Digital Commons Network^™

The Therapy Behind The Tractor: An Occupational Therapists’ Guide For Treating Farmers, Allison Haiby

Occupational Therapy Capstones

Background: Historically, farming is known as a highly laborious job, placing farmers at increased risk for injury. Despite an injury, the farm must continue to be cared for. Although occupational therapy cultivates client-centered care, many therapists have limited knowledge of farming culture and best practice methods to integrate the demands of farming into therapy.

Purpose: The purpose of this scholarly project was to develop an educational guide, Built for the Farm: An Occupation-Based Guide for Therapists Working with Farmers, to support therapists treating farmers. The guide promotes culturally informed, occupation-based strategies to strengthen therapeutic relationships and improve the healthcare experiences …

Pathways To Participation: Enhancing Inclusion For Individuals With Idd, Katie Koxlien

Occupational Therapy Capstones

Background: Youth with intellectual and developmental disabilities (IDD) continue to experience barriers to meaningful community participation despite policies promoting inclusive community-based services (Friedman, 2017). Sensory sensitivities, difficulty with transitions, and overstimulating environments frequently limit engagement and increase anxiety or behavioral responses when appropriate supports are not present (Bagatell et al., 2022; Dean et al., 2018; Tint et al., 2017). Research indicates that inclusion requires intentional programming that incorporates structured supports, consistent routines, and opportunities for meaningful engagement (Edwards et al., 2021; Hall, 2016).

Methods: The purpose of this scholarly project was to develop a week long sensory exploration camp for …

Introduction Of Occupational Therapy Into A Suburban Supportive Housing Organization, Madeline Kuntz

Occupational Therapy Capstones

Abstract: Unhoused individuals experience compounded barriers beyond housing access and are often underserved within occupational therapy practice. This doctoral capstone project partnered with a nonprofit residential program to develop a research-informed onboarding manual grounded in the holistic occupational therapy framework, Model of Human Occupation (MOHO, O’Brien, 2017). The manual was designed to clarify expectations of the supportive housing program, address diverse resident needs, and promote independence as the organization expands. Development was informed by a comprehensive literature review and informal needs assessment of the organization, identifying anticipatory barriers and supports commonly experienced prior to program entry. Key areas of need …

The Lens Of Farmers: Understanding Culture To Improve Occupational Therapy Care, Allison Marie Stephani

Occupational Therapy Capstones

Introduction: Accessible healthcare is essential for farmers due to their limited available time and hazardous job duties (Hildebrand et al., 2019; Hopkins et al., 2023; Salmon et al., 2025; U.S. Department of Agriculture, 2023). Due to the high incidence of injuries that occur within the profession, it is crucial that farmers seek appropriate healthcare services to address these concerns. However, a significant barrier for seeking healthcare assistance is the limited cultural competence among healthcare professionals in understanding the unique needs within farming communities (Gordon et al., 2024; Hildebrand et al., 2019; Hopkins et al., 2023; Purc-Stephenson et al., 2024). The …

A Firm’S Operational Risk: Data Set And Empirical Evidence, Vivek Astvansh, Joseph J. Simpson

International Business and Entrepreneurship Faculty Publications

Problem definition: A firm’s stakeholders would benefit from a quantitative measure of the managerial disclosure of its operational risk and the implications of this disclosure. However, a quantitative and scalable measure of a firm’s disclosed operational risk is unavailable. Thus, the firm’s stakeholders remain unaware of its disclosed operational risk and the risk’s implications. Methodology/results: U.S. law requires a public firm to textually disclose its operational and nonoperational risks in Item 1A of its annual report (i.e., Form 10-K). We train 64 transformer models on U.S. public firms’ Item 1A text to score 131,920 firm-years (16,959 firms, 2005 to 2024) …

Making Words Count: Computational Linguistics In Management Research, Joseph J. Simpson, Richard A. Hunt, David M. Townsend, Judy Rady, Elham Asgari, Mohammad Rady, Daniel J. Beal

International Business and Entrepreneurship Faculty Publications

In recent years, a rapidly growing number of management scholars are using computational linguistics (CL) to analyze vast corpora of naturally occurring organizational language. Yet the rapid adoption of CL methods has outpaced the development of shared standards for linking theoretical constructs, linguistic data, and computational measurement. We synthesize 353 articles published in leading management journals for 2013–2025, identifying four recurring challenges shaping the credibility of CL-based research: misalignment between constructs and textual corpora, unnecessary model complexity, the opacity of large language model workflows, and insufficient transparency in reporting. Building on these patterns, we develop four integrative design principles—construct-language fit, …

