Cette étude est consacrée à la modélisation spatio-temporelle de la pollution atmosphérique urbaine en utilisant un ensemble de méthodes statistiques exploitant les mesures de concentrations de polluants (NO2, O3) fournies par un réseau de surveillance de la qualité de l'air (AIRPARIF). Le principal objectif visé est l'amélioration de la cartographie des champs de concentration de polluants (le domaine d'intérêt étant la région d'Île-de-France) en utilisant, d'une part, des méthodes d'interpolation basées sur la structure spatiale ou spatio-temporelle des observations (krigeage spatial ou spatio-temporel), et d'autre part, des algorithmes, prenant en compte les mesures, pour corriger les sorties d'un modèle déterministe (Filtre de Kalman d'Ensemble). Les résultats obtenus montrent que dans le cas du dioxyde d'azote la cartographie basée uniquement sur l'interpolation spatiale (le krigeage) conduit à des résultats satisfaisants, car la répartition spatiale des stations est bonne. En revanche, pour l'ozone, c'est l'assimilation séquentielle de données appliquée au modèle (CHIMERE) qui permet une meilleure reconstitution de la forme et de la position du panache pendant les épisodes de forte pollution analysés. En complément de la cartographie, un autre but de ce travail est d'effectuer localement la prévision des niveaux d'ozone sur un horizon de 24 heures. L'approche choisie est celle mettant en œuvre des méthodes de type réseaux neuronaux. Les résultats obtenus en appliquant deux types d'architectures neuronales indiquent une précision correcte surtout pour les 8 premières heures de l'horizon de prédiction / This study is devoted to the spatio-temporal modelling of air pollution at a regional scale using a set of statistical methods in order to treat the measurements of pollutant concentrations (NO2, O3) provided by an air quality monitoring network (AIRPARIF). The main objective is the improvement of the pollutant _elds mapping using either interpolation methods based on the spatial or spatio-temporal structure of the data (spatial or spatiotemporal kriging) or some algorithms taking into account the observations, in order to correct the concentrations simulated by a deterministic model (Ensemble Kalman Filter). The results show that nitrogen dioxide mapping based only on spatial interpolation (kriging) gives the best results, while the spatial repartition of the monitoring sites is good. For the ozone mapping it is the sequential data assimilation that leads us to a better reconstruction of the plume's form and position for the analyzed cases. Complementary to the pollutant mapping, another objective was to perform a local prediction of ozone concentrations on a 24-hour horizon; this task was performed using Artificial Neural Networks. The performance indices obtained using two types of neural architectures indicate a fair accuracy especially for the first 8 hours of prediction horizon

Dans le monde industriel comme dans le monde scientifique, le développement de capteurs a toujours répondu à la volonté d’observer l’inobservable. La caméra rapide fait partie de ceux-là puisqu’elle permet de dévoiler des dynamiques invisibles, de la formation de fissure au vol du moustique. Dans un environnement extrêmement concurrentiel, ces caméras sont principalement limitées par le nombre d’images acquises par seconde. Le but de cette thèse est d’augmenter la capacité de dévoiler la dynamique invisible en enrichissant l’acquisition initiale par des modèles dynamiques. La problématique consiste alors à élaborer des méthodes permettant de relier en temps réel un modèle et la perception d’un système réel. Les bénéfices de cette utilisation offrent ainsi la possibilité de faire de l’interpolation, de la prédiction et de l’identification. Cette thèse est composée de trois parties. La première est axée sur la philosophie du traitement vidéo et propose d’utiliser des modèles élémentaires et génériques. Un algorithme d’estimation de grands mouvements est proposé mais l’approche actuellement proposée n’est pas assez générique pour être exploitée dans un contexte industriel. La deuxième partie propose d’utiliser des méthodes d’assimilation de données séquentielle basées sur la famille des filtres de Kalman afin d’associer un modèle avec des observations par caméras rapides pour des systèmes mécaniques. La troisième partie est une application à l’analyse modale expérimentale non linéaire. Deux schémas d’assimilation temps réel multicapteurs sont présentés et leur mise en œuvre est illustrée pour de la reconstruction 3D et de la magnification. / The development of sensors has always followed the ambition of industrial and scientific people to observe the unobservable. High speed cameras are part of this adventure, revealing invisible dynamics such as cracks formation or subtle mosquito flight. Industrial high speed vision is a very competitive domain in which cameras stand out through their acquisition speed. This thesis aims to broaden their capacity by augmenting the initial acquisition with dynamic models. This work proposes to develop methods linking in real time a model with a real system. Aimed benefits are interpolation, prediction and identification. Three parts are developed. The first one is based on video processing and submits to use kinematic elementary and generic models. An algorithm of motion estimation for large movements is proposed but the generic nature does not allow a sufficient knowledge to be conclusive. The second part proposes using sequential data assimilation methods known as Kalman filters. A scheme to assimilate video data with a mechanical model is successfully implemented. An application of data assimilation in modal analysis is developed. Two multi sensors real time assimilation schemes for nonlinear modal identification are proposed. These schemes are integrated in two applications on 3D reconstruction and motion magnification.

