Self-organized Criticality Research Articles

From Cell States to Cell Fates: Control of Cell State Transitions.

We examine the coordinated behavior of thousands of genes in cell fate transitions through genome expression as an integrated dynamical system using theconcepts of self-organized criticality and coherent stochastic behavior. To quantify theeffects of thecollective behavior of genes, we adopted the flux balance approach and developed it in a new tool termed expression flux analysis (EFA). Here we describe this tool and demonstrate how its application to specific experimental genome-wide expression data provides new insights into the dynamics of the cell-fate transitions. Particularly, we show that in cell fate change, specific stochastic perturbations can spread over the entire system to guide distinct cell fate transitions through switching cyclic flux flow in the genome engine. Utilization of EFA enables us to elucidate a unified genomic mechanism for when and how cell-fate change occurs through critical transitions.

Controls on calving at a large Greenland tidewater glacier: stress regime, self-organised criticality and the crevasse-depth calving law

Abstract We investigate the physical basis of the crevasse-depth (CD) calving law by analysing relationships between glaciological stresses and calving behaviour at Sermeq Kujalleq (Store Glacier), Greenland. Our observations and model simulations show that the glacier has a stable position defined by a compressive arch between lateral pinning points. Ice advance beyond the arch results in calving back to the stable position; conversely, if melt-undercutting forces the ice front behind the stable position, it readvances because ice velocities exceed subaqueous melt rates. This behaviour is typical of self-organising criticality, in which the stable ice-front position acts as an attractor between unstable super-critical and sub-critical regimes. This perspective provides strong support for a ‘position-law’ approach to modelling calving at Sermeq Kujalleq, because any calving ‘rate’ is simply a by-product of how quickly ice is delivered to the critical point. The CD calving law predicts ice-front position from the penetration of surface and basal crevasse fields, and accurately simulates super-critical calving back to the compressive arch and melt-driven calving into the sub-critical zone. The CD calving law reflects the glaciological controls on calving at Sermeq Kujalleq and exhibits considerable skill in simulating its mean position and seasonal fluctuations.

Scale Invariance in Gamma-Ray Flares of the Sun and 3C 454.3

Using the gamma-ray flare samples of the Sun and 3C 454.3 observed by the Fermi telescope, we investigate the statistical properties of sizes including fluence (energy), peak flux (luminosity), duration time, and waiting time in this work. We find that the cumulative distribution of the fluctuations of these sizes follow well the Tsallis q-Gaussian function. The obtained q values from q-Gaussian distribution remain stable around 2 without any significant change, implying that there is a scale invariance structure in gamma-ray flares of the Sun and 3C 454.3. This scale invariance characteristics of the Sun and 3C 454.3 indicated by q values are also comparable to those of earthquakes, soft gamma repeaters, fast radio burst (FRB 20121102), and X-ray flares of gamma-ray bursts. On top of that, we verify the relationship between q values and the power-law indices α from the size frequency distributions, which is expressed as q = (α + 2)/α. These statistical findings could be well explained within the physical framework of a self-organizing criticality system.

Collective Behaviour of Crimes In Cyberspace

Aim. The Convention of Cybercrimes (ETS No. 185) singned in Budapest, Hungary in 2001 created the unification of cyber-crimes and had impact on national criminal codes across the world. Therefore I started to colaborate with the National Police Headquarters from Warsaw to investigate direct and indirect connections between cyber-crimes defined by the Convention and the Criminal Code in Poland because statistical analysis of cyber-crimes were not thus far satisfactory .
 Methods. Statistical analysis of data collected in time series may lead to computer correlation coefficients between crimes and detect a hierarchical structure of selected cyber-crimes
 Results. According to correlation coefficients between crimes, the behaviour of independent cyber criminals is collective and might lead to self-organised criticality. Correlations and anticorrelations between crimes are extremely strong. Therefore crimes may exist collectively or may exclude each other
 Conclusion. Hierarchical structure of crimes according to the MST seems to be extremely logical and might lead to a perfect crime plans or prevention against cyber-crimes as well. Therefore the sensitive details given by graph of the MST had to be censored.

