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- Title
- ESSAYS ON COMMUNITY FOCUSED SUPPLY CHAINS
- Creator
- Cole, Dustin
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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Businesses are increasingly being called upon to improve their Environment, Social and Governance (ESG) performance. The need to tackle a range of concerns, both environmentally and socially, can be seen in the United Nations’ 17 development goals set forth in 2015. Beyond governments and regulators, businesses themselves are increasingly aware of the importance of addressing such issues. Two hundred of the top CEOs of the country have emphasized the importance of the role that businesses...
Show moreBusinesses are increasingly being called upon to improve their Environment, Social and Governance (ESG) performance. The need to tackle a range of concerns, both environmentally and socially, can be seen in the United Nations’ 17 development goals set forth in 2015. Beyond governments and regulators, businesses themselves are increasingly aware of the importance of addressing such issues. Two hundred of the top CEOs of the country have emphasized the importance of the role that businesses play in confronting community-related issues and Diversity, Equity and Inclusion (DEI) (Murray 2019). In a series of three essays, this dissertation focuses on the social and environmental sustainability aspects of ESG, thus contributing substantially to the overall domain of sustainability. The first essay examines the impact of leader-worker disability status similarity on front-line manufacturing worker productivity using micro-data gathered from a real-world organization in Michigan. It contributes to the nascent field of inclusive operations and explores how organizations can both be profitable and inclusive of traditionally marginalized workers. The essay focuses on the moderating influence of direct supervisors with a disability on workgroup productivity as the number of workers with disabilities increases. Results suggest that a direct supervisor with a disability does indeed benefit the productivity of workers with disabilities. This benefit, however, is the mitigation of potential productivity declines as the number of workers with a disability increases in the workgroup. A follow-up qualitative study is performed to understand the mechanisms of the productivity benefit by interviewing 50 workers and supervisors with and without disabilities across three organizations. The second and third essays focus on the issue of water, a resource that is increasingly important as an environmental concern. As a resource shared between communities and firms, water is an essential component of building sustainable cities and communities.The second essay examines trade-offs and synergies experienced by organizations when reducing water use and carbon emissions using secondary panel data of large firms. Previous research has found differing results of organizations trading off carbon emissions and water. Some have found reducing one comes at the expense of the other, while other research has found organizations can reduce these two concerns jointly. This past research, though, has generally been qualitative and at the facility level, without quantitative analysis at the firm level. This research fills this gap by providing a firm-level examination of such potential trade-offs using a combination of Data Envelopment Analysis and econometric methods.The third essay uses a vignette experiment with real-world procurement professionals to examine how buyers weigh the competing environmental concerns of carbon emissions and water use reductions in the supply chain against supplier location (local vs. offshore suppliers). The results show an overwhelming preference for local suppliers with lower carbon emissions, to the extent that a supplier with a superior overall environmental performance may be passed over in pursuit of local suppliers with marginally lower carbon emissions.
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- Title
- Supervised Dimension Reduction Techniques for High-Dimensional Data
- Creator
- Molho, Dylan
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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The data sets arising in modern science and engineering are often extremely large, befitting the era of big data. But these data sets are not only large in the number of samples they have, they may also have a large number of features, placing each data point in a high-dimensional space.However, unique problems arise when the dimension of the data has the same or even greater order than the sample size. This scenario in statistics is known as the High Dimension, Low Sample Size problem (HDLSS...
Show moreThe data sets arising in modern science and engineering are often extremely large, befitting the era of big data. But these data sets are not only large in the number of samples they have, they may also have a large number of features, placing each data point in a high-dimensional space.However, unique problems arise when the dimension of the data has the same or even greater order than the sample size. This scenario in statistics is known as the High Dimension, Low Sample Size problem (HDLSS). In this paradigm, many standard statistical estimators are shown to perform sub-optimally and in some cases can not be computed at all. To overcome the barriers found in HDLSS scenarios, one must make additional assumptions on the data, either with explicit formulations or with implicit beliefs about the behavior of the data. The first type of research leads to structural assumptions placed on the probability model that generates the data, which allow for alterations to classical methods to yield theoretically optimal estimators for the chosen well-defined tasks. The second type of research, in contrast, makes general assumptions usually based on the the causal nature of chosen real-world data application, where the data is assumed to have dependencies between the parameters.This dissertation develops two novel algorithms that successfully operate in the paradigm of HDLSS. We first propose the Generalized Eigenvalue (GEV) estimator, a unified sparse projection regression framework for estimating generalized eigenvector problems.Unlike existing work, we reformulate a sequence of computationally intractable non-convex generalized Rayleigh quotient optimization problems into a computationally efficient simultaneous linear regression problem, padded with a sparse penalty to deal with high-dimensional predictors. We showcase the applications of our method by considering three iconic problems in statistics: the sliced inverse regression (SIR), linear discriminant analysis (LDA), and canonical correlation analysis (CCA). We show the reformulated linear regression problem is able to recover the same projection space obtained by the original generalized eigenvalue problem. Statistically, we establish the nonasymptotic error bounds for the proposed estimator in the applications of SIR and LDA, and prove these rates are minimax optimal. We present how the GEV is applied to the CCA problem, and adapt the method for a robust Huber-loss based formulation for noisy data. We test our framework on both synthetic and real datasets and demonstrate its superior performance compared with other state-of-the-art methods in high dimensional statistics. The second algorithm is the scJEGNN, a graphical neural network (GNN) tailored to the task of data integration for HDLSS single-cell sequencing data.We show that with its unique model, the GNN is able to leverage structural information of the biological data relations in order to perform a joint embedding of multiple modalities of single-cell gene expression data. The model is applied to data from the NeurIPS 2021 competition for Open Problems in Single-Cell Analysis, and we demonstrate that our model is able to outperform top teams from the joint embedding task.
