Borel-Leroy summability of a nonpolynomial potential

We investigate the perturbation series for the spectrum of a class of Schrodinger operators with potential V = 1/2 x(2) + g(m-1)x(2m)/(1 + alpha gx(2)) which generalize particular cases investigated in the literature in connection with models in laser theory and quantum field theory of particles and fields. It is proved that the series obey a modified strong asymptotic condition of order (m - 1) and have an order (m - 1) strong asymptotic series in g which are shown to be summable in the sense of Borel-Leroy method.

The number of open paths in an oriented rho-percolation model

We study the asymptotic properties of the number of open paths of length n in an oriented rho-percolation model. We show that this number is e(n alpha(rho)(1+o(1))) as n ->infinity. The exponent alpha is deterministic, it can be expressed in terms of the free energy of a polymer model, and it can be explicitly computed in some range of the parameters. Moreover, in a restricted range of the parameters, we even show that the number of such paths is n(-1/2)We (n alpha(rho))(1+o(1)) for some nondegenerate random variable W. We build on connections with the model of directed polymers in random environment, and we use techniques and results developed in this context.

Size and power properties of some tests in the Birnbaum-Saunders regression model

The Birnbaum-Saunders distribution has been used quite effectively to model times to failure for materials subject to fatigue and for modeling lifetime data. In this paper we obtain asymptotic expansions, up to order n(-1/2) and under a sequence of Pitman alternatives, for the non-null distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the Birnbaum-Saunders regression model. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters and for testing the shape parameter. Monte Carlo simulation is presented in order to compare the finite-sample performance of these tests. We also present two empirical applications. (C) 2010 Elsevier B.V. All rights reserved.

Estimation of the mean quality-adjusted survival using a multistate model for the sojourn times

In clinical trials, it may be of interest taking into account physical and emotional well-being in addition to survival when comparing treatments. Quality-adjusted survival time has the advantage of incorporating information about both survival time and quality-of-life. In this paper, we discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models for the sojourn times in health states. Semiparametric and parametric (with exponential distribution) approaches are considered. A simulation study is presented to evaluate the performance of the proposed estimator and the jackknife resampling method is used to compute bias and variance of the estimator. (C) 2007 Elsevier B.V. All rights reserved.

Local power of some tests in exponential family nonlinear models

In this paper we obtain asymptotic expansions up to order n(-1/2) for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in exponential family nonlinear models (Cordeiro and Paula, 1989), under a sequence of Pitman alternatives. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters and for testing the dispersion parameter, thus generalising the results given in Cordeiro et al. (1994) and Ferrari et al. (1997). We also present Monte Carlo simulations in order to compare the finite-sample performance of these tests. (C) 2010 Elsevier B.V. All rights reserved.

Volsurf Descriptors to Analyse Anti-HCV and Cytotoxic Activities of Sesquiterpene Lactones from Asteraceae Family

Various significant anti-HCV and cytotoxic sesquiterpene lactones (SLs) have been characterized. In this work, the chemometric tool Principal Component Analysis (PCA) was applied to two sets of SLs and the variance of the biological activity was explored. The first principal component accounts for as much of the variability in the data as possible, and each succeeding component accounts for as much of the remaining variability as possible. The calculations were performed using VolSurf program. For anti-HCV activity, PC1 (First Principal Component) explained 30.3% and PC2 (Second Principal Component) explained 26.5% of matrix total variance, while for cytotoxic activity, PC1 explained 30.9% and PC2 explained 15.6% of the total variance. The formalism employed generated good exploratory and predictive results and we identified some structural features, for both sets, important to the suitable biological activity and pharmacokinetic profile.

