983 resultados para spatial distance
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We used microsatellites to study the fine-scale genetic structure of a highly polygynous and largely uni-colonial population of the ant Formica paralugubris. Genetic data indicate that long-distance gene flow between established nests is limited and new queens are primarily recruited from within their natal nest. Most matings occur between nestmates and are random at this level. In the center of the study area, budding and permanent connections between nests result in strong population viscosity, with close nests being more similar generically than distant nests. In contrast, nests located outside of this supercolony show no isolation by distance, suggesting that they have been initiated by queens that participated in mating flights rather than by budding from nearby nests in our sample population. Recruitment of nestmates as new reproductive individuals and population viscosity in the supercolony increase genetic differentiation between nests. This in turn inflates relatedness estimates among worker nestmates (r = 0.17) above what is due to close pedigree links. Local spatial genetic differentiation may favor the maintenance of altruism when workers raise queens that will disperse on foot and compete with less related queens from neighboring nests or disperse on the wing and compete with unrelated queens.
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Background: Previous magnetic resonance imaging (MRI) studies in young patients with bipolar disorder indicated the presence of grey matter concentration changes as well as microstructural alterations in white matter in various neocortical areas and the corpus callosum. Whether these structural changes are also present in elderly patients with bipolar disorder with long-lasting clinical evolution remains unclear. Methods: We performed a prospective MRI study of consecutive elderly, euthymic patients with bipolar disorder and healthy, elderly controls. We conducted a voxel-based morphometry (VBM) analysis and a tract-based spatial statistics (TBSS) analysis to assess fractional anisotropy and longitudinal, radial and mean diffusivity derived by diffusion tensor imaging (DTI). Results: We included 19 patients with bipolar disorder and 47 controls in our study. Fractional anisotropy was the most sensitive DTI marker and decreased significantly in the ventral part of the corpus callosum in patients with bipolar disorder. Longitudinal, radial and mean diffusivity showed no significant between-group differences. Grey matter concentration was reduced in patients with bipolar disorder in the right anterior insula, head of the caudate nucleus, nucleus accumbens, ventral putamen and frontal orbital cortex. Conversely, there was no grey matter concentration or fractional anisotropy increase in any brain region in patients with bipolar disorder compared with controls. Limitations: The major limitation of our study is the small number of patients with bipolar disorder. Conclusion: Our data document the concomitant presence of grey matter concentration decreases in the anterior limbic areas and the reduced fibre tract coherence in the corpus callosum of elderly patients with long-lasting bipolar disorder.
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We develop a setting with weak intellectual property rights, where firms' boundaries, location and knowledge spillovers are endogenous. We have two main results. The first one is that, if communication costs increase with distance, entrepreneurs concerned about information leakage have a benefit from locating away from the industry center: distance is an obstacle to collusive trades between members andnon-members. The second result is that we identify a trade-off for the entrepreneur between owning a facility (controlling all its characteristics) and sharing a facility with a {\it non-member} (an agent not involved in production), therefore losing control over some of its characteristics. We focus on ``location" as the relevant characteristic of the facility, but location can be used as a spatial metaphor for other relevant characteristics of the facility. For theentrepreneur, sharing the facility with non-members implies that the latter, as co-owners, know the location (even if they do not have access to it). Knowledge of the location for the co-owners facilitates collusion with employees, what increases leakage. The model yields a benefit for new plants from spatial dispersion (locating at the periphery of the industry), particularly so for new plants of new firms.We relate this result with recent empirical findings on the dynamics of industry location.
