911 resultados para classifier combination
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The development and use of techniques that extend the life vase of the flowers, maintaining the quality of the product, is essential for reducing postharvest losses. The objective of this work was to evaluate different solutions for maintenance, associated or not to sucrose, in maintaining the postharvest quality of chrysanthemum stems. The treatments used distilled water, 8-HQC to 100 mg L-1, 8-HQC to 100 mg L-1 + sucrose 50 g L-1, 8-HQC to 200 mg L-1, 8-HQC to 200 mg L-1 + sucrose 50 g L-1. Physical assessments were made: color, fresh mass and relative water content; chemical evaluations: reducing sugars and pigments, and qualitative assessments: turgidity, color of the flowers, and number of buttons, open flowers and partially open flowers. The combination of 8-HQC 200 mg L-1 + sucrose 50 g L-1 was the best performance that made for maintaining the quality of flower stems, favoring the opening of buttons and turgidity of petals. Sucrose contributed to better maintenance of the reserve substances in the shaft, which had increased the flower vase life.
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This study examined the influence of three polymerization cycles (1: heat cure - long cycle; 2: heat cure - short cycle; and 3: microwave activation) on the linear dimensions of three denture base resins, immediately after deflasking, and 30 days after storage in distilled water at 37± 2ºC. The acrylic resins used were: Clássico, Lucitone 550 and Acron MC. The first two resins were submitted to all three polymerization cycles, and the Acron MC resin was cured by microwave activation only. The samples had three marks, and dimensions of 65 mm in length, 10 mm in width and 3 mm in thickness. Twenty-one test specimens were fabricated for each combination of resin and cure cycle, and they were submitted to three linear dimensional evaluations for two positions (A and B). The changes were evaluated using a microscope. The results indicated that all acrylic resins, regardless of the cure cycle, showed increased linear dimension after 30 days of storage in water. The composition of the acrylic resin affected the results more than the cure cycles, and the conventional acrylic resin (Lucitone 550 and Clássico) cured by microwave activation presented similar results when compared with the resin specific for microwave activation.
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The purpose of this paper is to report a case of central retinal vein thrombosis associated with isolated heterozygous protein C deficiency. Acute occlusion of the central retinal vein presents as one of the most dramatic pictures in ophthalmology. It is often a result of both local and systemic causes. A rare systemic cause is heterozygous protein C deficiency, and it usually occurs in combination with other thrombophilic conditions. This case highlights that isolated heterozygous protein C deficiency may be the cause of central retinal vein thrombosis and underscores the importance of its screening in young patients with this ophthalmologic disease.
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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
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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