20 resultados para VLE data sets

em Scielo Saúde Pública - SP


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Digital information generates the possibility of a high degree of redundancy in the data available for fitting predictive models used for Digital Soil Mapping (DSM). Among these models, the Decision Tree (DT) technique has been increasingly applied due to its capacity of dealing with large datasets. The purpose of this study was to evaluate the impact of the data volume used to generate the DT models on the quality of soil maps. An area of 889.33 km² was chosen in the Northern region of the State of Rio Grande do Sul. The soil-landscape relationship was obtained from reambulation of the studied area and the alignment of the units in the 1:50,000 scale topographic mapping. Six predictive covariates linked to the factors soil formation, relief and organisms, together with data sets of 1, 3, 5, 10, 15, 20 and 25 % of the total data volume, were used to generate the predictive DT models in the data mining program Waikato Environment for Knowledge Analysis (WEKA). In this study, sample densities below 5 % resulted in models with lower power of capturing the complexity of the spatial distribution of the soil in the study area. The relation between the data volume to be handled and the predictive capacity of the models was best for samples between 5 and 15 %. For the models based on these sample densities, the collected field data indicated an accuracy of predictive mapping close to 70 %.

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OBJECTIVE: To assess the variation in Anopheles darlingi's biting activity compared to An. marajoara in the same locality and to biting activity data from other regions. METHODS: Using human bait, eight observations of the biting activity of An. darlingi and An. marajoara were carried out during 1999 and 2000 in the municipality of São Raimundo do Pirativa, state of Amapá, Brazil. Each observation consisted of three consecutive 13-hour collections, close to full moon. There were shifts of collectors in the observation points and nocturnal periods. RESULTS: An. darlingi revealed considerable plasticity of biting activity in contrast to An. marajoara, which showed well-defined crepuscular biting peaks. No significant correlation between density and biting activity was found, but a significant correlation existed between time and proportional crepuscular activity, indicating underlying ecological processes not yet understood. Two of the four available data sets having multiple observations at one locality showed considerable plasticity of this species' biting patterns as well. CONCLUSION: Intra-population variation of biting activity can be as significant as inter-population variation. Some implications in malaria vector control and specific studies are also discussed.

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Evidence suggests that human semen quality may have been deteriorating in recent years. Most of the evidence is retrospective, based on analysis of data sets collected for other purposes. Measures of male infertility are needed if we want to monitor the biological capacity for males to reproduce over time or between different populations. We also need these measures in analytical epidemiology if we want to identify risk indicators, risk factors, or even causes of an impaired male fecundity-that is, the male component in the biological ability to reproduce. The most direct evaluation of fecundity is to measure the time it takes to conceive. Since the time of conception may be missed in the case of an early abortion, time to get pregnant is often measured as the time it takes to obtain a conception that survives until a clinically recognized pregnancy or even a pregnancy that ends with a live born child occurs. A prolonged time required to produce pregnancy may therefore be due to a failure to conceive or a failure to maintain a pregnancy until clinical recognition. Studies that focus on quantitative changes in fecundity (that does not cause sterility) should in principle be possible in a pregnancy sample. The most important limitation in fertility studies is that the design requires equal persistency in trying to become pregnant and rather similar fertility desires and family planning methods in the groups to be compared. This design is probably achievable in exposure studies that make comparisons with reasonable comparable groups concerning social conditions and use of contraceptive methods.

