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Title: Detecting and Mitigating Bias in Natural Languages
Creator: Liu, Haochen
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Natural language processing (NLP) is an increasingly prominent subfield of artificial intelligence (AI). NLP techniques enable intelligent machines to understand and analyze natural languages and make it possible for humans and machines to communicate through natural languages. However, more and more evidence indicates that NLP applications show human-like discriminatory bias or make unfair decisions. As NLP algorithms play an increasingly irreplaceable role in promoting the automation of...
Show moreNatural language processing (NLP) is an increasingly prominent subfield of artificial intelligence (AI). NLP techniques enable intelligent machines to understand and analyze natural languages and make it possible for humans and machines to communicate through natural languages. However, more and more evidence indicates that NLP applications show human-like discriminatory bias or make unfair decisions. As NLP algorithms play an increasingly irreplaceable role in promoting the automation of people's lives, bias in NLP is closely related to users' vital interests and demands considerable attention.While there are a growing number of studies related to bias in natural languages, the research on this topic is far from complete. In this thesis, we propose several studies to fill up the gaps in the area of bias in NLP in terms of three perspectives. First, existing studies are mainly confined to traditional and relatively mature NLP tasks, but for certain newly emerging tasks such as dialogue generation, the research on how to define, detect, and mitigate the bias in them is still absent. We conduct pioneering studies on bias in dialogue models to answer these questions. Second, previous studies basically focus on explicit bias in NLP algorithms but overlook implicit bias. We investigate the implicit bias in text classification tasks in our studies, where we propose novel methods to detect, explain, and mitigate the implicit bias. Third, existing research on bias in NLP focuses more on in-processing and post-processing bias mitigation strategies, but rarely considers how to avoid bias being produced in the generation process of the training data, especially in the data annotation phase. To this end, we investigate annotator bias in crowdsourced data for NLP tasks and its group effect. We verify the existence of annotator group bias, develop a novel probabilistic graphical framework to capture it, and propose an algorithm to eliminate its negative impact on NLP model learning.
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Title: Computational methods to investigate connectivity in evolvable systems
Creator: Ackles, Acacia Lee
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Evolution sheds light on all of biology, and evolutionary dynamics underlie some of the most pressing issues we face today. If we can deepen our understanding of evolution, we can better respond to these various challenges. However, studying such processes directly can be difficult; biological data is naturally messy, easily confounded, and often limited. Fortunately, we can use computational modeling to help simplify and systematically untangle complex evolutionary processes. The aim of this...
Show moreEvolution sheds light on all of biology, and evolutionary dynamics underlie some of the most pressing issues we face today. If we can deepen our understanding of evolution, we can better respond to these various challenges. However, studying such processes directly can be difficult; biological data is naturally messy, easily confounded, and often limited. Fortunately, we can use computational modeling to help simplify and systematically untangle complex evolutionary processes. The aim of this dissertation is therefore to develop innovative computational frameworks to describe, quantify, and build intuition about evolutionary phenomena, with a focus on connectivity within evolvable systems. Here I introduce three such computational frameworks which address the importance of connectivity in systems across scales.First, I introduce rank epistasis, a model of epistasis that does not rely on baseline assumptions of genetic interactions. Rank epistasis borrows rank-based comparison testing from parametric statistics to quantify mutational landscapes around a target locus and identify how much that landscape is perturbed by mutation at that locus. This model is able to correctly identify lack of epistasis where existing models fail, thereby providing better insight into connectivity at the genome level.Next, I describe the comparative hybrid method, an approach to piecewise study of complex phenotypes. This model creates hybridized structures of well-known cognitive substrates in order to address what facilitates the evolution of learning. The comparative hybrid model allowed us to identify both connectivity and discretization as important components to the evolution of cognition, as well as demonstrate how both these components interact in different cognitive structures. This approach highlights the importance of recognizing connected components at the level of the phenotype.Finally, I provide an engineering point of view for Tessevolve, a virtual reality enabled system for viewing fitness landscapes in multiple dimensions. While traditional methods have only allowed for 2D visualization, Tessevolve allows the user to view fitness landscapes scaled across 2D, 3D, and 4D. Visualizing these landscapes in multiple dimensions in an intuitive VR-based system allowed us to identify how landscape traversal changes as dimensions increase, demonstrating the way that connections between points across fitness landscapes are affected by dimensionality. As a whole, this dissertation looks at connectivity in computational structures across a broad range of biological scales. These methods and metrics therefore expand our computational toolkit for studying evolution in multiple systems of interest: genotypic, phenotypic, and at the whole landscape level.
