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BEHAVIORAL & SOCIAL SCIENCES
Although there has been extensive research on how well coloring has improved test scores, mental-emotional-social well being, improvements of anxiety for adolescents, and been a way to promote mental health, there is very little information on how younger adolescents (ages ten through fourteen) feel about the activity of coloring, and what their experience is with it. This gap in research leads to the question "What are the emotional and physical experiences of adolescents ages 11 through 14 from coloring?” To begin this research, I went to a local middle school and asked the administration for the students to participate in my study. Once allowed, I went to available classes to talk about the goal of my study, and how I needed them to participate. I gathered participants and their consent forms, and ran the study with multiple classes. Each class had a 10 minute period of coloring in a mandala, where they focused on relaxing, being in the moment, and the how they felt physically and emotionally. Once the 10 minutes ended, they were asked to complete a survey with 20 multiple choice questions and 5 free response questions. I used free response on top of multiple choice so I could gather the participants' experience in their own words. Once I am done collecting the data from my participants, I will analyze the multiple choice responses and code the free response questions to make a conclusion about the participants' experience from coloring. I hypothesize that these adolescents will find the coloring experience fun and emotionally good, but that it did not have an effect on their physical state, as previous studies have seen that 18-26 year old's enjoy the experience because it reminds them of childhood and the comfort of being at home.
BEHAVIORAL & SOCIAL SCIENCES
Recent studies have found that grip strength can be used as a predictive tool for identifying older adults at risk for poor health. We also know that social isolation increases as people age. The purpose of this experiment is to determine the most effective way of encouraging older people to improve their grip strength. We wanted to see if there is a correlation between motivating older adults within a social setting and an improvement in their grip strength. We hypothesized that a weekly social group for 6 weeks in combination with a series of exercises lasting 15 minutes would increase the participant’s grip strength. Grip strength was measured using a hand dynamometer at the beginning and end of the study and compared to the grip strength of other visitors to the Senior Center who did not participate in the social group. Visitors to a Senior Center will be more likely to exercise if they have previously participated in a community-based exercise group that teaches them how to improve grip strength compared to people receiving only written information on how to improve grip strength.
BEHAVIORAL & SOCIAL SCIENCES
Obesity is a major public health issue in the United States, in 2017, over 40% of adults had standard obesity. This condition is linked to health problems such as diabetes and heart disease. With these rampant issues, finding a solution is vital. This paper will compare the effectiveness of three different diets, a sensory, metabolic, and traditional one in achieving sustainable weight loss. The sensory diet alters the perception of food, with a smaller plate having the illusion of more food when compared to a larger plate with the same amount of food. The metabolic diet, shown by the ketogenic diet, offers weight loss, but it requires a high-fat diet which may not be sustainable. The traditional diet shown through a Mediterranean diet is a more sustainable approach, however, it is not the most popular approach since it requires high adherence. Even though there is existing research on these individual diets, a decisive comparison has not been reached. There has not been a use of both a survey and a meta-analysis to answer the question of which diet is most effective. the research intends to solve that gap through both a survey and meta-analysis, evaluating which diet is most effective for weight loss. The survey was sent out to public forms to review data from a wide amount of people. The meta-analysis was performed on pre-existing data on the weight loss resulting from individual diets.
BEHAVIORAL & SOCIAL SCIENCES
Misinformation spreads rapidly online, often more than true content. False news stories are 70% more likely to be shared than true ones. True information take six times longer to reach same number of people as misinformation. People are more likely to engage with and believe misinformation when it aligns with their political identity, whether conservative or liberal. While existing research focuses on detecting and removing misinformation, little attention has been given to increasing engagement with fact-checked information across political ideologies.
This project explores how moral identities influence interaction with fact-checked content. Using Moral Foundations Theory (MFT), fact-checked headlines are framed around five moral foundations—authority, sanctity, loyalty, care, and fairness—to align with conservative and liberal values. Since misinformation spreads when it resonates with political identity, this study tests whether morally framed fact-checked headlines enhance engagement.
The methodology includes (1) controlled studies with 1,000+ respondents across seven countries and (2) a real-world study conducted on a digital ad platform that presented the headlines to more than 62,000 people, examining how they engage with fact-checked headlines that are framed using the five moral foundations. The results showed that the fairness and care frames enhanced engagement among liberals, while the sanctity and loyalty frames increased engagement among conservatives.
By aligning fact-checked information with moral identity, this approach aims to counter misinformation, foster accurate beliefs, and increase engagement with true content, ultimately slowing the spread of false information. Most importantly, this approach can help mitigate misunderstandings driven by political ideologies.
BEHAVIORAL & SOCIAL SCIENCES
Book covers are essential for binding the pages of a book, grabbing the reader's attention, and displaying key points from the story (Haque et al. 2022). Without covers, the book’s expectations will be skewed and less likely to stand out against their neighboring shelves of books. With artificial intelligence (AI) penetrating the art world, authors and publishers can use this technology to create book covers. However, as AI is used more in the art world, it threatens to diminish artists' purpose, profit, and self-expression ( Jiang et al., 2023; Otmar, 2024). In recent years, authors have used AI to generate their covers and their books are currently accessible to the public. Hence, with AI used in book covers, further research needs to be done to predict if AI may help increase reader interaction with authors’ books, compared to their human-made covers. If authors’ AI-generated cover increases reader interaction, measured by book pick-up rates, then authors and publishers should consider using AI for their book covers. However, using AI to make book covers would directly impact cover designers’ jobs as they could be replaced. By comparing reader pick-up interaction between the AI-generated book cover to the human-made book cover, this project aims to see if using AI may benefit authors and publishers by getting their books into more readers’ hands when hiring cover designers’ has been the standard.
BEHAVIORAL & SOCIAL SCIENCES
Attention spans recently among audience members have begun to significantly decrease, only averaging around 35-45 seconds in the past 5 years. The reason for this significant decrease is due to short-form content apps, such as Tiktok, that create a more favorable form of media that provides quick results of dopamine and information. Because of the shorting of attention spans, overall movies and shot lengths have also begun to be affected as long form scenes are no longer favorable in this climate. However from past studies done, specifically in the areas of soundtracks and attention spans on the movies, a increase in attention is shown in focus when certain portions of track are made. Furthermore I decide to focus more on the character level and how characters and their theme songs may be able to attract audience attention more due to key factors from previous studies of likability, memorability, and familiarity. By testing audiences familiarity of characters from 12 movie clips shown through a likert scale , their memorability of the characters soundtrack through a listening-matching activity, and overall audience observation of the clips, it was aimed to find an increase in audience attention spans. Overall from the results no significant results were gathered as results from two test groups were similar in results, however certain results that were close to significant provide a basis of future research into this topic.
BEHAVIORAL & SOCIAL SCIENCES
Epilepsy is a pervasive neurological disorder affecting millions globally, causes recurrent seizures, and increases the risk of premature mortality. Epilepsy also has multiple types, like mesial temporal lobe epilepsy (mTLE), and it is the most common type of focal epilepsy, accounting for around 40% of all epilepsy cases. One way researchers develop therapies for epilepsy is by creating animal models that replicate the disease from humans. Animal models like the intrahippocampal kainic acid (IHK) mouse model allow researchers to study mesial temporal lobe epilepsy. The gap in this research stems from a study published in 2021 by Christos Lisgaras and Helen Scharfman, who concluded that evidence of frequent and robust seizures often varied across studies of the IHK model. Therefore, this study will attempt to characterize a novel iteration of the IHK model in various ways and assess its ability to test drug treatments for mTLE. This study's research question asks what happens to the frequency and patterns of seizure activity in the IHK mouse model of epilepsy over time, as visible through V-EEG data analysis. As past studies have indicated an extensive variability in seizure frequency and patterns, the hypothesis for this study is that the frequency and severity of seizure activity in this novel IHK mouse model will, too, show no significant patterns of seizure frequency or severity as the disease progresses. Furthering understanding of this model can help researchers understand the model for future use and help identify critical periods of administration of ASMs.
BEHAVIORAL & SOCIAL SCIENCES
This project investigates the how repeating answer sequences on a multiple choice test (MCT) affects student testing behavior. Repeating answer sequences occur when the correct answer position on a MCT is the same for numerous questions in a row. For example, the correct answer for questions 1 through 5 on a MCT could be the 3rd answer option. As MCT have become the main form of testing for the majority of schools, it is important to fully understand how students behave during testing so that the most optimal performance is achieved. This project will investigate this question through 3 main data collection points. The first is a initial survey sent out to Juniors and Sophomores. This survey will determine if students have noticed repeating answer sequences in the past. The second is a test which has specific patterns created by the investigator. The third is a second survey, taken after the test which askes about students own actions taken during the test. A fourth data collection will be derived from the physical scan-tron used during the test.
BIOLOGY & MICROBIOLOGY
This study represents an investigation into the potentials of three polyphenols: Epigallocatechin gallate (EGCG), Curcumin, and Resveratrol as immunomodulators for immune therapy for cancer. Their effects on cancerous cell viability and stimulation of the immune system are the major focuses. This research probes into the potential of such compounds at multiple concentrations regarding their cytotoxicity on four different types of human cancer cell lines-A549-lung, HCT-15-colon, and Malme-3M-skin using Peripheral Blood Mononuclear Cells to model the human immune system. In this study, the assessment of cell viability was done through the CellTiter-Glo luminescence assay, while immune responses were analyzed using Luminex. The results showed that the drugged PBMC’s were cytotoxic to cancer cells in a dose-dependent manner. The assay showed that there was cancer cell death, including more in the drugged PBMC’s. Luminex analysis demonstrated that these polyphenols significantly changed cytokine profiles by upregulating immune-stimulatory cytokines and modulating both pro- and anti-inflammatory cytokines, showing an enhancement of immune-mediated tumor suppression. In summary, these polyphenols have shown promise as immunomodulators for immune therapies in cancer through the induction of cancer cell death and enhancement of immune responses. These findings support further research into their mechanisms, immune activation, and their potential to enhance tumor suppression.
BIOLOGY & MICROBIOLOGY
Temporal lobe epilepsy (TLE) is a common form of focal epilepsy which affects over 60% of people with focal epilepsy, . However, because of the novelty of the Lisargas IHK model, certain aspects such as the analysis of the interaction of the circadian rhythm, the body’s internal 24-hour clock, have yet to be tested against it. According to one human study, circadian rhythms play an important role in determining and predicting seizure risk, with seizures often coinciding with specific periods during the sleep-wake cycle. Thus, an analysis of the relationship between the IHK mouse model and circadian rhythm can further validate the model, while also contributing to the development of effective treatments of TLE. Using a thorough analysis of sleep-wake cycles in relation to circadian rhythms in the IHK mouse model, effective epilepsy medication dosage administration amounts and times could potentially be identified to reduce seizure activity. Therefore, in order to understand this relationship, the Wilcox lab gathered 17 male mice and injected 100 nL of 20 mM kainic acid into the CA1 region of the hippocampus to induce TLE. Simultaneously, electrodes were also implanted into the brain. After epilepsy was verified, the mice were given a 6 week break to recover from the surgery. Following the break, the mice were monitored for 26 days, where a combination of video and electroencephalographic data was analyzed to detect and score seizures.
P.S: By the way, I don't know Dr. Wilcox's phone number and I can't find it so I just put in Dr Celestino's
BIOLOGY & MICROBIOLOGY
Vorticella is a single celled organism that's known for its distinctive ciliary structures, which generate currents for feeding and propulsion, This project investigates how Vorticella cilia behave before and after a rapid "collapse" event, focusing on quantifying the wave speed of ciliary motion. To do this, high-speed video recordings were processed using ImageJ and MATLAB to create kymographs, which map time onto one axis and ciliary position onto the other. By measuring the slopes of diagonal lines in these kymographs, I calculated ciliary velocities and compared them before versus after the collapse.