Integrative biology for integrative medicine: A complete approach

BackgroundIndia's AYUSH systems of medicine, Ayurveda, Yoga and Naturopathy, Unani, Siddha and Sowa-Rigpa, and Homeopathy, use natural self-healing abilities of body and mind. Their ways to treat non-communicable diseases reduce use of modern drugs with their side-effects. Scientific acceptance requires them to be explained from a modern biological perspective. This paper indicates how to achieve such an integrative approach, using aspects of biology not yet taught in medical schools. MethodsA new, ‘Sandwich Model’ of biology is introduced that includes holistic epigenetic regulation; also, complexity biology's concept of self-organized criticality; a systems treatment of organism function from Ayurveda; and Ayurveda's six stages of etiology, Shadkriyakala. ResultsMolecular biology is upgraded by the sandwich model's layer of epigenetics, leading to a new, scientific definition of health as optimized regulation. Fractal Physiology then expands this to explain self-healing, used in all AYUSH systems. Ayurveda contributes in two ways: its systems approach yields a holistic understanding of organism functioning, while Shadkriyakala improves our understanding of pathophysiology. DiscussionThese additions create an integrative biology; modern biology expands to include AYUSH systems' concepts. It provides a scientific basis for India's plan for integrative medical education, with AYUSH systems treated as equal to modern medicine.

Dragon kings in self-organized criticality systems

Dragon kings in self-organized criticality systems

Statistical Properties of X-Ray Bursts from SGR J1935+2154 Detected by Insight-HXMT

As one class of the most important objects in the universe, magnetars can produce a lot of different frequency bursts including X-ray bursts. In Cai et al., 75 X-ray bursts produced by magnetar SGR J1935+2154 during an active period in 2020 are published, including the duration and net photon counts of each burst, and waiting time based on the trigger time difference. In this paper, we utilize the power-law model, , to fit the cumulative distributions of these parameters. It can be found that all the cumulative distributions can be well fitted, which can be interpreted by a self-organizing criticality theory. Furthermore, we check whether this phenomenon still exists in different energy bands and find that there is no obvious evolution. These findings further confirm that the X-ray bursts from magnetars are likely to be generated by some self-organizing critical process, which can be explained by a possible magnetic reconnection scenario in magnetars.

Viscoelastic Slider Blocks as a Model for a Seismogenic Fault.

In this work, a model is proposed to examine the role of viscoelasticity in the generation of simulated earthquake-like events. This model serves to investigate how nonlinear processes in the Earth's crust affect the triggering and decay patterns of earthquake sequences. These synthetic earthquake events are numerically simulated using a slider-block model containing viscoelastic standard linear solid (SLS) elements to reproduce the dynamics of an earthquake fault. The simulated system exhibits elements of self-organized criticality, and results in the generation of avalanches that behave similarly to naturally occurring seismic events. The model behavior is analyzed using the Epidemic-Type Aftershock Sequence (ETAS) model, which suitably represents the observed triggering and decay patterns; however, parameter estimates deviate from those resulting from natural aftershock sequences. Simulated aftershock sequences from this model are characterized by slightly larger p-values, indicating a faster-than-normal decay of aftershock rates within the system. The ETAS fit, along with realistic simulated frequency-size distributions, supports the inclusion of viscoelastic rheology to model the seismogenic fault dynamics.

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

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

Asymptotics and criticality for a space-dependent branching process

We investigate a non-conservative semigroup determined by a branching process tracing the evolution of particles moving in a domain in . When a particle is killed at the boundary, a new generation of particles with mean number is born at a random point in the domain. Between branching, the particles are driven by a diffusion process with Dirichlet boundary conditions. According to the sign of , we distinguish super/sub-critical regimes and determine the exact exponential rate for the total number of particles , with depending explicitly on . We prove the Yaglom limit , where the quasi-stationary distribution ν is determined by the resolvent of the Dirichlet kernel at the point . The main application is in particle systems, where the normalization of the semigroup by its total mass gives the hydrodynamic limit of the Bak-Sneppen branching diffusions (BSBD). Since ν is the asymptotic profile under equilibrium, and the family of quasi-stationary distributions ν is indexed by , the model provides an explicit example of self-organized criticality.

