140 resultados para NIRS. Plum. Multivariate calibration. Variables selection
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Introduction Despite the great advances in serological testing for transfusion-transmitted infections, the selection of blood donors by blood bank operators remains the only way to avoid transmission within the testing window period. Part of this selection is the self-exclusion form, on which the donors can exclude their blood from donation without any explanation. This study assessed the clinical and epidemiological characteristics related to positivity for viral hepatitis and to the use of the confidential self-exclusion (CSE) form. Methods This transversal study analyzed the data collected from blood donors' files in a hospital in Southern Brazil. Univariate and multivariate analyses identified the clinical and epidemiological variables related to positive serologies of viral hepatitis and to whether the donor was self-excluded. Results Of the 3,180 donors included in this study, 0.1% tested positive for HBsAg, 2.1% for anti-HBc, and 0.9% for anti-HCV. When the 93 donors with positive serologies for viral hepatitis were compared with those who were negative, a greater proportion of the positive serology group was found to have had a history of blood transfusions (OR=4.908; 95%CI=1.628 - 14.799; p<0.01), had repeatedly donated (OR=2.147; 95%CI=1.236 - 3.729; p<0.01), and used the CSE form for self-exclusion (OR=7.139; 95%CI=2.045 - 24.923; p<0.01). No variables were independently associated with self-exclusion. Conclusions A history of blood transfusion, repeated donations, and self-exclusion are factors that should be considered during viral hepatitis screenings in blood banks.
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Introduction Leprosy is a chronic disease that affects skin and peripheral nerves. Disease complications include reactional episodes and physical impairment. One World Health Organization (WHO) goal of leprosy programs is to decrease the number of grade 2 impairment diagnoses by 2015. This study aims to evaluate clinical factors associated with the occurrence of leprosy reactions and physical impairment in leprosy patients. Methods We conducted a retrospective study of data from medical records of patients followed in two important centers for the treatment of leprosy in Aracaju, Sergipe, Brazil, from 2005 to 2011. We used the chi-square test to analyze associations between the following categorical variables: gender, age, operational classification, clinical forms, leprosy reactions, corticosteroid treatment, and physical impairment at the diagnosis and after cure. Clinical variables associated with multibacillary leprosy and/or reactional episodes and the presence of any grade of physical impairment after cure were evaluated using the logistic regression model. Results We found that men were more affected by multibacillary forms, reactional episodes, and grade 2 physical impairment at diagnosis. Leprosy reactions were detected in a total of 40% of patients and all were treated with corticosteroids. However, physical impairment was observed in 29.8% of the patients analyzed at the end of the treatment and our multivariate analysis associated a low dose and short period of corticosteroid treatment with persistence of physical impairments. Conclusions Physical impairment should receive an increased attention before and after treatment, and adequate treatment should be emphasized.
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Modeling clays have been used in several ecological experiments and have proved to be an important tool to variables control. The objective of our study was to determine if fruit color in isolated and grouped displays influences the fruit selection by birds in the field using artificial fruits. Data were collected in six plots distributed homogeneously in 3 km long trails with a minimum distance of 0.5 km. We used a paired experimental design to establish our experiments, so that all treatments were available to the local bird community in each plot. Overall, red was more pecked than brown and white. Isolated red and brown displays were significantly more pecked than others display. Even though our study was conducted in small spatial scales, artificial fruits appeared to be efficient in register fruit consumption attempts by bird. Although inconclusive about selective forces that sharp the dynamics of fruit color polymorphisms and choice by frugivorous birds, our findings corroborate recent studies wherein birds showed preferences by high- over low-contrast fruit signals.
