Sinisa Pajevic
2009-01-01
Full Text Available Cascading activity is commonly found in complex systems with directed interactions such as metabolic networks, neuronal networks, or disease spreading in social networks. Substantial insight into a system's organization can be obtained by reconstructing the underlying functional network architecture from the observed activity cascades. Here we focus on Bayesian approaches and reduce their computational demands by introducing the Iterative Bayesian (IB and Posterior Weighted Averaging (PWA methods. We introduce a special case of PWA, cast in nonparametric form, which we call the normalized count (NC algorithm. NC efficiently reconstructs random and small-world functional network topologies and architectures from subcritical, critical, and supercritical cascading dynamics and yields significant improvements over commonly used correlation methods. With experimental data, NC identified a functional and structural small-world topology and its corresponding traffic in cortical networks with neuronal avalanche dynamics.
小世界网络下电网连锁故障预测%Cascading Failures Prediction of Transmission Network in Small World Network
潘一飞; 李华强; 贺含峰; 王伊渺; 廖苑晰; 李扬
2013-01-01
The cascading failure of power grid condition can cause serious accidents including large-scale power cut. The small-world network is an important net model of complex net theories. In this paper, based on the small-world network construction, reasonable construction of topology model was put forward to establish the method of forecasting chain fault priority. Secondly, the weighted electrical betweenness was constructed based on the factors of physical properties, electrical parameters, power loss, etc. By combining with complete branch static energy function model, an energy index was built to map the change of flow. Again, the comprehensive margin index of predicting the cascading failures was proposed to reflect the state and structure change of the small-world network model after the power grid failure. Finally, the algorithm was applied in IEEE-57 bus system for example analysis. The simulation results showed that the proposed prediction method can quickly and accurately search out more serious chain failure mode set, which verified the rationality and effectiveness of this method.%电网连锁故障可能导致大规模停电等严重后果,小世界网络是复杂网络理论中重要网络模型之一.该文首先提出了基于小世界网络构建合理的拓扑模型,建立预测连锁故障优先级的方法.其次,构造了建立在物理特性、电气参数、功率损耗等因素基础上的加权电气介数,结合完整的支路静态能量函数模型,建立了映射潮流变化的能量指标.再次,提出了反映电网发生故障后小世界网络模型的状态和结构变化的综合性裕度指标预测连锁故障.最后,将该算法在IEEE-57母线系统中进行算例分析,仿真结果表明所提预测方法能够快速、准确地搜索出较严重的连锁故障模式集,验证了该方法的合理性、有效性.
Wei, Zong-Wen; Han, Xiao-Pu
2011-01-01
Quantum networks are critical to quantum communication and distributed quantum computing. Here we propose a small-world model of large-scale quantum repeater networks, where "small-world" is a fundamental concept rooted in complex networks, which describe a broad range of real systems. The core of the model is to relate the hierarchical fashion of measurements to coarse-graining process, when quantum repeater protocols are implemented. We demonstrate that quantum repeater networks with fractal structure can be enlarged with certain length scale in geographic space, while preserving topology by performing renormalization. Actually, renormalization here serves as an organizing principle determining the distribution of long-range entangled links over quantum networks, which gives rise to fractal to small-world transition. Furthermore, by iterative implementation of renormalization on the former coarse-grained network, we eventually obtain an onion-like, hierarchical quantum small-world network, where the distanc...
Deterministic Small-World Networks
Comellas, Francesc; Sampels, Michael
2001-01-01
Many real life networks, such as the World Wide Web, transportation systems, biological or social networks, achieve both a strong local clustering (nodes have many mutual neighbors) and a small diameter (maximum distance between any two nodes). These networks have been characterized as small-world networks and modeled by the addition of randomness to regular structures. We show that small-world networks can be constructed in a deterministic way. This exact approach permits a direct calculatio...
Identifying Vulnerable Nodes of Complex Networks in Cascading Failures Induced by Node-Based Attacks
Shudong Li
2013-01-01
Full Text Available In the research on network security, distinguishing the vulnerable components of networks is very important for protecting infrastructures systems. Here, we probe how to identify the vulnerable nodes of complex networks in cascading failures, which was ignored before. Concerned with random attack (RA and highest load attack (HL on nodes, we model cascading dynamics of complex networks. Then, we introduce four kinds of weighting methods to characterize the nodes of networks including Barabási-Albert scale-free networks (SF, Watts-Strogatz small-world networks (WS, Erdos-Renyi random networks (ER, and two real-world networks. The simulations show that, for SF networks under HL attack, the nodes with small value of the fourth kind of weight are the most vulnerable and the ones with small value of the third weight are also vulnerable. Also, the real-world autonomous system with power-law distribution verifies these findings. Moreover, for WS and ER networks under both RA and HL attack, when the nodes have low tolerant ability, the ones with small value of the fourth kind of weight are more vulnerable and also the ones with high degree are easier to break down. The results give us important theoretical basis for digging the potential safety loophole and making protection strategy.
Trust Propagation in Small Worlds
Gray, Elizabeth; Seigneur, Jean-Marc; Chen, Yong; Jensen, Christian D.
do not scale well. We aim to develop trust-based security mechanisms using small world concepts to optimise formation and propagation of trust amongst entities in these vast networks. In this regard, we surmise that in a very large mobile ad hoc network, trust, risk, and recommendations can be...... propagated through relatively short paths connecting entities. Our work describes the design of trust-formation and risk-assessment systems, as well as that of an entity recognition scheme, within the context of the small world network topology....
Trust Propagation in Small Worlds
Gray, Elizabeth; Seigneur, Jean-Marc; Chen, Yong;
2003-01-01
do not scale well. We aim to develop trust-based security mechanisms using small world concepts to optimise formation and propagation of trust amongst entities in these vast networks. In this regard, we surmise that in a very large mobile ad hoc network, trust, risk, and recommendations can be...... propagated through relatively short paths connecting entities. Our work describes the design of trust-formation and risk-assessment systems, as well as that of an entity recognition scheme, within the context of the small world network topology.......The possibility of a massive, networked infrastructure of diverse entities partaking in collaborative applications with each other increases more and more with the proliferation of mobile devices and the development of ad hoc networking technologies. In this context, traditional security measures...
The small world of psychopathology
Denny Borsboom; Cramer, Angélique O. J.; Schmittmann, Verena D.; Sacha Epskamp; Waldorp, Lourens J.
2011-01-01
BACKGROUND: Mental disorders are highly comorbid: people having one disorder are likely to have another as well. We explain empirical comorbidity patterns based on a network model of psychiatric symptoms, derived from an analysis of symptom overlap in the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV). PRINCIPAL FINDINGS: We show that a) half of the symptoms in the DSM-IV network are connected, b) the architecture of these connections conforms to a small world structure, fe...
The small world of psychopathology
Borsboom, D; Cramer, A.O.J.; Schmittmann, V.D.; Epskamp, S.; Waldorp, L.J.
2011-01-01
Background Mental disorders are highly comorbid: people having one disorder are likely to have another as well. We explain empirical comorbidity patterns based on a network model of psychiatric symptoms, derived from an analysis of symptom overlap in the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV). Principal Findings We show that a) half of the symptoms in the DSM-IV network are connected, b) the architecture of these connections conforms to a small world structure, feat...
The small world of psychopathology.
Denny Borsboom
Full Text Available BACKGROUND: Mental disorders are highly comorbid: people having one disorder are likely to have another as well. We explain empirical comorbidity patterns based on a network model of psychiatric symptoms, derived from an analysis of symptom overlap in the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV. PRINCIPAL FINDINGS: We show that a half of the symptoms in the DSM-IV network are connected, b the architecture of these connections conforms to a small world structure, featuring a high degree of clustering but a short average path length, and c distances between disorders in this structure predict empirical comorbidity rates. Network simulations of Major Depressive Episode and Generalized Anxiety Disorder show that the model faithfully reproduces empirical population statistics for these disorders. CONCLUSIONS: In the network model, mental disorders are inherently complex. This explains the limited successes of genetic, neuroscientific, and etiological approaches to unravel their causes. We outline a psychosystems approach to investigate the structure and dynamics of mental disorders.
Brain networks: small-worlds, after all?
Since its introduction, the ‘small-world’ effect has played a central role in network science, particularly in the analysis of the complex networks of the nervous system. From the cellular level to that of interconnected cortical regions, many analyses have revealed small-world properties in the networks of the brain. In this work, we revisit the quantification of small-worldness in neural graphs. We find that neural graphs fall into the ‘borderline’ regime of small-worldness, residing close to that of a random graph, especially when the degree sequence of the network is taken into account. We then apply recently introducted analytical expressions for clustering and distance measures, to study this borderline small-worldness regime. We derive theoretical bounds for the minimal and maximal small-worldness index for a given graph, and by semi-analytical means, study the small-worldness index itself. With this approach, we find that graphs with small-worldness equivalent to that observed in experimental data are dominated by their random component. These results provide the first thorough analysis suggesting that neural graphs may reside far away from the maximally small-world regime. (paper)
The ubiquity of small-world networks
Telesford, Qawi K; Hayasaka, Satoru; Burdette, Jonathan H; Laurienti, Paul J
2011-01-01
Small-world networks by Watts and Strogatz are a class of networks that are highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. These characteristics result in networks with unique properties of regional specialization with efficient information transfer. Social networks are intuitive examples of this organization with cliques or clusters of friends being interconnected, but each person is really only 5-6 people away from anyone else. While this qualitative definition has prevailed in network science theory, in application, the standard quantitative application is to compare path length (a surrogate measure of distributed processing) and clustering (a surrogate measure of regional specialization) to an equivalent random network. It is demonstrated here that comparing network clustering to that of a random network can result in aberrant findings and networks once thought to exhibit small-world properties may not. We propose a new small-world metric, {\\omega}...
Small-World Brain Networks Revisited
Bassett, Danielle S.; Bullmore, Edward T.
2016-01-01
It is nearly 20 years since the concept of a small-world network was first quantitatively defined, by a combination of high clustering and short path length; and about 10 years since this metric of complex network topology began to be widely applied to analysis of neuroimaging and other neuroscience data as part of the rapid growth of the new field of connectomics. Here we review briefly the foundational concepts of graph theoretical estimation and generation of small-world networks. We take ...
Disrupted Small-World Networks in Schizophrenia
Liu, Yong; Liang, Meng; Zhou, Yuan; He, Yong; Hao, Yihui; Song, Ming; Yu, Chunshui; Liu, Haihong; Liu, Zhening; Jiang, Tianzi
2008-01-01
The human brain has been described as a large, sparse, complex network characterized by efficient small-world properties, which assure that the brain generates and integrates information with high efficiency. Many previous neuroimaging studies have provided consistent evidence of "dysfunctional connectivity" among the brain regions in…
Fractal and Small-World Networks Formed by Self-Organized Critical Dynamics
Watanabe, Akitomo; Yakubo, Kousuke
2015-01-01
We propose a dynamical model in which a network structure evolves in a self-organized critical (SOC) manner and explain a possible origin of the emergence of fractal and small-world networks. Our model combines a network growth and its decay by failures of nodes. The decay mechanism reflects the instability of large functional networks against cascading overload failures. It is demonstrated that the dynamical system surely exhibits SOC characteristics, such as power-law forms of the avalanche size distribution, the cluster size distribution, and the distribution of the time interval between intermittent avalanches. During the network evolution, fractal networks are spontaneously generated when networks experience critical cascades of failures that lead to a percolation transition. In contrast, networks far from criticality have small-world structures. We also observe the crossover behavior from fractal to small-world structure in the network evolution.
Fractal and Small-World Networks Formed by Self-Organized Critical Dynamics
Watanabe, Akitomo; Mizutaka, Shogo; Yakubo, Kousuke
2015-11-01
We propose a dynamical model in which a network structure evolves in a self-organized critical (SOC) manner and explain a possible origin of the emergence of fractal and small-world networks. Our model combines a network growth and its decay by failures of nodes. The decay mechanism reflects the instability of large functional networks against cascading overload failures. It is demonstrated that the dynamical system surely exhibits SOC characteristics, such as power-law forms of the avalanche size distribution, the cluster size distribution, and the distribution of the time interval between intermittent avalanches. During the network evolution, fractal networks are spontaneously generated when networks experience critical cascades of failures that lead to a percolation transition. In contrast, networks far from criticality have small-world structures. We also observe the crossover behavior from fractal to small-world structure in the network evolution.
XY model in small-world networks
Kim, Beom Jun; Hong, H.; Holme, Petter; Jeon, Gun Sang; Minnhagen, Petter; Choi, M. Y.
2001-01-01
The phase transition in the XY model on one-dimensional small-world networks is investigated by means of Monte-Carlo simulations. It is found that long-range order is present at finite temperatures, even for very small values of the rewiring probability, suggesting a finite-temperature transition for any nonzero rewiring probability. Nature of the phase transition is discussed in comparison with the globally-coupled XY model.
Small Worlds: Strong Clustering in Wireless Networks
Brust, Matthias R
2007-01-01
Small-worlds represent efficient communication networks that obey two distinguishing characteristics: a high clustering coefficient together with a small characteristic path length. This paper focuses on an interesting paradox, that removing links in a network can increase the overall clustering coefficient. Reckful Roaming, as introduced in this paper, is a 2-localized algorithm that takes advantage of this paradox in order to selectively remove superfluous links, this way optimizing the clustering coefficient while still retaining a sufficiently small characteristic path length.
Fastest learning in small world neural networks
Simard, D.; Nadeau, L; Kröger, H.
2004-01-01
We investigate supervised learning in neural networks. We consider a multi-layered feed-forward network with back propagation. We find that the network of small-world connectivity reduces the learning error and learning time when compared to the networks of regular or random connectivity. Our study has potential applications in the domain of data-mining, image processing, speech recognition, and pattern recognition.
Networks, Clusters, and Small Worlds: Are they related?
Luca Giustiniano
2015-07-01
Full Text Available In recent years, many industries have seen the rise of new inter-organizational forms. Among those new forms, organizational networks, clusters, and small worlds are attracting increasing interest, both in academic research and management practice. While economic theory considers such forms to be market failures, organization theory highlights their potential positive effects on the participating organizations. The organizational literature often uses the terms “networks”, “clusters”, and “small worlds” as synonymous even though there are differences between them. Moreover, given the sometimes-spontaneous emergence of these organizational forms, the extent to which they can be designed is not always clear. This article discusses the characteristics of networks, clusters, and small worlds; their operational parameters; and how these organizational forms are related. Further, we identify the role of design in these types of organizations.
A small world network of prime numbers
Chandra, Anjan Kumar; Dasgupta, Subinay
2005-11-01
According to Goldbach conjecture, any even number can be broken up as the sum of two prime numbers: n=p+q. We construct a network where each node is a prime number and corresponding to every even number n, we put a link between the component primes p and q. In most cases, an even number can be broken up in many ways, and then we chose one decomposition with a probability |p-q|α. Through computation of average shortest distance and clustering coefficient, we conclude that for α>-1.8 the network is of small world type and for α<-1.8 it is of regular type. We also present a theoretical justification for such behaviour.
Social influence in small-world networks
孙锴; 毛晓明; 欧阳颀
2002-01-01
We report on our numerical studies of the Axelrod model for social influence in small-world networks. Our simulation results show that the topology of thenetwork has a crucial effect on the evolution of cultures. As the randomness of the network increases, the system undergoes a transition from a highly fragmented phase to a uniform phase. We also find that the power-law distribution at the transition point, reported by Castellano et al, is not a critical phenomenon; it exists not only at the onset of transition but also for almost any control parameters. All these power-law distributions are stable against perturbations. A mean-field theory is developed to explain these phenomena.
The lesioned brain: still a small world?
Johannes C Baayen
2010-11-01
Full Text Available The intra-arterial amobarbital procedure (IAP or Wada test is used to determine language lateralization and contralateral memory functioning in patients eligible for neurosurgery because of pharmaco-resistant epilepsy. During unilateral sedation, functioning of the contralateral hemisphere is assessed by means of neuropsychological tests. We use the IAP as a reversible model for the effect of lesions on brain network topology. Three artifact free epochs (4096 samples were selected from each EEG record before and after amobarbital injection. Functional connectivity was assessed by means of the synchronization likelihood (SL. The resulting functional connectivity matrices were constructed for all six epochs per patient in four frequency bands, and weighted network analysis was performed. The clustering coefficient, average path length, small-world-index, and edge weight correlation were calculated. Recordings of 33 patients were available. Network topology changed significantly after amobarbital injection: clustering decreased in all frequency bands, while path length decreased in the theta and lower alpha band, indicating a shift towards a more random network topology. Likewise, the edge weight correlation decreased after injection of amobarbital in the theta and beta bands. Network characteristics after injection of amobarbital were correlated with memory score: higher theta band small-world-index and increased upper alpha path length were related to better memory score. The whole-brain network topology in patients eligible for epilepsy surgery becomes more random and less optimally organized after selective sedation of one hemisphere, as has been reported in studies with brain tumor patients. Furthermore, memory functioning after injection seems related to network topology, indicating that functional performance is related to topological network properties of the brain.
Small Worldness in Dense and Weighted Connectomes
Colon-Perez, Luis; Couret, Michelle; Triplett, William; Price, Catherine; Mareci, Thomas
2016-05-01
The human brain is a heterogeneous network of connected functional regions; however, most brain network studies assume that all brain connections can be described in a framework of binary connections. The brain is a complex structure of white matter tracts connected by a wide range of tract sizes, which suggests a broad range of connection strengths. Therefore, the assumption that the connections are binary yields an incomplete picture of the brain. Various thresholding methods have been used to remove spurious connections and reduce the graph density in binary networks. But these thresholds are arbitrary and make problematic the comparison of networks created at different thresholds. The heterogeneity of connection strengths can be represented in graph theory by applying weights to the network edges. Using our recently introduced edge weight parameter, we estimated the topological brain network organization using a complimentary weighted connectivity framework to the traditional framework of a binary network. To examine the reproducibility of brain networks in a controlled condition, we studied the topological network organization of a single healthy individual by acquiring 10 repeated diffusion-weighted magnetic resonance image datasets, over a one-month period on the same scanner, and analyzing these networks with deterministic tractography. We applied a threshold to both the binary and weighted networks and determined that the extra degree of freedom that comes with the framework of weighting network connectivity provides a robust result as any threshold level. The proposed weighted connectivity framework provides a stable result and is able to demonstrate the small world property of brain networks in situations where the binary framework is inadequate and unable to demonstrate this network property.
Schmitt, Rafael J. P.; Bizzi, Simone; Castelletti, Andrea
2016-05-01
Sediment connectivity in fluvial networks results from the transfer of sediment between multiple sources and sinks. Connectivity scales differently between all sources and sinks as a function of distance, source grain size and sediment supply, network topology and topography, and hydrologic forcing. In this paper, we address the challenge of quantifying sediment connectivity and its controls at the network scale. We expand the concept of a single, catchment-scale sediment cascade toward representing sediment transport from each source as a suite of individual cascading processes. We implement this approach in the herein presented CAtchment Sediment Connectivity And DElivery (CASCADE) modeling framework. In CASCADE, each sediment cascade establishes connectivity between a specific source and its multiple sinks. From a source perspective, the fate of sediment is controlled by its detachment and downstream transport capacity, resulting in a specific trajectory of transfer and deposition. From a sink perspective, the assemblage of incoming cascades defines provenance, sorting, and magnitude of sediment deliveries. At the network scale, this information reveals emerging patterns of connectivity and the location of bottlenecks, where disconnectivity occurs. In this paper, we apply CASCADE to quantitatively analyze the sediment connectivity of a major river system in SE Asia. The approach provides a screening model that can support analyses of large, poorly monitored river systems. We test the sensitivity of CASCADE to various parameters and identify the distribution of energy between the multiple, simultaneously active sediment cascades as key control behind network sediment connectivity. To conclude, CASCADE enables a quantitative, spatially explicit analysis of network sediment connectivity with potential applications in both river science and management.
A new small-world network created by Cellular Automata
Ruan, Yuhong; Li, Anwei
2016-08-01
In this paper, we generate small-world networks by the Cellular Automaton based on starting with one-dimensional regular networks. Besides the common properties of small-world networks with small average shortest path length and large clustering coefficient, the small-world networks generated in this way have other properties: (i) The edges which are cut in the regular network can be controlled that whether the edges are reconnected or not, and (ii) the number of the edges of the small-world network model equals the number of the edges of the original regular network. In other words, the average degree of the small-world network model equals to the average degree of the original regular network.
Phase Synchronization in Small World Chaotic Neural Networks
WANG Qing-Yun; LU Qi-Shao
2005-01-01
@@ To understand collective motion of realneural networks very well, we investigate collective phase synchronization of small world chaotic Hindmarsh-Rose (HR) neural networks. By numerical simulations, we conclude that small world chaotic HR neural networks can achieve collective phase synchronization. Furthermore, it is shown that phase synchronization of small world chaotic HR neural networks is dependent on the coupling strength,the connection topology (which is determined by the probability p), as well as the coupling number. These phenomena are important to guide us to understand the synchronization of real neural networks.
Small-World Propensity and Weighted Brain Networks
Muldoon, Sarah Feldt; Bridgeford, Eric W.; Bassett, Danielle S.
2016-02-01
Quantitative descriptions of network structure can provide fundamental insights into the function of interconnected complex systems. Small-world structure, diagnosed by high local clustering yet short average path length between any two nodes, promotes information flow in coupled systems, a key function that can differ across conditions or between groups. However, current techniques to quantify small-worldness are density dependent and neglect important features such as the strength of network connections, limiting their application in real-world systems. Here, we address both limitations with a novel metric called the Small-World Propensity (SWP). In its binary instantiation, the SWP provides an unbiased assessment of small-world structure in networks of varying densities. We extend this concept to the case of weighted brain networks by developing (i) a standardized procedure for generating weighted small-world networks, (ii) a weighted extension of the SWP, and (iii) a method for mapping observed brain network data onto the theoretical model. In applying these techniques to compare real-world brain networks, we uncover the surprising fact that the canonical biological small-world network, the C. elegans neuronal network, has strikingly low SWP. These metrics, models, and maps form a coherent toolbox for the assessment and comparison of architectural properties in brain networks.
Braess like Paradox in a Small World Network
Toyota, Norihito
2013-01-01
Braess \\cite{1} has been studied about a traffic flow on a diamond type network and found that introducing new edges to the networks always does not achieve the efficiency. Some researchers studied the Braess' paradox in similar type networks by introducing various types of cost functions. But whether such paradox occurs or not is not scarcely studied in complex networks. In this article, I analytically and numerically study whether Braess like paradox occurs or not on Dorogovtsev-Mendes network\\cite{2}, which is a sort of small world networks. The cost function needed to go along an edge is postulated to be equally identified with the length between two nodes, independently of an amount of traffic on the edge. It is also assumed the it takes a certain cost $c$ to pass through the center node in Dorogovtsev-Mendes network. If $c$ is small, then bypasses have the function to provide short cuts. As result of numerical and theoretical analyses, while I find that any Braess' like paradox will not occur when the n...
Dawn of small worlds dwarf planets, asteroids, comets
Moltenbrey, Michael
2016-01-01
This book gives a detailed introduction to the thousands and thousands of smaller bodies in the solar system. Written for interested laymen, amateur astronomers and students it describes the nature and origin of asteroids, dwarf planets and comets, and gives detailed information about their role in the solar system. The author nicely reviews the history of small-world-exploration and describes past, current and future space craft missions studying small worlds, and presents their results. Readers will learn that small solar system worlds have a dramatically different nature and appearance than the planets. Even though research activity on small worlds has increased in the recent past many of their properties are still in the dark and need further research.
The Efficiency of a Small-World Functional Brain Network
ZHAO Qing-Bai; ZHANG Xiao-Fei; SUI Dan-Ni; ZHOU Zhi-Jin; CHEN Qi-Cai; TANG Yi-Yuan
2012-01-01
We investigate whether the small-world topology of a functional brain network means high information processing efficiency by calculating the correlation between the small-world measures of a functional brain network and behavioral reaction during an imagery task.Functional brain networks are constructed by multichannel eventrelated potential data,in which the electrodes are the nodes and the functional connectivities between them are the edges.The results show that the correlation between small-world measures and reaction time is task-specific,such that in global imagery,there is a positive correlation between the clustering coefficient and reaction time,while in local imagery the average path length is positively correlated with the reaction time.This suggests that the efficiency of a functional brain network is task-dependent.%We investigate whether the small-world topology of a functional brain network means high information processing efficiency by calculating the correlation between the small-world measures of a functional brain network and behavioral reaction during an imagery task. Functional brain networks are constructed by multichannel event-related potential data, in which the electrodes are the nodes and the functional connectivities between them are the edges. The results show that the correlation between small-world measures and reaction time is task-specific, such that in global imagery, there is a positive correlation between the clustering coefficient and reaction time, while in local imagery the average path length is positively correlated with the reaction time. This suggests that the efficiency of a functional brain network is task-dependent.
Spatial prisoner's dilemma optimally played in small-world networks
Cooperation is commonly found in ecological and social systems even when it apparently seems that individuals can benefit from selfish behavior. We investigate how cooperation emerges with the spatial prisoner's dilemma played in a class of networks ranging from regular lattices to random networks. We find that, among these networks, small-world topology is the optimal structure when we take into account the speed at which cooperative behavior propagates. Our results may explain why the small-world properties are self-organized in real networks
Small World Architecture For Peer-to-Peer Networks
Liu, Lu; Mackin, Stephen; Antonopoulos, Nick
2006-01-01
Small-world phenomenon has been observed in existing peer-to-peer (P2P) networks, such as Gnutella and Freenet. Due to the similarity of P2P networks to social networks, the previous small-world model proposed by Duncan Watts can be adopted in the design of P2P networks: each node is connected to some neighbouring nodes, and a group of nodes keep a small number of long links to randomly chosen distant nodes. Unfortunately, current unstructured search algorithms have difficulty distinguishing ...
