A complex structure in the (beta+gamma(0)) region of the Cu-Al alloys

The identification, characterization and stability range of the phases present in a series of Cu-Al alloys, with Al content from 11.0 to 15.0 wt.%, were studied by Differential Thermal Analysis (DTA), Optical Microscopy (OM), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Selected Area Electron Diffraction (SAED), Auger Electron Spectroscopy (AES), Energy Dispersive X-Ray Spectroscopy (EDX) and X-Ray Diffraction (XRD). In some alloys and in a temperature range from 790 degrees C to 850 degrees C the presence of black spots exhibiting regular shapes and an homogeneous distribution was noticed through metallographic microscopy. Data from TEM and AES indicate that these spots are made of two monocrystalline phases having different Al contents and a crystallographic orientation relationship. (C) 1998 Elsevier B.V. S.A. All rights reserved.

Avaliação da ingestão de nutrientes, segundo padrão alimentar de idosos do município de Botucatu - SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Ensaio clínico randomizado duplo-cego do perfil inflamatório e do nível de estresse oxidativo em indivíduos com diagnóstico polissonográfico de SAOS antes e após o uso de CPAP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

O impacto do excesso de gordura corporal sobre a remodelação óssea de adolescentes

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

Cetaceans of Southeast Alaska: Distribution and Seasonal Occurrence

Aim To assess the distribution, group size, seasonal occurrence and annual trends of cetaceans. Location The study area included all major inland waters of Southeast Alaska. Methods Between 1991 and 2007, cetacean surveys were conducted by observers who kept a constant watch when the vessel was underway and recorded all cetaceans encountered. For each species, we examined distributional patterns, group size, seasonal occurrence and annual trends. Analysis of variance (anova F) was used to test for differences in group sizes between multiple means, and Student’s t-test was used to detect differences between pairwise means. Cetacean seasonal occurrence and annual trends were investigated using a generalized linear model framework. Results Humpback whales (Megaptera novaeangliae) were seen throughout the region, with numbers lowest in spring and highest in the fall. Fin whale (Balaenoptera physalus) and minke whale (Balaenoptera acutorostrata) distributions were more restricted than that reported for humpback whales, and the low number of sightings precluded evaluating seasonal trends. Three killer whale (Orcinus orca) eco-types were documented with distributions occurring throughout inland waters. Seasonal patterns were not detected or could not be evaluated for resident and offshore killer whales, respectively; however, the transient eco-type was more abundant in the summer. Dall’s porpoise (Phocoenoides dalli) were distributed throughout the region, with more sightings in spring and summer than in fall. Harbour porpoise (Phocoena phocoena) distribution was clumped, with concentrations occurring in the Icy Strait/Glacier Bay and Wrangell areas and with no evidence of seasonality. Pacific white-sided dolphins (Lagenorhynchus obliquidens) were observed only occasionally, with more sightings in the spring. For most species, group size varied on both an annual and seasonal basis. Main conclusions Seven cetacean species occupy the inland waters of Southeast Alaska, with distribution, group size, seasonal occurrence and annual trends varying by species. Future studies that compare spatial and temporal patterns with other features (e.g. oceanography, prey resources) may help in identifying the key factors that support the high density and biodiversity of cetaceans found in this region. An increased understanding of the region’s marine ecology is an essential step towards ensuring the long-term conservation of cetaceans in Southeast Alaska.

Bivariate gamma-geometric law and its induced Levy process

In this article we introduce a three-parameter extension of the bivariate exponential-geometric (BEG) law (Kozubowski and Panorska, 2005) [4]. We refer to this new distribution as the bivariate gamma-geometric (BGG) law. A bivariate random vector (X, N) follows the BGG law if N has geometric distribution and X may be represented (in law) as a sum of N independent and identically distributed gamma variables, where these variables are independent of N. Statistical properties such as moment generation and characteristic functions, moments and a variance-covariance matrix are provided. The marginal and conditional laws are also studied. We show that BBG distribution is infinitely divisible, just as the BEG model is. Further, we provide alternative representations for the BGG distribution and show that it enjoys a geometric stability property. Maximum likelihood estimation and inference are discussed and a reparametrization is proposed in order to obtain orthogonality of the parameters. We present an application to a real data set where our model provides a better fit than the BEG model. Our bivariate distribution induces a bivariate Levy process with correlated gamma and negative binomial processes, which extends the bivariate Levy motion proposed by Kozubowski et al. (2008) [6]. The marginals of our Levy motion are a mixture of gamma and negative binomial processes and we named it BMixGNB motion. Basic properties such as stochastic self-similarity and the covariance matrix of the process are presented. The bivariate distribution at fixed time of our BMixGNB process is also studied and some results are derived, including a discussion about maximum likelihood estimation and inference. (C) 2012 Elsevier Inc. All rights reserved.

