The graduate and undergraduate research collections share, archive and preserve research from University of Arizona students. Collections include honors theses, master's theses, and dissertations, in addition to capstone and other specialized research and presentation topics.


If you have questions about items in these collections, or are a faculty member who would like to provide students in your program an opportunity to showcase their research, please contact the Campus Repository Services team at repository@u.library.arizona.edu with your request. We look forward to working with you.

Sub-communities within this community

Collections in this community

Recent Submissions

  • Advancements in Light Field-based Laparoscopes

    Hua, Hong; Kwan, Elliott; Liang, Rongguang; Sawyer, Travis W. (The University of Arizona., 2022)
    In the 20th century, rigid laparoscopes revolutionized surgery such that minimally invasive procedures are now the norm. However, these systems only provide surgeons with a two-dimensional (2D) view of the operative field and are subject to two major optical limitations: (1) the absence of binocular vision results in restricted depth perception and (2) the field of view (FOV) is restricted to the local operating region to ensure high image spatial resolution. Performing surgery through a monitor without depth perception is challenging and requires extensive training. Meanwhile, surgical accidents that occur outside of the limited FOV and have gone unnoticed may cause unnecessary trauma to the patient. In this dissertation, two novel optical designs were developed to address the two limitations and further advance this technology. The conceptualization, lens design, prototyping, calibration, and processed results are discussed for both designs. The first design is a programmable aperture light field laparoscope. It was used to investigate and explore the requirements of three-dimensional depth information extraction in a monocular form factor. Compared to state-of-the-art dual objective stereoscopic laparoscopes, this form factor preserves more design volume for transmitting more of the object scene’s light field. A programmable aperture is used to preserve the laparoscope’s conventional high resolution 2D imaging and upon demand, capture the light field. The light field information enables this system to view the object scene from different viewing angles, digitally refocus, and generate depth maps for surgical guidance in post processing. A second-generation design called a tri-aperture monocular laparoscope was then developed to address the depth perception and FOV limitations simultaneously. This system uses two displaced apertures and a custom prism to capture the stereoscopic views simultaneously, which can then be processed to generate absolute depth maps. Meanwhile, a wide FOV for situational awareness is captured via a central third aperture. It provides 2D vision over an area 2x as large as that of the stereoscopic views. Such a system may pave the way towards restoring the binocular and large, foveated FOV qualities of human vision within the minimally invasive surgical setting.
  • The Rise and Fall of Lunar Topography

    Byrne, Shane; O'Brien, Patrick; Pelletier, Jon; McEwen, Alfred; Zega, Tom; Bray, Veronica (The University of Arizona., 2022)
    Landscape evolution on the Moon is driven by a relatively small number of physical mechanisms, making it an ideal laboratory for studying how the surfaces of airless planetary bodies change over time. By investigating the processes that shape topography, predominantly impact cratering, we can better interpret the present-day lunar surface. Decades of remote sensing observations have vastly improved our understanding of lunar topography and constrained the present-day crater formation rate. Coupled with high-resolution remote sensing datasets, numerical models offer a powerful tool for investigating the drivers of lunar geomorphology. In this thesis, I study the evolution of small-scale topography on the Moon across three main areas of focus. I first develop a general-purpose landscape evolution model for airless bodies that is calibrated by tuning the rate of diffusive degradation to match topographic roughness statistics on the maria. Using this model, I simulate the horizontal and vertical mixing of lunar regolith to constrain the timescales of surface exposure during which soil grains are exposed to space weathering effects. Over 3.5 Gyr of surface evolution, grains spend relatively little time at the uppermost surface due to rapid gardening by small impacts, with 98% of regolith tracer particles spending less than 20 Myr within a millimeter of the surface. By mapping the distribution of regolith exposure ages onto existing soil maturity measurements, I find that regolith grains reach a state of chemical maturity after 7-19 Myr of cumulative surface exposure. The same processes that excavate, transport, and bury regolith are also responsible for the erosion of lunar surface features and are therefore crucial for interpreting their ages. I next model the degradation of kilometer-scale craters and quantify the rate of topographic diffusion from small impacts to assess whether micrometeorite gardening has been the dominant erosional mechanism on the lunar surface over the last few billion years. Under commonly used lunar crater production functions, the erosion rate from small impacts is approximately 200 times lower than the value inferred from elevation profiles of degraded kilometer-scale craters on the maria. However, the abundance of fresh craters detected over the last decade is consistent with small impacts dominating the erosion of these features, but only if that abundance continues down to the sub-millimeter scale. My results also demonstrate that, regardless of the magnitude of diffusivity, mass transport from small impacts is fundamentally a nonlinear diffusion process and so are a revision to canonical lunar erosion models. Finally, the landforms resulting from impact processes, i.e., craters, can serve as reservoirs for thermally unstable species that record the delivery of volatiles to the inner solar system. Because of the Moon's low obliquity, small topographic depressions on the floors of large circumpolar craters can be doubly shadowed, shielded from both direct solar illumination and scattered light from nearby sunlit terrain. These locations are among the coldest in the solar system and could hold clues to the origins of the Moon's most volatile deposits. With illumination models applied to high-resolution digital terrain models, I derive the first map of double shadows at the lunar poles. At 30 m/pxl resolution, the total doubly shadowed surface area is 1.47 km$^2$ in the north and 5.37 km$^2$ in the south (~0.04% of singly shadowed area poleward of 85$^{\circ}$ latitude). The largest double shadows, nearly 600 meters across, could potentially be resolved with orbital temperature and reflectance measurements and are high-priority targets for future in situ exploration.
  • "We're All Doing the Best that we Can": A Hermeneutic Phenomenological Study of Novice Principal's Sense-Making of the Transition into the Role of a Principal in the Age of COVID-19

