Poster Presentations: One

This research examines how, after the communist period, China and its population became one of the most dynamic countries in the world. After the death of Mao Zedong in 1976, China took an economic turn inspired by the Western model to modernize and lift its population out of poverty. In less than 50 years, China became the world’s largest manufacturing industrial economy and exporter of goods. While many studies have focused on the economic growth and policy reforms that fueled this rise, fewer have explored how these transformations reshaped Chinese society and culture. This research therefore fills that gap by analyzing both the economic mechanisms and the human consequences of those reforms. Understanding this connection is essential to grasp how China’s modernization influenced not only its economy but also its people’s way of life in a globalized world. It aims to understand the combination of policies, leadership strategies, and global integration that allowed China to achieve such an accomplishment and to analyze the positive and negative impacts of this sudden modernization and global opening on the Chinese population.

This study combines the analysis of economic decisions as well as two post-reform films, Shower (1999) and Platform (2000). Using film as a cultural lens provides an innovative approach to understanding how macroeconomic reform translated into everyday life, social change, and evolving cultural identity. This research evaluates how China’s modernization was not only an economic success but also a redefinition of national identity, global position, and everyday life. Through policy innovation, international openness, and cultural adaptation, Deng Xiaoping’s reforms established the foundation for China’s emergence as the world’s second-largest economy and a central player in globalization. By bridging economic analysis with cultural interpretation, this study contributes a new interdisciplinary understanding of how reform shaped both prosperity and identity in modern China, offering insights into the broader relationship between economic development and cultural transformation in a globalized world.

Adapting origami patterns to three-dimensional designs has enabled new applications for deployable mechanisms. Origami-inspired engineering is especially desirable in aerospace applications, as it allows for compact stowage during launch and deployment into much larger configurations in space. This work proposes a design for an origami-inspired earth observation Light Detection and Ranging (LiDAR) telescope, based on the flasher origami pattern. This system is comprised of 25 panels patterned around a central pentagon panel. To account for the thickness of the metal panels, the design uses the axis shift technique, which shifts mountain and valley folds to the upper and lower surfaces of the system. This technique is accomplished by implementing compliant mechanisms and magnetic joints. Compliant mechanisms are parts that move by bending flexible members. The compliant hinges help deploy the system by storing strain energy in the stowed state. Magnetic joints are also implemented along fold lines, which secure panels in their deployed state. This work quantifies the torque required to deploy two adjacent panels with magnetic joints and analyzes its relationship to the overall deployment force of the entire system. During deployment, mechanisms called booms are attached to the outer panels and slowly extend out. If the deployment force is too high the booms risk failing. The experimental results of this work characterize a novel computational model used to predict deployment forces in the booms based on placement, size and strength of the magnets along the joints. Once validated, this model will inform future flasher design iterations to achieve desirable deployment force.

Autism Spectrum Disorder (ASD) is a common diagnosis found in our population today. Applied Behavior Analysis (ABA) is one of the most common therapeutic resources today to assist individuals with ASD in skill building and development. However, ABA has a controversial history and this has created push back on the use of this therapy. My capstone project addresses the question: given its complex history, what are the benefits and drawbacks of ABA therapy? This thematic literature review dives into the historical, social, and psychological research into ABA treatment and evaluates common themes in the scholarly literature, touching on ABA’s history, therapeutic strategies over time, therapeutic benefits, and therapeutic downfalls.

I am interested in this question because I have been working in the field of ABA as a direct support professional for adults with various neurological disabilities as well as a registered behavior technician for children with autism for about four years and was encouraged to understand more about the history, development, and controversies surrounding ABA. Through this project, I have learned the foundation of ABA and how it has evolved. I have learned why certain cognitive aversives were used in early years and the extinction of them. I have examined many research studies that have supported the improvement of cognitive ability and interpersonal skills in ABA clients. I have gained greater understanding of the significance that self-injurious behavior has on this population and ABA’s focus on safety for clients. I discovered ABA’s uses of intense treatment while developing individualized behavior support plans. Through evaluating the negative impacts of masking on individuals with ASD, I have learned how ABA has evolved to be patient centered and embrace diversity. The Autism Rights Movement and activists express concern for the lack of representation of autistic voices in ABA development. I have found that ABA is progressing in the direction of prompting autonomy and choice to the clients they work with. Gaps in the literature that are most prevalent encourage future research to explore educational and infield training for behavior analysis practitioners, evaluate complex situations where consequences of choice can cause conflict, using sample sizes that reflect a wider age range and more diverse populations over longer durations, and dive into the social effects of misinformation.

Hypomyces chrysospermus is a mycoparasitic Hypocrealean mold that attacks bolete mushroom hosts. However, how the parasite locates hosts and counters host defenses is unknown. This project will test the host preference of H. chrysospermus and identify which genes are involved in H. chrysospermus parasitic attack. To find host preference, MMN media plates will be cut so there are four separated paths of media coming out from the center. The center will be inoculated with H. chrysospermus and the ends of the tracks with different strains of the bolete Boletus edulis (porcini). The parasite will reach more preferred hosts the fastest. RNA sequencing of the host and parasite before and during co-culturing will show what genes are differentially regulated in the attack and in the host’s defense. If conspecific B. edulis hosts exhibit disparities in resistance to H. chrysospermus, we will look for genomic differences that correlate with high or low resistance in previously generated genomes of the host strains. This study will improve the understanding of mycoparasitism more broadly.

Ant-plant mutualisms are ecological interactions that often result in specialization and coevolutionary dynamics. In most established associations, ants defend their host plants from herbivores and parasites, which can enhance host plant fitness and promote its reproduction. In return, host plants typically provide preformed nesting structures (domatia) and nutritional rewards. However, not all mutualisms conform to this pattern. In some systems, such as the Myrmelachista ant and Lauraceae plant associations, host plants offer limited structural or nutritional rewards to their tenant ants, suggesting the symbiosis is still in its primordia. The genus Myrmelachista is comprised of obligately arboreal ants that nest within both dead and live plant stems. Among the live-stem nesters are specialists, which exhibit associations with specific host plants while others are generalists, occupying a broader range of host plant species. In the absence of direct nutritional rewards from their host, several Myrmelachista species associate with sap-feeding hemipterans (Coccoidea: mealybugs and soft scales) that inhabit the same stems. These hemipterans produce an exudate called honeydew, a sugar and amino acid rich substance that serves as a nutritional resource for the ants. The resulting association represents an incipient tri-trophic mutualism, wherein ants rely on both the host plant for nesting and the Coccoidea for food. Because Lauraceae hosts do not readily provide domatia, Myrmelachista colonies must excavate internal cavities within the stems. Our study investigates the demographic composition of live-stem specialist Myrmelachista colonies inhabiting Lauraceae plants. We surveyed 47 Lauraceae branches inhabited by Myrmelachista colonies, collecting branches from each host tree as representative subsets of the resident colony. Branch lengths ranged from 23.2–205 cm (mean = 99.8 cm), and diameters ranged from 0.2–7.0 cm (mean = 1.6 cm). For each subset, we quantified caste structure (alate queens, males, and workers), brood presence (larvae and pupae), and associated Coccoidea abundance. Subsets contained an average of 1,778 individuals (±1,374 SD), comprising approximately 68% adults and 32% brood, with workers consistently dominating the adult caste. Associated Coccoidea populations averaged 43 individuals per branch (±52 SD). Subset size increased with branch length (R² = 0.34, p < 0.01), indicating that host stem architecture constrains colony growth. Coccoidea abundance correlated positively with total adults (r = 0.582, p < 0.01), suggesting that honeydew supplements colony nutrition where host plants lack direct food rewards. Examining these incipient associations helps to uncover the mechanisms by which simple cohabitations evolve into stable, coadapted mutualisms.

Atrazine and polychlorinated biphenyls (PCBs) are environmental contaminants found throughout the US. They have been shown to be harmful to certain plants and animals, including humans. Atrazine is an herbicide that has been linked to environmental concerns such as toxicity to fish, insects, crustaceans, reptiles, and amphibians. It was also recognized by the US EPA as an endocrine toxin to humans. Despite these concerns, atrazine is still widely used in the US today, with approximately 30,000 tons being applied annually. PCBs are man-made, chlorinated hydrocarbons derived from oil and tar. Their use was banned in the 1970s due to increasing evidence linking PCBs to environmental and human toxicity. Despite the ban, PCBs are still found in harmful levels throughout the US today due to their long half-life. PCBs have been linked to a wide variety of diseases such as cardiovascular disease, type II diabetes, and liver disorders. The harmful effects of atrazine and PCBs are largely due to the chlorinated structures of both. Chlorinated species are frequently toxic to the environment and generally have longer half-lives due to environmental inability to dechlorinate them.

The increasing evidence linking both atrazine and PCBs to environmental and human toxicity leads to a large interest in bioremediation of these chemicals. One strategy has been to identify microbes capable of degrading these compounds, then identifying the enzymes involved in the degradation process. From this approach, the enzymes atzA and trzN have shown the ability to dechlorinate atrazine into the less harmful compound hydroxyatrazine. trzN has also been found to dechlorinate a variety of compounds, leading us to be curious if it could dechlorinate PCBs as well.

There is growing research surrounding the idea of using bioengineered microalgae for bioremediation purposes. This study aims to test if the enzymes atzA and trzN can be expressed in the algae Chlamydomonas reinhardtii, resulting in an algae capable of degrading the herbicide atrazine. The first phase will involve testing the atrazine degradation abilities of atzA and trzN expressed in E. coli, to determine which enzyme is the better catalyst for atrazine dechlorination. PCB dechlorination will also be tested, as to date no one has examined whether either enzyme is capable of dechlorinating PCBs. For phase two, the enzyme with the highest efficiency and broadest substrate specificity will then be expressed in Chlamydomonas reinhardtii which will then be tested for atrazine and PCB degradation capabilities.

Periprosthetic joint infection (PJI) after total knee arthroplasty is a devastating complication, often requiring multiple surgeries and leading to high patient morbidity. Current diagnostic standards, such as joint aspiration and culture, are invasive, time-consuming, and may produce false-negative results. This creates a critical need for a rapid, non-invasive, point-of-care diagnostic tool.

Our previous research (Wilkes et al., 2024) established the foundational physics for such a device. We experimentally validated the computational models of Ash et al. (2017), confirming that visible light transmissivity increases with a wider beam diameter, which is essential for penetrating scattering, tissue-like media. This new project, identified as a key future direction of our work, applies this validated optical system to the PJI clinical challenge.

The purpose of this research is to determine if our non-invasive optical scattering system can identify the unique "signatures" of bacteria associated with post-operative knee infections. We hypothesize that bacterial suspensions in synovial fluid will produce a distinct optical scattering pattern that is measurably different from sterile fluid.

Our methodology involves developing in vitro knee joint phantoms using an established agarose technique (McIlvain et al., 2019). These phantoms will be inoculated with clinically relevant bacterial strains (e.g., Staphylococcus aureus) at varying concentrations. We will adapt our existing experimental apparatus (Wilkes et al., 2024)—which includes a laser, sample holder, and camera system—to measure both on-axis transmitted power and full-area scattering patterns.

The anticipated conclusion is that bacterial contamination produces a unique, measurable optical "fingerprint." This study will provide the "proof-of-concept" for a non-invasive, cost-effective device for the early detection of PJI. The significance lies in its potential to allow for earlier intervention, reducing the need for invasive diagnostics and improving surgical outcomes for knee replacement patients.

Pregnancy exacts many costs on female organisms, including in humans. Not only do females bear the energetic costs of the developing offspring, but female body shape also changes in ways that can affect locomotion, coordination, and movement. Females that minimize these costs, while still successfully reproducing, should be favored. In this study, we focus on a livebearing fish model (Alfaro cultratus) with an usual body morphology: both males and females have a highly laterally compressed body. This novel shape is in stark contrast to the almost 300 other species in this family, where males have a fusiform body shape, and females have a profoundly distended abdomen when pregnant. Here, we ask the simple question, does the laterally-compressed morphology in Alfaro cultratus allow pregnant females to minimize the cost of pregnancy during swimming? This is an important question because it will help us understand the relationship between body shape, swimming performance, and fitness.

The microbiota, especially the gut microbiome, can have important impacts on organismal behavior. Due to complexity in human and mammalian microbiomes, Drosophila melanogaster is used as a model organism due to its simple composition. Some microbes, such as Acetobacter DmW_125, produce heat in specific conditions, but the impacts of such heat producing bacteria in fly activity has not been investigated. My research will compare axenic (germ free) flies to flies mono-associated with heat producing bacteria and a control strain (Acetobacter orientalis). I will use the DAM2 system to monitor fly locomotor levels at 20°C, 25°C, and 30°C to determine if microbial heat mediates extreme temperatures. I predict heat from the bacteria will increase fly activity at lower temperatures. In wild flies, higher tolerance would lengthen the reproductive window and increase survival. My research contributes to a larger understanding of host-microbe interactions specifically with bacterial heat production and its impact on behavior.

Xanthommatin (Xa) is a natural pigment found in many invertebrates, including cephalopods such as octopuses, squids, and cuttlefish, and insects such as butterflies, dragonflies, and caterpillars. In cephalopods, Xa enables rapid color changes for camouflage, while in insects it contributes to the pigmentation of the eyes, wings, and body. This ability to produce both fixed and dynamic coloration stems from Xa’s photochromic and electrochromic properties, allowing it to change color in response to light and electrochemical stimuli, making it attractive for applications in color-changing products and UV-protective technologies, such as sunscreens and coatings. Xa is typically derived from the dimerization of two 3-hydroxy-L-kynurenine (3-HK) molecules via phenoxazinone synthetase. While organisms synthesize Xa efficiently, laboratory production has been limited by low yield and high cost. Recently, researchers at the University of California, San Diego engineered a Pseudomonas putida strain capable of producing large quantities of Xa from 3-HK using a system that links pigment production to bacterial growth and increases yield up to 1,000-fold.1 This production occurred in the absence of phenoxazinone synthetase, suggesting that a native enzyme in the modified strain may catalyze the final conversion. Three candidate enzymes with potentially compatible active sites—tyrosinase, catalase, and catalase peroxidase—were identified for investigation. In this project, we aim to determine which enzyme catalyzes the final step in Xa biosynthesis using protein-ligand docking, molecular dynamics (MD) simulations, and free-energy calculations. Enzyme models were built from crystallographic and AlphaFold data, with protonation states reflecting pH 6 where the conversion occurs. Docking generated 3-HK binding poses, providing initial prediction of substrate-enzyme interactions. These poses were then evaluated with MD simulations to assess their stability and conformational behavior over time, followed by refinement of binding free energies to quantify relative affinities. This computational approach enables us to narrow down the responsible enzyme, propose a plausible catalytic mechanism, and guide subsequent experimental efforts.

Pro-opiomelanocortin (POMC) is an important gene for endocrine regulation due to its peptide products – which include alpha-melanocyte stimulating hormone, a key satiety signal. Deficiency in POMC impacts hypothalamic signaling and can potentially impair downstream gonadal hormone balance and reproductive cycles. Mouse models are useful in diagnostic research as a proxy for humans, where mechanisms can be difficult to study. POMC-deficient mice show early-onset obesity due to hyperphagia, and also seem to be infertile. This study will investigate baseline estrogen levels in POMC-deficient female mice and evaluate their estrous cycle compared to wild-type control female mice. This will shed more light on the impact of POMC loss on reproductive endocrinology. Serum samples will be collected from adult female mice. Estrogen will be quantified using an enzyme-linked immunosorbent assay (ELISA) and calibrated with standard curves. At the same time, vaginal smears will be collected, analyzed & imaged to classify the estrous cycle stages. The estrous cycle consists of four stages: proestrus, estrus, metestrus & diestrus, which can be identified based on the cytology present in the vaginal smear. Our analysis will compare baseline POMC-deficient and wildtype estradiol concentration, and how these concentrations change throughout the estrous cycle. We hypothesize that POMC deficiency will result in below wildtype estrogen levels, which may be the cause of the irregular estrus cycles. In turn, this may reflect altered levels of gonadotropin-releasing hormone, luteinizing hormone and/or follicle-stimulating hormone. This research will provide more insight regarding the relationship of POMC to estrogen levels and estrous cycling. In addition, we hope to learn more about the inter-connectedness of obesity and infertility, both of which are major health concerns as they increase in humans.

Devils beggar ticks (Bidens frondosa) is a wetland plant native to North America. Within its habitat it produces small seeds that are covered in small recurved barbs and contain two large spikes. These achenes are noted for their ability to stick to materials in their habitat. As they easily fall off the plant these seeds can float on water where they may be of interest to local fish. Based on several field observations of Devils beggar ticks growing on fish carcases, we asked if these seeds may kill the fish that consume them and then benefit from growing in a high nutrient source. We designed an experiment to look at the germination, and fitness of plants growing in a high nutrient environment, a fish carcass, and a control. We predict that plants growing in the fish carcass and the high nutrient environment will have the highest germination rates as well the largest overall fitness. Our results may demonstrate a novel situation of a plant killing a vertebrate to increase its overall fitness.

Background: Trauma bays are crowded, time-critical environments where multiple clinicians work in parallel and infection prevention can be neglected due to urgency of care, rapid turnovers, and the need to prioritize life-saving interventions. However, approximately 1 in 18 trauma patients develops a healthcare associated infection (HAI) with substantial increases in length of hospital stay and ICU/ventilator time. (Hessels et al., 2020). Given many potential contributors, we will focus on hand hygiene (HH), one of the simplest and most effective HAI prevention strategies.

Objectives: 1.To assess Emergency Department (ED) personnel knowledge, attitudes, and practices (KAP) about HH during trauma resuscitations via a structured, anonymous survey. 2.To translate the findings into a video-review study that accurately flags hand hygiene opportunities, compliance, and gaps.

Methods: We will field an anonymous KAP survey of ED clinicians who have been in the trauma bay ≥1 time in the past 6 months (screened at survey start). The instrument covers role/experience, HH knowledge, attitudes and self-reported practices/barriers. We also include de-identified, aggregate ratings of colleagues’ HH practices to assess perceived team norms. In the next phase of the study, we will analyze video recordings of trauma bays to identify and quantify HH opportunities and gaps using a predefined observation scheme.

Planned Results for Poster Presentation: Descriptive KAP results by role/shift, highlighting practical barriers and improvement ideas, plus anonymous peer ratings of colleagues’ HH consistency.

Significance: By pairing staff-level insights with a structured observation framework, this project will identify workflow-compatible opportunities to reduce cross-contamination without delaying critical care. The outputs will set the stage for a future randomized control trial for one of the approved HH methods under defined conditions.

The ability to stably modify the chicken genome has wide-reaching applications in developmental biology, agriculture, and biotechnology. Transgenic chickens can serve as powerful models for studying gene regulation, developmental pathways, and disease mechanisms, and they hold promise as bioreactors for producing pharmaceutical proteins or vaccines. However, traditional transgenic approaches often rely on random gene insertion, leading to unpredictable expression patterns and potential disruption of endogenous gene function. Our project aims to identify and validate a safe harbor locus within the Gallus gallus genome, a genomic location that supports consistent, heritable transgene expression without interfering with normal gene activity. Establishing such a site would enable precise, reproducible genetic engineering and improve reliability across research and commercial applications. To accomplish this, we utilized DNase-seq, ATAC-seq, and Hi-C data to identify an open chromatin region on chromosome 1 that remains transcriptionally active across all tissues and developmental stages. This region, termed the Oasis locus, was selected for targeted gene insertion. Primordial germ cells (PGCs) were isolated from fertilized chicken embryos, genetically modified with a GFP reporter at the Oasis locus, and reintroduced into recipient embryos to generate chimeric founders capable of transmitting the modification to their offspring. GFP expression in PGCs, embryos, and hatched chicks demonstrated stable, non-mosaic, and ubiquitous expression, confirming the activity and safety of the targeted locus. Breeding of heterozygous founders produced viable homozygous offspring in expected Mendelian ratios, establishing that integration at the Oasis site does not compromise viability or fertility. These findings represent a foundational step toward a reliable avian transgenesis platform. By minimizing the variability associated with random insertion and enabling consistent expression across generations, this work provides a framework for future studies involving precise genomic modification, including recombinase-mediated cassette exchange and the development of genetically engineered chicken lines for biomedical and agricultural innovation.