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In order to interpret the biplot it is necessary to know which points usually variables are the ones that are important contributors to the solution, and this information is available separately as part of the biplot s numerical results. We propose a new scaling of the display, called the contribution biplot, which incorporates this diagnostic directly into the graphical display, showing visually the important contributors and thus facilitating the biplot interpretation and often simplifying the graphical representation considerably. The contribution biplot can be applied to a wide variety of analyses such as correspondence analysis, principal component analysis, log-ratio analysis and the graphical results of a discriminant analysis/MANOVA, in fact to any method based on the singular-value decomposition. In the contribution biplot one set of points, usually the rows of the data matrix, optimally represent the spatial positions of the cases or sample units, according to some distance measure that usually incorporates some form of standardization unless all data are comparable in scale. The other set of points, usually the columns, is represented by vectors that are related to their contributions to the low-dimensional solution. A fringe benefit is that usually only one common scale for row and column points is needed on the principal axes, thus avoiding the problem of enlarging or contracting the scale of one set of points to make the biplot legible. Furthermore, this version of the biplot also solves the problem in correspondence analysis of low-frequency categories that are located on the periphery of the map, giving the false impression that they are important, when they are in fact contributing minimally to the solution.
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Ce mémoire est l’occasion de partager le résultat de la mise en place de ce dispositif de formation à distance que nous avons mené dans l’université du Cap-Vert. Dans la première partie, nous décrirons la nature de la politique éducative au Cap-Vert. Nous contextualiserons les principes de l’installation de l’université publique dans ce pays, ainsi que les intentions d’innovation pédagogique de cette université. La deuxième partie portera un regard complémentaire sur l’utilisation des TIC et de l’internet dans l’enseignement/apprentissage d’une langue, cas du français langue étrangère, et nous nous inspirerons des théories constructiviste et socio-constructiviste. Finalement, la troisième partie détaillera toutes les étapes de la conception et de la mise en place du dispositif de formation à distance. Dans cette troisième partie, nous aborderons dans un premier temps la question des enjeux et des risques du e-Learning et nous présenterons notre mission dans le projet « e-Learning.cv » mené par l’université. Puis, dans un deuxième temps nous analyserons quelques cours que nous avons mis en ligne, en sachant qu’un cours en ligne n’est pas la simple reproduction d’un support pédagogique imprimé mais il offre à l’apprenant un environnement multimédia et interactif. Finalement dans un troisième temps nous essayerons de prendre un peu de recul pour faire une analyse critique de ce que nous avons réalisé et essayer par là même de dégager les perspectives pour améliorer le travail effectué.
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What explains the spatial distribution of wages across US counties? I find that two of the most important factors are spatial technology diffusion and externalities due to the aggregate scale of production. One empirical finding supporting the importance of spatial technology diffusion is that average wages in a county decrease with the average level of schooling in neighboring counties when employment in the county and average wages in neighboring counties are held constant. All empirical results are obtained using anovel instrument for (endogenous) employment at the county-leveland take into account other factors (e.g. productivity-differencesacross states, climate) that may determine wages.
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Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.
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1. Aim - Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics in evolutionary and community contexts, highlight the growing need for robust methods to quantify niche differences between or within taxa. We propose a statistical framework to describe and compare environmental niches from occurrence and spatial environmental data.¦2. Location - Europe, North America, South America¦3. Methods - The framework applies kernel smoothers to densities of species occurrence in gridded environmental space to calculate metrics of niche overlap and test hypotheses regarding niche conservatism. We use this framework and simulated species with predefined distributions and amounts of niche overlap to evaluate several ordination and species distribution modeling techniques for quantifying niche overlap. We illustrate the approach with data on two well-studied invasive species.¦4. Results - We show that niche overlap can be accurately detected with the framework when variables driving the distributions are known. The method is robust to known and previously undocumented biases related to the dependence of species occurrences on the frequency of environmental conditions that occur across geographic space. The use of a kernel smoother makes the process of moving from geographical space to multivariate environmental space independent of both sampling effort and arbitrary choice of resolution in environmental space. However, the use of ordination and species distribution model techniques for selecting, combining and weighting variables on which niche overlap is calculated provide contrasting results.¦5. Main conclusions - The framework meets the increasing need for robust methods to quantify niche differences. It is appropriate to study niche differences between species, subspecies or intraspecific lineages that differ in their geographical distributions. Alternatively, it can be used to measure the degree to which the environmental niche of a species or intraspecific lineage has changed over time.
