The increase in antibiotic resistance continues to pose a public health risk as very few new antibiotics are being produced, and bacteria resis- tant to currently prescribed antibiotics is growing. Within a typical hospital setting, one may find patients colonized with bacteria resistant to a single an- tibiotic, or, of a more emergent threat, patients may be colonized with bacteria resistant to multiple antibiotics. Precautions have been implemented to try to prevent the growth and spread of antimicrobial resistance such as a reduction in the distribution of antibiotics and increased hand washing and barrier pre- ventions; however, the rise of this resistance is still evident. As a result, there is a new movement to try to re-examine the need for the development of new antibiotics. In this paper, we use mathematical models to study the possible benefits of implementing a new antibiotic in this setting; through these models, we examine the use of a new antibiotic that is distributed in various ways and how this could reduce total resistance in the hospital. We compare several dif- ferent models in which patients colonized with both single and dual-resistant bacteria are present, including a model with no additional treatment proto- cols for the population colonized with dual-resistant bacteria as well as models including isolation and/or treatment with a new antibiotic. We examine the benefits and limitations of each scenario in the simulations presented.

This paper investigates the theoretical meaning of plausibility in mathematics from a teacher’s perspective. The study applies a phenomenographic research approach and uses empirical content analysis. The theory used comes from the writings on plausibility assessment from McIntosh (2008). Furthermore, Karlsson & Kilborn’s (2015) and Kilpatrick, Swafford & Findell’s (2001) writings on mathematical modeling has been applied. The data gathered in this study comes from interviewing 6 teachers. The results show that teachers in the study do not work explicitly but rather work implicitly with assessment in plausibility as a complement to their general teaching of mathematics. The results further show that the teachers have the mathematical knowledge and competence to educate in plausibility but that they lack the theoretical- and didactic knowledge to apply it in their teaching. There is also very little research, if any, in this area which is a concern for the development of teaching plausibility assessment.

Orientador: Aguinaldo Robinson de Souza / Banca: Olival Freire Junior / Banca: Nelson Henrique Morgon / Banca: Roberto Nardi / Banca: Moacir Ferreira de Souza Filho / Resumo: Este estudo procura contribuir, primeiramente com a historiografia da ciência, mostrando quais foram os fundamentos teóricos que proporcionaram à física construir um novo modelo matemático para explicar os fenômenos microfísicos. Em seguida, observamos que os recursos computacionais de modelagem matemática aplicada à física podem contribuir estreitando as relações entre o ensino e a aprendizagem da física. Partindo da análise histórica dos artigos originais (fontes primárias) procuramos narrar, com o rigor natural que a história da ciência exige, a origem da Mecânica Quântica a partir dos fundamentos da termodinâmica. Identificamos quais foram as motivações que fizeram com que dois grandes pensadores da ciência, Boltzmann e Poincaré nos legassem um arcabouço de ideias originais que promoveram o avanço e a modificação completa da Mecânica Clássica, transformando-a em Mecânica Quântica "a partir" de Planck. Investigando a história da teoria ondulatória do calor mostramos que o éter exerceu um papel fundamental na óptica, mas não o fez na termodinâmica, embora Poincaré o quisesse presente ainda em 1912, mesmo que experimentos fundamentais tivessem mostrado a sua ausência. Este texto pode contribuir também como suporte e auxílio no ensino da termodinâmica e seus fundamentos no nível superior, permitindo a estudantes e professores obterem uma visão mais clara sobre a origem da Mecânica Quântica. / Abstract: This study seeks to contribute, firstly with the historiography of science, showing what were the theoretical foundations that enabled physics to construct a new mathematical model to explain the microphysical phenomena. We then, observe that the computational resources of mathematical modeling applied to physics can contribute to narrow the relations between teaching and learning of physics. Starting from the historical analysis of the original articles (primary sources) we seek to narrate with the natural rigor that the history of science demands, the origin of the Quantum Mechanics from the foundations of the thermodynamics. We identified the motivations that lead two great thinkers of science, Boltzmann and Poincaré, to give us a framework of original ideas that promoted the advance and complete modification of Classical Mechanics, transforming it into Quantum Mechanics "from" Planck. Investigating the history of the wave theory of heat we have shown that the ether played a fundamental role in optics, but didn't do it in thermodynamics, although Poincaré wanted to present it still in 1912, even though fundamental experiments had shown its absence. This text can also contribute as support and aid in the teaching of thermodynamics and its fundamentals at the higher level, allowing students and teachers to get a clearer view on the origin of Quantum Mechanics / Doutor