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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
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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
- Novel Depth Representations for Depth Completion with Application in 3D Object Detection
- Creator
- Imran, Saif Muhammad
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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Depth completion refers to interpolating a dense, regular depth grid from sparse and irregularly sampled depth values, often guided by high-resolution color imagery. The primary goal of depth completion is to estimate depth. In practice methods are trained by minimizing an error between predicted dense depth and ground-truth depth, and are evaluated by how well they minimize this error. Here we identify a second goal which is to avoid smearing depth across depth discontinuities. This second...
Show moreDepth completion refers to interpolating a dense, regular depth grid from sparse and irregularly sampled depth values, often guided by high-resolution color imagery. The primary goal of depth completion is to estimate depth. In practice methods are trained by minimizing an error between predicted dense depth and ground-truth depth, and are evaluated by how well they minimize this error. Here we identify a second goal which is to avoid smearing depth across depth discontinuities. This second goal is important because it can improve downstream applications of depth completion such as object detection and pose estimation. However, we also show that the goal of minimizing error can conflict with the goal of eliminating depth smearing.In this thesis, we propose two novel representations of depths that can encode depth discontinuity across object surfaces by allowing multiple depth estimation in the spatial domain. In order to learn these new representations, we propose carefully designed loss functions and show their effectiveness in deep neural network learning. We show how our representations can avoid inter-object depth mixing and also beat state of the art metrics for depth completion. The quality of ground-truth depth in real-world depth completion problems is another key challenge for learning and accurate evaluation of methods. Ground truth depth created from semi-automatic methods suffers from sparse sampling and errors at object boundaries. We show that the combination of these errors and the commonly used evaluation measure has promoted solutions that mix depths across boundaries in current methods. The thesis proposes alternate depth completion performance measures that reduce preference for mixed depths and promote sharp boundaries.The thesis also investigates whether additional points from depth completion methods can help in a challenging and high-level perception problem; 3D object detection. It shows the effect of different depth noises originated from depth estimates on detection performances and proposes some effective ways to reduce noise in the estimate and overcome architecture limitations. The method is demonstrated on both real-world and synthetic datasets.
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- Title
- Soil invertebrate interactions with microplastic pollution
- Creator
- Helmberger, Maxwell Summit
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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Microplastics are an unfortunate byproduct of human society’s increasing reliance on synthetic plastics for packaging, clothing, and other products. Microplastics have long been known to pollute the world’s oceans, but recent work has shown them to be just as prevalent, if not more so, in soil. Early findings indicate similar potential for harm to soil organisms as has been seen for marine microplastics. Yet aside from microplastics’ direct physical and toxicological effects on soil organisms...
Show moreMicroplastics are an unfortunate byproduct of human society’s increasing reliance on synthetic plastics for packaging, clothing, and other products. Microplastics have long been known to pollute the world’s oceans, but recent work has shown them to be just as prevalent, if not more so, in soil. Early findings indicate similar potential for harm to soil organisms as has been seen for marine microplastics. Yet aside from microplastics’ direct physical and toxicological effects on soil organisms, one must also consider their interactions with these organisms, the ways in which organisms may influence microplastics’ formation, occurrence, and distribution in soil as well as mediate their effects on the rest of the soil community. My research is focused on soil invertebrates’ ability to create microplastics by fragmenting large plastic debris. To advance this goal, I first developed a novel fluorescent counterstaining technique, adding a blend of Calcofluor white and Evans blue to the traditional Nile red staining approach. The counterstain allowed microplastics to be visually distinguished from chitin, cellulose, and other biological materials that may survive chemical digestion along with the plastics, making it possible to detect plastics in samples of soil invertebrate fecal material and biomass. I then investigated four soil invertebrates’ ability to generate microplastic from polystyrene (PS) foam debris. Individuals of the beetle larva Zophobas morio, the cricket Gryllodes sigillatus, the isopod Oniscus asellus, and the snail Cornu aspersum were placed in glass arenas with pieces of pristine or weathered PS foam for 24 h, after which I counted microplastic particles in the invertebrates’ fecal material, cadaver biomass, and the sand substrate of their arenas. Z. morio fragmented all plastics and produced the most detectable microplastic, C. aspersum produced almost none, and G. sigillatus and O. asellus fragmented only the weathered plastics. In a follow-up experiment with O. asellus, identical pieces of pristine PS foam were subjected to ultraviolet light, immersion in a soil suspension, and combination treatments to assess the effects of exposure to the elements on fragmentation by the isopods. Plastics immersed in the soil suspension were fragmented to a significantly greater degree than other treatments. Together, these results suggest that large plastic debris could represent a source of microplastics into soil environments, and that laboratory experiments investigating fragmentation of pristine plastics may risk underestimating the phenomenon. My further investigations focused on fragmentation of weathered PS foam by the isopods O. asellus and Trachelipus rathkii, examining fragmentation over different spans of time and the effects of natural materials as alternate substrates for the isopods. Neither species appreciably fragmented the PS foam until after 48 h, an interesting contrast to the previous experience, and O. asellus produced more fragments than T. rathkii. The presence of wood as an alternate substrate did not significantly affect fragmentation. More broadly, these results indicate that laboratory experiments should be conducted over short timescales and do not necessarily need to include alternate or supplementary food for the study organisms. In summary, the potential of soil invertebrates to affect microplastic dynamics, complicating their effects on other organisms compared to what would be seen in a standard ecotoxicological assay, should be considered when assessing this novel pollutant’s impact on soil ecosystems.
