936 resultados para Cluster Analysis of Variables
Resumo:
This paper aims to consider whether there is a link between youth happiness levels and adult life satisfaction. Our results are unequivocal that such a link exists both because demographic and socio-economic conditions are persistent over a lifetime and also because there is a persistence in personality effects. To test this link, we estimate a model of happiness for a sample of young people. This model provides us with a range of variables measuring socio-economic effects and personality effects amongst young people. These variables are then included in the adult life satisfaction model. The model is estimated using data from the British Household Panel Survey for 1994–2008. In addition to childhood happiness levels influencing adult life satisfaction significantly, we also find that the youthful personality trait for happiness has a larger effect on adult life satisfaction than demographic and socio-economic conditions.
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Land cover plays a key role in global to regional monitoring and modeling because it affects and is being affected by climate change and thus became one of the essential variables for climate change studies. National and international organizations require timely and accurate land cover information for reporting and management actions. The North American Land Change Monitoring System (NALCMS) is an international cooperation of organizations and entities of Canada, the United States, and Mexico to map land cover change of North America's changing environment. This paper presents the methodology to derive the land cover map of Mexico for the year 2005 which was integrated in the NALCMS continental map. Based on a time series of 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) data and an extensive sample data base the complexity of the Mexican landscape required a specific approach to reflect land cover heterogeneity. To estimate the proportion of each land cover class for every pixel several decision tree classifications were combined to obtain class membership maps which were finally converted to a discrete map accompanied by a confidence estimate. The map yielded an overall accuracy of 82.5% (Kappa of 0.79) for pixels with at least 50% map confidence (71.3% of the data). An additional assessment with 780 randomly stratified samples and primary and alternative calls in the reference data to account for ambiguity indicated 83.4% overall accuracy (Kappa of 0.80). A high agreement of 83.6% for all pixels and 92.6% for pixels with a map confidence of more than 50% was found for the comparison between the land cover maps of 2005 and 2006. Further wall-to-wall comparisons to related land cover maps resulted in 56.6% agreement with the MODIS land cover product and a congruence of 49.5 with Globcover.
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This contribution is concerned with aposteriori error analysis of discontinuous Galerkin (dG) schemes approximating hyperbolic conservation laws. In the scalar case the aposteriori analysis is based on the L1 contraction property and the doubling of variables technique. In the system case the appropriate stability framework is in L2, based on relative entropies. It is only applicable if one of the solutions, which are compared to each other, is Lipschitz. For dG schemes approximating hyperbolic conservation laws neither the entropy solution nor the numerical solution need to be Lipschitz. We explain how this obstacle can be overcome using a reconstruction approach which leads to an aposteriori error estimate.
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Objective. Therapeutic alliance, modality, and ability to engage with the process of therapy have been the main focus of research into what makes psychotherapy successful. Individuals with complex trauma histories or schizophrenia are suggested to be more difficult to engage and may be less likely to benefit from therapy. This study aimed to track the in-session ‘process’ of working alliance and emotional processing of trauma memories for individuals with schizophrenia. Design. The study utilized session recordings from the treatment arm of an open randomized clinical trial investigating trauma-focused cognitive behavioural therapy (TF-CBT) for individuals with schizophrenia (N = 26). Method. Observer measures of working alliance, emotional processing, and affect arousal were rated at early and late phases of therapy. Correlation analysis was undertaken for process measures. Temporal analysis of expressed emotions was also reported. Results. Working alliance was established and maintained throughout the therapy; however, agreement on goals reduced at the late phase. The participants appeared to be able to engage in emotional processing, but not to the required level for successful cognitive restructuring. Conclusion. This study undertook novel exploration of process variables not usually explored in CBT. It is also the first study of process for TF-CBT with individuals with schizophrenia. This complex clinical sample showed no difficulty in engagement; however, they may not be able to fully undertake the cognitive–emotional demands of this type of therapy. Clinical and research implications and potential limitations of these methods are considered.
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Within-field variation in sugar beet yield and quality was investigated in three commercial sugar beet fields in the east of England to identify the main associated variables and to examine the possibility of predicting yield early in the season with a view to spatially variable management of sugar beet crops. Irregular grid sampling with some purposively-located nested samples was applied. It revealed the spatial variability in each sugar beet field efficiently. In geostatistical analyses, most variograms were isotropic with moderate to strong spatial dependency indicating a significant spatial variation in sugar beet yield and associated growth and environmental variables in all directions within each field. The Kriged maps showed spatial patterns of yield variability within each field and visual association with the maps of other variables. This was confirmed by redundancy analyses and Pearson correlation coefficients. The main variables associated with yield variability were soil type, organic matter, soil moisture, weed density and canopy temperature. Kriged maps of final yield variability were strongly related to that in crop canopy cover, LAI and intercepted solar radiation early in the growing season, and the yield maps of previous crops. Therefore, yield maps of previous crops together with early assessment of sugar beet growth may make an early prediction of within-field variability in sugar beet yield possible. The Broom’s Barn sugar beet model failed to account for the spatial variability in sugar yield, but the simulation was greatly improved when corrected for early canopy development cover and when the simulated yield was adjusted for weeds and plant population. Further research to optimize inputs to maximise sugar yield should target the irrigation and fertilizing of areas within fields with low canopy cover early in the season.
