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Title: AGGRESSION AND THE GUT-BRAIN AXIS
Creator: Kwiatkowski, Christine Carole
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Violence is a widespread public health and justice system problem with far-reaching consequences for victims, offenders, and their communities. Aggression, the cognitive and behavioral antecedent to violent action, is mainly understood in terms of the psychosocial risk factors that increase the likelihood of aggressive behavioral strategies. Neighborhood context is a principal risk factor for violent crime perpetration, but the mechanisms that mediate the effect of the environment on...
Show moreViolence is a widespread public health and justice system problem with far-reaching consequences for victims, offenders, and their communities. Aggression, the cognitive and behavioral antecedent to violent action, is mainly understood in terms of the psychosocial risk factors that increase the likelihood of aggressive behavioral strategies. Neighborhood context is a principal risk factor for violent crime perpetration, but the mechanisms that mediate the effect of the environment on individual-level aggression behavior are poorly understood, especially the biological factors that may contribute to our understanding of violent behavior. In order to gain a better understanding of mechanisms that precipitate violence in specific geographic contexts, this dissertation explores the relationship between aggression behavior and the gut microbiome, a spatially determined physiological system that affects human health and behavior. Preclinical experiments elucidate the role of the gut microbiome in territorial, reactive aggression behavior in mice. Results show significant differences in gut microbiome composition across the spectrum of murine aggression behavior. Moreover, manipulation of the gut microbiome via administration of short-term antibiotics and sodium butyrate, a short-chain fatty acid byproduct of microbial fermentation, increases aggression behavior. The overall goal of this research is to use basic science findings in mice to better understand how environmental exposures could influence human health and behavior, thus revealing how community health affects individuals and supplying a potential target for future intervention.
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Title: CIRCADIAN RHYTHMS IN LATE PREGNANCY : A ROLE IN THE REPRODUCTIVE AXIS, UTERINE CONTRACTIONS AND PRETERM LABOR
Creator: Duong, Thu Van Quynh
Date: 2022
Collection: Electronic Theses & Dissertations
Description: What drives labor onset remains largely unknown. Understanding the molecular mechanisms defining pregnancy duration and preparing the uterus for labor onset can help improve current treatment strategies to promote or halt labor. Biological processes with a ~24-hour cycle called circadian rhythms are generated by endogenous “clock” transcription factors referred to as the molecular clock, which drives daily changes in cellular functions. To understand the role of circadian rhythms in pregnancy...
Show moreWhat drives labor onset remains largely unknown. Understanding the molecular mechanisms defining pregnancy duration and preparing the uterus for labor onset can help improve current treatment strategies to promote or halt labor. Biological processes with a ~24-hour cycle called circadian rhythms are generated by endogenous “clock” transcription factors referred to as the molecular clock, which drives daily changes in cellular functions. To understand the role of circadian rhythms in pregnancy, we first characterized how the molecular clock of the reproductive axis adapts to pregnancy and found the molecular clock is upregulated. Next, to understand if the molecular clock helps define pregnancy duration, we analyzed gene expression data from pregnant women. We found that low maternal levels of two clock genes increased the risk of preterm birth 5 fold. As preterm birth is driven by a premature increase in uterine contractions, we then asked how time of day impacted uterine contractile response to oxytocin, a hormone that increases uterine contractions and is widely used to induce labor. As model for human pregnancy, mice presented with daily time windows of increased uterine sensitivity to oxytocin. To determine if the molecular clock drives this daily change in sensitivity to oxytocin, we used conditional knockout mice which had the molecular clock ablated in uterine smooth muscle. These mice lost the daily change in sensitivity to oxytocin-induced contractions and presented stronger spontaneous uterine contractions than controls. In conclusion, we show that circadian rhythms have an important role in regulating pregnancy duration and uterine function, where the uterine molecular clock defines daily time windows of enhanced uterine sensitivity to oxytocin.
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Title: Metamodeling in Evolutionary Multi-Objective Optimization for constrained and unconstrained Problems
Creator: Hussein, Rayan
Date: 2022
Collection: Electronic Theses & Dissertations
Description: One of the main difficulties in applying an optimization algorithm to a practical problem is that the evaluation of objectives and constraints often involve computationally expensive procedures. To handle such problems, a metamodel (or surrogate model, or response surface approximations) is first formed from a few exact (high-fidelity) solution evaluations, and then optimized by an algorithm in a progressive manner. However, there has been lukewarm interest in finding multiple trade-off...
Show moreOne of the main difficulties in applying an optimization algorithm to a practical problem is that the evaluation of objectives and constraints often involve computationally expensive procedures. To handle such problems, a metamodel (or surrogate model, or response surface approximations) is first formed from a few exact (high-fidelity) solution evaluations, and then optimized by an algorithm in a progressive manner. However, there has been lukewarm interest in finding multiple trade-off solutions for multi-objective optimization problems using surrogate models. The literature on surrogate modeling for constrained optimization problems is also rare. The difficulty lies in the requirement ofbuilding and solving multiple surrogate models, one for each Pareto-optimal solution. In this study, we propose a taxonomy of different possible metamodeling frameworks for multi-objective optimization and provide a comparative study by discussing advantages and disadvantages of each framework. Also, we argue that it is more efficient to use different metamodeling frameworks at different stages of the optimization process. Thereafter, we propose a novel adaptive method for switching among different metamodeling frameworks. Moreover, we observe the convergence behavior of the proposed approaches is better with a trust regions method applied within the metamodeling frameworks. The results presented in this study are obtained using the well-known Kriging metamodeling approach. Based on our extensive simulation studies on proposed frameworks, we report new and interesting observations about the behavior of each metamodeling framework, which may provide salient guidelines for further studies in this emerging area within evolutionary multi-objective optimization. Results of this study clearly show the efficacy and efficiency of the proposed adaptive switching approach compared to three recently-proposed other metamodeling algorithms on challenging multi-objective optimization problems using a limited budget of high-fidelity evaluations.
