgWrjRd3SwMBlsHrL1s0xr5ICYT69XODlJoDgvRQG6yEvtvi8U1BDowWK+raPW+N5oxSwYlzWu0nzuZsJ1xK8yFHvab3P5v6Lgu6zYLkW67sKlvEV3ixW8LOEuGa5qzg8RaiwZqEckuxlZiPA++LR8ciSMmhtNGAEg8ypf1hsdrwyMeHUN3WjazYUPzs0lESjdJzWMbRk5ZiNW1duPf9/eg223DJ6DhsXnEJ9v9+Hv56fR7mj09ASmQI7r7QO275Q6G/Om9n5dN2+/2+J0V17Vj82g78cKYBQUoO91+cja2/novrpqR6Z8B9EGo3VzMMlPG23xdj7HNa7OHns7XThB/OCJsPSyYnD3WYQ8JR5933tY/VZDcMoe3d6dp2fLinAgDw9NXjkRETio/um4nYMDXY/rs3arwtNh7tA8zXUDnKjNVklJkz+jNYcy7BLGno8EiF97m9y8aSySk+8+4AhI2lpEHWeXebrSi019rPyPL+fTUQGfSMGgwGTJo0CStXrnT7/AsvvIDXXnsNq1atwp49exAaGooFCxagu9sxabfddhuOHz+OjRs3Yu3atdi2bRvuv/9+8Xm9Xo/58+cjIyMDBw4cwF//+lc888wzePPNN8Vjdu3ahVtuuQXLly/HoUOHcO211+Laa6/FsWPHBjUWwjN4nhd7kV7UwyTGOfsWSHXeLOPdn3R2dICcl9lqEzOSg8kQq5QKTE6LBOBf/bwFYxlBohszBNlYoh8ZrPE8jzKJpeaAvM7mNXrhsxWlDZItc9dfFkEKzFab2PLkQi/WdzN0YsZbuoVnrYyGd/0RrgnCzGxhkbV5mHLzv357GrtKmqANVuKft+eLGxZyIvbyHiDj3Wmy4N7396O+3YjRCWF4/dYpUCkViAlT44ZpaXjzjmnY+dvLMG98ghzD9oix/Shl9pc7Au89pU1u5aUf762E0WLDpNQIfPfoJfjdonE+mSOmUjN4WON9yWhBslvi4QbzN8dqYbbyGJekQ65d1ScXAzmbW228+FxTx+BKqniexx++Pg6rjceVFyTiQnsiJSs2FB/dWyBmp6MllGtrgpRiT/BWg3fqvB2O5pEDH6xUAosWCQ/l8O9nzNvAndTcWS1pstgG3Ehu6zRj0wlhw2fp1JR+j5UDttHuqbP5kao2mCw2xIapxXs44cqgA++FCxfij3/8I6677rpez/E8j1deeQVPPvkklixZgry8PPz73/9GdXW1mBk/efIkNmzYgLfffhsFBQWYPXs2Xn/9dXzyySeorhZkPR999BFMJhPeeecdXHDBBbj55pvx85//HC+99JL4Xq+++iquvPJK/PrXv8a4cePw3HPPYerUqXjjjTc8HgvhOQ0dRpxr7YKCc+9SGIh13izj7a6+mzEmQM6rtq0bNh5QqxSDblnD6rwPlPtPnbezo/lQnKZZIOJNmbKnNHaY0G60gOOkrVdlzuanatu9Jt9jsN3uxAj53KXFLEKzd1Q0hytb0WmyIkobJAYj3oQF3lLWeLONpUSdfPPSFw65ed8S5YFYe6Qa/9xWCgD46/WTxPuK3Hhirmaz8Xj000Icr9YjOjQY/7pzuk8C0MHSX8bb2WTTaLGJ7YwYVhuPr48I67RHLsuVtX1YT8KY1HwAV3MmyWa1sqUNBo8MGzfayyaumSRvthtwOGX31Ru6Tt8Ns1W45tt4z5QZjO9O1GFXSROCVQr8btE4l+fGJIbj0/tn4YGLs3HDNGkVDCzr7Y1e3o329SnHARNSPChN0WiAdeuEh2b4m5Zsvnqaq7UYTGLnHPZdGci48Osj1TBZbRibGI4LkuXP3vdksBlv1kasICvaa11CAh1JNQxlZWWora3FvHnzxJ9FRESgoKAAu3fvBgDs3r0bkZGRmDZtmnjMvHnzoFAosGfPHvGYiy++GMHBjh23BQsW4PTp02hpaRGPcX4fdgx7H0/GQnhOsb0uKiMmVKytciaQM979SWfZwq+0wQCzF92Vhwur706JGnygOtUPDdaG2sObkeRHGW9W350SGSJptjg3PhwcJ7Q8GorccDDUiQGefH2I+1rMSMWuEuZmHuOVOs2eOLcUkwKh7p5tiPjeOfbycYLB2v6zzWjpkSneeqoe0/+0CZ8fqOrz90/XtuPxz44AAB64OBuL85K8N9gBYJuXJQ0dfW5qbTlVj2+P1yFYqcCbt+cPuiTGV7ANu7PNnS6O4F0mK45XC8H4zGxhc52p3Bg/ljahod2IiJAgXDzaty7tWrureX8Zb7PVJqpCCrJioAlSwGS1iRu7/XHMbtZVkC1/jS0L0lgbyp70zJrWe+hl0m224k/rTgIA7puT5bYmf0xiOJ5YNE702JCKSC8G3kxmnh0bKqlE3lOYuVqTweTi4cHWw6lRIaKycKCSvi/sMvNlU+Ut3eiLxD6czVfvr8SCl7eJhsuMPXYV2fRMqu/uC0kD79paoe1CQoKrrCohIUF8rra2FvHxrvb4KpUK0dHRLse4ew3n9+jrGOfnBxpLT4xGI/R6vcuDEGAXixy72VhPArGXd729hjihnwxxSmQIQoOVMFltbut3/IWq5sHXdzOmZkSB44Sbeb0MfZM9YaiO5owke2Z2sP0nvQFbPEmdHQoJVortybxtsOaLjHdmP3VzUrBLrO+Wp79yhN2sSKqMt77bgi67FFgOp/mBSI3SYlySDjbe0QoHEDY4H11diIZ2Iz7dX9nn7//2iyPoNFlxUU4Mfr1gjBxD7pMZmdEIDVaiqqVLLEfoyWr7udwxKwPTAsi9NzZMjdgwNXje1WW5sLIVFhuPRJ0GN09PBwBsL2pw+d3/FZ4DACyamIRglW+9eVkCoNts61NqzZRgwSoF4sPVyI4V1i8DOZs3tBtR324Ex0EWNUxP2L3ibFOn23Or7BF4e2oi+sXBc6ho7kSCTo2fzc0Z/kAHQZSTwZrUDEpm7gXC1CrRcPisU2kUWw+PSQgX1879ZbxLGzpwsKIVCg5YMkV+pYU73GW8zVYbXthwGqfr2vHU/46Jm5NWG4+D9gTOdD/o4uCvkKu5E88//zwiIiLER1pamq+H5DewlkW5AwTelc1dA5qd+AuemKspFI769cLKNlnGNRSqhuBoztBpgkRJvb/IzR0bCUML9JIj2c3C91LzUi8F3oBDaeLtUghP/BCkhmVjGjtMA7YMGixdJisOnm0FII+xGuBkriZR4M3UHJHaIIQE+94xGwCuGOfaVsxm4/Gr1YfFxfaRqla3yqFmgwmH7D3AX7xhslcd5j0hVK3CVXnCwneNmyx9Q7sRW04Jmws3Tg+8dQLr533KKVu13y4Rzc+MwkX2ut/j1XpRxtxttuKbo0LS4lqZzcbcoXX6zPeV9RZbbEaGQKHgkGs3Sx2oBSPL4mXFhLrteOJtkiNDEKwUsvPuyqV6Zuw93TA/USOsYa7PT3WrXPQmnkjNeZ7H14erB62cPGI38/K4f7fBAISGCg+DNBu7oieJ00Yxuy+PTgwX18j9Zbz/e0jY2Lp4dJzkioOhwtbHtU413ptP1outFveVt+A7e1nGyRo9OowWhGtUYkkL0RtJ726JiYkAgLo6V3OVuro68bnExETU17vWgFksFjQ3N7sc4+41nN+jr2Ocnx9oLD154okn0NbWJj4qK/venT/fYC042I2rJ9GhwaI8z5/csfuDBRMD9eBkzoys9ZA/MpQe3s7k+5ncnEnphprxTvSjjHdZo/B98EbgzW5uJ71ssOaLtlU6TZBo8CN11vvA2RaYrDYk6jSy1alK3U6s1gebIQNxub3O+4fTDTBarPjXjjLsKG6EJkiB0GAlus22XtJEQJAwA0J20R9k8wBw43RB6rnuSE2vjZ8vD52DxcZjclqkz+rQh4PDmNER4LBr/7SMKMSFq8U2bjvs7ubfn65Hu9GCpAiNX/TnVasUUNlLRPqq865yKsECgJw4zzLe7DM6Ltk3wYNSwYmlNqVu5OZVQ8x4s3WClF4jnsJM21r6yXhvPV2PRz4+hF98Uujx6/I8jyP2soBJaYOoie7sFB4S4c7Z/IxTxpslrYrr3Tub22w8vjgoBN7+IjMHHOpB57K9T/YJjvgsy/+Xb07BbLWJMvNpGVFQylC+FahIGnhnZWUhMTERmzdvFn+m1+uxZ88ezJo1CwAwa9YstLa24sCBA+IxW7Zsgc1mQ0FBgXjMtm3bYDY7vqAbN27EmDFjEBUVJR7j/D7sGPY+noylJ2q1GjqdzuVBCLAbVW5834sMljU94+dGZIBwsWb9Lwda6LGM2I+lTV43sRoq7IY61JroaZn+E3jzPI9Se8uXUUPse51sn9P6dqNHRjrepGwEZbzlblvlrTpvUWaeEyObAYxO4hrvWhn7qnvKxJQIxIerYTBZ8e7Ocrzw7SkAwFNXXSDKsQ+6ucaw+Zglk/rAE6amRyE7LhRdZivW2Q3FAOH6xGTmN04LvGw34LRhZw8wbTYeBytY4C3M08X27iU77HXerKf1NZOSZfFEGAiO4was82bO32xDmsl9B3I2P2H/u4z3QQ95Rn913qwUi10fPa3xrhpCy1GpYBnv1n4y3uwzdqpW77HKqai+Aw3tRig4YHyS78zIMnsY4vE878h4J4QjLVoLtUoBo8Umbgg5s6esGedauxCuUeEKP+qCwO4vDR1GmK02nGvtwg9nhBKUd++ajpjQYJQ2GvDx3grsswfe1EasfwYdeHd0dKCwsBCFhYUABBOzwsJCVFRUgOM4/PKXv8Qf//hHfPXVVzh69CjuuOMOJCcn49prrwUAjBs3DldeeSXuu+8+7N27Fzt37sTDDz+Mm2++GcnJgnzp1ltvRXBwMJYvX47jx4/j008/xauvvooVK1aI4/jFL36BDRs24MUXX8SpU6fwzDPPYP/+/Xj44YcBwKOxEJ7R1GFEk8EEjgNGxbnPeAOObHgg1Hm3dJphsgdkcWH9G0ZNy4xCkJLDudYur/YUHg7DkZoDjsXW8XNtMFr6d4n1NrX6bhhMVqgUnLiLPFhiwtRQKThYbbzXjcf6w2bjxRsxqy+UEiYZLarv8OoGgy8y3gCQEe2dwHunXb0iV3034GyuJo1sXqy796OMt0LBiVnvP39zCmYrjyvGJ+CWGWmiquagXVLuzC4fzMdAcBwnBtar9zvk5oWVrSiq74AmSIGrJvnOAG449OyIcKa+He3dFmiDleI1ZbY98N5e1Ah9txmb7dL6a/xAZs5gcum+yttYoMn6YrM1SnF936Z5AHCi2g8Cb/umc5m7wNteipWfLnynWBKhP3ieH/Y6YTgMlPHuNluxyS5Z5nm4Vca446XvzgAQuir4suQms8dGSZ3eCH23BUoFh+y4UCgVnLh+LqrrvfHDendflZckW8tOT4gJDUaQkgPPCxs8q/dVgueBWdkxmJgagV/OywUAvLKpCHvKhOv4jCwyVuuPQQfe+/fvx5QpUzBlyhQAwIoVKzBlyhQ89dRTAIDHH38cjzzyCO6//35Mnz4dHR0d2LBhAzROlv0fffQRxo4di8svvxyLFi3C7NmzXXp0R0RE4LvvvkNZWRny8/Pxq1/9Ck899ZRLr+8LL7wQ//nPf/Dmm29i0qRJ+Oyzz/Dll19iwoQJ4jGejIUYGJbtTo0K6ffCJma8AyDwZhm8mNDgAU1itMEqTEkTLiS7/FBubrLYUGM/n6HuZKdGhUCnUcFi4weU4Xkb9v7pMVoEDbHWU6ngxNokX8rNq9u6YLLYEKTkxLpzKUmL0kIbrITJYnPbQ1QKukxWsS65Pz8Eb+BOvjdc9N1mHLXXBMpV3w1IX+Mt1t37UcYbAK4Y7zBPjQ9X4y/L8sBxHKams8DbNeNd29aN0gaD0KrSzwx5lk5JgVLB4cDZFvG6xILwRROSAqJ9mDty4sOgVHBo6zKjVt8t9u+enBYp1tdPz4xGsEqBWn03Vm4phsliQ058mE+D0Z44Au/+pebsvpgREwqVgoPBZO3zvtBttqLErrga7yOpOSA4dAO9pebdZqtYZsI6kniyudzYYUK32QaOc8iH5WSgjPfWU/UwmBzzyJzK++NQRQs2HK+FggMe87Eho6OXt/CZYwmozBitGEizjZ8zPTwGOk0WfHO0BgCw1I9k5oCwmcru++daurDGrva5eUaa/b/pyI4NRbPBhJZOM9QqBSamRPpquAHBoFe1c+fOBc/zvR7vvfceAGGX+Nlnn0VtbS26u7uxadMmjB492uU1oqOj8Z///Aft7e1oa2vDO++8g7Aw12xQXl4etm/fju7ublRVVeE3v/lNr7HccMMNOH36NIxGI44dO4ZFixa5PO/JWIiBER3N+8l2A4KBBCDsVPqrJJvhaX03Y+Yo/63zrmnrAs8DmiAFYsOCB/4FN3Ach7H2BZWve5aXePh5GwjRjbPVd4E3y1akR2u9YhilUHBijelJLzmbs0WeNlgJnUZeQ57M2N6GNcNlb2kzbLwg5UyOlG8BKnWNt69UCANx4ahY8XPy4o2TxDr9SWkR4DghC+lsBrW7VJAyT0yJEP9G/kK8ToO59rZZnx2oQpfJiq8PC3LYGwJUZg4AapVSLOM5VdMu9uueluHIVGmClCiwb4S8vaMMgGCq5k+9eUPtiYBOD6XmQUqFKM/ua4P5dG07bLywKR/fT8cTb8MCOeYRwmDnpA1WirX6npirsU2IJJ3GJ470LHg7Ua1Hl6n3RsnaI0LgyeaUtXPrC57n8ZcNQinL0qmpPvdacJiBGtFhtIgll2OcXPHFOu8eGe+vCqthMFmRHq11+Q76C0xVtXp/JarbuhGpDcKCCwSvrCClAr9dOFY8dkp6pM87Hvg79NchBkSs7x7gwjY+SYdglQKNHSaUNPhv6y3AIc1K8LAvMcuM7Srxvzpv57qt4SyK3Bnu+IJiVt/dh4O+pyRFMoM13zmbO+q7pZeZM8Z6uc671knSLPeiOz1aWHxWSCg13+mjemIWVA6U8e42Wz2aSzYvcqsQBkITpMQn98/CmgdnYU6uo9dzuFP3BOYoDwC7ilk/df+RmTvDAuzPD1bh6yPV6DBakB6tFYPSQMXZmHH/WeZo7npOs+3u5swM6ppJKTKOcGCY47jBTSBntfHipmuKk7Sa+dT0ZQLLJM7jk3U+3WRgUvNzLV0u5V+slVhalFZ0vq7XGwdcl/iyvhsQ+qGnRoWgyWDCp3ZzLobBaMHmU4LM/L6LswEAx6r7D7x/ONOAH0ubEaxS4NErfJ9QiwhxNQN1tBJzqCZy3Tib22w83tpeCkBoTehPG1sMpqpirutLp6S6yOGvGJ+AGfZrx6xs/7yO+xMUeBMDwlpv9NXDm6EJUoq7dcwsx18RzaI8bNkwJT0SapUCjR1Gn0uxeyJV3RZbiPk68C6pF4JVyTLePpSas8A7e4gmcZ4wRtww8Y6zea3edyZezLCmuq0b3WZpvAeYauUimQM9nb2Pd6fJ6ralFuP59Sex4JVtWOtk6OUOpkTwhWx0IMYn69w6X0+xy80P2eXmPM+L5Tv+ZKzmzGVj4xETGoyGdiP+3/qTAIAb8lP9wmBsOLA6721nGlDZ3AWOE+5zzjhvnExJjxSzev5CqNpuruamxrtO3w2LjUeQknNpzZTj5C7tDmasNs7Hkvq4MDXC1CrYeNe+3ayVWFp0COLtiQOjxYb2AczIKn1Y3w0ImdEHLhkFAHhzWylMFsc1cPOpenSbbciI0eKWGUIP+eL6jj6VDDYbjxc2nAYA3DEzQ6zh9xiFArjkEuGhkC4McjYDFR3NEx3rGGdnc5t9M2vLqXqUNBgQrlbhJj9tTcjWUmwD7pYZruPkOA5v3DYFv1s0FsvnZMk+vkCDAm9iQMRWYh5kIMXMcLH/SbKdqWsfnEuzWqUUnb93l/rXuQ23lRhDDOA8NDXxFpJlvMXA2/cZ78whmsR5Apu3M24MW6Sgts3u/u+DzGp0aDDC7XWclRIYGzYbTOLGUkG2vBnLcKd64L6czXmex/pjQq9kZ0OvnnSbrWJvbH8yVxuIqfbAjkmbK5u7cK61CyoFh+mZ/iexBIBglQLXTREyva2dZnAcsCzfv+owh8I4+0brj6VCtntMQnivmvWxieFi+dKSSf5jqsboz1yN3ReTIkJcWhsN5GzuD8ZqgBDMMGfzUicFIWsllhol1A6H28s6BjJYk2qdMBxuyE9FfLga1W3d+NKePQWAtfbyjavykpCg0yAuXA0b33f51NdHqnGiRo9wtQoPXZoz+IGEhADffy88QqT7e2TFsPnqEANvZwl8erQWwUoFusxWsWTgTXu2+9aCdJd7hD+R6LS5m58R5Vb9Gh+uwf0Xj0KYzP3hAxEKvIl+aes0i60qBsp4A8CFdmna7tImt70K/QUWTHgqNQccjrv+tqlQ2exqIDNUxoj1YkY0G/pu+eFN2rrMYk/SobYSYyT5QS9vb7YSY7DvZWVLp2RZYWd82baK4zhkxErnbL7X7ro6OiFM7EEqF0oFJ24i9CU3P1PXIX7+dxU39mlExGTmIUFKMZMeCDAzqCPn2mCy2ERl1JT0SFE27I8413PPyY2T1RvAWzjXngKOlpLOKBQc/u+q8Vg6JcUva9rZZ6bTjdS8LyUYu14W1fcO6mw23kVq7mvYfcPZ2Zx1Vkmzd3yIs9ehD1TnLQbePujhzdAEKXHfHEFK/o8fSmC18WjvNuN7e3uqq/KEzZ0J9r+9uzpvk8WGF+1O5g9cko2o0KH52ngDZga6vagR3WYbglUKl84sKqVCVL8V1bejsLIVe8uaoVJwuPsi/80UO/uI3OynWflAggJvol+KG4SbU1KExqPduLyUCISpVWjrMnvcDsIXsJuUp1JzwCGF/LGsSZQJ+QNS7WSHqVVIixZew1uy5YFgbrIJOvWwd399ba5mstjETRFvSs3jwtQI16jA89KakDFqfeyenRHN3GKHf24suzcz2zeyZrGXd7d7CeWOYkeJjsXG4zt7e52eOBur+WNNYF9kx4YiUhsEk8WGEzV6J5m5f9cFjkkMF8uobp0xMhaeSREaF7NE1lKyJ0smp+ClmyaL2WV/ghlxuct4n+vRSowxKi4MHCe0tWrq4QZe0dwJg8mKYJVCdBX3JZluAm8mGU+3B9DMAK5hgF7evmwl5sytBemI1AahrNGAdUdrsPFEHUwWG0bFhYp+JRNThH7c7gLvzw5UoaK5E7Fhatwz27+CVWYGuq9cuM/k2rsHOJOb4FCovbVNyHZfMznZ77pTOMM+a+FqFRbnBWYLRX+CAm+iX5jM3JNsNyDs6DHTmZ3F/lvnLdZ4D0KmOTElAqHBSrR2mnHSR4GpO1jgnSaBaQqr8/aVszmru/P089YfSfb2XfXt3V7tcd0XlS2dsPGC+6w33XE5ztEflNXHS0mtj/tFO9fNDZcf7WUivgq8BzJY21EkZH7Y33q9vcVMT1jdvb8Zqw2Ec1uxA2dbnPp3+2d9tzN//8lUfLB8Bq6cMDIWns6dLAD3GW9/R5Sau6kF7stMLCRYKQbjPeu8WbJgTEK4V7pQDJZsd4F3s6PGG4BYv95f4G2z8ZKuE4ZDqFqFuy8UAua/by0WuwRcledwzJ9gD7yPugm8P7Ebsz14SfbQVTIGAxAXJzwM0t0zWXab5WXGuJFks5LNLSfr8c0x4fp+v91Qzl+5IFmHZ5dcgH/eke/XyqRAwfdXFsKvYe6LzAnUE5jcfKcftt4CBIMIdpMajNQ8SKkQ+8z6S1uxbrNVrFeXYid7nFjn7ZvAm2W8h2usBgCxoWoEKTnYeIjlEnJS1uCo7/Z2VlIMvBukr/P2dcab1cefHWaNt3N9t6/6RTNZuDsJucliw54yIVPy+8XjAAibl22dvYN0Virjb63EPIHVea/ZX4nGDiPUKkUvUy9/JD5c42I2NhJg1/tEnWbwBlV+ADNX63TTx7tnKzFnWPDDnKcZzFjN1/XdjJ5Sc323Wdy0YwG0Q2re9z2uscMIk8UGBee767gzd12YiTC1Cqdq27H1tLDZePUkx4YWC7yL6jtcyqdO17bjSFUbVApO9F0YMo2NwkNCMnuYD45O7L1uHm3v5b23XGhrefHoODHh4a9wHIc7ZmWK5ZbE8KDAm+gXMfBO8DwQYtmLfWXNLs6V/kJThxE2HlBwQMwg6zzFOm8/CbwrmjvB80C4RiW2shgOY0Rncx9JzeulMVYDhPpEtsiokMCYa7CI9d1elJkzRsUL7yF14G2x2sRNKl8t2NLFjHfvzERrp8ntz93hy/puRrZ9g+QHe02jM4WVreg0WRETGozFE5MwJiEcZiuP707U9jqW1d17ag7pT7CMN9sEmZ4ZDbVK2d+vEF6iwK78mDsmLqBKFhiOdmLuMt7CNT/FTeCdby8beHdnucsaRTRW84P6bsAhNa9vF3pDs9Kl6NBgMdvP1FT1+r5LqiqdjOaC/CCTH6ENwk9mZoj/PzYxHDlOyZ2kCA1iQoNhtfEuXVY+O1AJALh8XPyg125yEKkNRqTWUSLnLuOd0yOJ9YCfZ7sJ6fH9N5Dwa0rEjLfngdCYhHDEhAajy2xFYWWrl0Y2dOrs7p9x4epe9TcDweq895Y1+0S+3BPmdpodK01WlbWYOVPX4RNzPNb/XYqMN+Bw7nVXK+ZtShsdc+NtvJXxbrBvUqkUHGJDfbPQYRnvqpYulzZcPM/jlrf24IqXtqG8ceDg29f13QCwbKrghr3+aA303a6ZbCYzvygnFgoFh0UTk8Rje+JoJRZ4gfektEg4X3b9tY3Y+cDCCYn49P6ZePKq8b4eypBwtBNzzXjbbDyqW/tWgt11URZiw9QoazTg/V3l4s9P+JGxGiCUpjBX+fJGg0Nm7nROrKVYQ0ffGW9/qe92ZvnsLKhVQghyVY+6YY7jcEEPubnZasN/Dwmy9Ovz/ddnwdlMzV3GOyNGiyClcAEcn6QLiDIbQloo8Cb6pMNoEeVag6m5VSg4cTHlj3XerL57KDWr45J0iAgJQofR4rb+SG6kds3OjAmFWiW0u5A7S2y0WMXspRQZb0BY5APA4Sr556pcBkdzhnONt5TGf8zEK0Gn8Vnf4vhwNTRBClhtPKpbHa3h9pW34GSNHiarDd+frh/wdXxd3w0IMuvc+DB0m234qtC1TzczVpttL9VZnJco/rxnTbiv6+6HQ6haJSprgMCo7x6pcByHguyYgG0BFNpHxruhwwiT1QalgnP7HQlTq/D4gjEAgNc2F6GxQ+jkwa53Y90ETL6CbTyWNRocHUycnMnjwuxeJv20E+ur3t2XxIWr8eRV4zErOwY323t3OzMxRbhGHLevs3443YDGDiNiw4Ixd4z/lnwwuXm4WoVkNxujQUqF2CP+gUuyA1JpQgwPCryJPmHZ7rhwNSK1g5MxM0m2v9RCO8OyRfFDWLQqFRxm2vv/+oPcvKxRmKOsWGkCVaWCE/tOnpZZbl7eKJiRhatVkpmR5aUKu+ZHqloleT1P4Xle7EeeKUPgnRGjhUrBoctsFT/fUlDX5tv6bkDYyGOuquVOBmtr9leK/95d2v93scUP6rsBIdC5yd6OZbXT+PXdZnFz6KJc4dqZEx+O0QlhMFt5bOrhbl7jB/MyHFidd5haJToYE8RgYXLrnjXeLMObqNP0aZJ2fX4qJqTo0G604MXvzojGaunRWr/qp+xc593T0RxwZLz7q/H2x4w3ANw+MwMf3z/TbenPhGTXjPdnB6oAANdOTvELuXxfsIz36MTwPoPqF2+YhFdvnoxrJiXLOTTCT/DfTy/hc4qGIDNnXJQjZDEOVbag0039lS+pFx3NhxbczbJnzH4cYLEvB+WNwg2VtbGQAtbf9aTMBmtMJp0dHybZLnBeSiQAwRG7r57I3mBXSRMa2o3QBivd1nlJTZBSIbp/Syk3r/GTzCpbzDBFhMFowTonCfaPpc39ZvqZaZkv67sZ101JQZCSw5GqNrGm9MeSJlhtPLJiQ11MrnrKzU0WG/5XeA6NHb6tux8uF48WMlZzx8T5hXs0EZho7e3EOnq0E/OkxaZCweGpqy4AAHy6rwKfHxQCO38xVmMwjxDnjLezMznbpG7rMsNo6W0yBzh1PvFhD+/BwgzWztS1o07fjc