Condições de vida e mortalidade por doenças cardiovasculares na área de influência do Complexo Petroquímico do Estado do Rio de Janeiro - COMPERJ.

O objetivo desta tese foi identificar e caracterizar áreas com altas taxas de mortalidade por doenças do aparelho circulatório (DAC) e seus dois principais subgrupos de causas: as doenças isquêmicas do coração (DIC) e as doenças cerebrovasculares (DCV), entre os anos de 2008 e 2012 na área de influência do complexo petroquímico do estado do Rio de Janeiro COMPERJ, por meio de métodos estatísticos e sistemas de informações geográficas (SIG). Os resultados da investigação são apresentados na forma de dois manuscritos. O primeiro objetivou descrever o perfil da distribuição espacial da mortalidade por (DAC), caracterizar e predizer territórios com maior risco de morte por esta causa, com base em classificação das unidades espaciais por indicador de qualidade urbana (IQUmod). A análise multivariada foi realizada por meio do método conhecido como árvore de decisão e regressão, baseado em algoritmo CART para a obtenção do modelo preditivo para UVLs com diferentes riscos de mortalidade por DAC. O modelo desenvolvido foi capaz de discriminar sete conjuntos de UVLs, com diferentes taxas médias de mortalidades. O subconjunto que apresenta a maior taxa média (1037/100 mil hab.) apresenta 3 UVLs com mais de 75% de seus domicílios com abastecimento de água inadequado e valor de IQUmod acima de 0.6. Conclui-se que na área de influência do COMPERJ existem áreas onde a mortalidade por DAC se apresenta com maior magnitude e que a identificação dessas áreas pode auxiliar na elaboração, diagnóstico, prevenção e planejamento de ações de saúde direcionadas aos grupos mais susceptíveis. O segundo manuscrito teve por objetivo descrever o perfil da distribuição espacial da mortalidade por DIC e DCV em relação ao contexto socioambiental segundo áreas geográficas. O modelo de regressão linear de Poisson com parâmetro de estimação via quasi-verossimilhança foi usado para verificar associação entre as variáveis. Foram identificados como fatores de risco para mortalidade por DIC e DCV a variável relativa a melhor renda e maior distância entre domicílios e unidades de saúde; a proporção de domicílios em ruas pavimentadas aparece como fator de proteção. A distribuição espacial e as associações encontradas entre os desfechos e preditores sugerem que as populações residentes em localidades mais afastadas dos centros urbanos apresentam maiores taxas de mortalidade por DIC e DCV e que isto pode estar relacionado a contextos rurais de localização das residências e a distância geográfica destas populações aos serviços de saúde. Aponta-se para a necessidade de desenvolvimento de ações que propiciem maior amplitude no atendimento em saúde, no intuito da redução de eventos cardiovasculares mórbidos incidentes naquelas populações.

Efeito do corante Vermelho de sudan B na marcaçao e no desenvolvimento de Diatraea saccharalis ( Fabricius, 1794) (Lepidoptera: Crambidae) e de Cotesia flavipes (Cameron, 1891) ( Hymenoptera: Braconidae)

The objective of this work was to evaluate biological aspects of Diatraea saccharalis fed on artificial diet containing different concentrations of the Sudan B Red dye and the possibility to mark the parasitoid Cotesia flavipes, when submitted to the parasitism of dyed caterpillars. For that, were added to the artificial diet four concentrations of Sudan Red B dye (100, 200, 300 and 400 ppm) and control (no dye addition). It was evaluated larval and pupal period, larval and pupal viability, longevity, sex rate, pupal weigh, eggs per female, eggs per day, number of eggs per egg mass, egg viability and embrionary period; besides same were accomplished measurements in the caterpillars (bioassay I). Caterpillars of 17 days old (30) of each treatment were removed from the tubes and exposed to the parasitism of C. flavipes (bioassay 2). The egg-pupae period, sex rate, pupal period and viability, number of females, males, total of emerged adults and longevity were evaluated. The data were submitted to the multivariate analisys methods: cluster analysis, two-way and principal component analysis. Based on analysis, it was observed that the treatment of 100 ppm was the least harmful to the biology of the sugar cane borer larvae by groping to the control and did not influence negatively its biological aspects. The concentration of 400 ppm affected negatively the biology of C. flavipes. The Sudan Red B it is ended doses marked the caterpillars and the adults, however the concentration of 100 ppm is the most suitable to dye D. saccharalis. None of the tested concentration marked adults of C. flavipes, despite to affect negatively its biology. It is unviable to increase the concentration seeking futures tests, for that dye to be harmful to the biological aspects of D. saccharalis and C. flavipes.