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Title: WRITING ASSESSMENT IN MIDDLE SCHOOL STUDENTS : ANALYZING SPELLING WITHIN A MULTIDIMENSIONAL LANGUAGE FRAMEWORK
Creator: Sweet, Lake Eiseler
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Although producing quality written expression is a vital skill, many students in the United States struggle to produce proficient written language. There are many academic and career outcomes related to the ability to produce written expression, yet many schools lack formalized writing assessment and instruction. As such, many questions remain related to individual differences in writing ability and best practices in assessment and instruction. To answer these questions, it is necessary to...
Show moreAlthough producing quality written expression is a vital skill, many students in the United States struggle to produce proficient written language. There are many academic and career outcomes related to the ability to produce written expression, yet many schools lack formalized writing assessment and instruction. As such, many questions remain related to individual differences in writing ability and best practices in assessment and instruction. To answer these questions, it is necessary to establish a model of written expression and what specific variables exist within the model to be used to assess written language. Modern writing assessment theory uses levels of language as a framework with commonly assessed dimensions of accuracy, complexity and productivity. This framework has yet to be firmly established in the literature, and the variables included in each level are just beginning to be explored. One salient variable in writing research, assessment and instruction is spelling ability, and how this ability may influence the production of written language. This study furthers the work by Wilson et al. (2017), Troia and colleagues (2019) and many others (e.g., Berninger et al., 2006; Flower & Hayes, 1981) with the ultimate goal of developing a model of written language to guide assessment and instruction in schools. Specifically, data were drawn from Truckenmiller and colleagues (2020) study piloting a writing assessment tool, Writing Architect, which sampled 526 students from third to eight grades; this study used sixth, seventh and eighth grades with a resulting sample size of 290 students. Results indicated spelling was a significant predictor of writing quality, in that better spelling indicated better writing quality. The same was true for text. For the sentence-level variable, a higher score indicated worse writing quality in a significant way. The word variable did not significantly predict writing quality in the model. The significant interaction between spelling and text variables suggests that the effect of text on writing quality is even higher when spelling ability is also high. Findings highlight the importance of writing and spelling instruction in school. The findings for this age group help identify how writing abilities may change over the trajectory of development and vary individually. Additionally, this analysis echoes the call for further research to establish variables for automated writing assessment.
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Title: DEVELOPMENT OF NOVEL FLUORESCENT PROTEIN TAGS FOR NO-WASH LIVE-CELL IMAGING WITH MINIMUM FLUORESCENT BACKGROUND
Creator: Esmatpour Salmani, Rahele
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Recent fluorescence microscopy technologies have revolutionized many areasof biomedical research. Nonetheless, high brightness, far-red/near infra-red emission, deep tissue penetration, and selective fluorescent imaging with the minimum background are among the most desired novel fluorescent labeling. One of our primary goals is to develop flexible fluorescent protein tags capable of being tailored ad infinitum. We successfully demonstrated the ability to fine-tune the absorption and emission...
Show moreRecent fluorescence microscopy technologies have revolutionized many areasof biomedical research. Nonetheless, high brightness, far-red/near infra-red emission, deep tissue penetration, and selective fluorescent imaging with the minimum background are among the most desired novel fluorescent labeling. One of our primary goals is to develop flexible fluorescent protein tags capable of being tailored ad infinitum. We successfully demonstrated the ability to fine-tune the absorption and emission spectra of protein-bound chromophores over an unprecedented wide range (~200 nm). In contrast to intrinsically fluorescent proteins that are always “ON” in our systems, fluorescent is activated upon covalent binding of ligand and the target protein leading to temporal control of fluorescence. However, the fluorescence background from unbound free chromophore and non-specific binding has always been a deep concern in fluorescent labeling. This Ph.D. research aimed to develop novel proteinbased fluorescent tags emitting in the far-red/NIR region of the spectrum for no-wash background-free live-cell imaging applications. This was accomplished by coupling novel synthetic fluorogenic chromophores with hCRBPII mutants. Unbound free aldehyde ThioPhenol and CyThioPhenol are non-emissive dyes that become highly iii fluorescent upon imine formation with an active site lysine residue engineered deep in the hCRBPII cavity. We created a hydrogen-bonding network around the ThioPhenol hydroxyl group through rational protein engineering that facilitates its deprotonation upon photoexcitation. On the other hand, engineering the target protein to maintain a high iminium pKa resulted in Protonated Schiff Base (PSB) formation. The resultant complex experiences a strong intramolecular charge transfer (ICT), leading to fluorescence and a large bathochromic shift in the emission (~700 nm). The designed protein-based photoacid provides an unprecedented spatiotemporal control for nowash bright NIR imaging. Our most recent report demonstrated that hCRBPII/chromophore complexes could be developed as a photobase where the imine is converted to an iminium upon photoexcitation. In the course of optimizing hCRBPII to promote ESPT of the hydroxyl group, we discovered that ThioPhenol is capable of acting as both a photoacid and a photobase upon a single photoirradiation. When bound as a Schiff base (SB) to protein mutants that maintain a low iminium pKa (~5), engineered to deprotonate the hydroxyl group, a dual ESPT process leads to protonation of the imino to iminium (the photobase) and deprotonation of the hydroxyl to alkoxide (the photoacid). This double ESPT feature is recapitulated in a proteinligand micro-environment, yielding bright protein-dye complexes with unapparelled large pseudo-Stokes shifts (~250 nm). Additionally, the double ESPT ThioPhenol/hCRBPII complexes show fast binding rates (half-life of <3 min) that were successfully used to visualize whole-cell and the nucleus as a fluorogenic tag without any washing steps. Currently, further modifications are in progress to optimize the double ESPT systems with CyThioPhenol and further in-vivo applications.
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Title: MUTANT ANALYSIS OF A POLYOL MONOSACCHARIDE TRANSPORTER IN ARABIDOPSIS INVOLVED IN LIGNIFICATION
Creator: Tran, John Dang Khoa
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Monolignols have important roles in plant development and primarily serve as monomers for lignin polymerization in secondary cell walls. Monolignols are synthesized in the plant cytoplasm prior to entering the apoplast where oxidation occurs. Upon oxidation, monolignols are incorporated into the cell wall. Several mechanisms have been suggested to explain how monolignols cross the plasma membrane, including endocytosis, diffusion, and active transport. However, evidence for those models...
