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Title: Three dimensional analysis of the gas flow in piston ring pack
Creator: Kharazmi, Ali
Date: 2017
Collection: Electronic Theses & Dissertations
Description: "Cylinder-kit dynamics design in an internal combustion engine is highly relevant for the engine performance characteristics, durability and reliability. Since the middle of the 20th century, researchers have been using numerical models to describe the processes that occur in a ring pack. Because it is difficult and extremely costly to conduct experiments on every series of engines to check for the blow-by and oil consumption, a computational analysis can be performed on the ring pack to...
Show more"Cylinder-kit dynamics design in an internal combustion engine is highly relevant for the engine performance characteristics, durability and reliability. Since the middle of the 20th century, researchers have been using numerical models to describe the processes that occur in a ring pack. Because it is difficult and extremely costly to conduct experiments on every series of engines to check for the blow-by and oil consumption, a computational analysis can be performed on the ring pack to study the blow-by and oil-consumption characteristics. In this dissertation a 3D CFD simulation model is introduced to analyze the flow between the cylinder liner and the piston. This model allows for calculation of the piston assembly with consideration of the ring dynamics, transient boundary conditions for combustion chamber pressure and temperature as well as thermal distortion of the piston and liner. The determination of the complex geometry of the cylinder-kit is established in a STL (STereoLithography) format by considering the complicated geometrical details of the ring pack such as thermal distortion of piston and liner, ring twist and ring/groove conformability. The blow by and blow back is numerically calculated for a small bore cylinder operating at 2000 RPM and verified by the results of commercially available 1D models. The calculated velocity filed shows substantial circumferential flow in the piston ring pack that is dominated by the ring and groove geometry as well as the relative position of the rings end gap. It is found that the amount of gas that flows back to the combustion chamber increases when the in-cylinder pressure trace decreases from its peak value. The knowledge from this study can be used as a basis for further multiphase calculations containing oil flow such as oil consumption, oil evaporation and eventually cylinder-kit wear."--Page ii.
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Title: Atomic simulation on chemical-mechanical coupled deformations in complex nano structures
Creator: Liu, Jialin (Graduate of Michigan State University)
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "Nano-structured materials often exhibit very different mechanical properties comparing with their bulk counterpart and are more sensitive and active to chemical interactions with the environments due to the large surface-to-volume ratio. In this thesis, predictive modeling techniques including density functional theory (DFT) and reactive molecular dynamics method (MD) are designed and applied to understand the deformation mechanisms of complex nano-structured material and describe chemical...
Show more"Nano-structured materials often exhibit very different mechanical properties comparing with their bulk counterpart and are more sensitive and active to chemical interactions with the environments due to the large surface-to-volume ratio. In this thesis, predictive modeling techniques including density functional theory (DFT) and reactive molecular dynamics method (MD) are designed and applied to understand the deformation mechanisms of complex nano-structured material and describe chemical-mechanical coupled interactions. Three technologically important materials are investigated, to understanding the high strain rate toughening mechanism in nacre, predicting the formation and fracture of aluminum oxide bifilms in aluminum castings, and revealing the lithium growth morphology as a function of oxygen partial pressure. For nacre, its hierarchical structure and toughening mechanisms have inspired many materials developments. Recently, a new toughening mechanism, deformation twins was observed in nacre after dynamic loading (103 s--1). The deformation twinning tendency and the competition between fracture and deformation twinning were revealed by DFT calculations. We discovered that the ratio of the unstable and the stable stacking fault energy in aragonite is hitherto the highest in a broad range of metallic and oxide materials and the bonding nature for this high ratio is explained. Both aluminum and lithium have high oxygen affinity. Their interaction with the oxygen environment affects the mechanical properties and vice versa. During casting of aluminum, it has long been proposed that the entrapped alumina "bifilms" are detrimental to the fatigue properties of the cast product. However, its properties have never been measured due to experimental limitations. Therefore, a ReaxFF based MD protocol was designed to simulate aging, folding, and fracture of oxide bifilms. The predicted fracture energy, fracture location, and differences between old and young oxides are explained a series of experimental observations. To illustrate the Li-growth mechanism in a solid-state-battery testing platform, we modeled the morphology of Li nano-structure growth in oxygen environment via ReaxFF-based MD. The simulation revealed that the competition of the Li growth rate and oxidation rate leads to the sphere-nanowire-sphere morphology transition with increasing oxygen partial pressure. Understanding the impact of chemical reaction on Li dendrite growth mechanisms and morphology evolution provided insights on the formation of the solid electrolyte interface (SEI) layer in a Li-ion battery. Finally, a shortcoming of the current charge transfer scheme (qEq) used in the ReaxFF MD simulation is discussed. It is demonstrated that qEq method will lead to overductile ionic materials in the MD simulation. A new Force field method and new parameters are proposed to mitigate this problem."--Pages ii-iii.
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Title: MULTIPACTOR DISCHARGE WITH TWO-FREQUENCY RF FIELDS
Creator: Iqbal, Asif
Date: 2021
Collection: Electronic Theses & Dissertations
Description: Multipactor is a nonlinear ac discharge in which a high frequency rf field creates an electron avalanche sustained through secondary electron emission from metallic or dielectric surfaces. Multipactor discharge can adversely affect various rf systems, such as telecommunications systems, high power electromagnetic sources, and accelerator structures. The restricted frequency spectrum and the cluttered satellite orbits require a single spacecraft to perform the same or enhanced functions which...
