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Title: Essays in International Trade
Creator: Park, Jun-Tae
Date: 2022
Collection: Electronic Theses & Dissertations
Description: In chapter 1, I investigate how resource reallocation can affect the change of trade patterns and welfareeffect of trade. Specifically, trade liberalization can lead to a surge in the trade of intermediate goods. Increased accessibility to the critical intermediate goods through international trade can create an opportunity to initiate the expansion of capital-intensive industries, which can be referred to as specialization dynamics for developing countries. For this to occur, domestic...
Show moreIn chapter 1, I investigate how resource reallocation can affect the change of trade patterns and welfareeffect of trade. Specifically, trade liberalization can lead to a surge in the trade of intermediate goods. Increased accessibility to the critical intermediate goods through international trade can create an opportunity to initiate the expansion of capital-intensive industries, which can be referred to as specialization dynamics for developing countries. For this to occur, domestic resources must be reallocated toward high productivity sectors. In this paper, I capture the reallocation frictions in the labor market with sectoral wage differentials. A general equilibrium analysis explains the relationship between specialization dynamics and resource reallocation. I find that higher distortions in the skilled labor market negatively affect the productivity gain in the capital-intensive sector. This effect lowers overall welfare gains from trade for the countries with higher labor market distortions. In chapter 2, I improve the argument in chapter 1 by extending the model to dynamic structural model. Sluggish labor market response to trade liberalization can reduce the welfare gains from trade by impeding resource reallocation. I estimate sectoral labor switching costs for 30 countries in a dynamic discrete choice problem to derive welfare implications of labor market rigidity through comparative cross-country analysis. On average, workers have to give up approximately 4-years of income to switch to another sector. Compared with labor market flexibility measures, labor switching costs are low when the country has a flexible labor market and vice versa. In addition, I embed the switching cost estimates into a dynamic multi-country, multi-sector Eaton and Kortum model. In a counterfactual trade liberalization simulation with a 20% drop in trade costs, high switching costs lead to a slower response in the labor market, which in turn, negatively affect a country’s ability to achieve welfare gains from trade.
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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: THE PROCESS OF LEAVING SEX TRAFFICKING : USING LIFE HISTORY CALENDAR METHODS TO UNDERSTAND THE ROLE OF FORMAL SYSTEMS AND SUPPORT
Creator: Vollinger, Lauren
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Sex trafficking (ST) is a serious and hidden social problem affecting thousands of people in United States. ST is defined as “the recruitment, harboring, transportation, provision, or obtaining of a person for the purposes of a commercial sex act” or when that person “has not attained 18 years of age” (Trafficking Victims Protection Act, 2000). Given the violent, coercive, and economic tactics used to control victims of this crime, it is challenging for individuals to leave their trafficking...
Show moreSex trafficking (ST) is a serious and hidden social problem affecting thousands of people in United States. ST is defined as “the recruitment, harboring, transportation, provision, or obtaining of a person for the purposes of a commercial sex act” or when that person “has not attained 18 years of age” (Trafficking Victims Protection Act, 2000). Given the violent, coercive, and economic tactics used to control victims of this crime, it is challenging for individuals to leave their trafficking situation. Thus, the purpose of this study was to understand how survivors exit from ST and use formal systems or services to facilitate that exit. This study presents findings from qualitative interviews with 34 survivors of domestic ST to understand the process of exiting the sex industry over time. Life History Calendar methodology was used to guide interviews about: 1) how participants conceptualized their experiences in the sex industry over time: 2) what formal systems participants had contact with during their time in the sex industry: and 3) the circumstances surrounding participants’ most recent exit from the sex industry. Results revealed that participants were in and out of ST multiple times over the course of their lives and had contact with many formal systems over time. However, what made the difference in most survivors’ last exit from the sex industry was the collaboration between formal systems to coordinate referrals and service provision. Findings from this study contribute to future research on exiting from sex trafficking and provide recommendations for policy and practice.
