Hysteresis-Loop Criticality in Disordered Ferromagnets–A Comprehensive Review of Computational Techniques

Disordered ferromagnets with a domain structure that exhibit a hysteresis loop when driven by the external magnetic field are essential materials for modern technological applications.Therefore,the understanding and potential for controlling the hysteresis phenomenon in thesematerials,especially concerning the disorder-induced critical behavior on the hysteresis loop,have attracted significant experimental,theoretical,and numerical research efforts.We review the challenges of the numerical modeling of physical phenomena behind the hysteresis loop critical behavior in disordered ferromagnetic systems related to the non-equilibriumstochastic dynamics of domain walls driven by external fields.Specifically,using the extended Random Field Ising Model,we present different simulation approaches and advanced numerical techniques that adequately describe the hysteresis loop shapes and the collective nature of the magnetization fluctuations associated with the criticality of the hysteresis loop for different sample shapes and varied parameters of disorder and rate of change of the external field,as well as the influence of thermal fluctuations and demagnetizing fields.The studied examples demonstrate how these numerical approaches reveal newphysical insights,providing quantitativemeasures of pertinent variables extracted from the systems’simulated or experimentally measured Barkhausen noise signals.The described computational techniques using inherent scale-invariance can be applied to the analysis of various complex systems,both quantum and classical,exhibiting non-equilibrium dynamical critical point or self-organized criticality.

Self-organized Criticality Model for Ocean Internal Waves

In this paper, we present a simple spring-block model for ocean internal waves based on the self-organized criticality （SOC）. The oscillations of the water blocks in the model display power-law behavior with an exponent of -2 in the frequency domain, which is similar to the current and sea water temperature spectra in the actual ocean and the universal Garrett and Munk deep ocean internal wave model [Geophysical Fluid Dynamics 2 （1972） 225; J. Geophys. Res. 80 （1975） 291]. The influence of the ratio of the driving force to the spring coefficient to SOC behaviors in the model is also discussed.

Self-Organized Criticality Analysis of Earthquake Model Based on Heterogeneous Networks

The original Olami-Feder-Christensen （OFC） model, which displays a robust power-law behavior, is a quasistatic two-dimensional version of the Burridge-Knopoff spring-block model of earthquakes. In this paper, we introduce a modified OFC model based on heterogeneous network, improving the redistribution rule of the original model. It can be seen as a generalization of the originM OFC model We numerically investigate the influence of the parameters θandβ, which respectively control the intensity of the evolutive mechanism of the topological growth and the inner selection dynamics in our networks, and find that there are two distinct phases in the parameter space （θ,β）. Meanwhile, we study the influence of the control parameter a either. Increasing a, the earthquake behavior of the model transfers from local to global.

A Modified Earthquake Model of Self-Organized Criticality on Small World Networks

A modified Olami Feder-Christensen model of self-organized criticality on a square lattice with the properties of small world networks has been studied.We find that our model displays power-law behavior and the exponent τ of the model depends on φ,the density of long-range connections in our network.

Self-Organized Criticality Theory Model of Thermal Sandpile

A self-organized criticality model of a thermal sandpile is formulated for the first time to simulate the dynamic process with interaction between avalanche events on the fast time scale and diffusive transports on the slow time scale. The main characteristics of the model are that both particle and energy avalanches of sand grains are considered simultaneously. Properties of intermittent transport and improved confinement are analyzed in detail. The results imply that the intermittent phenomenon such as blobs in the low confinement mode as well as edge localized modes in the high confinement mode observed in tokamak experiments are not only determined by the edge plasma physics, but also affected by the core plasma dynamics.

Engineering Quantum Criticality for Quantum Dot Power Harvesting

Coupling of quantum-dot circuits to microwave photons enables us to investigate photon-assisted quantum transport.Here,we revisit this typical circuit quantum electrodynamical setup by introducing the Kerr nonlinearity of photons.By exploiting quantum critical behavior,we propose a powerful scheme to control the power-harvesting efficiency in the microwave regime,where the driven-dissipative optical system acts as an energy pump.It drives electron transport against a load in the quantum-dot circuit.The energy transfer and,consequently,the harvesting efficiency are enhanced near the critical point.As the critical point moves towards to low input power,high efficiency within experimental parameters is achieved.Our results complement fundamental studies of photon-to-electron conversion at the nanoscale and provide practical guidance for designs of integrated photoelectric devices through quantum criticality.

