Uso de modelo de regressão aleatória na análise de produção de leite em bubalinos

Dados referentes a 1.719 controles de produção de leite de 357 fêmeas predominantemente da raça Murrah, filhas de 110 reprodutores, com partos distribuídos entre os anos de 1974 e 2004, obtidos do Programa de Melhoramento Genético de Bubalinos (PROMEBUL) com adição de registros do rebanho pertencente à EMBRAPA Amazônia Oriental - EAO, localizada em Belém, Pará. Os registros foram usados para comparar modelos de regressão aleatória na estimação de componentes de variância e predição de valores genéticos dos reprodutores utilizando a. função polinomial de Legendre, variando de segunda à quarta ordem. O modelo de regressão aleatória incluiu os efeitos de rebanho-ano, mês de parto, coeficientes de regressão para idade da fêmea (para descrever a parte fixa da curva de lactação) e coeficientes de regressão relacionados ao efeito genético direto e de ambiente permanente. A comparação entre modelos foram realizadas por meio do Critério de Informação de Akaike. O modelo de regressão aleatória que utilizou a terceira ordem de polinômio de Legendre, com quatro classes de resíduo para o ambiente temporário, foi o que melhor descreveu a variação genética aditiva da produção de leite. A herdabilidade estimada variou entre 0,08 a 0,40. A correlação genética entre produções mais próximas foram próximas da unidade, mas em idades mais distantes a correlação foi baixa. A correlação de Spearman e de Pearson entre os valores genéticos preditos em todas as situações foram próximas da unidade.

Silk fibroin biopolymer films as efficient hosts for DFB laser operation

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Multiplicity of solutions for a biharmonic equation with subcritical or critical growth

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Dimensional reduction of the massless limit of the linearized 'New Massive Gravity'

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estabilidade de sistemas dinâmicos: Estudo do memristor

Pós-graduação em Matematica Aplicada e Computacional - FCT

Técnica para dedução do modelo algébrico PTT, aplicações e análises numéricas em escoamentos bidimensionais

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

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

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

Random regression models using different functions to model milk flow in dairy cows

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

Spurious transients of projection methods in microflow simulations

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

Massive spin-2 theories in arbitrary D>= 3 dimensions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Dual descriptions of massive spin-3 particles in D=2+1 via Noether gauge embedment

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Variational and perturbative schemes for a spiked harmonic oscillator

A variational analysis of the spiked harmonic oscillator Hamiltonian operator - d2/dx2 + x2 + l(l + 1)/x2 + λ|x| -α, where α is a real positive parameter, is reported in this work. The formalism makes use of the functional space spanned by the solutions of the Schrödinger equation for the linear harmonic oscillator Hamiltonian supplemented by a Dirichlet boundary condition, and a standard procedure for diagonalizing symmetric matrices. The eigenvalues obtained by increasing the dimension of the basis set provide accurate approximations for the ground state energy of the model system, valid for positive and relatively large values of the coupling parameter λ. Additionally, a large coupling perturbative expansion is carried out and the contributions up to fourth-order to the ground state energy are explicitly evaluated. Numerical results are compared for the special case α = 5/2. © 1989 American Institute of Physics.

Existence and concentration of solutions for a class of biharmonic equations

Some superlinear fourth order elliptic equations are considered. A family of solutions is proved to exist and to concentrate at a point in the limit. The proof relies on variational methods and makes use of a weak version of the Ambrosetti-Rabinowitz condition. The existence and concentration of solutions are related to a suitable truncated equation. (C) 2012 Elsevier Inc. All rights reserved.

New Optimization Algorithms for Structural Reliability Analysis

Solution of structural reliability problems by the First Order method require optimization algorithms to find the smallest distance between a limit state function and the origin of standard Gaussian space. The Hassofer-Lind-Rackwitz-Fiessler (HLRF) algorithm, developed specifically for this purpose, has been shown to be efficient but not robust, as it fails to converge for a significant number of problems. On the other hand, recent developments in general (augmented Lagrangian) optimization techniques have not been tested in aplication to structural reliability problems. In the present article, three new optimization algorithms for structural reliability analysis are presented. One algorithm is based on the HLRF, but uses a new differentiable merit function with Wolfe conditions to select step length in linear search. It is shown in the article that, under certain assumptions, the proposed algorithm generates a sequence that converges to the local minimizer of the problem. Two new augmented Lagrangian methods are also presented, which use quadratic penalties to solve nonlinear problems with equality constraints. Performance and robustness of the new algorithms is compared to the classic augmented Lagrangian method, to HLRF and to the improved HLRF (iHLRF) algorithms, in the solution of 25 benchmark problems from the literature. The new proposed HLRF algorithm is shown to be more robust than HLRF or iHLRF, and as efficient as the iHLRF algorithm. The two augmented Lagrangian methods proposed herein are shown to be more robust and more efficient than the classical augmented Lagrangian method.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.