Masters Theses
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ItemA Content Analysis of Advertising by Popular Online Sports Betting Companies(Middle Tennessee State University, 2024)This study applies McCraken’s (1986) Meaning Transfer Model (MTM) to analyze popular metaphors used in sports betting advertisements. It examines four dominant metaphors and how some attributes from sport can be transferred to sports betting advertisements. The four metaphors that will inform this study are Betting is Loving, Betting as a Sport, Betting as a Natural Environment, and Betting as a Market which come from Lopez-Gonzalez et al. (2017). By examining the way these metaphors frame sports betting as a source of income, competitive, emotional, and instinctual activity, this study highlights how sports betting advertisements use popular narratives to shape consumer perceptions and behaviors. The MTM provides a lens to understand how these metaphors not only influence attitudes towards sports betting, but also strengthen the association between sports and gambling. This is further complicated by the rise in sports betting advertisements, persuasive roles of the media, and celebrity endorsements. The findings suggest that while these metaphors enhance engagement, they also raise concerns about the normalization and potential risks associated with gambling behavior.
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ItemA Brief History of the Preventorium: Architectural and Other Challenges of Preserving the Children’s Preventorium(Middle Tennessee State University, 2024)Beginning in the 1970s, with assessments increasing in number in the 1980s and 1990s, historic preservationists have studied sanitoriums, small and large, across the United States. Almost no attention has been given to preventoriums, which were institutions that housed those with latent or bone and joint tuberculosis. These institutions represent a significant period of American medicine and understanding this resource’s significance was the primary purpose of the thesis. It combines both architectural survey and primary resources to make the case for the future preservation and interpretation of preventoriums.
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ItemConfronting a Miracle: How Americans adapted a hockey victory into a symbol of national pride(Middle Tennessee State University, 2024)This thesis provides an in-depth analysis of the cultural phenomenon known as the Miracle on Ice. The research covers the period from the team's selection in the summer of 1979 to the present-day utilization of their story by those within various culturally significant American institutions. While the game is often remembered as a historic sporting event that profoundly impacted those living during the American Cold War era, this project examines the narrative development of the Miracle, its evolution into a myth, and the diverse ways in which individuals in different contexts have invoked it to meet their needs and interests. By defeating the formidable Soviet hockey team, the young American players not only revitalized a sense of American exceptionalism following a time of disappointment but also established a lasting self-legitimizing myth. As we move further away from 1980, the significance of this victory remains relevant, shaping a nationalistic mythology that continues to resonate with the public.
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ItemDetermine the Orientation of β-Sheet Conformation for Specific Residues in N-Terminus of α-syn(61－95) in Monolayer by pMAIRS(Middle Tennessee State University, 2024)Parkinson’s disease (PD) is the second most common neurodegenerative disorder, and the hallmark of PD is the presence of Lewy bodies in the midbrain. The protein component of Lewy bodies is α-synuclein, a protein that consists of 140 amino acids. The sequence of α-synuclein can be divided into three distinct domains, namely, the N-terminus domain, the non-amyloid component domain or NAC, and the C-terminus domain. The NAC domain, which consists of residues 61-95, has been of utmost importance due to the disordered self-assembly behavior. In addition, NAC and other segment peptides have been detected in Lewy bodies. Previously in our research group, NAC was investigated by p-Polarized Multiple Angle Incidence Resolution Spectroscopy (pMAIRS) which can be used to detect the orientation of various vibrations in ultrathin films (such as monolayer). The overall conformation of NAC in a freshly prepared monolayer structure was shown to be α-helix. In addition, 13C isotopic label has been introduced into residue 93C in NAC. By pMAIRS, the orientation of the α-helix at 93G is parallel to the interface. In this thesis, the monolayer of NAC was compressed for several days, and β-sheet conformation was detected in the monolayer of NAC. By introducing 13C isotopic label into the other residues in the sequence of NAC, 93G was found to be still in α-helix after three days of compression. However, the N-terminus residue (68G) changed its conformation from α-helix to β-sheet after three days of compression. Moreover, 63V which is closer to the N-terminus changed its conformation after only two days of compression. Furthermore, edge-up orientation was detected for the newly generated β-sheet conformation. Therefore, the capability of pMAIRS to analyze the structure of membrane proteins in a monolayer with residue-level resolution was demonstrated.
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ItemIntegrating Vision-Language Models with Knowledge Graphs for Advancing AI-Driven Robotics and Precision Agriculture(Middle Tennessee State University, 2024)Precision agriculture is at the forefront of modern innovations in farming, using ad- vanced technologies to optimize resource use, increase crop yields, and promote sustainable agricultural practices. This thesis, therefore, addresses some of the critical challenges in precision agriculture, including accurate weed detection, efficient resource allocation, and integration of multimodal data from diverse sources such as drones and IoT devices. In order to address these challenges, a novel strategy is suggested that combines MiniGPT-4, a multimodal vision-language model, with a systematic Knowledge Graph (KG) derived from credible datasets, specifically FAOSTAT and USDA PLANTS. This KG, integrated in the inference pipeline of MiniGPT-4, further expands the model’s contextual understanding and increases its reasoning capabilities; hence, more accurate results are generated in tasks like weed detection and crop monitoring. Empirical evaluations demonstrate that the KG-enhanced MiniGPT-4 significantly out- performs the baseline model on various performance metrics, including BLEU scores, METEOR, ROUGE, and CIDEr, in addition to lowering hallucination rates and improving object and relation coverage. While the quantized model exhibits a slight trade-off with respect to some performance measures, it still retains good functionality, which is acceptable for real-time agricultural applications. This work not only contributes to the technical integration of vision-language models with structured knowledge bases but also provides practical solutions to enhance precision agriculture robotics. The proposed system fosters more sustainable and productive farming practices by enabling smarter decision-making and automating complex agricultural tasks. Future research will look into dynamic Knowl- edge Graph updates, mechanisms for continual learning, and further applications in both agricultural and non-agricultural domains to further solidify the role of AI-driven solutions in modern agriculture.