2nhM3HZfmpvhzWgFwyOg4hQUosnJDY5zG5CeFYMjmFst3nKXTHI/qkqF4IvIYSeKdHa5ESGQKzlcde+6LXX2A13oPp4e3MVLsxiz/0KXfUEUuT8QYcMju5W4qJrcQkqu8GBBMXJv06IqPc/J0dZQCErIpc/W8dcnPpAu86HzuaMzJ7tBRbd7QGnSYrMmK0CFOr0NZlFusz3eEPMnNGTJgaV4xPAODIeu/sITNnLLYH3tuLGvG3b0/jor9swS8+KYSNF+q7fVV3P1zmj0/Af+4rwJ+unejroRABjJjxNrkPvN0ZqzkzIysai/OSYOOBLw6eA+A/9d0M5hFS2mgQTdJYKzFAqAMPtm9e9dVSzJONCH8jNSoEESFBMFt5vLDhNMxWHhNSdKJMe1goFMC0acJDIW0YlJ8RhWN/WIB755BpGuEeCryJPilmPbyHkLHjOE6s3fM3uTlrvzXUHrgswGnsMKHZIF8WtSf6brOY+ZIy4z3WR87mYisxieq7GRNTIwHIJzcvazRgi73m+K4LM2V5T8BRF88M6qTAXzLe6T0y3p/tF7JTN05Lw3R7/+H+FCjsuYIs3wfegDBuAPjvoXPoNlvF+u6LegTeuQnhyIkPg8lqwxtbi9HQbkR8uBqPzhuNrx6e7bO6++Ei3B9iEaH1H0kvEXg4+ni7ZnodrcQGvi/+9sqxCFY5lsKSBHYSwkqVyho6RMm4c8ab47h+W4rZbDzOBWDgzXGcWIbC1Ag3SGWqFhIC7NsnPEKk/5sM1rSXOL+gwJvok+FIzQHHInJniX8ZrLGMd/wQpeahapUoBy2WMLs4WJh5V1y4WtKaNOZsfra5U9YyAfa3HCVx+61J9jpvuQzW3t9VDp4HLh0TJ7aPkgO2ISTlZ9LXPbwZLONd3tSJ8kYD9pY3Q8EBS6emiEaOfW3wOdd3F2T7rr7bmTm5cUiO0KCty4z3d5WjpMEABecoY3HmnouyAAAzMqPxxq1TsPO3l+EX83LFxTZBnK+E2qXmJovNpeOBmOH1oDd5WrQW9ztlJ/0t483M1fTdFnSbbeA4ILnHebFrgbuMd317/0Zz/swEJ/+HICVHNdHEiIACb8ItXSaraOQx1MCbLYiPV+tlra8diHoJggmWlfVl4C21ozkjNkyN2LBg8LzQVkwObDZebI0mdcY7T8aMt77bLJp+3TM7y+vv5wzbsJCyxrvWT0y82OKzorlTlGfPzo1DUkQIZmULG3x9tfhj9d258b6v72YoFRyut2e9X9p4BoCgzHCXAb61IB2n/3glVj84C1flJfu1sRBByAnr4w24GqwN1kzsp3NHIS81AnNyY906UfsSTZDSxfchOSLEJUMPoN+MN/tbJEX0bTTnr0xIcWyCzBuXgKjQwZn8EoQ/EljfQkI2Sho6wPNAdGgwYoa4WE3QaZATHwae9w8jMkDYGW+yy8OHWuMNODYjWB28L2CBalaM9K7ZTG4ul7N5dVsXusxWBCk5F8dWKZiQooOCE5QOdW4cv4vrOyQLytfsr4LBZEVufFivel1vw7Lr9e3GXj2ihwLP846Mt48zJUkRGqgUHEwWGz7YfRYAcIPdZGd8sg46jQrtRguOV/f+vPpTfbczN+SnguMAo0XYLJjTz+dFrVLKNSyCCBiCVQqxvpm1FON5Z2m1Z/eSULUKXz08Gx8sL/BLwyvnzXV3mwnMYK3Bzf1NNFbzo1ZinuLc8eB6KU3VOjuBzEzh0Slv21SCoMCbcItodDXM7CNrvbWvvGXYY5KCBntNdLBSgchh1BfmJvg+411ur3fNkliaDTgM1uRyNmd/x8yYUMl35bXBKuTGC+dzuLLV5TmD0YLrV+3CdX/fNWwzOauNx3u7BFO1uy/Kkn0BFxESJGY+SiWo867TG2GyB4VD9UOQCpVSITrythst0GlUokGZUsFhhr12211bMX8NvNOitS6bMz3ruwmCGBitWtiUYmVRDe1GGC2CJNvXSh2pcA683TmTx9uTCGx944zY+zuA6rsZ6dFazB+fgDm5sbhktIS9u3keOHtWePB9d8MgCG9AgTfhluPVQj3sUGXmjKnpgvHRoQr/CLyZdDZepx5WYDSSpeaAo6WYXM7mzBBslJdqoh39vF3rvL8sPIfWTjOsNh5vbC0e1ntsPlmHyuYuRGqDcN2UlGG91lAR5eYSfC7f21UOQPjb9ZQ2+gLWLg0AlkxOgSbIkQVmRo67etR5t3aacLrOv+q7nWEma5ogBaZmRPp2MAQRgITa5eYdRiuK6ztwxzt7AQhKMH+4bklBpnPg7SZzLUrN9e6k5oPL/vsTHMfhzTum4YPlBQEnkyeIvpD8k5yZmQmO43o9HnroIQDA3Llzez334IMPurxGRUUFFi9eDK1Wi/j4ePz617+GxeJq8vT9999j6tSpUKvVyMnJwXvvvddrLCtXrkRmZiY0Gg0KCgqwd+9eqU93RNJpsmDNAcFFcrhZGBZ4H6vW99ljUk4cPbyHtxOeEycEpjVt3WiXQNY7WHieR1kDayUmfeDNnF1P1erBy7AjLJXCoi/y0iIBAIedJOU8z+PDHyvE/197pHpYGynv7BSy3bfMSEdIsG+kwWJLsWHWeTe0G/G+PfD++WW5wx2WJGQ6lVSwgJXB/CT2lzeLJks8z+P/rT8JnveP/t3uWDghEQ9cnI3nl04kOTlBDAHWy/vTfZW4+vUdOFXbjtiwYPx5WZ6PRyYd2S4Z776l5m5rvFsDN+NNECMRyQPvffv2oaamRnxs3LgRAHDDDTeIx9x3330ux7zwwgvic1arFYsXL4bJZMKuXbvw/vvv47333sNTTz0lHlNWVobFixfj0ksvRWFhIX75y1/i3nvvxbfffise8+mnn2LFihV4+umncfDgQUyaNAkLFixAfX291Kc84vhkbyVaO83IjNFiwQWJw3qtjBgtorRBMFlsssmW+6NODLyHtwiP0AaJNztfZL0bO0xoN1rAcUB6jPQ72TnxYVBwQEunuc/eoFLirVZiDOZsfvRcm7iRcLCiFSdr9FCrFJiVHQOeB/4+xKz3yRo9fixthlLB4faZGZKNe7BIFXj/84cSdJmtmJQagcvHxUsxtGHDlB1jE8NdTHcAYExCOKK0Qeg0WcV6/VU/lGL1/iooOOCJRePkHq5HqJQKPLFoHK6bImH9IkGcR7CWYh/vrUCX2YoLR8Vg/S/mYEaW/ylchsqAUnNd367mYo23xN4pBEEMDckD77i4OCQmJoqPtWvXYtSoUbjkkkvEY7RarcsxOp1jEfXdd9/hxIkT+PDDDzF58mQsXLgQzz33HFauXAmTSTDFWrVqFbKysvDiiy9i3LhxePjhh3H99dfj5ZdfFl/npZdewn333Ye7774b48ePx6pVq6DVavHOO+9IfcojCpPFhre3lwIAHrhk1LD7EXIchyl+JDevs9+Y4odhrMbwpdycycxTo0K8kinTBCnFm/1JGeTmJWIrMe8E3mMTdQhWKtDaaUaFvebtox8Fk66rJyXjiUVjAQD/O1wttmkbDK9tLgIAXDkhsVerFzmRopd3nb4bH9j/No9eMdpvzIaWTk3BLTPS8edleb3GpFBwYg337pImrD9ag79sOAUAePrqC3DpGP/YPCAIQlrC7IG3ggN+dcVofLC8QJL7uz+RGhWC0GAlFJz70jImNW/sMMJmcyjUrDYe1a2B18ObIEYyXi2aMJlM+PDDD3HPPfe4LJQ++ugjxMbGYsKECXjiiSfQ6eQquHv3bkycOBEJCQnizxYsWAC9Xo/jx4+Lx8ybN8/lvRYsWIDdu3eL73vgwAGXYxQKBebNmyceQ7jnq8PVqG7rRny4GkunSlOnOsUu8z1U0SrJ6w2HOgn7Euf6NPB2mJF5i7F2uTmr9/cW9fpu0Wk+2wtGcYDgfjvO3p/8cFUbWgwmrD1aAwD4ycwM5KVGYu6YOFhtPP7+/eCy3oWVrfjmWC04zveybLYZdLbJ4NLXdjD84/sSGC025GdESWtoM0zCNUF4fulETLZfT3rC5OZfHDyHRz8tBADcdWEm7rwwU54BEgQhO7cWpGNmdjT+c99MPHJ57rCTBf6ISqnAW3dOwz9+ku+2ZCY2TA2OAyw2Hs1OrVvr9N0wW3moFJzPDTIJghBQDXzI0Pnyyy/R2tqKu+66S/zZrbfeioyMDCQnJ+PIkSP4zW9+g9OnT+OLL74AANTW1roE3QDE/6+tre33GL1ej66uLrS0tMBqtbo95tSpU32O12g0wmh0SHX0enlaKfkLNhuPVT+UAACWz86SLJMqZrwrfZ/xZuYjw5WaA0BOghDIFfkk8BY2q7xR382YmBKBdUdqcOyc9wJvo8WKRz4+BECQEDPZoDfIS43E4ao2HKlsRV1bN0wWGyak6EQZ+iOX5eL70w344uA5PHJZrkfSPJ7n8ZdvhGvK0impoimdr0jSaRASpESX2YrK5k6xxZjRYsWq70sxMVWHy8Ym9Pn71a1d+M8eoe79V36U7faEWfaMd6ldsXDpmDg8udg/JeYEQUjDoolJWDQxydfD8DoXjurbbydIqUC0NhhNBhMa2o1icM5k5smRISNyQ2LIcBwwfrzj3wQhI14NvP/1r39h4cKFSE5OFn92//33i/+eOHEikpKScPnll6OkpASjRo3y5nAG5Pnnn8cf/vAHn47Bl2w6WYfi+g6Ea1S4tSBdstfNS4sAxwGVzV1oaDeKsihfINZ4SyE1j/N9xtsbjuaMvBT3TuBSwfM8nvj8KPaUNSNMrcLLN032yvswmLP54apWsRbuJwUZYnCZnxGF2Tmx2FHciH/8UIL/d93EAV9ze1Ejdpc2IVipwKNX+N6ETKHgkB0XiuPVepQ0GMTA++WNRVj1QwkUHPDe3TNwcR+Z7JVbi2Gy2lCQFS1mkAOFnHjBQK2xw4ixieF4/dap5IRLEMR5QVy4Gk0GE+rbjRhn34eoahE26N0Zsp3XaLWAXUFLEHLjtVXJ2bNnsWnTJtx77739HldQUAAAKC4W5J2JiYmoq6tzOYb9f2JiYr/H6HQ6hISEIDY2Fkql0u0x7DXc8cQTT6CtrU18VFZWenCmIwOe5/H374Vs9x2zMhCuGXqP657oNEGiLLuwRx9luanVs3ZiEkjN7b28K1s60WWS17FdbCXmpZpoALjAHnhXtXShxWAa4OjB88qmInxx6ByUCg4rb5sqOql7i0l2ifK+8haUN3UiXKPCNZOTXY75+eVC8Lxmf6VYG9cXNhsv1hHfPivDb9q19DRYO1jRgje3Cd9tGw88/J+DKHVjvlbWaMDq/cI171fzxwRUthsQ/CQemz8ac8fE4V93TRdrPwmCIEY6jpZi3eLPxFZikf5xbyIIwouB97vvvov4+HgsXry43+MKCwsBAElJwhbdrFmzcPToURf38Y0bN0Kn02G8XRoya9YsbN682eV1Nm7ciFmzZgEAgoODkZ+f73KMzWbD5s2bxWPcoVarodPpXB7nC3vKmlFY2Qq1SoG7LsyS/PWnpPneYK3TZEF7t9CWTgqpeUxoMKK0QeD54btIDwarjUd5k/el5hEhQci0O6YflVhu/vmBKrxqNyT747UTZKklHhUXJraeAYBlU1OhDXYNzmZkRaMgKxpmK4+37CaDfbH2aA2OV+sRplbhoUtzvDLmoSAG3vUd6DZb8diaw7Dxgonc1PRI6LstuPf9/WjrEtrg8TyP1fsrcc0bO2C28piTGxuwjsA3z0jHe3fPQIoPDe4IgiDkhhnKObcUq2ymVmIE4W94JfC22Wx49913ceedd0KlcixsS0pK8Nxzz+HAgQMoLy/HV199hTvuuAMXX3wx8vKEnovz58/H+PHjcfvtt+Pw4cP49ttv8eSTT+Khhx6CWi0ESw8++CBKS0vx+OOP49SpU/j73/+O1atX49FHHxXfa8WKFXjrrbfw/vvv4+TJk/jpT38Kg8GAu+++2xunHPD8w57tvnFamlek4FPSIwH41mBtT1kzAKHvpxTZMI7jkBsv1PTKGXhXt3bBZLEhWKnwuoP2hBRHGy6p+LG0Cb/94ggA4MFLRuGWGdKVNfSHUsGJ5wMAt/VRTvHTuULJy+cHqtBtdq9kMFlsePG70wCA+y/ORnRosMSjHTqj4oXNmOKGDry08QxKGwyID1fjuSUXYNXt+UiK0KC00YBHPj6EyuZO3PXuPjz+2RG0d1swKS0Szy8dWGJPEARB+A9s3Xaqth3bixrw5aFzosIwlaTmrnR2AhdcIDyczJ0JQg68osXbtGkTKioqcM8997j8PDg4GJs2bcIrr7wCg8GAtLQ0LFu2DE8++aR4jFKpxNq1a/HTn/4Us2bNQmhoKO688048++yz4jFZWVlYt24dHn30Ubz66qtITU3F22+/jQULFojH3HTTTWhoaMBTTz2F2tpaTJ48GRs2bOhluEYAbZ1mbC9qAADcO0f6bDfgMFg7XNUKq42X1ejjcGUrXt50Bt+fFs4xJz5MMhntqPgw7C1vRlGdfIE3k5mnx2i9/nfMS43A2iM1OCpRnXdrpwk///gQzFYei/OS8PiCMZK8rqdMTovE3rJmFGRFIzfBvRHaxblxSIkMwbnWLnxzrMZtj+VP91XgbFMnYsPUWD7bO9+ZocIy3ser9eLC6/mlExGpFTYH3rpjGm5YtRvbzjRg7t++h9XGI1ilwK+uGI3ls7OoLpogCCLAiLcH3l8frsbXh6tdnvNm95OAhOeBEycc/yYIGfFK4D1//nzwbj7MaWlp+OGHHwb8/YyMDKxfv77fY+bOnYtDhw71e8zDDz+Mhx9+eMD3O9/ZU9YEGy+0csrw0gU6Jz4MYWoVOowWnKlr93o9LwDUtnXjyS+PYtNJoWxBqeBw/dRU/FJCEyxWu15U7/1e14zyJnt9txdl5gwpM948z+P3Xx5DfbsR2XGh+Nv1k6CQ2Wl1+ewstHaacN+c7D6PUSg43DQ9DS9tPIOP91b2Crzbusx4ZZMgk//55TledWIfClmxoeA4ISsPCJL6y8c5NhwnpETgxRsn4WcfHYTVxmNqeiReuH6S2IqMIAiCCCwuGROH5O0amKw8YsOCERMWjJhQNcYn6/pswUgQhPz414qR8Am7SpoAABd60cVYqeAwKS0CO4ubcKiiVZbA+7E1h7GjuBEKDrhuSip+fnmO5BsLzGBNTmfz0gYh8PZmfTeDBd7nWrvQbDANS1L91eFqrDtSA6WCw8s3TkZIsDTt6gZDgk6DF66fNOBxN0xLxSubzmBvWTOK6ztcgtKXN55Bk8GEUXGhuHm6PDL5waAJUiI1KgSVzV1I0Knx1NXjex2zaGIS3rpjGvRdZlw7JYVazRAEQQQwo+LCsOuJy309DIIgBoA0hQR2i4F3330ipUBOg7VtZxqwo7gRQUoOax+ZgxdvnOSVbD4LyMqbOsUMo7cRHc1lCLx1miDxfYaT9a5p68L/fXkMAPDzy3JFh3F/JSkiBJeNjQcgyMoZJ2v0+PfucgDAH66ZgGCVf15CLxkdh2CVAi9cPwkRIe47FFwxPgHL8lMp6CYIgiAIgpAB/1w1ErLR0G7E6TpBJj0z27t9e5nB2kEvB942G48/f2Nv8zQzE+OTvZddT9RpEKZW2Z3GDV57H2fkDLwBYCKTm1e1Dun3bTYej605DL3dvOuhS0dJODrvwbLZnx88B6PFCp7n8fRXx2HjgUUTEzE717sbVcPhuSUTsP/JebK4xRMEQRAEQRADQ4H3ec6PpUK2e1ySzuvOzMxgraTBgLZOs9fe56vD1ThRo0e4WoWHL/NumyeO48Sstxxyc6PFiqoWwYVTrsA7L3V4dd7v7y7HzuImaIIUePnGSQFj3jV3TBwSdGo0G0zYeKIOXx2uxt6yZmiCFPj94t7ybX+C4zjoNO4z3QRBEARBEIT8BMYKmOiXLpMVLQbTkH5XjvpuRnRosNgXunCI2dOBMFqs+Ju9zdODc0fJ0uaJBd5yOJtXNnfCxgOhwUqvtH1zh2iwNgRn87YuM/6yQVAf/G7ROGTHBY6Bl0qpwE3T0gAA7+4sx5/WnQQAPHxpDvWJJgiCIIhAhOOAjAzhIVGHG4LwFAq8A5yVW4txwdMb8NqWoiH9/u6SRgDyBN6AI+vtrTrvD3+sQFVLF+LD1bjnInnaPMnpbF5iN1bLiguVrCXaQFyQrAPHAdVt3WjsMA7qd787Xotusw258WG4fWaGl0boPW6cngaOAw6cbUF9uxEZMVrc248jOkEQBEEQfoxWC5SXCw+t1tejIc4zKPAOcJIiNLDxQ8tGVrd2obypE0oFhxlZ0V4YXW8cdd6tkr+2vtuMN+wbEI9eMVo212w5nc03HKsFAExMifT6ezHCh2Gwtu5oDQDg6knJsm0USElqlBZzch110k9fPR6aIPnd2AmCIAiCIIjAhgLvAIfV3x6v1sNiHZyrNnMzn5gSgXCZ6kHzM4SM94HyZpgHOd6B+OcPJWjpNGNUXChuyE8d+BckIjc+HABQ2mgY9BwMhhaDSQxkb5qe5rX3cUeeXW5+bBAbPC0GE3YUCYqKxXlJXhmXHCyfLSgnrrwgEZeNTRjgaIIgCIIgCILoDQXeAU52bBhCg5XoMltFGbKnyFnfzRiXKJi4GUxWHJIw663vNuNfO8oAAI9fOVZWA6+UyBBoghQwWWwo8mLW+/ODVTBZbBifpMMk+4aLXLA67yM9Mt6tnSZ8c7QGVhvf63e+O1ELi43HuCQdRgVQbXdPLhkdh+2PX4rXb53i66EQBEEQBDEcurqA6dOFR1eXr0dDnGdQ4B3gKBScGBQdHoRhGc/zTvXd8rVFUig4MdDfUdQg2ev+WNKEbrMNmTFazB8vb1ZSoeBEOfIneysGOHpo8DyP/9hf+9aCdNll23mpkQCAY06Bd2unCdev2o2ffnQQb24r7fU7a48I2fmrAjjbzUiL1iIoQNzYCYIgCILoA5sN2L9feNi8p1IkCHfQSnIEILZ7GoQM+GxTJ6rbuhGk5ET5t1zMsfc/3l7cKNlrsuz97NxYn9QS3zkrEwDw2YEqtHdL3yptT1kzShsM0AYrsWRysuSvPxDMYK2mrRsN7UZ0m6249/39Yl37W9tL0WmyiMc3dRjFORkJgTdBEARBEARBDAcKvEcAE+3ZyJ4y4P5gQdGU9CjZTMgYs+3Z4cOVrdBLFKTusmfvL5Ixe+/MRTkxGBUXCoPJii8OnpP89T/aI2S7l0xOka0e35lQtUqUixdWtuKRjw9h/9kWhGtUSIrQoNlgwsd7K8XjNxyvhdXGY2JKBDJi5Ok3ThAEQRAEQRD+CgXeIwBW73uyRg+TxTPZzC6Z24g5kxIZguzYUNh4h8HbcKhv78aZug5wHDAzW/7zAQCO43DnhZkAgPd3l8PmpubZaLGitXPw/dabOozYcEyQbd9WkD6scQ6HifaSht/99yg2nqhDsEqBt+6Yhp9fngsAeHNbCYwWKwBg7WFhvIFsqkYQBEEQBEEQUkGB9wggPVoLnUYFk8WGM3W9e0n/ce0JXPTnLXj26xMoqmu313czYzXfZIhn2+XmzPV6OLBzGZ+kQ1Ro8LBfb6gsnZqKMLUKpQ0G7CxxPa8OowXXrdyFC/+8BeWNgzPB++xAFcxWHnmpEWI9vy9ggXdDuxEcB7x602TMzI7B0qkpSNRpUKc34rMDVahv78aeMmFOFk+kwJsgCIIgCIIgKPAeAXAcJ5pfHelR512v78Y7O8twrrUL7+wswxUvb8Pi13agyWCCJkiByWmR8g8YwOwce+Dtps67Xt+NK1/Zhme/PuHRa+0qlt+d3R1hahWut7cxe39Xufhzm43Hik8LcaJGj06TFf/efdbj17TZeHzMTNVm+C7bDTi8BADg2SUTsNAeVKtVSjxwSTYA4B/fl2Dt4RrYeGBSWiTSorU+GStBEARBEARB+BMUeI8QRIO1c60uP//i0DnYeGB0Qhjmj0+AUsHhRI0eADA9MxrBKt98BGaOioFSwaGs0YCqlk6X517bUoRTte14f3c5mg0DS7N3ldpl8zm+yd47c/usDADA5lP1qGgSzuvVzUX47kQdmOfbmgOVLkZk/bG7tAnlTZ0IU6tw9ST5TdWcmZoehQcuycafl07E7TMzXJ67eXo6YkKDUdXShRe/Ow0AuJpk5gRBEARB+BuxscKDIGRG5esBENLAAm/njDfP81izXzC8uueiLNw8Ix31+m58drAKu0ua8MhluT4ZKwDoNEGYnBaJA2dbsKOoETfbs7lVLZ34dJ8wZquNx7fHa3FLP5neyuZOVDZ3QaXgMCMzWpax98eouDDMyY3F9qJGfLjnLKamR+LVzUUAgL8sy8PKrcU429SJrwqrxXNmdJmsWLm1GEX17TBbeZitNpTae7NfNyUFoWrffl0VCg5PLBzn9rmQYCXunZONv2w4BYNJqPNeRDJzgiAIgiD8idBQoEG6drYEMRgo4z1CYM7mp2vb0W0WAp/CylaUNBigCVKIJlfxOg1+NjcHHywvwIws3waqF+X0biv2+uZimK08gu09k9cfren3NXbaf3dyWqTPA1PGXXaTtY/3VmDF6sMAhI2PG6el4ScFQqb437vPguddDdieW3cCb2wtxrfH67DlVD22FzXiXGsXFBxw20zfysw94Scz06HTCHOQnxGF5MgQH4+IIAiCIAiCIPwDCrxHCMkRGsSEBsNi43HSLiVfc6AKALBwQpJPWlANBOvnvau4ETYbj/JGAz47KIz5z8smCs+VNPUrN2dt0fxBZs6YOyYe6dFatHdb0Gmy4qKcGPxu0VgAwA3TUqFWKXCiRo+DFa3i72w4Vov/7KkAxwG/XjAGL1yfh1dumow3bp2Crx6ejbGJOh+djeeEa4Lwi3mjAQB3zMoY4GiCIAiCIAiCOH+gwHuEIBissTrvNnSbrfj6cDUA4Aa74Ze/MTktEmFqFVo6zThercerm4tgtfG4dEwclk5NxfgkHaw2Ht8dr3X7+zzPOwJvHxurOaNUcGLgmR6txRu3TIXKnsGP1AbjGnut9oc/CiZrtW3d+O0XRwAA91+cjYcuzcGN09Jw7ZQUXJWX7FMn88GyfHYWjjwzH0smp/h6KARBEARBEK50dQFz5wqPri5fj4Y4z5A88H7mmWfAcZzLY+zYseLz3d3deOihhxATE4OwsDAsW7YMdXV1Lq9RUVGBxYsXQ6vVIj4+Hr/+9a9hsbiaUX3//feYOnUq1Go1cnJy8N577/Uay8qVK5GZmQmNRoOCggLs3btX6tP1K5jc/HBlG749Xov2bgtSo0J81tt6IIKUCszMFuTu7+4qw5eF5wAAK64YA8DRA3pdH3LzovoONHYYoQlSYEp6pPcHPAjuujATf70+D6sfmNWrxRkzYFt3pAYN7UasWF2I1k4zJqZE4Ff2cw9kdH6oriAIgiAIgoDNBvzwg/Cw2Xw9GuI8wysZ7wsuuAA1NTXiY8eOHeJzjz76KL7++musWbMGP/zwA6qrq7F06VLxeavVisWLF8NkMmHXrl14//338d577+Gpp54SjykrK8PixYtx6aWXorCwEL/85S9x77334ttvvxWP+fTTT7FixQo8/fTTOHjwICZNmoQFCxagvr7eG6fsF+SlOJzN1+wXJNvLpqZCoeB8Oax+YW3Fvjh4DjwPzB+fgIn2zD0z5+pLbs7qu6dnRkOtUso0Ys9QKRW4YVoaEiM0vZ7LS43EpLRImKw2/OTtPdhV0oSQICVeuXmyz1zmCYIgCIIgCILwHl5Z5atUKiQmJoqPWLtlf1tbG/71r3/hpZdewmWXXYb8/Hy8++672LVrF3788UcAwHfffYcTJ07gww8/xOTJk7Fw4UI899xzWLlyJUwmIfhatWoVsrKy8OKLL2LcuHF4+OGHcf311+Pll18Wx/DSSy/hvvvuw913343x48dj1apV0Gq1eOedd7xxyn4Bk5oX1XdgZ4kQlF7vpzJzxuzcOPHfHAesmD9a/P+s2NB+5eYOmbn/1Hd7CmvHdbquHQDwzDXjMSouzJdDIgiCIAiCIAjCS3gl8C4qKkJycjKys7Nx2223oaKiAgBw4MABmM1mzJs3Tzx27NixSE9