Show moreMonolignols have important roles in plant development and primarily serve as monomers for lignin polymerization in secondary cell walls. Monolignols are synthesized in the plant cytoplasm prior to entering the apoplast where oxidation occurs. Upon oxidation, monolignols are incorporated into the cell wall. Several mechanisms have been suggested to explain how monolignols cross the plasma membrane, including endocytosis, diffusion, and active transport. However, evidence for those models relied on theoretical calculations or produced results using in vitro approaches. Further, only one active transporter protein has been characterized to date. Yet, of the three monolignols tested, the transporter was only demonstrably shown to transport p-coumaryl alcohol, the least abundant monolignol present in Arabidopsis.Here we show that AtPMT4 is likely a monolignol transporter, particularly for the more abundant monolignols: coniferyl alcohol and sinapyl alcohol. Gene expression analysis performed on AtPMT4 in dicots and monocots shows coexpression with lignin biosynthetic genes. Cell-specific expression analysis of the inflorescence stem, a tissue that undergoes intense lignification to provide plant structural support, shows that AtPMT4 is expressed higher in cell types that lignify. We demonstrate that Arabidopsis Col-0 plants transformed with a CRISPR-Cas9 construct targeted near the TSS of AtPMT4, a member of the POLYOL/ MONOSACCHARIDE TRANSPORTER family, which is a subfamily of the MONOSACCHARIDE TRANSPORTER-LIKE family, displayed altered lignin phenotypes. We quantified the total lignin, free monomer subunits, and digestibility of the inflorescence stem in pmt4. Our studies show lower amounts of lignin and increased digestibility when AtPMT4 is mutated. Further, we show that pmt4 is sensitive to monolignols when grown in the presence of coniferyl alcohol. pmt4 displayed shorter root length compared to Col-0 at low concentrations of coniferyl alcohol. In conclusion, we provide evidence for an understanding of monolignol translocation and lignification by which transporters are likely involved in a proton-coupled manner.
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Title: THE NUCLEO-CYTOPLASMIC FUNCTION OF ACTIN AND ACTIN DEPOLYMERIZATION FACTORS IN PLANT IMMUNITY
Creator: Li, Pai
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The plant immune system is a multi-phase complex network that involves the collaboration of multiple subcellular structures. In the past two decades, the core signaling pathways of the immune process, including pattern-triggered immunity (PTI), effector-triggered immunity (ETI), and systemic acquired resistance (SAR), as well as the behavior of organelles, have been revealed to a level of clarity that is able to describe a general and well-covered process of the immune response. However,...
Show moreThe plant immune system is a multi-phase complex network that involves the collaboration of multiple subcellular structures. In the past two decades, the core signaling pathways of the immune process, including pattern-triggered immunity (PTI), effector-triggered immunity (ETI), and systemic acquired resistance (SAR), as well as the behavior of organelles, have been revealed to a level of clarity that is able to describe a general and well-covered process of the immune response. However, there are still many events during the immune response that remain mysterious. For instance, while higher plants live a sessile lifestyle, there are countless intracellular motions mediated by the cytoskeleton (including its associated proteins) in response to the external triggers, such as the invasion of pathogens. As our knowledge of plant immunity accumulates, the deficiency in knowledge on how immune signaling regulates the behavior of the cytoskeleton as a critical aspect of defense response, howbeit, becomes more evident. Therefore, this is a field of research that calls for powerful toolboxes to facilitate the analysis of the cytoskeleton in the context of immunity, as well as instructive biological model(s) that guide the direction of the multifarious studies. In this dissertation, I focus on the summary and prospective discussion on the immune function of the actin cytoskeleton and, more importantly, describe my original studies on two major aspects of this topic. First, a prerequisite to functional study of the actin cytoskeleton in the cytoplasm is the ability to accurately describe the status of the cytoskeleton. To achieve this goal, I developed an algorithm, namely implicit Laplacian of enhanced edge (ILEE), to accurately identify and analyze the biological status of the cytoskeleton from confocal image samples. This method significantly improves the accuracy, stability, and robustness of cytoskeleton segmentation, solves other technical hindrances, and enables abundant information to be extracted from images for biological interpretation (see Chapter 2). The ILEE algorithm will further help me to explore the phenotypes of actin architecture in response to immune signaling, which was not previously available due to the lack of the toolbox. Also, the ILEE has been packaged as a library released publicly to benefit the community with a powerful cytoskeleton analysis platform.For the second project of my total research, I focused on the immune function of the actin cytoskeleton in the nucleus. Previously, some Arabidopsis actin depolymerization factors were reported to genetically contribute to plant immunity by unknown mechanism(s), and my story began with a novel activity identified among Arabidopsis actin depolymerization factors – to interact with WRKYs, the stress-responsive transcription factors. During my research, I proved that certain ADFs can form a complex with WRKYs that binds to targeted promoters, hence regulating the activity of WRKYs and playing a positive role in the immune response. The knowledge obtained through this study, in combination with previous research (Lu et al., 2020; Porter et al., 2012a) of my lab, can be summarized into a biological model, in which ADF mediates a nuclear-cytoplasmic immune regulation that systemically facilitates both cytoskeleton dynamics and pro-immune transcriptome reprogramming. In general, this study reveals a novel yet general pattern of cytoskeleton mediated transcriptional regulation, as ADF and perhaps other components of the actin cytoskeleton can shuttle between the cytoplasm and nucleus to form a network with a higher level of complexity. As a potential broader impact, the application range of this model includes but is not necessarily limited to plant immunity.
