Collective Behavior Research Articles

Collective behaviour in proton number fluctuations seen in [formula omitted] 2.4 GeV Au+Au collisions

At energies of a few GeV per nucleon, nuclear collisions exhibit phenomena more complex than the individualistic nucleon interactions observed at much higher energies. From recent results on proton number fluctuations in Au+Au collisions at sNN=2.4 GeV obtained by the HADES experiment at GSI, we suggest that measuring the multiplicity distributions heavy-ion collisions can be used to probe density fluctuations associated with correlation phenomena. Using the combinant analysis, we demonstrate that the proton multiplicity distributions can be described by a compound Poisson-binomial distribution, suggesting the formation of clusters as a possible mechanism of such proton number fluctuations.

Emergence of Collective Behaviors for the Swarm Robotics Through Visual Attention-Based Selective Interaction

Emergence of Collective Behaviors for the Swarm Robotics Through Visual Attention-Based Selective Interaction

Virtual Crowds Rheology: Evaluating the Effect of Character Representation on User Locomotion in Crowds.

Crowd data is a crucial element in the modeling of collective behaviors, and opens the way to simulation for their study or prediction. Given the difficulty of acquiring such data, virtual reality is useful for simplifying experimental processes and opening up new experimental opportunities. This comes at the cost of the need to assess the biases introduced by the use of this technology. Our paper is part of this effort, and investigates the effect of the graphical representation of a crowd on the behavior of a user immersed within. More specifically, we inspect the virtual navigation through virtual crowds, in terms of travel speeds and local navigation choices as a function of the visual representation of the virtual agents that make up the crowd (simple geometric model, anthropomorphic model or realistic model). Through an experiment in which we ask a user to navigate virtual crowds of varying densities, we show that the effect of the visual representation is limited, but that an anthropomorphic representation offers the best trade-off between computational complexity and ecological validity, even though a more realistic representation can be preferred when user behaviour is studied in more details. Our work leads to clear recommendations on the design of immersive simulations for the study of crowd behavior.

Social Learning in Neural Agent-Based Models

Abstract Agent-based models (ABMs) are widely used to study how individual interactions shape collective behaviors. Critics argue that ABMs are often too simplistic to capture real-world complexities. We address this by integrating artificial neural networks into ABMs, focusing on enhancing the Hegselmann–Krause (HK) model. By using multilayer perceptrons as agents, we create more realistic ABMs that better reflect actual agents. This approach yields multiple models, as core elements of the HK model can be defined in various ways. We conduct two computational studies to compare these models with each other and with traditional individual-learning paradigms.

Tuning collective behaviour in zebrafish with genetic modification.

Zebrafish collective behaviour is widely used to assess their physical and mental state, serving as a valuable tool to assess the impact of ageing, disease genetics, and the effect of drugs. The essence of these macroscopic phenomena can be represented by active matter models, where the individuals are abstracted as interactive self-propelling agents. The behaviour of these agents depends on a set of parameters in a manner reminiscent of those between the constituents of physical systems. In a few cases, the system may be controlled at the level of the individual constituents such as the interactions between colloidal particles, or the enzymatic behaviour of de novo proteins. Usually, however, while the collective behaviour may be influenced by environmental factors, it typically cannot be changed at will. Here, we challenge this scenario in a biological context by genetically modifying zebrafish. We thus demonstrate the potential of genetic modification in the context of controlling the collective behaviour of biological active matter systems at the level of the constituents, rather than externally. In particular, we probe the effect of the lack of col11a2 gene in zebrafish, which causes the early onset of osteoarthritis. The resulting col11a2 -/- zebrafish exhibited compromised vertebral column properties, bent their body less while swimming, and took longer to change their orientations. Surprisingly, a group of 25 mutant fish exhibited more orderly collective motion than the wildtype. We show that the collective behaviour of wildtype and col11a2 -/- zebrafish are captured with a simple active matter model, in which the mutant fish are modelled by self-propelling agents with a higher orientational noise on average. In this way, we demonstrate the possibility of tuning a biological system, changing the state space it occupies when interpreted with a simple active matter model.

