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Exploring the Impact of Attorneys with Exposed Tattoos on Jurors
No full textWithin the legal field, there appears to be a pervasive stigmatization of exposed tattoos. Law firms justify their explicit or implicit bans on exposed body art by arguing that tattoos could negatively prejudice jurors who may be biased against people with tattoos. This thesis intends to put that notion to the test via a digital survey. Subjects who meet the qualifications to serve as a juror in the United States were shown one of two identical videos of an opening statement. However, in one video the attorney has a neck tattoo, whereas in the other the attorney does not. Subjects were then asked a series of questions measuring their impressions of the video to determine if there was some difference correlated with the presence of the exposed neck tattoo. After reviewing the responses, responses indicated that there was no statistically significant difference between when the attorney had or did not have the neck tattoo. Subjects did not mention the tattoo a single time in any open-ended questions, and the ultimate verdict jurors came to did not have any statistically significant difference either. The aim of this thesis was to allow prospective attorneys to make educated decisions about whether to get a tattoo, whether they should display this tattoo in court, and how that tattoo can influence jurors in court
My Body, Your Choice: Exploring Reproductive Abuse Among Undergraduate Women In A Post-Roe America
No full textThe U.S. Supreme Court’s Dobbs v. Jackson decision in June 2022 overruled Roe v. Wade (1973) and held that abortion access is not a constitutionally protected right. The overturn of Roe v. Wade has had notable impacts on women’s overall sexual behavior and reproductive choices, and it highlights a macro-level infringement on women’s reproductive agency. Coercive condom use resistance violates reproductive autonomy on a micro-level, but can have equally harsh effects. Previous literature has studied these occurrences singularly; this research investigates connections between them. This study recruited 14 undergraduate women with a history of reproductive coercion, in the form of coercive condom use resistance, from the University of Central Florida for semi-structured interviews. Using an inductive qualitative approach, this research explores participants’ perspectives on the US government in a post-Roe world in relation to their personal experiences with reproductive decision-making. I also discuss how experiences with reproductive coercion may contribute to feelings of shame and subsequent cycles of self-blame and victim-blaming. This study investigates the relationship between two complex forms of reproductive abuse and opens a dialogue around how society and actors (and thus institutions) within the U.S. government perpetuate the shame associated with both
Collectives in Cases of Human-Machine Interaction: A Pragmatic Defense of Human-Machine Collectives
No full textHumanity’s future will include greater integration with different kinds of increasingly autonomous and interactive technological systems. Doing so is likely to confront us with reasons to adapt some of our currently accepted concepts and practices. We contend that among these is included a persuasive pragmatic reason to undertake just such an adaptation in our concept of collective responsibility and the practices attendant to it. The core of this pragmatic reason lies in how it allows us to respond to the issue of possible techno-responsibility gaps, which have been at the center of much of the attention and debate surrounding autonomous technologies. Our guiding thought is that we ought to consider a spectrum of interactiveness as an additional parameter when confronting such possible gaps. We contend that as one proceeds along the spectrum of increasingly depthful interactivity between human and machine, individual responsibility fails to provide the tools necessary for fully accounting for the role of responsibility, and we turn to the idea of collectivizing responsibility in such cases. We will claim that collectives can be instantiated by some agent-non-agent relationships, with the central condition being that this relationship reaches a meaningful level of interactivity. We take a requirement for this to be that the technology in question occupies a particular space upon an Interactive- Autonomous Spectral Field. Without having to single out specific humans in the loop or consider machines as bearers of responsibility, we may consider humans and the machines they interact with as a morally-relevant collective
College Students’ Perceptions of Artificial Intelligence (AI) Risks and Benefits in Pakistan
No full textWith the rapid advancements in technology over the past 2 decades, it has become crucial to understand people’s attitudes toward artificial intelligence (AI) adoption and its associated risks. Given the increasing access to the AI technologies, it is imperative to examine how young people in non-Western societies like Pakistan perceive AI risks and benefits. We conducted an online survey of college students who had used AI technology in the past 6 months. The results of our study indicate that the majority of college students view AI technology positively and perceive it as an opportunity to enhance workplace productivity. In addition, most of the respondents are optimistic about the future applications of AI in their individual lives and society. This research contributes to the literature on how college students in Pakistan perceive AI in their daily lives and offer implications for future scholars interested in studying AI technology use in non-Western countries
Marine Ecosystem Services Disruption and Social Violence
No full textOver the past century, human activities have profoundly altered ocean and coastal ecosystems, significantly impacting communities whose livelihoods depend on these environments. This dissertation explores how disruptions in marine ecosystem services contribute to the emergence of social violence in coastal communities, with a specific focus on the Colombian Caribbean. While prior research suggests a potential link between environmental degradation and conflict, empirical evidence remains limited and inconclusive. This study addresses that gap through a multi-method, interdisciplinary approach that integrates environmental science, political science, and computational modeling to examine the mechanisms linking ecosystem disruption to social violence.
