Self-organization Phenomena Research Articles

Morphology and spatial distribution of ordered domains in GaInP/GaAs(001) according to transmission electron microscopy

The structure of epitaxial films of the GaInP solid solution, in which ordering occurs, was studied using transmission electron microscopy. The films were grown by metalorganic vapor phase epitaxy on GaAs (001) substrates near the half-composition point. During the study, dark-field images obtained using superstructure reflections for cross-sectional and plan-view specimens of films were analyzed. The morphology and relative spatial arrangement of ordered domains have been determined. The phenomenon of spontaneous self-organization of regions with CuPt–B+ and CuPt–B– ordering near the surface was discovered, while in the bulk of the film the domains are uniformly located and mutually overlap each other. The effect of spatial separation of domains is associated with the lattice relaxation, leading to a change in the surface topology.

Metastable states in the Ising model with Glauber-Kawasaki competing dynamics.

Metastable states are identified in the Ising model with competition between the Glauber and Kawasaki dynamics. The model of interaction between magnetic moments was implemented on a network where the degree distribution follows a power law of the form P(k)∼k^{-α}. The evolution toward the stationary state occurred through the competition between two dynamics, driving the system out of equilibrium. In this competition, with probability q, the system was simulated in contact with a heat bath at temperature T by the Glauber dynamics, while with probability 1-q, the system experienced an external energy influx governed by the Kawasaki dynamics. The phase diagrams of T as a function of q were obtained, which are dependent on the initial state of the system, and exhibit first- and second-order phase transitions. In all diagrams, for intermediate values of T, the phenomenon of self-organization between the ordered phases was observed. In the regions of second-order phase transitions, we obtained the critical exponents of the order parameter β, susceptibility γ, and correlation length ν. Furthermore, in the regions of first-order phase transitions, we have demonstrated the instability due to transitions between ordered phases through hysteresislike curves of the order parameter, in addition to the existence of absorbing states. We also estimated the value of tricritical points when the discontinuity in the order parameter in the phase transitions was no longer observed.

An extended cellular automation model for bicycles with group and retrograde behaviors at signalized intersections

The rise of shared bicycles has increased the demand for group riding, integrating bicycles into social groups. Additionally, retrograde riding, where cyclists travel against the designated direction, is a common behavior observed in bicycle flows. The interaction and self-organization phenomenon of group and retrograde behaviors are complex, significantly impacting traffic efficiency. This paper develops a two-dimensional Extended Moore Neighborhood and constructs state-updating rules for regular riding, group riding and retrograde riding. Each rule comprises a psychological decision layer and a physical execution layer, forming a cellular automaton model for group and retrograde bicycles. Field experiments are conducted to calibrate the model parameters and verify the behavioral characteristics. Finally, we execute numerical simulations at a signalized intersection to explore the coupling effects of group and retrograde behaviors on self-organization within the bicycle flow and the traffic capacity. The results indicate that group behavior increases queue length while reducing start wave speed and expansion degree. Retrograde behavior intensifies the negative effects on bicycle flow. These findings provide insights for managing both forward and retrograde bicycle flows.

3D Puzzle at the Nanoscale-How do RNA Viruses Self-Assemble their Capsids into Perfectly Ordered Structures.

The phenomenon of RNA virus self-organization, first observed in the mid-20th century in tobacco mosaic virus, is the subject of extensive research. Efforts to comprehend this process intensify due to its potential for producing vaccines or antiviral compounds as well as nanocarriers and nanotemplates. However, direct observation of the self-assembly is hindered by its prevalence within infected host cells. One of the approaches involves in vitro and in silico research using model viruses featuring a ssRNA(+) genome enclosed within a capsid made up of a single type protein. While various pathways are proposed based on these studies, their relevance in vivo remains uncertain. On the other hand, the development of advanced microscopic methods provide insights into the events within living cells, where following viral infection, specialized compartments form to facilitate the creation of nascent virions. Intriguingly, a growing body of evidence indicates that the primary function of packaging signals in viral RNA is to effectively initiate the virion self-assembly. This is in contrast to earlier opinions suggesting a role in marking RNA for encapsidation. Another noteworthy observation is that many viruses undergo self-assembly within membraneless liquid organelles, which are specifically induced by viral proteins.