Future Mining: Learning For Safety And Security, Md Sazedur Rahman, Mizanur Rahman Jewel, Sanjay Madria

Computer Science Faculty Research & Creative Works

Mining industry is rapidly transforming into an AI-driven cyber-physical ecosystem where safety and operational reliability depend on robust perception, resilient communication, trustworthy distributed intelligence and continuous monitoring of miners and equipment. Real-world mining environments impose severe constraints like poor illumination, dust, occlusion, GPS-denied conditions, irregular underground topologies, and intermittent connectivity. These factors degrade perception quality, disrupt situational awareness, impair trajectory prediction and weaken the reliability of distributed learning systems. Emerging cyber-physical threats, including backdoor triggers, sensor spoofing, label-flip attacks and poisoned model updates, further jeopardize operational safety, particularly as mines increasingly adopt autonomous vehicles, humanoid assistance, and federated learning for …

Dynamic Hub-Aware Knowledge Distillation For Efficient Traffic Flow Forecasting, Xiangjie Kong, Can Shu, Wenchao Weng, Zhenzhen Zhao, Guojiang Shen, Lei Wang, Sajal K. Das

Computer Science Faculty Research & Creative Works

Real-time traffic forecasting acts as a critical enabling service for IoT-driven Intelligent Transportation Systems (ITS). While existing Spatiotemporal Graph Neural Networks (STGNNs) achieve superior forecasting accuracy, their intensive computational complexity and high latency create a deployment bottleneck for resource-constrained IoT edge devices. To address this resource-accuracy mismatch, we propose a novel framework termed Dynamic Hub-Aware Knowledge Distillation (DHKD). Unlike traditional uniform distillation paradigms, DHKD introduces a topology-aware strategy to transfer knowledge from a complex teacher to a lightweight Spatiotemporal Multi-Layer Perceptron (STMLP) student model. Specifically, we design a dynamic hub-aware gating (DHAG) mechanism that adaptively identifies time-varying pivotal sensing nodes …

Digital Twin Freshness Maximization In Edge Computing, Jing Li, Jianping Wang, Weifa Liang, Quan Chen, Sajal K. Das, Xiaohua Jia

Computer Science Faculty Research & Creative Works

Mobile Edge Computing (MEC) shifts powerful computing resource provisioning from remote powerful data centers to the edge of core networks. Meanwhile, Digital Twin (DT) has surfaced as a promising technology to provide comprehensive and dynamic descriptions of physical objects in cyberspace with bidirectional and real-time interactions. Moreover, Internet of Things (IoT) devices have contributed abundant, heterogeneous and continuous data from interconnected devices to the explosion of DTs. With technologies evolution, there is an increasing necessity to address the freshness of both DT states and DT data, through timely synchronizations between DTs and their objects in a highly dynamic IoT environment. …

Feddot: Defending Federated Learning Against Overwhelming Targeted Attacks, Priyesh Ranjan, Ashish Gupta, Federico Coro, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL), which facilitates collaborative model training and protects users' privacy, has drawn great interest from the research community. With FL, participants train their models on local data and submit the corresponding updates for aggregation to a server. While concealing the identities of the participants, FL may attract adversaries in order to hamper the underlying model. In this paper, we propose an FL framework, FedDOT, to defend against adversaries performing targeted attacks. FedDOT incorporates two powerful defense algorithms, Maximum Spanning Tree based attacker detection (MSTAD) and Densest graph-based attacker detection (Density-AD), which leverage correlation between weight updates and graph …

Utility-Preserving Federated Graph Learning With Dual-Perspective Fairness, Renqiang Luo, Huafei Huang, Shuo Yu, Fengqi Yu, Feng Xia, Sajal K. Das, Chengqi Zhang

Computer Science Faculty Research & Creative Works

Fairness-aware federated graph neural networks (FedGNNs) necessitate consideration of both the server and the clients. However, fairness-aware methods struggle to enhance dual-perspective (i.e., server and clients) fairness without sacrificing utility due to the distributed learning framework. As a consequence, the utility sacrifices of fairness-aware graph learning methods are even exacerbated in federated frameworks. In this work we propose F3GL, a dual-perspective fairness federated graph learning method that enhances both global (for the server) and local fairness (for clients) while preserving utility. Through theoretical analysis, we delineate the similarity between original sensitive features and those after convolution under different spectra. Our …

Escher: Efficient And Scalable Hypergraph Evolution Representation With Application To Triad Counting, S. M. Shovan, Arindam Khanda, Sanjukta Bhowmick, Sajal K. Das

