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Real‐time individuals' destination prediction is of great significance for real‐time user tracking, service recommendation and other related applications. Traditional technology mainly used statistical methods based on the travel patterns mined from personal history travel data. However, it is not clear how to predict the destinations of individuals with only limited personal historical data. In this paper, taking the public transportation metro systems as example, we design a practical method called practical model with strong interpretability and predictability to predict each passenger's destination. Our main novelties are two aspects: (1) We propose to predict individuals' destination by combining personal and crowd behavior under certain context. (2) An explanatory model combining discrete choice model and neural network model is proposed to predict individuals' stochastic trip's destination, which can be applied to other transportation analysis scenarios about individuals' choice behavior such as travel mode choice or route choice. We validate our method based on extensive experiments, using smart card data collected by automatic fare collection system and weather data in Shenzhen, China. The experimental results demonstrate that our approach can achieve better performance than other baselines in terms of prediction accuracy. [ABSTRACT FROM AUTHOR]

In social insects, collective behavior is regulated by substances secreted by various glands of different members of society. In this study, we investigate whether salivary glands of the arboreal termite Nasutitermes corniger (Motschulsky) (Isoptera: Termitidae) contain substances that regulate the intensity of foraging behavior. Foraging arenas of N. corniger nests maintained under laboratory conditions received the addition of two filter paper substrates, one impregnated with salivary gland extract from third‐instar small workers (SW3) (treatment) and the other impregnated with distilled water (control). A similar experiment was conducted using salivary gland extract from fourth‐instar large workers (LW4). Occurrences of initial exploration, mass recruitment, and substrate gnawing behaviors, as well as numbers of recruited and gnawing workers, were recorded. There was a higher rate of mass recruitment to treated substrates than to the control (SW3: 80 vs. 25%; LW4: 90 vs. 25%). Gnawing behavior also occurred at higher rates on treated substrates (SW3: 95 vs. 35%; LW4: 100 vs. 45%). The number of workers recruited to and gnawing on treated substrate was significantly higher than the number of workers recruited to and gnawing on control substrate. The higher rates of worker recruitment, as well as the higher numbers of recruited and gnawing workers, show that salivary glands of last‐instar workers contain substances with arresting and/or phagostimulating pheromonal actions or substances that release compounds with these properties. [ABSTRACT FROM AUTHOR]

The construction of living systems from the bottom‐up helps to explore the complex processes of life and to understand their working mechanism. Prototissues, constructed using artificial cells as building blocks, mimic life systems at a high‐order tissue level, whilst artificial cells usually mimic living cells at the individual cell level. The 3D biomimetic prototissues demonstrate exceptional performances and collective functions, which reveal the working mechanisms of living tissues and hold promising potential for biomedical applications. This review systematically summarized the research progress of the field of prototissues. The engineering methods for fabricating two types of prototissues are introduced first, followed by the functions of prototissues including collective behaviors and signal communications, as well as their biomedical applications. The challenges and future trends are proposed at the end of the paper. [ABSTRACT FROM AUTHOR]

Maintenance goals have a fundamental albeit understudied role in human motivation. From health to relationships, to personal possessions and the environment, the things people value require regular care. When maintaining a friendship, for instance, one may need to catch‐up regularly, share life updates and offer support, and occasionally make time to meet and spend time together. Distinct from the more commonly studied approach and avoidance goals, maintenance goals focus on sustaining current states over time, a process that has recently begun to attract increasing scholarly attention. This paper explores the construct of maintenance goals; It provides a comprehensive review of key findings and offers a novel perspective on the potential role of maintenance in individual and collective behavior, centering on topics such as well‐being, leadership, and group perceptions across different cultural contexts. By integrating theory with empirical evidence, this review underscores the necessity of incorporating maintenance goals into a broader psychological framework and recognizes their potential to inform interventions aimed at fostering resilience and stability in an ever‐changing world. [ABSTRACT FROM AUTHOR]

The real‐time simulation of human crowds has many applications. In a typical crowd simulation, each person ('agent') in the crowd moves towards a goal while adhering to local constraints. Many algorithms exist for specific local 'steering' tasks such as collision avoidance or group behavior. However, these do not easily extend to completely new types of behavior, such as circling around another agent or hiding behind an obstacle. They also tend to focus purely on an agent's velocity without explicitly controlling its orientation. This paper presents a novel sketch‐based method for modelling and simulating many steering behaviors for agents in a crowd. Central to this is the concept of an interaction field (IF): a vector field that describes the velocities or orientations that agents should use around a given 'source' agent or obstacle. An IF can also change dynamically according to parameters, such as the walking speed of the source agent. IFs can be easily combined with other aspects of crowd simulation, such as collision avoidance. Using an implementation of IFs in a real‐time crowd simulation framework, we demonstrate the capabilities of IFs in various scenarios. This includes game‐like scenarios where the crowd responds to a user‐controlled avatar. We also present an interactive tool that computes an IF based on input sketches. This IF editor lets users intuitively and quickly design new types of behavior, without the need for programming extra behavioral rules. We thoroughly evaluate the efficacy of the IF editor through a user study, which demonstrates that our method enables non‐expert users to easily enrich any agent‐based crowd simulation with new agent interactions. [ABSTRACT FROM AUTHOR]

In emergency situation, mass panic often causes more causalities than the disaster itself. The crowd emotional model could be used to simulate how crowd behavior in emergency scenarios and be helpful for developing crowd evacuation plans in emergency situations. However, existing crowd emotional models usually set model parameters in an empirical manner and are not validated by real cases. In this paper, a crowd emotional model is proposed to simulate the crowd movement in outdoor emergency situations. First of all, the crowd entropy and the movement difference are proposed to describe the emotional impact of the crowd scene on the agents. The perception of vision and hearing are considered, and the calculation formulas of the agent's emotional intensity and crowd emotional contagion are proposed. By calculating individual trajectories in the real video, the cumulative differences between the movements of the real crowd and the corresponding virtual crowd are analyzed. At last, a multi‐parameter optimization method is implemented by the differential evolution algorithm. To verify the parameters in models, three videos which are generated from three real cases, including explosion attack, shooting incident, and crowd disturbance are selected for experimental verification. The results showed that the proposed model could be a feasible method for optimizing parameters to simulate the emergency scenario. [ABSTRACT FROM AUTHOR]