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The number of bidders, N, involved in a construction procurement auction is known to have an important effect on the value of the lowest bid and the mark-up applied by bidders. In practice, for example, it is important for a bidder to have a good estimate of N when bidding for a current contract. One approach, instigated by Friedman in 1956, is to make such an estimate by statistical analysis and modelling. Since then, however, finding a suitable model for N has been an enduring problem for researchers and, despite intensive research activity in the subsequent 30 years, little progress has been made, due principally to the absence of new ideas and perspectives. The debate is resumed by checking old assumptions, providing new evidence relating to concomitant variables and proposing a new model. In doing this and in order to ensure universality, a novel approach is developed and tested by using a unique set of 12 construction tender databases from four continents. This shows the new model provides a significant advancement on previous versions. Several new research questions are also posed and other approaches identified for future study.
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P>Vegetable oils can be extracted using ethanol as solvent. The main goal of this work was to evaluate the ethanol performance on the extraction process of rice bran oil. The influence of process variables, solvent hydration and temperature was evaluated using the response surface methodology, aiming to maximise the soluble substances and gamma-oryzanol transfer and minimise the free fatty acids extraction and the liquid content in the underflow solid. It can be noted that oil solubility in ethanol was highly affected by the water content. The free fatty acids extraction is improved by increasing the moisture content in the solvent. Regarding the gamma-oryzanol, it can be observed that its extraction is affected by temperature when low level of water is added to ethanol. On the other hand, the influence of temperature is minimised with high levels of water in the ethanol.
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This work evaluated the effect of pressure and temperature on yield and characteristic flavour intensity of Brazilian cherry (Eugenia uniflora L) extracts obtained by supercritical CO(2) using response surface analysis, which is a simple and efficient method for first inquiries. A complete central composite 2(2) factorial experimental design was applied using temperature (ranging from 40 to 60 degrees C) and pressure (from 150 to 250 bar) as independent variables. A second order model proved to be predictive (p <= 0.05) for the extract yield as affected by pressure and temperature, with better results being achieved at the central point (200 bar and 50 degrees C). For the flavour intensity, a first order model proved to be predictive (p <= 0.05) showing the influence of temperature. Greater characteristic flavour intensity in extracts was obtained for relatively high temperature (> 50 degrees C), Therefore, as far as Brazilian cherry is concerned, optimum conditions for achieving higher extract yield do not necessarily coincide to those for obtaining richer flavour intensity. Industrial relevance: Supercritical fluid extraction (SFE) is an emerging clean technology through which one may obtain extracts free from organic solvents. Extract yields from natural products for applications in food, pharmaceutical and cosmetic industries have been widely disseminated in the literature. Accordingly, two lines of research have industrial relevance, namely, (i) operational optimization studies for high SFE yields and (ii) investigation on important properties extracts are expected to present (so as to define their prospective industrial application). Specifically, this work studied the optimization of SFE process to obtain extracts from a tropical fruit showing high intensity of its characteristic flavour, aiming at promoting its application in natural aroma enrichment of processed foods. (C) 2008 Elsevier Ltd. All rights reserved.
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The main goal of this work was to evaluate thermodynamic parameters of the soybean oil extraction process using ethanol as solvent. The experimental treatments were as follows: aqueous solvents with water contents varying from 0 to 13% (mass basis) and extraction temperature varying from 50 to 100 degrees C. The distribution coefficients of oil at equilibrium have been used to calculate enthalpy, entropy and free energy changes. The results indicate that oil extraction process with ethanol is feasible and spontaneous, mainly under higher temperature. Also, the influence of water level in the solvent and temperature were analysed using the response surface methodology (RSM). It can be noted that the extraction yield was highly affected by both independent variables. A joint analysis of thermodynamic and RSM indicates the optimal level of solvent hydration and temperature to perform the extraction process.
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Flickering is a phenomenon related to mass accretion observed among many classes of astrophysical objects. In this paper we present a study of flickering emission lines and the continuum of the cataclysmic variable V3885 Sgr. The flickering behavior was first analyzed through statistical analysis and the power spectra of lightcurves. Autocorrelation techniques were then employed to estimate the flickering timescale of flares. A cross-correlation study between the line and its underlying continuum variability is presented. The cross-correlation between the photometric and spectroscopic data is also discussed. Periodograms, calculated using emission-line data, show a behavior that is similar to those obtained from photometric datasets found in the literature, with a plateau at lower frequencies and a power-law at higher frequencies. The power-law index is consistent with stochastic events. The cross-correlation study indicates the presence of a correlation between the variability on Ha and its underlying continuum. Flickering timescales derived from the photometric data were estimated to be 25 min for two lightcurves and 10 min for one of them. The average timescales of the line flickering is 40 min, while for its underlying continuum it drops to 20 min.
