Self-organization Mechanism Research Articles

Biomimetic three-dimensional scaffolds with aligned electrospun nanofibers and enlarged pores for enhanced cardiac cell colonization

Among the wide range of biomimetic scaffolds, those made of aligned nanofibers represent an important class for tissue engineering applications, and particularly for cardiac repair. Electrospinning is a powerful technique allowing the fabrication of scaffolds with aligned nanofibers. However, the resulting morphology is characterized by low porosity and small pore size due to the formation of a compact structure of aligned fibers preventing cell colonization inside the scaffold. In the present work, supported by numerical simulation, it is demonstrated that when optimal electrostatic interactions occur during the simultaneous deposition of electrospun nanofibers and electrosprayed microparticles on a collector rotating at high speed, a 3D structured scaffold is obtained. Thanks to a self-organization mechanism, islands of microparticles intercalate inside a network of loosely packed and highly aligned nanofibers. In the case of poly(lactic acid) electrospinning and poly(glycerol sebacate)/cyclodextrin electrospraying, the resulting 3D biomimetic scaffold, deeply investigated by X-ray microtomography and mechanical characterization, shows an open porosity with enlarged interconnected pores with a mechanical behavior mimicking that of cardiac tissue. Finally, after functionalizing the fiber surface using laminin, it is shown an efficient 3D colonization of cardiac cells through a network of aligned nanofibers.

Unwinding Spherical Helices Increases Entropy and Stability of Frank-Kasper and Body-Centered-Cubic Periodic Arrays To Facilitate Discrimination between Self-Organization Mechanisms.

Spherical supramolecular dendrimers including helical, self-organize soft Frank-Kasper, other cubic such as body-centered cubic, and quasicrystal periodic and quasiperiodic arrays. When any of these periodic or quasiperiodic arrays forms immediately above a columnar phase, a supramolecular orientational memory effect was found to discriminate between mechanisms of self-organization of supramolecular spheres and generate unprecedented periodic arrays of helical columns which cannot be constructed by any other methodology. Here, we demonstrate that unwinding spherical helices, via their precursor nonhelical columns, increases the entropy and stability of their periodic and quasiperiodic spherical arrays and places the Frank-Kasper and other cubic phases immediately above the columnar phase. This process is not available in biology where spherical viruses self-organize body-centered cubic lattices. However, this concept reengineers, on increasing temperature, the originally expected position of the periodic and quasiperiodic array versus that of the columnar lattice. This process facilitates discrimination between different self-organization mechanisms of supramolecular spheres and also mediates the emergence of unprecedentedly complex and technologically important periodic arrays of nonhelical columns.

Synchronized stepwise control of firing and learning thresholds in a spiking randomly connected neural network toward hardware implementation.

Spiking randomly connected neural network (RNN) hardware is promising as ultimately low power devices for temporal data processing at the edge. Although the potential of RNNs for temporal data processing has been demonstrated, randomness of the network architecture often causes performance degradation. To mitigate such degradation, self-organization mechanism using intrinsic plasticity (IP) and synaptic plasticity (SP) should be implemented in the spiking RNN. Therefore, we propose hardware-oriented models of these functions. To implement the function of IP, a variable firing threshold is introduced to each excitatory neuron in the RNN that changes stepwise in accordance with its activity. We also define other thresholds for SP that synchronize with the firing threshold, which determine the direction of stepwise synaptic update that is executed on receiving a pre-synaptic spike. To discuss the effectiveness of our model, we perform simulations of temporal data learning and anomaly detection using publicly available electrocardiograms (ECGs) with a spiking RNN. We observe that the spiking RNN with our IP and SP models realizes the true positive rate of 1 with the false positive rate being suppressed at 0 successfully, which does not occur otherwise. Furthermore, we find that these thresholds as well as the synaptic weights can be reduced to binary if the RNN architecture is appropriately designed. This contributes to minimization of the circuit of the neuronal system having IP and SP.

Nanoscale 3D DNA tracing reveals the mechanism of self-organization of mitotic chromosomes.

