UC Merced Undergraduate Research Journal

Letter from the URJ editorial team introducing Volume 17, Issue 1, First, Further, Forward: Challenge the Now. The letter includes excerpts from the editorial team: Yu Fang Tseng, Mitchell Bauer, Micah Angela Lardizabal, Kaisy Reynoso, Jose Mondragon, Genesis Iniguez-Espinoza, Analee Munoz Luna, Zachary Gatto, and Susan Varnot

The nopal, or prickly pear cactus, is a common cactus native to Mexico and the American Southwest. This cactus holds great cultural significance to the people of Mexico and is featured on the Mexican flag as an homage to the story of how Tenochtitlan, in today’s Mexico City, became the capital of the Aztec Empire. The Aztecs, one of several indigenous Nahua groups of Central Mexico, have a rich tradition of oral and glyphic history, recorded in documents often referred to as codices. The Florentine Codex, a series of 12 books, meticulously documents the lives of the Nahua people and is written by Nahua authors and Spanish translators. By analyzing the textual and visual representations of the nopal in these books, I seek to understand the many roles that this essential plant played in the lives of the indigenous Nahua prior to and during Spanish colonization. By looking at the nopal’s role as food, medicine, cultural and geographical symbol, and host for the parasitic and prized cochineal, I seek to foster greater understanding of the nopal’s significance to the ancient Nahua people, and how their descendants have carried some of this knowledge into the modern world.

The medium of film has a larger impact on the world than many realize. The messages they project onto audiences have a multitude of consequences. The research begins with an exploration of what makes a film a film and eventually arrives upon its agreed definition. Different genres of film often hold different sets of meaning, and the stories presented have the potential to mirror real-world sentiment in relation to massive world events, such as wars. This research dives into the implications of these films, and how the things they display can change a society. These movies demonstrate the capability of socializing audiences, teaching them learned behavior and stigmas against various groups of people, such as the sexually inexperienced, or individuals within the LGBTQ+ community. In addition to the films themselves, this research takes a look at the actors that promote and work in these movies, deducing whether or not their presence held significant economic returns, and if their influence is truly that powerful. Research found that while actors themselves did not lead to the guaranteed monetary success of a film,there was a correlation between the popularity of the actor and the paycheck they received. The paper also includes an analysis of modern films and the highly tailored fictional worlds they sell to viewers. The research concludes with a synthesis of all these topics, demonstrating the importance of an educated consumer, one that understands the capitalistic enterprise that is the modern film industry.

This literature review provides research that looks at the treatment of depressive symptoms with transcranial magnetic stimulation. Depression affects many people directly by presenting symptoms that can become debilitating. Between 30% and 50% of people with depression encounter resistances to treatment, meaning their symptoms do not show improvement (Shanoket al., 2023). Transcranial magnetic stimulation (TMS) is an alternative treatment for depressionthat shows resistance to traditional medications and therapies. TMS utilizes magnetic fields to affect functions in the brain that can change the way people feel. Some researchers suggest that it could also be more widely used, even if patients are not showing signs of treatment resistance. Advancements in this field are possible, and TMS shows signs of further improving upon itself.

Several studies strongly indicate a connection between the quality of sleep and students' learning abilities and academic success. Thus, understanding the factors that disrupt one’s sleep quality is important. One potent factor that can disrupt sleep is mental health, particularly anxiety. Although anxiety is a natural process that tries to keep a person safe by alerting them to potential dangers, this has a downside by increasing psychological and physiological arousal that can disrupt how well one sleeps. Previous research has found strong correlations between sleep quality and anxiety; however, some people may be more vulnerable than others to the negative association of anxiety and sleep. Notably, those experiencing burnout may be psychologically depleted from their workplaces and have fewer resources to cope with anxious states. Therefore, this study will investigate how anxiety predicts sleep quality (Research Question 1), and how anxiety and burnout both relate to each other in their relationship to affect sleep quality (Research Question 2). Online surveys were completed by non-faculty employees (n = 140) from the University of California, Merced participants. These measures included the Generalized Anxiety Disorder-7 Scale, the Pittsburgh Sleep Quality Index, and the Bergen Burnout Inventory. The results show a significant increase in poorer sleep quality as anxiety levels increased while the impact of burnout on this relationship was not significant enough. However, the results also indicated that a trend of sleep quality decreased as burnout increased, in the population with medium and high anxiety.

