Architecture

Authors: Mason Davis. Mentors: Mohammad Shekaramiz. Insitution: Utah Valley University. Forest fires are disasters that devastate our local communities here in Utah and communities abroad. Characterized as uncontrolled and unpredictable fires in areas with combustible vegetation, these phenomena cause ecological and economic harm. With global warming driving temperature increases and variability in weather patterns, these fires are becoming more severe and frequent. Calls from local and national leaders for solutions are ever-growing. An important factor in fighting these fires includes early detection and monitoring. With advances in artificial intelligence and computer vision, the accuracy and speed of detection can be greatly improved. In this research, two new deep learning approaches making use of transfer learning are developed and investigated for fire detection. To compare performance further, existing architectures are also deployed for analysis on the fire detection problem, including ResNet-50, Xception, MobileViT, and Support Vector Machine. To train and evaluate the performance of the above models, the popular forest fire dataset known as DeepFire was utilized. This dataset consists of a symmetrical split of fire and no-fire images consisting of 1900 total images in varying forest environments. Each architecture was tuned through hyperparameter searches and trails to seek ideal combinations for optimal performance. A comparison was drawn with the most recent literature making use of this dataset. Here, our modified Xception architecture leveraging transfer learning topped all recent publications on the DeepFire dataset by achieving 99.211% accuracy. With wildfires increasing in frequency and severity, the early detection of these disasters is paramount to controlling their spread. We have seen that deep learning can provide an increasingly accurate way to autonomously survey and detect these disasters. This is a promising step toward autonomous detection and early elimination of these disasters as they start. Future work will include the investigation of real-time processing techniques for fire detection, allowing for real-time data acquisition, inference, and transmission of geo-information to emergency and forest management teams.

Authors: Rachel Krupnek. Mentors: Jie Liu, Sazib Hasan, Vinodh Chellamuthu. Insitution: Utah Tech University. Many groups are interested in potential market indicators because more than 60% of adults in the United States have investments in the stock market. Extreme stock trading volumes can be an important indicator of unusual market events, including those that precede market crashes. Several studies utilized Extreme Value Theory (EVT) and the Generalized Pareto Distribution (GPD) to examine and model the behavior of these extreme volumes. In particular, various estimation techniques are explored within the GPD framework to best fit the stock trading volume data. The goal of this study is to utilize mathematical approaches in economics. Our results have implications in both mathematical and economic fields, providing benefits by enhancing our ability to analyze and prepare for extreme market occurrences.

Authors: Matthew Williams. Mentors: Elena Laricheva. Insitution: Utah Valley University. Protein-ligand docking is a computational method widely used in drug discovery to predict binding affinities of small molecules to target receptors. However, despite its widespread utility, the method has inherent limitations that can lead to false negative and false positive results, affecting its reliability. False positives occur when docking predicts strong binding affinities that experimental evidence does not confirm, while false negatives arise when the method fails to identify potent binders validated in experiments.Various factors contribute to these inaccuracies, including limitations in scoring functions and search algorithms, but a significant issue lies in the neglect of protein dynamics, i.e., receptor flexibility. To address this limitation, flexible docking methods, which partially account for receptor flexibility, have been developed, but they come at a considerable computational cost. In this project, we incorporated molecular dynamics simulations and k-means clustering to improve prediction of binding energies of a series of small molecules to the human dopamine 2 receptor, a crucial therapeutic target for neuropsychiatric disorders.Our findings demonstrate that sampling conformational states through molecular dynamics and clustering, followed by docking to representative clusters, offers a more accurate assessment of binding energies. Remarkably, this enhanced predictive capability is achieved with minimal additional computational expense.