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Title: ENGINEERING B. SUBTILIS TRANSCRIPTIONAL CONTROL AND PHYSIOLOGY FOR THE ADVANCEMENT OF BACTERIOTHERAPIES
Creator: Greeson, Emily Marilynn
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This dissertation explores to avenues of improvement for current bacteriotherapy approaches. Cody Madsen and I worked closely to advance engineered B. subtilis as a modular platform technology and Dr. Ashley Makela was instrumental in the in vivo studies (Chapter 2). In Chapter 2, transcriptional control of B. subtilis will demonstrate the ability to use magnetothermal energy generated by superparamagnetic iron oxide nanoparticles (SPIONs) and alternating magnetic fields (AMF) to induce...
Show moreThis dissertation explores to avenues of improvement for current bacteriotherapy approaches. Cody Madsen and I worked closely to advance engineered B. subtilis as a modular platform technology and Dr. Ashley Makela was instrumental in the in vivo studies (Chapter 2). In Chapter 2, transcriptional control of B. subtilis will demonstrate the ability to use magnetothermal energy generated by superparamagnetic iron oxide nanoparticles (SPIONs) and alternating magnetic fields (AMF) to induce temperature-sensitive repressors. Chapter 3 demonstrates how synthetic biology techniques can allow engineered B. subtilis to invade epithelial cells with the “zipper” mechanism. This was a collaborative effort as it was a multidisciplinary study and the contributions of Cody Madsen, Evran Ural, Dr. Ashley Makela, Dr. Bige Unluturk, and Victoria Toomajian were important and have been specifically noted in author contributions at the end of Chapter 3.Most patients on organ transplant waitlists will need alternative therapeutics due to a deficit of organ donations. Regenerative medicine approaches, including cellular reprogramming are being used to help address the deficit, but there are limitations. Bacteriotherapies aim to better deliver the therapeutics to a variety of targets, however, most approaches do so externally to the target cells. B. subtilis, a generally recognized as safe organism, engineered to express listeriolysin O (LLO) has been shown to replicate in the cytoplasm of macrophages and deliver transcription factors and modulate cell surface markers, cytokines, and chemokines. This mechanism of uptake only works with phagocytic cells creating an opportunity for the engineering of B. subtilis that targets internalization into non-phagocytic cells. When introducing known virulence factors into non-native organisms it is important to consider controlling the gene expression while trying to remain as minimally invasive as possible. Alternating magnetic fields (AMF) cause local temperature increases in regions with Superparamagnetic iron oxide nanoparticles (SPIONs), and we investigated the ability of this magnetic hyperthermia approach to regulate temperature-sensitive repressors (TSRs) in bacteria. Magnetic hyperthermia-based control of bacterial gene expression would advance development of bacteriotherapies and expand options of regulated bacterial transcription. TSRs block transcription in a temperature-dependent manner. B. subtilis was coated with three SPION variations, plain-dextran, amine- or carboxyl-coated and the interactions and AMF responses were characterized and induction of the TSRs was demonstrated using AMF. Murine intramuscular injections revealed continual association of SPIONs with B. subtilis. While there was no induction via AMF in vivo, pairing TSRs with magnetothermal energy using SPIONs for localized heating with AMF can lead to regional bacterial transcriptional control, a minimally invasive method that could be used with virulence factors and therapeutics. To delivery therapeutics to epithelial cells, B. subtilis llo was engineered to express internalin A (InlA), a protein native to Listeria monocytogenes. Internalin A is an adhesin that binds to the E-cadherin host cell receptor found in epithelial cells and mediates a “zipper” mechanism of invasion. B. subtilis llo inlA demonstrated cytosolic persistence and B. subtilis llo remained extracellular. Ultimately, the engineering of B. subtilis transcriptional control and physiology creates a new modular approach to regenerative medicine, cellular reprogramming, and cancer therapy that can be used in human health applications.
