Le Grand-Tunis présente une vulnérabilité face à la pollution atmosphérique compte tenu des fortes densités de population et des nombreuses infrastructures caractérisant son territoire. L’ozone (O3) et les particules en suspension (PM10) dépassent fréquemment les normes tunisiennes relatives à ces polluants. Quant aux normes internationales fixées par l’OMS (Organisation Mondiale de la Santé), elles n’ont été respectées que rarement. L’appareil respiratoire constitue une voie d’exposition privilégiée aux agressions en rapport avec l’environnement. De nombreuses pathologies pulmonaires sont directement liées à l’inhalation des polluants dans l’atmosphère. Les influences des mécanismes climatiques sur la santé respiratoire sont très étendues également, notamment les épisodes météorologiques extrêmes appelés aussi paroxysmes météorologiques.L’objectif principal de cette thèse est de caractériser l’impact des facteurs environnementaux, climat et polluants atmosphériques sur la santé respiratoire dans le Grand-Tunis. Nous avons choisi de quantifier cette relation à partir des indicateurs biométéorologiques et des seuils absolus de stress météorologique, spécifiques au climat tunisois, et de la qualité de l’air pour prévoir des épisodes à risque pour la santé respiratoire. Cela est fait à partir des extrêmes météorologiques des paramètres les plus irritants pour la santé respiratoire : la température, l’humidité relative de l’air et la vitesse maximale du vent. Nous avons aussi établi des normes réalistes pour la qualité de l’air, relatives à l’O3 et aux PM10, identifiant les seuils critiques de surplus des hospitalisations dans le Grand-Tunis et qui peuvent être appliquées dans tout le pays. Compte tenu de l’effet de certains paramètres climatiques sur la dispersion des polluants dans l’atmosphère, nous avons aussi étudié la relation entre les paramètres météorologiques et les polluants d’O3 et de PM10. Les résultats de cette étude révèlent que, durant toute l’année, les tunisois sont confrontés au moins à un risque environnemental : la pollution photochimique et les vagues de chaleur, très répandues durant la saison chaude ; durant la saison froide, c’est le risque du froid et de la pollution particulaire ; et pendant les intersaisons, c’est la pollution biologique, avec les pollens, qui est le risque le plus important. Toutefois, l’exposition à court terme à ces risques, sur l’aggravation de la maladie respiratoire ou l’irritation du système respiratoire sont bien réelles. Cette recherche montre que le développement et l’aggravation des maladies respiratoires semblent découler d’une interaction complexe entre divers facteurs individuels et environnementaux. Ils sont essentiellement en relation avec le temps, la qualité de l’air et l’atopie. L’importance de ces facteurs varie selon la maladie considérée. Par ailleurs, le faible niveau socioéconomique de la famille augmente la probabilité d’être exposé à plusieurs de ces facteurs de risque. À cela s’ajoutent les facteurs comportementaux tels que l’alcool, le tabagisme actif et passif. / The Greater metropolitan area of Tunis, often referred to as Grand Tunis or Tunis, presents a vulnerability to air pollution due to the high concentrations of population and the infrastructures characterizing its territory. Ozone (O3) and particles (PM10) often exceed the Tunisian thresholds for these pollutants. As for the international standards set by the WHO (world health organization), they have not been met infrequently.The respiratory tract is a preferred route of exposure to aggressions related to the environment. Many lung diseases are directly linked to inhalation of pollutants in the atmosphere. The influences of climate mechanisms on respiratory health are also very extensive, including extreme weather events, also called weather paroxysms.The main objective of this thesis was to characterize the impact of environmental factors, climate and atmospheric pollutants on respiratory health in Grand Tunis. We have chosen to quantify this relationship from the biometeorological indicators and absolute thresholds of meteorological stress, specific Tunisian climate, and air quality to predict episodes at risk for respiratory health and thresholds of weather variables and air quality resulting in excess hospital admissions for respiratory causes. And this from the climate extremes of the parameters affecting the respiratory health : temperature, relative humidity and maximum wind speed. We, too, set realistic standards for air quality, relative to O3 and PM10, identifying critical thresholds excess hospitalizations in Grand Tunis and can be applied throughout the country. Given the effect of some climatic parameters on the dispersion of pollutants in the atmosphere, we also studied the relationship between climatic parameters and pollutants of O3 and PM10. The results of this study reveal that, throughout the year, Tunisians are confronted with at least an environmental risk : photochemical pollution and heat waves, which are very responsive during the hot season ; during the cold season, it is the risk of cold and particulate pollution; and during the off-season, biological pollution, together with pollen, is more at risk. However, short-term exposure to these risks, the worsening of the respiratory illness or irritation of the respiratory system is real. This study showed that the development and worsening of respiratory diseases appear to result from a complex interplay of individual and environmental factors. They are mainly in relation to time, air quality and atopy. The importance of these factors varies the respective disease. Moreover, the low socioeconomic status of the family increases the likelihood of being exposed to more of these risk factors. Added to this are behavioral factors such as alcohol, active and passive smoking.

