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Simulation of Photochemical Effects on Air Quality
Get PDFNitrogen dioxide is an atmospheric pollutant with largely anthropogenic sources; it is a combustion side product often produced by automobiles and industrial activity. It has negative effects on the respiratory system. In addition to being a pollutant itself, nitrogen dioxide is also a contributor to tropospheric ozone through photochemical reactions, both of which are EPA criteria air pollutants. Nitrogen dioxide and ozone participate in a net-zero reaction cycle in which the formation of ozone is rate-limited by the photolysis rate of nitrogen dioxide. The destruction of ozone and reformation of nitrogen dioxide is a fast reaction unaffected by photochemistry, therefore it occurs at relatively stable rates, regardless of available radiation. It is necessary to quantify the rate of nitrogen dioxide photolysis, the first half of this cycle, under varying atmospheric conditions, due to its dependence on radiation.
FastJX is a software package which simulates the effects of atmospheric aerosols on radiation, which then affects photolysis rates. FastJX uses optical properties at a range of wavelengths to simulate the extent of radiation absorption or scattering for an aerosol layer at a specified elevation. This project specifically uses aerosol optical properties measured during the NASA Langley ACTIVATE campaign. The optical properties were most closely examined in the UV-A and UV-B wavelengths, as shorter wavelengths penetrate minimally to the troposphere and longer wavelengths do not carry enough energy to drive nitrogen dioxide photolysis.
This project aims to correlate photolysis rates simulated by FastJX, measured aerosol optical depths, and measured concentrations of nitrogen dioxide. The measured aerosol optical depths and nitrogen dioxide concentrations come from co-located NASA AERONET and EPA monitoring sites, respectively, which allows for direct comparison. The sites, in Pasadena, California, were chosen due to their location in an urban center with consistently high levels of sunlight.
It was found that FastJX simulation results are most closely correlated with measured changes in nitrogen dioxide levels during hours of peak sunlight, which is when photolysis is most active. This is consistent with the expectation that time of day plays a significant role in nitrogen dioxide levels, due to the combined factors of nitrogen dioxide production during rush hour traffic and nitrogen dioxide destruction via photolysis when UV radiation is present.
Utilizing simulation allows for knowledge of photolysis rates under a greater range of atmospheric conditions without the resource-intensive steps of measuring actinic flux in a field environment. Instead, aerosol optical depth monitors, which require less man hours, can be combined with existing optical property sets. FastJX is additionally equipped to simulate aerosol effects on other photolysis reactions, which means that the sensitivity analysis conducted here may be applied to other chemical species.https://scholarworks.uark.edu/hnrcsturpc25/1009/thumbnail.jp
A Statistical Analysis for Evaluating the Parameters Influencing the Rutting and Cracking Performance of Asphalt Mixtures
Get PDFDurable pavement is essential for modern transportation infrastructure, especially in the United States of America which boasts over 8.5 million lane miles of roads and highways. Despite advanced construction techniques, asphalt pavements are susceptible to rutting and cracking, significantly affecting their performance and maintenance costs. Current methods for analyzing rutting and cracking in asphalt mixtures rely on various parameters, leading to measurement variability. This highlights the need for more rigorous analysis to explore the relationship between mix design variables and pavement performance. This research explores the IDEAL-CT and Asphalt Pavement Analyzer (APA) data from mix designs collected by the Arkansas Department of Transportation. Both mix designs had virgin and recycled asphalt mixtures to compare how the percent recycled asphalt affected the susceptibility of rutting and cracking along with other variables. To better understand which asphalt mixture properties impact cracking and rutting in the field, box-and-whisker plots, Pearson correlation, Spearman rank correlation, and Kendall’s Tau analysis methods were used. After running these analysis methods, the CTIndex for virgin mixtures had the highest correlation with the number of design gyrations, while the CTIndex for RAP mixtures had the highest correlation with the theoretical maximum specific gravity. The rut depth correlated heavily with the upper performance grade for both virgin and RAP mixtures. Interestingly, the second highest correlation for the CTIndex was the bulk specific gravity of aggregate mixture for both virgin and RAP mixtures. The rut depth had the second highest correlation with the number of design gyrations for both types of mixtures. The outcome of this research contributes valuable insight into the key factors affecting the asphalt mixture performance and allows other owners to examine how their asphalt mixture properties impact their own performance tests.https://scholarworks.uark.edu/hnrcsturpc25/1010/thumbnail.jp