How genomic DNA is folded during cell division to form the characteristic rod-shaped mitotic chromosomes essential for faithful genome inheritance is a long-standing open question in biology. Here, we use nanoscale DNA-tracing in single dividing cells to directly visualize how the 3D fold of genomic DNA changes during mitosis, at scales from single loops to entire chromosomes. Our structural analysis reveals a characteristic genome scaling minimum at 6-8 Mbp in mitosis. Combined with data-driven modeling and molecular perturbations, we can show that very large and strongly overlapping loops formed by Condensins are the fundamental structuring principle of mitotic chromosomes. These loops compact chromosomes locally and globally to the limit set by chromatin self-repulsion. The characteristic length, density and increasingly overlapping structure of mitotic loops we observe in 3D, fully explain how the rod-shaped mitotic chromosome structure emerges by self-organization during cell division.

Recording morphogen signals reveals mechanisms underlying gastruloid symmetry breaking.

Aggregates of stem cells can break symmetry and self-organize into embryo-like structures with complex morphologies and gene expression patterns. Mechanisms including reaction-diffusion Turing patterns and cell sorting have been proposed to explain symmetry breaking but distinguishing between these candidate mechanisms of self-organization requires identifying which early asymmetries evolve into subsequent tissue patterns and cell fates. Here we use synthetic 'signal-recording' gene circuits to trace the evolution of signalling patterns in gastruloids, three-dimensional stem cell aggregates that form an anterior-posterior axis and structures resembling the mammalian primitive streak and tailbud. We find that cell sorting rearranges patchy domains of Wnt activity into a single pole that defines the gastruloid anterior-posterior axis. We also trace the emergence of Wnt domains to earlier heterogeneity in Nodal activity even before Wnt activity is detectable. Our study defines a mechanism through which aggregates of stem cells can form a patterning axis even in the absence of external spatial cues.

The effect of diffusion on multistability and stochastic sensitivity in spatially extended systems

A spatially-extended reaction-diffusion model is considered. The work is focused on self-organization mechanisms of diffusion instability and Turing pattern formation. Pattern generation and multistability of the system is demonstrated for varying diffusion intensity. In the stochastic variant of the model, the sensitivity of coexisting patterns to noise is studied. The stochastic sensitivity function technique is used for the analysis of noise-induced transitions between patterns. Application of stochastic sensitivity functions is discussed on examples.

Criticality and universality in neuronal cultures during "up" and "down" states.

The brain can be seen as a self-organized dynamical system that optimizes information processing and storage capabilities. This is supported by studies across scales, from small neuronal assemblies to the whole brain, where neuronal activity exhibits features typically associated with phase transitions in statistical physics. Such a critical state is characterized by the emergence of scale-free statistics as captured, for example, by the sizes and durations of activity avalanches corresponding to a cascading process of information flow. Another phenomenon observed during sleep, under anesthesia, and in in vitro cultures, is that cortical and hippocampal neuronal networks alternate between "up" and "down" states characterized by very distinct firing rates. Previous theoretical work has been able to relate these two concepts and proposed that only up states are critical whereas down states are subcritical, also indicating that the brain spontaneously transitions between the two. Using high-speed high-resolution calcium imaging recordings of neuronal cultures, we test this hypothesis here by analyzing the neuronal avalanche statistics in populations of thousands of neurons during "up" and "down" states separately. We find that both "up" and "down" states can exhibit scale-free behavior when taking into account their intrinsic time scales. In particular, the statistical signature of "down" states is indistinguishable from those observed previously in cultures without "up" states. We show that such behavior can not be explained by network models of non-conservative leaky integrate-and-fire neurons with short-term synaptic depression, even when realistic noise levels, spatial network embeddings, and heterogeneous populations are taken into account, which instead exhibits behavior consistent with previous theoretical models. Similar differences were also observed when taking into consideration finite-size scaling effects, suggesting that the intrinsic dynamics and self-organization mechanisms of these cultures might be more complex than previously thought. In particular, our findings point to the existence of different mechanisms of neuronal communication, with different time scales, acting during either high-activity or low-activity states, potentially requiring different plasticity mechanisms.

