958 resultados para multivariate binary data
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Eight depositional sequences (DS) delimited by regional disconformities had been recognized in the Miocene of Lisbon and Setúbal Peninsula areas. In the case of the western coast of the Setúbal Peninsula, outcrops consisting of Lower Burdigalian to Lower Tortonian sediments were studied. The stratigraphic zonography and the environmental considerations are mainly supported on data concerning to foraminifera, ostracoda, vertebrates and palynomorphs. The first mineralogical and geochemical data determined for Foz da Fonte, Penedo Sul and Penedo Norte sedimentary sequences are presented. These analytical data mainly correspond to the sediments' fine fractions. Mineralogical data are based on X-ray diffraction (XRD), carried out on both the less than 38 nm and 2 nm fractions. Qualitative and semi-quantitative determinations of clay and non-clay minerals were obtained for both fractions. The clay minerals assemblages complete the lithostratigraphic and paleoenvironmental data obtained by stratigraphic and palaeontological studies. Some palaeomagnetic and isotopic data are discussed and correlated with the mineralogical data. Multivariate data analysis (Principal Components Analysis) of the mineralogical data was carried out using both R-mode and Q-mode factor analysis.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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RESUMO - O consumo de tabaco foi responsável por 100 milhões de mortes no século XX. Apesar dos grandes avanços alcançados no controlo deste problema a nível mundial, sob os auspícios da OMS, no contexto da Convenção-Quadro para o Controlo do Tabaco da OMS, se não forem adoptadas medidas consistentes e efectivas de saúde pública, a morbi-mortalidade que lhe está associada continuará a aumentar durante o presente século. A promoção da cessação tabágica constitui a estratégia populacional que permitirá obter ganhos em saúde a mais curto prazo. Embora a larga maioria dos fumadores faça, ao longo da vida, várias tentativas para parar de fumar sem apoio, apenas uma pequena minoria consegue manter-se abstinente a longo prazo. Os médicos de Medicina Geral e Familiar são, de entre todos os profissionais de saúde, os que podem intervir de modo mais consistente e efectivo neste âmbito e que melhores resultados obtêm na cessação tabágica dos pacientes fumadores, dado o vínculo terapêutico e a interacção frequente e continuada que com eles estabelecem ao longo do seu ciclo de vida. O aconselhamento breve, tendo por base a adopção de um estilo de comunicação motivacional centrado no paciente, adaptado aos estádios de mudança comportamental, tem-se revelado efectivo no apoio à mudança de comportamentos relacionados com a saúde e à resolução da ambivalência que caracteriza este processo. A revisão de literatura evidenciou o facto de os médicos nem sempre intervirem nas áreas preventivas e de promoção da saúde, em particular na área da cessação tabágica, com o investimento e a continuidade desejáveis. Por outro lado, muitos pacientes fumadores referem nunca ter sido aconselhados pelo seu médico a deixar de fumar.. Não são conhecidos estudos de âmbito nacional que permitam conhecer esta realidade, bem como os factores associados às melhores práticas de intervenção ou as barreiras sentidas pelos médicos de MGF à actuação nesta área. O presente trabalho teve como objectivos: (i) avaliar a hipótese de que os médicos que disseram adoptar o método clínico centrado no paciente teriam atitudes mais favoráveis relativamente à cessação tabágica e uma maior probabilidade de aconselhar os seus pacientes a parar de fumar; (ii) estudar a relação entre as atitudes, a percepção de auto-eficácia, a expectativa de efectividade e as práticas de aconselhamento sobre cessação tabágica, auto-referidas pelos médicos; (iii) Identificar as variáveis preditivas da adopção de intervenções breves de aconselhamento adaptadas ao estádio de mudança comportamental dos pacientes fumadores; (iv) identificar as barreiras e os incentivos à adopção de boas práticas de aconselhamento nesta área. A população de estudo foi constituída pelo total de médicos de medicina geral e familiar inscritos na Associação Portuguesa de Médicos de Clínica Geral, residentes em Portugal. Para recolha de informação, foi utilizado um questionário de resposta anónima, de autopreenchimento, aplicado por via postal a 2942 médicos, em duas séries de envio. O questionário integrou perguntas fechadas, semifechadas, escalas de tipo Likert e escalas de