66 resultados para Compositional data analysis-roots in geosciences


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Recurrences are close returns of a given state in a time series, and can be used to identify different dynamical regimes and other related phenomena, being particularly suited for analyzing experimental data. In this work, we use recurrence quantification analysis to investigate dynamical patterns in scalar data series obtained from measurements of floating potential and ion saturation current at the plasma edge of the Tokamak Chauffage Alfveacuten Breacutesilien [R. M. O. Galva approximate to o , Plasma Phys. Controlled Fusion 43, 1181 (2001)]. We consider plasma discharges with and without the application of radial electric bias, and also with two different regimes of current ramp. Our results indicate that biasing improves confinement through destroying highly recurrent regions within the plasma column that enhance particle and heat transport.

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A two-dimensional numeric simulator is developed to predict the nonlinear, convective-reactive, oxygen mass exchange in a cross-flow hollow fiber blood oxygenator. The numeric simulator also calculates the carbon dioxide mass exchange, as hemoglobin affinity to oxygen is affected by the local pH value, which depends mostly on the local carbon dioxide content in blood. Blood pH calculation inside the oxygenator is made by the simultaneous solution of an equation that takes into account the blood buffering capacity and the classical Henderson-Hasselbach equation. The modeling of the mass transfer conductance in the blood comprises a global factor, which is a function of the Reynolds number, and a local factor, which takes into account the amount of oxygen reacted to hemoglobin. The simulator is calibrated against experimental data for an in-line fiber bundle. The results are: (i) the calibration process allows the precise determination of the mass transfer conductance for both oxygen and carbon dioxide; (ii) very alkaline pH values occur in the blood path at the gas inlet side of the fiber bundle; (iii) the parametric analysis of the effect of the blood base excess (BE) shows that V(CO2) is similar in the case of blood metabolic alkalosis, metabolic acidosis, or normal BE, for a similar blood inlet P(CO2), although the condition of metabolic alkalosis is the worst case, as the pH in the vicinity of the gas inlet is the most alkaline; (iv) the parametric analysis of the effect of the gas flow to blood flow ratio (Q(G)/Q(B)) shows that V(CO2) variation with the gas flow is almost linear up to Q(G)/Q(B) = 2.0. V(O2) is not affected by the gas flow as it was observed that by increasing the gas flow up to eight times, the V(O2) grows only 1%. The mass exchange of carbon dioxide uses the full length of the hollow-fiber only if Q(G)/Q(B) > 2.0, as it was observed that only in this condition does the local variation of pH and blood P(CO2) comprise the whole fiber bundle.

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In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.

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This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

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In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

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Objective. To describe homicide mortality in the municipality of Sao Paulo according to type of weapon, sex, race or skin color, age, and areas of socioeconomic inequalities, between 1996 and 2008. Method. For this ecological time-series study, data about deaths in the municipality of Sao Paulo were collected from the municipal program for improvement of mortality information, using International Classification of Diseases, 10th revision (ICD-10) codes. Homicide mortality rates (HMR) were calculated for the overall population and specifically for each sex, race or skin color, age range, type of weapon, and occurrence in social deprivation/affluence areas. HMR were adjusted for age using the direct method. The percentage age of variation in HMR was calculated for the study period. For areas of socioeconomic inequalities, the relative risk of death from homicide was calculated. Results. HMR fell 73.7% between 2001 and 2008. A reduction in HMR was observed in all groups, especially males (-74.5%), young men between 15 and 24 years of age (-78.0%), and residents in areas of extreme socioeconomic deprivation (-79.3%). The reduction occurred mostly in firearm homicide rates (-74.1%). The relative risk of death from homicide in areas of extreme socioeconomic deprivation, as compared to areas with some degree of socioeconomic deprivation, was 2.77 in 1996, 3.9 in 2001, and 2.13 in 2008. In areas of high socioeconomic deprivation, the relative risk was 2.07 in 1996 and 1.96 in 2008. Conclusions. To understand the reduction in homicide rates in the municipality of Sao Paulo, it is important to take into consideration macrodeterminants that affect the entire municipality and all population subgroups, as well as micro/local determinants that have special impact on homicides committed with firearms and on subgroups such as the young, males, and residents of areas of high socioeconomic deprivation.

