Our project will focus on the evaluation of how the introduction of invasive fire ant species has affected horned lizard populations. The fire ant species is not native to the greater Texas area and, when introduced, preyed on the Texas horned lizard’s primary food source, the harvester ant. This has greatly reduced the lizard’s range, as it consumes few other insects. Its status as the university mascot further highlights its vulnerability to the TCU community. This study examines the impact of invasive fire ants on horned lizard populations in Texas. We will accomplish this through two approaches in the ArcGIS environment: first, by comparing maps of the lizard’s historical and current ranges, and second, by analyzing the temporal distribution of fire ant populations to determine whether a correlation exists with changes in the lizard’s range.

The Fort Worth metropolitan area faces increasing roadway congestion, automobile dependency, and growing accessibility challenges for households with limited vehicle and physical access. Although Tarrant County contains several rail assets, much of the regions' transit network remains limited in coverage and connectivity compared to neighboring systems in Dallas. Rather than proposing new infrastructure, this study aims to evaluate the existing rail corridors within Tarrant County to identify where improvements could generate the greatest mobility, equity, and connectivity benefits.

Using ArcGIS Pro, a weighted multi-criteria analysis is applied to three existing corridors where freight lines are already present: a south-to-north line dubbed the “Green Line”, with termini in Burleson and Keller, a west-to-east line dubbed the “Blue Line”, with termini in Benbrook and Arlington, and a southwest-to-northeast line dubbed the “Purple Line”, with termini in Crowley and Euless/Grapevine. Each corridor meets at Fort Worth T&P / Central stations and stops in significant population/economic centers. Buffers surrounding each corridor are analyzed to evaluate demographic demand, transportation efficiency, connectivity, and physical feasibility. Key variables include the percentage of households without vehicles, median income, senior and disability populations, highway congestion proximity, risk factors, and major destinations served.

By integrating demographic vulnerability indicators with transportation demand and physical constraints, this study identifies which existing retail corridors demonstrate greatest need and potential for targeted improvements. The results provide a GIS-based framework for prioritizing transit investments in automobile-dependent metropolitan regions and offer data-driven guidance for improving rail accessibility and connectivity across Tarrant County.

This project will study how rare earth elements (REEs) and other important critical materials can be released (leached) from coal and coal ash. Coal ash is produced in large amounts across the United States, and many studies show that it can contain valuable elements that are needed for electronics, renewable energy technology, and national defense. However, we still do not fully understand how easily these elements can be removed from the ash or what chemical conditions make them more or less available. Learning this will help determine whether coal ash can be used as a practical source of critical materials and how it should be safely managed.

We are looking to map sea-level rise along the California coast from 2000 to 2026. The sea level is currently rising approximately .25 inches per year. We are going to focus on how this is affecting California, and we are going to pair this information with properties in California that will be underwater by 2050. It is estimated that 10 billion dollars' worth of property will be underwater in the next 30 years. The part of California that is under the highest risk is Northern California, specifically the Bay Area. We will be mapping floodplains and low-lying areas in the Bay Area to show what areas are at the highest risk of water damage.

Landslides are among the most common and, at times, the most destructive natural hazards, posing significant risks to infrastructure, ecosystems, and human populations. Central Texas, particularly the Texas Hill Country, is recognized as a landslide-susceptible region due to its rugged topography and variable geology. This project maps landslide susceptibility across the region using spatial analysis techniques in a GIS framework. Multiple datasets were integrated, including Digital Elevation Models (DEMs) to derive slope and flow accumulation, as well as geologic formations, soils (hydrologic and erosion data), and stream networks. Each variable was reclassified according to relative landslide risk and combined using a weighted overlay analysis to generate a landslide susceptibility map identifying areas of high, moderate, and low risk. The resulting analysis provides a framework for environmental hazard assessment and can inform land-use planning and risk mitigation strategies in Central Texas.

Science for Starters is a student-led outreach initiative that provides weekly after-school STEM programming for elementary grade students at the Como Community Center in a historically underserved neighborhood. Supported by the EPIC (Experiential Projects to Impact the Community) grant, the program aims to address gaps in grade-level STEM skills and limited access to hands-on learning opportunities. TCU undergraduate volunteers lead each session, which includes relationship-building activities, a brief introduction to a STEM concept, and a hands-on, inquiry-based activity that encourages problem-solving and collaboration. Topics explored include chemistry, physics, space exploration, engineering, and the human body. Through these experiences, the program fosters curiosity in STEM while promoting mentorship, leadership development among undergraduate volunteers, and sustainable STEM enrichment within the Como community.

