scholarly journals Resilience Design of Healthcare Resources Supply Network Based on Self-Organized Criticality

Healthcare ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 245
Author(s):  
Liang Geng ◽  
Renbin Xiao ◽  
Jie Chen
Keyword(s):  
Absorptive Capacity ◽  
Structural Design ◽  
Performance Indicator ◽  
Self Organization ◽  
Supply Network ◽  
Healthcare Resources ◽  
Extremal Optimization ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Micro Level

The healthcare resources supply network design for resilience is an effective way to deal with uncertainty disruption. In this article we propose a model of supply network self-organization evolution, and establish self-organized criticality as a cause of cascade failure. Our main purpose is to keep the system in a resilient range, i.e., critical state. A network structural design with smaller degree distribution exponent can achieve better absorptive capacity at macro level. An interactive rule design with extremal optimization has better adaptive capacity at micro level. Using macro statistic and indicator micro performance indicator, we demonstrate that our design can slow the development to a supercritical state and can improve the resilience of the supply network.

scholarly journals Self-Organized Criticality on Twitter: Phenomenological Theory and Empirical Investigation Based on Data Analysis Results

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Andrey Dmitriev ◽  
Victor Dmitriev ◽  
Stepan Balybin
Keyword(s):  
Time Series ◽  
Critical State ◽  
Empirical Investigation ◽  
Phenomenological Theory ◽  
Self Organization ◽  
Protest Movements ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Stochastic Sources ◽  
Adiabatic Mode

Recently, there has been an increasing number of empirical evidence supporting the hypothesis that spread of avalanches of microposts on social networks, such as Twitter, is associated with some sociopolitical events. Typical examples of such events are political elections and protest movements. Inspired by this phenomenon, we built a phenomenological model that describes Twitter’s self-organization in a critical state. An external manifestation of this condition is the spread of avalanches of microposts on the network. The model is based on a fractional three-parameter self-organization scheme with stochastic sources. It is shown that the adiabatic mode of self-organization in a critical state is determined by the intensive coordinated action of a relatively small number of network users. To identify the critical states of the network and to verify the model, we have proposed a spectrum of three scaling indicators of the observed time series of microposts.

Generalized External Optimization

2005 ◽  
pp. 41-60 ◽  
Author(s):  
Fabiano Luis de Sousa ◽  
Fernando Manuel Ramos ◽  
Roberto Luiz Galski ◽  
Issamu Muraoka
Keyword(s):  
Optimization Problems ◽  
Evolutionary Model ◽  
Design Tool ◽  
Thermal Design ◽  
Extremal Optimization ◽  
Integer Variables ◽  
Constrained Problems ◽  
Self Organized ◽  
Complex Design ◽  
Self Organized Criticality

In this chapter a recently proposed meta-heuristic devised to be used in complex optimization problems is presented. Called Generalized Extremal Optimization (GEO), it was inspired by a simple co-evolutionary model, developed to show the emergence of self-organized criticality in ecosystems. The algorithm is of easy implementation, does not make use of derivatives and can be applied to unconstrained or constrained problems, non-convex or even disjoint design spaces, with any combination of continuous, discrete or integer variables. It is a global search meta-heuristic, like the Genetic Algorithm (GA) and the Simulated Annealing (SA), but with the advantage of having only one free parameter to adjust. The GEO has been shown to be competitive to the GA and the SA in tackling complex design spaces and a useful tool in real design problems. Here the algorithm is described, including a step-by-step implementation to a simple numerical example, its main characteristics highlighted, and its efficacy as a design tool illustrated with an application to satellite thermal design.

scholarly journals Transition from Self-Organized Criticality into Self-Organization during Sliding Si3N4 Balls against Nanocrystalline Diamond Films

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1055
Author(s):  
Bogatov ◽  
Podgursky ◽  
Vagiström ◽  
Yashin ◽  
Shaikh ◽  
...  
Keyword(s):  
Friction Force ◽  
Power Law ◽  
Early Stage ◽  
Nanocrystalline Diamond ◽  
The Self ◽  
Self Organization ◽  
Power Law Distribution ◽  
Reciprocating Sliding ◽  
Self Organized ◽  
Self Organized Criticality