Pathogen-specific social immunity is associated with erosion of individual immune function in an ant

Contagious diseases are a major threat to societies in which individuals live in close contact. Social insects have evolved collective defense behaviors, such as social care or isolation of infected workers, that prevent outbreaks of pathogens. It has thus been suggested that individual immunity is reduced in species with such ‘social immunity’. However, this hypothesis has not been tested functionally. Here, we characterize the immune response of the ant Lasius niger using a combination of genomic analysis, experimental infections, gene expression quantification, behavioural observations and pathogen quantifications. We uncover a striking specialization of immune responses towards different pathogens. Systemic individual immunity is effective against opportunistic bacterial infections, which are not covered by social immunity, but is not elicited upon fungal infections, which are effectively controlled by social immunity. This specialization suggests that immune layers have evolved complementary functions predicted to ensure the most cost-effective response against a wide range of pathogens.

Tree structures may be the leadership structures employed by group motions exhibiting hierarchy

Collective behaviors leading to various fascinating movement patterns are believed to be the product of complex interplay among individuals. Previous studies have identified two types of leadership structures in pigeon flocks, i.e., hierarchical networks and reciprocal relationships. However, both of these leadership structures are predicated based on data analysis and lack substantial empirical evidence. Additionally, it is difficult to delineate a direct correspondence between leadership structures and trajectory data for pigeon flocks because birds cannot report their leadership structure. Herein, based on experiments involving volunteers, we found that tree structures may serve as the leadership structures employed by group motions exhibiting hierarchy. In the tree structure, each follower follows its only leader during collective motions, and the single top leader determines the direction of collective motions. By employing the tree structure, we introduced a model for describing collective motions. A method for obtaining the leadership structure through experimental trajectory data was proposed. This strategy was used to analyze flight trajectory data from a pigeon flock and elucidate the pigeons' leadership relationships. Our model can simulate the collective behavior of pigeon flocks, thus accurately replicating the findings of previous experimental studies. The results of this study provide insights regarding the leadership structure in pigeon flocks and have implications for artificial collective systems, e.g., autonomous formation control of multiple unmanned aerial vehicles or unmanned surface vehicles. Published by the American Physical Society 2024

“No punishment is enough for monsters”: vindictiveness as an important political emotion in dealing with Belgian (potential) returnee men

ABSTRACT Building on the call to further integrate emotions in critical security and terrorism studies, we explore the ways emotions figure in media discourses and shape responses and policies on the returnee question. Through critical discourse analysis and thick description, we show how Belgian (potential) returnee men were subject to varying securitising discourses and emotional portrayals in media coverage over the past decade. Our argument contends that media discourse(s) on the returnee question exhibit a complex emotional landscape. We discern dominant, alternative and rising emotions that undergird the media coverage. We will illustrate how the “dominant” emotion of fear oscillated with an “alternative” emotion of vulnerability and, over the course of a decade, was accompanied by a “rising” emotion of vindictiveness. We argue that the cultivation of vindictiveness contributes to securitising narratives that portray Belgian (potential) returnee men as irredeemable monsters deserving of extreme punishments. This rising discourse undermines democratic principles and the rule of law. We speak of political emotions because emotions are deeply intertwined with power dynamics, societal structures, and political processes, which shape collective attitudes, behaviours, and policies towards (potential) returnees.

Long range juxtacrine signalling through cadherin for collective cell orientation

Many life phenomena, such as development, morphogenesis, tissue remodelling, and wound healing, are often driven by orderly and directional migration of collective cells. However, when cells are randomly oriented or localized disorder exists in orderly oriented collective cells, cell migration cannot occur in an orderly manner although various motion modes such as global rotation and local swirling and/or various motion patterns such as radial pattern and chiral pattern often occur. Therefore, it is important to control cell orientation to ensure the orderly migration of collective cells. Here, we show that it is not force transmission, but juxtacrine signalling through cadherin that plays a critical role in the orientation of collective cells. Surprisingly, juxtacrine signalling for cell orientation reached cells on a plastic dish that were not directly subjected to mechanical stimulation, up to 7 mm away from the actuator. The present study suggests that even weak mechanical stimulation is transmitted in a long range without force transmission through juxtacrine signalling. The long range juxtacrine signalling might play an important role in various life phenomena. Statement of SignificanceJuxtacrine signalling is direct cell-cell contact-dependent signalling, which plays a crucial role in cell behaviors such as mechanosensing, mechanotransduction and collective cell behaviors, however, there is not enough understanding about juxtacrine signalling. The present study has demonstrated that juxtacrine signalling for collective cell orientation is transmitted over a long range through cadherin. To the best of our knowledge, this is the first report of long range juxtacrine signalling. This finding may lead to the elucidation of various life phenomena such as development, morphogenesis, tissue remodelling, and wound healing.