On Transducing Properties of Kombucha-Proteinoid Complexes.

We investigate the information processing capacities of kombucha-proteinoid proto-brains, focusing on the transducing properties through accommodation spiking, tonic bursting spiking, and optical and acoustic stimulation. We explore self-organization, adaptability, and emergent phenomena in this unconventional proto-architecture. By constructing kombucha-proteinoid networks exposed to diverse audio stimuli, we analyze nonlinear dynamics using time series analysis. Assessing information representation in the presence of extreme noise, we examine the system's resilience. Our results illustrate intricate pathways resulting from the interplay between the synthetic biological substrate and bio-inspired stimulation. The kombucha-proteinoid proto-brains consistently map complex stimuli to distinct activation levels, showcasing their adaptability and potential for information processing without the need for external shaping circuits.

Lineages of Fractal Genera Comprise the 88-Million-Year Steel Evolutionary Spine of the Ecosphere.

Fractal evolution is apparently effective in selectively preserving environmentally resilient traits for more than 80 million years in Streptotrichaceae (Bryophyta). An analysis simulated maximum destruction of ancestral traits in that large lineage. The constraints enforced were the preservation of newest ancestral traits, and all immediate descendant species obtained different new traits. Maximum character state changes in ancestral traits were 16 percent of all possible traits in any one sub-lineage, or 73 percent total of the entire lineage. Results showed, however, that only four ancestral traits were permanently eliminated in any one lineage or sub-lineage. A lineage maintains maximum biodiversity of temporally and regionally survival-effective traits at minimum expense to resilience across a geologic time of 88 million years for the group studied. Similar processes generating an extant punctuated equilibrium as bursts of about four descendants per genus and one genus per 1-2 epochs are possible in other living groups given similar emergent processes. The mechanism is considered complexity-related, the lineage being a self-organized emergent phenomenon strongly maintained in the ecosphere by natural selection on fractal genera.

From Malthusian stagnation to modern economic growth: a swarm-intelligence perspective

The correlation between decentralized decision-making and swarm intelligence has emerged as a significant subject within self-organization phenomena. Here, we demonstrate that, if an exponential probability distribution of income emerges in a decentralized economic system, then the total income of all agents can be represented by an aggregate production function, in which the technology factor precisely aligns with the information content inherent in the event of decentralized decision-making by all agents. In particular, for sufficiently large population sizes, the emergence of this technology factor enables the income per capita to increase with the population size, akin to a manifestation of swarm intelligence. More importantly, we find that an exponential probability distribution of income can be generated within a peer-to-peer economy governed by specific game rules, characterizing a decentralized-decision economic system. Building upon this discovery, we propose a swarm-intelligence explanation to elucidate the transition from thousands of years of Malthusian stagnation to modern economic growth.

A collision operator for describing dissipation in noncanonical phase space

The phase space of a noncanonical Hamiltonian system is partially inaccessible due to dynamical constraints (Casimir invariants) arising from the kernel of the Poisson tensor. When an ensemble of noncanonical Hamiltonian systems is allowed to interact, dissipative processes eventually break the phase space constraints, resulting in a thermodynamic equilibrium described by a Maxwell–Boltzmann distribution. However, the time scale required to reach Maxwell–Boltzmann statistics is often much longer than the time scale over which a given system achieves a state of thermal equilibrium. Examples include diffusion in rigid mechanical systems, as well as collisionless relaxation in magnetized plasmas and stellar systems, where the interval between binary Coulomb or gravitational collisions can be longer than the time scale over which stable structures are self-organized. Here, we focus on self-organizing phenomena over spacetime scales such that particle interactions respect the noncanonical Hamiltonian structure, but yet act to create a state of thermodynamic equilibrium. We derive a collision operator for general noncanonical Hamiltonian systems, applicable to fast, localized interactions. This collision operator depends on the interaction exchanged by colliding particles and on the Poisson tensor encoding the noncanonical phase space structure, is consistent with entropy growth and conservation of particle number and energy, preserves the interior Casimir invariants, reduces to the Landau collision operator in the limit of grazing binary Coulomb collisions in canonical phase space, and exhibits a metriplectic structure. We further show how thermodynamic equilibria depart from Maxwell–Boltzmann statistics due to the noncanonical phase space structure, and how self-organization and collisionless relaxation in magnetized plasmas and stellar systems can be described through the derived collision operator.