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Title: Development and Assessment of Predictive Models for Improved Swine Farming
Creator: Han, Junjie
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Prediction of outcomes is critical in both swine breeding and management. This necessitates the development of predictive models that address challenges in swine farming. For predictive modeling, there have been significant advances in deep learning. Nevertheless, there are needs to adapt deep learning-based models for specific swine farming problems including genomic prediction and behavior analysis. Furthermore, there is not yet a clear guideline on how to validate a model in this field....
Show morePrediction of outcomes is critical in both swine breeding and management. This necessitates the development of predictive models that address challenges in swine farming. For predictive modeling, there have been significant advances in deep learning. Nevertheless, there are needs to adapt deep learning-based models for specific swine farming problems including genomic prediction and behavior analysis. Furthermore, there is not yet a clear guideline on how to validate a model in this field. The overarching goal of this dissertation was to validate a collection of predictive models for improved swine farming with applications to precision management, phenotyping, and breeding. The first study addressed the pig genomic prediction problem. Differential evolution was utilized to optimize deep learning (DL) hyperparameters that affected the predictive performance of DL models. Performance of optimized DL was compared with “best practice” DL architectures selected from literature and baseline DL models with randomly specified hyperparameters. Optimized models showed clear improvement. Further, differential evolution saved considerable time compared to traditional optimization approaches e.g., grid search. Despite the success of genomic prediction, phenotyping has become a bottleneck in breeding programs as it is still time-consuming and labor-intensive. Computer vision (CV) can be used to automate the phenotyping process. Nonetheless, there are limited amount of public data for CV development in livestock farming. Most published CV applications to livestock farming were developed using rather small datasets, and their broader validity remained unknown. Therefore, the second study aimed at reviewing publicly available image datasets that were used for CV algorithms in livestock farming and the validation methods in the related work. Through the review, we could not find public datasets that addressed pigs’ agonistic behaviors (negative social behaviors), which is an important topic in swine farming. Given this, the third study aimed at collecting a video dataset to study pig’s agonistic behavior and adapting a state-of-the-art DL pipeline to classify pigs’ agonistic behaviors through video analysis. The pipeline was validated through various training-validation data partitions, where the training data were used for model development and the validation data were used for model evaluation. Results showed that splitting the training and validation sets at random led to over-optimistic estimates of model performance. The last study focused on developing and validating a statistical model for the analysis of pigs’ social interactions. Generalized linear mixed models were fitted, and a Bayesian framework was used for parameter estimation and posterior predictive model checking. The predictive performance of the models varied depending on the validation strategy, where three strategies were defined: random cross-validation, block-by-social-group cross-validation, and block-by-focal-animals validation. In conclusion, this dissertation provides information about how state-of-the-art models can be adapted for and validated in swine farming applications. Future directions of this research could aim at creating reference imagery datasets in swine farming that provides a platform for CV applications and developing integrated computer vision systems, which eventually assists in prediction tasks for improved pig management and breeding.
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Title: Assuming Ambiguity
Creator: Conklin, Rebecca C.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This dissertation considers ambiguity throughout the history of Rhetoric and Composition, a discipline generally concerned with clarity, concision, and correctness as key attributes of “good” writing. In the first part of this dissertation, I draw from the theoretical contributions made by Simone de Beauvoir in The Ethics of Ambiguity (1947) and show how the central tensions she wrestled with in that text mirror the tensions experienced at the dawn of this discipline, tensions that have (re...
Show moreThis dissertation considers ambiguity throughout the history of Rhetoric and Composition, a discipline generally concerned with clarity, concision, and correctness as key attributes of “good” writing. In the first part of this dissertation, I draw from the theoretical contributions made by Simone de Beauvoir in The Ethics of Ambiguity (1947) and show how the central tensions she wrestled with in that text mirror the tensions experienced at the dawn of this discipline, tensions that have (re)emerged throughout subsequent decades. I trace the disciplinary conversations in the decades following World War II, as Rhetoric and Composition sought to define itself and its space in increasingly neoliberal, corporate college and university structures. Summarizing field conversations around the problems of relevance, content/standards, teachers and students, and assessment, I show how the gap between disciplinary knowledge/best practices bumps up against the demands of a profit-driven university. This project offers another way of thinking and doing through a praxis of ambiguity, explored and articulated through five guiding verbs: imagine, emerge, expand, intuit, and situate. Through these guiding verbs, I explore how these verbs and the scholarship that supports them may offer ways to intentionally disrupt the presence of white supremacy culture in teaching, research, and administration in the discipline by making visible the characteristics of this culture and sketching the outlines of an interventional framework based on a praxis of ambiguity, offering avenues for future research.
