2020-
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Item Embargo EXPLORING RADAR AS A TOOL FOR STUDYING MIGRATORY BIRDS AND THEIR RELATIONSHIPS WITH DYNAMIC LANDSCAPES(Colorado State University. Libraries, 2025) Jimenez, Miguel, author; Horton, Kyle G., advisor; Koons, David N., committee member; Ruegg, Kristen C., committee member; Yovovich, Veronica, committee memberAs a crisis-based discipline, conservation biology necessitates that we make timely management decisions to protect species based on the best available information. In effect, as new scientific tools become available, we must contend with simultaneously applying them in ways that provide novel insights and evaluating their limitations to assess the validity of those insights. The integration of radar with machine learning is one such tool that has revolutionized aeroecology, or the study of airborne organisms. Burgeoning methodologies leverage this integration, offering unique opportunities to understand how migratory birds are responding to large-scale environmental changes, such as urbanization and shifting light regimes. In this dissertation, my goal was to elucidate the promises and shortcomings of radar and machine learning as tools for informing migratory bird conservation management amid rapid global change. As a first step, I focused on validating observations from a local weather radar station. Weather radar systems have become a central tool in the study of nocturnal bird migration. Yet, while studies have sought to validate weather radar data through comparison to other sampling techniques, few have explicitly examined the impact of range and topographical blockage on sampling detection—critical dimensions that can bias broader inferences. In my first chapter, I assess these biases with relation to the Cheyenne, WY Next Generation Weather Radar (NEXRAD) site, one of the large-scale radars in a network of 160 weather surveillance stations based in the United States. I compared local density measures collected using a mobile, vertically looking radar with reflectivity from the NEXRAD station in the corresponding area. Both mean nightly migration activity and within night migration activity between NEXRAD and the mobile radar were strongly correlated (r = 0.85 and 0.70, respectively), but this relationship degraded with both increasing distance and beam blockage. Range-corrected NEXRAD reflectivity was a stronger predictor of observed mobile radar densities than uncorrected reflectivity at the mean nightly scale, suggesting that current range correction methods are somewhat effective at correcting for this bias. At the within night temporal scale, corrected and uncorrected reflectivity models performed similarly up to 65 km, but beyond this distance, uncorrected reflectivity became a stronger predictor than range-corrected reflectivity, suggesting range limitations to these corrections. Together, these findings further validate weather radar as an ornithological tool, but also highlight and quantify potential sampling biases. In my second chapter, I focused on using NEXRAD to study habitat transitions by migratory birds. During migration, birds regularly transition between terrestrial and aerial habitats. Yet, much of our understanding of migratory behavior is centered around either terrestrial habitat quality or atmospheric conditions separately, at relatively coarse temporal scales. I employed NEXRAD to study the dynamic drivers and relative importance of terrestrial, aerial, and sampling predictors as birds transition between the terrestrial and airspace boundary. I found that atmospheric conditions were consistently strong predictors of migration activity throughout the night, and across spring and fall seasons. Key sampling predictors, such as the time after local sunset, fluctuated throughout the night, with high importance shortly after sunset and diminishing importance in the middle of the night. Yet, terrestrial variables were not a strong predictor of nightly variation in migration activity. My results demonstrate that the importance of predictors of activity varies temporally, both within a single night and across seasons. These findings illuminate bird migration as a dynamic process, highlighting limitations and opportunities for employing weather surveillance radar to study transitions between terrestrial and aerial habitats. In my third chapter, I used NEXRAD to study migratory stopover in urban areas. Despite global expansion, the role of cities in macroecological processes remains understudied. Using radar estimates of migratory bird stopover across the U.S., I assessed urban landscapes' contributions to stopover and links to social demographics for 2,130 parks across 88 cities. Stopover hotspots disproportionately occurred on urban landscapes relative to land area, with nearly 50% of spring migration hotspots falling within Metropolitan Statistical Areas. The relationship between urbanization and stopover varied regionally, correlating negatively in eastern flyways and positively in western flyways. Finally, stopover was positively correlated with income but varied considerably, with many cities showing no effect or an effect in the opposite direction. This study highlights the significance of cities in a hemispheric-scale ecological process and demonstrate radar as tool for studying urban social-ecological interactions. Finally, in my fourth chapter, I investigated the effects of different light spectrums on birds in flight for the purpose of informing novel conservation management approaches. Artificial light at night (ALAN) has been shown to influence the behavior of migratory birds, yet how different light spectra modulate these effects is somewhat unclear. I conducted a field experiment across 31 nights at a remote site in northern Colorado using LED floodlights with white, red, amber, and blue lighting treatments during fall migration in 2023 and 2024. Using a vertically looking radar system, I quantified avian in-flight responses in migration traffic rate, flight height, and flight direction. I found that short wavelength, white light significantly reduced flight height, and this response was stronger than red, amber, or blue lights. Beyond providing insight into avian biology, my results could have implications for the conservation management of ALAN. Further, the ability to detect behavior changes from a small point source in a low-density migration system supports the notion that ALAN may be more pervasive than is often recognized. At its core, my dissertation is indicative of a broader shift in ecology and conservation science. Advances in remote sensing offer an opportunity to vastly expand the way we characterize social-ecological systems thereby diversifying the options we have for managing them. However, this “big data” approach must be validated and informed by local inference. My work emphasizes this point. As the integration of large datasets and machine learning become increasingly prominent in conservation biology, I urge the conservation community to explore their potential with creativity while remaining vigilant of the potential biases they may introduce.Item Open Access FAMILY TIES: EXAMINING FAMILY FUNCTIONING AND ALCOHOL USE AMONG AMERICAN INDIAN YOUTH(Colorado State University. Libraries, 2024) Douglass, Morgan A., author; Prince, Mark A., advisor; Davalos, Deana, committee member; Riggs, Nathaniel, committee member; Emery, Noah, committee memberObjective: American Indian (AI) adolescents report earlier initiation and higher frequencies of alcohol use than their non-AI peers. Early initiation and higher frequency alcohol use are associated with worse health outcomes. Researchers have been called to identify factors which protect AI youth from harmful alcohol use behaviors and other risk factors such as peer use. Method: This study is a secondary data analysis of an ongoing epidemiological research survey with AI youth. Data was collected in the Fall of 2021 and Spring of 2022. Participants were 4,373 AI adolescents from grades 6-12 across seven regions of the contiguous United States. Structural Equation Modeling (SEM) was used to test a second-order latent variable of family functioning built from measures of family