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This report describes the technology, benefits, and deployment of autonomous vehicles and how they are expected to impact the insurance industry, specifically collision coverage policies. A pure premium trend analysis is done to come up with a realistic prediction of how the frequency and severity of vehicle collisions will change

This report describes the technology, benefits, and deployment of autonomous vehicles and how they are expected to impact the insurance industry, specifically collision coverage policies. A pure premium trend analysis is done to come up with a realistic prediction of how the frequency and severity of vehicle collisions will change over time. Two additional scenarios are done to address the fact that there is still uncertainty surrounding the timing of the implementation of AVs. Lastly, the risks that come with AVs are discussed along with potential risk mitigation strategies.
ContributorsMullenmeister, Morgan (Author) / Zhou, Hongjuan (Thesis director) / Milovanovic, Jelena (Committee member) / Zicarelli, John (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of International Letters and Cultures (Contributor)
Created2022-12
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Description
There are 6 methods of persuasion: reciprocity, scarcity, authority, commitment, liking, and social proof. Although these are typically used in economic scenarios, they may be present between professors and their students as well. We surveyed ASU students to find out which methods of persuasion professors may be implementing in their

There are 6 methods of persuasion: reciprocity, scarcity, authority, commitment, liking, and social proof. Although these are typically used in economic scenarios, they may be present between professors and their students as well. We surveyed ASU students to find out which methods of persuasion professors may be implementing in their classrooms, and whether or not these were effective in improving student outcomes (performance, memory, etc.).
ContributorsPautz, Daniella (Author) / Honeycutt, Claire (Thesis director) / Krause, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2022-05
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Description
Substance use disorders account for billions of dollars annually in emergency and inpatient healthcare, not taking into account the healthcare costs of the disorders with which substance use disorders are associated with increased risks of developing. However, while treatment for these disorders shows a decreasing action on health costs, a

Substance use disorders account for billions of dollars annually in emergency and inpatient healthcare, not taking into account the healthcare costs of the disorders with which substance use disorders are associated with increased risks of developing. However, while treatment for these disorders shows a decreasing action on health costs, a low percentage of affected individuals receive treatment, despite many insurance payers providing coverage for treatments of this nature. Thus, this maintains the issues under the current healthcare system of mitigatable, generally higher, healthcare costs and increased health risks for individuals with substance use disorders.
ContributorsWelsh, Isabelle (Author) / Zhou, Hongjuan (Thesis director) / Milovanovic, Jelena (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05
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Description

Four-dimensionalism is a popular philosophical view of how we persist through time. However, some philosophers, such as Mark Johnston and Eric Olson, argue that four-dimensionalism has perverse implications on our practical ethics. This is because, if four-dimensionalism is true, then there exist entities called personites. And if personites exist, then

Four-dimensionalism is a popular philosophical view of how we persist through time. However, some philosophers, such as Mark Johnston and Eric Olson, argue that four-dimensionalism has perverse implications on our practical ethics. This is because, if four-dimensionalism is true, then there exist entities called personites. And if personites exist, then many of the ordinary prudential, social, and moral habits we engage in, like present self-sacrifice for future benefit, promising to do something painful in the future, or being held responsible for something the we did in the past, subjects personites to suffering without sufficient compensation, consent, or desert. And this would be immoral according to our common-sense morality. In this paper, I argue that if four-dimensionalism is true, and personites exist, then we are still morally permitted to engage in the above practices. If four-dimensionalism turns out to be true, it has no perverse implications on how we ought to live.

