920 resultados para use pattern analysis
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Wastewater-based epidemiology consists in acquiring relevant information about the lifestyle and health status of the population through the analysis of wastewater samples collected at the influent of a wastewater treatment plant. Whilst being a very young discipline, it has experienced an astonishing development since its firs application in 2005. The possibility to gather community-wide information about drug use has been among the major field of application. The wide resonance of the first results sparked the interest of scientists from various disciplines. Since then, research has broadened in innumerable directions. Although being praised as a revolutionary approach, there was a need to critically assess its added value, with regard to the existing indicators used to monitor illicit drug use. The main, and explicit, objective of this research was to evaluate the added value of wastewater-based epidemiology with regards to two particular, although interconnected, dimensions of illicit drug use. The first is related to trying to understand the added value of the discipline from an epidemiological, or societal, perspective. In other terms, to evaluate if and how it completes our current vision about the extent of illicit drug use at the population level, and if it can guide the planning of future prevention measures and drug policies. The second dimension is the criminal one, with a particular focus on the networks which develop around the large demand in illicit drugs. The goal here was to assess if wastewater-based epidemiology, combined to indicators stemming from the epidemiological dimension, could provide additional clues about the structure of drug distribution networks and the size of their market. This research had also an implicit objective, which focused on initiating the path of wastewater- based epidemiology at the Ecole des Sciences Criminelles of the University of Lausanne. This consisted in gathering the necessary knowledge about the collection, preparation, and analysis of wastewater samples and, most importantly, to understand how to interpret the acquired data and produce useful information. In the first phase of this research, it was possible to determine that ammonium loads, measured directly in the wastewater stream, could be used to monitor the dynamics of the population served by the wastewater treatment plant. Furthermore, it was shown that on the long term, the population did not have a substantial impact on consumption patterns measured through wastewater analysis. Focussing on methadone, for which precise prescription data was available, it was possible to show that reliable consumption estimates could be obtained via wastewater analysis. This allowed to validate the selected sampling strategy, which was then used to monitor the consumption of heroin, through the measurement of morphine. The latter, in combination to prescription and sales data, provided estimates of heroin consumption in line with other indicators. These results, combined to epidemiological data, highlighted the good correspondence between measurements and expectations and, furthermore, suggested that the dark figure of heroin users evading harm-reduction programs, which would thus not be measured by conventional indicators, is likely limited. In the third part, which consisted in a collaborative study aiming at extensively investigating geographical differences in drug use, wastewater analysis was shown to be a useful complement to existing indicators. In particular for stigmatised drugs, such as cocaine and heroin, it allowed to decipher the complex picture derived from surveys and crime statistics. Globally, it provided relevant information to better understand the drug market, both from an epidemiological and repressive perspective. The fourth part focused on cannabis and on the potential of combining wastewater and survey data to overcome some of their respective limitations. Using a hierarchical inference model, it was possible to refine current estimates of cannabis prevalence in the metropolitan area of Lausanne. Wastewater results suggested that the actual prevalence is substantially higher compared to existing figures, thus supporting the common belief that surveys tend to underestimate cannabis use. Whilst being affected by several biases, the information collected through surveys allowed to overcome some of the limitations linked to the analysis of cannabis markers in wastewater (i.e., stability and limited excretion data). These findings highlighted the importance and utility of combining wastewater-based epidemiology to existing indicators about drug use. Similarly, the fifth part of the research was centred on assessing the potential uses of wastewater-based epidemiology from a law enforcement perspective. Through three concrete examples, it was shown that results from wastewater analysis can be used to produce highly relevant intelligence, allowing drug enforcement to assess the structure and operations of drug distribution networks and, ultimately, guide their decisions at the tactical and/or operational level. Finally, the potential to implement wastewater-based epidemiology to monitor the use of harmful, prohibited and counterfeit pharmaceuticals was illustrated through the analysis of sibutramine, and its urinary metabolite, in wastewater samples. The results of this research have highlighted that wastewater-based epidemiology is a useful and powerful