Indiana University-Purdue University Indianapolis (IUPUI) / Metabolic flux analyses and their more comprehensive forms, genome-scale metabolic networks (GSMNs), have gained tremendous attention in industrial and medical research. Saccharomyces cerevisiae (S. cerevisiae) is one of the organisms that has had its GSMN subjected to multiple frequent updates. The objective of this study is to develop a visualization tool for the GSMN of S. cerevisiae for educational and research purposes. This visualization tool is called the Master Metabolic Map of Saccharomyces cerevisiae (MMMSC). In this study, a metabolic database of S. cerevisiae developed by us was transferred to Cytoscape, a useful and efficient bioinformatics software platform for visualizing molecular networks. After the MMMSC was created, nodes, representing metabolites and enzymes, and edges, representing the chemical reactions that connect the nodes, were curated manually to develop a metabolic visualization map of the whole metabolic system of S. cerevisiae (Figure 4). In the discussion, examples are provided regarding possible applications of MMMSC to predict possible effects of the manipulation of the S. cerevisiae metabolome for industrial and medical purposes. Ultimately, it is concluded that further work is needed to complete the metabolic database of S. cerevisiae and the related MMMSC. In future studies, these tools may be integrated with other omics and other approaches, especially the directed-evolution approach, to increase cost and time efficiency of future research and to find solutions for complex and, thus far, poorly managed environmental and health problems.

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Odor problems are a common complaint from residents living near landfills. Many compounds can cause malodorous conditions. However, hydrogen sulfide (h2s) has been identified as a principal odorous component from construction and demolition (c&d)debris landfills. Although several studies have reported the ambient concentrations of h2s near c&d landfills, few studies have quantified emission rates of h2s. The most widely used and proven technique for measuring gas emission rates from landfills is the flux chamber method. Typically the flux chamber is a cylindrical enclosure device with a spherical top which limits the gas emission area. Pure zero grade air is introduced into the chamber, allowed to mix with emitting gases captured from the landfill surface, and then transported to the exit port where concentrations can be measured. Flux measurements using the flux chamber were performed at five different c&d landfills from june to august, 2003. The flux rates of h2s measured in this research were three to six orders of magnitude lower than the flux rates of methane reported in the literature. In addition to the h2s flux measurements, dispersion modeling was conducted, using the epa dispersion model, industrial source complex short term (iscst3), in order to evaluate impacts on landfill workers and communities around the landfills. The modeling results were analyzed to estimate the potential ground level maximum h2s concentrations for 1-hr and 3-min periods and the frequency (occurrences per year) above the h2s odor detection threshold for each landfill. Odor complaints could be expected from four among five landfills selected for this study, based on 0.5-ppb odor detection threshold.

Dans un contexte automobile électrique et hybride, la part des machines synchrones à aimants permanents s'est accrue exponentiellement. Cette évolution s'accompagne d'exigences en termes d'émissions vibro-acoustiques. En termes de dimensionnement de la chaîne de traction, l'analyse multiphysique du moteur s'avère être un enjeu crucial pour son développement. La nécessité de disposer de codes informatiques de conception possédant des temps de calcul faibles pour une précision maximale se fait ressentir pour l'exploration de solutions potentiellement performantes dans les premières étapes du processus de dimensionnement. A ce titre, les aspects vibratoires et acoustiques sont modélisés analytiquement et par éléments finis dans la présente thèse. Ainsi, au moyen du modèle magnétique, l'analyse magnéto-vibro-acoustique faiblement couplée (résolution itérative des différentes physiques) peut être réalisée.La thèse est découpée en quatre parties. La première expose un état de l’art sur les émissions vibro-acoustiques des machines et notamment la modélisation du bruit d’origine magnétique. Les problématiques de la modélisation sont détaillées. Dans une deuxième partie, les modèles sont largement décrits. Les modèles éléments finis sont validés expérimentalement. Une troisième partie se propose de valider les modèles analytiques par éléments finis, en complexifiant progressivement la géométrie d’une machine à aimants montés en surface à flux radial. Enfin, la dernière partie utilise les modèles éléments finis pour étudier des machines non-conventionnelles comme les machines à commutation de flux et les machines à aimants en surface à flux axial. / The proportion of permanent magnets synchronous motors used for electric and hybrid automotive traction has exponentially increased during the past decade. This evolution comes with ever-demanding low noise and vibrations requirements. Multi-physics analysis of the motor is a decisive issue for the development of the powertrain. For the exploration of potentially efficient motor solutions in first design steps, it is thus a necessity to have at disposal fast and accurate computer codes. In this respect, acoustic and vibratory aspects are modeled using finite element and analytical models in this thesis. As a result, using an electromagnetic model, the weakly-coupled magneto-vibro-acoustic analysis (iterative solving of each physic) can be performed.The thesis is divided into four parts. The first part states the art on machine vibro-acoustic emissions and focuses on noise of magnetic origins modeling. Issues of modeling are detailed. Then, models are described to a great extent in the second part. Finite element models are favorably compared to experimental measures. A third part validates analytical models in comparison to finite element analysis, by gradually complicating the geometry of a surface permanent magnets radial flux machine. Finally, a fourth part uses finite element models to study non-conventional machines such as flux switching radial flux machines and surface permanent magnets axial flux machines.

