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Leveraging Primary Care Settings to Reduce Adolescent Suicide: Voices of Youth and Caregivers
Full text linkSuicidal thoughts and behaviors (STBs), particularly among adolescents with marginalized identities, are alarmingly high. Improving prevention requires increased identification and treatment of acute, proximal, and modifiable behavioral health (BH) factors related to STBs (i.e., online victimization, anhedonia, sleep disturbances). Marginalized adolescents face individual- and systemic- level stressors (i.e., discrimination) that can increase BH concerns and STBs. BH concerns are raised in over 50% of pediatric primary care visits, making primary care providers (PCPs) important “gateway providers” to triage adolescents at risk of STBs. To optimize this prevention approach, this mixed-methods study aimed to understand how adolescents and caregivers perceive their BH discussions with PCPs, and how adolescents’ perceptions vary depending on their experiences of discrimination.
Thirty-three adolescents with depression and current or past STBs (Mage = 15.1 years, 63.6% female, 45.45% Black, 45.45% White) and their caregivers were recruited from primary care. Adolescents and caregivers completed interviews soliciting their experiences with discussing STB-related BH concerns with PCPs. Results indicated that caregivers reported youth’s BH symptoms to PCPs more than youth did, but 42.1% of adolescent’s BH concerns still were not discussed by either caregiver or adolescent. Participants identified facilitators (i.e., client-initiated discussion, supportive providers, screening tools, discussing related concerns, adequate assessment and follow-up) and barriers (i.e., low symptom salience, perception of PCPs, client knowledge, limited opportunities for caregiver participation, cultural misunderstandings and transgressions from PCPs) for these BH conversations. Mixed-methods analyses revealed that adolescent’s perceptions of BH conversations varied by their previous experiences of discrimination, and that the most reported experience of discrimination was based on weight. These findings suggest that supportive providers, timely follow-up referrals, and culturally sensitive care can promote BH discussions with PCPs and ideally guide adolescents into appropriate treatment to prevent STBs. As implied by youth who experienced discrimination, it is imperative that PCPs deliver culturally sensitive care that also accounts for the intersecting stressors that vary depending on adolescents’ identities. Findings also highlight the importance of considering how weight-based discrimination impacts adolescent STBs and how PCPs can mitigate these impacts in healthcare settings as well
Quantifying the Effects of Environmental Covariates on Leaf Area Index (LAI) in Riparian Reforestation in Western Oregon, USA
Full text linkRiparian reforestation projects are projected to have high potential for increasing Leaf Area Index (LAI) after planting, but this benefit is not yet well quantified. Riparian forests are adjacent to a stream, wetland, lake, or other body of water. These areas have an abundance of ecosystem services, such as providing habitat and corridors to wildlife, filtering water, stabilizing streambanks, and providing shade and cooling for the adjacent water body. Western Oregon, USA contains an array of river systems surrounded by riparian habitat within temperate forest ecosystems, but many of these forests have been historically degraded. To restore some of these degraded ecosystems, over 2,000 riparian reforestation plantings have occurred in Oregon since 1995 to achieve goals such as providing wildlife habitat, streambank stability, and mitigating water temperature. Measuring the LAI outcomes of these projects can improve strategies for maximizing leaf output as a co-benefit in future plantings. We hypothesize that a combination of edaphic, climatic, geomorphic, and stand properties can be used to predict the LAI values from riparian plantings over time and space. To understand reforestation trajectories, we measured LAI using Digital Hemispherical Photography (DHP) at 37 riparian sites in western Oregon, which ranged in their environmental and planting conditions. Using these measured values, we created linear regression models to predict LAI values across the most significant predictor variables. Our models predict that both total LAI and canopy LAI increase with years since planting, proximity to streambank, tree stem density, decrease with fine particle content, with two, three, and four-way interactions, and decrease with slope as an independent effect. A unique set of predictors were important for understory LAI, which increased with understory species richness, distance from streambank, years since planting, lower temperatures, with two, three, and four-way interactions, with stream size as an individual effect. By quantifying the LAI of past riparian reforestation projects and the variables that impact it the most, we can understand strategies to optimize future projects, and therefore maximize their environmental benefits
Interactive Corruption: Atonal Freedom and Narrative in Video Games
No full textEngagement in rigorous pitch analysis of dissonant media music is remarkably infrequent; I attribute this reluctance to the (perfectly valid) reason of horrific music often being difficult to transcribe and/or using non-discrete pitches. As a result, such music is often viewed through an affective or topical lens. I acknowledge that both of these factors are important to the listening experience; as such, I view atonality (and the analysis thereof) as a sort of topic in and of itself. When a dissonant piece does utilize discrete pitches, however, analyzing its pitch content with greater specificity than has been historically applied offers rich information about a game's story, its world, and its characters. My choice to use video game music is purposeful: ludomusicology is a field that is, perhaps more than any other discipline, chiefly concerned with media immersion. My study, then, adds a pitch-narrative dimension to ludomusicological analyses of horror and horror-adjacent music. In this dissertation, I apply relatively basic post-tonal analytical techniques to video game music tracks that may be considered “atonal” or otherwise dissonant. Following Gassi (2019), I contend that composers set significant atonal relationships using other musical parameters to increase their audibility to the audience, even if subconsciously. In doing so, I elucidate otherwise latent narrative information that arises from the relationships discovered in those analyses.
