25 resultados para Modelagem estatística
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BACKGROUND: Changes in heart rate during rest-exercise transition can be characterized by the application of mathematical calculations, such as deltas 0-10 and 0-30 seconds to infer on the parasympathetic nervous system and linear regression and delta applied to data range from 60 to 240 seconds to infer on the sympathetic nervous system. The objective of this study was to test the hypothesis that young and middle-aged subjects have different heart rate responses in exercise of moderate and intense intensity, with different mathematical calculations. METHODS: Seven middle-aged men and ten young men apparently healthy were subject to constant load tests (intense and moderate) in cycle ergometer. The heart rate data were submitted to analysis of deltas (0-10, 0-30 and 60-240 seconds) and simple linear regression (60-240 seconds). The parameters obtained from simple linear regression analysis were: intercept and slope angle. We used the Shapiro-Wilk test to check the distribution of data and the t test for unpaired comparisons between groups. The level of statistical significance was 5%. RESULTS: The value of the intercept and delta 0-10 seconds was lower in middle age in two loads tested and the inclination angle was lower in moderate exercise in middle age. CONCLUSION: The young subjects present greater magnitude of vagal withdrawal in the initial stage of the HR response during constant load exercise and higher speed of adjustment of sympathetic response in moderate exercise.
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OBJECTIVE: To adapted the critical velocity (CV), RAST test and lactate minimum (LM) to evaluation of female basketball players. METHODS: Twelve well-trained female basketball players (19 ± 1yrs) were submitted to four intensities running (10 - 14 km/h) at shuttle exercise until exhaustion, applied on alternate days. The linear model 'velocity vs. 1/tlim' was adopted to determine the aerobic (CV) and anaerobic (CCA) parameters. The lactate minimum test consisted of two phases: 1) hiperlactatemia induction using the RAST test and 2) incremental test composed by five shuttle run (20-m) at 7, 8, 9, 10, and 12 km/h. Blood samples were collected at the end of each stage. RESULTS: The velocity (vLM) and blood lactate concentration at LM were obtained by two polynomial adjustments: lactate vs. intensity (LM1) and lactate vs. time (LM2). ANOVA one-way, Student t-test and Pearson correlation were used for statistical analysis. The CV was obtained at 10.3 ± 0.2 km/h and the CCA estimated at 73.0 ± 3.4 m. The RAST was capable to induce the hiperlactatemia and to determine the Pmax (3.6 ± 0.2 W/kg), Pmed (2.8 ± 0.1 W/kg), Pmin (2.3 ± 0.1 W/kg) and FI (30 ± 3%). The vLM1 and vLM2 were obtained, respectively, at 9.47 ±0.13 km/h and 9.8 ± 0.13 km/h, and CV was higher than vLM1. CONCLUSION: The results suggest that the non-invasive model can be used to determine the aerobic and anaerobic parameters. Furthermore, the LM test adapted to basketball using RAST and progressive phase was effective to evaluate female athletes considering the specificity of modality, with high success rates observed in polynomial adjustment 'lactate vs. time' (LM2).
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Evolving interfaces were initially focused on solutions to scientific problems in Fluid Dynamics. With the advent of the more robust modeling provided by Level Set method, their original boundaries of applicability were extended. Specifically to the Geometric Modeling area, works published until then, relating Level Set to tridimensional surface reconstruction, centered themselves on reconstruction from a data cloud dispersed in space; the approach based on parallel planar slices transversal to the object to be reconstructed is still incipient. Based on this fact, the present work proposes to analyse the feasibility of Level Set to tridimensional reconstruction, offering a methodology that simultaneously integrates the proved efficient ideas already published about such approximation and the proposals to process the inherent limitations of the method not satisfactorily treated yet, in particular the excessive smoothing of fine characteristics of contours evolving under Level Set. In relation to this, the application of the variant Particle Level Set is suggested as a solution, for its intrinsic proved capability to preserve mass of dynamic fronts. At the end, synthetic and real data sets are used to evaluate the presented tridimensional surface reconstruction methodology qualitatively.
Resumo:
Evolving interfaces were initially focused on solutions to scientific problems in Fluid Dynamics. With the advent of the more robust modeling provided by Level Set method, their original boundaries of applicability were extended. Specifically to the Geometric Modeling area, works published until then, relating Level Set to tridimensional surface reconstruction, centered themselves on reconstruction from a data cloud dispersed in space; the approach based on parallel planar slices transversal to the object to be reconstructed is still incipient. Based on this fact, the present work proposes to analyse the feasibility of Level Set to tridimensional reconstruction, offering a methodology that simultaneously integrates the proved efficient ideas already published about such approximation and the proposals to process the inherent limitations of the method not satisfactorily treated yet, in particular the excessive smoothing of fine characteristics of contours evolving under Level Set. In relation to this, the application of the variant Particle Level Set is suggested as a solution, for its intrinsic proved capability to preserve mass of dynamic fronts. At the end, synthetic and real data sets are used to evaluate the presented tridimensional surface reconstruction methodology qualitatively.
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Type II 3β-hydroxysteroid dehydrogenase/Δ5-Δ4-isomerase (3β-HSD2), encoded by the HSD3B2 gene, is a key enzyme involved in the biosynthesis of all the classes of steroid hormones. Deleterious mutations in the HSD3B2 gene cause the classical deficiency of 3β-HSD2, which is a rare autosomal recessive disease that leads to congenital adrenal hyperplasia (CAH). CAH is the most frequent cause of ambiguous genitalia and adrenal insufficiency in newborn infants with variable degrees of salt losing. Here we report the molecular and structural analysis of the HSD3B2 gene in a 46,XY child, who was born from consanguineous parents, and presented with ambiguous genitalia and salt losing. The patient carries a homozygous nucleotide c.665C>A change in exon 4 that putatively substitutes the proline at codon 222 for glutamine. Molecular homology modeling of normal and mutant 3β-HSD2 enzymes emphasizes codon 222 as an important residue for the folding pattern of the enzyme and validates a suitable model for analysis of new mutations.
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PURPOSE: To evaluate the prevalence of pterygium in a population-based sample at Botucatu City - São Paulo State, Brazil. METHODS: A population-based cross-sectional study with randomized clustered sampling of households was conducted in the urban area of the Botucatu City -São Paulo State, Brazil and 85.1% of the intended sample was evaluated. All participants were submitted to ophthalmologic examination and the data were statistically analyzed. RESULTS: The prevalence of pterygium lesion in Botucatu City was 8.12% (7.0% < CI < 9.2%), affecting mainly males (10.4% males X 6.5% females - 8.5% < CI < 12.3% for males and 5.1% < CI < 7.8% for females) with 49.6 ± 14.9 years old in average; 32.18% of the pterygium carriers aged between 40 and 50 years. CONCLUSIONS: The prevalence of pterygium at Botucatu is 8.12%, affecting most frequently 40-50 year-old males.
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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