Les buts de cette thèse sont doubles, et concernent les circuits métaboliques synthétiques, qui permettent de détecter des composants chimiques par transmission de signal et de faire du calcul en utilisant des enzymes. La première partie a consisté à développer des outils d’apprentissage actif et par renforcement pour améliorer la conception de circuits métaboliques et optimiser la biodétection et la bioproduction. Pour atteindre cet objectif, un nouvel algorithme (RetroPath3.0) fondé sur une recherche arborescente de Monte Carlo guidée par similarité est présenté. Cet algorithme, combiné à des règles de réaction apprises sur des données et des niveaux différents de promiscuité enzymatique, permet de focaliser l’exploration sur les composés et les chemins les plus prometteurs en bio-rétrosynthèse. Les chemins obtenus par rétrosynthèse peuvent être implémentés dans des cellules ou des systèmes acellulaires. Afin de concevoir le meilleur milieu pour optimiser la productivité du système, une méthode d’apprentissage actif qui explore efficacement l’espace combinatoire des composants du milieu a été développée.La deuxième partie a consisté à développer des méthodes d’analyse, pour générer des connaissances à partir de données biologiques, et modéliser les réponses de biocapteurs. Dans un premier temps, l’effet du nombre de copies de plasmides sur la sensibilité d’un biocapteur utilisant un facteur de transcription a été modélisé. Ensuite, en utilisant des systèmes acellulaires qui permettent un meilleur contrôle des variables expérimentales comme la concentration d’ADN, l’utilisation des ressources a été modélisée pour assurer que notre compréhension actuelle des phénomènes sous-jacents est suffisante pour rendre compte du comportement du circuit, en utilisant des modèles empiriques ou mécanistiques. Couplés aux outils de conception de circuits métaboliques, ces modèles ont ensuite permis de développer une nouvelle approche de calcul biologique, appelée perceptrons métaboliques.Dans l’ensemble, cette thèse présente des outils de conception et d’analyse pour les circuits métaboliques synthétiques. Ces outils ont été utilisés pour développer une nouvelle méthode permettant d’effectuer des calculs en biologie synthétique. / The aims of this thesis are two-fold, and centered on synthetic metabolic circuits, which perform sensing and computation using enzymes.The first part consisted in developing reinforcement and active learning tools to improve the design of metabolic circuits and optimize biosensing and bioproduction. In order to do this, a novel algorithm (RetroPath3.0) based on similarity-guided Monte Carlo Tree Search to improve the exploration of the search space is presented. This algorithm, combined with data-derived reaction rules and varying levels of enzyme promiscuity, allows to focus exploration on the most promising compounds and pathways for bio-retrosynthesis. As retrosynthesis-based pathways can be implemented in whole cell or cell-free systems, an active learning method to efficiently explore the combinatorial space of components for rational media optimization was also developed, to design the best media maximizing cell-free productivity.The second part consisted in developing analysis tools, to generate knowledge from biological data and model biosensor response. First, the effect of plasmid copy number on sensitivity of a transcription-factor based biosensor was modeled. Then, using cell-free systems allowing for broader control over the experimental factors such as DNA concentration, resource usage was modeled to ensure our current knowledge of underlying phenomenons is sufficient to account for circuit behavior, using either empirical models or mechanistic models. Coupled with metabolic circuit design, those models allowed us to develop a new biocomputation approach, called metabolic perceptrons.Overall, this thesis presents tools to design and analyse synthetic metabolic circuits, which are a novel way to perform computation in synthetic biology.

Indiana University-Purdue University Indianapolis (IUPUI) / In the healthcare industry, several modern patient identification and patient matching systems have been introduced. Most of these implement patient identification by their first, middle and last names. They also use Social Security Number and other similar national identifiers. These methods may not work for many developing and underdeveloped countries where identifying a patient is a challenge with highly redundant and interchangeable first and last names of the patient, this is aggravated by the absence of a national identification system. In order to make the patient identification more efficient, Muzima, an interface of OpenMRS (Open source medical records system) introduced an additional identifier, fingerprint, through a module to the system. Ordinary and Time Petri nets are used to analyze this module. Chapter 1 introduces Muzima fingerprint module and describes the workflow of this interface followed by the related work, importance and applications of Petri nets. Chapter 2 introduces Ordinary and Time Petri nets using examples. Chapter 3 discusses about the mathematical modeling of the Muzima Fingerprint module using Petri nets. Chapter 4 explains the qualitative and quantitative analysis done on the Muzima fingerprint module. Chapter 5 discusses about the programming and simulation done to prove the theoretical results obtained. Chapter 6 provides the conclusion and future work for the thesis.

