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Title: COMPOSITION AND FUNCTION : UNRAVELING THE ROLE OF GROUP B STREPTOCOCCAL MEMBRANE VESICLES
Creator: McCutcheon, Cole Ross
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Group B Streptococcus (GBS) is an opportunistic pathogen that asymptomatically colonizes the vaginal tract of approximately 30% of women. In individuals with an altered immune state such as the elderly, pregnant women, and neonates, GBS can cause invasive infections. During pregnancy, GBS frequently contributes to infections in utero that can result in chorioamnionitis, preterm birth, or miscarriage. The bacterial factors that promote these adverse outcomes, however, are under studied. For...
Show moreGroup B Streptococcus (GBS) is an opportunistic pathogen that asymptomatically colonizes the vaginal tract of approximately 30% of women. In individuals with an altered immune state such as the elderly, pregnant women, and neonates, GBS can cause invasive infections. During pregnancy, GBS frequently contributes to infections in utero that can result in chorioamnionitis, preterm birth, or miscarriage. The bacterial factors that promote these adverse outcomes, however, are under studied. For instance, previous reports have demonstrated that GBS produces membrane vesicles (MVs), which have been linked to adverse pregnancy outcomes in a murine model. Nonetheless, little is known about the composition of GBS MVs and their role in pathogenesis and impact on the immune response. Therefore, using genotypically diverse strains of GBS, I sought to examine MV production and composition, as well as their impact on ascending infection in vivo to better understand their role in GBS disease. While MVs contain a variety of immunomodulatory virulence factors, including hyaluronidase, C5a peptidase, and sialidase, the relative abundance of these virulence factors varies in a lineage dependent manner. With this information in hand, I then assessed the host response to GBS derived MVs using human THP-1 derived macrophages. I found that regardless of strain, MVs induce a potent proinflammatory immune response characterized by the production of proinflammatory cytokines and chemokines. Notably, many neutrophil chemokines were highly upregulated in response to MVs, which is consistent with observations seen during murine challenge with MVs. I went on to demonstrate that MVs, in the absence of t, induce a potent IL-1ß response, which is dependent on caspase-1 and NLRP3, suggesting that the NLRP3 inflammasome is a sensor of GBS derived MVs. Previous data had suggested that MVs induce inflammation at the maternal-fetal interface. We have confirmed these findings and identified a potential mechanism for this inflammatory response. Furthermore, others utilized models of intra-amniotic injection that bypasses many immune defenses such as the extraplacental membranes and the cervix, which may prevent this response, while we assessed the role of MVs during vaginal challenge with GBS. However, we found that the addition of exogenous MVs does not promote ascending infection in vivo. While bacteria were able to ascend from the vaginal tract into gestational tissues, similar levels of bacteria were found regardless of the addition of exogenous MVs. Consistent with this observation, using flow cytometry we showed that neither exogenous MVs supplemented at the time of infection nor vaginal supplementation of MVs alone alter inflammatory responses at the maternal-fetal interface, suggesting that these innate barriers are capable of blocking MV mediated effects. The work presented here dramatically alters our understanding of the composition and host-pathogen interactions of GBS MVs, by substantially increasing our knowledge of both their composition and function during infection.
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Title: INVESTIGATING THE RELATIONSHIP BETWEEN WELLBEING AND GRAZING MANAGEMENT DECISIONS ON MICHIGAN’S PASTURE-BASED BEEF FARMS
Creator: MathisonSlee, Morgan
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Livestock producers around the world are concerned about land degradation and the increase in extreme weather events such as more frequent flooding and droughts, as well as current rates of biodiversity loss, soil erosion, and desertification. One suggested change that could improve grassland sustainability is the use of adaptive grazing management approaches, however the ramifications of using an adaptive grazing approach have been understudied from a social perspective. In this dissertation...
Show moreLivestock producers around the world are concerned about land degradation and the increase in extreme weather events such as more frequent flooding and droughts, as well as current rates of biodiversity loss, soil erosion, and desertification. One suggested change that could improve grassland sustainability is the use of adaptive grazing management approaches, however the ramifications of using an adaptive grazing approach have been understudied from a social perspective. In this dissertation I used a social-ecological systems approach to investigate the relationship between grazing management style and farmer wellbeing in Michigan’s pasture-based beef farms. I created a novel theoretical framework which integrated the Theory of Planned Behavior with the Theory of Basic Human Values at an individual farm scale to understand why farmers manage their animals the way they do. Further,. I explored the relationship between management style and the physical, psychological, and social wellbeing of farmers to better understand if certain management practices result in higher farmer wellbeing. I investigated wellbeing from a benefits-challenges perspective to acknowledge there will always be tradeoffs in the system. This focus on wellbeing is necessary because farmers often suffer from higher-than-average rates of mental illness and are one of the top three occupations most likely to die by suicide. Thus, it is imperative we determine if there are any management techniques that bolster wellbeing.I used a sequential mixed methods approach by coupling an online survey with follow up interviews from a subsample of the participants to better understand the range of grazing management practices being used on Michigan’s pasture-based beef farms, particularly how perceptions of control, attitudes, norms, and values influence the farmer’s choice of grazing management behaviors. I found pasture-based beef farmers managed their grazing animals either rotationally or adaptively, and that my theoretical framework can explain why there are differences in what drives the adoption of different grazing management styles. If we want to understand the adoption of adaptive grazing management as a tool for grassland restoration it is important to know what management strategies are used on the ground. Farmers who were managing rotationally were more likely to be a generational, family farm and the adaptive farmers were more likely to be an independent startup farm. Additionally, there were differences in the role of diversification between the two groups, mainly, adaptive farmers are more confident in their ability to create a highly diversified farm than their rotational counterparts I also found that Michigan’s pasture-based beef farmers did not report the low levels of wellbeing I expected, rather farmers across the management spectrum have high physical and psychological wellbeing. The largest challenge to wellbeing was in the social dimension where many farmers expressed feeling isolated. However, when the COVID-19 pandemic emerged farmers coped in ways that supported their wellbeing, including receiving financial support and spending additional time outdoors. These findings and my theoretical framework serve as an initial exploration into the wellbeing and management decisions of pasture-based beef farmers in Michigan that will hopefully be useful for future research on the wellbeing of farmers across the state and beyond.
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Title: Efficient and Secure Message Passing for Machine Learning
Creator: Liu, Xiaorui
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Machine learning (ML) techniques have brought revolutionary impact to human society, and they will continue to act as technological innovators in the future. To broaden its impact, it is urgent to solve the emerging and critical challenges in machine learning, such as efficiency and security issues. On the one hand, ML models have become increasingly powerful due to big data and models, but it also brings tremendous challenges in designing efficient optimization algorithms to train the big ML...