approach with numerous scopes. Faced with the complexity of measuring a hidden phenomenon like illicit drug use, it is a major addition to the panoply of existing indicators. -- L'épidémiologie basée sur l'analyse des eaux usées (ou, selon sa définition anglaise, « wastewater-based epidemiology ») consiste en l'acquisition d'informations portant sur le mode de vie et l'état de santé d'une population via l'analyse d'échantillons d'eaux usées récoltés à l'entrée des stations d'épuration. Bien qu'il s'agisse d'une discipline récente, elle a vécu des développements importants depuis sa première mise en oeuvre en 2005, notamment dans le domaine de l'analyse des résidus de stupéfiants. Suite aux retombées médiatiques des premiers résultats de ces analyses de métabolites dans les eaux usées, de nombreux scientifiques provenant de différentes disciplines ont rejoint les rangs de cette nouvelle discipline en développant plusieurs axes de recherche distincts. Bien que reconnu pour son coté objectif et révolutionnaire, il était nécessaire d'évaluer sa valeur ajoutée en regard des indicateurs couramment utilisés pour mesurer la consommation de stupéfiants. En se focalisant sur deux dimensions spécifiques de la consommation de stupéfiants, l'objectif principal de cette recherche était focalisé sur l'évaluation de la valeur ajoutée de l'épidémiologie basée sur l'analyse des eaux usées. La première dimension abordée était celle épidémiologique ou sociétale. En d'autres termes, il s'agissait de comprendre si et comment l'analyse des eaux usées permettait de compléter la vision actuelle sur la problématique, ainsi que déterminer son utilité dans la planification des mesures préventives et des politiques en matière de stupéfiants actuelles et futures. La seconde dimension abordée était celle criminelle, en particulier, l'étude des réseaux qui se développent autour du trafic de produits stupéfiants. L'objectif était de déterminer si cette nouvelle approche combinée aux indicateurs conventionnels, fournissait de nouveaux indices quant à la structure et l'organisation des réseaux de distribution ainsi que sur les dimensions du marché. Cette recherche avait aussi un objectif implicite, développer et d'évaluer la mise en place de l'épidémiologie basée sur l'analyse des eaux usées. En particulier, il s'agissait d'acquérir les connaissances nécessaires quant à la manière de collecter, traiter et analyser des échantillons d'eaux usées, mais surtout, de comprendre comment interpréter les données afin d'en extraire les informations les plus pertinentes. Dans la première phase de cette recherche, il y pu être mis en évidence que les charges en ammonium, mesurées directement dans les eaux usées permettait de suivre la dynamique des mouvements de la population contributrice aux eaux usées de la station d'épuration de la zone étudiée. De plus, il a pu être démontré que, sur le long terme, les mouvements de la population n'avaient pas d'influence substantielle sur le pattern de consommation mesuré dans les eaux usées. En se focalisant sur la méthadone, une substance pour laquelle des données précises sur le nombre de prescriptions étaient disponibles, il a pu être démontré que des estimations exactes sur la consommation pouvaient être tirées de l'analyse des eaux usées. Ceci a permis de valider la stratégie d'échantillonnage adoptée, qui, par le bais de la morphine, a ensuite été utilisée pour suivre la consommation d'héroïne. Combinée aux données de vente et de prescription, l'analyse de la morphine a permis d'obtenir des estimations sur la consommation d'héroïne en accord avec des indicateurs conventionnels. Ces résultats, combinés aux données épidémiologiques ont permis de montrer une bonne adéquation entre les projections des deux approches et ainsi démontrer que le chiffre noir des consommateurs qui échappent aux mesures de réduction de risque, et qui ne seraient donc pas mesurés par ces indicateurs, est vraisemblablement limité. La troisième partie du travail a été réalisée dans le cadre d'une étude collaborative qui avait pour but d'investiguer la valeur ajoutée de l'analyse des eaux usées à mettre en évidence des différences géographiques dans la consommation de stupéfiants. En particulier pour des substances stigmatisées, telles la cocaïne et l'héroïne, l'approche a permis d'objectiver et de préciser la vision obtenue avec les indicateurs traditionnels du type sondages ou les statistiques policières. Globalement, l'analyse des eaux usées s'est montrée être un outil très utile pour mieux comprendre le marché des stupéfiants, à la fois sous l'angle épidémiologique et répressif. La quatrième partie du travail était focalisée sur la problématique du cannabis ainsi que sur le potentiel de combiner l'analyse des eaux usées aux données de sondage afin de surmonter, en partie, leurs limitations. En utilisant un modèle d'inférence hiérarchique, il a été possible d'affiner les actuelles estimations sur la prévalence de l'utilisation de cannabis dans la zone métropolitaine de la ville de Lausanne. Les résultats ont démontré que celle-ci est plus haute que ce que l'on s'attendait, confirmant ainsi l'hypothèse que les sondages ont tendance à sous-estimer la consommation de cannabis. Bien que biaisés, les données récoltées par les sondages ont permis de surmonter certaines des limitations liées à l'analyse des marqueurs du cannabis dans les eaux usées (i.e., stabilité et manque de données sur l'excrétion). Ces résultats mettent en évidence l'importance et l'utilité de combiner les résultats de