The role of clouds in improving the regression model for hourly values of diffuse solar radiation

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Anti-hypertensive drugs have different effects on ventricular hypertrophy regression

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUÇÃO: A malaria é uma doença endêmica na região da Amazônia Brasileira, e a detecção de possíveis fatores de risco pode ser de grande interesse às autoridades em saúde pública. O objetivo deste artigo é investigar a associação entre variáveis ambientais e os registros anuais de malária na região amazônica usando métodos bayesianos espaço-temporais. MÉTODOS: Utilizaram-se modelos de regressão espaço-temporais de Poisson para analisar os dados anuais de contagem de casos de malária entre os anos de 1999 a 2008, considerando a presença de alguns fatores como a taxa de desflorestamento. em uma abordagem bayesiana, as inferências foram obtidas por métodos Monte Carlo em cadeias de Markov (MCMC) que simularam amostras para a distribuição conjunta a posteriori de interesse. A discriminação de diferentes modelos também foi discutida. RESULTADOS: O modelo aqui proposto sugeriu que a taxa de desflorestamento, o número de habitants por km² e o índice de desenvolvimento humano (IDH) são importantes para a predição de casos de malária. CONCLUSÕES: É possível concluir que o desenvolvimento humano, o crescimento populacional, o desflorestamento e as alterações ecológicas associadas a estes fatores estão associados ao aumento do risco de malária. Pode-se ainda concluir que o uso de modelos de regressão de Poisson que capturam o efeito temporal e espacial em um enfoque bayesiano é uma boa estratégia para modelar dados de contagem de malária.

The Poisson-exponential regression model under different latent activation schemes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The Conway-Maxwell-Poisson-generalized gamma regression model with long-term survivors

In this paper, we proposed a flexible cure rate survival model by assuming the number of competing causes of the event of interest following the Conway-Maxwell distribution and the time for the event to follow the generalized gamma distribution. This distribution can be used to model survival data when the hazard rate function is increasing, decreasing, bathtub and unimodal-shaped including some distributions commonly used in lifetime analysis as particular cases. Some appropriate matrices are derived in order to evaluate local influence on the estimates of the parameters by considering different perturbations, and some global influence measurements are also investigated. Finally, data set from the medical area is analysed.

Short-Term Multinodal Load Forecasting Using a Modified General Regression Neural Network

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Cytokines and acute-phase serum proteins as markers of inflammatory regression during pulmonary tuberculosis treatment

Tuberculosis is still increasing and was declared a worldwide sanitary emergency by the World Health Organization (WHO) in 1995. Its control is difficult due to long treatment duration and lack of markers of treatment success or failure. Cytokines such as IFN-gamma and TNF-alpha, a central factor in immune response against Mycobacterium tuberculosis, are responsible for the interaction between T lymphocytes and the infected macrophage and are also produced during this interaction. As proinflammatory cytokines have a close relationship with mycobacteria clearance, in fact even preceding it, they could be used as markers for inflammatory activity and response to treatment. Proinflammatory cytokines act in the liver and stimulate a strong local and systemic acute-phase response as a result of homeostatic and physiological responses also induced by them. Acute-phase proteins produced by cytokine activity are useful diagnostic markers that could also be used to monitor treatment response as they can be serially quantified. The objective of this study was to evaluate IFN-gamma, TNF-alpha, IL-10 and TGF-beta production in supernatant of peripheral blood mononuclear cell (PBMC) and monocyte (MO) cultures, as well as serum acute-phase response through total protein, albumin, globulin, C-reactive protein (CRP), alpha-1-acid glycoprotein (AGP), and erythrocyte sedimentation rate (ESR) as regression markers of inflammatory response during pulmonary tuberculosis treatment. Twenty blood donors (G1) from the Blood Bank at Botucatu School of Medicine's University Hospital (BSM-UH) were evaluated once and 28 pulmonary tuberculosis patients (G2): 13 from BSM-UH and 15 from the Bauru State Health Secretariat. Patients were evaluated at three moments of treatment: before (M1), at three months (M2), and at the end (M3). Cytokines were determined in 20ml of peripheral blood (ELISA), with or without activation: lipopolysaccharide (LPS) for MO culture and phytohemagglutinin (PHA) for PBMC culture. Acute-phase protein behavior in G2 throughout treatment was: Globulins: M1> M2, M1> M3 (rho < 0.001); CRP: M1> M2> M3 (.< 0.001); AGP for men: M1> M2, M1> M3 (rho < 0.001); ESR for men: M1> M2, M1> M3 (rho < 0.0016) and for women: M1> M2 (.< 0.025). Comparison between cytokine levels found in supernatant of MO and PBMC cultures, with and without stimulus, in G1 and G2 during treatment showed: TNF-alpha (with/ without LPS) at M1: G2> G1; at M2: G2> G1 (rho < 0.001); (without LPS) at M3: G2> G1 (rho < 0.001), (with LPS) at M3: G2> G1 (rho < 0.028); IFN-. (with and without PHA) at M1: G2> G1; at M2: G2> G1 (rho < 0.001); IL-10 (with and without LPS) at M1: G2> G1; at M2: G2> G1; at M3: G2> G1 (rho < 0.001); TGF-beta (with and without LPS) at M1: G2> G1; at M2: G2> G1 (rho < 0.001), (without LPS) at M3: G2> G1 (rho < 0.001). In G2, all cytokines in supernatant of MO and PBMC cultures, with and without stimulus, showed: M1> M2> M3 (rho < 0.01). Levels of globulins, CRP, AGP, and ESR in patients with pulmonary tuberculosis before treatment (M1) were significantly higher than reference values, suggesting their use as diagnostic markers and indicators of treatment. The CRP decreasing values along treatment could be taken as a marker of the regression of inflammatory process and of response to treatment in patients with pulmonary tuberculosis.Regarding cytokines, there was significant increase in TNF-alpha, IFN-gamma, IL-10, and TGF-alpha levels before and at three months treatment, with and without stimulus; in TNF-a and IL-10 lvels, with and without stimulus, as well as in TGF-alpha levels without stimulus at six months. Patients had higher levels of all studied cytokines than controls before treatment, and these values decreased along treatment. In this study, pulmonary tuberculosis patients showed a Th0 cytokine profile before treatment, with the production of both Th1 (IFN-gamma) and Th2 (IL-10) cytokines, in addition to TNF-alpha inflammatory and TGF-alpha regulatory and fibrosis-inducer cytokines. At the end of treatment, all had evolved to Th2 profile, probably in an attempt to reduce the harmful effects of the proinflammatory activity of the Th1 cytokine profile and of the still above-normal levels of TNF-alpha. The high levels of TGF-alpha, also found in these patients, are related to its important role in the extracellular matrix deposition and fibrosis induction that characterize tuberculosis healing process. IFN-gamma was the only cytokine reaching normal levels at the end of treatment, which suggests its use as a marker of response to treatment.

