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 allows 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 including climate change, biodiversity, and water pollution. Students are encouraged to develop and test solutions to these challenges in the areas of solar energy, energy efficiency, sustainable agriculture, and environmental remediation. Students have access to an on-campus solar array, organic garden, 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 annual Baylor School Science 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/posters are on display in addition to work done by our middle school and extra-curricular programs. Students and their advisors have spent countless hours producing this work and we could not be more proud of their efforts.
MEET THE BAYLOR RESEARCH TEAM
Dr. Ben Holt, Environmental : bholt@baylorschool.org
Dr. R. Antonio Herrera, Biomedical: raherrera@baylorschool.org
Jesse Young, Science Department Chair: jyoung@baylorschool.org
Dr. Louie Elliott, Engineering: lelliott@baylorschool.org
RESEARCH 1: BIOMEDICAL
BEN BOEHM
CHEMOTAXIS IN CAENORHABDITIS ELEGANS WITH GENES daf-6 AND tax-6
How animals use chemical odor signals to interact with their environment is a central question in biology. Organisms can sense and react to chemical signals in their surrounding environment due to the intricate structure of their nervous system, in a process called chemotaxis. To understand how genes contribute to chemotaxis, we will use the roundworm nematode, Caenorhabditis elegans, as a model organism. By studying wild-type and mutant animals in their chemotaxis response, we can understand how genes control animal behavior in reaction to their environmental stimulus. C. elegans has a quick life cycle and a completely mapped connectome. It shares many conserved nervous system genes with humans, making it an excellent organism for studying chemotaxis. Past research has shown that two neurons, ASE and AWC, have a significant role in chemotaxis in C. elegans Here, we will study how two genes, daf-6 and tax-6 regulate C. elegans chemotaxis behaviors in response to various chemical odorants. The results of these experiments can provide a deeper understanding of how sensory neurons process information for decision-making.
ADDISON CLARK
DISRUPTION OF CIRCADIAN RHYTHM IN AMERICAN BROWN MILLIPEDES
The daily activity pattern many organisms exhibit is known as the circadian rhythm. The circadian rhythm dictates when an organism is active versus when it rests or recharges. This cycle also regulates many physical and behavioral changes in an organism over 24 hours. This period corresponds to the solar cycle of daylight exposure. In this study, we are training American Brown millipedes (Orthoporus texicolens) on a 12-hour light and 12-hour dark daily cycle. Previous analysis of millipede behavior shows that these arthropods tend to avoid the light during the day and become more active during the dark hours. Also, millipedes dwell in dark and moist environments like forests and caves. Here we will be testing if millipedes will maintain a circadian rhythm when the light/dark cycles are altered. We expect to see that tinkering with their light cycles has strong effects on their lull/crawl schedule. Humans also exhibit circadian rhythms, with some people not even being aware that they have one. Human rhythms are opposite to millipedes; during the day we are awake and active, while we tend to rest at night. It would be interesting to see if tinkering with the inner workings of these millipedes will lead follow similar patterns from animals or humans when their patterns are disrupted.
ANANYA CHAKRABORTY
THE EFFECTS OF CHLORPYRIFOS ON THE FORMATION OF POLYQ35 AGGREGATES IN A mir-1 MUTANT
NEMATODE MODEL OF HUNTINGTON’S DISEASE
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 polyglutamine 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 environmental and genetic factors significantly influence the disease's progression. Environmental factors such as heavy metals, pesticides, and air pollutants can increase protein aggregation. The organophosphate chlorpyrifos, known to cause protein aggregates in neurodegenerative diseases like Alzheimer’s and Parkinson’s, has unknown effects on the Huntington protein, polyQ35. A genetic factor that mitigates HD's effects is a null mir-1 mutation, which 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. Investigating the effects of chlorpyrifos on the null mir-1 mutation can reveal 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 and environmental factors on protein aggregation can aid scientists in developing experimental treatments for the disease.
ADDI KEGERREIS
TARDIGRADE CULTURE AND SCANNING ELECTRON MICROSCOPY IMAGING
This project establishes a replicable tardigrade lab culture and captures Scanning Electron Microscopy (SEM) images of specimens from the Hypsibius exemplaris tardigrade. Tardigrades, commonly known as water bears, are eight-legged invertebrate microorganisms renowned for their incredible resilience and adaptability. This survivability is due to their ability to enter a “tun” state, allowing them to endure extremely unfavorable environments. Tardigrades have reportedly survived space, explosions, and SEM imaging, which involves coating the organism in a heavy metal. Scanning Electron Microscopes provide
high-resolution images by scanning the surface of the specimen with a beam of electrons. This technology is crucial for observing the intricate details of tardigrades, which are otherwise difficult to capture with conventional microscopy techniques. By utilizing SEM, researchers can gain deeper insights into the structural adaptations that contribute to the tardigrade's resilience. This project will outline detailed procedures for green algae culture, which serves as a food source for tardigrades, ensuring a sustainable lab environment. Additionally, it will cover the establishment and maintenance of tardigrade cultures, including optimal conditions for their growth and reproduction. The project will also include protocols for viewing tardigrades under a microscope, highlighting techniques for observing their behavior and physical characteristics. Finally, we provide comprehensive guidelines for preparing tardigrades for SEM imaging. This includes steps for coating the specimens with heavy metal and ensuring they are properly positioned for electron beam scanning. By following these procedures, researchers can produce high-quality images that contribute to the understanding of tardigrade biology and their extraordinary survival mechanisms.
AJ LORSON and AUBREY ROBBINS
ENHANCING DIAGNOSTIC ACCESSIBILITY: THE ADVANTAGES AND APPLICATIONS OF LOOP-MEDIATED ISOTHERMAL AMPLIFICATION
Loop-mediated isothermal amplification (LAMP) is a molecular diagnostic method that enables rapid and sensitive DNA amplification without the need for thermal cycling. This study provides an overview of the LAMP process, focusing on its reaction mechanism, primer design, and operational simplicity. LAMP offers clear advantages over conventional methods such as PCR and CRISPR-based assays, including faster results, minimal equipment requirements, and suitability for visual readout. The LAMP technique involves a unique set of primers and a strand-displacing DNA polymerase, allowing the amplification to occur at a constant temperature. This eliminates the need for expensive thermal cyclers, making LAMP highly accessible and cost-effective. The simplicity of the LAMP procedure also reduces the risk of contamination and errors, further enhancing its reliability. These characteristics make LAMP especially valuable for on-site diagnostics in low-resource or remote settings, where access to sophisticated laboratory equipment is limited. Diseases such as Carrion’s disease and scrub typhus are used as examples to illustrate contexts where LAMP could significantly improve diagnostic access and speed. By providing rapid and accurate results, LAMP can facilitate timely medical interventions and better disease management. Overall,
the LAMP method represents a significant advancement in molecular diagnostics, offering a practical and efficient solution for detecting various pathogens in diverse environments.
RICHARD LU and MANDY YU
USING ELECTROENCEPHALOGRAPHY TO IDENTIFY BRAINWAVE PATTERNS AND GENERATE IMAGES, PAINTINGS, AND TEXTS REPRESENTING HUMAN THOUGHTS
Electroencephalography (EEG) is a non-invasive neuroimaging technique that records brain activity via scalp electrodes, capturing microvolt ( V)-level signals categorized into frequency bands linked to cognitive and emotional states. EEG plays a vital role in neuroscience, brain-computer interfaces (BCIs), training artificial intelligence (AI) models, and rehabilitation, enabling the interpretation of neural patterns and translating brain activity into meaningful outputs. This project explores how AI can decode EEG signals into expressive outputs like text, images, and art. Extensive EEG datasets are collected using the NeuroSky MindWave Mobile 2 EEG headset with NeuroExperimenter software, capturing neural responses to specific visual stimuli (e.g., colored shapes) under varied conditions. The raw EEG data is preprocessed and analyzed using Python to visualize temporal patterns and extract key features (amplitude, frequency bands) for use in AI classification. Signal processing techniques filter and analyze electrical patterns, while neural networks translate them into actionable data, advancing assistive technologies, neurofeedback systems, and brain-controlled interfaces. Beyond clinical diagnostics, EEG technology enables movement-free communication for individuals with severe motor or speech impairments. Additionally, EEG supports immersive gaming, smart device control, and emotion recognition, with applications like brain-controlled paintbrushes, wheelchairs, eye-wink navigation, and VR rehabilitation. By integrating EEG with intelligent computing frameworks, this research highlights the profound potential of neurotechnology to enhance humancomputer interaction, support individuals with disabilities, and foster new modes of creative expression. As AI-powered EEG-based BCIs evolve, their transformative capacity promises to revolutionize assistive and interactive technologies across multiple domains.
JAMES MCCORKLE
USING COLLAGEN-19 EXPRESSION IN CAENORHABDITIS ELEGANS HYPODERMIS DEVELOPMENT TO FURTHER EXPAND THE let-7 MICRORNA GENETIC INTERACTOME
MicroRNAs (miRNAs), a novel class of small noncoding RNA genes, play a crucial role in regulating gene expression in human cancer and normal development. The let-7 family of miRNAs is involved in various cellular processes, including cell division, differentiation, and programmed cell death. These miRNAs act as tumor suppressor genes, preventing cancer cells from forming, though the precise molecular mechanisms are largely unknown. This project aims to elucidate the molecular genetic underpinnings of let-7 miRNA function by studying adult cuticle formation and hypodermal maturation in the roundworm nematode, Caenorhabditis elegans. Larval development in C. elegans follows a precise molecular genetic clock requiring let-7 miRNAs to synchronize terminal differentiation across tissues, resulting in the expression of an adult-specific collagen, col-19, after the juvenile-toadult transition. We use col-19 transcriptional activation of a green fluorescent protein (GFP) to detect cuticle maturation and compare this to let-7 miRNA mutants. Next, we will uncover and validate molecular interaction partners by performing RNA interference (RNAi) assays in let-7 (null); col-19>GFP animals to knock down candidate molecular partners that are possible downstream targets for let-7 regulation. Given that col-19>GFP expression is abrogated in let-7 mutants, RNAi depletion of downstream targets will restore col-19>GFP expression. Identifying these target genes will enhance the understanding of the genetic interactomes of these miRNAs, their roles in developmental timing, and the broader roles of the let-7 family in cell proliferation and differentiation. Ultimately, this research will provide greater insights into the let-7 tumor suppressor regulatory pathways in human cancer.
KRISHNA PATEL
TESTING THE EFFECTS OF AN ARSA GENE MUTATION IN CAENORHABDITIS ELEGANS ON PARKINSON’S DISEASE
PATHOGENESIS
Parkinson’s disease (PD) is the second most common neurodegenerative disease after Alzheimer’s disease. PD primarily affects motor functions but also has non-motor symptoms. Common symptoms include tremors, rigidity, and impaired balance. The exact cause of Parkinson’s is unknown; however, certain genetic and environmental factors may contribute to its development. Genetic mutations linked to PD include genes such as GBA, LRRK, and PINK1, which are associated with
the formation of Lewy bodies—aggregates of the alpha-synuclein protein, a hallmark of PD. One gene mutation that may be linked to PD is arylsulfatase A, encoded by ARSA. Although some association has been observed, a definitive connection has not been established. This research aims to test the ARSA gene's potential association with PD using the roundworm nematode, Caenorhabditis elegans. We will use the nematode ortholog of the human ARSA gene, sul-2, to test for aggregate formation in C. elegans with RNAi knockdown of sul-2 and explore behaviors that might correlate with PD. The aggregates found in C. elegans would be reminiscent of Lewy bodies in humans, and worms display similar neurodegeneration behaviors. Given the controversial and uncertain association between ARSA and PD, this research will contribute to existing studies and evidence regarding the effects of ARSA on PD.
