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: Jalynn Lunceford. Mentors: Crystal Koenig, Arianna Harrington. Insitution: Southern Utah University. At Southern Utah University, the Anthropology and Mammalogy Teaching Collections were widespread and disorganized. The Anthropology Teaching Collection had not been curated yet, and only a binder of handwritten records from 2005 existed for Mammalogy. Mammalogy had over 70 specimens exhibiting dry rot, unsealed taxidermy was found to be leaking onto storage trays, and various skeletal specimens were in severely fragile states. When tasked with organizing these collections, my main goal was to create a better inventory and curation system for easier access to teaching materials and increase interdepartmental resource-sharing. Over 600 recorded hours, I created separate websites for each collection to display photos of available specimens, and specimens were inventoried using a taxonomic-based numerical barcoding system. Their housing system was reorganized and improved where possible. Over 100 specimens were cataloged in Anthropology; the majority were additive-manufactured primates with no real human remains. In Mammalogy, 1,296 specimens were cataloged; over 700 were skeletal remains and the remaining 500 were taxidermy, with one surprise discovery of undocumented human remains. The human remains were sent to the State Forensic Examiner and was determined to be a poorly prepared anatomical specimen. This project allowed me to prevent further damage to the Mammalogy specimens by effectively removing rotting and highly damaged specimens, and treating for moths. Lost materials were rediscovered, including the first known primate to the collections. Now, professors and students can effectively navigate and locate teaching/learning resources from the databases and websites I created, and better anticipate future collection needs.

Authors: Brandie Statham, Rebekah Hakala. Mentors: Todd Spencer. Insitution: Utah Valley University. The link between attachment style and sexual intercourse frequency is critical in determining an individual's sexual satisfaction in a romantic relationship. Secure, anxious, avoidant, and disordered attachment types all have a substantial impact on how people approach sexual intimacy (Mark, Vowels, & Murray, 2018). Individuals who are securely attached tend to have better levels of sexual satisfaction because they can openly communicate their desires and needs, creating a positive and supportive sexual environment. Anxiously connected people, on the other hand, may experience swings in sexual satisfaction as a result of their reliance on sexual connection for reassurance. Individuals who prioritize physical proximity over emotional intimacy may have difficulty forming deep emotional relationships, affecting their overall sexual satisfaction. Disorganized attachment patterns can result in complex and occasionally contradictory experiences (Mark, Vowels, & Murray, 2018).. They may want both closeness and distance, which can create confusion. This attachment style's unpredictability can have an impact on both frequency and satisfaction.The purpose of the present study is to examine the relationship among attachment styles and sexual satisfaction, and sexual frequency. Our sample consists of 411 married individuals. Participants completed The Relationship Questionnaire (RQ; Bartholomew & Horowitz, 1991), Sexual Frequency, and Sexual Satisfaction Index (CSI-4; Funk & Rogge, 2000). Results of the one way Anova were significant F (3,407) = 8.21, p=<.001. There was a significant difference in levels of sexual satisfaction among attachment styles. Secure attachment (M=32.95, SD = 8.23), fearful attachment (M=29.40, SD = 9.80), preoccupied (M=29.54, SD = 9.82), and dismissing (M = 30.77, SD = 9.97). Results of the Bonferroni Post-hoc analysis indicated a significantly higher levels of couple satisfaction than fearful and dismissing attachment styles (p.<.001). There was no significant difference in the amount of frequency of sex and attachment style. Results provide empirical support that secure attachment styles tend to be beneficial for sexual satisfaction despite having no statistical difference in sexual frequency.

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: Brian Seamons. Mentors: . Insitution: Utah Valley University. We compare the atmospheric compositions of WASP-39b and WASP-178b, as well as the different observing modes and analysis techniques for both observations. While both objects are gas giants, WASP-178b’s short-period orbit around its A-type host star leads to an equilibrium temperature more than double that of WASP-39b. WASP-39b was the one of the first exoplanets to be studied by JWST, and subsequently gave astronomers the first insights into JWST’s unprecedented exoplanet characterization capabilities. The data was collected using the NIRSpec PRISM observing mode, which provides broad-wavelength observations typically between 0.5 and 5.5 microns. Our intent was to use the publicly released data files and independently confirm the findings of the Early Release Science team while simultaneously validating our own data analysis pipeline. Our custom methods produced satisfactory results, ultimately yielding a transmission spectra that was consistent with that of the ERS team. Following this, we turned our attention to our second planet, WASP-178b, using data from the Cycle 1 program JWST-GO- 2055 (PI Lothringer). Using the G395H NIRSpec observing mode, which provides narrower wavelength coverage (~3-5 microns) with higher-resolution (R~3000), we constrained atmospheric conditions and molecular abundances, specifically H2O and CO. Though these two gas giants are quite unique, we present the results of each study side-by-side to highlight similarities and differences of both planetary atmospheric composition and the JWST observation modes which provided the data.