Interpretação de dados de GPR com base na hierarquização de superfícies limitantes e na adaptação de critérios sismoestratigráficos

Due to its high resolution, Ground Penetrating Radar (GPR) has been used to image subsurface sedimentary deposits. Because GPR and Seismic methods share some principles of image construction, the classic seismostratigraphic interpretation method has been also applied as an attempt to interpret GPR data. Nonetheless some advances in few particular contexts, the adaptations from seismic to GPR of seismostratigraphic tools and concepts unsuitable because the meaning given to the termination criteria in seismic stratigraphy do not represent the adequate geologic record in the GPR scale. Essentially, the open question relies in proposing a interpretation method for GPR data which allow not only relating product and sedimentary process in the GPR scale but also identifying or proposing depositional environments and correlating these results with the well known Sequence Stratigraphy cornerstones. The goal of this dissertation is to propose an interpretation methodology of GPR data able to perform this task at least for siliciclastic deposits. In order to do so, the proposed GPR interpretation method is based both on seismostratigraphic concepts and on the bounding surface hierarchy tool from Miall (1988). As consequence of this joint use, the results of GPR interpretation can be associated to the sedimentary facies in a genetic context, so that it is possible to: (i) individualize radar facies and correlate them to the sedimentary facies by using depositional models; (ii) characterize a given depositional system, and (iii) determine its stratigraphic framework highligthing how it evolved through geologic time. To illustrate its use the proposed methodology was applied in a GPR data set from Galos area which is part of the Galinhos spit, located in Rio Grande do Norte state, Northeastern Brazil. This spit presents high lateral sedimentary facies variation, containing in its sedimentary record from 4th to 6th cicles caused by high frequency sea level oscillation. The interpretation process was done throughout the following phases: (i) identification of a vertical facies succession, (ii) characterization of radar facies and its associated sedimentary products, (iii) recognition of the associated sedimentary process in a genetic context, and finally (iv) proposal of an evolutionay model for the Galinhos spit. This model proposes that the Galinhos spit is a barrier island constituted, from base to top, of the following sedimentary facies: tidal channel facies, tidal flat facies, shore facies, and aeolic facies (dunes). The tidal channel facies, in the base, is constituted of lateral accretion bars and filling deposits of the channels. The base facies is laterally truncated by the tidal flat facies. In the foreshore zone, the tidal flat facies is covered by the shore facies which is the register of a sea transgression. Finally, on the top of the stratigraphic column, aeolic dunes are deposited due to areal exposition caused by a sea regression

Canine corpus luteum regression: Apoptosis and caspase-3 activity

The present study evaluated the occurrence of apoptosis and caspase-3 activity in the canine corpus luteum during the period of luteal regression in eight pregnant and nine nonpregnant diestrus bitches. Intact luteal cells were obtained from corpora lutea in both peripartum pregnant bitches and nonpregnant diestrus bitches at approximately 65 d (range 63-68) after estrus, but not at days 75 and 85 in nonpregnant bitches. In all bitches, apoptotic cells were rarely detected and when present, those cells were more easily detected using the hematoxylin and eosin technique than using the critical electrolyte concentration technique. The luteal structures at 75 and 85 d of diestrus had histological characteristics similar to a corpus albicans. Caspase-3 activity was detected in morphologically normal corpora lutea from both pregnant and diestrus bitches around day 65, and also in the later structures considered corpus albicans tissue. These results suggested that apoptosis may not be the major mechanism involved in canine functional luteal regression, and that caspase-3 participated in both functional and morphological luteolysis and in the tissue reorganization involved in corpus albicans formation. (c) 2006 Published by Elsevier B.V.

