912 resultados para Data distribution


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AimTo identify the bioclimatic niche of the endangered Andean cat (Leopardus jacobita), one of the rarest and least known felids in the world, by developing a species distribution model.LocationSouth America, High Andes and Patagonian steppe. Peru, Bolivia, Chile, Argentina.MethodsWe used 108 Andean cat records to build the models, and 27 to test them, applying the Maxent algorithm to sets of uncorrelated bioclimatic variables from global databases, including elevation. We based our biogeographical interpretations on the examination of the predicted geographic range, the modelled response curves and latitudinal variations in climatic variables associated with the locality data.ResultsSimple bioclimatic models for Andean cats were highly predictive with only 3-4 explanatory variables. The climatic niche of the species was defined by extreme diurnal variations in temperature, cold minimum and moderate maximum temperatures, and aridity, characteristic not only of the Andean highlands but also of the Patagonian steppe. Argentina had the highest representation of suitable climates, and Chile the lowest. The most favourable conditions were centrally located and spanned across international boundaries. Discontinuities in suitable climatic conditions coincided with three biogeographical barriers associated with climatic or topographic transitions.Main conclusionsSimple bioclimatic models can produce useful predictions of suitable climatic conditions for rare species, including major biogeographical constraints. In our study case, these constraints are also known to affect the distribution of other Andean species and the genetic structure of Andean cat populations. We recommend surveys of areas with suitable climates and no Andean cat records, including the corridor connecting two core populations. The inclusion of landscape variables at finer scales, crucially the distribution of Andean cat prey, would contribute to refine our predictions for conservation applications.

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To ensure efficient energy supply to the high demanding brain, nutrients are transported into brain cells via specific glucose (GLUT) and monocarboxylate transporters (MCT). Mitochondrial dysfunction and altered glucose metabolism are thought to play an important role in the progression of neurodegenerative diseases, including multiple sclerosis (MS). Here, we investigated the cellular localization of key GLUT and MCT proteins in human brain tissue of non-neurological controls and MS patients. We show that in control brain tissue GLUT and MCT proteins were abundantly expressed in a variety of central nervous system cells, particularly in microglia and endothelial cells. In active MS lesions, GLUTs and MCTs were highly expressed in infiltrating leukocytes and reactive astrocytes. Astrocytes manifest increased MCT1 staining and maintain GLUT expression in inactive lesions, whereas demyelinated axons exhibit significantly reduced GLUT3 and MCT2 immunoreactivity in inactive lesions. Finally, we demonstrated that the co-transcription factor peroxisome proliferator-activated receptor gamma co-activator 1-alpha (PGC-1α), an important protein involved in energy metabolism, is highly expressed in reactive astrocytes in active MS lesions. Overexpression of PGC-1α in astrocyte-like cells resulted in increased production of several GLUT and MCT proteins. In conclusion, we provide for the first time a comprehensive overview of key nutrient transporters in white matter brain samples. Moreover, our data demonstrate an altered expression of these nutrient transporters in MS brain tissue, including a marked reduction of axonal GLUT3 and MCT2 expression in chronic lesions, which may impede efficient nutrient supply to the hypoxic demyelinated axons thereby contributing to the ongoing neurodegeneration in MS. GLIA 2014;62:1125-1141.

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In this paper we propose a subsampling estimator for the distribution ofstatistics diverging at either known rates when the underlying timeseries in strictly stationary abd strong mixing. Based on our results weprovide a detailed discussion how to estimate extreme order statisticswith dependent data and present two applications to assessing financialmarket risk. Our method performs well in estimating Value at Risk andprovides a superior alternative to Hill's estimator in operationalizingSafety First portofolio selection.

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Do the contests with the largest prizes attract the most able contestants? Towhat extent do contestants avoid competition? In this paper, we show, theoreticallyand empirically, that the distribution of abilities plays a crucial role in determiningcontest choice. Sorting exists only when the proportion of high-ability contestantsis sufficiently small. As this proportion increases, contestants shy away from competitionand sorting decreases, such that, reverse sorting becomes a possibility. Wetest our theoretical predictions using a large panel data set containing contest choiceover three decades. We use exogenous variation in the participation of highly-ablecompetitors to provide empirical evidence for the relationship among prizes, competition,and sorting.

