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  Neural Network Algorithms for Ontology Informed Information Extraction

  Bethard, Steven; Xu, Dongfang; Cui, Hong; Surdeanu, Mihai; Miller, Timothy (The University of Arizona., 2021)

  Ontology, as a formal and explicit specification of a shared conceptualization for a particular domain, is useful in information extraction. On the one hand, since information extraction is concerned with retrieving information for a particular domain, formally and explicitly specifying the concepts of that domain through an ontology defines the boundary of what information needs to be extracted. On the other hand, an ontology, typically consisting of classes (or concepts), attributes (or properties), and relationships (or relations among class members), contains the structured information that information extraction systems aim to extract. In this thesis, we are interested in how using an ontology can improve the information extraction process. We explore two research directions that both employ ontologies in the information extraction process, temporal normalization and biomedical concept normalization. In both research directions, we show that leveraging resources in ontologies helps to build high-performance information extraction systems, and presenting the extracted output using such ontologies makes the structured information concise and interchangeable.
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  Special Education Teacher Experiences and Efficacy During a Pandemic (COVID-19)

  Pope, Elizabeth; Williams, Raina Lee; Burross, Heidi; McCaslin, Mary; Schutz, Paul (The University of Arizona., 2020)

  In this study, special education teachers in Arizona provided responses to survey and interview questions about their experiences during the COVID-19 pandemic. Survey questions included topics such as: technology, communication with administrators, other teachers, students, and students’ parents, supports and resources, control over decisions being made, preparedness, teacher self-efficacy, and their plans moving forward. In the survey, on average, participants reported less clear and regular communication from their schools and districts during the pandemic than before. Survey participants reported having the resources they needed to teach before the pandemic more from their schools than their districts and during the pandemic reported having more from their districts rather than their schools. On average, participants felt good and effective at their job before the pandemic, and on average felt less good and less effective during the pandemic. Of the five interview participants, 80% felt they had the resources they needed to incorporate technology into their class before the pandemic and less than half reported not having all of the technological resources they needed during the pandemic. Four interview participants said that they felt they had opportunities to share their opinion regarding the pandemic, but they felt it wasn’t seriously considered for the final decision. Of the five special education teachers that participated in interviews, four of them said that transparency is the number one thing that they need moving forward. Implications for school administrators, administrators of teacher preparation programs, and special education teachers are discussed as well as recommendations for future research.
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  Physicochemical and Hydraulic Characterization of Soilless Greenhouse Substrates and Modeling of Flow and Transport in Soilless Substrate Growth Modules with High Performance Computing

  Tuller, Markus; Gohardoust Monfared, Mohammadreza; Ferré, Paul A.; Schaap, Marcel G.; Walworth, James L. (The University of Arizona., 2020)

