30 resultados para Nonparametric Estimators


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Soil penetration resistance (PR) is a measure of soil compaction closely related to soil structure and plant growth. However, the variability in PR hampers the statistical analyses. This study aimed to evaluate the variability of soil PR on the efficiency of parametric and nonparametric analyses in indentifying significant effects of soil compaction and to classify the coefficient of variation of PR into low, medium, high and very high. On six dates, the PR of a typical dystrophic Red Ultisol under continuous no-tillage for 16 years was measured. Three tillage and/or traffic conditions were established with the application of: (i) no chiseling or additional traffic, (ii) additional compaction, and (iii) chiseling. On each date, the nineteen PR data (measured at every 1.5 cm to a depth of 28.5 cm) were grouped in layers with different thickness. In each layer, the treatment effects were evaluated by variance (ANOVA) and Kruskal-Wallis analyses in a completely randomized design, and the coefficients of variation of all analyses were classified (low, intermediate, high and very high). The ANOVA performed better in discriminating the compaction effects, but the rejection rate of null hypothesis decreased from 100 to 80 % when the coefficient of variation increased from 15 to 26 %. The values of 15 and 26 % were the thresholds separating the low/intermediate and the high/very high coefficient variation classes of PR in this Ultisol.

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This paper focused on four alternatives of analysis of experiments in square lattice as far as the estimation of variance components and some genetic parameters are concerned: 1) intra-block analysis with adjusted treatment and blocks within unadjusted repetitions; 2) lattice analysis as complete randomized blocks; 3) intrablock analysis with unadjusted treatment and blocks within adjusted repetitions; 4) lattice analysis as complete randomized blocks, by utilizing the adjusted means of treatments, obtained from the analysis with recovery of interblock information, having as mean square of the error the mean effective variance of this same analysis with recovery of inter-block information. For the four alternatives of analysis, the estimators and estimates were obtained for the variance components and heritability coefficients. The classification of material was also studied. The present study suggests that for each experiment and depending of the objectives of the analysis, one should observe which alternative of analysis is preferable, mainly in cases where a negative estimate is obtained for the variance component due to effects of blocks within adjusted repetitions.

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Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

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Ten common doubts of chemistry students and professionals about their statistical applications are discussed. The use of the N-1 denominator instead of N is described for the standard deviation. The statistical meaning of the denominators of the root mean square error of calibration (RMSEC) and root mean square error of validation (RMSEV) are given for researchers using multivariate calibration methods. The reason why scientists and engineers use the average instead of the median is explained. Several problematic aspects about regression and correlation are treated. The popular use of triplicate experiments in teaching and research laboratories is seen to have its origin in statistical confidence intervals. Nonparametric statistics and bootstrapping methods round out the discussion.

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Scientific evidence on climate changes at global level has gained increasing interest in the scientific community in general. The impacts of climate change as well as anthropogenic actions may cause errors in hydro-agricultural projects existent in the watershed under study. This study aimed to identify the presence or absence of trend in total annual precipitation series of the watershed of the Mirim Lagoon, state of Rio Grande do Sul-RS / Brazil / Uruguay (Brazilian side) as well as to detect the period in which they occurred. For that, it was analyzed the precipitation data belonging to 14 weather stations. To detect the existence of monotonic trend and change points, it was used the nonparametric tests of Mann-Kendall and Mann-Whitney, the "t" test of Student for two samples of unpaired data (parametric), as well as the technique of progressive mean. The Weather Station 3152014 (Pelotas) presented changes in the trend in the series of annual precipitation in the period from 1953 to 2007. The methodologies that use subdivided series were more efficient in detecting change in trend when compared with the Mann-Kendall test, which uses the complete series (from 1921 to 2007).

