415 research outputs found

    Two-dimensional SIR epidemics with long range infection

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    We extend a recent study of susceptible-infected-removed epidemic processes with long range infection (referred to as I in the following) from 1-dimensional lattices to lattices in two dimensions. As in I we use hashing to simulate very large lattices for which finite size effects can be neglected, in spite of the assumed power law p(x)xσ2p({\bf x})\sim |{\bf x}|^{-\sigma-2} for the probability that a site can infect another site a distance vector x{\bf x} apart. As in I we present detailed results for the critical case, for the supercritical case with σ=2\sigma = 2, and for the supercritical case with 0<σ<20< \sigma < 2. For the latter we verify the stretched exponential growth of the infected cluster with time predicted by M. Biskup. For σ=2\sigma=2 we find generic power laws with σ\sigma-dependent exponents in the supercritical phase, but no Kosterlitz-Thouless (KT) like critical point as in 1-d. Instead of diverging exponentially with the distance from the critical point, the correlation length increases with an inverse power, as in an ordinary critical point. Finally we study the dependence of the critical exponents on σ\sigma in the regime 0<σ<20<\sigma <2, and compare with field theoretic predictions. In particular we discuss in detail whether the critical behavior for σ\sigma slightly less than 2 is in the short range universality class, as conjectured recently by F. Linder {\it et al.}. As in I we also consider a modified version of the model where only some of the contacts are long range, the others being between nearest neighbors. If the number of the latter reaches the percolation threshold, the critical behavior is changed but the supercritical behavior stays qualitatively the same.Comment: 14 pages, including 29 figure

    Positive words carry less information than negative words

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    We show that the frequency of word use is not only determined by the word length \cite{Zipf1935} and the average information content \cite{Piantadosi2011}, but also by its emotional content. We have analyzed three established lexica of affective word usage in English, German, and Spanish, to verify that these lexica have a neutral, unbiased, emotional content. Taking into account the frequency of word usage, we find that words with a positive emotional content are more frequently used. This lends support to Pollyanna hypothesis \cite{Boucher1969} that there should be a positive bias in human expression. We also find that negative words contain more information than positive words, as the informativeness of a word increases uniformly with its valence decrease. Our findings support earlier conjectures about (i) the relation between word frequency and information content, and (ii) the impact of positive emotions on communication and social links.Comment: 16 pages, 3 figures, 3 table

    Fatal outcome of a hypersensitivity reaction to paclitaxel: a critical review of premedication regimens

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    Hypersensitivity reactions (HSRs) to paclitaxel are frequently encountered in patients receiving this antitumour drug. Administration of histamine H1- and H2-receptor antagonists and corticosteroids has been shown to reduce significantly the risk of developing an HSR in patients receiving taxanes. In this case report, we describe the fatal outcome of an HSR in a patient receiving paclitaxel despite short-course premedication. The level of evidence supporting the short-course i.v. premedication schedule is challenged, as it is not compatible with the pharmacokinetic properties of dexamethasone

    A Random Matrix Approach to Language Acquisition

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    Since language is tied to cognition, we expect the linguistic structures to reflect patterns we encounter in nature and analyzed by physics. Within this realm we investigate the process of protolanguage acquisition, using analytical and tractable methods developed within physics. A protolanguage is a mapping between sounds and objects (or concepts) of the perceived world. This mapping is represented by a matrix and the linguistic interaction among individuals is described by a random matrix model. There are two essential parameters in our approach. The strength of the linguistic interaction β\beta, which following Chomsky's tradition, we consider as a genetically determined ability, and the number NN of employed sounds (the lexicon size). Our model of linguistic interaction is analytically studied using methods of statistical physics and simulated by Monte Carlo techniques. The analysis reveals an intricate relationship between the innate propensity for language acquisition β\beta and the lexicon size NN, Nexp(β)N \sim \exp(\beta). Thus a small increase of the genetically determined β\beta may lead to an incredible lexical explosion. Our approximate scheme offers an explanation for the biological affinity of different species and their simultaneous linguistic disparity.Comment: 16 pages, 4 figures. Submitted to JSTA

    Combination antiretroviral therapy and the risk of myocardial infarction

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