Depuis la révolution industrielle, les croissances économique et démographique ont augmenté de manière exponentielle induisant l’augmentation de la combustion d’énergies fossiles, telles que le charbon, le pétrole, et le gaz naturel. La combustion de ces sources d’énergie conduit à l’émission de gaz à effet de serre, principalement le dioxyde de carbone (CO2) et le méthane (CH4), qui par leur accumulation dans l’atmosphère entraînent une augmentation de l’effet de serre. Selon le GIEC (Groupe d'experts Intergouvernemental sur l'Évolution du Climat), l’implication des émissions anthropiques dans l’augmentation de l’effet de serre est extrêmement probable avec un pourcentage de certitude qui dépasse 95%. Toutefois, l’estimation des bilans régionaux d'émissions de GES reste très incertaine. L’objectif de cette thèse est de contribuer à l’amélioration de l’estimation des bilans régionaux de GES en France, en utilisant pour la première fois les concentrations atmosphériques du CO2 et de CH4 mesurées par le réseau ICOS (Integrated Carbon Observation System) et la modélisation inverse à l’échelle régionale.Dans un premier temps, on s’est focalisé sur l’étude des concentrations mesurées de CO2, CH4 et CO (monoxyde de carbone) fournis par des stations de surface. Cette étude a pour objectif l'identification des mesures atmosphériques contaminées par les émissions locales (quelques kilomètres au tour de la station) et qui provoque ce qu’on appelle « les pics de concentrations ». Trois méthodes ont été appliquées sur des séries temporelles fournies par quatre stations du réseau ICOS, afin de déterminer leur degré de contamination. Les résultats des différentes méthodes ont été comparés entre eux, puis comparés à un inventaire de données contaminées préparé manuellement par les gestionnaires des stations. Cette comparaison a permis l’évaluation de la performance des trois méthodes pour la détection réussie des pics. À l’issue de ce travail, la méthode la plus performante a été proposée pour effectuer un nettoyage automatique des séries de mesure du réseau ICOS.Dans un deuxième temps, le modèle régional de chimie-transport CHIMERE est utilisé pour simuler les concentrations atmosphériques du CO2 et du CH4 de l’année 2014 sur un domaine centré sur la France. L’objectif de cette étude est d’étudier la sensibilité des concentrations simulées en utilisant différentes données d’entrées. Premièrement, on étudie la sensibilité des concentrations simulées par rapport au transport en utilisant deux modèles météorologiques AROME et ECMWF. Deuxièmes, on analyse la sensibilité des concentrations simulées face aux différentes cartes d’émissions. Dans cette dernière étape, on étudie les différences entre les cartes d’émissions anthropiques séparément des cartes d’émissions biogéniques. Ce travail nous permet de quantifier à la fois les erreurs liées aux transports et les erreurs liées aux flux d’émissions. La meilleure combinaison des données d’entrée va être sélectionnée pour l’étape d’inversion des flux.Dans un dernier plan, les mesures atmosphériques des concentrations de CO2 et du CH4 sont utilisées par le système d’inversion PYMAI (Berchet et coll., 2013 et 2015) afin d’estimer les bilans régionaux d'émissions des principaux GES en France. L’inversion s’est exécutée pour un mois d’hiver (janvier) et un mois d’été (juillet) en utilisant le modèle de transport CHIMERE forcé par ECMWF et les flux de surface (EDGAR et VPRM). Le résultat de ce travail permet une réduction des incertitudes des bilans nationaux à hauteur de 35 %, et la quantification les émissions de CO2 et de CH4 à l'échelle nationale et régionale. Par contre, cette inversion ne contraint que partiellement les flux d’émissions. Cependant, la question sur l’efficacité de la quantité d’informations disponibles ressort à nouveau. / Since the industrial revolution, the economic and the demographic growths have increased exponentially,leading to an enhancement of the fossil fuels combustion, such as coal, oil, and natural gas. Consumingthese source of energy amplifies the greenhouse gas emissions, mainly carbon dioxide (CO2) and methane(CH4), whose accumulation in the atmosphere lead to the increase of the greenhouse effect. According tothe 5th assessment report of the Intergovernmental Panel on Climate Change (IPCC), it is extremely likely(95-100% of certainty) that the observed increase in the greenhouse effect is related to the increase of theanthropogenic emissions. However, the estimations of the GHG budget at the regional and the nationalscales remains highly uncertain. The aim of this thesis is to improve the estimation of the CO2 and CH4fluxes in France, using data assimilation techniques and atmospheric measurements provided by theIntegrated Carbon Observation System (ICOS) network.The first phase focuses on analyzing the measured CO2, CH4, and CO (Carbon monoxide) atmosphericconcentrations