Strong's Creek is a headwater stream in Weber County, Utah, with a wide variety of terrestrial and aquatic invertebrates. We focused on the larval stages of aquatic invertebrates, which represent the primary consumer stage in the stream. Blackflies and mayflies occupy low trophic levels and are an important link between basal resources and predators. Larval blackflies are filter feeders that feed on microscopic particles transported in stream water. In contrast, grazing larval mayflies scrape algae, bacteria, and fungi from rocks. Predators can be broadly grouped into benthic (larval stoneflies), terrestrial (spiders), and air-water interface (water striders) consumers. Previous research in Strong’s Creek found that blackflies have higher mercury concentrations than other invertebrates in the stream. The present study focused on the trophic ecology and food web dynamics among different invertebrates to further explore mercury concentrations among taxa. In the summer of 2024 and 2025, craneflies, blackflies, mayflies, stoneflies, and caddisflies were collected from Strong’s Creek. We also collected water striders and spiders in addition to the taxa above in 2025. We then sorted and identified the invertebrates to the lowest possible taxonomic rank. The specimens were dried and analyzed for total mercury concentration. We found that blackflies and spiders had the highest mercury concentration, while the other taxa had significantly lower levels, mayflies in particular having little to none. This suggests that blackflies accumulate high mercury and could be a source of elevated mercury to any organism that consumes them. Spiders that position their webs along emergence zones of blackflies may be more susceptible to the bioaccumulation of mercury than water striders and larval stoneflies, which occupy different microhabitats. Understanding the roles these invertebrates have in Strong’s Creek could help us understand the bioaccumulation of mercury through the stream.

Acute Myeloid Leukemia (AML) is a malignancy of the bone marrow characterized by the accumulation of immature leukemic cells and impaired differentiation of normal white blood cells. It is commonly associated with reduced levels of erythrocytes, megakaryocytes, and multiple myeloid lineages, including neutrophils, eosinophils, basophils, monocytes, and macrophages. Mutations in the Zebrafish and Human Telomeres 1 (ZHT1) gene have been proposed as a potential driver of AML pathogenesis. This study aimed to establish a zebrafish (Danio rerio) model of AML via CRISPR/Cas9-mediated zebrafish zht1 knockout and to verify the function of ZHT1 variants of unknown significance. Gene expression analysis by quantitative PCR (qPCR) revealed reduced levels of hematopoietic markers (spi1b, lyz, mpx, gata1, and rag1) in zht1 knockout (KO) zebrafish larvae compared to wild type (WT). To determine if these changes reflected decreased cell-type abundance, whole-mount in situ hybridization was performed using probes for spi1b, lyz, mpx, and gata1. Visual analysis confirmed a significant reduction in gata1 expression and a modest, non-significant decrease in lyz. These findings suggest that zht1 plays a critical role in hematopoietic development and may contribute to AML pathogenesis by disrupting blood cell lineage differentiation.

Convergent evolution, where dissimilar species evolve similar traits, is a well understood concept, but the underlying genetic and reproductive mechanisms remain unclear (Stern 2013). Gilia capitata ssp., a wildflower whose maximum likelihood phylogenetic tree shows polyphyly, (Johnson et al. 2017), may represent two closely related lineages that evolved convergent traits (Woźniak et al. 2018). Thus, G. capitata ssp. would be a great candidate for studying convergence. To evaluate its suitability as a model, I bred three different subspecies of G. capitata—ssp. capitata, ssp. abrotanifolia, ssp. stamenea—and recorded checkpoints for fertility and compared the data using non-parametric comparison tests between control (self and sibling) crosses and experimental (hybrid) crosses. I found evidence for self-incompatibility in G. c. stamenea, as well as statistically significant changes in pre-zygotic fertility among G. c. stamenea hybrid crosses. Further studies will need to plant the F1 generation and record fertility to find clearer patterns of isolation among the subspecies.

Pharmaceutical contamination in water systems poses a growing threat to environmental and public health, as the use of prescription and over-the-counter medications increase. This study aims to detect two widely used over-the-counter drugs—ibuprofen and aspirin—in local water sources using capillary electrophoresis (CE) coupled with ultraviolet (UV) light detection. CE provides high-resolution separation based on charge-to-size ratios, while UV detection enables sensitive quantification of analytes with aromatic structures, such as these common pharmaceuticals. Water samples will be collected from multiple sites and analyzed under optimized CE-UV conditions to assess potential contamination levels. By developing a reliable, accessible method for monitoring pharmaceutical residues, this research supports future environmental surveillance efforts and reinforces the importance of clean water as a foundation for community health.

Oxidative stress plays a central role in the progression of diabetic complications, including diabetic kidney disease (DKD), through the overproduction of reactive oxygen species. Endothelial cells are particularly susceptible to damage and highly vulnerable to injury due to from prolonged hyperglycemia. Pterostilbene is a naturally occurring compound that has demonstrated anti-oxidative, anti-inflammatory, and anti-diabetic properties in various disease models and cell types, including endothelial cells. Despite promising evidence from multiple studies, pterostilbene has not yet been adopted as treatment for diabetic kidney disease. The purpose of this research is to evaluate the effects of pterostilbene on NOX-derived ROS production in human umbilical vein endothelial cells (HUVECs) exposed to hyperglycemic conditions. Previous studies have shown that high glucose exposure increases NOX activity and ROS production in endothelial cells, leading to oxidative damage and endothelial dysfunction. In order to assess these effects, HUVECs are cultured under four experimental conditions: normal glucose, normal glucose with mannitol (as an osmotic control), high glucose, and high glucose with pterostilbene. To examine the impact of pterostilbene, oxidative stress is quantified using an ROS assay, while NOX enzyme activity and expression are evaluated through enzyme assays and Western Blot analysis. Together, these methods will allow for a comprehensive assessment of pterostilbene’s ability to mitigate oxidative stress in endothelial cells exposed to hyperglycemic conditions. It is expected that pterostilbene will downregulate NOX expression and activity, lower ROS levels, and improve overall endothelial cell health, including markers of oxidative damage and endothelial function. These results would provide further insight into the molecular mechanisms by which pterostilbene protects vascular cells in hyperglycemic conditions and support its potential as a therapeutic strategy in diabetic kidney disease.

RNA-binding proteins (RBPs) are essential regulators of post-transcriptional gene expression, and their dysregulation has been implicated in congenital neurological disorders and brain tumors. Despite their recognized biochemical roles, the physiological functions of RBPs during vertebrate neurodevelopment remain poorly understood. The Like-Sm (LSM) proteins, LSM1 and LSM8, form distinct cytoplasmic and nuclear complexes that regulate mRNA decay and pre-mRNA splicing, respectively. In this study, we focus on elucidating the developmental and stress-adaptive roles of LSM1 and LSM8 using zebrafish (Danio rerio), a powerful vertebrate model with conserved neurodevelopmental pathways and amenability to genetic manipulation. We observed high expression of lsm1 and lsm8 in the developing central nervous system, and functional perturbation via CRISPR/Cas9 and morpholino knockdown revealed increased apoptosis, altered proliferation, and markers of reactive astrocytosis, suggesting critical roles in CNS development. Future directions include stage- and lineage-specific functional dissection of LSM proteins during neural development, along with integrative transcriptomic analyses to define downstream regulatory networks and RNA interactomes. We will also explore how LSM1- and LSM8-dependent mechanisms influence stress adaptation by regulating RNA granule dynamics and transcript fate. This work will provide foundational insights into how distinct LSM complexes maintain RNA homeostasis in vivo and how their dysfunction may underlie neurodevelopmental and neurodegenerative disorders.

Lycoperdon is a genus of puffball mushrooms that are often pear-shaped and covered in small spines. To disperse their spores, puffball mushrooms develop a small opening at the top, and then release them in a puff-like cloud. In North America, this genus is largely understudied. Accurate identification is important because many edible mushrooms have morphologically similar but inedible counterparts, and mistaking them can have dire consequences. For this reason, this study aims to answer the following: What are the evolutionary relationships among species of Lycoperdon and closely related genera in North America based on genetic traits? To answer this question, we will perform DNA extractions on specimens of Lycoperdon and close relatives from the Natural History Museum of Utah. We will then use PCR to amplify multiple barcoding genes, and the results will be sent through Sanger sequencing in order to create a multilocus phylogeny. From this phylogenetic tree, we can discover cryptic speciation and potential misclassification within the genus. This will also allow us to create an ancestral state reconstruction for morphological traits such as spine presence and sporocarp size. These analyses will provide deeper insight into the relationships within Lycoperdon and closely related species and the evolution of sporocarp morphology in puffballs.

Using Computational Strategies to Measure Nanoparticle Sizes from SEM Images Nanoparticles are extremely small materials whose chemical and physical properties depend strongly on their size and shape. Accurately determining nanoparticle size is essential for understanding their behavior. Nanoparticles and the knowledge of their size can be applied to applications like consumer products, energy, and medicine. The central question of this project is: Can automated image analysis using Python provide a faster and more reliable way to measure nanoparticles from scanning electron microscope (SEM) images compared to traditional methods? To address this question, I collaborated with faculty from the Chemistry, Computer Science, and Physics departments to develop a Python-based tool. The tool automates the measuring of nanoparticles area and counts the amount of nanoparticles within the image. Previously, researchers measured particles manually by drawing lines on SEM images or by using a software called ImageJ. These are processes that are time consuming and prone to human error. My Python program streamlines this workflow by reading the imputed SEM images, calibrating the distances using the provided micron-to-pixel scale, and detecting particle edges through image processing techniques. The program uses functions from the OpenCV and NumPy libraries to detect nanoparticles and compute their areas, therefore producing a set of size measurements for each image. Currently, I am validating the program by comparing the automated measurements from the Python program to manually obtained data from previous researchers to assess accuracy. Preliminary results indicate the automated method significantly reduces measurement time and produces consistent results across multiple images. Future improvements include saving the data automatically to a file, creating a UI for the program, and automated micron-to-pixel ratio calculations. This project demonstrates how computational tools can bridge the gap between chemistry, physics, and computer science to solve practical challenges. By automating SEM image analysis, the Python script enhances efficiency, minimizes human bias, and provides a framework that can be adapted for other nanoparticle systems or microscopy techniques.

Polychlorinated biphenyls (PCBs) are toxic, long-lasting chemicals once widely used in electrical manufacturing (1930s–1970s). Although now banned in the U.S. due to serious health risks and environmental persistence, PCBs remain in ecosystems because of improper disposal and their resistance to degradation. Here we are studying the microbial diversity and potential for bioremediation of PCBs. In summer 2023, PCB and heavy metal contaminated sediments were collected from the historically-contaminated Woods Pond, Massachusetts. Analysis of the sediments confirmed that PCBs, various heavy metals, and diverse microbial communities, including known PCB-degrading microbes, were present. The sediments were then used to create microcosm cultures with three different treatments: aerobic, anaerobic, and anaerobic with the addition of sulfate. These microcosms have been growing since July 2023 and show signs of active microbial metabolism (e.g. rust patches in sediment, gas production). Additionally, the microcosms have been used as inoculate for agar plates containing PCBs and more than 100 PCB-tolerant colonies have been isolated from the microcosms. After years of growth, we’ve terminated the microcosms to analyze how the microbial communities have changed over time by DNA sequencing and if they were able to degrade the PCBs by gas-chromatography mass-spectroscopy. This data will aid further research to determine if and how these microbes metabolize PCB compounds and may contribute to the future bioremediation of chronically contaminated environments.

Status Epilepticus (SE) is a severe neurological emergency characterized by continuous or rapidly recurring seizures lasting five minutes or more, with no recovery of neuronal activity between events. Affecting 24 individuals per 100,000 annually, SE carries a high mortality rate of 26% which rises to 36% in cases of Refractory Status Epilepticus (RSE) which is defined as a form of SE where standard anti-epileptic drugs (AEDs) no longer terminate epileptiform activity. This limited efficacy of existing treatments underscores the urgent need for novel therapeutic strategies. Metabolic-based interventions, particularly those involving ketone bodies such as β-Hydroxybutyrate (BHB), have shown promise in reducing neuronal hyperexcitability and seizure activity, as seen in patients treated with the ketogenic diet for chronic epilepsy. However, the diet’s long-term implementation limits its use during acute SE episodes. This study aims to investigate through an ex vivo rodent brain slice model whether direct application of a ketone body solution containing BHB is a viable option to rapidly suppress or terminate SE activity in human patients suffering from SE and RSE. Using a Multielectrode Array (MEA), electrophysiological recordings will capture real-time neural activity after SE is induced with a 0 Mg²⁺ convulsant solution. Once SE is established, a ketone body solution will be applied to the rodent brain slice, and subsequent analysis will assess its effectiveness in terminating SE. This approach allows for precise, controlled observation of the acute electrophysiological impact of BHB on seizure-like activity without systemic metabolic confounds. By combining live MEA recordings with direct ketone body administration, this study provides a novel framework to assess the therapeutic potential of metabolic interventions for pharmacoresistant seizures. If successful, this research could advance the development of fast-acting, metabolism-based treatments for SE and RSE and offer valuable insights into the neurophysiological mechanisms underlying ketone-mediated seizure suppression.

The ability to recognize kin is an important and adaptive trait with several direct and indirect benefits. Parent-offspring recognition is arguably even more important, since parents and offspring are more related to each other than they are to any other relative. While offspring recognition has been widely studied in organisms that provide postnatal care to their young, it has not been well studied in organisms that do not provide postnatal parental care, preventing us from fully understanding its ultimate and proximate causes. To begin remedying this, we plan to search for evidence of offspring recognition in livebearing fish from the family Poeciliidae, which do not care for their offspring after birth. To do this, we have come up with two separate experimental setups; which one we use will be determined after a preliminary pilot study. The first is an assay based on cannibalism. After a brood is born, we will split it in half, putting one half in a tank with the mother, and the other half in a tank with an unrelated female. Rates of fry consumption between mothers and unrelated females will be compared. We believe cannibalism to be a viable experimental setup because a) it is a widely observed phenomenon in fish, making it easily replicable, b) it has been used to determine offspring recognition in other fish species, and c) it allows us to test for recognition of newborns, the group that is of particular interest to us. We intend to run this assay three times to determine if cannibalism occurs at high enough rates to justify its use in our study; if it doesn’t, we will use an assay based on male-male competition instead. Once fry are sexually mature, we will place a male fish in a tank with their father, one unrelated male, and three females. We will then count the number of aggressive actions by each male, as well as the fish it’s directed towards. This setup has been used to determine kin recognition in other species within this family, but has not been used to determine parent-offspring recognition. Overall, we hope that our study will answer questions about how parent-offspring recognition evolves, both generally and within this family specifically. We also hope to open the door for more questions to be asked regarding how social behaviors appear within different lineages.

T cells play an important role in the adaptive immune response, producing immune regulating molecules and fighting pathogens. T cells need to be activated in order to effectively respond to infection, and when they are activated they switch their metabolic processes from cellular respiration and glycolysis to solely glycolysis. This metabolic change helps meet energy needs for proliferation, cytokine production, and DNA replication. A cellular coreceptor called CD5 (cluster of differentiation 5) inhibits T cell differentiation in the thymus. Previous work in our lab has shown that CD5 knockout CD4+ cells rely more on cellular respiration and glycolysis than wild type (WT) cells. CD6 (cluster of differentiation 6) has similar structure and function to CD5, and affects T cell differentiation, stabilizing the TCR and MHC, and migration of T cells from blood into tissues. The goal of our research is to determine if CD6 knockout CD4+ T cells have metabolic changes compared to WT. We harvested and isolated CD4+ T cells from CD6 knockout mouse spleens, ran Seahorse metabolic profiling assays and found that CD6 knockout mice have higher basal oxygen consumption rate compared to WT. We also did analysis of metabolite levels in the serum from the same mice, and are currently waiting for the results of that analysis. They will be ready by the time of the conference. Understanding and influencing T cell activation and metabolism could help develop treatments that modulate immune responses to treat autoimmunity or upregulate activity to fight infections. Future research is needed to understand how CD6 knockouts affect the metabolism of activated T cells and mitochondrial structure

Paratransgenesis is a strategy to control vector-borne diseases by genetically modifying an insect’s symbiotic microbes rather than the insect itself. Current approaches, which rely on microinjection’s relatively large hollow needles, often cause irreparable egg damage and high mortality in insects. Nanoinjection, which uses much smaller solid lances and electrostatic attraction to deliver material, offers a less damaging alternative for generating paratrangenic insects. We tested the implantation of Sodalis praecaptivus into Callosobruchus maculatus (bean beetle) eggs at three injection sites (head, side, and back) to evaluate the viability of nanoinjection for creating paratransgenic insects. We hypothesized that nanoinjection would enable the creation of paratransgenic insects, even in species lacking native symbionts. Further, we hypothesized that back injections offered the best conditions for bacterial uptake as it is the predominant injection location for microinjections. Nanoinjection achieved symbiont establishment in 35.8 ± 5.3% (n=891) of injected eggs, indiscriminate of injection site. Hatch rates for injected eggs were 1.2 ± 0.8% with symbiotic integration occurring in 62.5 ± 33.6% (n=8) of hatched beetles. This represents the first documented case of symbiont uptake in a species without a native S. praecaptivus symbiont, underscoring the versatility of nanoinjection as a model system for introducing symbionts across a diverse range of insect species. We further observed that symbiont transmission occurred maternally. Injected females passed S. praecaptivus onto their offspring (12.4 ± 6.3%, n=105), while injected males showed no vertical transmission (0 ± 0%, n=70) despite confirmed bacterial presence and some horizontal transfer to the wild-type mate. Future work will focus on applying nanoinjection to mosquitos to establish paratransgenic strains capable of countering malaria as well as other vector-borne diseases.

In the wild, fruit flies rely on olfaction to respond to environmental stimuli. Our lab has discovered that verbenone, an organic compound naturally found in fermenting juniper berries, elicits opposite behavioral responses in two Drosophila species. While verbenone attracts Drosophila pseudoobscura, it repels Drosophila melanogaster. However, the neuronal and genetic basis behind these contrasting olfactory responses was unclear. Transgenic systems are not yet available in Drosophila pseudoobscura. Therefore, I utilized the Gal4-UAS system- a powerful genetic tool that enables control over gene expression within specific neurons of the Drosophila brain- to investigate the repulsion mechanism in Drosophila melanogaster. The Gal4-UAS system operates through the combined action of two components: the Gal4 driver provides access to select neurons, and the UAS component carries a gene that inhibits neuron function. In flies carrying both the Gal4 and UAS components, specific target neurons are disabled. To identify the neurons mediating verbenone repulsion, I first inhibited neurons expressing Orco, a protein required for the function of most Drosophila olfactory receptors. Flies with Orco-dependent neurons silenced were tested using olfactory trap assays. Olfactory trap assays are a method of testing innate olfactory behavior and simulate natural foraging behaviors in Drosophila. Over 48 hours, flies are given a choice between two odor sources, after which they are collected and counted to determine olfactory preference. Flies lacking functional Orco-dependent olfactory receptor neurons displayed no significant avoidant response to verbenone compared to odorless mineral oil, suggesting that Orco-dependent neurons are critical for mediating verbenone repulsion in Drosophila melanogaster. Subsequent calcium imaging and screening of individual Orco-dependent neurons allowed us to discover a particular olfactory receptor, Or67b, as a likely mediator of verbenone repulsion. However, calcium imaging also revealed that multiple neurons in the Drosophila melanogaster brain respond to verbenone. Moving forward, I will be continuing my search to find additional olfactory receptors that mediate the repulsion response.

