摘要翻译：
在野外监测自发进化的绵羊小群体，我们破译了绵羊在个体尺度上遵循的行为规则，以维持集体运动。个体在零速度下交替放牧模式，在步行速度下交替移动模式，因此当它们决定在两种模式之间切换时，凝聚力运动源于同步。我们提出了一个个体决策过程的模型，该模型基于停/走状态之间的切换率，该切换率依赖于后面/前面的位置和其他位置的状态。我们从数据中参数化了这个模型。接下来，我们将这个（微观的）基于个体的模型转换成它的密度-流动（宏观的）方程对应。数值解这些方程组显示了一个以恒定速度传播的旅行脉冲，即使每个人在任何时刻停止或行走。考虑到这些方程中的最小模型，我们解析地导出了脉冲的稳态形状（sech平方）。脉冲的参数（形状和速度）表示为单个参数的函数。这种脉冲产生于启动/停止个体决策的非线性耦合，这种耦合精确地补偿了扩散，并促进了稳定的行走/停止个体比例，这反过来又决定了脉冲的行进速度。系统似乎从任何初始条件收敛到该脉冲，并在扰动后恢复该脉冲。这使得该协调机制具有很高的鲁棒性。
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英文标题：
《Traveling pulse emerges from individuals coordinating their stop-and-go
  motion: a case study in sheep》
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作者：
Manon Aza\"is and St\'ephane Blanco and Richard Bon and Richard
  Fournier and Marie-H\'el\`ene Pillot and Jacques Gautrais
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最新提交年份：
2018
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分类信息：

一级分类：Physics        物理学
二级分类：Pattern Formation and Solitons        图形形成与孤子
分类描述：Pattern formation, coherent structures, solitons
图案形成，相干结构，孤子
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一级分类：Physics        物理学
二级分类：Adaptation and Self-Organizing Systems        自适应和自组织系统
分类描述：Adaptation, self-organizing systems, statistical physics, fluctuating systems, stochastic processes, interacting particle systems, machine learning
自适应，自组织系统，统计物理，波动系统，随机过程，相互作用粒子系统，机器学习
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一级分类：Physics        物理学
二级分类：Biological Physics        生物物理学
分类描述：Molecular biophysics, cellular biophysics, neurological biophysics, membrane biophysics, single-molecule biophysics, ecological biophysics, quantum phenomena in biological systems (quantum biophysics), theoretical biophysics, molecular dynamics/modeling and simulation, game theory, biomechanics, bioinformatics, microorganisms, virology, evolution, biophysical methods.
分子生物物理、细胞生物物理、神经生物物理、膜生物物理、单分子生物物理、生态生物物理、生物系统中的量子现象（量子生物物理）、理论生物物理、分子动力学/建模与模拟、博弈论、生物力学、生物信息学、微生物、病毒学、进化论、生物物理方法。
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一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
  Monitoring small groups of sheep in spontaneous evolution in the field, we decipher behavioural rules that sheep follow at the individual scale in order to sustain collective motion. Individuals alternate grazing mode at null speed and moving mode at walking speed, so cohesive motion stems from synchronising when they decide to switch between the two modes. We propose a model for the individual decision making process, based on switching rates between stopped / walking states that depend on behind / ahead locations and states of the others. We parametrize this model from data. Next, we translate this (microscopic) individual-based model into its density-flow (macroscopic) equations counterpart. Numerical solving these equations display a traveling pulse propagating at constant speed even though each individual is at any moment either stopped or walking. Considering the minimal model embedded in these equations, we derive analytically the steady shape of the pulse (sech square). The parameters of the pulse (shape and speed) are expressed as functions of individual parameters. This pulse emerges from the non linear coupling of start/stop individual decisions which compensate exactly for diffusion and promotes a steady ratio of walking / stopped individuals, which in turn determines the traveling speed of the pulse. The system seems to converge to this pulse from any initial condition, and to recover the pulse after perturbation. This gives a high robustness to this coordination mechanism.
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PDF链接：
https://arxiv.org/pdf/1712.05774