l'analyse des eaux usées aux indicateurs existants. De la même façon, la cinquième partie du travail était centrée sur l'apport de l'analyse des eaux usées du point de vue de la police. Au travers de trois exemples, l'utilisation de l'indicateur pour produire du renseignement concernant la structure et les activités des réseaux de distribution de stupéfiants, ainsi que pour guider les choix stratégiques et opérationnels de la police, a été mise en évidence. Dans la dernière partie, la possibilité d'utiliser cette approche pour suivre la consommation de produits pharmaceutiques dangereux, interdits ou contrefaits, a été démontrée par l'analyse dans les eaux usées de la sibutramine et ses métabolites. Les résultats de cette recherche ont mis en évidence que l'épidémiologie par l'analyse des eaux usées est une approche pertinente et puissante, ayant de nombreux domaines d'application. Face à la complexité de mesurer un phénomène caché comme la consommation de stupéfiants, la valeur ajoutée de cette approche a ainsi pu être démontrée.
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The present study focused on the quality of rainwater at various land use locations and its variations on interaction with various domestic rainwater harvesting systems.Sampling sites were selected based upon the land use pattern of the locations and were classified as rural, urban, industrial and sub urban. Rainwater samples were collected from the south west monsoon of May 2007 to north east monsoon of October 2008, from four sampling sites namely Kothamangalam, Emakulam, Eloor and Kalamassery, in Ernakulam district of the State of Kerala, which characterized typical rural, urban, industrial and suburban locations respectively. Rain water samples at various stages of harvesting were also collected. The samples were analyzed according to standard procedures and their physico-chemical and microbiological parameters were determined. The variations of the chemical composition of the rainwater collected were studied using statistical methods. It was observed that 17.5%, 30%, 45.8% and 12.1% of rainwater samples collected at rural, urban, industrial and suburban locations respectively had pH less than 5.6, which is considered as the pH of cloud water at equilibrium with atmospheric CO,.Nearly 46% of the rainwater samples were in acidic range in the industrial location while it was only 17% in the rural location. Multivariate statistical analysls was done using Principal Component Analysis, and the sources that inf1uence the composition of rainwater at each locations were identified .which clearly indicated that the quality of rain water is site specific and represents the atmospheric characteristics of the free fall The quality of harvested rainwater showed significant variations at different stages of harvesting due to deposition of dust from the roof catchment surface, leaching of cement constituents etc. Except the micro biological quality, the harvested rainwater satisfied the Indian Standard guide lines for drinking water. Studies conducted on the leaching of cement constituents in water concluded that tanks made with ordinary portland cement and portland pozzolana cement could be safely used for storage of rain water.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The Zagros oak forests in Western Iran are critically important to the sustainability of the region. These forests have undergone dramatic declines in recent decades. We evaluated the utility of the non-parametric Random Forest classification algorithm for land cover classification of Zagros landscapes, and selected the best spatial and spectral predictive variables. The algorithm resulted in high overall classification accuracies (>85%) and also equivalent classification accuracies for the datasets from the three different sensors. We evaluated the associations between trends in forest area and structure with trends in socioeconomic and climatic conditions, to identify the most likely driving forces creating deforestation and landscape structure change. We used available socioeconomic (urban and rural population, and rural income), and climatic (mean annual rainfall and mean annual temperature) data for two provinces in northern Zagros. The most correlated driving force of forest area loss was urban population, and climatic variables to a lesser extent. Landscape structure changes were more closely associated with rural population. We examined the effects of scale changes on the results from spatial pattern analysis. We assessed the impacts of eight years of protection in a protected area in northern Zagros at two different scales (both grain and extent). The effects of protection on the amount and structure of forests was scale dependent. We evaluated the nature and magnitude of changes in forest area and structure over the entire Zagros region from 1972 to 2009. We divided the Zagros region in 167 Landscape Units and developed two measures— Deforestation Sensitivity (DS) and Connectivity Sensitivity (CS) — for each landscape unit as the percent of the time steps that forest area and ECA experienced a decrease of greater than 10% in either measure. A considerable loss in forest area and connectivity was detected, but no sudden (nonlinear) changes were detected at the spatial and temporal scale of the study. Connectivity loss occurred more rapidly than forest loss due to the loss of connecting patches. More connectivity was lost in southern Zagros due to climatic differences and different forms of traditional land use.