    Bosworth, Kris; Thompson, Kent Alan; Brunderman, Lynnette; Demps, Dawn; Ylimaki, Rose (The University of Arizona., 2022)
    Novice public-school principals face tremendous external pressures (e.g., high-stakes accountability, market forces, legitimization) and internal pressures (e.g., identity (re)construction, identity verification, authenticity) in the enactment of their role as a novice principal. These pressures converge in the dissonance of competing values, exacerbated by shifting roles and identities from teacher to leader. This qualitative hermeneutic phenomenological study on the lived experiences of five novice principals in southern Arizona investigates the meaning-making and sense-making processes of navigating the transition into the principalship at the tension points of neoliberal accountability regimes and social justice values. Informed by frameworks of hermeneutical phenomenology, sociological identity theory, neoliberalism, and social justice leadership, this study uses a hermeneutic phenomenological research design with methodological procedures modeled on interpretive phenomenological analysis, IPA. Additionally, a hermeneutic circle is woven throughout, charting a path of my journey and work as a researcher and participant. The five study participants, representing a variety of identities, personal histories, and lived experiences, provided experiences, values, and motivations that led to several key findings: Novice principals are largely motivated by their personal values of supporting those around them, specifically the importance of student-centered leadership and practice. Novice principals in this study held values that reflected current neoliberal accountability frameworks of monolithic student achievement over social justice leadership values. Novice principal motives, judgments, and experiences shed light on inadequacies of principal preparation programs and district mentoring efforts, which are exacerbated by neoliberal policy and practices.
  • Improving Skin Protection Behaviors in People With Skin Cancer

    Prettyman, Allen; Shaw, Patricia Ann; Kiser, Lisa H.; Autry, Tiffany K. (The University of Arizona., 2022)
    Purpose: This project aims to identify knowledge gaps in skin cancer and skin protection to determine if an educational program focused on skin cancer prevention will result in a greater understanding of skin cancer and adopting new behaviors to prevent skin cancer. Background: The number of skin cancer diagnoses increases significantly every year. The cost of treating skin cancers places a tremendous burden on healthcare costs. Exposure to ultraviolet rays is a known cause of skin cancer. The perception and knowledge of skin cancer vary significantly among patients diagnosed with skin cancer. A knowledge deficit about skin cancer and skin cancer prevention practices can diminish sun protection practices. Method: A 12-question Likert scale pre-questionnaire was administered to measure patient knowledge of skin cancer, risk factors, and skin cancer prevention. The same pre-questionnaire was distributed to a family member/friend. A 15-minute educational PowerPoint with voice-over was then presented. Following the PowerPoint, an open forum of questions/answers was conducted. The same 12-question Likert scale post-questionnaire was administered again to the patient and family member/friend. The Likert scale was utilized because it provides information about patient thoughts and feelings about the topic and can offer insight into patient perceptions. The results of the composite scores of the questionnaire were analyzed. Results: 16 participants, 10 patients, and six family members/friends participated in the session. There was a higher composite score in the patient group following the educational session, except for one question determined to be confounding. Likewise, the overall combined score of the family member/friends increased after the educational session. Conclusion: The educational session was successful, given the increase in scores following the session. It was clear from the scores that knowledge of skin cancer and skin protection measures is understood. What is not clear is if the increased knowledge will ultimately result in the adoption of skin protection behaviors. In future quality improvement (QI) projects on this topic, a follow-up questionnaire could be administered to directly measure the practice of skin protection behaviors of the participants.
  • Base-Activated Lysine Probes and their Utility in Mosquito Larvae Midguts