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Title: Essays on the Economics of Education
Creator: Wood, William Jesse
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This dissertation provides three chapters on the economics of education. In the first chapter, I provide evidence that diversifying the labor supply of teachers to better reflect the racial distribution of students improves noncognitive outcomes for students of color without diminishing outcomes for White students. I use administrative data spanning 2007 to 2017 from the Los Angeles Unified School District, one of the most racially diverse school districts in the country, to measure the...
Show moreThis dissertation provides three chapters on the economics of education. In the first chapter, I provide evidence that diversifying the labor supply of teachers to better reflect the racial distribution of students improves noncognitive outcomes for students of color without diminishing outcomes for White students. I use administrative data spanning 2007 to 2017 from the Los Angeles Unified School District, one of the most racially diverse school districts in the country, to measure the effect of student-teacher race matching on various noncognitive and behavior outcomes: GPA, work habits, cooperation, grade retention, suspensions, absences, and a data generated noncognitive index. I mitigate the concern that race matches are endogenous by including school-grade and student fixed effects in a linear regression model. My findings indicate that students of color are expected to experience increases in GPA, work habits, and cooperation and see decreases in suspensions and absenteeism when matched with a teacher of the same race. I do not find statistically significant effects on White students' outcomes. Because noncognitive outcomes lead to higher high school graduation rates, college enrollment rates, and wages, such effects could lead to a tightening in the achievement and wage gap found between students of color and White students. This result can be achieved with an increase in institutional efforts to ensure teacher populations more closely reflect that of their students. The second chapter estimates the impact of race matched faculty (i.e., any teacher outside of a particular student’s classroom) on student test scores. While the student population rapidly diversifies, the teaching corps' diversification continues to lag behind. For example, the proportion of Latino student enrollment in public schools has increased from 11 to 27 percent in just the last two decades. In contrast, the share of Latino public school teachers during this same period has increased from 3 to only 9 percent (Pew Research Center, 2021). If the disparity between student and teacher racial distributions continues to grow, students of color may find it more difficult to benefit from direct student-teacher race matching. However, it may still be possible for students to benefit from same-race teachers even if they are not placed in the same classroom. Using administrative panel data between school years 2008-09 through 2017-18 from Los Angeles Unified School District, I estimate that Latino students see positive impacts of race matched faculty. By basing this study in an area with a large proportion of Latino students and teachers, we can fill a gap within the literature by examining the effects of race match and faculty race match on Latino students. The findings indicate that matching Latino students to racially congruent teachers and faculty can improve math and English Language Arts test scores. Increasing the supply of Latino teachers may provide a crucial catalyst in decreasing the achievement gaps found between Latino and white students. The final chapter continues along the lines of educational equity. The success of many students with disabilities (SWDs) depends on access to high-quality general education teachers. Yet, most teacher value-added measures (VAMs) fail to distinguish between a teacher’s effectiveness in educating students with and without disabilities. I create two VAMs: one focusing on teachers’ effectiveness in improving outcomes for SWDs, and one for non-SWDs. I find top-performing teachers for non-SWDs often have relatively lower VAMs for SWDs, and SWDs sort to teachers with lower scores in both VAMs. Overall, SWD-specific VAMs may be more suitable for identifying which teachers have a history of effectiveness with SWDs and could play a role in ensuring that students are being optimally assigned to these teachers.
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Title: SECOND LANGUAGE LEARNERS’ INDIVIDUAL DIFFERENCES AS A DYNAMIC SYSTEM : EVIDENCE FROM A RUSSIAN IMMERSION PROGRAM
Creator: Pastushenkov, Dmitrii
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Guided by Dynamic Systems Theory (DST) and multidimensional perspectives on individual differences (IDs) in instructed second language (L2) learning (e.g., Larsen-Freeman, 2014; Sun & Zhang, 2020), this longitudinal mixed-methods study focuses on three conceptually different categories of L2 learners’ IDs: working memory (WM), motivation, and the amount of L2 exposure. Despite previous propositions regarding cognitive, affective, and exposure-related IDs being interrelated (e.g., Pawlak, 2012...
Show moreGuided by Dynamic Systems Theory (DST) and multidimensional perspectives on individual differences (IDs) in instructed second language (L2) learning (e.g., Larsen-Freeman, 2014; Sun & Zhang, 2020), this longitudinal mixed-methods study focuses on three conceptually different categories of L2 learners’ IDs: working memory (WM), motivation, and the amount of L2 exposure. Despite previous propositions regarding cognitive, affective, and exposure-related IDs being interrelated (e.g., Pawlak, 2012), including WM and motivation (e.g., Serafini, 2017) and WM and the amount of L2 exposure (e.g., Denhovska et al., 2016), the longitudinal development of motivation and L2 exposure, as well as the effects of WM, motivation, and L2 exposure on learning gains in different skills and at different stages of L2 development have not yet been investigated. In this study, I aimed to address this gap and explore how L2 learners’ motivation and the amount of L2 exposure change over time and how WM, motivation, and the amount of L2 exposure affect learning gains in lexicogrammar, speaking, and writing at different initial proficiency levels. Considering that Second Language Acquisition (SLA) and Instructed SLA (ISLA) research are dominated by studies of more commonly taught languages, I also strove to promote the need for more ecologically valid research with Less Commonly Taught Languages (LCTLs) and investigated IDs in the instructed L2 learning of Russian. The participants were 52 students recruited from an eight-week Russian summer immersion program from four curricular levels (First-Year, Second-Year, Third-Year, and Fourth-Year Russian). The program was conducted online due to the COVID-19 pandemic. The results supported the view of L2 learners’ motivation and L2 exposure as constructs showing stable and dynamic patterns and that different constituents of WM, motivation, L2 Russian exposure, and learning gains were engaged in complex relationships that varied at different curricular levels, language skills, and phases of the study. This dissertation includes a discussion of theoretical implications with regards to DST and the mixed-methods approach as future directions for ISLA studies of IDs, including research with LCTLs. The dissertation also includes a section on practical implications that discusses pedagogical aspects and implications for the development of background questionnaires and placement testing.
