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The State of Marriage Equality for Disabled Adults in America: The Social, Cultural, and Legal Barriers
No full textAn Exploratory Study in Measuring Interviews Through Self-Perceptions, Mutual Gaze, and Qualitative Language Analysis
No full textInterviews are frequently used in clinical, media, and research settings to elicit rich information, share experiences, and develop common understandings. Despite their prevalence, it is difficult to determine the objective quality of an interview because assessments usually rely on participants’ subjective post-interview impressions. To establish the basis for more objective assessments, we used two different approaches to test whether gaze behavior during interviews may serve as a useful predictor of interview quality. First, we tested whether global gaze synchrony could be reliably assessed and could positively predict interview outcomes. Second, we rated the interviews and analyzed what qualitatively was common between the higher and lower rated interviews. We corroborated these measures against two basic measures of interview quality: subjective ratings of interviews and cognitive load. We recorded gaze data using Tobii Pro Glasses 3 worn by dyad pairs while they discussed biographical experiences. Participants completed a post interview questionnaire assessing their cognitive load and subjective experiences, and interviews were judged for quality and interestingness of elicited experiences. We tested whether our derived measures were valid by assessing their technical feasibility, their basic psychometric properties, and the degree to which they predicted interview quality. Though gaze did not predict interview quality, participants demonstrated a propensity to overestimate their performance in the interview when compared with outside raters. Additionally, it seemed that gaze was significantly lower in interviews than otherwise reported in literature
Development of Improved Electron Transfer Materials in Bioelectrochemical Systems
No full textThere has been a growing interest in leveraging biological materials to solve problems related to electrochemistry in recent years. Efforts in this area have been hindered by a lack of materials that can adequately provide an interface to harness nature’s refinement. Previous studies have shown that conductive polymers are excellent candidates for providing a supportive framework to enhance the usage of such biomaterials. This dissertation focuses on improving the field of biomaterials, particularly centered on the Photosystem I (PSI) protein, a vital component necessary for photosynthesis in plants. PSI has been shown to be an excellent component to promote light-driven reactions due to its robust nature, near perfect internal quantum efficiency, and high redox potential. Through the refinement of the process of interfacing biological components to inorganic substrates, the field can further address renewable energy problems through the application of PSI. This refinement is explored in three areas: morphology, direct electronic wiring, and metal loading of the polymer. By exploring anion effects in the electropolymerization of the conductive polymer PEDOT, notable improvements were made, revealing an enhanced synergy between the two materials. In the next component, polypyrrole was grown directly out from one of the active sites of PSI, producing hybrid, photoactive nanocomposites capable of direct electron transfer. Continuing with the theme of conductive polymers, an organometallic redox polymer was also studied. While osmium-coupled poly(vinylimidazole allylamine) has been widely used in some electrochemical sensors, control of the extent of metal loading has been poorly quantified and not well optimized. This work reveals the correlation between metal loading and the effect on the resulting polymer’s electrochemical properties. Each of these areas has shown different avenues with which a system may be tuned to enhance the interface with biomaterials. Specific examples are discussed including biohybrid energy generation and microfluidic sensing. Finally, an overview of areas for improvement amongst solid-state applications is presented along with a new paradigm of characterization for electrochemical assays to significantly aid in the understanding of magnetic bead-based detection methods
Students’ Self-Regulated Learning in Mathematics: An Examination of Beliefs, Monitoring, and Control
No full textThis dissertation explores students’ self-regulated learning within the mathematics context. An overarching conclusion from the general self-regulated learning literature is that students are poor self-regulators. This conclusion is based on survey and experimental, lab-based research demonstrating that students underuse effective study strategies, like retrieval practice and interleaving (Hartwig et al., 2022; Karpicke et al., 2009; Tauber et al., 2013); and that posttest performance is lower when students have to self-regulate their use and amount of practice (Badali et al., 2022, 2023; Dunlosky & Rawson, 2015). I explore the generalizability of this conclusion to college students learning mathematics by examining students’ study strategy use, study strategy beliefs, and relations between students’ monitoring, control, and learning. Chapter 2 reports on two online surveys that explore study strategy use and beliefs for mathematics, and contrast this with a domain that involves less problem solving: social sciences. Many students reported using effective study strategies, like studying worked examples and problem solving for their mathematics learning, and students believed these study strategies to be effective. Moreover, there was evidence of domain-specificity, as study strategy use and belief differed across domains. Chapter 3 was conducted in an authentic learning environment, and explored