For the last 22 years, systematic rapes and punitive violence against women in the Democratic Republic of Congo (DRC) were utilized as weapons of war and a control strategy. This quantitative study built upon the ecological model of impact of sexual assault on women's mental health to investigate the relationship between the health impacts and chronic pain and depression among women survivors of sexual rape in eastern DRC. The sample included 156 female rape survivors, between 18-80 years old, and raped between 2010 and 2014 while residing in the conflict area. The research questions focused on the association between fistulas, other sexual rape-related injuries, post-traumatic stress disorder (PTSD), feelings of worthlessness, social rejection, support from family/friends, and chronic pain and depression among women victims of sexual rape in eastern DRC. Results from multinomial logistic regression and ordinal regression tests showed strong links between independent and dependent variables: Fistula was strongly linked with chronic illness over 6 months (p = 0.003), and with upset all the time (p = 0.033); PTSD was associated with chronic illness due to violent rapes (p = 0.004) and sadness (p = 0.000); feelings of worthlessness was related to prolonged illness over 6 months (p = 0.024) and feeling blue (p = 0.006); social rejection was linked to avoidance (p = 0.003); and support from family/friends was associated with prolonged illness over 6 months (p = 0.025) and lack of excitement (p = 0.011). The results of this study could assist health care providers in formulating response strategies for identifying public health priorities in conflict area, addressing health needs, and defining approaches for reducing war-related sexual violence, chronic pain, and depression among rape survivors.

The problems encountered when empirical fit is used as the sole criterion for choosing a distribution to represent annual flood data are discussed. Some theoretical direction is needed for this choice. Extreme value theory is established as a viable tool for analyzing annual flood data. Extreme value distributions have been used in previous analyses of flood data. How�ver, no systematic investigation of the theory has previously been applied. Properties of the extreme value distributions are examined. The most appropriate distribution for flood data has not previously been fit to such data. The fit of the chosen extreme value distribution compares favorably with that of the Pearson and log Pearson Type III distributions.

