scholarly journals Body size affects the strength of social interactions and spatial organization of a schooling fish ( Pseudomugil signifer )

2017 ◽  
Vol 4 (4) ◽  
pp. 161056 ◽  
Author(s):  
Maksym Romenskyy ◽  
James E. Herbert-Read ◽  
Ashley J. W. Ward ◽  
David J. T. Sumpter
Keyword(s):  
Spatial Organization ◽  
Collective Motion ◽  
Developmental Stages ◽  
Statistical Properties ◽  
Inversion Method ◽  
Particle Model ◽  
Fish Schools ◽  
Schooling Fish ◽  
Particle Speed ◽  
Fish Interactions

While a rich variety of self-propelled particle models propose to explain the collective motion of fish and other animals, rigorous statistical comparison between models and data remains a challenge. Plausible models should be flexible enough to capture changes in the collective behaviour of animal groups at their different developmental stages and group sizes. Here, we analyse the statistical properties of schooling fish ( Pseudomugil signifer ) through a combination of experiments and simulations. We make novel use of a Boltzmann inversion method, usually applied in molecular dynamics, to identify the effective potential of the mean force of fish interactions. Specifically, we show that larger fish have a larger repulsion zone, but stronger attraction, resulting in greater alignment in their collective motion. We model the collective dynamics of schools using a self-propelled particle model, modified to include varying particle speed and a local repulsion rule. We demonstrate that the statistical properties of the fish schools are reproduced by our model, thereby capturing a number of features of the behaviour and development of schooling fish.

scholarly journals A Turing test for collective motion

2015 ◽  
Vol 11 (12) ◽  
pp. 20150674 ◽  
Author(s):  
J. E. Herbert-Read ◽  
M. Romenskyy ◽  
D. J. T. Sumpter
Keyword(s):  
Large Scale ◽  
Collective Motion ◽  
Model Fitting ◽  
Turing Test ◽  
Statistical Properties ◽  
Biological Research ◽  
Particle Model ◽  
Fish Schools ◽  
The Public ◽  
Alan Turing

A widespread problem in biological research is assessing whether a model adequately describes some real-world data. But even if a model captures the large-scale statistical properties of the data, should we be satisfied with it? We developed a method, inspired by Alan Turing, to assess the effectiveness of model fitting. We first built a self-propelled particle model whose properties (order and cohesion) statistically matched those of real fish schools. We then asked members of the public to play an online game (a modified Turing test) in which they attempted to distinguish between the movements of real fish schools or those generated by the model. Even though the statistical properties of the real data and the model were consistent with each other, the public could still distinguish between the two, highlighting the need for model refinement. Our results demonstrate that we can use ‘citizen science’ to cross-validate and improve model fitting not only in the field of collective behaviour, but also across a broad range of biological systems.

scholarly journals Collective Motion of Swarming Agents Evolving on a Sphere Manifold: A Fundamental Framework and Characterization

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Wei Li
Keyword(s):  
Phase Transitions ◽  
Euclidean Space ◽  
Collective Motion ◽  
Statistical Properties ◽  
Important Impact ◽  
Almost All

Abstract Collective motion of self-propelled agents has attracted much attention in vast disciplines. However, almost all investigations focus on such agents evolving in the Euclidean space, with rare concern of swarms on non-Euclidean manifolds. Here we present a novel and fundamental framework for agents evolving on a sphere manifold, with which a variety of concrete cooperative-rules of agents can be designed separately and integrated easily into the framework, which may perhaps pave a way for considering general spherical collective motion (SCM) of a swarm. As an example, one concrete cooperative-rule, i.e., the spherical direction-alignment (SDA), is provided, which corresponds to the usual and popular direction-alignment rule in the Euclidean space. The SCM of the agents with the SDA has many unique statistical properties and phase-transitions that are unexpected in the counterpart models evolving in the Euclidean space, which unveils that the topology of the sphere has an important impact on swarming emergence.

