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add description for target systems
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paper/main.tex

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@@ -356,13 +356,20 @@ \subsubsection*{Bayesian Optimization}
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%###################################################################################################
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\section{Target System}
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\section{Target Systems}
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\label{section:target-system}
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\begin{itemize}
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\item Make clear that black-box optimization is required
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\item Should have some application for real-world scenarios
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\end{itemize}
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In order to compare various optimization methods, we study two distinct target systems.
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The first one aims to estimate parameters of the \ac{abm} by comparing individual agents with
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experimental data.
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Meanwhile, the second system represents the use-case of an objective function which is applied to a
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large collection of agents.
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We use cellular\_raza~\cite{Pleyer2025} to implement the numerical realization of these systems.
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%---------------------------------------------------------------------------------------------------
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\subsection{Bacterial Rods}
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\label{subsection:bacterial-rods}
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\item neighbor interaction $\rightarrow$ not diff.-able
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\end{itemize}
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This model describes the growth and interactions of rod-shaped bacteria such as \textit{E.Coli} or
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\textit{B.Subtilis}.
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It has been published with cellular\_raza~\cite{Pleyer2025} and consists of 4 simulation aspects.
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\paragraph{Mechanics}
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individual bacteria are represented by a collection of vertices $\vec{v}_i$ which are coupled to
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each other via springs.
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In addition, a bending force acts between the angles of connecting edges, thus promoting a straight
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shape without curvature.
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\paragraph{Interaction}
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Bacteria exert forces which repell or attract each other.
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These forces act between a single vertex $\vec{v}_i$ on one agent and the closest point on each
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connection between two vertices $\vec{w}_j$ and $\vec{w}_{j+1}$ of the interacting agent.
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\paragraph{Cell Cycle}
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Each cell-agent is continuously growing, thus extending the length of the rod via the insertion of
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new material at the cylindtrical part.
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Once they reach a certain length threshold, the bacteria divide in the middle.
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During this process, new vertices are determined such that the resulting two new bacteria align
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identically within the path of the vertices of the mother-cell.
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\paragraph{Domain}
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We can choose the simulation dimension (2D,3D).
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For the estimation of individual parameters, we restrict ourselves to 2D to realistically depict the
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bacterial growth on a plate.
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The domain has reflective boundary conditions which are however not applied since our bacteria are
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located far enough in the center of the simulation domain.
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Figure~\ref{fig:bacterial-rods-sim} shows various results of numerical simulations of this model.
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Subfigure (A-B) show the growth of these bacteria inside a cuboid, thus slowly filling up the space
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from the left to right and favoring an alignment of the rods along this dimension of growth.
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Meanwhile, subfigures (C-E) show snapshots of a shallow 3D simulation where the postiion of agents
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has been converted to individual cell-masks such as produced by cell-segmentation algorithms.
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The last subfigures (F-G) show microscopic images from which we extracted the position of the
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bacterial agents and then made a prediction for the position of the rod-agents, which could
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now be compared with the experimental data (i.e. the next microscopic image) in order to estimate
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the parameters of the system.
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\begin{figure}[H]
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\centering
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\includegraphics[width=0.48\textwidth]{figures/cr_mech_coli/bacterial-rods-0000000025.png}%

paper/references.bib

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@@ -301,3 +301,16 @@ @article{Piou2009
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month = sep,
302302
pages = {1957–1967},
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}
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@article{Pleyer2025,
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doi = {10.21105/joss.07723},
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url = {https://doi.org/10.21105/joss.07723},
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year = {2025},
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publisher = {The Open Journal},
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volume = {10},
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number = {110},
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pages = {7723},
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author = {Jonas Pleyer and Christian Fleck},
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title = {cellular\_raza: Cellular Agent-based Modeling from a Clean Slate},
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journal = {Journal of Open Source Software},
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}

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