Science Symposium Program.26

FEATURING WORK FROM 87 STUDENTS (18 HONORS THESIS RESEARCHERS, 26 HONORS ADVANCED RESEARCHERS, AND 43 RESEARCH I STUDENTS), PRESENTING PROJECTS IN THE FIELDS OF ENGINEERING, ENVIRONMENTAL, SUSTAINABILITY, AND BIOMEDICAL SCIENCES.

WEDNESDAY, APRIL 29 from 5:00 -7:00 P.M. WEEKS SCIENCE BUILDING

Training students to think like scientists is the mission of Baylor Research.

We understand that science is not about content or a body of facts that explain the natural world, but instead is a process that we use to generate and confirm new knowledge.

MOLECULAR BIOLOGY AND DEVELOPMENTAL GENETICS LAB: Students are trained to ask basic questions about how life is regulated on genetic and epigenetic levels. Students are trained in the use of model and non-model genetic organisms to ask relevant questions affecting human health and disease. The laboratory is equipped for students to explore how life functions at a molecular level. Students can visualize subcellular structures on a fluorescence compound microscope, culture cells, tissues, and organisms in temperature-controlled incubators, and perform quantitative measurements on DNA, RNA, and protein in biological samples. Students are also trained to collect, analyze, and present quantitative data using data science, computational biology, bioinformatic, and data visualization techniques on very large genomic data sets generated using next-generation sequencing techniques.

ENGINEERING RESEARCH LAB: Students become well-versed in various engineering-related topics such as electronics, mechanical systems, and modeling/computational studies. With precision electronics equipment, students can further their understanding of embedded systems and how they can be used to control mechanical systems (mechatronics). In the Fabrication Lab space, custom 3D designs/prototypes can be realized with fabrication tools such as 3D printers, a CNC router, or a laser cutter.

The lab also includes high performance computing systems for virtual reality/modeling capabilities.

ENVIRONMENTAL LAB: Students asks questions concerning the ecological and evolutionary processes shaping the interactions between organisms and their environments. This can be as fine as how symbiosis is mediated between hosts and microbes, or as broad as the effects of anthropogenic activities on our planet. Students in Environmental Research utilize an array of techniques in Molecular Biology, Data Science, GIS, and laboratory experiments to understand the intricate linkage of Biological systems for the sake of conserving our ecosystems.

SUSTAINABILITY RESEARCH LAB: Students learn about a range of sustainability issues, focusing upon sustainable agriculture and applied mechanics. Students are encouraged to develop and test solutions to these challenges in the areas of solar energy, biodiversity, soil management, plant health, and equipment design and modification. Students have access to an organic garden, metal fabrication equipment, electronics equipment, and advanced software. With a mix of field measurement, laboratory experiments, and computer simulations, students are trained to collect, analyze, and present findings.

WELCOME! We would like to welcome families and friends to the Tenth Anniversary of the annual Baylor Science and Engineering Symposium.This event is a culmination of the work produced by students engaged in Baylor Science Research. Students have been working for up to three years in the following fields: Biomedical, Engineering, Environmental, and Sustainability. Over 80 research projects and posters are on display. This work represents countless hours of dedication by students and their advisors, and we are extremely proud of their accomplishments.

MEET THE BAYLOR RESEARCH TEAM Dr. R. Antonio Herrera, Biomedical raherrera@baylorschool.org Dr. Louie Elliott, Engineering lelliott@baylorschool.org Dr. Robin Fazio, Sustainability rfazio@baylorschool.org Dr. Ben Holt, Environmental bholt@baylorschool.org

BIOMEDICAL: HONORS THESIS RESEARCH DANIEL BRUCE MAPPING DNA ACCESSIBILITY DURING C. ELEGANS DEVELOPMENT USING SODIUM BISULFITE SEQUENCING Gene expression during development is regulated by changes in chromatin accessibility. This study investigates whether accessibility at the heterochronic gene lin-28 changes across developmental stages in C. elegans. Because lin-28 is highly expressed in early larval stages and downregulated later, it provides a model for studying stage-specific gene regulation. We test whether sodium bisulfite sequencing can detect structural DNA changes associated with accessibility at this locus.

AMELIE JOHNSON UNDERSTANDING THE EVOLUTIONARILY CONSERVED ROLE OF JNK USING CIONA GENOME EDITING During cancer and tumor formation, terminally developed and non-mitotic epithelial cells may detach, change morphology, and begin to divide rapidly- a process known as the epithelial to-mesenchymal transition (EMT). While this transition is a crucial component of developmental timing and cell differentiation, it is also a key mediator in both tumorigenesis and the prevention of the disease. Several molecular pathways are known to regulate EMT, such as the MAP-Kinase signaling cascade, in which the kinase JNK plays a critical role. JNK is the terminal kinase for the transcription co-factor c-JUN and has been linked to EMT, cancer-drug resistance, and other cancer-related issues within humans. While this pathway shows strong promise as a target to investigate these processes, most JNK research focuses on other diseases, namely, neurodegenerative diseases. To investigate the role of JNK signaling in development and, by extension, tumorigenesis, this project will study nervous system development in the organism C. intestinalis. In this study, the goal is to remove JNK function using genome editing, more commonly known as the CRISPR/Cas-9 system. It has been found that JNK expression is elevated in neural progenitor cells, and it is expected that by deleting and mutating JNK, the nervous system will not grow properly. By investigating the role of JNK and the MAPK pathway in the development and processes of C. intestinalis, it is hoped that a better understanding of their role in EMT will be obtained.

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BIOMEDICAL: HONORS ADVANCED RESEARCH BEN BOEHM TESTING CHEMOTAXIS IN C. ELEGANS WITH GENES DAF-6 AND TAX-6 How animals navigate and interact with their environments is a key part of learning animal science. Animals do this by using their senses such as smell. The process of an animal using their olfactory senses is called chemotaxis. All animals use chemotaxis, using pleasant senses to move towards a stimulus and negative senses to move away from that stimulus. The process is done through the nervous system which first picks up a signal with sensory neurons, sends the signal to the brain for processing, and then to a muscle to initiate a coordinated movement. To test chemotaxis, I have been using C. elegans to investigate how genes daf-6 and tax-6 play a role in the animals’ olfactory decision making. I set up choice assays with different chemicals on each half and record which chemical the worms migrate to. I test this in the N2 wild-type worms with a normal genome and compare the results to the worms with mutated genes. Using the results I can know that the gene is what causes the worms to make different decisions.

The nervous system is incredibly complex and by investigating how it functions in relation with genes helps us to get a better understanding of the overall area.

ANANYA CHAKRABORTY CHARACTERIZING THE EFFECTS OF POLYQ35 AGGREGATION ON MUSCLE MOBILITY IN A HUNTINGTON’S DISEASE MIR-1 MUTANT NEMATODE MODEL Neurodegenerative diseases are characterized by the breakdown of the nervous system and the gradual degradation of neurons. Huntington’s disease (HD) is the most common monogenic neurodegenerative disease globally, with symptoms including movement disorders, muscular atrophy, dementia, and mood disorders. HD is hereditary, caused by a single mutation in the Huntington gene (HTT). This gene codes for the huntingtin protein, and the mutation leads to an abnormal expansion of the CAG repeat sequence in the HTT gene beyond 35-40 repeats. The resulting excess polyglutamine tracts are toxic to the nervous system, causing neuronal degradation. Currently, there is no cure for HD, but various genetic factors significantly influence the disease's progression. A genetic factor that mitigates HD's effects is the null mutation of a noncoding protein gene, mir-1. The mutation reduces the number of polyQ35 aggregates. mir-1 is a microRNA highly conserved in both humans and nematodes, playing a crucial role in the cardiovascular system of humans and the pharynx of nematodes. However, the roles of certain protein coding genes—fan-1, tcer1, rnr-2—on mir-1 and their combined effect on protein aggregation is unknown. This interplay of coding and noncoding genes can reveal BIOMEDICAL: HONORS ADVANCED RESEARCH

whether this mutation continues to protect against protein aggregates and mitigate HD's effects. Although there is no cure for HD, studying the interplay of genetic factors on protein aggregation can aid scientists in developing experimental treatments for the disease.

ADDISON CLARK HYDRATION STATE INFLUENCES DNA DAMAGE PERCENTAGES IN TARDIGRADES UNDER OXIDATIVE STRESS Tardigrades, also known as Water Bears, are classified as Extremophiles, meaning that they live on the edge of existence under extremely harsh conditions that would kill most other organisms, including humans. They are able to tolerate conditions such as, life without water (Anhydrobiosis), life without oxygen, (osmobiosis), high salt or solute concentration. They do this by protecting themselves using various strategies, one being to enter a protective state known as the tun. Tun state is triggered by extreme environmental conditions: chemical changes, extreme temperature, dehydration. Tardigrades are able to enter tun state by contracting their limbs, retracting along their medial axis, and in the process decrease their internal water stores (dehydration). Oxidative stress is an imbalance between free radicals (unstable molecules) and protective antioxidants. The stress caused by an imbalance of free radicals can lead to cell, protein, and DNA damage in the tardigrades. Measuring DNA damage percentages after oxidative stress exposure is key to understanding how well the Tardigrade tun state protects the organism from DNA damage. To do this, the Comet Assay will be crucial as it allows for a lysed tardigrade’s DNA to be stained, revealing streaks of damaged DNA. This research can provide awareness about what makes the tardigrades so resilient and the mechanisms inside them that could benefit biotechnology or biological preservation.

AJ LORSON DEVELOPMENT AND OPTIMIZATION OF A LAMP-BASED MOLECULAR DIAGNOSTIC FOR NEGLECTED TROPICAL DISEASES FOR FIELD-DEPLOYABLE TESTING Neglected tropical diseases remain a major public health challenge in many parts of the world where access to rapid and reliable molecular diagnostics is limited. Carrion’s disease, caused by the bacteria Bartonella bacilliformis, is an example of such an infection and is endemic to Andean regions of South America. The disease includes a potentially fatal acute hemolytic phase, making early detection essential for effective treatment and improved patient outcomes. However, commonly used PCR-based diagnostic methods require thermocycling equipment and laboratory infrastructure that are often unavailable in rural and resource-limited settings. Loop-mediated isothermal amplification (LAMP) offers a promising alternative by enabling rapid DNA amplification at a constant temperature with minimal equipBIOMEDICAL: HONORS ADVANCED RESEARCH

ment requirements and the potential for simple visual readout. These characteristics make LAMP particularly suitable for point-of-care diagnostic applications outside conventional laboratory environments.

This study focuses on the development and optimization of a LAMPbased assay targeting the pap31 gene of Bartonella bacilliformis as a step toward a sensitive and field-adaptable molecular diagnostic approach for neglected tropical diseases. By improving accessibility to pathogen detection, this work contributes to efforts supporting earlier diagnosis and treatment in endemic regions.

RICHARD LU & MANDY YU FREQUENCY-DOMAIN CHARACTERIZATION OF EEG SIGNALS ACROSS EYE AND MOVEMENT CONDITIONS USING THE FAST FOURIER TRANSFORM Electroencephalography (EEG) is a noninvasive technique that records electrical activity of the brain through electrodes placed on the scalp. This captures microvolt-level signals associated with different cognitive and physiological states. EEG is an accessible and widely used tool in neuroscience, and it plays an important role in brain– computer interface (BCI) systems and human–computer interaction.

A typical BCI workflow involves recording brain activity, processing signals, and translating them into outputs. In this project, we investigated whether a low-cost, single-channel EEG device could detect meaningful changes in brainwave activity under various conditions, including eyes open vs. eyes closed, blinking vs. non-blinking, body moving vs. body resting, and odor exposure under essential oils such as lavender and lemongrass. EEG signals were collected using the NeuroSky MindWave Mobile 2 headset and processed in Python using Fast Fourier Transform (FFT) to convert time-domain data into the frequency domain. In this way, we can identify characteristics and peaks across EEG frequency bands. We used the synthetic signals to validate the reliability of the analysis pipeline. Results showed increased alpha activity during eyes-closed conditions, while blinking and movement introduced low-frequency artifacts, particularly in the delta range. In addition, being exposed to different odors have observable effects on brainwave patterns compared to baseline, especially in the lower frequency range. Overall, these findings demonstrate that even with low-cost EEG systems, when combining with signal processing techniques, they can capture meaningful neural patterns, which provides a foundation for future machine learning– based classification in BCI applications.

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JAMES MCCORKLE USING COLLAGEN-19 EXPRESSION IN CAENORHABDITIS ELEGANS DEVELOPMENT TO FURTHER EXPAND THE LET-7 microRNA GENETIC INTERACTOME MicroRNAs (miRNAs), small noncoding RNA genes, play crucial roles in regulating gene expression in human development and cancer. The let-7 miRNA is involved in various cellular processes, including cell division, differentiation, and programmed cell death. let-7 acts as a tumor suppressor gene, preventing cancer cells from forming, though its precise mechanisms are not fully known. This study aims to clarify the genetic basis of let-7 function by studying adult cuticle formation and hypodermal maturation in the roundworm nematode, Caenorhabditis elegans. Larval development in worms follows a precise genetic clock requiring let-7 to synchronize terminal differentiation across tissues, such as driving expression of the adult-specific collagen col-19 in hypodermal cells after the juvenile to adult transition. To identify potential downstream targets for let-7 regulation, RNA interference (RNAi) was performed in a strain made by genetic crosses with a let-7 mutation and a pCol-19::gfp reporter, a transgene for col-19 transcriptional activation of a green fluorescent protein, to knock down candidate genetic interaction partners. Observing that pCol-19::gfp expression was lost in let-7 mutants, RNAi depletion of downstream targets was expected to restore pCol-19::gfp expression. After performing RNAi targeting known let-7 targets lin-41 and daf-12, pCol-19::gfp expression was observed, confirming the sensitivity of the pCol-19::gfp reporter in identifying potential let-7 targets. Identifying these target genes will enhance the understanding of let-7 genetic interactions and its broader roles in developmental timing, cell proliferation and differentiation.

Ultimately, this study aims to provide insights into the let-7 tumor suppressor regulatory pathways in human cancer.