In total, I do not only conclude that post-tonal analysis can reveal dormant conflict narratives in video game music. I also argue that video game music tells us a great deal about post-tonal analysis at large, that when it is applied to a medium that necessitates audience input, it inherently flirts with an interpretive dimension beyond merely pitch and narrative: other musical parameters such as rhythm, timbre, and dynamics become analogous to active agents in both the subconscious and perceivable realization of narrative
Border Fictions: Nationalism and Decolonial Aesthetics in US-Mexico Migration Literature
No full textSubmitted to the Undergraduate Library Research Award scholarship competition: (2025). 35 p.This essay explores the literary representations of national identity, national borders, and transnational Latinx migrants in Valeria Luiselli’s Lost Children Archive (2019) and Yuri Herrera’s Signs Preceding the End of the World (2015). Both novels interrogate the myth of American exceptionalism and the common preconceptions Americans have toward Latinx migrants: Luiselli’s novel portrays a national identity crisis following the narrator’s confrontation with the reality of the ongoing child refugee crisis, while Herrera’s novel assumes the transnational migrant’s perspective to dissect the illogical meanings attributed to the symbols and practices that support American nationalism. This project builds from Glenda R. Carpio’s formulation of “migrant aesthetics” in contemporary migration literature, from which I consider literary features that expose the fragile yet highly consequential assumptions that compose American national identity. Across the various sections of the essay, I argue that migration fiction constructively questions the nationalist ideologies that produce physical and intangible violence against Latinx migrants
THE IMPORTANCE OF FOLEY IN FILMMAKING: A CASE STUDY OF BUSTER KEATON’S “THE ELECTRIC HOUSE”
Full text link20 pagesFoley, the art of adding sound effects to film, is a vital but often overlooked part of what makes a movie come alive. This thesis explores the process of creating Foley in film, specifically for Buster Keaton's silent comedy The Electric House (1922). This project allowed me to explore how sound can function as a primary storytelling tool (a task usually associated with music) and how vital Foley is to a film's success. Over the course of several months, I successfully planned, sourced, implemented, and mixed Foley for the complete 22-minute film. As a creative thesis, the primary work is the film itself. This document serves as a supplemental reflection of that creative process, offering context and insights into the work that went into it. The final project represents a new treatment of The Electric House with over 100 Foley elements chosen, edited, and mixed using digital sound manipulation. This film should give the audience a deeper understanding of Foley’s place within an auditory landscape. Beyond my own creative goals, the project serves as a portfolio piece, showing applied sound design and helping position me for future work in film production
Psychological Distance in Maps: A Conceptual Framework for Applying Construal Level Theory in Cartography
No full textThe construal level theory of Psychological Distance (CLT) is an emerging psychological theory that could offer a rich framework for understanding communication in maps. According to CLT, as an individual’s psychological distance (the degree to which the topic is removed from an individual's frame of reference) from a topic increases, so too does their construal level (the degree of mental abstraction) of that topic. In cartography, this theory can offer a useful framework for trying to understand how the content of a map can moderate an individual’s reception of the map’s message. This thesis offers a conceptual framework for understanding how psychological distance may be present in maps.2026-08-0
Mean Field Langevin Dynamics, Mean Field Neural Networks, and Mean Field Ising Models
Full text linkWe study novel theoretical and algorithmic frameworks for sampling from complex probability distributions. We present three interconnected contributions that advance our understanding of Markov chain mixing, mean field optimization, and neural network training.
First, we introduce a virtual particle stochastic approximation algorithm for mean field Langevin dynamics. The key innovation is a two-particle system: real particles that form the output and virtual particles used for unbiased gradient estimation. This design achieves quadratic computational savings compared to standard particle methods while avoiding the technical machinery of propagation of chaos. We prove exponential convergence under standard regularity conditions and demonstrate the method's effectiveness on pairwise interaction energies common in physics and machine learning.
Second, we extend our framework to mean field neural networks, providing a computationally efficient algorithm for entropy-regularized training of two-layer networks. By leveraging the favorable geometry of proximal Gibbs distributions, we establish quantitative convergence guarantees without requiring the uniform-in-dimension bounds typical in prior work. This bridges the gap between mean field theory and practical neural network optimization.
Third, we analyze the mean-field tensor Ising model, which generalizes the classical Ising model to capture higher-order interactions beyond pairwise dependencies. Using discrete Ricci curvature theory — a departure from traditional coupling-based methods — we establish the first polynomial mixing time bounds for a Markov chain based on locally balanced proposals. Our approach reveals how geometric tools from optimal transport can provide new insights into sampling from high-dimensional spin systems.