    Jewett, John C.; Sofka, Holly Anne; Mash, Eugene; Schwartz, Jacob; Riehle, Michael (The University of Arizona., 2022)
    Protein bioconjugation is an essential tool for the deeper understanding of protein behavior and localization. New bioconjugation tools are constantly being developed, increasing the scope of what residues can be targeted and under which conditions, ultimately reporting on the chemical environment of the system. Although many different amino acid residues can be targeted through tailored probes, the most commonly targeted residues are cysteine and lysine due to their high nucleophilic character. Lysine is much more abundant on the surface of proteins, making it an attractive target for robust protein labeling, but can also be problematic when looking to conjugate to other nucleophilic residues. We initially looked for compounds that would act as a reversible lysine probe that could be utilized as a protecting group, masking reactivity in situations where lysine is competing with another residue. In this search, we came across a Meldrum’s acid derivative, equipped with a Michael acceptor that showed reversibility when a single amine was attached. When testing this compound for our own purposes, we found an unexpected, irreversible side reaction at pH 10, which was evident by the loss of our protein band of interest in our gel analyses. Switching to small molecules to identify this side reactivity, we found the Meldrum’s acid derivative was not only capable of accepting one amine but was accepting two amines in high pH environments. This showed that the loss of our protein band was due to oligomerization by the addition of two lysine residues to the probe backbone. We were intrigued by this new reactivity and began characterizing the second amine addition further. Herein, this dissertation will discuss the characterization of the double amine addition through kinetics, water stability, and resilience against reducing agents and other nucleophiles. Our kinetic studies have shown the reaction rate of this second amine addition increases with increasing pH (fastest at pH 10), leading to use of these compounds to label proteins in basic environments within minutes. Furthermore, the single and double amine adducts have shown to be stable across a wide range of pH values, showing excellent stability of both compounds in aqueous systems. Therefore, we envisioned using this reactivity to our advantage and add a single amine equipped with our cargo of choice to the backbone and allow the second amine addition to be a pH dependent reaction with lysine residues, forming a stable, permanent covalent linkage of our cargo to the surface of the protein. We call this series of probes MaMa (Meldrum’s acid amine-reactive Michael acceptor) and these compounds have shown to be easily functionalized with different types of cargo. This dissertation will discuss the design and synthesis of many different MaMa probes, including ones equipped with fluorophores, click handles, and even a fluorogenic system, along with their pH reactivity profiles with proteins. Due to the ease of functionalization and stability, our MaMa probes overcome the limitations of currently existing lysine technologies. To test these probes in a larger system, we chose mosquito larvae, as their midguts have aunique pH gradient ranging from pH 7-11. As our MaMa probes are activated at high pH, we sought to use our probes as a tool to find new protein drug targets to help overcome the resistance mosquitoes are gaining against current control methods. This dissertation will highlight the use of a MaMa probe already equipped with a fluorophore, a fluorogenic system, and our click-ready probes in the mosquito midgut for fluorescent labeling. We have found the importance of using a bright fluorophore for optimal visualization and the need to choose fluorophores that do not cross cellular membranes. Preliminary data does show promise for the use of these probes in mosquito larvae midguts to shed light on new protein drug targets for tailored insecticide development. Finally, this dissertation will discuss attempts at altering the optimal pH necessary for the double amine addition. Since the reactivity of these probes are dependent on the pKa of both the MaMa probe and lysine, we sought to manipulate the pKa of the N-H bond on the MaMa backbone by conjugating aniline compounds equipped with varying substituents of varying degrees of electron donating and withdrawing character. This dissertation discusses the synthesis of this class of aniline probes along with small molecule kinetic data showing reactivity at various pH values. Some of these compounds have shown optimal pH conditions at lower pH values than the first class of MaMa probes, showing promise for labeling at a wider range of aqueous conditions. Additionally, the tuning of the pKa with a MaMa probe containing a propargyl linker will be discussed, as it deviates slightly from the initially determined kinetic trend. Finally, the attempt at altering pKa of the MaMa probes with other nucleophiles, such as hydrazines and hydroxylamines will be discussed. Overall, the MaMa probe series has shown promise for use in many different environments and experimental setups, including in vivo and in vitro. The story of the development and design of these probes along with their uses will be highlighted throughout this dissertation.
  • Novel Strategies for Improved Chronic Neurochemical Measurements In Vivo

    Heien, Michael L.; Seaton, Blake; Aspinwall, Craig A.; Cowen, Stephen L.; Heien, Michael L.; Marty, Michael T.; Pemberton, Jeanne E. (The University of Arizona., 2022)
    The work detailed in this dissertation investigates the challenges of chronic neurochemical measurements in vivo and expands the toolbox of the neuroanalytical chemist working to overcome those challenges. Following the introduction in Chapter 1, Chapter 2 investigates the effects that biofouling has on chronically implanted electrodes, specifically for long-term FSCV. The effects on impedance and reference electrode polarization are explored, and a three-electrode FSCV configuration is designed and employed to mitigate the effects on impedance. Chapter 3 describes the fabrication, characterization, and utilization of an iridium oxide (IrOx) reference electrode. The IrOx reference electrode is shown to perform as well as the conventional Ag/AgCl-wire reference electrode in vitro and in vivo, with the additional benefit of biocompatibility. IrOx has the capability to provide a stable reference potential for chronic FSCV in animals and eventually humans. Chapter 4 details the design and employment of an Ommaya-reservoir-based probe for chronic, minimally invasive collection of cerebrospinal fluid (CSF) from non-human primates (NHPs). The development and optimization of an ion-pair HPLC method with electrochemical detection for neurochemical analysis of the collected CSF is described. The use of this novel collection strategy to investigate the effects of vagus nerve stimulation on CSF neurotransmitter levels is explored. Additionally, the behavioral characteristics of NHPs during the completion of custom-written visual learning tasks involving social hierarchy are studied. Combination of these behavioral observations with CSF neurotransmitter analysis via Ommaya reservoir is feasible and would allow for novel insight into the relationships between neurotransmission, social hierarchy, and learning. Together, the work presented in this dissertation offers novel insights, tools, and strategies toward making accurate and meaningful neurochemical measurements in vivo and paves the way for further advancements in the field of chronic in vivo neurochemistry.
  • Quantum States of Confined Atomic and Molecular Systems in a Basis of Explicitly Correlated Gaussians