KRISHNA PATEL INVESTIGATING THE ROLE OF SUL-2 ON PARKINSON’S DISEASE PATHOGENESIS USING CAENORHABDITIS ELEGANS Parkinson’s disease (PD) is the second most neurodegenerative disease, after Alzheimer’s disease. PD affects motor functions but also has non-motor symptoms. Common symptoms of PD include tremors, rigidity, and impaired balance. The exact cause of Parkinson’s is unknown; however, there are certain genetic and environment conditions that could lead to PD. Genetic factors, such as certain gene mutations, have been linked to PD through the formation of Lewy bodies, made of aggregates from the alpha-synuclein protein, which are a hallmark of PD. However, there are many unconfirmed gene mutations that could be associated with PD. One of these gene mutated is arylsulfatase A, encoded by ARSA. ARSA is a lysosomal acid hydrolase which is known for causing metachromatic leukodystrophy. It has shown some association: however, a full link has not been made BIOMEDICAL: HONORS ADVANCED RESEARCH

and there has been controversy on the effects of ARSA on PD. In this research, we plan to test the ARSA gene using the Caenorhabditis elegans and sul-2, the C. elegans ortholog gene of ARSA. We will test for the formation of aggregates in C. elegans using the RNAi knockdown of sul-2 and explore any behaviors that might correlate to PD. We have collected data on the average number of aggregates in younger and older adults, and we found that there is a greater number and size of aggregates that form in older adults. This research explores new possibilities and outcomes of the relationship between ARSA and PD. AUBREY ROBBINS EPIDEMIOLOGY, EVOLUTION, AND CULTURAL IMPACT OF BARTONELLA BACILLIFORMIS IN ANDEAN POPULATIONS Carrion’s disease, caused by Bartonella bacilliformis is a neglected tropical disease endemic to Andean regions of South America. This study integrates the anthropological, epidemiological, and genomic aspects of this disease to provide a comprehensive understanding of the pathogen across time. Archaeological evidence, including pre-Incan pottery and mummified remains, suggests the long-standing presence of the disease, particularly its chronic manifestation, Verruga peruana, within ancient Andean populations. Cultural analyses reveal how endemic communities historically viewed and treated the disease, including the use of traditional medicine and the social stigmatization of affected individuals. Epidemiological mapping highlights the geographic restriction of the disease to high-altitude valleys and examines its relationship to socioeconomic factors such as regional wealth distribution and access to healthcare. Historical records and government archives are used to construct a timeline of outbreaks, demonstrating shifts in disease prevalence and the impact of modern intervention strategies. Despite advances in antibiotic treatment, disparities in healthcare infrastructure continue to influence disease outcomes in endemic regions. At the molecular level, comparative genomic and synteny analyses are used to evaluate the conservation and evolutionary context of diagnostic targets, including pap31, across Bartonella species. Phylogenetic reconstruction further clarifies the evolutionary specialization of B. bacilliformis and its adaptation to human hosts and sand fly vectors. Together, this approach underscores the importance of integrating cultural, epidemiological, and genomic data to better understand the persistence of Carrion’s disease and to inform the development of effective diagnostic and control strategies.

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EVAN ZOU COMPUTATIONAL MODELING OF CONSTRAINED SYNAPTIC DYNAMICS IN HEBBIAN AND OJA NEURAL NETWORKS Synaptic plasticity (SP) is the ability of synapses to undergo lasting changes in strength and organization in response to neuronal activity.

This process enables nervous systems to encode information, learn, and adapt. A central theoretical framework for understanding plasticity is Hebbian learning. It is a theory that explains how synapses get stronger when neurons fire together. Experiments discoveries on spike-timing dependent plasticity offered biological support for Hebbian principles by demonstrating that the timing of neuronal spikes determines whether the synapses strengthen or weaken. In this project, we constructed a simple Hebbian model to explore how synaptic weights evolve over repeated exposure to input patterns and training. The network was first implemented using the classical Hebbian rule and was then expanded from a two-input, two-output model to a five-input, five-output model, where Oja’s rule introduced a normalization term that stabilized weight growth. Our extended implementation using Oja’s rule revealed a compensatory relationship among synaptic inputs converging onto the same neuron. As individual weights strengthened in response to correlated activity, others proportionally weakened, maintaining a normalized constraint in which the sum of squared synaptic weights converged toward one.

This competitive redistribution reflects a limited-resource principle, where a neuron cannot indefinitely amplify all incoming connections.

Such normalization is paralleled by biological homeostatic plasticity mechanisms, including synaptic scaling, which regulate overall synaptic strength to preserve stable activity levels. Identifying this stable pattern of constrained competition provides a foundation for extending the model to broader neural systems, allowing the construction of larger-scale network.

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BIOMEDICAL: RESEARCH I DYLAN ANDREWS GRAM STAIN ANALYSIS OF THE MOUTH MICROBIOME DURING PREGNANCY Periodontal disease affects the periodontium, the group of supporting structures that bind, surround, support, and stabilize teeth within the alveolar bone. The periodontium consists of the gingiva, periodontal ligament, cementum, and alveolar bone. Periodontal disease typically begins as gingivitis, a reversible inflammatory condition of the gingival tissues most often caused by bacterial plaque. If untreated, gingivitis can progress to periodontitis, a more serious bacterial infection that can lead to tooth loss due to chronic plaque accumulation. Periodontitis affects approximately 40% of pregnant women, largely due to hormonal changes during pregnancy. Increased levels of estrogen and progesterone heighten gum sensitivity and make gingival tissues more susceptible to inflammation. When plaque buildup becomes excessive, harmful bacteria may enter the bloodstream and spread systemically, triggering an inflammatory response. This response increases the production of prostaglandins, which play a key role in initiating labor by stimulating uterine contractions. Elevated prostaglandin levels can result in premature labor and adverse pregnancy outcomes, including low birth weight, miscarriage, perinatal mortality, long-term disabilities, and preeclampsia. Although research has identified associations between periodontal disease and adverse pregnancy outcomes, further investigation is needed. Specifically, studying whether routine dental hygiene products such as toothpaste and mouthwash can reduce bacterial load during pregnancy may help determine whether improving oral hygiene can lower these risks.

MAKENZIE DINSMORE INVESTIGATING HOW PROTEIN AGGREGATES AFFECT NEURONAL AND MUSCULAR BEHAVIORS IN ALZHEIMER'S DISEASE IN CAENORHABDITIS ELEGANS Protein misfolding and aggregation are defining features of many neurodegenerative diseases; however, the mechanisms by which these processes impair neuromuscular function remain incompletely understood. Using Caenorhabditis elegans as a model organism, this study will investigate how amyloid accumulation disrupts neuronal signaling, muscle activity, and neuromuscular junction (NMJ) integrity. The amyloid expressing CL4176 strain and the non amyloid CL802 control strain are used to assess behavioral phenotypes and synaptic function associated with protein aggregation. This study aims to characterize how misfolded protein accumulation alters communication between neurons and muscle cells, determine how NMJ dysfunction impacts muscle contraction, and evaluate the molecular

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mechanisms required to maintain synaptic health. In addition, iron assays are incorporated to examine the role of metal ion homeostasis in amyloid aggregation and neuromuscular impairment. Comparative analyses of protein accumulation, locomotion patterns, and paralysis rates between strains are used to elucidate the relationship between amyloid burden, NMJ integrity, and iron regulation. Together, these findings offer insight into the cellular mechanisms underlying neuromuscular dysfunction in neurodegenerative disease models and may inform future strategies for assessing and mitigating the effects of protein aggregation on nervous system function.

LAKSHMI MISHRA & KEILANI PETTY LOOP MEDIATED ISOTHERMAL AMPLIFICATION AS AN ACCESSIBLE DIAGNOSTIC TOOL FOR WOMEN’S REPRODUCTIVE HEALTH DISEASES Cervical and female reproductive tract diseases caused by infectious agents remain significant global health challenges, particularly in low resource settings where access to advanced diagnostic technologies is limited. Early and accurate detection of pathogen genetic material is essential for effective treatment, disease management, and prevention of long term complications. Loop mediated isothermal amplification (LAMP) offers a rapid, cost effective, and accessible alternative to traditional diagnostic methods such as polymerase chain reaction (PCR), as it enables DNA amplification at a constant temperature without the need for specialized equipment. This combined study explores the use of LAMP for the detection of two clinically important pathogens affecting female reproductive health. One focus is the development of a LAMP assay targeting the HPV 18 E6 and E7 oncogenes—key drivers of uncontrolled cell proliferation—using HeLa human cervical cancer as a model system. The second focus investigates the application of LAMP for detecting Schistosoma haematobium DNA, the causative agent of female genital schistosomiasis (FGS), a neglected tropical disease that is frequently misdiagnosed due to overlapping symptoms with other reproductive conditions. Together, these projects highlight the versatility of LAMP as a diagnostic tool capable of improving early detection, reducing misdiagnosis, and expanding access to reliable testing. Implementation of LAMP based diagnostics has the potential to significantly reduce disease burden and improve health outcomes for women in underserved communities worldwide.

MATT PALIOTTA TRANSGENERATIONAL EPIGENETIC INHERITANCE OF ACOUSTIC-DRIVEN MTBI IN CAENORHABDITIS ELEGANS Traumatic brain injury (TBI) is a leading cause of long term neurological dysfunction, yet the potential transgenerational consequences of mild TBI (mTBI) remain poorly understood. Transgenerational epiBIOMEDICAL: RESEARCH I

genetic inheritance enables organisms to transmit information about environmental stressors to subsequent generations, often manifesting as altered behavioral phenotypes. This study uses the nematode Caenorhabditis elegans to investigate whether mechanical trauma can induce a heritable stress memory. To model concussive injury, a custom cavitation free, frequency based vibration chamber will be employed to deliver acoustic driven mTBI to the parental (P0) generation. It is hypothesized that injured P0 animals will exhibit behavioral impairments, including delayed chemotaxis responses and reduced motility. These deficits are further expected to persist in the unexposed F2 generation, indicating stable transgenerational inheritance through the germline. To elucidate the underlying mechanism, this study examines whether inheritance of these phenotypes depends on the hrde 1 nuclear RNA interference pathway, thereby testing whether traumatic stress can be encoded as a heritable epigenetic memory.

Because RNAi mediated regulation of stress responses is highly conserved across species, confirmation of this hypothesis would suggest that the long term effects of human mTBI may include a previously unrecognized heritable component. Such findings would expand current understanding of concussive trauma and imply that the consequences of head injury may extend beyond the directly affected individual.

MANIT PATEL USING ARTIFICIAL INTELLIGENCE TO PREDICT THE THERMAL INSULATION PERFORMANCE AND COOLING OF BIOPLASTIC AEROGELS BASED ON THEIR STRUCTURE As industries face increasing pressure to move away from petroleum based synthetics, the demand for affordable, high performance, and environmentally sustainable thermal regulators has become increasingly critical. Bioplastic aerogels represent a promising alternative; however, their widespread adoption is limited by conventional fabrication methods that are energy intensive and cost prohibitive. This study investigates Ambient Pressure Drying (APD) as a more accessible manufacturing approach while addressing the structural collapse and performance degradation typically associated with low cost production. To overcome these limitations, an artificial intelligence framework utilizing the XGBoost machine learning algorithm was employed to predict and optimize the aerogel microstructure prior to physical fabrication. The effects of varying concentrations of natural polymers and nanoparticles, including zinc oxide, on thermal conductivity and radiative cooling efficiency were examined. By replacing traditional trial and error experimentation, the AI driven approach identified optimal material compositions while minimizing repeated physical testing. Experimental results demonstrated that AI optimized aerogels achieved a thermal conductivity of 0.038 W/m·K, representing a 41% improvement in insulation performance compared to non optimized, air dried samples. Additionally, bio based cross linking agents preserved meBIOMEDICAL: RESEARCH I

chanical integrity and fire retardancy under high temperature conditions. These findings demonstrate that computational design can effectively bridge predictive modeling and fabrication, enabling cost efficient production of high quality, eco friendly aerogels with potential applications in thermal shielding and medical wound care.

TVESHA PATEL GENOME-WIDE IDENTIFICATION OF LET-7 REGULATORY NETWORKS IN CAENORHABDITIS ELEGANS USING RNA-SEQ AND RNAI SCREENING Cancer encompasses a diverse group of diseases characterized by uncontrolled cell proliferation resulting from disruptions in normal regulatory pathways. MicroRNAs (miRNAs) are small, noncoding RNA molecules that play critical roles in gene regulation and are known to function as either tumor suppressors or oncogenes. The let 7 family of miRNAs is highly conserved across species and functions as a tumor suppressor in humans. In Caenorhabditis elegans, a well established model organism, let 7 is essential for regulating developmental timing during the larval to adult transition. In this study, RNA sequencing (RNA-Seq) and RNA interference (RNAi) screening will be used to identify genes whose expression is altered in let 7 mutant C. elegans and to determine candidate genes that may be directly regulated by let 7. Quantitative PCR (qPCR) is performed to validate gene expression changes identified through RNA-Seq and RNAi analyses. Identification of let 7 target genes in C. elegans provides insight into conserved regulatory mechanisms that may be disrupted during tumorigenesis. These findings contribute to a broader understanding of miRNA mediated gene regulation in cancer and may inform future strategies for cancer prevention and therapeutic development.

SOPHIE RYMER ELUCIDATING THE MOLECULAR GENETIC ROLE OF JUN IN CIONA ROBUSTA (INTESTINALIS TYPE A) DEVELOPMENT AND APOPTOSIS The Jun gene is a member of the AP 1 family of transcription factors and has been implicated in regulating key developmental processes. Transcription factors play essential roles in development by controlling gene expression; however, the specific functions of many remain incompletely characterized. This study uses Ciona robusta, an invertebrate chordate with a fully sequenced genome, as a model organism to investigate the developmental role of Jun. Ciona is widely used to study chordate development and provides valuable insight into the evolutionary origins of vertebrate gene regulation. CRISPR based gene editing is employed to introduce targeted modifications to the Jun gene, allowing assessment of its functional role during development. Phenotypic and developmental analyses are then used to examine how alterations in Jun affect embryonic patterning and tissue differentiation. This research focuses on determining the spatial BIOMEDICAL: RESEARCH I

and temporal influence of Jun during Ciona development, apoptosis, and metamorphosis. Understanding the role of Jun in this system may provide broader insight into conserved transcriptional mechanisms regulating chordate development and evolutionary biology.