المعنى المشترك وجماليات الخطاب في التصميم الداخلي

Designers seek to create a design product that is dialogic and communicative with the largest number of segments of society, with visual formations that prepare for a spatial environment that is distinguished by intellectual richness and seeks to communicate with minds. Then, the design represents a visual discourse that influences the recipient, as an intentional message that reaches his imagination with its idea, including the aesthetic meanings inherent in it, and what its intellectual and semantic content carries, the aim of which is to reach a common meaning between the designer and the recipient so that the designer can lead the recipient's behavior according to the ideas presented by the design. Therefore, the research problem was formulated with the following question: "Is interior design concerned with visual formations to highlight formal values that aim to improve the aesthetic taste through the visual reception system of the recipient only, or is it an ideology that indicates that these formations are more than just what the eye sees because of their connection to the shared latent meaning between the designer and the recipient, which is reflected in the nature of collective behavior?" The research aimed to "reveal the data of the aesthetic image of the formal discourse by translating the latter into an internal space that gives the recipient interpretations that are in harmony with what the designer is going for as a directed message with intent and meaning." The research came out with a set of conclusions, the most important of which are: The design product constitutes a message with a clear meaning when it is a reflection of the social, cultural, material and geographical environment of the design context through the aesthetic formations of the design discourse, and that the reception mechanism is not destined to succeed unless the designer has a specific idea that reflects the privacy of society and the identity of the place through what the design broadcasts in order to obtain a clear and easy response from the recipient and decipher the symbols of the discourse and enjoy its connotations and goals.

How root-grafted trees form networks: Modeling network dynamics with pyNET

Natural root grafting is a widespread phenomenon in woody plants. While previous studies have focused on the effects of reduced growth and resource exchange at the individual level, we lack an understanding of the collective behavior of groups of grafted trees and the networks they form. Here, we present pyNET, a mechanistic agent-based model designed to explore the emergence of root graft networks. We performed simulation experiments with different scenarios involving water scarcity and different cost-benefit dynamics. Costs denote the resources required to form root grafts, while benefits denote the water redistributed among trees. Our model successfully replicates observed patterns linking structural variables to network characteristics. Specifically, we were able to reproduce observed characteristics such as grafting frequency and mean group size. In particular, we find that while the network structure is naturally strongly influenced by the size of the root system, the time and resources allocated to grafting are also critical factors. pyNET serves as a valuable tool for exploring the formation of root grafting networks under diverse environmental conditions and understanding their impact on resource competition. Our study supports theory development on the subject and hopefully stimulates further empirical studies.

Collective swimming pattern and synchronization of fish pairs (Gobiocypris rarus) in response to flow with different velocities.

Collective behaviors in moving fish originate from social interactions, which are thought to be driven by beneficial factors, such as predator avoidance and reduced energy expenditure. Despite numerical simulations and physical experiments aiming at the hydrodynamic mechanisms and interaction rules, how shoaling is influenced by flow velocity and group size is still only partially understood. In this study, spatial distributions, kinematics, and synchronization states between pairs (smallest subsystem of a shoal) of Gobiocypris rarus were investigated in a recirculating swim tunnel with increasing flow velocities from 0.1 to 0.5 m/s (Ucrit = 0.6 m/s). Tests of single fish were also conducted as the control group. The results of spatial distributions showed that fish pairs preferred to swim in the side-by-side configuration under high flows, while under low flows the neighboring fish's positions were more uniformly distributed around the focal fish in the transverse direction. Kinematic analysis revealed that fish pairs adopted similar tail beats (i.e., frequency and Strouhal number) as single fish in low flows, while in high flows both the frequency and Strouhal number of fish pairs were slightly lower. Moreover, the synchronization rates of fish pairs were found to increase with flow velocities, suggesting that synchronized swimming may be beneficial, especially in high flows.

Collective behavior of active filaments with homogeneous and heterogeneous stiffness.

The collective dynamics of active biopolymers is crucial for many processes in life, such as cellular motility, intracellular transport, and division. Recent experiments revealed fascinating self-organized patterns of diverse active filaments, while an explicit parameter control strategy remains an open problem. Moreover, theoretical studies so far mostly dealt with active chains with uniform stiffness, which are inadequate in describing the more complicated class of polymers with varying stiffness along the backbone. Here, using Langevin dynamics simulations, we investigate the collective behavior of active chains with homogeneous and heterogeneous stiffness in a comparative manner. We map a detailed non-equilibrium phase diagram in activity and stiffness parameter space. A wide range of phase states, including melt, cluster, spiral, polar, and vortex, are demonstrated. The appropriate parameter combination for large-scale polar and vortex formation is identified. In addition, we find that stiffness heterogeneity can substantially modulate the phase behaviors of the system. It has an evident destructive effect on the long-ranged polar structure but benefits the stability of the vortex pattern. Intriguingly, we unravel a novel polar-vortex transition in both homogeneous and heterogeneous systems, which is closely related to the local alignment mechanism. Overall, we achieve new insights into how the interplay among activity, stiffness, and heterogeneity affects the collective dynamics of active filament systems.

