914 resultados para label regression
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The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil. ©FUNPEC-RP.
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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.
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A surface confined redox group contributes to an interfacial charging (quantifiable by redox capacitance) that can be sensitively probed by impedance derived capacitance spectroscopy. In generating mixed molecular films comprising such redox groups, together with specific recognition elements (here antibodies), this charging signal is able to sensitively transduce the recognition and binding of specific analytes. This novel transduction method, exemplified here with C-reactive protein, an important biomarker of cardiac status and general trauma, is equally applicable to any suitably prepared interfacial combination of redox reporter and receptor. The assays are label free, ultrasensitive, highly specific and accompanied by a good linear range. © 2013 Elsevier B.V.
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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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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The objective of this research was to estimate (co) variance functions and genetic parameters for body weight in Colombian buffalo populations using random regression models with Legendre polynomials. Data consisted of 34,738 weight records from birth to 900 days of age from 7815 buffaloes. Fixed effects in the model were contemporary group and parity order of the mother. Random effects were direct and maternal additive genetic, as well as animal and maternal permanent environmental effects. A cubic orthogonal Legendre polynomial was used to model the mean curve of the population. Eleven models with first to sixth order polynomials were used to describe additive genetic direct and maternal effects, and animal and maternal permanent environmental effects. The residual was modeled considering five variance classes. The best model included fourth and sixth order polynomials for direct additive genetic and animal permanent environmental effects, respectively, and third-order polynomials for maternal genetic and maternal permanent environmental effects. The direct heritability increased from birth until 120 days of age (0.32 +/- 0.05), decreasing thereafter until one year of age (0.18 +/- 0.04) and increased again, reaching 0.39 +/- 0.09, at the end of the evaluated period. The highest maternal heritability estimates (0.11 +/- 0.05), were obtained for weights around weaning age (weaning age range is between 8 and 9.5 months). Maternal genetic and maternal permanent environmental variances increased from birth until about one year of age, decreasing at later ages. Direct genetic correlations ranged from moderate (0.60 +/- 0.060) to high (0.99 +/- 0.001), maternal genetic correlations showed a similar range (0.41 +/- 0.401 and 0.99 +/- 0.003), and all of them decreased as time between weighings increased. Direct genetic correlations suggested that selecting buffalos for heavier weights at any age would increase weights from birth through 900 days of age. However, higher heritabilities for direct genetic weights effects after 600 days of age suggested that selection for these effects would be more effective if done during this age period. A greater response to selection for maternal ability would be expected if selection used maternal genetic predictions for weights near weaning. (C) 2013 Elsevier B.V. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Central giant cell granuloma (CGCG) of the jaws represents a localized and benign neoplastic lesion sometimes characterized by aggressive osteolytic proliferation. The World Health Organization defines it as an intraosseous lesion composed of cellular and dense connective tissues that contain multiple hemorrhagic foci, an aggregation of multinucleated giant cells, and occasional bone tissue trabeculae. The origin of this lesion is uncertain; however, factors such as local trauma, inflammation, intraosseous hemorrhage, and genetic abnormalities have been identified as possible causes. CGCG generally affects those younger than 30 years and occurs more frequently in women (2: 1). This lesion corresponds to approximately 7% of all benign tumors of the jaws, with prevalence in the anterior region of the jaw. Aggressive lesions are characterized by symptoms, such as pain, numbness, rapid growth, cortical perforation, root resorption, and a high recurrence rate after curettage. In contrast, nonaggressive CGCGs have a slow rate of growth, may contain sparse trabeculation, and are less likely to move teeth or cause root resorption or cortical perforation. Nonaggressive CGCGs are generally asymptomatic lesions and thus are frequently found on routine dental radiographs. Radiographically, the 2 forms of CGCG present as radiolucent, expansive, unilocular or multilocular masses with well-defined margins. The histopathology of CGCG is characterized by multinucleated giant cells, surrounded by round, oval, and spindle-shaped mononuclear cells, scattered in dense connective tissue with hemorrhagic and abundant vascularization foci. The final diagnosis is determined by histopathologic analysis of the biopsy specimen. The preferred treatment for CGCG consists of excisional biopsy, curettage with a safety margin, and partial or total resection of the affected bone. Conservative treatments include local injections of steroids, calcitonin, and antiangiogenic therapy. Drug treatment using antibiotics, painkillers, and corticosteroids and clinical and radiographic monitoring are necessary for approximately 10 days after surgery. There are only a few cases of spontaneous CGCG regression described in the literature; therefore, a detailed case report of CGCG regression in a 12-yearold boy with a 4-year follow-up is presented and compared with previous studies. (c) 2014 American Association of Oral and Maxillofacial Surgeons
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In general, pattern recognition techniques require a high computational burden for learning the discriminating functions that are responsible to separate samples from distinct classes. As such, there are several studies that make effort to employ machine learning algorithms in the context of big data classification problems. The research on this area ranges from Graphics Processing Units-based implementations to mathematical optimizations, being the main drawback of the former approaches to be dependent on the graphic video card. Here, we propose an architecture-independent optimization approach for the optimum-path forest (OPF) classifier, that is designed using a theoretical formulation that relates the minimum spanning tree with the minimum spanning forest generated by the OPF over the training dataset. The experiments have shown that the approach proposed can be faster than the traditional one in five public datasets, being also as accurate as the original OPF. (C) 2014 Elsevier B. V. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)