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Background:The risk factors that characterize metabolic syndrome (MetS) may be present in childhood and adolescence, increasing the risk of cardiovascular disease in adulthood.Objective:Evaluate the prevalence of MetS and the importance of its associated variables, including insulin resistance (IR), in children and adolescents in the city of Guabiruba-SC, Brazil.Methods:Cross-sectional study with 1011 students (6–14 years, 52.4% girls, 58.5% children). Blood samples were collected for measurement of biochemical parameters by routine laboratory methods. IR was estimated by the HOMA-IR index, and weight, height, waist circumference and blood pressure were determined. Multivariate logistic regression models were used to examine the associations between risk variables and MetS.Results:The prevalence of MetS, IR, overweight and obesity in the cohort were 14%, 8.5%, 21% and 13%, respectively. Among students with MetS, 27% had IR, 33% were overweight, 45.5% were obese and 22% were eutrophic. IR was more common in overweight (48%) and obese (41%) students when compared with eutrophic individuals (11%; p = 0.034). The variables with greatest influence on the development of MetS were obesity (OR = 32.7), overweight (OR = 6.1), IR (OR = 4.4; p ≤ 0.0001 for all) and age (OR = 1.15; p = 0.014).Conclusion:There was a high prevalence of MetS in children and adolescents evaluated in this study. Students who were obese, overweight or insulin resistant had higher chances of developing the syndrome.
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AbstractBackground:30-40% of cardiac resynchronization therapy cases do not achieve favorable outcomes.Objective:This study aimed to develop predictive models for the combined endpoint of cardiac death and transplantation (Tx) at different stages of cardiac resynchronization therapy (CRT).Methods:Prospective observational study of 116 patients aged 64.8 ± 11.1 years, 68.1% of whom had functional class (FC) III and 31.9% had ambulatory class IV. Clinical, electrocardiographic and echocardiographic variables were assessed by using Cox regression and Kaplan-Meier curves.Results:The cardiac mortality/Tx rate was 16.3% during the follow-up period of 34.0 ± 17.9 months. Prior to implantation, right ventricular dysfunction (RVD), ejection fraction < 25% and use of high doses of diuretics (HDD) increased the risk of cardiac death and Tx by 3.9-, 4.8-, and 5.9-fold, respectively. In the first year after CRT, RVD, HDD and hospitalization due to congestive heart failure increased the risk of death at hazard ratios of 3.5, 5.3, and 12.5, respectively. In the second year after CRT, RVD and FC III/IV were significant risk factors of mortality in the multivariate Cox model. The accuracy rates of the models were 84.6% at preimplantation, 93% in the first year after CRT, and 90.5% in the second year after CRT. The models were validated by bootstrapping.Conclusion:We developed predictive models of cardiac death and Tx at different stages of CRT based on the analysis of simple and easily obtainable clinical and echocardiographic variables. The models showed good accuracy and adjustment, were validated internally, and are useful in the selection, monitoring and counseling of patients indicated for CRT.
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Between January and March 1998, a cross-sectional survey was carried out in four rural communities in Honduras, Central America. We examined the prevalence and intensity of Ascaris lumbricoides and Trichuris trichiura infections among 240 fecal specimens, and the association between selected socio-demographic variables and infection for 62 households. The overall prevalence of A. lumbricoides and T. trichiura was 45% (95% CI 39.0-51.9) and 38% (95% CI 31.8-44.4) respectively. The most intense infections for Ascaris and Trichuris were found in children aged 2-12 years old. By univariate analysis variables associated with infections of A. lumbricoides were: number of children 2-5 years old (p=0.001), level of formal education of respondents (p=0.01), reported site of defecation of children in households (p=0.02), households with children who had a recent history of diarrhea (p=0.002), and the location of households (p=0.03). Variables associated with both A. lumbricoides and T. trichiura infection included: number of children 6-14 years old (p=0.01, p=0.04, respectively), ownership of a latrine (p=0.04, p=0.03, respectively) and coinfection with either helminth (p=0.001, p=0.001, respectively). By multivariate analysis the number of children 2-5 years living in the household, (p=0.01, odds ratio (OR)=22.2), children with a recent history of diarrhea (p=0.0, OR=39.8), and infection of household members with T. trichiura (p=0.02, OR=16.0) were associated with A. lumbricoides infection. The number of children 6-14 years old in the household was associated with both A. lumbricoides and T. trichiura infection (p=0.04, p=0.01, OR=19.2, OR=5.2, respectively).