Logistic regression analysis of potential prognostic factors for pulmonary thromboembolism

Objective: To identify potential prognostic factors for pulmonary thromboembolism (PTE), establishing a mathematical model to predict the risk for fatal PTE and nonfatal PTE.Method: the reports on 4,813 consecutive autopsies performed from 1979 to 1998 in a Brazilian tertiary referral medical school were reviewed for a retrospective study. From the medical records and autopsy reports of the 512 patients found with macroscopically and/or microscopically,documented PTE, data on demographics, underlying diseases, and probable PTE site of origin were gathered and studied by multiple logistic regression. Thereafter, the jackknife method, a statistical cross-validation technique that uses the original study patients to validate a clinical prediction rule, was performed.Results: the autopsy rate was 50.2%, and PTE prevalence was 10.6%. In 212 cases, PTE was the main cause of death (fatal PTE). The independent variables selected by the regression significance criteria that were more likely to be associated with fatal PTE were age (odds ratio [OR], 1.02; 95% confidence interval [CI], 1.00 to 1.03), trauma (OR, 8.5; 95% CI, 2.20 to 32.81), right-sided cardiac thrombi (OR, 1.96; 95% CI, 1.02 to 3.77), pelvic vein thrombi (OR, 3.46; 95% CI, 1.19 to 10.05); those most likely to be associated with nonfatal PTE were systemic arterial hypertension (OR, 0.51; 95% CI, 0.33 to 0.80), pneumonia (OR, 0.46; 95% CI, 0.30 to 0.71), and sepsis (OR, 0.16; 95% CI, 0.06 to 0.40). The results obtained from the application of the equation in the 512 cases studied using logistic regression analysis suggest the range in which logit p > 0.336 favors the occurrence of fatal PTE, logit p < - 1.142 favors nonfatal PTE, and logit P with intermediate values is not conclusive. The cross-validation prediction misclassification rate was 25.6%, meaning that the prediction equation correctly classified the majority of the cases (74.4%).Conclusions: Although the usefulness of this method in everyday medical practice needs to be confirmed by a prospective study, for the time being our results suggest that concerning prevention, diagnosis, and treatment of PTE, strict attention should be given to those patients presenting the variables that are significant in the logistic regression model.

Some practical advice on polynomial regression analysis from blocked response surface designs

It is often necessary to run response surface designs in blocks. In this paper the analysis of data from such experiments, using polynomial regression models, is discussed. The definition and estimation of pure error in blocked designs are considered. It is recommended that pure error is estimated by assuming additive block and treatment effects, as this is more consistent with designs without blocking. The recovery of inter-block information using REML analysis is discussed, although it is shown that it has very little impact if thc design is nearly orthogonally blocked. Finally prediction from blocked designs is considered and it is shown that prediction of many quantities of interest is much simpler than prediction of the response itself.

BORN-INFELD ELECTRODYNAMICS and EULER-HEISENBERG-LIKE MODEL: OUTSTANDING EXAMPLES of THE LACK of COMMUTATIVITY AMONG QUANTIZED TRUNCATED ACTIONS and TRUNCATED QUANTIZED ACTIONS

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Carbon Nuclear Magnetic Resonance Spectroscopic Profiles coupled to Partial Least-Squares Multivariate Regression for Prediction of Several Physicochemical Parameters of Brazilian Commercial Gasoline

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Logistic regression to estimate the welfare of broiler breeders in relation to environmental and behavioral variables

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bayesian binary regression model: an application to in-hospital death after AMI prediction

Um modelo bayesiano de regressão binária é desenvolvido para predizer óbito hospitalar em pacientes acometidos por infarto agudo do miocárdio. Métodos de Monte Carlo via Cadeias de Markov (MCMC) são usados para fazer inferência e validação. Uma estratégia para construção de modelos, baseada no uso do fator de Bayes, é proposta e aspectos de validação são extensivamente discutidos neste artigo, incluindo a distribuição a posteriori para o índice de concordância e análise de resíduos. A determinação de fatores de risco, baseados em variáveis disponíveis na chegada do paciente ao hospital, é muito importante para a tomada de decisão sobre o curso do tratamento. O modelo identificado se revela fortemente confiável e acurado, com uma taxa de classificação correta de 88% e um índice de concordância de 83%.