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A new phylogenetic analysis of the Nyssorhynchus subgenus (Danoff-Burg and Conn, unpub. data) using six data sets {morphological (all life stages); scanning electron micrographs of eggs; nuclear ITS2 sequences; mitochondrial COII, ND2 and ND6 sequences} revealed different topologies when each data set was analyzed separately but no heterogeneity between the data sets using the arn test. Consequently, the most accurate estimate of the phylogeny was obtained when all the data were combined. This new phylogeny supports a monophyletic Nyssorhynchus subgenus but both previously recognized sections in the subgenus (Albimanus and Argyritarsis) were demonstrated to be paraphyletic relative to each other and four of the seven clades included species previously placed in both sections. One of these clades includes both Anopheles darlingi and An. albimanus, suggesting that the ability to vector malaria effectively may have originated once in this subgenus. Both a conserved (315 bp) and a variable (425 bp) region of the mitochondrial COI gene from 15 populations of An. darlingi from Belize, Bolivia, Brazil, French Guiana, Peru and Venezuela were used to examine the evolutionary history of this species and to test several analytical assumptions. Results demonstrated (1) parsimony analysis is equally informative compared to distance analysis using NJ; (2) clades or clusters are more strongly supported when these two regions are combined compared to either region separately; (3) evidence (in the form of remnants of older haplotype lineages) for two colonization events; and (4) significant genetic divergence within the population from Peixoto de Azevedo (State of Mato Grosso, Brazil). The oldest lineage includes populations from Peixoto, Boa Vista (State of Roraima) and Dourado (State of São Paulo).

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Geographical Information Systems (GIS) facilitate access to epidemiological data through visualization and may be consulted for the development of mathematical models and analysis by spatial statistics. Variables such as land-cover, land-use, elevations, surface temperatures, rainfall etc. emanating from earth-observing satellites, complement GIS as this information allows the analysis of disease distribution based on environmental characteristics. The strength of this approach issues from the specific environmental requirements of those causative infectious agents, which depend on intermediate hosts for their transmission. The distribution of these diseases is restricted, both by the environmental requirements of their intermediate hosts/vectors and by the ambient temperature inside these hosts, which effectively govern the speed of maturation of the parasite. This paper discusses the current capabilities with regard to satellite data collection in terms of resolution (spatial, temporal and spectral) of the sensor instruments on board drawing attention to the utility of computer-based models of the Earth for epidemiological research. Virtual globes, available from Google and other commercial firms, are superior to conventional maps as they do not only show geographical and man-made features, but also allow instant import of data-sets of specific interest, e.g. environmental parameters, demographic information etc., from the Internet.

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In 1991, the World Health Organization (WHO) committed to reducing the prevalence of leprosy to below 1 in 10,000 inhabitants by 2000. Significant improvements in leprosy control have occurred, but leprosy remains a public health problem in many countries due to its high incidence and rate of transmission. This paper reviews data published by the WHO in the years 2000, 2005 and 2010. These data sets included 148 countries or territories that reported to the WHO at least once. Only four countries reported higher prevalence rates in 2010 than in 2000 and eight reported higher case detection rate (CDR) in 2009 than in 1999. Prevalence rate reductions were greater for the first five-year period examined, while CDR reductions were greater in the second five-year period. Thirty-six countries and territories reported at least one prevalence value higher than 1 per 10,000 inhabitants and 32 reported at least one CDR value higher than 9 per 100,000 inhabitants. A total of 39 countries fit at least one of these criteria and all were located in tropical regions.

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Asymptomatic Plasmodium infection carriers represent a major threat to malaria control worldwide as they are silent natural reservoirs and do not seek medical care. There are no standard criteria for asymptomaticPlasmodium infection; therefore, its diagnosis relies on the presence of the parasite during a specific period of symptomless infection. The antiparasitic immune response can result in reducedPlasmodium sp. load with control of disease manifestations, which leads to asymptomatic infection. Both the innate and adaptive immune responses seem to play major roles in asymptomatic Plasmodiuminfection; T regulatory cell activity (through the production of interleukin-10 and transforming growth factor-β) and B-cells (with a broad antibody response) both play prominent roles. Furthermore, molecules involved in the haem detoxification pathway (such as haptoglobin and haeme oxygenase-1) and iron metabolism (ferritin and activated c-Jun N-terminal kinase) have emerged in recent years as potential biomarkers and thus are helping to unravel the immune response underlying asymptomatic Plasmodium infection. The acquisition of large data sets and the use of robust statistical tools, including network analysis, associated with well-designed malaria studies will likely help elucidate the immune mechanisms responsible for asymptomatic infection.