Computer Science Faculty Research & Creative Works

Higher-order interactions beyond pairwise relationships in large complex networks are often modeled as hypergraphs. Analyzing hypergraph properties such as triad counts is essential, as hypergraphs can reveal intricate group interaction patterns that conventional graphs fail to capture. In realworld scenarios, these networks are often large and dynamic, introducing significant computational challenges. Due to the absence of specialized software packages and data structures, the analysis of large dynamic hypergraphs remains largely unexplored. Motivated by this gap, we propose ESCHER, a GPU-centric parallel data structure for Efficient and Scalable Hypergraph Evolution Representation, designed to manage largescale hypergraph dynamics efficiently. We also design …

Sustainable Safety Planning On Two-Lane Highways: A Random Forest Approach For Crash Prediction And Resource Allocation, Fahmida Rahman, Cidambi Srinivasan, Xu Zhang, Mei Chen

Civil Engineering Faculty Publications

During the safety planning stage, accurate crash prediction tools are critical for prioritizing countermeasures and allocating resources effectively. Traditional statistical approaches, while long applied in this field, often depend on distributional assumptions that may introduce bias and limit model accuracy. To address these issues, studies have started exploring Machine Learning (ML)-based techniques for crash prediction, particularly for higher functional class roads. However, the application of ML models on two-lane highways remains relatively limited. This study aims to develop an approach to integrate traffic, geometric, and critically, speed-based factors in crash prediction using Random Forest (RF) and SHapley Additive exPlanations (SHAP) …

Comparative Analysis Of Serum-Free Culture Conditions On Cell Proliferation And Extracellular Vesicle Production By Adipose-Derived Stem Cells, Ayna Ghulldu

Honors Undergraduate Theses

Adipose-derived stem cells (ADSCs) are promising candidates in regenerative medicine due to their proliferative capacity, self-renewal, and secretion of extracellular vesicles (EVs) that mediate intercellular communication. Serum-free media has been increasingly explored for MSC culture as it eliminates xenogeneic components, improving human therapeutic suitability. However, comparative evaluation of distinct serum-free formulations on ADSC proliferation and EV output simultaneously remains limited. This study compares a serum-containing medium to three proprietary serum-free media prototypes differing in composition, including the presence or absence of extracellular matrix proteins, to inform the optimization of culture conditions for clinical use. Proliferation, EV characteristics, and gene expression …

The Depuration Of Microplastic Pollution In Aquacultured Indian River Lagoon Oysters, Lee Nguyen

Honors Undergraduate Theses

Plastics are widely used in consumer goods and industrial manufacturing, and their degradation into microplastics (MP, size < 5 mm) has created an emergent environmental pollutant. Plastics readily enter aquatic environments, where they accumulate additional contaminants and bioaccumulate in organisms. While MP contamination in marine ecosystems is well documented, less is known about MP presence in aquacultured shellfish. Depuration, the process of purging contaminants from shellfish, is conducted in sterile seawater without food, which may cause oyster starvation and death. To date, MP depuration has not been examined in the aquacultured eastern oyster (Crassostrea virginica) in published studies. This study had 3 goals: 1) evaluate the effects of algal feed on oyster survival during depuration, 2) determine the effect of algal feed on depuration effectiveness, and 3) investigate the effect of a ten-day depuration on MP concentration in aquacultured C. virginica soft tissue. MP were quantified in oyster tissues, biodeposits, and in industrial algal feed. Tissues were digested using alkaline solutions, manually examined via microscopy, and analyzed using Fourier-Transform Infrared Spectroscopy (FTIR) to investigate MP polymer …

Caught In The Web: The Resolution Of The Internet Service Provider Contributory Copyright Infringement Split, Olivia F. Johnson

Cybaris®

No abstract provided.

Examining The Results Of Revolutions In The Third World: A Case Study Of The Iranian, Libyan, And Nicaraguan Revolutions, Noah A. Mohammedelamien

Honors Undergraduate Theses

This thesis examines the post-revolutionary trajectories of Libya, Iran, and Nicaragua to explain why some Third World revolutionary projects preserve and use elements of their founding ideology while others fragment, personalize, or diffuse over time. Rather than focusing on the causes of revolution alone, it analyzes the durability of religious-socialist ideological continuity after revolutionary upheaval. Using a (MDSD) comparative historical and institutional approach grounded in primary and secondary sources, the study evaluates five key dimensions across the cases: religious-socialist ideological fusion, religious elite loyalty, popular religious mobilization, institutional embedding of ideology, and external pressure. The findings suggest ideological continuity is …

Are Courts Developing A Consistent Standard For Sanctioning Attorneys Who Misuse Genai In Legal Filings?, Natalia Borges