The Great Salt Lake is in grave danger. With the effects of climate change being felt more intensely as time goes on, saline lakes around the globe are drying up without any action being taken. The result is major ecosystem instability along with a decrease in carbon sink potential both as autotrophic density decreases and carbon dioxide emissions increase from the exposed lake beds. For the Great Salt Lake, as the lake’s water volume declines, salinity levels are rising to threatening levels for the microorganisms that thrive there. Split into two halves, the lake contains two primary single-celled algae species: Dunaliella salina in the far more saline North Arm and Dunaliella viridis in the less saline South Arm. While both are evolutionarily adapted to high saline environments, Dunaliella viridis is far less so, rendering it more vulnerable to the pressing environmental shifts that loom over the lake. As a primary food source for the brine shrimp and flies in the lake, this road to extinction could have catastrophic impacts on the entire Great Salt Lake ecosystem along with critical migratory patterns and climate change dynamics. Studying how Dunaliella viridis responds to these shifting conditions is essential for understanding the danger we are facing as the algae is vital in supporting the microbial food web, brine shrimp and brine fly populations, and ultimately the birds who depend on the lake during their migration. Our experiment mimics real salinity conditions observed in the South Arm of the Great Salt Lake. We prepared four samples of 5% F2 algal media with acetate and a base sodium chloride concentration of 33 g/L: a control with no added salt and three treatments adjusted to 75 g/L, 120 g/L, and 170 g/L of sodium chloride concentration. We then inoculated the media samples in triplicate with Dunaliella viridis to reach an initial concentration of approximately 5.0 × 10⁶ cells/mL. We will be taking cell counts and optical densities to monitor the initial growth curves in each condition. Next, to understand how salinity stress impacts algae carbon intake, we will use the Picarro, a gas analysis instrument with isotopic measuring capabilities, providing further understanding of the imminent threat to our dearly valued Great Salt Lake.

Migration is a key event in the behavior of birds and can have a significant impact on their survival and breeding success. With climatic warming and changing environmental conditions, shifts have been observed in bird migration timing and numbers in many areas. In the spring, birds have been observed to generally migrate earlier. Far more varied changes have been observed in fall migration. I examined 41 years of bird banding data collected at a banding station along the Rio Grande in central New Mexico to determine long term trends in the timing and abundance of seven migratory passerine species during autumn migration. Median capture date was used to estimate peak migration in each year, and birds captured per 100 net hours was used to estimate abundance and account for varying effort. Only one of the seven species, dusky flycatcher, had a statistically significant change in migration time, advancing migration over 18 years. Two warbler species, while not statistically significant, delayed migration by several days over 41 years. Four of the seven species showed increased abundance at the site. No other species experienced large changes in abundance, and no species decreased considerably. These findings highlight the variability of long term changes in fall bird migration timing and abundance over time.

Preserving genetic diversity in plant populations is a goal of both restoration ecology as well as horticulturists interested in growing native plants. However, native plants have mechanisms that prevent germination. This dormancy may be advantageous in the wild but breaking it can sometimes take up to years to do in cultivation. Due to this problem we investigated several strategies to improve and speed the germination rates of three Utah native plant species. We focused on Arctostaphylos pumila, Sambucus cereaulea, and Amalanchier alnifolia, all species with fleshy fruits and potential for home landscapes. We tested seeds of these species using cold stratification, a fire treatment, an acid treatment, and combinations of these. We expect the treatments will improve the number of seeds germinating as well as increase the speed of germination. We hope that our results will lead to improved and easier methods for germinating these native plants.

We will be comparing sites with varying wildfire histories to observe if more native or invasive species dominate after a wildfire. The aftermath of a wildfire creates opportunities for new plants to grow in the new bare ground. Fast-growing invasive species may take this chance to expand in population and dominate the area. Native plants may control the land after the invasive species have been burnt away. We will test this by assessing the plant communities at varying sites with different wildfire histories; within the past year, 5 years, and 10 years ago. Each community site will be surveyed in 3 1m2 plots. We will also survey an unaffected area near each site as a control, comparing the differences in vegetation after a wildfire. We expect for the invasive species to take over as they grow and populate quickly. This study may assist in deciding how to manage land after a wildfire. If invasive species dominate the area, then weeding invasives, or reseeding & planting native plants may be helpful for the site recovery.

Background: One key element for providing quality speech language pathology (SLP) services in a school setting is service delivery schedules (i.e., length and frequency of sessions). Generally, school-based SLPs utilize a service delivery schedule of providing one or two 30-minute sessions per week for language intervention; following professional convention. Most literature examining service delivery elements have utilized longer sessions rather than shorter sessions that could be successfully implemented in a school setting. Further exploration is necessary to understand the impact of various service delivery models that could be applied to school-based settings. To address this gap in the literature, we explored: 1) the extent to which different service delivery schedules (i.e., one 30-minute session or three 10-minute sessions per week) impacted language outcomes across an 8-week period of time; and 2) whether the participants and their parents considered their experience in treatment to be acceptable.

Method: For this exploratory study, we recruited four participants (aged 8;0-11;1) and randomized them into one of two conditions. Condition 1 consisted of one 30-minute session per week, and Condition 2 consisted of three 10-minute sessions per week. Each condition equated to four total hours in treatment across eight weeks. Treatment for all participants utilized a standard storytelling intervention focused on retelling stories and generating personal stories. Single case multiple baseline design with randomized start points was used to track change in participant skills over time. In addition, magnitude of change from treatment will be measured using Tau and compared across the two conditions. Semi-structured interviews were used to collect data about treatment acceptability and will be analyzed using Qualitative Content Analysis.

Anticipated Results: Data collection was recently completed and is currently being processed. Preliminary examination of the data suggests that Condition 1 supported greater change for retelling stories whereas Condition 2 supported greater change for generating personal stories. It is anticipated that upon completion of data analysis, parents and participants will find both service delivery schedules to be acceptable.

Clinical implications: Results suggest the professional convention of utilizing 30-minute sessions may be beneficial depending on the desired outcome. SLPs may need to consider the desired outcomes of treatment (i.e., story retell or social/personal storytelling) when selecting which service delivery schedule is most appropriate for their students. Future directions include replication and expansion to examine the impact of service delivery schedules on a wider range of language goals.

Early exposure to positive STEM experiences can play a critical role in shaping students' attitudes toward science and their interest in pursuing STEM-related careers. The Little Lab Rats Outreach Project aims to foster curiosity and positive associations with science through interactive, collaborative, hands-on games designed for K-6 students. These activities introduce core scientific practices, such as hypothesis testing, experimentation, and evidence-based reasoning within engaging and playful contexts. In particular, the project prioritizes reaching underserved communities to ensure equitable access to meaningful and inspiring STEM learning experiences. Our study explores how these experiences influence students' perceptions of science and their self-identification with STEM careers. By collecting pre- and post-activity survey data and qualitative feedback, we assess changes in attitudes toward science and career interest. The results of this project may guide the creation of outreach approaches that promote enduring positive experiences and attributions toward science, ultimately fostering sustained interest and broader more diverse participation in STEM disciplines.

Abstract Growing up in Zambia and later studying in the United States has shaped my understanding of global inequality and human rights, particularly the issue of child marriage. In Zambia, public awareness campaigns—such as roadside billboards urging communities not to marry off young girls—are powerful reminders of the ongoing struggle to protect children’s rights. These images have remained with me since childhood and inspired this research project, which seeks to raise awareness among American students about the realities of child marriage in developing countries. By sharing data, context, and human stories, this study aims to promote global empathy and a deeper understanding of how gender inequality and poverty intersect to limit opportunities for girls. This research uses a qualitative review of secondary data drawn from national and international sources, including the Zambia Demographic and Health Survey (ZDHS, 2024), UNICEF, UNFPA, and the World Bank. Reports and peer-reviewed studies were analyzed to identify statistical trends, policy responses, and socio-cultural factors contributing to child marriage. Findings reveal that approximately 29% of Zambian women aged 20–24 were married before the age of 18, and 5% before age 15 (UNICEF, 2024). The practice remains most prevalent in rural areas, where economic hardship, limited educational opportunities, and cultural traditions reinforce early marriage as a perceived social or financial necessity. Although Zambia’s Marriage Act now legally establishes 18 as the minimum age for marriage, enforcement remains inconsistent, particularly in customary and informal unions that fall outside statutory regulation. The persistence of child marriage demonstrates how legal reforms alone are insufficient without addressing underlying economic and cultural conditions. This study highlights the importance of community-based education, poverty reduction efforts, and empowerment programs that engage local leaders and families. By examining Zambia’s experience, this research underscores the need for sustained awareness, both locally and globally. It also invites American students to reflect on their role in promoting gender equality and human rights, fostering a more connected and compassionate approach to global citizenship.

Effective communication is essential to the education of multilingual learners (MLs) and educators can make accommodations for the benefit of their students. One of the most impactful strategies in accommodating the needs of MLs is adjusting the pace of speech, use of vocabulary, and pronunciation. In this study, tutors for MLs made note of the differences in conversation capabilities of students learning English when the pace of conversation was slowed and vocabulary was simplified. At the tutors' university, there is an ESL program for students wanting to learn English in college, with the majority of them being international students studying in the US or recent immigrants to the US. As part of the students' required workload, they must meet weekly with the ESL tutors in 15 minute sessions to practice conversing on various topics relating to what the students had learned in their ESL courses that week or any topic the students desired to discuss. During the sessions, the tutors would follow a pattern of asking questions to the students, listening to the student responses, and responding with their input as well to maintain a conversation. It was discovered that the MLs were able to contribute best to the conversation when the tutors slowed their speech pace a little to allow for extra processing time to decode unfamiliar words and phrases. With the slower pace, the ML students were also able to formulate more complex responses and think about how they could expand on the conversation. The tutors also learned to adjust their use of vocabulary by using comprehensible input when talking to the students because it is important for MLs to expand their vocabulary knowledge but they do not want to confuse the student with too many unfamiliar concepts. Comprehensible input, a theory coined by James Cummins, is the concept of giving students language input that is slightly above their current proficiency level. This ensures that MLs can use context clues and their current language proficiency to decode unfamiliar phrases. The conclusions from this tutoring study found that the MLs were able to respond best when the pace of conversation was decelerated enough to allow for more processing time and using vocabulary that pushes students to learn more without overcomplicating the conversation to a point where they cannot maintain the interaction.

Sexual health and well-being encompass three interrelated components: sexual health, sexual pleasure, and sexual rights. Young adulthood is a critical developmental stage during which sexual experiences and education shape long-term attitudes, behaviors, and outcomes. The sources from which individuals learn about sexuality strongly influence these outcomes. Rodrigues et al. (2024) proposed a four-category framework for classifying these sources: formal traditional, informal traditional, formal modern, and informal modern. Utah provides a distinctive sociocultural context for examining these dynamics due to its restrictive, abstinence-based sex education policies, which may lead young adults to seek alternative sources of information. Despite growing literature on sexuality education, few studies have examined how diverse sources of information relate to all three domains of sexual health and well-being, particularly in restrictive policy environments or among young adult populations. To address this gap, the present study asks: A) What are the most frequently reported primary and secondary sources of sexuality reported by young adults in Utah? B) How do scores of sexual health and well-being differ across reported primary sources of sexuality information? Using a cross-sectional online survey, participants will report their primary and secondary sources of sexuality information using Rodrigues et al.’s (2024) four-category framework and complete the Natsal Sexual Well-being Measure (Mitchell et al., 2025). Demographic data will also be collected. Analyses will include descriptive statistics, Pearson correlations, and one-way ANOVAs. While this project is in progress, we hypothesize that young adults who report receiving comprehensive, inclusive sexuality education will score higher on measures of sexual health and well-being. In this poster presentation, we will share our theory and argument for the importance of understanding how educational contexts and information sources impact sexual health and well-being in young adults.

Background: Communication often occurs in distracting environments, requiring the speaker to split attention between speaking and attending to another task. While communicating in this manner is often necessary, it results in greater cognitive load, which may negatively impact spoken language (Engonopulos et al., 2013). For example, previous research has shown that dual-task conditions (e.g., walking while talking and performing pursuit rotor tracking while talking) interfere with fluency, complexity, and coherence of spoken language (Kemper et al., 2005; Kemper et al., 2009; Kemper et al., 2010). This study aims to determine how computer-based dual tasking impacts spoken language production for young and older adults.

Methods: Participants included two age groups: 30 young adults (18-30) and 30 older adults (55+). Each participant was asked to perform various speaking tasks to quantify the effects of computer-based multitasking on spoken language. Participants completed procedural discourse tasks across four conditions: (1) in isolation, (2) while making formatting changes to a Microsoft Word document by highlighting every instance of “the” (i.e., formatting level 1), (3) while making formatting changes to a Microsoft Word document by highlighting “the” and underlining each occurrence of “a” (i.e., formatting level 2), and (4) entering data in Microsoft Excel by sorting items from a shopping list into appropriate categories (i.e., data entry). Each task lasted 60 seconds. Language samples were transcribed and coded using the multilevel language analysis approach described by Marini et al., 2011. Coding and analysis will be completed using Codes for the Human Analysis of Transcripts (CHAT) and Computerized Language ANalysis (CLAN) to determine how computer tasks affected spoken language. Dependent variables will include speech rate, disfluencies, lexical-phonological errors, morphosyntactic errors, and macrolinguistic errors.

Anticipated Results: Based on previous findings (Kemper et al., 2005; Kemper et al., 2009; Kemper et al., 2010), we expect computer-based multitasking to interfere with spoken language for both young and older adults but in different ways. Specifically, we anticipate that young adults will significantly slow down during multitasking conditions and produce more verbal disfluencies but otherwise maintain relatively accurate production. For older adults, we anticipate that multitasking will interfere more with their accuracy as manifested by more lexical-phonological and macrolinguistic errors. Findings have implications for vocational training as contemporary work often requires simultaneous communication and computer-based tasks. Future research should also use similar conditions with participants with communication disorders to better understand how to help them re-enter the workforce.

Spinal disc replacement has become a common treatment for both acute and chronic cervical spine pain and for limited indications in lumbar spine pain [1]. The most common total disc replacements (TDRs) involve ball and socket mechanisms in which a polyethylene insert articulates against a metal bearing surface. This type of design has a long history of successful use in diarthrodial joint replacement. However, a low-friction, fixed center of rotation disc replacement cannot duplicate the more complex biomechanics of the spinal disc. Our research team has designed a novel lumbar disc replacement device based on an interior compliant rolling element (I-CORE) compliant mechanism that accurately reproduces the biomechanics of the healthy spinal disc. A unique feature of the design was its intentional design for a lateral surgical approach, which significantly reduces the surgical complexity of the procedure as well as reducing the potential for iatrogenic damage. An additional advantage of the design is that it does not include sliding components (i.e., the device reduces wear and associated wear debris). The purpose of the present work was to validate that the device meets or exceeds the performance of currently approved lumbar spinal disc replacements when undergoing benchtop mechanical testing. Static testing in compression, compressive shear (10 degree and 45 degree), and torsion was performed following the ASTM F2346-18 [2] standard with slight modifications. For example, 304 stainless steel with a yield strength of 1170 MPa was used for the testing fixture rather than high-strength steel, due to ease of access and machineability. Four printed titanium prototypes of the novel disc replacement were subjected to the mechanical testing regimen. Each device was tested to sub-yield loading in each of the four modes of loading three times, after which one of the devices was loaded to static failure in each mode of loading. Results indicated that the device performs comparably with currently FDA-approved lumbar spinal disc replacements under similar test conditions. REFERENCES: [1] Lanman Spinal Neurosurgery. (n.d.). Types of artificial disc replacement: Fully explained (with photos). Spine.MD. https://www.spine.md/artificial-disc-replacement/types-of-artificial-disc-replacement/. [2] ASTM International. (2018). Standard test methods for static and dynamic characterization of spinal artificial discs: ASTM F2346-18. https://doi.org/10.1520/F2346-18.

After amputation, many transtibial amputees experience pain due to walking with a passive prosthesis. Available passive ankle prostheses do not provide as much push-off power as a biological ankle, leading to compensatory hip effort and asymmetric gait. Conditions like these can predispose individuals to secondary conditions such as osteoarthritis and back pain, negatively impacting quality of life. A powered ankle prosthesis is a promising solution as it can replace the full push-off power of a biological ankle by providing active torque to drive the person forward. However, it is unclear whether replacing the push-off power at the ankle can effectively reduce residual hip work. One transtibial amputee walked on an instrumented treadmill using the Utah Powered Ankle. The prosthesis supplied two different levels of push-off power: 1.4 W and 2.3 W. The lower power is comparable to a passive ankle prosthesis and the higher power is comparable to a biological ankle. A twelve camera motion capture system recorded walking kinematics. We processed the results using Vicon Nexus, Visual3D, and MATLAB. Key outcome measures included the work done by the residual hip, and the ankle power index of asymmetry (IOA) which quantifies the relative difference in ankle power generation between the prosthesis and intact sides. When comparing high and low push-off levels, greater ankle power reduced hip work. At the low level of push-off, hip work was 0.046 +/- 0.0037 J, while at the high push-off level, hip work decreased to 0.038 +/- 0.0051 J. Increasing push-off power also improved symmetry. At the low push-off level, the IOA was −0.18 +/- 0.097, meaning the intact ankle produced more power than the prosthetic ankle. At the high push-off level, the IOA increased to 0.038 +/- 0.12, indicating that the prosthetic ankle generated slightly more power than the intact ankle. These results suggest that greater push-off power from the prosthesis leads to a more symmetric and natural gait pattern. In the low push-off condition, the prosthesis provides little energy return, so the user compensates by generating more work at the hip. When the prosthesis contributes more ankle power, the hip no longer needs to overcompensate to maintain gait speed. By improving push-off symmetry and reducing hip compensatory work, powered ankle prostheses have the potential to reduce the risk of painful secondary conditions and improve the quality of life for individuals with transtibial amputation.

After amputation, many transtibial amputees experience pain due to walking with a passive prosthesis. Available passive ankle prostheses do not provide as much push-off power as a biological ankle, leading to compensatory hip effort and asymmetric gait. Conditions like these can predispose individuals to secondary conditions such as osteoarthritis and back pain, negatively impacting quality of life. A powered ankle prosthesis is a promising solution as it can replace the full push-off power of a biological ankle by providing active torque to drive the person forward. However, it is unclear whether replacing the push-off power at the ankle can effectively reduce residual hip work.