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In the State of Rio Grande do Sul, the municipality of Pelotas is responsible for 90 % of peach production due to its suitable climate and soil conditions. However, there is the need for new studies that aim at improved fruit quality and increased yield. The aim of this study was to evaluate the relationship that exists between soil physical properties and properties in the peach plant in the years 2010 and 2011 by the technique of multivariate canonical correlation. The experiment was conducted in a peach orchard located in the municipality of Morro Redondo, RS, Brazil, where an experimental grid of 101 plants was established. In a trench dug beside each one of the 101 plants, soil samples were collected to determine silt, clay, and sand contents, soil density, total porosity, macroporosity, microporosity, and volumetric water content in the 0.00-0.10 and 0.10-0.20 m layers, as well as the depth of the A horizon. In each plant and in each year, the following properties were assessed: trunk diameter, fruit size and number of fruits per plant, average weight of the fruit per plant, fruit pulp firmness, Brix content, and yield from the orchard. Exploratory analysis of the data was undertaken by descriptive statistics, and the relationships between the physical properties of the soil and of the plant were assessed by canonical correlation analysis. The results showed that the clay and microporosity variables were those that exhibited the highest coefficients of canonical cross-loading with the plant properties in the soil layers assessed, and that the variable of mean weight of the fruit per plant was that which had the highest coefficients of canonical loading within the plant group for the two years assessed.
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The objectives of this work were to evaluate the genotype x environment (GxE) interaction for popcorn and to compare two multivariate analyses methods. Nine popcorn cultivars were sown on four dates one month apart during each of the agricultural years 1998/1999 and 1999/2000. The experiments were carried out using randomized block designs, with four replicates. The cv. Zélia contributed the least to the GxE interaction. The cv. Viçosa performed similarly to cv. Rosa-claro. Optimization of GxE was obtained for cv. CMS 42 for a favorable mega-environment, and for cv. CMS 43 for an unfavorable environment. Multivariate analysis supported the results from the method of Eberhart & Russell. The graphic analysis of the Additive Main effects and Multiplicative Interaction (AMMI) model was simple, allowing conclusions to be made about stability, genotypic performance, genetic divergence between cultivars, and the environments that optimize cultivar performance. The graphic analysis of the Genotype main effects and Genotype x Environment interaction (GGE) method added to AMMI information on environmental stratification, defining mega-environments and the cultivars that optimized performance in those mega-environments. Both methods are adequate to explain the genotype x environment interactions.
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The objective of this work was to estimate the genetic variability and divergence among 22 superior rubber tree (Hevea sp.) genotypes of the IAC 400 series. Univariate and multivariate analyses were performed using eight quantitative traits (descriptors), including yield. In the univariate analyses, the estimated parameters were: genetic and environmental variances; genetic and environmental coefficients of variation; and the variation index. The Mahalanobis generalized distance, the Tocher agglomerative method and canonical variables were used for the multivariate analyses. In the univariate analyses, variability was verified among the genotypes for all the variables evaluated. The Tocher method grouped the genotypes into 11 clusters of dissimilarity. The first four canonical variables explained 87.93% of the cumulative variation. The highest genetic variability was found in rubber yield-related traits, which contributed the most to the genetic divergence. The most divergent pairs of genotypes are suggested for crossbreeding. The genotypes evaluated are suitable for breeding and may be used to continue the IAC rubber tree breeding program.
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This paper is a translation from IUPAC nomenclature document by K. Danzer and L. A. Currie (Pure Appl. Chem., 1998, 70(4), 993-1014). Its goal is to establish an uniform and meaningful approach to terminology (in Portuguese), notation, and formulation for calibation in analytical chemistry. In this first part, general fundamentals of calibration are presented, namely for both relationships of qualitative and quantitative variables (relations between variables characterizing certain types analytes of the measured function on the other hand and between variables characterizing the amount or concentration of the chemical species and the intensities of the measured signals, on the other hand). On this basis, the fundamentals of the common single component calibration (Univariate Calibration) which models the relationship y = f(x) between the signal intensities y and the amounts or concentrations x of the analyte under given conditions are represented. Additional papers will be prepared dealing with extensive relationships between several intensities and analyte contents, namely with multivariate calibrations and with optimization and experimental design.