EVAN ZOU
INVESTIGATING THE ROLE OF snb-1 AND SNARE PROTEIN COMPLEX MUTANTS IN NEUROTRANSMITTER RELEASE AND PARALYSIS IN C. ELEGANS
Understanding how neurons communicate is vital for uncovering the molecular mechanisms that govern muscle control and neurological function. Neurotransmitter release, which enables synaptic transmission and proper neuromuscular signaling, is a key component of this process. The SNARE protein complex, particularly synaptobrevin (snb-1), is essential for vesicle fusion and acetylcholine release at the neuromuscular junction in the roundworm nematode, Caenorhabditis elegans. Botulinum toxin (Botox) disrupts this process by cleaving SNARE proteins, leading to paralysis. Due to safety limitations in handling Botox, this study examines genes that mediate the Botox response, using C. elegans mutants for snb-1 and potentially other SNARE components. We hypothesize that mutations in these genes will impair neurotransmitter release, helping to reveal the physiological and genetic mechanisms underlying recovery from synaptic disruption. Through locomotion assays, fluorescent imaging, and pharmacological interventions, we aim to evaluate both the extent of impairment and potential reversibility of nerve disruptions. These findings could enhance our understanding of synaptic plasticity and neuromuscular recovery, with broader implications for neurobiological and pharmacological applications.
ADVANCED RESEARCH:
TOVA AJAYI
UNDERSTANDING THE MOLECULAR MECHANISMS OF ADDICTION WITHIN THE SCOPE OF pde-4 AND DOPAMINE REGULATION
Addiction is a severe disease affecting many people worldwide, leading to significant personal, economic, and health concerns. It is caused by the compulsive use of substances that create pathological and physiological stress states, linked to dopamine signaling in neurons. Dopamine, a neurotransmitter, is regulated by factors including cyclic AMP and phosphodiesterase-4 (PDE-4) activity. To study PDE-4 function, we are using Caenorhabditis elegans, a roundworm nematode model organism with a simple nervous system and robust behaviors. This project aims to understand the molecular mechanisms of addiction within the scope of dopamine regulation through PDE-4 processes. We plan to observe the effects of pde4 mutation on neural signal flow. Similar experiments have shown shifts in swimming directions and changes in body size and mating. In addition to these behaviors, we will observe the effects of ethanol exposure on physical responses and the duration and nature of interactions between worms during developmental stages L3 and L4. Understanding the relationship between dopamine dependency and reactions after withdrawal is essential for comprehending addictive behaviors in humans.
DANIEL BRUCE
IDENTIFYING THE STATE OF DNA ACCESSIBILITY DURING NEMATODE DEVELOPMENT
Understanding how DNA accessibility is regulated in cells is a pressing question in biology. For a gene to be expressed, the DNA double helix must be open and accessible to enzymes that produce new mRNA transcripts. This project will use the roundworm Caenorhabditis elegans as a developmental genetic model organism to examine DNA accessibility on genes important for development. C. elegans have four larval stages, punctuated by molts, before becoming reproductive adults. Many genes, including lin-28, are crucial for regulating the timing of development, and their expression is switch-like, turning on and off. Although we know the genes responsible for developmental timing, we do not know the state of DNA accessibility. Current methods infer DNA accessibility by using RNA sequencing to identify when genes are transcribed and opened, but we lack a way to verify this directly. Our goal is to use sodium bisulfite to identify which DNA segments are accessible during development. Sodium bisulfite can irreversibly
convert accessible cytosine residues in DNA to uracil, which is detectable using sequencing methods. This project will employ DNA deep sequencing on the lin-28 gene in bisulfite-treated nuclei to find which segments are accessible and single-stranded, indicating they are currently being transcribed during larval development.
LANEY FROST
THE
EFFECTS OF NUTRITION AND EXERCISE-INDUCED STRESS ON MUSCLE
HEALTH AND MORPHOLOGY
Movement in animals is achieved through the essential function of muscles contracting and relaxing. Over an animal's lifetime, muscle health is a key factor in determining quality of life by directly affecting behavior, mobility, and response to stimuli. In humans, nutrition and diet also affect muscle health by impacting how muscles age. Understanding the link between nutrition, muscle health, and longevity is crucial because without healthy muscles, the body cannot function properly, leading to a decline in quality of life. Mitochondria are an important part of muscle cells, providing energy for contractions and aligning along muscle cell fibers. To study the effect of nutrition on muscle health deterioration, we are using the developmental genetic model organism Caenorhabditis elegans. We have a strain of C. elegans roundworms with muscle mitochondria labeled with green fluorescent protein (GFP), making them easy to visualize using fluorescence microscopy. This project will examine how GFP-labeled body wall muscles are impacted by the quality of food fed to the nematodes. Our goal is to understand the genes that influence muscle health in adults to improve quality of life.
AMELIE JOHNSON
UNDERSTANDING THE EVOLUTIONARY CONSERVED ROLE OF JNK IN THE NERVOUS SYSTEM
During cancer and tumor formation, terminally differentiated epithelial cells may detach, change morphology, and begin to divide rapidly during the epithelial-to-mesenchymal transition (EMT). This transition is crucial for developmental timing and cell differentiation, but can also contribute to cancer formation and treatment resistance. Several molecular pathways regulate EMT, such as the MAP-kinase signaling cascade, where 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 in humans. To investigate the role of JNK signaling in development and tumorigenesis, this project will study nervous system development in two genetic model organisms: the tunicate sea squirt (Ciona robusta)
and the nematode Caenorhabditis elegans. In C. robusta, the goal is to remove JNK function using genome editing via the CRISPR-CAS9 system. Elevated JNK expression has been found in neural progenitor cells, and it is expected that deleting and mutating JNK will impair nervous system growth. The project's initial steps involve designing guide RNAs to direct CAS9 to specific DNA genome sites to learn how JNK influences neural development and the EMT transition in cancer. In C. elegans, the goal is to characterize two JNK-positive worm strains and observe the role of JNK by exposing the worms to various environmental stresses. By investigating the role of JNK and the MAPK pathway in the development and processes of C. robusta and C. elegans, we hope to gain a better understanding of their role in EMT and potential crosstalk with other pathways.
LAYAH SHELTON THE NEUROPROTECTIVE POTENTIAL OF TURMERIC AGAINST ALZHEIMER’S DISEASE
This study aims to investigate the potential effects of turmeric on Alzheimer’s Disease (AD) neurodegeneration using the genetic model organism Caenorhabditis elegans. Turmeric is known for its anti-inflammatory and antioxidant properties in humans and has been suggested as a preventive measure against AD onset and progression. This project will expose C. elegans to curcumin, the active compound in turmeric powder, during early development to determine its effect on the nervous system. We are using a transgenic strain of worms that express the human Amyloid Beta (Aβ) protein in their neurons. A hallmark of AD is the formation of plaques due to Aβ protein aggregation and subsequent neuronal degeneration. Worms grown on plates containing turmeric powder will be examined for morphological and behavioral phenotypes. To assess the effects of Aβ accumulation, behavioral observations will be conducted. Fluorescence microscopy will be used to visualize and quantify Aβplaques in transgenic C. elegans to determine if turmeric exposure is protective. Image analysis will illustrate the differences in Aβ plaque accumulation between transgenic worms and control animals. The results of this experiment could provide insights into the potential neuroprotective effects of turmeric against Alzheimer’s disease pathology.
LEYA ALANI
DEVELOPING METHODOLOGY TO CHARACTERIZE
TUMOR
COMPOSITION IN C. ELEGANS
Reproductive cancer affects many people, leading to fertility issues and death. Understanding how genes that prevent tumor formation function is vitally important. To better understand genes that impact tumor formation, we use Caenorhabditis elegans, a roundworm nematode model organism with genetic traits like humans. One such tumor suppressor, PUF-8, is a conserved member of the Pumilio protein family and normally prevents tumor formation by controlling cell division in the germline of C. elegans. In humans, the absence of this gene has been linked to ovarian cancer. This project aims to understand how the loss of PUF-8 leads to germline tumor formation in C. elegans gonads. We observe the presence of germline tumors using the germline-specific fluorescent reporter fkh-6, which drives the expression of Green Fluorescent Protein (GFP). C. elegans are amenable to genetic analysis due to their quick life cycles, small size, and transparent bodies, allowing us to observe internal structures and examine where tumors grow. We have found that tumors grow in the spermatheca of C. elegans after the loss of PUF-8 by mutation and RNA interference. To quantify the size and cell number, we visualized nuclei in fixed cells using the DNA stain DAPI in germlines dissected from puf-8 mutants or worms treated with puf-8 RNAi. Ultimately, we aim to understand what influences tumor formation in nematodes to better understand the role of Pumilio proteins in human reproductive cancer using a candidate gene approach. Future work will examine how Pumilio-interacting genes affect puf-8 mutant germline tumor size in C. elegans
EMILY BEARDSLEY
CHARACTERIZATION OF AXON BREAKAGE AND REGROWTH IN CAENORHABDITIS ELEGANS ß-SPECTRIN MUTANTS
When neurons sustain damage, they must undergo adequate repair without causing further harm to the nervous system. Improper rehabilitation can lead to impaired neural function. Thus, offering a treatment that facilitates optimal recovery time and minimizes further injury risk is essential. This study aims to investigate defects in Dorsal D (DD) neurons in Caenorhabditis elegans with a mutation in the unc-70 gene, resulting in a lack of β-spectrin. This causes sporadic neuron breakage, allowing observation of neural outgrowth post-breakage. A systematic method for inducing commissure breakages using M9
was developed, and GABAergic commissures were examined under a Leica microscope during L4 to early adult stages. Recent efforts have focused on quantifying the number of breaks in the first DD commissure within the new population. The goal is to use this control data to assess glucose's impact on neuron breaks. Understanding the mechanisms of axon outgrowth after injury involves classifying and quantifying the number of breaks. Understanding incorrect axon guidance after injury can help develop new treatments that encourage proper axon outgrowth and prevent additional damage. This research could aid in developing therapies for neurodegenerative diseases and spinal injuries by promoting axon regeneration.
CLAIRE ELLISH
PARASITIC NEMATODES IN LUMINOUS MILLIPEDES
As a scientific community, we are constantly exploring how organisms interact, specifically how parasites communicate with their hosts. In southeastern Tennessee, many diverse types of millipedes contain parasitic nematodes either in their gut or translucent legs. We are investigating the parasite-host relationship among nematodes and various millipedes around the Baylor School woods to determine whether the relationship is positive or negative for the millipede. If the relationship is negative, the nematode would be killing the millipede, known as a pathogenic parasite. If the relationship is not harmful, they are nonpathogenic parasites. However, the nature of these relationships at the Baylor School is unknown. Our goal is to identify the species of nematodes present in various luminous millipedes and determine the prevalence of nematodes in each millipede species. We will collect various millipede species from multiple locations on campus, examine their translucent legs under a microscope, dissect the millipedes, and grow the nematodes until adulthood. Ultimately, we aim to understand the functions of these parasites and determine how they affect the health of their millipede hosts.