Stigmergy: from mathematical modelling to control.

Stigmergy, the indirect communication between agents of a swarm through dynamic environmental modifications, is a fundamental self-organization mechanism of animal swarms. Engineers have drawn inspiration from stigmergy to establish strategies for the coordination of swarms of robots and of mixed societies of robots and animals. Currently, all models of stigmergy are algorithmic, in the form of behavioural rules implemented at an individual level. A critical challenge for the understanding of stigmergic behaviour and translation of stigmergy to engineering is the lack of a holistic approach to determine which modifications of the environment are necessary to achieve desired behaviours for the swarm. Here, we propose a mathematical framework that rigorously describes the relationship between environmental modifications and swarm behaviour. Building on recent strides in continuification techniques, we model the swarm and environmental modifications as continua. This approach allows us to design the environmental modifications required for the swarm to behave as desired. Through analytical derivations and numerical simulations of one- and two-dimensional examples, we show that our framework yields the distribution of traces required to achieve a desired formation. Such an approach provides an adaptable framework for different implementation platforms, from robotic swarms to mixed societies of robots and animals.

Self-organizing broad network with frequency-domain analysis

The broad network (BN) based on random feature extraction has fast computational nature. However, it usually suffers from redundant features due to its randomization in dealing with massive samples, which brings the risk of overfitting. To overcome this problem, a self-organizing BN (SO-BN) is proposed in this article. First, several groups of polynomial-based fuzzy rules (P-FRs) are embedded into BN instead of the original feature nodes. Then, P-FR with the form of approximated bell functions has the capability to cope with the uncertainties of feature extraction. Second, a frequency domain parameter calculation algorithm is presented to update the parameters of P-FRs in SO-BN. Different from traditional randomization, P-FRs are shaped with frequency-domain analysis for achieving the representative features of samples. Third, an efficient self-organizing mechanism is built to adjust the structure of the enhancement layer dynamically. Then, the enhancement layer can be expanded and pruned rapidly to reduce the redundant feature as well as improve the performance of SO-BN. Finally, the proposed SO-BN is tested on two benchmark datasets and three real-world engineering applications, especially the prediction of sunspot numbers, electrical output and total phosphorus concentration. The results indicate that SO-BN can achieve superior prediction performance than other models.

Self-organization of mortal filaments and its role in bacterial division ring formation

Filaments in the cell commonly treadmill. Driven by energy consumption, they grow on one end while shrinking on the other, causing filaments to appear motile even though individual proteins remain static. This process is characteristic of cytoskeletal filaments and leads to collective filament self-organization. Here we show that treadmilling drives filament nematic ordering by dissolving misaligned filaments. Taking the bacterial FtsZ protein involved in cell division as an example, we show that this mechanism aligns FtsZ filaments in vitro and drives the organization of the division ring in living Bacillus subtilis cells. We find that ordering via local dissolution also allows the system to quickly respond to chemical and geometrical biases in the cell, enabling us to quantitatively explain the ring formation dynamics in vivo. Beyond FtsZ and other cytoskeletal filaments, our study identifies a mechanism for self-organization via constant birth and death of energy-consuming filaments.

Synergistic Aspects Of The Transformation Of Energy Security Management Mechanisms In Conditions Of Geopolitical Instability