Um modelo estocástico combinado de previsão sazonal para a precipitação no Brasil

Este artigo discute um modelo de previsão combinada para a realização de prognósticos climáticos na escala sazonal. Nele, previsões pontuais de modelos estocásticos são agregadas para obter as melhores projeções no tempo. Utilizam-se modelos estocásticos autoregressivos integrados a médias móveis, de suavização exponencial e previsões por análise de correlações canônicas. O controle de qualidade das previsões é feito através da análise dos resíduos e da avaliação do percentual de redução da variância não-explicada da modelagem combinada em relação às previsões dos modelos individuais. Exemplos da aplicação desses conceitos em modelos desenvolvidos no Instituto Nacional de Meteorologia (INMET) mostram bons resultados e ilustram que as previsões do modelo combinado, superam na maior parte dos casos a de cada modelo componente, quando comparadas aos dados observados.

Validação do Questionário de Freqüência Alimentar para Adolescentes (QFAA) por grupos de alimentos em uma população de escolares

OBJETIVO: Verificar a validade do Questionário de Freqüência Alimentar para Adolescentes para avaliar o consumo de grupos de alimentos entre escolares de Piracicaba, São Paulo. MÉTODOS: Participaram do estudo 94 adolescentes, com idade entre 11 e 15 anos, matriculados em uma escola da rede pública. O consumo alimentar foi avaliado pelo Questionário de Freqüência Alimentar para Adolescentes (QFAA) e a média de dois Recordatórios de 24 horas (R24h) foi utilizada como método de referência. Os itens alimentares foram classificados em 18 grupos. Foram realizadas análises descritivas, teste t-Student pareado e de Wilcoxon, coeficientes de correlação de Pearson e de Spearman. Foram também utilizadas análise de quartis e estatística Kappa ponderado. Os coeficientes de correlação foram corrigidos pela variância intrapessoal dos R24h, estimada a partir de ANOVA com um fator de classificação. RESULTADOS: Não foram verificadas diferenças significativas entre os instrumentos para o arroz, massas, carnes, refrigerantes e sucos artificiais. Os coeficientes de correlação corrigidos pela variabilidade intrapessoal variaram de -0,26 a 0,78. A concordância de classificação dos indivíduos no mesmo quartil de consumo para ambos os métodos variou de 22% (massas) a 50% (feijão). Para quartis opostos, os grupos que tiveram mais de 10% dos indivíduos classificados incorretamente foram massas (19%), carnes (13%) e gorduras (11%). Os valores de Kappa ponderado variaram de - 0,15 (massas) a 0,56 (feijão). O QFAA superestimou o consumo de quase a totalidade dos grupos alimentares e subestimou os grupos dos óleos, feijão, carnes e refrigerantes. CONCLUSÃO: O instrumento apresentou boa validade para feijão, verduras e legumes, leite e derivados, biscoitos recheados e para o arroz.

Espacialização da temperatura do ar anual no estado de Alagoas com diferentes modelos digitais de elevação e resoluções espaciais

The aim of this study was to establish a digital elevation model and its horizontal resolution to interpolate the annual air temperature for the Alagoas State by means of multiple linear regression models. A multiple linear regression model was adjusted to series (11 to 34 years) of annual air temperatures obtained from 28 weather stations in the states of Alagoas, Bahia, Pernambuco and Sergipe, in the Northeast of Brazil, in function of latitude, longitude and altitude. The elevation models SRTM and GTOPO30 were used in the analysis, with original resolutions of 90 and 900 m, respectively. The SRTM was resampled for horizontal resolutions of 125, 250, 500, 750 and 900 m. For spatializing the annual mean air temperature for the state of Alagoas, a multiple linear regression model was used for each elevation and spatial resolution on a grid of the latitude and longitude. In Alagoas, estimates based on SRTM data resulted in a standard error of estimate (0.57 degrees C) and dispersion (r(2) = 0.62) lower than those obtained from GTOPO30 (0.93 degrees C and 0.20). In terms of SRTM resolutions, no significant differences were observed between the standard error (0.55 degrees C; 750 m - 0.58 degrees C; 250m) and dispersion (0.60; 500 m - 0.65; 750 m) estimates. The spatialization of annual air temperature in Alagoas, via multiple regression models applied to SRTM data showed higher concordance than that obtained with the GTOPO30, independent of the spatial resolution.

