Principal components and factor analytic models for birth to mature weights in Nellore cattle

A total of 61,528 weight records from 22,246 Nellore animals born between 1984 and 2002 were used to compare different multiple-trait analysis methods for birth to mature weights. The following models were used: standard multivarite model (MV), five reduced-rank models fitting the first 1, 2, 3, 4 and 5 genetic principal components, and five models using factor analysis with 1, 2, 3, 4 and 5 factors. Direct additive genetic random effects and residual effects were included in all models. In addition, maternal genetic and maternal permanent environmental effects were included as random effects for birth and weaning weight. The models included contemporary group as fixed effect and age of animal at recording (except for birth weight) and age of dam at calving as linear and quadratic effects (for birth weight and weaning weight). The maternal genetic, maternal permanent environmental and residual (co)variance matrices were assumed to be full rank. According to model selection criteria, the model fitting the three first principal components (PC3) provided the best fit, without the need for factor analysis models. Similar estimates of phenotypic, direct additive and maternal genetic, maternal permanent environmental and residual (co)variances were obtained with models MV and PC3. Direct heritability ranged from 0.21 (birth weight) to 0.45 (weight at 6 years of age). The genetic and phenotypic correlations obtained with model PC3 were slightly higher than those estimated with model MV. In general, the reduced-rank model substantially decreased the number of parameters in the analyses without reducing the goodness-of-fit. © 2013 Elsevier B.V.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

Estimates of genetic parameters and eigenvector indices for milk production of Holstein cows

The objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated. © 2013 American Dairy Science Association.

Lead-germanate glasses and fibers: A practical alternative to tellurite for nonlinear fiber applications

We report on the fabrication of novel lead-germanate glasses and fibers. We have characterized these glasses in terms of their thermal properties, Raman spectra and refractive indices (both linear and nonlinear) and present them as viable alternatives to tellurite glasses for applications requiring highly nonlinear optical fibers. © 2013 Optical Society of America.

Modelo de programação matemática para controle do crescimento da vegetação sob redes de distribuição de energia elétrica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Método previsor-corretor primal-dual de pontos interiores em problemas multiobjetivo de despacho econômico e ambiental

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Planejamento e projeto de circuitos secundários de distribuição de energia elétrica por meio de algoritmo busca tabu

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Alocação otimizada de dispositivos de proteção em sistema de distribuição de energia elétrica

Pós-graduação em Engenharia Elétrica - FEIS

Análise não-linear física de vigas de concreto armado utilizando o elemento finito prismático regular linear associado ao de barra

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Um estudo da dependência do índice de refração linear com a composição dos vidros teluretos dos sistemas TeO2-Li2O-TiO2 e TeO2-Li2O-WO3

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Wage share and economic growth in Latin America, 1950-2011

This article builds series of wage shares in gross domestic product (GDP) for 15 Latin American economies individually and as a group for the period 1950-2010. Using different methodologies, it is established that wage share is non-linear and has undergone two major cycles. The article discusses various authors, especially classic and post-Keynesian thinkers, who have explored the relationship between wage share in GDP and economic activity. It is also shown that the post-Keynesian approach is relevant in explaining that the main variables determining real gdp variations include wage share, gross capital formation and exports of goods and services. However, the contribution of wage share to real output growth has declined from the 1980s onwards.

Análise crítica de aspectos de modelagem matemática no planejamento da expansão a longo prazo de sistemas de transmissão

Pós-graduação em Engenharia Elétrica - FEIS

Modelagem 1D e 2,5D de dados do método CSEM marinho em meios com anisotropia transversal inclinada

Neste trabalho apresentamos a solução do campo eletromagnético gerado por um dipolo elétrico horizontal em meios transversalmente isotrópicos com eixo de simetria vertical (TIV) e com eixo de simetria inclinado (TII). Para modelos unidimensionais, o campo eletromagnético foi obtido por duas metodologias distintas: (1) solução semi-analítica das equações de Maxwell com auxílio de potenciais vetores no caso TIV e (2) em modelos com anisotropia transversal inclinada o campo eletromagnético foi separado em primário e secundário, e então, o campo secundário foi calculado pelo método de elementos finitos no domínio (k_x, k_y, z) da transformada de Fourier. Para estruturas bidimensionais, foi aplicada a mesma metodologia usado nos modelos TII unidimensionais, onde o campo secundário foi calculado pelo método de elementos finitos no domínio (x, k_y, z), da transformada de Fourier, com a utilização de malhas não estruturadas para discretização dos modelos. Estas respostas foram usados para avaliar os efeitos da anisotropia elétrica nos dados CSEM marinho 1D e 2,5D.

Extensometria: avaliação de implantes de sextavado externo posicionados na configuração linear e compensada (offset), sob carregamento axial

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise linear e espacial entre alguns atributos produtivos e tecnológicos da cana- de-açúcar com o pH de um argissolo vermelho de Suzanápolis (SP)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)