ABOUT THE COLLECTION

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.

We have digitized the entire backfile of master's theses and doctoral dissertations that have been submitted to the University of Arizona Libraries - since 1895! If you can't find the item you want in the repository and would like to check its digitization status, please contact us.

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Please refer to the Dissertations and Theses in the UA Libraries guide for more details about UA Theses and Dissertations, and to find materials that are not available online. Email repository@u.library.arizona.edu with your questions about UA Theses and Dissertations.

Recent Submissions

  • Networks and Discourses Around Third Grade Reading Policy: Neoliberalism and New Governance in the Classroom

    Reff, Audrey (The University of Arizona., 2018)
    While top down federal policy processes continue to deliver policy as grand solutions to real and imagined problems within the nation’s public schools, states continue to churn out their own layers of educational accountability policy. But it is no secret that state and federal policies and programs like No Child Left Behind and Reading First have failed to achieve their objectives and, with each failure, new iterations of these reforms become more punitive to schools, teachers, and students. This dissertation critically engages one such policy, Arizona’s Move On When Reading third grade reading law. The study contextualizes the policy process at the intersection of neoliberalism, new governance, and the legacy of NCLB’s scientifically based reading instruction to understand the contributions of a state level ad hoc policy committee charged with reviewing and recommending revisions to the state law. Drawing conceptually on comparative case study (Vavrus & Bartlett, 2006), critical discourse analysis (Fairclough, 2012; Koyama, 2017), and network ethnography (Ball, 2012), I applied Ball’s (1993) theory of the policy cycle to understand the policy’s network and discourse as it was discursively shaped within the contexts of influence, text production, and practice effects. Consistent with vertical case study design (Vavrus & Bartlett, 2006), data were collected and analyzed at the text, practice, and broader socio-cultural level to provide macro, micro, and local level views of policy contexts, processes, and effects. Answering Gillborn’s (2005) critical policy study questions about policy drivers, policy rhetoric and reality, and policy winners and losers, the study illustrates how the state’s policy has been produced and continues to be perpetuated by networks of influence and neoliberal and managerial discourses despite status quo effects for children. Study findings reveal that Arizona’s Move On When Reading statutes, as amended, reflect the dominant narratives of testing and accountability, science, and learn-to-read then read-to learn that grew within conservative and neoliberal ideologies made popular by the No Child Left Behind Act and the National Reading Panel and which continue through the Every Student Succeeds Act. These narratives combine and travel through networks and discourses and sanction, via state statute, the punitive, harmful, raced, and classed practice of retention that decades of research has warned against, leaving the opportunity gap unchanged and critical implications for local educational leaders. Keywords: third grade reading policy, new governance, neoliberalism, discourse, networks, critical theory, policy cycle, vertical case study
  • Mind the Gap: Gender Differences in Alcohol Consumption and Protective Behavioral Strategies at a Large Public University, 2002 - 2016

    Salafsky, David B. (The University of Arizona., 2019)
    Alcohol use among college students is a persistent and far-reaching public health issue. While some measures of alcohol use within the college population appear to have improved, questions remain as to whether the alcohol use gender gap has been stable or is in a period of change. Protective behavioral strategies (PBS), harm reduction approaches commonly used to address high-risk alcohol use among college students, were also assessed, to determine their relationship with several key alcohol consumption measures for both males and females. Methods: This research summarizes alcohol-related consumption measures based on annual, cross-sectional survey data collected between 2002 - 2016 at a large, public university. Linear regression models as well as descriptive statistics were used to explain overall trends and gender-specific patterns of use over time. In addition, an analysis based on pooled data between 2013 – 2016 was conducted to determine the association between protective behavioral strategies and key alcohol consumption measures, to inform programming that uses these strategies to reduce high risk alcohol use among students, and determine which strategies may be more likely to benefit either males and females for the following alcohol measures: binge drinking in the past two weeks, average drinks when partying and the number of drinks last time consumed alcohol. Both logistic and linear regression models were used to describe these relationships. Results: The results of the 15-year trend analysis revealed significant and meaningful declines among all students in past 30-day alcohol use, average number of drink consumed in the past week, average number of nights students “party” each week, and reductions in the frequency of binge drinking. Looking at the gender gap specifically, these results showed a declining gender gap (i.e. where the difference between male and female use decreased) most notably in average number of drinks consumed in the past week, estimated BAC last time students drank, and past 30 day alcohol use. Based on recent survey results, women showed slightly higher past 30-day alcohol use and reported a higher estimated BAC last time they drank, compared to men. For the second aim of the study, which was based on pooled data collected between 2013 - 2016, most PBS that were expected to moderate alcohol use showed clear and strong protective effects, with a few exceptions. Top strategies for females that were associated with lower alcohol consumption included stopping alcohol use 1-2 hours before going home, avoiding pre-partying and avoiding hard liquor. For men, these included setting a limit on drinks, avoiding pre-parting, and avoiding hard liquor. Conclusion: A number of alcohol measures improved during the study period, and for these, male university students showed greater declines, on average, than females – resulting in a shrinking gender gap. Decreases in the frequency of drinking occasions likely influenced overall declines in average drinks per week and the frequency of binge drinking. Male and female students showed considerable overlap with respect to protective behavioral strategies that were negatively associated with alcohol use and identified a few strategies that may have limited effectiveness. These results highlight evolving trends in alcohol use among college students and point to specific strategies which can help address this longstanding public health issue. Policy and program recommendations, informed by these findings, are detailed in its conclusion.
  • The Effects of Radiation Damage Accumulation and Annealing on Helium Diffusion in Zircon

