71 resultados para Dispersive Estimates


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The global radiation incident on a tilted surfaces consists of components direct, diffuse and reflected from the ground. On a hourly database, the direct radiation can be calculated by geometric projections (ratio of the incidence angle to the solar zenith angle). The reflected radiation has a small effect on calculations and may be calculated with an isotropic model. Both components presents dependence of measures in incidence or horizontal surface. The great difficulty is to evaluate the diffuse radiation by variations of circumsolar, brightness horizontal, isotropic and anisotropic subcomponents. This study evaluated twenty models to estimate hourly diffuse radiation incident on tilted surfaces at 12.85° (latitude - 10°), 22.85° (latitude) and 32.85° (latitude + 10°) facing to North, under different cloudiness sky conditions, in Botucatu, São Paulo State, Brazil (22°53' S, 48°26' W and 786 m above the mean sea level). In contrast, models for estimating the diffuse component show major differences, which justify the validation for local calibrations. There is a decrease of the maximum total radiation scattered with increasing atmospheric transmissivity and inclination angle. The best results are obtained by anisotropic models: Ma and Iqbal, Hay, Reindl et al. and Willmott; isotropic: Badescu and Koronakis, and the Circumsolar model. The increase of the inclination angle allows for a reduction in the performance of statistical parametric models for estimating the hourly diffuse radiation.

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The objective of this study was to estimate genetic parameters for milk yield at 244 days and lactation length in graded buffalo cows at the El Cangre Cattle Genetic Enterprise. Data were gathered from 2575 lactations, 1377 buffalo cows, 37 milking units and between 2002-2009 calving years. It was employed the Restricted Maximum Likelihood method (REML) for estimating (co) variance components with multi trait model. Average of milk yield at 244 days and lactation length were 864 kg and 240 days, respectively. Heritability was 0.15 for milk yield and 0.13 for lactation length. Genetic correlation between these traits was 0.63. It was concluded that it is necessary to intensify selection and to increase control of the information of the genetic herds to obtain high precision in the estimates and therefore, obtain bigger genetic progress in of this species in our country.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The objective of this study was to estimate variance components and genetic parameters for accumulated 305-day milk yield (MY305) over multiple ages, from 24 to 120 months of age, applying random regression (RRM), repeatability (REP) and multi-trait (MT) models. A total of 4472 lactation records from 1882 buffaloes of the Murrah breed were utilized. The contemporary group (herd-year-calving season) and number of milkings (two levels) were considered as fixed effects in all models. For REP and RRM, additive genetic, permanent environmental and residual effects were included as random effects. MT considered the same random effects as did REP and RRM with the exception of permanent environmental effect. Residual variances were modeled by a step function with 1, 4, and 6 classes. The heritabilities estimated with RRM increased with age, ranging from 0.19 to 0.34, and were slightly higher than that obtained with the REP model. For the MT model, heritability estimates ranged from 0.20 (37 months of age) to 0.32 (94 months of age). The genetic correlation estimates for MY305 obtained by RRM (L23.res4) and MT models were very similar, and varied from 0.77 to 0.99 and from 0.77 to 0.99, respectively. The rank correlation between breeding values for MY305 at different ages predicted by REP, MT, and RRM were high. It seems that a linear and quadratic Legendre polynomial to model the additive genetic and animal permanent environmental effects, respectively, may be sufficient to explain more parsimoniously the changes in MY305 genetic variation with age.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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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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A novel, simple, rapid and eco-friendly method based on dispersive liquid-liquid microextraction using a bromosolvent was developed to determine six estrogenic mycotoxins (zearalenone, zearalanone, alpha-zearalanol, beta-zearalanol, alpha-zearalenol and beta-zearalenol) in water samples by liquid chromatography-electrospray ionization tandem mass spectrometry in the negative mode (LC-ESI-MS/MS). The optimal conditions for this method include the use of 100 mu L bromocyclohexane as an extraction solvent (using a non-dispersion solvent), 10 mL of aqueous sample (adjusted to pH 4), a vortex extraction time of 2 min, centrifugation for 10 min at 3500 rpm and no ionic strength adjustment. The calibration function was linear and was verified by applying the Mandel fitting test with a 95% confidence level. No matrix effect was observed. According to the relative standard deviations (RSDs), the precision was better than 13% for the repeatability and intermediate precision. The average recoveries of the spiked compounds ranged from 81 to 118%. The method limits of detection (LOD) and quantification (LOQ) considering a 125-fold pre-concentration step were 4-20 and 8-40 ng L-1, respectively. Next, the method was applied to the analysis of the environmental aqueous samples, demonstrating the presence of beta-zearalanol and zearalanone in the river water samples. (C) 2015 Elsevier B.V. All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Weight records of Brazilian Nelore cattle, from birth to 630 d of age, recorded every 3 mo, were analyzed using random regression models. Independent variables were Legendre polynomials of age at recording. The model of analysis included contemporary groups as fixed effects and age of dam as a linear and quadratic covariable. Mean trends were modeled through a cubic regression on orthogonal polynomials of age. Up to four sets of random regression coefficients were fitted for animals' direct and maternal, additive genetic, and permanent environmental effects. Changes in measurement error variances with age were modeled through a variance function. Orders of polynomial fit from three to six were considered, resulting in up to 77 parameters to be estimated. Models fitting random regressions modeled the pattern of variances in the data adequately, with estimates similar to those from corresponding univariate analysis. Direct heritability estimates decreased after birth and tended to be lowest at ages at which maternal effect estimates tended to be highest. Maternal heritability estimates increased after birth to a peak around 110 to 120 d of age and decreased thereafter. Additive genetic direct correlation estimates between weights at standard ages (birth, weaning, yearling, and final weight) were moderate to high and maternal genetic and environmental correlations were consistently high.