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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: Disentangling the branched respiratory chain of Shewanella oneidensis MR-1
Creator: Duhl, Kody Lee
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Bacteria possess a wide range of metabolic pathways, allowing them to adapt to an array of environmental changes. Focusing on these different metabolic pathways allows us to observe how bacteria catabolize substrate or use anabolic pathways to generate biomass. A more in-depth look shows that many of these pathways are redundant, meaning a single organism can conduct the same overall reactions differing only by the types of enzymes or intermediates used. Overlapping pathways are common in...
Show moreBacteria possess a wide range of metabolic pathways, allowing them to adapt to an array of environmental changes. Focusing on these different metabolic pathways allows us to observe how bacteria catabolize substrate or use anabolic pathways to generate biomass. A more in-depth look shows that many of these pathways are redundant, meaning a single organism can conduct the same overall reactions differing only by the types of enzymes or intermediates used. Overlapping pathways are common in bacteria and have become a focal point of metabolism research to determine the advantages of conserving redundant pathways throughout evolution. The metal reducing bacterium Shewanella oneidensis MR-1 is a practical model organism for metabolic studies, as it has substantial branching within its respiratory pathways. In this work, we focused on the extensive electron transport chain (ETC) of S. oneidensis MR-1 to understand the importance of seemingly redundant respiratory complexes and their functions during aerobic growth. The S. oneidensis MR-1 genome encodes four different NADH dehydrogenases (NDHs): a proton-pumping Type I NDH (Nuo), two sodium-pumping NDHs (Nqr1 and Nqr2), and one type II ‘uncoupling NDH (Ndh). NDHs oxidize NADH to move electrons into the ETC and generate ion-motive force that drives ATP synthesis, active transport, and motility. We determined that either Nuo or Nqr1 was required for aerobic growth in minimal medium. The presence of theoretically redundant complexes (Nqr2 and Ndh) did not rescue cell growth. Further, we determined that knocking out NDHs led to the inability to properly oxidize NADH. NADH build up inhibited the tricarboxylic acid cycle causing an amino acid synthesis defect and inhibiting growth of the S. oneidensis strain lacking Nuo and Nqr1. Recently, bacterial metabolic models have been developed to explain the use of energetically inefficient pathways during fast growth. Two standout models postulate that energetically inefficient pathways are used to reduce a cell’s proteome cost by eliminating thermodynamic barriers or to reduce dependence on the ETC as cells grow larger. We sought to uncover if these models applied to the respiratory chain of S. oneidensis MR-1 during aerobic growth, as the ETC can vary in energetic efficiency based on the combination of NDH and terminal oxidase used. Our findings indicate that the models apply to S. oneidensis MR-1 in the context of overflow metabolism during growth at higher growth rates, while the structuring of the ETC was not in agreement. Most importantly, determined that both carbon metabolism and the ETC were restructured for adaptive growth under differing conditions. As carbon metabolism became less efficient at faster growth rates, the NDH step of the ETC became more efficient, using complexes with higher coupling efficiencies.
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Title: ALGAL CULTIVATION AND BIOMASS UTILIZATION FOR SUSTAINABLE CARBON CAPTURE FROM THE POWER INDUSTRY
Creator: Cutshaw, Ashley
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Anthropogenic climate change is a critical issue that must be addressed with a systems approach. Greenhouse gas (GHG) emissions, like carbon dioxide (CO2), are key contributors to the climate crisis and originate from several different sources. Namely, the power industry is responsible for approximately 30% of U.S. CO2 emissions and 45% of global CO2 emissions. These emissions result from the combustion of carbon-based fuels, like coal and natural gas, and are emitted into the atmosphere in...
