Digital Commons Network^™

Policy Design, And The Repeal Of Ghana’S Emissions Levy Act: A Multiple Streams Framework Analysis, Anthony Amotoe-Bondzie

Collected Student Papers

Ghana’s 2023 Emissions Levy Act (Act 1112) imposed charges on large industrial emitters and vehicles, intending to internalize pollution costs and raise government revenue. This study applies to Kingdon’s Multiple Streams Framework (MSF) to explain the policy’s rapid repeal. Drawing on legislative texts, official reports, and media accounts, it categorizes influences into the problem (rising living costs), policy (design features), and politics (stakeholder mobilization) streams. Key findings reveal that the levy’s mixed design, a per-ton CO₂ fee on industry combined with a flat vehicle ownership tax, undermined its climate rationale and appeared more as a revenue grab. Implementation gaps exacerbated …

Closing The Loop In Sustainable Fashion: Recycling Textile Waste And Its Environmental, Social, And Consumer Impacts, Anthony Amotoe-Bondzie

Collected Student Papers

Fast fashion has intensified textile waste, emissions, and social inequities across global supply chains. This study examines sustainable fashion frameworks and the role of textile recycling in advancing circularity. It employes a qualitative integrative literature review synthesizing interdisciplinary research on waste streams, recycling technologies, policy instruments, and consumer behavior. However, advanced recycling technologies offer environmental benefits but remain limited in scale. Nonetheless, rising consumption offsets efficiency gains, while economic and behavioral barriers hinder systemic change. Technological innovation alone is insufficient; circular design, regulatory enforcement, and reduced overproduction are essential for sustainable transformation.

Budgeting Apps, Financial Literacy, And Financial Control, Max Masabo, Abdullah Mohammad Mahi

Presentations - 2026

Our paper shows the real hidden connections between budgeting app usage and financial wellbeing of U.S Households

Comparative Analysis Of Mlp And Cnn Models For Cardiac Arrhythmia Classification, Veltman Okey-Ejowhor, Vahid Emamian

Posters - 2026

Electrocardiogram (ECG) is a record of the electric activity of the heart over time. ECG analysis plays a pivotal role in diagnosing critical heart conditions. Significant developments have been made in the realm of deep learning and applied artificial intelligence. These deep learning models have been utilized heavily because of their ability to analyze deep morphological features of each signal. The model architecture used in this study is a convolutional neural network (CNN) combined with a multi-layered perceptron (MLP). The MLP acts as an input filter that classifies normal heartbeat signals from abnormal. The CNN is the second filter in …

The Willow Who Kept The Secrets Of The Heart, Ana Suarez

Speak for the Trees!

This digital museum exhibit features the climate change fairy tale The Willow Who Kept the Secrets of the Heart, presented as a written narrative and recorded reading that explores the symbolic relationship between the Weeping Willow, water, and ecological care in the face of climate change. It also includes an infographic highlighting the Weeping Willow’s habitat, characteristics, and environmental challenges in Texas, along with a curator’s talk and curator’s board. The exhibit features an artifact entry using a half-filled vial of water to represent climate instability and the often-overlooked resources that sustain life, as well as a persuasive essay, …

Foxbuddy, Luis Eduardo Garza Jr.

Posters - 2026

Emergency preparedness remains a significant challenge for individuals due to disorganized resource management and lack of accessible guidance. Additionally, cybersecurity risks during emergencies are often overlooked, leaving individuals vulnerable to digital threats such as phishing, scams, and data exposure. FoxBuddy provides a centralized, user-friendly platform that enhances both physical preparedness and cybersecurity awareness.