The research follows a three-stage research path that combines qualitative and quantitative methods. First, it conducts an empirical analysis of how climate change-induced disruptions in marine ecosystem services affect selected sites in the Colombian Caribbean, utilizing environmental data, statistical techniques, and geospatial analysis. Second, a semi-digital survey experiment examines how narratives of ecosystem service disruption influence public perceptions of non-state violent actors, investigating whether environmental stress increases social tolerance toward such groups. Finally, an agent-based simulation model is developed to explore the conditions under which ecosystem degradation may lead to social violence, drawing on empirical insights from the previous stages.
By applying an innovative conceptual and methodological framework, this dissertation offers new insights into the mechanisms linking environmental change and social instability. The findings suggest that environmental degradation not only heightens adverse social outcomes but also increases community vulnerability to violent actors. These results carry significant implications for policymakers, conservation practitioners, and scholars by underscoring the need for sustainable marine ecosystem management strategies that address both ecological and social resilience. Ultimately, this research advances our understanding of the complex socio-environmental dynamics shaping human security in the face of climate change
Analyzing the Global Changes in the Seasonal Cycle of Sea Level, Storm Surge, and Ocean Waves
No full textChanges in the seasonal cycle of extreme sea level components can modulate the flooding risk along coastlines. This dissertation evaluates the changes in and potential co-occurrence of the seasonal cycles of mean sea level, storm surge, and ocean waves. Seasonal cycles characterize the generally expected climate conditions throughout the year with distinct high and low patterns. These regular and predictable cycles have shown non-stationarity in some locations across the globe. This means the timing of the expected peak may shift to occur earlier or later. Shifts in the timing of the maximum sea level impact coastlines with increased risk of flooding if the higher mean sea level occurs at a time of year when factors like storms or high tides are also at their peak. A moving harmonic analysis is applied to decompose the data into amplitude and phase components which describe the variability and timing of the annual peak, respectively. Clustering techniques reveal coherent regions in the North Atlantic coast with similar patterns of variability in their annual sea level cycle. Dominant modes of large-scale climate variability influence changes in the seasonal cycle of both sea level and storm surge. The seasonal cycles of mean sea level and storm surge peak within 30 days of each other at a major portion of tide gauges studied. Extreme value analysis shows that the month of highest storm surge return levels often changes from winter to summer or fall when focusing on longer return periods in places where tropical cyclones occur. Globally, ocean wave seasonality is more stable over time with peaks occurring mostly within the same month over the time period studied. Significant wave height measured from satellite altimetry versus estimated from multi-model products show agreeable estimates yet also point to regions where uncertainties are relatively larger
Holographic optical elements for complex beam transformations
No full textIn this thesis, we explore the design, fabrication, and application of volume holographic phase elements in photo-thermo-refractive (PTR) glass for two key purposes: expanding the eye-box in augmented reality (AR) displays and controlling optical angular momentum (OAM) modes in laser cavities.
Encoding complex phase structures in PTR glass enables efficient beam shaping, multiplexing, and wavefront engineering, offering strong potential in AR displays, optical communications, and structured light. Holographic optical elements (HOEs) recorded in PTR glass exhibit high diffraction efficiency (over 99%), thermal stability, and chemical durability. Combined with low absorption and scattering in the visible and near-IR, these features make them suitable for both low- and high-power laser systems.