Results showed that cilia typically beat at around 59-72 micrometers per second pre-collapse, while the speeds after the collapse generally ranged from 55-68 micrometers per second, depending on the region of the ciliary tuft. The middle area carried the fastest speed, although it still experienced a slight reduction, whereas the rightmost region exhibited the most significant drop in velocity. Standard deviations and standard errors were also calculated, confirming the reliability and reproducibility of the findings.
These results support the hypothesis that collapse events alter ciliary dynamics in Vorticella. The work combines advanced image-processing techniques, quantitative data analysis, and biological observation to highlight the sensitivity of ciliary motion to mechanical or physiological disruptions. This research may contribute to understanding how single-celled organisms adapt their feeding currents and locomotion to respond to environmental or internal triggers.
BIOLOGY & MICROBIOLOGY
Transient receptor potential melastatin three (TRPM3) is a membrane protein expressed in somatosensory neurons. This protein is activated when it detects noxious heat (homeostatic threatening heat) and other chemical signals. When TRPM3 detects this signal, it causes the release of an extremely potent vasodilator known as Calcitonin gene-related peptide (CGRP). Vasodilation widens the blood vessels, allowing for increased and faster blood flow, thereby reducing body heat. This protein response can be observed in many organisms, however, this research intended to explore the protein’s relationship in penguins. Penguin species can range from tropical climates to polar climates, including South America, Australia, South Africa, and Antarctica. Considering their antithetic climates, a protein like TRPM3 should have some extent of alteration resulting from this climatic evolutionary change in penguins. In examination of this, my research intended to investigate how the temperature-sensing protein TRPM3, evolved through climatically different penguin species. As a result of climate change, there has been a mass requirement for adaptation among countless organisms, and heat-regulatory proteins such as TRPM3 are becoming increasingly important. Polar birds are extremely vulnerable to such drastic temperature changes because of their limited heat tolerance and lack of evaporative cooling capabilities. Considering the threat to these animals, finding an adaptation is key to ensuring their future survival and fitness. Research aimed toward the identification of heat-resilient adaptations has the potential to save countless species using gene-editing tools like CRISPR. It is through looking at proteins like TRPM3 that we may find one.
BIOLOGY & MICROBIOLOGY
Rubbing or isopropyl alcohol is found in many homes because of its usefulness as a cleaner and antiseptic but if consumed it may be lethal. It can also affect you when inhaled or passing through your skin. Since planaria share some key elements of the vertebrate nervous system, we selected them as a model organism to study the effects of rubbing alcohol. Planaria exhibit a range of behaviors to environmental stimuli including scrunching behavior that is well-documented in literature. The purpose of this experiment is to understand how different levels of rubbing alcohol affect planarian behavior, looking specifically at, curling, distance traveled and scrunching. It was hypothesized that the higher the amount of rubbing alcohol exposure to planaria, the more negative responses we would encounter. Planaria were exposed to increasing concentrations of rubbing alcohol, and then speed of movement, frequency of curling and scrunching were measured for 3 minutes. Higher concentrations of rubbing alcohol increased the number of negative responses while lower concentrations decreased, seeming to have relatively normal behavior. We also asked if prior rubbing alcohol exposure affected the ability of planaria to regenerate when cut in half. The results from this study may help inform human health and the effects of rubbing alcohol on our health.
BIOLOGY & MICROBIOLOGY
This science project is centered around exploring the different types of suture materials, the amount of weight the sutures can endure when attached to chicken wings, and how different sterilization materials affect the occurrence of infection. By choosing various types of suture materials, I will be able to see which ones will withstand the most tension. The types of suture materials I will be testing are nylon monofilament, silk braided, polypropylene monofilament, and polyester braided. The type of suture I am using is a subcuticular running stitch. The hope is to find which types of suture materials will be the most beneficial for the medical community. After I perform this original experiment, I will prepare the suture materials by boiling in red cabbage juice. Red cabbage juice contains a pH indicator which changes color in the presence of acidic conditions common in bacterial infections, I am going to use different sterilization liquids to test which ones would be the best in preventing infections. The three liquids I will be using are betadine, ethanol (70%), and dish soap.
BIOLOGY & MICROBIOLOGY
Human brains are built out of dozens of billions of neurons and dozens of trillions of inter-neuronal connections. Being the fundamental information-processing units, neurons are compartmentalized, containing a terminally branched axon that transmits signals and a dendritic tree for receiving and propagating information. The proper formation of dendritic arbors are essential to the development and formation of neural circuits. Clustered Protocadherins (Pcdh-α, Pcdh-β, and Pcdh-γ) are the largest group of cell-cell adhesion molecules in the cadherin superfamily and play critical roles in shaping neural circuits including dendritic arborization. Members of the Pcdh-α subfamily differ in the extracellular domain but share an identical intracellular constant region (CR). At the carboxy-terminal of the constant region is a highly conserved lysine-rich domain. This project aims to dissect the role of this lysine-rich domain in mediating Pcdh-α’s function in dendrite regulation. Plasmid DNA, encoding the constant region and lysine-rich domain, were introduced into primary cultured mouse hippocampal neurons. Dendritic trees were visualized and quantified by a co-expressed GFP reporter. The results showed that the full-length constant region reduces dendritic growth in contrast to the lysine-rich domain which enhances dendritic growth. This contrasting effect between the constant region and lysine-rich domain indicates that the Pcdh-α constant region has a previously unrecognized intra-molecular antagonistic mechanism in transducing the signals required for dendrite regulation. The discovery of the dendrite-promoting effect on the lysine-rich domain may also have implications in treating neurodegenerative disorders.
BIOLOGY & MICROBIOLOGY
Pathogenic fungi of the Candida genus, including Candida albicans, can be extremely dangerous to humans and threaten global health, especially in immunocompromised populations. Almost all Candida species belong to the CTG clade, which deviates from the common genetic code by ambiguously translating serine at CUG codons instead of leucine at a rate of about 97%. Simultaneously, to be virulent, Candida species must rapidly shift between two growth states: planktonic, where it grows as a regular yeast would, and biofilm, where it forms complex sheets and networks of branching filaments called hyphae. The goal of this project was to elucidate a potential biophysical relationship between ambiguous CUG codon translation and morphological phenotypes that influence virulence. Proteins that could play a role in this relationship were screened through an in-silico investigation to select candidates for planned in-vitro verification. Based on a review of literature, I selected a series of key morphology-associated C. albicans proteins that are rich in CUG residues or include CUG residues at critical sites, and generated predicted structure models for each protein using AlphaFold. Structures were then mutated to leucine at CUG residues and compared to wild-type structures in a series of in-silico assays to evaluate the implications of serine incorporation. Analyzed metrics included folding energy, stability, internal protein interactions, protein-complex interactions, protein-ligand interactions, active site cavities, solubility, and molecular dynamics. Preliminary results suggest that leucine incorporation may significantly interrupt structure and function in three signal transduction proteins and one cyclin, implying that C. albicans morphology and virulence could be associated with genetic code deviation at CUG codons. These proteins are promising candidates for planned in-vitro evaluation of phenotypic changes in response to leucine incorporation to verify the proposed mechanisms.
BIOLOGY & MICROBIOLOGY
Some salamanders, including newts, have the remarkable ability to regenerate their lost limbs and organs. These abilities are very limited in mammals, with one exception. Members of the cervid (deer) family can regenerate their antlers annually at an incredible rate. Tenascin C (TNC) and pleiotrophin (PTN) are proteins that are expressed at high levels in the regeneration blastema—a group of undifferentiated progenitor cells at the regenerating antler tip that is responsible for continued antler growth.
Previously, I investigated the effects of TNC and PTN on mouse preosteoblasts (MC3T3-E1, subclone 4 cells), a cell line that is typically committed to the bone lineage. My results suggested that these proteins were able to inhibit differentiation, keeping the cells in an undifferentiated state even after exposure to osteogenic growth medium. This finding raises the question of whether TNC and PTN not only prevent differentiation but also actively induce dedifferentiation of these cells to a multipotent state capable of redifferentiating down multiple cell lineages—a trait exhibited by cultured antler blastemal cells.
To explore this possibility, my current project will assess the extent to which TNC and PTN can induce regenerative capabilities in MC3T3-E1 cells. After treating these preosteoblasts with TNC and PTN, I will expose them to adipogenesis-inducing conditions to determine whether they can transdifferentiate into fat cells—a lineage distinct from their original bone-committed state. Using Oil Red O and Nile Red staining, I aim to determine whether these proteins can expand the differentiation potential of mouse bone progenitor cells.
BIOLOGY & MICROBIOLOGY
This project aims to measure the effects of artificial sweeteners on the microbiome, specifically how the gram of the bacteria affects the susceptibility to the sweetener.
CHEMISTRY & BIOCHEMISTRY
The goal of my project is to synthesize gadusol, an organically produced sunscreen that several aquatic organisms, such as zebrafish, brine shrimp and cod, maternally place on their eggs to protect them from ultraviolet radiation. Researchers demonstrated that gadusol is required for the survival of zebrafish embryos. These organisms synthesize gadusol through a metabolic route using a sugar intermediary. Synthesizing gadusol in yeast or bacteria is complicated and inefficient because it cannot easily be isolated and requires genetic modification of those organisms. In my project I worked on implementing a strategy for a complete chemical synthesis of gadusol through a process of several chemical reactions. The importance of this project is that modern sunscreens, even reef-friendly versions, can cause harm to aquatic life, and gadusol could potentially be the basis for a marine-friendly sunscreen. Moreover, chemical synthesis of this compound would have the benefit of modifying the structure so we can make bio-inspired analogs. Multiple sequential precursors, that built upon each other, were produced in the process of synthesizing gadusol. Because of the significant amount of work I was able to achieve over the summer, the final steps of the synthesis are underway and a provisional patent has been filed.
CHEMISTRY & BIOCHEMISTRY
Synthetic fertilizers and pesticides can cause public health issues, environmental harm, and further runoff into nearby water bodies. The contaminated water can result in the growth of harmful algal blooms (HABs), which lead to detrimental consequences on aquatic life within an ecosystem. Creating a sustainable and effective biofertilizer from algal strains commonly found in HABs can both give insight into mitigating the negative impacts of HABs and reduce harmful impacts of synthetic fertilizer runoff. To address these environmental problems, this study will use strains of algae commonly found in HABs such as Anabaena and Microcystis and convert the microalgae into biofertilizer in the form of a solution. The biofertilizer will be tested on mini peppers, and compared to both unfertilized plants and those fertilized with a commercially available synthetic fertilizer. Plant height, mass and color will be measured weekly, as well as the plant yield.It is predicted that the biofertilizer will lead to a greater mass, yield, and a higher height in the mini pepper plants as compared to the synthetic fertilizer and the control. Furthermore, mini pepper plants are anticipated to respond positively to the biofertilizer due to their extensive root systems. Future research entails combining growth-promoting plant hormones, such as gibberellins, with the algal strains found in HABs to create a more effective biofertilizer or testing biofertilizer created from HABs themselves.
CIVIL & ENVIRONMENTAL ENGINEERING
Plastic is arguably one of the best inventions of the 20th century. But we are now realizing that degradation of plastic leads to the formation of microplastics which are hazardous to human health by causing inflammation and neurotoxicity. The purpose of this experiment is to see if we can create a water filter from biochar to remove microplastics from water. We will investigate whether the pore size of biochar affects how much microplastic it can retain. I hypothesized that the smaller the pore size of the biochar source, the more microplastic it will filter out. Small filters containing biochar from pistachio shells, rice husk, or pine trees were constructed. Microplastics were added and the filters were subjected to 10 wet/dry cycles. The penetration of microplastics through the filter was quantified by taking 1cm cross sections of the biochar filters and counting microplastics under the microscope. The data from this experiment showed that all three biochar sources retained microplastics. My second experiment designed a method for isolating smaller microplastics to use in the biochar water filters.
