Phase separation driven by density-dependent movement: A novel mechanism for ecological patterns

Many ecosystems develop strikingly regular spatial patterns because of small-scale interactions between organisms, a process generally referred to as spatial self-organization. Self-organized spatial patterns are important determinants of the functioning of ecosystems, promoting the growth and survival of the involved organisms, and affecting the capacity of the organisms to cope with changing environmental conditions. The predominant explanation for self-organized pattern formation is spatial heterogeneity in establishment, growth and mortality, resulting from the self-organization processes. A number of recent studies, however, have revealed that movement of organisms can be an important driving process creating extensive spatial patterning in many ecosystems. Here, we review studies that detail movement-based pattern formation in contrasting ecological settings. Our review highlights that a common principle, where movement of organisms is density-dependent, explains observed spatial regular patterns in all of these studies. This principle, well known to physics as the Cahn–Hilliard principle of phase separation, has so-far remained unrecognized as a general mechanism for self-organized complexity in ecology. Using the examples presented in this paper, we explain how this movement principle can be discerned in ecological settings, and clarify how to test this mechanism experimentally. Our study highlights that animal movement, both in isolation and in unison with other processes, is an important mechanism for regular pattern formation in ecosystems.     

孕震断层锁固段累积损伤导致失稳的自组织-临界行为特征

弄清锁固段（岩石）破裂过程中自组织临界性的物理涵义,对正确认识地震可预测性问题等具有重要意义.本文指出锁固段破裂过程存在两个临界点,第一临界点为体积膨胀点,是自组织过程起点,在该点锁固段发生可判识的高能级破裂事件,这可视为锁固段宏观破裂前的惟一可识别前兆;第二临界点为峰值强度点,即失稳点,在该点通常发生有明显地表破裂带的大地震.基于以前研究给出的两者之间应变比理论关系以及地震震级与能量约束关系,可预测锁固段在第一和第二临界点处发生的某些标志性地震,并已得到诸多震例分析的支持.本文研究结果表明：由于锁固段是非均匀介质,失稳前必须出现自组织过程,自组织是“因”,临界失稳是“果”,正是因为自组织过程的存在,才使得对某些大地震（如标志性地震）的预测成为可能;两个临界点之间的破裂演化过程并不是瞬态行为,通常是一个长期过程,该过程中标志性地震的发生遵循确定性规律,并不存在小地震直接导致大地震（如标志性地震）的级联效应.     

Functional Interdependence in Coupled Dissipative Structures: Physical Foundations of Biological Coordination

Coordination within and between organisms is one of the most complex abilities of living systems, requiring the concerted regulation of many physiological constituents, and this complexity can be particularly difficult to explain by appealing to physics. A valuable framework for understanding biological coordination is the coordinative structure, a self-organized assembly of physiological elements that collectively performs a specific function. Coordinative structures are characterized by three properties: (1) multiple coupled components, (2) soft-assembly, and (3) functional organization. Coordinative structures have been hypothesized to be specific instantiations of dissipative structures, non-equilibrium, self-organized, physical systems exhibiting complex pattern formation in structure and behaviors. We pursued this hypothesis by testing for these three properties of coordinative structures in an electrically-driven dissipative structure. Our system demonstrates dynamic reorganization in response to functional perturbation, a behavior of coordinative structures called reciprocal compensation. Reciprocal compensation is corroborated by a dynamical systems model of the underlying physics. This coordinated activity of the system appears to derive from the system’s intrinsic end-directed behavior to maximize the rate of entropy production. The paper includes three primary components: (1) empirical data on emergent coordinated phenomena in a physical system, (2) computational simulations of this physical system, and (3) theoretical evaluation of the empirical and simulated results in the context of physics and the life sciences. This study reveals similarities between an electrically-driven dissipative structure that exhibits end-directed behavior and the goal-oriented behaviors of more complex living systems.     

The strain relaxation of InAs/GaAs self-organized quantum dot

This paper presents a detailed analysis of the dependence of degree of strain relaxation of the self-organized InAs/GaAs quantum dot on the geometrical parameters. Differently shaped quantum dots arranged with different transverse periods are simulated in this analysis. It investigates the total residual strain energy that stored in the quantum dot and the substrate for all kinds of quantum dots with the same volume, as well as the dependence on both the aspect ratio and transverse period. The calculated results show that when the transverse period is larger than two times the base of the quantum dots, the influence of transverse periods can be ignored. The larger aspect ratio will lead more efficient strain relaxation. The larger angle between the faces and the substrate will lead more efficient strain relaxation. The obtained results can help to understand the shape transition mechanism during the epitaxial growth from the viewpoint of energy, because the strain relaxation is the main driving force of the quantum dot's self-organization.     

