946 resultados para Random regression models


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A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

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This paper examines the spatial pattern of ill-defined causes of death across Brazilian regions, and its relationship with the evolution of completeness of the deaths registry and changes in the mortality age profile. We make use of the Brazilian Health Informatics Department mortality database and population censuses from 1980 to 2010. We applied demographic methods to evaluate the quality of mortality data for 137 small areas and correct for under-registration of death counts when necessary. The second part of the analysis uses linear regression models to investigate the relationship between, on the one hand, changes in death counts coverage and age profile of mortality, and on the other, changes in the reporting of ill-defined causes of death. The completeness of death counts coverage increases from about 80% in 1980-1991 to over 95% in 2000-2010 at the same time the percentage of ill-defined causes of deaths reduced about 53% in the country. The analysis suggests that the government's efforts to improve data quality are proving successful, and they will allow for a better understanding of the dynamics of health and the mortality transition.

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Investigate factors associated with the onset of diabetes in women aged more than 49 years. Cross-sectional, population-based study using self-reports with 622 women. The dependent variable was the age of occurrence of diabetes using the life table method. Cox multiple regression models were adjusted to analyse the onset of diabetes according to predictor variables. Sociodemographic, clinical and behavioural factors were evaluated. Of the 622 women interviewed, 22.7% had diabetes. The mean age at onset was 56 years. The factors associated with the age of occurrence of diabetes were self-rated health (very good, good) (coefficient=-0.792; SE of the coefficient=0.215; p=0.0001), more than two individuals living in the household (coefficient=0.656, SE of the coefficient=0.223; p=0.003), and body mass index (BMI) (kg/m(2)) at 20-30 years of age (coefficient= 0.056, SE of the coefficient=0.023; p=0.014). Self-rated health considered good or very good was associated with a higher rate of survival without diabetes. Sharing a home with two or more other people and a weight increase at 20-30 years of age was associated with the onset of type 2 diabetes.

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A method using the ring-oven technique for pre-concentration in filter paper discs and near infrared hyperspectral imaging is proposed to identify four detergent and dispersant additives, and to determine their concentration in gasoline. Different approaches were used to select the best image data processing in order to gather the relevant spectral information. This was attained by selecting the pixels of the region of interest (ROI), using a pre-calculated threshold value of the PCA scores arranged as histograms, to select the spectra set; summing up the selected spectra to achieve representativeness; and compensating for the superimposed filter paper spectral information, also supported by scores histograms for each individual sample. The best classification model was achieved using linear discriminant analysis and genetic algorithm (LDA/GA), whose correct classification rate in the external validation set was 92%. Previous classification of the type of additive present in the gasoline is necessary to define the PLS model required for its quantitative determination. Considering that two of the additives studied present high spectral similarity, a PLS regression model was constructed to predict their content in gasoline, while two additional models were used for the remaining additives. The results for the external validation of these regression models showed a mean percentage error of prediction varying from 5 to 15%.

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In this work a fast method for the determination of the total sugar levels in samples of raw coffee was developed using the near infrared spectroscopy technique and multivariate regression. The sugar levels were initially obtained using gravimety as the reference method. Later on, the regression models were built from the near infrared spectra of the coffee samples. The original spectra were pre-treated according to the Kubelka-Munk transformation and multiplicative signal correction. The proposed analytical method made possible the direct determination of the total sugar levels in the samples with an error lower by 8% with respect to the conventional methodology.

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Remote sensing data are each time more available and can be used to monitor the vegetal development of main agricultural crops, such as the Arabic coffee in Brazil, since that the relationship between spectral and agronomical data be well known. Therefore, this work had the main objective to assess the use of Quickbird satellite images to estimate biophysical parameters of coffee crop. Test area was composed by 25 coffee fields located between the cities of Ribeirão Corrente, Franca and Cristais Paulista (SP), Brazil, and the biophysical parameters used were row and between plants spacing, plant height, LAI, canopy diameter, percentage of vegetation cover, roughness and biomass. Spectral data were the reflectance of four bands of QUICKBIRD and values of four vegetations indexes (NDVI, GVI, SAVI and RVI) based on the same satellite. All these data were analyzed using linear and nonlinear regression methods to generate estimation models of biophysical parameters. The use of regression models based on nonlinear equations was more appropriate to estimate parameters such as the LAI and the percentage of biomass, important to indicate the productivity of coffee crop.

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The main objective of this work was to evaluate the linear regression between spectral response and soybean yield in regional scale. In this study were monitored 36 municipalities from the west region of the states of Parana using five images of Landsat 5/TM during 2004/05 season. The spectral response was converted in physical values, apparent and surface reflectances, by radiometric transformation and atmospheric corrections and both used to calculate NDVI and GVI vegetation indices. Those ones were compared by multiple and simple regression with government official yield values (IBGE). Diagnostic processing method to identify influents values or collinearity was applied to the data too. The results showed that the mean surface reflectance value from all images was more correlated with yield than individual dates. Further, the multiple regressions using all dates and both vegetation indices gave better results than simple regression.