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- Title
- THE ROLE OF ARID1A IN ENDOMETRIOSIS-RELATED INFERTILITY
- Creator
- Marquardt, Ryan Michael
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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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
- VISIONING THE AGRICULTURE BLOCKCHAIN : THE ROLE AND RISE OF BLOCKCHAIN IN THE COMMERCIAL POULTRY INDUSTRY
- Creator
- Fennell, Chris
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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Blockchain is an emerging technology that is being explored by technologists and industry leaders as a way to revolutionize the agriculture supply chain. The problem is that human and ecological insights are needed to understand the complexities of how blockchain could fulfill these visions. In this work, I assert how the blockchain's promising vision of traceability, immutability and distributed properties presents advancements and challenges to rural farming. This work wrestles with the...
Show moreBlockchain is an emerging technology that is being explored by technologists and industry leaders as a way to revolutionize the agriculture supply chain. The problem is that human and ecological insights are needed to understand the complexities of how blockchain could fulfill these visions. In this work, I assert how the blockchain's promising vision of traceability, immutability and distributed properties presents advancements and challenges to rural farming. This work wrestles with the more subtle ways the blockchain technology would be integrated into the existing infrastructure. Through interviews and participatory design workshops, I talked with an expansive set of stakeholders including Amish farmers, contract growers, senior leadership and field supervisors. This research illuminates that commercial poultry farming is such a complex and diffuse system that any overhaul of its core infrastructure will be difficult to ``roll back'' once blockchain is ``rolled out.'' Through an HCI and sociotechnical system perspective, drawing particular insights from Science and Technology Studies theories of infrastructure and breakdown, this dissertation asserts three main concerns. First, this dissertation uncovers the dominant narratives on the farm around revision and ``roll back'' of blockchain, connecting to theories of version control from computer science. Second, this work uncovers that a core concern of the poultry supply chain is death and I reveal the sociotechnical and material implications for the integration of blockchain. Finally, this dissertation discusses the meaning of ``security’’ for the poultry supply chain in which biosecurity is prioritized over cybersecurity and how blockchain impacts these concerns. Together these findings point to significant implications for designers of blockchain infrastructure and how rural workers will integrate the technology into the supply chain.
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- Title
- USE OF LAGRANGIAN METHODS TO SIMULATE HEAVY STORM-INDUCED RIVER PLUME DYNAMICS AND RECREATIONAL WATER QUALITY IMPACTS IN THE NEARSHORE REGION OF SOUTHWESTERN LAKE MICHIGAN
- Creator
- Weiskerger, Chelsea
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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The Great Lakes are the primary source of drinking water for nearly 30 million people in the region. During storm events runoff from upstream watersheds and (combined) sewer overflows delivers pathogens to the Lakes. The pathogens are then transported to beaches and water intakes by the lake circulation, posing risks to human health. Fecal indicator organisms such as Escherichia coli are used to track pollution levels and to take proactive measures to manage coastal resources and to safeguard...
Show moreThe Great Lakes are the primary source of drinking water for nearly 30 million people in the region. During storm events runoff from upstream watersheds and (combined) sewer overflows delivers pathogens to the Lakes. The pathogens are then transported to beaches and water intakes by the lake circulation, posing risks to human health. Fecal indicator organisms such as Escherichia coli are used to track pollution levels and to take proactive measures to manage coastal resources and to safeguard public health by closing beaches to the public, issuing swimming advisories, etc. Predictive modeling of coastal water quality continues to be an attractive approach to generate water quality forecasts and to gain insights into key processes. Although progress has been made in understanding and quantifying the impacts of tributary loading and river plumes on microbial pollution at beaches, the impacts of extreme storm events on coastal water quality are not well-understood. As the frequency and intensity of storm events increase, the pollution footprint of extreme storm events has not been quantified in a way that can be used to inform policy. Complex nearshore features, including irregular coastlines and coastal structures calls for high-resolution modeling that is computationally demanding. While traditional Eulerian approaches to plume modeling have been previously used, comparisons with available observed plume data indicated that Lagrangian particle tracking improves prediction of plume dimensions (and hence risks) in southwestern Lake Michigan. Therefore, coupled hydrodynamic and reactive particle tracking models were developed and tested to simulate the complex dynamics of multiple river plumes induced by extreme storm events in the Chicago area in southwestern Lake Michigan. The present-day Chicago River normally flows to the Mississippi River and discharges into Lake Michigan only during “backflow” events triggered by these storms. Simulations of extreme storm-induced river plumes during years 2008, 2010, 2011, 2013 and 2017 were reported and models tested using available data on currents, water temperatures, concentrations of indicator bacteria (E. coli) and the spatial extent of turbidity plumes using MODIS Terra satellite imagery. Results suggest that plumes associated with the extreme storms persist along the Chicago shoreline for up to 24 days after the commencement of backflow release and that plume areas of influence range from 7.9 to 291 km2 in the nearshore. Plume spatiotemporal dynamics were largely related to the volume of water released via backflow events and the duration of the backflow releases. Empirical relations were proposed to allow beach and stormwater managers to predict plume spatiotemporal dynamics in real time. Model results from a Lagrangian E. coli fate and transport model were compared against monitoring data collected at 16-18 beaches during and after backflow events in 2010 and 2011. Results indicate that all Chicago Park District beaches are susceptible to E. coli concentrations that exceed USEPA thresholds for safe recreation after extreme storms. Therefore, the current approach to beach management, which involves closing all beaches during and immediately after backflow events, is likely prudent. However, results also suggest that beaches are probably being reopened prematurely after storm events, as beaches may be at risk for degraded water quality for multiple days, post backflow event. To address data gaps, we recommend that future research focus on the collection of additional in situ hydrometeorological and water quality data during and after extreme storms and backflow events. These data may be collected using unmanned aerial vehicles or autonomous sensor systems.
