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Queer Inclusion in Libba Bray\u27S Beauty Queens: the Case for LGBTQ Ya Literature
No full textThis thesis is a time sensitive case study on the nature of Libba Bray\u27s novel Beauty Queensand it\u27s placement as both a metacognitive novel and discourse in the nature of queer acceptance in the publishing and media landscape of the 2010s and 2020s. This includes focusing on contextualizing the book in the changing landscape of queer acceptance and visibility in the media over the last 20 years through the lens of the inclusion in YA and how that manifest in the 2010 and 2020s book bans on LGBTQ YA fiction. The novel highlights the wider need for LGBTQ YA literature and how it compares to its contemporaries in avoiding book bans as compared to other books. The goal of this work is to study the Young Adult publishing market in terms of its willingness and ability to promote and publish novels featuring LGBTQ+ characters now (as of March 2025) as compared to the culture and climate of the industry in the 2010s. This study will use the 2011 novel Beauty Queensby Libba Bray, which features three different types of queer female characters, as a litmus test and barometer for the change in the perceived publishability of queerness in books published by major United States publishers in the 2010s and now in the 2020s. Sparked by a 2011 instance of publishers and editors asking a number of authors to remove their queer characters, Beauty Queenswas curiously not only able to keep its queer characters, but works to depict said queer characters with a vibrancy and integrity well beyond that of its counterparts at the time, which were censored for much less. Bray\u27s particular inclusion of a transgender character in the context of competing in a beauty pageant embodies the book\u27s goal of challenging readers in what they believe a beauty queen and teenage girl can be, outside of the societal norms and conformity ascribed to them. It is my belief that Beauty Queens\u27 unique narrative construction and interwoven plot that guarantees the keeping of its queer female characters, which are statistically less likely to appear among queer YA novels
Strategic Pricing in a Disrupted Hospitality Landscape: Asset Valuation, Competitive Behavior, and Consumer Preferences
No full textThe lodging industry is experiencing profound disruption as short-term vacation rentals (STVRs) such as Airbnb increasingly compete with traditional hotels, reshaping competitive structures, consumer expectations, and pricing strategies. While prior research has examined the impact of STVRs on hotel performance metrics, significant gaps remain regarding how pricing resilience, competitive behaviors, and consumer perceptions evolve under these new conditions. In particular, little is known about how ADR-based valuation models withstand competitive pressure, how STVR hosts respond strategically to hotel pricing signals, and how consumers evaluate partitioned pricing structures across accommodation types. This dissertation addresses these gaps through three interconnected studies designed to investigate pricing dynamics at the asset, competitive, and consumer levels. The overarching research question guiding the dissertation is: How can lodging companies adopt strategic pricing behaviors to sustain competitive advantage in the face of disruptive market forces and evolving consumer expectations?
The first study applies a panel data analysis across 16 U.S. cities from 2014 to 2022 to examine how STVR penetration and hotel development moderate the relationship between ADR and hotel market sale prices. The second study employs a dynamic panel Generalized Method of Moments (GMM) approach to investigate whether STVR hosts exhibit strategic inertia in response to hotel ADR fluctuations. The third study utilizes a choice-based conjoint experiment to evaluate consumer sensitivity to partitioned pricing, such as cleaning fees and resort fees, across STVR and resort settings. Findings reveal that ADR remains a critical but increasingly conditional determinant of hotel valuation, STVR hosts adjust pricing sluggishly and inconsistently to competitive signals, and consumers prioritize total price attractiveness and reputational attributes over proportional fairness in price structures.