    Ginster, Ursula (The University of Arizona., 2018)
    Accurate diffusion models are essential for interpreting thermal histories from noble-gas thermochronology and the timing and rates of near-surface geological processes that come from them. These models use kinetic descriptions of noble gas daughter loss to predict radioisotopic dates for minerals based on parent nuclide abundances (e.g., effective uranium concentration (eU)) and time-temperature (t-T) paths. By matching predicted date-eU correlations with observed ones, the models constrain potential t-T paths for rocks, thereby, elucidating exhumation and burial histories. For some thermochronometers, including the (U-Th)/He system in apatite and zircon, diffusive daughter loss depends not only on temperature but also radiation damage (α-damage and fission tracks), which is imparted by the same radioactive decay that produces the daughter nuclides. Accordingly, the models require a robust understanding of the effects of radiation damage on noble gas diffusion as a function of both damage accumulation and annealing, as well as the kinetics of damage annealing. The current predominant model used for the zircon (U-Th)/He system is the zircon radiation damage accumulation and annealing model (ZRDAAM), which is calibrated from He diffusion data for natural unannealed zircon samples. The model relies on several untested assumptions: (1) He migrates through zircon by thermally activated volume diffusion, (2) radiation damage anneals with the same kinetics as etchable fission tracks, (3) damage annealing reverses the effects of damage accumulation on He diffusion in zircon, and (4) the diffusivity-damage relationship is the same for both damage accumulation and annealing. This dissertation comprises several studies that explore the unknowns underlying these assumptions, provides new observations that modify our understanding of them, and integrates all available data to provide a more accurate, internally consistent, and mechanistically based model for how radiation damage affects zircon (U-Th)/He thermochronometry. In our studies, we consistently use Raman spectroscopy as a measurement of radiation damage, which allows us to quantify and compare damage extent in natural and partially annealed zircon. Our diffusion data support thermally activated volume diffusion as the dominant He migration mechanism in zircon rather than first order single jump. Furthermore, the data generally confirm the overall trend of diffusivity versus radiation damage accumulation in ZRDAAM. However, they reveal a different correlation between activation energy and damage than previously observed. Thus, we present a new quantitative and mechanistically based model to describe the effects of damage accumulation on the diffusion kinetic parameters activation energy and frequency factor and on the bulk He retention and closure temperature properties. Our annealing study shows that ZRDAAM overestimates bulk damage annealing as function of time and temperature. Our data show that annealing of bulk radiation damage generally requires significantly higher temperatures and longer durations than fission tracks. For example, radiation damage is annealed by only 50% when etchable fission tracks are fully annealed. Although our study shows that the diffusivity-damage correlation used in ZRDAAM is appropriate for the case of damage accumulation, it also reveals that the same correlation is not followed during damage annealing. For damage doses ranging from 7.6 × 1016 to 1.3 × 1018 α/g, the closure temperature (domain size of 100 µm, cooling rate of 10 °C/Ma) of partially annealed zircon is 20 to 40 °C higher than for natural zircon with similar damage. This discrepancy is compounded by the fact that ZRDAAM overestimates damage annealing, which can lead to differences between predicted and actual closure temperatures of up to 75 °C. This work improves our mechanistic understanding how radiation damage modifies He diffusion in zircon by a succession of several mechanisms— increasing damage initially impedes diffusion due to trapping combined with sequestration and then causes diffusion to increase due to amorphous phase expansion. In addition, the work provides radiation damage annealing models and the first data on He diffusion in partially annealed zircon, which in combination allow us to better constrain t-T histories of rocks and interpretations of exhumation and burial histories.
  • High-Confidence Learning from Uncertain Data with High Dimensionality

    Washburn, Ammon (The University of Arizona., 2018)
    Some of the most challenging issues in big data are size, scalability and reliability. Big data, such as pictures, videos, and text, have innate structure that does not fit into the structure of the normal data table. Often the sources come from the internet or other domains where accuracy is not possible. When drawn from these sources, it is likely that important information is missing or cannot be measured. This leads to situations where identifying the important part of the data would lead to good solutions, but with all the data the tasks become ill-posed. Another case is where all the data is useful but there is some important and/or hidden structure of which classical methods are not equipped to take advantage. However, many methods have been developed to either deal with data uncertainty or with ill-posed problems. Data uncertainty can come from missing or distributional data. Data imputation combined with uncertainty quantification can allow regular statistical and machine learning methods to be applied and then verified. Other methods combine the steps in a robust way to directly inform the model. This last type of method is common in chance-constrained, robust or distributionally robust programs from the mathematical optimization community. Well-posed problems have a solution which is unique and changes slowly and continuously with the initial conditions. For standard machine learning models, a data set with many irrelevant features gives rise to ill-posed problems. Regularization and feature selection are two possible ways to deal with these problems. Both the regularization and feature selection techniques have been around for a long time. Regularization approaches can include Lp norms or the matrix trace which will give certain properties. Feature selection has been achieved in many ways including a preprocessing step to rank and select features and the use of stepwise regression to classical modern techniques such as LASSO. For many applications, there are both uncertainties and a high-dimensional component of the data. By combining methods that deal with both of these methods and then deriving quick computational algorithms, we can formulate robust, highly-generalizable machine learning models that achieve very good results. Two of our classification models handle samples of points to be classified as one. Traditional machine learning models in classification expect to classify one point but with an interesting data set from Karyometry, several hundred points must be consolidated into one classification. One of the algorithms also can take advantage of a certain nested structure in this data set to gain further information useful for doctors. The third model deals with data and label uncertainty in classification. We do it in a data-driven, distributionally robust way that gives us some confidence intervals on our classification. A large part of this dissertation also deals with the algorithms used to solve these optimization formulations. We advance the solution path algorithms to general cases of convex programming that many machine learning models fall into. We also develop three methods to solve a multiclass generalization of SVM that hitherto has been considered very difficult. In this dissertation, we will focus on support vector machines and how to reformulate them to deal with these issues while still being computationally tractable. In addition, our approach could be applied to many different machine learning models through the general form of Tikhonov regularization. This allows this research to apply to many models which fit the Tikhonov framework.
  • Needs Assessment for Using a Stroke Scale in Kenyan Hospitals

