The UA Dissertations Collection provides open access to dissertations produced at the University of Arizona, including dissertations submitted online from 2005-present, and dissertations from 1924-2006 that were digitized from paper and microfilm holdings.

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Recent Submissions

  • The Role of Sleep in Retention and Generalization of Statistically Learned Language

    Gomez, Rebecca; Sweeney, Lucia; Forster, Kenneth; Lai, Vicky (The University of Arizona., 2020)
    Across the lifespan, learners capitalize on regularities in language to find words in fluent speech and learn grammatical patterns, a process called statistical learning. Much of this research has focused on encoding, and few studies have investigated whether this type of knowledge is long-lasting. Related to retention, sleep promotes stabilization of memories in adulthood, with a growing literature on the benefits of sleep for memory in infants and children. In 5 studies, we examined the role of sleep in retention and generalization of statistically learned language. Specifically, 13-month-olds learned the order of syllables within words, discriminating words with the correct order from words with a reversed syllable order (Exp. 1), but they do not retain this level of detail across a nap (Exp. 2). Looking at the same type of learning in adults (Exp. 3), the group who slept after learning failed to show retention. Further analyses revealed an association between total sleep and memory for syllable order, indicating more sleep after learning related to retention. On the other hand, a group of wakefulness participants remembered which syllables formed words but not their correct order, and correlations showed they retained order after wakefulness if they encoded it during learning. Lastly, we demonstrated that sleep stabilized memory for grammatical patterns in 18-month-olds, promoting specific memory for learned phrases (Exp. 4). Additionally, only infants who napped after learning generalized their knowledge of the pattern to completely novel phrases (Exp. 5). Overall, our data suggest sleep does not benefit detailed representations earlier in infancy, but it promotes specific and abstract memory by 18 months. Furthermore, sleep relates to retention of order in adults, though wakefulness participants also showed retention. Future studies can elucidate how the effect of sleep develops, and whether sleeping after statistical learning in adulthood promotes memory for order more so than wakefulness.
  • School Nurse Workload Tool: A Quality Improvement Project

    Peek, Gloanna J.; Manning Britton, Karen A.; Williams, Deborah K.; McClanahan, Rachel (The University of Arizona., 2020)
    Background: Every student should have access to a school nurse; ensuring students are safe, healthy, and ready to learn. The role has become increasingly complex and changed as the needs of students have evolved. Students who once never survived their complex diseases are surviving, thriving, and attending school. The evolving needs of students increase the workload and challenges confronting the school nurse daily. Purpose: The purpose of this DNP project was to evaluate (retrospective review) of data collected using the workload survey tool (WLST) related to school nurse activities. The workload survey tool was developed around the concepts associated with the National Associations of School Nurses Framework for the 21st Century School Nursing Practice™. Methods: A workload survey tool (WLST) was developed and deployed within a suburban school district as a QI project. Five cycles of data were collected across three school years. The DNP QI project utilized data collected by the WLST project and consolidated WSLT cycle data from 23 nurses across the five cycles, utilizing descriptive analysis examined trends. The mean determined across five cycles for the WLST subcategories included: nursing care related items (39.74%); care coordination activities (10.59%); special education-related activities (17.94%); documentation and record-keeping (11.31%); meetings, presentations, administrative functions (13.48%); and personal necessity leave, sick time, lunch (9.18%). Discussion: The data provides a baseline that we did not have before the project. The data collected provides a picture of the distribution of the nurse workload.
  • Evolution by Ancient Gene and Genome Duplication in Hexapods and Land Plants

    Barker, Michael S.; Li, Zheng; Sanderson, Michael J.; Wiens, John J.; Moore, Wendy (The University of Arizona., 2020)
    Gene and genome duplications have been found across the eukaryotic tree of life. Yet, many aspects of evolution by gene and genome duplications remain unclear, especially ancient duplications. In my dissertation, I focus on the incidence of ancient gene and genome duplication in different lineages of land plants and hexapods, their impact on genome evolution, and the pattern and processes of diploidization following polyploidy. In Appendix A, I use transcriptomes of gymnosperms and outgroups, and a novel phylogenetic algorithm to provide the first comprehensive study of ancient WGD in gymnosperms. In Appendix B, I use over 150 insect genomes and transcriptomes to infer ancient WGDs and other large-scale gene duplications during the evolution of hexapods. In Appendix C, I investigate ancient WGD in ferns from over 140 fern transcriptomes and test the long standing hypothesis on high chromosome number in ferns. In Appendix D, I summarize current studies on the patterns and processes of diploidization in the land plants and provide directions for testing hypotheses and understanding diploidization in the future. As a whole, this work improves our understanding of the mode and tempo of eukaryotic genome evolution and diversity.
  • Advancing and Addressing Uncertainties in Scenario-Specific Healthcare QMRAs with Multidisciplinary Approaches

