Digital Commons Network^™

The Prospect Of F.E.W. Resources: How Food, Energy, And Waste Management Workforce Programs Address Global Equity And Sustainability, Quincy P. Biddle

Student Theses 2015-Present

As a global society, the issues affecting a specific city or country are no longer isolated; instead, they impact other places in myriad ways. Over the past few decades, environmental degradation and economic inequality, both within and between countries, have caused shortages of necessities like food and water, inadequate access to safe energy sources, and increased pollution, impacting people’s prosperity and the well-being of the planet. It is of global interest to remediate these issues for the betterment and progress of society, and thus, an approach to addressing these complications collectively and comprehensively is of utmost importance. This paper investigates …

Solid Waste Management In Greater Khartoum City, Sudan, Roba Mahmoud

Student Theses 2015-Present

This study investigates the rising solid waste management (SWM) dilemma in Greater Khartoum City (GKC), a critical environmental and public health issue caused by fast urbanization and inadequate infrastructure, with historical linkages to Sudan's colonial and postcolonial growth. Chapter 1 describes the current problem using quantitative and qualitative data, demonstrating that GKC produces approximately 3,340 tons of waste each day, with 56% organic matter, 8% plastics, and 16% paper. Collection efficiency remains severely poor, at 31.5%. Informal recyclers known as Nakasha or Barkata collect approximately 7% of total waste, supporting roughly 3,900 people, whereas filthy open dumps and unsorted medical …

How Ai Governance Differs Between Regime Type, Jackson T. Guillou

Honors Theses

This thesis will examine how artificial intelligence (AI) regulation and development differ across political regime types, arguing that governance outcomes are fundamentally shaped by institutional political structures. This thesis will draw on comparative frameworks analyzing democratic and authoritarian systems. This thesis will also include case studies of the European Union, the United States of America, China, and Russia. The study finds that democratic regimes tend to emphasize transparency, accountability, and rights-based regulation of AI. This often results in slow regulation of AI, but it is more ethically legitimate and constrained. In contrast, authoritarian regimes prioritize centralized control, strategic coordination, and …

Automated Evaluation Of Web Accessibility In Cybersecurity Tools, William Robert Cox

Theses and Dissertations

Screen reader users face significant barriers when using web-based cybersecurity tools, however, the accessibility of these interfaces has received minimal systematic research attention. Existing automated evaluation tools assess Web Content Accessibility Guidelines (WCAG) conformance but do not measure the practical operability of complex and domain-specific interfaces for users of assistive technology. This dissertation presents the Deciphering Interfaces for Your Accessibility (DIYA) framework, an open-source automated auditing framework that evaluates cybersecurity tool web interfaces across eight normalized dimensions: WCAG conformance, Accessible Rich Internet Applications (ARIA) usage, semantic structure, keyboard operability, form accessibility, dynamic content accessibility, interaction cost, and screen reader readiness. …

A Socio-Computational Framework For Understanding Information Campaigns Through A Collective Action Perspective, Sayantan Bhattacharya

Theses and Dissertations

In a time when social media significantly influences public dialogue, grasping the elements that contribute to the success of information campaigns has become vital for understanding modern social movements and political engagement. This dissertation explores the essential factors that affect the efficacy of information campaigns across digital platforms, addressing a notable gap in existing research that frequently neglects the systematic connection between information spread and outcomes of collective action. Instead of viewing these as distinct phenomena, this study constructs an integrated framework that highlights three crucial dimensions of successful information campaigns: the human factor, which emphasizes the role of influential …

Liquefaction Susceptibility And Brittleness Of Coal Ash - A State Parameter Approach, Suafa'i Manson, Benoit Wentzinger, Scott Lines