college students’ study strategy use and beliefs, and relations between study strategy use and calculus midterm scores. Perceived effectiveness of study strategies positively correlated with study strategy use, while perceived effort did not correlate with study strategy use. I identified only one significant correlation between study strategy use (ineffective study strategies) and midterm performance, and this relation was marginal after accounting for prior achievement. Chapter 4 reported on two experiments that examined the effectiveness of participants’ self-regulated learning choices, and explored relations between monitoring, control, and learning. Contrary to my hypotheses, allowing participants to self-regulate how much and/or what study strategies they used did not negatively affect their posttest performance. I also found evidence that prior knowledge, which is often not measured, informed monitoring and control processes. If we wish to increase mathematics learning, our theories of how students self-regulate their learning need to at least be somewhat domain-specific
Subset-Specific Mitochondrial Stress and DNA Damage Shape T Cell Responses to Fever and Inflammation
No full textHeat is a cardinal feature of inflammation, yet impacts on immune cells remain uncertain. We show that moderate-grade fever temperatures (39°C) increased murine CD4 T cell metabolism, proliferation, and inflammatory effector activity while decreasing regulatory T cell (Treg) suppressive capacity. However, heat-exposed T helper 1 (Th1) cells selectively developed mitochondrial stress and DNA damage that activated Trp53 and STING pathways. Although many Th1 cells subjected to such temperatures died, surviving Th1 cells exhibited increased mitochondrial mass and enhanced activity. Electron transport chain complex 1 (ETC1) was rapidly impaired under fever-range temperatures, a phenomenon that was specifically detrimental to Th1 cells. Th1 cells with elevated DNA damage and ETC1 signatures were also detected in human chronic inflammation. Fever-relevant temperatures thus disrupt ETC1 to selectively drive apoptosis or adaptation of Th1 cells to maintain genomic integrity and enhance effector functions
Transforming Experiences Into Expertise: Leveraging Event Cognition to Support Self-Regulation in a Practical Learning System
No full textTheoretical and empirical evidence suggests that event cognition influences both the quantity and quality of self-regulatory processes learners deploy. This dissertation examines the relationship between event cognition, self-regulation, and learning from events, detailing the development of a guided reflection tool designed to leverage basic cognitive and perceptual processing to support self-regulation in experiential learning. This tool was empirically evaluated against a control condition in a within-subjects study with 17 Vanderbilt nursing students completing three clinical simulation exercises. The guided reflection tool was hypothesized to support students’ self-regulation, leading to improved simulation memory, metacognitive judgment accuracy, and simulation performance outcomes. Students who engaged with the Reflect System demonstrated significant improvements in metacognitive judgment accuracy and confidence. However, the tool did not significantly impact simulation memory, follow-up performance, or motivation. Additionally, findings diverge from established theoretical predictions, yet the observed link between event segmentation and metacognitive judgment accuracy highlights a promising avenue for future research. This work represents an initial step toward developing a generalized framework for integrating event cognition principles into experiential learning across diverse educational contexts
Rehabilitation Framework for Branched Water Distribution Systems
No full textWater distribution systems are essential for providing safe drinking water, yet their design presents complex challenges. These systems necessitate careful selection of pipes, pumps, and tanks, balancing service quality and cost while adhering to hydraulic equations and accounting for uncertainties. Various optimization techniques have been employed, including linear programming, nonlinear programming, and metaheuristics. This thesis develops an Integer Linear Programming (ILP) model for rehabilitating branched water distribution systems, taking into account future demand and generating optimal daily operational schedules accordingly. We apply our model to rural piped networks, focusing on multi-village redesign water networks in the Khardi and Karegaon villages of Maharashtra, India. The model is implemented in Julia and produces INP files of the generated networks that can be simulated and analyzed further using software like EPANET. It opens avenues for future research, including extending the model to looped systems, integrating with smart grids, and developing resilience to power outages in developing countrie
Perception of Auditory, Visual, and Audiovisual Motion in Macaque Monkeys
No full textThe ability to perceive moving objects, which tend to engage multiple sensory systems, is critical for navigating everyday environments. This dissertation examines how motion cues are processed and integrated across auditory and visual modalities in rhesus macaques. In Chapter 1, macaques performed a direction discrimination task using auditory motion stimuli that systematically varied in displacement, duration, and velocity. Behavioral analyses revealed that displacement had the strongest influence on motion direction sensitivity, with duration exerting a moderate effect (particularly at short timescales) and velocity contributing the least. These findings support a “snapshot” model of auditory motion perception, in which motion is inferred from sequential spatial samples, rather than encoded directly through dedicated velocity-tuned mechanisms.