    Reynolds, Kelly A.; Wilson, Amanda Marie; Beamer, Paloma I.; Verhougstraete, Marc P.; Weir, Mark H. (The University of Arizona., 2020)
    The quantitative microbial risk assessment (QMRA) framework continues to develop to address exposure routes beyond its original application in water quality contexts, especially in its use to address healthcare-associated infections. Exposure models used within these QMRAs must be advanced to incorporate multiple exposure routes and to account for not only the magnitude of microbial spread but also spatial patterns of this spread. In this dissertation, an agent-based model integrated with an exposure transfer model was developed to evaluate the contribution of wheelchairs to spatial contamination spread in a healthcare facility and exposures to subsequent patients riding the wheelchair. This integrated framework provided insights into emergent patterns of exposures for subsequent riders on contaminated wheelchairs and spread throughout the facility. Main findings include that disinfection of wheelchairs in between patients may protect future riders under low contamination conditions, and that the frequency of traveled paths is related to heterogeneity of fomite contamination throughout a facility. In analyzing emergent behaviors, the number of wheelchairs had a positive relationship with number of contaminated patches over a specific concentration threshold. Cleaning wheelchairs in between patients weakened this relationship. While the integration of multiple modeling approaches is a future direction of QMRA, uncertainty in mechanisms of microbial spread still need to be addressed in order to improve accuracy in integrated model frameworks. For example, in this work, the exposure transfer model used in this integrated model includes the assumption that transfer occurs according to a concentration gradient. This was evaluated experimentally with bacteriophage transfer efficiency studies and supported the hypothesis that transfer efficiency varies by a ratio of the concentrations on the fingertip and surface prior to contact. These experimental data were then used in an Approximate Bayesian Computation (ABC) analysis to compare two microbial transfer models in their ability to explain the experimental data and offer insights regarding swabbing efficiencies and transfer efficiencies that are challenging to measure experimentally. This analysis demonstrated that swabbing efficiencies and direction-specific transfer efficiencies “balance” exchanges between the fingertip and surface in predicting after-contact concentrations on the fingertip or surface. Future research involves furthering the integration of exposure model frameworks to account for complex transmission systems, especially those that incorporate spatial human behavior. This also necessitates further experimental and mathematical evaluation of these models to advance not only our ability to model complex built environment systems but also to improve our accuracy in estimated exposure and health outcomes.
  • The Choral Works of John Joubert: A Conductor’s Guide

    Chamberlain, Bruce; Schauer, Elizabeth; Peterson, Tom; Mugmon, Matthew (The University of Arizona., 2020)
    Over a career spanning seven decades, John Joubert (1927–2019) wrote operas, symphonies, concertos, oratorios, and other instrumental works for large forces, chamber ensembles, and soloists. Running as a thread through his output is an extensive body of work for chorus, which is at once varied—sacred and secular, sprightly and contemplative—and yet unified by the composer’s set of signature stylistic traits. This body of work draws upon influences and techniques used by composers in both traditional and avant garde camps (though these terms are laden with subtext and connotation, this study will use them because they were the most commonly used terms by Joubert). While the divide between these composers grew in the post-World War II era, and attention and funds increasingly flowed to composers firmly in one idiom or the other, Joubert followed Benjamin Britten (1913–1976) and other composers who did not embrace either extremity but sought a middle path. Later in Joubert’s career, changing taste in art music culture was met with a correlative increase in interest in and recordings of his work. This study explores Joubert’s works for chorus, puts them in context musically and historically, and provides a resource and guide for those who perform them. Given the depth and breadth of this body of work, it is necessary to narrow the scope to his choral works that are unaccompanied, or accompanied only by a keyboard instrument. This omits many longer works, including some like the English Requiem (2010) that are intriguing both for their musical content and their connections to tradition, but these compositions may serve as subjects of future study.
  • Commissioning Fizeau Interferometry with the Large Binocular Telescope Interferometer

    Morzinski, Katie M.; Spalding, Eckhart Arthur; Hinz, Philip M.; Rieke, George; Close, Laird; Apai, Dániel; Males, Jared (The University of Arizona., 2020)
    This work demonstrates the use of two different observing modes with the twin apertures of the LBT. One pointing mode involves the incoherent juxtaposition of two filled-aperture PSFs to perform differential photometry in the thermal infrared. This is "wall-eyed" pointing, which is used to perform differential photometry on three sets of test targets. To test the possibility of applying this to the study of atmospheres of low-mass objects, one of the targets involves an exoplanet transit in front of its host star, and another involves a secondary occultation. Though the photometric precision in differential mode is increased compared to single-aperture mode, it remains limited by line-of-sight systematics possibly stemming from water vapor variations. The remainder (and majority) of the thesis involves the long-anticipated Fizeau mode---the coherent and multiaxial combination of the LBT beams. Compared to a single filled aperture, the Fizeau mode can generate a PSF that can in principle increase the resolution by a factor of ~3 along the long baseline. A number of technical challenges are described, and a science dataset of a nearby star in Fizeau mode is reduced in a first-ever trial of this mode to perform high-contrast imaging. The PSF remains unstable, particularly in phase. A new codebase was written to perform the requisite angular differential imaging of a Fizeau PSF with highly time-dependent optical aberrations. I describe the results of this process and outline avenues of possible future work.
  • Protocols and Algorithms for Harmonious Coexistence Over Unlicensed Bands in Next-Generation Wireless Networks