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With the quickening pace of crash reporting, the statistical editing of data on a weekly basis, and the ability to provide working databases to users at CTRE/Iowa Traffic Safety Data Service, the University of Iowa, and the Iowa DOT, databases that would be considered incomplete by past standards of static data files are in “public use” even as the dynamic nature of the central DOT database allows changes to be made to both the aggregate of data and to the individual crashes already reported. Moreover, “definitive” analyses of serious crashes will, by their nature, lag seriously behind the preliminary data files. Even after these analyses, the dynamic nature of the mainframe data file means that crash numbers can continue to change long after the incident year. The Iowa DOT, its Office of Driver Services (the “data owner”), and institutional data users/distributors must establish data use, distribution, and labeling protocols to deal with the new, dynamic nature of data. In order to set these protocols, data must be collected concerning the magnitude of difference between database records and crash narratives and diagrams. This study determines the difference between database records and crash narratives for the Iowa Department of Transportation’s Office of Traffic and Safety crash database and the impacts of this difference.

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In the mid-1980s, many European countries introduced fixed-term contracts.Since then their labor markets have become more dynamic. This paper studiesthe implications of such reforms for the duration distribution ofunemployment, with particular emphasis on the changes in the durationdependence. I estimate a parametric duration model using cross-sectionaldata drawn from the Spanish Labor Force Survey from 1980 to 1994 to analyzethe chances of leaving unemployment before and after the introduction offixed-term contracts. I find that duration dependence has increased sincesuch reform. Semi-parametric estimation of the model also shows that forlong spells, the probability of leaving unemployment has decreased sincesuch reform.

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Les décisions de gestion des eaux souterraines doivent souvent être justiffées par des modèles quantitatifs d'aquifères qui tiennent compte de l'hétérogénéité des propriétés hydrauliques. Les aquifères fracturés sont parmi les plus hétérogènes et très difficiles à étudier. Dans ceux-ci, les fractures connectées, d'ouverture millimètrique, peuvent agir comme conducteurs hydrauliques et donc créer des écoulements très localisés. Le manque général d'informations sur la distribution spatiale des fractures limite la possibilité de construire des modèles quantitatifs de flux et de transport. Les données qui conditionnent les modèles sont généralement spatialement limitées, bruitées et elles ne représentent que des mesures indirectes de propriétés physiques. Ces limitations aux données peuvent être en partie surmontées en combinant différents types de données, telles que les données hydrologiques et de radar à pénétration de sol plus commun ément appelé géoradar. L'utilisation du géoradar en forage est un outil prometteur pour identiffer les fractures individuelles jusqu'à quelques dizaines de mètres dans la formation. Dans cette thèse, je développe des approches pour combiner le géoradar avec les données hydrologiques affn d'améliorer la caractérisation des aquifères fracturés. Des investigations hydrologiques intensives ont déjà été réalisées à partir de trois forage adjacents dans un aquifère cristallin en Bretagne (France). Néanmoins, la dimension des fractures et la géométrie 3-D des fractures conductives restaient mal connue. Affn d'améliorer la caractérisation du réseau de fractures je propose dans un premier temps un traitement géoradar avancé qui permet l'imagerie des fractures individuellement. Les résultats montrent que les fractures perméables précédemment identiffées dans les forages peuvent être caractérisées géométriquement loin du forage et que les fractures qui ne croisent pas les forages peuvent aussi être identiffées. Les résultats d'une deuxième étude montrent que les données géoradar peuvent suivre le transport d'un traceur salin. Ainsi, les fractures qui font partie du réseau conductif et connecté qui dominent l'écoulement et le transport local sont identiffées. C'est la première fois que le transport d'un traceur salin a pu être imagé sur une dizaines de mètres dans des fractures individuelles. Une troisième étude conffrme ces résultats par des expériences répétées et des essais de traçage supplémentaires dans différentes parties du réseau local. En outre, la combinaison des données de surveillance hydrologique et géoradar fournit la preuve que les variations temporelles d'amplitude des signaux géoradar peuvent nous informer sur les changements relatifs de concentrations de traceurs dans la formation. Par conséquent, les données géoradar et hydrologiques sont complémentaires. Je propose ensuite une approche d'inversion stochastique pour générer des modèles 3-D de fractures discrètes qui sont conditionnés à toutes les données disponibles en respectant leurs incertitudes. La génération stochastique des modèles conditionnés par géoradar est capable de reproduire les connexions hydrauliques observées et leur contribution aux écoulements. L'ensemble des modèles conditionnés fournit des estimations quantitatives des dimensions et de l'organisation spatiale des fractures hydrauliquement importantes. Cette thèse montre clairement que l'imagerie géoradar est un outil utile pour caractériser les fractures. La combinaison de mesures géoradar avec des données hydrologiques permet de conditionner avec succès le réseau de fractures et de fournir des modèles quantitatifs. Les approches présentées peuvent être appliquées dans d'autres types de formations rocheuses fracturées où la roche est électriquement résistive.