Show moreMultipactor is a nonlinear ac discharge in which a high frequency rf field creates an electron avalanche sustained through secondary electron emission from metallic or dielectric surfaces. Multipactor discharge can adversely affect various rf systems, such as telecommunications systems, high power electromagnetic sources, and accelerator structures. The restricted frequency spectrum and the cluttered satellite orbits require a single spacecraft to perform the same or enhanced functions which previously required several satellites. This necessitates complex multi-frequency operation for a much-enlarged orbital capacity and mission, where the requirement of high power rf payload significantly increases the threat of multipactor. This work provides a comprehensive understanding of multipactor discharge driven by two-frequency rf fields. The study provides important results on single and two-surface multipactor, including multipactor mitigation, migration of electron trajectory, and frequency domain analysis.We use Monte Carlo simulations and analytical calculations to obtain single surface multipactor susceptibility diagrams with two-frequency rf fields. We present a novel multiparticle Monte Carlo simulation model with adaptive time steps to investigate the time dependent physics of the single surface multipactor. The effects of the relative strength and phase of the second carrier mode as well as the frequency separation between the two carrier modes are studied. It is found that two-frequency operation can reduce the multipactor strength compared to single-frequency operation with the same total rf power. Migration of the multipactor trajectory is demonstrated for different configurations of the two-frequency rf fields. Formation of beat waves is observed in the temporal profiles of the surface charging electric field with small frequency separation between the two carrier modes. We study the amplitude spectrum of the surface charging field due to multipactor in the frequency domain. It is found that for the single-frequency rf operation, the normal electric field consists of pronounced even harmonics of the driving rf frequency. For two-frequency rf operation, spectral peaks are observed at various frequencies of intermodulation product of the rf carrier frequencies. Pronounced peaks are observed at the sum and difference frequencies of the carrier frequencies, at multiples of those frequencies, and at multiples of the carrier frequencies. We also study two surface multipactor with single- and two-frequency rf fields using Monte Carlo simulations and CST. The effects of the relative strength and phase of the second carrier mode, and the frequency separation between the two carrier modes on multipactor susceptibility are studied. Regions of single and mixed multipactor modes are observed in the susceptibility chart. The effect of space charge on multipactor susceptibility and the time dependent physics is also studied.
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Title: PROBLEM GAMBLING, GENERAL STRAIN THEORY AND GENDER
Creator: Malkin, Michelle L.
Date: 2021
Collection: Electronic Theses & Dissertations
Description: The prevalence of problem gambling has increased in the late 20th Century. Prior research has identified a host of factors that increase the likelihood that an individual will become a problem gambler, most of which would be identified by criminologists as “strains” under the framework of General Strain Theory (GST). Yet, GST has not been widely used as a possible explanation for why people become problem gamblers. In addition, there has been no examination of how gender interacts with those...
Show moreThe prevalence of problem gambling has increased in the late 20th Century. Prior research has identified a host of factors that increase the likelihood that an individual will become a problem gambler, most of which would be identified by criminologists as “strains” under the framework of General Strain Theory (GST). Yet, GST has not been widely used as a possible explanation for why people become problem gamblers. In addition, there has been no examination of how gender interacts with those variables to affect problem gambling. In this dissertation, I use propositions from General Strain Theory to determine if it provides a framework for understanding why people become problem gamblers and whether gender is a moderating factor in this relationship. Secondary analysis of data collected from the Social and Economic Impacts of Gambling in Massachusetts (SEIGMA) study is analyzed to assess types of non-gambling strains, their relationship to problem gambling, and the role gender plays in this relationship. Findings demonstrate that non-gambling strains play a minor role in why people become problem gamblers. More relevant factors include having a non-substance behavioral problem and experiencing strain from a spouse/partner who is a problem gambler. Gender was found to have a strong direct effect on problem gambling (with men more likely to be problem gamblers than women), but few moderating effects were found, with one exception—men were more likely be problem gamblers than women if they experienced strain from their spouse/partner’s gambling behavior.
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Title: THE INTERACTION BETWEEN GENETICS AND CLIMATE ON CRANIOFACIAL VARIATION : EXAMINING THE CAUSATIVE FORCES OF MACROMORPHOSCOPIC TRAIT EXPRESSION
Creator: Plemons, Amber
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Anthropologists have an extensive history using cranial form to measure group relatedness in past and present populations to answer a range of questions concerning population histories and cultural practices. However, most biological distance studies using skeletal remains do not consider extrinsic forces influencing modern human variation. Researchers have explored evolutionary and plastic responses in cranial form using measurements of the cranium and mandible, but these studies generally...
Show moreAnthropologists have an extensive history using cranial form to measure group relatedness in past and present populations to answer a range of questions concerning population histories and cultural practices. However, most biological distance studies using skeletal remains do not consider extrinsic forces influencing modern human variation. Researchers have explored evolutionary and plastic responses in cranial form using measurements of the cranium and mandible, but these studies generally drew inferences through population comparisons or using inadequate statistical and biological models that so often lead to conflicting findings or confounding interpretations. To fill this gap in our current understanding of modern human variation, I have combined global craniofacial morphological, climatic, and genetic datasets to measure the magnitude and directionality of several climate variables on craniofacial form, while controlling for population structure (e.g., microevolutionary forces and population history). Craniofacial morphological data from the Macromorphoscopic Databank (MaMD) are used in conjunction with microsatellite data from Pemberton (2013), representing populations that overlap in geographic space with those in the MaMD. Finally, climate data from the National Oceanic and Atmospheric Association (NOAA) and Climate Research Unit (CRU) websites were obtained for weather stations in close proximity to populations under study. This combined dataset is used to explore the interaction between climate and genetics on craniofacial variation across 11 geographic regions using a mixed model approach known as Bayesian Sparse Factor Analysis of Genetic Covariance Matrices (BSFG). Data analysis follows the methods described by Katz and colleagues (2016) but expands their study through the exploration of selection processes using additional climate variables, including coldest month and driest month averages and annual ranges of temperature and absolute humidity. Overall, the study found significant correlation between genetic and phenotypic data indicating MMS traits can serve as genetic proxies in biodistance analyses. Several traits had higher heritability estimates (malar tubercle, zygomaticomaxillary suture course, postbregmatic depression and anterior nasal spine). Features associated with the nasal complex and facial breadth, particularly anterior nasal spine, nasal bone contour, and interorbital breadth, had strong associations to climate. These climate findings correspond to previous research on nasal form and environment where cold-dry environments select for high, narrow noses. Further evidence of selective forces in MMS traits are apparent with the reduction of these features in more variable climates where the respiratory system experiences less stress. The evolutionary mechanisms behind craniometric data have been explored extensively. Such studies use a full suite of traits that capture overall size and shape of the human cranium; however, MMS traits focus on macroscopic assessments primarily in the midfacial skeleton. MMS trait data are particularly important for expanding our understanding of natural selection whereby a large portion of cranial evolutionary research has centered around the neutral evolutionary processes. The wealth of research demonstrating the nasal complex is highly responsive to climate due to respiratory stress emphasizes the importance of exploring the proportion of genetics and environments on MMS trait manifestation. This project provides an evolutionary foundation of the neutral evolutionary and selection processes controlling systematic patterns of global craniofacial variation in the Macromorphoscopic Databank (MaMD).