Show moreAnthropogenic climate change is a critical issue that must be addressed with a systems approach. Greenhouse gas (GHG) emissions, like carbon dioxide (CO2), are key contributors to the climate crisis and originate from several different sources. Namely, the power industry is responsible for approximately 30% of U.S. CO2 emissions and 45% of global CO2 emissions. These emissions result from the combustion of carbon-based fuels, like coal and natural gas, and are emitted into the atmosphere in the form of flue gas. Being a large contributor of CO2 emissions has made the power industry the focus of research efforts to develop post-combustion carbon capture technologies. This work represents a comprehensive examination of microalgal cultivation and biomass utilization as methods for post-combustion carbon capture and replacement of fossil-dependent technologies and products. Optimized pilot-scale cultivation represents a sustainable post-combustion carbon capture technology with downstream economic value. An initial study of a 100 L photobioreactor (PBR) within a 100 MW power plant was conducted to optimize the long-term, continuous cultivation of the green microalgae Chlorella sorokiniana. The culture utilized flue gas as a source of CO2 and successfully operated continuously over a year long period. Insights from this study include the growth kinetics of C. sorokiniana, optimal cultivation conditions of the PBR, and an in-depth analysis of the microbial-microalgal assemblage throughout the study. The biomass produced during the 12-month study was stored and subsequently utilized to develop methods for cell disruption and protein recovery. This work investigated a mechanochemical method, using ball milling technology and chemically induced pH changes, to efficiently extract and recover microalgal proteins. The results of this study indicate that the mechanochemical method requires less energy than existing mechanical methods, while achieving similar levels of cell disruption. In addition to protein extraction and recovery, an alternate pathway for biomass utilization was explored. Microalgal biomass and microalgal proteins contain the foundational building blocks required for synthesis of chemicals like polyols. Polyols, used for polyurethane (PU) foam production, represent another value-added product that could provide the economic incentive to invest in microalgal cultivation for post-combustion carbon capture. Using biomass and recovered proteins as feedstocks, polyols were synthesized using a one-pot, two step method. Two microalgal polyols were selected based on their characterization and were evaluated using life cycle and techno-economic frameworks. The results elucidated the environmental and economic advantages when using microalgal biomass as an alternative to petrochemicals as a feedstock for polyol synthesis. Finally, this work evaluated a combined biological and chemical post-combustion carbon capture system using microalgal cultivation and a novel microalgal amino acid salt solution (MAASS). Life cycle and techno-economic frameworks were used to compare the MAASS to a standard amine-based solvent. The results of these assessments show that the MAASS capture system performs significantly better than an amine capture system, both in terms of environmental impacts and the cost of capture. This comprehensive collection of data and analysis represents advances in the field, as well as innovative methods and technologies that further demonstrate the viability of microalgal cultivation and biomass utilization for carbon capture from the power industry.
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Title: OCCUPATIONAL STRESS AMONG EMPLOYEES IN CRIMINAL-LEGAL SYSTEMS : A META-ANALYSIS
Creator: Lawson, Spencer Grant
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Occupational stress is all too common, especially for employees in the criminal-legal system. Many sources of stress (i.e., stressors) have been shown to be associated with perceived occupational stress in the literature; yet, methodological variations and inconsistent findings across research articles obscure the empirical status of the effect of stressors on occupational stress among criminal-legal employees. To synthesize the research on this stressor-stress link, a meta-analysis was...
Show moreOccupational stress is all too common, especially for employees in the criminal-legal system. Many sources of stress (i.e., stressors) have been shown to be associated with perceived occupational stress in the literature; yet, methodological variations and inconsistent findings across research articles obscure the empirical status of the effect of stressors on occupational stress among criminal-legal employees. To synthesize the research on this stressor-stress link, a meta-analysis was conducted. Based on 80 peer-reviewed articles representing 57 unique data sets that contained 1,993 effect size estimates, random-effects analyses using multilevel modeling techniques were used to establish the grand mean effect of stressors on occupational stress. Results showed a modest effect of stressors on occupational stress (Mz = 0.15, 95% CI = [0.13, 0.18]). Importantly, the findings indicate that the strength of the effect size differed by the type of stressor. Specifically, larger effect sizes were yielded if the type of stressor was operational, followed by organizational stressors. The predicted effect size was smaller if the stressor was an individual demographic. Also, certain methodological decisions and study quality indicators moderate this effect. Overall, researchers must continue to explore the dimensions of these stressors to better understand their impact on occupational stress in criminal-legal systems. Theoretical, methodological, and practical implications of the meta-analytic findings are discussed and several directions for future research are identified in an effort to bring synergy to a disjointed evidence base.