World of Coal Ash Proceedings

Limited data exists on the liquefaction susceptibility of combined fly ash and bottom ash deposits. Their low plasticity and settling density pose a risk of liquefaction under certain triggers. The liquefaction potential is linked to the in-situ state, defining its shearing behaviour as dilative or contractive based on relative density and effective confining stress. This can be assessed using the state parameter (Ψ) concept from critical state soil mechanics theory. This paper presents findings from a follow-up to our 2021 study, which used cone penetration test (CPT) based methods to estimate the in-situ state parameter and perform liquefaction susceptibility screening. …

Toward The Salmon Prize: A Computational Certificate For The M5, M6, And M9 Equation Families Of Σ4(P3 × P3 × P3), John Trevino

Theatre Faculty Publications

We present a computational certificate for three families of explicit polyno- mial equations whose zero locus contains the fourth secant variety σ4(P3×P3×P3) inside P63. The three families are: 192 degree-5 Strassen commutation equa- tions (M5); 160 degree-6 equations lifted from the Bates–Oeding generators of σ4(P2 × P2 × P3) via the Landsberg–Manivel–Friedland theorem (M6); and 64 degree-9 Ottaviani 9 × 9 determinant equations (M9). All 416 generators are explicit polynomials in the coordinate ring Z[Zijk | i, j, k ∈ {0, 1, 2, 3}]. We verify by exact integer arithmetic that every generator vanishes on rank-4 test tensors (six independent …

Predicting And Decoding Allosteric Binding Sites Using Protein Language Models And Structure-Based Machine Learning: An Energy Landscape-Guided Explainable Ai Framework, Kamila Riedlová, Vít Skrhák, William G. Gatlin, Max Ludwick, Lucas Turano, Marian Novotný, David Hoksza, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Computational prediction of allosteric binding sites in protein structures remains a persistent challenge, as these regulatory pockets evade detection by both sequence-based and structure-based algorithms. Both computational and physical origins of this predictive asymmetry remain insufficiently understood. In this study, we systematically examine the determinants of binding site predictability using a dual framework that integrates a fine-tuned protein language model and the structure-based method P2Rank as complementary tools probing a diverse data set of 453 human kinases, together with a physics-based interpretability layer derived from energy landscape frustration analysis. Both predictors exhibit a sharp and reproducible dichotomy on protein kinases, …

Sustainability And Waste Diversion At Tva Shawnee "Project Phoenix", Bryan Jacob, Shane Harris

World of Coal Ash Proceedings

An engineered turf closure system can serve as an ideal foundation for a solar energy system to be installed atop coal combustion residual (CCR) impoundments. This approach not only enables productive power generation during the post-closure period, it also preserves opportunities for recovery and beneficial use of CCR material in the future. “Project Phoenix” at TVA’s Shawnee Fossil Plant offers an illustrative example. This paper will cover the sustainability benefits of the companion ClosureTurf® and PowerCap® systems installed at that site as well as waste diversion activities undertaken during construction to recycle as much as practical and minimize waste destined …

Demystifying Large Language Models: How Ai Is Transforming Data, Compliance, And Decision-Making In Coal Ash And Environmental Management, Scott Pfeiffer

World of Coal Ash Proceedings

The environmental and coal combustion residuals (CCR) industries generate vast amounts of information—from groundwater monitoring reports and RCRA documentation to closure plans and analytical data. Managing, interpreting, and communicating this information is a growing challenge for utilities, regulators, and consultants alike. Large Language Models (LLMs), such as OpenAI’s GPT architecture, represent a breakthrough in how organizations can interact with their technical data. These models use deep neural networks trained on billions of words to understand, summarize, and generate language with human-like accuracy. When securely adapted for enterprise use, LLMs can automate routine reporting, extract data from technical documents, generate regulatory …

Online Legislation: Developments And Trends In Data Privacy And Software Development, Garrett J. Splinter

Honors Program: Senior Projects (Public)

The increasingly relevant interaction between the law and data privacy, as well as compliance requirements enforced by the United States, is currently in a state of transition. Various states, such as California, Colorado, Connecticut, Nebraska, and many others, all have passed legislation with varied requirements and definitions that make for a challenging framework in which software developers operate, as the universal nature of the internet renders their compliance with current legislation a challenge. Enforcement also tends to be relatively relaxed in most modern examples, though it has escalated after 2020, and this trend may continue in the future, lending credence …