The paper investigates the variation of friction force (Fx) during reciprocating sliding tests on nanocrystalline diamond (NCD) films. The analysis of the friction behavior during the run-in period is the focus of the study. The NCD films were grown using microwave plasma-enhanced chemical vapor deposition (MW-PECVD) on single-crystalline diamond SCD(110) substrates. Reciprocating sliding tests were conducted under 500 and 2000 g of normal load using Si3N4 balls as a counter body. The friction force permanently varies during the test, namely Fx value can locally increase or decrease in each cycle of sliding. The distribution of friction force drops (dFx) was extracted from the experimental data using a specially developed program. The analysis revealed a power-law distribution f-µ of dFx for the early stage of the run-in with the exponent value (µ) in the range from 0.6 to 2.9. In addition, the frequency power spectrum of Fx time series follows power-law distribution f-α with α value in the range of 1.0–2.0, with the highest values (1.6–2.0) for the initial stage of the run-in. No power-law distribution of dFx was found for the later stage of the run-in and the steady-state periods of sliding with the exception for periods where a relatively extended decrease of coefficient of friction (COF) was observed. The asperity interlocking leads to the stick-slip like sliding at the early stage of the run-in. This tribological behavior can be related to the self-organized criticality (SOC). The emergence of dissipative structures at the later stages of the run-in, namely the formation of ripples, carbonaceous tribolayer, etc., can be associated with the self-organization (SO).

scholarly journals Research on MAS-Based Supply Chain Resilience and Its Self-Organized Criticality

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Liang Geng ◽  
Renbin Xiao ◽  
Xing Xu
Keyword(s):  
Supply Chain ◽  
Fitness Function ◽  
The Self ◽  
Self Organization ◽  
Neighborhood Structure ◽  
Supply Chain System ◽  
Supply Chain Resilience ◽  
Self Organized ◽  
Agglomeration Effect ◽  
Self Organized Criticality

Building resilient supply chain is an effective way to deal with uncertain risks. First, by analyzing the self-organization of supply chain, the supply chain resilience is described as a macroscopic property that generates from self-organizing behavior of each enterprise on the microlevel. Second, a MAS-based supply chain resilience model is established and its local fitness function, neighborhood structure, and interaction rules that are applicable to supply chain system are designed through viewing the enterprise as an agent. Finally, with the help of a case, we find that there is an agglomeration effect and a SOC characteristic in supply chain and the evolution of supply chain is controlled by parameters of MAS. Managers can control the supply chain within the resilient range and choose a good balance between interest and risk by controlling enterprises’ behavior.

scholarly journals SELF-ORGANIZED CRITICALITY, OPTIMIZATION AND BIODIVERSITY

2003 ◽  
Vol 14 (07) ◽  
pp. 911-916 ◽  
Author(s):  
ROBERTO N. ONODY ◽  
PAULO A. DE CASTRO
Keyword(s):  
Optimization Theory ◽  
Steady State Regime ◽  
Discrete Form ◽  
Extremal Optimization ◽  
Self Organized ◽  
Self Organized Criticality ◽  
State Regime ◽  
Mean Fitness ◽  
Essential Prerequisite

By driving to extinction species that are less or poorly adapted, the Darwinian evolutionary theory is intrinsically an optimization theory. We investigate two optimization algorithms with such evolutionary characteristics: the Bak–Sneppen and the Extremal Optimization. By comparing their mean fitness in the steady state regime, we conclude that the Bak–Sneppen dynamics is more efficient than the Extremal Optimization if the parameter τ is in the interval [0, 0.86]. The determination of the spatial correlation and the probability distribution of the avalanches show that the Extremal Optimization dynamics does not lead the system into a critical self-organized state. Through a discrete form of the Bak–Sneppen model we argue that biodiversity is an essential prerequisite to preserve the self-organized criticality.

scholarly journals Managing Complexity in Socio-Economic Systems

2009 ◽  
Vol 17 (2) ◽  
pp. 423-438 ◽  
Author(s):  
Dirk Helbing
Keyword(s):  
Complex Systems ◽  
Driving Forces ◽  
Production Systems ◽  
Power Laws ◽  
Self Organization ◽  
Economic Systems ◽  
Hierarchical Systems ◽  
Cascading Effects ◽  
Self Organized ◽  
Self Organized Criticality

This contribution summarizes some typical features of complex systems such as non-linear interactions, chaotic dynamics, the ``butterfly effect’’, phase transitions, self-organized criticality, cascading effects, and power laws. These imply sometimes quite unexpected, counter-intuitive, or even paradoxical behaviors of socio-economic systems. A typical example is the faster-is-slower effect. Due to their tendency of self-organization, complex systems are often hard to control. Instead of trying to control their behavior, it would often be better to pursue the approach of guided self-organization, i.e. to use the driving forces of the system rather than to fight against them. This is illustrated by the example of hierarchical systems, which need to fulfill certain principles in order to be efficient and robust in an ever-changing environment. We also discuss the important role of fluctuations and heterogeneity for the adaptability, flexibility and robustness of complex systems. The presentation is enriched by a number of examples ranging from decision behavior up to production systems and disaster spreading.