One transtibial amputee walked on an instrumented treadmill using the Utah Powered Ankle. The prosthesis supplied two different levels of push-off power: 1.4 W and 2.3 W. The lower power is comparable to a passive ankle prosthesis and the higher power is comparable to a biological ankle. A twelve camera motion capture system recorded walking kinematics. We processed the results using Vicon Nexus, Visual3D, and MATLAB. Key outcome measures included the work done by the residual hip, and the ankle power index of asymmetry (IOA) which quantifies the relative difference in ankle power generation between the prosthesis and intact sides.

When comparing high and low push-off levels, greater ankle power reduced hip work. At the low level of push-off, hip work was 0.046 +/- 0.0037 J, while at the high push-off level, hip work decreased to 0.038 +/- 0.0051 J. Increasing push-off power also improved symmetry. At the low push-off level, the IOA was -0.18 +/- 0.097, meaning the intact ankle produced more power than the prosthetic ankle. At the high push-off level, the IOA increased to 0.038 +/- 0.12, indicating that the prosthetic ankle generated slightly more power than the intact ankle.

These results suggest that greater push-off power from the prosthesis leads to a more symmetric and natural gait pattern. In the low push-off condition, the prosthesis provides little energy return, so the user compensates by generating more work at the hip. When the prosthesis contributes more ankle power, the hip no longer needs to overcompensate to maintain gait speed. By improving push-off symmetry and reducing hip compensatory work, powered ankle prostheses have the potential to reduce the risk of painful secondary conditions and improve the quality of life for individuals with transtibial amputation.

Chronic Venous Insufficiency (CVI) is a dangerous and painful condition that affects 150,000 new patients each year, with an annual direct cost of approximately $500 million [1]. Current clinical solutions are primarily based around ablation or removal of compromised veins; however, these procedures have serious long-term consequences and do not halt progression of the condition. A potential alternative solution is to replace the venous valve entirely.

The purpose of the current work was to develop proof-of-concept designs that fulfilled the functional requirements for an artificial venous valve, and then to evaluate the utility of those designs using prototyping and computational modeling. Following a structured design process, we arrived at 2 candidate designs that show promise. The first design is a modified Tesla valve design, which consists of a series of diverging and converging paths that cause self-interference of the fluid flow. Including compliance with the structure and/or added flaps improved the effectiveness of the valve in resisting reflux. The second design included a series of compliant arches forming a convex dome, over which a very flexible material (such as Gor-Tex) formed overlapping leaves. The flexible leaves were designed to be efficiently manufactured from a single, laser-cut sheet and to easily be connected to the stent-arch structure.

Both designs were prototyped for empirical testing. Additionally, the performance of the designs was predicted using computational fluid dynamics simulations and fluid-structural interaction analysis in order to compare performance with published data of natural venous valves. After the designs were validated, further analysis and optimization was done to mimic natural functionality.

[1] Patel SK and Surowiec SM (2024), "Venous insufficiency" NIH StatPearls Publishing, LLC, PMID: 28613694.

INTRODUCTION: Chronic low back pain is increasingly the leading cause of long-term disability worldwide, with 800 million cases projected by 2050 [1]. This condition often results in surgical intervention such as total disc replacement (TDR) to alleviate pain and restore mobility. Current TDR implants use ball-and-socket designs, which are prone to generating excessive wear debris and therefore introducing inflammation and spinal pathologies such as osteolysis. Our lab previously developed a novel, anteriorly inserted Lumbar Compliant Interbody Device (L-CID) that successfully mimics the healthy biomechanics of a lumbar spinal disc and greatly reduces wear debris [2]. While the anterior device is effective, a lateral approach is often advantageous in TDR as it can reduce tissue disruption and accelerate patient recovery [3, 4].

METHODS: The geometry of the original anterior L-CID was modified to fit the inherent anatomical limitations of the lateral surgical corridor. The new Lateral L-CID is similar to its predecessor in that it is still a single-piece implant, 3D-printed through selective laser melting and made of grade 23 Ti6Al4V. The primary changes include a longer, narrower profile and a rounded bullet nose for safe insertion. Superior and inferior keels on the endplates ensure stable fixation in the intervertebral space. To accommodate variety in spine geometry, three variations of the L-CID were made to fit lordotic angles at zero, six, and ten degrees. We used finite element analysis (FEA) to simulate physiological loads, and the results were compared to force displacement curves obtained from testing cadaveric functional spinal units (FSUs).

RESULTS AND DISCUSSION: The FEA and mechanical testing data showed that the Lateral L-CID preserved biomechanical function of the original anterior design while conforming to the size constraints of a lateral approach. The force-displacement curves of the lateral device are very similar to both the anterior version and the tested FSUs. The graph shows a two-phase response: an initial low-stiffness region that allows for natural movement, followed by a much stiffer phase once the geometry reaches its displacement limit. The lateral L-CID has the potential to expand treatment options for TDR by adapting the original anterior device for situations where a lateral approach is advantageous.

REFERENCES: [1] M. Ferreira et al, Lancet Rheumatol, 2023, 5(6), p. 316-329. [2] D. Orr et al, J Med Devices, 2025, 19(3). [3] G. Tsalimas et al, J Med Life, 2025, 18(3), p. 165-170. [4] B.M. Ozgur et al, Spine, 2006, 6(4), p. 435-443.

Thermal diffusivity and thermal transport anisotropy are critical properties in material selection for a wide variety of fields. Frequency-domain thermoreflectance (FDTR) is a non-contact optical technique that measures thermal diffusivity by analyzing the phase lag between modulated heating from a pump laser and the temperature response of a probe laser.

Previous methods of FDTR have required significant investments of time and setup due to the precision needed in laser alignment, sample placement, and manual laser frequency modulation. We have developed an automated FDTR workflow that streamlines data collection and processing across multiple orientations, to produce more repeatable and analysis ready data, faster.

This work highlights how integrating automated experimental methods can enable the analysis of structural and functional materials. With the consistently increasing demand for materials with tailored thermal properties in fields like nuclear power and biomedical engineering, automation is a critical tool to meet the growing need for data.

The rate of development of wind energy has dramatically accelerated in recent years, driven by the increasing global demand for clean and sustainable energy sources. Wind energy has emerged as a reliable and environmentally favorable alternative to traditional energy sources. However, the efficiency and performance of new wind turbine designs heavily depend on the precision, accuracy, and speed of the analysis tools used to create them.
WATT.jl is an aeroelastic code that couples aerodynamic and structural solvers, including CCBlade, DynamicStallModels, and GXBeam. It uses gradient-based optimization to provide an algorithmic approach to producing optimal designs. Within this framework, GXBeam employs geometrically exact beam theory to perform static and dynamic structural analyses, providing the structural solutions necessary to accurately model turbine behavior. Despite its accuracy, GXBeam is the primary computational bottleneck in WATT.jl and significantly limits overall simulation performance and speed. Reducing computational time is essential for WATT.jl to become a practical design tool and produce exact gradients cheaply.
This research focuses on improving the efficiency of the structural analysis by developing a faster constant mass matrix formulation for large-scale aeroelastic simulations. By reducing computational cost associated with repeated mass matrix assembly while preserving numerical accuracy, this approach aims to significantly accelerate aeroelastic simulations, allowing faster analysis for gradient-based optimization.

Autonomous robot swarms enable large-scale exploration and environmental mapping in GPS-denied environments, yet practical deployment of truly decentralized systems lacks reliable positioning without centralized infrastructure. Current multi-robot coordination relies on either global positioning systems (GPS), which are unavailable indoors and denied environments, or bandwidth-intensive inter-robot communication architectures. This research investigates a novel approach: whether robots can reliably estimate relative positions using visual features from their cameras alone, while intelligently managing communication overhead through adaptive feature selection.

We propose an integrated system where multiple robots execute concurrent line-following navigation and environmental mapping tasks. Each robot builds an independent local environmental map using lightweight CNN/Vision Transformer neural networks for robust visual feature extraction. The core innovation is a decentralized mechanism where robots identify shared visual landmarks in their local maps and infer relative positions through geometric triangulation. Critically, instead of exchanging all detected features, the system employs an adaptive feature selection strategy: each robot intelligently selects which visual features to share based on utility metrics (distinctiveness, stability, geometric importance) and current communication bandwidth constraints. This adaptive selection significantly reduces communication overhead while maintaining localization accuracy.

The system combines three core components: (1) lightweight CNN/Vision Transformer neural networks for efficient feature extraction across varying environmental conditions, (2) classical geometric pose estimation and triangulation algorithms for deterministic inter-robot relative localization, and (3) an adaptive feature selection mechanism integrated with decentralized consensus protocols for communication-constrained coordination.

Deployed on TurboPi robots (Raspberry Pi 5, 8GB RAM), we evaluate two specific research objectives: First, whether visual landmark correspondence in independently computed local maps provides sufficient geometric information for accurate inter-robot positioning. Second, how adaptive feature selection achieves communication efficiency without compromising localization accuracy.

Evaluation involves two robots performing concurrent line-following and mapping tasks in shared environments. Key measurements include: (1) relative position estimate accuracy, (2) communication overhead comparison-adaptive selection versus baseline (target: >50% bandwidth reduction with minimal accuracy loss), (3) robustness across different environmental conditions and lighting variations, and (4) practical feasibility on resource-constrained hardware.

Results demonstrate that visual-only inter-robot positioning is viable on budget platforms, and that intelligent feature selection achieves significant communication savings-addressing a critical bottleneck in decentralized swarm coordination. This work directly enables practical deployment of autonomous swarms for search-and-rescue, agricultural monitoring, and infrastructure inspection applications where GPS is unavailable and communication bandwidth is limited. Open-source implementation and reproducible evaluation methodology support future research in edge-deployed autonomous systems.

For robots to be more integrated into our lives, they need to be safer for gentle interaction with humans and their environments while maintaining their strength. Our research seeks to address this need by designing and building a soft robot made of a collection of balloons capable of coordinated self-inflation to allow the robot to move itself as well as lift and manipulate other objects. This novel type of robot could safely interact with its environment, even while exerting large forces, by distributing a relatively low pressure over a large area. This quality gives our robot potential for applications like removing rubble in search and rescue or holding and manipulating patients dynamically and comfortably in a healthcare setting. This work will focus primarily on the manufacturing methods and mechatronic design of the robot.

Our robot is comprised of many individual balloons that can change shape. Custom balloons are cast using a soft, stretchy silicone (Ecoflex 0030), in a 3D printed mold. This process allows us to create balloons with high elastic deformation ranges, uniform inflation and the ability to easily integrate other components. We have found that they can reach 3 times their original size before they start to deform permanently and 6.5 times their original size before popping, while the pressure stays relatively low (~0.7 psi).

For the robot to function, each balloon must independently control its size. This must account for the fact that the pressure and size of a balloon do not have a clear correlation. Instead, we must estimate the volume of air within the balloon. This can include measuring distinct air pulses using a peristaltic pump or timing solenoid valve actuation. We also want to track the shape and size of our balloons through a code that analyzes video footage of our robot. This approach helps us more accurately compare our physical inflation tests with our simulated robot movement.

This highly customized method of manufacturing and mechatronics will allow us to explore soft robots that are both soft and strong. Our future work includes refining methods for connecting the balloons that allow increased freedom of motion, implementing new methods of measuring the volume of each balloon for precise control, and adapting the robot for bearing and manipulating loads. Pursuing these goals could open new possibilities for technologies that help robots interact with people and fragile environments more safely.

The Department of Defense and Missile Defense Agency are pursuing a new class of hypersonic vehicles capable of sustained flight in the stratosphere. This flight regime introduces extreme heating, chemical dissociation, and material ablation effects that are not encountered elsewhere in aerospace applications. While analytical and computational tools for hypersonic flows have advanced considerably, experimental testing remains indispensable for technology development and validation. However, high-enthalpy testing is prohibitively expensive, and access to the limited number of high-fidelity facilities is restricted to mature, high-Technology Readiness Level (TRL) programs. As a result, early-stage hypersonic concepts face significant barriers to experimental evaluation.
This project aims to address that gap through the development of a gas-generator system based on "green" propellant hybrid rockets as a low-cost, mid-fidelity testbed for hypersonic research. The system includes a thrust chamber, nozzle, and a secondary gas-injection system for regulating plume temperature. This configuration will enable controlled simulation of hypersonic flow environments for applications such as materials testing, sensor development, and code validation.
When fully developed, the proposed technology will provide a unique national testing capability. This approach enables simultaneous replication of flight-like enthalpy and dynamic pressure, which is unachievable for existing hypersonic arc-jet facilities. Because mid-fidelity testing can be performed at a fraction of the cost and at a higher rate of turnover than can be achieved with the current generation of high-enthalpy facilities, it will be invaluable for maturing novel hypersonic concepts. This approach will accelerate concept maturation, improve access to experimental data, and enhance the overall pace of innovation in hypersonic systems research and development.

Achieving high-density yttria-stabilized zirconia (YSZ) electrolytes is essential for optimal performance in solid oxide fuel cells (SOFCs). This work evaluates multiple compaction approaches, processing parameters, and density characterization methods to develop YSZ samples suitable for electrochemical and microstructural analysis. Several three-dimensional characterization techniques were compared, including a FaroArm laser scanner and a Keyence digital microscope. The Keyence system provided higher-resolution surface measurements, enabling more reliable density and microstructure evaluation. Processing conditions were also examined, and results indicate that increases in sintering temperature had a greater effect on densification than variations in pressing pressure. By integrating quantitative density measurements with microstructural imaging, this study establishes a reproducible framework for producing high-quality YSZ ceramics that support continued grain boundary and SOFC performance research.
Keywords: Solid Oxide Fuel Cells, Density, 3D Volumetric Characterization

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder affecting over 6 million Americans. One key pathological hallmark of AD is the buildup of amyloid-beta (Aβ) plaques, which contribute to neuronal dysfunction and memory loss. Recent research suggests that reactivation of latent Herpes Simplex Virus Type 1 (HSV-1) in the brain may accelerate Aβ aggregation and inflammation, especially in individuals carrying the APOE-e4 allele. Quercetin (Q), a naturally occurring flavonoid used to treat HSV-1 infections, has demonstrated potential to reduce viral-induced neuroinflammation. However, its effectiveness in treating AD is limited due to low bioavailability and poor permeability across the blood-brain barrier (BBB).

This study aims to develop a nanoparticle-based nasal drug delivery system to enhance antiviral's bioavailability and target delivery to the brain. Nanoparticles are synthesized from poly(lactic-co-glycolic acid) (PLGA) and coated with Poloxamer 188 (P188) using a nanoprecipitation method. This formulation supports controlled drug release, increased stability, and direct nose-to-brain transport via the olfactory and trigeminal nerve pathways, bypassing the BBB. Characterization includes dynamic light scattering for particle size, zeta potential for surface charge, atomic force microscopy for morphology, and UV-Vis spectroscopy for encapsulation efficiency. Current experiments are focused on drug release profiling in physiological conditions, cytotoxicity assays using 3T3 fibroblasts, and antiviral testing against HSV-1 in infected cell lines. Results are in progress, with current efforts focused on nanoparticle characterization, sustained drug release profiling, and in vitro antiviral testing.

Preserving historical buildings is not only a sustainable practice that reduces construction waste sent to landfills, but it is also an excellent way to pass on cultural identity to future generations. (Scaron, 2020). The Giv Legacy reimagines the historic U.S. Forest Service Building in Ogden, Utah, as a vibrant, multi-use space that balances heritage preservation with community enrichment. Aging infrastructure, outdated systems, and accessibility challenges limit the building's functionality, making adaptive reuse essential to support contemporary cultural, educational, and residential needs. The project repurposes the basement and first floor into dynamic, student-focused environments for Weber State University, featuring an art gallery and flexible creative spaces. Meanwhile, the upper floors are transformed into affordable residential units that address local housing needs. Design strategies draw on heritage-inspired approaches, historical revival, free historicism, and eclectic historicism to preserve architectural identity while integrating sustainable materials and modern functionality (Rashdan & Ashour, 2024). Acoustic wall panels, adjustable walls, and Art Deco-inspired furniture and lighting allow spaces to serve multiple functions while maintaining elegance, ensuring both form and function in a timeless design (Ullah et al., 2025). By uniting historical preservation with flexible design and community engagement, The Giv Legacy's main goal focuses on Ogden's cultural heritage, fosters creativity and social connection, and advances sustainable urban revitalization.

Understanding the thermal properties of biological materials can provide valuable insights for applications in energy-efficient materials and insulation design. This project investigates the thermal transfer coefficient of animal hair to evaluate how its heat transfer characteristics vary between summer and winter seasons. Many mammals adapt to seasonal temperature changes by altering the thickness, density, and internal structure of their hair. However, few studies have quantitatively measured how these structural changes influence thermal conductivity or the overall heat transfer coefficient.

The purpose of this research is to quantify the heat transfer coefficient of animal hair and determine whether significant differences exist between winter and summer samples. Hair samples from different mammals were collected and analyzed under controlled conditions. To assess thermal performance, the samples were subjected to a steady-state heat transfer experiment designed to measure the rate of heat conduction through the hair. The thermal conductivity and convection effects were then used to calculate the overall heat transfer coefficient.

Preliminary results indicate measurable differences in the thermal behavior between winter and summer hair. Winter hair, characterized by larger air pockets and thicker shafts, demonstrated lower heat transfer coefficients, suggesting improved insulation efficiency. Conversely, summer hair allowed greater heat flow, consistent with thermoregulatory adaptations in warm conditions.

By scaling these biological heat transfer mechanisms, this study aims to inspire biomimetic applications in materials engineering, such as developing sustainable and thermally adaptive building materials. Future work will involve creating 3D-printed models of hair structures to further explore their thermodynamic behavior and validate their potential in architectural and environmental design contexts.

Involvement in opportunities beyond the classroom are among the most impactful developmental experiences for students. Opportunities to engage in research stimulate critical reasoning, creativity, and problem solving skill sets that are a basis for success in academia and a career both now and in the future. Students develop a more thorough understanding of their academic discipline, grow their scholarly identity, and enhance their academic chapter. Students also foster lasting mentor relationships with faculty and access unique scholarship, internship, and research opportunities that prepare them for careers in competitive fields and graduate programs. Nevertheless, many students do not pursue these types of engagement with research opportunities, as they find no clear entry point, do not know how to search for engagement opportunities, or simply do not know or feel intimidated in traversing the academic unknown.

The project aims to address the obstacles described above by establishing a scaffolded, student centered platform; one that was intended to make research more accessible, supported, and engaging to students at all levels. The platform will offer a guided, structured experience with curated research pathways, defined mentorship pathways, interactive learning modules, and tools to track student progress from the initial exploration period through to project completion. The goal of streamlining and organizing the research experience will reduce barriers for students related to gaps in knowledge, underdeveloped self confidence, and inconsistency in access to information or other resources. The scaffolding process will also demystify the research exercise by reducing the overall research task into discrete, manageable elements thereby allowing individual students to enhance their own momentum and progress with more comfort and confidence.

In addition to supporting the individual journeys of researchers, the goal is to create a culture on campus that promotes inquiry, exploration, and scholarly development. The platform normalizes engaging in research and provides the tools that will support skill development, allowing students to develop key habits of practice, such as reflection, planning, communication, and resilience. The peer mentoring structure also fosters collaboration between students and faculty, developing an inclusive academic community focused on nurturing curiosity and sharing in the success of all. Ultimately, the project seeks to develop students who have the capacity to not only conduct research but also have the confidence to see themselves as scholars and professionals. The platform supports students by removing barriers for participation, improving access to opportunities arranged for them, and increased guidance to aid students in realizing their potential in their desired academic and professional future and transforming from passive bystanders to engaged and active participants in the communities in which they aspire to belong.