Authors: G. Colton Gardner, J David Symons, Sohom Mookherjee, Michael Judge, Lynasi Gapelu, Sihem Boudina. Mentors: J. David Symons. Insitution: Utah Valley University. The prevalence of cardiovascular disease (CVD) is higher in residents of rural vs. urban communities, and in older vs. younger individuals. Precise mechanisms responsible for CVD are elusive, and the need for new and novel therapeutic interventions is urgent. Autophagy is a conserved process whereby damaged and dysregulated intracellular proteins are identified, tethered, and escorted to the lysosome for degradation and recycling. Emerging evidence indicates that autophagy is important in maintaining endothelial cell (EC) proteostasis and function. For example, my laboratory showed that: (i) autophagy repression specifically in ECs of adult mice produces arterial dysfunction; and (ii) indexes of autophagy are repressed in ECs of older vs. adult mice and humans that display concurrent EC dysfunction. Sequestosome 1 (p62) tethers proteins targeted for degradation and enables their entry into the autophagic pathway. The contribution from EC p62 to arterial function is unknown. To address this, p62 was depleted from ECs of adult male and female mice (KO) using genetic procedures, and results were compared to animals wherein EC p62 is intact (CON). It was hypothesized that depleted p62 would induce arterial dysfunction. The efficacy and specificity of EC p62 depletion was evaluated in both groups by measuring p62 mRNA (qPCR) and protein (immunoblotting) expression in ECs and vascular smooth muscle. At tissue collection: (i) contraction to non-receptor (potassium chloride) and α-1 receptor (phenylephrine) mediated agonists, and relaxation to endothelium-dependent (acetylcholine) and independent (sodium nitroprusside) stimuli, were measured using isometric (mesenteric arteries) and isobaric (cerebral arteries) approaches; and (ii) intravascular signaling pathways (immunoblotting) important to vasorelaxation were assessed in both groups. Our preliminary findings found no significant differences in arterial function between groups. However, our data suggests that another cohort of mice may lead to statistical significance, and this is actively being conducted. While our results indicate EC specific p62 depletion does not impact arterial responsiveness, hypoxia or ischemia might unmask differences. Additionally, even though EC specific p62 depletion was inducible, other proteins with similar roles (e.g., NBR1) might have upregulated in a compensatory manner. All of these are topics for future study and projects are being designed to investigate them. While this study did not provide enough evidence to confirm the original hypothesis, it did provide several new questions that need answers, and this will direct the future research ambitions of this ongoing project.

Authors: Andrew Knowlton, Matt Olson. Mentors: Matt Olson. Insitution: Utah Valley University. Snow melt is one of the most important parts of Utah’s water budget and has an impact on the Great Salt Lake (GSL) ecosystem, which hit a historic low point in 2022. One aspect contributing to water availability is an increase in dust on our snowpack which enhances snow melt and causes less water in the GSL basin. Using satellite imagery, we will calculate the increase in energy (radiative forcing) over the snowpack due to dust on snow. In previous research, I used a coarse satellite product from the Moderate Resolution Imaging Spectroradiometer (MODIS) to locate areas of dust hotspots on snow in the mountains surrounding the GSL. This project will use imagery with higher spatial detail (Landsat 8) using the same algorithm to measure radiative forcing over snow due to dust deposition. I will compare this data to the same algorithm using MODIS data to have a better analysis of dust in the snowpack. After performing this analysis I can better understand how spatial detail and acquisition frequency affect our accuracy at detecting radiative forcing due to dust on snow and how it changes our water budget.

Authors: Jaycob M Russell, Sujeong Hwang, Jake A Harward, Emily R Morden, Danielle T Taylor, Devin H Taylor. Mentors: Danielle Taylor, Devin Taylor. Insitution: Utah Valley University. Fetal alcohol spectrum disorder (FASD) is estimated to cost four billion dollars per year in the United States that has a wide range of symptoms including low birth weight, microcephaly, and neurobehavioral problems (Belhorma et al., 2021). Drosophila melanogaster is a prime model organism to study FASD as they have variation in sensitivity to alcohol, metabolic and functional tolerance, and withdrawal to ethanol. We collected wild-type (WT) fly embryos and raised them in a regular diet or an antioxidant supplemented diet (acai or curcumin) both with or without ethanol exposure during development. Adult 4-8 day old fruit flies were starved for 24 hours before the conditioning paradigm. The different conditions included exposure to different odors in either an agar environment (CS-) or agar with sucrose (CS+) environment. After conditioning flies were starved again for 24 hours before testing. Y-mazes were used to test their learning and memory abilities. We hypothesized that flies reared on ethanol with the supplemented diet of antioxidants will show an increase in learning and memory performance compared to the FASD condition of flies raised in normal food without antioxidant supplementation, as flies raised in antioxidant supplemented diets will have less oxidative stress. Performance indices for Y-maze tests were calculated based on published protocols: [# No. of flies choosing (CS+) - # No. of flies choosing (CS-) ]/ Total # of flies that made a choice (Mohandasan et al., 2020).