Px+7duwEAu3fvxsSJE5GQkCAes2DBAuj1ehw/flw8xvk12DHsNUwmEw4cOOByjEKhwLx588Rj3GE0GqHX610egUS8ToNEnQY8D/A8MDM7GmnRWl8Pq19GxYUiyZ4VXjwxqZeJWF9yc4vVhh9L/a++21OuyktCpFaQZC+ckIgbp6X5eEQEQRAEQRAEQXgLyQPvgoICvPfee9iwYQP+8Y9/oKysDHPmzEF7eztqa2sRHByMyMhIl99JSEhAba2Q0aytrXUJutnz7Ln+jtHr9ejq6kJjYyOsVqvbY9hruOP5559HRESE+EhLC7xgiMm0AeCGfP8fP8dxeOjSHExOi8Rvrhzb63lnuXmLk9z8WLUe7d0W6DSqgDIfY2iClPjLsjzcMiMNf16aB47z33IAgiAIgiAIgiCGh+SNjxcuXCj+Oy8vDwUFBcjIyMDq1asREuLffX2feOIJrFixQvx/vV4fcMF3XkoENp6oQ5hahYUTE309HI/4ycwM/GSm+/ZTTG5+okaPb4/X4rJx8Xh/Vzk+2C04gs/MjoHSj2vY+2PBBYlYcEFgzBFBEARBEARBEEPH605OkZGRGD16NIqLi5GYmAiTyYTW1laXY+rq6pCYKAQgiYmJvVzO2f8PdIxOp0NISAhiY2OhVCrdHsNewx1qtRo6nc7lEWgsyktCTGgwHrg4G9pgyfdVfAKTm7+48Qxm/3krVm4tgb7bgqzYUPx6QeC7gBMEQRAEQRAyodUKD4KQGa8H3h0dHSgpKUFSUhLy8/MRFBSEzZs3i8+fPn0aFRUVmDVrFgBg1qxZOHr0qIv7+MaNG6HT6TB+/HjxGOfXYMew1wgODkZ+fr7LMTabDZs3bxaPGamMigvDgf+7Ao9cnuvroUgGk5s3tBthstowNT0Sq36Sj00rLkFuQriPR0cQBEEQBEEEBKGhgMEgPEJDfT0a4jxD8pToY489hquvvhoZGRmorq7G008/DaVSiVtuuQURERFYvnw5VqxYgejoaOh0OjzyyCOYNWsWZs6cCQCYP38+xo8fj9tvvx0vvPACamtr8eSTT+Khhx6CWq0GADz44IN444038Pjjj+Oee+7Bli1bsHr1aqxbt04cx4oVK3DnnXdi2rRpmDFjBl555RUYDAbcfffdUp8y4WWyYkPxy3m5KGs04PaZGZiWGe3rIREEQRAEQRAEQXiM5IF3VVUVbrnlFjQ1NSEuLg6zZ8/Gjz/+iLg4oW3Uyy+/DIVCgWXLlsFoNGLBggX4+9//Lv6+UqnE2rVr8dOf/hSzZs1CaGgo7rzzTjz77LPiMVlZWVi3bh0effRRvPrqq0hNTcXbb7+NBQsWiMfcdNNNaGhowFNPPYXa2lpMnjwZGzZs6GW4RgQGv5w3euCDCIIgCIIgCIIg/BCO53ne14PwV/R6PSIiItDW1haQ9d4EQRAEQRAEQdjp7gaWLRP+/fnngEbj2/EQAc9g4sWR4b5FEARBEARBEATRH1YrsH69498EISNeN1cjCIIgCIIgCIIgiPMZCrwJgiAIgiAIgiAIwotQ4E0QBEEQBEEQBEEQXoQCb4IgCIIgCIIgCILwIhR4EwRBEARBEARBEIQXIVfzfmCd1vR6vY9HQhAEQRAEQRDEsDAYHP/W68nZnBg2LE70pEM3Bd790N7eDgBIS0vz8UgIgiAIgiAIgpCM5GRfj4AYQbS3tyMiIqLfYzjek/D8PMVms6G6uhrh4eHgOM7Xwxmx6PV6pKWlobKycsDG84RvobkKDGieAgeaq8CA5ilwoLkKDGieAgeaq/7heR7t7e1ITk6GQtF/FTdlvPtBoVAgNTXV18M4b9DpdPSFDhBorgIDmqfAgeYqMKB5ChxorgIDmqfAgeaqbwbKdDPIXI0gCIIgCIIgCIIgvAgF3gRBEARBEARBEAThRSjwJnyOWq3G008/DbVa7euhEANAcxUY0DwFDjRXgQHNU+BAcxUY0DwFDjRX0kHmagRBEARBEARBEAThRSjjTRAEQRAEQRAEQRBehAJvgiAIgiAIgiAIgvAiFHgTBEEQBEEQBEEQhBehwJsgCIIgCIIgCIIgvAgF3oQkbNu2DVdffTWSk5PBcRy+/PJLl+fr6upw1113ITk5GVqtFldeeSWKiopcjqmtrcXtt9+OxMREhIaGYurUqfj8889djmlubsZtt90GnU6HyMhILF++HB0dHd4+vRGFHHNVXl6O5cuXIysrCyEhIRg1ahSefvppmEwmOU5xRCDXd4phNBoxefJkcByHwsJCL53VyETOuVq3bh0KCgoQEhKCqKgoXHvttV48s5GFXPN05swZLFmyBLGxsdDpdJg9eza2bt3q7dMbUUgxVyUlJbjuuusQFxcHnU6HG2+8EXV1dS7H0JpieMgxT7SekAa5vlMMWlO4hwJvQhIMBgMmTZqElStX9nqO53lce+21KC0txf/+9z8cOnQIGRkZmDdvHgwGg3jcHXfcgdOnT+Orr77C0aNHsXTpUtx44404dOiQeMxtt92G48ePY+PGjVi7di22bduG+++/X5ZzHCnIMVenTp2CzWbDP//5Txw/fhwvv/wyVq1ahd/97neynWegI9d3ivH4448jOTnZq+c0UpFrrj7//HPcfvvtuPvuu3H48GHs3LkTt956qyznOBKQa56uuuoqWCwWbNmyBQcOHMCkSZNw1VVXoba2VpbzHAkMd64MBgPmz58PjuOwZcsW7Ny5EyaTCVdffTVsNpv4WrSmGB5yzBOtJ6RBru8Ug9YUfcAThMQA4P/73/+K/3/69GkeAH/s2DHxZ1arlY+Li+Pfeust8WehoaH8v//9b5fXio6OFo85ceIED4Dft2+f+Pw333zDcxzHnzt3zktnM7Lx1ly544UXXuCzsrKkG/x5hLfnaf369fzYsWP548eP8wD4Q4cOeeU8zge8NVdms5lPSUnh3377be+ewHmCt+apoaGBB8Bv27ZNfF6v1/MA+I0bN3rpbEY2Q5mrb7/9llcoFHxbW5t4TGtrK89xnDgPtKaQFm/NkztoPTE8vD1XtKboG8p4E17HaDQCADQajfgzhUIBtVqNHTt2iD+78MIL8emnn6K5uRk2mw2ffPIJuru7MXfuXADA7t27ERkZiWnTpom/M2/ePCgUCuzZs0eekxnhSDVX7mhra0N0dLTXxn4+IeU81dXV4b777sMHH3wArVYr2zmcL0g1VwcPHsS5c+egUCgwZcoUJCUlYeHChTh27Jis5zNSkWqeYmJiMGbMGPz73/+GwWCAxWLBP//5T8THxyM/P1/WcxqpeDJXRqMRHMdBrVaLx2g0GigUCvEYWlN4F6nmyR20npAWKeeK1hT9Q4E34XXGjh2L9PR0PPHEE2hpaYHJZMJf/vIXVFVVoaamRjxu9erVMJvNiImJgVqtxgMPPID//ve/yMnJASDU1sXHx7u8tkqlQnR0NEn4JEKquepJcXExXn/9dTzwwANyncqIRqp54nked911Fx588EGXxSchHVLNVWlpKQDgmWeewZNPPom1a9ciKioKc+fORXNzs0/ObSQh1TxxHIdNmzbh0KFDCA8Ph0ajwUsvvYQNGzYgKirKV6c3ovBkrmbOnInQ0FD85je/QWdnJwwGAx577DFYrVbxGFpTeBep5qkntJ6QHqnmitYUA0OBN+F1goKC8MUXX+DMmTOIjo6GVqvF1q1bsXDhQigUjo/g//3f/6G1tRWbNm3C/v37sWLFCtx44404evSoD0d/fuGNuTp37hyuvPJK3HDDDbjvvvvkPJ0Ri1Tz9Prrr6O9vR1PPPGEr05lxCPVXLEaut///vdYtmwZ8vPz8e6774LjOKxZs8Yn5zaSkGqeeJ7HQw89hPj4eGzfvh179+7Ftddei6uvvrrPQIIYHJ7MVVxcHNasWYOvv/4aYWFhiIiIQGtrK6ZOneoyn4T38MY80XrCO0g1V7Sm8AAfS92JEQh61I4409raytfX1/M8z/MzZszgf/azn/E8z/PFxcW96kt4nucvv/xy/oEHHuB5nuf/9a9/8ZGRkS7Pm81mXqlU8l988YXEZ3F+4K25Ypw7d47Pzc3lb7/9dt5qtUp/AucJ3pqnJUuW8AqFglcqleIDAK9UKvk77rjDeyc0gvHWXG3ZsoUHwG/fvt3lmBkzZvC/+93vJD6LkY+35mnTpk296iB5nudzcnL4559/XuKzOD8Yylw509DQwLe0tPA8z/MJCQn8Cy+8wPM8rSmkxlvzxKD1hHR4a65oTTEwtO1HyEpERATi4uJQVFSE/fv3Y8mSJQCAzs5OAOi1w6lUKsVMz6xZs9Da2ooDBw6Iz2/ZsgU2mw0FBQUyncH5w3DmChB2pufOnStm5ijL4B2GM0+vvfYaDh8+jMLCQhQWFmL9+vUAgE8//RR/+tOfZDyL84PhzFV+fj7UajVOnz4tPm82m1FeXo6MjAyZzuD8YDjz1NcxCoXCrfMvMTz6mitnYmNjERkZiS1btqC+vh7XXHMNAFpTyMlw5gmg9YScDGeuaE3hAb6O/ImRQXt7O3/o0CH+0KFDPAD+pZde4g8dOsSfPXuW53meX716Nb9161a+pKSE//LLL/mMjAx+6dKl4u+bTCY+JyeHnzNnDr9nzx6+uLiY/9vf/sZzHMevW7dOPO7KK6/kp0yZwu/Zs4ffsWMHn5uby99yyy2yn28gI8dcVVVV8Tk5Ofzll1/OV1VV8TU1NeKD8Ay5vlPOlJWVkQPpEJBrrn7xi1/wKSkp/LfffsufOnWKX758OR8fH883NzfLfs6BiBzz1NDQwMfExPBLly7lCwsL+dOnT/OPPfYYHxQUxBcWFvrkvAOR4c4Vz/P8O++8w+/evZsvLi7mP/jgAz46OppfsWKFyzG0phgecswTrSekQa7vlDO0pugNBd6EJGzdupUH0Otx55138jzP86+++iqfmprKBwUF8enp6fyTTz7JG41Gl9c4c+YMv3TpUj4+Pp7XarV8Xl5er7YtTU1N/C233MKHhYXxOp2Ov/vuu/n29na5TnNEIMdcvfvuu27fg/b6PEeu75QzdJMcGnLNlclk4n/1q1/x8fHxfHh4OD9v3rxesmeib+Sap3379vHz58/no6Oj+fDwcH7mzJn8+vXr5TrNEYEUc/Wb3/yGT0hI4IOCgvjc3Fz+xRdf5G02m8sxtKYYHnLME60npEGu75QztKboDcfzPD/8vDlBEARBEARBEARBEO6gIgmCIAiCIAiCIAiC8CIUeBMEQRAEQRAEQRCEF6HAmyAIgiAIgiAIgiC8CAXeBEEQBEEQBEEQBOFFKPAmCIIgCIIgCIIgCC9CgTdBEARBEARBEARBeBEKvAmCIAiCIAiCIAjCi1DgTRAEQRAEQRAEQRBehAJvgiAIgiAIgiAIgvAiFHgTBEEQBEEQBEEQhBehwJsgCIIgCIIgCIIgvAgF3gRBEARBEARBEAThRf4/r1LRA1c/fkwAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 1000x600 with 2 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from tabpfn_time_series.plot import plot_actual_ts\n",
+    "\n",
+    "plot_actual_ts(train_tsdf, test_tsdf_ground_truth)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "UWmQq17tHS_4"
+   },
+   "source": [
+    "## Adding Features\n",
+    "\n",
+    "In our paper, we propose adding `Running Index`, `Calendar Features`, and `Auto Seasonal Features` to the table.\n",
+    "\n",
+    "**Feel free to experiment with your own features!**\n",
+    "\n",
+    "To do that, simply define your own feature functions and pass them to the `FeatureTransformer`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "jKWF7CrmHS_5"
+   },
+   "outputs": [],
+   "source": [
+    "from tabpfn_time_series import FeatureTransformer\n",
+    "from tabpfn_time_series.features import (\n",
+    "    AutoSeasonalFeature,\n",
+    "    CalendarFeature,\n",
+    "    RunningIndexFeature,\n",
+    ")\n",
+    "\n",
+    "selected_features = [\n",
+    "    RunningIndexFeature(),\n",
+    "    CalendarFeature(),\n",
+    "    AutoSeasonalFeature(),\n",
+    "]\n",
+    "\n",
+    "feature_transformer = FeatureTransformer(selected_features)\n",
+    "\n",
+    "train_tsdf, test_tsdf = feature_transformer.transform(train_tsdf, test_tsdf)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "N9WZ46ywJylH"
+   },
+   "source": [
+    "Let's take a look at the tables (train and test) before we proceed to do predictions.\n",
+    "\n",
+    "✅ Realize that we have added some features into the tables."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "tnKwZbngJx0X",
+    "outputId": "1ea42799-8360-42d5-e1f6-648340baabca"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "toHiW8LeHS_5"
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "type": "dataframe",
+       "variable_name": "train_tsdf"
       },
-      "source": [
-        "## Visualize the Results\n",
-        "\n",
-        "Let's visualize the forecasting results.\n",
-        "\n",
-        "Also, note that we provide both **point prediction** and **quantile prediction**, how amazing! 😄"
+      "text/html": [
+       "\n",
+       "  <div id=\"df-99cec216-cf7f-44bf-ae5a-72a21d117994\" class=\"colab-df-container\">\n",
+       "    <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>target</th>\n",
+       "      <th>running_index</th>\n",
+       "      <th>year</th>\n",
+       "      <th>second_of_minute_sin</th>\n",
+       "      <th>second_of_minute_cos</th>\n",
+       "      <th>minute_of_hour_sin</th>\n",
+       "      <th>minute_of_hour_cos</th>\n",
+       "      <th>hour_of_day_sin</th>\n",
+       "      <th>hour_of_day_cos</th>\n",
+       "      <th>day_of_week_sin</th>\n",
+       "      <th>...</th>\n",
+       "      <th>sin_#0</th>\n",
+       "      <th>cos_#0</th>\n",
+       "      <th>sin_#1</th>\n",
+       "      <th>cos_#1</th>\n",
+       "      <th>sin_#2</th>\n",
+       "      <th>cos_#2</th>\n",
+       "      <th>sin_#3</th>\n",
+       "      <th>cos_#3</th>\n",
+       "      <th>sin_#4</th>\n",
+       "      <th>cos_#4</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>item_id</th>\n",
+       "      <th>timestamp</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
+       "      <th>1979-01-31</th>\n",
+       "      <td>1149.8700</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1979-02-28</th>\n",
+       "      <td>1053.8002</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>6.123234e-17</td>\n",
+       "      <td>1.224647e-16</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1979-03-31</th>\n",
+       "      <td>1388.8798</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.866025</td>\n",
+       "      <td>5.000000e-01</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>1.224647e-16</td>\n",
+       "      <td>-1.000000e+00</td>\n",
+       "      <td>-2.449294e-16</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1979-04-30</th>\n",
+       "      <td>1783.3702</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>6.123234e-17</td>\n",
+       "      <td>1.224647e-16</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1.000000e+00</td>\n",
+       "      <td>-1.836970e-16</td>\n",
+       "      <td>3.673940e-16</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-2.449294e-16</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1979-05-31</th>\n",
+       "      <td>1921.0252</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.224647e-16</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.866025</td>\n",
+       "      <td>-5.000000e-01</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>-2.449294e-16</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>-4.898587e-16</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 29 columns</p>\n",
+       "</div>\n",
+       "    <div class=\"colab-df-buttons\">\n",
+       "\n",
+       "  <div class=\"colab-df-container\">\n",
+       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-99cec216-cf7f-44bf-ae5a-72a21d117994')\"\n",
+       "            title=\"Convert this dataframe to an interactive table.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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+       "  </svg>\n",
+       "    </button>\n",
+       "\n",
+       "  <style>\n",
+       "    .colab-df-container {\n",
+       "      display:flex;\n",
+       "      gap: 12px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert {\n",
+       "      background-color: #E8F0FE;\n",
+       "      border: none;\n",
+       "      border-radius: 50%;\n",
+       "      cursor: pointer;\n",
+       "      display: none;\n",
+       "      fill: #1967D2;\n",
+       "      height: 32px;\n",
+       "      padding: 0 0 0 0;\n",
+       "      width: 32px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert:hover {\n",
+       "      background-color: #E2EBFA;\n",
+       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "      fill: #174EA6;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-buttons div {\n",
+       "      margin-bottom: 4px;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert {\n",
+       "      background-color: #3B4455;\n",
+       "      fill: #D2E3FC;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert:hover {\n",
+       "      background-color: #434B5C;\n",
+       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "      fill: #FFFFFF;\n",
+       "    }\n",
+       "  </style>\n",
+       "\n",