Show moreMachine learning (ML) techniques have brought revolutionary impact to human society, and they will continue to act as technological innovators in the future. To broaden its impact, it is urgent to solve the emerging and critical challenges in machine learning, such as efficiency and security issues. On the one hand, ML models have become increasingly powerful due to big data and models, but it also brings tremendous challenges in designing efficient optimization algorithms to train the big ML models from big data. The most effective way for large-scale ML is to parallelize the computation tasks on distributed systems composed of many computational devices. However, in practice, the scalability and efficiency of the systems are greatly limited by information synchronization since the message passing between the devices dominates the total running time. In other words, the major bottleneck lies in the high communication cost between devices, especially when the scale of the system and the models becomes larger while the communication bandwidth is relatively limited. This communication bottleneck often limits the practical speedup of distributed ML systems. On the other hand, recent research has generally revealed that many ML models suffer from security vulnerabilities. In particular, deep learning models can be easily deceived by the unnoticeable perturbations in data. Meanwhile, graph is a kind of prevalent data structure for many real-world data that encodes pairwise relations between entities such as social networks, transportation networks, and chemical molecules. Graph neural networks (GNNs) generalize and extend the representation learning power of traditional deep neural networks (DNNs) from regular grids, such as image, video, and text, to irregular graph-structured data through message passing frameworks. Therefore, many important applications on these data can be treated as computational tasks on graphs, such as recommender systems, social network analysis, traffic prediction, etc. Unfortunately, the vulnerability of deep learning models also translates to GNNs, which raises significant concerns about their applications, especially in safety-critical areas. Therefore, it is critical to design intrinsically secure ML models for graph-structured data.The primary objective of this dissertation is to figure out the solutions to solve these challenges via innovative research and principled methods. In particular, we propose multiple distributed optimization algorithms with efficient message passing to mitigate the communication bottleneck and speed up ML model training in distributed ML systems. We also propose multiple secure message passing schemes as the building blocks of graph neural networks aiming to significantly improve the security and robustness of ML models.
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Title: AI ACCELERATED COLLISIONAL CROSS SECTION PREDICTION FOR HIGH THROUGHPUT METABOLITE IDENTIFICATION
Creator: Tanemura, Kiyoto Aramis
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Metabolomics refers to the collective characterization of small organic molecules in a biological sample. While instrumentation and software continues to improve for metabolomics studies, the fraction of annotated signals in untargeted metabolomics experiments remain small. Translating features to metabolite identities present a major bottleneck, confounded by the lack of authentic standards to build comprehensive experimental databases. I illustrate the development of collisional cross...
Show moreMetabolomics refers to the collective characterization of small organic molecules in a biological sample. While instrumentation and software continues to improve for metabolomics studies, the fraction of annotated signals in untargeted metabolomics experiments remain small. Translating features to metabolite identities present a major bottleneck, confounded by the lack of authentic standards to build comprehensive experimental databases. I illustrate the development of collisional cross section (CCS) prediction methods through deduction from theory and induction from available data. The theoretical CCS prediction involves multistep modeling of conformational ensemble followed by simulation of ion mobility. The advanced computational chemistry operations were automated using the AutoGraph conformational clustering protocol and implementation of the workflow in Snakemake. In a complementary approach, I applied a graph convolutional deep Bayesian neural net to predict CCS values and their uncertainty values. The quantified uncertainty was used to guide ab initio prediction of CCS values in an active learning strategy. The developed methodologies lay the foundation to a continuously refining in silico CCS library to aid in metabolite annotation.
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Title: THE ROLE OF DISTRICT AND UNION SUPPORT IN PURSUING THREE-DIMENSIONAL SCIENCE TEACHING PROFESSIONAL COMMUNITIES
Creator: Thomas, Christie Morrison
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This qualitative study compares four public school districts in a state to investigate how Next Generation Science Standards-aligned, three-dimensional science classroom teaching and learning in biology classrooms could become normal, instead of exceptional. Interview data were collected through two rounds of interviews – one year apart – with teachers, district science coordinators, and teachers’ union staff and leaders in districts using Carbon TIME instructional resources in high school...
Show moreThis qualitative study compares four public school districts in a state to investigate how Next Generation Science Standards-aligned, three-dimensional science classroom teaching and learning in biology classrooms could become normal, instead of exceptional. Interview data were collected through two rounds of interviews – one year apart – with teachers, district science coordinators, and teachers’ union staff and leaders in districts using Carbon TIME instructional resources in high school biology. Results are shared through district-level identifying stories of current realities (actual identities) and future plans and goals (designated identities).Each of the four school districts described similar interacting communities of practice – teachers’ classrooms; teachers’ course-based (biology) professional communities; and district administrators and local union leaders. The study’s analytical framework addresses roles, responsibilities, and professional actions of teachers, union leaders, and administrators and district science coordinators relevant to teachers’ course-based professional communities. Attention was given to professional actions that could “cross the classroom door,” connecting what teachers do together in their course-based (biology) professional communities with their own classroom communities. Two orientations of the identifying stories varied across school districts in ways that influence three-dimensional science classroom teaching and learning: collective (versus individual) orientations and three-dimensional science (versus one-dimensional science) orientations. Identifying stories in districts with collective and three-dimensional science orientations described teachers’ professional community work as necessary to realizing classroom goals for students’ three-dimensional science experiences and performances. District and union leaders endorsed teachers’ professional community work as integral to classroom instruction and supported such work through mitigating transaction and conflict costs. Teachers’ professional actions within their course-based (biology) professional communities included selecting, developing, and revising common three-dimensional instructional resources and making sense of their classroom science instruction using evidence of student learning. Differently, in districts with identifying stories as individually and non-three-dimensional-science oriented professional communities, participants described teachers with individual classroom goals and teachers’ professional communities with traditional norms of non-interference and egalitarian beliefs. District and union leaders endorsed teachers’ independent expertise and classroom autonomy. Teachers’ work with their course-based (biology) professional community was described connecting in optional ways or as not connected to teachers’ individual classroom communities. This study suggests that collectively oriented professional communities can help all classroom communities engage in three-dimensional science teaching and learning. Districts and local teachers’ unions can play important roles in reducing transaction and conflict costs and endorsing identifying stories that support collective orientations.
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Title: Language Ideologies and Practices, Transnationalism, and Identity in Multilingual Families
Creator: Reichmuth, Heather Lyn
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This three-paper formatted dissertation is a qualitative case study of one intermarried Korean-English speaking family residing in South Korea. Data was drawn from in-depth, semi-structured interviews, participant journals, and video documentation of familial interactions, including discussions of family member’s language portraits, family mealtimes, and familial time spent playing board and card games. The first of the three articles examines the language ideologies and practices of the...