This dissertation includes previously published co-authored material
Essays in Environmental and Labor Economics
No full textThis dissertation includes previously published and unpublished co-authored material. This dissertation consists of four essays that exploring two topics: a study on the effect of exogenous time shocks on labor productivity; and a study on the reliability of air pollution estimates from machine learning models, an empirical application this work using predicted fine particulate matter (PM2.5), and a reproducible database of PM2.5 concentrations across the contiguous United States.
In the first substantive chapter, using data on GitHub users around the world, I estimate the effects of transitions to Daylight Saving Time (DST) on worker activity. I find that transitions appear short lived at the daily level, with evidence of two days of declines before activity returns to baseline levels. However, hourly analysis reveals a transition to Daylight Saving Time that is much longer, with losses appearing in the early working hours of work days into the second week following the initiation of Daylight Saving Time in the Spring.
In the second substantive chapter, I examine spatial predictions of fine particulate matter (PM2.5). The accuracy and reliability of these predictions depend crucially on methodological choices. I examine these choices across the contiguous United States (CONUS) from 2002-2019. My analysis investigates how modeling and validation decisions affect (1) predictions' perceived accuracy for different tasks, (2) predictions' suitability throughout space, and (3) results in downstream empirical analyses. I evaluate model performance across conventional and spatially explicit cross-validation procedures, demonstrating that the standard validation methods substantially overstate predictive accuracy due to data leakage. I estimate prediction uncertainty bounds to better understand confidence in the predictions and propose a novel monitor-presence probability model to subset predicted PM2.5 to areas most similar to the training data, providing a more reliable set of estimates for empirical analyses. I conclude that there is no one-size-fits-all approach to modeling PM2.5 and the methodological decisions to generate PM2.5 predictions should be tailored to the specific application.
In my third substantive chapter, I revisit recent work evaluating the effect of the Clean Air Act's PM2.5 nonattainment designations. Building on the methodological critiques from Chapter 2, I replicate and extend the Difference-in-Differences (DiD) analysis from a recent published paper on the subject, using both original and revised predicted PM2.5 datasets. Using a binary classification model, I introduce a novel propensity-weighted DiD framework that reweights observations by their similarity to monitored locations, addressing monitor placement endogeneity. This approach reduces the size of estimated treatment effects and in one case, reverses the sign of the estimated effect. I conclude that the using predicted-PM2.5 data to estimate the impact of regulation on pollution levels remains sensitive both measurement errors in the predictive data source and the endogenous placement of air quality monitors.
Following my second and third chapter, my fourth substantive chapter contributes to the growing PM2.5 prediction literature by developing a reproducible, high-resolution database of PM2.5 concentrations across the CONUS from 2002 to 2019. The code repository includes all steps necessary to reproduce the results in this dissertation, including data collection, model training, and prediction generation. I provide a detailed description of the code repository's structure and functionality, allowing future researchers to adapt the PM2.5 predictions for their specific applications
[n]Cycloparaphenylenes: Unconventional Monomers in Polymer Synthesis for Electronic and Biomedical Applications
No full textLarge aromatic hydrocarbons are not generally thought of as suitable monomers in polymer synthesis on account of their poor solubility and limited ability to be functionalized. [n]Cycloparaphenylenes ([n]CPPs), a π-conjugated macrocycle in this class, differs from this expectation. Often conceptualized as the shortest cross-section of armchair carbon nanotubes, these “nanohoops” occupy a unique intermediate between discrete organic molecules and extended carbon nanomaterials. Of the former, [n]CPPs are soluble in a variety of common organic solvents and can be precisely constructed through a bottom-up synthetic approach. To the latter, [n]CPPs are thermally and chemically robust and exhibit fluorescence in a manner similar to – but distinct from – extended π-conjugated systems. Herein, this work explores the use of [n]CPPs as monomers and additives in polymeric systems towards the development of functional materials. We first look at the incorporation of these unconventional monomers in the context of conjugated polymers – generating high molecular weight polymers while highlighting improved electron delocalization between the linearly oriented conjugated backbone and radially oriented [n]CPP. We then transition to the implementation of [n]CPPs as a new class of thermally and chemically robust fluorescent monomers and polymer additives towards biological and biomedical applications.2027-10-1
The Memory Architect
Full text link10 page PDF and accompanying transcript (Word) with full image descriptions.“The Memory Architect” is a hand-drawn comic with bold, graphic black and white art with detailed crosshatching and manga-inspired character designs. It was created in collaboration between undergraduate cartoonist Emma Richardson and UO researcher Dasa Zeithamova as part of the Science and Comics Initiative. Read the comic online here: https://opentext.uoregon.edu/science-comics/chapter/the-memory-architect/Funded by NSF CAREER – 1944826-PHY; NSF-2238247 CAREER NSF; and R01-DA055439 NIDA – NSF CRCN