provided by surface monitoring stations. This study is concerned with the problem ofidentifying atmospheric data influenced by local emissions that can result in spikes in the GHG time series.Three methods are implemented on continuous measurements of four contrasted atmospheric sites. The aimof this analysis is to evaluate the performance of the used methods for the correctly detect the contaminateddata. This work allows us to select the most reliable method that was proposed to perform daily spikedetection in the ICOS Atmospheric Thematic Centre Quality Control (ATC-QC) software.Secondly, we simulate the atmospheric concentrations of CO2 and CH4 using the chemistry transport modelCHIMERE in a domain centered over France for the year 2014. The objective of this study is to evaluate thesensitivity of simulated concentrations using different input data (sensitivity to the meteorological transportand sensitivity to the surface fluxes). This work led to the quantification of both the transport and surfacefluxes errors based on the combination of different simulations. Thus, the most reliable combination of thebest input data was selected for the flux inversion study.Lastly, the measured CO2 and CH4 concentrations are used by the PYMAI inversion system (Berchet et al.,2013 and 2015) in order to estimate the CO2 and CH4 fluxes in France. The Inversion is performed for onemonth in winter (January) and one month in summer (July), using the transport model CHIMERE. Theinversion results have provided very interesting results for the regional estimation of the CO2 and CH4surface fluxes in France with an uncertainty reduction that may attain 35% of the national totals.

Depuis plusieurs années, les évolutions considérables survenues au niveau des moyens de calcul à disposition ont entraîné de nouvelles pratiques de simulation des structures mécaniques. Parmi ces nouvelles pratiques celle qui motive ces travaux de thèse est le paradigme Dynamic Data Driven Application Systems (DDDAS). L’idée fondatrice de cette approche est de mettre en place un dialogue entre un système physique et son modèle numérique. L’objectif est alors de (i) permettre un recalage du modèle numérique à l’aide de mesures faites sur le système physique ; (ii) contrôler l’évolution du système physique à l’aide de la prédiction faite par la simulation numérique. La difficulté majeure est de réaliser ce dialogue en temps réel. Ces travaux de thèse se focalisent sur l’étape de recalage de modèle du paradigme DDDAS. La problématique est alors de développer des méthodes et outils de résolution de problèmes inverses prenant en compte diverses contraintes à savoir : (i) une robustesse vis-à-vis des données corrompues ; (ii) une généricité permettant de considérer une grande variété de problèmes et de modèles mécaniques ; (iii) un temps de calcul réduit afin de tendre vers un recalage de modèle en temps réel. Le point de départ de ces travaux est l’Erreur en Relation de Comportement modifiée, approche énergétique dédiée à la résolution des problèmes inverses en mécanique, s’étant notamment illustrée par sa grande robustesse vis-à-vis des bruits de mesure. Dans un premier temps, afin de garantir un processus d’identification rapide, nous avons couplé l’Erreur en Relation de Comportement modifiée avec la réduction de modèle PGD dans le cadre de modèle linéaire, permettant ainsi de mettre en place un processus d’identification rapide et automatique. Ensuite, dans le but d’être appliquée au paradigme DDDAS, nous avons développé une démarche d’identification reposant sur un processus d’assimilation de données (le filtre de Kalman) et utilisant l’Erreur en Relation de Comportement modifiée comme opérateur d’observation toujours dans le cadre de problèmes linéaires. Nous avons ensuite étendu cette méthode d’assimilation de données à la problématique de l’identification de champs de paramètres en introduisant une séparation des discrétisations spatiales et des outils provenant de l’adaptation de maillage. Nous avons ensuite abordé la problématique des modèles mécaniques non-linéaires, au travers de modèles d’endommagement et de visco-plasticité. Pour cela nous avons dans un premier temps reformulé et étendu le concept d’Erreur en Relation de Comportement modifiée à ce cadre non-linéaire matériau et nous avons mis en place un processus de résolution dédié, s’inspirant de la méthode LaTIn. Pour finir nous avons introduit cette reformulation de l’Erreur en Relation de Comportement modifiée au sein de la méthode d’assimilation de données développée précédemment afin de traiter le recalage dynamique de modèles non-linéaires. / For several years, the considerable changes that have occurredin computing tools have led to new practices in the simulation of mechanical structures. Among them, the motivation for this work is the Dynamic Data Driven Application Systems paradigm (DDDAS). The founding idea of this approach is to establish a dialogue between a physical system and its numericalmodel. The objective is then to (i) allow a calibration of the numerical model by means of measurements performed on the physical system; (ii) control the evolution of the physical system using theprediction given by numerical simulation. The major difficulty is to realize this dialogue in real time. This work focuses on the model updating step of the DDDAS paradigm. The problem is then to develop methods and tools to solve inverse problems taking into account various constraints, namely: (i) robustness with respect to corrupted data; (ii) genericity for considering a wide variety of problems and mechanical models; (iii) a reduced computation time in order to tend towards a real-time model updating.The starting point of this work is the modified Constitutive Relation Error, an energetic approach dedicated to the solution of inverse problems in mechanics, notably illustrated by its robustness with respect to measurement noises. First, in order to guarantee a fast identification process, we have coupled the modified Constitutive Relation Error with the PGD model reduction in the linear model framework, thus enabling a fast and automatic identification process. Then, in order to be applied to the DDDAS paradigm, we have developed an identification method based on a data assimilation process (the Kalman filter) and using the modified Constitutive Relation Error as an observer alwayswithin the framework of linear problems. We have then extended this data assimilation approach to the problem of the identification of parameter fields by introducing a separation of the spatial discretizations and by introducing tools resulting from the mesh adaptation framework. We have then addressed the problem of non-linear mechanical models, through damage and visco-plasticitymodels. To this end, we have first recast and extended the concept of the modified Constitutive Relation Error to this nonlinear material framework and we have implemented a dedicated resolution process, based on the LaTIn method. Finally, we have introduced this reformulation of the modified Constitutive Relation Error in the previously data assimilation method in order to process the model updating of nonlinear models.

Intimate partner violence (IPV), typically considered in the domestic context, has been shown to have considerable effects on women's employment and health. While the literature has recently grown in this area, very few studies have examined the prevalence of work-related IPV among men. Furthermore, the extant literature on work-related IPV has largely ignored the experience of ethnic minorities, specifically Latinos. Many factors suggest that rates and forms of IPV might be different among other racial and ethnic groups. Some studies that examine IPV among Latinos have sought to understand the role of acculturation and socioeconomic contexts. The purpose of this study was to examine work-related IPV among a sample of men enrolled in batterer intervention programs. In addition, we sought to examine the relationship between acculturation, socioeconomic contexts, and reports of work-related IPV among a subset of male Latinos. Overall, the findings confirm the upper ranges of previous estimates across studies (36% to 75%) of employed victims of IPV and their harassment by abusive partners while at work (Swanberg, Logan, & Macke, 2005; Taylor & Barusch, 2004). Specifically, we found that 60% of the entire sample reported work-related IPV that involved threatening behaviors and physical violence at their partner's job. The findings among Latinos suggest that a positive relationship exists between acculturation and work-related IPV. Specifically, proxy variables of acculturation (e.g., country of birth, language of survey, number of years in the U.S.) were hypothesized to be positively associated with higher levels of acculturation. Consistent with the hypotheses, we found significant relationships in the direction proposed. Lastly, socioeconomic status (e.g., income, education, employment status) was hypothesized to play a moderating role between acculturation and work-related IPV. However, results generally suggest that socioeconomic status (i.e., income, education) did not moderate the relationship between acculturation and work-related IPV. This study makes important contributions to the literature and has implications for employers. The significant rates of work-related IPV found in this study highlight the need to address this problem among employed males as an important step in preventing work-related IPV. Among Latinos, the level of acculturation and factors such as income, employment, and education are important contextual factors that provide a better understanding of IPV in Latino communities (Gryywacz, Rao, Gentry, Marin, & Arcury, 2009).