    Krunz, Marwan; Hirzallah, Mohammed; Lazos, Lucas; Li, Ming (The University of Arizona., 2020)
    The unlicensed spectrum offers tremendous opportunities for mobile network operators (MNOs), whose traffic can be offloaded from licensed bands to unlicensed ones. To realize these opportunities, three new technologies have been proposed: LTE-Unlicensed (LTE-U), 4G LTE Licensed-Assisted Access (LAA), and 5G New Radio Unlicensed (NR-U). Although unlicensed spectrum seems attractive to MNOs, its access is fraught with many challenges that need to be addressed. These include coexistence with legacy unlicensed technologies such as Wi-Fi and Bluetooth, fairness in channel access, and supporting a desired level of quality of service (QoS) in a shared-spectrum environment. Addressing these challenges is critical for achieving harmonious coexistence between various technologies. In this dissertation, we design resource management algorithms and channel access protocols to overcome these challenges. We mainly focus on issues arising in three scenarios: (1) coexistence between Listen-Before-Talk (LBT), e.g., Wi-Fi, and non-LBT systems, e.g., LTE-U, (2) coexistence within LBT systems (e.g., 4G LTE LAA, 5G NR-U, and Wi-Fi), and (3) resource allocation for LBT systems sharing a common network infrastructure (e.g., 5G NR-U and Wi-Fi). For the first scenario, we develop a cross-technology detection scheme that allows LBT devices to concurrently transmit over and sense the channel, a.k.a., full-duplex (FD) sensing. This will reduce the impact of collisions between LBT and non-LBT devices. LBT devices can then detect collisions with non-LBT devices earlier, allowing them to react properly by pausing transmission and preventing interference. We develop a framework based on Partially Observable Markov Decision Process (POMDP) that allows FD-enabled LBT devices to mitigate interference generated by non-LBT devices. By following a POMDP policy, LBT devices can jointly adapt their transmission rates and duplex mode based on their belief about interference caused by non-LBT devices. Although enabling LBT devices with FD capabilities helps mitigate cross-technology interference, it makes the provisioning of QoS harder. Traditional QoS provisioning frameworks are designed to support half-duplex operation. Accordingly, we present a framework, called AFD-QoS, for provisioning of QoS in an FD network. AFD-QoS incorporates FD-based Enhanced Distributed Channel Access (FD-EDCA) and FD-based Block Acknowledgement (FD-BA) schemes to achieve its goals. For the second scenario, we investigate the fair setting of LBT parameters, e.g., contention windows, airtime, etc., and the harmonious setting of their sensing thresholds (STs). To support different QoS applications, e.g., voice, video, etc., LBT systems define multiple channel access classes with different settings. To study the interplay between these classes, we develop a Markov-based model and derive key performance measures, including probability of successful transmission, average channel access delay, and effective throughput for each class. We first discuss how the heterogeneous setting of channel access parameters across traffic classes leads to unfairness in channel access. Our study pinpoints some settings that need to be optimized to ensure fairness. We then discuss the heterogeneity due to having fixed and asymmetric configurations of ST values among different devices, which results in different sensing floors and gives rise to hidden and exposed terminals. To reduce collisions and improve frequency reuse, we investigate distributed learning solutions for adapting the ST values based on the observed environment. We develop a novel clustering-based multi-armed bandit framework, called Sense-Bandits, to perform such adaptation in real time, aiming at boosting the overall network throughput. Finally, we investigate the challenges arising when MNOs run 5G NR-U services over a shared network infrastructure. Ensuring fairness and efficient allocation of network resources among MNOs are challenging due to communication overhead and privacy concerns. To resolve these issues, we introduce a novel framework, called MatchMaker, which extends the 3GPP network sharing model to a cloud-based 5G NR-U system. We define new interfaces and messages for facilitating private NR-U operation over managed and shared network infrastructure. According to MatchMaker, the network manager runs a Graph Coloring Evolution (GCE) algorithm to learn potential interference between operators and match them with channel resources.
  • Discriminating Changes in Protein Structure Using Tyrosine Conjugation

    Schwartz, Jacob C.; Moinpour, Mahta; Montfort, William R.; Horton, Nancy C.; Buchan, Ross (The University of Arizona., 2020)
    Exploration of protein structure by its solvent-accessible surfaces has been widely exploited in structural biology. Amino acids most commonly targeted for covalent modification of the native folded proteins are lysine and cysteine. For the first time, the present study has leveraged ene-type chemistry targeting tyrosine residues to discriminate those solvent-exposed from those buried. We find that 4-phenyl-3H-1,2,4- triazole-3,5(4H)-dione (PTAD) can conjugate the phenolic group of tyrosine in a manner heavily influenced by the orientation and depth of the residue with respect to the protein surface. We developed a strategy to investigate protein structure by analyzing PTAD conjugations with free tyrosine, protein structure, and found it adaptable to a wide range of analytic technologies, including fluorescence, chromatography, and mass spectrometry. This study shows how the established tyrosine-specific bioconjugation chemistry can be used as an analytical tool to distinguish the conformational states of a protein where traditional structural approaches are limited. Among limitations of the traditional structural techniques, are studies of low complexity proteins, such as tyrosine rich FET proteins, with essential cellular functions in transcription and DNA repair, and mutations associated with some neurodegenerative diseases (Schwartz et al., 2015a). The N-terminal low complexity domains of FET proteins have the ability to drive the formation of non-membrane bound cellular organelles, also known as granular bodies, through a process referred to as phase separation. Low complexity proteins are typically intrinsically disordered or lacking in rigid secondary structure elements. This renders the most popular NMR and X-ray crystallography methods incapable of providing high-resolution structure data and elevates the potential for a new method of structural analysis to reveal a wealth of otherwise unattainable information.
  • The Detection and Characterization of Transiting Exoplanets