    Sillah, Ishmail A. (The University of Arizona., 2018)
    Purpose/Aims. The purpose of this project was to conduct a needs assessment for the use of the National Institute of Health Stroke Scale (NIHSS) at an urban and rural hospital in Kenya. The specific aims were: 1) Describe the patient demographics, clinician perspectives, and current stroke care practices at both hospitals; 2) Describe the facilitators and barriers of implementing the NIHSS at both hospitals; 3) Create a program implementation and evaluation plan to address the needs that are identified at both hospitals; and, 4) Compare and contrast the findings from the urban and rural hospitals. Background, Stroke is a leading cause of death in sub-Saharan Africa (SSA) and the burden of stroke in this region is increasing. Despite the known benefits of the use of systematic stroke protocols (which include the gold standard NIHSS to assess stroke severity) in developed countries, their use is virtually nonexistent in Kenya and is urgently needed. Methodology. The setting for the study was an urban Mater Misericordiae Hospital in Nairobi and a rural Sagam Community Hospital in the western region of Kenya. Data on clinician and stroke population demographics and current stroke care practices (Aim I) was collected using an anonymous online Survey Monkey® questionnaire completed by 80 nurses, physicians and clinical officers working at both hospitals. Facilitators and barriers to using the NIHSS (Aim II) are determined via questions from the anonymous online survey. Results. Results from Aims I and II are used to develop an implementation and evaluation plan for the use of NIHSS for each hospital (Aim III). Other than demographic differences evidenced by scarcity of physicians in the rural hospital, clinicians from both hospitals expressed similar desires for improved stroke assessment and reported similar facilitators and barriers for NIHSS implementation (Aim IV). Note that the scarcity of physician providers in the rural hospital was compensated for by the availability of clinical officers (nurse practitioner and physician assistant equivalents). Conclusion. Clinician desire for improved stroke assessment and the facilitators and barriers for NIHSS implementation were not only similar between urban and rural hospital settings in Kenya, but also similar to those identified in stroke studies in developed countries. This finding is promising because it highlights the possibility for multinational discourse for establishing standardized protocols to improve stroke management in Kenya, a country with a significant stroke burden. In addition, this DNP quality improvement project highlights the global reach of a DNP student.
  • An Evidence Based Practice Training and Educational Curriculum for Adolescent Mental Health Promotion

    Marnell, Nicole (The University of Arizona., 2018)
    Background: The adolescent age population is subject to inherent risks due to the slow rate of their neurobiochemical development, which poses additional challenges for appropriate cognitive functioning. There are additional risk factors that influence the inherent risks of adolescence, but only one the risk factors for mental health can be impacted by healthcare providers. The prevalence rate of mental health disorders, worldwide and in Alaska, in adolescents continues to rise, indicating that this is a priority age to promote the development of positive mental health. The Positive Youth Development (PYD) framework is a strength-based perspective that has demonstrated and empirically supported outcomes for the development of protective assets, life skills, and competencies. Primary care providers are at a disadvantage to address the cultivation of mental health promotion due to time constraints within the primary care setting. The collaboration of pediatric primary care providers and community-based programs can provide a solution to address this healthcare gap through the use of a PYD evidence-based practice educational curriculum. Purpose: The purpose of this DNP project was to create a PYD evidence based educational curriculum that can be taught to and used by local youth engagement community-based programs for adolescent mental health promotion. A secondary purpose of this DNP project was to have the PYD program for adolescent mental health promotion evaluated by content experts for understandability and actionability. Methods: A comprehensive training program and associated educational curriculum PYD program for adolescent mental health promotion was written by the author, presented in a narrated PowerPoint presentation that was emailed to eight content experts that resided in either Arizona or Alaska who were nursing faculty members in community and/or pediatric health. The panel of experts reviewed the educational presentation using the Patient Educational Material’s Assessment Tool for Audio Visual (PEMAT-AV) and returned the PEMAT-AV excel sheet, which auto scored for the understandability and actionability components of the program. Results: The eight content experts returned completed PEMAT-AV tools and the mean actionability score was 96.86% and mean understandability score was 95% of the PYD program for adolescent mental health promotion. Discussion: The educational curriculum is a strong program as evidenced by the high mean scores for understandability and actionability, indicating the program is a tool for adolescent mental health promotion that can be understood and implemented by viewers. Additionally, individual feedback from content experts deemed it a dire need in the Anchorage community that should be explored for implementation within the community, which would require additional research and evaluation.
  • Employing Chemical Biology Tools for Selective Control of Acetyltransferases and Interrogation of Signal Transduction Pathways of Kinases

