Analyse multidimensionnelle interactive de résultats de simulation (aide à la décision dans le domaine de l'agroécologie)

Dans cette thèse, nous nous sommes intéressés à l'analyse des données de simulation issues du modèle agro-hydrologique TNT. Les objectifs consistaient à élaborer des méthodes d'analyse des résultats de simulation qui replacent l'utilisateur au coeur du processus décisionnel, et qui permettent d'analyser et d'interpréter de gros volumes de données de manière efficace. La démarche développée consiste à utiliser des méthodes d'analyse multidimensionnelle interactive. Tout d'abord, nous avons proposé une méthode d'archivage des résultats de simulation dans une base de données décisionnelle (i.e. entrepôt de données), adaptée au caractère spatio-temporel des données de simulation produites. Ensuite, nous avons suggéré d'analyser ces données de simulations avec des méthodes d'analyse en ligne (OLAP) afin de fournir aux acteurs des informations stratégiques pour améliorer le processus d'aide à la prise de décision. Enfin, nous avons proposé deux méthodes d'extraction de skyline dans le contexte des entrepôts de données afin de permettre aux acteurs de formuler de nouvelles questions en combinant des critères environnementaux contradictoires, et de trouver les solutions compromis associées à leurs attentes, puis d'exploiter les préférences des acteurs pour détecter et faire ressortir les données susceptibles de les intéresser. La première méthode EC2Sky, permet un calcul incrémental et efficace des skyline en présence de préférences utilisateurs dynamiques, et ce malgré de gros volumes de données. La deuxième méthode HSky, étend la recherche des points skyline aux dimensions hiérarchiques. Elle permet aux utilisateurs de naviguer le long des axes des dimensions hiérarchiques (i.e. spécialisation / généralisation) tout en assurant un calcul en ligne des points skyline correspondants. Ces contributions ont été motivées et expérimentées par l'application de gestion des pratiques agricoles pour l'amélioration de la qualité des eaux des bassins versants agricoles, et nous avons proposé un couplage entre le modèle d'entrepôt de données agro-hydrologiques construit et les méthodes d'extraction de skyline proposées.This thesis concerns the analysis of simulation data generated by the agrohydrological model TNT. Our objective is to develop analytical methods for massive simulation results. We want to place the user at the heart of the decision-making process, while letting him handle and analyze large amounts of data in a very efficient way. Our first contribution is an original approach N-Catch, relying on interactive multidimensional analysis methods for archiving simulation results in a decisional database (i.e. data warehouse) adapted to the spatio-temporal nature of the simulation data. In addition, we suggest to analyze the simulation data with online analytical methods (OLAP) to provide strategic information for stakeholders to improve the decision making process. Our second contribution concern two methods for computing skyline queries in the context of data warehouses. These methods enable stakeholders to formulate new questions by combining conflicting environmental criteria, to find compromise solutions associated with their expectations, and to exploit the stakeholder preferences to identify and highlight the data of potential interest. The first method EC2Sky, focuses on how to answer efficiently and progressively skyline queries in the presence of several dynamic user preferences despite of large volume of data. The second method HSky, extends the skyline computation to hierarchical dimensions. It allows the user to navigate along the dimensions hierarchies (i.e. specialize / generalize) while ensuring the online computation of associated skylines. Finally, we present the application of our proposals for managing agricultural practices to improve water quality in agricultural watersheds. We propose a coupling between the agro-hydrological data warehouse model N-Catch and the proposed skyline computation methods.RENNES1-Bibl. électronique (352382106) / SudocSudocFranceF

Impact of source data on the interpretation of contrast-enhanced magnetic resonance angiography of the lower limbs

Background The primary purpose of this study is to examine whether use of source data is effective in increasing the number of arterial segments that can be interpreted from maximum intensity projections of lower limb MR angiograms. Correlation between sites of arterial disease and venous contamination was also measured. Interpretation of source data is performed routinely by radiologists, but the value of this has not been well studied with randomized studies. Results The proportion of segments visible above the knee was 87% using maximal intensity projection alone (MIP) and 88% when the MIP was combined with source data. The proportions were 67% for MIP and 72% for MIP plus source data below the knee. There was substantial agreement between presence of arterial disease and venous contamination in the calf and thigh. Conclusion The use of source data increases the number of assessable segments, but not individuals, by a statistically significant but small amount (1.2%, p <0.05). This study supports the association between arterial disease and venous contamination

Shedding light on plant litter decomposition: Advances, implications and new directions in understanding the role of photodegradation

Litter decomposition contributes to one of the largest fluxes of carbon (C) in the terrestrial biosphere and is a primary control on nutrient cycling. The inability of models using climate and litter chemistry to predict decomposition in dry environments has stimulated investigation of non-traditional drivers of decomposition, including photodegradation, the abiotic decomposition of organic matter via exposure to solar radiation. Recent work in this developing field shows that photodegradation may substantially influence terrestrial C fluxes, including abiotic production of carbon dioxide, carbon monoxide and methane, especially in arid and semi-arid regions. Research has also produced contradictory results regarding controls on photodegradation. Here we summarize the state of knowledge about the role of photodegradation in litter decomposition and C cycling and investigate drivers of photodegradation across experiments using a meta-analysis. Overall, increasing litter exposure to solar radiation increased mass loss by 23% with large variation in photodegradation rates among and within ecosystems. This variation was tied to both litter and environmental characteristics. Photodegradation increased with litter C to nitrogen (N) ratio, but not with lignin content, suggesting that we do not yet fully understand the underlying mechanisms. Photodegradation also increased with factors that increased solar radiation exposure (latitude and litter area to mass ratio) and decreased with mean annual precipitation. The impact of photodegradation on C (and potentially N) cycling fundamentally reshapes our thinking of decomposition as a solely biological process and requires that we define the mechanisms driving photodegradation before we can accurately represent photodegradation in global C and N models. © 2012 US Government

Species Richness and Trophic Diversity Increase Decomposition in a Co-Evolved Food Web

Ecological communities show great variation in species richness, composition and food web structure across similar and diverse ecosystems. Knowledge of how this biodiversity relates to ecosystem functioning is important for understanding the maintenance of diversity and the potential effects of species losses and gains on ecosystems. While research often focuses on how variation in species richness influences ecosystem processes, assessing species richness in a food web context can provide further insight into the relationship between diversity and ecosystem functioning and elucidate potential mechanisms underpinning this relationship. Here, we assessed how species richness and trophic diversity affect decomposition rates in a complete aquatic food web: the five trophic level web that occurs within water-filled leaves of the northern pitcher plant, Sarracenia purpurea. We identified a trophic cascade in which top-predators — larvae of the pitcher-plant mosquito — indirectly increased bacterial decomposition by preying on bactivorous protozoa. Our data also revealed a facultative relationship in which larvae of the pitcher-plant midge increased bacterial decomposition by shredding detritus. These important interactions occur only in food webs with high trophic diversity, which in turn only occur in food webs with high species richness. We show that species richness and trophic diversity underlie strong linkages between food web structure and dynamics that influence ecosystem functioning. The importance of trophic diversity and species interactions in determining how biodiversity relates to ecosystem functioning suggests that simply focusing on species richness does not give a complete picture as to how ecosystems may change with the loss or gain of species

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability