Sobre a composição química em estrelas evoluídas do aglomerado aberto M67

The Galaxy open clusters have a wide variety of physical properties that make them valuable laboratories for studies of stellar and chemical evolution of the Galaxy. In order to better settle these properties we investigate the abundances of a large number of chemical elements in a sample of 27 evolved stars of the open cluster M67 with different evolutionary stages (turn-off, subgiant and giant stars). For such a study we used high-resolution spectra (R 47 000) and high S/N obtained with UVES+FLAMES at VLT/UT2, covering the wavelength interval 4200-10 600 Å. Our spectral analysis is based on the MARCS models of atmosphere and Turbospectrum spectroscopic tool. The oxygen abundances were determined from the [O I] line at 6300 Å. In addition, we have also computed abundances of Si I, Na I, Mg I, Al I, Ca I, Ti I, Co I, Ni I, Zr I, La II and Cr I. The abundances investigated in this work, combined with their stellar parameters, offers an opportunity to determine the level of mixing and convective dilution of evolved stars in M67. Based on the obtained parameters, the abundances of these seem to follow a similar trend to the curve of solar abundances. Additionally, following strategies of other studies have investigated the relative abundances as a function of effective temperature and metallicity, where it was possible to observe an abundance of Na, Al and Si to the stars in the field of giants. A large dispersion from star to star, is observed in the ratios [X / Fe] for the Co, Zr and La, and the absence of Zr and La, in the stars of the turn-off. Comparisons made between our results and other studies in the literature show that values of abundances are in agreement and close to the limits of the errors

Mortalidade em idosos longevos e "mais jovens" no Brasil

The aim of the present study was to trace the mortality profile of the elderly in Brazil using two neighboring age groups: 60 to 69 years (young-old) and 80 years or more (oldest-old). To do this, we sought to characterize the trend and distinctions of different mortality profiles, as well as the quality of the data and associations with socioeconomic and sanitary conditions in the micro-regions of Brazil. Data was collected from the Mortality Information System (SIM) and the Brazilian Institute of Geography and Statistics (IBGE). Based on these data, the coefficients of mortality were calculated for the chapters of the International Disease Classification (ICD-10). A polynomial regression model was used to ascertain the trend of the main chapters. Non-hierarchical cluster analysis (K-Means) was used to obtain the profiles for different Brazilian micro-regions. Factorial analysis of the contextual variables was used to obtain the socio-economic and sanitary deprivation indices (IPSS). The trend of the CMId and of the ratio of its values in the two age groups confirmed a decrease in most of the indicators, particularly for badly-defined causes among the oldest-old. Among the young-old, the following profiles emerged: the Development Profile; the Modernity Profile; the Epidemiological Paradox Profile and the Ignorance Profile. Among the oldest-old, the latter three profiles were confirmed, in addition to the Low Mortality Rates Profile. When comparing the mean IPSS values in global terms, all of the groups were different in both of the age groups. The Ignorance Profile was compared with the other profiles using orthogonal contrasts. This profile differed from all of the others in isolation and in clusters. However, the mean IPSS was similar for the Low Mortality Rates Profile among the oldest-old. Furthermore, associations were found between the data quality indicators, the CMId for badly-defined causes, the general coefficient of mortality for each age group (CGMId) and the IPSS of the micro-regions. The worst rates were recorded in areas with the greatest socioeconomic and sanitary deprivation. The findings of the present study show that, despite the decrease in the mortality coefficients, there are notable differences in the profiles related to contextual conditions, including regional differences in data quality. These differences increase the vulnerability of the age groups studied and the health iniquities that are already present.