cohesion, family norms against adolescent alcohol use (FN), and parental monitoring. Structural paths and interaction terms between peer use and family functioning were added to the SEM to explore direct effects and moderations Results: Family cohesion, FN, and parental monitoring were best represented by a second-order latent variable of family functioning. Family functioning was related a later initiation of alcohol use and lower alcohol use frequency. Family functioning moderated the relationship between peer use and alcohol outcomes. Conclusions: The latent variable of family functioning and its component measures are appropriate for use in AI samples. Additionally, family functioning, which is an inherent resilience factor in AI communities, was shown to be protective against harmful alcohol use behaviors. Results have implications for prevention/intervention research.Item Open Access EMOTIONAL LABOR AT WORK AND RECOVERY AFTER WORK: A MULTILEVEL DAILY STUDY OF THE DIFFERENTIAL EFFECTS OF SURFACE AND DEEP ACTING ON RECOVERY EXPERIENCES(Colorado State University. Libraries, 2025) Colley, Kelsie Lee, author; Prasad, Joshua, advisor; Prince, Mark, committee member; Riggs, Nathan, committee member; Gardner, Danielle, committee memberThe purpose of this study was to explore how daily experiences of self-regulation at work spilled over into after-work experiences. Specifically, this study examined whether the relationship between daily emotional labor at work and after-work experiences (recovery experiences) was mediated by perceived gratitude and/or motivation to detach from work. To investigate my hypotheses, I conducted an experience sampling study with Amazon’s Mechanical Turk (Mturk) with participants in the service-providing industry to better understand the process of emotional labor. This study heeds the call to understand better daily surface-acting and deep-acting relationships with variables outside of work and to explore the differential effects of different forms of emotional labor on recovery through more novel mediators. Contrary to expectations, many hypothesized relationships were not supported, suggesting that predicting recovery outcomes through emotional labor processes may be more complex than initially theorized. Nonetheless, a subset of findings indicates that surface acting and deep acting produce differential effects; specifically, surface acting appeared to more negatively impact recovery, whereas deep acting sometimes helped cultivate more recovery experiences—though these effects were inconsistent. The study further highlights that perceived customer gratitude and motivation to detach from work operate in nuanced ways, underscoring the complexity of pinpointing exact pathways to successful recovery. Taken together, the results challenge simplistic views of emotional labor as purely detrimental or beneficial and encourage more distinct theoretical and applied perspectives. These findings may prompt practitioners and organizational leaders to rethink emotional demands and how at-work experiences impact after-work experiences.Item Open Access Statistical inference on reproducibility in high-throughput experiments(Colorado State University. Libraries, 2025) Ellingworth, Austin, author; Guan, Yawen, advisor; Zhou, Wen, advisor; Keller, Kayleigh, committee member; Kokoszka, Piotr, committee member; Mykles, Donald, committee memberResults in high-throughput genomics are known to have large variability across independent replicate studies. For this reason, the formal assessment of the agreement of results for many hypotheses across replicate studies has been a burgeoning area of research in statistical genomics. Hypotheses with consistent results are called reproducible, while those without consistency are called irreproducible. The presence of reproducibility in experimental research is critical, as it ensures the validity of findings. In this dissertation, we devise three methods for assessing the reproducibility of results from high-throughput genomic studies, each with advantages under certain settings. First, we notice that many of the existing approaches to assessing the reproducibility of results from two replicate high-throughput genomics studies either depend on strict parametric assumptions on available summary statistics or fail to properly consider the consistency of reproducible signal across experiments in addition to its strength. Motivated by \cite{philtron2018maximum}, we introduce a function based on the rankings of summary statistics from each experiment to define a notion for reproducibility and identify reproducible hypotheses. The proposed nonparametric statistic takes into account both the signal strength and consistency of results. By examining the geometry of the space of ranks of summary statistics and utilizing the negative association dependence structure of ranks, a novel procedure is introduced for recognizing reproducible findings while controlling the false discovery rate (FDR). This method controls FDR under relatively mild assumptions. The theoretical FDR findings are validated through simulations that also reveal the method to be more powerful than existing procedures. Finally, the procedure is applied to two large-scale TWAS datasets, uncovering reproducible features. Second, we notice that existing methods for assessing the reproducibility of high-throughput studies ignore the known group structures of genetic features, such as transcripts belonging to the same gene or genes belonging to the same pathway. Motivated by \cite{li2011measuring} and \cite{Liu2016ANATMTOGH}, we present an empirical Bayesian framework for reproducibility that incorporates this group structure. Additionally, we introduce algorithms for testing reproducibility at the hypothesis and group levels that maintain control of posterior FDR. Next, a data-driven estimation procedure based on the EM algorithm is proposed to enable the application of these algorithms when the parameters it relies on are unknown. In simulation, we show that the inclusion of the group structure in the hypothesis-level procedure leads to superior performance in terms of power and FDR control compared to more naive methods, and that the group-level procedure outperforms methods that rely on aggregation prior to analysis. The proposed procedures enable researchers to integrate known group structure information into the reproducibility problem, yielding higher-quality results. Finally, while there is a dearth of existing literature for analyzing reproducibility across two replicate studies, there are strikingly few methods that consider cases with more than two studies, and those that exist generally assume the distributions of irreproducible summary statistics are known. Leveraging Kendall's coefficient of concordance, we introduce a rank-based statistic that quantifies the agreement of results for a particular hypothesis without enforcing such strict assumptions. Noticing that in real high-throughput genomic settings, we have many ``housekeeping'' genes that are unrelated to the disease of interest and thus can be considered as a control set, we utilize conformal inferential and bootstrapping techniques to devise three procedures for calculating approximate $p$-values from a set of the proposed statistics that can be used to discover reproducible hypotheses at a nominal level of FDR. Simulation studies reveal that the three methods show preferable performance to existing methods in terms of power and FDR control. Applying the methods to single-cell expression data from five COVID-19 studies, we show that the proposed statistic and its procedures can identify genes and gene pathways associated with COVID-19.Item Embargo CHEMICALLY RECYCLABLE POLYMERS VIA ACCEPTORLESS DEHYDROGENATIVE POLYMERIZATION: SYNTHESIS AND CHARACTERIZATION OF FUNCTIONAL POLYESTERS AND POLYAMIDES(Colorado State University. Libraries, 2025) Harry, Katherine Leigh, author; Miyake, Garret M., advisor; Chen, Eugene Y.