JULIA GARDNER
THE EFFECT OF PARAQUAT ON -SYNUCLEIN AGGREGATE FORMATION IN A NEMATODE MODEL OF PARKINSON’S DISEASE
Parkinson’s disease (PD) is the second most common neurodegenerative disease globally, with symptoms including tremor, pain, slowness of movement, and cognitive issues. While researchers have identified genetic and environmental factors that can trigger PD, many fundamental causes remain unknown. Exposure to environmental factors such as metals, pesticides, and herbicides has been shown to influence PD development. One such herbicide is Paraquat, which is
thought to increase the risk of PD, although the mechanisms are not fully understood. This research aims to use the genetic model organism Caenorhabditis elegans to characterize the effects of Paraquat on the aggregation of the misfolding-prone protein -Syn, a hallmark pathological component of PD. By observing transgenic expression of human -Syn in C. elegans body wall muscle and dopaminergic neurons, with and without Paraquat exposure and RNAi knockdown of common familial PD genes, we aim to identify a methodology to find a synergistic effect on -Syn aggregation between candidate genes and Paraquat exposure. This would show that Paraquat interacts with these genes to increase the risk of developing PD. Additionally, we hope to test these systems with and without the presence of TOR-2, a neuroprotective agent, to investigate its potential protection against Paraquat-induced -Syn aggregation.
ADDI GREENE
EIDONOMY OF LOCAL UNIDENTIFIED BIOLUMINESCENT SPECIES OF MILLIPEDE
Millipedes are arthropods that live as detritivores, breaking down decaying plant matter on the forest floor. They are segmented species with overlapping dorsal and ventral segments, using their “armor-like” segments and cyanide secretion as defensive mechanisms against predators. We isolated an unknown millipede species from decaying log samples collected on the campus of The Baylor School in Chattanooga, Tennessee, near the Tennessee River. These millipedes are typically found near water and damp areas, often by uncovering the forest floor and looking under the bark of decaying trees. To avoid disturbing the natural order, disturbed objects were returned to their original state. After collection, the millipede samples were brought to the lab and housed in a tank that mimics their natural environment. Uniquely, this species glows on the blue-green spectrum when exposed to ultraviolet light. Under regular white light, the millipedes are maculate and black with orange specks along the dorsal surface. We have characterized the morphology of the adult millipedes and their reproductive organs. Males have gonopods replacing a pair of legs on the seventh segment, while females have vulvae between the second and third segments. Observations of newly hatched juvenile millipedes have also been performed.
LUCI HEMPHILL
USING CRISPR TO IDENTIFY THE ROLE OF SUL1 IN CIONA METAMORPHOSIS
Sanfilippo Syndrome is a neurodegenerative disease caused by a genetic mutation that leads to the deletion of the intracellular enzyme heparan sulfatase, responsible for managing cellular waste. The absence of this enzyme results in neurotoxic waste accumulation, inhibiting brain function. Individuals with this disease experience rapid neurological degeneration, losing memory retention, fine motor skills, irregular sleep cycles, and immune function, leading to death or coma within ten to fifteen years. Due to limited research and few successful in-vivo trials, this study aims to replicate the Sanfilippo Syndrome phenotype in the model organism Ciona robusta, a tunicate species closely related to humans. Using CRISPR-CAS9 gene editing, we nullified the Ciona equivalent of the heparan sulfatase gene, inhibiting its production. Next-generation sequencing verified the success of the CRISPR-CAS9 nullification. Microscopy of mutant juvenile Ciona revealed that their body plan resembled larvae, unlike wild-type or lab-grown juveniles. This phenotypic difference suggests that heparan sulfatase is vital for Ciona metamorphosis and proper neurological function is essential for normal developmental timing in this species. We have also characterized the expression pattern of SUL1 in developing larvae using a SUL-1 green fluorescent protein transcriptional reporter.
EDIE HERNDON THE EFFECTS OF MECHANICAL AND CHEMICAL STIMULATION ON MEMORY
Memory is an invaluable component of life, as all organisms must respond to their environment by learning and recalling sensory inputs. Several substances, including caffeine, are known to affect the quality of memory and learning in animals. This study focuses on caffeine's impact using Caenorhabditis elegans as a model organism due to their short lifespan, predictable behavior, and invariant cell lineage. These nematodes exhibit a reversal response, which we are studying through a tapping mechanism that initiates this behavior. Our research aims to uncover the molecular mechanisms behind learning and identify the impacts of caffeine on these processes. We hope to find that extended caffeine exposure throughout their lifespan will elicit specific changes in behavior and learning. Additionally, we intend to identify the critical concentration of caffeine that can be considered harmful to C. elegans. By evaluating contextual learning caused by caffeine, our study will provide evidence of habituation and robustness of learning in these organisms.
MICHELLE
JIANG
CHEMICAL ANALYSIS AND SPECIES IDENTIFICATION OF A BIOFLUORESCENT MILLIPEDE
Millipedes are the largest class in the Arthropod subfamily Myriapoda, which includes centipedes, millipedes, symphylans, and pauropods. Unlike most other arthropods, millipedes do not possess external defense mechanisms like pinchers and stingers. Instead, they rely on their chitin-based exoskeletons and irritating secretions from their trunks for survival. As detritivores, millipedes recycle nutrients from decaying plant matter into materials essential for soil fertility and plant growth. In the Chattanooga River valley area, several millipede species exist, and we have focused on one found in rotting logs year-round that exhibits biofluorescence under ultraviolet light. The causes and reasons for this species’ fluorescence are currently unknown. We aim to identify and characterize this species on a molecular level using genomic DNA extraction, PCR technology, and Sanger sequencing. Additionally, we are working towards amplifying a part of the mitochondrial gene, cytochrome c oxidase subunit I (COX1), and using this sequence to determine the exact species of millipede by comparing it to published millipede phylogenetic trees. Moreover, we aim to identify and categorize the fluorescent compounds and defense secretions to better understand the relationship between this millipede and its environment.
ELLA GRACE LAZENBY
OBSERVING
THE
MOLECULAR MECHANISMS
OF GENETIC DISORDERS INVOLVING CONNECTIVE TISSUE USING THE MODEL ORGANISM CAENORHABDITIS ELEGANS
Ehlers-Danlos Syndrome (EDS) is a group of heritable genetic disorders that produce mutations in proteins or enzymes, affecting connective tissue. Different classifications of EDS are characterized by joint hypermobility, skin hyperextensibility, and tissue fragility. To understand the molecular mechanisms behind genetic mutations in diseases like EDS, we aim to observe the effects of genes associated with EDS using common orthologs from the model organism Caenorhabditis elegans and their impact on vulval morphogenesis. We used sqv-2, the ortholog for B4GALT7—a gene found in various classifications of EDS—and crossed it with a strain expressing let-805 fused to green fluorescent protein (GFP) to observe its effect on the vulval morphology of C. elegans. When performing molecular epistasis to create a genetic cross, we must understand the body morphology of our model organism, the mechanics of cellular biology, and its interactions. After performing the genetic cross, we plan to observe the interaction, if any, between the sqv-2 mutation and the LET-805::GFP strain. This will provide a better understanding of the specific gene's role in genetic disorders like EDS.
REYNA PARK
UNDERSTANDING
THE
ROLE OF MITOCHONDRIAL SIR-2.2 IN LONGEVITY
Organisms go through different developmental stages before reaching adulthood. Various factors influence development, and aging is a crucial stage in life. To understand these complex processes, Caenorhabditis elegans nematodes are used as a model organism to study molecular mechanisms in biological processes. Mitochondrial function significantly affects longevity. Mitochondria are essential for survival as they provide energy for all biological processes, regulate metabolism, and perform various other functions. Stress is one factor that impacts mitochondrial function. Mild mitochondrial stress through genetic or pharmacological interventions extends C. elegans lifespan, while severe mitochondrial dysfunction, such as disease, can arrest development or shorten lifespan. Mitochondrial sirtuins, including sir2.2, regulate biological pathways in development and are associated with longevity. Here, we demonstrate that sir-2.2 is localized in the mitochondria, suggesting it also plays a role in aging in worms. This research aims to discover the role of mitochondrial sirtuins in lifespan regulation by using 48 well longevity chambers called WorMotels. Ultimately, using C. elegans can enhance our knowledge of the correlation between this gene in humans and its effects on longevity.
GUSSIE SMITH
THE EFFECTS
OF DIETARY CHANGES ON NEUROLOGICAL FUNCTION AND HEALTH IN CAENORHABDITIS ELEGANS
This study aims to examine the relationship between diet and neurodegenerative disorders such as Alzheimer’s and Parkinson’s Disease using the roundworm nematode Caenorhabditis elegans as a genetic model organism. In worms, diet has been shown to influence nervous system health. We expect that worms grown in media with high glucose levels will experience a decline in dopaminergic neuron function. Using fluorescence transgenes allows us to visualize the health of dopaminergic neurons in the worms, enabling observation of the effects of diet on neuron morphology and related behaviors. Humans with neurodegenerative disorders experience a decline in quality of life, and we are furthering this research by investigating how this is affected by the inclusion of artificial food dyes. Here, we report our preliminary findings on how the nematode nervous system is affected by a diet high in glucose or Red 40, showing the effect of glucose on egg laying and dopaminergic neuron health. The long-term goal of this project is to determine how nervous system health is impacted by diets with high levels of glucose or artificial food coloring.
CORALIE VERVILLE
THE EFFECTS OF MOUTHWASH ON ORAL MICROBIAL BIODIVERSITY
The study of the oral microbiome is rapidly advancing due to its significant impact on overall health. The oral cavity hosts a complex microbial community that influences both oral and systemic health. Maintaining a balanced oral microbiome is crucial, as disruptions can contribute to various health issues. This experiment aims to collect, isolate, and characterize bacteria in the human mouth, focusing on the effects of mouthwash on oral microbial biodiversity. The study will span two weeks: one week as a control and the other involving mouthwash use. During the control week, participants will rinse with 20 ml of water each night, followed by a mouth swab the next morning. In the second week, participants will rinse with 20 ml of alcohol-free mouthwash, with swabs collected on Monday, Wednesday, and Friday of both weeks. Using deep sequencing of the 16S gene in DNA extracted from bacteria, we will be able to identify which species are present in the mouth microbiome before and after mouthwash usage. This experiment will provide insights into how mouthwash impacts the oral microbiome. It will expand our knowledge of which bacterial species are resilient to mouthwash and which are inhibited, revealing the potential effects on oral and overall health. The findings could have important implications for how mouthwash use influences the balance of oral microorganisms and, by extension, the body's broader health.
SEAN YOSHIDA
THE ROLE OF HOMEOBOX GENES IN SEA SQUIRT METAMORPHOSIS AND REGENERATION
In the study of neural regeneration, Ciona robusta presents a unique platform through the processes of neural genesis. This platform is a powerful tool for investigating neural regeneration and allows researchers to analyze processes and recovery from neural damage. Ciona, being an ascidian and a chordate, is the most closely related invertebrate to all vertebrates. This means that Ciona shares physical properties and processes with vertebrates, making it a valuable model organism for genetic studies relevant to vertebrates, including humans. Specifically, Ciona’s unique life cycle presents an opportunity to study neural genesis as the larval organism transitions into the adult form. The life cycle of Ciona involves somatic morphogenesis and nervous system metamorphosis, which includes the complete restructuring and creation of a nervous system for the adult organism. This creation of a new nervous system allows us to observe properties and processes like neural regeneration, making Ciona an excellent model organism. In this study, we plan to use CRISPR-CAS9 technology to observe and identify the functions of genes like Irx (a homeobox-containing transcription factor) and their roles in neural genesis in Ciona. It is currently unknown how many genes play important roles in the neural metamorphosis of Ciona. We plan to use qualitative assessments of developmental characteristics to evaluate the roles of tested genes.