Small Worlds Week: Raising Curiosity and Contributing to STEM
Ng, C.; Mayo, L.; Stephenson, B. E.; Keck, A.; Cline, T. D.; Lewis, E. M.
2015-12-01
Dwarf planets, comets, asteroids, and icy moons took center stage in the years 2014-2015 as multiple spacecraft (New Horizons, Dawn, Rosetta, Cassini) and ground-based observing campaigns observed these small and yet amazing celestial bodies. Just prior to the historic New Horizons encounter with the Pluto system, NASA celebrated Small Worlds Week (July 6-10) as a fully online program to highlight small worlds mission discoveries. Small Worlds Week leveraged the infrastructure of Sun-Earth Days that included a robust web design, exemplary education materials, hands-on fun activities, multimedia resources, science and career highlights, and a culminating event. Each day from July 6-9, a new class of solar system small worlds was featured on the website: Monday-comets, Tuesday-asteroids, Wednesday-icy moons, and Thursday-dwarf planets. Then on Friday, July 10, nine scientists from Goddard Space Flight Center, Jet Propulsion Laboratory, Naval Research Laboratory, and Lunar and Planetary Institute gathered online for four hours to answer questions from the public via Facebook and Twitter. Throughout the afternoon the scientists worked closely with a social media expert and several summer interns to reply to inquirers and to archive their chats. By all accounts, Small Worlds Week was a huge success. The group plans to improve and replicate the program during the school year with a more classroom focus, and then to build and extend the program to be held every year. For more information, visit http:// sunearthday.nasa.gov or catch us on Twitter, #nasasww.
The conundrum of functional brain networks: small-world efficiency or fractal modularity
Gallos, Lazaros K; Makse, Hernan A
2012-01-01
The human brain has been studied at multiple scales, from neurons, circuits, areas with well defined anatomical and functional boundaries, to large-scale functional networks which mediate coherent cognition. In a recent work, we addressed the problem of the hierarchical organization in the brain through network analysis. Our analysis identified functional brain modules of fractal structure that were inter-connected in a small-world topology. Here, we provide more details on the use of network science tools to elaborate on this behavior. We indicate the importance of using percolation theory to highlight the modular character of the functional brain network. These modules present a fractal, self-similar topology, identified through fractal network methods. When we lower the threshold of correlations to include weaker ties, the network as a whole assumes a small-world character. These weak ties are organized precisely as predicted by theory maximizing information transfer with minimal wiring costs.
Small-world networks of optical fiber lattices
We use a simple dynamical model and explore coherent dynamics of wavepackets in complex networks of optical fibers. We start from a symmetric lattice and through the application of a Monte–Carlo criterion we introduce structural disorder and deform the lattice into a small-world network regime. We investigate in the latter both structural (correlation length) as well as dynamical (diffusion exponent) properties and find that both exhibit a rapid crossover from the ordered to the fully random regime. For a critical value of the structural disorder parameter ρ≈0.25 transport changes from ballistic to sub-diffusive due to the creation strongly connected local clusters and channels of preferential transport in the small world regime. (fast track communication)
Exploring the Critical Sensitivity in Small-World Networks
罗嘉元; 欧阳颀
2004-01-01
Catastrophic phenomena such as earthquakes, avalanches, and critical points in the stock market are hard to predict. Recently, Xia et al. [Pure Appl. Geophys. 159 (2002)2491] showed that a geometrical system near catastrophic rupture presents a general critical sensitivity: the system becomes significantly sensitive near the catastrophe transition. Here we report that the phenomenon of critical sensitivity also exists in small-world network systems. With the increase of the small-world rewiring probability p, from the regular network p = 0 to the random one p = 1, the system performs more sensitively before the critical point while remaining in better organization through the evolutional progress, and the prediction threshold Ps performs more in advance. The concept of critical sensitivity can be applied to other complex network systems.
Small-world networks of optical fiber lattices
Perakis, F; Tsironis, G P
2014-01-01
We use a simple dynamical model and explore coherent dynamics of wavepackets in complex networks of optical fibers. We start from a symmetric lattice and through the application of a Monte-Carlo criterion we introduce structural disorder and deform the lattice into a small-world network regime. We investigate in the latter both structural (correlation length) as well as dynamical (diffusion exponent) properties and find that both exhibit a rapid crossover from the ordered to the fully random regime. For a critical value of the structural disorder parameter $\\rho \\approx 0.25$ transport changes from ballistic to sub-diffusive due to the creation strongly connected local clusters and channels of preferential transport in the small world regime.
Scaling and percolation in the small-world network model
In this paper we study the small-world network model of Watts and Strogatz, which mimics some aspects of the structure of networks of social interactions. We argue that there is one nontrivial length-scale in the model, analogous to the correlation length in other systems, which is well-defined in the limit of infinite system size and which diverges continuously as the randomness in the network tends to zero, giving a normal critical point in this limit. This length-scale governs the crossover from large- to small-world behavior in the model, as well as the number of vertices in a neighborhood of given radius on the network. We derive the value of the single critical exponent controlling behavior in the critical region and the finite size scaling form for the average vertex-vertex distance on the network, and, using series expansion and Pade approximants, find an approximate analytic form for the scaling function. We calculate the effective dimension of small-world graphs and show that this dimension varies as a function of the length-scale on which it is measured, in a manner reminiscent of multifractals. We also study the problem of site percolation on small-world networks as a simple model of disease propagation, and derive an approximate expression for the percolation probability at which a giant component of connected vertices first forms (in epidemiological terms, the point at which an epidemic occurs). The typical cluster radius satisfies the expected finite size scaling form with a cluster size exponent close to that for a random graph. All our analytic results are confirmed by extensive numerical simulations of the model. (c) 1999 The American Physical Society
Small Worlds in the Tree Topologies of Wireless Sensor Networks
Qiao, Li; Lingguo, Cui; Baihai, Zhang; Fan, Zhun
In this study, the characteristics of small worlds are investigated in the context of the tree topologies of wireless sensor networks. Tree topologies, which construct spatial graphs with larger characteristic path lengths than random graphs and small clustering coefficients, are ubiquitous in...... wireless sensor networks. Suffering from the link rewiring or the link addition, the characteristic path length of the tree topology reduces rapidly and the clustering coefficient increases greatly. The variety of characteristic path length influences the time synchronization characteristics of wireless...
Recursive graphs with small-world scale-free properties
Comellas, Francesc; Fertin, Guillaume; Raspaud, André
2004-03-01
We discuss a category of graphs, recursive clique trees, which have small-world and scale-free properties and allow a fine tuning of the clustering and the power-law exponent of their discrete degree distribution. We determine relevant characteristics of those graphs: the diameter, degree distribution, and clustering parameter. The graphs have also an interesting recursive property, and generalize recent constructions with fixed degree distributions.
Self-organized Criticality on Small World Networks
de Arcangelis, L.; Herrmann, H. J.
2001-01-01
We study the BTW-height model of self-organized criticality on a square lattice with some long range connections giving to the lattice the character of small world network. We find that as function of the fraction $p$ of long ranged bonds the power law of the avalanche size and lifetime distribution changes following a crossover scaling law with crossover exponents 2/3 and 1 for size and lifetime respectively.
Fastest learning in small-world neural networks
We investigate supervised learning in neural networks. We consider a multi-layered feed-forward network with back propagation. We find that the network of small-world connectivity reduces the learning error and learning time when compared to the networks of regular or random connectivity. Our study has potential applications in the domain of data-mining, image processing, speech recognition, and pattern recognition
Small-world networks of fuzzy chaotic oscillators
Bucolo, M; Fortuna, L
2003-01-01
Small-world topology has been used to build lattices of nonlinear fuzzy systems. Chaotic units, ruled by linguistic description and with specified Lyapunov exponent, have been realized and connected using linear diffusion coefficient. The dynamic features of the networks versus the number of systems connected have been investigated to underline phenomena like spatiotemporal chaos and complete regularization. The synchronization characteristics in case of sparse long-term connections and the performances comparison with regular and random network configurations are shown.
Small-world networks of fuzzy chaotic oscillators
Bucolo, M.; Fazzino, S.; La Rosa, M. E-mail: mlarosa@dees.unict.it; Fortuna, L
2003-07-01
Small-world topology has been used to build lattices of nonlinear fuzzy systems. Chaotic units, ruled by linguistic description and with specified Lyapunov exponent, have been realized and connected using linear diffusion coefficient. The dynamic features of the networks versus the number of systems connected have been investigated to underline phenomena like spatiotemporal chaos and complete regularization. The synchronization characteristics in case of sparse long-term connections and the performances comparison with regular and random network configurations are shown.
Renormalization group analysis of the small-world network model
Newman, M. E. J.; Watts, D. J.
1999-01-01
We study the small-world network model, which mimics the transition between regular-lattice and random-lattice behavior in social networks of increasing size. We contend that the model displays a normal continuous phase transition with a divergent correlation length as the degree of randomness tends to zero. We propose a real-space renormalization group transformation for the model and demonstrate that the transformation is exact in the limit of large system size. We use this result to calcul...
Is it really a small world - network connectivity revisited
Barzel, Baruch; Biham, Ofer
2010-03-01
Networks are useful for describing systems of interacting objects, the applications include chemical and metabolic systems, food webs as well as social networks. Lately, it was found that many of these networks display some common topological features, such as high clustering, small average path length and a power-law degree distribution. These topological features are commonly related to the network's functionality. However, the topology alone does not account for the nature of the interactions in the network and their strength. In this talk we will introduce a method for evaluating the correlations between pairs of nodes in the network. These correlations depend both on the topology and on the functionality of the network. A network with high connectivity displays strong correlations between its interacting nodes and thus features small-world functionality. The method can be used to obtain the correlation matrix or to evaluate the correlation function of the network. Certain networks display a typical correlation length. The connectivity of a network is then defined as the ratio between this correlation length and the average path length of the network. Using this method one can distinguish between a topological small world and a functional small world, where the latter is characterized by long range correlations and high connectivity. Clearly, networks which share the same topology, may have different connectivities, based on the nature and strength of their interactions.
A small-world network model of facial emotion recognition.
Takehara, Takuma; Ochiai, Fumio; Suzuki, Naoto
2016-01-01
Various models have been proposed to increase understanding of the cognitive basis of facial emotions. Despite those efforts, interactions between facial emotions have received minimal attention. If collective behaviours relating to each facial emotion in the comprehensive cognitive system could be assumed, specific facial emotion relationship patterns might emerge. In this study, we demonstrate that the frameworks of complex networks can effectively capture those patterns. We generate 81 facial emotion images (6 prototypes and 75 morphs) and then ask participants to rate degrees of similarity in 3240 facial emotion pairs in a paired comparison task. A facial emotion network constructed on the basis of similarity clearly forms a small-world network, which features an extremely short average network distance and close connectivity. Further, even if two facial emotions have opposing valences, they are connected within only two steps. In addition, we show that intermediary morphs are crucial for maintaining full network integration, whereas prototypes are not at all important. These results suggest the existence of collective behaviours in the cognitive systems of facial emotions and also describe why people can efficiently recognize facial emotions in terms of information transmission and propagation. For comparison, we construct three simulated networks--one based on the categorical model, one based on the dimensional model, and one random network. The results reveal that small-world connectivity in facial emotion networks is apparently different from those networks, suggesting that a small-world network is the most suitable model for capturing the cognitive basis of facial emotions. PMID:26315136
Navigation in a small world with local information
It is commonly known that there exist short paths between vertices in a network showing the small-world effect. Yet vertices, for example, the individuals living in society, usually are not able to find the shortest paths, due to the very serious limit of information. To study this issue theoretically, here the navigation process of launching messages toward designated targets is investigated on a variant of the one-dimensional small-world network (SWN). In the network structure considered, the probability of a shortcut falling between a pair of nodes is proportional to r-α, where r is the lattice distance between the nodes. When α=0, it reduces to the SWN model with random shortcuts. The system shows the dynamic small-world effect, which is different from the well-studied static SW effect. We study the effective network diameter, the path length as a function of the lattice distance, and the dynamics. They are controlled by multiple parameters, and we use data collapse to show that the parameters are correlated. The central finding is that, in the one-dimensional network studied, the dynamic SW effect exists for 0≤α≤2. For each given value of α in this region, the point where the dynamic SW effect arises is ML'∼1, where M is the number of useful shortcuts and L' is their average reduced (effective) length
Low-rank network decomposition reveals structural characteristics of small-world networks
Barranca, Victor J.; Zhou, Douglas; Cai, David
2015-12-01
Small-world networks occur naturally throughout biological, technological, and social systems. With their prevalence, it is particularly important to prudently identify small-world networks and further characterize their unique connection structure with respect to network function. In this work we develop a formalism for classifying networks and identifying small-world structure using a decomposition of network connectivity matrices into low-rank and sparse components, corresponding to connections within clusters of highly connected nodes and sparse interconnections between clusters, respectively. We show that the network decomposition is independent of node indexing and define associated bounded measures of connectivity structure, which provide insight into the clustering and regularity of network connections. While many existing network characterizations rely on constructing benchmark networks for comparison or fail to describe the structural properties of relatively densely connected networks, our classification relies only on the intrinsic network structure and is quite robust with respect to changes in connection density, producing stable results across network realizations. Using this framework, we analyze several real-world networks and reveal new structural properties, which are often indiscernible by previously established characterizations of network connectivity.
Corona graphs as a model of small-world networks
Lv, Qian; Yi, Yuhao; Zhang, Zhongzhi
2015-11-01
We introduce recursive corona graphs as a model of small-world networks. We investigate analytically the critical characteristics of the model, including order and size, degree distribution, average path length, clustering coefficient, and the number of spanning trees, as well as Kirchhoff index. Furthermore, we study the spectra for the adjacency matrix and the Laplacian matrix for the model. We obtain explicit results for all the quantities of the recursive corona graphs, which are similar to those observed in real-life networks.
Epidemics with pathogen mutation on small-world networks
Shao, Zhi-Gang; Tan, Zhi-Jie; Zou, Xian-Wu; Jin, Zhun-Zhi
2006-05-01
We study the dynamical behavior of the epidemiological model with pathogen mutation on small-world networks, and discuss the influence of the immunity duration τR, the cross-immunity threshold hthr, and system size N on epidemic dynamics. A decaying oscillation occurs because of the interplay between the immune response and the pathogen mutation. These results have implications for the interpretation of longitudinal epidemiological data on strain abundance, and they will be helpful to assess the threat of highly pathogenic and mutative viruses, such as avian influenza.
Phase multistability in a dynamical small world network.
Shabunin, A V
2015-01-01
The effect of phase multistability is explored in a small world network of periodic oscillators with diffusive couplings. The structure of the network represents a ring with additional non-local links, which spontaneously arise and vanish between arbitrary nodes. The dynamics of random couplings is modeled by "birth" and "death" stochastic processes by means of the cellular automate approach. The evolution of the network under gradual increasing of the number of random couplings goes through stages of phases fluctuations and spatial cluster formation. Finally, in the presence of non-local couplings the phase multistability "dies" and only the in-phase regime survives. PMID:25637920
Small World Folksonomies: Clustering in Tri-Partite Hypergraphs
Schmitz, Christoph
2006-01-01
Many recent Web 2.0 resource sharing applications can be subsumed under the "folksonomy" moniker. Regardless of the type of resource shared, all of these share a common structure describing the assignment of tags to resources by users. In this report, we generalize the notions of clustering and characteristic path length which play a major role in the current research on networks, where they are used to describe the small-world effects on many observable network datasets. To that end, we s...
Coordination sequences and information spreading in small-world networks
We study the spread of information in small-world networks generated from different d-dimensional regular lattices, with d=1, 2, and 3. With this purpose, we analyze by numerical simulations the behavior of the coordination sequence, e.g., the average number of sites C(n) that can be reached from a given node of the network in n steps along its bonds. For sufficiently large networks, we find an asymptotic behavior C(n)∼ρn, with a constant ρ that depends on the network dimension d and on the rewiring probability p (which measures the disorder strength of a given network). A simple model of information spreading in these networks is studied, assuming that only a fraction q of the network sites are active. The number of active nodes reached in n steps has an asymptotic form λn, λ being a constant that depends on p and q, as well as on the dimension d of the underlying lattice. The information spreading presents two different regimes depending on the value of λ: For λ>1 the information propagates along the whole system, and for λ<1 the spreading is damped and the information remains confined in a limited region of the network. We discuss the connection of these results with site percolation in small-world networks
Random walks in small-world exponential treelike networks
In this paper, we investigate random walks in a family of small-world trees having an exponential degree distribution. First, we address a trapping problem, that is, a particular case of random walks with an immobile trap located at the initial node. We obtain the exact mean trapping time defined as the average of the first-passage times (FPT) from all nodes to the trap, which scales linearly with the network order N in large networks. Then, we determine analytically the mean sending time, which is the mean of the FPTs from the initial node to all other nodes, and show that it grows with N, varying approximately as NlnN. After that, we compute the precise global mean first-passage time among all pairs of nodes and find that it also varies approximately as NlnN in the large limit of N. After obtaining the relevant quantities, we compare them with each other and relate our results to the efficiency for information transmission by regarding the walker as an information messenger. Finally, we compare our results with those previously reported for other trees with different structural properties (e.g., degree distribution), such as the standard fractal trees and the scale-free small-world trees, and show that the shortest path between a pair of nodes in a tree is responsible for the scaling of the FPT between the two nodes
Structure of Small World Innovation Network and Learning Performance
Shuang Song
2014-01-01
Full Text Available This paper examines the differences of learning performance of 5 MNCs (multinational corporations that filed the largest number of patents in China. We establish the innovation network with the patent coauthorship data by these 5 MNCs and classify the networks by the tail of distribution curve of connections. To make a comparison of the learning performance of these 5 MNCs with differing network structures, we develop an organization learning model by regarding the reality as having m dimensions, which denotes the heterogeneous knowledge about the reality. We further set n innovative individuals that are mutually interactive and own unique knowledge about the reality. A longer (shorter distance between the knowledge of the individual and the reality denotes a lower (higher knowledge level of that individual. Individuals interact with and learn from each other within the small-world network. By making 1,000 numerical simulations and averaging the simulated results, we find that the differing structure of the small-world network leads to the differences of learning performance between these 5 MNCs. The network monopolization negatively impacts and network connectivity positively impacts learning performance. Policy implications in the conclusion section suggest that to improve firm learning performance, it is necessary to establish a flat and connective network.
Quantitative high-throughput screen identifies inhibitors of the Schistosoma mansoni redox cascade.
Anton Simeonov
Full Text Available Schistosomiasis is a tropical disease associated with high morbidity and mortality, currently affecting over 200 million people worldwide. Praziquantel is the only drug used to treat the disease, and with its increased use the probability of developing drug resistance has grown significantly. The Schistosoma parasites can survive for up to decades in the human host due in part to a unique set of antioxidant enzymes that continuously degrade the reactive oxygen species produced by the host's innate immune response. Two principal components of this defense system have been recently identified in S. mansoni as thioredoxin/glutathione reductase (TGR and peroxiredoxin (Prx and as such these enzymes present attractive new targets for anti-schistosomiasis drug development. Inhibition of TGR/Prx activity was screened in a dual-enzyme format with reducing equivalents being transferred from NADPH to glutathione via a TGR-catalyzed reaction and then to hydrogen peroxide via a Prx-catalyzed step. A fully automated quantitative high-throughput (qHTS experiment was performed against a collection of 71,028 compounds tested as 7- to 15-point concentration series at 5 microL reaction volume in 1536-well plate format. In order to generate a robust data set and to minimize the effect of compound autofluorescence, apparent reaction rates derived from a kinetic read were utilized instead of end-point measurements. Actives identified from the screen, along with previously untested analogues, were subjected to confirmatory experiments using the screening assay and subsequently against the individual targets in secondary assays. Several novel active series were identified which inhibited TGR at a range of potencies, with IC(50s ranging from micromolar to the assay response limit ( approximately 25 nM. This is, to our knowledge, the first report of a large-scale HTS to identify lead compounds for a helminthic disease, and provides a paradigm that can be used to jump
The structure of borders in a small world
Thiemann, C; Grady, D; Brune, R; Brockmann, D
2010-01-01
Geographic borders are not only essential for the effective functioning of government, the distribution of administrative responsibilities and the allocation of public resources, they also influence the interregional flow of information, cross-border trade operations, the diffusion of innovation and technology, and the spatial spread of infectious diseases. However, as growing interactions and mobility across long distances, cultural, and political borders continue to amplify the small world effect and effectively decrease the relative importance of local interactions, it is difficult to assess the location and structure of effective borders that may play the most significant role in mobility-driven processes. The paradigm of spatially coherent communities may no longer be a plausible one, and it is unclear what structures emerge from the interplay of interactions and activities across spatial scales. Here we analyse a multi-scale proxy network for human mobility that incorporates travel across a few to a few...
Synchronization in Small-World-Connected Computer Networks
Guclu, H
2006-01-01
In this thesis we study synchronization phenomena in natural and artificial coupled multi-component systems, applicable to the scalability of parallel discrete-event simulation for systems with asynchronous dynamics. We analyze the properties of the virtual time horizon or synchronization landscape (corresponding to the progress of the processing elements) of these networks by using the framework of non-equilibrium surface growth. When the communication topology mimics that of the short-range interacting underlying system, the virtual time horizon exhibits Kardar-Parisi-Zhang-like kinetic roughening. Although the virtual times, on average, progress at a nonzero rate, their statistical spread diverges with the number of processing elements, hindering efficient data collection. We show that when the synchronization topology is extended to include quenched random communication links (small-world links) between the processing elements, they make a close-to-uniform progress with a nonzero rate, without global sync...
Network Marketing on a Small-World Network
Kim, B J; Kim, J Y; Choi, M Y; Kim, Beom Jun; Jun, Tackseung; Kim, Jeong-Yoo
2005-01-01
We investigate a dynamic model of network marketing in a small-world network structure artificially constructed similarly to the Watts-Strogatz network model. Different from the traditional marketing, consumers can also play the role of the manufacturer's selling agents in network marketing, which is stimulated by the referral fee the manufacturer offers. As the wiring probability $\\alpha$ is increased from zero to unity, the network changes from the one-dimensional regular directed network to the star network where all but one player are connected to one consumer. The price $p$ of the product and the referral fee $r$ are used as free parameters to maximize the profit of the manufacturer. It is observed that at $\\alpha=0$ the maximized profit is constant independent of the network size $N$ while at $\\alpha \
Phase synchronization on small-world networks with community structure
In this paper, we propose a simple model that can generate small-world network with community structure. The network is introduced as a tunable community organization with parameter r, which is directly measured by the ratio of inter- to intra-community connectivity, and a smaller r corresponds to a stronger community structure. The structure properties, including the degree distribution, clustering, the communication efficiency and modularity are also analysed for the network. In addition, by using the Kuramoto model, we investigated the phase synchronization on this network, and found that increasing the fuzziness of community structure will markedly enhance the network synchronizability; however, in an abnormal region (r ≤ 0.001), the network has even worse synchronizability than the case of isolated communities (r = 0). Furthermore, this network exhibits a remarkable synchronization behaviour in topological scales: the oscillators of high densely interconnected communities synchronize more easily, and more rapidly than the whole network. (general)
Characteristics of Preferentially Attached Network Grown from Small World
Lee, Seungyoung
2015-01-01
We introduce a model for a preferentially attached network which has grown from a small world network. Here, the average path length and the clustering coefficient are estimated, and the topological properties of modeled networks are compared as the initial conditions are changed. As a result, it is shown that the topological properties of the initial network remain even after the network growth. However, the vulnerability of each to preferentially attached nodes being added is not the same. It is found that the average path length rapidly decreases as the ratio of preferentially attached nodes increases and that the characteristics of the initial network can be easily disappeared. On the other hand, the clustering coefficient of the initial network slowly decreases with the ratio of preferentially attached nodes and its clustering characteristic remains much longer.
Small-world property evaluated by exchanging network topology
Suzuki, Tomoya; Okazawa, Masayuki; Ohkura, Kuniaki
2015-03-01
The present study quantified the degree of the small-world (SW) property defined by Watts, and evaluated its achievement level to characterize complex networks. However, because this process has a combinatorial optimization problem, we applied the chaos neural network (CNN) and the simulated annealing (SA), and confirmed their performance in terms of optimized values and numerical costs. Next, we visualized the original network and its optimized networks whose SW property was maximized or minimized by exchanging the original network topology. As a result, although CNN and SA require huge computational time, we confirmed that they can evaluate the SW property and even real SW networks still have plenty of room to enlarge their own SW property.
Diffusion-limited-aggregation on a directed small world network
Ren, J; Wang, W X; Yan, G; Ren, Jie; Wang, Bing-Hong; Wang, Wen-Xu; Yan, Gang
2006-01-01
For real world systems, nonuniform medium is ubiquitous. Therefore, we investigate the diffusion-limited-aggregation process on a two dimensional directed small-world network instead of regular lattice. The network structure is established by rewiring connections on the two dimensional directed lattice. Those rewired edges are controlled by two parameters $\\theta$ and $m$, which characterize the spatial length and the density of the long-range connections, respectively. Simulations show that there exists a maximum value of the fractal dimension when $\\theta$ equals zero. Interestingly, we find that the symmetry of the aggregation pattern is broken when rewired connections are long enough, which may be an explanation for the formation of asymmetrical fractal in nature. Then, we perform multifractal analysis on the patterns further.
