935 resultados para principal components analysis


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ABSTRACT This study investigated the assemblages attributes (composition, abundance, richness, diversity and evenness) and the most representative genera of Odonata, Anisoptera at Água Boa and Perobão Streams, Iguatemi River basin, Brazil. Both are first order streams with similar length that are impacted by riparian forest removal and silting. Quarterly samplings were conducted from March to December 2008 in the upper, intermediate and lower stretch of each stream. The Mantel test was used to check the influence of spatial autocorrelation on the Odonata composition. Spatial variations in the composition were summarized by the Principal Coordinates Analysis (PCoA) using Mantel test residuals. The effects of spatial correlation on richness and abundance were investigated by the spatial correlogram of Moranʼs I coefficients. The most representative genera in each stream were identified by the Indicator Value Method. The spatial variations in the attributes of the assemblages were assessed using analysis of variance of null models. We collected 500 immature individuals of 23 genera and three families. Among the attributes analyzed only the composition and abundance showed significant spatial differences, with the highest mean abundance found in the Perobão Stream. Miathyria and Zenithoptera were the indicator genera of the Água Boa Stream and Erythrodiplax, Libellula, Macrothemis, Progomphus and Tramea were the indicator genera of the Perobão Stream.

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Species distribution models (SDMs) are increasingly used to predict environmentally induced range shifts of habitats of plant and animal species. Consequently SDMs are valuable tools for scientifically based conservation decisions. The aims of this paper are (1) to identify important drivers of butterfly species persistence or extinction, and (2) to analyse the responses of endangered butterfly species of dry grasslands and wetlands to likely future landscape changes in Switzerland. Future land use was represented by four scenarios describing: (1) ongoing land use changes as observed at the end of the last century; (2) a liberalisation of the agricultural markets; (3) a slightly lowered agricultural production; and (4) a strongly lowered agricultural production. Two model approaches have been applied. The first (logistic regression with principal components) explains what environmental variables have significant impact on species presence (and absence). The second (predictive SDM) is used to project species distribution under current and likely future land uses. The results of the explanatory analyses reveal that four principal components related to urbanisation, abandonment of open land and intensive agricultural practices as well as two climate parameters are primary drivers of species occurrence (decline). The scenario analyses show that lowered agricultural production is likely to favour dry grassland species due to an increase of non-intensively used land, open canopy forests, and overgrown areas. In the liberalisation scenario dry grassland species show a decrease in abundance due to a strong increase of forested patches. Wetland butterfly species would decrease under all four scenarios as their habitats become overgrown

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BACKGROUND AND AIMS: Inflammatory bowel disease (IBD) frequently manifests during childhood and adolescence. For providing and understanding a comprehensive picture of a patients' health status, health-related quality of life (HRQoL) instruments are an essential complement to clinical symptoms and functional limitations. Currently, the IMPACT-III questionnaire is one of the most frequently used disease-specific HRQoL instrument among patients with IBD. However, there is a lack of studies examining the validation and reliability of this instrument. METHODS: 146 paediatric IBD patients from the multicenter Swiss IBD paediatric cohort study database were included in the study. Medical and laboratory data were extracted from the hospital records. HRQoL data were assessed by means of standardized questionnaires filled out by the patients in a face-to-face interview. RESULTS: The original six IMPACT-III domain scales could not be replicated in the current sample. A principal component analysis with the extraction of four factor scores revealed the most robust solution. The four factors indicated good internal reliability (Cronbach's alpha=.64-.86), good concurrent validity measured by correlations with the generic KIDSCREEN-27 scales and excellent discriminant validity for the dimension of physical functioning measured by HRQoL differences for active and inactive severity groups (p<.001, d=1.04). CONCLUSIONS: This study with Swiss children with IBD indicates good validity and reliability for the IMPACT-III questionnaire. However, our findings suggest a slightly different factor structure than originally proposed. The IMPACT-III questionnaire can be recommended for its use in clinical practice. The factor structure should be further examined in other samples.

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In this paper we re-examine the long standing and puzzling correlation between national savings and investment in industrial countries. We apply an econometric methodology that allows us to separate idiosyncratic correlation at the country level from correlation at the global level. In a major break with the existing literature, we find no evidence of a long run relationship in the idiosyncratic components of savings and investment. We also find that the global components in savings and investments comove, indicating that they react to shocks of a global nature.

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Existing empirical evidence suggests that the Uncovered Interest Rate Parity (UIRP) condition may not hold due to an exchange risk premium. For a panel data set of eleven emerging European economies we decompose this exchange risk premium into an idiosyncratic (country-specific) elements and a common factor using a principal components approach. We present evidence of a stationary idiosyncratic component and nonstationary common factor. This result leads to the conclusion of a nonstationary risk premium for these countries and a violation of the UIRP in the long-run, which is in contrast to previous studies often documenting a stationary premium in developed countries. Furthermore, we report that the variation in the premium is largely attributable to a common factor influenced by economic developments in the United States.