tipo visual analógico. Para avaliação da adopção do método clínico centrado no paciente, foi usada a Patient Practitioner Orientation Scale (PPOS). O tratamento estatístico dos dados foi efectuado com o Programa PASW Statistics (ex-SPSS), versão 18. Foram utilizados: o índice de α de Cronbach, diversos testes não paramétricos e a análise de regressão logística binária. Foi obtida uma taxa de resposta de 22,4%. Foram analisadas 639 respostas (67,4% de mulheres e 32,6% de homens). Referiram ser fumadores 23% dos homens e 14% das mulheres. Foi identificada uma grande carência formativa em cessação tabágica, tendo apenas 4% dos médicos afirmado não necessitar de formação nesta área. Responderam necessitar de formação em entrevista motivacional 66%, em prevenção da recaída 59%, de treino numa consulta de apoio intensivo 55%, em intervenção breve 54% e em terapêutica farmacológica 55%. Cerca de 92% dos respondentes consideraram que o aconselhamento para a cessação tabágica é uma tarefa que faz parte das suas atribuições, mas apenas 76% concordaram totalmente com a realização de uma abordagem oportunística deste assunto em todos os contactos com os seus pacientes. Como prática mais frequente, perante um paciente em preparação para parar, 85% dos médicos disseram tomar a iniciativa de aconselhar, 79% avaliar a motivação, 67% avaliar o grau de dependência, 60% marcar o “dia D” e 50% propor terapêutica farmacológica. Apenas 21% assumiram realizar com frequência uma intervenção breve com pacientes em preparação (5 Ás); 13% uma intervenção motivacional com pacientes não motivados para mudar (5 Rs) e 20% uma intervenção segundo os princípios da entrevista motivacional, relativamente a pacientes ambivalentes em relação à mudança. A análise multivariada de regressão logística permitiu concluir que as variáveis com maior influência na decisão de aconselhar os pacientes sobre cessação tabágica foram a percepção de auto-eficácia, o nível de atitudes negativas, a adopção habitual do Programa-tipo de cessação tabágica da DGS, a posse de formação específica nesta área e a não identificação de barreiras ao aconselhamento, em particular organizacionais ou ligadas ao processo de comunicação na consulta. Embora se tenha confirmado a existência de associação entre a adopção do método clínico centrado no paciente e as atitudes face à cessação tabágica, não foi possível confirmar plenamente a associação entre a adopção deste método e as práticas autoreferidas de aconselhamento. Os médicos que manifestaram um nível baixo ou moderado de atitudes negativas, uma percepção elevada de auto-eficácia, que nunca fumaram, que referiram adoptar o Programa-tipo de cessação tabágica e que não identificaram barreiras organizacionais apresentaram uma maior probabilidade de realizar uma intervenção breve (“5 Ás”) de aconselhamento de pacientes fumadores em preparação para parar de fumar. Nunca ter fumado apresentou-se associado a uma probabilidade de realizar uma intervenção breve (“5 Ás”) com frequência, superior à verificada entre os médicos que referiram ser fumadores (Odds-ratio ajustado = 2,6; IC a 95%: 1,1; 5,7). Os médicos com o nível de auto-eficácia no aconselhamento mais elevado apresentaram uma probabilidade superior à encontrada entre os médicos com o menor nível de auto-eficácia de realizar com frequência uma intervenção breve de aconselhamento, integrando as cinco vertentes dos “5 Ás” (Odds ratio ajustado = 2,6; IC a 95%: 1,3; 5,3); de realizar uma intervenção motivacional breve com fumadores renitentes a parar de fumar (Odds ratio ajustado = 3,1; IC a 95%: 1,4; 6,5) ou de realizar com frequência uma intervenção motivacional com pacientes em estádio de ambivalência (Odds ratio = 8,8; IC a 95%: 3,8; 19,9). A falta de tempo, a falta de formação específica e a falta de equipa de apoio foram as barreiras ao aconselhamento mais citadas. Como factores facilitadores de um maior investimento nesta área, cerca de 60% dos médicos referiram a realização de um estágio prático de formação; 57% a possibilidade de dispor do apoio de outros profissionais; cerca de metade a melhoria da sua formação teórica. Cerca de 25% dos médicos investiria mais em cessação tabágica se dispusesse de um incentivo financeiro e 20% se os pacientes demonstrassem maior interesse em discutir o assunto ou existisse uma maior valorização desta área por parte dos colegas e dos órgãos de gestão. As limitações de representatividade da amostra, decorrentes da taxa de resposta obtida, impõem reservas à possibilidade de extrapolação destes resultados para a população de estudo, sendo de admitir que os