-X., committee member; Kennan, Alan, committee member; Peers, Graham, committee memberThis dissertation presents advancements in the development of acceptorless dehydrogenative polymerization (ADP) and its application to the synthesis of polyesters, polyamides, and their copolymers. ADP is an emerging catalytic strategy that overcomes many limitations of traditional polymerization methods, offering key advantages such as improved atom economy, enhanced sustainability, and a broader monomer scope. These features position ADP as a powerful platform for the synthesis of functional, structurally diverse polymers. The motivation for this work stems from the escalating plastic waste crisis. While plastics have undeniably advanced modern society through their performance and versatility, the linear nature of their life cycle continues to drive global pollution. Polyolefins, in particular, combine excellent material properties with extreme resistance to degradation, allowing them to persist in the environment for decades. The central challenge is to create materials that not only rival polyolefins in performance but also offer improved pathways for depolymerization and recycling. In this context, both ruthenium- and manganese-catalyzed ADP are explored as strategies to synthesize a range of polymers with tunable properties and built-in degradability via ester linkages. These polymers can be selectively deconstructed, offering a pathway to closed-loop recycling. The dissertation highlights recent progress in ADP, its mechanistic underpinnings, and its potential to support a circular polymer economy.Item Open Access CONTAGIOUS CONSPIRACIES: UNMASKING THE ROLE OF CONSPIRACY THEORIES IN ONLINE ANTI-VACCINATION COMMUNITIES(Colorado State University. Libraries, 2025) Henery, Giovanna Leah, author; Martey, Rosa M., advisor; Clegg, Benjamin A., committee member; Long, Marilee, committee member; Arthur, Tori Ω., committee member; Burgchardt, Carl R., committee memberConspiracy theories in online anti-vax communities reinforce ingroup formation by showcasing an us vs. them dynamic between a “marginalized” ingroup and an oppressive, sinister outgroup, as well as promoting the group’s digital affective public and reinforcing their perceived libidinal economy. This is achieved through anti-vax-related posts that villainize public figures, posts that adopt hate speech and bigoted rhetoric, and posts that blend anti-vax and non-anti-vax-related content together, as well as the use of digital communication tools provided by social media platforms.While traditional research has focused on the psychological and sociological aspects of these beliefs, the functional role of conspiracy theories in shaping the dynamics of non-mainstream online communities remains underexplored. Employing a mixed-methods approach that combines Critical Technocultural Discourse Analysis with a discourse analysis conducted by a multimodal large language model (LLM), this dissertation addresses this gap by investigating the role conspiracy theories play in the functionality and communicative practices of online anti-vaccination communities. Grounded in the theoretical frameworks of social identity theory (SIT) and affective publics, this dissertation analyzes public content posted between June 1, 2023 and November 15, 2024 to the largest and most active anti-vaccination groups on two social media platforms, Facebook and Gab Social, to examine how identity, community, and platform architecture influence conspiracy theory discourse. The findings reveal how these communities operate across platforms. On Facebook, the anti-vaccination group functions as an affective public, characterized by community-building, supportive interactions, and the use of humor, with these relational elements driving user engagement. In contrast, the Gab Social group operates as a bulletin board where engagement is driven primarily by the dissemination of anti-vaccination conspiracy theories and interactions between group members are frequently combative. Analysis of post contents and the use of digital tools, such as comments and emojis, reveals that hate speech, extremist signaling, and the more extreme non-vaccine-related conspiracy theories are all more prevalent on Gab than on Facebook, further cementing the distinct platform dynamics. However, the major theme across both platforms is a shared us vs. them dynamic, which is a crucial aspect of community formation and building within SIT. This research provides a nuanced understanding of how platform architecture and community norms shape the expression of conspiracy theory discourse. The findings offer crucial insights for academics, social media companies, and law enforcement for monitoring online non-mainstream communities and understanding the mechanisms that can foster either social cohesion or dangerous rhetoric.Item Embargo Genomics of flowering time to accelerate breeding of drought-tolerant pearl millet for Senegal(Colorado State University. Libraries, 2025) Fall, Safietou Tooli, author; Morris, Geoffrey, advisor; Kane, Ndjido, advisor; Mckay, John, committee member; Argueso, Cristiana, committee member; Mason, Esten, committee memberDistinct selection strategies are required for two categories of traits targeted by breeding programs. While directional selection increases the mean of a desired trait (e.g., grain yield), stabilizing selection is necessary to maintain the optimal state of an acquired trait (e.g., flowering time). Balancing these strategies requires an optimized breeding framework that enables the de novo creation of elite gene pools to guide cross-design and accelerate genetic gain, especially in under-resourced programs. This thesis hypothesizes that trait-informed elite definition, grounded in trait architecture, enhances the precision of breeding programs.The Chapter 1 frames the challenge of managing multiple traits under different selection pressures in traditional and emerging millet programs. The Chapter 2 develops and compares molecular inference strategies to define cis- and trans-elite types. We show that the QGI-based similarity method outperforms other approaches, particularly for known QTL regions. Importantly, this finding highlights that uncovering the genetic basis of key traits is critical to applying this framework effectively. To address this, Chapters 3 and 4 focus on dissecting the genetic control of flowering time, a central adaptive trait in pearl millet. In Chapter 3, a forward genetics approach using genome-wide association studies (GWAS) in West African germplasm revealed an oligogenic architecture, with key loci including Phytochrome C (PhyC) driving ecotypic divergence. Population structure analysis further indicated the existence of shared gene pools at the regional level, offering opportunities for collaborative breeding. In Chapter 4, a reverse genetics approach was used to characterize the gene regulatory network underlying flowering. Expression profiling of early (Souna) and late (Sanio) genotypes showed that flowering is regulated by differential activation of the GI–CaHd3a pathway, modulated by photoreceptors such as CaPhyC and CaPhyA, leading to divergent regulatory dynamics between ecotypes. Together, these results provide the genomic and regulatory basis for trait-informed elite inference and support a breeding strategy that simultaneously conserves elite backgrounds while introducing desired traits. This integrative framework, which leverages population structure, trait architecture, and molecular regulation, demonstrates how quantitative, molecular, and functional genetics can be combined to enhance selection strategies in pearl millet and similar crops facing climate-related challenges.Item Embargo YOU WILL KNOW THEM BY THEIR MOVEMENT: EVALUATING PAIN AND MOBILITY BEHAVIOR IN PRECLINICAL MODELS OF POST-TRAUMATIC AND INFECTION- ASSOCIATED OSTEOARTHRITIS(Colorado State University. Libraries, 2025) Kloser, Heidi, author; Santangelo, Kelly, advisor; Henao-Tamayo, Marcela, advisor; Dobos, Karen, committee member; Goodrich, Laurie, committee memberOsteoarthritis (OA) is a progressive, multifactorial joint disease affecting an estimated 595 million people globally and is the leading cause of disability in the United States. Characterized by cartilage degradation, subchondral bone remodeling, and synovial inflammation, OA leads to pain, stiffness, and loss of mobility. These factors further contribute to comorbidities such as cardiovascular disease, metabolic