Digital Commons Network^™

2026 Workshop On Bridging The Gaps: Tackling Microplastics And Nanoplastics Challenges In Coastal Ecosystems, Shenghua Wu, Kaushik Venkiteshwaran, Melike Dizbay-Onat, Alexandra Stenson, Jinhui Wang, Tina Miller-Way, Ebenezer Nyadjro, Bhuvnesh Bharti, John Weinstein, Yi Bao, Shihui Shen, Valerie Longa, Shenghua Zha, John Cleary, Marty Lind

Workshops

This report presents the findings from the 2026 Workshop on Tackling Microplastics and Nanoplastics (MNPs) in Coastal Ecosystems, which took place in Mobile, Alabama. More than 140 experts from universities, government, industry, and community organizations gathered to address the increasing issue of MNPs in coastal regions.

Simultaneous Carrier, Cargo, And Functional Tracking Of Lipid Nanoparticles, Hannia Vanessa Balcorta Muñoz

Open Access Theses & Dissertations

Lipid nanoparticles (LNPs) have become effective delivery vehicles in nanomedicine, particularly for nucleic acid-based treatments. However, a major limitation remains in the field regarding the simultaneous monitoring of the nanoparticle carrier, its encapsulated payload, and the resulting functional protein production in both in vitro and in vivo systems. Furthermore, traditional lipophilic dyes employed for labeling LNPs frequently exhibit incompatibility with tissue-clearing methods, such as CLARITY, due to signal loss following lipid removal. This research developed and evaluated a new fluorescent labeling method using CM-DiI, a dye that reacts with thiols, for multimodal tracking of LNPs. CM-DiI was included in the …

Developing Warning Signage For Harmful Algal Blooms At Lake Fayetteville, Abigail R. Evans

Biological Sciences Undergraduate Honors Theses

The presence of harmful algal blooms (HABs) poses many risk factors for human health, and once microcystin concentration has reached a certain level, that water source will be closed for the duration of the bloom. Agencies tend to use static signage with limited information to inform the public about the current status of the water, but a sign similar to the one used by the National Fire Danger Rating System can allow for constant updates detailing specific risk levels for the public. Using previously reported data on Lake Fayetteville, thresholds for risk factors that are easily measurable were determined. The …

Developing Transparent Sustainability Data Systems In A Poultry And Pet Food Company: An Internship Case Study, Catherine L. Warren

Biological and Agricultural Engineering Undergraduate Honors Theses

My honors thesis examined my internship experiences and its implications on sustainability data gathering and reporting in poultry and pet food companies. It highlighted my internship projects, the skills I developed, and the connections to sustainability data transparency and reliability in a corporate environment.

In my thesis, I shared details about my internship. I described what projects I worked on, the places I visited, the hands-on experience I gained, and the different teams I worked with throughout the internship duration. I discussed the analytic and professional skills I developed through conducting a waste audit, developing Tableau dashboards, and helping to …

Cross-Facility Reliable Deep Learning Based Beef Marbling Assessment Via Unsupervised Domain Adaptation Regression, Samuel Vinson

Biological and Agricultural Engineering Undergraduate Honors Theses

Inconsistent quality grading in beef production leads to inefficiencies, economic disparity, and consumer mistrust. While USDA meat grading traditionally relies on skilled visual inspectors, these human evaluations suffer from cross-facility variability and subjectivity. This paper introduces the first known application of unsupervised domain adaptation regression for cross-facility beef marbling score prediction—an innovation that improves generalization across diverse environments in the beef supply chain. Utilizing numerical scores ranging from 100-900, the research employed convolutional neural networks (CNNs), including ResNet, VGG, and AlexNet architectures. The study specifically introduced and validated a unified unsupervised domain adaptation regression method using the ResNet-50 architecture to …

Per- And Polyfluoroalkyl Substances (Pfas) In Cave And Withrow Springs, Arkansas, Luke A. Ahlemeier

Biological and Agricultural Engineering Undergraduate Honors Theses

The class of chemicals known as Per- and Polyfluoroalkyl Substances (PFAS) are believed to be widespread in the natural environment, but the full extent of PFAS prevalence is not well understood, particularly in karst springs. The objectives of this study were to (1) collect water samples from Cave Springs and Withrow Springs, Northwest Arkansas, (2) measure for concentrations of 40 PFAS compounds using EPA Method 1633, and (3) compare differences in PFAS concentrations and discuss potential sources of PFAS for each spring. Each spring was sampled on September 29, 2025, October 13, 2025, and November 10, 2025, and water samples …