Using Ai-Based Predictive Scheduling To Improve Patient Flow And Reduce Wait Times In Healthcare Clinics, Oscar Martinez

Posters - 2026

• Healthcare systems face increasing challenges in patient access and wait times
• Average wait times for specialist care continue to rise, creating:
  • Delays in treatment
  • Reduced patient satisfaction
  • Increased system inefficiencies (Sanford, 2025)
• A major contributor is operational bottlenecks, defined as:
  • Points of congestion that slow or disrupt service flow
• Hospitals typically operate under process layouts, which:
  • Handle diverse patient needs
  • Reduce specialization efficiency
• Contributing factors to bottlenecks:
  • Physician shortages and burnout
  • Administrative burden
  • Inefficient scheduling systems (Moura & Pinho, 2025)
• AI offers potential solutions through:
  • Predictive scheduling
  • Automation of administrative processes
  • Data-driven optimization of patient flow

Agglomeration Of Particles Streaming Down A Zigzag, Juan Llamas

Posters - 2026

Zigzags or “letdown ladders” limit the flow speed of dry grains as they flow downward by gravity when loading silos, ships, barges, railcars, or trucks.

• Reduce cracking and shattering of grains.

• Increase grain shelf life.

• Increase grain resale value. • Increase ability of grain to germinate.

• Reduce generation of grain dust, an explosion and environmental hazard.

How can we design a zigzag that we know will not plug?

A View Under The Hood: Duquesne Kline's Law And Computing Program, Wesley M. Oliver, Katherine L.W. Norton, Martin Mckown, David Horrigan

West Virginia Law Review

No abstract provided.

Fear In The Forecast: Do You Believe The Government Controls The Weather?, Gabriella Bartsch

Honors Papers and Posters

Weather manipulation by the government is among the most widely believed conspiracy theories in America, with over 49 percent of Americans subscribing to this belief. As belief in weather-related conspiracies continues to gain traction, understanding the political and social factors that drive these beliefs becomes increasingly essential. In this study, data from the Chapman Survey of American Fears, a representative national sample of U.S. adults, as well as a qualitative content analysis of X/Twitter posts from 2020 to 2026, are used. This research examines how political partisanship and conspiratorial predisposition are reflected in media consumption and levels of institutional trust, …

Multi-Jurisdictional Hazard Mitigation Plan For Landslides For The Kentucky River Area Development District, Kentucky, Hudson J. Koch, Matt M. Crawford, Jason M. Dortch

Contract Reports--KGS

Landslides are a widespread and complex geologic hazard that affects people and infrastructure. The Kentucky River Area Development District, Kentucky, sustains relatively high landslide activity that impacts several municipalities in eastern Kentucky. This hazard mitigation planning project outlines landslide hazard and risk assessments for the Kentucky River Area Development District, with information needed for each community in the region to develop mitigation strategies that will support infrastructure and development needs, land-use planning, situational awareness, and response and recovery actions for the communities.

Fluid-Mediated Particle Transport: Revisiting Snowstorm Simulations In 2d With An Updated Pressure Calculation Algorithm, E. Maldonado, Michael W. Roth

The Compass: Earth Science Journal of Sigma Gamma Epsilon

We develop and present computer simulations of snowfall and snowfall management near buildings using deflection fins. Our approach first entails a numerical solution to the Navier – Stokes fluid dynamics equations in order to determine wind velocity profiles with and without deflection fins. Subsequent to finding the velocity field, snow particles are introduced and are subject to Newton’s Laws in order to allow transport, sticking to surfaces, landing and ultimately accumulation. We revisit previous work, presenting and discussing program construction and validation, along with cursory systematic studies of varying geometrical parameters in the simulation. The utility of the simulations is …

Sigma Gamma Epsilon Student Research Poster Session, Geological Society Of America Annual Meeting 2025, San Antonio, Texas, Usa, Scott R. Beason, Lee S. Potter

The Compass: Earth Science Journal of Sigma Gamma Epsilon

The Society of Sigma Gamma Epsilon (SGE) sponsors a poster session at every annual meeting of the Geological Society of America. The 37th SGE undergraduate research poster session took place during the 2025 Geological Society of America Annual Meeting (GSA Connects) in San Antonio, Texas, USA, on Monday, October 20, 2025. Fifty-seven (57) posters were presented in Exhibit Hall 1 at the Henry B. Gonzalez Convention Center between 8:30 AM and 5:30 PM at the poster session, with authors present between 9:00 AM and 11:00 AM. Titles, authors (italics for the presenting author), affiliations, and abstracts for each poster are …

