Validação de um instrumento de preocupação com a forma corporal aplicado a estudantes universitárias

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

Estudo de controladores aplicados a inversores para UPS com operação ilhada

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Thermochemical equilibrium modeling of a biomass downdraft gasifier: Constrained and unconstrained non-stoichiometric models

The objective of this work is to develop a non-stoichiometric equilibrium model to study parameter effects in the gasification process of a feedstock in downdraft gasifiers. The non-stoichiometric equilibrium model is also known as the Gibbs free energy minimization method. Four models were developed and tested. First a pure non-stoichiometric equilibrium model called M1 was developed; then the methane content was constrained by correlating experimental data and generating the model M2. A kinetic constraint that determines the apparent gasification rate was considered for model M3 and finally the two aforementioned constraints were implemented together in model M4. Models M2 and M4 showed to be the more accurate among the four developed models with mean RMS (root mean square error) values of 1.25 each.Also the gasification of Brazilian Pinus elliottii in a downdraft gasifier with air as gasification agent was studied. The input parameters considered were: (a) equivalence ratio (0.28-035); (b) moisture content (5-20%); (c) gasification time (30-120 min) and carbon conversion efficiency (80-100%). (C) 2014 Elsevier Ltd. All rights reserved.

Psychometric Properties of the Oral Health Impact Profile and New Methodological Approach

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

Tool Condition Monitoring of Single-Point Dresser Using Acoustic Emission and Neural Networks Models

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

Interpolação geoespacial da evapotranspiração de referência (ETo) em regiões com escassez de dados: estudo de caso no Sul de Minas Gerais, Brasil

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

The influence of the use of stabilizer bracelet in a child with choreoathetoid cerebral palsy

Introduction: The use of stabilizer bracelet is a frequent treatment for movement disorders to strengthen muscles and adjust coordination. Still questions remain regarding the benefi t of using loads to decrease involuntary movements and the best load and placement. Objective: To measure the infl uence of the stabilizer bracelet on the kinematics and spatiotemporal parameters in planar movements performed by the upper limb. Method: One child, who has the spastic diplegy type of cerebral palsy with choreoathetoid component, and a control child without cerebral palsy, both female and 7 years old, were subjected to analysis of movements in relation to displacement, velocity, linear acceleration, and the calculation of mean square error (MSE) with and without use of stabilizer bracelet with loads of 25, 50, and 75% of the supported maximum load. Results: After comparing data between subjects, a difference was found between patient and control in all situations and variables. An inter-individual comparison using 25% of the maximum load showed the smallest difference with the NDE. Discussion and Conclusion: This therapeutic option is low cost, easy to apply, and does not signifi cantly interfere in the aesthetic of the individual. Therefore, physiotherapists may prescribe this for activities that require greater control of the upper limb because for the case studied the upper limb movement was more effi cient with the use of the stabilizer bracelet.

Avaliação de Técnicas de Interpolação de Imagens Digitais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fast determination of beef quality parameters with time-domain nuclear magnetic resonance spectroscopy and chemometrics

The noteworthy of this study is to predict seven quality parameters for beef samples using time-domain nuclear magnetic resonance (TD-NMR) relaxometry data and multivariate models. Samples from 61 Bonsmara heifers were separated into five groups based on genetic (breeding composition) and feed system (grain and grass feed). Seven sample parameters were analyzed by reference methods; among them, three sensorial parameters, flavor, juiciness and tenderness and four physicochemical parameters, cooking loss, fat and moisture content and instrumental tenderness using Warner Bratzler shear force (WBSF). The raw beef samples of the same animals were analyzed by TD-NMR relaxometry using Carr-Purcell-Meiboom-Gill (CPMG) and Continuous Wave-Free Precession (CWFP) sequences. Regression models computed by partial least squares (PLS) chemometric technique using CPMG and CWFP data and the results of the classical analysis were constructed. The results allowed for the prediction of aforementioned seven properties. The predictive ability of the method was evaluated using the root mean square error (RMSE) for the calibration (RMSEC) and validation (RMSEP) data sets. The reference and predicted values showed no significant differences at a 95% confidence level.

Mapeamento de QTL e análises de espectroscopia para teor de óleo visando aplicação em programas de melhoramento de soja

Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV

Orientação e ortorretificação de imagens terrestres nadirais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Mapeamento de cianobactérias por meio da fluorescência da ficocianina e de análise geoestatística

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Tool condition monitoring of aluminum oxide grinding wheel in dressing operation using acoustic emission and neural networks

The grinding operation gives workpieces their final finish, minimizing surface roughness through the interaction between the abrasive grains of a tool (grinding wheel) and the workpiece. However, excessive grinding wheel wear due to friction renders the tool unsuitable for further use, thus requiring the dressing operation to remove and/or sharpen the cutting edges of the worn grains to render them reusable. The purpose of this study was to monitor the dressing operation using the acoustic emission (AE) signal and statistics derived from this signal, classifying the grinding wheel as sharp or dull by means of artificial neural networks. An aluminum oxide wheel installed on a surface grinding machine, a signal acquisition system, and a single-point dresser were used in the experiments. Tests were performed varying overlap ratios and dressing depths. The root mean square values and two additional statistics were calculated based on the raw AE data. A multilayer perceptron neural network was used with the Levenberg-Marquardt learning algorithm, whose inputs were the aforementioned statistics. The results indicate that this method was successful in classifying the conditions of the grinding wheel in the dressing process, identifying the tool as "sharp''(with cutting capacity) or "dull''(with loss of cutting capacity), thus reducing the time and cost of the operation and minimizing excessive removal of abrasive material from the grinding wheel.

Classification of intact açai (Euterpe oleracea Mart.) and jucara (Euterpe edulis Mart) fruits based on dry matter content by means of near infrared spectroscopy

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

Desenvolvimento de um sistema de SHM sem fio e com compensação automática de temperatura

Pós-graduação em Engenharia Elétrica - FEIS