Ensemble-based methods have gained widespread popularity in the field of data assimilation. An ensemble of model realizations encapsulates information about the error correlations driven by the physics and the dynamics of the numerical model. This information can be used to obtain improved estimates of the state of non-linear dynamical systems such as the atmosphere and/or the ocean. This work develops efficient ensemble-based methods for data assimilation. A major bottleneck in ensemble Kalman filter (EnKF) implementations is the solution of a linear system at each analysis step. To alleviate it an EnKF implementation based on an iterative Sherman Morrison formula is proposed. The rank deficiency of the ensemble covariance matrix is exploited in order to efficiently compute the analysis increments during the assimilation process. The computational effort of the proposed method is comparable to those of the best EnKF implementations found in the current literature. The stability analysis of the new algorithm is theoretically proven based on the positiveness of the data error covariance matrix. In order to improve the background error covariance matrices in ensemble-based data assimilation we explore the use of shrinkage covariance matrix estimators from ensembles. The resulting filter has attractive features in terms of both memory usage and computational complexity. Numerical results show that it performs better that traditional EnKF formulations. In geophysical applications the correlations between errors corresponding to distant model components decreases rapidly with the distance. We propose a new and efficient implementation of the EnKF based on a modified Cholesky decomposition for inverse covariance matrix estimation. This approach exploits the conditional independence of background errors between distant model components with regard to a predefined radius of influence. Consequently, sparse estimators of the inverse background error covariance matrix can be obtained. This implies huge memory savings during the assimilation process under realistic weather forecast scenarios. Rigorous error bounds for the resulting estimator in the context of data assimilation are theoretically proved. The conclusion is that the resulting estimator converges to the true inverse background error covariance matrix when the ensemble size is of the order of the logarithm of the number of model components. We explore high-performance implementations of the proposed EnKF algorithms. When the observational operator can be locally approximated for different regions of the domain, efficient parallel implementations of the EnKF formulations presented in this dissertation can be obtained. The parallel computation of the analysis increments is performed making use of domain decomposition. Local analysis increments are computed on (possibly) different processors. Once all local analysis increments have been computed they are mapped back onto the global domain to recover the global analysis. Tests performed with an atmospheric general circulation model at a T-63 resolution, and varying the number of processors from 96 to 2,048, reveal that the assimilation time can be decreased multiple fold for all the proposed EnKF formulations.Ensemble-based methods can be used to reformulate strong constraint four dimensional variational data assimilation such as to avoid the construction of adjoint models, which can be complicated for operational models. We propose a trust region approach based on ensembles in which the analysis increments are computed onto the space of an ensemble of snapshots. The quality of the resulting increments in the ensemble space is compared against the gains in the full space. Decisions on whether accept or reject solutions rely on trust region updating formulas. Results based on a atmospheric general circulation model with a T-42 resolution reveal that this methodology can improve the analysis accuracy. / Ph. D.