  Because of the urgent need to secure and sustain the food and water supply for an ever-growing human population, especially in underdeveloped arid and semiarid regions of the world, and an increasing demand for out-of-season fruits, vegetables, and ornamentals in the industrial world, there is a momentous incentive to shift from soil-based crop production to more resource-efficient containerized soilless culture production systems. Mineral and organic substrates are commonly mixed to establish an optimal rhizosphere environment for soilless crop production. Soilless substrates exhibit major advantages over soils. Besides the alleviated risk for spreading soilborne pathogens, the physicochemical properties of soilless substrates can be controlled within narrow margins, which commonly leads to healthier plants and higher yields than in soil-based production, while conserving water resources. Although there is considerable recent empirical and theoretical research devoted to specific issues related to the control and management of soilless culture production systems, a comprehensive approach that quantitatively considers all relevant physicochemical processes within the growth substrates is lacking. An important first step towards the advancement of soilless culture management strategies is a comprehensive characterization of hydraulic and physicochemical substrate properties. In course of my dissertation research, I have applied state-of-the-art measurement techniques to characterize six soilless substrates and mixtures including coconut coir, perlite, volcanic tuff, perlite/coconut coir (50/50 vol.-%), tuff/coconut coir (70/30 vol.-%), and foamed glass (Growstone®)/coconut coir (50/50 vol.-%), all of which are commonly used in commercial soilless culture production. The measured properties include water retention characteristics, saturated hydraulic conductivity, packing and particle densities, as well as phosphorus and ammonium adsorption isotherms.Although economic and environmental considerations are important when selecting suitable soilless substrates, their physicochemical and hydraulic properties are the most imperative performance indicators. While the chemistry of soilless substrate systems can be manipulated and managed to a large extent during the growth season, there is little opportunity for altering the hydraulic properties, which implies the crucial importance of initial plant-specific substrate selection. While the substrate water characteristic (SWC), which defines the relationship between water content and matric potential and governs the storage and release of water, is essential for precise irrigation and fertilization management, its measurement is very laborious. In soilless culture production, it is common practice to test growth substrates via costly and time-consuming trial and error experiments. To provide a scientifically sound basis for a priori elimination of substrate mixtures with unfavorable water retention and associated aeration characteristics, as part of my dissertation, I have developed a new model for the estimation of water retention properties of two-component soilless substrate mixtures with arbitrary mixing ratios based on the water characteristics of their pure constituents. A comparison of mixture SWCs measured with cutting-edge laboratory methods and estimated with my new model revealed a very good agreement for the tuff/coconut coir, perlite/coconut coir, and foamed glass/coconut coir mixtures. The new model can be applied in conjunction with numerical simulations to tailor soilless substrate mixtures for specific crop physiological traits and aid with the design of growth modules and the selection of optimal irrigation and fertigation practices. To advance numerical simulations of three-dimensional water flow and solute transport in containerized variably saturated soilless substrates, the final part of my dissertation research has been focused on the adaptation and validation of the open-source ParSWMS numerical code for High Performance Computing (HPC). Numerical simulation of three-dimensional water flow and solute transport in containerized variably saturated soilless substrates with complex hydraulic properties and boundary conditions necessitates high-resolution discretization of the spatial and temporal domains, which commonly leads to several million nodes requiring numerical evaluation. Even today’s computing prowess of workstations is not adequate to tackle such problems within a reasonable timeframe, especially when numerous realizations are desired to optimize the geometry, substrate properties, and irrigation and fertigation management of soilless plant growth modules. Hence, the parallelization of the numerical code and the utilization of HPC are essential. In course of my dissertation research, I have adapted and applied the open-source ParSWMS parallelized code that is amenable to solving the 3D Richards equation for water flow and the convection-dispersion equation (CDE) for solute transport subject to linear solute adsorption. The code was modified to allow for nonlinear equilibrium solute adsorption with new boundary conditions and applied to simulate water flow and nitrogen and phosphorus transport in containerized soilless substrates. Multi-solute transport simulations with the modified Linux ParSWMS code were first performed on a workstation and referenced to the Windows-based HYDRUS (2D/3D) numerical code. After confirming the agreement between the modified ParSWMS code and HYDRUS (2D/3D), various preconditioners and iterative solvers were evaluated to find the computationally most efficient combinations. The performance of the modified ParSWMS code and its stability were compared to HYDRUS (2D/3D) simulations for three soilless substrates consisting of horticultural perlite, volcanic tuff, and a volcanic tuff/coconut coir mixture. Considering the solute mass balance error as a stability measure, ParSWMS outperformed HYDRUS (2D/3D). Moreover, simulations with the modified ParSWMS code were about 22% faster than simulations with HYDRUS (2D/3D) on the workstation. Tests of ParSWMS on two HPC clusters with 28 and 94 cores revealed a potential 94% simulation speedup relative to the HYDRUS (2D/3D) simulations performed on the workstation.
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  Fundamental Information-Theoretic Limits of Distributed Information Retrieval and Processing

  Tandon, Ravi; Attia, Mohamed Adel; Lazos, Loukas; Vasic, Bane; Glickenstein, David (The University of Arizona., 2020)

  We consider an information theoretic study of the challenges facing distributed information processing and retrieval systems, in which the data is partitioned, stored, and processed across distributed machines/workers. In our research, we propose practical solutions leveraging tools from information and coding theory. In large-scale systems, there are several challenges in moving towards distributed algorithms compared to other centralized approaches. These challenges include communication bottlenecks due to data movement across machines, latency due to heterogeneity among working nodes, and privacy concerns from untrustworthy service providers. In this dissertation, we address the above challenges by a) devising novel coding schemes and optimal storage design to minimize the communication overhead needed to shuffle the data among distributed nodes; b) minimizing the impact of heterogeneity via novel iterative work exchange and balancing among nodes, and c) characterizing the fundamental limits of privately retrieving information from distributed databases under the following practical constraints: limited storage at databases, tolerable privacy leakage, and privacy for hidden latent variables.Data shuffling between a distributed cluster of nodes is one of the critical steps in implementing large-scale learning algorithms. Randomly shuffling the data-set among a cluster of workers allows different nodes to obtain fresh data assignments at each learning epoch. This process has been shown to provide statistical improvements in the learning process (via testing and training error). However, the statistical benefits of distributed data shuffling come at the cost of extra communication overhead from the master node to worker nodes, and can act as one of the major bottlenecks in the overall time for computation. Another major bottleneck that adversely impacts the time efficiency is the computational heterogeneity of distributed nodes, often limiting the task completion time due to the slowest worker. In our first contribution, we propose new approaches to increase the time efficiency in distributed computing systems. First, we study how to use codes and exploit excess storage at workers in a principled manner in order to reduce communication overhead for distributed data shuffling. Then, we present our approach of work exchange to combat the latency problem, in which faster workers can be reassigned additional leftover computations that were originally assigned to slower workers. In distributed retrieval systems, assuring privacy while retrieving information from public databases has become a crucial need for users. Private information retrieval (PIR) allows a user to retrieve a desired message from a set of databases without revealing the identity of the desired message. The replicated database scenario, where N databases store each of the K messages was considered by Sun and Jafar, and the optimal download cost was characterized. In our second objective, we consider a practical scenario where the databases are not replicated and have storage limitations. In particular, we study the problem of PIR from uncoded storage constrained databases, where each database has a limited storage capacity and is only allowed to store uncoded data. The novel aspect of this work is to characterize the optimum download cost of PIR from uncoded storage constrained databases for any storage value. In our third and final objective, we consider other practical scenarios for the PIR model where perfect privacy is not necessarily required. These scenarios arise in applications where some leakage in the privacy is tolerable with the goal of enhancing the PIR capacity. We focus on two models for privacy leakage. In the first model, we assume asymmetric bounded leakage for both user privacy, i.e., message identity and database privacy, i.e, information user obtains about unwanted messages. We refer to this model as Asymmetric Leaky PIR (AL-SPIR). We study the three-way tradeoff between user privacy, database privacy, and communication efficiency of PIR. In the second model, we propose a novel relaxed privacy definition for PIR. Instead of hiding the message index queried by the user, we focus on providing information-theoretic privacy for latent traits. We model the user profile with a latent variable model captured by a latent random variable S. Using this new privacy notion, also refereed to as Latent Variable PIR (LV-PIR), we show how the PIR download cost from a single database can be reduced.
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  Improving Patient Knowledge and Confidence in Implementing Physical Activity for Hypertension