Radar Spoofing Attacks And Their Impact On Sensor Fusion-Based Perception For Autonomous Vehicles, Ahmad Mohammed Bara

Student Theses

Safe autonomous vehicle (AV) operation depends on robust perception of the surrounding environment. While multimodal sensing—integrating cameras, LiDAR, and radar—provides comprehensive environmental awareness, radar’s robustness under adverse conditions has made it a critical component of modern perception pipelines. However, the security vulnerabilities of radar within these fusion architectures remain largely unexplored. This work presents an end-to-end analysis of radar spoofing attacks on learning-based radar–camera fusion systems. Using a simulation framework grounded in reflect-array attack models, we inject physically plausible perturbations into radar measurements by altering depth by and velocity, while maintaining crossmodal consistency. Evaluation on the nuScenes dataset shows that …

Evaluation In Applied Ai: Predictive Modeling, Agent Safety, And Model Validation, Tanmay Sah

Harrisburg University Dissertations and Theses

This dissertation focuses on three applied challenges in machine learning and artificial intelligence: predicting social media content virality, evaluating safety in tool using large language model agents, and standardizing model validation in regulated settings. Across these domains, the dissertation argues that evaluation in applied AI must be matched to context, combining predictive performance with the relevant evidence needed for interpretability, safety, reproducibility, and governance readiness. First, Decoding Reddit Memes Virality extracts and analyzes 16,968 posts using computer vision, natural language processing, and gradient boosting to identify visual, textual, and temporal signals associated with virality. Second, The Verifier Tax designs and …

Perspectives On Interpretability For Neural Text Representations, Jia Peng Lim

Dissertations and Theses Collection (Open Access)

In this dissertation, we investigate interpretability in the three elements of learning neural text representations: inputs, passed into models, to produce probabilistic outputs. We emphasise perspectives as we present alternative novel methods to mine and organise meaning in this work.

Models. We initiate our investigation by examining Neural Topic Models (NTM), proposing an alternate angle of interpreting its word-topic distribution, producing better topic representations for interpretation. Our method maps the problem of finding these better interpretations to classical NP-hard graph problems, enabling examination of topic distributions in a composite manner. Next, we apply our previous findings to extract interpretations from …

The Cobalt Curse: Cobalt’S Role And Risks, Marley Jackowitz

Student Theses 2015-Present

This paper examines the hidden environmental, geopolitical, economic, and social costs of the cobalt supply chain. Fueled by the demand for battery technology and electric vehicles, cobalt has become an essential element to the green energy transition. With the largest share of global cobalt deposits, the Democratic Republic of the Congo bears a disproportionate share of the industry’s harms. Cobalt mining in the DRC is marked by environmentally degrading practices and inhumane working conditions, compromising Congolese health, safety, and well-being. Chapter 1 discusses the environmental impacts of DRC cobalt mining and its adverse effects on public health. Environmentally degrading mining …

A Forecasting Framework For Distribution Center Capacity Utilization: An Applied Industry Study, Jordan J. Shortt

Data Science Undergraduate Honors Theses

This project develops and evaluates a predictive modeling framework for forecasting distribution center capacity utilization at Company Y, with monthly forecast horizons up to one year. Motivated by the operational challenges of seasonal demand volatility, promotional cycles, and the absence of a formally defined capacity metric, the study first constructs a historical capacity utilization measure from raw warehouse management system data — reconciling item volumes, location dimensions, and utilization factors across all DCs — which serves as the target variable for all modeling work. Four models are developed and evaluated against a naïve seasonal baseline: SARIMA, LightGBM, LSTM, and a …

Recursion, Regurgitation, And Regeneration: Testing Limits And Revealing Biases Of Generative Ai Models Through Multimodal Feedback Loops, William Donnell-Lonon

Data Science Undergraduate Honors Theses

Contemporary generative AI systems such as OpenAI's GPT-4o and DALL-E models embed complex priors about society, reality, and history shaped by training data distributions, social alignment procedures, legal constraints, and safety regulations. This study uses a "telephone game" methodology to investigate how embedded social, political, and visual biases propagate and reveal themselves through iterative multimodal generation loops, where image captioning and text-to-image models are chained in successive feedback cycles.