Honors Undergraduate Theses

This thesis examines whether Florida courts are developing an emerging statewide standard governing attorney use of generative artificial intelligence in litigation and whether this trend supports the need for formal statewide codification. This study addresses growing concerns about fabricated citations, unverified legal research, attorney sanctions, and inconsistent disclosure practices as generative artificial intelligence becomes integrated into legal drafting and research. This research reviews the Florida Rules regulating the Florida Bar, ethics guidance on generative AI, Florida procedural certification requirements, disciplinary actions, and administrative orders from Florida judicial circuits that require disclosure and verification of artificial intelligence use in court filings. …

Beyond Full Fine-Tuning: The New Playbook For Adapting Deep Neural Networks, Cristian S. Mcgee

Honors Undergraduate Theses

Fine-tuning is the process of teaching and specializing a pre-trained neural network on a downstream task. Fine-tuning is a rapidly growing topic in artificial intelligence domains; however, many fine-tuning endeavors are highly specialized without a coherent framework connecting them. This work presents a unified perspective on fine-tuning methods and performance metrics. Our perspective organizes the methods in terms of how they are applied to fine-tuning. This framework showcases methods that (i) update effective subspaces of the pre-trained model, (ii) change the adaptation optimization procedure, and (iii) alter the representations of the embedded input. Additionally, we present unconventional metrics such as …

Deep Learning Approaches For Voltammetric Analysis Of Coffee, Ryan Koes

Honors Theses

This thesis investigates deep learning approaches for voltammetric analysis of brewed coffee using a low-cost electrochemical system and screen-printed electrodes (SPEs). Traditional analytical methods, such as high-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS), provide precise quantification of key compounds but require expensive instrumentation and specialized expertise, limiting accessibility. While SPEs offer a more accessible alternative, they yielded poor results with traditional processing; however, when combined with a neural network, the system proved more effective. In experiments with 132 coffee samples, mean errors for caffeine, CGA, and TDS predictions were 52.98 ppm, 70.48 ppm, and 0.08%, respectively. These findings …

Utilizing Computer Modeling To Optimize Electric Fields Within Xenon Time Projection Chambers, Miles Meloni

Honors Theses

XENONnT is a physics experiment designed with the goal of detecting dark matter particles. The detector is a time projection chamber; a series of charged electrodes creates an electric field, surrounding a central body filled with liquid and gaseous xenon. Photomultiplier tubes (PMTs), positioned on either end of the chamber, serve to detect light signals. We seek to minimize the root mean square of the electric field norms experienced by the PMTs. This quantity corresponds to the variance in the electric field observed by the PMTs. Establishing a consistent electric field is important to maintaining these sensitive components. The electric …

A Web-Based Wizard-Of-Oz Platform For Collaborative And Reproducible Human-Robot Interaction Research, Sean O'Connor

Honors Theses

The Wizard-of-Oz (WoZ) technique is widely used in Human-Robot Interaction (HRI) research, but two persistent problems limit its effectiveness: existing tools impose technical barriers that exclude non-engineering domain experts (the Accessibility Problem), and the fragmented landscape of robot-specific implementations makes interaction scripts difficult to port across platforms (the Reproducibility Problem- concerning execution consistency and portability, not third-party replication). Through a literature review, I identified three design principles to address both: a hierarchical specification model, an event-driven execution model, and a plugin architecture that decouples experiment logic from robot-specific implementations. I realized these principles in HRIStudio, an open-source, web-based platform providing …

Quantitative Assessment Of Roasted Coffee Freshness Over Time Using Multi-Parameter Analysis, Maya Fetzer

Honors Theses

Roasted coffee undergoes continuous chemical and physical degradation after roasting, yet industry freshness standards remain empirically defined rather than grounded in measurable parameters. This study developed a multi-parameter framework for quantifying roasted coffee freshness by integrating gas-phase and solid-phase analysis, backed by human sensory evaluation, across three roast levels — light (City+), medium (Full City), and dark (Vienna) — over a four-month storage period. CO2 off-gassing was monitored continuously for 30 day, gas chromatography-mass spectrometry (GC-MS) tracked volatile compound changes in headspace gas, and Fourier transform infrared-diffuse reflectance spectroscopy (FTIR-DRIFTS) quantified oxidation-associated functional group changes, and microindentation assessed bean stiffness. …

Barriers To Immunity: Understanding Covid-19 Vaccine Uptake In Africa, Emilia Blechschmidt

Honors Theses

This thesis examines the factors influencing COVID-19 vaccine uptake across African countries, with a focus on structural, informational, and behavioral barriers to immunization. Drawing on cross-country data, the study analyzes how access to transportation, reliable information, and healthcare resources shape vaccination rates, alongside the effect of demographics and institutional factors in shaping individual perceptions of risk and vaccine safety.