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Root canal treatment is a frequently performed dental procedure and is carried out on teeth in which irreversible pulpitis has led to necrosis of the dental pulp. Removal of the necrotic tissue remnants and cleaning and shaping of the root canal are important phases of root canal treatment. Treatment options include the use of hand and rotary instruments and methods using ultrasonic or sonic equipment. OBJECTIVES: The objectives of this systematic review of randomized controlled trials were to determine the relative clinical effectiveness of hand instrumentation versus ultrasonic instrumentation alone or in conjunction with hand instrumentation for orthograde root canal treatment of permanent teeth. MATERIAL AND METHODS: The search strategy retrieved 226 references from the Cochrane Oral Health Group Trials Register (7), the Cochrane Central Register of Controlled Trials (CENTRAL) (12), MEDLINE (192), EMBASE (8) and LILACS (7). No language restriction was applied. The last electronic search was conducted on December 13th, 2007. Screening of eligible studies was conducted in duplicate and independently. RESULTS: Results were to be expressed as fixed-effect or random-effects models using mean differences for continuous outcomes and risk ratios for dichotomous outcomes with 95% confdence intervals. Heterogeneity was to be investigated including both clinical and methodological factors. No eligible randomized controlled trials were identifed. CONCLUSIONS: This review illustrates the current lack of published or ongoing randomized controlled trials and the unavailability of high-level evidence based on clinically relevant outcomes referring to the effectiveness of ultrasonic instrumentation used alone or as an adjunct to hand instrumentation for orthograde root canal treatment. In the absence of reliable research-based evidence, clinicians should base their decisions on clinical experience, individual circumstances and in conjunction with patients' preferences where appropriate. Future randomized controlled trials might focus more closely on evaluating the effectiveness of combinations of these interventions with an emphasis on not only clinically relevant, but also patient-centered outcomes.

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We assessed the inequality in the distribution of dental caries and the association between indicators of socioeconomic status and caries experience in a representative sample of schoolchildren. This study followed a cross-sectional design, with a sample of 792 schoolchildren aged 12 years, representative of this age group in Santa Maria, RS, Brazil. Guardians answered questions on socioeconomic status and a dental examination provided information on the dental caries experience (DMF-T). Inequality in dental caries distribution was measured by the Gini coefficient and the Significant Caries Index (SiC). The assessment of association used Poisson regression models. Socioeconomic factors were associated with prevalence of dental caries for the whole sample and also for individuals with a high-caries level. Children from low-income households had the highest prevalence of dental caries. The Gini coefficient was 0.7 and the SiC Index 2.5. The percentage of caries prevalence was 39.3% (95% CI: 35.8%-42.8%) and the mean for DMF-T was 0.9 (± SD 1.5). Inequalities in the distribution of dental caries were observed and socioeconomic factors were found to be strong predictors of the prevalence of oral disease in children of this age group.

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Este estudo teve como objetivo desenvolver modelos preditores de fitomassa epigéa da vegetação arbórea da Floresta Baixa de Restinga. Foram selecionadas 102 árvores de 29 espécies ocorrentes na área de estudo e 102 indivíduos de jerivá (Syagrus romanzoffiana (Cham.) Glassman), distribuídos proporcionalmente entre as classes de diâmetro da vegetação arbórea. As árvores foram cortadas, ao nível do solo e foram medidos a altura total e o diâmetro à altura do peito (DAP) de cada árvore. As folhas foram separadas do lenho e a massa fresca da porção lenhosa e foliar medidas separadamente. Amostras de cada fração foram secas a 70 °C, até peso constante, para determinação da massa seca das árvores. Os modelos foram desenvolvidos através de análise de regressão linear, sendo a variável dependente a massa seca (MS) das árvores e as variáveis independentes a altura (h), o diâmetro a altura do peito (d) e as relações d² h e d² h multiplicada pela densidade da madeira (ρ d² h). Os modelos desenvolvidos indicam que o diâmetro explica grande parte da variabilidade da fitomassa das árvores da restinga e a altura é a variável explanatória da equação específica para o jerivá. Os modelos selecionados foram: ln MS (kg) = -1,352 + 2,009 ln d (R² = 0,96; s yx = 0,34) para a comunidade vegetal sem jerivá, ln MS (kg) = -2,052 + 0,801 ln d² h (R² = 0,94; s yx = 0,38) para a comunidade incluindo o jerivá, e ln MS (kg) = -0,884 + 2,40 ln h (R² = 0,92; s yx = 0,49) para o jerivá.