JAELYN SANDERS ASSESSING THE CHROMATIN ACCESSIBILITY LANDSCAPE OF LIN-28 DURING C. ELEGANS DEVELOPMENT Developmental timing is a critical process that ensures organisms grow in the correct order. In the microscopic worm Caenorhabditis elegans, the gene lin-28 acts switches on to off; it is active during early development to maintain a youthful state but must be turned off for the worm to mature into an adult. While scientists know how the lin28 protein is destroyed, it is still unclear how the gene itself is silenced at the DNA level. This research aims to determine if the silencing of lin-28 is caused by a physical change in the DNA structure. We are investigating whether the gene shifts from an “open” state (euchromatin), where it is accessible for use, to a “closed,” tightly packed state (heterochromatin) as the worm ages. Using a specialized technique called ATAC-seq, we will map these physical changes across different larval stages. We expect to find high DNA accessibility during early stages (L1/L2) and a significant “closing” of the gene by the later stages (L3). Because the lin-28 mechanism is highly conserved and often reawakens in human cancers, understanding how a natural off-switch works in worms could provide vital insights into potential treatments for human disease.

BECK SEANG THE EFFECTS OF HEAT SHOCK AND GLUCOSE ON LIFESPAN REGULATION IN CAENORHABDITIS ELEGANS Aging is regulated by conserved molecular pathways that respond to multiple stressors, including environmental and metabolic challenges.

The nematode Caenorhabditis elegans is a widely used model organism for studying longevity due to its short lifespan and conserved signaling pathways. This study investigates the interaction between the heat shock response and glucose induced metabolic stress in regulating lifespan. The heat shock response, mediated by the transcription factor Heat Shock Factor 1 (HSF 1), promotes protein stability and cellular protection and has been associated with lifespan extension in C. elegans. In contrast, high glucose conditions negatively affect longevity by activating the insulin/IGF 1 signaling pathway, which reduces stress resistance. Activation of daf-2 inhibits daf-16, preventing the expression of genes involved in stress resistance, protein repair, and longevity. This study examines whether induction of the heat shock response can provide sustained protection against glucose induced metabolic stress in C. elegans, or whether metabolic stress ultimately overrides the benefits of heat shock.

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GRACE TANG THE DETECTION OF VIRUSES USING RNA SEQUENCING Thousands of diseases exist worldwide, many of which have been identified and treated; however, countless others remain unknown to humanity. Viruses represent a vast and largely unexplored component of global biodiversity. Advances in genome sequencing technology have made it possible to detect and study previously unknown viruses through analysis of RNA. In this study, local millipedes are collected and homogenized, and their RNA is extracted and sequenced. Bioinformatic analysis is then used to differentiate between host RNA sequences and viral RNA signatures by identifying unique genetic frames associated with viruses. This approach allows for the discovery of novel viruses that may be present within millipede populations and provides insight into viral diversity within invertebrate hosts. Additionally, by comparing viral sequences across different millipede genomes, this research can help trace evolutionary relationships among viruses and improve understanding of how viruses adapt to new hosts over time. The goal of this research project is to expand scientific knowledge of virus identification, diversity, and evolution, contributing to broader efforts in understanding emerging diseases and viral ecology.

MARTINA XU COMPUTATIONAL MODELING OF CONSTRAINED OJA BASED SYNAPTIC PLASTICITY WITH FEEDFORWARD LEARNING AND OUTPUT COUPLING Synaptic plasticity is a fundamental biological mechanism that enables neurons to adapt and encode information through activity dependent changes in synaptic strength. Computational models such as Hebbian learning and Oja’s rule have been widely used to capture these processes by describing how synaptic weights evolve based on correlations between neural inputs and outputs while maintaining stability through normalization. These models provide an essential mathematical framework for understanding learning dynamics in neuroscience, artificial neural networks, and computational biology. Traditional Oja based feedforward models typically assume that output neurons operate independently. In contrast, this study will extend the classical Oja learning framework by incorporating output output coupling to better represent biologically realistic neural interactions. Computational simulations implemented in Python introduce a coupling matrix that enables inhibitory or excitatory interactions between output neurons, allowing neural activity to be shaped by both feedforward inputs and inter neuronal connectivity. The effects of output coupling on network behavior are analyzed with respect to convergence, competition, and feature specialization. Results demonstrate that inhibitory coupling promotes competition and differentiation of learned features, whereas excitatory coupling encourages synchronization and similarity among neural responses. By integrating biologically plausible network interactions into established synaptic learning models, this research offers deeper insight into how neural systems organize and process information across cellular and network levels. Beyond its theoretical contributions, this framework also informs the development of more accurate artificial neural networks and provides potential applications in modeling neurological disorders and adaptive learning systems.

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ENGINEERING: HONORS THESIS RESEARCH ALEX BAILEY THE DEVELOPMENT OF A SIX FINGER ROBOTIC HAND FEATURING BIDIRECTIONAL JOINTS Prosthetic technology has had a similar format ever since its creation circa 1,000 BCE, as a mummy with a toe made of wood and leather was found in Egypt. Until recently, prosthetics attachments had to be manually manipulated for use, including moving fingers with your own, pushing objects, to even lever mechanisms. Modern prosthetics often rely on brain activity to move, similar to how original body parts move. For example, when a brain sends an electrical signal to move a hand, robotic sensors pick up on this and act accordingly. Because of the lack of innovation in the field of prosthetics, the formula has been the same. I’m conducting my research on prosthetics as they are becoming topical in the scientific community. To determine the strengths and weaknesses of modern prosthetics, we bought a robotic hand. This hand allowed me to study and test the workings of general mechanisms in the field of prosthetics. The hand featured four servos facing the same direction, these four controlled the fingers, and a servo at roughly a 100º angle, which controlled the thumb.

There are custom metal pieces which ensure any one phalanx can move and fold inwards or outwards respectively, or as gauged from its command. This hand was important to my research, as seeing an example of a prosthetic hand helped me understand how they work.

Modeling this hand, I created a tinkercad circuit which proved this is a reliable model. As later step in my research, I decided to make the joint bidirectional, since my research was in efforts for more innovation to be found in the field of artificial attachments.

GRACE CHEN DESIGNING AN AI-POWERED LIP HEALTH DIAGNOSTIC SYSTEM Lip health conditions and early oral lesions are relatively common, but they are often overlooked. Traditional diagnostic methods relying on professional medical consultation often result in delayed intervention due to limited access to information and insufficient public awareness. With the widespread application of mobile imaging tools, there is an increasing demand for non-invasive, user-friendly self-assessment tools for lip health. Currently, the accuracy of international oral health diagnosis based on artificial intelligence ranges is high, but it is limited to a single disease classification, lacks models for non-professional users, and has insufficient exploration of the application of pretrained models in subtle lip-specific features - this study aims to address these key issues. This study developed a transfer learning model based on ResNet50 for multi-class classification of two lip states, with ENGINEERING: HONORS THESIS RESEARCH

a target accuracy rate exceeding 80%. Public medical datasets and anonymous lip images from Google were used; the ResNet50 model was fine-tuned by freezing the base layers and customizing the top layers. The model meets core indicators (accuracy > 80%, precision > 80%), demonstrating strong practical applicability and the ability to effectively extract lip lesion features. Transfer learning reduces the need for data and training time, and this model can serve as a reliable auxiliary tool for personal self-assessment and preliminary diagnosis in primary care, enabling early disease detection, reducing misdiagnosis in resource-poor areas, and laying the foundation for large-scale lip health epidemiological research. Its limitations include a small dataset (lacking samples of rare cases) and sensitivity to extreme lighting/cosmetics. Future research will expand the dataset to cover more situations and different populations, optimize the model to achieve lightweight mobile deployment, and integrate image segmentation and clinical data for multimodal diagnosis.

VIRGINIA FOSTER CONVOLUTIONAL NEURAL NETWORK FOR HUMAN IDENTIFICATION IN NATURAL DISASTER ZONES Natural disasters are one of the deadliest events in the world. In 2023, over 95,000 civilians died from natural disasters, with many still unidentified. There is an excess amount of carbon monoxide, polycyclic aromatic hydrocarbons, and sulfur dioxide left in the air, being partly responsible for the bad health effects firefighters get when rescuing trapped civilians during disasters. Currently, firefighters have twice the likelihood of dying from cardiovascular disease compared to an average civilian. Limiting the exposure time of the firefighters is important for lowering their chance of getting cardiovascular disease from less exposure to toxic chemicals. The average search lasts 7-14 days depending on the size and scale of the disaster before the searchers give up and cannot being immediately due to the unsafe conditions. Humans may not survive the entire search period, so there needs to be a more efficient solution to save lives and limit exposure.

Using a drone with a thermal imaging recognition system for human detection in natural disaster zones would save lives by eliminating unnecessary exposure for the rescuers, cutting down the search time, and allowing for better area coverage. This project is being completed on TensorFlow CoLab using Keras and a convolutional neural network (CNN) for human identification. I have created a functioning CNN for human detection tested on human and non-human images and a single image identification system (SIIS) using the downloaded CNN. By the end of this project, the CNN will be able to detect humans with a high enough accuracy to be used in real world disasters. Using a drone will bring down the search time needed for the first search, reducing the number of deaths from lack of time.

ENGINEERING: HONORS THESIS RESEARCH

WILLIAM HUBBARD DEVELOPING A CHINESE LANGUAGE TONE TRAINING APP UTILIZING PITCH DETECTION People learning to speak Mandarin Chinese often find mastering the pitch of their voice to be enormously challenging. Chinese is a tonal language, meaning the definition of a word is determined not only by consonants and vowels, as in non-tonal languages, but also by the pitch at which the word is said. Because of this, if a learner of Chinese makes tone mistakes while speaking, a native speaker will be unable to understand what they are saying. One of the best methods for tone practice is working with a pronunciation coach, but this is not feasible for many people because of monetary and time constraints. I seek to combat this issue by developing a Chinese language tone training app. The goal of this project is to create an application that will listen to a Chinese language learner attempting to speak a sentence or word and then give visual feedback informing the user of how to improve. To accomplish this, I am utilizing Python because it easily processes audio and is compatible with statistical libraries that will help me create understandable feedback for the user. Thus far, the program can successfully train users on (ma; first tone ma), (má; second tone ma), (ma; third tone ma), and (mà; fourth tone ma).

The overall purpose of this app is to create a more interconnected world by easing the process of learning to speak Mandarin Chinese.

RIGDON KING-ANDERSON ON THE DEVELOPMENT OF A TWO QUBIT NUCLEAR MAGNETIC RESONANCE QUANTUM COMPUTER Quantum computing is a burgeoning field in science and technology. As with any adolescent, quantum computing requires enormous expense to further its development. Thus, learning tools for quantum computing remain beyond the reach of many smaller institutions. Our goal is to build a low cost, two qubit Nuclear Magnetic Resonance (NMR) quantum computer for a tenable price. We will thoroughly document the process of building the computer from start to finish, providing comprehensive documentation on the construction and operation of a small NMR quantum computer. We aim to implement the following single qubit gates: the Hadamard gate, the CNOT gate and the X, Y and Z rotation gates. In addition, we hope to implement at least one two qubit gate. We hope that this project will enable other schools to build their own quantum devices, improving upon our methodology along the way. Eventually, this collective work can form a “quantum open-source community.” Such a community would provide resources for anyone to learn how to build a quantum computer, increasing public awareness of quantum computing.

ENGINEERING: HONORS THESIS RESEARCH

JERRY MA ACTIVE WINGLET DESIGN FOR THE BOEING 757 In the last 40 years, wingtip devices have captured the attention of many aeronautical engineers in their efforts to improve the efficiency of aircraft performance. As aircraft get larger and fly farther, wingtip device technology's effects on efficiency could be more dramatic. For example, a Boeing 747 enhanced with a blended winglet would save an estimated 23,000 pounds of fuel on flights from the U.S. West Coast to Hong Kong. The efficiency doesn’t only translate to fuel saving but also to longer range and carrying a larger payload. This project aims to develop a new vortex-reducing winglet device for fixed-wing aircraft and better understanding of how wingtip devices modify vortex structure. Using the Boeing 757 as the test case, different winglet designs will be analyzed using a low-speed wind tunnel to compare the differences in induced drag (CDi), drag (CD), and lift coefficient (CL). This will produce an optimal winglet design for the 757 and provide empirical data to support the final product. Currently, a 3D CFD ready model of the Boeing 757-200 with the active winglet attached was made; Cmesh and unstructured mesh model of NACA6409 were made in Gmsh; 3D printed model of the active winglet Validation of CFD and wind tunnel was completed with essential comparisons such as Cl vs Alpha, Cd vs Alpha, Cl/Cd vs Alpha, and Cd vs Cl. BRANDON OAKES DEVELOPMENT OF DATA COLLECTION SYSTEM FOR THE F24 ELECTRIC RACECAR Affordable data acquisition systems remain a significant challenge for student engineering teams, particularly in Formula 24 (F24) electric racing, where commercial telemetry solutions are often cost-prohibitive. This project addresses that gap by developing a low-cost, modular system capable of collecting and analyzing real-time performance data, with a primary focus on motor rotational speed (RPM).

The main objective was to design and validate a reliable RPM measurement system that can be expanded to include additional sensors.

A Raspberry Pi 5 was integrated with a Hall-effect sensor mounted to the motor assembly to detect rotational pulses. Custom Python software processes these signals by timestamping pulses, calculating RPM over fixed intervals, and applying smoothing techniques to reduce noise. A lightweight web interface enables real-time monitoring over a local Wi-Fi connection, while a custom-designed sensor housing ensures consistent alignment and measurement accuracy. Testing was conducted using a controlled bench setup with a motor test rig to simulate operating conditions. The system demonstrated stable and accurate RPM measurements, with effective noise reduction and ENGINEERING: HONORS THESIS RESEARCH

strong responsiveness to speed changes. By providing an accessible and scalable telemetry solution, this system enables data-driven optimization for student racing teams. Its implementation supports improved vehicle performance and strategy. Future work will include integrating additional sensors, such as current and voltage monitoring, and deploying the system on a dynamometer and in on-track conditions for further validation.

ELIZABETH SILVA CREATING A CONVOLUTIONAL NEURAL NETWORK TO CLASSIFY SPIRAL AND ELLIPTICAL GALAXIES Sky surveys have produced millions of images of galaxies, including the European Space Agency’s newest telescope, Euclid, which has captured over 26 million galaxies in one week in its first data release.