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Title: Structural connectivity of an interoception network in schizophrenia
Creator: Yao, Beier
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Interoception refers to the processing, integration, and interpretation of bodily signals by the brain. Interoception is key to not only basic survival, but also many cognitive processes, especially motivational and affective functioning. There is emerging evidence suggesting altered interoception in schizophrenia, but its neural underpinning has not been examined. The current study aims to investigate the structural connectivity of a putative interoception network in schizophrenia, and its...
Show moreInteroception refers to the processing, integration, and interpretation of bodily signals by the brain. Interoception is key to not only basic survival, but also many cognitive processes, especially motivational and affective functioning. There is emerging evidence suggesting altered interoception in schizophrenia, but its neural underpinning has not been examined. The current study aims to investigate the structural connectivity of a putative interoception network in schizophrenia, and its relationship with affective functioning and clinical symptoms. Thirty-five participants with schizophrenia (SZ) and 36 healthy control participants (HC) underwent diffusion tensor imaging (DTI) and performed tasks measuring emotional functioning. Probabilistic tractography was used to identify white matter tracts connecting the key hubs forming the interoception network (i.e., rostral and caudal anterior cingulate cortex, ventral anterior insula, dorsal mid and posterior insula, and amygdala). Microstructural integrity of these tracts was compared across groups and correlated with measures of emotional functioning and symptom severity. I found that SZ exhibited altered structural connectivity in the putative interoception network, compared to HC. The structural connectivity of the network was correlated with emotion recognition in HC, supporting a link between the interoception network and emotional functioning. However, this correlation was much weaker in SZ, suggesting less reliance on this network. I did not find a correlation between the structural connectivity and clinical symptoms in SZ. These findings suggest that altered interoception may play a role in illness mechanisms of schizophrenia, especially in relation to emotional deficits.
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Title: Aspects of Computational Topology and Mathematical Virology
Creator: Wang, Rui
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Being able to describe the shape of data is of paramount importance to the fields of biology, physics, chemistry, pharmaceutics, etc. Therefore, in recent years, scientists from the TDA community have been applying advanced mathematical tools to decode the topological structures of data. Methods such as persistent homology, path homology, and de Rham-Hodge theory have become the main workhorse of TDA, which pioneered new branches in algebraic topology and differential geometry. Later, various...
Show moreBeing able to describe the shape of data is of paramount importance to the fields of biology, physics, chemistry, pharmaceutics, etc. Therefore, in recent years, scientists from the TDA community have been applying advanced mathematical tools to decode the topological structures of data. Methods such as persistent homology, path homology, and de Rham-Hodge theory have become the main workhorse of TDA, which pioneered new branches in algebraic topology and differential geometry. Later, various topological Laplacians such as graph Laplacian, Hodge Laplacian, sheaf Laplacian, and Dirac Laplacian are proposed to preserve topological invariants and geometric shapes simultaneously. However, such Laplacians fail to extract the topological and geometric deformations when one introduces the filtration parameters in. Therefore, we proposed a new topological Laplacians called persistent Laplacians to fully recover the topological persistence and homotopic shape evolution during filtration. It is worth mentioning that persistent Laplacians are insensitive to asymmetry or directed relations, which limits their power to preserve the directional information of structures in practical applications. Therefore, we proposed persistent path Laplacians to overcome this issue. Similar to the persistent Laplacians, one can also extract the topological persistence and geometric deformations during filtration from the persistent path Laplacians by calculating their harmonic and non-harmonic spectra. In addition, the persistent path Laplacians are constructed on the directed graphs or network, which address the importance of directional representation in datasets such as gene regulation datasets in biology. Versatile mathematical tools have been playing an essential role in various biological applications. Since the first COVID-19 case was reported in December 2019, researchers worldwide have been pursuing scientific endeavors in the SARS-CoV-2 projects. Instead of designing promising vaccines and antibody therapies that required wet lab resources, we proposed a new mathematical-AI model called TopNetmAb to systematically analyze the mutation-induced impacts on the SARS-CoV-2 infectivity, vaccines, and antibody drugs. In this dissertation, the topological data analysis (including the persistent Laplacians mentioned above), artificial intelligence, various network models, and genomics analysis are all included in our SARS-CoV-2-related projects to provide comprehensive representations for the understanding of the transmission and evolution of SARS-CoV-2.
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Title: Laboring for the motherland : A mother-artist-researcher-teacher's reconfiguration of the state-sponsored transnational teacher
Creator: Gordon, Rebekah R.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This arts-based inquiry explores historical and contemporary configurations of state-sponsored transnational teachers, or those who teach overseas in programs that are financially and/or programmatically supported by their home government. In the U.S., some examples of state-sponsored transnational teaching programs include the Peace Corps, the Fulbright Specialist Program, and the English Language Fellow Program. Standing on feminist grounding, I draw upon maternal concepts from the field of...
Show moreThis arts-based inquiry explores historical and contemporary configurations of state-sponsored transnational teachers, or those who teach overseas in programs that are financially and/or programmatically supported by their home government. In the U.S., some examples of state-sponsored transnational teaching programs include the Peace Corps, the Fulbright Specialist Program, and the English Language Fellow Program. Standing on feminist grounding, I draw upon maternal concepts from the field of mother(hood) studies to frame my exploration and to interrogate and disrupt the patriarchal systems in which state-sponsored transnational teaching is situated. More specifically, I extend a/r/tographic methodology to include my identifications and embodied perspectives as a mother-artist-researcher-teacher. My proposed methodology of m/a/r/tography affords me the opportunity to think intergenerationally about the ways that orientations, collective body memory, family histories, and national legacies relevant to state-sponsored transnational teaching are passed down. By using epistolary narrative and creative non-fiction, I reflect on my own experiences as a mother, as a daughter, and as a former state-sponsored transnational teacher who labored for her motherland. To analyze these personal experiences, I adopt a diffractive approach in which these experiences are viewed through one another as well as through additional sources of data, including interviews with other state-sponsored transnational teachers, letters from my mother, photographs and images, poetry, film, children’s literature, and other forms of scholarship. The use of a diverse and wide-ranging set of scholarship is an attempt to not only spark creative connections between seemingly disparate sources of data but also inspire more accessible and humanizing ways of doing research and re-imagining (teacher) education that welcomes processes of re/dis/orientation.
