1000 resultados para associação de técnicas multivariadas


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Com o objetivo de avaliar a epidemiologia da raiva, procedimentos complementares ao diagnóstico - caracterização antigênica e genética - foram incluídos neste estudo para investigar o perfil epidemiológico da raiva animal na Amazônia brasileira, entre janeiro de 2000 e julho de 2009. Foi realizada uma revisão cuidadosa das informações de amostras do sistema nervoso central (SNC) recebidas e analisadas no Laboratório de Raiva do Instituto Evandro Chagas. Um total de 265 cepas de vírus rábico isoladas de amostras do SNC de seres humanos (n=33) e animais domésticos/silvestres (n=232) foram caracterizadas antigenicamente por imunofluorescência indireta (IFI), utilizando um painel de oito anticorpos monoclonais preparados pelo CDC contra a nucleoproteína do vírus da raiva; Além disso, 21 delas tiveram a nucleoproteína (gene N) caracterizada geneticamente por sequenciamento nucleotídico parcial seguida de análise filogenética. As sequências obtidas foram comparadas entre si e com outras sequências de vírus da raiva do Brasil e outros países das Américas, utilizando os métodos de máxima verossimilhança e bayesiano. Foi observada uma menor transmissão do vírus da raiva em áreas urbanas; detecção do ciclo rural da raiva em quase todos os estados da Amazônia; ocorrência do ciclo aéreo nos estados do Pará e Amapá; identificação da variante antigênica 2 (AgV2) do vírus da raiva, entre cães e gatos domésticos como o principal mecanismo de transmissão viral, detecção de circulação de variantes antigênicas AgV3, AgV4 e variante "Eptesicus" entre animais silvestres e, finalmente, a redução da transmissão cão-homem do vírus da raiva, que foi substituído por um aumento da transmissão morcego-homem, especialmente no estado de Pará. Em conclusão, a associação de técnicas antigênica e moleculares permitiu uma melhor compreensão da epidemiologia molecular do vírus da raiva na Amazônia Brasileira.

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Efficiency in the use of genetic variability, whether existing or created, increases when properly explored and analysed. Incorporation of biotechnology into breeding programs has been the general practice. The challenge for the researcher is the constant development of new and improved cultivars. The aim of this experiment was to select progenies with superior characteristics, whether or not carriers of the RR gene, derived from bi-parental crosses in the soybean, with the help of multivariate techniques. The experiment was carried out in a family-type experimental design, including controls, during the agricultural year 2010/2011 and 2011/2012 in Jaboticabal in the Brazilian State of São Paulo. From the F3 generation, phenotypically superior plants were selected, which were evaluated for the following traits: number of days to flowering; number of days to maturity; height of first pod insertion; plant height at maturity; lodging; agronomic value; number of branches; number of pods per plant; 100-seed weight; number of seeds per plant; grain yield per plant. Given the results, it appears possible to select superior progeny by principal component analysis. Cluster analysis using the K-means method links progeny according to the most important characteristics in each group and identifies, by the Ward method and by means of a dendrogram, the structure of similarity and divergence between selected progeny. Both methods are effective in aiding progeny selection.

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Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV

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The soybean crop is considered a high expression around the world. In plant breeding programs, knowledge of genetic diversity is extremely important and in this context, are frequently used multivariate analyzes. Thus, the aim of the present study was to evaluate the genetic divergence between soybean crosses through multivariate techniques. In total, 16 crosses were evaluated, which were in the F2 generation of inbreeding. The evaluated characteristics were plant height at maturity, height of the first pod, number of branches per plant, number of pods per plant, number of nodes per plant, hundred seed weight, grain yield and oil content. For the analyzes was used Euclidean distance, methods of hierarchical clustering UPGMA and Ward and principal component analysis. Genetic distances estimated using Euclidean distance ranged from 1.24 to 8.13, with the smallest distance observed between crosses C1 and C4, and the greatest distance between the C2 crosses and C6. The methods UPGMA clustering and Ward met crossings in five different groups. The principal component analysis explained 86.2% of the variance contained in the original eight variables with three main components. The APM characters, NV, NR, NN, PG% and oil were the main contributors to genetic divergence among traits. Multivariate techniques were crucial to the analysis of genetic diversity, and the methods of Ward and UPGMA clustering and principal components have consistent results in this way, the simultaneous use of these tools in genetic analysis of crosses is indicated

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Pós-graduação em Engenharia Mecânica - FEG

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Sometimes we face clinical situations in which the lack of harmony in the smile is caused by a major exhibition of the gingival tissue. In these cases the professional should be able to perform a detailed analysis of the static and dynamic components of the smile, in search of a satisfactory planning and treatment which may include different dental specialties. For these situations, the association of periodontics/prosthesis is a viable alternative that has been used positively in search of an aesthetic and functional condition that benefits the patient, without leaving aside the preservation of periodontal tissues and of the remaining structure of the tooth. Thus, the aim of this study was to describe a case in which the association between these two areas was proposed to correct gummy smile and dental vestibularization. Clinical results and the satisfaction of the patient indicate that this multidisciplinary treatment combining periodontal and prosthetic techniques is favorable to positive results in cases of compromised smile aesthetics due to excessive gum tissue.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Engenharia Civil e Ambiental - FEB

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Measures of agro-ecosystems genetic variability are essential to sustain scientific-based actions and policies tending to protect the ecosystem services they provide. To build the genetic variability datum it is necessary to deal with a large number and different types of variables. Molecular marker data is highly dimensional by nature, and frequently additional types of information are obtained, as morphological and physiological traits. This way, genetic variability studies are usually associated with the measurement of several traits on each entity. Multivariate methods are aimed at finding proximities between entities characterized by multiple traits by summarizing information in few synthetic variables. In this work we discuss and illustrate several multivariate methods used for different purposes to build the datum of genetic variability. We include methods applied in studies for exploring the spatial structure of genetic variability and the association of genetic data to other sources of information. Multivariate techniques allow the pursuit of the genetic variability datum, as a unifying notion that merges concepts of type, abundance and distribution of variability at gene level.

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La utilización de nuevas tecnologías asociadas a la agricultura de precisión permite capturar información de múltiples variables en gran cantidad de sitios georreferenciados dentro de lotes en producción. Las covariaciones espaciales de las propiedades del suelo y el rendimiento del cultivo pueden evaluarse a través del análisis de componentes principales clásico (PCA). No obstante, como otros métodos multivariados descriptivos, el PCA no ha sido desarrollado explícitamente para datos espaciales. Nuevas versiones de análisis multivariado permiten contemplar la autocorrelación espacial entre datos de sitios vecinos. En este trabajo se aplican y comparan los resultados de dos técnicas multivariadas, el PCA y MULTISPATI-PCA. Este último incorpora la información espacial a través del cálculo del índice de Moran entre los datos de un sitio y el dato promedio de sus vecinos. Los resultados mostraron que utilizando MULTISPATI-PCA se detectaron correlaciones entre variables que no fueron detectadas con el PCA. Los mapas de variabilidad espacial construidos a partir de la primera componente de ambas técnicas fueron similares; no así los de la segunda componente debido a cambios en la estructura de co-variación identificada, al corregir la variabilidad por la autocorrelación espacial de los datos. El método MULTISPATI-PCA constituye una herramienta importante para el mapeo de la variabilidad espacial y la identificación de zonas homogéneas dentro de lotes.