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- Title
- ESSAYS ON FIRMS, CLIMATE CHANGE AND FOOD SYSTEMS TRANSFORMATION
- Creator
- Nuhu, Ahmed Salim
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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This dissertation broadly examines how climate change, and the rapidly transforming agrifood value chains are impacting firms, workers, and farmers in developing countries. Chapter 1 examines the effect of ignoring adaptation when estimating the short-run impacts of temperature shocks on workers and firms in developing regions. To do this, we first obtain naïve estimates of the short-run impacts of extreme temperatures (shocks) on workers’ wages and firm output in Sub-Saharan Africa using the...
Show moreThis dissertation broadly examines how climate change, and the rapidly transforming agrifood value chains are impacting firms, workers, and farmers in developing countries. Chapter 1 examines the effect of ignoring adaptation when estimating the short-run impacts of temperature shocks on workers and firms in developing regions. To do this, we first obtain naïve estimates of the short-run impacts of extreme temperatures (shocks) on workers’ wages and firm output in Sub-Saharan Africa using the standard panel fixed effects approach. We then obtain the pure short-run effects by adjusting the naïve estimates by conditioning the effects of the temperature shocks on the historical local temperature information held by firms and workers prior to the occurrence of the temperature shocks. The difference between the naïve and the pure short-run estimates provide evidence of adaptation. We find evidence of temperature shock effects on wages and output that similar to other studies from our naïve estimates. However, the estimated effects are much higher when we condition on firms’ prior knowledge of the local temperature. This finding indicates the importance of accounting for firms and workers’ knowledge of local temperature patterns (when estimating the impacts of temperature shocks) and provides evidence of incomplete adaptation (of up to 50% of the original effects). Evidence of incomplete adaptation suggests the presence of barriers to adaptation that need to be addressed to prevent a locking-in of vulnerability to climate change impacts. In a further application to the United States in Chapter 2, we find that accounting for the historical local temperature information is less relevant in the presence of more complete adaptation that may be aided by established institutional capacity for dealing with extreme weather. Taken together, these findings reveal (1) the importance of accounting for adaptation in estimating the impacts of short-term temperature shocks in developing regions with more barriers to adaptation and (2) that policies aimed at adaptation should not ignore local institutional and environmental contexts in which adaptation occurs. Chapter 3 examines the effects of the recent rise of numerous midstream agri-food firms and their authorized agents on smallholder soybean farmers in Zambia. Specifically, I examine the implications of non-contractual sale of soybean output to midstream firms and processors for the welfare of smallholder farmers. Using fixed effects and instrumental variables estimation techniques to address the endogeneity of the smallholder decision to sell to large-scale firms, I find significant positive crop income effects of selling to soybean large-scale firms on all smallholders. However, the observed effects only translate into higher total household incomes and poverty reduction for medium-scale smallholders (operating 5 ha- 20 ha) but not for small-scale smallholders operating less than five hectares. The positive crop income effects are mainly driven by the opportunity to sell more although small-scale smallholders also receive a price premium from selling to large buyers. These results suggest that the recent rise in purchasing activity by firms in the soybean industry in Zambia is benefiting smallholder farmers but not necessarily enough to move the smallest of these farmers out of poverty.
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- Title
- SUBJECTIVE AND OBJECTIVE STRESS RESPONSES AMONG YOUNG AUTISTIC ADULTS
- Creator
- Peña, Jarhed Macarubbo
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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This study was conducted to examine the subjective (psychological) and objective (physiological) stress responses of autistic individuals guided by the Transactional Theory of Stress and Coping by Lazarus and Folkman (1984). Subjective stress responses were measured through a Visual Analog Scale (VAS) rating by the participants on their stress perception and objective stress responses were measured through heart rate variability (HRV) using a heart rate monitor as participants underwent a...