Unhoused individuals with diabetes frequently present to the Beautiful Feet Ministries Medical Clinic with preventable foot complications due to limited access to foot care supplies and limited education on preventive practices. This project addresses these gaps through a combined resource distribution and educational intervention model. Free foot care kits, patient-friendly educational materials, and an instructional video were developed to support preventive foot care and improve recognition of warning signs. Awareness workshops further expand outreach and encourage clinic-based foot screenings. By integrating accessible resources with targeted education, this initiative aims to empower unhoused individuals with diabetes to take a proactive role in their foot health and reduce avoidable complications.

Quantifying the Reach of Social Determinant–Focused Supplemental Benefits in Medicare Advantage: A Health Informatics Approach
Medicare Advantage (MA) plans now offer supplemental benefits that go beyond traditional medical coverage. These include things like transportation to appointments, meal delivery, housing support, utility assistance, and pest control, all of which target the social determinants of health (SDOH) that affect patient outcomes well before a doctor visit ever happens. Federal policy, particularly through the expansion of Special Supplemental Benefits for the Chronically Ill (SSBCI), has given plans more flexibility to offer these services. But offering a benefit and actually getting it to the people who need it are two different things. I wanted to find out how many plans are really providing these benefits, and how many beneficiaries are actually enrolled in them.
Using SAS, I combined multiple CMS administrative datasets, including Plan Benefit Package (PBP) data and MA Enrollment by Plan files from the Centers for Medicare & Medicaid Services, into one analytic dataset. I linked plan-level benefit indicators to enrollment counts so I could estimate both the proportion of MA plans offering specific SDOH-related benefits and the percentage of beneficiaries enrolled in those plans.
What I found early on is a clear gap. Plans may list SDOH benefits on paper, but enrollment in those plans varies sharply depending on the benefit type. That disconnect between what is offered and who it actually reaches matters, because it tells us that expanding policy alone does not guarantee equity. This project shows that publicly available CMS data, when properly organized and integrated through health informatics methods, can expose these gaps and move the conversation from policy language toward something measurable.

Background: It is estimated that close to 50% of Americans experience stress daily. Research has documented that Latinos report higher levels of stress than other ethnicities. Stress is a normal occurrence and defined as the body and brain's natural, automatic response to any demand, challenge, or perceived threat. There are many factors that can impact stress, including sleep, diet, and exercise which are modifiable risk factors. These factors may affect ethnic groups in different ways. Purpose: The purpose of this integrative literature review is to explore the impact of exercise, diet, and sleep on the stress levels or perceptions of stress in the Hispanic and Non-Hispanic population. Methods: Databases used for this review included: CINAHL, EMBASE, PsycInfo, PubMed, Web of Science, and Scopus. The inclusion criteria were randomized control trials, mixed-method studies, quantitative and qualitative studies, systematic reviews, individuals age 18 or greater, Hispanic and Non-Hispanic populations. The articles reviewed included the years 2006-2026 utilizing the PRISMA extraction system. Conclusion: The findings should help researchers identify strategies to mitigate negative responses to these factors. Based on the increasing Hispanic demographic in the US, future research should address the inclusion of this population to address health disparities and gaps and enhance culturally competent interventions

Key words: exercise, diet, sleep, stress, Hispanic, Non-Hispanic, perceptions, diet quality

Physicians face increasing difficulty accessing relevant clinical evidence due to time constraints and the fragmentation of biomedical literature across multiple databases. Existing search platforms often require separate queries and may prioritize a single source, limiting the breadth and efficiency of evidence retrieval. This project aimed to develop and evaluate an artificial intelligence (AI)-based system designed to aggregate and prioritize clinical information from multiple open-access medical databases.
A multi-source retrieval tool was developed that integrates results from PubMed, Semantic Scholar, Directory of Open Access Journals (DOAJ), CORE, the World Health Organization (WHO), the Centers for Disease Control and Prevention (CDC), PLOS, and the National Network of Libraries of Medicine (NNLM). The system uses AI-assisted query processing and a source-weighting strategy to prioritize databases based on relevance to the query topic. Design decisions emphasized accessibility, ethical use of open-access content, and integration with clinical workflows.
Preliminary testing using representative clinical queries demonstrated the system’s ability to retrieve evidence from multiple complementary sources, increasing evidence diversity compared to single-database searches. Informal physician feedback highlighted the potential value of integrated retrieval for improving search efficiency and supporting evidence-based decision-making.
This work represents an early-stage clinical informatics approach to addressing information overload in healthcare. Future work will include structured usability testing with physicians, refinement of source prioritization algorithms, and evaluation of time savings and clinical relevance. AI-driven evidence aggregation tools may support more efficient clinical decision-making and improve access to high-quality medical information.