4 resultados para Spatial Durbin model

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Voluntary physical activity improves memory and learning ability in rodents, whereas status epilepticus has been associated with memory impairment. Physical activity and seizures have been associated with enhanced hippocampal expression of BDNF, indicating that this protein may have a dual role in epilepsy. The influence of voluntary physical activity on memory and BDNF expression has been poorly studied in experimental models of epilepsy. In this paper, we have investigated the effect of voluntary physical activity on memory and BDNF expression in mice with pilocarpine-incluced epilepsy. Male Swiss mice were assigned to four experimental groups: pilocarpine sedentary (PS), pilocarpine runners (PRs), saline sedentary (SS) and saline runners (SRs). Two days after pilocarpine-induced status epilepticus, the affected mice (PR) and their running controls (SR) were housed with access to a running wheel for 28 days. After that, the spatial memory and the expression of the precursor and mature forms of hippocampal BDNF were assessed. PR mice performed better than PS mice in the water maze test. In addition, PR mice had a higher amount of mature BDNF (14 kDa) relative to the total BDNF (14 kDa + 28 kDa + 32 kDa forms) content when compared with PS mice. These results show that voluntary physical activity improved the spatial memory and increased the hippocampal content of mature BDNF of mice with pilocarpine-induced status epilepticus. (C) 2009 Elsevier B.V. All rights reserved.

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The transition to turbulence (spatio-temporal chaos) in a wide class of spatially extended dynamical system is due to the loss of transversal stability of a chaotic attractor lying on a homogeneous manifold (in the Fourier phase space of the system) causing spatial mode excitation Since the latter manifests as intermittent spikes this has been called a bubbling transition We present numerical evidences that this transition occurs due to the so called blowout bifurcation whereby the attractor as a whole loses transversal stability and becomes a chaotic saddle We used a nonlinear three-wave interacting model with spatial diffusion as an example of this transition (C) 2010 Elsevier B V All rights reserved

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[1] The retrieval of aerosol optical depth (Ta) over land by satellite remote sensing is still a challenge when a high spatial resolution is required. This study presents a tool that uses satellite measurements to dynamically identify the aerosol optical model that best represents the optical properties of the aerosol present in the atmosphere. We use aerosol critical reflectance to identify the single scattering albedo of the aerosol layer. Two case studies show that the Sao Paulo region can have different aerosol properties and demonstrates how the dynamic methodology works to identify those differences to obtain a better T a retrieval. The methodology assigned the high single scattering albedo aerosol model (pi o( lambda = 0.55) = 0.90) to the case where the aerosol source was dominated by biomass burning and the lower pi(o) model (pi(o) (lambda = 0.55) = 0.85) to the case where the local urban aerosol had the dominant influence on the region, as expected. The dynamic methodology was applied using cloud-free data from 2002 to 2005 in order to retrieve Ta with Moderate Resolution Imaging Spectroradiometer ( MODIS). These results were compared with collocated data measured by AERONET in Sao Paulo. The comparison shows better results when the dynamic methodology using two aerosol optical models is applied (slope 1.06 +/- 0.08 offset 0.01 +/- 0.02 r(2) 0.6) than when a single and fixed aerosol model is used (slope 1.48 +/- 0.11 and offset - 0.03 +/- 0.03 r(2) 0.6). In conclusion the dynamical methodology is shown to work well with two aerosol models. Further studies are necessary to evaluate the methodology in other regions and under different conditions.

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We study a stochastic process describing the onset of spreading dynamics of an epidemic in a population composed of individuals of three classes: susceptible (S), infected (I), and recovered (R). The stochastic process is defined by local rules and involves the following cyclic process: S -> I -> R -> S (SIRS). The open process S -> I -> R (SIR) is studied as a particular case of the SIRS process. The epidemic process is analyzed at different levels of description: by a stochastic lattice gas model and by a birth and death process. By means of Monte Carlo simulations and dynamical mean-field approximations we show that the SIRS stochastic lattice gas model exhibit a line of critical points separating the two phases: an absorbing phase where the lattice is completely full of S individuals and an active phase where S, I and R individuals coexist, which may or may not present population cycles. The critical line, that corresponds to the onset of epidemic spreading, is shown to belong in the directed percolation universality class. By considering the birth and death process we analyze the role of noise in stabilizing the oscillations. (C) 2009 Elsevier B.V. All rights reserved.