The role of self-organization during confined comminution of granular materials

2010 ◽  
Vol 368 (1910) ◽  
pp. 231-247 ◽  
Author(s):  
Oded Ben-Nun ◽  
Itai Einav
Keyword(s):  
Fractal Dimension ◽  
Granular Materials ◽  
Power Law ◽  
Self Organization ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Self Similar ◽  
Discrete Element Simulations ◽  
Comprehensive Study

During confined comminution of granular materials a power-law grain size distribution (gsd) frequently evolves. We consider this power law as a hint for fractal topology if self-similar patterns appear across the scales. We demonstrate that this ultimate topology is mostly affected by the rules that define the self-organization of the fragment subunits, which agrees well with observations from simplistic models of cellular automata. There is, however, a major difference that highlights the novelty of the current work: here the conclusion is based on a comprehensive study using two-dimensional ‘crushable’ discrete-element simulations that do not neglect physical conservation laws. Motivated by the paradigm of self-organized criticality, we further demonstrate that in uniaxial compression the emerging ultimate fractal topology, as given by the fractal dimension, is generally insensitive to alteration of global index properties of initial porosity and initial gsd. Finally, we show that the fractal dimension in the confined crushing systems is approached irrespective of alteration of the criteria that define when particles crush.

SEX AND SELF-ORGANIZATION ON RUGGED LANDSCAPES

1996 ◽  
Vol 07 (05) ◽  
pp. 705-715 ◽  
Author(s):  
JAN FINJORD
Keyword(s):  
Phase Transition ◽  
Abrupt Change ◽  
Fitness Landscape ◽  
Self Organization ◽  
Self Organized ◽  
Genetic Overlap ◽  
Self Organized Criticality

The two-parent reproduction model of Derrida and Peliti is simulated on a rugged fitness landscape. Fixed fitness values for each possible genotype are assigned randomly, with all fit individuals having the same probability of reproduction. The previously observed transition to a self-organized state of the population with less recombinational load, implies an abrupt change of genetic overlap distributions, showing up characteristics of a phase transition. A crossover variant of the model has a smoother transition to the adapted regime, with a residual collective adaptation for small values of the threshold in fitness. When a geographical constraint (shortest possible distance) on pairwise reproduction in a population arranged one-dimensionally is imposed, a poised state results, suggestive of self-organized criticality.

scholarly journals Self-Organization Toward Criticality by Synaptic Plasticity

2021 ◽  
Vol 9 ◽  
Author(s):  
Roxana Zeraati ◽  
Viola Priesemann ◽  
Anna Levina
Keyword(s):  
Synaptic Plasticity ◽  
Network Models ◽  
Self Organization ◽  
Scale Free ◽  
Neural Recordings ◽  
Self Organized ◽  
Self Organized Criticality ◽  
The Brain ◽  
Universal Mechanism

Self-organized criticality has been proposed to be a universal mechanism for the emergence of scale-free dynamics in many complex systems, and possibly in the brain. While such scale-free patterns were identified experimentally in many different types of neural recordings, the biological principles behind their emergence remained unknown. Utilizing different network models and motivated by experimental observations, synaptic plasticity was proposed as a possible mechanism to self-organize brain dynamics toward a critical point. In this review, we discuss how various biologically plausible plasticity rules operating across multiple timescales are implemented in the models and how they alter the network’s dynamical state through modification of number and strength of the connections between the neurons. Some of these rules help to stabilize criticality, some need additional mechanisms to prevent divergence from the critical state. We propose that rules that are capable of bringing the network to criticality can be classified by how long the near-critical dynamics persists after their disabling. Finally, we discuss the role of self-organization and criticality in computation. Overall, the concept of criticality helps to shed light on brain function and self-organization, yet the overall dynamics of living neural networks seem to harnesses not only criticality for computation, but also deviations thereof.

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