Multivariate analysis of the energy cycle of the South American rainy season

The South American (SA) rainy season is studied in this paper through the application of a multivariate Empirical Orthogonal Function (EOF) analysis to a SA gridded precipitation analysis and to the components of Lorenz Energy Cycle (LEC) derived from the National Centers for Environmental Prediction (NCEP) reanalysis. The EOF analysis leads to the identification of patterns of the rainy season and the associated mechanisms in terms of their energetics. The first combined EOF represents the northwest-southeast dipole of the precipitation between South and Central America, the South American Monsoon System (SAMS). The second combined EOF represents a synoptic pattern associated with the SACZ (South Atlantic convergence zone) and the third EOF is in spatial quadrature to the second EOF. The phase relationship of the EOFs, as computed from the principal components (PCs), suggests a nonlinear transition from the SACZ to the fully developed SAMS mode by November and between both components describing the SACZ by September-October (the rainy season onset). According to the LEC, the first mode is dominated by the eddy generation term at its maximum, the second by both baroclinic and eddy generation terms and the third by barotropic instability previous to the connection to the second mode by September-October. The predominance of the different LEC components at each phase of the SAMS can be used as an indicator of the onset of the rainy season in terms of physical processes, while the existence of the outstanding spectral peaks in the time dependence of the EOFs at the intraseasonal time scale could be used for monitoring purposes. Copyright (C) 2009 Royal Meteorological Society

Use of Bayesian Methods for Multivariate Bioequivalence Measures

In this paper, we introduce a Bayesian analysis for bioequivalence data assuming multivariate pharmacokinetic measures. With the introduction of correlation parameters between the pharmacokinetic measures or between the random effects in the bioequivalence models, we observe a good improvement in the bioequivalence results. These results are of great practical interest since they can yield higher accuracy and reliability for the bioequivalence tests, usually assumed by regulatory offices. An example is introduced to illustrate the proposed methodology by comparing the usual univariate bioequivalence methods with multivariate bioequivalence. We also consider some usual existing discrimination Bayesian methods to choose the best model to be used in bioequivalence studies.

MODELING THE EVOLUTION OF COMPLEX NETWORKS THROUGH THE PATH-STAR TRANSFORMATION AND OPTIMAL MULTIVARIATE METHODS

The topology of real-world complex networks, such as in transportation and communication, is always changing with time. Such changes can arise not only as a natural consequence of their growth, but also due to major modi. cations in their intrinsic organization. For instance, the network of transportation routes between cities and towns ( hence locations) of a given country undergo a major change with the progressive implementation of commercial air transportation. While the locations could be originally interconnected through highways ( paths, giving rise to geographical networks), transportation between those sites progressively shifted or was complemented by air transportation, with scale free characteristics. In the present work we introduce the path-star transformation ( in its uniform and preferential versions) as a means to model such network transformations where paths give rise to stars of connectivity. It is also shown, through optimal multivariate statistical methods (i.e. canonical projections and maximum likelihood classification) that while the US highways network adheres closely to a geographical network model, its path-star transformation yields a network whose topological properties closely resembles those of the respective airport transportation network.

Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the corrected estimators. The numerical results show that the bias correction scheme yields nearly unbiased estimates. We also give an application to a real data set.

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.

Multivariate measurement error models based on scale mixtures of the skew-normal distribution

Scale mixtures of the skew-normal (SMSN) distribution is a class of asymmetric thick-tailed distributions that includes the skew-normal (SN) distribution as a special case. The main advantage of these classes of distributions is that they are easy to simulate and have a nice hierarchical representation facilitating easy implementation of the expectation-maximization algorithm for the maximum-likelihood estimation. In this paper, we assume an SMSN distribution for the unobserved value of the covariates and a symmetric scale mixtures of the normal distribution for the error term of the model. This provides a robust alternative to parameter estimation in multivariate measurement error models. Specific distributions examined include univariate and multivariate versions of the SN, skew-t, skew-slash and skew-contaminated normal distributions. The results and methods are applied to a real data set.

Metabolomic assessment with CE-MS of the nutraceutical effect of Cystoseira spp extracts in an animal model

There is a need of scientific evidence of claimed nutraceutical effects, but also there is a social movement towards the use of natural products and among them algae are seen as rich resources. Within this scenario, the development of methodology for rapid and reliable assessment of markers of efficiency and security of these extracts is necessary. The rat treated with streptozotocin has been proposed as the most appropriate model of systemic oxidative stress for studying antioxidant therapies. Cystoseira is a brown alga containing fucoxanthin and other carothenes whose pressure-assisted extracts were assayed to discover a possible beneficial effect on complications related to diabetes evolution in an acute but short-term model. Urine was selected as the sample and CE-TOF-MS as the analytical technique to obtain the fingerprints in a non-target metabolomic approach. Multivariate data analysis revealed a good clustering of the groups and permitted the putative assignment of compounds statistically significant in the classification. Interestingly a group of compounds associated to lysine glycation and cleavage from proteins was found to be increased in diabetic animals receiving vehicle as compared to control animals receiving vehicle (N6, N6, N6-trimethyl-L-lysine, N-methylnicotinamide, galactosylhydroxylysine, L-carnitine, N6-acetyl-N6-hydroxylysine, fructose-lysine, pipecolic acid, urocanic acid, amino-isobutanoate, formylisoglutamine. Fructoselysine significantly decreased after the treatment changing from a 24% increase to a 19% decrease. CE-MS fingerprinting of urine has provided a group of compounds different to those detected with other techniques and therefore proves the necessity of a cross-platform analysis to obtain a broad view of biological samples.