Authors: Danielle Keysaw, Michael C Rotter. Mentors: Michael C Rotter. Insitution: Utah Valley University. New botany students are faced with a long list of confusing terminology used within dense textbooks and dichotomous keys. This can be a challenge to learn all the terminology while learning how to identify plants by their various parts which may also be out of date due to the constant change within the field of Botany. The Field Manual of the Utah Valley Flora is written by students for students which results in a more user-friendly resource for learning that is up to date. Students in select botany classes are assigned a specific genus of plants that are found within the vicinity of Utah County (Utah Valley). Students use Utah Valley University’s herbarium, mapping and imaging software, as well as online databases to write descriptions for each species, creating a dichotomous key, and designing range maps. By allowing students to contribute to this field manual, not only will it be easier to read, but it also encourages engaged learning as well as a great opportunity for students to gain experience in technical writing, research methods, and current knowledge of plant terminology and nomenclature. Using the genus Veronica, I demonstrate the process in writing a full treatment for inclusion in the Field Manual of the Utah Valley Flora. First, I looked for details about each species morphology (such as the habit of the plant and the leaves, stems, roots, and flower details). These details allow me to write individual species descriptions for plants in Utah County. Herbarium records are used to describe the habitat and distribution within the greater Utah Valley Region. Next, I used a camera attached to a dissecting microscope to provide pictures of the plants for aid in identification. Lastly, I present a finished and full treatment for the genus Veronica found in Utah Valley. These plants are often considered weeds, but some have medicinal traits used by indigenous peoples as well as serve as habitat for some butterfly and moth species.

Authors: Savanna Greer. Mentors: Zhenyu Jin. Insitution: Utah Tech University. Geographic Information Systems (GIS) play a crucial role in predicting avalanches by enabling the analysis, visualization, and modeling of various spatial data that contribute to understanding avalanche risk. Here's how GIS can assist in predicting avalanches:* Terrain Analysis: GIS allows experts to analyze terrain features such as slope, aspect, elevation, and curvature, which are critical factors in determining avalanche-prone areas. Steep slopes, specific aspects, and changes in elevation are indicative of higher avalanche risk. GIS software can create detailed elevation models and analyze slope angles to identify potential avalanche zones.
* Snowpack Analysis: By integrating data from snow telemetry stations, weather stations, and remote sensing technologies, GIS can help monitor snow depth, density, temperature, and moisture content. These factors are critical in assessing the stability of the snowpack. GIS can create maps showing the distribution of snow depth and snow water equivalent, aiding in the assessment of avalanche risk.
* Historical Data Integration: GIS enables the integration of historical avalanche data and events into mapping systems. Analyzing past avalanche occurrences can help identify patterns, understand triggers, and determine high-risk areas. This data can be used to create predictive models.
* Weather and Climate Data: GIS allows the integration of real-time and historical weather data into avalanche prediction models. Changes in temperature, precipitation, wind speed, and direction greatly impact snow stability and can trigger avalanches. GIS can overlay weather data onto terrain and snowpack information to create comprehensive predictive models.
* Risk Zoning and Modeling: Using the spatial analysis capabilities of GIS, experts can create risk zones and models that categorize areas based on their susceptibility to avalanches. These zones help in urban planning, land-use management, and emergency response planning. GIS can also simulate and model potential avalanche paths, allowing for the visualization of potential avalanche runout zones.
* Decision Support Systems: GIS-based decision support systems provide valuable tools for avalanche forecasters and emergency management personnel. These systems integrate various data sources, allowing for real-time monitoring, risk assessment, and decision-making to mitigate potential avalanche threats.
* Communication and Public Awareness: GIS can be used to create maps and visualizations that communicate avalanche risk to the public, backcountry enthusiasts, and local authorities. This can aid in raising awareness and promoting safety measures in avalanche-prone areas.
By leveraging GIS, avalanche forecasters, researchers, and land management agencies can significantly improve their understanding of avalanche dynamics, develop more accurate predictive models, and take proactive measures to mitigate risks and enhance safety in avalanche-prone areas.