Using CLIP similarity metrics, facial recognition algorithms, semantic drift analysis, and qualitative content observations, I tested how image subject matter affects the rate and quality of semantic and visual shift, identity …

Cyanine Dyes As Next-Generation Fluorophores: Applications In Cell Sorting And Fingerprinting Technologies, Super-Multiplexed Spectroscopy, Biomedical Imaging, And Beyond, Lucas Allen Davis

Undergraduate Honors Thesis Collection

As biochemical, pharmaceutical, and medical sciences advance, the demand for technologies capable of probing multiple cellular targets simultaneously continues to increase. Super-multiplexed spectroscopic techniques offer a pathway toward comprehensive cellular fingerprinting by overcoming the spectral limitations of conventional fluorescence labeling. By circumventing the traditional “color barrier,” cyanine-based Raman tags enable the simultaneous discrimination of numerous cellular morphologies, allowing spectroscopy and imaging to be integrated for high-dimensional cellular analysis. Technologies developed in Goda Lab—including high-throughput flow cytometry, virtual freezing fluorescence imaging (VIFFI), Fourier-transform coherent anti-Stokes Raman spectroscopy (FT-CARS), and MERdot nanoparticles—address longstanding trade-offs between throughput, resolution, sensitivity, and multiplexing capacity. Central …

Collective Dissipative Charging And Energy Extraction In Quantum Batteries, Sagar Pokhrel

Graduate Theses and Dissertations

In this dissertation, we investigate the charging and discharging dynamics of a quantum battery composed of a collectively driven ensemble of $N$ identical two level systems coupled to a structured electromagnetic environment. The system is described using collective angular momentum operators in the Dicke basis, which provides a compact and physically transparent framework for analyzing collective light-matter interactions. Rather than treating dissipation as an unwanted source of loss, we explicitly use it as a mechanism for energy storage and work extraction. Starting from a coherently driven ensemble coupled to common reservoirs, we derive a master equation in Lindblad form under …

Urban Heat Mitigation In Newark, New Jersey Using Remote Sensing And Spatial Analysis, Ama Akowa Rhule

Theses, Dissertations and Culminating Projects

This study examines urban heat patterns in Newark, New Jersey, using remote sensing and spatial analytics to support targeted mitigation strategies. Land Surface Temperature (LST) was derived from a Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) scene acquired on July 28, 2025, representing a summer snapshot of surface thermal conditions. While urban heat island effects are typically considered long-term climatic phenomena, this study uses a single-date observation to capture spatial variability in temperature across the city. Land cover variables, including tree canopy and impervious surface fractions, were obtained from the National Land Cover Database (NLCD), and demographic variables, including …

Mineralogy, Geology, And Geochemistry Of The Mcafee Quarries And Greater Mcafee Area, Sussex County, New Jersey, Cristian J. Van Rossen

Theses, Dissertations and Culminating Projects

The Franklin Marble is one of North America’s most famous geologic units, a result of its complex geology, diverse mineralogy, and significant ore deposits. While it has been widely studied, a location that has received little attention is that of the quarries at McAfee, Vernon Township, NJ. This study addresses this oversight by investigating the mineralogy, geology, and geochemistry of the marble and associated geologic units found in the area. Sample analysis consisted of physical and optical analysis as well as chemical analysis using SEM-EDS. Geochemical analysis using ICP-MS allowed for major, trace, and rare earth element concentrations of select …

Implementation Of A Droplet Interface Lipid Bilayer System For Electrical Characterization, Olivia J. Ziemer