CIVIL & ENVIRONMENTAL ENGINEERING
Levels of arsenic in drinking water are an area of concern for public health officials because arsenic is known to cause cancer, skin lesions, and death upon continues ingestion. The purpose of this experiment was to build a water filter using biochar that would effectively retain arsenic. We wanted to determine the relationship between biochar concentration in a filter and arsenic levels after filtration. I hypothesized that increasing biochar concentration (5, 10, 15, and 20% biochar) in the filter would decrease the arsenic concentration in the output water. Filters were constructed with a mixture of biochar and sand in 30.5cm lengths of PVC pipe. Preliminary findings with a chemically similar cation to arsenic showed that the chemical properties of biochar were possibly able to retain sodium chloride although, the result is difficult to determine due to possible leaching from the filters. Arsenic contaminated water was put through biochar filters, after which the concentration of arsenic was measured using mass spectrometry. The results from this study suggest that biochar filters can be used in facilities to decrease arsenic levels in drinking water at 5% and 10% biochar concentration.
CIVIL & ENVIRONMENTAL ENGINEERING
Perfluoroalkyl and poly-fluoroalkyl substances (PFAS) have garnered significant attention and
are being tracked in environmental matrices because of their high toxicity and growing health
risks for cancers and thyroid. PFAS are detected globally in numerous biotic and abiotic
samples, including polar bears, packaged drinking water, and human blood, due to their
widespread domestic and industrial uses, such as semiconductor and electro-plating industries,
cleaning agents, personal care products, and fire-fighting foam.
Many studies reported that WWTPs are the primary gateway for polluting PFAS in our
environment. Therefore, in Dr. Goel’s lab at the University of Utah, I investigated the presence
of PFAS by collecting actual solid and liquid environmental samples from a local wastewater
treatment plant (WWTP) in Utah. Data from this study revealed that Long-chain PFAS such as
PFOA and PFOS are present at higher levels, specifically in the biosolids samples, than short-
chain PFAS. Generated biosolids are heavily used in agricultural fields, which could result in
increasing PFAS contamination in our environment and living entities. Additionally, both short-
and long-chain PFAS are detected in the treated wastewater, thereby polluting the water bodies
and affecting the overall transport of PFAS into our environment.
CIVIL & ENVIRONMENTAL ENGINEERING
Industrialization continues to drive climate change and place significant stress on the environment. The production of concrete contributes to approximately 8% of global carbon emissions, making it one of the largest emitting industries. Calcite, the binding agent in cement, is responsible for the bulk of carbon emissions due to the mining and processing of limestone. This study aims to synthesize a strong, carbon-neutral biocement from the calcifying marine macroalgae Halimeda opuntia, which sequesters carbon dioxide. H. opuntia will be cultivated in artificial saltwater, then processed in a dry form before being incorporated into different cement samples at varying ratios. Once the samples have set, the compressive strength of the cement will be evaluated using a compression testing machine (CTM) to determine the optimal ratio of algae in the cement mixture. It is anticipated that biocement derived from H. opuntia will perform comparably to traditional cement in compressive strength due to the high CaCO3 tissue content in H. opuntia. Future research will investigate how algae-extracted CaCO3 affects the strength of biocement and will compare the setting time of biocement to that of traditional cement.
CIVIL & ENVIRONMENTAL ENGINEERING
Our project aims to take salty water from the ocean and convert it into clean drinkable water autonomously. We are achieving this by using three sources of clean renewable energy powering repurposed boats. Our three power sources are solar, wind, and microbial fuel cells. The microbial fuel cell is our backup system that works in any weather and powers the boat when the solar cells and wind fans aren’t able to generate energy. The boat, which is active near the shore, takes in water rich with phytoplankton, which produces organic matter through photosynthesis. This organic matter is metabolized by the microorganisms that release electrons which we can then harness. But to be able to use this power, we need to have very efficient systems. Our code moves different types of boats in an efficient and simple way to allow for scalability and energy efficiency. This code allows us to access GPS tracking and navigation to allow for movement in different areas in the world paired along with an object avoidance system to avoid any issues and transport the energy. With the combination of highly efficient code and three sources of power, we are able to create a fully autonomous boat that purifies water and can be used to help solve the global water crisis.
CIVIL & ENVIRONMENTAL ENGINEERING
Water pollution is a major crisis that affects almost every country in the world. Access to safe drinking water in many of the developing and under developed countries have posed a major health risk around the world. In this project, I will investigate the use of different bio organic biochars mixed with potato starch including cilantro biochar mixed with potato starch, wood biochar mixed with potato starch, coconut biochar mixed with potato starch prepared at different time intervals and compare it with the commercial Brita water filter to compare the effectiveness in reducing heavy metal and other contamination in water. After using filters for at least 3 times, I will mix the biochar with the soil and measure the soil moisture content to access the effectiveness of different biochars on soil. The reason for this research is to eventually be able to create a product, based off the information gathered from this experiment, that will be able to create a cost effective bioorganic filter compared to commercial filters, thus eliminating the need for billions of dollars to be spent on importing clean water to countries from other countries and provide access to clean and safewater. If the biochars after filtration can be used as an effective way of increasing the quality of soil by enhancing the soil water retention, the amount of waste released to the environment from commercial filters can be greatly reduced.
CIVIL & ENVIRONMENTAL ENGINEERING
Victor and Forest were inspired by the tragic wildfires every year, especially the Post Fire in California this last June. Around $500 billion and 7 million acres are consumed each year in the U.S. alone. We talked to local firefighters, who said they only use their brains and experience currently. FlameFender and its AI applications are here to change that. FlameFender has 4 main parts. First, we created an app on MIT App Inventor for firefighters and the public. It defines fires to different levels of severity using a trained CNN, detects live human movement using Posenet, detects smoke inhalation using FaceMesh, generates smart responses for different situation, etc. Second, we assembled our Freenove Smart Car, with our RPi5 on top. Firefighters move the car using the computer, live video with YOLO detection is shown, and the Raspberry Pi collects physical data like temperature and humidity using the DHT11 Sensor. Third, we trained an ANN to predict fire risk based on the data from the RPi to enable early prevention of fires. We used National Weather Services and 700 cities as input and developed our ANN into a working Streamlit App. Lastly, we trained a handshape classifier for victims unable to yell for help but able to use some American Sign Language to sign for help. Our vision is a Freenove Smart Car fleet following a team of firefighters to carry supplies, enhance communication, ensure early detection and treatment of injuries, and ultimately stop destruction of our Earth to achieve environmental sustainability.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
Large Language Models have made significant contributions to a significant portion of machine intelligence. Yet, there consists of such text inputs for language models- including changes that may seem insignificant to a human- that could easily cause misinterpretations and confusion for the model and interfere with the accuracy of its outputs. We can refer to these transformations in text as “obfuscation”. With the digital landscape continuing to evolve, detecting abusive text proves to be a critical challenge in mitigating the spread of encoded (or obfuscated) malicious text online, especially in multilingual cases. In this experiment, we conduct a comparative analysis between using a multilingual BERT model by itself to detect multilingual obfuscated abusive text and adopting vision transformers for the same range of text inputs. We augment the vision transformer model and compare it to the mBERT model to test its effect on key metrics and to create a more efficient model. During preprocessing, we obfuscate the test data to simulate real world noise, while using training data in its original form. We evaluated both models by running 10 mBERT epochs and 20 ViT epochs with NLP metrics including validation loss, training loss, and validation accuracy. The mBERT model achieved an accuracy of only 62% while tested on the obfuscated data. On the other hand, incorporating ViTs resulted in a significant increase to 99% in the validation accuracy. This research can significantly contribute to the refinement and development of advanced content moderation tools on social media and game platforms online.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
Accurate modeling of tumor growth and therapeutic response is essential for optimizing cancer treatment strategies. This study developed a computational model employing logistic growth equations to describe untreated tumor dynamics, with extensions incorporating decay functions to simulate chemotherapy and radiation effects. Based on the collected data, untreated tumor growth follows a logistic curve with a carrying capacity of approximately 1700–2000 mm³. Chemotherapy induces a shallow sigmoid response, reflecting slowed growth, while radiation therapy leads to a downward trend in tumor size as time advances. Combined chemotherapy and radiation exhibit faster initial growth but achieve a more substantial reduction in tumor volume in later stages. The model’s decay rate during treatment was quantified at 0.02 per interval, corresponding to a 2% reduction in tumor size relative to its current volume. Between treatment intervals, a recovery multiplier of 0.0098 facilitates a 0.98% size increase, while a lingering decay factor of 0.99 proportionally reduces the logistic growth rate over time, capturing long-term suppression effects. Continuous low-dose therapy demonstrated superior efficacy in curbing growth, though it imposes a greater physiological burden compared to spaced high-dose regimens. This model offers a computational framework for visualizing tumor progression and optimizing treatment schedules, enhancing the precision of personalized oncology approaches.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
The objective of this project was to diagnose breast cancer more efficiently with AI models using data from minimally invasive techniques. This included various models that were developed to accurately distinguish between benign and malignant cancer cells.
Custom scores assigned to models , were a weighted mean of accuracy, precision, and recall. I assigned recall a high weightage because it measures the model’s ability to predict whether you have cancer, given that you do in reality. Recall is vital due to cancer’s high fatality rate. The best model was a Support Vector Machine with principal component analysis (n_components=9). A custom range for n_components was determined based on the scree plot and accumulated explained variance. Hyperparameters were optimized through cross validation, and I was cautious to avoid overfitting in my model. The aforementioned model used a linear kernel, and regularization parameter of 0.1. The coefficients of this linear kernel were analyzed to inspect feature importance. This model is practical due to it solely using data obtained via fine needle aspiration (FNA). The most common biopsy is a core needle biopsy, which is more painful than FNA and requires anesthesia to be performed (FNA doesn't). FNA biopsies can be conveniently done in a regular doctor’s office. This project presents a practical advantage in remote areas due to the simplicity and ease of fine-needle aspiration procedures and could also benefit people as an inexpensive data centric diagnosis, thereby relieving them from financial burden.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
The human experience is shaped by sensory perceptions, particularly visual and auditory stimuli, which play a crucial role in memory formation and retention. The amygdala, a key component of the brain's limbic system, is important in processing emotions and signaling when to remember significant events. This study investigates the correlation between contextual changes in sensory stimuli and perceived significant events during daily experiences. The goal is to automate the processing of sensory data to better understand when memories are formed. Data for this project consisted of various sensory inputs collected from participants navigating different routes. Visual and auditory data were transformed into continuous time-series signals, with shifts detected through computational models. The alignment between detected shifts in visual and auditory signals were closely correlated, with a cosine similarity of 99.979% between the dataset’s mean and standard deviation. These shifts closely matched manually labeled significant events, suggesting that automated detection of sensory shifts can effectively reflect human-perceived contextual changes. This study highlights the potential of using sensory data to improve understanding of memory formation and emotional processing in real-time environments.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
Lung Adenocarcinoma (LUAD) is the most common form of lung cancer, with 40% of all lung cancers being diagnosed as LUAD. As such, research into early diagnosis is vital for improving the overall survival of LUAD. This project aims to develop a method to diagnose LUAD earlier, faster, and cheaper. It uses artificial intelligence to predict LUAD from RNA-seq data of LUAD cells and normal tissue cells. Gene selection with the JS divergence and KL divergence were discussed. Three different AI models (support vector machine, deep neural network, and random forest classifier) were compared. Overall results are promising; all three AI models outputted an area under the receiver operating characteristic curve (AUC) measurement of around 0.99 while used to predict LUAD using RNA-seq gene expression data.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
Bayesian Optimization is a robust methodology for optimizing complex and expensive-to-evaluate functions, widely used in hyperparameter tuning, experimental design, and decision-making. The effectiveness of Bayesian Optimization depends on the appropriate selection of parameters, such as the surrogate model, acquisition function, and constraints, among others. These parameters significantly influence the problem-specific code template required to model and solve the optimization query.