Authors: Vanessa Tuttle. Mentors: Liz McGuire. Insitution: Brigham Young University. Despite significant strides in global gender equality, women remain underrepresented in leadership roles, prompting investigation into public perceptions of women’s leadership. Our research delves into the often-overlooked aspect of female-to-female interactions and their impact on women's self-perception as leaders. We aim to identify the voices that most influence women's beliefs about their leadership abilities, contributing to the broader discourse on gender parity in leadership. Drawing on historical and cross-cultural perspectives, we theorize that women, historically designated as primary caregivers and reproducers of society, play a pivotal role in shaping individuals' beliefs. This designated role may lead women to internalize societal norms that undervalue their leadership capabilities outside the home. We examine the potential impact of empowered female role models on women's confidence in leadership roles. We employ a lab-in-field experiment conducted in Kuala Lumpur, Malaysia, and Arusha and Dar es Salaam, Tanzania. Participants are assigned to groups with varying gender compositions, engaging in a task where success is dependent upon the leader, followed by a post-treatment survey evaluating their experience, leader, and perceptions of female leadership. Through this experiment, we contribute empirical evidence to the ongoing discussion on gender disparities in leadership and challenge existing theories, providing valuable insights into the complex dynamics that contribute to the confidence gap between men and women in leadership roles. Our preliminary findings from our ongoing research may have implications for strategies aimed at fostering gender equality in leadership, encouraging a more nuanced understanding of the factors influencing women as leaders.

Authors: Derek Wolfgramm. Mentors: Kaicee Postler. Insitution: Utah Valley University. Since 2008, Utah Valley University has taught community classes through the Family Life Education curriculum called the "Stronger Families Project". Previous research has demonstrated the importance of evidence-based family life education (FLE) programs in strengthening families (e.g., Myers-Walls et al, 2011). This study investigates the efficacy of the Stronger Families Project (SFP) by employing a pre- and post-test analysis of change for participants enrolled in the program in Spring 2023 and analyzing qualitative satisfaction data.

Authors: Frankie Medina. Mentors: Joy McMurrin. Insitution: Utah Tech University. My research looks at the multifaceted extent of the lived experiences of Mexican-American women through the eyes of Chicana feminist's scholarships and social media content. The first research question considers the insights presented by Chicana feminists’ scholarship to delve into complex experiences. This will highlight their struggles, identities, and achievements. I aim to root around the fundamental theories and narratives that support the study of Mexican-American women.Second, I will examine the everyday experiences of Mexican-American women, and how it aligns with and/or deviates from the scholarship mentioned above. Through secondary research, I will examine common themes in the scholarship and compare them with the everyday experiences that I previously identified.Thirdly, I will research how contemporary Chicanas interact in formal and informal actions of protest that go against traditional norms and patriarchal systems. My research will focus on the gap between scholarly discourse and activism in real-life norms. I seek to present the different ways in which Mexican-American women delve into their own resilience and resistance in challenging existing obstacles. This qualitative research has three phases: first I will identify and synthesize common themes in Chicana feminist scholarship; second, I will code social media content, using both a priori and in vivo coding methods; third, I will write a thematic analysis of the contemporary Chicana experience. By reviewing these sources and data, I will provide an understanding of the experiences of Mexican-American women, their morale with scholarly discourse, and their roles in continued socio-cultural and political activities. The outcomes of this research hope to have regard for the complications around the Mexican-American female experience and their continuing efforts to challenge and change traditional norms and patriarchy

Authors: Reagan Bartholomew. Mentors: Dylan Hansen. Insitution: Utah Valley University. Unveiling the Challenges Faced by Deaf and Disabled Undocumented ImmigrantsThis paper shows the overlooked challenges confronted by a particularly vulnerable group—deaf and disabled undocumented immigrants. The motivation behind this study comes from the need to address the unique hardships experienced by this marginalized population. Our research employs a mixed-methods approach, combining participant observation, policy analysis and comparative analysis. Comprehensively exploring their experiences and shed light on their daily struggles.Our finding show that access to language resources is not just a matter of practicality but a matter of preserving their cognitive abilities and preventing language loss, particularly among young immigrants. We advocate for programs and specific policy changes that can help these individuals and their families with the skills they need to communicate effectively and integrate into society.This research significantly contributes to the fields of immigration studies, disability studies, and language acquisition. It underscores the urgency of allocating resources to address the specific communication needs of deaf and disabled undocumented immigrants, preserving their linguistic development and cognitive abilities.In conclusion, this paper seeks to raise awareness and advocate for more inclusive policies and resources to facilitate language acquisition for this vulnerable population. We look forward to presenting our research at UCUR 2024 and engaging in productive discussions about this pressing issue.