Show moreThis study was conducted to examine the subjective (psychological) and objective (physiological) stress responses of autistic individuals guided by the Transactional Theory of Stress and Coping by Lazarus and Folkman (1984). Subjective stress responses were measured through a Visual Analog Scale (VAS) rating by the participants on their stress perception and objective stress responses were measured through heart rate variability (HRV) using a heart rate monitor as participants underwent a standardized online Trier Online Stress Test (TSST; Kirschbaum et al., 1993) protocol to stimulate a social evaluative stress protocol. A systematic and qualitative interview was followed to investigate the appraisal of participants’ perception on the TSST. Literature suggests lack of insight and poor reporting of stressful experiences among autistic individuals. Participants consisted of 12 young adults with autism spectrum disorder (ASD) and 24 typically developing young adults currently attending college. Both subjective and objective stress quantitative analyses resulted in non-significant findings. However, findings suggested some between-group differences in subjective stress responses and objective stress responses for each phase of the stress stimulation (i.e., Baseline, Stress Task, Recovery). Particularly, higher observed stress perception and HRV were noted during Baseline and Recovery and lower observed stress perception and HRV were noted during the Stress Task in the ASD group. Further exploration of qualitative data findings revealed that both groups were able to have insight and self-report physical stress response such as increased heart rate and sweating, further supporting the importance of the appraisal of the stressful experience. Clinical, education, and research implications are also addressed. In terms of clinical implications, the current study highlighted young adults are susceptible to stress and can benefit from stress management intervention regardless of ASD diagnosis. Early intervention to teach autistic individuals stress management skills may also be beneficial. Furthermore, the use of objective measures can raise the awareness of one’s stress response, and that the appraisal of one’s subjective perception of stress is equally important in understanding individual differences in the stress experience. In terms of education implications, educators should train health professionals such as rehabilitation counselors in understanding diverse ways of stress manifestation and coping. They should also be trained to teach stress coping skills when working with clients, including autistic individuals. In terms of research implications, the unique methodology to combine psychological data with physiological data, as well as appraisal process to obtain cognitive information to gain a more holistic perspective on the stress experiences of participants. Future research recommends increasing sample size and diverse demographic participants, matching participants with ASD with those without, re-examining different methods to characterize potential similarities and differences among ASD, typically developing and other clinical groups, further examining not only the stress phase but also the baseline and recovery phases of the stress stimulation, improving the ASD screening to verify autism diagnosis, recruiting participants who have not received stress management intervention or training, examining the impact of in person and online TSST, and investigating the impact of comorbid conditions on stress responses in the ASD population.
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- Title
- RECREATIONAL CANNABIS LEGALIZATION : PREDICTING LOCAL POLICY ADOPTION AND ESTIMATING THE ASSOCIATED EFFECTS ON POPULATION CANNABIS USE
- Creator
- Montgomery, Barrett Wallace
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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Cannabis is undergoing a remarkable transformation from a regulated drug to a recreationally legal one in the United States (U.S.). Yet, in states that have legalized recreational cannabis, there is substantial geographic variability in actual cannabis policies and the effects of cannabis legalization are still being debated. This dissertation addresses these modern scientific issues of the recreational cannabis landscape. The population under study primarily includes non-institutionalized U...
Show moreCannabis is undergoing a remarkable transformation from a regulated drug to a recreationally legal one in the United States (U.S.). Yet, in states that have legalized recreational cannabis, there is substantial geographic variability in actual cannabis policies and the effects of cannabis legalization are still being debated. This dissertation addresses these modern scientific issues of the recreational cannabis landscape. The population under study primarily includes non-institutionalized U.S. civilian residents, sampled and assessed in successive waves of the National Survey on Drug Use and Health (NSDUH) starting in 2008 through 2019. Estimates on drug use and mental illness prevalences are aggregated to the county level for the first aim, and to the state level for the second and third aims. In the first aim, the county-level data are linked to several other publicly available sources of information on all 3,142 U.S. counties including the 2010 Census, 2012 presidential election, and recreational cannabis sales policies. I then used these data to train a machine learning algorithm to predict which counties allowed for the recreational sale of cannabis in 2014. In the second aim, I used state-level estimates of cannabis incidence in an event study model to estimate the effects of legalizing recreational cannabis on cannabis use onsets for persons under and over the legal minimum age of 21. The final aim focuses specifically on 21 year-olds to better understand the implications for setting a legal minimum age drug policy on age-specific patterns of incidence and proposes a theoretical framework that may help understand these findings. For the first aim, the model-averaging predictions classified almost 94% of the U.S. counties correctly. The main factors associated with county-level recreational cannabis laws were the prevalences of past-month cannabis use and past-year cocaine use. In the second aim, I found that for those who were legally able to purchase cannabis (21 and older), cannabis legalization did not appear to affect incidence in the first year following legalization. Even so, between two and four years after legalization, the difference in differences modeling disclosed statistically robust increases of 0.6% for this sub-population of adults. After four years, the estimated increase is 1.3%. The corresponding estimates for underage persons who were ineligible to legally purchase cannabis show no appreciable differences in the occurrence in past-year cannabis use incidence. Finally, the age-specific incidence estimates for 21-year-olds show a rise after the passage of recreational cannabis laws (RCL) and are suggestive of the arrival of a new pattern of age-specific incidence. Taken together, the work and results of this dissertation point toward four potential conclusions. First, cannabis legalization might depend on a predictable process driven in part by prior drug use in each jurisdiction. Second, once implemented, recreational cannabis legalization might not have effects on adolescent onset newly incident cannabis use. Third, for adults permitted to buy cannabis without penalty, the occurrence of newly incident cannabis use might increase. Fourth, a tentative conclusion is that legalization of retail sales to adults removes a barrier for adults who had been interested in trying cannabis, but did not do so, perhaps due to concerns about legal or social consequences faced before legalization.