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The most advanced stage of water erosion, the gully, represents severe problems in different contexts, both in rural and urban environments. In the search for a stabilization of the process in a viable manner it is of utmost importance to assess the efficiency of evaluation methodologies. For this purpose, the efficiency of low-cost conservation practices were tested for the reduction of soil and nutrient losses caused by erosion from gullies in Pinheiral, state of Rio de Janeiro. The following areas were studied: gully recovered by means of physical and biological strategies; gullies in recovering stage, by means of physical strategies only, and gullies under no restoration treatment. During the summer of 2005/2006, the following data sets were collected for this study: soil classification of each of the eroded gully areas; planimetric and altimetric survey; determination of rain erosivity indexes; determination of amount of soil sediment; sediment grain size characteristics; natural amounts of nutrients Ca, Mg, K and P, as well as total C and N concentrations. The results for the three first measurements were 52.5, 20.5, and 29.0 Mg in the sediments from the gully without intervention, and of 1.0, 1.7 and 1.8 Mg from the gully with physical interventions, indicating an average reduction of 95 %. The fully recovered gully produced no sediment during the period. The data of total nutrient loss from the three gullies under investigation showed reductions of 98 % for the recovering gully, and 99 % for the fully recovered one. As for the loss of nutrients, the data indicate a nutrient loss of 1,811 kg from for the non-treated gully. The use of physical and biological interventions made it possible to reduce overall nutrient loss by more than 96 %, over the entire rainy season, as compared to the non-treated gully. Results show that the methods used were effective in reducing soil and nutrient losses from gullies.

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Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

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Pedotransfer functions (PTF) were developed to estimate the parameters (α, n, θr and θs) of the van Genuchten model (1980) to describe soil water retention curves. The data came from various sources, mainly from studies conducted by universities in Northeast Brazil, by the Brazilian Agricultural Research Corporation (Embrapa) and by a corporation for the development of the São Francisco and Parnaíba river basins (Codevasf), totaling 786 retention curves, which were divided into two data sets: 85 % for the development of PTFs, and 15 % for testing and validation, considered independent data. Aside from the development of general PTFs for all soils together, specific PTFs were developed for the soil classes Ultisols, Oxisols, Entisols, and Alfisols by multiple regression techniques, using a stepwise procedure (forward and backward) to select the best predictors. Two types of PTFs were developed: the first included all predictors (soil density, proportions of sand, silt, clay, and organic matter), and the second only the proportions of sand, silt and clay. The evaluation of adequacy of the PTFs was based on the correlation coefficient (R) and Willmott index (d). To evaluate the PTF for the moisture content at specific pressure heads, we used the root mean square error (RMSE). The PTF-predicted retention curve is relatively poor, except for the residual water content. The inclusion of organic matter as a PTF predictor improved the prediction of parameter a of van Genuchten. The performance of soil-class-specific PTFs was not better than of the general PTF. Except for the water content of saturated soil estimated by particle size distribution, the tested models for water content prediction at specific pressure heads proved satisfactory. Predictions of water content at pressure heads more negative than -0.6 m, using a PTF considering particle size distribution, are only slightly lower than those obtained by PTFs including bulk density and organic matter content.

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Taking into account the nature of the hydrological processes involved in in situ measurement of Field Capacity (FC), this study proposes a variation of the definition of FC aiming not only at minimizing the inadequacies of its determination, but also at maintaining its original, practical meaning. Analysis of FC data for 22 Brazilian soils and additional FC data from the literature, all measured according to the proposed definition, which is based on a 48-h drainage time after infiltration by shallow ponding, indicates a weak dependency on the amount of infiltrated water, antecedent moisture level, soil morphology, and the level of the groundwater table, but a strong dependency on basic soil properties. The dependence on basic soil properties allowed determination of FC of the 22 soil profiles by pedotransfer functions (PTFs) using the input variables usually adopted in prediction of soil water retention. Among the input variables, soil moisture content θ (6 kPa) had the greatest impact. Indeed, a linear PTF based only on it resulted in an FC with a root mean squared residue less than 0.04 m³ m-3 for most soils individually. Such a PTF proved to be a better FC predictor than the traditional method of using moisture content at an arbitrary suction. Our FC data were compatible with an equivalent and broader USA database found in the literature, mainly for medium-texture soil samples. One reason for differences between FCs of the two data sets of fine-textured soils is due to their different drainage times. Thus, a standardized procedure for in situ determination of FC is recommended.

