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In this study we identify a process of "entrainment" around open source software (OSS) development release cycles to capture patterns of self-organized task allocation among developers. We conducted an abductive, computationally intensive study of eight OSS projects, using relational event modeling to analyze 1,169,489 actions covering 93 major software releases. The process of entrainment that we identify involves three task allocation mechanisms: (1) developer-issue inertia, (2) developer contribution frequency, and (3) issue popularity. Our analysis demonstrates that these mechanisms and the phases of the release cycle entrain each other. Before a major release, developers engage in a concentrated mobilization phase, whereby they democratize development activity and increasingly allocate community contributions to the set of issues related to the release. After a major release, the extended cleanup phase garners a greater share of development work from recently highly active developers and dilutes the activity of these developers across a wider range of issues. Our theorizing suggests that major releases constitute important events around which OSS communities self-organize and we characterize how this occurs. Our research contributes to theorizing on organizing in OSS communities by explaining how self-organizing task allocation interacts with release cycles through the mechanism of entrainment. We also contribute to the literature on entrainment by showing how it may unfold in the context of online peer production communities such as OSS. [ABSTRACT FROM AUTHOR]

It is increasingly important to understand the spatial dynamics of epidemics. While there are numerous mathematical models of epidemics, there is a scarcity of physical systems with sufficiently well-controlled parameters to allow quantitative model testing. It is also challenging to replicate the macro non-equilibrium effects of complex models in microscopic systems. In this work, we demonstrate experimentally a physics analog of epidemic spreading using optically-driven non-equilibrium phase transitions in strongly interacting Rydberg atoms. Using multiple laser beams we can impose any desired spatial structure. The observed spatially localized phase transitions simulate the outbreak of an infectious disease in multiple locations, and the splitting of the outbreak in subregions, as well as the dynamics towards "herd immunity" and "endemic state" in different regimes. The reported results indicate that Rydberg systems are versatile enough to model complex spatial-temporal dynamics. [ABSTRACT FROM AUTHOR]

The glabrous skin of the rhinarium (naked nose) of many mammalian species exhibits a polygonal pattern of grooves that retain physiological fluid, thereby keeping their nose wet and, among other effects, facilitating the collection of chemosensory molecules. Here, we perform volumetric imaging of whole-mount rhinaria from sequences of embryonic and juvenile cows, dogs, and ferrets. We demonstrate that rhinarial polygonal domains are not placode-derived skin appendages but arise through a self-organized mechanical process consisting of the constrained growth and buckling of the epidermal basal layer, followed by the formation of sharp epidermal creases exactly facing an underlying network of stiff blood vessels. Our numerical simulations show that the mechanical stress generated by excessive epidermal growth concentrates at the positions of vessels that form rigid base points, causing the epidermal layers to move outward and shape domes—akin to arches rising against stiff pillars. Remarkably, this gives rise to a larger length scale (the distance between the vessels) in the surface folding pattern than would otherwise occur in the absence of vessels. These results hint at a concept of "mechanical positional information" by which material properties of anatomical elements can impose local constraints on an otherwise globally self-organized mechanical pattern. In addition, our analyses of the rhinarial patterns in cow clones highlight a substantial level of stochasticity in the pre-pattern of vessels, while our numerical simulations also recapitulate the disruption of the folding pattern in cows affected by a hereditary disorder that causes hyperextensibility of the skin. [Display omitted] • Rhinarial polygonal domains are not placode-derived but mechanically self-organized • The rhinarial skin pattern is mechanically coupled with underlying blood vessels • Epidermal domes rise against stiffer blood vessels—like arches against pillars • Rhinarial folds are as variable among cow clones as among unrelated individuals Dagenais et al. demonstrate that the characteristic polygonal folding patterns on the noses of many mammalian species, such as dogs, ferrets, and cows, emerge via a peculiar self-organizational process involving mechanical positional information encoded by the spatial distribution of stiffness in adjacent tissues. [ABSTRACT FROM AUTHOR]

The physical mechanism of self-organization of a multilayer nanolaminated coating based upon non-equilibrium (TiAlCrSiY)N/(TiAlCr)N nitride on a cutting tool during high-speed (600 m/min.) dry cutting of N13 steel is established. Using a set of modern surface analysis methods coating degradation and tribo-oxidation are studied within the running-in and steady stages of wear. It is shown that during cutting, amorphous-nanocrystalline films of oxides similar to Cr2O3, TiO2, Al2O3 (sapphire) and Al2O3 · 2 (SiO2) (mullite) are formed within a wear crater. Using computer calculations by a finite element method, heat transfer is considered in the cutting zone during formation of protective tribo-oxides. It is found that among all tribo-oxides, mullite has the best thermal barrier properties. Oxidation is the main adaptation mechanism of a cutting tool under extreme mechanical and thermal shock during high-speed cutting. The topography of chip contact surface is studied at various cutting stages, which makes it possible to establish a change in plastic deformation mechanisms of treated metal and friction cutting modes. Quantum chemical calculations of the electron structure of mullite show the highest degree of its electron polarization and explain the radical drop in friction coefficient during film formation upon a wear surface. In this case, mullite acts as a solid lubricant. [ABSTRACT FROM AUTHOR]

