Self-organization Phenomena Research Articles

Exploring crowd persistent dynamism from pedestrian crossing perspective: An empirical study

Crowd studies have gained increasing relevance due to the recurring incidents of crowd crush accidents. In addressing the issue of the crowd's persistent dynamism, this paper explored the macroscopic and microscopic features of pedestrians crossing in static and dynamic contexts, employing a series of systematic experiments. Firstly, empirical evidence has confirmed the existence of crowd’s persistent dynamism. Subsequently, the research delves into two aspects, qualitative and quantitative, to address the following questions: (1) Cross pedestrians tend to avoid high-density areas when crossing static crowds and particularly evade pedestrians in front to avoid deceleration, thus inducing the formation of cross-channels, a self-organization phenomenon. (2) In dynamic crowds, when pedestrian suffers spatial constrained, two patterns emerge: decelerate or detour. Research results indicate the differences in pedestrian crossing behaviors between static and dynamic crowds, such as the formation of crossing channels, backward detours, and spiral turning. However, the strategy of pedestrian crossing remains consistent: utilizing detours to overcome spatial constraints. Finally, the empirical results of this study address the final question: pedestrians detouring causes crowds’ persistent collective dynamism. These findings contribute to an enhanced understanding of pedestrian dynamics in extreme conditions and provide empirical support for research on individual movement patterns and crowd behavior prediction.

General multi-switching synchronization using sliding mode control

Chaotic synchronization is a self-organizing phenomenon that occurs when two or more chaotic systems become synchronized. So far for multi-switching synchronization (MSS), only a homogeneous kind of switches have been discussed. This paper presents a generalized approach to MSS in which all possible heterogeneous combinations are presented. This generalization of MSS allows for greater flexibility and robustness in the MSS process. The switches are designed based on the order of the drive/response subsystems. The author also uses sliding mode control to achieve synchronization among various heterogeneous combinations during MSS. To demonstrate the effectiveness of the proposed approach, the author uses the Lorenz hyper chaotic system (LHCS) and the Chen hyper chaotic system (CHCS). The four different heterogeneous types of switches are designed and demonstrated for the chosen hyper chaotic systems. Mathematica is used for all numerical simulations. The results show that the proposed approach can achieve synchronization between two hyper chaotic systems with high accuracy. The author also shows that the proposed approach is robust to change in the parameters of the systems. This paper provides a new approach to chaotic synchronization that has potential applications in a variety of fields. The results presented in this paper are an important step towards the development of more robust and flexible synchronization schemes.

Signatures of the Self-organized Criticality Phenomenon in Precursors of Gamma-Ray Bursts

Precursors provide important clues to the nature of gamma-ray burst (GRB) central engines and can be used to contain GRB physical processes. In this Letter, we study the self-organized criticality in precursors of long GRBs in the third Swift/Burst Alert Telescope catalog. We investigate the differential and cumulative size distributions of 100 precursors, including peak flux, duration, rise time, decay time, and quiescent time with the Markov Chain Monte Carlo technique. It is found that all of the distributions can be well described by power-law models and understood within the physical framework of a self-organized criticality system. In addition, we inspect the cumulative distribution functions of the size differences with a q-Gaussian function. The scale-invariance structures of precursors further strengthen our findings. Particularly, similar analyses are made in 127 main bursts. The results show that both precursors and main bursts can be attributed to a self-organized criticality system with the spatial dimension S = 3 and driven by a similar magnetically dominated process.

Vital Heat and the Organized Body: Burke, Blake, The French Revolution and The [First] Book of Urizen

ABSTRACT During the French Revolution, it had become apparent that the conventional metaphor of the body politic, framed around a stable hierarchical relationship between the monarchical head and the subservient body, was no longer fit for such a purpose. Indeed, in the late eighteenth century, medical understandings of the body were far more sophisticated than ever before. This article puts Blake in intimate dialogue with Burke, Sieyès, and other revolutionary and reactionary writers who evocatively updated the body politic metaphor to describe a radically changing political landscape. Reading The [First] Book of Urizen against Blake’s neglected, unpublished The French Revolution, this article demonstrates how Blake’s biological myth, though obscure, was deeply embedded in contemporary revolutionary discourse. In doing so, this article contests assumptions in recent Blake criticism that Blake found images of freedom in the organic phenomenon of self-organization (a logic of form taken up in Burkean conservatism), emphasizing instead Blake’s indebtedness to the Hunterian doctrine of vital heat.