Show moreThis three-paper formatted dissertation is a qualitative case study of one intermarried Korean-English speaking family residing in South Korea. Data was drawn from in-depth, semi-structured interviews, participant journals, and video documentation of familial interactions, including discussions of family member’s language portraits, family mealtimes, and familial time spent playing board and card games. The first of the three articles examines the language ideologies and practices of the intermarried family and argues that a translanguaging stance needs to be taken up by caregivers in a bilingual home to support bilingual children and push back on monolingual ideologies placed on bilingual children. The second article looks at the influence of transnational knowledge that the parent members of the family possessed and how this knowledge alongside their ethnotheories of childrearing influenced their bonding and language practices in the home. The third paper examines the practiced and positioned identities of the four family members in Korea. The findings of this dissertation suggest that: 1) multiple and conflicting language ideologies and practices can exist in multilingual homes, 2) a translanguaging stance among caregivers of bilingual children is important to support their evolving bilingual identities, 3) transnational knowledge and ethnotheories are present in the decision making of family language policies and practices in intermarried families, and 4) practiced identities may conflict with positioned identities, especially those of multilingual and multiracial children in the Korean context.
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Title: Tool Wear Study in Turning Ti-6Al-4V and Edge Trimming of Carbon Fiber Reinforced Plastics (CFRP)
Creator: Khawarizmi, Ryan Muhammad
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Lightweight materials such as titanium alloys and carbon fiber reinforced plastics (CFRP) are highly desirable due to their low density and high strength properties for many aerospace, chemical, petroleum, automotive, and sports applications. However, both materials are considered difficult to machine due to various factors.In machining titanium alloys, the low thermal conductivity and highly reactive nature of titanium with cutting tools cause the temperature to rise quickly, producing a...
Show moreLightweight materials such as titanium alloys and carbon fiber reinforced plastics (CFRP) are highly desirable due to their low density and high strength properties for many aerospace, chemical, petroleum, automotive, and sports applications. However, both materials are considered difficult to machine due to various factors.In machining titanium alloys, the low thermal conductivity and highly reactive nature of titanium with cutting tools cause the temperature to rise quickly, producing a segmented or “saw-tooth” chip. Chip segmentation caused a periodic loading on the tool and affected the cutting process. Ti-6Al-4V depending on the heat treatment, produces four distinct types, elongated (ELO), mill-annealed (MIL), solution treated and aged (STA), and lamellar (LAM). In this dissertation, four different microstructures of Ti64, ELO, MIL, STA, and LAM, are machined at 61, 91, and 122 m/min. The machining chips were collected and characterized to study the impact of the microstructure. In addition, the crater wear for different types of Ti64 was measured and compared. A finite element numerical simulation was developed using the chip morphology measured, which enables estimating the cutting temperature for Ti64-STA. Electron backscatter images of the cutting chips (EBSD) and crater wear surfaces were also analyzed to verify the wear mechanism. The findings suggested a high interface temperature during cutting enables faster tool diffusion. Another machinability study of turning Ti64-STA using a variety of coated tools was conducted. The coated tool materials include TiAlN, AlTiN, AlMgB14(BAM), ZrN, and (AlCrSi/Ti)N. The performance of these cutting tools was assessed using cutting force data, flank wear, and crater wear measurements. In conjunction with the coating experiments, another machining study was conducted in minimum quantity lubrication (MQL) using oil mixed with solid additives such as hBN, WS2, MoS2, and xGnP. For CFRP, the abrasion from the fibers was the leading cause of tool wear. Three distinctly different types of CFRPs with T300 PAN-based carbon fibers as standard modulus (SM), IM-7 PAN-based carbon fibers as intermediate modulus (IM), and K13312 pitch-based carbon fibers as high modulus (HM) are used. Tool wear during the edge-trimming process of three types of CFRP laminates is analyzed for four different ply angles, namely 0°, 45°, 90°, 135°, to investigate the interactions between the fiber type and the fiber orientation.
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Title: Monetary Policy and Labor Supply
Creator: Burke, Patrick
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The first chapter gives an overview of the current literature on participation in the labor market. Special attention is paid to trends in participation since 2000. The role of demographic change in those trends is compared against other explanations. With the increasing focus on labor market participation at the United States Federal Reserve, the history of monetary policy changes and participation is also examined. The second chapter estimates a labor market matching model to get a more...
Show moreThe first chapter gives an overview of the current literature on participation in the labor market. Special attention is paid to trends in participation since 2000. The role of demographic change in those trends is compared against other explanations. With the increasing focus on labor market participation at the United States Federal Reserve, the history of monetary policy changes and participation is also examined. The second chapter estimates a labor market matching model to get a more accurate measure of the market tightness elasticity of the job finding rate and unexplained residual. The estimation strategy in the second chapter follows the approach in Borowczyk-Martins et al. (2013) which models the autocorrelation structure of the unobserved component in the matching function to address simultaneity bias. This chapter then uses asset data present in the Survey of Income and Program Participation. This allows for the use of average household debt as an additional instrument to correct for measurement error. These results help characterize the recent shifts in the Beveridge curve and the decline of the matching rate between job seekers and job openings between 2008-2013. How important is labor supply for the ability of monetary policy to influence inflation and employment? Hiring costs alter the response of inflation to monetary policy. As shown in Kurozumi and Van Zandweghe (2010), adjustments in employment can make it difficult for monetary policy to reach its price stability and full employment targets. As the policy response is more vigorous in maintaining inflation around a target, that target becomes impossible to maintain. Recent fluctuations in the participation rate have led to a growing concern about the role of labor supply in monetary policy. This chapter shows that as labor supply becomes more elastic, the monetary authority is more likely to be able to stabilize the economy around its steady state targets. The central bank's response to cyclical unemployment is important for price level stability regardless of business cycle goals. Journal of Economic Literature codes: E12 E24 E31 E32 E52.
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Title: THE GALACTIC NOVA RATE : ESTIMATES FROM ALL-SKY TIME DOMAIN SURVEYS
Creator: Kawash, Adam
Date: 2022
Collection: Electronic Theses & Dissertations
Description: There is a significant discrepancy between recent predictions of the Milky Way classical novarate of ∼ 60 per year and the annual discovery rate of ∼ 10. Why the recovery fraction of these events is ∼ 15% even with large advancements to observational time domain astronomy remains largely unexplained. Because of the location of Earth within the Galaxy, discovering Galactic transients requires a large field of view. For the past few decades, observations from a network of amateur astronomers...