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Title: Novel methods for functional data analysis with applications to neuroimaging studies
Creator: Guha Niyogi, Pratim
Date: 2022
Collection: Electronic Theses & Dissertations
Description: In recent years, there has been explosive growth in different neuroimaging studies such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI). The data generated from such studies are often complex structured which are collected for different individuals, via various time-points and across various modalities, thus paving the way for interesting problems in statistical methodology for analysis of such data. In this dissertation, some efficient methodologies are...
Show moreIn recent years, there has been explosive growth in different neuroimaging studies such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI). The data generated from such studies are often complex structured which are collected for different individuals, via various time-points and across various modalities, thus paving the way for interesting problems in statistical methodology for analysis of such data. In this dissertation, some efficient methodologies are proposed with considerable development which have nice statistical properties and can be useful not only in neuroimaging but also in other scientific domains. A brief overview of the dissertation is provided in Chapter 1 and in particular, different kinds of data structures that are commonly used in consecutive chapters are described. Some useful mathematical results frequently used in the theoretical derivations in various chapters are also provided. Moreover, we raise some fundamental questions that arise due to some specific data structures with applications in neuroimaging and answer these questions in subsequent chapters. In Chapter 2, we consider the problem of estimation of coefficients in constant linear effect models for semi-parametric functional regression with functional response, where each response curve is decomposed into the overall mean function indexed by a covariate function with constant regression parameters and random error process. We provide an alternative semi-parametric solution to estimate the parameters using quadratic inference approach by estimating bases functions non-parametrically. Therefore, the proposed method can be easily implemented without assuming $\sqrt{?}$-convergence rate of the proposed estimator under the proper choice of bandwidth and establish its asymptotic normality. A multi-step estimation procedure to simultaneously estimate the varying-coefficient functions using a local linear generalized method of moments (GMM) based on continuous moment conditions is developed in Chapter 3 under heteroskedasticity of unknown form. To incorporate spatial dependence, the continuous moment conditions are first projected onto eigen-functions and then combined by weighted eigen-values. This approach solves the challenges of using an inverse covariance operator directly. We propose an optimal instrumental variable that minimizes the asymptotic variance function among the class of all local linear GMM estimators, and it is found to outperform the initial estimates that do not incorporate spatial dependence. Neuroimaging data are increasingly being combined with other non-imaging modalities, such as behavioral and genetic data. The data structure of many of these modalities can be expressed as time-varying multidimensional arrays (tensors), collected at different time-points on multiple subjects. In Chapter 4, we consider a new approach to study neural correlates in the presence of tensor-valued brain images and tensor-valued predictors, where both data types are collected over the same set of time-points. We propose a time-varying tensor regression model with an inherent structural composition of responses and covariates. This development is a non-trivial extension of function-on-function concurrent linear models for complex and large structural data where the inherent structures are preserved. Through extensive simulation studies and real data analyses, we demonstrate the opportunities and advantages of the proposed methods.
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Title: Data-Driven Multi-Scale Modeling, Analysis and Simulation of Material Failure
Creator: Barros de Moraes, Eduardo Augusto
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Material failure processes are inherently stochastic and anomalous, occurring across a wide span of length and time scales, from dislocation motion at the micro-scale, to formation of micro-cracks, up to crack propagation and aging mechanisms at the macro-scale and cascading failure at the system-level. Anomalies such as intermittent signals in Acoustic Energy experiments, power-law distribution of the energy spectrum, crackling noise, dislocation avalanches, among other indicators, occur...
Show moreMaterial failure processes are inherently stochastic and anomalous, occurring across a wide span of length and time scales, from dislocation motion at the micro-scale, to formation of micro-cracks, up to crack propagation and aging mechanisms at the macro-scale and cascading failure at the system-level. Anomalies such as intermittent signals in Acoustic Energy experiments, power-law distribution of the energy spectrum, crackling noise, dislocation avalanches, among other indicators, occur even in standard, ordered, crystalline materials. Modeling and simulation of failure must take into account parametric and model-form uncertainties that propagate across the scales, when seemingly unimportant material properties or loading conditions could cause catastrophic failure at the component level. The pursuit of a unified framework for quantitative and qualitative failure prediction that can bridge the multiple scales while still incorporating the material’s underlying stochastic processes is still a challenge, which requires a new modeling paradigm that incorporates such features with both robustness and simplicity.In this work, we propose a data-driven methodology for multi-scale, statistically consistent modeling of anomalous failure processes. At the micro-scale, the goal is to study the dynamics of dislocations, which play a vital role in plasticity and crack nucleation mechanisms, and shows anomalous features across different time and length-scales. We start by investigating the dislocation mobility properties at the nano-scale and propose a surrogate model for dislocation motion based on a Kinetic Monte Carlo method, where the dislocation motion is emulated as a random-walk on a network following a Poisson process. The surrogate learns the rates of the corresponding Poisson process directly from high-fidelity, Molecular Dynamics (MD) simulations. The surrogate is capable of efficiently obtaining uncertainty measures for the mobility parameter, which can be then propagated to more complex simulations in upper scales. At the meso-scale, the collective behavior of dislocation dynamics leads to avalanche, strain bursts, intermittent energy spikes, and nonlocal interactions. We develop a probabilistic model for dislocation motion constructed directly from trajectory data from Discrete Dislocation Dynamics (DDD). We obtain the corresponding Probability Density Function for the dislocation position, and propose a nonlocal transport model for the PDF. We use a bi-level Machine Learning framework to learn the parameters of the nonlocal operator and the coefficients of the PDF evolution equation, facilitating a continuum representation of the anomalous phenomena.At the macro-scale, parametric material uncertainties substantially affect the predictability of failure at the component level. We develop an Uncertainty Quantification (UQ) and Sensitivity Analysis (SA) framework for propagation of parametric uncertainties in a stochastic phase-field model of damage and fatigue, and we use the Probabilistic Collocation Method (PCM) as a building block. A Global SA indicates the most influential parameters in solution uncertainty and shows that damage initiation is sensitive to parameters associated with classical free-energy potential definitions, providing another motivation to incorporate the heavy-tail processes as observed in the meso-scale. We extend the framework and develop a Machine Learning (ML) framework for failure prediction phase-field models for brittle materials. We combine a classification algorithm with a pattern recognition scheme using virtual nodes from the phase-field damage model to generate patterns of material softening at each time-step. The framework identifies the presence and location of cracks and is robust even under noisy data, whether from model, parametric, or experimental uncertainties.