Collective firing induced by noise in an excitable media in small-world and random network
S Ghassami
2013-09-01
Full Text Available Synchrony is significant in brain neural network. In this study we investigate the collective firing in an excitable media and modeling the brain network by an small-world one. The Gaussian white noise is taken to the system of phase oscillators, and then to the frequency distribution. An order parameter in non stationary situation and other usefull statistical parameters such as firing are computed. Three regimes are identified in such a network: no firing regime, where all elements are confined near the fixed point; coherent pulsation, where a macroscopic fraction fire simultaneously; and incoherent pulsation, where units fire in a disordered fashion.
Limitation of Small-world Topology for Application in Non-dominated Sorting Differential Evolution
Bu-han Zhang; Junfang Li
2012-01-01
In the context of complex network theory, the small-world network is famous for the small-world phenomenon, namely six degrees of separation. Different from its wide application in the social, physical and technological network analysis, it can be combined with the mathematical optimization algorithm recently. In this paper, the limitation of small-world network topology for application in multi-objective optimization algorithm is proposed. The optimization algorithm based on small-world netw...
Multiobjective Bak-Sneppen model on a small-world network
Elettreby, M.F. [Department of Mathematics, Faculty of Science, Mansoura University, Mansoura 35516 (Egypt)] e-mail: mohfathy@mans.edu.eg
2005-11-01
Small-world networks (SWN) are relevant to biological systems. We study the dynamics of the Bak-Sneppen (BS) model on small-world network, including the concepts of extremal dynamics, multiobjective optimization and coherent noise. We find that the small-world structure stabilizes the system. Also, it is more realistic to augment the Bak-Sneppen model by these concepts.
Multiobjective Bak-Sneppen model on a small-world network
Small-world networks (SWN) are relevant to biological systems. We study the dynamics of the Bak-Sneppen (BS) model on small-world network, including the concepts of extremal dynamics, multiobjective optimization and coherent noise. We find that the small-world structure stabilizes the system. Also, it is more realistic to augment the Bak-Sneppen model by these concepts. (author)
Small World Model-Based Polylogarithmic Routing Using Mobile Nodes
Jie Wu; Shu-Hui Yang
2008-01-01
The use of mobile nodes to improve network system performance has drawn considerable attention recently.The movement-assisted model considers mobility as a desirable feature, where routing is based on the store-carry-forward paradigm with random or controlled movement of resource rich mobile nodes. The application of such a model has been used in several emerging networks, including mobile ad hoc networks (MANETs), wireless sensor networks (WSNs), and delay tolerant networks (DTNs). It is well known that mobility increases the capacity of MANETs by reducing the number of relays for routing, prolonging the lifespan of WSNs by using mobile nodes in place of bottleneck static sensors, and ensuring network connectivity in DTNs using mobile nodes to connect different parts of a disconnected network. Trajectory planning and the coordination of mobile nodes are two important design issues aiming to optimize or balance several measures,including delay, average number of relays, and moving distance. In this paper, we propose a new controlled mobility model with an expected polylogarithmic number of relays to achieve a good balance among several contradictory goals, including delay, the number of relays, and moving distance. The model is based on the small-world model where each static node has "short" link connections to its nearest neighbors and "long" link connections to other nodes following a certain probability distribution. Short links are regular wireless connections whereas long links are implemented using mobile nodes. Various issues are considered, including trade-offs between delay and average number of relays, selection of the number of mobilenodes, and selection of the number of long links. The effectiveness of the proposed model is evaluated analytically as well as through simulation.
Robustness of Diversity Induced Synchronization Transition in a Delayed Small-World Neuronal Network
TANG Jun; QU Li-Cheng; LUO Jin-Ming
2011-01-01
In a diverse and delayed small-world neuronal network, we have identified the oscillatory-like synchronization transition between anti-phase and complete synchronization [Phys. Rev. E 83(2011)046207]. Here we study the influence of the network topology and noise on the synchronization transition. The robustness of this transition is investigated. The results show that: (I) the synchronization transition is robust to the neuron number N in the network; (ii) only when the coupled neighbor number k is in the region [4,10], does the synchronization transition exist; (iii) to some extent, the synchronization is destroyed by noise and the oscillatory-like synchronization transition exists for relatively weak noise (D <0.003).%In a diverse and delayed small-world neuronal network,we have identified the oscillatory-like synchronization transition between anti-phase and complete synchronization [Phys.Rev.E 83 (2011) 046207].Here we study the influence of the network topology and noise on the synchronization transition.The robustness of this transition is investigated.The results show that:(i) the synchronization transition is robust to the neuron number N in the network;(ii) only when the coupled neighbor number k is in the region [4,10],does the synchronization transition exist;(iii) to some extent,the synchronization is destroyed by noise and the oscillatory-like synchronization transition exists for relatively weak noise (D ＜0.003).In the theoretical study of neuron systems,the synchronized behavior of a population of interacting neurons,namely,a neuronal network,is a hot issue due to its importance to the processing and transmission of information.[1] Many types of synchronization are identified in neuronal networks,such as complete synchronization,phase synchronization,anti-phase synchronization,phase-lock synchronization,cluster synchronization and lag synchronization.[2
Synchronization transition of identical phase oscillators in a directed small-world network.
Tönjes, Ralf; Masuda, Naoki; Kori, Hiroshi
2010-09-01
We numerically study a directed small-world network consisting of attractively coupled, identical phase oscillators. While complete synchronization is always stable, it is not always reachable from random initial conditions. Depending on the shortcut density and on the asymmetry of the phase coupling function, there exists a regime of persistent chaotic dynamics. By increasing the density of shortcuts or decreasing the asymmetry of the phase coupling function, we observe a discontinuous transition in the ability of the system to synchronize. Using a control technique, we identify the bifurcation scenario of the order parameter. We also discuss the relation between dynamics and topology and remark on the similarity of the synchronization transition to directed percolation. PMID:20887048
Emergence of small-world anatomical networks in self-organizing clustered neuronal cultures
de Santos-Sierra, Daniel; Leyva, Inmaculada; Almendral, Juan A; Anava, Sarit; Ayali, Amir; Papo, David; Boccaletti, Stefano
2014-01-01
In vitro primary cultures of dissociated invertebrate neurons from locust ganglia are used to experimentally investigate the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. At all the different stages of the culture's development, identification of neurons' and neurites' location by means of a dedicated software allows to ultimately extract an adjacency matrix from each image of the culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main network's characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graph's micro- and meso-scale properties emerge. Finally, we identify the main physical processes ruling the culture's morphological transformati...
The Griffiths Phase on Hierarchical Modular Networks with Small-world Edges
Li, Shanshan
2016-01-01
The Griffiths phase has been proposed to induce a stretched critical regime that facilitates self organizing of brain networks for optimal function. This phase stems from the intrinsic structural heterogeneity of brain networks, such as the hierarchical modular structure. In this work, we extend this concept to modified hierarchical networks with small-world connections based on Hanoi networks [1]. Through extensive simulations, we identify the essential role played by the exponential distribution of the inter-moduli connectivity probability across hierarchies on the emergence of the Griffiths phase in this network. Additionally, the spectral analysis on the adjacency matrix of the relevant networks [2] shows that a localized principle eigenvector is not necessarily the fingerprint of the Griffiths phase.
Mapping small-world properties through development in the human brain: disruption in schizophrenia.
Dardo Tomasi
Full Text Available Evidence from imaging studies suggests that the human brain has a small-world network topology that might be disrupted in certain brain disorders. However, current methodology is based on global graph theory measures, such as clustering, C, characteristic path length, L, and small-worldness, S, that lack spatial specificity and are insufficient to identify regional brain abnormalities. Here we propose novel ultra-fast methodology for mapping local properties of brain network topology such as local C, L and S (lC, lL and lS in the human brain at 3-mm isotropic resolution from 'resting-state' magnetic resonance imaging data. Test-retest datasets from 40 healthy children/adolescents were used to demonstrate the overall good reliability of the measures across sessions and computational parameters (intraclass correlation > 0.5 for lC and lL and their low variability across subjects (< 29%. Whereas regions with high local functional connectivity density (lFCD; local degree in posterior parietal and occipital cortices demonstrated high lC and short lL, subcortical regions (globus pallidus, thalamus, hippocampus and amygdala, cerebellum (lobes and vermis, cingulum and temporal cortex also had high, lS, demonstrating stronger small-world topology than other hubs. Children/adolescents had stronger lFCD, higher lC and longer lL in most cortical regions and thalamus than 74 healthy adults, consistent with pruning of functional connectivity during maturation. In contrast, lFCD, lC and lL were weaker in thalamus and midbrain, and lL was shorter in frontal cortical regions and cerebellum for 69 schizophrenia patients than for 74 healthy controls, suggesting exaggerated pruning of connectivity in schizophrenia. Follow up correlation analyses for seeds in thalamus and midbrain uncovered lower positive connectivity of these regions in thalamus, putamen, cerebellum and frontal cortex (cingulum, orbitofrontal, inferior frontal and lower negative connectivity in
Six Degrees of Information Seeking: Stanley Milgram and the Small World of the Library
James, Kathryn
2006-01-01
Stanley Milgram's 1967 "small world" social connectivity study is used to analyze information connectivity, or patron information-seeking behavior. The "small world" study, upon examination, offers a clear example of the failure of social connectivity. This failure is used to highlight the importance of the subjectivities of patron experience of…
Immunizations on small worlds of tree-based wireless sensor networks
The sensor virus is a serious threat, as an attacker can simply send a single packet to compromise the entire sensor network. Epidemics become drastic with link additions among sensors when the small world phenomena occur. Two immunization strategies, uniform immunization and temporary immunization, are conducted on small worlds of tree-based wireless sensor networks to combat the sensor viruses. With the former strategy, the infection extends exponentially, although the immunization effectively reduces the contagion speed. With the latter strategy, recurrent contagion oscillations occur in the small world when the spatial-temporal dynamics of the epidemic are considered. The oscillations come from the small-world structure and the temporary immunization. Mathematical analyses on the small world of the Cayley tree are presented to reveal the epidemic dynamics with the two immunization strategies. (general)
Local Interactions and the Emergence of a Twitter Small-World Network
Ch'ng, Eugene
2015-01-01
The small-world phenomenon is found in many self-organising systems. Systems configured in small-world networks spread information more easily than in random or regular lattice-type networks. Whilst it is a known fact that small-world networks have short average path length and high clustering coefficient in self-organising systems, the ego centralities that maintain the cohesiveness of small-world network have not been formally defined. Here we show that instantaneous events such as the release of news items via Twitter, coupled with active community arguments related to the news item form a particular type of small-world network. Analysis of the centralities in the network reveals that community arguments maintain the small-world network whilst actively maintaining the cohesiveness and boundary of the group. The results demonstrate how an active Twitter community unconsciously forms a small-world network whilst interacting locally with a bordering community. Over time, such local interactions brought about ...
Zhou, Guangye; Li, Chengren; Li, Tingting; Yang, Yi; Wang, Chen; He, Fangjun; Sun, Jingchang
2016-09-01
Some typical dual-ring erbium-doped fiber lasers with hyperchaos behaviors are taken as nodes to construct two kinds of small-world networks-NW and WS networks. Based on Lyapunov stability theorem, the appropriate controllers are designed and the outer synchronization between the small-world networks with diverse structures and different node numbers is further investigated. The simulation results show that the perfect synchronization between the complex small-world networks is realized, which is of potential application for all optical communication network.
The conundrum of functional brain networks: small-world or fractal modularity
Gallos, Lazaros K; Sigman, Mariano
2011-01-01
The human brain is organized in functional modules. Such an organization poses a conundrum: modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture may solve this problem. However, there is intrinsic tension between shortcuts generating small-worlds and the persistence of modules. Here we provide a solution to this puzzle. We show that the functional brain network formed by percolation of strong links is highly modular. Contrary to the common view, modules are self-similar and therefore are very far from being small-world. Incorporating the weak ties to the network converts it into a small-world preserving an underlying backbone of well-defined modules. Weak ties are organized precisely as predicted by theory maximizing information transfer with minimal wiring costs. This trade-off architecture is reminiscent of the "strength of weak ties"...
Avoiding the "It's a Small World" Effect: A Lesson Plan to Explore Diversity
Endacott, Jason L.; Bowles, Freddie A.
2013-01-01
Classroom instruction about other cultures all too often resembles the Disney version of "It's a Small World" with Fantasyland-like cultural stereotypes, ceremonial activities, and traditional dress that can lead to serious
Local stability and Hopf bifurcation in small-world delayed networks
The notion of small-world networks, recently introduced by Watts and Strogatz, has attracted increasing interest in studying the interesting properties of complex networks. Notice that, a signal or influence travelling on a small-world network often is associated with time-delay features, which are very common in biological and physical networks. Also, the interactions within nodes in a small-world network are often nonlinear. In this paper, we consider a small-world networks model with nonlinear interactions and time delays, which was recently considered by Yang. By choosing the nonlinear interaction strength as a bifurcation parameter, we prove that Hopf bifurcation occurs. We determine the stability of the bifurcating periodic solutions and the direction of the Hopf bifurcation by applying the normal form theory and the center manifold theorem. Finally, we show a numerical example to verify the theoretical analysis
Emergence of small-world anatomical networks in self-organizing clustered neuronal cultures.
Daniel de Santos-Sierra
Full Text Available In vitro primary cultures of dissociated invertebrate neurons from locust ganglia are used to experimentally investigate the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. At all the different stages of the culture's development, identification of neurons' and neurites' location by means of a dedicated software allows to ultimately extract an adjacency matrix from each image of the culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main network's characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graph's micro- and meso-scale properties emerge. Finally, we identify the main physical processes ruling the culture's morphological transformations, and embed them into a simplified growth model qualitatively reproducing the overall set of experimental observations.
An effective method to improve the robustness of small-world networks under attack
In this study, the robustness of small-world networks to three types of attack is investigated. Global efficiency is introduced as the network coefficient to measure the robustness of a small-world network. The simulation results prove that an increase in rewiring probability or average degree can enhance the robustness of the small-world network under all three types of attack. The effectiveness of simultaneously increasing both rewiring probability and average degree is also studied, and the combined increase is found to significantly improve the robustness of the small-world network. Furthermore, the combined effect of rewiring probability and average degree on network robustness is shown to be several times greater than that of rewiring probability or average degree individually. This means that small-world networks with a relatively high rewiring probability and average degree have advantages both in network communications and in good robustness to attacks. Therefore, simultaneously increasing rewiring probability and average degree is an effective method of constructing realistic networks. Consequently, the proposed method is useful to construct efficient and robust networks in a realistic scenario. (interdisciplinary physics and related areas of science and technology)
Achieving Small World Properties using Bio-Inspired Techniques in Wireless Networks
Agarwal, Rachit; Gauthier, Vincent; Becker, Monique; Yeo, Chai Kiat; Lee, Bu Sung
2011-01-01
Self-Organization properties of the nodes play an important role in an autonomous wireless sensor environment in achieving network wide characteristics. Self-Organization can be used to achieve small world characteristics in a network. In real networks, however, where there is non-uniform distribution of nodes and overall connectivity of the network is less, achieving small world properties while increasing connectivity must be studied. We believe that network connectivity can be increased and small world properties can be achieved with the help of beamforming, biologically inspired algorithms and using local information. Most of the researches performed in direction of achieving above mentioned goals in wireless networks assume knowledge of network with either heterogeneous or hybrid uniform deployment. We propose that without the knowledge of the global environment or introduction of any special features in the network, we can achieve our goal with the help of inspirations from the nature in a non-uniform n...
Potts model on directed small-world Voronoi-Delaunay lattices
Marques, R. M.; Lima, F. W. S.; Costa Filho, Raimundo N.
2016-06-01
The critical properties of the Potts model with q = 3 and 4 states in two-dimensions on directed small-world Voronoi-Delaunay random lattices with quenched connectivity disorder are investigated. This disordered system is simulated by applying the Monte Carlo update heat bath algorithm. The Potts model on these directed small-world random lattices presents in fact a second-order phase transition with new critical exponents for q = 3 and value of the rewiring probability p = 0.01, but for q = 4 the system exhibits only a first-order phase transition independent of p (0 < p < 1).
Immunizations on small worlds of tree-based wireless sensor networks
Li, Qiao; Zhang, Bai-Hai; Cui, Ling-Guo; Fan, Zhun; Vasilakos, Athanasios V.
2012-01-01
, are conducted on small worlds of tree-based wireless sensor networks to combat the sensor viruses. With the former strategy, the infection extends exponentially, although the immunization effectively reduces the contagion speed. With the latter strategy, recurrent contagion oscillations occur in the......The sensor virus is a serious threat, as an attacker can simply send a single packet to compromise the entire sensor network. Epidemics become drastic with link additions among sensors when the small world phenomena occur. Two immunization strategies, uniform immunization and temporary immunization...
Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small world properties of the underlying neural systems. (authors)
Damage spreading in spatial and small-world random Boolean networks
Lu, Qiming; Teuscher, Christof
2014-02-01
The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean networks (RBNs) are commonly used as a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other nonrandom connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the Hamming distance at very low connectivities (K¯≪1) and that the critical connectivity of stability Ks changes compared to random networks. At higher K¯, this scaling remains unchanged. We also show that the Hamming distance of spatially local networks scales with a power law as the system size N increases, but with a different exponent for local and small-world networks. The scaling arguments for small-world networks are obtained with respect to the system sizes and strength of spatially local connections. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.
Small-world topology of functional connectivity in randomly connected dynamical systems
Hlinka, Jaroslav; Hartman, David; Paluš, Milan
2012-01-01
Roč. 22, č. 3 (2012), art no 033107. ISSN 1054-1500 R&D Projects: GA ČR GCP103/11/J068 Institutional support: RVO:67985807 Keywords : graph theory * nonlinear dynamical systems * small-world networks Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.188, year: 2012
Dynamics in small worlds of tree topologies of wireless sensor networks
Li, Qiao; Zhang, Baihai; Fan, Zhun;
2012-01-01
Tree topologies, which construct spatial graphs with large characteristic path lengths and small clustering coefficients, are ubiquitous in deployments of wireless sensor networks. Small worlds are investigated in tree-based networks. Due to link additions, characteristic path lengths reduce rapi...
The small world phenomenon and assortative mixing in Polish corporate board and director networks
Sankowska, Anna; Siudak, Dariusz
2016-02-01
This paper investigates the corporate board and director networks in the Polish capital market in 2014. We examined real board and director networks in comparison with networks that were randomly constructed. Through empirical analyses, we demonstrated that the real networks have the characteristics of small-world networks. In addition, the networks are assortative and highly clustered, which imposes certain behaviors on them.
Extraction of Network Topology From Multi-Electrode Recordings: Is there a Small-World Effect?
Gerhard, Felipe; Pipa, Gordon; Lima, Bruss; Neuenschwander, Sergio; Gerstner, Wulfram
2011-01-01
The simultaneous recording of the activity of many neurons poses challenges for multivariate data analysis. Here, we propose a general scheme of reconstruction of the functional network from spike train recordings. Effective, causal interactions are estimated by fitting generalized linear models on the neural responses, incorporating effects of the neurons' self-history, of input from other neurons in the recorded network and of modulation by an external stimulus. The coupling terms arising from synaptic input can be transformed by thresholding into a binary connectivity matrix which is directed. Each link between two neurons represents a causal influence from one neuron to the other, given the observation of all other neurons from the population. The resulting graph is analyzed with respect to small-world and scale-free properties using quantitative measures for directed networks. Such graph-theoretic analyses have been performed on many complex dynamic networks, including the connectivity structure between different brain areas. Only few studies have attempted to look at the structure of cortical neural networks on the level of individual neurons. Here, using multi-electrode recordings from the visual system of the awake monkey, we find that cortical networks lack scale-free behavior, but show a small, but significant small-world structure. Assuming a simple distance-dependent probabilistic wiring between neurons, we find that this connectivity structure can account for all of the networks' observed small-world ness. Moreover, for multi-electrode recordings the sampling of neurons is not uniform across the population. We show that the small-world-ness obtained by such a localized sub-sampling overestimates the strength of the true small-world structure of the network. This bias is likely to be present in all previous experiments based on multi-electrode recordings. PMID:21344015
Extraction of network topology from multi-electrode recordings: Is there a small-world effect?
Felipe eGerhard
2011-02-01
Full Text Available The simultaneous recording of the activity of many neurons poses challenges for multivariate data analysis. Here, we propose a general scheme of reconstruction of the functional network from spike train recordings. Effective, causal interactions are estimated by fitting Generalized Linear Models (GLMs on the neural responses, incorporating effects of the neurons' self-history, of input from other neurons in the recorded network and of modulation by an external stimulus. The coupling terms arising from synaptic input can be transformed by thresholding into a binary connectivity matrix which is directed. Each link between two neurons represents a causal influence from one neuron to the other, given the observation of all other neurons from the population. The resulting graph is analyzed with respect to small-world and scale-free properties using quantitative measures for directed networks. Such graph-theoretic analyses have been performed on many complex dynamic networks, including the connectivity structure between different brain areas. Only few studies have attempted to look at the structure of cortical neural networks on the level of individual neurons. Here, using multi-electrode recordings from the visual system of the awake monkey, we find that cortical networks lack scale-free behavior, but show a small, but significant small-world structure. Assuming a simple distance-dependent probabilistic wiring between neurons, we find that this connectivity structure can account for all of the networks' observed small-world-ness. Moreover, for multi-electrode recordings the sampling of neurons is not uniform across the population. We show that the small-world-ness obtained by such a localized sub-sampling overestimates the strength of the true small-world-structure of the network. This bias is likely to be present in all previous experiments based on multi-electrode recordings.
Dynamics of organizational rumor communication on connecting multi-small-world networks
We study the dynamics of an epidemic-like model for the spread of a rumor on a connecting multi-small-world-network (CM-SWN) model, which represents organizational communication in the real world. It has been shown that this model exhibits a transition between regimes of localization and propagation at a finite value of network randomness. Here, by numerical means, we perform a quantitative characterization of the evolution in the three groups under two evolution rules, namely the conformity and obeying principles. The variant of a dynamic CM-SWN, where the quenched disorder of small-world networks is replaced by randomly changing connections between individuals in a single network and stable connection by star nodes between networks, is also analysed in detail and compared with a mean-field approximation. (general)
Synchronization and Control of Halo-Chaos in Beam Transport Network with Small World Topology
LIU Qiang; FANG Jin-Qing; LI Yong
2007-01-01
The synchronous conditions of two kinds of the small-world (SW) network are studied.The small world topology can affect on dynamical behaviors of the beam transport network (BTN) largely,if the BTN is constructed with the SWtopology,the global linear coupling and special linear feedback can realize the synchronization control of beam halo-chaos as well as periodic state in the BTN with the SW topology,respectively.This important result can provide an effective way for the experimental study and the engineering design of the BTN in the high-current accelerator driven radioactive clean nuclear power systems,and may have potential use in prospective applications for halo-chaos secure communication.
Complete and phase synchronization in a heterogeneous small-world neuronal network
Han Fang; Lu Qi-Shao; Wiercigroch Marian; Ji Quan-Bao
2009-01-01
Synchronous firing of neurons is thought to be important for information communication in neuronal networks. This paper investigates the complete and phase synchronization in a heterogeneous small-world chaotic Hindmarsh-Rose neuronal network. The effects of various network parameters on synchronization behaviour are discussed with some biological explanations. Complete synchronization of small-world neuronal nctworks is studied theoretically by the master stability function method. It is shown that the coupling strength necessary for complete or phase synchronization decreases with the neuron number, the node degree and the connection density are increased. The cffect of heterogeneity of neuronal networks is also considered and it is found that the network heterogeneity has an advcrse effect on synchrony.
Complete and phase synchronization in a heterogeneous small-world neuronal network
Synchronous firing of neurons is thought to be important for information communication in neuronal networks. This paper investigates the complete and phase synchronization in a heterogeneous small-world chaotic Hindmarsh–Rose neuronal network. The effects of various network parameters on synchronization behaviour are discussed with some biological explanations. Complete synchronization of small-world neuronal networks is studied theoretically by the master stability function method. It is shown that the coupling strength necessary for complete or phase synchronization decreases with the neuron number, the node degree and the connection density are increased. The effect of heterogeneity of neuronal networks is also considered and it is found that the network heterogeneity has an adverse effect on synchrony. (general)
GENERAL: Complete and phase synchronization in a heterogeneous small-world neuronal network
Han, Fang; Lu, Qi-Shao; Wiercigroch, Marian; Ji, Quan-Bao
2009-02-01
Synchronous firing of neurons is thought to be important for information communication in neuronal networks. This paper investigates the complete and phase synchronization in a heterogeneous small-world chaotic Hindmarsh-Rose neuronal network. The effects of various network parameters on synchronization behaviour are discussed with some biological explanations. Complete synchronization of small-world neuronal networks is studied theoretically by the master stability function method. It is shown that the coupling strength necessary for complete or phase synchronization decreases with the neuron number, the node degree and the connection density are increased. The effect of heterogeneity of neuronal networks is also considered and it is found that the network heterogeneity has an adverse effect on synchrony.