The preparation of core–sheath fibers by electrospinning is a topic of significant interest for producing composite fibers with distinct core and sheath functionalities. Moreover, in core–sheath fibers, low-molecular-weight substances or nanosized inorganic additives can be deposited in a targeted manner within the core or the sheath. Commonly, for obtaining a core–sheath structure, coaxial electrospinning is used. It requires a coaxial spinneret and suitable immiscible solvents for the inner and outer solutions. The single-nozzle spinneret electrospinning of emulsions can address these issues, but use of a stabilizing agent is needed. A third approach—preparation of core–sheath fibers by single-nozzle spinneret electrospinning of homogeneous blend solutions of two polymers or of a polymer/low-molecular-weight substance—has been much less studied. It circumvents the difficulties associated with the coaxial and the emulsion electrospinning and is thoroughly discussed in this review. The formation of core–sheath fibers in this case is attributed to phase-separation-driven self-organization during the electrospinning process. Some possibilities for obtaining core–double sheath fibers using the same method are also indicated. The gained knowledge on potential applications of core–sheath fibers prepared by single-nozzle spinneret electrospinning of emulsions and homogeneous blend solutions is also discussed. [ABSTRACT FROM AUTHOR]

Proponents of the Extended Evolutionary Synthesis (EES) emphasize the critical role that organisms and their development play in the process of evolution. This framework explicitly rejects the genocentric focus that once dominated interpretations of the Modern Synthesis in evolutionary theory. In place of genocentrism, EES highlights processes like niche construction, developmental constraint, and extragenetic inheritance as central to any understanding of the evolutionary process. However, much more is at stake in adopting the EES than simply moving beyond the gene-dominant viewpoint of the Modern Synthesis. The EES, in fact, represents a fundamental challenge to the core of classic Darwinism itself by actively repudiating Darwin's key idea that natural selection acts as a creative force in the construction of phenotypes and phenotypic change. In this paper, we more fully explore the assumptive base of Darwinism's population-oriented, selectional focus. We demonstrate how taking development seriously in evolutionary theory mandates a systematic overhaul of Darwinism's assumptive base in favor of grounding all understanding of phenotypic construction in the developmental processes of self-organization endemic to organisms' active engagement with their worlds. [ABSTRACT FROM AUTHOR]

The notion of 'order' has been central in 20th-century attempts to explain complex phenomena. The notion of order in the case of complex phenomena has been generally associated with the idea of 'selforganization'; that is, the spontaneous emergence of coordinating patterns in complex systems. In briefly re-considering the idea of order, this article focuses on 'self-organizing orders' and the implication of this issue not only for a theory of the city but also for a theory of intervention on the city (i.e. a theory of planning). [ABSTRACT FROM AUTHOR]

The purpose of this study was to identify the effectiveness of the project method as an innovative tool for the teaching of humanitarian subjects. The research used such methods as follows: questionnaire, observation, experiment, as well as statistical methods for data processing. In the course of the research, it was determined that the students who were engaged in the project activity, during the project, autonomously researched scientific, reference, educational, and methodological literature. A group of experts found that students' participation in project activities influenced the development of creative activity, and creative systemic thinking contributed to their self-organization. During the survey, it was determined that students' independent work on creating projects ensures the development of personal and functional components of selforganization. The research's scientific novelty lies in its exclusive focus on students studying humanitarian disciplines. The restricted scope of the experiment facilitated the identification of the project approach as such that it can be integrated into the academic system to enhance students' personal and practical proficiencies, thereby promoting their overall growth. Further research can be aimed at determining the effectiveness of using game methods in the course of teaching humanitarian disciplines. [ABSTRACT FROM AUTHOR]

Oncostreams are self-organized structures formed by spindle-like, elongated, self-propelled cells recently described in glioblastomas and especially in gliosarcomas. Cells within these structures either move as large clusters in one main direction, flocks, or as linear, intermingling collections of cells advancing in opposite directions, streams. Round, passive cells are also observed, either inside or segregated from the oncostreams. Here we generalize a recently formulated particle-field approach to investigate the genesis and evolution of these structures, first showing that, in systems consisting only of identical self-propelled cells, both flocks and streams emerge as self-organized dynamic configurations. Flocks are the more stable configurations, while streams are transient and usually originate in collisions between flocks. Stream degradation is easier at low self-propulsion speeds. In systems consisting of both motile and passive cells, the latter block stream formation and accelerate their degradation and flock stabilization. Since the flock appears to be the most effective invasive structure, we thus argue that a phenotype mixture (motile and passive cells) may favor glioblastoma invasion. hlBy relating cellular properties to the observed outcome, our model shows that oncostreams are self-organized structures that result from the interplay between speed, shape, and steric repulsion. [ABSTRACT FROM AUTHOR]

Living cationic ring‐opening polymerization accompanied by isomerization of cyclic imino ethers is performed at high temperatures that provide access to the synthesis of self‐organizable systems in their isotropic melt or solution state. This Perspective discusses fundamental mechanistic principles of this polymerization and bridges with the polymerization of dendronized cyclic iminoethers forming polymers that self‐organize soft Frank–Kasper and quasicrystal periodic and quasiperiodic arrays. These two fields represent frontiers in macromolecular and supramolecular science. A brief discussion of the impact of this polymerization on biomaterials and how it impacted contemporary mechanistic investigations is also made. Expected impacts via future synthetic developments and mechanistic investigations are discussed. [ABSTRACT FROM AUTHOR]

Corrosion processes are often discussed as stochastic events. Here, it is shown that some of these seemingly random processes are not driven by nanoscopic fluctuations but rather by the spatial distribution of micrometer‐scale heterogeneities that trigger fast reactions associated with corrosion. Using a novel excitable reaction‐diffusion model, corrosion waves traveling over the metal surface and the associated material loss are described. This resulting nonuniform corrosion penetration, seen as a height loss in modeling, exposes buried intermetallic particles, which depending on the local electrochemical state of the surface trigger or block new waves. Informed by quantitative experimental data for the Mg–Al–Zn alloy AZ31B, wave speeds, wave widths, and average material loss are accurately captured. Morphogenic mitigation based on wave‐breaking microparticles is also simulated. While AZ31B corrosion is identified as a process driven by rare‐wave events, this study predicts several other corrosion regimes that proceed via spots or patchy patterns, opening the door for new protection, design, and prediction strategies. [ABSTRACT FROM AUTHOR]