scholarly journals Optimality, reduction and collective motion

2015 ◽  
Vol 471 (2177) ◽  
pp. 20140606 ◽  
Author(s):  
Eric W. Justh ◽  
P. S. Krishnaprasad
Keyword(s):  
Collective Motion ◽  
Optimal Control Problems ◽  
Coupling Parameter ◽  
Rigid Motion ◽  
Particle Model ◽  
Explicit Integration ◽  
Hidden Symmetry ◽  
Necessary Conditions For Optimality ◽  
Special Solutions ◽  
Optimality Principles

The planar self-steering particle model of agents in a collective gives rise to dynamics on the N -fold direct product of SE (2), the rigid motion group in the plane. Assuming a connected, undirected graph of interaction between agents, we pose a family of symmetric optimal control problems with a coupling parameter capturing the strength of interactions. The Hamiltonian system associated with the necessary conditions for optimality is reducible to a Lie–Poisson dynamical system possessing interesting structure. In particular, the strong coupling limit reveals additional (hidden) symmetry, beyond the manifest one used in reduction: this enables explicit integration of the dynamics, and demonstrates the presence of a ‘master clock’ that governs all agents to steer identically. For finite coupling strength, we show that special solutions exist with steering controls proportional across the collective. These results suggest that optimality principles may provide a framework for understanding imitative behaviours observed in certain animal aggregations.

The combined effect of attraction and orientation zones in 2D flocking models

2016 ◽  
Vol 30 (04) ◽  
pp. 1650002 ◽  
Author(s):  
Tarras Iliass ◽  
Dorilson Cambui
Keyword(s):  
Collective Motion ◽  
Numerical Study ◽  
Biological Behavior ◽  
Behavior Patterns ◽  
Vicsek Model ◽  
Agent Based ◽  
Fish Schools ◽  
Behavioral Rules ◽  
Parallel Group ◽  
Kinetic Phase Transition

In nature, many animal groups, such as fish schools or bird flocks, clearly display structural order and appear to move as a single coherent entity. In order to understand the complex motion of these systems, we study the Vicsek model of self-propelled particles (SPP) which is an important tool to investigate the behavior of collective motion of live organisms. This model reproduces the biological behavior patterns in the two-dimensional (2D) space. Within the framework of this model, the particles move with the same absolute velocity and interact locally in the zone of orientation by trying to align their direction with that of the neighbors. In this paper, we model the collective movement of SPP using an agent-based model which follows biologically motivated behavioral rules, by adding a second region called the attraction zone, where each particles move towards each other avoiding being isolated. Our main goal is to present a detailed numerical study on the effect of the zone of attraction on the kinetic phase transition of our system. In our study, the consideration of this zone seems to play an important role in the cohesion. Consequently, in the directional orientation, the zone that we added forms the compact particle group. In our simulation, we show clearly that the model proposed here can produce two collective behavior patterns: torus and dynamic parallel group. Implications of these findings are discussed.

scholarly journals Developmental expression of fibrillin genes suggests heterogeneity of extracellular microfibrils.

1995 ◽  
Vol 129 (4) ◽  
pp. 1165-1176 ◽  
Author(s):  
H Zhang ◽  
W Hu ◽  
F Ramirez
Keyword(s):  
Spatial Organization ◽  
Developmental Stages ◽  
Elastic Fiber ◽  
Biomechanical Properties ◽  
Developmental Expression ◽  
Elastic Fibers ◽  
Fiber Assembly ◽  
Structural Support ◽  
Functional Relationships ◽  
Fibrillin 1

Extracellular microfibrils, alone or in association with elastin, confer critical biomechanical properties on a variety of connective tissues. Little is known about the composition of the microfibrils or the factors responsible for their spatial organization into tissue-specific macroaggregates. Recent work has revealed the existence of two structurally related microfibrillar components, termed fibrillin-1 and fibrillin-2. The functional relationships between these glycoproteins and between them and other components of the microfibrils and elastic fibers are obscure. As a first step toward elucidating these important points, we compared the expression pattern of the fibrillin genes during mammalian embryogenesis. The results revealed that the two genes are differentially expressed, in terms of both developmental stages and tissue distribution. In the majority of cases, fibrillin-2 transcripts appear earlier and accumulate for a shorter period of time than fibrillin-1 transcripts. Synthesis of fibrillin-1 correlates with late morphogenesis and the appearance of well-defined organ structures; fibrillin-2 synthesis, on the other hand, coincides with early morphogenesis and, in particular, with the beginning of elastogenesis. The findings lend indirect support to our original hypothesis stating that fibrillins contribute to the compositional and functional heterogeneity of the microfibrils. The available evidence is also consistent with the notion that the fibrillins might have distinct, but related roles in microfibril physiology. Accordingly, we propose that fibrillin-1 provides mostly force-bearing structural support, whereas fibrillin-2 predominantly regulates the early process of elastic fiber assembly.