This project introduces a novel Large Language Model (LLM) to streamline the Bayesian Optimization workflow. By inputting a problem statement, our LLM generates values for 10 key parameters essential for defining a Bayesian Optimization task. Beyond parameter generation, the LLM integrates the user’s problem statement into a predefined code template based on the parameters to produce a customized and executable script that accurately models the query.
This dual-functionality system eliminates the need for manual parameter selection and code adaptation, reducing the barrier to entry for non-experts and enhancing efficiency for experienced practitioners. The LLM used two key functionalities: Retrieval Augmented Generation (RAG) for determining code scripts based on parameter selection, and the Tool-Calling Capability of Llama 3.2. By automating parameter selection and code generation, this system empowers users to focus on solving their optimization challenges without being encumbered by technical complexities. This innovation can potentially accelerate research and application in areas where Bayesian Optimization is critical.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
Spinal cord stimulation (SCS) is a prominent neural prostheses technique that uses electrodes to improve patient mobility and reduce chronic pain. Nevertheless, current SCS involves manual localization of electrodes in the dorsal spinal cord—a method that causes imprecise muscle activation. This project develops an automated image-segmentation model that isolates vertebrae in the spine, a prerequisite to more accurate mapping of electrodes in the spine and improved patient outcomes. Data was collected from an online database consisting of 852 spine X-rays, each with seven vertebrae. 70% of the data was used in the training set, 20% in the validation set, and 10% in the testing set. The model followed a symmetrical U-Net architecture to improve feature extraction and localization. Multiple networks (each with different hyperparameters) were trained for 25 epochs during the training phase, with dice loss, cross-entropy, and loss calculated at each epoch. After hyperparameter tuning, the U-Net achieved a final validation cross-entropy of 0.0970, a validation dice loss of 2.2559, and a validation loss of 1.6082. These values indicate the model was able to reasonably segment vertebrae images and would improve with more training time. Using post-processing techniques to streamline the model’s output and remove errors, the U-Net’s segmentation improved even further. In the future, this project could be extended to segment electrodes on the spine to map muscle activation with electrode stimulation—facilitating more accurate forms of SCS that enable patients to attain better mobility after a neural injury.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
According to captialoneshopping.com and shipscience.com, less than 1% of the 380 billion packages delivered in 2024 were delivered to the incorrect address, equating to approximately 2 billion dollars wasted on mis-delivered packages! The goal of this project was to develop a mobile application, coded in Swift, for package deliverers to detect if they are delivering a package to the correct address by taking a picture of the package. Swift is a high-level, general purpose, multi-paradigm, compiled programming language, used to code Apple operating systems (iOS, MacOS, etc.). The application’s flow was as follows. The user opens the app, clicks a button to access the camera screen, and grants permission to the app to access their phone’s camera and location. After taking a picture of the package, the app extracts valid addresses from the text in the image, converts the user’s GPS coordinates to the corresponding street address, and searches the list of valid addresses for this address. If found, the deliverer delivers the package to the correct address. The application was tested with a sample package at four different houses, one with the address on the package and three with addresses other than the one on the package. Succeeding in all the locations, the app showed the package was delivered correctly at the first house and delivered incorrectly at the other three houses. The goal was accomplished. This invention can be improved in multiple ways and needs to be further tested in various conditions to confirm its success.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
This project utilizes NASA's open-access Landsat satellite data to study the impacts of vegetation changes on the Wasatch Front from 2000 to 2020. By analyzing the normalized difference vegetation index (NDVI), the project measures vegetation health and density over time. The NDVI uses the difference between red and near-infrared (NIR) light reflected by vegetation, providing an effective way to track changes in plant growth and coverage. Healthy vegetation reflects more NIR and absorbs more red light, creating a clear indicator of environmental conditions. Using Python, the project processes satellite images month by month over two decades. It identifies the spectral bands associated with red and infrared light in each image and calculates the NDVI for every pixel. The results are then classified into three categories: low vegetation density (red), moderate density (yellow), and high density (green). By compiling this data, the project generates detailed time-series visualizations to highlight trends in vegetation health throughout the region. This analysis not only helps reveal the impacts of climate change on the Wasatch Front but also provides insight into how seasonal patterns and human activity influence vegetation. The 20-year dataset allows for comparisons between earlier Landsat satellites and newer models, which show varying levels of accuracy in vegetation detection. These results can inform climate engineering strategies, conservation efforts, and urban planning, contributing to a better understanding of the relationship between climate change and the environment in one of Utah's most ecologically significant areas.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
The VacciGuard App successfully completed its first round of testing, showing progress toward its main goal: creating a large database that includes all important flu-related information for each county and state across the United States. VacciGuard connects with reliable data from the Centers for Disease Control and Prevention (CDC), giving users up-to-date information on flu trends and patterns.
The app offers a wide range of engaging features, including daily fun facts, weather-based flu alerts, and multiple-choice quizzes to educate users about flu awareness in an interactive way. Users can also choose between trusted flu vaccination providers, such as CVS and Walgreens, empowering them to make personalized and informed healthcare decisions. By combining educational tools with practical options for vaccination, the app fosters flu preparedness while making learning about public health both fun and accessible.
By being available on the Google Play Store, the app reaches a wide audience, so more people can benefit from its features. This project aligns with public health efforts to promote flu preparedness and vaccination, helping reduce the impact of flu on communities.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
Two of the fastest growing industries right now are the game design industry, and the artificial intelligence(AI) industry. AI has seen lots of use by individuals and companies because of it's generative abilities, which help increase the efficiency of work. Game development is a giant industry because of the increase in consumption of video games, which someone has to make. But what if someone didn't need to make a video game? What if the AI did it for you? This is my question in it's most basic form. In this project, I will use the AI to create code, and see how good it is at coding for me. I will rate the complexity of the scripts it creates through a couple of statistics, as well as how many attempts it took and the prompt i gave it.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
Traffic congestion is a major issue in urban transportation, resulting in increased travel time, increased fuel consumption, and increased frustration for drivers. Phantom Traffic Congestion (PTC) occurs when small braking events propagate backward, creating stop-and-go waves. Variable Speed Limit (VSL) systems attempt to mitigate congestion by dynamically adjusting speed limits based on real-time traffic conditions.
We introduce an AI-powered VSL system that uses a Large Language Model (LLM) trained on real-world and simulated traffic data to proactively adjust speed limits and reduce PTC. Using datasets from Utah State traffic records and SUMO (Simulation of Urban Mobility), we trained the model to identify congestion-prone areas and recommend optimal speed adjustments. Unlike traditional VSL systems, our approach predicts congestion before it occurs and dynamically adapts speed limits accordingly. Future work will focus on real-world deployment and further model refinement by incorporating more datasets to increase predictive accuracy and responsiveness to traffic conditions.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
The COVID-19 pandemic showed the need for predictive models to assess mortality risks based on underlying health conditions and demographic factors. This study utilizes machine learning to analyze publicly available datasets from the CDC to predict COVID-19 death rates. The data was cleaned and grouped at a national level based on age, medical conditions, and broader condition categories. Population statistics were integrated to calculate death rates for each group. A linear regression model was developed in Python to predict mortality risk based on key variables. Feature importance analysis determined the most significant predictors of death, and visualizations such as bar charts were generated to compare risk across different demographic groups, and the model’s accuracy was evaluated using statistical metrics. Results indicate strong correlations between certain pre-existing conditions and increased mortality risk, with age being a primary factor. The findings provide valuable insights for public health officials to identify high-risk populations and allocate resources more effectively. Future work includes refining the model with additional factors, such as vaccination status and geographic location, and testing advanced machine learning algorithms for improved prediction accuracy. This study demonstrates the potential of data-driven approaches in public health decision-making and highlights the importance of predictive modeling in managing future pandemics.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
Neck and head immobility is a serious problem that can be caused by neurodegenerative diseases, Dropped Head Syndrome, and traumatic events such as car accidents. The current solution is a rigid brace that supports the head, restricts mobility, and prevents users from performing tasks effectively. In order to address this problem, a mechanical device was created, and it allowed users to move their heads to the necessary location. However, in order to find this location or head movement, this research uses a unique combination of virtual reality and machine learning to predict future head movements based on prior movements of the head and eyes. First, a dataset was created using a virtual reality device, with participants participating in four tests to capture different eye movement patterns. Using this dataset, a Long Short-Term Memory (LSTM) neural network was developed and trained. The model demonstrated high accuracy and a minimal Mean Squared Error (MSE). This meant that the neural network was able to successfully learn how to identify future head movements. This has a large impact on those affected by neck immobility, as they can now use our system of adaptive head movement to increase their neck and head mobility and function more efficiently. Through the data and results from this research, we will be able to positively change the lives of millions around the world who are impacted by neck mobility problems, while at the same time, showing the potential of combining virtual reality and machine learning.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
One of the biggest problems in modern cybersecurity is password re-use. Current password managers attempt to solve that problem, but their reliance on storing passwords can cause additional issues. Storing passwords locally can result in the user's online accounts being compromised when their device is stolen, as well as passwords being lost when the user's device is lost or damaged. Similarly, storing passwords in the cloud can result in passwords being exposed in data breaches, or being inaccessible when cloud infrastructure goes down, or the user does not have internet access. I have created a solution (in the form of a browser extension) which utilizes the SHA-256 hashing algorithm to enable the user to sign in to any of their online accounts using a single password without the risk of that password being exposed in a data breach. In addition, this password can be used for authentication without any additional data stored on the user's device or in the cloud, making this solution more convenient and secure than traditional password managers. This solution also does not depend on any authentication protocols being implemented by the web service beyond a simple password input, allowing it to function as a drop-in replacement for regular password-based authentication, and allowing it to be used alongside additional security features such as two-factor authentication.
COMPUTER SCIENCE & APPLIED COMPUTATIONAL METHODS
An emerging use-case for cryptographic tools that maintain privacy is the need for confidence in voluntary carbon markets that utilize carbon credit frameworks to produce financial incentives for the reduction of emissions. Investment in emissions reduction projects depends on both investor confidence in whether a company’s shares result in tangible emissions reductions, as well as the credibility of the verification process for carbon credits via third party standards to avoid fraudulent credits and double counting. Such a standard of disclosure is heavily reliant on trust and transparency, which reveals a large barrier to entry for many companies to enter the carbon market—that proving emissions compliance often requires exposing sensitive operational data. The use of zero-knowledge proofs provides a computational method to generate proofs that a company satisfies an emissions limit without revealing compromising emissions data. This is done through a Zero-Knowledge Succinct Non-Interactive Argument of Knowledge powered by Circom and snarkjs that uses an arithmetic circuit to mathematically prove emissions either meet or don’t meet a compliance threshold without revealing any information about the data. Under a multi-party powers of tau trusted setup ceremony, proofs are generated and verified through the Groth16 protocol and the BN128 elliptic curve, allowing such cryptographic guarantees of emissions compliance to be adopted by existing carbon credit standards and blockchain platforms to mitigate the uncertainties of disclosure when entering the carbon market. This provides a trusted avenue for increased participation and scalability for carbon markets to meet global demands and climate targets.
