The outbreak of the coronavirus disease 2019 (COVID-19) has seen the world scramble for effective countermeasures to limit infection spread in society. Understanding how infection spreads in places where strangers meet in relatively high numbers and proximity to one another is especially important. Supermarkets are one such place where strangers inevitably gather in close proximity indoors. In particular, the checkout area where people queue up to pay tends to be densely populated, making it especially hazardous. One approach to understanding the infection spread is to use agent-based computer simulations to model different scenarios. This paper describes one such simulation of a supermarket checkout area using the Unity 3D engine, including the effect of checkout types and quantity, customer load and COVID-19 countermeasures, i.e., masking and distancing, on infection spread. Using the results from one default scenario and eleven variations, the relative impact of aforementioned factors on exposure in the simulation is discussed. Results indicate that for this simulation the most important factor is preventing queue buildup via having sufficient customer throughput capacity, with potent effects also resulting from operating service registers in such a way that the distance between each queue is maximized as well as increasing distances between agents within queues. Including a self-checkout area was found to be a viable approach to reducing queue times and consequently exposure rates. Comparatively, masking did not yield as notable reductions in exposure rates in the simulation. Similarities in exposure patterns to previous work in the context of supermarkets are discussed, as well as limitations of simulations in capturing the real world. / Utbrottet av coronavirus disease 2019 (COVID-19) föranledde införandet av smittskyddsåtgärder världen över i ett försök att begränsa smittspridningen i samhället. Särskilt viktigt är att förstå hur smittspridning äger rum i trånga utrymmen där ett förhållandevis stort antal främmande människor samlas. Ett exempel på en inomhusmiljö där stora folksamlingar oundvikligen uppstår är mataffärer, där kassaområdena är högriskområden för smittspridning eftersom kunder köar för att betala i dessa områden. Ett tillvägagångssätt för att erhålla kunskap kring smittspridning är att använda agentbaserade datorsimuleringar för att modellera olika scenarion. Den här publikationen beskriver en sådan simulering av en mataffärs kassaområde i spelmotorn Unity 3D. Simuleringen används för att undersöka betydelsen av kassaområdets utformning för smittspridningen, samt inverkan av besökstryck och smittskyddsåtgärder, härvidlag användning av munskydd och social distansering. Som diskussionsunderlag för att fastställa vilken effekt dessa faktorer har på smittspridningen används ett grundscenario och elva simuleringsvarianter. Resultaten visar att den enskilt viktigaste faktorn i denna simulering är att hålla tillräckligt många kassor öppna, vilket förhindrar kötillväxt. Att hålla maximalt avstånd mellan öppna kassor, samt anamma social distansering mellan köande agenter bidrar också påtagligt till minskad smittspridning. Vidare förefaller inkludering av självskanningskassor vara ett effektivt tillvägagångssätt för att minska kötid och därmed även smittspridning. Användande av munskydd har jämförelsevis en mindre påtaglig effekt i simuleringen. I publikationen diskuteras även likheter i exponeringsmönster gentemot tidigare forskning rörande simulering av smittspridning i mataffärskontext, samt vilka begränsningar simuleringar kan uppvisa när det kommer till att replikera verkligheten.