Context tree selection: A unifying view

Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

A Separation Principle for the Continuous-Time LQ-Problem With Markovian Jump Parameters

In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.

The Kumaraswamy Weibull distribution with application to failure data

For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

General results for the beta-modified Weibull distribution

We study in detail the so-called beta-modified Weibull distribution, motivated by the wide use of the Weibull distribution in practice, and also for the fact that the generalization provides a continuous crossover towards cases with different shapes. The new distribution is important since it contains as special sub-models some widely-known distributions, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among several others. It also provides more flexibility to analyse complex real data. Various mathematical properties of this distribution are derived, including its moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are also derived for the chf, mean deviations, Bonferroni and Lorenz curves, reliability and entropies. The estimation of parameters is approached by two methods: moments and maximum likelihood. We compare by simulation the performances of the estimates from these methods. We obtain the expected information matrix. Two applications are presented to illustrate the proposed distribution.

Genetic variability in S(1) families from different maize populations.

Genetic variability in S(1) families from different maize populations. The objectives of the present work were directed towards the study of genetic: variablilty In seven maize populations with a broad genetic base, as a guide for population improvement. The field evaluation was conducted in completely randomized blocks, at one location (Anhembi, Sao Paulo state) with different groups, of S(1) families Obtained from seven populations (GO-D: dent type, GO-F: flint type, GO-L: long car, GO-G: thick Car; and composites G3, G4 and GO-S). Estimates were obtained for genetic variance (progeny mean basis), phenotypic variance of families means, and coefficient of heritability (broad sense) for progeny means. Estimates of heritability were high for Car weight (0,89 to 0.94), car length (0.77 to 0.88) and car diameter (0.77 to 0.92); and lower for plant height (0.58 to 0.80) and Car height (0.54 to 0.84), thus showing the high Potential of the populations for recurrent selection based oil S, families. Ear yield in the base populations used as controls varied front 11,200 kg ha(-1) (GO-D) to 12,800 kg ha(-1) (G3). The means of S(1) families varied from 6,070 kg ha(-1) (GO-F) to 7,380 kg ha(-1) (G4); the Inbreeding depression in S(1) Families varied front 37.5% (G4) to 48.0% (G3) relative to the non-inbred population.

Electrocardiographic Alterations During Endosseous Implant Placement Performed with Local Anesthetic Agents

Purpose: The purpose of this study was to analyze electrocardiographic alterations during dental implant surgeries when local anesthetic agents were used. Materials and Methods: Twenty implants were placed in 18 healthy patients. An electrocardiogram and Wincardio software were used to gather recordings from 12 static leads every 2 minutes, continuously record coronary artery (D2) derivations, and automatically measure the following electrocardiographic parameters: heart rate, duration and amplitude of the P wave, PR segment duration, ST segment deviation, QRS complex duration, and duration of the RR, QT, and corrected QT (QTc) intervals. Results: Analysis of variance of the values obtained at the different stages showed significant differences (P < .05) for the heart rate and for the duration of the RR and QT intervals. The heart rate increased during the anesthesia, incision, and bone drilling stages, reaching a peak during drilling. Duration of the RR and QT intervals decreased during the incision and drilling stages. Among the electrocardiographic parameters individually assessed, several altered values were found for the duration of the P wave, the QRS complex, and the QT and QTc intervals. Sinusal tachycardia and bradycardia, sinusal arrhythmia, supraventricular extrasystole, ventricular extrasystole, and T-wave inversion were detected. Conclusion: Dental implant placement surgery may induce electrocardiographic alterations. The most frequently found arrhythmias were extrasystole and sinusal tachycardia. The anesthesia, incision, and bone drilling stages exhibited the highest heart rate values and the shortest durations of the RR and QT intervals. INT J ORAL MAXILLOFAC IMPLANTS 2009;24:412-418