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- Title
- Coalescence and Animal Use : Examining Community Building at the Multi-Ethnic Morton Village Site
- Creator
- Painter, Autumn Marie
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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Across human history, groups of people have come together, found commonalities, and negotiated their differences in order to form new communities; a process known as coalescence. Until recently, archaeologists have primarily studied this social phenomenon by looking at the large-scale changes that occur, including settlement aggregation and demography. New research has begun to focus on smaller scales of analysis, including aspects of daily life and the role of common behaviors in bringing...
Show moreAcross human history, groups of people have come together, found commonalities, and negotiated their differences in order to form new communities; a process known as coalescence. Until recently, archaeologists have primarily studied this social phenomenon by looking at the large-scale changes that occur, including settlement aggregation and demography. New research has begun to focus on smaller scales of analysis, including aspects of daily life and the role of common behaviors in bringing people together. One such aspect of daily life is food. While previous research has recognized that changes in subsistence systems, such as a need to intensify the production of food to feed larger numbers of people, are commonly part of the coalescence process, little has been done to understand how these changes would affect a community or how a socially charged medium, such as food, may have contributed to ongoing coalescence. In this dissertation, I examine how animal use intersects with the broader process of coalescence through a multidimensional analysis of faunal remains from Morton Village, a site of on-going coalescence in the central Illinois River valley. Specifically, three aspects of animal use during the coalescence process were examined: 1) studying the overall diet as it intersects with the negotiation of everyday life, 2) animal access strategies including foodsharing practices, and 3) the use of animals and animal symbolism in ritual activities as a part of the long-term process of coalescence. These analyses found that the occupants of Morton Village used a diverse range of animal species, avian symbolism, and foodsharing/distribution practices within a variety of social interactions and practices. From this data, I argue that the use of animals played an important role in the coalescence process at Morton Village by assisting in building social relationships that were critical to community formation and maintenance during the coalescence process. This study demonstrates that the study of animal use is a fruitful avenue of research that can reveal several mechanisms for how social relationships are formed and community building processes occurred during coalescence.
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- Title
- Three Essays on Panel Data Models with Interactive and Unobserved Effects
- Creator
- Brown, Nicholas Lynn
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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Chapter 1: More Efficient Estimation of Multiplicative Panel Data Models in the Presence of Serial Correlation (with Jeffrey Wooldridge)We provide a systematic approach in obtaining an estimator asymptotically more efficient than the popular fixed effects Poisson (FEP) estimator for panel data models with multiplicative heterogeneity in the conditional mean. In particular, we derive the optimal instrumental variables under appealing `working' second moment assumptions that allow...
Show moreChapter 1: More Efficient Estimation of Multiplicative Panel Data Models in the Presence of Serial Correlation (with Jeffrey Wooldridge)We provide a systematic approach in obtaining an estimator asymptotically more efficient than the popular fixed effects Poisson (FEP) estimator for panel data models with multiplicative heterogeneity in the conditional mean. In particular, we derive the optimal instrumental variables under appealing `working' second moment assumptions that allow underdispersion, overdispersion, and general patterns of serial correlation. Because parameters in the optimal instruments must be estimated, we argue for combining our new moment conditions with those that define the FEP estimator to obtain a generalized method of moments (GMM) estimator no less efficient than the FEP estimator and the estimator using the new instruments. A simulation study shows that the GMM estimator behaves well in terms of bias, and it often delivers nontrivial efficiency gains -- even when the working second-moment assumptions fail.Chapter 2: Information equivalence among transformations of semiparametric nonlinear panel data modelsI consider transformations of nonlinear semiparametric mean functions which yield moment conditions for estimation. Such transformations are said to be information equivalent if they yield the same asymptotic efficiency bound. I first derive a unified theory of algebraic equivalence for moment conditions created by a given linear transformation. The main equivalence result states that under standard regularity conditions, transformations which create conditional moment restrictions in a given empirical setting need only to have an equal rank to reach the same efficiency bound. Example applications are considered, including nonlinear models with multiplicative heterogeneity and linear models with arbitrary unobserved factor structures.Chapter 3: Moment-based Estimation of Linear Panel Data Models with Factor-augmented ErrorsI consider linear panel data models with unobserved factor structures when the number of time periods is small relative to the number of cross-sectional units. I examine two popular methods of estimation: the first eliminates the factors with a parameterized quasi-long-differencing (QLD) transformation. The other, referred to as common correlated effects (CCE), uses the cross-sectional averages of the independent and response variables to project out the space spanned by the factors. I show that the classical CCE assumptions imply unused moment conditions which can be exploited by the QLD transformation to derive new linear estimators which weaken identifying assumptions and have desirable theoretical properties. I prove asymptotic normality of the linear QLD estimators under a heterogeneous slope model which allows for a tradeoff between identifying conditions. These estimators do not require the number of cross-sectional variables to be less than T-1, a strong restriction in fixed-$T$ CCE analysis. Finally, I investigate the effects of per-student expenditure on standardized test performance using data from the state of Michigan.
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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
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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
- EXAMINING THE RELATIONSHIP AMONG PHYSICAL ACTIVITY, STRESS, DEPRESSION, AND ANXIETY IN COLLEGE STUDENTS
- Creator
- Hayden, Dorian James
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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Mental health challenges have been steadily increasing around college campuses, with consistent findings pointing to ethnic minorities and low socioeconomic groups adversely affected and needing more support than their counterparts. On the other end, physical activity (PA) has consistently been associated with positive mental health outcomes. Therefore, further understanding the relationship among race, socioeconomic status, and PA, as well as college students personal experiences on campuses...
