20,824 research outputs found

    HST Observations of the Central-Cusp Globular Cluster NGC 6752. The Effect of Binary Stars on the Luminosity Function in the Core

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    We consider the effect of binary stars on the main-sequence luminosity functions observed in the core of globular clusters, with specific reference to NGC 6752. We find that mass segregation results in an increased binary fraction at fainter magnitudes along the main-sequence. If this effect is not taken into account when analyzing luminosity functions, erroneous conclusions can be drawn regarding the distribution of single stars, and the dynamical state of the cluster. In the core of NGC 6752, our HST data reveal a flat luminosity function, in agreement with previous results. However, when we correct for the increasing binary fraction at faint magnitudes, the LF begins to fall immediately below the turn-off. This effect appears to be confined to the inner core radius of the cluster.Comment: 10 pages, 3 figures Accepted to ApJ Lett Vol 513 Number

    On quasi-Jacobi and Jacobi-quasi bialgebroids

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    We study quasi-Jacobi and Jacobi-quasi bialgebroids and their relationships with twisted Jacobi and quasi Jacobi manifolds. We show that we can construct quasi-Lie bialgebroids from quasi-Jacobi bialgebroids, and conversely, and also that the structures induced on their base manifolds are related via a quasi Poissonization

    Estimativas de parâmetros genéticos clássicos para proteínas totais em feijão-caupi.

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    Neste trabalho foram estimados parâmetros genéticos para subsidiar trabalhos de melhoramento do feijão-caupi para maior teor de proteínas total. Linhagens F6 e gerações dos cruzamentos IT97K-1042-3 x Canapu e IT97K-1042-3 x BRS Tapaihum foram quantificadas para o teor de proteína total pelo método microKjeldhal. As linhagens F6 foram avaliadas em condições de sequeiro, em blocos ao acaso com duas repetições, enquanto as gerações foram avaliadas em ambiente irrigado, sem delineamento experimental. Todas as variáveis analisadas nas linhagens F6 apresentaram significância, com coeficientes de variação de 2,9% a 50,7%. Os valores da variância de dominância foram considerados como zero, por causa das estimativas negativas obtidas. Os valores da herdabilidade no sentido restrito foram 84,32% e de 45,21% nos cruzamento IT97K-1042-3 X Canapu e IT97K-1042-3 X BRS Tapaihum, respectivamente. Toda a variância genética observada nos dois cruzamentos decorreu dos efeitos aditivos dos genes. As estimativas do número de genes foram em torno de 5,0 e 6,0 para os cruzamentos IT97K-1042-3 X Canapu e IT97K-1042-3 X BRS Tapaihum, respectivamente. Esses resultados indicam que o caráter proteína total bruta é controlado por um número reduzido de genes em feijão-caupi, podendo o acúmulo de alelos favoráveis ser obtido em poucas gerações de seleções

    Avaliação e seleção de bulbos de cebola de baixo teor de ácido pirúvico de cultivares adaptadas ao Nordeste.

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    Diferente de outros países, o Brasil não desenvolveu populações de cebola com baixa pungência, o que poderia aumentar o consumo nacional e criar novas oportunidades para os agricultores. O objetivo deste trabalho foi avaliar o teor de ácido pirúvico em algumas populações de cebola desenvolvidas para o Nordeste brasileiro para orientar trabalhos de melhoramento da espécie. Foram avaliados bulbos de cinco variedades de cebola cultivados nos Campos Experimentais de Bebedouro e Mandacaru/Embrapa Semiárido, em 2010. As condições de cultivo e manejo de fertilizantes foram semelhantes nos dois locais. Os bulbos foram quantificados para o teor de ácido pirúvico por espectrofotometria, sendo selecionados aqueles com teor menor que 5 μmol/mL. Dos 206 bulbos de Bebedouro, os teores de ácido pirúvico variaram de 3,02 μmol/mL a 14,22 μmol/mL de suco de cebola, dos quais selecionou-se 14 (6,8%). Dos 360 bulbos, colhidos no Campo Experimental de Mandacaru, os teores de ácido pirúvico variaram de 3,65 μmol/mL a 18,52 μmol/mL de suco de cebola; destes 13 (3,6%) foram selecionados. Obteve-se sementes em 18 plantas dos 27 bulbos selecionados, o que possibilitará um novo ciclo de seleção recorrente, visando o desenvolvimento de populações de cebola com baixos teores de ácido pirúvico para o Nordeste brasileiro

    A systematic comparison of supervised classifiers

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    Pattern recognition techniques have been employed in a myriad of industrial, medical, commercial and academic applications. To tackle such a diversity of data, many techniques have been devised. However, despite the long tradition of pattern recognition research, there is no technique that yields the best classification in all scenarios. Therefore, the consideration of as many as possible techniques presents itself as an fundamental practice in applications aiming at high accuracy. Typical works comparing methods either emphasize the performance of a given algorithm in validation tests or systematically compare various algorithms, assuming that the practical use of these methods is done by experts. In many occasions, however, researchers have to deal with their practical classification tasks without an in-depth knowledge about the underlying mechanisms behind parameters. Actually, the adequate choice of classifiers and parameters alike in such practical circumstances constitutes a long-standing problem and is the subject of the current paper. We carried out a study on the performance of nine well-known classifiers implemented by the Weka framework and compared the dependence of the accuracy with their configuration parameter configurations. The analysis of performance with default parameters revealed that the k-nearest neighbors method exceeds by a large margin the other methods when high dimensional datasets are considered. When other configuration of parameters were allowed, we found that it is possible to improve the quality of SVM in more than 20% even if parameters are set randomly. Taken together, the investigation conducted in this paper suggests that, apart from the SVM implementation, Weka's default configuration of parameters provides an performance close the one achieved with the optimal configuration

    What are the Best Hierarchical Descriptors for Complex Networks?

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    This work reviews several hierarchical measurements of the topology of complex networks and then applies feature selection concepts and methods in order to quantify the relative importance of each measurement with respect to the discrimination between four representative theoretical network models, namely Erd\"{o}s-R\'enyi, Barab\'asi-Albert, Watts-Strogatz as well as a geographical type of network. The obtained results confirmed that the four models can be well-separated by using a combination of measurements. In addition, the relative contribution of each considered feature for the overall discrimination of the models was quantified in terms of the respective weights in the canonical projection into two dimensions, with the traditional clustering coefficient, hierarchical clustering coefficient and neighborhood clustering coefficient resulting particularly effective. Interestingly, the average shortest path length and hierarchical node degrees contributed little for the separation of the four network models.Comment: 9 pages, 4 figure

    Levantamento de nematóides fitoparasitas associados a pomares de videira em declínio da serra gaúcha.

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