Territoires contingents pour populations temporaires. Le cas de la Région Urbaine Milanaise

Cette communication propose une réflexion critique sur les périmètres administratifs et les limites des compétences institutionnelles à partir de l’étude des pratiques de mobilités dans la Région Urbaine Milanaise. L’intégration de sources traditionnelles avec des données de téléphonie mobile nous a permis de mettre au point une carte inédite de la Région, dessinée à partir des comportements de mobilité. La notion de « territoires contingents » permet de comprendre les périmètres de pratiques à «géométrie variable» que cette carte fait apparaître

The International Finance Facility for Immunisation: stakeholders' perspectives.

OBJECTIVE: To evaluate stakeholders' understanding and opinions of the International Finance Facility for Immunisation (IFFIm); to identify factors affecting funding levels; and to explore the future use of IFFIm. METHODS: Between July and September 2015, we interviewed 33 individuals from 25 organizations identified as stakeholders in IFFIm. In total 22.5 hours of semi-structured interviews were recorded, transcribed and analysed using a framework method. FINDINGS: Stakeholders' understanding of IFFIm's financing mechanism and its outcomes varied and many stakeholders wanted more information. Participants highlighted that the change in the macro-economic environment following the 2008 financial crisis affected national policy in donor countries and subsequently the number of new commitments IFFIm received. Since Gavi is now seen as a successful and mature organization, participants stated that donors prefer to donate directly to Gavi. The pharmaceutical industry valued IFFIm for providing funding stability and flexibility. Other stakeholders valued IFFIm's ability to access funds early and enable Gavi to increase vaccine coverage. Overall, stakeholders thought IFFIm was successful, but they had divergent views about IFFIm's on-going role. Participants listed two issues where bond financing mechanisms may be suitable: emergency preparedness and outcome-based time-limited interventions. CONCLUSION: The benefit of pledging funds through IFFIm needs to be re-evaluated. There are potential uses for bond financing to raise funds for other global health issues, but these must be carefully considered against criteria to establish effectiveness, with quantifiable pre-defined outcome indicators to evaluate performance

Bayesian participatory-based decision analysis : an evolutionary, adaptive formalism for integrated analysis of complex challenges to social-ecological system sustainability

Includes bibliographical references (pages. 379-400).This dissertation responds to the need for integration between researchers and decision-makers who are dealing with complex social-ecological system sustainability and decision-making challenges. To this end, we propose a new approach, called Bayesian Participatory-based Decision Analysis (BPDA), which makes use of graphical causal maps and Bayesian networks to facilitate integration at the appropriate scales and levels of descriptions. The BPDA approach is not a predictive approach, but rather, caters for a wide range of future scenarios in anticipation of the need to adapt to unforeseeable changes as they occur. We argue that the graphical causal models and Bayesian networks constitute an evolutionary, adaptive formalism for integrating research and decision-making for sustainable development. The approach was implemented in a number of different interdisciplinary case studies that were concerned with social-ecological system scale challenges and problems, culminating in a study where the approach was implemented with decision-makers in Government. This dissertation introduces the BPDA approach, and shows how the approach helps identify critical cross-scale and cross-sector linkages and sensitivities, and addresses critical requirements for understanding system resilience and adaptive capacity

An Examination of Contemporary Marketing Practices Used by Organization with Different Culture Types: A Test of the Convergence Theory in the US and Cote d\u27Ivoire

A framework for a strategy fit with national and organizational culture holds several implications for multinational business managers. First, culture is a critical variable in the strategy process and it should be explicitly examined as a part of the process. Second, culture might encourage and support organizationally a particular business level strategy and may affect marketing practices. This approach views transactional and relational practices as part of a continuum. This study has examined over 250 firms in the United States and the Cote d’Ivoire on the dimensions of their organizational culture, national culture and contemporary marketing practices. In essence, this is a test of the convergence theory versus cultural specificity debate. The study first establishes a model in the US of the relationship between organizational culture and contemporary marketing practices and then tests it in Cote d’Ivoire. Lisrel is used to examine the goodness of the fit of the model. Results indicate that differences in national cultures call for differences in marketing practices since the US model does not fit in Cote d’Ivoire. The differences between the two models and implications for a new Ivorian model are discussed