Exploring Cognitive Load Theory In The Post-Secondary Engineering Classroom, Gabriel Q. Van Dyke

All Graduate Theses and Dissertations, Fall 2023 to Present

Engineering programs often emphasize subject-matter expertise over pedagogical training, which can leave students struggling with course demands and contribute to retention challenges. This study applied Cognitive Load Theory (CLT) to examine how undergraduate engineering students experience the cognitive demands of their coursework compared to non-engineering classes. Using a sequential explanatory mixed methods design, cognitive load surveys were followed by interviews to address two research questions: (1) What are the differences in intrinsic and extraneous cognitive load levels between engineering courses and non-engineering courses taken concurrently by undergraduate engineering students? (2) How do engineering students perceive the unique challenges or benefits …

Spectral Characterization Of Colorectal Cancer Using Excitation-Scanning Hyperspectral Imaging, Natalie Hadad

Honors Theses

Colorectal cancer is one of the most common and deadly cancers worldwide, with a lifetime risk of approximately one in twenty-three for men and one in twenty-five for women. Although early detection significantly improves survival, current diagnostic approaches such as tissue biopsy are invasive, reliant on subjective interpretation, have extended turnaround times, and risk missing flat or depressed lesions that are more difficult to detect than raised polyps. These limitations highlight the need for objective, minimally invasive technologies capable of detecting early tissue changes. This study investigates excitation-scanning hyperspectral imaging (Ex-HSI) as a label-free optical approach for identifying colorectal cancer–associated …

Experimental Data-Driven System Identification Of Scale-Model Airboat Dynamics For Control And Autonomy Applications, Miguel A. Trejos

LSU New Orleans Theses and Dissertations

To achieve autonomous control of a surface watercraft requires an accurate model describing the dynamics of the system. To this end, the modeling of dynamics of an airboat with a combustion engine-based propulsion system is investigated. Specifically, a black-box data-based approach using neural networks. To facilitate this, a custom data collection system was developed to record linear and rotational motion during field tests. Due to the airboats unique ability to traverse different terrains, not just water, the modeling of dynamics on different terrains was investigated.

Beyond Local Pathology: Exploring The Role Of Gut Microbiota In Chronic Low Back Pain Using An Integrated Behavioral And Microbiological Approach, Adan L. Redwine

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Chronic low back pain (LBP) affects millions worldwide, often originating from intervertebral disc (IVD) degeneration. While the gut microbiome modulates musculoskeletal pain, prior studies of the gut-disc axis have focused entirely on structural changes. This leaves a critical gap: does the microbiome influence the experience of discogenic pain? To answer this, an integrated approach using longitudinal gut microbiome profiling, machine learning-based behavioral phenotyping, and structural disc assessments in a rat model of discogenic LBP was utilized.

Female Sprague Dawley rats underwent one of four conditions: sham surgery, IVD injury, antibiotic-mediated microbiome depletion + IVD injury, or IVD injury + treatment …

Design, Simulation, And Experimentation Of A Box Barge Model Under Asymmetrical Conditions, Kylie Sink

Senior Honors Theses

This study investigates the ability of numerical simulations to predict vessel motion responses under asymmetrical loading conditions. A raked barge model was designed, constructed, and tested in a towing tank to evaluate the response amplitude operators (RAOs) for heave, roll, and pitch under various wave conditions. The model included six internal compartments that allowed different flooding scenarios to be simulated in order to create asymmetric loading conditions. Experimental testing was conducted under head seas (0 degrees) and beam seas (90 degrees) with multiple wave periods.

A numerical model of the vessel was developed using GHS to generate predicted RAOs for …

Exploring The Role Of Video Games In Civil Engineering Education And K-12 Stem Engagement, Jillian S. Codron

Architectural Engineering

Civil engineering education has traditionally emphasized a linear progression from theory to application, with foundational concepts introduced in lecture before being reinforced through laboratory or design experiences. While effective for advanced learners, this approach can limit early engagement for K–12 students who may struggle to connect abstract principles to realworld engineering practice. This project examines the use of video games as interactive, feedback-driven environments for introducing civil engineering concepts and practices to younger learners in more exploratory and accessible ways.