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Com características morfológicas e edafo-climáticas extremamente diversificadas, a ilha de Santo Antão em Cabo Verde apresenta uma reconhecida vulnerabilidade ambiental a par de uma elevada carência de estudos científicos que incidam sobre essa realidade e sirvam de base à uma compreensão integrada dos fenómenos. A cartografia digital e as tecnologias de informação geográfica vêm proporcionando um avanço tecnológico na colecção, armazenamento e processamento de dados espaciais. Várias ferramentas actualmente disponíveis permitem modelar uma multiplicidade de factores, localizar e quantificar os fenómenos bem como e definir os níveis de contribuição de diferentes factores no resultado final. No presente estudo, desenvolvido no âmbito do curso de pós-graduação e mestrado em sistemas de Informação geográfica realizado pela Universidade de Trás-os-Montes e Alto Douro, pretende-se contribuir para a minimização do deficit de informação relativa às características biofísicas da citada ilha, recorrendo-se à aplicação de tecnologias de informação geográfica e detecção remota, associadas à análise estatística multivariada. Nesse âmbito, foram produzidas e analisadas cartas temáticas e desenvolvido um modelo de análise integrada de dados. Com efeito, a multiplicidade de variáveis espaciais produzidas, de entre elas 29 variáveis com variação contínua passíveis de influenciar as características biofísicas da região e, possíveis ocorrências de efeitos mútuos antagónicos ou sinergéticos, condicionam uma relativa complexidade à interpretação a partir dos dados originais. Visando contornar este problema, recorre-se a uma rede de amostragem sistemática, totalizando 921 pontos ou repetições, para extrair os dados correspondentes às 29 variáveis nos pontos de amostragem e, subsequente desenvolvimento de técnicas de análise estatística multivariada, nomeadamente a análise em componentes principais. A aplicação destas técnicas permitiu simplificar e interpretar as variáreis originais, normalizando-as e resumindo a informação contida na diversidade de variáveis originais, correlacionadas entre si, num conjunto de variáveis ortogonais (não correlacionadas), e com níveis de importância decrescente, as componentes principais. Fixou-se como meta a concentração de 75% da variância dos dados originais explicadas pelas primeiras 3 componentes principais e, desenvolveu-se um processo interactivo em diferentes etapas, eliminando sucessivamente as variáveis menos representativas. Na última etapa do processo as 3 primeiras CP resultaram em 74,54% da variância dos dados originais explicadas mas, que vieram a demonstrar na fase posterior, serem insuficientes para retratar a realidade. Optou-se pela inclusão da 4ª CP (CP4), com a qual 84% da referida variância era explicada e, representando oito variáveis biofísicas: a altitude, a densidade hidrográfica, a densidade de fracturação geológica, a precipitação, o índice de vegetação, a temperatura, os recursos hídricos e a distância à rede hidrográfica. A subsequente interpolação da 1ª componente principal (CP1) e, das principais variáveis associadas as componentes CP2, CP3 e CP4 como variáveis auxiliares, recorrendo a técnicas geoestatística em ambiente ArcGIS permitiu a obtenção de uma carta representando 84% da variação das características biofísicas no território. A análise em clusters validada pelo teste “t de Student” permitiu reclassificar o território em 6 unidades biofísicas homogéneas. Conclui-se que, as tecnologias de informação geográfica actualmente disponíveis a par de facilitar análises interactivas e flexíveis, possibilitando que se faça variar temas e critérios, integrar novas informações e introduzir melhorias em modelos construídos com bases em informações disponíveis num determinado contexto, associadas a técnicas de análise estatística multivariada, possibilitam, com base em critérios científicos, desenvolver a análise integrada de múltiplas variáveis biofísicas cuja correlação entre si, torna complexa a compreensão integrada dos fenómenos.