Corporate Fiduciary Duties And The Climate And Biodiversity Crisis, Eric W. Orts, Sandra G. Schafhäutle

Michigan Journal of Environmental & Administrative Law

This Article argues that addressing one of the most urgent environmental challenges facing humanity today—the global climate and biodiversity crisis—calls for a transformation at the heart of corporate law: its fiduciary duties. After demonstrating how current corporate fiduciary duties are implicated in this crisis, we argue for reform of fiduciary duties operating at two levels: those governing directors and officers of business corporations, and those governing institutional investors and asset managers. We then distinguish between two general kinds of corporate fiduciary duties: permissive and mandatory. We contend that corporate law should accommodate a more expansive understanding of fiduciary duties by …

The Energy And Environmental Footprint Of Ai, Michael P. Vandenbergh, Ethan I. Thorpe, Jonathan M. Gilligan

Michigan Journal of Environmental & Administrative Law

Artificial intelligence (AI) has the potential to create major economic and social benefits, but also to rapidly escalate electricity demand and its associated environmental impacts. Information availability has been a cornerstone of environmental law for half a century, and this Article argues that providing information to individual, corporate, and other users about the electricity demand and environmental impacts of AI can reduce those impacts without delaying development of the technology. Little is known about how different large language models (LLMs) compare on these metrics, though. To address whether users have access to the information necessary to address this shortcoming, the …

Four Decades, No Progress: Time For A Columbia River Basin Compact, Liesl L. Bogaard

Michigan Journal of Environmental & Administrative Law

Since the Power Act’s passage in 1980, the government entities who develop and implement energy policy in the Pacific Northwest have operated under a congressional mandate to protect fish and wildlife in the Columbia River Basin. However, nearly half a century later, the number of wild salmon and steelhead returning to their native spawning grounds is still in decline, largely due to dam operations in the Columbia and its tributaries. This Note examines the history of hydroelectric power generation in the Columbia River Basin and its impact on fish populations, drawing parallels between the environmental crisis in the Columbia River …

Owning Geothermal Energy, Gabriel Eckstein

Michigan Journal of Environmental & Administrative Law

Geothermal energy holds vast potential for decarbonizing the U.S. energy system, yet the sector remains significantly underdeveloped, supplying only 0.4% of the nation's electricity. A principal barrier to growth is the fragmented and ambiguous legal landscape currently governing ownership of geothermal resources: thirty-three states lack any clear statutory or common-law framework identifying who owns subsurface thermal energy. This Article examines the physical characteristics of geothermal energy, recent developments in the U.S. geothermal sector, and the principal doctrinal approaches that might govern ownership of subsurface heat, including the ad coelum doctrine, common-pool and open-access frameworks, the rule of capture, and public …

Harvest Scanner, Alexander Murphy

Posters - 2026

In current times, people can find themselves at the whims of markets and may be spending more than they realize or want to on regular, everyday goods. New tools can help users keep track of the goods they are paying for. Harvest Scanner was developed to scan and track local grocery prices from stores using their publicly available website information. It was developed in Python using PyQt5 for GUI. The database is stored as an SQL file with Python using SQLite engine. Users will be able to view local grocery prices in a database interface (GUI). There are many features …

Machine Learning In Fundamental Physics: From Early Universe Signatures To Qcd Evolution, Brandon Stevenson

Physics Theses and Dissertations

In both cosmology and small-x quantum chromodynamics, the relevant theoretical predictions are well-defined but expensive to evaluate repeatedly over broad parameter spaces or large ensembles of simulated data. The central question of this thesis is when machine learning can accelerate those calculations without weakening the reliability of the final physics conclusions. The thesis develops and tests this idea in three settings. First, it studies the Derivative Approximation for Likelihoods (DALI) as a means of diagnosing when Fisher-matrix forecasts cease to be trustworthy in cosmological parameter inference. Second, it investigates graph-based spherical neural networks for estimating primordial non-Gaussianity directly from simulated …

Lego®-Based Cubesats For Space Outreach, Stefan Brandle, Joshua Brown, Evan Smith, Drew Nye, Sydney Reddy, Twidy Kwae, Kaiya Grzesiak, Matthew Roderer, John Hetz