    Griffith, Caitlin; Pearson, Kyle; Swain, Mark; Koskinen, Tommi; Barman, Travis; Apai, Daniel (The University of Arizona., 2020)
    The existence of worlds beyond our own has been a subject of fascination and inspiration since the times of the ancient Greeks. The first exoplanet discovery in Wolszczan and Frail 1992 led to a revolution that sparked the scientific community to develop new space missions (e.g. Kepler, TESS and ARIEL) and instruments (e.g. HARPS, GPI, etc.) purely dedicated to exoplanet science (Borucki et al. 2010; Ricker et al. 2015; Tinetti et al. 2016; Mayor et al. 2003; Macintosh et al. 2006). The thousands of exoplanets discovered over the past decade have mostly been Earth-sized planets around low-mass stars. The potential of habitable planets drives the field towards detailed spectroscopic observations to better characterize their mass and/or atmospheric composition. Planetary search surveys from the ground and space are expected to detect more exoplanets orbiting nearby stars, which is conducive for atmospheric characterization. This dissertation addresses two main questions, how can we identify which stars have transiting exoplanets and what are the atmospheres of these planets made of? Currently, the transit method of detection is one of the most successful tools for probing the size and orbits of planetary systems. However, for Earth-sized planets the signal is small (∼100 ppm for a Sun-like star) and comparable to the photometric noise from the host star (∼0.1-1%). The manual interpretation of such data is labor-intensive and subject to human error, the results of which can be difficult to quantify. I present a new method for combining existing techniques with machine learning in order to expedite, automate, and increase the robustness of processing large observational data sets. The technique is applied to Kepler and TESS data where I find evidence for 3 new multi-planet systems. The second part of my dissertation focuses on atmospheric characterization where I use spectroscopic observations to search for signatures of Na in the hot-Jupiter XO-2b.
  • Patterns of Islamist Mobilization in the Muslim-Majority World

    Ghosn, Faten; Curtis, Justin Glenn; Schuler, Paul; Willerton, John P.; Cyr, Jennifer (The University of Arizona., 2020)
    This dissertation addresses two interrelated questions about mobilization and electoral politics among Islamists in the Muslim-majority world. A fundamental question in the study of Islamist political parties regards the conditions under which they will fully participate in electoral politics and integrate into electoral regimes. Because many—perhaps even most—Islamist parties emerged out of a broader social and religious movement in non-democratic political environments; there was little incentive to publicly declare allegiance to democratic norms and institutions when ruling elites made political democracy an impossibility. When opportunities for electoral participation emerged in the global shift toward more electoral regimes—if not democracies—Islamist groups had to make decisions about forming parties and how intensely to participate in elections. Chapter 2 reviews several expectations about party-level and regime-level inputs that may have caused Islamist parties to limit their participation in elections. I then rely on a set theoretic approach to test the relevance of each of the causal pathways. I find strong support for the hypothesis that the combination of parties that grew directly out of social and religious movements rather than merely adopting an association with these movements after their formation in combination with uncompetitive electoral institutions are nearly sufficient for parties to avoid fully participating in national elections. These results point to the relevance of this—their antecedent organization structure—highly salient and frequently overlooked dimension of variance among Islamist political parties. Over the last three decades both Islamist political parties and Islamist terrorist organizations have proliferated across the Muslim-majority world. Non-democratic regimes often argue that restrictions on Islamist political parties are necessary to curtail levels of Islamist violence, while these parties argue that without opportunities to participate, Islamist supporters may be more likely to turn to violent forms of mobilization. Scholars generally agree that the freedoms of association granted under political democracy will facilitate the organization of violent groups. In chapter 3, I present a theoretical discussion, based on the demands and preferences of Islamists themselves, that argues that opportunities for governance at the subnational level will condition this effect on levels of Islamist violence. Drawing on data from states where Islamist parties are organized and utilizing disaggregated measures of democracy, this hypothesis is tested quantitatively. I find support for the notion that only when there are not opportunities for subnational governance are increasing levels of free association rights are associated with increasing levels of violence. When there are opportunities for subnational governance, there is no relationship between free association rights and levels of violence. These findings highlight the demands of Islamist parties and the potential of subnational governance as a means of disincentivizing Islamist violence. The relationship between democratization and Islamism has traditionally been analyzed through an examination of either Islamist civil society or violent Islamist groups; the former, the argument goes, needs to “moderate” and the latter needs to “deradicalize”. However, Islamist civil society and Islamist violent groups compete over control over the same legitimizing symbols in Islam as well as over support from individuals sympathetic to Islamist ideas in both the populace and the state. Chapter 4 is an extended case study of the process of democratization in Indonesia and the varying relationships that Islamist civil society and violent groups had with each other and the state through this process. I divide the process of democratization into three pieces: the pre-transition phase, the initial transition phase, and the consolidation phase. I then trace the evolution of Islamist civil society into normalized political parties and the rise and demise of violent Islamist groups through these three phases.
  • Johann Schein: An Analysis of Rhetoric and Word Painting in the Diletti Pastorali Collection

    Schauer, Elizabeth R.; Dunsavage, Angelica Marie; Brobeck, John T.; Felipe, Miguel A. (The University of Arizona., 2020)
    The focus of this document is the use of rhetoric and word painting in the German madrigals of Johann Hermann Schein (1586-1630), particularly those in his Diletti pastorali Hirtenlust collection of 1624. As both the poet and composer of this collection, Schein displays a synthesis of Italianate and Germanic styles. Schein’s texts feature pastoral and mythological characters common in the works of Torquato Tasso (1544-1595), Giovanni Battista Guarini (1538-1612), and Francesco Petrarch (1304-1374). Like Claudio Monteverdi (1567-1643) and Heinrich Schütz (1585-1672), Schein combines mannerist word painting and rhetoric in these works. These Italianate features are especially interesting considering Schein’s lifelong residence in Germany. As a Leipzig church musician and predecessor to J.S. Bach, Schein is often recognized for his sacred compositions. His secular works, however, remain under-researched and under- performed in comparison. Schein’s madrigals provide a glimpse of popular musical trends in 1620s Leipzig and demonstrate the Italian madrigal’s popularity in Germany during Schein’s lifetime.
  • Aspects of Microalgae Biology Related to Cultivation for Biofuel Production: Microbial Phycosphere Interactions and Adaptive Physiology