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Calmodulin (CaM) is a ubiquitous Ca(2+) buffer and second messenger that affects cellular function as diverse as cardiac excitability, synaptic plasticity, and gene transcription. In CA1 pyramidal neurons, CaM regulates two opposing Ca(2+)-dependent processes that underlie memory formation: long-term potentiation (LTP) and long-term depression (LTD). Induction of LTP and LTD require activation of Ca(2+)-CaM-dependent enzymes: Ca(2+)/CaM-dependent kinase II (CaMKII) and calcineurin, respectively. Yet, it remains unclear as to how Ca(2+) and CaM produce these two opposing effects, LTP and LTD. CaM binds 4 Ca(2+) ions: two in its N-terminal lobe and two in its C-terminal lobe. Experimental studies have shown that the N- and C-terminal lobes of CaM have different binding kinetics toward Ca(2+) and its downstream targets. This may suggest that each lobe of CaM differentially responds to Ca(2+) signal patterns. Here, we use a novel event-driven particle-based Monte Carlo simulation and statistical point pattern analysis to explore the spatial and temporal dynamics of lobe-specific Ca(2+)-CaM interaction at the single molecule level. We show that the N-lobe of CaM, but not the C-lobe, exhibits a nano-scale domain of activation that is highly sensitive to the location of Ca(2+) channels, and to the microscopic injection rate of Ca(2+) ions. We also demonstrate that Ca(2+) saturation takes place via two different pathways depending on the Ca(2+) injection rate, one dominated by the N-terminal lobe, and the other one by the C-terminal lobe. Taken together, these results suggest that the two lobes of CaM function as distinct Ca(2+) sensors that can differentially transduce Ca(2+) influx to downstream targets. We discuss a possible role of the N-terminal lobe-specific Ca(2+)-CaM nano-domain in CaMKII activation required for the induction of synaptic plasticity.
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Diseases and insect pests are major causes of low yields of common bean (Phaseolus vulgaris L.) in Latin America and Africa. Anthracnose, angular leaf spot and common bacterial blight are widespread foliar diseases of common bean that also infect pods and seeds. One thousand and eighty-two accessions from a common bean core collection from the primary centres of origin were investigated for reaction to these three diseases. Angular leaf spot and common bacterial blight were evaluated in the field at Santander de Quilichao, Colombia, and anthracnose was evaluated in a screenhouse in Popayan, Colombia. By using the 15-group level from a hierarchical clustering procedure, it was found that 7 groups were formed with mainly Andean common bean accessions (Andean gene pool), 7 groups with mainly Middle American accessions (Middle American gene pool), while 1 group contained mixed accessions. Consistent with the theory of co-evolution, it was generally observed that accessions from the Andean gene pool were resistant to Middle American pathogen isolates causing anthracnoxe, while the Middle American accessions were resistant to pathogen isolates from the Andes. Different combinations of resistance patterns were found, and breeders can use this information to select a specific group of accessions on the basis of their need.
