957 resultados para Minimum Variance Model
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This study evaluated the effect of cycling various pH demineralizing solutions on the surface hardness, fluoride release and surface properties of restorative materials (Ketac-Fil Plus, Vitremer, Fuji II LC, Freedom and Fluorofil). Thirty specimens of each material were made and the surface hardness measured. The specimens were randomized into five groups according to the pH (4.3; 4.6; 5.0; 5.5 and 6.2) of the demineralizing solution. The specimens were submitted to pH-cycling for 15 days. The specimens remained in the demineralizing solution for six hours and in the remineralizing solution for 18 hours. Then, the surface hardness (SH) was remeasured and the surface properties were assessed. Fluoride release was determined daily. Data from SH and the percentage of alteration in surface hardness were analyzed by analysis of variance (p < 0.05); the Kruskal-Wallis test was performed for the fluoride release results. When hardness was compared, the variation in pH led to a positive correlation for glass ionomer cements and a negative correlation for fluoride release. For polyacid-modified resin composites, a negative correlation was found with regards to fluoride release; no significant correlation was observed for hardness. Surface properties were influenced: an acidic pH led to a greater alteration, except for polyacid-modified resin composites. The pH of the demineralizing solution influenced fluoride release from the tested materials. The pH variation altered hardness and surface properties of glass ionomer cements but did not influence polyacid-modified resin composites.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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In this paper a model, called ELLOBO running in STELLA II, was set to describe the plankton system of the Broa reservoir (SP). The three state variables of the model are: phytoplankton, zooplankton, and the fish Astyanax fasciatus. The forcing variables are: temperature, nitrate, phosphorus and solar radiation. The model did not consider the cycling of nutrients inside the reservoir. The results show that: temperature is the principal forcing variable in the phytoplankton dynamic and in the subsequent evolution of the whole system. The zooplankton predation was described by Odum's equation, and there is a strong random component in zooplankton grazing, which was essential for the model, because zooplankton estimates have high variance. One must collect data in a short space of time (maybe daily) to better explain the zooplankton and phytoplankton variation. Validation was performed using simple statistics (arithmetic mean, standard deviation) and the results show concordance between observed and simulated values. Overhead was used to calibrate some parameters and to validate the model. The highest overhead value (5%) imply in the better accordance between estimated and;observed state variables values. We believe this approach in Broa reservoir will provide an useful tool for future research and it could be used comparatively in other continental aquatic ecosystems. (C) 2000 Elsevier B.V. B.V. All rights reserved.
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Adopting the framework of the Jaynes-Cummings model with an external quantum field, we obtain exact analytical expressions of the normally ordered moments for any kind of cavity and driving fields. Such analytical results are expressed in the integral form, with their integrands having a commom term that describes the product of the Glauber-Sudarshan quasiprobability distribution functions for each field, and a kernel responsible for the entanglement. Considering a specific initial state of the tripartite system, the normally ordered moments are then applied to investigate not only the squeezing effect and the nonlocal correlation measure based on the total variance of a pair of Einstein-Podolsky-Rosen type operators for continuous variable systems, but also the Shchukin-Vogel criterion. This kind of numerical investigation constitutes the first quantitative characterization of the entanglement properties for the driven Jaynes-Cummings model.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Uma equação de regressão múltipla MOS (da sigla em inglês para Model Output Statistics), para previsão da temperatura mínima diária do ar na cidade de Bauru, estado de São Paulo, é desenvolvida. A equação de regressão múltipla, obtida usando análise de regressão stepwise, tem quatro preditores, três do modelo numérico global do Centro de Previsão de Tempo e Estudos Climáticos (CPTEC) e um observacional da estação meteorológica do Instituto de Pesquisas Meteorológicas (IPMet), Bauru. Os preditores são prognósticos para 24 horas do modelo global, válidos para 00:00GMT, da temperatura em 1000hPa, vento meridional em 850hPa e umidade relativa em 1000hPa, e temperatura observada às 18:00GMT. Esses quatro preditores explicam, aproximadamente, 80% da variância total do preditando, com erro quadrático médio de 1,4°C, que é aproximadamente metade do desvio padrão da temperatura mínima diária do ar observada na estação do IPMet. Uma verificação da equação MOS com uma amostra independente de 47 casos mostra que a previsão não se deteriora significativamente quando o preditor observacional for desconsiderado. A equação MOS, com ou sem esse preditor, produz previsões com erro absoluto menor do que 1,5°C em 70% dos casos examinados. Este resultado encoraja a utilização da técnica MOS para previsão operacional da temperatura mínima e seu desenvolvimento para outros elementos do tempo e outras localidades.