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The ADH (alcohol dehydrogenase) system is one of the earliest known models of molecular evolution, and is still the most studied in Drosophila. Herein, we studied this model in the genus Anastrepha (Diptera, Tephritidae). Due to the remarkable advantages it presents, it is possible to cross species with different Adh genotypes and with different phenotype traits related to ethanol tolerance. The two species studied here each have a different number of Adh gene copies, whereby crosses generate polymorphisms in gene number and in composition of the genetic background. We measured certain traits related to ethanol metabolism and tolerance. ADH specific enzyme activity presented gene by environment interactions, and the larval protein content showed an additive pattern of inheritance, whilst ADH enzyme activity per larva presented a complex behavior that may be explained by epistatic effects. Regression models suggest that there are heritable factors acting on ethanol tolerance, which may be related to enzymatic activity of the ADHs and to larval mass, although a pronounced environmental effect on ethanol tolerance was also observed. By using these data, we speculated on the mechanisms of ethanol tolerance and its inheritance as well as of associated traits.

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OBJECTIVE: To analyze the impact on human health of exposure to particulate matter emitted from burnings in the Brazilian Amazon region. METHODS: This was an ecological study using an environmental exposure indicator presented as the percentage of annual hours (AH%) of PM2.5 above 80 μg/m3. The outcome variables were the rates of hospitalization due to respiratory disease among children, the elderly and the intermediate age group, and due to childbirth. Data were obtained from the National Space Research Institute and the Ministry of Health for all of the microregions of the Brazilian Amazon region, for the years 2004 and 2005. Multiple regression models for the outcome variables in relation to the predictive variable AH% of PM2.5 above 80 μg/m3 were analyzed. The Human Development Index (HDI) and mean number of complete blood counts per 100 inhabitants in the Brazilian Amazon region were the control variables in the regression analyses. RESULTS: The association of the exposure indicator (AH%) was higher for the elderly than for other age groups (β = 0.10). For each 1% increase in the exposure indicator there was an increase of 8% in child hospitalization, 10% in hospitalization of the elderly, and 5% for the intermediate age group, even after controlling for HDI and mean number of complete blood counts. No association was found between the AH% and hospitalization due to childbirth. CONCLUSIONS: The indicator of atmospheric pollution showed an association with occurrences of respiratory diseases in the Brazilian Amazon region, especially in the more vulnerable age groups. This indicator may be used to assess the effects of forest burning on human health.

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OBJETIVO: Analisar a tendência da mortalidade por diarreia entre menores de 5 anos, no município de Osasco (SP), entre 1980 e 2000. MÉTODOS: Trata-se de estudo observacional com dois delineamentos. Um descritivo, que toma o indivíduo como unidade do estudo, e outro ecológico, analisando agregado populacional que incluiu análise de séries temporais. A fonte de dados foi o sistema de informação de mortalidade do Estado de São Paulo e censos de 1980, 1991 e 2000. Descreveu-se a variação sazonal e para a análise de tendência aplicaram-se modelos log lineares de regressão polinomiais, utilizando-se variáveis sociodemográficas da criança e da mãe. Foram analisadas a evolução de indicadores sociodemográficos do município de 1980 a 2000, as taxas médias de mortalidade por diarreia nos menores de 5 anos e seus diferenciais por distrito nos anos 90. RESULTADOS: Dos 1.360 óbitos, 94,3 e 75,3% atingiram, respectivamente, menores de 1 ano e de 6 meses. O declínio da mortalidade foi de 98,3%, com deslocamento da sazonalidade do verão para o outono. A mediana da idade elevou-se de 2 meses nos primeiros períodos para 3 meses no último. O resíduo de óbitos manteve-se entre filhos de mães de 20 a 29 anos e escolaridade < 8 anos. O risco relativo entre o distrito mais atingido e a taxa média do município diminuiu de 3,4 para 1,3 do primeiro para o segundo quinquênio dos anos 90. CONCLUSÃO: Nossos resultados apontam uma elevação da idade mais vulnerável e a provável mudança do agente mais frequentemente associado ao óbito por diarreia.

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O presente estudo teve como objetivo descrever as principais características dos estudos epidemiológicos que investigaram a associação entre condições socioeconômicas e câncer de cabeça e pescoço. Foram pesquisadas as bases de dados Medline (Literatura Internacional em Ciências), Lilacs (Literatura Latino-Americana e do Caribe em Ciências da Saúde) e Scielo (Scientific Electronic Library Online), além de referências citadas nos artigos obtidos a partir da busca primária nessas bases. O período de publicação considerado englobou 38 anos (1970-2007) e a análise restringiu-se aos artigos em espanhol, inglês ou português. Foram selecionados 25 estudos, 15 com delineamento caso-controle, quatro ecológicos e seis que mesclaram informações de bases de dados oficiais, como censos e registros de câncer ou de óbitos. A maior parte das pesquisas reportou associação entre piores condições socioeconômicas e câncer de cabeça e pescoço. Os indicadores mais empregados foram a ocupação e a escolaridade. Poucos estudos investigaram mediação, procurando evidenciar quais os fatores proximais operam na associação investigada. Pesquisas adicionais, com critérios uniformes para proceder aos ajustes nos modelos de regressão e amostra suficiente, são necessárias para investigar essa dimensão.