Authors: Heather Smith. Mentors: Vinodh Chellamuthu, Jie Liu, MD Sazib Hasan. Insitution: Utah Tech University. The invasive species Japanese Beetle (Popillia Japonica) poses significant ecological and economic challenges in the United States, with an annual expenditure exceeding $300 million on damage repair and control efforts. The beetle's life cycle predominates as grubs in turf from late August to April, suggesting a strategic window for control interventions. We developed an individual based model of the Japanese Beetle life cycle, utilizing predator-prey models, to demonstrate the effectiveness of various control methods. Our findings would suggest that ideal timing of grub treatments within the diapause stage markedly reduces beetle populations and is a cost-effective control method. The results of this model can inform land management decisions in controlling Japanese Beetles.

Authors: Ben Martinez, Virginia Merrill. Mentors: Muhammed Yildiz. Insitution: Utah Tech University. This study investigates the multifaceted dimensions of food insecurity among students at Utah Tech University, drawing from the American College Health Association National College Health Assessment survey conducted in Spring 2021, comprising a sample size of 347 students. Shockingly, 46.7% experienced food insecurity in the past 30 days, with certain demographics disproportionately affected—specifically, male, nonwhite, non-heterosexual, disabled, athlete, and single students. We also found associations between food insecurity and deteriorating health and well-being. Those affected reported significantly lower overall health and well-being levels, alongside heightened instances of suicidality, stress, and psychological distress. This research underlines the urgency to address food insecurity, particularly among at-risk demographic groups, and emphasizes the critical need for targeted interventions and support mechanisms. It highlights the concerning link between food access and mental health and advocates for inclusive strategies to address disparities among students. Implementing support systems to mitigate food insecurity's adverse impacts is crucial in fostering an environment conducive to the academic success and overall well-being of all students at Utah Tech University.

Authors: Megan Frisby, Alma Laney, Geoff Zahn. Mentors: Alma Laney. Insitution: Utah Valley University. The oil-bearing species, Hyssopus officinalis (hyssop) and Lavandula angustifolia (lavender) are important ecological, ornamental, and agriculturally cultivated plants in the state of Utah, playing a central role in the state’s major essential oils industry, and thus economic climate. However, little is known about the virological agents infecting Utah plant species. A project was initiated to identify the viruses infecting symptomatic H. officinalis and L. angustifolia specimens obtained from Utah. Tissues collected from plants of both species exhibited viral associated symptoms of stunting and chlorosis, while collected hyssop specimens displayed additional leaf curling and mottling. Initial MinION sequencing was conducted on cDNA libraries synthesized from lavender and hyssop samples which were multiplexed with that of other species using the cDNA PCR barcoding kit and chip v 9.4.1. The primary run yielded contigs for a novel single-stranded negative-sense RNA nucleorhabdovirus in both specimens, a sequence closest to tomato yellow leaf curl China virus (TYLCCNV) in hyssop, and an ilarvirus related to tobacco streak virus in lavender. However, additional, exclusive MinION runs consistently failed to yield quality results in attempts to obtain the complete the genomes of these viruses. DNA and RNA extractions were once again performed on hyssop and lavender samples, and RNA from 2020 and 2023 were sent out of lab for RNAseq using the Illumina Novaseq. Once complete genomes are achieved further research will be conducted to characterize these novel viral agents, determine the identity of their associated vectors and calculate host ranges. The results of this project will help to advance the limited virological knowledge of Utah plants as well as that of the nation and world, and aid in developing future scientifically-sound pathogen management strategies.

Authors: Dante Celani, Laisha Noyes, Candice Johnson, Seun Onileowo, Randy Klabacka. Mentors: Randy Klabacka. Insitution: Utah Tech University. Increased accessibility to next generation sequencing technology (NGS) has facilitated genomic research in diverse biological disciplines studying non-model organisms (which constitute 99.99% of all organisms on Earth). However, most techniques in NGS require mapping of raw-sequencing reads to a refence genome, this presents a challenge for studies involving non-model organisms since no con-specific reference genome is available for the vast majority of these species. Researchers facing this challenge frequently use the reference genome of a related taxon. While it is understood that read mapping efficiency is inversely related to evolutionary distance between read and reference taxa, the exact nature of the relationship is unknown. To examen this we mapped whole genome sequence data from four Aspidoscelis lizard species (“whiptails”) to twenty-eight genomes of varying relatedness across the vertebrate tree of life. We examined the relationship of mapping success to phylogenetic distance and assessed the relationship between these variables.