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Title: Sex and Individual Differences in Agonistic Behavior of Spotted Hyenas (Crocuta Crocuta) : Effects on Fitness and Dominance
Creator: McCormick, S. Kevin
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Agonistic behavior can be observed across all taxa arising from a common need to compete over limiting resources. Within species, individual variation of agonistic behavior can allow individuals to acquire and maintain limiting resources leading to higher reproductive success or fitness. However, what is often overlooked in studies of agonistic behavior is submissiveness, and how this aspect of agonistic behavior relates to aggressiveness. Further, historical studies of agonistic behavior...
Show moreAgonistic behavior can be observed across all taxa arising from a common need to compete over limiting resources. Within species, individual variation of agonistic behavior can allow individuals to acquire and maintain limiting resources leading to higher reproductive success or fitness. However, what is often overlooked in studies of agonistic behavior is submissiveness, and how this aspect of agonistic behavior relates to aggressiveness. Further, historical studies of agonistic behavior among social mammals are biased towards studies of male agonistic behavior, often ignoring aspects and effects of female agonistic behavior. Here, I address these knowledge gaps through a long-term study of a free living highly gregarious mammal, the spotted hyena (Crocuta crocuta). Spotted hyenas offer an excellent model system for studying variation in aggressive and submissive behavior within individuals and between sexes, as they live in complex societies formed around a female dominated, or matrilineal, hierarchy that is enforced through constant agonistic interactions. For this dissertation, I utilized 30 years’ worth of consistently recorded behavioral data collected by Dr. Kay E. Holekamp and her team from free living hyenas residing within the Masai Mara National Reserve, Keyna. Because this dissertation involved many collaborations with other scientists, I use “we” throughout this abstract to describe participation in each chapter. In Chapter 1, we describe sexually dimorphic traits within spotted hyenas that fit common mammalian patterns, as well as numerous traits that violate mammalian norms, including sex differences in agonistic behavior. In particular, adult female spotted hyenas are significantly more likely to emit unsolicited acts of aggression down the hierarchy than adult breeding males, and females do so significantly more ferociously, or intensely. For Chapter 2, we analyzed rates and intensities of unprovoked aggressive and submissive acts emitted by adult females to determine if these two behaviors were individually consistent, as well as testing the hypothesis that these two behaviors may represent separate traits within individuals. Here we found that the intensity at which females emit aggressive and submissive behaviors are consistent, and that these traits were not correlated within individuals. Further, both consistent aggressive intensity and submissive intensity were correlated to adult female fitness, such that individuals expressing high or low extremes of these behaviors had lower annual offspring survival. Then in Chapter 3, we assessed drivers of female dominance within spotted hyenas. Within this chapter we tested two hypotheses 1) that intrinsic sex differences in agonistic behavior drives female dominance and/or 2) social support facilitates female dominance in this species. Further, we assessed these hypotheses among juvenile age classes to determine if drivers of female dominance occurred prior to sexual maturity and subsequent male dispersal. We found that females are intrinsically more aggressive both as cubs and adults, and adult males more submissive whether provoked or not. Further, social support during agonistic encounters is more likely to occur when acting against a female than a male, and adult females can dominate males with or without support. In completion, my dissertation provides interesting insights to sexual and individual variation on agonistic behavior among a social mammal.
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Title: LEAN IN : THE ANTECEDENTS AND CONSEQUENCES OF FEMALE DIRECTORS’ ATTAINMENT OF POWERFUL POSITIONS ON BOARDS
Creator: Kim, Jooyoung
Date: 2022
Collection: Electronic Theses & Dissertations
Description: With the heightened societal demand for promoting egalitarian values in corporate boards, firms have devoted much effort to improving female board representation. However, recent insights have suggested that some progress made thus far may be the result of firms’ symbolic conformity to external pressure, which alludes to the possibility that female directors’ low influence and lack of integration on boards may still persist. In this dissertation, I aim to develop and test theoretical...
Show moreWith the heightened societal demand for promoting egalitarian values in corporate boards, firms have devoted much effort to improving female board representation. However, recent insights have suggested that some progress made thus far may be the result of firms’ symbolic conformity to external pressure, which alludes to the possibility that female directors’ low influence and lack of integration on boards may still persist. In this dissertation, I aim to develop and test theoretical arguments of what determines and follows female directors’ attainment of power and influence, as reflected in their assignment to major committee member or chair positions. First, I propose that female directors are at a relative disadvantage in attaining major committee positions. Specifically, although directors in general can benefit from expertise cues to be assigned to committee positions, the benefits are less for females than males. This gap can be attenuated when females are similar to board members in terms of other demographic dimensions and when the board is demographically heterogeneous. Second, I develop predictions about how female representation on board committee positions can contribute to gender diversity on boards and firm performance. I propose that greater female representation on board committees has negative relationship with a female director’s likelihood of exit, and has positive relationship with female additions to the board and firm performance. Results were drawn from a sample of S&P 1,500 companies during 2009 to 2019.
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Title: Role of circular exercise on forelimb loading and accompanying skeletal and joint adaptations
Creator: Logan, Alyssa A.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Circular exercise is used frequently in equine exercise and competition, but little is known of the impact circular diameter and gait have to the joint and bone health of the forelimb. The first study evaluated the impact of circle diameter (10-m and 15-m) and gait to the forelimb solar outputs of average surface area, vertical force, and average pressure. Nine horses exercised in a straight line and in a round pen while wearing the Tekscan Hoof SystemTM on both front hooves with a glue-on...
