927 resultados para distributions to shareholders


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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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Abiotic factors such as climate and soil determine the species fundamental niche, which is further constrained by biotic interactions such as interspecific competition. To parameterize this realized niche, species distribution models (SDMs) most often relate species occurrence data to abiotic variables, but few SDM studies include biotic predictors to help explain species distributions. Therefore, most predictions of species distributions under future climates assume implicitly that biotic interactions remain constant or exert only minor influence on large-scale spatial distributions, which is also largely expected for species with high competitive ability. We examined the extent to which variance explained by SDMs can be attributed to abiotic or biotic predictors and how this depends on species traits. We fit generalized linear models for 11 common tree species in Switzerland using three different sets of predictor variables: biotic, abiotic, and the combination of both sets. We used variance partitioning to estimate the proportion of the variance explained by biotic and abiotic predictors, jointly and independently. Inclusion of biotic predictors improved the SDMs substantially. The joint contribution of biotic and abiotic predictors to explained deviance was relatively small (similar to 9%) compared to the contribution of each predictor set individually (similar to 20% each), indicating that the additional information on the realized niche brought by adding other species as predictors was largely independent of the abiotic (topo-climatic) predictors. The influence of biotic predictors was relatively high for species preferably growing under low disturbance and low abiotic stress, species with long seed dispersal distances, species with high shade tolerance as juveniles and adults, and species that occur frequently and are dominant across the landscape. The influence of biotic variables on SDM performance indicates that community composition and other local biotic factors or abiotic processes not included in the abiotic predictors strongly influence prediction of species distributions. Improved prediction of species' potential distributions in future climates and communities may assist strategies for sustainable forest management.

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We analyze crash data collected by the Iowa Department of Transportation using Bayesian methods. The data set includes monthly crash numbers, estimated monthly traffic volumes, site length and other information collected at 30 paired sites in Iowa over more than 20 years during which an intervention experiment was set up. The intervention consisted in transforming 15 undivided road segments from four-lane to three lanes, while an additional 15 segments, thought to be comparable in terms of traffic safety-related characteristics were not converted. The main objective of this work is to find out whether the intervention reduces the number of crashes and the crash rates at the treated sites. We fitted a hierarchical Poisson regression model with a change-point to the number of monthly crashes per mile at each of the sites. Explanatory variables in the model included estimated monthly traffic volume, time, an indicator for intervention reflecting whether the site was a “treatment” or a “control” site, and various interactions. We accounted for seasonal effects in the number of crashes at a site by including smooth trigonometric functions with three different periods to reflect the four seasons of the year. A change-point at the month and year in which the intervention was completed for treated sites was also included. The number of crashes at a site can be thought to follow a Poisson distribution. To estimate the association between crashes and the explanatory variables, we used a log link function and added a random effect to account for overdispersion and for autocorrelation among observations obtained at the same site. We used proper but non-informative priors for all parameters in the model, and carried out all calculations using Markov chain Monte Carlo methods implemented in WinBUGS. We evaluated the effect of the four to three-lane conversion by comparing the expected number of crashes per year per mile during the years preceding the conversion and following the conversion for treatment and control sites. We estimated this difference using the observed traffic volumes at each site and also on a per 100,000,000 vehicles. We also conducted a prospective analysis to forecast the expected number of crashes per mile at each site in the study one year, three years and five years following the four to three-lane conversion. Posterior predictive distributions of the number of crashes, the crash rate and the percent reduction in crashes per mile were obtained for each site for the months of January and June one, three and five years after completion of the intervention. The model appears to fit the data well. We found that in most sites, the intervention was effective and reduced the number of crashes. Overall, and for the observed traffic volumes, the reduction in the expected number of crashes per year and mile at converted sites was 32.3% (31.4% to 33.5% with 95% probability) while at the control sites, the reduction was estimated to be 7.1% (5.7% to 8.2% with 95% probability). When the reduction in the expected number of crashes per year, mile and 100,000,000 AADT was computed, the estimates were 44.3% (43.9% to 44.6%) and 25.5% (24.6% to 26.0%) for converted and control sites, respectively. In both cases, the difference in the percent reduction in the expected number of crashes during the years following the conversion was significantly larger at converted sites than at control sites, even though the number of crashes appears to decline over time at all sites. Results indicate that the reduction in the expected number of sites per mile has a steeper negative slope at converted than at control sites. Consistent with this, the forecasted reduction in the number of crashes per year and mile during the years after completion of the conversion at converted sites is more pronounced than at control sites. Seasonal effects on the number of crashes have been well-documented. In this dataset, we found that, as expected, the expected number of monthly crashes per mile tends to be higher during winter months than during the rest of the year. Perhaps more interestingly, we found that there is an interaction between the four to three-lane conversion and season; the reduction in the number of crashes appears to be more pronounced during months, when the weather is nice than during other times of the year, even though a reduction was estimated for the entire year. Thus, it appears that the four to three-lane conversion, while effective year-round, is particularly effective in reducing the expected number of crashes in nice weather.

