964 resultados para Time correlation function


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Background: Rift Valley fever (RVF) is a zoonotic arbovirosis for which the primary hosts are domestic livestock (cattle, sheep and goats). RVF was first described in South Africa in 1950-1951. Mechanisms for short and long distance transmission have been hypothesised, but there is little supporting evidence. Here we describe RVF occurrence and spatial distribution in South Africa in 2008-11, and investigate the presence of a contagious process in order to generate hypotheses on the different mechanisms of transmission. Methodology/Principal Findings: A total of 658 cases were extracted from World Animal Health Information Database. Descriptive statistics, epidemic curves and maps were produced. The space-time K-function was used to test for evidence of space-time interaction. Five RVF outbreak waves (one in 2008, two in 2009, one in 2010 and one in 2011) of varying duration, location and size were reported. About 70% of cases (n = 471) occurred in 2010, when the epidemic was almost country-wide. No strong evidence of space-time interaction was found for 2008 or the second wave in 2009. In the first wave of 2009, a significant space-time interaction was detected for up to one month and over 40 km. In 2010 and 2011 a significant intense, short and localised space-time interaction (up to 3 days and 15 km) was detected, followed by one of lower intensity (up to 2 weeks and 35 to 90 km). Conclusions/Significance: The description of the spatiotemporal patterns of RVF in South Africa between 2008 and 2011 supports the hypothesis that during an epidemic, disease spread may be supported by factors other than active vector dispersal. Limitations of under-reporting and space-time K-function properties are discussed. Further spatial analyses and data are required to explain factors and mechanisms driving RVF spread. © 2012 Métras et al.

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Tese de doutoramento, Ciências Geofísicas e da Geoinformação (Geofisíca), Universidade de Lisboa, Faculdade de Ciências, 2014

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This paper presents a new paradigm for signal reconstruction and superresolution, Correlation Kernel Analysis (CKA), that is based on the selection of a sparse set of bases from a large dictionary of class- specific basis functions. The basis functions that we use are the correlation functions of the class of signals we are analyzing. To choose the appropriate features from this large dictionary, we use Support Vector Machine (SVM) regression and compare this to traditional Principal Component Analysis (PCA) for the tasks of signal reconstruction, superresolution, and compression. The testbed we use in this paper is a set of images of pedestrians. This paper also presents results of experiments in which we use a dictionary of multiscale basis functions and then use Basis Pursuit De-Noising to obtain a sparse, multiscale approximation of a signal. The results are analyzed and we conclude that 1) when used with a sparse representation technique, the correlation function is an effective kernel for image reconstruction and superresolution, 2) for image compression, PCA and SVM have different tradeoffs, depending on the particular metric that is used to evaluate the results, 3) in sparse representation techniques, L_1 is not a good proxy for the true measure of sparsity, L_0, and 4) the L_epsilon norm may be a better error metric for image reconstruction and compression than the L_2 norm, though the exact psychophysical metric should take into account high order structure in images.

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We present molecular dynamics (MD) and slip-springs model simulations of the chain segmental dynamics in entangled linear polymer melts. The time-dependent behavior of the segmental orientation autocorrelation functions and mean-square segmental displacements are analyzed for both flexible and semiflexible chains, with particular attention paid to the scaling relations among these dynamic quantities. Effective combination of the two simulation methods at different coarse-graining levels allows us to explore the chain dynamics for chain lengths ranging from Z ≈ 2 to 90 entanglements. For a given chain length of Z ≈ 15, the time scales accessed span for more than 10 decades, covering all of the interesting relaxation regimes. The obtained time dependence of the monomer mean square displacements, g1(t), is in good agreement with the tube theory predictions. Results on the first- and second-order segmental orientation autocorrelation functions, C1(t) and C2(t), demonstrate a clear power law relationship of C2(t) C1(t)m with m = 3, 2, and 1 in the initial, free Rouse, and entangled (constrained Rouse) regimes, respectively. The return-to-origin hypothesis, which leads to inverse proportionality between the segmental orientation autocorrelation functions and g1(t) in the entangled regime, is convincingly verified by the simulation result of C1(t) g1(t)−1 t–1/4 in the constrained Rouse regime, where for well-entangled chains both C1(t) and g1(t) are rather insensitive to the constraint release effects. However, the second-order correlation function, C2(t), shows much stronger sensitivity to the constraint release effects and experiences a protracted crossover from the free Rouse to entangled regime. This crossover region extends for at least one decade in time longer than that of C1(t). The predicted time scaling behavior of C2(t) t–1/4 is observed in slip-springs simulations only at chain length of 90 entanglements, whereas shorter chains show higher scaling exponents. The reported simulation work can be applied to understand the observations of the NMR experiments.

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The concept of Fock space representation is developed to deal with stochastic spin lattices written in terms of fermion operators. A density operator is introduced in order to follow in parallel the developments of the case of bosons in the literature. Some general conceptual quantities for spin lattices are then derived, including the notion of generating function and path integral via Grassmann variables. The formalism is used to derive the Liouvillian of the d-dimensional Linear Glauber dynamics in the Fock-space representation. Then the time evolution equations for the magnetization and the two-point correlation function are derived in terms of the number operator. (C) 2008 Elsevier B.V. All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Gels consist of soft materials with vast use in several activities, such as in pharmaceutical industry, food science, and coatings/textile applications. In order to obtain these materials, the process of gelification, that can be physical (based on physical interactions) and/or chemical (based on covalent crosslinking), has to be carried out. In this work we used dynamic light scattering (DLS) and rheometry to monitor the covalent gelification of chitosan solutions by glutaraldehyde. Intensity correlation function (ICF) data was obtained from DLS and the exponential stretched Kohrausch-William-Watts function (KWW) was fitted to them. The parameters of the KWW equation, β, Γ and C were evaluated. These methods were effective in clarifying the process of sol-gel transition, with the emergence of non-ergodicity, and determining the range of gelation observed in about 10-20 minutes. The dependence between apparent viscosity on reaction time was used to support the discussion proposed.