Show moreCircular exercise is used frequently in equine exercise and competition, but little is known of the impact circular diameter and gait have to the joint and bone health of the forelimb. The first study evaluated the impact of circle diameter (10-m and 15-m) and gait to the forelimb solar outputs of average surface area, vertical force, and average pressure. Nine horses exercised in a straight line and in a round pen while wearing the Tekscan Hoof SystemTM on both front hooves with a glue-on shoe, a method of adherence which was determined to be reliable when measurements were recorded within one session. Gait, and not circle diameter, impacted forelimb outputs, with the average loaded area of the outside hoof while circling, being greatest at the canter (P = 0.001). While exercising on both a large and small circle, the outside hoof had greater vertical force at the canter than the trot (P = 0.01). A second study utilizing calves as a model for juvenile horses allowed the determination of physiological responses to circular exercise. Calves were assigned to small circle exercise (12 m), large circle exercise (18 m), treadmill exercise, or non-exercised control treatments (n = 6). Computed tomography and biomarkers were evaluated to determine impacts to bone and joint health. The inside leg of the small circular exercise group had larger dorsopalmar external diameter than the outside (P = 0.05). The medial proximal phalanx had greater mediolateral diameter than the lateral proximal phalanx of the small circle group (P = 0.01). Cartilage glycosaminoglycan concentration was greater in the outside leg of the small circle exercise treatment than the inside leg (P = 0.03). Combined, both of these studies suggest that circular exercise diameter and gait can impact animal health and should be considered when performing circular exercise.
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Title: Causal Inference with Mendelian Randomization for Longitudinal Data
Creator: Qu, Jialin
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Mendelian Randomization (MR) uses genetic variants as instrumental variables (IVs) to examinethe causal relationship between an exposure and an outcome in observational studies. When confounding factors exist, the correlation between a predictor variable and an outcome variable does not imply causation. IV regression has been a popular method to control the confounding effect for causal inference. According to Mendel’s first and second laws of inheritance, genetic variants can be considered...
Show moreMendelian Randomization (MR) uses genetic variants as instrumental variables (IVs) to examinethe causal relationship between an exposure and an outcome in observational studies. When confounding factors exist, the correlation between a predictor variable and an outcome variable does not imply causation. IV regression has been a popular method to control the confounding effect for causal inference. According to Mendel’s first and second laws of inheritance, genetic variants can be considered as valid IVs. Popular MR methods include the ratio estimator, the inverse-variance weighted estimator and the two stage estimator. However, all these methods are based on cross-sectional data. In practice, data in the observational studies can be collected over time, the so-called longitudinal data. Longitudinal data makes it possible to capture changes within subjects over time and thus offers advantages to causal modeling to establish causal relationships. However, causal inference method that can control the time-varying confounding effect is largely lacking in literature. In this dissertation, we explore MR analysis for longitudinal data by proposing different causal models and assuming different casual mechanisms. The proposed methods are strongly motivated by a real study to examine the causal relationship between hormone secretion and emotional eating disorder in teen girls. We start with a concurrent model which assumes current outcome is only affected by current exposure. Coefficients of both genetic variants (i.e., IVs) and exposure are considered as time- varying effects. We apply the quadratic inference function approach in a two-step IV regression framework and focus on statistical testing to infer causality. Through extensive simulation studies, we show that the proposed method can well protect type I error and has reasonable testing power. In Chapter 3, we generalize the concurrent model to a more complex case and propose a time lag model to investigate time delayed causal effects. In the time lag model, we assume current outcome at time ? is affected by previous exposures measured up to ? − ? time points, where the time lag △? can be determined by a rigorous model selection procedure based on data. Similar to the concurrent model, we assume the effects of genetic variants on exposure and the effects of exposure on outcome both are time-varying. We propose different tests for point-wise and simultaneous testing to assess the causal relationship. In Chapter 4, We further generalize the time lag model to the case where the cumulative effect of previous ? exposures contributes to the outcome at time ?, under a sparse functional data analysis framework. The causal relationship is examined under the functional principal component regression framework with sparse functional data. Simulation results show that the type I error is well controlled. We apply our models to the emotional eating disorder data to examine if hormone secretion during the menstrual cycle in teen girls has a causal effect on emotional eating behavior and identify interesting results. This thesis work represents the very first exploration in MR analysis with longitudinal data.
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Title: PHENYLENEDIAMINE PYRIDYL LIGANDS AND BORYL SUPPORT LIGANDS FOR ORTHO-DIRECTED IRIDIUM CATALYZED C–H BORYLATION
Creator: O'Connell, Alex C.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: With organoboron compounds being useful components in the synthesis of pharmaceuticals, agrochemicals, and materials, it is imperative to find new catalytic strategies to design an effective system capable of borylating a broad range of (hetero)arene substrates in high yields and high selectivity. Traditional iridium-catalyzed systems borylate aromatic compounds and are directed by steric factors of the substrate. These steric-directed catalysts are hypothesized to have a singly open...
Show moreWith organoboron compounds being useful components in the synthesis of pharmaceuticals, agrochemicals, and materials, it is imperative to find new catalytic strategies to design an effective system capable of borylating a broad range of (hetero)arene substrates in high yields and high selectivity. Traditional iridium-catalyzed systems borylate aromatic compounds and are directed by steric factors of the substrate. These steric-directed catalysts are hypothesized to have a singly open coordination site on the metal center where activation of the most accessible C–H bond can occur. In order to change regioselectivity from steric products to alternatives, new catalyst systems must be designed.A phenylenediamine pyridyl framework was implemented for chelate-directed C–H borylation, where an aromatic substrate undergoes borylation of the ortho C–H bond, relative to a directing group. This ligand type has been explored and shown to have three major components that influence the reactivity, selectivity, and coordination of the ligand. These parts that make up the ligand were examined using a ligand screen, NMR studies, and stoichiometric reactions. From the literature, it has been shown that double B,N-bidentate ligated catalysts work well for a broad substrate scope and produce borylated products whose substitution pattern is based on steric effects. Other variants of this system have used a single B,N-bidentate ligand to produce products borylated in the ortho-position relative to a directing group on the substrate. To improve upon these catalytic systems, experiments were performed to optimize ortho-selectivity of the originally steric-directed catalyst containing two B,N-bidentate ligands by reducing the loading of the dimer boryl ligand. In doing so, regioselectivities can be completely switched from steric products to chelate products. This modification of ligand to metal ratio greatly effects selectivity and is a unique feature to dimer boryl ligands. These phenylenediamine pyridyl ligands and boryl support ligands will be explored.
