948 resultados para Random Coefficient Autoregressive Model{ RCAR (1)}
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Fluorescence diagnosis of malignant lesions has been showed as an attractive optical technique due especially to its real-time response and a more objective and quantitative evaluation. Even though the oral cavity allows a direct examination many lesions are diagnosed when it is already in advanced stage, compromising the patient prognosis. In this study, the fluorescence spectroscopy was used to the detection of chemically induced carcinoma at the lateral border of the tongue in a hamster model. Two excitations wavelengths in visible region were applied: 442 and 532 nm. All the spectra results were analyzed comparing with the histopathological diagnosis. The better results were achieved with the 442 nm laser excitation. The spectra from carcinoma showed new emission bands and these were used to determined different ratios for a quantitative analysis. Using the 625-645 nm fluorescence range under 442 nm excitation (A3 coefficient) the percentage of false negative was of 9.1%, however the false positive percentage was of 18.5%. The 532 nm excitation provided a better normal tissue detection compared to 442 nm excitation. The ideal clinical condition is probably the use of multiple wavelengths excitation for a broader tissue fluorescence investigation.
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We report results from a search for neutral Higgs bosons produced in association with b quarks using data recorded by the D0 experiment at the Fermilab Tevatron Collider and corresponding to an integrated luminosity of 7.3fb-1. This production mode can be enhanced in several extensions of the standard model (SM) such as in its minimal supersymmetric extension (MSSM) at high tan β. We search for Higgs bosons decaying to tau pairs with one tau decaying to a muon and neutrinos and the other to hadrons. The data are found to be consistent with SM expectations, and we set upper limits on the cross section times branching ratio in the Higgs boson mass range from 90 to 320GeV/c2. We interpret our result in the MSSM parameter space, excluding tan β values down to 25 for Higgs boson masses below 170GeV/c2. © 2011 American Physical Society.
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The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.
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We present a search for the standard model (SM) Higgs boson produced in association with a Z boson in 9.7fb -1 of pp̄ collisions collected with the D0 detector at the Fermilab Tevatron Collider at √s=1.96TeV. Selected events contain one reconstructed Z→e +e - or Z→μ +μ - candidate and at least two jets, including at least one jet identified as likely to contain a b quark. To validate the search procedure, we also measure the cross section for ZZ production in the same final state. It is found to be consistent with its SM prediction. We set upper limits on the ZH production cross section times branching ratio for H→bb̄ at the 95% C.L. for Higgs boson masses 90≤M H≤150GeV. The observed (expected) limit for M H=125GeV is 7.1 (5.1) times the SM cross section. © 2012 American Physical Society.
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We present a search for the standard model Higgs boson in final states with a charged lepton (electron or muon), missing transverse energy, and two or three jets, at least one of which is identified as a b-quark jet. The search is primarily sensitive to WH→ νbb̄ production and uses data corresponding to 9.7fb -1 of integrated luminosity collected with the D0 detector at the Fermilab Tevatron pp̄ Collider at √s=1.96TeV. We observe agreement between the data and the expected background. For a Higgs boson mass of 125 GeV, we set a 95% C.L. upper limit on the production of a standard model Higgs boson of 5.2×σ SM, where σ SM is the standard model Higgs boson production cross section, while the expected limit is 4.7×σ SM. © 2012 American Physical Society.
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The urea effect on the giant extracellular hemoglobin of Glossoscolex paulistus (HbGp) stability was studied by analytical ultracentrifugation (AUC) and small angle X-ray scattering (SAXS). AUC data show that the sedimentation coefficient distributions curves c (S), at 1.0mol/L of urea, display a single peak at 57 S, associated to the undissociated protein. The increase in urea concentration, up to 4.0mol/L, induces the appearance of smaller species, due to oligomeric dissociation. The sedimentation coefficients and molecular masses are 9.2S and 204kDa for the dodecamer (abcd)3, 5.5S and 69kDa for the tetramer (abcd), 4.1S and 52kDa for the trimer (abc) and 2.0 S and 17kDa for the monomer d, respectively. SAXS data show initially a decrease in the I(0) values due to the oligomeric dissociation, and then, above 4.0mol/L of denaturant, for oxy-HbGp, and above 6.0mol/L for cyanomet-HbGp, an increase in the maximum dimension and gyration radius is observed, due to the unfolding process. According to AUC and SAXS data the HbGp unfolding is described by two phases: the first one, at low urea concentration, below 4.0mol/L, characterizes the oligomeric dissociation, while the second one, at higher urea concentration, is associated to the unfolding of dissociated species. Our results are complementary to a recent report based on spectroscopic observations. © 2012 Elsevier B.V.
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Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.
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Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data. © FUNPEC-RP.
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Type I diabetes is a disease caused by autoimmune destruction of the beta cells in the pancreas that leads to a deficiency in insulin production. The aim of this study was to evaluate the prophylactic potential of a prime-boost strategy involving bacille Calmette-Guérin (BCG) and the pVAXhsp65 vaccine (BCG/DNAhsp65) in diabetes induced by streptozotocin (STZ) in C57BL/6 mice and also in spontaneous type 1 diabetes in non-obese diabetic (NOD) mice. BCG/DNAhsp65 vaccination in NOD mice determined weight gain, protection against hyperglycaemia, decreased islet inflammation, higher levels of cytokine production by the spleen and a reduced number of regulatory T cells in the spleen compared with non-immunized NOD mice. In the STZ model, however, there was no significant difference in the clinical parameters. Although this vaccination strategy did not protect mice in the STZ model, it was very effective in NOD mice. This is the first report demonstrating that a prime-boost strategy could be explored as an immunomodulatory procedure in autoimmune diseases. © 2013 British Society for Immunology.
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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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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 Agronomia (Energia na Agricultura) - FCA
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Odontologia - FOA