Collectively, these results contribute to extending Industrial Organization Theory, Disruptive Innovation Theory, Sticky Price Theory, and Prospect Theory within hospitality management. The dissertation offers practical implications for hotel revenue managers, STVR hosts, investors, and policymakers aiming to navigate evolving pricing challenges and proposes directions for future research to further explore strategic adaptation in the disrupted lodging sector
Investigating the Immunomodulatory Effects of CDK8/19 Inhibitor SENEXIN631 in a HER2-Positive Breast Cancer Model
No full textHER2-positive (HER2⁺) breast cancer is aggressive and often develops resistance to anti-HER2 therapies. CDK8 and CDK19, transcription-associated cyclin-dependent kinases (tCDKs) in the Mediator complex, are dysregulated in HER2⁺ breast cancer, correlate with poor survival, and support transcriptional escape driving therapeutic resistance. Previous studies Previous studies in immune-deficient models demonstrated that CDK8/19 inhibition (CDK8/19i) reduces pro-tumor macrophages (M2Φs), but its role in immune-competent tumors and innate immune–mediated tumor control remains unclear. Since HER2⁺ tumors are often immunogenic and anti-HER2 therapies rely on innate immune activation, reprogramming immunosuppressive M2Φ toward an M1Φ-like phenotype could enhance antitumor immunity. We hypothesized that CDK8/19i modulates the tumor immune microenvironment (TIME) promotes pro-inflammatory (pro-INF) M1Φ reprogramming through transcriptional and metabolic programs. In vivo, Senexin (SNX)631, a selective tCDK8/19i, suppressed tumor growth in HER2⁺ immune-replete mice but not in immunodeficient (NSG, Foxn1nu) models, confirming immune dependence. In our fourth model, Tamoxifen-inducible CDK8fl/fl; CDK19−/−; ROSA-CreERT2⁺ mice exhibited impaired tumor progression independent of drug treatment, demonstrating that immune-intrinsic CDK8/19 loss reshapes the TIME. Compared to controls, CDK8/19 KO tumors exhibited increased M1-like macrophages and reduced immature myeloid populations, shifting from suppressive, myeloid-dense niches to helper- and effector-enriched immune zones—consistent with immune re-education rather than direct cytotoxicity. In vitro, SNX631 consistently skewed polarization towards an M1Φ phenotype across BMDMs, RAW264.7 (RAW), and THP-1 models, exhibiting strong STAT1–CXCL10 axis activation and CCL5 induction, while decreasing M2 related genes. In RAW, we compared IFNγ-only, LPS-only, and IFNγ+LPS M1Φ-polarizing conditions to evaluate whether CDK8/19i uniformly skews polarization or exhibits stimulus-specific effects, to better mimic complex TIME signaling cues. This allowed most physiologically relevant model for downstream mechanistic studies. Temporal (30min or acute phase & 24hr sustained phase) and dose analyses revealed transcriptionally efficient programs shifting to metabolically reactive, stress-driven programs. At 24hrs, M1 and M2 biases demonstrated dose-dependent STAT3/6 reduction with increasing dosage. For single M1 biases, intermediate SNX631 doses (0.5–1 µM) preserved STAT1 Tyr701 signaling with increasing HIF1α and ROS, basal-to-moderate p62, generating a transcriptionally efficient (adaptive) M1 program. IFNγ+LPS preserved pro-longed STAT1 Tyr701 signaling with increasing HIF1α, p62 accumulation, lysosomal stress, and ROS remodeling suggesting a stress-driven, trained-like phenotype. M2 programs were dose-dependently dismantled, peaking at 1 µM with increased HIF1α, p62, and ROS. Mito-Tracker and mitophagy analyses confirmed enhanced mitochondrial biogenesis and fusion-lysosome coordination in M1Φ, contrasting with disrupted lysosomal flux and mitochondrial loss in M2Φs. Importantly, CDK8/19 act as immune-regulatory checkpoints, distinguished by M1 biases, in a controlled dosing and time-dependent manner. These findings support a model in which SNX631 shifts transcriptional efficiency to stress-driven, adaptive M1-like state, resembling trained innate features which may lock in and skew M1Φs in an antitumor state
A Spatial Scan Statistic for Group Testing Data
No full textGroup testing involves pooling specimens from multiple individuals and offers an efficient means to surveil low-prevalence pathogens, but poses challenges for spatial cluster detection when only pooled results are observed. In this thesis, we develop a spatial scan statistic tailored to group-testing data with variable pool sizes. The statistic compares a null hypothesis of a homogeneous infection rate across all clusters to an alternative hypothesis that infection probabilities differ inside and outside a candidate cluster, with both models fitted by maximum likelihood estimation. We approximate the null distribution of the maximum likelihood ratio test via Monte Carlo simulation.