The substantial number of these images makes manually classifying each one nearly impossible. Machine learning, a subsection of artificial intelligence and computer science that focuses on processing data to identify and predict patterns, can provide an opportunity to create a system that can classify these galaxy images with minimal human intervention. The goal of my research project is to create a convolutional neural network (CNN) that can differentiate between spiral and elliptical galaxies accurately even when complex qualities are present in the images with an accuracy of 95% without overfitting in less than 20 epochs with over 1,000 galaxy images. I am using galaxy images from the SDSS images of selected RC3 galaxies for training and testing data for the neural network. I have also created a new dataset based on the Galaxy Zoo 2 Project, consisting of 11,653 spiral galaxy images and 686 elliptical galaxy images. TensorFlow was used through Google Research Colab to create the CNN. So far, I have created a CNN that can classify spiral and elliptical galaxies with a mean accuracy of 85% in less than 20 epochs with considerable overfitting.

I have also written code that can display the galaxy images with the results of the CNN to compare the actual and the predicted values and observe trends in the classification accuracy. My main goal is to create an efficient CNN for the Galaxy Zoo 2 dataset and to fix the issue of overfitting by adjusting the CNN layers. My research can help make galaxy classification for sky surveys more efficient and help deepen scientists’ understanding of galaxy morphology and creation.

ANNA STODDARD UTILIZING NUCLEAR MAGNETIC RESONANCE (NMR) ARCHITECTURE TO DESIGN A SMALL-SCALE QUANTUM COMPUTER Quantum computers are at the forefront of the current technological revolution. However, high-level computation remains largely inaccesENGINEERING: HONORS THESIS RESEARCH

sible due to their steep price tag, limiting progress in this emerging field. Small-scale single- to multi-qubit systems bring quantum computers out of highly controlled lab environments and into the hands of communities. We researched several quantum systems to arrive at nuclear magnetic resonance (NMR) architecture. NMR computers do not require specialized lasers, supercooling, or superconducting magnets. Instead, they use radio frequencies to encode information onto a half-spin solution, where entanglement can occur. Although they are not as scalable, NMR computers control qubits in water. We have assembled a test bed with neodymium magnets, a 3D-printed holding structure, and a 5mm NMR test tube. We calculated an approximate Larmor frequency for our system with several half-spin solutions, such as water and phosphoric acid. Currently, we are designing the radio frequency circuit and coil bobbin. In addition, we used IBM’s Qiskit software to run quantum algorithms from simple Hadamard gates to Shor’s algorithm for factoring. Future work will include measuring the emitted frequencies and developing corresponding quantum gates to encode information onto the particles.

HENRY WANG ON THE DEVELOPMENT OF ELECTROMAGNETIC SUSPENSION SYSTEMS FOR CARS Cars have become one of the most common modes of transportation in modern society. While driving, comfort is a major aspect of competition between car companies. In most cars, coils and metal fluids are used as shock absorbers to increase comfort, stability, and overall safety. In regular shock absorbers, the variable mechanical dampening changes the firmness quickly during car rides but is limited by the speed of the mechanical action inside the shock itself. The goal of this research is to find a way to instantly change the dampening without relying on mechanical parts. A benefit of this design is that the pressure can be instantly changed by a control built into the car. With adjustable pressure, the car’s comfort can be applied for many different types of roads, especially for different types of cars going through rough places. In this new design, the upper body of the car is suspended through the magnetic pressure of the Suspension System. Single magnetic coils cause a small delay when the ECU turn off the current caused by a temporary electric current called an Eddy Current. This design creates a quicker responding suspension system. A test bed with a motor will provide vibration that can simulate actual road conditions. Programming of the motor will present the number of rotations and better exemplify the vibrations. Future work includes camera detection and repetitive testing of electromagnetic coils. These improvements can make the cars better in comfort, safety, or stability.

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ENGINEERING: HONORS ADVANCED RESEARCH HARRISON HALEY DEVELOPMENT OF VOICE RECOGNITION FOR ROBOT CONTROL In the last few years there has been an increase in the amount of disaster relief robots. Most robots for disaster relief are controlled through manual control. This manual control can be less effective, and more difficult as a means to control a robot. I conducted this study to create voice commands used for a disaster relief robot. This can create the easy use of disaster relief robots by just a person’s voice, which would create a simpler way to have control. This creates convenience by only needing to speak into the computer to facilitate actions of the robot based on what the computer hears. I put together a code that uses the microphone in the computer to hear what a person says and translates it into a phrase on the computer. This phrase is read by another code to recognize certain words and conduct actions for a motor based on these words. This code can take what is said into the microphone and translate it into a phrase on the computer. Additionally, code was created to produce function of motors. Currently function with two motors and four wheels for forward, backward, and stop commands has been achieved. The future work of this product is to have a working robot that is fully controlled through voice commands. This will fix the problem of having to manually control the robot. This will create a user-friendly way for control that can happen away from the robot.

MICHAEL KINER MAPPING UNKNOWN AREAS IN DISASTER ZONES USING A LiDAR SYSTEM Disaster scenarios like an earthquake damaged building are often extremely dangerous for rescuers to enter without knowing where endangered people are. Mapping the inside of a room in a disaster scenario can map walls but also can help tell rescuers where they need to go. LiDAR, or Light Detection and Ranging, is a technology that uses pulses of light to measure distances. Using the distances that the LiDAR finds, you can then make point clouds, which are 3D points in space. Multiple-point cloud data can represent a room. Many LiDAR systems can map a wall; however, not a single method that I found was reliable, quick, and could map the inside of a room. The reason this gap in knowledge is so problematic is because without this, people in earthquake damaged buildings could go unsaved due to the risks unknown areas propose to a rescuer. The goal of this project is to develop a LiDAR system that can map a room from a drone. I ENGINEERING: HONORS ADVANCED RESEARCH

have coded and calibrated my LiDAR to show accurate distance, built a mechanism to rotate my it, made a mapping software in Python to project my points that I obtained, and projected 2D points with accuracy. Next year I plan to obtain point cloud data and build a drone carrier for my LiDAR so it can map a room from a drone. In the future, I plan to obtain a projection of my mapped room as well as map new rooms. More information on disaster scenarios could save lives by limiting misjudgment in a scenario with very little margin for error.

AVERY LEVIN USING DEEP LEARNING TO CLASSIFY HANDWRITING SAMPLES FOR SPECIFIC LEARNING DISABILITIES Specific learning disabilities, or SLDS, are neurological conditions that impact information processing in a specific area, such as written expression, reading, and math. Around 20 percent of the American adult population suffers from an SLD, and when caught early, students can receive accommodations and intervention for their SLD. However, only 5 percent of public-school students receive accommodations for an SLD, meaning that 75 percent of diagnoses are made after childhood. Barriers to diagnosis include high costs, the lack of qualified professionals, and subjective diagnostic criteria. Therefore, there is a clear need for a cheap, accessible, and objective method of diagnosis. The field of supervised machine learning, a form of artificial intelligence based off labeled training data, has shown potential with detecting dysgraphia - an SLD also known as disorder of written expression - from handwriting samples. We have written a dataset of our handwriting, demonstrating characteristics of both typical and dysgraphic handwriting. I have trained a machine learning model with this dataset using an open-source library known as TensorFlow, utilizing convolutional layers for feature extraction and feedforward layers for classification. Next, I plan to design a protocol for the use of this model as a form of surveillance testing for all kids of a specific age.

This model would expand access to dysgraphia screening to more children in need while serving as an inspiration and reference for future research into classification models for similar conditions.

OWEN MCKENNA DEVELOPMENT OF AN AUTONOMOUS ROBOT UTILIZING 2D LiDAR-BASED SLAM After disasters, environments can be unpredictable. When every second counts, first responders need as much information as possible about the environment they are about to enter. Buildings may have confusing, unfamiliar layouts, made worse by elements such as smoke. This negatively impacts response times and thus outcomes. I propose, as a solution to this issue, a near-ground, low-cost Lidar enabled robot, capable of rapidly and autonomously scanning an entire ENGINEERING: HONORS ADVANCED RESEARCH

floor of a building, while transmitting both visual and mapping data live back to a remote endpoint. Over the past year I have advanced work by previous researchers, rewriting all the software on our Lidar-enabled robot. I have developed multiple processes to process raw Lidar data, which consists of measurements relative to the robot given as polar coordinates. While algorithms to perform these tasks do exist, they require much more advanced sensors or more processing power. As this robot is designed to operate in hostile environments damage is likely, and decreasing cost is an important goal. This has necessitated the development of a custom algorithm. Currently, our algorithm does actually generate localization data, but it's prone to "desync" where the algorithm interprets movement as the discovery of a new room. Future work will focus on resolving this issue, improving reliability, and creating autonomous pathing to allow for unattended multi-room scanning.

DAVID PUCHALSKI IMPLEMENTING HAND GESTURE RECOGNITION SOFTWARE TO CONTROL DRONES AND ELECTRONIC DEVICES Drones and other electronic devices often require remote controls for operation. A benefit of a hands-free control system is that users can perform other tasks while controlling a device. This study aims to evaluate whether hands-free recognition software can be as effective as traditional remote controls. We plan to implement hand gesture recognition software to provide a hands-free method for controlling electronic devices, specifically drones. The system can distinguish four hand gestures: left thumbs up, right thumbs up, left thumbs down, and right thumbs down. To enable interaction between this software and the drone, we will use the drone’s mobile app. Since the app needs to run on a computer, I will use an Android emulator to launch the drone control application on my laptop. To translate hand gestures detected by the system into drone movements, I will use mouse automation software to simulate control presses on the app.

The ultimate goal of this project is to develop a drone that can be fully operated by just hand gestures, a camera, and a computer—from takeoff to landing. This will allow users to operate the drone while freeing another hand for other tasks, and it will test the effectiveness and practicality of hand gesture recognition-controlled systems.

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IVAN ZHENG UTILIZING OPENCV FOR BACTERIA DETECTION THROUGH COLOR CHANGE AND FLUORESCENCE LIGHTING According to the CDC, nearly 1 in 31 hospital patients develop a Healthcare-Associated Infection (HAI). One of the main causes of these infections is due to the doctor’s failure to sterilize properly: inadequate hand hygiene may put many patients at risk of multiple life-threatening diseases. Because bacteria are hardly visible to the human eye, doctors cannot tell if there are any infectious bacteria on their hands before undergoing medical procedures, even if they have washed their hands. Recent studies have tested for bacterial detection whether through AI or the use of substances that require extreme conditions, however for my study, I need to find a safe substance that can be used on hands and surfaces. In this study, I used a water sample coliform test that includes 4 - methylumbelliferyl-β-Dglucuronide (MUG), a substrate that when reacted with the enzyme E. coli produces β-Glucuronidase, which will produce fluorescence. This fluorescence can be seen under UV lights, which I would shine on the test bottles. The presence of fluorescence indicates the presence of bacteria. By attaching a portable microscope to my laptop, I can scan for this color detection by using contours and thresholds in my Python code. My findings led me to the conclusion that MUG can indeed be used for this project; however, the results were produced in around 6 hours. In the future, I hope to develop a fully functional sensor and mechanism that detects bacteria more rapidly. By having an almost instantaneous reaction, I will be able to detect bacteria on surfaces and prevent them from spreading, leading to a cleaner world.

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ENGINEERING: RESEARCH I LUKE ALLEN USING DRONE-MOUNTED LiDAR TO DETECT MISSING PERSONS IN DENSE FOLIAGE ENVIRONMENTS In the United States alone, over half a million people go missing every year and over ninety thousand of these cases remain unsolved by the end of the year. While camera drones can be used easily in open areas without any cover, missing persons who are believed to be in a region with dense foliage often necessitate a ground search that involves a group of rescuers manually walking through the area attempting to locate the missing person. This method can be extremely inefficient if the last known location of the person is not recent and can fail to locate the person within a reasonable time. Drones with sensors such as LiDAR can cover much more ground than ground searches while functioning at nighttime, and they can effectively detect missing persons on the ground through dense foliage. This research addresses the limitations of traditional search and rescue methods by developing a LiDAR equipped drone system for rapid detection of missing persons underneath dense foliage cover in a wide area or in remote environments, and it attempts to make the technology more accessible so more search and rescue operations will be able to utilize drone mounted LiDAR to expedite their operations. It also continues the research in a preliminary test of drones being used to detect humanoid forms under tree cover. This project used a 1D LiDAR sensor connected to a Raspberry PI 4 Model B in order to obtain distance measurements. Future directions include using X and Y coordinates fused with the detection values of the sensor mounted on a drone in order to create a 3D map of the ground and detect humanoid objects.

AJ BASS-MAYS ON THE DEVELOPMENT OF A PERSONALIZED AUTONOMOUS ROBOT A wide variety of individuals globally experience limitations such as mobility, injury, disability, or chronic illness. The CDC supports the fact that a high percentage of adults in the United States will experience a mobility limitation at some point in their lives. These issues also introduce the problem of putting stress and a greater workload on those who care for those individuals who have a loss of mobility. Intervention technologies reduce stress on a person's body, which could help them maintain independence before a care giver becomes necessary.

The goal is to design a hybrid controlled robotic system that is an assistive mobility device capable of autonomously following a person, ENGINEERING: RESEARCH I

carrying said person's items, and reducing the stress of an individual's body. The function of this robotic system will support people with a wide variety of issues. Currently, a small prototype of the hybrid robot has been produced which includes an Arduino Uno system capable of autonomous pathing which allows it to avoid obstacles and maintain a safe distance from whomever it is following. It uses ultrasonic sensors to detect objects and find the best path to continue to whatever its goal is. Moving forward, the goal is to integrate a larger raspberry pi and Arduino uno together to produce a hybrid system. This system will use a sensor detecting system to maintain distance and make paths, four-wheel omni directional driving mechanics, and the integration of a dept tracking camera to identify personalia. The goal is to allow this robotic system to support loads up to 50 pounds, run on smooth environments, and continue for a sustained amount of time.