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The objective of this work was to evaluate the Nelore beef cattle, growth curve parameters using the Von Bertalanffy function in a nested Bayesian procedure that allowed estimation of the joint posterior distribution of growth curve parameters, their (co)variance components, and the environmental and additive genetic components affecting them. A hierarchical model was applied; each individual had a growth trajectory described by the nonlinear function, and each parameter of this function was considered to be affected by genetic and environmental effects that were described by an animal model. Random samples of the posterior distributions were drawn using Gibbs sampling and Metropolis-Hastings algorithms. The data set consisted of a total of 145,961 BW recorded from 15,386 animals. Even though the curve parameters were estimated for animals with few records, given that the information from related animals and the structure of systematic effects were considered in the curve fitting, all mature BW predicted were suitable. A large additive genetic variance for mature BW was observed. The parameter a of growth curves, which represents asymptotic adult BW, could be used as a selection criterion to control increases in adult BW when selecting for growth rate. The effect of maternal environment on growth was carried through to maturity and should be considered when evaluating adult BW. Other growth curve parameters showed small additive genetic and maternal effects. Mature BW and parameter k, related to the slope of the curve, presented a large, positive genetic correlation. The results indicated that selection for growth rate would increase adult BW without substantially changing the shape of the growth curve. Selection to change the slope of the growth curve without modifying adult BW would be inefficient because their genetic correlation is large. However, adult BW could be considered in a selection index with its corresponding economic weight to improve the overall efficiency of beef cattle production.
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The objectives of the current study were to assess the feasibility of using stayability traits to improve fertility of Nellore cows and to examine the genetic relationship among the stayabilities at different ages. Stayability was defined as whether a cow calved every year up to the age of 5 (Stay5), 6 (Stay6), or 7 (Stay7) yr of age or more, given that she was provided the opportunity to breed. Data were analyzed based on a maximum a posteriori probit threshold model to predict breeding values on the liability scale, whereas the Gibbs sampler was used to estimate variance components. The EBV were obtained using all animals included in the pedigree or bulls with at least 10 daughters with stayability observations, and average genetic trends were obtained in the liability and transformed to the probability scale. Additional analyses were performed to study the genetic relationship among stayability traits, which were compared by contrasting results in terms of EBV and the average genetic superiority as a function of the selected proportion of sires. Heritability estimates and SD were 0.25 +/- 0.02, 0.22 +/- 0.03, and 0.28 +/- 0.03 for Stay5, Stay6, and Stay7, respectively. Average genetic trends, by year, were 0.51 +/- 0.34, and 0.38% for Stay5, Stay6, and Stay7, respectively. Estimates of EBV SD, in the probability scale, for all animals included in the pedigree and for bulls with at least 10 daughters with stayability observations were 7.98 and 12.95, 6.93 and 11.38, and 8.24 and 14.30% for Stay5, Stay6, and Stay7, respectively. A reduction in the average genetic superiorities in Stay7 would be expected if the selection were based on Stay5 or Stay6. Nonetheless, the reduction in EPD, depending on selection intensity, is on average 0.74 and 1.55%, respectively. Regressions of the sires' EBV for Stay5 and Stay6 on the sires' EBV for Stay7 confirmed these results. The heritability and genetic trend estimates for all stayability traits indicate that it is possible to improve fertility with selection based on a threshold analysis of stayability. The SD of EBV for stayability traits show that there is adequate genetic variability among animals to justify inclusion of stayability as a selection criterion. The potential linear relationship among stayability traits indicates that selection for improved female traits would be more effective by having predictions on the Stay5 trait.
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Variance dispersion graphs have become a popular tool in aiding the choice of a response surface design. Often differences in response from some particular point, such as the expected position of the optimum or standard operating conditions, are more important than the response itself. We describe two examples from food technology. In the first, an experiment was conducted to find the levels of three factors which optimized the yield of valuable products enzymatically synthesized from sugars and to discover how the yield changed as the levels of the factors were changed from the optimum. In the second example, an experiment was conducted on a mixing process for pastry dough to discover how three factors affected a number of properties of the pastry, with a view to using these factors to control the process. We introduce the difference variance dispersion graph (DVDG) to help in the choice of a design in these circumstances. The DVDG for blocked designs is developed and the examples are used to show how the DVDG can be used in practice. In both examples a design was chosen by using the DVDG, as well as other properties, and the experiments were conducted and produced results that were useful to the experimenters. In both cases the conclusions were drawn partly by comparing responses at different points on the response surface.