+       "    <script>\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#df-99cec216-cf7f-44bf-ae5a-72a21d117994 button.colab-df-convert');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      async function convertToInteractive(key) {\n",
+       "        const element = document.querySelector('#df-99cec216-cf7f-44bf-ae5a-72a21d117994');\n",
+       "        const dataTable =\n",
+       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+       "                                                    [key], {});\n",
+       "        if (!dataTable) return;\n",
+       "\n",
+       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+       "          + ' to learn more about interactive tables.';\n",
+       "        element.innerHTML = '';\n",
+       "        dataTable['output_type'] = 'display_data';\n",
+       "        await google.colab.output.renderOutput(dataTable, element);\n",
+       "        const docLink = document.createElement('div');\n",
+       "        docLink.innerHTML = docLinkHtml;\n",
+       "        element.appendChild(docLink);\n",
+       "      }\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "\n",
+       "    <div id=\"df-7fe1f8e8-4e45-46b1-9769-44b88ccd2a71\">\n",
+       "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7fe1f8e8-4e45-46b1-9769-44b88ccd2a71')\"\n",
+       "                title=\"Suggest charts\"\n",
+       "                style=\"display:none;\">\n",
+       "\n",
+       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "     width=\"24px\">\n",
+       "    <g>\n",
+       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+       "    </g>\n",
+       "</svg>\n",
+       "      </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
+       "      --hover-fill-color: #174EA6;\n",
+       "      --disabled-fill-color: #AAA;\n",
+       "      --disabled-bg-color: #DDD;\n",
+       "  }\n",
+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
+       "      --hover-bg-color: #434B5C;\n",
+       "      --hover-fill-color: #FFFFFF;\n",
+       "      --disabled-bg-color: #3B4455;\n",
+       "      --disabled-fill-color: #666;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart {\n",
+       "    background-color: var(--bg-color);\n",
+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
+       "    display: none;\n",
+       "    fill: var(--fill-color);\n",
+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    30% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "      <script>\n",
+       "        async function quickchart(key) {\n",
+       "          const quickchartButtonEl =\n",
+       "            document.querySelector('#' + key + ' button');\n",
+       "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "          try {\n",
+       "            const charts = await google.colab.kernel.invokeFunction(\n",
+       "                'suggestCharts', [key], {});\n",
+       "          } catch (error) {\n",
+       "            console.error('Error during call to suggestCharts:', error);\n",
+       "          }\n",
+       "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "        }\n",
+       "        (() => {\n",
+       "          let quickchartButtonEl =\n",
+       "            document.querySelector('#df-7fe1f8e8-4e45-46b1-9769-44b88ccd2a71 button');\n",
+       "          quickchartButtonEl.style.display =\n",
+       "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "        })();\n",
+       "      </script>\n",
+       "    </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
+      ],
+      "text/plain": [
+       "                       target  running_index  year  second_of_minute_sin  \\\n",
+       "item_id timestamp                                                          \n",
+       "0       1979-01-31  1149.8700              0  1979                   0.0   \n",
+       "        1979-02-28  1053.8002              1  1979                   0.0   \n",
+       "        1979-03-31  1388.8798              2  1979                   0.0   \n",
+       "        1979-04-30  1783.3702              3  1979                   0.0   \n",
+       "        1979-05-31  1921.0252              4  1979                   0.0   \n",
+       "\n",
+       "                    second_of_minute_cos  minute_of_hour_sin  \\\n",
+       "item_id timestamp                                              \n",
+       "0       1979-01-31                   1.0                 0.0   \n",
+       "        1979-02-28                   1.0                 0.0   \n",
+       "        1979-03-31                   1.0                 0.0   \n",
+       "        1979-04-30                   1.0                 0.0   \n",
+       "        1979-05-31                   1.0                 0.0   \n",
+       "\n",
+       "                    minute_of_hour_cos  hour_of_day_sin  hour_of_day_cos  \\\n",
+       "item_id timestamp                                                          \n",
+       "0       1979-01-31                 1.0              0.0              1.0   \n",
+       "        1979-02-28                 1.0              0.0              1.0   \n",
+       "        1979-03-31                 1.0              0.0              1.0   \n",
+       "        1979-04-30                 1.0              0.0              1.0   \n",
+       "        1979-05-31                 1.0              0.0              1.0   \n",
+       "\n",
+       "                    day_of_week_sin  ...    sin_#0        cos_#0  \\\n",
+       "item_id timestamp                    ...                           \n",
+       "0       1979-01-31     8.660254e-01  ...  0.000000  1.000000e+00   \n",
+       "        1979-02-28     8.660254e-01  ...  0.500000  8.660254e-01   \n",
+       "        1979-03-31    -8.660254e-01  ...  0.866025  5.000000e-01   \n",
+       "        1979-04-30     0.000000e+00  ...  1.000000  6.123234e-17   \n",
+       "        1979-05-31     1.224647e-16  ...  0.866025 -5.000000e-01   \n",
+       "\n",
+       "                          sin_#1  cos_#1        sin_#2        cos_#2  \\\n",
+       "item_id timestamp                                                      \n",
+       "0       1979-01-31  0.000000e+00     1.0  0.000000e+00  1.000000e+00   \n",
+       "        1979-02-28  8.660254e-01     0.5  1.000000e+00  6.123234e-17   \n",
+       "        1979-03-31  8.660254e-01    -0.5  1.224647e-16 -1.000000e+00   \n",
+       "        1979-04-30  1.224647e-16    -1.0 -1.000000e+00 -1.836970e-16   \n",
+       "        1979-05-31 -8.660254e-01    -0.5 -2.449294e-16  1.000000e+00   \n",
+       "\n",
+       "                          sin_#3  cos_#3        sin_#4  cos_#4  \n",
+       "item_id timestamp                                               \n",
+       "0       1979-01-31  0.000000e+00     1.0  0.000000e+00     1.0  \n",
+       "        1979-02-28  1.224647e-16    -1.0  8.660254e-01    -0.5  \n",
+       "        1979-03-31 -2.449294e-16     1.0 -8.660254e-01    -0.5  \n",
+       "        1979-04-30  3.673940e-16    -1.0 -2.449294e-16     1.0  \n",
+       "        1979-05-31 -4.898587e-16     1.0  8.660254e-01    -0.5  \n",
+       "\n",
+       "[5 rows x 29 columns]"
       ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_tsdf.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "yKaNq3RAKMH9",
+    "outputId": "73791141-2b67-4019-bf3d-d4bf1bde5738"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "FCxt23reHS_5"
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "type": "dataframe",
+       "variable_name": "test_tsdf"
       },
-      "outputs": [],
-      "source": [
-        "from tabpfn_time_series.plot import plot_pred_and_actual_ts\n",
-        "\n",
-        "plot_pred_and_actual_ts(\n",
-        "    train=train_tsdf,\n",
-        "    test=test_tsdf_ground_truth,\n",
-        "    pred=pred,\n",
-        ")"
+      "text/html": [
+       "\n",
+       "  <div id=\"df-80d21b08-9078-44d7-b5b6-5046e14b7c8a\" class=\"colab-df-container\">\n",
+       "    <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>target</th>\n",
+       "      <th>running_index</th>\n",
+       "      <th>year</th>\n",
+       "      <th>second_of_minute_sin</th>\n",
+       "      <th>second_of_minute_cos</th>\n",
+       "      <th>minute_of_hour_sin</th>\n",
+       "      <th>minute_of_hour_cos</th>\n",
+       "      <th>hour_of_day_sin</th>\n",
+       "      <th>hour_of_day_cos</th>\n",
+       "      <th>day_of_week_sin</th>\n",
+       "      <th>...</th>\n",
+       "      <th>sin_#0</th>\n",
+       "      <th>cos_#0</th>\n",
+       "      <th>sin_#1</th>\n",
+       "      <th>cos_#1</th>\n",
+       "      <th>sin_#2</th>\n",
+       "      <th>cos_#2</th>\n",
+       "      <th>sin_#3</th>\n",
+       "      <th>cos_#3</th>\n",
+       "      <th>sin_#4</th>\n",
+       "      <th>cos_#4</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>item_id</th>\n",
+       "      <th>timestamp</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
+       "      <th>1992-08-31</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>163</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.500000</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>-1.000000e+00</td>\n",
+       "      <td>-2.596808e-14</td>\n",
+       "      <td>5.193617e-14</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1992-09-30</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>164</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.866025</td>\n",
+       "      <td>-5.000000e-01</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>-3.135839e-14</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>-6.271677e-14</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1992-10-31</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>165</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-1.000000</td>\n",
+       "      <td>-1.224956e-14</td>\n",
+       "      <td>2.449913e-14</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>3.674869e-14</td>\n",
+       "      <td>7.349738e-14</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-4.899825e-14</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1992-11-30</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>166</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.866025</td>\n",
+       "      <td>5.000000e-01</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "      <td>-1.470443e-14</td>\n",
+       "      <td>-1.000000e+00</td>\n",
+       "      <td>2.940885e-14</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1992-12-31</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>167</td>\n",
+       "      <td>1992</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.224647e-16</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.500000</td>\n",
+       "      <td>8.660254e-01</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>-1.000000e+00</td>\n",
+       "      <td>9.314124e-15</td>\n",
+       "      <td>-1.862825e-14</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-8.660254e-01</td>\n",
+       "      <td>-0.5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 29 columns</p>\n",
+       "</div>\n",
+       "    <div class=\"colab-df-buttons\">\n",
+       "\n",
+       "  <div class=\"colab-df-container\">\n",
+       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-80d21b08-9078-44d7-b5b6-5046e14b7c8a')\"\n",
+       "            title=\"Convert this dataframe to an interactive table.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+       "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+       "  </svg>\n",
+       "    </button>\n",
+       "\n",
+       "  <style>\n",
+       "    .colab-df-container {\n",
+       "      display:flex;\n",
+       "      gap: 12px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert {\n",
+       "      background-color: #E8F0FE;\n",
+       "      border: none;\n",
+       "      border-radius: 50%;\n",
+       "      cursor: pointer;\n",
+       "      display: none;\n",