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Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

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Alzheimer`s Disease (AD) is the most common type of dementia among the elderly, with devastating consequences for the patient, their relatives, and caregivers. More than 300 genetic polymorphisms have been involved with AD, demonstrating that this condition is polygenic and with a complex pattern of inheritance. This paper aims to report and compare the results of AD genetics studies in case-control and familial analysis performed in Brazil since our first publication, 10 years ago. They include the following genes/markers: Apolipoprotein E (APOE), 5-hidroxytryptamine transporter length polymorphic region (5-HTTLPR), brain-derived neurotrophin factor (BDNF), monoamine oxidase A (MAO-A), and two simple-sequence tandem repeat polymorphisms (DXS1047 and D10S1423). Previously unpublished data of the interleukin-1 alpha (IL-1 alpha) and interleukin-1 beta (IL-1 beta) genes are reported here briefly. Results from others Brazilian studies with AD patients are also reported at this short review. Four local families studied with various markers at the chromosome 21, 19, 14, and 1 are briefly reported for the first time. The importance of studying DNA samples from Brazil is highlighted because of the uniqueness of its population, which presents both intense ethnical miscegenation, mainly at the east coast, but also clusters with high inbreeding rates in rural areas at the countryside. We discuss the current stage of extending these studies using high-throughput methods of large-scale genotyping, such as single nucleotide polymorphism microarrays, associated with bioinformatics tools that allow the analysis of such extensive number of genetics variables, with different levels of penetrance. There is still a long way between the huge amount of data gathered so far and the actual application toward the full understanding of AD, but the final goal is to develop precise tools for diagnosis and prognosis, creating new strategies for better treatments based on genetic profile.

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In this paper a new parametric method to deal with discrepant experimental results is developed. The method is based on the fit of a probability density function to the data. This paper also compares the characteristics of different methods used to deduce recommended values and uncertainties from a discrepant set of experimental data. The methods are applied to the (137)Cs and (90)Sr published half-lives and special emphasis is given to the deduced confidence intervals. The obtained results are analyzed considering two fundamental properties expected from an experimental result: the probability content of confidence intervals and the statistical consistency between different recommended values. The recommended values and uncertainties for the (137)Cs and (90)Sr half-lives are 10,984 (24) days and 10,523 (70) days, respectively. (C) 2009 Elsevier B.V. All rights reserved.

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One of the main questions on Neoproterozoic geology regards the extent and dynamics of the glacial systems that are recorded in all continents. We present evidence for short transport distances and localized sediment sources for the Bebedouro Formation, which records Neoproterozoic glaciomarine sedimentation in the central-eastern Sao Francisco Craton (SFC), Brazil. New data are presented on clast composition, based on point counting in thin section and SHRIMP dating of pebbles and detrital zircon. Cluster analysis of clast compositional data revealed a pronounced spatial variability of clast composition on diamictite indicating the presence of individual glaciers or ice streams feeding the basin. Detrital zircon ages reveal distinct populations of Archean and Palaeoproterozoic age. The youngest detrital zircon dated at 874 +/- 9 Ma constrains the maximum depositional age of these diamictites. We interpret the provenance of the glacial diamictites to be restricted to sources inside the SFC, suggesting deposition in an environment similar to ice streams from modern, high latitude glaciers.

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This in vivo study evaluated the dissociation quality of maxillary premolar roots combining variations of vertical and horizontal angulations by using X-ray holders (Rinn -XCP), and made a comparison between two types of intraoral radiography systems - conventional film (Kodak Insight, Rochester, USA) and digital radiography (Kodak RVG 6100, Kodak, Rochester, USA). The study sample was comprised of 20 patients with a total of 20 maxillary premolars that were radiographed, using the paralleling angle technique (GP), with a 20º variation of the horizontal angle (GM) and 25º variation of the horizontal angle combined with 15º vertical angle (GMV). Each image was independently analyzed by two experienced examiners. These examiners assigned a score to the diagnostic capability of root dissociation and the measurement of the distance between the apexes. Statistical data was derived using the Wilcoxon Signed Rank test, Friedman and T test. The means of the measured distances between buccal and lingual root apexes were greater for the GMV, which ranged from 2.3 mm to 3.3 mm. A statistically significant difference was found between GM and GMV when compared to GP with p < 0.01. An established best diagnostic dissociation roots image was found in the GMV. These results support the use of the anterior X-ray holders which offer a better combined deviation (GMV) to dissociate maxillary premolar roots in both radiography systems.