Dynamics of organizational rumor communication on connecting multi-small-world networks
Xing Qi-Bin; Zhang Yuan-Biao; Liang Zhi-Ning; ZhangFan
2011-01-01
We study the dynamics of an epidemic-like model for the spread of a rumor on a connecting multi-small-world-network (CM-SWN) model,which represents organizational communication in the real world.It has been shown that this model exhibits a transition between regimes of localization and propagation at a finite value of network randomness.Here,by numerical means,we perform a quantitative characterization of the evolution in the three groups under two evolution rules,namely the conformity and obeying principles.The variant of a dynamic CM-SWN,where the quenched disorder of small-world networks is replaced by randomly changing connections between individuals in a single network and stable connection by star nodes between networks,is also analysed in detail and compared with a mean-field approximation.
Self-Organized Criticality in Small-World Networks Based on the Social Balance Dynamics
MENG Qing-Kuan
2011-01-01
A node model is proposed to study the self-organized criticality in the small-world networks which represent the social networks. Based on the node model and the social balance dynamics, the social networks are mapped to the thermodynamic systems and the phenomena are studied with physical methods. It is found that the avalanche in the small-world networks at the critical state satisfies the power-law distribution spatially and temporally.%A node model is proposed to study the self-organized criticality in the small-world networks which represent the social networks.Based on the node model and the social balance dynamics,the social networks are mapped to the thermodynamic systems and the phenomena are studied with physical methods.It is found that the avalanche in the small-world networks at the critical state satisfies the power-law distribution spatially and temporally.The balance dynamics on social networks[1] based on the notion of social balance has been studied.[2-4]In Ref.[2],the authors studied the triad balance dynamic on a completely connected network representing a social network.At each step,they choose a triad relation from the social network and let it evolve.When the network gets dynamically balanced,they will reach the distributions of each triad relation.Moreover,other researchers subsequently carried out several studies on balance dynamics.[5,6]In this Letter,a node model is proposed to describe the triad relations,so the edge relations in Ref.[2] are changed to node relations,which may be more a universal method to study the phenomena in social networks.We will introduce the node model later.
Complex Behavior in an Integrate-and-Fire Neuron Model Based on Small World Networks
LIN Min; CHEN Tian-Lun
2005-01-01
Based on our previously pulse-coupled integrate-and-fire neuron model in small world networks, we investigate the complex behavior of electroencephalographic (EEG)-like activities produced by such a model. We find EEG-like activities have obvious chaotic characteristics. We also analyze the complex behaviors of EEG-like signals,such as spectral analysis, reconstruction of the phase space, the correlation dimension, and so on.
THE COMPLEX, YET SMALL WORLD OF GLOBAL MULTINATIONALS – INSIGHTS ON SOME APPARENT PARADOXES
OGREAN Claudia; Herciu, Mihaela
2013-01-01
Globalization, as it is today, shapes a complex, networked world – that embeds all the features (both vantages and liabilities) of a complex adaptive system. Being one of the biggest networks that define this world, the system of international business – characterized by diversity, (nondeterministic) interconnectivity and uncertainty – is also characterized by the small-world syndrome. Global multinationals are the best supporting agents in order to dismantle the apparent paradox of the compl...
GENERAL: Synchronization of time-delay chaotic systems on small-world networks with delayed coupling
Qi, Wei; Wang, Ying-Hai
2009-04-01
By using the well-known Ikeda model as the node dynamics, this paper studies synchronization of time-delay systems on small-world networks where the connections between units involve time delays. It shows that, in contrast with the undelayed case, networks with delays can actually synchronize more easily. Specifically, for randomly distributed delays, time-delayed mutual coupling suppresses the chaotic behaviour by stabilizing a fixed point that is unstable for the uncoupled dynamical system.
Smallest-Small-World Cellular Harmony Search for Optimization of Unconstrained Benchmark Problems
Sung Soo Im; Do Guen Yoo; Joong Hoon Kim
2013-01-01
We presented a new hybrid method that combines cellular harmony search algorithms with the Smallest-Small-World theory. A harmony search (HS) algorithm is based on musical performance processes that occur when a musician searches for a better state of harmony. Harmony search has successfully been applied to a wide variety of practical optimization problems. Most of the previous researches have sought to improve the performance of the HS algorithm by changing the pitch adjusting rate and harmo...
Small Worlds in Networks of Inventors and the Role of Science: An Analysis of France.
Francesco Lissoni; Patrick Llerena; Bulat Sanditov
2011-01-01
· Using data on patent applications at European Patent Office, we examine the structural properties of networks of inventors in France in different technologies, and how they depend from the inventive activity of scientists from universities and public research organizations (PROs). We revisit earlier findings on small world properties of social networks of inventors, and propose more rigorous tests of such hypothesis. We find that academic and PRO inventors contribute significantly to patent...
Continuous Forest Fire Propagation in a Local Small World Network Model
F. Aguayo; A. Fuentes; Clerc, J.-P.; Porterie, B.
2013-01-01
This paper presents the development of a new continuous forest fire model implemented as a weighted local small-world network approach. This new approach was designed to simulate fire patterns in real, heterogeneous landscapes. The wildland fire spread is simulated on a square lattice in which each cell represents an area of the land's surface. The interaction between burning and non-burning cells, in the present work induced by flame radiation, may be extended well beyond nearest neighbors. ...
Complex Behavior in an Integrate-and-Fire Neuron Model Based on Small World Networks
Based on our previously pulse-coupled integrate-and-fire neuron model in small world networks, we investigate the complex behavior of electroencephalographic (EEG)-like activities produced by such a model. We find EEG-like activities have obvious chaotic characteristics. We also analyze the complex behaviors of EEG-like signals, such as spectral analysis, reconstruction of the phase space, the correlation dimension, and so on.
A small-world network derived from the deterministic uniform recursive tree by line graph operation
Hou, Pengfeng; Zhao, Haixing; Mao, Yaping; Wang, Zhao
2016-03-01
The deterministic uniform recursive tree ({DURT}) is one of the deterministic versions of the uniform recursive tree ({URT}). Zhang et al (2008 Eur. Phys. J. B 63 507-13) studied the properties of DURT, including its topological characteristics and spectral properties. Although DURT shows a logarithmic scaling with the size of the network, DURT is not a small-world network since its clustering coefficient is zero. Lu et al (2012 Physica A 391 87-92) proposed a deterministic small-world network by adding some edges with a simple rule in each DURT iteration. In this paper, we intoduce a method for constructing a new deterministic small-world network by the line graph operation in each DURT iteration. The line graph operation brings about cliques at each node of the previous given graph, and the resulting line graph possesses larger clustering coefficients. On the other hand, this operation can decrease the diameter at almost one, then giving the analytic solutions to several topological characteristics of the model proposed. Supported by The Ministry of Science and Technology 973 project (No. 2010C B334708); National Science Foundation of China (Nos. 61164005, 11161037, 11101232, 11461054, 11551001); The Ministry of education scholars and innovation team support plan of Yangtze River (No. IRT1068); Qinghai Province Nature Science Foundation Project (Nos. 2012-Z-943, 2014-ZJ-907).
Yu, Haitao; Guo, Xinmeng; Wang, Jiang; Deng, Bin; Wei, Xile
2015-10-01
The phenomenon of vibrational resonance is investigated in adaptive Newman-Watts small-world neuronal networks, where the strength of synaptic connections between neurons is modulated based on spike-timing-dependent plasticity. Numerical results demonstrate that there exists appropriate amplitude of high-frequency driving which is able to optimize the neural ensemble response to the weak low-frequency periodic signal. The effect of networked vibrational resonance can be significantly affected by spike-timing-dependent plasticity. It is shown that spike-timing-dependent plasticity with dominant depression can always improve the efficiency of vibrational resonance, and a small adjusting rate can promote the transmission of weak external signal in small-world neuronal networks. In addition, the network topology plays an important role in the vibrational resonance in spike-timing-dependent plasticity-induced neural systems, where the system response to the subthreshold signal is maximized by an optimal network structure. Furthermore, it is demonstrated that the introduction of inhibitory synapses can considerably weaken the phenomenon of vibrational resonance in the hybrid small-world neuronal networks with spike-timing-dependent plasticity.
Damage Spreading in Spatial and Small-world Random Boolean Networks
Lu, Qiming [Fermilab; Teuscher, Christof [Portland State U.
2014-02-18
The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean Networks (RBNs) are commonly used a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other non-random connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the relevant component at very low connectivities ($\\bar{K} \\ll 1$) and that the critical connectivity of stability $K_s$ changes compared to random networks. At higher $\\bar{K}$, this scaling remains unchanged. We also show that the relevant component of spatially local networks scales with a power-law as the system size N increases, but with a different exponent for local and small-world networks. The scaling behaviors are obtained by finite-size scaling. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.
Damage spreading in spatial and small-world random boolean networks
Lu, Qiming [Los Alamos National Laboratory; Teuscher, Christof [Los Alamos National Laboratory
2008-01-01
Random Boolean Networks (RBNs) are often used as generic models for certain dynamics of complex systems, ranging from social networks, neural networks, to gene or protein interaction networks. Traditionally, RBNs are interconnected randomly and without considering any spatial arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, small-world, or other non-random connections. Here we explore the RBN network topology between extreme local connections, random small-world, and random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the relevant component at very low connectivities ({bar K} << 1) and that the critical connectivity of stability K{sub s} changes compared to random networks. At higher {bar K}, this scaling remains unchanged. We also show that the relevant component of spatially local networks scales with a power-law as the system size N increases, but with a different exponent for local and small-world networks. The scaling behaviors are obtained by finite-size scaling. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key trade-offs between damage spreading (robustness), the network wiring cost, and the network's communication characteristics.
On the agreement between small-world-like OFC model and real earthquakes
Ferreira, Douglas S.R., E-mail: douglas.ferreira@ifrj.edu.br [Instituto Federal de Educação, Ciência e Tecnologia do Rio de Janeiro, Paracambi, RJ (Brazil); Geophysics Department, Observatório Nacional, Rio de Janeiro, RJ (Brazil); Papa, Andrés R.R., E-mail: papa@on.br [Geophysics Department, Observatório Nacional, Rio de Janeiro, RJ (Brazil); Instituto de Física, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ (Brazil); Menezes, Ronaldo, E-mail: rmenezes@cs.fit.edu [BioComplex Laboratory, Computer Sciences, Florida Institute of Technology, Melbourne (United States)
2015-03-20
In this article we implemented simulations of the OFC model for earthquakes for two different topologies: regular and small-world, where in the latter the links are randomly rewired with probability p. In both topologies, we have studied the distribution of time intervals between consecutive earthquakes and the border effects present in each one. In addition, we also have characterized the influence that the probability p produces in certain characteristics of the lattice and in the intensity of border effects. From the two topologies, networks of consecutive epicenters were constructed, that allowed us to analyze the distribution of connectivities of each one. In our results distributions arise belonging to a family of non-traditional distributions functions, which agrees with previous studies using data from actual earthquakes. Our results reinforce the idea that the Earth is in a critical self-organized state and furthermore point towards temporal and spatial correlations between earthquakes in different places. - Highlights: • OFC model simulations for regular and small-world topologies. • For small-world topology distributions agree remarkably well with actual earthquakes. • Reinforce the idea of a critical self-organized state for the Earth's crust. • Point towards temporal and spatial correlations between far earthquakes in far places.
Small Worlds Week: An online celebration of planetary science using social media to reach millions
Mayo, Louis
2015-11-01
In celebration of the many recent discoveries from New Horizons, Dawn, Rosetta, and Cassini, NASA launched Small Worlds Week, an online, social media driven outreach program leveraging the infrastructure of Sun-Earth Days that included a robust web design, exemplary education materials, hands-on fun activities, multimedia resources, science and career highlights, and a culminating social media event. Each day from July 6-9, a new class of solar system small worlds was featured on the website: Monday-comets, Tuesday-asteroids, Wednesday-icy moons, and Thursday-dwarf planets. Then on Friday, July 10, nine scientists from Goddard Space Flight Center, Jet Propulsion Laboratory, Naval Research Laboratory, and Lunar and Planetary Institute gathered online for four hours to answer questions from the public via Facebook and Twitter. Throughout the afternoon the scientists worked closely with a social media expert and several summer interns to reply to inquirers and to archive their chats. By all accounts, Small Worlds Week was a huge success with 37 million potential views of the social media Q&A posts. The group plans to improve and replicate the program during the school year with a more classroom focus, and then to build and extend the program to be held every year. For more information, visit http:// sunearthday.nasa.gov or catch us on Twitter, #nasasww.
Toyota, Norihito
2011-01-01
We reformulated the string formalism given by Aoyama, using an adjacent matrix of a network and introduced a series of generalized clustering coefficients based on it. Furthermore we numerically evaluated Milgram condition proposed by their article in order to explore $q$-$th$ degrees of separation in scale free networks. In this article, we apply the reformulation to small world networks and numerically evaluate Milgram condition, especially the separation number of small world networks and its relation to cycle structures are discussed. Considering the number of non-zero elements of an adjacent matrix, the average path length and Milgram condition, we show that the formalism proposed by us is effective to analyze the six degrees of separation, especially effective for analyzing the relation between the separation number and cycle structures in a network. By this analysis of small world networks, it proves that a sort of power low holds between $M_n$, which is a key quantity in Milgram condition, and the gen...
On the agreement between small-world-like OFC model and real earthquakes
In this article we implemented simulations of the OFC model for earthquakes for two different topologies: regular and small-world, where in the latter the links are randomly rewired with probability p. In both topologies, we have studied the distribution of time intervals between consecutive earthquakes and the border effects present in each one. In addition, we also have characterized the influence that the probability p produces in certain characteristics of the lattice and in the intensity of border effects. From the two topologies, networks of consecutive epicenters were constructed, that allowed us to analyze the distribution of connectivities of each one. In our results distributions arise belonging to a family of non-traditional distributions functions, which agrees with previous studies using data from actual earthquakes. Our results reinforce the idea that the Earth is in a critical self-organized state and furthermore point towards temporal and spatial correlations between earthquakes in different places. - Highlights: • OFC model simulations for regular and small-world topologies. • For small-world topology distributions agree remarkably well with actual earthquakes. • Reinforce the idea of a critical self-organized state for the Earth's crust. • Point towards temporal and spatial correlations between far earthquakes in far places
Shi, Li; Niu, Xiaoke; Wan, Hong
2015-05-01
The biological networks have been widely reported to present small-world properties. However, the effects of small-world network structure on population's encoding performance remain poorly understood. To address this issue, we applied a small world-based framework to quantify and analyze the response dynamics of cell assemblies recorded from rat primary visual cortex, and further established a population encoding model based on small world-based generalized linear model (SW-GLM). The electrophysiological experimental results show that the small world-based population responses to different topological shapes present significant variation (t test, p 0.8), while no significant variation was found for control networks without considering their spatial connectivity (t test, p > 0.05; effect size: Hedge's g numerical experimental results show that the predicted response under SW-GLM is more accurate and reliable compared to the control model without small-world structure, and the decoding performance is also improved about 10 % by taking the small-world structure into account. The above results suggest the important role of the small-world neural structure in encoding visual information for the neural population by providing electrophysiological and theoretical evidence, respectively. The study helps greatly to well understand the population encoding mechanisms of visual cortex. PMID:25764307
Purpose: To explore changes in functional connectivity and topological organization of brain functional networks in cirrhotic patients with minimal hepatic encephalopathy (MHE) and non hepatic encephalopathy (nonHE) and their relationship with clinical markers. Materials and methods: Resting-state functional MR imaging was acquired in 22 MHE, 29 nonHE patients and 33 healthy controls. Functional connectivity networks were obtained by computing temporal correlations between any pairs of 90 cortical and subcortical regions. Graph analysis measures were quantitatively assessed for each subject. One-way analysis of covariance was applied to identify statistical differences of functional connectivity and network parameters among three groups. Correlations between clinical markers, such as Child–Pugh scores, venous blood ammonia level, and number connection test type A (NCT-A)/digit symbol test (DST) scores, and connectivity/graph metrics were calculated. Results: Thirty functional connectivities represented by edges were found to be abnormal (P < 0.05, FDR corrected) in cirrhotic patients, in which 16 edges (53.3%) were related with sub-cortical regions. MHE patients showed abnormal small-world attributes in the functional connectivity networks. Cirrhotic patients had significantly reduced nodal degree in 8 cortical regions and increased nodal centrality in 3 cortical regions. Twenty edges were correlated with either NCT-A or DST scores, in which 13 edges were related with sub-cortical regions. No correlation was found between Child–Pugh scores and graph theoretical measures in cirrhotic patients. Conclusion: Disturbances of brain functional connectivity and small world property loss are associated with neurocognitive impairment of cirrhotic patients. Reorganization of brain network occurred during disease progression from nonHE to MHE
Power-Aware Anycast Routing in Wireless Sensor Network Exploiting Small World Effect
JIANG Nan; YANG Shu-qun; LI Ling-zhi; DING Qiu-lin
2008-01-01
By considering energy-efficient anycast routing in wireless sensor network (WSN), and combining small world characteristics of WSN with the properties of the ant algorithm, a power-aware anycast routing algorithm (SWPAR) with multi-sink nodes is proposed and evaluated. By SWPAR, the optimal sink node is found and the problem of routing path is effectively solved. Simulation results show that compared with the sink-based anycast routing protocol (SARP) and the hierarchy-based anycast routing protocol (HARP), the proposed algorithm improves network lifetime and reduces power consumption.
Evolutionary dynamics in the Bak-Sneppen model on small-world networks
Kulkarni, R. V.; Almaas, E.; Stroud, D.
1999-01-01
We study the dynamics of the Bak-Sneppen model on small-world networks. For each site in the network, we define a ``connectance,'' which measures the distance to all other sites. We find radically different patterns of activity for different sites, depending on their connectance and also on the topology of the network. For a given network, the site with the minimal connectance shows long periods of stasis interrupted by much smaller periods of activity. In contrast, the activity pattern for t...
Synchronization of Coupled Oscillators on Newman-Watts Small-World Networks
GUAN Jian-Yue; XU Xin-Jian; WU Zhi-Xi; WANG Ying-Hai
2006-01-01
We investigate the collection behaviour of coupled phase oscillators on Newman- Watts small-world networks in one and two dimensions. Each component of the network is assumed as an oscillator and each interacts with the others following the Kuramoto model. We then study the onset of global synchronization of phases and frequencies based on dynamic simulations and finite-size scah'ng. Both the phase and frequency synchronization are observed to emerge in the presence of a tiny fraction of shortcuts and enhanced with the increases of nearest neighbours and lattice dimensions.
The Dynamic Consequences of Cooperation and Competition in Small-World Networks
Fernández-Rosales, Iván Y.; Liebovitch, Larry S.; Guzmán-Vargas, Lev
2015-01-01
We present a study of the social dynamics among cooperative and competitive actors interacting on a complex network that has a small-world topology. In this model, the state of each actor depends on its previous state in time, its inertia to change, and the influence of its neighboring actors. Using numerical simulations, we determine how the distribution of final states of the actors and measures of the distances between the values of the actors at local and global levels, depend on the numb...
Chaos in complex motor networks induced by Newman—Watts small-world connections
We investigate how dynamical behaviours of complex motor networks depend on the Newman—Watts small-world (NWSW) connections. Network elements are described by the permanent magnet synchronous motor (PMSM) with the values of parameters at which each individual PMSM is stable. It is found that with the increase of connection probability p, the motor in networks becomes periodic and falls into chaotic motion as p further increases. These phenomena imply that NWSW connections can induce and enhance chaos in motor networks. The possible mechanism behind the action of NWSW connections is addressed based on stability theory. (interdisciplinary physics and related areas of science and technology)
Effects of Different Connectivity Topologies in Small World Networks on EEG-Like Activities
Based on our previously pulse-coupled integrate-and-fire neuron model in small world networks, we investigate the effects of different connectivity topologies on complex behavior of electroencephalographic-like signals produced by this model. We show that several times series analysis methods that are often used for analyzing complex behavior of electroencephalographic-like signals, such as reconstruction of the phase space, correlation dimension, fractal dimension, and the Hurst exponent within the rescaled range analysis (R/S). We find that the different connectivity topologies lead to different dynamical behaviors in models of integrate-and-fire neurons.
Nonlocal effects and counter measures in cascading failures
Witthaut, Dirk
2015-01-01
We study the propagation of cascading failures in complex supply networks with a focus on nonlocal effects occurring far away from the initial failure. It is shown that a high clustering and a small average path length of a network generally suppress nonlocal overloads. These properties are typical for many real-world networks, often called small-world networks, such that cascades propagate mostly locally in these networks. Furthermore, we analyze the spatial aspects of countermeasures based on the intentional removal of additional edges. Nonlocal actions are generally required in networks which have a low redundancy and are thus especially vulnerable to cascades.
Evaluating the transport in small-world and scale-free networks
We present a study of some properties of transport in small-world and scale-free networks. Particularly, we compare two types of transport: subject to friction (electrical case) and in the absence of friction (maximum flow). We found that in clustered networks based on the Watts–Strogatz (WS) model, for both transport types the small-world configurations exhibit the best trade-off between local and global levels. For non-clustered WS networks the local transport is independent of the rewiring parameter, while the transport improves globally. Moreover, we analyzed both transport types in scale-free networks considering tendencies in the assortative or disassortative mixing of nodes. We construct the distribution of the conductance G and flow F to evaluate the effects of the assortative (disassortative) mixing, finding that for scale-free networks, as we introduce different levels of the degree–degree correlations, the power-law decay in the conductances is altered, while for the flow, the power-law tail remains unchanged. In addition, we analyze the effect on the conductance and the flow of the minimum degree and the shortest path between the source and destination nodes, finding notable differences between these two types of transport
Synchronization of the small-world neuronal network with unreliable synapses
As is well known, synchronization phenomena are ubiquitous in neuronal systems. Recently a lot of work concerning the synchronization of the neuronal network has been accomplished. In these works, the synapses are usually considered reliable, but experimental results show that, in biological neuronal networks, synapses are usually unreliable. In our previous work, we have studied the synchronization of the neuronal network with unreliable synapses; however, we have not paid attention to the effect of topology on the synchronization of the neuronal network. Several recent studies have found that biological neuronal networks have typical properties of small-world networks, characterized by a short path length and high clustering coefficient. In this work, mainly based on the small-world neuronal network (SWNN) with inhibitory neurons, we study the effect of network topology on the synchronization of the neuronal network with unreliable synapses. Together with the network topology, the effects of the GABAergic reversal potential, time delay and noise are also considered. Interestingly, we found a counter-intuitive phenomenon for the SWNN with specific shortcut adding probability, that is, the less reliable the synapses, the better the synchronization performance of the SWNN. We also consider the effects of both local noise and global noise in this work. It is shown that these two different types of noise have distinct effects on the synchronization: one is negative and the other is positive
Smallest-Small-World Cellular Harmony Search for Optimization of Unconstrained Benchmark Problems
Sung Soo Im
2013-01-01
Full Text Available We presented a new hybrid method that combines cellular harmony search algorithms with the Smallest-Small-World theory. A harmony search (HS algorithm is based on musical performance processes that occur when a musician searches for a better state of harmony. Harmony search has successfully been applied to a wide variety of practical optimization problems. Most of the previous researches have sought to improve the performance of the HS algorithm by changing the pitch adjusting rate and harmony memory considering rate. However, there has been a lack of studies to improve the performance of the algorithm by the formation of population structures. Therefore, we proposed an improved HS algorithm that uses the cellular automata formation and the topological structure of Smallest-Small-World network. The improved HS algorithm has a high clustering coefficient and a short characteristic path length, having good exploration and exploitation efficiencies. Nine benchmark functions were applied to evaluate the performance of the proposed algorithm. Unlike the existing improved HS algorithm, the proposed algorithm is expected to have improved algorithmic efficiency from the formation of the population structure.
2014-01-01
Topology construction and control is a vital technique in wireless sensor networks. In this paper, based on small-world and scale-free concepts of complex network theory and considering the characteristics of wireless sensor network, a topology model with small-world and scale-free concepts for heterogeneous sensor network is presented. This work is achieved by applying heterogeneous sensors and preferential attachment mechanism. Furthermore, the topology evolution algorithm is designed. Fina...
无
2006-01-01
In this paper, we introduce a modified small-world network added with new links with preferential connection instead of adding randomly, then we apply Bak-Sneppen (BS) evolution model on this network. Several dynamical character of the model such as the evolution graph, fo avalanche, the critical exponent D and τ, and the distribution of mutation times of all the nodes, show particular behaviors different from those of the model based on the regular network and the small-world network.
Impact of mobility structure on the optimization of small-world networks of mobile agents
Lee, Eun
2015-01-01
In ad hoc wireless networking, units are connected to each other rather than to a central, fixed, infrastructure. Constructing and maintaining such networks create several trade-off problems between robustness, communication speed, power consumption, etc., that bridges engineering, computer science and the physics of complex systems. In this work, we address the role of mobility patterns of the agents on the optimal tuning of a small-world type network construction method. By this method, the network is updated periodically and held static between the updates. We investigate the optimal updating times for different scenarios of the movement of agents (modeling, for example, the fat-tailed trip distances, and periodicities, of human travel). We find that these mobility patterns affect the power consumption in non-trivial ways and discuss how these effects can best be handled.
Prisoner's Dilemma Game with Heterogeneous Influential Effect on Regular Small-World Networks
WU Zhi-Xi; XU Xin-Jian; WANG Ying-Hai
2006-01-01
@@ The effect of heterogeneous influence of different individuals on the maintenance of co-operative behaviour is studied in an evolutionary Prisoner's Dilemma game with players located on the sites of regular small-world networks. The players interacting with their neighbours can either co-operate or defect and update their states by choosing one of the neighbours and adopting its strategy with a probability depending on the payoff difference.The selection of the neighbour obeys a preferential rule: the more influential a neighbour, the larger the probability it is picked. It is found that this simple preferential selection rule can promote continuously the co-operation of the whole population with the strengthening of the disorder of the underlying network.