respondentes possam corresponder aos médicos mais interessados por este tema e que optam por não fumar. Outra importante limitação advém do facto de não ter sido estudada a vertente relativa aos pacientes, no que se refere às suas atitudes, percepções e expectativas quanto à actuação do médico neste campo. Pesem embora estas limitações, os resultados obtidos revelaram uma grande perda de oportunidades de prevenção da doença e de promoção da saúde. Parece ter ficado demonstrada a importante influência que as atitudes, em especial as negativas, e as percepções, em particular a percepção de auto-eficácia, podem exercer sobre as práticas de aconselhamento auto-referidas. Todavia, será necessário aprofundar os resultados agora encontrados com estudos de natureza qualitativa, que permitam compreender melhor, por um lado, as percepções, expectativas e necessidades dos pacientes, por outro, as estratégias de comunicação que deverão ser adoptadas pelo médico, atendendo à complexidade do problema e ao tempo disponível na consulta, tendo em vista aumentar a literacia dos pacientes para uma melhor autogestão da sua saúde. Parece ter ficado igualmente patente a grande carência formativa neste domínio. A adopção do modelo biomédico como paradigma da formação médica pré e pós-graduada, proposto, há precisamente cem anos, por Flexner, tem contribuído para a desvalorização das componentes psicoemocionais e sociais dos fenómenos de saúde e de doença, assim como para criar clivagens entre cuidados curativos e preventivos e entre medicina geral e familiar e saúde pública. Porém, o actual padrão de saúde/doença próprio das sociedades desenvolvidas, caracterizado por “pandemias” de doenças crónicas e incapacitantes, determinadas por factores de natureza sociocultural e comportamental, irá obrigar certamente à revisão daquele paradigma e à necessidade de se (re)adoptarem os grandes princípios Hipocráticos de compreensão dos processos de saúde/doença e do papel da medicina.
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RESUMO - Introdução: A saúde oral é uma componente essencial na saúde geral e no bem-estar dos indivíduos. Sabe-se que os problemas de saúde oral afectam predominantemente os elementos de níveis socioeconómicos mais baixos, evidenciando a influência dos determinantes sociais da saúde na saúde oral das populações. Os objectivos deste estudo são caracterizar os comportamentos de rotinas diárias de higiene oral, frequências de idas a consultas de saúde oral, auto-avaliação do estado de saúde oral e percepção de dor na cavidade oral em crianças de 12 anos em Portugal e analisar a associação entre estes e os factores sociodemográficos. Métodos: Foi realizado um estudo observacional, transversal e analítico, abrangendo 1309 jovens e baseado em informação recolhida no III Estudo Nacional de Prevalência de Doenças Orais (ENPDO). Para além das estatísticas descritivas usuais, as estatísticas inferenciais basearam-se predominantemente em modelos de regressão logística binária. Resultados: Dos participantes, 70.6% (n=924) escova “duas ou mais vezes por dia” com associação com todas as variáveis sociodemográficas. Na análise multivariada, o género masculino (OR=2.088; IC95%: 1.574-2.770, em relação ao género feminino), a área de residência predominantemente rural ou mediamente urbana (OR= 1.800; IC95%: 2.587; OR=1.516; IC95%: 1.093-2.103, em relação a zonas predominantemente urbanas), a escolaridade da mãe ser o ensino básico (OR= 2.112; IC95%: 1.408-3.168, em relação ao ensino superior) e a actividade laboral do pai ser desempregado (OR= 1.938; IC95%: 1.280-2.934, em relação a ser trabalhador) foram as variáveis com mais impacto para a adopção de comportamentos de escovagem potencialmente inadequados (p<0.05). A maioria dos inquiridos (94.2%; n=1247) já tinham ido a uma consulta de saúde oral e 74.5% (n=860) nos últimos 12 meses, 95.5% (n=1250) encontram-se satisfeitos com a saúde oral e 44.5% (n=578) afirma ter tido algum tipo de dor na cavidade oral nos últimos 12 meses. Conclusão: Os resultados obtidos estão de acordo com a literatura em termos de factores de associação. Desta forma, a saúde oral nos jovens de 12 anos em Portugal, nos diversos contextos aqui analisados, pode ser considerada como satisfatória. A única excepção relevante é a componente da dor, com valores alarmantes embora de natureza mais subjectiva. A influência dos factores sociodemográficos sugere que futuras abordagens para a promoção da saúde oral tenham em conta os determinantes de saúde no delineamento de estratégias quer a nível individual quer a nível comunitário.
