981 resultados para Third-order model
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The current work was developed on the dune systems of the Parque das Dunas and Barreira do Inferno. These places are located in the cities of Natal and Parnamirim (RN, Brazil), respectively. This project has the purpose of developing the deterministic model on a specific blowout at Parque das Dunas, based in the geophysical interpretations of the lines gotten with the Ground Penetration Radar and the planialtimetric acquisitions of the topographical surface of the land. Also analyses of the vulnerability/susceptibility of these dune systems had been done in relation to the human pressures. To develop its deterministic model, it is necessary to acquire inner and outer geometries of the cited blowout. In order to depict inner geometries underneath the surface are used the GPR observing the altimetric control for topographical correction of the GPR lines. As for the outer geometries, the geodesic GPS gives us the planialtimetric points (x, y and z points) with milimetric precision, resulting in high-resolution surfaces. Using interpolation methods of the planialtimetric points was possible create Digital Elevations Models (DEM´s) of these surfaces. As a result, 1,161.4 meters of GPR lines were acquired on the blowout at the Parque das Dunas and 3,735.27 meters on the blowout at the Barreira do Inferno. These lines had been acquired with a 200 MHz antenna, except the 7 and 8 lines, for which we had been used a 100 MHz antenna. The gotten data had been processed and interpreted, being possible to identify boundary surfaces of first, second and third order. The first order boundary surface is related with the contact of the rocks of the Barreiras Group with the aeolian deposits. These deposits had been divided in two groups (Group 1 and Group 2) which are related with the geometry of stratum and the dip of its stratifications. Group 1 presented stratum of sigmoidal and irregular geometries and involved bodies where the reflectors had presented dips that had varied of 20 to the 28 degrees for the Parque das Dunas blowout and of 22 to the 29 degrees for the Barreira do Inferno blowout. Usually, it was limited in the base for the first order surface and in the top for the second order surface. Group 2 presented stratum of trough, wedge or lens geometries, limited in the base for the second order vi surface, where the corresponding deposits had more shown smoothed reflectors or with dips of low angle. The Deterministic and Digital Elevation Models had been developed from the integration and interpretation of the 2D data with the GOCAD® program. In Digital Elevations Models it was possible to see, for the localities, corridor or trough-shaped blowouts. In Deterministic Model it was possible to see first and second order boundary surfaces. For the vulnerability/susceptibility of the dune systems it was applied the methodology proposal by Boderè al (1991); however the same one did not show adequate because it evaluates actual coastal dunes. Actual coastal dunes are dunes that are presented in balance with the current environmental conditions. Therefore, a new methodology was proposal which characterizes the supplying and activity sedimentary, as well as the human pressures. For the methodology developed in this work, both the localities had presented a good management. The Parque das Dunas was characterized as a relic dune system and the Barreira do Inferno was characterized as a palimpsestic dune system. Also two Thematic Maps had been elaborated for the environmental characterization of the studied dune systems, with software ArcGis 8.3, and its respective data bases
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Objetivou-se comparar modelos de regressão aleatória com diferentes estruturas de variância residual, a fim de se buscar a melhor modelagem para a característica tamanho da leitegada ao nascer (TLN). Utilizaram-se 1.701 registros de TLN, que foram analisados por meio de modelo animal, unicaracterística, de regressão aleatória. As regressões fixa e aleatórias foram representadas por funções contínuas sobre a ordem de parto, ajustadas por polinômios ortogonais de Legendre de ordem 3. Para averiguar a melhor modelagem para a variância residual, considerou-se a heterogeneidade de variância por meio de 1 a 7 classes de variância residual. O modelo geral de análise incluiu grupo de contemporâneo como efeito fixo; os coeficientes de regressão fixa para modelar a trajetória média da população; os coeficientes de regressão aleatória do efeito genético aditivo-direto, do comum-de-leitegada e do de ambiente permanente de animal; e o efeito aleatório residual. O teste da razão de verossimilhança, o critério de informação de Akaike e o critério de informação bayesiano de Schwarz apontaram o modelo que considerou homogeneidade de variância como o que proporcionou melhor ajuste aos dados utilizados. As herdabilidades obtidas foram próximas a zero (0,002 a 0,006). O efeito de ambiente permanente foi crescente da 1ª (0,06) à 5ª (0,28) ordem, mas decrescente desse ponto até a 7ª ordem (0,18). O comum-de-leitegada apresentou valores baixos (0,01 a 0,02). A utilização de homogeneidade de variância residual foi mais adequada para modelar as variâncias associadas à característica tamanho da leitegada ao nascer nesse conjunto de dado.
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Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed), daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genetic de Bubalinos (PROMEBUL) and from records of EMBRAPA Amazonia Oriental - EAO herd, located in Belem, Para, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre's polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve) and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre's polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.
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Fractal dimensions of grain boundary region in doped SnO2 ceramics were determined based on previously derived fractal model. This model considers fractal dimension as a measure of homogeneity of distribution of charge carriers. Application of the derived fractal model enables calculation of fractal dimension using results of impedance spectroscopy. The model was verified by experimentally determined temperature dependence of the fractal dimension of SnO2 ceramics. Obtained results confirm that the non-Debye response of the grain boundary region is connected with distribution of defects and consequently with a homogeneity of a distribution of the charge carriers. Also, it was found that C-T-1 function has maximum at temperature at which the change in dominant type of defects takes place. This effect could be considered as a third-order transition.
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Starting from a decomposition of the self-dual field in (2 + 1) dimensions, we build up an alternative quantum theory which consists of a self-dual model coupled to a Maxwell-generalized Chern-Simons theory. We discuss the fermion-boson equivalence of this quantum theory by comparing it with the Thirring model. Using these results we were able to compute the mass of the bosonized fermions up to third order in 1/m. Some problems related to the number of poles of the effective propagator are also addressed.
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We study a model for dynamical localization of topology using ideas from non-commutative geometry and topology in quantum mechanics. We consider a collection X of N one-dimensional manifolds and the corresponding set of boundary conditions (self-adjoint extensions) of the Dirac operator D. The set of boundary conditions encodes the topology and is parameterized by unitary matrices g. A particular geometry is described by a spectral triple x(g) = (A X, script H sign X, D(g)). We define a partition function for the sum over all g. In this model topology fluctuates but the dimension is kept fixed. We use the spectral principle to obtain an action for the set of boundary conditions. Together with invariance principles the procedure fixes the partition function for fluctuating topologies. The model has one free-parameter β and it is equivalent to a one plaquette gauge theory. We argue that topology becomes localized at β = ∞ for any value of N. Moreover, the system undergoes a third-order phase transition at β = 1 for large-N. We give a topological interpretation of the phase transition by looking how it affects the topology. © SISSA/ISAS 2004.
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Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data. © FUNPEC-RP.
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The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil. ©FUNPEC-RP.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Ciências Cartográficas - FCT
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)