Analysis of ensemble models in the medium term hydropower scheduling

The medium term hydropower scheduling (MTHS) problem involves an attempt to determine, for each time stage of the planning period, the amount of generation at each hydro plant which will maximize the expected future benefits throughout the planning period, while respecting plant operational constraints. Besides, it is important to emphasize that this decision-making has been done based mainly on inflow earliness knowledge. To perform the forecast of a determinate basin, it is possible to use some intelligent computational approaches. In this paper one considers the Dynamic Programming (DP) with the inflows given by their average values, thus turning the problem into a deterministic one which the solution can be obtained by deterministic DP (DDP). The performance of the DDP technique in the MTHS problem was assessed by simulation using the ensemble prediction models. Features and sensitivities of these models are discussed. © 2012 IEEE.

Bone metabolism biomarkers, body weight, and bone age in healthy Brazilian male adolescents

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

Rheological properties of frozen concentrated orange juice (FCOJ) as a function of concentration and subzero temperatures

Data on flow properties of Frozen Concentrated Orange Juice (FCOJ) produced from oranges cv. Pera-Rio (65.04 Brix, 8.8% w/w pulp content, 2.5% w/w pectin, 3.84% citric acid, 1.293 g cm(-3)) from -18 to 0 degrees C were fitted with appropriate predictive models. The power law model was found to be the most appropriate to fit the flow curves obtained for FCOJ between 46.56 and 65.04 degrees Brix. In higher concentrations, thixotropy was observed and showed more temperature dependence. A single equation combining Arrhenius and exponential relationships was applied to describe the temperature effect and shear rate on the quantity of breakdown of FCOJ.

Temperature and concentration dependence of heat capacity of model aqueous solutions

Heat capacities of binary aqueous solutions of different concentrations of sucrose, glucose, fructose, citric acid, malic acid, and inorganic salts were measured with a differential scanning calorimeter in the temperature range from 5degreesC to 65degreesC. Heat capacity increased with increasing water content and increasing temperature. At low concentrations, heat capacity approached that of pure water, with a less pronounced effect of temperature, and similar abnormal behavior of pure water with a minimum around 30degreesC-40degreesC. Literature data, when available agreed relatively well with experimental values. A correction factor, based on the assumption of chemical equilibrium between liquid and gas phase in the Differential Scanning Calorimeter, was proposed to correct for the water evaporation due to temperature rise. Experimental data were fitted to predictive models. Excess molar heat capacity was calculated using the Redlich-Kister equation to represent the deviation from the additive ideal model.

Thermal properties of passion fruit juice as affected by temperature and water content

The specific heat, thermal conductivity and density of passion fruit juice were experimentally determined from 0.506 to 0.902 (wet basis) water content and temperatures from 0.4 to 68.8C. The experimental results were compared with existing and widely used models for the thermal properties. In addition, based on empiric equations from literature, new simple models were parameterized with a subset of the total experimental data. The specific heat and thermal conductivity showed linear dependency on water content and temperature, while the density was nonlinearly related to water content. The generalized predictive models were considerably good for this product but the empiric, product-specific models developed in the present work yield better predictions. Even though the existing models showed a moderate accuracy, the new simple ones would be preferred, because they constitute an easier and direct way of evaluating the thermal properties of passion fruit juice, requiring no information about the chemical composition of the product, and a reduced time of the estimation procedure, as the new empiric models are described in terms of only two physical parameters, the water content and the temperature. © Copyright 2005, Blackwell Publishing All Rights Reserved.

Modelagem das exigências de lisina para aves de postura em crescimento

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimativa da produtividade de trigo em função da adubação nitrogenada utilizando modelagem neuro fuzzy

Currently new techniques for data processing, such as neural networks, fuzzy logic and hybrid systems are used to develop predictive models of complex systems and to estimate the desired parameters. In this article the use of an adaptive neuro fuzzy inference system was investigated to estimate the productivity of wheat, using a database of combination of the following treatments: five N doses (0, 50, 100, 150 and 200 kg ha(-1)), three sources (Entec, ammonium sulfate and urea), two application times of N (at sowing or at side-dressing) and two wheat cultivars (IAC 370 and E21), that were evaluated during two years in Selviria, Mato Grosso do Sul, Brazil. Through the input and output data, the system of adaptive neuro fuzzy inference learns, and then can estimate a new value of wheat yield with different N doses. The productivity prediciton error of wheat in function of five N doses, using a neuro fuzzy system, was smaller than that one obtained with a quadratic approximation. The results show that the neuro fuzzy system is a viable prediction model for estimating the wheat yield in function of N doses.

