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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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Small‐world properties of nonlinear brain activity in schizophrenia

TL;DR: Nonlinear measures of cortical interactions and graph‐theoretical metrics of network topography are combined to investigate this schizophrenia “disconnection hypothesis” by analyzing the spatiotemporal structure of resting state scalp EEG data from 40 young subjects with a recent first episode of schizophrenia and 40 healthy matched controls.
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A Comparative Analysis of Community Detection Algorithms on Artificial Networks

TL;DR: This study uses the Lancichinetti-Fortunato-Radicchi benchmark graph to test eight state-of-the-art community detection algorithms and provides guidelines that help to choose the most adequate community detection algorithm for a given network.
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Navigability of complex networks

TL;DR: In this article, a framework is proposed to explain why "navigability" is so efficient in complex networks, considering that no node has a full view of the entire network.
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Synchronization of Networks of Nonidentical Euler-Lagrange Systems With Uncertain Parameters and Communication Delays

TL;DR: The main result of the paper is the construction of an adaptive controller that achieves global full-state synchronization, i.e., the difference between the agents positions and velocities asymptotically converges to zero.
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A network approach to psychopathology: New insights into clinical longitudinal data

TL;DR: The analysis generates a plausible and replicable network architecture, the structure of which is related to variables such as neuroticism; that is, for subjects who score high on neuroticism, worrying plays a more central role in the network.
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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.