Bubbling and large-scale structures in avalanche dynamics

Using a simple lattice model for granular media, we present a scenario of self-organization that we term self-organized structuring where the steady state has several unusual features: (1) large-scale spatial and/or temporal inhomogeneities and (2) the occurrence of a nontrivial peaked distribution of large events which propagate like "bubbles" and have a well-defined frequency of occurrence. We discuss the applicability of such a scenario for other models introduced in the framework of self-organized criticality.     

红外光谱评价内燃机油抗氧化性能的研究

红外光谱快速检测石油产品性能是近年来发展的新技术,目前国内外在该领域的研究仅限于测试燃料油性能,由于润滑油组成、结构复杂,红外光谱技术测试润滑油性能的研究还未见报道。文章研究了润滑油组成、结构的红外光谱特征,提出了根据内燃机油组成、结构对抗氧化性能的贡献来提取其光谱信息的技术路线。结合BP神经网络和自组织神经网络的优点,发展了量化自组织神经网络数学模型,该数学模型具有自组织神经网络的定性聚类功能和BP神经网络的定量分析功能,与BP神经网络相比较,量化自组织神经网络具有更好的鲁棒性,测试结果优于BP神经网络,该论文的研究为润滑油性能的快速检测提供了一种新的技术手段。     

核子与核力决定的核形状(英文)

讨论了最近提出的作为量子多体系统重要潜在机制之一的量子自组织,原子核无疑是最好的实例。由于原子核内核子的单粒子和集体运动共存,它们的相互制约决定了核结构。集体模式因其驱动力,如使椭球形变的四极力及其阻力达到平衡形成,而单粒子能量就是产生阻力的一种根源。当存在较大单粒子能隙时,相关的集体运动更易受到阻碍。因此,一般认为,单粒子运动和集体运动是相互对抗的"天敌"。然而,由于核力的多样和复杂性,单极相互作用使单粒子能量改变也能减小其对集体运动的阻碍而加强集体模式,该现象将通过Zr同位素实例加以说明。这就导致了量子自组织的产生:单粒子能量由两种量子液体（质子和中子）和控制阻力的单极相互作用自组织。于是,不同于朗道费米液体理论的结论,原子核不一定像填装了自由核子的刚性瓶。Ⅱ型壳演化即是包含跨准幻壳能隙激发的直观实例。在重核中,量子自组织因其轨道和核子数更多而更为重要。We discuss the quantum self-organization introduced recently as one of the major underlying mechanisms of the quantum many-body systems. Atomic nuclei are actually a good example, because two types of the motion of nucleons, single-particle states and collective modes, interplay in determining their structure. The collective mode appears as a consequence of the balance between the effect of the mode-driving force (e.g., quadrupole force for the ellipsoidal deformation) and the resistance power against it. The single-particle energies are one of the sources to bring about such resistance power:a coherent collective motion is more hindered by larger spacings between relevant single particle states. Thus, the single-particle state and the collective mode are "enemies" against each other in the usual understanding. However, the nuclear forces are rich and complicated enough so as to enhance relevant collective mode by reducing the resistance power by changing single-particle energies for each eigenstate through monopole interactions. This will be demonstrated with the concrete example taken from Zr isotopes. In this way, the quantum self-organization occurs:single-particle energies can be self-organized by (i) two quantum liquids, e.g., protons and neutrons, (ii) monopole interaction (to control resistance). Thus, atomic nuclei are not necessarily like simple rigid vases containing almost free nucleons, in contrast to the naïve Fermi liquid picture a la Landau. Type Ⅱ shell evolution is considered to be a simple visible case involving excitations across a (sub)magic gap. The quantum self-organization becomes more important in heavier nuclei where the number of active orbits and the number of active nucleons are larger.     

Self-organized phenomena of pedestrian counterflow through a wide bottleneck in a channel

The pedestrian counterflow through a bottleneck in a channel shows a variety of flow patterns due to self-organization.In order to reveal the underlying mechanism,a cellular automaton model was proposed by incorporating the floor field and the view field which reflects the global information of the studied area and local interactions with others.The presented model can well reproduce typical collective behaviors,such as lane formation.Numerical simulations were performed in the case of a wide bottleneck and typical flow patterns at different density ranges were identified as rarefied flow,laminar flow,interrupted bidirectional flow,oscillatory flow,intermittent flow,and choked flow.The effects of several parameters,such as the size of view field and the width of opening,on the bottleneck flow are also analyzed in detail.The view field plays a vital role in reproducing self-organized phenomena of pedestrian.Numerical results showed that the presented model can capture key characteristics of bottleneck flows.     