RESEARCH I:
HARRISON HALEY
DEVELOPMENT OF VOICE RECOGNITION FOR ROBOT CONTROL
In the last few years there has been an increase in the use of robots for disaster relief. Most robots for disaster relief are controlled manually. The goal of this project is to use voice commands to control disaster relief robots. The user would speak into the computer to get the robot to do what the person says just based on what the computer hears. I have implemented a code that uses the microphone in the computer to hear what a person says and translates that into a phrase on the computer. This control phrase is read by another code to recognize certain words and conduct actions for a robot motor based on these words. Currently, this code converts what I say into a phrase on the computer. Also, I have created Arduino code for a motor, and I am working on the motor side of the project to integrate with the python code. I expect in the future to have a working robot that is fully controlled through voice commands so that I can run tests on a functioning disaster relief robot. This will help the problem of having only manual control of a disaster robot.
OWEN MCKENNA
QUANTIFICATION OF MICROPLASTICS WITH COMPUTER VISION
Microplastics are a serious problem in our industrialized world due to the toxic chemicals used to create them and their inablility to degrade, which causes them to build up in an environment. While it is known that having an environment full of plastic is certainly not a positive, their effects are very difficult to study without a means of determining quantitatively the number of microplastics at scale in a large experiment. While there are many different methods of counting microplastics such as spectroscopy or manual identification, we decided to focus on algorithmic analysis of images using the software library OpenCV due to inadequacies of other methods. By applying algorithms from the library and custom heuristics, I can detect evidence of microplastics from raw microscope image data. Over the course of the year, I developed and tested different algorithms to work in the general chain of image preprocessing thresholding (binarization) contour detection interpretation. The code is able to pick out the outline of a microplastic in a sample image, although false positives are a significant problem. This work and understanding of the specific challenges involved with algorithmic image processing lays the groundwork for the development of an automated method for counting microplastics in a real world environment. The completion of this project will enable significant further investigation of the growing problem of microplastics.
DAVID PUCHALSKI
IMPLEMENTING HAND GESTURE RECOGNITION SOFTWARE TO CONTROL DRONES AND ELECTRONIC DEVICES
Drones and other various electronic devices often require a remote control to operate from afar. This study plans to address if handsfree hand recognition software would be as effective as using a remote control. In this study, we plan to implement the use of hand gesture recognition software in order to provide a hands-free way to control electronic devices, more specifically drones. When we started developing the software, we expected to run into the problem of the software having trouble detecting the difference between hand gestures that look similar to a camera. So far, the code can detect the difference between several hand gestures, and it was a challenge to get the code to detect the difference between them. This project's final goal is to create a drone that can be fully operated from take-off to landing by just hand gestures using a camera, a radio transmitter, and a computer.
IVAN ZHENG
UTILIZING OPENCV TO DEVELOP A BACTERIA SENSOR THROUGH COLOR DETECTION UNDER FLUORESCENT LIGHTS
According to the CDC, nearly 1 in every 30 hospital patients receive a condition of what is known as 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 to multiple life-threatening diseases. However, in most cases, this is not the doctor’s fault, because bacteria are minuscule, meaning that doctors cannot tell if there are any infectious bacteria on their hands before undergoing medical procedures. In the past, there have been many research studies on bacteria detection in food by using AI algorithms like You Only Look Once version 4. In this study, I am using a method where bacteria can be detected by color determination. With OpenCV, any camera connected will detect certain color pixels. Currently, we use a mixture of glow-in-the-dark powder and water to simulate the bacteria appearing under the UV light. In the future, we hope to find a non-toxic and antibacterial substance that could react with infectious bacteria and change color that could be viewed under certain lighting. By having this code, we’ll be able to detect bacteria based on color change in the future. This code will ultimately be used in the future as we continue to research bacteria detection.
ORHUN BEKIRCAN
UTILIZING CO 2 DETECTION FOR HUMAN SEARCH AND RESCUE IN DISASTER ZONES
Natural disasters often leave victims trapped under debris, making rapid detection critical for survival. Traditional search and rescue methods, such as trained dogs and thermal imaging, have limitations, particularly in locating unconscious or deeply buried individuals. This study investigates the use of carbon dioxide (CO2) detection as an alternative method for identifying human presence. A portable, cost-effective system was developed using an Arduino Uno and an MQ-135 gas sensor to detect elevated CO2 levels produced by human exhalation. After calibration, testing showed that exhaling onto the sensor caused CO2 concentrations to rise from a baseline of approximately 400 ppm to peaks between 700 and 800 ppm, clearly indicating the presence of a human. The system provided real-time feedback and demonstrated a rapid response to nearby breathing, even without direct visibility. This method offers several advantages, including low cost, ease of deployment, and the ability to detect unresponsive or hidden victims. Future work will focus on improving detection range and minimizing interference from environmental CO2 sources. Overall, CO2 detection shows strong potential for enhancing search and rescue operations by providing an additional tool to locate trapped individuals more efficiently.
MICHAEL KINER
MAPPING UNKNOWN AREAS IN DISASTER ZONES USING A LIDAR MAPPING SYSTEM
Disaster scenarios often leave victims and rescuers in grave danger because of unknown areas in disaster scenarios; however, this can be fixed by mapping these rooms prior to entering. LiDAR, or Light Detection and Ranging, is a device that uses pulses of light to measure distances to objects. Using these distances, you can then make point clouds of the environment, which are 3D points in space. Multiple-point cloud data can represent a room. Many LiDAR systems can map a wall; however, not all are reliable, quick, and can map the inside of a room. In this study, I will implement LiDAR on a drone so that it can map the room. I have already calibrated and coded the distance measurement part of my LiDAR, as well as built my LiDAR circuit, and I have inputted my calibration formula into my LiDAR to obtain the accurate distance. The reason this gap in knowledge is so important is that mapping the inside of a room in a disaster scenario is an exceedingly difficult job and has not been done efficiently yet. In the future, I plan to produce a projection of my mapped room as well as the ability to map new rooms. More information on disaster scenarios could save lives by limiting misjudgment in a scenario with very little margin of error. This is why mapping the inside of a room in a disaster scenario is so important.
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. SLDs can impede one’s skills in written expression, reading, and math. Around 20% 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% of public school students receive accommodations for an SLD, meaning that 75% 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 low-cost, 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, or disorder of written expression, from handwriting samples. I plan to gather a training dataset of handwriting samples from Baylor students with and without dysgraphia which would require an IRB exemption due to the sensitive nature of the data collected. I will then train a machine learning model with this data using an open source library known as TensorFlow, utilizing convolutional layers for feature extraction and either recurrent or feedforward layers for classification. Finally, I aim to design a protocol for the use of this model as a form of 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.
LANDER MCNEELY
BUILDING A LOW SCALE IONIC THRUST ENGINE
Ionic propulsion uses a high voltage potential between an anode and a cathode to create a powerful electronic field that accelerates ionized air to create thrust. While this technology does not produce a lot of thrust, in space the longevity, reliability, and low cost make it valuable to space missions. Ionic propulsion has been used in past missions, but the technology can be applied to a lot more than it has been. For instance, it can be used to position satellites and increase the longevity of satellites. In this study, I created a basic ionic thrust engine to study the extent to which low scale ion thrusters can be used for numerous space missions, mainly satellite positioning. In my research I have learned that the weight to thrust ratio is important for the practicality of implementing this technology. By using a copper plated 3D printed part and thin sheet metal as my cathode and anode, I have reduced the weight significantly. I expect to be able to calculate the thrust produced by the engine and to use this data to research the practicality of this technology on a satellite. Ionic propulsion is the future of space travel because of its cost effectiveness, versatility, and efficiency.
GRACE CHEN
DESIGNING AN AI POWERED LIP HEALTH DIAGNOSTIC SYSTEM
In the field of medical image analysis, deep learning techniques have shown great potential in diagnosing various health conditions. Existing studies have demonstrated the effectiveness of machine learning in oral health assessment. However, there is a lack of in-depth research specifically focused on accurately identifying and classifying different lip conditions. This research aims to fill this gap by applying deep-learning methods to lip - condition diagnosis. The research methodology involves the use of computer learning, specifically Convolutional Neural Networks (CNN). The Python programming language and Google CoLab framework are used for model development, data and language management. A wide variety of lip image datasets have been collected from medical databases, online repositories, and clinical resources. Standard metrics such as accuracy and precision are used to evaluate the model. At present, a certain amount of data collection has been collected and the part of model training and testing is being carried out. Preliminary experiments suggest that the deep learning model will show promising results in accurately identifying and classifying lip diseases. It is expected to be superior to traditional diagnostic methods in terms of convenience and efficiency, enabling better early detection and management of lip health problems. This study helps to apply deep learning techniques to the diagnosis of lip health, thereby improving the overall awareness and health level related to lip health. Future research will likely focus on expanding the dataset, further optimizing the model, and comparing to more traditional diagnostic methods in a real-world clinical setting.
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. After fires and other disasters, 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. Currently, firefighters have twice the likelihood of dying from cardiovascular disease compared to an average civilian. Within natural disaster zones, there are many collapsed or toxic areas that are deemed too dangerous to search for the sake of the rescuer’s health. The average search lasts
7-14 days depending on the size and scale of the disaster before the searchers give up. A human 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. So far in this process I have taken thermal images of objects and people around my school to use as data in my CNN. I have created a functioning CNN for human detection tested on human and non-human images. 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. Limiting the exposure time of the firefighters is important for lowering their chance of getting cardiovascular disease from less exposure to the toxic chemicals. Using a drone will bring down the search time needed for the first search, reducing the number of deaths from lack of time.
ROWAN LANGSTON
POSE RECOGNITION USING POSE ESTIMATION AND MACHINE LEARNING
With a quickly growing population, safety becomes more and more important. The population would benefit from a system that uses machine learning to detect dangerous situations. By detecting body positions that would match that of being at risk of harm, a program could prevent possible disasters. My project aims to make steps in this direction. I use OpenCV as a computer vision library and mediapipe for tracking figures through machine learning. Even if a program like this is not foolproof, any steps towards making the world a safer place is a good step to take. In crowded settings, someone could experience health issues that require medical attention but not get the help they need in time if the people surrounding them don’t take immediate action. If there were overhead cameras that could detect this kind of thing and notify authorities, a life could potentially be saved.
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 arti-
ficial 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% in less than 20 epochs without overfitting. I am using galaxy images from the SDSS images of selected RC3 galaxies for training and testing data for the neural network. TensorFlow was used through Google Research Colab to create the CNN. So far, my CNN 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 current goal is to fix the issue of overfitting by adjusting the CNN layers. In the future, I plan on adding another galaxy type to be classified, irregular galaxies, or supplementing the process by adding another neural network. My research can help make galaxy classification for sky surveys more efficient and help deepen scientists’ understanding of galaxy morphology and creation.
KRISTIN SPYKERMAN
USING ARTIFICIAL
INTELLIGENCE
TO SOLVE MATH WORD PROBLEMS
Major breakthroughs in AI in the past years make the topic of Mathematical Word Problem (MWP) solvers very important, as AI programs have had significantly lower success rates in relation to MWP’s than other tasks. In fact, a study at Stanford suggests that state of the art MWP’s are only about 36% accurate. My research project aims to create a program capable of solving elementary level mathematical word problems. After much research into Large Language Models, I discovered that due to their lack of accuracy in solving math as well as how difficult they are to create from scratch, I needed to figure out a different approach. I discovered that I could use the order of words in a sentence to solve a certain type of MWP with high accuracy. By parsing word problems and assigning each of them a variable that will then be placed into an equation, my program can solve a simple MWP of a format similar to “Johnny has six apples. If he give Mary three apples, how many does he have?” While the use of this strategy with extensive if/then statements can cover a wide array of MWP’s, using artificial intelligence ultimately has the potential to solve a much wider array of word problems. Therefore, future research would harness the power of AI into creating a python program for each individual
word problem, an idea explored in Program Aided Language models, which would proceed to solve with incredible accuracy. All of this is significant as it can be a helpful tool in the classroom, but also a building block for creating something more powerful that can solve MWP’s which even humans have not figured out how to solve.
