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  Women Professionals of Color at U.S. Medical Schools Navigating Emotional Labor

  Rhoades, Gary; Givens, Raquel Hernandez; Nicolazzo, Z; Cabrera, Nolan (The University of Arizona., 2023)

  This dissertation presents an ethnographic exploration of the experiences of nontrans women professionals of color employed at U.S. medical schools, focusing on the intersectionality of gender and race and its influence on emotional labor. By conducting qualitative interviews, this research seeks to elucidate the multifaceted nature of emotional labor within the context of medical school environments and shed light on the participants' perceptions of their roles. The study's objective is to comprehend how the convergence of gender and race shapes the emotional labor of women professionals of color in medical schools, examining the intricacies of their experiences and the impact of these experiences on the broader mission of diversity, equity, and inclusion within these institutions. Thirteen women professionals of color were interviewed, encompassing various organizational positions and racial/ethnic backgrounds, to capture a range of perspectives. The findings underscore the integral role that emotional labor plays in the daily tasks and responsibilities of the women professionals interviewed. The participants' contributions to advancing diversity, equity, and inclusion initiatives within their respective medical schools were intricately intertwined with their emotional labor. Moreover, the data analysis revealed nuances that cut across both organizational positions and racial/ethnic identities, offering a deeper understanding of the distinct challenges faced by these professionals. A significant divergence was identified between groups with Black and Middle Eastern participants, as they reported experiencing racialized emotions in their roles. This aligns with existing scholarship on racialized emotions and supports the notion that the emotional labor of women professionals of color cannot be detached from the racial dynamics within medical institutions (Wingfield; Bonilla-Silva). Furthermore, the study illuminates the participants' agency in managing emotional labor. They exhibited self-awareness and adeptly performed their gender and race roles to navigate through the gendered and racialized landscape of medicine. Additionally, the importance of finding community emerged as a vital coping strategy, as these professionals leveraged collective support to overcome the challenges inherent in their roles. In summary, this ethnographic study contributes to the growing body of knowledge on emotional labor, gender, and race within organizational contexts, with a specific focus on U.S. medical schools. The findings emphasize the intricate interplay of emotional labor and diversity initiatives, while also highlighting the agency of nontrans women professionals of color as they negotiate their roles in a complex and dynamic environment.
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  Modulators of Neuroimmune Interactions Induced by Toxoplasma gondii

  Koshy, Anita A.; Merritt, Emily Frances; Goodrum, Felicia D.; Kuhns, Michael S.; Bhattacharya, Martha RC (The University of Arizona., 2023)

  Toxoplasma gondii is a common, intracellular parasite that establishes a long-terminfection in neurons in the central nervous system (CNS). Infections are often asymptomatic; however, in individuals lacking a T cell response Toxoplasma infection can lead to uncontrolled neuroinflammation, and potentially death. A long-standing question in the field is how Toxoplasma survives long term within the host. One hypothesis suggests that long term persistence is enabled by parasites residing in neurons because neurons do not have the same cell-intrinsic immune capabilities to clear parasites as non-neuronal cells (i.e., neurons are thought to lack major histocompatibility complex as an immune receptor to interact with T cells and are considered unable to respond to cytokine). Another hypothesis is that Toxoplasma modifies neurons to allow persistence by manipulating neurons through injection of Toxoplasma effector proteins, known as ROPs and GRAs, which are secreted into host cells during infection and can alter host cell signaling. Given we know Toxoplasma modifies many signaling pathways through these effector proteins, we set out to identify novel pathways that may aid in parasite persistence by transcriptionally profiling neurons that have been injected with Toxoplasma proteins. We infected Cre reporter mice, which only express a green fluorescent protein (GFP) after Cre mediated recombination, with Toxoplasma strains that have Cre recombinase fused to an effector protein that is secreted into host cells prior to invasion. Therefore, in the brain we can detect Toxoplasma injected neurons (TINs). Laser capture microdissection allowed us to isolate these injected neurons from an infected brain and perform transcriptional analysis to compare the transcripts of these injected neurons to neighboring neurons that have not interacted with parasites (Bystander neurons). Pathway analysis indicated a high level of T cell transcripts within the TINs transcriptome compared to the Bystander neurons transcriptome. Analysis of immunofluorescently stained infected brain sections was consistent with T cells being in closer proximity to TINs compared to Bystander neurons. This extreme proximity suggested potential MHCI-T cell receptor interactions. To test this idea, we infected primary neuronal cultures with parasites expressing the model antigen, OVA, and cocultured antigen specific T cells with these infected cultures. We found T cells could be activated by the infected neuronal cultures, indicating neurons are capable of presenting peptide on MHCI to T cells. To explore the ability of neurons to clear parasites (a possible outcome of T cell-neuron interactions), we infected Cre reporter mice with a strain of Toxoplasma that only triggers Cre mediated recombination in host cells after a successful invasion (GCre). We generated 200μm thick brain sections from these mice, optically cleared the sections using PACT clearing, and generated 3D reconstructions of the GFP+ neurons to determine if they actively harbor parasites. Approximately 50% of rendered neurons did not harbor parasites, indicating that neurons are capable of clearing Toxoplasma in vivo. Lastly, within this dissertation, I explored the importance of a specific effector protein, GRA15, and how it contributes to parasite persistence. Analysis of the peripheral immune response and parasite burden in the brain indicates that GRA15—an effector that causes polarization to classically activated macrophages—is does not significantly influence parasite dissemination and persistence. Overall, this dissertation uses Toxoplasma as a tool to investigate the immune capacity of neurons. We find that neurons can interact with T cells and possess competence at clearing Toxoplasma. Future directions include describing how utilizing tools I generated will allow others to determine how T cell recognition of and activation by antigen generated at different life-stages of Toxoplasma contributes to parasite clearance vs persistence.
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  Using Response Generation Behaviors to Improve the Quality of Survey Data

  Valacich, Joseph; Kumar, Manasvi; Jenkins, Jeffrey; Hashim, Matthew; Chen, Wei; Brandimarte, Laura (The University of Arizona., 2023)

