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.

Análise de agrupamentos dos dados de DFA oriundos de perfis elétricos de indução de poços de petróleo

The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis

Análise de DFA e de agrupamento do perfil de densidade de poços de petróleo

In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means

Dinâmica espaço-temporal em uma guilda de borboletas frugívoras no limite norte da Floresta Atlântica Nordestina

The extent of the Brazilian Atlantic rainforest, a global biodiversity hotspot, has been reduced to less than 7% of its original range. Yet, it contains one of the richest butterfly fauna in the world. Butterflies are commonly used as environmental indicators, mostly because of their strict association with host plants, microclimate and resource availability. This research describes diversity, composition and species richness of frugivorous butterflies in a forest fragment in the Brazilian Northeast. It compares communities in different physiognomies and seasons. The climate in the study area is classified as tropical rainy, with two well defined seasons. Butterfly captures were made with 60 Van Someren-Rydon traps, randomly located within six different habitat units (10 traps per unit) that varied from very open (e.g. coconut plantation) to forest interior. Sampling was made between January and December 2008, for five days each month. I captured 12090 individuals from 32 species. The most abundant species were Taygetis laches, Opsiphanes invirae and Hamadryas februa, which accounted for 70% of all captures. Similarity analysis identified two main groups, one of species associated with open or disturbed areas and a second by species associated with shaded areas. There was a strong seasonal component in species composition, with less species and lower abundance in the dry season and more species and higher abundance in the rainy season. K-means analysis indicates that choice of habitat units overestimated faunal perceptions, suggesting less distinct units. The species Taygetis virgilia, Hamadryas chloe, Callicore pygas e Morpho achilles were associated with less disturbed habitats, while Yphthimoides sp, Historis odius, H. acheronta, Hamadryas feronia e Siderone marthesia likey indicate open or disturbed habitats. This research brings important information for conservation of frugivorous butterflies, and will serve as baseline for future projects in environmental monitoring

Desenvolvimento de um compósito de espuma rígida de poliuretana de mamona e fibras de sisal para isolação térmica

The search for sustainable technologies that can contribute to reduce energy consumption is a great challenge in the field of insulation materials. In this context, composites manufactured from vegetal sources are an alternative technology. The principal objectives of this work are the development and characterization of a composite composed by the rigid polyurethane foam derived from castor oil (commercially available as RESPAN D40) and sisal fibers. The manufacture of the composite was done with expansion controlled inside a closed mold. The sisal fibers where used in the form of needlepunched nonwoven with a mean density of 1150 g/m2 and 1350 g/m2. The composite characterization was performed through the following tests: thermal conductivity, thermal behavior, thermo gravimetric analysis (TG/DTG), mechanical strength in compression and flexural, apparent density, water absorption in percentile, and the samples morphology was analyzed in a MEV. The density and humidity percentage of the sisal fiber were also determined. The thermal conductivity of the composites was higher than the pure polyurethane foam, the addition of nonwoven sisal fibers will become in a higher level of compact foam, reducing empty spaces (cells) of polyurethane, inducing an increase in k value. The apparent density of the composites was higher than pure polyurethane foam. In the results of water absorption tests, was seen a higher absorption percent of the composites, what is related to the presence of sisal fibers which are hygroscopic. From TG/DTG results, with the addition of sisal fibers reduced the strength to thermal degradation of the composites, a higher loss of mass was observed in the temperature band between 200 and 340 °C, related to urethane bonds decomposition and cellulose degradation and its derivatives. About mechanical behavior in compression and flexural, composites presented a better mechanical behavior than the rigid polyurethane foam. An increase in the amount of sisal fibers induces a higher rigidity of the composites. At the thermal behavior tests, the composites were more mechanically and thermally resistant than some materials commonly used for thermal insulation, they present the same or better results. The density of nonwoven sisal fiber had influence over the insulation grade; this means that, an increaser in sisal fiber density helped to retain the heat

Síntese e caracterização de materiais mesoporosos para a captura de CO2: influência do óxido de níquel

Several materials are currently under study for the CO2 capture process, like the metal oxides and mixed metal oxides, zeolites, carbonaceous materials, metal-organic frameworks (MOF's) organosilica and modified silica surfaces. In this work, evaluated the adsorption capacity of CO2 in mesoporous materials of different structures, such as MCM-48 and SBA- 15 without impregnating and impregnated with nickel in the proportions 5 %, 10 % and 20 % (m/m), known as 5Ni-MCM-48, 10Ni-MCM-48, 20Ni-MCM-48 and 5Ni-SBA-15, 10NiSBA-15, 20Ni-SBA-15. The materials were characterized by means of X-ray diffraction (XRD), thermal analysis (TG and DTG), Fourier transform infrared spectroscopy (FT-IR), N2 adsorption and desorption (BET) and scanning electron microscopy (SEM) with EDS. The adsorption process was performed varying the pressure of 100 - 4000 kPa and keeping the temperature constant and equal to 298 K. At a pressure of 100 kPa, higher concentrations of adsorption occurred for the materials 5Ni-MCM-48 (0.795 mmol g-1 ) and SBA-15 (0.914 mmol g-1 ) is not impregnated, and at a pressure of 4000 kPa for MCM-48 materials (14.89 mmol g-1) and SBA-15 (9.97 mmol g-1) not impregnated. The results showed that the adsorption capacity varies positively with the specific area, however, has a direct dependency on the type and geometry of the porous structure of channels. The data were fitted using the Langmuir and Freundlich models and were evaluated thermodynamic parameters Gibbs free energy and entropy of the adsorption system