    de Silva, Chandi Sagarika (The University of Arizona., 2018)
    The reversible post translational modifications (PTMs) of proteins are often integral for the cell to respond to external stimuli. The cellular pathways involve molecular interactions between proteins and other molecules and/or enzymatic activity. The molecular interactions, trafficking between cellular compartments and enzymatic activity are often regulated by PTMs. Reversible PTMs allow cells to respond and subsequently return to a resting state. Human diseases often arise from defects in these signaling networks sometimes from perturbations in PTMs. Clearly ascribing a particular PTM on a particular protein in a signaling network to a particular enzyme has been very challenging. Advances in understanding may help in an improved understanding of signaling and thus impact our battle against the disease. The primary focus of this dissertation is to discuss the fragment complementation approach which was employed to regulate the function of proteins belong to two major classes that govern two classes of post translational modifications, phosphorylation and acetylation. The >500 protein kinases in humans catalyze the phosphorylation of Tyr, Ser and Thr residues on proteins and thus modulate their function. The structural similarity of kinases makes it challenging to selectively turn-on or turn-off desired kinases using small molecule inhibitors or activators. Genetic approaches are powerful, but cells and organisms respond and adapt to long-term changes in gene expression levels, thus making it challenging to understand the exact role of any enzyme in time and space. Towards a potential solution to this problem, we have developed a method to control the activity of individual enzymes utilizing small molecules. This approach was successfully applied to protein kinases and phosphatases, leading to the control of their activity in vitro and in cells. The strategy entails sequence alignment and the identification of regions that harbor significant dissimilarities to eventually generate ligand-gated split proteins. The well-studied chemical inducer of dimerization (CID), rapamycin dependent heterodimerization of FKBP/FRB was used as the first test of a successful ligand-gated split-enzyme. Moreover, orthogonal CIDs rapamycin and abscisic acid were successfully used for regulating the activity of Kinases in mammalian cells. Src is the first identified proto-oncogene and is often considered as the quintessential member of a Src kinase family proteins. We generated two stable cell lines each expressing constitutively active split Src kinase that can be conditionally regulated by two chemical inducers rapamycin and abscisic acid. Subsequently, those stable cell lines were used for phosphoproteomic studies to understand Src signaling. Rapid activation of stably expressing systems enabled identification of numerous potential direct or indirect Src substrates and specific phosphosites. These downstream targets may be implicated in many different cellular networks thus, provides a general understanding of the role of Src and Src family kinases in cell signaling. We have also used the split-protein approach for Lysine Acetyl Transferases (KATs). There are numerous KATs, and currently available small molecule-based inhibition methods are not uniquely specific while RNAi based gene knockdown studies can fail to provide details related to the true role of any enzyme as compensatory acetylation may occur. To address this problem, the first generation of ligand-inducible split-KATs, GCN5 and PCAF were successfully tested in bacterial expression systems. In this work, we validated a series of full-length split acetyltransferases and developed in cellulo approaches for their study. However, we were not successful in developing robust methods for observing ligand inducible full-length split-KATs in cells. Finally, the last section of this dissertation focuses on developing an approach for selective DNA methylation studies that would improve upon methods to target specific DNA sequences using designed zinc fingers. Transcription activator-like effectors (TALEs) were designed, cloned and tested as the DNA binding domain for targeting mir 200c promoter regions, which are known to demonstrate hypermethylation activity. We discovered that all the designed TALEs displayed higher binding specificity to the desired targets of the mir 200c promoter than zinc finger-based designs. This work sets the stage for the further design of selective reagents for targeting DNA. In summary, this work describes approaches for selectively targeting and studying protein phosphorylation, protein acetylation as well as DNA methylation.
  • Development of New Anionic Hopping Cascade Routes to Synthesize Various Heterocycles

    Das, Pradipta (The University of Arizona., 2018)
    Four new synthetic methods employing anion hopping strategy to synthesize various heterocylces are presented. In Chapter 1.A, a micro-review is presented which comprehensively cover reported reactions employing thio- and aminophosphate precursors for forming sulfur and nitrogen heterocycles. Whereas, in Chapter 1.B, a cationic and an anionic hopping cascades are reported to form 1,2,3,6-tetrahydropyridines. Origins, design, reaction, and optimizations are discussed. In Chapter 2, an asymmetric approach to assemble cis-vinyl aziridines is reported employing a strategically substituted dienolate, decorated with a γ-leaving group. Chapter 4 highlight efforts toward asymmetric total synthesis of (-)-kainic acid and (+)-α-allokainic acid. In Chapter 4A and Chapter 4B, lays the groundwork for a lithium-assisted asymmetric anion-accelerated amino-Cope rearrangement cascades in which nitrogen atom chiral auxiliary serves three critical roles, by (1) enabling in situ assembly of the chiral 3-amino-1,5-diene precursor, (2) facilitating the rearrangement via a lithium enolate chelate, and (3) imparting its influence on consecutive inter- or intramolecular C−C or C−X bond-forming events via resulting chiral enamide intermediates or imine products. Chapter 5 presents a comprehensive compilation and analysis of US FDA approved combination drugs, from the first approval in 1943 through 2018.
  • Reconstructing Tropical Pacific Climate Variability from Coral Archives

