975 resultados para Mean-field model
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Brazil is a major world producer and exporter of agricultural products like soybeans, sugar, coffee, orange and tobacoo. However, the action of phytopathogenic fungi has been one of the largest challenges encountered in the field as they are responsible for approximately 25 to 50 per cent of losses in crops of fruits and vegetables. The presence of these pathogens is always a problem, because the damage on the tissues and organs promote lesions which decreses growth vegetation and often leads the individual (host) to death. Therefore, it is crucial to understand the process of spreading of these pathogens in the field to develop strategies which prevent the epidemics caused by them. In this study, the dispersal of fungi phytopathogenic in the field was modeled using the automata cellular formalism. The growth rate of infected plants population was measured by the radius of gyration and the influence of host different susceptibility degrees into the disease spread was assessed. The spatial anisotropy related to the plant-to-plant space and the system’s response to distinct seasonal patterns were also evaluated. The results obtained by a mean field model (spatially implicit models) emphasized the importance of the spatial structure on the spreading process, and dispersal patterns obtained by simulation (using a cellular automata) were in agreement with thse observed in data. All computational implementation was held in language Cl
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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For the first time in metallic glasses, we extract both the exponents and scaling functions that describe the nature, statistics, and dynamics of slip events during slow deformation, according to a simple mean field model. We model the slips as avalanches of rearrangements of atoms in coupled shear transformation zones (STZs). Using high temporal resolution measurements, we find the predicted, different statistics and dynamics for small and large slips thereby excluding self-organized criticality. The agreement between model and data across numerous independent measures provides evidence for slip avalanches of STZs as the elementary mechanism of inhomogeneous deformation in metallic glasses.
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We present a mean field model for spin glasses with a natural notion of distance built in, namely, the Edwards-Anderson model on the diluted D-dimensional unit hypercube in the limit of large D. We show that finite D effects are strongly dependent on the connectivity, being much smaller for a fixed coordination number. We solve the nontrivial problem of generating these lattices. Afterward, we numerically study the nonequilibrium dynamics of the mean field spin glass. Our three main findings are the following: i the dynamics is ruled by an infinite number of time sectors, ii the aging dynamics consists of the growth of coherent domains with a nonvanishing surface-volume ratio, and iii the propagator in Fourier space follows the p4 law. We study as well the finite D effects in the nonequilibrium dynamics, finding that a naive finite size scaling ansatz works surprisingly well.
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We present a mean-field model of cloud evolution that describes droplet growth due to condensation and collisions and droplet loss due to fallout. The model accounts for the effects of cloud turbulence both in a large-scale turbulent mixing and in a microphysical enhancement of condensation and collisions. The model allows for an effective numerical simulation by a scheme that is conservative in water mass and keeps accurate count of the number of droplets. We first study the homogeneous situation and determine how the rain-initiation time depends on the concentration of cloud condensation nuclei (CCN) and turbulence level. We then consider clouds with an inhomogeneous concentration of CCN and evaluate how the rain initiation time and the effective optical depth vary in space and time. We argue that over-seeding even a part of a cloud by small hygroscopic nuclei, one can substantially delay the onset and increase the amount of precipitation.
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We present the results of electrical resistivity, magnetic susceptibility, specific heat and x-ray absorption spectroscopy measurements in Tb1−xYxRhIn5 (x = 0.00, 0.15, 0.4.0, 0.50 e 0.70) single crystals. Tb1−xYxRhIn5 is an antiferromagnetic AFM compound with ordering temperature TN ≈ 46 K, the higher TN within the RRhIn5 serie (R : rare earth). We evaluate the physical properties evolution and the supression of the AFM state considering doping and Crystalline Electric Field (CEF) effects on magnetic exchange interaction between Tb3+ magnetic ions. CEF acts like a perturbation potential, breaking the (2J + 1) multiplet s degeneracy. Also, we studied linear-polarization-dependent soft x-ray absorption at Tb M4 and M5 edges to validate X-ray Absorption Spectroscopy as a complementary technique in determining the rare earth CEF ground state. Samples were grown by the indium excess flux and the experimental data (magnetic susceptibility and specific heat) were adjusted with a mean field model that takes account magnetic exchange interaction between first neighbors and CEF effects. XAS experiments were carried on Total Electron Yield mode at Laborat´onio Nacional de Luz S´ıncrotron, Campinas. We measured X-ray absorption at Tb M4,5 edges with incident polarized X-ray beam parallel and perpendicular to c-axis (E || c e E ⊥ c). The mean field model simulates the mean behavior of the whole system and, due to many independent parameters, gives a non unique CEF scheme. XAS is site- and elemental- specific technique and gained the scientific community s attention as complementary technique in determining CEF ground state in rare earth based compounds. In this work we wil discuss the non conclusive results of XAS technique in TbRhIn5 compounds.