Through a comprehensive simulation study in a 46-county setting, we assess performance across two sample sizes (1,380 and 2,760 individuals), three pooling schemes (fixed sizes of 3 or 6, and randomly varying sizes 2–6), and two infection prevalences (low and high). Our results demonstrate that geographically coherent pooling (same county assignment) markedly enhances power compared to random pooling. The method performed best with smaller pool sizes and larger sample sizes, while larger pools and random assignment diluted the spatial signal and reduced detection performance.
We apply the method to tick pools tested for Rickettsia parkeri collected across South Carolina from 2021 to 2024. Ticks were gathered at multiple sites during that period, grouped into pools, and each pool was tested for Rickettsia parkeri infection using a group testing protocol. No statistically significant clusters were identified
Database Development for Reliable Small Object Detection in Maritime Environments
No full textAchieving high reliability in small object detection is critical for advancing maritime and littoral intelligent navigation operations. Computer vision provides an undetectable form of perception that can be easily integrated into existing camera systems, offering a low-profile yet powerful solution for navigation and situational awareness in water-based environments. While deep learning techniques have significantly advanced the field of computer vision, the detection of small objects remains a persistent challenge. Limited pixel representation, the scarcity of large-scale small object datasets, and the reduced detail and indistinct features of small objects complicate detection efforts, especially in complex environments. These factors collectively hinder the ability of detection algorithms to accurately detect, localize, and classify small objects in maritime and littoral settings. To address these challenges, the IMSEL Maritime Dataset has been developed and labeled in accordance with UMAA guidelines, providing a dedicated resource aimed at improving the reliability of small object detection in maritime and littoral environments
Integrating Ensemble Hydrologic Forecasts with Policy Optimization Models for Forecast-Informed Reservoir Operations (FIRO)
No full textEffective reservoir management in hydrologically variable regions such as California’s Central Valley faces increasing pressure to balance flood control, water supply reliability, hydropower generation, and ecosystem health. Traditional rule-based operations, while operationally simple, often lack the adaptability required to respond to real-time hydrologic conditions and forecast uncertainty. This study presents an integration of a policy tree optimization model with ensemble streamflow forecasts to enhance Forecast-Informed Reservoir Operations (FIRO) at Folsom Reservoir. Building on historical data for inflow, storage, and release, an interpretable, threshold-based decision framework was developed and coupled with 14-day ensemble inflow forecasts from the California-Nevada River Forecast Center’s Hydrologic Ensemble Forecast Service. The resulting policy tree was evaluated against historical operations, with performance assessed across key metrics including flood risk reduction, water supply reliability, and robustness under forecast uncertainty. The optimized forecast-informed policy tree demonstrated improved operational flexibility and resilience compared to historical operations. These findings highlight the potential of integrating machine learning-based optimization and real-time forecasting to advance adaptive, data-driven reservoir management under changing climate and hydrologic conditions
I See Him in Me: Implementing Culturally Responsive Small Group Reading for Multilingual Learners
No full textThis mixed methods study explores the implementation and impact of differentiated guided reading instruction for MLs in a second-grade classroom. Specifically, it examines how differentiation strategies are applied during guided reading sessions and investigates the role of culturally relevant texts in engaging and supporting ML students’ literacy development. Through a mixed-methods approach combining classroom observation, student artifacts, and interviews, the research highlights best practices for meeting the diverse needs of MLs and underscores the importance of using culturally responsive texts. Additionally, the study analyzes the effect of these instructional approaches on students’ academic progress by comparing Edmentum Winter and Spring assessment scores before and after implementation. Findings suggest that differentiated guided reading with culturally relevant materials can positively influence both student engagement and achievement among MLs
The Impact of Hosting Sport Mega-Events in Small Communities: An Analysis of Local Real Estate Markets and Relocation of Local Residents