dysfunction, and early mortality. While aging and female sex are primary risk factors, OA can also be triggered or exacerbated by joint trauma, repetitive stress, obesity, and systemic inflammation. Despite current therapies, an estimated 20-50% of joint injuries will typically progress to clinical post-traumatic osteoarthritis (PTOA) within 10-20 years, underscoring the urgent need for more effective therapies. Emerging evidence also implicates infectious diseases, including tuberculosis (TB), as potential facilitators of joint degeneration. To better understand these complex interactions, this work employed longitudinal assessments of pain and mobility behaviors to evaluate disease onset and progression across preclinical OA models. This dissertation aims to enhance the translational utility of rodent post-traumatic and infection-associated OA models by refining behavioral and mobility assessments, testing protocols, evaluating the therapeutic efficacy of stromal cell therapy and PTOA, and investigating the potential for infectious diseases to exacerbate joint degeneration. Chapter 1 presents a comprehensive review of rodent mobility and pain-related behaviors following destabilization of the medial meniscus (DMM) injury. This chapter highlights significant behavioral differences between injured and control animals in these PTOA models, identifies timelines for when changes are expected to occur, and provides a comprehensive summary of current efforts to understand behavioral and pain responses post-injury. Additionally, this review emphasizes the importance of standardizing and improving communication within the field to enhance reproducibility and translational relevance. Chapter 2 builds upon the behavioral insights presented in Chapter 1 by providing an in-depth analysis of short-term open-field testing in mice. This work establishes foundational behavioral profiles for naïve juvenile and adult male and female mice, offering evidence-based recommendations for optimal test durations and parameter selection. These findings support the refinement of behavioral assessments in preclinical research. Chapters 3 and 4 apply behavioral and pathological outcome measures to evaluate the effects of therapeutic and comorbid modifiers of OA. Chapter 3 investigates the potential of stromal cell therapies to modulate inflammation and improve clinical indicators of PTOA. Chapter 4 examines how chronic pulmonary TB infection affects joint degeneration and mobility-related behaviors in animal models, providing new insights into the pathogenesis of infection-associated OA. Chapter 5 concludes the dissertation by integrating the findings across studies, underscoring how behavioral outcomes are interconnected across different models and interventions. This work discusses the broader implications for the field and proposes future directions, including the development of composite behavioral scoring systems to enhance consistency and interpretability in OA research.Item Open Access Bayesian approaches to extreme value modeling, with applications to wildfires(Colorado State University. Libraries, 2025) Lawler, Liz, author; Shaby, Benjamin, advisor; Cooley, Daniel, committee member; Zhou, Tianjian, committee member; Mahmoud, Hussam, committee memberThe growing frequency and size of wildfires across the US necessitates accurate quantitative assessment of evolving wildfire behavior to predict risk from future extreme wildfires. In Chapter 2, we build a joint model of wildfire counts and burned areas, regressing key model parameters on climate and demographic covariates. We use extended generalized Pareto distributions to model the full distribution of burned areas, capturing both moderate and extreme sizes, while leveraging extreme value theory to focus particularly on the right tail. We model wildfire counts using a zero-inflated negative binomial model and join the wildfire counts and burned areas sub-models via a temporally varying shared random effect. Our model successfully captures the trends of wildfire counts and burned areas. By investigating the predictive power of different sets of covariates, we find that fire indices are better predictors of wildfire burned area behavior than individual climate covariates, whereas climate covariates are influential drivers of wildfire occurrence behavior. Recent advances in multivariate extreme value modeling leverage a geometric perspective, using the shape of the multivariate point cloud and its connection to the Lebesgue joint density, to make inference on joint tail probabilities. While the original statistical framework was fully parametric, relying on a gauge function that uniquely defines the shape for a given density, newer methods have introduced semi- and non-parametric alternatives to increase flexibility. In Chapter 3, we propose a modeling approach that retains the simplicity of the parametric framework but adds flexibility by using Bayesian model averaging (BMA) to improve prediction of tail risk probabilities. In contrast to previous works that rely solely on a truncated radial likelihood, we propose using a censored likelihood, which we find consistently outperforms the truncated radial likelihood, particularly in small-sample settings. To generate predictions, we use a simple importance sampling scheme that matches the accuracy of more complex methods at a fraction of the computational cost. Finally, we apply our approach to two fire weather indices, which are designed to capture somewhat orthogonal aspects of fire risk, to illustrate the practical utility of our method in environmental applications.Item Open Access Cumulative Trauma and Aggression Among Youth in Secure Residential Settings(Colorado State University. Libraries, 2025) Tunstall, Ashley M., author; Williford, Anne, advisor; Jones, Tiffany, committee member; Yoder, Jamie, committee member; Riggs, Nathaniel, committee memberThis study examined the association between cumulative trauma exposures and physical aggression among youth in secure residential facilities in Colorado. Using a nonexperimental, quantitative design, administrative data from 1,001 youth (ages 13–20) were analyzed to identify trauma exposure profiles and assess their relationship with aggressive behavior. Grounded in General Strain Theory (GST), Bronfenbrenner’s Bioecological Model, and Critical Race Theory (CRT), trauma exposures were measured with the UCLA PTSD Reaction Index–Version 5 and incidents of physical aggression were obtained from incident reports. Latent class analysis identified four distinct trauma profiles: (a) polyvictimization across community, interpersonal, and family domains; (b) polyvictimization in interpersonal and family domains; (c) high exposure to community violence and separation; and (d) lower trauma exposure. Logistic regression analyses indicated latent class membership was not significantly associated with physical aggression. Younger youths and Black youths had significantly higher odds of physical aggression. Consistent with CRT, the latter finding indicates the importance of examining how racialized trauma, structural racism, and systemic inequities contribute to patterns of aggressive behavior in secure residential settings.Item Embargo HIGH-ENERGY, FEW-CYCLE LASER BEAMLINE FOR RELATIVISTIC INTERACTION WITH ALIGNED NANOSTRUCTURES(Colorado State University. Libraries, 2025) Meadows, Alexander, author; Rocca, Jorge, advisor; Carmen, Menoni, committee member; Wilson, Jesse, committee member; Yost, Dylan, committee memberUltra-high intensity lasers have been used to produce a variety of sources of intense radiation and energetic particles through the irradiation of nanostructured targets, including high-brightness x-ray sources, energetic collimated sources of ion and electron beams, and quasi-monoenergetic pulses of neutrons. However, these experiments have been constrained to the use of multi-cycle laser pulse drivers with duration of 30-50 fs or longer. This work presents results from the development and commissioning of a new relativistic-intensity laser beamline for solid target interaction experiments with pulses in the few-cycle regime. Application of these laser pulses to nanostructured targets will produce a unique and