This literature review aims to summarize the body of research on convicting and sentencing decision bias with a focus on the jury box. Disparities in the criminal justice system have long been recorded to largely impact individuals of color by influencing convictions, the length of sentencing, and the probability of probation as opposed to time served when compared to White individuals. The increasing volume of incarcerated minorities calls for an understanding of the judicial system to combat the implications. Studies show how Afrocentric features, trustworthiness of faces, and depiction of ethnicity and race can lead to longer sentences by highlighting cognitive shortcomings and the use of methods in the criminal justice system. With the inclusion of interventions, the influence that is shown on both implicit and explicit levels can be found to be harmful and due for advancement. By exploring cognitive and social mechanisms alongside the systematic drives of the criminal justice system, factors and sources of bias are identified to provide a review of the need for improvement on the impartiality and equity of convicting and sentencing decisions.

The widespread use of antibiotics has revolutionized modern medicine, helping to fight against countless bacterial infections, significantly reducing mortality rates, and preventing the further spread of bacterial diseases. However, the overuse and misuse of antibiotics have come with a significant downside: they have allowed bacteria to develop antibiotic resistance, posing a major challenge to public health and the effective treatment of infectious diseases. Antibiotic resistance occurs when bacteria evolve and adapt to withstand the effects of the antibiotics designed to kill them. This phenomenon poses a great threat to global health, complicating the treatment of patients and increasing the risk of severe illnesses, death, and disease spread. Bacteria have evolved to develop antibiotic resistance through various mechanisms, including genetic mutations and the process of horizontal gene transfer. Additionally, other non-genetic factors such as ecological contexts and interspecies interactions, play a crucial role in the evolution and spread of antibiotic-resistant bacteria. The effects of antibiotic resistance worldwide result in prolonged hospital stays, increased healthcare costs, and higher mortality rates. In this review, I explore the phenomenon of antibiotic resistance in bacteria, how it has evolved, and its impact on society, while emphasizing the importance of developing new strategies to combat this growing threat.

In epidemiology, the SIR model is commonly used to describe the population dynamics ofinfectious diseases. It divides the population into three categories: Susceptible, Infected, and Recovered. We consider two approaches to describe its population dynamics. In the Ordinary Differential Equation (ODE) approach, we solve a set of differential equations that describe the rate of change of the fraction of each category. In the Agent-Based Model (ABM), we keep track of the state of each person and its position in a two-dimensional lattice. The ODE model has two model parameters, the infection strength b and the recovery rate k, whereas the ABM has three model parameters describing the diffusion, infection, and recovery rates. Our research aims to compare the two approaches and to establish a relationship between the ODE and ABM parameters. To find the optimal values of the b and k parameters that give matching results to the ABM simulation results, we employ two methods. In the first method, we determine the optimal b and k values by minimizing the differences between the curves generated by the ODE and ABM approaches. In the second method, we use an established relation between the end-state ratio of uninfected people and the contact number b/k. Our results show that these two estimation methods give consistent results and explain the fast-diffusion limit situation.

Hematopoiesis in the bone marrow (BM) produces red blood cells, platelets, or various white blood cells. Common lymphocyte progenitors in the BM can migrate to the thymus to form T lymphocytes, a type of immune cell. In some cases, bone marrow failure (BMF) arises from impairments in hematopoiesis and results in the inability to produce necessary blood cells. California’s Central Valley has a high exposure to pesticides due to agriculture. Past research shows correlations between leukemia and high pesticide exposure, but surprisingly, there has been little published research regarding the direct effects of pesticides on BMF. This study aims to use mouse models to aid our understanding of the molecular effects of two pesticides, abamectin and pyraclostrobin, on hematopoiesis. In previous studies, abamectin led to weight loss while pyraclostrobin led to weight gain. We hypothesize that changes in the BM due to pesticide exposure may result in lower numbers of T lymphocytes. We exposed 8-week-old C57BL/6 mice to pyraclostrobin or abamectin for 14 days via intraperitoneal injections and monitored their health with routine weighing and complete blood cell analysis using a Hemavetcell counter. After 14 days, we collected BM and spleen cells for flow cytometric analysis on a ZE5 Cell Analyzer and the thymus for histology. We expect to see a decrease in T lymphocytesin the periphery and impairments in the thymus structure.

Do Native American students, faculty, and staff at select University of California (UC) campuses feel that their interests are recognized and represented within the UC system? This research analyzes the opportunities and barriers Native Americans face in higher education in the United States. In the United States, Native Americans have the lowest enrollment and graduation rates of all racial and ethnic minority groups that seek out higher education and are the only group to have not experienced a consistent rise in attendance. If the University of California system wants to improve the experience of the Native American demographic at UC campuses, then understanding their experiences is critical.