    Monti, Oliver L.A.; Coomar, Arunima; Huxter, Vanessa; Mazumdar, Sumitendra; Adamowicz, Ludwik (The University of Arizona., 2022)
    A model for describing the ground and excited states of a hydrogen atom (or amolecule) confined to a soft-wall cuboidal potential energy trap, which allows a small part of the wave function to leak across the boundary, is proposed and implemented. Explicitly Correlated Gaussian (ECG) functions are used to expand these wave functions that are symmetry adapted with respect to the trapping potential. These quantum systems are studied without assuming the Born-Oppenheimer approximation, to achieve highly accurate results. Both the electronic and nuclear densities of all the states are visualized using density plots. This novel method to understand the behavior of a trapped hydrogen atom (or a molecule), when extended to multiple hydrogen molecules, has potential for predicting the cage occupancy of different clathrate molecules used for hydrogen storage, because current data regarding these are highly contested. Since the cage occupancy directly corresponds to the % hydrogen by weight, the work described in the thesis can potentially be used to advance the field of hydrogen storage in clathrates. In addition, the studies shed more light on the confinement of small quantum systems subjected to a partially penetrable potential, which can, when developed further, help in the understanding of several response properties such as polarizability, hyperpolarizability, dipole moment etc under these confinement conditions.
  • Meissner Effect Transistor & Orbiting Astronomical Satellite for Investigating Stellar Systems

    Walker, Christpher K.; Sirsi, Siddhartha; Rieke, George; Potter, Kelly S.; Roveda, Janet M. (The University of Arizona., 2022)
    The Meissner Effect Transistor (MET) is a new device concept with the potential of revolutionizing high-speed computing and communication systems. Essentially all radios, telephones, and computers utilize conventional semiconductor transistors. The operation of conventional transistors is based on modulating the conductivity within a semiconductor by the application of an electric field. The speed and complexity of semiconductor transistor networks is limited by the mobility of charge carriers and the subsequent heat produced within the substrate. The MET has a complementary device architecture within which the conductivity of a superconducting bridge is modulated by an applied magnetic field by way of the Meissner Effect. The speed of an MET is only limited by the recombination time of Cooper pairs within the superconductor. Being a superconductor, there is no Ohmic heating to limit the density to which METs can be packed, potentially allowing the realization of far more powerful CPUs than is currently possible. The speed of the MET also holds the potential of enabling the realization of terahertz amplifiers and oscillators for use in ultra-wideband communication systems1.In this body of work, an analytical model is developed using superconductor theory and a Field Effect Transistor (FET) small signal model. The upper cut-off frequency of MET is derived by determining Cooper pair relaxation time. The noise model is determined by defining noise parameters based on FET equivalent small signal circuit. An analytical model, simulation results, and typical parameters of superconducting bridge are then used to derive theoretical magnetic amplification, followed by detailed discussion on design, and fabrication of test setup, and results. The Orbiting Astronomical Satellite for Investigating Stellar Systems (OASIS) is a proposed space telescope with a 14 m inflatable primary reflector that will perform high spectral resolution observations at terahertz frequencies with heterodyne receivers. The telescope consists of an inflatable metallized polymer membrane that serves as the primary antenna, followed by aberration correction optics, and a scanner that enables a 0.1 degrees Field of View while achieving diffraction limited performance over a wavelength range from 63 to 660 μm. This work covers the optical design of the telescope, parametric analysis of solution space, and metrological solutions for characterizing the surface profile of inflatable membrane optics. Terahertz receiver systems, receiver architecture and optical design are also discussed.
  • Deep Learning with Diversity Imaging from AdaptiSPECT System for Estimation Tasks

    Clarkson, Eric W.; Aguwa, Kasarachi E.; Kupinski, Matthew A.; Furenlid, Lars R. (The University of Arizona., 2022)
    This dissertation introduces a novel machine-learning method in deep learning for medical imaging for a signal estimation task of an adaptive Single-Photon Emission Computed Tomography (SPECT) system. In SPECT, estimation tasks aim to measure or quantify features of the object that has been imaged. Currently, several algorithms exist that estimate the parameters used to describe the signal. Our approach to this problem is to apply a deep convolutional neural network that learns and estimates the signal parameters from a given SPECT image dataset. The developed machine learning model learned and extracted essential features from the input image through supervised learning techniques that minimize the mean-squared error (MSE) loss for the estimation task. The SPECT system used in this work is the modeled adaptive SPECT system called AdaptiSPECT. The image data for the neural network model is acquired from the modeled AdaptiSPECT system's diversity imaging. We vary the imaging data by combining data from all camera positions at once, giving the impression that the cameras in AdaptiSPECT are moving while we collect data. The object data consists of digitally simulated Mouse Whole-Body (MOBY) phantom objects containing variations of spherical lesions (signals). The estimation task is set up to demonstrate realistically with the signal and the object's attributes being variable, as in clinical settings. In summary, we developed and trained a deep convolutional network for a signal estimation task, which is a good estimator across the signal parameters. Root mean-squared Error (RMSE) is the figure of merit used to assess how well the model predicts the parameters that define the signal. The results indicate that this supervised learning network accurately predicts the signal parameters of interest. It also demonstrates that deep convolutional neural networks are practical for adaptive SPECT imaging systems.
  • Intelligent Federated Cyber-physical Systems Experimental Testbeds: Design, Analysis, and Evaluation