CORPORATE SOCIAL RESPONSIBILITY IN ROMANIA

The purpose of this paper is to identify the main opportunities and limitations of corporate social responsibility (CSR). The survey was defined with the aim to involve the highest possible number of relevant CSR topics and give the issue a more wholesome perspective. It provides a basis for further comprehension and deeper analyses of specific CSR areas. The conditions determining the success of CSR in Romania have been defined in the paper on the basis of the previously cumulative knowledge as well as the results of various researches. This paper provides knowledge which may be useful in the programs promoting CSR.Corporate social responsibility, Supportive policies, Romania

Étude des effets reliés à la taille du domaine d'intégration d'une simulation climatique régionale avec le protocole du grand frère

Les modèles régionaux de climat (MRCs) permettent de simuler les écoulements atmosphériques sur une région limitée de la surface terrestre. Pilotés à leurs frontières latérales par des données à basse résolution provenant de modèles mondiaux (MCGs), ils permettent d'augmenter considérablement la résolution spatiale des simulations en vue de répondre au besoin grandissant d'évaluer les impacts régionaux reliés aux changements climatiques. Plusieurs études ont démontré que la taille du domaine régional est un paramètre pouvant affecter considérablement les résultats des simulations. En effet, le domaine doit être assez grand pour permettre le développement des fines échelles qui n'existent pas dans les conditions aux frontières latérales. D'un autre côté, une simulation effectuée sur un trop grand domaine peut montrer d'importantes différences avec les données de pilotage si aucun forçage des grandes échelles n'est appliqué à l'intérieur du domaine régional. Les effets reliés à la taille du domaine d'intégration d'une simulation MRC sont évalués selon le cadre expérimental du "Grand-Frère". L'expérience consiste d'abord à générer une simulation climatique à haute résolution (-45 km) sur un domaine continental couvrant la majorité de l'Amérique du Nord, sur 196x196 points de grille. Cette simulation de référence, le Grand-Frère (GF), est ensuite traitée à l'aide d'un filtre passe-bas ayant la propriété de conserver les plus grandes échelles de l'écoulement (approximativement ≥ 2160 km). La série de données ainsi obtenue, le Grand-Frère Filtré (GFF), possède un niveau de détails similaire à celui des données provenant des MCGs. On utilise alors le GFF pour piloter quatre simulations, les Petits-Frères (PFs), à l'aide du même modèle mais sur des domaines plus restreints et de tailles différentes qu'on notera PFl à PF4, et qui ont des dimensions respectives de 144x144, 120x120, 96x96 et 72x72 points de grille. Les résultats des PFs sont comparés avec le GF en cumulant les statistiques climatiques (moyenne temporelle et écart-type) sur quatre mois d'hiver, au-dessus d'une zone commune correspondant pratiquement à la province canadienne du Québec. De manière générale, les patrons (pression, vent, humidité relative et taux de précipitation) des PFs s'améliorent en corrélation spatiale par rapport au GF lorsque le domaine est réduit de 144x144 à 72x72. Cette tendance a aussi été observée pour la moyenne temporelle des fines échelles de l'écoulement. Toutefois, il a été observé que l'intensité de la variabilité transitoire (écart-type) de ces échelles pouvait être compromise par la proximité des frontières latérales par rapport à la zone d'intérêt. En effet, d'importantes sous-estimations ont été détectées, particulièrement du côté entrant du domaine, ce qui suggère l'existence d'une distance de "spin-up" se devant d'être parcourue par l'écoulement avant que celui-ci démontre des particularités de fines échelles. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : Modèle régional de climat, Sensibilité à la taille du domaine, Petites échelles, Protocole du Grand-Frère

Préférences hétérogènes des grands projets miniers : trois essais en évaluation non marchande