mostly unexplored plasma regime in which the driving pulse duration is shorter than the time scale of ion motions. The scaling of few-cycle pulse compression to the multi-terawatt regime is demonstrated here by the performance of a laser beamline based on the spectral broadening of Ti:sapphire pulses in a large-bore hollow-capillary fiber and subsequent recompression. The millimeter fiber waveguide presents a unique geometry for spectral broadening in the Ti:sapphire spectral range that results in an exceptionally high energy throughput and its performance has been characterized over a wide range of gas pressure conditions. The compressed output pulses of 15 mJ energy and 6.9 fs duration set a new record for the peak power of post-compressed pulses in the <10 fs regime. A new reverse pressure gradient operation mode has been introduced and applied to allow for operation of the hollow-capillary fiber beyond the usual peak power limit set by the onset of self focusing. The output of the beamline has been focused to a relativistic intensity of 6.5 1018 W/cm2 and relativistic electrons have been accelerated by the irradiation of solid flat and nanostructured targets and characterized by a custom-built magnetic spectrometer. This beamline will allow for relativistic laser-matter interactions with nanostructured targets in a new and unexplored few-cycle pulse duration regime.Item Open Access ESSAYS ON AVIATION, REGIONAL ECONOMIC DEVELOPMENT, AND MIGRATION(Colorado State University. Libraries, 2025) Kalandarova, Ulmaskhon, author; Pena, Anita, advisor; Weiler, Stephan, advisor; Tavani, Daniele, committee member; Graff, Gregory, committee memberAviation is an important factor of promoting regional development. Its impact to the economy could be analyzed from various angles, including through the effect of airports to local and regional economies, and through the effects of novel aviation fuels to the local economies and sustainability, in general. The first two essays in this dissertation examine the effect of aviation from those above-mentioned angles to local economies in Colorado and California. The third essay focuses on the phenomenon of migration and remittances during the post-Soviet era in Tajikistan, a country in Central Asia. Motivated by reverse causality issue between airport development and regional economic growth, in Chapter 1, titled as “Air Transportation and Regional Economic Development in Colorado”, we examine the dynamic causal relationship between air transportation at Denver International Airport (DIA) and regional economic development for the Denver MSA and the overall state of Colorado using time series methods for the period from 2000 to 2019. The results reveal overall positive effects of air transportation on local regional development in the Denver MSA with muted effects for the state of Colorado as a whole, consistent with impacts fading for more remote areas. Estimation of VECM models and Impulse Response Function reveals bi-directional, positive, significant long-run causality between Total Domestic Flight Passengers and Total Business Entities in Denver: a 1% change in Total Domestic Flights Passengers leads to a 3% increase in Total Registered Businesses and this magnitude is higher than in the vice-versa case. Total Domestic Flight Passengers are also positively associated with local employment in Denver, in contrast to a negative effect for the larger Colorado region in the short-run. A 1% change in Total Domestic Flights Passengers leads to a 0.006% increase in Total Non-Farm Employment in Denver and about a 0.004% decrease in Colorado broadly. Total Cargo affects employment positively both in Denver and beyond, estimated by both VAR model and Impulse Response Functions. The same 1% change in Total Cargo is associated with about a 0.007% increase in Total Non-Farm Employment in Denver and about a 0.005% increase in Colorado. The paper confirms traditional claims that airport services play an important role in local and regional development measured via both traditional employment and non-traditional business variables. Furthermore, comparison of the Denver MSA to the wider state illustrates differences associated to the distance to the hub city. Chapter 2, titled as “Inter-fuel Substitution in the Aviation Sector and Sustainable Aviation Fuel: Case study of California”, explores the dynamics of inter-fuel substitution, focusing on the impact of biofuels in the aviation sector and their potential in decarbonizing aviation in California. Specifically, the research investigates two key objectives: (1) understanding the historical interplay of substitution or complementary relationships among general transportation fuels after the mid-2010’s introduction of biofuels, and (2) evaluating the extent to which biofuel adoption drives inter-fuel substitution in particularly aviation sector. Ordinary Least Squares (OLS) and Seemingly Unrelated Regression (SUR) methods are used to analyze the data from U.S. Energy Information Administration (EIA) and U.S. Environmental Protection Agency (EPA) for 1980-2022 to provide a comprehensive view of biofuel integration. Results reveal that while biofuels have not significantly changed traditional substitution and complementarity relationships in the general transportation sector, they serve as a viable alternative to kerosene-based jet fuel in aviation. A 1% increase in jet fuel price leads to 1.043% increase of SAF volumes consumed, demonstrating that SAF has become a valid substitute for a traditional kerosine-based jet fuel. The effect of price changes of SAF on jet fuel volumes still remains limited because of small shares of biofuels in aviation. The paper demonstrates biofuels' growing potential to reduce dependency on fossil fuels and their important contribution to achieving long-term sustainability in aviation. Finally, in Chapter 3, titled as “Motives of Migration and Remittances in Tajikistan”, we focus on migration phenomena in Tajikistan, analyzing what factors drive people to migrate from Tajikistan and to remit back to Tajikistan. Probit and Heckman sample selection correction methods are used to analyze migrant and household characteristics data from the World Bank’s “Jobs, Skills, and Migration Survey in Tajikistan, 2013.” Results reveal that migration cost variables like having networks and family arrangement of costs related to migration have a highest strong positive association with the probability of having migrants in the households, empirically reinforcing the evidence of how important migration networks and family arranged costs of migration are in shaping the migrations flows from Tajikistan to Russia, making diasporas important “non-formal” institutions between two countries. The college education and language skills variables reveal a negative association with the probability of having migrants in the households, complying with a Negative Selection migration process predicted by Roy’s model (1951). Language skills demonstrate a positive association with the amount of remittances, since it makes easier to find a higher-paid job knowing the destination language, and so more remittances could be sent to Tajikistan. Also, family size and family income show a positive association with remittances transferred to households. Additionally, the results reveal that there is a significant selection bias (errors from two equations are correlated, lambda is negative and significant) and therefore Heckman estimation method usage is justified to correct for the self-selection bias.Item Open Access THREE ESSAYS ON THE ECONOMIC AND ENVIRONMENTAL IMPLICATIONS OF AGRICULTURAL CONSERVATION INCENTIVES AT THE FIELD, REGIONAL, AND GLOBAL SCALES(Colorado State University. Libraries, 2025) Wang, Ming, author; Manning, Dale T., advisor; Countryman, Amanda M., committee member; Suter, Jordan F., committee member; Ogle, Stephen M., committee memberAgricultural conservation policies are central to efforts to address the dual challenges of climate change mitigation and rural economic sustainability. Agriculture contributes significantly to greenhouse gas (GHG) emissions, particularly through soil-based processes, leading to the expansion of agri-environmental incentive programs aimed