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Title: IMPROVED DETECTION AND MANAGEMENT OF PHYTOPHTHORA SOJAE
Creator: McCoy, Austin Glenn
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Phytophthora spp. cause root and stem rots, leaf blights and fruit rots on agricultural and economically important plant species. Symptoms of Phytophthora infected plants, particularly root rots, can be difficult to distinguish from other oomycete and fungal pathogens and often result in devastating losses. Phytophthora spp. can lie dormant for many years in the oospore stage, making long-term management of these diseases difficult. Phytophthora sojae is an important and prevalent pathogen of...
Show morePhytophthora spp. cause root and stem rots, leaf blights and fruit rots on agricultural and economically important plant species. Symptoms of Phytophthora infected plants, particularly root rots, can be difficult to distinguish from other oomycete and fungal pathogens and often result in devastating losses. Phytophthora spp. can lie dormant for many years in the oospore stage, making long-term management of these diseases difficult. Phytophthora sojae is an important and prevalent pathogen of soybean (Glycine max L.) worldwide, causing Phytophthora stem and root rot (PRR). PRR disease management during the growing season relies on an integrated pest management approach using a combination of host resistance, chemical compounds (fungicides; oomicides) and cultural practices for successful management. Therefore, this dissertation research focuses on improving the detection and management recommendations for Phytophthora sojae. In Chapter 1 I provide background and a review of the current literature on Phytophthora sojae management, including genetic resistance, chemical control compounds (fungicides; oomicides) and cultural practices used to mitigate losses to PRR. In my second chapter I validate the sensitivity and specificity of a preformulated Recombinase Polymerase Amplification assay for Phytophthora spp. This assay needs no refrigeration, does not require extensive DNA isolation, can be used in the field, and different qPCR platforms could reliably detect down to 3.3-330.0 pg of Phytophthora spp. DNA within plant tissue in under 30 minutes. Based on the limited reagents needed, ease of use, and reliability, this assay would be of benefit to diagnostic labs and inspectors monitoring regulated and non-regulated Phytophthora spp. Next, I transitioned the Habgood-Gilmour Spreadsheet (‘HaGiS’) from Microsoft Excel format to the subsequent R package ‘hagis’ and improved upon the analyses readily available to compare pathotypes from different populations of P. sojae (Chapter 3; ‘hagis’ beta-diversity). I then implemented the R package ‘hagis’ in my own P. sojae pathotype and fungicide sensitivity survey in the state of Michigan, identifying effective resistance genes and seed treatment compounds for the management of PRR. This study identified a loss of Rps1c and Rps1k, the two most widely plant Phytophthora sojae resistance genes, as viable management tools in Michigan and an increase in pathotype complexity, as compared to a survey conducted twenty years ago in Michigan (Chapter 4). In Chapter 5 I led a multi-state integrated pest management field trial that was performed in Michigan, Indiana, and Minnesota to study the effects of partial resistance and seed treatments with or without ethaboxam and metalaxyl on soybean stand, plant dry weights, and final yields under P. sojae pressure. This study found that oomicide treated seed protects stand across three locations in the Midwest, but the response of soybean varieties based on seed treatment, was variety and year specific. Significant yield benefits from using oomicide treated seed were only observed in one location and year. The effects of partial resistance were inconclusive and highlighted the need for a more informative and reliable rating system for soybean varieties partial resistance to P. sojae. Finally, in Chapter 6 I present conclusions and impacts on the studies presented in this dissertation. Overall, the studies presented provide an improvement to the detection, virulence data analysis, and integrated pest management recommendations for Phytophthora sojae.
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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: 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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Title: Leveraging Angiosperm Pangenomics to Understand Genome Evolution
Creator: Yocca, Alan E.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: 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: Novel Depth Representations for Depth Completion with Application in 3D Object Detection
Creator: Imran, Saif Muhammad
Date: 2022
Collection: Electronic Theses & Dissertations
Description: 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: Characterizing and Quantifying the Relationship between Triacylglycerol and Membrane Lipids during Nitrogen Deprivation and Resupply in Chlamydomonas using Isotopic Labeling
Creator: Young, Danielle Yvonne
Date: 2022
Collection: Electronic Theses & Dissertations
Description: As concerns about energy security and climate change have increased, microalgae have emerged as a promising feedstock for biofuel production. Microalgal oils have also recently gained popularity as nutraceutical supplements, such as serving as a source of omega-3 fatty acids. If microalgal oil content is to be tailored to a favorable composition for biofuel or nutritional purposes, the major biochemical pathways contributing to oil synthesis must be characterized. Chlamydomonas reinhardtii...