scholarly journals Identification of Biofilm Matrix-Associated Proteins from an Acid Mine Drainage Microbial Community

2011 ◽  
Vol 77 (15) ◽  
pp. 5230-5237 ◽  
Author(s):  
Yongqin Jiao ◽  
Patrik D'haeseleer ◽  
Brian D. Dill ◽  
Manesh Shah ◽  
Nathan C. VerBerkmoes ◽  
...  
Keyword(s):  
Extracellular Matrix ◽  
Spatial Organization ◽  
Extracellular Polymeric Substances ◽  
Developmental Stages ◽  
Mine Drainage ◽  
Cell Envelope ◽  
Shotgun Proteomics ◽  
Extracellular Proteins ◽  
Cold Shock Protein ◽  
Biofilm Development

ABSTRACTIn microbial communities, extracellular polymeric substances (EPS), also called the extracellular matrix, provide the spatial organization and structural stability during biofilm development. One of the major components of EPS is protein, but it is not clear what specific functions these proteins contribute to the extracellular matrix or to microbial physiology. To investigate this in biofilms from an extremely acidic environment, we used shotgun proteomics analyses to identify proteins associated with EPS in biofilms at two developmental stages, designated DS1 and DS2. The proteome composition of the EPS was significantly different from that of the cell fraction, with more than 80% of the cellular proteins underrepresented or undetectable in EPS. In contrast, predicted periplasmic, outer membrane, and extracellular proteins were overrepresented by 3- to 7-fold in EPS. Also, EPS proteins were more basic by ∼2 pH units on average and about half the length. When categorized by predicted function, proteins involved in motility, defense, cell envelope, and unknown functions were enriched in EPS. Chaperones, such as histone-like DNA binding protein and cold shock protein, were overrepresented in EPS. Enzymes, such as protein peptidases, disulfide-isomerases, and those associated with cell wall and polysaccharide metabolism, were also detected. Two of these enzymes, identified as β-N-acetylhexosaminidase and cellulase, were confirmed in the EPS fraction by enzymatic activity assays. Compared to the differences between EPS and cellular fractions, the relative differences in the EPS proteomes between DS1 and DS2 were smaller and consistent with expected physiological changes during biofilm development.

Optimization Inversion of the Micro-Properties of Bonded Particle Model in PFC Based on the Asynchronous Particle Swarm Algorithm

2014 ◽  
Vol 1082 ◽  
pp. 240-245
Author(s):  
Lei Xu ◽  
Qing Wen Ren
Keyword(s):  
Particle Swarm ◽  
Fortran Program ◽  
Inversion Method ◽  
Particle Model ◽  
Particle Swarm Algorithm ◽  
Trial And Error ◽  
Time Consumption ◽  
Bonded Particle Model ◽  
Swarm Algorithm ◽  
Related Constraint

The calibration of micro-properties of bonded particle model (BPM) is usually artificially accomplished by the means of trial and error which has some intrinsic drawbacks such as high time consumption, arbitrariness, uncontrolled accuracy, etc. In order to overcome these shortcomings, the optimization inversion method based on the asynchronous particle swarm algorithm is proposed to estimate the micro-properties of BPM in PFC. The optimization model is firstly established by formulating the objective function and related constraint conditions, and then the procedure of optimization inversion is presented. Furthermore, a FORTRAN program called PIBPM is developed for the realization of the proposed method. The feasibility of the proposed method and the correctness of PIBPM are verified through an application example.

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