The COVID-19 pandemic has and will continue to radically shift the workplace. An increasing percentage of the workforce desires flexible working options and, as such, firms are likely to require less office space going forward. Additionally, the economic downturn caused by the pandemic provides an opportunity for companies to secure favorable rent rates on new lease agreements. This project aims to evaluate and measure Company X’s potential cost savings from terminating current leases and downsizing office space in five selected cities. Along with city-specific real estate market research and forecasts, we employ a four-stage model of Company X’s real estate negotiation process to analyze whether existing lease agreements in these cities should be renewed or terminated.

Following the Global Financial Crisis of 2007-2008, financial institutions faced regulatory changes due to inherent weaknesses that were exposed by the recession. Within the United States, regulation came via the passing of the Dodd-Frank Wall Street Reform and Consumer Protection Act in 2010, which was heavily influenced by the internationally focused Basel III accord. A key component to both of these sets of regulations focused on raising the capital requirements for financial institutions, as well as creating capital buffers to help protect solvency during economic downturns in the future. The goal of this study is to evaluate the effectiveness of these changes to capital requirements, and to hypothesize as to what would happen if the modern banking system experienced the COVID-19 pandemic recession with the capital and leverage levels of the banking institutions circa 2007. To accomplish this, data from the Federal Reserve describing the capital and leverage ratios of the banking industry will be evaluated during both the Global Financial Crisis of 2007-2008, as well as during the COVID-19 Recession. Specifically, we will look at by how much capital was improved due to Dodd-Frank/Basel III, the resiliency of the capital and leverage ratios during the modern COVID-19 recession, and we will look at the average drop in capital levels caused by the COVID-19 recession and apply these percentage changes to the leverage/capital levels seen in 2007. Given the results, it is clear to see that the change in capital requirements along with the counter-cyclical buffers described in Dodd-Frank and Basel III allowed the banking system to function throughout the COVID recession without approaching insolvency in the slightest, something that ailed many large banks and firms during the Global Financial Crisis. As an answer to our hypothetical, we found that the drop seen affecting the measures of bank capital experienced during the COVID pandemic when applied to values seen at the beginning of the 2007 recession still led to a well-capitalized banking industry as a whole, highlighting the resiliency seen during the COVID recession thanks to the capital buffers put in place, as well as the direct assistance provided by the federal government (via PPP loans and stimulus checks) and the Federal Reserve in keeping the hit on capital to minimal values throughout the pandemic.

This thesis project is part of a larger collaboration documenting the history of the ASU Biodesign Clinical Testing Laboratory (ABCTL). There are many different aspects that need to be considered when transforming to a clinical testing laboratory. This includes the different types of tests performed in the laboratory. In addition to the diagnostic polymerase chain reaction (PCR) test that is performed detecting the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), antibody testing is also performed in clinical laboratories. Antibody testing is used to detect a previous infection. Antibodies are produced as part of the immune response against SARS-CoV-2. There are many different forms of antibody tests and their sensitives and specificities have been examined and reviewed in the literature. Antibody testing can be used to determine the seroprevalence of the disease which can inform policy decisions regarding public health strategies. The results from antibody testing can also be used for creating new therapeutics like vaccines. The ABCTL recognizes the shifting need of the community to begin testing for previous infections of SARS-CoV-2 and is developing new forms of antibody testing that can meet them.

In this project, I examined the relationship between lockdowns implemented by COVID-19 and the activity of animals in urban areas. I hypothesized that animals became more active in urban areas during COVID-19 quarantine than they were before and I wanted to see if my hypothesis could be researched through Twitter crowdsourcing. I began by collecting tweets using python code, but upon examining all data output from code-based searches, I concluded that it is quicker and more efficient to use the advanced search on Twitter website. Based on my research, I can neither confirm nor deny if the appearance of wild animals is due to the COVID-19 lockdowns. However, I was able to discover a correlational relationship between these two factors in some research cases. Although my findings are mixed with regard to my original hypothesis, the impact that this phenomenon had on society cannot be denied.

The COVID-19 pandemic has resulted in preventative measures and has led to extensive changes in lifestyle for the vast majority of the American population. As the pandemic progresses, a growing amount of evidence shows that minority groups, such as the Deaf community, are often disproportionately and uniquely affected. Deaf people are directly affected in their ability to personally socialize and continue with daily routines. More specifically, this can constitute their ability to meet new people, connect with friends/family, and to perform in their work or learning environment. It also may result in further mental health changes and an increased reliance on technology. The impact of COVID-19 on the Deaf community in clinical settings must also be considered. This includes changes in policies for in-person interpreters and a rise in telehealth. Often, these effects can be representative of the pre-existing low health literacy, frequency of miscommunication, poor treatment, and the inconvenience felt by Deaf people when trying to access healthcare. Ultimately, these effects on the Deaf community must be taken into account when attempting to create a full picture of the societal shift caused by COVID-19.

Optimal foraging theory provides a suite of tools that model the best way that an animal will <br/>structure its searching and processing decisions in uncertain environments. It has been <br/>successful characterizing real patterns of animal decision making, thereby providing insights<br/>into why animals behave the way they do. However, it does not speak to how animals make<br/>decisions that tend to be adaptive. Using simulation studies, prior work has shown empirically<br/>that a simple decision-making heuristic tends to produce prey-choice behaviors that, on <br/>average, match the predicted behaviors of optimal foraging theory. That heuristic chooses<br/>to spend time processing an encountered prey item if that prey item's marginal rate of<br/>caloric gain (in calories per unit of processing time) is greater than the forager's<br/>current long-term rate of accumulated caloric gain (in calories per unit of total searching<br/>and processing time). Although this heuristic may seem intuitive, a rigorous mathematical<br/>argument for why it tends to produce the theorized optimal foraging theory behavior has<br/>not been developed. In this thesis, an analytical argument is given for why this<br/>simple decision-making heuristic is expected to realize the optimal performance<br/>predicted by optimal foraging theory. This theoretical guarantee not only provides support<br/>for why such a heuristic might be favored by natural selection, but it also provides<br/>support for why such a heuristic might a reliable tool for decision-making in autonomous<br/>engineered agents moving through theatres of uncertain rewards. Ultimately, this simple<br/>decision-making heuristic may provide a recipe for reinforcement learning in small robots<br/>with little computational capabilities.