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Title: DEVELOPMENT OF GENOMIC RESOURCES TO FACILITATE PLANT BREEDING
Creator: Bornowski, Nolan
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Recent advances in sequencing and computation power have greatly contributed to our knowledge of plant genomics, and the development and use of plant genomic resources will be critical as plant researchers and breeders address future food security in light of the increasing world population, decreasing arable land, and variable effects of climate change. Plants belonging to the mint family provide culinary, medicinal, and cultural value due to their production of secondary metabolites. Genome...
Show moreRecent advances in sequencing and computation power have greatly contributed to our knowledge of plant genomics, and the development and use of plant genomic resources will be critical as plant researchers and breeders address future food security in light of the increasing world population, decreasing arable land, and variable effects of climate change. Plants belonging to the mint family provide culinary, medicinal, and cultural value due to their production of secondary metabolites. Genome assemblies and annotations for four important culinary herbs were generated to highlight genes involved in terpenoid biosynthetic pathways. Maize (Zea mays L.) is the most produced crop worldwide due in part to extensive commercial breeding programs. Genome assemblies and annotations for five commercially relevant maize inbred lines belonging to the stiff-stalk heterotic group were generated to characterize the pan-stiff-stalk gene repertoire and genomic regions associated with these founder lines. Tepary bean (Phaseolus acutifolius A. Gray), a close relative of the common bean (Phaseolus vulgaris L.), is indigenous to the arid climates of northern Mexico and produces high seed yields under drought stress. A diverse panel of tepary bean accessions was assembled, genotyped, and phenotyped to identify genomic regions associated with key agronomic traits that can be harnessed for tepary bean improvement.
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Title: DEVELOPMENT OF A NEWS SUBSCRIPTION MOTIVATION SCALE
Creator: Chen, Weiyue
Date: 2022
Collection: Electronic Theses & Dissertations
Description: As news organizations face accelerated loss in advertising revenue, increasing importance is placed on strategies to increase subscription sales. Although previous studies have found several predictors of paywall, willingness to pay, and paying for news research, these factors did not fit into one clear conceptual framework that links them together. In this dissertation, I aim to introduce a new construct, News Subscription Motivation, that provides theoretical linkages between different...
Show moreAs news organizations face accelerated loss in advertising revenue, increasing importance is placed on strategies to increase subscription sales. Although previous studies have found several predictors of paywall, willingness to pay, and paying for news research, these factors did not fit into one clear conceptual framework that links them together. In this dissertation, I aim to introduce a new construct, News Subscription Motivation, that provides theoretical linkages between different predictors of paying for news. Mixed method research was employed to conceptualize and operationalize this new construct. In Chapter 1, I discuss my thought process developing this study, the purpose of the study, and why this topic matters in the context of digital economy. Chapter 2 includes a review of previous research on what drives people to pay for news, and the literature on consumer decision-making processes, consumer decision-making styles, and consumer motivation in general. The need to develop a new construct and measurement tools that are specially designed for news consumption was also addressed. In Chapter 3, I conducted 22 in-depth interviews to generate possible dimensions of the construct, analyzed the qualitative data to propose a conceptual framework and definition. Study 1 results suggested nine possible dimensions: content utility, journalism quality, price, convenience, hitting the paywall, surveillance, being a good citizen, brand reputation, and journalism. Conceptual definitions of each dimension were also elaborated. Chapter 4 focuses on the operationalization of News Subscription Motivation. An initial items pool was generated based on Study 1. After the pilot test, I recruited two independent samples, and they were respectively subjected to Exploratory Factor Analysis and Confirmatory Factor Analysis. The final scale included six dimensions with 19 items, and this scale demonstrated robust model fit and adequate convergent and discriminant validity. Six dimensions of News Subscription Motivation were identified: supporting journalism, journalism quality, triggered by the paywall, community attachment, price, and content utility. In Chapter 5, I aim to establish the nomological validity of News Subscription Motivation. Factors extracted from Chapter 4 demonstrated statistically significant relationships with numbers of news subscription people report paying for, types of subscriptions people get, and individuals’ intention to maintain their primary subscriptions in the next 3 months, 6 months, and 12 months. Finally, I discuss the theoretical and practical implications of the scale of News Subscription Motivation in Chapter 6.