The pathogenesis of hepatotoxic and hepatocarcinogenic actions of the mycotoxin aflatoxin B1 (AFB1) involves initial bioactivation by microsomal cytochrome P450s (P450) to a reactive and electrophilic intermediate, exo-aflatoxin B1-8,9-epoxide (exo-AFBO). Poultry, especially turkeys, are extremely sensitive to AFB1, a condition associated with efficient epoxidation by P450s. The purpose of this research was to 1) discover and characterize the P450s in turkey liver responsible for AFB1 bioactivation, and 2) determine the relative importance of these P450s in turkey liver. Initial investigations led to the discovery of CYP1A5. We then identified CYP3A37, a human CYP3A4 homologue from turkey liver, which along with CYP1A5 plays an important role in the bioactivation of AFB1 to exo-AFBO. The E. coli-expressed CYP3A37 possessed striking similarities to human CYP3A4, in terms of its catalytic activities and the kinetics of AFB1 oxidation. After the discovery of CYP3A37, further research evaluated its relative importance to CYP1A5, with respect to the epoxidation of AFB1, to determine which of the homologues bioactivated relatively low "real world" AFB1 concentrations, reflective of the potential dietary exposure. Using antibodies directed to both the enzymes as tools in immuno-inhibition experiments, we determined that CYP1A5 contributes to about 98% of the exo-AFBO formation at the low AFB1 concentrations (0.1 µM), which led us to conclude that CYP1A5 is likely the dominant homologue involved in the extreme sensitivity of the turkeys to AFB1. CYP3A37 also efficiently epoxidated AFB1, but only at high concentrations of this mycotoxin, not likely to be achievable in turkey liver in vivo. Our research has helped shed light on the relative importance of CYP1A5 and CYP3A37 in the bioactivation of AFB1 to the toxic exo-AFBO, and thus on the mechanisms of the extreme sensitivity of turkeys to AFB1. Given that AFB1 is a ubiquitous component of corn-based poultry feed and contamination is practically unavoidable, we conducted further studies evaluating the chemopreventive action of probiotic bacteria, Lactobacillus, on AFB1 toxicity in turkeys. Probiotic bacteria are known to bind AFB1, thus reducing its bioavailability. A mix of probiotic bacteria provided protection against key endpoints of aflatoxicosis, like AFB1-induced reduction in body and liver weights. Our data demonstrate that Lactobacillus was protective against aflatoxicosis in turkeys, thus validating its use as a possible chemopreventive, thereby helping alleviate the significant annual losses to the poultry industry due to feed contamination by AFB1.

La hausse des températures et les modifications du régime des précipitations affectent les écosystèmes particulièrement fragiles des régions arctiques et subarctiques et ont des conséquences socio-économiques pour les populations locales. La perception et l'évaluation des opportunités et des risques qui y sont associés, dépendent des moyens de subsistance, des normes, des valeurs et des représentations du monde des individus qui y sont confrontés.La perception du climat est culturellement et socialement construite. Cette perception varie dans le temps et dans l'espace et, parfois même, diffère parmi différents groupes sociaux en fonction des valeurs et des modes de représentation du monde. Pour toutes ces raisons, nous avons non seulement étudié certains phénomènes météorologiques mais aussi intégré le cadre culturel, politique et historique dans lesquels ils s'inscrivent. Nous avons analysé l'environnement et le climat – et par extension, les événements météorologiques à forts impacts – comme des objets socio-culturels afin de mieux comprendre à la fois leurs impacts mais aussi leurs perceptions par les habitants. Ce travail se situe à la croisée de ces chemins, en confrontant l'observation, et donc les changements, et la perception qu'en ont différents acteurs, en considérant deux régions distinctes, les mers nordiques et la République de Touva.Dans une première partie, nous avons analysés l'impact des Polar Lows, d'intenses cyclones de méso-échelle qui se développent sur les mers libres de glace de l'Arctique pendant l'hiver, sur les régions côtières du nord de la Norvège. Ces systèmes sont associés à des vents de surface forts avec bien souvent des rafales qui peuvent être très violentes (Heinemann et Claud, 1997). Les conditions en mer lors du passage d'un PL peuvent s'avérer dangereuses avec des fortes vagues, des précipitations neigeuses brutales et du blizzard. Ces événements météorologiques extrêmes représentent un véritable risque pour les activités maritimes et côtières de la région, notamment pour le transport maritime, la pêche et les plateformes pétrolières et gazières offshore. En