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Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.
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Background: Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective: To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods: The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results: The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion: The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.
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This paper proposes a contemporaneous-threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex ante probabilities that latent regime-specific variables exceed certain threshold values. A key feature of the model is that the transition function depends on all the parameters of the model as well as on the data. Since the mixing weights are also a function of the regime-specific innovation covariance matrix, the model can account for contemporaneous regime-specific co-movements of the variables. The stability and distributional properties of the proposed model are discussed, as well as issues of estimation, testing and forecasting. The practical usefulness of the C-MSTAR model is illustrated by examining the relationship between US stock prices and interest rates.
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SUMMARYSpecies distribution models (SDMs) represent nowadays an essential tool in the research fields of ecology and conservation biology. By combining observations of species occurrence or abundance with information on the environmental characteristic of the observation sites, they can provide information on the ecology of species, predict their distributions across the landscape or extrapolate them to other spatial or time frames. The advent of SDMs, supported by geographic information systems (GIS), new developments in statistical models and constantly increasing computational capacities, has revolutionized the way ecologists can comprehend species distributions in their environment. SDMs have brought the tool that allows describing species realized niches across a multivariate environmental space and predict their spatial distribution. Predictions, in the form of probabilistic maps showing the potential distribution of the species, are an irreplaceable mean to inform every single unit of a territory about its biodiversity potential. SDMs and the corresponding spatial predictions can be used to plan conservation actions for particular species, to design field surveys, to assess the risks related to the spread of invasive species, to select reserve locations and design reserve networks, and ultimately, to forecast distributional changes according to scenarios of climate and/or land use change.By assessing the effect of several factors on model performance and on the accuracy of spatial predictions, this thesis aims at improving techniques and data available for distribution modelling and at providing the best possible information to conservation managers to support their decisions and action plans for the conservation of biodiversity in Switzerland and beyond. Several monitoring programs have been put in place from the national to the global scale, and different sources of data now exist and start to be available to researchers who want to model species distribution. However, because of the lack of means, data are often not gathered at an appropriate resolution, are sampled only over limited areas, are not spatially explicit or do not provide a sound biological information. A typical example of this is data on 'habitat' (sensu biota). Even though this is essential information for an effective conservation planning, it often has to be approximated from land use, the closest available information. Moreover, data are often not sampled according to an established sampling design, which can lead to biased samples and consequently to spurious modelling results. Understanding the sources of variability linked to the different phases of the modelling process and their importance is crucial in order to evaluate the final distribution maps that are to be used for conservation purposes.The research presented in this thesis was essentially conducted within the framework of the Landspot Project, a project supported by the Swiss National Science Foundation. The main goal of the project was to assess the possible contribution of pre-modelled 'habitat' units to model the distribution of animal species, in particular butterfly species, across Switzerland. While pursuing this goal, different aspects of data quality, sampling design and modelling process were addressed and improved, and implications for conservation discussed. The main 'habitat' units considered in this thesis are grassland and forest communities of natural and anthropogenic origin as defined in the typology of habitats for Switzerland. These communities are mainly defined at the phytosociological level of the alliance. For the time being, no comprehensive map of such communities is available at the national scale and at fine resolution. As a first step, it was therefore necessary to create distribution models and maps for these communities across Switzerland and thus to gather and collect the necessary data. In order to reach this first objective, several new developments were necessary such as the definition of expert models, the classification of the Swiss territory in environmental domains, the design of an environmentally stratified sampling of the target vegetation units across Switzerland, the development of a database integrating a decision-support system assisting in the classification of the relevés, and the downscaling of the land use/cover data from 100 m to 25 m resolution.The main contributions of this thesis to the discipline of species distribution modelling (SDM) are assembled in four main scientific papers. In the first, published in Journal of Riogeography different issues related to the modelling process