The study pursues four primary objectives: evaluating the educational affordances of selected video games; examining how gaming experiences have influenced …

Preclinical Animal Modeling To Investigate Redox-Mediated Molecular Dysfunction In Traumatic Brain Injury, Brandon Z. Mcdonald

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Impacts associated with traumatic brain injury (TBI) induce a multitude of neurological morbidities mediated by a spread of biochemical dysfunction. Redox stress is a significant contributor to TBI pathophysiology and several redox stress markers have substantial evidence to support their role in diagnosing preclinical and clinical TBI. However, there is a critical need to verify their translational utility through correlations with behavioral, imaging, and molecular modalities. In chapter two, we examined the therapeutic efficacy of an antioxidant treatment (NPC3) using a controlled cortical impact (CCI) mouse model of TBI. NPC3 alleviated glial expression and reactivity while influencing the expression of …

Sheep Pen Improvements At City Farm Slo, Ryan S. Bodmer

Construction Management

City Farm SLO is an urban non-profit educational farm located in San Luis Obispo, CA. It serves the community through offering farm learning programs, including hands-on experience in sustainable farming practices and livestock care. This project, completed over the winter and spring quarters, focused on delivering an upgraded sheep pen to improve access and safety for both volunteers and sheep. The project consisted of developing design plans, coordination of materials and allowable working times with the owner, where the animals were either moved out of the working area or when work would not jeopardize animal health, schedule creation, cost estimates, …

Impact Of Biomass Type On Hydrocarbon Yield And Chain Length Distribution Produced Via Fischer-Tropsch Synthesis, Nicholas R. Hawe

Honors Scholar Theses

This paper investigates the relationship between biomass composition and hydrocarbon yield as well as chain length distribution produced by Fischer-Tropsch synthesis. Through an Aspen Plus model, the conversion of three different biomasses – digestate, sawdust, and corn stover – into hydrocarbon fuel was simulated. The model converts biomass into gaseous and liquid hydrocarbons via various unit operations and reactions. Simulation results highlight the product distribution and hydrocarbon output, allowing for an analysis of hydrocarbon yield and comparison of chain length distributions amongst the three biomasses. Overall, the simulation showed biomass composition had no significant impact on hydrocarbon yield or chain …

A Novel Approach To Creativity Assessment: Forced Pairwise Ranking With Large Language Models, Phillip R. Gregory Jr

Master's Theses

Assessing creativity at scale remains a persistent challenge in cognitive science, as human raters are costly, slow, and often inconsistent in their judgments. This thesis introduced a novel framework for automated scientific creativity assessment using forced pairwise ranking, in which fine-tuned large language models compared response pairs and determined which was more creative. Five empirical studies were conducted using Llama-2-7B and Llama-2-13B models adapted via LoRA fine-tuning and benchmarked against human scored responses from the Scientific Creative Thinking Test. A regression baseline achieved Pearson �� = .74 on the test set, matching the human inter-rater ceiling reported in the literature. …

Design And Development Of A Perfusable Hydrogel Platform With Bioprinted Human-Endothelialized Microvascular Channels, Calvin A. Chernyatinskiy

All Theses

We developed an integrated bioprinting and perfusion platform to generate vascularized hydrogel constructs that support perfusable microchannel networks. Multiple hydrogel formulations, sacrificial ink systems, device geometries, and perfusion conditions were systematically evaluated to optimize print fidelity, mechanical stability, and cellular compatibility. Internally gelling alginate–calcium carbonate hydrogels were identified as a robust matrix, providing tunable gelation kinetics and structural stability during embedded printing. In parallel, Pluronic F-127 fugitive ink enabled reliable fabrication of continuous hollow channels due to its shear-thinning behavior and efficient post-print removal.

The finalized platform integrates stereolithographically fabricated perfusion chambers with extrusion-based bioprinting to produce three-dimensional, perfusable vascular …

Moodify: A Mood-Based Music Recommendation System, Meghana Kagitha

Theses and Dissertations

Music has long been recognised as a powerful tool for emotional regulation, yet existing music streaming platforms often fail to align song recommendations with a user's current emotional state. Moodify is a mood-based music recommendation system designed to bridge this gap by delivering personalised playlists that reflect how a user feels in real time.