Show moreAs concerns about energy security and climate change have increased, microalgae have emerged as a promising feedstock for biofuel production. Microalgal oils have also recently gained popularity as nutraceutical supplements, such as serving as a source of omega-3 fatty acids. If microalgal oil content is to be tailored to a favorable composition for biofuel or nutritional purposes, the major biochemical pathways contributing to oil synthesis must be characterized. Chlamydomonas reinhardtii was chosen as a model microalga for this work because it has served as a model system for several areas of biology for well over fifty years, and thus has many resources and tools available for its study. Several environmental stresses are known to induce oil accumulation in microalgae, and deprivation of nitrogen was chosen in this study as it is the most widely-used, is easily applied, and induces very strong accumulation of neutral oil. This dissertation describes my research findings on the biochemical relationship between membrane glycerolipids and triacylglycerol (TAG) in C. reinhardtii during nitrogen deprivation and resupply. It includes the results of my work to elucidate the flow of fatty acids during TAG synthesis and the fate of fatty acids during TAG breakdown. It also includes my analysis of the biochemical mechanisms by which membrane glycerolipids are converted into TAG as well as which lipid moieties are converted into TAG. Time course experiments and isotopic labeling were the methods used in these analyses to trace the flow of carbon between biomolecules. An overview of acyl editing is also provided in this dissertation, as it is an important component of the TAG synthesis pathway in plants that is under-explored in microalgae. Finally, the dissertation concludes with future directions and experiments that would help address the outstanding questions that remain in C. reinhardtii lipid biochemistry.
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Title: ESSAYS IN LABOR ECONOMICS
Creator: Datta, Priyankar
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This dissertation contains three chapters that study the impact of a labor market policy onnursing home staffing and patient outcomes, the impact of parental divorce on long-term market outcomes, and the impact of a change in housing wealth on children’s schooling decisions. Chapter one examines the effect of paid sick leave mandates on nursing home outcomes, with a focus on low-paid nursing staff. I use the synthetic control group method and traditional difference-in-differences models along...
Show moreThis dissertation contains three chapters that study the impact of a labor market policy onnursing home staffing and patient outcomes, the impact of parental divorce on long-term market outcomes, and the impact of a change in housing wealth on children’s schooling decisions. Chapter one examines the effect of paid sick leave mandates on nursing home outcomes, with a focus on low-paid nursing staff. I use the synthetic control group method and traditional difference-in-differences models along with Nursing Home Compare data and Vital Statistics microdata to estimate the causal effect of paid sick leave mandates on nursing home outcomes. I find significant increases in part-time nursing assistant staffing and resident health and safety improvements. Nursing homes in areas with sick pay mandates also show reductions in the elderly mortality rate. Nursing assistant hours per resident day increase by 2.3 percent driven by a 12 percent increase in the hours for part-time workers, and there are no significant reductions in hours of full-time nursing assistants. I find improvements along multiple measures of patient health and safety. My calculations show that sick pay mandates helped prevent at least 4000 nursing home deaths per year among the elderly. Chapter two explores the importance of divorce in explaining the gender gap in children’s long-term educational outcomes. I find large differences in the gender gap between divorced and non-divorced families. Boys perform much worse in divorced families. I use a sibling fixed effects model to find that boys in divorced families have a lower likelihood of graduating high school and attending college relative to their sisters. My results show that boys’ likelihood of graduating high school declines by 6.4 percentage points if their parents are divorced before they turn 13, and their chances of attending college decline by 12.2 percentage points if they are a teenager at the time of divorce. I find that parents’ divorce is unrelated to the gender gap in achievement scores. My event study models show a drop in boys’ achievement scores relative to girls around the time of divorce. Chapter three examines the effect of housing wealth changes on private school enrolment. I use data from The National Longitudinal Survey of Youth’s child supplement to examine the relationship between housing wealth and private school enrolment. I use a multinomial logit model and find that self-reported housing price changes increase the likelihood that respondents switch from private to public school. Heterogeneity analyses reveal that house price increases have a positive relationship between switching from private to public school across income, gender, race, and religion. Finally, a rise in house prices increases the likelihood that a child moves from public school to private school when transitioning from middle school to private school.
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Title: Richard Hilton Tobitt's Diaspora : Religion, Migration, and Grassroots Organizing, 1865-1945
Creator: Shell, Christopher Michael
Date: 2022
Collection: Electronic Theses & Dissertations
Description: My doctoral dissertation project, titled, Richard Hilton Tobitt’s Diaspora: Religion, Migration, and Grassroots Organizing, 1865-1945, is an early twentieth-century political narrative of Black activism in the eastern Caribbean and New York City. The main argument of my dissertation is that through the lens of Antiguan-born Reverend Richard Hilton Tobitt (1873-1961), we learn about the monumental impact of Leeward Islander migration on Black political organizing in the understudied areas of...
Show moreMy doctoral dissertation project, titled, Richard Hilton Tobitt’s Diaspora: Religion, Migration, and Grassroots Organizing, 1865-1945, is an early twentieth-century political narrative of Black activism in the eastern Caribbean and New York City. The main argument of my dissertation is that through the lens of Antiguan-born Reverend Richard Hilton Tobitt (1873-1961), we learn about the monumental impact of Leeward Islander migration on Black political organizing in the understudied areas of Bermuda and Staten Island, New York. Using the early twentieth-century experiences of Tobitt as a window into much larger phenomenon, my project brings attention to Black political organizing in Bermuda, the roots of Caribbean nationalism, and highlights the understudied Black community in Staten Island.
