The Arizona Teachers Academy is a program that was first designed and implemented by Governor Doug Ducey in 2017 with a simple concept: to cover the tuition and fees of Arizona higher education students learning to teach in exchange for fulfilling a commitment to teach at an Arizona public school following graduation. The academy has evolved quite rapidly in its short history, going from an unfunded mandate that Arizona universities could not afford to be funded to a voter-approved tax, and seeing its student enrollment numbers increase by over tenfold. This paper seeks to be an overview and process evaluation of the program, as well as an outlook into the program’s future. As a process evaluation, the thesis includes examinations of the program’s presumed logic model, that model’s assumptions, and relevant stakeholders. I used a multi-method approach: statutory and financial data were collected from web research and agency archival collections, and a series of interviews were conducted to ask analytical questions to key stakeholders and program directors about the program’s internal operations and data findings. These stakeholders and program directors consist of staff at the Arizona Board of Regents, the Arizona Department of Education, all three major Arizona public universities (Arizona State University, Northern Arizona University, and the University of Arizona), as well as multiple elected officials and political advocacy groups that have impacted the program through legislation and ballot initiative. This thesis finds that the Arizona Teachers Academy does not have a stated logic model, which in turn led to program assumptions that fail to meet the needs of Arizona public schools and did not allow for all key stakeholders to be involved in the process.

In the United States, clinical testing is monitored by the federal and state governments, held to standards to ensure the safety and efficacy of these tests, as well as maintaining privacy for patients receiving a test. In order for the ABCTL to lawfully operate in the state of Arizona, it had to meet various legal criteria. These major legal considerations, in no particular order, are: Clinical Laboratory Improvement Amendments compliance; FDA Emergency Use Authorization (EUA); Health Insurance Portability and Accountability Act compliance; state licensure; patient, state, and federal result reporting; and liability. <br/>In this paper, the EUA pathway will be examined and contextualized in relation to the ABCTL. This will include an examination of the FDA regulations and policies that affect the laboratory during its operations, as well as a look at the different authorization pathways for diagnostic tests present during the COVID-19 pandemic.

One of the largest problems facing modern medicine is drug resistance. Many classes of drugs can be rendered ineffective if their target is able to acquire beneficial mutations. While this is an excellent showcase of the power of evolution, it necessitates the development of increasingly stronger drugs to combat resistant pathogens. Not only is this strategy costly and time consuming, it is also unsustainable. To contend with this problem, many multi-drug treatment strategies are being explored. Previous studies have shown that resistance to some drug combinations is not possible, for example, resistance to a common antifungal drug, fluconazole, seems impossible in the presence of radicicol. We believe that in order to understand the viability of multi-drug strategies in combating drug resistance, we must understand the full spectrum of resistance mutations that an organism can develop, not just the most common ones. It is possible that rare mutations exist that are resistant to both drugs. Knowing the frequency of such mutations is important for making predictions about how problematic they will be when multi-drug strategies are used to treat human disease. This experiment aims to expand on previous research on the evolution of drug resistance in S. cerevisiae by using molecular barcodes to track ~100,000 evolving lineages simultaneously. The barcoded cells were evolved with serial transfers for seven weeks (200 generations) in three concentrations of the antifungal Fluconazole, three concentrations of the Hsp90 inhibitor Radicicol, and in four combinations of Fluconazole and Radicicol. Sequencing data was used to track barcode frequencies over the course of the evolution, allowing us to observe resistant lineages as they rise and quantify differences in resistance evolution across the different conditions. We were able to successfully observe over 100,000 replicates simultaneously, revealing many adaptive lineages in all conditions. Our results also show clear differences across drug concentrations and combinations, with the highest drug concentrations exhibiting distinct behaviors.

As political campaigning becomes increasingly digital and data-driven, data privacy has become a question of democratic governance. Yet, Congress has yet to pass a comprehensive federal data privacy law and even the strongest subnational data privacy laws exempt political campaigns from regulation. <br/><br/>This thesis examines how data privacy laws impact data-driven and digital political campaigning. Specifically, it investigates what information is incorporated into the political data ecosystem, how data privacy laws regulate the collection of this data, and how actors in the political data ecosystem respond to these laws. It examines both sector-specific federal law and subnational data protection regulation through a case study of California. This research suggests that although the California Consumer Privacy Act and California Privacy Rights Act are landmark steps in American data protection, subnational data privacy law remains inhibited by the federal market-based approach.