  Pacheco, Christy L.; Race, Alyssa Ann; Gregg, Renee S.; Godfrey, Timian M. (The University of Arizona., 2020)

  Purpose: The purpose of this DNP quality improvement project was to create an educational webinar to improve patient knowledge and confidence in managing hypertension by providing education over the disease process, techniques for adequate blood pressure measurements, and reasoning behind the importance of physical activity. Background: Hypertension is the top chronic condition diagnosed and managed within the primary care setting. Almost half of the adult American population are affected by hypertension, accounting for an estimated $131B in annual healthcare expenses. Only about 25% of the population has their blood pressure under control. Incorporating physical activity into management plan is an inexpensive and effective way to help control blood pressure. There is an estimated 100+ known hypertensive patients at James R. Brown, M.D., Inc. This practice recently introduced the use of technology, such as podcasts and social media, to educate patients at a safe distance during the COVID-19 pandemic. Methods: Through collaboration with this primary care practice, a patient-focused educational webinar about hypertension was created. An email and social media post invited eligible patients to participate in this project. An online anonymous quantitative survey was used to evaluate the impact of the educational webinar on patient knowledge and confidence and use of technology for patient education. Results: The practice identified 30 eligible patients with hypertension to participate. The webinar was viewed 35 times, social media posts received 12 likes, and 4 patients attempted the survey. Only 3 participants completed the evaluation survey. The amount of participation was less than expected, but responses to knowledge-based questions improved after viewing the webinar and responses focused on satisfaction and increasing physical activity were positive. Conclusion: The low participation rate suggests this form of education through email and social media was new to the patient population at James R. Brown, M.D., Inc. The responses received showed positive impact in patient knowledge and confidence in hypertension management and the use of technology to promote patient education during the COVID-19 pandemic. The implementation of a webinar to promote patient education may lead to better control over blood pressure management in patients at the project site.
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  Near Real-Time Forecasting of Epidemics Using Data Assimilation with Simple Models

  Lega, Joceline; Biegel, Hannah; Morzfeld, Matthias; Watkins, Joe; Zhang, Hao (The University of Arizona., 2020)

  With the advent of expedient data sharing of epidemiological reports, efforts have been made to forecast ongoing epidemics in real-time. Throughout this work, we develop a real-time forecasting framework that can be applied to a variety of diseases. Specifically this framework pairs data assimilation with a simple mechanistic model in the form of an incidence vs cumulative cases (ICC) curve. We provide results in two different contexts: seasonal influenza and COVID-19. We demonstrate that the flexibility in this framework results in accurate forecasts even when disease dynamics change during the outbreak, such as was the case with COVID-19. We further provide the groundwork for an avenue of improvement of the flu forecasts by using epidemiological data available early on in the flu season to categorize the severity of the ongoing season. The presented framework can be applied to other diseases, locations, or population scales.
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  Data Assimilation and Applications in Forecasting

  Morzfeld, Matthias; Harty, Travis Michael; Snyder, Chris; Venkataramani, Shankar C.; Arellano, Avelino F. (The University of Arizona., 2021)