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Title: NATIVE AMERICAN COMMUNITY PERSPECTIVES ON RENEWABLE ENERGY TECHNOLOGY
Creator: Gregorini, Jared
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Future generations of humans and our non-human relatives will face the environmental consequences of a human-first approach towards development. The transition from fossil fuels towards renewable energy sources represents a deviation in behavior back to the eco-centric principles practiced by our ancestors for millennia. Renewable energy technology and infrastructure development often faces barriers within communities for numerous reasons. Using Native Nation Building theory from the...
Show moreFuture generations of humans and our non-human relatives will face the environmental consequences of a human-first approach towards development. The transition from fossil fuels towards renewable energy sources represents a deviation in behavior back to the eco-centric principles practiced by our ancestors for millennia. Renewable energy technology and infrastructure development often faces barriers within communities for numerous reasons. Using Native Nation Building theory from the community development literature as a foundation, this thesis examines the perspectives of tribal affiliated individuals for initiating renewable energy development in a Michigan tribal community. The study relies on 14 semi-structured interviews with tribal citizens and employees in one Native American community that has repeatedly expressed interest in developing renewable energy infrastructure projects on tribal lands. Through thematic analysis, observations, and personal experience, I show how both required elements of Native Nation Building have not been fulfilled and barriers to development are a result of conditions witnessed during repeated site visits to conduct qualitative interviews. This research makes it clear that the barriers identified by academic literature are overshadowed by the conditions witnessed while interacting with tribal community members. In addition to participatory based action research strategies, I argue that addressing poor community conditions is necessary while attempting community development projects focused on renewable energy transitions.
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Title: The efficacy of implementing a technology-mediated dialogic pedagogy to support reading comprehension in virtual and co-located settings
Creator: Working, Christopher Scott
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Text-based discussion within a technology-mediated dialogic discussion (T+DLD) has the potential to engage students in higher-level reading comprehension with upper elementary students. While supported empirically, this approach is still not commonplace, and little is known about its efficacy within a remote setting. The primary aim of this project was to synthesize what is currently known about T+DLD and to explore changes in discussion within a remote setting to support practitioners...
Show moreText-based discussion within a technology-mediated dialogic discussion (T+DLD) has the potential to engage students in higher-level reading comprehension with upper elementary students. While supported empirically, this approach is still not commonplace, and little is known about its efficacy within a remote setting. The primary aim of this project was to synthesize what is currently known about T+DLD and to explore changes in discussion within a remote setting to support practitioners enacting the approach. This was achieved through a systematic review of the literature on T+DP that analyzed 18 included studies for study quality as well as patterns around study features (i.e., instructional design, environmental factors, task, methodology). Text-based discussion via web-based teleconferencing was studied using a comparative case study using sociocultural discourse analysis to study student discussion in three different training conditions: dialogic only, technology only, and a T+DLD training. A pathway of implementation was then developed to translate research into practice to support teachers in adopting T+DLD. A key finding within this project was that T+DLD builds on the key elements of ground rules for talk, an open task, and student reflection for talk. Additionally, the pedagogical approach of the teacher influences the way technology is used by students. Finally, technology can successfully support T+DLD in both co-located and remote settings. This dissertation provides recommendations for future research that compares methods of implementation and evaluates the direct impact on reading comprehension.
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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: THREE ESSAYS ON THE CHOICE OF COLLEGE MAJOR AND TRADE EXPOSURE
Creator: Wu, Yu-Siang
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This dissertation is composed of three chapters on the effects of import exposure. For my dissertation I mainly use the variation of import competition across local labor markets to explore its impact on labor market outcomes (e.g., wages and employment status), human capital investment decisions (choice of college major), and education-job mismatch.Chapter one explores the relationship between increasingly intense Chinese import competition and American college students’ choice of major in...