itself are investigated. First is assessed the effect of five different stepwise selection methods on model performance, stability and parsimony, using data of the forest inventory of State of Vaud. In the same paper are also assessed: the effect of weighting absences to ensure a prevalence of 0.5 prior to model calibration; the effect of limiting absences beyond the environmental envelope defined by presences; four different methods for incorporating spatial autocorrelation; and finally, the effect of integrating predictor interactions. Results allowed to specifically enhance the GRASP tool (Generalized Regression Analysis and Spatial Predictions) that now incorporates new selection methods and the possibility of dealing with interactions among predictors as well as spatial autocorrelation. The contribution of different sources of remotely sensed information to species distribution models was also assessed. The second paper (to be submitted) explores the combined effects of sample size and data post-stratification on the accuracy of models using data on grassland distribution across Switzerland collected within the framework of the Landspot project and supplemented with other important vegetation databases. For the stratification of the data, different spatial frameworks were compared. In particular, environmental stratification by Swiss Environmental Domains was compared to geographical stratification either by biogeographic regions or political states (cantons). The third paper (to be submitted) assesses the contribution of pre- modelled vegetation communities to the modelling of fauna. It is a two-steps approach that combines the disciplines of community ecology and spatial ecology and integrates their corresponding concepts of habitat. First are modelled vegetation communities per se and then these 'habitat' units are used in order to model animal species habitat. A case study is presented with grassland communities and butterfly species. Different ways of integrating vegetation information in the models of butterfly distribution were also evaluated. Finally, a glimpse to climate change is given in the fourth paper, recently published in Ecological Modelling. This paper proposes a conceptual framework for analysing range shifts, namely a catalogue of the possible patterns of change in the distribution of a species along elevational or other environmental gradients and an improved quantitative methodology to identify and objectively describe these patterns. The methodology was developed using data from the Swiss national common breeding bird survey and the article presents results concerning the observed shifts in the elevational distribution of breeding birds in Switzerland.The overall objective of this thesis is to improve species distribution models as potential inputs for different conservation tools (e.g. red lists, ecological networks, risk assessment of the spread of invasive species, vulnerability assessment in the context of climate change). While no conservation issues or tools are directly tested in this thesis, the importance of the proposed improvements made in species distribution modelling is discussed in the context of the selection of reserve networks.RESUMELes modèles de distribution d'espèces (SDMs) représentent aujourd'hui un outil essentiel dans les domaines de recherche de l'écologie et de la biologie de la conservation. En combinant les observations de la présence des espèces ou de leur abondance avec des informations sur les caractéristiques environnementales des sites d'observation, ces modèles peuvent fournir des informations sur l'écologie des espèces, prédire leur distribution à travers le paysage ou l'extrapoler dans l'espace et le temps. Le déploiement des SDMs, soutenu par les systèmes d'information géographique (SIG), les nouveaux développements dans les modèles statistiques, ainsi que la constante augmentation des capacités de calcul, a révolutionné la façon dont les écologistes peuvent comprendre la distribution des espèces dans leur environnement. Les SDMs ont apporté l'outil qui permet de décrire la niche réalisée des espèces dans un espace environnemental multivarié et prédire leur distribution spatiale. Les prédictions, sous forme de carte probabilistes montrant la distribution potentielle de l'espèce, sont un moyen irremplaçable d'informer chaque unité du territoire de sa biodiversité potentielle. Les SDMs et les prédictions spatiales correspondantes peuvent être utilisés pour planifier des mesures de conservation pour des espèces particulières, pour concevoir des plans d'échantillonnage, pour évaluer les risques liés à la propagation d'espèces envahissantes, pour choisir l'emplacement de réserves et les mettre en réseau, et finalement, pour prévoir les changements de répartition en fonction de scénarios de changement climatique et/ou d'utilisation du sol. En évaluant l'effet de plusieurs facteurs sur la performance des modèles et sur la précision des prédictions spatiales, cette thèse vise à améliorer les techniques et les données disponibles pour la modélisation de la distribution des espèces et à fournir la meilleure information possible aux gestionnaires pour appuyer leurs décisions et leurs plans d'action pour la conservation de la biodiversité en Suisse et au-delà. Plusieurs programmes de surveillance ont été mis en place de l'échelle nationale à l'échelle globale, et différentes sources de données sont désormais disponibles pour les chercheurs qui veulent modéliser la distribution des espèces. Toutefois, en raison du manque de moyens, les données sont souvent collectées à une résolution inappropriée, sont échantillonnées sur des zones limitées, ne sont pas spatialement explicites ou ne fournissent pas une information écologique suffisante. Un exemple typique est fourni par les données sur 'l'habitat' (sensu biota). Même s'il s'agit d'une information essentielle pour des mesures de conservation efficaces, elle est souvent approximée par l'utilisation