The double sampling and the EWMA charts based on the sample variances

We propose a new statistic to control the covariance matrix of bivariate processes. This new statistic is based on the sample variances of the two quality characteristics, in short VMAX statistic. The points plotted on the chart correspond to the maximum of the values of these two variances. The reasons to consider the VMAX statistic instead of the generalized variance vertical bar S vertical bar is its faster detection of process changes and its better diagnostic feature; that is, with the VMAX statistic it is easier to identify the out-of-control variable. We study the double sampling (DS) and the exponentially weighted moving average (EWMA) charts based on the VMAX statistic. (C) 2008 Elsevier B.V. All rights reserved.

Estimative of genetic parameters in progeny test of Pinus caribaea Morelet var. hondurensis Barret & Golfari by quantitative traits and microsatellite markers

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

Diretrizes para conservação da espécie Mimosa Caesalpiniifolia Benth., Macaíba-RN

About 40% of the earth is occupied by tropical and subtropical forests, including 42% of dry forests, where there is Caatinga Bioma, contemplating tree forests and shrubs, with xerophytic characteristics. Study and conservations of Caatinga biologic diversity is one of the greatest challenges of Brazilian science because those are, proportionally, the less studied among natural areas, with most of the scientific effort centered in very few points around the main cities in the area and also because it is the less protected natural Brazilian area. The environmental degradation is constantly increasing and has its rhythm accelerated by the men appropriation to meet or not their own needs. Therefore, species conservation should be based in three principles: the use of natural resources by present generation, waste prevention and use of the natural resources to benefit the majority of the citizens. Among the strategies to species conservation, we can mention the ex situ conservation , in which the conservation of genetic resources may be realized outside of the natural environment in which the species occur, and in situ conservation , or, in other words, in the places where the species occur. In ex situ conservation, the germplasm collections are maintained in the field and/or in laboratories (conservation chambers), and this mainly conserves intraspecific diversity (genetic variance), the ex situ collections are continuously enriched by collection activities, introduction and germplasm interchange; the in situ conservation preserving ecosystems and habitats, maintaining and recovering native population of species of interest. So, the objective of this paper is the search for strategies to the conservation of Mimosa caesalpiniifolia B. (sabiá) using instruments of environmental perception and plant biotechnology, as mechanisms of in situ and ex situ conservation. To environmental perception, were realized open, semi-structured and qualitative interviews. The questions included socioeconomic data and knowledge of Sabiá specie. To plant biotechnology, Sabiá seed collection were realized in different location to formation of a germplasm bank. The specie micropropagation was made from nodal segment of plants from the matrizeiro. About the knowledge of rural populations and the use of Sabiá plant, some preferences occurred from speeches that the plant possesses a firm wood, not attacked by termites, legalized for exploration by the Brazilian environmental organ (IBAMA), and is a native specie. This research found the rural population has knowledge about Sabiá specie and the natural resources are exhausting. The proposal that the rural community brought was the donation of the Sabiá specie seeding initiating on the rain season, in which the seeding would be plated between the lots, in individual plantations. To the formation of a matrix bank, plant biothecnology brought answers favorable to Sabiá specie seeding, with the formation of multiple shoots

Componentes de (co)variância e parâmetros genéticos de características de crescimento da raça Simental no Brasil

