978 resultados para NIRS. Plum. Multivariate calibration. Variables selection


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OBJECTIVE: To assess the relationship of blood lead and hemoglobin, zinc protoporphyrin, and ferritin concentrations in children. METHODS: A cross-sectional study was carried out in 136 anemic and non-anemic children from two rural villages near a lead smelter in Adrianópolis, Southern Brazil, from July to September 2001. Hemoglobin electrophoresis was performed to exclude children with hemoglobin variants and thalassemia syndromes associated with anemia. Lead was determined by atomic absorption spectrophotometry; hemoglobin by automated cell counting; zinc protoporphyrin by hematofluorometry; ferritin by chemiluminescence. Student's t-test, Mann-Whitney test, and the c² test were used to assess the significance of the differences between the variables investigated in anemic and non-anemic children. Stepwise multivariate linear regression analysis was performed using two models for anemic and non-anemic children respectively. RESULTS: Lead was negatively associated to hemoglobin (p<0.017) in the first model, and in the second model lead was positively associated to zinc protoporphyrin (p<0.004) after controlling for ferritin, age, sex, and per capita income. There was an inverse association between hemoglobin and blood lead in anemic children. It was not possible to confirm if anemic children had iron deficiency anemia or subclinical infection, considering that the majority (90.4%) had normal ferritin. CONCLUSIONS: The study detected a relationship between anemia and elevated blood lead concentrations. Further epidemiological studies are necessary to investigate the impact of iron nutritional interventions as an attempt to decrease blood lead in children.

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OBJECTIVE: To identify risk factors associated with infant mortality and, more specifically, with neonatal mortality. METHODS: A case-control study was carried out in the municipality of Caxias do Sul, Southern Brazil. Characteristics of prenatal care and causes of mortality were assessed for all live births in the 2001-2002 period with a completed live-birth certificate and whose mothers lived in the municipality. Cases were defined as all deaths within the first year of life. As controls, there were selected the two children born immediately after each case in the same hospital, who were of the same sex, and did not die within their first year of life. Multivariate analysis was performed using conditional logistic regression. RESULTS: There was a reduction in infant mortality, the greatest reduction was observed in the post-neonatal period. The variables gestational age (<36 weeks), birth weight (<2,500 g), and 5-minute Apgar (<6) remained in the final model of the multivariate analysis, after adjustment. CONCLUSIONS: Perinatal conditions comprise almost the totality of neonatal deaths, and the majority of deaths occur at delivery. The challenge for reducing infant mortality rate in the city is to reduce the mortality by perinatal conditions in the neonatal period.

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27th Annual Conference of the European Cetacean Society. Setúbal, Portugal, 8-10 April 2013.

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OBJECTIVE: To estimate the prevalence of alcohol abuse/dependence and identify associated factors among demographic, family, socioeconomic and mental health variables. METHODS: A household survey was carried out in the urban area of Campinas, southeastern Brazil, in 2003. A total of 515 subjects, aged 14 years or more were randomly selected using a stratified cluster sample. The Self-Report Questionnaire and the Alcohol Use Disorder Identification Test were used in the interview. Prevalences were calculated, and univariate and multivariate logistic analyses performed by estimating odds ratios and 95% confidence intervals. RESULTS: The estimated prevalence of alcohol abuse/dependence was 13.1% (95% CI: 8.4;19.9) in men and 4.1% (95% CI: 1.9;8.6) in women. In the final multiple logistic regression model, alcohol abuse/dependence was significantly associated with age, income, schooling, religion and illicit drug use. The adjusted odds ratios were significantly higher in following variables: income between 2,501 and 10,000 dollars (OR=10.29); income above 10,000 dollars (OR=10.20); less than 12 years of schooling (OR=13.42); no religion (OR=9.16) or religion other than Evangelical (OR=4.77); and illicit drug use during lifetime (OR=4.47). Alcohol abuse and dependence patterns were different according to age group. CONCLUSIONS: There is a significantly high prevalence of alcohol abuse/dependence in this population. The knowledge of factors associated with alcohol abuse, and differences in consumption patterns should be taken into account in the development of harm reduction strategies.