This project presents the design, development, and evaluation of Moodify, a mobile application that leverages the Circumplex Model of Emotion to capture user mood through an intuitive two-dimensional valence-arousal interface. Rather than relying on text input or manual search, users plot their emotional state directly onto …

Dor-E: Final Design Report, Arav Singh, August Hogen-Esch, Bruce Le, Patrick Mcgee, Spencer Major

Mechanical Engineering

I. PROBLEM STATEMENT

The Chumash Heritage National Marine Sanctuary contains a diverse array of benthic habitats that remain largely undocumented due to the financial and logistical barriers of deep-sea exploration. Traditional high-end autonomous underwater vehicles and remotely operated vehicles capable of reaching 1000-meter depths require significant surface support infrastructure and hundreds of thousands of dollars in funding. Furthermore, navigating protected ecological zones demands strict adherence to "Leave No Trace" principles. Conventional benthic landers and submersibles routinely leave metallic debris behind; many submersibles use galvanic timed releases that corrode in seawater over a set period of time or heat-activated bolts to …

Baseline Cervical Intervertebral Disc Biomechanics And Implications For Allograft Preservation, Nathan F. Buchweitz

All Dissertations

Neck pain has become an increasingly common orthopaedic healthcare issue. Evidence shows that degeneration of cervical intervertebral discs (the cartilage between the spinal vertebrae in the neck) may be associated. While disc degeneration in the lumbar spine has been extensively studied in relation to low back pain, it has received less attention in the cervical spine. Biomechanically, the cervical (neck) and lumbar (lower back) regions of the spine differ in function. Lumbar discs resist a greater burden of body weight, whereas cervical discs are adapted for mobility to aid flexible head orientation. Despite these key differences, disc injury and degeneration …

Enhancing Food Security In Stann Creek, Belize Using Meat Rabbits: Engineering Perspective, Lindsey Garretson

Biological and Agricultural Engineering Undergraduate Honors Theses

The purpose of this paper is to discuss the engineering perspective within the overall project of using meat rabbits to enhance food security and nutrition within Stann Creek, Belize. From the engineering perspective, the overarching goals were like the overarching project goals including the construction and materials required guide within the manual, designing potential upgrades to the design including a solar and battery system and an automatic watering system, and to design the system to be “practically sustainable” where possible. The constraints for this project included cost, the size of land dedicated for the rabbitry, and the operational and environmental …

Versatile Exoskeleton Control Paradigms For Agile Human Locomotion: Task-Agnostic And Stability-Augmented Assistance, Miao Yu

All Dissertations

Lower-limb exoskeletons have shown great potential for assisting human locomotion, but designing controllers that provide assistance across diverse locomotor tasks and under external perturbations remains a major challenge. Many existing controllers for steady-state walking rely on pre-defined reference trajectories, which constrain voluntary human motion and limit adaptability across tasks. Moreover, they usually assume stable walking, while their performance under unstable conditions remains largely unexplored. In addition, existing gait stability augmentation controllers are often reactive rather than proactive to unstable conditions. In this dissertation, we propose control frameworks that preserve voluntary human motion while addressing two major challenges: providing task-agnostic assistance …

A Low-Cost Motion Classification System For A Stuffed Animal Using An Imu And Machine Learning, Rachel N. Guynes

Honors Theses

One of the many fields that has seen the integration of robots is therapy. Zoomorphic robots (ZR) are designed to look and behave like animals to assist in Animal Assisted Therapy (AAT) practices. Studies show that ZRs can provide benefits similar to working with an actual animal; however, their high cost limits their accessibility. This thesis documents the process of building a real-time, low-cost motion classification system that can be attached to a stuffed animal to make it more interactive. Using a Random Forest (RF) classifier, the system identifies movements with approximately 81.67% accuracy.

Quantitative Fluorescence Imaging Using A Paired Agent Approach For Improving Surgical Decision Making, Sanjana Pannem

Dartmouth College Ph.D Dissertations

Surgical resection remains to be the cornerstone of treatment for most solid tumors, where the primary objective is to remove all visible and microscopic disease. However, the extent of tumor resection is inherently limited by the surgeon’s ability to distinguish tumor from normal tissue, intraoperatively. As a result, positive surgical margins (PSM), where residual tumor remains after surgery, are a common occurrence and are associated with increased recurrence, need for adjuvant therapies, dismal patient outcomes, and high healthcare costs.