DANTE BEAUMONT THRUST VECTOR CONTROL AND VERTICAL LANDING OF MODEL ROCKETS Model rocketry is an emerging field that serves as a hobby for millions of people around the world. Model rocketry, however, can be very expensive as well as very time consuming. Furthermore, every time a rocket is launched it must be retrieved by a parachute system that risks damage or even loss of the rocket which isn't efficient. This problem is also present in full scale rockets which has inspired companies like Blue Origin and more notably SpaceX to develop rockets that can land and be reused which is termed vertical landing. With the success of these major companies in full-scale rockets, there are a few pioneers in vertical landing of model rockets such as Joe Barnard from BPS.Space, but it is still a developing topic. If vertical landing of model rockets can become more accessible to all hobbyists, it will make model rocketry much more affordable, and this same technology can and is being used in full scale rockets. In this study, I am developing a thrust vector control system that will be used to gimbal the rocket motor in order to perform a vertical landing. I am using 3D printed parts for the gimbal along with an Arduino Uno for my flight computer. By the end of my research project, I hope to land a model rocket, reuse the rocket for other flights and landings, and gather informative flight data about the rocket that can be given to others who want to develop more efficient ways to launch and land their rockets.

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OWEN BIBLE DESIGN AND DEVELOPMENT OF A SMART GOLF PUTTER Technology is becoming more common in sports, especially when it comes to improving performance and consistency. In golf, putting is one of the most important parts of the game, but it is also one of the hardest skills to master. Even small errors in a putting stroke - like a slight misalignment of the club face or inconsistent tempo - can cause a player to miss short putts. Because of this, many golfers look for better ways to understand and improve their stroke. Most modern putting analysis systems rely on cameras or advanced tracking equipment to measure motion. While these systems can be very accurate, they are often expensive and not practical for everyday use. Some newer products, such as Blast Motion, use small motion sensors attached to the putter, making them more portable. However, these devices can still be costly and don’t always offer much flexibility or customization. In many cases, they also don’t provide feedback that is especially useful for the average golfer. With my research I am creating a device that is not only cheaper but easier for golfers to use, apply, and improve their own unique putting stroke. Using an IMU, Arduino Nano, battery pack and a 3D printed housing attached to the putter, kinematic data collected from the golfers' stroke is put through a software that allows the data to be usable and helpful for the golfer to improve their stroke.

The goal is to measure and analyze key parts of a golfer’s putting stroke in a way that is both simple and accessible.

BRYLEE FAULKNER USING HAPTIC FEEDBACK FOR THE VISUALLY IMPAIRED Millions of people around the world live with vision impairment, and for many of them, simple daily tasks such as navigating through streets can be difficult and even dangerous. While tools like the white cane are helpful, they mainly detect objects on the ground and do not always warn users about obstacles at the head or waist level. More advanced electronic devices do exist, but they are often expensive, complicated, or not easily accessible. Because of this, this project’s goal is to develop a simple, affordable, wearable device to improve how visually impaired individuals detect obstacles and move more safely throughout their daily lives. This device is designed to be a lightweight system using ultrasonic sensors along with vibration and audio feedback to provide real-time awareness of objects at multiple distances and heights. The mix of these components allows users to receive quick information about their surroundings in an easy way.

So far, I have created a working prototype that can detect nearby obstacles and alert the user when an object is within the range. This prototype was developed at a low cost, which helps complete the ENGINEERING: RESEARCH I

goal of affordability. My future plan is to program the device to detect objects at different distances and heights and adjust the speaker audio so that sounds become louder as objects get closer to the sensor. Overall, this project exemplifies that wearable, affordable, and assistive technology has the ability to improve the independence and safety of visually impaired individuals, but while also maintaining a solution that is more reliable to the majority.

BRITTAN HYDE DEVELOPMENT OF AN ELECTROLYSIS SYSTEM FOR GENERATING HYDROGEN FOR USE IN FUEL CELLS One of the largest issues contributing to global warming and an increase in CO2 levels in the atmosphere is personal vehicles, such as cars and boats. An average car’s engine produces around 8.8 Kg of CO2 for every gallon of gasoline burned. While a common solution to this issue is battery powered vehicles, these systems have their own drawbacks. The most promising solution, however, utilizes hydrogen as a fuel for fuel cells and internal combustion engines. However, a consistent source of fuel would be needed. Hydrolyzing water is a good way to generate hydrogen gas, and saltwater already includes a catalyst needed for hydrolysis. I plan to manufacture a hydrogen-burning internal combustion engine fed by a self-refilling hydrolysis chamber, and I plan to use it in sea-fairing vessels due to their saltwater operations. I have tested a classroom hydrolysis chamber.

This chamber is able to split water into hydrogen and oxygen. I can view the value of hydrogen produced in PPM from the chamber from a sensor. I plan to test different voltages and levels of salinity in the hydrolysis chamber to see which produces the most hydrogen, as well as manufacturing my own chamber. Eventually, I will test electric motor input and output from a fuel cell power source and test an internal combustion engine’s input volume and power output. This research helps the fight against global warming, as well as aiding in power generation at a personal level. The methods used in this project – hydrolysis chamber, fuel cell, and internal combustion engines – can be used as generators for houses or engines in cars.

ALLI MCCROSKEY IMPLEMENTATION OF FLEXIBLE PRINTED CIRCUIT BOARDS IN ROBOTIC HEART DRIVERS FOR SPACE MANAGEMENT AND EFFICIENCY The first robotic heart was created in 1982 but was very bulky and full of problems. Since then, the robotic heart is much better, but the driver is still very bulky and is not a sustainable solution to heart issues.

The current leading heart and driver system is made by the company Syncardia and is a vast improvement to the original but could still be

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improved upon. The goal of my research is to create a smaller version of the driver using flexible printed circuit boards and to increase the battery life and manageability in order to make it a feasible and widely used machine to combat heart limitations. The objective for the driver is to pull air and push it into a tube with enough pressure that the bladder lining will inflate and push liquid through in order to simulate a real heart meaning that there will need to be two pulses, enough blood pressure, and a relaxation and release of pressure. In the future I will create a system that pumps and controls liquid to simulate a real heart, using the current robotic heart, using flexible printed circuit boards and lithium-ion batteries for the purpose of creating a sustainable heart. Once this system is working it will allow everyday people to have a chance at a normal life, not wait endlessly on the organ transplant list and possibly die in wait, and allow millions of people to have a normal life with a reduced risk and more comfort every day.

ANTON PRUENSTER DEVELOPMENT OF AN INSTRUMENTED ROWING SYSTEM FOR REAL TIME PERFORMANCE ANALYSIS Rowing is a sport that requires a lot of technique, strength, and endurance. But out of those three traits, one can be seen by a coach and the other two are only shown as average numbers to a coxswain in the boat. To solve this, there are systems, such as X-boat, the Empower Oarlock, and Powerline system, which measure individual rowing pressure, not just average of the whole boat, by placing sensors on the oarlock. However, no system exists that analyzes and organizes the data given by the sensor on the oarlock. This creates inefficient and impractical uses for the data, especially for coaches mentoring young athletes. A system that properly analyzes this data could help coaches prevent injuries, create boat lineups, draw attention to improvement, and let coaches better create workouts for their rowers.

My research has mostly focused on analyzing other research papers and understanding rowing telemetry. Additionally, I have created a simple Arduino system that utilizes a 10kg Load Cell with an HX711 amplifier. This uses the deformation of the load cell with strain gauges to provide a quantifiable output, the HX711 then converts the data into numbers the Arduino can understand. This has allowed me to prepare a linear equation that calibrates the Arduino’s numbers to pounds. In the future, I will reduce the size to fit inside a modified oarlock design to measure pressure. Then I will modify the Arduino to have a Bluetooth transmitter and carry a battery pack. After that, I will start writing the code that organizes and analyzes the data. Completion of this system will benefit future rowers and help coaches by both providing and analyzing the data.

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JAXSON SIMPKINS USING POSE ESTIMATION TO CORRECT EXERCISE FORM AND AVOID INJURY In the world of sports and exercise, thousands of people get hurt each year mostly resulting from falling or contact injuries but also from improper exercise form. Improper exercise has been addressed in different ways most importantly through technological methods such as computer vision pose estimation. Computer vision is the use of AI deep learning and computer code used for tasks such as pose estimation which is the ability to track the joints and limbs of a person’s movement. My goal is to use computer vision pose estimation to track people’s form when exercising to minimize the risk of injury and improve strength. To do so, I will use a standard laptop for all of my programming. My programming will be done on PyCharm, a software for coding in python code language. I utilize a software for pose estimation called MediaPipe and will combine that with OpenCV which will allow my program to analyze image, videos, and feed from my laptop’s web camera. I have applied the MediaPipe pose estimation on an image analyzing the position of joints and limbs on the image. I also made code for PyCharm to open up my laptop web camera. I’m going to synthesize a final program from the two codes that combines the ability to analyze pose stance and live footage from web cam to track live movement. Future work will be to synthesize a code that establishes the stance for certain exercises that can be compared to whatever the stance of the user is. My research is significant because it aims to prevent injuries by giving people a personal exercise coach that can correct their form.

ANARA SUMMERS THE USE OF BIOMIMICRY IN STRUCTURAL ARCHITECTURE TO LESSEN THE OUTPUT OF CARBON EMISSIONS Almost half of the world’s carbon emissions come from the creation, usage, and destruction of buildings and other human structures. Climate studies and environmental sciences combat things like climate change and humans’ effect on the natural world through preserving habitats and trying to untangle humans from the fragile aspects of nature, but a growing sect of architecture has decided to try and fix the problem from within our society as well. Biomimicry uses natural structures and biological concepts to limit carbon emissions and energy usage. Through evolution, the natural world has already given us the most efficient and sustainable attributes it could think of, and biomimicry has already started utilizing them to achieve a negative carbon potential without giving up the luxuries of lighting and temperature control with incredible success. This project’s goal is to test

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how effective natural properties aid in lighting and temperature control through structure alone. Using test boxes, structural and property mimics of plants and animals will be organized into a test wall to view the effectivity of these properties in terms of light and temperature control through Arduino light and temperature sensors. These test walls will then be arranged to make a model house that can be tested with the same goal in different climates. This test house will be compared to a base house made of the conglomerate averages of a single-story house, and sensor readings will be used to determine how effective biomimetic structure aids in these aspects so energy usually used for them can be limited. Further work seeks to implement these structures and ideas in continued architectural projects and propagate biomimicry’s usage throughout the construction sphere.

KATHAN THOMAS 3D SCANNING USING STEREOSCOPIC CAMERAS TO AID IN DISASTER RECOVERY In the immediate aftermath of structural disasters, rapid and precise assessment of unstable environments is essential for effective search and rescue operations. However, current industrial 3D scanning solutions, such as high-powered LiDAR, are often prohibitively expensive, heavy, and power-intensive, which limits their integration into agile, disposable platforms like small unmanned aerial vehicles (UAVs).

This research addresses these limitations by proposing a low-cost, lightweight, passive stereoscopic 3D mapping system designed for micro-UAV swarms. The proposed system utilizes a StereoPi v2 and a Raspberry Pi Compute Module 4 (CM4), with a fixed 65 mm baseline. To overcome the failure rate of standard passive stereo vision in low-light or featureless environments, a low-power laser diode will be integrated to provide artificial texture and reference points. Computational tasks, including rectification and stereo matching, will be offloaded to a remote client-server architecture to minimize onboard power consumption and maintain a target payload mass of 100 g. The system will be validated in a controlled environment to compare digital volumetric models against physical measurements. It is expected to achieve a target accuracy of ±5 mm while successfully identifying semi-transparent obstacles like glass. Ultimately, this research seeks to demonstrate that budget-friendly hardware can provide high-fidelity structural assessments, potentially enabling the use of disposable, rapid response technology in hazardous debris fields.

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WILLIAM YAO USING AN AUGMENTED REALITY OVERLAY FOR THERMAL AND ELECTROMAGNETIC VISUALIZATION Many important physical phenomena, such as thermal heat and electromagnetic fields, are invisible to the human eye, but they provide crucial information for engineering, system monitoring, and hazard identification. Conventional sensing tools such as infrared thermal imagers and software-defined radios capture this data in two dimensions, forcing operators to mentally map sensor output onto complex three-dimensional environments — a process prone to human error and misinterpretation. Existing augmented reality approaches rely on handheld devices or projector-based systems that lack spatial depth or fail in dynamic environments, leaving a gap in mixed reality solutions for invisible field visualization. This study proposes and implements an augmented reality overlay system using the Meta Quest 3 to visualize thermal and electromagnetic data as three-dimensional heatmaps anchored to physical surfaces. A FLIR infrared thermal imager and HackRF One software-defined radio are planned to be mounted to the Quest 3 controllers as the live sensor input. A surface-based ray casting pipeline in Unity 6 detects intersections between a virtual ray and the Quest 3's real-time scene mesh, recording precise world-space coordinates for each sensor reading. Temperature and signal intensity values are mapped to a blue-to-red color gradient and rendered as spatially anchored markers using the Meta Mesh API and Meta Depth API for occlusion. The system produces accurate heatmap visualizations anchored to real physical surfaces in a mixed reality environment. These results suggest that consumer-grade mixed reality hardware can serve as an accessible platform for invisible field visualization, previously limited to expensive industrial systems. Current results use pre-recorded CSV data as a stand-in for live sensor input. Future work will extend this system to support real-time sensor streaming, enabling live thermal and electromagnetic visualization during active inspection tasks.

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CAROLINE YOUNG ON THE DEVELOPMENT OF AN RF MITIGATION SYSTEM A large problem in theater is a microphone being turned on or off at the right time, forcing the audience to be drawn out of their immersion in the story. This can be caused by the sound technician making a mistake or being overwhelmed by the demands of their role. A possible solution to this is the use of an automatic audio mixer, but these are not designed for theater and have a hard time with multiple microphones or real time mixing as is needed with theater settings.

I intend to test multiple methods to automatically turn off or block the radio frequencies in microphones and evaluate which is the most effective, cost efficient, and easiest to implement. I plan to build a Faraday cage to block RF from reaching the receiver when an actor is backstage and eliminate the need to even turn microphones off. I am also going to use a combination of cameras and RFID chips to track the movement of the microphones and use Arduino to automatically turn them off when they are leaving the area of the stage. The final solution that I intend to test is a proximity sensor that will turn the microphone off when it gets close. I have designed and determined the gap spacing for the Faraday cage and begun fabrication of the prototype. I have also acquired two materials to test which are more effective in blocking RF. The solution to this problem will improv the theater going experience for consumers and increase the profits of a struggling theater industry.