Unbridled Healing: Identifying the Barriers of Equine-Assisted Therapy
Get PDFDespite the documented benefits of equine-assisted therapy (EAT) for mental health conditions, this complementary approach remains underutilized. This qualitative study investigated barriers preventing wider EAT implementation by examining challenges faced by clients, facilities, and volunteers. Data collected through open-ended surveys from 33 participants and the researcher\u27s autoethnographic observations revealed eight common barriers: Accessibility (48 mentions), Money (43), Time (30), Awareness (23), Physical Factors (13), Relationships (13), Risk (13), and Weather (7). Clients identified financial constraints as their primary barrier, particularly insurance limitations. Facilitators struggled most with accessibility challenges, including lack of resources, trained staff, suitable horses, and appropriate facilities. Volunteers faced significant time constraints and communication difficulties. Novel findings included communication issues for volunteers, relationship barriers affecting retention, physical limitations to participation, and weather-related constraints affecting all stakeholder groups. The study\u27s findings support advocacy efforts to address these barriers and potentially expand EAT access to more diverse populations.https://scholarworks.uark.edu/hnrcsturpc25/1046/thumbnail.jp
Incorporating Mindfulness Techniques in Therapeutic Practices to Impact a Patient’s Pain Perception
Get PDFBackground: Chronic pain is a widespread condition that affects millions of individuals and leads to substantial healthcare costs, with estimates in the U.S. ranging from 635 billion annually. Traditional pain management heavily relies on opioid prescriptions, which, while effective in the short term, have contributed to the ongoing opioid crisis due to risks of addiction and dependency. As a result, there is a growing interest in alternative, non- pharmacological approaches to pain management, including mindfulness-based interventions (MBIs). MBIs have been increasingly recognized for their ability to help patients modulate pain perception and improve overall well-being. This study aims to analyze how mindfulness techniques can serve as an effective complementary pain management strategy. Purpose: This study explores the role of mindfulness techniques, including Mindfulness-Based Stress Reduction (MBSR), Acceptance and Commitment Therapy (ACT), and Cognitive-Behavioral Therapy (CBT), in altering pain perception. The objective is to determine how these interventions can be integrated into physical and occupational therapy to enhance patient outcomes and reduce reliance on opioids for chronic pain management.https://scholarworks.uark.edu/coesym25/1004/thumbnail.jp
Surviving Their Stripes: the Diagnostic Odyssey and Impact of Life with Hypermobile Ehlers-Danlos Syndrome
No full textBackground: Hypermobile type Ehlers-Danlos Syndrome (hEDS) is subtype of Ehlers-Danlos Syndrome that is a genetic connective tissue disorder with complexities involving joint hypermobility, tissue fragility and severe pain. Patients often experience misdiagnosis, medical dismissal and years of waiting for a diagnosis. Purpose: This study aims to evaluate the quality of life and diagnostic journey for patients living with hEDS.https://scholarworks.uark.edu/coesym25/1008/thumbnail.jp
Strengthening Voter Education Campaigns Through User-centered Design
Get PDFVoter education materials should serve as a bridge to civic participation, but can fall short due to complex language, inadequate access, or clarity issues. These issues have the potential to disproportionately discourage already impacted groups, such as rural voters, first-time voters, non-native English speakers, and voters with disabilities. Though voter suppression is commonly discussed in terms of restrictive law, there is a gap in research regarding how the lack of available and accessible voter information can contribute to disenfranchisement.
Arkansas, in particular, struggles with voter participation. Despite barriers like strict Photo ID laws, lack of translated materials, and tight absentee ballot requirements, there is a significant lack of official government information to guide these communities through the voting process and to help them navigate these obstacles.