Winner-loser effects improve social network efficiency between competitors with equal resource holding power

Animal societies are structured of dominance hierarchy (DH). DH can be viewed as networks and analyzed by graph theory. We study the impact of state-dependent feedback (winner-loser effect) on the emergence of local dominance structures after pairwise contests between initially equal-ranking members (equal resource-holding-power, RHP) of small and large social groups. We simulated pairwise agonistic contests between individuals with and without a priori higher RHP by Monte-Carlo-method. Random pairwise contests between equal-ranking competitors result in random dominance structures (‘Null variant’) that are low in transitive triads and high in pass along triads; whereas state-dependent feedback (‘Winner-loser variant’) yields centralized ‘star’ structured DH that evolve from competitors with initially equal RHP and correspond to hierarchies that evolve from keystone individuals. Monte-Carlo simulated DH following state-dependent feedback show motif patterns very similar to those of a variety of natural DH, suggesting that state-dependent feedback plays a pivotal role in robust self-organizing phenomena that transcend the specifics of the individual. Self-organization based on state-dependent feedback leads to social structures that correspond to those resulting from pre-existing keystone individuals. As the efficiency of centralized social networks benefits both, the individual and the group, centralization of social networks appears to be an important evolutionary goal.

The GGDEF protein Dgc2 suppresses both motility and biofilm formation in the filamentous cyanobacterium Leptolyngbya boryana.

Colony pattern formations of bacteria with motility manifest complicated morphological self-organization phenomena. Leptolyngbya boryana is a filamentous cyanobacterium, which has been used as a genetic model organism for studying metabolism including photosynthesis and nitrogen fixation. A widely used type strain [wild type (WT) in this article] of this species has not been reported to show any motile activity. However, we isolated a spontaneous mutant strain that shows active motility (gliding activity) to give rise to complicated colony patterns, including comet-like wandering clusters and disk-like rotating vortices on solid media. Whole-genome resequencing identified multiple mutations in the genome of the mutant strain. We confirmed that inactivation of the candidate gene dgc2 (LBDG_02920) in the WT background was sufficient to give rise to motility and morphologically complex colony patterns. This gene encodes a protein containing the GGDEF motif which is conserved at the catalytic domain of diguanylate cyclase (DGC). Although DGC has been reported to be involved in biofilm formation, the dgc2 mutant significantly facilitated biofilm formation, suggesting a role for the dgc2 gene in suppressing both gliding motility and biofilm formation. Thus, Leptolyngbya is expected to be an excellent genetic model for studying dynamic colony pattern formation and to provide novel insights into the role of DGC family genes in biofilm formation. IMPORTANCE Self-propelled bacteria often exhibit complex collective behaviors, such as formation of dense-moving clusters, which are exemplified by wandering comet-like and rotating disk-like colonies; however, the molecular details of how these structures are formed are scant. We found that a strain of the filamentous cyanobacterium Leptolyngbya deficient in the GGDEF protein gene dgc2 elicits motility and complex and dynamic colony pattern formation, including comet-like and disk-like clusters. Although c-di-GMP has been reported to activate biofilm formation in some bacterial species, disruption of dgc2 unexpectedly enhanced it, suggesting a novel role for this GGDEF protein for inhibiting both colony pattern formation and biofilm formation.