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Title: Moral Intuition Prominence in Narratives Shapes Audience Attention and Affective Dispositions
Creator: Baldwin, Joshua Aaron
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The affective disposition theory (ADT) of drama suggests that moral judgments of a narrative character’s actions are a key determinant of character and story appeal. Specifically, approbation of behaviors prompts positive character dispositions and subsequent story liking. The modified affective disposition model (MADM; Tamborini, Grizzard et al., 2021) attempts to expand ADT by (a) explicating mechanisms that influence how dispositions are formed in morally complex storylines, (b)...
Show moreThe affective disposition theory (ADT) of drama suggests that moral judgments of a narrative character’s actions are a key determinant of character and story appeal. Specifically, approbation of behaviors prompts positive character dispositions and subsequent story liking. The modified affective disposition model (MADM; Tamborini, Grizzard et al., 2021) attempts to expand ADT by (a) explicating mechanisms that influence how dispositions are formed in morally complex storylines, (b) identifying factors that moderate these mechanisms, and (c) describing the mental processes that underlie them. ADT argues that narrative audiences are constantly monitoring the morality of a character’s behavior (Zillmann, 2000), and disposition formation is shaped by these moral appraisals. The theory suggests that people like characters that behave morally and dislike those that do not, but it gives little detail about how people make moral appraisals. The MADM builds on recent research indicating that moral appraisals are strongly influenced by character behaviors upholding or violating those moral intuitions most salient in the minds of audience members. In doing so, MADM attempts to explicate the mechanisms that increase or decrease the salience of competing intuitions in morally complex stories (i.e., stories wherein two or more moral intuitions are in conflict such that a character must violate one intuition to uphold another). According to the MADM, the salience of different moral intuitions in audience members is shaped by narrative exemplars that vary the prominence of different moral intuitions in the narrative. Specifically, it suggests that when storylines are morally complex, the level of a competing intuition’s prominence in content will strengthen the intuition’s salience in the minds of audience members and the attention that audiences give to intuition-related information. The influence of this prominence on the salience of and attention to different intuitions by audience members is predicted to moderate the disposition process and shape both (a) whether positive or negative dispositions are formed, and (b) whether dispositions are formed intuitively or deliberatively. This dissertation tests these proposed expansions using a 2 X 2 experiment that manipulates the prominence of two conflicting moral intuitions in content (i.e., dominantly vs. overridingly prominent) and whether a character upholds the prominent intuition (i.e., upholds vs. violates).The study results reveal two important findings. The first finding suggests that the comparative prominence of conflicting intuitions in content can influence the level of salience in the minds of audiences, which in turn strengthens or weakens the effect of observing a moral/immoral behavior on approbation. Higher prominence of the superordinate intuition weakens the strength of the subordinate intuition’s salience, which then weakens its ability to moderate the effect of upholding the superordinate intuition on approbation. The second finding suggests that different levels of comparative prominence (dominant versus overriding) can alter whether affect disposition (i.e., character liking) is formed intuitively or deliberatively. When the prominence of a superordinate intuition is dominant, disposition formation is intuitive. By comparison, when the prominence of a superordinate intuition is overriding, disposition formation is deliberative. The theoretical and social implications of these findings are discussed.
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Title: Interpreting Gravitational Waves and Developing Relativistic Multiphysics Solvers for Core-collapse Supernova Simulations
Creator: Pajkos, Michael Anton
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Core-collapse supernovae (CCSNe) mark the endpoint for millions of years of massive stellar evolution. After a successful explosion, supernovae increase the metallicity of the interstellar medium, generate intense electromagnetic radiation ionizing their surroundings, generate compact objects such as black holes or neutron stars, and create ripples in spacetime---gravitational waves (GWs). Advances in supernova theory over the past few decades have furthered our understanding of CCSNe....
Show moreCore-collapse supernovae (CCSNe) mark the endpoint for millions of years of massive stellar evolution. After a successful explosion, supernovae increase the metallicity of the interstellar medium, generate intense electromagnetic radiation ionizing their surroundings, generate compact objects such as black holes or neutron stars, and create ripples in spacetime---gravitational waves (GWs). Advances in supernova theory over the past few decades have furthered our understanding of CCSNe. However, constraints on the physics enshrouded in the supernova center would further illuminate their explosion mechanisms. Advances in high performance computing (HPC) resources and the ever-increasing sensitivities of GW observatories have positioned the field of astrophysics between two recent technological advances. The work presented here leverages HPC to perform CCSN simulations, allowing astronomers to translate between GW signals and internal physics. Using this insight, astronomers are better positioned to constrain the physics driving these explosive events that have such a widespread influence throughout astronomy.Investigating the evolution of 12-, 20-, 40-, and 60 solar mass progenitors, I perform axisymmetric neutrino radiation-hydrodynamic CCSN simulations, to relate the convective activity behind the supernova shock to the expected GW strength. I quantify how the rotational content of the supernova lowers GW frequencies. I present a novel method that combines two features of a single GW event to constrain the mass distribution within the stellar progenitor. By only requiring the two most detectable parts of the GW signal, astronomers can also potentially predict the explosion properties ~days before shock breakout. I present work with my undergraduate research assistant, that considers the impact of viewing angle on detecting GWs from CCSNe. Presented is a novel analysis method to identify the distribution of GW emission over all angles, accompanied with results showing that the preferred direction of GW emission for CCSNe migrates over time. Lastly, I present new numerical solvers targeted at exascale computing platforms that account for magnetized fluid evolution with velocities near the speed of light and in extreme spacetimes. These solvers are accompanied with stringent baseline tests, paired with 1D and 2D supernova simulations making use of these features.