L’évaluation fine des impacts miniers représente un défi majeur considérant l’ampleur des changements socio-économiques et environnementaux et les controverses que le secteur minier continue jusqu’à lors de susciter. Un aspect souvent manquant de l’évaluation des projets miniers est lié à la question de l’impact sur le bien-être. La thèse a pour objectif d’apporter un ensemble d’éclairages sur les potentiels impacts, notamment en considérant l’hétérogénéité de la population. Le contexte d’étude est la province minière du Québec, au Canada, avec une enquête des ménages mesurant les variations de bien-être par la méthode Choice Experiment. L’article 1 pointe l’importance du contexte géographique, marquée par des inégalités spatiales dans les impacts miniers. Nous trouvons que le développement minier peut avoir des impacts de longues distances sur le bien-être, liés au type de minerai et à la perception individuelle du risque. L’article 2 tire avantage du passé minier de l’exploitation de l’or au Québec pour étudier si cette expérience collective facilite les arbitrages miniers sur les terres rares, un minerai nouveau dans la province et souvent méconnu par le public. Enfin l’article 3 teste les effets potentiels de campagnes d’information sur les changements de bien-être. L’information apparaît avoir peu ou aucun effet. Cependant, ce résultat masque des effets élevés et contrastés auprès des individus opposés par leurs perceptions sur l’opportunité/menace d’une nouvelle mine. La thèse conclue en présentant des nouvelles pistes de recherche pour mieux évaluer les effets du développement minier sur le bien-être.Abstract: Granular evaluation of mining impacts is highly challenging as regards to the strong social, environmental and economic changes at play, and possibly related controversies. This thesis raises the question on how mining can affect people’s well-being with a research focus on population heterogeneity. A choice experiment survey is conducted to collect ground information on changing well-being due to mining within the province of Quebec, in Canada. Article 1 points to the importance of the geographic context, marked by spatial inequalities in mining impacts. We find that mining development can have long-range impacts on welfare, related to the type of mineral and individual risk perception. Paper 2 takes advantage of strong gold mining history in Quebec to study whether collective experience facilitates mining trade-offs over rare earths, that are new to the province and often poorly known by general public. Finally, paper 3 tests potential effects of information campaigns on welfare changes. Information appears to have little or no effect. However, this result masks high and contrasting effects according to opposing prior beliefs for or against mining windfall. The thesis concludes on relevant research extensions to help estimate mining effects on people’s well-being

A COMPARATIVE STUDY OF ENGLISH SECOND LANGUAGE READING COMPREHENSION OF A RELIGION-BASED ASSESSMENT IN TWO DIFFERENT LOCATIONAL CONTEXTS

ABSTRACT A Comparative Study of English Second Language Reading Comprehension of a Religion-Based Assessment in Two Different Locational Contexts This study examined two different educational locations which had distinct environments. Both locations were part of the same religious (Christian) denomination and both were in higher education settings. The monolingual context was on campuses of universities and a seminary located in central United States. The multilingual context was a regional seminary campus located in Asia. All of the participants were second language users of English. Two main instruments were administered. One was a C-Test adapted from Babii et al to independently assess the proficiency level of the participants apart from the measures that might have been used for their admission to the various institutions they were attending. The second instrument was a reading comprehension test patterned after the TOEFL but using texts that were compatible with a religious education setting. The two instruments showed a strong correlation with a Pearson r = .748 The results of this study indicate that there is no significant difference between the reading comprehension scores of students studying in a multicultural educational context and students studying in a monolingual educational context. The main predictor of reading comprehension scores was the students’ level of proficiency. A lesser predictor was whether they were graduate students or undergraduate students. Additionally, the country or area of origin seemed to have a small measure of predictability for the reading comprehension scores

Computationally Linking Chemical Exposure to Molecular Effects with Complex Data: Comparing Methods to Disentangle Chemical Drivers in Environmental Mixtures and Knowledge-based Deep Learning for Predictions in Environmental Toxicology