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We propose a new econometric estimation method for analyzing the probabilityof leaving unemployment using uncompleted spells from repeated cross-sectiondata, which can be especially useful when panel data are not available. Theproposed method-of-moments-based estimator has two important features:(1) it estimates the exit probability at the individual level and(2) it does not rely on the stationarity assumption of the inflowcomposition. We illustrate and gauge the performance of the proposedestimator using the Spanish Labor Force Survey data, and analyze the changesin distribution of unemployment between the 1980s and 1990s during a periodof labor market reform. We find that the relative probability of leavingunemployment of the short-term unemployed versus the long-term unemployedbecomes significantly higher in the 1990s.

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This paper aims to study the distribution of natural nests of Xylocopa ordinaria and characterize its nesting habits in the restinga of Grussai/Iquipari (RJ), supporting future studies on the pollinators management in the northern Rio de Janeiro state. The data obtained from Aug/2003 to Dec/2004, in an area of 11.6ha, were related to the nest distribution, substrate identification and dimensions, emergence, sex ratio, nest structure (n= 23 nests) and pollen content analysis of provisioning masses and feces. X. ordinaria nests were abundant and presented a clustered distribution. These bees do not present taxonomical affinity for nesting substrates, but preferences for wood availability and characteristics, being Pera glabrata the main substrate. X. ordinaria is a multivoltine species that tolerates co-specifics in their nests. These bees were generalist on their nectar and pollen consumption, but presented floral constancy while provisioning brood cells. These behaviors, activity along the year, flights throughout the day, and legitimate visits to flowers indicate the importance of X. ordinaria on the pollination of plants in the restinga.

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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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Abstract Accurate characterization of the spatial distribution of hydrological properties in heterogeneous aquifers at a range of scales is a key prerequisite for reliable modeling of subsurface contaminant transport, and is essential for designing effective and cost-efficient groundwater management and remediation strategies. To this end, high-resolution geophysical methods have shown significant potential to bridge a critical gap in subsurface resolution and coverage between traditional hydrological measurement techniques such as borehole log/core analyses and tracer or pumping tests. An important and still largely unresolved issue, however, is how to best quantitatively integrate geophysical data into a characterization study in order to estimate the spatial distribution of one or more pertinent hydrological parameters, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first develop a strategy for the assimilation of several types of hydrogeophysical data having varying degrees of resolution, subsurface coverage, and sensitivity to the hydrologic parameter of interest. In this regard a novel simulated annealing (SA)-based conditional simulation approach was developed and then tested in its ability to generate realizations of porosity given crosshole ground-penetrating radar (GPR) and neutron porosity log data. This was done successfully for both synthetic and field data sets. A subsequent issue that needed to be addressed involved assessing the potential benefits and implications of the resulting porosity realizations in terms of groundwater flow and contaminant transport. This was investigated synthetically assuming first that the relationship between porosity and hydraulic conductivity was well-defined. Then, the relationship was itself investigated in the context of a calibration procedure using hypothetical tracer test data. Essentially, the relationship best predicting the observed tracer test measurements was determined given the geophysically derived porosity structure. Both of these investigations showed that the SA-based approach, in general, allows much more reliable hydrological predictions than other more elementary techniques considered. Further, the developed calibration procedure was seen to be very effective, even at the scale of tomographic resolution, for predictions of transport. This also held true at locations within the aquifer where only geophysical data were available. This is significant because the acquisition of hydrological tracer test measurements is clearly more complicated and expensive than the acquisition of geophysical measurements. Although the above methodologies were tested using porosity logs and GPR data, the findings are expected to remain valid for a large number of pertinent combinations of geophysical and borehole log data of comparable resolution and sensitivity to the hydrological target parameter. Moreover, the obtained results allow us to have confidence for future developments in integration methodologies for geophysical and hydrological data to improve the 3-D estimation of hydrological properties.