Show moreThere is a significant discrepancy between recent predictions of the Milky Way classical novarate of ∼ 60 per year and the annual discovery rate of ∼ 10. Why the recovery fraction of these events is ∼ 15% even with large advancements to observational time domain astronomy remains largely unexplained. Because of the location of Earth within the Galaxy, discovering Galactic transients requires a large field of view. For the past few decades, observations from a network of amateur astronomers were largely responsible for discovering classical novae, so the sky-coverage as a function of position and depth was difficult to model. Fortunately, in the past decade, many time domain surveys with fields of view that cover large areas of the sky have been commissioned, making the sky-coverage more well defined. To date, there are no Galactic nova rate predictions made using data from a time domain survey that is capable of observing the entire sky. In this thesis, the first estimate of the Galactic nova rate using observations from two all-sky surveys is made. The All-Sky Automated Survey for Supernovae (ASAS-SN) is the first survey to systematically observe the entire sky every night, providing unprecedented cadence of the sky for transients and variable stars. The space-based survey Gaia has a broad observing filter and a fine (∼ 0.1 arcsecond) pixel scale, so it is capable of detecting Galactic plane transients in crowded fields that are heavily affected by extinction. These are the only two all-sky surveys to report classical nova candidates, and they have contributed to marginally increasing the discovery rate of Galactic novae to 13 per year on average since 2017. In addition to the increase in discoveries, this thesis exploits the systematic observing patterns to estimate what fraction of the Galaxy’s novae these surveys detect. To make this estimate, I have constructed a statistical model of Galactic classical novae by utilizing the recently published models of stellar density and extinction of the Milky Way. Using ASAS-SN photometry, I measure the outburst amplitude of novae to be normally distributed with mean and standard deviation μ = 11.43 ± 0.25 mag and σ = 2.57 ± 0.20 mag, respectively. By using recently available all-sky 3D dust maps, I estimate that ∼ 50% of Galactic novae are hidden by extinction from being detected by ASAS-SN. Finally, I estimate that the recovery fraction of the global population of Galactic novae for ASAS-SN ≈ 33%, Gaia ≈ 42%, and a joint effort of the two surveys ≈ 54%, predicting that the Galactic nova rate is 26 ± 5 yr−1, significantly lower than recent estimates.
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Title: ELUCIDATING THE POTENTIAL ROLE OF ARYL HYDROCARBON RECEPTOR IN THE PATHOGENESIS OF CAMPYLOBACTER JEJUNI.
Creator: Ahmed, Husnain
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Campylobacter jejuni is a leading cause of human foodborne gastroenteritis in the US, with an incidence rate of 13.6 diagnosed cases per 100,000 individuals. The most frequent cause of C. jejuni infection in the US is the consumption of chicken contaminated during processing. Macrolide antibiotics such as azithromycin and ciprofloxacin are the drug of choice to treat C. jejuni infection in human populations. However, the over-use of antibiotics has led to the emergence of antimicrobial...
Show moreCampylobacter jejuni is a leading cause of human foodborne gastroenteritis in the US, with an incidence rate of 13.6 diagnosed cases per 100,000 individuals. The most frequent cause of C. jejuni infection in the US is the consumption of chicken contaminated during processing. Macrolide antibiotics such as azithromycin and ciprofloxacin are the drug of choice to treat C. jejuni infection in human populations. However, the over-use of antibiotics has led to the emergence of antimicrobial-resistant C. jejuni strains and reduced treatment efficacy. The development of antimicrobial resistance traits in C. jejuni isolates has augmented the need to develop innovative strategies to treat drug-resistant C. jejuni infections in human and animal populations.Members of the genus Lactobacillus are commonly used as probiotics, however the mechanisms by which they provide protective health effects remain elusive. In the first study, we described a novel mechanism by which L. murinus attenuates pro-inflammatory responses in the human intestinal epithelial cells. The results showed that L. murinus activates aryl hydrocarbon receptor (AHR) to decrease the secretion of IL-8 in response to exogenous stimulation by TNF-alpha in the human intestinal epithelial cells. Furthermore, activating the AHR with its defined ligand also reduced the secretion of IL-8 upon TNF-alpha stimulation. These results suggest that AHR can a novel target for inflammatory bowel disease (IBD) treatment. Furthermore, these results suggest that L. murinus can be a novel probiotic for treating IBD. In the 2nd study, we determined the effect of prophylactic inoculation of L. muirnus on the pathogenesis of C. jejuni in the BALB/c IL-10-/- mice. A total of 41 BALB/c IL-10-/- mice were used in this study. 11 mice were sham inoculated, 10 mice received only L. murinus, 10 mice received only C. jejuni, and 10 mice in the test group received both L. murinus and C. jejuni such that L. murinus was inoculated 32 days before C. jejuni infection. In addition, 30 days post-C. jejuni challenge mice were sacrificed and assessed for gut pathology. Fecal samples were also collected to access bacterial colonization levels in the gut through routine culture techniques and 16S sequence analysis. Both positive control group for C. jejuni and test groups mice developed severe colitis. 16S analysis of fecal DNA revealed that bacterial diversity in the test and positive control group for C. jejuni was significantly less (P<0.001) than in the Lactobacillus only and negative control group. These results suggest that prophylactic administration of L. murinus does not protect BALB/c IL-10-/- mice from developing disease following C. jejuni infection. Overall, this dissertation contains identification of a novel mechanism of action of L. murinus. The results provide insights for the identification of novel targets to treat C. jejuni disease without using antibiotics. This dissertation provides a basis for the future studies to further dissect the role of the AHR in the pathogenesis of C. jejuni.
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Title: ADVANCING ENGINEERED ENDOSYMBIONTS AS A PLATFORM TECHNOLOGY FOR THERAPEUTIC MACROPHAGE MODULATION
Creator: Madsen, Cody Scott
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This dissertation describes the construction of engineered endosymbionts (EES) as a platform technology for modulating macrophage function for therapeutic applications. Dr. Ashley Makela and I worked closely to advance the EES technology. Dr. Makela focused on the characterization of the EES ability to change macrophage function and I focused on developing the EES technology and working with Dr. Makela on characterization and using the EES in applications (Chapter 2 and 3). In Chapter 2,...