Self-adapting infectious dynamics on random networks.

Self-adaptive dynamics occurs in many fields of research, such as socio-economics, neuroscience, or biophysics. We consider a self-adaptive modeling approach, where adaptation takes place within a set of strategies based on the history of the state of the system. This leads to piecewise deterministic Markovian dynamics coupled to a non-Markovian adaptive mechanism. We apply this framework to basic epidemic models (SIS, SIR) on random networks. We consider a co-evolutionary dynamical network where node-states change through the epidemics and network topology changes through the creation and deletion of edges. For a simple threshold base application of lockdown measures, we observe large regions in parameter space with oscillatory behavior, thereby exhibiting one of the most reduced mechanisms leading to oscillations. For the SIS epidemic model, we derive analytic expressions for the oscillation period from a pairwise closed model, which is validated with numerical simulations for random uniform networks. Furthermore, the basic reproduction number fluctuates around one indicating a connection to self-organized criticality.

Avalanches and the Distribution of Reconnection Events in Magnetized Circumstellar Disks

Cosmic rays produced by young stellar objects can potentially alter the ionization structure, heating budget, chemical composition, and accretion activity in circumstellar disks. The inner edges of these disks are truncated by strong magnetic fields, which can reconnect and produce flaring activity that accelerates cosmic radiation. The resulting cosmic rays can provide a source of ionization and produce spallation reactions that alter the composition of planetesimals. These reconnection and particle acceleration processes are analogous to the physical processes that produce flaring in and the heating of stellar coronae. Flaring events on the surface of the Sun exhibit a power-law distribution of energy, reminiscent of those measured for earthquakes and avalanches. Numerical lattice reconnection models are capable of reproducing the observed power-law behavior of solar flares under the paradigm of self-organized criticality. One interpretation of these experiments is that the solar corona maintains a nonlinear attractor—or “critical”—state by balancing energy input via braided magnetic fields and output via reconnection events. Motivated by these results, we generalize the lattice reconnection formalism for applications in the truncation region of magnetized disks. Our numerical experiments demonstrate that these nonlinear dynamical systems are capable of both attaining and maintaining criticality in the presence of Keplerian shear and other complications. The resulting power-law spectrum of flare energies in the equilibrium attractor state is found to be nearly universal in magnetized disks. This finding indicates that magnetic reconnection and flaring in the inner regions of circumstellar disks occur in a manner similar to the activity on stellar surfaces. These results, in turn, have ramifications for the spallation-driven injection of radionuclides in planetesimals, disk ionization, and the subsequent planetary formation process.

Relationship between structural heterogeneity and serrated flow in nanoscale phase separated Zr-Cu-Fe-Al bulk metallic glasses

In this work, the relationship between structural heterogeneity and serrated flow in nanoscale phase separated Zr-Cu-Fe-Al bulk metallic glasses with different plasticity was investigated. The results showed that liquid-liquid phase separation would occur during rapid cooling of Zr59(Cu1-xFex)33Al8 (x = 0.4 and 0.5) alloys, resulting in the microstructure formation of amorphous FeZr-rich nanoparticles embedded in the amorphous CuZr-rich matrix. The compression test and statistical analysis indicated that serration dynamics transforms from a chaotic state with a characteristic length scale of stress drop to a self-organized critical (SOC) state with the increase of the atomic ratio of Cu to Fe. This transformation is ascribed to the increase of the number of nucleation sites for shear transformation zones with the increase of structural heterogeneity, which is conducive to the formation of multiple shear bands. This work will be helpful to understand the relationship between the microstructure and deformation behavior.