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Title: HELLGATE TO HIGHWAY : ISLAND MAKING, DREDGING, AND INFRASTRUCTURE IN THE DETROIT RIVER, 1874-1938
Creator: Swayamprakash, Ramya
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This dissertation exposes the tensions, trials, and tribulations along the U.S.-Canada border in the Detroit River between 1874 and 1938. I study how dredging—a seemingly inert process of removing river bottom sediment and depositing it elsewhere—helped create landforms across and along the political border, in turn, revealing the myriad social and political tensions that undergird it. By exposing how infrastructure revealed border tensions, especially those related to resource extraction,...
Show moreThis dissertation exposes the tensions, trials, and tribulations along the U.S.-Canada border in the Detroit River between 1874 and 1938. I study how dredging—a seemingly inert process of removing river bottom sediment and depositing it elsewhere—helped create landforms across and along the political border, in turn, revealing the myriad social and political tensions that undergird it. By exposing how infrastructure revealed border tensions, especially those related to resource extraction, scarcity, and national security—on both sides of the Canada-U.S. border—this dissertation offers a new way to link environmental and border history as well as environmental diplomacy.The lower Detroit River forms the ideal study site for two interrelated reasons. One, its narrow and rocky riverbed along the shipping channel was a dangerous bottleneck, slowing traffic on one of the busiest waterways in the world. Two, dredging the lower part of the river kept this busy waterway running efficiently. The Livingstone Channel fundamentally reordered the Detroit River when it was carved out of the riverbed where hitherto there existed fish spawning grounds and shallow water. Concentrating on the lower Detroit River in general and the Livingstone Channel in particular, this dissertation will show how conflict and cooperation overlapped when it came to international diplomacy in the Great Lakes. Cultural and social historians have analyzed Great Lakes borderlands. Environmental historians though have yet to fully analyze these lakes. The political border between the United States and Canada has often been portrayed as being benign and uncontested. Yet, as this dissertation shows, border infrastructure, such as shipping channels, was seldom uncontested. By focusing on the political border, this dissertation aims to bring attention to the border as a site rather than a liminal space or an end zone of state sovereignty. The border in this reading is the origin of state sovereignty. Studies of the Canada-U.S. borderlands have often explored the role of international environmental diplomacy, especially in the joint management and conservation of binational water bodies like the Great Lakes through policy mechanisms such as the Boundary Waters Treaty (BWT) of 1908 and the International Joint Commission. As my dissertation shows, however, the BWT was an important staging point on which the different intercultural and international misunderstandings were exposed. The Great Lakes have often been cast as being abundant, yet there is little or no work on how that plentitude was not just manufactured in thought, but also embodied in infrastructures. As a transformative process, dredging does not seem monumental. Yet, dredging in the Detroit River has permanently lowered the levels of Lakes Huron and Michigan by at least 25 cm. Dredging thus reveals how environmental transformation lies at the heart of Great Lakes geography as we know it. By exposing dredging in a connecting channel, this dissertation shows that infrastructural creation and imagination undergirds the Great Lakes environment. Infrastructure, as I show, is an important and unseen filter to understand intercultural and international relationships. This is especially true of countries such as the U.S. and Canada which pride themselves in intercultural similarities more than differences. Studying conflict and contestation offers a novel way to understand the cooperative mechanism that drives current borderlands diplomacy. Studying dredging along the lower Detroit River in the nineteenth and twentieth centuries reveals ideas about nature as well as historical challenges and contestations to them.
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Title: IMPROVING QT CORRECTION METHODS THROUGH THE ANALYSIS OF PRECLINICAL SAFETY PHARMACOLOGY DATA
Creator: Ether, Nicholas David
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Torsade de pointes is a polymorphic ventricular tachycardia that has been linked to sudden cardiac death. While typically rare and fleeting, increased risk for occurrence of and problematic outcomes from this arrhythmia has been attributed to prolonged QT intervals. These interval measurements of electrocardiogram waveforms represent the time between depolarization and repolarization of the ventricles. Prolongation of this period increases the likelihood of disruptions in ventricular...
Show moreTorsade de pointes is a polymorphic ventricular tachycardia that has been linked to sudden cardiac death. While typically rare and fleeting, increased risk for occurrence of and problematic outcomes from this arrhythmia has been attributed to prolonged QT intervals. These interval measurements of electrocardiogram waveforms represent the time between depolarization and repolarization of the ventricles. Prolongation of this period increases the likelihood of disruptions in ventricular cardiomyocyte conduction, which can lead to torsade de pointes events. Due to the potentially fatal outcomes associated with QT prolongation, it was not long until drugs found to induce this prolongation began to be removed from the market. These concerns led to the creation of safety pharmacology guidelines S7B and E14 that outlined suggested QT prolongation risk assessments to be performed during the preclinical and clinical stages of drug development, respectively. Studies based on these guidelines are intended to identify drug-induced changes to the QT interval, but must first control for the effect heart rate has on QT. To isolate drug effect QT correction methods are used to estimate corrected QT values as if the data was collected at a fixed heart rate. Using these values as a biomarker has led to highly sensitive assessments that have prevented any new drugs from reaching the market with unacceptable QT prolongation risk. However, these assessments are still in need of improvement as the pharmaceutical industry must deal with costly and time-consuming clinical safety studies despite the high sensitivity of preclinical assessments, leading to calls for the integration of preclinical and clinical guidelines. To achieve this, the translatability of preclinical results must be improved.This dissertation aims to increase the reliability of preclinical results and improve their translatability by optimizing the QT correction methods they rely on. To do this, I analyzed large ECG datasets from preclinical safety pharmacology studies obtained through Eli Lilly and Company (Indianapolis, IN). The central hypothesis of this dissertation is that through statistical analysis of these data, the collective understanding of QT correction methods will be expanded, and an improved method can be developed. In pursuit of this goal, the effectiveness of various preclinical QT correction methods was evaluated in simulated drug treatment scenarios, against 130,000+ bootstrap resampled ECG recordings of vehicle control treatments, and with study data from non-human primates treated with known QT prolonging drugs. The results of these evaluations provided evidence of how assumptions inherent to these methods affect the result of correction. Examples of such assumptions include what heart rate is relevant for the species, that a predetermined population-based estimate of the QT-rate relationship is appropriate for individuals, that this relationship will not change over time or between treatments, and that assuming this relationship before correction is appropriate in the first place. All of this led to the development of the novel Ratio QT correction method designed to be applicable to any scenario by dynamically responding to moment-to-moment changes in the relationship between timepoints. This novel method combines the simplicity and ease-of-use of population-based methods with the effectiveness of individual methods. Taken together, this research has increased the collective understanding of QT correction methods and resulted in a novel method that is as effective as it is simple to use. The investigations presented in this dissertation have explored aspects of QT correction methods that have been in question for years. Optimizing these methods is now easier thanks to the information gained through these analyses of large preclinical ECG datasets. An integral step has been made towards the creation of a new industry standard of QT correction capable of bridging the gap between preclinical and clinical safety pharmacology studies. Such improvements can be used to help reduce the number of research subjects necessary for preclinical and clinical QT prolongation assessments.