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This cross-sectional study aimed to investigate the presence of inequalities in the access and use of dental services for people living in the coverage area of the Family Health Strategy (FHS) in Ponta Grossa, Paraná State, Brazil, and to assess individual determinants related to them. The sample consisted of 747 individuals who answered a pre-tested questionnaire. Data analysis was performed by chi-square test and Poisson regression analysis, obtaining explanatory models for recent use and, by limiting the analysis to those who sought dental care, for effective access. Results showed that 41% of the sample had recent dental visits. The lowest visit rates were observed among preschoolers and elderly people. The subjects who most identified the FHS as a regular source of dental care were children. Besides age, better socioeconomic conditions and the presence of a regular source of dental care were positively associated to recent dental visits. We identified inequalities in use and access to dental care, reinforcing the need to promote incentives to improve access for underserved populations.

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Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method's sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results.

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Background: Researches to evaluate Primary Health Care performance in TB control in Brazil show that different cities aggregate local specificities in the dynamics of coping with the disease. This study aims to evaluate health services' performance in TB treatment in cities across different Brazilian regions. Methods: This cross-sectional study was conducted in five cities that are considered priorities for TB control in Brazil: Itaborai (ITA), Ribeirao Preto (RP) and Sao Jose do Rio Preto (SJRP) in the Southeast; Campina Grande (CG) and Feira de Santana (FS) in the Northeast. Data were collected through interviews with 514 TB patients under treatment in 2007, using the Primary Care Assessment Tool adapted for TB care in Brazil. Indicators were constructed based on the mean response scores (Likert scale) and compared among the study sites. Results: ""Access to treatment"" was evaluated as satisfactory in the Southeast and regular in the Northeast, which displayed poor results on 'home visits' and 'distance between treatment site and patient's house'. ""Bond"" was assessed as satisfactory in all cities, with a slightly better performance in RP and SJRP. ""Range of services"" was rated as regular, with better performance of southeastern cities. 'Health education', 'DOT' and 'food vouchers' were less offered in the Northeast. ""Coordination"" was evaluated as satisfactory in all cities. ""Family focus"" was evaluated as satisfactory in RP and SJRP, and regular in the others. 'Professional asking patient's family about other health problems' was evaluated as unsatisfactory, except in RP. Conclusions: Two types of obstacles are faced for health service performance in TB treatment in the cities under analysis, mainly in the Northeast. The first is structural and derives from difficulties to access health services and actions. The second is organizational and derives from the way health technologies and services are distributed and integrated. Incentives to improve care organization and management practices, aimed at the integration of primary, secondary and tertiary services, can contribute towards a better performance of health services in TB treatment.

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Background: Xylella fastidiosa, a Gram-negative fastidious bacterium, grows in the xylem of several plants causing diseases such as citrus variegated chlorosis. As the xylem sap contains low concentrations of amino acids and other compounds, X. fastidiosa needs to cope with nitrogen limitation in its natural habitat. Results: In this work, we performed a whole-genome microarray analysis of the X. fastidiosa nitrogen starvation response. A time course experiment (2, 8 and 12 hours) of cultures grown in defined medium under nitrogen starvation revealed many differentially expressed genes, such as those related to transport, nitrogen assimilation, amino acid biosynthesis, transcriptional regulation, and many genes encoding hypothetical proteins. In addition, a decrease in the expression levels of many genes involved in carbon metabolism and energy generation pathways was also observed. Comparison of gene expression profiles between the wild type strain and the rpoN null mutant allowed the identification of genes directly or indirectly induced by nitrogen starvation in a sigma(54)-dependent manner. A more complete picture of the sigma(54) regulon was achieved by combining the transcriptome data with an in silico search for potential sigma(54)-dependent promoters, using a position weight matrix approach. One of these sigma(54)-predicted binding sites, located upstream of the glnA gene (encoding glutamine synthetase), was validated by primer extension assays, confirming that this gene has a sigma(54)-dependent promoter. Conclusions: Together, these results show that nitrogen starvation causes intense changes in the X. fastidiosa transcriptome and some of these differentially expressed genes belong to the sigma(54) regulon.