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Socio-Ecological Risk and Protective Factors, Individual Differences, and Adolescent Outcomes: A Developmental Cascade
No full textAdolescent alcohol use remains prevalent, and internalizing symptoms and sleep deficits have worsened for adolescents in recent years. To better understand the development of these outcomes, I tested a developmental cascade model that indirectly linked key socio-ecological risk and protective factors (adverse childhood experiences [ACEs], parent socioeconomic status [SES], neighborhood deprivation, school engagement) at ages 9/10 to later adolescent alcohol use, internalizing symptoms, and poor sleep quality (ages 13/14) through key transdiagnostic individual difference factors (impulsivity and emotion dysregulation) at ages 11/12 and 12/13. This analysis was conducted using data from the Adolescent Brain and Cognitive Development (ABCD) Study, Release 5.1 (N = 4,677; 47.5% female, 55.9% Non-Hispanic White, 11.1% African American or Black, and 2.5% Asian). I evaluated the developmental cascade hypothesis for each predictor separately, first examining direct effects and then indirect effects via structural equation modeling (SEM). I also evaluated a final multivariate model with all predictors and associated direct/indirect effects. Baseline covariates (ages 9/10) in all models included sex at birth, race/ethnicity, impulsivity, alcohol use, internalizing symptoms, and poor sleep quality. Results confirmed that ACEs and school engagement significantly predicted internalizing symptoms and poor sleep quality. These associations were consistently found to be indirectly linked through impulsivity and emotion dysregulation, as hypothesized, with some evidence that emotion dysregulation was more relevant to paths involving ACEs in the final model. Contrary to expectations, there was limited support for the developmental cascade hypothesis regarding alcohol use; instead, greater wealth (higher parent SES, lower neighborhood disadvantage) was a risk factor (i.e., associated with a higher probability) of alcohol use. The effect sizes realized for each risk/protective factor were medium (Owen et al., 2021). Effect sizes for indirect paths were small. Results showed that 16.2%, 18.9%, and 31.0% of the predicted variance in alcohol use, internalizing symptoms, and poor sleep were explained by the final model. Findings emphasize the importance of preventing and reducing ACEs and promoting school engagement to mitigate impulsivity, enhance emotion dysregulation, and ultimately reduce internalizing symptoms and improve sleep at a sensitive turning point in adolescence. Further research is required to understand the predictors of early adolescent alcohol use in contemporary adolescent samples
Implementation of Asphalt Balanced Mix Design in Oklahoma: Progress, Challenges, and Future Prospects
No full textThe Oklahoma Department of Transportation (ODOT) has undertaken a comprehensive, multi-phase initiative to implement Balanced Mix Design (BMD) for asphalt pavements, aiming to improve long-term performance, sustainability, and cost-effectiveness. This dissertation documents the development, evaluation, and statewide implementation efforts of BMD in Oklahoma, highlighting the transition from traditional volumetric-based Superpave methods to performance-based specifications.
This study began with a critical assessment of ODOT’s pavement performance challenges and the limitations of existing mix design practices. A phased implementation strategy was adopted, involving pilot projects, performance testing, specification development, and stakeholder engagement. Key rutting and cracking performance tests were evaluated for their repeatability, sensitivity, and practicality. Hamburg wheel tracking test (HWTT), which ODOT has used continuously for over a decade, remained an integral part of the BMD framework, and it is intended to be used in conjunction with the ideal cracking test (IDEAL-CT), selected for further evaluation due to its operational simplicity and ease of implementation.
Over seven years, four implementation phases were completed. These included 33 pilot and implementation projects across the state with diverse traffic and environmental conditions. Asphalt mixtures were tested under design and production, according to different aging protocols, followed by statistical analyses to evaluate their consistency during both phases and variability within and between laboratories.
The dissertation also details the iterative process of developing ODOT’s BMD specifications, including adjustments to reclaimed asphalt pavement (RAP) allowances, short-term aging protocols, and pay factor functions. A public-private partnership model was introduced to address workforce limitations, expand testing capacity, and support field implementation. It also assisted with integrating IDEAL-CT into ODOT’s certification program and deploying field testing infrastructure and statewide training.
