998 resultados para Sequential selection
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Eucalyptus camaldulensis has great importance in Brazil because of their phenotypic plasticity for different environmental conditions, as soils, altitudes and rainfall. This study is an investigation of a base population of E. camaldulensis from Australia through a progeny test implanted in Selviria, MS. The trial was established in a randomized block design, with 25 families and 60 replications of single tree plots. Genetic parameters for anatomic traits and volume shrinkage were estimated, as well as their correlations with wood basic density. No significant differences among progenies were observed for the traits studied. The additive genetic variation coefficient at individual and among progeny levels ranged from low (0.26%) to high (16.98%). The narrow sense heritability at individual and family means levels also ranged from low (0.01) to high (0.87). This indicates that some traits are under strong genetic control and can be improved by selection. In the present situation, in order to attain the highest genetic gains, the sequential selection among and within progeny would be recommended.
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Records of Nellore animals born from 1990 to 2006 were used to estimate genetic correlations of visual scores at yearling (conformation, C; finishing precocity, P; and muscling, M) with primiparous subsequent rebreeding (SR) and days to first calving (DC), because the magnitude of these associations is still unknown. Genetic parameters were estimated by multiple-traits Bayesian analysis, using a nonlinear (threshold) animal models for visual scores and SR and a linear animal models for weaning weight (WW) and DC. WW was included in the analysis to account for the effects of sequential selection. The posterior means of heritabilities estimated for C, P, M, SR and DC were 0.24 +/- 0.01, 0.31 +/- 0.01, 0.30 +/- 0.01, 0.18 +/- 0.02 and 0.06 +/- 0.02, respectively. The posterior means of genetic correlations estimated between SR and visual scores were low and positive, with values of 0.09 +/- 0.02 (C), 0.19 +/- 0.03 (P) and 0.18 +/- 0.05 (M). on the other hand, negative genetic correlations were found between DC and C (-0.11 +/- 0.09), P (-0.19 +/- 0.09) and M (-0.16 +/- 0.09). The primiparous rebreeding trait has genetic variability in Nellore cattle. The genetic correlations between visual scores, and SR and DC were low and favourable. The genetic changes in C, P and M were 0.02, 0.03 and 0.03/year, respectively. For SR and DC, genetic trends were 0.01/year and -0.01 days/year, respectively, indicating that the increase in genetic merit for reproductive traits was small over time. Direct selection for visual scores together with female reproductive traits is recommended to increase the fertility of beef cows.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Eucalyptus camaldulensis has great importance in Brazil because of their phenotypic plasticity for different environmental conditions, as soils, altitudes and rainfall. This study is an investigation of a base population of E. camaldulensis from Australia through a progeny test implanted in Selvíria, MS. The trial was established in a randomized block design, with 25 families and 60 replications of single tree plots. Genetic parameters for anatomic traits and volume shrinkage were estimated, as well as their correlations with wood basic density. No significant differences among progenies were observed for the traits studied. The additive genetic variation coefficient at individual and among progeny levels ranged from low (0.26%) to high (16.98%). The narrow sense heritability at individual and family means levels also ranged from low (0.01) to high (0.87). This indicates that some traits are under strong genetic control and can be improved by selection. In the present situation, in order to attain the highest genetic gains, the sequential selection among and within progeny would be recommended.
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Pós-graduação em Zootecnia - FCAV
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The development of a high-density active microelectrode array for in vitro electrophysiology is reported. Based on the Active Pixel Sensor (APS) concept, the array integrates 4096 gold microelectrodes (electrode separation 20 microm) on a surface of 2.5 mmx2.5 mm as well as a high-speed random addressing logic allowing the sequential selection of the measuring pixels. Following the electrical characterization in a phosphate solution, the functional evaluation has been carried out by recording the spontaneous electrical activity of neonatal rat cardiomyocytes. Signals with amplitudes from 130 microVp-p to 300 microVp-p could be recorded from different pixels. The results demonstrate the suitability of the APS concept for developing a new generation of high-resolution extracellular recording devices for in vitro electrophysiology.
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This paper presents a multiple robots formation manoeuvring and its collision avoidance strategy. The direction priority sequential selection algorithm is employed to achieve the raw path, and a new algorithm is then proposed to calculate the turning compliant waypoints supporting the multi-robot formation manoeuvre. The collision avoidance strategy based on the formation control is presented to translate the collision avoidance problem into the stability problem of the formation. The extension-decomposition-aggregation scheme is next applied to solve the formation control problem and subsequently achieve the collision avoidance during the formation manoeuvre. Simulation study finally shows that the collision avoidance problem can be conveniently solved if the stability of the constructed formation including unidentified objects can be satisfied.
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Causal inference methods - mainly path analysis and structural equation modeling - offer plant physiologists information about cause-and-effect relationships among plant traits. Recently, an unusual approach to causal inference through stepwise variable selection has been proposed and used in various works on plant physiology. The approach should not be considered correct from a biological point of view. Here, it is explained why stepwise variable selection should not be used for causal inference, and shown what strange conclusions can be drawn based upon the former analysis when one aims to interpret cause-and-effect relationships among plant traits.
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A number of authors have proposed clinical trial designs involving the comparison of several experimental treatments with a control treatment in two or more stages. At the end of the first stage, the most promising experimental treatment is selected, and all other experimental treatments are dropped from the trial. Provided it is good enough, the selected experimental treatment is then compared with the control treatment in one or more subsequent stages. The analysis of data from such a trial is problematic because of the treatment selection and the possibility of stopping at interim analyses. These aspects lead to bias in the maximum-likelihood estimate of the advantage of the selected experimental treatment over the control and to inaccurate coverage for the associated confidence interval. In this paper, we evaluate the bias of the maximum-likelihood estimate and propose a bias-adjusted estimate. We also propose an approach to the construction of a confidence region for the vector of advantages of the experimental treatments over the control based on an ordering of the sample space. These regions are shown to have accurate coverage, although they are also shown to be necessarily unbounded. Confidence intervals for the advantage of the selected treatment are obtained from the confidence regions and are shown to have more accurate coverage than the standard confidence interval based upon the maximum-likelihood estimate and its asymptotic standard error.
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Most statistical methodology for phase III clinical trials focuses on the comparison of a single experimental treatment with a control. An increasing desire to reduce the time before regulatory approval of a new drug is sought has led to development of two-stage or sequential designs for trials that combine the definitive analysis associated with phase III with the treatment selection element of a phase II study. In this paper we consider a trial in which the most promising of a number of experimental treatments is selected at the first interim analysis. This considerably reduces the computational load associated with the construction of stopping boundaries compared to the approach proposed by Follman, Proschan and Geller (Biometrics 1994; 50: 325-336). The computational requirement does not exceed that for the sequential comparison of a single experimental treatment with a control. Existing methods are extended in two ways. First, the use of the efficient score as a test statistic makes the analysis of binary, normal or failure-time data, as well as adjustment for covariates or stratification straightforward. Second, the question of trial power is also considered, enabling the determination of sample size required to give specified power. Copyright © 2003 John Wiley & Sons, Ltd.