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Title: BLENDING OF POLY(LACTIC ACID) AND POLY(3-HYDROXYBUTYRATE-CO-3-HYDROXYVALERATE) – THE EFFECT OF MALEATED PLA AS A REACTIVE COMPATIBILIZER AND BIODEGRADATION STUDY
Creator: Muangmala, Woranit
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Poly(lactic acid), PLA was blended with poly(3-hydroxybutyrate-co-3-hydroxyvalerate), PHBV, based on a crossed mixture-factorial experimental design with three levels of factorial variable of the type of pre-produced maleated PLA, PLAgMA-type, used as the blend compatibilizer, and three components mixture variable which were the contents of PLA, PHBV, and PLAgMA, included in the polymer blends. The mixture model was based on the constrained level of the weight fraction of each mixture...
Show morePoly(lactic acid), PLA was blended with poly(3-hydroxybutyrate-co-3-hydroxyvalerate), PHBV, based on a crossed mixture-factorial experimental design with three levels of factorial variable of the type of pre-produced maleated PLA, PLAgMA-type, used as the blend compatibilizer, and three components mixture variable which were the contents of PLA, PHBV, and PLAgMA, included in the polymer blends. The mixture model was based on the constrained level of the weight fraction of each mixture component as follows: 0.2 ≤ PHBV ≤ 0.7, 0.2 ≤ PLA ≤ 0.7, and 0.05 ≤ PLAgMA ≤ 0.15. The design of experiment yielded 16 runs of compatibilized blends, with 2 runs of non-compatibilized blend and 2 runs of neat polymers, PLA and PHBV, for comparison. The model of relationship between variables was derived based on the multiplication of a linear relationship of one factorial variable with a quadratic Scheffe model of the mixture ingredients. Multiple formulas of the blend compatibilizer, maleated PLA (PLA-g-MA), were pre-produced by a reactive melt blending method to functionalize maleic anhydride, MA, on the PLA backbone in a twin-screw co-rotating extruder. Dicumyl peroxide, DCP, was used as a free radical initiator in the reactive blending. The formulas were designed using response surface experimental design to determine the effect of the contents of MA and DCP on the amount of grafted MA, MA-grafting yield, and the molecular weight properties, Mn, Mw, IV, and dispersity of PLA-g-MA. The model regression indicated a significant effect of DCP with increasing DCP tending to reduce the MA-grafting yield, Mn, Mw, and IV, and increase the dispersity. The optimum point that maximized the desirability of these responses simultaneously was with the content of DCP = 0.1 wt. % and MA = 3.94 wt. % (PLA basis). Blending of PLA and PHBV clearly increased the crystalline fraction of the blends compared to neat PLA, which affects the barrier properties of the materials. Inclusion of PHBV at 25 wt. % in the non-compatiblilized blend and at 45 – 60 wt. % in compatibilized blends resulted in more than 60% reduction of water and O2 permeability compared to PLA. The compatibilized PLA/PHBV blend with PLA weight fraction of 0.45 achieved 300% increase in the tensile strength compared to the neat PHBV; this level of improvement was equivalent to the non-compatibilized blend containing PLA 75 wt. %. This was attributed to enhanced interfacial adhesion that was evidently supported by increased miscibility between the blend components in compatibilized blends which was exhibited through the shifting of Tg of PLA and the decrease of k constants based on the Gordon-Taylor equation of the compatibilized blends. The factorial-mixture model regression suggested the validity of the mixture variable of PLA, and PHBV in both tensile and barrier properties; the PLAgMA had a significant effect only on the tensile performance of the polymer blends. The overlapped contour plots as well as the desirability functions could be used to optimize the mixture of the PLA/PHBV blend components that provide desirable tensile and barrier properties. A biodegradation study was conducted on neat PLA, PHBV, non-compatibilized blend of 75:25 PLA/PHBV, and compatibilized blend of 65:15:20 PLA/PLA-g-MA/PHBV. PLA/PLA-g-MA/PHBV was the fastest to reach 100% mineralization, followed by PLA and PLA/PHBV samples, according to the CO2 evolution and % mineralization, whereas PHBV reached only 81% mineralization at the end of the test of 180 days. The facilitation of anhydride present in PLA-g-MA on the hydrolysis of PLA was a major cause of the fast biodegradation of PLA/PLA-g-MA/PHBV. A sharp increase in enthalpy of fusion, ΔHf, as well as a rapid reduction of the molecular weight of PLA/PLA-g-MA/PHBV compared to PLA and PLA/PHBV support the occurrence of an elevated rate of hydrolysis. The PHBV sample showed the biodegradation was barely affected by abiotic hydrolytic degradation as the thermal properties did not show any shifting of the melting transition and the ΔHf remained stable until 30 days of the test; the main mechanism was the enzymatic microbial degradation causing an erosion at the surface rather than affecting the bulk properties such as the molecular weight. The scanning electron micrographs also revealed the biodegradation of PHBV that initially occurred was from the surface and later showed the degradation of the crystalline structure. The PLA crystals formed during the biodegradation of PLA/PHBV and PLA/PLA-g-MA/PHBV samples could be seen from SEM photos.