KUZEY TUKEL
DESIGNING A 3-D ENVIRONMENT FOR ROBOT NAVIGATION AND PATHPLANNING
Currently, robots are used in every facet of our life: in assembly lines, in storage facilities and even in cars. However, robots have a hard time planning movements on their own. Humans can help the robots by setting a predetermined path for the robots to follow. With the help of Virtual Reality (VR) humans can get a better understanding of the environment that the robot has to traverse through. My goal is to design a 3D environment in the Unity Game Engine to help robots navigate. Specific points can be inputted and the code will calculate the path the robot needs to take to go through the points as accurately as possible. I will use VR to enhance the experience and make it more immersive. The research is being done primarily with the Unity 6 Game Engine. The Engine uses C# as its default programming language. The calculations for the pathfinding will be done using splines, specifically Bézier Curves. I used Autodesk’s Fusion 360 to create the 3D models of the Field and the Robot. In terms of VR, I’m using the Meta Quest 2 as my headset. The robot can move through human input with the WASD keys. Currently I am working on a point input system. The current method of inputting coordinates is using a mouse but I plan on changing it to the VR Hand Controllers. In the future, I hope people can implement my results onto actual robots elsewhere in the world.
BRUIN WEBSTER DEVELOPMENT OF MODULAR SENSOR PLATFORMS FOR UAVS
Drones have been vital tools in a variety of industries; however they are limited by their singular uses. In this study I plan to construct first a smaller-scale way to have modular components and sensors attached to a UAV, depending on the task needed. While many drones have been constructed to do specific jobs, such as agriculture, thermal imagery, law enforcement, and more, modularity has been ignored, resulting in super costly multi-drone fleets that one may be able to do with something as simple as an ability to swap out parts. However, this small-scale idea would have the ability to show proof of concept and then allow for a more advanced UAV, capable of carrying
more payload and sensors for more data gathering. I used a Raspberry Pi microcomputer as the brain for the operation, communicating with the camera and sensors to be analyzed later. The module was to be made of PLA, which is a printable plastic that is liquid when heated until cooled. With the combination of these tools, the drone was able to take pictures during flight. Having more modules will allow for quicker transfer of data and more utilitarian use for drones. This data will then make it more cost effective for completing many tasks instead of the one the drone was designed to do. In conclusion, this would allow a new era of data collection and implementation of a singular drone that could do it all, no matter what is thrown at it. In doing so, UAVs would be more available to civilians and business owners and transition our world into the future and beyond.
ALEX BAILEY
THE DEVELOPMENT OF A ROBOTIC HAND FEATURING SIX FINGERS
Because of the lack of innovation in the field of prosthetics, their design and functionality has been the same. To determine the innovation that could be found in this field, I studied a robotic hand able to mimic an artificial hand. This hand allowed me to study and test the workings of general mechanisms in the field of robotic attachments. It features custom metal pieces which ensure any one phalanx can move and fold inwards or outwards respectively, or as gauged from its command. This is an important aspect of the hand, as it provide examples of ways to manipulate the whole finger in one action. I decided that a sixth finger would improve this aspect of robotic attachments. My goal with this research is to understand how robotic end effectors work, so that I may develop one for a body part in the future. I was able to design a mechanism that utilizes six servo motors to control six individual fingers. These servos are coded, and in a base to hold them all. Rather that have just a replacement body part, an improvement could be better, and there are more uses found when not limited to just five fingers. In my future research, I want to have all six servos developed and working, as well as continue to work on further material for the arm.
JERRY MA
NEW WINGLET DESIGN FOR THE BOEING 757
In the last 40 years, wingtip devices have captured the attention of many aeronautical engineers in their effort 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 just 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 understand 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, the airfoil for the testbed has been designed in CAD and fabricated with a 3D printer. Basic performance data from the wind tunnel was also collected. In the future, I hope to use the testbed to research and analyze different winglet designs. This research will assist in the efficiency of aircraft and save future air travel costs.
BRANDON OAKES DEVELOPMENT OF A MECHANICAL SHREDDER FOR A 3D PRINTER FILAMENT RECYCLING SYSTEM
3D printing is increasingly common in homes, businesses, and schools, but its growth has led to a surge in waste, including leftover filament, failed prints, and support structures. This research addresses the challenge of managing this waste by developing a cost-effective recycling system that converts 3D printed waste into usable filament. The research fills a gap by focusing on affordable solutions to reduce financial barriers to 3D printing adoption. Central to this research is the creation of a system with three main components: a shredder, a filament maker, and a filament spooler. Initial efforts focused on building a test bed to assess different blade shapes and materials for the shredder, utilizing a high-torque motor due to the high strength needed to break down plastics. Preliminary results include the successful design and testing of a small-scale shredder prototype, capable of processing pieces up to 3 cm3. The research seeks to identify the best combination of blade shape, material, and configuration for efficient and safe shredding. The significance of this research lies in its potential to enhance the sustainability and affordability of 3D printing, particularly for budget-constrained communities. Future work includes developing a full-scale shredder, optimizing the pellet-to-filament process, and finalizing the system into as close to a 100% yield recycling solution. This project contributes to sustainable manufacturing and offers practical implications for reducing 3D printing waste and costs.
GRADY ROBBINS
PERFORMANCE TESTING OF 3D PRINTED CARBON FIBER GEARS
3D printing has been around since 1980, and it has evolved considerably since then. You can now print massive houses using a cement printer, or you can print detailed objects. In this study I am testing the strength to weight ratio of a gear by using the carbon printer to see how the carbon filament holds up in biking gears. The reason for studying this is to minimize weight on a bike. In the competitive side of the sport, extra weight will make you slower, so by making the small objects lighter it will make your times go down. By making the gears out of carbon fiber, it will make them lighter but will keep the strength up. I am making two gears and putting them in a test bed. The test bed has two mounts to hold two motors. One of the motors will be spinning and acts like someone pedaling and the other one will not be powered. My hypothesis is that the gear’s teeth may wear down fast however, the gear’s integrity will be fine. In the future I want to run tests with different gears to see how strong I can make them. Then I want to fit the most optimal gear to my bike so I can field test them. I also want to make other parts that involve around bikes like brake levers, cranks, and other small parts in a bike.
AIDEN SAADEH DEVELOPING A FRAMEWORK TO EXPEDITE FLIGHT SOFTWARE DEVELOPMENT
Developing flight simulator software is time consuming, complicated, and expensive. A facet of flight simulator development is the flight model which determines how an aircraft will fly. Creating a set of tools that simplifies and speeds up the process of developing the flight model would expedite testing, reduce costs, and lower the barrier of entry into the flight simulation field. Other solutions each have issues such as prohibitive price, unrealistic simulation, difficult usage, and obsolescence. The goal of this project is to create a set of tools and systems for the Unity engine that will reduce the development time of an aircraft’s flight model. The current goal is to maximize the accuracy of the tools by comparing simulated flight performance with actual flight performance. Currently, I have created various tools that allow for suspensions, control surfaces, wings, and a debug menu. The debug menu provides valuable information, while the suspension tool simulates an aircraft’s landing gear. The wing tool allows the creation -in real time- of any wing, and the control surface tool allows articulation of wings to mimic control surfaces on actual aircraft. I’ve used these tools to simulate a Cessna 172 which can be flown with realistic lift and drag characteristics. Furthermore, these tools allow any (subsonic, single piston engine) aircraft’s flight model to be simulated quickly, which allows developers to quickly prototype their flight software and expedite their development.
HENRY WANG
ELECTROMAGNETIC SUSPENSION SYSTEM 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 provides vibration that can simulate actual road conditions. Programming of the motor will present the amount 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.
ERIC ZHENG
DEVELOPMENT OF A CENTRAL UNWINDING SPOOL FOR UTILIZATION IN 2-DOF CABLE ACTUATED SYSTEMS
Many mechanical designs use cable-actuated systems to facilitate force transmission and motion using spools. Despite their widespread use, existing pulley designs can run off the side of the pod, adding additional components to the system’s control. This project aims to address this issue by developing a new pulley spool prototype that runs the string out of a center coaxially driven pod. The experimental approach involves design iterations, reviewing pre-existing control methods, and developing one that fits the custom spool pods. Data collected from further experimentation will provide a comprehensive understanding of the prototype's performance under varying loads and operating conditions for optimized pulley designs in real-world applications. The objectives of this project are to develop a custom coaxially-driven central unwinding cable spool and use a simple PID controller to drive all four pods individually. Currently, a motor and pulley mount is in the design phase, tailored specifically to fit over the 3D-printed frame mounts. This new mount aims to ensure com-
patibility with the existing structure while maintaining stability during operation. The motor and spool setup will be mounted on top of the extrusion, enabling controlled movements and reliable testing capabilities. Once complete, the test rig will serve as a versatile platform for various applications, emphasizing ease of use, adaptability, and precision in its design and assembly. The future objectives include designing a new control method that can control the rotation and translation of an end effector.
CALEN HAWK
THE DEVELOPMENT OF THERMAL CAMOUFLAGING TECHNOLOGIES
Camouflage was first used and developed in France in 1914. Throughout the history of camouflage, many various patterns and designs have been used to conceal and distort the shape of the human body. While most camouflage patterns work, especially when used in environments for their intended purpose, they all fall short of true camouflage. Traditional camouflage, when used correctly, successfully conceals the person from the human eye by blending in with its surroundings, but you cannot hide from different methods of detection like night vision or thermal imaging. However, advanced technology is allowing the production of materials that can mask and change a human's heat signature to blend in with the surrounding temperature of the environment. Not many examples of this technology have been publicly introduced, but there are many different ways to make a thermal camouflage possible. My research started with photographing a Mylar blanket in front of a person utilizing a FLIR thermal camera, which tested the properties of human concealment without alterations. I then made a testbed with a heat source and nearly sealed chamber that allows hot air to flow from one end of the chamber to the other end of the chamber where the Mylar is held in an airtight fashion against the air chamber. The subsequent tests involved pointing the FLIR thermal camera at the outside of the Mylar and recording the temperature over a five minute time period. More layers were added after each test and graphed using Excel to represent the effectiveness of multiple layers of Mylar. The future goal of this research is to create a lightweight thermal camouflage that fills the current gap in combating new multi-spectrum technology.
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 (m ; first tone; means mother) and (m ; third tone; means horse). 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
THE DEVELOPMENT OF A LOW COST 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. Thus far we have characterized two magnets which we will use to build the computer. We have also begun modeling the computer’s frame, which will be 3D printed. A 3D printed housing will be the most effective because we must avoid metal when designing this computer to avoid interfering with our magnetic field. 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 opensource community.” Such a community would provide resources for anyone to learn how to build a quantum computer, increasing public awareness of quantum computing.
ANNA STODDARD UTILIZING THE NUCLEAR MAGNETIC RESONANCE ARCHITECTURE TO CONSTRUCT A SMALL-SCALE QUANTUM COMPUTER
Quantum computers are at the forefront of the current technological revolution. However, the computers’ high-level computation remains largely inaccessible due to their steep price tag, limiting progress in this emerging field. Small-scale single to multiple 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, we plan to control qubits with this architecture and to determine the entanglement efficiencies of available half-spin solutions which range from transcrotonic acid to water. We have sourced the magnets and measured the magnetic field strength to map their homogeneity. We have also secured several half-spin solutions, NMR 5 mm test tubes, and a radio frequency generator. The Larmor frequency of our system has also been calculated for several half-spin solutions, such as water and phosphoric acid. Currently, we are designing the 3-D printed holding structure and coil bobbin. Future work will include measuring the emitted frequencies and developing corresponding quantum gates to encode information onto the particles. Our work with these small-scale systems could introduce affordable quantum computers to schools and communities, broadening the accessibility of this groundbreaking technology for educational and experimental purposes.