ContributorsRavi, Ashwin (Author) / Portmore, Douglas (Thesis director) / Calhoun, Cheshire (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05
Description
Traumatic brain injury (TBI) poses a significant global health concern with substantial health and economic consequences. Patients often face significant consequences after injury, notably persistent cognitive changes and an increased risk of developing neurodegenerative disease later in life. Apart from the immediate insult, the resulting inflammatory response can lead to

Traumatic brain injury (TBI) poses a significant global health concern with substantial health and economic consequences. Patients often face significant consequences after injury, notably persistent cognitive changes and an increased risk of developing neurodegenerative disease later in life. Apart from the immediate insult, the resulting inflammatory response can lead to neuroinflammation, oxidative stress, tissue death, and long-term neurodegeneration. Microglia and astrocytes play critical roles in these inflammatory processes, emphasizing the unmet need for targeted therapies. Vaccine formulations consisting of poly (a-ketoglutarate) (paKG) microparticles (MPs) encapsulating PFK15 (1-(4-pyridinyl)-3-(2-quinolinyl)-2-propen-1-one) and myelin proteolipid protein (PLP) were developed for prior studies and have demonstrated the production of antigen-specific adaptive T-cell responses in the brain, spleen, and lymph nodes of mice, suggesting that these formulations may be able to prevent neuronal inflammation in mice after TBI. The vaccine efficacy was further evaluated through the image analysis of immunohistochemically stained brain tissue sections from naive, saline, and paKG(PFK15+PLP) MPs or paKG(PFK15) MPs treated mice. Though microglia (Iba1), astrocytes (GFAP) and CD86 were visualized in this method, only Iba1 was found to be significantly reduced in the contralateral hemisphere for paKG(PFK15+PLP) MPs and paKG(PFK15) MPs groups when compared to naive (p=0.0373 and p=0.0186, respectively). However, the naive group also showed an unexpectedly high level of CD86 after thresholding (compared to the TBI groups), indicating flaws were present in the analysis pipeline. Challenges of the image analysis process included thresholding setting optimization, folded tissues, bubbles, and saturated punctate signal. These issues may have impacted data accuracy, underscoring the need for rigorous optimization of experimental techniques and imaging methodologies when evaluating the therapeutic potential of the vaccines in mitigating TBI-induced neuroinflammation. Thus, future analyses should consider microglial morphology and employ more accurate thresholding in FIJI/ImageJ to better measure cellular activation and the overall positive signal.
ContributorsSundem, Andrea (Author) / Stabenfeldt, Sarah (Thesis director) / Willingham, Crystal (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2024-05
Description
A reliable method for real-time blood flow monitoring in vivo is critical for several medical applications, including monitoring cardiovascular diseases, evaluating interventional procedures and surgeries, and increasing the safety and efficacy of neuromodulation procedures. High-speed methods are particularly necessary for neural monitoring, due to the brain's heightened sensitivity to hypoxic and

A reliable method for real-time blood flow monitoring in vivo is critical for several medical applications, including monitoring cardiovascular diseases, evaluating interventional procedures and surgeries, and increasing the safety and efficacy of neuromodulation procedures. High-speed methods are particularly necessary for neural monitoring, due to the brain's heightened sensitivity to hypoxic and ischemic conditions. High-speed CBF monitoring methods may also provide a useful biomarker for the development of a closed-loop deep brain stimulation (DBS) system. Current methods such as laser Doppler, bold fMRI, and positron emission tomography (PET) often involve cumbersome instrumentation and are therefore not well- suited for chronic microvasculature monitoring. The purpose of this study is to develop a method for real-time measurement of blood flow changes using electrochemical impedance spectra (EIS). Utilizing EIS to measure CBF has the potential to be included in a chronic, closed-loop DBS system that is modulated by fluctuations in CBF, using minimal additional instrumentation. Five experiments in rodents were conducted, with the objective of 1) determining whether electrochemical impedance spectra showed impedance changes correlated with changes in blood flow, assessing the sensitivity, specificity, and limitations of detection of this method, and 2) determining whether cyclic voltammetry-based method could be used to produce EIS more rapidly than current methods. The experimental set-up included electrodes in the femoral artery with the administration of endothelin (ET-1) to induce blood flow changes (N=1), electrodes in the motor cortex using isoflurane variation to induce blood flow changes (N=3), and electrodes in the femoral artery with the administration of nitroglycerin (NTG) to induce blood flow changes (N=1). Preliminary results suggest that impedance changes in the higher frequencies (over 160 Hz) demonstrated higher sensitivity to blood flow changes in the femoral artery model compared to <100 Hz frequencies, with inconclusive results in the motor cortex model. Future in vivo experiments will be conducted using endothelin-1 to further establish the relationship between impedance and cerebral blood flow in the brain.
ContributorsJitendran, Elizabeth (Author) / Greger, Bradley (Thesis director) / Kodibagkar, Vikram (Committee member) / Muthuswamy, Jitendran (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2024-05
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Description
This thesis details a Python-based software designed to calculate the Jones polynomial, a vital mathematical tool from Knot Theory used for characterizing the topological and geometrical complexity of curves in 3-space, which is essential in understanding physical systems of filaments, including the behavior of polymers and biopolymers. The Jones polynomial serves as a topological