    Jimenez, Gloria (The University of Arizona., 2018)
    The tropical Pacific Ocean is a critical component of the climate system, and its mean state and variability are linked to effects across the globe. Our understanding of the area is limited by the scarcity of direct observations of important climatic variables prior to the mid-twentieth century, without which it is difficult to characterize longer timescale variability and trends. Various paleoclimate proxies have been used to extend the observational record into the past; coral records are especially useful as they can offer high-resolution snapshots of sea surface temperature (SST) variability, sometimes as long as hundreds of years. Taken together, these records can be a powerful tool with which to reconstruct climate across the tropical Pacific basin. In the present study, I use two new coral paleoclimate records to examine trends and variability in the eastern equatorial Pacific. I then apply reduced dimension reconstruction techniques to a network of tropical Pacific coral records to evaluate the possibility of reconstructing the Pacific SST field into the past. First, my coauthors and I generate a 1940-2010 Sr/Ca-SST reconstruction from two Wolf Island corals, in the northern Galápagos archipelago. We apply trend analysis to this and several other twentieth century eastern tropical Pacific coral and instrumental datasets, showing that on multidecadal timescales, the entire area has warmed in response to radiative forcing. In recent decades, though, increases in strength in upwelling and the Equatorial Undercurrent have led to spatially complex trends, including cooling in the eastern tropical Pacific during boreal fall and winter. In the second chapter, my colleagues and I report on a second coral SST reconstruction from the northern Galápagos, this one from Darwin Island. Based on coral δ18O, the reconstruction runs from 1866-2015 and is one of few seasonally resolved SST reconstructions from the eastern Pacific to span the nineteenth to twenty-first centuries. The Darwin reconstruction shows unique features relative to other tropical Pacific coral records, including antiphasing with central and western Pacific coral records that suggests it may be monitoring decadal-scale variability related to Central Pacific El Niño activity. Finally, we use the PAGES2k network of tropical coral records to reconstruct annual SSTs across the Indo-Pacific basin over the last several centuries. We test the ability of two related climate field reconstruction techniques, both reduced dimension approaches based in optimal interpolation, to estimate the leading climate features of the field from this sparse proxy network. Evaluation of reconstruction skill and uncertainty suggests that both methods are negatively affected by proxy system error, as well data availability in space and time.
  • Adaptation of Post-Crisis Team Debriefing in an Inpatient Psychiatric Hospital

    Su, Yong Yi (The University of Arizona., 2018)
    Working in psychiatric nursing can be stressful. The nursing employees’ stress level has been heightened in a southwestern psychiatric hospital due to patient violence and organizational changes and demands. To reduce employee’s stress and prevent burnout, ultimately improving the quality of patient care, this doctor of nursing practice (DNP) quality improvement project incorporated the use of aromatherapy with lavender oil and a moment (60 seconds) of self-reflection into the current crisis team debriefing process in a two-week period. The frontline registered nurses and mental health technicians in inpatient units and psychiatric emergency services department were invited to participate in this project. Forty-six survey forms were collected in 10 team calls for crisis debriefing. Using paired t-test and chi-square test statistics in SPSS and line graph in Excel function, the participants’ mean stress level was found significantly reduced at a p-value of 0.000 by the interventions implemented. Between two components of the interventions, participants were more in favor of aromatherapy with lavender oil. Participants also wanted individual debriefing incorporated to further sustain their mental health. Some limitations were observed in this project. Future projects on the exact amount of lavender oil applied, with an improved project design, and the incorporation of individual debriefing are suggested.
  • Increasing Medication Adherence Using Motivational Interviewing in Patients with Depression

    Fuangunyi, Fuanjia Njukeng (The University of Arizona., 2018)
    Depression is a psychiatric illness with a high incidence of medication non-adherence, which is a challenge in treating patients with depression. Non-adherence influences the effectiveness of treatment and the direct and indirect costs associated with untreated depression. Design: This study used a pre-post one-group design with medical record audit to examine the effectiveness of motivational interviewing (MI) in increasing medication adherence in patients with depression. The main outcome of this quality improvement study was medication adherence, an objective measure of the Medication Possession Ratio (MPR) and Proportion of Days Covered (PDC) of the pharmacy refill records defined as a calculated PDC and MPR ≥ 80%. Sample: The sample of this study consisted of patients with depression (N = 5). Intervention: The patients each received MI sessions that lasted 15-20 minutes in two sessions. The pharmacy refill records were used to determine medication adherence rate through calculations of the MPR and PDC before and after the intervention. Baseline data were obtained by reviewing the pharmacy refill records three months prior to the first MI session and the patient self-report at baseline confirmed the data. The pharmacy refill records were reviewed over a period of one month after each MI session. The percentages of the MPR and PDC of the patients were compared at the pre-test, post-test, and at one-month follow-ups. Result: A significant increase was noted in the medication adherence rate. While there was no statistical increase after the second MI session with the PDC adherence rates, there was an overall significant increase in medication adherence from baseline. Conclusion: MI is an effective intervention for improving adherence to medication but does not determine if the patient is actually taking the medications. Keywords: motivational interviewing, medication adherence, major depressive disorder, adherence, and psychiatric conditions.
  • Preoperative Teaching of Spanish Speaking Patients Undergoing a Total Knee Arthroplasty

    Pacheco, Daria (The University of Arizona., 2018)
    An increasing number of minority individuals are seeking care in the healthcare industry. Patients whose second language is English often do not read or understand post-operative care materials. This is detrimental to recovery and increases the length of hospital stays. Incorporating clinical practice guidelines (CPG) for same-day rehabilitation into the preoperative education for Spanish speaking patients will facilitate patient understanding, and knowledge that patients cannot receive through information packets or in the education they are currently receiving. The purpose of this DNP project was to develop educational materials that are effective for a culturally diverse population of patients of Hispanic origin receiving total knee arthroplasty (TKA). The study question was: Does improving educational materials effectively increase minority patients’ understanding of post-operative care, thus resulting in shorter hospital stays? The Campinha-Bacote Model of Cultural competence guided this quality improvement project. This project had two phases. The first phase was to design the delivery of pre- and post-operative instruction through development of a pre- and post-operative educational product for Spanish-speaking TKA patients to engage in post-operative care activities. The second phase involved the training of nurses with the use of the educational product, as well as the delivery process for the pre- and post-operative educational product given to patients. The target population of this study was minority patients who underwent TKA surgery and were treated with accelerated rehabilitation post-operation. Chart reviews was used to collect date of discharge for patients given the instructions in Spanish. Feedback was obtained from the nurses and the patients on how to improve the educational material. The average length of stay was calculated for these patients and compared with previous length of stays for non-English speaking patients in a bar graph. Results indicated that intervention-based patients had a shorter length of stay.
  • Literacy Practices with Media: Popular Culture Media and the Role of Pedagogical Guidance in L2 Learning of Japanese