I dagens samhälle berör integrationspolitiken en av de viktigaste samhällsfrågorna för invånarna i Sverige men när det kommer till begreppet integration så finns det en tvetydighet kring begreppet och förhållningssättet. Vidare finns det också en diskursiv påverkan kring begreppet gjord av politiker. Syftet med uppsatsen utgår från att se hur diskursen kring integration hålls av vår nuvarande regering samt Sverigedemokraterna, om den håller sig till den teoretiska definitionen och vilken påverkan diskursen har över samhället. Den kommer att försöka besvara frågeställningarna ”Vilken diskurs kring integration förs av dagens regering och Sverigedemokraterna?” och ”Hur förhåller sig deras diskurser till teoretiska begreppsdefinitioner och teoretiska perspektiv?” samt ”Vad för påverkan kan den politiska diskursen kring integration ha när det kommer till samhället?”. Utifrån en diskursanalys inspirerad utifrån Foucaults förståelse av den har jag analyserat diskursen kring integration som visas på partiernas hemsidor samt i Tidöavtalet som de gemensamt skrivit. I användandet av teorier och teoretiska begrepp som berör integration kunde jag finna att den diskurs som analyseras egentligen inte förespråkar integration utan förespråkar assimilation samtidigt som den leder till en segregation i samhället mellan majoritetssamhället och minoritetssamhället. Min forskning visar alltså att dagens politiker använder ordet integration i deras politik men förespråkar en politik som inte är för integration. / Today, integration politics touches one of the most important social issues for the inhabitants of Sweden, but when it comes to the concept of integration, there is an ambiguity surrounding it and the way to approach it. Furthermore, there is also a discursive influence around integration made by politicians. The aim of the essay is based on seeing how the discourse around integration is held by our current government and the Swedish Democrats, whether it adheres to the theoretical definition and what impact the discourse has on society. It will try to answer the questions "Which discourse around integration is being held by today's government and the Swedish Democrats?" and "How do their discourses relate to theoretical conceptual definitions and theoretical perspectives?" and "What impact can this political discourse around integration have when it comes to society?". Based on a discourse analysis inspired by Foucault's understanding of it, I have analyzed the discourse around integration that appears on the parties' websites and in the Tidö-agreement that they jointly wrote. In the use of theories and theoretical concepts that concern integration, I could find that the discourse being analyzed does not really advocate integration but advocates assimilation. It also leads to a segregation in society between the majority society and the minority. My research thus shows that today's politicians use the word integration in their politics but advocate a policy that is not for integration.

Studien behandlar ackommodation, assimilation och transfer efter en företagsintern utbildning med fokusområdet personliga styrkor. Uppsatsens teoretiska grund ligger i att ackommodation, assimilation och transfer är tre centrala pedagogiska fenomen som behöver tacklas inom skola och arbetsliv. Tidigare forskning belyser vikten av att ny kunskap går att överföra och använda i praktiken när en organisation investerar i lärande. Att utvärdera lärprocessen är därmed viktigt för att bedöma effektivitet och effekt av utbildningsprogram. Genom en triangulering, innehållande tre kvalitativa metoder, samlades data in som sedan analyserades med hjälp av Kirkpatricks modell för att utvärdera lärande. Målsättningen var att avgöra vilket resultat som uppnåtts av den genomförda utbildningen samt att besvara frågeställningen om huruvida utbildningsdeltagarna såg sitt lärande som assimilativt eller ackommodativt. Författarna visar på ett resultat där både ackommodativt och assimilativt lärande kan anses ha uppstått. Ett år efter utbildningsinsatsen kan konstateras att positiv transfer till viss del skett och kursen har gett en upplevelse av Aha snarare än Blaha.

Doctor of Philosophy / Department of Sociology, Anthropology, and Social Work / Robert K. Schaeffer / The United States has resettled unaccompanied minors before. In the 1960s and 1970s, minors from Indochina were resettled in the United States. In the 1970s, the U.S accepted 14,000 unaccompanied minors from Cuba through Operation Peter Pan. Many of these Cuban minors, aged five to eighteen, were sent to the United States by parents fearing their children would be indoctrinated in communist schools. In the case of these minors, they arrived in the United States with the consent of their still-living family members. In contrast, about 3,500 Sudanese Lost Boys were resettled in the United States in 2000, and more recently in 2010, 53 “lost children” from Haiti were brought to the United States following a devastating earthquake. This study investigated the integration and assimilation patterns of the Sudanese Lost Boys in the Kansas City area with the purpose of understanding the sociological impact on these Boys from their own perspective. As opposed to previous studies done on these Boys in Kansas and other areas in the United States, the present study used interview-based research and analyzed data using both qualitative and quantitative research methodologies. The study concluded that the Lost Boys were both “Lost” and “Found” in complex ways. The study found that unaccompanied refugees labeled as minors at the time of resettlement integrated more “successfully” than those resettled as adults. Minor Boys received certain advantages over Boys who were labeled legal adults. Over time, those resettled as minors accumulated more social capital relevant in American society, while those resettled as legal adults fell behind. The findings highlighted problems associated with age-based treatment of refugees, especially in the case of the Boys who were arbitrarily classified as adults. Assigned ages significantly impacted their assimilation process into American society. Unlike those Boys resettled as minors, legal adults did not have access to structure and immersion opportunities afforded by foster families, formal education, and social activities. This study concluded that age-based disadvantage was evident in the case of the Lost Boys.