Demographic and clinical correlates of comorbid substance use disorders in psychosis : multivariate analyses from an epidemiological sample

Background: While there has been substantial research examining the correlates of comorbid substance abuse in psychotic disorders, it has been difficult to tease apart the relative importance of individual variables. Multivariate analyses are required, in which the relative contributions of risk factors to specific forms of substance misuse are examined, while taking into account the effects of other important correlates. Methods: This study used multivariate correlates of several forms of comorbid substance misuse in a large epidemiological sample of 852 Australians with DSMIII- R-diagnosed psychoses. Results: Multiple substance use was common and equally prevalent in nonaffective and affective psychoses. The most consistent correlate across the substance use disorders was male sex. Younger age groups were more likely to report the use of illegal drugs, while alcohol misuse was not associated with age. Side effects secondary to medication were associated with the misuse of cannabis and multiple substances, but not alcohol. Lower educational attainment was associated with cannabis misuse but not other forms of substance abuse. Conclusion: The profile of substance misuse in psychosis shows clinical and demographic gradients that can inform treatment and preventive research.

Numerical schemes and multivariate extrapolation of a two-dimensional anomalous sub-diffusion equation

Anomalous dynamics in complex systems have gained much interest in recent years. In this paper, a two-dimensional anomalous subdiffusion equation (2D-ASDE) is considered. Two numerical methods for solving the 2D-ASDE are presented. Their stability, convergence and solvability are discussed. A new multivariate extrapolation is introduced to improve the accuracy. Finally, numerical examples are given to demonstrate the effectiveness of the schemes and confirm the theoretical analysis.

Multivariate methods to identify cancer-related symptom clusters

Multivariate methods are required to assess the interrelationships among multiple, concurrent symptoms. We examined the conceptual and contextual appropriateness of commonly used multivariate methods for cancer symptom cluster identification. From 178 publications identified in an online database search of Medline, CINAHL, and PsycINFO, limited to articles published in English, 10 years prior to March 2007, 13 cross-sectional studies met the inclusion criteria. Conceptually, common factor analysis (FA) and hierarchical cluster analysis (HCA) are appropriate for symptom cluster identification, not principal component analysis. As a basis for new directions in symptom management, FA methods are more appropriate than HCA. Principal axis factoring or maximum likelihood factoring, the scree plot, oblique rotation, and clinical interpretation are recommended approaches to symptom cluster identification.

Characterisation of soils with the use of instrumental techniques : a multivariate forensic study