    Hariri, Salim; Wu, Chongke; Akoglu, Ali; Cao, Siyang (The University of Arizona., 2022)
    The advancement of computer information technology, Internet services, and Internet of Things (IoT) have made their deployments touch all aspects of our life. In fact, almost all modern engineering systems integrate software components with physical systems (Cyber-Physical Systems) such as washing machines, cooking appliances, autonomous vehicles, drones, power grids, medical devices, and industrial control systems. Cyber-Physical System (CPS) research is active in nearly every industrial field including agriculture, energy management, automotive, smart city, medical devices, and military equipment. CPS produces new functionality in traditional physical systems while at the same time they are adding vulnerabilities and complexities when they are integrated with cyber components. On one hand, CPS makes a huge contribution to national economic growth. For example, the number of self-driving cars, a promising CPS application in transportation, has reached 20.3 million units in 2021. On the other hand, the interconnectivity of cyberspace and physical components face the threats of cyberattacks. Cybercrime has caused more than 6 trillion US dollars loss in 2016 and it is expected to reach 10.5 trillion US dollars annually by 2025. CPS Design requires a comprehensive testing and evaluation methodology to ensure the security, performance, and reliability of the system and it requires financial investment in hardware and software support. A testbed with real-world applications can accelerate the research to increase the security, reliability, and performance of CPS applications and consequently lead to rapid acceptance and deployment of CPS services. Currently, there are many isolated CPS testbeds; however, little research has focused on methods to automatically build a federated CPS testbed. There is a lack of fundamental research on designing methodologies that address the challenges of seamlessly and efficiently composing isolated CPS testbeds and scheduling experiments on heterogeneous CPS testbeds that can be managed by different organizations. We critically need the capabilities to collect and analyze data of a federated CPS testbed to experiment with and evaluate different algorithms for securing and protecting cyber-physical systems and their services under normal and abnormal conditions. Abnormal events can be caused by natural causes, accidents, or malicious actions. Hence, there is an urgent need for designing a federated CPS testbed platform that helps users to experiment with, validate and evaluate different CPS designs that meet their security and performance requirements. The objective of this research is to investigate the design of a cloud platform that can seamlessly compose federated CPS testbeds to facilitate CPS experimentations and data analysis.In this dissertation, we developed an efficient federated CPS testbed platform that we refer to as Federated Cybersecurity Testbed as a Service (FCTaaS). The FCTaaS provides the following capabilities: 1) An efficient method to build a federated testbed using experiment manager service, policy and security services, interoperability service, and web services; 2) Data preparation and machine learning services to support data standardization and provide machine learning algorithms to uncover the hidden pattern of CPS system from CPS traffic; 3) An explainable machine learning service and model-agonistic interpretation approaches that can significantly improve the trustworthiness of ML algorithms. We validated the effectiveness of the FCTaaS by conducting cybersecurity experimentations such as Denial-of-Service attacks and Man-in-the-middle attacks. We evaluated the federated testbed performance by measuring the data transmission latency between geographically distributed testbeds and the integration overhead with the CPU and memory usage in the federated testbed. For validating the federated testbed data preparation and machine learning services, we developed an intelligent video surveillance system and our experimental results show that our model achieves comparable results when compared to the state-of-the-art approaches in spite of using a lower complexity model.
  • A Clonal, Transcriptomic, and Functional Analysis of T-cells Mobilized to Blood in Response to Acute Exercise

    Simpson, Richard J.; Zuniga, Tiffany Marie; Katsanis, Emmanuel; Gustafson, Michael P.; Zhao, Ningning; Stern, Jennifer (The University of Arizona., 2022)
    Regular participation in physical activity induces remarkable health benefits that are associated with immediate (e.g. improved sleep quality, reduction in subjective stress) and long-term effects (e.g. decreased risk and incidence of cardiovascular disease/cancer). Emerging evidence has also determined that physical activity lowers the risk of infection and mortality caused by virus’ such as SARS-CoV-2. Indeed, there is a compelling link between physical activity and the body’s defense system that has prompted the investigation of immune modulation via exercise. Over the last few decades, it has been established that both chronic and acute exercise act as an immune system adjuvant that improves defense mechanisms to reduce the incidence of disease and boost anti-viral activity. One mechanism by which exercise enhances systemic immune function is through the redistribution of leukocytes with each exercise bout; a response that is driven by catecholamines and purported to increase host immune surveillance. The robust exercise-induced mobilization of responsive immune cells (e.g. natural killer cells, CD8+ T-cells) display favorable phenotypes associated with enhanced lytic function against tumor and virus cells, increased trafficking ability, greater response to cytokines, and augmented response to cognate antigens. Technological advances in system biology analysis (e.g. transcriptomics) would provide a greater comprehensive phenotype of exercise responsive cells, including preferentially mobilized T-cell subsets. Therefore, assessment of the T-cell receptor (TCR) repertoire, is vital to deepen our understanding of the beneficial effect of acute exercise on immune cell phenotype and function. Furthermore, utilizing multimodal sequencing analysis would elucidate the transcriptomic changes induced by acute exercise at an individual cell level. In addition, our lab has proposed that exercise-mobilized cells may provide excellent precursors for the isolation and manufacture of several cell therapeutics used to treat hematological cancers. Therefore, it is necessary to determine the capacity by which exercise has application across different cell products utilized for immunotherapy. Consequently, the summation of effects induced by acute exercise over time, may improve immunosurveillance against viral pathogens, providing beneficial anti-viral effects. While exercise has been shown to promote anti-viral immunity, the mechanisms by which exercise can ameliorate symptoms and enhance synthetic immunity against SARS-CoV-2 is still under investigation. Herein, this dissertation explores the effects of acute exercise in humans on T-cell diversity and function, the manufacturing of adoptive cell therapeutic CIK cells, and the COVID-19 vaccine induced immune response. Cumulatively, these data enhance our understanding of the exercise-induced immune changes that occur within T-cells at the clonal and transcriptional level, and provides insight for the translational potential of acute exercise to improve immune responses to viruses and cancer in a clinical setting.
  • Chemical Biology Strategies for the Control of Protein Function and the Interrogation of Cyclin/CDK Interactions