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Title: Iris Recognition : Enhancing Security and Improving Performance
Creator: Sharma, Renu
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Biometric systems recognize individuals based on their physical or behavioral traits, viz., face, iris, and voice. Iris (the colored annular region around the pupil) is one of the most popular biometric traits due to its uniqueness, accuracy, and stability. However, its widespread usage raises security concerns against various adversarial attacks. Another challenge is to match iris images with other compatible biometric modalities (i.e., face) to increase the scope of human identification....
Show moreBiometric systems recognize individuals based on their physical or behavioral traits, viz., face, iris, and voice. Iris (the colored annular region around the pupil) is one of the most popular biometric traits due to its uniqueness, accuracy, and stability. However, its widespread usage raises security concerns against various adversarial attacks. Another challenge is to match iris images with other compatible biometric modalities (i.e., face) to increase the scope of human identification. Therefore, the focus of this thesis is two-fold: firstly, enhance the security of the iris recognition system by detecting adversarial attacks, and secondly, accentuate its performance in iris-face matching.To enhance the security of the iris biometric system, we work over two types of adversarial attacks - presentation and morph attacks. A presentation attack (PA) occurs when an adversary presents a fake or altered biometric sample (plastic eye, cosmetic contact lens, etc.) to a biometric system to obfuscate their own identity or impersonate another identity. We propose three deep learning-based iris PA detection frameworks corresponding to three different imaging modalities, namely NIR spectrum, visible spectrum, and Optical Coherence Tomography (OCT) imaging inputting a NIR image, visible-spectrum video, and cross-sectional OCT image, respectively. The techniques perform effectively to detect known iris PAs as well as generalize well across unseen attacks, unseen sensors, and multiple datasets. We also presented the explainability and interpretability of the results from the techniques. Our other focuses are robustness analysis and continuous update (retraining) of the trained iris PA detection models. Another burgeoning security threat to biometric systems is morph attacks. A morph attack entails the generation of an image (morphed image) that embodies multiple different identities. Typically, a biometric image is associated with a single identity. In this work, we first demonstrate the vulnerability of iris recognition techniques to morph attacks and then develop techniques to detect the morphed iris images.The second focus of the thesis is to improve the performance of a cross-modal system where iris images are matched against face images. Cross-modality matching involves various challenges, such as cross-spectral, cross-resolution, cross-pose, and cross-temporal. To address these challenges, we extract common features present in both images using a multi-channel convolutional network and also generate synthetic data to augment insufficient training data using a dual-variational autoencoder framework. The two focus areas of this thesis improve the acceptance and widespread usage of the iris biometric system.
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Title: STUDYING MENTORS AND MENTORING FROM A LEARNER-CENTERED PERSPECTIVE
Creator: Croel-Perrien, Amy
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Teacher candidates, while completing their student teaching internship, are part of an important teaching-and-learning triad. The other members of the triad, mentor teachers and university field instructors, provide essential support to teacher candidates throughout the student teaching internship experience (Yee, 1968). Recent research has examined the roles of mentor teachers and university field instructors. Not as much is understood, however, about the moments or experiences teacher...
Show moreTeacher candidates, while completing their student teaching internship, are part of an important teaching-and-learning triad. The other members of the triad, mentor teachers and university field instructors, provide essential support to teacher candidates throughout the student teaching internship experience (Yee, 1968). Recent research has examined the roles of mentor teachers and university field instructors. Not as much is understood, however, about the moments or experiences teacher candidates recognize as when they learned the most about teaching. With retirements increasing and as much as 50% leaving the field within the first five years of teaching (Shwartz & Dori, 2016), there is an urgency in studying, and hopefully improving, novice teacher support systems.In this dissertation, I explore the moments or experiences teacher candidates recognize as insightful and valuable from their student teaching experience, from the perspective of four recent student teachers. Using phenomenology as a method of inquiry (Giorgi, 1985), data were collected through phenomenological interviews of four teacher candidates after they completed a year-long student teaching internship. These interviews tell the story of teacher candidates becoming through learning (Hodkinson et al., 2008). Findings indicate that framing problems of practice within practical situations, situations that likely occur in an elementary classroom, positively influence teacher candidates’ learning. The practice of adaptative mentoring (van Ginkel et al., 2015) provides opportunities for mentor teachers to support teacher candidates as they learn about teaching practice, while also helping them with emotional and practical concerns. Ultimately, I argue that grounding mentoring in both the how and why of teaching, along with adapting to the individual needs of teacher candidates, provides supportive opportunities for teacher candidates’ learning.
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Title: UNDERSTANDING THE PARASITIC VARIABILITY OF THE NORTHERN ROOT KNOT NEMATODE (MELOIDOGYNE HAPLA) THROUGH MULTIDISCIPLINARY APPROACHES OF SOIL BIOME AND ENVIRONMENT
Creator: Lartey, Isaac
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Managing Meloidogyne hapla remains challenging due to the ban of broad-spectrumnematicides, lack of resistant crops and its broad host range. It also has parasitic variability (PV) where populations (pop) are morphologically and genetically similar but vary in pathogenicity and reproductive potential. Although PV in M. hapla appears to have some relationship to soil types, what soil conditions favor its PV and/or its distribution are unknown. The goal of my research was to understand the soil...