EARTH & ENVIRONMENTAL SCIENCES
Water Cleanliness has always been a problem especially to the ecosystem and animals. I plan to collect water downstream from two constructed wetlands, Fife and Cornell I, and test for phosphate, nitrates, dissolved oxygen, turbidity, nitrate, and conductivity. Using the Vernier Conductivity Probe, Vernier Dissolved Oxygen, Vernier Turbidity Sensor, Phosphate chemical test, Nitrogen chemical test, and coliform bacteria test to analyze the multiple water samples. Fife will make the water down to Cornell I show less phosphorous, nitrates, and nitrogen but with increased levels of dissolved oxygen, turbidity, and conductivity.
EARTH & ENVIRONMENTAL SCIENCES
Insect repellents are classified as a type of pesticide that repel insects rather than kill them. They have a variety of uses including protecting humans from insect borne diseases and protecting plants from infestations of insects. Alternatives to chemical repellents like peppermint and neem oil are available to the consumer but ultimately both can end up in runoff water leading to lakes or reservoirs potentially causing harm to the wildlife in surrounding areas. The question we asked was, what are the effects of both chemical and natural insect repellents on the heart rate of an aquatic invertebrate? We hypothesised that increasing the concentration and exposure times of chemical repellent will have detrimental effects on the heart rate of Daphnia magna when compared to natural repellents. Both the natural and chemical repellents decreased the heart rates of Daphnia over time. The chemical and neem oil repellents had a greater effect than the peppermint oil.
ELECTRICAL ENGINEERING
This project focuses understanding signal transmission in aqueous salt solutions. Signals of various frequencies were transmitted and received in an aqueous environment. Various ions and ion concentrations are used to determine the effects on the received signal, with distilled water used as a control. Salt solutions were chosen to mimic physiologic environments as this type of technology can have applications in the health care scenarios among other industries. It is hypothesized that there may be specific signal frequencies that show resonance leading to the identification of ions in solution, with a stronger signal correlating to a higher ion concentration. The device features a contactless measurement which is helpful in corrosive environments or preventing contamination. This could be particularly useful for automation, research, and any other fields where real time measurements are critical.
ELECTRICAL ENGINEERING
Considering 90% of athletes sustain some form of athletic injury during their career, it makes sense that 41% of athletic injuries occur in the knee area. Athletes develop tears in their anterior cruciate ligament (ACL) and medial collateral ligament (MCL). This project focuses on the development of our Biomechanical Knee Orthotic System (BKOS) that provides joint stabilization for ACL or MCL tears and prevents knee injuries featuring specialized 3d printed hinges that only let your knee bend a controlled certain amount of degrees to prevent hyperextension. We calculated the recommended distance that the knee could deviate and compared it with how much our knee brace could avert hyperextension using proximity sensors. This with the combination of our pressure sensors that can detect and accurately display the force being exerted on your knee makes our knee brace especially innovative.
ELECTRICAL ENGINEERING
I have a few neodymium magnets that I have put on a fan and I was wondering if I could make that fan more efficient by putting other magnets around it to make it spin more.
ELECTRICAL ENGINEERING
The goal of this project was to create a better alternative to permanent magnet synchronous motors, by enhancing specific characteristics of the synchronous reluctance motor. Specifically, I utilized inductive cores to increase the rotor's initial angular velocity, at which point it would be close enough to the angular velocity of the 4 pole rotating magnetic field for the reluctance effect of the iron cores to take effect. To increase the available torque band for the motor, I utilized an axial flux type layout to increase the magnetic flux interaction. Permanent magnet synchronous motors are flawed, in that they have both major supply chain issues as well as terrible performance at high speeds due to an array of factors. The mining of rare earth metals for production of magnets for these motors is responsible for human rights abuses, and the destruction of habitats and water sources by toxic pollution. For these reasons, it is necessary to develop an alternative than keep up with modern day demands, without relying on rare earth metals.
ELECTRICAL ENGINEERING
Effective repair of electronic appliances is often hindered by the unavailability of circuit schematics, leading to unnecessary waste and environmental harm. This study introduces Appliance X-Ray, an AI-driven approach that extracts schematics from PCB circuit images, much like a medical X-ray helps doctors diagnose patient issues. By making circuit structures visible and interpretable, Appliance X-Ray aims to facilitate repairs and extend the lifespan of electronic devices. The system employs a YOLOv5 convolutional neural network (CNN) to identify circuit components, followed by k-nearest-neighbors regression to predict missing elements based on the inferred circuit function. A graph convolutional network (GCN) then analyzes component relationships to reconstruct the schematic. Human-in-the-loop feedback refines the model’s inferences, improving future iterations. This project experimentally proves the viability of this dual CNN-GCN model in identifying circuit components and inferring connections in a circuit while also creating a scalable circuit schematic graph edges inferencing dataset made from actual and synthetic data for future research and contributing to the research community.
ENERGY: CHEMICAL & PHYSICAL
As the energy sector continues to contribute to carbon emissions through use of fossil fuels, there is a need for competitive, sustainable energy sources. Algal fuel cells have emerged as a promising solution to sustainable energy; however electrical production, scalability, and lifespan remains an issue. Traditionally, single chamber microbial fuel cells (MFCs) rely solely on bacteria consortiums to initiate the oxidation of organic compounds in wastewater for the production of electricity. Unfortunately, not much is known about consortiums and the roles that particular species play in electricity production culminating in suboptimal performance in fuel cells. In order to tackle these issues, this study aims to build a sustainable, highly-productive microbial fuel cell with an algae-yeast co-culture to improve both cell productivity and biomass production. A double chamber algae fuel cell will consist of an anode and cathode separated by a proton exchange membrane. This study will optimize ratios of Chlorella vulgaris and Saccharomyces cerevisiae in a suspended culture at the cathode. While the yeast will play a supportive role boosting algal growth and therefore biomass production via nutrient exchange, the algae will function as an electron acceptor for electrolysis. The anode site uses a combination of wastewater and substrate to catalyze the oxygen reduction reaction at the anode site and produce energy through the decomposition of substrate. We predict this co-culture MFC system will simultaneously be able to efficiently produce electricity and lipid-rich algal biomass. Future research for co-cultures in MFCs include understanding the intricate mechanisms of co-cultures.
ENERGY: CHEMICAL & PHYSICAL
More than half of the world’s population suffers from natural disasters that potentially limit access to electricity during or after the disaster. Climate change has resulted in a 100% increase in natural disasters over the past decade. The purpose of the experiment was to build a small portable wind turbine that could generate enough power to charge a cell phone using wind power. We changed the number and shape of wind turbine blades in a wind tunnel with increasing wind speeds and measured the ability of the wind turbine to produce electricity. The data from this experiment showed that the more wind blades the less electricity it was able to produce at higher wind speeds. An increase in blade number was able to produce more electricity at low wind speeds. The data from this experiment can be used to show how portable wind turbines can produce energy and be used in cases of emergency.
ENERGY: CHEMICAL & PHYSICAL
Entrained flow gasification (EFG) is a process used to convert biomass, such as bio-liquid, into low emission hydrogen gas and carbon monoxide. My research focused mainly on finding the best combination of bio-liquid and plastic oil or water for ideal gasification. This was achieved by combining different amounts of these substances and then measuring the viscosity and surface tension for each. The lower the viscosity of a substance, the easier it is for heat transfer, and therefore combustion, to occur. Surface tension influences the degree to which droplets break apart. The better the breakup, the better the atomization and conversion.
MECHANICAL & MATERIALS ENGINEERING
This project investigates the phenomenon of magnetic levitation-by-rotation that uses rotational spin of magnets to achieve stable suspension in mid-air. The primary objective was to develop a device that consistently demonstrated magnetic levitation. By designing a custom setup
that utilizes a spinning magnet that causes levitation of a free-floating magnet, I was able to test various configurations to identify the most stable and consistent design. This project explores a new physical phenomenon with a wide range of potential applications, including the development of levitating transportation systems.
MECHANICAL & MATERIALS ENGINEERING
Paper is a very important tool in our lives. However, the most efficient/best way (and therefore the most common) is to cut down and process cellulose fibers found in the wood of trees. This is not sustainable. Paper fibers can be recycled, but they become too weak to hold together after 6 cycles, meaning fresh cellulose is added to maintain the strength of paper. However, paper can also be created through processing other plants and plant products. Banana peels are also high in cellulose fibers, and so they can potentially be used as a complete replacement to wood cellulose in the creation of paper products.
In my engineering project, I explored the use of banana peels and cotton to create a paper product. I initially boiled the peels, and created a “slurry” with the peels, cotton, and water, and allowed the paper to dry out in my kitchen oven. If I noticed a sudden improvement in the quality of the paper, after changing an aspect of the process, I would stick with that aspect and keep trying to improve the quality of the end result. I was successful in the end, where the end result behaved very similarly to a piece of “rough” paper, and could be written on.
By using banana peels as an alternative to wood cellulose, it helps to do a few major things. It helps to cut back on our tree use, and also helps to provide people with a job in less fortunate areas
MECHANICAL & MATERIALS ENGINEERING
During emergency responses, rapid assessment and reconnaissance are critical for saving lives. While large drones can carry heavier payloads, smaller, faster drones can navigate hazardous areas significantly more efficiently. My project focuses on an autonomous pathfinding model for small, First Person View (FPV) style drones as a Drone First Responder (DFR) solution, a concept with limited prior research. I began by researching various drone configurations and then built a simple prototype. Next, I developed an algorithm to interpret a live camera feed and used April tags to tune a custom telemetric model since the drone will travel between fixed waypoints without GPS. Next, I'm integrating a proactive detect-and-avoid feature, which rapidly processes the video stream to identify obstacles, adjusting the drone’s path or altitude. If the drone deviates, the telemetry system adapts to guide it back on course. To measure performance, I am refining both pathfinding and object avoidance algorithms in tandem, testing each independently. By testing on specified waypoints and monitoring deviations, I can gather data on flight accuracy to visualize overall efficiencies. This iterative testing framework allows me to continuously improve the model’s speed, reliability, and adaptability. Ultimately, my research confirms the feasibility of deploying small FPV-style drones for DFR missions, enhancing emergency response capabilities.
MECHANICAL & MATERIALS ENGINEERING
Titanium metal has been widely used for orthopedic and dental implants due to its strength and biocompatibility. Under normal conditions, titanium forms a protective oxide layer which protects it from interaction with fluids in the human body. However, under inflammatory conditions, this layer can be broken and the oxide can be released in the human body, leading to adverse health effects such as lymphedema. In this project, we propose to add a single atomic layer of graphene or boron nitride to protect titanium from being oxidized. Our quantum mechanical calculations indicated that graphene has exceptionally strong bonding with titanium, while boron nitride exhibits much weaker bonding with titanium due to the rumpling of the boron nitride layer. Our calculation further shows that the oxygen molecule needs to overcome an extraordinarily high energy barrier in order to penetrate the graphene layer. This strongly supports our hypothesis that a graphene coating can successfully prevent oxidation of the underlying titanium. Further experimental validation of our theoretical modeling results in living animals will be of great interest. If succeeded, this coating can significantly extend the lifespan of titanium implants and eliminate the need for dangerous replacement surgeries, revolutionizing the field of biomedical materials and saving lives.