at encouraging the adoption of climate-smart practices. Evaluating the effectiveness of these policies requires careful consideration of economic feasibility, producer behavior, market interactions, and broader socio-economic impacts. This dissertation consists of three essays that use quantitative methods, integrating econometric models, biophysical simulations, and general equilibrium analysis, to examine these dimensions. Together, the essays underscore the importance of incorporating market feedbacks, accounting for international emissions leakage, and evaluating local labor market outcomes to design agri-environmental policies that are both environmentally effective and economically inclusive.In the first essay (chapter 2) of this dissertation, we examine how endogenous crop prices affect estimates of greenhouse gas abatement supply on corn and soybean acres at the farm level under alternative climate change scenarios in the U.S. Corn Belt. We combine a discrete choice model of farmer behavior with a spatially explicit biogeochemical model of GHG emissions and link this model to crop demand curves to allow for price feedbacks. Producers are offered payments from the GHG reductions achieved by adopting climate-smart practices, no-till, cover crops, and reduced nitrogen application, and their adoption behavior is simulated across varying carbon price and climate scenarios. Results indicate that accounting for endogenous prices increases estimated abatement, particularly from nitrous oxide reductions, by up to 18 percent at a carbon price of $190t CO2e under the extreme climate scenario and by 25 percent under the sustainability scenario, relative to estimates based on exogenous prices. Results underscore the importance of considering market interactions when constructing abatement cost functions. In the second essay (chapter 3), we investigate emissions leakage from domestic conservation policy at the global scale by modeling the worldwide GHG emissions implications of expanding the U.S. Conservation Reserve Program (CRP). While CRP has been considered as a policy that can reduce domestic GHG emissions, our results show that it also generates significant spillover effects via global market adjustments. For an additional 4 million acres (1.6 million hectares) enrolled in CRP, approximately 236 thousand hectares of forest are converted to agriculture within the U.S., while cropland expands by 205 thousand hectares outside the U.S. due to market-driven land use changes. These spillover effects fully offset the mitigation achieved on the enrolled cropland, resulting in over 200% global emissions leakage. These findings underscore the importance of incorporating international leakage and market-mediated effects into the evaluation of land-based climate policies. The study contributes a novel framework for assessing conservation policies in a globally integrated economy and highlights the need for internationally coordinated approaches to ensure environmental effectiveness. In the third essay (chapter 4), we assess the regional-level economic effects of agri-environmental programs by examining the employment trade-offs between land retirement and working lands programs. We use panel data and a fixed effect model to address the endogeneity of EQIP and CRP enrollment. We deploy alternative identification strategies and controls to test the robustness of our results. Findings indicate that both cropland retirement and working lands programs are associated with higher local employment levels, and that reallocating conservation dollars from temporary retirement to working lands at the state level increases overall employment in each rural county by 0.4% per million dollars, with agricultural jobs increasing faster than non-agricultural jobs. These results offer valuable insights for policymakers seeking to generate environmental benefits while supporting rural employment.Item Embargo CHEMICAL DYNAMICS UNDERPINNING THE COMPOUNDED SEQUENCE AND SPATIOTEMPORAL TOPOLOGY CONTROLS IN LEWIS PAIR POLYMERIZATION(Colorado State University. Libraries, 2025) Reilly, Liam, author; Chen, Eugene Y.-X., advisor; Miyake, Garret M., committee member; Crans, Debbie C., committee member; Radford, Donald W., committee memberLewis Pair Polymerization (LPP) has emerged as a uniquely versatile platform for precision polymer synthesis. In particular, LPP’s ability to regulate polymer comonomer sequence and topology sets it apart from alternative methodologies. This contribution unravels the chemical dynamics and mechanisms of control that underpin LPP’s most unique capabilities. Specifically, this work elucidates the interplay of the kinetic and thermodynamic biases that arise within comonomer mixtures and demonstrates how this fundamental knowledge can be used to prepare advanced materials. Likewise, this work dissects the dynamic origin of LPP’s spatiotemporal control and leverages these findings to develop a new route to access traditionally elusive polymers of advanced topology. Collectively, these efforts serve as an example of how fundamental research can lead to new frontiers in materials design and discovery.Item Embargo Electrochemical Immunoassays for Point-of-Care Detection of Heart Failure Biomarkers in Saliva: Advancing Accessible Healthcare Testing(Colorado State University. Libraries, 2025) Pittman, Trey, author; Henry, Charles, advisor; Levinger, Nancy, committee member; Kennan, Alan, committee member; Kipper, Matt, committee memberHeart failure (HF) remains a leading cause of morbidity and mortality worldwide, with early detection and ongoing management critical for improving patient outcomes. However, current medical testing methods are often invasive, expensive, and inaccessible to many populations, particularly those in rural or resource-limited settings. Electrochemical detection offers a promising pathway to address these limitations. Electrochemical assays on screen-printed carbon electrodes (SPCEs) are an attractive option due to their low cost, favorable electrochemical properties, and ability to be fabricated in unique geometries. When combined with microfluidics, these technologies open opportunities for automated platforms, multiplexed detection, and the use of non-invasive sample matrices like saliva. However, developing a sensor compatible with saliva, engineering a microfluidic platform capable of processing viscous samples, and integrating these components into a unified system all present significant challenges. This dissertation addresses these issues by developing a novel, non-invasive electrochemical immunoassay platform for the detection of HF biomarkers in saliva, towards rapid, affordable, and decentralized point-of-care testing (POCT), and exploring simpler detection modalities. By leveraging saliva as a sample and integrating advanced sensor technologies, this work aims to bridge the gap between clinical need and technological capability, ultimately supporting more equitable healthcare delivery. Chapter 2 introduces the development of an electrochemical immunosensor specifically designed for the detection of galectin-3 (Gal-3) in saliva. The sensor utilizes SPCEs and optimized surface chemistry to ensure stability and sensitivity suitable for clinical applications. The chapter details strategies to overcome challenges associated with the complex saliva matrix, including effective antibody immobilization and sample preparation protocols, resulting in reliable biomarker quantification. Chapter 3 expands the platform to enable multiplexed detection of both Gal-3 and S100A7, two biomarkers relevant to HF prognosis. A dual-electrode array is integrated into a capillary-driven microfluidic device, allowing simultaneous detection of multiple analytes from a single saliva sample. The device automates reagent delivery and streamlines the assay workflow, requiring minimal user intervention and delivering results rapidly and cost-effectively. In the microfluidic system, the assay quantifies salivary levels of Gal-3 and S100A7, demonstrating successful multiplex detection and differentiation between these biomarkers. Chapter 4 investigates surface modification and antibody immobilization strategies for label-free immunosensors using