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Title: LONGITUDINAL EXAMINATION OF FIRM-LEVEL SUPPLY CHAIN SUSTAINABILITY
Creator: Li, Ming
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Supply chain sustainability is a topic of immense importance for the press, political activists, managers, analysts, investors, shareholders, and stakeholders (e.g., local communities). One aspect of a firm’s sustainability concerns the actions taken by members of its supply chain, such as the use of child labor and the dumping of toxic emissions. While there have been several attempts in measuring firms’ sustainability as it pertains to their supply chains, these approaches suffer from...
Show moreSupply chain sustainability is a topic of immense importance for the press, political activists, managers, analysts, investors, shareholders, and stakeholders (e.g., local communities). One aspect of a firm’s sustainability concerns the actions taken by members of its supply chain, such as the use of child labor and the dumping of toxic emissions. While there have been several attempts in measuring firms’ sustainability as it pertains to their supply chains, these approaches suffer from numerous methodological weaknesses. This has limited our ability to answer important questions such as how firms’ sustainability performance as it pertains to their supply chain evolved over time, and what factors affect this evolution? This question constitutes my primary research interest and has motivated my three-essay dissertation that:Essay one: develops a new approach for measuring firm-level corporate social responsibility (CSR) and corporate social irresponsibility (CSI) supply chain practices using log-logistic item response theory models; Essay two: studies how firm-level CSR and CSI supply chain practices have evolved over time using piecewise latent growth curve models; and Essay three: examines the dynamic inter-relationships between firm-level CSR and CSI supply chain practices using dynamic panel models. To answer these questions, I use panel data from 2003 – 2018 for hundreds of publicly-traded manufacturers, wholesalers, and retailers from KLD, which I merge with financial data from COMPUSTAT, market concentration from US Census Bureau Economic Indicators, and Upstreamness measuring of the average distance from final use from American Economic Review. My results improve our theoretical understanding of how sustainable supply chain practices can be measured and how they evolve over time.
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Title: ESSAYS ON COMMUNITY FOCUSED SUPPLY CHAINS
Creator: Cole, Dustin
Date: 2022
Collection: Electronic Theses & Dissertations
Description: 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: Fighting Zombies Together : A Longitudinal Experimental Test of Prejudice Reduction Through Media Exposure to Non-Human Villains
Creator: Yao, Xuejing
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Increasing the salience of shared human identity has been demonstrated as an effective mechanism to reduce interracial prejudice (e.g., Ellithorpe et al. 2018; Yao et al., 2022a). Previous research has found that watching racially diverse human heroes fighting against non-human villains increased the strength of viewers’ human identity, and their stronger human identity is in turn associated with more positive attitudes toward racial minority groups. This dissertation replicated Ellithorpe et...
Show moreIncreasing the salience of shared human identity has been demonstrated as an effective mechanism to reduce interracial prejudice (e.g., Ellithorpe et al. 2018; Yao et al., 2022a). Previous research has found that watching racially diverse human heroes fighting against non-human villains increased the strength of viewers’ human identity, and their stronger human identity is in turn associated with more positive attitudes toward racial minority groups. This dissertation replicated Ellithorpe et al.’s (2018) research through a longitudinal controlled experiment with three waves of stimuli exposure and a posttest. The longitudinal design also made it possible to test the chronic accessibility of the human identity. Overall, minimal support was found for the longitudinal mediation with the current data and the human identity showed relatively short salience. However, this set of findings provided important information about the property of the superordinate human identity. Implications of the current findings as well as directions for future research were discussed.
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Title: STUDYING ENGAGEMENT TO INFORM DESIGN OF CALCULUS 2 COMPUTATIONAL LABS
Creator: Krause, Andrew Joseph
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This is a study of student engagement with computational labs in Calculus 2. The labs task students with using MATLAB to investigate contexts such as rocket science, disease modeling, and market economics forecasting by modifying and executing provided code, guided by questions that have students report the results of their simulations or observations of the model, as well as interpretive questions that ask them to make sense of their findings in the context of the realistic situation.Locally...