Modeling the Mutual Anticipation in Human Crowds With Attention Distractions

Human crowds exhibit rich self-organizing behaviors through local interactions. The understanding of interaction mechanisms has important implications for the management of large-scale crowds. Although most vision-based heuristic models are successful, some features such as distracted pedestrians, and empirical phenomena like sudden turns are difficult to be explained. Here, a heuristic interaction model is proposed, which incorporates the extracted laws of pedestrian heterogeneity and mutual anticipation. We argue that pedestrians are heterogeneous in terms of speed and attention (e.g., distracted by cell phones), and have anticipations for other pedestrians’ velocities during the interaction. Numerical simulations indicate that our model realistically simulates the self-organizing phenomenon in the “distraction experiment”, along with related experimental findings. The “freezing-by-heating” phenomenon, as well as interesting phenomena such as “sidewalk shuffling” are successfully predicted, as exhibited in empirical observations. Taken together, our model may serve various potential fields involving the control of traffic flows and navigation of autonomous swarm robots.

Non-Classical Self-Assembly of Anisotropic Magneto-Organosilica Janus Particles Possessing Surfactant Properties and the Field-Triggered Breakdown of Surface Activity and Amphiphilic Properties.

Using colloidal particles as models to understand processes on a smaller scale is a precious approach. Compared to molecules, particles are less defined, but their architecture can be more complex and so is their long-range interaction. One can observe phenomena that are unknown or much more difficult to realize on the molecular level. The current paper focuses on particle-based surfactants and reports on numerous unexpected properties. The main goal is creating an amphiphilic system with responsiveness in surface activity and associated self-organization phenomena depending on applying an external trigger, preferably a physical field. A key step is the creation of a Janus-type particle characterized by two types of dipoles (electric and magnetic) which geometrically stand orthogonal to each other. In a field, one can control which contribution and direction dominate the interparticle interactions. As a result, one can drastically change the system's properties. The features of ferrite-core organosilica-shell particles with grain-like morphology modified by click chemistry are studied in response to spatially isotropic and anisotropic triggers. A highly unusual aggregation-dissolution-reaggregation sequence w as discovered. Using a magnetic field, one can even switch off the amphiphilic properties and use this for the field-triggered breaking of multiphase systems such as emulsions.

The phenomenon of self-organization of the rural population: Principles and prospects of research

The phenomenon defined as self-organization implements its cognitive-analytical function in many disciplines - physics and chemistry, cybernetics and computer science, economics and sociology, psychology and cultural studies. Russian and foreign researchers study forms and practices of self-organization of the rural population and, as a rule, consider them through the factors that affect the pace, forms and quality of social-economic transformations, material appearance and event dynamics of the non-urban living space. The most effective factors that affect the reconstruction of the social space of rural areas and, in general, optimization of the rural world are managerial, social-economic, innovative, demographic and urbanistic, climatic and environmental, and also factors of complementary and intermediate character. The authors systematize the main principles in the study of self-organization practices of the rural population, which are empirically manifested in their regional and subject-activity features (local nature, cultural and ethnographic traditions, changing composition of the local population, their work habits, indicators of professional skills and diligence). All the above historically develops into a kind of genius loci (“spirit of place”, “genius locus”) as densely packed in customs and determining mechanisms for the development of initiatives by subjects of self-organization, who aim at building such institutional mechanisms and practices that cannot but contribute to the transition to a new development trajectory, first of individual segments (households, farmer associations, etc.), and then of all basic elements of rural society, which are embodied in the everyday life of rural ‘localities’.

Self-organizing neural network for reproducing human postural mode alternation through deep reinforcement learning

