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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

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.

ContributorsRuan, Ellen (Co-author) / Smetanick, Jennifer (Co-author) / Majhail, Kajol (Co-author) / Anderson, Laura (Co-author) / Breshears, Scott (Co-author) / Compton, Carolyn (Thesis director) / Magee, Mitch (Committee member) / School of Life Sciences (Contributor, Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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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

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.

ContributorsHeimlich, Kiana Raye (Author) / Dorn, Ronald (Thesis director) / Martin, Roberta (Committee member) / Donovan, Mary (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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In a healthcare system already struggling with burnout among its professionals, the COVID-19 pandemic presented a barrage of personal and occupational strife to US healthcare workers. Structural and everyday discrimination contributed to the health inequities of people of color in the US, exacerbated by COVID-19-related racism and xenophobia. There is

In a healthcare system already struggling with burnout among its professionals, the COVID-19 pandemic presented a barrage of personal and occupational strife to US healthcare workers. Structural and everyday discrimination contributed to the health inequities of people of color in the US, exacerbated by COVID-19-related racism and xenophobia. There is little research regarding the effects of COVID-19 and related and/or concurring discrimination upon minority nursing staff, despite their importance in supporting the diverse American patient population with culturally competent, tireless care amid the pandemic. This cross-sectional survey study aimed to examine 1) the relationships between discrimination, social support, resilience, and quality of life among minority nursing staff in the US during COVID-19, and 2) the differences of discrimination, social support resilience, and quality of life among minority nursing staff between different racial/ethnic groups during COVID-19. The sample (n = 514) included Black/African American (n = 161, 31.4%), Latinx/Hispanic (n = 131, 25.5%), Asian (n = 87, 17%), Native American/Alaskan Native (n = 69, 13.5%), and Pacific Islander (n = 65, 12.7%) nursing staff from 47 US states. The multiple regression results showed that witnessing discrimination was associated with a lower quality of life score, while higher social support and resilience scores were associated with higher quality of life scores across all racial groups. Furthermore, while participants from all racial groups witnessed and experienced discrimination, Hispanic/Latinx nursing staff experienced discrimination most commonly, alongside having lowest quality of life and highest resilience scores. Native American/Alaskan Native nursing staff had similarly high discrimination and low quality of life, although low resilience scores. Our findings suggest that minority nursing staff who have higher COVID-19 morbidity and mortality rates (Hispanic/Latinx, Native American/Alaskan Native) were left more vulnerable to negative effects from discrimination. Hispanic/Latinx nursing staff reported a relatively higher resilience score than all other groups, potentially attributed to the positive effects of biculturality in the workplace, however, the low average quality of life score suggests a simultaneous erosion of well-being. Compared to all other groups, Native American and Alaskan Native nursing staff’s low resilience and quality of life scores suggest a potential compounding effect of historical trauma affecting their well-being, especially in contrast to Hispanic/Latinx nursing staff. This study has broader implications for research on the lasting effects of COVID-19 on minority healthcare workers’ and communities’ well-being, especially regarding Hispanic/Latinx and Native American/Alaskan Native nursing staff.

ContributorsLaufer, Annika Noreen (Author) / Chen, Angela (Thesis director) / Fries, Kathleen (Committee member) / Edson College of Nursing and Health Innovation (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Actuaries can analyze healthcare trends to determine if rates are reasonable and if reserves are adequate. In this talk, we will provide a framework of methods to analyze the healthcare trend during the pandemic. COVID-19 may influence future healthcare cost trends in many ways. First, direct COVID-19 costs may increase

Actuaries can analyze healthcare trends to determine if rates are reasonable and if reserves are adequate. In this talk, we will provide a framework of methods to analyze the healthcare trend during the pandemic. COVID-19 may influence future healthcare cost trends in many ways. First, direct COVID-19 costs may increase the amount of total experienced healthcare costs. However, with the implementation of social distancing, the amount of regularly scheduled care may be deferred to a future date. There are also many unknown factors regarding the transmission of the virus. Implementing epidemiology models allows us to predict infections by studying the dynamics of the disease. The correlation between infection amounts and hospitalization occupancies provide a methodology to estimate the amount of deferred and recouped amounts of regularly scheduled healthcare costs. Thus, the combination of the models allows to model the healthcare cost trend impact due to COVID-19.

