Fix a few issues

main.tex

@@ -234,7 +234,7 @@
 7. McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA; %
 8. Division of Experimental Psychology and Neuropsychology, Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany; %
 9. Institute of Neuroscience and Medicine, Research Centre Jülich, Jülich, Germany; %
-10. Centre for Cognitive Neuroimaging, School of Psychology & Neuroscience University of Glasgow, UK; %
+10. Centre for Cognitive Neuroimaging, School of Psychology \& Neuroscience University of Glasgow, UK; %
 11. Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, CA; %
 12. CHU Sainte-Justine Research Center, University of Montreal, Montreal, QC, CA; %
 13. Department of Computer Engineering and Software Engineering, Polytechnique Montreal, Montreal, CA; %
@@ -275,7 +275,7 @@
 48. Medical Faculty, Heinrich Heine University Düsseldorf; %
 49. McGill, Montreal Neurological Institute - Hospital, Montreal, Quebec, Canada; %
 50. Institut Pasteur, Université Paris Cité, Unité de Neuroanatomie Appliquée et Théorique, F-75015 Paris, France; %
-51. Institute of Systems Neuroscience, Medical Faculty & University Hospital Düsseldorf, Heinrich-Heine- University, Düsseldorf, Germany; %
+51. Institute of Systems Neuroscience, Medical Faculty \& University Hospital Düsseldorf, Heinrich-Heine- University, Düsseldorf, Germany; %
 52. University of Toronto, Toronto, Ontario, Canada; %
 53. Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands; %
 54. Nuffield Department of Population Health, University of Oxford, Oxford, UK; %
@@ -345,7 +345,7 @@ \section*{Introduction}
 five main principles:
 
 \begin{enumerate}
-\tightlist
+% \tightlist
 \item
   Providing a hybrid event incorporating the positive aspects of
   in-person and virtual events alike,
@@ -371,8 +371,8 @@ \section*{Introduction}
 
 After a quick explanation of each main contribution of the core team, the next pages are dedicated to the summaries of the projects that were developed during the four days of hacking.
 
-\vfill\eject
-\columnbreak
+% \vfill\eject
+% \columnbreak
 
 \section{Hacktrack}
 

summaries/exploding_brains.tex

@@ -4,10 +4,9 @@
 
 \subsection{Exploding brains in Julia}\label{sec:explodingbrains}
 
-\authors{\"Omer Faruk G\"ulban, %
-Leonardo Muller-Rodriguez}
+\authors{\"Omer Faruk G\"ulban, Leonardo Muller-Rodriguez}
 
-Particle simulations are used to generate visual effects (in movies, games, etc.). In this project, we explore how we can use magnetic resonance imaging (MRI) data to generate interesting visual effects by using (2D) particle simulations. \added{Aside from providing an entertaining avenue to the interested participants, our project has further educational utility. For instance, anatomical MRI data analysis is done in two major frameworks: (1) manipulating fixed regularly spaced points in space (also known as Eulerian point of view), and (2) manipulating moving irregularly spaced points in space (Lagrangian point of view). For instance, bias field correction is commonly done from Eulerian point of view (e.g.\ computing a bias field is similar to computing a particle velocity field in each frame of the explosions), whereas cortical surface inflation is commonly done from Lagrangian point of view of the MRI data (e.g.\ computing the inflated brain surface is similar to computing the new positions of particles in each frame of the explosion). Therefore, our project provides an educational opportunity for those who would like to peek into the deep computational and data structure manipulation aspects of MRI image analysis. We note that we already made two hackathon projects in 2020 (see below) and were first inspired by a blog post (\url{https://nialltl.neocities.org/articles/mpm_guide.html}}) on the material point method\supercite{Jiang1965, Love2006, Stomakhin2013a}. Our additional aim in Brainhack 2022 is to convert our previous progress in Python programming language to Julia. The reason why we have moved to Julia language is because we wanted to explore this new programming language's potential for developing MRI image analysis methods as it has convenient parallelization methods that speeds-up the particle simulations (and any other advanced image manipulation algorithms).}
+Particle simulations are used to generate visual effects (in movies, games, etc.). In this project, we explore how we can use magnetic resonance imaging (MRI) data to generate interesting visual effects by using (2D) particle simulations. \added{Aside from providing an entertaining avenue to the interested participants, our project has further educational utility. For instance, anatomical MRI data analysis is done in two major frameworks: (1) manipulating fixed regularly spaced points in space (also known as Eulerian point of view), and (2) manipulating moving irregularly spaced points in space (Lagrangian point of view). For instance, bias field correction is commonly done from Eulerian point of view (e.g.\ computing a bias field is similar to computing a particle velocity field in each frame of the explosions), whereas cortical surface inflation is commonly done from Lagrangian point of view of the MRI data (e.g.\ computing the inflated brain surface is similar to computing the new positions of particles in each frame of the explosion). Therefore, our project provides an educational opportunity for those who would like to peek into the deep computational and data structure manipulation aspects of MRI image analysis. We note that we already made two hackathon projects in 2020 (see below) and were first inspired by a blog post (\url{https://nialltl.neocities.org/articles/mpm_guide.html}) on the material point method\supercite{Jiang1965, Love2006, Stomakhin2013a}. Our additional aim in Brainhack 2022 is to convert our previous progress in Python programming language to Julia. The reason why we have moved to Julia language is because we wanted to explore this new programming language's potential for developing MRI image analysis methods as it has convenient parallelization methods that speeds-up the particle simulations (and any other advanced image manipulation algorithms).}
 
 -----------------------------------
 

summaries/neurocausal.tex

@@ -30,7 +30,7 @@ \subsection{NeuroCausal: Development of an Open Source Platform for the Storage,
 \begin{figure}
 	\centering
 	\includegraphics[width=0.5\textwidth]{NeuroCausal_BHproceeding.png}
-	\caption{NeuroCausal: The future of neuropsychology, i.e. brain lesions-symptom mapping, will be transdiagnostic, open, and FAIR: we set out to provide the field with an open-source platform fostering storage, sharing, synthesis, and meta-analysis of clinical data.
+	\caption{NeuroCausal: The future of neuropsychology, i.e.\ brain lesions-symptom mapping, will be transdiagnostic, open, and FAIR: we set out to provide the field with an open-source platform fostering storage, sharing, synthesis, and meta-analysis of clinical data.
 }
 	% Add a label to reference in text. Make it specific!
 	\label{fig:NeuroCausal}