Summary: This paper studies sign consensus, a collective behavior of multiagent systems, when both cooperative and antagonistic interactions coexist among agents. By sign consensus, it means that the states of all agents will eventually achieve the same sign but may with different magnitudes. Compared with some recent works on sign‐consensus problems, where only fixed graphs are considered and the graph adjacency matrix needs to be eventually positive, this paper allows the graph to be switching over time. Control laws are proposed and analyzed with respect to three classes of switching graphs. Examples illustrate the efficacy of the control algorithms. [ABSTRACT FROM AUTHOR]

Collective behavior sometimes requires forming a particular formation or reaching a certain velocity to accomplish a specific task, such as bird migration. In this paper, we investigate the collective migration model, which consists of two parts: Cucker–Smale type interaction and target velocity. Each agent has a strategy to allocate limited energy to group interaction and velocity tracking. In this case, if the system achieves monocluster flocking then the final velocity is equal to target velocity. When the strategy is invariant, we show that 1/2 is a critical threshold which is consistent with the classical Cucker–Smale model. When the strategy is time varying, we provide a time‐varying strategy named threshold strategy to ensure that for any initial state the system achieves monocluster flocking and the final velocity reaches target velocity. In addition, the case of multiple target velocities is considered. According to the theory of bicluster flocking, we obtain a sufficient framework to guarantee that the system achieves bicluster flocking and two groups would reach their target velocities, respectively. [ABSTRACT FROM AUTHOR]

This paper discusses crowd control at stadiums in emergency evacuation situations such as fire, bomb threat, and terror incidents. As a comparative reference for this study, the author observed egress/way‐home crowd behavior at eight stadiums by walking with the crowd as a tracer. At some stadiums, the crowd was controlled by closing certain exits, installing temporary fences, and providing staff guidance to relieve congestion and counterflow outside the stadiums. At other stadiums, there was no accumulation, and spectators egressed freely. In case of a fire, flames and smoke can be controlled by fire extinguishment, smoke control, etc.; therefore, the need for urgent evacuation can be relieved to some extent. However, urgent evacuation is needed in emergencies such as a fire in a closed‐roof stadium or indoor premises, or a bomb threat. In such situations, sufficient space for accumulation outside the stadium is required. Therefore, stadiums that let spectators returning home walk freely after normal events are desirable because urgent evacuation can be completed in the same manner. The above aspects should be considered in the whole process of selecting stadium sites, planning circulation in stadiums, and deploying guiding staff. [ABSTRACT FROM AUTHOR]

The general particle dynamics (GPD), which is based on the kernel approximation method and Navier–Stokes equation, was developed from smoothed‐particle hydrodynamics to simulate the fracture behaviors by using the collective of damage variable to describe the damage evolution behaviors. In this paper, an advanced GPD with a nonlocal foundation is proposed for better description of the solid mechanics. The nonlocal vector calculus and microscopic constitutive model are employed to derive the governing equations in the proposed theory. The novel GPD with a nonlocal core is a generalization, which permits the inclusion of the microscopic constitutive model and the multi‐scale modeling compared with the previous GPD. To accomplish this generalization, the relationship between GPD and the previous kernel‐based theory is established. The novel GPD is superior in the fracture problems and multi‐scale modeling. Some numerical experiments are launched to verify the ability of the novel GPD. Highlights: Advanced GPD with nonlocal foundation for is proposed for better description of the solid mechanics.The governing equations are re‐derived by nonlocal vector calculus and micro‐bond model.The advanced GPD is good at handling with multi‐scale problem and fracture problems. [ABSTRACT FROM AUTHOR]

It is a significant issue to explore the collective behaviors of the delayed complex systems. This paper studies asymptotic collective behaviors of a delayed multi‐particle system with multiple processes while particles interact directionally and locally. Up to now, the studies on dynamic behaviors of multi‐particle systems do not involve limited processing capacity, that is, the information queuing phenomenon is ignored. To this aim, we introduce multiple processes to formulate the evolution of a delayed multi‐particle system. To optimize the delay parameters, we choose the greedy principle to set the processing order. The main idea is to decompose the velocity into each process and use functional differential equation theory and matrix theory to constrain the velocity variation rate while the processing order is fixed. As the new results, in the non‐critical and general situation, when the time delay is less than or equal to the threshold value and the eigenvalue 1 of the average matrix is semi‐simple, we achieve the criterion of flocking and multi‐cluster with exponential convergence rate involving multiple processes. Furthermore, we get the lower bound estimate of the processing capacity. [ABSTRACT FROM AUTHOR]

This paper studies large‐population dynamic games involving a linear‐quadratic‐Gaussian (LQG) system with an exponential cost functional. The parameter in the cost functional can describe an investor's risk attitude. In the game, there are a major agent and a population of N$$ N $$ minor agents where N$$ N $$ is very large. The agents in the games are coupled via both their individual stochastic dynamics and their individual cost functions. The mean field methodology yields a set of decentralized controls, which are shown to be an ϵ$$ \epsilon $$‐Nash equilibrium for a finite N$$ N $$ population system where ϵ=O1N$$ \epsilon =O\left(\frac{1}{\sqrt{N}}\right) $$. Numerical results are established to illustrate the impact of the population's collective behaviors and the consistency of the mean field estimation. [ABSTRACT FROM AUTHOR]