  The work presented here spans two projects which are connected by data assimilationand specifically the ensemble Kalman filter (EnKF). The first explores how spatial localization, an important method commonly used in the EnKF, can be extended to multiscale problems. Rather than using a single length scale when localizing, we construct a localized covariance matrix through the estimation of eigenvectors. Specifically, we estimate the leading large-scale eigenvectors from a sample covari- ance matrix calculated from a spatially smoothed ensemble with spatial localization applied with a long localization distance. We then create projection matrices from these eigenvectors which allows us to calculate the space orthogonal to these initial large scales. This process can then be repeated for multiple scales if required. We present numerical experiments using this localization method using both simplified examples in which the correct covariance matrix is known and cycling experiments with the Lorenz Model III. The second project explores an application of the EnKF. We use the EnKF as part of a system to forecast cloud cover. Cloud cover forecasts are useful when forecasting solar power generation because clouds are the primary driver of reducing irradiance and therefore solar power generation. Our method uses satellite images, optical flow, and numerical weather prediction (NWP) in conjunction with an EnKF to estimate cloud motion vectors (CMVs) which are then used to advect cloud index (CI) fields using a 2-D advection scheme. This system produces an ensemble forecast which can be used to produce deterministic forecasts. We explore the effectiveness of these forecasts over Tucson, AZ.
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  Cognitive and Adaptive Equalizer Implementation in GNU Radio

  Bose, Tamal; Elkadi, Melissa Margret; Marcellin, Michael; Ditzler, Gregory (The University of Arizona., 2020)

  Machine learning (ML) is now being applied to wireless communications to optimize existing communication techniques. GNU Radio, an open-source developmental toolkit used to model communication systems, however, has seen few machine learning techniques implemented in its library. Real time simulators, like GNU Radio, are critical in verifying the performance of communication systems. One aspect of communication theory that can be improved by machine learning is adaptive equalization. Specifically, machine learning can be used to adjust the type of adaptive equalizer algorithm as well as the structure of an equalizer (i.e. taps, step size, filter type, etc.) to determine optimal equalizer parameters for current channel conditions. This process is referred to as cognitive equalization. The objective of this research is to demonstrate how cognitive equalization algorithms can be implemented in GNU Radio along with channel model blocks as tools for further validate the cognitive equalizers. This is valuable for analyzing modern equalization techniques in various channel conditions and communication scenarios. When a signal is passed from transmitter to receiver, the channel effects on the signal can be drastic. This is especially apparent in high frequency (HF) communications (3 MHz to 30 MHz) where the effects are caused by reflections of the transmitted signal across the ionosphere. One consequence caused by the ionosphere is that the signal will take multiple paths when arriving at the receiver. Due to the various propagation paths, several components of the signal will arrive at the receiver at different times, causing multipath. Furthermore, signal fading can be observed when multiple paths are taken by the signal during transmission and the arriving signal is summed at the receiver and cancellation occurs. Channels will often introduce noise to the signal and cause inter-symbol interference (ISI), which will create errors in signal recovery. Inter-symbol interference, multipath, and fading, will result in a corrupted signal which will be difficult for the receiver to interpret. This corrupted signal can be reconstructed at the receiver with the aid of an equalizer. Equalization can be used to optimize the signal recovery in various communication systems by removing the impairments caused by the channel from the received signal. The equalizers implemented in this work utilize a least mean square (LMS) algorithm to update the associated tap values, making them a form of adaptive equalizers. Both linear and non-linear adaptive equalizers were implemented in GNU Radio, and the implementation is discussed further in this work. An additional enhancement that can be made to improve the effectiveness of the equalizers is to utilize reinforcement learning algorithms to vary the structure of the equalizer. The reinforcement learning algorithm will update the structure based on the incoming signal’s channel effects in attempt to lower the error rates. The use of a reinforcement learning algorithm in changing an attribute of a communication system based on the channel conditions is referred to as a cognitive engine. These cognitive engines can change the actual structure of the equalizer by changing the number of parameters, such as the number of taps and step size. Alternatively, the adaptive algorithms utilized within the equalizer only change the coefficient value of the taps. The benefit of implementing cognitive engines in GNU Radio is it enables the optimal equalizer parameters to be learned for a specific set of channel conditions in real time. Additionally, the implementation of these cognitive communication systems sets the stage for future development with the incorporation of real hardware. This will allow us to conduct real-time tests with true over-the-air experiments. This work details the implementation of three cognitive engines and three different channel models within GNU Radio. The contributions of this thesis include the development and deployment of three LMS adaptive equalizers into the GNU Radio library. This development included various validation tests conducted to guarantee the functionality of these equalizers. These tests included analyzing the convergence trends posed by the LMS algorithm for the tap coefficient values and the changing bit error rate (BER) for several SNR values. Contributions related to the design of the Watterson channel model have also been included in this work. Following the implementation of the adaptive equalizers, we then deployed a cognitive engine block into GNU Radio, which utilizes the epsilon greedy RL algorithm. This algorithm was tested prior to implementation and further validated with the previously implemented adaptive equalizers. The CE and equalizers were then tested together to ensure that the CE does in fact improve the performance of the equalizers by changing the structure of each equalizer based on the current channel conditions.  
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  Silicon Photonics Expanding into Cryogenics, and the Future of Optical Interconnects

