Individuals with health conditions and special preferences—especially those of the senior population—often have a hard time cooking and preparing healthy meals for themselves, mainly because of lack of knowledge regarding their specific diet like diabetes and high blood pressure. Personalized nutrition plays a crucial role in promoting a healthier lifestyle and minimizing food waste, making it increasingly important to accurately understand the nutritional composition of foods. Most current individualized nutrition assistants use lookup tables for these values, which are sometimes inconvenient for users with uncommon names of foods. This research project leverages a dataset of 2,395 names of foods with precise macronutrient and vitamin data to train a Machine Learning model. The model predicts numerical nutritional values such as carbohydrates, sugar, and saturated fat, based on the name of the food (given 100g). This project will optimize the performance of the model by using different training methods, including custom Neural Network models and Large Language models, and analyzing their accuracies. By analyzing the names’ semantic meanings, this research will be able to tackle this problem and advance personalized nutrition solutions.

As neurotechnology rapidly advances, the criminal justice system faces unprecedented opportunities and challenges in offender rehabilitation. This research explores how closed-loop brain devices (CBDs) and similar brain-stimulating technologies could transform approaches to reducing offender recidivism (when prisoners return) while simultaneously examining the associated human rights implications. Recognizing the current criminal justice system’s shortfalls in successfully reducing recidivism rates in rehabilitation programs, the study proposes developing implementation criteria for neurotechnologies that simultaneously address behavioral modification and promote fundamental human and neurological rights. Through a hybrid research approach combining quantitative analysis of existing recidivism reduction programs and qualitative investigation of existing and emerging human rights frameworks through ethics, this research seeks to answer a critical question: How can the criminal justice system integrate successful neurorehabilitation technologies while ensuring compliance with established human rights and emerging neurorights principles?

What if you could find out which sunscreen has higher UV protection in 3 seconds using just a $10 sensor? Currently, golden standard sunscreen tests performed on human skin are timely and expensive, and have raised ethical and accuracy concerns. Consequently, scientists are working to perform these tests in labs instead, using equipment like spectrophotometers and artificial skin. These in vitro tests still have their own flaws, and there is no unanimous sunscreen test used globally that scientists have agreed on. Instead, this study aims to focus on a low-cost, fast solution that focuses more on comparing sunscreens relative to one another than finding the true accuracy of one sunscreen—information more helpful for consumers. In a series of tests, UV light is emitted on different percentages of zinc oxide cream, where a low-cost UVM30A sensor detects how much UV penetrates through the cream. The accuracy of the UV sensor will be supported if, as the percent of zinc oxide in the cream increases, the amount of UV detected decreases.

As climate change and climate anxiety worsen, it is increasingly important to view climate change from an angle of progress. The goal of this paper is to discover the quantitative amount of progress the world has made toward stopping and eventually reversing climate change. Climate change poses a major threat not just to the natural environment, but to the livelihoods of every human affected by sea-level rise, extreme weather, and more. Furthermore, millions of people are affected by climate anxiety - the worry of the effects of climate change on the world and humanity. Although existing research shows general trends about climate change, it is necessary to quantify the current amount of progress made to help the world reduce emissions and curb climate change faster. This research will be conducted using descriptive research to observe current and historical climate change data. The study will synthesize existing databases with information on global greenhouse gas emissions, global temperature, global population, climate change projections, and more to statistically describe the progress being made, which will be demonstrated with graphs, progress bars, and other representations. The result of this paper will hopefully motivate the world to take faster action and inspire people with climate anxiety.

Pain is the defining factor in sickle cell disease, an inherited blood disorder caused by a mutation in the hemoglobin gene. The variability of chronic pain in sickle cell disease and the transition from acute to chronic pain is not well understood. Research on the prevalence of the neuropathic component of chronic pain, which is pain initiated by dysfunction of the peripheral or central nervous system, will allow for a more complete understanding of the effect of the neuropathic component on the complexity and severity of the pain experience. Furthermore, insights gained from this research will highlight the importance of the inclusion of pharmacological, non-pharmacological, and integrative therapeutic interventions in pain management of sickle cell disease and utilization of the biopsychosocial approach, which recognizes that biologic, neuropsychosocial, and socio-environmental elements play a key role in pain-related processes. This study will be descriptive, and systematically assess and identify the neuropathic component of pain in adults with sickle cell disease through administration of the painDETECT questionnaire (Freyhagen, 2006) in an outpatient setting. Information gained from this research will allow for a more individualized approach to pain management and the enhancement of patient centered care in sickle cell disease.