ALISHA CHANDRA
BUILDING A CONVOLUTIONAL NEURAL NETWORK FOR DIAGNOSIS OF DIABETIC RETINOPATHY/MACULAR EDEMA AND DIFFERENTIAL DIAGNOSIS BETWEEN WET AND DRY AGERELATED MACULAR DEGENERATION
Diabetic retinopathy and age-related macular degeneration (AMD) are two of the most prevalent eye diseases today: one in three of the 285 million adults with diabetes have diabetic retinopathy and 170 million adults across the globe are affected by one of the two forms of AMD (wet or dry). Diabetic retinopathy is detected through the presence of microaneurysms, hemorrhages, and exudates (abnormal masses of fluid and cells). Although there is no cure for either diabetic retinopathy or AMD, early diagnosis of these diseases can prevent their progression, and machine learning, a subset of artificial intelligence, is being increasingly used to expand access to diagnoses. This project creates a convolutional neural network for feature selection and prediction for one of four categories: Diabetic Macular Edema/Retinopathy, Wet AMD , Dry AMD, and Normal, and has an accuracy of 85.1 percent on average, with higher and lower accuracies for specific categories. The model was built using a publicly available dataset of 20,000 OCT images split equally between the four categories, and supplemented with images from the charts of SERA, a local ophthalmologist office. The neural network itself utilizes convolutional, pooling, dense, and batch normalization layers. This network is geared towards primary care providers and optometrists who have access to OCT imaging to provide a preliminary diagnosis to their patients, increasing early diagnosis overall.
TATE HARRISON
IMPROVING THE ACCURACY AND RELIABILITY OF ATTITUDE CONTROL SYSTEMS IN CUBE SATELLITES
A Cube Satellite, or CubeSat, is a cube with a side length of 10cm sent into Low Earth Orbit (LEO) to run tests in space. CubeSats often use attitude control systems to orient themselves in space to face a certain direction. The most common type of attitude control system uses reaction wheels, which are wheels that spin in one direction on certain axes to rotate the entire CubeSat in the opposite direction using the conservation of angular momentum. The CubeSat attitude control system in this project uses reaction wheels in a low-friction test environment to allow accurate tests simulated in space to fur-
ther CubeSat research. Using a previously implemented air-bearing as well as wireless serial communication from an on-board IMU, real time CubeSat X, Y and Z angle differences were read by an external computer running Megunolink software. The efficiency and effectiveness of reaction wheels fabricated from materials with differing densities was then compared to find the optimal material. Tests were carried out along the X axis with PLA, stainless steel, and brass reaction wheels at differing start angles to find the fastest converging system. The findings proved that denser reaction wheels performed better at larger start angles, while less dense reaction wheels performed better at smaller start angles. This data can now be used to optimize future reaction wheels that will benefit CubeSats in space. Research is now being furthered by creating an expanding reaction wheel that can automatically change its moment of inertia based on its needs for maximum efficiency. Initial tests with an expanding prototype have displayed a roughly 16% increase in moment of inertia with only a small redistribution of mass.
RESEARCH I: ENVIRONMENTAL
LILY HARTLEY
UNDERSTANDING MAINTENANCE OF COLOR POLYMORPHISM IN SOUTHERN ZIG-ZAG SALAMANDERS
Color polymorphisms within a population represent an evolutionary conundrum since selection and drift have the tendency to remove variation from populations. The maintenance of these color polymorphisms could be explained by frequency dependent selection and predation, in which polymorphs benefit from either a rare form advantage (looking different) or common form advantage (blending in). Salamanders act as vital links to trophic cascades in North American forests and have appeared to maintain polymorphic populations in nearly twelve species. The Southern Zig-Zag salamander (Plethodon ventralis) is characterized by a striped or unstriped dorsal pattern on individuals. Inheritance of dorsal striping appears to be population dependent and can be maintained through epistatic, polygenic, or classical Mendelian inheritance. In this study, we attempt to apply an evolutionary genetic framework to four years of observations of zig-zag salamanders in Baylor Woods. Future work will expand sampling to further research the maintenance of polymorphisms in zig-zag salamanders.
CAROLINE CHASE and RUBY DOZIER
SEASONAL SHEDDING FREQUENCY AND MOLECULAR IDENTIFICATION OF A SALAMANDER PARASITE, METAGONIMOIDES OREGONENSIS
Parasites can affect the evolutionary trajectory of hosts because they regulate host density, alter host behavior, can affect reproduction, gene flow, and increase susceptibility to other stressors. Digenetic parasites utilize multiple intermediate hosts to complete their life cycles. The first intermediate host is usually a snail, then the second intermediate host is a fish/salamander, then the final definitive host is often a bird or mammal. Metagonimoides oregonensis is a digenetic trematode using Elimia proxima as a first intermediate host and Desmognathus amphileucus as a second intermediate host. While fitness consequences of metacercarial loads on larval salamanders have been explored, it has yet to be evaluated how seasonal shedding rates correlated with larval development. Our research attempts to establish seasonal shedding rate of Metagonimoides oregonensis cercaria from Elima proxima. Additionally, we seek to molecularly analyze M. oregonensis and conduct longevity assays to understand the correlation between metacercaria infection counts and seasonal shedding patterns. The results of this study will provide vital insight into the dynamic and complex relationships between hosts, other hosts, and the evolution of digenetic parasites.
COLE LOOKABILL and LOUIS ZHAO
ASSESSING
THE ACCURACY OF NICHE MODELING ON THE DISTRIBUTION OF ZIG-ZAG SALAMANDERS IN BAYLOR WOODS
Niche modeling is a powerful tool in ecological and environmental research, enabling the prediction of species distributions based on environmental variables and habitat suitability. This is particularly useful for species in need of conservation. Amphibians have faced global declines over the last century due to a plethora of anthropogenic activities. As a result, niche modeling has become a common place for predicting current and future species distributions. One major challenge, however, is field verification of predicted suitable habitats— particularly for small-bodied amphibians like the zig-zag salamander (Plethodon dorsalis), which rely heavily on microhabitat conditions to maintain physiological homeostasis. A high-resolution Maxent ecological niche model was produced for zig-zag salamanders in Baylor Woods. Our project seeks to assess the predictive output of this model by sampling suitable and unsuitable habitats. We first generated spatial polygons of Baylor Woods identifying habitat with high predicted suitability and low predicted suitability. We then randomly sampled ten points from each generated polygon. Each point was sampled and the number of salamanders found was recorded. Our
results indicate the predictive output from Maxent performed adequately but largely reflects points used in our training data. The results of this study highlight both the capabilities and challenges of small-scale ecological niche modeling for small-bodied amphibians.
BRODY BROOKS
SEXUAL DIMORPHISM IN BIOFLUORESCENCE OF SALAMANDERS IN THE EURYCEA SPECIES COMPLEX
Sexual dimorphism refers to phenotypic or behavioral differences between males and females of a species, often shaped by sexual selection and mate choice. While studying sexual dimorphism is straightforward when traits are visibly distinct, evolutionary differences in visual perception among taxa may obscure certain patterns, necessitating advanced technological approaches for proper characterization. Salamanders exhibit heightened sensitivity to blue light, and recent evidence suggests biofluorescence is widespread among amphibians. The functional significance of biofluorescence in salamanders has been hypothesized to include roles in intraspecific signaling, predator deterrence, and mate selection. This study aims to assess sexual dimorphism in biofluorescence across three lineages of twolined salamanders (Eurycea bislineata complex). Using blue light to stimulate fluorescence and yellow-filtered goggles to visualize emitted wavelengths, individuals of both sexes will be photographed in a controlled dark-box environment. Molecular techniques, including DNA sequencing, will be employed to confirm lineage and sex in cases lacking distinct secondary characteristics. Fluorescence intensity and distribution will be compared across sexes and lineages, while genetic data will further inform lineage distributions and zones of secondary contact within the greater Chattanooga area. The findings of this study will provide high-resolution insights into biofluorescence patterns and their potential evolutionary significance, offering a foundational framework for future investigations into the functional role of fluorescence in amphibians.
SHIRLEY HUANG
ASSESSING GENE FLOW AND SPECIES LIMITS ACROSS COMPLEX GEOGRAPHICAL BARRIERS
Gene flow refers to the movement of alleles within and between populations. High levels of gene flow tend to homogenize allele frequencies, while its absence can drive speciation. Barriers to gene flow can arise due to geographical distance (isolation by distance), large physical barriers (isolation by environment), and limited dispersal ability across complex microhabitats (isolation by resistance). This study investigates the genetic distribution of the zig-zag salaman-
der complex (Plethodon dorsalis and Plethodon ventralis) across distinct geographical features in Tennessee, including the Cumberland Plateau, Tennessee River, and Sequatchie Valley. To assess gene flow patterns, we will collect tail tissue samples from zig-zag salamanders at various sampling sites throughout the state. DNA will be extracted using the Qiagen DNeasy Blood and Tissue Kit, then quantified, normalized, and prepared for double-digest restriction-site associated DNA (ddRAD) sequencing. Bioinformatics and population genetics will then be carried out to infer gene flow within and between populations while also identifying species limits across complex geographical features. These results will provide insights into how geographical structures influence gene flow for dispersal limited species.
ANGELINA FALCONE DEVELOPING A QPCR MULTIPLEX ASSAY FOR CHARACTERIZING FISH COMMUNITIES IN THE CUMBERLAND PLATEAU
Freshwater fish populations in the southeastern United States have undergone significant declines in recent years due to a combination of factors, including climate change, parasitic infections, and anthropogenic disturbances. One species that has experienced severe population declines is Chrosomus saylori (Laurel Dace), an endangered freshwater minnow listed as such since 2011. This species is currently restricted to only two streams within the Cumberland Plateau. To assess the presence of Laurel Dace in these aquatic systems, we will employ environmental DNA (eDNA) analysis, a non-invasive and efficient method for detecting species by sampling genetic material left behind in the environment. Following eDNA sample collection, we will utilize multiplex quantitative polymerase chain reaction (qPCR) to analyze the samples. This technique enables the simultaneous monitoring of multiple species using species-specific probes, which have been validated through in silico testing. In addition to detecting Laurel Dace, we will apply multiplex qPCR to survey coexisting species, including invasive sunfish, Blacknose Dace (Rhinichthys atratulus), and White Sucker (Catostomus commersonii). The findings of this study will provide valuable insights into suitable habitat conditions for potential genetic rescue efforts aimed at preserving Laurel Dace populations and informing conservation strategies for their reintroduction into appropriate stream environments.
RUSSELL BOYD
DETERMINING THE SPECIES AND SPATIAL PREFERENCE OF OPHIDIOMYCES OPHIDIICOLA ON BAYLOR’S CAMPUS
Ophidiomyces ophidiicola is the etiological agent of Snake Fungal Disease (SFD), a pathogenic fungus responsible for significant declines in snake populations across the United States and parts of Eurasia. Mortality rates among infected individuals can reach approximately 40%, posing a substantial threat to snake biodiversity. This study aims to characterize the spatial distribution and species-specific prevalence of O. ophidiicola to deepen our understanding of its ecological dynamics. To achieve this, cover boards will be utilized to facilitate the collection of biological samples from infected snakes. Two distinct sampling approaches will be employed: culture-independent and culture-dependent methods. Culture-independent swabs will undergo quantitative polymerase chain reaction (qPCR) and DNA sequencing to detect O. ophidiicola and assess the composition of the skin microbiome. Culture-dependent swabs will be used for challenge assays and microbial culturing to evaluate potential inhibitory interactions within the microbiome. The findings of this study will provide critical insights into the ecological niche of O. ophidiicola, including its host preferences and environmental distribution. Additionally, identifying components of the snake microbiome that exhibit antagonistic effects against the pathogen may inform future conservation strategies aimed at mitigating the impact of SFD and preserving snake populations within their native ecosystems.