For AR applications, we developed a compact method to expand the eye-box using volume gratings operating in the Raman-Nath regime. This achieved uniform 2D image replication over a large area, significantly expanding the viewer’s zone while maintaining brightness and optical efficiency. To demonstrate this, we integrated a time-modulated single RGB laser source with a single phase-light-modulator as image generator, reducing system size and mitigating chromatic and spherical aberrations. The phase control of HOEs enables precise image projection without bulky optics, allowing more compact and lightweight AR devices.
For OAM applications, we designed a non-resonant Fabry-Pérot (FP) structured cavity with a holographic phase mask (HPM), maintaining the orthogonality of Laguerre-Gaussian (LG) modes that produces a flat, resonance-free spectral response and supports broadband output. This cavity design opens up new opportunities in optical communications, beam shaping, and quantum optics. In general, this work demonstrates the potential of volume holography to reshape optical systems by enabling compact, efficient solutions for wavefront control, structured light, and multimodal beam generation
Advanced Deep Learning Algorithms for Medical Imaging Applications: Tumor and Organ at Risk Segmentation
No full textAccurate segmentation of tumors and organs at risk (OAR) remains a fundamental challenge in medical image analysis, directly affecting diagnostic accuracy, treatment planning, and patient outcomes. Although automated segmentation methods have advanced, they still face difficulties in anatomically complex regions and in cases with low tissue contrast. A major contributor to this variability is intra- and interobserver disagreement, introducing uncertainty into annotations and model predictions.
This dissertation investigates the role of segmentation uncertainty and its impact on model reliability, interpretability, and clinical integration, with a focus on lung, pancreatic, and head and neck cancers.
The first component introduces uncertainty-aware segmentation models that incorporate probabilistic outputs and spatially guided loss functions. A novel Uncertainty-Guided Coarse-to-Fine framework enhances both conventional and transformer-based architectures, improving performance in ambiguous regions. Additionally, self-supervised pretraining is employed to improve feature representation and generalization, particularly in settings with limited labeled data.
The second component examines how tumor-specific characteristics relate to segmentation performance. Radiomic features emerge as more reliable indicators of case-level difficulty than traditional descriptors. These insights inform the design of expert-in-the-loop systems for selective case review and model refinement.
The final component extends uncertainty modeling to clinical outcome prediction. A hybrid strategy that combines deep neural embeddings with handcrafted radiomic features is applied to two tasks: predicting three-year survival for non-small cell lung cancer and stratifying the risk of pancreatic cysts using MRI. Notably, a correlation is observed between peritumoral uncertainty and prognostic value in lung tumors.
This dissertation presents clinically grounded, uncertainty-aware frameworks for segmentation and outcome prediction. By integrating anatomical priors, spatial uncertainty, and radiomic interpretability, it advances robust solutions for improving segmentation accuracy and supporting precision oncology through predictive modeling
Gradient-based Optimization and Control of Systems with Two Decision-makers and Delayed Information
No full textIn today’s world systems are complex in nature, often involving two or more decision-makers (DMs) each attempting to optimize the performance of the system using an objective function that reflects its own preferences and is usually different from the other. Such systems are very common in power, microeconomics, and other systems. The focus of this research is how such systems are optimized and how the results of optimization are implemented in practice. Without loss of generality, we consider systems with two DMs, each attempting to optimize the system’s by minimizing its own objective function. The solution of these types of problems is known as the Nash equilibrium.
One of the main drawbacks of the Nash equilibrium is that neither DM can minimize its own function without having some knowledge of the decision variables or decision process of the other DM. What information do the DMs agree to exchange or share will determine the process by which the Nash equilibrium is reached. We examine this issue in detail. We propose an iterative process for each DM to adjust its decisions based on the direction of the gradient of its own objective function. We explore two possible alternatives in which each DM will decide to share current or past information with the other DM at every iteration in the process. These two alternatives generate two different scenarios that will describe the evolution of the process by which the Nash equilibrium may or may not be reached. We investigate analytically the conditions in each scenario on the parameters in the objective functions that will guarantee convergence of the process to the Nash equilibrium. We investigate the implementation of the gradient-based algorithms to two important real-world applications: the duopoly problem in microeconomics and the microgrid price control in an energy management system