The global steady state of a system in thermal equilibrium exponentially favors configurations with lesser energy. This principle is a powerful explanation of selforganization because energy is a local property of configurations. For nonequilibrium systems, there is no such property for which an analogous principle holds, hence no common explanation of the diverse forms of self-organization they exhibit. However, a flurry of recent empirical results has shown that a local property of configurations called "rattling" predicts the steady states of some nonequilibrium systems, leading to claims of a far-reaching principle of nonequilibrium self-organization. But for which nonequilibrium systems is rattling accurate, and why? Wedevelop a theory of rattling in terms of Markov processes that gives simple and precise answers to these key questions. Our results show that rattling predicts a broader class of nonequilibrium steady states than has been claimed and for different reasons than have been suggested. Its predictions hold to an extent determined by the relative variance of, and correlation between, the local and global "parts" of a steady state. We show how these quantities characterize the local-global relationships of various random walks on random graphs, spin-glass dynamics, and models of animal collective behavior. Surprisingly, we find that the core idea of rattling is so general as to apply to equilibrium and nonequilibrium systems alike. [ABSTRACT FROM AUTHOR]

Self‐organizing protein patterns are crucial for living systems, governing important cellular processes such as polarization and division. While the field of protein self‐organization has reached a point where basic pattern‐forming mechanisms can be reconstituted in vitro using purified proteins, understanding how cells can dynamically switch and modulate these patterns, especially when transiently needed, remains an interesting frontier. Here, we demonstrate the efficient regulation of self‐organizing protein patterns through the modulation of simple biophysical membrane parameters. Our investigation focuses on the impact of membrane affinity changes on Min protein patterns at lipid membranes composed of Escherichia coli lipids or minimal lipid compositions, and we present three major results. First, we observed the emergence of a diverse array of pattern phenotypes, ranging from waves over flower‐shaped patterns to snowflake‐like structures. Second, we demonstrated the dependency of these patterns on the density of protein‐membrane linkers. Finally, we demonstrate that the shape of snowflake‐like patterns is fine‐tuned by membrane charge. Our results demonstrate the significant influence of membrane linkage as a straightforward biophysical parameter governing protein pattern formation. Our research points towards a simple yet intriguing mechanism by which cells can adeptly tune and switch protein patterns on the mesoscale. [ABSTRACT FROM AUTHOR]

Mathematical models of heat and moisture transfer for anisotropic materials, based on the use of the fractional calculus of integro-differentiation, are considered because such two-factor fractal models have not been proposed in the literature so far. The numerical implementation of mathematical models for determining changes in heat exchange and moisture exchange is based on the adaptation of the fractal neural network method, grounded in the physics of processes. A fractal physics-informed neural network architecture with a decoupled structure is proposed, based on loss functions informed by the physical process under study. Fractional differential formulas are applied to the expressions of non-integer operators, and finite difference schemes are developed for all components of the loss functions. A step-by-step method for network training is proposed. An algorithm for the implementation of the fractal physics-informed neural network is developed. The efficiency of the new method is substantiated by comparing the obtained numerical results with numerical approximation by finite differences and experimental data for particular cases. [ABSTRACT FROM AUTHOR]

Evolution requires selection. Molecular/chemical/preDarwinian evolution is no exception. One molecule must be selected over another for molecular evolution to occur and advance. Evolution, however, has no goal. The laws of physics have no utilitarian desire, intent or proficiency. Laws and constraints are blind to "usefulness." How then were potential multi-step processes anticipated, valued and pursued by inanimate nature? Can orchestration of formal systems be physico-chemically spontaneous? The purely physico-dynamic self-ordering of Chaos Theory and irreversible non-equilibrium thermodynamic "engines of disequilibria conversion" achieve neither orchestration nor formal organization. Natural selection is a passive and after-the-fact-of-life selection. Darwinian selection reduces to the differential survival and reproduction of the fittest already-living organisms. In the case of abiogenesis, selection had to be 1) Active, 2) Pre-Function, and 3) Efficacious. Selection had to take place at the molecular level prior to the existence of non-trivial functional processes. It could not have been passive or secondary. What naturalistic mechanisms might have been at play? [ABSTRACT FROM AUTHOR]

Copyright of South Architecture / Nanfang Jianzhu is the property of South Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Hydrothermal vents maintain far‐from equilibrium conditions that may have provided the necessary settings for the origin of life. To understand reactions under these physicochemical conditions, scientists have turned to the classic demonstration experiment, chemical gardens. The self‐organization of precipitate tubes separates high and low pH environments similarly to the naturally occurring geological structures. Here, we report calcium‐based chemical gardens forming in solutions containing anions of silicate, carbonate, or a mixture of the two in 100 °C and 23 °C environments. Under high temperature conditions, chemical gardens tend to have faster average growth velocities and form taller structures. We measure the composition of the precipitate tubes using Fourier transform infrared spectroscopy and find the formation of all polymorphs of calcium carbonate along with calcium silicates. [ABSTRACT FROM AUTHOR]

Animal collective behavior produces group‐level patterns that emerge from individual‐level interactions among members. Such sophisticated behavioral coordination can be observed across various taxa, indicating evolutionary convergence. Among the most striking examples are two social insect lineages: ants and termites. Ants and termites evolved socially independently, inhabit terrestrial and subterranean environments, and face a similar collective task of maintaining their colonies with many individuals. This results in the convergent evolution of collective phenomena, such as constructing complex nest structures or movement coordination based on chemical and tactile cues. However, although the striking similarity attracts the most attention, little research has focused on how ants and termites differ in collective behaviors at individual and group levels. Here, we review the similarities and distinctions of collective behaviors in ants and termites. Even with similarities in group‐level patterns, rich diversity exists in mechanisms of behavioral coordination and the functions of collective patterns. Comparative analysis of collective behavior is challenging, but recent advances in automatic movement tracking methodologies have greatly expanded the potential for generating further insights. Finally, we conclude that comparative collective behavioral analysis can enhance our ability to understand biodiversity and provide alternative solutions for collective problem‐solving in many fields. [ABSTRACT FROM AUTHOR]