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: Grant Cole, Vitaliy Walker, Daniel Adams, Nathan Twitchell, Melissa Lee, Jennifer Mortensen, Brittney Stockholm, Tatiana LeRoy. Mentors: Claudia Jorgensen. Insitution: Utah Valley University. When exposed to stressful situations, the human nervous system reacts with the fight or flight response activation. Physiological indicators of the activation of the fight or flight response include a change in body temperature, increased heart rate, blood pressure, and sweating (Sriram et.al, 2012). There is mounting evidence implicating stress as physiologically and psychologically harmful. For example, recent research has found a correlation between chronic exposure to stress and the development of mental illnesses such as anxiety and depression. Furthermore, chronic stress has the potential to change the anatomy of the brain along the hypothalamic pituitary adrenal axis (HPA), which is an important part of the neuroendocrine system, plays a role in the release of stress hormones, and helps regulate moods, emotions, and sexual behaviorisms (Ramirez, et.al., 2013). As college can be quite stressful, developing healthy coping mechanisms to deal with stress might positively influence the students’ academic performance and it might improve and maintain their psychological and physiological well-being (Skowronek, 2014). Various research studies have been conducted to reveal the therapeutic qualities of music. Music can effectively relieve nervousness, promote mental health, and positively affect students' psychological state (Chi, 2020). Current research on stress-related outcomes shows that music interventions play a significant role in stress reduction on physiological levels (de Witte et. al, 2020).  Preliminary results indicated that physiological responses (including heart rate, electrodermal skin response, and body temperature) to a mathematical calculation task were not impacted by the type of background noise (control, calm music, or upbeat music). Therefore, the current study is while being exposed to various music genre types (Kirschbaum et al., 1993). We hypothesize that calmer music might reduce stress response, while faster and more upbeat music might increase the stress response. The study will employ a between-subject measures design. After obtaining the baseline physiological measures when no music is played, the participant will either be exposed to two segments of relaxation/mediation music or two segments of fast-beat music. While exposed to different music conditions, the physiological response will be used to compare the impact of music genre (calm meditation music versus techno music) as well as practice (music segment 1 versus music segment 2) on the human stress response. Findings on the effects of music manipulation on the human nervous system can be used as additional tools for the management of stress.

Authors: Minh Nguyen, Eugene Leung. Mentors: Ming Yu. Insitution: Utah Valley University. A rapid, non-invasive method of disease detection method is vital for diagnosis or prevention. Many recent studies suggest that biomarker proteins that are associated with certain diseases were often found in urine samples of the patient. Quantum dots (QDs), a type of nanomaterial, have been investigated in previous studies, revealing their fast response in fluorescent properties when interacting with biomarker proteins. In this study, we examined the impact of QDs’ fluorescent properties in complex solutions by utilizing various concentrations of artificial urine samples. The results of this study provide insight into the possibility of using QDs as an alternative method of disease detection.

Authors: Vince Rossi, Spencer Brown. Mentors: Vince Rossi. Insitution: Utah Valley University. Current systems of generating 3D fluorescent images of samples require scanning of a sample or multiple exposures to acquire a series of images. Collecting a 3D fluorescent image in these fashions is timely, ranging from minutes to tens of minutes. This is not ideal for imaging live, dynamic samples that change as time progresses. The use of holographic techniques allows for the collection of a 3D image on the scale of milliseconds, therefore negating motion artifacts. Combining the speed of digital holography with fluorescent imaging will allow for identification of labeled biological components within a sample as well as the ability to view the sample in a 3D space thus offering greater detail and information on the sample. This process is called Holographically Informed Fluorescence Imaging (HIFI). Simulations have been run using MatLab in which a sample is imaged using Phase Shifting Digital Holography. The 3D reconstruction of the image is propagated using Huygens Convolution Method, and then all of the pixels of the image are brought into focus numerically. This image is then overlayed with the fluorescence image obtained. Each pixel of the fluorescent image is propagated to the depth of focus for each pixel within the 3D holographic image and a 3D fluorescent image is obtained. Simulations of this process have proved successful. A proof of principle experiment is currently underway as to prove the effectiveness of this fluorescent imaging method.