MECHANICAL & MATERIALS ENGINEERING
Fluorapatite, a calcium phosphate ceramic, has gained significant interest due to its biocompatibility, chemical stability, and potential to promote bone integration. However, its brittleness and sensitivity to processing conditions present challenges in optimizing its mechanical properties. This study examines the effects of sintering temperature (1050°C, 1150°C, and 1250°C) and duration (2, 6, and 10 hours) on fluorapatite ceramics. The sintered pellets were analyzed for mechanical, physical, and chemical characteristics. Shrinkage was calculated by measuring the pellets before and after sintering, while mechanical properties were evaluated using compression testing. Density was determined via the Archimedes method, and phase composition was analyzed through X-ray diffraction. Microstructural changes, including grain size and morphology, were examined using scanning electron microscopy. Results indicate that higher sintering temperatures and longer durations enhance densification by reducing porosity and improving particle bonding, leading to increased hardness and elastic modulus. However, excessive sintering times or temperatures result in grain coarsening, which reduces hardness and increases porosity, though it may enhance fracture toughness through crack deflection mechanisms. These findings provide critical insights into optimizing sintering conditions to balance densification, mechanical performance, and microstructural integrity for potential biomedical applications.
MECHANICAL & MATERIALS ENGINEERING
Common refrigerants in household cooling systems contain hydrofluorocarbons: potent greenhouse gases that leak into the atmosphere upon disposing cooling equipment. A solid-state alternative to these greenhouse gases that stores thermal energy in a solid-solid phase transition could prevent harmful climate effects. 2D perovskites are promising solid-state refrigerant candidates due to low phase transition temperatures and significant changes in enthalpy (ΔHtrans) and entropy (ΔStrans), which support their applicability and efficiency as refrigerants. They contain an n-alkylammonium organic cation layer that undergoes an order-to-disorder phase transition, absorbing and releasing thermal energy upon changes in pressure or temperature. This study shows how blending different molar ratios of halides and organic cations of varying lengths leads to a decrease in phase transition temperature and a variance in ΔHtrans and ΔStrans of Cu- and Mn-based 2D perovskites. I found that a 75:25 molar composition between bromide and chloride (halides) and a 50:50 molar composition between longer and shorter organic cations results in the lowest phase transition temperatures. Through halide and organic cation blending, the transition temperature was fine-tuned over a 30℃ and 21℃ range respectively. Further, I found that a pure chloride and pure longer organic cation composition yields the largest ΔHtrans and ΔStrans. Additionally, I found that blending Cu2+ and Mn2+ has minimal effect on the transition temperature, ΔHtrans, and ΔStrans. This study suggests novel principles for tuning the thermodynamic properties of 2D perovskites through halide, organic cation, and metal cation alloying to develop new materials with maximal efficiency and applicability for solid-state refrigeration.
MECHANICAL & MATERIALS ENGINEERING
Cardiovascular diseases (CVD), a group of disorders of the heart and blood, are the world’s leading cause of death, claiming 17.9 million lives every year. Biomaterials, or materials that can safely be implanted in the body for treatment, are rapidly being recognized as a viable therapeutic for CVD treatment: biomaterial-based stents lower the risk of myocardial infarctions by 40% and implantable biomaterial defibrillators can detect heart attacks with 98% accuracy hours before they occur, potentially saving millions of lives every year. However, research costs and time of development prohibit biomaterial treatment from reaching a global scale. To generate biomaterials in an affordable and efficient manner, this project presents Regenerate: a state-of-the-art algorithm for the synthesis of novel biomaterials for the cardiovascular system. First, three different generative algorithms were tested to find the best-performing material simulator, which was identified to be the Wasserstein GAN. To model stable biomaterials, the Wasserstein GAN’s architecture was improved by employing the MAGNET formation energy calculator, after which the algorithm (Regenerate) successfully produced 300+ stable predicted biomaterials, a feat that may have otherwise taken decades. To prove the viability of Regenerate’s novel materials, the top three material candidates (SiO₂25-BisGMA56-TEGDMA19, TEGDMA50-HEMA50, and UDMA30-TEGDMA70) were successfully synthesized in lab and all three candidates were verified to be more inert than many biomaterials used in cardiovascular applications today through an LC-MS test, experimentally validating Regenerate and its goal to generate revolutionary biomaterials. Regenerate can combat the world’s most pressing medicinal issues by generating novel biomaterials and regenerating global health.
MECHANICAL & MATERIALS ENGINEERING
In the past years, an influx of out-of-state migration has come into SLC. Due to this, there has been a high demand for construction materials used in housing. However, due to the high demand for materials, there has been an increase in the amount of pollution that the city has endured. Specialists at the Utah Physicians for a Healthy Environment estimate that construction material mining is the second-highest polluter in the state. Therefore in order to combat this problem there needs to be an alternative for material for construction. Due to the high abundance of Copper in Utah, Copper Tailings are the most effective solution. However, due to the storage system that these tailings were originally placed in, the pyrite that was contained within the tailings oxidized causing the tailings to be practically unusable. Therefore, in order to ensure the usefulness of the tailings from Kennecott, the pryrite needs to be removed from the tailings. This is what I am doing in my research in order to determine the usability of the tailings.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Despite the common knowledge of dermal fillers utilized solely for cosmetic and aesthetic treatment, certain hyaluronic acid-based dermal fillers contain hydrophilic components, creating a potential novel use. The goal of this experiment is to investigate the hydrating efficacy of dermal fillers on synthetic models with simulated chronic dry skin and atopic dermatitis. Eczematous conditions are replicated by chemically and environmentally disrupting the skin barrier using controlled irritants to simulate barrier dysfunction, a characteristic of eczema. Dermal filler is administered evenly intradermally, and skin hydration levels are quantitatively assessed over increments of time after injection. This experiment demonstrated the potential of dermal fillers to enhance skin moisture retention, highlighting insights into the application beyond cosmetic purposes, and creating a new treatment option for chronic skin dryness and barrier-related conditions
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Age-related macular degeneration (AMD) is a progressive condition characterized by degeneration of the retina and retinal pigment epithelium (RPE), with a particular impact on the macula. This disease accounts for approximately fifty percent of all cases of blindness and visual impairment in developed countries. The RPE, a monolayer of cells critical for maintaining retinal health, is particularly susceptible to oxidative stress due to its high metabolic activity, exposure to light, and the presence of abundant polyunsaturated fatty acids prone to oxidation. Chronic oxidative stress induces senescence in RPE cells, amplifying inflammation and disrupting retinal homeostasis, thereby accelerating the progression of AMD. Further research is essential to elucidate the mechanisms by which oxidative stress contributes to RPE
dysfunction and senescence at the molecular level. In this study, we utilized an in vitro RPE cell culture model to investigate how hydrogen peroxide (H2O2) induces senescence in RPE cells and the role of the small GTPase ARF6 in modulating the outcomes associated with H2O2-
induced senescence.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Cataracts are a common eye condition where the lens becomes cloudy, affecting vision. Detection is crucial for preventing severe vision loss, but current detection methods often require expensive equipment and expert knowledge. This project aims to create an affordable and accessible system for detecting cataracts using a Raspberry Pi and a USB camera. The system captures high-quality images of the eye and processes them to identify signs of cataracts. The camera captures a clear image of the lens, and software analyzes the image to detect abnormalities like cloudiness or light scattering, which are early signs of cataract formation. The software uses a technique called image processing to convert the image into a form that can easily be analyzed for these changes. It highlights areas where light passes through the lens differently due to cataracts. The main goal of the project is to build a simple, low-cost tool that can be used in remote areas or by people without access to expensive eye care facilities. By providing an early diagnosis, the system can help detect cataracts before they worsen, potentially delaying surgery and preserving vision. The system is non-invasive and easy to use, allowing anyone to take a picture of their eye and receive immediate feedback on their eye health. This project demonstrates how technology can make healthcare more accessible and help people maintain good vision for longer.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Whole genome sequencing of microorganisms
By: Oskar Kapitonov
At: Beehive Science and Technology Academy
Whole genome sequencing (WGS) is a powerful tool for understanding microbial genetics, evolution, and potential applications in medicine and biotechnology. This study aimed to sequence and analyze the genome of a selected microorganism to identify key genetic markers, antimicrobial resistance genes, and potential biotechnological applications. Genomic DNA was extracted from a cultured non pathogenic microorganism and assessed for quality and purity. Library preparation was performed using the Quanta Bio Spark Q, followed by high-throughput sequencing using the Illumina Nova Seq-X. Geneious bioinformatics tool was used for genome assembly, annotation, and comparative analysis. The study focused on identifying functional genes, mutations, and potential adaptations. Comparative genomic analysis revealed key similarities and differences with closely related species, providing insights into evolutionary relationships.This research successfully sequenced and analyzed the genome of a microorganism, demonstrating the potential of WGS for microbial characterization. The findings contribute to understanding microbial genetics and may have applications in biotechnology, Medicine, and antibiotic resistance research.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
This project involves designing and printing a primitive cell chip using UV reactive resin, molding agents, small glass pieces, and plasma bonding. It also involves cell culturing PASMC using cell media, a cell culture hood, an incubator, a centrifuge and trypsin. After this, cells were pipetted into the chips and monitored closely for formation and growth direction. After this, half of the chips with cells were attached to flow systems, and half were not. After, cells were monitored again, observing for the previously mentioned conditions. Data was taken throughout and cells were observed through a microscope. This experiment clearly showed the effects of flow on the cells. If continued, the next step would be gene sequencing to identify certain cell markers.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
This project aims to assess the ability of Artificial Intelligence to count U937 cells with object detection, as well as provide modern techniques with increased throughput, accuracy, and efficiency. Matched to manual counting, the model performed with a 12% error, compared to a 457% error with previous tools, increasing accuracy from tools before significantly. These findings are relevant for future research on developing more accurate and precise models, as well as providing more training for the model.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Vira Regen Inc., an early-stage biotech startup pioneering novel, non-invasive medical devices and gene therapies via gene-specific electric stimulation modalities. They specialize in targeted modulation of gene expression that leads to desired physiological outcome. Currently they have established this proof of concept in bone regeneration, primarily in bone fracture healing.
Studies done by Vira Regen have shown an increase in osteoprotegerin (OPG) (a gene that regulates bone growth) mRNA expression after electric stimulation. Post-transcriptionally mRNA is regulated at multiple levels that can affect protein production. An increase in mRNA does not necessarily correlate with protein synthesis, therefore this project aims to confirm this gene expression at the level of protein synthesis.
Murine Preosteoblasts were electrically stimulated at key frequencies. Post-stimulation, the supernatant was harvested from the stimulation plates and prepared for enzyme linked immunosorbent assay (ELISA) from which the protein concentration and gene expression was collected and analyzed.
There was an increase in OPG protein production after stimulation for the most part. 90kHz showed the highest increase of OPG protein production, a 3 fold increase in protein concentration from the controls, whereas 50kHz showed a 0.5 fold decrease.