The Middle East and North Africa (MENA) is the most water-scarce region in the world. Recent research suggests that agroecology could be a basis for sustainable agriculture. We assess the spread of agroecology in the region and explore the prospect of self-organization among farming communities as an indicator for self-determination of the farming system. The focus is on Lebanon, Morocco and Tunisia. We present empirical data and propose an analytical framework for capturing the conditions for self-organizing arrangements in a transition to agroecology. [ABSTRACT FROM AUTHOR]

Copyright of Arbeit is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The wear rate variation in frictional systems where several significant factors act is studied. Options for reducing the wear rate are explored. [ABSTRACT FROM AUTHOR]

Copyright of Educational Academic Research is the property of Ataturk University Coordinatorship of Scientific Journals and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Abstract It is increasingly important to understand the spatial dynamics of epidemics. While there are numerous mathematical models of epidemics, there is a scarcity of physical systems with sufficiently well-controlled parameters to allow quantitative model testing. It is also challenging to replicate the macro non-equilibrium effects of complex models in microscopic systems. In this work, we demonstrate experimentally a physics analog of epidemic spreading using optically-driven non-equilibrium phase transitions in strongly interacting Rydberg atoms. Using multiple laser beams we can impose any desired spatial structure. The observed spatially localized phase transitions simulate the outbreak of an infectious disease in multiple locations, and the splitting of the outbreak in subregions, as well as the dynamics towards “herd immunity” and “endemic state” in different regimes. The reported results indicate that Rydberg systems are versatile enough to model complex spatial-temporal dynamics.

Abstract Oncostreams are self-organized structures formed by spindle-like, elongated, self-propelled cells recently described in glioblastomas and especially in gliosarcomas. Cells within these structures either move as large clusters in one main direction, flocks, or as linear, intermingling collections of cells advancing in opposite directions, streams. Round, passive cells are also observed, either inside or segregated from the oncostreams. Here we generalize a recently formulated particle-field approach to investigate the genesis and evolution of these structures, first showing that, in systems consisting only of identical self-propelled cells, both flocks and streams emerge as self-organized dynamic configurations. Flocks are the more stable configurations, while streams are transient and usually originate in collisions between flocks. Stream degradation is easier at low self-propulsion speeds. In systems consisting of both motile and passive cells, the latter block stream formation and accelerate their degradation and flock stabilization. Since the flock appears to be the most effective invasive structure, we thus argue that a phenotype mixture (motile and passive cells) may favor glioblastoma invasion. hlBy relating cellular properties to the observed outcome, our model shows that oncostreams are self-organized structures that result from the interplay between speed, shape, and steric repulsion.

Sadia Qazi,1 Muhammad Atif Mazhar,1 Abdul Ahad Shaikh,2 Abdul Jabar Rasool,2 Kanza Atif,3 Akef Obeidat1 1Anatomy Department, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia; 2Physiology Department, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia; 3College of Medicine, Alfaisal University, Riyadh, Saudi ArabiaCorrespondence: Sadia Qazi, Anatomy Department, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia, Email sqazi@alfaisal.eduAbstract: This study explores the implementation of Team-Based Learning (TBL) at Alfaisal University’s College of Medicine through the lens of Complex Adaptive Systems (CAS) theory. The research question investigates how the application of CAS principles can enhance the implementation and effectiveness of TBL in medical education. The study employed a convergent parallel mixed methods longitudinal design, integrating quantitative performance metrics and qualitative themes. Quantitative analysis revealed modest improvements in individual and team-based learning scores, with a promising trend of students moving from the lower to the higher quartiles over time. Qualitative insights aligned with CAS principles, highlighting the adaptive implementation, emergent outcomes, self-organization, positive feedback loops, and depth of learning facilitated by TBL. The findings demonstrate the value of a CAS-informed approach in navigating the complexities of educational change and fostering a more resilient and adaptive educational model. The study contributes to the understanding of how CAS theory can guide the successful implementation of innovative pedagogies like TBL in medical education.Keywords: educational change, adaptive implementation, emergent behaviors, feedback loops, self-organization

Global supply chains feature multi-tier systems encompassing many geographically dispersed and sequential partners operating across diversified product chains. This research attempts to examine the different mechanisms that reinforce the management of sustainability throughout complex multi-tier supply chain. Using a multi-case study of a sample of eight firms and relying on the foundations of complexity theory, this research recognises the complex operating environment of global multi-tier supply chains and reveals various mechanisms to effectively manage and facilitate the relationships with first- and lower-tier suppliers. Although institutional controls are important to manage the sustainability of first-tier suppliers, the findings posit that due to the inherent complexities of global multi-tier supply chains, duplicating institutional controls to lower-tier suppliers might not be effective. Therefore, firms should attempt to foster modest mechanisms that reinforce adaptation and self-organisation, for example, collaboration and guiding mechanisms, to effectively manage the sustainability of lower-tier suppliers. The research contributes to multi-tier sustainable supply chain management literature by exploring the different mechanisms to manage multi-tier supply chains and the inherent complexities that may impact on firms' endeavours in achieving their sustainability goals. Managers can utilise different contingent mechanisms to effectively manage the relationships with suppliers that are beyond their immediate visibility. [ABSTRACT FROM AUTHOR]