The article systematizes the basic provisions of the concept of energy security, in which the emphasis is placed on uninterrupted access to energy sources, their diversification, environmental friendliness, and ensuring resistance to external threats. The content of the concept of «energy security», which acts as a system-forming element of national (economic, ecological, technical) security, orienting this system to the goals of sustainable energy development thanks to the effective use of fuel and energy resources in the context of ensuring economic growth, social progress, and environmental well-being, has been studied. It is proved that for the interpretation of the logic of energy development, it is advisable to use the system-synergistic approach, which explains the transformation of a complex system by passing bifurcation points, the formation of order attractors, and the emergence of self-organization mechanisms. Among the factors that determine the level of energy security, the geopolitical aspect associated with a wide variety of fluctuating influences that can bring the system out of equilibrium is highlighted in the first place. Any imbalance in the energy system directly affects the economic and social spheres, the state of the environment, as well as the international competitiveness of the state. Therefore, special attention is focused on the development of effective institutions, their consolidation in the daily activities of business entities that are part of the fuel and energy complex, and timely adaptation to changes in the operating environment. For the formation of attractors of sustainable energy development, it is necessary to apply effective management mechanisms that combine institutional and market components. Energy security is defined as a management object in which certain functional units, regulatory mechanisms, and algorithms for making and implementing management decisions are distinguished. The trends considered in the course of the study confirm the high energy interdependence of states in the conditions of globalization and, accordingly, the need to develop international energy security management mechanisms. As a result of combining the principles of flexibility, adaptability to modern geopolitical trends, requirements for socio-economic efficiency and environmental standards, on the one hand, and the characteristics of resistance, stability (to ensure national stability), on the other hand, a special regime of sustainable energy development at the level of individual states, integration associations and in the global dimension.

Self-organizing interval type-2 function-link fuzzy neural network control for uncertain manipulators under saturation: A predefined-time sliding-mode approach

Robotic manipulators have extensive applications in academic and industrial fields such as grabbing, welding, and machining. Nowadays, better tracking performance and faster transient response have been the fundamental demands in the field of manipulator control. However, robotic manipulators suffer from uncertainties due to various factors in real-world environments. Therefore, achieving satisfactory tracking performance for the manipulator in the presence of uncertainties is a pressing problem. Moreover, most existing control schemes struggle to determine the convergence time of the whole system and rely on specifically designed parameters via experience and prior knowledge, which leads to poor transferability and generalization. To address the abovementioned issues, a predefined-time controller based on a self-organizing interval type-2 function-link fuzzy neural network (IT2FLFNN) is proposed in this paper. Different from most existing fuzzy neural network (FNN) based control schemes, the proposed network starts from an empty rule base and it is constructed by a self-organizing mechanism during the online control process, which provides greater flexibility in terms of network structure and input partition. Also, a function-link network (FLN) is integrated into IT2FLFNN to enhance its convergence speed and rejection of uncertainties. Furthermore, to ensure the predefined-time convergence, a predefined-time sliding-mode control part is merged into the control framework and online learning laws for IT2FLFNN are established via the Lyapunov stability analysis. Finally, a comparative simulation and an experiment demonstrate the superiority of the proposed IT2FLFNN control scheme.

Interference mechanism of plasma self-organization in transparent dielectrics under the intense femtosecond laser pulse exposure

A new mechanism of plasma self-organization in transparent dielectrics with wide bandgap exposed to the intense tightly focused laser radiation was revealed, which causes the generation of 3D periodic ring structures with subwavelength period both along the laser pulse propagation and in the radial direction. The mechanism involves formation of dense plasma burst in the pre-focal region that provides efficient scattering of the incident wave. The interference of a plane incident laser wave in the focal region and a divergent reflected one will form the standing wave pattern with local minima and maxima of laser field both in the direction of the incident wave propagation and perpendicular to it producing the ring patterns of effective ionization regions in the dielectric volume. Analytical and numerical simulations of the process of laser wave scattering on a near-spherical plasma object with dimensions both smaller and larger than the laser radiation wavelength are performed to verify the proposed model.

Robust adaptive learning control using spiking-based self-organizing emotional neural network for a class of nonlinear systems with uncertainties

For second-order general nonlinear systems with uncertainties, a control scheme combining fractional-order fast terminal sliding mode control (FOFTSMC) and self-organizing emotional neural network (SOENN) is proposed and designed. Firstly, a novel emotional neural network which can approximate the uncertainties in nonlinear systems is constructed and introduced. Meanwhile, in order to optimize the network structure and reduce the computing burden, a novel spiking-based self-organizing mechanism is added. Then the FOFTSMC is designed for second-order general nonlinear systems, and the stability and finite time convergence is proved by Lyapunov theory. Besides, the FOFTSMC and SOENN are combined to form the final control scheme, and adaptive laws of the parameters are also designed. Finally, inverted pendulum and active power filter (APF) are selected as the research objects to carry out a series of simulations and experiments to validate and highlight the effectiveness and superiority of the proposed control scheme.