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Krameria plants are found in arid regions of the Americas and present a floral system that attracts oil-collecting bees. Niche modeling and multivariate tools were applied to examine ecological and geographical aspects of the 18 species of this genus, using occurrence data obtained from herbaria and literature. Niche modeling showed the potential areas of occurrence for each species and the analysis of climatic variables suggested that North American species occur mostly in deserted or xeric ecoregions with monthly precipitation below 140 mm and large temperature ranges. South American species are mainly found in deserted ecoregions and subtropical savannas where monthly precipitation often exceeds 150 mm and temperature ranges are smaller. Principal Component Analysis (PCA) performed with values of temperature and precipitation showed that the distribution limits of Krameria species are primarily associated with maximum and minimum temperatures. Modeling of Krameria species proved to be a useful tool for analyzing the influence of the ecological niche variables in the geographical distribution of species, providing new information to guide future investigations. (C) 2011 Elsevier Ltd. All rights reserved.
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Developed countries have an even distribution of published papers on the seventeen model organisms. Developing countries have biased preferences for a few model organisms which are associated with endemic human diseases. A variant of the Hirsch-index, that we call the mean (mo)h-index (""model organism h-index""), shows an exponential relationship with the amount of papers published in each country on the selected model organisms. Developing countries cluster together with low mean (mo)h-indexes, even those with high number of publications. The growth curves of publications on the recent model Caenorhabditis elegans in developed countries shows different formats. We also analyzed the growth curves of indexed publications originating from developing countries. Brazil and South Korea were selected for this comparison. The most prevalent model organisms in those countries show different growth curves when compared to a global analysis, reflecting the size and composition of their research communities.
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Background and Objective: Although certain serotypes of Aggregatibacter actinomycetemcomitans are associated more with aggressive periodontitis than are other serotypes, the correlation between distinct lineages and virulence traits in this species is poorly understood. This study aimed to evaluate the polymorphism of genes encoding putative virulence factors of clinical isolates, and to correlate these findings with A. actinomycetemcomitans serotypes, genotypes and periodontal status of the hosts. Material and Methods: Twenty-six clinical isolates from diverse geographic populations with different periodontal conditions were evaluated. Genotyping was performed using pulse-field gel electrophoresis. Polymorphisms in the genes encoding leukotoxin, Aae, ApaH and determinants for serotype-specific O polysaccharide were investigated. Results: The isolates were classified into serotypes a-f, and exhibited three apaH genotypes, five aae alleles and 25 macrorestriction profiles. Two serotype b isolates (7.7%), obtained from Brazilian patients with aggressive periodontitis, were associated with the highly leukotoxic genotype; these isolates showed identical fingerprint patterns and aae and apaH genotypes. Serotype c, obtained from various periodontal conditions, was the most prevalent among Brazilian isolates, and isolates were distributed in two aae alleles, but formed a genetically distinct group based on apaH analysis. Cluster analysis showed a close relationship between fingerprinting genotypes and serotypes/apaH genotypes, but not with aae genotypes. Conclusion: Apart from the deletion in the ltx promoter region, no disease-associated markers were identified. Non-JP2-like strains recovered from individuals with periodontal disease exhibited considerable genetic variation regarding aae/apaH genotypes, serotypes and XhoI DNA fingerprints.
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A new polymeric coating consisting of a dual-phase, polydimethylsiloxane (PDMS) and polypyrrole (PPY) was developed for the stir bar sorptive extraction (SBSE) of antidepressants (mirtazapine, citalopram, paroxetine, duloxetine, fluoxetine and sertraline) from plasma samples, followed by liquid chromatography analysis (SBSE/LC-UV). The extractions were based on both adsorption (PPY) and sorption (PDMS) mechanisms. SBSE variables, such as extraction time, temperature, pH of the matrix, and desorption time were optimized, in order to achieve suitable analytical sensitivity in a short time period. The PDMS/PPY coated stir bar showed high extraction efficiency (sensitivity and selectivity) toward the target analytes. The quantification limits (LOQ) of the SBSE/LC-UV method ranged from 20 ng mL(-1) to 50 ng mL(-1), and the linear range was from LOQ to 500 ng mL(-1), with a determination coefficient higher than 0.99. The inter-day precision of the SBSE/LC-UV method presented a variation coefficient lower than 15%. The efficiency of the SBSE/LC-UV method was proved by analysis of plasma samples from elderly depressed patients. (C) 2008 Elsevier B.V. All rights reserved.
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In this paper, we study the influence of the National Telecom Business Volume by the data in 2008 that have been published in China Statistical Yearbook of Statistics. We illustrate the procedure of modeling “National Telecom Business Volume” on the following eight variables, GDP, Consumption Levels, Retail Sales of Social Consumer Goods Total Renovation Investment, the Local Telephone Exchange Capacity, Mobile Telephone Exchange Capacity, Mobile Phone End Users, and the Local Telephone End Users. The testing of heteroscedasticity and multicollinearity for model evaluation is included. We also consider AIC and BIC criterion to select independent variables, and conclude the result of the factors which are the optimal regression model for the amount of telecommunications business and the relation between independent variables and dependent variable. Based on the final results, we propose several recommendations about how to improve telecommunication services and promote the economic development.