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PURPOSE: To investigate the association between polymorphisms in genes that encode enzymes involved in folate- and vitamin B12-dependent homocysteine metabolism and recurrent spontaneous abortion (RSA).METHODS: We investigated the C677T and A1298C polymorphisms of the methylenetetrahydrofalate reductase gene (MTHFR), the A2756G polymorphism of the methionine synthase gene (MS) and the 844ins68 insertion of the cystathionine beta synthetase gene (CBS). The PCR technique followed by RFLP was used to assess the polymorphisms; the serum levels of homocysteine, vitamin B12 and folate were investigated by chemiluminescence. The EPI Info Software version 6.04 was used for statistical analysis. Parametric variables were compared by Student's t-test and nonparametric variables by the Wilcoxon rank sum test.RESULTS: The frequencies of gene polymorphisms in 89 women with a history of idiopathic recurrent miscarriage and 150 controls were 19.1 and 19.6% for the C677T, insertion, 20.8 and 26% for the A1298C insertion, 14.2 and 21.9% for the A2756G insertion, and 16.4 and 18% for the 844ins68 insertion, respectively. There were no significant differences between case and control groups in any of the gene polymorphisms investigated. However, the frequency of the 844ins68 insertion in the CBS gene was higher among women with a history of loss during the third trimester of pregnancy (p=0.003). Serum homocysteine, vitamin B12 and folate levels id not differ between the polymorphisms studied in the case and control groups. However, linear regression analysis showed a dependence of serum folate levels on the maintenance of tHcy levels.CONCLUSION: The investigated gene polymorphisms and serum homocysteine, vitamin B12 and folate levels were not associated with idiopathic recurrent miscarriage in the present study. Further investigations are needed in order to confirm the role of the CBS 844ins68 insertion in recurrent miscarriage.

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Cedrela odorata L. (Meliaceae) occurs in the Atlantic forest, Amazon rain forest, riparian forest of the country, and wetlands, which demand species adapted to their water conditions. Studies in ecological wood anatomy demonstrated that weather factors' variations have direct influence on the wood anatomical structure and that the fragmentation of the natural habitats is a direct cause of the edge effect which alters the abiotic aspects of the location, interfering consequently in its vegetation. A comparative analysis of 20 anatomical quantitative features of the wood structure was performed in populations of Cedrela odorata growing inside and on the edge of the swamp forest and granulometric analysis was made on the soil. The quantitative data were submitted to the Mann-Whitney's nonparametric test, presenting a statistically significant value decrease in the eleven wood features mean for the specimens growing in the edge of swamp forest.

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Diabetic nephropathy (DN) is characterized structurally by progressive mesangial deposition of extracellular matrix (ECM). Transforming growth factor-ß (TGF-ß) is considered to be one of the major cytokines involved in the regulation of ECM synthesis and degradation. Several studies suggest that an increase in urinary TGF-ß levels may reflect an enhanced production of this polypeptide by the kidney cells. We evaluated TGF-ß in occasional urine samples from 14 normal individuals and 23 patients with type 2 diabetes (13 with persistent proteinuria >500 mg/24 h, DN, 6 with microalbuminuria, DMMA, and 4 with normal urinary albumin excretion, DMN) by enzyme immunoassay. An increase in the rate of urinary TGF-ß excretion (pg/mg UCreat.) was observed in patients with DN (296.07 ± 330.77) (P<0.001) compared to normal individuals (17.04 ± 18.56) (Kruskal-Wallis nonparametric analysis of variance); however, this increase was not observed in patients with DMMA (25.13 ± 11.30) or in DMN (18.16 ± 11.82). There was a positive correlation between the rate of urinary TGF-ß excretion and proteinuria (r = 0.70, a = 0.05) (Pearson's analysis), one of the parameters of disease progression.

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Air pollution has been associated with health effects on different age groups. The present study was designed to assess the impact of daily changes in air pollutants (NO2, SO2, CO, O3, and particle matter (PM10)) on total number of daily neonatal deaths (those that occur between the first and the 28th days of life) in São Paulo, from January 1998 to December 2000, since adverse outcomes such as neonatal deaths associated with air pollution in Brazil have not been evaluated before. Generalized additive Poisson regression models were used and nonparametric smooth functions (loess) were adopted to control long-term trend, temperature, humidity, and short-term trends. A linear term was used for holidays. The association between air pollutants and neonatal deaths showed a short time lag. Interquartile range increases in PM10 (23.3 µg/m³) and SO2 (9.2 µg/m³) were associated with increases of 4% (95% CI, 2-6) and 6% (95% CI, 4-8), respectively. Instead of adopting a two-pollutant model we created an index to represent PM10 and SO2 effects. For an interquartile range increase in the index an increase of 6.3% (95% CI, 6.1-6.5) in neonatal deaths was observed. These results agree with previous studies performed by our group showing the deleterious effects of air pollutants during the perinatal period. The method reported here represents an alternative approach to analyze the relationship between highly correlated pollutants and public health problems, reinforcing the idea of the synergic effects of air pollutants in public health.