Non‐equilibrium patterns are widespread in nature and often arise from the self‐organization of constituents through nonreciprocal chemotactic interactions. In this study, we demonstrate how active oil‐in‐water droplet mixtures with predator‐prey interactions can result in a variety of self‐organized patterns. By manipulating physical parameters, the droplet diameter ratio and number ratio, we identify distinct classes of patterns within a binary droplet system, rationalize the pattern formation, and quantify motilities. Experimental results are recapitulated in numerical simulations using a minimal computational model that solely incorporates chemotactic interactions and steric repulsion among the constituents. The time evolution of the patterns is investigated and chemically explained. We also investigate how patterns vary with differing interaction strength by altering surfactant composition. Leveraging insights from the binary droplet system, the framework is extended to a ternary droplet mixture composed of multiple chasing droplet pairs to create chemically directed hierarchical organization. Our findings demonstrate how rationalizable, self‐organized patterns can be programmed in a chemically minimal system and provide the basis for exploration of emergent organization and higher order complexity in active colloids. [ABSTRACT FROM AUTHOR]

A dynamical system is considered such that, in this system, particles move on a toroidal lattice of the dimension N1×N2$$ {N}_1\times {N}_2 $$ according to a version of the rule of particle movement in Biham–Middleton–Levine traffic model. We introduce a stochastic case with direction choice for particles. Particles of the first type move along rows, and the particles of the second type move along columns. The goal is to find conditions of self‐organization system for any lattice dimension. We have proved that the BML model as a dynamical system is a special case of Buslaev nets. This equivalence allows us to use of Buslaev net analysis techniques to investigate the BML model. In Buslaev nets conception, the self‐organization property of the system corresponds to the existence of velocity single point spectrum equal to 1. In the paper, we consider the model version when one notable aspect is that a particle may change its type. Exactly, we assume a constant probability q$$ q $$ that a particle changes type at each step. In the case where q=0$$ q=0 $$, the system corresponds to the classical version of the BML model. We define a state of the system where all particles continue to move indefinitely, in both the present and the future, as a state of free movement. A sufficient condition for the system to result in a state of free movement from any initial state (condition for self‐organization) has been found. This condition is that the number of particles be not greater than half the greatest common divisor of the numbers N1,N2,...,Nn$$ {N}_1,{N}_2,\dots, {N}_n $$. It has been proved that, if n=2$$ n=2 $$, and whether 0

Fullerene molecules have been intensively studied over the past few decades due to their unique chemical and physical properties, which have great potential in a wide range of applications. In this article, the formation and aging of C60 colloids in the xylene/ethanol system is considered. The peculiarities of these processes are studied by the methods of refractometry, optical absorption, Raman spectroscopy and dynamic light scattering (DLS). It has been experimentally established that the formation of colloidal particles in a C60/xylene/ethanol mixture depends on the volume content of the components and the storage time of the solution. The time required to achieve stability of self-organization of solute molecules in a C60/xylene/ethanol mixture is discussed. [ABSTRACT FROM AUTHOR]

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Abstract Background Primary care is often described as slow to change. But conceptualized through complexity theory, primary care is continually changing in unpredictable, non-linear ways through self-organization processes. Self-organization has proven hard to study directly. We aimed to develop a methodology to study self-organization and describe how a primary care clinic self-organizes over time. Methodology We completed a virtual case study of an urban primary care clinic from May-Nov 2021, applying methodological insights from actor-network theory to examine the complexity theory concept of self-organization. We chose to focus our attention on self-organization activities that alter organizational routines. Data included fieldnotes of observed team meetings, document collection, interviews with clinic members, and notes from brief weekly discussions to detect actions to change clinical and administrative routines. Adapting schema analysis, we described changes to different organizational routines chronologically, then explored intersecting changes. We sought feedback on results from the participating clinic. Findings Re-establishing equilibrium remained challenging well into the COVID-19 pandemic. The primary care clinic continued to self-organize in response to changing health policies, unintended consequences of earlier adaptations, staff changes, and clinical care initiatives. Physical space, technologies, external and internal policies, guidelines, and clinic members all influenced self-organization. Changing one created ripple effects, sometimes generating new, unanticipated problems. Member checking confirmed we captured most of the changes to organizational routines during the case study period. Conclusions Through insights from actor-network theory, applied to studying actions taken that alter organizational routines, it is possible to operationalize the theoretical construct of self-organization. Our methodology illuminates the primary care clinic as a continually changing entity with co-existing and intersecting processes of self-organization in response to varied change pressures.

This article addresses the bathing problem in multi-machine collaborative operations, proposing a method based on improved self-organizing iterative clustering. This approach circumvents the issues of traditional manual parameter setting in the self-organizing iterative clustering algorithm that is often inconvenient and non-intuitive. The proposed method allows multiple machines to autonomously adjust the parameters involved in the clustering process, given a small number of intuitive hyperparameters. The ultimate goal is to iterate toward reasonable editing results. Initially, this article focuses on selecting feature vectors for the multi-machine collaborative confrontation situation. It applies standardization and principal component analysis to high-dimensional multi-machine situation information to confirm the new vector space. This space mainly encompasses position information in three dimensions and speed information. Subsequently, the paper introduces the concept of neighborhood density discrimination from density clustering. This improves the merging and splitting operations of the traditional self-organizing iterative clustering method. It optimizes and reduces the artificial parameters involved in these operations, enhancing the intelligent autonomy for batch clustering tasks. Before optimization, artificial parameters primarily include the number of expected clusters, minimum number of points within a class, number of iterations, upper limit of standard deviation that limits data distribution within a class, and an allowable shortest distance indicator between classes. Post optimization, the artificial parameters are limited to the expected cluster quantity, minimum number of points, and the number of iterations within a single classification. These optimized parameters are relatively intuitive, and the algorithm output does not strongly correlate with the input parameters. Ultimately, the paper selects algorithm evaluation indicators, including Dunn, Davies–Bouldin, silhouette coefficient, and Calinski–Harabasz. It uses these to evaluate the proposed algorithms ISODATA+ and K-MEANS+, along with the original ISODATA algorithm, against multiple artificially synthesized data sets (completely random data, Gaussian-generated data, and sin-type data) and real-world scenarios. The experimental results suggest that while KMEANS+ shows significant advantages owing to multiple manually set hyperparameters, it requires constant debugging when adjusting parameters, which increases the complexity of the task. Compared with the original self-organizing iterative algorithm ISODATA, statistical results show that the improved algorithm has equivalent capabilities to the original algorithm. This demonstrates that the ISODATA+ algorithm maintains good clustering capabilities even after removing some artificial parameters. The batching results from actual scenario tests further illustrate the effectiveness of the improved self-organizing iterative clustering algorithm in specific application scenarios, demonstrating its practicability for future real-world applications.