The Countoscope: Measuring Self and Collective Dynamics without Trajectories

Driven by physical questions pertaining to quantifying particle dynamics, microscopy can now resolve complex systems at the single-particle level, from cellular organisms to individual ions. Yet, available analysis techniques face challenges reconstructing trajectories in dense and heterogeneous systems where accurately labeling particles is difficult. Furthermore, the inescapable finite field of view of experiments hinders the measurement of collective effects. Inspired by Smoluchowski, we introduce a broadly applicable analysis technique that probes dynamics of interacting particle suspensions based on a remarkably simple principle: counting particles in finite observation boxes. Using colloidal experiments, advanced simulations, and theory, we first demonstrate that statistical properties of fluctuating counts can be used to determine self-diffusion coefficients, so alleviating the hurdles associated with trajectory reconstruction. We also provide a recipe for practically extracting the diffusion coefficient from experimental data at variable particle densities, which is sensitive to steric and hydrodynamic interactions. Remarkably, by increasing the observation box size, counting naturally enables the study of collective dynamics in dense suspensions. Using our novel analysis of particle counts, we uncover a surprising enhancement of collective behavior due to hydrodynamics as well as a new length scale which can be connected with hyperuniform structure. Our counting framework, the “countoscope,” thus enables efficient measurements of self and collective dynamics in dense suspensions and opens the way to quantifying dynamics and identifying novel physical mechanisms in diverse complex systems where single particles can be resolved. Published by the American Physical Society 2024

Fluid mediated communication among flexible micro-posts in chemically reactive solutions.

Communication in biological systems typically involves enzymatic reactions that occur within fluids confined between the soft, elastic walls of bio-channels and chambers. Through the inherent transformation of chemical to mechanical energy, the fluids can be driven to flow within the confined domains. Through fluid-structure interactions, the confining walls in turn are deformed by and affect this fluid flow. Imbuing synthetic materials with analogous feedback among chemo-mechanical, hydrodynamic and fluid-structure interactions could enable materials to perform self-driven communication and self-regulation. Herein, we develop computational models to determine how chemo-hydro-mechanical feedback affects interactions in biomimetic arrays of chemically active and passive micro-posts anchored in fluid-filled chambers. Once activated, the enzymatic reactions trigger the latter feedback, which generates a surprising variety of long-range, cooperative motion, including self-oscillations and non-reciprocal interactions, which are vital for propagating coherent, directional signals over net distances in fluids. In particular, the array propagates a distinct message; each post interprets the message; and the system responds with a specific mode of organized, collective behavior. This level of autonomous remote control is relatively rare in synthetic systems, particularly as this system operates without external electronics or power sources and only requires the addition of chemical reactants to function.

This Is an Eventful Era: Exploring Event-Oriented Approaches to Organizational Research

This special issue explores the transformative role of discrete events in fostering changes at different organizational levels, challenging traditional feature-oriented approaches that focus on stable attributes of individuals, groups, and organizations. Joining the growing body of event-oriented research in diverse settings, the nine published articles evoke a novel theoretical lens (i.e., Event System Theory) to examine a number of discrete events (e.g., everyday change events, organizational downsizing, merger, corporate scandal, technology implementation, the U.S.–China trade war, the Black Lives Matter movement). Their findings demonstrate the interesting ways discrete events disrupt routines, prompt adaptation, and impact individual and collective behaviors across various levels within organizations. Our further analysis underscores the importance of adopting an event-oriented perspective for a better understanding of management issues, offering new insights and directions for future research. We hope this special issue provides a robust foundation for integrating event-centric research approaches into organizational theory, emphasizing the need for continued empirical investigation and theoretical refinement in a variety of management research domains, such as strategic management, organizational behavior, entrepreneurship, and human resource management.