Comparing the results of this study to that of the gene expression study, we see there is an increased production of OPG with increase in frequency up to about 100kHz mostly supporting the hypothesis that there is a correlation between mRNA production and protein production.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
The significance of using multiple drugs (Azeliragon with Venetoclax or Azacytidine) in combination to obtain a synergistic effect on acute myeloid leukemia was studied. The goal was to see whether they worked well with each other and it was worth it to use smaller concentrations of both on a patient or to use one drug with a higher concentration. To do so, we used eight 96-well plates to contain all of the concentrations used for the experiment, each increment being a half of the last, and the first concentration being the concentration required to kill 50% of a population of cells. They were incubated and measured using a molecule that helps determine whether the cell is alive or dead, and measured over four hours. The results showed there was not very much synergy between the drugs, but retrials have been made showing otherwise.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Dravet syndrome is a rare epileptic disorder that is diagnosed in infancy. It causes developmental delays, and early research shows some connections between Dravet syndrome and intermittent explosive disorder as well as autism. SUDEP (Sudden Unexpected Death In Epilepsy) affects 20% of patients with this disorder, and the causes of it are still unknown. This project aims to test the hypothesis that SUDEP may be caused by severe inflammation in the brain and other organs in the body. We tested this by measuring the amounts of interleukin-6 (IL-6), a pro-inflammatory protein that causes swelling. Using tissue samples of laboratory mice that had been genetically engineered to exhibit Dravet Syndrome, we compared them to healthy mice tissue samples. We tested plasma, lung, forebrain, and brain stem samples and found no significant difference in IL-6 levels between the two mice samples in the plasma, lung, and brain stem. However, we found elevated levels of IL-6 in the forebrain tissue of the Dravet syndrome mice compared to the healthy mice tissue.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Electromyographic (EMG) control of prostheses relies on supervised learning algorithms that map EMG signals to motor intent. Traditional EMG training data is collected while participants mimic predetermined movements of a virtual hand with their own hand. This assumes participants are perfectly synchronized with the predetermined movements, which is unlikely due to reaction time and signal-processing delays. Previous research has used cross-correlation to globally shift EMG and kinematic data for better alignment. We evaluate both the online and offline performance and intuitiveness of a prosthesis trained on EMG using global re-alignment. We also introduce a trial-by-trial re-alignment method that individually aligns kinematics to signals, providing EMG and movement data on a per-movement basis. We trained a joint classification-regression novel on EMG collected from participants with the unaligned kinematics, globally aligned, and aligned using trial-by-trial.To assess these algorithms on proportional control of a prosthesis, we employed a virtual Target Touching Task (TTT) to test the proportional control of controlling a prosthesis. To assess the intuitiveness of control, we used a Detection Response Task (DRT) in a dual-task paradigm with the primary TTT. The DRT is used as a secondary task in a dual-task paradigm as an objective measure of cognitive load. Subjective cognitive load was assessed using the NASA TLX survey after each task. Our results showed that trial-by-trial re-alignment significantly reduced cognitive load, along with significantly improving online and offline performance. These findings suggest that trial-by-trial re-alignment should be implemented in future EMG-controlled prosthetic systems to improve performance and intuitiveness.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Cardiovascular complications from surgery remain a leading cause of mortality, with a 30-day mortality rate exceeding 2.3%. Millions of patients worldwide, however, require the use of implanted medical devices (IMDs) to treat chronic illnesses, such as pacemakers or defibrillators (treating nearly 4 million Americans currently). These devices are battery-powered, often requiring invasive surgeries to recharge or replace, introducing extensive patient discomfort, risk of infection, and potential heart complications. This makes the non-invasive recharging of these devices a critical forefront of research for long-term patient health.
This project utilizes wireless power transfer (WPT) for IMDs, specifically through inductive coupling principles and highly efficient Litz wire coils, to test the wireless recharging of implanted batteries. A human body model was constructed and used to simulate real-world conditions, measuring factors such as power transfer efficiency, voltage requirements, skin temperature increase, and overall safety of use to determine biocompatibility. This project also explores On-Off Keying (OOK) modulation, allowing for data retrieval from implanted sensors (allowing for the measuring of predictive metrics such as blood pressure, oxygen saturation, pH levels, etc.) through binary encoded data. This modulation is contained within the powering system and requires no extra materials or space within the patient.
Overall, this project was able to thoroughly develop a wireless power system eliminating the need for invasive battery replacements. Simultaneously, the developed system allows for OOK modulation, retrieving binary encoded data from implanted sensors contained within the body.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Cancer is a leading cause of death around the world, and over 88% of these cancers have solid tumors. With the precision of monoclonal antibodies and the toxicity of cytotoxic payloads, an antibody-payload conjugate could be developed to create a treatment for cancerous tumors. This was done by modifying the monoclonal antibody by attaching the cytotoxic payload via a chemical linker. Afterward, the modification, referred to as an antibody-payload conjugate, was purified and then run through an electrophoresis gel. Then, two fluorescent assays were performed to determine the payload's stability and how much of the payload was being released in both tumor microenvironment and physiological conditions. All of this would help to determine if the antibody-payload conjugate could be developed further as a treatment for cancerous tumors, as the monoclonal antibody would provide precision in responding to the tumor microenvironment and the payload would add the toxin to help kill the tumor.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
This analytical project looks at the idea of engineering human heart cells, known as cardiomyocytes, to perform photosynthesis as a potential solution for the energy loss that occurs in ischemic heart disease. Ischemic heart disease happens when the heart doesn’t get enough oxygen and nutrients, and it remains one of the top causes of death worldwide. Current treatments don't directly address the energy loss in the damaged cells. The goal of this project is to model how genetically modified cardiomyocytes could produce energy (ATP) through photosynthesis using light, even when oxygen is low. This process, inspired by cyanobacteria, could help these cells survive, reduce stress, and repair damaged heart tissue.
The main idea behind this project is that genetically engineered cardiomyocytes with photosynthetic genes will be able to create ATP using light, which might help regenerate tissue in the heart. Instead of doing experiments, the project will use computational models and data from existing cell lines to simulate how this photosynthetic energy could affect the cells’ functions, regeneration, and metabolism under conditions where the heart isn't getting enough oxygen. This is an analytical study that aims to provide insights into how photosynthesis could be used for heart disease treatment, without any hands-on biological testing.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Cardiovascular simulations are an efficient, personalized, and non-invasive tool in diagnosing various heart diseases, and the open-source application SimVascular is a popular simulation tool for the research community. It allows users to construct digital 3D models of arteries from CT scans, and simulates the blood flow of every vessel region. The results are useful for diagnostic and research purposes.
SimVascular provides several methods of segmentation (the process of defining the boundaries of the artery, resulting in a skeletal “rough draft” of the 3D model). Manually segmenting a model takes around a day to complete, so auto-segmentation features were implemented within SimVascular. However, they do not have sufficient accuracy when modeling pulmonary arteries, because of low CT scan resolution and occluded images.
Due to the unusual features of pulmonary artery scans, an auto-segmentation program couldn’t succeed when trained on a wide range of vasculature. Therefore, I hypothesized that coding a convolutional neural network specialized for pulmonary arteries would advance the state-of-the-art. Real CT scans were gathered with corresponding reliable segmentations from the Vascular Model Repository to form the training data. My program advances the accuracy of automated segmentation for pulmonary arteries, and can be applied to different types of vasculature. The pulmonary artery carries blood to the lungs, and while artery stenosis is treatable, complications after placing catheters can be life-threatening. Automatic segmentation features may reduce treatment costs for a future clinical use of SimVascular. They further enable large-scale modeling experiments, and accelerate the process of discovering new symptoms for diseases.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
ADHD is a developmental disorder caused by an imbalance of neurotransmitters in the brain and weaker function in the prefrontal cortex, which regulates attention and control. Currently treatment involves stimulant medications, which increase the production of dopamine (DA) and norepinephrine (NE) chemicals to facilitate the proper function of the prefrontal cortex. However, due to the nature of these medications as a stimulant, concerns have been raised that ADHD medication may serve as gateway drugs for youths and enable them to consume harder drugs and develop addictive disorders. Substance abuse disorders occur due to the reward pathways of the brain; the brain releases dopamine as a reward to encourage completion of survival tasks. Drugs confuse this reward system by releasing quick and intense bursts of dopamine, enabling people to consume greater dosages in order to receive more dopamine. The difference between ADHD stimulant medications, including amphetamine and methylphenidate, is that they release neurotransmitters at a slower rate than illicit drugs such as cocaine, reducing risk of abuse. The hypothesis of this research project was that ADHD medications when taken in prescribed dosages will not lead to a higher probability of substance abuse in patients. Research was conducted by comparing the speed of DA and NE release from amphetamine and methylphenidate drugs versus FDA-prohibited drugs such as methamphetamine and cocaine and resulting behavior. By additionally examining statistics of people who had developed substance abuse in ADHD and non-ADHD populations, it was found that people with ADHD actually had a reduced risk of substance abuse.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
The mitochondrial pyruvate carrier 1 is a critical protein enabling ATP production by transporting pyruvate into the mitochondria for the Krebs cycle. This study investigated the effects of MPC1 deficiency on the mortality rates of Drosophila under high-salt dietary conditions. Flies with different genotypes (wild-type control, heterozygous mutants, and homozygous mutants) were subject to normal and elevated salt diets. Results showed that salt stress increased mortality in all groups to varying degrees. While the control genotypes (wild type, 33 over wild type, and 34 over wild type) exhibited no significant changes in mortality, the homozygous mutant (33/33) experienced a 44% mortality rate increase under high-salt conditions. The heterozygous mutant (33/34) displayed no significant mortality increase but had lower initial mortality than controls on normal salt diets. The second homozygous mutant (34/34) was lethal during larval development. These findings highlight the role of MPC1 in maintaining homeostasis under salt stress.
This study exhibits the connection between metabolic pathways and environmental stress, particularly with rising salt levels in diets worldwide. The findings have broader implications for understanding mitochondrial dysfunction and its relevance to human health. Future research will explore tissue-specific MPC1 expression, improved techniques for generating mutants, larger sample sizes, extended observation periods, and transgenic fly models to study human-related mutations. These improvements aim to investigate strategies for mitigating the effects of salt stress, potentially to develop genetic approaches to address related human health problems.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
The consumption of energy drinks poses health risks for young people, among which are anxiety, an excessive intake of sugar and caffeine, twitching, and in the worst case, seizures. It has also been shown that when youth consume energy drinks, they are more likely to engage in risky behavior with drugs and alcohol (Ruiz and Scherr, 2018). The purpose of this experiment is to understand how different energy drinks affect how long it takes fruit flies to climb up a 6cm vial. We hypothesized that the more caffeine content the energy drink has, the faster the flies are going to climb up the 6cm mark. Fruit flies were exposed to different levels of caffeine content for 24 hours, after which the time it took 3 flies to pass the 6cm line was recorded. We observed that the flies that were fed higher caffeine content energy drinks were able to climb the 6cm vial wall the fastest. The data from this experiment suggests that caffeine content in energy drinks should be more highly regulated.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Osteoarthritis (OA), a degenerative joint disease, affects articular cartilage in weight-bearing joints such as the knees, leading to pain, disability, and reduced quality of life. Angiotensin receptor blockers (ARBs), particularly losartan, have shown potential protective effects on cartilage volume by inhibiting TGF-β and associated inflammatory pathways. This study retrospectively analyzed data from the Osteoarthritis Initiative (OAI) database to evaluate the relationship between ARB use and knee cartilage volume preservation in patients with OA.
Data from 4,476 patients were analyzed using SAS software. Patient demographics, ARB usage (losartan versus non-losartan groups), and normalized cartilage volume (medial tibia) were assessed at baseline and at 12, 24, 36, and 48 months. Statistical comparisons were performed using ANOVA to determine significant differences between groups.
Results revealed a progressive decline in cartilage volume over time for both ARB and non-ARB groups, with ARB users demonstrating a slower rate of loss. Although differences were not statistically significant, trends suggested losartan's potential to mitigate cartilage volume reduction. The study highlights the need for further research to confirm these findings and explore the mechanisms of ARB-mediated cartilage preservation.
These findings suggest ARBs could provide therapeutic benefits beyond hypertension management by reducing cartilage degeneration in OA. Future investigations should assess risk factors, long-term effects, and optimal ARB dosing in OA treatment protocols.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
The core experimental plan remains the same as before: it includes setting up a well defined obstacle course of cardboard obstacles of different shape and size as well as a conventional visual acuity test that is carried out by student volunteers in my school using my VR headset and I gather data about their performance in carrying our various tasks such as walking the obstacle course and counting the time for completion and number of collisions as well as the ability to read increasingly smaller font on the visual acuity test board. Using my own software, I adjust e.g. resolution, outline pixel count, etc. and record the performance for each configuration that would simulate forms of blindness or anticipated forms of perception of light flashes (phosphenes) they would perceive with a visual neural implant that could provide useful guidance for a blind person. The phosphenes will be concentrated in areas that the participant is looking at to as to simulate the focusing of the eye.
