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211	TURBULENCE-INFORMED PREDICTIVE MODELING FOR RESILIENT SYSTEMS IN EMERGING GLOBAL CHALLENGES: APPLICATIONS IN RENEWABLE ENERGY MANAGEMENT AND INDOOR AIRBORNE TRANSMISSION CONTROL Jhon Jairo Quinones Cortes (17592753) 09 December 2023 (has links) <p dir="ltr">Evidence for climate change-related impacts and risks is already widespread globally, affecting not only the ecosystems but also the economy and health of our communities. Data-driven predictive modeling approaches such as machine learning and deep learning have emerged to be powerful tools for interpreting large and complex non-linear datasets such as meteorological variables from weather stations or the distribution of infectious droplets produced in a cough. However, the strength of these data-driven models can be further optimized by complementing them with foundational knowledge of the physical processes they represent. By understanding the core physics, one can enhance the reliability and accuracy of predictive outcomes. The effectiveness of these combined approaches becomes particularly feasible and robust with the recent advancements in the High-Performance Computing field. With improved processing speed, algorithm design, and storage capabilities, modern computers allow for a deeper and more precise examination of the data. Such advancements equip us to address the diverse challenges presented by climate change more effectively.</p><p dir="ltr">In particular, this document advances research in mitigating and preventing the consequences of global warming by implementing data-driven predictive models based on statistical, machine learning, and deep learning methods via two phases. In the first phase, this dissertation proposes frameworks consisting of machine and deep learning algorithms to increase the resilience of small-scale renewable energy systems, which are essential for reducing greenhouse gas emissions in the ecosystems. The second phase focuses on using data from physics-based models, i.e., computational fluid dynamics (CFD), in data-driven predictive models for improving the design of air cleaning technologies, which are crucial to reducing the transmission of infectious diseases in indoor environments. </p><p dir="ltr">Specifically, this work is an article-based collection of published (or will be published) research articles. The articles are reformatted to fit the thesis's structure. The contents of the original articles are self-contained. </p> Turbulent flows Deep learning Machine learning Atmospheric boundary layer Microgrids Renewable energy Multi-objective optimization Robust optimization techniques pandemics/epidemics Indoor Transmission Control Wind Energy Forecasting Multi step ahead forecasting Respiratory flows physics-informed machine learning
212	Living under the threat of Ebola : a phenomenological study Matua, Amandu Gerald 08 1900 (has links) This study articulates the phenomenon of living under a constant threat of Ebola haemorrhagic fever, including what people’s reactions towards individuals and families affected by the illness symbolizes as well as the meanings ascribed to Ebola. The study was conducted in Kibale district in Midwestern Uganda to aid understanding of the human aspects of Ebola which has continued to result in widespread fear and anxiety, thereby creating challenges for affected individuals, families and health care professionals. A phenomenological inquiry was undertaken using Wertz’s (1983, 2005, 2011) empirical psychological reflection approach for data analysis, after utilizing purposive, convenience and criterion sampling techniques to select twelve (12) adult survivors and caregivers who anticipated, experienced and survived the outbreak and were in good health and also willing to take part in the study. Data were generated using in-depth qualitative interviews and the interviews continued until data redundancy was reached. The interview proceedings were digitally audio-recorded in addition to taking field notes and these were transcribed verbatim. Data analysis occurred at idiographic and nomothetic levels according to the principles of Wertz’s empirical psychological reflection. Thematic analysis of the research data revealed seven (7) themes, namely:  Living under constant threat of Ebola  Nature of Ebola experience: unique and general meanings  Surviving Ebola: physical, psychological, social, spiritual and economic implications on survivors  Caring for Ebola patients: social and psychological implications  Public reaction toward persons affected by Ebola  Social-cultural beliefs and practices related to Ebola  Coping with and living in the aftermath of Ebola outbreaks Adaptation emerged as the single most encompassing and accommodating concept that united the various themes, categories and sub-categories. It further grounded survivors’, caregivers’ and community’s experience of anticipating, experiencing and coping with challenges associated with Ebola. The findings add substantial knowledge about how survivors and caregivers experience Ebola outbreaks. Important recommendations are made and guidelines that may be used to increase survivors’, caregivers’ as well as the community’s resilience to challenges of future Ebola outbreaks are suggested. / Health Studies / D. Lit. et Phil. (Health Science) Ebola Threat Phenomenology Lived experience Survivors Family caregivers Fear Stigma Ostracism Coping Adaptation Resilience Kibale Uganda 614.57096761
213	Living under the threat of Ebola : a phenomenological study Matua, Amandu Gerald 08 1900 (has links) This study articulates the phenomenon of living under a constant threat of Ebola haemorrhagic fever, including what people’s reactions towards individuals and families affected by the illness symbolizes as well as the meanings ascribed to Ebola. The study was conducted in Kibale district in Midwestern Uganda to aid understanding of the human aspects of Ebola which has continued to result in widespread fear and anxiety, thereby creating challenges for affected individuals, families and health care professionals. A phenomenological inquiry was undertaken using Wertz’s (1983, 2005, 2011) empirical psychological reflection approach for data analysis, after utilizing purposive, convenience and criterion sampling techniques to select twelve (12) adult survivors and caregivers who anticipated, experienced and survived the outbreak and were in good health and also willing to take part in the study. Data were generated using in-depth qualitative interviews and the interviews continued until data redundancy was reached. The