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An increase in daily mortality from myocardial infarction has been observed in association with meteorological factors and air pollution in several cities in the world, mainly in the northern hemisphere. The objective of the present study was to analyze the independent effects of environmental variables on daily counts of death from myocardial infarction in a subtropical region in South America. We used the robust Poisson regression to investigate associations between weather (temperature, humidity and barometric pressure), air pollution (sulfur dioxide, carbon monoxide, and inhalable particulate), and the daily death counts attributed to myocardial infarction in the city of São Paulo in Brazil, where 12,007 fatal events were observed from 1996 to 1998. The model was adjusted in a linear fashion for relative humidity and day-of-week, while nonparametric smoothing factors were used for seasonal trend and temperature. We found a significant association of daily temperature with deaths due to myocardial infarction (P < 0.001), with the lowest mortality being observed at temperatures between 21.6 and 22.6ºC. Relative humidity appeared to exert a protective effect. Sulfur dioxide concentrations correlated linearly with myocardial infarction deaths, increasing the number of fatal events by 3.4% (relative risk of 1.03; 95% confidence interval = 1.02-1.05) for each 10 µg/m³ increase. In conclusion, this study provides evidence of important associations between daily temperature and air pollution and mortality from myocardial infarction in a subtropical region, even after a comprehensive control for confounding factors.

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Several methods are used to estimate anaerobic threshold (AT) during exercise. The aim of the present study was to compare AT obtained by a graphic visual method for the estimate of ventilatory and metabolic variables (gold standard), to a bi-segmental linear regression mathematical model of Hinkley's algorithm applied to heart rate (HR) and carbon dioxide output (VCO2) data. Thirteen young (24 ± 2.63 years old) and 16 postmenopausal (57 ± 4.79 years old) healthy and sedentary women were submitted to a continuous ergospirometric incremental test on an electromagnetic braking cycloergometer with 10 to 20 W/min increases until physical exhaustion. The ventilatory variables were recorded breath-to-breath and HR was obtained beat-to-beat over real time. Data were analyzed by the nonparametric Friedman test and Spearman correlation test with the level of significance set at 5%. Power output (W), HR (bpm), oxygen uptake (VO2; mL kg-1 min-1), VO2 (mL/min), VCO2 (mL/min), and minute ventilation (VE; L/min) data observed at the AT level were similar for both methods and groups studied (P > 0.05). The VO2 (mL kg-1 min-1) data showed significant correlation (P < 0.05) between the gold standard method and the mathematical model when applied to HR (r s = 0.75) and VCO2 (r s = 0.78) data for the subjects as a whole (N = 29). The proposed mathematical method for the detection of changes in response patterns of VCO2 and HR was adequate and promising for AT detection in young and middle-aged women, representing a semi-automatic, non-invasive and objective AT measurement.

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Even though frequency analysis of body sway is widely applied in clinical studies, the lack of standardized procedures concerning power spectrum estimation may provide unreliable descriptors. Stabilometric tests were applied to 35 subjects (20-51 years, 54-95 kg, 1.6-1.9 m) and the power spectral density function was estimated for the anterior-posterior center of pressure time series. The median frequency was compared between power spectra estimated according to signal partitioning, sampling rate, test duration, and detrending methods. The median frequency reliability for different test durations was assessed using the intraclass correlation coefficient. When increasing number of segments, shortening test duration or applying linear detrending, the median frequency values increased significantly up to 137%. Even the shortest test duration provided reliable estimates as observed with the intraclass coefficient (0.74-0.89 confidence interval for a single 20-s test). Clinical assessment of balance may benefit from a standardized protocol for center of pressure spectral analysis that provides an adequate relationship between resolution and variance. An algorithm to estimate center of pressure power density spectrum is also proposed.