  Despite their prevalent use, online surveys are vulnerable to data quality problems that may be attributed to several factors, including respondent induced measurement errors that cause discrepancies between respondent attributes and their responses. This research explores how a respondent’s response generation data manifests in their human computer interaction (HCI) device usage; and how these fine-grained HCI data may be used to identify poor-quality responses in online surveys. The larger goal of this research is to establish a structured set of guidelines to address the presence, impact, and appropriate mitigation for poor-quality survey responses. To this end, this dissertation provides a framework that utilizes individual characteristics, survey characteristics, as well as other external factors to determine one's response generation process and consequently the usefulness of that response.This dissertation establishes the prevalence of poor-quality responses in survey research and examines how behavioral differences between respondents exhibiting previously known undesirable behaviors may be used to detect poor-quality responses. ‘Essay One’ examines the presence of poor quality data among professional survey respondents and how HCI based behavioral data can be used to identify them. ‘Essay Two’ examines the same problem among another common participant pool, university students. ‘Essay Three’ alleviates typical Type I concerns in ‘Essay One’ and ‘Essay Two’ by examining whether specific undesirable behaviors exhibited by respondents while answering a question may be captured using appropriate metrics. The overall results obtained suggest that behavioral differences during the response generation process may be captured through HCI devices to create appropriate metrics that identify poor quality responses.
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  Machine Learning Application in Sleep Disorder Analysis

  Roveda, Janet M.; Huo, Jiayan; Kuo, Phillip H.; Li, Ao; Toosizadeh, Nima (The University of Arizona., 2023)

  Sleep is a natural state of reduced consciousness and physical activity that is crucial for the body’s circadian rhythm and various physiological processes. Sleep disordered breathing events, such as sleep apnea, can cause cortical arousal during sleep, leading to sleep cycle breaking and sleep fragmentation. Inadequate sleep can jeopardize the immune system and pose a significant risk to health and life. Sleep disordered breathing (SDB) screening and understanding the coupling between cortical arousal and health burden are critical for sleep and health monitoring. Machine learning can be compatible of recognizing patterns in complex data and prediction on future unseen data, which not only can reduce the intensive labor for manual processing but also uncover the new knowledge that people may have not been awareof. In this dissertation, we developed a six-item questionnaire for obstructive sleep apnea (OSA) screening tool using a large general population database - Sleep Heart Health Study(SHHS). Two independent logistic regressions underlie the algorithm of OSA binary prediction by considering two phenotype groups. We evaluated the tool on the SHHS test set (n = 1237) and an independent set Wisconsin Sleep Cohort (WSC) (n = 1120). The model outperformed these questionnaires on both test sets regarding the area under the receiver operating characteristic (AUROC) and the area under the precision-recall curve (AUPRC). The model achieved AUROC (SHHS 1: 0.78, WSC: 0.76) and AUPRC (SHHS 1: 0.72, WSC: 0.74), respectively. A multi-task deep learning algorithm was investigated based on previous study for cortical arousal detection and sleep staging using the single-lead Electrocardiogram (ECG). The model was developed on Multi-Ethnic Study of Atherosclerosis (MESA) dataset of which 1069 full night PSG were included in this study. We analyzed the fairness of the model by comparing the performance between subgroups with different demographics factors including gender, age and ethnicity. The model achieved an AUROC of 0.947 and AUPRC of 0.61 regarding the arousal detection, and Conhen’s κ of 0.68 and overall accuracy of 0.79 for four stage sleep prediction-light(N1/N2), deep(N3/N4), REM and wake. Though numerical differences regarding the aforementioned metrics were observed between different subgroups, the differences were not statistical significant. We also analyzed the intermediate channel outputs that shared by both tasks to explore the features that model have learned from raw ECGs. The results showed that intermediate channel outputs have a strong correlation with instantaneous heart rate on at least 80% of the subjects in testing set. More complicated HRV features were also investigated, though less portion of subjects showed strong correlations. Lastly, we studied the instantaneous association between cortical arousal onsets and heart rate variability (HRV) with the help of deep learning model among the general population. We compared the HRV changes pre-, intra- and post- arousal occurrence using a 25-second window. We also examined the cardiac response difference between different genders (male and female) and different sleep stages(REM or NREM). Significant variations were observed in heart rate and HRVs due to arousal onsets. Most importantly, female showed a more intensive cardiac response to the arousal onsets compared to male subjects which can potentially result in heavier heart burdens and long-term cardiovascular morbidity. More intensive variations caused by arousal were observed in REM, implying the instantaneous elevation of the sympathetic tome which may stress the cardiac function and cause sudden cardiac death.
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  A Synergistic Approach to Radiation Shielding Design Through Computation-Informed Selection of Additively Manufacturable Composite Materials and Shield Configurations

  Potter, Barrett G.; Baumann, Nicholas; Simmons-Potter, Kelly; Muralidharan, Krishna; Pearson, Charlotte (The University of Arizona., 2023)