Show moreThis is a study of student engagement with computational labs in Calculus 2. The labs task students with using MATLAB to investigate contexts such as rocket science, disease modeling, and market economics forecasting by modifying and executing provided code, guided by questions that have students report the results of their simulations or observations of the model, as well as interpretive questions that ask them to make sense of their findings in the context of the realistic situation.Locally, the study is situated within an iterative design process with the goal of improving the labs and their implementation, meaning there are direct connections between the research and improvements to the written tasks or teaching practices. The goal of this dissertation, from a research perspective, is to examine student engagement to contribute to the development of theory about lab-type activities and the learning opportunities they facilitate. To accomplish both goals, this study follows a design-based research (DBR) methodology, which provides a structure to relate the local goal to inform practice to the broader research goal to develop theory that is useful broadly.The labs can be considered novel learning activities, with novel learning goals, in a novel teaching context. The labs were novel learning activities because they were the original product of the curriculum designers and they were still being substantially revised during the third year of the project, when this study took place. The learning goals were novel at the research site because they involved collaborative and higher-level objectives, a notable departure from the traditional emphasis on individual mastery of various rote calculation. The teaching context was novel because this research was conducted during the first time the labs were taught “at-scale”, meaning it was the first time the labs were being led by graduate students during recitations connected to a multi-section large-lecture. In this novel context, studying engagement provides a way to understand how the labs facilitate students’ attainment of those learning goals without attempting to measure students’ individual attainment of those learning goals. Students learn through engagement, so understanding how students engage with the labs is a way to understand how students are learning—if students are engaged in the mathematical practices the labs are intended to facilitate, then they are learning those mathematical practices.This study examined engagement through interviews, classroom observations, and a post-course survey. Students were observed collaborating productively by discussing their thinking, tinkering with code, and co-authoring solutions. Rarely were off-task behaviors observed. Some interview participants identified intrinsic learning goals and other students were invested in completing the labs simply because they were a required, graded assignment. Some students found the labs to be interesting, challenging, and useful, but the broader sentiment was a more negative reaction that was especially pronounced in the post-course survey data. These negative feelings, however, did not appear to disrupt students’ behavioral or cognitive engagement in the classroom, because students continued to put forward effort to complete the labs through the end of the semester, suggesting that negative emotional engagement does not necessarily lead to overall disengagement or undermine students’ motivation. In other words, even though some students might not be trying to learn how to use MATLAB to model Calculus 2 concepts, they learn some of those skills anyway because they have to do the things they are supposed to learn.
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Title: Detecting and Mitigating Bias in Natural Languages
Creator: Liu, Haochen
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Natural language processing (NLP) is an increasingly prominent subfield of artificial intelligence (AI). NLP techniques enable intelligent machines to understand and analyze natural languages and make it possible for humans and machines to communicate through natural languages. However, more and more evidence indicates that NLP applications show human-like discriminatory bias or make unfair decisions. As NLP algorithms play an increasingly irreplaceable role in promoting the automation of...
Show moreNatural language processing (NLP) is an increasingly prominent subfield of artificial intelligence (AI). NLP techniques enable intelligent machines to understand and analyze natural languages and make it possible for humans and machines to communicate through natural languages. However, more and more evidence indicates that NLP applications show human-like discriminatory bias or make unfair decisions. As NLP algorithms play an increasingly irreplaceable role in promoting the automation of people's lives, bias in NLP is closely related to users' vital interests and demands considerable attention.While there are a growing number of studies related to bias in natural languages, the research on this topic is far from complete. In this thesis, we propose several studies to fill up the gaps in the area of bias in NLP in terms of three perspectives. First, existing studies are mainly confined to traditional and relatively mature NLP tasks, but for certain newly emerging tasks such as dialogue generation, the research on how to define, detect, and mitigate the bias in them is still absent. We conduct pioneering studies on bias in dialogue models to answer these questions. Second, previous studies basically focus on explicit bias in NLP algorithms but overlook implicit bias. We investigate the implicit bias in text classification tasks in our studies, where we propose novel methods to detect, explain, and mitigate the implicit bias. Third, existing research on bias in NLP focuses more on in-processing and post-processing bias mitigation strategies, but rarely considers how to avoid bias being produced in the generation process of the training data, especially in the data annotation phase. To this end, we investigate annotator bias in crowdsourced data for NLP tasks and its group effect. We verify the existence of annotator group bias, develop a novel probabilistic graphical framework to capture it, and propose an algorithm to eliminate its negative impact on NLP model learning.
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Title: Wall-Crossing for Tilt Stability
Creator: Rekuski, Nicholas
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Recent techniques from Bridgeland Stability have given new, interesting results about stable vector bundles on surfaces. However, in higher dimensions the theory is substantially harder, so there has been significantly less progress in this case. In this thesis, we develop theory for a related notion—tilt stability— then apply this theory to stable vector bundles.In the first part of this thesis, we recall and further develop the theory of tilt stability. This development culminates in a wall...
