ANÁLISE DE REGRESSÃO em EXPERIMENTOS em PARCELAS SUBDIVIDIDAS COM DADOS NÃO-BALANCEADOS: UMA SOLUÇÃO NA LINGUAGEM GLIM

São estabelecidas as matrizes necessárias para a realização da análise de variância de experimentos em parcelas subdivididas, com dados não-balanceados e balanceados, quando os tratamentos aplicados às parcelas e os tratamentos aplicados às subparcelas são ambos fatores quantitativos, usando a teoria de modelos lineares e de modelos lineares generalizados. Foi desenvolvido um programa computacional, na linguagem GLIM, para a realização da análise.

Modeling approach based on experimental results for prediction of measurement errors in energy meters

This paper presents a general modeling approach to investigate and to predict measurement errors in active energy meters both induction and electronic types. The measurement error modeling is based on Generalized Additive Model (GAM), Ridge Regression method and experimental results of meter provided by a measurement system. The measurement system provides a database of 26 pairs of test waveforms captured in a real electrical distribution system, with different load characteristics (industrial, commercial, agricultural, and residential), covering different harmonic distortions, and balanced and unbalanced voltage conditions. In order to illustrate the proposed approach, the measurement error models are discussed and several results, which are derived from experimental tests, are presented in the form of three-dimensional graphs, and generalized as error equations. © 2009 IEEE.

The AIDS epidemic in the Amazon region: a spatial case-control study in Rondonia, Brazil

OBJETIVO Analisar mudanças espaciais no risco de Aids e a relação entre incidência da doença e variáveis socioeconômicas. MÉTODOS Estudo caso-controle espacial, de base populacional, realizado em Rondônia, Brasil, com 1.780 casos notificados pelo Sistema de Vigilância Epidemiológica e os controles a partir de dados demográficos de 1987 a 2006. Os casos foram agrupados em cinco períodos de cinco anos consecutivos. Um modelo aditivo generalizado foi ajustado aos dados. O status dos indivíduos (caso ou controle) foi considerado como a variável dependente e independente: um alisamento ( spline ) bidimensional das coordenadas geográficas e variáveis socioeconômicas municipais. Os valores observados para o teste Moran I foram comparados com a distribuição de referência dos valores obtidos em condições de aleatoriedade espacial. RESULTADOS O risco de Aids apresentou padrão espacial e temporal marcado. A incidência associou-se a indicadores socioeconômicos municipais, como urbanização e capital humano. As maiores taxas de incidência de Aids ocorreram em municípios ao longo da rodovia BR-364; os resultados do teste Moran I mostram correlação espacial positiva associada à contiguidade dos municípios com a rodovia, no terceiro e quarto períodos (p = 0,05). CONCLUSÕES A incidência da doença foi maior em municípios de maior riqueza econômica e urbanização e naqueles cortados pelas estradas principais de Rondônia. O rápido desenvolvimento associado à ocupação de regiões remotas pode ser acompanhado por aumento de riscos à saúde.

Previsão da velocidade dos ventos por redes neurais artificiais e arima de box & jenkins

Pós-graduação em Engenharia Elétrica - FEIS

Spatial Distribution of the Risk of Dengue and the Entomological Indicators in Sumare, State of Sao Paulo, Brazil

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

Associação entre exposição ao material particulado e internações por doenças respiratórias em crianças

The aim of this study was to estimate the association between exposure to particulate matter less than 2.5 microns in diameter and hospitalization for respiratory diseases. It was an ecological time series study with daily indicators of hospitalization for respiratory diseases in children up to 10 years, living in Piracicaba, SP, Southeastern Brazil, between August 1, 2011 and July 31, 2012. We used generalized additive model for the Poisson regression. The relative risks were RR = 1.008; 95%CI 1.001; 1.016 for lag 1 and RR = 1.009; 95%CI 1.001; 1.017 for lag 3. The increment of 10 mu g/m(3) in particulate matter less than 2.5 microns in diameter implies increase in relative risk between 7.9 and 8.6 percentage points. In conclusion, exposure to particulate matter less than 2.5 microns in diameter was associated with hospitalization for respiratory diseases in children.

Assessment of the relationship between entomologic indicators of Aedes aegypti and the epidemic occurrence of dengue virus 3 in a susceptible population, São José do Rio Preto, Sao Paulo, Brazil

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

Estimation of a preference map of new consumers for spatial load forecasting simulation methods using a spatial analysis of points

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimação espaço-temporal das perdas não técnicas no sistema de distribuição de energia elétrica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The Abundance of Harbor Seals in the Gulf of Alaska