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The Aitchison vector space structure for the simplex is generalized to a Hilbert space structure A2(P) for distributions and likelihoods on arbitrary spaces. Centralnotations of statistics, such as Information or Likelihood, can be identified in the algebraical structure of A2(P) and their corresponding notions in compositional data analysis, such as Aitchison distance or centered log ratio transform.In this way very elaborated aspects of mathematical statistics can be understoodeasily in the light of a simple vector space structure and of compositional data analysis. E.g. combination of statistical information such as Bayesian updating,combination of likelihood and robust M-estimation functions are simple additions/perturbations in A2(Pprior). Weighting observations corresponds to a weightedaddition of the corresponding evidence.Likelihood based statistics for general exponential families turns out to have aparticularly easy interpretation in terms of A2(P). Regular exponential families formfinite dimensional linear subspaces of A2(P) and they correspond to finite dimensionalsubspaces formed by their posterior in the dual information space A2(Pprior).The Aitchison norm can identified with mean Fisher information. The closing constant itself is identified with a generalization of the cummulant function and shown to be Kullback Leiblers directed information. Fisher information is the local geometry of the manifold induced by the A2(P) derivative of the Kullback Leibler information and the space A2(P) can therefore be seen as the tangential geometry of statistical inference at the distribution P.The discussion of A2(P) valued random variables, such as estimation functionsor likelihoods, give a further interpretation of Fisher information as the expected squared norm of evidence and a scale free understanding of unbiased reasoning

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Micas are commonly used in Ar-40/Ar-39 thermochronological studies of variably deformed rocks yet the physical basis by which deformation may affect radiogenic argon retention in mica is poorly constrained. This study examines the relationship between deformation and deformation-induced microstructures on radiogenic argon retention in muscovite, A combination of furnace step-heating and high-spatial resolution in situ UV-laser ablation Ar-40/Ar-39 analyses are reported for deformed muscovites sampled from a granitic pegmatite vein within the Siviez-Mischabel Nappe, western Swiss Alps (Penninic domain, Brianconnais unit). The pegmatite forms part of the Variscan (similar to 350 Ma) Alpine basement and exhibits a prominent Alpine S-C fabric including numerous mica `fish' that developed under greenschist facies metamorphic conditions, during the dominant Tertiary Alpine tectonic phase of nappe emplacement. Furnace step-heating of milligram quantities of separated muscovite grains yields an Ar-40/Ar-39 age spectrum with two distinct staircase segments but without any statistical plateau, consistent with a previous study from the same area. A single (3 X 5 mm) muscovite porphyroclast (fish) was investigated by in situ UV-laser ablation. A histogram plot of 170 individual Ar-40/Ar-39 UV-laser ablation ages exhibit a range from 115 to 387 Ma with modes at approximately 340 and 260 Ma. A variogram statistical treatment of the (40)Ad/Ar-39 results reveals ages correlated with two directions; a highly correlated direction at 310 degrees and a lesser correlation at 0 degrees relative to the sense of shearing. Using the highly correlated direction a statistically generated (Kriging method) age contour map of the Ar-40/Ar-39 data reveals a series of elongated contours subparallel to the C-surfaces which where formed during Tertiary nappe emplacement. Similar data distributions and slightly younger apparent ages are recognized in a smaller mica fish. The observed intragrain age variations are interpreted to reflect the partial loss of radiogenic argon during Alpine (similar to 35 Ma) greenschist facies metamorphism. One-dirnensional diffusion modelling results are consistent with the idea that the zones of youngest apparent age represent incipient shear band development within the mica porphyroclasts, thus providing a network of fast diffusion pathways. During Alpine greenschist facies metamorphism the incipient shear bands enhanced the intragrain loss of radiogenic argon. The structurally controlled intragrain age variations observed in this investigation imply that deformation has a direct control on the effective length scale for argon diffusion, which is consistent with the heterogeneous nature of deformation. (C) 2001 Elsevier Science B.V. All rights reserved.