Faculty-Led Student Projects in CSE

Taylor University Computer Science and Engineering, in collaboration with NearSpace Education, has initiated a multi-year effort to enhance space-awareness by offering K-12 students career-impacting opportunities to build and fly satellites that have a LEGO®-robotics-based payload. This effort is intended as an outreach in the spirit of the ThinSat project (2017-2021) supported by Virginia Space, Twiggs Space Lab, Orbital ATK, NearSpace Launch, and the NASA Wallops Flight Facility, among others. We hope to receive permission to name the satellite LEGO-SAT-0.

Deep Learning Frameworks For Biological Data Integration And Generation, Alexa Beachum

Statistical Science Theses and Dissertations

Data integration represents a key area of research for analyzing the rapidly growing volume of high-dimensional biological data across sources, stages, and modalities. To model and understand these complex, often non-linear relationships, deep learning has become an increasingly powerful tool. Here, we present two novel deep learning frameworks that address distinct but complementary integration challenges. The first framework aligns single-cell omics data across temporal stages, and the second bridges imaging and omics modalities to generate patient-level molecular profiles.

In Chapter 1, we briefly summarize existing approaches---both statistical and deep learning-based---for single-cell omics data integration and discuss their limitations for handling …

Water Current, Volume 58, No. 1, Spring 2026

Water Current Newsletter

No abstract provided.

Evaluation Of Seal!Nd: School Year 2024-2025, Shawnda Schroeder, Rashid Ahmad

Indigenous Health Faculty Publications

Dr. Schroeder and Rashid worked with the team at the Oral Health Program to collect data on the clinical reach of the School-based Sealant program (SEAL!ND), the referral practices, dental sealant cost savings, and perceptions of school personnel regarding their experiences with the program. SEAL!ND continues to make a measurable difference in improving children’s oral health by increasing access to preventive care, reducing barriers for families, and supporting schools in meeting the needs of their students. The program’s impact is reflected not only in the thousands of services provided each year, but also in the strong satisfaction and gratitude expressed …

Coastal Flooding And Community Resilience: Evaluating Management Strategies For Pawleys Island, Lindsey Degrendel

Goal 11: Sustainable Cities and Communities

No abstract provided.

Next-Generation Democratic Cyber Statecraft - Balancing The Signal: Shutdown Shocks And Democratic Digital Governance, Scott M. Di Panni

School of Public Policy Capstones

This paper develops Next-Generation Democratic Cyber Statecraft (NG-DCS), a unified strategic doctrine for democratic governments to contest the cognitive domain against authoritarian adversaries. Drawing on twenty-six years of cross-national panel data (1999–2024) spanning 213 countries, game-theoretic modeling, and qualitative case analysis, the paper establishes three interconnected empirical and theoretical foundations. First, cross-national OLS regression across 160+ countries demonstrates that regime type is the dominant structural determinant of internet freedom (R²=0.615, β=2.513, p< 0.001), explaining more than twice the variance attributable to per-capita wealth (R²=0.268). Democratic governance, not economic development, produces open digital environments. Second, a two-way fixed effects (TWFE) difference-in-differences study exploiting government-ordered internet shutdowns as discrete policy interventions finds that digital restrictions causally degrade V-Dem governance quality by 0.21–0.38 standard deviations (p< 0.001 across all specifications). Treatment effects are immediate (β=−0.302 at k=0) and persist through five post-treatment years (β=−0.246 at k=+5), indicating structural rather than transitory governance damage. Parallel trends validation (p=0.352) and Callaway–Sant’Anna heterogeneity-robust estimation (ATT=−0.230, SE=0.077) support causal identification. Instrumental variable triangulation (2SLS β=−0.949, p=0.005) confirms that simultaneity was attenuating, not inflating, the primary estimates. Third, formal game-theoretic analysis reveals that the current U.S.–adversary equilibrium is (Restrain, Escalate)—the risk-dominant but Pareto-inferior outcome of a Stag Hunt structure. China, Russia, North Korea, and Venezuela each occupy structurally distinct positions (Stackelberg commitment, asymmetric two-level, autarky, and reactive trigger, respectively), requiring differentiated doctrinal responses rather than a uniform strategic playbook. Generative AI and algorithmic governance are shown to accelerate cognitive vulnerability by collapsing influence operation costs and exploiting engagement-optimized platform architectures that systematically degrade deliberative capacity in democratic populations.