du sol, l'information qui s'en approche le plus. En outre, les données ne sont souvent pas échantillonnées selon un plan d'échantillonnage établi, ce qui biaise les échantillons et par conséquent les résultats de la modélisation. Comprendre les sources de variabilité liées aux différentes phases du processus de modélisation s'avère crucial afin d'évaluer l'utilisation des cartes de distribution prédites à des fins de conservation.La recherche présentée dans cette thèse a été essentiellement menée dans le cadre du projet Landspot, un projet soutenu par le Fond National Suisse pour la Recherche. L'objectif principal de ce projet était d'évaluer la contribution d'unités 'd'habitat' pré-modélisées pour modéliser la répartition des espèces animales, notamment de papillons, à travers la Suisse. Tout en poursuivant cet objectif, différents aspects touchant à la qualité des données, au plan d'échantillonnage et au processus de modélisation sont abordés et améliorés, et leurs implications pour la conservation des espèces discutées. Les principaux 'habitats' considérés dans cette thèse sont des communautés de prairie et de forêt d'origine naturelle et anthropique telles que définies dans la typologie des habitats de Suisse. Ces communautés sont principalement définies au niveau phytosociologique de l'alliance. Pour l'instant aucune carte de la distribution de ces communautés n'est disponible à l'échelle nationale et à résolution fine. Dans un premier temps, il a donc été nécessaire de créer des modèles de distribution de ces communautés à travers la Suisse et par conséquent de recueillir les données nécessaires. Afin d'atteindre ce premier objectif, plusieurs nouveaux développements ont été nécessaires, tels que la définition de modèles experts, la classification du territoire suisse en domaines environnementaux, la conception d'un échantillonnage environnementalement stratifié des unités de végétation cibles dans toute la Suisse, la création d'une base de données intégrant un système d'aide à la décision pour la classification des relevés, et le « downscaling » des données de couverture du sol de 100 m à 25 m de résolution. Les principales contributions de cette thèse à la discipline de la modélisation de la distribution d'espèces (SDM) sont rassemblées dans quatre articles scientifiques. Dans le premier article, publié dans le Journal of Biogeography, différentes questions liées au processus de modélisation sont étudiées en utilisant les données de l'inventaire forestier de l'Etat de Vaud. Tout d'abord sont évalués les effets de cinq méthodes de sélection pas-à-pas sur la performance, la stabilité et la parcimonie des modèles. Dans le même article sont également évalués: l'effet de la pondération des absences afin d'assurer une prévalence de 0.5 lors de la calibration du modèle; l'effet de limiter les absences au-delà de l'enveloppe définie par les présences; quatre méthodes différentes pour l'intégration de l'autocorrélation spatiale; et enfin, l'effet de l'intégration d'interactions entre facteurs. Les résultats présentés dans cet article ont permis d'améliorer l'outil GRASP qui intègre désonnais de nouvelles méthodes de sélection et la possibilité de traiter les interactions entre variables explicatives, ainsi que l'autocorrélation spatiale. La contribution de différentes sources de données issues de la télédétection a également été évaluée. Le deuxième article (en voie de soumission) explore les effets combinés de la taille de l'échantillon et de la post-stratification sur le la précision des modèles. Les données utilisées ici sont celles concernant la répartition des prairies de Suisse recueillies dans le cadre du projet Landspot et complétées par d'autres sources. Pour la stratification des données, différents cadres spatiaux ont été comparés. En particulier, la stratification environnementale par les domaines environnementaux de Suisse a été comparée à la stratification géographique par les régions biogéographiques ou par les cantons. Le troisième article (en voie de soumission) évalue la contribution de communautés végétales pré-modélisées à la modélisation de la faune. C'est une approche en deux étapes qui combine les disciplines de l'écologie des communautés et de l'écologie spatiale en intégrant leurs concepts de 'habitat' respectifs. Les communautés végétales sont modélisées d'abord, puis ces unités de 'habitat' sont utilisées pour modéliser les espèces animales. Une étude de cas est présentée avec des communautés prairiales et des espèces de papillons. Différentes façons d'intégrer l'information sur la végétation dans les modèles de répartition des papillons sont évaluées. Enfin, un clin d'oeil aux changements climatiques dans le dernier article, publié dans Ecological Modelling. Cet article propose un cadre conceptuel pour l'analyse des changements dans la distribution des espèces qui comprend notamment un catalogue des différentes formes possibles de changement le long d'un gradient d'élévation ou autre gradient environnemental, et une méthode quantitative améliorée pour identifier et décrire ces déplacements. Cette méthodologie a été développée en utilisant des données issues du monitoring des oiseaux nicheurs répandus et l'article présente les résultats concernant les déplacements observés dans la distribution altitudinale des oiseaux nicheurs en Suisse.L'objectif général de cette thèse est d'améliorer les modèles de distribution des espèces en tant que source d'information possible pour les différents outils de conservation (par exemple, listes rouges, réseaux écologiques, évaluation des risques de propagation d'espèces envahissantes, évaluation de la vulnérabilité des espèces dans le contexte de changement climatique). Bien que ces questions de conservation ne soient pas directement testées dans cette thèse, l'importance des améliorations proposées pour la modélisation de la distribution des espèces est discutée à la fin de ce travail dans le contexte de la sélection de réseaux de réserves.