    Brown, Judith K.; Steichen, Seth; Baltrus, David; Hurwitz, Bonnie; McMahon, Michelle; Schmidt, Monica (The University of Arizona., 2020)
    The interest in microalgal cultivation for the production of renewable biofuel and other applications has grown significantly over the last several decades in close correspondence with increasing concerns over global climate change and energy security. These unicellular organisms fix atmospheric carbon photosynthetically while offering a wide range of desirable characteristics that are not found in other categories of feedstock crops. Owing to their ubiquitous distribution in nature, microalgae have evolved into species capable of growing at extremely rapid rates under many varied conditions and to synthesize very high concentrations of lipids upon induction. Screening, identification, and characterization efforts have yielded promising results, projecting certain algal strains to be capable of producing significantly more biodiesel per unit of land than any other studied crop. There remain challenges to economical large-scale production at each aspect of the process including strain selection/optimization, improving cultivation, harvesting biomass, and product extraction. Life-cycle analyses and modeling predictions have concluded that cultivation in outdoor, open style reactor systems are critical to meet national and international goals for increased biofuel usage. This type of system not only exposes the target algal strains to unpredictable environmental conditions, but also exposes them to other microorganisms, whose total interactions result in a phycosphere, or zone of microbial influence. The relationships between algae and their associated phycosphere members range from mutualistic to parasitic, depending on the relative abundances of species and on environmental factors. Understanding how these relationships affect algal growth in their industrial context provides guidance for successful manipulation of microbial consortia for maximum productivity. Minimization of inputs is an important goal, regardless of the growth system chosen. Several algal strains have been manipulated by adaptive laboratory evolution to produce greater amounts of biomass, carotenoids, lipids, and other products without additional nutrient inputs. This process is not only capable of producing novel strains with valuable characteristics, but also offers an opportunity to dissect the adaptive physiological and metabolic mechanisms employed by the algae. Here I focus on aspects of algal biology related to improving and stabilizing growth characteristics for optimizing biomass cultivation. The experiments described herein follow two major themes of algal biology. First, the effects of bacterial phycosphere members are considered from the perspectives of overall community ecology and individual species’ relationships to the host algae. Second, reflections on the adaptability of microalgae to oligotrophic conditions to determine factors allowing for more efficient macronutrient metabolism and their impacts on lipid content intended for conversion to biodiesel. To determine the influence of bacterial members of the phycosphere on algae grown in open, outdoor, reactors at an industrial pilot scale, my coauthors and I used high throughput sequence data from 16S rRNA V4 region amplicons to characterize complete prokaryotic assemblages and their relationships to a variety of important environmental and engineered factors. These experiments were conducted with collaborators on the Regional Algal Feedstock Testbed (RAFT) project, which operated a variety of open raceway style reactors to test aspects of microalgae cultivation in the Southwest United States. The primary algal production species used during the project was a strain of the chlorophyte, Chlorella sorokiniana (Shihira and Krauss 1965), designated DOE1412. Regular sampling across 41 growth cycles spanning two separate seasons yielded one of the most comprehensive surveys of prokaryotic phycospheres in mass algal cultures to date. Longitudinal analyses of taxonomic assignments of 16S rRNA sequence data revealed that phycosphere diversity increased significantly with the amount of time in outdoor culture, and that there were consistent patterns associated with the stationary, growth, and death phases of algal cultures. Furthermore, computation of a Health Index metric that compared observed algal growth to model-predicted growth identified strong positive correlations with bacteria belonging to the Burholderiaceae and Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium clade, determined by rank-based multinomial regression. The results also confirmed the predominance of the algicidal bacteria, Vampirovibrio chlorellavorus, during the summer months, and that a benzalkonium chloride treatment regimen suppressed its growth along with several other bacterial taxa. To understand the molecular mechanisms by which an algal strain adapted to more efficient growth under phosphorus limited conditions, my coauthors and I collected periodic transcriptomic and lipidomic data from algal cell populations subjected adaptive laboratory evolution in continuous cultures. The green microalgae, Auxenochlorella protothecoides, was grown in continuous culture with 100 times less inorganic phosphate (Pi) than the amount in the typical growth media for more than 41 generations. The resulting algal populations grew more rapidly in low Pi media than unadapted progenitor cells at an average maximal rate of 0.72 d-1 and 0.54 d-1 respectively. The fatty acid (FA) profiles of the adapted cells shifted minorly from the wild type A. protothecoides, with relative increases in one monounsaturated species being compensated by decreases in another, indicating very little effect on the biodiesel product. The mechanisms by which the algae adapted to low Pi growth were typified by an early and late stage wherein transcriptomic and lipid profiles differed significantly in samples collected prior to ~ 11 generations compared to results after ~ 34 generations. The short-term changes in gene expression were associated with shifts in major metabolic pathways including carbon metabolism, oxidative phosphorylation, glycolysis, and gluconeogenesis. By comparison, certain transcripts showing decreased expression, reflected increased fatty acid turnover, and a stable decrease in photosynthesis-related gene expression. The most significant changes in lipids occurred in the glycerolipid class with adapted populations containing 306% monogalactosyldiacylglycerol (MGDG) and 189% sulfoquinovosyldiacylglycerol (SQDG) of the amounts in unadapted cells by the final sampling time point at 41 generations after fluctuating throughout the experiments. These results provided insights into some basic variations of low Pi adaptation displayed by A. protothecoides compared to other algal species and to plants that could be utilized for optimization of other production strains. Lastly, my collaborators and I investigated the viral-like element, prophage/plasmid content, of available genomes of a pernicious bacterial pathogen of a biofuel production microalgae species using comparative genomic approaches. By combining three prophage identification algorithms, we were able to identify 14 putative integrated prophage regions among the three currently published Vampirovibrio chlorellavorus bacterial genome assemblies. In addition to the previously described circular plasmids in the genome assembly of an isolate collected from a Ukrainian lake, Vc_UKR, at least one prophage was found in all genomes. Because the other two assemblies were derived from isolates collected in an algal biofuel production reactor in the Southwest United States, these findings implicate a heterogenous distribution of viral-like elements likely contributing to fitness and pathogenicity of V. chlorellavorus populations. The Vc_AZ2 and Vc_UKR both contained prophage regions homologous to genomic regions of Melainabacteria sp. nbed3b74 (GenBank; GCA_902168245.1), a closely related soil borne bacteria found to contribute to disease suppression in plant rhizospheres. Additionally, functional predictions indicated that prophage regions contained genes involved in pathogenicity, including 10 toxin-antitoxin system genes, 19 transcriptional regulators, and other bacterial virulence factors. One of these was the identification of TonB-dependent receptor (TBDR) genes that are known to require several accessory genes to complete their function of collecting extracellular iron across the outer bacterial membrane. Intriguingly, homologs to TBDR-related genes were found in chromosomal locations. These findings represent the first reports of predicted MGE involvement in the pathogenicity of an algicidal bacteria.
  • VECSEL Frequency Combs for Mid-Infrared Spectroscopy

