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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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One out of ten women has a difficult time getting or staying pregnant in the United States. Recent studies have identified aging as one of the key factors attributed to a decline in female reproductive health. Existing fertility diagnostic methods do not allow for the non-invasive monitoring of hormone levels

One out of ten women has a difficult time getting or staying pregnant in the United States. Recent studies have identified aging as one of the key factors attributed to a decline in female reproductive health. Existing fertility diagnostic methods do not allow for the non-invasive monitoring of hormone levels across time. In recent years, olfactory sensing has emerged as a promising diagnostic tool for its potential for real-time, non-invasive monitoring. This technology has been proven promising in the areas of oncology, diabetes, and neurological disorders. Little work, however, has addressed the use of olfactory sensing with respect to female fertility. In this work, we perform a study on ten healthy female subjects to determine the volatile signature in biological samples across 28 days, correlating to fertility hormones. Volatile organic compounds (VOCs) present in the air above the biological sample, or headspace, were collected by solid phase microextraction (SPME), using a 50/30 µm divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) coated fiber. Samples were analyzed, using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS). A regression model was used to identify key analytes, corresponding to the fertility hormones estrogen and progesterone. Results indicate shifts in volatile signatures in biological samples across the 28 days, relevant to hormonal changes. Further work includes evaluating metabolic changes in volatile hormone expression as an early indicator of declining fertility, so women may one day be able to monitor their reproductive health in real-time as they age.
ContributorsOng, Stephanie (Author) / Smith, Barbara (Thesis advisor) / Bean, Heather (Committee member) / Plaisier, Christopher (Committee member) / Arizona State University (Publisher)
Created2018
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Description
The Multiple Antibiotic Resistance Regulator Family (MarR) are transcriptional regulators, many of which forms a dimer. Transcriptional regulation provides bacteria a stabilized responding system to ensure the bacteria is able to efficiently adapt to different environmental conditions. The main function of the MarR family is to create multiple antibiotic resistance

The Multiple Antibiotic Resistance Regulator Family (MarR) are transcriptional regulators, many of which forms a dimer. Transcriptional regulation provides bacteria a stabilized responding system to ensure the bacteria is able to efficiently adapt to different environmental conditions. The main function of the MarR family is to create multiple antibiotic resistance from a mutated protein; this process occurs when the MarR regulates an operon. We hypothesized that different transcriptional regulator genes have interactions with each other. It is known that Salmonella pagC transcription is activated by three regulators, i.e., SlyA, MprA, and PhoP. Bacterial Adenylate Cyclase-based Two-Hybrid (BACTH) system was used to research the protein-protein interactions in SlyA, MprA, and PhoP as heterodimers and homodimers in vivo. Two fragments, T25 and T18, that lack endogenous adenylate cyclase activity, were used for construction of chimeric proteins and reconstruction of adenylate cyclase activity was tested. The significant adenylate cyclase activities has proved that SlyA is able to form homodimers. However, weak adenylate cyclase activities in this study has proved that MprA and PhoP are not likely to form homodimers, and no protein-protein interactions were detected in between SlyA, MprA and PhoP, which no heterodimers have formed in between three transcriptional regulators.
ContributorsTao, Zenan (Author) / Shi, Yixin (Thesis advisor) / Wang, Xuan (Committee member) / Bean, Heather (Committee member) / Arizona State University (Publisher)
Created2018