Mesoscopic transport in KSTAR plasmas: avalanches and the E × B staircase

Abstract The self-organization is one of the most interesting phenomena in the non-equilibrium complex system, generating ordered structures of different sizes and durations. In tokamak plasmas, various self-organized phenomena have been reported, and two of them, coexisting in the near-marginal (interaction dominant) regime, are avalanches and the E × B staircase. Avalanches mean the ballistic flux propagation event through successive interactions as it propagates, and the E × B staircase means a globally ordered pattern of self-organized zonal flow layers. Various models have been suggested to understand their characteristics and relation, but experimental researches have been mostly limited to the demonstration of their existence. Here we report detailed analyses of their dynamics and statistics and explain their relation. Avalanches influence the formation and the width distribution of the E × B staircase, while the E × B staircase confines avalanches within its mesoscopic width until dissipated or penetrated. Our perspective to consider them the self-organization phenomena enhances our fundamental understanding of them as well as links our findings with the self-organization of mesoscopic structures in various complex systems.

Collision-aware deflection model for boundary-constrained intersecting pedestrian streams

We propose a new model of boundary-constrained intersecting pedestrian flow based on the collision-free velocity model, named the collision-aware deflection model (CADM). The movement of pedestrians in the new model depends on the positions and velocities of other pedestrians ahead. A pedestrian walks in the desired direction at a free speed until an obstacle appears in the desired direction. When there is an obstacle in the desired direction, pedestrians tend to choose the direction with the smallest deflection angle. When the decision of a pedestrian conflicts with the movement of the nearest neighbor in front, the pedestrian stops moving. Comparing CADM with other models, the evacuation time of CADM during the simulation is very close to the time in the experiment. CADM also successfully reproduced the stripe phenomenon in boundary-constrained intersecting pedestrian streams, which was difficult to accomplish with the compared model. CADM also inherits several advantages of the original model, in that it can reproduce the corresponding self-organization phenomena in straight corridors and bottlenecks.

Self-organising phenomena in 2D complex plasma simulations withnon-mono dispersed dust size distributions

Complex plasma with a variety of continuous and discrete dust grain size distributions are simulated in 2D with molecular dynamics simulations with radial geometry to determine differences in self-organizing phenomena to more realistically represent the actual in situ variations in dust-size. The standard deviation of particle size σ(a) strongly correlates with phase separation and coupling parameter Γ for all distribution types. We observe local differences in bond order parameters and Voronoi diagrams for different size distributions, and our results suggest that phase transition is affected by continuous size distributions, particularly in the binary distribution case. Simulations with discrete size result in artifacts and discontinuities that are not found in the continuous distributions. The use of continuous distributions is observed to be beneficial both for more realistic approximation of complex plasma experiments and to study systems of strongly coupled particles in general.

