960 resultados para 3 Models
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The viability of achieving gravitational consistent braneworld models in the framework of a f(R) theory of gravity is investigated. After a careful generalization of the usual junction conditions encompassing the embedding of the 3-brane into a f(R) bulk, we provide a prescription giving the necessary constraints in order to implement the projected second-order effective field equations on the brane. © 2013 American Physical Society.
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The objective of this research was the preparation of a silica gel functionalized successively with 3-chloropropyltrimethoxysilane (SG-PrCl) and thiourea (SG-Pr-THIO), and its application in adsorption and catalysis. The materials were characterized by 13C and 29Si NMR, FTIR, scanning electron micrographs (SEM), analysis of nitrogen and elemental analysis. Aiming at its application in adsorption, the [3-(thiourea)-propyl] silica gel (SG-Pr-THIO) was tested as an adsorbent for transition-metal ions using a batchwise process. The organofunctionalized surface showed the ability to adsorb the metal ions Cd(ii), Cu(ii), Ni(ii), Pb(ii) and Co(ii) from water, ethanol and acetone. The adsorption isotherms were fitted by Langmuir, Freundlich, Temkin and Dubinin-Radushkevich (D-R) models. The kinetics of adsorption of metals were performed using three models such as pseudo-first order, pseudo-second order and Elovich. The Langmuir and pseudo-first order models were the most appropriate to describe the adsorption and kinetic data, respectively. With the purpose of application in catalysis, the SG-Pr-THIO was reacted with a Mo(ii) organometallic complex, forming the new material SG-Pr-THIO-Mo. Only a few works in the literature have reported this type of reaction, and none dealt with thiourea and Mo(ii) complexes. The new Mo-silica gel organometallic material was tested as catalyst in the epoxidation of cyclooctene and styrene. © 2013 The Royal Society of Chemistry and the Centre National de la Recherche Scientifique.
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Searches are reported for Higgs bosons in the context of either the standard model extended to include a fourth generation of fermions (SM4) with masses of up to 600 GeV or fermiophobic models. For the former, results from three decay modes (ττ, WW, and ZZ) are combined, whilst for the latter the diphoton decay is exploited. The analysed proton-proton collision data correspond to integrated luminosities of up to 5.1 fb-1 at 7 TeV and up to 5.3 fb-1 at 8 TeV. The observed results exclude the SM4 Higgs boson in the mass range 110-600 GeV at 99% confidence level (CL), and in the mass range 110-560 GeV at 99.9% CL. A fermiophobic Higgs boson is excluded in the mass range 110-147 GeV at 95% CL, and in the range 110-133 GeV at 99% CL. The recently observed boson with a mass near 125 GeV is not consistent with either an SM4 or a fermiophobic Higgs boson. © 2013 CERN.
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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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Grinding is a workpiece finishing process for advanced products and surfaces. However, the constant friction between workpiece and grinding wheel causes the latter to lose its sharpness, thereby impairing the result of the grinding process. When this occurs, the dressing process is essential to sharpen the worn grains of the grinding wheel. The dressing conditions strongly influence the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The purpose of this study was to classify the wear condition of a single-point dresser using intelligent systems whose inputs were obtained by digitally processing acoustic emission signals. Two multilayer perceptron (MLP) neural networks were compared for their classification ability, one using the root mean square (RMS) statistics and another the ratio of power (ROP) statistics as input. In this study, it was found that the harmonic content of the acoustic emission signal is influenced by the condition of the dresser, and that the condition of the tool under study can be classified by using the aforementioned statistics to feed a neural network. © IFAC.
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We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields. © FUNPEC-RP.
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Pós-graduação em Ciências Cartográficas - FCT
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Includes bibliography
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Pós-graduação em Biologia Geral e Aplicada - IBB
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Ciência e Tecnologia de Materiais - FC
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Pós-graduação em Odontologia - FOAR
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Pós-graduação em Física - FEG