Show moreRecent techniques from Bridgeland Stability have given new, interesting results about stable vector bundles on surfaces. However, in higher dimensions the theory is substantially harder, so there has been significantly less progress in this case. In this thesis, we develop theory for a related notion—tilt stability— then apply this theory to stable vector bundles.In the first part of this thesis, we recall and further develop the theory of tilt stability. This development culminates in a wall-crossing result for tilt stability.In the second part of this thesis, we apply our wall-crossing result to study stable vectorbundles. Our first application is a criterion for when the restriction of a slope stable bundle to an integral subvariety is still slope stable. Our second application is to the theory of Lazarsfeld-Mukai bundles. Specifically, we show the Lazarsfeld-Mukai bundle associated to a Gieseker stable bundle is slope stable, and that slope stability and slope semistability are equivalent for Lazarsfeld-Mukai bundles associated to ample line bundles.
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Title: SOCIAL MECHANISM OF SOCIAL SUPPORT PROVISION : A BEHAVIORAL STUDY OF ONLINE SUPPORT GROUPS
Creator: Lee, Sanguk
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The popularity of Online Support Groups (OSGs) is ever increasing as OSGs enable people with (dis)similar health conditions to exchange social supports easily. Social support provision is a critical activity for individual well-being and community sustainability, yet the underlying social mechanism that promotes social support provision is underexplored. Employing social capital theory, the current study examines how brokerage and closure structures yield different forms of social capital...
Show moreThe popularity of Online Support Groups (OSGs) is ever increasing as OSGs enable people with (dis)similar health conditions to exchange social supports easily. Social support provision is a critical activity for individual well-being and community sustainability, yet the underlying social mechanism that promotes social support provision is underexplored. Employing social capital theory, the current study examines how brokerage and closure structures yield different forms of social capital such as non-redundant information and trust, which subsequently facilitate the diverse dimensions of informational and emotional support provisions, including quantity, quality, and timing. Methodologically, the study utilizes computational methods to collect online behavioral data from an online cancer community, measure network metrics and support provision behaviors, and capture the dynamic relationships between the network structure, social capital, and support provision behaviors. Results indicate that the brokerage structure and non-redundant information enhance the volume, uniqueness, and speed of information support provision. Although the closure structure and trust have a positive influence on the quality of emotional support, their overall impacts are limited in promoting information and emotional supports in the context of OSGs. The findings also indicate the importance of considering the dynamic development stage of OSGs in understanding the social mechanism of support provisions.
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Title: AGENTS OF SEE CHANGE : CATHOLIC WOMEN’S ORGANIZATIONS IN WEST GERMANY, 1945-1968
Creator: Brothers, Heather
Date: 2022
Collection: Electronic Theses & Dissertations
Description: ABSTRACTAGENTS OF SEE CHANGE: CATHOLIC WOMEN’S ORGANIZATIONS IN WEST GERMANY, 1945-1968ByHeather Brothers This dissertation examines Catholic women's organizations in West Germany from 1945 to 1968. Women in organizations like the Central Association of Catholic Women and Mothers’ Organizations (ZKFM) were important agents of change within both West German society and the Catholic Church. Despite being largely left out of scholarly discussions about the postwar period, West German Catholic...
Show moreABSTRACTAGENTS OF SEE CHANGE: CATHOLIC WOMEN’S ORGANIZATIONS IN WEST GERMANY, 1945-1968ByHeather Brothers This dissertation examines Catholic women's organizations in West Germany from 1945 to 1968. Women in organizations like the Central Association of Catholic Women and Mothers’ Organizations (ZKFM) were important agents of change within both West German society and the Catholic Church. Despite being largely left out of scholarly discussions about the postwar period, West German Catholic women and the knowledge they created fundamentally shaped the intellectual culture of the Catholic milieu during this era. The ZKFM, and other organizations like it, gave Catholic women a platform within the Church that both limited the scope of their ideas and actions, but also provided these women with networks and connections that empowered them to effectively challenge Catholic dogma and tradition and to intervene in West German debates about women’s role in family, society, and state. By studying the intellectual work of Catholic women and their organizational labor, I argue that we can better understand the relationship between women, the Church, and West German society. This dissertation explores how interactions between conceptions of gender and Catholic faith are integral to understanding both women’s place within the structures of Church and state and also how women worked to shape these structures to their own ends. Women in the ZKFM expressed a wide diversity of opinions, and the organization allowed and encouraged new interpretations on both faith and gender that helped to set the association’s agenda moving forward. While influenced by conservative Catholic tradition and a conservative West German state, the diversity within the ZKFM also emboldened members to explore feminist ideas and other progressive pursuits. When we look closely at ZKFM conferences, publications, benevolent activities, and public interventions, we can see that these women and their intellectual work played a significant role in shaping the landscape of postwar West Germany.