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BACKGROUND: Chest pain is a common complaint in primary care, with coronary heart disease (CHD) being the most concerning of many potential causes. Systematic reviews on the sensitivity and specificity of symptoms and signs summarize the evidence about which of them are most useful in making a diagnosis. Previous meta-analyses are dominated by studies of patients referred to specialists. Moreover, as the analysis is typically based on study-level data, the statistical analyses in these reviews are limited while meta-analyses based on individual patient data can provide additional information. Our patient-level meta-analysis has three unique aims. First, we strive to determine the diagnostic accuracy of symptoms and signs for myocardial ischemia in primary care. Second, we investigate associations between study- or patient-level characteristics and measures of diagnostic accuracy. Third, we aim to validate existing clinical prediction rules for diagnosing myocardial ischemia in primary care. This article describes the methods of our study and six prospective studies of primary care patients with chest pain. Later articles will describe the main results. METHODS/DESIGN: We will conduct a systematic review and IPD meta-analysis of studies evaluating the diagnostic accuracy of symptoms and signs for diagnosing coronary heart disease in primary care. We will perform bivariate analyses to determine the sensitivity, specificity and likelihood ratios of individual symptoms and signs and multivariate analyses to explore the diagnostic value of an optimal combination of all symptoms and signs based on all data of all studies. We will validate existing clinical prediction rules from each of the included studies by calculating measures of diagnostic accuracy separately by study. DISCUSSION: Our study will face several methodological challenges. First, the number of studies will be limited. Second, the investigators of original studies defined some outcomes and predictors differently. Third, the studies did not collect the same standard clinical data set. Fourth, missing data, varying from partly missing to fully missing, will have to be dealt with.Despite these limitations, we aim to summarize the available evidence regarding the diagnostic accuracy of symptoms and signs for diagnosing CHD in patients presenting with chest pain in primary care. REVIEW REGISTRATION: Centre for Reviews and Dissemination (University of York): CRD42011001170.
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A 0.125 degree raster or grid-based Geographic Information System with data on tsetse, trypanosomosis, animal production, agriculture and land use has recently been developed in Togo. This paper addresses the problem of generating tsetse distribution and abundance maps from remotely sensed data, using a restricted amount of field data. A discriminant analysis model is tested using contemporary tsetse data and remotely sensed, low resolution data acquired from the National Oceanographic and Atmospheric Administration and Meteosat platforms. A split sample technique is adopted where a randomly selected part of the field measured data (training set) serves to predict the other part (predicted set). The obtained results are then compared with field measured data per corresponding grid-square. Depending on the size of the training set the percentage of concording predictions varies from 80 to 95 for distribution figures and from 63 to 74 for abundance. These results confirm the potential of satellite data application and multivariate analysis for the prediction, not only of the tsetse distribution, but more importantly of their abundance. This opens up new avenues because satellite predictions and field data may be combined to strengthen or substitute one another and thus reduce costs of field surveys.