Indiana University-Purdue University Indianapolis (IUPUI) / Thermoregulation system in mammal keeps their body temperature in a vital and yet narrow range of temperature by adjusting two main activities, heat generation, and heat loss. Also, these activities get triggered by other causes such as exercise or certain drugs. As a result, thermoregulation system will respond and try to bring back the body temperature to the normal range. Although these responses are very well experimentally explored, they often can be unpredictable and clinically deadly. Therefore, this thesis aims to analytically characterize the neural circuitry components of the system that control the heat generation and heat loss. This modeling approach can help us to analyze the relationship between different components of the thermoregulation system without directly measuring them and explain its complex responses in mathematical form. The first chapter of the thesis is dedicated to introducing a mathematical modeling approach of the circuitry components of the thermoregulation system in response to Methamphetamine which was first published in [1]. Later, in other chapters, we will expand this mathematical framework to study the other components of this system under different conditions such as different circadian phases, various pharmacological interventions, and exercise. This thesis is composed by materials from the following papers. ‎CHAPTER 1 uses the main idea, model, and figures from References [1]. Meanwhile, ‎CHAPTER 2 is based on [2] coauthored with me and is reformatted according to Purdue University Thesis guidelines. Also, ‎CHAPTER 3 interpolates materials from reference [3] coauthored and is reformatted to comply with Purdue University Thesis guidelines. ‎CHAPTER 4 is inserted from the reference [4] and is reformatted according to Purdue University Thesis guidelines. Finally, ‎CHAPTER 5 is based on Reference [5] and is reformatted according to Purdue University Thesis guidelines. Some materials from each of these references have been used in the introduction Chapter.

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The centrifugal casting process is a common method for manufacturing the tubes, etc. Due to its high temperature and invisible mold, it is really difficult to know the mechanism of molten steel inside the mold. It is important to know the mechanism of the molten steel inside mold, since it will help the manufacturer to know more accuracy of the flow of the molten steel so that it can work for improving the productivity and quality of the products. Casting funnel design is the designed by Åkers for their funnel which will result in different flow behavior. In thesis work, casting funnel design will be investigated so that it can make sure that the casting funnel design can affect the flow behavior of molten steel or not. Another method of changing the diameter of nozzle was also carried out and investigated with both simulation and experiment to changing flow behavior of molten steel. It will give Åkers alternative method for changing the flow behavior to liquid steel. The mechanism of solidification in centrifugal casting is also really important since it can give manufacturer the general view of solidification process. So solidification of centrifugal casting is also investigated in the thesis work.

When an anode electrode potential is larger than the lowest unoccupied molecular orbital (LUMO) of the electrolyte, Li-ions and electrolyte molecules will participate in reduction reactions on the anode surface and form a solid electrolyte interface (SEI) layer. Active Li-ion consumption in the formation reactions is the main source of capacity loss (>50) and ageing in Li-ion batteries (LIBs). Due to the fast-occurring and complex nature of the electrochemical processes, conventional experimental techniques are not a feasible approach for capturing and characterizing the SEI formation phenomenon. The lack of experimental data and consequently the absence of potential parameters for crystal structures in this layer makes molecular dynamics~(MD) simulations inapplicable to it. Also, due to the multi-component multi-layer structure of the SEI, the smallest system representing an SEI layer is too large for employing the principles of quantum mechanics~(QM), that traditionally work with much smaller system sizes. Addressing this, this thesis presents a novel computational framework for coupling QM and MD calculations to simulate a system with the size limits of MD simulations independent of the experimental data. The QM evaluates sub-atomic properties such as energy barriers against diffusion and employs seven new algorithms to estimate potential parameters as the input of the MD simulations. Then MD simulations forecast SEI's properties including density, Young's Modules, Poisson's Ratio, thermal conductivity, and diffusion coefficient mechanisms. The output of the QM and MD calculations are employed to develop two macro-scale mathematical models for predicting battery ageing and battery performance, incorporating the impact of the SEI layer in addition to the cathode, anode, and separator parts. Finally, the results obtained have been validated with respect to the experimental data in different operational conditions. / Thesis / Doctor of Philosophy (PhD) / The limited lifespan of expensive batteries is the main obstacle to electrification of the transport sector, despite its necessity for addressing the current environmental issues. Li+/electrolyte reduction on the electrode surface is responsible for more than 50% of capacity loss and the consequent ageing is a complex and fast-occurring phenomenon (few ns) that cannot be easily resolved using conventional experimental and computational techniques. This thesis presents the development of some computational frameworks and demonstrates their employment to investigate this phenomenon from a multi-scale perspective, i.e., from a few electrons to an entire battery length scale, with the operating cycles ranging from a few ps to several months, employing Quantum Mechanics, Molecular Dynamics, and Macro-Scale Modeling. The frameworks have been successfully validated with respect to experimental data from the literature and have been applied successfully to highlight the parameters that impact ageing in batteries. The findings presented in this thesis can be used as the base for further research on next-gen durable batteries with liquid and solid-state electrolytes.