Additionally, multi-phase benchmarking studies established separate CT-Index thresholds for surface and intermediate mixtures, while round-robin testing across 27 laboratories revealed significant inter-laboratory variability, highlighting the need for standardized specimen preparation and adequate technician training. Furthermore, a long-term monitoring strategy has been integrated into ODOT’s pavement management system (PMS), with ongoing data collection on cracking, rutting, and surface condition metrics. Additionally, ODOT continues to sponsor accelerated testing at the NCAT Test Track to validate the field performance of BMD mixtures under controlled conditions.
Key conclusions include the selection of IDEAL-CT for statewide use, the importance of determining adequate design aging and production reheating protocols for consistent IDEAL-CT results, and the demonstrated success of collaborative implementation strategies involving both public and private stakeholders. Recommendations for future work include refining CT-Index thresholds based on field performance, developing a framework for RAP management and rejuvenator use, expanding field testing infrastructure, and evaluating the feasibility of performance-based specifications such as percent-within-limits (PWL) pay factors.
This work provides a replicable model for transportation agencies seeking to modernize asphalt mix design through performance-based specifications, collaborative implementation strategies, and data-driven decision-making
Evaluation of the Effects of Grass-Legume Mixtures on Beef Cattle in the Deep South
Get PDFForage systems in the Deep South, USA, present seasonal limitations that reduce cattle productivity, particularly due to suboptimal summer forage quality and the prevalence of toxic tall fescue (Schedonorus arundinaceus). This dissertation evaluated the integration of leguminous species — alfalfa (Medicago sativa L.) and red clover (Trifolium pratense) — into perennial grass systems to enhance nutritive value, reduce fescue toxicosis, and improve beef cattle performance under regional production constraints.
Three studies were conducted to address complementary objectives. First, a digestibility trial using four ruminally fistulated steers assessed microbial responses and nutrient digestibility of conserved forages — bermudagrass (Cynodon dactylon) hay, alfalfa baleage, and alfalfa-bermudagrass baleage — in a completely randomized design. Second, a metabolism trial utilizing a Latin square design examined the effects of increasing red clover hay inclusion (0%, 10%, 20%, and 30%) in ‘KY31’ tall fescue diets on digestive kinetics and fescue toxicosis indicators. Third, a grazing study, utilizing a completely randomized block design on tall fescue pastures, each grazed by stocker steers (267 ± 35.8 kg body weight (BW)), evaluated red clover interseeding and supplementation with a 50:50 soybean hull/corn gluten feed blend at 0.5% and 1.0% of body weight as strategies to maintain growth and mitigate fescue toxicosis.
Inclusion of alfalfa in conserved forages significantly increased crude protein (CP) concentration (P < 0.01) and dry matter digestibility (DMD; P < 0.01), with corresponding shifts in microbial communities (P < 0.01). Increasing red clover inclusion in tall fescue diets reduced rumen temperature (P < 0.01), suggesting attenuation of vasoconstriction associated with fescue toxicosis. Clover inclusion also elevated DMD (P < 0.04) and CP concentration (P < 0.01). The grazing trial demonstrated that red clover inclusion improved average daily gain (ADG) relative to non-supplemented controls and was comparable to the 0.5% supplementation group (P < 0.05); gain per hectare followed a similar pattern (P = 0.03).