    Shintaku, Kayo (The University of Arizona., 2018)
    Advancement of digital technologies has increased the accessibility of authentic resources in various languages, and this wide and easy access to authentic resources supports exposure to and interaction with second and foreign language (L2) and communities online. As the objective of learning is also shifting from what people learn to how people learn (Jenkins, 2009), the digitally-mediated communication landscape is radically reshaping the terrain of language and literacy education (Lankshear & Knobel, 2011; Lotherington & Jenson, 2011). In this way, digital technologies add alternative channels and options for communication. Because digital technologies are multimodal by nature, they allow us to integrate multiple facets of literacy to communicate by using many modalities to make meaning (New London Group, 1996; Thorne & Reinhardt, 2008). Consequently, expanded views of text and literacy (Kern, 2000, 2003) have been emphasized in the literature in order to holistically integrate multiple literacies into L2 education. Regarding Japanese-as-a-foreign language (JFL) education in particular, entertainment media, such as anime, digital games, and manga, often serve entry points into formal course-based language learning (Japan Foundation, 2014, 2017b; Mori & Mori, 2011). In addition, JFL learners use increasingly-available educational media, such as language apps like Google Translate and language websites like Jisho.org. However, the existing body of Computer Assisted Language Learning (CALL) literature has not fully investigated the use of entertainment media as part of formal course study to enhance authenticity and provide more literacy practices in the wild (Thorne, 2010). In this way, it is critical to understand how digital literacies are integral to the autonomous and self-directed learning at the learner’s level before curricular and class level implementation is even considered. The current research investigates what digital literacies that JFL learners are exposed to and employ in their autonomous and self-directed JFL learning using entertainment media (i.e., anime and digital games) and educational media (e.g., language apps). The data analyzed were collected from 12 JFL learners divided into two projects (anime and games focus groups) and from online survey responses from JFL learners enrolled in the Japanese language program (n = 191) and students enrolled in the Anime Class (n = 104) at the University of Arizona. In the first project, anime focus group (AFG) participants (n = 6) watched three titles of anime and self-studied with four available language setting options. In the second project, game focus group (GFG) participants (n = 6) played one single-player online game individually and one single-player PlayStation3 game as two sub-groups (n = 2, n = 3) and solo (n = 1). Both focus groups then participated in an interview at the end of the study. The findings from the AFG project showed that a digital environment promoted digital literacies and individuality in autonomous and self-directed learning. They also displayed the capacity of anime to make space for linguistic and cultural learning opportunities and provide reinforcement of learning by connecting inside- and outside-of-class learning. The findings from the GFG project demonstrated that JFL learners viewed games as milestones of achievement in their educational pathways. They also personalized learning strategies by utilizing various educational media to learn with games. Furthermore, the results demonstrated learner autonomy by controlling their learning process and the learner’s awareness as a member of community of practice. The analyzed data exhibited that JFL learners shared their expertise and learned from one another via group gameplay based on the reported ZPD and scaffolding moments. Built on those two projects, the research explores pedagogical implications for anime and digital games in both formal learning and autonomous and self-directed learning settings. The online survey results also evidenced the relationship between entertainment media consumption and formal language course enrollment. The current research contributes to a further understanding of outside literacies practiced by JFL learners via entertainment and educational media. The research is also potentially significant in its exploration of CALL-based L2 instructional designs not only in JFL but also in other L2 pedagogy taking place in contemporary digital spaces.
  • Design, Fabrication and Testing of Diffractive Multifocal Intraocular Lens (MIOL)

    Xie, Jihong (The University of Arizona., 2018)
    The optical engineering exploration in making the capable of diffractive multifocal Intraocular lens (MIOL) will be be presented in the dissertation. The Diffractive multifocal IOL is a surgical implanted medical devices that have potential to provide the recovery of full range functional vision for cataract patients. The developed design principle, fabrication technique, and performance verification method associated with the diffractive MIOLs will be reported and discussed in this presentation. Two examples will be provided as a demonstration for the capability in the creation of diffractive MIOLs
  • Multilayered Regulation of TORC1 Signaling in Saccharomyces cerevisiae