This research applies user-centered design to improve voter education materials in Arkansas by directly addressing information barriers that discourage participation
The Effect of Administered Animal-Assisted Therapy on University Students\u27 Anxiety and Stress
Get PDFAbstract
Purpose: The purpose of this research study is to evaluate the effects of animal-assisted therapy (AAT) on undergraduate student anxiety and stress, comparing the effectiveness between an individual AAT session to a group study session without AAT. Animal-assisted therapy is a type of canine therapy that may be a helpful tool to decrease student test anxiety, and potentially, a meaningful stress-reducing intervention for university students. Our results sought to examine differences in traditional study practices vs the use of AAT prior to exams, and support or refute animal-assisted therapy as a low-cost, minimal-risk, effective solution for undergraduate student anxiety. This will add valuable information to the gap in the literature regarding AAT use among undergraduate students.
Methods: This cross-sectional study used a convenience sample of volunteer students, solicited prior to the interaction date, and placed in the intervention group (AAT) with a certified therapy dog, Bella, approved by The Institutional Animal Care and Use Committee (IACUC). A single 20-minute AAT session of interacting and playing with a therapy dog in a group of up to 5 students was utilized. The dog handler, Dr. Scott, was present and did not encourage interaction between the participant and the dog. Outcome measures include pre-exam and post-exam State-Anxiety Inventory scores, Trait-Anxiety Inventory scores, and Perceived Stress Scale scores, validated tools for measuring anxiety in young adults. The pre-exam State- and Trait-Anxiety Inventory test, and the Perceived Stress Scale test were taken prior to interacting with the therapy dog (intervention), and taking the exam. The post-test surveys were completed on the day of the exam, within two hours of the intervention. Both pre- and post-surveys were administered using a QR code linked to Qualtrics, using the participants’ hand-held device.
Results: Demographics of this study included 11 female participants with the majority of participants (n = 9, 81.8%) identifying as nursing students. Eighty-two percent of participants displayed significant decreases in post-intervention State anxiety scores, while 18.2% reported no statistically significant changes in State anxiety scores. Nine percent of participants showed significant decreases in post-intervention Trait anxiety scores, while 90.9% expressed no significant changes in Trait anxiety scores, deeming this an insignificant finding. Twenty-seven percent of participants reported a statistically significant decrease in post-intervention stress scores, while 72.7% showed no statistically significant change in post-intervention stress scores, making these results statistically insignificant as well.
Discussion: A short 20-minute animal-assisted therapy session had the most significant effect on post-intervention State-anxiety scores. This discovery was not unexpected, as much AAT research had similar findings. Due to the small sample size, further research is needed. The findings of this research study are that state anxiety, anxiety that is temporarily felt by a person, decreases after an AAT session before an exam, while trait anxiety, a participant\u27s general anxiety, is unaffected
Shortage to Surge - Studying the Post-COVID-19 Guitar Retail Market
Get PDFThe COVID-19 pandemic was one of the most catalyzing events of the 21st century, leading to supply chain disruptions, lifestyle changes, and a massive shift towards digital technologies. During the COVID-19 lockdown, many people had more time, and over 16 million people learned guitar in the first 2 years of the pandemic. According to a study by Fender, 62% of these new guitar learners cited the pandemic as their primary reason for learning the instrument. However, pandemic policies and supply chain disruptions meant that many guitar retailers were unable to satisfy demand, and backorders began to accumulate. Since both guitars and clothing in the past have been retail items that consumers preferred to buy in person rather than online, this student-led research project seeks to compare the guitar and clothing retail markets before and after the COVID-19 pandemic (2019-2023) to discover guitar market category trends and predict future market growth to better inform manufacturers, retailers, and consumers. The study will include a literature review, hypothesis testing, a preliminary study of the datasets through summary statistics and basic visualizations (using Tableau, Python, and R), and several iterations of predictive models (regression, clustering, neural networks, etc.). The clothing retail data will be procured from the Information Systems Department in the Walton College of Business, and the guitar retail data will be procured from 2 anonymous US music retailers. After conducting interviews with industry experts at the NAMM (National Association of Music Merchants) show in California, the modeling results will be compared with the interviews, and an appropriate final model will be selected to predict the guitar retail market’s growth in the next five years.https://scholarworks.uark.edu/hnrcsturpc25/1026/thumbnail.jp