Show moreThis dissertation is composed of three chapters on the effects of import exposure. For my dissertation I mainly use the variation of import competition across local labor markets to explore its impact on labor market outcomes (e.g., wages and employment status), human capital investment decisions (choice of college major), and education-job mismatch.Chapter one explores the relationship between increasingly intense Chinese import competition and American college students’ choice of major in the 2000s. By employing a modified version of the measure for Chinese import competition from Autor, Dorn, and G. Hanson (2013) and analyzing the relationship between industries and college majors, I find that rising Chinese trade exposure of nineteen industries in the 2000s has a negative effect on American students’ choice ofsix engineering majors. The magnitudes of the effects range from 0.62 to 0.69 percentage point decreases in the probability of choosing those six engineering majors. I also find that males are more negatively affected by Chinese import competition in terms of the choice of the six engineering majors, whereas no significant results exist if I restrict my sample to females.Chapter two analyzes how increased trade exposure affects students’ choice of STEM major. I first present a simple model to illustrate how trade exposure impacts students’ utility functions through their self-beliefs about labor market outcomes and then use assorted data to show that import competition positively affects the choice of STEM major. I find that increased import exposure in the 2000s leads to 1.05 and 0.72 percentage point increases in the probability of choosing STEM majors for college underclassmen and upperclassmen, respectively. As for labor market outcomes, my results suggest that a rise in import competition leads to a pronounced negative effect on weekly wages, employment status, and full-time employment across STEM and non-STEM occupations from the late 1990s through the 2000s. STEM occupations, however, are less negatively impacted by import competition, which helps explain why a rise in import exposure increases the probability of students choosing STEM majors.Chapter three investigates the impact of import exposure on education-occupation mismatch. I first use the concept of a matching function to explain the connection between mismatch and the supply of and demand for college graduates. Next, I use an input-output table to construct a measure of import exposure that accounts for both direct and indirect trade shocks. Findings show that increased import exposure leads to a rise in education-occupation mismatch from 2011 through 2019. Moreover, for the supply side I present that a rise in import exposure significantly increases the number of bachelor’s degrees awarded in 4-year colleges and in most degree fields. However, for the demand side, I do not observe corresponding increases in occupational employment for most fields of education. The unbalanced demand for and supply of college graduates might potentially explain the rise in education-occupation mismatch.
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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: Differential Effects in Exposure to ACEs and Problematic Drinking : An Examination of Protective Factors
Creator: Welch, Timothy Sean
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Exposure to Adverse Childhood Experiences (ACEs) has been associated with numerous negative developmental outcomes across the lifespan, including problematic drinking. However, not all individuals exposed to ACEs go on to drink problematically. This difference in the effect of exposure to ACEs on drinking use is an example of heterogeneity and is called a differential effect. Relatively little research has examined what factors predict resilience to the harmful effects of ACEs. Most existing...
Show moreExposure to Adverse Childhood Experiences (ACEs) has been associated with numerous negative developmental outcomes across the lifespan, including problematic drinking. However, not all individuals exposed to ACEs go on to drink problematically. This difference in the effect of exposure to ACEs on drinking use is an example of heterogeneity and is called a differential effect. Relatively little research has examined what factors predict resilience to the harmful effects of ACEs. Most existing research has examined either a single protective factor or examined the total number of protective factors in a cumulative scale. No study has yet to specifically examine differential effects in the context of ACEs and alcohol use. The aim of this study was to examine differential effects in exposure to ACEs and alcohol use to empirically identify a resilient group of individuals. Two research questions drove this study 1) How can heterogeneity in the association between ACEs and alcohol use be characterized? and 2) What factors predict group membership? Using data from the National Longitudinal Study of Adolescent to Adult Health (Add health), two complimentary analytic tools were used to achieve these aims: Regression Mixture Modeling (RMM) and Structural Equation Model Trees (SEM trees). Results from the RMM found evidence of two groups: a resilient group consisting of 72.6% percent of the sample and a harmful effects group consisting of 27.4% percent of the sample. Two factors were positively associated with belonging to the resilient group, school bonding and self-control. One factor, having a mentor, was associated with a lower likelihood of being in the resilient group. Results from the SEM-tree divided the data into three groups based on two variables: self-esteem and having a mentor. In this analysis, higher self-esteem and having a mentor during adolescence were both associated with problematic drinking. Findings from this study provide empirical evidence of a resilient group of individuals for whom there is not an association between exposure to ACEs and alcohol use. Despite testing multiple theoretically based protective factors, only school bonding and problem solving were associated with resilience. This suggests future research should consider additional alternative protective factors. The results suggest therapists and clinicians working with youths exposed to ACEs should work to foster increased levels of school bonding during adolescence and should assess levels of self-control and focus on helping youths develop greater self-control.