Belowground feedbacks as drivers of spatial self-organization and community assembly

Vegetation patterning in water-limited and other resource-limited ecosystems highlights spatial self-organization processes as potentially key drivers of community assembly. These processes provide insight into predictable landscape-level relationships between organisms and their abiotic environment in the form of regular and irregular patterns of biota and resources. However, two aspects have largely been overlooked; the roles played by plant – soil-biota feedbacks and allelopathy in spatial self-organization, and their potential contribution, along with plant-resource feedbacks, to community assembly through spatial self-organization. Here, we expand the drivers of spatial self-organization from a focus on plant-resource feedbacks to include plant – soil-biota feedbacks and allelopathy, and integrate concepts of nonlinear physics and community ecology to generate a new hypothesis. According to this hypothesis, below-ground processes can affect community assemblages through two types of spatial self-organization, global and local. The former occurs simultaneously across whole ecosystems, leading to self-organized patterns of biota, allelochemicals and resources, and niche partitioning. The latter occurs locally in ecotones, and determines ecotone structure and motion, invasion dynamics, and species coexistence. Studies of the two forms of spatial self-organization are important for understanding the organization of plant communities in drier climates which are likely to involve spatial patterning or re-patterning. Such studies are also important for developing new practices of ecosystem management, based on local manipulations at ecotones, to slow invasion dynamics or induce transitions from transitive to intransitive networks of interspecific interactions which increase species diversity.     

On the Nature of Functional Differentiation: The Role of Self-Organization with Constraints

The focus of this article is the self-organization of neural systems under constraints. In 2016, we proposed a theory for self-organization with constraints to clarify the neural mechanism of functional differentiation. As a typical application of the theory, we developed evolutionary reservoir computers that exhibit functional differentiation of neurons. Regarding the self-organized structure of neural systems, Warren McCulloch described the neural networks of the brain as being “heterarchical”, rather than hierarchical, in structure. Unlike the fixed boundary conditions in conventional self-organization theory, where stationary phenomena are the target for study, the neural networks of the brain change their functional structure via synaptic learning and neural differentiation to exhibit specific functions, thereby adapting to nonstationary environmental changes. Thus, the neural network structure is altered dynamically among possible network structures. We refer to such changes as a dynamic heterarchy. Through the dynamic changes of the network structure under constraints, such as physical, chemical, and informational factors, which act on the whole system, neural systems realize functional differentiation or functional parcellation. Based on the computation results of our model for functional differentiation, we propose hypotheses on the neuronal mechanism of functional differentiation. Finally, using the Kolmogorov–Arnold–Sprecher superposition theorem, which can be realized by a layered deep neural network, we propose a possible scenario of functional (including cell) differentiation.     

Phenomenological model of nonequilibrium solidification

The maximum entropy production principle is used as a foundation for the nonequilibrium solidification theory. Based on this principle, a new simple model of dendrite solidification is proposed. The model predicts the explicit dependency of a dendrite’s rate and tip size on supercooling. The obtained results are devoid of the contradictions of the previous models and show quantitative agreement with the recent experimental data for the SCN dendrite.     

Self-organized structures in a superorganism: do ants “behave” like molecules?

While the striking structures (e.g. nest architecture, trail networks) of insect societies may seem familiar to many of us, the understanding of pattern formation still constitutes a challenging problem. Over the last two decades, self-organization has dramatically changed our view on how collective decision-making and structures may emerge out of a population of ant workers having each their own individuality as well as a limited access to information. A variety of collective behaviour spontaneously outcome from multiple interactions between nestmates, even when there is no directing influence imposed by an external template, a pacemaker or a leader. By focussing this review on foraging structures, we show that ant societies display some properties which are usually considered in physico-chemical systems, as typical signatures of self-organization. We detail the key role played by feed-back loops, fluctuations, number of interacting units and sensitivity to environmental factors in the emergence of a structured collective behaviour. Nonetheless, going beyond simple analogies with non-living self-organized patterns, we stress on the specificities of social structures made of complex living units of which the biological features have been selected throughout the evolution depending on their adaptive value. In particular, we consider the ability of each ant individual to process information about environmental and social parameters, to accordingly tune its interactions with nestmates and ultimately to determine the final pattern emerging at the collective level. We emphasize on the parsimony and simplicity of behavioural rules at the individual level which allow an efficient processing of information, energy and matter within the whole colony.     

ORDER AND CHAOS IN NATURE-PHENOMENA AT SURFACES

In chemical reaction systems far from thermodynamical equlibrium rate oscillations and chemical wave patterns develop. This paper presents a condensed overview of recent developments in the study of self-organization processes during heterogeneously catalyzed reactions, whereby the main emphasis is focused on low pressure single crystal studies of oscillatory and pattern forming reactions on Pt and Rh surfaces. Chemical wave patterns on a macroscopic scale as well as reaction induced-microscopic roughening and coverage fluctuations in nano-scale systems are discussed.     