+       "      fill: #1967D2;\n",
+       "      height: 32px;\n",
+       "      padding: 0 0 0 0;\n",
+       "      width: 32px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert:hover {\n",
+       "      background-color: #E2EBFA;\n",
+       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "      fill: #174EA6;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-buttons div {\n",
+       "      margin-bottom: 4px;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert {\n",
+       "      background-color: #3B4455;\n",
+       "      fill: #D2E3FC;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert:hover {\n",
+       "      background-color: #434B5C;\n",
+       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "      fill: #FFFFFF;\n",
+       "    }\n",
+       "  </style>\n",
+       "\n",
+       "    <script>\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#df-80d21b08-9078-44d7-b5b6-5046e14b7c8a button.colab-df-convert');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      async function convertToInteractive(key) {\n",
+       "        const element = document.querySelector('#df-80d21b08-9078-44d7-b5b6-5046e14b7c8a');\n",
+       "        const dataTable =\n",
+       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+       "                                                    [key], {});\n",
+       "        if (!dataTable) return;\n",
+       "\n",
+       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+       "          + ' to learn more about interactive tables.';\n",
+       "        element.innerHTML = '';\n",
+       "        dataTable['output_type'] = 'display_data';\n",
+       "        await google.colab.output.renderOutput(dataTable, element);\n",
+       "        const docLink = document.createElement('div');\n",
+       "        docLink.innerHTML = docLinkHtml;\n",
+       "        element.appendChild(docLink);\n",
+       "      }\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "\n",
+       "    <div id=\"df-628d6697-813b-467d-b311-55143ccd38c1\">\n",
+       "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-628d6697-813b-467d-b311-55143ccd38c1')\"\n",
+       "                title=\"Suggest charts\"\n",
+       "                style=\"display:none;\">\n",
+       "\n",
+       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "     width=\"24px\">\n",
+       "    <g>\n",
+       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+       "    </g>\n",
+       "</svg>\n",
+       "      </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
+       "      --hover-fill-color: #174EA6;\n",
+       "      --disabled-fill-color: #AAA;\n",
+       "      --disabled-bg-color: #DDD;\n",
+       "  }\n",
+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
+       "      --hover-bg-color: #434B5C;\n",
+       "      --hover-fill-color: #FFFFFF;\n",
+       "      --disabled-bg-color: #3B4455;\n",
+       "      --disabled-fill-color: #666;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart {\n",
+       "    background-color: var(--bg-color);\n",
+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
+       "    display: none;\n",
+       "    fill: var(--fill-color);\n",
+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    30% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "      <script>\n",
+       "        async function quickchart(key) {\n",
+       "          const quickchartButtonEl =\n",
+       "            document.querySelector('#' + key + ' button');\n",
+       "          quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "          quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "          try {\n",
+       "            const charts = await google.colab.kernel.invokeFunction(\n",
+       "                'suggestCharts', [key], {});\n",
+       "          } catch (error) {\n",
+       "            console.error('Error during call to suggestCharts:', error);\n",
+       "          }\n",
+       "          quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "          quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "        }\n",
+       "        (() => {\n",
+       "          let quickchartButtonEl =\n",
+       "            document.querySelector('#df-628d6697-813b-467d-b311-55143ccd38c1 button');\n",
+       "          quickchartButtonEl.style.display =\n",
+       "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "        })();\n",
+       "      </script>\n",
+       "    </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
+      ],
+      "text/plain": [
+       "                    target  running_index  year  second_of_minute_sin  \\\n",
+       "item_id timestamp                                                       \n",
+       "0       1992-08-31     NaN            163  1992                   0.0   \n",
+       "        1992-09-30     NaN            164  1992                   0.0   \n",
+       "        1992-10-31     NaN            165  1992                   0.0   \n",
+       "        1992-11-30     NaN            166  1992                   0.0   \n",
+       "        1992-12-31     NaN            167  1992                   0.0   \n",
+       "\n",
+       "                    second_of_minute_cos  minute_of_hour_sin  \\\n",
+       "item_id timestamp                                              \n",
+       "0       1992-08-31                   1.0                 0.0   \n",
+       "        1992-09-30                   1.0                 0.0   \n",
+       "        1992-10-31                   1.0                 0.0   \n",
+       "        1992-11-30                   1.0                 0.0   \n",
+       "        1992-12-31                   1.0                 0.0   \n",
+       "\n",
+       "                    minute_of_hour_cos  hour_of_day_sin  hour_of_day_cos  \\\n",
+       "item_id timestamp                                                          \n",
+       "0       1992-08-31                 1.0              0.0              1.0   \n",
+       "        1992-09-30                 1.0              0.0              1.0   \n",
+       "        1992-10-31                 1.0              0.0              1.0   \n",
+       "        1992-11-30                 1.0              0.0              1.0   \n",
+       "        1992-12-31                 1.0              0.0              1.0   \n",
+       "\n",
+       "                    day_of_week_sin  ...    sin_#0        cos_#0  \\\n",
+       "item_id timestamp                    ...                           \n",
+       "0       1992-08-31     0.000000e+00  ... -0.500000 -8.660254e-01   \n",
+       "        1992-09-30     8.660254e-01  ... -0.866025 -5.000000e-01   \n",
+       "        1992-10-31    -8.660254e-01  ... -1.000000 -1.224956e-14   \n",
+       "        1992-11-30     0.000000e+00  ... -0.866025  5.000000e-01   \n",
+       "        1992-12-31     1.224647e-16  ... -0.500000  8.660254e-01   \n",
+       "\n",
+       "                          sin_#1  cos_#1        sin_#2        cos_#2  \\\n",
+       "item_id timestamp                                                      \n",
+       "0       1992-08-31  8.660254e-01     0.5 -1.000000e+00 -2.596808e-14   \n",
+       "        1992-09-30  8.660254e-01    -0.5 -3.135839e-14  1.000000e+00   \n",
+       "        1992-10-31  2.449913e-14    -1.0  1.000000e+00  3.674869e-14   \n",
+       "        1992-11-30 -8.660254e-01    -0.5 -1.470443e-14 -1.000000e+00   \n",
+       "        1992-12-31 -8.660254e-01     0.5 -1.000000e+00  9.314124e-15   \n",
+       "\n",
+       "                          sin_#3  cos_#3        sin_#4  cos_#4  \n",
+       "item_id timestamp                                               \n",
+       "0       1992-08-31  5.193617e-14    -1.0  8.660254e-01    -0.5  \n",
+       "        1992-09-30 -6.271677e-14     1.0 -8.660254e-01    -0.5  \n",
+       "        1992-10-31  7.349738e-14    -1.0 -4.899825e-14     1.0  \n",
+       "        1992-11-30  2.940885e-14     1.0  8.660254e-01    -0.5  \n",
+       "        1992-12-31 -1.862825e-14    -1.0 -8.660254e-01    -0.5  \n",
+       "\n",
+       "[5 rows x 29 columns]"
       ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_tsdf.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "CqNGS6a0HS_5"
+   },
+   "source": [
+    "## Prediction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "iAh9dvY5HS_5"
+   },
+   "source": [
+    "Now, let's perform prediction.\n",
+    "\n",
+    "We provide two options, `TabPFNMode.LOCAL` and `TabPFNMode.CLIENT`, as the backend for TabPFN.\n",
+    "\n",
+    "- `TabPFNMode.LOCAL` uses your local machine to run TabPFN.\n",
+    "- `TabPFNMode.CLIENT` uses TabPFN's inference service provided by [tabpfn-client](https://github.com/automl/tabpfn-client)\n",
+    "\n",
+    "For this demo, we'll use `TabPFNMode.CLIENT` to perform prediction. If you have not used the client before, you'll be prompted to create an account.\n",
+    "\n",
+    "Note: if your machine doesn't have a GPU, using `TabPFNMode.CLIENT` is recommended -- much faster 😉.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 721
     },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "_EJU0ILwHS_5"
-      },
-      "outputs": [],
-      "source": [
-        "pred.head()"
-      ]
+    "collapsed": true,
+    "id": "v_gi5gDFHS_5",
+    "jupyter": {
+     "outputs_hidden": true
     },
+    "outputId": "7c0a617b-7fbb-4534-c392-92ea999c146a"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "source": [
-        "# Using TabPFN as a Base Model for Causal Inference <a name=\"causal\"></a>\n",
-        "\n",
-        "Often decisions hinge on **what changes because of an action**, not just what correlates with it. Causal effect estimation turns data into these counterfactual answers—e.g., _If we treat someone like xxx, how much does the expected outcome change?_\n",
-        "\n",
-        "Below we show how to use TabPFN to estimation the effect of these causal intervations.\n",
-        "\n",
-        "*In depth explanation:*\n",
-        "\n",
-        "To estimate it most methods build two ingredients: an **outcome model** (predict yyy under T\\=1T{=}1T\\=1 and T\\=0T{=}0T\\=0) and often a **propensity model** (estimate Pr⁡(T\\=1∣X)\\\\Pr(T{=}1\\\\mid X)Pr(T\\=1∣X)) to reduce selection bias. You can treat this as AutoML, or take a strong default: **TabPFN**, a pretrained transformer for tabular data that frequently works **out of the box** as the base learner inside CATE pipelines—cutting tuning time while staying competitive.\n",
-        "\n",
-        "\n",
-        "Many causal inference methods require selection of base models to fit either propensity or outcome models. While recent studies have framed this as an AutoML model selection problem ([Vandershueren et al, 2025](https://openreview.net/forum?id=QbOoz74GNO)), other studies ([Zhang et al, 2025](https://arxiv.org/pdf/2505.20003)) have shown TabPFN to be a strong choice \"out of the box\" in various CATE estimation methods. In parallel, there is a growing body of research pre-training PFNs specifically for the conditional average treatment effect (CATE) estimation task ([Robertson et al.](https://arxiv.org/pdf/2506.06039)), defined as:\n",
-        "\n",
-        "$$CATE : \\tau = E[y | do(1), x] - E[y | do(0), x]$$\n",
-        "\n",
-        "\n",
-        "**NOTE:** Current CATE estimators only work when *unconfoundedness* $(Y_0, Y_1) \\perp \\kern-1.8ex \\perp T$ $|$ $X$ is satisfied. We are working on pre-training a foundation model called \"Do-PFN\" ([Robertson et al.](https://arxiv.org/pdf/2506.06039)) that is designed to offer strong out-of-the box performance in **all** identifiable scenarios (including front-door and instrumental variable settings)."
-      ],
-      "metadata": {
-        "id": "0bBYgouXsh2A"
-      }
+     "ename": "AttributeError",