Disinformation has long been a tactic used by the Russian government to achieve its goals. Today, Vladimir Putin aims to achieve several things: weaken the United States’ strength on the world stage, relieve Western sanctions on himself and his inner circle, and reassert dominant influence over Russia’s near abroad (the Baltics, Ukraine, etc.). This research analyzed disinformation in English, Spanish, and Russian; noting the dominant narratives and geopolitical goals Russia hoped to achieve by destabilizing democracy in each country/region.

Artificial Intelligence’s facial recognition programs are inherently racially biased. The programs are not necessarily created with the intent to disproportionately impact marginalized communities, but through their data mining process of learning, they can become biased as the data they use may train them to think in a biased manner. Biased data is difficult to spot as the programming field is homogeneous and this issue reflects underlying societal biases. Facial recognition programs do not identify minorities at the same rate as their Caucasian counterparts leading to false positives in identifications and an increase of run-ins with the law. AI does not have the ability to role-reverse judge as a human does and therefore its use should be limited until a more equitable program is developed and thoroughly tested.

The thesis analyzes the apathetic youth turnout myth and researches to see if voter suppression can explain the reason behind low youth turnout. This thesis is a study done with Arizona State University students to assess their level of voter turnout, their levels of political engagement, and if they have experienced voter suppression. Respondents were also asked about the support given by ASU in terms of helping with the voting process. Results indicate that Arizona State students have high levels of political engagement, and that 1 in 5 ASU students have experienced voter suppression. Furthermore, ASU students on a whole are uncertain about the role ASU should play in supporting students with the voting process.

The field of behavioral economics explores the ways in which individuals make choices under uncertainty, in part, by examining the role that risk attitudes play in a person’s efforts to maximize their own utility. This thesis aims to contribute to the body of economic literature regarding risk attitudes by first evaluating the traditional economic method for discerning risk coefficients by examining whether students provide reasonable answers to lottery questions. Second, the answers of reasonable respondents are subject to our economic model using the CRRA utility function in which Python code is used to make predictions of the risk coefficients of respondents via a two-step regression procedure. Lastly, the degree to which the economic model provides a good fit for the lottery answers given by reasonable respondents is discerned. The most notable findings of the study are as follows. College students had extreme difficulty in understanding lottery questions of this sort, with Medical and Life Science majors struggling significantly more than both Business and Engineering majors. Additionally, gender was correlated with estimated risk coefficients, with females being more risk-loving relative to males. Lastly, in regards to the model’s goodness of fit when evaluating potential losses, the expected utility model involving choice under uncertainty was consistent with the behavior of progressives and moderates but inconsistent with the behavior of conservatives.

Water quality and accessibility can impact most aspects of life such as hygiene, medicine, thermal comfort, sewage disposal, and health, to name a few. Rising concerns related to the quality of drinking water in the United States caused by municipal water utility failures such as in Texas or in Michigan has led to an inquiry into the root cause of how a supply-chain for a basic necessity such as water can run into issues. After initial research and investigation, one hypothesis for this was the nature of how recyclable materials in a linear economy eventually run into production or storage problems as exhaustible resources (or space) become less accessible over time. To remedy this issue, LifeGear360 is introduced to allow individual users the liberty to treat their water directly if needed, while also remaining in a circular economy for the lifecycle of the product. As a backpack with water treatment capabilities, natural plant fibers are used to ensure a renewable cycle of production while also redefining the traditional “plastic-taste” characteristics many people associate with water pouches to a smoother, cleaner taste. Engineering, sustainability, and business and public service practice have been used in an interdisciplinary way to prepare this product for its intended use such as in school, for travel, and for the outdoors. According to the collected outreach, many indicated that they feel as though there is a need for a product that allows for the feeling of water security which can include carrying any personal belongings as well. Marketing strategies such as logo creating and online outreach continually influence product design, up until production would take place following the finalized design.