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ENVIRONMENTAL: HONORS THESIS RESEARCH GAVIN BOGGS IDENTIFYING SYMBIOSIS: TERRESTRIAL SALAMANDERS AND PSEUDOMONAS Symbioses are associations between unlike organisms. Such relationships are categorized most often by the consequences of their interactions – whether they are beneficial, impartial, or harmful to either organism. The definition of symbiosis is somewhat unhelpful in this capacity, as its significance is obscured by its broad and arguably arbitrary applications within ecology. Though many relationships and interactions between amphibians and microbes have been identified and characterized with possible mutualisms, the role of either host or inhabitant in facilitating these associations remains unclear. This study focuses on the interactions between Terrestrial Salamanders and Pseudomonas, one such association that has been identified but has yet to be investigated. Bacteria – including but not exclusive to Pseudomonas – was cultured and isolated from salamanders and their immediate surroundings. After undergoing quantitative liquid assays utilizing controls and salamander skin secretions, their respective and comparative growth was analyzed based on their lag time, maximum growth rate, and saturation density. Thesis growth metrics were then used to differentiate the effect of control factors on isolates. The results of this study will either support the argument that skin microbiomes are selective for specific microbes, meaning the associations evolved and intimate, or that amphibian skin microbiomes are coincidental assemblies.

SYDNEY DOUGLAS ASSESSING PH AFFINITY OF HOST-ASSOCIATED AND FREE-LIVING MICROBES Amphibian skin harbors a diverse community of micro-organisms, including bacteria, fungi, and protists, which play vital roles in host defense and disease prevention. The host skin microbiome is affected by environmental factors, such as host traits and geography. Central to the understanding of amphibian skin microbiota is the role of pH, the level of acidity, which is a critical environmental factor that may influence microbial colonization patterns. The aim of this study is to investigate the relationship between Southern Zigzag Salamander skin pH and bacterial colonization patterns, with a focus on understanding whether these colonization patterns are indeed non-random. My research intent is to contribute to a deeper comprehension of the intricate relationship between host physiology and microbial ecology ENVIRONMENTAL: HONORS THESIS RESEARCH

in amphibian skin, with potential implications for conservation efforts and our understanding of host-microbe interactions across ecosystems. Samples of bacteria found on the skin microbiome will be collected from 5 individual Southern Zigzag Salamanders (Plethodon ventralis) found on Baylor School’s campus, the pH of the salamander skin will be tested using a Hanna Halo Wireless pH meter. Then the bacteria are to be cultured on R2A agar plates of 3 different pH levels: 5, 7, and 9. Next, the DNA will be extracted using the Promega DNA Purification Kit, amplified using PCR, then sequenced using Sanger sequencing. Lastly, assays will be conducted at three different pH levels. This project is significant to the understanding of symbiosis, especially of the salamander skin microbiome and the role pH has.

The results of this study could explain how chemical characteristics of secretory compounds shape the amphibian skin microbiome through consistent processes acting on stochastic dispersal.

HUNTER SHAW THE EFFECTS OF SECONDARY CONTACT ON PLETHODON AUREOLUS Hybridization between closely related species is a common occurrence and can make it difficult to apply species definitions. This study aims to measure secondary contact and establish ranges for three species of salamanders of the genus Plethodon native to the Unicoi mountains of Tennessee and North Carolina. Hybridization is easy to determine when both species are easily recognizable and separate.

Plethodon salamanders are morphologically complex due to past and present hybridization as well as habitat overlap and physical similarities. The Plethodon salamanders, endemic to Southern Appalachia, are useful for hybrid research due to their relatively recent divergence and similar niche requirements. Tail tips were collected from individuals of each of the three species in the Bald River Gorge Wilderness, the Citico Creek Wilderness, and the Cherokee National Forest. DNA sequencing using a 2RAD approach was used to identify single nucleotide polymorphisms across the genomes of species in this study.

This sequencing allows for grouping samples based on the number of shared loci to determine the species that each sample came from.

The results of RADseq DNA sequencing will allow us to analyze the genetic composition of our samples to further research hybrid relevance and find hybrid zones of the Plethodon salamanders in the mountainous regions of Tennessee and North Carolina. The results will evaluate the historical, current, and future effects of secondary contact on salamanders in Southern Appalachia.

ENVIRONMENTAL: HONORS THESIS RESEARCH

ENVIRONMENTAL: HONORS ADVANCED RESEARCH RUSSELL BOYD ASSESSING PCR CYCLE NUMBER BIAS IN 16S MICROBIOME SEQUENCING AND ITS IMPLICATIONS FOR SNAKE FUNGAL DISEASE RESEARCH Fungal pathogens have become a serious and growing threat to wildlife, driving declines in amphibians, bats, and reptiles. One of the newer concerns is Ophidiomyces ophidiicola (Oo), the fungus behind Snake Fungal Disease, which kills roughly 40% of the wild snakes it infects, and the bacteria living on a snake's skin may play a big role in whether that snake survives. Identifying those protective bacteria relies on PCR to amplify the 16S rRNA gene, but PCR doesn't copy every microbe equally, and cycle-number effects on low-biomass skin and water samples remain unclear. Since any conclusions about a protective microbiome are only as reliable as the PCR prep behind them, this study tests how changing cycle number changes the microbiome you actually see.

To survey snakes on the Baylor campus, tin coverboards were placed across campus as refuges, and captured snakes will be swabbed for culture-dependent and culture-independent assays, including anti-fungal challenge assays. To directly test the cycle-number question, DNA from salamander skin swabs and tank water was amplified with 16S rRNA primers at 25, 30, 35, and 40 cycles, verified by gel electrophoresis, quantified with Qubit, and prepped for MinION sequencing. All four conditions amplified successfully, with DNA yields rising as cycle count increased, confirming the reactions ran cleanly and produced enough product for sequencing. Pinning down this bias will make snake microbiome work more trustworthy and improve the search for bacteria that protect snakes from Ophidiomyces ophidiicola.

BRODY BROOKS SEXUAL AND LINEAGE DIMORPHISM OF BIOFLUORESCENCE IN THE EURYCEA COMPLEX Biofluorescence is the absorption and re-emission of light through the skin and is widespread among amphibians, yet its exact functional purpose remains unclear. Recent studies have found biofluorescence in salamanders, but the ecological and phylogenetic contexts have yet to be evaluated. This study investigates variation in biofluorescence across lineage and sex in salamanders of the Eurycea genus, several of whose lineages occur in the Chattanooga region.

We extracted pigments from archived specimens and first evaluated solvent choice for fluorescent compound extraction. Then, we compared fluorescence intensity and spectral properties among individuals using methanol and quantification on a plate reader. These ENVIRONMENTAL: HONORS ADVANCED RESEARCH

data are paired with genetic identification through Sanger sequencing, enabling direct comparison between lineage-specific genotypes and fluorescence phenotypes. Integrating genetic approaches allows for credible characterization of these individuals. Our results support the theory that biofluorescence is related to sexual selection. This is due to differences in biofluorescence among members of the same lineage. Ultimately, this research aims to clarify the ecological and evolutionary drivers of biofluorescence in Eurycea, contributing to a broader understanding of amphibian signaling and adaptation in biodiverse freshwater systems.

CAROLINE CHASE AND RUBY DOZIER SHEDDING FREQUENCY AND MOLECULAR IDENTIFICATION OF A SALAMANDER PARASITE Parasites effect the evolution trajectory of the hosts by altering behavior, physiology, and survival. Digenetic parasites utilize primary and secondary intermediate hosts to complete their life cycle before sexually reproducing in a definitive host. Black-bellied salamanders act as the second intermediate hosts for the parasite Metagonimoides oregonensis, and salamanders infected with metacercaria show decreased movement, making them less likely to disperse and forage.

Our research evaluates the prevalence of M. oregonensis in its first intermediate host, Elimia proxima to understand shedding patterns in concordance with rates of infected salamanders. We collected 100 E. proxima from Dicks Creek right outside of Gainesville, Ga. and attempted to induce shedding using fluorescent lamps. Shed cercaria were then isolated, amplified, and sequenced to determine their identity. While a relatively low percentage of our snails were harboring parasites, M. oregonensis was successfully isolated and identified from one individual, providing the first molecular characterization of M. oregonensis in the state of Georgia. Other parasites shed from snails included Microparyphium and Neogogatea kentuckiensis. The results of this study contribute to our understanding of the complex ecological and evolutionary interactions between digenetic parasites and intermediate hosts.

ANGELINA FALCONE DEVELOPING AND IMPLEMENTING A QPCR MULTIPLEX ASSAY TO CONSERVE AN ENDANGERED SPECIES Freshwater fish populations in the southeastern United States have experienced significant declines in recent years, driven by a combination of climate change, parasitic pressures, and human disturbance.

Among the most critically affected species is Chrosomus saylori (Laurel dace), a freshwater minnow listed as endangered since 2011 and now restricted to only three streams on the Cumberland Plateau. To ENVIRONMENTAL: HONORS ADVANCED RESEARCH

assess the presence of this imperiled species, we will employ environmental DNA (eDNA), a rapid and non-invasive method that detects genetic material shed by organisms into their environment. Following sample collection, eDNA will be analyzed using multiplex quantitative PCR (qPCR), a technique that enables the simultaneous detection of multiple species within a single assay. Species-specific primers and probes were carefully designed and validated through in-silico and in-vitro testing to ensure accuracy and specificity. This multiplex approach will allow us to monitor not only Laurel dace, but also other relevant species, including invasive sunfish, blacknose dace, stoneroller, and white suckers. The significance of this research lies in its potential to inform conservation strategies, particularly genetic rescue efforts, and to identify creek systems that may be suitable for future reintroduction of Laurel dace populations.

SHIRLEY HUANG DECIPHERING AND DELIMITING THE ZIG-ZAG SALAMANDER COMPLEX IN CENTRAL AND EASTERN TENNESSEE Understanding evolution is essential to the study of living organisms because it explains patterns of diversity, adaptation, and relationships across biology, with applications ranging from medicine and agriculture to ecology and conservation. One complex that highlights the significance of evolutionary processes is the zig-zag salamander complex, which consists of three closely related species. In Tennessee forests, these salamanders play an important ecological role and are also valuable as indicator species because their lungless, skin-based respiration makes them especially sensitive to environmental change and pollution. As a result, studying this complex can provide insight into both evolutionary history and ecosystem health. Our research project focuses on three major questions: where the species boundaries within the zig-zag salamander complex truly occur; how much gene flow exists among populations; and how geographic features influence patterns of gene flow across the landscape. To address these questions, we integrate multiple scientific approaches, including fieldwork, genomics, and computational analysis. Salamanders are sampled across sites in Tennessee, where ecological and morphological data are recorded alongside tissue collection for genetic study. We then use ddRADseq on extracted DNA, with sequencing conducted at the University of Tennessee Genomics Core and downstream bioinformatic analyses performed at Baylor School. By combining genomic data with geographic and ecological information, this project aims to clarify species relationships and improve our understanding of how evolution shapes biodiversity in Tennessee salamanders.

ENVIRONMENTAL: HONORS ADVANCED RESEARCH

ENVIRONMENTAL: RESEARCH I ELIZABETH AGNER TRANSGENERATIONAL LETHAL AND SUB-LETHAL EFFECTS OF GLYPHOSATE ON A WIDESPREAD AQUATIC SNAIL Glyphosate, a widely used chemical herbicide, targets 5-enolpyruvylshikimate-3-phospate (EPSPS), an enzyme in plants that is essential to the formation of acids that are the building blocks of proteins in plants. It’s use extends from household garages to agricultural complexes and allows for recontrol of unwanted plant growth, revolutionizing agriculture. Oftentimes, glyphosate is mixed with surfactants that are crucial to penetrating leaf structure. Glyphosate has historically been considered safe for use, but a plethora of studies have been conducted that show non-target effects ranging from invertebrates up to humans. This research project will be assessing the lethal and sub-lethal effects of glyphosate and surfactants on the aquatic snail species, Physa acuta. Physa acuta is a species of snail that is widespread across the U.S. and is known for their resilience and adaptability. In this study, we will quantify the effects that glyphosate has on the growth, reproductive rate, and life span of the snail. A preliminary study was conducted in which a sample of seven snails were taken from Stringer’s Branch and taken back to the lab where their growth was monitored by means of measuring the diameter of their shell lengths with digital calipers and weighing their dry mass with a digital scale. Future studies will include an LD50 for acute toxicity to see if the herbicide has significant effects on invertebrates so that a further assessment could be done to qualify the safety of glyphosate.

This research is significant because if the study were to find that there is an effect on Physa acuta, there could be cause for concern for the effects that glyphosate could cause for humans and other organisms.

DEMIR BOZBEY USING MACHINE LEARNING AND COMPUTER VISION TO AID IN CAPTURE-RECAPTURE STUDIES OF AMPHIBIAN COMMUNITIES Computer vision (CV) is an emerging technology that incorporates machine learning and imaging and highlights how photographic information can transform phenomics to be more accurate. CV and machine learning are fields of study to teach a computer program to see and interpret the world through images. A collection of images or videos will be given to the model to extract certain features and recognize patterns. Machine learning offers a non-invasive method for identifying individual salamanders through photographic pattern recognition. Traditional identification techniques, such as VIE tagging, can be invasive and costly. In this investigation, zig-zag salamanders will be captured ENVIRONMENTAL: RESEARCH I

across Baylor Woods and photographed using a standardized imaging setup to ensure consistency. This controlled “studio box” approach will minimize environmental variability and improve image quality for analysis. A custom machine learning model will then be developed using public community-taken photos to detect unique dorsal patterns and then used to match individuals across multiple sampling sessions. It was hypothesized that, if effective, the model would consistently recognize individuals across sessions, reflecting both reliable pattern detection and salamander site fidelity. By comparing photographic identification to traditional tagging methods, this research assesses the potential of computer vision as a reliable and efficient tool for ecological monitoring and long-term population studies.

HANK ETZLER DEBRIS MITIGATION IN STRINGERS BRANCH AND BAYLOR LAKE Water pollution is one of the most significant issues affecting freshwater ecosystems worldwide. Anthropogenic debris is often transported through tributary systems, accumulating in rivers and lakes where it can disrupt ecological balance. Similar to global trends, debris buildup in Baylor Lake is a major concern because ingestion by wildlife can lead to ecosystem degradation. The primary objective of this project is to reduce the amount of debris entering Baylor Lake from Stringers Branch. At the start of the project, a litter boom configured in a C-shape was installed as a mitigation strategy to intercept debris.

