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This paper is intended to identify a correlation between the winning percentage of sports teams in the four major professional sports leagues in the United States and the GDP per capita of their respective cities. We initially compiled fifteen years of franchise performance along with economic data from the Federal

This paper is intended to identify a correlation between the winning percentage of sports teams in the four major professional sports leagues in the United States and the GDP per capita of their respective cities. We initially compiled fifteen years of franchise performance along with economic data from the Federal Reserve Bank of St. Louis to analyze this relationship. After converting the data into a language recognized by Stata, the regression tool we used, we ran multiple regressions to find relevant correlations based off of our inputs. This paper will show the value of the economic impact of strong or weak performance throughout various economic cycles through data analysis and conclusions drawn from the results of the regression analysis.
ContributorsAndl, Tyler (Co-author) / Shirk, Brandon (Co-author) / Goegan, Brian (Thesis director) / Eaton, John (Committee member) / School of Accountancy (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
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Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and

Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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This paper explores how marginalist economics defines and inevitably constrains Victorian sensation fiction's content and composition. I argue that economic intuition implies that sensationalist heroes and antagonists, writers and readers all pursued a fundamental, "rational" aim: the attainment of pleasure. So although "sensationalism" took on connotations of moral impropriety in

This paper explores how marginalist economics defines and inevitably constrains Victorian sensation fiction's content and composition. I argue that economic intuition implies that sensationalist heroes and antagonists, writers and readers all pursued a fundamental, "rational" aim: the attainment of pleasure. So although "sensationalism" took on connotations of moral impropriety in the Victorian age, sensation fiction primarily involves experiences of pain on the page that excite the reader's pleasure. As such, sensationalism as a whole can be seen as a conformist product, one which mirrors the effects of all commodities on the market, rather than as a rebellious one. Indeed, contrary to modern and contemporary critics' assumptions, sensation fiction may not be as scandalous as it seems.
ContributorsFischer, Brett Andrew (Author) / Bivona, Daniel (Thesis director) / Looser, Devoney (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor) / School of Politics and Global Studies (Contributor) / Department of English (Contributor)
Created2014-12
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Description
Through collection of survey data on the characteristics of college debaters, disparities in participation and success for women and racial and ethnic minorities are measured. This study then uses econometric tools to assess whether there is an in-group judging bias in college debate that systematically disadvantages female and minority participants.

Through collection of survey data on the characteristics of college debaters, disparities in participation and success for women and racial and ethnic minorities are measured. This study then uses econometric tools to assess whether there is an in-group judging bias in college debate that systematically disadvantages female and minority participants. Debate is used as a testing ground for competing economic theories of taste-based and statistical discrimination, applied to a higher education context. The study finds persistent disparities in participation and success for female participants. Judges are more likely to vote for debaters who share their gender. There is also a significant disparity in the participation of racial and ethnic minority debaters and judges, as well as female judges.
ContributorsVered, Michelle Nicole (Author) / Silverman, Daniel (Thesis director) / Symonds, Adam (Committee member) / Dillon, Eleanor (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Politics and Global Studies (Contributor)
Created2014-12
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Description
Marijuana is the most commonly used illicit substance in the United States with over two million pounds seized annually and with a usage rate estimated at 19.8 million people in 2013 (SAMSHA, 2014). Currently there is a nationwide movement for the legalization of recreational marijuana via referendum at the state

Marijuana is the most commonly used illicit substance in the United States with over two million pounds seized annually and with a usage rate estimated at 19.8 million people in 2013 (SAMSHA, 2014). Currently there is a nationwide movement for the legalization of recreational marijuana via referendum at the state level. Three states and the District of Columbia have already adopted amendments legalizing marijuana and over a dozen more currently have pending ballots. This report explores what would be the impact of legalizing marijuana in Arizona through the examination of data from Colorado and other governmental sources. Using a benefit/cost analysis the data is used to determine what the effect the legalization of marijuana would have in Arizona. I next examined the moral arguments for legalization. Finally I propose a recommendation for how the issue of the legalization of recreational marijuana should be approached in Arizona.
ContributorsDiPietro, Samuel Miles (Author) / Kalika, Dale (Thesis director) / Lynk, Myles (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor)
Created2015-05
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Description
Despite the 40-year war on cancer, very limited progress has been made in developing a cure for the disease. This failure has prompted the reevaluation of the causes and development of cancer. One resulting model, coined the atavistic model of cancer, posits that cancer is a default phenotype of the