South Africa is grappling with a severe housing crisis, deeply rooted in apartheid-era policies, rapid urbanization, and persistent poverty. These historical, economic, and social challenges have created significant barriers to affordable and sustainable living for a large portion of the population. This research project investigates how sustainable architectural methods can alleviate the cost of living and enhance housing conditions for impoverished communities in South Africa. By analyzing existing housing models and comparing sustainable and traditional systems, the study incorporates expert insights from a local South African architect to identify cost-saving and sustainable solutions. Preliminary findings indicate that utilizing sustainable materials and innovative remodeling approaches, such as the AAT model, can significantly reduce maintenance costs and improve living standards. However, the research also highlights critical obstacles, including limited government funding and a shortage of skilled labor, which impede the widespread adoption of these sustainable practices. The study proposes a comprehensive pathway to address South Africa’s housing crisis through sustainable architecture, aiming to reduce economic inequality and improve living conditions. By bridging historical injustices with modern sustainable solutions, this research offers a viable strategy to mitigate the housing shortage and foster more resilient and equitable communities.

Can fixing up an old gas car be the key to a cleaner, fairer future for first-time drivers? While EVs are celebrated for their low emissions during use, their production imposes significant environmental and social costs, including lithium mining that depletes water supplies, harms ecosystems, and disproportionately impacts vulnerable communities. At the same time, older gas cars are often prematurely scrapped, wasting resources that could be salvaged through repair and reuse. This study combines historical research on vehicle recycling trends and correlational analysis of emissions data to compare the sustainability of EV production with the repair of older gas cars. Using emissions statistics, data on first-time drivers, and recycling efficiencies, the research employs coding techniques to identify key trade-offs, supported by visual aids like emissions graphs. By challenging the assumption that "new" is always better, this research will reveal how repairing older cars can reduce waste, lower emissions, and promote equity—offering first-time drivers a practical, affordable, and sustainable alternative.

There are many real-world situations that can be mathematically modeled to find an optimal solution. Whether it be in managing resources, maximizing profits, or minimizing travel distances, we have all, in many unique ways, used the process of optimization. With this vast importance, it seems rather obvious that effort should be made to create the most efficient and strong approaches to these decision problems. Boolean satisfiability (SAT) is the most basic language of computation and logic and can be used in unique ways to potentially address optimization problems. The aim of the research is to uncover a specific instance in which the solution to an optimization problem can be better addressed through satisfiability.

My project aims to help improve aerodynamic efficiency for electric cars. Following up on existing research and integrating aerodynamic efficiency with high downforce using design changes as well as working upon the half car body. The final goal is to end up with a electric car design that has low drag and high downforce both which are important factors for high performance road cars. Using computational fluid dynamic (software) to analyze the performance of my final design to evaluate the parameters such as drag and downforce, which will help me create a better design. My research question is How can the aerodynamic design of electric vehicles be optimized to reduce drag at high speeds while maintaining acceleration, as evaluated through simulations? The study will help benifit consumers as well as manufacaturers ad the enviroment by helping increasing efficiency, range and speed of electric cars.

Across the vast emptiness of the cosmos, there lay a type of exotic matter so dangerous yet so interesting that if found to be real, would change what we know and understand about matter forever. That is the power of strange matter. Along with a strange name, it comes with interesting properties. To begin with, it is theorized to originate in a theoretical type of neutron star, a quark star. Strange matter is held within that quark star until it explodes, sending strange matter everywhere. They could be flying around our galaxy in numbers greater than the amount of stars in the milky way in sizes ranging from just a single water molecule to the Saturn V rocket. If one piece were to come in contact with Earth, it would transform the entirety of Earth and everything touching it (including us humans) into Strange matter, giving it the infectious property. Earth would become a strange star and all life would cease to exist. Think of it like King Midas from Greek mythology tripping and turning the whole Earth to gold. Except instead of gold it's strange matter. This study aims to clarify the actual implications of discovering of the existence of strange matter and how it would impact our understanding on matter and the universe as a whole.