This design showed moderate effectiveness under stable hydrological conditions; however, during high-flow events, increased water velocity and discharge allowed debris to bypass the boom, leading to downstream accumulation. Throughout data collection, environmental variability, including rainfall, snow, and drought, affected boom performance. These fluctuations influenced debris capture rates, with optimal efficiency occurring under moderate flow conditions. Debris collection involved removing accumulated waste, placing it into reusable mesh bags, and measuring mass with a calibrated fish scale.

Overall, the C-shaped boom functioned effectively only within a limited range of conditions. Increased precipitation in the Chattanooga area reduced containment efficiency and caused overflow, contributing to continued debris transport into Baylor Lake. This research establishes a foundation for future litter boom design and placement, with the goal of improving long-term ecosystem protection, reducing pollution, and minimizing impacts on the hydrology of local creeks and streams.

ENVIRONMENTAL: RESEARCH I

EUGENIE LI REAL TIME, FIELD-BASED MONITORING OF ESCHERICHIA COLI IN URBAN FRESHWATER STREAMS Escherichia coli is gram-negative, rod-shaped bacteria commonly found in the lower intestines of humans and warm-blooded animals.

It is traditionally used as an indicator of fecal contamination in environmental waters. Current detection methods such as PCR require laboratory equipment and trained personnel, limiting rapid, fieldbased monitoring. This study will address the critical gap in field-deployable, rapid, and user-friendly methods for E. coli detection. The objective is to design and evaluate a detection system capable of delivering accurate, quantifiable results under field conditions, improving water quality monitoring and public health responses for the community. The research will utilize three complementary identification approaches: Colisense enzyme-based assays for preliminary field screening, loop-mediated isothermal amplification (LAMP) for nucleic acid amplification under isothermal conditions (detection limit: 102–103 gene copies per reaction), and nucleic acid lateral flow (NALF) systems for visual readout without specialized equipment.

The system will allow E. coli detection in under one hour with high specificity and inhibitor tolerance, comparing to Colisense for efficiency and NALF for clear visual results. This workflow will balance speed, sensitivity, and field practicality, offering a promising solution for on-site environmental monitoring in resource-limited settings.

RHODES KELLY EFFECTS OF PREDATOR TIMING ON EARLY HATCHED GRAY TREEFROGS, DRYOPHETES VERSICOLOR Hatching plasticity refers to a unique biological process where an embryo can alter the timing of their hatch earlier or later based on certain environmental factors. Rather than hatching at a fixed stage of development, cues such as hydroperiod, salinity, and predatory cues affect when an embryo hatches and how quickly development proceeds. Similarly, developmental plasticity is widespread across the animal kingdom but is particularly relevant for amphibians, who undergo entire morphological and physiological changes in their biphasic lives. As a result, tradeoffs at particular stages of development could result in consequences not apparent until adulthood. For example, tadpoles accelerating development in short hydroperiods are smaller in adulthood, making them less likely to disperse and more prone to predation. A less investigated topic is how the timing and duration of stressors can act as brakes or accelerators on amphibian development. This study aims to evaluate how short-term predator exposure impacts development rates on early hatched anurans. Using the wetland adjacent to Baylor Lake, multiple experimental chambers will be ENVIRONMENTAL: RESEARCH I

set up containing Gray Treefrog tadpoles. Chambers will be assigned to one of four treatments (no interaction, only early interaction, only later interaction, and full-time exposure to a caged predator. We will track the growth of each frog, comparing it to other treatments, and use Gosner stages as a metric to track development. The results of this research show how predator-derived early hatching and interaction change Gray Treefrogs behavior and furthermore how these alterations in behavior effect long term developmental outcomes.

BRECKEN MCKENNA QUANTIFICATION OF HEAVY METAL POLLUTION IN BAYLOR LAKE Heavy Metal pollution poses serious environmental threats through direct toxicity and food chain transference. Various Heavy Metals have different biological effects, such as Chromium, which is known to damage chloroplast structures, or lead, which can lead to increased infertility and cognitive decline. Heavy Metals commonly originate from industrial sources, such as the sites adjacent to Stringers Branch, a tributary that empties into Baylor Lake. With the increase in industry to meet a growing population, remediation of historical and contemporary sites has become a top priority for developers and scientists. This study aims to evaluate the extent to which Baylor Lake is contaminated with these metals, using soil cores and colorimetric assays using chelation reactions. Soil cores will be taken from a variety of points around Baylor Lake, then the samples will be stratified and tested for metal pollutants. This will be done through the use of chelation reactions. With this data, the most concentrated pollutants can be identified, paving the way for future remediation. This will help protect against the future effects of heavy metal pollution, such as lead poisoning, and allow us to better preserve the environment of our campus.

ANNABELLA NESLIN AND GRACEY WEEKLEY AQUATIC SAFE GLYPHOSATE AND THE LETHAL AND SUBLETHAL EFFECTS ON AQUATIC ISOPODS Glyphosate is the world’s most popular herbicide and is used widely in agriculture and lawncare. Glyphosate’s mode of action targets the shikimic acid pathway, which results in reduced amino acid synthesis and failed protein production. This, in turn, inhibits ability to synthesize chlorophyll, ultimately leading to the death of the plant. While the shikimic acid pathway is specific to plants, non-target organisms often experience by enzymatic damage and toxicity from glyphosate. Surfactants used to increase glyphosate uptake on plant leaves are additionally highly toxic to animal life. Recently, ‘aquatic safe’ glyphosate formulations have hit the market, but thorough investigations into the lethal and sublethal effects of these formulations have not been conducted. This study aims to determine the impact of glyphosate with ENVIRONMENTAL: RESEARCH I

and without a surfactant compared with aquatic safe glyphosate. Our two-part study will evaluate the efficacy of formulations for removing invasive wintercreeper in common garden experiments before exploring how each formulation impacts aquatic isopods, a commonly used model organisms for toxicity assays. Isopods will be tested with different concentrations of glyphosate alone, surfactant alone, and then together. Mortality, movement, behavior, and metabolic rate will be tracked. The results of this study will provide important clarity into the effectiveness of glyphosate formulations in targeted application and their non-target impacts in freshwater ecosystems.

RICHARD RODRIGUEZ DEVELOPMENT OF A PCR-RFLP PROGRAM TO MONITOR MICROPTERUS HYBRIDIZATION IN CHATTANOOGA Hybridization among closely related fish species is an important topic in ecology, particularly as environmental changes alter species distributions and reproductive interactions. The Smallmouth bass is a freshwater species found throughout North America that often coexists with other members of the Micropterus genus. While these species are typically reproductively isolated through differences in habitat preference and spawning behavior, environmental disturbances and stocking efforts have increased opportunities for hybridization.

Notably, in Tennessee, there is a growing population of invasive Alabama bass. These bass mate with native Smallmouth and decrease pure bred small mouth population. This is potentially detrimental to the ecosystem because these hybrids are more aggressive and outcompete native fish for food and mates. While the number of reports of invasive bass have increased, the prevalence of Alabama bass and extent of hybridization with native species remains poorly understood and difficult to assess. This study seeks to develop and implement an amplified fragment length polymorphism (AFLP) assay to genetically survey bass populations around Baylor’s campus using a combination of mitochondrial and nuclear genes. After developing and validating molecular markers and restriction enzymes, baited minnow traps and fishing surveys will be used to sample bass populations. Fin clippings will be taken, and assays will be scored using gel electrophoresis. The results of this study will provide a cost-effective genetic resource for managers while also documenting the extent of Alabama bass influence in the Chattanooga area.

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SUSTAINABILITY

SUSTAINABILITY: HONORS THESIS RESEARCH CALEN HAWK SUBFRAME DEVELOPMENT FOR AN ELECTRIC CONVERSION OF A 1980 JOHN DEERE 950 TRACTOR The electrification of agricultural machinery presents a practical way to reduce emissions, lower the operating costs, and extend the usable life of older equipment. This project focuses on the design and development of a custom structural subframe for converting a 1980 John Deere 950 tractor from a diesel to an electric drivetrain. The removal of the original three-cylinder diesel engine separates the tractor into two structural halves, requiring a subframe to reconnect the front and rear sections while also supporting new electric components. To begin the process of developing the subframe, the tractor was disassembled, the frame geometry and mounting points were measured, and a 3D model using Autodesk Fusion 360 CAD software was produced. Prior to designing the subframe in Fusion 360, a wooden subframe was constructed to align with the transmission and existing mounting points on the tractor. This helped to confirm fit, and the spatial constraints required to accommodate motor and battery placement while keeping the original length and balance.

Finite Element Analysis (FEA) was performed to evaluate structural performance under expected loads such as motor torque, battery weight, and off-road forces. Initial results indicate that the tractor’s existing frame and transmission housing provide viable mounting points, and that sufficient space exists for an electric drivetrain. This work demonstrates the feasibility of a custom subframe design and contributes toward developing a cost-effective, replicable method for electric tractor conversion.

PIPPA HILL EFFECTS OF MONOCULTURE AND POLYCULTURE COVER CROPS ON CARBON SEQUESTRATION Soil plays a critical role in storing carbon and mitigating climate change, and agricultural practices such as cover cropping may influence how effectively carbon is retained in the soil. This study examines differences in soil organic carbon (SOC) between a monoculture cover crop system of crimson clover and a diverse polyculture mixture including legumes, grasses, and brassicas. Baseline SOC levels were measured through laboratory dry combustion analysis following planting and before significant plant growth occurred. Initial results showed high SOC concentrations in both treatments, with the monoculture plot containing slightly more carbon than the polyculture. Due

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to these already elevated carbon levels and the relatively short duration of the study, large changes in SOC may not be immediately detectable. However, active carbon is a different parameter that responds much more rapidly to changes in soil conditions. Active carbon content is still being measured using a spectral analysis procedure. Existing research suggests polyculture systems may gradually store carbon more effectively through greater biomass diversity and improved soil structure. Continued sampling and analysis of both active carbon and total SOC will determine whether meaningful differences emerge over time. This research contributes to broader efforts to evaluate regenerative agriculture practices and their potential role in long-term soil carbon sequestration.

LAKE MONTGOMERY EXAMINING THE EXTENT TO WHICH SOLAR PANELS INFLUENCE ELECTRIC TRACTOR RUN TIME Electric tractors were first conceived in 1959, but electric tractors have not been widely adopted among farmers. One of the reasons electric tractors have not been adopted is because tractors must be able to run for long times in the field. Electric tractors are limited by their battery capacity and require charging from the grid or another fuel source. This study will analyze the extent to which on-board solar panels can charge the batteries and increase an electric tractor’s run time. This study was able to make a wiring diagram and procedure that could be followed for connecting solar panels to an electric tractor. The study used a field test to determine that at an amp draw of 56 the tractor could run for 102 minutes and a simulation to find that the two dual sided 455-watt panels could produce 726 kWh/year. Additional calculations demonstrated that the solar panels in this configuration could increase run time by 10 percent. The results will be used to approximate the same experiment with different tractors and different solar panels. This study was limited by logistical constraints, so to properly test the effect of solar panels on electric tractor run time, extensive field tests would need to be conducted.

SUSTAINABILITY: HONORS THESIS RESEARCH

SUSTAINABILITY: HONORS ADVANCED RESEARCH JACK HOUSTON DETERMINING THE ELECTRICITY PRODUCTION BENEFITS OF ROOFTOP SOLAR ARRAYS ON AN ACADEMIC CAMPUS With energy and electricity needs growing rapidly across the world, solar power has become a growing suggestion to fuel new demand.

Solar panels offer many advantages as an electricity production method: they are increasingly affordable, customizable by location, and produce renewable, low-carbon energy. Furthermore, academic campuses have been shown to be especially suitable for solar power; large roofs and significant electricity consumption make schools suitable for solar, and solar energy deployment has shown to make positive impressions on students and reinforce environmental stewardship. This project utilizes PVsyst, a modeling software, to analyze the production of several optimized rooftop arrays across Baylor’s campus. The blueprints of five buildings were used to design arrays that would produce a share of Baylor’s electricity. The preliminary results of just two buildings show a minimum of 5 megawatts produced per year. The final production total between all five buildings will be contextualized within Baylor’s electricity production to determine whether the venture would be economically advantageous. These results will inform Baylor and similar campuses about the possibility of considering solar installation on unused, large rooftop areas, but future research could expand this concept to consider similar methods in commercial and industrial sectors.

MAX MINNINGER A CONVOLUTION NEURAL NETWORK OPERATED SMARTBIN TO LIMIT RECYCLING CONTAMINATION The world produces around 400 million tons of plastic every year, and that number continues to rise rapidly. Substantial amounts of this plastic end up as pollutants in the world’s ecosystems. A large reason for this pollution is due to inadequate waste management systems and contamination inside recycling bins, as contamination can cause an entire load of recycling to be redirected to a landfill. This study is developing a Smart Bin that uses a Convolution Neural Network (CNN) to identify and correctly classify various images of waste items (plastic, cardboard, glass, metal, etc.). Google Colab was used to create the CNN code in the python language, and it is being run off the Raspberry Pi operating system. The code is designed to receive SUSTAINABILITY: HONORS ADVANCED RESEARCH

an image from a camera and then assess the image individually and decide if the object is allowed inside the bin. If allowed inside, the system should open the bin, if not allowed, the bin will stay closed. A system that limits human error may help prevent potential contamination or misplacement of waste.

ELLY WU FIELD STUDY OF THE EFFECT OF VARIOUS CONCENTRATIONS OF NEEM OIL ON THE PREVALENCE OF MICROTHECA OCHROLOMA IN ORGANIC CRUCIFER PRODUCTION The yellow margined leaf beetle, M. ochroloma, has emerged as a devastating pest to organic crucifer production due to the inability of organic farmers to use conventional insecticides. As an invasive species in the southeastern United States, M. ochroloma currently has few natural predators. M. ochroloma feeds upon brassicaceae by creating irregularly shaped holes in the leaves, causing complete defoliation and devastating economic loss for farmers. With the limited research surrounding organic management practices against M. ochroloma in the field, the aim of this study was to evaluate the impact of various concentrations of azadirachtaindica, or neem oil, on M. ochroloma proliferation in an organic farm. The first iteration of this study utilized a 2.5% solution of neem oil on four raised beds and after four treatments, no clear conclusion could be drawn connecting M. ochroloma and the application of neem due to insufficient M. ochroloma presence. Based on prior observations, the study was replicated in the spring at two different times to investigate the impact of staggered planting dates on M. ochroloma proliferation. 1, 2, and 3% solutions of neem were applied weekly and M. ochroloma presence was counted daily. This study will be conducted across two more growing seasons and aims to expand upon the limited literature surrounding M. ochroloma and effective organic management strategies.