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Title: Adaptation to agriculture in a serious crop weed, weedy radish (raphanus raphanistrum)
Creator: Garrison, Ava
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The colonization of novel environments requires organisms to shift their trait means in response to differing abiotic and biotic conditions in order to survive and persist. This response can be done via phenotypic plasticity (a trait shift in response to the environment), adaptation (a trait shift due to genetic change), or both strategies can be used together, with plasticity “buying time” for adaptation to occur. The colonization of novel environments is especially important to the...
Show moreThe colonization of novel environments requires organisms to shift their trait means in response to differing abiotic and biotic conditions in order to survive and persist. This response can be done via phenotypic plasticity (a trait shift in response to the environment), adaptation (a trait shift due to genetic change), or both strategies can be used together, with plasticity “buying time” for adaptation to occur. The colonization of novel environments is especially important to the establishment of agricultural weeds worldwide, which thrive in these extreme environments of intense competition and frequent disturbance. In this dissertation, I address the establishment and evolution of a harmful agricultural weed, weedy radish (Raphanus raphanistrum), as well as its divergence from a wild relative of the same species, the native radish ecotype. I first investigated the hypothesis of phenotypic plasticity “buying time” for adaptation to agricultural fields in weedy radish. Using growth chambers to simulate the ancestral (native) and derived (weedy) environments of weedy radish, I performed a reciprocal transplant with the weedy and native radish ecotypes. I found phenotypic plasticity between environments and genetic divergence between ecotypes to be equally common among traits, suggesting similar importance of plasticity and adaptation in weedy radish establishment. Further, in the majority of traits that were both plastic and differentiated between ecotypes, the direction of change matched, with the weedy environment producing phenotypic shifts in the direction of the weedy ecotype mean. This suggests plasticity in these traits may have enabled the subsequent adaptation and ecotype differentiation, supporting the buying-time hypothesis. Next, I explored the role of the plant hormone Gibberellic Acid (GA) in the evolution of weedy radish. Using exogenous application of GA both in the greenhouse and in weedy and native growth chamber environments, I found evidence that there has been an evolutionary change in the role of GA in trait expression between the two ecotypes. Namely, weedy radish is less responsive to GA application than native radish, suggesting either upregulation in GA production in weeds, or a lower level of GA required to enable gene expression in the weedy ecotype. This change in gene regulation by GA may have been important in the evolution of weedy radish in the agricultural field. Finally, I assessed the likelihood of weedy radish diverging from a native ancestor via adaptive evolution. I found that adaptive evolution was likely in the establishment of weedy radish due to increased fitness of the weedy ecotype compared to the native ecotype in the agricultural field. I also found traits under directional selection in the native ecotype, with the key takeaway that faster flowering is adaptive in the agricultural fields. I finally looked at the ability of weedy radish to evolve advanced flowering in the agricultural field via standing genetic variance by artificially selecting for early flowering in native radish. I found that in only two generations of selection, native populations significantly advanced their flowering time, supporting the notion of weedy radish rapidly adapting to agricultural conditions via standing genetic variation alone. Taken together, these findings work to piece together the evolutionary history of weedy radish, providing insight into its mechanisms of establishment. This work also contributes to our overall understanding of rapid evolution and phenotypic plasticity in the colonization of novel environments, in agricultural weeds and beyond.
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Title: INVESTIGATING THE IMPACT OF ANTIOXIDANT SUPPLEMENTATION ON MUSCLE ANTIOXIDANT STATUS AND THE SKELETAL MUSCLE PROTEOME IN THOROUGHBRED RACEHORSES
Creator: Henry, Marisa LeeAnn
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Glutathione (GSH) and Coenzyme Q10 (CoQ10) are potent cellular antioxidants that work to mitigate oxidative stress arising from reactive oxygen species (ROS) production. GSH is not well absorbed because it is broken down into individual amino acids in the small intestines. Cysteine is the rate limiting amino acid in GSH synthesis but is not well absorbed and is instead largely produced from methionine intracellularly. N-acetyl cysteine (NAC) supplementation has been studied as an alternative...