Informações de genealogia e produção, cedidas pela Associação Brasileira de Criadores da Raça Simental (ABCRS), relativas aos pesos desde o nascimento até um ano de idade, foram utilizadas para estimar, sob modelos alternativos, os componentes de variância e os parâmetros genéticos em animais da raça Simental no Brasil. A matriz de parentesco incluiu 25.812 animais dos quais 7587 com dados de produção. O modelo 1 contém, além do erro, o efeito genético direto. Os modelos seguintes contêm os componentes do modelo 1, mais o efeito permanente de ambiente materno (modelo 2), ou o componente genético materno (modelo 3), ambos os componentes (modelo 5), os componentes do modelo 3 mais a covariância entre os efeitos genéticos direto e materno (modelo 4) e todos os componentes citados (modelo 6). Os modelos foram comparados pelo teste de razão de verossimilhança pelo chi² (P<0,01). Os componentes de variância e os valores de herdabilidades, estimados para os efeitos direto e materno, foram decrescentes, desde o modelo 1 até o modelo 6, na razão direta em que o modelo incorpora mais efeitos aleatórios. Para a fase de aleitamento foi encontrada variância genética nula, entretanto, alto valor para a variância de ambiente permanente. Os efeitos maternos, genético e de ambiente permanente são importantes para a raça Simental no Brasil e devem ser considerados em programas de seleção. Entretanto, os valores mais elevados de herdabilidade materna, encontrados com modelos sem efeito de ambiente permanente, sugerem que o método utilizado não discrimina apropriadamente esses efeitos, oriundos de mesma fonte de variação.

Gráfico de controle de VMAX para o monitoramento da matriz de covariâncias

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

Gráfico de controle MCMAX para o monitoramento simultâneo do vetor de médias e da matriz de covariâncias

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

Genetic characterization of egg weight, egg production and age at first egg in quails

O objetivo neste estudo foi obter estimativas de parâmetros genéticos para as características peso do ovo, produção de ovos em 189 dias de postura e dia do primeiro ovo em codornas de três linhagens de postura e uma de corte. Os dados foram analisados por meio de procedimentos bayesianos usando amostragem de Gibbs. As estimativas de herdabilidade para peso do ovo, produção de ovos em 189 dias de postura e dia do primeiro ovo foram, respectivamente, para a linhagem amarela, 0,31; 0,84 e 0,53; azul, 0,14; 0,82 e 0,60; vermelha, 0,70; 0,96 e 0,75; e de corte, 0,73; 0,96 e 0,72. As correlações genéticas entre peso do ovo e produção de ovos em 189 dias de postura, peso do ovo e dia do primeiro ovo e, produção de ovos em 189 dias de postura e dia do primeiro ovo foram, para amarela, 0,58; -0,77; e -0,90; azul, 0,09; -0,01; e -0,95; vermelha, 0,09; 0,03; e -0,76; e de corte, -0,18; 0,19 e -0,91. A partir das probabilidades de superposição das distribuições posteriories dos parâmetros, as linhagens dividem-se em dois grupos distintos: um com as linhagens amarela e azul e outro com as linhagens vermelha e de corte.

Joint control charts for monitoring location and dispersion

The T-2 and the generalized variance vertical bar S vertical bar charts are used for monitoring the mean vector and the covariance matrix of multivariate processes. In this article, we propose for bivariate processes the use of the T-2 and the VMAX charts. The points plotted on the VMAX chart correspond to the maximum of the sample variances of the two quality characteristics. The reason to consider the VMAX statistic instead of the generalized variance vertical bar S vertical bar is the user's familiarity with the computation of simple sample variances; we can't say the same with regard to the computation of the generalized variance vertical bar S vertical bar.

Rede neural não supervisionada baseada em transformada Karhunen-Loève para processamento, compressão e reconhecimento de imagens

The merit of the Karhunen-Loève transform is well known. Since its basis is the eigenvector set of the covariance matrix, a statistical, not functional, representation of the variance in pattern ensembles is generated. By using the Karhunen-Loève transform coefficients as a natural feature representation of a character image, the eigenvector set can be regarded as an feature extractor for a classifier.