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Background The application and better understanding of traditional and new breast tumor biomarkers and prognostic factors are increasing due to the fact that they are able to identify individuals at high risk of breast cancer, who may benefit from preventive interventions. Also, biomarkers can make possible for physicians to design an individualized treatment for each patient. Previous studies showed that trace elements (TEs) determined by X-Ray Fluorescence (XRF) techniques are found in significantly higher concentrations in neoplastic breast tissues (malignant and benign) when compared with normal tissues. The aim of this work was to evaluate the potential of TEs, determined by the use of the Energy Dispersive X-Ray Fluorescence (EDXRF) technique, as biomarkers and prognostic factors in breast cancer. Methods By using EDXRF, we determined Ca, Fe, Cu, and Zn trace elements concentrations in 106 samples of normal and breast cancer tissues. Cut-off values for each TE were determined through Receiver Operating Characteristic (ROC) analysis from the TEs distributions. These values were used to set the positive or negative expression. This expression was subsequently correlated with clinical prognostic factors through Fisher’s exact test and chi-square test. Kaplan Meier survival curves were also evaluated to assess the effect of the expression of TEs in the overall patient survival. Results Concentrations of TEs are higher in neoplastic tissues (malignant and benign) when compared with normal tissues. Results from ROC analysis showed that TEs can be considered a tumor biomarker because, after establishing a cut-off value, it was possible to classify different tissues as normal or neoplastic, as well as different types of cancer. The expression of TEs was found statistically correlated with age and menstrual status. The survival curves estimated by the Kaplan-Meier method showed that patients with positive expression for Cu presented a poor overall survival (p < 0.001). Conclusions This study suggests that TEs expression has a great potential of application as a tumor biomarker, once it was revealed to be an effective tool to distinguish different types of breast tissues and to identify the difference between malignant and benign tumors. The expressions of all TEs were found statistically correlated with well-known prognostic factors for breast cancer. The element copper also showed statistical correlation with overall survival.