    Sullivan, Arron (The University of Arizona., 2018)
    The Target of Rapamycin Complex 1 (TORC1) is a master regulator of cellular growth in eukaryotes. Much insight has been gained into how amino acid and nitrogen levels regulate TORC1 through the escape from rapamycin-induced growth arrest complex (EGOC), and its regulators including the Seh1-associated complex (SEAC). However, other nutrient levels and environmental stresses also act on TORC1, and far less is known about how these signals are transmitted to the complex. In two projects presented here we investigate the osmotic stress signaling network acting on TORC1 as well as regulators of TORC1 agglomeration that act in glucose and nitrogen starvation conditions. In the first investigation, we introduce a novel and reproducible high-throughput assay to screen for genes that affect TORC1 activity in stress conditions. We then use these methods to measure the expression of a TORC1 dependent ribosome biogenesis gene, NSR1, in ~4700 strains from the yeast knock-out library during osmotic stress. We show that 440 of these strains are not able to properly repress NSR1 transcription. The genes identified in the screen form a highly-connected network including 17 proteins that directly interact with TORC1. Secondary rapamycin-based assays performed on these strains allowed us to further characterize the network and show that more than 50 of the proteins act downstream of TORC1. The data derived from this work serve as a resource for our lab and others studying TORC1, and the assay itself is customizable and can be used to characterize any gene regulatory network. In the second study, we sought to further our understanding of the movement of TORC1 from its position distributed across the surface of the vacuolar membrane to a single agglomerate (TORC1-body) in starvation conditions. Previous work suggested that the AMPK in yeast, Snf1, indirectly promoted the phosphorylation of the TORC1 component Kog1. This phosphorylation event sped up aggregation of the complex by ~20 fold. In order to identify other signaling proteins that regulate TORC1-body formation we performed a screen examining the impact that nearly all non-essential kinases and phosphatases in yeast, as well as selected proteins from the previous high-throughput network, have on TORC1 agglomeration. We identified 13 new regulators of TORC1 body formation, including the PI(3)P binding protein Pib2. We also examined the impact of EGOC deletions and mutants had on body formation and discovered that active EGOC was an inhibitor of TORC1 aggregation. Together, we show that seven of the new regulators likely act at or above the EGOC dependent inhibition of TORC1 body formation; while others act at a later step to assist in body formation.
  • Deoxygenation Treatment Strategy to Control Vampirovibrio chlorellavorus in Chlorella sorokiniana Cultures

    Attalah, Said (The University of Arizona., 2018)
    Researchers and algae growers have shown deep interest in the cultivation of Chlorella microalgae because of its significant growth potential, high biomass quality, and broad range of applications. Both small and large-scale cultivation systems (laboratory or outdoors) with Chlorella microalgae have been extensively studied, and promising results have been demonstrated in terms of cultivation procedures, growth media, growth parameters, harvesting, and processing; however, protection against biological contaminants such as the predatory Vampirovibrio chlorellavorus requires more investigation. Despite the high growth potential of Chlorella species, the impact of V. chlorellavorus infection on the culture productivity is significantly damaging and cannot be counterbalanced naturally. Thus, a pressing need to develop appropriate preventative and/or curative strategies for an optimal control of this type of predator has become one of the priorities in the cultivation process of Chlorella microalgae. The present research focusses on the management of dissolved oxygen (DO) during the nighttime (dark period) in co-cultures of Chlorella sorokiniana and V. chlorellavorus. We developed an unprecedented method to control the infection of C. sorokiniana by V. chlorellavorus. Because V. chlorellavorus is an obligate aerobe and C. sorokiniana is not, deoxygenating the culture assumably harms the predator and not the host. This research first examined the effect of deoxygenation on pathogen-free C. sorokiniana monoculture, and then on C. sorokiniana-V. chlorellavorus co-cultures. In the first section, initial experiments with pathogen-free C. sorokiniana cultures included different deoxygenation-aeration cycle times. Pure nitrogen gas was used to create anoxic conditions, and ambient air was used to reestablish aerobic conditions. In these initial experiments, C. sorokiniana tolerated anoxic conditions for extended time intervals as long as 8 hours. In the experiments with infection by V. chlorellavorus, aerated controls collapsed while the deoxygenated cultures sustained a normal growth cycle. Visual observation showed a healthy green C. sorokiniana culture in the treated cultures and a brown slime and collapsed culture in the aerated controls. In the second section, we evaluated the technical aspects of the deoxygenation practice and cost of nitrogen gas sparging as an appropriate method to create anoxic conditions in the cultivation system. In this experiment, DO concentrations were driven to low levels (0.2 ppm to 0.5 ppm) by sparging nitrogen gas for one hour at the beginning of the night (dark period), and then natural deoxygenation by dark respiration kept the oxygen concentration at a low level. The laboratory results showed that this method kept the DO levels low during the entire dark period and effectively controlled V. chlorellavorus infection in C. sorokiniana co-cultures. The cost of the deoxygenation method was estimated in outdoor experiments with pathogen-free C. sorokiniana cultures. Nitrogen sparging for one-hour at the beginning of the dark period maintained dissolved oxygen concentrations at low levels (<0.5 ppm) throughout the night. The total nitrogen injection per night per liter algae culture was then translated to annual commercial-scale raceway cost. Finally, the technical and economic feasibility of this process was evaluated for onsite nitrogen gas generators in commercial-scale reactors.
  • Revisiting the Neighborhood: A Spatial Analysis of Community Organizations and Juvenile Recidivism in the Urban Southwest