Comparing two multivariate unit root tests

In this essay, a method for comparing the asymptotic power of the multivariate unit root tests proposed in Phillips & Durlauf (1986) and Flˆores, Preumont & Szafarz (1996) is proposed. In order to determine the asymptotic power of the tests the asymptotic distributions under the null hypothesis and under the set of alternative hypotheses described in Phillips (1988) are determined. In addition, a test which combines characteristics of both tests is proposed and its distributions under the null hypothesis and the same set of alternative hypotheses are determined. This allows us to determine what causes any difference in the asymptotic power of the two tests against the set of alternative hypotheses considered

Analysis of contagion from the constant conditional correlation model with Markov regime switching

Over the last decades, the analysis of the transmissions of international nancial events has become the subject of many academic studies focused on multivariate volatility models volatility. The goal of this study is to evaluate the nancial contagion between stock market returns. The econometric approach employed was originally presented by Pelletier (2006), named Regime Switching Dynamic Correlation (RSDC). This methodology involves the combination of Constant Conditional Correlation Model (CCC) proposed by Bollerslev (1990) with Markov Regime Switching Model suggested by Hamilton and Susmel (1994). A modi cation was made in the original RSDC model, the introduction of the GJR-GARCH model formulated in Glosten, Jagannathan e Runkle (1993), on the equation of the conditional univariate variances to allow asymmetric e ects in volatility be captured. The database was built with the series of daily closing stock market indices in the United States (SP500), United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) for the period from 02/01/2003 to 09/20/2012. Throughout the work the methodology was compared with others most widespread in the literature, and the model RSDC with two regimes was de ned as the most appropriate for the selected sample. The set of results provide evidence for the existence of nancial contagion between markets of the four countries considering the de nition of nancial contagion from the World Bank called very restrictive. Such a conclusion should be evaluated carefully considering the wide diversity of de nitions of contagion in the literature.

Invariant tests in an instrumental variables model with unknown data generating process

In this work we focus on tests for the parameter of an endogenous variable in a weakly identi ed instrumental variable regressionmodel. We propose a new unbiasedness restriction for weighted average power (WAP) tests introduced by Moreira and Moreira (2013). This new boundary condition is motivated by the score e ciency under strong identi cation. It allows reducing computational costs of WAP tests by replacing the strongly unbiased condition. This latter restriction imposes, under the null hypothesis, the test to be uncorrelated to a given statistic with dimension given by the number of instruments. The new proposed boundary condition only imposes the test to be uncorrelated to a linear combination of the statistic. WAP tests under both restrictions to perform similarly numerically. We apply the di erent tests discussed to an empirical example. Using data from Yogo (2004), we assess the e ect of weak instruments on the estimation of the elasticity of inter-temporal substitution of a CCAPM model.

Avaliação longitudinal do impacto da saúde bucal na estratégia saúde da família em Natal

As a result of the financial incentive provided by the GM / MS 1.444, since 2000, Brazil has experienced a substantial increase in the number of oral health services at the Family Health Strategy. There is, however, evidence that these teams have produced qualitatively different experiences which do not translate necessarily into improved quality of life and health. Thus, evaluative research of great importance. This study aims to assess the impact of the Family Health Strategy in oral health in a longitudinal perspective natalense the years 2006 and 2009. This is an intervention study whose design is a community trial in parallel, nearly randomized. The sample consisted of census tracts covered by oral health teams in the Family Health and the Traditional Model (Basic Health Units and non-FHS Program of Community Health Agents and areas not covered.) The sample was determined by drawing ten census tracts to form the experimental group and ten other sectors for the control group by pairing intentional based on socio-economic and geographic. To check the net effect of the intervention was performed multivariate analysis by Poisson regression. As a result of cross-sectional analysis of year 2009, it was found that the effects of the ESF in Natal were satisfactory only for the variables of injuries and for other purposes without and with negative impact on stock coverage reclaimers. However, the longitudinal analysis revealed that the ESB / ESF improved their performance in dealing with grievances, access and coverage of the type of actions and this fact is independent of age, sex and social and economic conditions. In other employees' words are related to the presence of the Family Health Strategy in the region. However it does not say that both models under study (the Family Health Strategy Model and Traditional) are different in terms of performance and it is pertinent to reflect on the need for further development of evaluation studies that use other approaches able to clarify the dynamics of the process whose results can come to the knowledge of the actors responsible for leading the ESF and encourage them to incorporate the assessment in their routine