Show moreMental health challenges have been steadily increasing around college campuses, with consistent findings pointing to ethnic minorities and low socioeconomic groups adversely affected and needing more support than their counterparts. On the other end, physical activity (PA) has consistently been associated with positive mental health outcomes. Therefore, further understanding the relationship among race, socioeconomic status, and PA, as well as college students personal experiences on campuses, is of great importance to improve college student well-being. This two-study dissertation sought to address these relationships. Study 1 evaluated differences in mental health across race, parental education (proxy for SES) and PA. Student obstacles to using on-campus mental health and PA resources were examined in a mixed methods design. Most of the data was collected prior to the establishment of COVID-19 restrictions at a large Midwest university. Mental health levels were anticipated to vary between the variables of race, parental education, and PA, which was partially supported. Results showed that low SES participants had significantly higher levels of depression, while PA was associated with lower levels of anxiety and stress. Study 2 sought to replicate findings of study 1 and test the relationships within the context of a diathesis-stress model that includes PA using an expanded sample of students drawn from a large Midwest university and a smaller East Coast university. In addition to replicating study 1 findings, study 2 yielded several themes that revealed common obstacles of college students and how they overcome those obstacles. The hypothesized relationship among race, SES, PA and mental health was partially supported. Specifically, participants whose parents or guardians had lower levels of education reported higher levels of anxiety, while there were significant differences in mental health across different levels of PA. The other goal of this study was to map the above relationship onto a PA moderating model, including variables of race, parental education, depression, stress, and anxiety, based on an adapted diathesis-stress model. This relationship was not supported by the data. Free response answers revealed interesting themes related to the college student experience and campus resources. Focus groups added to this through discussions on topics like the COVID-19 pandemic, mental health, and advice for future students. Data from study 2 was collected while COVID-19 pandemic restrictions were in place. Overall results expanded knowledge on the experience of COVID-19 on college campus and the interconnection between race, parental education, PA, and mental health. Further social relations were important for student wellbeing. Students’ also shared obstacles they faced with the use of on campus mental health and other resources.
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- Title
- Profiles of Student Engagement in Synchronous and Asynchronous Science Instruction
- Creator
- Schell, Matthew J.
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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Virtual instruction at the K-12 level is on the rise, yet we know very little about the ways students engage in different types of virtual instruction. The goals of this study were to: 1) describe high school students’ engagement in virtual science courses in terms of behavioral, affective, cognitive-value, and cognitive-self regulatory dimensions; 2) explore whether students’ engagement patterns across these dimensions differed depending on whether science activities were synchronous or...
Show moreVirtual instruction at the K-12 level is on the rise, yet we know very little about the ways students engage in different types of virtual instruction. The goals of this study were to: 1) describe high school students’ engagement in virtual science courses in terms of behavioral, affective, cognitive-value, and cognitive-self regulatory dimensions; 2) explore whether students’ engagement patterns across these dimensions differed depending on whether science activities were synchronous or asynchronous; and 3) examine whether these engagement patterns were associated with students’ final course grades or over-summer retention in a virtual high school. Students enrolled in a range of science courses at virtual high school (n=124) provided multiple reports (n=493) of their engagement during both synchronous and asynchronous learning activities. Latent Profile Analysis (LPA) conducted with these data suggested five distinct situational engagement profiles representing different constellations of the affective, behavioral, cognitive-value, and cognitive-self-regulatory dimensions of engagement. During synchronous instruction, students tended to engage in ways characterized by higher engagement in all dimensions compared with asynchronous instruction. These high engagement profiles were also associated with higher final course grades. There were few differences in the extent to which profiles predicted retention; however, lower self-regulation was associated with higher rates of retention.
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- Title
- Examining an Important Assumption in the Faultline Literature
- Creator
- Guo, Zhiya
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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Group faultlines are defined as hypothetical dividing lines that split a team into subgroups based on the alignment of team members’ attributes. Prior faultline research has almost exclusively focused on the implications of between-subgroup relationships assuming that “team members form homophilous ties on either side of a faultline by associating with others in the team who have similar demographic attributes” (Ren et al., 2015, p. 390). However, this important assumption has not been tested...
Show moreGroup faultlines are defined as hypothetical dividing lines that split a team into subgroups based on the alignment of team members’ attributes. Prior faultline research has almost exclusively focused on the implications of between-subgroup relationships assuming that “team members form homophilous ties on either side of a faultline by associating with others in the team who have similar demographic attributes” (Ren et al., 2015, p. 390). However, this important assumption has not been tested. Drawing from social comparison theory and its “similarity hypothesis,” I argue that homogeneous, faultline-based subgroups may serve as a hotbed for social comparisons, and comparisons on social power can engender conflict under certain circumstances, triggering within-subgroup conflict. More specifically, consistent with the emerging research that recognizes different types of group faultlines, I outlined a) different dimensions that different faultline-based subgroups are more likely to compare and b) the downstream effects of these comparisons. Hypotheses were tested using multi-wave, round-robin data from multiple intact work teams of full-time employees. Results largely supported my predictions regarding knowledge-based subgroups but not so much for identity-based subgroups or resource-based subgroups. Implications and future directions are discussed.