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We present model results for the two-halo-neutron correlation functions, C-nn, for the dissociation process of light exotic nuclei modelled as two neutrons and a core. A minimum is predicted for C-nn as a function of the relative momentum of the two neutrons, p(nn), due to the coherence of the neutrons in the halo and final state interaction. Studying the systems Be-14, Li-11, and He-6 within this model, we show that the numerical asymptotic limit, C-nn-> 1, occurs only for p(nn)greater than or similar to 400 MeV/c, while such limit is reached for much lower values of p(nn) in an independent particle model as the one used in the analysis of recent experimental data. Our model is consistent with data once the experimental correlation function is appropriately normalized.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The structural evolution in silica sols prepared from tetraethoxysilane (TEOS) sonohydrolysis was studied 'in situ' using small-angle x-ray scattering (SAXS). The structure of the gelling system can be reasonably well described by a correlation function given by gamma(r) similar to (1/R(2))(1/r) exp(- r/xi), where xi is the structure correlation length and R is a chain persistence length, as an analogy to the Ornstein-Zernike theory in describing critical phenomenon. This approach is also expected for the scattering from some linear and branched molecules as polydisperse coils of linear chains and random f-functional branched polycondensates. The characteristic length. grows following an approximate power law with time t as xi similar to t(1) (with the exponent quite close to 1) while R remains undetermined but with a constant value, except at the beginning of the process in which the growth of. is slower and R increases by only about 15% with respect to the value of the initial sol. The structural evolution with time is compatible with an aggregation process by a phase separation by coarsening. The mechanism of growth seems to be faster than those typically observed for pure diffusion controlled cluster-cluster aggregation. This suggests that physical forces (hydrothermal forces) could be actuating together with diffusion in the gelling process of this system. The data apparently do not support a spinodal decomposition mechanism, at least when starting from the initial stable acid sol studied here.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Small-angle X-ray scattering (SAXS) and nitrogen adsorption techniques were used to study the temperature and time structural evolution of the nanoporosity in silica xerogels prepared from acid- and ultrasound-catalyzed hydrolysis of tetraetboxysilane (TEOS). Silica xerogels present a structure of nanopores of fully random shape, size, and distribution, which can be described by an exponential correlation function gamma(r) = exp (-r/a), where a is the correlation distance, as predicted by the Debye, Anderson, and Brumberger (DAB) model. The mean pore size was evaluated as about 1.25 nm from SAXS and about 1.9 nm from nitrogen adsorption. The nanopore elimination in TEOS sonohydrolysis-derived silica xerogels is readily accelerated at temperatures around 900 degrees C probably by the action of a viscous flow mechanism. The nanopore elimination process takes place in such a way that the pore volume fraction and the specific surface are reduced while the mean pore size remains constant. (c) 2005 WILEY-VCH Verlag GmbH S Co. KGaA, Weinheim.

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The electromagnetic tensor for inclusive electron scattering off the pion Wμν for momentum transfers such that q+ = 0, (q+ = q0 + q3) is shown to obey a sum-rule for the component W++. From this sum-rule, one can define the quark-antiquark correlation function in the pion, which characterizes the transverse distance distribution between the quark and antiquark in the light-front pion wave-function. Within the realistic models of the relativistic pion wave function (including instanton vacuum inspired wave function) it is shown that the value of the two-quark correlation radius (rqq̄) is near twice the pion electromagnetic radius (rπ), where rπ ≈ 2/3 fm. We also define the correlation length lcorr where the two-particle correlation have an extremum. The estimation of lcorr ≈ 0.3-0,5 fm is very close to estimations from instanton models of QCD vacuum. It is also shown that the above correlation is very sensitive to the pion light-front wave-function models. © 1997 Elsevier Science B.V.

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A total of 20,065 weights recorded on 3016 Nelore animals were used to estimate covariance functions for growth from birth to 630 days of age, assuming a parametric correlation structure to model within-animal correlations. The model of analysis included fixed effects of contemporary groups and age of dam as quadratic covariable. Mean trends were taken into account by a cubic regression on orthogonal polynomials of animal age. Genetic effects of the animal and its dam and maternal permanent environmental effects were modelled by random regressions on Legendre polynomials of age at recording. Changes in direct permanent environmental effect variances were modelled by a polynomial variance function, together with a parametric correlation function to account for correlations between ages. Stationary and nonstationary models were used to model within-animal correlations between different ages. Residual variances were considered homogeneous or heterogeneous, with changes modelled by a step or polynomial function of age at recording. Based on Bayesian information criterion, a model with a cubic variance function combined with a nonstationary correlation function for permanent environmental effects, with 49 parameters to be estimated, fitted best. Modelling within-animal correlations through a parametric correlation structure can describe the variation pattern adequately. Moreover, the number of parameters to be estimated can be decreased substantially compared to a model fitting random regression on Legendre polynomial of age. © 2004 Elsevier B.V. All rights reserved.

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This paper discusses two pitch detection algorithms (PDA) for simple audio signals which are based on zero-cross rate (ZCR) and autocorrelation function (ACF). As it is well known, pitch detection methods based on ZCR and ACF are widely used in signal processing. This work shows some features and problems in using these methods, as well as some improvements developed to increase their performance. © 2008 IEEE.