Cytoplasmic stirring by active carpets

Large cells often rely on cytoplasmic flows for intracellular transport, maintaining homeostasis, and positioning cellular components. Understanding the mechanisms of these flows is essential for gaining insights into cell function, developmental processes, and evolutionary adaptability. Here, we focus on a class of self-organized cytoplasmic stirring mechanisms that result from fluid-structure interactions between cytoskeletal elements at the cell cortex. Drawing inspiration from streaming flows in late-stage fruit fly oocytes, we propose an analytically tractable active carpet theory. This model deciphers the origins and three-dimensional spatiotemporal organization of such flows. Through a combination of simulations and weakly nonlinear theory, we establish the pathway of the streaming flow to its global attractor: a cell-spanning vortical twister. Our study reveals the inherent symmetries of this emergent flow, its low-dimensional structure, and illustrates how complex fluid-structure interaction aligns with classical solutions in Stokes flow. This framework can be easily adapted to elucidate a broad spectrum of self-organized, cortex-driven intracellular flows.

Cogwheel Mechanism of Helical Self-Organization is Thermodynamically Controlled, Self-Repairing, and Universal.

The cogwheel mechanism of helical self-organization, reported by us, generates columns with the alkyl chains of their components parallel to the column axis. This mechanism disregards the enantiomeric purity of constituents and, under suitable design, provides the fastest rate of helical self-organization. Here, we investigate the supramolecular structure of a thermodynamically controlled helical self-organization system. Unexpectedly, we found that this system follows a cogwheel mechanism of helical self-organization that does not contain the two key parameters of the cogwheel mechanism: the length of the alkyl group of the self-assembling dendron identical to the helical half-pitch (hhp) of the column and the presence of chiral branches pointing toward the column center. Unpredictably, we uncovered that the presence of chiral branching points and strict alkyl chain lengths is not a requirement of the cogwheel mechanism. A self-repairing process provides access to a constant hhp via a shorter and longer alkyl chain length than the originally exact demanded value, which together with the lack of branching point(s) demonstrates the universality of the cogwheel mechanism of helical self-organization. Applications derived from this concept are envisioned.

Features of creative self-development of adolescents with intellectual disabilities by means of theatrical art

Importance. The problem of creative self-development of adolescents with disabilities is very relevant, since the social adaptation of such adolescents implies the complexity of interaction with others, is characterized by an unformed skills of self-knowledge, self-organization, self-regulation, and other mechanisms of self-development. In particular, the creative self-development of adolescents with intellectual disabilities is associated with the development of thinking, motor skills, and communicative functions. This is possible through amateur theater as a form of social and pedagogical work with young people with disabilities. The purpose of the study is to determine the role and pedagogical possibilities of amateur theatrical art as a means of creative self–development of adolescents with disabilities, taking into account the specifics of adolescents with intellectual disability (mental retardation).Research Methods. In the course of the research, such theoretical methods as generalization, comparison, etc. were used, domestic psychological and pedagogical works in the field of theater pedagogy were studied, empirical methods were used – understanding the experience of working with participants of the psychotherapeutic theater “We”.Results and Discussion. It is revealed and substantiated that amateur theater is a means of creative development and self-development of a personality, that is, an environment where activities aimed at the personal development of adolescents with disabilities can be fully realized on the basis of the existing personal potential in accordance with the norms of morality and cultural context accepted in society. The pedagogical possibilities of theatrical art, realized in specific forms of work (trainings, sketches, effective analysis of a play, staged work, etc.) and used at various stages of organizational and creative activity of an amateur theater group, contribute to the development of appropriate skills of self-knowledge and self-organization, thinking, and communicative abilities of adolescents with intellectual disabilities (mental retardation).Conclusions. The application of the research results contributes to the development of new methods and means of pedagogical work with young people with disabilities, the formation of an effective creative environment for their creative self-development and social adaptation.