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Title: Computational methods to investigate connectivity in evolvable systems
Creator: Ackles, Acacia Lee
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Evolution sheds light on all of biology, and evolutionary dynamics underlie some of the most pressing issues we face today. If we can deepen our understanding of evolution, we can better respond to these various challenges. However, studying such processes directly can be difficult; biological data is naturally messy, easily confounded, and often limited. Fortunately, we can use computational modeling to help simplify and systematically untangle complex evolutionary processes. The aim of this...
Show moreEvolution sheds light on all of biology, and evolutionary dynamics underlie some of the most pressing issues we face today. If we can deepen our understanding of evolution, we can better respond to these various challenges. However, studying such processes directly can be difficult; biological data is naturally messy, easily confounded, and often limited. Fortunately, we can use computational modeling to help simplify and systematically untangle complex evolutionary processes. The aim of this dissertation is therefore to develop innovative computational frameworks to describe, quantify, and build intuition about evolutionary phenomena, with a focus on connectivity within evolvable systems. Here I introduce three such computational frameworks which address the importance of connectivity in systems across scales.First, I introduce rank epistasis, a model of epistasis that does not rely on baseline assumptions of genetic interactions. Rank epistasis borrows rank-based comparison testing from parametric statistics to quantify mutational landscapes around a target locus and identify how much that landscape is perturbed by mutation at that locus. This model is able to correctly identify lack of epistasis where existing models fail, thereby providing better insight into connectivity at the genome level.Next, I describe the comparative hybrid method, an approach to piecewise study of complex phenotypes. This model creates hybridized structures of well-known cognitive substrates in order to address what facilitates the evolution of learning. The comparative hybrid model allowed us to identify both connectivity and discretization as important components to the evolution of cognition, as well as demonstrate how both these components interact in different cognitive structures. This approach highlights the importance of recognizing connected components at the level of the phenotype.Finally, I provide an engineering point of view for Tessevolve, a virtual reality enabled system for viewing fitness landscapes in multiple dimensions. While traditional methods have only allowed for 2D visualization, Tessevolve allows the user to view fitness landscapes scaled across 2D, 3D, and 4D. Visualizing these landscapes in multiple dimensions in an intuitive VR-based system allowed us to identify how landscape traversal changes as dimensions increase, demonstrating the way that connections between points across fitness landscapes are affected by dimensionality. As a whole, this dissertation looks at connectivity in computational structures across a broad range of biological scales. These methods and metrics therefore expand our computational toolkit for studying evolution in multiple systems of interest: genotypic, phenotypic, and at the whole landscape level.
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Title: Plasma Based Methods for the Synthesis and Deposition of Nanoparticles
Creator: Ho, Alexander
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Nanoparticles exhibit tunable properties that offer the opportunity to improve existing technologies. Nanoparticles also possess emergent properties that are not shared by their bulk scale counterparts; this difference in properties allows for application of materials in devices and processes that were traditionally unsuitable. For semiconducting nanoparticles, the emergent and tunable properties hold promise for applications in solar cells, light emitting devices, sensors, catalysis, and a...
Show moreNanoparticles exhibit tunable properties that offer the opportunity to improve existing technologies. Nanoparticles also possess emergent properties that are not shared by their bulk scale counterparts; this difference in properties allows for application of materials in devices and processes that were traditionally unsuitable. For semiconducting nanoparticles, the emergent and tunable properties hold promise for applications in solar cells, light emitting devices, sensors, catalysis, and a variety of other spaces.Explored first was the syntheis of InN, GaN, and InGaN at low pressure. These materials possess properties suitable for high-power and high-frequency electronics applications. The materials also possess bandgaps that span from the IR to the UV allowing for the use in a host of optoelectronic applications. A low-pressure RF plasma reactor was used to dissociate precursor gases whose subsequent reactions formed the nanoparticles. Nanoparticles were then collected and characterized with a host of techniques. Experiments were conducted that demonstrated the synthesis of crystalline nanoparticles with narrow size distributions. It was shown that particle size and crystallinity could be controlled through modulation of residence time and RF power respectively. This method demonstrated the synthesis of luminescent InGaN nanoparticles without any subsequent surface modification or post-synthesis treatment. To eliminate the time and capital costs of vacuum equipment and processes an atmospheric pressure microplasma operated with ambient surroundings was investigated. With this method crystalline silicon nanoparticles were synthesized. OES and FTIR were used in conjunction to ascertain if particles were synthesized in an oxygen contaminated environment. Results of the experiments indicatethat particles were not exposed to oxygen in the reaction volume. Lastly an integrated atmospheric pressure synthesis reactor and aerosol jet printing process are described. Such a process would be useful for fabrication or prototyping of devices that require nanoaprticles. Combination of the reactor with a motorized stage and gantry allowed for deposition of nanoparticles with linewidths down to 100 microns. Methods to improve impaction efficiency were implemented and allowed for capture of sub-5 nm particles that exhibited luminescence at 680 nm. Also demonstrated was the control of synthesis parameters at the time of deposition to deposit particles with spatially varied properties.
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