Soft robots can enable new applications in the healthcare and public safety industry. They boast flexibility, adaptability, and provide safe human contact. Their inherent compliance means that the robots will change shape under different loads. Our research focuses on a soft robot made of multiple, spherical silicone bubbles that individually inflate and deflate to form different structures. As the robot inflates, it applies a strong force over a large contact area capable of lifting debris, people, or structures safely. To capture this behavior, we will develop an analytical model and perform experiments on how a single bubble deforms as it’s being compressed by two parallel, flat planes.

Our analytical model computes the force required to compress the bubble to a specified displacement. While prior studies have examined deformations of spherical objects, our model differs from these studies by incorporating large strain and nonlinear material effects. First, the model looks at the cross section in the middle of the sphere and assumes the membrane to always be in tension. Then, a model is derived by equating the pressure force, the tensile force in the membrane, and the external force applied to the system. Finally, external force as a function of the sphere’s geometry and the internal pressure can be computed.

To validate the analytical predictions, we will conduct experiments by fabricating a silicone bubble and compressing it. We will measure force with a load cell, and shape will be recorded with a camera while controlling the displacement and internal pressure. Plots relating the applied force to the geometry of the bubble with varying internal pressure values will be generated. Juxtaposing the analytical model with the test data will allow us to improve our analytic model and predict the eventual behavior of the robot.

These results enable accurate prediction of the bubble’s deformation under real-world loads. One application is a soft robot that can inflate under a hospital patient to reposition them in bed. This research will help us understand how the robot will deform under the force of a human body. The aforementioned research would aid in the kinematics of soft robots that are formed from many interconnected bubbles and enable them to locomote and manipulate objects.

Plastic pollution is a critical global issue because synthetic polymers such as polyethylene terephthalate (PET) are highly resistant to microbial degradation, allowing them to persist in the environment for centuries. The discovery of PETase, an enzyme capable of hydrolyzing PET into its monomeric components, provides a promising biocatalytic route for sustainable plastic recycling. However, the wild-type PETase exhibits limited thermostability, restricting its application under industrial processing conditions. Enhancing the enzyme's thermal stability without impairing catalytic activity remains a central challenge in bioengineering. This project aims to develop an integrated computational framework that combines data-driven machine learning with physics-based energy modeling to identify mutations that improve PETase thermostability. We will first curate a comprehensive dataset of stability measurements for PETase-related enzymes from public resources such as ProThermDB and ThermoMutDB. Physics-based models (FoldX and Rosetta) will be used to evaluate residue energetics and identify active and structurally sensitive positions most likely to influence thermostability of PETase. A geometric deep learning model (GeoStab), pre-trained on large-scale protein stability datasets, will then predict changes in folding free energy and melting temperature upon mutations at these selected positions. The model will be fine-tuned on PETase-specific data to capture enzyme-specific nuances. Finally, molecular dynamics simulations and enhanced sampling will be applied to validate top-ranked variants and assess potential backbone effects. We anticipate that this hierarchically integrated pipeline, combining physics-based and machine learning approaches, will yield a prioritized set of thermostabilizing mutations with improved predictive accuracy over standalone methods. We will further evaluate the effectiveness of the proposed framework in advancing the rational engineering of PETase for industrial-scale biodegradation by submitting the top-ranked computational designs to 2025 PETase Engineering Tournament organized by Align Foundation for experimental validation and benchmarking.

Ants are one of the most abundant and ecologically influential insect groups on Earth, a success often attributed to their complex social organization and cooperative behavior. One colony structure thought to contribute to this success is polydomy, the occupation of multiple socially connected but spatially separated nests. Understanding how polydomy improves colony performance is essential for explaining the success of invasive ants, yet field studies are often laborious and costly. We use mathematical modeling to examine how spatial organization influences foraging efficiency and resource allocation in the polydomous ant genus Oecophylla. Building on the optimization models of Adler & Gordon (2003), we investigate whether increased foraging success promotes the emergence and stability of polydomy. We further develop an agent-based model to explore how colonies achieve spatial and foraging equilibrium under competitive pressure. Preliminary simulations indicate that polydomous organization extends effective foraging range and increases collective resource return, supporting the hypothesis that polydomy improves foraging efficiency These findings suggest that spatially distributed nests can enhance overall colony performance with minimal changes in individual behavior. By combining optimization and agent-based modeling, this study provides mechanistic insight into the conditions that favor polydomy and contributes to a broader understanding of how spatial organization promotes the evolutionary success of social insects.

Success in college goes far beyond grades or attendance. It depends on how students feel, think, and belong within the campus community. Many institutions still struggle to understand why some students flourish while others quietly disengage. Most retention strategies rely on numerical indicators such as GPA, test results, or attendance rates. While useful, those measures reveal only a fraction of a much larger story. Behind every statistic are emotions, personal challenges, cultural adjustments, and mental health factors that deeply affect whether a student continues toward graduation. The project proposes a more holistic approach that blends conventional academic metrics with insights drawn from students' own words. Learners share their experiences through brief reflections and open-ended responses, offering direct glimpses into their academic and emotional worlds. Large Language Models (LLMs) and Machine Learning (ML) techniques are applied to interpret these narratives and identify subtle early signs of stress, isolation, or loss of motivation. The qualitative patterns are then connected with academic data to build a fuller understanding of each student's situation. The innovation lies in moving beyond surface numbers to acknowledge the human depth behind persistence and withdrawal. The research also considers broader social and environmental conditions that shape student retention. International students and underrepresented groups may face cultural barriers or discrimination that create feelings of exclusion. Others worry about safety on or near campus, or struggle to find a supportive community. First-year students often experience emotional strain as they adapt to new expectations, while upper-level students face heightened anxiety about demanding coursework and future careers. By listening directly to student voices and examining their reflections through LLM and ML analysis, the study reveals underlying causes of disengagement that standard quantitative models fail to capture. The broader goal is to build a technology-supported system that helps universities recognize early signs of risk and respond before students fall behind. When indicators of disconnection appear, the system can recommend timely support---whether through advising, tutoring, mentoring, or counseling. Merging the precision of data-driven insight with the compassion of human understanding, the project aims to shift retention work from reaction to prevention and to nurture a campus environment where every student feels valued, supported, and guided toward graduation.

Wearable biosensors have enabled continuous monitoring of physiological states of athletes, such as heart rate, heart rate variability (HRV), and SpO2 from smart watches. VO2 Master offers a portable way to gather respiratory and aerobic performance metrics including VO2, VCO2, ventilation and respiratory rate. The sensor data provides detailed insights into athlete's aerobic capacity, fatigue, and recovery. However, several gaps remain in interpreting these rich sensor streams for improving athlete performance and well-being. First, the high sampling rate is often applied for high-resolution monitoring in modern sensors, which generates large, complex datasets that require advanced statistical and visualization methods for effective analysis. Second, these quantitative signals alone lack the contextual information that human coaches collect from athletes' training logs, psychological assessment, and behavioral reports. These structural logs and narrative reports provide the missing context that sensor data alone cannot capture. Third, results from purely numerical analyses create accessibility barriers for general users, who receive no professional training, to translate metrics into actionable training and recovery suggestions. We think integrating biosensor data with text-based training logs through large language models (LLMs) offers a promising solution to tackle these challenges. Built upon the text comprehension and generation capabilities of LLMs, this project aims to prompt pre-trained healthcare-related LLMs with sensor stream data within natural language contexts. The goal is to create a chat-based intelligent assistant that can interpret biosensor and log data, respond to coach or athlete queries, and provide context-aware, data-driven suggestions to support human coaching in athlete training. To fully integrate and understand the rich pattern contained in sensor data, we proposed two strategies: first, leverage LLMs to autonomously generate code for visualizing high-frequency sensor data streams and summarizing salient physiological patterns from the resulting plots; Second, train a suite of machine learning models in advance to predict key wellness factors, such as stress, fatigue, sleep quality, anxiety and depression. The LLMs then interface with these models to obtain a predicted profile for new sensor inputs. By combining visual summaries, ML-derived health-factor predictions, contextual information from athlete logs, and Chain-of-Thought reasoning, we expect LLMs to generate personalized advice for training, recovery and overall athlete development.

Dengue is a vector borne illness that circulates among Aedes mosquitoes and humans. There are four serotypes of dengue that have been known to co-circulate. Use of the bacterium Wolbachia can mitigate dengue transmission by reducing the level of dengue virus in the mosquito and/or shortening the mosquitoes lifespan. Since Wolbachia is not naturally occurring in Aedes mosquitoes, it must be introduced. Temperature is a critical determinant of mosquito behavior and life cycle dynamics. This study focuses on the development of a mathematical model to quantify the effect of temperature on dengue transmission. The model is a compartment-based system consisting of first-order differential equations; temperature-based variability is introduced into several of the parameters. The analysis focuses on an outbreak of two, co-circulating dengue serotypes typical of a tropical monsoon climate. Temperature data and mosquito parameters are based on Chiang Mai, Thailand. We found that a significant reduction in human dengue cases can be achieved when Wolbachia-carrying mosquitoes persist in the population. Once introduced to the population, Wolbachia can persist for many years. When compared to other strategies for dengue mitigation, Wolbachia has a long-term impact. Temperature also influences the optimal timing of Wolbachia mosquito releases. Leveraging the temperature-dependent mosquito dynamics provided by the model, we can identify optimal Wolbachia release strategies to mitigate dengue transmission.

Finding an available parking spot is a challenge in many cities, often resulting in wasted time and user frustration. To address this issue, this research asks: “What models are most efficient for parking spot detection and parking availability prediction?” SmartPark aims to determine and implement the most efficient and accurate parking detection model. Current parking systems work to some extent, providing spaces and lanes to guide traffic. That being said, these systems fail to lower real time spent searching for an empty spot, which can lead to congestion and user frustration. With more and more people returning to in-person work and events post-COVID, these issues are only accentuated. This research focuses on implementing a trained Convolutional Neural Network (CNN) for spot recognition using the publicly available parking data set, PKLot, for a deep learning approach to parking detection. Additionally, using Random Forest Regressor (RFR) will contribute to prediction theory for short-term availability based on factors of weather, lighting, and shadows. Unsupervised clustering will also be applied to identify behavioral patterns in data, improving visual accuracy, and supporting RFR prediction. These techniques will be tested with variables of differing dataset sizes and feature selection to check overall accuracy of the system. Multiple classification scenarios will be studied to improve model generalization under such conditions, and results will be compared with existing machine learning approaches in current research to find the best solution. SmartPark’s goal is to reduce the time and frustration drivers experience when looking for parking using applied machine learning methods instead of relying on intensive infrastructure. This research applies supervised and unsupervised learning techniques, incorporating CNN-based classification, clustering analysis, and ensemble regression models. The combination of these methods will help determine patterns, prediction accuracy, and a scalable model for real-world use.

We develop and analyze a mathematical model to study the spread of West Nile Virus (WNV) within a closed environment consisting of mosquitoes, crows, and humans. WNV, a vector-borne pathogen, can lead to febrile illness and severe neurological conditions such as meningitis and encephalitis. Using a temperature-dependent system of first-order differential equations, we investigate the effectiveness of different control strategies. While traditional approaches focus on reducing adult mosquito populations with adulticides, larval control methods represent an alternative. In particular, we examine the novel introduction of \textit{Toxorhynchites} mosquitoes as a biological control mechanism within an SEIR framework, comparing its performance with that of chemical adulticides. Our results show that although adulticides yield rapid short-term reductions in mosquito populations, the long-term persistence of control is more effectively achieved through \textit{Toxorhynchites}. These findings highlight the potential of biocontrol-based strategies to complement or replace chemical interventions and provide a baseline for future mathematical modeling of WNV control.

Topological Data Analysis has emerged as a rich mathematical tool capable of describing the complex evolutionary relationships and interactions of rapid horizontal evolution and turnover involved in viral microevolution. TDA has been used to rapidly identify recombinant strains of influenza and estimate temporality of reticulate events, a resource critical to tracking and mitigating the dissemination of resistance genes in pathogenic microbes. However, TDA's capacity to distinguish between the topological signatures of the three primary modes of Horizontal Gene Transfer (conjugation, transduction, and transformation) in bacterial pathogens, a process critical to the rapid spread of Antibiotic-Resistant Genes (ARG's), remains to be fully potentialized. TDA can identify instances of reticulate events given that phylogenetic metric spaces of genetic distance in which HGT occurs possess topological properties which can describe horizontal evolutionary relationships and allow for the Persistent Homology to be computed. Through this pipeline, this study aims to model simplified interactions of conjugation, transduction, and transformation through parametrized simulations in RStudio dependent on the mode of HGT and meta-analyzed parameter data to identify changes in their polytope structures and resulting simplicial complexes. To accomplish this, three simulations are conducted for each mode of HGT with initial population size N=100 to N=1000 and a fixed initial MGE plasmid size (200bp), Background Mutation Rate (BMR), HGT recombination rate parameter (PHGT) over 100 generations. Simplicial complexes are constructed from the Principal Coordinate Analysis (PCoA) of the Hamming genetic distance matrix for each simulation at various time points t. The resulting topology is quantified using Persistent Homology, with focus on changes in Betti number βk (the number of k-dimensional holes) to capture complexity of reticulate events occurring during horizontal evolution. We anticipate that Persistent Homology analysis of the simulated evolutionary data will reveal a topological signature unique to each HGT mode with variation given input parameter values. Specifically, conjugation simulations are expected to produce complexes with higher counts in Betti numbers one (β1) and two (β2) than transduction and transformation across equivalent generations and time point t, indicating a stronger signal for cyclical reticulate events. If validated, these results will demonstrate the potential TDA provides as a novel computational framework capable of distinguishing mechanisms of HGT from genetic sequencing data alone. This distinction would prove critical in developing more accurate and efficacious predictive surveillance models to track the rapid spread of ARG's in pathogenic bacterial populations of concern both on local and global scales.

Untreated, pressurized, municipal irrigation water (UPMIW), also known as secondary water, is commonly used among residential areas across Northern Utah for irrigation purposes. As untreated water, irrigated directly from river water and snow runoff, secondary water may contain harmful pathogens that have the potential to cause disease in residents who water their properties with it. Following a confirmed outbreak of Shiga Toxin-Producing Escherichia coli O157:H7 in 2023 that was traced back to a UPMIW holding reservoir in Utah County, questions were raised about the pathogen prevalence in secondary water across other sections of the Wasatch Front. 15 UPMIW sites were sampled along Davis and Weber counties. Eleven samples were collected from holding reservoirs supplied by the Weber River, and four were collected from residential endpoints. The samples, treated with sodium thiosulfate, were centrifuged, and the sediments from the samples were tested for common intestinal pathogens. From the primary plating media, 61 isolates were grown. Each organism was identified by Matrix-Assisted Laser Desorption/Ionization Time of Flight (MALDI-TOF). Among the 61 isolates, 51 were found to be disease-causing pathogens in humans, with the remaining being common water-dwelling organisms that pose minimal risk to human health. After identifying the pathogenic species, Minimal Inhibitory Concentration (MIC) panels were used to assess antibiotic resistance among the organisms. Of the 15 organisms tested, 13 were confirmed to be resistant to antibiotics, to varying degrees. This study investigates the microbial species present in UPMIW, emphasizes the importance of understanding the risks associated with its use and ingestion, and aims to educate the community on the matter.

N/A

Brain-eating amoeba Naegleria fowleri: Feeding activity reduced by treatment drugs What drugs will kill the brain-eating amoeba? Only four survivors out of 154 cases of Naegleria fowleri have occurred in the US, and those that survive are likely to suffer from minor brain damage, immune reactions, or adverse side effects from the drug treatment. Each survivor was treated with amphotericin B, but many fatal cases also attempted this drug. Infections are rare, but what makes N. fowleri dangerous is its speed (time to death is around four days post-exposure) and thus how difficult it is to diagnose and treat. We have some basic information about potential drugs: The Centers for Disease Control (CDC) list amphotericin B, fluconazole, rifampin, azithromycin, nitroxoline, and miltefosine. We investigated the effectiveness of combinations of these drugs on cultured human cells infected with N. fowleri. We hypothesized that each of the selected drugs would have varying levels of effectiveness at reducing the amoeba's feeding levels. The investigational drugs were tested by first measuring toxicity on the amoeba to establish the appropriate dose of each drug. We then set up cultures of amoeba in 24-well plates and presented them with fluorescent plastic beads to eat, and treated them with the appropriate dose of each drug for 24-48 hours. Amoeba killed due to drug inhibition were unable to eat beads and remained negative for fluorescence when measured with a flow cytometer. We found that amphotericin B and azithromycin reduced the brain-eating amoeba's ability to feed by 40%, while the other four drugs were ineffective or caused only a modest reduction in amoeba activity. We will next investigate combinations of drugs and run variations of our infection model. These findings will inform clinical practice as physicians attempt to save the lives of those infected with this killer

The performance of modern electronics from solar cells to microchips is determined by the capacity to advance in the field of semiconductor devices. We focus specifically on organic semiconductors because they have the advantage of being processed onto a variety of surfaces such as plastic, glass and skin. This property makes them promising for the design of portable bioelectronic devices that can monitor the health of an individual. In this study, we investigate how photoinduced doping can be an effective way to modulate the charge carriers in conjugated polymers and optimize their electrical properties. The process of photoinduced doping involves a chemical procedure that uses light to activate the dopant source. We use Poly(3-hexylthiophene) (P3HT) as the conjugated polymer and introduce the photoacid generator ILP-113 that acts as the dopant source. Upon exposure of light, the photoacid generator releases a strong acid that acts as an oxidant creating mobile charge carriers. This facilitates electronic charge transport in conjugated polymers making it conductive. One of the advantages to this method is our ability to control the intensity of the light and illumination time to optimize the conductivity of the material. We do this through a code that an automatic robot uses to generate heatmaps which feature a standard xy coordinate system. We look at hotspots on the heatmap to determine the optimal light power and time exposure that create the highest conductivity levels. This allows for induced conductivity in specific areas demonstrating a powerful technique for creating conductive patterns for organic semiconductors. Our results demonstrate that photoinduced doping provides a controllable and cleaner alternative to traditional chemical doping methods. This approach opens opportunities to design light-responsive organic bioelectronic devices that are functional and efficient.

Thermoacoustic engines convert heat into sound and then into electricity, offering a potentially sustainable energy solution. This research investigates how variations in internal components—such as the stack geometry and heat exchanger efficiency—affect the engine's power output and operating frequency. We built a prototype standing-wave thermoacoustic engine and tested multiple stack materials, including ceramic honeycomb and stainless steel mesh. Our data indicate that stack placement relative to the pressure nodes is the most critical factor for maximizing performance. Furthermore, we observed a linear relationship between the temperature gradient and the acoustic amplitude. These findings provide practical guidelines for optimizing thermoacoustic systems for small-scale power generation.

As plastic production continues to rise, its environmental consequences have become a growing concern. Secondary microplastics (MPs), derived from the breakdown of larger plastics, constitute the majority of environmental plastic pollution. This research uses Raman spectroscopy to identify types of plastic in freshwater, snow, and cave environmental samples. Raman spectroscopy is an effective method to identify MPs due to its ability to detect low concentrations of molecules and distinguish them by their unique spectral fingerprints. However, the small size and fluorescent nature of dyed MPs introduce obstacles to accurate identification. To address these obstacles, we explore several complementary detection techniques including time-gated Raman spectroscopy, fluorescent imaging, and adding exogenous indicators. The potential of surface-enhanced Raman spectroscopy (SERS) to improve detection of microplastic is likewise investigated. By comparing these techniques, we assess their effectiveness for the aid in the detection of MPs. We also assess existing methods for microplastic detection by using a near-infrared, co-aligned Raman micro-spectroscopy system and explore confocal Raman microscopy to minimize the signal from background substrates. Raman spectroscopy is paired with existing machine learning algorithms to identify the types of plastic present in the sample. These methodological advances are applied to samples from various alpine locations. The resulting data will provide insight into MP pollution in alpine environments and support broader conservation efforts to preserve these ecosystems from the growing threat of plastic pollution.