The process with the volunteers follows a similar pattern as last year:
a) Explain the project to all participants
b) Provide, explain and have signed relevant waiver forms
c) Demonstrate the use and function of the VR headset and inform participants of risks
d) Have each participant do reading tests from an eye chart while using the VR headset
e) Having each participant walk an obstacle course while using the VR headset. The participant will have at least one helper close by to help if they stumble.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Mutations in TP53, a key tumor suppressor gene, are present in over 50% of human cancers, leading to impaired apoptosis and uncontrolled proliferation. Li-Fraumeni Syndrome (LFS) is a hereditary cancer predisposition disorder caused by germline TP53 mutations, resulting in a high lifetime cancer risk and aggressive malignancies that don’t have targeted therapeutic options or any other cure with lesser sider effects even . Lipid nanoparticles (LNPs) offer a promising gene delivery system for restoring TP53 function, reactivating apoptotic pathways in TP53-deficient malignancies. This study evaluates the impact of TP53-loaded LNPs on U2OS WT (osteosarcoma) and NHDF (normal human dermal fibroblast) cells, focusing on seeding density optimization, dose-dependent cytotoxicity, and apoptotic pathway activation.
Cells were plated at 5K, 10K, 15K, and 20K cells per well to determine optimal growth kinetics, confluency, and treatment response consistency. Following optimization, cells were treated with TP53-loaded LNPs, mCherry LNPs (fluorescent control), and EP53 LNPs at varying concentrations. CellTiter-Glo assays assessed metabolic viability, while LDH release assays quantified membrane integrity to measure cytotoxicity. Additionally, Annexin V/Propidium Iodide staining and Caspase-3/7 activity assays were performed to confirm apoptosis as the primary mechanism of cell death. Time-dependent effects were analyzed at 24, 48, and 72 hours.
Results demonstrated preferential apoptosis in U2OS WT cells, confirming that LNP-mediated TP53 restoration selectively induces cytotoxicity in malignant cells while sparing normal fibroblasts. Additionally, seeding density significantly influenced drug response, underscoring the importance of controlled plating conditions for robust LNP efficacy assessments. This study establishes a novel approach to TP53 restoration, highlighting LNP-based gene therapy as a precision-driven treatment for TP53-deficient cancers, including LFS-associated malignancies.
MEDICINE, HEALTH SCIENCES, & BIOMEDICAL ENGINEERING
Nicotinamide Adenine Dinucleotide (NAD+) plays a pivotal role in cellular metabolism and energy production, with its decline being a hallmark of aging and neurodegenerative diseases such as Alzheimer’s Disease. Studies suggest that increasing NAD+ levels can help mitigate age-related conditions. Small molecule precursors of NAD+, such as Nicotinamide Riboside (NR) and Nicotinamide Mononucleotide (NMN), are known to be easily absorbed by cells, however, their gastrointestinal (GI) absorption and oral bioavailability remains a significant challenge. This project virtually screened large chemical libraries of compounds structurally similar to NAD+ precursors, and therefore identified potential candidates that have better GI absorption, better bioavailability, and have higher lipophilicity. SwissADME and PubChem were used to optimize the pharmacokinetics and pharmacodynamics of these NAD+ analogs and precursors, potentially offering novel therapeutic options for treating Alzheimer’s Disease
PHYSICS, ASTRONOMY & MATH
Songbirds, such as, warblers and American Robins, sing to establish territory and attract mates. The acoustics of songbirds provide a unique lens to study the dynamic relationships and processes that occur between various components of the Earth system. Their songs reflect changes in the habitat health (biosphere), climate-driven migration shifts (atmosphere), water availability (hydrosphere), land-use changes (geosphere), and human impacts (anthroposphere). The bird songs, as small-scale biological indicators, can reveal large-scale planetary processes between Earth’s interconnected systems.
American Robins are versatile generalists, foraging in urban areas, forests and grasslands, while warblers are habitat specialists, suited for life in dense forests as insectivores. While the American Robin songs are simpler, repetitive and melodious, those of warblers are complex, rapid, and varied. The species-specific songs help warblers to communicate and compete in crowded acoustic environments. Such complexity makes them challenging to identify. The vocalization differences reflect their distinct ecological niches and communication needs.
The wolves of the sky, Harris’s hawks, are social, cooperative hunters that thrive in open habitats using group tactics to capture prey, while the Cooper’s Hawks are solitary, stealthy hunters adapted to wooded and suburban areas, relying on surprise attacks to catch birds and small mammals. Their hunting strategies and vocal behaviors reflect their distinct ecological niches and social structures.
By employing the digital recordings of avian sounds to induce vibrations in different Chladni metal plates, I hypothesize distinct standing wave patterns will emerge that could help identify challenging species and understand processes that shape animal communication.
PHYSICS, ASTRONOMY & MATH
Cosmic rays are high energy fast particles and protons that break apart on contact with our atmosphere, there is still a lot to learn from them and I hope to help the process of finding new info.
This experiment aimed to determine if there is a relationship between cosmic ray strength and weather concentration.
We hypothesize that increasing the concentration of weather, such as smog, pollution, cloud coverage, etc., will decrease the cosmic ray strength.
Variable (cosmic ray strength) was measured via cosmic ray detectors and analyzed with and without certain weather patterns
So far enough data has not been collected to make heads of the outcome.
The data from this experiment could be used to help understand our cosmos and the connection between our sky and cosmic rays.
PHYSICS, ASTRONOMY & MATH
Fusion energy, the same energy powering our sun, is a promising avenue for sustainable, green energy. It faces two major challenges: high energy usage and fast material degradation. Reactors consume over 60 times more energy than they produce and will become unusable after 5-10 years of full operation. Even though fusion has not been cracked in over 70 years of research, the only validated approach to fusion has been completely ignored: stellar fusion. Stars operate efficiently at much lower temperatures with reactions 170 times more difficult to achieve. This phenomenon is due to density, so understanding how density affects fusion reaction rates quantitatively is paramount to discovering new principles in reactor design. No specific model existed to describe how temperature and fuel density affect fusion reactions. This research analyzed stellar cores to determine the effect of temperature and density on fusion reactions per second per cubic meter. This was achieved by running stellar evolution simulations with the Modules for Experiments in Stellar Astrophysics. These simulations revealed a complex relationship between temperature, density, and reaction rates. Temperature had a cubic-function relationship with reaction rates, and density had a negative impact. However, the interaction between temperature and density positively impacted reaction rates. Because of this interaction, as temperature grew, density gained a greater and greater positive effect on reaction rates. This shows that both temperature and density are impactful factors in fusion and future reactor designs should explore optimizing both fuel density and temperature rather than just one as is current practice.
PLANT SCIENCES
According to a startling report published by Brigham Young University in early 2023, the Great Salt Lake could disappear in five years. Fortunately with the two wet winters of 2023 and 2024, the Great Salt Lake has rebounded somewhat. But it is still far from where it was historically. The Great Salt Lake might not disappear in 5 years, but the environmental concerns still stand. When water recedes from the Great Salt Lake, it exposes contaminants on the bottom of the lake such as arsenic, lead, mercury, copper and other dangerous heavy metals. Winds pick up these pollutants and carry them into cities, causing major health concerns such as respiratory issues, chronic disease, cancer and other health issues. In this research, I propose the use of two Marigold plant species: Tagetes Erecta and Tagetes Patula, known for their phytoextraction characteristic to extract arsenic and heavy metals from the soil around the Great Salt Lake. Six soil samples were collected off the Great Salt Lake Marina in Magna and also around the Antelope Island. Tagetes Erecta and Tagetes Patula were planted into these 6 soil samples. Heavy compost and some potting soil were required to keep some of them alive. Soil samples were sent for testing before and 6 weeks after planting of the Marigolds. Slight reduction in Copper can be seen in the soil. Therefore, Tagetes Erecta and Tagetes Patula can be a viable option to phytoextract arsenic and heavy metals from the soil surrounding the Great Salt Lake.
PLANT SCIENCES
USA is the leading producer of corn in the world. Corn is mostly grown in the Midwest states such as Iowa, Illinois, Indiana, Nebraska, and Minnesota. The "Corn Belt" region stretches from Nebraska to Ohio. Recent heat and drought conditions in Midwest have led to catastrophic yield losses of corn crop in some areas since corn is not a drought resistance crop .My experiment focuses on testing different biodegradable biohydrogels and finding the effective amount of biodegradable biohydrogel to enhance the drought resistance of corn plants to increase corn yields in the areas affected by a drought. In this experiment, biohydrological drought will be simulated in corn plants by not watering the plants for 8 days. Even though the drought conditions last for several months,the drought period in this experiment is set to 8 days due to plants maturity. Three different types of biohydrogels in varying amounts of 2g , 4 g and 6 g are applied to 3 different corn plants samples and one section which is a control group is left without water or biohydrogel . The chlorophyll content, average height of the plant, relative water content of the leaves different samples are determined before and after setting the drought simulation.The results were analyzed to determine the right amount of biohydrogel that will enhance the drought resistance in corn plants.
PLANT SCIENCES
My experiment hopes to determine if inoculating different soil samples with mycorrhizae in addition to different cover crop seeds can replenish the amount of nutrients (potassium, nitrogen, and pH levels) to the soil. This project will have many materials which include of plastic pots, Red Clover seed, Mustard seed, 4 different types of soils, a plant nursery rack with lights, heating pads, scale, and a soil testing kit. I will be conducting a potassium, nitrogen, and pH test on the soil before and after adding mycorrhizae seeds. I will have 32 different pots spread across 4 trays that will all receive the same amount of water, sunlight, and soil. The Mustard Seed will act as a control because it cannot work with mycorrhizae. After the germinated seed's soil has been tested, I will measure the Biomass of the plants to see if there is a different in biomass between the plants inoculated with mycorrhizae compared to the ones without. The crop covers will be tilled back into the soil to do their process of nitrogen fixation and after 4 weeks the soil will be tested for the same nutrients. The results from the testing revealed that the pots inoculated with mycorrhizae and Red Clover seed had less nutrients in the soil because the mycorrhizae were helping transfer the nutrients to the plant to help it grow. In conclusion, the Red Clover cover crops that were inoculated with mycorrhizae grew better because the mycorrhizae were giving nutrients to the plant. However, these nutrients can be added back to the soil after the cover crop completes its process of Nitrogen fixation.
PLANT SCIENCES
This project explores the potential of aloe vera base bioplastic as an eco-friendly alternative to conventional plastic wraps for food storage. Aloe vera is known for its anti-bacterial and and moisture retentive properties. In this project, aloe vera serves as a key ingredient in creating bioplastic wrap to aim at extending the storage life of fruits. To test this, I created a bioplastic using a combination of aloe vera gel, white vinegar, water, glycerin, and tapioca starch which was inspired by multiple online websites. I also created a bioplastic wrap without the aloe vera to test its effectiveness to its full potential. The bioplastic wrap is tested by wrapping fruits like strawberries, apples, and bananas, while the control group will use conventional plastic wraps. Over a month long period, I will monitor spoilage and visual changes in the fruits in order to evaluate the effectiveness of the aloe vera based bioplastic. I believe this experiment will demonstrate the potential of aloe vera bioplastic as a sustainable alternative due to its natural properties that align with food preservation necessities. I wanted to explore a solution that could reduce plastic waste while also improving food storage efficiency.