THE LOG-BURR XII REGRESSION MODEL FOR GROUPED SURVIVAL DATA

The log-Burr XII regression model for grouped survival data is evaluated in the presence of many ties. The methodology for grouped survival data is based on life tables, where the times are grouped in k intervals, and we fit discrete lifetime regression models to the data. The model parameters are estimated by maximum likelihood and jackknife methods. To detect influential observations in the proposed model, diagnostic measures based on case deletion, so-called 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 these measures, the total local influence and influential estimates are also used. We conduct Monte Carlo simulation studies to assess the finite sample behavior of the maximum likelihood estimators of the proposed model for grouped survival. A real data set is analyzed using a regression model for grouped data.

Tomotherapy dose distribution verification using MAGIC-f polymer gel dosimetry

Purpose: This paper presents the application of MAGIC-f gel in a three-dimensional dose distribution measurement and its ability to accurately measure the dose distribution from a tomotherapy unit. Methods: A prostate intensity-modulated radiation therapy (IMRT) irradiation was simulated in the gel phantom and the treatment was delivered by a TomoTherapy equipment. Dose distribution was evaluated by the R2 distribution measured in magnetic resonance imaging. Results: A high similarity was found by overlapping of isodoses of the dose distribution measured with the gel and expected by the treatment planning system (TPS). Another analysis was done by comparing the relative absorbed dose profiles in the measured and in the expected dose distributions extracted along indicated lines of the volume and the results were also in agreement. The gamma index analysis was also applied to the data and a high pass rate was achieved (88.4% for analysis using 3%/3 mm and of 96.5% using 4%/4 mm). The real three-dimensional analysis compared the dose-volume histograms measured for the planning volumes and expected by the treatment planning, being the results also in good agreement by the overlapping of the curves. Conclusions: These results show that MAGIC-f gel is a promise for tridimensional dose distribution measurements. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4704496]

Global pharmacogenomics: Impact of population diversity on the distribution of polymorphisms in the CYP2C cluster among Brazilians

The impact of biogeographical ancestry, self-reported 'race/color' and geographical origin on the frequency distribution of 10 CYP2C functional polymorphisms (CYP2C8*2, *3, *4, CYP2C9*2, *3, *5, *11, CYP2C19*2, *3 and *17) and their haplotypes was assessed in a representative cohort of the Brazilian population (n = 1034). TaqMan assays were used for allele discrimination at each CYP2C locus investigated. Individual proportions of European, African and Amerindian biogeographical ancestry were estimated using a panel of insertion-deletion polymorphisms. Multinomial log-linear models were applied to infer the statistical association between the CYP2C alleles and haplotypes (response variables), and biogeographical ancestry, self-reported Color and geographical origin (explanatory variables). The results showed that CYP2C19*3, CYP2C9*5 and CYP2C9*11 were rare alleles (<1%), the frequency of other variants ranged from 3.4% (CYP2C8*4) to 17.3% (CYP2C19*17). Two distinct haplotype blocks were identified: block 1 consists of three single nucleotide polymorphisms (SNPs) (CYP2C19*17, CYP2C19*2 and CYP2C9*2) and block 2 of six SNPs (CYP2C9*11, CYP2C9*3, CYP2C9*5, CYP2C8*2, CYP2C8*4 and CYP2C8*3). Diplotype analysis generated 41 haplotypes, of which eight had frequencies greater than 1% and together accounted for 96.4% of the overall genetic diversity. The distribution of CYP2C8 and CYP2C9 (but not CYP2C19) alleles, and of CYP2C haplotypes was significantly associated with self-reported Color and with the individual proportions of European and African genetic ancestry, irrespective of Color self-identification. The individual odds of having alleles CYP2C8*2, CYP2C8*3, CYP2C9*2 and CYP2C9*3, and haplotypes including these alleles, varied continuously as the proportion of European ancestry increased. Collectively, these data strongly suggest that the intrinsic heterogeneity of the Brazilian population must be acknowledged in the design and interpretation of pharmacogenomic studies of the CYP2C cluster in order to avoid spurious conclusions based on improper matching of study cohorts. This conclusion extends to other polymorphic pharmacogenes among Brazilians, and most likely to other admixed populations of the Americas. The Pharmacogenomics Journal (2012) 12, 267-276; doi: 10.1038/tpj.2010.89; published online 21 December 2010

The McDonald inverted beta distribution

We introduce a five-parameter continuous model, called the McDonald inverted beta distribution, to extend the two-parameter inverted beta distribution and provide new four- and three-parameter sub-models. We give a mathematical treatment of the new distribution including expansions for the density function, moments, generating and quantile functions, mean deviations, entropy and reliability. The model parameters are estimated by maximum likelihood and the observed information matrix is derived. An application of the new model to real data shows that it can give consistently a better fit than other important lifetime models. (C) 2012 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Generalized beta-generated distributions

This article introduces generalized beta-generated (GBG) distributions. Sub-models include all classical beta-generated, Kumaraswamy-generated and exponentiated distributions. They are maximum entropy distributions under three intuitive conditions, which show that the classical beta generator skewness parameters only control tail entropy and an additional shape parameter is needed to add entropy to the centre of the parent distribution. This parameter controls skewness without necessarily differentiating tail weights. The GBG class also has tractable properties: we present various expansions for moments, generating function and quantiles. The model parameters are estimated by maximum likelihood and the usefulness of the new class is illustrated by means of some real data sets. (c) 2011 Elsevier B.V. All rights reserved.