Chapter 2 builds on this by presenting experiments utilizing matched auditory, visual, and audiovisual motion stimuli. In most conditions, audiovisual stimulation produced multisensory gain, i.e., enhanced motion sensitivity relative to the unisensory condition eliciting the highest sensitivity. However, these effects were often suboptimal relative to predictions from the Maximum Likelihood Estimation (MLE) model, which assumes cues are integrated based on their relative reliability. These results suggest that crossmodal motion integration in macaques does not consistently follow MLE predictions and may reflect more flexible strategies, such as those described by Bayesian causal inference models. Taken together, this work provides a detailed behavioral account of motion processing and multisensory integration in a nonhuman primate model. The results also lay a foundation for future neurophysiological studies,and highlight the importance of naturalistic sensory stimulation in studies of auditory and visual perception
Three Essays in Labor Economics and the Economics of Crime
No full textThis dissertation examines how information shocks, labor demand disruptions, and policy interventions affect crime, labor markets, and racial inequality. Each chapter uses quasi-experimental methods and administrative or panel data to document unintended consequences of social media trends, mass layoffs, and employment regulations. The first chapter studies a viral social media trend that spread information on how to steal certain Kia and Hyundai models. Using a difference-in-differences framework, I show that thefts of these vehicles surged more than sixfold relative to other cars. Cities more socially connected to Milwaukee—the trend’s origin—experienced markedly greater increases in thefts, alongside higher vehicle theft arrests. The results suggest that social media accelerated the diffusion of criminal skills, imposing large costs through victim damages and criminal justice expenditures. The second chapter examines the effects of manufacturing mass layoffs using data on workers certified for Trade Adjustment Assistance over two decades. I find that large layoffs—those eliminating at least one percent of a county’s labor force—lead to long-lasting declines in labor force participation and per capita income, accompanied by sustained increases in violent and property crime. These effects are most pronounced in areas hit by layoffs in low-wage manufacturing sectors and do not appear driven by reductions in police deterrence. The third chapter analyzes Ban-the-Box (BtB) laws, which delay employer access to criminal records. Using a stacked difference-in-differences approach with county-level data, I find that BtB significantly reduces employment for Black workers, driven entirely by a decline in hiring. There are no comparable effects for White or Hispanic workers. Employment losses are largest in counties with high rates of Black crime and large Black–White crime gaps, consistent with employers relying on group-level proxies when individualized information is unavailable
Designing Future Pedestrian Navigation Interfaces for Future Augmented Reality Smartglasses
No full textHead-worn augmented-reality (AR) technologies overlay 3D digital content directly onto physical environment, freeing users from traditional 2D interaction paradigms and positioning AR as a promising next-generation, always-on computing platform. However, designing effective AR interfaces remains a challenging problem. AR devices must operate in a variety of lighting and background conditions, which presents challenges for hardware and graphics. They offer novel interaction affordances and must work effectively for a wide range of individuals to be true consumer-level devices. This dissertation investigates the design space of head-worn AR interfaces, focusing on the display of spatial navigational cues using empirically grounded
methods in simulated mixed reality environments. It provides practical recommendations for AR navigation on smart glasses, derived from comprehensive evaluations of gaze behavior, cognitive load, and spatial learning. Furthermore, the research finds distinct engagement patterns with AR cues based on users' spatial abilities, informing personalized interface design. Notably, we demonstrate the utility of content-independent gaze metrics as indicators of spatial navigation ability and learning, suggesting their potential in adaptive extended reality applications. This research contributes to the advancement of human-centered AR navigation systems capable of adapting to individual characteristics and enhancing the process of spatial
learning