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The objective of this work was to build mock-ups of complete yerba mate plants in several stages of development, using the InterpolMate software, and to compute photosynthesis on the interpolated structure. The mock-ups of yerba-mate were first built in the VPlants software for three growth stages. Male and female plants grown in two contrasting environments (monoculture and forest understory) were considered. To model the dynamic 3D architecture of yerba-mate plants during the biennial growth interval between two subsequent prunings, data sets of branch development collected in 38 dates were used. The estimated values obtained from the mock-ups, including leaf photosynthesis and sexual dimorphism, are very close to those observed in the field. However, this similarity was limited to reconstructions that included growth units from original data sets. The modeling of growth dynamics enables the estimation of photosynthesis for the entire yerba mate plant, which is not easily measurable in the field. The InterpolMate software is efficient for building yerba mate mock-ups.

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Imide compounds have shown biological activity. These compounds can be easily synthesized with good yields. The objective of this paper was the rational planning of imides and sulfonamides with antinociceptive activity using the 3D-QSAR/CoMFA approach. The studies were performed using two data sets. The first set consisted of 39 cyclic imides while the second set consisted of 39 imides and 15 sulfonamides. The 3D- QSAR/CoMFA models have shown that the steric effect is important for the antinociceptive activity of imide and sulphonamide compounds. Ten new compounds with improved potential antinociceptive activity have been proposed by de novo design leapfrog simulations.

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Taking into account that the sampling intensity of soil attributes is a determining factor for applying of concepts of precision agriculture, this study aims to determine the spatial distribution pattern of soil attributes and corn yield at four soil sampling intensities and verify how sampling intensity affects cause-effect relationship between soil attributes and corn yield. A 100-referenced point sample grid was imposed on the experimental site. Thus, each sampling cell encompassed an area of 45 m² and was composed of five 10-m long crop rows, where referenced points were considered the center of the cell. Samples were taken from at 0 to 0.1 m and 0.1 to 0.2 m depths. Soil chemical attributes and clay content were evaluated. Sampling intensities were established by initial 100-point sampling, resulting data sets of 100; 75; 50 and 25 points. The data were submitted to descriptive statistical and geostatistics analyses. The best sampling intensity to know the spatial distribution pattern was dependent on the soil attribute being studied. The attributes P and K+ content showed higher spatial variability; while the clay content, Ca2+, Mg2+ and base saturation values (V) showed lesser spatial variability. The spatial distribution pattern of clay content and V at the 100-point sampling were the ones which best explained the spatial distribution pattern of corn yield.

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The aim of this study was to compare the hydrographically conditioned digital elevation models (HCDEMs) generated from data of VNIR (Visible Near Infrared) sensor of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), of SRTM (Shuttle Radar Topography Mission) and topographical maps from IBGE in a scale of 1:50,000, processed in the Geographical Information System (GIS), aiming the morphometric characterization of watersheds. It was taken as basis the Sub-basin of São Bartolomeu River, obtaining morphometric characteristics from HCDEMs. Root Mean Square Error (RMSE) and cross validation were the statistics indexes used to evaluate the quality of HCDEMs. The percentage differences in the morphometric parameters obtained from these three different data sets were less than 10%, except for the mean slope (21%). In general, it was observed a good agreement between HCDEMs generated from remote sensing data and IBGE maps. The result of HCDEM ASTER was slightly higher than that from HCDEM SRTM. The HCDEM ASTER was more accurate than the HCDEM SRTM in basins with high altitudes and rugged terrain, by presenting frequency altimetry nearest to HCDEM IBGE, considered standard in this study.