Show moreThis dissertation describes the construction of engineered endosymbionts (EES) as a platform technology for modulating macrophage function for therapeutic applications. Dr. Ashley Makela and I worked closely to advance the EES technology. Dr. Makela focused on the characterization of the EES ability to change macrophage function and I focused on developing the EES technology and working with Dr. Makela on characterization and using the EES in applications (Chapter 2 and 3). In Chapter 2, Bacillus subtilis was developed as a chassis organism for EES that escape phagosome destruction, reside in the cytoplasm of mammalian cells, and secrete proteins that are transported to the nucleus to impact host cell response and function. Two synthetic operons encoding either the mammalian transcription factors (TFs) Stat-1 and Klf6 or Klf4 and Gata-3 were recombined into the genome of B. subtilis expressing listeriolysin O (LLO) from Listeria monocytogenes and expressed from regulated promoters. Controlled expression of the mammalian proteins from B. subtilis LLO in the cytoplasm of J774A.1 macrophage/monocyte cells altered surface marker, cytokine and chemokine expression. Once the EES platform was developed and initially tested in vitro with a macrophage cell line, translating the EES to applications became the next step to understand the capacity of the new technology (Chapter 3). For increased translatability, the effect of the engineered B. subtilis LLO TF strains on murine bone marrow-derived macrophages (BMDMs) function was characterized. The TF strains shifted BMDM production of cytokines, chemokines and metabolic patterns. RNA-seq is still being analyzed to elucidate effects on gene expression. Furthermore, the ability of the B. subtilis LLO TF strains to alter the tumor microenvironment was characterized in a murine 4T1 orthotopic breast cancer model. The B. subtilis LLO strains altered the tumor microenvironment by promoting immune cell invasion, altering the functional metabolism of cells within the tumor, and causing tumor growth stabilization. Additionally, safety of this EES platform was observed as multiple doses at bacterial concentrations 100-fold more than other bacterial therapies were injected without affecting the health of mice. Yet, during the development and characterization of the EES, the sugar (D-mannose) that was used to induce transcription in the EES once inside the host cell was observed to significantly impact macrophage physiology which created additional complexity and was not ideal for in vivo applications. Accordingly, Emily Greeson and I worked on developing a mechanism for non-invasive localized control of gene expression in vivo. Emily Greeson engineered B. subtilis with temperature sensitive repressors (TSRs) and characterized this new genetic switch. I then coated B. subtilis with superparamagnetic iron oxide nanoparticles (SPIONs) which could be stimulated by an alternating magnetic field (AMF) to generate thermal energy. Chapter 4 discusses this new approach, and we investigated the ability of magnetic hyperthermia to regulate TSRs of bacterial transcription. The TSR, TlpA39, was derived from a Gram-negative bacterium, and used here for thermal control of reporter gene expression in Gram-positive B. subtilis. In vitro heating of B. subtilis with TlpA39 controlling bacterial luciferase expression, resulted in a 14.6-fold (12 hour; h) and 1.8-fold (1 h) increase in reporter transcripts with a 9-fold (12 h) and 11.1-fold (1 h) increase in bioluminescence. To develop magnetothermal control, B. subtilis cells were coated with three SPION variations which was confirmed by electron microscopy coupled with energy dispersive X-ray spectroscopy. Furthermore, using long duration AMF, we demonstrated magnetothermal induction of the TSRs in SPION-coated B. subtilis with a maximum of 4.6-fold increases in bioluminescence. Pairing TSRs with magnetothermal energy using SPIONs for localized heating with AMF can lead to improved EES transcriptional control. The research described in this dissertation demonstrates a multi-disciplinary approach towards developing a new modular technology to alter mammalian cell function with the specific focus on macrophages.
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Title: Efficient Distributed Algorithms : Better Theory and Communication Compression
Creator: LI, YAO
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Large-scale machine learning models are often trained by distributed algorithms over either centralized or decentralized networks. The former uses a central server to aggregate the information of local computing agents and broadcast the averaged parameters in a master-slave architecture. The latter considers a connected network formed by all agents. The information can only be exchanged with accessible neighbors with a mixing matrix of communication weights encoding the network's topology....
Show moreLarge-scale machine learning models are often trained by distributed algorithms over either centralized or decentralized networks. The former uses a central server to aggregate the information of local computing agents and broadcast the averaged parameters in a master-slave architecture. The latter considers a connected network formed by all agents. The information can only be exchanged with accessible neighbors with a mixing matrix of communication weights encoding the network's topology. Compared with centralized optimization, decentralization facilitates data privacy and reduces the communication burden of the single central agent due to model synchronization, but the connectivity of the communication network weakens the theoretical convergence complexity of the decentralized algorithms. Therefore, there are still gaps between decentralized and centralized algorithms in terms of convergence conditions and rates. In the first part of this dissertation, we consider two decentralized algorithms: EXTRA and NIDS, which both converge linearly with strongly convex objective functions and answer two questions regarding them. \textit{What are the optimal upper bounds for their stepsizes?} \textit{Do decentralized algorithms require more properties on the functions for linear convergence than centralized ones?} More specifically, we relax the required conditions for linear convergence of both algorithms. For EXTRA, we show that the stepsize is comparable to that of centralized algorithms. For NIDS, the upper bound of the stepsize is shown to be exactly the same as the centralized ones. In addition, we relax the requirement for the objective functions and the mixing matrices. We provide the linear convergence results for both algorithms under the weakest conditions.As the number of computing agents and the dimension of the model increase, the communication cost of parameter synchronization becomes the major obstacle to efficient learning. Communication compression techniques have exhibited great potential as an antidote to accelerate distributed machine learning by mitigating the communication bottleneck. In the rest of the dissertation, we propose compressed residual communication frameworks for both centralized and decentralized optimization and design different algorithms to achieve efficient communication. For centralized optimization, we propose DORE, a modified parallel stochastic gradient descent method with a bidirectional residual compression, to reduce over $95\%$ of the overall communication. Our theoretical analysis demonstrates that the proposed strategy has superior convergence properties for both strongly convex and nonconvex objective functions. Existing works mainly focus on smooth problems and compressing DGD-type algorithms for decentralized optimization. The class of smooth objective functions and the sublinear convergence rate under relatively strong assumptions limit these algorithms' application and practical performance. Motivated by primal-dual algorithms, we propose Prox-LEAD, a linear convergent decentralized algorithm with compression, to tackle strongly convex problems with a nonsmooth regularizer. Our theory describes the coupled dynamics of the inexact primal and dual update as well as compression error without assuming bounded gradients. The superiority of the proposed algorithm is demonstrated through the comparison with state-of-the-art algorithms in terms of convergence complexities and numerical experiments. Our algorithmic framework also generally enlightens the compressed communication on other primal-dual algorithms by reducing the impact of inexact iterations.
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Title: LEVEL 101 : A VIDEO GAME ABOUT VIDEO GAMES
Creator: Wigard, Justin Michael
Date: 2022
Collection: Electronic Theses & Dissertations
Description: For my dissertation, I developed a serious game entitled Level 101: A Video Game About Video Games, a playable video game that explores, explains, and interrogates the video game in order to understand the medium through a methodology of play. In doing so, Level 101 puts disparate elements of Game Studies into practice due to its branching paths, introducing players to three distinct frameworks for understanding video games: 1) history, 2) design, and 3) theory. Each of these three branches...