interview proceedings were digitally audio-recorded in addition to taking field notes and these were transcribed verbatim. Data analysis occurred at idiographic and nomothetic levels according to the principles of Wertz’s empirical psychological reflection. Thematic analysis of the research data revealed seven (7) themes, namely:  Living under constant threat of Ebola  Nature of Ebola experience: unique and general meanings  Surviving Ebola: physical, psychological, social, spiritual and economic implications on survivors  Caring for Ebola patients: social and psychological implications  Public reaction toward persons affected by Ebola  Social-cultural beliefs and practices related to Ebola  Coping with and living in the aftermath of Ebola outbreaks Adaptation emerged as the single most encompassing and accommodating concept that united the various themes, categories and sub-categories. It further grounded survivors’, caregivers’ and community’s experience of anticipating, experiencing and coping with challenges associated with Ebola. The findings add substantial knowledge about how survivors and caregivers experience Ebola outbreaks. Important recommendations are made and guidelines that may be used to increase survivors’, caregivers’ as well as the community’s resilience to challenges of future Ebola outbreaks are suggested. / Health Studies / D. Litt. et Phil. (Health Science) Ebola Threat Phenomenology Lived experience Survivors Family caregivers Fear Stigma Ostracism Coping Adaptation Resilience Kibale Uganda 614.57096761
214	Metapopulation dynamics of dengue epidemics in French Polynesia / Dynamique métapopulationelle des épidémies de dengue en Polynésie française Teissier, Yoann 22 May 2017 (has links) La dengue circule en Polynésie française sur un mode épidémique depuis plus de 35 ans. Néanmoins, en dépit de la taille relativement faible de la population de Polynésie française, la circulation de la dengue peut persister à de faibles niveaux pendant de nombreuses années. L’objectif de ce travail de thèse est de déterminer si l'épidémiologie de la dengue dans le système insulaire de la Polynésie française répond aux critères d’un contexte de métapopulation. Après avoir constitué une base de données regroupant les cas de dengue répertoriés sur les 35 dernières années, nous avons réalisé des analyses épidémiologiques descriptives et statistiques. Celles-ci ont révélé des disparités spatio-temporelles distinctes pour l’incidence de la dengue des archipels et des îles, mais la structure de l'épidémie globale à l’échelle de la Polynésie française pour un même sérotype ne semble pas être affectée. Les analyses de la métapopulation ont révélé l'incidence asynchrone de la dengue dans un grand nombre d’îles. Celle-ci s’observe plus particulièrement par la différence de dynamique de l’incidence entre les îles plus peuplées et celles ayant une population plus faible. La taille critique de la communauté nécessaire à la persistance de la dengue n’est même pas atteinte par la plus grande île de Polynésie Française, Tahiti. Ce résultat suggère que la dengue peut uniquement persister grâce à sa propagation d’île en île. L'incorporation de la connectivité des îles à travers des modèles de migration humaine dans un modèle mathématique a produit une dynamique de la dengue davantage en adéquation avec les données observées, que les tentatives de modélisation traitant la population dans son ensemble. Le modèle de la métapopulation a été capable de simuler la même dynamique que les cas de dengue observés pour l'épidémie et la transmission endémique qui a suivi pour la période de 2001 à 2008. Des analyses complémentaires sur la différenciation de l'incidence de la maladie et de l'infection seront probablement instructives pour affiner le modèle de métapopulation de l'épidémiologie de la dengue en Polynésie française. / Dengue has been epidemic in French Polynesia for the past 35 years. Despite the relatively small population size in French Polynesia, dengue does not disappear and can persist at low levels for many years. In light of the large number of islands comprising French Polynesia, this thesis addresses the extent to which a metapopulation context may be the most appropriate to describe the epidemiology and persistence of dengue in this case. After compiling a database of dengue cases over the last 35 years, we used a number of descriptive and statistical epidemiological analyses that revealed distinct spatio-temporal disparity in dengue incidence for archipelago and islands. But the global structure of the epidemics of the same serotype were not affected. Metapopulation analyses revealed asynchronous dengue incidence among many of the islands and most notably larger islands lagged behind the smaller islands. The critical community size, which determines dengue persistence, was found to exceed even the largest island of Tahiti, suggesting that dengue can only exist by island-hopping. Incorporation of island connectedness through patterns of human migration into a mathematical model enabled a much better fit to the observed data than treating the population as a whole. The metapopulation model was able to capture to some extent the epidemic and low level transmission dynamics observed for the period of 2001-2008. Further analyses on differentiating incidence of disease and infection will likely prove informative for the metapopulation model of dengue epidemiology in French Polynesia. Dengue Épidémies Métapopulation Polynésie française Modélisation SEIR Transmission endémique Persistance Infection Migration Population Circulation insulaire Population critique Connections insulaires Modèle Logiciel R Études statistiques Identification des facteurs de risques Densité de la population Vecteur Aedes aegypti Géographie insulaire Milieu tropical Distance de vol du vecteur Immunité de la population Densité vectorielle Taux de récupération de l’hôte Mortalité du vecteur Cycle de transmission des virus Arbovirus Dynamique de la dengue Simulations Dynamique épidémique Dengue Epidemics Metapopulation French Polynesia Modeling SEIR Endemic transmission Persistence Infection Migration Population Insular circulation Critical population Insular connections Model Ordinary differential equation (ODE) R software Statistical study Risk factor identification Population density Vector Aedes aegypti Insular geography Tropical environment Vector flight distance Population immunity Vector density Host recovery rate Vector mortality Virus transmission cycle Arbovirus Dengue dynamic Simulations Epidemic dynamics 614.4

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