Body orientation change of neighbors leads to scale-free correlation in collective motion

Collective motion, such as milling, flocking, and collective turning, is a common and captivating phenomenon in nature, which arises in a group of many self-propelled individuals using local interaction mechanisms. Recently, vision-based mechanisms, which establish the relationship between visual inputs and motion decisions, have been applied to model and better understand the emergence of collective motion. However, previous studies often characterize the visual input as a transient Boolean-like sensory stream, which makes it challenging to capture the salient movements of neighbors. This further hinders the onset of the collective response in vision-based mechanisms and increases demands on visual sensing devices in robotic swarms. An explicit and context-related visual cue serving as the sensory input for decision-making in vision-based mechanisms is still lacking. Here, we hypothesize that body orientation change (BOC) is a significant visual cue characterizing the motion salience of neighbors, facilitating the emergence of the collective response. To test our hypothesis, we reveal the significant role of BOC during collective U-turn behaviors in fish schools by reconstructing scenes from the view of individual fish. We find that an individual with the larger BOC often takes on the leading role during U-turns. To further explore this empirical finding, we build a pairwise interaction mechanism on the basis of the BOC. Then, we conduct experiments of collective spin and collective turn with a real-time physics simulator to investigate the dynamics of information transfer in BOC-based interaction and further validate its effectiveness on 50 real miniature swarm robots. The experimental results show that BOC-based interaction not only facilitates the directional information transfer within the group but also leads to scale-free correlation within the swarm. Our study highlights the practicability of interaction governed by the neighbor’s body orientation change in swarm robotics and the effect of scale-free correlation in enhancing collective response.

Using reinforcement learning to autonomously identify sources of error for agents in group missions

When deploying agents to execute a mission with collective behavior, it is common for accidental malfunctions to occur in some agents. It is challenging to distinguish whether these malfunctions are due to actuator failures or sensor issues based solely on interactions with the affected agent. However, we humans know that if we cause a group behavior where other agents collide with a suspected malfunctioning agent, we can monitor the presence or absence of a positional change and identify whether it is the actuator (position changed) or the sensor (position unchanged) that is broken. We have developed artificial intelligence that can autonomously deploy such “information acquisition strategies through collective behavior” using machine learning. In such problems, the goal is to plan collective actions that result in differences between the hypotheses for the state [e.g., actuator or sensor]. Only a few of the possible collective behavior patterns will lead to distinguishing between hypotheses. The evaluation function to maximize the difference between hypotheses is therefore sparse, with mostly flat values across most of the domain. Gradient-based optimization methods are ineffective for this, and reinforcement learning becomes a viable alternative. By handling this maximization problem, our reinforcement learning surprisingly gets the optimal solution, resulting in collective actions that involve collisions to differentiate the causes. Subsequent collective behaviors, reflecting this situation awareness, seemed to involve other agents assisting the malfunctioning agent.

Environmental shocks and agriculture: implications of floods on labor market outcomes

Abstract Floods often displace people and exacerbate their access to finance, affecting the livelihood of daily wage workers in least-developed countries. In August 2017, Nepal experienced the heaviest rainfall in more than 60 years, severely flooding about 80 per cent of the land in the southern part of the country. Using the two-way fixed effects approach and an event study design, we evaluate the impact of severe flooding on the wages of agricultural workers. We show that the 2017 floods resulted in a 9–10 per cent decrease in cash wages among agricultural households while in-kind wages of agricultural laborers increased significantly after the floods, implying that in-kind wages helped mitigate the adverse effects of floods on cash wages. We also investigate changes in assistance, loan-seeking behavior, loan repayment, and collection behavior as mechanisms leading to the risk-mitigating behavior by farmers.

A graphite thermal Tesla valve driven by hydrodynamic phonon transport.

The Tesla valve benefits the rectification of fluid flow in microfluidic systems1-6 and inspires researchers to design modern solid-state electronic and thermal rectifiers referring to fluid-rectification mechanisms in a liquid-state context. In contrast to the rectification of fluids in microfluidic channels, the rectification of thermal phonons in micro-solid channels presents increased complexity owing to the lack of momentum-conserving collisions between phonons and the infrequent occurrence of liquid-like phonon flows. Recently, investigations and revelations of phonon hydrodynamics in graphitic materials7-10 have opened up new avenues for achieving thermal rectification. Here we demonstrate a phonon hydrodynamics approach to realize the rectification of heat conduction in isotopically enriched graphite crystals. We design a micrometre-scale Tesla valve within 90-nm-thick graphite and experimentally observe a discernible 15.2% difference in thermal conductivity between opposite directions at 45 K. This work marks an important step towards using collective phonon behaviour for thermal management in microscale and nanoscale electronic devices, paving the way for thermal rectification in solids.