Show moreManaging Meloidogyne hapla remains challenging due to the ban of broad-spectrumnematicides, lack of resistant crops and its broad host range. It also has parasitic variability (PV) where populations (pop) are morphologically and genetically similar but vary in pathogenicity and reproductive potential. Although PV in M. hapla appears to have some relationship to soil types, what soil conditions favor its PV and/or its distribution are unknown. The goal of my research was to understand the soil conditions where M. hapla PV exist by quantifying the biophysicochemical (BPC) conditions from the ecosystem down to microbiome level. I designed observational and experimental approaches and tested four objectives. First, was to evaluate the association between soil conditions and M. hapla distribution at the ecosystem level. My hypothesis was that the presence of M. hapla will be associated with degraded soil conditions. I selected 15 (6 muck and 9 mineral soil) agricultural fields with adjacent natural vegetation in southwest, northwest and eastern regions of the lower peninsula of Michigan as study sites. I collected a total of 75 (5 per field) georeferenced soil samples from agricultural fields and equal number from adjacent natural vegetation soils, quantified the soil food web (SFW) conditions using the Ferris SFW model, and screened for M. hapla presence or absence. The fields were described either as disturbed, degraded (worst-case) or maturing (best-case). Meloidogyne hapla was present in 3 mineral (2, 8 and 13) and 6 muck (4, 5, 6, 10, 14 15) agricultural fields with degraded and/or disturbed soil conditions and absent from maturing soils, partially supporting the hypothesis. Degraded soils had low nitrogen content in both soil groups. The second objective was to isolate and culture the 9 M. hapla populations to test a hypothesis that PV is related to specific SFW conditions. I found three categories of reproductive potential: the highest (Pop 13), medium (Pop 8), both from degraded mineral soils, and lowest from disturbed mineral (Pop 2) and disturbed (Pops 4, 6 and 10) and degraded (Pops 5, 14 and 15) muck soils. Thus, the hypothesis was not supported. The third objective, was to determine relationships between microbial community structure and M. hapla distribution. My working hypotheses were that there is a relationship among microbiome, soil health and M. hapla occurrence. Microbial community structure in the fields was determined from sub-samples of the same samples where the nematodes were isolated. I used 16S (bacteria) and ITS (fungi) rDNA analysis and characterized the microbial composition, core- and indicator-microbes co-existing with M. hapla pop in the field soils and soil conditions relative to the Ferris SFW model description. The results showed that bacterial and fungal community abundance and composition varied by soil group, SFW conditions and/or M. hapla occurrence. I found that a core of 39 bacterial and 44 fungal sub-operational taxonomic units (OTUs) were found variably, 25 bacterial OTUs associated with presence or absence of M. hapla, and 1,065 OTUs were associated SFW conditions. All three hypotheses were supported. The final objective was to determine the relationship between PV and the microbes associated with M. hapla pop. I compared bacteria present in M. hapla pop isolated from the field and greenhouse cultures. The hypothesis was that either presence and/or absence of specific bacteria are associated with M. hapla population. Population 8 shared more bacteria with the lowest reproductive potential pop than Population 13. Presence of several bacteria was unique to Population 8 as was the absence of other bacteria to Pop 13 in either field or greenhouse nematodes. Therefore, the hypothesis was supported. My research findings provide a foundation for: a) testing the relationship between M. hapla PV and the BPC conditions and b) designing soil health-based management strategies.
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Title: Level Structures on Finite Group Schemes and Applications
Creator: Guan, Chuangtian
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The notion of level structures originates from the study of the moduli of elliptic curves. In this thesis, we consider generalizing the notion of level structures and make explicit calculations on different moduli spaces. The first moduli space we consider is the moduli of finite flat (commutative) group schemes. We give a definition of $\Gamma(p)$-level structure (also called the ``full level structure") over group schemes of the form $G\times G$, where $G$ is a group scheme or rank $p$ over...
Show moreThe notion of level structures originates from the study of the moduli of elliptic curves. In this thesis, we consider generalizing the notion of level structures and make explicit calculations on different moduli spaces. The first moduli space we consider is the moduli of finite flat (commutative) group schemes. We give a definition of $\Gamma(p)$-level structure (also called the ``full level structure") over group schemes of the form $G\times G$, where $G$ is a group scheme or rank $p$ over a $\Z_p$-scheme. The full level structure over $G\times G$ is flat over the base of rank $|\GL_2(\F_p)|$. We also observe that there is no natural notion of full level structures over the stack of all finite flat commutative group schemes. The second moduli space we consider is the moduli of principally polarized abelian surfaces in characteristic $p>0$ with symplectic level-$n$ structure ($n\ge 3$), which is known as the Siegel threefold. By decomposing the Siegel threefold using the Ekedahl--Oort stratification, we analyze the $p$-torsion group scheme of the universal abelian surface over each stratum. To do this, we establish a machinery to produce group schemes from their Dieudonn\'e modules using a version of Dieudonn\'e theory due to de Jong. By using this machinery, we give explicit local equations of the Hopf algebras over the superspecial locus, the supersingular locus and ordinary locus. Using these local equations, we calculate explicit equations of the $\Gamma_1(p)$-covers over these strata using Kottwitz--Wake primitive elements. These equations can be used to prove geometric and arithmetic properties of the $\Gamma_1(p)$-cover over the Siegel threefold. In particular, we prove that the $\Gamma_1(p)$-cover over the Siegel threefold is not normal.
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Title: The Aging Mind and Body in Eighteenth-Century British Literature and Culture, 1680-1830
Creator: Oh, June Young
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Aging Mind and Body offers a literary history of the concept of aging between 1680 and 1830. I trace the interplay between the century’s literature and developing medical theories of the human body, revealing the long eighteenth century to be a crucial cultural moment that transformed what aging meant both for writers and for the broader public. While in the early modern period authors predominantly associated aging with wisdom and spiritual growth, Enlightenment science reconceived aging as...
Show moreAging Mind and Body offers a literary history of the concept of aging between 1680 and 1830. I trace the interplay between the century’s literature and developing medical theories of the human body, revealing the long eighteenth century to be a crucial cultural moment that transformed what aging meant both for writers and for the broader public. While in the early modern period authors predominantly associated aging with wisdom and spiritual growth, Enlightenment science reconceived aging as radically debilitating for both the body and the mind. I argue that this shift spurred significant literary innovations as writers exploited, negotiated, and subverted scientific assumptions about growing old. Excavating the history behind the emergence of derogatory terms for aging such as “senility” and “senescence,” I show that the literary portrayal of aging was effectively turned into a contested site for reimagining normative human life and progress. Each of my chapters examines a different supposed problem of aging—rising immobility, mental disability, changing physical appearance, and declining sexuality—as it emerges in the major works of Daniel Defoe, Jonathan Swift, Lady Mary Wortley Montagu, Mary Leapor, John Cleland, and Jane Austen. In particular, I undertake a critical re-reading of aging as it intersects with racism, sexism, ableism, and classism. Reading these works in terms of aging, I argue, complicates our traditional story of the long eighteenth century’s attention to progress, revealing not simply an ongoing struggle to marginalize the aging mind and body but also an important literary attempt that refigured “decline” as a constitutive and meaningful part of the whole life experience.