Show moreFor my dissertation, I developed a serious game entitled Level 101: A Video Game About Video Games, a playable video game that explores, explains, and interrogates the video game in order to understand the medium through a methodology of play. In doing so, Level 101 puts disparate elements of Game Studies into practice due to its branching paths, introducing players to three distinct frameworks for understanding video games: 1) history, 2) design, and 3) theory. Each of these three branches features five stages designed to educate players about the video game medium, as well as encourage critical reflection on video games and the process of playing through them. The primary audiences are twofold: college instructors who will use and assign the video game as a lecture supplement, and college students who would play through the video game. This is accompanied by a traditional dissertation component that addresses several issues: 1) historical and cultural contextualization; 2) theoretical and methodological investments; 3) a summation of the project’s critical contributions; and 4) a reflection of the development process. Level 101 seeks to begin filling in a crucial and overlooked pedagogical gap in Game Studies through uniting play and learning via digital means, but only in conjunction with other aspects of traditional learning. As such, Level 101 sits at the intersection of three distinct areas of inquiry: Game Studies, Pedagogy, and Digital Humanities. By drawing not just from Game Studies, but from other corollaries in such disparate fields as comic studies, literary studies, film studies, among others, Level 101 also holds the potential for further experimentations with playable methods of academic engagement and alternative scholarship.
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Title: PRE-SERVICE TEACHERS AND AUTHOR IDENTITIES ON SOCIAL MEDIA : BEING AUTHORS AND TEACHING AUTHORING
Creator: Galvin, Sarah M.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Social media are some of the most used digital composition tools by both youth and adults yet authoring in digital spaces remains undervalued and digital literacy education remains misaligned with workplace needs and expectations. Using a multiple case study design (n=3) to explore the authorship of pre-service English/ELA teachers on social media and how it impacts their composition instruction, this study forefronts social media as a critical space for authoring that should be considered in...
Show moreSocial media are some of the most used digital composition tools by both youth and adults yet authoring in digital spaces remains undervalued and digital literacy education remains misaligned with workplace needs and expectations. Using a multiple case study design (n=3) to explore the authorship of pre-service English/ELA teachers on social media and how it impacts their composition instruction, this study forefronts social media as a critical space for authoring that should be considered in the context of education. Multiple interview sessions and composition artifacts (e.g., social media posts, course assignments, creative writing) were used to gather stories of the pre-service teachers’ authorship experiences and their approaches to composition instruction. This study speaks to the need to reconsider what counts as valuable literacies; pre-service teachers’ frequent authoring on social media cannot be siloed away from the authorial identities they bring into their classrooms and their classroom instruction. Final analyses offer implications for future research at the intersection of authorship theory, social media, and pre-service teachers ’education, as well as implications for revised authorship theories and practical implications for supporting pre-service teachers as authors and composition instructors.
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Title: Eigenvector Continuation : Convergence and Emulators
Creator: Sarkar, Avik
Date: 2022
Collection: Electronic Theses & Dissertations
Description: There has been a great interest in the scientific community in using machine learning to build emulators that can accurately predict scientific processes using only a fraction of the time needed for direct calculations. The computational advantage of emulators allows us to study processes that are beyond what is possible with direct calculations. Eigenvector continuation is one such emulation technique that was introduced recently. It is a variational method that finds the extremal...
Show moreThere has been a great interest in the scientific community in using machine learning to build emulators that can accurately predict scientific processes using only a fraction of the time needed for direct calculations. The computational advantage of emulators allows us to study processes that are beyond what is possible with direct calculations. Eigenvector continuation is one such emulation technique that was introduced recently. It is a variational method that finds the extremal eigenvalues and eigenvectors of a Hamiltonian matrix with one or more control parameters. The computational advantage comes from projecting the Hamiltonian onto a much smaller subspace of basis vectors corresponding to eigenvectors at some chosen training values of the control parameters. The method has proven to be very efficient and accurate for interpolating and extrapolating eigenvectors. In this work, we present a study on the error convergence properties of eigenvector continuation. With the insights we gain from learning the convergence properties, we then propose a self-learning algorithm to efficiently select training eigenvectors for eigenvector continuation. Self-learning is an active-learning process that relies on a fast estimate of the emulator error and a greedy local optimization algorithm that becomes more accurate as the emulator approximation improves. We show that self-learning emulators are highly efficient algorithms that offer both high speed and high accuracy, and it can be applied to any emulator that emulates the solution to a system of constraint equations, such as solutions of algebraic or transcendental equations, linear and nonlinear differential equations, and linear and nonlinear eigenvalue problems.
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Title: PERCEPTIONS OF VOICE PRODUCTION IN HEALTHY FEMALES IN REGARDS TO AGE AND PROFESSIONALISM : AS QUANTIFIED BY ACOUSTIC AND PERCEPTUAL MEASURES
Creator: Nizami, Hafsaah Fatima
Date: 2022
Collection: Electronic Theses & Dissertations
Description: PURPOSE: This study aims to research the perception of voice as it relates to aging and professionalism in an individual. The production of voice varies in accordance with various factors. These variations often provide an insight into a listener’s perceptions of a speaker’s vocal characteristics and these perceptions may vary across settings. METHODS: This study required four components. The first component required college aged participants to rate perceptions of age and health in regards...
Show morePURPOSE: This study aims to research the perception of voice as it relates to aging and professionalism in an individual. The production of voice varies in accordance with various factors. These variations often provide an insight into a listener’s perceptions of a speaker’s vocal characteristics and these perceptions may vary across settings. METHODS: This study required four components. The first component required college aged participants to rate perceptions of age and health in regards to young and old female vocalists. The second section required college aged participants to rate professionalism in regards to young and old female vocalists. Speech Professionals were asked to participate in the third component of this study, in which they rated listeners among the GRBAS scale. The last component required a quantification of results using a standard acoustic measure like cepstral peak prominence. RESULTS: Strong positive correlations were found between estimated age and actual age, strong negative correlations were found between older women and professionalism; moderately positive correlations were found between younger women and professionalism; moderate to strong correlation was found between age and GRBAS; and moderate negative correlations were found between age and CPPS. DISCUSSION: The following results were found: College-aged students were able to distinguish between the younger and older females. Older women were perceived as less professional. As age increases, GRBAS scores also increase. As age increases, CPPS ratings will decrease. CONCLUSION: Further research may require completion of surveys in a controlled environment, and inclusion of pitch-related measures as they relate to the workplace. Keywords: Aging voice, biological sex differences, perception of voice, professional voice, acoustic measures
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Title: A MULTICASE STUDY OF THREE GRADUATE TEACHING ASSISTANTS PARTICIPATING IN THE MDISC TEACHING PROFESSIONAL DEVELOPMENT
Creator: Kuechle, Valentin Alexander Balthasar
Date: 2022
Collection: Electronic Theses & Dissertations
Description: In this multicase study (Stake, 2005), I studied a semester-long online implementation of the “Mathematics Discourse in Secondary Classrooms” (Herbel-Eisenmann, Cirillo, et al., 2017) (MDISC) teaching professional development (T-PD)—slightly modified for the university context—which I offered to three mathematics-teaching graduate teaching assistants (GTAs) (i.e., Finnegan, Valeria, and Alice) who were no longer in their first year of teaching. I sought to understand: (a) How does the...