Organoids are 3D cultured tissues derived from stem cells that resemble the structure of living organs. Based on the accumulated knowledge of neural development, neural organoids that recapitulate neural tissue have been created by inducing self-organized neural differentiation of stem cells. Neural organoid techniques have been applied to human pluripotent stem cells to differentiate 3D human neural tissues in culture. Various methods have been developed to generate neural tissues of different regions. Currently, neural organoid technology has several significant limitations, which are being overcome in an attempt to create neural organoids that more faithfully recapitulate the living brain. The rapidly advancing neural organoid technology enables the use of living human neural tissue as research material and contributes to our understanding of the development, structure and function of the human nervous system, and is expected to be used to overcome neurological diseases and for regenerative medicine.

The connection between digital literacy and the three core dimensions of psychological well-being is not yet well understood, and the evidence is controversial. We analyzed a sample of 2,314 individuals, aged 50 years and older, that participated in the English Longitudinal Study of Aging. Participants were clustered according to drivers of psychological well-being using Self-Organizing Maps. The resulting groups were subsequently studied separately using generalized estimating equations fitted on 2-year lagged repeated measures using three scales to capture the dimensions of well-being and Markov models. The clustering analysis suggested the existence of four different groups of participants. Statistical models found differences in the connection between internet use and psychological well-being depending on the group. The Markov models showed a clear association between internet use and the potential for transition among groups of the population characterized, among other things, by higher levels of psychological well-being.

Animal groups need to achieve and maintain consensus to minimize conflict among individuals and prevent group fragmentation. An excellent example of a consensus challenge is cooperative transport, where multiple individuals cooperate to move a large item together. This behaviour, regularly displayed by ants and humans only, requires individuals to agree on which direction to move in. Unlike humans, ants cannot use verbal communication but most likely rely on private information and/or mechanical forces sensed through the carried item to coordinate their behaviour. Here, we investigated how groups of weaver ants achieve consensus during cooperative transport using a tethered-object protocol, where ants had to transport a prey item that was tethered in place with a thin string. This protocol allows the decoupling of the movement of informed ants from that of uninformed individuals. We showed that weaver ants pool together the opinions of all group members to increase their navigational accuracy. We confirmed this result using a symmetry-breaking task, in which we challenged ants with navigating an open-ended corridor. Weaver ants are the first reported ant species to use a 'wisdom-of-the-crowd' strategy for cooperative transport, demonstrating that consensus mechanisms may differ according to the ecology of each species. [ABSTRACT FROM AUTHOR]

The spatial arrangement of variant phenotypes during stem cell division plays a crucial role in the self-organization of cell tissues. The patterns observed in these cellular assemblies, where multiple phenotypes vie for space and resources, are largely influenced by a mixture of different diffusible chemical signals. This complex process is carried out within a chronological framework of interplaying intracellular and intercellular events. This includes receiving external stimulants, whether secreted by other individuals or provided by the environment, interpreting these environmental signals, and incorporating the information to designate cell fate. Here, given two distinct signaling patterns generated by Turing systems, we investigated the spatial distribution of differentiating cells that use these signals as external cues for modifying the production rates. By proposing a computational map, we show that there is a correspondence between the multiple signaling and developmental cellular patterns. In other words, the model provides an appropriate prediction for the final structure of the differentiated cells in a multi-signal, multi-cell environment. Conversely, when a final snapshot of cellular patterns is given, our algorithm can partially identify the signaling patterns that influenced the formation of the cellular structure, provided that the governing dynamic of the signaling patterns is already known. [ABSTRACT FROM AUTHOR]

Summary Digital MemComputing machines (DMMs), which employ nonlinear dynamical systems with memory (time non‐locality), have proven to be a robust and scalable unconventional computing approach for solving a wide variety of combinatorial optimization problems. However, most of the research so far has focused on the numerical simulations of the equations of motion of DMMs. This inevitably subjects time to discretization, which brings its own (numerical) issues that would be otherwise absent in actual physical systems operating in continuous time. Although hardware realizations of DMMs have been previously suggested, their implementation would require materials and devices that are not so easy to integrate with traditional electronics. Addressing this, our study introduces a novel hardware design for DMMs, utilizing readily available electronic components. This approach not only significantly boosts computational speed compared to current models but also exhibits remarkable robustness against additive noise. Crucially, it circumvents the limitations imposed by numerical noise, ensuring enhanced stability and reliability during extended operations. This paves a new path for tackling increasingly complex problems, leveraging the inherent advantages of DMMs in a more practical and accessible framework. [ABSTRACT FROM AUTHOR]