Despite the 40-year war on cancer, very limited progress has been made in developing a cure for the disease. This failure has prompted the reevaluation of the causes and development of cancer. One resulting model, coined the atavistic model of cancer, posits that cancer is a default phenotype of the cells of multicellular organisms which arises when the cell is subjected to an unusual amount of stress. Since this default phenotype is similar across cell types and even organisms, it seems it must be an evolutionarily ancestral phenotype. We take a phylostratigraphical approach, but systematically add species divergence time data to estimate gene ages numerically and use these ages to investigate the ages of genes involved in cancer. We find that ancient disease-recessive cancer genes are significantly enriched for DNA repair and SOS activity, which seems to imply that a core component of cancer development is not the regulation of growth, but the regulation of mutation. Verification of this finding could drastically improve cancer treatment and prevention.
ContributorsOrr, Adam James (Author) / Davies, Paul (Thesis director) / Bussey, Kimberly (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2015-05
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Description
According to the Tax Policy Center, a joint project of the Brookings Institution and Urban Institute, the Earned Income Tax Credit (EITC) will provide 26 million households with 60 billion dollars of reduced taxes and refunds in 2015 \u2014 resources that serve to lift millions of families above the federal

According to the Tax Policy Center, a joint project of the Brookings Institution and Urban Institute, the Earned Income Tax Credit (EITC) will provide 26 million households with 60 billion dollars of reduced taxes and refunds in 2015 \u2014 resources that serve to lift millions of families above the federal poverty line. Responding to the popularity of EITC programs and recent discussion of its expansion for childless adults, I select three comparative case studies of state-level EITC reform from 2005 to 2013. Each state represents a different kind of policy reform: the creation of a supplemental credit in Connecticut, credit reduction in New Jersey, and finally credit expansion for childless adults in Maryland. For each case study, I use Current Population Survey panel data from the March Supplement to complete a differences-in-differences (DD) analysis of EITC policy changes. Specifically, I analyze effects of policy reform on total earned income, employment and usual hours worked. For comparison groups, I construct unique counterfactual populations of northeastern U.S. states, using people of color with less than a college degree as my treatment group for their increased sensitivity to EITC policy reform. I find no statistically significant effects of policy creation in Connecticut, significant decreases in employment and hours worked in New Jersey, and finally, significant increases in earnings and hours worked in Maryland. My work supports the findings of other empirical work, suggesting that awareness of new supplemental EITC programs is critical to their effectiveness while demonstrating that these types of programs can affect the labor supply and outcomes of eligible groups.
ContributorsRichard, Katherine Rose (Author) / Dillon, Eleanor Wiske (Thesis director) / Silverman, Daniel (Committee member) / Herbst, Chris (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor)
Created2015-05
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Description
The relationship between the European Union and Britain has been long and contentious. It has been dominated by Britain's skepticism towards the EU and a hesitation to participate in an integrated Europe. This paper outlines the costs and benefits of Britain's membership in three areas: trade and foreign direct investment,

The relationship between the European Union and Britain has been long and contentious. It has been dominated by Britain's skepticism towards the EU and a hesitation to participate in an integrated Europe. This paper outlines the costs and benefits of Britain's membership in three areas: trade and foreign direct investment, financial contributions, and immigration. In addition to analyzing the effect of a British exit in these three areas, alternatives are also discussed.
ContributorsLeon, Monique Briana (Author) / Mendez, Jose (Thesis director) / Kenchington, David (Committee member) / Barrett, The Honors College (Contributor) / W. P. Carey School of Business (Contributor) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor)
Created2015-05
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Description
Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might mimic a power law or an exponential distribution. In order to consider the question regarding the growth trends of metastatic

Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might mimic a power law or an exponential distribution. In order to consider the question regarding the growth trends of metastatic brain tumors, this thesis analyzes the volume measurements of the tumor sizes from the BNI data and attempts to explain such size distributions through mathematical models. More specifically, a basic stochastic cellular automaton model is used and has three-dimensional results that show similar size distributions of those of the BNI data. Results of the models are investigated using the likelihood ratio test suggesting that, when the tumor volumes are measured based on assuming tumor sphericity, the tumor size distributions significantly mimic the power law over an exponential distribution.
ContributorsFreed, Rebecca (Co-author) / Snopko, Morgan (Co-author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
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Description
Many fear that the growth of automation and artificial intelligence will lead to massive unemployment since human labor would no longer be needed. Although automation does displace workers from their current jobs, it is unclear the total net effect on jobs this period of advancement will have. One possible solution

Many fear that the growth of automation and artificial intelligence will lead to massive unemployment since human labor would no longer be needed. Although automation does displace workers from their current jobs, it is unclear the total net effect on jobs this period of advancement will have. One possible solution to help displaced workers is a Universal Basic Income. A Universal Basic Income(UBI) is a set payment paid to all members of society regardless of working status. Compared to current unemployment programs, a Universal Basic Income does not restrict participants in how to spend the money and is more inclusive. This paper examines the effects of a UBI on a person's motivation to work through a study on current college students. There is reason to believe that a Universal Basic Income will lead to fewer people working as people may become dependent on a base payment to meet their basic needs and not look for work. In addition, some people may drop out of their current jobs and rely on a UBI as their main form of income. The current literature does not offer a consensus opinion on this relationship and more studies are being completed with the threat of mass unemployment looming. This study shows the effects of a UBI on participants' willingness to work and then applies these results to the current economic model. With these results and new economic model, a decision about future policies surrounding a UBI can be made.
ContributorsAgarwal, Raghav (Author) / Pulido Hernadez, Carlos (Thesis director) / Foster, William (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05