  Ionizing radiation is the collection of particles including photons, electrons, protons, andneutrons which have sufficient kinetic energy to remove bound electrons from an atomic nucleus. Thus, radiation effects can play a significant role in degrading the resiliency of technologies for a variety of applications, including those central to nuclear energy production and space travel. Radiation in these environments can be both acutely and chronically harmful to both humans and electronic and optical systems, hence the need for appropriate design of radiation protection measures and radiation resistance or hardness. In general, the three tenets of radiation protection are time, distance, and shielding. For many of these cutting-edge applications like space colonization and nuclear power generation via fission and fusion, the time within the radiation environment cannot be reduced nor the distance from the source increased, leaving radiation shielding as the primary method of exposure mitigation. The present work details and demonstrates a synergistic approach to radiation shielding design and implementation, focusing on the computation-based design of additively manufacturable composite radiation shielding materials. Monte Carlo simulations explore the shielding design space and inform optimization algorithms. The materials selected for these simulations are additively manufacturable via fused deposition modeling (FDM) into homogeneous and layered composite structures, the performance of which has been experimentally validated. Four publications are provided in the work (Chapters 4 – 7 respectively), in which the principles of this design approach have been demonstrated to address a range of radiation environments and shield design classes. The works are each presented with an assessment of their 16 contextual rationale and, when appropriate, a summary of subsequent follow-on efforts to extend the results and impact obtained beyond that of the original works. The first publication explored the effect of Cu loading on the radiation shielding performance of additively manufacturable homogeneous particle-loaded composites against monochromatic gamma and electron irradiation using GEANT4 Monte Carlo radiation transport code. Experimental validation of the GEANT4 simulations was performed for FDM printed Culoaded, Fe-loaded, and BaSO4-loaded composites. For gamma radiation between 0.1 and 15 MeV, shielding performance was essentially independent of composition because of the similarity of the mass attenuation coefficients of copper and PLA in that energy range and because the shield thicknesses investigated were less than the gamma mean free paths at each energy for each material. In contrast, for monochromatic electron radiation, the optimum composition was found to be dependent on both energy and shield areal density. This dependence was determined to correspond to the continuous slowing down approximation (CSDA) range for electrons, with pure Cu being optimal when the shield areal density is less than the CSDA range, and PLA with <10 wt.% Cu being optimal when the areal density is greater than the CSDA range. The second publication presented a material replacement case study. The total ionizing dose (TID) transmissivity of additively manufacturable homogeneous Cu-PLA composites was compared against 1 g/cm2 of aluminum (a prototypical radiation shielding for CubeSats in low earth orbit (LEO)) in the LEO trapped electron radiation environment. An optimization algorithm identified the required composite thickness to match the TID transmissivity of 1 g/cm2 of aluminum for each composite composition (increments of 10 wt.% Cu) and monoenergetic electron energy (0.1, 0.2, 0.5, 1, 2, 5 and 10 MeV). For all compositions except for pure PLA (0 17 wt.% Cu), there was at least a 60% shield mass reduction while achieving the same TID performance as 1 g/cm2 of aluminum, when the average mass reduction weighted by the LEO spectrum was calculated. A 10 wt.% Cu-loaded PLA homogeneous composite provided the same shielding effectiveness as 1 g/cm2 of Al while being 65% lighter and 24% thinner. Further volume reduction with similar mass improvements were achievable with higher Cu loaded compositions. The third publication demonstrated a simulation-based investigation of sensitive parameters for two-phase, multilayered radiation shielding against gamma and electron radiation. Similar to results of the first publication, gamma shielding is generally insensitive to number of layers, layer ordering, high-Z layer fraction, mean composition, and areal density compared to homogeneous compositions in the 0.1 to 10 MeV energy range. Experimental irradiation using a 60Co radioisotope source confirmed the gamma performance of the homogeneous composites and lack of improvement or reduction in performance from a layered composite shield. The sparce experimental results were used to reconstruct the most probable true center location of the gamma source. These results were used to determine the intrinsic mass attenuation coefficients of homogeneous composites at a mean gamma energy of 1.25 MeV. For monoenergetic electron radiation, an additively manufacturable hierarchical composite radiation shield provided the best TID reduction; 50 – 66% more than a homogeneous composite shield of identical composition. The optimum structure consisted of two layers, a PLA layer facing the incident radiation and an 83 wt.% Cu-loaded PLA layer behind, the latter being 0.3 of the entire shield thickness, resulting in a mean composition of 50 wt.% Cu. An areal density greater than or equal to 3x the CSDA range at the incident electron energy was required to observe significant performance enhancement with layered shielding. 18 The fourth and final publication was a culmination of all previous publications. It centered on simulation-based design of additively manufacturable radiation shielding consisting of 10 equal areal density layers of three possible materials, PLA, B4C-PLA, and CuPLA, for the deuteriumtritium fusion neutron (14 MeV) environment. An initial random search of the layer ordering– composition parameter space led to the selection of a compositional family with low yet largely varying TID transmissivity, depending on configuration. The TID transmissivity for every shield configuration within the compositional family consisting of 6 layers of PLA, 2 layers of B4C-PLA, and 2 layers of CuPLA (77.4 wt.% PLA, 16.6 wt.% Cu, and 6.0 wt.% B4C) was measured via simulation. A novel design parameter, Z-Grading Degree (?), which expresses how monotonically increasing (+) or decreasing (–) a shield configuration is, was found to correlate negatively with dose transmissivity. Further, position of the rear-most B4C-PLA layer was found to strongly correlate (in the negative sense) with dose transmissivity, i.e., the further back the B4C-PLA layer was within the shield, the more effective the shield was at reducing the transmitted total ionizing dose from 14 MeV neutron irradiation. These findings were confirmed with experimental irradiation testing using an uncollimated deuterium-tritium fusion neutron source. Anisotropies in the neutron flux data were used to confirm the spatial extent of the source and allowed for a novel reconstruction of its most probable true center location.
• Coupling Data Science and Design Science to Solve Real-World Business and Healthcare Challenges

  Ram, Sudha; Li, Yuanxia; Brown, Susan; Leroy, Gondy (The University of Arizona., 2023)

  Big and heterogeneous data that have become increasingly available provide precious opportunities for addressing real-world challenges. Nevertheless, the 3Vs (volume, velocity and variety) of big data have created computational challenges. In addition, because big data are often not collected for the purpose of research, careful repurposing is needed in harnessing the power of data. Data science has provided powerful tools to address the 3Vs of big data, while design science offers a paradigm that guide the effective usage of tools and the repurpose of data. In this dissertation, three essays are included to demonstrate how data science and design science may be coupled to address real-world business and healthcare challenges. In the first essay, a theory-enhanced hierarchical neural network model with correction is proposed to provide fine-grained classification of social media users. The artifact is an important tool that helps the repurposing of social media data and is itself a demonstration of coupling data science tools (e.g., machine learning) with design science (e.g., theory-guided design). The second essay integrates and repurposes heterogenous data sources from the contact tracing process to evaluate multi-method contact tracing. It is another manifestation of using careful design with the help of analytical tools to obtain insights from data. The third essay investigates the use of theoretical lenses in startup success prediction. Specifically, the effect of social capital theory and knowledge spillover theory is experimented. It demonstrates how theories can guide the design choices and enhance predictive modeling that used to be data-centric. This dissertation has demonstrated how data science and design science can be integrated to address real-world business and healthcare challenges. It has great relevance to both the data science and designs science communities, and the artifacts and insights created also have great implications to researchers and practitioners in the field of social media analytics, contact tracing, and startup evaluating and investing.
• Precision Identification and Targeting of Rod Microglia in Diffuse Brain-Injured Cortex