ContributorsGabric, Lydia Joan (Author) / Zhou, Hongjuan (Thesis director) / Zicarelli, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Dreadnought is a free-to-play multiplayer flight simulation in which two teams of 8 players each compete against one another to complete an objective. Each player controls a large-scale spaceship, various aspects of which can be customized to improve a player’s performance in a game. One such aspect is Officer Briefings,

Dreadnought is a free-to-play multiplayer flight simulation in which two teams of 8 players each compete against one another to complete an objective. Each player controls a large-scale spaceship, various aspects of which can be customized to improve a player’s performance in a game. One such aspect is Officer Briefings, which are passive abilities that grant ships additional capabilities. Two of these Briefings, known as Retaliator and Get My Good Side, have strong synergy when used together, which has led to the Dreadnought community’s claiming that the Briefings are too powerful and should be rebalanced to be more in line with the power levels of other Briefings. This study collected gameplay data with and without the use of these specific Officer Briefings to determine the precise impact on gameplay. Linear correlation matrices and inference on two means were used to determine performance impact. It was found that, although these Officer Briefings do improve an individual player’s performance in a game, they do not have a consistent impact on the player’s team performance, and that these Officer Briefings are therefore not in need of rebalancing.

ContributorsJacobs, Max I. (Author) / Schneider, Laurence (Thesis director) / Tran, Samantha (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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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

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.

ContributorsDubey, Shreya Shashi (Co-author) / Asuncion, David Leonard (Co-author) / Patterson, Lindsey (Thesis director) / Lee, Lindsay (Committee member) / School of Molecular Sciences (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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The NFL is one of largest and most influential industries in the world. In America there are few companies that have a stronger hold on the American culture and create such a phenomena from year to year. In this project aimed to develop a strategy that helps an NFL team

The NFL is one of largest and most influential industries in the world. In America there are few companies that have a stronger hold on the American culture and create such a phenomena from year to year. In this project aimed to develop a strategy that helps an NFL team be as successful as possible by defining which positions are most important to a team's success. Data from fifteen years of NFL games was collected and information on every player in the league was analyzed. First there needed to be a benchmark which describes a team as being average and then every player in the NFL must be compared to that average. Based on properties of linear regression using ordinary least squares this project aims to define such a model that shows each position's importance. Finally, once such a model had been established then the focus turned to the NFL draft in which the goal was to find a strategy of where each position needs to be drafted so that it is most likely to give the best payoff based on the results of the regression in part one.
ContributorsBalzer, Kevin Ryan (Author) / Goegan, Brian (Thesis director) / Dassanayake, Maduranga (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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In the words of W. Edwards Deming, "the central problem in management and in leadership is failure to understand the information in variation." While many quality management programs propose the institution of technical training in advanced statistical methods, this paper proposes that by understanding the fundamental information behind statistical theory,

In the words of W. Edwards Deming, "the central problem in management and in leadership is failure to understand the information in variation." While many quality management programs propose the institution of technical training in advanced statistical methods, this paper proposes that by understanding the fundamental information behind statistical theory, and by minimizing bias and variance while fully utilizing the available information about the system at hand, one can make valuable, accurate predictions about the future. Combining this knowledge with the work of quality gurus W. E. Deming, Eliyahu Goldratt, and Dean Kashiwagi, a framework for making valuable predictions for continuous improvement is made. After this information is synthesized, it is concluded that the best way to make accurate, informative predictions about the future is to "balance the present and future," seeing the future through the lens of the present and thus minimizing bias, variance, and risk.
ContributorsSynodis, Nicholas Dahn (Author) / Kashiwagi, Dean (Thesis director, Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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Analytic research on basketball games is growing quickly, specifically in the National Basketball Association. This paper explored the development of this analytic research and discovered that there has been a focus on individual player metrics and a dearth of quantitative team characterizations and evaluations. Consequently, this paper continued the exploratory

Analytic research on basketball games is growing quickly, specifically in the National Basketball Association. This paper explored the development of this analytic research and discovered that there has been a focus on individual player metrics and a dearth of quantitative team characterizations and evaluations. Consequently, this paper continued the exploratory research of Fewell and Armbruster's "Basketball teams as strategic networks" (2012), which modeled basketball teams as networks and used metrics to characterize team strategy in the NBA's 2010 playoffs. Individual players and outcomes were nodes and passes and actions were the links. This paper used data that was recorded from playoff games of the two 2012 NBA finalists: the Miami Heat and the Oklahoma City Thunder. The same metrics that Fewell and Armbruster used were explained, then calculated using this data. The offensive networks of these two teams during the playoffs were analyzed and interpreted by using other data and qualitative characterization of the teams' strategies; the paper found that the calculated metrics largely matched with our qualitative characterizations of the teams. The validity of the metrics in this paper and Fewell and Armbruster's paper was then discussed, and modeling basketball teams as multiple-order Markov chains rather than as networks was explored.
ContributorsMohanraj, Hariharan (Co-author) / Choi, David (Co-author) / Armbruster, Dieter (Thesis director) / Fewell, Jennifer (Committee member) / Brooks, Daniel (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2013-05
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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

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.

ContributorsMiner, Jackson J (Author) / McDaniel, Cara (Thesis director) / Wong, Kelvin (Committee member) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05