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Title: Neutron-unbound states in the nucleus 31Ne
Creator: Chrisman, Dayah Nichole
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Studies of nuclei far from stability reveal trends among groups of neighboring nuclei where new and unexpected properties appear. One such region, the Island of Inversion near the N=20 shell gap, is home to nuclei with reordered single-particle energy levels compared to the spherical shell model. Studies of the 31Ne nucleus have revealed that its ground state has a halo component, characterized by a valence neutron orbiting a deformed 30Ne core. This lightly-bound nucleus with a separation...
Show moreStudies of nuclei far from stability reveal trends among groups of neighboring nuclei where new and unexpected properties appear. One such region, the Island of Inversion near the N=20 shell gap, is home to nuclei with reordered single-particle energy levels compared to the spherical shell model. Studies of the 31Ne nucleus have revealed that its ground state has a halo component, characterized by a valence neutron orbiting a deformed 30Ne core. This lightly-bound nucleus with a separation energy of Sn=0.15(+0.16, -0.10)$~MeV is expected to have excited states that are neutron-unbound. This work presents a first study of the neutron-unbound excited states of 31Ne. Neutron-unbound states in 31Ne were populated in a two-proton knockout reaction from an 89 MeV/u 33Mg beam incident on a segmented Be reaction target. The 30Ne fragment and associated neutron from the decay of 31Ne* were detected by the MoNA-LISA-Sweeper experimental setup at the National Superconducting Cyclotron Laboratory. Invariant mass spectroscopy was used to reconstruct the two-body decay energy (30Ne+n).The two-body decay energy spectrum exhibits two features: a low-lying peak at 0.30 (+/- 0.17) MeV and a broad enhancement at 1.50 (+/- 0.33) MeV, each fit with an energy-dependent asymmetric Breit-Wigner line shape representing a resonance in the continuum. Accompanying shell model calculations combined with cross-section calculations using the eikonal reaction theory indicate that these features in the decay energy spectrum originate from multiple resonant states in 31Ne.
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Title: Patient-specific prediction of abdominal aortic aneurysm expansion using efficient physics-based machine learning approaches
Creator: Jiang, Zhenxiang
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Computational vascular Growth and Remodeling (G&R) models have been developed to capture key physiological and morphological features during the arterial disease progression and have shown promise for aiding clinical diagnosis, prognosis prediction, and staging classification. However, the translation of computational G&R models into their applications has yet to wait for clinical practice. Partly, due to the high complexity of the arterial adaptation mechanism, high-fidelity arterial G&R...
Show moreComputational vascular Growth and Remodeling (G&R) models have been developed to capture key physiological and morphological features during the arterial disease progression and have shown promise for aiding clinical diagnosis, prognosis prediction, and staging classification. However, the translation of computational G&R models into their applications has yet to wait for clinical practice. Partly, due to the high complexity of the arterial adaptation mechanism, high-fidelity arterial G&R simulations typically require hours or even days, which hinders its time-consuming applications such as patient-specific parameter estimation, disease prediction, verification, validation, and sensitivity analysis. Furthermore, the typical Finite Element Method (FEM) based computational G&R model should be extended to provide the uncertainty quantification associated with simulation and prediction results. Therefore, to enhance practicality of the G&R modeling, we develop a novel and computationally efficient simulation framework that comprehensively combines physics-based G&R simulations and data-driven machine learning methods using a Multi-Fidelity Surrogate (MFS) approach. This greatly enhances the computational efficiency of arterial G&R simulations, enabling more time-consuming applications such as personalized parameter estimation. The proposed framework is then tested for a specific disease, Abdominal Aortic Aneurysms (AAAs), by estimating G&R model parameters from follow-up CT images in 21 patients.
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Title: IT’S LIKE LOOKING IN A MIRROR, ONLY NOT : THE INFLUENCE OF ACQUIRER-TARGET SIMILARITY ON CORPORATE ACQUISITIONS
Creator: Wuorinen, Stefan
Date: 2022
Collection: Electronic Theses & Dissertations
Description: With the recent explosion of behavioral acquisition research, the collective knowledge in respect to acquisition behavior and outcomes has advanced tremendously. Despite these advancements, due to the rapid growth in this literature, various shortcomings have also developed. One such shortcoming is that the vast majority of this literature has examined acquisition influences emanating from the acquirer or the target but has rarely investigated the joint effects of these two entities. As such,...
Show moreWith the recent explosion of behavioral acquisition research, the collective knowledge in respect to acquisition behavior and outcomes has advanced tremendously. Despite these advancements, due to the rapid growth in this literature, various shortcomings have also developed. One such shortcoming is that the vast majority of this literature has examined acquisition influences emanating from the acquirer or the target but has rarely investigated the joint effects of these two entities. As such, in an attempt to contribute to the growing wealth of acquisition knowledge, the aim of this dissertation is to extend this research by examining how the degree of similarity between the acquirer and target can contribute to the outcomes of acquisition decisions. Specifically, this dissertation first investigates the implications for post-acquisition innovation due to pre-acquisition authority structure similarity, while also introducing and testing the arguments of Structural Adaptation Theory to the macro-organizational level and acquisition literature. Second, the influence of CEO regulatory fit between acquirer and target executives and the degree to which their respective orientations align with each manager’s negotiation roles within an acquisition are argued to influence acquisition premium and market reactions. Collectively, these studies begin to illuminate the joint affects that acquirers and targets have on distinct acquisition outcomes.
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Title: Application of topological data analysis and machine learning for mutation induced protein property change prediction
Creator: Wang, Menglun
Date: 2021
Collection: Electronic Theses & Dissertations
Description: Mutagenesis is a process by which the genetic information of an organism is changed, resulting in a mutation. A lot of diseases are caused by mutation of protein, including Cystic fibrosis, Alzheimer's Disease and most of cancer. To get a better understanding of mutation induced protein properties change, accurate and efficient computational models are urgently needed. For protein-protein binding affinity changes upon mutation ($\Delta\Delta G$), we built a prediction model called TopNetTree....