Spatial Heterogeneity Impacts of Urbanisation on Open Space Fragmentation in Hong Kong’s Built-Up Area

Rapid urbanisation has generated numerous environmental consequences, particularly regarding open space fragmentation. Open space fragmentation is the transformation of open space from a state of homogeneity, integration, and continuity to a state of heterogeneity, division, and incoherence. Nevertheless, one main obstacle to understanding this issue is how to address the spatial heterogeneity of the impact of urbanisation on open space fragmentation. Thus, this paper provides a comprehensive framework for the mechanistic associations between open space fragmentation and urbanisation in Hong Kong’s built-up area. The results illustrate that both open space fragmentation index and urbanisation index values are noticeably higher in dense urban areas. Land urbanisation, represented by the percentage of construction land in total land, has the highest explanatory power for spatial differentiation in open space fragmentation, followed by social and population urbanisation factors. Furthermore, the relational interrelations of open space fragmentation drivers are the bivariate and nonlinear enhancement interactions. Social urbanisation and land urbanisation have the strongest bivariate enhancement interaction for the use fragmentation form and the largest nonlinear enhancement interaction for the internal fragmentation form. Based on initial urban planning, open space fragmentation is an adaptation outcome of population, land, and social urbanisation factors, and this self-organisation phenomenon has been further emphasised in the historical process. These insights significantly enrich our understanding of how urbanisation affects open space fragmentation and provide valuable guidance for better open space strategies.

Noise-induced excitation wave and its size distribution in coupled FitzHugh-Nagumo equationson a square lattice.

There are various research topics such as stochastic resonance, coherent resonance, and neuroavalanche in excitable systems under external noises. We perform numerical simulation of coupled noisy FitzHugh-Nagumo equationson the square lattice. Excitation waves are generated most efficiently at an intermediate noise strength. The cluster size distributions obey a power-law-like distribution at a certain parameter range. However, we consider that this is not a self-organized critical phenomenon, partly because the exponent of the power law is not constant. We have studied the propagation of excitation waves in the coupled noisy FitzHugh-Nagumo equationswith a one-dimensional pacemaker region and found that there is a phase-transition-like phenomenon from the short-range propagation to the whole-system propagation by changing the noise strength T. The power-law distribution is observed most clearly near the phase transition of the propagation of excitation waves in the coupled noisy FitzHugh-Nagumo equationswithout the one-dimensional pacemaker.

N-Alkylisoquinolinium bromides and α,ω-alkanediols: Eutectic systems with co-crystal formation

This research focuses on ionic liquids (ILs), specifically N-alkylisoquinolinium bromides with various chain lengths: octyl, decyl, dodecyl, and hexadecyl. The study covers the synthesis and thermophysical characterisation of these compounds, as well as crystal structure determination for all excluding N-decylisoquinolinium bromide ([i-QuinC10][Br]). The obtained thermophysical parameters were compared with the literature data and also within the extended homologous series.The solid–liquid phase equilibria (SLE) in mixtures of ILs with certain α,ω-alkanediols (1,6-hexanediol, 1,8-octanediol, 1,10-decanediol, 1,12-dodecanediol) were investigated. As a result of SLE studies, eutectic mixtures capable of acting as eutectic phase-change materials - ePCMs - were determined. Additionally, a self-organization phenomenon was observed between specific pairs, leading to the formation of co-crystals (solid-complex phase). All binary mixtures with [i-QuinC8][Br] formed a simple eutectic system, while in the case of [i-QuinC10][Br], the formation of a non-congruent melting compound was observed in the systems with 1,8-octanediol and 1,10-decanediol. Among the systems with [i-QuinC12][Br], congruent melting compounds were observed for mixtures with 1,8-octanediol, 1,10-decanediol and 1,12-dodecanediol, while a simple eutectic was recorded for 1,6-hexanediol. IL [i-QuinC16][Br] co-crystalised only with 1,12-dodecanediol, while with other diols formed simple eutectic systems. Calorimetric analysis (DSC) and crystal structure determination (X-ray diffraction) were used to characterize the obtained supramolecular compounds.As a result, a series of ePCMs with melting points ranging from 295 K to 343 K are presented, with the {[i-QuinC12][Br] + 1,10-decanediol} system showing the highest enthalpy of melting (173.5 J·g−1). The found features and correlations between structure and properties imply the necessity for additional investigation, indicating the potential for a new generation of compounds with customizable physicochemical properties.