Effects of Vertex Activity and Self-organized Criticality Behavior on a Weighted Evolving Network

Effects of vertex activity have been analyzed on a weighted evolving network.The network is characterized by the probability distribution of vertex strength,each edge weight and evolution of the strength of vertices with different vertex activities.The model exhibits self-organized criticality behavior.The probability distribution of avalanche size for different network sizes is also shown.In addition,there is a power law relation between the size and the duration of an avalanche and the average of avalanche size has been studied for different vertex activities.

Self-organized Criticality in an Earthquake Model on Random Network

A simplified Olami-Feder-Christensen model on a random network has been studied. We propose a new toppling rule -- when there is an unstable site toppling, the energy of the site is redistributed to its nearest neighbors randomly not averagely. The simulation results indicate that the model displays self-organized criticality when the system is conservative, and the avalanche size probability distribution of the system obeys finite size scaling. When the system is nonconservative, the model does not display scaling behavior. Simulation results of our model with different nearest neighbors q is also compared, which indicates that the spatial topology does not alter the critical behavior of the system.

Landslide and Basin Self-organized Criticality in the Lushan Hot Spring Area

Defining a basin under a critical state （or a self-organized criticality） that has the potential to initiate landslides, debris flows, and subsequent sediment disasters, is a key issue for disaster prevention. The Lushan Hot Spring area in Nantou County, Taiwan, suffered serious sediment disasters after typhoons Sinlaku and Jangmi in aoo8, and following Typhoon Morakot in 2009. The basin＇s internal slope instability after the typhoons brought rain was examined using the landslide frequency-area distribution. The critical state indices attributed to landslide frequency-area distribution are discussed and the marginally unstable characteristics of the study area indicated. The landslides were interpreted from Spot 5 images before and after disastrous events. The results of the analysis show that the power-law landslide frequency-area curves in the basin for different rainfall-induced events tend to coincide with a single line. The temporal trend of the rainfall- induced landslide frequency-area distribution shows 1If noise and scale invariance. A trend exists for landslide frequency-area distribution in log-log space for larger landslides controlled by the historical maximum accumulated rainfall brought by typhoons. The unstable state of the basin, including landslides, breached dams, and debris flows, are parts of the basin＇s self-organizing processes. The critical state of landslide frequency-area distribution could be estimated by a critical exponent of 1.0. The distribution could be used for future estimation of the potential landslide magnitude for disaster mitigation and to identify the current state of a basin for management.

Self-organized Criticality in an Integrate-and-Fire Neuron Model Based on Modified Aging Networks

Based on an integrate-and-fire mechanism, we investigate self-organized criticality of a simple neuron model on a modified BA scale-free network with aging nodes. In our model, we find that the distribution of avalanche size follows power-law behavior. The critical exponent τ depends on the aging exponent α. The structures of the network with aging of nodes change with an increase of α. The different topological structures lead to different behaviors in models of integrate-and-fire neurons.

Self-organized Criticality in Hierarchical Brain Network

It is shown that the cortical brain network of the macaque displays a hierarchically clustered organizationand the neuron network shows small-world properties.Now the two factors will be considered in our model and thedynamical behavior of the model will be studied.We study the characters of the model and find that the distribution ofavalanche size of the model follows power-law behavior.

Self-Organized Criticality in a Simple Neuron Model Based on Scale-Free Networks

A simple model for a set of interacting idealized neurons in scale-free networks is introduced. The basic elements of the model are endowed with the main features of a neuron function. We find that our model displays powerlaw behavior of avalanche sizes and generates long-range temporal correlation. More importantly, we find different dynamical behavior for nodes with different connectivity in the scale-free networks.

Self-organized Criticality in a Modified Evolution Model on Generalized Barabasi-Albert Scale-Free Networks

A modified evolution model of self-organized criticality on generalized Barabasi-Albert （GBA）.scale-free networks is investigated. In our model, we find that spatial and temporal correlations exhibit critical behaviors. More importantly, these critical behaviors change with the parameter b, which weights the distance in comparison with the degree in the GBA network evolution.