A study on the formation of InGaN ternary compounds in the three-dimensional growth mode is presented. For the first time, we demonstrate that the self-organization during InGaN growth is responsible for the formation of core–shell nanowires (NWs), nanotubes, zinc blende (ZB) phases, and nanoflowers. It is found that the core–shell InGaN NWs are formed at the very initial stage of growth. An increase in growth time results in the ascending indium diffusion from the cores of NWs and their accumulation at the NW tips, enabling three-dimensional lateral growth and formation of nanotubes. Further nanostructure growth leads to the formation of nanoflowers with empty stems and ZB/wurtzite (WZ) phase interface at the periphery. The observed structural transformations of NWs are supported by transmission electron microscopy and photoluminescence measurements, as well as theoretical estimates. Understanding the formation mechanisms of these complex three-dimensional nanostructures can facilitate the development of InGaN compounds for gas-sensing applications. [ABSTRACT FROM AUTHOR]

Background: Primary care is often described as slow to change. But conceptualized through complexity theory, primary care is continually changing in unpredictable, non-linear ways through self-organization processes. Self-organization has proven hard to study directly. We aimed to develop a methodology to study self-organization and describe how a primary care clinic self-organizes over time. Methodology: We completed a virtual case study of an urban primary care clinic from May-Nov 2021, applying methodological insights from actor-network theory to examine the complexity theory concept of self-organization. We chose to focus our attention on self-organization activities that alter organizational routines. Data included fieldnotes of observed team meetings, document collection, interviews with clinic members, and notes from brief weekly discussions to detect actions to change clinical and administrative routines. Adapting schema analysis, we described changes to different organizational routines chronologically, then explored intersecting changes. We sought feedback on results from the participating clinic. Findings: Re-establishing equilibrium remained challenging well into the COVID-19 pandemic. The primary care clinic continued to self-organize in response to changing health policies, unintended consequences of earlier adaptations, staff changes, and clinical care initiatives. Physical space, technologies, external and internal policies, guidelines, and clinic members all influenced self-organization. Changing one created ripple effects, sometimes generating new, unanticipated problems. Member checking confirmed we captured most of the changes to organizational routines during the case study period. Conclusions: Through insights from actor-network theory, applied to studying actions taken that alter organizational routines, it is possible to operationalize the theoretical construct of self-organization. Our methodology illuminates the primary care clinic as a continually changing entity with co-existing and intersecting processes of self-organization in response to varied change pressures. [ABSTRACT FROM AUTHOR]

Inorganic–inorganic self‐organized composite architectures resulting from the chemical coupling of alkaline‐earth carbonate and polymeric silica are a promising alternative to organic‐based hybrid bio‐mimetic systems for developing innovative multi‐functional materials. Although the importance of pH in the generation of these structures reminiscent of primitive living organisms (and for this called biomorphs) is widely acknowledged, the effect of pH is generally investigated on the basis of starting pH value. This approach inadvertently neglects the important spatial and temporal pH gradients associated with biomorph nucleation and growth. A deep understanding of the role of pH on morphogenesis requires the ability to detect locally the pH in real‐time with a non‐invasive technique and correlate pH to the different stages of biomorphic growth. This aim is achieved by combining optical and fluorescence imaging. An accurately selected pH probe suitable for ratiometric pH measurement in the silica gel is exploited during a typical counter‐diffusion experiment. The results are compared with computer simulation of the synthesis of biomorphs by counter‐diffusion experiments. The results demonstrate the existence of two main morphogenetic regimes. Interestingly, the morphogenetic process controlling the complex shaping of biomorphs results to be independent of the silica speciation. [ABSTRACT FROM AUTHOR]

Summary: Environmental disasters such as earthquakes, tsunamis, floods, and landslides disrupt natural resources, human casualties, and so on. Early warning and alert of such events will help for preparedness to avoid human and economic causalities. Managing a disaster or emergency scenario is a difficult endeavor. These episodes of mass devastation, whether caused by natural disasters or man‐made disasters, result in massive losses of money, property, and lives as a result of inadequate response by the government and management authorities. As a result, actions must be taken to avoid these circumstances from occurring by discovering the causes of these catastrophes in advance and providing swift rescue procedures once the crisis happens. In a disaster situation, communication plays a vital role, and a lot of people turn towards it as a source of information conveyance/delivery for controlling the situation. Even these communication networks are damaged and incur tremendous losses during disasters. All the communication networks, including mobile wireless sensor networks (WSNs) deployed for communication, also suffer huge damage and face many challenges during disasters. Nature appears to deal with these issues well. WSN is inspired by several biological systems and processes that have intrinsically attractive properties such as adaptation, self‐organization, and self‐healing. In this paper, we proposed an enhanced bio‐inspired energy‐efficient localization (EBEEL) routing for Mobile WSN. The main focus of the proposed EBEEL algorithm is to overcome the challenges faced by peer‐existing routing protocols such as data aggregation, limited bandwidth, scalability, data redundancy, energy consumption, packet drops, load balancing, and Quality of Service (QoS). [ABSTRACT FROM AUTHOR]

Cell polarity networks are defined by quantitative features of their constituent feedback circuits, which must be tuned to enable robust and stable polarization, while also ensuring that networks remain responsive to dynamically changing cellular states and/or spatial cues during development. Using the PAR polarity network as a model, we demonstrate that these features are enabled by the dimerization of the polarity protein PAR-2 via its N-terminal RING domain. Combining theory and experiment, we show that dimer affinity is optimized to achieve dynamic, selective, and cooperative binding of PAR-2 to the plasma membrane during polarization. Reducing dimerization compromises positive feedback and robustness of polarization. Conversely, enhanced dimerization renders the network less responsive due to kinetic trapping of PAR-2 on internal membranes and reduced sensitivity of PAR-2 to the anterior polarity kinase, aPKC/PKC-3. Thus, our data reveal a key role for a dynamically oligomeric RING domain in optimizing interaction affinities to support a robust and responsive cell polarity network, and highlight how optimization of oligomerization kinetics can serve as a strategy for dynamic and cooperative intracellular targeting. Synopsis: Establishment of cell polarity is mediated by PAR protein pattern formation and is thought to rely on complex feedback responses. This study identifies membrane-dependent dimerization of the posterior polarity protein PAR-2 via its RING domain as one source of such feedback, which drives cooperative and selective stabilization of PAR-2 at the plasma membrane. PAR-2 exhibits cooperative plasma membrane binding. Cooperativity emerges from concentration-dependent PAR-2 RING domain dimerization. Increasing or decreasing dimer affinity compromises robustness of polarization. Optimized dimer affinity allows rapid and selective plasma membrane targeting. RING domain dimerization stabilises posterior polarity protein PAR-2 at the plasma membrane to support polarization of the C. elegans zygote. [ABSTRACT FROM AUTHOR]