    Ghosh, Indraneel; Andakudi Kesavan, Keerthana; Charest, Pascale; Montfort, William; Jewett, John (The University of Arizona., 2022)
    Protein-protein interactions (PPIs) are ubiquitous in the cell, and it is difficult to overstate their importance in biology. They form the backbone for a majority of signaling pathways, they are required for post-translational modifications, and for transcription and translation. Hence, aberrant PPIs have been implicated in several disease states and they have become important drug targets. A lot of work has gone into understanding the features of PPIs and what drives them with the goals of predicting them a priori as well as using them as tools in biochemistry. In this dissertation, we utilize and interrogate specific protein-protein interactions for different purposes in each chapter. In Chapter 2, we detail our efforts toward developing potent and selective bivalent inhibitors for protein phosphatase 1 (PP1). The bivalent inhibitor strategy involves utilizing the Jun-Fos coiled coil interaction to aid in discovering bivalent inhibitors, a strategy successfully used for protein kinases. Even though we did not discover bivalent inhibitors for PP1, we demonstrate that acid-amide analogs of norcantharidin are unstable and not effective phosphatase inhibitors. Chapter 3 follows our studies toward engineering an orthogonal Bcl-xL/Bad interface for studying biochemistry. We make several rational mutations on Bcl-xL and use a Bad phage-displayed library with the goal of selecting high affinity and potentially selective Bad peptides. In the process, we obtain a Bad peptide blueprint for Bcl-xL and Bcl-xL R139A via phage display. Finally, in Chapter 4, we profile cyclin/CDK interactions in vitro and in cell lysate using the split-luciferase assay. We confirm most of the interactions known to date in this assay, and we discover many new interactions and highlight their potential significance in signaling pathways and in diseases.
  • Intervention Study to Improve Deaf and Hard-of-Hearing Students Morphosyntax Production in Single Sentences and Connected Language

    Rivera, M. Christina; Hasko, Janna; Liaupsin, Carl; Hong, Songye (The University of Arizona., 2022)
    Through a non-traditional approach, the author completed this dissertation with the following components: 1) an introduction to the problem examined, 2) a literature review, 3) a manuscript prepared for submission to a peer reviewed journal, and 4) a reflection of her experiences completing doctoral studies during the COVID-19 Global Pandemic. Although the pandemic changed the process to complete this dissertation, the research began prior to and persisted throughout the pandemic to examine the effect a systematically organized morphosyntax intervention on deaf and hard of hearing (DHH) students’ production of English single sentences and connected language. The author begins by introducing the barriers DHH students face when accessing morphosyntax knowledge (Chapter 1). In the next chapters, the paucity of morphosyntactical interventions for deaf and hard of hearing students (Chapter 2) provides a rationale for the study described in the following chapter (Chapter 3). The final chapter (Chapter 4) is in the format of a lesson plan, describing the author’s educational experiences while reflecting on her journey as a student, researcher, administrator, and mother to complete the requirements of her doctoral program.  
  • Inferring Ecosystem Functioning in a Changing World through the Lens of Eco-Metabolomics

    Tfaily, Malak; AminiTabrizi, Roya; Marty, Michael; Dontsova, Katerina; Carini, Paul (The University of Arizona., 2022)
    Understanding the controls on microbial functioning and community interactions under climate change-induced environmental disturbances is critical to deciphering the global carbon budget and greenhouse gas (GHG) fluxes. Currently, most climate projections rely on various scenarios and models to investigate how altered climate conditions influence the tradeoffs in microbial ecological traits as a function of GHG emissions. However, the complex interactions between biotic (microbially-mediated) and abiotic (environmentally-mediated) processes under climate change posit a challenge for accurate climate change prediction and the development of effective climate adaptation and mitigation plans.In this dissertation, I will describe the results of several experiments designed to understand the impact of environmental disturbances on biogeochemical processes and how they influence the ecosystem output (GHGs) through a combination of field and various experimental manipulations through the lens of integrated multi-omics and biogeochemical analyses. This work revealed that environmental disturbances such as temperature increase, oxygen availability, and nutrient imbalance could significantly influence microbial activity with direct implications for GHG emissions. The results of these studies will help better understand ecosystem responses to changes in environmental conditions and how these changes are translated into GHG emissions. Such in depth-analyses through the lens of multi-omics are necessary to unravel the biological complexity around us and for climate model improvement and enhancement of future climate predictions.
  • Characterization and Exposure Assessment of Polycyclic Aromatic Hydrocarbons (PAHs) Volatile Organic Compounds (VOCs) Particulate Matter 2.5 (PM2.5) and Dioxins Produced by Garbage Burning