Pattern dynamics in cellular perception

By using a giant amoeboid cell of the Physarum plasmodium, changes in the intracellular distribution of chemical components are studied in relation to information processing in cell behavior. Various kinds of metabolites oscillate, and so the protoplasm should be a collection of chemical oscillators. Spatially, characteristic chemical patterns are self-organized for different cell shapes, and hence cell behavior. New phase waves propagate throughout the cell upon local stimulation, their direction being opposite for attraction and repulsion. Locomotion is inhibited when the coherence of the oscillators breaks. Thus, pattern dynamics is correlated with information processing in the amoeboid cell.     

The Markov blanket trick: On the scope of the free energy principle and active inference

The free energy principle (FEP) has been presented as a unified brain theory, as a general principle for the self-organization of biological systems, and most recently as a principle for a theory of every thing. Additionally, active inference has been proposed as the process theory entailed by FEP that is able to model the full range of biological and cognitive events. In this paper, we challenge these two claims. We argue that FEP is not the general principle it is claimed to be, and that active inference is not the all-encompassing process theory it is purported to be either. The core aspects of our argumentation are that (i) FEP is just a way to generalize Bayesian inference to all domains by the use of a Markov blanket formalism, a generalization we call the Markov blanket trick; and that (ii) active inference presupposes successful perception and action instead of explaining them.     

液体基底表面金薄膜中的有序结构和自组装现象

研究了沉积在液体基底（硅油）表面金薄膜中的带状有序结构和自组装现象.实验结果表明：在一定条件下，生长在硅油表面的金薄膜中可形成一种特征的有序结构，它是由近似矩形状的畴块拼接而成的；相邻畴块的长度近似相等，但宽度一般不同，因而具有特征长度为101—102μm数量级的准周期结构.进一步的实验发现：此类带状有序结构是由薄膜中特征内应力所引起的物质相互挤压而形成的.另外，对此类具有近似自由支撑边界条件的薄膜中的内应力形成机理进行了研究. 关键词： 薄膜 有序结构 内应力 自组装     

Epitaxial self-organization: from surfaces to magnetic materials

Self-organization of magnetic materials is an emerging and active field. An overview of the use of self-organization for magnetic purposes is given, with a view to illustrate aspects that cannot be covered by lithography. A first set of issues concerns the quantitative study of low-dimensional magnetic phenomena (1D and 0D). Such effects also occur in microstructured and lithographically-patterned materials but cannot be studied in these because of the complexity of such materials. This includes magnetic ordering, magnetic anisotropy and superparamagnetism. A second set of issues concerns the possibility to directly use self-organization in devices. Two sets of examples are given: first, how superparamagnetism can be fought by fabricating thick self-organized structures, and second, what new or improved functionalities can be expected from self-organized magnetic systems, like the tailoring of magnetic anisotropy or controlled dispersion of properties. To cite this article: O. Fruchart, C. R. Physique 6 (2005).     

Dynamic synchronization and chaos in an associative neural network with multiple active memories

Associative memory dynamics in neural networks are generally based on attractors. Retrieval based on fixed-point attractors works if only one memory pattern is retrieved at the time, but cannot enable the simultaneous retrieval of more than one pattern. Stable phase-locking of periodic oscillations or limit cycle attractors leads to incorrect feature bindings if the simultaneously retrieved patterns share some of their features. We investigate retrieval dynamics of multiple active patterns in a network of chaotic model neurons. Several memory patterns are kept simultaneously active and separated from each other by a dynamic itinerant synchronization between neurons. Neurons representing shared features alternate their synchronization between patterns, thus multiplexing their binding relationships. Our model includes a mechanism for self-organized readout or decoding of memory pattern coherence in terms of short-term potentiation and short-term depression of synaptic weights.     

Thermodynamics of natural selection

It is shown that biological-natural-selection-like behavior can occur, as a general type of time evolution, in a statistical system where detailed balance is violated owing to the presence of metastable energy states. A model of a non-equilibrium phase transition corresponding to the spontaneous origin of self-reproduction in the system is suggested. After a phase transition, the system passes from one quasistationary distribution of self-reproducing subsystems to another, with an increase in the total organization, as long as the growth of the energy flow through the system or a reduction of energy dissipation in the system is possible. The entropy production is calculated for this process in terms of selective values of Eigen's theory for self-organization in autocatalytic systems. Correspondence of the extremal principle of Eigen's theory with the criterion of evolution in Prigogine's thermodynamics is established.     

Onset of self-organized critical state in a one-dimensional multijunction SQUID as a result of random arrangement of junctions

The critical state of a one-dimensional multijunction SQUID with randomly distributed junctions exposed to a slowly varying magnetic field is studied. It is shown that a small scatter of interjunction distances is sufficient for the critical state of the system to become self-organized. A simplified and basically new model is proposed for studying the self-organization in a system where this phenomenon occurs in a fully deterministic situation.