Patch size, functional isolation, visibility and matrix permeability influences neotropical primate occurrence within highly fragmented landscapes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Avaliação dos modelos de predição da erosão hídrica MEUPS e WEPP: contribuição em bacias hidrográficas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Analysis of the effects of damping in the models validation

The search for better performance in the structural systems has been taken to more refined models, involving the analysis of a growing number of details, which should be correctly formulated aiming at defining a representative model of the real system. Representative models demand a great detailing of the project and search for new techniques of evaluation and analysis. Model updating is one of this technologies, it can be used to improve the predictive capabilities of computer-based models. This paper presents a FRF-based finite element model updating procedure whose the updating variables are physical parameters of the model. It includes the damping effects in the updating procedure assuming proportional and non proportional damping mechanism. The updating parameters are defined at an element level or macro regions of the model. So, the parameters are adjusted locally, facilitating the physical interpretation of the adjusting of the model. Different tests for simulated and experimental data are discussed aiming at evaluating the characteristics and potentialities of the methodology.

Factors predictive of inappropriateness in requests for parenteral antimicrobials for therapeutic purposes: A study in a small teaching hospital in Brazil

Background: The identification of patterns of inappropriate antimicrobial prescriptions in hospitals contributes to the improvement of antimicrobial stewardship programs (ASP). Methods: We conducted a cross-sectional study to identify predictors of inappropriateness in requests for parenteral antimicrobials (RPAs) in a teaching hospital with 285 beds. We reviewed 25% of RPAs for therapeutic purposes from y 2005. Appropriateness was evaluated according to current guidelines for antimicrobial therapy. We assessed predictors of inappropriateness through univariate and multivariate models. RPAs classified as 'appropriate' or 'probably appropriate' were selected as controls. Case groups comprised inappropriate RPAs, either in general or for specific errors. Results: Nine hundred and sixty-three RPAs were evaluated, 34.6% of which were considered inappropriate. In the multivariate analysis, general predictors of inappropriateness were: prescription on week-ends/holidays (odds ratio (OR) 1.67, 95% confidence interval (CI) 1.20-2.28, p = 0.002), patient in the intensive care unit (OR 1.57, 95% CI 1.11-2.23, p = 0.01), peritoneal infection (OR 2.15, 95% CI 1.27-3.65, p = 0.004), urinary tract infection (OR 1.89, 95% CI 1.25 -2.87, p = 0.01), combination therapy with 2 or more antimicrobials (OR 1.72, 95% CI 1.15-2.57, p = 0.008) and prescriptions including penicillins (OR 2.12, 95% CI 1.39-3.25, p = 0.001) or 1(st) generation cephalosporins (OR 1.74, 95% CI 1.01-3.00, p = 0.048). Previous consultation with an infectious diseases (ID) specialist had a protective effect against inappropriate prescription (OR 0.34, 95% CI 0.24-0.50, p < 0.001). Factors independently associated with specific prescription errors varied. However, consultation with an ID specialist was protective against both unnecessary antimicrobial use (OR 0.04, 95% CI 0.01-0.26, p = 0.001) and requests for agents with an insufficient antimicrobial spectrum (OR 0.14, 95% CI 0.03-0.30, p = 0.01). Conclusions: Our results demonstrate the importance of previous consultation with an ID specialist in assuring the quality of prescriptions. Also, they highlight prescription patterns that should be approached by ASP policies.

Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. © 2013 Blackwell Verlag GmbH.

Mean surface temperature prediction models for broiler chickens-a study of sensible heat flow

Body surface temperature can be used to evaluate thermal equilibrium in animals. The bodies of broiler chickens, like those of all birds, are partially covered by feathers. Thus, the heat flow at the boundary layer between broilers' bodies and the environment differs between feathered and featherless areas. The aim of this investigation was to use linear regression models incorporating environmental parameters and age to predict the surface temperatures of the feathered and featherless areas of broiler chickens. The trial was conducted in a climate chamber, and 576 broilers were distributed in two groups. In the first trial, 288 broilers were monitored after exposure to comfortable or stressful conditions during a 6-week rearing period. Another 288 broilers were measured under the same conditions to test the predictive power of the models. Sensible heat flow was calculated, and for the regions covered by feathers, sensible heat flow was predicted based on the estimated surface temperatures. The surface temperatures of the feathered and featherless areas can be predicted based on air, black globe or operative temperatures. According to the sensible heat flow model, the broilers' ability to maintain thermal equilibrium by convection and radiation decreased during the rearing period. Sensible heat flow estimated based on estimated surface temperatures can be used to predict animal responses to comfortable and stressful conditions. © 2013 ISB.

Comparison of a genetic group and unknown paternity models for growth traits in Nellore cattle

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

Simple agrometeorological models for estimating Guineagrass yield in Southeast Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)