SUMMARY Many models have been developed in recent years to describe pedestrian group behavior. Most prior research on group behavior focuses mainly on small groups and does not provide a general approach for grouping pedestrians with respect to different group sizes. They also analyze pedestrian group dynamics in normal circumstances. However, people's reactions who are aware of an emergency are not the same as how they respond to normal or usual situations. The central focus of this paper is to study pedestrian group behavior during evacuation. To accomplish these objectives, a new model is proposed with some extensions of a social force model in its emergency context. The new extensions are intended to simulate the single leader‐centered and group‐centered crowd behavior in emergencies. Besides small pedestrian groups, larger ones are also considered, and extensions are added in this direction. The model is calibrated using the results of an existing experimental study. Then, the model is verified by testing for the occurrence of certain emergent patterns. The results indicate that the proposed model can capture these trends. Additionally, the model is validated by comparing the simulation results with experimental results available in the literature. Also, several different evacuation scenarios are used to evaluate the proposed model. The simulation results show that leader‐centered behavior performs better than group‐centered behavior with respect to the evacuation time for small groups. The number of leaders also affects the evacuation time. Moreover, an increase in the number of leaders positively influences the effect of the width of the door on evacuation time, but the size of this effect depends on the number of leaders. Finally, group‐centered behavior results in less evacuation time than leader‐centered behavior in the presence of multiple exits, and leader‐centered (also called single leader‐centered in this study) behavior causes a more unbalanced use of the exits than group‐centered behavior. [ABSTRACT FROM AUTHOR]

The notion that mass mobilization has analytically important stages is underappreciated in the literature. This paper proposes an approach that decomposes mass mobilization into three main phenomena: origins, protest and outcome. Each stage is characterized by unique factors and mechanisms. Accordingly, the research questions pertaining to each stage are dealt with by multiple levels of analysis and alternative explanations, allowing theory testing and theory development. The paper highlights separate causal mechanisms that operate in the emergence of grievances and protest motivation during the origins stage; mechanisms involving different forms of pressure, organization, psychological processes, and external forces during the protest stage; and mechanisms pertaining to key players and strategies that determine outcomes of mass mobilization. We illustrate that certain factors and mechanisms which are key in one stage have little or no causal relevance in the other stages. Other factors and mechanisms may also dramatically change in content, meaning or configuration between the stages. This theoretical approach facilitates the integration of a large and diverse body of scholarship into a structured analysis of mass mobilization that allows for both a detailed case study as well as comparison of stages across mass protests. The analysis of stages and causal mechanisms is illustrated across cases of democratization, revolution, and protest within democracy. [ABSTRACT FROM AUTHOR]

Panic buying emerged as a significant phenomenon during the COVID‐19 pandemic. This study draws on the scarcity principle, crowd psychology and contagion theory to investigate the antecedents and consequences of panic buying. The antecedents included in this study are government measures, media and peer influence and the fear of missing out. The consequences are founded on a sense of security and guilt. Retailer intervention is included as a moderator to the proposed main effects. Data were collected from 341 consumers who engaged in panic buying and were residents of the United States and Australia during the COVID‐19 pandemic. Structural equation modelling was employed to test the proposed model. The results show that the proposed antecedents (except fear of missing out) were significantly related to panic buying, which in turn had a significant influence on panic buyers' psychological outcomes. The moderating effects of retailer intervention varied across different product categories. Discussion and implications of these findings are provided for policy makers, customers and practitioners. [ABSTRACT FROM AUTHOR]

In the first of three papers the current philosophical, sociological and ecological approaches to 'community' were considered from a psychoanalytic perspective. This second paper aims to arrive at a set of principles that will underpin a psychoanalytic concept of communities. Those principles include: psychoanalytic understandings of groups; the unconscious of the collective; the subjectivity and inter-subjectivity of individuals and collectives; the symbolic function of an abstract concept; and the processes involved in making sense, such as mentalization and symbolization. The emerging psychoanalytic framework conceptualizes communities in terms of their collective psychological tasks, such as the maintenance of shared identification and boundaries, their responses to trauma and the work of mourning, rather than by their geographical or sociological characteristics. This new approach to the concept of community also highlights the utility of distinguishing the nature of groups by their respective, collective psychological tasks. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

B EuroVis 2020 b B Eurographics / IEEE VGTC Conference on Visualization 2020 b Norrköping, Sweden May 25 - 29, 2020 GLO:BNX/01jun20:cgf14006-gra-0001.jpg PHOTO (COLOR): . gl EUROGRAPHICS The European Associationfor Computer Graphics IEEE Visualization and Graphics Technical Committee B Conference Chairs b Anders Ynnerman, Linköping University, Sweden Matthew Cooper, Linköping University, Sweden Ingrid Hotz, Linköping University, Sweden Patric Ljung, Linköping University, Sweden B Full Papers Chairs b Ivan Viola, King Abdullah University of Science and Technology, Saudi Arabia Michael Gleicher, University of Wisconsin, Madison, USA Tatiana Landesberger von Antburg, Karlsruhe Institute of Technology and Technische Universität Darmstadt, Germany B STARs Chairs b Noeska Smit, University of Bergen, Norway Steffen Oeltze-Jafra, University of Magdeburg, Germany Bei Wang, University of Utah, USA B Short Papers Chairs b Andreas Kerren, Linnaeus University, Sweden Christoph Garth, University of Kaiserslautern, Germany G. Elisabeta Marai, University of Illinois at Chicago, USA B Posters Chairs b Jan Byska, Masaryk University Brno, Czech Republic Stefan Jänicke, University of Southern Denmark, Denmark B Industrial Chairs b Anders Carlsson, Visual Sweden, Sweden Matthew Cooper, Linköping University, Sweden Preface EuroVis 2020, the Eurographics / IEEE VGTC Conference on Visualization was scheduled to be held in Norrköping, Sweden from May 25-29th, 2020. Topics include visualization techniques for spatial data, such as volumetric, tensor, and vector field datasets, and for non-spatial data, such as graphs, text, and high-dimensional datasets. EuroVis also covers the theory of visualization, hardware acceleration, large datasets, perception, interaction, user studies, information visualization, visual analytics, and many application areas of visualization. [Extracted from the article]