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Dissertação de Mestrado, Gestão e Conservação da Natureza, 11 de Junho de 2014, Universidade dos Açores.

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Tese de Doutoramento, Ciências do Mar (Biologia Marinha)

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Dissertação de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica Ramo de Manutenção e Produção

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3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

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Dissertação de Mestrado, Engenharia Zootécnica, 10 de Setembro de 2015, Universidade dos Açores.

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OBJECTIVE: To examine the interaction between physical and psychosocial demands of work associated to low back pain. METHODS: Cross-sectional study carried out in a stratified proportional random sample of 577 plastic industry workers in the metropolitan area of the city of Salvador, Northeast Brazil in 2002. An anonymous standard questionnaire was administered in the workplace by trained interviewers. Physical demands at work were self-rated on a 6-point numeric scale, with anchors at each end of the scale. Factor analysis was carried out on 11 physical demand variables to identify underlying factors. Psychosocial work demands were measured by demand, control and social support questions. Multivariate analysis was performed using the likelihood ratio test. RESULTS: The factor analysis identified two physical work demand factors: material handling (factor 1) and repetitiveness (factor 2). The multiple logistic regression analysis showed that factor 1 was positively associated with low back pain (OR=2.35, 95% CI 1.50;3.66). No interaction was found between physical and psychosocial work demands but both were independently associated to low back pain. CONCLUSIONS: The study found independent effects of physical and psychosocial work demands on low back pain prevalence and emphasizes the importance of physical demands especially of material handling involving trunk bending forward and trunk rotation regardless of age, gender, and body fitness.

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O estudo teve como objectivo comparar o impacto do estigma e do bem-estar subjectivo em pessoas com diferentes doenças crónicas. Foram avaliados 729 doentes, recrutados em hospitais de Portugal, que após o diagnóstico retomaram a sua vida normal. Controlando para um conjunto de variáveis sócio-demográficas e clínicas, a aplicação de Modelos de Análise de Covariância Multivariada, permitiu verificar diferenças significativas apenas para a percepção do estigma entre os grupos de doenças crónicas. Pessoas com obesidade, epilepsia e esclerose múltipla referem mais estigma e pessoas com diabetes tipo1 e miastenia gravis referem menos estigma.

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Cluster analysis for categorical data has been an active area of research. A well-known problem in this area is the determination of the number of clusters, which is unknown and must be inferred from the data. In order to estimate the number of clusters, one often resorts to information criteria, such as BIC (Bayesian information criterion), MML (minimum message length, proposed by Wallace and Boulton, 1968), and ICL (integrated classification likelihood). In this work, we adopt the approach developed by Figueiredo and Jain (2002) for clustering continuous data. They use an MML criterion to select the number of clusters and a variant of the EM algorithm to estimate the model parameters. This EM variant seamlessly integrates model estimation and selection in a single algorithm. For clustering categorical data, we assume a finite mixture of multinomial distributions and implement a new EM algorithm, following a previous version (Silvestre et al., 2008). Results obtained with synthetic datasets are encouraging. The main advantage of the proposed approach, when compared to the above referred criteria, is the speed of execution, which is especially relevant when dealing with large data sets.

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Resource constraints are becoming a problem as many of the wireless mobile devices have increased generality. Our work tries to address this growing demand on resources and performance, by proposing the dynamic selection of neighbor nodes for cooperative service execution. This selection is in uenced by user's quality of service requirements expressed in his request, tailoring provided service to user's speci c needs. In this paper we improve our proposal's formulation algorithm with the ability to trade o time for the quality of the solution. At any given time, a complete solution for service execution exists, and the quality of that solution is expected to improve overtime.

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil

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Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.