Collectively, these findings highlight the potential benefits of incorporating legumes into forage systems in the southeastern United States. Alfalfa significantly enhanced the nutritional value of conserved forages. At the same time, red clover improved digestibility and reduced the effects of fescue toxicosis. Interseeding legumes into perennial grass pastures offered a low-input, sustainable alternative to feed-based supplementation. These results support the broader adoption of legume-inclusive systems to optimize forage quality and cattle performance across the region
College Students' Food Insecurity: A Growing Public Health Concern
No full textFood insecurity, defined as limited or uncertain access to adequate food due to financial constraints, remains a pressing issue in the United States, affecting 13.5% of households in 2023. Among college students, the prevalence is even higher, with approximately one in three experiencing food insecurity. This issue negatively impacts students’ physical and mental health, academic performance, and retention. Despite growing awareness, there is no validated tool specifically designed to assess food and nutrition security in college populations. Nutrition security, which emphasizes consistent access to nutritious, safe, and affordable food that supports health and well-being, is also under-assessed in this demographic.
This dissertation aimed to address this gap by developing and validating a survey instrument tailored to college students. The study (1) reviewed existing tools used to measure food insecurity among college students, (2) evaluated the applicability of the USDA 10-item Food Security Survey Module (FSSM) through cognitive interviews, (3) developed a new College Student Food and Nutrition Security Survey Module (CS-FNSSM), and (4) assessed its psychometric properties.
A systematic review revealed that most studies relied on the USDA-FSSM, which lacks validation for college populations and often yields inconsistent prevalence rates due to varied methodologies. Cognitive interviews with students highlighted misinterpretations of key terms and difficulty recalling food experiences over a 12-month period, underscoring the need for a more appropriate tool.
Using a mixed-methods approach, including expert panel input, surveys, and cognitive interviews, the CS-FNSSM was developed to reflect the lived experiences of college students. Rasch analysis demonstrated strong item performance and structural validity. The CS-FNSSM showed good internal consistency (Cronbach’s alpha = 0.79), moderate test-retest reliability (r = 0.59), and high sensitivity (89%) and specificity (76%). Qualitative findings confirmed the tool’s clarity and relevance.
The CS-FNSSM offers a validated, student-centered approach to measuring both food and nutrition security, providing a critical resource for researchers, campus administrators, and policymakers to design effective interventions and support student well-being
The Improvement of Intramolecular Symmetry-Adapted Perturbation Theory
No full textSymmetry-adapted perturbation theory (SAPT) is a popular and versatile tool to compute and decompose noncovalent interaction energies between molecules. The intramolecular SAPT (ISAPT) variant provides a similar energy decomposition between two nonbonded fragments of the same molecule, covalently connected by a third fragment. The presence of artificial dipole moments at the interfragment boundary, as the atoms of A and B directly connected to C are missing electrons on one of their hybrid orbitals, displays several issues for many fragmentation patterns (that is, specific assignments of atoms to the A/B/C subsystems), including an artificially repulsive electrostatic energy (even when the fragments are hydrogen-bonded) and very large and mutually cancelling induction and exchange-induction terms. The improved ISAPT(SIAO1) approach reassigns one electron on a singly occupied link hybrid orbital from C to each of A/B, providing reasonable values of all ISAPT corrections for all fragmentation patterns, and a fast and systematic basis set convergence. An alternative approach to study the SAPT/ISAPT interaction energy is established by singling out the noncovalent interaction using the long-ranged part of the Coulomb potential based on the Gaussian or error-function range separation. The long-ranged Coulomb potential is evaluated with either the entire intermolecular/interfragment interaction or only its attractive terms. The energy corrections from range-separated SAPT/ISAPT are in reasonable agreement with complete SAPT/ISAPT data. The best consistency is attained for the error-function separation applied to all interaction terms, both attractive and repulsive. The range separation appears to be a potentially promising technique towards a fragmentation-free decomposition of intramolecular nonbonded energy
Impacts of Urban Agglomerations on Weather Dynamics: A Multifaceted Initiative for Better Understanding, Global Urban Monitoring, and Improved Urban-Rainfall Forecasting