HELENA GARCIA NIETO
ASSESSING THE GENETIC DIVERSITY OF LAUREL DACE IN HUMAN CARE USING MICROSATELLITES AND eDNA
Genetic diversity sustains variation in a population which can counteract the effects of selection and drift. Small populations in decline typically display decreased genetic diversity and obtaining tissue samples for genetic assessment is challenging for federally listed species. Environmental DNA (eDNA) sampling offers a powerful, non-invasive tool for monitoring biodiversity and has recently been proposed as a tool for assessing the genetic diversity of species in human care. This study attempts to design, test, and implement a microsatellite program from eDNA to assess and monitor the genetic diversity of the federally Endangered laurel dace (Chrosomus saylori) using eDNA techniques. Water samples were collected from captive tanks at the Tennessee Aquarium Conservation Institute, and DNA was extracted
using a modified DNEasy PowerWater protocol, amplified with PCR using 12 specific SSR primers, and verified using gel electrophoresis. Results showed variability in DNA concentration (ranging from -3.2 g/mL to 69.4 g/mL) and purity (260/280 ratios from 1.32 to 1.88), reflecting differences in sample quality and extraction efficiency. Despite some inconsistencies, we successfully identified genetic markers crucial for assessing population structure and diversity. These findings support the use of eDNA and microsatellite analysis in conservation genetics and offer a baseline for monitoring Laurel Dace populations in human care and potentially in the wild.
HUNTER SHAW
THE EFFECTS OF SECONDARY CONTACT ON TELLICO SALAMANDERS (PLETHODON AUREOLUS)
Secondary contact occurs when previously isolated species occur sympatrically due to changes in geological or geographical conditions. Four possible consequences of secondary contact are hybridization, competitive exclusion, stable coexistence, or a mix of the three. 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. Plethodon aureolus, Plethodon teyahalee, and Plethodon shermani show some elevational preferences but have a broad contact zone at middle and higher elevations. Additionally, strong morphological similarities and similar microhabitat utilization make putative species assignments in the field challenging. We collected tissue samples from individuals of each of the three species in the Bald River Gorge Wilderness, the Citico Creek Wilderness, and the Cherokee National Forest and used nuclear and mitochondrial DNA gene sequencing to infer phylogenetic relationships and genetic composition of individuals in the study area. The results will evaluate the historical, current, and future effects of secondary contact on salamanders in Southern Appalachia and their associated conservation implications.
SYDNEY DOUGLAS
ASSESSING pH AFFINITY OF HOST-ASSOCIATED AND FREE-LIVING BACTERIA
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 factor that may influence mi-
crobial colonization patterns. The aim of this study is to investigate the relationship between Southern Zig-zag salamander skin pH and bacterial colonization patterns, with a focus on whether colonization is driven by pH affinities of bacteria. Samples of bacteria found on the skin microbiome were collected from 5 individual Southern Zig-zag 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, phenotypic 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 of pH. The results of this study could explain how chemical characteristics of secretory compounds, rather than bioactivity, shape the amphibian skin microbiome through consistent processes acting on stochastic dispersal.
GABRIEL COSTILOW
ABIOTIC PARTITIONING OF THE EURYCEA BISLINEATA COMPLEX
Species ranges are an outcome of evolutionary history, biotic interaction, and abiotic factors. Three distinct lineages of the Eurycea bislineata complex have overlapping ranges in the Chattanooga area, creating a large swatch of secondary contact. This theorized to have happened to three separate linages of the Eurycea species complex, Eurycea cf. wildrae (C+F), Eurycea cf. aquatica (G+H), and Eurycea cf. bislineata (M). These species/lineages can occur together in a habitat and the presence of one another is hypothesized to influence the behavior of one another, via interspecific competition. Niche Modeling is a powerful ecological tool used to predict the distribution of species and understanding their environmental limitations. In this project we used the Maximum Entropy (Maxent) modelling. Maxent is a machine learning predictive method that considers all the data that is not accounted for in the dataset. We used historical records of each lineage and abiotic variables to determine important predictors for lineage detection. Additionally, we calculated probability of secondary contact by calculating scaled suitable habitat for multiple lineages. Our results suggest each lineage contains specific abiotic predictors for detection and a small range of potential secondary contact in the greater Chattanooga area. Future surveys will confirm the outputs of our model to assess the utility of ENMs for predicting zones of hybridization and high interspecific competition.
CAIDEN SUMNER
REVISITING THE BIOGEOGRAPHY OF P. LEUCIODUS USING DNA TECHNOLOGIES
The Southeastern US boasts the highest freshwater fish diversity in the southeastern United States. The high richness of this region reflects pre-Pleistocene dispersal-mediated allopatric speciation, geological heterogeneity, and changes in ancient rivers, yielding high endemism and many cryptic species. The minnows of the family Leuciscidae are the most speciose family in North America and perhaps the most phylogenetically complex of North American fishes. Paranotropis leuciodus, the Tennessee Shiner, is endemic to the Cumberland and Tennessee River drainages throughout the eastern and central regions of Tennessee. Thirty years ago, allozyme analyses suggested multiple divergent and isolated populations with an ancestral origin in the early Tertiary, but thorough genetic and morphometric analyses have not been conducted since. This study attempts to reassess Mayden and Mason’s work to further parse the genetic organization of Paranotropis leuciodus with expanded sampling and molecular sequencing. The results of this study will provide important clarity concerning endemism and patterns of divergence pertaining to Tennessee hydrology, while also potentially taking initial steps in species delimitation, which could produce species important for conservation.
GAVIN BOGGS
IDENTIFYING SYMBIOSIS BETWEEN PSEUDOMONAS AND TERRESTRIAL SALAMANDERS
Co-occurring species take part in outcome independent interactions known as symbiosis. Such long-term interactions are characterized by positive effects on the fitness of one or both symbionts, these relationships and their effects are developed and sustained over successive generations. Co-evolutionary relationships influence factors such as physiology and behavior that better accommodate interactions, for example, amphibians rely on bacterial inhabitants of their skin microbiome to perform or aid necessary processes such as pathogen inhibition and production of sex-specific scents. This study to explores whether direct host-microbe interactions demonstrate favorable interactions between Pseudomonas colonies and Plethodon. By comparing how Pseudomonads associated with either hosts or cover objects grow with and without host secreted bioactive compounds, we can confirm the existence of a direct adapted mechanism favoring the growth of host-related Pseudomonas. If a favoring mechanism is confirmed, we can identify genomic evidence adaptation from Pseudomonas based on relations in DNA sequences. The positive results of this study may give merit to the argument that host-microbe relationships are intimate associations rather than arbitrary environmental encounters.
MOLLY KATE DICKSON and AVA MCCOY
IMPLEMENTATION OF AN eDNA PROGRAM TO MONITOR THE ENDANGERED LAUREL DACE (CHROSOMUS SAYLORI)
The Southeastern United States boasts the highest freshwater diversity in the temperate world, containing over 550 species of fish. Anthropogenic activities have led to the decline and imperilment of freshwater fishes, particularly endemic species with narrow distribution and strict habitat requirements. The Laurel Dace (Chrosomus saylori) previously occupied eight streams in three systems, but recent surveys have documented declines or possible extirpation at all sites. eDNA provides a non-invasive alternative to traditional sampling methodologies and can be effective in detecting small species in difficult-to-sample habitats. Additionally, metabarcoding of local fish communities can be informative for identifying candidate reintroduction sites. To aid in ongoing conservation efforts, our study implements a two-pronged approach using standard metabarcoding and probe-based qPCR assays to potentially detect new, or elusive populations of Laurel Dace while additionally characterizing fish communities on Walden Ridge. We first validated methodologies using controlled and unknown samples. Preliminary results show consistency with field sampling, and we hope to expand our eDNA program to other sites in the future. Our results hope to highlight the utility of eDNA programs for monitoring and surveying aquatic organisms, particularly those with high conservation priority.
HARPER KELLY
MOLECULAR IDENTIFICATION AND MICROPLASTIC ACCUMULATION IN CORBICULA FLUMINEA ALONG THE TENNESSEE RIVER
Anthropogenic activities are linked to a worldwide decline in the quality and condition of freshwater ecosystems. Two of these pervasive threats come in the form of microplastic pollution and invasive species stemming from a global homogenization of biodiversity. One of the most notorious freshwater invaders, the Asian clam (Corbicula fluminea), has become established worldwide, outcompeting native species and disrupting ecosystem function. Genetic analyses have proven useful for tracing invasive species, but lineage description has yet to be carried out Asian clams found in the Tennessee River. Furthermore, while clams have been hypothesized to serve as bioindicators of microplastic pollution in lentic habitats, investigations of the relationship between microplastic bioaccumulated in clams, sediment, and water are currently lacking. We seek to address this
gap by comparing the abundance of microplastics in Asian clams to the surrounding environment in urbanized portions of the Tennessee River, while also providing lineage reconstruction and physiological quantification of Asian clams in the southeastern United States. The results of this study provide lineage-level clarity for Asian clams in the Tennessee River while also evaluating their proficiency to serve as bioindicators of microplastic pollution in lotic systems.
MEGHAN ROYAL SPATIAL AND TEMPORAL VARIATION OF MEIOFAUNAL COMMUNITIES IN THE TENNESSEE RIVER
Meiofauna are small-sized organisms that persist in multiple different environments across the globe, including freshwater and benthic communities. As a result, meiofauna are valuable bioindicators of environmental change. However, the biodiversity and distribution of freshwater meiofauna remain poorly resolved in freshwater environments. While meiofauna are helpful, they are hard to sample, and laboratory identification is time consuming. Recent advancements in High Throughput Sequencing targeting meiofaunal genes have been proposed as a more efficient strategy for the biomonitoring of meiofauna. This study seeks to identify the spatial distribution of meiofauna along an urbanized portion of the Tennessee River. Sediment and water meiofauna samples were collected at nine locations along the Tennessee River to see if there is a difference in biodiversity pertaining to where the samples are located. High Throughput Sequencing (HTS) of the 18S and CO1 regions was carried out to amplify the DNA and the clarity that each primer provides will be compared. The study also focuses on how abiotic variables, such as conductivity, dissolved oxygen, oxidation-reduction potential, pH, temperature, total dissolved solids, and turbidity, influence richness, community composition, and community dissimilarity. The results link the relationship of abiotic variables to biodiversity and assess how meiofauna can serve as a bioindicator of anthropogenic changes in freshwater environments.
JACK HOUSTON
DATA-DRIVEN DESIGN OF COMMERCIAL SOLAR ARRAYS: ENERGY CONSUMPTION AND LOAD CONSIDERATIONS
With energy and electricity demand growing rapidly across the world, more than 25% since 2013, installations and expansions of renewable energy sources—like solar power—have been a growing electricity supply option. Solar panels are increasingly affordable, easy to install, customizable by location, and safe, making them a prime contender for electricity production. Solar power production also provides a unique set of sustainable benefits not offered by other power sources: it is renewable, has zero carbon emissions, and has an electricity production profile very similar to electricity consumption profiles, or load profiles, of households, businesses, and institutions. Regarding that last benefit, it is hypothesized that by adjusting the solar system design, particularly solar panel orientation and panel placements, the system will provide economic and reliability benefits. The goal of this study is to evaluate the use of a solar system design that matches the electricity production profile more accurately to the load profile of an academic campus to more effectively supply power when needed. An analysis of Baylor’s campus and solar installation modeling software will be used to make two solar system designs: One in which standard design and orientation are used and one in which the load profile of the campus is considered. In comparing the results of these two systems, it is hoped that the latter will be more cost-effective, reliable, and efficient. These results will inform academic campuses of the importance of considering load profile in solar system design. Future research could expand this concept to consider similar methods in commercial and industrial sectors.
