952 resultados para Spectral Difference Method
                                
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Losses of horticulture product in Brazil are significant and among the main causes are the use of inappropriate boxes and the absence of a cold chain. A project for boxes is proposed, based on computer simulations, optimization and experimental validation, trying to minimize the amount of wood associated with structural and ergonomic aspects and the effective area of the openings. Three box prototypes were designed and built using straight laths with different configurations and areas of openings (54% and 36%). The cooling efficiency of Tommy Atkins mango (Mangifera Indica L.) was evaluated by determining the cooling time for fruit packed in the wood models and packed in the commercially used cardboard boxes, submitted to cooling in a forced-air system, at a temperature of 6ºC and average relative humidity of 85.4±2.1%. The Finite Element Method was applied, for the dimensioning and structural optimization of the model with the best behavior in relation to cooling. All wooden boxes with fruit underwent vibration testing for two hours (20 Hz). There was no significant difference in average cooling time in the wooden boxes (36.08±1.44 min); however, the difference was significant in comparison to the cardboard boxes (82.63±29.64 min). In the model chosen for structural optimization (36% effective area of openings and two side laths), the reduction in total volume of material was 60% and 83% in the cross section of the columns. There was no indication of mechanical damage in the fruit after undergoing the vibration test. Computer simulations and structural study may be used as a support tool for developing projects for boxes, with geometric, ergonomic and thermal criteria.
                                
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INTRODUCTION: Data is scarce regarding adverse events (AE) of biological therapy used in the management of Crohn's Disease (CD) among Brazilian patients. OBJECTIVES: To analyse AE prevalence and profile in patients with CD treated with Infliximab (IFX) or Adalimumab (ADA) and to verify whether there are differences between the two drugs. METHOD: Retrospective observational single-centre study of CD patients on biological therapy. Variables analysed: Demographic data, Montreal classification, biological agent administered, treatment duration, presence and type of AE and the need for treatment interruption. RESULTS: Forty-nine patients were analysed, 25 treated with ADA and 24 with IFX. The groups were homogeneous in relation to the variables studied. The average follow-up period for the group treated with ADA was 19.3 months and 21.8 months for the IFX group (p = 0.585). Overall, 40% (n = 10) of patients taking ADA had AE compared with 50% (n = 12) of IFX users (p = 0.571). There was a tendency towards higher incidence of cutaneous and infusion reactions in the IFX group and higher incidence of infections in the ADA treated group, although without significant difference. CONCLUSIONS: No difference was found in the AE prevalence and profile between ADA and IFX CD patients in the population studied.
                                
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PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.
                                
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Universidade Estadual de Campinas . Faculdade de Educação Física
                                
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Universidade Estadual de Campinas . Faculdade de Educação Física
                                
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Universidade Estadual de Campinas . Faculdade de Educação Física
                                
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Universidade Estadual de Campinas . Faculdade de Educação Física
                                
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Universidade Estadual de Campinas . Faculdade de Educação Física
                                
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Universidade Estadual de Campinas. Faculdade de Educação Física
                                
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Universidade Estadual de Campinas . Faculdade de Educação Física
                                
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Universidade Estadual de Campinas . Faculdade de Educação Física
Analise da variabilidade da frequencia cardiaca em mulheres na pos-menopausa sedentarias e treinadas
                                
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Universidade Estadual de Campinas . Faculdade de Educação Física
                                
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Universidade Estadual de Campinas . Faculdade de Educação Física
                                
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Universidade Estadual de Campinas . Faculdade de Educação Física
                                
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Universidade Estadual de Campinas . Faculdade de Educação Física
 
                    