894 resultados para Branching random walk
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Background: Meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal's life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality.Results: The set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism.Conclusions: These results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle. © 2013 Mokry et al.; licensee BioMed Central Ltd.
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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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Background: The Stroke remains one of the major chronic diseases worldwide, and is considered a major cause of disability, which results not only in persistent neurological deficits, but also in the high physical deconditioning, nevertheless there are not many forms of assessing functional capacity in this population. We aimed to investigate the feasibility of the Six Minute Walk Teste and the Six-Minute Step Test (6MST) in post-stroke patients and compare the behavior of physiological variables during the 6MST and the Six-Minute Walk Test (6MWT), by correlating the functional performance obtained in both tests. Method. The 6MWT was carried out according to the American Thoracic Society (ATS) and the 6MST was performed in six minutes in order to compare it to the 6MWT in a 20 cm step. Was included post-stroke individuals able to walk without aid. All of them did the 6MWT and the 6MST. Results: 12 patients participated in the study. There was no statistical difference in the parameters analyzed when tests were compared. There was poor correlation between the functional performance in both tests. Conclusion: The 6MWT and the 6MST is feasible for post-stroke patients and physiological responses are equal during the performance of both tests. However, there was no correlation with respect to functional performance, which was assessed by the distance walked in the 6MWT and by the number of steps climbed in the 6MST. © 2013 da Silva et al.; licensee BioMed Central Ltd.
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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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Results are presented from a search for the rare decays Bs0→μ+μ- and B0→μ+μ - in pp collisions at √s=7 and 8 TeV, with data samples corresponding to integrated luminosities of 5 and 20 fb-1, respectively, collected by the CMS experiment at the LHC. An unbinned maximum-likelihood fit to the dimuon invariant mass distribution gives a branching fraction B(Bs0→μ+μ-)=(3.0-0.9+1.0) ×10-9, where the uncertainty includes both statistical and systematic contributions. An excess of Bs0→μ+μ- events with respect to background is observed with a significance of 4.3 standard deviations. For the decay B0→μ+μ- an upper limit of B(B0→μ+μ-)<1.1×10 -9 at the 95% confidence level is determined. Both results are in agreement with the expectations from the standard model. © 2013 CERN. Published by the American Physical Society under the terms of the.
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Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.
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Pós-graduação em Fisiopatologia em Clínica Médica - FMB
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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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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The physical properties of novel thermoplastic random copolyesters [-(CH2)(n)-COO-/-(CH2)(n)-COO-](x) made of long (n=12) and medium (n=8) chain length -hydroxyfatty esters [HO-(CH2)(n)-COOCH3] derived from bio-based vegetable oil feedstock are described. Poly(-hydroxy tridecanoate/-hydroxy nonanoate) P(-Me13-/-Me9-) random copolyesters (M-n=11,000-18,500 g/mol) with varying molar ratios were examined by TGA, DSC, DMA and tensile analysis, and WAXD. For the whole range of P(-Me13-/-Me9-) compositions, the WAXD data indicated an orthorhombic polyethylene-like crystal packing. Their melting characteristics, determined by DSC, varied with composition suggesting an isomorphic cocrystallization behavior. TGA of the P(-Me13-/-Me9-)s indicated improved thermal stability determined by their molar compositions. The glass transition temperature, investigated by DMA, was also found to vary with composition. The crystallinities of P(-Me13-/-Me9-)s however, were unaffected by the composition. The stiffness (Young's modulus) of these materials was found to be related to their degrees of crystallinity. (c) 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014, 131, 40492.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)