Generalized Metropolis dynamics with a generalized master equation: An approach for time-independent and time-dependent Monte Carlo simulations of generalized spin systems

The extension of Boltzmann-Gibbs thermostatistics, proposed by Tsallis, introduces an additional parameter q to the inverse temperature beta. Here, we show that a previously introduced generalized Metropolis dynamics to evolve spin models is not local and does not obey the detailed energy balance. In this dynamics, locality is only retrieved for q = 1, which corresponds to the standard Metropolis algorithm. Nonlocality implies very time-consuming computer calculations, since the energy of the whole system must be reevaluated when a single spin is flipped. To circumvent this costly calculation, we propose a generalized master equation, which gives rise to a local generalized Metropolis dynamics that obeys the detailed energy balance. To compare the different critical values obtained with other generalized dynamics, we perform Monte Carlo simulations in equilibrium for the Ising model. By using short-time nonequilibrium numerical simulations, we also calculate for this model the critical temperature and the static and dynamical critical exponents as functions of q. Even for q not equal 1, we show that suitable time-evolving power laws can be found for each initial condition. Our numerical experiments corroborate the literature results when we use nonlocal dynamics, showing that short-time parameter determination works also in this case. However, the dynamics governed by the new master equation leads to different results for critical temperatures and also the critical exponents affecting universality classes. We further propose a simple algorithm to optimize modeling the time evolution with a power law, considering in a log-log plot two successive refinements.

The McDonald extended distribution: properties and applications

We study a five-parameter lifetime distribution called the McDonald extended exponential model to generalize the exponential, generalized exponential, Kumaraswamy exponential and beta exponential distributions, among others. We obtain explicit expressions for the moments and incomplete moments, quantile and generating functions, mean deviations, Bonferroni and Lorenz curves and Gini concentration index. The method of maximum likelihood and a Bayesian procedure are adopted for estimating the model parameters. The applicability of the new model is illustrated by means of a real data set.

On Wald Residuals in Generalized Linear Models

A rigorous asymptotic theory for Wald residuals in generalized linear models is not yet available. The authors provide matrix formulae of order O(n(-1)), where n is the sample size, for the first two moments of these residuals. The formulae can be applied to many regression models widely used in practice. The authors suggest adjusted Wald residuals to these models with approximately zero mean and unit variance. The expressions were used to analyze a real dataset. Some simulation results indicate that the adjusted Wald residuals are better approximated by the standard normal distribution than the Wald residuals.

Clinical correlates of social adjustment in patients with obsessive-compulsive disorder

Background: Patients with obsessive-compulsive disorder (OCD) frequently show poor social adjustment, which has been associated with OCD severity. Little is known about the effects that age at symptom onset, specific OCD symptoms, and psychiatric comorbidities have on social adjustment. The objective of this study was to investigate the clinical correlates of social functioning in OCD patients. Methods: Cross-sectional study involving 815 adults with a primary DSM-IV diagnosis of OCD participating in the Brazilian Research Consortium on Obsessive-Compulsive Spectrum Disorders. Patients were assessed with the Social Adjustment Scale, the Medical Outcomes Study 36-item Short-Form Health Survey, the Yale-Brown Obsessive-Compulsive Scale, the Dimensional Yale-Brown Obsessive-Compulsive Scale, and the Structured Clinical Interview for DSM-IV Axis I Disorders. Clinical correlates of social adjustment were assessed with generalized linear models with gamma distribution. Results: Poor overall social functioning was associated with greater OCD severity (p = 0.02); hoarding symptoms (p = 0.004); sexual/religious obsessions (p = 0.005); current major depressive disorder (p = 0.004); current post-traumatic stress disorder (p = 0.002); and current eating disorders (p = 0.02). Poor social adjustment was also associated with impaired quality of life. Conclusions: Patients with OCD have poor social functioning in domains related to personal relationships and professional performance. Hoarding symptoms and sexual/religious obsessions seem to have the strongest negative effects on social functioning. Early age at OCD symptom onset seems to be associated with professional and academic underachievement and impairment within the family unit, whereas current psychiatric comorbidity worsen overall social functioning. In comparison with quality of life, social adjustment measures seem to provide a more comprehensive overview of the OCD-related burden. (C) 2012 Elsevier Ltd. All rights reserved.