111 resultados para Random coefficient logit (RCL) model

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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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 correct selection of the operational sequence of soil tillage is essential to reduce the cost of agricultural mechanization in the regions that mobilize intensively the soil. The objective of this work was to evaluate the energetic demand and disaggregation of the soil in different operational sequences of subsoiling and systems of periodic soil tillage. The experimental design was blocks at random, in a factorial model 5 x 2 with 5 replications, being 5 tillage systems (D - Disc plow, Dn - disc plow followed at leveler rail, G - weight rail, Gn - weight rail followed of leveler rail and E - Stirrer.) and two sequencies of subsoiling (SP - Subsoiling - tillage and PS - Tillage - subsoiling). There were evaluated the energetic demand, fuel consumption by area and the soil disaggregation. The results showed that the operational sequence tillage of the soil subsoiling (PS) had a lower energetic requirement, except for the stirrer, the sequence tillage the soil - subsoiling consumed less fuel and soil disaggregation didn't show statistic variation.

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The aims of this study were (a) to assess the ability of the rating of perceived exertion (RPE) to predict performance (i.e. number of vertical jumps performed to a fixed jump height) of an intermittent vertical jump exercise, and (b) to determine the ability of RPE to describe the physiological demand of such exercise. Eight healthy men performed intermittent vertical jumps with rest periods of 4, 5, and 6s until fatigue. Heart rate and RPE were recorded every five jumps throughout the sessions. The number of vertical jumps performed was also recorded. Random coefficient growth curve analysis identified relationships between the number of vertical jumps and both RPE and heart rate for which there were similar slopes. In addition, there were no differences between individual slopes and the mean slope for either RPE or heart rate. Moreover, RPE and number of jumps were highly correlated throughout all sessions (r=0.97-0.99; P0.001), as were RPE and heart rate (r=0.93-0.97; P0.001). The findings suggest that RPE can both predict the performance of intermittent vertical jump exercise and describe the physiological demands of such exercise.

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Understanding the microscopic origin of the dielectric properties of disordered materials has been a challenge for many years, especially in the case of samples with more than one phase. For polar dielectrics, for instance, the Lepienski approach has indicated that the random free energy barrier model of Dyre must be extended. Here we analyse the dielectric properties of a polymer blend made up with the semiconducting poly(o-methoxyaniline) and poly( vinylidene fluoride-trifluorethylene) POMA/P(VDF-TrFE), and of a hybrid composite of POMA/P(VDF-TrFE)/Zn2SiO4:Mn. For the blend, the Lepienski model, which takes into account the rotation or stretching of electric dipoles, provided excellent fitting to the ac impedance data. Because two phases had to be assumed for the hybrid composite, we had to extend the Lepienski model to fit the data, by incorporating a second transport mechanism. The two mechanisms were associated with the electronic transport in the polymeric matrix and with transport at the interfaces between Zn2SiO4: Mn microparticles and the polymeric matrix, with the relative importance of the interfacial component increasing with the percentage of Zn2SiO4: Mn in the composite. The analysis of impedance data at various temperatures led to a prediction of the theoretical model of a change in morphology at 190 +/- 40 K, and this was confirmed experimentally with a differential scanning calorimetry experiment.

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The alternating conductivity, sigma*(f) = sigma'(f) + i sigma ''(f), of in situ polymerized polyaniline thin films doped with hydrochloric acid, deposited on top of an interdigitated gold line array previously deposited on glass substrates, were measured in the frequency (f) range between 0.1 Hz to 10 MHz and in the temperature range from 100 to 430 K. The results for sigma'(f) are typical of a disordered solid material: for frequencies lower than a certain hopping frequency gamma(hop), log[sigma'(f)] is frequency-independent rising almost linearly for in logf > gamma(hop). A master curve was thus obtained by plotting the real component of the conductivity using normalized scales sigma'(f)/sigma(dc) and f/gamma(hop) which is indicative of a single process operating in the whole frequency range. An expression encompassing the conduction through a disordered structure taken from previous random free energy barrier model for hopping carriers, as well a dielectric function to represent the capacitive behavior of the PAni was employed to fit the experimental results. The dielectric constant and activation energy for hopping carriers were obtained as function of the polymer doping level. (c) 2007 Elsevier B.V. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Engenharia Mecânica - FEG