This paper focuses on simulating agents transporting passive objects in a virtual environment with pedestrians. The agents adopt the pushing manipulation patterns to transport the passive objects. We propose techniques to achieve two kinds of cooperation. First, the agents transport the passive objects to the goal positions. During the transportation process, the agents may adjust their formation to transport the passive objects effectively. Second, the agents avoid collision with each other and passive objects in an unfreezing manner. Experiment results show that our technique avoids the freezing problem while the agents are transporting multiple objects. [ABSTRACT FROM AUTHOR]

Computer modeling promotes mechanistic reasoning when learners build and analyze models of complex systems to explore causal mechanisms and use models to generate patterns. StarLogo Nova (SLN), an agent‐based modeling (ABM) environment, enables novice programmers to model a system's individual components and investigate its emergent, collective behavior. Through case analysis of teachers using SLN, we demonstrate how ABM advances thinking about mechanisms generating phenomenon. Teachers who used simulation combined with the decoding of SLN models utilized mechanistic reasoning to make sense of how and why complex phenomenon emerged. Practitioner Notes: What is already known about this topic Mechanisms, or causal explanatory processes, are critical in science. Mechanistic reasoning is concerned with why a phenomenon occurs.Traditionally in science classrooms, teachers incorporate pre‐packaged simulations that limit the ability to understand mechanisms within the simulations.Agent‐based modeling empowers learners to model at the micro‐level to understand how macro‐level phenomenon emerge in complex systems. What this paper adds StarLogo Nova, an agent‐based modeling environment, has features that support mechanistic reasoning.Using simulation combined with decoding of models in StarLogo Nova promotes mechanistic explanations of why phenomenon occurs.Teachers are able to scaffold student interactions in StarLogo Nova to support students' mechanistic reasoning. Implications for practice and/or policy When using computer simulations in instruction, incorporate decoding of models to engage students in uncovering why a phenomenon occurs.In professional development programs on scientific modeling, it is important for educators to learn how decoding contributes to students' understanding of mechanisms in models and experience modeling as a scientific practice. [ABSTRACT FROM AUTHOR]

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This paper analyses how workers in Germany's automotive industry developed power in the process of a transnational carve out - namely the carve-out of the rubber and plastics department of the German automotive supplier ZF Friedrichshafen AG to the Chinese based Zhuzhou Times New Material Technology Co., Ltd. in 2013. The worker's actions were successful because they used their production network knowledge and decided against a strategy of pure co-operative co-determination but implemented a strategy of resistance. They concentrated their resistance on the weak points within the value creation processes of the automotive production network. On the basis of this, the authors argue that production network knowledge can be used to develop collective power within organisations. The study is based on qualitative interviews with ZF observing participation of workers events and a press analyses on the particular acquisition. [ABSTRACT FROM AUTHOR]

This paper introduces a new crowd formation transform approach to achieve visually pleasing group formation transition and control. Its core idea is to transform crowd formation shapes with a least effort pair assignment using the Kuhn-Munkres algorithm, discover clusters of agent subgroups using affinity propagation and Delaunay triangulation algorithms and apply subgroup-based social force model (SFM) to the agent subgroups to achieve alignment, cohesion and collision avoidance. Meanwhile, mutual information of the dynamic crowd is used to guide agents' movement at runtime. This approach combines both macroscopic (involving least effort position assignment and clustering) and microscopic (involving SFM) controls of the crowd transformation to maximally maintain subgroups' local stability and dynamic collective behaviour, while minimizing the overall effort (i.e. travelling distance) of the agents during the transformation. Through simulation experiments and comparisons, we demonstrate that this approach is efficient and effective to generate visually pleasing and smooth transformations and outperform several existing crowd simulation approaches including reciprocal velocity avoidances, optimal reciprocal collision avoidance and OpenSteer. [ABSTRACT FROM AUTHOR]

Zöller et al. (Ethology, 2020) criticize our original publication (Wikelski et al., Ethology, 126(9), 2020, 931) for obvious reasons: we only observed the behavior of one group of farm animals before, during and after one earthquake series in one area of the world. It is clear that no earthquake predictions are possible, and should not be attempted, from this data set. However, what we show is that there is important information within this animal collective pertaining to potential future local forecasting of earthquakes when combined with traditional data sources. We maintain that combining Zöller et al.'s (2020) modeling tools with the adequate use of our data can stimulate novel ways of earthquake forecasting. Future studies should combine both approaches. [ABSTRACT FROM AUTHOR]

When multiple individuals interact in a conversation or as part of a large crowd, emergent structures and dynamics arise that are behavioral properties of the interacting group rather than of any individual member of that group. Recent work using traditional signal processing techniques and machine learning has demonstrated that global acoustic data recorded from a crowd at a basketball game can be used to classify emergent crowd behavior in terms of the crowd's purported emotional state. We propose that the description of crowd behavior from such global acoustic data could benefit from nonlinear analysis methods derived from dynamical systems theory. Such methods have been used in recent research applying nonlinear methods to audio data extracted from music and group musical interactions. In this work, we used nonlinear analyses to extract features that are relevant to the behavioral interactions that underlie acoustic signals produced by a crowd attending a sporting event. We propose that recurrence dynamics measured from these audio signals via recurrence quantification analysis (RQA) reflect information about the behavioral dynamics of the crowd itself. We analyze these dynamics from acoustic signals recorded from crowds attending basketball games, and that were manually labeled according to the crowds' emotional state across six categories: angry noise, applause, cheer, distraction noise, positive chant, and negative chant. We show that RQA measures are useful to differentiate the emergent acoustic behavioral dynamics between these categories, and can provide insight into the recurrence patterns that underlie crowd interactions. [ABSTRACT FROM AUTHOR]

We study stochastic flocking dynamics of the inertial spin (IS) model with state‐dependent noises. The IS model was considered to describe the collective behaviors of starling flocks moving with constant speed. Unlike mechanical flocking models extensively studied in the literature, this model incorporates an internal dynamic observable, namely spin (internal angular momentum) in addition to mechanical observables (position and velocity), and it describes how spin interacts with mechanical observables. In previous works, emergent dynamics of the deterministic counterparts for the IS model and its mean‐field limit have been investigated under some specific setting in which network topology is multiplicatively separable. In this work, we present sufficient frameworks for stochastic flocking dynamics of the IS model, which state‐dependent noises vanish at the equilibria of the deterministic IS model. The proposed frameworks are in terms of coupling strength, friction, and inertial coefficients, and our asymptotic convergence results for sample paths are given in both an almost sure and an expectation sense. We have also conducted several numerical experiments to verify our analytical results and to explore what can be studied further in future work [ABSTRACT FROM AUTHOR]

The multi‐scale roughness of a fault interface is responsible for multiple asperities that establish a complex and discrete set of real contacts. Since asperities control the initiation and evolution of the fault slip, it is important to explore the intrinsic relationships between the collective behavior of local asperities and the frictional stability of the global fault. Here we propose a novel analog experimental approach, which allows us to capture the temporal evolution of the slip of each asperity on a faulting interface. We find that many destabilizing events at the local asperity scale occurred in the slip‐strengthening stage which is conventionally considered as the stable regime of a fault. We compute the interseismic coupling to evaluate the slipping behaviors of asperities during the slip‐strengthening stage. We evidence that the interseismic coupling can be affected by the elastic interactions between asperities through the embedding soft matrix. Scaling laws of natural slow slip events are reproduced by our setup in particular the moment‐duration scaling. We also evidence an unexpected persistency of a disordering of the asperities through the seismic cycles despite the relaxation effects of the large slip events. Plain Language Summary: Earthquakes are the results of a slip along a rough fault on which a complex and discrete set of asperities establish the interfacial contacts and control the frictional stability of the fault. We propose a novel experimental setup capable of measuring directly the subtle motion of individual asperities on an analog faulting interface. By capturing the temporal evolution of the slip of each asperity, we link the mechanical behavior of the global fault with the collective behavior of local asperities. Many destabilizing events at the local asperity scale are found during the globally stable stage of the fault. We prove that the interseismic coupling of asperities is affected by the normal load, the peak height of asperities, and the interactions between asperities. The spatiotemporal interactions of asperities are quantified as slip episodes to mimic the ruptures including both stable and unstable slips. With the catalog of slip episodes, we reproduce the significant characteristics and scaling laws observed in natural faults, such as the magnitude‐frequency distribution and the moment‐duration scaling. Such upscaling suggests that our results can be extrapolated to natural faults and provide insights into fault physics and mechanics. Key Points: We propose a novel direct‐shear setup to observe the collective behavior of asperities along an analog fault interface during stick‐slipsScaling laws, that mimic those of slow slip events, are observed in our experiments and originate during the slip‐strengthening phaseLarge scale quenched topography of the asperities along the interface has a direct impact on the interseismic coupling [ABSTRACT FROM AUTHOR]

With the increasing number of emergencies, the crowd simulation technology has attracted wide attention in the recent years. Existing emergencies have shown that individuals are easy to be influenced by others' emotion during the evacuation. This will make it easier for people to aggregate together and increase security risks. Some of the existing evacuationmodelswithout considering emotion are therefore not suitable for describing crowd behaviors in emergencies. We propose a perception-based emotion contagion model and use multiagent technology to simulate crowd behaviors. Navigation points are introduced to guide the movement of the agents. Based on the proposed model, a prototype simulation system for crowd emotion contagion is developed. The comparative simulation experiments verify that the model can effectively deduct the evacuation time and crowd emotion contagion. The proposed model could be an assistant analysis method for crowd management in emergencies. [ABSTRACT FROM AUTHOR]

Despite an emerging catalogue of collective behaviours in communities of homogeneously distributed cell‐like objects, microscale protocell colonies with spatially segregated populations have received minimal attention. Here, we use microfluidics to fabricate Janus‐like calcium alginate hydrogel microspheres with spatially partitioned populations of enzyme‐containing inorganic colloidosomes and investigate their potential as integrated platforms for domain‐mediated chemical communication and programmable protocell‐matrix dynamics. Diffusive chemical signalling within the segregated communities gives rise to increased initial enzyme kinetics compared with a homogeneous distribution of protocells. We employ competing enzyme‐mediated hydrogel crosslinking and decrosslinking reactions in different domains of the partitioned colonies to undertake selective expulsion of a specific protocell population from the community. Our results offer new possibilities for the design and construction of spatially organized cytomimetic consortia capable of endogenous chemical processing and protocell‐environment interactivity. [ABSTRACT FROM AUTHOR]

Many types of bacteria engage in complex collective behaviors, often controlled by a form of cell‐cell communication mediated by diffusible signal molecules called quorum sensing (QS). Each individual produces and responds to these diffusible signaling molecules, inferring properties of their environment, and modulating the regulation of hundreds of downstream genes in response. A threshold concept is ingrained in the QS literature following the use of the legal 'quorum' analogy, where populations of bacteria are synchronously sub‐quorate below a threshold population size or synchronously quorate above a threshold population size. However, a growing body of literature highlights that QS can produce more nuanced, graded responses to environmental variation, implying there is no simple threshold 'quorum' on either the single cell or population scale. In this commentary, we discuss reaction norms as a tool to quantify and compare QS‐controlled behaviors in an environmental context. [ABSTRACT FROM AUTHOR]

Due to the complex and subtle behaviors of humans, realistic crowd simulation is difficult. To that end, we propose a novel crowd simulation method that can generate realistic crowd animations with behaviors similar to real crowds and model complex pedestrian behaviors at multiple levels using social long short‐term memory (LSTM) neural networks. At the high level, our multi‐level simulation model provides global group navigation while at the low level, it can simulate local individual interactions with collision avoidance. We introduce a data‐driven method using an improved social LSTM for learning local motion decisions from real pedestrian trajectories in order to capture the subtle movements of the crowd. To achieve scalability, we formulate the low‐level and high‐level motion control in a force‐based scheme. Extensive simulation results demonstrate that our method can produce realistic crowd animations in a variety of scenarios. Evaluations in various metrics show that our method produces better crowd behaviors than previous methods. [ABSTRACT FROM AUTHOR]