+     "evalue": "'list' object has no attribute 'exists'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "\u001b[0;32m/tmp/ipython-input-1981978721.py\u001b[0m in \u001b[0;36m<cell line: 0>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mtabpfn_time_series\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mTabPFNMode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mTabPFNTimeSeriesPredictor\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m predictor = TabPFNTimeSeriesPredictor(\n\u001b[0m\u001b[1;32m      4\u001b[0m     \u001b[0mtabpfn_mode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mTabPFNMode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLOCAL\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0;31m# adapt this to TabPFNMode.CLIENT if using API\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m )\n",
+      "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/tabpfn_time_series/predictor.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, tabpfn_mode, config)\u001b[0m\n\u001b[1;32m     37\u001b[0m         }\n\u001b[1;32m     38\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtabpfn_mode\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtabpfn_mode\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 39\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtabpfn_worker\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mworker_mapping\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mtabpfn_mode\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     40\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     41\u001b[0m     def predict(\n",
+      "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/tabpfn_time_series/predictor.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     33\u001b[0m         worker_mapping = {\n\u001b[1;32m     34\u001b[0m             \u001b[0mTabPFNMode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCLIENT\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mlambda\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mTabPFNClient\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 35\u001b[0;31m             \u001b[0mTabPFNMode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLOCAL\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mlambda\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mLocalTabPFN\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     36\u001b[0m             \u001b[0mTabPFNMode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mMOCK\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mlambda\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mMockTabPFN\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     37\u001b[0m         }\n",
+      "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/tabpfn_time_series/tabpfn_worker.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, config, num_workers_per_gpu)\u001b[0m\n\u001b[1;32m    240\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    241\u001b[0m         \u001b[0;31m# Download the model specified in the config\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 242\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_download_model\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"tabpfn_internal\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"model_path\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    243\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    244\u001b[0m     def predict(\n",
+      "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/tabpfn_time_series/tabpfn_worker.py\u001b[0m in \u001b[0;36m_download_model\u001b[0;34m(model_name)\u001b[0m\n\u001b[1;32m    288\u001b[0m         )\n\u001b[1;32m    289\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 290\u001b[0;31m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mmodel_path\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexists\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    291\u001b[0m             download_model(\n\u001b[1;32m    292\u001b[0m                 \u001b[0mto\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmodel_path\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mAttributeError\u001b[0m: 'list' object has no attribute 'exists'"
+     ]
+    }
+   ],
+   "source": [
+    "from tabpfn_time_series import TabPFNMode, TabPFNTimeSeriesPredictor\n",
+    "\n",
+    "predictor = TabPFNTimeSeriesPredictor(\n",
+    "    tabpfn_mode=TabPFNMode.LOCAL,  # adapt this to TabPFNMode.CLIENT if using API\n",
+    ")\n",
+    "\n",
+    "pred = predictor.predict(train_tsdf, test_tsdf)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "toHiW8LeHS_5"
+   },
+   "source": [
+    "## Visualize the Results\n",
+    "\n",
+    "Let's visualize the forecasting results.\n",
+    "\n",
+    "Also, note that we provide both **point prediction** and **quantile prediction**."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "FCxt23reHS_5"
+   },
+   "outputs": [],
+   "source": [
+    "from tabpfn_time_series.plot import plot_pred_and_actual_ts\n",
+    "\n",
+    "plot_pred_and_actual_ts(\n",
+    "    train=train_tsdf,\n",
+    "    test=test_tsdf_ground_truth,\n",
+    "    pred=pred,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "_EJU0ILwHS_5"
+   },
+   "outputs": [],
+   "source": [
+    "pred.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "0bBYgouXsh2A"
+   },
+   "source": [
+    "# Using TabPFN as a Base Model for Causal Inference <a name=\"causal\"></a>\n",
+    "\n",
+    "Often decisions hinge on **what changes because of an action**, not just what correlates with it. Causal effect estimation turns data into these counterfactual answers—e.g., _If we treat ($T=1$) someone like $X$, how much does the expected outcome change?_\n",
+    "\n",
+    "Below we show how to use TabPFN to estimation the effect of these causal intervations.\n",
+    "\n",
+    "*In depth explanation:*\n",
+    "\n",
+    "To estimate it most methods build two ingredients: an **outcome model** (predict $y$ under $T=1$ and $T=0$) and often a **propensity model** (estimate $Pr⁡(T=1∣X)$) to reduce selection bias. You can treat this as AutoML, or take a strong default: **TabPFN**, a pretrained transformer for tabular data that frequently works **out of the box** as the base learner inside CATE pipelines—cutting tuning time while staying competitive.\n",
+    "\n",
+    "\n",
+    "Many causal inference methods require selection of base models to fit either propensity or outcome models. While recent studies have framed this as an AutoML model selection problem ([Vandershueren et al, 2025](https://openreview.net/forum?id=QbOoz74GNO)), other studies ([Zhang et al, 2025](https://arxiv.org/pdf/2505.20003)) have shown TabPFN to be a strong choice \"out of the box\" in various CATE estimation methods. In parallel, there is a growing body of research pre-training PFNs specifically for the conditional average treatment effect (CATE) estimation task ([Robertson et al.](https://arxiv.org/pdf/2506.06039)), defined as:\n",
+    "\n",
+    "$$CATE : \\tau = E[y | do(1), x] - E[y | do(0), x]$$\n",
+    "\n",
+    "\n",
+    "**NOTE:** Current CATE estimators only work when *unconfoundedness* $(Y_0, Y_1) \\perp \\kern-1.8ex \\perp T$ $|$ $X$ is satisfied. We are working on pre-training a foundation model called \"Do-PFN\" ([Robertson et al.](https://arxiv.org/pdf/2506.06039)) that is designed to offer strong out-of-the box performance in **all** identifiable scenarios (including front-door and instrumental variable settings)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "yn_gs71ksBfH"
+   },
+   "source": [
+    "### 1) Install the required packages\n",
+    "\n",
+    "Note: you will need to restart the notebook (Runtime -> Restart Session)\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "QNU2S_pwrSq1",
+    "outputId": "94a9eebb-71a1-487f-b5b2-df81930d1182"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "source": [
-        "### 1) Install the required packages\n",
-        "\n",
-        "Note: you will need to restart the notebook (Runtime -> Restart Session)\n",
-        "\n",
-        "\n",
-        "\n"
-      ],
-      "metadata": {
-        "id": "yn_gs71ksBfH"
-      }
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: tabpfn in /usr/local/lib/python3.12/dist-packages (6.0.3)\n",
+      "Requirement already satisfied: torch<3,>=2.1 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (2.8.0+cu126)\n",
+      "Requirement already satisfied: numpy<3,>=1.21.6 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (2.0.2)\n",
+      "Requirement already satisfied: scikit-learn<1.8,>=1.2.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (1.6.1)\n",
+      "Requirement already satisfied: typing_extensions>=4.12.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (4.15.0)\n",
+      "Requirement already satisfied: scipy<2,>=1.11.1 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (1.16.3)\n",
+      "Requirement already satisfied: pandas<3,>=1.4.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (2.2.2)\n",
+      "Requirement already satisfied: einops<0.9,>=0.2.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (0.8.1)\n",
+      "Requirement already satisfied: huggingface-hub<2,>=0.25.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (0.36.0)\n",
+      "Requirement already satisfied: pydantic>=2.8.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (2.11.10)\n",
+      "Requirement already satisfied: pydantic-settings>=2.10.1 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (2.11.0)\n",
+      "Requirement already satisfied: eval-type-backport>=0.2.2 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (0.2.2)\n",
+      "Requirement already satisfied: joblib>=1.2.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (1.5.2)\n",
+      "Requirement already satisfied: tabpfn-common-utils>=0.1.8 in /usr/local/lib/python3.12/dist-packages (from tabpfn-common-utils[telemetry-interactive]>=0.1.8->tabpfn) (0.2.2)\n",
+      "Requirement already satisfied: kditransform>=1.2 in /usr/local/lib/python3.12/dist-packages (from tabpfn) (1.2.0)\n",
+      "Requirement already satisfied: filelock in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (3.20.0)\n",
+      "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (2025.3.0)\n",
+      "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (25.0)\n",
+      "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (6.0.3)\n",
+      "Requirement already satisfied: requests in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (2.32.5)\n",
+      "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (4.67.1)\n",
+      "Requirement already satisfied: hf-xet<2.0.0,>=1.1.3 in /usr/local/lib/python3.12/dist-packages (from huggingface-hub<2,>=0.25.0->tabpfn) (1.2.0)\n",
+      "Requirement already satisfied: numba>=0.48 in /usr/local/lib/python3.12/dist-packages (from kditransform>=1.2->tabpfn) (0.60.0)\n",
+      "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.12/dist-packages (from pandas<3,>=1.4.0->tabpfn) (2.9.0.post0)\n",
+      "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.12/dist-packages (from pandas<3,>=1.4.0->tabpfn) (2025.2)\n",
+      "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.12/dist-packages (from pandas<3,>=1.4.0->tabpfn) (2025.2)\n",
+      "Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.12/dist-packages (from pydantic>=2.8.0->tabpfn) (0.7.0)\n",
+      "Requirement already satisfied: pydantic-core==2.33.2 in /usr/local/lib/python3.12/dist-packages (from pydantic>=2.8.0->tabpfn) (2.33.2)\n",
+      "Requirement already satisfied: typing-inspection>=0.4.0 in /usr/local/lib/python3.12/dist-packages (from pydantic>=2.8.0->tabpfn) (0.4.2)\n",
+      "Requirement already satisfied: python-dotenv>=0.21.0 in /usr/local/lib/python3.12/dist-packages (from pydantic-settings>=2.10.1->tabpfn) (1.2.1)\n",
+      "Requirement already satisfied: threadpoolctl>=3.1.0 in /usr/local/lib/python3.12/dist-packages (from scikit-learn<1.8,>=1.2.0->tabpfn) (3.6.0)\n",