Kim, Beom Jun; Trusina, Ala; Holme, Petter; Minnhagen, Petter; Chung, Jean S; Choi, M Y
2002-08-01
A two-dimensional small-world-type network, subject to spatial prisoners' dilemma dynamics and containing an influential node defined as a special node, with a finite density of directed random links to the other nodes in the network, is numerically investigated. It is shown that the degree of cooperation does not remain at a steady state level but displays a punctuated equilibrium-type behavior manifested by the existence of sudden breakdowns of cooperation. The breakdown of cooperation is linked to an imitation of a successful selfish strategy of the influential node. It is also found that while the breakdown of cooperation occurs suddenly, its recovery requires longer time. This recovery time may, depending on the degree of steady state cooperation, either increase or decrease with an increasing number of long-range connections. PMID:12241214
Modeling and Analysis of Epidemic Diffusion within Small-World Network
Ming Liu
2012-01-01
Full Text Available To depict the rule of epidemic diffusion, two different models, the Susceptible-Exposure-Infected-Recovered-Susceptible (SEIRS model and the Susceptible-Exposure-Infected-Quarantine-Recovered-Susceptible (SEIQRS model, are proposed and analyzed within small-world network in this paper. Firstly, the epidemic diffusion models are constructed with mean-filed theory, and condition for the occurrence of disease diffusion is explored. Then, the existence and global stability of the disease-free equilibrium and the endemic equilibrium for these two complex epidemic systems are proved by differential equations knowledge and Routh-Hurwiz theory. At last, a numerical example which includes key parameters analysis and critical topic discussion is presented to test how well the proposed two models may be applied in practice. These works may provide some guidelines for decision makers when coping with epidemic diffusion controlling problems.
On the agreement between small-world-like OFC model and real earthquakes
Ferreira, Douglas S R; Menezes, Ronaldo
2014-01-01
In this article we implemented simulations of the OFC model for earthquakes for two different topologies: regular and small-world, where in the latter the links are randomly rewired with probability $p$ . In both topologies, we have studied the distribution of time intervals between consecutive earthquakes and the border effects present in each one. In addition, we also have characterized the influence that the probability $p$ produces in certain characteristics of the lattice and in the intensity of border effects. From the two topologies, networks of consecutive epicenters were constructed, that allowed us to analyze the distribution of connectivities of each one. In our results distributions arise belonging to a family of non-traditional distributions functions, which agrees with previous studies using data from actual earthquakes. Our results reinforce the idea that the Earth is in a critical self-organized state and furthermore point towards temporal and spatial correlations between earthquakes in differ...
Integration of neuroblasts into a two-dimensional small world neuronal network
Schneider-Mizell, Casey; Zochowski, Michal; Sander, Leonard
2009-03-01
Neurogenesis in the adult brain has been suggested to be important for learning and functional robustness to the neuronal death. New neurons integrate themselves into existing neuronal networks by moving into a target destination, extending axonal and dendritic processes, and inducing synaptogenesis to connect to active neurons. We hypothesize that increased plasticity of the network to novel stimuli can arise from activity-dependent cell and process motility rules. In complement to a similar in vitro model, we investigate a computational model of a two-dimensional small world network of integrate and fire neurons. After steady-state activity is reached in the extant network, we introduce new neurons which move, stop, and connect themselves through rules governed by position and firing rate.
Self-organized emergence of navigability on small-world networks
We study the origin of navigability in small-world (SW) networks and propose a general scheme for navigating SW networks. We find that navigability can naturally emerge from self-organization in the absence of prior knowledge about the underlying reference frames of networks. Through a process of information exchange and accumulation on networks, a hidden metric space for navigation on networks is constructed. Navigation based on distances between vertices in the hidden metric space can efficiently deliver messages on SW networks, in which long-range connections play an important role. Numerical simulations further demonstrate that a high cluster coefficient and a low diameter are both necessary for navigability. These interesting results provide profound insights into scalable routing on the Internet due to its distributed and localized requirements.
Scale-free and small-world properties of earthquake network in Chile
Pasten, Denisse; Munoz, Victor; Suzuki, Norikazu
2010-01-01
The properties of earthquake networks have been studied so far mainly for the seismic data sets taken from California, Japan and Iran, and features common in these regions have been reported in the literature. Here, an earthquake network is constructed and analyzed for the Chilean data to examine if the scale-free and small-world properties of the earthquake networks constructed in the other geographical regions can also be found in seismicity in Chile. It is shown that the result is affirmative: in all the regions both the exponent "gamma" of the power-law connectivity distribution and the clustering coefficient C take the universal invariant values "gamma ~1" and "C~0.85", respectively, as the cell size becomes larger than a certain value, which is the scale of coarse graining needed for constructing earthquake network. An interpretation for this remarkable result is presented based on physical considerations.
Excitement and synchronization of small-world neuronal networks with short-term synaptic plasticity.
Han, Fang; Wiercigroch, Marian; Fang, Jian-An; Wang, Zhijie
2011-10-01
Excitement and synchronization of electrically and chemically coupled Newman-Watts (NW) small-world neuronal networks with a short-term synaptic plasticity described by a modified Oja learning rule are investigated. For each type of neuronal network, the variation properties of synaptic weights are examined first. Then the effects of the learning rate, the coupling strength and the shortcut-adding probability on excitement and synchronization of the neuronal network are studied. It is shown that the synaptic learning suppresses the over-excitement, helps synchronization for the electrically coupled network but impairs synchronization for the chemically coupled one. Both the introduction of shortcuts and the increase of the coupling strength improve synchronization and they are helpful in increasing the excitement for the chemically coupled network, but have little effect on the excitement of the electrically coupled one. PMID:21956933
An evolutionary inspection game with labour unions on small-world networks
Kamal, Salahuddin M.; Al-Hadeethi, Yas; Abolaban, Fouad A.; Al-Marzouki, Fahd M.; Perc, Matjaž
2015-03-01
We study an evolutionary inspection game where agents can chose between working and shirking. The evolutionary process is staged on a small-world network, through which agents compare their incomes and, based on the outcome, decide which strategy to adopt. Moreover, we introduce union members that have certain privileges, of which the extent depends on the bargaining power of the union. We determine how the union affects the overall performance of the firm that employs the agents, and what are its influences on the employees. We find that, depending on its bargaining power, the union has significant leverage to deteriorate the productivity of a firm, and consequently also to lower the long-run benefits of the employees.
Zhekang Dong
2014-01-01
Full Text Available In this paper, we present an implementation scheme of memristor-based multilayer feedforward small-world neural network (MFSNN inspirited by the lack of the hardware realization of the MFSNN on account of the need of a large number of electronic neurons and synapses. More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons. Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy. Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme.
Heterogeneous delay-induced asynchrony and resonance in a small-world neuronal network system
Yu, Wen-Ting; Tang, Jun; Ma, Jun; Yang, Xianqing
2016-06-01
A neuronal network often involves time delay caused by the finite signal propagation time in a given biological network. This time delay is not a homogenous fluctuation in a biological system. The heterogeneous delay-induced asynchrony and resonance in a noisy small-world neuronal network system are numerically studied in this work by calculating synchronization measure and spike interval distribution. We focus on three different delay conditions: double-values delay, triple-values delay, and Gaussian-distributed delay. Our results show the following: 1) the heterogeneity in delay results in asynchronous firing in the neuronal network, and 2) maximum synchronization could be achieved through resonance given that the delay values are integer or half-integer times of each other.
Migration in a Small World: A Network Approach to Modeling Immigration Processes
Fotouhi, Babak
2012-01-01
Existing theories of migration either focus on micro- or macroscopic behavior of populations; that is, either the average behavior of entire population is modeled directly, or decisions of individuals are modeled directly. In this work, we seek to bridge these two perspectives by modeling individual agents decisions to migrate while accounting for the social network structure that binds individuals into a population. Pecuniary considerations combined with the decisions of peers are the primary elements of the model, being the main driving forces of migration. People of the home country are modeled as nodes on a small-world network. A dichotomous state is associated with each node, indicating whether it emigrates to the destination country or it stays in the home country. We characterize the emigration rate in terms of the relative welfare and population of the home and destination countries. The time evolution and the steady-state fraction of emigrants are also derived.
Synchronizations in small-world networks of spiking neurons: Diffusive versus sigmoid couplings
By using a semianalytical dynamical mean-field approximation previously proposed by the author [H. Hasegawa, Phys. Rev. E 70, 066107 (2004)], we have studied the synchronization of stochastic, small-world (SW) networks of FitzHugh-Nagumo neurons with diffusive couplings. The difference and similarity between results for diffusive and sigmoid couplings have been discussed. It has been shown that with introducing the weak heterogeneity to regular networks, the synchronization may be slightly increased for diffusive couplings, while it is decreased for sigmoid couplings. This increase in the synchronization for diffusive couplings is shown to be due to their local, negative feedback contributions, but not due to the short average distance in SW networks. Synchronization of SW networks depends not only on their structure but also on the type of couplings
Impact of mobility structure on optimization of small-world networks of mobile agents
Lee, Eun; Holme, Petter
2016-06-01
In ad hoc wireless networking, units are connected to each other rather than to a central, fixed, infrastructure. Constructing and maintaining such networks create several trade-off problems between robustness, communication speed, power consumption, etc., that bridges engineering, computer science and the physics of complex systems. In this work, we address the role of mobility patterns of the agents on the optimal tuning of a small-world type network construction method. By this method, the network is updated periodically and held static between the updates. We investigate the optimal updating times for different scenarios of the movement of agents (modeling, for example, the fat-tailed trip distances, and periodicities, of human travel). We find that these mobility patterns affect the power consumption in non-trivial ways and discuss how these effects can best be handled.
Covert, Michael
2015-01-01
This book is intended for software developers, system architects and analysts, big data project managers, and data scientists who wish to deploy big data solutions using the Cascading framework. You must have a basic understanding of the big data paradigm and should be familiar with Java development techniques.
Quantification of degeneracy in Hodgkin-Huxley neurons on Newman-Watts small world network.
Man, Menghua; Zhang, Ya; Ma, Guilei; Friston, Karl; Liu, Shanghe
2016-08-01
Degeneracy is a fundamental source of biological robustness, complexity and evolvability in many biological systems. However, degeneracy is often confused with redundancy. Furthermore, the quantification of degeneracy has not been addressed for realistic neuronal networks. The objective of this paper is to characterize degeneracy in neuronal network models via quantitative mathematic measures. Firstly, we establish Hodgkin-Huxley neuronal networks with Newman-Watts small world network architectures. Secondly, in order to calculate the degeneracy, redundancy and complexity in the ensuing networks, we use information entropy to quantify the information a neuronal response carries about the stimulus - and mutual information to measure the contribution of each subset of the neuronal network. Finally, we analyze the interdependency of degeneracy, redundancy and complexity - and how these three measures depend upon network architectures. Our results suggest that degeneracy can be applied to any neuronal network as a formal measure, and degeneracy is distinct from redundancy. Qualitatively degeneracy and complexity are more highly correlated over different network architectures, in comparison to redundancy. Quantitatively, the relationship between both degeneracy and redundancy depends on network coupling strength: both degeneracy and redundancy increase with complexity for small coupling strengths; however, as coupling strength increases, redundancy decreases with complexity (in contrast to degeneracy, which is relatively invariant). These results suggest that the degeneracy is a general topologic characteristic of neuronal networks, which could be applied quantitatively in neuroscience and connectomics. PMID:27155043
Effects of distance-dependent delay on small-world neuronal networks
Zhu, Jinjie; Chen, Zhen; Liu, Xianbin
2016-04-01
We study firing behaviors and the transitions among them in small-world noisy neuronal networks with electrical synapses and information transmission delay. Each neuron is modeled by a two-dimensional Rulkov map neuron. The distance between neurons, which is a main source of the time delay, is taken into consideration. Through spatiotemporal patterns and interspike intervals as well as the interburst intervals, the collective behaviors are revealed. It is found that the networks switch from resting state into intermittent firing state under Gaussian noise excitation. Initially, noise-induced firing behaviors are disturbed by small time delays. Periodic firing behaviors with irregular zigzag patterns emerge with an increase of the delay and become progressively regular after a critical value is exceeded. More interestingly, in accordance with regular patterns, the spiking frequency doubles compared with the former stage for the spiking neuronal network. A growth of frequency persists for a larger delay and a transition to antiphase synchronization is observed. Furthermore, it is proved that these transitions are generic also for the bursting neuronal network and the FitzHugh-Nagumo neuronal network. We show these transitions due to the increase of time delay are robust to the noise strength, coupling strength, network size, and rewiring probability.
Altered functional connectivity and small-world in mesial temporal lobe epilepsy.
Wei Liao
Full Text Available BACKGROUND: The functional architecture of the human brain has been extensively described in terms of functional connectivity networks, detected from the low-frequency coherent neuronal fluctuations that can be observed in a resting state condition. Little is known, so far, about the changes in functional connectivity and in the topological properties of functional networks, associated with different brain diseases. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we investigated alterations related to mesial temporal lobe epilepsy (mTLE, using resting state functional magnetic resonance imaging on 18 mTLE patients and 27 healthy controls. Functional connectivity among 90 cortical and subcortical regions was measured by temporal correlation. The related values were analyzed to construct a set of undirected graphs. Compared to controls, mTLE patients showed significantly increased connectivity within the medial temporal lobes, but also significantly decreased connectivity within the frontal and parietal lobes, and between frontal and parietal lobes. Our findings demonstrated that a large number of areas in the default-mode network of mTLE patients showed a significantly decreased number of connections to other regions. Furthermore, we observed altered small-world properties in patients, along with smaller degree of connectivity, increased n-to-1 connectivity, smaller absolute clustering coefficients and shorter absolute path length. CONCLUSIONS/SIGNIFICANCE: We suggest that the mTLE alterations observed in functional connectivity and topological properties may be used to define tentative disease markers.
Networks of neuroblastoma cells on porous silicon substrates reveal a small world topology
Marinaro, Giovanni
2015-01-01
The human brain is a tightly interweaving network of neural cells where the complexity of the network is given by the large number of its constituents and its architecture. The topological structure of neurons in the brain translates into its increased computational capabilities, low energy consumption, and nondeterministic functions, which differentiate human behavior from artificial computational schemes. In this manuscript, we fabricated porous silicon chips with a small pore size ranging from 8 to 75 nm and large fractal dimensions up to Df ∼ 2.8. In culturing neuroblastoma N2A cells on the described substrates, we found that those cells adhere more firmly to and proliferate on the porous surfaces compared to the conventional nominally flat silicon substrates, which were used as controls. More importantly, we observed that N2A cells on the porous substrates create highly clustered, small world topology patterns. We conjecture that neurons with a similar architecture may elaborate information more efficiently than in random or regular grids. Moreover, we hypothesize that systems of neurons on nano-scale geometry evolve in time to form networks in which the propagation of information is maximized. This journal is
Disrupted small-world brain networks in moderate Alzheimer's disease: a resting-state FMRI study.
Xiaohu Zhao
Full Text Available The small-world organization has been hypothesized to reflect a balance between local processing and global integration in the human brain. Previous multimodal imaging studies have consistently demonstrated that the topological architecture of the brain network is disrupted in Alzheimer's disease (AD. However, these studies have reported inconsistent results regarding the topological properties of brain alterations in AD. One potential explanation for these inconsistent results lies with the diverse homogeneity and distinct progressive stages of the AD involved in these studies, which are thought to be critical factors that might affect the results. We investigated the topological properties of brain functional networks derived from resting functional magnetic resonance imaging (fMRI of carefully selected moderate AD patients and normal controls (NCs. Our results showed that the topological properties were found to be disrupted in AD patients, which showing increased local efficiency but decreased global efficiency. We found that the altered brain regions are mainly located in the default mode network, the temporal lobe and certain subcortical regions that are closely associated with the neuropathological changes in AD. Of note, our exploratory study revealed that the ApoE genotype modulates brain network properties, especially in AD patients.
Small-world of communities: communication and correlation of the meta-network
Given a network and a partition in n communities, we address the issues of 'how communities influence each other' and 'when do two given communities communicate'. We prove that, for a small-world network, a simple superposition principle applies among communities and each community plays the role of a microscopic spin governed by a sort of effective TAP (Thouless, Anderson and Palmer) equation. The relative susceptibilities derived from these equations calculated at finite or zero temperature (where the method provides an effective percolation theory) give us the answers to the above issues. As for the already studied case n = 1, these equations are exact in the paramagnetic regions (at T = 0 this means below the percolation threshold) and provide effective approximations in the other regions. However, unlike the case n = 1, asymmetries among the communities may lead, via the TAP-like structure of the equations, to many metastable states whose number, in the case of negative short-cuts among the communities, may increase exponentially fast with n and glassy scenarios with a remarkable number of abrupt jumps take place. Furthermore, as a by-product, a natural and efficient method for detecting the community structure of a generic network emerges from the relative susceptibilities. (letter)
Continuous Forest Fire Propagation in a Local Small World Network Model
Aguayo, F; Clerc, J -P; Porterie, B
2013-01-01
This paper presents the development of a new continuous forest fire model implemented as a weighted local small-world network approach. This new approach was designed to simulate fire patterns in real, heterogeneous landscapes. The wildland fire spread is simulated on a square lattice in which each cell represents an area of the land's surface. The interaction between burning and non-burning cells, in the present work induced by flame radiation, may be extended well beyond nearest neighbors. It depends on local conditions of topography and vegetation types. An approach based on a solid flame model is used to predict the radiative heat flux from the flame generated by the burning of each site towards its neighbors. The weighting procedure takes into account the self-degradation of the tree and the ignition processes of a combustible cell through time. The model is tested on a field presenting a range of slopes and with data collected from a real wildfire scenario. The critical behavior of the spreading process...
IMDB network revisited: unveiling fractal and modular properties from a typical small-world network
Gallos, Lazaros K; Andrade, José S; Makse, Hernan A
2013-01-01
We study a subset of the movie collaboration network, imdb.com, where only adult movies are included. We show that there are many benefits in using such a network, which can serve as a prototype for studying social interactions. We find that the strength of links, i.e., how many times two actors have collaborated with each other, is an important factor that can significantly influence the network topology. We see that when we link all actors in the same movie with each other, the network becomes small-world, lacking a proper modular structure. On the other hand, by imposing a threshold on the minimum number of links two actors should have to be in our studied subset, the network topology becomes naturally fractal. This occurs due to a large number of meaningless links, namely, links connecting actors that did not actually interact. We focus our analysis on the fractal and modular properties of this resulting network, and show that the renormalization group analysis can characterize the self-similar structure ...
Dynamic Evolution with Limited Learning Information on a Small-World Network
This paper investigates the dynamic evolution with limited learning information on a small-world network. In the system, the information among the interaction players is not very lucid, and the players are not allowed to inspect the profit collected by its neighbors, thus the focal player cannot choose randomly a neighbor or the wealthiest one and compare its payoff to copy its strategy. It is assumed that the information acquainted by the player declines in the form of the exponential with the geographical distance between the players, and a parameter V is introduced to denote the inspect-ability about the players. It is found that under the hospitable conditions, cooperation increases with the randomness and is inhibited by the large connectivity for the prisoner's dilemma; however, cooperation is maximal at the moderate rewiring probability and is chaos with the connectivity for the snowdrift game. For the two games, the acuminous sight is in favor of the cooperation under the hospitable conditions; whereas, the myopic eyes are advantageous to cooperation and cooperation increases with the randomness under the hostile condition. (interdisciplinary physics and related areas of science and technology)
2014-01-01
Prevailing economic models of consumer behavior completely ignore the well-documented link between context and evaluation. We propose and test a theory that explicitly incorporates this link. Changes in one group's spending shift the frame of reference that defines consumption standards for others just below them on the income scale, giving rise to expenditure cascades. Our model, a descendant of James Duesenberry's relative income hypothesis, predicts the observed ways in which individual sa...
Yilmaz, Ergin; Baysal, Veli; Ozer, Mahmut; Perc, Matjaž
2016-02-01
We study the effects of an autapse, which is mathematically described as a self-feedback loop, on the propagation of weak, localized pacemaker activity across a Newman-Watts small-world network consisting of stochastic Hodgkin-Huxley neurons. We consider that only the pacemaker neuron, which is stimulated by a subthreshold periodic signal, has an electrical autapse that is characterized by a coupling strength and a delay time. We focus on the impact of the coupling strength, the network structure, the properties of the weak periodic stimulus, and the properties of the autapse on the transmission of localized pacemaker activity. Obtained results indicate the existence of optimal channel noise intensity for the propagation of the localized rhythm. Under optimal conditions, the autapse can significantly improve the propagation of pacemaker activity, but only for a specific range of the autaptic coupling strength. Moreover, the autaptic delay time has to be equal to the intrinsic oscillation period of the Hodgkin-Huxley neuron or its integer multiples. We analyze the inter-spike interval histogram and show that the autapse enhances or suppresses the propagation of the localized rhythm by increasing or decreasing the phase locking between the spiking of the pacemaker neuron and the weak periodic signal. In particular, when the autaptic delay time is equal to the intrinsic period of oscillations an optimal phase locking takes place, resulting in a dominant time scale of the spiking activity. We also investigate the effects of the network structure and the coupling strength on the propagation of pacemaker activity. We find that there exist an optimal coupling strength and an optimal network structure that together warrant an optimal propagation of the localized rhythm.
Small-world Characteristics of EEG Patterns in Post-Anoxic Encephalopathy
Martijn eBeudel
2014-06-01
Full Text Available Post-Anoxic Encephalopathy (PAE has a heterogenous outcome which is difficult to predict. At present, it is possible to predict poor outcome using somatosensory evoked potentials (SSEP in only a minority of the patients at an early stage. In addition, it remains difficult to predict good outcome at an early stage. Network architecture, as can be quantified with continuous electroencephalography (cEEG, may serve as a candidate measure for predicting neurological outcome. Here we explore whether cEEG monitoring can be used to detect the integrity of neural network architecture in patients with PAE after cardiac arrest. From 56 patients with PAE treated with mild therapeutic hypothermia (MTH, 19-channel cEEG data was recorded starting as soon as possible after cardiac arrest. Adjacency matrices of shared frequencies between 1 and 25 Hz of the EEG channels were obtained using Fourier transformations. Number of network nodes and connections, clustering coefficient (C, average path length (L and small-world index (SWI were derived. Outcome was quantified by the best Cerebral Performance Category (CPC-score within 6 months. Compared to non-survivors, survivors showed significantly more nodes and connections. L was significantly higher and C and SWI were significantly lower in the survivor group than in the non-survivor group. The number of nodes, connections and the L negatively correlated with the CPC-score. C and SWI correlated positively with the CPC-score. The combination of number of nodes, connections, C and L showed the most significant difference and correlation between survivors and non-survivors and CPC-score. Our data might implicate that non-survivors have insufficient distribution and differentiation of neural activity for regaining normal brain function. These network differences, already present during hypothermia, might be further developed as early prognostic markers. The predictive values are however still inferior to current practice
Small-world characteristics of EEG patterns in post-anoxic encephalopathy.
Beudel, Martijn; Tjepkema-Cloostermans, Marleen C; Boersma, Jochem H; van Putten, Michel J A M
2014-01-01
Post-anoxic encephalopathy (PAE) has a heterogenous outcome which is difficult to predict. At present, it is possible to predict poor outcome using somatosensory evoked potentials in only a minority of the patients at an early stage. In addition, it remains difficult to predict good outcome at an early stage. Network architecture, as can be quantified with continuous electroencephalography (cEEG), may serve as a candidate measure for predicting neurological outcome. Here, we explore whether cEEG monitoring can be used to detect the integrity of neural network architecture in patients with PAE after cardiac arrest. From 56 patients with PAE treated with mild therapeutic hypothermia, 19-channel cEEG data were recorded starting as soon as possible after cardiac arrest. Adjacency matrices of shared frequencies between 1 and 25 Hz of the EEG channels were obtained using Fourier transformations. Number of network nodes and connections, clustering coefficient (C), average path length (L), and small-world index (SWI) were derived. Outcome was quantified by the best cerebral performance category (CPC)-score within 6 months. Compared to non-survivors, survivors showed significantly more nodes and connections. L was significantly higher and C and SWI were significantly lower in the survivor group than in the non-survivor group. The number of nodes, connections, and the L were negatively correlated with the CPC-score. C and SWI correlated positively with the CPC-score. The combination of number of nodes, connections, C, and L showed the most significant difference and correlation between survivors and non-survivors and CPC-score. Our data might implicate that non-survivors have insufficient distribution and differentiation of neural activity for regaining normal brain function. These network differences, already present during hypothermia, might be further developed as early prognostic markers. The predictive values are however still inferior to current practice parameters
Isles within islets: The lattice origin of small-world networks in pancreatic tissues
Barua, Amlan K.; Goel, Pranay
2016-02-01
The traditional computational model of the pancreatic islets of Langerhans is a lattice of β-cells connected with gap junctions. Numerous studies have investigated the behavior of networks of coupled β-cells and have shown that gap junctions synchronize bursting strongly. This simplistic architecture of islets, however, seems increasingly untenable at the face of recent experimental advances. In a microfluidics experiment on isolated islets, Rocheleau et al. (2004) showed a failure of penetration of excitation when one end received high glucose and other end was not excited sufficiently; this suggested that gap junctions may not be efficient at inducing synchrony throughout the islet. Recently, Stozer et al. (2013) have argued that the functional networks of β-cells in an islet are small world. Their results implicate the existence of a few long-range connections among cells in the network. The physiological reason underlying this claim is not well understood. These studies cast doubt on the original lattice model that largely predict an all-or-none synchrony among the cells. Here we have attempted to reconcile these observations in a unified framework. We assume that cells in the islet are coupled randomly to their nearest neighbors with some probability, p. We simulated detailed β-cell bursting in such islets. By varying p systematically we were led to network parameters similar to those obtained by Stozer et al. (2013). We find that the networks within islets break up into components giving rise to smaller isles within the super structure-isles-within-islets, as it were. This structure can also account for the partial excitation seen by Rocheleau et al. (2004). Our updated view of islet architecture thus explains the paradox how islets can have strongly synchronizing gap junctions, and be weakly coordinated at the same time.