Honors Theses

Lipid bilayers are the fundamental structural framework of cell membranes, providing cells with both protection from the environment and interaction with the surrounding environment. Experimental investigation of lipid bilayers and embedded protein channels often involves the formation of an artificial membrane within an electrical circuit. The focus of this project is to implement and verify the functionality of a lipid bilayer characterization technique known as the droplet interface bilayer (DIB), with emphasis on cost-effective system design. To achieve this, the amplifier and software from the ELEMENTS black lipid membrane (BLM) kit were repurposed to reduce the cost of implementing a …

Bottles, Butterflies, And Biomass: Recycled Glass Sand, Microbial Additions, And Herbivory Effects On Milkweed Growth, Kealey Skinner

Honors Theses

Plant-soil-microbe interactions are integral components of ecological networks and drive ecosystem function from the bottom-up. Whereas herbivores regulate ecosystem function from the top-down, having opposing and potentially complementary effects on ecosystem function. My thesis sought to understand how below-ground microbial communities contribute to herbivore preference and plant biomass across varied soil substrates. My thesis asked: how do substrate and soil microbial communities influence herbivore preference and plant biomass accumulation on swamp milkweed (Asclepias incarnata)? To address this question, seedlings of A. incarnata were sown in 2.5 cm wide × 10 cm deep pots filled with either natural beach sand or …

Grazed Pasture Effects On Greenhouse Gas Emissions In The Ozark Highlands, Tyler Buchanan

Graduate Theses and Dissertations

In the United States (US), grazinglands serve as the main foundation for the livestock industry, and, in Arkansas specifically, pastures are essential for rotational grazing and dairy operations. Climate change is increasingly becoming a concern in the agriculture industry, largely caused by anthropogenic activities increasing greenhouse gas (GHG) concentrations in the atmosphere, at least partly due to the nutrient recycling that occurs from animal manure additions in grazinglands. Therefore, quantifying GHG emissions from pastures is essential to better understanding the impacts of grazing on the environment. The objective of this study was to quantify and evaluate the potential effects of …

Social And Institutional Factors Influencing Restoration Decisions In Sagebrush Plant Communities In The Great Basin, Carmen Calzado-Martínez

All Graduate Theses and Dissertations, Fall 2023 to Present

Sagebrush landscapes of the Great Basin in the western United States have changed dramatically over the past century. Invasive grasses, repeated wildfires, and past land-use practices have made it increasingly difficult for native plant communities to recover once they are damaged. Most restoration efforts occur after disturbances such as wildfire, when ecosystems may already be severely degraded. An alternative approach is proactive restoration, which aims to strengthen ecosystems before major damage occurs. 

This dissertation examines whether proactive restoration strategies could realistically be used in sagebrush rangelands and what factors influence their adoption. The research combines three complementary approaches. First, interviews …

Teaching Machines To Deter: Exploring Strategic Deterrence In Ai Models, Will Taylor

Theses/Capstones/Creative Projects

This capstone project investigates whether deterrence can emerge as a meaningful strategy within a zero-sum stochastic game using multi-agent reinforcement learning (MARL). After outlining core concepts in game theory and deterrence, the study models a simplified deterrence environment in which two minimax-Q agents repeatedly interact under uncertainty and adversarial incentives. The agents learn from rewards shaped by escalation costs, unilateral vulnerability, and the stabilizing benefits of restraint. Results show that both agents consistently converge toward a conservative, status-quo strategy, overwhelmingly selecting the Maintain action while avoiding both escalation and restraint in most scenarios. This behavior reflects the risk-averse logic of …

Microplastic Composition And Exposure Pathways In Freshwater Systems: A Multi-Matrix Comparison Between Streams And Retention Ponds In Hamilton County, In, Mya Whaley

