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AI-Powered Portable Optical Biosensors for Environmental Toxicants and Biomarkers
No full textDetecting environmental toxicants and biomarkers is vital for protecting ecosystems and public health, yet current methods often lack portability, speed, and precision for field and point- of-care applications. AI-powered portable optical biosensors address these challenges by combining molecular detection units with compact optical devices and advanced data analytics. These systems offer high sensitivity, specificity, portability, and rapid decision-making.This dissertation focuses on developing AI-powered biosensor platforms for environmental field testing and medical diagnostics. Four platforms were designed to detect microRNAs, protein biomarkers, micro/nanoplastics (MNPs), and per- and polyfluoroalkyl substances (PFAS). The detection relies on light scattering or intensity measurements captured by compact photodetectors or smartphone cameras, analyzed using AI frameworks like computer vision and machine learning for pattern recognition, contaminant level prediction, and scalability via cloud processing. Chapter 2 outlines the targets, detection methods, and data analysis techniques across the projects.
Overall, this work highlights the transformative potential of AI-powered biosensors in advancing environmental monitoring, healthcare, and industry, with future research aiming to enhance detection capabilities and expand applications
Design and Evaluation of a Retroreflector System for Primary Mirror Health Diagnostics in ITER Optical Systems
No full textThe integrity of optical components in the ITER tokamak is critical for accurate plasma diagnostics, yet prolonged exposure to high-energy plasma environments leads to contamination and degradation of reflective surfaces. This thesis presents the design, implementation, and validation of an in-situ health monitoring system for the primary diagnostic mirror, utilizing a 1D retroreflector mounted on the shutter to assess its condition. The proposed system enables back-illumination from the image plane, allowing for the analysis of mirror reflectivity, contamination levels, and overall surface quality.Through extensive optical modeling in Zemax and FRED, this work demonstrates that the retroreflector provides a viable and effective method for monitoring mirror health by analyzing the return signal from the reflector. The study establishes a quantitative framework for evaluating mirror performance, showing that quality and contamination can be directly correlated with scattering effects. By leveraging Bidirectional Scattering Distribution Function (BSDF) models and Total Integrated Scatter (TIS) analysis, this research quantifies how mirror degradation leads to increased optical noise, signal attenuation, and cross-talk between image channels. Additionally, this thesis identifies ghost imaging and stray light as significant sources of optical contamination, with simulations revealing that up to 69% of power can be lost due to unintended reflections. These findings emphasize the need for careful system design, optimized anti-reflective coatings, and advanced scattering control strategies to maintain high signal integrity. The results further demonstrate that the retroreflector method is highly sensitive to scattering variations, amplifying the observed scattering effects and enabling early detection of mirror degradation. By comparing beam-based and retroreflector-based measurements, this study confirms that scattering effects can be quantified and used as a diagnostic metric for assessing long-term mirror health. Ultimately, this work proves that a retroreflector-based system provides a practical, scalable, and non-invasive solution for monitoring primary mirror health in high-exposure plasma environments. The findings contribute to the development of an optimized calibration and monitoring strategy, ensuring that IT-ER’s optical diagnostics maintain long-term accuracy and reliability despite the challenges posed by plasma-induced contamination and degradation
Increased Resolution in Black and White Film Digitization Utilizing a Narrow Bandpass Light Source
No full textIn an effort to preserve and to provide access to their collections of black and white film negatives, many institutions (museums, libraries, archives, etc) are digitizing these collections. Several international committees were formed to define the needed image quality and created digitization guidelines with specifics for different material types to ensure that collection materials are properly documented and digitally preserved. Current practices for digitizing black and white negatives involve many different technologies, most of which incorporate broad-band "white" light sources. To assist with black and white film digitization image quality improvement efforts and standardizations, the author explores the benefits of utilizing a camera sensor without a