effet, les nouvelles zones libres de glace offrent de multiples opportunités économiques dans ces régions, en particulier en mer de Barents. Or dans le même temps, le recul de la banquise élargit mécaniquement les régions de formation des PLs.Dans une seconde partie, nous avons regardé les impacts du changement climatique et des événements météorologiques sévères en République de Touva. La République de Touva se localise entre 49°5 et 53°5 N en latitude, 88°5 et le 99°E en longitude, c'est par conséquent une région subarctique très méridionale. Le climat y est extrêmement continental et les précipitations ont tendance à être faibles en raison de la faible teneur en humidité dans l'air froid. La plupart du territoire est caractérisé par une végétation forestière de taïga ou de steppe semi-aride. Au cours du XXème siècle, la région a connu des changements socio-économiques majeurs, parfois brutaux, avec notamment le passage d'une société communiste à l'économie planifiée à une économie de marché au début des années 1990. Malgré ces récents bouleversements, les pasteurs nomades (chevaux, vaches, yaks, moutons, chameaux) en Touva occidentale et les chasseurs-cueilleurs éleveurs de rennes en Touva orientale, vivent toujours en étroite relation avec l’environnement naturel. Les populations autochtones de Touva, confrontées à un changement rapide de la société et à des changements globaux causés par certaines politiques régionales et nationales contemporaines, avec notamment l’expansion de l'industrie minière et par le développement de mégaprojets (complexe hydroéléctrique, construction d'une voie chemin de fer), offrent des points de vue variés, en fonction de leurs modes de vie, sur les changements environnementaux qu'ils observent et leurs impacts sur leurs activités quotidiennes. / The perception of the climate is culturally and socially constructed. For this reason, we have studied some weather events integrating the cultural, political and historical contexts in which they occur.In a first part, we analyzed the impact of Polar Lows, intense mesocyclones that develop over ice-free Arctic seas during winter time, on coastal regions of Norway. The passage of PL can provoke dangerous sea conditions with strong waves, sudden snowfall and blizzard. This phenomenon may represent a risk to maritime and coastal activities in the region, particularly for shipping, fishing and oil and gas offshore platforms.In a second part we studied the impacts of climate change and severe weather events in the Republic of Tuva. Tuva is a very southern subarctic region. Its climate is extremely continental and precipitation tend to be low due to the low moisture content in the cold air. During the twentieth century, the region has experienced major socio-economic changes, sometimes brutal, including the transition from a communist and planned economy to a market economy in the early 1990. Despite these recent changes, pastoralists in western Tuva (horses, cows, yaks, sheep, camels) and reindeer herders in eastern Tuva, still live in close contact with the natural environment. Indigenous peoples of Tuva are facing global changes caused by certain contemporary regional and national policies, including the expansion of the mining industry and the development of mega projects. They offer different points of view, describing environmental changes and their impact on their daily activities.

Indiana University-Purdue University Indianapolis (IUPUI) / Geospatial analysis is a generic term describing several technologies or methods of computational analysis using the Earth as a living laboratory. These methods can be implemented to assess risk and study preventative mitigation practices for Public Health. Through the incorporation Geographic Information Science and Remote Sensing tools, data collection can be conducted at a larger scale, more frequent, and less expensive that traditional in situ methods. These techniques can be extrapolated to be used to study a variety of topics. Application of these tools and techniques were demonstrated through Public Health research. Although it is understand resolution, or scale, of a research project can impact a study’s results; further research is needed to understand the extent of the result’s bias. Extreme heat vulnerability analysis was studied to validate previously identified socioeconomic and environmental variables influential for mitigation studies, and how the variability of resolution impacts the results of the methodology. Heat was also investigated for the implication of spatial and temporal resolution, or aggregation, influence on results. Methods studying the physical and socioeconomic environments of Dengue Fever outbreaks were also studied to identify patters of vector emergence.