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The introduction of culture-independent molecular screening techniques, especially based on 16S rRNA gene sequences, has allowed microbiologists to examine a facet of microbial diversity not necessarily reflected by the results of culturing studies. The bacterial community structure was studied for a pesticide-contaminated site that was subsequently remediated using an efficient degradative strain Arthrobacter protophormiae RKJ100. The efficiency of the bioremediation process was assessed by monitoring the depletion of the pollutant, and the effect of addition of an exogenous strain on the existing soil community structure was determined using molecular techniques. The 16S rRNA gene pool amplified from the soil metagenome was cloned and restriction fragment length polymorphism studies revealed 46 different phylotypes on the basis of similar banding patterns. Sequencing of representative clones of each phylotype showed that the community structure of the pesticide-contaminated soil was mainly constituted by Proteobacteria and Actinomycetes. Terminal restriction fragment length polymorphism analysis showed only nonsignificant changes in community structure during the process of bioremediation. Immobilized cells of strain RKJ100 enhanced pollutant degradation but seemed to have no detectable effects on the existing bacterial community structure.

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In this paper we examine the out-of-sample forecast performance of high-yield credit spreads regarding real-time and revised data on employment and industrial production in the US. We evaluate models using both a point forecast and a probability forecast exercise. Our main findings suggest the use of few factors obtained by pooling information from a number of sector-specific high-yield credit spreads. This can be justified by observing that, especially for employment, there is a gain from using a principal components model fitted to high-yield credit spreads compared to the prediction produced by benchmarks, such as an AR, and ARDL models that use either the term spread or the aggregate high-yield spread as exogenous regressor. Moreover, forecasts based on real-time data are generally comparable to forecasts based on revised data. JEL Classification: C22; C53; E32 Keywords: Credit spreads; Principal components; Forecasting; Real-time data.

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Despite the long tradition for asking about the negative social and health consequences of alcohol consumption in surveys, little is known about the dimensionality of these consequences. Analysing cross-sectional and longitudinal data from the Nordic Taxation Study collected for Sweden, Finland, and Denmark in two waves in 2003 and 2004 by means of an explorative principal component analysis for categorical data (CATPCA), it is tested whether consequences have a single underlying dimension across cultures. It further tests the reliability, replicability, concurrent and predictive validity of the consequence scales. A one-dimensional solution was commonly preferable. Whereas the two-dimensional solution was unable to distinguish clearly between different concepts of consequences, the one-dimensional solution resulted in interpretable, generally very stable scales within countries across different samples and time.

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In order to classify mosquito immature stage habitats, samples were taken in 42 localities of Córdoba Province, Argentina, representing the phytogeographic regions of Chaco, Espinal and Pampa. Immature stage habitats were described and classified according to the following criteria: natural or artificial; size; location related to light and neighboring houses; vegetation; water: permanence, movement, turbidity and pH. Four groups of species were associated based on the habitat similarity by means of cluster analysis: Aedes albifasciatus, Culex saltanensis, Cx. mollis, Cx. brethesi, Psorophora ciliata, Anopheles albitarsis, and Uranotaenia lowii (Group A); Cx. acharistus, Cx. quinquefasciatus, Cx. bidens, Cx. dolosus, Cx. maxi and Cx. apicinus (Group B); Cx. coronator, Cx. chidesteri, Mansonia titillans and Ps. ferox (Group C); Ae. fluviatilis and Ae. milleri (Group D). The principal component analysis (ordination method) pointed out that the different types of habitats, their nature (natural or artificial), plant species, water movement and depth are the main characters explaining the observed variation among the mosquito species. The distribution of mosquito species by phytogeographic region did not affect the species groups, since species belonging to different groups were collected in the same region.

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The reported prevalence of late-life depressive symptoms varies widely between studies, a finding that might be attributed to cultural as well as methodological factors. The EURO-D scale was developed to allow valid comparison of prevalence and risk associations between European countries. This study used Confirmatory Factor Analysis (CFA) and Rasch models to assess whether the goal of measurement invariance had been achieved; using EURO-D scale data collected in 10 European countries as part of the Survey of Health, Ageing and Retirement in Europe (SHARE) (n = 22,777). The results suggested a two-factor solution (Affective Suffering and Motivation) after Principal Component Analysis (PCA) in 9 of the 10 countries. With CFA, in all countries, the two-factor solution had better overall goodness-of-fit than the one-factor solution. However, only the Affective Suffering subscale was equivalent across countries, while the Motivation subscale was not. The Rasch model indicated that the EURO-D was a hierarchical scale. While the calibration pattern was similar across countries, between countries agreement in item calibrations was stronger for the items loading on the affective suffering than the motivation factor. In conclusion, there is evidence to support the EURO-D as either a uni-dimensional or bi-dimensional scale measure of depressive symptoms in late-life across European countries. The Affective Suffering sub-component had more robust cross-cultural validity than the Motivation sub-component.