Effects of inspections in small world social networks with different contagion rules
Muñoz, Francisco; Nuño, Juan Carlos; Primicerio, Mario
2015-08-01
We study the way the structure of social links determines the effects of random inspections on a population formed by two types of individuals, e.g. tax-payers and tax-evaders (free riders). It is assumed that inspections occur in a larger scale than the population relaxation time and, therefore, a unique initial inspection is performed on a population that is completely formed by tax-evaders. Besides, the inspected tax-evaders become tax-payers forever. The social network is modeled as a Watts-Strogatz Small World whose topology can be tuned in terms of a parameter p ∈ [ 0 , 1 ] from regular (p = 0) to random (p = 1). Two local contagion rules are considered: (i) a continuous one that takes the proportion of neighbors to determine the next status of an individual (node) and (ii) a discontinuous (threshold rule) that assumes a minimum number of neighbors to modify the current state. In the former case, irrespective of the inspection intensity ν, the equilibrium population is always formed by tax-payers. In the mean field approach, we obtain the characteristic time of convergence as a function of ν and p. For the threshold contagion rule, we show that the response of the population to the intensity of inspections ν is a function of the structure of the social network p and the willingness of the individuals to change their state, r. It is shown that sharp transitions occur at critical values of ν that depends on p and r. We discuss these results within the context of tax evasion and fraud where the strategies of inspection could be of major relevance.
SW-R2P: A Trusted Small World Overlay P2P Network with Zero Knowledge Identification
Yingjie Xia
2008-10-01
Full Text Available In order to implement both the efficiency and security in the Peer-to-Peer (P2P network, we design a trusted small world overlay P2P network with the role based and reputation based access control policies, denoted as SW-R2P. The SW-R2P system integrates the small world topology with zero knowledge identification and Bayesian trust model. The zero knowledge identification is utilized to securely cluster all the peers into several groups without transferring any related information. The peer groups are then linked together to construct a trusted small world network based on the probabilities calculated by the Bayesian trust model. The simulation experiments demonstrate that the SW-R2P system achieves the performance with increased success rate in the resources lookup, strengthened robustness under the overwhelming traffic loadings, reduced reputation errors caused by the malicious peers and enhanced peer satisfaction rate for different trust metrics. In conclusion, the SW-R2P system collectively exploits the advantages of small world, zero knowledge identification and Bayesian trust model, therefore implementing a scalable, secure and efficient P2P network.
Zhang, Jianbao [School of Science, Hangzhou Dianzi University, Hangzhou 310018 (China); Ma, Zhongjun, E-mail: mzj1234402@163.com [School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004 (China); Chen, Guanrong [Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong (China)
2014-06-15
All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.
All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations
A Small Morris-Lecar Neuron Network Gets Close to Critical Only in the Small-World Regimen
Juan Luis Cabrera
2013-01-01
Full Text Available Spontaneous emergence of neuronal activity avalanches characterized by power-law distributions is known to occur in different types of nervous tissues suggesting that nervous systems may operate at a critical regime. Here, we explore the possible relation of this dynamical state with the underlying topology in a small-size network of interconnected Morris-Lecar neurons. Studying numerically different topological configurations, we find that, very close to the efficient small-world situation, the system self-organizes near to a critical branching process with observable distributions in the proximity of a power law with exponents similar to those reported in the experimental literature. Therefore, we conclude that the observed scaling is intimately related only with the small-world topology.
This paper presents the latest developments and validation results of a hybrid model which combines a broad-scale stochastic small-world network model with a macroscopic deterministic approach, to simulate the effects of large fires burning in heterogeneous landscapes. In the extended version of the model, vegetation is depicted as an amorphous network of combustible cells, and both radiation and convection from the flaming zone are considered in the preheating process of unburned cells. Examples are given to illustrate small-world effects and fire behavior near the percolation threshold. The model is applied to a Mediterranean fire that occurred in Corsica in 2009 showing a good agreement in terms of rate of spread, and area and shape of the burn. A study, based on a fractional factorial plan, is conducted to evaluate the influence of variations of model parameters on fire propagation.
Effects of small-world connectivity on noise-induced temporal and spatial order in neural media
We present an overview of possible effects of small-world connectivity on noise-induced temporal and spatial order in a two-dimensional network of excitable neural media with FitzHugh-Nagumo local dynamics. Small-world networks are characterized by a given fraction of so-called long-range couplings or shortcut links that connect distant units of the system, while all other units are coupled in a diffusive-like manner. Interestingly, already a small fraction of these long-range couplings can have wide-ranging effects on the temporal as well as spatial noise-induced dynamics of the system. Here we present two main effects. First, we show that the temporal order, characterized by the autocorrelation of a firing-rate function, can be greatly enhanced by the introduction of small-world connectivity, whereby the effect increases with the increasing fraction of introduced shortcut links. Second, we show that the introduction of long-range couplings induces disorder of otherwise ordered, spiral-wave-like, noise-induced patterns that can be observed by exclusive diffusive connectivity of spatial units. Thereby, already a small fraction of shortcut links is sufficient to destroy coherent pattern formation in the media. Although the two results seem contradictive, we provide an explanation considering the inherent scale-free nature of small-world networks, which on one hand, facilitates signal transduction and thus temporal order in the system, whilst on the other hand, disrupts the internal spatial scale of the media thereby hindering the existence of coherent wave-like patterns. Additionally, the importance of spatially versus temporally ordered neural network functioning is discussed
Yu, Haitao; Guo, Xinmeng; Wang, Jiang; Deng, Bin; Wei, Xile
2014-09-01
The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient for the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks. PMID:25273205
Yu, Haitao; Guo, Xinmeng; Wang, Jiang, E-mail: jiangwang@tju.edu.cn; Deng, Bin; Wei, Xile [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)
2014-09-01
The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient for the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks.
European energy policy pursues the objective of a sustainable, competitive and reliable supply of energy. In 2007, the European Commission adopted a proper energy policy for Europe supported by several documents and included an action plan to meet the major energy challenges Europe has to face. A farsighted diversified yearly mix of energies was suggested to countries, aiming at increasing security of supply and efficiency, but a wide and systemic view of energy interchanges between states was missing. In this paper, a Small-World methodology of analysis of Interchange Energy-Networks (IENs) is presented, with the aim of providing a useful tool for planning sustainable energy policies. A proof case is presented to validate the methodology by considering the European IEN behaviour in the period of economical crisis. This network is approached as a Small World Net from a modelling point of view, by supposing that connections between States are characterised by a probability value depending on economic/political relations between countries. - Highlights: • Different view of the imports and exports of electric energy flows between European for potential use in ruling exchanges. • Panel data from 1996 to 2010 as part of a network of exchanges was considered from Eurostat official database. • The European import/export energy flows modelled as a network with Small World phenomena, interpreting the evolution over the years. • Interesting systemic tool for ruling and governing energy flows between countries
Contingency Analysis of Cascading Line Outage Events
Thomas L Baldwin; Magdy S Tawfik; Miles McQueen
2011-03-01
As the US power systems continue to increase in size and complexity, including the growth of smart grids, larger blackouts due to cascading outages become more likely. Grid congestion is often associated with a cascading collapse leading to a major blackout. Such a collapse is characterized by a self-sustaining sequence of line outages followed by a topology breakup of the network. This paper addresses the implementation and testing of a process for N-k contingency analysis and sequential cascading outage simulation in order to identify potential cascading modes. A modeling approach described in this paper offers a unique capability to identify initiating events that may lead to cascading outages. It predicts the development of cascading events by identifying and visualizing potential cascading tiers. The proposed approach was implemented using a 328-bus simplified SERC power system network. The results of the study indicate that initiating events and possible cascading chains may be identified, ranked and visualized. This approach may be used to improve the reliability of a transmission grid and reduce its vulnerability to cascading outages.
Information cascade on networks
Hisakado, Masato; Mori, Shintaro
2016-05-01
In this paper, we discuss a voting model by considering three different kinds of networks: a random graph, the Barabási-Albert (BA) model, and a fitness model. A voting model represents the way in which public perceptions are conveyed to voters. Our voting model is constructed by using two types of voters-herders and independents-and two candidates. Independents conduct voting based on their fundamental values; on the other hand, herders base their voting on the number of previous votes. Hence, herders vote for the majority candidates and obtain information relating to previous votes from their networks. We discuss the difference between the phases on which the networks depend. Two kinds of phase transitions, an information cascade transition and a super-normal transition, were identified. The first of these is a transition between a state in which most voters make the correct choices and a state in which most of them are wrong. The second is a transition of convergence speed. The information cascade transition prevails when herder effects are stronger than the super-normal transition. In the BA and fitness models, the critical point of the information cascade transition is the same as that of the random network model. However, the critical point of the super-normal transition disappears when these two models are used. In conclusion, the influence of networks is shown to only affect the convergence speed and not the information cascade transition. We are therefore able to conclude that the influence of hubs on voters' perceptions is limited.
YUAN Wu-Jie; LUO Xiao-Shu; JIANG Pin-Qun
2007-01-01
In this paper,we propose a new model of weighted small-world biological neural networks based on biophysical Hodgkin-Huxley neurons with side-restrain mechanism.Then we study excitement properties of the model under alternating current (AC) stimulation.The study shows that the excitement properties in the networks are preferably consistent with the behavior properties of a brain nervous system under different AC stimuli,such as refractory period and the brain neural excitement response induced by different intensities of nolse and coupling.The results of the study have reference worthiness for the brain nerve electrophysiology and epistemological science.
Zhang, Ying-Yue; Yang, Qiu-Ying; Chen, Tian-Lun
2007-07-01
We introduce a modified small-world network adding new links with nonlinearly preferential connection instead of adding randomly, then we apply Bak-Sneppen (BS) evolution model on this network. We study several important structural properties of our network such as the distribution of link-degree, the maximum link-degree, and the length of the shortest path. We further argue several dynamical characteristics of the model such as the important critical value fc, the f0 avalanche, and the mutating condition, and find that those characteristics show particular behaviors.
In this paper, we propose a new model of weighted small-world biological neural networks based on biophysical Hodgkin-Huxley neurons with side-restrain mechanism. Then we study excitement properties of the model under alternating current (AC) stimulation. The study shows that the excitement properties in the networks are preferably consistent with the behavior properties of a brain nervous system under different AC stimuli, such as refractory period and the brain neural excitement response induced by different intensities of noise and coupling. The results of the study have reference worthiness for the brain nerve electrophysiology and epistemological science.
A Comparison of Methods for Cascade Prediction
Guo, Ruocheng
2016-01-01
Information cascades exist in a wide variety of platforms on Internet. A very important real-world problem is to identify which information cascades can go viral. A system addressing this problem can be used in a variety of applications including public health, marketing and counter-terrorism. As a cascade can be considered as compound of the social network and the time series. However, in related literature where methods for solving the cascade prediction problem were proposed, the experimental settings were often limited to only a single metric for a specific problem formulation. Moreover, little attention was paid to the run time of those methods. In this paper, we first formulate the cascade prediction problem as both classification and regression. Then we compare three categories of cascade prediction methods: centrality based, feature based and point process based. We carry out the comparison through evaluation of the methods by both accuracy metrics and run time. The results show that feature based met...
Cappon, Giacomo; Pedersen, Morten Gram
2016-05-01
Many multicellular systems consist of coupled cells that work as a syncytium. The pancreatic islet of Langerhans is a well-studied example of such a microorgan. The islets are responsible for secretion of glucose-regulating hormones, mainly glucagon and insulin, which are released in distinct pulses. In order to observe pulsatile insulin secretion from the β-cells within the islets, the cellular responses must be synchronized. It is now well established that gap junctions provide the electrical nearest-neighbor coupling that allows excitation waves to spread across islets to synchronize the β-cell population. Surprisingly, functional coupling analysis of calcium responses in β-cells shows small-world properties, i.e., a high degree of local coupling with a few long-range "short-cut" connections that reduce the average path-length greatly. Here, we investigate how such long-range functional coupling can appear as a result of heterogeneity, nearest-neighbor coupling, and wave propagation. Heterogeneity is also able to explain a set of experimentally observed synchronization and wave properties without introducing all-or-none cell coupling and percolation theory. Our theoretical results highlight how local biological coupling can give rise to functional small-world properties via heterogeneity and wave propagation.
Lijun Bai
2013-01-01
Full Text Available As an intermediate state between normal aging and dementia, mild cognitive impairment (MCI became a hot topic and early treatments can improve disease prognosis. Acupuncture is shown to have possible effect in improving its cognitive defect. However, the underlying neural mechanism of acupuncture and relations between De Qi and different needling depths are still elusive. The present study aimed to explore how acupuncture can exert effect on the reorganization of MCI and to what extent needling depths, associating with De Qi sensations, can influence the acupuncture effects for MCI treatment. Our results presented that MCI patients exhibited losses of small-world attributes indicated by longer characteristic path lengths and larger clustering coefficients, compared with healthy controls. In addition, acupuncture with deep needling can induce much stronger and a wide range of De Qi sensations both in intensity and prevalence. Acupuncture with deep needling showed modulatory effect to compensate the losses of small-world attributes existed in MCI patients while acupuncture with superficial needling did not. Furthermore, acupuncture with deep needling enhanced the nodal centrality primarily in the abnormal regions of MCI including the hippocampus, postcentral cortex as well as anterior cingulate cortex. This study provides evidence to understand neural mechanism underlying acupuncture and the key role of De Qi for MCI treatment.
They are small worlds after all: revised properties of Kepler M dwarf stars and their planets
Gaidos, E.; Mann, A. W.; Kraus, A. L.; Ireland, M.
2016-04-01
We classified the reddest (r - J > 2.2) stars observed by the NASA Kepler mission into main-sequence dwarf or evolved giant stars and determined the properties of 4216 M dwarfs based on a comparison of available photometry with that of nearby calibrator stars, as well as available proper motions and spectra. We revised the properties of candidate transiting planets using the stellar parameters, high-resolution imaging to identify companion stars, and, in the case of binaries, fitting light curves to identify the likely planet host. In 49 of 54 systems, we validated the primary as the host star. We inferred the intrinsic distribution of M dwarf planets using the method of iterative Monte Carlo simulation. We compared several models of planet orbital geometry and clustering and found that one where planets are exponentially distributed and almost precisely coplanar best describes the distribution of multiplanet systems. We determined that Kepler M dwarfs host an average of 2.2 ± 0.3 planets with radii of 1-4 R⊕ and orbital periods of 1.5-180 d. The radius distribution peaks at ˜1.2 R⊕ and is essentially zero at 4 R⊕, although we identify three giant planet candidates other than the previously confirmed Kepler-45b. There is suggestive but not significant evidence that the radius distribution varies with orbital period. The distribution with logarithmic orbital period is flat except for a decline for orbits less than a few days. 12 candidate planets, including two Jupiter-size objects, experience an irradiance below the threshold level for a runaway greenhouse on an Earth-like planet and are thus in a `habitable zone'.
They are Small Worlds After All: Revised Properties of Kepler M Dwarf Stars and their Planets
Gaidos, E; Kraus, A L; Ireland, M
2015-01-01
We classified the reddest (r-J> 2.2) stars observed by the NASA Kepler mission into main sequence dwarf or evolved giant stars and determined the properties of 4216 M dwarfs based on a comparison of available photometry with that of nearby calibrator stars, as well as available proper motions and spectra. We then revised the properties of candidate transiting planets using the stellar parameters, high-resolution imaging and aperture masking to identify companion stars, and refitting of the light curves to identify the component most likely to host the planet. We inferred the intrinsic distribution of M dwarf planets using the method of iterative Monte Carlo simulation. We compared several models of planet orbital geometry and clustering and found that one where planets are exponentially distributed and almost precisely coplanar best describes the distribution of multi-planet systems. We determined that Kepler M dwarfs host an average of 1.9+/-0.3 planets with radii of 1-4Re and orbital periods of 1.5-180d. Th...
Cheng, Justin; Adamic, Lada A.; Kleinberg, Jon; Leskovec, Jure
2016-01-01
Cascades of information-sharing are a primary mechanism by which content reaches its audience on social media, and an active line of research has studied how such cascades, which form as content is reshared from person to person, develop and subside. In this paper, we perform a large-scale analysis of cascades on Facebook over significantly longer time scales, and find that a more complex picture emerges, in which many large cascades recur, exhibiting multiple bursts of popularity with period...
Massobrio, Paolo; Pasquale, Valentina; Martinoia, Sergio
2015-01-01
The spontaneous activity of cortical networks is characterized by the emergence of different dynamic states. Although several attempts were accomplished to understand the origin of these dynamics, the underlying factors continue to be elusive. In this work, we specifically investigated the interplay between network topology and spontaneous dynamics within the framework of self-organized criticality (SOC). The obtained results support the hypothesis that the emergence of critical states occurs in specific complex network topologies. By combining multi-electrode recordings of spontaneous activity of in vitro cortical assemblies with theoretical models, we demonstrate that different 'connectivity rules' drive the network towards different dynamic states. In particular, scale-free architectures with different degree of small-worldness account better for the variability observed in experimental data, giving rise to different dynamic states. Moreover, in relationship with the balance between excitation and inhibition and percentage of inhibitory hubs, the simulated cortical networks fall in a critical regime. PMID:26030608
Percha, B; Zochowski, M; Percha, Bethany; Dzakpasu, Rhonda; Zochowski, Micha{\\l} \\.
2004-01-01
Temporal correlations in the brain are thought to have very dichotomic roles. On one hand they are ubiquitously present in the healthy brain and are thought to underlie feature binding during information processing. On the other hand large scale synchronization is an underlying mechanism of epileptic seizures. In this paper we show a possible mechanism of transition to pathological coherence underlying seizure generation. We show that properties of phase synchronization in the 2-D lattice of non-identical coupled Hindmarsh-Rose neurons change radically depending on the connectivity structure. We modify the connectivity using the small world network paradigm and measure properties of phase synchronization using previously developed measure based on assessment of the distributions of relative interspike intervals. We show that the phase synchronization undergoes a dramatic change as a function of locality of network connections from local coherence strongly dependent on the distance between two neurons to globa...
Qiu, Tian; Hadzibeganovic, Tarik; Chen, Guang; Zhong, Li-Xin; Wu, Xiao-Run
2010-12-01
Cooperation in the evolutionary snowdrift game with a self-questioning updating mechanism is studied on annealed and quenched small-world networks with directed couplings. Around the payoff parameter value r=0.5, we find a size-invariant symmetrical cooperation effect. While generally suppressing cooperation for r>0.5 payoffs, rewired networks facilitated cooperative behavior for raltruism even under large-reward conditions. Our results suggest that an updating mechanism of this type is necessary to stabilize cooperation in a spatially structured environment which is otherwise detrimental to cooperative behavior, especially at high cost-to-benefit ratios. Additionally, we employ component and local stability analyses to better understand the nature of the manifested dynamics.
Kim, Sang-Yoon
2016-01-01
We consider an inhomogeneous small-world network (SWN) composed of inhibitory short-range (SR) and long-range (LR) interneurons. By varying the fraction of LR interneurons $p_{long}$, we investigate the effect of network architecture on emergence of sparsely synchronized rhythms, and make comparison with that in the Watts-Strogatz SWN. Although SR and LR interneurons have the same average in- and out-degrees, their betweenness centralities (characterizing the potentiality in controlling communication between other interneurons) are distinctly different. Hence, in view of the betweenness, SWNs we consider are inhomogeneous, unlike the "canonical" Watts-Strogatz SWN with nearly same betweenness centralities. As $p_{long}$ is increased, the average path length becomes shorter, and the load of communication traffic is less concentrated on LR interneurons, which leads to better efficiency of global communication between interneurons. Eventually, when passing a critical value $p_{long}^{(c)}$ $(\\simeq 0.16)$, spars...
We study the collective dynamics of excitatory integrate-and-fire-like oscillators interacting via δ-pulses on a small-world network. The oscillators are endowed with refractory periods and time delays. For weak coupling strengths, the network self-organizes into synchronous and asynchronous regions. Such chimera states allow for two separate routes to synchrony/asynchrony. In addition to the loss of stability of either synchronous or asynchronous regions mediated by long-ranged connections, regions may grow or shrink mediated by the lattice structure. The interplay between these behaviors leads to controlled total sizes of asynchronous regions or to an alternation of synchronization and desynchronization phenomena with irregular macroscopic observables. (paper)
Wu Hao; Jiang Huijun [Hefei National Laboratory for Physical Sciences at the Microscale and Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026 (China); Hou Zhonghuai, E-mail: hzhlj@ustc.edu.cn [Hefei National Laboratory for Physical Sciences at the Microscale and Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026 (China)
2011-10-15
Highlights: > We compare neuronal dynamics in dependence on two types of delayed coupling. > Distinct results induced by different delayed coupling can be achieved. > Time delays in type 1 coupling can induce a most spatiotemporal ordered state. > For type 2 coupling, the systems exhibit synchronization transitions with delay. - Abstract: We investigate temporal coherence and spatial synchronization on small-world networks consisting of noisy Terman-Wang (TW) excitable neurons in dependence on two types of time-delayed coupling: {l_brace}x{sub j}(t - {tau}) - x{sub i}(t){r_brace} and {l_brace}x{sub j}(t - {tau}) - x{sub i}(t - {tau}){r_brace}. For the former case, we show that time delay in the coupling can dramatically enhance temporal coherence and spatial synchrony of the noise-induced spike trains. In addition, if the delay time {tau} is tuned to nearly match the intrinsic spike period of the neuronal network, the system dynamics reaches a most ordered state, which is both periodic in time and nearly synchronized in space, demonstrating an interesting resonance phenomenon with delay. For the latter case, however, we cannot achieve a similar spatiotemporal ordered state, but the neuronal dynamics exhibits interesting synchronization transitions with time delay from zigzag fronts of excitations to dynamic clustering anti-phase synchronization (APS), and further to clustered chimera states which have spatially distributed anti-phase coherence separated by incoherence. Furthermore, we also show how these findings are influenced by the change of the noise intensity and the rewiring probability of the small-world networks. Finally, qualitative analysis is given to illustrate the numerical results.
Highlights: → We compare neuronal dynamics in dependence on two types of delayed coupling. → Distinct results induced by different delayed coupling can be achieved. → Time delays in type 1 coupling can induce a most spatiotemporal ordered state. → For type 2 coupling, the systems exhibit synchronization transitions with delay. - Abstract: We investigate temporal coherence and spatial synchronization on small-world networks consisting of noisy Terman-Wang (TW) excitable neurons in dependence on two types of time-delayed coupling: {xj(t - τ) - xi(t)} and {xj(t - τ) - xi(t - τ)}. For the former case, we show that time delay in the coupling can dramatically enhance temporal coherence and spatial synchrony of the noise-induced spike trains. In addition, if the delay time τ is tuned to nearly match the intrinsic spike period of the neuronal network, the system dynamics reaches a most ordered state, which is both periodic in time and nearly synchronized in space, demonstrating an interesting resonance phenomenon with delay. For the latter case, however, we cannot achieve a similar spatiotemporal ordered state, but the neuronal dynamics exhibits interesting synchronization transitions with time delay from zigzag fronts of excitations to dynamic clustering anti-phase synchronization (APS), and further to clustered chimera states which have spatially distributed anti-phase coherence separated by incoherence. Furthermore, we also show how these findings are influenced by the change of the noise intensity and the rewiring probability of the small-world networks. Finally, qualitative analysis is given to illustrate the numerical results.
TOPOLOGY AND CASCADING LINE OUTAGES IN POWER GRIDS
David L. PEPYNE
2007-01-01
Motivated by the small world network research of Watts & Strogatz, this paper studies relationships between topology and cascading line outages in electric power grids. Cascading line outages are a type of cascading collapse that can occur in power grids when the transmission network is congested. It is characterized by a self-sustaining sequence of line outages followed by grid breakup, which generally leads to widespread blackout. The main findings of this work are twofold: On one hand, the work suggests that topologies with more disorder in their interconnection topology tend to be robust with respect to cascading line outages in the sense of being able to support greater generation and demand levels than more regularly interconnected topologies. On the other hand, the work suggests that topologies with more disorder tend to be more fragile in that should a cascade get started, they tend to break apart after fewer outages than more regularly interconnected topologies. Thus, as has been observed in other complex networks, there appears to be a tradeoff between robustness and fragility.These results were established using synthetically generated power grid topologies and verified using the IEEE 57 bus and 188 bus power grid test cases.
Liew, T. C. H.; Glazov, M. M.; Kavokin, K. V.; Shelykh, I. A.; Kaliteevski, M A; Kavokin, A.V.