To understand and to predict the weather and climate, numerical models are important tools and it is crucial that the controlling processes are described correctly. Since 70% of the global surface is covered with water the description how the ocean and atmosphere communicates has a considerable impact. The ocean–atmosphere exchange occurs through transport of momentum (friction) and heat, governed by turbulent eddies. The sea surface is also an important source of turbulence in both directions. The scales of the turbulent eddies cannot be resolved in ocean and climate models. Therefore, the turbulent exchanges have to be related to mean variables, such as wind speed and temperature differences. By using measurements, new methods to describe the air–sea exchange during two specific processes were developed. These processes are the so-called UVCN-regime (Unstable Very Close to Neutral stratification) and swell, i.e. waves which are not produced by the local wind. These processes were included in an ocean model and in a regional atmospheric climate model and the impact was investigated. The UVCN-regime enhances the heat transport significantly during the autumn and winter months in the ocean model. This results in a shallower well-mixed surface layer in the ocean. Wind-following swell reduces the surface friction, which is very important for the atmosphere. Some secondary effects in the climate model are reduced low-level cloud cover and reduced precipitation by more than 10% over sea areas. Locally and for short periods the impact is large. It is important to include the UVCN-regime and the swell impact in models, to make simulations more reliable.

Majority of the rain producing monsoon systems in India form or intensify over the Bay of Bengal and move onto the land. We expect the air-sea interaction to be a crucial factor in the frequent genesis and intensification of monsoon systems over the Bay. Knowledge of air-sea fluxes is essential in determining the air-sea interactions. However, the Bay remains a poorly monitored ocean basin and the state of the near surface conditions during the monsoon months remains to be studied in detail. For example, we do not know yet which among the various flux formulae used in the General circulation models are appropriate over the Bay since there are no direct measurements of surface fluxes here during the peak monsoon months. The present thesis aims towards filing that gap. In this thesis fluxes were computed using the Bulk method, Inertial dissipation method and direct covariance method. The flux comparisons were reasonable during certain flow conditions which are clearly identified. When these conditions are not met the differences among the fluxes from these methods can be larger than the inherent uncertainties' in the methods. Stratification, flow distortion and averaging time are the key variables that give rise to the differences in the fluxes. It is found that there are significant differences in the surface flux estimates computed from different atmospheric General Circulation Model bulk parameterization schemes. In this thesis, the flow gradients are estimated by taking advantage of the natural pitch and roll motion of the ship. A attempt is made to gain insight into the flow distortion and its influence on the fluxes. In our analysis it is found that the displacement of the streamlines is an important component in quantifying flow distortion.

This thesis explored the impacts of forest harvesting on gaseous elemental mercury emissions from forest soils in both field and laboratory studies, through novel use of enriched mercury isotope tracers. Forest floor Hg emissions, sourced from legacy deposition, increased proportionally to the vegetation quantity removed, with biomass harvesting most exacerbating emissions. Contemporary Hg deposition did not appear to be influenced by harvesting. Some of the tracer was rapidly lost to the atmosphere (~8%), but most was sequestered within the soil. Two regimes facilitating Hg emissions were observed in low-light conditions. Under extremely dry conditions deeper Hg sources (> 2cm depth) were as equally susceptible to emission as shallower sources. Following wetting to field capacity, emissions were elevated only from shallow sources, likely as a result of upward capillary transport. Impacts of vegetation removal and dry fluxes are previously uncharacterized and may constitute large additional sources to regional atmospheric Hg cycling.

This thesis explored the impacts of forest harvesting on gaseous elemental mercury emissions from forest soils in both field and laboratory studies, through novel use of enriched mercury isotope tracers. Forest floor Hg emissions, sourced from legacy deposition, increased proportionally to the vegetation quantity removed, with biomass harvesting most exacerbating emissions. Contemporary Hg deposition did not appear to be influenced by harvesting. Some of the tracer was rapidly lost to the atmosphere (~8%), but most was sequestered within the soil. Two regimes facilitating Hg emissions were observed in low-light conditions. Under extremely dry conditions deeper Hg sources (> 2cm depth) were as equally susceptible to emission as shallower sources. Following wetting to field capacity, emissions were elevated only from shallow sources, likely as a result of upward capillary transport. Impacts of vegetation removal and dry fluxes are previously uncharacterized and may constitute large additional sources to regional atmospheric Hg cycling.