Show moreIn this multicase study (Stake, 2005), I studied a semester-long online implementation of the “Mathematics Discourse in Secondary Classrooms” (Herbel-Eisenmann, Cirillo, et al., 2017) (MDISC) teaching professional development (T-PD)—slightly modified for the university context—which I offered to three mathematics-teaching graduate teaching assistants (GTAs) (i.e., Finnegan, Valeria, and Alice) who were no longer in their first year of teaching. I sought to understand: (a) How does the classroom discourse change in each of the participant’s classes over the course of their participation in the MDISC T-PD?; and (b) How do participants talk about their use of the teacher discourse moves (TDMs) (e.g., Cirillo et al., 2014; Herbel-Eisenmann et al., 2013)? To analyze the change in classroom discourse, I studied two sets of classroom discourse dimensions: (a) the TDMs (i.e., waiting, inviting student participation, revoicing, asking students to revoice, probing a student’s thinking, and creating opportunities to engage with another’s reasoning), which were a central set of practical tools offered by the T-PD; and (b) student discourse dimensions drawn from the discourse dimensions of the “Equity QUantified In Participation” (EQUIP) tool (Reinholz & Shah, 2018).In line with a multicase approach, this study consists of one case report for each participant, with each report driven by an emic issue, as well as a multicase report thereafter in which the participants’ similarities and differences with respect to the research questions are explored. Finnegan, Valeria, and Alice’s respective emic issues were: (a) How can an instructor who wants students to participate in their class invite student participation?; (b) How does an instructor who weighs wielding her authority to engage students against respecting students’ agency (even if that agency is used to not participate) implement the TDMs?; and (c) How does an instructor who finds herself in a stage of “survival” (Beisiegel et al., 2019; Katz, 1972) implement and talk about the TDMs? Finnegan, who sought to invite student participation, especially took to TDMs that helped him do so: waiting (particularly wait time 1 [Rowe, 1986]), probing a student’s thinking, and inviting student participation via cold-calling. Valeria, who did not want to force students to do things, felt more comfortable implementing TDMs that relied more on what she was doing than on what students were doing. She mainly used waiting (particularly wait time 1), revoicing, and inviting student participation via inviting further responses. Last, Alice, who found herself in a stage of survival, continued using those TDMs that she was already familiar with, that is, waiting and revoicing. This study contributes to the emerging area of T-PD for GTAs beyond their first year of teaching. In addition, it offers a refinement of the TDMs and a detailed account of how and why participants used (or did not) each TDM. The TDM refinement includes: (a) a refinement of “waiting” that builds on work by Rowe (1986) and Ingram and Elliott (2016); (b) a refinement of “probing a student’s thinking” that distinguishes between two types of probing (i.e., to clarify a student’s turn or to go deeper with it) enacted in two ways (i.e., instructor- or student-centric) in response to student statements or questions; and (c) a refinement of “creating opportunities to engage with another’s reasoning” by distinguishing between five types of such engagement (i.e., adding to, anticipating, comparing to, evaluating, and understanding). Further, the participants’ uses for revoicing add to work on different uses of revoicing (e.g., Herbel-Eisenmann et al., 2009), and the participants’ hesitations about asking students to revoice provide insight into the challenges of learning to use this TDM.
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Title: Numerical Simulations of Plasmas in Galaxy Clusters
Creator: Glines, Forrest Wolfgang
Date: 2022
Collection: Electronic Theses & Dissertations
Description: As the largest gravitationally bound objects in the universe, galaxy clusters are a unique probeof large scale cosmological structure. Determining the distribution of galaxy clusters and their virial masses may be key to constraining properties of dark energy and dark matter. Since 84% of a typical galaxy cluster’s mass is comprised of non-radiating dark matter, however, determining the virial mass of galaxy clusters depends on inference from the radiating baryonic matter. 84% of this...
Show moreAs the largest gravitationally bound objects in the universe, galaxy clusters are a unique probeof large scale cosmological structure. Determining the distribution of galaxy clusters and their virial masses may be key to constraining properties of dark energy and dark matter. Since 84% of a typical galaxy cluster’s mass is comprised of non-radiating dark matter, however, determining the virial mass of galaxy clusters depends on inference from the radiating baryonic matter. 84% of this baryonic matter is contained in the intracluster medium (ICM) – a hot, diffuse, magnetized plasma permeating the galaxy cluster. While the baryonic matter is the only emitter of observable electromagnetic emissions from galaxy clusters, the complex behavior of the ICM as a turbulent magnetized plasma makes constraining the virial mass of the cluster with observable signatures difficult. Numerical simulations are essential tools for advancing understanding of the ICM and for tying galaxy cluster observables to virial masses. The goal of this dissertation is to explore and enable simulations of galaxy clusters and magnetized plasmas via a number of different avenues.I first explore self-regulation of feedback from active galactic nuclei (AGN) preventing over-cooling in cool-core (CC) clusters – galaxy clusters with anomalously high central thermal emission which should cool on shorter timescales than they persist. In the idealized galaxy cluster simulations with a thermal abstraction of AGN feedback, we find that the thermal-only heating kernels we test are unable to offset cooling while maintaining a realistic structure, suggesting exploration of more complex AGN feedback mechanisms such as those including magnetic fields and turbulence.We then explore how kinetic and magnetic energy thermalizes in the ICM by studying decayingmagnetized turbulence with simulations of the magnetized compressible Taylor-Green vortex. Using a shell-to-shell energy transfer analysis, we find that the magnetic fields facilitate a significant amount of the energy flux that is not seen in hydrodynamic turbulence. Although the full cascade will not be directly captured in ICM simulations for the foreseeable future, higher resolution simulations enabled by larger computational resources can diminish such effects.Different novel many-core architectures have emerged in recent years on the way toward largersupercomputers in the exascale era. Performance portability is required to prevent repeated nontrivial refactoring of a code for different architectures. To address the need for a performance portable magnetohydrodynamics (MHD) code, we combined Athena++, an existing MHD CPU code, with Kokkos, a performance portable framework, into K-Athena to allow efficient simulations on multiple architectures using a single codebase. K-Athena has also inspired the Parthenon performance portable adaptive mesh refinement (AMR) framework. Using this framework, we developed the performance portable AMR MHD code AthenaPK.Galaxy clusters contain significant magnetic fields, although their origin and role is still underinvestigation. Numerical modeling is essential for the inference of their properties. One aspect is whether magnetic AGN feedback models can self-regulate. I present work-in-progress simulations with AthenaPK of magnetized galaxy clusters slated for exascale supercomputers later this year.With the higher resolutions enabled by exascale systems, galaxy cluster simulations with relativistic jet velocities will be possible. Robust methods for relativistic plasmas will be needed.With this goal, I present a discontinuous-Galerkin (DG) method for relativistic hydrodynamics. We include an exploration of different methods to recover the primitive variables from conserved variables, a new operator for enforcing a physically permissible conserved state, and numerous tests of the method. This method has been used at Sandia National Laboratories to study terrestrial plasmas and will inform relativistic MHD methods for AthenaPK.Finally, I cover the future directions of the work in this dissertation, including the many codesenabled by Parthenon, additions to the magnetized galaxy cluster simulations with AthenaPK, and the large body of projects at Los Alamos National Laboratory to explore binary black hole mergers embedded within AGN accretion disks as a possible formation channel of the massive black holes observed by LIGO. The work in this dissertation to develop performance portable plasma simulations will enable ground-breaking simulations for years to come.