I argue, in short, that expressive groups, interpellated groups, and group psychopaths possess the emergent capacities necessary for attributability, accountability, and answerability respectively, and that this is why we meet them with the reactive attitudes that we do. Section II outlines the problem of aberrant groups by distinguishing between three different types of groups - expressive groups, interpellated groups, and group psychopaths - that arguably warrant specific group-reactive attitudes. Sometimes reactive attitudes target groups rather than individuals.[1] This suggests that groups are sometimes morally responsible. If the emotion of the group is the sum of how the individual group members happen to feel and their feelings are not altered by their group membership, there is I no i emergent group emotion but merely an aggregate emotion. [Extracted from the article]

Hydrodynamic effects are known to significantly affect the collective behavior of wet active matter systems. However, the non‐linear many‐body nature of these interactions makes them very challenging to analyze, particularly in dense suspensions. Quincke rollers are one of the canonical examples of artificial microswimmers. These are active particles that move freely above a plate due to the torque generated by a uniform DC electric field. A system involving many such particles exhibits a variety of collective dynamics, such as the disordered gas, polar liquid, and active crystal states. This work accomplishes numerical simulations of a 3D system containing many rollers in order to explicitly resolve the hydrodynamic interactions and understand the role these play in the resulting active dynamics. It reveals that the far‐field hydrodynamic effects tend to drive ordered collective motion, while the near‐field effects tend to drive disordered collective behavior, and reproduce diverse collective behavior while capturing the role of hydrodynamic effects between rollers without resorting to the approximations previously employed. [ABSTRACT FROM AUTHOR]

Pain is rarely suffered alone. In contemporary online contexts, publicly shared pain can command the collective attention of hundreds, even millions of people. We sought to explore the possibility that collectively attending to others' pain promotes affiliation among those with whom it is attended online and identify the mechanisms that mediate these effects. Across two experimental studies, utilizing independent group designs, physically dispersed undergraduate students attended to real‐world videos depicting either physical, social, or no‐pain online. In Study 1 (N = 74, 66.22% female, Mage = 25.31 years, SDage = 6.81 years), we found evidence for the phenomenon of pain collectively attended to online, with online videos depicting physical and social pain eliciting stronger perceptions of collective attention than the non‐painful online video. In Study 2 (Time 1: N = 185, 75.14% female, Mage = 22.62 years, SDage = 7.44 years; Time 2: N = 91, 72.53% female, Mage = 23.32, SDage = 8.19), we subsequently found collectively attending to others' physical and social pain online indirectly promoted cohesion, interpersonal closeness, and desire to affiliate among participants through perceived emotional synchrony. This pattern of indirect effects was found immediately after collective attention to painful online content (Time 1) and at 1‐week follow‐up (Time 2). Although preliminary, our findings increase practical understanding of how shared pain can be harnessed to bond physically dispersed individuals together online, the implications of which we discuss in the context of the COVID‐19 pandemic. [ABSTRACT FROM AUTHOR]

Long‐term interactions among individuals are a hallmark of animal societies, but groups rarely remain entirely stable over time. Individuals die or emigrate, or groups become spatially fragmented. Group fragmentation can alter the phenotypic composition of subgroups by separating well‐connected individuals or altering sex ratios, which may alter the execution of collective behaviors. Over 10 days, we measured the aggregation behavior and collective prey capture of experimentally fragmented social spider (Stegodyphus dumicola) colonies collected from different populations in South Africa and Namibia. Colonies were fragmented for 4 weeks, after which subgroups were allowed to aggregate into a single group over time in a shared novel environment. Namibian colonies aggregated more rapidly than South African colonies. Across both populations, colonies containing individuals with higher average boldness values (faster recovery time after an antagonistic stimulus) attacked prey stimuli with more participants. However, bolder colonies from South Africa attacked prey stimuli faster, whereas attack latency in Namibian colonies was unaffected by colony boldness. These data suggest that fragmentation events, which are a common phenomenon in this species and other animal societies, can influence how individuals interact to accomplish collective tasks. Further, collective behavior and group fusion after fragmentation events can differ among groups from different populations. [ABSTRACT FROM AUTHOR]

Systems chemistry represents a shift from studying molecules in isolation to studying the collective behavior of mixtures or ensembles of reacting and interacting molecules. This research direction provides new ways to build and understand collective chemical properties and emergent functions that are inaccessible using conventional, reductionist, chemistry approaches. This field exemplifies fundamental connections between chemistry and biology, and has the potential to give rise to completely new ways for chemists to approach and resolve wide‐ranging issues related to all aspects of living systems, that themselves are complex systems. Short peptides, while simple in design, carry rich and versatile information encoded in sequence specific side‐chain interactions, that makes it possible to access a high level of complex, information rich systems with emergent properties from Life's simplified building blocks. This review focuses on recent developments in the synthesis of complex adaptive systems based on peptides, where multiple components are designed to cooperatively interact, react and collectively adapt to their context. [ABSTRACT FROM AUTHOR]

During the past decades, high‐fidelity realistic simulations of various flying insects exhibiting collective behavior have been broadly used in entertainment industries and virtual reality applications. However, due to the intrinsic complexity and high computational cost, shape constrained simulation of collective behaviors remains a challenging topic. In this paper, we present a robust multi‐agent model for large‐scale controllable shape constrained simulation of flying insects. Specifically, we design an internal force model to biologically mimic an individual insect. We also propose an external force model based on a trade‐off mechanic to guide the insects smoothly deforming into a target shape. Our experimental results and comparative studies show our method is able to simulate realistic and dynamic flying insects with various user‐specified shape constraints. [ABSTRACT FROM AUTHOR]