    Moloney, Jerome V.; Rockmore, Robert; Norwood, Robert A.; Jones, Ronald J. (The University of Arizona., 2020)
    Frequency combs with high repetition rates above 1 GHz offer a number of advantages over more common Mhz combs, such as higher power per comb line, more easily resolvable comb teeth, and higher time resolution for sensing applications. Vertical external cavity surface emitting lasers (VECSELs) are a type of semiconductor laser that can be readily modelocked with GHz repetition rates. In this dissertation, I will present the development of these VECSELs into fully stabilized frequency combs operating in the mid-infrared spectral region around 3 µm. This region is of special interest because of the strong absorption exhibited by many gas molecules at these wavelengths, making such sources attractive for remote sensing and gas spectroscopy applications. I will first present the development of these VECSEL sources into reliable GHz oscillators and some of the benefits and limitations of these devices. Next, I will go into detail of the development of a fully stabilized mid-infrared frequency comb using a VECSEL oscillator and describe its performance characteristics. This comb produces over 300 mW of output power from 3.0-3.5 µm and has zero offset frequency allowing for full stabilization with a simple repetition rate lock. The stability of this comb was leveraged for comb resolved spectroscopy using a virtually imaged phased array (VIPA) spectrometer that was used with a native GHz frequency comb for the first time. The capability of this system for high resolution time resolved gas spectroscopy measurements was demonstrated. The spectrometer can resolve the individual comb teeth, which leads to resolution and accuracy that is limited by the comb linewidth instead of the spectrometer resolution.
  • Simulating Planetesimal Formation in the Kuiper Belt and Beyond

    Youdin, Andrew; Li, Rixin; Rieke, George; Kratter, Kaitlin; Apai, Daniel; Eisner, Joshua (The University of Arizona., 2020)
    A critical step in planet formation is to build super-kilometer-sized planetesimals out of dust particles in gaseous protoplanetary disks. The origin of planetesimals is crucial to understanding the Solar System, exoplanetary systems, and circumstellar disks. In this thesis, I present my work on exploring and better understanding promising planetesimal formation pathways with extensive numerical modeling and robust statistical analyses, with a main focus on the streaming instability (SI), a mechanism to aerodynamically concentrate solids in disks and trigger gravitational collapse to form planetesimals. The first study focuses on the numerical robustness of the SI, where I demonstrate that the nonlinear particle clumping by the SI is robust to various numerical setups. In the next study, I carry out the SI simulations including particle self-gravity with the highest resolution to date, which produces a broad and top-heavy initial mass distribution of planetesimals. Necessitated by analyzing my simulations, I have built and published an efficient clump-finding code, PLAN, capable of robustly identifying and characterizing self-bound clumps. I then present the highlights from analyses of the demographics of planetesimals. I first apply a maximum likelihood estimator to fit a suite of parameterized models with different levels of complexity to the simulated mass distribution. I show that our simulations produce different mass distributions with different aerodynamic properties of the disk and participating solids. I will report the first evidence for a turnover in the low mass end of the planetesimal mass distribution. With PLAN, I also find that the clumps in our simulations possess excess angular momenta that might explain why all planetesimals formed as binaries/multiples and the high binary fraction among Cold Classical Kuiper Belt Objects. Furthermore, the predicted binary orbits show a broad inclination distribution with 80% of prograde orbits, excellently matching the observations of trans-Neptunian binaries. Finally, I conclude with the key results in this thesis and discuss the future directions for planetesimal formation studies, with some pioneering results from my on-going work.
  • A New Edition of Anlun Huang's A Requiem in Chinese with an English Translation and International Phonetic Alphabet Transliteration