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Title: Three Essays on Causes and Consequences of Violence and Conflict
Creator: Ayesh, Abubakr
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This dissertation revolves around the theme of violence, crime and conflict. It is an attempt at (a) improving the understanding of the causes of violence and crime, and (b) the consequences of violence and conflict. Specifically, the first chapter investigates if air pollution can be a contributor to crime, the second chapter looks at the labor market impacts of terrorism in non-war zones, and the last chapter tries to understand the human capital accumulation decisions of permanently...
Show moreThis dissertation revolves around the theme of violence, crime and conflict. It is an attempt at (a) improving the understanding of the causes of violence and crime, and (b) the consequences of violence and conflict. Specifically, the first chapter investigates if air pollution can be a contributor to crime, the second chapter looks at the labor market impacts of terrorism in non-war zones, and the last chapter tries to understand the human capital accumulation decisions of permanently displaced individuals.The first chapter looks at air pollution as a potential contributor to criminal activity. Using the seasonal variation in increase in air pollution --due to increased rice stubble burning-- in the Punjab province of Pakistan, I explore the relationship between air pollution and crime. I combine eight different sources of data and use an instrumental variable approach to estimate the causal impact of air pollution on crime. Air pollution increases both violent and non-violent crimes, but the increase in violent crimes is much more salient. A one standard deviation increase in seasonal variation in air pollution increases violent crime by at least 15 percent. Back of the envelope calculations suggest that the cost of increased crime due to air pollution are at least 5 million US dollars, but maybe as high as 600 million US dollars. One potential mechanism driving the estimates is the reduction in earnings for middle aged male individuals due to high air pollution. The results suggest that the social costs of air pollution are much wider than those previously considered. They also have significant implications for developing countries whose economies rely on agriculture. The second chapter of the dissertation looks at the impact of violence in non-war zones on incomes. A non-war zone does not have an active presence of the military, and it is not characterized by mass migration or shutting down of the economy. I use data from Pakistan on intermittent but sustained terrorist attacks for this purpose. After accounting for the intensity of the attacks, incomes reduce by about 2.5 percent on average due to terrorist attacks. However, the effect is almost twice in the same month in which a terrorist attack takes place in a district. The effects are more severe for low skilled members of the labor force as well as for relatively inexperienced members. The two potential channels driving this impact are the changes in employment compositions across different occupations and a reduction in the number of days worked. From a policy perspective, relief and welfare efforts targeted towards (a) the most vulnerable groups in the labor force and (b) the sectors of the economy directly affected by the violence seem to be the best possible response -instead of general aid aimed at overall rebuilding of the economy which is more relevant for a war or conflict zone. The last chapter considers the event of partition between India and Pakistan in 1947 that induced forced migration and permanent displacement of about 14.5 million people. I compare the educational outcomes of migrants and natives who were still in school going age when they were forced to migrate. I use a differences-in-differences approach. I also address the recent development in related literature on concerns related to identification, power, and bias in a differences-in-differences approach. I find that migrants are more likely to achieve certain educational milestones than their native counterparts. The results may be driven by the choices of older migrants pertaining to location and occupation. They also highlight the importance of an enabling and convenient environment for migrants which plays a crucial role in the pursuit of their educational goals.
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Title: LAKE TYPE AND CONNECTIVITY PREDICT ZEBRA MUSSEL (DREISSENA POLYMORPHA) PRESENCE
Creator: Matuszak, Danielle
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Studies that differentiate between lake type or origin, i.e., natural lakes and reservoirs, or that focus solely on reservoirs are rare, especially at broad scales. These facts lead to reservoirs being less well understood compared to natural lakes. It is known that adding dams/impoundments alters the flow regime of the original water body and changes surface water connectivity. However, the impact of these alterations on invasive species dispersal is widely unknown. Reservoirs are also...
Show moreStudies that differentiate between lake type or origin, i.e., natural lakes and reservoirs, or that focus solely on reservoirs are rare, especially at broad scales. These facts lead to reservoirs being less well understood compared to natural lakes. It is known that adding dams/impoundments alters the flow regime of the original water body and changes surface water connectivity. However, the impact of these alterations on invasive species dispersal is widely unknown. Reservoirs are also thought to have higher levels of human disturbance, which can provide opportunities for non-native species such as the zebra mussel (Dreissena polymorpha) to invade and establish. Surface water connections allow zebra mussel larvae to flow from one waterbody to another. Additionally, trailering of recreational boats among lakes can promote overland dispersal of zebra mussels through live wells and boating equipment. Although such connectivity promotes zebra mussel spread, we do not yet know how zebra mussels vary according to lake type nor the relative roles of surface and human connectivity and lake type. Taking a data-intensive approach at the macroscale, we ask: Are zebra mussels more common in reservoirs than in natural lakes? How does surface water and human connectivity influence the presence of zebra mussels in reservoirs and natural lakes? To answer these questions, we used 907 lakes within a 17-U.S. state extent and data from a variety of sources. Water quality, surface water connectivity, and human disturbance data were from the LAke multi-scaled GeOSpatial and temporal (LAGOS) database, public lake access sites were from the United States Geological Survey (USGS), and zebra mussel presence data were from the USGS Nonindigenous Aquatic Species database. We characterized surface water connectivity using six unique lake connectivity classes. We characterized human connectivity two ways: watershed road densities measured in meters per hectare and, for a 3-state subset of the study extent, the presence of public access sites on lakes. We characterized surface water connectivity using a lake connectivity classification based on lake and stream inflow(s)/outflow(s). Using logistic multiple regressions and controlling for region and lake chlorophyll a concentrations, we found that a higher proportion of reservoirs have zebra mussels compared to natural lakes for the 17-state extent. At this same spatial extent, we found that more highly connected lakes, both by humans and surface waters, were more likely to have zebra mussels present, regardless of lake type. Finally, at the 3-state extent, lakes with a public access site were more likely to have zebra mussels than those without, regardless of lake type. We conclude that not all ‘lakes’ are equally likely to have zebra mussels present and that both surface water and human connectivity are important predictors of zebra mussel presence. This study improves the understanding of how natural lakes and reservoirs differ and the extent to which reservoirs disproportionately harbor the invasive zebra mussel, which can improve management and prevention. For example, these results suggest that legislation and management focused on uninvaded reservoirs that are highly connected may help slow the spread of this invasive species.
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