Self-organized Criticality and Synchronization in a Pulse-coupled Integrate-and-Fire Neuron Model Based on Small World Networks＊

A lattice model for a set of pulse-coupled integrate-and-fire neurons with small world structure is introduced.We find that our model displays the power-law behavior accompanied with the large-scale synchronized activities among the units. And the different connectivity topologies lead to different behaviors in models of integrate-and-fire neurons.

Effects of Aging and Self-organized Criticality in a Pulse-Coupled Integrate-and-Fire Neuron Model Based on Small World Networks

Effects of aging and self-organized criticality in a pulse-coupled integrate-and-fire neuron model based on small world networks have been studied. We give the degree distribution of aging network, average shortest path length, the diameter of our network, and the clustering coefficient, and find that our neuron model displays the power-law behavior, and with the number of added links increasing, the effects of aging become smaller and smaller. This shows that if the brain works at the self-organized criticality state, it can relieve some effects caused by aging.

基于IAHP-CRITIC二维云模型的舰船电力系统韧性评价

舰船电力系统是舰船正常运行的关键,具有高度的复杂性和模糊性,导致难以对其韧性做出准确、客观地评价。对此,基于对舰船电力系统主要任务的分析,对舰船电力系统韧性评价指标体系进行构建,采用区间层次分析法(interval analytic hierarchy process,IAHP)和层间相关性准则重要性法(criteria importance though intercrieria correlation,CRITIC)分别求解评价指标体系的主、客观权重,并运用改进博弈论方法确定组合权重,降低权重计算的主观性和随机性。结合二维云模型从防御能力和恢复能力两个维度对舰船电力系统韧性进行评价,更为全面、客观地反映舰船电力系统韧性。示例表明,所提方法能够有效解决舰船电力系统韧性评价中的随机性和不确定性问题,有利于得到更为准确、客观的评价结果。

Electrical Tree Simulation Based on the Self-Organization Criticality

So far much effort has been made to understand the development of electrical treeing. For the simulation based study of electrical treeing, the most common method is to apply DBM stochastic model to simulate the growing of electrical treeing patterns. Previous simulation results showed that this stochastic model is capable of simulating the real electrical treeing patterns in a point-to-plane electrode system. However, this model only allows the tree channels to propagate on equipotential lines proportional to local electrical field. Therefore, it is necessary to develop a novel stochastic model to simulate the electrical patterns in order to get a good agreement with experimental results.

The Research of Transmission Network Planning Based on System’s Self-organized Criticality

This paper presents a new line importance degree evaluation index for the propagation of cascading failures, which is used to quantify transmission lines for cascade spread. And propose an improved capital matching model, according to the results of the evaluation, to enhanced robustness of the power system. The simulation results proved that in the case of the same system, the new model can inhibit cascade spread, reduce the probability of large-scale blackouts.

Tilting homeostatic and dyshomeostatic microglial balance in health and disease:transforming growth factor-beta1 as a critical protagonist

Adult microglia,by continuously sensing changes in their environment and communicating with nearly all brain cell types,are considered to be the immune sentinels of the brain.In the healthy central nervous system(CNS),microglia display a unique molecular homeostatic signature(i.e.,Tmem119,P2ry12,Sall1,Siglech,Gpr34,and Hexb)(Figure 1A).

Unlocking hypoglycemia–associated brain microvascular dysfunction:critical insights from proteomic analysis

Hypoglycemia-a critical complication linked to worsened brain function in diabetic subjects:Hypoglycemia is characterized by a decline in circulatory glucose levels below sta nda rd physiological thresholds.Mild hypoglycemia,classified as level 1 hypoglycemia,is defined by blood glucose levels below 70 mg/dL and can be effectively addressed through carbohydrate intake.Severe hypoglycemia,denoted by blood glucose levels less than 54 mg/dL,poses a life-threatening risk if left untreated.Individuals with type 1 and type 2 diabetes undergoing insulin treatment are particularly susceptible to hypoglycemia due to impaired counterregulatory mechanisms.