To avoid competition for the same food resource, scarab beetles form dung ball and roll it away from the dung pile. They randomly choose direction which they strictly follow. According to previous results, the dynamic behavior of the beetle rolling dung ball is essentially defined by the complexity of the surface. The typical real surface is combined from a universal scale invariant (fractal) component and another component having a well‐defined characteristic scale. If the transported dung ball has a size comparable with the dimensions of peculiarities of the surface, it strongly influences the motion trajectory. On the flat terrain and at the absence of competitors, beetles manage to roll the ball along a nearly perfect straight path. However, even if the beetle is alone, on a more realistic terrain, the motion is more complex. The motion becomes much more complicated in the realistic situation, when the beetles complete for the balls. In this study, a numerical model is developed which combines 1) attraction of the beetles to the dung, (2) production of the balls of different sizes depending on the size/fitness of the animals, 3) the ball transportation on complex terrains, and 4) the competition between the beetles for already existing balls. A strong correlation between typical radius of the ball and the size of the relief minimums and the results of the competitions, as well as possible optimal strategies of the beetle behavior are found. [ABSTRACT FROM AUTHOR]

We present a simulation method of pursuit‐evasion behaviors between different herds with runtime situational awareness. We model the collective movement of predators and prey in the hunting process based on an improved Boid model and the finite state machine involving multiple perception factors about the situations. Taking wolves hunting caribous as an example, our method not only simulates the collective behavior, but also realizes individual intelligent behaviors consistent with the observations. We conducted intensive experiments, and the results show that our method can simulate more realistic pursuit‐evasion behavior under different testing scenarios with a variety of parameters. Our method can be easily transferred to the theoretical study of collective behaviors of other herds. [ABSTRACT FROM AUTHOR]

The social movement‐countermovement relationship is most often one of competition. The subject of police reform has become more complex after calls for greater restrictive police policies and the emergence of Blue Lives Matter. This study demonstrates how Blue Lives Matter acts as a countermovement to police reform, frame it in a historical context, explain why it appeals to sympathizers, and illustrate how it interacts with opposing groups and individuals. This study also assesses how Blue Lives Matter operates in direct opposition to Black Lives Matter and efforts for greater police accountability. The central theme of this literature addresses how the Blue Lives Matter Movement addresses competition, criticisms, and attitudes of Blue Lives Matter adherents and detractors in local and national contexts. This study questions if reconciliation between the stated objectives and tactics of the countermovement is possible without a change in police behavior and law enforcement practices. Conflict theories identify social constructionism as a process in social and countermovements. [ABSTRACT FROM AUTHOR]

Seagrasses are vital organisms in coastal waters, and the drastic demise of their population in the last decades has worrying implications for marine ecosystems. Spatial models for seagrass meadows provide a mathematical framework to study their dynamical processes and emergent collective behavior. These models are crucial to predict the response of seagrasses to different global warming scenarios, analyze the resilience of existing seagrass distributions, and optimize restoration strategies. In this article, we propose a model that includes interactions among different species based on the clonal growth of seagrasses. We present a theoretical analysis of the model considering the specific case of the seagrass–seaweed interaction between Cymodocea nodosa and Caulerpa prolifera. Our simulations successfully reproduce field observations of shoot densities in mixed meadows in the Ebro River Delta in the Mediterranean Sea. Besides, the proposed model allows us to investigate the possible underlying mechanisms that mediate the interaction among the two macrophytes. [ABSTRACT FROM AUTHOR]

Plant essential oils are potential sources of insecticidal compounds, but have rarely been explored for their effect on termites. In the present study, we assessed the chemical composition of essential oils of Lippia sidoides Cham. (pepper-rosmarin; Verbenaceae) and Pogostemon cablin ( Blanco) Benth. (patchouli; Lamiacaeae) and evaluated their toxicity, behavioral impairment, and repellence to termite species of the genera Amitermes and Microcerotermes (Isoptera: Termitidae: Termitinae). The main components of essential oils of L. sidoides and P. cablin were thymol (44.6%) and patchouli alcohol (36.6%), respectively. The essential oil of P. cablin was most potent against Amitermes cf. amifer Silvestri and had the lowest LD50 (0.63 μg mg−1). There was no difference in toxicity for Microcerotermes indistinctus Mathews between the essential oils of L. sidoides ( LD50 = 1.49 μg mg−1) and P. cablin ( LD50 = 1.67 μg mg−1). Pogostemon cablin essential oil was the most toxic to M. indistinctus ( LC50 = 0.32 μl ml−1) and A. cf. amifer ( LC50 = 0.29 μl ml−1). The essential oils analyzed exhibited high toxicity and repellence to the termites, in addition to reducing behavioral interactions among individuals, thus constituting potential termiticides. [ABSTRACT FROM AUTHOR]

Conventional bubbles are generally made of an outside water film and the interior air, and their formation and rupture involve rich scientific knowledge. An intriguing question is what would happen if the water film and air of such bubbles were replaced by completely different fluids? Here, a high‐surface‐tension liquid metal‐solution bilayer is introduced into the two‐phase interface system, and a new conceptual hybrid vacuole consisting of a liquid metal outer membrane and inner solution core is proposed and demonstrated for the first time. Through tuning the filling volume of the liquid metal, various vacuolar structures with diverse interfacial morphologies are constructed. Such vacuoles can maintain long‐term stability via adjusting the composition of the solution, which is a mixture of surfactant and alkali. If switching glass substrate to graphite, liquid metal vacuoles would become more robust and exhibit further abundant individual and collective behaviors, which are mainly attributed to the firmer bonding strength between the two‐phase interfaces. In addition to interpreting the generation and maintenance mechanisms of the vacuole, different rupture processes are also presented and disclosed. The current findings on the liquid metal‐solution hybrid vacuoles are expected to enrich the content of liquid metal interfacial science, and will stimulate further promising applications in the emerging engineering fields. [ABSTRACT FROM AUTHOR]