The findings emphasize that the broader strength and preparedness of national health systems strongly influence vaccine uptake. Countries that demonstrated higher coverage of routine childhood immunizations, such as polio and hepatitis B, also tended to perform better in COVID-19 uptake efficiency …

Combining Haptic Feedback With Electromyography To Study Knee Injury In Stationary Cycling, Christopher Kirby

Honors Theses

Patellofemoral Pain Syndrome (PFPS) is the most prevalent overuse injury in cycling, often linked to altered neuromuscular activation patterns of the quadriceps and hamstrings. While sensory feedback has successfully modified cyclists posture, there is a critical lack of evidence-based interventions targeting the underlying muscle activation imbalances associated with chronic knee pain. This study aimed to develop and validate a novel, real-time biofeedback system that utilizes electromyography (EMG) to trigger vibrotactile cues, aiming to shift muscle onset timing earlier in the pedal stroke to mitigate PFPS-related imbalances. A closed-loop system was engineered by integrating a Delsys EMG system with a SageMotion …

Design And Analysis Of Energy Recovery Methods For Reduced Aircraft Emissions, Joshua C. Hauck

Honors Theses

Aircraft flights are an increasingly popular mode of transportation. However, their harmful impacts on the environment are a growing concern. Many engineers have worked to develop fully electric aircraft to address this issue. Although they are much more sustainable than conventional aircraft, electric aircraft encounter severe limitations imposed by current battery technology. One alternative route engineers have taken is developing energy recovery methods (ERMs). These are marketed as devices that reduce aircraft fuel consumption without significantly changing their structure and functionality, making them an excellent short-term solution. However, there is little to no consideration of the tradeoffs induced by the …

Assessing Relations Between Rape Myth Acceptance, Prior Sexual Victimization, And Bystander Intervention Behavior, Zoe Mendel

Honors Theses

Campus Sexual Assault (CSA) remains a very prevalent issue in higher education (Koss et al., 2022). Through cultural norms, sexual violence is often normalized, with blame frequently shifted away from perpetrators and onto victims. Rape myth acceptance (RMA) contributes to harmful harmful attitudes that justify or minimize sexual violence (Lonsway & Fitzgerald, 1994). Prior research suggests that lower endorsement of rape myths is associated with greater prosocial bystander intervention behavior (McMahon, 2010); however, findings on the role of prior victimization are mixed. This study used a mix-method approach, including a survey and interviews. Results indicated that members of Greek life …

Sedimentological Characterization Of Main And Chute Channel Scroll Bars Along The Kantishna River, Alaska, Cooper Sentz

Honors Theses

Scroll bars, arcuate sediment ridges found along the inner banks of river bends, are common floodplain features in meandering river systems that form during lateral channel migration. Two hypothesized formation mechanisms described in prior studies are the aggradation of suspended load onto abandoned inner bank levee (IBL) deposits during overbank flow and the migration of transverse bar packages from the channel bed up onto the point bar during flooding events. To study the sedimentology and geometry of these features, we conduct remote sensing and field analysis on a 60 km portion of the Kantishna River, AK: a highly sinuous, pro-glacial …

A Study Of Adaptive Reuse Of A Decommissioned Golf Course Through A Nature-Based Approach: Woodhaven Golf Course, Fort Wort Texas., Justin B. Watson Mr.

Landscape Architecture Masters & Design Theses

Across the nation, golf courses are shutting down due to a lack of demand. Golf course developments began in the United States in the early 1950s During that era, demand for golf courses and housing was high. As golf’s popularity grew, developers saw golf courses in developments as high value-add amenities (Grooms, 2010). During the late 1990s and early 2000s, developers across the country raced to construct as many golf course communities as they could even as the number of golfers leveled out (Downey,2011).

Decommissioned golf courses across Texas are being underutilized as potential amenities for both the local community …

Buckling Analysis Of Auxetic Composite Laminates And Optimal Design Using Lamination Parameters And Machine Learning, Hans Bendon Maria Tamil Selvan

Mechanical and Aerospace Engineering Theses

Composite materials are widely used as structural panels in aerospace, automotive, and civil engineering applications, where buckling is often a critical failure mode. This thesis focuses on the analysis and design of composite laminates that maximize buckling performance under prescribed stiffness and thickness constraints.

The first part of the study investigates the buckling behavior of auxetic laminates, which exhibit a negative Poisson's ratio. While previous studies suggest that auxetic laminates can achieve higher critical buckling loads than non-auxetic laminates under simply supported boundary conditions with lateral restraint, the influence of other boundary conditions and plate aspect ratios has not been …