SPCEs. Commercial SPCEs are identified as superior to lab-fabricated counterparts due to their enhanced consistency and electrochemical performance. Air-plasma treatment is shown to enhance electrode properties, and a comparison of immobilization methods-including passive adsorption, Protein A binding, and EDC/NHS coupling-provides insight into optimal strategies for sensor performance. A proof-of-concept immunoassay for HF biomarker Gal-3 validates the platform’s sensitivity and clinical relevance, advancing label-free SPCE-based biosensors for decentralized testing. This dissertation establishes a foundation for next-generation HF testing by demonstrating that non-invasive, saliva-based electrochemical immunoassays can deliver clinically relevant results at the point-of-care. The developed platform combines affordability, ease of use, and adaptability, making it suitable for widespread deployment in diverse healthcare environments. By reducing barriers to regular monitoring and early intervention, this work has the potential to transform HF management, reduce hospitalizations, and ultimately improve patient outcomes. Future directions include expanding the biomarker panel, further automating the testing process, and integrating digital health solutions to enhance remote patient monitoring and disease management.Item Open Access Investigating group-V doping limits in CdSeTe and potential application of CdSe as tandem top-cells(Colorado State University. Libraries, 2025) Hill, Taylor, author; Sites, James, advisor; Sampath, Walajabad, committee member; Munshi, Amit, committee member; Sambur, Justin, committee member; Rockett, Angus, committee memberCadmium selenium tellurium alloys (CdSeXTe(1-X) known as CST) are a photovoltaic specialist's dream: with ideal single-junction and tandem top-cell bandgaps (based on Se stoichiometry) and large absorption coefficient for all stoichiometries (enabling thin-film applications), CST continues to be a promising material for photovoltaic applications. However, CST is not without its problems. Record efficiency CST devices have demonstrated short-circuit current density (JSC) and fill factor (FF) near their theoretical maximum based on measured bandgaps, but continued improvements to device performance has been limited by the open-circuit voltage (VOC), which has been less than 900mV (< 80% of theoretical maximum) for nearly a decade. Advances in absorber doping for p-type conversion have enabled increased carrier densities, moving from roughly 10^14 cm^-3 with group-I doping (copper) to 10^16 cm^-3 using group-V doping (arsenic or phosphorus), but increases in VOC have not been reflected by this fact. This is typically attributed to the so-called "dopant activation" problem, which accounts for the density of acceptor states provided per density of dopant incorporated and tends to be less than 10% in polycrystalline CST. This indicates that roughly 9 out of 10 dopant atoms form defects which may compensate p-type conversion and additionally hinder device performance. Meanwhile, the use of Se alloying to reducing the effective absorber bandgap has afforded increased JSC, but the roles in which Se and group-V dopants play in conjunction with typical device processing is not widely appreciated. In this work, the modern advancements which have allowed for record efficiency CdTe based devices, namely the incorporation of group-V dopants and Se alloying, are examined to address misunderstandings and provide a framework for improving device processing. An investigation into the impact of group-V dopant concentration in CST using optimized device processing conditions reveals that the density of acceptors formed by group-V doping tends to plateau at a point (roughly 1-5 X 10^16 cm^-3) and further incorporation of dopants tends to reduce device performance through increased radiative recombination. Evaluation of a novel process to increase group-V dopant activation, thereby reducing the concentration of nonactive dopant defects, is presented by use of ion implanted oxygen getters. The presence of oxygen in CST devices is inevitable and an oxidated dopant is effectively an inactive dopant. By implanting elements which have a higher affinity for oxidation relative to dopant atoms, the formation of dopant oxides is reduced, and an increased dopant activation is demonstrated. However, this did not improve device performance in practice, indicating that while the methodology of reducing group-V oxides can increase activation, the process of ion implantation itself may introduce additional lattice defects which negate the increased dopant activation. This leads to an examination of the role Se plays in intrinsic CST absorbers independent of group-V doping, revealing an unexpected n-type intrinsic conductivity, which may be a source of defects which compensate the use of group-V dopants. This indicates that work must be done to carefully balance the distribution of Se throughout the absorber bulk, where a concentration gradient, rather than a uniform ternary stoichiometry, is shown to enable the best performance. Finally, pure CdSe absorbers with a large bandgap of roughly 1.7 eV are examined for potential application in tandem PV devices. CdSe absorbers grown at CSU demonstrate the requisite large bandgap and provide insight into limitations based on absorber thickness. This leads to a discussion on CdSe devices with record VOC. To date, published record efficiency CdSe devices have shown >80% of theoretical short circuit current (JSC/JSCSQ) and >60% of theoretical fill factor (FF/FFSQ). However, such record devices have achieved <50% of the theoretical open circuit voltage (VOC/VOCSQ). The development of CdSe devices using novel transport and contact layer structures involving organic semiconductors and transition metal oxides to achieve >60% of VOCSQ (VOC >900 mV) is presented. The limitations of CdSe absorbers are addressed through temperature and intensity dependent photoluminescence measurements, indicating that low charge mobility due to intrinsic trap states in CdSe bulk are the primary limiting factor to further increasing VOC.Item Embargo (In)Visibilities in the U.S. Imperial Academy: Central American Knowledge Production from Outside of Disciplinary Borders(Colorado State University. Libraries, 2025) Galvez, Eileen Michelle, author; Muñoz, Susana, advisor; Poon, OiYan, committee member; Sagas, Ernesto, committee member; Blanco, Yianella, committee memberIn the U.S. academy, Central American knowledge faces severe epistemic invisibility and a lack of disciplinary investment, with only two Central American Studies departments nationally. Within the discipline of higher education, there is a dearth of studies related to Central Americans that follow the pattern of erasure in the national landscape wherein U.S. Central Americans are excluded from the academy, knowledge production, and even the national imaginaries of minoritization in the U.S. (Padilla, 2022). This study aimed to better understand the systems that produce Central American invisibility by examining how U.S. Central American faculty experience three forms of (in)visibilities in the academy: invisibility, hypervisibility, and visibility.Designed as a project of epistemological disobedience (Mignolo, 2009), the study’s framework, Colonialities of the U.S. Imperial Academy, is a tool for fugitive scholarship (Harney & Moten, 2013), which employs the framings of coloniality of power (Quijano, 2000), gender (Lugones, 2007), knowledge (Lander, 2000; Quijano, 2000), and being (Maldonado-Torres, 2007) to interrogate the academy as an arm of empire. Combined with Central American-informed methods that include research accompaniment (Tomlinson & Lipsitz, 2019; Abrego, 2022). Central American diasporic storytelling (Contreras, 2024), and Black and Indigenous Central American feminist practices of re/memory (Ramsey, 2024; Guzman, 2025; White, 2025), the study’s findings are drawn from the storytelling of five U.S. Central American faculty. Co-constructed from a research relationality of Central American kinship, this study offers a larger story of the interconnectivity between coloniality, (in)visibilities, U.S. Empire, and its academy; articulates a Black Central