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Tese (doutorado)Universidade de Brasília, Instituto de Física, Programa de Pós-Graduação em Física, 2015.
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We investigate the influence of the driving mechanism on the hysteretic response of systems with athermal dynamics. In the framework of local mean-field theory at finite temperature (but neglecting thermally activated processes), we compare the rate-independent hysteresis loops obtained in the random field Ising model when controlling either the external magnetic field H or the extensive magnetization M. Two distinct behaviors are observed, depending on disorder strength. At large disorder, the H-driven and M-driven protocols yield identical hysteresis loops in the thermodynamic limit. At low disorder, when the H-driven magnetization curve is discontinuous (due to the presence of a macroscopic avalanche), the M-driven loop is reentrant while the induced field exhibits strong intermittent fluctuations and is only weakly self-averaging. The relevance of these results to the experimental observations in ferromagnetic materials, shape memory alloys, and other disordered systems is discussed.
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We investigate the influence of the driving mechanism on the hysteretic response of systems with athermal dynamics. In the framework of local mean-field theory at finite temperature (but neglecting thermally activated processes), we compare the rate-independent hysteresis loops obtained in the random field Ising model when controlling either the external magnetic field H or the extensive magnetization M. Two distinct behaviors are observed, depending on disorder strength. At large disorder, the H-driven and M-driven protocols yield identical hysteresis loops in the thermodynamic limit. At low disorder, when the H-driven magnetization curve is discontinuous (due to the presence of a macroscopic avalanche), the M-driven loop is reentrant while the induced field exhibits strong intermittent fluctuations and is only weakly self-averaging. The relevance of these results to the experimental observations in ferromagnetic materials, shape memory alloys, and other disordered systems is discussed.
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Geostrophic surface velocities can be derived from the gradients of the mean dynamic topography-the difference between the mean sea surface and the geoid. Therefore, independently observed mean dynamic topography data are valuable input parameters and constraints for ocean circulation models. For a successful fit to observational dynamic topography data, not only the mean dynamic topography on the particular ocean model grid is required, but also information about its inverse covariance matrix. The calculation of the mean dynamic topography from satellite-based gravity field models and altimetric sea surface height measurements, however, is not straightforward. For this purpose, we previously developed an integrated approach to combining these two different observation groups in a consistent way without using the common filter approaches (Becker et al. in J Geodyn 59(60):99-110, 2012, doi:10.1016/j.jog.2011.07.0069; Becker in Konsistente Kombination von Schwerefeld, Altimetrie und hydrographischen Daten zur Modellierung der dynamischen Ozeantopographie, 2012, http://nbn-resolving.de/nbn:de:hbz:5n-29199). Within this combination method, the full spectral range of the observations is considered. Further, it allows the direct determination of the normal equations (i.e., the inverse of the error covariance matrix) of the mean dynamic topography on arbitrary grids, which is one of the requirements for ocean data assimilation. In this paper, we report progress through selection and improved processing of altimetric data sets. We focus on the preprocessing steps of along-track altimetry data from Jason-1 and Envisat to obtain a mean sea surface profile. During this procedure, a rigorous variance propagation is accomplished, so that, for the first time, the full covariance matrix of the mean sea surface is available. The combination of the mean profile and a combined GRACE/GOCE gravity field model yields a mean dynamic topography model for the North Atlantic Ocean that is characterized by a defined set of assumptions. We show that including the geodetically derived mean dynamic topography with the full error structure in a 3D stationary inverse ocean model improves modeled oceanographic features over previous estimates.
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This report outlines the derivation and application of a non-zero mean, polynomial-exponential covariance function based Gaussian process which forms the prior wind field model used in 'autonomous' disambiguation. It is principally used since the non-zero mean permits the computation of realistic local wind vector prior probabilities which are required when applying the scaled-likelihood trick, as the marginals of the full wind field prior. As the full prior is multi-variate normal, these marginals are very simple to compute.
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We have the purpose of analyzing the effect of explicit diffusion processes in a predator-prey stochastic lattice model. More precisely we wish to investigate the possible effects due to diffusion upon the thresholds of coexistence of species, i. e., the possible changes in the transition between the active state and the absorbing state devoid of predators. To accomplish this task we have performed time dependent simulations and dynamic mean-field approximations. Our results indicate that the diffusive process can enhance the species coexistence.