Chemical exposures affect the environment and may lead to adverse outcomes in its organisms. Omics-based approaches, like standardised microarray experiments, have expanded the toolbox to monitor the distribution of chemicals and assess the risk to organisms in the environment. The resulting complex data have extended the scope of toxicological knowledge bases and published literature. A plethora of computational approaches have been applied in environmental toxicology considering systems biology and data integration. Still, the complexity of environmental and biological systems given in data challenges investigations of exposure-related effects. This thesis aimed at computationally linking chemical exposure to biological effects on the molecular level considering sources of complex environmental data. The first study employed data of an omics-based exposure study considering mixture effects in a freshwater environment. We compared three data-driven analyses in their suitability to disentangle mixture effects of chemical exposures to biological effects and their reliability in attributing potentially adverse outcomes to chemical drivers with toxicological databases on gene and pathway levels. Differential gene expression analysis and a network inference approach resulted in toxicologically meaningful outcomes and uncovered individual chemical effects — stand-alone and in combination. We developed an integrative computational strategy to harvest exposure-related gene associations from environmental samples considering mixtures of lowly concentrated compounds. The applied approaches allowed assessing the hazard of chemicals more systematically with correlation-based compound groups. This dissertation presents another achievement toward a data-driven hypothesis generation for molecular exposure effects. The approach combined text-mining and deep learning. The study was entirely data-driven and involved state-of-the-art computational methods of artificial intelligence. We employed literature-based relational data and curated toxicological knowledge to predict chemical-biomolecule interactions. A word embedding neural network with a subsequent feed-forward network was implemented. Data augmentation and recurrent neural networks were beneficial for training with curated toxicological knowledge. The trained models reached accuracies of up to 94% for unseen test data of the employed knowledge base. However, we could not reliably confirm known chemical-gene interactions across selected data sources. Still, the predictive models might derive unknown information from toxicological knowledge sources, like literature, databases or omics-based exposure studies. Thus, the deep learning models might allow predicting hypotheses of exposure-related molecular effects. Both achievements of this dissertation might support the prioritisation of chemicals for testing and an intelligent selection of chemicals for monitoring in future exposure studies.:Table of Contents ... I Abstract ... V Acknowledgements ... VII Prelude ... IX 1 Introduction 1.1 An overview of environmental toxicology ... 2 1.1.1 Environmental toxicology ... 2 1.1.2 Chemicals in the environment ... 4 1.1.3 Systems biological perspectives in environmental toxicology ... 7 Computational toxicology ... 11 1.2.1 Omics-based approaches ... 12 1.2.2 Linking chemical exposure to transcriptional effects ... 14 1.2.3 Up-scaling from the gene level to higher biological organisation levels ... 19 1.2.4 Biomedical literature-based discovery ... 24 1.2.5 Deep learning with knowledge representation ... 27 1.3 Research question and approaches ... 29 2 Methods and Data ... 33 2.1 Linking environmental relevant mixture exposures to transcriptional effects ... 34 2.1.1 Exposure and microarray data ... 34 2.1.2 Preprocessing ... 35 2.1.3 Differential gene expression ... 37 2.1.4 Association rule mining ... 38 2.1.5 Weighted gene correlation network analysis ... 39 2.1.6 Method comparison ... 41 Predicting exposure-related effects on a molecular level ... 44 2.2.1 Input ... 44 2.2.2 Input preparation ... 47 2.2.3 Deep learning models ... 49 2.2.4 Toxicogenomic application ... 54 3 Method comparison to link complex stream water exposures to effects on the transcriptional level ... 57 3.1 Background and motivation ... 58 3.1.1 Workflow ... 61 3.2 Results ... 62 3.2.1 Data preprocessing ... 62 3.2.2 Differential gene expression analysis ... 67 3.2.3 Association rule mining ... 71 3.2.4 Network inference ... 78 3.2.5 Method comparison ... 84 3.2.6 Application case of method integration ... 87 3.3 Discussion ... 91 3.4 Conclusion ... 99 4 Deep learning prediction of chemical-biomolecule interactions ... 101 4.1 Motivation ... 102 4.1.1Workflow ...105 4.2 Results ... 107 4.2.1 Input preparation ... 107 4.2.2 Model selection ... 110 4.2.3 Model comparison ... 118 4.2.4 Toxicogenomic application ... 121 4.2.5 Horizontal augmentation without tail-padding ...123 4.2.6 Four-class problem formulation ... 124 4.2.7 Training with CTD data ... 125 4.3 Discussion ... 129 4.3.1 Transferring biomedical knowledge towards toxicology ... 129 4.3.2 Deep learning with biomedical knowledge representation ...133 4.3.3 Data integration ...136 4.4 Conclusion ... 141 5 Conclusion and Future perspectives ... 143 5.1 Conclusion ... 143 5.1.1 Investigating complex mixtures in the environment ... 144 5.1.2 Complex knowledge from literature and curated databases predict chemical- biomolecule interactions ... 145 5.1.3 Linking chemical exposure to biological effects by integrating CTD ... 146 5.2 Future perspectives ... 147 S1 Supplement Chapter 1 ... 153 S1.1 Example of an estrogen bioassay ... 154 S1.2 Types of mode of action ... 154 S1.3 The dogma of molecular biology ... 157 S1.4 Transcriptomics ... 159 S2 Supplement Chapter 3 ... 161 S3 Supplement Chapter 4 ... 175 S3.1 Hyperparameter tuning results ... 176 S3.2 Functional enrichment with predicted chemical-gene interactions and CTD reference pathway genesets ... 179 S3.3 Reduction of learning rate in a model with large word embedding vectors ... 183 S3.4 Horizontal augmentation without tail-padding ... 183 S3.5 Four-relationship classification ... 185 S3.6 Interpreting loss observations for SemMedDB trained models ... 187 List of Abbreviations ... i List of Figures ... vi List of Tables ... x Bibliography ... xii Curriculum scientiae ... xxxix Selbständigkeitserklärung ... xlii