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BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships. BIOMOD includes the ability to model species distributions with several techniques, test models with a wide range of approaches, project species distributions into different environmental conditions (e.g. climate or land use change scenarios) and dispersal functions. It allows assessing species temporal turnover, plot species response curves, and test the strength of species interactions with predictor variables. BIOMOD is implemented in R and is a freeware, open source, package

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Addendum to Annual Report of the Iowa Department of Revenue FY2007. Comparison to prior years. Local option tax distributions.

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In this paper we argue that corporate social responsibility (CSR) to various stakeholders(customers, shareholders, employees, suppliers, and community) has a positive effect on globalbrand equity (BE). In addition, policies aimed at satisfying community interests help reinforcecredibility to social responsible polices with other stakeholders. We test these theoreticalcontentions using panel data comprised of 57 global brands originating from 10 countries (USA,Japan, South Korea, France, UK, Italy, Germany, Finland, Switzerland and the Netherlands) forthe period 2002 to 2008. Our findings show that CSR to each of the stakeholder groups has apositive impact on global BE. In addition, global brands that follow local social responsibilitypolicies over communities obtain strong positive benefits in terms of the generation of BE, as itenhances the positive effects of CSR to other stakeholders, particularly to customers. Therefore,for managers of global brands it is particularly productive for generating brand value to combineglobal strategies with the satisfaction of the interests of local communities.

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We argue that when stakeholder protection is left to the voluntaryinitiative of managers, concessions to social activists and pressuregroups can turn into a self-entrenchment strategy for incumbent CEOs.Stakeholders other than shareholders thus benefit from corporategovernance rules putting managers under a tough replacement threat. Weshow that a minimal amount of formal stakeholder protection, or the introduction of explicit covenants protecting stakeholder rights in thefirm charter, may deprive CEOs of the alliance with powerful socialactivists, thus increasing managerial turnover and shareholder value.These results rationalize a recent trend whereby well-known socialactivists like Friends of the Earth and active shareholders likeCalPERS are showing a growing support for each other s agendas.

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A major challenge in community ecology is a thorough understanding of the processes that govern the assembly and composition of communities in time and space. The growing threat of climate change to the vascular plant biodiversity of fragile ecosystems such as mountains has made it equally imperative to develop comprehensive methodologies to provide insights into how communities are assembled. In this perspective, the primary objective of this PhD thesis is to contribute to the theoretical and methodological development of community ecology, by proposing new solutions to better detect the ecological and evolutionary processes that govern community assembly. As phylogenetic trees provide by far, the most advanced tools to integrate the spatial, ecological and evolutionary dynamics of plant communities, they represent the cornerstone on which this work was based. In this thesis, I proposed new solutions to: (i) reveal trends in community assembly on phylogenies, depicted by the transition of signals at the nodes of the different species and lineages responsible for community assembly, (ii) contribute to evidence the importance of evolutionarily labile traits in the distribution of mountain plant species. More precisely, I demonstrated that phylogenetic and functional compositional turnover in plant communities was driven by climate and human land use gradients mostly influenced by evolutionarily labile traits, (iii) predict and spatially project the phylogenetic structure of communities using species distribution models, to identify the potential distribution of phylogenetic diversity, as well as areas of high evolutionary potential along elevation. The altitudinal setting of the Diablerets mountains (Switzerland) provided an appropriate model for this study. The elevation gradient served as a compression of large latitudinal variations similar to a collection of islands within a single area, and allowed investigations on a large number of plant communities. Overall, this thesis highlights that stochastic and deterministic environmental filtering processes mainly influence the phylogenetic structure of plant communities in mountainous areas. Negative density-dependent processes implied through patterns of phylogenetic overdispersion were only detected at the local scale, whereas environmental filtering implied through phylogenetic clustering was observed at both the regional and local scale. Finally, the integration of indices of phylogenetic community ecology with species distribution models revealed the prospects of providing novel and insightful explanations on the potential distribution of phylogenetic biodiversity in high mountain areas. These results generally demonstrate the usefulness of phylogenies in inferring assembly processes, and are worth considering in the theoretical and methodological development of tools to better understand phylogenetic community structure.

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Intonation is a fundamental music concept that has a special relevance in Indian art music. It is characteristic of the rāga and intrinsic to the musical expression of the performer. Describing intonation is of importance to several information retrieval tasks like the development of rāga and artist similarity measures. In our previous work, we proposed a compact representation of intonation based on the parametrization of the pitch histogram of a performance and demonstrated the usefulness of this representation through an explorative rāga recognition task in which we classified 42 vocal performances belonging to 3 rāgas using parameters of a single svara. In this paper, we extend this representation to employ context-based svara distributions, which are obtained with a different approach to find the pitches belonging to each svara. We quantitatively compare this method to our previous one, discuss the advantages, and the necessary melodic analysis to be carried out in future.