  Lifshitz, Jonathan; Giordano, Katherine R.; Stabenfeldt, Sarah; Morrison, Helena; Anderson, Trent; Van Keuren-Jensen, Kendall; Mastroeni, Diego (The University of Arizona., 2023)

  Diffuse traumatic brain injury (TBI) leads to complex pathophysiological processes that result in clinical symptoms. Neuroinflammation and associated microglia activation are hallmark pathophysiological processes of diffuse TBI and contribute significantly to both damage and ensuing repair. Microglia are the resident innate immune cells in the brain and microglia function is linked to cellular morphology. Inflammatory signaling after diffuse TBI initiates microglia activation where microglia go from a ramified morphology (small soma with long, highly branched processes) to an activated morphology (swollen soma with enlarged, retracted processes). We also report an abundance of rod microglia (elongated soma with polarized processes) in the cortex after diffuse TBI. Rod microglia were first described in the early 1900’s and have since been sporadically reported in neurological conditions such as chemical exposure, viral infection, Alzheimer’s disease, Lewy Body dementia, ischemia, and TBI. Despite their occurrence across injury and disease, very little is known about rod microglia. Investigations have been limited to post-mortem histology using general microglia markers. The objective of this dissertation was to identify markers and develop tools to differentiate rod microglia from other microglia morphologies and confirm rod microglia mechanisms after TBI with the central hypothesis that rod microglia have a unique molecular profile compared to other microglia morphologies. First, we applied phage display biopanning to isolate antigen-binding domains specific to rod microglia compared to other microglia morphologies. We modified a novel discovery pipeline to develop antibody-mimetics from antigen-binding domains that can be validated for rod microglia specificity and used for downstream applications such as immunohistochemistry. Next, we investigated gene expression of rod microglia pathology with single nucleus RNA sequencing to provide insight into rod microglia function. We identified three distinct subclusters of microglia within the somatosensory cortex and inferred that those with inflammatory and neurological disease pathways may represent rod microglia. Finally, we used diffusion magnetic resonance imaging (MRI) to refine a non-invasive imaging signature of rod microglia. Water restriction was visible by diffusion MRI in the somatosensory cortex and corresponding histology reported activated microglia in regions where water restriction was observed. While not a marker of rod microglia specifically, novel post-image processing was sensitive to detect changes in microglia. This dissertation is the first step in developing and validating tools to target rod microglia. Until rod microglia mechanisms can be investigated with new tools, their role in the evolution, progression, and resolution of diffuse TBI pathophysiology remains unknown.
• Ecosystem Services on Shrub-Encroached Rangelands: Balancing Supply and Demand

  Archer, Steven R.; Jones, Scott Andrew; Fisher, Larry A.; Marsh, Stuart E.; Guertin, David P. (The University of Arizona., 2023)

  The encroachment of woody plants into grasslands and savannas has been a phenomenon widely reported across both the Southwestern US and globally. Once established, woody plants may be long-lived and highly persistent creating numerous challenges for resource managers. The upper limits of shrub cover are regionally dictated by mean annual precipitation, but topoedaphic features play a key role in determining these limits, which can vary widely at the local level. Grasslands and savannas are of high value to socioecological systems due to the diverse portfolio of ecosystem services they provide. However, the transition to shrublands and woodlands can alter both processes and functions ultimately disrupting the availability of these services. Although there is a significant body of research on woody plant encroachment, little is known about the upper limits of shrub cover for a given topoedaphic setting or how this conversion has altered important ecosystem services. Improving our understanding of these topics can enhance management of these systems and is therefore of broad geographic interest. The overarching goal of this dissertation was to explore the woody plant encroachment phenomenon through a holistic lens evaluating both the physical and social impacts of this landscape wide cover change. Within the following manuscript I will present research on the underlying topoedaphic drivers dictating rates and patterns of encroachment at the local level, the long term impacts of encroachment on key ecosystem services, as well as the social perceptions on which ecosystem services are valued highest across these systems. The first study used high spatial resolution imagery to classify cover of a model shrub (Prosopis velutina, velvet mesquite) proliferating in a Sonoran Desert grassland. The analysis also explored how the upper limits of shrub cover varies across ecological sites and topoedaphic settings. Upper limits were found to have a wide range variously dictated by elevation, slope inclination/aspect, soil texture, and rainfall re-distribution. Furthermore, this variation was not equal across ecological sites, especially between lowland and upland sites. For the second project I conducted a case study in southern Arizona and New Mexico to evaluate stakeholder perceptions of and preferences for various ecosystem services provided on semi-arid rangelands where shrub proliferation has impacted traditional livestock grazing. Perceptions of rangeland ecosystem services were elicited via a visually-based landscape interpretation while preferences were quantified using Best-Worst Scaling (BWS). Results suggest that stakeholders familiar with rangelands and their management generally perceive low shrub cover as providing a wider range of valued ecosystem services compared to rangelands with high shrub cover. Contrary to expectations, ecosystem service preferences in the context of shrub encroachment were generally uniform across all stakeholder groups surveyed (e.g. ranchers, state/federal governmental employees, non-governmental land managers, academicians, recreationists), with habitat for biodiversity and erosion control being identified as the most preferred. The third study built on the above case study by spatially modeling changes to the two highest valued ecosystem services (habitat for biodiversity and erosion control) following documented shrub encroachment across a semi-arid grassland in southern Arizona from 1936-2017. While overall shrub cover change was found to be low over this time (~5%) it was highly variable across the landscape. Changes to ecosystem services were also found to have high spatial variability with some services being increased in concert with encroachment while others were negatively impacted. Understanding where and to what extent these services have been altered will help improve planning efforts with respect to the location, type (e.g., prescribed fire), and timing of brush management.
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  Documenting Reawakening Languages: A Case Study of Tunica