Authors: Parker McKasson, Hannah Hornberger, Sydnee Bond, Olivia Heller, Josh Marchant. Mentors: Patrick Steffen. Insitution: Brigham Young University. BackgroundIntrinsic religiosity is a deeply rooted connection to one's faith. Individuals with high intrinsic religiosity find purpose and meaning through their spiritual connections. Extrinsic religiosity is primarily driven by social or other superficial factors. Individuals with high extrinsic religiosity may be more inclined to participate in religious activities and communities without having a deep connection to their faith. Intrinsic religiosity has demonstrated associations with lower self-reported stress, however, associations between intrinsic/extrinsic religiosity and baseline heart rate variability (HRV), a proxy measure of the parasympathetic nervous system, have not been studied. Such research has the ability to explain how the complex relationship between religiosity and stress affects overall well-being. We hypothesize that higher self-reported stress will be associated with lower baseline HRV, but intrinsic religiosity will serve as a buffer, such that stress will have a weaker influence on baseline HRV among individuals who are more intrinsically religious. We predict that extrinsic religiosity will have no influence on the relationship between stress and HRV. MethodsA survey and biofeedback study were conducted on a sample of 165 college students. We used the Depression, Anxiety, and Stress Scale (DASS) and Intrinsic/Extrinsic Religiosity Scale (IE/R), as well as measured baseline heart rate variability (HRV) using a 3 lead ECG. We will analyze the impacts of stress on HRV across people with varying levels of intrinsic/extrinsic religiosity through a multivariate regression model.ConclusionsReligiosity is not often viewed as a direct contributor to health and wellness, however, when viewed as a protective barrier against stress, intrinsic religiosity could play an important role in an individual’s stress response and wellbeing. In the presence of stressors, we expect intrinsic religiosity to be related to healthier parasympathetic functioning as measured through HRV.

Authors: Ives Hong, Grace Carsey, Tara Caplin, Hunter Mitchell, Peg Bird, Bridger Lisonbee, Maria Balaceanu, Dannelle Larsen-Rife. Mentors: Dannelle Larsen-Rife. Insitution: Utah Tech University. Attachment is fundamental to human development. The parent-child relationship impacts the physical and mental health of the child, particularly social development. The two attachment dimensions — attachment anxiety and attachment avoidance underlie the caregiver-child relationship in early childhood (Bowlby et al., 1973). Attachment anxiety and avoidance may change or persist throughout the life span. Major life transitions may influence attachment, however, people tend to revert to previous attachment trajectories after experiencing life transition (Fraley et al., 2021). Adverse childhood experiences (ACEs) are linked to attachment insecurity which may have notable outcomes in adult relationships (Ross et al., 2022; Synder et al., 2023). Individuals with attachment avoidance and anxiety may have difficulty maintaining existing connections. People with high attachment anxiety and inadequate social support experience poor health outcomes (Stanton & Campbell. 2014). Lack of social support predict post-traumatic stress and thoughts of suicide (Scoglio et al., 2023). Loneliness and social isolation are associated with insecure attachment (Spence et al., 2020). Loneliness is correlated with poor mental health ratings and symptoms, and even mortality (Holt-Lunstad et al., 2015; Jenkins et al., 2023). This study evaluates early attachment, health, and relationships. Approximately 200 adults will be recruited to complete the Experiences in Close Relationships-Revised questionnaire (Fraley et al., 2011), Adverse Childhood Experience Questionnaire (Felitti et al.,1998), the Social Support Questionnaire-Short Form (SSQ6; Sarason et al. 1987), and the three-Item Loneliness Scale (Russell et al., 1980 ).We expect attachment anxiety and avoidance will be positively correlated with loneliness and negatively correlated with social support, while ACEs moderate these associations. Examining how ACEs may interact with attachment avoidance and anxiety may prompt early intervention to improve the caregiver-child relationship.