A self-organized phenomenon in postural coordination is essential for understanding the auto-switching mechanism of in-phase and anti-phase postural coordination modes during standing and related supra-postural activities. Previously, a model-based approach was proposed to reproduce such self-organized phenomenon. However, if we set this problem including the process of how we establish the internal predictive model in our central nervous system, the learning process is critical to be considered for establishing a neural network for managing adaptive postural control. Particularly when body characteristics may change due to growth or aging or are initially unknown for infants, a learning capability can improve the hyper-adaptivity of human motor control for maintaining postural stability and saving energy in daily living. This study attempted to generate a self-organizing neural network that can adaptively coordinate the postural mode without assuming a prior body model regarding body dynamics and kinematics. Postural coordination modes are reproduced in head-target tracking tasks through a deep reinforcement learning algorithm. The transitions between the postural coordination types, i.e. in-phase and anti-phase coordination modes, could be reproduced by changing the task condition of the head tracking target, by changing the frequencies of the moving target. These modes are considered emergent phenomena existing in human head tracking tasks. Various evaluation indices, such as correlation, and relative phase of hip and ankle joint, are analyzed to verify the self-organizing neural network performance to produce the postural coordination transition between the in-phase and anti-phase modes. In addition, after learning, the neural network can also adapt to continuous task condition changes and even to unlearned body mass conditions keeping consistent in-phase and anti-phase mode alternation.

Особенности межмолекулярного взаимодействия в нефтяных дисперсных системах

Oil, gas condensates, oil products present a complex colloidal-dispersed system which often demonstrates the abnormally changing properties when external conditions change. Mixing the petroleum products can be accompanied by a non-linear behavior accompanied by synergistic and antagonistic effects. Understanding of the oil and oil products as oil dispersed systems, the specific features of intermolecular interaction largely clarify their behavior, changes in properties, chemistry and mechanism of reactions occurring in them. Petroleum systems are polydisperse, in which the components can coexist in different aggregate states, and the size of the dispersed phase can vary over a wide range. They consist of diverse compounds that differ in properties, structure, shapes and sizes of molecules. Due to the variety of components that make up oil disperse systems the intermolecular interactions determine such a feature of the behavior of oil systems as the phenomenon of self-organization and structuring, which manifest themselves when external influences change and are sensitive to them. They are characterized by the absence of charge and a minimum of charge-polarization interactions of molecules, and intermolecular interactions are largely determined by the presence of paramagnetic molecules. The uncompensated spin of macromolecular compounds due to the steric obstacles, a homolytic dissociation, and the presence of microelement compounds ensure the paramagnetism of petroleum dispersed systems. This leads to developing the stable associative combinations and the formation of complex structural units capable of redistributing components and layers between phases under the influence of external effects. Comprehensive analysis and unanimity of views on the physical and chemical interactions of the components of oil systems leading to a change in their structure, open up fundamentally new opportunities for intensifying processes in the practice of production, transportation and processing of hydrocarbon raw materials and the use of petroleum products, and also allow predicting the behavior of oil systems in processes which they are participating.

Growth of self-integrated atomic quantum wires and junctions of a Mott semiconductor.

Continued advances in quantum technologies rely on producing nanometer-scale wires. Although several state-of-the-art nanolithographic technologies and bottom-up synthesis processes have been used to engineer these wires, critical challenges remain in growing uniform atomic-scale crystalline wires and constructing their network structures. Here, we discover a simple method to fabricate atomic-scale wires with various arrangements, including stripes, X-junctions, Y-junctions, and nanorings. Single-crystalline atomic-scale wires of a Mott insulator, whose bandgap is comparable to those of wide-gap semiconductors, are spontaneously grown on graphite substrates by pulsed-laser deposition. These wires are one unit cell thick and have an exact width of two and four unit cells (1.4 and 2.8 nm) and lengths up to a few micrometers. We show that the nonequilibrium reaction-diffusion processes may play an essential role in atomic pattern formation. Our findings offer a previously unknown perspective on the nonequilibrium self-organization phenomena on an atomic scale, paving a unique way for the quantum architecture of nano-network.

DigiHive: Artificial Chemistry Environment for Modeling of Self-Organization Phenomena.

The article presents the DigiHive system, an artificial chemistry simulation environment, and the results of preliminary simulation experiments leading toward building a self-replicating system resembling a living cell. The two-dimensional environment is populated by particles that can bond together and form complexes of particles. Some complexes can recognize and change the structures of surrounding complexes, where the functions they perform are encoded in their structure in the form of Prolog-like language expressions. After introducing the DigiHive environment, we present the results of simulations of two fundamental parts of a self-replicating system, the work of a universal constructor and a copying machine, and the growth and division of a cell-like wall. At the end of the article, the limitations and arising difficulties of modeling in the DigiHive environment are presented, along with a discussion of possible future experiments and applications of this type of modeling.