Avaliação da estratégia saúde da família na capital potiguar

This research aimed to evaluate the Family Health Strategy (FHS) in Natal, Rio Grande do Norte, through its managers, professionals and users, having as its support the Theory of Belief and the Cognitive-Behavioral Theory. This is a multimethod research and is divided into three sub-studies. In the first study, nine managers answered to a semi-structured interview, to verify the knowledge and beliefs on SUS; the quantitative data were analyzed with descriptive statistics with the aid of SPSS software and the qualitative data were submitted to lexical analysis with support of ALCESTE software. In the second study, we have a descriptive correlational research in which the antecedent variables are related to working conditions in the family health units (FHUs) and to the professionals‟ profile; the corresponding variables refer to the evaluations of the FHS; a stratified probabilistic sample with 475 professionals, who answered to two scales, both consisting of three factors: Physical infrastructure, Material resources, and Treatment effectiveness, and data were analyzed using descriptive, bivariate and multivariate statistics, with the aid of SPSS. The third study is a descriptive correlational research in which the antecedent variables refer to the treatment in the FHUs and to the users‟ profile, and the corresponding variables refer to the evaluations of the FHS, with a stratified non-probabilistic sample with 390 users, who contributed to the construction of a new scale with a factor, effectiveness in treatment, analyzed through descriptive, bivariate and multivariate statistics, with the aid of SPSS. The results showed problems which start from management, under the shape of admission due to political indication and lack of knowledge on SUS and the FHS; they pass through the low tenure of professionals and insufficient professional; and they end up spreading all over the analyzed items: infrastructure of FHUs, material resources, professionals‟ training, accessibility and referral system. One concludes that, despite following an ideal model, the FHS is in need of changes with regard to the barriers to its operational reality

Taxonomia e biogeografia da espécie politípica Herpsilochmus rufimarginatus (TEMMINCK, 1822) (Aves: THAMNOPHILIDAE)

The genus Herpsilochmus is composed mainly of cryptic species, among them is Herpsilochmus rufimarginatus, which is currently represented by four subspecies: H. r. rufimarginatus, H. r. frater, H. r. scapularis and H. r. exiguus. Differences in plumage and vocalization suggest that there are more than one species involved in this complex. Thus this and other subspecific taxa need urgent revision, the disjunct distribution of this species also allows us to infer the relationship between birds that occur in this biome and / or different centers of endemism. This study aims to make a taxonomic revision of the taxa included in the complex time Herpsilochmus rufimarginatus based on morphological, morphometric, vocals and geographical distribution of this bird. Besides creating distribution models current potential and make the reconstruction of the distribution bygone using ecological niche modeling, and testing the niche conservatism and divergence between different subspecies. Consultations for examination of the skins of specimens of the museums: Museum of Zoology, University of São Paulo (MZUSP), National Museum of Rio de Janeiro (MN) and Emilio Goeldi Museum of Pará (MPEG), and the skins deposited at the collection of Ornithological Federal University of Rio Grande do Norte (COUFRN). We studied the following measures length of specimens: exposed culmen, culmen and total culmen nostril, tarsus, wing and tail flattened. The voice analysis was performed with vocalizations banks and / or digital banks people where 17 voice parameters were measured. This information and more available in the literature were used to assemble a bunch of data under the limit distribution of taxa and generate ecological niche models. This analyzes carried out in the program Maxent, having as model selection criterion the AUC, and the models were greater than 0.80 are considered good models. Environmental data for the realization of the modeling were downloaded on the website of Worldclim. The morphometric information, vocals and geographic distribution point for the separation of these taxa to be considering various uni and multivariate analyzes. The potential distribution models performed well (AUC> 0.80), and its distribution associated with environmental characteristics of the Amazon forest and Atlantic forest (forests of south and southeast, northeast and forest). The reconstruction of the distribution indicates a possible contact between the southern part of the Atlantic forest in the northern part of the Amazon. The analysis of niche overlap showed a low overlap between taxa and comparisons between the null model and the generated overlay link probably occurring niche conservatism. The data suggest that the taxa that occur in the Amazon and Atlantic forest represent three distinct species

Exploring community assembly through an individual-based model for trophic interactions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Fluorescence spectroscopy for the detection of tongue carcinoma - validation in an animal model

The efficacy of fluorescence spectroscopy to detect squamous cell carcinoma is evaluated in an animal model following laser excitation at 442 and 532 nm. Lesions are chemically induced with a topical DMBA application at the left lateral tongue of Golden Syrian hamsters. The animals are investigated every 2 weeks after the 4th week of induction until a total of 26 weeks. The right lateral tongue of each animal is considered as a control site (normal contralateral tissue) and the induced lesions are analyzed as a set of points covering the entire clinically detectable area. Based on fluorescence spectral differences, four indices are determined to discriminate normal and carcinoma tissues, based on intraspectral analysis. The spectral data are also analyzed using a multivariate data analysis and the results are compared with histology as the diagnostic gold standard. The best result achieved is for blue excitation using the KNN (K-nearest neighbor, a interspectral analysis) algorithm with a sensitivity of 95.7% and a specificity of 91.6%. These high indices indicate that fluorescence spectroscopy may constitute a fast noninvasive auxiliary tool for diagnostic of cancer within the oral cavity. (C) 2008 Society of Photo-Optical Instrumentation Engineers.