From d66351cd161fffc14bf2113157c071d0c7a24dff Mon Sep 17 00:00:00 2001
From: Nitish Bharambe <nitish.bharambe@alliander.com>
Date: Wed, 14 May 2025 18:53:29 +0200
Subject: [PATCH] correction enum pf assignment

Signed-off-by: Nitish Bharambe <nitish.bharambe@alliander.com>
---
 ...Power Flow Assignment with Solutions.ipynb | 584 +++++++++---------
 .../Power Flow Assignment.ipynb               |   4 +-
 2 files changed, 294 insertions(+), 294 deletions(-)

diff --git a/power-flow-assignment/Power Flow Assignment with Solutions.ipynb b/power-flow-assignment/Power Flow Assignment with Solutions.ipynb
index f7699a8..0d49f31 100644
--- a/power-flow-assignment/Power Flow Assignment with Solutions.ipynb	
+++ b/power-flow-assignment/Power Flow Assignment with Solutions.ipynb	
@@ -111,7 +111,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Execution time for Add Operation is 0.002006 s\n"
+      "Execution time for Add Operation is 0.002952 s\n"
      ]
     }
    ],
@@ -143,11 +143,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "node     : 2001\n",
-      "line     : 2000\n",
-      "source   :    1\n",
-      "sym_load : 2000\n",
-      "Execution time for Loading Input Data is 0.015631 s\n"
+      "ComponentType.node: 2001\n",
+      "ComponentType.line: 2000\n",
+      "ComponentType.source:    1\n",
+      "ComponentType.sym_load: 2000\n",
+      "Execution time for Loading Input Data is 0.012547 s\n"
      ]
     }
    ],
@@ -157,7 +157,7 @@
     "    for component in [ComponentType.node, ComponentType.line, ComponentType.source, ComponentType.sym_load]:\n",
     "        \n",
     "        # Use pandas to read CSV data\n",
-    "        df = pd.read_csv(f'../data/{component}.csv')\n",
+    "        df = pd.read_csv(f'../data/{component.value}.csv')\n",
     "\n",
     "        # Initialize array\n",
     "        input_data[component] = initialize_array(DatasetType.input, component, len(df))\n",
@@ -197,7 +197,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Execution time for Validating Input Data is 0.004683 s\n"
+      "Execution time for Validating Input Data is 0.009321 s\n"
      ]
     }
    ],
@@ -228,8 +228,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Execution time for Model Construction is 0.000797 s\n",
-      "{'node': 2001, 'line': 2000, 'source': 1, 'sym_load': 2000}\n"
+      "Execution time for Model Construction is 0.002634 s\n",
+      "{<ComponentType.node: 'node'>: 2001, <ComponentType.line: 'line'>: 2000, <ComponentType.source: 'source'>: 1, <ComponentType.sym_load: 'sym_load'>: 2000}\n"
      ]
     }
    ],
@@ -264,9 +264,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Execution time for Newton-Raphson Power Flow is 0.003964 s\n",
-      "Min line loading: 0.14188449783808707\n",
-      "Max line loading: 1.6292378285645808\n"
+      "Execution time for Newton-Raphson Power Flow is 0.003671 s\n",
+      "Min line loading: 0.1418844978380699\n",
+      "Max line loading: 1.6292378285645368\n"
      ]
     }
    ],
@@ -290,7 +290,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Execution time for Linear Power Flow is 0.000925 s\n",
+      "Execution time for Linear Power Flow is 0.002162 s\n",
       "Min line loading: 0.1395686087394204\n",
       "Max line loading: 1.6156849991055762\n"
      ]
@@ -377,123 +377,123 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2022-01-01 00:00:00</th>\n",
-       "      <td>1.212021e+06</td>\n",
-       "      <td>8.519954e+05</td>\n",
-       "      <td>7.560917e+05</td>\n",
-       "      <td>1.438055e+06</td>\n",
-       "      <td>7.396164e+05</td>\n",
-       "      <td>6.948326e+05</td>\n",
-       "      <td>1.278412e+06</td>\n",
-       "      <td>2.304984e+06</td>\n",
-       "      <td>9.588319e+05</td>\n",
-       "      <td>9.406021e+05</td>\n",
+       "      <td>1.522690e+06</td>\n",
+       "      <td>7.365325e+05</td>\n",
+       "      <td>1.883955e+06</td>\n",
+       "      <td>1.747342e+06</td>\n",
+       "      <td>1.235460e+06</td>\n",
+       "      <td>1.250241e+06</td>\n",
+       "      <td>1.067713e+06</td>\n",
+       "      <td>1.307628e+06</td>\n",
+       "      <td>1.168910e+06</td>\n",
+       "      <td>1.218901e+06</td>\n",
        "      <td>...</td>\n",
-       "      <td>2.109739e+05</td>\n",
-       "      <td>1.220735e+06</td>\n",
-       "      <td>9.715073e+05</td>\n",
-       "      <td>1.463336e+06</td>\n",
-       "      <td>3.436582e+05</td>\n",
-       "      <td>1.764624e+05</td>\n",
-       "      <td>5.271467e+05</td>\n",
-       "      <td>9.022588e+05</td>\n",
-       "      <td>1.055085e+06</td>\n",
-       "      <td>1.166126e+06</td>\n",
+       "      <td>1.589131e+06</td>\n",
+       "      <td>1.702425e+06</td>\n",
+       "      <td>1.148132e+06</td>\n",
+       "      <td>8.532146e+05</td>\n",
+       "      <td>7.044042e+05</td>\n",
+       "      <td>8.186826e+05</td>\n",
+       "      <td>8.116150e+05</td>\n",
+       "      <td>7.100930e+05</td>\n",
+       "      <td>1.203160e+06</td>\n",
+       "      <td>1.149239e+06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2022-01-01 01:00:00</th>\n",
-       "      <td>8.693649e+05</td>\n",
-       "      <td>9.754355e+05</td>\n",
-       "      <td>5.038237e+05</td>\n",
-       "      <td>1.204583e+06</td>\n",
-       "      <td>8.941464e+05</td>\n",
-       "      <td>7.513620e+04</td>\n",
-       "      <td>1.137045e+06</td>\n",
-       "      <td>1.708324e+06</td>\n",
-       "      <td>1.342389e+06</td>\n",
-       "      <td>1.959986e+06</td>\n",
+       "      <td>8.881127e+05</td>\n",
+       "      <td>1.053687e+06</td>\n",
+       "      <td>3.734167e+05</td>\n",
+       "      <td>1.614773e+06</td>\n",
+       "      <td>1.348900e+06</td>\n",
+       "      <td>3.942241e+05</td>\n",
+       "      <td>9.418381e+05</td>\n",
+       "      <td>-1.287045e+05</td>\n",
+       "      <td>7.848680e+05</td>\n",
+       "      <td>1.169359e+06</td>\n",
        "      <td>...</td>\n",
-       "      <td>3.954700e+05</td>\n",
-       "      <td>6.418734e+05</td>\n",
-       "      <td>1.166324e+06</td>\n",
-       "      <td>1.218541e+06</td>\n",
-       "      <td>1.256374e+06</td>\n",
-       "      <td>1.747930e+06</td>\n",
-       "      <td>1.375117e+06</td>\n",
-       "      <td>5.358348e+04</td>\n",
-       "      <td>1.628927e+06</td>\n",
-       "      <td>8.230403e+05</td>\n",
+       "      <td>4.982993e+05</td>\n",
+       "      <td>9.892282e+05</td>\n",
+       "      <td>6.087048e+05</td>\n",
+       "      <td>1.143115e+06</td>\n",
+       "      <td>1.496269e+06</td>\n",
+       "      <td>1.504554e+06</td>\n",
+       "      <td>4.250855e+05</td>\n",
+       "      <td>9.431208e+05</td>\n",
+       "      <td>1.697681e+06</td>\n",
+       "      <td>1.585010e+06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2022-01-01 02:00:00</th>\n",
-       "      <td>7.923984e+05</td>\n",
-       "      <td>1.434058e+06</td>\n",
-       "      <td>5.024506e+05</td>\n",
-       "      <td>1.627207e+06</td>\n",
-       "      <td>1.164684e+06</td>\n",
-       "      <td>4.291224e+05</td>\n",
-       "      <td>6.576416e+05</td>\n",
-       "      <td>9.367841e+05</td>\n",
-       "      <td>8.624529e+05</td>\n",
-       "      <td>7.692469e+05</td>\n",
+       "      <td>9.811829e+05</td>\n",
+       "      <td>1.413438e+06</td>\n",
+       "      <td>9.972503e+05</td>\n",
+       "      <td>1.233187e+06</td>\n",
+       "      <td>1.295709e+06</td>\n",
+       "      <td>3.746883e+05</td>\n",
+       "      <td>1.720246e+06</td>\n",
+       "      <td>1.248101e+06</td>\n",
+       "      <td>4.639225e+05</td>\n",
+       "      <td>9.123818e+05</td>\n",
        "      <td>...</td>\n",
-       "      <td>1.044997e+06</td>\n",
-       "      <td>8.009140e+05</td>\n",
-       "      <td>1.240692e+06</td>\n",
-       "      <td>-2.777931e+04</td>\n",
-       "      <td>9.717390e+05</td>\n",
-       "      <td>1.261385e+06</td>\n",
-       "      <td>8.674137e+05</td>\n",
-       "      <td>1.158677e+06</td>\n",
-       "      <td>1.320565e+06</td>\n",
-       "      <td>1.354277e+06</td>\n",
+       "      <td>1.866030e+06</td>\n",
+       "      <td>1.744288e+06</td>\n",
+       "      <td>1.412359e+06</td>\n",
+       "      <td>7.322985e+05</td>\n",
+       "      <td>8.552735e+05</td>\n",
+       "      <td>9.632037e+05</td>\n",
+       "      <td>1.006114e+06</td>\n",
+       "      <td>6.947516e+05</td>\n",
+       "      <td>7.969410e+05</td>\n",
+       "      <td>1.487227e+06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2022-01-01 03:00:00</th>\n",
-       "      <td>1.269392e+06</td>\n",
-       "      <td>1.463432e+06</td>\n",
-       "      <td>1.018994e+06</td>\n",
-       "      <td>1.524115e+06</td>\n",
-       "      <td>5.695050e+05</td>\n",
-       "      <td>1.577387e+06</td>\n",
-       "      <td>1.525168e+05</td>\n",
-       "      <td>3.880051e+04</td>\n",
-       "      <td>1.383405e+06</td>\n",
-       "      <td>5.596274e+05</td>\n",
+       "      <td>1.594312e+06</td>\n",
+       "      <td>1.711561e+06</td>\n",
+       "      <td>7.238942e+05</td>\n",
+       "      <td>6.706983e+05</td>\n",
+       "      <td>2.852392e+05</td>\n",
+       "      <td>8.300269e+05</td>\n",
+       "      <td>1.148656e+06</td>\n",
+       "      <td>1.037572e+06</td>\n",
+       "      <td>1.086457e+06</td>\n",
+       "      <td>1.633151e+06</td>\n",
        "      <td>...</td>\n",
-       "      <td>8.182543e+05</td>\n",
-       "      <td>1.632945e+06</td>\n",
-       "      <td>1.010543e+06</td>\n",
-       "      <td>4.009558e+05</td>\n",
-       "      <td>1.478580e+06</td>\n",
-       "      <td>5.612716e+05</td>\n",
-       "      <td>1.245279e+06</td>\n",
-       "      <td>1.028181e+06</td>\n",
-       "      <td>1.294013e+06</td>\n",
-       "      <td>1.162580e+06</td>\n",
+       "      <td>1.190132e+06</td>\n",
+       "      <td>1.383107e+06</td>\n",
+       "      <td>7.801834e+05</td>\n",
+       "      <td>9.776243e+05</td>\n",
+       "      <td>2.293418e+06</td>\n",
+       "      <td>9.743710e+05</td>\n",
+       "      <td>1.804552e+06</td>\n",
+       "      <td>7.211640e+05</td>\n",
+       "      <td>1.145045e+06</td>\n",
+       "      <td>1.421976e+06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2022-01-01 04:00:00</th>\n",
-       "      <td>5.811972e+05</td>\n",
-       "      <td>1.614621e+06</td>\n",
-       "      <td>9.650531e+05</td>\n",
-       "      <td>9.365501e+05</td>\n",
-       "      <td>1.209160e+06</td>\n",
-       "      <td>3.318855e+05</td>\n",
-       "      <td>3.351287e+05</td>\n",
-       "      <td>1.444800e+06</td>\n",
-       "      <td>-2.583068e+05</td>\n",
-       "      <td>1.052083e+06</td>\n",
+       "      <td>4.667720e+05</td>\n",
+       "      <td>1.128695e+06</td>\n",
+       "      <td>1.028832e+06</td>\n",
+       "      <td>5.444642e+05</td>\n",
+       "      <td>1.052969e+05</td>\n",
+       "      <td>5.439632e+05</td>\n",
+       "      <td>1.916725e+06</td>\n",
+       "      <td>1.075958e+06</td>\n",
+       "      <td>9.885185e+05</td>\n",
+       "      <td>1.375559e+06</td>\n",
        "      <td>...</td>\n",
-       "      <td>4.259355e+05</td>\n",
-       "      <td>2.095648e+06</td>\n",
-       "      <td>1.368940e+06</td>\n",
-       "      <td>1.935897e+05</td>\n",
-       "      <td>1.291826e+06</td>\n",
-       "      <td>1.599473e+06</td>\n",
-       "      <td>1.193099e+06</td>\n",
-       "      <td>1.676480e+06</td>\n",
-       "      <td>6.758581e+05</td>\n",
-       "      <td>5.690138e+05</td>\n",
+       "      <td>5.633235e+05</td>\n",
+       "      <td>5.196102e+05</td>\n",
+       "      <td>4.177027e+05</td>\n",