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Title: SLEEP MANAGEMENT AS A COLLABORATIVE WORK FOR THE FAMILY : DESIGNING SLEEP MANAGEMENT SYSTEMS TO IMPROVE BEDTIME ROUTINE
Creator: Shin, Ji Youn
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Sleep is a vital health issue. In families with young children, sleep problems can influence the physical, emotional, and behavioral health of all family members. Previous studies have investigated sleep as an individual activity, rarely considering the interconnected aspects of sleep among family members. To understand the social aspects of family sleep, this dissertation consists of two studies which can help researchers and designers understand the core issues of family sleep and address...
Show moreSleep is a vital health issue. In families with young children, sleep problems can influence the physical, emotional, and behavioral health of all family members. Previous studies have investigated sleep as an individual activity, rarely considering the interconnected aspects of sleep among family members. To understand the social aspects of family sleep, this dissertation consists of two studies which can help researchers and designers understand the core issues of family sleep and address them through the design of sleep-support technology. In the first study, I identified sleep as a complex experience entangled with the social dynamics between family members. For example, children's sleep means time not just for children to rest, but for a parent to have self-care. The results suggested how the boundaries that define sleep in terms of time (at night), space (in bedrooms), and unit of analysis (individual-focused) limit designers' opportunities to tackle the deeper sleep issues of families. I also suggest "division of labor" as an important but rarely discussed design concept to enhance family sleep, and as a promising design theme for home technologies that address issues emerging from social dynamics between household members. In the second study, by incorporating the identified themes from the first stage, I designed and tested two types of family-based sleep management prototypes. These prototypes redistributed the sleep-relevant tasks among family members and provided them with chances to reflect on the difficulties and values involved in the tasks. Through the in-the-wild study deploying two design prototypes in home settings, this study empirically revealed the importance of considering social dynamics as a design factor for family sleep management technologies. Implications of future design are discussed.
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Title: Assessing Theoretical Mediators of Campaign-Induced Communication in the Context of Social Norms Campaigns
Creator: Park, Sunyoung
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The present paper examines the role of campaign-induced communication on the effects of a social norms campaign by focusing on cognitive elaboration, perceived injunctive norms, and message recall as mediating variables. Participants (n = 252) read an injunctive norms campaign message about choosing not to drink at parties or when socializing and were randomly assigned to one of three conditions (control: received no prompts, prompt only; received prompts to engage in interpersonal...
Show moreThe present paper examines the role of campaign-induced communication on the effects of a social norms campaign by focusing on cognitive elaboration, perceived injunctive norms, and message recall as mediating variables. Participants (n = 252) read an injunctive norms campaign message about choosing not to drink at parties or when socializing and were randomly assigned to one of three conditions (control: received no prompts, prompt only; received prompts to engage in interpersonal communication about the campaign message with close others during the following week; prompt & plan: received prompts to engage in interpersonal communication with close others during the following week and to write a plan for the communication). The results revealed that the prompt (either alone or with the plan) significantly motivated participants to engage in positive conversations about the campaign message during the next week. Similar to past findings (Morgan et al., 2018), a higher frequency of positive conversations about the campaign message indirectly predicted better behavioral outcomes via higher cognitive elaboration. The findings suggest that social norms campaign developers should be encouraged to design social norms messages with a brief prompt to motivate the target audience to engage in interpersonal communication and need to account for such interpersonal communication and its indirect effects in evaluating campaign messages.
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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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