This thesis details a Python-based software designed to calculate the Jones polynomial, a vital mathematical tool from Knot Theory used for characterizing the topological and geometrical complexity of curves in 3-space, which is essential in understanding physical systems of filaments, including the behavior of polymers and biopolymers. The Jones polynomial serves as a topological invariant capable of distinguishing between different knot structures. This capability is fundamental to characterizing the architecture of molecular chains, such as proteins and DNA. Traditional computational methods for deriving the Jones polynomial have been limited by closure-schemes and high execu- tion costs, which can be impractical for complex structures like those that appear in real life. This software implements methods that significantly reduce calculation times, allowing for more efficient and practical applications in the study of biological poly- mers. It utilizes a divide-and-conquer approach combined with parallel computing and applies recursive Reidemeister moves to optimize the computation, transitioning from an exponential to a near-linear runtime for specific configurations. This thesis provides an overview of the software’s functions, detailed performance evaluations using protein structures as test cases, and a discussion of the implications for future research and potential algorithmic improvements.
ContributorsMusfeldt, Caleb (Author) / Panagiotou, Eleni (Thesis director) / Richa, Andrea (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor)
Created2024-05
Description
In this paper, a novel model of Hotelling duopoly is introduced that explains horizontal product variety as the result of consumer preferences, expanding on and meshing the works of Hotelling (1929) and Neven (1985). From this model, two opposing forces from consumer preferences are found that impact the variety and

In this paper, a novel model of Hotelling duopoly is introduced that explains horizontal product variety as the result of consumer preferences, expanding on and meshing the works of Hotelling (1929) and Neven (1985). From this model, two opposing forces from consumer preferences are found that impact the variety and price decisions of firms: market share revenues and price revenues. As firms face consumers with highly linear (weak) preferences over variety, the profit incentive is to simply capture the market by offering products that appeal to the middle consumer. However, as firms face consumers with highly quadratic (strong) preferences over variety, the profit incentive is to carve out and exploit a market segment by offering a distinct variety. Thus, observed product variety between minimal and maximal differentiation is emergent from consumer preferences, as firms face a balance of price and market share incentives.
ContributorsMalaki, Adam (Author) / Leiva Bertran, Fernando (Thesis director) / Hanemann, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor) / School for the Future of Innovation in Society (Contributor)
Created2024-05
Description
Artificial intelligence (AI) and machine learning (ML) algorithms are revolutionizing the field of healthcare by offering new opportunities for improved diagnosis and treatment planning. These technologies have the potential to transform the way medical professionals approach patient care by analyzing vast amounts of data, identifying patterns, and making predictions. This

Artificial intelligence (AI) and machine learning (ML) algorithms are revolutionizing the field of healthcare by offering new opportunities for improved diagnosis and treatment planning. These technologies have the potential to transform the way medical professionals approach patient care by analyzing vast amounts of data, identifying patterns, and making predictions. This overview highlights the current state of research and development in the field of AI and ML for diagnosis and treatment planning, as well as explore the ethical benefits and challenges associated with their implementation.
ContributorsShankar, Kruthy (Author) / Arquiza, Jose (Thesis director) / Sobrado, Michael (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2024-05
ContributorsShankar, Kruthy (Author) / Arquiza, Jose (Thesis director) / Sobrado, Michael (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2024-05