Joel H. Goodman is a retired assistant professor of architecture at the University of Minnesota who, motivated to bridge the gap between sustainable living and underdeveloped communities, began developing various solar cooker designs. To bring forth Goodman’s vision, we were tasked with designing a solar cooker to be permanently integrated into a building and able to direct variable sun rays towards the cooking surface with its funnel-like shape. The cooker provides a sustainable alternative to traditional cooking methods such as wood and coal burning, which remain prevalent in underdeveloped regions despite their harmful environmental and health impacts. Solar cookers, like other clean cooking technologies, have the potential to significantly reduce greenhouse gas emissions, mitigate deforestation, and improve public health by reducing indoor air pollution. Furthermore, access to clean cooking methods reduces the time and effort required for fuel collection, which can increase societal productivity and lower mortality rates, particularly among women and children. The integration of solar cookers into architectural designs represents a sustainable solution that not only enhances the well-being of communities but also supports global climate change mitigation efforts by reducing reliance on nonrenewable energy sources.

As Large Language Models (LLMs) find increasing use in important fields such as healthcare, finance, and law, ensuring their accuracy and reliability is critical. One significant challenge is the occurrence of “hallucinations,” where these models produce nonsensical or incorrect information. This paper introduces a new framework designed to identify and categorize hallucinations in the outputs of LLMs, particularly in safety-sensitive applications. We present a detailed system that classifies hallucinations into four categories: Factual Errors, Speculative Responses, Logical Fallacies, and Improbable Scenarios. Our methodology employs a scoring system that combines metrics to offer a clearer picture of the model performance. Using the TruthfulQA dataset, and the Falcon 7B model, we analyze different types of hallucinations and their potential to compromise decision making in safety critical domains. By focusing on clarity and accuracy, this framework aims to improve the safety and reliability of LLMs in high stakes situations and sets the stage for more effective validation methods in artificial intelligence.

In November 2022, the world of artificial intelligence, programming, and efficiency changed forever, as OpenAI created the first-ever publicly accessible large language generative chatbot: Generative Pre-trained Transformed (GPT)-3.5 (Open AI, 2022). The bot passed several Advanced Placement course exams, which are tests high school students can take to obtain college credit. It passed graduate-level exams such as the GRE, and even the BAR exam required to become a professional lawyer (Open AI, 2023). With all of GPT’s success, the specific issue with OpenAI’s model, GPT-3.5, is that it cannot access the internet or fetch real-time data (OpenAI, 2022). The challenge we undertook was to use the GPT chatbot to create a stock-prediction trading algorithm, guiding the model to provide a conclusive output, and limiting our influence on the model—outside of errors—as much as possible. From November 2 to November 17 of 2023, we manually compared GPT’s predictions to the actual results of ten stocks within a trading day (6:30 AM PST – 1:00 PM PST). It has been widely concluded in the past that GPT models are unable to make daily stock predictions accurately. Past researchers suggest, “It is too soon to claim AI can beat the stock markets” (Mokhtari, 2021) as they perform better in the long-term, which is why we are testing their short-term and long-term capabilities. From the tests we ran to evaluate GPT’s capabilities, we conclude there is great value in incorporating artificial intelligence into current trading models. However, generative AI models like GPT cannot be solely relied upon for accurate predictions. Models built with AI can help advise full-time stock traders, casual investors, and large trading firms about the effectiveness of AI models in their technical analysis before investing in a stock.

Despite the advances in Artificial Intelligence technology, its application in elderly care still presents many challenges and limitations, particularly compared to human caregivers. This synthesis reviewed empirical articles that examined the role of AI robots in elderly care, focusing on their potential benefits and drawbacks. It revealed that AI robots are not capable of replacing human caregivers due to high costs, technical limitations, and the need for human cooperation. Additionally, the study warns that using AI robots may pose potential safety, privacy, and ethical risks, including data security issues, privacy breaches, and negative effects from the incorrect use of the technologies. This paper argues that AI robots can significantly enhance elderly care by providing consistent support and reducing caregiver burden, yet they cannot replace the essential human elements of caregiving. The findings emphasize the need for ethical and legal standards in the deployment of AI robots in elderly care, to ensure that the quality of life for the elderly is improved with these advanced technologies, rather than diminishes.