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Complex networks: Structure and dynamics

TLDR
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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Information cascades in complex networks

TL;DR: Simulation results on sample networks reveal just how relevant the centrality of initiator nodes is on the latter development of an information cascade, and the spreading influence of a node is defined as the fraction of nodes that is activated as a result of the initial activation of that node.
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Self-organization towards optimally interdependent networks by means of coevolution

TL;DR: In this paper, the authors introduce the coevolution of strategy and network interdependence to see whether this can give rise to elevated levels of cooperation in the prisoner's dilemma game.
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On QUAD, Lipschitz, and Contracting Vector Fields for Consensus and Synchronization of Networks

TL;DR: The usefulness of the links highlighted in this paper to obtain proofs of asymptotic synchronization in networks of identical nonlinear oscillators are illustrated via numerical simulations on some representative examples.
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Dynamical patterns of cattle trade movements.

TL;DR: A novel definition of dynamical motifs is proposed that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions.
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Entropy of network ensembles.

TL;DR: The structural entropy is defined and evaluated, i.e., the entropy of the ensembles of undirected uncorrelated simple networks with given degree sequence, and a solution to the paradox is proposed by proving that scale-free degree distributions are the most likely degree distribution with the corresponding value of the structural entropy.
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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.
Journal ArticleDOI

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.