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- Title
- Leveraging Angiosperm Pangenomics to Understand Genome Evolution
- Creator
- Yocca, Alan E.
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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My dissertation work focused on species-level comparative genomics and pangenomics to describe patterns of genetic variation. I studied multiple systems and unsurprisingly discovered different patterns of variation. Within a species, individuals are genetically diverse. There are some DNA regions present in every individual (core), while others may be specific to a single individual or lineage (variable). The sum of the genetic sequences found across an entire taxonomic group is called the...
Show moreMy dissertation work focused on species-level comparative genomics and pangenomics to describe patterns of genetic variation. I studied multiple systems and unsurprisingly discovered different patterns of variation. Within a species, individuals are genetically diverse. There are some DNA regions present in every individual (core), while others may be specific to a single individual or lineage (variable). The sum of the genetic sequences found across an entire taxonomic group is called the pangenome. This DNA variation greatly contributes to observed phenotypic differences between individuals. Therefore, to understand genome evolution and the link between genotype and phenotype, we must understand the pangenome. In this work, I compare the core and variable genetic regions both coding and noncoding across different flowering plant lineages. I note many consistent features across lineages as well as ways in which each pangenomic pattern is unique. These consistencies and differences can be leveraged in the future to better understand genome evolution as well as how genotype relates to phenotype. Specifically, my dissertation includes four chapters; (1) Evolution of Conserved Noncoding Sequences in Arabidopsis thaliana, (2) Machine learning identifies differences between core and variable genes in Brachypodium distachyon and Oryza sativa, (3) Current status and future perspectives on the evolution of cis-regulatory elements in plants, and (4) A pangenome for Vaccinium.
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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
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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
- Characterization of the human gut resistome, microbiome, and metabolome during enteric infection
- Creator
- Hansen, Zoe A.
- Date
- 2022
- Collection
- Electronic Theses & Dissertations
- Description
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The human gut environment is replete with host-microbe and microbe-microbe interactions that shape human health. This system is also a known reservoir for antimicrobial resistance (AMR). The ubiquity of AMR is alarming, as greater than 2.8 million antibiotic-resistant infections and 35,000 deaths occur annually in the United States. Multiple human pathogens have demonstrated reduced susceptibility to various antibiotics, including enteric pathogens such as Campylobacter, Salmonella, Shigella,...
Show moreThe human gut environment is replete with host-microbe and microbe-microbe interactions that shape human health. This system is also a known reservoir for antimicrobial resistance (AMR). The ubiquity of AMR is alarming, as greater than 2.8 million antibiotic-resistant infections and 35,000 deaths occur annually in the United States. Multiple human pathogens have demonstrated reduced susceptibility to various antibiotics, including enteric pathogens such as Campylobacter, Salmonella, Shigella, and STEC, which cause millions of foodborne infections each year. The increasing incidence of antibiotic resistant enteric infections substantiates a need to further characterize these pathogens’ role in the curation and dissemination of AMR across environments. In this dissertation, a total of 223 human stools were assessed using shotgun metagenomics sequencing to investigate gut microbiome changes associated with enteric infection. Sixty-three stools were collected from patients suffering from enteric infection between 2011-2015 by the Michigan Department of Health and Human Services (MDHHS). Sixty-one of these patients submitted a follow-up sample between 1- and 29-weeks post-infection, and 99 healthy household members also submitted stools to serve as controls. In Chapter 2, a subset of patients infected with Campylobacter spp. and their related controls were investigated to assess the gut resistome, or collection of all antimicrobial resistance genes (ARGs) and their genetic precursors, related to infection. This examination revealed significantly higher ARG diversity in infected patients compared to healthy controls. Specifically, levels of multi-drug resistance (MDR) were greatly increased during infection. Three case clusters with distinct resistomes were identified; two of these clusters had unique ARG profiles that differed from those of healthy family members. In Chapter 3, a larger subset of 120 paired samples (60 infected vs. 60 recovered) were investigated to further characterize resistome and microbiome fluctuations related to infection and recovery. Again, infected patients harbored greater resistome diversity; however, recovered individuals displayed higher diversity in their microbiota composition. Despite their lower overall microbial diversity, patients with acute infections showed an increase in the abundance of members of Enterobacteriaceae, with specific expansion of the genus Escherichia. Host-tracking analysis revealed that many Enterobacteriaceae carried ARGs related to MDR and biocide resistance, a finding with broad implications for the ecology of resistance during infection. The fourth chapter explored metabolic capacity of gut microbial communities. In addition to metabolic pathway prediction, untargeted metabolomics was performed via LC/MS for 122 paired samples. Pathway annotation suggested that infected individuals contain greater microbial functional capacity, but metabolomics indicated greater overall metabolite diversity among recovered patients. Infection was associated with enhanced nitrogen and amino acid metabolism pathways. Although many metabolites remain uncharacterized, their presence or absence among individuals suggest their importance during and after infection. Altogether, the findings of this dissertation further characterize ecological consequences related to enteric infection in the human gut. Specifically, this research illustrates the importance of enteric infection in the dissemination and persistence of resistance determinants. Moreover, the expansion of Enterobacteriaceae and the evident increase in nitrogen- and amino acid-related metabolism during infection represent potential targets for future intervention practices.
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