We use a series of historical natural experiments in association football to test whether social pressure from a home stadium crowd affected behavior and outcomes. The standout effect of an empty stadium was that referees cautioned visiting players less often, by over a third of a yellow card per match or once for every 22 fouls committed. Stadium crowds caused referees to favor the home team in their decision‐making. Empty stadiums appear to have reduced the overall home advantage in the final outcomes of football matches, but we cannot statistically reject no effect. [ABSTRACT FROM AUTHOR]

In this study, a one‐dimensional cellular automata model is used to represent a self‐organized queueing system with local interaction between captive and boundedly rational customers who repeatedly choose a facility for service. While previous work has focused on decision rules based on adaptive expectations, the present work expands this analysis by explicitly incorporating customers' attitude toward risk to study the impact of risk aversion on the collective behavior and the average system sojourn time. The customers' decision process is modeled using adaptive expectations and incorporating the uncertainty involved in these expectations. Customers update their expectations based on their own experience and that of their neighbors. Simulation analysis is used to compare the aggregated behavior for different degrees of customer risk aversion. Risk‐neutral customers base their decisions only on their expected sojourn time, while risk‐averse customers account for uncertainty by estimating an upper bound of the sojourn times. The results indicate that the more risk‐averse the customers, the longer the transient period, and the more slowly the system converges to an almost stable average sojourn time. Systems where customers have an intermediate level of risk aversion achieve the worst average sojourn times. [ABSTRACT FROM AUTHOR]

Agent‐based modeling (ABM) has been extensively used to study the collective behavior of systems emerging from the interaction of numerous independent individuals called agents. Python and C++ are commonly used for ABM thanks to their unique features; the latter offers superior performance while the former provides ease‐of‐use and rich libraries in data science, visualization, and machine learning. We present the framework CppyABM that unifies these features by providing identical ABM semantic and development styles in both C++ and Python as well as the essential binding tools to expose a certain functionality from C++ to Python. The binding feature allows users to tailor and further extend a type or function within Python while it is originally defined in C++. Using CppyABM, users can choose either C++ or Python depending on their expertise and the specialty of the model or combine them to benefit from the advantages of both languages simultaneously. We provide showcases of CppyABM capabilities using several examples in computational biology, ecology, and virology. These examples are implemented in different formats using either C++ or Python or a combination of both to provide a comparison between the performance of implementation scenarios. The results of the example show a clear performance advantage of the models entirely or partly implemented in C++ compared to purely Python‐based implementations. [ABSTRACT FROM AUTHOR]

Most of the tragedies on any bridge structure have been the cause of high‐density crowd behavior as a response to trampling as well as the crushing scenario. Therefore, it is most important to monitor such unforeseen situations by sensing the load imposed on the bridge structures. This scenario may arise where crowd movement is huge on these types of bridges. Similarly, the fiber Bragg grating (FBG) is a promising technology for structural health monitoring applications. In this work, an Internet of Things based FBG optical sensing scheme is proposed to monitor real‐time strain distribution throughout the bridge structures and localization of load imposed on the structure from a central control room. A suspension bridge model is designed by referring to a real bridge scenario and these FBG sensors are deployed to validate the proposed machine learning models. In this article, the performances of two machine learning strategies are discussed for the accurate estimation of load and its position by acquiring high sensitive FBG sensors signals at a very high data rate. The algorithms include K‐nearest neighbor (KNN) and random forest (RF); which are applied on each sensing data source, and then validated using a prototype suspension bridge model integrated with three FBG sensors (1532 nm, 1538 nm, and1541 nm) on a single optical fiber cable. [ABSTRACT FROM AUTHOR]

In this article, I discuss some ongoing and emerging debates on spatial dynamics of protest and examine different approaches in studying spaces of protest. With a thematic approach, I first discuss studies that engage with space from a bird's eye view perspective. These studies generally focus on relational dynamics of space and examine how socioeconomic, political, and cultural elements of spatially bounded entities provide spatial contexts for mobilization and protest. I then turn to space/movement relations through revisiting dynamics of social movements as they unfold in space. Three main lines of research help in structuring these scholarly conversations: claim making; policing and control of space; and meaning making and cultural production. Finally, I discuss some new and evolving themes and trajectories, including virtual spaces and their interactions with the physical space. I conclude by discussing how these approaches intersect and shape our knowledge of spatial dynamics of protest. [ABSTRACT FROM AUTHOR]

A large number of coupled systems in nature and society can be modeled by complex cyber-physical networks, whose normal functioning significantly relies on the tight interactions between its physical and cyber components. Analysis and control of complex cyber-physical networks have received a lot of attention recently, from various scientific and engineering communities. The focus of this special issue is on new approaches to analysis and synthesis of complex cyber-physical networks as well as their potential practical applications. [Extracted from the article]

A large number of coupled systems in nature and society can be modeled by complex cyber-physical networks, whose normal functioning significantly relies on the tight interactions between its physical and cyber components. Analysis and control of complex cyber-physical networks have received a lot of attention recently, from various scientific and engineering communities. The focus of this special issue is on new approaches to analysis and synthesis of complex cyber-physical networks as well as their potential practical applications. [Extracted from the article]

An approach to manage human performance related risks in petrochemical sector is to use human reliability analyses (HRA) techniques. However, the focus of HRAs on individuals and on decomposed tasks overlooks the likelihood that collective actions and behaviors might lead to system failures. This study introduces an alternative approach, referred to as Human Performance Integrity (HPI) index, to assess human performance conditions on the whole, as they relate to safety, in petrochemical facilities. Additionally, the approach is used to rate installations in terms of their defenses against safety‐relevant human failures. The HPI index is built upon the notions of Cognitive Reliability and Error Analysis Method. By means of a 42‐question survey, data was collected on the factors that improve or reduce human performance in 11 oil refineries. Data was used to assess the facilities' safety performance. Results were compared against information obtained from relevant investigation reports, as well as and an independent evaluation of the facilities carried out by certified auditors. Findings support the use of HPI index from novice and experienced scholars and/or practitioners as a quick and effortless, yet sound and efficient manner to assess safety and reliability performance of oil refineries from a human factors perspective. [ABSTRACT FROM AUTHOR]