+       "      <td>1.353726e+06</td>\n",
+       "      <td>7.087020e+05</td>\n",
+       "      <td>7.139034e+05</td>\n",
+       "      <td>8.842609e+05</td>\n",
+       "      <td>7.882466e+05</td>\n",
+       "      <td>-8.232680e+04</td>\n",
+       "      <td>1.445546e+06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -521,123 +521,123 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2022-02-11 11:00:00</th>\n",
-       "      <td>9.550081e+05</td>\n",
-       "      <td>1.050358e+06</td>\n",
-       "      <td>1.183558e+06</td>\n",
-       "      <td>9.563775e+05</td>\n",
-       "      <td>9.167803e+05</td>\n",
-       "      <td>7.077838e+05</td>\n",
-       "      <td>5.764765e+05</td>\n",
-       "      <td>1.628767e+06</td>\n",
-       "      <td>1.062615e+06</td>\n",
-       "      <td>1.755868e+06</td>\n",
+       "      <td>6.554215e+05</td>\n",
+       "      <td>1.519971e+06</td>\n",
+       "      <td>7.346373e+05</td>\n",
+       "      <td>2.468342e+05</td>\n",
+       "      <td>1.391215e+06</td>\n",
+       "      <td>2.756525e+05</td>\n",
+       "      <td>1.064843e+06</td>\n",
+       "      <td>1.632632e+06</td>\n",
+       "      <td>2.255325e+06</td>\n",
+       "      <td>3.975464e+05</td>\n",
        "      <td>...</td>\n",
-       "      <td>1.557175e+06</td>\n",
-       "      <td>9.978829e+05</td>\n",
-       "      <td>1.428223e+06</td>\n",
-       "      <td>9.375576e+05</td>\n",
-       "      <td>1.544223e+06</td>\n",
-       "      <td>1.230698e+06</td>\n",
-       "      <td>6.241062e+05</td>\n",
-       "      <td>1.172571e+06</td>\n",
-       "      <td>1.420599e+06</td>\n",
-       "      <td>9.502391e+04</td>\n",
+       "      <td>3.516876e+05</td>\n",
+       "      <td>9.236746e+05</td>\n",
+       "      <td>1.067935e+06</td>\n",
+       "      <td>1.237977e+06</td>\n",
+       "      <td>4.839377e+05</td>\n",
+       "      <td>1.140204e+06</td>\n",
+       "      <td>1.391819e+06</td>\n",
+       "      <td>1.668330e+06</td>\n",
+       "      <td>6.788123e+05</td>\n",
+       "      <td>1.408043e+06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2022-02-11 12:00:00</th>\n",
-       "      <td>5.272977e+05</td>\n",
-       "      <td>8.443402e+05</td>\n",
-       "      <td>1.338616e+06</td>\n",
-       "      <td>4.481988e+05</td>\n",
-       "      <td>1.426800e+06</td>\n",
-       "      <td>2.918600e+05</td>\n",
-       "      <td>1.875643e+06</td>\n",
-       "      <td>1.500691e+06</td>\n",
-       "      <td>1.178919e+06</td>\n",
-       "      <td>7.893541e+05</td>\n",
+       "      <td>1.059431e+06</td>\n",
+       "      <td>6.340614e+05</td>\n",
+       "      <td>1.400879e+06</td>\n",
+       "      <td>1.494647e+05</td>\n",
+       "      <td>8.775668e+05</td>\n",
+       "      <td>1.161970e+06</td>\n",
+       "      <td>9.090381e+05</td>\n",
+       "      <td>6.548579e+05</td>\n",
+       "      <td>5.131747e+05</td>\n",
+       "      <td>2.268062e+05</td>\n",
        "      <td>...</td>\n",
-       "      <td>7.506101e+05</td>\n",
-       "      <td>1.146763e+06</td>\n",
-       "      <td>8.711101e+05</td>\n",
-       "      <td>8.625724e+05</td>\n",
-       "      <td>7.775495e+05</td>\n",
-       "      <td>7.721788e+05</td>\n",
-       "      <td>1.647198e+06</td>\n",
-       "      <td>1.898852e+06</td>\n",
-       "      <td>7.778365e+05</td>\n",
-       "      <td>-7.752296e+03</td>\n",
+       "      <td>3.092005e+05</td>\n",
+       "      <td>8.351009e+05</td>\n",
+       "      <td>1.194604e+05</td>\n",
+       "      <td>1.132886e+06</td>\n",
+       "      <td>3.542770e+05</td>\n",
+       "      <td>8.243507e+05</td>\n",
+       "      <td>6.221985e+05</td>\n",
+       "      <td>1.249335e+06</td>\n",
+       "      <td>8.687152e+05</td>\n",
+       "      <td>2.072785e+05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2022-02-11 13:00:00</th>\n",
-       "      <td>5.938971e+05</td>\n",
-       "      <td>1.213851e+06</td>\n",
-       "      <td>8.529911e+05</td>\n",
-       "      <td>9.887598e+05</td>\n",
-       "      <td>1.508931e+06</td>\n",
-       "      <td>1.097557e+06</td>\n",
-       "      <td>6.580392e+05</td>\n",
-       "      <td>1.490143e+06</td>\n",
-       "      <td>2.179459e+06</td>\n",
-       "      <td>1.281627e+06</td>\n",
+       "      <td>6.521878e+05</td>\n",
+       "      <td>2.955911e+05</td>\n",
+       "      <td>3.741276e+05</td>\n",
+       "      <td>4.800967e+05</td>\n",
+       "      <td>4.995738e+05</td>\n",
+       "      <td>1.584803e+06</td>\n",
+       "      <td>-9.873880e+04</td>\n",
+       "      <td>1.179757e+06</td>\n",
+       "      <td>1.031841e+06</td>\n",
+       "      <td>4.159367e+05</td>\n",
        "      <td>...</td>\n",
-       "      <td>9.361254e+05</td>\n",
-       "      <td>1.127648e+06</td>\n",
-       "      <td>1.259310e+06</td>\n",
-       "      <td>8.589567e+05</td>\n",
-       "      <td>1.479782e+06</td>\n",
-       "      <td>8.000593e+05</td>\n",
-       "      <td>1.123723e+06</td>\n",
-       "      <td>1.760520e+06</td>\n",
-       "      <td>4.914607e+05</td>\n",
-       "      <td>6.471767e+05</td>\n",
+       "      <td>1.372591e+06</td>\n",
+       "      <td>1.306696e+06</td>\n",
+       "      <td>6.394788e+05</td>\n",
+       "      <td>6.803029e+05</td>\n",
+       "      <td>5.756530e+05</td>\n",
+       "      <td>6.008684e+05</td>\n",
+       "      <td>2.463446e+05</td>\n",
+       "      <td>6.338162e+05</td>\n",
+       "      <td>1.040108e+06</td>\n",
+       "      <td>1.004782e+06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2022-02-11 14:00:00</th>\n",
-       "      <td>-7.901549e+04</td>\n",
-       "      <td>9.920080e+05</td>\n",
-       "      <td>1.248552e+06</td>\n",
-       "      <td>9.973602e+05</td>\n",
-       "      <td>3.706510e+05</td>\n",
-       "      <td>7.892669e+05</td>\n",
-       "      <td>1.235685e+06</td>\n",
-       "      <td>5.331243e+05</td>\n",
-       "      <td>1.387667e+06</td>\n",
-       "      <td>1.211971e+06</td>\n",
+       "      <td>9.818727e+05</td>\n",
+       "      <td>1.401407e+06</td>\n",
+       "      <td>6.278580e+05</td>\n",
+       "      <td>1.540642e+06</td>\n",
+       "      <td>7.379792e+05</td>\n",
+       "      <td>9.621891e+05</td>\n",
+       "      <td>1.303348e+06</td>\n",
+       "      <td>1.306518e+06</td>\n",
+       "      <td>6.933143e+05</td>\n",
+       "      <td>1.436222e+06</td>\n",
        "      <td>...</td>\n",
-       "      <td>1.480956e+06</td>\n",
-       "      <td>8.259945e+05</td>\n",
-       "      <td>9.107577e+05</td>\n",
-       "      <td>1.661959e+06</td>\n",
-       "      <td>1.338668e+06</td>\n",
-       "      <td>4.982817e+05</td>\n",
-       "      <td>5.063463e+05</td>\n",
-       "      <td>1.539331e+06</td>\n",
-       "      <td>8.271139e+05</td>\n",
-       "      <td>1.865608e+06</td>\n",
+       "      <td>1.673705e+06</td>\n",
+       "      <td>2.049235e+06</td>\n",
+       "      <td>6.810229e+05</td>\n",
+       "      <td>7.839749e+05</td>\n",
+       "      <td>1.888354e+06</td>\n",
+       "      <td>5.954157e+05</td>\n",
+       "      <td>5.539249e+05</td>\n",
+       "      <td>1.735490e+06</td>\n",
+       "      <td>1.495662e+06</td>\n",
+       "      <td>9.269474e+05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2022-02-11 15:00:00</th>\n",
-       "      <td>6.426911e+05</td>\n",
-       "      <td>1.237143e+06</td>\n",
-       "      <td>1.089214e+06</td>\n",
-       "      <td>1.668091e+06</td>\n",
-       "      <td>1.560656e+06</td>\n",
-       "      <td>1.719503e+06</td>\n",
-       "      <td>1.341792e+06</td>\n",
-       "      <td>1.133504e+06</td>\n",
-       "      <td>2.014883e+06</td>\n",
-       "      <td>1.603223e+06</td>\n",
+       "      <td>7.800493e+05</td>\n",
+       "      <td>6.834265e+05</td>\n",
+       "      <td>8.261629e+05</td>\n",
+       "      <td>2.505578e+05</td>\n",
+       "      <td>1.228073e+06</td>\n",
+       "      <td>1.239210e+06</td>\n",
+       "      <td>1.084346e+06</td>\n",
+       "      <td>1.147520e+06</td>\n",
+       "      <td>1.145728e+06</td>\n",
+       "      <td>1.233379e+06</td>\n",
        "      <td>...</td>\n",
-       "      <td>1.713791e+06</td>\n",
-       "      <td>7.433124e+05</td>\n",
-       "      <td>3.933410e+05</td>\n",
-       "      <td>8.715794e+05</td>\n",
-       "      <td>1.913798e+06</td>\n",
-       "      <td>1.902275e+06</td>\n",
-       "      <td>2.006757e+06</td>\n",
-       "      <td>1.587522e+06</td>\n",
-       "      <td>7.056554e+05</td>\n",
-       "      <td>5.005233e+05</td>\n",
+       "      <td>8.740778e+05</td>\n",
+       "      <td>9.273301e+05</td>\n",
+       "      <td>1.663515e+06</td>\n",
+       "      <td>1.564655e+06</td>\n",
+       "      <td>4.959054e+05</td>\n",
+       "      <td>1.722500e+06</td>\n",
+       "      <td>1.381114e+06</td>\n",
+       "      <td>9.182470e+05</td>\n",
+       "      <td>-1.350229e+05</td>\n",
+       "      <td>1.169486e+06</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -646,82 +646,82 @@
       ],
       "text/plain": [
        "                             4002          4003          4004          4005  \\\n",
-       "2022-01-01 00:00:00  1.212021e+06  8.519954e+05  7.560917e+05  1.438055e+06   \n",
-       "2022-01-01 01:00:00  8.693649e+05  9.754355e+05  5.038237e+05  1.204583e+06   \n",
-       "2022-01-01 02:00:00  7.923984e+05  1.434058e+06  5.024506e+05  1.627207e+06   \n",
-       "2022-01-01 03:00:00  1.269392e+06  1.463432e+06  1.018994e+06  1.524115e+06   \n",
-       "2022-01-01 04:00:00  5.811972e+05  1.614621e+06  9.650531e+05  9.365501e+05   \n",
+       "2022-01-01 00:00:00  1.522690e+06  7.365325e+05  1.883955e+06  1.747342e+06   \n",
+       "2022-01-01 01:00:00  8.881127e+05  1.053687e+06  3.734167e+05  1.614773e+06   \n",
+       "2022-01-01 02:00:00  9.811829e+05  1.413438e+06  9.972503e+05  1.233187e+06   \n",
+       "2022-01-01 03:00:00  1.594312e+06  1.711561e+06  7.238942e+05  6.706983e+05   \n",
+       "2022-01-01 04:00:00  4.667720e+05  1.128695e+06  1.028832e+06  5.444642e+05   \n",
        "...                           ...           ...           ...           ...   \n",
-       "2022-02-11 11:00:00  9.550081e+05  1.050358e+06  1.183558e+06  9.563775e+05   \n",
-       "2022-02-11 12:00:00  5.272977e+05  8.443402e+05  1.338616e+06  4.481988e+05   \n",
-       "2022-02-11 13:00:00  5.938971e+05  1.213851e+06  8.529911e+05  9.887598e+05   \n",
-       "2022-02-11 14:00:00 -7.901549e+04  9.920080e+05  1.248552e+06  9.973602e+05   \n",
-       "2022-02-11 15:00:00  6.426911e+05  1.237143e+06  1.089214e+06  1.668091e+06   \n",
+       "2022-02-11 11:00:00  6.554215e+05  1.519971e+06  7.346373e+05  2.468342e+05   \n",
+       "2022-02-11 12:00:00  1.059431e+06  6.340614e+05  1.400879e+06  1.494647e+05   \n",
+       "2022-02-11 13:00:00  6.521878e+05  2.955911e+05  3.741276e+05  4.800967e+05   \n",
+       "2022-02-11 14:00:00  9.818727e+05  1.401407e+06  6.278580e+05  1.540642e+06   \n",
+       "2022-02-11 15:00:00  7.800493e+05  6.834265e+05  8.261629e+05  2.505578e+05   \n",
        "\n",
        "                             4006          4007          4008          4009  \\\n",
-       "2022-01-01 00:00:00  7.396164e+05  6.948326e+05  1.278412e+06  2.304984e+06   \n",
-       "2022-01-01 01:00:00  8.941464e+05  7.513620e+04  1.137045e+06  1.708324e+06   \n",
-       "2022-01-01 02:00:00  1.164684e+06  4.291224e+05  6.576416e+05  9.367841e+05   \n",
-       "2022-01-01 03:00:00  5.695050e+05  1.577387e+06  1.525168e+05  3.880051e+04   \n",
-       "2022-01-01 04:00:00  1.209160e+06  3.318855e+05  3.351287e+05  1.444800e+06   \n",
