Author
Stefano Boccaletti
Other affiliations: King Juan Carlos University, Istituto Nazionale di Fisica Nucleare, East China Normal University ...read more
Bio: Stefano Boccaletti is an academic researcher from Moscow Institute of Physics and Technology. The author has contributed to research in topics: Complex network & Synchronization (computer science). The author has an hindex of 60, co-authored 348 publications receiving 25776 citations. Previous affiliations of Stefano Boccaletti include King Juan Carlos University & Istituto Nazionale di Fisica Nucleare.
Papers published on a yearly basis
Papers
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TL;DR: How opinions evolve in time according to the frequency rates of the nodes, to the coupling term, and also to the presence of group structures is studied.
Abstract: In this paper we discuss opinion dynamics in the opinion changing rate ( OCR ) model, recently proposed in Pluchino et al. [Int. J. Mod. Phys. C 16(4) (2005) 515–531]. The OCR model allows to study whether and how a group of social agents, with a different intrinsic tendency ( rate ) to change opinion, finds agreement. In particular, we implement the OCR model on a small graph describing the topology of a real social system. The nodes of the graph are scientists participating in the Tepoztlan conference, celebrating Alberto Robledo's 60th birthday, and the links are based on coauthorship in scientific papers. We study how opinions evolve in time according to the frequency rates of the nodes, to the coupling term, and also to the presence of group structures.
52 citations
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TL;DR: An analytic method is proposed to measure the stability of the synchronous state (SSS) the subgraph displays and it is shown that, for undirected graphs, the SSS is correlated with the relative abundance, while in directed graphs the correlation exists only for some specific motifs.
Abstract: We address the problem of understanding the variable abundance of 3-node and 4-node subgraphs (motifs) in complex networks from a dynamical point of view. As a criterion in the determination of the functional significance of a n-node subgraph, we propose an analytic method to measure the stability of the synchronous state (SSS) the subgraph displays. We show that, for undirected graphs, the SSS is correlated with the relative abundance, while in directed graphs the correlation exists only for some specific motifs.
52 citations
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TL;DR: In this paper, the morphology of the spatial structures displayed by an optical system consisting of a liquid crystal light valve (LCLV) in a feedback configuration, as the feedback is gradually tuned from purely diffractive to mixed interferential and diffractive.
Abstract: We compare the morphology of the spatial structures displayed by an optical system consisting of a liquid crystal light valve (LCLV) in a feedback configuration, as the feedback is gradually tuned from purely diffractive to mixed interferential and diffractive. Different kinds of spatially coherent structures (e.g. hexagons, rolls), as well as localized structures and space-time turbulent patterns are observed. The features of the localized structures change with the parameter setting, and certain regions of the parameter space provide stable clusters of isolated spots (`molecules'). Numerical simulations based on a Kerr-like model of the LCLV are in agreement with the experimental observations. We analyse the links between the observed behaviours and the results of a linear-stability analysis of the underlying homogeneous stationary states.
51 citations
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TL;DR: In this article, an experimental observation of such a scenario has been done in a laser with an intracavity saturable absorber, and the authors have shown that the oscillations in the vicinity of subcritical or transcritical bifurcations with a different scenario from those previously introduced in biology, chemistry and liquid-crystal physics.
Abstract: Excitability and relaxation oscillations are shown to appear in the vicinity of subcritical or transcritical bifurcations with a different scenario from those previously introduced in biology, chemistry and liquid-crystal physics. Experimental observation of such a scenario has been done in a laser with intracavity saturable absorber.
51 citations
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TL;DR: It is demonstrated that explosive transitions coexist with standard transitions in the limit of f → 0, and it is shown that this behavior is far more likely to occur naturally than was previously believed.
Abstract: Explosive synchronization has recently been reported in a system of adaptively coupled Kuramoto oscillators, without any conditions on the frequency or degree of the nodes. Here, we find that, in fact, the explosive phase coexists with the standard phase of the Kuramoto oscillators. We determine this by extending the mean-field theory of adaptively coupled oscillators with full coupling to the case with partial coupling of a fraction f. This analysis shows that a metastable region exists for all finite values of f > 0, and therefore explosive synchronization is expected for any perturbation of adaptively coupling added to the standard Kuramoto model. We verify this theory with GPU-accelerated simulations on very large networks (N ∼ 106) and find that, in fact, an explosive transition with hysteresis is observed for all finite couplings. By demonstrating that explosive transitions coexist with standard transitions in the limit of f → 0, we show that this behavior is far more likely to occur naturally than was previously believed.
51 citations
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28,685 citations
28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。
18,940 citations
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.
10,141 citations
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TL;DR: This article reviews studies investigating complex brain networks in diverse experimental modalities and provides an accessible introduction to the basic principles of graph theory and highlights the technical challenges and key questions to be addressed by future developments in this rapidly moving field.
Abstract: Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization. The brain's structural and functional systems have features of complex networks--such as small-world topology, highly connected hubs and modularity--both at the whole-brain scale of human neuroimaging and at a cellular scale in non-human animals. In this article, we review studies investigating complex brain networks in diverse experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans) and provide an accessible introduction to the basic principles of graph theory. We also highlight some of the technical challenges and key questions to be addressed by future developments in this rapidly moving field.
9,700 citations