Doctor of Philosophy / Department of Grain Science and Industry / Praveen V. Vadlani / Lactic acid is an important platform chemical that has long history and wide applications in food, polymer, pharmaceutics and cosmetic industries. Lactic acid has two optical isomers; namely D-lactic acid and L-lactic acid. Racemic mixture of lactic acid are usually used as preservatives and ingredients in solvents, or as precursors for different chemicals. Currently there is an increasing demand of optical pure lactic acid as a feedstock for the production of poly-lactic acid (PLA). PLA is a biodegradable, biocompatible and environmental friendly alternative to plastics derived from petroleum based chemicals. Optically pure D or L-lactic acid is used for the synthesis of poly D or L- lactic acid (PDLA, PLLA). Blend of PDLA with PLLA results in a heat-resistant stereocomplex PLA with excellent properties. As a consequence, large quantity of cost effective D-lactic acid is required to meet the demand of stereocomplex PLA. Lignocellulosic biomass is a promising feedstock for lactic acid production because of its availability, sustainability and cost effectiveness compared to refined sugars and cereal grain-based sugars. Commercial use of lignocellulosic biomass for economic production of lactic acid requires microorganisms that are capable of using all sugars derived from lignocellulosic biomass. Therefore, the objectives of this study were: 1) to produce high level of optically pure D-lactic acid from lignocellulosic biomass-derived sugars using a homofermentative strain L. delbrueckii via simultaneous saccharification and fermentation (SSF); 2) to develop a co-culture fermentation system to produce lactic acid from both pentose and hexose sugars derived from lignocellulosic biomass; 3) to produce D-lactic acid by genetically engineered L. plantarum NCIMB 8826 ∆ldhL1 and its derivatives; 4) to construct recombinant L. plantarum by introduction of a plasmid (pLEM415-xylAB) used for xylose assimilation and evaluate its ability to produce D-lactic acid from biomass sugars; and 5) to perform metabolic flux analysis of carbon flow in Lactobacillus strains used in our study. Our results showed that D-lactic acid yield from alkali-treated corn stover by L. delbrueckii and L. plantarum NCIMB 8826 ∆ldhL1 via SSF were 0.50 g g[superscript]-1 and 0.53 g g[superscript]-1 respectively; however, these two D-lactic acid producing strains cannot use xylose from hemicellulose. Complete sugar utilization was achieved by co-cultivation of L. plantarum ATCC 21028 and L. brevis ATCC 367, and lactic acid yield increased to 0.78 g g[superscript]-1 from alkali-treated corn stover, but this co-cultivation system produced racemic mixture of D and L lactic acid. Simultaneous utilization of hexose and pentose sugars derived from biomass was achieved by introduction of two plasmids pCU-PxylAB and pLEM415-xylAB carrying xylose assimilation genes into L. plantarum NCIMB 8826 ∆ldhL1, respectively; the resulting recombinant strains ∆ldhL1-pCU-PxylAB and ∆ldhL1-pLEM415-xylAB used xylose and glucose simultaneously and produced high yield of optically pure D-lactic acid. Metabolic flux analysis verified the pathways used in these Lactobacillus strains and provided critical information to judiciously select the desired Lactobacillus strain to produce lactic acid catering to the composition of raw material and the optical purity requirement. This innovative study demonstrated strategies for low-cost biotechnological production of tailor-made lactic acid from specific lignocellulosic biomass, and thereby provides a foundational manufacturing route for a flexible and sustainable biorefinery to cater to the fuel and chemical industry.