The abundance of harbor seals (Phoca vitulina richardii) has declined in recent decades at several Alaska locations. The causes of these declines are unknown, but there is concern about the status of the populations, especially in the Gulf of Alaska. To assess the status of harbor seals in the Gulf of Alaska, we conducted aerial surveys of seals on their haul-out sites in August-September 1996. Many factors influence the propensity of seals to haul out, including tides, weather, time of day, and time of year. Because these “covariates” cannot simultaneously be controlled through survey design, we used a regression model to adjust the counts to an estimate of the number of seals that would have been ashore during a hypothetical survey conducted under ideal conditions for hauling out. The regression, a generalized additive model, not only provided an adjustment for the covariates, but also confirmed the nature and shape of the covariate effects on haul-out behavior. The number of seals hauled out was greatest at the beginning of the surveys (mid-August). There was a broad daily peak from about 1100-1400 local solar time. The greatest numbers were hauled out at low tide on terrestrial sites. Tidal state made little difference in the numbers hauled out on glacial ice, where the area available to seals did not fluctuate with the tide. Adjusting the survey counts to the ideal state for each covariate produced an estimate of 30,035 seals, about 1.8 times the total of the unadjusted counts (16,355 seals). To the adjusted count, we applied a correction factor of 1.198 from a separate study of two haul-out sites elsewhere in Alaska, to produce a total abundance estimate of 35,981 (SE 1,833). This estimate accounts both for the effect of covariates on survey counts and for the proportion of seals that remained in the water even under ideal conditions for hauling out.

Survival Analysis of Patients with Heart Failure: Implications of Time-Varying Regression Effects in Modeling Mortality

Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.

Study of the interactions of Neptunium with humic substances and the clay mineral montmorillonite by direct and non direct speciation methods

For the safety assessment of radioactive waste, the possibility of radionuclide migration has to be considered. Since Np (and also Th due to the long-lived 232-Th) will be responsible for the greatest amount of radioactivity one million years after discharge from the reactor, its (im)-mobilization in the geosphere is of great importance. Furthermore, the chemistry of Np(V) is quite similar (but not identical) to the chemistry of Pu(V). Three species of neptunium may be found in the near field of the waste disposal, but pentavalent neptunium is the most abundant species under a wide range of natural conditions. Within this work, the interaction of Np(V) with the clay mineral montmorillonite and melanodins (as model substances for humic acids) was studied. The sorption of neptunium onto gibbsite, a model clay for montmorillonite, was also investigated. The sorption of neptunium onto γ-alumina and montmorillonite was studied in a parallel doctoral work by S. Dierking. Neptunium is only found in ultra trace amounts in the environment. Therefore, sensitive and specific methods are needed for its determination. The sorption was determined by γ spectroscopy and LSC for the whole concentration range studied. In addition the combination of these techniques with ultrafiltration allowed the study of Np(V) complexation with melanoidins. Regrettably, the available speciation methods (e.g. CE-ICP-MS and EXAFS) are not capable to detect the environmentally relevant neptunium concentrations. Therefore, a combination of batch experiments and speciation analyses was performed. Further, the preparation of hybrid clay-based materials (HCM) montmorillonitemelanoidins for sorption studies was achieved. The formation of hybrid materials begins in the interlayers of the montmorillonite, and then the organic material spreads over the surface of the mineral. The sorption of Np onto HCM was studied at the environmentally relevant concentrations and the results obtained were compared with those predicted by the linear additive model by Samadfam. The sorption of neptunium onto gibbsite was studied in batch experiments and the sorption maximum determined at pH~8.5. The sorption isotherm pointed to the presence of strong and weak sorption sites in gibbsite. The Np speciation was studied by using EXAFS, which showed that the sorbed species was Np(V). The influence of M42 type melanodins on the sorption of Np(V) onto montmorillonite was also investigated at pH 7. The sorption of the melanoidins was affected by the order in which the components were added and by ionic strength. The sorption of Np was affected by ionic strength, pointing to outer sphere sorption, whereas the presence of increasing amounts of melanoidins had little influence on Np sorption.

Markers Models in Survival Analysis and Applications to Issues Associated with AIDS

Jewell and Kalbfleisch (1992) consider the use of marker processes for applications related to estimation of the survival distribution of time to failure. Marker processes were assumed to be stochastic processes that, at a given point in time, provide information about the current hazard and consequently on the remaining time to failure. Particular attention was paid to calculations based on a simple additive model for the relationship between the hazard function at time t and the history of the marker process up until time t. Specific applications to the analysis of AIDS data included the use of markers as surrogate responses for onset of AIDS with censored data and as predictors of the time elapsed since infection in prevalent individuals. Here we review recent work on the use of marker data to tackle these kinds of problems with AIDS data. The Poisson marker process with an additive model, introduced in Jewell and Kalbfleisch (1992) may be a useful "test" example for comparison of various procedures.

Practical Large-Scale Spatio-Temporal Modeling of Particulate Matter Concentrations

The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988-2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. We develop a conceptually simple spatio-temporal model that uses a rich set of covariates. The model is used to estimate concentrations of PM10 for the full time period and PM2.5 for a subset of the period. For the earlier part of the period, 1988-1998, few PM2.5 monitors were operating, so we develop a simple extension to the model that represents PM2.5 conditionally on PM10 model predictions. In the epidemiological analysis, model predictions of PM10 are more strongly associated with health effects than when using simpler approaches to estimate exposure. Our modeling approach supports the application in estimating both fine-scale and large-scale spatial heterogeneity and capturing space-time interaction through the use of monthly-varying spatial surfaces. At the same time, the model is computationally feasible, implementable with standard software, and readily understandable to the scientific audience. Despite simplifying assumptions, the model has good predictive performance and uncertainty characterization.