171 resultados para Differenzial Imaging, Principal Component Analysis, esopianeti, SPHERE, IFS


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O objetivo deste trabalho foi determinar o número de medições (experimentos) necessários à predição do desempenho de cultivares de feijão (Phaseolus vulgaris L.). Quatorze cultivares de feijão foram avaliadas em nove experimentos conduzidos em Santa Maria, Estado do Rio Grande do Sul (latitude 29°42'S, longitude 53°49'W e 95m de altitude), nos anos agrícolas de 2000/2001 a 2004/2005. As avaliações foram constituídas por produtividade de grãos, número de vagens por planta, número de sementes por vagem, massa de cem grãos, população final de plantas, número de dias da emergência ao florescimento, número de dias da emergência à colheita, altura de inserção da primeira vagem, altura de inserção da última vagem, grau de acamamento e coloração do tegumento dos grãos. As estimativas dos coeficientes de repetibilidade foram obtidas por três métodos - análise de variância, componentes principais e análise estrutural. Sete experimentos possibilitam a identificação de cultivares superiores de feijão em relação às características de produção, de fenologia e de morfologia, com 85% de exatidão no prognóstico de seu valor real.

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Os lagos de pesca recreativa, pesque-pague, surgiram no Brasil em um cenário agrícola denominado como novo rural brasileiro. Este estudo conduzido no noroeste paulista teve como foco o desempenho produtivo dos lagos de pesca recreativa. Foram feitas visitas mensais a nove empreendimentos de pesca recreativa durante seis meses. A cada visita foi aplicado um questionário contendo 13 indicadores de desempenho. Os dados levantados foram submetidos à análise multivariada (MANOVA), análise de componente principal (ACP) e análise de agrupamento. A MANOVA indicou diferenças significativas entre os lagos de pesca recreativa. A ACP revelou, a partir do coeficiente dos autovalores, três atributos: sistema produtivo, gerenciamento pesqueiro e administração operacional. A análise de agrupamento classificou os lagos de pesca recreativa em quatro grupos. Freqüência de pescadores (FP), densidade de estocagem (DE), biomassa de estocagem (BE), captura total (CT) e captura lago dia (CLD), os quais fazem parte do atributo sistema produtivo, mostrando-se os indicadores mais importantes para a avaliação de desempenho dos lagos de pesca recreativa neste estudo.

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Foram estudados 125 países avaliados por um conjunto de 26 indicadores básicos, de saúde, econômicos e educacionais, usando-se três métodos estatísticos multivariados: Análise de Agrupamento, Análise de Componentes Principais e Análise de Variância Multivariada. As variáveis mais discriminatórias foram a expectativa de vida, as taxas de mortalidade infantil e de menores de cinco anos, as taxas de natalidade e de fertilidade e a taxa de matrícula no segundo grau para o sexo feminino. Os países foram ordenados de acordo com um índice de padrão de vida e separados em cinco grupos.

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

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Pathogenic variation in Colletotrichum gloeosporioides infecting species of the tropical pasture legume Stylosanthes at its center of diversity was determined from 296 isolates collected from wild host population and selected germ plasm of S. capitata, S. guianensis, S. scabra, and S. macrocephala in Brazil. A putative host differential set comprising 11 accessions was selected from a bioassay of 18 isolates on 19 host accessions using principal component analysis. A similar analysis of anthracnose severity data for a subset of 195 isolates on the 11 differentials indicated that an adequate summary of pathogenic variation could be obtained using only five of these differentials. of the five differentials, S. seabrana 'Primar' was resistant and S. scabra 'Fitzroy' was susceptible to most isolates. A cluster analysis was used to determine eight natural race clusters using the 195 isolates. Linear discriminant functions were developed for eight race clusters using the 195 isolates as the training data set, and these were applied to classify a test data set of the remaining 101 isolates. All except 11 isolates of the test data set were classified into one of the eight race clusters. Over 10% of the 296 isolates were weakly pathogenic to all five differentials and another 40% were virulent on just one differential. The unclassified isolates represent six new races with unique virulence combinations, of which one isolate is virulent on all five differentials. The majority of isolates came from six field sites, and Shannon's index of diversity indicated considerable variation between sites. Pathogenic diversity was extensive at three sites where selected germ plasm were under evaluation, and complex race clusters and unclassified isolates representing new races were more prevalent at these sites compared with sites containing wild Stylosanthes populations.