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In order to determine if habitat similarity is correlated with a similarity of sensilla pattern, we analyzed six species of Triatominae present in two biogeographic regions of Brazil: the "caatinga" and the "cerrado". In broad terms Triatoma infestans (cerrado) and T. brasiliensis (caatinga) are found in human domiciles, T. sordida (cerrado) and T. pseudomaculata (caatinga) colonize peridomestic habitats, and Rhodnius neglectus (cerrado) and R. nasutus (caatinga) inhabit palm tree crowns. The number and distribution of four sensilla types (bristles, thin and thick walled trichoidea, and basiconica) were compared in these species. Sexual dimorphism of sensilla patterns was noted in T. sordida, T. brasiliensis and T. pseudomaculata. A principal component analysis showed three main groups: (i) species that live in the palms, (ii) domiciliated species and (iii) those living in the peridomestic habitat. T. infestans almost exclusively domestic, was placed at the centre of the canonical map and some individuals of other species overlapped there. These results support the idea that the patterns of antennal sensilla are sensitive indicators of adaptive process in Triatominae. We propose that those species that inhabit less stable habitats possess more types of sensilla on the pedicel, and higher number of antennal sensilla.

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DREAM is an initiative that allows researchers to assess how well their methods or approaches can describe and predict networks of interacting molecules [1]. Each year, recently acquired datasets are released to predictors ahead of publication. Researchers typically have about three months to predict the masked data or network of interactions, using any predictive method. Predictions are assessed prior to an annual conference where the best predictions are unveiled and discussed. Here we present the strategy we used to make a winning prediction for the DREAM3 phosphoproteomics challenge. We used Amelia II, a multiple imputation software method developed by Gary King, James Honaker and Matthew Blackwell[2] in the context of social sciences to predict the 476 out of 4624 measurements that had been masked for the challenge. To chose the best possible multiple imputation parameters to apply for the challenge, we evaluated how transforming the data and varying the imputation parameters affected the ability to predict additionally masked data. We discuss the accuracy of our findings and show that multiple imputations applied to this dataset is a powerful method to accurately estimate the missing data. We postulate that multiple imputations methods might become an integral part of experimental design as a mean to achieve cost savings in experimental design or to increase the quantity of samples that could be handled for a given cost.

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El treball té com a objectiu l'estudi de les propietats semàntiques d'un grup de verbs de desplaçament i els seus corresponents arguments. La informació sobre el tipus de complement que demana cada verb és important de cara a conèixer l'estructura sintàctica de la frase i oferir solucions pràctiques en tasques de Processament del Llenguatge Natural. L'anàlisi se centrarà en els verbs conduir, navegar i volar, a partir dels sentits bàsics que el Diccionari d'ús dels verbs catalans (DUVC) descriu per a cadascun d'aquests verbs i de les seves restriccions selectives. Comprovarem, mitjançant un centenar de frases extretes del Corpus d'Ús del Català a la Web de la Universitat Pompeu Fabra i del Corpus Textual Informatitzat de la Llengua Catalana de l'Institut d'Estudis Catalans, si en la llengua es donen només els sentits i usos descrits en el DUVC i quins són els més freqüents. Finalment, descriurem els noms que fan de nucli dels arguments en termes de trets semàntics.

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This study examines how structural determinants influence intermediary factors of child health inequities and how they operate through the communities where children live. In particular, we explore individual, family and community level characteristics associated with a composite indicator that quantitatively measures intermediary determinants of early childhood health in Colombia. We use data from the 2010 Colombian Demographic and Health Survey (DHS). Adopting the conceptual framework of the Commission on Social Determinants of Health (CSDH), three dimensions related to child health are represented in the index: behavioural factors, psychosocial factors and health system. In order to generate the weight of the variables and take into account the discrete nature of the data, principal component analysis (PCA) using polychoric correlations are employed in the index construction. Weighted multilevel models are used to examine community effects. The results show that the effect of household’s SES is attenuated when community characteristics are included, indicating the importance that the level of community development may have in mediating individual and family characteristics. The findings indicate that there is a significant variance in intermediary determinants of child health between-community, especially for those determinants linked to the health system, even after controlling for individual, family and community characteristics. These results likely reflect that whilst the community context can exert a greater influence on intermediary factors linked directly to health, in the case of psychosocial factors and the parent’s behaviours, the family context can be more important. This underlines the importance of distinguishing between community and family intervention programmes.

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Ecological niche modelling was used to predict the potential geographical distribution of Rhodnius nasutus Stål and Rhodnius neglectus Lent, in Brazil and to investigate the niche divergence between these morphologically similar triatomine species. The distribution of R. neglectus covered mainly the cerrado of Central Brazil, but the prediction maps also revealed its occurrence in transitional areas within the caatinga, Pantanal and Amazon biomes. The potential distribution of R. nasutus covered the Northeastern Region of Brazil in the semi-arid caatinga and the Maranhão babaçu forests. Clear ecological niche differences between these species were observed. R. nasutus occurred more in warmer and drier areas than R. neglectus. In the principal component analysis PC1 was correlated with altitude and temperature (mainly temperature in the coldest and driest months) and PC2 with vegetation index and precipitation. The prediction maps support potential areas of co-occurrence for these species in the Maranhão babaçu forests and in caatinga/cerrado transitional areas, mainly in state of Piaui. Entomologists engaged in Chagas disease vector surveillance should be aware that R. neglectus and R. nasutus can occur in the same localities of Northeastern Brazil. Thus, the identification of bugs in these areas should be improved by applying morphometrical and/or molecular methods.