Is modelocking the most successful self-organized phenomenon?

Passive modelocking is the spontaneous self-organization of all light within a laser cavity that is initially disordered into a short pulse. The tutorial begins with a brief history, introduces the fundamental principles, and discusses modern modelocked lasers, and open questions.

Gel transition of active triblock copolymers

The self-propulsion of active matter leads to many non-equilibrium self-organization phenomena, and the conformational freedom of polymer chains can produce unique equilibrium self-assembly behaviors, which stimulates cross-disciplinary research between active matter and polymer physics. In this work, we use molecular dynamics simulations to investigate the modulation of self-propulsion activity on the gel transition of ABA triblock copolymers. The research results indicate that under different active forces and attractive strengths, the gel states formed by ABA copolymers can be divided into three types: stable polymer gels with stable percolation paths and uniform spatial distribution, dynamic polymer gels with constantly changing percolation path and strand conformation, and collapsed polymer gels aggregating into large percolating clusters. The spatial uniformity of active gels is related not only to the concentration fluctuation during the formation of the network, but also to the inconsistent movement of the network chains caused by the activity, which is manifested in the rotation of crosslinking points in the flexible system and the directional movement of the bundles along their contour directions in the semi-flexible and rigid systems. In terms of topological conformation of polymer networks, when the attractive strength between A blocks is strong, the proportion of loop increases with the active force increasing. When attractive strength is weak, inter- and intra-chain binding are unstable, and the conformation is easily changed by the activity drive, noise and other chain collisions, so the proportion of loop decreases with the active force increasing. The branching number of crosslinking points varies with active force, which is not only affected by the attraction strength, but also related to the rigidity of the network chain. Generally, the branch number of crosslinking points in semi-flexible networks is larger than that in flexible and rigid networks. In addition, the directional motion of active polymers induces anomalous diffusion in stable polymer gels. This study contributes to the understanding of the collective behavior of active polymers and serves as a guide for designing and implementing active polymeric materials.

The down to earth pole of understanding the complexity of life

This paper argues that the down-to-earth pole of the understanding of the complexity of life is made up by a threefold factor, namely the interplay of geology, microbiology, and evolution. It is such intertwining that provides the ground for life as we know it. This paper claims that the origins of life are contemporarily the origin of the biosphere as a living system. Dualism must be overcome at all costs; hence, there is not physics, say, geology on the one hand, and biology on the other hand. On the contrary, both make up a highly integrated complex system. The approach suggested in this paper conveys a phenomenological endeavor as a non-substantive comprehension of life and the living systems. Life, it can be safely said, is non-causal, and a self-organizing and autopoietic phenomenon. An evolutionary view of life implies hence after an open-ended understanding. At the end the paper explores the consequences of such a take.

Влияние тренинга профессионального самоопределения на ценностно-мотивационную направленность подростков