All-Inclusive List of Electronic Theses and Dissertations

Since the early 1900s, the use of plastics has increased exponentially. The breakdown of plastic materials has exposed all ecosystems to microplastics (small particles of plastic < 5 mm), which are now ubiquitous in natural settings. Microplastics have a relatively large surface area, and many chemicals adsorb to these small particles, impacting their fate and transport of pollution. While microplastics have been found in virtually every setting on Earth, research is necessary to understand their impact on freshwater ecosystems and biogeochemical cycles. The focus of this research was to investigate microplastic compositions in crayfish, sediments, and water samples collected in streams and retention ponds. We analyzed trends in microplastic counts across different land-cover classes, waterbody types, and species, and compared concentrations among matrices to improve our understanding of microplastic exposure pathways in freshwater ecosystems. As a secondary objective, lead and arsenic concentrations were analyzed from sediment samples to investigate metal burdens and compare them to microplastic concentrations. Our findings revealed that, in general, urban streams had the highest microplastic concentrations within land cover categories, and retention ponds had higher microplastic counts than streams. Crayfish, such as F. rusticus had higher microplastic concentrations than F. virilis and F. propinquus, although these results may be influenced by study design. The most common microplastic type was fibers, and most common color was transparent. There was no significant correlation between microplastic and metal concentrations in sediments. We found crayfish to be adequate bioindicators of microplastic pollution, because they were less impacted by environmental variability than sediment and water samples. This research presents the first evidence of microplastics in our study species, F. propinquus, F. rusticus, and F. virlis. This work presents new evidence of microplastic accumulation in crayfish, sediments, and water from freshwater systems in the Midwestern United States. Microplastics were found in every sample type—crayfish, water, and sediment—across urban, rural, and forested landscapes, highlighting their pervasive distribution. The findings provide foundational data for assessing emerging ecological and human-health risks and emphasize the importance of sustained monitoring and research on MP contamination in freshwater environments.

Improving Online Political Discussion With Automated Bot Intervention, Bethanie E. Hackett

Departmental Honors & Graduate Capstone Projects

The quality of political discussions occurring on online platforms or social media sites has been deemed quite poor. To address this issue, I investigated whether a Large Language Model (LLM) can be used to promote civil and productive political discussions by identifying and responding to unproductive dialogue. I fine-tuned an existing LLM to detect elements of problematic dialogue, namely misinformation, misrepresentation of sources, logical fallacies, bias, and toxic language, and then respond in a corrective yet non-confrontational manner. The resulting model is referred to as FroBot and was evaluated through an experiment in which a human participant was placed in …

Open Space Management Planning: A Framework And Case Study From Eagle Mountain City, Utah, Nathan K. Shumway

All Graduate Reports and Creative Projects, Fall 2023 to Present

Open Space Management Plans (OSMPs) are increasingly used by municipalities to guide the long-term stewardship of natural lands; however, little formal guidance exists regarding how these plans are structured, developed, or organized in practice. While numerous OSMPs are publicly available, their compositional logic, procedural workflows, and thematic priorities remain largely undocumented within academic literature. This study addresses that gap through a qualitative document analysis of fifteen publicly accessible OSMPs from the western United States, published between 2015 and 2024.

Using manual matrix-based coding in Microsoft Excel, each plan was analyzed through three lenses: structural composition, procedural development, and thematic content. …

Assessment Of Mississippi Landfill Capacity In Relation To Waste Generation And Land-Use Constraints, Jason C. Anderson

Master's Theses

Municipal solid waste (MSW) management presents a growing challenge in Mississippi as population trends, socioeconomic change and regional development continue to place pressure on existing landfill capacity. This thesis examines waste generation and disposal patterns from 2000 through 2022 across Mississippi counties, with projections extending to 2050. Historical landfill tonnage data was gathered and compiled from the Mississippi Department of Environmental Quality (MDEQ) and analyzed using regression models in Excel and RStudio, with forecasts generated for both in-state and out-of-state waste flow. Results highlight significant variations among landfills, including differing closure timelines, changing county service areas and notable shifts in …