The role of complexity for digital twins of cities.

We argue that theories and methods drawn from complexity science are urgently needed to guide the development and use of digital twins for cities. The theoretical framework from complexity science takes into account both the short-term and the long-term dynamics of cities and their interactions. This is the foundation for a new approach that treats cities not as large machines or logistic systems but as mutually interwoven self-organizing phenomena, which evolve, to an extent, like living systems.

Evidence for the Self-organized Criticality Phenomenon in the Prompt Phase of Short Gamma-Ray Bursts

The prompt phase of gamma-ray bursts (GRBs) contains essential information regarding their physical nature and central engine, which are as yet unknown. In this paper, we investigate the self-organized criticality phenomenon in GRB prompt phases as done in X-ray flares of GRBs. We obtain the differential and cumulative distributions of 243 short GRB pulses, such as peak flux, FWHM, rise time, decay time, and peak time in the fourth BATSE Time-Tagged Event Catalog with the Markov Chain Monte Carlo technique. It is found that these distributions can be well described by power-law models. In particular, comparisons are made with 182 short GRB pulses in the third Swift GRB Catalog from 2004 December to 2019 July. The results are essentially consistent with the BATSE ones. We notice that there is no obvious power-law index evolution across different energy bands for either BATSE or Swift short GRBs. The joint analysis suggests that the GRB prompt phase can be explained by a fractal-diffusive self-organized criticality system with the spatial dimension S = 3 and the classical diffusion β = 1. Our findings show that GRB prompt phases and X-ray flares possess the very same magnetically dominated stochastic process and mechanism.

Machine-guided path sampling to discover mechanisms of molecular self-organization

Molecular self-organization driven by concerted many-body interactions produces the ordered structures that define both inanimate and living matter. Here we present an autonomous path sampling algorithm that integrates deep learning and transition path theory to discover the mechanism of molecular self-organization phenomena. The algorithm uses the outcome of newly initiated trajectories to construct, validate and—if needed—update quantitative mechanistic models. Closing the learning cycle, the models guide the sampling to enhance the sampling of rare assembly events. Symbolic regression condenses the learned mechanism into a human-interpretable form in terms of relevant physical observables. Applied to ion association in solution, gas-hydrate crystal formation, polymer folding and membrane-protein assembly, we capture the many-body solvent motions governing the assembly process, identify the variables of classical nucleation theory, uncover the folding mechanism at different levels of resolution and reveal competing assembly pathways. The mechanistic descriptions are transferable across thermodynamic states and chemical space.

Ethno-cultural Aura of Language Images in the Light of Cognitive Linguopoetics

The nature and essence of the language image are considered from the standpoint of modern cognitive linguopoetics, its differences from the general philological concepts of “image” and “imagery” are shown. According to the authors’ idea, the language image is considered in line with creative discursive activity. It is proved that language images integrating real ideas about the world picture and the author’s emotional attitude to them synergetically create an ethno-cultural aura of a literary text. Discourse, due to the multiplicity of its components, is a speech-thinking platform for forming a language image. The latter is considered by us as a synergetic phenomenon in the aspect of a multichannel derivative stimulus and a self-organizing phenomenon in open systems of linguocreative thinking. The article substantiates that in a literary text a language image is generated not by a real, but by a so-called communicative and aesthetically significant event, i.e. a literary discourse - the denotative aura of language images. The analysis shows that the language image is formed not only by the text itself, but also by various extralinguistic factors (knowledge of the world, opinions, values) that play an important role in understanding, interpreting and perceiving verbal images of a communicative event. Therefore, the work interprets all the main (event and non-event) elements of the text’s discursive situation, forming a complex language image. The extralinguistic factors determining the semantic architectonics of the internal context and actively participating in the formation of the ethno-cultural shell of language images are revealed. Each of these images serves as a shadow cloud of the internal context, an element of the ethno-cultural aura of the speech activity. In contrast to the existing stereotypes, according to which the concept and image are considered products of different mental operations: the first is analytical, and the second is synthetic, the article proves that the genesis of language image is characterized by their fusion. At the initial stage, there is an analytical perception of the signs of a denotative situation, and at the final stage, their synthesis. Ultimately, the genetic connection of such phenomena as literary text, discourse and concept generates the ethno-cultural aura of a pictorial-speech work.