  Peyghambarian, Nasser; Norwood, Robert A.; Fard, Erfan Motafakker; Pau, Stanley K. H. (The University of Arizona., 2020)

  Significant advances in silicon photonics over the last two decades have led to a wide array of robust photonic devices that have found many applications including in telecommunications. Despite these advances, the cost of optical interfacing (packaging) of photonic integrated circuits (ICs) makes up the bulk of the manufacturing cost of these chips. In this dissertation, I will present my research in developing compact, efficient and low-cost adiabatic couplers that can enable lower-cost and higher-throughput manufacturing of photonic ICs. I will also present a novel method for designing compact, highly efficient and high misalignment tolerance multi-segment couplers for chip-to-chip connectivity. This technology was also extended to ion-exchange glass waveguides which can provide a platform for more efficient chip-to-chip communication and more economical integration of photonic and electronic components. I will further demonstrate electro-optic modulation using silicon micro-disk modulators and wavelength division multiplexing at cryogenic temperatures which is pivotal to the advancement of cryogenic computing systems including cryogenic supercomputers of the future.
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  Franz Schubert’s Use of Harmony To Express the Texts in His Musical Settings of Franz Grillparzer's Poetry

  Brobeck, John T.; Chamberlain, Bruce; Crosby, Matthew; Schauer, Elizabeth (The University of Arizona., 2020)

  Franz Schubert (1797-1828) is perhaps best known for his artistic development of German Lieder. Schubert’s choral songs with poetic texts, however, have been given little attention, especially with regard to his treatment of harmony. Three vocal works, the art song Bertha’s Lied in der Nacht, D 653, the part-song Ständchen, D 920, and the cantata Mirjams Siegesgesang, D 942, are Schubert’s only musical settings of the texts of the Austrian poet Franz Grillparzer (1791-1872). This paper will focus on the harmonic elements in these works and their abilities to express the text. Harmonic motives, as discussed in the analysis of Brian Black, serve as descriptors for Schubert’s harmonic expression of text on the micro and macro levels. Schubert has been both lauded and berated for his incorporation of chromatic harmony. This document suggests that the study of the relationship between Schubert’s choice of harmony and his text setting is key to understanding his artistry as a composer and essential to interpreting these works as a performer.
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  Feasibility and Acceptability of Alternate Nostril Breathing to Reduce Stress in Pregnant Women Survivors of Intimate Partner Violence: A Mixed Methods Study

  Loescher, Lois J.; Rung, Ottilie; Stauber, Leah; Pace, Thaddeus W. (The University of Arizona., 2020)

  Intimate partner violence (IPV) is a pervasive and insidious problem that results in considerable deleterious effects to the physical and psychological health of women, as well as their children. When women exposed to IPV are pregnant, it also results in poor pregnancy and birth outcomes for themselves and their fetuses. Evidence suggests that these impacts result due to toxic stress experienced by women exposed to IPV. Alternate nostril breathing (ANB), a slow yogic breathing technique, has demonstrated effectiveness in reducing stress in various populations, including women who were pregnant, but had not experienced IPV, and women who experienced IPV, but were not pregnant. This dissertation study aimed to determine the feasibility and acceptability of an intervention of ANB to reduce stress in pregnant survivors of IPV. Mitigating the stress of these women could potentially be an initial step in improving their pregnancy and birth outcomes. This mixed methods dissertation study initially was conducted in a face-to-face format, and included collection of salivary C-reactive protein (CRP) pre- and post-intervention in order to assess convergence or divergence with results from pre- and posttest scores on the perceived stress scale (PSS-10), in addition to thematic analysis of post-intervention interview data. Due to the onset of the COVID-19 pandemic, the study had to be revised to a completely online format. This was performed using the research electronic data capture (REDCap) program. CRP could no longer be collected in an online format. Conducting an interventional study with a highly vulnerable population (pregnant women exposed to IPV) during a pandemic proved to present considerable challenges to enrollment and retention. This dissertation describes the study and examines potential methods to improve recruitment, enrollment, and retention of a highly vulnerable population.
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  The Characterization of Apollo in the Iliad

  Park, Arum; Burks, Jonathan Phillip; Christenson, David; Friesen, Courtney (The University of Arizona., 2020)

  This thesis explores the actions and behaviors of Apollo and his impact on the story of Homer’s Iliad. Apollo’s actions throughout the epic are complex and sometimes strange. I examine Apollo’s words and deeds to determine how he influences the story. Apollo’s character proves not only the catalyst of the poem, but he also plays a necessary role in the outcome of the story. While scholarly focus is predominately directed at the mortal characters, the gods’ individual characterization in the Iliad warrants equal examination. While the bulk of my thesis will be an intense focus on Apollo’s actions, it is important to examine them against some of the actions of the other gods in the epic. My Introduction lays out my methodology and purpose, and analyzes explores the actions of the other major gods of the epic. I focus on gods whose actions either inform, emphasize, or allude to Apollo’s own actions. Chapter 1 explores Apollo in books 1-12 and specifically how he catalyzes the story and his interest in guarding the boundary between men and gods. Chapter 2 analyzes Apollo in books 13-24, especially in his role as agent of fate and Zeus’ will. My summary conclusion emphasizes just how vital and nuanced Apollo is as a character in the Iliad.
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  Epigenetics of BRCA1 and Xenobiotic Sensory in Breast Cancer