Observation of long-radial-range-correlation in turbulence in high-collisionality high-confinement plasmas on DIII-D

We report on the observation of spatially asymmetric turbulent structures with a long radial correlation length in the core of high-collisionality H-mode plasmas on DIII-D tokamak. These turbulent structures develop from shorter wavelength turbulence and have a radially elongated structure. The envelope of turbulence spans a broad radial range in the mid-radius region, leading to streamer-like transport events. The underlying turbulence is featured by intermittency, long-term memory effect, and the characteristic spectrum of self-organized criticality. The amplitude and the radial scale increase substantially when the shearing rate of the mean flow is reduced below the turbulent scattering rate. The enhanced long-radial-range-correlated (LRRC) transport events are accompanied by apparent degradation of normalized energy confinement time. The emergence of such LRRC transport events may serve as a candidate explanation for the degrading nature of H-mode core plasma confinement at high collisionality on DIII-D tokamak.

Cell-autonomous diversification in bacteria arises from calcium dynamics self-organizing at a critical point.

How dynamic bacterial calcium is regulated, with kinetics faster than typical mechanisms of cellular adaptation, is unknown. We discover bacterial calcium fluctuations are temporal-fractals resulting from a property known as self-organized criticality (SOC). SOC processes are poised at a phase transition separating ordered and chaotic dynamical regimes and are observed in many natural and anthropogenic systems. SOC in bacterial calcium emerges due to calcium channel coupling mediated via membrane voltage. Environmental or genetic perturbations modify calcium dynamics and the critical exponent suggesting a continuum of critical attractors. Moving along this continuum alters the collective information capacity of bacterial populations. We find that the stochastic transition from motile to sessile lifestyle is partially mediated by SOC-governed calcium fluctuations through the regulation of c-di-GMP. In summary, bacteria co-opt the physics of phase transitions to maintain dynamic calcium equilibrium, and this enables cell-autonomous population diversification during surface colonization by leveraging the stochasticity inherent at a boundary between phases.

Investigating structural and functional aspects of the brain’s criticality in stroke

This paper addresses the question of the brain’s critical dynamics after an injury such as a stroke. It is hypothesized that the healthy brain operates near a phase transition (critical point), which provides optimal conditions for information transmission and responses to inputs. If structural damage could cause the critical point to disappear and thus make self-organized criticality unachievable, it would offer the theoretical explanation for the post-stroke impairment of brain function. In our contribution, however, we demonstrate using network models of the brain, that the dynamics remain critical even after a stroke. In cases where the average size of the second-largest cluster of active nodes, which is one of the commonly used indicators of criticality, shows an anomalous behavior, it results from the loss of integrity of the network, quantifiable within graph theory, and not from genuine non-critical dynamics. We propose a new simple model of an artificial stroke that explains this anomaly. The proposed interpretation of the results is confirmed by an analysis of real connectomes acquired from post-stroke patients and a control group. The results presented refer to neurobiological data; however, the conclusions reached apply to a broad class of complex systems that admit a critical state.

Sandpile-simulation-based graph data model for MVD generative design of shield tunnel lining using information entropy

BIM standard development is central to the performance and behavior of BIM model application across transmission, visualization, and information management perspectives. Tremendous effort has been made to ease the implementation of IFC data model in practice. Yet, the complexity of IFC data model hurdles the implementation of the import and export functionality by software vendors. To overcome this, buildingSMART introduced the concept of Model View Definitions to define which parts of an IFC data model need to be implemented for a specific data exchange scenario. With such, the certification of compatibility for software products with the IFC standard is formed. The Model View Definition is use case orientated to determine whether the specific information should be included in an IFC partial model. With the creation of ad-hoc, project-specific Exchange Requirements increasing, associated MVD development requires much more work to incorporate standard development. To resolve this issue, this paper attempts to exploit the potential of information entropy which has proven itself extremely crucial in many other industries in terms of information management, and then integrates it with sandpile simulation to propose a Top-down hierarchy to structure as well as interpret IFC partial model via Model View Definition. The proposed information entropy shifted MVD development approach would manage to unify the MVD development process that enables the reduction on confusion for various end users, specific organization, or project needs. Moreover, to better translate the BIM standard topology into sandpile simulations, a new notion system is proposed. Sandpile simulations are further implemented to prove their applicability, during the simulation, self-organized criticality is identified, and the existence of chaos is observed.