A relevant problem of pedagogical psychology is to provide effective career counseling services that would aid students to make a conscious career decision. Psychological characteristics of optants (high school students who choose a profession) in some sense imbricate with such a personal quality as subjectivity, which is manifested in adolescents’ values and motivation. One of the ways to help students choose a profession can be career guidance courses and trainings aimed at aiding students to make a conscious career decision. The goal of the research is to justify the use of such a training in order to ease the difficulties for adolescents to choose a profession and develop values and increase motivation, and as a consequence, to develop subjectivity. The hypothesis is as follows: career counseling eases the difficulties for adolescents to choose a profession and contributes to the development of values and boosts motivation. Study participants: 9th grade students (N = 54) of the Samara secondary school, who were divided into two groups: experimental and control. The participants of the experimental group (n = 25; M = 14.8; SD = 0.41; 40% of women) had a career counseling session once a week for 15 weeks. The control group (n = 29; M = 14.9; SD = 0.36; 52% of women) studied according to a conventional curriculum. Methods (tools): The diagnosis was performed with a time interval of 19 weeks. A projective technique for assessing the phases of the subjectivity formation in students (E. S. Volkova, A. V. Kaptsov) was used to assess the real, possible and ideal phases of the subjectivity formation and their changes after the training. A questionnaire on the difficulties of making a decision about choosing a profession (CDDQ, I. Gati, M. Kraus and S. Osipov, adapted by E. S. Volkova) was used to determine the problems of the ninth-graders when choosing a profession. Results: The research has demonstrated the positive effect of the training on easing the difficulties to choose a profession, as well as on the development of the motivational component of subjectivity; the training has increased the value of the educational activity expressed by the growth of the indicator of the ideal phase of the “master” stage of subjectivity in the experimental group. In ideal and possible phases of subjectivity formation, the experimental group has demonstrated the phenomenon of self-organization in terms of the formation of attractors, as a result of which the phases of subjectivity formation take place. The main conclusions. Career counseling eases the difficulties for high school students to choose a profession; it promotes the development of values and boosts motivation, and as a result, it helps to form the subjectivity in students; additionally, it promotes the phenomenon of self-organization in an ideal phase of subjectivity formation, which may potentially affect the real phase of subjectivity formation in the future.

Simulation of bi-directional pedestrian flow in corridor based on direction fuzzy visual field

Bi-directional pedestrian flow in corridors is a complex dynamic system due to the diversity in pedestrian psychological characteristics. Incorporating individual differences of pedestrians is vital for improving pedestrian flow models. However, due to the inherent complexity and variability of pedestrian movement, model parameter calibration remains challenging. Controlled experiments are needed to collect empirical pedestrian movement data under different environments. This enriches the database on pedestrian movement patterns and provides necessary support for improving pedestrian flow models. To address this issue, we conducted controlled experiments to quantify pedestrian heterogeneity by defining the direction of fuzzy visual field (DFVF). The DFVF incorporates various static and dynamic pedestrian factors. We used it to modify the traditional cellular automata model. This improved model simulates bi-directional pedestrian movements in the corridors, reproduces density-speed and density-volume relationships, and reveals self-organization phenomena. Furthermore, an analysis was conducted to examine the impacts of pedestrian density and facility spatial layout on evacuation time. Pedestrian interactions were also studied to uncover fundamental bi-directional flow properties. As pedestrian density increased, the evacuation time showed an exponential upward trend. Corridor length significantly impacts evacuation time, while increasing corridor width helps control it. As crowd density increases, pedestrian flows exhibit three distinct steady states: the strolling flow at low densities, directional separated flows at medium densities, and dynamic multi-lane flows at high densities. In summary, the modified cellular automata model successfully incorporates pedestrian heterogeneity and reveals intrinsic bi-directional pedestrian flow patterns. This study provides valuable insights for pedestrian facility design and optimizing pedestrian flow organization.

Pedestrian lane formation with following–overtaking model and measurement of system order

Pedestrian self-organizing movement plays a significant role in evacuation studies and architectural design. Lane formation, a typical self-organizing phenomenon, helps pedestrian system to become more orderly, the majority of following behavior model and overtaking behavior model are imprecise and unrealistic compared with pedestrian movement in the real world. In this study, a pedestrian dynamic model considering detailed modelling of the following behavior and overtaking behavior is constructed, and a method of measuring the lane formation and pedestrian system order based on information entropy is proposed. Simulation and analysis demonstrate that the following and avoidance behaviors are important factors of lane formation. A high tendency of following results in good lane formation. Both non-selective following behavior and aggressive overtaking behavior cause the system order to decrease. The most orderly following strategy for a pedestrian is to overtake the former pedestrian whose speed is lower than approximately 70% of his own. The influence of the obstacle layout on pedestrian lane and egress efficiency is also studied with this model. The presence of a small obstacle does not obstruct the walking of pedestrians; in contrast, it may help to improve the egress efficiency by guiding the pedestrian flow and mitigating the reduction of pedestrian system orderliness.