The Effect Protein Supplementation on Waist-to-Hip Ratio, BMI, Lipid Profile, and Resting Energy Expenditure in Postmenopausal Women
Get PDFPostmenopausal women are a growing and at risk population that face increased risk for adverse changes in body composition, lipid profile, and overall cardiometabolic health due to hormonal changes associated with aging. Over 40% of postmenopausal women have obesity, which can be linked not just aging but the menopausal transition. Because of the negative effects of menopause on cardiometabolic, research into dietary interventions to combat these effects are needed. High-protein diets have shown promise in mitigating these effects, but sufficient research has not been done to determine the effects on postmenopausal women. This study aimed to evaluate the effects of daily beef consumption as a part of a high-protein diet on markers of cardiometabolic health, body composition, and energy metabolism in postmenopausal women over 8 weeks . In a randomized controlled trial, healthy postmenopausal women were assigned to either a high-protein diet that included daily lean beef consumption or a standard-protein diet with limited beef intake for 16 weeks. The evaluated markers for healthy aging were BMI, waist-to-hip ratio, resting energy expenditure (REE), and lipid profile. REE and lipid profile were both taken in a fasted state. Preliminary findings showed trends in the high-protein beef group for improvements in HDL cholesterol, REE, and waist-to-hip ratio. There was no change in BMI for either group and REE improved in both the intervention group and the control. The limited sample size and time allowing only for the first 8 weeks of data to be collected up to this point hindered the statistical significance of the data collected. As the study continues and sample sizes grow, more conclusive results will be found. The adverse health effects of menopause are a serious public health issue for a growing population. Sufficient research to provide this specific population nutritional information for healthy aging has not been thoroughly conducted, so this study is a step in the right direction of helping improve the wellness of postmenopausal women
Guide to Data Science: A User-Friendly App for Data Exploration
No full textThis honors thesis presents the development of a user-friendly data science application built with Streamlit, designed to facilitate data exploration and analysis for users with little to no prior knowledge of data science. The application is structured into five interactive pages, guiding users through the essential stages of data analysis: a welcome page, data cleaning, data visualization, modeling, and interpretation.
The welcome page serves as the entry point, allowing users to upload their data, which will be used throughout the subsequent pages. It also features the company logo for Bentley Ave Data Labs, the industry partner that requested the development of this application. This collaboration ensures that the app meets real-world industry needs while providing an accessible tool for data exploration.
The data cleaning page offers intuitive, clickable functions for basic preprocessing tasks such as handling missing values, removing duplicates, and dropping unnecessary columns. Once the data is cleaned, users can move to the data visualization page, where they can generate two customizable graphs by selecting variables to display, alongside a heatmap highlighting data outliers and a z-score graph for deeper insights. Users are also given the option to remove outliers directly from this interface.
The modeling page providing users the ability to choose between three categorical models and three regression models to fit their data. This streamlined approach empowers users to build and evaluate machine learning models without writing any code, promoting accessibility and enabling more people to harness the power of data science.
The interpretation page ties together the insights gathered throughout the application by presenting the results of the chosen machine learning model in an easy-to-understand format. Users are shown key performance metrics of accuracy, R-squared, and feature importance. Additionally, the page displays a confusion matrix or residual plot to help users visualize how well the model performed. This
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final step not only reinforces the outcomes of their analysis but also supports informed decision-making by translating complex results into clear, actionable information.
Through this application, the thesis aims to bridge the gap between complex data analysis techniques and users who lack programming experience, offering an accessible platform for understanding and interpreting data with ease and confidence