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OBJECTIVE: As part of the WHO ICD-11 development initiative, the Topic Advisory Group on Quality and Safety explores meta-features of morbidity data sets, such as the optimal number of secondary diagnosis fields. DESIGN: The Health Care Quality Indicators Project of the Organization for Economic Co-Operation and Development collected Patient Safety Indicator (PSI) information from administrative hospital data of 19-20 countries in 2009 and 2011. We investigated whether three countries that expanded their data systems to include more secondary diagnosis fields showed increased PSI rates compared with six countries that did not. Furthermore, administrative hospital data from six of these countries and two American states, California (2011) and Florida (2010), were analysed for distributions of coded patient safety events across diagnosis fields. RESULTS: Among the participating countries, increasing the number of diagnosis fields was not associated with any overall increase in PSI rates. However, high proportions of PSI-related diagnoses appeared beyond the sixth secondary diagnosis field. The distribution of three PSI-related ICD codes was similar in California and Florida: 89-90% of central venous catheter infections and 97-99% of retained foreign bodies and accidental punctures or lacerations were captured within 15 secondary diagnosis fields. CONCLUSIONS: Six to nine secondary diagnosis fields are inadequate for comparing complication rates using hospital administrative data; at least 15 (and perhaps more with ICD-11) are recommended to fully characterize clinical outcomes. Increasing the number of fields should improve the international and intra-national comparability of data for epidemiologic and health services research, utilization analyses and quality of care assessment.

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Understanding factors that shape ranges of species is central in evolutionary biology. Species distribution models have become important tools to test biogeographical, ecological and evolutionary hypotheses. Moreover, from an ecological and evolutionary perspective, these models help to elucidate the spatial strategies of species at a regional scale. We modelled species distributions of two phylogenetically, geographically and ecologically close Tupinambis species (Teiidae) that occupy the southernmost area of the genus distribution in South America. We hypothesized that similarities between these species might have induced spatial strategies at the species level, such as niche differentiation and divergence of distribution patterns at a regional scale. Using logistic regression and MaxEnt we obtained species distribution models that revealed interspecific differences in habitat requirements, such as environmental temperature, precipitation and altitude. Moreover, the models obtained suggest that although the ecological niches of Tupinambis merianae and T. rufescens are different, these species might co-occur in a large contact zone. We propose that niche plasticity could be the mechanism enabling their co-occurrence. Therefore, the approach used here allowed us to understand the spatial strategies of two Tupinambis lizards at a regional scale.

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We review methods to estimate the average crystal (grain) size and the crystal (grain) size distribution in solid rocks. Average grain sizes often provide the base for stress estimates or rheological calculations requiring the quantification of grain sizes in a rock's microstructure. The primary data for grain size data are either 1D (i.e. line intercept methods), 2D (area analysis) or 3D (e.g., computed tomography, serial sectioning). These data have been used for different data treatments over the years, whereas several studies assume a certain probability function (e.g., logarithm, square root) to calculate statistical parameters as the mean, median, mode or the skewness of a crystal size distribution. The finally calculated average grain sizes have to be compatible between the different grain size estimation approaches in order to be properly applied, for example, in paleo-piezometers or grain size sensitive flow laws. Such compatibility is tested for different data treatments using one- and two-dimensional measurements. We propose an empirical conversion matrix for different datasets. These conversion factors provide the option to make different datasets compatible with each other, although the primary calculations were obtained in different ways. In order to present an average grain size, we propose to use the area-weighted and volume-weighted mean in the case of unimodal grain size distributions, respectively, for 2D and 3D measurements. The shape of the crystal size distribution is important for studies of nucleation and growth of minerals. The shape of the crystal size distribution of garnet populations is compared between different 2D and 3D measurements, which are serial sectioning and computed tomography. The comparison of different direct measured 3D data; stereological data and direct presented 20 data show the problems of the quality of the smallest grain sizes and the overestimation of small grain sizes in stereological tools, depending on the type of CSD. (C) 2011 Published by Elsevier Ltd.

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The speed and width of front solutions to reaction-dispersal models are analyzed both analytically and numerically. We perform our analysis for Laplace and Gaussian distribution kernels, both for delayed and nondelayed models. The results are discussed in terms of the characteristic parameters of the models