Authors: Sadie Jensen, Nellie Bowman, Nick Jeffery, Heather Wilson Ashworth. Mentors: Heather Ashworth. Insitution: Utah Valley University. The STEM career field has been found to be particularly unwelcoming to women and minorities resulting in attrition of these demographics in STEM degrees and careers.2 To address this problem, the National Science Foundation awarded Utah Valley University a grant to fund undergraduate research opportunities with faculty. This preliminary research project explores the effect of mentored undergraduate research opportunities on student retention and success in the UVU Biology Department. Each year for the last 4 years, 10 students were accepted each year into a research cohort. The following factors are known indicators of student success and retention in the STEM fields: self-efficacy1, effort control4, and teacher immediacy3. These factors were qualitatively measured with reflection questions. Students were surveyed at the end of each academic semester. There are two completed cohorts and data is still being collected on the remaining two cohorts. A coding scheme was developed, and reflection questions were coded to consensus. The Pearson's coefficient was greater than 0.76. The preliminary coding results show themes of positive or very positive effects of the research experience on self-efficacy, effort control, and teacher immediacy. The greatest gains were observed in self-efficacy and teacher immediacy. This preliminary data supports the role of undergraduate research in retaining women and minorities in STEM majors. Sources: Kalender, Z. Y., Marshman, E., Schunn, C. D., Nokes-Malach, T. J., & Singh, C. (2020). Damage caused by women’s lower self-efficacy on physics learning. Physical Review Physics Education Research, 16(1). https://doi.org/10.1103/physrevphyseducres.16.010118 White, J. L., & Massiha, G. H. (2016). The retention of women in Science, Technology, engineering, and Mathematics: A framework for persistence. International Journal of Evaluation and Research in Education (IJERE), 5(1), 1. https://doi.org/10.11591/ijere.v5i1.4515 Micari, M., & Pazos, P. (2012). Connecting to the professor: Impact of the student–faculty relationship in a highly challenging course. College Teaching, 60(2), 41-47. Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of educational psychology, 82(1), 33.

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.

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: Lilliana Rogers. Mentors: Dannelle Larson-Rife. Insitution: Utah Tech University. One in five girls and one in twenty boys are victims of childhood sexual assault in the United States (Crimes, 2012). There is ample research on the effects and treatment of CSA on victims, however, a paucity of research on pedophiles and sexual offenders. In this social policy paper, the effects of childhood sexual abuse (CSA) on victims should use neuroscience research to prevent CSA. Furthermore, attachment in childhood is pertinent in developing healthy adult relationships, however, despite having a secure attachment to parents, children still face adverse effects of CSA in intimacy in adulthood (Barnum & Perrone-McGovern, 2017). Furthermore, adults exposed to CSA face a higher risk for mental health disorders, physical health problems, and substance abuse disorders, compared with adults who have not been exposed to CSA (Herder & Redner, 1991). Four main effects of concern are addressed in CSA victims: intimacy in adulthood, mental health risks, physical health risks, and substance abuse. These main points of concern illustrate the detrimental effects of CSA, and justify the need for change. Survivors are not the root cause of childhood sex abuse; perpetrators of sexual abuse against children are, leaving perpetrators who commit CSA at risk for reoffending. Incarceration is ineffective due to short sentencing and the child has already been sexually abused (Grady et al., 2015). In addition to ineffective reprimands, little research has been conducted on why and how pedophilia occurs. However, the limited research that has been conducted, is promising, but needs further funding and research to investigate the origins of pedophilia, how to treat it and how to prevent it. In addition, current pedophilia prevention efforts are noninclusive, inaccurate, and not targeted toward caregivers (Kenny & Wurtele, 2010; Grady et al., 2015; Finkelhor, 2009). Pedophilia is not addressed and treated, only the aftermath of CSA is. By analyzing these main concerns, we examine three points of intervention by addressing sexual offenders and pedophiles through the ineffectiveness of incarceration, the lack of funded research, neuroscientific research, and inadequate prevention methods. These points of intervention can be implemented and may reduce the risk of CSA so no child ever has to experience childhood sexual assault.

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: Avary Fielding. Mentors: John Salmon. Insitution: Brigham Young University. Human-robot co-manipulation is a field of study that explores humans and robots collaboratively moving objects in various applications, including areas such as search and rescue or disaster response. The focus of this particular research is the coordination of a group of 2-3 human participants to maneuver a 55-lb table and execute specific tasks, in order to draw insights on effective strategies for humans-robots teams. Within each group, a leader was equipped with a virtual reality (VR) headset, providing them with a visual representation of the end goal. In contrast, one or multiple followers, who were unable to see the desired final position, had the responsibility of following the leader to complete the task. Data pertaining to forces, torques, and position was recorded for several iterations of 18 unique table movements to investigate group strategies and learning over time. One specific maneuver involving diagonal translation in the transverse plane (xy, with +y being to the left of the leader) became of special interest and led to the formation of two key hypotheses surrounding the evolution of human coordination strategies. First, it was hypothesized that participants would initially approach the task by translating forwards (in the x direction) and then sideways (in the y direction), before potentially optimizing their strategy in subsequent trials. Second, it was anticipated that, after successfully completing the task twice, participants would adapt to a more efficient method, involving direct diagonal translation. This research aims to answer whether the transition from sequential translations to diagonal movement is a learned behavior, developed over time as groups become more adept at the maneuver. Understanding how humans naturally tend to optimize large object manipulation can be invaluable in the realm of human-robot co-manipulation, as it provides a point of reference on which to base robot behavior, ultimately improving performance and efficiency in various co-manipulation scenarios.

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: 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.