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This study aimed at registering and monitoring the presence of Aedes aegypti in the University Hospital Júlio Muller, Cuiabá-MT, as well as investigating the influence of temperature and rainfall on its temporal distribution and egg densities in ovitraps. The study was performed from April/2007 to March/2008, utilizing ovitraps with 10% of hay infusion and a wood paddle as an oviposition substrate. For surveillance, one ovitrap was placed in each of the 12 points distributed throughout the hospital. Ovitraps were collected monthly at the end of a 5-day installation period. After egg counting, wood paddles were immersed in water to allow larval eclosion for species identification through optical microscopy. Egg Density Index (EDI), Positive Ovitraps Index (POI), and Mean Number of Eggs (MNE) were used for data analysis. The presence of A. aegypti in the hospital was registered throughout the study period, except in July. The MNE was proportionally higher in the internal area (n= 8.47 eggs/paddle) when compared to the external area (n= 5.46 eggs/paddle), and was higher in September/October 2007 and January/February 2008. A significant increase in EDI, POI and MNE was registered in periods where the average temperature was higher, and the increase in POI was also concomitant with an increase in rainfall. The continuous presence of A. aegypti in the hospital throughout the study period, points out the need of including this mosquito in the arthropod control list in this environment. This is particularly important, considering that A. aegypti is an important vector of several arboviroses.

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We study the statistical properties of three estimation methods for a model of learning that is often fitted to experimental data: quadratic deviation measures without unobserved heterogeneity, and maximum likelihood withand without unobserved heterogeneity. After discussing identification issues, we show that the estimators are consistent and provide their asymptotic distribution. Using Monte Carlo simulations, we show that ignoring unobserved heterogeneity can lead to seriously biased estimations in samples which have the typical length of actual experiments. Better small sample properties areobtained if unobserved heterogeneity is introduced. That is, rather than estimating the parameters for each individual, the individual parameters are considered random variables, and the distribution of those random variables is estimated.

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We obtained the first data on spatial distribution of a spherical galling insect (Hymenoptera, Eulophidae) at the Caryocar brasiliense Camb. (Caryocaraceae) tree level. This work was developed in two pastures in Montes Claros, Minas Gerais State, Brazil. The areas studied were: pasture 1 (in activity) and pasture 2 (abandoned pasture = savanna in recovery). We evaluated the distribution of spherical galls in: foliage orientation (slope), among leaves (border and interior of the tree crown), among leaflets (right, central, left), distal, median, and proximal as well as border, central area, and adjacent to the mid leaf vein of the leaflet, and difference between areas in 10 infested trees per area. The smaller number of spherical gall/leaflet was observed in pasture 1 than in pasture 2. More spherical galls were found on the northern in pasture 1, but in the pasture 2, the lower spherical galls were observed on the northeast than other slopes. The average number of spherical galls did not differ statistically among the three leaflets of C. brasiliense in pasture 2. However, in pasture 1, we observed highest number of spherical galls in the central leaflet. More spherical galls were found in the border than interior of the tree crown. The average number of spherical galls did not differ statistically among the longitudinal region on leaflet of C. brasiliense. The spherical gall insect preferred to colonize the leaf margin than the central portion or near mid vein on transversal regions on a leaflet.

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Persons with Down syndrome (DS) uniquely have an increased frequency of leukemias but a decreased total frequency of solid tumors. The distribution and frequency of specific types of brain tumors have never been studied in DS. We evaluated the frequency of primary neural cell embryonal tumors and gliomas in a large international data set. The observed number of children with DS having a medulloblastoma, central nervous system primitive neuroectodermal tumor (CNS-PNET) or glial tumor was compared to the expected number. Data were collected from cancer registries or brain tumor registries in 13 countries of Europe, America, Asia and Oceania. The number of DS children with each category of tumor was treated as a Poisson variable with mean equal to 0.000884 times the total number of registrations in that category. Among 8,043 neural cell embryonal tumors (6,882 medulloblastomas and 1,161 CNS-PNETs), only one patient with medulloblastoma had DS, while 7.11 children in total and 6.08 with medulloblastoma were expected to have DS. (p 0.016 and 0.0066 respectively). Among 13,797 children with glioma, 10 had DS, whereas 12.2 were expected. Children with DS appear to be specifically protected against primary neural cell embryonal tumors of the CNS, whereas gliomas occur at the same frequency as in the general population. A similar protection against neuroblastoma, the principal extracranial neural cell embryonal tumor, has been observed in children with DS. Additional genetic material on the supernumerary chromosome 21 may protect against embryonal neural cell tumor development.