  Romagnolo, Donato F.; Donovan, Micah Gerard; Selmin, Ornella I.; Doetschman, Thomas C.; Laukaitis, Christina; Hebert, Lora (The University of Arizona., 2020)

  Breast cancers are the most common malignancies and leading causes of cancer mortality among women worldwide. Global breast cancer statistics reveal vast international and interethnic differences, which are attributed to non-genetic risk factors such as dietary pattern. Several lines of evidence indicate a role of the aryl hydrocarbon receptor (AhR) in breast cancer initiation and promotion of aggressive tumor phenotypes. The studies documented in this dissertation investigate the effects of the soy isoflavone genistein on oncogenic activity of the AhR in multiple in vitro and in vivo model systems. Cell culture studies investigating the effect of genistein on AhR-dependent epigenetic regulation of BRCA1 were performed in HCC38 triple negative breast cancer (TNBC) and MCF7 luminal A breast cancer cells. The effects of lifetime exposure to dietary genistein on carcinogen induced mammary tumors were investigated in a mouse model of BRCA1 mutation carriers (Brca1+/-) and wildtype littermates. The Brca1+/- model was derived using Brca1+/F22-24 mice and CRE-LOX recombination driven by transgenic expression of Cre under control of a mouse mammary tumor virus (MMTV) promoter construct. Cell culture studies demonstrated genistein reversed BRCA1 epigenetic silencing in HCC38 cells, which was attributed to antagonism toward overexpressed and hyperactive AhR. Mouse studies suggested the effect of lifetime exposure to dietary genistein on carcinogen-induced mammary tumorigenesis is dependent on genotype (Brca1+/+ vs. Brca1+/-). In Brca1+/+ mice, the genistein diet suppressed tumor growth, whereas tumor growth was enhanced in Brca1+/- mice administered genistein. These collective studies indicate the potential utility for genistein to influence epigenetic regulation of BRCA1 and antagonize AhR in mammary tumorigenesis.
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  Implementing an Educational Module on Integrative Therapies Used Among Palliative Care Patients

  Rishel, Cindy J.; Diola, Lea; Morrison, Helena W.; Carlisle, Heather L. (The University of Arizona., 2020)

  Purpose. To evaluate the influence of an educational module about integrative therapies used in palliative care on knowledge among palliative care patients and its feasibility as a tool to provide patient education at the University of Arizona Telehealth Learning Center (TLC). Background. Palliative care is an interdisciplinary medical approach that aims to provide supportive care for chronically or critically ill individuals. Integrative palliative care helps improve the delivery of palliative care by incorporating integrative therapies in the palliative care setting. However, 80% of palliative care patients reported a lack of knowledge of integrative therapies. This project aimed to address the lack of patient education through an educational module on integrative therapies. Methods. This QI project was implemented online at the University of Arizona TLC on 10 simulated palliative care patients (SPs) using Zoom because of the COVID-19 pandemic. The SPs completed a pre-test survey to determine their baseline knowledge of integrative therapies before participating in a 20-minute Panopto educational module. After completing the educational module, the SPs answered a post-test survey to assess knowledge acquisition of integrative therapies and a post-test questionnaire to evaluate the feasibility of the educational module as a tool to deliver patient education. Results. The educational module resulted in knowledge acquisition among the SPs (N= 10) with a mean improvement of 2.6 correct answers and a standard deviation of 2.01. There was a statistically significant difference between the pre-test and post-test scores (P= 0.003). The SPs who completed the post-test questionnaire (N= 9) stated that they “strongly agree” and “somewhat agree” that the educational module was a feasible tool for patient education. Only one SP (11.1%) “neither agreed nor disagreed” that the overall presentation of the educational module was conducive to learning. Conclusions. An educational module on integrative therapies used in palliative care was a feasible tool for patient education and improved patient knowledge of integrative therapies. Ongoing implementation of the educational module can benefit more palliative care patients. To help advance future practice and research in palliative care, the results from this pilot project can be disseminated to other palliative care clinics or institutions.
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  Patient Education on Medication Assisted Treatment for Opioid Use Disorder

  Davis, Mary P.; Torres, Nidia J.; Carlisle, Heather L.; Jovanov, Cynthia (The University of Arizona., 2020)

