AJUR Volume 21 Issue 2 (September 2024)

Click on this link to download the full high-definition interactive pdf for AJUR Volume 21 Issue 2 (September 2024) or https://doi.org/10.33697/ajur.2024.114

Links to individual manuscripts, abstracts, and keywords are provided below.


p. 3. Microfiber Content in Pacific Oysters (Crassostrea gigas) from Morro Bay, California
Julia Bures & Andrea Huvard
https://doi.org/10.33697/ajur.2024.115
ABSTRACT: Plastics are a major source of marine pollution. One form of plastic pollution is microfibers, which are synthetic fibers five micrometers or smaller that are shed by artificial clothing. The size of microfibers enables them to easily be ingested by a number of marine organisms, including oysters. Oysters are filter feeders and a major aquaculture asset, which presents a concern for the effects of microfiber ingestion on human health. Very few studies have been conducted quantifying microfibers using Pacific oysters (Crassostrea gigas) sourced from California. This study quantifies microfiber content in the Pacific oyster farmed for human consumption in Morro Bay, California. Microfibers were quantified after being isolated from oyster samples. An average of 9.12 microfibers were recovered per oyster sample. Although some of the smaller oysters contained more microfibers compared to larger oysters, this difference was not significant. There also was no significant difference between the quantities of black and blue microfibers. However, there was a significant increase in quantities of black microfibers compared to green or red microfibers. The results of this study indicate that a large amount of microfibers are present in commercial oysters, but more research needs to be conducted to determine how this will impact human health. KEYWORDS: Marine Pollution; Microplastic; Microfiber; Trophic Transfer; Keystone Species; Aquaculture; Oyster; Human Health

p. 15. Autoregressive Bandits in Near-Unstable or Unstable Environment
Uladzimir Charniauski & Yao Zheng
https://doi.org/10.33697/ajur.2024.116
ABSTRACT: AutoRegressive Bandits (ARBs) is a novel model of a sequential decision-making problem as an autoregressive (AR) process. In this online learning setting, the observed reward follows an autoregressive process, whose action parameters are unknown to the agent and create an AR dynamic that depends on actions the agent chooses. This study empirically demonstrates how assigning the extreme values of systemic stability indexes and other reward-governing parameters severely impairs the ARBs learning in the respective environment. We show that this algorithm suffers numerically larger regrets of higher forms under a weakly stable environment and a strictly exponential regret under the unstable environment over the considered optimization horizon. We also test ARBs against other bandit baselines in both weakly stable and unstable systems to investigate the deteriorating effect of dropping systemic stability on their performance and demonstrate the potential advantage of choosing other competing algorithms in case of weakened stability. Finally, we measure the discussed bandit under various assigned values of key input parameters to study how we can possibly improve this algorithm’s performance under these extreme environmental conditions. KEYWORDS: Reinforcement Learning; Machine Learning; Autoregressive Processes; Bandit Algorithms; Non-Stationary Bandits; Online Learning


p. 27. Extracts from Soil Samples around Pennsylvania Exhibit Potent Antibacterial Properties against Bacillus anthracis
Annalee M. Schmidt, Shawn Xiong, & John N. Alumasa
https://doi.org/10.33697/ajur.2024.117
ABSTRACT: Deadly bacterial infections such as anthrax continue to pose a significant threat to human health worldwide. This disease is caused by Bacillus anthracis, which the CDC classifies as a Tier 1 biological agent due to its ability to form spores resistant to severe environmental stress conditions, including antibiotics. Identifying new antibiotics against this pathogen is therefore crucial for combatting anthrax infections. In this research, crude extracts from Pennsylvania soil were purified using various chromatography methods, resulting in natural products, which were assessed for their antimicrobial properties. After performing minimum inhibitory and bactericidal concentration assays, two compounds, AMS002 and AMS003, exhibited growth inhibitory and killing activity against B. anthracis at 0.8 mg/ml and 0.2 mg/ml, respectively. Both compounds inhibited greater than 80% of protein synthesis relative to the control samples in cell-based and in-vitro fluorescent reporter assays, suggesting that these compounds may target the bacterial protein synthesis pathway as their primary mode of action. The novelty of this discovery is vital due to the resistant nature of B. anthracis spores and their use as a potential weapon in bioterrorism. KEYWORDS: Antibiotics; Resistance; Natural Products; Chromatography; B. anthracis; Minimum Inhibitory Assay; Minimum Bactericidal Assay; Reporter Assays; Course-based Undergraduate Research Experience (CURE)