    Thompson-Dyck, Kendra (The University of Arizona., 2018)
    It is well documented that characteristics of residential neighborhoods shape the lives of residents in ways that can perpetuate or alleviate inequality. One compelling but comparably understudied explanation for these “neighborhood effects” is that organizations in the neighborhood shape the opportunities and constraints residents face. A small body of work has examined neighborhood contributors to adult repeat offending and scholars have called for more work on the role of organizations in offender recidivism. Surprisingly, no prior research has examined whether spatial proximity to community organizations influences the likelihood that juvenile offenders will repeat offend despite theories of juvenile delinquency that suggest local institutions generate social and formal control that, in turn, may influence delinquent behavior. To fill this gap, I examined seven types of organizations theorized to influence recidivism serving as risk enhancers or risk reducers in a juvenile’s neighborhood. I conducted tract-level and individual-level analysis in the Phoenix-urbanized area using point-level geolocated data on organizations and juvenile offenders who completed diversion or probation supervision with Maricopa County Juvenile Probation in 2007. Spatial regression models indicated there were more organizations per capita in census tracts with higher socioeconomic disadvantage across the metropolitan area, rather than a negative association as predicted. However, descriptive maps indicated a spatial mismatch between juvenile offenders and resources; reentering youthful offenders were largely located in areas lacking socioeconomic and organizational resources in select suburbs and communities just outside the urban core. Using Cox proportional hazard models, I also examined the influence of aggregate neighborhood disadvantage and the number of organizations accessible within walking distance of a juvenile’s approximate residential address on their likelihood of subsequent recidivism, net of individual characteristics. My results were mixed and modest and did not provide strong support for the general predictions of social disorganization theory. Rather than exerting uniform risk enhancing or risk reducing effects, the influence of nearby organizations on repeat offending varied by juvenile population and type of recidivism (any, status/public peace, property, violent/drug). Neighborhood disadvantage enhanced the risk of a new property offending but was unrelated to other types of repeat offending. However, this relationship was largely accounted for by proximity to the total number of organizations lending support to a routine activities approach for property offense behavior. Findings indicated that public parks, middle and high schools, libraries and community centers, civic/membership/voluntary establishments, and detention/police facilities influenced recidivism risk for status/public peace and violent/drug infractions, but the direction and significance of these effects varied by juvenile population. Together, this research suggests organizations are not inconsequential, but there is no one-size-fits-all approach. Successful integration of organizational measures into neighborhood effects research warrants greater specificity in the types of organizations, resident population, and specific behaviors or outcomes modeled.
  • Breast Tumor Stiffness and Bone Metastasis: How “Soil Selects Soil”

    Watson-Hurthig, Adam William (The University of Arizona., 2018)
    Breast cancer is the most common cancer amongst women globally and continues to produce considerable harm. The microenvironment of primary breast tumors plays a well-described role in promoting the growth and progression of the disease; however, despite our wealth of knowledge concerning how the biochemical and biophysical properties of primary tumors influence cancer cells in situ, very little is known about whether this influence persists after dissemination to metastatic sites, such as the skeleton. Bone metastases inflict the greatest morbidity associated with breast cancer, and they affect a majority of women with advanced disease. Although predictive gene signatures of osteolytic metastasis have been identified, their genesis remains obscure. Current models propose that bone metastases originate from rare subclones that arise stochastically during clonal evolution of primary tumors. In contrast, we reveal a deterministic origin of the osteolytic phenotype that lies in the response of breast cancer cells to mechanical stimuli in their primary microenvironment. Here, we show that primary tumor stiffness encodes a “mechanical memory” which instructs cancer cells to adopt and maintain distinct biophysical properties, in addition to promoting osteolytic bone metastasis. We present a “mechanical conditioning score” comprised of mechanically-regulated genes in order to proxy tumor stiffness response clinically, and we show that it is associated with bone-specific metastasis. Using a discovery approach, we trace mechanical memory to the mechanotransductive activation of RUNX2, an osteogenic gene bookmarker and bone metastasis driver. This combination of traits allows for the stable transactivation of osteolytic target genes which persists after cancer cells disseminate from their activating environment. Using genetic, epigenetic, and functional approaches, RUNX2-mediated mechanical memory can be simulated, repressed, selected, or extended. Taken together, these results show that the primary tumor microenvironment can determine the metastatic microenvironment, i.e. "soil selects soil."
  • Laboring on the Margins: Muslim Women, Precarity, and Potentiality in Russia

    Rabinovich, Tatiana (The University of Arizona., 2018)
    Titled Laboring on the Margins: Muslim Women, Precarity, and Potentiality in Russia, this dissertation explores how working-class pious Muslim women in Saint Petersburg cope with the ongoing economic crisis and political authoritarianism in today’s Russia. In order to understand the women’s responses to precarity, I examine the different forms of gendered labor they undertake to sustain themselves and their community. Based on 18 months of field research in Saint Petersburg, I demonstrate how the women run small businesses and volunteer, practice self-care and mother, struggle with health issues and invest their energies in cultivating the bonds of solidarity under a regime of austerity. Drawing from feminist literature on affect and embodiment, I advance a concept of “embracing” precarity, which allows the women not only to survive on the margins of Russian society, but also to imagine and act upon more just and inclusive worlds. This work offers a unique window into the lives of disempowered population groups in Russia, as well as into the exigencies of late capitalism, precarity, and gendered labor.
  • Autonomous Sensor Tasking for Space Situational Awareness ​using Deep Reinforcement Learning

    Jones, Quintina R. (The University of Arizona., 2018)
    The Joint Space Operations Center of the United States Strategic Command’s Joint Functional Component Command for Space is responsible for detecting, tracking, and identifying all artificial objects in the Earth’s orbit. Over 39,000 man-made objects are cataloged and over 16,000 objects are being tracked. It also tasks the Space Surveillance Network, a network of 30 space surveillance telescopes observing these space objects, which results in approximately 400,000 observations daily. There must be an autonomous system to manage resources generating the catalog of space objects and update information on these space objects for catalog maintenance. Maintaining the growing space object catalog will become more complex due to sensors ever increasing capability to detect a larger number of objects. This work will focus on the development and analysis of a physically-based machine learning algorithm for real-time inference of Space Objects energy parameters and states to predict the space objects orbits for the purpose of sensor tasking system to meet the high-level goals of Space Situational Awareness. By using a predictive algorithm, the system only needs to track periodically instead of continuously, which minimizes system utilization. Summarily, the system will need to be able to track existing objects already in the catalog. The sensors tasking problem will be devised as a Markov Decision Process and solved using Reinforcement Learning to design a deep neural network to generate the optimal actions for the sensors for tracking space objects.

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