No full textUrban areas are expanding rapidly and becoming increasingly connected, which has serious effects on the environment around them. The first objective of this dissertation evaluates this interaction by looking at how these connected urban clusters affect air quality at both local and regional levels. It shows that traditional studies, which often focus on cities as separate units, tend to miss the combined impacts of these larger urban networks. The investigation further pointed to a notable gap in the availability of continuous, long-term, high-resolution, and globally consistent datasets capable of capturing changes in urban areas over time, especially in rapidly developing regions of low- and middle-income countries. This kind of data is particularly important for understanding how cities grow and affect their surrounding weather and climate systems. To fill this gap, the second objective develops a new dataset called the Normalized Difference Urban Index Plus (NDUI+). This dataset uses satellite images and advanced deep learning techniques to produce yearly maps of global urban areas at a high resolution (30 meters) from 1999 to the present. NDUI+ combines data from several satellite sensors (such as VIIRS, DMSP-OLS, and Landsat) and corrects for differences caused by changes in sensors over time, creating a consistent and reliable product. It is well known that cities can affect local weather patterns, but weather prediction models often struggle to simulate these effects accurately. One major reason is the lack of up-to-date, detailed urban data. The third objective of this study tries to solve this issue by using NDUI+ data in the Weather Research and Forecasting (WRF) model to see if it can improve rainfall prediction over cities. Three urban fraction configurations (NLCD 2011 (default to WRF), NLCD-2020, and NDUI+ 2020) were tested over the city of Chicago to simulate a deadly Derecho event from the year 2020. Results showed that improved and updated urban representation from NDUI+ data yields more accurate rainfall forecasts. Overall, NDUI+ urban fraction-based total rainfall forecast achieved a 40.4% improvement in rainfall forecast accuracy compared to the default NLCD 2011 urban fraction case, and 21.6 % better accuracy than NLCD 2020 urban fraction configuration over the city
Moving from Disconnection to Connection: Understanding the experiences of South Asian International Students in the United States using a Relational Cultural Framework
Get PDFSouth Asian international students represent a growing yet understudied demographic in
U.S. higher education. While these students are often academically successful, they face unique
psychosocial challenges, including acculturative stress, cultural dissonance, and systemic
marginalization that can adversely affect their mental health and well-being. Drawing on
Relational Cultural Theory (RCT), this dissertation explores how the quality of relational
connections with peers, mentors, and community members (i.e., relational health) influences
psychological distress and life satisfaction among South Asian international students. The
dissertation consists of two manuscripts: a conceptual paper that situates RCT as a culturally
congruent and socially just framework for understanding international students' well-being, and
an empirical study that investigates relational health as a moderating variable in the relationship
between acculturative stress and psychological health outcomes. Using survey data from 210
South Asian international students in the U.S., the study found that higher levels of peer and
community relational health significantly buffered the negative effects of acculturative stress on
psychological distress and enhanced life satisfaction. These findings underscore the importance
of not only social support quantity but also the quality of relational connections in fostering
resilience and well-being. The study advances a culturally responsive framework that can inform
counseling psychology practices and institutional policies aimed at supporting international
student success and mental health
Essays on CEO Compensation and Information Asymmetry in Equity Markets
Get PDFIn the first study, the scholarly literature finds that informed traders prefer to transact in the options market, presumably because of the increased leverage found in that market. We define a new
measure of asset interest that combines the monetary size of changes in option open interest or
volume with the probability of options expiring out-of-the-money (OTM). We sort portfolios into
deciles based on the asset's call option interest measure divided by the aggregate call and put
measure. The information measure has predictive value. Long-short zero-cost portfolios have raw
returns exceeding 100 percent and excess returns both relative to reference portfolios and Fama-
French factors. Most of the return is due to the short side of the positions.
In the second essay, this paper elucidates the opposite views in risk management from bondholders
and shareholders after a negative shock. I use the 8-hour Ozone standard under the U.S. Clean Air
Act as an exogenous identification to show that bondholders seek to control the risk by requiring
higher cash balances, while shareholders grant more risk-taking incentives to CEOs when the firms
are treated to more stringent regulations. The effects on cash balance are stronger, while the effects
on risk-taking incentives become weaker in the firms with higher leverage. Overall, a negative
shock will elevate the risk-control demands from bondholders, while increasing risk-taking
Incentives to counter the risk aversion of CEOs.