American Caribbean consciousness; and weaves together testimonial narratives of Central American knowledge production as struggles for epistemic sovereignty.Item Open Access The Cost of Conformity: Masking Among Neurodivergent Workers and the Relationship with Mental Health and Job Attitudes(Colorado State University. Libraries, 2025) Clancy, Rebecca, author; Fisher, Gwenith, advisor; Dik, Bryan, committee member; Nelson, Niccole, committee member; Henle, Christine, committee memberNeurodivergent individuals are an important, but underrepresented, part of the workforce who face a number of challenges when it comes to obtaining and maintaining employment. Masking, defined here as the strategies used to conceal neurodivergent traits in an effort to conform to neurotypical norms, has been shown to have negative repercussions for individuals’ well-being, but has limited empirical research tied to the workplace. Using self-determination theory, the present study investigated how masking is related to worker mental health and job attitudes. Self-determination theory, and more specifically, basic psychological needs theory, has been used to explain motivation and well-being through the satisfaction of three basic needs: autonomy, competence, and relatedness. In this study, I hypothesized that masking would be associated with negative consequences for workers at least in part due to the active frustration of these needs, such that the experience of masking actively thwarts basic needs for autonomy, competence, and relatedness, and is likely associated with lower satisfaction of these needs as well. N=293 neurodivergent participants completed an online survey regarding their masking behaviors, perceptions of basic psychological needs, well-being, and job attitudes. Data were analyzed using higher-order structural equation modeling to test the hypothesized models regarding the associations between masking, needs frustration, need satisfaction, and individual mental health and job attitudes and found initial evidence for the role of need frustration and need satisfaction as atemporal and partial mediators between masking, mental health, and job attitudes. These results may inform future research and theory regarding the psychological process of masking used by a variety of neurodivergent individuals and its presence in the workplace. Results may also be used to inform HR policy and training programs to better support neurodivergent workers and increase broader understanding and knowledge for neurotypical leaders, managers, and coworkers.Item Open Access Exploring the Utility of Exposure Therapy in Anorexia Nervosa: The Role of the Fear of Food Measure(Colorado State University. Libraries, 2025) Kulish, Bailee Mae, author; Chavez, Ernest, advisor; Emery, Noah, committee member; Dik, Bryan, committee member; Faw, Meara H., committee memberBackground: Approximately 5% of patients diagnosed with anorexia nervosa (AN) die within four years of the diagnosis (Crisp et al., 1992; Moller-Madsen et al., 1970–1987; Patton, 1988). However, current evidence-based treatments for AN show limited efficacy (e.g., McIntosh et al., 2005; Kaidesoja et al., 2023). Exposure therapies have been recommended for use in AN due to the extensive overlap of anxiety disorder and eating disorder (ED) symptoms (e.g., Strober et al., 2004; Steinglass & Walsh, 2006), though which anxieties are central to ED symptomology is understudied (e.g., fear of weight gain, Brown & Levinson, 2022; Fairburn et al., 2009; fear of food, Brown & Levinson, 2022; Steinglass et al., 2010). The Fear of Food Measure (FOFM) examines fears that address all three components of a cognitive-behavioral model of anxiety. This study will examine the efficacy of exposure therapy in AN by examining scores on the FOFM and ED outcomes (using the Eating Disorder Inventory-3 (EDI-3)) after exposure therapy interventions. It will also examine the validity of fear of food (using the FOFM) as a central motivator/component to AN, by examining the connection between scores on the FOFM and the EDI-3. Lastly, this study will examine weight gain and its relationship to the FOFM and EDI-3. Results: Scores on the subscales of the FOFM and the EDI-3 significantly decreased from pre- to post-treatment. Feared Concerns was a significant predictor of all EDI-3 subscales, while Food Anxiety Behaviors was not. Additionally, Anxiety about Eating subscale significantly predicted some of the EDI-3 subscales, including Drive for Thinness and Body Dissatisfaction. Lastly, subscales on the FOFM were not a significant predictor of weight gain during treatment. Weight gain was also not a significant predictor of decreased scores on the EDI-3 subscales at post-treatment, aside from Drive for Thinness, although post analysis showed significant weight gain among participants from pre- to post-treatment.Item Embargo ANALYSIS OF FREQUENCY CONTROL AND GRID STORAGE EFFECTIVENESS FOR A WEST AFRICAN INTERCONNECTED TRANSMISSION SYSTEM(Colorado State University. Libraries, 2025) Abayateye, Julius, author; Bradley, Thomas, advisor; Zimmerle, Dan, advisor; Young, Peter, committee member; Burkhardt, Jesse, committee memberThe West Africa Power Pool (WAPP) Interconnected Transmission System (WAPPITS) has faced challenges with frequency control due to limited primary frequency control reserves (PFR). Battery Energy Storage Systems (BESS) have been identified as a possible solution to address frequency control challenges and to support growing levels of variable renewable energy in the WAPPITS.This dissertation examines existing frequency control challenges in the West African Power Pool Interconnected Transmission System and evaluates the effectiveness of Battery Energy Storage Systems (BESS) as a solution to enhance grid stability and resilience amid growing ambitions to increase variable renewable energy (VRE) penetration. To carry out this assessment, three studies were conducted - the first study assesses the effectiveness of BESS in providing primary frequency reserves (PFR) using open-loop simulations based on real WAPPITS frequency data. Results from this study suggest that droop-based BESS control strategies can mitigate fast frequency variations. In addition, it demonstrates that integrating BESS alone into the grid will not solve the frequency control challenges in WAPPITS, requiring the need for a revision of frequency control provision, including mandatory participation of traditional power plants in the provision of the service. The second study investigates primary and secondary frequency control challenges in WAPPITS using surveys from Transmission System Operators, field tests on power plants as well as analysis of events in the grid. Results reveal critical challenges: inadequate PFR reserves, reliance on under-frequency load shedding, and a lack of automatic secondary frequency control via automatic generation control (AGC). The study recommends (1) enforcing mandatory PFR compliance and (2) establishing an ancillary services market to incentivize reserve provision. The third study uses PSS/E dynamic simulations to assess primary frequency response provision using different mixes of BESS and conventional generation in responding to the maximum N-1 contingency (400MW loss). Simulation results suggest that BESS -only PFR provision outperforms conventional generation-only PFR in fast frequency response across the frequency metrics analyzed. However, a hybrid mix of BESS and conventional reserves achieves adequate performance on all metrics and is more cost effective. The research demonstrates that BESS can significantly improve frequency stability in WAPPITS, but to successfully achieve this, there is need for technical and regulatory reforms, including: • Mandatory PFR participation for conventional plants, • Ancillary services markets to mobilize reserves, and • Implementation of hybrid PFR provision by BESS and conventional power plants. This research provides policy makers and technical experts with insights to guide the implementation of frequency control service provision, underscoring the need for institutional and market reforms coupled with technological innovations to solve the existing frequency control challenges in WAPPITS.