    Chamberlain, Bruce; Brobeck, John; Luo, Yujia; Schauer, Elizabeth (The University of Arizona., 2020)
    Anlun Huang’s (b. 1949) A Requiem in Chinese is the only large, unaccompanied,mixed-voice choral requiem in Chinese history. It was completed in May 2004 and the premiere was conducted by the composer on September 12, 2004. Despite the fact that a large unaccompanied requiem in traditional Western style with Chinese liturgical text is unique in both Western and Eastern music of the twenty-first century, the work has received little international attention and only a small number of performances. It is my belief that the difficulty of Mandarin pronunciation and the understanding of the Chinese text are the main obstacles to learning and performing this piece for non-Mandarin-speaking choirs. I have provided an English translation of the text and a new edition of the work featuring an International Phonetic Alphabet (IPA) transliteration of the text, making the work more accessible and allowing it to be widely studied and performed.
  • Evaluating Soil Microbial Communities and Foliar Nitrogen Across Complex Landscapes: Insights into Terrestrial Biogeochemical Cycles

    Gallery, Rachel E.; Farella, Martha; Breshears, David D.; van Leeuwen, Willem J.; Mitchell, Jessica (The University of Arizona., 2020)
    Photosynthesis and decomposition are two fundamental and interconnected components of terrestrial biogeochemical cycles, and large variations in Carbon model projections are due to uncertainties surrounding these parameters. Although foliar Nitrogen and soil microbial activities exert key constraints on plant productivity and decomposition, these variables are seldom included in modeling endeavors because we lack robust methodologies to estimate these parameters across ecosystems. This research demonstrates how advances in remote sensing technologies and machine learning analytical approaches can overcome this limitation and help us understand the distribution and controls of foliar Nitrogen and microbial community biomass and exoenzyme activities across large spatial areas. I used airborne imaging spectroscopy data, provided by The National Ecological Observatory Network (NEON), combined with 475 samples collected across the U.S. to develop generalizable models for the prediction of foliar Nitrogen. Results show higher accuracy (R2 = 0.65) predictions of this key ecosystem parameter across disparate ecosystems than any other existing methodology. Furthermore, many of the wavelength regions identified as important predictors of foliar Nitrogen are associated with regions known to provide information regarding plant growth type and photosynthetic parameters. I then present how foliar Nitrogen influences decomposition dynamics at The Santa Rita Experimental Range (SRER), a dryland site undergoing woody shrub encroachment. In this analysis, I identified the main drivers of soil microbial biomass and exoenzyme activity across plant cover types, and determined that the strength of plant cover effects depends on various state factor controls such as precipitation, topography, and parent material. I used machine learning to link trends in foliar Nitrogen and other remote sensing derived aboveground data products to belowground soil nutrient and microbial community dynamics. This resulted in one of the first high-resolution, complex landscape-scale maps of soil microbial characteristics. These landscape scale predictions of soil microbial communities can help us understand decomposition dynamics across spatial scales that have not previously been possible. These results highlight that high-resolution predictive mapping of foliar Nitrogen and soil microbial biomass and exoenzyme activities can inform key, difficult to measure, constraints on photosynthesis and decomposition in drylands and could also be applied more broadly to other systems.
  • Photoelectron Imaging of Molecular Anions

    Sanov, Andrei; Wallace, Adam; Monti, Oliver; Stafford, Charles; Sandhu, Arvinder; Brown, Michael (The University of Arizona., 2020)
    This dissertation employs photoelectron imaging spectroscopy to explore properties of molecular electronic structure of heterocyclic aromatics. First, photoelectron angular distributions of these molecules are modeled to gain insight into their stability and electronic structure. The model is adapted to include the local charge density of anionic aromatics and find trends in photoelectron angular distributions. Applications of this model may have the power to predict photoelectron angular distributions from ab initio calculations. Second, a photoelectron imaging study of three anion isomers of deprotonated isoxazole is presented. Deprotonation at the most acidic position yields the isoxazolide anion, but the reaction at another site cleaves the O-N bond and opens the ring of the anion. This bond breaking causes a rearrangement of the energies of its electronic states. The sensitivity of these competing deprotonation pathways is explored by adjustments made to ion generation conditions. Third, a study of bond-breaking probes a covalent bond stretched far beyond its equilibrium length. This transient structure has an inherently multiconfigurational electronic structure due to the interaction of two unpaired electrons−a diradical−over the distance of a few angstroms. This is achieved by attaching an electron to isoxazole which populates an antibonding orbital and cleaves the O-N bond. Photodetachment of this electron leave the molecule as a diradical with the molecular framework holding the two radical centers at a chemically relevant distance. Quantum calculations help to distinguish and assign the nearly degenerate electronic states in this almost bonded aromatic molecule. Ideas for future study are presented in the final chapter.
  • Fusion and Wildtype Proteins of EWSR1 Interact in a Protein Granule