Fluorescence guided surgery (FGS) has emerged as a promising technique to enhance intraoperative visualization of tumors and may help reduce the …

Uncertainty Handling In Stock Market Prediction: A Fuzzy Markov Chain Approach, Alpa Singh Rajput, Arpan Singh Rajput

Neutrosophic Systems with Applications

Predicting the stock market is never easy because it is influenced by many uncertain and constantly changing factors such as economic conditions, investor behaviour, and global events. Traditional models like the Crisp Markov Chain (CMC) try to predict market movements by using fixed probabilities for different states like bullish, bearish, or stagnant. However, real markets do not behave in such a strict way—they often move gradually between states, which these models fail to capture. To overcome this limitation, this study introduces a Fuzzy Markov Chain (FMC) model, where fuzzy logic is used to handle uncertainty and allow smoother transitions between …

Modeling Agentic Artificial Intelligence Uncertainty In Agriculture Based 6generation: A Hybrid Q-Rung Orthopair Fuzzy Mcdm Methodology, Zekra Sakr, Mona Mohamed

Neutrosophic Systems with Applications

In era of advanced intelligent revolutions, the collaboration between intelligent technologies became imperative. For instance, integrating 6G communications with agentic artificial intelligence considered a catalyst to shift agriculture sector into optimized and intelligence sector. This integration resulted in transitioning the sector from static automation to autonomous, agent-based ecosystems. Accordingly, the efficiency roles for artificial intelligence agents (AIAs), deploying and selecting optimal AIA is important. Yet, selection process is still difficult because agricultural criteria are multifaceted and there are inherent environmental uncertainties. To address these challenges and bolster the selection process, this paper suggests a hybrid multi-criteria decision-making (MCDM) that bolstered …

An Improved Logarithmic Ratio-Product Type Estimator For Mean Modeling And Estimation Under Neutrosophic Uncertainty, Anchal Yadav, Mukesh Kumar

Neutrosophic Systems with Applications

In classical statistics, population mean estimation generally assumes precise and determinate data along with known auxiliary information. However, in real-world situations where observations are imprecise or expressed in interval form, such as temperature variations or financial market data, classical approaches become less effective. To address this limitation, neutrosophic statistics provide a more flexible framework for handling uncertainty and indeterminacy. This study proposes a neutrosophic logarithmic ratio-product type estimator for estimating the finite population mean using auxiliary information. The bias and mean squared error (MSE) of the proposed estimator are derived using a first-order approximation. Furthermore, performance evaluation is carried out …

Enhanced Parametric Approach For Solving Interval-Valued Trapezoidal Neutrosophic Linear Fractional Programming Problems, Hamiden Abd El- Wahed Khalifa H.A.Khalifa, Moodi Abdulrahman Abdullah Al-Rajeh, Sultan S. Alodhaibi

Neutrosophic Systems with Applications

Neutrosophic sets (NSs) generalize the classical versions, by providing a flexible framework capable of representing incomplete, inconsistent, and unclassified data that frequently arises in practical decision frameworks. In this study, a linear fractional programming (LFP) problem with uncertain parameters is investigated. All coefficients in the objective function (OF) as well as the left- and right-hand sides of the constraints are represented using fully trapezoidal neutrosophic numbers (NNs). By employing a suitable score function, the proposed neutrosophic LFP model is transformed into an equivalent scalar LFP problem. Subsequently, a parametric solution procedure is established to regulate the neutrosophic optimum solution. This …

Gauss Elimination Method For Solving The System Of Neutrosophic Linear Equations, Elsayed Badr, Shokry Nada, Saeed Ali, Aya Rabie

Neutrosophic Systems with Applications

This paper proposes a unified computational framework for solving linear systems under trapezoidal Neutrosophic uncertainty. The system is formulated as A( I )x = b( I ), where both the coefficient matrix and the right-hand side vector incorporate an indeterminacy parameter I, expressed as A( I ) = A₀ + IA₁ and b( I ) = b₀ + Ib₁. A decomposition strategy is developed to separate the model into deterministic and indeterminacy components, yielding a solution of the form x( I ) = x₀ + Ix₁. The deterministic component is obtained via …

Mapping The Void In Electric Vehicle (Ev) Adoption Research: Uncovering Lack Of Socio-Economic Study In The Global South, Satvik Pandey, Rahul Tiwari, Rajat Soni

Mansoura Engineering Journal

Electric Vehicles (EVs) are considered an effective contemporary alternative to Internal Combustion Engine (ICE) vehicles. Research in the domain of EV is being conducted globally across a variety of fields; among them, our study explored research on consumer adoption. Going through the bibliometric analysis of the data taken from the Scopus database, what came to our attention is the minimal amount of work that is done on understanding consumers of EVs. From the literature, we found that consumer preferences are shaped through the influence of several parameters related to EVs, and this influence varies according to the consumer’s socio-economic and …