color filter array and differing narrow-band light sources to mitigate image degradation caused by diffraction and chromatic change of focus. This thesis demonstrates that utilizing this technique enhances the optical resolution, or modulation transfer function, of the imaging setup with minimal drawbacks as is discussed in this thesis
INTERNAL COMPASSES: EXPLORING THE RELATIONSHIPS BETWEEN MOBILITY AND SPATIAL NAVIGATION
No full textThis study investigates the relationship between athletic experience, sensorimotor balance control, and path integration performance in an immersive virtual reality (VR) environment. While athletic status did not predict navigation accuracy, we found that balance, particularly balance relying on proprioceptive and vestibular inputs, was a strong predictor of angular precision during spatial navigation tasks. These findings suggest that sensorimotor control plays a critical role in spatial navigation and underscore the integrated nature of mobility and orientation. As data collection progresses, future analyses with a larger sample will allow for a more detailed exploration of individual differences, including potential effects of visual dependence, motor strategies, and habitual physical activities. Understanding the interplay between mobility and navigation may have implications for interventions aimed at preserving cognitive and physical independence across various populations
PFAS REMOVAL FOR MUNICIPAL DRINKING WATER
No full textPoly- and perfluoroalkyl substances (PFAS) are hazardous synthetic chemicals that pose significant health risks and have contaminated water supplies in many communities, including a community in the Southside of Tucson, Summit, Arizona. In response, this project proposes a water treatment solution targeting the region's need for clean and safe drinking water. The REAL Water Treatment Plant combines granulated activated carbon filtration with advanced oxidation to effectively remove PFAS and other contaminant 1,4-dioxane. The treatment process effectively removes PFAS concentrations to levels well below the EPA drinking water regulations. To optimize efficiency, the system includes breakthrough modeling that extends the lifespan of filtration media, reduces waste, and minimizes operational costs. Environmental stewardship is central to the design, with a strong emphasis on reducing chemical waste and carbon emissions through media reactivation rather than landfill disposal. Safety protocols are also in place to manage potentially hazardous materials used in the oxidation process. This project provides a model for how communities can address PFAS contamination while promoting environmental responsibility and economic viability. Its successful implementation can serve as a blueprint for broader efforts to ensure universal access to clean water
WHY AMERICA HASN'T ELECTED A FEMALE PRESIDENT: AN ANALYSIS OF HILLARY CLINTON'S AND KAMALA HARRIS'S DEFEATS
No full textThis thesis explores the electoral defeats of the two most successful female presidential candidates in American history, Hillary Clinton and Kamala Harris, where both candidates shockingly lost to the same opponent, Donald Trump. Through a comparative analysis using Clinton as the primary case study and Harris as a secondary reference, this thesis explores the social, cultural, political, and economic factors that shaped both of their campaigns and their losses. The comparative analysis is broken down into four main chapters: (1) the political climate of both election periods, (2) Trump's populist brand and appeal, (3) the role of race and gender in presidential politics, and (4) the influence of social media and misinformation. Ultimately, Clinton's loss revealed the difficulties that women face while pursuing the presidency, laying the precedent for Harris' election defeat, in which Harris encountered a similar but more intensified version of Clinton's experience
ONLINE MASTER OF SCIENCE IN MARKETING PROGRAM DIGITAL MARKETING CAMPAIGN
No full textThis thesis focuses on researching, developing, and implementing a comprehensive marketing strategy to promote the University of Arizona's new Online Master of Science in Marketing program. As online education continues to grow, establishing a strong and competitive presence in the digital marketplace is essential for attracting prospective students. Our objective was to create a data-driven, multi-channel marketing plan that effectively communicates the program's value, differentiates it from competitors, and drives enrollment. We collaborated with industry professionals and academic scholars, including Sangeetha Venkataramani, Assistant Marketing Department Head and Lecturer in Marketing at the Eller College of Management; Elyse Flynn Meyer, President of Prism Global Marketing Solutions; and Jenny Budwig, Director of Marketing at Fransmart. Their expertise in marketing assisted us in developing impactful initiatives. Our plan began with preliminary market research to analyze industry trends and target audience behaviors. Through