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Heat capacities of binary aqueous solutions of different concentrations of sucrose, glucose, fructose, citric acid, malic acid, and inorganic salts were measured with a differential scanning calorimeter in the temperature range from 5degreesC to 65degreesC. Heat capacity increased with increasing water content and increasing temperature. At low concentrations, heat capacity approached that of pure water, with a less pronounced effect of temperature, and similar abnormal behavior of pure water with a minimum around 30degreesC-40degreesC. Literature data, when available agreed relatively well with experimental values. A correction factor, based on the assumption of chemical equilibrium between liquid and gas phase in the Differential Scanning Calorimeter, was proposed to correct for the water evaporation due to temperature rise. Experimental data were fitted to predictive models. Excess molar heat capacity was calculated using the Redlich-Kister equation to represent the deviation from the additive ideal model.
Assessing the uncertainties of model estimates of primary productivity in the tropical Pacific Ocean
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Depth-integrated primary productivity (PP) estimates obtained from satellite ocean color-based models (SatPPMs) and those generated from biogeochemical ocean general circulation models (BCGCMs) represent a key resource for biogeochemical and ecological studies at global as well as regional scales. Calibration and validation of these PP models are not straightforward, however, and comparative studies show large differences between model estimates. The goal of this paper is to compare PP estimates obtained from 30 different models (21 SatPPMs and 9 BOGCMs) to a tropical Pacific PP database consisting of similar to 1000 C-14 measurements spanning more than a decade (1983-1996). Primary findings include: skill varied significantly between models, but performance was not a function of model complexity or type (i.e. SatPPM vs. BOGCM); nearly all models underestimated the observed variance of PR specifically yielding too few low PP (< 0.2 g Cm-2 d(-1)) values; more than half of the total root-mean-squared model-data differences associated with the satellite-based PP models might be accounted for by uncertainties in the input variables and/or the PP data; and the tropical Pacific database captures a broad scale shift from low biomassnormalized productivity in the 1980s to higher biomass-normalized productivity in the 1990s, which was not successfully captured by any of the models. This latter result suggests that interdecadal and global changes will be a significant challenge for both SatPPMs and BOGCMs. Finally, average root-mean-squared differences between in situ PP data on the equator at 140 degrees W and PP estimates from the satellite-based productivity models were 58% lower than analogous values computed in a previous PP model comparison 6 years ago. The success of these types of comparison exercises is illustrated by the continual modification and improvement of the participating models and the resulting increase in model skill. (C) 2008 Elsevier BY. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The effect of increasing phosphorus (P) intake on P utilization was investigated in balance experiments using 12 Saanen goats, 4 to 5 mo of age and weighing 20 to 30 kg. The goats were given similar diets with various concentrations of P, and 32P was injected to trace the movement of P in the body. A P metabolism model with four pools was developed to compute P exchanges in the system. The results showed that P absorption, bone resorption, and excretion of urinary P and endogenous and fecal P all play a part in the homeostatic control of P. Endogenous fecal output was positively correlated to P intake (P < .01). Bone resorption of P was not influenced by intake of P, and P recycling from tissues to the blood pool was lesser for low P intake. Endogenous P loss occurred even in animals fed an inadequate P diet, resulting in a negative P balance. The extrapolated minimum endogenous loss in feces was .067 g of P/d. The minimum P intake for maintenance in Saanen goats was calculated to be .61 g of P/ d or .055 g of P/(kg.75·d) at 25 kg BW. Model outputs indicate greater P flow from the blood pool to the gut and vice versa as P intake increased. Intake of P did not significantly affect P flow from bone and soft tissue to blood. The kinetic model and regressions could be used to estimate P requirement and the fate of P in goats and could also be extrapolated to both sheep and cattle.
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Heterogeneity of variances for milk yield (MY) was determined for Brazilian and Colombian herds. The herds were grouped as high or low variability within each country, using as criterion the phenotypic standard deviation (PSD) of MY in the contemporary groups of cows, from the first to the sixth calving. Brazilian and Colombian herds with PSD greater than 1,168 kg or 1,012 kg, respectively, were classified as high variability while the herd groups with values lower than those were classified as low variability. The genetic parameters for MY within each herd group were estimated using bivariate analysis in an animal model and the restricted maximum likelihood method with a derivative free algorithm, using 72,280 first lactations of cows, daughters of 1,880 sires. Heterogeneous variances were found, and Brazilian herds with high PSD had the greatest additive and residual genetic variances and heritability coefficients for MY. MY genetic correlation coefficients between herds of high and low variability within each country were 0.96 and 0.93 while between countries they varied from 0.72 to 0.81, suggesting that there was a reclassification of animals in the two countries and also heterogeneity of variances. This phenomenon leads to the questioning of the strategy of imported semen usage and the need to do genetic evaluations to identify sires with greater genetic potential for (sub) tropical environmental conditions.