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Complex networks: Structure and dynamics

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The major concepts and results recently achieved in the study of the structure and dynamics of complex networks are reviewed, and the relevant applications of these ideas in many different disciplines are summarized, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.
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This article is published in Physics Reports.The article was published on 2006-02-01 and is currently open access. It has received 9441 citations till now. The article focuses on the topics: Network dynamics & Complex network.

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Chimera states in brain networks: empirical neural vs. modular fractal connectivity

TL;DR: In this paper, the collective dynamics of FitzHugh-Nagumo neurons in complex networks were analyzed for epileptic seizures and the influence of the removal of nodes on the network synchronizability.
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Epidemic spreading with nonlinear infectivity in weighted scale-free networks

TL;DR: In this article, the authors investigate the epidemic spreading for the SIR model in weighted scale-free networks with the nonlinear infectivity and weighted transmission rate, and examine the impact of α and β on epidemic spreading.
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Centrality measures for networks with community structure

TL;DR: A centrality measure is proposed here that requires information only at the community level and is evaluated by performing experiments on synthetic and real-world networks with community structure in the case of immunization of nodes for epidemic control.
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Impact of policies on electric vehicle diffusion: An evolutionary game of small world network analysis

TL;DR: Wang et al. as mentioned in this paper used the NW (Newman and Watts) network model to explore the dynamic effects of different policies on the diffusion of electric vehicles and found that the government's purchase subsidy policy and restricted travel policy can promote the diffusion rate of automobiles to 60%, and the short-term effect is remarkable.
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Percolation on complex networks: Theory and application

TL;DR: The percolation theory has already percolated into the researches of structure analysis and dynamic modeling in network science, such as robustness, epidemic spreading, vital node identification, and community detection.
References
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Optimization by Simulated Annealing

TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Book

Computers and Intractability: A Guide to the Theory of NP-Completeness

TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
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Collective dynamics of small-world networks

TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Book

Matrix computations

Gene H. Golub
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The authors review the major concepts and results recently achieved in the study of the structure and dynamics of complex networks, and summarize the relevant applications of these ideas in many different disciplines, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.