+       "2022-01-01 00:00:00  1.235460e+06  1.250241e+06  1.067713e+06  1.307628e+06   \n",
+       "2022-01-01 01:00:00  1.348900e+06  3.942241e+05  9.418381e+05 -1.287045e+05   \n",
+       "2022-01-01 02:00:00  1.295709e+06  3.746883e+05  1.720246e+06  1.248101e+06   \n",
+       "2022-01-01 03:00:00  2.852392e+05  8.300269e+05  1.148656e+06  1.037572e+06   \n",
+       "2022-01-01 04:00:00  1.052969e+05  5.439632e+05  1.916725e+06  1.075958e+06   \n",
        "...                           ...           ...           ...           ...   \n",
-       "2022-02-11 11:00:00  9.167803e+05  7.077838e+05  5.764765e+05  1.628767e+06   \n",
-       "2022-02-11 12:00:00  1.426800e+06  2.918600e+05  1.875643e+06  1.500691e+06   \n",
-       "2022-02-11 13:00:00  1.508931e+06  1.097557e+06  6.580392e+05  1.490143e+06   \n",
-       "2022-02-11 14:00:00  3.706510e+05  7.892669e+05  1.235685e+06  5.331243e+05   \n",
-       "2022-02-11 15:00:00  1.560656e+06  1.719503e+06  1.341792e+06  1.133504e+06   \n",
+       "2022-02-11 11:00:00  1.391215e+06  2.756525e+05  1.064843e+06  1.632632e+06   \n",
+       "2022-02-11 12:00:00  8.775668e+05  1.161970e+06  9.090381e+05  6.548579e+05   \n",
+       "2022-02-11 13:00:00  4.995738e+05  1.584803e+06 -9.873880e+04  1.179757e+06   \n",
+       "2022-02-11 14:00:00  7.379792e+05  9.621891e+05  1.303348e+06  1.306518e+06   \n",
+       "2022-02-11 15:00:00  1.228073e+06  1.239210e+06  1.084346e+06  1.147520e+06   \n",
        "\n",
        "                             4010          4011  ...          5992  \\\n",
-       "2022-01-01 00:00:00  9.588319e+05  9.406021e+05  ...  2.109739e+05   \n",
-       "2022-01-01 01:00:00  1.342389e+06  1.959986e+06  ...  3.954700e+05   \n",
-       "2022-01-01 02:00:00  8.624529e+05  7.692469e+05  ...  1.044997e+06   \n",
-       "2022-01-01 03:00:00  1.383405e+06  5.596274e+05  ...  8.182543e+05   \n",
-       "2022-01-01 04:00:00 -2.583068e+05  1.052083e+06  ...  4.259355e+05   \n",
+       "2022-01-01 00:00:00  1.168910e+06  1.218901e+06  ...  1.589131e+06   \n",
+       "2022-01-01 01:00:00  7.848680e+05  1.169359e+06  ...  4.982993e+05   \n",
+       "2022-01-01 02:00:00  4.639225e+05  9.123818e+05  ...  1.866030e+06   \n",
+       "2022-01-01 03:00:00  1.086457e+06  1.633151e+06  ...  1.190132e+06   \n",
+       "2022-01-01 04:00:00  9.885185e+05  1.375559e+06  ...  5.633235e+05   \n",
        "...                           ...           ...  ...           ...   \n",
-       "2022-02-11 11:00:00  1.062615e+06  1.755868e+06  ...  1.557175e+06   \n",
-       "2022-02-11 12:00:00  1.178919e+06  7.893541e+05  ...  7.506101e+05   \n",
-       "2022-02-11 13:00:00  2.179459e+06  1.281627e+06  ...  9.361254e+05   \n",
-       "2022-02-11 14:00:00  1.387667e+06  1.211971e+06  ...  1.480956e+06   \n",
-       "2022-02-11 15:00:00  2.014883e+06  1.603223e+06  ...  1.713791e+06   \n",
+       "2022-02-11 11:00:00  2.255325e+06  3.975464e+05  ...  3.516876e+05   \n",
+       "2022-02-11 12:00:00  5.131747e+05  2.268062e+05  ...  3.092005e+05   \n",
+       "2022-02-11 13:00:00  1.031841e+06  4.159367e+05  ...  1.372591e+06   \n",
+       "2022-02-11 14:00:00  6.933143e+05  1.436222e+06  ...  1.673705e+06   \n",
+       "2022-02-11 15:00:00  1.145728e+06  1.233379e+06  ...  8.740778e+05   \n",
        "\n",
        "                             5993          5994          5995          5996  \\\n",
-       "2022-01-01 00:00:00  1.220735e+06  9.715073e+05  1.463336e+06  3.436582e+05   \n",
-       "2022-01-01 01:00:00  6.418734e+05  1.166324e+06  1.218541e+06  1.256374e+06   \n",
-       "2022-01-01 02:00:00  8.009140e+05  1.240692e+06 -2.777931e+04  9.717390e+05   \n",
-       "2022-01-01 03:00:00  1.632945e+06  1.010543e+06  4.009558e+05  1.478580e+06   \n",
-       "2022-01-01 04:00:00  2.095648e+06  1.368940e+06  1.935897e+05  1.291826e+06   \n",
+       "2022-01-01 00:00:00  1.702425e+06  1.148132e+06  8.532146e+05  7.044042e+05   \n",
+       "2022-01-01 01:00:00  9.892282e+05  6.087048e+05  1.143115e+06  1.496269e+06   \n",
+       "2022-01-01 02:00:00  1.744288e+06  1.412359e+06  7.322985e+05  8.552735e+05   \n",
+       "2022-01-01 03:00:00  1.383107e+06  7.801834e+05  9.776243e+05  2.293418e+06   \n",
+       "2022-01-01 04:00:00  5.196102e+05  4.177027e+05  1.353726e+06  7.087020e+05   \n",
        "...                           ...           ...           ...           ...   \n",
-       "2022-02-11 11:00:00  9.978829e+05  1.428223e+06  9.375576e+05  1.544223e+06   \n",
-       "2022-02-11 12:00:00  1.146763e+06  8.711101e+05  8.625724e+05  7.775495e+05   \n",
-       "2022-02-11 13:00:00  1.127648e+06  1.259310e+06  8.589567e+05  1.479782e+06   \n",
-       "2022-02-11 14:00:00  8.259945e+05  9.107577e+05  1.661959e+06  1.338668e+06   \n",
-       "2022-02-11 15:00:00  7.433124e+05  3.933410e+05  8.715794e+05  1.913798e+06   \n",
+       "2022-02-11 11:00:00  9.236746e+05  1.067935e+06  1.237977e+06  4.839377e+05   \n",
+       "2022-02-11 12:00:00  8.351009e+05  1.194604e+05  1.132886e+06  3.542770e+05   \n",
+       "2022-02-11 13:00:00  1.306696e+06  6.394788e+05  6.803029e+05  5.756530e+05   \n",
+       "2022-02-11 14:00:00  2.049235e+06  6.810229e+05  7.839749e+05  1.888354e+06   \n",
+       "2022-02-11 15:00:00  9.273301e+05  1.663515e+06  1.564655e+06  4.959054e+05   \n",
        "\n",
        "                             5997          5998          5999          6000  \\\n",
-       "2022-01-01 00:00:00  1.764624e+05  5.271467e+05  9.022588e+05  1.055085e+06   \n",
-       "2022-01-01 01:00:00  1.747930e+06  1.375117e+06  5.358348e+04  1.628927e+06   \n",
-       "2022-01-01 02:00:00  1.261385e+06  8.674137e+05  1.158677e+06  1.320565e+06   \n",
-       "2022-01-01 03:00:00  5.612716e+05  1.245279e+06  1.028181e+06  1.294013e+06   \n",
-       "2022-01-01 04:00:00  1.599473e+06  1.193099e+06  1.676480e+06  6.758581e+05   \n",
+       "2022-01-01 00:00:00  8.186826e+05  8.116150e+05  7.100930e+05  1.203160e+06   \n",
+       "2022-01-01 01:00:00  1.504554e+06  4.250855e+05  9.431208e+05  1.697681e+06   \n",
+       "2022-01-01 02:00:00  9.632037e+05  1.006114e+06  6.947516e+05  7.969410e+05   \n",
+       "2022-01-01 03:00:00  9.743710e+05  1.804552e+06  7.211640e+05  1.145045e+06   \n",
+       "2022-01-01 04:00:00  7.139034e+05  8.842609e+05  7.882466e+05 -8.232680e+04   \n",
        "...                           ...           ...           ...           ...   \n",
-       "2022-02-11 11:00:00  1.230698e+06  6.241062e+05  1.172571e+06  1.420599e+06   \n",
-       "2022-02-11 12:00:00  7.721788e+05  1.647198e+06  1.898852e+06  7.778365e+05   \n",
-       "2022-02-11 13:00:00  8.000593e+05  1.123723e+06  1.760520e+06  4.914607e+05   \n",
-       "2022-02-11 14:00:00  4.982817e+05  5.063463e+05  1.539331e+06  8.271139e+05   \n",
-       "2022-02-11 15:00:00  1.902275e+06  2.006757e+06  1.587522e+06  7.056554e+05   \n",
+       "2022-02-11 11:00:00  1.140204e+06  1.391819e+06  1.668330e+06  6.788123e+05   \n",
+       "2022-02-11 12:00:00  8.243507e+05  6.221985e+05  1.249335e+06  8.687152e+05   \n",
+       "2022-02-11 13:00:00  6.008684e+05  2.463446e+05  6.338162e+05  1.040108e+06   \n",
+       "2022-02-11 14:00:00  5.954157e+05  5.539249e+05  1.735490e+06  1.495662e+06   \n",
+       "2022-02-11 15:00:00  1.722500e+06  1.381114e+06  9.182470e+05 -1.350229e+05   \n",
        "\n",
        "                             6001  \n",
-       "2022-01-01 00:00:00  1.166126e+06  \n",
-       "2022-01-01 01:00:00  8.230403e+05  \n",
-       "2022-01-01 02:00:00  1.354277e+06  \n",
-       "2022-01-01 03:00:00  1.162580e+06  \n",
-       "2022-01-01 04:00:00  5.690138e+05  \n",
+       "2022-01-01 00:00:00  1.149239e+06  \n",
+       "2022-01-01 01:00:00  1.585010e+06  \n",
+       "2022-01-01 02:00:00  1.487227e+06  \n",
+       "2022-01-01 03:00:00  1.421976e+06  \n",
+       "2022-01-01 04:00:00  1.445546e+06  \n",
        "...                           ...  \n",
-       "2022-02-11 11:00:00  9.502391e+04  \n",
-       "2022-02-11 12:00:00 -7.752296e+03  \n",
-       "2022-02-11 13:00:00  6.471767e+05  \n",
-       "2022-02-11 14:00:00  1.865608e+06  \n",
-       "2022-02-11 15:00:00  5.005233e+05  \n",
+       "2022-02-11 11:00:00  1.408043e+06  \n",
+       "2022-02-11 12:00:00  2.072785e+05  \n",
+       "2022-02-11 13:00:00  1.004782e+06  \n",
+       "2022-02-11 14:00:00  9.269474e+05  \n",
+       "2022-02-11 15:00:00  1.169486e+06  \n",
        "\n",
        "[1000 rows x 2000 columns]"
       ]
@@ -737,7 +737,7 @@
     "load_id = input_data[ComponentType.sym_load][\"id\"]\n",
     "load_p = input_data[ComponentType.sym_load][\"p_specified\"]\n",
     "profile = np.tile(load_p, (n_scenarios, 1)) + 5e5 * np.random.randn(n_scenarios, n_loads)\n",
-    "dti = dti = pd.date_range(\"2022-01-01\", periods=n_scenarios, freq=\"H\")\n",
+    "dti = dti = pd.date_range(\"2022-01-01\", periods=n_scenarios, freq=\"h\")\n",
     "df_load_profile = pd.DataFrame(profile, columns=load_id, index=dti)\n",
     "display(df_load_profile)"
    ]
@@ -786,7 +786,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Execution time for Validating Batch Data is 1.695239 s\n"
+      "Execution time for Validating Batch Data is 2.216290 s\n"
      ]
     }
    ],
@@ -807,7 +807,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Execution time for Batch Calculation using Newton-Raphson is 2.420980 s\n"
+      "Execution time for Batch Calculation using Newton-Raphson is 1.261293 s\n"
      ]
     }
    ],
@@ -827,7 +827,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Execution time for Batch Calculation using linear calculation is 0.363697 s\n"
+      "Execution time for Batch Calculation using linear calculation is 0.610796 s\n"
      ]
     }
    ],
@@ -856,7 +856,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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Ro0eH0zVp0gS33XYbnnzySZSXl+PUU0/F559/jvnz5+O9995jmuXee+89NGrUyPGIzkQ1J1bLtAjCa4SWHfP+7dixQ1EURVm2bJkydOhQJTMzU8nIyFBOP/105ddff9XkVVJSovzzn/9UGjZsqNSoUUPp16+fsnDhwojlvIqiKNu2bVMuuOACJSMjQ8nJyVFuvfVWZebMmcJLwZ988smIewFjOfKHH36otG/fXklLS1M6deqkfPnll8qll16qtG/fXuj5vPDCC0r79u2VlJQUJS8vTxk7dmzEsl23loLrl+fPnTuXudx57ty5ytChQ5Xs7GwlPT1dad26tTJq1ChlyZIlQvdYv359BYBSUFAQPrZgwQIFgDJgwICI9Pp3oiiK8uuvvyo9evRQUlNTNe9h5MiRSs2aNSPyYD0HFnbaDi8/o/auZ/Xq1crZZ5+tZGRkKLVr11auvvpqJT8/PyJdIBBQJk+erDRv3lxJTU1VOnbsqLz77rvMOqxbt04BoEyYMMH0/glCBp+iJJDXIUEQUnTr1g25ubmYNWtWrKtCEAThGORzQxDVgPLyclRUVGiOzZs3DytXriRzAEEQCQdpbgiiGrB161YMGTIE11xzDRo1aoR169Zh6tSpyM7OxurVq1GvXr1YV5EgCMIxyKGYIKoBderUQY8ePfD6669j3759qFmzJoYPH47HHnuMBBuCIBIO0twQBEEQBJFQkM8NQRAEQRAJBQk3BEEQBEEkFNXO5yYYDGL37t2oVatWVEOlEwRBEARhHUVRcOTIETRq1Mh0j7dqJ9zs3r07vP8PQRAEQRDxxY4dO9CkSRPDNNVOuKlVqxaAyocT2geIIAiCIAhvU1RUhKZNm4bncSOqnXATMkVlZWWRcEMQBEEQcYaISwk5FBMEQRAEkVCQcEMQBEEQREJBwg1BEARBEAkFCTcEQRAEQSQUJNwQBEEQBJFQkHBDEARBEERCQcINQRAEQRAJBQk3BEEQBEEkFCTcEARBEASRUJBwQxAEQRBEQkHCDUEQBEEQCQUJNwRBEARBJBQk3BAEIUxJeQDBoBLrahAEQRhCwg1BEEIUlZSj46TvccnLv8a6KgRBEIaQcEMQhBC/bNyPQFDBih2Fsa4KQRCEISTcEARBEASRUJBwQxAEQRBEQkHCDUEQBEEQCQUJNwRBEARBJBQk3BAEQRAEkVCQcEMQBEEQREJBwg1BEARBEAkFCTcEQRAEQSQUJNwQBEEQBJFQkHBDEARBEERCQcINQRAEQRAJBQk3BEEQBEEkFDEVbn7++Wecf/75aNSoEXw+Hz7//HPTa+bNm4dTTjkFaWlpaNOmDd566y3X60kQBEEQRPwQU+GmuLgYXbt2xYsvviiUfsuWLRg+fDhOP/10rFixArfddhuuv/56fP/99y7XlCAIgiCIeCE5loUPGzYMw4YNE04/depUtGzZEk899RQA4OSTT8aCBQvw3//+F0OHDnWrmgRBEARBxBFx5XOzcOFCDBkyRHNs6NChWLhwIfea0tJSFBUVaf4RBEEQBJG4xJVwk5+fj7y8PM2xvLw8FBUV4fjx48xrpkyZguzs7PC/pk2bRqOqBEEQBEHEiLgSbqwwceJEHD58OPxvx44dsa4SQRAEQRAuElOfG1kaNGiAgoICzbGCggJkZWWhRo0azGvS0tKQlpYWjeoRRELj88W6BgRBEGLEleamT58+mD17tubYrFmz0KdPnxjViCCqD4oS6xoQBEGIEVPh5ujRo1ixYgVWrFgBoHKp94oVK7B9+3YAlSalESNGhNPfdNNN2Lx5M+666y6sW7cOL730Ev73v//h9ttvj0X1CYIgCILwIDEVbpYsWYLu3buje/fuAIAJEyage/fueOCBBwAAe/bsCQs6ANCyZUt88803mDVrFrp27YqnnnoKr7/+Oi0DJwiCIAgiTEx9bgYPHgzFQNfNij48ePBgLF++3MVaEQRBEAQRz8SVzw1BEARBEIQZJNwQBEEQBJFQkHBDEARBEERCQcINQRAEQRAJBQk3BEEIQUH8CIKIF0i4IQiCIAiCy5crd+OrlbtjXQ0p4mr7BYIgCIIgosfR0grc8kFl+JUz2tdHzbT4EBtIc0MQBEEQBJNjZRXh32UVwRjWRA4SbgiCIAiCSChIuCEIgiAIgokP8bmSgIQbgiAIgiCYKOBvkeRlSLghCIIgCCKhIOGGIAiCIIiEgoQbgiCkUZT4VFUTBGGdeArkScINQRAEQRAJBQk3BEFIQ4obgiC8DAk3RFywdncRHvxyDQ4Wl8W6KgRBEITHiY84ykS159zn5gMA8g+XYOq1PWJcG4IUNwRBeBnS3BBxxZ/5RbGuAkEQBOFxSLghCEIaWi1FENWEOO3qJNwQBCFNnI53BEFUE0i4IQiCIAiCjSq2TTwpbEm4IeKKeOpciQy9B4IgvAwJNwRBEARBmBJP3zQk3BBxRbzuUJto0HsgiGpCnHZ1Em4IIsZsKDiCuz9ehZ2HjsW6KgRBEFziaZUkBfEjiBhz/vMLUFoRxOrdh/HNLQNiXR0h4miMIwiiGkKaG4KIMaUVQQDA2j0UoJAgCG+hcH57HRJuiLiCNAYEQRCxIZ7GXxJuiLginjqXLPF0b/FUV4IgrBOvfZ2EG4IgCIIgmKhXRsbTKkkSbgiCkCaeBjmCIKofJNwQBEEQBMFEiVOPYhJuCIIQpGqTmXi1wxMEIUe8dnUSbgiCIAiCMCWeBB0SbgiCkCaeBjmCIKyjjkocTxpbEm48zp7Dx/H0rA3YW1QS66oQBEEQ1Yx4EmjU0PYLHmfktEXYUHAUP63fiy/G9491dWJOPO1tksjQeyCI6kc8rZIkzY3H2VBwFACwcufhGNeEIBTGL4IgCO9Bwg0RV9CkShAEET3UStp4UtiScEMQhDTxNMgRBOEM8dTtSbghCIIgCIJJPPnZqCHhhiAIeeJzvCMIQhKtWSp+Oj4JN0RcEUd9iyCw4+AxjHpzEX7dtD/WVSGIagUJNwRBCKLafoFUN0L886OVmLd+H656/fdYV4UgLKHZWiqOuj0JN0RcQZMqEU8UUPBNIs6JJ1OUGhJuCIKQJk7Hu6jjM09CEIQLkHBDEIQ0JNsQRPWAzFIEEQXiqXMRhM9HuhsivonXMZeEG4IgpIlXOzxBENaJJ59HEm6IuCJ+uhZBkM8NkQjE56hLwg1BENLE53AXA0i6IeIc2luKIIgEJ45GNoIgqjUxF25efPFFtGjRAunp6ejduzcWLVrETVteXo6HH34YrVu3Rnp6Orp27YqZM2dGsbYEQQDx9QVnRkUgiCMl5a7kTYobb/Lx0p2455NVCAQTqCG7hML57XViKtzMmDEDEyZMwKRJk7Bs2TJ07doVQ4cOxd69e5np77vvPrzyyit4/vnnsXbtWtx00024+OKLsXz58ijXnIgViTSpxhuJ+uyHPTsfnR/8AfuPljqeN62W8iZ3fLQSHy7ega9X7Y51VTwP7S1lgaeffhpjxozB6NGj0aFDB0ydOhUZGRmYNm0aM/306dPxr3/9C+eeey5atWqFsWPH4txzz8VTTz0V5ZoTRPUmnlZNmLFx71EAwM8b9jmeN4k23ubwcXc0dkTsiZlwU1ZWhqVLl2LIkCFVlfH7MWTIECxcuJB5TWlpKdLT0zXHatSogQULFnDLKS0tRVFRkeYfQRDyKNw/CIJIVNQfMvHU7WMm3Ozfvx+BQAB5eXma43l5ecjPz2deM3ToUDz99NPYuHEjgsEgZs2ahU8//RR79uzhljNlyhRkZ2eH/zVt2tTR+yAIguBBViki3okjS5SGmDsUy/Dss8+ibdu2aN++PVJTUzF+/HiMHj0afj//NiZOnIjDhw+H/+3YsSOKNSacJ057WgKgsb3HrhoE4RjxOnHHinh6XjETbnJycpCUlISCggLN8YKCAjRo0IB5TW5uLj7//HMUFxdj27ZtWLduHTIzM9GqVStuOWlpacjKytL8IwiCiAY+8roh4hwlTu3RMRNuUlNT0aNHD8yePTt8LBgMYvbs2ejTp4/htenp6WjcuDEqKirwySef4MILL3S7uoRHiKcvh0RDY3un9yAEmaWIeCdeFw8kx7LwCRMmYOTIkejZsyd69eqFZ555BsXFxRg9ejQAYMSIEWjcuDGmTJkCAPj999+xa9cudOvWDbt27cKDDz6IYDCIu+66K5a3QRDVAhJoCKJ6E09jQEyFm8svvxz79u3DAw88gPz8fHTr1g0zZ84MOxlv375d409TUlKC++67D5s3b0ZmZibOPfdcTJ8+HbVr147RHRCJwModhXj7162465z2aJCdbn5BFHlx7iZ8tXI3ZtzQB9kZKbGuTph4/ZojCEKOeBJo1MRUuAGA8ePHY/z48cxz8+bN0/w9aNAgrF27Ngq1IryKG/3swhd/AQDsOVyCD244zYUSrPPk9+sBAG8s2IwJZ7eLaV3idIyLKRTEL7b8vGEfGtepgda5mbGuSkIQT2NAzIUbgvAKm/cfjXUVuJQGgrGugoZ4/ZqLNiTaxI7Vuw5jxLTK7Xy2PjY8xrUhok1cLQUnCDfDf3t6ZYsHhAn1s/dAdeICUtzEjjW7D8e6CgkB7QpOVCtow7noQk/bfeJp4CaIaKGNUBw/nYSEG0Ka7/7Yg5Pvn4nv/uBHho5HvPyV7bUN67xWH4IgCDUk3BDSjH1vGcoCQYx9b1msq1JtIFkiPvGywEwQIpBZiiCigL5vBYIKvlm1B7sLj8ekPtHCC2NKvA5yscTTflwEIUC8dnUSbqoJq3cdxs8b9sW6Go7z4eLtGPf+Mgx6cm6sq+IqJEzEJ6S5IRKJeBqHSLipJpz3/AKMmLYI2w4Ux7oqjjJ/w34AQHnAfq/z8jzkBUc+L9QhWiiKgs37jiJIjvNENUfEv05RFIx+cxEuf2WhZ/zxSLipZmw7cCzWVSAs4JHxotrw2vzNOOOpn3DfF6tt5eNlgZkgRFA0v9kDUWlFEHPX78PvWw5i5yFvuAiQcFPNCMT5LOlm9SmarDHVyefmP99vAAC8//t25vlnf9yIM/4zD4eKy4wzojZFJBDx1O9JuKlmeE3Nvnz7IYx6cxE2FhyxdH11mTtkVb0HjpZi3HvLXPOzqk4mKhb//XEDNu8vxmvzNxumqybNk0hgZAWaXYXH8b8lOzB33V53KiQICTcO8sWKXRg5bREOHyuPdVW42A2+t2mvNSGEx8Uv/Yp56/dh1JuLhdJ7xZ4bbWTv+pGv1+KbP/aEw887Uofq+egNiXdNaHWnuo4ncsg9o9W7DuOuj1fh+TkbXaqPGCTcOMitH67ATxv24bkYv1QjgjY686y1BRjy9M8O1qaKXQm+lNsusq9td2GJOxU5Ac0JlfhNVIfVRbNIEHpibeYn4cYFio57WXNj/doPF7H9Dwj38YIZKPY1iCKC47LfJB3JNvHL/I378MyPGzxnyo82Ir52rOOxbvu0K7gLmH3NxRI7avRYS+IsnKySB28vjOxrc1sYSvjhXvAGzTU3Hm5UhCHXvlFp0m2ZUxMXdmsc49rEDpHVUpr9p078jHXTJ+HGBfwe1ofZ+QqJdWMFqsGkeoJdhcfx9crd4b9l79sNsxH5J0TigS5BuAyZzM3RaHdOjFaxjs5Nwo0LePlrzY5DsZkKPipUk/n14hd/wd4jpeG/vSZXJIqgo74PS3dkprmxkqcH+HLlbvyycT/+fXEnpCR5+GstCsR6ko41QmYpVnrS3CQenhACONhxKPaiuS1RBx61YFOJ3HtzQ/RIDHFGC7c7OOVzE6fN85YPlgMAujatjat6N4txbWJLvL5Dp5D9kAl9P8d6HqzeIrlLeFEICGFHuPHwbTmCl+/PE4oShfkzrrF7H6Y+N3EufB8s1gvZiYWIlj3Wk7SX4PUXrQbUG2YpEm5cwMvCTYUdn5s4H6jN8PL9STsUuywNeULYcgC7z4kmvsTHy+NCNBDpISyzVKynQRJuXMDLwo2dVY1euK0EmVOlkV395I5ZKvGevt078rJ/HeEM1f0Va31uOKulWEvBSbhJPLz8NWdvtZSHbyzB8Z6mxHMVsoTd52raJajLEAkEt7swBKBYa7xIuHEBv4elG3tmKSJWeGMpuPN5xhq72ihzn5vYc6i4DM/P3oidh47FuiqeQNYUWd0/6kT6iBfj3JBw4wIiZqmyChuhgm1gx8cg1o3Vbbx8f14TLLxWH6vYvY94WC11x0cr8dSsDbhs6sJYV8UTyL5zD3+rRgfJCMVeGRpIuHEBswFt2fZDOOm+7/D0D+ujUyEV9uLcxL6XRwhnsa9SVPCGzw2hxwt9woxf/toPANhz2N39xryGfqj4ZOlOfLRkh3Q79v4bjj2sZxprjRcJNy5gJuk//NVaAMBzczZFoTZabJmlBNpquZ3NqyzgZPfx8iAmrWFwe7WUq7lHD7c1ULH2O/BKHdT8uLYAk75YHdWx4nhZAP/8aCXu/HgVDkvu/RfrSTrWKAZ/hY8qDLOUazUSg4QbF0jyWGfQNjz3loK/PO8vnHTfd1i67ZDlMsxIlElVFi9EBPZAFRzHbZ+beMeNif36d5bg7YXboroRr9oN4Hh5IPx7X0SwzEi8+IpLygM4XhYwT+gAIv1enSQUSy3Wz42EGxcwGxBiOUfY+Vgy00g9PnMdFAW497M/rBdCMPGaXJEogg7vPvRN/fDxcjz1w3ps2ntEczwefG7s1MFNoTq/KIpmMtUzUK8YfWHuJjw3e6PopZ4gEFTQ+cHvcfIDM6OuKRcSdE4kirXgT8KNC8i81HcWbsX3a/JdrI22QdrbFdyByniYRFI/ux3nJlFi3ojexUNfrsHzczZhyNM/a46btRkvNCkPVIGJV8xlT8/aYJzACy9RxdHSCpQHKlvugaNlrpen7fecNKoTQTJLJS6m3vWqlvDAF2tw4/SlrtZHozKkCMVxiXyEYnfqkWhwg5Lp/l6+o5CZzlRz42CfKSkP4KuVu3H4WPR8RtwU+KMpM6jLkt2CxnOrpVTVj8YzFDNLVSUis1QCYxbnJqZmKTsbZ3qgtbg5aXttDFPjBVlFZHfgeEMbNl7sptTpoqnte+TrtfjHB8sx6q1FUtd5uV3HAtm266SAWlYRxOpdh22Z+9SCRLTfrb7apRUB3Pf5H5j9596qNOFfsW15tCu4C8Ta1qhH3ZHsaG5i3VirM7KDYaKYjdxG1OdG/bci8eXs5FDw+fJdAIDl2wvlLqRuqzObyAbxc64et3ywHDPX5OPec0/GmIGtLOWhqX40NDcG56Yv3IZ3f9M6hpPmJsFQTz5masxof/Wqi7MT5ybWjRWInLQTyU/GCC+IKqzN8eIewftgrQYBvPchw8KrNYxqvWwEmXOynjNP+Fe+On+z5Ty0so37T9FotW0+I3YSLQVPMNQyg9mAx/qqtqdREceWQ7GD9SAkIZ8bV5D9ige0fch8tVTse42+DtsPHMOCjftjVBsVUXw2QYMJ2oxoVHP1rsN4ce4mocj1sQwL8fbCrSgpN16CHprLYt30ySzlEEGNHd44LattBhQFfpfEB41KNs4jFLuKh29POkKxK8ul4me11N4jJchKT0F6SpJhOtG74JulPNxoTqCv4sAn5wIAPr25L05pVicGNYo+Ws2b3LVuvGN9juc9vwAAkJLkww0DWxteG4hyP1SX8O0f+WhWdyPuGdaemz5Uv1gvQCHNjUOozT1WhAARc5FVk5K6A9hyKPbAOF5tHYq9LUt4it2Fx9Hr0dnoM2W2aVphJ2LVb82HjMl1XmhTvDqs4qwAixZuPxveO5N3KHYe3hTx554j7BMA9hw+juLSCm39ozEu6MpY+Jex1o82zkwwgjZ9bkQEl1d/tm6nrSrH+rVe/Er1Xo3cQXopuBt1UP/2sLD1y6bKwfeQwJJpK7ch8yHjhS7D67cefoWOE5TUdthZEVdSHnDcdLTz0DH0mTIHvSfP1rS/KHkzSBG691i3fRJuHELd4JIsLAUX0ai89/s22WpVlueQWcpqYw0EFfy4tkAo1LkZHuzLUcHrZiAvIfOkRHczVjd9jX+dyQiqvu7w8XIhnwqn8YB8xSSak59sGAP1O5ap5l/7jqL9/TNxzyfORmn/9a8DACoD+MkKanaRLSMcxI8iFCcGQdWYZeWliggdTnwM2HMottZY31+0Hde/swRDn/nZMF3+4RKsiLGq3KvIyqRuOB16WVtjFc3AbbDEmxcPR6ZPdH3oB5zx1Dy5CjpArL+geUTTJ0MtEIg4kcv4UKp55ae/AAAzluwQv0gAjXCtmmuioblZseOw5m/Nai3GswkvBXexTiKQcOMQ2hUU8q9VZLduJyYstRB1sLiMuZSPh9VB8se1BeHyjDhtymxc9OIvWLu7yFpBNon1l4YRXhAsWDv/ehIp1Y36p9j9qbW0sk1m56Hjchc4Ascs5eV36DCymht1GpnxXPSZygp26rHJzsovK5jtvaWHNDcJhsyAx2qQIpobq1I6r/2f8sgsnDZlNopKxMK5R8uheOm2g8Jp7fafzfuOVuVlLyuXqUYzkU1k1OhW/Ig0JgtTnxvvtqrq1KJkHYqtam6iQcDjHxkKaW4SCzve+ICY5sZKTA7AfLDffuCYUD5WB2rZWhumd7gzn/HUT85m6BJeGMS0izQ8UCEOMs+K53Nj1NRlvpZjPcAD3pucQ8TK50ZkHLXa39zqFepHdenLv1aVF4NuaFYmRShOMNSaG7OB3+pqKSc0N3b6QrSCR8V6Iq8IBHHJS79gwv9WxLYiKqQFRIELZizejmvf+B1HBDV3iYioKUqNuh+a9YlYD/CANwQsFtGslz2fG289wULVKkCrH7xuUlxWGeQv1k+NhBuHsNvIxL4m5MvYsr9Y2OxkRrSWHUZPiGKXs2TbISzbXohPl+2KSj1EcGNvqbs/+QPzN+7Ha4IhBuJl40zrq6XErrTjlB8LPDY3xwSt5sY8vUwsI145Rjj1TmIh3Jj1k29W7QEQe6GQIhQ7hNqD3ay9sRqHkEOxZJ027T2KIU+zzS5WnENFO5Ld/hat7qp/5KG+GIvluma4+UwOH08szY2UWUr1W1R4lwunEDnAl5QHcLwsgDo1UyXysY6dVUlPfr8eYwe1ht8Fh7tozn2ymht1CimHYsGeKnvrvCp4WcyOtUxNmhuH0IbENobVt8QciuWa8q+MSJIhocaKABKtjwSjcpz09eA9z4qg94QbWaxO8KLpvDyoSjkUW1BHyVzCmpQGPDEX3R+Z5UjcJxG4E6Pg/f6+RdzB36uoh1ehsBua0B4uVMghYrnPlCnkc5MYBILyg6QaIYdiB+1CVtSZUTMXSaS103/0zyD0hVse8N6A4bUxzNODqgRW/NFkzFKs9hkSahZJCg1W1fx25xizjRKtEk2zhaLR3Jint2zusau15pTLF1DtlWcFt5a7Ow0JNw4h0xlYKUUciqVD8BtqQNS/xTK27tAsd+G/v1lrkJf2b7MBUlEUbvm8alV4UbhxMb3o64kXgcbyvGTBPOvlVWNEFTJO4JXpq9J4YU89nqDgxe0XQsT6uZFw4xDa1VLGMOPcSHY4q4RysGSWitJArijAunz7gfwqAkEMe3Y+bpi+lFsO8zoPmqWkHYqlhG0LWjzpK6KHZYdiwcjDMv5qXjBpxNqx0wvIbh5s+UOOcWz59kN4ce4mVKg29pN9J3yfG+/2xFg3O3IodgiNcGOhvYnFuZHPl4fdJbBuU1xqXxW+bHsh1uUfwbp89k67XJ8bD2pu3CROFDKuoOkHnON67Gw+awenNWfCGjvBCbSkPIBHv/kTZ3XIw8CTck3TR9WhWHLLArPxcdbaAqQl+4Xu8+KXKuPS1Ep3frqNxXeY+nkYCWlklkoQ7JqlhJzcJKV040BkUlmduCaas6D9ssxMfRE+Nyeel5Oam92Fxx15btImSZfShq/xskAk0xctuMrJBOw0GuCjNblHq5zX52/G9N+2YcS0RULpvby3lFGSA0dLMeadJRgxbZGUH+R6zkeWHWKtuTEa20hzkyBoNTfyDc7NIH5q7ExK0ZzQeGXJVMFsEOM9T7sOxWUVQUz7ZQvW7SnC5yt24x9ntME/z25nK083BzFxnxvXqhAzFM5vI2Q+ZJz+wLBCtCYZ1r5Z5YEgUpJi8w3NE1xlV6bqUxce1wbR8wsKaW68bi/3yVgLN6S5cQiNw5pZYkYCMYdi51qyFf8d4Tg3gt34aGmFQVmcvCXqbfZMeXmpbeNWnvlbv27BY9+tw+crdgMAnp+zyTC9yCAgrUySqrYl3Y2Fa6KDnM8N+6PESKugiWllkn+sB3jAvobE6rDzwpyNOOm+77BiR6Gt8q2iHoe0mhvza43SqJ+mPpnReOGGIOK2cMO6H/URY9+ham6WevHFF9GiRQukp6ejd+/eWLTIWKX5zDPPoF27dqhRowaaNm2K22+/HSUl4jtbu0WLehnh3+ZB/CJx08mNWQcZYcyF8n/9az86Tfqee94JQc7cLMU+XmHTf2r1Lud3NZfV3Fh1qnWyDrHCjRg/apzalTnRzFJ6/vPDBigKMOnLNczzbteLN8bJRoM3WqEp9/pVwrPkvfOECLcjFNvJPtaCfUyFmxkzZmDChAmYNGkSli1bhq5du2Lo0KHYu3cvM/3777+Pe+65B5MmTcKff/6JN954AzNmzMC//vWvKNc8knqZaTi/ayPL17u5caYaRfdfGZzsSI9/t87wvGhJRv3HrL68iUltlrJyx9IDl0AaN8cwazGPXKiIQ7De6ydLd2Le+shxRdTnRhsnRcIsFetIZuC3L1FhVTiuCaegWD0BnkAjIpBqBSOdbx4nX32Zetxw/uWVd6yMrxV3In8RYt3yYyrcPP300xgzZgxGjx6NDh06YOrUqcjIyMC0adOY6X/99Vf069cPV111FVq0aIGzzz4bV155pam2J1qEXqZZg2AuBXchzo1oHYS/Pj3gcyODrOYm9HUUUI1CViZ+Nzq1F2QJK9q+WJN/uATr84/gnx+txKg3FzNSqAVZsbuSMkE72BgsB/GL9Sc0B1atNu09ige/XIOCIge08ZwxTmS1m1G/Vz9OdbJdhcfxxQlTNLM6NnoN7w2y6rl8+yF0eOB73Pf5H5bLC8E0SwmOibFudjETbsrKyrB06VIMGTKkqjJ+P4YMGYKFCxcyr+nbty+WLl0aFmY2b96Mb7/9Fueee25U6mxG6GWavXymWSrK0Zhirbkxgxt4TyIPWc1NqC9qNDcWblk+hoVAesl6SMW5iRdJRRD17Zw2ZTbOfW4+P60q8ay1BRj+3HxsLDBe1eLFnZiNiN4cYz92ywUvLMBbv27FPz5Ybrs2Ws2N+recC0CEWUp1n2qBZbhBO9PnKW+WYh9n3cp/f9wIAHj3t+1yhbDy5x1XFFz/9mK8arDpbqy1lpZWS1188cXMAdnn8yE9PR1t2rTBVVddhXbt+CtE9u/fj0AggLy8PM3xvLw8rFvHNllcddVV2L9/P/r37w9FUVBRUYGbbrrJ0CxVWlqK0tKqPVyKipz3h3CCaAk34b2lJJwiQzgbZ8feeRHMTH18nxuVQ7GFmrjxxeKqz42FdF6e3/V1M+pb6jOLtx4CAIx/33hiDUqobjyhM4lx6H6Z/nCsrDK+1epdh22Xy1shZTdgqvp+1E2h8JjxBrS2/Fc4L9GOZkUEXlab9xfjxz/Z7iMh4jJCcXZ2NubMmYNly5bB5/PB5/Nh+fLlmDNnDioqKjBjxgx07doVv/zyi6OVnTdvHiZPnoyXXnoJy5Ytw6effopvvvkGjzzyCPeaKVOmIDs7O/yvadOmjtZJjei7ZDUYmf1qRGFlWeVzY8HPwl51tHmZZCb8OAweumycmxAVNjU3MrsIA+743JilD9p0mvYyUoIdI7HZLula2cb7D0/dviZ/+2f4txWh1kkMYwA5kL/G9K46Lhvnxii125HAzfN0F16dRT7GY20OtaS5adCgAa666iq88MIL8Psr5aNgMIhbb70VtWrVwocffoibbroJd999NxYsWMDMIycnB0lJSSgoKNAcLygoQIMGDZjX3H///bj22mtx/fXXAwA6d+6M4uJi3HDDDbj33nvDdVEzceJETJgwIfx3UVGRawJO6GWar5aKTBA1s9SJYqxMaFE1SznQbU0neAGHYiu40aWdFn41K8IsOJbGyz5TZrDu3ex5yMW5ib3uRl0HIzMCD7s+FrwnUFxWgcPHy5FdI4WRl/3nxhNoRBx7jXwSeZobqQpJwnscLF9NZ30z5Y57CUuamzfeeAO33XabRpjw+/34xz/+gVdffRU+nw/jx4/H6tWruXmkpqaiR48emD17dvhYMBjE7Nmz0adPH+Y1x44dixBgkpKSAPA7YFpaGrKysjT/3KLKodjM1yPyWNTMUifqZqU00UFOJJn5BGI97xDmcW60f7MiFFvzuXE+vZM7wgO6CVow63jQUgD2/Y1khGKztE6KNlYFyliLVzxB5ZkfN6LrQz+grCJS2rAr2wSDCjYUHA3/rTFR2Qy7oV0KLv5O1OU65Y/CKj0a/VTkGcZarrck3FRUVDD9YtatW4dAoNJmmp6ebip9T5gwAa+99hrefvtt/Pnnnxg7diyKi4sxevRoAMCIESMwceLEcPrzzz8fL7/8Mj788ENs2bIFs2bNwv3334/zzz8/LOTEK9HzuQn9V94sYVVat3Kd03Fu2LZp9nUVkvZ5PSID19HSCqzcUSh8nyKhAtSYDXBazY088SHmmGNkuuUh8yqMhsBYCx2i7Dlcgg8XbUdJuf393liwzICypl09j81chw8WVTnUygik+vRGyAwPbvQZVj31hyoCQcvjKU/4F8kuLh2Kr732Wlx33XX417/+hVNPPRUAsHjxYkyePBkjRowAAPz000/o2LGjYT6XX3459u3bhwceeAD5+fno1q0bZs6cGXYy3r59u0ZTc99998Hn8+G+++7Drl27kJubi/PPPx+PPvqoldtwnvBqKflL9cJNIKgw43LYJSzcaI8KXRvd1VJi6Yw6UEA3oOnHS97eUoEoxLk5//kF2LK/GA9faNxHQsgKv2bPz8p2IfGgigZkJxz25GD0DoM2BcNoI7PShkUoCN/2g8dw1zntHapVFSlJrMUp9vLUm9/U3UcsYCpfGDKKc2OEOinXhMc5wX0cJprHopJyDH5yHvq2rocXrjpFqJ7a7Nn3Fw+aG0vCzX//+1/k5eXhiSeeCPvM5OXl4fbbb8fdd98NADj77LNxzjnnmOY1fvx4jB8/nnlu3rx52somJ2PSpEmYNGmSlWq7TmiiNXvtIg7F7y/ajvs/55v1rBJqrLLhyGXSCdVDYPItPFaGh75ai7/1aGKpjIDJJMTroNodgS1obgR69Zb9xQCAB75gR2/V47Rmz+4EHS+CjhnsL1Mzk2lszFJWceoL+qcN+ywJN5rtCgQ1qHY1N5FlyGljhbXZMnWQSCsKa1hQj1/frNqDg8Vl+HrVHrxwlXz+9lZ4xRZLwk1SUhLuvfde3HvvveGl1XpflmbNmtmvXZxiyVlX10p/WJPvUG20hOumMI6ZXutc9zTLqiKo4LHv1uGz5bvw2fJdlsqwunGmjDvK/qOl+GPXYQxqmwv/ibWPrHF556FjaFInI/KEILIOxSLPN4QVucnL/jd266bA+PnJmaWcG+L1eZWUB/DFil0YeFIuGmbXYF5TVGK88ksGq4IcL+hd+BjjGqeXEWt9buTS69uT+i8ZzY3W50YOrvaNo3m0Wk5k/uwyhcxS8ai5UeOmg268IfoyWUKCrE+FVRiyjSv2ZdF68AgqCnYcOmarjEjTi/YFiQQK5N3z3iMl+GTpLjw+s9L37Im/dcHfe1auwmM1g398sByf3dxPtOoROK65Ud1YhUjI1jhCyizFSGvWH7QaQeO0bo7v//1xA175aTPq1UzF0vvPiji/seAIzvrvz9zrYyGgsn1EIo85vcpMu1rK+L4f/mot9hyO3OGciUFWiqJYdj6OhLe3FKtcG8VE5GXdLBVrLDkUFxQU4Nprr0WjRo2QnJyMpKQkzb/qiuhqKRb6ycutJaRVDsWRx8xwokHvO1JqngiVz8NuceZmKe3fYbOi5tmwKzHm7SVhwQYAZv9ZFdKA9er+2ns08qAEFTaXp0fkp7p5UcFa0X7OehY5UwH7y9eo+3llGfy8dfsAAAeKy/AYY6+2d3/b5mh5Vu9aG9FXLF+nRz/RCMUbC45g2i9b8N3qKs25PrnWxMUvM/K6qt9bDxzDzNV7DOushrsUXFdIIKg4KrTychIpIdbdxJLmZtSoUdi+fTvuv/9+NGzY0BOxHLxA1fYLxulk/D+cRznx//J+JU4oD0599Efce+7JAmXJCzf6LyXT7Rd0b4LVjHlZrNypjaCq9hFwwsfB59Or0mXNUiYmObVwk2CaGyMiv6bZadSszz+i03Sq05oUaNAU9h8txWfLd+Lczg2Rlmzvo3DqT3/hljPbICNVfEiPxeTDW32jx+kpRdTH8DhjRZiRkGLULwOKAj/4be2md5dh62PD+ZURQZXnh4u244Ev1qDMwf7MXy3lDQHfCEvCzYIFCzB//nx069bN4epUD1jtImpmKZbmRvRaq2Xqrnz02z/RvkEtw2tENRV6e776b81yZ5b5QSSYl1AttOU64S/g05UtY5b6c08Rdh/WbjwYDCooPF6OujVTAVjV3Kh+C9dGjmBQwdz1e9G5STbq10q3lIfRuKtvI6ykRSXaHZWHPqM17Ti1K/j9J5zJ1+UfwcRh5gK/Hn2/ivL2dOJonrdYJZ13KFb/5tdBtlyju9G3k3IbQofIxpn3fBq5Uabtx8i5Qc+2NRWWzFJNmzaNC8kt2tj5Ytfbgd3WhWm/ZCyYJVwmoIipV42WZRo5BbLSs9IKR2dV1cQJTaZ+kJURboY9G7mB3/XvLMEpj8zC8u2HIvLzkv3846U7cd3bS3DmUz9ZzsOo3ejPWGnTmtVSJmlFmsIPawrME3kAs2clEqGYlcVr8yOjJssKGeWBoKEGUrsruKQW1OCckf+O/l5nr3MvtAcPu1pkfl/yzpjBw5Jw88wzz+Cee+7B1q1bHa5OfCO6KziLqDsUy6jWTxDNSTBowedGnzxgornh5m9BQ6Eei1njclFJBZ79caOwCUifh93tF+acGFjfWVjph2H2bFiok7nVFGavq5zoj6i0J3uLSqS+eo01NzoBWK56APTRnb0/yHsJ1uOysiWEmopAEP0em4PTn5pn4ADL/q2HbZrmfzQZEY3x0u0yeKvbRLpjrHuGJbPU5ZdfjmPHjqF169bIyMhASop2b5CDBw86Url4hdfegkEFuwqPs7UIEQ7FbtSMLXjFZLWUSV5frdqN37fItSN9nrIbZ/oYx294ZwmuH9AK53ZuaJiXT8Dn5r8/bkBeVhqu6GUeJsGnM0w5vVrKinATDfR1WbP7MIY/twBdmmTjy/H97edvUp4IZubM8e8vAwBLQdNkcOu9cVcROlCesFlK4rM7v6gEe08sVDhWFkDNtMhpTVRTLaLpUN+DUV6OxgWTPO52uSLjUazHFUvCzTPPPONwNRIDM4Hkjo9X4tNl7JgtbuwKzoKpuRG8Npqam182HZC+prQigNTkqlFRelfw0ManqkPLthfi5vfMHf/Ur96oHWw7KLi8Xa+5cVO4EWwBZmY+J9DnGuovq3QO3Jbzj6i2/H1oIl/rzh06ETANAB6+sExogHfL3Gs1V6erYxbnhoWMWUrjIM5JI7oUnCVUGfvVGJ2Tf5CfLd+Fvq3r4bKe2s2deVmZth2bH8nxvBTcknAzcuRIp+uRIBhHKOYJNkAMHIpjtFrKTTo/+AP+c1nXcERj/fYLenj3Y+U+1U7ERg7FKYLexvpUTi0FD+VrV5h2T2ug/dvKIGrUniMCslm4D6P8rfiyWeEIIzifXSGpoKgE/1u8A38/tSnzvHlMHxGthxhSwo06f4FnYGiWErkHjVXSoK1Z9B++8+NVEcIN78kt3noIq3Yexq1D2lorzARWqYqiiGluYmyYEhZuioqKwgH7QlGJeVTXwH6iS8FZRMuhmKm5Ea2vo2pWdxr+HR+tDAs3QYZ2QlEUPPL1n2hdvyZ3xZalzTLVZimDgTk5yc/cKDAyP+3fFSJLuyQIWNj5PDqDlZzwEQgquP7txWjfMAuXntIY//zfynCkaGbuuvys+dzw89O/e5Fnpk5RXFqBP/cU4ZRmdQzv486PVhnmI4J+Yh795mKs3VOEHzmOr6ZKAoFBS9xBXxyz1W+AuNDJfOQGbcZpzY0sbyzYAgColZ7CPG97sRTnFqJlabCDsHBTp04d7NmzB/Xr10ft2rWZA3gohkRoZ3BCnGiFGgkNLtb2lrLWoKWceSU4VlaBj5bu5J5nfV0s3noI036pHBA+uqkP8zpL+0lxfuv5ecM+PD9no3T+QaVSWDOa8GRQtzcrr0J/zcK/DmDptoO4eXAbx+oImL+LBZv2Y+76fZi7fh/mrd+HP/cYf3hF5i9fJyubjopy+asLsXpXEf59USdcc1pzbrqZa/LRtn6m5pjdqqw98exW7ii0l5EOtTZEWCsq0YQ0QQJ52lh1ezfyuWE5FBv2EDEtnl3Msvprn70godxyWUEuYR7lGYgjn5s5c+agbt26AIC5c+e6VqF4xl6E4ugGUlPXUNws5S1p/f3ftxueZ5mlilRaE562zMqr0Aj7BgPzkm2H5DM/QUVQQapDgkO5BenG6PVf+dpvAICmdTNwYbfGluslq1kpVQVdO1RcJp+/w2avyMRyea/eVSlgfLx0p6Fww8pa9l6i1Z01AoMrPjfm+avHLmOtg4hZSuzDMBoOxa7D09x43UcBEsLNoEGDmL+JKuyYpaLmUKxo/ws4vyu4PhlrnHJCUCphRBPVlCG7/ULo/VkYSvwa2cYdo6IjA8qJqh06Zi4IGKEoCv7adxRlFUGc3LDKDL3tgL39wPR3aB5lWjZ/ndlL8npAZ5aycL0e3nJbJ/JxEkfuVTiIn/bv937fhlY5mejTul5EWqNYV+FyBca7DQVHcOnLvxpeC+jNUvz7savV21tUgk37jqJPq3qm75anSVF/dAWCCsoDQaSniEfDFjHzeRVh4WbVqkgbL48uXbpYqkyiYOW1bz8ouFGbTaoGF43uRvBaB+vhxDxt8nWn1dwoJ65BxDE91hyK1T438teLUOl3YzwwiZplDqq0HMKrpXS/Q4H2Vk46u+q4w2Oe2btQl5dfVMJPyEjP+lsEGdNXNKcA70834s9b/YGwaMtB3PvZagAwXbUoEpiTl+amd5dq4ivxEPVXFPlg1W8Hoqbf43NQHlDw3vW9Tfvop8v5i1VCnPf8AmwsOIIVk85GJmO5PLt+rIPRc6Owg7Bw061bN/h8PsOXEaK6+tyEOuSqnYWYt34vBrerL3ztzxv2YcnWg+jZoq5b1QNgT3PjpH9BNCR/sw7Iu29LPjcOb7/AwmzF1NHSCmZ0Yj2KomD/UZVwY9PpZq9KqLDrdCwfME3SFBPxt3x9P1y8o+p6t5qx4MRo9LfTmEYo5h1XnRDVdKiv2c4Jn1AeCGL/0VIkafaTY+etCeLHSXSQY9Y0umu7cW4CQQXJSewnV36ivy/ffgjN69U0z4yBOueQUL5460GcLjg38fpHPDgUC4dK2rJlCzZv3owtW7bgk08+QcuWLfHSSy9h+fLlWL58OV566SW0bt0an3zyiZv19TShPjZv/T6MenMxdojGNDnBJ8uqnGNd3xVcdUxU0LC6TcPxskhh163OoRlITc1SzmlutMIN/93ZEXzMwgUUl5p/dUIBLn/1Nzw3e6P6kBgCK05EX+vKHYW4++NVEbvERwgfZmYpm83I9vWm+QsIKRynTTOKS7X9St5E5276EGa7ggPApr1HcebTVVtuiIx/V776G/pMmYNFW6uCfYrEZeEKQJwTkVkqBufM81PD69OlFVXvdn3BURwV6dsuwHfQlhe+o42w5qZ58+bh35dddhmee+45nHvuueFjXbp0QdOmTXH//ffjoosucrSS8YK+O+4uPI6mdTOEr09JsrQbBhdW4woNpOrO/s6v2/DUDxvwxsieaJWbGXFNCCuOtjsOHsOy7YWO5BVi4V8HmLZ3AEhWSQ9mcW54Xc+a5kYdoZhPSpIfpRXGe+DwBnYnloMfOlaGRbrIz9acalW/LeR14Yu/AAAOFJfi9ZGnMvNl/R1RD6HS1PnJaoasI7zEnpFO5ENCb4ZzwuRmiAP58ep058crsXlfcfhvkY+AkHP+h4uqNGlCmhtGJab/tk14N21Rs5TI8+cJNwWHq4T+r1buxlcrdwvVTY+ZjLi3qATTf9uGK3s1Q6PaNSLOc6xSgnFuYoul2fSPP/5Ay5YtI463bNkSa9eutV2pREFWA+C0cMOiPKBAUbT7Ni3aehBb9hfjjKd+Qv5hvt+CqObmr33F+HpVZWf8cDF7RZMds1RoZQ6LZFWIUdbXhZGKvGr7Bfk6acYQgxElyWTUDg0aLKdkM7OUyICTJBPXXoeItk/20W0o0C5h1V9v6lAsWaATZilt+camIScHeLP5Ph5WS/Get17raHVXcL5G0fhD5/7PV6OknC3cGG/EamSWEtDccASqgiPm/mNOMGb6Ujw/ZxNGTFvEPM9rUwllllJz8sknY8qUKSgrq7JRlpWVYcqUKTj55JMdq1y8YSWAlxq17dUJo9TnKyKl/aXbDuHyV3/jDmzv/76Nm5+MQDL+/eWG591aSqjW3FSYLGvRd9zQ+7MWxK/yv7sLj2MGR6ADzAdto0HD7JmJPVNrJhCA76cl+iXLwuxZmzoUy/rcuKzd0GixbIg2Vurl9nTjSP6cTCJXJImXJuIsrD4svSt4RN2qsBvEj6e5KTfQ7jpJKKbRpr3sODn2zFJWa+UMlrZfmDp1Ks4//3w0adIkvDJq1apV8Pl8+OqrrxytYFwj+XJTHdTcbD9wDCs4wbgWbTnIHTyMbN1WBBLesmi3wiQkJXHMUoz75WmhrXTKkNByzjM/o8hgxYWZut3I8mRmljrAcYh89ee/wr+Z5jlL74J9kaxgGCls6DUfzmpujKLNOoGmPopY/UTfiVlWsZ5MRPxkhMNOCAbd08OdjFUnpv/G/4CTLcOuQzFPG+vUq3TDdVNRlLjQ3FgSbnr16oXNmzfjvffew7p16wBU7hR+1VVXoWZNa17diYjs61ebVOw2yn1HjdWavLZpZDZxsj275WzGM0uxiuMFTrTyxR16akaCjQhGg6WRQ/E3q/Zg3IndqPVM/nZd+DfPhi6C9guZfdxVYYFZJ8n89HFubLZDI42DnZytXCutxYqSV4R2Y0uxydyq2drJRQIhjEyZxj43imn74n2wuCk7yEwttjQ3Mfa6sSTcAEDNmjVxww03OFmXuEcvkMh20JRkJ8PWW7vOSLixIq3zhDS3JH+NQ7FJB+QJC1b8dkUHTzPhJ/RcWM/NyOdm8rd/CpXPbJN2HYodNEuZaXIi6+GcicERdM8imsO72x/TW/YX473ft+Hq3s0t58Gro1MfO06GdxDBeBNV83fC19w4U1+jgKKTvlhtej13KXiimqVCrF27Ftu3b9f43gDABRdcYKtS8Yq+Icm+3BQbzp56zIrmCV5GPiGsBp1/uAQNstO51/Byc83nRmWWUt8jqzR9HaociuXr5pSwZvRFZKS5ER287VRTu0KK/fVq2wdGd71MED+h8kwPyOanN6Pxz0nla0XgtFyaOPd+ttqecCN43Go7tRuiQORi3kpBVl3MiuX16WgIBm8vNDfP8cyjJmsbPIEl4Wbz5s24+OKL8ccff4QD+wFV6sdqG8RPN5PLvv8UTTAne1ocU3U+5/zirQfx7fN78O+LOqFr09qm19zx0Uq8e31vx+snAksO42luWJNFhHBjY/sMp74M84tKUDsjlXnOaP8xcdOS9Ws113C/kOXyMdPcOB3sUdanRz5/7e9oxvoQMRXEAs3WT9yGo/3T7MOEBy9/dVwnWYwEL6NnHggqpu2XZ5byyvYGvFp4ta2psaQquPXWW9GyZUvs3bsXGRkZWLNmDX7++Wf07NkT8+bNc7iK8YvswJbsoEOxqTqfc3zOur34Y9dhXP367xHnWNqWzWa70XI0QW5pbtT7pqi/Llilcc1SjGdn9jydup9znpmPnzbsY54zMkuJNjVm7CPRa1W/tZOPsRBplueh4jJM/ekv5B8ukTYbyfuZ6P62q7kxuN5BZYErOF2GiJ+goGxjw+eGffyIQ0Hwdhcex7Lth0zLA0LCrXF+Xncojuel4JY0NwsXLsScOXOQk5MDv98Pv9+P/v37Y8qUKbjllluwfPlyp+sZF+jbkbRZihOGO5y/g57vZpMQKyIma8CxGknZiS8Tlj05LblKQDTbaZ0nkPBMWLww6ZXnDYuSYsw7S5DC8H0yi1BsFREB4ZdN+/HyPONVV0bHuWUrwG0zVuCnDfvwydKdyMlM0503EdItlGfn+oj8Iv7WCnoi2Tul3fHqfKPdz42dRv8MrDZ1NzQe6iz7PjZHe84kzo255kZQ2osRTE2vksBB/AKBAGrVqgUAyMnJwe7dlfFUmjdvjvXr1ztXuzjDtkNxkvFqKSkvd5vnWbCFG+NreKejMRCrO+BTP2zA0m2HNAKRjObG7EvFyUG1jBPjwtDnRvCNWvUn1mvy+D43ciiKEtZUbdx7lLGayex6yfJU+ReVlOP6d5bIZWCWv84sZXWEZ71P0yB+NrVYMqzcUYidh8S2l9GYpQRXS1nVhDoQxDsCI+HTqP2JjAlOrth0A7bPjRIXcW4sCTedOnXCypUrAQC9e/fGE088gV9++QUPP/wwWrVq5WgF4xnZl2sWvVZGS+J0ZNfKPCOPmQo3UV4tpc5XPUB+sGg7Ln35V21anbolJPiw7tOZAHr24EUzlcGpQZM3idh28NWX47RQqUr+5oKtcteysjMwoznlvO3mNVbYsr8YF774C/o/Plf6WtE6WhZuojyjGgs35vUp55mlXLyNoKJgyndiqyt5PTRhzVL33Xcfiosr9wF5+OGHcd5552HAgAGoV68eZsyY4WgF44nICMVymLUXJ+MxWVGFswYco6WGsnk5gXr+NzPjRJz3AQeOloajdhqm1Zcbhc5uvFpKLA+WUGJpIuXlb5LZpr1HNPutme31ZB6hWA51+uIy5zcj1IT5P/E/mToZHbOSjxus3V0UceyleZvw0ZKdjNRaRFczWTXVudENjbI0au+fLd+JTXuzDfMOBNmxcNwcTr5euQefLt8llJZXDzGH4tgKQJaEm6FDh4Z/t2nTBuvWrcPBgwdRp04d13azjgcifW5k1cRV6VlPUWq/FYcnBcCqWcq99sAqW63mZQlQ6ii++vOLthxkOlID5p3Z6dUDrH7khEBodQdqPVa+kL/7Yw/GvrcMfVpVbXqqvyV9rqbFyCpuTqQ/VlaBV3/eLHcxs3i+cBbtj1tpgcBiBfXrHv7adxRPzBRzR+CVqH+OVj8Woq65MTj37m/8bVhCBBWFY/pxBtY4ot9w1Qim4K0ksOZGzc6dldJ6kyZNbFcm7rG5FNy0vTgn21gzSzEmV6sb3LmFWgBgrUS446OVVWkZD2Fd/hFmvqaamyiYpcoNzFKipf+2+WDEMUVRcPfHq1A3MxV3n9NeLCPOJG40wb7161YAwMLNB/jpJb/grUblnb9xv9R13PwMildMzhvlwfyaN8knWqtz9RPm4ePlwulFHdGtWmDddih2urygwhMgnLkPux/JvGqIvJ9Yyz+WfG6CwSAefvhhZGdno3nz5mjevDlq166NRx55BEE3PLriFDvRU+0v4TM7L9/yrPjcRBu1kGE28AQkIlGZam6i0JPdEqA27y/GjCU7NKuhzOAtBTeqYhljRIyUbXSaEOEayeGWUK6+n1d/3ozFWyOFSaF8oniVLMk630A5c7qYWcrppeB2CCoKbn5vKZ76IVI7ZVcICXLMUl4JI8P7eDgmYNKNtXBjSXNz77334o033sBjjz2Gfv36AQAWLFiABx98ECUlJXj00UcdrWS8YDdCsTq5/SWqJhO7FZ8bllnK5JpoCz/qOkr73NhIGxWHYgd8blioNUKKogiZltXFfb1qj+o4vyKsVWDq1H6f/CRn1RJjtoGpVdT3/8Eic7OEQUbyl0RpMvH71ZoYBTKVteRQbPqhpv7t/ENYtOUgflhbwC378ZnrsHrXYUt586MYe0O64a2uPGJzD71oYEm4efvtt/H6669rtlno0qULGjdujJtvvrn6Cje2zVLRa9DWVmMwhBuPqW7UikMnVziZ5uXwq2M9VaMgfk5hFs8nhFroUPuuhA7vPHQMq3cdxtCODcJthGVWU7ep1GQ/I5hb1e/1+UfQrkEt7nkRQsmjobkRvsYhPyjp8cZCGQDw0/qqIJMVQbbPiBr1oxbd+8n6ailLlxlSwgnNECpPRuOpJ8B5fk5NBW5ZAI6UGJsivYAls9TBgwfRvn2kbb59+/Y4eNCaGjYRkQ26pk7NbJQS2Zl1DiuDB+sasy9gN0UfpgCgkm54oc2rzos/gznr9mKBgZ9GNART46CE1stXP0dRjZ5Z7LH+j8/FTe8uw1cqrQ5r2as6n5QkP2P1VNXfQ5/5mVGerOn3RHqHGmbkdg7u5Ct2TeV/dxcex+Mz12HPYXHHURlCvlOAvMAtqqcw8i8zIqgoKHYoGnEI4zg3TvjcOCPcsmAt6JDpM7y0ZhsAewFLwk3Xrl3xwgsvRBx/4YUX0KVLF9uVilf0zeiWD5YbToh6dhw0Dool1yiNsWLTZvrcuCq+yKMeE818akLPwCy+EABM+nINrnnjd26Aveg4FLtfBq9ZRAjb3CW92uOLt1R97LDNUlXp1dGlzeojep6X3j3NjTPviJWLaBC/UW8uwsvz/sKPf7JNKeH0DlS1PBgUGJXkHYrtCDenPvqjpWt5GDsU28ubu1rKG1YpA82NgM9NPC4Ff+KJJzB8+HD8+OOP6NOnD4DKLRl27NiBb7/91tEKxhOs8fLG6Uuw5uFzhK5/fs4mXNS9MVrnZjLPyzR4p8PW8xxqrQbxcwLTpeBmDsUn7snvA0S3euUJMdEQbozKsDMY+n2+sKDHKqOkPCAcf0afTh11u5Ql3Og1N/rzJgOk1du+//PVFq/Ula+rgCVzkkOT2+Rv1+Gd/+uFDQUm+705SEVAzizFFW50Ty6oVI45fknnKEUBjpU5u3GzURu0r7nhabI8It1wEDFLxVpAs6S5GTRoEDZs2ICLL74YhYWFKCwsxCWXXII1a9Zg+vTpTtcxbmBpMWR9UkKaHrsaEbN2JTsZx0NcA6DqvhRFEfa5ccJvqPILzMFnxKiS8fYLzrB612HMWLxdcy8Dn5gbWR5Xc6P9O1WljWH73LDThjBdfGlhRWL+4RJsN9GSCudnrzrMPCqPyWf0M2fDVTepCAal2r2MxrjcwsrbaMe5efJ7e9sNue1zw0LuI5l1TGHuPeg1LMe5adSoUYTj8MqVK/HGG2/g1VdftV2xREF23jS070plZHxaVljhDRp+nw+Fx8q4aspoOxwHFeDRb9biy5W7sf9omWHakE9OkkQdK69JijgeCCquL9802n7BKcHq8ld/AwBk10jFOZ0a4NFv1mLvkdKIdHyfG+2J1GR/eAUWS7hRt6vUJL/8ainDs+z6HS110xkyPj4CAO272nag2FIe3F2tbYTBCFEeUJAmOUO50QeNbmXzfmvPTZ33zxsjhVLHfG7sOhQzahJUIOTXFOueYElzQ7Cxu9klYNwguNvPB5UIfwZTdb6scMOZV30+oNvDszCA8XVvl06NswzPs3xQKoJBvDZ/CwqKIifkiOsrKq/Xx+0wostDP+DPPZHh5wOKuQOzXdzaFZzVbteeuMfX5m9hXsOrib5ZPTd7Iy568RdmG9Xnw1otZXbHsjLdmHeWYMjTkY7JVokwSzn0iqKtKL1x+lJL11UE2CONuv4+znFNembe8sK8G5obN7VBOw4eYz77aK6cNYJVjaCiuDYWOQkJNw7CmiJlNRehNiNz2fDn5uPUR39EaUWVrdmsb8i2TV4Hd1Mxk+T3c5193/99O1MlLCNfHC+vfF5pKZGaGB6KAjz6TeSmc4qiuL5U29DnxuGynpu9EXPX7eWXx51cIs+t3HkYq3cdZg6I6rTJjEA35r5jcnfutj9KLH1u7JTLi8xtRqVZipE3r0zBIH5AZdDHKd/+ibs+WVV17ISALLqk3AncfBc7ODure0VIZl3Oc4J2umy7kHDjMm6apY6XBfDI12uxLv8IDh8vx597qgYop3ex5pmxzHyD7Ag/KX4fd6n5vz77g3lcRnsSEm5qpMp1gxRGHBhFcVazwrptKz4IIvCqPfqtxdxrjBxDWZGIeauTNNn4fKY+LBM//QO7C4+zr48BRntLOUkwqOCowxt9OlHViiB7c1D1OPbD2oJwRFv+84k8UR5Q8Ipu/6+LX/oFx8sCXIdW0S4yrFMDsYTMmjmHqIO15fyZ74adNhhU8PvmA+HtNNbnH8Hr8yP3XxNdtRlrp2gpi+Yll1xieL6wsNBOXeIfxgBeeKwc03/bhmtPa247e32jfHneJryxgG02MJtnZVWtCmfQcCvSK1C5RLtS8yXjsCief8kJ4SY9WVxzAwBpjPSrdx/GMEYcFquwbsNoabudSdXaVhzsaz5dtguTzusYcZwn5OrNF/r3py/ng0Xb8f2afCy7/6yI62NB5Gopdyr0f28vdvxeHVkKzjEd6bN+5afNuP2skzCHow1k1eU4Q5hbs7sIHSbN5E/QgjeVlZ4ilK6ybu41MtFVh1Zha9XYmY98cxHmb9yPNvUz8eOEQcy4UoD1ZfrRRkq4yc7ONj0/YsQIWxWKZ3jz/P2frxYWbkKNUUTjYeTM5vRScK4DsklF7az6SknySzn7ynK8LGSWktPcsNIrCrDbpaBpIdyyc1vJ1uiaBZsiYzuJxBLy+dhLgvUcVO3sHmvNjR5rk5Kx5gMA5q13fiWUE4JYRUBhvgT9c3h29kb0alkXz87eKJx3cSl7SbcTcWfSJfq8uyuXxM10TsEbk0ObyW7aa2y6jUakdCeQEm7efPNNt+qREDgxD8sMOEYThlkn//UvuV2RuT43UrnIkWRglnKC4xY1N6lJsbHmvvXrVhQdL8fTl3eLOBdtB0SjdsoyGYgEzZMNyj3hfyvw6bJdpvm6iVtP3Wq+Mu0glNRO26k0SzHyZhy9+vXf+XVhHCsWNMOpqy96L1J+dsIp5eHHuXEG0Xcjg1vmcachnxuPEdbccMQGdec10mqYLfX+35KdUvWyGsTPDilJPleXkoeFG4mBDpDX9FiBd9efLt/leHh5Kxg1L1bbE5EHfT4fY/URv6BYCzYsYu0IKqOFCz1bkZWFPCoCHIdiyfqz3vMxjubGCGHNDSOmUizgVdexSNexdLAmh+LEwYmtCMzag7ph6aN3qhuy04160Vb2nmFmX+R2ZBMRU4YdSsqsCTeymh6n2cqISeIlRTFbEBbT3IgureYJ21FHv7rLwptwsqvK+NKFkm6xEavFKVMpKxtRzY02Hxc0N7HwuXGtxOgR63sg4cZBHDFLmbSI0OmPl+7Ewr8OcNM5EZvhUHEZJn2xGn/sPIzx7y9npnFT/kjmfO7n1kpzJP8qzY1cN2BF0o0m2w44E13XDkbCBfuUeXus9LnR58W+zisRs9W1WLGjEO/+ts2hfK3dn8wqyFDK/KLjhumM4K2Wkl6wwNLcWNhGQVi4kejDbsrRXLOUY5obsWN6Qost4hkSbjzG4zPXYdPeI4YfuhsKjuCOj1ZiVyF/UHLCof3hr9fi7YXbcP4LC7hpTJeC2yg/2c/O3al5LTR4slY/eZmCIobjcpTneqPiWAKvyAThgy9iUOddF429vGS56MVf8MGiHY7kpX4MRsHsjK4TTVtabn2wcMosxULU/KoWrkTLlRFurNzKpzf3xckNjYOQAu47FFsVkouO24/iHetAhCTcOIhTSoyrXjNwvFMUTZwPHk5objbuFQjsxbnpkBbLjjYr2c9rnpH3duOgVtL5hzZylNXcRGNiNfI18sK8btS+WM/HanvkDZBeiZDqxPjNdvqsooSzEz0LGY1WaOJjbWgqCi/miexjYaUX1dyo/VvdMEtZeclZ6SnIyUw1TcfzzXWqdYvs3s2iSGBjTDNi3UNJuHEQp3xfWXv5hFAg1mickJpTBLxAeWYpJx4Fb1sE1q2JrMbhIetzIxrEyi1YJqFo18ioeT341VpmetNXxDjPK8co5k8ioL5vGROBFZ8b1rYYolQEg5ztF2Q9iiMPifrcqAU6UZnXbc2NzyfmMzhzTT7zuFNbPjzwxZqIYyI5//gnPzp5vEDCjYM4ubKHl5NRm1efcuLDVkS4MTdLWX8myUk+9oTHLMc68pqb2C6FZH2dR30puGR5QUUxFUAZuy9wB3mvLEd1IlYM61mWVQTwzao9OFRcJqVZseJozYooLUrlrtbuCNuiq6XUmkJxnxvxD5pVOw8Lpw3hg9yedXrcdJgXyfux79bZLuei7o1t52EHEm4SFCdMJyLxXHjzlR1NSgi+5iby3uwUV0NWcxNjkwhrAI92jWQfgaKYO5/74IsQFnhmFq8EEnNLpiwqqcC495fhild/k9TciJcR6kd2zVKOLAVnHBOPc6Mwfxsh+0Eji9/ns7Xa003TdzSc8WfdPhCnt6vvejlGeEK4efHFF9GiRQukp6ejd+/eWLRoETft4MGD4fP5Iv4NHz48ijWOHQoUoZnMGbOUeefkCTGO+Nwk+dnRT61nyUR29VM0TCJGz80Ly6BlNRZBRTHV4q3ZfThiY0vevcZLCHi7rC84IuXwK7O3WujR2jFLBYMKW1siLfwyVkuJam4smaXcXUTg8xn5DJrj5hATjfGjbV4t18swI+bCzYwZMzBhwgRMmjQJy5YtQ9euXTF06FDs3cu2+X366afYs2dP+N/q1auRlJSEyy67LMo1j8Qpq5SRxkRUZnGi/YpM+m4G8ZPxubFXjlw3iIYzq2GQPMZcFO2FCfK7ypu3lSKG8yPvK9Mrwo0Tj10BcNRgZVBJhbjmZtEWdjwqdrmVtbcj3AQUhdkWZIVfO5obaw7F7k59PtjT3LgpgHgljILbxFy4efrppzFmzBiMHj0aHTp0wNSpU5GRkYFp06Yx09etWxcNGjQI/5s1axYyMjI8Idw4hZlQwRs41G3WCYc0O18eTgQ05Prc8LaCsFikiIZKjczXsVWMBjcvDE5W4phYMVXyHnWsnbqdpPBYOTpN+h7//jrSERuQcyhetq1QOG3YoThgPaZJgKO5sWK21COqsQpa0ty4LNz47PncuPkB5ZHvAteJqXBTVlaGpUuXYsiQIeFjfr8fQ4YMwcKFC4XyeOONN3DFFVegZs2azPOlpaUoKirS/HMLJyZ0wLzj8eaVf3+zFgeOVq60csJmK7bZofFyKTtO1kkc4Yq9OsO6UzGvHB7R0BoYCTBsB87oTvayPi9BAZ8bFup23LxeBmqlVW6H5xnNjYOP/fUFW5jHj0os5z1aKr6EN1R1W5objkOxrPDLSl8qqLFStxFxnxv3zVK2NDduRkX2gFk7GsRUuNm/fz8CgQDy8vI0x/Py8pCfz14ip2bRokVYvXo1rr/+em6aKVOmIDs7O/yvadOmtuvNwzGzVLKfKxQYtfnl2wtx24wVpulEEfny4KZwYrUWr3yOid+qE3OypObGzmQgipFw6oUAdrLPQFEUaUF3/PvLNEJe39Y5SDrxrjwj3JxojO8s3OpaGUbBOvUUS0T1dWIpeKXmJvK4tGaPcazEiuZGsG+4rbnx+3y2TF9Pfr/ewdpoiYbm2QvE3CxlhzfeeAOdO3dGr169uGkmTpyIw4cPh//t2OFMBFEWTrmfGHU8sy/0BZsqd/t2QvIX+fLglRKqp51nksQROniaG8vCjeQXlp3VJaIYBsljLgV3szaRyAoXIj43er5etQf7dDGfQpvFeiWIXwhWPBGn2HlIQriR2lT1hM+NDUExqLDNUtLtkZFe1NdI3RS85FDcMLuGq2VYxWNdxzViKtzk5OQgKSkJBQUFmuMFBQVo0KCB4bXFxcX48MMPcd111xmmS0tLQ1ZWluaf10lLTrIsFIQGFScasIhww/tSCh22Uw2ZpeAKFMuaM1n1sZ1w9aIYaWc84HIjPSEGFcX2RqhqVX95FARMIaLwLt7gmKtYyOyk7SXNDQtrPjdi5drxhxHBBx8a1U53Lf/TWtW1fC1pbqJAamoqevTogdmzZ4ePBYNBzJ49G3369DG89qOPPkJpaSmuueYat6spjFNmqZRkfkaKIja5RUtzw5uEQwKInSXpPIdmZo4WNANm5fAojYJJxEg4ZT3zaMs78mYp+7GPfFAJN9Xl81MSo1VXesJ7S9mKUMz2uXHCdCqquVGXJVqu32Xhxu8DaqYmu5a/nQ+FHQetb5QaT7j39AWZMGECRo4ciZ49e6JXr1545plnUFxcjNGjRwMARowYgcaNG2PKlCma69544w1cdNFFqFevXiyqzcQph2IjB1cFYhOZE05jIl83PMfX0FE7MhbPF4aXZyL53BjhBZ8bWbOUoiiO9A6vaW5i/ya0HBNcPg1UfQDZEW54cW5klQMsc7uo5kZdvMhKwjPb13ddcwMf0L9tjmvZOxEkNdGJuXBz+eWXY9++fXjggQeQn5+Pbt26YebMmWEn4+3bt8Ovm+zXr1+PBQsW4IcffohFlV3HB74WQlQT4sT8p3YAzctKQ0FRKWqkJOG4amkqT4gKVdPOKh6+5oatuYiez431pbNOwGwDUZ5lZQW8Sp8b56JWe8ah2As2QhVHZcxSJ/5rO84N43L5UAGRx6xobkQ+6l4f2dN1vzm/z4eM1GTcOKgVXvlpsyv5E8bEXLgBgPHjx2P8+PHMc/PmzYs41q5dO88NKoBzZimzfETu3YlYKOpBI7RyIadWqkataVTO/5bssKe5kQjiFwxa97lJFthmQk3MNTceaPuycWYq95ayX66fzFKGyDgUh5qRTBwdPfw4N/ZXS4lmoe4PIjKvz+dzXTgI5X7jwNb4Yvlu5BeVOJq/Xf+16kBcr5ZKVIyarahZygnhTz1ohL6Uk3SDgtEcc9fHq7D1wDHL5XPNUpxjVru7F1dLGcGMUBxl1Y0Vh2K7qAOjecYs5TEZ67iEoBJqMweKyyyXFwgq2Ktb0QZYCeJn/UGqrxUV/F13KD4xTtatmYqFE89wPH/S3JhDwo2DGKndZVY8+Hx87x3x7RccEG5UX+ehoG16RzwzNfDB4siBTxTu1wnLKqNYdxKUXy0VW7PU6l2H8cnSnZpj0Z5kpR2K4YzlzB9eCu4N4SauUSq1q/rl9jxYkdMDQYUZk0VWWLHTNtQa5goToTs0REfDobiqTOfLklQ2V0voEUWJRzih1VkY9jth4Ua4uAhCk706lkj5iclE/8Vg5txqR32awunBbJ8ba+H9AfmvODtxQZzgj12H8c+PVqLjAzNxywfLoSjR1ttYcyh2JLDkCW1emUe2X/BGLayhoFK7KsqPtw+KOMYzacmaTu20DfUQ5AVne8C5xSU8SHNjDgk3DuJUc/PBZzhoCi0Ft9HJQ6angOrrOFRmpFnKuBw7nZAnGPGKtL79QnyZpUIUlwXw5crdKCiyrh2zirRDcRCwKwr44KsK4ucRh+J4Rq9duXFQK8P06YyIu7y+EE3FmnqsM/MFi5aG06d7VANPynU0f7c1T4kACTcO4qQwzeuEot/odsxSoftgjRP6TuWu5ob9/cNzPrSi/k3y+6Sv85qfxf6jpVF3sJePUOyM5ibJc6ulYl0D6yjQjllDTs7jpgXA/HrgCblu7o1kVFZAQqr6/raBblQHQOSjeunqUxzN3/Wl7AkACTceJGBgZqjsx2ZfJ+yooaKEtC1frdwdcU5vKTJTP7M0Nyc3FIsSneT3cwQZdplW+nuSgX+TCDNuOM3G1c6w/2j0NTfyq6W0rTa7RgruGdZeutwq4YZf/rNXdJPO1yrRNwg6h6IA7RtU9sWXrj7FtB+wegpPcxNNoU+9n5bMKrqMVPe2YNB/MDkti8gGHnUDr6/Yiv0TSiCcetWVX7n84Hhm/Ze3PFMUozarF1bMzF8szU69mqlC9eBtnMkqsXKpsTXNjVVya6WhXmaa5eudYv/RsqhNsVf2qtx4Vt7vKLJNp0p6RWq2XzAov3dL7wT29DJBRQnHbKpbM9VUg8nqKjyfm2hqbtQEJIRuN91W9M/KaR+ZFNVK0jPb13c0b1G8Ltx4Is5NouCUV3wwyP8evOGdJViy7ZDh9ZWBtewIN/z70N+jmeaGJdzUERRuZHxuKs1SQtlGlGF5Tyqf9WudJJqam9CGg6IrbELoNTcALO2aHPpirTCYxKI55sa7WSpkVkpLZmtJ1bDGN67PTYweTLmEWcqNVUzhvF12KFaPjf3b5mD2ur2ulsesgxcGPwNIc+MgVt/133o00fwdUBgzwQnMBBuAv5mdKEbOavozZmMJU7jJSBGqR3KSX2qIsKq5sToQJfndDwYmwrGyQNQmWaMd643Q+9wEFUVacwNUtU0jzZGbk1YsufXMthjeuaFzGSpVwklqst+0LbPOesHnRo3Maik3W4n+UTqvuanqO/qPwL6to6O59LrmhoQbD6Bf8hwM2rPlV7holtLnajaYsDQ7tWsICjcSncfqruBHSyssC6V+v7sDpCgyTpR2sS7caH2lKgIKM26KGaE2YbRay+uDrlVOa1UPl/Zo7Fh+gaCi0twkmfvcMBLwtiKJ1YpsI42eHjdlYH3eTpelHhvVglO/NvXw4lXOOi/z8Ho3I+HGQZz1ubF+fSDgjEMxE13FrJilagjuliuzoWXD7BqWvo7sxMXwilmqIooziRWBBEBELJ7yQFBaUPJBLIhfdM1S0Xv2fp+z5o6KYJXPTVqy37Qts8ou4Wxu6cTGvVaQ8QVz03Skz9tpzY16yxh13v4ojkle/4gg4cZJLLcq7UBgV7ipCNrzuTFS6+tzteJQXEPQ10JmRcB1/VtafvzWNTfWTVpOIvO1aherJh9FF6K4IqhwgzQaUbX9Av+erdQxLyv2juFm+Hw+R1WFgWBQ43NjOgFLaG5itf+ZlFkqqg7Fzuav1tyou1E0TbJJHlixZYS3a1dN0I8Ddlc7BRV71xvNORF1NSmHVY8agkswRTU39w0/GekpSZa/jtJTrC0JTbbhjOwk0Qxod6REfGNGNUFGeAPZDUuBqq/FGUt2cNNYmUisth3RXnbn0HaW8lfjd1a2QWlFMKzhFdHIsc1SsV8KrmaOhGOtuz43PsO/AWBU3xaW81ePjeq2m+Swdk9NzdQkzSotr28B4fHqxRdONSkDf2IhKuw6FBsM9HphxexLiaVVEBUmZANVsaotkkXj2jUijt00qLXpdVYnxJF9mlu6jkc0d8ge1qmBpetYVeQt9efh8/mEVOFW1OVuO4a3zs20nYfPJx9w0ohjqvgwaclJAmapSHi+T17ZBiFWiDTBmmnW4+zwfG78Dmv3QvRtXQ+rHhyKgW2rIi3TaqlqhFPvOuCIz407S8H1mJmlFm4+EHEsQ9jnRqx5huqrrvfYwa0x947BaFGvpun1LGGrVa75dUl+n6Uw6E6rjqO5Q3btjBT0bF5H+jpW7CY7mhsjrAgqVl9JNDUUTmtujquEG6HVUozzXotzI4WrDsXmmYfCKlhB3XfUWhyfSz43FUElIpq717eAIOHGQZxSBwaCCo6VWVP/A5XOlk5sv8BC1izFoobDmptQfdWp69dKQ8ucmpYHMJGvkspl5PI4rSWIpkOx32dNoGNt7injMB5CRLix8nitm6XEnr0Tr9xpZ9HiE2NMst8nFO+J9ei9ZpaSIdr+cjNuOE2zf5cdh1y+5sYdmS2kiVNX2etbQJBw40F2HjqOX/+K1HiIYjfOjVGn0wtNVlYhszbgY5Ut2nlYmhtZrcBnN/fFjQOrBh4RXzmrk43TY0I091ny+aypoxUlcsJLseCQKNImrAgqbo/TTmTv9znrwB7S3IRWrZnHuYk8zxOsl+8otFe5KBBtq0rvVvVwZvuq/bvslJ9iuFrK+RurCAs3pLmplnjFBGk3zo0MVsox8rlR5ye6WirUx9TPP+TPIfpKujerg4nnnqzK0/zKZIurpZxuJ9FcLVVpipO/rjJCsd4sZUEIEfG5sWSWsrEKLEr4fM4KYcdPmJRSTgg3ZlnLPKLnZm+0WKvoEYvhWv0M7Qiq6o9A9XecW7G3QrG01H2fNDfVCK+86oDNpeBGzoD6wdyKScRoZYY6/yTRyc9Ac2N10hIRbvwWV0vx6vTJ2L54+u9dpfMzivniNFbNN6zwBikWhBuRAdXSO5G/RC5/ByRap51FQxq/0Dv1ysdZtIhFJGt1iXZkgxTOainXfG5OfED5fOxyvQgJNwmI7aXkRsKNA1s0inZq0S+D0IoNdV8LbfGgdpoU4fR2uahfKw0DT8o1TWt1R3HeNXVrploKkie7Q7cdfD5r2gqmz40FFZDIgBrNSSuariWVX+XO3Vuo3VRpPs0cih0r2hPEXHNjowLqGDMRZikX7izAMEvx3BeGdsxjHo82tHGmg3il89tdCm7kJOyM7yr/QaUm+8PCiqjD3R87CwFoO17TuhkAgF2Fx6VqNm3UqQgEFaEJMsmi9x4vbx+smVTiQXOjhP+vClmzlFV/H7HMrV0mKug55nPjyu2LmXC9ELDSSWKjeVBpWWw8T228Ga1DsRuIOBTXrZmKe85pj2GdrYWLcBoSbhzEamN12m4fCEYuu5W9nocT4eaNxpS8rDRc1as5MlKThCPY/q1HUwBAcWnVCjNW7BqxuvmQnOTT3CdPW+G3uHGm0SVWtA7R1NxYnWALikoitH5WIhS7FfI9HqZtt1bChN6n+VJwFwqPIbEIsOuU5kat9fRrhBv3loKH8meVC1QKN38/tanzhVuEzFJO4pHOXxEM2gqiZSjcWM61CrPHNHZwa4wUjN459ZpT0L9tDoDKCTREzTR7crtayPjHGW2ZaZIsTja8a3w+a5N3NCMUW5UtXpz7l0YIu7BbI0sOia4JN5ZnhOgtBXc6iF8433D+YukSBbttqXfLutLXOPUMtRGKVfm7rLlR56/XonotqB8JNx7ACT8WNVe99juKBMLk8yYXGYdiK/h8Pjx0QUf2Ocnu31wVpM+KBuOeYe3NE3FuOsnvtzTZGF1iZbyNZpwbJybXN0ediv9c1lV6ub4PYhGKrWAn12htnunWV3nYodjkKXjdgVQWu23Jin+cuv/Y6UuavaUiloJbzpZLyPRtpLnxWvMg4cZBvPRul247ZJqG17mN5konBnK/Dxjcju2wK9tB1J3Niu9J/zY5pml4zyPJ4rJLo0nCSuwIXgh8N5Cp3untcnFx98YRxzs2ykJKkt/Sain3NDfWrlMUMT80Z4L4uWuWMtXceGmAc4BYaBp8nN+yaExROp8bN3yj9h8tC+cfQv9xHIvVZ0aQcOMgXnu5ZqRyvpyNhARnzFJ8j379UbNnqu5fVhQYIq+Mp1kTierKLJN73JoPj1uaG5bwIbMag7ss9cQxK6ul3IqtYcdfLloxpdz6Khc2S8XZ+GaGXUHZyrJrp3xuIvaTUv22UycefVrViyhL//y81jpIuKnG8FarGClAnDFLGZ3TnjTTFNkdcEWECZ7sYHnZpUGZllZLueRzwxI+ZCYEH9jPN/TMrGhuvBgVVUS4ceJr2rWFYow4UdUBJ4Q1Ozk4da36G9VnITyFWfpBJ+WGzfdGcW5i4aBthMeqE9/E29DA83koN5BunPpKdWoctZJPTmZa+LeYcGOgubHQg7iaG581nxu3VkuxhA95s2HksSoziFxmPp+LmhurZikolrYgsYLbmhPjjw5Xi45LfLDQhlW9346gztfcWOlXxunvHX4yOjXODucfIlJz461GQsKNg8TbAMCbKIzkF9c1NxFpzcxS8g+9T+t6QnUJw/W5sRjEz+AiKwOe1Tg3dw5tZ3ietVRbRu1dKayxNDfW8aJ2QUjgd8jnxg1CX9wl5fx25L2nHnusfIxozFI2ylaXyxN0hOskVa5WkNLk47FGQsKNg3jt5bLo2bxO+LeVOCNOYNgBHdAM8Bg7uDUW3H068mqpNTfm1/GmrhopSZa+pg0dii2ZpaxJnFf2amZ4nifciMMWhOxoILy2FDzaPjei8PzpWJRXVNa/YXY6N02i+ds4Qf7hEnvaCtUzbZDFf/bsa6t+6oP4ydbIfMNUdVr+dV5rIyTcVDPU7c/KxoVODOQ+H18QlLcXi19RKz0ZTepk6Jz6BMxSHKeb9JQkR+PcAFr7uShlHJ8bs32qzOrOah9+n0RUXo6K3OoQyPPhcQKruX60dCce+26da/lr8pB49ukp8g0pPSUJ53VpyC5bOrfE52BxmfQ1PM2NbDgQnrbG0t5SJul542WEcCNZrNuQcOMgTkQovq5/S4dqw0bdOGW+7kI4YpaCc8HIZLIJhPfSUQ0GAtcpALo2rR1xvFJzI15+uEyeYGfBXg4ARzgxjS7o2shSPUKw2odM/SqFEflyY4GdOr33+3bnKmIAS7C79rTmEcd8vkpBRRR1ttk1UkzTuI1b2jmnSbEQC0IriFQdl13wqNGmqLpp5QpOWT8g8RSGq6U89tpIuHEQJ16u2/1anX2NVPEBMIQTAQdlVkuZIeOjUhGOsilnow4qCt4efSqevaIbTmlWO3w8PcVvSaA1ukcnY28YBclrnVvTtO48zZ5dn5vqiGO7guu485xIvym/zycn3Kh+8wSLaJocvBbplkdyknzvT1MF/lNfbeejUf28rDjcy2y7oTFL6cryWl8n4cYDqNu13QYy/67TDc+rs8+0sEWBM5obgxVDknnJ9GVWCHGR560oQO2MVFzYrTEy06u+bNMd19xYi3Mjy6kt6uC9608zfdh2fbJ4cXuMpoRLT2nCz8/FR+P2c3cid1ZbZwkCPlgzS1WWwRFuLOVmjXjR3CRb2FsuI7VqzFVfKhscVTNncAL6iWJ2C1otkfrDUJvOa6+NhBuPwfpCGt6ZbQdnYSawqDtjhiXNjX2M7MKyc4zMt1Not3PZvVjUA0+K6mKrwo36HTSpo93gMxqxIm4+vQ0aGDiPhpDdHkEP99mojjc7sXt7iCt6GW+859ZWBzLv8cpeTfHPs05ypR5GMP2XGPWW1dyIfFzFyizldUFH9rmoteXq4JtBRUGtdGv74akFXCtaL5kr1Nnry6Kl4AmMI0GhdFk8cF4HvHj1KULXfv2P/qYbRqrzT0u2INw4MLcYLV2W7SCWNDeqMkRemdoerjbV1EhJsmaWUv2efHFnzXHW5OL0+B7eS8jU58Zewdyl4KpDX43vjxeu6q6qm60iLSNT7NkdGiBNUjPilsma1f58PiDdQt8G+A7t0Zy4NMKNx0wdahTIa7RqqITOkrJA+HdQARZOPBNt6mdK18NovycRzOYtnhlff53XXhUJNw7ihupZZnVSp8bZSE32a+y6etSDlFE6Pk7sLWUxsi8DGYEyJNwYLWdkofYzUmsznDBL6a9nCzfOjho+3X95WNkeQVuOjzMhV5GdkYL2DWpVnZMYaB1FJl+bVbB6C6LtwO/zSQtfZmU4vbmvEclxorlRFPn2qN5ss6S8SrhRFAWZaclomVOTdZkh6m5q5XFJmaXUmhtdEyPhhjBEP7gY7dDNI88gZoI6exnVdYhrT2sBABjQ1nzDSR55WemOmaWsaG6g+fowv04tX2rNUn6LS8F5X0LsL2enhZsqzY1xvlZCBUSUxXhBkeWynwfrOifNUl2bZKvKFb/OB3lNhjq91SjLZlow9TErWlmA/+VvZRyyiroObkWkdgJFUWzJuSUVKuHmxH+t3K5dTZfZFTwfxcil4N56VyTcOIjRF7lwHrq/rWyKOJwTqwLQTiw8zc01p/GDu40d3Bof3dQHr17bU7peADDu9NaWruMRDc2N+hUkqT6TrAbxM3JoFvWrsEMoP7NsOzTKslkQu4wI0UbzPOSKGHJyfdlahflifH9unYywqz2yqo3w+dh60yydr0alz41VzY2lyxxFLdDY2aJg6jU9kJeVZp7QIgrAbDhvjBQbG9URoUMye8R+TQK377pZSmPG55dFe0slMLwvcqk8dNfxAsgZkZvJ79Dq3Hmq60cu7ISv/9GfeS4lyYdTW9Q1XEb+wZjTuOdCK3B4T0d6KTgjOe9rr8Kiz43GoVilzUizGMRPjca5GT7ml5fjZinB7AadlIsn/tYFdTLYsU9My4GYsGYnfLxVDYUdKu9L8hq1Ot/i++Rpbr4Y3x89VJHHfT45raxaGeYFHxf1fdrR3JzTqQH6tRbXMP/r3PZS+fNcBs48OU/o+uM6sxQQ+Y47NsoGC3XRdrdfMHvEvI8Pciiupjg1gAUsqOFTjHxuVNnzJgafz8ddTSMifPRpXY87+IeXF/PMUqa5m9eHr1qv/FLSCxRmKEYOxTb7s0isCKe/pkP3LFL3v/dsGt40L3y94E37fD6mdlD/zEVvj5XOqV3C1Uv83cZqnXkOxS1zauK/f++mOmZ9KbgXQuir+1i0fG5yMtMwoG2u1DV2LaR6h2LAuE+e0Z6tpdSuLpOvh8w7pyB+1RSNhCvxZNWdRN9ARDQ3OZlp+O/lVaH2jVa5qBun0QBo9wuO1/GtREU2glVNXt0rmHFuzMtQf6GpnWzTU/y2JwP9snRWu7GjublpUKQZMFSmqWB34ratbrnhA1CbofXR346Rmc4MB9yCAAAt62Xg1jPbohsjErUeS07kqt9WJ2wjn5v6KvNLUUmFjdVSsZ+h1HWIns+NIv1eFcWeb7na5ybI0dyoubJXM9w5tB0+vbmv5rismV2PzBVGYTS8IBirIeHGQdSv1uqEpO/LIpqbX+85Axd3rwp+ZhR8TWOWMhgAk5yaNXSEzDq8idVo4mPBejy8AbFORmrEMbHVUlWozVJWIjzr0Q8Iok6jotx9TjvccmZbZpmmz5Z3XFDY8fnYwk1EOrU5V3JEctJkd/tZJ2FU3xZCaW1t/mnZZM04duK/ejOUlcUCgDd8bjRxW3TjUP82Obi8p3EsJCNYwn4Ip6ONm3FKsypTYpXPDT99SpIP405vo7kO0GoCrQinpqulNAIN3wTmhbajhoQbB3HCrq7vLCIOxfpGpRZu1LuAA1qVr9FScJH