  Henderson, Robert; Harvey, Megan Anna; Zepeda, Ofelia; de Lima Silva, Wilson (The University of Arizona., 2023)

  As more communities work to create new speakers of their languages we are seeing a new linguistic environment develop and, from that, particular styles of language use emerge. This dissertation adds to the growing literature on studying and supporting the process of language revitalization (e.g. Stebbins et al. 2017, Zuckerman 2021), by describing the process of documenting and analyzing Tunica (tun ISO 639-3), a reawakening language spoken in central Louisiana, USA. ‘Reawakening languages’ are languages whose usual transmission has been interrupted and the community is looking to learn them through existing documentation, meaning looking at their revitalization process has the potential to be both incredibly illuminating and in- credibly disruptive to language learners and language workers. With these concerns in mind, this dissertation presents a method for documenting languages as they are being revitalized that minimizes disruption and maximizes support by centering the documentation around language revitalization activities and output. The first chapter introduces key terms and situates current research in language revitalization. Chapter 2 provides background on Tunica, the revitalization efforts in the community, and the language structure. Chapter 3 provides general recommendations for documenting the process of languages being reclaimed and reawakened. Chapters 4 and 5 focus specifically on documenting Tunica, with Chapter 4 describing the process of documenting Tunica in the classroom, through the creation of podcasts, and with more traditional elicitation. Chapter 5 turns to the types of questions we can look at using documentation of reawakening languages by considering trends in three morphological and syntactic phenomena in the language: the use of gender-number-agreement clitics, the use of overt subjects, and the structure of questions. Chapter 6 ties this all together and looks towards future projects.
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  The Estimation of High-contrast Spectra via Iterated Whitening

  Lin, Kevin K.; McBride, Jared Adam; Venkataramani, Shankar C.; Watkins, Joe (The University of Arizona., 2023)

  Power spectra are a fundamental tool in data analysis, signal processing, and linear prediction and control. Many who seek to estimate power spectrum are obliged to do so with very little theoretical information of the underlying process and prefer accurate estimates which require as little effort as possible. This work focuses on estimation of the power spectrum of time series data from dynamical systems and stochastic differential equations (SDEs) and attempts to satisfy the preferences above. The method, called iterated whitening (IW) spectral estimation, iteratively builds inexpensive filters that progressively ameliorate the data until the resulting modified data is suitable for accurate spectral estimation. This spectral estimate is then post-processed to return an accurate estimate of the original data. Time series from dynamical systems and SDEs often possess a very large dynamic spectral range which makes them difficult to estimate cheaply and accurately. IW provides a solution to this difficulty. In this dissertation, I discuss some of the issues that the Bartlett estimator has in approximating these ``high-contrast'' spectra by deriving expanded bias and variance formulas. I also showcase another technique for improving a spectral estimator using the method on control variates from Monte Carlo Markov chain theory. I apply these methods to some time series from a solution to the Kuramoto-Sivashinsky equation which is in spatiotemporal chaos.
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  Investigation of the Electronic Structure of 2D Materials Using X-Ray and UV Photoemission Techniques

  Monti, Oliver; Zachritz, Sara; Schwartz, Steven; Huxter, Vanessa; Bredas, Jean-Luc (The University of Arizona., 2023)

  The limitations of current day electronics have created a tremendous drive to find new materials for more advanced electronic devices. However, without a fundamental understanding of key interfacial processes, such as electron transfer or charge carrier dynamics, developing practical devices becomes an impossible task. It therefore is of vital importance to comprehend the fundamental physics that governs these interfacial processes to fulfill the practical need for more advanced electronic devices. In this dissertation, I mainly focus on the class of inorganic 2D materials called transition metal dichalcogenides that present a wide range of electronic properties based on their composition. I begin by exploring the ultrafast charge carrier dynamics at the interface between an organic and inorganic semiconductor (C60/WSe2). The interfacial charge transfer, which results in an interfacial electric field, reveals new opportunities to control the different spin degrees of freedom inherent to the inorganic semiconductor (WSe2) and provides a novel mechanism to create spin-polarization in a nonmagnetic heterostructure. Next, I investigate the temperature-induced electronic phase transition between the semimetallic 1T’-phase of MoTe2 and the topological Weyl semimetal Td-MoTe2. The platform provided by this phase transition constitutes a new opportunity for systematic control of the electronic structure. As a result of the more exotic electronic properties of Td-MoTe2, new scattering pathways are available and I demonstrate how the electronic structure influences the ultrafast charge-carrier dynamics in the two phases. Finally, I demonstrate the importance of the electronic structure and its influence on the luminescent properties of two types of lanthanide-doped metalorganic complexes. The energy level alignment between the ligands and the rare earth centers in the complexes determines not only the efficiency of the material’s luminescent capabilities but also its influence on the emissive color properties. Overall, the case studies presented in this dissertation highlight how the electronic structure governs the ultrafast charge carrier dynamics and electron transfer properties, presenting new opportunities towards advanced electronic devices.
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  Improving PL Approximations of Harmonic Maps and a Penalty-Function Approach to Harmonic Maps

  Glickenstein, David; Banks, Robert; Venkataramani, Shankar C.; Sethuraman, Sunder; Izosimov, Anton (The University of Arizona., 2023)

