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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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Description

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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Description

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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Description

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
Description

COVID-19 misinformation covers a wide range of topics such as fatality rate, mask effectiveness, potential cures, vaccine development, and the idea of a "plandemic". The spread of this misinformation happens at a rapid speed with the help of social media and powerful influencers, including major political figures. This thesis is

COVID-19 misinformation covers a wide range of topics such as fatality rate, mask effectiveness, potential cures, vaccine development, and the idea of a "plandemic". The spread of this misinformation happens at a rapid speed with the help of social media and powerful influencers, including major political figures. This thesis is a focused case study on hydroxychloroquine, and builds a timeline of the misinformation surrounding the drug. From poorly conducted studies to the use of false experts, this study reveals how politicized misinformation garners more public attention than the actual science.

ContributorsPitts, Benjamin Jack (Author) / Ingram-Waters, Mary (Thesis director) / Hurlbut, Ben (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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Description

Due to the COVID-19 pandemic, declared in March of 2020, there have been many lifestyle changes which have likely influenced tobacco smoking behavior. Such lifestyle changes include lockdowns, stay at home orders, reduction in social cues related to smoking, increased stress, and boredom among other things. This study utilized a

Due to the COVID-19 pandemic, declared in March of 2020, there have been many lifestyle changes which have likely influenced tobacco smoking behavior. Such lifestyle changes include lockdowns, stay at home orders, reduction in social cues related to smoking, increased stress, and boredom among other things. This study utilized a cross-sectional survey which looked into these behaviors, primarily perceived risk to COVID-19, and determined if there is an association between perceived risk and education level/race. Education level is a proxy for income and material resources, therefore making it more likely that people with lower levels of education have fewer resources and higher perceived risk to negative effects of COVID-19. Additionally, people of color are often marginalized in the medical community along with being the target of heavy advertising by tobacco companies which have likely impacted risk to COVID-19 as well.

ContributorsLodha, Pratishtha (Author) / Leischow, J. Scott (Thesis director) / Pearson, Jennifer (Committee member) / School of Life Sciences (Contributor) / School of Human Evolution & Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

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

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.

ContributorsSaker, Logan (Co-author) / Ries, Sarah (Co-author) / Hegardt, Brandon (Co-author) / Patterson, Jack (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description
This thesis surveys and analyzes applications of machine learning techniques to the fields of animation and computer graphics. Data-driven techniques utilizing machine learning have in recent years been successfully applied to many subfields of animation and computer graphics. These include, but are not limited to, fluid dynamics, kinematics, and character

This thesis surveys and analyzes applications of machine learning techniques to the fields of animation and computer graphics. Data-driven techniques utilizing machine learning have in recent years been successfully applied to many subfields of animation and computer graphics. These include, but are not limited to, fluid dynamics, kinematics, and character modeling. I argue that such applications offer significant advantages which will be pivotal in advancing the fields of animation and computer graphics. Further, I argue these advantages are especially relevant in real-time implementations when working with finite computational resources.
ContributorsSaba, Raphael Lucas (Author) / Foy, Joseph (Thesis director) / Olson, Loren (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
Speech nasality disorders are characterized by abnormal resonance in the nasal cavity. Hypernasal speech is of particular interest, characterized by an inability to prevent improper nasalization of vowels, and poor articulation of plosive and fricative consonants, and can lead to negative communicative and social consequences. It can be associated with

Speech nasality disorders are characterized by abnormal resonance in the nasal cavity. Hypernasal speech is of particular interest, characterized by an inability to prevent improper nasalization of vowels, and poor articulation of plosive and fricative consonants, and can lead to negative communicative and social consequences. It can be associated with a range of conditions, including cleft lip or palate, velopharyngeal dysfunction (a physical or neurological defective closure of the soft palate that regulates resonance between the oral and nasal cavity), dysarthria, or hearing impairment, and can also be an early indicator of developing neurological disorders such as ALS. Hypernasality is typically scored perceptually by a Speech Language Pathologist (SLP). Misdiagnosis could lead to inadequate treatment plans and poor treatment outcomes for a patient. Also, for some applications, particularly screening for early neurological disorders, the use of an SLP is not practical. Hence this work demonstrates a data-driven approach to objective assessment of hypernasality, through the use of Goodness of Pronunciation features. These features capture the overall precision of articulation of speaker on a phoneme-by-phoneme basis, allowing demonstrated models to achieve a Pearson correlation coefficient of 0.88 on low-nasality speakers, the population of most interest for this sort of technique. These results are comparable to milestone methods in this domain.
ContributorsSaxon, Michael Stephen (Author) / Berisha, Visar (Thesis director) / McDaniel, Troy (Committee member) / Electrical Engineering Program (Contributor, Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05