6sxzn1BokFqGl1KKrpczmUdZEy1P733JG24hjIpNjlspkoX4/ol/H717Xm3tO/Zx9YA9OdkwvPp8PE846Cc9e0a0qP8HsQo/WqvrdByAzzV3NjVNmKVZd3KJuzUghWwSZiVQmzIN6mTfveUZp43MAes0Na38za/ku+teZuJuxXYVVgoq8tgcAfrpzMKZc0hkj+rQIHwu9A33717wbTmFJBgKHCFbj3OibisdkGxJunEU1UUm8aXUD1l+nl9JZ6Bu0Wrh5+MJOaKWKnVBLNVEbxcIQ+QJQB5xqmJ2ONQ8N1WiQWJiZpWS/nlhfqE3r1mCkrIypwiiQy38v74r+bXJwy5ltwscqAlXvSlRz079tDi7sxt7EUkRT5bSTpxX1u/Z6sQx8Ph9qpkU+I6N3bNjsfJHPPBYOsLwoTUZVUQC8cFV39G5ZFw9e0NG5uqgKVQs0VjU3XnAoVo897I1XJeqoSlo/K517bWXMGvFsQ9dYoXm9mriyVzNNzJsqnxujvmGu7ba0Wkr1W/8xrD9vZAKjvaUSGPWLT7UUIE/bQDo3zsbZHcw97/VtKjVZq6ZU10W966+R5kFEuNHvrm0WHRmo8g0Q7QZG/eXOoe00g/iMG07D6e1y8eJVYhGdAePJ9OLuTfDu9b1RW2XOUkdXthYEUV++WufL2SvIgUFDnUeKifYsREjothrAzQegloDmRj0g+3w+TL+uF7duF3VvjP5tqlbAWF1++shFnZjHxQW3yGNG/iGKApzXpRFm3NiH6axfz6o2R/Vb3Wdlgvg5scrTScw0N26ZP2SzdTKwYdVqKX4a9avRfBCram4pzo3qksf/1gV3Dm2niaTM1awKfJjFEhJuHMSsU4qgbtzndWkoNNjq06g1N/rOohFuDL7uRDqJflIyIsnvw82DW2PQSbmG6WU6SEddHJbererhzdG90LyecZRP3jJKEdRmQhmhQ/Qrz+pqKf2z0KPOImRmM9OS2TVLAUCj2pETub5U7ZehDwPa5uLGgWzfiLTkJLx7fW9Neln8PuDa05ozz9kZn43qonbKZvtViZUcqUWr+q3us511K9wM8zTQHIvgtNOv0YocwJ1JVLGQb1DnULzs/rOw5qGhlsoPDSsRK5DU1gDOtZo2YGHaUXs+1KuZinGnt9Fov3mhMyLbsbekGxJuHET9slOSrb1ojRRucdBQCzeVm1RW5aMWbow2TxRRb8pUb3jnhrjrnPbSWgijiVVmYhP18TGjIsDfF0u8LuwvZR98zOeuj2Kspk39TPw28Uy8YKKtUk+uWSfagKhDsWXZxgfUy0yL8Dky2pMm9JO14o8ljFnpI8ZRkMXyYCUzMrmqnyE7lpFYuRH14LSN7s3q4NVre+C+4Sdby1iCepnWtE48NB+JSZFtxT3tkvzYpH7+dWumCmmvDWtg0De44TPU/cfCs1GvyA37RHIK02vrteeki3YVEm4cRD0xGa1YMsKOcyWrbL9P2wjVg0XjOjVwSffGlsoAdM6wJlXVLyfmJZcJ8y7zfHgCgrTmJuCcKlpfF4A9QKiP6duVD5VCqllck6OlFeHfRrsPq/d54q2K4k3svK/O/m1zcGqLOtzrWWYR0f6jf3+tBPbmMXrldgKRGW1XodHcMG7NiSXY+jzO7tgAHRrajDItQL2azkYB1u5fZCzsm+FuYDl72y+w0N+uJkwIb4WpTbNUQBPqovJ6rcDErl9kdHXpol2FhBsHUTcsq/FczFSyIqjLTvL70L1Z7fDfR0qqJrms9BQ8eVlXzPnnIPRqWVe6HN5XIwsjdboavfDQKpc/WcnYvNXFGcUVMqPc4h47vKv0gwhbDV91LE0v3Jw4ZTaIq987L0p0arIfM28bGFlngVvOzkiJXD2h0cjw2wprIBX1WdMPsF+M72d6jdEKRJH24POxv5CTjTQ3qkZnZ8JupxI+9Zi1HbewGjCQh7rOLJOXG5obxcLKJze227KiVdSapSwIN8HItqkZ29X18xv0YzJLJS7qdmV100G7DRXQmsT8Ph8mnnsybh9yEn6cMBDndGwAoMpHI8nvQ6vcTMNmydskU6Z+ooHgyoNas8/zV3Y31DSIwh0YJDtkIGjfLKVGZMWB+ktf/yyqNsE0LudISXnEsYiJj/OK9O9uRJ9IfxW/jyHAcv6IUL2r8/HzNTese9Qnq6WLNNwgKx392+RoNDpGTVG0NbDqkmLQH9TNxuwdG5FdIwVjB7P9kazuS6YV9tkXGPVepwP/mS1tdjgOaBjZu7AiEOkJ7QIe+rg0dChW/daEp1CnsVAftVkq9OxF+m5EjC6PSRMeq058Y9ksxXFwdcbnBshMS8atQ9qiTf1aaJFTEwsnnoFPxmqjXBoNXoPb1UezuhkY1qmB5rh6EDKb8yPNUux705ulmtTJ4K5+khFMeIO27CMWMUtNvcbY/8Vn8JvtUFx17PazTmJqNcxuQ6254V0ToQlTNP8Jw9o7h/UueOpso4qE0hltIaLGzDesTf1MvHt9b/xw+0DDdKKBDY0w1NyofjMnbImCeSurorEvGQuny1B/GLI+Ep2ObQSEHIrl8g3tVGeH967vjVvObIsXrupemZuh5qbqXKfG2Rh/ehs8dklnw8B6IgQ0JlPfif+qyuU4NetLIs1NAqNxKLZslqr6bTXmRKrG5yYyj4bZNSJWSoU2mGOpgdOS/Zh3x2C8dLV20vZJ3KKoCpclPPAeg1WzlBrZwUAkANspzepEmNO4/iu64tk+N1UH87LS8YPKdBQe2ExuowcrfoVecRMh25xYCs6ou97sytv3iPVbD2vjP735TeRao1dpJHjwSE/xo1+behHHfWA/biNtralZygWfG0BeeLdSC6c1NykaszprKbg3JlEnAhs2ql0DE846CfVr8Rd3hNDf9h1D2+GKXs244QBEYX2YiqyQingP3ngtYWIu3Lz44oto0aIF0tPT0bt3byxatMgwfWFhIcaNG4eGDRsiLS0NJ510Er799tso1dYY9fhpeXmkuvFY9blJVg8OYnmMHdwaUy7pjLl3DI44pygK/H5fxFeFRnNj0tMjJkhOtSoYPc2JLwIRe7UIdwxth9Pb5WLqNT2MEwoPfLpnarL0NcnvY65YMHtG53dphJeuPgW/3HMGN42+yoavVC+UmdTb2Ik38rfoakMzE4b8PFh1QWqSH+9dz9/hXo+Rn51auGd9tMh8yMiEUZDVRpglf3PUqaiVnqxp/04LN+qxUy8v+nw+yWclXq7sXViNUGwVXlF2F6Gwxm6tv5w6f3Yaq2W7SUyFmxkzZmDChAmYNGkSli1bhq5du2Lo0KHYu3cvM31ZWRnOOussbN26FR9//DHWr1+P1157DY0bW1/x4yQyDrZqtCrrqt9WbctWtEapyX5c2asZmtbNiDjH07qoG7O+f9wzrL3mb1GHYpnVUjLw97KS65A5mWl4c3QvnKMz0VlFKwBECpBA5NcSS2gwuw2/34dzOzdE49qq+BW6i3jaJdZRfXFmQpmhcMMYSZk+N4xr1UKVE3OsuiqG2h6mQ7FRBYxXSzkxMTihuTHj9Pb1sfKBszXt3+lJLSXZRHPj4E2FIvJeekoT0z6UlZ6MS05RzTU2N86Uhf+BZq8PsPYvFNF068uipeAqnn76aYwZMwajR49Ghw4dMHXqVGRkZGDatGnM9NOmTcPBgwfx+eefo1+/fmjRogUGDRqErl2N9zOKFtp9gvhveuZtA7jnDNV+JzhFtfqJhXqQdUJY4Gll1OOOPs2NA1th/l2nm+ahp1zCLCWDlzoe76uIh35pLFO4caBe+idfL7NyiS/r1bG+2tTbcUSkN6gh08Qj6J2o/ZJkCViSmgvV75Cw8PU/+kckkq2zuhs6vTmqcb7mGatfr1B71HUmx81SGt9FdwW2aaNPxSvX9sBd57Qz1X4uue8sPHVZ1VwTbc2NyNux8i7MhmbeR7vRwgAvEDPhpqysDEuXLsWQIUOqKuP3Y8iQIVi4cCHzmi+//BJ9+vTBuHHjkJeXh06dOmHy5MkIBALM9ABQWlqKoqIizT+3EP2CMYoLwRpc9QzpkGdo9kpRDbLOCDfs4xrNje6cz+fTaIH0efBqz6qvE50mGktigUo/jbo1U1FH55vDXwoeaWLSo/9a0gf+0+czZkBLfHOLbkIWIDTITb3mFEwc1h7dmtY2rLu2jsCr1/ZELU0QMzFNpnZyrUwoatbVbzyqR/ata7apOFGHToLRflkTcQj1BMLq12aT0o2DWpmWbxYjqXm9SK2sE/h9PkcFDrXGjKWlYZmlujbJRoMsc78VPVnpKRjasQHSkpNMBZXUZL+mfbikZNbQ1uCDgYVjWi1OvzLycSOz1An279+PQCCAvDztyou8vDzk5+czr9m8eTM+/vhjBAIBfPvtt7j//vvx1FNP4d///je3nClTpiA7Ozv8r2nTpo7ehxqNh7mhGt4gD9VJq347ap8bqzsQq+nahD24qwcZnkkjRMRqKc5DYPncOCHdRKPbXd+/JVY8cDaSk/x4+u9d0bN5HebO6bL10i+/NFuFdHbHBujYSDz8vp5zOjXEjYNUy42ZauvIr/dm9TLw/IlVH5V1FStP3XZC1ySxIhSzJm+NWcq6aSycRvWbVQejvIw1N8ZbHBgJNxd0bYSJw6oiDfP6mln8nMEntj4xwspHQJIf+HHCIOnreKiFRH1tfGBP4Ff2aobcWs4GEzTDyb2lWFxxalPcc26VeV/k1Ti18ak6F814o2ri5FDsIMFgEPXr18err76KHj164PLLL8e9996LqVOncq+ZOHEiDh8+HP63Y8cO1+onqhI0SiXqHGYWd2LB3adj3h2DbYUDn3fHYLw5+lT0bMEO8KeunplqU3RlgdMRgMOo6+pOCUhN9odXoTWvVxMfj+3LXDatqZbA5KuNCqprFyd+uzmuMH1uOF9t6gleO0DK9Q1hzY2Jz436kIgvmrqaKRxhhWe+MFwtpU7HyNd4CTD3lAZz4c56KzH6eAnFyhLhzdGnMlegqVE/H7PQCOH6gePULlQrayiKuSO/LOpbe/CCjtx4NjxCz+Zl3cpWO/XgbawaKXh6S7qxHx3NIjk5OUhKSkJBQYHmeEFBARo0YDtrNmzYECkpKUhKqlrGfPLJJyM/Px9lZWVITY3UUqSlpSEtLToSvVZlZzRYVX59s30Zqq7jCUuKYq4paVLHvgq6RU5NtDAIZ69V0UpqbjjpWBOEE50m5ipTzuMRubcIh2LN9Sf+64s85hTMdqr7O9RWedpLozqxHo16gquTkYJDx8pxTseGEemMHKT1pCb5UVZhHJApRRfdm4fsPlf6peA/3TkY5QEFQ57+qfKYoDbXCKZwI9karHQTmb6VlZ5sml4fp0sPT0a1a5GRvXfFwjVmDOvUEJ8s3YmuTWsjLdmPMtVediLCaajbDOsc2VcswxGQIwOQOlekE8RMc5OamooePXpg9uzZ4WPBYBCzZ89Gnz59mNf069cPmzZtQlBlutiwYQMaNmzIFGyijZFUK56H6rfRYGkxf7cwq88pzepo/ub100aqycosrQzRkG2M/UpUZgnONfzN6tS/tSuqqhyKI485BUv9HhEWwM/S3IjViRUhVy3kzvnnYPx052B0VplHp43qifGnt8Fw1SDOKkM9UYpEDc9URYA2Wi3FNksZCTfav5vXq6lxwDYWpPRls9Oy4+eo68BZDWdzMJFzYjVPqzZLsbRcPOHI7u7k8pv6Or+3VK+WdbFy0tmYfl3vyo9gTgA9Hk6ZpXgYLQWP9fejnpiapSZMmIDXXnsNb7/9Nv7880+MHTsWxcXFGD16NABgxIgRmDhxYjj92LFjcfDgQdx6663YsGEDvvnmG0yePBnjxo2L1S1oMHrxavSn1IOOJkIxJxOvNSJAG8Jbzex/DsJ9w0/G+DPaCOXTmCXc2KqZc3nECr0ww9SIuHiDIpqbULtNsqC5yUit0sSG9ilST5gZaUloXk+rQTyjfR7uGNqO63Pz4Pkd0LRuDdx/XofwMZGBX+0QLTtZGmkkzDSbhhOrsFnKuE4ik7c6hfpZjDud339lJlSRR6oWSOtkpGC8rmymWUqxr52VvdqJIH4s+KuTzK91yu+I9wGWZNCeyCyl4vLLL8e+ffvwwAMPID8/H926dcPMmTPDTsbbt2+HXyW5N23aFN9//z1uv/12dOnSBY0bN8att96Ku+++O1a3oEE9IBu9Zp+v8ryZL4Oxmlu6eq7Cq0/r3Ey0ZtjjeR3hbz2aCJfZjBGTh4e6I7o2KBm8daEyOZerHcQrV6YwzA+aQ84OMiJ1D7XVJAs+NzXTkvHaiJ7wAchIrRySUkz8Lliou8uofi0xql9LzXmRbNSaGxltCmAWodi4XKNJX/j+TeLcmJmyAWge0spJZyOgKFizuwidDVaM8TTMbetnYuPeo7r6+Eyfhd436o6h7fDC3E3hv1nvRYESddNzNIZgTR8y6NdvjOyJA8Vlwr5PpuVyrBB+gznOa3tLxVS4AYDx48dj/PjxzHPz5s2LONanTx/89ttvLtfKGryvpLRkP3q2qINfNh2oPGcU88PAphnCa4ININ/ReePQBV0bMdJGJu7Vsm7E17wR0bAHWxlbza5pXLsGHrqgI4Y9Ox9A5QBi5jjrNMx3qysw9EWn1naILHMPcVYHreN1EkcjY4R5OgHNjcqBkxdGge/4bV1z48RmnmwNivWW4ff74IcvHBJAtNyBJ+ViyiWd8d0fe/Dvb/7UnBNx6jYSEn0+tjClKOaBJM2Q7b+VcW7cHVhEA8OaLVyQLpdTB21EcN01HjMpxFy4SSR4Uu2AtrkY0ad5WLgxGm/UDcbqzuKxQDRInxG10pM5gdgi0w7k7FTOR2yQiAa8nXVZ9frlnjNQUl4Vx8mvs8Oz8nEa1hc/76uNN8HLVq+GylQleqlZGSICboZqz7Xj5fz4WdI+NyblGp23I9yJCfVsfzBR9MJGrfTkCPPy9f1bYu+RUpzcsJbpEmozcyDvtN0YL7JmlWh8ZHphBtBqblTHI8xS3oKEGwfh+dyYRbJkBTGrzM9rzYWPEx2dd7fM71HJZ6NO7iXNl+wb9vug2bA0dCvaLy2blRKA61DMFcjlKtWiXgYu79kU2RkpwpOWWZsQ6U/qskqMhBvG/RguADDzuTE6J/jo3NrWwQyeMkZ9y/epfJ/M+p/akZuVlKWhUmC84kwEdbbt8mph39FSHCwuE77GDWR9btwu13j7BW/NVyTcOIi201X9rtCptyudQn3MXq4PtR8vyGpuWP1AZkNAWaJiljI4x3s8IvemN3eyhT3zfJxEX16ojrwIprL18/l8ePxvXeSuMc1Trg484YaXjcxqKT05Bo6gooK8aEwYRgmqsoSK0qAXNppL+MKxMHqOPnCESEWxPV6qrx7aqQF+++sAFhUftJWnXbSm3djMB+pyk3hf8JF/xhyPuQDFNxqzlFpzE1SEl/Tx7JtqhjsZw8AhnFCGyHQO0ZD44bw9pzStRF0vEflQ71AcukZ2yagMMnFuND43Gi2kw5ViYDaRi1ah5YnYTgPbGkT0ZWSW5PehV0t2wEuzUP0+VG57wTwnWHHrPif2em9o3PtgzGkY0ae56cpIU+dqv3Gf4L1nJ+L8hEjy+YQ+2KI5oRtt7+E0vOdm6HPjZoUsQJobB+Htkl0RDApHCtXGuYk8375BLcPAerFCaCWGCqbfiEHqEN/fNhDr8oukfW6iMggJFsLVaHAeoXrSqpuRytF6CRVtCZEw86FBL4kj4EdDuDQToEQ1IP+7sQ8WbNqH/m3Ywg0vH7/Ph3ev640vVuzCnR+vkqpb6Hr2cfNreddrzLECeVh5T6F336d1PfRpXRV9mNduzNqT0dJyn8/HNYPZ1nSrLk9OEhRuotCuR/Vtgf1HSw03pnUT3tylv3dyKE5gknQzVafGWVi9qwiXnNJEt6TPwL9ErblhdFYn9opyA1k/FqtmqXYNaqFdg1pyhSH2XxW8AV2kXkl+Hz4Z2welFUFkZ6RozCXRcB8yi6QNVH1tawUadXoXKmZSp8jzYvnk1krDxd21IQla59bEX/uKq/JiXJfs9yE12a9xhh7VtwV+23wAF3ZrbFoub3IWnUDN4ty4hezHVuPaGQD45h6zBVUy2y/IoDe/RGNjTBEevKBj9AvlPEqj7U48JtuQcOMkakfPoALMuKEP1hccQfemtbFw8wGhPDQ+N15rLQY4sVqKd7dWdvuNyDsKz9JSCZova/4z7NGcbe4IZyOoGbQC6902yErXOFuaaW6iMcmaxdmwU4Xvbh2Ik+77TpVXZGahyVV9rw+c10F40u3fNgdt62fi5IZZ+HLl7qp8Bet933kdsGz7rxgzoKXqWrmbblo3Mogmj/eu741fNu3HFafKbUZ87/CTUR4I4u89m+KaN36POG9WZ14QP7vjpU839opoo+NoiJaC92GiFjz178Frpn8SbhxE3bmCioKaacnhbQeMQtGr+5DGG91m3IZoIh3nhnWMc2+NatfA6yN6IjsjhZ1ApDyPPjdZnxsg+qsS1LFfQrx49SkYMe137Dh4HIAqiJ/O+bnqD3frWFmE/KQoioi/Q8jfyKrGKi05CT/cPhA+n08j3IgKq61zM7H8/rN0UZvNr1O3u/5tcnDf8JPRvkGW6XX92uSgXxu+eZjXnuvWTMVzV3bnXmf2nngaLicXYCT5fbjmtOZYqTMvVke4K3h1j9tr61/IodhBRLZOAEwGYbXdl7nLrcda0AnkzVJM8YabfkiHPJzK2Z1crDzLlzqCZv8kXhrBvDTN4kTGbjoUP/X3rujQMAsvqXYabplTE+9ff1pVncJmKXY9ovH4zQZXO8KNSEwP5jOQLFM0zhOPiA8iyVv2+Xy4fkAr9JeOI+Uc6nACLG0mW3PDjlAs8+zUSZP8PqFo6d4cje3D8ws0Cq4Z6zFWDwk3DqJWi+u/IvSNhdcQ9DtAVyfcvN1oCIVW6q/WCIh++ZhNgE4/x9a5mfj21gE4V7dKT93GQ7ehPqaJ3xQNs5RDq6Wskhw2S8lfq38+157WvOqcnSjDAs/dI64lYYzq7AP7+Sow99UxQxMd3u8TarNec6J1G6PNob02X5Fw4yDql6sPZib62s3i3His/VhGTm9jH80eOy4N51YmodoZqfi/fi0xul8L1M4QcxbX3kuo7OjDMqGq66beTDUa9TPtGw5VgvdxEtLWygzyoT2b9FqC24a01ZSnKV84d/4KzmggUtzrI3ri1BZ1NMeMzEstc2qy95bibL8gg/pqr5lYog1PE6zt87prPDY5kc+Ng6hNUUm6Ny/64rkBkzjEayeM9nJmT3U8XV0eOL8DJyHvcpbQG/37Y6mo/VzNjfv1MV0t5WBZ6aptGkKUBoIn6iGez8dj+2DXoeMRGx469T41wiZHuollzxjSIQ9DOuShxT3fhI+xBLKPb+qDr1ftwW1nnYTFW9krrWzvCm7iEsC8xlaJ3oW3QEG7OTSZpaoNRp0jwiwF9iSgiXMj0FqS7epiPYSbpiM3+12j7MrVXGd35G9e5/ZHs0/zOzqjjHq38tDEqXeqr6qT+9jxuZH1zchMi/wuLCwuNy1HT1pyEnMnZ3UOohMtC3Vb4Ak3XjNLsT7qeraoiwcv6IjMtGTm8x14Uq6jDsVeM7HYJbdWGt69rrela9VPIkmzt5Q2Xc3USIE/lpDmxkGMYtToJ5/zujbEp8t2oUsTfqRdtllKeywlTlU3dh0nZVFPxE4z547B2HekFE0Fw867cZuxGIvTVM80tIM2zwziCZ8bB6tQkyHcHDp2Ymm8A+XwnDgBOWFEsw+Z16QYDmZDmlqAnnfHYCT5fWhaN8MBh+JITaTARXFBeoofzRjjU6+WdbFoS6QmjL+Nio/5GwBG9WvpQE2dI3E++z2G4f4oPuDfF3XCfy7rirdH90JuZtW+MurAUSJxGxJLc+M8T13WFY1r18B/L+/mQu6VpKckCQs2ThPefiEG0k2qqu1VBE4IN5rJNLqaGzOc/Bqvlc7Q3Byr1NzY3VsJ0E60dvq4n6NJiwZWizOLC6Q+XSs9Odz3eL44whgIlAKXeJorTm0WIejlZKbh/evZ2hyuWUqz4KUqzXldGjK1mbHEW7VJICJXS2kdtDJSk8NOhLcOaYtdhcdwcffGmgEoiRFbQ38kJZGEGxcm6Et7NMGlOmfNa09rjukLt0Ws/nETt+YVlnO01ceYk8nfvJGFehKqCFb6m2gnU3WlrNVJqj5REvB8Prbm5viJyNGtcjPxxsieqCf5PLWFVP20Y5bS+txYr040Mf2o45jubTsU+9i/E4GbBrXG7sLjmmONaqdzBWdeXzLyufEaJNy4hJHPjZ7sGil45dqeAICfNuwLH2d1cv2haG6mlijUy0zD4nuH2A7Xnmh8eIM1mzxQZZZSt1m14BWVvaUshO23ivor9aJujTBn3V48fGFVmPwzT+b7X4mg8d+z0cdFNDey+8K5wbvX9Q5HK5YxIfsZTu1W0fo5idXBUwsVDEjy++TiJXHS8gJExr4FRULCjUvoV0upMeoQ6oGGlYX+Sied6GJNNMeJWAo2Tt4na15Ks+Bf9O+LOqFNffk9u0KUh81SbM1NNN5tVH1uVM6TF5/SBE//vZujbUoTVsLAf0+G6C8FFy+wf9scjOrbApv3F0sF61Q/mhqMFWxW37moQjyeRl99/zBqD9wo0BxfHC9Cwo1L6DuHj/NbjyLpcxNrs1SS3xf+areL1zuLPdyfWW4b0hb7j5aibZ68kGL3q5fVBqLtc+PUxpkCJWnU+cfLAo4Ly9oVKs743HhBQ2OElQ0i1ZPwqH4t8Mmyndh+8Bg+H9dPOi8rkaXjacyScq7mJFY3c00aDzYtEm5cwijOjVEjU3/tiKyWsmOPd4KUJAeFm7j6DrIOa68mq6gf/W1DTrKcj91BOuRzo0Z9KCpxbkzPu1OJVrlyu2KLYCXmCot49LlRwxLIeKuasmuk4Oe7TrdclkagjCepRRCZ9i9ilvL6EyLhxiWMVMnGZinjdPojsV4tlZLkR0l55MRmhQSysBlybqcG+LFro4jIrFYIMIQKK9h99KHVUmq0cW7cf7kss4Qau+1r0Em52HnoWDh8w48TBmLP4RKcZEFTZoZsME8e6sk/oHofTerUwM5Dx1mXOEY0FEVO+lEZLb/nXuP5Kb4K/aMyMhtyHYo5x92K+m4HEm5cwmhvKSNEv67aN6iFdflHcEn3xpI1cxYnzWLx4pxnBfVAn5zkN9wVWQaWUGEFu5NEBcsspfrt5qt94tIumPrTX5h8SWfDdHbb11ujT4WiVH29tqlfy5afkhHqqtpZNKCxHKga4dv/1wtnPvVT5XHLubuP2Ttz64NI1MwYT0OWvq7N6/I1jrzxgOdT50WLZ+KsI/YYkZobsV5gFosi1OZm3NgHb/9fL/xf/5aW6ucUTq7WiqNxwjOUO6S5sfvwWaZJjebGxVng76c2xZw7BqNljrF5yG4VfD5fTBzR9SZumSqon7t6aGnNiIrsRcz8hMw1LOIPS6MtM2gsH93UB23rZ+L9MdZXF8YC/Rz00IVaHyetPw07D+3jrno3XhRuSHPjEqwYNSKYN5LKfLNrpGDQSbmWynASRx2aSbqRxinNTWubfiPlgUghS2titZW9I3igCsIYaW7+1rMp3vp1K05vX18qTy9OQDwy05JxtLTC9B6dFJrVWRn5cJ/aoi5mTRjkWLnRQn1/Nw5qFRHXSrMrukCcG6/7cJFw4xIycW7UeH1Fg55UJ81SjuVUfWCZg2T4fFw/bNl/FD2aiy+/ZWG2WsoL/lTxtF+Qkc9NZloy5t4xWHpiD8TR2PLzXac70i6tEk9tRRTtit3I+1M3M55GLJa7zMtCwo1L5NbSSsUnN8xCp8ZZmq0WWJi1F6/1OfK5EcOtcaCCoTGRoVvT2ujWtLbterDNUlW/veB4yWpeF3ZrhC9W7Maovi2iXh8jtKulIvuYlb4STx9OdWumom5NtmDj1jBhZYVaPI1ZpnGgVH2Ul1Qt9KidiMmhuBrw7BXdsGjLQVzQVevom+T34avx/U2vb1HPxG/AVu2cJyWZfG5iiV3NjVOw9lqKlkOxKCwB65nLu+HxS7sg3WSlVbRR19SpcA/RbirxJEzpEXYodrkeTmLaB9VmOW6cG9LcVFsu7NYYF3Zjr2ASkfI7NMrCS1efgka1a3DysFU9x5Hdj8gIr91bPOCUz41VXhvRE8/N3oin/t4t4lwwykH8TGFUwufzeU6wAXSbFTrktB/tjTPdIrQUn7XLtR7XdwWPI8y0p34f+zcvjbo9ebFpkXDjQaK5oaNd/n1RJ/zjg+W4zoFVW14wXbiFW1+xrOB50eSsDnk4qwN7HyUlSqulRPGC348o6qqm2IhQrIanuXFrYmpT350VWRmpyfjz4XMc31dPE+cmESMUq5oRc8NdAeHOC/1YFBJuCFs0qZOBz26WD3XOIo76jWcoj7HmxogYy10RxNPXuJWAcmZE20w0tGMDPHh+B3RxwKdLT41U57Vt6qfskDzpKUytUpql4OZtTt2cvDgKkXATZySydoNILLRxbmJYEQ/VQRT15OKUhoIn27gl9Ph8PozqF9s4XDJoTIEJGcTPzCylvn/z/LzoRKwmAeXTxCaeOpMs8aTylMXbw4A7eG21VDxpbtQ4pbmpneHcnmbxgtUnJ2yW8kC7FkWjmWJt7SPgUKxGrZklnxvCNu0auBPu3QvEzzBBiOEtzU28YjfcwvNXdsfW/cWokZqEr1ftiTifyB8VMqhlyHoOLpTwCmqB5ZRmdSLOmwk/ejwoz2gg4SZO+GJcP8z+swA3DWod66q4Rtem2bGuAuEgWs1N7Im3SfzvPZtg75FSdGyUZSuf87s2AgC8Pn8z83w8L9l2Ep/Ph//d2Acl5QHUrZl64pixViKemlSN1CRc2aspjpcFcCYj8rO6f4jcl9dX35FwEyd0bVobXV1wzPMCE4e1x5GSCtw4qFWsq0I4iOIxn5t4Wi0FAE/8rauj+Xl8LvIEvVpqAwe2rFcTm/cXc9PHWZPClEu6cM/5Jc1SWrzXuMjnhog5JzWohTuGtkOt9MT1CaiOE4tGc+MB6SZefW6cokF2eqyrEHe8MepUDO2Yhy/HO7Mi1Iv8rUcTAMAtZ7YNHxP6EPD4mEaaGyLmNBcIxkXEH2q1tUjANbep3qINMLxzQ6zZXYSezSP9LRIVu/Jsy5yaeOXanu4V4AEev7QLxg5ujVY5VdHxRSI0UxA/guDw9T/6Y9/RUrTKdSfYFxFb1APeFac2xa7C4+jXOidm9UmAecgWfr8P9wxrH3Hcg/MSEUWS/D601o3BIlrOph74YDGChBsiZnRqXH0ciGUmkFY5lXb+vKz4XrGh/rJLTvLj7nMiJ9boUs2lG8JxErVFGSlu3h/TGxvyj6Bv63rhY14UkMnnhiA8xtv/1wtX9W6GD2/ow00z9ZoeAIAnLuU7CMYar62miDeHYsL7JKo20Ehz07d1Dkb1a6nxo/PiijvS3BCEx2haNwOTL+5smOacTg2w4d/DkJrs3e8Tr413iToREYTTyC4A8FhXB0CaG4KICm582XhZsAG8J9xU99VS1RG3Iwh7uUWFIlI3yJJfJZcIWk5vj44EQcQtXtt7hmQbDt56TY7Sw+WVYV4IccDjoxv74PyujfDu9b2lrxXdfsLLkFmKIKJAh0ZZmL9xf6yrEVWCHps0vTwREe5wQddGUKCga5ParuTv5RbVNq8Wnr+yu6VrRZaCq/GalhYg4YYgosKtZ7ZFWpIfZ3dsEOuqRA2vORR7eSIi3MHv9+Hi7k1iXY24Q/Y7oEmdGu5UxAYk3BBEFMhITcaEs9vFuhpRxWOyDWluCMdJ1CYl6p/23vW98emyXbhraKzDPERCwg1BEK5AmhtvM6BtDuZv3I+rTmsW66oQHkPUKtWvTQ76tYldYE4jSLghCMIVvCbcZKQmxboKnuKVa3tg6bZDOK1VPfPEBBO3V2PFikRYWUirpQiCcJTLTmzEd9uZJ8W4JlomnH0S2jeohQfP7xDrqniCjNRkDGibi5QkmgYsE/8yAJNEMOGS5oYgCEd54m9dcPew9sjJ9Nb2EfVrpWPmbQNjXQ2C8DxJ8S/bkOaGIAhn8fl8nhNsCMINEkAGYCK7FNyLkHBDEARBEBZIAOsNk6Z1vL3jtwhkliIIgiAIIszgdrm4Z1h7dGyUFeuqWMYTmpsXX3wRLVq0QHp6Onr37o1FixZx07711lvw+Xyaf+np8ntnEARBEIQdEnW1lM/nw02DWmNA29xYV8UyMRduZsyYgQkTJmDSpElYtmwZunbtiqFDh2Lv3r3ca7KysrBnz57wv23btkWxxgRBEAQBpKfEfAolOMT8zTz99NMYM2YMRo8ejQ4dOmDq1KnIyMjAtGnTuNf4fD40aNAg/C8vLy+KNSYIgiAI4KELOqFVTk1MvrhzrKtC6IipcFNWVoalS5diyJAh4WN+vx9DhgzBwoULudcdPXoUzZs3R9OmTXHhhRdizZo13LSlpaUoKirS/CMIgiAIuzSrl4E5dwzGVb0pyrPXiKlws3//fgQCgQjNS15eHvLz85nXtGvXDtOmTcMXX3yBd999F8FgEH379sXOnTuZ6adMmYLs7Ozwv6ZNmzp+HwRBEARBeIeYm6Vk6dOnD0aMGIFu3bph0KBB+PTTT5Gbm4tXXnmFmX7ixIk4fPhw+N+OHTuiXGOCIAiCIKJJTJeC5+TkICkpCQUFBZrjBQUFaNCggVAeKSkp6N69OzZt2sQ8n5aWhrQ0CihGEARBENWFmGpuUlNT0aNHD8yePTt8LBgMYvbs2ejTp49QHoFAAH/88QcaNmzoVjUJgiAIgogjYh7Eb8KECRg5ciR69uyJXr164ZlnnkFxcTFGjx4NABgxYgQaN26MKVOmAAAefvhhnHbaaWjTpg0KCwvx5JNPYtu2bbj++utjeRsEQRAEQXiEmAs3l19+Ofbt24cHHngA+fn56NatG2bOnBl2Mt6+fTv8/ioF06FDhzBmzBjk5+ejTp066NGjB3799Vd06EA7/RIEQRAEAfgURVFiXYloUlRUhOzsbBw+fBhZWfEbWpogCIIgqhMy83fcrZYiCIIgCIIwgoQbgiAIgiASChJuCIIgCIJIKEi4IQiCIAgioSDhhiAIgiCIhIKEG4IgCIIgEgoSbgiCIAiCSChiHsQv2oTC+hQVFcW4JgRBEARBiBKat0XC81U74ebIkSMAgKZNm8a4JgRBEARByHLkyBFkZ2cbpql2EYqDwSB2796NWrVqwefzOZp3UVERmjZtih07dlD0Yxeh5xwd6DlHD3rW0YGec3Rw6zkrioIjR46gUaNGmm2ZWFQ7zY3f70eTJk1cLSMrK4s6ThSg5xwd6DlHD3rW0YGec3Rw4zmbaWxCkEMxQRAEQRAJBQk3BEEQBEEkFCTcOEhaWhomTZqEtLS0WFcloaHnHB3oOUcPetbRgZ5zdPDCc652DsUEQRAEQSQ2pLkhCIIgCCKhIOGGIAiCIIiEgoQbgiAIgiASChJuCIIgCIJIKEi4cYgXX3wRLVq0QHp6Onr37o1FixbFukpxxZQpU3DqqaeiVq1aqF+/Pi666CKsX79ek6akpATjxo1DvXr1kJmZiUsvvRQFBQWaNNu3b8fw4cORkZGB+vXr484770RFRUU0byWueOyxx+Dz+XDbbbeFj9FzdoZdu3bhmmuuQb169VCjRg107twZS5YsCZ9XFAUPPPAAGjZsiBo1amDIkCHYuHGjJo+DBw/i6quvRlZWFmrXro3rrrsOR48ejfateJpAIID7778fLVu2RI0aNdC6dWs88sgjmv2H6FnL8/PPP+P8889Ho0aN4PP58Pnnn2vOO/VMV61ahQEDBiA9PR1NmzbFE0884cwNKIRtPvzwQyU1NVWZNm2asmbNGmXMmDFK7dq1lYKCglhXLW4YOnSo8uabbyqrV69WVqxYoZx77rlKs2bNlKNHj4bT3HTTTUrTpk2V2bNnK0uWLFFOO+00pW/fvuHzFRUVSqdOnZQhQ4Yoy5cvV7799lslJydHmThxYixuyfMsWrRIadGihdKlSxfl1ltvDR+n52yfgwcPKs2bN1dGjRql/P7778rmzZuV77//Xtm0aVM4zWOPPaZkZ2crn3/+ubJy5UrlggsuUFq2bKkcP348nOacc85Runbtqvz222/K/PnzlTZt2ihXXnllLG7Jszz66KNKvXr1lK+//lrZsmWL8tFHHymZmZnKs88+G05Dz1qeb7/9Vrn33nuVTz/9VAGgfPbZZ5rzTjzTw4cPK3l5ecrVV1+trF69Wvnggw+UGjVqKK+88ort+pNw4wC9evVSxo0bF/47EAgojRo1UqZMmRLDWsU3e/fuVQAoP/30k6IoilJYWKikpKQoH330UTjNn3/+qQBQFi5cqChKZWf0+/1Kfn5+OM3LL7+sZGVlKaWlpdG9AY9z5MgRpW3btsqsWbOUQYMGhYUbes7OcPfddyv9+/fnng8Gg0qDBg2UJ598MnyssLBQSUtLUz744ANFURRl7dq1CgBl8eLF4TTfffed4vP5lF27drlX+Thj+PDhyv/93/9pjl1yySXK1VdfrSgKPWsn0As3Tj3Tl156SalTp45m3Lj77ruVdu3a2a4zmaVsUlZWhqVLl2LIkCHhY36/H0OGDMHChQtjWLP45vDhwwCAunXrAgCWLl2K8vJyzXNu3749mjVrFn7OCxcuROfOnZGXlxdOM3ToUBQVFWHNmjVRrL33GTduHIYPH655ngA9Z6f48ssv0bNnT1x22WWoX78+unfvjtdeey18fsuWLcjPz9c85+zsbPTu3VvznGvXro2ePXuG0wwZMgR+vx+///579G7G4/Tt2xezZ8/Ghg0bAAArV67EggULMGzYMAD0rN3AqWe6cOFCDBw4EKmpqeE0Q4cOxfr163Ho0CFbdax2G2c6zf79+xEIBDQDPQDk5eVh3bp1MapVfBMMBnHbbbehX79+6NSpEwAgPz8fqampqF27tiZtXl4e8vPzw2lY7yF0jqjkww8/xLJly7B48eKIc/ScnWHz5s14+eWXMWHCBPzrX//C4sWLccsttyA1NRUjR44MPyfWc1Q/5/r162vOJycno27duvScVdxzzz0oKipC+/btkZSUhEAggEcffRRXX301ANCzdgGnnml+fj5atmwZkUfoXJ06dSzXkYQbwnOMGzcOq1evxoIFC2JdlYRjx44duPXWWzFr1iykp6fHujoJSzAYRM+ePTF58mQAQPfu3bF69WpMnToVI0eOjHHtEov//e9/eO+99/D++++jY8eOWLFiBW677TY0atSInnU1hsxSNsnJyUFSUlLEapKCggI0aNAgRrWKX8aPH4+vv/4ac+fORZMmTcLHGzRogLKyMhQWFmrSq59zgwYNmO8hdI6oNDvt3bsXp5xyCpKTk5GcnIyffvoJzz33HJKTk5GXl0fP2QEaNmyIDh06aI6dfPLJ2L59O4Cq52Q0bjRo0AB79+7VnK+oqMDBgwfpOau48847cc899+CKK65A586dce211+L222/HlClTANCzdgOnnqmbYwkJNzZJTU1Fjx49MHv27PCxYDCI2bNno0+fPjGsWXyhKArGjx+Pzz77DHPmzIlQVfbo0QMpKSma57x+/Xps3749/Jz79OmDP/74Q9OhZs2ahaysrIiJprpy5pln4o8//sCKFSvC/3r27Imrr746/Jues3369esXEcpgw4YNaN68OQCgZcuWaNCggeY5FxUV4ffff9c858LCQixdujScZs6cOQgGg+jdu3cU7iI+OHbsGPx+7VSWlJSEYDAIgJ61Gzj1TPv06YOff/4Z5eXl4TSzZs1Cu3btbJmkANBScCf48MMPlbS0NOWtt95S1q5dq9xwww1K7dq1NatJCGPGjh2rZGdnK/PmzVP27NkT/nfs2LFwmptuuklp1qyZMmfOHGXJkiVKnz59lD59+oTPh5Yon3322cqKFSuUmTNnKrm5ubRE2QT1ailFoefsBIsWLVKSk5OVRx99VNm4caPy3nvvKRkZGcq7774bTvPYY48ptWvXVr744gtl1apVyoUXXshcStu9e3fl999/VxYsWKC0bdu2Wi9PZjFy5EilcePG4aXgn376qZKTk6Pcdddd4TT0rOU5cuSIsnz5cmX58uUKAOXpp59Wli9frmzbtk1RFGeeaWFhoZKXl6dce+21yurVq5UPP/xQycjIoKXgXuL5559XmjVrpqSmpiq9evVSfvvtt1hXKa4AwPz35ptvhtMcP35cufnmm5U6deooGRkZysUXX6zs2bNHk8/WrVuVYcOGKTVq1FBycnKUf/7zn0p5eXmU7ya+0As39Jyd4auvvlI6deqkpKWlKe3bt1deffVVzflgMKjcf//9Sl5enpKWlqaceeaZyvr16zVpDhw4oFx55ZVKZmamkpWVpYwePVo5cuRING/D8xQVFSm33nqr0qxZMyU9PV1p1aqVcu+992qWF9Ozlmfu3LnMMXnkyJGKojj3TFeuXKn0799fSUtLUxo3bqw89thjjtTfpyiqMI4EQRAEQRBxDvncEARBEASRUJBwQxAEQRBEQkHCDUEQBEEQCQUJNwRBEARBJBQk3BAEQRAEkVCQcEMQBEEQREJBwg1BEARBEAkFCTcEQcQVo0aNwkUXXRTrahAE4WFoV3CCIDyDz+czPD9p0iQ8++yzoNijBEEYQcINQRCeYc+ePeHfM2bMwAMPPKDZgDIzMxOZmZmxqBpBEHEEmaUIgvAMDRo0CP/Lzs6Gz+fTHMvMzIwwSw0ePBj/+Mc/cNttt6FOnTrIy8vDa6+9huLiYowePRq1atVCmzZt8N1332nKWr16NYYNG4bMzEzk5eXh2muvxf79+6N8xwRBuAEJNwRBxD1vv/02cnJysGjRIvzjH//A2LFjcdlll6Fv375YtmwZzj77bFx77bU4duwYAKCwsBBnnHEGunfvjiVLlmDmzJkoKCjA3//+9xjfCUEQTkDCDUEQcU/Xrl1x3333oW3btpg4cSLS09ORk5ODMWPGoG3btnjggQdw4MABrFq1CgDwwgsvoHv37pg8eTLat2+P7t27Y9q0aZg7dy42bNgQ47shCMIu5HNDEETc06VLl/DvpKQk1KtXD507dw4fy8vLAwDs3bsXALBy5UrMnTuX6b/z119/4aSTTnK5xgRBuAkJNwRBxD0pKSmav30+n+ZYaBVWMBgEABw9ehTnn38+Hn/88Yi8GjZs6GJNCYKIBiTcEARR7TjllFPwySefoEWLFkhOpmGQIBIN8rkhCKLaMW7cOBw8eBBXXnklFi9ejL/++gvff/89Ro8ejUAgEOvqEQRhExJuCIKodjRq1Ai//PILAoEAzj77bHTu3Bm33XYbateuDb+fhkWCiHd8CoX6JAiCIAgigaBPFIIgCIIgEgoSbgiCIAiCSChIuCEIgiAIIqEg4YYgCIIgiISChBuCIAiCIBIKEm4IgiAIgkgoSLghCIIgCCKhIOGGIAiCIIiEgoQbgiAIgiASChJuCIIgCIJIKEi4IQiCIAgioSDhhiAIgiCIhOL/Abmg3docO9NwAAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -898,10 +898,10 @@
     {
      "data": {
       "text/plain": [
-       "DatetimeIndex(['2022-01-03 00:00:00', '2022-01-09 02:00:00',\n",
-       "               '2022-01-14 04:00:00', '2022-01-18 02:00:00',\n",
-       "               '2022-01-23 00:00:00', '2022-01-25 04:00:00',\n",
-       "               '2022-02-03 13:00:00', '2022-02-10 13:00:00'],\n",
+       "DatetimeIndex(['2022-01-03 18:00:00', '2022-01-06 10:00:00',\n",
+       "               '2022-01-09 05:00:00', '2022-01-11 03:00:00',\n",
+       "               '2022-01-28 16:00:00', '2022-02-08 07:00:00',\n",
+       "               '2022-02-09 20:00:00'],\n",
        "              dtype='datetime64[ns]', freq=None)"
       ]
      },
@@ -937,7 +937,7 @@
     "n_lines = len(input_data[ComponentType.line])\n",
     "\n",
     "# Initialize an empty line profile\n",
-    "line_profile = initialize_array(DataType.update, ComponentType.line, (n_lines, n_lines))\n",
+    "line_profile = initialize_array(DatasetType.update, ComponentType.line, (n_lines, n_lines))\n",
     "\n",
     "# Set the attributes for the batch calculation\n",
     "line_profile[\"id\"] =  input_data[ComponentType.line][\"id\"]\n",
@@ -958,7 +958,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Execution time for Validating Batch Data is 3.396744 s\n"
+      "Execution time for Validating Batch Data is 3.770749 s\n"
      ]
     }
    ],
@@ -979,7 +979,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Execution time for Batch Calculation using Newton-Raphson is 5.572404 s\n"
+      "Execution time for Batch Calculation using Newton-Raphson is 4.393309 s\n"
      ]
     }
    ],
@@ -999,7 +999,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Execution time for Batch Calculation using linear calculation is 1.636546 s\n"
+      "Execution time for Batch Calculation using linear calculation is 2.711576 s\n"
      ]
     }
    ],
@@ -1029,11 +1029,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Execution time for Sequential is 5.430197 s\n",
-      "Execution time for Single thread is 5.460312 s\n",
-      "Execution time for Two threads in parallel is 2.783122 s\n",
-      "Execution time for Four threads in parallel is 1.555401 s\n",
-      "Execution time for Use number of threads based the machine hardware is 0.648667 s\n"
+      "Execution time for Sequential is 4.250867 s\n",
+      "Execution time for Single thread is 4.385878 s\n",
+      "Execution time for Two threads in parallel is 2.271115 s\n",
+      "Execution time for Four threads in parallel is 1.146302 s\n",
+      "Execution time for Use number of threads based the machine hardware is 0.559351 s\n"
      ]
     }
    ],
diff --git a/power-flow-assignment/Power Flow Assignment.ipynb b/power-flow-assignment/Power Flow Assignment.ipynb
index 46d2f2b..9ce1f61 100644
--- a/power-flow-assignment/Power Flow Assignment.ipynb	
+++ b/power-flow-assignment/Power Flow Assignment.ipynb	
@@ -137,7 +137,7 @@
     "    for component in [ComponentType.node, ComponentType.line, ComponentType.source, ComponentType.sym_load]:\n",
     "        \n",
     "        # Use pandas to read CSV data\n",
-    "        df = pd.read_csv(f'../data/{component}.csv')\n",
+    "        df = pd.read_csv(f'../data/{component.value}.csv')\n",
     "\n",
     "        # TODO: Initialize array\n",
     "        input_data[component] = ...\n",
@@ -280,7 +280,7 @@
     "load_id = input_data[ComponentType.sym_load][\"id\"]\n",
     "load_p = input_data[ComponentType.sym_load][\"p_specified\"]\n",
     "profile = np.tile(load_p, (n_scenarios, 1)) + 5e5 * np.random.randn(n_scenarios, n_loads)\n",
-    "dti = pd.date_range(\"2022-01-01\", periods=n_scenarios, freq=\"H\")\n",
+    "dti = pd.date_range(\"2022-01-01\", periods=n_scenarios, freq=\"h\")\n",
     "df_load_profile = pd.DataFrame(profile, columns=load_id, index=dti)\n",
     "display(df_load_profile)"
    ]