166 research outputs found

    Collective predator evasion: Putting the criticality hypothesis to the test

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    According to the criticality hypothesis, collective biological systems should operate in a special parameter region, close to so-called critical points, where the collective behavior undergoes a qualitative change between different dynamical regimes. Critical systems exhibit unique properties, which may benefit collective information processing such as maximal responsiveness to external stimuli. Besides neuronal and gene-regulatory networks, recent empirical data suggests that also animal collectives may be examples of self-organized critical systems. However, open questions about self-organization mechanisms in animal groups remain: Evolutionary adaptation towards a group-level optimum (group-level selection), implicitly assumed in the "criticality hypothesis", appears in general not reasonable for fission-fusion groups composed of non-related individuals. Furthermore, previous theoretical work relies on non-spatial models, which ignore potentially important self-organization and spatial sorting effects. Using a generic, spatially-explicit model of schooling prey being attacked by a predator, we show first that schools operating at criticality perform best. However, this is not due to optimal response of the prey to the predator, as suggested by the "criticality hypothesis", but rather due to the spatial structure of the prey school at criticality. Secondly, by investigating individual-level evolution, we show that strong spatial self-sorting effects at the critical point lead to strong selection gradients, and make it an evolutionary unstable state. Our results demonstrate the decisive role of spatio-temporal phenomena in collective behavior, and that individual-level selection is in general not a viable mechanism for self-tuning of unrelated animal groups towards criticality

    Active Brownian particles with velocity-alignment and active fluctuations

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    We consider a model of active Brownian particles with velocity-alignment in two spatial dimensions with passive and active fluctuations. Hereby, active fluctuations refers to purely non-equilibrium stochastic forces correlated with the heading of an individual active particle. In the simplest case studied here, they are assumed as independent stochastic forces parallel (speed noise) and perpendicular (angular noise) to the velocity of the particle. On the other hand, passive fluctuations are defined by a noise vector independent of the direction of motion of a particle, and may account for example for thermal fluctuations. We derive a macroscopic description of the active Brownian particle gas with velocity-alignment interaction. Hereby, we start from the individual based description in terms of stochastic differential equations (Langevin equations) and derive equations of motion for the coarse grained kinetic variables (density, velocity and temperature) via a moment expansion of the corresponding probability density function. We focus here in particular on the different impact of active and passive fluctuations on the onset of collective motion and show how active fluctuations in the active Brownian dynamics can change the phase-transition behaviour of the system. In particular, we show that active angular fluctuation lead to an earlier breakdown of collective motion and to emergence of a new bistable regime in the mean-field case.Comment: 5 figures, 22 pages, submitted to New Journal of Physic

    Collective motion of active Brownian particles in one dimension

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    We analyze a model of active Brownian particles with non-linear friction and velocity coupling in one spatial dimension. The model exhibits two modes of motion observed in biological swarms: A disordered phase with vanishing mean velocity and an ordered phase with finite mean velocity. Starting from the microscopic Langevin equations, we derive mean-field equations of the collective dynamics. We identify the fixed points of the mean-field equations corresponding to the two modes and analyze their stability with respect to the model parameters. Finally, we compare our analytical findings with numerical simulations of the microscopic model.Comment: submitted to Eur. Phys J. Special Topic

    Low Reynolds number hydrodynamics of asymmetric, oscillating dumbbell pairs

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    Active dumbbell suspensions constitute one of the simplest model system for collective swimming at low Reynolds number. Generalizing recent work, we derive and analyze stroke-averaged equations of motion that capture the effective hydrodynamic far-field interaction between two oscillating, asymmetric dumbbells in three space dimensions. Time-averaged equations of motion, as those presented in this paper, not only yield a considerable speed-up in numerical simulations, they may also serve as a starting point when deriving continuum equations for the macroscopic dynamics of multi-swimmer suspensions. The specific model discussed here appears to be particularly useful in this context, since it allows one to investigate how the collective macroscopic behavior is affected by changes in the microscopic symmetry of individual swimmers.Comment: 10 pages, to appear in EPJ Special Topic

    High-statistics modeling of complex pedestrian avoidance scenarios

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    Quantitatively modeling the trajectories and behavior of pedestrians walking in crowds is an outstanding fundamental challenge deeply connected with the physics of flowing active matter, from a scientific point of view, and having societal applications entailing individual safety and comfort, from an application perspective. In this contribution, we review a pedestrian dynamics modeling approach, previously proposed by the authors, aimed at reproducing some of the statistical features of pedestrian motion. Comparing with high-statistics pedestrian dynamics measurements collected in real-life conditions (from hundreds of thousands to millions of trajectories), we modeled quantitatively the statistical features of the undisturbed motion (i.e. in absence of interactions with other pedestrians) as well as the avoidance dynamics triggered by a pedestrian incoming in the opposite direction. This was accomplished through (coupled) Langevin equations with potentials including multiple preferred velocity states and preferred paths. In this chapter we review this model, discussing some of its limitations, in view of its extension toward a more complex case: the avoidance dynamics of a single pedestrian walking through a crowd that is moving in the opposite direction. We analyze some of the challenges connected to this case and present extensions to the model capable of reproducing some features of the motion

    Similarly Efficacious Anti-Malarial Drugs SJ733 and Pyronaridine Differ in Their Ability to Remove Circulating Parasites in Mice

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    BACKGROUND: Artemisinin-based combination therapy (ACT) has been a mainstay for malaria prevention and treatment. However, emergence of drug resistance has incentivised development of new drugs. Defining the kinetics with which circulating parasitized red blood cells (pRBC) are lost after drug treatment, referred to as the parasite clearance curve , has been critical for assessing drug efficacy; yet underlying mechanisms remain partly unresolved. The clearance curve may be shaped both by the rate at which drugs kill parasites, and the rate at which drug-affected parasites are removed from circulation. METHODS: In this context, two anti-malarials, SJ733, and an ACT partner drug, pyronaridine were compared against sodium artesunate in mice infected with Plasmodium berghei (strain ANKA). To measure each compound\u27s capacity for pRBC removal in vivo, flow cytometric monitoring of a single cohort of fluorescently-labelled pRBC was employed, and combined with ex vivo parasite culture to assess parasite maturation and replication. RESULTS: These three compounds were found to be similarly efficacious in controlling established infection by reducing overall parasitaemia. While sodium artesunate acted relatively consistently across the life-stages, single-dose SJ733 elicited a biphasic effect, triggering rapid, partly phagocyte-dependent removal of trophozoites and schizonts, followed by arrest of residual ring-stages. In contrast, pyronaridine abrogated maturation of younger parasites, with less pronounced effects on mature parasites, while modestly increasing pRBC removal. CONCLUSIONS: Anti-malarials SJ733 and pyronaridine, though similarly efficacious in reducing overall parasitaemia in mice, differed markedly in their capacity to arrest replication and remove pRBC from circulation. Thus, similar parasite clearance curves can result for anti-malarials with distinct capacities to inhibit, kill and clear parasites

    Active Brownian Particles. From Individual to Collective Stochastic Dynamics

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    We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte
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