Correlation effects in a simple model of small-world network

We analyze the effect of correlations in a simple model of small world network by obtaining exact analytical expressions for the distribution of shortest paths in the network. We enter correlations into a simple model with a distinguished site, by taking the random connections to this site from an Ising distribution. Our method shows how the transfer matrix technique can be used in the new context of small world networks.Comment: 10 pages, 3 figure

Opinion and community formation in coevolving networks

In human societies opinion formation is mediated by social interactions, consequently taking place on a network of relationships and at the same time influencing the structure of the network and its evolution. To investigate this coevolution of opinions and social interaction structure we develop a dynamic agent-based network model, by taking into account short range interactions like discussions between individuals, long range interactions like a sense for overall mood modulated by the attitudes of individuals, and external field corresponding to outside influence. Moreover, individual biases can be naturally taken into account. In addition the model includes the opinion dependent link-rewiring scheme to describe network topology coevolution with a slower time scale than that of the opinion formation. With this model comprehensive numerical simulations and mean field calculations have been carried out and they show the importance of the separation between fast and slow time scales resulting in the network to organize as well-connected small communities of agents with the same opinion.Comment: 10 pages, 5 figures. New inset for Fig. 1 and references added. Submitted to Physical Review

State of the science and the way forward for the ecotoxicological assessment of contaminated land.

Durante as últimas duas décadas, ecotoxicologistas de solo têm feito progressos ao utilizar conceitos básicos e avanços da zoologia e ecologia do solo. Os métodos existentes têm sido aplicados, e têm-se desenvolvido novas ferramentas para avaliar de que modo a contaminação química pode afetar o ecossistema terrestre, inclusive pela degradação ou destruição da qualidade do solo e dos habitats ou pela redução da biodiversidade edáfica. Os ecotoxicologistas de solo utilizam um conjunto de protocolos padronizados, originalmente desenvolvidos como testes de laboratório com compostos químicos simples como os pesticidas e, posteriormente, adaptados em termos de abordagens e métodos, para a avaliação de áreas contaminadas. No entanto, a relevância ecológica de algumas abordagens permanece questionável. Neste artigo, os autores discutem os recentes desafios para uma avaliação ecotoxicológica coerente do ecossistema solo em áreas contaminadas e apresentam recomendações de como integrar os efeitos das propriedades físicoquímicas do solo, as variações na diversidade de invertebrados do solo e, as interações entre organismos dos vários níveis tróficos. São analisadas novas abordagens e métodos de avaliação, usando-se exemplos de três continentes (particularmente o trabalho desenvolvido no Brasil), e são dadas recomendações de como aumentar a relevância ecológica na avaliação ecotoxicológica de áreas contaminadas

Experimental evidence of stochastic resonance without tuning due to non Gaussian noises

In order to test theoretical predictions, we have studied the phenomenon of stochastic resonance in an electronic experimental system driven by white non Gaussian noise. In agreement with the theoretical predictions our main findings are: an enhancement of the sensibility of the system together with a remarkable widening of the response (robustness). This implies that even a single resonant unit can reach a marked reduction in the need of noise tuning.Comment: 4 pages, 3 figure

Enhancement of Stochastic Resonance in distributed systems due to a selective coupling

Recent massive numerical simulations have shown that the response of a "stochastic resonator" is enhanced as a consequence of spatial coupling. Similar results have been analytically obtained in a reaction-diffusion model, using "nonequilibrium potential" techniques. We now consider a field-dependent diffusivity and show that the "selectivity" of the coupling is more efficient for achieving stochastic-resonance enhancement than its overall value in the constant-diffusivity case.Comment: 10 pgs (RevTex), 4 figures, submitted to Phys.Rev.Let

Exact expression for the diffusion propagator in a family of time-dependent anharmonic potentials

We have obtained the exact expression of the diffusion propagator in the time-dependent anharmonic potential $V(x,t)={1/2}a(t)x^2+b\ln x$. The underlying Euclidean metric of the problem allows us to obtain analytical solutions for a whole family of the elastic parameter a(t), exploiting the relation between the path integral representation of the short time propagator and the modified Bessel functions. We have also analyzed the conditions for the appearance of a non-zero flow of particles through the infinite barrier located at the origin (b<0).Comment: RevTex, 19 pgs. Accepted in Physical Review

Exploring the measurement of markedness and its relationship with other linguistic variables

Antonym pair members can be differentiated by each word's markedness-that distinction attributable to the presence or absence of features at morphological or semantic levels. Morphologically marked words incorporate their unmarked counterpart with additional morphs (e.g., "unlucky" vs. "lucky"); properties used to determine semantically marked words (e.g., "short" vs. "long") are less clearly defined. Despite extensive theoretical scrutiny, the lexical properties of markedness have received scant empirical study. The current paper employs an antonym sequencing approach to measure markedness: establishing markedness probabilities for individual words and evaluating their relationship with other lexical properties (e.g., length, frequency, valence). Regression analyses reveal that markedness probability is, as predicted, related to affixation and also strongly related to valence. Our results support the suggestion that antonym sequence is reflected in discourse, and further analysis demonstrates that markedness probabilities, derived from the antonym sequencing task, reflect the ordering of antonyms within natural language. In line with the Pollyanna Hypothesis, we argue that markedness is closely related to valence; language users demonstrate a tendency to present words evaluated positively ahead of those evaluated negatively if given the choice. Future research should consider the relationship of markedness and valence, and the influence of contextual information in determining which member of an antonym pair is marked or unmarked within discourse

Topology and Computational Performance of Attractor Neural Networks

To explore the relation between network structure and function, we studied the computational performance of Hopfield-type attractor neural nets with regular lattice, random, small-world and scale-free topologies. The random net is the most efficient for storage and retrieval of patterns by the entire network. However, in the scale-free case retrieval errors are not distributed uniformly: the portion of a pattern encoded by the subset of highly connected nodes is more robust and efficiently recognized than the rest of the pattern. The scale-free network thus achieves a very strong partial recognition. Implications for brain function and social dynamics are suggestive.Comment: 2 figures included. Submitted to Phys. Rev. Letter

Optimal interdependence between networks for the evolution of cooperation

Recent research has identified interactions between networks as crucial for the outcome of evolutionary games taking place on them. While the consensus is that interdependence does promote cooperation by means of organizational complexity and enhanced reciprocity that is out of reach on isolated networks, we here address the question just how much interdependence there should be. Intuitively, one might assume the more the better. However, we show that in fact only an intermediate density of sufficiently strong interactions between networks warrants an optimal resolution of social dilemmas. This is due to an intricate interplay between the heterogeneity that causes an asymmetric strategy flow because of the additional links between the networks, and the independent formation of cooperative patterns on each individual network. Presented results are robust to variations of the strategy updating rule, the topology of interdependent networks, and the governing social dilemma, thus suggesting a high degree of universality

Statistical mechanics of complex networks

Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical links. While traditionally these systems were modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks is governed by robust organizing principles. Here we review the recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. After reviewing the empirical data that motivated the recent interest in networks, we discuss the main models and analytical tools, covering random graphs, small-world and scale-free networks, as well as the interplay between topology and the network's robustness against failures and attacks.Comment: 54 pages, submitted to Reviews of Modern Physic