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Our objective was to determine the presence of vascular endothelial growth factor (VEGF), matrix metalloproteinase-2 (MMP-2) and MMP-9 and specific tissue inhibitors of matrix metalloproteinase (TIMP-1 and TIMP-2) in tumor samples obtained from patients with primary breast cancer. We attempted to correlate these findings with the status of the sentinel lymph node (SLN) and clinical-pathological characteristics such as age, tumor size, histological type, histological grade, and vascular invasion. Tumor samples from 88 patients with primary breast cancer were analyzed. The immunoreactivity of VEGF, MMP-2, MMP-9, TIMP-1, and TIMP-2 in tumors was correlated with clinical and pathological features, as well as SLN status. Nonparametric, Mann-Whittney, Kruskal-Wallis, and Spearmann tests were used. Categorical variables were analyzed by the Pearson test. No statistically significant correlation was found between the amount of VEGF, MMP-2, MMP-9, TIMP-1, and TIMP-2 and the presence of tumor cells in the SLN. However, larger tumor diameter (P < 0.01) and the presence of vascular invasion (P < 0.01) were correlated positively with a positive SLN. A significant correlation of higher VEGF levels (P = 0.04) and lower TIMP-1 levels (P = 0.04) with ductal histology was also observed. Furthermore, lower TIMP-2 levels showed a statistically significant correlation with younger age (<50 years) and larger tumor diameter (2.0-5.0 cm). A positive SLN correlated significantly with a larger tumor diameter and the presence of vascular invasion. Higher VEGF and lower TIMP-1 levels were observed in patients with ductal tumors, while higher TIMP-1 levels were observed in lobular tumors.

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Research on molecular mechanisms of carcinogenesis plays an important role in diagnosing and treating gastric cancer. Metabolic profiling may offer the opportunity to understand the molecular mechanism of carcinogenesis and help to non-invasively identify the potential biomarkers for the early diagnosis of human gastric cancer. The aims of this study were to explore the underlying metabolic mechanisms of gastric cancer and to identify biomarkers associated with morbidity. Gas chromatography/mass spectrometry (GC/MS) was used to analyze the serum metabolites of 30 Chinese gastric cancer patients and 30 healthy controls. Diagnostic models for gastric cancer were constructed using orthogonal partial least squares discriminant analysis (OPLS-DA). Acquired metabolomic data were analyzed by the nonparametric Wilcoxon test to find serum metabolic biomarkers for gastric cancer. The OPLS-DA model showed adequate discrimination between cancer and non-cancer cohorts while the model failed to discriminate different pathological stages (I-IV) of gastric cancer patients. A total of 44 endogenous metabolites such as amino acids, organic acids, carbohydrates, fatty acids, and steroids were detected, of which 18 differential metabolites were identified with significant differences. A total of 13 variables were obtained for their greatest contribution in the discriminating OPLS-DA model [variable importance in the projection (VIP) value >1.0], among which 11 metabolites were identified using both VIP values (VIP >1) and the Wilcoxon test. These metabolites potentially revealed perturbations of glycolysis and of amino acid, fatty acid, cholesterol, and nucleotide metabolism of gastric cancer patients. These results suggest that gastric cancer serum metabolic profiling has great potential in detecting this disease and helping to understand its metabolic mechanisms.

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This study aimed to analyze the agreement between measurements of unloaded oxygen uptake and peak oxygen uptake based on equations proposed by Wasserman and on real measurements directly obtained with the ergospirometry system. We performed an incremental cardiopulmonary exercise test (CPET), which was applied to two groups of sedentary male subjects: one apparently healthy group (HG, n=12) and the other had stable coronary artery disease (n=16). The mean age in the HG was 47±4 years and that in the coronary artery disease group (CG) was 57±8 years. Both groups performed CPET on a cycle ergometer with a ramp-type protocol at an intensity that was calculated according to the Wasserman equation. In the HG, there was no significant difference between measurements predicted by the formula and real measurements obtained in CPET in the unloaded condition. However, at peak effort, a significant difference was observed between oxygen uptake (V˙O2)peak(predicted)and V˙O2peak(real)(nonparametric Wilcoxon test). In the CG, there was a significant difference of 116.26 mL/min between the predicted values by the formula and the real values obtained in the unloaded condition. A significant difference in peak effort was found, where V˙O2peak(real)was 40% lower than V˙O2peak(predicted)(nonparametric Wilcoxon test). There was no agreement between the real and predicted measurements as analyzed by Lin’s coefficient or the Bland and Altman model. The Wasserman formula does not appear to be appropriate for prediction of functional capacity of volunteers. Therefore, this formula cannot precisely predict the increase in power in incremental CPET on a cycle ergometer.