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This dissertation implements an optimal trading strategy based on the machine learning method and extreme value theory (EVT) to obtain an excess return on investments in the capital market. The trading strategy outperforms the benchmark S&P 500 index with higher returns and lower volatility through effective market timing. In addition, this dissertation starts by modeling the market tail risk using the EVT and reinforcement learning methods, distinguishing from the traditional value at risk method. In this dissertation, I used EVT to extract the characteristics of the tail risk, which are inputs for reinforcement learning. This process is proved to be effective in market timing, and the trading strategy could avoid market crash and achieve a long-term excess return. In sum, this study has several contributions. First, this study takes a new method to analyze stock price (in this dissertation, I use the S&P 500 index as a stock). I combined the EVT and reinforcement learning to study the price tail risk and predict stock crash efficiently, which is a new method for tail risk research. Thus, I can predict the stock crash or provide the probability of risk, and then, the trading strategy can be built. The second contribution is that this dissertation provides a dynamic market timing trading strategy, which can significantly outperform the market index with a lower volatility and a higher Sharpe ratio. Moreover, the dynamic trading process can provide investors an intuitive sense on the stock market and help in decision-making. Third, the success of the strategy shows that the combination of EVT and reinforcement learning can predict the stock crash very well, which is a great improvement on the extreme event study and deserves further study. / Business Administration/Finance

Adaptation to climate change requires a careful evaluation of the infrastructure performance under extreme events in a changing climate. Earthen levees are critical infrastructure systems, which play a vital role to the country’s safety, environment, and economic security. The main objective of this study is to quantitatively assess the integrity of earthen levees subject to extreme precipitation and flooding under a changing climate. A multi-disciplinary modeling framework is developed and applied to two earthen levees, Elkhorn and Sherman Island levees, in California. Patterns of extreme precipitation and flooding are obtained for the study areas under current and future climate. A nonstationary framework is employed, which accounts for climate change-induced changes in statistics of future extreme precipitation. The precipitation and flooding data are then applied as hydraulic loads in a set of fully coupled stresslow finite element simulations to determine the factory of safety (FOS) and probability of failure (Pf) of the levees for different scenarios. The Pf values are used to develop fragility curves, which can provide valuable tools for risk assessments. The modeling framework is used to study three distinct yet interrelated problems. The first problem assesses the performance of the Elkhorn levee using historical and projected future precipitation patterns. The results show that Pf increases 3%-12% under the projected extreme precipitation compared to the baseline scenario. The second problem involves quantifying the effects of changes in future streamflow on the fragility behavior of the Elkhorn levee considering multiple modes of failure. For the cases examined, incorporating future floods leads to up to 23% reduction in FOS and 95% increase in Pf. The third problem assesses the fragility behavior of the Sherman Island levee under compound flooding (induced by coastal, fluvial and pluvial processes), an overlooked aspect in the majority of the existing flood hazard analyses. Results show that considering compound flooding leads to 22% and 30% reductions in FOS for 2- and 50-year recurrence intervals, respectively. Using the projected future pluvial flooding increases Pf by 13%. Findings of this research suggest that risk assessments based on historical records can significantly underestimate the levee’s Pf in a changing climate.

Surrogate models are indispensable in the analysis of engineering systems. The quality of surrogate models is determined by the data quality and the model class but achieving a high standard of them is challenging in complex engineering systems. Heterogeneity, implicit constraints, and extreme events are typical examples of the factors that complicate systems, yet they have been underestimated or disregarded in machine learning. This dissertation is dedicated to tackling the challenges in surrogate modeling of complex engineering systems by developing the following machine learning methodologies. (i) Partitioned active learning partitions the design space according to heterogeneity in response features, thereby exploiting localized models to measure the informativeness of unlabeled data. (ii) For the systems with implicit constraints, failure-averse active learning incorporates constraint outputs to estimate the safe region and avoid undesirable failures in learning the target function. (iii) The multi-output extreme spatial learning enables modeling and simulating extreme events in composite fuselage assembly. The proposed methods were applied to real-world case studies and outperformed benchmark methods. / Doctor of Philosophy / Data-driven decisions are ubiquitous in the engineering domain, in which data-driven models are fundamental. Active learning is a subdomain in machine learning that enables data-efficient modeling, and extreme spatial modeling is suitable for analyzing rare events. Although they are superb techniques for data-driven modeling, existing methods thereof cannot effectively address modern engineering systems complicated by heterogeneity, implicit constraints, and rare events. This dissertation is dedicated to advancing active learning and extreme spatial modeling for complex engineering systems by proposing three methodologies. The first method is partitioned active learning that efficiently learns systems, changing their behaviors, by localizing the information measurement. Second, failure-averse active learning is established to learn systems subject to implicit constraints, which cannot be analytically solved, and to minimize constraint violations. Lastly, the multi-output extreme spatial model is developed to model and simulate rare events that are associated with extremely large values in the aircraft manufacturing system. The proposed methods overcome the limitations of existing methods and outperform benchmark methods in the case studies.