Preprocessing data for short-term load forecasting with a general regression neural network and a moving average filter

This paper proposes a filter based on a general regression neural network and a moving average filter, for preprocessing half-hourly load data for short-term multinodal load forecasting, discussed in another paper. Tests made with half-hourly load data from nine New Zealand electrical substations demonstrate that this filter is able to handle noise, missing data and abnormal data. © 2011 IEEE.

Short-term multinodal load forecasting in distribution systems using general regression neural networks

Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, trustable and has a short-time processing. This paper proposes two methodologies based on general regression neural networks for short-term multinodal load forecasting. The first individually forecast the local loads and the second forecast the global load and individually forecast the load participation factors to estimate the local loads. To design the forecasters it wasn't necessary the previous study of the local loads. Tests were made using a New Zealand distribution subsystem and the results obtained are compatible with the ones founded in the specialized literature. © 2011 IEEE.

Supplementation of diets for Santa Ines sheep with organic and inorganic zinc sources

This research was conducted with objective to evaluate the effect of different zinc (Zn) sources and doses in the diet for Santa Ines sheep. Forty lambs at weaning, with 18.4 kg of body weight were supplemented with three different sources of zinc (zinc oxide (ZnO), zinc amino acid and zinc proteinate) and three doses of zinc (200, 400 and 600 mg/kg DM) added to the basal diet. At every 28 days, animals were weighted and blood samples were collected for analyses of zinc (Zn), alkaline phosphatase and immunoglobulin G (IgG) and M (IgM). At the end of experiment, liver samples were collected for determination of the hepatic zinc levels. Zinc was analyzed with atomic absorption spectrophotometer, while phosphatase alkaline and immunoglobulins G and M were analyzed using Laborlab and Bioclin kits, respectively. There was no effect of diets on phosphatase alkaline levels and hepatic zinc, but there was difference in the plasmatic zinc levels and IgG and IgM levels. Based on the accumulation of hepatic zinc, the estimate of the zinc bioavailability, through the regression equation, showed that supplementation with organic and inorganic sources of zinc did not differ in the diet of Santa Ines sheep. © 2012 Sociedade Brasileira de Zootecnia.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

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.

Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

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.

Genetic evaluation using multi-trait and random regression models in Simmental beef cattle

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.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

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.

Suscetibilidade magnética do solo e estimação da capacidade de suporte à aplicação de vinhaça

The objective of this work was to evaluate the magnetic susceptibility efficiency for estimating the support capacity of areas for vinasse application. Two hundred forty-one soil samples were collected from a 380-ha area, on which soil chemical properties, clay content, and magnetic susceptibility were determined. Vinasse requirement was calculated for each sample. Data were subjected to descriptive statistical analysis, and regression models were developed between magnetic susceptibility and the other evaluated attributes. The analysis of data spatial dependence was performed using geostatistics. Kriging maps and cross variograms were built in order to investigate the spatial correlation between soil magnetic susceptibility and studied attributes. Based on the map of vinasse requirement, on the soil classes, and on the kriging map, calculations were done for average vinasse dose and average soil support capacity, weighted by the area. Magnetic susceptibility has significant linear spatial correlation with recommended vinasse doses and soil support capacity for the application of this effluent, and it can be used as a pedotransfer function for indirect quantification of soil support capacity.

Comparação entre três critérios de amostragem para a avaliação da densidade básica da madeira de florestas implantadas de eucaliptos

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

Aplicação de biomassa de Rubrivivax gelatinosus na ração de frangos de corte: desempenho animal e caracteristicas dos produtos

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

Crescimento relativo e composição do ganho de tecidos na carcaça de bubalinos mediterrâneos jovens abatidos com diferentes pesos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Deficiência auditiva referida por idosos do município de São Paulo (Estudo SABE): prevalência, incidência e fatores associados. -

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Uso de aparelho de amplificação sonora individual por idosos: estudo SABE - saúde, bem- estar e envelhecimento

PURPOSE: Describe hearing aid use by the elderly population in the city of São Paulo and identify associated factors. METHODS: A cross-sectional, descriptive, quantitative study integrated with the SABE (health, well-being and aging) project developed in 2006. A total of 1.115 individuals aged 65 or over were interviewed. Sample selection occurred in two stages, with replacement and probabilities proportional to the population to complement those aged 75 or over. Structured questionnaires and validated instruments were used. The data were weighted, the Rao-Scott test was used for univariate analysis and backward stepwise logistic regression was used for multivariate analysis, performed on Stata 10® software. RESULTS: Three hundred and seventy-seven subjects (30.4%) were classified as hearing impaired and 10.1% of these reported using hearing aids. To acquire the devices, 78.8% used their own resources and 16.9% acquired them through the Brazilian public health system (SUS). Among non-users of hearing aids, 16.6% reported prior indication; however, 8.6% were unable to adapt to the device and 8.0% could not afford to acquire one. Hearing aid use was associated with lower prevalence of probable dementia. CONCLUSION: The low number of hearing aid users indicates the difficulties elderly people face in acquiring them and/or that the health services face in effectively helping them to adapt. These findings may influence the quality of life of elderly with hearing impairment, given the association with probable dementia revealed by this study.

Genetic parameters for body weight in buffaloes (Bubalus bubalis) in Colombia using random regression models

The objective of this research was to estimate (co) variance functions and genetic parameters for body weight in Colombian buffalo populations using random regression models with Legendre polynomials. Data consisted of 34,738 weight records from birth to 900 days of age from 7815 buffaloes. Fixed effects in the model were contemporary group and parity order of the mother. Random effects were direct and maternal additive genetic, as well as animal and maternal permanent environmental effects. A cubic orthogonal Legendre polynomial was used to model the mean curve of the population. Eleven models with first to sixth order polynomials were used to describe additive genetic direct and maternal effects, and animal and maternal permanent environmental effects. The residual was modeled considering five variance classes. The best model included fourth and sixth order polynomials for direct additive genetic and animal permanent environmental effects, respectively, and third-order polynomials for maternal genetic and maternal permanent environmental effects. The direct heritability increased from birth until 120 days of age (0.32 +/- 0.05), decreasing thereafter until one year of age (0.18 +/- 0.04) and increased again, reaching 0.39 +/- 0.09, at the end of the evaluated period. The highest maternal heritability estimates (0.11 +/- 0.05), were obtained for weights around weaning age (weaning age range is between 8 and 9.5 months). Maternal genetic and maternal permanent environmental variances increased from birth until about one year of age, decreasing at later ages. Direct genetic correlations ranged from moderate (0.60 +/- 0.060) to high (0.99 +/- 0.001), maternal genetic correlations showed a similar range (0.41 +/- 0.401 and 0.99 +/- 0.003), and all of them decreased as time between weighings increased. Direct genetic correlations suggested that selecting buffalos for heavier weights at any age would increase weights from birth through 900 days of age. However, higher heritabilities for direct genetic weights effects after 600 days of age suggested that selection for these effects would be more effective if done during this age period. A greater response to selection for maternal ability would be expected if selection used maternal genetic predictions for weights near weaning. (C) 2013 Elsevier B.V. All rights reserved.