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The knowledge on Atlantic Forest scarab beetle fauna is quite limited. This biome is strongly degraded and these insects can be used as bioindicators since they are sensitive to forest destruction and show distinct organizational patterns in forest fragments or in areas that have been deteriorated by human activity. Thus, a study of the Scarabaeidae (sensu stricto) dung beetles fauna that inhabit Serra do Japi, São Paulo, Brazil (23º12'-23º22' S and 46º53'-47º03'W) was carried out; the monthly species richness was analyzed in six areas during one year and the vegetation's structural physiognomy was described. The areas included a conserved and a degraded valley, a northward and a southward hillside, a hilltop, and an area of secondary forest growing under eucalyptus trees. The specimens were collected using four pitfall traps baited with human feces, which remained at each spot during 48 hours. Between September, 1997 and August, 1998, 3524 individuals of 39 species were collected; the most abundant were: Canthidium trinodosum, Eurysternus cyanescens, Uroxys kratochvili, Scybalocanthon nigriceps, Uroxys lata, Canthonella sp., Dichotomius assifer, Deltochilum furcatum, Canthidium sp.2, Canthon latipes, Deltochilum rubripenne, Eurysternus sp., and Dichotomius sp.1. The number of individuals and species was greater in the hot, rainy season, when there was a correlation between the number of species and the mean annual temperature [r²= 0.69; p<0.01]. The lower winter richness was most pronounced in the conserved valley, while richness remained relatively constant in the degraded valley; abundance was much higher in the degraded valley. The cluster analysis showed that the valleys and hillsides are the most similar in relation to species composition and abundance, yet different from the secondary forest with eucalypts and the hilltop.
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One aspect of person-job fit reflects congruence between personal preferences and job design; as congruence increases so should satisfaction. We hypothesized that power distance would moderate whether fit is related to satisfaction with degree of job formalization. We obtained measures of job-formalization, fit and satisfaction, as well as organizational commitment from employees (n = 772) in a multinational firm with subsidiaries in six countries. Confirming previous findings, individuals from low power-distance cultures were most satisfied with increasing fit. However, the extent to which individuals from high power-distance cultures were satisfied did not necessarily depend on increasing fit, but mostly on whether the degree of formalization received was congruent to cultural norms. Irrespective of culture, satisfaction with formalization predicted a broad measure of organizational commitment. Apart from our novel extension of fit theory, we show how moderation can be tested in the context of polynomial response surface regression and how specific hypotheses can be tested regarding different points on the response surface.
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A class of composite estimators of small area quantities that exploit spatial (distancerelated)similarity is derived. It is based on a distribution-free model for the areas, but theestimators are aimed to have optimal design-based properties. Composition is applied alsoto estimate some of the global parameters on which the small area estimators depend.It is shown that the commonly adopted assumption of random effects is not necessaryfor exploiting the similarity of the districts (borrowing strength across the districts). Themethods are applied in the estimation of the mean household sizes and the proportions ofsingle-member households in the counties (comarcas) of Catalonia. The simplest version ofthe estimators is more efficient than the established alternatives, even though the extentof spatial similarity is quite modest.
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This paper examines competition in the standard one-dimensional Downsian model of two-candidate elections, but where one candidate (A) enjoys an advantage over the other candidate (D). Voters' preferences are Euclidean, but any voter will vote for candidate A over candidate D unless D is closer to her ideal point by some fixed distance \delta. The location of the median voter's ideal point is uncertain, and its distribution is commonly known by both candidates. The candidates simultaneously choose locations to maximize the probability of victory. Pure strategy equilibria often fails to exist in this model, except under special conditions about \delta and the distribution of the median ideal point. We solve for the essentially unique symmetric mixed equilibrium, show that candidate A adopts more moderate policies than candidate D, and obtain some comparative statics results about the probability of victory and the expected distance between the two candidates' policies.