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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Pós-graduação em Matematica Aplicada e Computacional - FCT

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Knowing the genetic parameters of productive and reproductive traits in milking buffaloes is essential for planning and implementing of a program genetic selection. In Brazil, this information is still scarce. The objective of this study was to verify the existence of genetic variability in milk yield of buffaloes and their constituents, and reproductive traits for the possibility of application of the selection. A total of 9,318 lactations records from 3,061 cows were used to estimate heritabilities for milk yield (MY), fat percentage (%F), protein percentage (%P), length of lactation (LL), age of first calving (AFC) and calving interval (CI) and the genetic correlations among traits MY, %F and %P. The (co) variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year and calving season), number of milking (2 levels), and age of cow at calving as (co) variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. Estimated heritability values for MY, % F, % P, LL, AFC and CI were 0.24, 0.34, 0.40, 0.09, 0.16 and 0.05, respectively. The genetic correlation estimates among MY and % F, MY and % P and % F and % P were -0.29, -0.18 and 0.25, respectively. The production of milk and its constituents showed enough genetic variation to respond to a selection program. Negative estimates of genetic correlations between milk production and its components suggest that selection entails a reduction in the other.

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The use of markers distributed all long the genome may increase the accuracy of the predicted additive genetic value of young animals that are candidates to be selected as reproducers. In commercial herds, due to the cost of genotyping, only some animals are genotyped and procedures, divided in two or three steps, are done in order to include these genomic data in genetic evaluation. However, genomic evaluation may be calculated using one unified step that combines phenotypic data, pedigree and genomics. The aim of the study was to compare a multiple-trait model using only pedigree information with another using pedigree and genomic data. In this study, 9,318 lactations from 3061 buffaloes were used, 384 buffaloes were genotyped using a Illumina bovine chip (Illumina Infinium (R) bovineHD BeadChip). Seven traits were analyzed milk yield (MY), fat yield (FY), protein yield (PY), lactose yield (LY), fat percentage (F%), protein percentage (P%) and somatic cell score (SCSt). Two analyses were done: one using phenotypic and pedigree information (matrix A) and in the other using a matrix based in pedigree and genomic information (one step, matrix H). The (co) variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year-calving season), number of milking (2 levels), and age of buffalo at calving as (co) variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. The heritability estimates using matrix A were 0.25, 0.22, 0.26, 0.17, 0.37, 0.42 and 0.26 and using matrix H were 0.25, 0.24, 0.26, 0.18, 0.38, 0.46 and 0.26 for MY, FY, PY, LY, % F, % P and SCCt, respectively. The estimates of the additive genetic effect for the traits were similar in both analyses, but the accuracy were bigger using matrix H (superior to 15% for traits studied). The heritability estimates were moderated indicating genetic gain under selection. The use of genomic information in the analyses increases the accuracy. It permits a better estimation of the additive genetic value of the animals.

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This study aimed to evaluate the potential for milk production (MP), lactation length (LL) and calving interval (CI), analyze the environmental component affecting these traits, and to estimate the heritability and repeatability for milk production in crossbreds of Murrah buffalo cows in the state of Alagoas, Brazil. Data was composed of 487 observations of MP from 136 lactations recorded between the years of 2000 and 2010. In the analysis of variance for PL, the fixed effects were season (1- October to March, 2 -April to September) and year of the beginning of lactation, calving order and the LL (covariate). For the analysis of LL only the fixed effect of year of the beginning of lactation was included, and finally for the CI analysis, year of the beginning of lactation and calving order. The estimates of covariance were obtained using unicharacteristic analysis by Bayesian inference method, applyingan animal model, through Gibbs sampling. The additive genetic, permanent environment and residual effects were included as random effects in the model. The averages (sd) of MP, LL and CI were 2,218.03 kg (408.18), 282.59 days (39.48) e 422.49 days (91.05), respectively. All the effects included in the models were important (P<0.01). The estimates of heritability and repeatability for PL were 0.29 and 0.69, respectively. The results suggest that there is a moderate genetic variability among individuals for PL, indicating the possibility to obtain gain using selection.