A Conception of Collaborative Decision Support Systems: Approach and Platform Architecture

The paper describes a general conception of collaborative decision support systems, in which teams providing decision support a) are formed flexibly in accordance with the problem and b) consist of both human experts and intelligent agents implementing AI methods and techniques. An analysis of the key problems of creating collaborative decision support systems based on the collaboration of humans and AI is carried out, the following problems are highlighted: ensuring interoperability (mutual understanding) between heterogeneous team members, reconciling differing positions of participants, ensuring trust between participants, ensuring the effectiveness of joint actions planning and maintaining a balance between predefined workflows and self-organization. Principles for constructing such systems have been formed, offering solutions to the identified problems. In particular, it is proposed to employ an ontology-oriented representation of information about the problem (in the form of multi-aspect ontology), a set of methods for monitoring team activities, reputation scheme, elements of explainable AI, as well as mechanisms of limited self-organization. The proposed concept forms the basis of a software platform for the development of collaborative decision support systems, the main architectural provisions of which are also presented in the paper. The use of the platform is illustrated by an example from the field of rational management of road infrastructure and the creation of a collaborative DSS for the development of measures to reduce road accidents.

Ideology and practice of planning fundamental research in the USSR (1920-1930)

Analysis of government regulation of the academic sphere in the USSR is a highly relevant area of research, enabling identification of the positive and negative aspects of the Soviet scientific model. The purpose of the study is to identify the main patterns of the transition to directive planning of academic science in the RSFSR/USSR in the 1920s - 1930s. In the context of this transformation of Soviet academic science, it is important to consider not only the institutional decisions of the authorities, but also the socio-psychological, as well as ideological motives that determined this transformation, which influenced the operation of the scientific community. This task methodologically required an interdisciplinary approach to its solution. This analysis is at the intersection of several related areas of research: history of science, science studies, and history of economics. The work employed comparative-historical, historical-cultural, and statistical methods to identify significant patterns of the phenomenon being studied. Methodologically, this is close to source studies and semiotic analysis. Concepts formed and institutionalized in the paradigm of directive planning of basic science - “scientist”, “thematic plan”, “thematic development”, “research plant” - form a contextual layer. The planning of basic science was conceived by its ideologists as a product of the industrial world. But, paradoxically, the ideology and methodology of directive planning implanted in theoretical science gave the opposite results - epistemological apathy of scientists, reduction, if not extinction, of huge areas of research activities. The state's attempt to adapt basic science to address strictly applied problems of industrialization ultimately resulted in a mere semblance of “planned science”. However, the internal compensation mechanisms of self-organization of the scientific community turned out to be quite effective in a long-term perspective, even under the conditions of “directive planning”. The conducted historical analysis allows us to draw significant conclusions in the context of the formation of Russian scientific policy at the present stage.

Test of the negative feedback hypothesis of colony size sensing in social insects.

Social insects can sense colony size-even without visual information in a dark environment. How they achieve this is yet largely unknown. We empirically tested a hypothesis on the proximate mechanism using ant colonies. In Diacamma colonies, the monogynous queen is known to increase the effort devoted to queen pheromone transmission behaviour (patrolling) as the colony grows, as if she perceives colony size. The negative feedback hypothesis assumes that, through repeated physical contact with workers, the queen monitors the physiological state (fertility) of workers and increases her patrolling effort when she encounters more fertile workers. Supporting this hypothesis, we found that the queen increased her patrolling effort in response to a higher ratio of fertile workers under the experimental condition of constant colony size. Furthermore, chemical analyses and bioassays suggested that cuticular hydrocarbons have queen pheromone activity and can mediate the observed queen-worker communication of fertility state. Such a self-organizing mechanism of sensing colony size may also operate in other social insects living in small colonies.