    O'Rourke, Mary; Gonzalez Figueroa, Emmanuel; Betterton, Eric; Lantz, Clark; Burgess, Jeff (The University of Arizona., 2022)
    Introduction: Garbage burning is an issue that affects two billion peopleworldwide, contributing to air pollution. Few studies have characterized and quantified the PAHs, VOCs, PM 2.5, and dioxins present in the smoke component in a communal setting. This dissertation aims to characterize the pollutants emitted by garbage burning and to estimate the risk of cancer for those who practice it or are exposed to the smoke produced by burning garbage in rural areas. Methods: Air samples from the smoke component produced by different garbage types were measured in a chamber for PM 2.5 PAHs, dioxins, and VOCs. Cancer risk at multiple distances from the source was estimated using a Gaussian plume model. Ambient air samples were collected as part of the San Carlos Apache Tribe Stop Burning Project. Backyard burning measurements of concentrations of PM 2.5 PAHs, dioxins, and VOCs were measured for the length of the burn. The contribution of garbage-type dioxins and PAH species was assessed via partial least squares regression. Results: The burning of plastics, cardboard, adult diapers and paperincreases the likelihood of developing cancer over a lifetime due to the inhalation of PM 2.5 up to 20 meters away from the burning source in rural areas. Using PLSR, I identified the burning of plastics as the main contributor to the presence of 1,2,3,7,8 pentachlorodibenzofuran,2,3,4,7,8-pentachlorodibenzofuran 1,2,3,4,7,8 hexachlorodibenzofuran, and 1,2,3,6,7,8 hexachlorodibenzofuran. The PAHs associated with plastic burning is of 1-methylnaphthalene, acenaphthylene, phenanthrene, and anthracene. These compounds increase the risk of cancer over a lifetime. Conclusion: I have addressed a gap in the literature regarding the use of real-time monitors and the pollutants produced by garbage burning at the source. Communal garbage burning studies are limited and represent a challenge for environmental health professionals due to many factors that affect the outcome and cannot be easily measured by a sampler. Garbage burning is an issue with sociopolitical ramifications that cannot be addressed by science alone.

    Hamilton, Allan; OLSEN, SARAH ASHLEY (The University of Arizona., 2021)
    Gender differences in conversational interruptions have been examined in a number of different professional areas, such as corporate and judicial settings. Previous studies on conversational interruptions show that a majority involve men interrupting women, and that these interruptions amplify the gender bias and discrimination faced by those in the workplace on a daily basis. However, there is a paucity of information reported on this subject within the field of medicine and, specifically, within undergraduate medical education. Hardly any research has explored gender and conversational interruptions amongst medical students, and between medical students and their instructors. To address this gap, University of Arizona medical students were recorded during their Advanced Cardiovascular Life Support (ACLS) trainings in the College of Medicine Arizona Simulation Technology and Education Center (ASTEC) for analysis of interruptions. Multiple raters watched and scored the video recordings of high-fidelity, mannequin-based simulation scenarios. A coding system for interruptions was developed to evaluate the impact of not only gender, but other potentially influential factors such as the type of interruption and status of the interrupter and interruptee. After analysis of the data collected, it was found that men interrupted women more often than women interrupted men (p<0.05), and more specifically, male students interrupted female students twice as often as the reverse (p<0.02). In regard to interruption type, there were twice as many male-student-on-female-student power interruptions than there were female-student-on-male-student power interruptions (p<0.05). These findings have interesting implications for ways to minimize conversational interruptions in medical simulation training.

    Atwood, Barbara; JOHNSON, MADISON ANNA (The University of Arizona., 2021)
    The current policy response to domestic violence in the United States is built upon a violent-incident model, focusing on isolated, physical instances of abuse. This model fails to address the gravity of emotional abuse, which occurs in long-term episodes of coercive control and infringement upon personal freedom. Domestic violence in familial relationships frequently occurs in the form of emotional abuse, producing long-standing consequences upon the victim’s mental wellbeing and sense of autonomy. European nations, including France, Ireland, and the United Kingdom, have initiated global awareness of emotional abuse through furnishing criminal provisions and sizable punishments against perpetrators. The violent-incident model of abuse in the United States must be reformed to include a universal definition of emotional abuse, which acknowledges that such abuse transpires in recurring, long-term incidents of coercive control. In addition, the United States must address the state-by-state variation in domestic violence law, which produces an inconsistency in legal protections against all forms of domestic violence. This variability of protections across state borders is clearly exhibited in an analysis of domestic violence policy in South Carolina and California, which is illustrated in this paper. It is essential that the United States implements a similar approach to that of European nations by criminalizing emotional abuse as a crime against personal liberty, which affects an individual’s autonomy, decision-making abilities, and mental wellbeing for a prolonged period.