No full textThis dissertation examines the impact that hosting a sport mega-event may have on the regional economy alongside the impact on local residents. Specifically, the present research estimates the net impact the 2018 Olympics had on temporary housing prices and the relocation of low-income households in small host and neighboring districts in South Korea. The study analyzes monthly rent prices and rental deposit prices over an 11-year period that includes the Olympics. Based on a hedonic pricing model, Two-Way Fixed Effects regressions estimate the magnitude of the impact on temporary housing prices and further assess whether the influence is associated with the Games. Additionally, Hot-Spot Analysis based on geographic information system visualizes the dispersed impact on the dynamic displacement of low-income residents in Olympic host districts. The empirical findings suggest that monthly rent prices only increased during the construction periods prior to the Games, while deposit prices inflated both before and after the event. Meanwhile, low-income residents moved into host regions prior to the Games but moved out of host districts after the Olympics. The increase in rent prices indicates demand for temporary housing in the vicinity of potential sport facilities before an event, while the gradual increase in deposit prices may imply financial burdens on low-income residents in host regions. Consistently relocating residents with low-income status provides a deeper understanding of the potential gentrification of regions that hosted the Games
Who Do I Want to Become?: Validating Identity as a Key Component of a Teacher Leadership Framework
No full textHistorically, teaching has been a solitary profession within a hierarchy, where educators work in isolation and their roles are primarily focused on instruction. However, as education has evolved, especially post COVID-19, there is a shift towards a need for a more collaborative, ecosystem-based approach, where teachers are not only in their classrooms but acting as teacher leaders within this ecosystem. This research aims to understand the development of teacher-leader identities through the use of the proposed, Ecosystem of Teacher Leadership Framework, which uses elements of self-leadership, recognition, and the ecosystem. Through both qualitative and quantitative methods, a survey-like interview was conducted with in-service teacher leaders. The questions examined teachers’ knowledge of teacher-leadership, and their perceptions of the proposed framework based on their personal experiences. Findings revealed that teacher leader identities are constantly evolving. It also highlighted the need for an emphasis on informal teacher leadership actions, as well as structured reflection and feedback. The study provides an updated framework that focuses on the findings of the study, as well as offering practical insights into both the implications of the study and future research
Quinone-Mediated Extracellular Electron Transfer in Escherichia Coli During Glucose Oxidation Metabolism
No full textThe growing global demand for energy, ongoing reliance on fossil fuels, and increasing water pollution from industrial and anthropogenic sources present significant environmental challenges. In response to these issues, renewable and sustainable energy sources offer substantial potential for reducing dependence on fossil fuels and ensuring access to clean water. Microbial electrochemical systems (MESs) have emerged as promising, eco-friendly solutions for energy-efficient wastewater treatment and bioremediation. A key challenge in MESs development is facilitating effective electron transfer between microorganisms and electrode surfaces. The first chapter of this thesis discusses the fundamentals of MES types, explains mechanisms of extracellular electron transfer, and explores microorganisms and electron mediators commonly used in MESs. The second chapter of this thesis presents a comprehensive review of soluble, redox-active quinones used as exogenous electron shuttles to help facilitate electron transfer from bacteria to electrode surfaces, providing insight on how mediator properties influence quinone-mediated bioelectrocatalytic performance. Specifically, this thesis examines a quinone-based mediator system for extracellular electron transfer (EET) in Escherichia coli during glucose metabolism. A library of 12 quinone redox mediators was evaluated through electrochemical measurements, revealing variations in mediated current densities based on mediator structure and concentration. Among the tested quinones, tetrahydroxy-1,4-benzoquinone produced the highest mediated current density of 11.7 ± 1.1 μA cm−2. Additional electrochemical characterization of quinone mediator reduction potentials in aqueous and aprotic media showed that redox properties in aqueous environments correlate with the observed mediated current densities in E. coli. These findings suggest that the critical electron transfer step occurs either within the bacterial cell or outside its membrane. This thesis offers valuable insights into the rational design of mediated bioelectrocatalytic systems, highlighting the importance of microorganism type, metabolic processes, and electrochemical mediator behavior in both aqueous and aprotic environments