p. 39. Numerical Solutions for Kinematics of Multi-bar Mechanisms Using Graph Theory and Computer Simulations
Brandon Torresa & Mahdi Farahikia
https://doi.org/10.33697/ajur.2024.118
ABSTRACT: A method is presented to demonstrate the application of computer simulations in the kinematic analysis of planar mechanisms, emphasizing its use in teaching the latter topic in a corresponding undergraduate course. Concepts of rigid-body dynamics are utilized in the kinematics of machines to analyze the motions (and forces in dynamics) transmitted within multiple interconnected links that make a mechanism, such as a car engine, airplane landing gear, press machine, door closer, and so on. Due to the tediousness of the analytical solutions, most textbooks limit the derivation of the equations to four-bar linkages like crank-rocker and crank-slider mechanisms. Benefiting from the advancements in computer programs, such as MATLAB, and their efficiency in solving large systems of linear and nonlinear equations, a method is proposed to facilitate teaching kinematic analysis of multi-bar linkages to undergraduate students while fostering the application of computational engineering via real-life examples. The results obtained from this method are shown to be in excellent agreement with the algebraic solution of the relative motion equations for each element in the mechanism. KEYWORDS: Kinematics of Machines; Linkage; Numerical Solutions; Graph Theory; Machine Dynamics; Computer Simulation; Mechanism; Linkage Kinematics


p. 53. Learning About Food Insecurity in Athens-Clarke County, Georgia Using Key Informant Interviews
Natalie Wong & Michelle Ritchie
https://doi.org/10.33697/ajur.2024.119
ABSTRACT: Several studies have suggested that food insecurity rates increased during the early days of the COVID-19 pandemic. This study sought to assess the strategies employed by food relief organizations to combat this issue amidst the challenges of 2020. Specifically, the research focused on six local food organizations in the Athens, Clarke County area in Georgia. Organizations were contacted via email, and subsequent key informant interviews were conducted via Zoom with the organization’s leaders to understand their responses to food insecurity relief during the 2020 COVID-19 pandemic. The findings were synthesized using a narrative qualitative approach to identify overarching themes in the organizations’ strategies amid the pandemic. Overall, this study revealed a prevalent lack of emergency preparedness among the organizations, exacerbating the issue of food insecurity in the Athens-Clarke County, Georgia area. These results underscore the need for public policy interventions addressing the underlying causes of food insecurity, including the elimination of food deserts, enhancement of food procurement accessibility, improvement of food affordability, and mitigation of associated disparities by race, income, and gender. By understanding the experiences of these organizations amidst the pandemic and the pre-existing factors that contribute to food insecurity, stakeholders, including other organizations, community leaders, and locals may be able to better prepare for future crises. KEYWORDS: Food insecurity; key informant interviews; qualitative analysis; COVID-19; health disparities; food deserts

p. 61. Inadvertent User Outcomes of Wearable Health Technology
Jeremy Cafritz
https://doi.org/10.33697/ajur.2024.120
ABSTRACT: Wearable health technologies are designed to improve a user’s self-awareness of their state of health and increase motivation and physical activity, but there is limited understanding of the psychological and behavioral impact these devices have. The present research attempts to further clarify the influence of individual characteristics on the cognitive, affective, and behavioral outcomes of activity tracker usage, including the development of dependency. A cross-sectional study of 212 college students who used activity trackers was conducted to evaluate the psychological and behavioral impact of activity tracker usage and users’ affective response to their device. Participants expressed more positive affect while wearing their device as opposed to when they were unable to wear it. Female participants exhibited more positive affect than male participants while wearing their device but less when unable to wear it. Only 9% of the sample reported a dependency effect. The dependency effect was negatively associated with intrinsic motivation to be physically active, motivation by the idea of success, and the personality traits of agreeableness and conscientiousness. The dependency effect was positively associated with extrinsic motivation for physical activity and tracker usage, as well as need for cognitive closure. This research elucidates the unintended outcomes of activity tracker usage along with the individual characteristics that present as predictors of these outcomes. KEYWORDS: Health Wearables; Activity Trackers; Physical Activity; Motivation; Dependency; Gamification; Personality