this research, we defined our ideal student demographic, identified key motivators influencing their decision-making process, and tailored our messaging accordingly. We leveraged a combination of search engine optimization (SEO), targeted email campaigns, social media marketing, earned media, and digital advertising to create an effective strategy. Additionally, we worked closely with Arizona Online, which manages the program's landing page and information inquiries, to assess the effectiveness of our marketing efforts. By analyzing website traffic and conversion rates, we continuously tailored our strategy to maximize reach and enrollment outcomes. This thesis serves as both an academic and practical exploration of digital marketing in higher education, providing valuable insights into how universities can leverage modern marketing techniques to attract students
THE IMPACT OF MINDFULNESS-BASED STRESS REDUCTION APPROACHES ON INDIVIDUALS WITH AUTISM SPECTRUM DISORDER
No full textNumerous studies have shown a stark increase in chronic stress, anxiety, and depression in individuals with Autism Spectrum Disorder (ASD) across the lifespan. Mindfulness-Based Stress Reduction (MBSR), a program developed by Jon Kabat-Zinn to help alleviate stressors through a combination of mindfulness, meditation, and yoga practices, is effective in reducing stress, anxiety, and depression with various population groups (Grossman et al., 2004). Though there is research that seeks to connect MBSR with individuals with ASD, much of the research has only studied small subgroups of this population. This illustrates the need for a review of the literature to draw connections and highlight areas of need for continued research. This review aims to provide a sample of the existing research on the use of MBSR as it pertains to children and adults with ASD. The review will conclude with a summary of proposed evidence-based treatment strategies that incorporate MBSR and that may be beneficial for rehabilitation professionals based on emerging research in this field
CLOSURE: THE DEATH PENALTY, RESTORATIVE JUSTICE, AND ARIZONA VICTIM SERVICES
No full textOne of the biggest justifications for the continued use of capital punishment in the United States is that the practice brings closure to co-victims, the family members of the murdered victim. However, this argument does not resonate with all co-victims due to various factors, including religious beliefs, moral convictions, and the emotional toll of the post-conviction appeals process. This thesis begins by evaluating victim services in Arizona, a death penalty state that prides itself in being victim-centered. Interviews from victim advocates, individuals in victim services, and a research review will offer insight into where victim services can be improved, and-what victims need in capital cases in Maricopa, Pima, and Pinal County. Second, the thesis will offer interviews and analysis with victims impacted by capital and non-capital offenses, their experiences with closure and thoughts about capital punishment. Third, the thesis will then explore the idea of restorative justice practices, such as victim offender dialogue, and their relationship to closure while also discussing the issue of the word closure for co-victims. Fourth, the thesis will highlight the hidden victims of the death penalty through discussion/analysis of an interview of a family member of a death row defendant and interviews of innocent people who spent time on Arizona and Florida's death row. Finally, the thesis will argue that the death penalty does not bring closure and healing to victims, but instead creates new victims, and that a more restorative approach to justice would better serve victims everywhere, including those in Arizona
ACCELERATING KINEMATIC LENSING INFERENCE WITH NEURAL NETWORKS
No full textCosmological surveys in the next decade will provide us with an unprecedented amount of data for Kinematic Lensing (KL) studies. KL infers the cosmic shear signal by jointly forward modeling the observed photometric image and velocity field of a disk galaxy, allowing for shear measurements with greatly reduced statistical noise. We show that there are good prospects for a future KL survey using the Dark Energy Spectroscopic Instrument (DESI), and that a pilot measurement can already be made using data from the DESI Peculiar Velocity (DESI-PV) survey. However, the process of KL inference for cosmic shear using MCMC will be time-consuming, and will become unfeasible with a large number of galaxies. In this work, we explore ways to accelerate KL inference using neural networks, in preparation for the DESI-KL pilot measurement and future KL endeavors using large survey data. Specifically, we created an algorithm to mass-generate galaxy images and spectra, which can then be used for neural network training and validation. We also develop a neural network schematic for emulating image and spectra generation, which we plan to implement and test in a future work