Show moreMutagenesis is a process by which the genetic information of an organism is changed, resulting in a mutation. A lot of diseases are caused by mutation of protein, including Cystic fibrosis, Alzheimer's Disease and most of cancer. To get a better understanding of mutation induced protein properties change, accurate and efficient computational models are urgently needed. For protein-protein binding affinity changes upon mutation ($\Delta\Delta G$), we built a prediction model called TopNetTree. Algebraic topology, a champion in recent worldwide competitions for protein-ligand binding affinity predictions, is a promising approach for simplifying the complexity of biological structures. Here, we introduce element-specific and site-specific persistent homology, a new branch of algebraic topology, to simplify the structural complexity of protein-protein complexes and embed crucial biological information into topological invariants. Additionally, we propose a new deep learning algorithm called NetTree, to take advantage of convolutional neural networks and gradient boosting trees. A topology-based network tree (TopNetTree) is constructed by integrating the topological representation and NetTree for predicting PPI $\Delta\Delta G$. Tests on major benchmark datasets indicate that the proposed TopNetTree significantly improves the current state-of-art in $\Delta\Delta G$ prediction.For mutation induced protein folding energy change, we proposed a local topological predictor (LTP) based machine learning model. To characterize molecular structure, Hessian matrix of local surface is generated from Exponential and Lorentz density kernel. Eigenvalues of Hessian matrix are calculated as local topological predictor, which are then fed into gradient boost machine learning model as features. Our LTP model obtained state-of-art results for various benchmark data sets of mutation induced protein folding energy change
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Title: THE ROLE OF ARID1A IN ENDOMETRIOSIS-RELATED INFERTILITY
Creator: Marquardt, Ryan Michael
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The inner lining of the uterus, the endometrium, is composed of a luminal epithelial cell layer supported by an underlying stroma which contains epithelial gland structures. These distinct cell types coordinate with complex and dynamic molecular crosstalk tightly controlled by ovarian steroid hormones to regulate a healthy menstrual cycle and support the initiation and maintenance of a healthy pregnancy. Endometriosis occurs when endometrium-like tissue forms lesions outside the uterine...
Show moreThe inner lining of the uterus, the endometrium, is composed of a luminal epithelial cell layer supported by an underlying stroma which contains epithelial gland structures. These distinct cell types coordinate with complex and dynamic molecular crosstalk tightly controlled by ovarian steroid hormones to regulate a healthy menstrual cycle and support the initiation and maintenance of a healthy pregnancy. Endometriosis occurs when endometrium-like tissue forms lesions outside the uterine cavity, and this painful disease afflicts about 10% of reproductive-age women, an estimated 176 million worldwide. Up to 50% of these individuals also experience infertility, and many cases cannot be explained by morphological or ovarian defects, which implicates a uterine environment that is non-receptive to embryo implantation. The molecular basis for the correlation between endometriotic lesion presence and a non-receptive endometrium is unclear, but available evidence suggests that dysregulation of epigenetic regulators may play a role. Expression of AT-rich interaction domain 1A (ARID1A), a chromatin remodeling factor, is lost in some endometriotic lesions and markedly reduced in endometrial biopsies from infertile women with endometriosis, but it is essential in the uterus for fertility. This dissertation evaluates the overarching hypothesis that ARID1A loss connects endometriosis and infertility by causing increased lesion development and a non-receptive endometrium. Chapter 1 provides a review of the current literature on the topics of normal ovarian steroid hormone regulation of endometrial function, the dysregulation that occurs in endometriosis with its clinical implications and therapeutic options, and the specific involvement of ARID1A in endometrial pathophysiology. Chapter 2 delineates a critical role for endometrial epithelial ARID1A in uterine gland function for fertility. Chapter 3 reports the need for endometrial epithelial ARID1A to maintain uterine immune homeostasis during early pregnancy. Chapter 4 explores the involvement of endometrial ARID1A loss in a mouse model of endometriosis-related infertility. Chapter 5 describes a method for in vivo photoacoustic imaging of this endometriosis mouse model through the application of nanoparticle labeling. Finally, Chapter 6 summarizes the findings, discusses conclusions from the synthesized data in the context of the current literature, and provides ideas for future studies of related topics. Together, the studies herein make the case that endometrial ARID1A loss contributes to endometriosis-related infertility by exacerbating endometriotic lesion formation and compromising the ability of the endometrium to maintain the gland function and immune homeostasis necessary for the establishment and maintenance of pregnancy. Continued investigation through studies like these is key to understanding endometrial pathophysiology at the molecular level in order to enable development of targeted treatment options for women suffering the devastating effects of endometriosis and related infertility.
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Title: (Im)mobility in a Sea of Migration : Race, mobilities, and transnational families in Zanzibar and Oman, 1856-2019
Creator: Marshall, Judith
Date: 2021
Collection: Electronic Theses & Dissertations
Description: The central aim of this dissertation is to examine the history of connections between Omanis and Zanzibaris from the point of view of non-elites. The principle actors of histories of movements and connections between East Africa and the Arabian Peninsula has, in past scholarship, generally been elite men, principally statesmen and merchants. Many of the core assumptions about this history that have shaped past scholarship have been based on the priorities of this cast of actors whose goals...
Show moreThe central aim of this dissertation is to examine the history of connections between Omanis and Zanzibaris from the point of view of non-elites. The principle actors of histories of movements and connections between East Africa and the Arabian Peninsula has, in past scholarship, generally been elite men, principally statesmen and merchants. Many of the core assumptions about this history that have shaped past scholarship have been based on the priorities of this cast of actors whose goals and motives have been recorded in archival documents. Using oral history, this dissertation is able to offer a history “from below” that instead privileges the experiences of women and the rural poor. This research is based principally on interviews in Pemba, rural Unguja, and Oman. By shifting the central actors in this history, this dissertation is able to make several important contributions. It highlights the important divisions between Arabs in East Africa, a racial category too often discussed as if it represented a unified bloc. Further, it offers immobility as a crucial missing piece in this history that has been most often typified by the mobility of its most elite actors, arguing that mobility has been too central in our understanding of transnational communities. Keywords: Immobility, Transnationalism, Oral History, East Africa, Indian Ocean, Arab, African, Identity, Gender, Class, Race, Rural, Pemba, Zanzibar, Oman, Mobility, Migration, Revolution
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