<p dir="ltr">Wound healing is a complex biological process orchestrated by intricate cellular and biochemical interactions. This study leverages a multiscale modeling approach, integrating agent-based and ordinary differential equation (ODE) methods within CompuCell3D, to investigate wound detection and calcium signaling in juvenile zebrafish. Calcium as a ubiquitous secondary messenger plays a crucial role in translating wound stimuli into cellular responses. We focus on the initial phase of wound detection, a multi-step process beginning at the subcellular level with the release of Damage-Associated Molecular Patterns (DAMPs) and subsequent calcium signaling. We hypothesize that an ATP diffusion wave acts as the primary trigger, initiating a downstream calcium signaling cascade mediated by inositol triphosphate (IP3). Calcium and IP3 production and movement from the injured cells to healthy ones would then coordinate a tightly regulated wound response. To investigate this hypothesis, we adapted existing equations from a Drosophila wing disc injury model. We carefully modified them to accurately represent the zebrafish system in our in-silico setup, specifically focusing on relevant agonists. Model predictions were rigorously compared to the zebrafish’s experimental data to validate the computational approach. Our findings provide preliminary evidence suggesting that ATP diffusion through the interstitial spaces of injured tissue may be a potent agonist, triggering localized calcium release closely resembling experimental observations. This multiscale modeling framework offers a promising avenue for significant advancements in wound healing research. It has the potential to facilitate the development of novel therapeutic strategies and discoveries by enabling the integration of cell signaling pathways and tissue engineering.</p>

Les forêts sont une ressource naturelle importante sur le plan écologique, culturel et économique, et sont confrontées à des défis croissants en raison des changements climatiques. Ces défis sont difficiles à prédire en raison de la nature complexe des interactions entre le climat et la végétation, dont une le feu. Compte tenu de l’importance des écosystèmes forestiers, des dangers potentiels des feux de forêt et de la complexité de leurs interactions, il est primordial d'acquérir une compréhension de ces systèmes à travers le prisme de la science des systèmes complexes. La science des systèmes complexes et ses techniques de modélisation associées peuvent fournir des informations sur de tels systèmes que les techniques de modélisation traditionnelles ne peuvent pas. Là où les techniques statistiques et basées sur équations cherchent à contourner la dynamique non-linéaire, auto-organisée et émergente des systèmes complexes, les approches de modélisation telles que les automates cellulaires et les modèles à base d'agents (MBA) embrassent cette complexité en cherchant à reproduire les interactions clés de ces systèmes. Bien qu'il existe de nombreux modèles de comportement du feu qui tiennent compte de la complexité, les MBA offrent un terrain d'entente entre les modèles de simulation empiriques et physiques qui peut fournir de nouvelles informations sur le comportement et la simulation du feu. Cette étude vise à améliorer notre compréhension du feu dans le contexte de la science des systèmes complexes en développant un tel MBA de propagation du feu. Le modèle utilise des données de type de carburant, de terrain et de météo pour créer l'environnement des agents. Le modèle est évalué à l'aide d’une étude de cas d'un incendie naturel qui s'est produit en 2001 dans le sud-ouest de l'Alberta, au Canada. Les résultats de cette étude confirment la valeur de la prise en compte de la complexité lors de la simulation d'incendies de forêt et démontrent l'utilité de la modélisation à base d'agents pour une telle tâche. / Forests are an ecologically, culturally, and economically important natural resource that face growing challenges due to climate change. These challenges are difficult to predict due to the complex nature of the interactions between climate and vegetation. Furthermore, fire is intrinsically linked to both climate and vegetation and is, itself, complex. Given the importance of forest ecosystems, the potential dangers of forest fires, and the complexity of their interactions, it is paramount to gain an understanding of these systems through the lens of complex systems science. Complex systems science and its attendant modeling techniques can provide insights on such systems that traditional modelling techniques cannot. Where statistical and equation-based techniques seek to work around the non-linear, self-organized, and emergent dynamics of complex systems, modelling approaches such as Cellular Automata and Agent-Based Models (ABM) embrace this complexity by seeking to reproduce the key interactions of these systems. While there exist numerous models of fire behaviour that account for complexity, ABM offers a middle ground between empirical and physical simulation models that may provide new insights into fire behaviour and simulation. This study seeks to add to our understanding of fire within the context of complex systems science by developing such an ABM of fire spread. The model uses fuel-type, terrain, and weather data to create the agent environment. The model is evaluated with a case study of a natural fire that occurred in 2001 in southwestern Alberta, Canada. Results of this study support the value of considering complexity when simulating forest fires and demonstrate the utility of ABM for such a task.