Raman laser induced self-organization with topology in a dipolar condensate.

We investigate the ground states of a dipolar Bose-Einstein condensate (BEC) subject to Raman laser induced spin-orbit coupling with mean-field theory. Owing to the interplay between spin-orbit coupling and atom-atom interactions, the BEC presents remarkable self-organization behavior and thus hosts various exotic phases including vortex with discrete rotational symmetry, stripe with spin helix, and chiral lattices with C4 symmetry. The peculiar chiral self-organized array of square lattice, which spontaneously breaks both U(1) and rotational symmetries, is observed when the contact interaction is considerable in comparison with the spin-orbit coupling. Moreover, we show that the Raman-induced spin-orbit coupling plays a crucial role in forming rich topological spin textures of the chiral self-organized phases by introducing a channel for atoms to turn on spin flipping between two components. The self-organization phenomena predicted here feature topology owing to spin-orbit coupling. In addition, we find long-lived metastable self-organized arrays with C6 symmetry in the case of strong spin-orbit coupling. We also present a proposal to observe these predicted phases in ultracold atomic dipolar gases with laser-induced spin-orbit coupling, which may stimulate broad theoretical as well as experimental interest.

Stable and Unstable Perturbations in Universal Scaling Phenomena Far from Equilibrium

We study the dynamics of perturbations around nonthermal fixed points associated with universal scaling phenomena in quantum many-body systems far from equilibrium. For an N-component scalar quantum field theory in 3+1 space-time dimensions, we determine the stability scaling exponents using a self-consistent large-N expansion to next-to-leading order. Our analysis reveals the presence of both stable and unstable perturbations, the latter leading to quasiexponential deviations from the fixed point in the infrared. We identify a tower of far-from-equilibrium quasiparticle states and their dispersion relations by computing the spectral function. With the help of linear response theory, we demonstrate that unstable dynamics arises from a competition between elastic scattering processes among the quasiparticle states. What ultimately renders the fixed point dynamically attractive is the phenomenon of a "scaling instability," which is the universal scaling of the unstable regime toward the infrared due to a self-similar quasiparticle cascade. Our results provide abinitio understanding of emergent stability properties in self-organized scaling phenomena.

ДИНАМИКА АДАПТАЦИИ ОБЩЕСТВА В УСЛОВИЯХ ГЛОБАЛЬНОГО ДИСТРЕССА: АНАЛИЗ СИТУАЦИИ С ФЕВРАЛЯ 2022 ПО ФЕВРАЛЬ 2023 Г.

The article considers the public reaction to the Special Military Operation launched in February 2022, which certainly became a stress for the Russian population. The data from different companies, that conducted polls between March and november, were collected and the subsequent analysis of the polling materials showed a curious dynamics of public opinion change. The reaction of the population, characterized by anxiety and fears and initially quite inert, gradually began to transform towards more and more support – both verbal and effective – for the Special Operation and the State. In addition, the phenomenon of individual self-organization of citizens to provide various kinds of assistance to combatants, the wounded, residents of new territories, institutions, animals, etc. has emerged. Active participation in providing assistance becomes an adaptive factor that relieves stress. In addition, active assistance to the Special Operation on the part of citizens becomes a model and an incentive for others, who until a certain time were in a state of waiting, to be included in that process. The positive tendencies of the process are obvious. Such reactions are anthroposystemic in nature and require special approaches to preserve social stability and consolidation of society as a whole