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A set of 25 quinone compounds with anti-trypanocidal activity was studied by using the density functional theory (DFT) method in order to calculate atomic and molecular properties to be correlated with the biological activity. The chemometric methods principal component analysis (PCA), hierarchical cluster analysis (HCA), stepwise discriminant analysis (SDA), Kth nearest neighbor (KNN) and soft independent modeling of class analogy (SIMCA) were used to obtain possible relationships between the calculated descriptors and the biological activity studied and to predict the anti-trypanocidal activity of new quinone compounds from a prediction set. Four descriptors were responsible for the separation between the active and inactive compounds: T-5 (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors give information on the kind of interaction that occurs between the compounds and the biological receptor. The prediction study was done with a set of three new compounds by using the PCA, HCA, SDA, KNN and SIMCA methods and two of them were predicted as active against the Trypanosoma cruzi. (c) 2005 Elsevier SAS. All rights reserved.

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A number of studies have analyzed various indices of the final position variability in order to provide insight into different levels of neuromotor processing during reaching movements. Yet the possible effects of movement kinematics on variability have often been neglected. The present study was designed to test the effects of movement direction and curvature on the pattern of movement variable errors. Subjects performed series of reaching movements over the same distance and into the same target. However, due either to changes in starting position or to applied obstacles, the movements were performed in different directions or along the trajectories of different curvatures. The pattern of movement variable errors was assessed by means of the principal component analysis applied on the 2-D scatter of movement final positions. The orientation of these ellipses demonstrated changes associated with changes in both movement direction and curvature. However, neither movement direction nor movement curvature affected movement variable errors assessed by area of the ellipses. Therefore it was concluded that the end-point variability depends partly, but not exclusively, on movement kinematics.

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The design of the present study enabled the authors to distinguish between the possible effects of movement displacement and trajectory length on the pattern of final positions of planar reaching movements. With their eyes closed, 9 subjects performed series of fast and accurate movements from different initial positions to the same target. For some series, the movements were unconstrained and were therefore performed along an approximately straight vertical line. For other series, an obstacle was positioned so that trajectory length was increased because of an increase in movement curvature. Ellipses of variability obtained by means of principal component analysis applied to the scatter of movement final positions enabled the authors to assess the pattern of movement variable errors. The results showed that the orientation of the ellipses was not affected by movement displacement or by trajectory length, whereas variable errors increased with move ment displacement. An increase in trajectory length as a consequence of increased curvature caused no change in variable error. From the perspective of current motor control theory, that finding was quite unexpected. Further studies are required so that one can distinguish among the possible effects of various kinematics, kinetics, and other variables that could affect the pattern of variable errors of reaching movements.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Magnetic susceptibility (chi, mass specific) is useful for easy indirect estimation of other soil properties at a low cost. The aim of this study was to assess the use of chi as measured with an analytical balance for predicting properties with a substantial influence on the management of Typic Haplustalfs in southern Brazil. To achieve this 48 topsoil samples were taken at the intersection points in a rectangular grid of 20 m x 20 m cells, with 38 of these used for calibration and 10 for validation in regression analyses. The obtained chi values were slightly higher than, and highly correlated (r = 0.970; P < 0.001) with those measured with a susceptibility meter. Highly significant (P < 0.001) correlations were also found between chi and other soil properties relevant to soil classification and management such as clay content (r = 0.68), cation exchange capacity (r = 0.62), P sorption capacity (r = 0.76) and haematite content (r = 0.82). Results from a principal component analysis of eight properties important for soil classification explained 11% of the variance in the data set. The good predictive ability of chi was consistent with current knowledge on the formation pathways for pedogenic ferrimagnets. In summary, chi, which can be readily measured with an analytical balance, has the potential for quantifying soil attributes and may therefore be used in pedotransfer functions.

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One of the major problems facing Blast Furnaces is the occurrence of cracks in taphole mud, as the underlying causes are not easily identifiable. The absence of this knowledge makes it difficult the use of conventional techniques for predictability and mitigation. This paper will address the application of Probabilistic Neural Network using the Matlab software as a means to detect and control such cracks. The most relevant BF operational variables were picked through the statistic tool "Principal Component Analysis - PCA." Based upon the selection of these variables a probabilistic neural network was built. A set of BF operational data, consisting of 30 controlling variables, was divided into 2 groups, one of which for network training, and the other one to validate the neural network. The neural network got 98% of the cases right. The results show the effectiveness of this tool for crack prediction in relation to clay intrinsic properties and as a result of the fluctuation in operational variables.

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