2012-01-01
We propose a concept of a quantum cascade laser based on transitions of bosonic quasiparticles (excitons and exciton-polaritons) in a parabolic potential trap in a semiconductor microcavity. This laser would emit terahertz radiation due to bosonic stimulation of excitonic transitions. Dynamics of a bosonic cascade is strongly different from the dynamics of a conventional fermionic cascade laser. We show that populations of excitonic ladders are parity-dependent and quantized if the laser oper...
Topology of the Italian airport network: A scale-free small-world network with a fractal structure?
In this paper, for the first time we analyze the structure of the Italian Airport Network (IAN) looking at it as a mathematical graph and investigate its topological properties. We find that it has very remarkable features, being like a scale-free network, since both the degree and the 'betweenness centrality' distributions follow a typical power-law known in literature as a Double Pareto Law. From a careful analysis of the data, the Italian Airport Network turns out to have a self-similar structure. In short, it is characterized by a fractal nature, whose typical dimensions can be easily determined from the values of the power-law scaling exponents. Moreover, we show that, according to the period examined, these distributions exhibit a number of interesting features, such as the existence of some 'hubs', i.e. in the graph theory's jargon, nodes with a very large number of links, and others most probably associated with geographical constraints. Also, we find that the IAN can be classified as a small-world network because the average distance between reachable pairs of airports grows at most as the logarithm of the number of airports. The IAN does not show evidence of 'communities' and this result could be the underlying reason behind the smallness of the value of the clustering coefficient, which is related to the probability that two nearest neighbors of a randomly chosen airport are connected
Topology of the Italian airport network: A scale-free small-world network with a fractal structure?
Guida, Michele [Dipartimento di Fisica ' E.R. Caianiello' , Universita degli Studi di Salerno, Via S. Allende, I-84081 Baronissi (Saudi Arabia) (Italy)]. E-mail: guida@sa.infn.it; Maria, Funaro [Liceo Scientifico ' B. Rescigno' , Via Viviano 3, I-84086 Roccapiemonte (Sa) (Italy)
2007-02-15
In this paper, for the first time we analyze the structure of the Italian Airport Network (IAN) looking at it as a mathematical graph and investigate its topological properties. We find that it has very remarkable features, being like a scale-free network, since both the degree and the 'betweenness centrality' distributions follow a typical power-law known in literature as a Double Pareto Law. From a careful analysis of the data, the Italian Airport Network turns out to have a self-similar structure. In short, it is characterized by a fractal nature, whose typical dimensions can be easily determined from the values of the power-law scaling exponents. Moreover, we show that, according to the period examined, these distributions exhibit a number of interesting features, such as the existence of some 'hubs', i.e. in the graph theory's jargon, nodes with a very large number of links, and others most probably associated with geographical constraints. Also, we find that the IAN can be classified as a small-world network because the average distance between reachable pairs of airports grows at most as the logarithm of the number of airports. The IAN does not show evidence of 'communities' and this result could be the underlying reason behind the smallness of the value of the clustering coefficient, which is related to the probability that two nearest neighbors of a randomly chosen airport are connected.
Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transitions between different activity states are closely related to corresponding functions in the brain. In particular, phase transitions to some rhythmic synchronous firing states play significant roles on diverse brain functions and disfunctions, such as encoding rhythmical external stimuli, epileptic seizure, etc. However, in previous studies, phase transitions in neuronal networks are almost driven by network parameters (e.g., external stimuli), and there has been no investigation about the transitions between typical activity states of neuronal networks in a self-organized way by applying plastic connection weights. In this paper, we discuss phase transitions in electrically coupled and lattice-based small-world neuronal networks (LBSW networks) under spike-timing-dependent plasticity (STDP). By applying STDP on all electrical synapses, various known and novel phase transitions could emerge in LBSW networks, particularly, the phenomenon of self-organized phase transitions (SOPTs): repeated transitions between synchronous and asynchronous firing states. We further explore the mechanics generating SOPTs on the basis of synaptic weight dynamics. (interdisciplinary physics and related areas of science and technology)
ZHOU Nan-run; GONG Li-hua; LIU Ye
2006-01-01
In this letter a cascade quantum teleportation scheme is proposed. The proposed scheme needs less local quantum operations than those of quantum multi-teleportation. A quantum teleportation scheme based on entanglement swapping is presented and compared with the cascade quantum teleportation scheme. Those two schemes can effectively teleport quantum information and extend the distance of quantum communication.
Christos A. Frantzidis
2014-08-01
Full Text Available Previous neuroscientific findings have linked Alzheimer’s disease (AD with less efficient information processing and brain network disorganization. However, pathological alterations of the brain networks during the preclinical phase of amnestic Mild Cognitive Impairment (aMCI remain largely unknown. The present study aimed at comparing patterns of the detection of functional disorganization in MCI relative to Mild Dementia (MD. Participants consisted of 23 cognitively healthy adults, 17 aMCI and 24 mild AD patients who underwent electroencephalographic (EEG data acquisition during a resting-state condition. Synchronization analysis through the Orthogonal Discrete Wavelet Transform (ODWT, and directional brain network analysis were applied on the EEG data. This computational model was performed for networks that have the same number of edges (N=500, 600, 700, 800 edges across all participants and groups (fixed density values. All groups exhibited a small-world (SW brain architecture. However, we found a significant reduction in the SW brain architecture in both aMCI and MD patients relative to the group of Healthy controls. This functional disorganization was also correlated with the participant’s generic cognitive status. The deterioration of the network’s organization was caused mainly by deficient local information processing as quantified by the mean cluster coefficient value. Functional hubs were identified through the normalized betweenness centrality metric. Analysis of the local characteristics showed relative hub preservation even with statistically significant reduced strength. Compensatory phenomena were also evident through the formation of additional hubs on left frontal and parietal regions. Our results indicate a declined functional network organization even during the prodromal phase. Degeneration is evident even in the preclinical phase and coexists with transient network reorganization due to compensation.
Burnett, Gary; Jaeger, Paul T.
2008-01-01
Introduction: This paper attempts to build bridges between two sets of theoretical concepts related to information behaviour: the macro-level concepts of Jurgen Habermas related to lifeworlds and the micro-level concepts of Elfreda Chatman related to small worlds. Argument: Habermas and Chatman explored similar issues of information behaviour at…
LIN Min; CHEN Tian-Lun
2005-01-01
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.
Aldrich, Preston R.; El-Zabet, Jermeen; Hassan, Seerat; Briguglio, Joseph; Aliaj, Enela; Radcliffe, Maria; Mirza, Taha; Comar, Timothy; Nadolski, Jeremy; Huebner, Cynthia D.
2015-11-01
Several studies have shown that human transportation networks exhibit small-world structure, meaning they have high local clustering and are easily traversed. However, some have concluded this without statistical evaluations, and others have compared observed structure to globally random rather than planar models. Here, we use Monte Carlo randomizations to test US transportation infrastructure data for small-worldness. Coarse-grained network models were generated from GIS data wherein nodes represent the 3105 contiguous US counties and weighted edges represent the number of highway or railroad links between counties; thus, we focus on linkage topologies and not geodesic distances. We compared railroad and highway transportation networks with a simple planar network based on county edge-sharing, and with networks that were globally randomized and those that were randomized while preserving their planarity. We conclude that terrestrial transportation networks have small-world architecture, as it is classically defined relative to global randomizations. However, this topological structure is sufficiently explained by the planarity of the graphs, and in fact the topological patterns established by the transportation links actually serve to reduce the amount of small-world structure.
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.
Interaction of a projectile with a solid has been considered in detail. It has been found that any collision cascade generated by a projectile can be characterized by the average kinetic energy of cascade atoms that represents an 'instantaneous temperature' of the cascade during its very short lifetime (10-12 s). We refer to this value as the 'dynamic temperature' in order to emphasize the fact that cascade atoms are in a dynamic equilibrium and have a definite energy distribution. The dynamic temperature defines the electron distribution in the cascade area and, hence, the ionization probability of sputtered atoms. The energy distribution of cascade atoms and, as a consequence, the dynamic temperature can be found experimentally by measuring the energy distribution of sputtered atoms. The calculated dynamic temperature has been found to be in good agreement with the experimental data on ion formation in the case of cesium and oxygen ion sputtering of silicon. Based on the developed model we suggest an experimental technique for a radical improvement of the existing cascade sputtering models
Informational Cascades : A Mirage?
Spiwoks, Markus; Bizer, Kilian; Hein, Oliver
2008-01-01
Experimental research found contradictory results regarding the occurrence of informational cascades. Whereas Anderson and Holt (1997) confirmed the model of Banerjee (1992), and Bikhchandani et al. (1992) through lab tests, Huck and Oechssler (2000) came to contradictory results on crucial issues. This article presents experimental evidence supporting further doubts concerning "Bayesian" informational cascades: Just under two thirds of all decisions are characterized by an excessive orientat...
Pack, Camille Marian
2009-01-01
Twenty-two-year-old Macy Oman narrates the book in retrospect from Cascade, Oregon, where she is visiting her mother. Macy's father moved with her to Portland shortly after the accidental death of her brother, Nick, seven years before the narration begins. Macy's mother stayed behind in Cascade. Thematically the work centers on the emotional repercussions of these losses. Macy's, and her older lover Jason's, involvement with Nick's death is unknown to everyone. Her guilt and her mother's perc...
Joseph Paul Caruso
2015-12-01
Full Text Available Course-based undergraduate research is known to improve science, technology, engineering, and mathematics student achievement. We tested “The Small World Initiative, a Citizen-Science Project to Crowdsource Novel Antibiotic Discovery” to see if it also improved student performance and the critical thinking of nonscience majors in Introductory Biology at Florida Atlantic University (a large, public, minority-dominant institution in academic year 2014–15. California Critical Thinking Skills Test pre- and posttests were offered to both Small World Initiative (SWI and control lab students for formative amounts of extra credit. SWI lab students earned significantly higher lecture grades than control lab students, had significantly fewer lecture grades of D+ or lower, and had significantly higher critical thinking posttest total scores than control students. Lastly, more SWI students were engaged while taking critical thinking tests. These results support the hypothesis that utilizing independent course-based undergraduate science research improves student achievement even in nonscience students.
Caruso, Joseph P; Israel, Natalie; Rowland, Kimberly; Lovelace, Matthew J; Saunders, Mary Jane
2016-03-01
Course-based undergraduate research is known to improve science, technology, engineering, and mathematics student achievement. We tested "The Small World Initiative, a Citizen-Science Project to Crowdsource Novel Antibiotic Discovery" to see if it also improved student performance and the critical thinking of non-science majors in Introductory Biology at Florida Atlantic University (a large, public, minority-dominant institution) in academic year 2014-15. California Critical Thinking Skills Test pre- and posttests were offered to both Small World Initiative (SWI) and control lab students for formative amounts of extra credit. SWI lab students earned significantly higher lecture grades than control lab students, had significantly fewer lecture grades of D+ or lower, and had significantly higher critical thinking posttest total scores than control students. Lastly, more SWI students were engaged while taking critical thinking tests. These results support the hypothesis that utilizing independent course-based undergraduate science research improves student achievement even in nonscience students. PMID:27047613
Wei Li
2013-10-01
Full Text Available The patent cooperation network which enterprises join is a very important network platform for enterprises’ open innovation. However, very limited work has been done to empirically investigate the dynamic change process of the network in China. To address this issue, this paper analyzes dynamic change process of cooperation network of enterprises and the small-world effect of the biggest subgroup according to the data of 36731 items of cooperative patents between enterprises from 1985 to 2010 published by the State Intellectual Property Office of China. A conclusion can be drawn from the analysis results that the biggest subgroup has the characteristics of small-world effect, but the overall network structure also has some defects, which limit the development of open innovation. For the first time, suggestions on open innovation strategies are put forward to provide theoretical reference for both the government and enterprises.
Joseph Paul Caruso; Natalie Israel; Kimberly Rowland; Lovelace, Matthew J.; Mary Jane Saunders
2016-01-01
Course-based undergraduate research is known to improve science, technology, engineering, and mathematics student achievement. We tested “The Small World Initiative, a Citizen-Science Project to Crowdsource Novel Antibiotic Discovery” to see if it also improved student performance and the critical thinking of non-science majors in Introductory Biology at Florida Atlantic University (a large, public, minority-dominant institution) in academic year 2014–15. California Critical Thinking Skills T...
Ireneusz Ankiersztejn
2013-09-01
Full Text Available This article outlines the development and modifications of the Lower Vistula Cascade concept in order to meet changing requirements for utilisation of the river for power generation and navigation purposes. In the years 1957–1993 the Lower Vistula Cascade concept was modified in order to achieve the maximum power generation capacity (an example was the high efficiency of the hydropower station at the Włocławek Barrage, built in 1970 as the first and so far the only barrage of the proposed cascade. In the 1990s the potential economic benefits of the Vistula River management were re-evaluated in favour of natural and landscape merits, and another multi-variant modification of the Lower Vistula Cascade concept was carried out applying the principles of sustainable development and environmental protection. The analysis of the cascade variants considered in 1999 led to the conclusion that there is no justification for the project implementation, with the exception of the barrage located downstream of Włocławek (Nieszawa-Ciechocinek, the construction of which is essential for the Włocławek Barrage safety.
Schlenker, Cody W.
2011-09-27
We demonstrate planar organic solar cells consisting of a series of complementary donor materials with cascading exciton energies, incorporated in the following structure: glass/indium-tin-oxide/donor cascade/C 60/bathocuproine/Al. Using a tetracene layer grown in a descending energy cascade on 5,6-diphenyl-tetracene and capped with 5,6,11,12-tetraphenyl- tetracene, where the accessibility of the π-system in each material is expected to influence the rate of parasitic carrier leakage and charge recombination at the donor/acceptor interface, we observe an increase in open circuit voltage (Voc) of approximately 40% (corresponding to a change of +200 mV) compared to that of a single tetracene donor. Little change is observed in other parameters such as fill factor and short circuit current density (FF = 0.50 ± 0.02 and Jsc = 2.55 ± 0.23 mA/cm2) compared to those of the control tetracene-C60 solar cells (FF = 0.54 ± 0.02 and Jsc = 2.86 ± 0.23 mA/cm2). We demonstrate that this cascade architecture is effective in reducing losses due to polaron pair recombination at donor-acceptor interfaces, while enhancing spectral coverage, resulting in a substantial increase in the power conversion efficiency for cascade organic photovoltaic cells compared to tetracene and pentacene based devices with a single donor layer. © 2011 American Chemical Society.
Martinelli, Massimo
2009-01-01
Curso "CSS - Cascading Style Sheets" sobre programación web con CSS para el "Máster doble competencia en ciencias informáticas y ciencias sociales" ("Master double competence in computer science and social science"). Proyecto TEMPUS JEP – 26235-2005
一种具有small world特性的ESN结构分析与设计%Analysis and design on structure of small world property ESN
薄迎春; 乔俊飞; 张昭昭
2012-01-01
For the problems of complex structure design and hard parameters selection on echo state network（ESN） frame, this paper proposes a structure design method of dynamic neurons reservoir（DNR） with the small world structure（SWESN）. Design method of SWESN is introduced in detail. Neurons space growth algorithm is used to generate network with small world topology structure on 2-D plane. Then the neurons are rearranged by Euclidean distance from network＇s nodes to the fiducial node, and the physical nodes of the plane region and their internal connections are mapped to the connection matrixes of ESN internal neurons. This design method makes the DNR have small world property. The simulation experiments show that, the proposed ESN can create more abundant dynamic behavior than conventional ESN, and both robustness and anti- interference ability of SWESN are better than that of conventional ESN.%针对回声状态网络（ESN）结构设计复杂、参数选择难度大的问题,提出一种具有small world特性的ESN（SWESN）.首先采用神经元空间增长算法在平面区域生成small world拓扑网络;然后根据网络节点与基准点的Euclidean距离将网络节点进行重新排序,并将平面上的物理节点及其连接映射为SWESN的内部神经元连接矩阵,从而使动态神经元池具有small world特性.实验表明,SWESN动力学特性比常规ESN更为丰富,在鲁棒性、抗干扰能力等方面均优于常规的ESN.
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.
Superconducting cascade electron refrigerator
Camarasa-Gómez, M.; Giazotto, F. [NEST, Istituto Nanoscienze-CNR and Scuola Normale Superiore, 56127 Pisa (Italy); Di Marco, A.; Hekking, F. W. J. [LPMMC, CNRS and Université Joseph Fourier, 38042 Grenoble (France); Winkelmann, C. B.; Courtois, H. [Univ. Grenoble Alpes, Institut Néel, 38042 Grenoble (France); CNRS, Institut Néel, 38042 Grenoble (France)
2014-05-12
The design and operation of an electronic cooler based on a combination of superconducting tunnel junctions is described. The cascade extraction of hot-quasiparticles, which stems from the energy gaps of two different superconductors, allows for a normal metal to be cooled down to about 100 mK starting from a bath temperature of 0.5 K. We discuss the practical implementation, potential performance, and limitations of such a device.
Giorgetta, Fabrizio R.; Baumann, Esther; Graf, Marcel; Yang, Quankui; Manz, Christian; Köhler, Klaus; Beere, Harvey E.; Ritchie, David A.; Linfield, Edmund; Davies, Alexander G.; Fedoryshyn, Yuriy; Jackel, Heinz; Fischer, Milan; Faist, Jérôme; Hofstetter, Daniel
2010-01-01
This paper gives an overview on the design, fabrication, and characterization of quantum cascade detectors. They are tailorable infrared photodetectors based on intersubband transitions in semiconductor quantum wells that do not require an external bias voltage due to their asymmetric conduction band profile. They thus profit from favorable noise behavior, reduced thermal load, and simpler readout circuits. This was demonstrated at wavelengths from the near infrared at 2 μm to THz radiation a...
Caruso, Joseph P.; Israel, Natalie; Rowland, Kimberly; Lovelace, Matthew J.; Saunders, Mary Jane
2016-01-01
Course-based undergraduate research is known to improve science, technology, engineering, and mathematics student achievement. We tested “The Small World Initiative, a Citizen-Science Project to Crowdsource Novel Antibiotic Discovery” to see if it also improved student performance and the critical thinking of non-science majors in Introductory Biology at Florida Atlantic University (a large, public, minority-dominant institution) in academic year 2014–15. California Critical Thinking Skills Test pre- and posttests were offered to both Small World Initiative (SWI) and control lab students for formative amounts of extra credit. SWI lab students earned significantly higher lecture grades than control lab students, had significantly fewer lecture grades of D+ or lower, and had significantly higher critical thinking posttest total scores than control students. Lastly, more SWI students were engaged while taking critical thinking tests. These results support the hypothesis that utilizing independent course-based undergraduate science research improves student achievement even in nonscience students. PMID:27047613
The double-cone-shaped Cascade reaction chamber rotates at 50 rpm to keep a blanket of ceramic granules in place against the wall as they slide from the poles to the exit slots at the equator. The 1 m-thick blanket consists of layers of carbon, beryllium oxide, and lithium aluminate granules about 1 mm in diameter. The x rays and debris are stopped in the carbon granules; the neutrons are multiplied and moderated in the BeO and breed tritium in the LiAlO2. The chamber wall is made up of SiO tiles held in compression by a network of composite SiC/Al tendons. Cascade operates at a 5 Hz pulse rate with 300 MJ in each pulse. The temperature in the blanket reaches 1600 K on the inner surface and 1350 K at the outer edge. The granules are automatically thrown into three separate vacuum heat exchangers where they give up their energy to high pressure helium. The helium is used in a Brayton cycle to obtain a thermal-to-electric conversion efficiency of 55%. Studies have been done on neutron activation, debris recovery, vaporization and recondensation of blanket material, tritium control and recovery, fire safety, and cost. These studies indicate that Cascade appears to be a promising ICF reactor candidate from all standpoints. At the 1000 MWe size, electricity could be made for about the same cost as in a future fission reactor
Heckman, Jonathan J; Verlinde, Herman; Wijnholt, Martijn
2008-01-01
The MSSM can arise as an orientifold of a pyramid-like quiver in the context of intersecting D-branes. Here we consider quiver realizations of the MSSM which can emerge at the bottom of a duality cascade. We classify all possible minimal ways this can be done by allowing only one extra node. It turns out that this requires extending the geometry of the pyramid to an octahedron. The MSSM at the bottom of the cascade arises in one of two possible ways, with the extra node disappearing either via Higgsing or confinement. Remarkably, the quiver of the Higgsing scenario turns out to be nothing but the quiver version of the left-right symmetric extension of the MSSM. In the minimal confining scenario the duality cascade can proceed if and only if there is exactly one up/down Higgs pair. Moreover, the symmetries of the octahedron naturally admit an automorphism of the quiver which solves a version of the mu problem precisely when there are an odd number of generations.
Compact Quantum Cascade Laser Transmitter
Anheier, Norman C.; Hatchell, Brian K.; Gervais, Kevin L.; Wojcik, Michael D.; Krishnaswami, Kannan; Bernacki, Bruce E.
2009-04-01
): In this paper we present design considerations, thermal and optical modeling results, and device performance for a ruggedized, compact laser transmitter that utilizes a room temperature quantum cascade (QC) laser source. The QC laser transmitter is intended for portable mid-infrared (3-12 µm) spectroscopy applications, where the atmospheric transmission window is relatively free of water vapor interference and where the molecular rotational vibration absorption features can be used to detect and uniquely identify chemical compounds of interest. Initial QC laser-based sensor development efforts were constrained by the complications of cryogenic operation. However, improvements in both QC laser designs and fabrication processes have provided room-temperature devices that now enable significant miniaturization and integration potential for national security, environmental monitoring, atmospheric science, and industrial safety applications.
Geothermal research, Oregon Cascades: Final technical report
Priest, G.R.; Black, G.L.
1988-10-27
Previous USDOE-funded geothermal studies have produced an extensive temperature gradient and heat flow data base for the State of Oregon. One of the important features identified as a result of these studies is a rapid transition from heat flow values on the order of 40 mW/m/sup 2/ in the Willamette Valley and Western Cascades to values of greater than or equal to100 mW/m/sup 2/ in the High Cascades and the eastern portion of the Western Cascades. These data indicate that the Cascade Range in Oregon has potential as a major geothermal province and stimulated much of the later work completed by government agencies and private industry. Additional data generated as a result of this grant and published in DOGAMI Open-File Report 0-86-2 further define the location and magnitude of this transition zone. In addition, abundant data collected from the vicinity of Breitenbush and Austin Hot Springs have permitted the formulation of relatively detailed models of these hydrothermal systems. These models are published in DOGAMI Open-File Report 0-88-5. Task 1.2 of the Deliverables section of Amendment M001 is fulfilled by DOGAMI publication GMS-48, Geologic map of the McKenzie Bridge quadrangle, Lane County, Oregon. This map was printed in October, 1988, and is part of the final submission to USDOE. 8 refs.
Displacement cascades in polyatomic materials
Parkin, D.M.; Coulter, C.A.
1982-01-01
Using a continuous-slowing-down, random amorphous material model, we have studied displacement cascades in a number of diatomic materials. This paper reviews a number of previous results that elucidate the effects of atomic mass, recoil energy, displacement energy, capture energy and material stoichiometry on the numbers of displacements in a cascade. The displacement cascade reveals a complex structure that is dependent on the type of irradiation and the material properties. Conclusions related to damage analysis for fusion reactors are given.
Zhuo, Ning; Liu, Feng Qi; Zhang, Jin Chuan; Wang, Li Jun; Liu, Jun Qi; Zhai, Shen Qiang; Wang, Zhan Guo
2014-01-01
We demonstrated an unambiguous quantum dot cascade laser based on InGaAs/GaAs/InAs/InAlAs heterostructure by making use of self-assembled quantum dots in the Stranski-Krastanow growth mode and two-step strain compensation active region design. The prototype generates stimulated emission at λ ~ 6.15 μm and a broad electroluminescence band with full width at half maximum over 3 μm. The characteristic temperature for the threshold current density within the temperature range of 82 to 162 K is up...
Rothkegel, Alexander; 10.1063/1.3087432
2012-01-01
We investigate numerically the collective dynamical behavior of pulse-coupled non-leaky integrate-and-fire-neurons that are arranged on a two-dimensional small-world network. To ensure ongoing activity, we impose a probability for spontaneous firing for each neuron. We study network dynamics evolving from different sets of initial conditions in dependence on coupling strength and rewiring probability. Beside a homogeneous equilibrium state for low coupling strength, we observe different local patterns including cyclic waves, spiral waves, and turbulent-like patterns, which -- depending on network parameters -- interfere with the global collective firing of the neurons. We attribute the various network dynamics to distinct regimes in the parameter space. For the same network parameters different network dynamics can be observed depending on the set of initial conditions only. Such a multistable behavior and the interplay between local pattern formation and global collective firing may be attributable to the sp...
2014-01-01
We demonstrated an unambiguous quantum dot cascade laser based on InGaAs/GaAs/InAs/InAlAs heterostructure by making use of self-assembled quantum dots in the Stranski-Krastanow growth mode and two-step strain compensation active region design. The prototype generates stimulated emission at λ ~ 6.15 μm and a broad electroluminescence band with full width at half maximum over 3 μm. The characteristic temperature for the threshold current density within the temperature range of 82 to 162 K is up to 400 K. Moreover, our materials show the strong perpendicular mid-infrared response at about 1,900 cm-1. These results are very promising for extending the present laser concept to terahertz quantum cascade laser, which would lead to room temperature operation. PACS 42.55.Px; 78.55.Cr; 78.67.Hc PMID:24666965
Physics at the AGS with a relativistic cascade
Kahana, S.H.; Pang, Yang; Schlagel, T.J.