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Entre março de 2011 e dezembro de 2012 foram realizadas 30 saídas de campo para avaliar os padrões de uso de habitat e estrutura de grupo de Sotalia guianensis na região da foz do rio Doce, costa norte do Espírito Santo. A coleta de dados foi realizada com auxílio de uma embarcação a partir de rotas pré-determinadas distribuídas homogeneamente na área de estudo. Informações sobre as variáveis ambientais foram coletadas a cada hora de amostragem e a cada grupo de golfinhos avistado. Através da análise de Cluster foram identificados três diferentes habitats baseados na similaridade entre variáveis ambientais. Durante 242hs48min de amostragem foram percorridos 1.523km e 119 grupos de botos-cinza foram avistados. Grupos de Sotalia guianensis, assim como indivíduos imaturos, foram observados ao longo de todo o ano na área de estudo, não apresentando diferença sazonal entre as estações seca (abril a setembro) e chuvosa (outubro a março). Os grupos apresentaram uma média de 9,9 indivíduos. Animais imaturos estavam presentes na maioria dos grupos (71%), apresentando uma relação direta com o número de adultos. Os botos-cinza apresentaram o uso quase exclusivo da região marinha aberta adjacente à desembocadura do rio apontando um padrão de uso de habitats heterogêneo, onde as áreas de maior concentração de golfinhos não corresponderam às áreas preferenciais de alimentação. Os resultados obtidos neste trabalho refletem como S. guianensis responde a complexidade dos fatores bióticos e abióticos da área de estudo, apontando um padrão de uso de habitat diferenciado para a espécie.
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Graphical user interfaces (GUIs) are critical components of todays software. Given their increased relevance, correctness and usability of GUIs are becoming essential. This paper describes the latest results in the development of our tool to reverse engineer the GUI layer of interactive computing systems. We use static analysis techniques to generate models of the user interface behaviour from source code. Models help in graphical user interface inspection by allowing designers to concentrate on its more important aspects. One particularly type of model that the tool is able to generate is state machines. The paper shows how graph theory can be useful when applied to these models. A number of metrics and algorithms are used in the analysis of aspects of the user interface's quality. The ultimate goal of the tool is to enable analysis of interactive system through GUIs source code inspection.
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A large and growing amount of software systems rely on non-trivial coordination logic for making use of third party services or components. Therefore, it is of outmost importance to understand and capture rigorously this continuously growing layer of coordination as this will make easier not only the veri cation of such systems with respect to their original speci cations, but also maintenance, further development, testing, deployment and integration. This paper introduces a method based on several program analysis techniques (namely, dependence graphs, program slicing, and graph pattern analysis) to extract coordination logic from legacy systems source code. This process is driven by a series of pre-de ned coordination patterns and captured by a special purpose graph structure from which coordination speci cations can be generated in a number of di erent formalisms
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Graphical user interfaces (GUIs) are critical components of today's open source software. Given their increased relevance, the correctness and usability of GUIs are becoming essential. This paper describes the latest results in the development of our tool to reverse engineer the GUI layer of interactive computing open source systems. We use static analysis techniques to generate models of the user interface behavior from source code. Models help in graphical user interface inspection by allowing designers to concentrate on its more important aspects. One particular type of model that the tool is able to generate is state machines. The paper shows how graph theory can be useful when applied to these models. A number of metrics and algorithms are used in the analysis of aspects of the user interface's quality. The ultimate goal of the tool is to enable analysis of interactive system through GUIs source code inspection.
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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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Reducing low-density lipoprotein cholesterol (LDL-C) levels using statins is associated with significant reductions in cardiovascular (CV) events in a wide range of patient populations. Although statins are generally considered to be safe, recent studies suggest they are associated with an increased risk of developing Type 2 diabetes (T2D). This led the US Food and Drug Administration (FDA) to change their labelling requirements for statins to include a warning about the possibility of increased blood sugar and HbA1c levels and the European Medicines Agency (EMA) to issue guidance on a small increased risk of T2D with the statin class. This review examines the evidence leading to these claims and provides practical guidance for primary care physicians on the use of statins in people with or at risk of developing T2D. Overall, evidence suggests that the benefits of statins for the reduction of CV risk far outweigh the risk of developing T2D, especially in individuals with higher CV risk. To reduce the risk of developing T2D, physicians should assess all patients for T2D risk prior to starting statin therapy, educate patients about their risks, and encourage risk-reduction through lifestyle changes. Whether some statins are more diabetogenic than others requires further study. Statin-treated patients at high risk of developing T2D should regularly be monitored for changes in blood glucose or HbA1c levels, and the risk of conversion from pre-diabetes to T2D should be reduced by intensifying lifestyle changes. Should a patient develop T2D during statin treatment, physicians should continue with statin therapy and manage T2D in accordance with relevant national guidelines.
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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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Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.