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Synchronization behavior of electroencephalographic (EEG) signals is important for decoding information processing in the human brain. Modern multichannel EEG allows a transition from traditional measurements of synchronization in pairs of EEG signals to whole-brain synchronization maps. The latter can be based on bivariate measures (BM) via averaging over pair-wise values or, alternatively, on multivariate measures (MM), which directly ascribe a single value to the synchronization in a group. In order to compare BM versus MM, we applied nine different estimators to simulated multivariate time series with known parameters and to real EEGs.We found widespread correlations between BM and MM, which were almost frequency-independent for all the measures except coherence. The analysis of the behavior of synchronization measures in simulated settings with variable coupling strength, connection probability, and parameter mismatch showed that some of them, including S-estimator, S-Renyi, omega, and coherence, aremore sensitive to linear interdependences,while others, like mutual information and phase locking value, are more responsive to nonlinear effects. Onemust consider these properties together with the fact thatMM are computationally less expensive and, therefore, more efficient for the large-scale data sets than BM while choosing a synchronization measure for EEG analysis.
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In order to obtain a high-resolution Pleistocene stratigraphy, eleven continuouslycored boreholes, 100 to 220m deep were drilled in the northern part of the PoPlain by Regione Lombardia in the last five years. Quantitative provenanceanalysis (QPA, Weltje and von Eynatten, 2004) of Pleistocene sands was carriedout by using multivariate statistical analysis (principal component analysis, PCA,and similarity analysis) on an integrated data set, including high-resolution bulkpetrography and heavy-mineral analyses on Pleistocene sands and of 250 majorand minor modern rivers draining the southern flank of the Alps from West toEast (Garzanti et al, 2004; 2006). Prior to the onset of major Alpine glaciations,metamorphic and quartzofeldspathic detritus from the Western and Central Alpswas carried from the axial belt to the Po basin longitudinally parallel to theSouthAlpine belt by a trunk river (Vezzoli and Garzanti, 2008). This scenariorapidly changed during the marine isotope stage 22 (0.87 Ma), with the onset ofthe first major Pleistocene glaciation in the Alps (Muttoni et al, 2003). PCA andsimilarity analysis from core samples show that the longitudinal trunk river at thistime was shifted southward by the rapid southward and westward progradation oftransverse alluvial river systems fed from the Central and Southern Alps.Sediments were transported southward by braided river systems as well as glacialsediments transported by Alpine valley glaciers invaded the alluvial plain.Kew words: Detrital modes; Modern sands; Provenance; Principal ComponentsAnalysis; Similarity, Canberra Distance; palaeodrainage
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Planners in public and private institutions would like coherent forecasts of the components of age-specic mortality, such as causes of death. This has been di cult toachieve because the relative values of the forecast components often fail to behave ina way that is coherent with historical experience. In addition, when the group forecasts are combined the result is often incompatible with an all-groups forecast. It hasbeen shown that cause-specic mortality forecasts are pessimistic when compared withall-cause forecasts (Wilmoth, 1995). This paper abandons the conventional approachof using log mortality rates and forecasts the density of deaths in the life table. Sincethese values obey a unit sum constraint for both conventional single-decrement life tables (only one absorbing state) and multiple-decrement tables (more than one absorbingstate), they are intrinsically relative rather than absolute values across decrements aswell as ages. Using the methods of Compositional Data Analysis pioneered by Aitchison(1986), death densities are transformed into the real space so that the full range of multivariate statistics can be applied, then back-transformed to positive values so that theunit sum constraint is honoured. The structure of the best-known, single-decrementmortality-rate forecasting model, devised by Lee and Carter (1992), is expressed incompositional form and the results from the two models are compared. The compositional model is extended to a multiple-decrement form and used to forecast mortalityby cause of death for Japan
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Self-organizing maps (Kohonen 1997) is a type of artificial neural network developedto explore patterns in high-dimensional multivariate data. The conventional versionof the algorithm involves the use of Euclidean metric in the process of adaptation ofthe model vectors, thus rendering in theory a whole methodology incompatible withnon-Euclidean geometries.In this contribution we explore the two main aspects of the problem:1. Whether the conventional approach using Euclidean metric can shed valid resultswith compositional data.2. If a modification of the conventional approach replacing vectorial sum and scalarmultiplication by the canonical operators in the simplex (i.e. perturbation andpowering) can converge to an adequate solution.Preliminary tests showed that both methodologies can be used on compositional data.However, the modified version of the algorithm performs poorer than the conventionalversion, in particular, when the data is pathological. Moreover, the conventional ap-proach converges faster to a solution, when data is \well-behaved".Key words: Self Organizing Map; Artificial Neural networks; Compositional data
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Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = Λf + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix Λ.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ΛΛT + ψ (2)where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as theloadings matrix Λ are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data