    Schwartz, Jacob; Ahmed, Nasiha Salma; Schroeder, Joyce; Montfort, Bill; Buchan, Ross; McEvoy, Justina (The University of Arizona., 2020)
    Ewing sarcoma is driven by fusion proteins containing a low complexity (LC) domain that is intrinsically disordered and a powerful transcriptional regulator. The most common fusion protein found in Ewing sarcoma, EWS-FLI1, takes its LC domain from the RNA-binding protein EWSR1 (Ewing Sarcoma RNA-binding protein 1) and a DNA-binding domain from the transcription factor FLI1 (Friend Leukemia Virus Integration 1). The LC domain in EWS-FLI1 can bind RNA polymerase II (RNA Pol II) and can self-assemble through a process known as phase separation. The ability of EWSR1 and related RNA-binding proteins to assemble into ribonucleoprotein granules in cells has been intensely studied but the role of phase separation in EWS-FLI1 activity is less understood. We investigated the overlapping functions of EWSR1 and EWS-FLI1 in controlling gene expression and tumorigenic cell growth in Ewing sarcoma, and our results suggested that these proteins function closely together. We then studied the nature of interactions among EWS-FLI1, EWSR1, and RNA Pol II. We observed EWSR1 and RNA Pol II to be present in protein granules in cells. We then identified protein granules in cells associated with the fusion protein, EWS-FLI1. The tyrosine residues in the LC domain are required for the abilities of EWS-FLI1 to bind its partners, EWSR1 and RNA Pol II, and to incorporate into protein granules. These data suggest that interactions among EWS-FLI1, RNA Pol II, and EWSR1 in Ewing sarcoma can occur in the context of a molecular scaffold found within protein granules in the cell.
  • Effective Communication of System-Level Events for System Health

    Carrington, Jane M.; Brittain, Angela Christine; Rainbow, Jessica G.; Rishel, Cindy J. (The University of Arizona., 2020)
    Millions of injuries and over 400,000 deaths occur yearly in the United States (US) from preventable errors (Classen, Griffin, & Berwick, 2017; James, 2013; Makary & Daniel, 2016). The cost of preventable errors has been estimated at roughly $20 billion per year and current statistics confirm that the US spends roughly double that of other high-income countries, despite comparable utilization rates (Papanicolas, Woskie, & Jha, 2018; Rodziewicz & Hipskind, 2019). Most mitigating efforts have been unsuccessfully applied at the bedside without regard for hospital organization complexity (Finn et al., 2018; James, 2013; Kobewka et al., 2017; Zhang et al., 2017). Given that hospitals represent complex systems with many interacting subsystems, an understanding of preventable errors as symptomology of underlying systemic factors is lacking (Begun, Zimmerman, & Dooley, 2003; Braithwaite, Wears, & Hollnagel, 2015; World Health Organization [WHO], 2009). The purpose of this research was to increase understanding of the perceptions of nurses and nursing leaders from magnet-designated and non-magnet-designated hospital organizations regarding what system-level events or circumstances may degrade hospital system health and compromise patient safety. This was underpinned by the Effective System-to-System Communication Framework, which was adapted from the Effective Nurse-to-Nurse Communication Framework and further informed by complexity theory (Capra & Luisi, 2014; Carrington, 2012a; Dekker, 2011; Karwowski, 2012). The sample was drawn magnet-designated and non-magnet designated hospitals in the US. Three staff nurses and three nursing leaders were recruited from magnet-designated hospitals and non-magnet designated hospitals for a total of 12 participants. Sampled participants were those whose work involves medical-surgical units or patients in their respective organizations. The interviews were transcribed verbatim and analyzed by thematic analysis, natural language processing, and the Goodwin statistic (Goodwin & Goodwin, 1985; LIWC.net, n.d.; Morse & Field, 1995).
  • Application and Limitation of Deep Learning Algorithms to Hydrogeology- Data Driven Approaches to Understanding Effective Hydraulic Conductivity, Flux, and Monitoring Network Design

    Ferre, P.A Ty; Abdolhosseini Moghaddam, Mohammad; Bethard, Steven; Sorooshian, Armin; Gupta, Hoshin Vijai (The University of Arizona., 2020)
    Groundwater monitoring at regional scales using conventional methods is challenging because of the need for regular measurements and due to high measurement error associated with existing instruments. With advances in sensor technology and wireless communication, automated groundwater monitoring systems provide us the opportunity to collect groundwater data with high temporal resolution. In the current study, we investigated the feasibility of using those high resolution collected data along with deep learning (DL) and machine learning (ML) algorithms to improve the computational and accuracy of water flux and parameter upscaling estimations. The results of this work are presented in the form of three studies. In the first study, simple ML algorithms, regression tree, and gradient boosting analyses were used to estimate flux using temperature and pressure data. Further, we examine how many and what type of observations (pressure and/or temperature) were necessary and at what depths to estimate surface/groundwater exchange based on simulated data provided by researchers at the Pacific Northwest National Laboratories for the Department of Energy Hanford site. The results suggest that the flux beneath a river can be determined with high temporal resolution (5 minutes) using a single combined temperature and pressure probe, but it cannot be determined using temperature sensors alone if temperature records include measurement error. In the second study, we extended the analysis of the first study by applying DL algorithms to estimate flux using temperature sensors alone with the presence of errors in the measurements. The analysis revealed that DL methods outperform the ML methods, especially convolutional neural networks when used to interpret noisy temperature data with a smoothing filter applied. Also, we attempted to utilize the Accumulated Local Effect to extract the importance of features in DL algorithms. In the third study, we used DL algorithms to infer the effective hydraulic conductivity of a binary conductivity field. Specifically, we made use of the energy dissipation weighting, which represents the importance of a cell in determining the flow field. Using UNET architecture, as an image to image translation model, we could retrieve both Keff and the energy dissipation weighting mapping from the conductivity field without running flow models. Finally, we examined what hidden layer activation output might represent if the model is designed based on physical information about the system.

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