SUSTAINABILITY: HONORS ADVANCED RESEARCH

ASHLEY YIM COMPARING THE PROTEIN CONTENT OF COMMERCIALLY AVAILABLE WHEY PROTEIN ISOLATES There is little understanding if multiple manufacturers of the same food product differ in nutritional value from each other. The nutritional value reflects the quality of a protein, which is tested by the varying structure, amount, and presence of essential amino acids. It is unclear the exact protein value in processed food products with current product labeling permitting a 20% margin of error. In this study, the protein content of commercially available whey protein isolate (WPI) powders is quantified using gel electrophoresis and the Bradford Assay method. In gel electrophoresis, the electrical separation of proteins based on their molecular mass and overall net charge, unknown whey proteins of varying molecular masses were identified suggesting that the WPI powder tested is composed of multiple whey proteins of varying amounts. Measuring the protein concentration of the WPI powder through a spectrometer, the exact protein value of the WPI powder will be compared to what is stated on the nutritional label in Bradford Assay. This study will also determine if a-lactalbumin is a suitable standard in Bradford Assay instead of bovine serum albumin for the protein determination of WPI powder. Once the various proportions of the whey proteins in the WPI powder are identified, the amino acid content of the whey proteins will be tested to determine the nutritional quality of the WPI powder.

SUSTAINABILITY: HONORS ADVANCED RESEARCH

SUSTAINABILITY: RESEARCH I ELISABETH CHILDS COLOR EXPRESSION IN RED LEAF LETTUCE AS A RESPONSE TO pH LEVELS This study investigates how different soil pH levels affect the color expression of red leaf lettuce. Soil pH is a crucial factor that influences how plants absorb nutrients, which can affect pigment development and overall plant quality. Plant pigments called anthocyanins appear brighter red in more acidic conditions and become less visible as pH increases. The goal of this experiment is to determine which soil pH level produces the most intense red color. Red leaf lettuce will be grown in four soil pH conditions, pH 5, 6, 7, and 8, with 24 plants in each group. Soil pH will be adjusted using sulfur and limestone and monitored weekly. Plant growth will be recorded over time while keeping other factors, such as sunlight, water, and soil type, consistent. Leaf color will be measured using a spectrophotometer. It is expected that lower soil pH levels will result in deeper red coloration, while higher pH levels will produce greener leaves. This study will help explain how soil conditions influence plant appearance and quality, although other factors such as light, temperature, and small changes in soil pH may also affect the results.

ANSON DANIEL EFFECT OF BIOCHAR-COMPOST PERCENTAGES ON SOIL HEALTH AND PLANT GROWTH Soil health plays a critical role in plant growth and agricultural productivity. Biochar, a carbon-rich material produced from organic matter, has been suggested as a soil amendment that can improve soil structure and water-holding capacity. When combined with compost, which supplies nutrients and organic matter, biochar may enhance overall soil performance. However, Biochar as a soil amendment can be expensive for farmers and its effectiveness depends on the percentage applied. This study investigates how different percentages of biochar mixed with compost affect soil properties and plant growth. Experimental plots were prepared with 0%, 10%, and 20% of biochar levels.

Soil and plant analyses were conducted during pre and post treatment, including measurements of bulk density, porosity, water retention, and soil nutrient content. It is expected that moderate biochar percentages will improve soil structure and increase water retention, whereas excessive amounts may not provide additional benefits. Findings from this study will help inform sustainable soil management practices and guide farmers in selecting effective biochar–compost combinations.

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SAM GRAFTON COMPARISON OF GRAPHITE AND TITANIUM ELECTRODES IN SYNTHESIS OF BIODIESEL FROM WASTE COOKING OIL In comparison to petroleum diesel fuel, biodiesel is made of mostly renewable resources such as waste cooking oil. Biodiesel is traditionally made from chemical methods, but studies have demonstrated that electrolysis can make this process more efficient. Electrolysis is the use of two electrodes placed in the biodiesel preparation solution and are connected to dc power. Electrolysis speeds up the transesterification process and may generate a greater yield. Many different types of metals can be utilized as electrodes, but it is unclear which type of electrode generates the greatest yield. Titanium and graphite electrodes were chosen for this experiment, because they are most used in other studies. 1000 ml cooking oil was placed in a 2000 ml beaker. NaCl, KOH, and distilled water were dissolved in 200 ml methanol, then added to the cooking oil. Electrodes were connected to positive and negative leads of a dc power unit set at 12 volts for two hours. Mixture was stirred constantly during the electrolysis procedure. Upon completion of the reaction, dc power was disconnected, and the mixture was allowed to settle for 24 hours. Glycerol layer was removed, and total yield of biodiesel was recorded. This experiment will be replicated multiple times and the yield from the different electrodes will be averaged and compared. The results of this experiment may help better utilize waste cooking oil in biodiesel production.

BRYCE LAU MECHANICAL TECHNIQUES TO SUPPRESS THE GROWTH OF CYNODON DACTYLON Cynodon dactylon, commonly known as Bermudagrass, is a fast growing, resilient summer grass that can be difficult to control on organic farms. The undergrowth of the plant, the rhizome, allows the grass to grow fast and survive in conditions like drought, heat, and shade. The objective of this study is to determine if different mechanical treatments (mulching, tilling, and occultation) can suppress the growth of Bermudagrass. The study was conducted in an organic garden known to have Bermudagrass, four 5 ft. by 10 ft. plots (one mulched, one tilled, one with tarp, and one control) were monitored over the duration of the study. The pinpoint drop method determined percentage of Bermudagrass before and after treatments. Treatments were applied and left in place for 6 weeks; after which, percentage of Bermudagrass will be counted again. Results may help farmers determine best practices for organic control of Bermudagrass.

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AMIYA LEACH SILAGE TARPS AND THEIR EFFECTS ON ARTHROPOD COMMUNITIES AND ABUNDANCE Silage tarping is the agricultural practice of placing black plastic tarps over a land area or crop beds to kill and suppress weeds. However, there is little research on how silage tarps effects soil organisms.

Arthropods are vital for soil health because they help decompose organic materials. This study focuses on how silage tarps effect arthropod communities in raised beds on an organic farm. Both Pitfall and cul-de-sac traps were used in order to catch and record the initial arthropod number and species before the tarps were placed. Silage tarps are placed on two crop beds and an additional two crop beds remained untarped, with pitfall traps being placed on both tarped and untarped beds. Contents of these traps were recorded every three days and arthropod numbers, and species were recorded. The data collected throughout the four weeks will be compared to data from before the tarps were placed in order to see changes in the arthropod communities. The findings of this study may inform farmers practices with regard to sustainable weed management.

CHASE MANSFIELD TOOLBAR MOUNTED NO-TILL PLANTER FOR THE ALLIS CHALMERS G SERIES No-till is a mechanical method of manipulating soil to plant seeds without tillage, and it is an important practice in sustainable soil management. The Allis Chalmers G series tractor (ACG), produced between 1948-55, has seen a resurgence in popularity recently among small-scale vegetable farmers. However, commercially produced notill planters are not available for the Allis Chalmers G. This research paper proposes a method of converting a Jang JP-1 push planter to a toolbar-mounted no-till planter for the ACG. Dimensions and angles of the ACG were measured. Then, a schematic was created for the toolbar-planter bolt attachment. One concept of attaching the coulter relative to the planter was designed to replace the gauge wheel (front wheel) with the coulter. Preliminary results suggest that the no-till coulter apparatus will need to be separately mounted from the JP-1 planter. Height adjustment systems were designed for coulter depth adjustment. A 3D model of the no-till system was developed in the Fusion 360 CAD software. Fusion 360 will be used to confirm the structural strength and integrity of this custom planter. Field tests will be conducted to determine functionality. The development of this apparatus may assist farmers in utilizing their existing equipment to adopt no-till practices.

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ADRIAN PEREZ-LITWIN COMPARING TILLAGE AND MULCHING WITH RESPECT TO BRIX VALUES OF LACTUCA SATIVA This research study investigates the influence of tillage versus mulching of Brix values on various types of Lactuca sativa crops. Tillage and mulching are two methods of sustainable weed control on farms where chemical herbicides are prohibited. Brix, or total soluble solids (TSS), is a measure of sugar concentration within a solution, where 1 Bx is equivalent to 1 gram of sugar per 100 grams of solution. Agriculturally, Brix is commonly used to evaluate the quality of a crop: a higher Brix level implies superior taste and nutritional content. This research project aims to determine which strategy optimizes the physiological quality of lettuce by analyzing Brix fluctuations throughout the growing season. A comparative field study was conducted using two beds: one prepared with organic leaf mulch and another with conventional tillage. After preparation, three-week-old lettuce crops were transplanted into the beds. To allow for adequate leaf development, leaves were tested two weeks after transplanting. Using a refractometer, Brix values were consistently measured semiweekly for one month. In addition, plant height and diameter were monitored throughout the season. This study may help inform farmers with sustainable methods of weed control.

SOFIE PETERSON WHITE-TAILED DEER FORAGING PREFERENCES The aim of this study is to determine whether White-Tailed deer show foraging preferences among different types of crops. In the wild, research suggests that deer prefer high-protein forage. However, it is unclear which of the commercially available forages planted by farmers or hunters are preferred by deer in southeastern Tennessee. Two high protein forages, purple turnips and trophy rapeseed, and one low protein crop, Rushmore oats (spring oats), were utilized. A total of four plots were used in this study, one control plot with no planted crop, and three plots, each containing one of the selected crops.

Prior to planting, trail cameras were placed at the plot location to confirm the presence of deer. After planting, crop consumption will be measured using a pinpoint and binomial method. In the pinpoint method, each plot will be divided into smaller sections, and markers will be randomly dropped within these sections. Observations will be taken over time by comparing the amount of plant material remaining at each marked location. The binomial method will count how many times deer visit each plot and determine which plot the deer prefers.

Analysis of this data will help estimate how much each crop has been consumed and determine which crops deer prefer.

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FRANK TREADWELL EVALUATIVE METRICS FOR MONITORING FATIGUE AND PERFORMANCE OF BAYLOR BOYS’ SOCCER While it is generally known that soccer matches are physically demanding, the extent to which they affect players’ performance and fatigue levels is unclear. This study aims to evaluate the extent to which matches affect players’ fatigue levels. To measure these variables, researchers used three methods of data collection. Players wore GPS vests to measure maximum velocity, total distance run, and acceleration. In addition, players completed SRPE surveys after every training session and Hooper Indexes daily to measure their perceived load, fatigue levels, and general well-being. Lastly, players completed countermovement jump tests and grip tests prior to every match to evaluate their levels of neuromuscular fatigue. To evaluate this data, researchers used the R code language to correlate variables, such as stretch shortening cycles, grip strength, maximum velocity, and number of acceleration and deceleration efforts per minute. This study could inform coaches and trainers on how to best adjust training schedules to maximize players’ performance.

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SPORTS SCIENCE: RESEARCH COLLABORATIONS BEN HOLT, BRICE JOHNSON, AND CURTIS BLAIR LONGITUDINAL AND POSITIONAL TRENDS IN PLAYER LOADS USING GPS DATA Soccer is a physically demanding sport characterized by intermittent aerobic activity with critical anaerobic spurts, necessitating a dynamic approach to seasonal training periodization. High-intensity match play frequently pushes athletes above the anaerobic threshold, leading to cumulative fatigue that elevates soft-tissue injury risk and diminishes performance over time. Because exertion levels exhibit high positional and individual specificity, a “one-size-fits-all” approach to training is often insufficient. These challenges are additionally exacerbated with youth athletes who are balancing academics, athletics, and social stress. To address these challenges, this pilot study monitored the Baylor Boys Soccer team for the 2026 season using GPS vests and session rating of perceived exertion (sRPE). By quantifying position-specific metrics, we monitor training loads in practice and matches to understand longitudinal trends of the competitive cycle and individual player needs. The results demonstrate how integrating objective GPS data with subjective load monitoring can individualize regimens and optimize team readiness, ensuring peak physical and cognitive performance throughout the season.

SPORTS SCIENCE: RESEARCH COLLABORATIONS

Thank you to our incredible judges for their time and support of Baylor Research.

Dr. Alberto Stolfi Associate Professor School of Biological Sciences at the Georgia Institute of Technology

Dr. Jeronimo Silva Molecular Ecologist Tennessee Aquarium Conservation Institute

J. Brad Stephenson Geologist/Environmental Consultant Tennessee Department of Environment and Conservation

Emily Culp GIS Analyst Tennessee Aquarium Conservation Institute

Sarah Farnsely Senior Lecturer University of Tennessee at Chattanooga

Stephen Nelson Reintroduction Manager Tennessee Aquarium Conservation Institute

Dr. German Gomez Assistant Professor Life Sciences at the Chattanooga State Community College

Dr. Ethan Carver Assoc. Provost for Academic Affairs and Dean of the Graduate School University of Tennessee at Chattanooga

Dr. John Phillips Professor Emeritus of Classics Philosophy and Religious Studies University of Tennessee Chattanooga Haley Treadway UT Extension Agriculture & Natural Resources Agent for Hamilton County The University of Tennessee Institute of Agriculture Matt Irvin AP Biology Professor Baylor School Dr. Jannatul Ferdoush Assistant Professor of Genetics University of Tennessee at Chattanooga Stephanie Chance Director of Conservation Tennessee Aquarium Conservation Institute

Dr. Mohammad Mahtabi Assoc. Professor of Mechanical Engineering University of Tennessee at Chattanooga Dr. Monireh Rahmati Lecturer, Data Analytics University of Tennessee at Chattanooga Austin Moore Mechanical Engineering Masters Student University of Tennessee at Chattanooga Dr. Akram Saad Adjunct Electrical Engineering Instructor University of Tennessee at Chattanooga

Baylor Research would like to thank the Weeks Family Their generosity makes this celebration of hard-earned accomplishments in science, technology, engineering, and mathematics possible.

BAYLOR RESEARCH THANKS YOU FOR YOUR SUPPORT!