  In this dissertation, we consider two problems in the approximation of harmonic maps between empirically-known manifolds embedded in Euclidean spaces. First, we suppose that the domain manifold $\mathcal{M}$ is known by a point cloud $M_s$ and that $M_s$ has been used to reconstruct a $PL$ surface $\tau$ approximating $\mathcal{M}$. Then, assuming that we have a $PL$ map $f^\tau: \tau\to \mathbb{R}^k_\mathcal{N}$ that approximates a harmonic map $\mathcal{M}\to \mathcal{N}$, we ask how we can improve the approximation by using finer triangulations. In particular, we ask where we should add a single vertex to the domain triangulation $\tau$ given a single added vertex in the image triangulation $\mathscr{T}=f^\tau(\tau)$. We prove that a unique optimal solution exists when $\mathcal{M}\subset\mathbb{R}^2$. We find this optimal solution explicitly for several special cases and constrain it in general via an inverse problem. We then consider the problem of how to approximate a harmonic map $\mathcal{M}\to \mathcal{N}$ when the target manifold $\mathcal{N}\subset \mathbb{R}^k$ is known only by the point cloud $N_t$. We explicitly construct a $\mathscr{C}^1$ penalty functional $\mathscr{P}_t$ which is determined by $N_t$ and such that, if $f: \mathcal{M}\to \mathbb{R}^k$ and $f(\mathcal{M})$ is near $\mathcal{N}$, then $\mathscr{P}_t(f)$ is small. We then investigate how approximate harmonic maps can be found by locally minimizing functionals of the form $\mathscr{G}_t(\lambda, f)=\mathscr{E}(f)+\lambda\mathscr{P}_t(f)$ where $\mathscr{E}$ is the Dirichlet energy and $\lambda$ is a positive parameter. This work provides a foundation for extending the methods of \cite{ChenStruwe1989} to sampled manifolds.
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  An Informal Online Community in the Digital Wilds: Possibilities for Language Learning

  Castek, Jill; Oguilve, Veronica; Dupuy, Beatrice; Hellmich, Emily (The University of Arizona., 2023)

  This study explores the establishment and evolution of an informal online community, tracing how it developed and evolved. More specifically, the study analyzed the characteristics of the online space, as well as how members engaged within the community, including participation patterns, preferences, and opinions and identity construction. The community members were made up of multilingual and global participants; the space was creativity-driven, free, and open to all. Free navigation mirrors how informal communities work in the digital wilds where interaction is voluntary and interest-driven. Using descriptive methods, this research looked at language learning as the product of social interaction as participation varied across asynchronous posting, responding, and engagement in live conversations. One hundred eighty-eight participants came from different ethnic, linguistic, and geographical backgrounds, and explored their shared and individual interests and learning opportunities within the virtual space. All online activities were situated in a dynamic system of interactions that developed over time in response to participation patterns and preferences. Four participation profiles were developed by calculating members’ weighted activities which included post clicks, cheers, messages, comments, and participation in live Zoom events. Analysis revealed characteristics and preferences of the Power, the Motivated, the Curious, and the Attentive member. Findings from this study suggest expanding opportunities for self-directed and collaborative work in member-driven online communities that encourage incidental language learning and the exploration of different perspectives and cultures. Implications address the importance of incidental language learning, which should be carried over into formal language learning environments. In informal spaces where language learning is not explicit, learners can make their own decisions, explore the world on their own terms and make their own conclusions on what is valuable or meaningful for themselves as they interact with others. Keywords: online community, informal learning, incidental language learning, Ecological Approach, Critical Relationality, global interaction, communication, multimodality, creativity.
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  Postcolonial Theory and Native American Literature

  Fatzinger, Amy S.; Sun, Xiaochen; Jenkins, Jennifer L.; Fox, Mary J. (The University of Arizona., 2023)

  Studying Native American literature through the lens of postcolonial theory has been controversial both in the field of Native American studies and postcolonial studies. However, this historical study of the evolution of thought among of scholars of Native American literature regarding the main research question of whether postcolonial theory can be meaningfully applied to Native American literature leads to the discovery that literary nationalists and cosmopolitans—supporters and opponents of postcolonial theory in the field of Native American studies—are actually working toward the same direction, revealing the impact of colonial discourses upon Native American people and striving to deconstruct such colonial influences. Eight postcolonial terms, including Antonio Gramsci's hegemony, Bill Ashcroft's appropriation, Gayatri Chakravorty Spivak's strategic essentialism, Homi Bhabha’s mimicry, liminality and vernacular cosmopolitanism, Frantz Fanon's critical nationalism and the idea of center and margin in Bill Ashcroft, Careth Griffiths, and Helen Tiffin’s The Empire Writes Back, are systematically selected and applied to four Native American texts—D’Arcy McNickle’s The Surrounded (1986), James Welch’s Fools Crow (1936), Louise Erdrich’s Tracks (1988), and Frances Washburn’s The Sacred White Turkey (2010)—both to examine if they can illuminate the influences of colonization upon Native American people, and to address the concerns of postcolonial scholars and scholars in the field of Native American literature.
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  Investigation of Active Control of Boundary Layer Transition in Laminar Separation Bubbles

  Little, Jesse C.; Borgmann, David; Fasel, Hermann F.; Craig, Stuart A. (The University of Arizona., 2023)