Fungal interactions with their growth environment play a key role in understanding both ecological behavior and material breakdown processes. In this project, the goal is to research how variations in the viscoelastic properties of growth media affect fungal growth and morphology. Armillaria, also known as the honey mushroom, is a genus of basidiomycete fungi that commonly infects tree roots and is a major contributor to forest root rot. This fungus serves as the study system for this project because of its ecological importance in forestry and its ability to degrade complex organic matter. To study how different viscosities influence fungal development, Armillaria will be cultured on agar plates along with cellulose, which the fungus enzymatically degrades to access carbon. This process allows us to observe how cellulose breakdown and media stiffness affect fungal growth and morphology. Using microrheological techniques, we will measure local viscosity changes by tracking embedded microbeads. The particle movements of the beads will be analyzed by calculating their mean squared displacement (MSD) over time, which quantifies how freely particles move within the media and directly relates to their viscous and elastic moduli. These measurements will demonstrate how fungal growth alters the stiffness and flow characteristics of media. We hypothesize that changes in media viscosity will significantly affect Armillaria’s growth rate, structure, and enzymatic activity. Because Armillaria secretes enzymes to break down cellulose for carbon, these interactions may influence both fungal physiology and the mechanical properties of the media. Although experiments are still ongoing, this research aims to clarify how fungal behavior adapts to environmental stiffness and nutrient availability, deepening our understanding of how physical and chemical conditions influence growth. In the future, these findings may also help inform studies in forest health, decomposition dynamics, and biophysical modeling that connect fungal ecology with material science.

Accurate and efficient blood glucose detection remains one of the most critical challenges in diabetes management. Millions of individuals worldwide rely on glucose monitoring devices to regulate their insulin levels and prevent long-term complications. However, current devices often suffer from limited sensitivity, high production costs, and decreased enzyme stability over time. To overcome these limitations, this study reports the fabrication and characterization of a novel glucose biosensor based on glucose oxidase (GOx) immobilized on a graphene–chitosan composite supported by a carbon electrode (CE). The design integrates the biocompatibility of chitosan with the superior conductivity and large surface area of graphene to enhance enzyme loading, stability, and electron transfer efficiency. The chitosan matrix served as a natural polymer film that securely immobilized GOx, maintaining its biological activity and preventing denaturation during operation. Graphene, with its high electrical conductivity and two-dimensional structure, provided an ideal interface for rapid electron transfer between the enzyme's redox center and the electrode surface. The surface morphology and structural properties of the fabricated electrode were examined using Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). These analyses confirmed the homogeneous dispersion of graphene within the chitosan network and the stable attachment of the enzyme composite to the electrode surface, resulting in a uniform and porous structure favorable for mass transport. Electrochemical behavior will be evaluated by cyclic Voltammetry (CV), which is expected to show clear redox peaks and a linear response to glucose concentrations across the physiological range. Ongoing experiments aim to further evaluate the biosensor's reproducibility, stability, and sensitivity under varying glucose concentrations and environmental conditions. These continuing studies will help determine the long-term reliability and operational lifespan of the graphene–chitosan–based electrode system. Current findings point toward the strong potential of the GOx/graphene–chitosan/CE biosensor as a foundation for next-generation glucose monitoring technologies. Its combination of low cost, high performance, and potential for miniaturization could enable the creation of wearable or noninvasive glucose sensors, offering diabetic patients a more reliable, comfortable, and real-time method for managing their blood glucose levels.

Acne Vulgaris, commonly referred to as acne, is an inflammatory skin disease often linked to the anaerobic bacterium Cutibacterium acne (C. acnes), which thrives in sebaceous glands. Acne Vulgaris causes redness, swelling, pus formation and in many cases lasting physical scarring. Beyond its physical effects, acne often results in significant psychological distress, including reduced self-esteem and anxiety, particularly during its peak prevalence in puberty. This study investigates the efficacy of common over-the-counter acne cleansers by correlating their salicylic acid concentration with their ability to inhibit C. acnes. Salicylic acid is a widely used active ingredient known for it's antimicrobial and anti-inflammatory properties that help to exfoliate the skin, reduce sebum buildup, and clear clogged pores. Using Capillary Electrophoresis for precise quantification of the active ingredients, the determined concentrations were then compared against the results of Minimum Inhibitory Concentration testing. The Minimum Inhibitory Concentration assay involved serially diluting each cleanser and inoculating it with C. acnes to determine the lowest concentration needed to prevent visible bacterial growth. The combination of the Capillary Electrophoresis and the Minimum Inhibitory Concentration testing allows for both chemical and biological assessment of product effectiveness. This work is important to assess whether higher salicylic acid levels translate into greater practical effectiveness against acne-causing bacteria. Understanding this relationship is crucial for developing effective yet safe acne treatments. Ideally, effective products are using the lowest salicylic acid concentrations necessary to inhibit the growth of C. acne, balancing clinical efficacy with consumer safety, affordability, and environmental sustainability by reducing excess chemical use and minimizing potential skin irritation.

Since sound reflects off walls, sound can persist in a room before dying down. The reverberation time (RT) is a measure of how much echo there is in a room. More specifically, the RT is the time it takes for sound to be reduced by 60 dB. The optimal RT will depend on what the room is used for. For concerts, a higher RT is desirable, between 1.2 s and >2 s, depending on the type of concert. For classrooms, the preferred RT would be between 0.6 and 1 s. This project measured and calculated the RT in two specific spaces on UVU campus with the intent to recommend specific amounts of acoustic absorptive materials to bring the RT to a reasonable level for speech. One room is a parking lot entrance that connects that level to the elevators. It has glass doors, many windows, and lots of concrete, which results in a long RT time. The other is a connecting corridor between two building that also has a high RT time. By measuring room dimensions and surface areas of the specific materials of the walls used in the room, a calculation of the reverberation time was made. The RT was also measured by taking audio recordings and matching the slope of the decay, the RT. From this data, we determined how much material will need to be added to the rooms to have a lower RT. These results were presented as recommendations for modification to the spaces to the facilities managers.

Ground Penetrating Radar (GPR) has become increasingly accessible and utilized by a variety of communities to detect below-surface features such as utilities, geologic features, and graves. Previous studies have explored the effectiveness of using GPR to locate graves using a multitude of techniques and scenario variability, creating a framework for other studies involving the search and recovery of gravesites. This study used the NOGGIN GPR system with a 250 MHz sensor to perform grid surveys at locations in both Weber County and Sevier County, Utah, each with several sites, to search for a lost individual and a clandestine grave. The purpose of locating these individuals is to help provide a form of finality for family members by finding their loved ones who have been missing for a long period of time. Additionally, this study aims to answer why GPR is a suitable option for locating potential targets such as human remains. Lastly, it provides undergraduate students with experience in planning and executing a real-world GPR survey. Two undergraduate students have participated in the initial planning, surveying, and analysis of the GPR data, with mentoring by faculty/staff from the University of South Florida and Weber State University. They have also had the opportunity to work with Weber County Search & Rescue as well as an investigative reporter to better understand the significance of geoscience research to the public. Reflexw software was used to process and analyze the radargram profiles for diffraction patterns that represent promising targets. The Sevier County GPR surveys were conducted over four sites in primarily dry, sandy-silty soils. Analysis resulted in one promising shallow target (70-80 cm depth) that was later excavated. The target was confirmed to be a large tree root system. The Weber County GPR surveys were conducted over three sites, each with its own challenging set of conditions. Two of the sites were in the flowing Weber River, and the third was on a predominantly cobble point bar. The analysis of radargram profiles collected at Site 1 using the Sensors & Software pulseEKKO Pro with 200 MHz antennas mounted on a raft resulted in identifying one promising target (30-40 cm below river bottom). Analysis at Site 2, using the NOGGIN GPR instrument for data collection, provided two promising anomalies (40-70 cm depth) that require exploratory excavation, once permission is given by local authorities, to disturb the sites.

As renewable energy becomes increasingly important, developing effective hydrogen storage materials remains a central challenge in unlocking hydrogen's promise as a clean, versatile fuel. This computational research project examines properties of four cyclic aminoborane complexes including potential energy landscapes, molecular dynamics simulations, and probability density distributions to uncover their potential for effective hydrogen storage. Density functional theory was utilized for most of the calculations including optimizations, frequencies, transition states, and reaction path calculations. Dissociation of the H2 unit from each cyclic aminoborane complex results in near thermo-neutrality (+/- 6 kcal/mol) with transition states of approximately 40 kcal/mol, a relatively low energetic barrier for bond dissociation. Additionally, the boron atom plays a key role in fostering this dissociation process. The molecular dynamics simulations revealed substantial differences in the energy landscapes and molecular geometries, even among molecules that are constitutional isomers. Specifically, the breadth and overall profiles of the B-H and N-H bond probability density distributions differ for each molecule, including their non-Gaussian distribution shapes. Time dependent analysis will also be included and will showcase how various geometries favor unique conformations within their dynamics trajectories.

Atmospheric Water Harvesting (AWH) has emerged as a promising solution to address growing water scarcity by extracting atmospheric water. Even in dry climates, there is a significant amount of water in the air. However, extraction and liquification of that water can be energy intensive and inefficient. This project explores a comprehensive approach to enhance AWH efficiency by utilizing electrowetting on dielectric (EWOD) and the use of amphiphilic materials for switchable surface wettability. EWOD leverages electric fields to change the wettability of hydrophobic surfaces, allowing manipulation of water droplets and enabling efficient water collection and transport. A key component of EWOD is the creation of dielectric surfaces through processes such as anodization. In the second part of the approach, this anodization is utilized to attach amphiphilic materials to dynamically control surface wettability. Once attached, the materials' hydrophilicity/hydrophobicity character is controlled with an applied voltage, potentially offering switchable control over the water interaction and droplet behavior. This comprehensive approach of using EWOD principles with modified surfaces aims to optimize AWH systems for both small-and large-scale applications. The project provides insights into the potential of dynamic surface wettability operational principles, current research trends, and future potential of these technologies, contributing to the development of sustainable water harvesting solutions. By advancing the integration of EWOD and surface modification, this project seeks to enhance efficiency and adaptability of AWH systems.

A temperature-dependent electrochemical investigation was conducted on a non-aqueous redox flow battery (NRFB) system employing ferrocene-trimethylammonium (FcNMe₃â_x0081_º/FcNMe₃²â_x0081_º) as the catholyte and methyl viologen (MV²â_x0081_º/MVâ_x0081_ºâ€¢) as the anolyte in propylene carbonate (PC) solvent. Cyclic voltammetry (CV) was performed at various temperatures to determine the influence of temperature on redox kinetics and mass transport properties. The diffusion coefficients (D) of both redox couples were calculated using the Randles–ŠevÄ_x008d_ík equation, showing a consistent increase with temperature due to enhanced molecular mobility in the solvent. The heterogeneous electron transfer rate constants (kâ_x0081_°) were derived using Nicholson’s method, exhibiting Arrhenius-type behavior. Activation energies for both diffusion and charge-transfer processes were evaluated, revealing distinct kinetic asymmetry between the FcNMe₃â_x0081_º/FcNMe₃²â_x0081_º and MV²â_x0081_º/MVâ_x0081_ºâ€¢ redox pairs. These results provide quantitative insight into the thermally activated transport and electron transfer mechanisms in PC-based NRFB electrolytes, offering valuable guidance for optimizing temperature control and electrolyte composition to improve system performance and efficiency.

Abstract: College and university students experience high amounts of distress relative to the general population. The COVID-19 pandemic compounded existing stress as uncertainty regarding school closings, food scarcity, and concerns about individual and societal health increased. Implementing inexpensive and accessible stress relief interventions is critical to universities' approach to fostering improved mental and academic outcomes. The current study sought to investigate whether student stress and facility use changed before and after COVID and compares efficacy of three stress-reduction interventions: chi machine, massage chair, and rejuvenation lounger. We analyzed existing data from the campus Stress Relief Center at Weber State University. Four measures of stress were taken before and after the intervention: blood pressure (BP), heart rate (HR), perceived stress (PS) and perceived pain (PP). The difference in Stress Relief Center visits between pre- and post-COVID timeframes was statistically significant with more visits before COVID than after. Of the stress measures, only systolic BP differed before and after COVID. When comparing interventions, the chi machine and massage chair were different on HR and diastolic BP, and the massage chair and rejuvenation lounger on HR. There were no statistically significant differences for any of the interventions for PP, PS or systolic BP measures.

Urban planning traditionally uses ‘top-down’ frameworks to guide the future of a city. In top-down frameworks, planners designate focus areas and develop proposals for decision-makers. However, by positioning planners as the ‘experts’ responsible for complex urban systems, top-down frameworks expose planning efforts to potential unintended consequences and unattended community voices. Additionally, it tempts the simplicity of one-size-fits-all planning solutions to vastly complex urban problems, which negate the unique identities and contexts of individual cities. Salt Lake City, Utah, is facing its own complex challenges, including fast-paced growth, a worsening housing crisis, and a shrinking Great Salt Lake. To better plan for the city and its multifaceted challenges, this project proposed the development of a new planning framework tailored to Salt Lake City. Design inputs for the framework were sourced from a combination of observational ethnography in 8 public locations and semi-structured interviews with 11 local stakeholders in the fields of planning, government, urban design, the arts, business, ecology, and public health. The transcribed interviews and ethnographic notes were manually coded for design inputs, with analytic methodology identifying actors of the framework and relationships between the different actors. The resulting planning framework is composed of three overlapping elements: Visibility, Structure, and Happenings. Visibility refers to the actors and relationships we choose to make visible or invisible in the urban fabric. It contains themes of identity, history, perception, transparency, and physical resources. Structure refers to the structures we can touch and the intangible structures we operate within. It contains themes of place, scale, flexibility, accessibility, collaboration, and bureaucracy. Finally, Happenings questions the prescriptive role of planners and policymakers as choreographers of the city and instead suggests a relational shift towards responsive facilitation of existing community improvisation. It contains themes of interaction, engagement, activation, and actionable policy. This framework aims to replace static top-down practices and instead ‘live’ in its implementation just as cities do: interdisciplinary and flexible, it highlights active feedback loops naturally occurring within the urban landscape and emphasizes the interactions between various urban elements as much as the elements themselves. An iterative design process to finalize the visual presentation of the framework will conclude in December 2025 (see Figure 1). A future study to be conducted in the spring of 2026 aims to build upon these findings by publicly testing and evaluating the effectiveness and scalability of the framework through small-scale public urban design installations and community surveys.

Introduction: About 67% of adults ages 18-34 report experiencing intense financial stress (APA, 2023). Women tend to report greater financial stress than men, even when in the same financially stressful situations (Chen et al., 2021; Dunn & Mirzaie, 2023; Koomsom et al., 2022; Snorradóttira et al., 2014). Financial stress has been linked to eating distress, though there is little research that has explored how childhood financial situations affect eating distress in adulthood (Burke et al., 2023; Mikhail et al., 2023, Tavolacci et al., 2021). This study aims to explore the relationships between current and childhood financial stress and eating distress in college students seeking psychological services, as well as the effect of sex on these relationships. Method: This study uses archival data from a large college counseling center between 2014 and 2024. Measures used include a demographic intake questionnaire and the CCAPS-62 (Counselling Center Assessment of Psychological Symptoms-62) (CCAPS-62; Locke et al., 2011). Participants include those who responded to questions regarding financial stress on the demographic questionnaire and the eating distress subscale of the CCAPS-62, resulting in a total of 22911 participants. SPSS Version 31 will be used to run linear regressions examining the relationships between eating distress and current and childhood financial stress, respectively. A multiple regression will then be run to determine whether sex has a moderating effect on these relationships. Results: Current financial stress predicts eating distress to a greater degree than past financial stress, though the effect size is small for both. Gender has a negligible effect on these relationships. Discussion: In cases of eating distress, clinicians should pay more attention to current financial stress than financial stress experienced in childhood. Inability to afford food due to financial stress may lead to eating distress, which may impact health, work, or other factors that may exacerbate financial stress, creating a vicious cycle.

Heart rate variability (HRV) reflects the body’s ability to regulate emotions and adapt to stress, with higher HRV linked to greater resilience. Personality traits, including neuroticism, influence how individuals respond to stress and select coping strategies. This study examines whether neuroticism moderates the relationship between coping strategies and HRV, predicting that higher neuroticism will be associated with lower HRV through maladaptive coping, whereas lower neuroticism will be associated with higher HRV through adaptive coping. A total of 120 undergraduate students at Brigham Young University participated for research credit. Participants completed online self-report measures of personality and coping via Qualtrics, using the IPIP-NEO scale to measure neuroticism and the Brief COPE to measure adaptive and maladaptive coping strategies. Physiological data, including blood pressure, heart rate, and HRV, were collected during a 15-minute resting period using ECG and blood pressure monitoring equipment in a controlled lab setting. Correlational analyses revealed that neuroticism showed a significant, weak negative correlation with adaptive coping strategies, consistent with our initial hypothesis. A significant, moderate positive correlation was found between neuroticism and maladaptive coping, indicating that individuals higher in neuroticism reported greater use of maladaptive coping strategies. Additionally, the interaction of neuroticism and coping strategies was not significantly correlated with HRV, suggesting that the relationship between personality and physiological stress regulation may be more complex than expected. These findings suggest that neurotic individuals may use more maladaptive, avoidant strategies, rather than adaptive, engagement-focused coping, confirming previous research. Future studies should examine personality's influence on stress physiology and whether adaptive coping strategies can buffer physiological stress reactivity in neurotic individuals.

This study examined the relationship between music, memory, and perception. The design of the study was a 2x3 mixed factorial design. Participants (N = 86) were randomly assigned to one of two between-subjects music groups: researcher-selected and participant-selected. Each participant was tasked with studying, and subsequently recalling, word lists under one of three levels of within-subjects music type (Lyrical, Non-Lyrical, and No Music). The order of music type and word list was counterbalanced across participants. The dependent variables included accurately recalled words and perceived task difficulty, enjoyability, and success, rated on 7-point Likert Scales. A series of repeated measures ANOVAs were conducted for each dependent variable using Tukey post-hoc comparisons. There were no significant between-subjects effects (all ps > 0.05). Overall, there were significant differences between music type and recall scores (F(2, 168) = 10.94, p < .001, η2p = 0.115), reported task difficulty (F(2, 168) = 14.74, p < .001, η2p = 0.149), enjoyability (F(2, 168) = 7.45, p < .001, η2p = 0.081), and success (F(2, 168) = 9.359, p < .001, η2p = 0.100). These results show better performance for Non-Lyrical or No Music. Tukey post-hoc comparisons revealed that recall scores were significantly lower while listening to Lyrical (M = 10.4, SD = 3.51) compared with Non-Lyrical (M = 11.2, SD = 3.39; p = 0.032) or No Music (M = 12.0, SD = 3.39; p < .001). Participants reported the task as more enjoyable while listening to music (Lyrical M = 4.21, SD = 1.39; Non-Lyrical M = 4.09, SD = 1.48) compared with No Music (M = 3.36, SD = 1.50). This trend was the opposite for perceived task difficulty; participants felt the task was more difficult while listening to music compared with No Music. This study provides valuable insight into the influence of music on academic settings.