Show moreGlutathione (GSH) and Coenzyme Q10 (CoQ10) are potent cellular antioxidants that work to mitigate oxidative stress arising from reactive oxygen species (ROS) production. GSH is not well absorbed because it is broken down into individual amino acids in the small intestines. Cysteine is the rate limiting amino acid in GSH synthesis but is not well absorbed and is instead largely produced from methionine intracellularly. N-acetyl cysteine (NAC) supplementation has been studied as an alternative to cysteine or GSH supplements and has been shown to increase the amount of circulating cysteine and increase transport activity for this reduced form in humans. GSH concentrations in skeletal muscle have been measured in only a few studies in other species. Neither GSH nor NAC have been previously studied in the skeletal muscle of horses. CoQ10 is an electron transporter in the mitochondrial electron transport chain (ETC) where it transfers electrons either from complex I or complex II to complex III. Within the ETC, complex I has been shown to be the primary source of ROS during exercise in comparison to the other complexes. Due to its location and function, CoQ10 can also function as a potent membrane bound antioxidant and mitigate ROS produced through the ETC. CoQ10’s function as an antioxidant and electron transporter has not been studied in great depth in horses. Branched chain amino acid (BCAA) supplements are three essential amino acids that have been shown to have positive effects on protein synthesis through the mammalian target of rapamycin pathway (mTOR). BCAA can serve as an energy source in skeletal muscle where they are directly metabolized in the tricarboxylic acid cycle. There are a limited number of studies of the impact of BCAA supplementation on equine skeletal muscle and none have looked at BCAA combined with antioxidant supplements. The overarching objective of this dissertation was to evaluate the impact of antioxidant supplementation on fit, healthy Thoroughbred horses. The first study supplemented NAC and CoQ10 to maximally exercising Thoroughbreds to determine its effect on the redox equilibrium and skeletal muscle proteome. We determine that NACQ increases muscle GSH concentrations post exercise while increasing TCA cycle enzymes and enhancing capacity for cellular NADPH production. The second study measured the effect of a single dose of differing amounts and formulations of CoQ10 on plasma CoQ10 concentrations. We determined that individual horses have different absorption responses, with 50% showing no response. The third study analyzed chronic CoQ10 supplementation’s effect on plasma CoQ10 concentrations, concentrations or activities of skeletal muscle antioxidants, mitochondrial respiration, and the skeletal muscle proteome. Results supported CoQ10’s function as an antioxidant and ability to alter the contribution of complex I and complex II to electron transfer without increasing mitochondrial volume density. The final study of this dissertation analyzed the impact of NAC and BCAA supplementation on sub-maximally exercising Thoroughbreds by measuring antioxidant status and alterations to the skeletal muscle proteome before and after exercise. This study identified no changes in skeletal muscle GSH concentrations and ROS before or after exercise but did find differentially expressed proteins within the ETC, redox reactions, and glycolysis after submaximal exercise. All supplements warrant further investigation in horses with myopathies.
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Title: PRE-SERVICE SCIENCE TEACHERS’ ARTICULATION AND REVISION OF FRAMEWORKS OF SCIENCE TEACHING IN A JUSTICE-ORIENTED METHODS CLASS
Creator: Brien, Sinéad Carroll
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The reasons particular people enjoy science, pursue science, and see themselves as science people, or not, are diverse and complex (Brickhouse, et al., 2000). The ways that teachers present science and value particular ways of knowing and doing in the classroom can influence which students see themselves as science people (Carlone et al, 2011). When teachers treat one particular cultural way of knowing in science as the superior way of knowing, specifically Eurocentric ethnoscience with its...