+      "Requirement already satisfied: platformdirs>=4.4.0 in /usr/local/lib/python3.12/dist-packages (from tabpfn-common-utils>=0.1.8->tabpfn-common-utils[telemetry-interactive]>=0.1.8->tabpfn) (4.5.0)\n",
+      "Requirement already satisfied: posthog~=6.7 in /usr/local/lib/python3.12/dist-packages (from tabpfn-common-utils>=0.1.8->tabpfn-common-utils[telemetry-interactive]>=0.1.8->tabpfn) (6.8.0)\n",
+      "Requirement already satisfied: setuptools in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (75.2.0)\n",
+      "Requirement already satisfied: sympy>=1.13.3 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (1.13.3)\n",
+      "Requirement already satisfied: networkx in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (3.5)\n",
+      "Requirement already satisfied: jinja2 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (3.1.6)\n",
+      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.6.77 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (12.6.77)\n",
+      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.6.77 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (12.6.77)\n",
+      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.6.80 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (12.6.80)\n",
+      "Requirement already satisfied: nvidia-cudnn-cu12==9.10.2.21 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (9.10.2.21)\n",
+      "Requirement already satisfied: nvidia-cublas-cu12==12.6.4.1 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (12.6.4.1)\n",
+      "Requirement already satisfied: nvidia-cufft-cu12==11.3.0.4 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (11.3.0.4)\n",
+      "Requirement already satisfied: nvidia-curand-cu12==10.3.7.77 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (10.3.7.77)\n",
+      "Requirement already satisfied: nvidia-cusolver-cu12==11.7.1.2 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (11.7.1.2)\n",
+      "Requirement already satisfied: nvidia-cusparse-cu12==12.5.4.2 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (12.5.4.2)\n",
+      "Requirement already satisfied: nvidia-cusparselt-cu12==0.7.1 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (0.7.1)\n",
+      "Requirement already satisfied: nvidia-nccl-cu12==2.27.3 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (2.27.3)\n",
+      "Requirement already satisfied: nvidia-nvtx-cu12==12.6.77 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (12.6.77)\n",
+      "Requirement already satisfied: nvidia-nvjitlink-cu12==12.6.85 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (12.6.85)\n",
+      "Requirement already satisfied: nvidia-cufile-cu12==1.11.1.6 in /usr/local/lib/python3.12/dist-packages (from torch<3,>=2.1->tabpfn) (1.11.1.6)\n",
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+      "Requirement already satisfied: backoff>=1.10.0 in /usr/local/lib/python3.12/dist-packages (from posthog~=6.7->tabpfn-common-utils>=0.1.8->tabpfn-common-utils[telemetry-interactive]>=0.1.8->tabpfn) (2.2.1)\n",
+      "Requirement already satisfied: distro>=1.5.0 in /usr/local/lib/python3.12/dist-packages (from posthog~=6.7->tabpfn-common-utils>=0.1.8->tabpfn-common-utils[telemetry-interactive]>=0.1.8->tabpfn) (1.9.0)\n",
+      "Requirement already satisfied: charset_normalizer<4,>=2 in /usr/local/lib/python3.12/dist-packages (from requests->huggingface-hub<2,>=0.25.0->tabpfn) (3.4.4)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.12/dist-packages (from requests->huggingface-hub<2,>=0.25.0->tabpfn) (3.11)\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.12/dist-packages (from requests->huggingface-hub<2,>=0.25.0->tabpfn) (2.5.0)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.12/dist-packages (from requests->huggingface-hub<2,>=0.25.0->tabpfn) (2025.10.5)\n",
+      "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.12/dist-packages (from sympy>=1.13.3->torch<3,>=2.1->tabpfn) (1.3.0)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.12/dist-packages (from jinja2->torch<3,>=2.1->tabpfn) (3.0.3)\n",
+      "Collecting econml\n",
+      "  Downloading econml-0.16.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (37 kB)\n",
+      "Requirement already satisfied: numpy in /usr/local/lib/python3.12/dist-packages (from econml) (2.0.2)\n",
+      "Requirement already satisfied: scipy>1.4.0 in /usr/local/lib/python3.12/dist-packages (from econml) (1.16.3)\n",
+      "Requirement already satisfied: scikit-learn<1.7,>=1.0 in /usr/local/lib/python3.12/dist-packages (from econml) (1.6.1)\n",
+      "Collecting sparse (from econml)\n",
+      "  Downloading sparse-0.17.0-py2.py3-none-any.whl.metadata (5.3 kB)\n",
+      "Requirement already satisfied: joblib>=0.13.0 in /usr/local/lib/python3.12/dist-packages (from econml) (1.5.2)\n",
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+      "Collecting shap<0.49.0,>=0.38.1 (from econml)\n",
+      "  Downloading shap-0.48.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (25 kB)\n",
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+      "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.12/dist-packages (from pandas>1.0->econml) (2.9.0.post0)\n",
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+      "Requirement already satisfied: tqdm>=4.27.0 in /usr/local/lib/python3.12/dist-packages (from shap<0.49.0,>=0.38.1->econml) (4.67.1)\n",
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+      "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.12/dist-packages (from python-dateutil>=2.8.2->pandas>1.0->econml) (1.17.0)\n",
+      "Downloading econml-0.16.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.4 MB)\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.4/5.4 MB\u001b[0m \u001b[31m77.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hDownloading shap-0.48.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.0 MB)\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.0/1.0 MB\u001b[0m \u001b[31m62.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hDownloading sparse-0.17.0-py2.py3-none-any.whl (259 kB)\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m259.4/259.4 kB\u001b[0m \u001b[31m26.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+      "\u001b[?25hInstalling collected packages: sparse, shap, econml\n",
+      "  Attempting uninstall: shap\n",
+      "    Found existing installation: shap 0.49.1\n",
+      "    Uninstalling shap-0.49.1:\n",
+      "      Successfully uninstalled shap-0.49.1\n",
+      "Successfully installed econml-0.16.0 shap-0.48.0 sparse-0.17.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install tabpfn\n",
+    "!pip install econml\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "4wlBhyRpy1wy"
+   },
+   "source": [
+    "### 2) Generate a synthetic CATE dataset\n",
+    "\n",
+    "The dataset $D = (T, X, Y, \\tau)$ below represents an observed confounder scenario $G = \\{X \\rightarrow Y, T \\rightarrow Y, X \\rightarrow T\\}$ and thus satisfies the unconfoundedness assumption: $(Y_0, Y_1) \\perp \\kern-1.8ex \\perp T$ $|$ $X$. We divide the dataset into train and test splits $(D_{train}, D_{test})$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "pFK2RGwpzIWz",
+    "outputId": "8d0fe6aa-8080-41dc-b16f-ebc04bbdefea"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "QNU2S_pwrSq1",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "94a9eebb-71a1-487f-b5b2-df81930d1182"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
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-            "Requirement already satisfied: tqdm>=4.27.0 in /usr/local/lib/python3.12/dist-packages (from shap<0.49.0,>=0.38.1->econml) (4.67.1)\n",
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-            "Requirement already satisfied: numba>=0.54 in /usr/local/lib/python3.12/dist-packages (from shap<0.49.0,>=0.38.1->econml) (0.60.0)\n",
-            "Requirement already satisfied: cloudpickle in /usr/local/lib/python3.12/dist-packages (from shap<0.49.0,>=0.38.1->econml) (3.1.1)\n",
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-            "Requirement already satisfied: patsy>=0.5.6 in /usr/local/lib/python3.12/dist-packages (from statsmodels>=0.10->econml) (1.0.2)\n",
-            "Requirement already satisfied: llvmlite<0.44,>=0.43.0dev0 in /usr/local/lib/python3.12/dist-packages (from numba>=0.54->shap<0.49.0,>=0.38.1->econml) (0.43.0)\n",
-            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.12/dist-packages (from python-dateutil>=2.8.2->pandas>1.0->econml) (1.17.0)\n",
-            "Downloading econml-0.16.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.4 MB)\n",
-            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.4/5.4 MB\u001b[0m \u001b[31m77.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25hDownloading shap-0.48.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.0 MB)\n",
-            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.0/1.0 MB\u001b[0m \u001b[31m62.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25hDownloading sparse-0.17.0-py2.py3-none-any.whl (259 kB)\n",
-            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m259.4/259.4 kB\u001b[0m \u001b[31m26.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25hInstalling collected packages: sparse, shap, econml\n",
-            "  Attempting uninstall: shap\n",
-            "    Found existing installation: shap 0.49.1\n",
-            "    Uninstalling shap-0.49.1:\n",
-            "      Successfully uninstalled shap-0.49.1\n",
-            "Successfully installed econml-0.16.0 shap-0.48.0 sparse-0.17.0\n"
-          ]
-        }
-      ],
-      "source": [
-        "!pip install tabpfn\n",
-        "!pip install econml\n"
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import networkx as nx\n",
+    "\n",
+    "edges = [[\"X\", \"Y\"], [\"T\", \"Y\"], [\"X\", \"T\"]]\n",
+    "graph = nx.DiGraph(edges)\n",
+    "nx.draw(graph, with_labels=True, node_size=2000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "gadFg7JusQ6l"
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "num_samples, num_features, train_test_split = 500, 5, 75\n",
+    "\n",
+    "noise_scale = 0.01\n",
+    "exogenous_scale = 0.1\n",
+    "heterogeneity_scale = 2\n",
+    "\n",
+    "X = np.random.normal(loc=0, scale=exogenous_scale, size=(num_samples, num_features)).astype(np.float32)\n",
+    "prop_eps = np.random.normal(loc=0, scale=noise_scale, size=(num_samples)).astype(np.float32)\n",
+    "Y_eps = np.random.normal(loc=0, scale=noise_scale, size=(num_samples)).astype(np.float32)\n",
+    "\n",
+    "w_X_Y = np.random.uniform(size=num_features)\n",
+    "w_X_T = np.random.uniform(size=num_features)\n",
+    "w_X_T_effect = np.random.uniform(size=num_features)\n",
+    "\n",
+    "T_0 = np.zeros(shape=num_samples).astype(np.float32)\n",
+    "T_1 = np.ones(shape=num_samples).astype(np.float32)\n",
+    "\n",
+    "base_X_Y = np.sum(w_X_Y * X, axis=1)\n",
+    "base_X_T = np.sum(w_X_T * X, axis=1)\n",
+    "heterogeneity_term = np.sum(w_X_T_effect * X, axis=1)\n",
+    "\n",
+    "propensity = np.sin(base_X_T) + prop_eps\n",
+    "T = (propensity > propensity.mean()).astype(np.float32)\n",
+    "\n",
+    "Y_0 = np.cos(base_X_Y) + np.sin(0.3 * T_0) + Y_eps\n",
+    "Y_1 = np.cos(base_X_Y) + np.sin(0.3 * T_1 + heterogeneity_scale * heterogeneity_term) + Y_eps\n",
+    "\n",
+    "Y = Y_0 * (1 - T) + Y_1 * T\n",
+    "tau = Y_1 - Y_0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "VnBaoFhLBiKq",
+    "outputId": "92c452fd-d8ca-45ec-daed-77f04730713a"
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "source": [
-        "### 2) Generate a synthetic CATE dataset\n",
-        "\n",
-        "The dataset $D = (T, X, Y, \\tau)$ below represents an observed confounder scenario $G = \\{X \\rightarrow Y, T \\rightarrow Y, X \\rightarrow T\\}$ and thus satisfies the unconfoundedness assumption: $(Y_0, Y_1) \\perp \\kern-1.8ex \\perp T$ $|$ $X$. We divide the dataset into train and test splits $(D_{train}, D_{test})$."