  Purpose: The purpose of this Doctor of Nursing Practice (DNP) quality improvement(QI) project was to increase knowledge of opioid use disorder (OUD) treatment via patient education on medication assisted treatment (MAT). A secondary aim was to promote an attitude change about persons with OUD. This scholarly inquiry was conducted as a quantitative design with descriptive analysis.Background: In 2018 there were over 47K deaths from opioid overdoses. This is about 130 people dying per day from opioids. In that same year, there were over 2 million people who were diagnosed with OUD and over 10 million who report misusing prescription opioids. The misuse of prescription opioids costs the U.S. $78.5 billion a year. Every month there are over 136K opioid prescriptions filled by pharmacies in Tucson AZ. This is an equivalent of 43mg of morphine per person per day. MAT is considered the best treatment option for opioid use disorder (OUD). It includes the use of medications such as (buprenorphine methadone or naltrexone) along with psychosocial and behavioral therapy. Methods: The setting for this project was the University of Arizona, Telehealth Learning Center. The participants were treated as patients and selected using convenience sampling. The Model for Improvement was used to guide the implementation of this quality improvement project. The tested change was delivered in the form of an evidence-based electronic educational presentation for patients that describes medication-assisted treatment for opioid used disorder. Evaluation was conducted with pre and post surveys to assess participant’s pre and post knowledge related to medication-assisted treatment for opioid use disorder. Results: Most participants understood what comprised MAT pre-intervention, but this project was efficacious in increasing knowledge in relation to where to obtain MAT. This project successfully broadened descriptive responses to include outcomes and treatment facilities which complements the increase in knowledge as to where to obtain MAT. There was little change in the belief, intent or attitude questions on the pre and post survey responses. Conclusions: An evidence based educational intervention can be effective in disseminating information about MAT and increasing understanding about OUD.
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  Improving Culturally-Based Diet among Hispanic Adults with Type 2 Diabetes Mellitus at Clinical Amistad

  Martin-Plank, Lorraine; Paguio, Chantel Therese B.; Godfrey, Timian; Williams, Deborah (The University of Arizona., 2020)

  Background: Culture is an important aspect when managing type 2 diabetes mellitus (T2DM) and plays significant role in determining dietary patterns. Evidence supports increased patient empowerment and motivation of diet modification when healthcare providers provide cultural humility and offer cultural tailored nutrition-based intervention. Purpose: Improve nutritional and dietary choices among Hispanic adults with T2DM by incorporating culturally based tailored strategies. Approach Methods: This project utilized a 1-group pretest-posttest design at baseline and at the patient’s follow up visit. An evidenced based education session on culturally-based diet including portion sizes and alternative options were presented to the participants. Results/Conclusion: The participants showed increased adherence to decreasing portion sizes and modification to their diet after culturally based education. The project highlighted the importance of acknowledging cultural aspect for diet modification when it comes to T2DM management.
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  What Happened? Co-Regulation and Personal Growth in Youth Sport

  McCaslin, Mary; Pierce, Lauren Elizabeth; Burross, Heidi; Good, Thomas; Erbacher, Monica (The University of Arizona., 2020)

  Youth athletes in team sports are embedded within a complex co-regulatory system. Their club implements expectations and regulations upon the players, their coaches work with the club to define the sociocultural system, and coaches work with teams and players to implement the activities, like practice time and game strategy. These provide opportunities for struggle and negotiation within and among teams, players, and coaches. As teams struggle together and reflect upon shared experiences, tensions emerge that begin to define their identity. This study aims to explore the role of reflection in emergent identity across shared history through the McCaslin (2009) co-regulation framework and causal attribution theory (Weiner, 2010). Results indicate that identified tensions play a key role in how players causally consider and attribute successful or unsuccessful events as they happen to themselves or their team. These tensions create a platform for shared experiences that inform future motivation and emergent identity through individual and team learnings.
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  Skin Inspection Education for the Identification of Skin Cancers in Primary Care

  Pacheco, Christy L.; Longbons, Tamika; Godfrey, Timian; Reel, Sally (The University of Arizona., 2020)