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Title: Efficient Transfer Learning for Heterogeneous Machine Learning Domains
Creator: Zhu, Zhuangdi
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Recent advances in deep machine learning hinge on a large amount of labeled data. Such heavy dependence on supervision data impedes the broader application of deep learning in more practical scenarios, where data annotation and labeling can be expensive (e.g. high-frequency trading) or even dangerous (e.g. training autonomous-driving models.) Transfer Learning (TL), equivalently referred to as knowledge transfer, is an effective strategy to confront such challenges. TL, by its definition,...
Show moreRecent advances in deep machine learning hinge on a large amount of labeled data. Such heavy dependence on supervision data impedes the broader application of deep learning in more practical scenarios, where data annotation and labeling can be expensive (e.g. high-frequency trading) or even dangerous (e.g. training autonomous-driving models.) Transfer Learning (TL), equivalently referred to as knowledge transfer, is an effective strategy to confront such challenges. TL, by its definition, distills the external knowledge from relevant domains into the target learning domain, hence requiring fewer supervision resources than learning-from-scratch. TL is beneficial for learning tasks for which the supervision data is limited or even unavailable. It is also an essential property to realize Generalized Artificial Intelligence. In this thesis, we propose sample-efficient TL approaches using limited, sometimes unreliable resources. We take a deep look into the setting of Reinforcement Learning (RL) and Supervised Learning, and derive solutions for the two domains respectively. Especially, for RL, we focus on a problem setting called imitation learning, where the supervision from the environment is either non-available or scarcely provided, and the learning agent must transfer knowledge from exterior resources, such as demonstration examples of a previously trained expert, to learn a good policy. For supervised learning, we consider a distributed machine learning scheme called Federated Learning (FL), which is a more challenging scenario than traditional machine learning, since the training data is distributed and non-sharable during the learning process. Under this distributed setting, it is imperative to enable TL among distributed learning clients to reach a satisfiable generalization performance. We prove by both theoretical support and extensive experiments that our proposed algorithms can facilitate the machine learning process with knowledge transfer to achieve higher asymptotic performance, in a principled and more efficient manner than the prior arts.
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Title: MACHINE LEARNING TOWARDS DATA WITH COMPLEX STRUCTURES
Creator: Su, Runze
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The development of sequential analysis provides a deeper understanding in the exploration of many different fields. In the application of sequential analysis, there are two main challenges: How to extract informative features from a high-dimensional noisy domain? How to model the interaction for the information flow from multiple domains? We explored the two core challenges in bio-informatics, sales forecasting and multimedia services. In biology field, a typical problem is the to evaluate...
Show moreThe development of sequential analysis provides a deeper understanding in the exploration of many different fields. In the application of sequential analysis, there are two main challenges: How to extract informative features from a high-dimensional noisy domain? How to model the interaction for the information flow from multiple domains? We explored the two core challenges in bio-informatics, sales forecasting and multimedia services. In biology field, a typical problem is the to evaluate the interaction mechanism between non-coding DNA sequences and transcription. We propose CANEE, a convolutional self-attention architecture to analyze the function of non-coding DNA sequences. Compared to other existing models, CANEE achieves a better performance in overall prediction of 919 regulatory functions with respect to receiver operating characteristics and has a significant improvement on some responses in precision recall curve with shorter training time. In sales forecasting field, we extract a unique customers’ microbehavior dependency structure from clickstream data based on a Word-to-Vector model. Then, we build a clickstream informed LSTM model to forecast the car sales over 30 days. Our model significantly outperforms the classic seasonal autoregressive integrated moving average model. Besides, we demonstrate that transfer knowledge among different car models can further improve the performance. Other applications for multi-domain sequences happens in multimedia service field, where we focus on the understanding of multiple domain modalities, we propose new principles for audio visual learning and introduce a new framework as well as its training algorithm to set sight of videos’ themes to facilitate AVC learning.
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Title: EMOTIONALLY FOCUSED THERAPY FOR COUPLES IN TAIWAN
Creator: Tseng, Chi-Fang
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This is the first study to begin to explore the effectiveness and predictors of change of emotionally focused therapy for relationship satisfaction and depressive symptoms among couples in Taiwan. This one-arm pragmatic trial assessed the clinical outcomes of 17 couples using paired-samples t-tests and multilevel modeling. Paired-sample t-tests revealed no statistical differences in relationship satisfaction and depressive symptoms before and after EFT. Additionally, multilevel modeling...
Show moreThis is the first study to begin to explore the effectiveness and predictors of change of emotionally focused therapy for relationship satisfaction and depressive symptoms among couples in Taiwan. This one-arm pragmatic trial assessed the clinical outcomes of 17 couples using paired-samples t-tests and multilevel modeling. Paired-sample t-tests revealed no statistical differences in relationship satisfaction and depressive symptoms before and after EFT. Additionally, multilevel modeling indicated no change in relationship satisfaction over time. However, there was a quadratic change in depressive symptoms over the course of EFT. While the study results were unexpected, it is important to note that most couples did not receive the recommended treatment “dose” in this pragmatic trial. In addition, the small sample size limited statistical power. In addition to assessing treatment outcomes, predictors of change were also examined. Findings showed that high traditionalism at intake predicted an increase in relationship satisfaction for women. Attachment was also a significant predictor of change; men with high attachment avoidance at intake demonstrated a significant decrease in depression, and men and women with high attachment anxiety at intake also experienced a significant decrease in depression. Lastly, emotional expressivity at intake was associated with an increase in relationship satisfaction and a decrease in depression for both men and women. Our study suggested that traditionalism, attachment, and emotional expressivity are important predictors of change among couples in Taiwan who receive EFT. While more research is needed, these findings offer preliminary support for the types of partners who may be more likely to experience change after receiving EFT.
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