In the last essay, we investigated the effect of the Russian invasion of Ukraine on Black Sea Wheat
futures. We find that the Black Sea Wheat futures are cointegrated with the Kansas City Wheat
futures, the global standard for wheat prices. However, the relationship between these two series
significantly changes as a reaction to the main geopolitical events in the region. We also document
a significant drop in open interest after the invasion. Our results are relevant to many market
participants, such as Ukrainian farmers and consumers in developing countries, including the
World Food Program, which buys about forty percent of its wheat supplies from Ukraine
Exploring Epigenomic Variation, Evolution, and the Implications for Long-term Population Viability
No full textThis dissertation used genomics, epigenomics, and computational biology to explore the inheritance, temporal stability, and functional relevance of epigenetic marks in shaping genetic diversity and population persistence. I began with a quantitative summary and examination of existing literature and identified key questions in ecological epigenetics and conservation biology, with an emphasis on wild systems. This review motivated an empirical investigation of the epigenome in a wild mammal population to inform our understanding of epigenome variation in natural systems. My second chapter examined multigenerational patterns of DNA methylation in a population of banner-tailed kangaroo rats (Dipodomys spectabilis) in southwest Arizona, revealing partial but detectable epigenetic inheritance that declined with generational distance. Building on these findings, my third chapter evaluated environmentally induced methylation patterns in the same population and found consistent epigenomic responses to local environmental variation, suggesting potential mechanisms for plasticity-mediated adaptation. These empirical results highlight the need for broader taxonomic application of epigenome investigations as well as theoretical refinement of epigenome change expectations for wild systems. My fourth and fifth chapters addressed this need by developing a suite of theoretical and simulation-based models to extend insights beyond the constraints of field data. In chapter four, I modeled how the interaction of migration and population size influenced long-term viability in high‑extinction‑risk species with limited connectivity, and found that even minimal migration (e.g., one migrant per generation) significantly countered post‑crash declines by maintaining heterozygosity and altering population trajectories toward those of the migrant source—effects that were most pronounced in critically endangered scenarios. My fifth chapter considered how migration might influence epigenomes. I developed a set of recursive equations and agent-based simulations to evaluate how migration and the mode of epigenetic transmission (heritable vs. plastic) influenced population divergence, showing that both processes could generate elevated epigenetic differentiation under distinct evolutionary scenarios. Together, these models emphasized the importance of accounting for both genomic and epigenomic dynamics in conservation planning. Finally, in my sixth chapter, I considered the overall conclusions across studies, synthesizing insights from empirical and theoretical approaches to highlight how integrating epigenomic and genomic perspectives can improve predictions of population resilience and inform more effective conservation strategies. By incorporating epigenomic processes alongside traditional genetic measures, my work considers how we can predict population resilience and enhance the effectiveness of conservation strategies in a rapidly changing world
Design and Performance Analysis of a Multi-Antenna Frequency-Locked GPS Attitude Determination Algorithm
Get PDFAs autonomous research advances, the necessity for a functioning GPS receiver that can provide a full pose solution is insurmountable. This thesis proposes a novel coupling of phased array information into the tracking and navigation software of a GPS software-defined receiver. Specifically, the receiver is designed to track the spatial phase of the antenna array with the added restriction that it must also be able to estimate this spatial phase with only a frequency lock of the signal (i.e. a phase lock is not required). It is designed based on the advancements in GPS tracking architectures, namely vector processing, and the subsequent under utilization of all the information a phased array can offer. The proposed coupling of a phased array into the GPS architecture allows for both beamforming as well as attitude determination. This greatly enhances the robustness of a GPS receiver and allows for accurate attitude estimates even at low GPS signal powers. The algorithm was evaluated using both correlator simulations in addition to signal simulations generated using the Skydel GNSS simulator. Monte Carlo simulations were performed, proving the efficacy and robustness of the proposed attitude estimation algorithm. Live-sky GPS data was also used to indicate the real-world capabilities of the system