    Jaeger, Elizabeth; ANDERS, ASHLEY ROSE (The University of Arizona., 2021)
    My thesis will focus on the importance of the portrayal of anxiety in children’s picture books and the lack of material that children have access to. This paper will explore the issue and offer insights to why it is important to address this topic and its importance to children. I will also provide data on the books that are available to children in my community of Tucson, Arizona, including the Pima County Library system as well as books available to children in classrooms. Through this investigation I will explore what gaps are still left when it comes to the availability of children’s book’s portraying anxiety. I will also discuss the current portrayal of anxiety and how this helps or hinders children’s and adult’s understanding of anxiety in children.

    Redford, Gary; KLIX, ALYSSA RAE (The University of Arizona., 2021)
    Refrigerant is used widely for maintaining the desired temperature of vaccines, food, and living spaces; However, as the grams of refrigerant a system requires is decreased, the required precision of refrigerant charging is increased, improved methods of supplying refrigerant must be developed to ensure proper operation and efficiency. Providing an accurate refrigerant quantity to any cooling system is critical. Most known methods of refrigerant delivery are done manually, introducing the potential for human error in the refrigerant delivery process. This design improves refrigerant delivery accuracy by automating the refrigerant recharge process and monitoring refrigerant mass. A refrigerant recharging process system was designed and built by the team using electronically controlled pumps, valves, and sensors. The system minimizes human involvement and maintains an accuracy of 40g ±0.10g of refrigerant during delivery. The monitoring system consists of load-cell based weighing stations that continuously collect data on the mass of the refrigerant tanks and medical refrigerator. The system alerts operators of events, such as empty refrigerant tanks needing to be switched out or full recovery tanks of excess refrigerant, ready to be handed off to a third party for recycling.
  • Insomnia and Anxiety

    Grandner, Michael; Kapoor, Ashna (The University of Arizona., 2021)
    INTRODUCTION: Previous research within the field of sleep psychology has shown that there is a relationship between the specific symptoms of depression and insomnia. Through this study, we will try to gain a deeper understanding of the relationship between anxiety and insomnia, particularly the main 7 specific symptoms of anxiety present on the GAD-7, and the daytime, nighttime, and perception symptoms of insomnia. The findings of this research will be able to further guide health professionals in being able to effectively treat patients with this comorbidity. METHODS: Data from the Sleep and Healthy Activity, Diet, Environment, and Socialization (SHADES) study were used, including N=1003 community-dwelling adults age 22-60 from southeastern Pennsylvania. All participants completed the Insomnia Severity Index (ISI) and the GAD7 anxiety questionnaire. The ISI was divided into 3 sections, based on prior work: SLEEP symptoms (difficulty falling asleep or staying asleep or early morning awakening), DAYTIME symptoms (difficulty functioning, noticeable effects), and PERCEPTION symptoms (dissatisfaction and worry about sleep). The items of the GAD7 were assessed separately, including anxiety level, loss of control, worry about many things, difficulty relaxing, restlessness, irritability, and feelings of fear; these were coded as yes/no indicating presence often. Binary logistic regression analyses examined each symptom, with each component of the ISI as predictor (adjusting for the others), as well as age, sex, race/ethnicity and education level. Post-hoc analyses included forward stepwise analyses to determine which components of the ISI contribute to each symptom. RESULTS: SLEEP symptoms were uniquely, independently associated with control (OR=1.09, p=0.03), many worries (OR=1.1, p=0.017), restlessness (OR=1.1, p=0.009), and irritability (OR=1.1, p=0.04). DAYTIME symptoms were uniquely, independently associated with anxiety level (OR=1.3, p<0.0005), control (OR=1.2, p<0.0005), many worries (OR=1.3, p<0.0005), difficulty relaxing (OR=1.2, p=0.004), restlessness (OR=1.3, p=0.001), and irritability (OR=1.2, p<0.0005). PERCEPTION symptoms were uniquely, independently associated with anxiety level (OR=1.1, p=0.03), control (OR=1.2, p=0.001), many worries (OR=1.2, p=0.001) , difficulty relaxing (OR=1.4, p<0.0005), irritability (OR=1.2, p=0.018), and feelings of fear (OR=1.2, p=0.002). In stepwise analyses, fear was predicted only by PERCEPTION symptoms; anxiety level and difficulty relaxing were predicted by DAYTIME and PERCEPTION symptoms; restlessness was predicted by SLEEP and DAYTIME symptoms; and control, many worries and irritability were predicted by all three symptoms. CONCLUSIONS: The results of this study suggest that daytime and perception symptoms of insomnia played a more significant role in the symptoms of anxiety than nighttime symptoms of insomnia. This information offers new insight into this topic and can be used by health professionals to approach this issue differently by focusing on daytime symptoms in the experience of insomnia and overall perception symptoms when treating insomnia and anxiety as a comorbidity.

View more