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This study developed and validated a method for moisture determination in artisanal Minas cheese, using near-infrared spectroscopy and partial-least-squares. The model robustness was assured by broad sample diversity, real conditions of routine analysis, variable selection, outlier detection and analytical validation. The model was built from 28.5-55.5% w/w, with a root-mean-square-error-of-prediction of 1.6%. After its adoption, the method stability was confirmed over a period of two years through the development of a control chart. Besides this specific method, the present study sought to provide an example multivariate metrological methodology with potential for application in several areas, including new aspects, such as more stringent evaluation of the linearity of multivariate methods.
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The study of spatial variability of soil and plants attributes, or precision agriculture, a technique that aims the rational use of natural resources, is expanding commercially in Brazil. Nevertheless, there is a lack of mathematical analysis that supports the correlation of these independent variables and their interactions with the productivity, identifying scientific standards technologically applicable. The aim of this study was to identify patterns of soil variability according to the eleven physical and seven chemical indicators in an agricultural area. It was used two multivariate techniques: the hierarchical cluster analysis (HCA) and the principal component analysis (PCA). According to the HCA, the area was divided into five management zones: zone 1 with 2.87ha, zone 2 with 0.8ha, zone 3 with 1.84ha, zone 4 with 1.33ha and zone 5 with 2.76ha. By the PCA, it was identified the most important variables within each zone: V% for the zone 1, CTC in the zone 2, levels of H+Al in the zone 4 and sand content and altitude in the zone 5. The zone 3 was classified as an intermediate zone with characteristics of all others. According to the results it is concluded that it is possible to separate into groups (management zones) samples with the same patterns of variability by the multivariate statistical techniques.
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The aim of this study was to investigate the effect of pre-slaughter handling on the occurrence of PSE (Pale, Soft, and Exudative) meat in swine slaughtered at a commercial slaughterhouse located in the metropolitan region of Dourados, Mato Grosso do Sul, Brazil. Based on the database (n=1,832 carcasses), it was possible to apply the integrated multivariate analysis for the purpose of identifying, among the selected variables, those of greatest relevance to this study. Results of the Principal Component Analysis showed that the first five components explained 89.28% of total variance. In the Factor Analysis, the first factor represented the thermal stress and fatiguing conditions for swine during pre-slaughter handling. In general, this study indicated the importance of the pre-slaughter handling stages, evidencing those of greatest stress and threat to animal welfare and pork quality, which are transport time, resting period, lairage time before unloading, unloading time, and ambience.
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ABSTRACT This study aimed to develop a methodology based on multivariate statistical analysis of principal components and cluster analysis, in order to identify the most representative variables in studies of minimum streamflow regionalization, and to optimize the identification of the hydrologically homogeneous regions for the Doce river basin. Ten variables were used, referring to the river basin climatic and morphometric characteristics. These variables were individualized for each of the 61 gauging stations. Three dependent variables that are indicative of minimum streamflow (Q7,10, Q90 and Q95). And seven independent variables that concern to climatic and morphometric characteristics of the basin (total annual rainfall – Pa; total semiannual rainfall of the dry and of the rainy season – Pss and Psc; watershed drainage area – Ad; length of the main river – Lp; total length of the rivers – Lt; and average watershed slope – SL). The results of the principal component analysis pointed out that the variable SL was the least representative for the study, and so it was discarded. The most representative independent variables were Ad and Psc. The best divisions of hydrologically homogeneous regions for the three studied flow characteristics were obtained using the Mahalanobis similarity matrix and the complete linkage clustering method. The cluster analysis enabled the identification of four hydrologically homogeneous regions in the Doce river basin.
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This work describes techniques for modeling, optimizing and simulating calibration processes of robots using off-line programming. The identification of geometric parameters of the nominal kinematic model is optimized using techniques of numerical optimization of the mathematical model. The simulation of the actual robot and the measurement system is achieved by introducing random errors representing their physical behavior and its statistical repeatability. An evaluation of the corrected nominal kinematic model brings about a clear perception of the influence of distinct variables involved in the process for a suitable planning, and indicates a considerable accuracy improvement when the optimized model is compared to the non-optimized one.