Adverse childhood events (ACEs) are negative incidents that caused trauma or harm to individuals during their childhood. This could be through physical, mental, emotional abuse or neglect. When these children grow up, they may find themselves in a university to continue their education. Universities have many resources available to students to help them succeed in earning their degree. These resources range from tutoring to financial assistance, group therapy etc. Studies indicate that healthy social interactions on campus leads to greater success for students' education. Yet research has also found that those who have experienced ACEs are less likely to trust those around them and to reach out for help. Through an analysis of previously collected data, we hope to understand the relationship between how students who have experienced ACEs in their past employed university resources and the success of finding a balanced school and social life. Following IRB approval, data was collected by emailing invites to UVU students and alumni to participate in a survey that included items related to ACEs, the use of university resources, and social support networks. Of the approximately 10,000 individuals that received invitations, approximately 400 completed the questionnaires. Data will be analyzed with descriptive statistics, t-tests, and ANOVAs to compare differences between those who experienced ACEs and those who did not. I anticipate that the findings will show that those that have utilized campus resources will have greater success balancing social and educational lives leading to lower dropout rates. However, I also conceive that campus resources will be underutilized by ACEs students. With the projected conclusion, universities may better understand the benefits campus resources have on ACEs students while also demonstrating the importance of creating programs that are welcoming and provide safe environments for ACEs students. Universities can use the findings to spread awareness to students who may have ACEs in their childhood, that campus resources can greatly help them during their time in higher education. In providing the support ACEs students may need, universities can keep them in school by assisting them in finding support in their classmates and in turn, finding success in their classes. The whole student body may benefit from campus resources, but with the projected findings, they may especially help ACE students in their education.

Intro: Those with Adverse Childhood Experiences (ACEs) have an increased risk of poor physical health, poor mental health, developmental disabilities, and poor academic outcomes (Baldwin, 2023; Daníelsdóttir, 2024; Craig, 2022; & Webster, 2022). ACEs are broadly defined by household challenges, abuse, or neglect that happen during childhood. Furthermore, 6 out of 10 adults have reported experiencing at least one ACE, and 1 in 6 adults report experiencing at least 4 ACEs (Madigan, 2023).

Our research focuses on how feelings of belongingness may interact with these outcomes related to ACEs. We first hypothesized that the presence of ACEs may be linked to a lower sense of belonging in college students. Furthermore, we predicted that feelings of belonging may moderate the relationship between ACEs and students' negative mental health outcomes. Higher feelings of belongingness may act as a buffer against the negative outcomes related to ACEs.

Methods: Quantitative data for this project were collected as part of a larger study on suicidality at a university in Utah. We pulled from 3 scales to assess variables, namely, the BRFSS Adverse Childhood Experiences Module (Felitti et al., 1998), 1 item about students' belongingness on campus, and the Depression, Anxiety, and Stress Scale (Lovibond, 1995). We then used SPSS to run a series of correlations followed by mediations using the PROCESS macro (Hayes, 2018) to draw comparisons between ACEs, belonging, and mental health variables.

Results: Ultimately, there was a significant negative correlation between ACEs scores and belongingness among our population, r(701) = -.15. Belongingness partially mediated the relationship between ACEs and scores on three mental health measures: depression (indirect effect = 0.21, 95% CI: [0.11, 0.33]), anxiety (indirect effect = 0.08, 95% CI: [0.03, 0.15]), and stress (indirect effect = 0.11, 95% CI: [0.05, 0.19]). Specifically, belongingness helped buffer the deleterious effects of ACEs on mental health outcomes such that more belongingness was related to lower depression, anxiety, and stress scores.

Discussion/Conclusion: Our findings ultimately support our hypothesis that low belongingness would be associated with the presence of an ACE for students on campus. They also support our hypothesis that belongingness would mediate the relationship between ACEs and mental health among students (i.e., anxiety, depression, and stress). This suggests that college students would benefit from more interventions to improve feelings of belongingness, particularly students with the presence of an ACE.

One of the most impactful things upon the human psyche is its environment. Environmental Psychology is defined as some variation of the study of the interaction between individuals and their built and natural environments (Steg et al., 2013). In this body of research, restorativeness is of utmost importance (Menardo et al., 2019). One of the foundational principles in Environmental Psychology is biophilia which can be roughly translated to the human requirement to value nature. Incorporating biophilia into architecture can require anything from the use of natural materials and shapes, to colors and nature itself. The incorporation of natural elements can reduce cortisol as well as enhancing connectedness and wellbeing by creating restorative environments (Inam, 2024). The purpose of this study is to analyze the restorativeness difference of places built in harmony with nature, such as a greenspace surrounded by older buildings constructed with natural materials, and places built in conflict with nature, such as places constructed around nature but built out of grey concrete with lots of negative space. The prediction is that walking within an environment built in harmony with nature will have significantly more restorativeness than walking in an environment built in conflict with nature. The scale level of restorativeness will be measured through physiological measures as well as an emotional evaluation coupling with an anxiety evaluation. These physiological measures will be collected through the use of a portable EKG ring that will be recording data throughout the entirety of the experiment. Participants will be given a digit span cognitive test where upon an incorrect answer a buzzer will sound informing the participant they are wrong, the caveat to this is that the buzzer will sound twice at assigned times regardless of if the participant is correct. This is designed to increase their stress levels in both groups. I predict that there will be greater restorativeness in the group exposed to places built in harmony with nature than the group exposed to places built in conflict with nature. This bridges several gaps within the current literature, by observing environments constructed around natural elements but with different construction materials and intentions as well as testing the restorativeness of nature and walking in the real world. This allows us even further insight into the role that movement and natural environments play within human health, which could allow the grounds to call for reform in the design of highly utilized spaces which has relevance for urban planning.

When individuals are exposed to stress, the sympathetic nervous system activates the stress response, leading to increased respiration and heart rate, fluctuating body temperature, and sweating. Stress is associated with poor health outcomes and mental illness. College students face many potential sources of stress, including financial, social, and academic pressures. Music interventions have been shown to mitigate the stress response and improve mental well-being, but research on the influence of specific music qualities is sparse. We performed a between-subject repeated measures experiment in which heart rate, electrodermal skin response, and body temperature were recorded while undergraduates performed a potentially stressful calculation task. The participants completed the task first without music and then two additional times with music, either with two fast-paced or two slow-paced music segments. The researchers also recorded the number of calculation errors during the three task segments. Following the completion of the calculation task segments, participants were asked to complete a brief survey on their music preferences. The survey asked them to rate the music they encountered, their listening habits when completing homework, and their music preference. Based on previously collected data from our lab, we predict that the math-induced stress response gets smaller with practice. We further predict that this reduction in the stress response is more pronounced when the music preference matches the background music, while we predict that this reduction in the stress response will be smaller when the music preference does not match the background music. We further predict that the error rate will be smaller when the music preference is a match, and larger when it is a mismatch.

Central Research Question and Purpose: This study investigated which nutritional and health factors, among several analyzed, most strongly predict depression and which were preventative. Classical models of depression focus on the monoamine theory, which postulates that depression is a consequence of imbalanced monoamines such as serotonin and dopamine. Depression, however, has since been found to be multifactorial, with lifestyle, nutrition, sleep, and physical activity all implicated. The purpose of this study was to examine which modifiable behaviors are most predictive of higher or lower depression scores, with the aim of informing which practical modifications to lifestyle might have utility in prevention and intervention.

Methodology: Following IRB approval, an online questionnaire was posted on social media and on a research participant pool web site hosted by Psychology professors at UVU. 910 participants completed questionnaires online. Depression was measured using the Patient Health Questionnaire-8, excluding the suicidal ideation question from the original PHQ-9. In addition, participants self-reported frequency of specific health-related behaviors, including daily water consumption, drinking of soda and alcohol, fast-food intake, physical activity, use of relaxation or meditation techniques, and sleep quality and quantity.

Results and Conclusions: A multiple linear regression was used to examine the associations between nutritional and physical activity behaviors and depression scores while controlling for age, gender, education, and income. The overall model was significant (p <.001) and explained approximately 13% of PhQ-8 scores (R² =.13). Physical activity, drinking alcohol, drinking water, and using tobacco did not significantly associate with depression scores. However, consuming fast food (β=.18, p < .001), drinking soda (β=.13, p = .003) were positively associated with depression. Drinking water (β=.10, p=.01) was negatively associated with depression. From the demographics, only age (β=.19, p=.01) was negatively associated with depression.

Significance: Results highlight the significant influence that daily behaviors have on mental health, underscoring the importance of lifestyle in both preventative measures and interventions. Focusing on a nutrient-dense diet, quality sleep, and consistent exercise may serve as a cost-effective method of improving mental health. These strategies can help to support mental health across diverse populations. Future research should focus on causal mechanisms, including inflammation, stress regulation, the gut-brain axis, and neuroplasticity, to further clarify the connections these findings represent.

Central Research Question and Purpose: This study investigated which nutritional and health factors, among several analyzed, most strongly predict depression and which were preventative. Classical models of depression focus on the monoamine theory, which postulates that depression is a consequence of imbalanced monoamines such as serotonin and dopamine. Depression, however, has since been found to be multifactorial, with lifestyle, nutrition, sleep, and physical activity all implicated. The purpose of this study was to examine which modifiable behaviors are most predictive of higher or lower depression scores, with the aim of informing which practical modifications to lifestyle might have utility in prevention and intervention.

Methodology: Following IRB approval, an online questionnaire was posted on social media and on a research participant pool web site hosted by Psychology professors at UVU. 910 participants completed questionnaires online. Depression was measured using the Patient Health Questionnaire-8, excluding the suicidal ideation question from the original PHQ-9. In addition, participants self-reported frequency of specific health-related behaviors, including daily water consumption, drinking of soda and alcohol, fast-food intake, physical activity, use of relaxation or meditation techniques, and sleep quality and quantity.

Results and Conclusions: A multiple linear regression was used to examine the associations between nutritional and physical activity behaviors and depression scores while controlling for age, gender, education, and income. The overall model was significant (p <.001) and explained approximately 13% of PhQ-8 scores (R² =.13). Physical activity, drinking alcohol, drinking water, and using tobacco did not significantly associate with depression scores. However, consuming fast food (β=.18, p < .001), drinking soda (β=.13, p = .003) were positively associated with depression. Drinking water (β=.10, p=.01) was negatively associated with depression. From the demographics, only age (β=.19, p=.01) was negatively associated with depression.

Significance: Results highlight the significant influence that daily behaviors have on mental health, underscoring the importance of lifestyle in both preventative measures and interventions. Focusing on a nutrient-dense diet, quality sleep, and consistent exercise may serve as a cost-effective method of improving mental health. These strategies can help to support mental health across diverse populations. Future research should focus on causal mechanisms, including inflammation, stress regulation, the gut-brain axis, and neuroplasticity, to further clarify the connections these findings represent.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that can affect attention, hyperactivity, and impulsiveness, with symptoms varying from person to person. Research has shown that there are differences in how ADHD symptoms can be experienced between males and females, with higher levels of inattention symptoms in females and symptoms of impulsivity in males (Gershon). More research in this area can help build a greater understanding of how ADHD affects college-aged students, male and female, and find ways to provide resources pertaining to awareness and how students can effectively gain their education, despite the ADHD symptoms they may experience. The present study will examine how ADHD symptoms differ by gender among UVU students. Data were collected through an IRB-approved study, utilizing a questionnaire assessing participants' ADHD symptoms, age, gender, and health behaviors. Emails were sent to approximately 10,000 individuals in a database of UVU students and alumni, inviting them to participate, and 250 individuals participated and provided data for this study. Data will be analyzed with descriptive statistics and t-tests to assess ADHD symptoms by gender, as well as educational attainment. We expect to find results relating to female symptom levels of inattention being higher than those of males, and males' symptom levels of impulsivity being higher than those of females. Our findings may contribute to a better understanding and awareness of how ADHD symptoms can differ by gender and how we can implement effective interventions or strategies for students. References: Gershon, J. (2002). A meta-analytic review of gender differences in ADHD. Journal of Attention Disorders, 5(3), 143–154. https://doi-org.uvu.idm.oclc.org/10.1177/108705470200500302

Many students have responsibilities outside of school such as work, volunteering, sports, and even caring for a family. Thus, finding study strategies that reliably improve memory retention and efficiency is paramount. There is a large body of research showing that taking practice tests during learning improves memory retention more than just re-reading material (Rawson et al., 2013; Rowland, 2014). The primary research question in this experiment is: Do multiple choice practice questions produce similar memory retention to cued recall practice questions at a lower time cost, and whether both outperform rereading? If multiple choice practice questions produce similar memory retention success while requiring less time, it would be a more efficient and adoptable study strategy for students. Undergraduate participants will learn 24 Italian/English word pairs, split evenly across three within-subject conditions: cued recall practice questions (type the English word translation when given the Italian cue), multiple choice practice questions (select the correct English word from three separate options), and rereading (viewing the Italian and English word together). Each study group will measure the time cost associated with each strategy. Participants will then complete two different memory tests (one cued recall and one multiple choice). Primary outcomes include accuracy and efficiency of each study method. We predict that completing cued-recall practice questions will lead to the highest performance on the memory tests, followed by multiple choice practice questions during learning, and finally rereading during learning leading to the lowest performance. When considering time cost, multiple choice may potentially be most efficient overall. We have received IRB approval for the study and have begun collecting data. We expect to finish our data collection by mid-January. References: Rawson, K. A., Dunlosky, J., & Sciartelli, S. L. (2013). The power of successive relearning: Improving performance on course exams and longâ€_x0090_term retention. Educational Psychology Review, 25(4), 523–548. https://doi.org/10.1007/s10648-013-9240-4 Rowland, C. A. (2014). The effect of testing versus restudy on retention: A meta-analytic review of the testing effect. Psychological Bulletin, 140(6), 1432–1463. https://doi.org/10.1037/a0037559

This literature review examines how mindfulness-based interventions, media literacy, and intuitive eating relate to the prevention and intervention of disordered eating and body image disturbances and describes the methods in which these interventions are provided. Western culture teaches individuals to pursue the "thin ideal" and to follow dieting trends; however, research shows that this leads to disordered eating and body image concerns. The purpose of this research was to compile intervention and prevention strategies to minimize the onset of eating disorders. A systematic literature search focusing on meta-analyses was conducted using two databases, yielding 36 sources. A large range of support for mindfulness-based interventions were identified, with stronger support for mindfulness-based eating awareness training (MB-EAT). Mindfulness is the ability to focus on the present moment with an open mind and an attitude of acceptance (Bishop et al., 2004). The skills to improve mindfulness can be taught using many different techniques, including group-led sessions and self-administered sessions via guided meditation or via video and audio. Media literacy refers to the ability to critically navigate online media. After extensive research, the SoMe program and MediaSmart program were found to be effective media literacy interventions that mitigate the presence of body image concerns. Most studies suggest that media literacy interventions should be used as a secondary intervention in conjunction with other programs rather than a standalone intervention. Intuitive eating involves four main subtopics including (1) unconditional permission to eat, (2) reliance on hunger and satiety cues, (3) eating for physical rather than emotional reasons, and (4) body-food choice congruence or gentle nutrition. Several intuitive eating intervention programs were identified, including Your Body is Your Home, a school-based classroom intervention; Eat for Life, a 10-week group intervention; the Acceptance Model of Intuitive Eating; the Theory of Embodiment; and the Intuitive Eating Workbook. Many of these programs encourage improved eating habits as well as improved body image. Overall, findings suggest that all three interventions listed are effective in decreasing body image concerns and disordered eating in individuals. Still, further study is needed to see if these interventions could be effective in treating clinical eating disorders. At the present time, the majority of the research identified, focused on women in the United States, notably of a large range of ages and demographics; however, more research should be conducted to test the effectiveness of these interventions among different races, nationalities, and genders.

Saline lakes are desiccating worldwide at alarming rates. These changing environmental conditions pose existential risks to ecosystems, local populations, economies, and the broader social world. Sociology offers critical frameworks and methods that serve essential processes in understanding and improving water levels in salt lakes. This project seeks to understand social drivers of desiccation. By isolating what processes are contributing to the declining water levels in these lakes, the threat can be further understood. The resulting data is key to advising policy action, consumer behavior, and overall risk mitigation. The project is composed of 2 essential elements: a literature review and data analysis. The literature review was composed. First is a rigorous literature review, composed of over 80 academic peer-reviewed articles. The identified scholarship illustrated central findings and gaps in the research. This process guided the second tenet of the project, data analysis. Through a Qualtrics survey (n=820), participants articulated their perception and understanding of The Great Salt Lake. Descriptive statistics and other qualitative methods offered exciting and interesting results. Key findings from the literature review and data analysis highlighted the role of several social factors in the context of drying saline lakes. First, agriculture was described as an especially influential consideration. In specific areas like Utah, alfalfa has been associated with high water demands. Population growth was also associated with declining water levels and greater water demands. Agriculture and growth were also associated with poor management and government practices. Social factors were deemed to be interconnected and related to the decline of water in salt lakes around the world. The implications of this project are valuable. Policy work is a powerful avenue for change, funding, and enforcement. The data and literature obtained in this project can be used to assist lawmakers and illustrate the growing environmental concerns. This research can also be used to inform the public. The Great Salt Lake, for example, is rapidly declining and is close to a large population. Education is central to resolving this crisis and effectively informing communities at immediate risk. Society is highly influential in the ecological crisis. This relationship can create severe harm and damage; however, social processes can also protect and preserve the environment. This sociological research describes the presence of harm, but also the capacity for change.

The Quiet Ego is a relatively new construct in positive psychology characterized by "an equanimity of mind that acknowledges the good and the bad in one's observations, compassion in one's view of others (interpersonally and collectively), curiosity to learn alternative points of view, and a long-term perspective on the self and others with a mind to facilitate their development"(Bauer & Weatherbie, 2023). By contrast, a noisier ego is self-centered, defensive, and validation-seeking. Quiet ego is positively associated with various measures of human flourishing (Bauer & Weatherbie, 2023) and balanced thinking about self and others in ways that foster healthy self and social functioning (Wayment et al., 2015). Experimental research showed that a quiet ego training intervention significantly improved emotional intelligence compared to control (Liu et al., 2022). Despite empirical evidence for the adaptive value of a quiet ego, there is almost no research on its development. Future research is needed to determine the relationship between parenting, quiet ego, and wellbeing in adolescence and early adulthood.