Der Stoffwechsel der Zelle besteht aus chemischen Reaktionen und Transportprozessen, deren Umsatzraten (Stoffflüsse) das Ergebnis genetischer, translationaler und metabolischer Kontrolle sind. Stoffflüsse erlauben daher wertvolle Einblicke in das interne Zellgeschehen, sind jedoch -- wenn überhaupt -- nur unter großem Aufwand experimentell bestimmbar. Ihre Vorhersage mittels mathematischer Modelle ist ebenfalls komplex; vereinfachend wird angenommen, der Stoffwechsel unterliege einer optimalen Regulation, wobei Optimalität vielfältig interpretiert wird. Die in dieser Arbeit entwickelte Methode zur Flussvorhersage basiert auf der Annahme, dass sich die Synthesewege wichtiger Metabolite im Laufe der Evolution optimiert haben und unabhängig voneinander reguliert werden. Dies ermöglicht den Organismen: 1. sich einer variierenden Umgebung schnell anzupassen und 2. Störungen und Schäden auf kleinere Teilsysteme (Module) zu begrenzen. Kern der Methode ist die Vorhersage optimaler Synthese-Module: stationärer Flusszustände, die jeweils nur einen Metaboliten synthetisieren und dabei eine vorgegebene Zielfunktion minimieren oder maximieren. Diese minimalen Flussmoden (\textit{MinModen}) sind schnell und ohne Kenntnis enzymspezifischer Parameter zu berechnen, womit sie sich auch zur systematischen Überprüfung der Synthesekapazität großer Netzwerke eignen. Durch lineare Kombination der MinModen kann das Flussgeschehen komplexer Stoffwechselleistungen abgebildet werden. Hinsichtlich verfügbarer experimenteller Daten ist die Qualität der so gewonnenen Flussvorhersagen vergleichbar mit bisherigen Konzepten, und das, obwohl die Kombination optimaler Synthesen ein suboptimales Gesamtflussgeschehen ergibt. Vorteil der MinModen-Methode ist die flexible Integration zusätzlich verfügbarer Daten. So können beispielsweise durch Berücksichtigung Freier Gibbs-Energien und recherchierter Metabolitkonzentrationsbereiche thermodynamisch zulässige Flusszustände vorhergesagt werden. / The metabolism of a cell consists of chemical transformations and transport processes. Their rates (fluxes) are the result of genetic, translational and metabolic control and therefore carry valuable information about the internal state of a cell. However, metabolic fluxes are hard to determine by experiment and are therefore subject of mathematical prediction methods. In this work, a conceptually new method for the prediction of fluxes in large scale metabolic networks is developed. The method is based on the assumption of optimally evolved synthesis pathways that are regulated independently of each other. This enables organisms: (i) to quickly adapt to a varying and complex environment and (ii) to modularly organize its metabolism in order to restrict internal disturbances and damage to smaller subsystems. The core of this method is the prediction of optimal ``synthesis-modules'''': stationary flux modes, each of which synthesizes a single metabolite while minimizing or maximizing a so-called objective function. These so-called minimal flux modes (MinModes) are rapidly calculable without knowledge of enzyme kinetics. As such they are suited for the determination of the synthesis capacity and the set of blocked reactions of large networks. Linearly combined, they allow for the representation of complex metabolic tasks. In contrast to previous approaches that optimize for the concerted accomplishment of complex metabolic tasks (e.g. biomass formation), optimizing single syntheses results in a rather suboptimal total network flux. However, with respect to available experimental data the prediction quality is comparable to previous (FBA) approaches. As major benefit, the method relies on a flexible structure that allows for the integration of diverse experimentally observed data. Here, incorporating free Gibbs-energy and metabolite concentration values enabled the prediction of thermodynamically feasible flux modes without prior restriction of flux directions.

Magnetic flux emergence is the subject of how magnetic fields from the solar interior can rise and expand into the atmosphere to produce active regions. It is the link that joins dynamics in the convection zone with dynamics in the atmosphere. In this thesis, we study many aspects of magnetic flux emergence through mathematical modelling and computer simulations. Our primary aim is to understand the key physical processes that lie behind emergence. The first chapter introduces flux emergence and the theoretical framework, magnetohydrodynamics (MHD), that describes it. In the second chapter, we discuss the numerical techniques used to solve the highly non-linear problems that arise from flux emergence. The third chapter summarizes the current literature. In the fourth chapter, we consider how changing the geometry and parameter values of the initial magnetic field can affect the dynamic evolution of the emerging magnetic field. For an initial toroidal magnetic field, it is found that its axis can emerge to the corona if the tube’s initial field strength is large enough. The fifth chapter describes how flux emergence models can produce large-scale solar eruptions. A 2.5D model of the breakout model, using only dynamic flux emergence, fails to produce any large scale eruptions. A 3D model of toroidal emergence with an overlying magnetic field does, however, produce multiple large-scale eruptions and the form of these is related to the breakout model. The sixth chapter is concerned with signatures of flux emergence and how to identify emerging twisted magnetic structures correctly. Here, a flux emergence model produces signatures found in observations. The signatures from the model, however, have different underlying physical mechanisms to the original interpretations of the observations. The thesis concludes with some final thoughts on current trends in theoretical magnetic flux emergence and possible future directions.