  The presented research addresses the dynamics of the transition process in laminar separation bubbles (LSBs). Two major objectives will be discussed in this work: an investigation of the natural transition process in an LSB forming in the flow along a flat plate when subjected to an adverse pressure gradient (APG) and active flow control (AFC) exploiting the inherent instabilities in the LSB shear layer to control and delay laminar to turbulent transition.Extensive characterization of the boundary conditions in the experiment indicate a low turbulence environment necessary for stability and transition research. Prior to characterization of the LSB, the boundary layer along the flat plate model is investigated in the absence of the APG. Development of Tollmien Schlichting (T-S) waves in the laminar boundary layer along the flat plate show linear growth for several tested amplitudes and frequencies. Comparison to linear stability theory (LST) calculations and accompanying direct numerical simulations (DNS) show reasonable agreement in disturbance profiles and downstream amplitude development. Differences to the numerical results increase with downstream distance and are attributed to a slight favorable pressure gradient and the onset of non-linear behavior around the first maximum in the disturbance amplitude profiles in the experiment. Results confirm adequate quality of the free-stream turbulence (FST) (Tu ≤ 0.035%) and velocity spectra in the Arizona Low Speed Wind Tunnel (ALSWT) for the subsequent LSB transition study. The flow around the displacement body, used to impose the favorable to adverse pressure gradient to the flat plate model, is investigated and flow control measures are installed to ensure smooth, attached flow along the surface of the NACA 643−618 airfoil. The resulting baseline matches the time-averaged LSB from DNS with low levels of random disturbances (Tu = 0.02%). Two major unsteady features are found in the experiment. Low frequency (6 Hz, St = 0.02) content in the shear layer is connected to a large scale ’flapping’ motion, leading to significant periodic change in the reattachment location, causing an expansion/ contraction of downstream half of the LSB. High frequency content is related to the inviscid Kelvin-Helmholtz instability, causing disturbance amplification along the separated shear layer. Finite disturbance growth leads to formation of two-dimensional vortical structures, followed by rapid breakdown to turbulence upstream of mean reattachment. The dominant frequency in the shear layer (centered at 250 Hz, St = 0.88) is found higher than in the DNS (185 Hz, St = 0.671). Linear stability calculations on the matching baseline show a broad peak of unstable frequencies, similar in shape to the experimental results, centered between the peak values found in experiment and DNS. AFC is applied upstream of laminar separation. Initial forcing further upstream in the favorable pressure gradient shows significant strengthening of the two-dimensional roller structures leading to significant reduction in bubble size. All tested AFC in the experiment was successful in suppressing the large scale, low frequency ’flapping’ in the LSB and led to a change in transition dynamics. Notable damping due to the reminder of the favorable pressure, reduces disturbance amplitudes far below the critical amplitude (Acr) suggested by secondary instability analysis (SIA) and rapid breakdown to turbulence similar to the baseline case is observed for all forcing amplitudes. Moving the actuator close to the onset of the adverse pressure gradient increases separation control authority and pressure data suggests the LSB is suppressed at high forcing amplitudes. Time resolved PIV data identifies significant amplitudes of two-dimensional roller structures, especially at low and intermediate amplitudes. Increased forcing amplitudes leads to three-dimensionality in the mean flow causing a peak valley formation predominantly in the streamwise velocity component. Spanwise periodic structures with a wavelength of λz = 1 and a frequency of half of the forced frequency, are observed in all tested cases, with decreasing amplitude at higher forcing amplitudes. Fourier amplitude development suggest an optimal set of forcing parameters at (6 kVpp). Results show a delay in secondary mode amplitude growth and signs of delay of transition in the experiment. This case is compared to numerical results and matches the wavelength of the primary and secondary instability with predictions from LST, SIA and DNS, confirming the same transition dynamics present in the experiment and numerical simulations. Addition of FST in the DNS significantly reduces the delay in transition found in the numerical simulations without FST, explaining the observed differences to the experiment.
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  Dynamic Supervised Principal Component Analysis for Classification

  Zhang, Hao Helen; Ouyang, Wenbo; Hao, Ning; Niu, Yue; An, Lingling (The University of Arizona., 2023)

  Contemporary research places great importance on high-dimensional classification, with dynamic classification problems being of particular interest. Such problems involve situations where the distributions of both classes are not static and change with time or other index variables. This paper proposes a new framework in the context of linear discriminant analysis (LDA) for learning classification decision rules that can adapt to changes with respect to the index variable. Furthermore, many existing works on high-dimensional classification problems make the sparsity assumption about the original feature space, which may not hold in practice. Our framework relaxes this assumption by learning the hidden sparse structure of the data through data rotation. In this work, we propose a new dimension reduction method in the context of dynamic problems. The new method employs a kernel smoothing procedure to determine the suitable direction for dimension reduction. Numerical simulations and real data examples are illustrated to demonstrate the performance of the new approach in terms of both classification accuracy and computational efficiency. One extension to solve non-normal data problems is also included.
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  Improving Nursing Confidence in the Management of Behavioral Health Patients in the Emergency Department

  Reel, Sally; Zimmerman, Jennifer Ann; Edmund, Sara; Velo, Jamie (The University of Arizona., 2023)

  Purpose: Improve nursing confidence in providing care to behavioral health behavioral healthpatients in the emergency department through education and implementation of the Safe Structure template, which addresses identified nursing barriers. Background and Significance: There is substantial growth in the number of behavioral health patients presenting to the emergency department. Evidence shows there are four primary barriers to nursing care of behavioral health patients in the emergency department: physical environment, time constraints, resources, and the overall impact on the process of triage within their role. Nursing learned behaviors, stigma, and attitudes contribute to frustration and fear of caring for the behavioral health population. Nurses report lack of confidence and education in their ability to care for the behavioral health population. Methods: Descriptive quantitative study design using a retrospective post then pre-surveys to measuring nursing confidence levels post education on nursing barriers to care for behavioral health patients and the use of the safe structure template using a five-point Likert scale. Results: Post-the-pre surveys (n=28) were completed. Although findings were not clinically significant (p >.05), there was a slight overall increase in mean confidence levels post education. Pre-education, the nurses who completed the survey reported on average most confident in their ability to provide safe limitations consistent with environment and policies for behavioral health patients (M = 3.21±1.287) and least confident in their ability to create a daily routine for behavioral health patients (M=2.93 ±1.303) Confidence scores from nurses post-education were similar to the pre-confidence results with a slight rise in confidence their ability to provide safe limitations consistent with environment and policies for behavioral health patients 11 (M=3.71±0.854). Paired t test of nursing confidence levels did not reveal statistically significant findings in confidence levels (p >.05). Conclusion: Nurses continue to experience gaps and lack confidence in their ability to care for behavioral health patients in the emergency department. The limited findings of this project support the need for ongoing education, training, and support. The need for streamline education and time to complete is education based on nursing feedback.
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  Surface Metrology Methods for X-ray Telescope Mirrors, Freeforms, and Heliostats