-      ],
-      "metadata": {
-        "id": "4wlBhyRpy1wy"
-      }
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x300 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "df = pd.DataFrame({**{f\"X{i}\": X[:, i] for i in range(num_features)}, \"T\": T, \"Y\": Y, \"Y_0\": Y_0, \"Y_1\": Y_1, \"tau\": tau})\n",
+    "fig, axes = plt.subplots(ncols=2, figsize=(6, 3))\n",
+    "sns.scatterplot(data=df, x=\"X0\", y=\"tau\", hue=\"T\", ax=axes[0], edgecolor=\"black\", palette=\"Set1\")\n",
+    "sns.scatterplot(data=df, x=\"X1\", y=\"tau\", hue=\"T\", ax=axes[1], edgecolor=\"black\", palette=\"Set1\")\n",
+    "fig.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "3KJJwIwSySzk"
+   },
+   "outputs": [],
+   "source": [
+    "perm = np.random.permutation(num_samples)\n",
+    "train_idx, test_idx = perm[:train_test_split], perm[train_test_split:]\n",
+    "X_train, X_test = X[train_idx], X[test_idx]\n",
+    "Y_train, Y_test = Y[train_idx], Y[test_idx]\n",
+    "T_train, T_test = T[train_idx], T[test_idx]\n",
+    "tau_test = tau[test_idx]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "STYhNc224Zmz"
+   },
+   "source": [
+    "### Run CATE estimators with TabPFN as a base model\n",
+    "\n",
+    "We fit three CATE estimators to our synthetic datasets with different choices of base models\n",
+    "\n",
+    "\n",
+    "\n",
+    "*   `s_tabpfn`: TabPFN applied as an `SLearner`\n",
+    "*   `cfdml_tabpfn`: TabPFN applied as a propensity and outcome in `CausalForestDML`\n",
+    "*   `cfdml_default`: `CausalForestDML` with default propensity and outcome models\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "-3id6xmIrajj"
+   },
+   "outputs": [],
+   "source": [
+    "from econml.metalearners import SLearner\n",
+    "from econml.dml import CausalForestDML\n",
+    "from tabpfn import TabPFNClassifier, TabPFNRegressor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "xuZ1kxQP1ZN6",
+    "outputId": "8741fedd-5b6e-4900-d856-5774a3348399"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "source": [
-        "import networkx as nx\n",
-        "\n",
-        "edges = [[\"X\", \"Y\"], [\"T\", \"Y\"], [\"X\", \"T\"]]\n",
-        "graph = nx.DiGraph(edges)\n",
-        "nx.draw(graph, with_labels=True, node_size=2000)"
-      ],
-      "metadata": {
-        "id": "pFK2RGwpzIWz",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "8d0fe6aa-8080-41dc-b16f-ebc04bbdefea"
-      },
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 640x480 with 1 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
-      ]
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/lib/python3.12/dist-packages/sklearn/utils/deprecation.py:151: FutureWarning: 'force_all_finite' was renamed to 'ensure_all_finite' in 1.6 and will be removed in 1.8.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "s_tabpfn = SLearner(overall_model=TabPFNRegressor())\n",
+    "\n",
+    "s_tabpfn.fit(Y=Y_train, X=X_train, T=T_train)\n",
+    "s_tabpfn_cate = s_tabpfn.effect(X=X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1eUVnX-r1waQ"
+   },
+   "outputs": [],
+   "source": [
+    "cfdml_tabpfn = CausalForestDML(model_y=TabPFNRegressor(), model_t=TabPFNClassifier(), discrete_treatment=True)\n",
+    "\n",
+    "cfdml_tabpfn.fit(Y=Y_train, X=X_train, T=T_train)\n",
+    "cfdml_tabpfn_cate = cfdml_tabpfn.effect(X=X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "R_QEm9P12tlH"
+   },
+   "outputs": [],
+   "source": [
+    "cfdml_default = CausalForestDML(discrete_treatment=True)\n",
+    "\n",
+    "cfdml_default.fit(Y=Y_train, X=X_train, T=T_train)\n",
+    "cfdml_default_cate = cfdml_default.effect(X=X_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "nbsS1tvf7GS1"
+   },
+   "source": [
+    "### Evaluate performance in CATE estimation\n",
+    "\n",
+    "We assess how close our predicted individual effects $\\hat{\\tau}(x)$ are to the true effects $\\tau(x)$ using **PEHE** (Precision in Estimation of Heterogeneous Effects).\n",
+    "PEHE is defined as the root-mean-squared-error (RMSE) between predicted and ground truth CATE values.\n",
+    "\n",
+    "$$\\text{PEHE} = \\sqrt{\\frac{1}{n} \\sum [\\widehat{\\tau}(x_i) - \\tau(x_i) ]^2}$$\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "LQYrBYLB7F2v",
+    "outputId": "48ceaeb6-81d5-4d74-8541-ee3656097969"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "source": [
-        "import numpy as np\n",
-        "\n",
-        "num_samples, num_features, train_test_split = 500, 5, 75\n",
-        "\n",
-        "noise_scale = 0.01\n",
-        "exogenous_scale = 0.1\n",
-        "heterogeneity_scale = 2\n",
-        "\n",
-        "X = np.random.normal(loc=0, scale=exogenous_scale, size=(num_samples, num_features)).astype(np.float32)\n",
-        "prop_eps = np.random.normal(loc=0, scale=noise_scale, size=(num_samples)).astype(np.float32)\n",
-        "Y_eps = np.random.normal(loc=0, scale=noise_scale, size=(num_samples)).astype(np.float32)\n",
-        "\n",
-        "w_X_Y = np.random.uniform(size=num_features)\n",
-        "w_X_T = np.random.uniform(size=num_features)\n",
-        "w_X_T_effect = np.random.uniform(size=num_features)\n",
-        "\n",
-        "T_0 = np.zeros(shape=num_samples).astype(np.float32)\n",
-        "T_1 = np.ones(shape=num_samples).astype(np.float32)\n",
-        "\n",
-        "base_X_Y = np.sum(w_X_Y * X, axis=1)\n",
-        "base_X_T = np.sum(w_X_T * X, axis=1)\n",
-        "heterogeneity_term = np.sum(w_X_T_effect * X, axis=1)\n",
-        "\n",
-        "propensity = np.sin(base_X_T) + prop_eps\n",
-        "T = (propensity > propensity.mean()).astype(np.float32)\n",
-        "\n",
-        "Y_0 = np.cos(base_X_Y) + np.sin(0.3 * T_0) + Y_eps\n",
-        "Y_1 = np.cos(base_X_Y) + np.sin(0.3 * T_1 + heterogeneity_scale * heterogeneity_term) + Y_eps\n",
-        "\n",
-        "Y = Y_0 * (1 - T) + Y_1 * T\n",
-        "tau = Y_1 - Y_0"
-      ],
-      "metadata": {
-        "id": "gadFg7JusQ6l"
-      },
-      "execution_count": null,
-      "outputs": []
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "s_tabpfn PEHE: 0.09701367904551404\n",
+      "cfdml_tabpfn PEHE: 0.22240085005502397\n",
+      "cfdml_default PEHE: 0.2537058237154443\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import root_mean_squared_error\n",
+    "\n",
+    "s_tabpfn_pehe = root_mean_squared_error(tau_test, s_tabpfn_cate)\n",
+    "cfdml_tabpfn_pehe = root_mean_squared_error(tau_test, cfdml_tabpfn_cate)\n",
+    "cfdml_default_pehe = root_mean_squared_error(tau_test, cfdml_default_cate)\n",
+    "\n",
+    "print(f\"s_tabpfn PEHE: {s_tabpfn_pehe}\")\n",
+    "print(f\"cfdml_tabpfn PEHE: {cfdml_tabpfn_pehe}\")\n",
+    "print(f\"cfdml_default PEHE: {cfdml_default_pehe}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 307
     },
+    "id": "-Jlg79mU_Ehg",
+    "outputId": "dd26be1d-37b0-4357-c32b-fe5d3697f85f"
+   },
+   "outputs": [
     {
-      "cell_type": "code",
-      "source": [
-        "import pandas as pd\n",
-        "import seaborn as sns\n",
-        "import matplotlib.pyplot as plt\n",
-        "\n",
-        "df = pd.DataFrame({**{f\"X{i}\": X[:, i] for i in range(num_features)}, \"T\": T, \"Y\": Y, \"Y_0\": Y_0, \"Y_1\": Y_1, \"tau\": tau})\n",
-        "fig, axes = plt.subplots(ncols=2, figsize=(6, 3))\n",
-        "sns.scatterplot(data=df, x=\"X0\", y=\"tau\", hue=\"T\", ax=axes[0], edgecolor=\"black\", palette=\"Set1\")\n",
-        "sns.scatterplot(data=df, x=\"X1\", y=\"tau\", hue=\"T\", ax=axes[1], edgecolor=\"black\", palette=\"Set1\")\n",
-        "fig.tight_layout()"
-      ],
-      "metadata": {
-        "id": "VnBaoFhLBiKq",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "92c452fd-d8ca-45ec-daed-77f04730713a"
-      },
-      "execution_count": null,
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 900x300 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df_test = pd.DataFrame({\"T\": T_test, \"Y\": Y_test, \"tau\": tau_test, **{f\"X{i}\": X_test[:, i] for i in range(num_features)}})\n",
+    "df_test[\"s_tabpfn_pred\"], df_test[\"cfdml_tabpfn_pred\"], df_test[\"cfdml_default_pred\"] = s_tabpfn_cate, cfdml_tabpfn_cate, cfdml_default_cate\n",
+    "\n",
+    "fig, axes = plt.subplots(ncols=3, figsize=(9, 3))\n",
+    "sns.scatterplot(data=df_test, x=\"tau\", y=\"s_tabpfn_pred\", hue=\"T\", ax=axes[0], edgecolor=\"black\", palette=\"Set1\")\n",
+    "sns.scatterplot(data=df_test, x=\"tau\", y=\"cfdml_tabpfn_pred\", hue=\"T\", ax=axes[1], edgecolor=\"black\", palette=\"Set1\")\n",
+    "sns.scatterplot(data=df_test, x=\"tau\", y=\"cfdml_default_pred\", hue=\"T\", ax=axes[2], edgecolor=\"black\", palette=\"Set1\")\n",
+    "fig.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "SlKBzRphHS_6"
+   },
+   "source": [
+    "# Feedback\n",
+    "\n",
+    "Let us know what you think!\n",
+    "\n",
+    "Write us at Discord: https://discord.gg/qK7AaXPN or just simply create an issue on [GitHub](https://github.com/PriorLabs/tabpfn).\n",
+    "\n",
+    "Thank you for trying out our method! 🎉\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "collapsed_sections": [
+    "tisgLOuqzrfo",
+    "o03aOVAw0Etg",
+    "iro4vB3w4rgE",
+    "c8iQ9KEd1h9R",
+    "ZVs_HfxbVCs3",
+    "ipG2Cpb7Jrc7",
+    "3uGfjIdjsCg-",
+    "mTnMbG9vXHkL",
+    "6RYILEoPXaMZ",
+    "PkphS4vSFNvg",
+    "ZBeID4YeMQ9L",
+    "8tvOmmiOOT4o",
+    "XcYaJKT_Pw6T"
+   ],
+   "gpuType": "T4",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.9"
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "0b0d8924f58949a2ba8c5de2dc99d9b2": {
+     "model_module": "@jupyter-widgets/output",
+     "model_module_version": "1.0.0",
+     "model_name": "OutputModel",
+     "state": {
+      "_dom_classes": [],
+      "_model_module": "@jupyter-widgets/output",
+      "_model_module_version": "1.0.0",
+      "_model_name": "OutputModel",
+      "_view_count": null,
+      "_view_module": "@jupyter-widgets/output",
+      "_view_module_version": "1.0.0",
+      "_view_name": "OutputView",
+      "layout": "IPY_MODEL_80873b8fc8734802a2422304e627a233",
+      "msg_id": "",
       "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 600x300 with 2 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
+       {
+        "data": {
+         "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">⠇</span> <span style=\"font-weight: bold\">Authenticating</span>\n</pre>\n",
+         "text/plain": "\u001b[32m⠇\u001b[0m \u001b[1mAuthenticating\u001b[0m\n"
+        },
+        "metadata": {},
+        "output_type": "display_data"
+       }
       ]
+     }
     },
-    {
-      "cell_type": "code",
-      "source": [
-        "perm = np.random.permutation(num_samples)\n",
-        "train_idx, test_idx = perm[:train_test_split], perm[train_test_split:]\n",
-        "X_train, X_test = X[train_idx], X[test_idx]\n",
-        "Y_train, Y_test = Y[train_idx], Y[test_idx]\n",
-        "T_train, T_test = T[train_idx], T[test_idx]\n",
-        "tau_test = tau[test_idx]"
-      ],
-      "metadata": {
-        "id": "3KJJwIwSySzk"
-      },
-      "execution_count": null,
-      "outputs": []
+    "0c458dab93ee415f839fd216d33b43d9": {
+     "model_module": "@jupyter-widgets/controls",
+     "model_module_version": "1.5.0",
+     "model_name": "DescriptionStyleModel",
+     "state": {
+      "_model_module": "@jupyter-widgets/controls",
+      "_model_module_version": "1.5.0",
+      "_model_name": "DescriptionStyleModel",
+      "_view_count": null,
+      "_view_module": "@jupyter-widgets/base",
+      "_view_module_version": "1.2.0",
+      "_view_name": "StyleView",
+      "description_width": ""
+     }
     },
-    {
-      "cell_type": "markdown",
-      "source": [
-        "### Run CATE estimators with TabPFN as a base model\n",
-        "\n",
-        "We fit three CATE estimators to our synthetic datasets with different choices of base models\n",
-        "\n",
-        "\n",
-        "\n",
-        "*   `s_tabpfn`: TabPFN applied as an `SLearner`\n",
-        "*   `cfdml_tabpfn`: TabPFN applied as a propensity and outcome in `CausalForestDML`\n",
-        "*   `cfdml_default`: `CausalForestDML` with default propensity and outcome models\n",
-        "\n"
-      ],
-      "metadata": {
-        "id": "STYhNc224Zmz"
-      }
+    "0ef1661193d44ef99f7e281cb79c40b5": {
+     "model_module": "@jupyter-widgets/controls",
+     "model_module_version": "1.5.0",
+     "model_name": "HTMLModel",
+     "state": {
+      "_dom_classes": [],
+      "_model_module": "@jupyter-widgets/controls",
+      "_model_module_version": "1.5.0",
+      "_model_name": "HTMLModel",
+      "_view_count": null,
+      "_view_module": "@jupyter-widgets/controls",
+      "_view_module_version": "1.5.0",
+      "_view_name": "HTMLView",
+      "description": "",
+      "description_tooltip": null,
+      "layout": "IPY_MODEL_b15054c98fd8457095b01a54ad491056",
+      "placeholder": "​",
+      "style": "IPY_MODEL_e4a2681db14a43a6836f0fd3ab154509",
+      "value": " 44.3k/? [00:00&lt;00:00, 932kB/s]"
+     }
     },
-    {
-      "cell_type": "code",
-      "source": [
-        "from econml.metalearners import SLearner\n",
-        "from econml.dml import CausalForestDML\n",
-        "from tabpfn import TabPFNClassifier, TabPFNRegressor"
-      ],
-      "metadata": {
-        "id": "-3id6xmIrajj"
-      },
-      "execution_count": null,
-      "outputs": []
+    "12a2a205bd944f8e8a3643f977c38b56": {
+     "model_module": "@jupyter-widgets/controls",
+     "model_module_version": "1.5.0",
+     "model_name": "FloatProgressModel",
+     "state": {
+      "_dom_classes": [],
+      "_model_module": "@jupyter-widgets/controls",
+      "_model_module_version": "1.5.0",
+      "_model_name": "FloatProgressModel",
+      "_view_count": null,
+      "_view_module": "@jupyter-widgets/controls",
+      "_view_module_version": "1.5.0",
+      "_view_name": "ProgressView",
+      "bar_style": "success",
+      "description": "",
+      "description_tooltip": null,
+      "layout": "IPY_MODEL_96db2596e70f4e809832e39642b8af99",
+      "max": 334951,
+      "min": 0,
+      "orientation": "horizontal",
+      "style": "IPY_MODEL_614ab8ceb45245cf8d11dcb576b3e27d",
+      "value": 334951
+     }
     },
-    {
-      "cell_type": "code",
-      "source": [
-        "s_tabpfn = SLearner(overall_model=TabPFNRegressor())\n",
-        "\n",
-        "s_tabpfn.fit(Y=Y_train, X=X_train, T=T_train)\n",
-        "s_tabpfn_cate = s_tabpfn.effect(X=X_test)"
-      ],
-      "metadata": {
-        "id": "xuZ1kxQP1ZN6",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "8741fedd-5b6e-4900-d856-5774a3348399"
-      },
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "/usr/local/lib/python3.12/dist-packages/sklearn/utils/deprecation.py:151: FutureWarning: 'force_all_finite' was renamed to 'ensure_all_finite' in 1.6 and will be removed in 1.8.\n",
-            "  warnings.warn(\n"
-          ]
-        }
-      ]
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-      "source": [
-        "cfdml_tabpfn = CausalForestDML(model_y=TabPFNRegressor(), model_t=TabPFNClassifier(), discrete_treatment=True)\n",
-        "\n",
-        "cfdml_tabpfn.fit(Y=Y_train, X=X_train, T=T_train)\n",
-        "cfdml_tabpfn_cate = cfdml_tabpfn.effect(X=X_test)"
-      ],
-      "metadata": {
-        "id": "1eUVnX-r1waQ"
-      },
-      "execution_count": null,
-      "outputs": []
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-      "cell_type": "code",
-      "source": [
-        "cfdml_default = CausalForestDML(discrete_treatment=True)\n",
-        "\n",
-        "cfdml_default.fit(Y=Y_train, X=X_train, T=T_train)\n",
-        "cfdml_default_cate = cfdml_default.effect(X=X_test)"
-      ],
-      "metadata": {
-        "id": "R_QEm9P12tlH"
-      },
-      "execution_count": null,
-      "outputs": []
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-    {
-      "cell_type": "markdown",
-      "source": [
-        "### Evaluate performance in CATE estimation\n",
-        "\n",
-        "We assess how close our predicted individual effects $\\hat{\\tau}(x)$ are to the true effects $\\tau(x)$ using **PEHE** (Precision in Estimation of Heterogeneous Effects).\n",
-        "PEHE is defined as the root-mean-squared-error (RMSE) between predicted and ground truth CATE values.\n",
-        "\n",
-        "$$\\text{PEHE} = \\sqrt{\\frac{1}{n} \\sum [\\widehat{\\tau}(x_i) - \\tau(x_i) ]^2}$$\n"
-      ],
-      "metadata": {
-        "id": "nbsS1tvf7GS1"
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-    {
-      "cell_type": "code",
-      "source": [
-        "from sklearn.metrics import root_mean_squared_error\n",
-        "\n",
-        "s_tabpfn_pehe = root_mean_squared_error(tau_test, s_tabpfn_cate)\n",
-        "cfdml_tabpfn_pehe = root_mean_squared_error(tau_test, cfdml_tabpfn_cate)\n",
-        "cfdml_default_pehe = root_mean_squared_error(tau_test, cfdml_default_cate)\n",
-        "\n",
-        "print(f\"s_tabpfn PEHE: {s_tabpfn_pehe}\")\n",
-        "print(f\"cfdml_tabpfn PEHE: {cfdml_tabpfn_pehe}\")\n",
-        "print(f\"cfdml_default PEHE: {cfdml_default_pehe}\")"
-      ],
-      "metadata": {
-        "id": "LQYrBYLB7F2v",
-        "colab": {
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-      "execution_count": null,
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-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "s_tabpfn PEHE: 0.09701367904551404\n",
-            "cfdml_tabpfn PEHE: 0.22240085005502397\n",
-            "cfdml_default PEHE: 0.2537058237154443\n"
-          ]
-        }
-      ]
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-        "df_test = pd.DataFrame({\"T\": T_test, \"Y\": Y_test, \"tau\": tau_test, **{f\"X{i}\": X_test[:, i] for i in range(num_features)}})\n",
-        "df_test[\"s_tabpfn_pred\"], df_test[\"cfdml_tabpfn_pred\"], df_test[\"cfdml_default_pred\"] = s_tabpfn_cate, cfdml_tabpfn_cate, cfdml_default_cate\n",
-        "\n",
-        "fig, axes = plt.subplots(ncols=3, figsize=(9, 3))\n",
-        "sns.scatterplot(data=df_test, x=\"tau\", y=\"s_tabpfn_pred\", hue=\"T\", ax=axes[0], edgecolor=\"black\", palette=\"Set1\")\n",
-        "sns.scatterplot(data=df_test, x=\"tau\", y=\"cfdml_tabpfn_pred\", hue=\"T\", ax=axes[1], edgecolor=\"black\", palette=\"Set1\")\n",
-        "sns.scatterplot(data=df_test, x=\"tau\", y=\"cfdml_default_pred\", hue=\"T\", ax=axes[2], edgecolor=\"black\", palette=\"Set1\")\n",
-        "fig.tight_layout()"
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-        "# Feedback\n",
-        "\n",
-        "Let us know what you think!\n",
-        "\n",
-        "Write us at Discord: https://discord.gg/qK7AaXPN or just simply create an issue on [GitHub](https://github.com/PriorLabs/tabpfn).\n",
-        "\n",
-        "Thank you for trying out our method! 🎉\n"
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