Synchronization between Attractors: Genomic Mechanism of Cell-Fate Change.

Herein, we provide a brief overview of complex systems theory approaches to investigate the genomic mechanism of cell-fate changes. Cell trajectories across the epigenetic landscape, whether in development, environmental responses, or disease progression, are controlled by extensively coordinated genome-wide gene expression changes. The elucidation of the mechanisms underlying these coherent expression changes is of fundamental importance in cell biology and for paving the road to new therapeutic approaches. In previous studies, we pointed at dynamic criticality as a plausible characteristic of genome-wide transition dynamics guiding cell fate. Whole-genome expression develops an engine-like organization (genome engine) in order to establish an autonomous dynamical system, capable of both homeostasis and transition behaviors. A critical set of genes behaves as a critical point (CP) that serves as the organizing center of cell-fate change. When the system is pushed away from homeostasis, the state change that occurs at the CP makes local perturbation spread over the genome, demonstrating self-organized critical (SOC) control of genome expression. Oscillating-Mode genes (which normally keep genome expression on pace with microenvironment fluctuations), when in the presence of an effective perturbative stimulus, drive the dynamics of synchronization, and thus guide the cell-fate transition.

Growth-induced crises and transitions in the governance of firm organizations

This paper discusses why organizational growth can cause crises in the governance of firms, how such crises typically unfold, and what options for responding they leave for management. More specifically, focus is on growth-induced changes in how the governance of an organization coordinates its members on, and motivate them to contribute to, the pursuit of the common purpose. As outlined by means of two distinct examples, governance approaches differ with respect to the solution of coordination and motivation problems. Nonetheless, when the organization size grows, adaptations in the firm members’ cognitive and motivational attitudes occur and tend to similarly undermine the governance of the organization. As a consequence, confusion, frictions, and internal rivalries increase and work effort declines. The unfolding of such crises is shown to be a case of a self-organizing criticality, a unique feature of nonlinear dynamics. Once the crisis has emerged, the cognitive and motivational conditions characterizing the outmoded governance approach constrain the options for making a transition to one that is better suited for the growing number of employees. Failure to accomplish such a transition results in any case in a state of muddling through with an outmoded governance approach that jeopardizes profitability and, in the longer run, the existence of the firm.

Noise and spike-time-dependent plasticity drive self-organized criticality in spiking neural network: Toward neuromorphic computing

Self-organized criticality (SoC) may optimize information transmission, encoding, and storage in the brain. Therefore, the underlying mechanism of the SoC provides significant insight for large-scale neuromorphic computing. We hypothesized that noise and stochastic spiking plays an essential role in SoC development in spiking neural networks (SNNs). We demonstrated that under appropriate noise levels and spike-time-dependent plasticity (STDP) parameters, an SNN evolves a SoC-like state characterized by a power-law distribution of neuronal avalanche size in a self-organized manner. Consistent with the physiological findings, the development of SNN was characterized by a transition from a subcritical state to a supercritical state and then to a critical state. Excitatory STDP with an asymmetric time window dominated the early phase of development; however, it destabilized the network and transitioned to the supercritical state. Synchronized bursts in the supercritical state enable inhibitory STDP with a symmetric time window, induce the development of inhibitory synapses, and stabilize the network toward the critical state. This sequence of transitions was observed when the appropriate noise level and STDP parameters were set to the initial conditions. Our results suggest that noise or stochastic spiking plays an essential role in SoC development and self-optimizes SNN for computation. Such neural mechanisms of noise harnessing would offer insight into the development of energy-efficient neuromorphic computing.