1993-02-01
The relativistic cascade code ARC is applied to the results from heavy ion collisions, at a laboratory energy of 14.6 GeV/c per nucleon, for a variety of projectiles and targets. A detailed discussion is given of the physics and inputs of this cascade. No deviation between ARC and experiment has yet been identified as a possible signal of collective hadronic behaviour.
Cascade Error Projection Learning Algorithm
Duong, T. A.; Stubberud, A. R.; Daud, T.
1995-01-01
A detailed mathematical analysis is presented for a new learning algorithm termed cascade error projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters.
Cascade Distillation System Development
Callahan, Michael R.; Sargushingh, Miriam; Shull, Sarah
2014-01-01
NASA's Advanced Exploration Systems (AES) Life Support System (LSS) Project is chartered with de-veloping advanced life support systems that will ena-ble NASA human exploration beyond low Earth orbit (LEO). The goal of AES is to increase the affordabil-ity of long-duration life support missions, and to re-duce the risk associated with integrating and infusing new enabling technologies required to ensure mission success. Because of the robust nature of distillation systems, the AES LSS Project is pursuing develop-ment of the Cascade Distillation Subsystem (CDS) as part of its technology portfolio. Currently, the system is being developed into a flight forward Generation 2.0 design.
Vurgaftman, I.; Weih, R.; Kamp, M.; Meyer, J. R.; Canedy, C. L.; Kim, C. S.; Kim, M.; Bewley, W. W.; Merritt, C. D.; Abell, J.; Höfling, S.
2015-04-01
We review the current status of interband cascade lasers (ICLs) emitting in the midwave infrared (IR). The ICL may be considered the hybrid of a conventional diode laser that generates photons via electron-hole recombination, and an intersubband-based quantum cascade laser (QCL) that stacks multiple stages for enhanced current efficiency. Following a brief historical overview, we discuss theoretical aspects of the active region and core designs, growth by molecular beam epitaxy, and the processing of broad-area, narrow-ridge, and distributed feedback (DFB) devices. We then review the experimental performance of pulsed broad area ICLs, as well as the continuous-wave (cw) characteristics of narrow ridges having good beam quality and DFBs producing output in a single spectral mode. Because the threshold drive powers are far lower than those of QCLs throughout the λ = 3-6 µm spectral band, ICLs are increasingly viewed as the laser of choice for mid-IR laser spectroscopy applications that do not require high output power but need to be hand-portable and/or battery operated. Demonstrated ICL performance characteristics to date include threshold current densities as low as 106 A cm-2 at room temperature (RT), cw threshold drive powers as low as 29 mW at RT, maximum cw operating temperatures as high as 118 °C, maximum cw output powers exceeding 400 mW at RT, maximum cw wallplug efficiencies as high as 18% at RT, maximum cw single-mode output powers as high as 55 mW at RT, and single-mode output at λ = 5.2 µm with a cw drive power of only 138 mW at RT.
We review the current status of interband cascade lasers (ICLs) emitting in the midwave infrared (IR). The ICL may be considered the hybrid of a conventional diode laser that generates photons via electron–hole recombination, and an intersubband-based quantum cascade laser (QCL) that stacks multiple stages for enhanced current efficiency. Following a brief historical overview, we discuss theoretical aspects of the active region and core designs, growth by molecular beam epitaxy, and the processing of broad-area, narrow-ridge, and distributed feedback (DFB) devices. We then review the experimental performance of pulsed broad area ICLs, as well as the continuous-wave (cw) characteristics of narrow ridges having good beam quality and DFBs producing output in a single spectral mode. Because the threshold drive powers are far lower than those of QCLs throughout the λ = 3–6 µm spectral band, ICLs are increasingly viewed as the laser of choice for mid-IR laser spectroscopy applications that do not require high output power but need to be hand-portable and/or battery operated. Demonstrated ICL performance characteristics to date include threshold current densities as low as 106 A cm−2 at room temperature (RT), cw threshold drive powers as low as 29 mW at RT, maximum cw operating temperatures as high as 118 °C, maximum cw output powers exceeding 400 mW at RT, maximum cw wallplug efficiencies as high as 18% at RT, maximum cw single-mode output powers as high as 55 mW at RT, and single-mode output at λ = 5.2 µm with a cw drive power of only 138 mW at RT. (topical review)
Dong, Lin-Rong
2010-09-01
This paper investigates the dynamic evolution with limited learning information on a small-world network. In the system, the information among the interaction players is not very lucid, and the players are not allowed to inspect the profit collected by its neighbors, thus the focal player cannot choose randomly a neighbor or the wealthiest one and compare its payoff to copy its strategy. It is assumed that the information acquainted by the player declines in the form of the exponential with the geographical distance between the players, and a parameter V is introduced to denote the inspect-ability about the players. It is found that under the hospitable conditions, cooperation increases with the randomness and is inhibited by the large connectivity for the prisoner's dilemma; however, cooperation is maximal at the moderate rewiring probability and is chaos with the connectivity for the snowdrift game. For the two games, the acuminous sight is in favor of the cooperation under the hospitable conditions; whereas, the myopic eyes are advantageous to cooperation and cooperation increases with the randomness under the hostile condition.
By extending a dynamical mean-field approximation previously proposed by the author [H. Hasegawa, Phys. Rev. E 67, 041903 (2003)], we have developed a semianalytical theory which takes into account a wide range of couplings in a small-world network. Our network consists of noisy N-unit FitzHugh-Nagumo neurons with couplings whose average coordination number Z may change from local (Z<< N) to global couplings (Z=N-1) and/or whose concentration of random couplings p is allowed to vary from regular (p=0) to completely random (p=1). We have taken into account three kinds of spatial correlations: the on-site correlation, the correlation for a coupled pair, and that for a pair without direct couplings. The original 2N-dimensional stochastic differential equations are transformed to 13-dimensional deterministic differential equations expressed in terms of means, variances, and covariances of state variables. The synchronization ratio and the firing-time precision for an applied single spike have been discussed as functions of Z and p. Our calculations have shown that with increasing p, the synchronization is worse because of increased heterogeneous couplings, although the average network distance becomes shorter. Results calculated by our theory are in good agreement with those by direct simulations
Cascade redox flow battery systems
Horne, Craig R.; Kinoshita, Kim; Hickey, Darren B.; Sha, Jay E.; Bose, Deepak
2014-07-22
A reduction/oxidation ("redox") flow battery system includes a series of electrochemical cells arranged in a cascade, whereby liquid electrolyte reacts in a first electrochemical cell (or group of cells) before being directed into a second cell (or group of cells) where it reacts before being directed to subsequent cells. The cascade includes 2 to n stages, each stage having one or more electrochemical cells. During a charge reaction, electrolyte entering a first stage will have a lower state-of-charge than electrolyte entering the nth stage. In some embodiments, cell components and/or characteristics may be configured based on a state-of-charge of electrolytes expected at each cascade stage. Such engineered cascades provide redox flow battery systems with higher energy efficiency over a broader range of current density than prior art arrangements.
Ultrarelativistic cascades and strangeness production
Kahana, D.E. [State Univ. of New York, Stony Brook, NY (United States). Dept. of Physics; Kahana, S.H. [Brookhaven National Lab., Upton, NY (United States). Physics Dept.
1998-08-24
A two-phase cascade code, LUCIFER II, developed for the treatment of ultra high energy-ion-ion collisions is applied to the production of strangeness at SPS energies {radical}(s)=17-20. This simulation is able to simultaneously describe both hard processes such as Drell-Yan and slower, soft processes such as the production of light mesons by separating the dynamics into two steps, a fast cascade involving only the nucleons in the original colliding relativistic ions followed, after an appropriate delay, by a normal multiscattering of the resulting excited baryons and mesons produced virtually in the first step. No energy loss can take place in the short time interval over which the first cascade takes place. The chief result is a reconciliation of the important Drell-Yan measurements with the apparent success of standard cascades to describe the nucleon stopping and meson production in heavy-ion experiments at the CERN SPS. (orig.) 26 refs.
Ultrarelativistic cascades and strangeness production
A two-phase cascade code, LUCIFER II, developed for the treatment of ultra high energy-ion-ion collisions is applied to the production of strangeness at SPS energies √(s)=17-20. This simulation is able to simultaneously describe both hard processes such as Drell-Yan and slower, soft processes such as the production of light mesons by separating the dynamics into two steps, a fast cascade involving only the nucleons in the original colliding relativistic ions followed, after an appropriate delay, by a normal multiscattering of the resulting excited baryons and mesons produced virtually in the first step. No energy loss can take place in the short time interval over which the first cascade takes place. The chief result is a reconciliation of the important Drell-Yan measurements with the apparent success of standard cascades to describe the nucleon stopping and meson production in heavy-ion experiments at the CERN SPS. (orig.)
Ultrarelativistic cascades and strangeness production
Kahana, D.E. [State Univ. of New York, Stony Brook, NY (United States). Physics Dept.; Kahana, S.H. [Brookhaven National Lab., Upton, NY (United States). Physics Dept.
1998-02-01
A two phase cascade, LUCIFER II, developed for the treatment of ultra high energy Ion-Ion collisions is applied to the production of strangeness at SPS energies. This simulation is able to simultaneously describe both hard processes such as Drell-Yan and slower, soft processes such as the production of light mesons by separating the dynamics into two steps, a fast cascade involving only the nucleons in the original colliding relativistic ions followed, after an appropriate delay, by a normal multiscattering of the resulting excited baryons and mesons produced virtually in the first step. No energy loss can take place in the short time interval over which the first cascade takes place. The chief result is a reconciliation of the important Drell-Yan measurements with the apparent success of standard cascades to describe the nucleon stopping and meson production in heavy ion experiments at the CERN SPS.
Interband Cascade Photovoltaic Cells
Yang, Rui Q. [Univ. of Oklahoma, Norman, OK (United States); Santos, Michael B. [Univ. of Oklahoma, Norman, OK (United States); Johnson, Matthew B. [Univ. of Oklahoma, Norman, OK (United States)
2014-09-24
In this project, we are performing basic and applied research to systematically investigate our newly proposed interband cascade (IC) photovoltaic (PV) cells [1]. These cells follow from the great success of infrared IC lasers [2-3] that pioneered the use of quantum-engineered IC structures. This quantum-engineered approach will enable PV cells to efficiently convert infrared radiation from the sun or other heat source, to electricity. Such cells will have important applications for more efficient use of solar energy, waste-heat recovery, and power beaming in combination with mid-infrared lasers. The objectives of our investigations are to: achieve extensive understanding of the fundamental aspects of the proposed PV structures, develop the necessary knowledge for making such IC PV cells, and demonstrate prototype working PV cells. This research will focus on IC PV structures and their segments for utilizing infrared radiation with wavelengths from 2 to 5 μm, a range well suited for emission by heat sources (1,000-2,000 K) that are widely available from combustion systems. The long-term goal of this project is to push PV technology to longer wavelengths, allowing for relatively low-temperature thermal sources. Our investigations address material quality, electrical and optical properties, and their interplay for the different regions of an IC PV structure. The tasks involve: design, modeling and optimization of IC PV structures, molecular beam epitaxial growth of PV structures and relevant segments, material characterization, prototype device fabrication and testing. At the end of this program, we expect to generate new cutting-edge knowledge in the design and understanding of quantum-engineered semiconductor structures, and demonstrate the concepts for IC PV devices with high conversion efficiencies.
A Cascading Failure Model by Quantifying Interactions
Qi, Junjian; Mei, Shengwei
2013-01-01
Cascading failures triggered by trivial initial events are encountered in many complex systems. It is the interaction and coupling between components of the system that causes cascading failures. We propose a simple model to simulate cascading failure by using the matrix that determines how components interact with each other. A careful comparison is made between the original cascades and the simulated cascades by the proposed model. It is seen that the model can capture general features of t...
Peng, Junhao
2016-03-01
In this paper, we study random walks on a small-world scale-free network, also called as pseudofractal scale-free web (PSFW), and analyze the volatilities of first passage time (FPT) and first return time (FRT) by using the variance and reduced moment as measures. Note that the FRT and FPT are deeply affected by the starting or target site. We do not intend to enumerate all the possible cases and analyze them. We only study the volatilities of FRT for a given hub (i.e. node with highest degree) and the volatilities of the global FPT (GFPT) to a given hub, which is the average of the FPTs for arriving at a given hub from any possible starting site selected randomly according to the equilibrium distribution of the Markov chain. Firstly, we calculate exactly the probability generating function of the GFPT and FRT based on the self-similar structure of the PSFW. Then, we calculate the probability distribution, mean, variance and reduced moment of the GFPT and FRT by using the generating functions as a tool. Results show that: the reduced moment of FRT grows with increasing network order N and tends to infinity while N\\to ∞ ; but for the reduced moments of GFPT, it is almost a constant(≈ 1.1605) for large N. Therefore, on the PSFW of large size, the FRT has huge fluctuations and the estimate provided by MFRT is unreliable, whereas the fluctuations of the GFPT are much smaller and the estimate provided by its mean is more reliable. The method we propose can also be used to analyze the volatilities of FPT and FRT on other networks with self-similar structure, such as (u, v) flowers and recursive scale-free trees.
Effects of link-orientation methods on robustness against cascading failures in complex networks
Jiang, Zhong-Yuan; Ma, Jian-Feng; Shen, Yu-Long; Zeng, Yong
2016-09-01
Unidirectional and bidirectional links may coexist in many realistic networked complex systems such as the city transportation networks. Even more, for some considerations, several bidirectional links are shifted to unidirectional ones. Many link-orientation strategies might be employed, including High-to-Low, Low-to-High and Random direction-determining methods, abbreviated as HTLDD, LTHDD and RDD respectively. Traffic passing through a unidirectional link is restricted to one-side direction. In real complex systems, nodes are correlated with each other. The failure from an initial node may be propagated iteratively, resulting in a large scale of failures of other nodes, called cascade phenomenon which may damage the safety or security of the networked system. Assuming that traffic load on any failed node can be redistributed to its non-failed neighbors, in this work, we try to reveal the effects of unidirectional links on network robustness against cascades. Extensive simulations have been implemented on kinds of networks including Scale-Free networks, Small-World networks, and Erdös-Rényi random networks. The results showed that all of the above three direction-determining methods decrease the robustness of the original networks against cascading failure. This work can help network designers and managers understand the robustness of network well and efficiently prevent the safety events.
Rescuing Ecosystems from Extinction Cascades
Sahasrabudhe, Sagar; Motter, Adilson
2010-03-01
Food web perturbations stemming from climate change, overexploitation, invasive species, and natural disasters often cause an initial loss of species that results in a cascade of secondary extinctions. Using a predictive modeling framework, here we will present a systematic network-based approach to reduce the number of secondary extinctions. We will show that the extinction of one species can often be compensated by the concurrent removal of a second specific species, which is a counter-intuitive effect not previously tested in complex food webs. These compensatory perturbations frequently involve long-range interactions that are not a priori evident from local predator-prey relationships. Strikingly, in numerous cases even the early removal of a species that would eventually be extinct by the cascade is found to significantly reduce the number of cascading extinctions. Other nondestructive interventions based on partial removals and growth suppression and/or mortality increase are shown to sometimes prevent all secondary extinctions.
Nanowire terahertz quantum cascade lasers
Quantum cascade lasers made of nanowire axial heterostructures are proposed. The dissipative quantum dynamics of their carriers is theoretically investigated using non-equilibrium Green functions. Their transport and gain properties are calculated for varying nanowire thickness, from the classical-wire regime to the quantum-wire regime. Our calculation shows that the lateral quantum confinement provided by the nanowires allows an increase of the maximum operation temperature and a strong reduction of the current density threshold compared to conventional terahertz quantum cascade lasers.
Power Grid Defense Against Malicious Cascading Failure
Shakarian, Paulo; Lindelauf, Roy
2014-01-01
An adversary looking to disrupt a power grid may look to target certain substations and sources of power generation to initiate a cascading failure that maximizes the number of customers without electricity. This is particularly an important concern when the enemy has the capability to launch cyber-attacks as practical concerns (i.e. avoiding disruption of service, presence of legacy systems, etc.) may hinder security. Hence, a defender can harden the security posture at certain power stations but may lack the time and resources to do this for the entire power grid. We model a power grid as a graph and introduce the cascading failure game in which both the defender and attacker choose a subset of power stations such as to minimize (maximize) the number of consumers having access to producers of power. We formalize problems for identifying both mixed and deterministic strategies for both players, prove complexity results under a variety of different scenarios, identify tractable cases, and develop algorithms f...
Characteristics for two kinds of cascading events
Zou, Sheng-Rong; Gu, Ai-Hua; Liu, Ai-Fen; Xu, Xiu-Lian; Wang, Jian; He, Da-Ren
2011-04-01
Avalanche or cascade failure is ubiquitous. We first classify the cascading phenomena into two categories: the cascading disasters which result in large-scale functional failures and the cascading events that do not lead to disasters. We elucidate that two important factors, the increasing amount of events and the acceleration of event frequency, can induce the crossover from the cascading phenomenon to the cascading disaster. Through a simplified sandpile model and a heuristic logistic map, we demonstrate that the dependence of the event number on the observation time behaves as a power-law and as an exponential for these two different cascading events, respectively. The analytic derivations are found to be consistent with several empirical observations. Our present findings contribute to the understanding of the transition between different cascading events, providing a basis for the further understanding of the transitions among more general critical events.
Cascade Support Vector Machines with Dimensionality Reduction
Oliver Kramer
2015-01-01
Full Text Available Cascade support vector machines have been introduced as extension of classic support vector machines that allow a fast training on large data sets. In this work, we combine cascade support vector machines with dimensionality reduction based preprocessing. The cascade principle allows fast learning based on the division of the training set into subsets and the union of cascade learning results based on support vectors in each cascade level. The combination with dimensionality reduction as preprocessing results in a significant speedup, often without loss of classifier accuracies, while considering the high-dimensional pendants of the low-dimensional support vectors in each new cascade level. We analyze and compare various instantiations of dimensionality reduction preprocessing and cascade SVMs with principal component analysis, locally linear embedding, and isometric mapping. The experimental analysis on various artificial and real-world benchmark problems includes various cascade specific parameters like intermediate training set sizes and dimensionalities.
Azobenzene-functionalized cascade molecules
Archut, A.; Vogtle, F.; De Cola, L.;
1998-01-01
Cascade molecules bearing up to 32 azobenzene groups in the periphery have been prepared from poly(propylene imine) dendrimers and N-hydroxysuccinimide esters. The dendritic azobenzene species show similar isomerization properties as the corresponding azobenzene monomers. The all-E azobenzene den...
Applications of cascade multilevel inverters
彭方正; 钱照明
2003-01-01
Cascade multilevel inverters have been developed for electric utility applications. A cascade M-level inverter consists of (M-1)/2 H-bridges in which each bridge's dc voltage is supported by its own de ca-pacitor. The new inverter can : ( 1 ) generate almost sinusoidal waveform voltage while only switching one timeper fundamental cycle ; (2) dispense with multi-pulse inverters' transformers used in conventional utility in-terfaces and static var compensators; (3) enables direct parallel or series transformer-less connection to medium- and high-voltage power systems. In short, the cascade inverter is much more efficient and suitable for utility applications than traditional multi-pulse and pulse width modulation (PWM) inverters. The authors have experimentally demonstrated the superiority of the new inverter for power supply, (hybrid) electric vehicle (EV) motor drive, reactive power (var) and harmonic compensation. This paper summarizes the features,feasibility, and control schemes of the cascade inverter for utility applications including utility interface of renewable energy, voltage regulation, var compensation, and harmonic filtering in power systems. Analytical,simulated, and experimental results demonstrated the superiority of the new inverters.
Applications of cascade multilevel inverters
彭方正; 钱照明
2003-01-01
Cascade multilevel inverters have been developed for electric utility applications. A cascade M-level inverter consists of (M-1)/2 H-bridges in which each bridge's dc voltage is supported by its own dc capacitor. The new inverter can: (1) generate almost sinusoidal waveform voltage while only switching one time per fundamental cycle; (2) dispense with multi-pulse inverters' transformers used in conventional utility interfaces and static var compensators; (3) enables direct parallel or series transformer-less connection to medium- and high-voltage power systems. In short, the cascade inverter is much more efficient and suitable for utility applications than traditional multi-pulse and pulse width modulation (PWM) inverters. The authors have experimentally demonstrated the superiority of the new inverter for power supply, (hybrid) electric vehicle (EV) motor drive, reactive power (var) and harmonic compensation. This paper summarizes the features, feasibility, and control schemes of the cascade inverter for utility applications including utility interface of renewable energy, voltage regulation, var compensation, and harmonic filtering in power systems. Analytical, simulated, and experimental results demonstrated the superiority of the new inverters.
Multiplicity distributions in QCD cascades
Multiplicity distributions for hadrons and for jets are studied in QCD parton cascades. The colour dipole formalism is used and earlier results in the double log approximation are generalized to include terms which are suppressed by colour factors or factors of ln s. The result is a set of coupled differential equations, together with appropriate boundary conditions
Strangeness Production and Ultrarelativistic Cascades
Kahana, D E
1998-01-01
A two phase cascade, LUCIFER II, developed for the treatment of ultra high energy ion-ion collisions is applied to the production of strangeness at SPS energies $\\sqrt{s}=17-20$. This simulation is able to simultaneously describe both hard processes such as Drell-Yan and slower, soft processes such as the production of light mesons, including strange mesons, by separating the dynamics into two steps, a fast cascade involving only nucleons in the original colliding relativistic ions followed, after an appropriate delay, by multiscattering of the resulting excited baryons and mesons produced virtually in the first step. No energy loss can take place in the short time interval over which the first cascade takes place. The chief result is a reconciliation of the important Drell-Yan measurements with the apparent success of standard cascades to describe the nucleon stopping and meson production in heavy ion experiments at the CERN SPS. A byproduct, obtained here in preliminary calculations, is a description of str...
Critical assessment and ramifications of a purported marine trophic cascade.
Grubbs, R Dean; Carlson, John K; Romine, Jason G; Curtis, Tobey H; McElroy, W David; McCandless, Camilla T; Cotton, Charles F; Musick, John A
2016-01-01
When identifying potential trophic cascades, it is important to clearly establish the trophic linkages between predators and prey with respect to temporal abundance, demographics, distribution, and diet. In the northwest Atlantic Ocean, the depletion of large coastal sharks was thought to trigger a trophic cascade whereby predation release resulted in increased cownose ray abundance, which then caused increased predation on and subsequent collapse of commercial bivalve stocks. These claims were used to justify the development of a predator-control fishery for cownose rays, the "Save the Bay, Eat a Ray" fishery, to reduce predation on commercial bivalves. A reexamination of data suggests declines in large coastal sharks did not coincide with purported rapid increases in cownose ray abundance. Likewise, the increase in cownose ray abundance did not coincide with declines in commercial bivalves. The lack of temporal correlations coupled with published diet data suggest the purported trophic cascade is lacking the empirical linkages required of a trophic cascade. Furthermore, the life history parameters of cownose rays suggest they have low reproductive potential and their populations are incapable of rapid increases. Hypothesized trophic cascades should be closely scrutinized as spurious conclusions may negatively influence conservation and management decisions. PMID:26876514
Critical assessment and ramifications of a purported marine trophic cascade
Grubbs, R. Dean; Carlson, John K.; Romine, Jason G.; Curtis, Tobey H.; McElroy, W. David; McCandless, Camilla T.; Cotton, Charles F.; Musick, John A.
2016-02-01
When identifying potential trophic cascades, it is important to clearly establish the trophic linkages between predators and prey with respect to temporal abundance, demographics, distribution, and diet. In the northwest Atlantic Ocean, the depletion of large coastal sharks was thought to trigger a trophic cascade whereby predation release resulted in increased cownose ray abundance, which then caused increased predation on and subsequent collapse of commercial bivalve stocks. These claims were used to justify the development of a predator-control fishery for cownose rays, the “Save the Bay, Eat a Ray” fishery, to reduce predation on commercial bivalves. A reexamination of data suggests declines in large coastal sharks did not coincide with purported rapid increases in cownose ray abundance. Likewise, the increase in cownose ray abundance did not coincide with declines in commercial bivalves. The lack of temporal correlations coupled with published diet data suggest the purported trophic cascade is lacking the empirical linkages required of a trophic cascade. Furthermore, the life history parameters of cownose rays suggest they have low reproductive potential and their populations are incapable of rapid increases. Hypothesized trophic cascades should be closely scrutinized as spurious conclusions may negatively influence conservation and management decisions.
Fragmentation of displacement cascades into subcascades: A molecular dynamics study
Highlights: • The subcascades formation in copper and iron is studied by molecular dynamics method. • A two-point density correlation function is a tool for detecting subcascade formation. • A fractal analysis served to determine the subcascade formation threshold energy. • The temporal evolution of displacement cascades is investigated. - Abstract: The fragmentation of displacement cascades into subcascades in copper and iron has been investigated through the molecular dynamics technique. A two-point density correlation function has been used to analyze the cascades as a function of the primary knock-on (PKA) energy. This approach is used as a tool for detecting subcascade formation. The fragmentation can already be identified at the end of the ballistic phase. Its resulting evolution in the peak damage state discriminates between unconnected and connected subcascades. The damage zone at the end of the ballistic phase is the precursor of the extended regions that contain the surviving defects. A fractal analysis of the cascade exhibits a dependence on both the stage of the cascade development and the PKA energy. This type of analysis enables the minimum and maximum displacement spike energies together with the subcascade formation threshold energy to be determined