Genetic variation between several species of sections Extranervosae, Caulorrhizae, Heteranthae, and Triseminatae (genus Arachis) estimated by DNA polymorphism

Genetic variation within and among accessions of the genus Arachis representing sections Extranervosae, Caulorrhizae, Heteranthae, and Triseminatae was evaluated using RFLP and RAPD markers. RAPD markers revealed a higher level of genetic diversity than did RFLP markers, both within and among the species evaluated. Phenograms based on various band-matching algorithms revealed three major clusters of similarity among the sections evaluated. The first group included the species from section Extranervosae, the second group consisted of sections Triseminatae, Caulorrhizae, and Heteranthae, and the third group consisted of one accession of Arachis hypogaea, which had been included as a representative of section Arachis. The phenograms obtained from the RAPD and RFLP data were similar but not identical. Arachis pietrarellii, assayed only by RAPD, showed a high degree of genetic similarity with Arachis villosulicarpa. This observation supported the hypothesis that these two species are closely related. It was also shown that accession V 7786, previously considered to be Arachis sp. aff. pietrarellii, and assayed using both RFLPs and RAPDs, was possibly a new species from section Extranervosae, but very distinct from A. pietrarellii.

Genetic variation and phylogenetic relationships based on RAPD analysis in section Caulorrhizae, genus Arachis (Leguminosae)

Wild Arachis germplasm includes potential forage species, such as the rhizomatous Arachis glabrata and the stoloniferous A. pinto and A. repens. Commercial cultivars of A. pintoi have already been released in Australia and in several Latin American countries, and most of these cultivars were derived from a single accession of A. pintoi (GK 12787). Arachis repens is less productive as a forage plant than is A. pintoi. However, it can be crossed with A. pintoi, and thus has good potential as germplasm for the improvement of A. pintoi. Arachis repens is also used as an ornamental plant and ground cover. Many new accessions of these two stoloniferous species are now available, and they harbor significant genetic variability beyond that available in the few older accessions, previously available. Therefore, these new accessions need to be conserved, documented and considered in terms of their potential for crop improvement and direct commercial use. Sixty-four accessions of this new germplasm were analyzed using RAPD analysis. Most of the accessions of A. repens grouped together into a clearly distinct group. In general, the accessions from the distinct valleys of the Jequitinhonha, Sao Francisco and Parana rivers did not group together, suggesting there is not a tight relation between dispersion by rivers and the geographic distribution of genetic variation in these species.

The use of principal components and univariate charts to control multivariate processes

In this article, we evaluate the performance of the T2 chart based on the principal components (PC chart) and the simultaneous univariate control charts based on the original variables (SU X̄ charts) or based on the principal components (SUPC charts). The main reason to consider the PC chart lies on the dimensionality reduction. However, depending on the disturbance and on the way the original variables are related, the chart is very slow in signaling, except when all variables are negatively correlated and the principal component is wisely selected. Comparing the SU X̄, the SUPC and the T 2 charts we conclude that the SU X̄ charts (SUPC charts) have a better overall performance when the variables are positively (negatively) correlated. We also develop the expression to obtain the power of two S 2 charts designed for monitoring the covariance matrix. These joint S2 charts are, in the majority of the cases, more efficient than the generalized variance |S| chart.

Monitoring bivariate processes

The T2 chart and the generalized variance |S| chart are the usual tools for monitoring the mean vector and the covariance matrix of multivariate processes. The main drawback of these charts is the difficulty to obtain and to interpret the values of their monitoring statistics. In this paper, we study control charts for monitoring bivariate processes that only requires the computation of sample means (the ZMAX chart) for monitoring the mean vector, sample variances (the VMAX chart) for monitoring the covariance matrix, or both sample means and sample variances (the MCMAX chart) in the case of the joint control of the mean vector and the covariance matrix.

The Poisson-exponential lifetime distribution

In this paper we proposed a new two-parameters lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk problem base. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulae for its reliability and failure rate functions, quantiles and moments, including the mean and variance. A simple EM-type algorithm for iteratively computing maximum likelihood estimates is presented. The Fisher information matrix is derived analytically in order to obtaining the asymptotic covariance matrix. The methodology is illustrated on a real data set. © 2010 Elsevier B.V. All rights reserved.

Comparison of factor-analytic and reduced rank models for test-day milk yield in Gyr dairy cattle (Bos indicus)

We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields. © FUNPEC-RP.