  Purpose. This quality improvement (QI) project aimed to educate providers, nurses regarding risk factors for skin cancer development and identification of pigmented lesions suspicious for skin cancer diseases. The goal was to increase provider, nursing knowledge, confidence in visual skin inspection technique, inform practice change in performance of visual skin inspections, skin cancer screening, and skin inspection education. Background. Skin cancers are most common forms of cancers diagnosed in United States (US), but only 4.4% of US population routinely visit dermatologists (AAD, 2019; Rapaport, 2018). There is an opportunity for primary care providers (PCPs) to aid in screening, early identification, and treatment of skin cancer diseases, however, most PCPs lack training in identification of abnormal skin lesions and rarely perform comprehensive visual skin inspections (Wise et al., 2009). Methods. An asynchronous webinar for providers, nurses was delivered to educate them regarding skin cancer risk factors, identification of abnormal pigmented precancerous and cancerous skin lesions. Content of asynchronous webinar was based on existing clinical decision support course called INFORMED (INternet curriculum FOR Melanoma Early Detection), to educate providers in identification of normal and abnormal skin findings (Weinstock et al., 2020). Post-intervention survey data was collected to evaluate knowledge, confidence, and intent to change practice based on webinar content. Results. QI project sample population included three providers and three nurses. All providers reported webinar increased knowledge of identification of precancerous, cancerous skin lesions, 66.67% of providers reported they would perform more visual skin inspections in primary care clinics. 66.67% of nurses reported feeling more confident in providing patient education regarding skin cancer screening, skin inspection after completing webinar and reported that they would educate more patients as a result. Conclusions. Providers and nurses in primary care clinic increased knowledge of pigmented skin lesions, educating patients regarding skin cancer screening, performed skin inspections after completing asynchronous skin cancer education webinar. Nurses were more confident in ability to provide patient education regarding skin cancer screening and skin inspection. Two thirds of providers and nurses indicated that education would change their clinical practice; they would perform more visual skin inspections and more skin cancer education.
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  Using Telehealth to Educate Geriatrics on the Risk of Depression during COVID-19

  Buchner, Brian; Lomibao, Chanie; Rainbow, Jessica; Kuo, Bradley (The University of Arizona., 2020)

  Purpose: The purpose of this quality improvement project was to present a 10-minute online presentation to a geriatric population aged 65 years old and older about the clinical manifestations of depression, biological and other known risk factors of depression, provide resource options that are available, and when to contact a healthcare provider. Background: The COVID-19 pandemic is a global public health crisis. At the greatest risk of the pandemic is the geriatric population due to their age and chronic health care morbidities. The COVID-19 pandemic has suspended social interactions, enforced statewide lockdowns, and implemented social distancing. Although social isolation can potentially be lifesaving in older adults, the feelings of loneliness can negatively affect the older adult’s mental health. Methods: This quality improvement project included a group of nine volunteer participants from the University of Arizona’s Telehealth Learning Center, who were 65 years old or older. The theoretical framework that drove this project was Lewin’s change model. A Zoom session was held in which the participants were asked to complete a pre-test survey, view the educational video, and complete a post-test survey. Results: Data collection took place prior to the educational presentation, and immediately after, with all nine participants completing both, the pre-test survey and post-test survey. There was a 11.1% increase in the knowledge of risk factors for depression, 77.8% of participants were able to identify clinical manifestations of depression which resulted in no change, and an increase in the ability of participants to identify when to seek help for depression and an improved self-perceived likelihood of seeking help Conclusion: This quality improvement project helped to improve the participant’s knowledge of depression at a basic level. Educating older adults on the risk of depression during the COVID-19 pandemic is key to the likelihood of seeking help.
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  Advanced Practice Registered Nurse Burnout and Mindfulness Meditation

  Prettyman, Allen; Ruiz, Ashley; Daly, Patricia; Karadsheh, Michael (The University of Arizona., 2020)

  Purpose: The purpose of this quality improvement project was to: 1) assess burnout of Advanced Practice Registered Nurses (APRNs) in a primary care clinic in Tucson, Arizona through the Maslach Burnout Inventory for Human Services Survey for Medical Personnel (MBI-HSSMP) pre-test, 2) present the use of mindfulness meditation through an online application, UCLA Mindful, 3) assess burnout of the APRNs through a post-test MBI-HSSMP after using the phone application for seven days. Background: The suicide and turnover rate for healthcare professionals, including APRNs continues to increase every year. The main reason for the high suicide rates and high rates for turnover is the result of burnout, a syndrome characterized by depersonalization, emotional exhaustion, cynicism, and perceived clinical ineffectiveness which not only can affect the health of the individual provider but is also associated with suboptimal patient care, decreased patient satisfaction, and increase the potential for medical errors. With the increasing demand and pressure placed on healthcare professionals, it is imperative to find ways to combat burnout. One such way that is garnering attention and has proved to be effective is mindfulness meditation. Methods: MBI-HSSMP scores, indicative of burnout in healthcare professionals, were measured before as a pre-test and after the APRN’s used the online phone application, UCLA Mindful for seven days, as a post-test. Consent and a demographic questionnaire were completed by the participants, and then they received an online PowerPoint presentation on mindfulness meditation and UCLA Mindful Application on their smart phone. This QI project was a description of a change proposal using the PDSA model. APRN’s in a primary clinic (TMC One) in Tucson, Arizona voluntarily participated in this QI project. Results: All participants completed the intervention and after seven days of application use, MBI-HSSMP scores improved, specifically in the subscales of emotional exhaustion (EE) and depersonalization (DP), which directly measure burnout of healthcare professionals. Conclusions: This pilot QI project employed an effective strategy to use mindfulness meditation through an online application to combat burnout and subsequent turnover that APRNs face in their careers. In order for APRNs to provide high-quality patient care, ways in which burnout can be lessened must be explored.

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