Swarms of self-organizing bots are becoming important elements in various technical systems, which include the control of bacterial cyborgs in biomedical applications, technologies for creating new metamaterials with internal structure, self-assembly processes of complex supramolecular structures in disordered media, etc. In this work, we theoretically study the effect of sudden fluidization of a dense group of bots, each of which is a source of heat and follows a simple algorithm to move in the direction of the gradient of the global temperature field. We show that, under certain conditions, an aggregate of self-propelled bots can fluidize, which leads to a second-order phase transition. The bots' program, which forces them to search for the temperature field maximum, acts as an effective buoyancy force. As a consequence, one can observe a sudden macroscopic circulation of bots from the edge of the group to its center and back again, which resembles classical Rayleigh-Benard thermal convection. In the continuum approximation, we have developed a mathematical model of the phenomenon, which reduces to the equation of a self-gravitating porous disk saturated with an incompressible fluid that generates heat. We derive governing equations in the Darcy-Boussinesq approximation and formulate a nonlinear boundary value problem. An exact solution to the linearized problem for infinitesimal perturbations of the base state is obtained, and the critical values of the control parameter for the onset of the bot circulation are calculated. Then we apply weakly nonlinear analysis using the method of multiple time scales. We found that as the number of bots increases, the swarm exhibits increasingly complex patterns of circulation. Graphic Abstract [ABSTRACT FROM AUTHOR]

Self-organization theory is an interdisciplinary scientific direction to improve the quality of acquired knowledge and skills. The article aims to study the development of interdisciplinary research activities among students based on self-organization theory. The study was conducted using an integrated approach, methods of analysis and synthesis, modeling, pedagogical experiments, and mathematical statistics. An elective course, “synergetic-interdisciplinary scientific theory”, and a model for preparing students for interdisciplinary research activities were developed and implemented. The knowledge and skills of 272 physics students in the Republic of Kazakhstan universities in control and experimental groups improved after the training. The knowledge highest level is observed among the experimental group students while studying the natural experiments’ theoretical aspects necessary for researching the natural objects’ sustainability. Experimental group students demonstrated better results in completing the task based on the acquired knowledge and skills. They rated the education quality significantly better on a short educational assessment scale. The results-developed course and the students’ preparing models for interdisciplinary research can be used in advanced courses for different specialties educators. Research perspectives could potentially contribute to the development of integrated subjects and interdisciplinary programs in natural sciences and humanities. [ABSTRACT FROM AUTHOR]

The parameters of the plasma of a low-pressure glow discharge in neon with microparticles, at which regions with equal values of the ion confinement efficiency in the cloud of microparticles are realized, are determined numerically. It is noted that such features are characteristic of dissipative synergetic systems controlled by the feedback. The simulation of a complex plasma of glow discharge in neon with microparticles shows that feedback in the plasma is realized through the source of the main losses of its energy—a cloud of microparticles. Controlling the discharge parameters by changing the concentration of microparticles in the cloud makes it possible to control the concentration of the ions in the plasma. [ABSTRACT FROM AUTHOR]

In the strive for energy efficient computing, many different neuromorphic computing and engineering schemes have been introduced. Nanoparticle networks (NPNs) at the percolation threshold have been established as one of the promising candidates, e.g., for reservoir computing because among other useful properties they show self‐organization and brain‐like avalanche dynamics. The dynamic resistance changes trace back to spatio‐temporal reconfigurations in the connectivity upon resistive switching in distributed memristive nano‐junctions and nano‐gaps between neighboring nanoparticles. Until now, however, there has not yet been any direct imaging or monitoring of current paths in NPN. In this study, an NPN comprising of Ag/CxOyHz core/shell and Ag nanoparticles at the percolation threshold is reported. It is shown that this NPN is within a critical regime, exhibiting avalanche dynamics. To monitor in situ the evolving current paths in this NPN, active voltage contrast and resistive contrast imaging are used complementarily. Including simulations, the results provide experimental insight toward understanding the complex current response of the memristive NPN. As such, this study paves the way toward an experimental characterization of dynamic reorganizations in current paths inside NPN, which is highly relevant for validating and improving simulations and finally establishing a deeper understanding of switching dynamics in NPNs. [ABSTRACT FROM AUTHOR]

Under nonequilibrium conditions, inorganic systems can produce a wealth of life-like shapes and patterns which, compared to well-formed crystalline materials, remain widely unexplored. A seemingly simple example is the formation of salt deposits during the evaporation of sessile droplets. These evaporites show great variations in their specific patterns including single rings, creep, small crystals, fractals, and featureless disks. We have explored the patterns of 42 different salts at otherwise constant conditions. Based on 7,500 images, we show that distinct pattern families can be identified and that some salts (e.g., Na2SO4 and NH4NO3) are bifurcated creating two distinct motifs. Family affiliations cannot be predicted a priori from composition alone but rather emerge from the complex interplay of evaporation, crystallization, thermodynamics, capillarity, and fluid flow. Nonetheless, chemical composition can be predicted from the deposit pattern with surprisingly high accuracy even if the set of reference images is small. These findings suggest possible applications including smartphone-based analyses and lightweight tools for space missions. [ABSTRACT FROM AUTHOR]