The value of soil evidence in the forensic discipline is well known. However, it would be advantageous if an in-situ method was available that could record responses from tyre or shoe impressions in ground soil at the crime scene. The development of optical fibres and emerging portable NIR instruments has unveiled a potential methodology which could permit such a proposal. The NIR spectral region contains rich chemical information in the form of overtone and combination bands of the fundamental infrared absorptions and low-energy electronic transitions. This region has in the past, been perceived as being too complex for interpretation and consequently was scarcely utilized. The application of NIR in the forensic discipline is virtually non-existent creating a vacancy for research in this area. NIR spectroscopy has great potential in the forensic discipline as it is simple, nondestructive and capable of rapidly providing information relating to chemical composition. The objective of this study is to investigate the ability of NIR spectroscopy combined with Chemometrics to discriminate between individual soils. A further objective is to apply the NIR process to a simulated forensic scenario where soil transfer occurs. NIR spectra were recorded from twenty-seven soils sampled from the Logan region in South-East Queensland, Australia. A series of three high quartz soils were mixed with three different kaolinites in varying ratios and NIR spectra collected. Spectra were also collected from six soils as the temperature of the soils was ramped from room temperature up to 6000C. Finally, a forensic scenario was simulated where the transferral of ground soil to shoe soles was investigated. Chemometrics methods such as the commonly known Principal Component Analysis (PCA), the less well known fuzzy clustering (FC) and ranking by means of multicriteria decision making (MCDM) methodology were employed to interpret the spectral results. All soils were characterised using Inductively Coupled Plasma Optical Emission Spectroscopy and X-Ray Diffractometry. Results were promising revealing NIR combined with Chemometrics is capable of discriminating between the various soils. Peak assignments were established by comparing the spectra of known minerals with the spectra collected from the soil samples. The temperature dependent NIR analysis confirmed the assignments of the absorptions due to adsorbed and molecular bound water. The relative intensities of the identified NIR absorptions reflected the quantitative XRD and ICP characterisation results. PCA and FC analysis of the raw soils in the initial NIR investigation revealed that the soils were primarily distinguished on the basis of their relative quartz and kaolinte contents, and to a lesser extent on the horizon from which they originated. Furthermore, PCA could distinguish between the three kaolinites used in the study, suggesting that the NIR spectral region was sensitive enough to contain information describing variation within kaolinite itself. The forensic scenario simulation PCA successfully discriminated between the ‘Backyard Soil’ and ‘Melcann® Sand’, as well as the two sampling methods employed. Further PCA exploration revealed that it was possible to distinguish between the various shoes used in the simulation. In addition, it was possible to establish association between specific sampling sites on the shoe with the corresponding site remaining in the impression. The forensic application revealed some limitations of the process relating to moisture content and homogeneity of the soil. These limitations can both be overcome by simple sampling practices and maintaining the original integrity of the soil. The results from the forensic scenario simulation proved that the concept shows great promise in the forensic discipline.

Modeling multivariate autoregressive conditional heteroskedasticity with the double smooth transition conditional correlation GARCH Model

In this paper, we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new double smooth transition conditional correlation (DSTCC) GARCH model extends the smooth transition conditional correlation (STCC) GARCH model of Silvennoinen and Teräsvirta (2005) by including another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. Applying the model to the stock and bond futures data, we discover that the correlation pattern between them has dramatically changed around the turn of the century. The model is also applied to a selection of world stock indices, and we find evidence for an increasing degree of integration in the capital markets.

Multivariate Markov Process Models for the transmission of methicillin-resistant Staphylococcus Aureus in a hospital ward

Methicillin-resistant Staphylococcus Aureus (MRSA) is a pathogen that continues to be of major concern in hospitals. We develop models and computational schemes based on observed weekly incidence data to estimate MRSA transmission parameters. We extend the deterministic model of McBryde, Pettitt, and McElwain (2007, Journal of Theoretical Biology 245, 470–481) involving an underlying population of MRSA colonized patients and health-care workers that describes, among other processes, transmission between uncolonized patients and colonized health-care workers and vice versa. We develop new bivariate and trivariate Markov models to include incidence so that estimated transmission rates can be based directly on new colonizations rather than indirectly on prevalence. Imperfect sensitivity of pathogen detection is modeled using a hidden Markov process. The advantages of our approach include (i) a discrete valued assumption for the number of colonized health-care workers, (ii) two transmission parameters can be incorporated into the likelihood, (iii) the likelihood depends on the number of new cases to improve precision of inference, (iv) individual patient records are not required, and (v) the possibility of imperfect detection of colonization is incorporated. We compare our approach with that used by McBryde et al. (2007) based on an approximation that eliminates the health-care workers from the model, uses Markov chain Monte Carlo and individual patient data. We apply these models to MRSA colonization data collected in a small intensive care unit at the Princess Alexandra Hospital, Brisbane, Australia.