  Chalifoux, Brandon D.; Wisniewski, Hayden James; Kim, Daewook; Schattenburg, Mark L. (The University of Arizona., 2023)

  Modern optical systems require or greatly benefit from freeform or non-rotationally symmetric optics. Increasingly stringent system performance requirements demand high accuracy surface shapes, which drives the need for surface metrology beyond state-of-the-art. This dissertation discusses three projects aimed at filling the need for more accurate or more flexible metrology methods to enable the construction of next generation systems. First is axial shift mapping, a self-referencing metrology technique to measure spaced based X-ray telescope mirrors. X-ray telescopes are composed of nested off-axis parabolic and hyperbolic surfaces, which are difficult to characterize due to their acylindrical shape. I present a shifting Fizeau interferometry technique that decouples contributions from the surface under test in the interferogram from the contributions due to the reference surface. I will present experimental results from using axial shift mapping to characterize a cylindrical mirror. This technique will allow better characterization of X-ray telescope mirrors on the path to a diffraction limited X-ray telescope. Second is the Virtual Ball Probe, an optical profiler being developed at Apre Instruments, Inc. Typically, optical profilers require the probe tip to be normal to the surface. This requires complicated stage geometry and can block certain areas of optics such as steep concave surfaces. The Virtual Ball Probe is designed to measure optical freeforms with surface slopes up to 50 degrees without the need for tilting of the probe tip to be normal with the surface. This allows for simple stage geometry and can accurately measure steep internal optical surfaces. I will discuss the system design and show current system performance. This system fills the need for an accurate yet flexible metrology system for modern freeform optics. Third is Grating Embedded Mirrors for single shot heliostat optical metrology. Commercial concentrated solar power plants are required to accurately monitor the surface slope error and canting error of thousands of heliostats to maintain plant efficiency. We have fabricated test Grating Embedded Mirrors (GEMs), which are float glass mirrors with phase gratings written into the bulk glass using an ultra-fast laser. We use these gratings to direct light to non-specular directions. I placed these grating embedded mirrors in front of a metrology system dubbed Diffractive Auto-Stigmatic Hartmann Camera (DASHCam) to measure the mirror surface slope error. I will compare the results gathered by DASHCam to the surface slope error as measured by a Fizeau Interferometer. GEM’s flexibility of design and ease of measurement is aimed at providing a compact, accurate, and high-speed heliostat slope error metrology system that is robust to harsh environmental conditions for the next generation of concentrated solar power plants. Together, these metrology systems advance the state-of-the-art by increasing flexibility while lowering uncertainty to meet the increasingly stringent requirements of next generation systems.
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  Examination of the Cop Operon Repressor and the Effects of Copper and Zinc in Streptococcus pneumoniae

  So, Magdalene Y.; O'Brien, Henrik Y.; Viswanathan, V.K.; Van Doorslaer, Koenraad M.; Johnson, Michael D. L. (The University of Arizona., 2023)

  Streptococcus pneumoniae is a Gram-positive opportunistic pathogen that typically lives asymptomatically in the human nasopharynx but can cause pneumoniae, meningitis, otitis media, and sepsis. As with any organism living within a host, S. pneumoniae must acquire all its nutrients from the host. One group of essential nutrients is metals. Metals are vital to many cellular processes where they serve as structural components or catalytic cofactors of proteins. While metals are essential for life, they can also become toxic if their concentration is not tightly regulated. Bombardment of bacteria with toxic metals is one of the strategies of the mammalian innate immune system. Two metals that are known for their antimicrobial activity are copper and zinc. The metal environment will change as the bacteria move to different host tissues or experience the host immune response. In order to overcome stresses imposed by excess metal, bacteria encode metal efflux proteins. A notable example is the cop operon, a dedicated copper export system under the control of CopY. CopY is a metal-sensitive repressor that binds more tightly to DNA in a zinc-bound state and releases from DNA upon copper binding. Due to the role of these two metals in CopY regulation and their use as antimicrobials, we studied how changes in their concentrations impact S. pneumoniae. This dissertation explores the transcriptional and metabolic profile under a range of zinc and copper concentrations. In addition, we focused on CopY as we had predicted its regulon would likely expand beyond the cop operon. However, this was not the case, and we now propose an updated consensus operator sequence for CopY. Lastly, we look at how dysregulation of the cop operon affects the cell and we present the early stages of work to predict the CopY regulon across bacteria for which a full annotated genome is available.
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  The RNA Helicase Ded1 Interacts with Cell Cycle Components and Other Key Proteins During Cellular Stress

  Bolger, Timothy; Carey, Sara Brooke; Buchan, Ross; Capaldi, Andrew; Sutphin, George (The University of Arizona., 2023)

  DEAD-box RNA helicases regulate each stage of the RNA life-cycle during gene expression. Ded1 is an essential yeast DEAD-box protein that regulates translation initiation through its effects on mRNA secondary structure and formation of pre-initiation complexes. Ded1 binding to mRNA is not sequence specific, and therefore, it relies on interaction partners for its specificity and regulatory activities during initiation. Stress conditions require large-scale changes in translation that upregulate certain stress response genes but repress most other nonstress-related genes. The target-of-rapamycin (TOR) pathway is a major regulator of these changes, and we have found that Ded1 is a critical mediator of this stress response. Interestingly, in contrast to its role in promoting translation initiation in pro-growth conditions, Ded1 plays an active role in repressing translation upon TOR inactivation. My work focuses on further characterizing the currently unknown interactions critical for Ded1’s repressive function during cellular stress. My results support a physical interaction between Ded1 and Cdc28 in stress conditions that is absent in normal growth conditions, and follow-up results suggest that this interaction may help to coordinate the cell cycle and translation during stress. Along with this clear connection to Cdc28, I conducted a large-scale screen that also shows connections of Ded1 with ATP transport, stress granule formation, cellular localization, cellular trafficking, and mitochondrial translation. All of these could play a key role in understanding how Ded1 fits into the larger picture of translational regulation during TOR inactivation and each subset seen in the annotated GO terms could be an individual area of study for future understanding of stress responses and translation.

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