Show moreThe reasons particular people enjoy science, pursue science, and see themselves as science people, or not, are diverse and complex (Brickhouse, et al., 2000). The ways that teachers present science and value particular ways of knowing and doing in the classroom can influence which students see themselves as science people (Carlone et al, 2011). When teachers treat one particular cultural way of knowing in science as the superior way of knowing, specifically Eurocentric ethnoscience with its grounding in whiteness, heteropatriarchy, Protestantism, and settler colonialism, they create/maintain a hierarchy of knowledge that limits how all students can participate and see themselves in science, in particular girls, Black students, Indigenous students, and students of Color (Archer et al., 2010; Bang et al., 2012; Mutegi, 2013). Especially as Eurocentric ethnoscience is often presented as neutral, objective and universal (Harding, 2006), science teachers may not realize that there are multiple ways to know and do in science. In this study I draw from Gee’s (2016) conception of Framework Discourse Analysis to posit that pre-service science teachers (PSTs) can be supported to articulate, question, and revise their socially-derived ideas/expectations of science and teaching (i.e., their “frameworks” of science and teaching) through participation in my two-semester long Science Teaching Methods Class focused on justice-oriented science teaching. Through a case study of three PSTs’ select artifacts from the class and interviews the summer after the class, I identified each PST’s frameworks of science and teaching, how PSTs questioned and revised these across Methods Class, and which types of Methods Class activities supported this articulation, questioning, and revising of frameworks. I found that all PSTs clearly articulated their frameworks of science and teaching and that a pluralist/contextual framework of science was important in developing justice-oriented science teaching frameworks. In addition, the types of Methods Class activities that supported clearer articulation of science and teaching frameworks were those focused on connecting science and culture, expanding notions of what it meant to be a “successful” science student, and methods to recognize and address the sociopolitical in science and teaching in the classroom. These findings have implications for the use of Gee’s (2016) Framework Discourse Analysis as a guide for raising critical consciousness and recognizing value in multiple ways of knowing and doing. In addition, they raise questions about criteria for recruiting pre-service science teachers and assessing their readiness to enter the field of teaching as justice-oriented science teachers.
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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: 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: 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: 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: ELEMENTARY TEACHER CANDIDATES’ CONNECTIONS BETWEEN MATHEMATICS AND LITERACY AND THE CONTEXTUAL FACTORS THAT ENCOURAGE CONNECTION-MAKING
Creator: Hawley, Lisa A.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Elementary teacher candidates (TCs) must learn to teach many subject areas. Although some mathematics education researchers have framed elementary teachers’ knowledge as a deficit (i.e., lack of depth of mathematics knowledge), this dissertation considers elementary teachers’ broad knowledge as a strength. Many elementary teachers and TCs feel anxious about teaching mathematics, but more confident in teaching other subjects, such as literacy. By identifying similarities between the teaching...
Show moreElementary teacher candidates (TCs) must learn to teach many subject areas. Although some mathematics education researchers have framed elementary teachers’ knowledge as a deficit (i.e., lack of depth of mathematics knowledge), this dissertation considers elementary teachers’ broad knowledge as a strength. Many elementary teachers and TCs feel anxious about teaching mathematics, but more confident in teaching other subjects, such as literacy. By identifying similarities between the teaching and learning of two subjects, they can draw on their knowledge of teaching other subjects to teach mathematics in a conceptually oriented, inquiry-based way. This case study of a cohort of elementary TCs taking concurrent mathematics and literacy methods courses sought to learn more about their connection-making by asking two questions: (a) What connections between subject areas, if any, do elementary TCs enrolled in concurrent literacy and mathematics methods courses identify? and (b) How do the contexts in which they are learning to teach encourage or limit the opportunities to make connections across subject areas? To answer the first question, I developed a conceptual framework of types of connections between mathematics and literacy, based on the research literature. This framework includes integrated curriculum, language as a basis for learning, and similarities in teaching and learning. I generated data through participant observations of class sessions and focus group discussions and analyzed the types of connections the TCs made using my framework. They identified a variety of connections between mathematics and literacy, with the two most frequent categories being about the role of reading in learning mathematics and similarities in pedagogy. To analyze the conditions which supported their connection making, I conceptualized the two methods courses as separate, but overlapping, communities of practice, and the focus group discussions as boundary encounters between them (Wenger, 1998). The focus groups, as boundary encounters, enabled TCs to identify a larger number of boundary objects (i.e., connections), as well as make richer connections. This took place through two types of knowledge brokering: brainstorming to identify boundary objects, and collaborative brokering, in which multiple participants contributed knowledge from other courses or experiences to collectively make sense of similarities or differences across the two subjects. In addition, my participation in collaborative brokering during the second focus group discussion suggests that TCs need the support of a more experienced knowledge broker to support their connection-making in order to go beyond surface-level similarities. These findings suggest that, in order to make connections that would enhance their mathematics teaching, elementary TCs need intentionally created spaces and the support of an instructor who is familiar with the teaching and learning of more than one subject area. This has implications for the structure of elementary teacher preparation programs, as well as the background and/or professional development of mathematics teacher educators who work with elementary TCs.
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