BLAKE MCGOWAN
OPTIMIZATION OF ELECTRIC VEHICLE CHARGING INFRASTRUCTURE ON AN ACADEMIC CAMPUS
Electric vehicle purchases continue to grow every year, driving demand to expand charging infrastructure. After home charging, the next step to expanding infrastructure is workplace charging. The primary goal of this study is to find the optimal number and level chargers an academic campus should install to meet current needs. This study determines the optimal number of chargers through a model that uses data from a survey conducted with Baylor School faculty and the eligible student body. The survey indicated that combustion engines are still seen as the better alternative to electric powered vehicles, few elec-
tric vehicles are on campus today, and it is appropriate to assume that once each vehicle is parked it will stay parked through business hours. Based on this, the optimal level charger is a level 2 charger due to the expected time to full charge being 8 hours. Additionally, the model indicates that the optimal number of chargers is a fraction of the current number of electric vehicles on campus. This study can be used in the future when installing EV charging becomes a priority.
MAX MINNINGER DEVELOPING A CONVOLUTIONAL NEURAL NETWORK TO IMPROVE WASTE MANAGEMENT
The world produces around 400 million tonnes of plastic every year, but that number continues to rise rapidly. Substantial amounts of this plastic end up as pollutants in the world’s ecosystems, especially in the ocean. 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. The study will develop a code for a Smart Bin that uses a Convolutional Neural Network (CNN) to identify and correctly classify various images of waste items (plastic, cardboard, glass, metal, etc.). The code will be designed to receive the images from a camera; it will then assess the image and decide if the item is allowed inside the bin. If allowed inside, the system will open the bin, if not allowed, the bin will stay closed. For the system to be effective, it will need to reach high levels of accuracy, 95% and up. A system like this will help prevent potential contamination or misplacement of waste, leading to a cleaner world.
TREY RICHARDSON
EFFECTS OF SOLAR PANEL ANGLE AND ORIENTATION ON VOLTAGE AND IRRADIANCE
The performance of solar panels is significantly influenced by their tilt angle and orientation, both of which affect the amount of solar irradiance received and the voltage generated by the panels. This study investigates how different tilt angles and orientations impact the irradiance and voltage output of photovoltaic panels. The experiments were conducted by adjusting the tilt angle to 10°, 30°, 50° and 85° and rotating the panels to face East, South, and West. Measurements of solar irradiance and panel voltage were recorded under consistent sunny weather conditions. Results showed that panels oriented toward the equator, which is south facing in the northern hemisphere, with a tilt angle approximately equal to the local latitude, made the highest irradiance and voltage. Tilting the panel too steeply or too flatly resulted in reduced efficiency due to suboptimal sunlight capture. Results also show that East and West facing orientations show
higher performance during morning and afternoon hours, but lower overall daily output compared to south facing panels. The findings highlight the importance of optimizing both tilt angle and orientation to maximize solar panel efficiency. Proper tilt angle and orientation can significantly improve energy production, making these factors important for maximizing efficiency of solar panels.
ELLY WU
TRACKING DEFORESTATION: USING MACHINE LEARNING TO IDENTIFY PALM OIL PLANTATION GROWTH IN MALAYSIA
Agricultural expansion drives 90% of global deforestation, causing the destruction of habitats and the releasing of carbon dioxide into the atmosphere. Palm oil has been a significant contributor to deforestation, particularly in Malaysia, as it accounts for approximately 40% of forest loss. With deforestation persisting as a global issue, it has become imperative to obtain accurate data on deforestation trends through satellite imagery to thoroughly understand the implications of palm oil collection. This study will focus on identifying palm oil concessions in the Sarawak province of Malaysia over the last two decades and will look at the trends in deforestation. The satellite imagery will be obtained from Sentinel-2 imagery and a NDVI rendering will be applied to better identify the plantations. Using Google Earth Engine Python API, a supervised machine learning model will be built and trained with satellite imagery that can identify palm oil plantations. This study aims to provide an up-to-date map of palm oil plantations in Malaysia and to run the data over different periods of time to analyze how the palm oil industry has changed in Malaysia over the last two decades. The results of the model will be compared with other mappings in another study to ensure sufficient accuracy. Lastly, the results from this study will be compared with RSPO (Roundtable on Sustainable Palm Oil) certified plantations to explore the relationships between them. This study will provide a more comprehensive understanding of sustainable palm oil to address social, economic, and environmental debates about palm oil. The research from this study will be expanded upon to differentiate the types of palm oil plantations and project future scenarios.
ASHLEY YIM
THE EFFECTS OF FARMING METHOD AND LOCATION ON THE NUTRITIONAL VALUE OF NORI
Seaweed, encompassing over 10,000 species of aquatic algae, is a nutrient-dense staple in the East Asian diets with the capacity to absorb greenhouse gases (GHGs), mitigating climate change. Beef production, a major contributor to GHG emissions, deforestation, and biodiversity loss, necessitates sustainable alternatives. This study gathers information by studying the effects different mariculture farming methods for both organic and inorganic seaweed. Its goal is to find out if these different farming methods in various locations has an effect on the nutritional value of seaweed. This study involves analyzing protein content from different locations using different farming methods. The methodology includes enzyme pre-treatment, protein extraction, the Bradford Assay, and Gel Electrophoresis. The study results are expected to provide a view on the nutritional variation of seaweed types and determine if sustainable mariculture practices influence nutrition. With these new findings, more insights will be provided on the topic of seaweed along with how we can utilize its many benefits to help shape the beef industry and having the ability to incorporate this aquatic plant throughout the world.
SUSTAINABILITY
PIPPA HILL
THE
EFFECTS
OF COVER CROPS ON SOIL CARBON SEQUESTRATION IN AN ORGANIC FARMING ENVIRONMENT
The soil on Earth has incredible potential to store large amounts of atmospheric carbon. Therefore, research into the mechanics of soil carbon sequestration and its relationship to agricultural practices could contribute to a future solution for climate change. Soil carbon storage both alleviates the effects of climate change and positively influences the growth and development of plant life. This study investigates the effects of cover crops on soil carbon levels in the context of an organic garden. In this case, we study the contrasting effects of cover crop coverage versus a bare plot approach during the winter season after the harvest of a sunflower crop in southeastern Tennessee. To simulate a real agricultural cycle, we planted sunflowers (our “cash crop”) in two different plots during the spring and harvested them in the fall. We then planted crimson clover (our cover crop) in one of the plots and left the other plot bare with some weed cover, which we left throughout the winter season and into the next spring. During the
different phases of this experiment, we conducted various lab tests to measure variations in soil carbon levels, soil nutrient levels, and soil respiration. The results gathered up to this point show that carbon levels in the weed and control plots consistently increased from the spring to the winter and then decreased to below original levels by April. Conversely, the carbon content of the covered plot generally increased from winter through April, to above original levels. Nutrient levels generally decreased in all three plots, in line with our expectations, but in April they dramatically increased. Soil respiration levels rapidly decreased with the onset of colder temperatures and then increased again in March. These findings, taken specifically within the context of organic farming conditions that eschew any synthetic chemicals, reflect the variability of soil carbon levels and support earlier conclusions in the field of soil science, promoting the advantages of sustainable agriculture and specifically cover cropping for carbon sequestration.
LAKE MONTGOMERY
ANALYZING THE EFFECT OF EXTERNAL CRACKS ON SOLAR PANEL POWER PRODUCTION
Solar energy, 5.2% of the US net electricity generation in 2024, is expected to grow substantially. The solar energy industry also forecasts that the solar energy capacity installed per year will continue to rise. With the growing installation of solar power, it is important to keep solar arrays functioning at full power, one operations challenge is external surface cracks on panels from rocks or hail. The goal of this study is to analyze the effects of surface cracks on solar panel power production. To fully understand the effects of surface cracks on solar power production, this study used the 200 kW Baylor Solar Array. This study measured open circuit voltage (Voc), short circuit current (Isc), and irradiance of both cracked and intact panels. On average, the Isc of cracked panels was 26 percent lower than intact panels. The Voc was 1% lower than cracked panels. While this is less power production, further cost analysis showed that even when replacing the cracked panels with brand new 410-watt panels it would take over five years to payback the investment. This study emphasizes that cracked panels may still be producing significant power and it may not make sense for solar owners to replace cracked panels.
EXTRACURRICULAR STEM ACTIVITIES AND CLUBS
Baylor Science has several student and faculty-led extracurricular clubs and after-school STEM activities, from the Science and Engineering Journal Club, Space Club, Sustainability Club, the Electric Vehicle Racing Team, Ohm Raiders Robotics Team, and Moonshot Design to name a few. We are proud to provide the opportunity to enrich our students in the STEM fields beyond the traditional classroom.
UPPER SCHOOL MOONSHOT DESIGN
NICO
GERACI,
BRITTAN HYDE, LANA MITCHELL, REYNA PARK, KATELYN STEELE, and GRACE TANG
Transportation's reliance on fossil fuels has led to high costs, pollution, and climate change, prompting the search for sustainable alternatives like acoustic levitation. Our project uses a Chladni Plate and a TinyLev Acoustic Levitator to demonstrate acoustics' potential. The Acoustic Levitator can handle various materials, while the cymatics machine visualizes soundwave-created shapes. Using a TinyLev kit, we levitated small objects through resonant standing waves, a process called Acoustophoresis. The Acoustic Levitator can stably levitate foam balls and heavier, irregular objects. Cymatics shows sound frequencies by vibrating an aluminum platform to manipulate sand into 2D images. We identified frequencies that produce clear images, enhancing our understanding of resonance with the aluminum platform.
MIDDLE SCHOOL MOONSHOT DESIGN
MALCOLM BROWN, OM PATEL, JULIEN SPILLER, and PARKER THOMPSON
Students designed a cat-and-mouse robot maze game. The 3D-printed mouse robot uses sonar sensors to navigate a maze with modular wooden walls, following a right-wall or left-wall strategy. The demonstration will showcase the robot prototype and maze, along with a 1-dimensional mouse and cat game using dice and a meter stick. This project highlights students' creativity, problem-solving skills, and ability to integrate technology into learning.
Thank you to our incredible judges for their time and support of Baylor Research.
Paul-Erik Bakland Teacher
East Hamilton High School
Dr. Ethan Carver Associate Provost for Academic Affairs and Dean of Graduate School
UTC
Stephanie Chance Conservation Manager TNACI
Emily Culp GIS Analyst and Ecologist Tennessee Aquarium Conservation Institute
Dr. Jennifer Disanto Associate Professor, Mathematics
Chattanooga State Community College
Sarah Farnsley Associate Lecturer
UTC
Morgan Fleming
Ph.D. Candidate in Ecology and Evolutionary Biology
UTK
Mark Hagan
Biofuels and Energy Expert Independent
Elizabeth Hammitt Director, Residential Energy and Environmental Solutions EPB
Dr. Alberto Stolfi Assistant Professor Georgia Institute of Technology
Christian Swartzbaugh
Ph.D. Candidate in Ecology Tennessee Aquarium Conservation Institute and University of Georgia
Ongeleigh Underwood Executive Director
Appalachian Carbon Exchange
Dr. Weidong Wu Associate Professor
UTC
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.