The increasing global prevalence of dementia and Alzheimer's disease and related dementia (ADRD) has become a significant matter, and it affects the quality of life of ADRD patients and their caregivers. Also, the public health burden of ADRD is expected to exceed $3 trillion by 2060. Given the current global increase in dementia, maintaining and improving cognitive health in older adults is now an urgent priority. Recently, research has increasingly explored the use of Virtual Reality (VR) as an intervention tool for cognitive training in older adults, and they have shown promising results, with several studies reporting improvement in executive function, attention, and global cognition. However, further research is required to determine the effectiveness of 3-D block puzzle-based visuospatial VR interventions in improving cognitive performance in older adults. 3-D block puzzle games require participants to use spatial transformation (e.g., object assembly), which is related to visuospatial functioning. Visuospatial cognition is important because they are closely associated with functional independence, mobility, and general cognitive abilities. Also, it is crucial to maintain cognitive functioning in healthy older adults, as early intervention can help prevent cognitive decline and further enhance cognitive independence and quality of life. Therefore, the purpose of this study is to examine whether the VR-based puzzle interventions can help maintain general cognitive functioning and visuospatial performance of community-dwelling healthy older adults aged 65 and above. The study has been conducted in four local senior facilities, and participants attended 12 VR sessions, each lasting 30-40 minutes. The Montreal Cognitive Assessment (MoCA) and Vandenberg Mental Rotation Test (VMRT) were conducted as pre- and post-assessments. Among the 27 community-dwelling older adults, participants with MoCA scores of 26 or above, indicating no cognitive impairment, were included (n = 15). Using the pre- and post-assessment results, a paired t-test was performed in SPSS for data analysis. The results showed that there was a significant difference in the overall score of MoCA (p = .045), and VMRT scores showed no significant difference (p = .064), but there was an improvement in average performance. Currently, more participants are being recruited, so it is expected that data analysis will be conducted again with a larger sample size. (Approx. 20 total)

Pre-health and pre-nursing university students' perceptions of health, fitness, normalcy, and typicalness inform how they will diagnose and treat their patients. These perceptions are shaped by healthcare curricula in ways that are both overt and implicit. Equitable care requires recognition of all body types as equally valid, Our survey gathers information on 1) student demographics and 2) student attitudes and perceptions about the body (via the image association test or IAT). The survey is administered to UVU students both entering their pre-requisite human anatomy course and soon after entering the nursing program. The IAT asks students to rate AI-generated body silhouettes based on their perceptions of health, fitness, normalcy and typicalness. Lower BMI silhouettes were rated more favorably across all terms: healthy, fit, normal, and typical. Extremely low BMIs were also rated with a negative term. Higher BMI silhouettes were generally perceived as less healthy. The analysis indicates that perceptions were spread across a spectrum of healthy or typical; suggesting societal norms that seem to favor moderation rather than extremes. There was a strong correlation between healthy or typical and normalcy or typicalness, highlighting cultural links between appearance and wellness. Understanding the differences in how pre-health students are entering the medical field can help us address biases in providing care. These potential weight and size biases highlight a concern for future healthcare providers because biased attitudes can influence clinical judgment, communication with patients, and treatment decisions. Providers may unknowingly dismiss individual symptoms or associate a distinct BMI with a specific level of health or fitness. Such biases may contribute to inequitable care and diagnostic errors. Addressing these biases early in pre-health education may promote patient-centered and evidence-based practice. Our aim is to suggest the need for education to remove biases and stigmas to promote more inclusive care.

With the recent publication and public data release of half of the all-sky data from the X-ray satellite eROSITA in late January 2024, it is an exciting time to consider X-ray source populations in the Milky Way galaxy, and to compare eROSITA data with X-ray source catalogs from previous missions. The eROSITA data release is, to date, the most detailed and sensitive all-sky X-ray survey ever completed, providing stunning views of the sky in X-rays and nearly one million distinct X-ray sources. While eROSITA was launched in 2019 and only the first of several data releases has been published, there are three public data releases from the Gaia optical all-sky survey (which launched in late 2013) that provide astrometric data including parallax distance estimates for over one billion stars in the Milky Way. Since X-ray binary systems consist of one living star alongside a compact object such as a white dwarf, neutron star, or black hole, it is often possible to match the X-ray source position to known, visible living stars. This research consists of matching Gaia counterparts to hard band (2.3-5.0 keV) eROSITA X-ray sources to determine the distances to these X-ray sources. In doing so, we produced a three-dimensional map of the Milky Way Galaxy’s bright X-ray source population, by focusing on just the 100 brightest sources in the eROSITA hard band catalog. This initial map is useful in examining the bright X-ray source population throughout the galaxy, which is the focus of this project. By extending this work and examining the distribution of detected X-ray binary systems, we can then illustrate the gap in known versus undiscovered X-ray binaries, and we may also discover new X-ray binary candidates worthy of additional follow-up. Finally, we plan to investigate source populations by comparing X-ray colors and luminosities of the eROSITA sources, which requires us to automate the Gaia source-matching process in Python to acquire distance estimates for the full eROSITA catalog.

In almost every stream, there is an abundant variety of aquatic invertebrates. However, the diversity of insects in small streams along the Wasatch Front are largely unknown to and unviewed by the general public. Caddisflies represent one of the most diverse orders of aquatic insects on Earth, spending most of their life cycle underwater and in larval form. Throughout the larval phase, individuals progress through multiple molting stages called instars. As an individual progresses from one instar to the next, it sheds its old exoskeleton and grows a new one. Butterflies and moths are the closest relatives to caddisflies, sharing their ability of silk production to make cocoons for metamorphosis, but caddisfly cocoons are aquatic and many caddisflies build cocoon-like cases for themselves, which they live in throughout one or several of their larval instars (not just during metamorphosis). With this project, I highlight two caddisflies, both collected from Strongs Creek, located along the Northern Wasatch Front, adjacent to the Weber State University, Ogden Campus. Specimens were collected from Strongs Creek and kept in 70% ethyl alcohol. To identify the larvae to genus, individuals had to be removed from their cases. The genus Neothremma and Protoptila are two common case building genera in Strongs Creek, but their cases are very different. Neothremma builds long, slender tubes out of sand, whereas Protoptila builds “turtle shellsâ€_x009d_ made of fine gravel. Because of this, case removal for each genus is relatively different. Neothremma cases can be peeled off in small pieces, whereas Protoptila cases each characteristically have a “largeâ€_x009d_ piece of small gravel on each side that can be opened like a trap door. The different cases of the two genera reveal the different lifestyles of each genus. Both genera graze on algal growth, but their cases allow them to feed in different areas. Cases of Protoptila look like a rocky protrusion on the rocks they cling to. Because it is harder for predators to determine what is rock and what is prey, they graze freely in the open and even on rocks that protrude above the water surface. In contrast, Neothremma remains submerged and typically grazes on the sides of rocks. Cases also promote respiration. Neothremma undulates its body inside its tube case, funneling oxygen-rich water over the body. Protoptila does not undulate, but small cracks in the case allow water exchange.

The purpose of this study is to critically examine and compare the concentrations of phenols and antioxidants in two co-occurring subspecies of Artemisia, Big Sagebrush A. t. ssp. vaseyana and Wyoming Sagebrush A. t. ssp. Wyomingensis. The findings of this study carry dual significance as they inform herbivore ecology through compound retention in Artemisia in late fall, which is critical for understanding seasonal concentrations that contribute to livestock toxicosis (e.g., “sage sicknessâ€_x009d_) through the grazing of sheep and horses. Additionally, they quantify bioactive chemotypes in Artemisia subspecies, which may have potentially higher concentrations than those previously used in Artemisia species in current cancer research studies, thereby expanding the possibilities of determining which subspecies is most suited for usage based on its bioactive chemotypes. The study utilizes methanol extracts from dried perennial leaves and flowering bodies of each subspecies to conduct a Folin-Ciocalteu phenolic assay on a gallic acid curve and an antioxidant capacity assessment via the DPPH Spot Test to determine concentrations. I hypothesize that the concentration of secondary metabolites will be higher in perennial leaves than in flowering bodies in both subspecies, potentially informing the selection of superior plant material for future biomedical research and guiding herding strategies seasonally to prevent sickness in grazing animals.

Plant productivity can be affected through multiple types of factors, but are dependent on environmental conditions to survive and function in different microclimates. One way of measuring this is through a plant’s light compensation point (LCP). This is understood to be the point where the rate of a plant’s carbon dioxide intake through photosynthesis is equal to the rate of carbon dioxide release through respiration. This research attempts to make a unique contribution by using a quantitative approach to explore the phenotypic plasticity of moss in contrasting microhabitats, focusing on the central question: How does the microclimate affect the light compensation point in moss species? Two samples from the same species of moss will be taken from two different microclimates. A light response curve for each moss will then be created using a LI-COR machine with a bryophyte chamber to measure the photosynthetic rate at different light intensities and determine the point at which photosynthetic gain and respiratory loss are equal. Expected results would be a reflection on the principles of phenotype plasticity and light adaptation. The expected results would show that the moss sample taken from a lower light microclimate will exhibit a lower LCP in comparison to the moss sample taken from a higher light microclimate. Since light environments can vary a plant species or a plant individual's LCP, it can be suggested that certain populations adjust their physiological mechanism to limit carbon loss when in low light conditions and is important for shaping plant function.

Allelopathy: definition: the chemical interaction where one organism (plant or tree) releases chemical substances that influence the growth, development, or death of another organism, either positively or negatively. Walnut trees are typically avoided in terms of planting because of its strong allelopathic chemicals. These chemicals the tree releases are strong enough to inhibit growth of a lot of its surrounding plants. This chemical the walnut tree produces is called"juglone". Ultimately this study covers the effects of the juglone chemical on garden crops, flowers, or weeds. In this case the garden flowers were chosen. All together this project is an education topic to normal homeowners who want to kill invasive weeds, but do not want to use toxic brands and chemicals like roundup. Which some studies have linked it to be carcinogenic.

Anyone who has worked with young children will agree that saying no is often challenging. This exploratory practice inquiry (Miller, Cunha, & Allwright, 2021) that seeks to understand lived experience within the context of their lives emerged from the frequent, stressful power struggles I had with my own son (18–22 months old). I sought to discover how intentionally shifting my practice—to prioritize meaningful voice and choice and suspend my adult agendas—would impact his development and our relationship. The method reflected the quality of "bricolage" (Levi-Strauss), fostering rich three-component multimodal dialogue among myself, my child, and faculty mentor as copractitioners of learning and teaching: 1) Self-inventory reflections examining my assumptions and emotional experience in relation to child development reading. 2) "Thinking Lens" photo documentation and reflexivity writing (Curtis & Carter, 2007) to deconstruct daily conflicts and understand ways to transform conflicts into opportunities for inquiry. 3) Faculty mentor discussions to guide reflexivity and theory development. Initial findings were simple yet profound: As I stepped back while supporting his desires, more opportunities for his voice and choice emerged, which in turn fostered holistic development for him and myself. These insights then evolved when I was introduced to Self-Determination Theory. It was like I had been given the language I was speaking without knowing. Learning that children have a sociocognitive need for Autonomy, Competence, and Relatedness affirmed that every single action—from the desire to remove things from the trash to tackling a new skill—was a bid for connection or an attempt to understand his world, and influence on the world: Autonomy: Making space for his voice improved his communication, and he expressed desires beyond the choices I offered. Competence: Problem-solving and confidence expanded through allowing ‘risky’, independent play. Relatedness: Attachment security was fostered. As I became more responsive to cues, his face and eyes were filled with joy, understanding that I would support his wishes. Alongside an understanding of what children need, my emerging professional identity has undergone a fundamental shift, from a stressed caregiver to a curious researcher who understands the nuanced relational ways in which child development unfolds and strives to see growth opportunities at every corner. This simultaneously demonstrates how using exploratory practice inquiry as a tool for professional reflection fulfilled my parent and teacher candidate's intrinsic need for autonomy and competence—resulting in a more self-aware and responsive practice—while concurrently fostering the child's own self-determination, leading to a more confident, agentic, and cooperative young learner. References: Curtis, D., & Carter, M. (2007). Learning together with young children: A curriculum framework for reflective teachers. Redleaf Press. Curtis, D. (2008). Seeing children. Beginnings Workshop, 38-42. Gartrell, D. (2021). Instead of discipline, use guidance. Teaching Young Children, Summer. Jablon, J. R., Dombro, A. L., & Wilkinson, M. (1999). The power of observation for birth through eight. Pearson. Lévi-Strauss, C. (1966). The savage mind (Original work published 1962). University of Chicago Press. Miller, I. K., Cunha, M. I. A., & Allwright, D. (2021). Teachers as practitioners of learning: The lens of exploratory practice. Educational Action Research, 29(3), 447-461. Murphy, T. F. (2024, April 2). Separation-individuation theory of child development. Psychology Fanatic. https://psychologyfanatic.com/separation-individuation-theory-of-child-development/ Utah Department of Workforce Services. (n.d.). Utah’s early learning guidelines for birth to age three. https://jobs.utah.gov/occ/provider/early_childhood.pdf

Purpose/Hypothesis: Obesity rates among young adults are steadily increasing (Sa et al., 2019), sparking greater interest in the dietary factors that contribute to increased Body Mass Index and waist circumference. As obesity is a well-established risk factor for chronic conditions such as cardiovascular disease, type 2 diabetes, and certain cancers (Wang & Beydoun, 2009), understanding its dietary determinants is critical. Meat consumption, including white meat, poultry, and processed meats has been linked to obesity (Shaghayegh et al., 2022). This study examines the relationship between reported meat consumption and two key indicators of obesity in college students: waist circumference and Body Mass Index (BMI). We hypothesized that higher levels of reported meat consumption are positively correlated with both waist circumference and BMI in this population.

Methodology: We used data collected from Weber State University students between 2015 and 2023. The data set included 316 participants, with 101 men and 215 women. Anthropometric measures were taken for each participant, including height, weight, and waist circumference. Height and weight measurements were used to calculate BMI. Participants tracked their diets for two days using Diet and Wellness Plus software, which assessed intake of total calories, saturated fat, and sodium. Participants also reported their weekly meat consumption habits on a scale from 1 (never) to 5 (every day).

Results: We used SPSS statistical analysis to examine the relationship between reported meat intake and body composition measures. We observed significant positive associations between reported meat consumption and BMI (p=.02) and waist circumference (p=.017) among female students. However, this association was not observed in male students. Additional analyses examining total caloric intake, saturated fat, and sodium revealed no significant correlations with BMI or waist circumference.

Conclusion: Our results suggest that higher levels of meat consumption may play a role in increased BMI and waist circumference among female students. Since total calorie intake, saturated fat, and sodium did not show significant correlations with BMI, these findings suggest that meat consumption independent of these factors may have a stronger association with obesity in college-aged females than previously thought. Given these results, we suggest that increasing plant-based food consumption, rather than focusing solely on calorie or fat reduction, may offer important benefits to female college students in preventing obesity.

A permutation (a_1,a_2, ..., a_n) of {1, 2, ..., n} is called good if the entries of (1 + a_1, 2 + a_2, ..., n + a_n) are distinct modulo n. We obtain some partial results on the problem of determining all positive integers n for which there exist good permutations. In particular, we show that every odd n has a good permutation. Our methods make connections with Latin squares. We show a relationship between good permutations and a class of n × n Latin squares with Zn entries such that the main diagonal is distinct. We further determine a lower bound for the number of good permutations for a fixed n and show that in some cases this bound is strict. These questions were proposed by H. A. ShahAli in MAA’s Mathematics Magazine Problems for Fall 2025.

This proposal was authored by the students in Weber State University's State Politics class in the fall semester of 2025. The emphasis of this report provides a framework for establishing and governing the newly incorporated Ogden Valley City in a manner that promotes transparency, fiscal stability, environmental stewardship, and sustainable economic development. The city's Code of Ethics underscores a commitment to public trust, responsible governance, and high standards of conduct for all municipal employees. Economic analysis indicates that Ogden Valley's business activity is primarily centered around recreation and tourism, restaurant and retail operations, and small service providers. Business clusters are currently concentrated in Eden and the Wolf Creek/Nordic Valley area. To ensure stable revenue to support essential public services, the proposal recommends modest increases in the property tax rate (from 0.67% to 0.75%) and the sales and use tax (by 0.25%). These incremental adjustments are designed to strengthen the city's financial capacity while remaining minimally burdensome to residents. Because Utah's Truth in Taxation law prevents automatic revenue growth from rising property values, annual fiscal reviews and public engagement are recommended to maintain transparency and support informed decision-making. The proposed Model City Charter provides a foundational governance structure defining powers, responsibilities, and operational procedures for the new municipality. Strategic land use and population growth planning account for projected expansion through 2035, emphasizing the preservation of open space and the rural character of the valley. Establishing North Fork Park as the centerpiece of a Dark Sky Park and Observatory initiative would leverage the valley's existing International Dark Sky status to promote education, tourism, and light-pollution reduction. Environmental sustainability is central to this proposal. Policy recommendations include reducing single-use plastic consumption, promoting recycling and public education, and implementing water-conservation measures in response to declining snowpack and long-term reductions in water availability. Residential water-use limits, outdoor watering schedules, tiered water rates, and conservation incentives are suggested to ensure a sustainable water future. Overall, this proposal seeks to balance economic vitality, responsible governance, and preservation of the natural landscape that defines Ogden Valley. It establishes a foundation for a fiscally secure, environmentally resilient, and community-focused municipal government.

DNA repair mechanisms are essential for preserving genomic integrity, and disruptions in these pathways can contribute to oncogenesis. kjul is a gene implicated in methylated DNA repair, functioning specifically by correcting T-to-G mismatches. Loss-of-function mutations in kjul result in MBD-associated neoplasia syndrome (MANS), a condition characterized by increased susceptibility to various cancers, including acute myeloid leukemia (AML). This study investigates the role of kjul in AML pathogenesis using Danio rerio (zebrafish) as a model organism. Zebrafish offer advantages such as genetic conservation with humans, rapid embryonic development, and transparency during early developmental stages, enabling real-time observation of hematopoietic processes. kjul expression was suppressed using morpholino oligonucleotides to assess its impact on myeloid cell development. In situ hybridization and quantitative PCR (qPCR) were employed to evaluate changes in myeloid gene expression. Additionally, we aim to functionally validate variants of unknown significance (VUS) found in the kjul gene, to determine their pathogenicity and potential role in leukemogenesis. Findings from this study will contribute to a deeper understanding of kjul in myeloid differentiation and its broader implications in AML development and genetic diagnosis.

Natural reverberation (reverb) in a 3-D environment is the result of a series of uniquely reflected sound waves that enhance the sound of acoustic music. Historic cathedrals and opera halls were designed to optimize natural reverberation and create a sense of space that listeners appreciate. However, access to these spaces is limited, and modern recording technology can now synthesize natural reverberation using a mathematical process called convolution. Convolutional reverb processes a ‘dry’ (studio) input audio file with the measured impulse response of an acoustic space, resulting in audio that sounds like it was recorded in the room. Multiple methods exist to record and pre-process the impulse response of an acoustic setting [1-3]. In addition, methods exist to accurately and efficiently convolve the input audio with an impulse response for real-time reverb applications. A long-term applied research project of the WSU ECE department is to develop an in-house convolutional reverb platform. The near-term objective is to develop the audio processing capability using open-source software and ECE designed hardware. An ECE department goal is to collaborate with the WSU Music department to acoustically characterize environments. For example, both the student and mentor hope to measure the impulse response in one of Ogden’s most notable acoustic settings, the historic Saint Joseph’s Church. The current research objectives are to acquire proficiency in measuring impulse responses of acoustic spaces, and to optimize the convolution process by creating a custom audio processing library (in Python). The hardware platform and post-processing algorithms are student-developed. Initial tests are encouraging and indicate that a high-fidelity student-developed convolutional reverb platform is feasible. Preliminary results will be presented with a discussion of future project goals. [1] Practical Recording Techniques, 4th ed., B.J. Bartlett, Elsevier, 2005 [2] ‘Recording Concert Hall Acoustics for Posterity’, A. Farina, R. Ayalon, Audio Engineering Society (AES) 24th Int’l Conf. on Multichannel Audio, June 26-28, 2003, pp 1-14 [3] ‘Estimating Room Impulse Responses from Recorded Balloon Pops’, J.S. Abel et al, Audio Engineering Society, 129th Conference, Nov 4-7, 2010.