Trade Liberalization Under Safta And Bimstec: Evidence From A Cge-Gtap Case Study Of A Small Open Economy, Gita Bhushal, Pankaj Lal

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Regional trade liberalization via preferential agreements increasingly shapes economic outcomes in small open economies embedded in overlapping regional frameworks. This study evaluates the short-run economy-wide effects of tariff and non-tariff measure (NTM) reforms under the South Asian Free Trade Area (SAFTA) and the Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) using a Computable General Equilibrium (CGE) model calibrated to the GTAP 10 database. Gravity-based estimates of ad valorem equivalents (AVEs) of NTMs are integrated into the CGE framework, enabling explicit modeling of regulatory barriers alongside tariff reductions. Policy simulations examine scenarios involving a 90 percent tariff …

Watch Me Watch: Reaction Videos As A Social Form Of Online Video Engagement, Rodney Okyere, Carlos Augusto Bautista Isaza, Jaehoon Pyon, Ihudiya Finda Ogbonnaya-Ogburu, Shuo Niu, Sang Wong Lee

Computer Science

Reaction videos (RVs) are surging in popularity, emerging as a distinctive facet of participatory culture on modern social video-sharing platforms such as YouTube, TikTok, and Twitch. This study aims to explore not only the motivations and engagement patterns of viewers towards RVs, but also the underlying nature of the virality and community-building phenomena that this sub-genre of video content fosters. We conducted 16 semi-structured interviews with individuals who identified as regular viewers of reaction videos to gain a deeper understanding of how they discover reaction videos (RQ1), the values that drive their motivations for viewing RVs (RQ2), and the ways …

Targeting Oncogenes: Development And Characterization Of Aurka And Her2 Inhibitors, Itzel Montoya

Chemistry Theses

Targeted inhibition of oncogenes has remained a key strategy in the development of more potent, effective, and less toxic therapeutic anticancer agents. Among the most clinically significant signaling pathways are those mediated by the Human Epidermal Growth Factor Receptor 2 (HER2) and Aurora Kinase A (AurKA). HER2 is a member of the ErbB receptor family that supports cell growth and proliferation through downstream signaling of the PI3K and MAPK pathways and is closely linked to more aggressive tumors and therapeutic resistance. AurKA is a protein kinase essential for mitotic spindle assembly, centrosome maturation, and other key processes in cell cycle …

Efficacy Analysis In Clinical Trials: A Comprehensive Review Of Statistical And Machine Learning Approaches, Dhrubajyoti Ghosh, Samhita Pal

Faculty Articles

Efficacy testing is a cornerstone of clinical trials, ensuring that medical interventions achieve their intended therapeutic effects. Over the decades, a wide range of statistical methodologies have been developed to address the complexities of clinical trial data, including parametric, nonparametric, Bayesian, and machine learning approaches. Parametric methods, such as t-tests, ANOVA, and LMMs, have traditionally been the foundation of efficacy testing due to their efficiency under well-defined assumptions. Nonparametric techniques, including the Friedman test, Brunner-Munzel test, and modern extensions like nparLD, have emerged as robust alternatives, particularly for skewed, ordinal, or non-normal data. Bayesian methodologies have enabled the incorporation of …

Be Responsible In Your Answers! Monitoring Out-Of-Domain Behaviors In Domain-Specific Llms, Boquan Li, Chenzhe Lou, Zhe Ren, Peixin Zhang, Zirui Fu, Jun Sun, Yaowen Zheng

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have accelerated the rapid development of chatbot web applications in various domains, such as coding, biomedicine and psychology. Compared to general LLMs like ChatGPT, domain-specific LLMs require a greater sense of responsibility. For instance, if a programming LLM casually answers medical or psychological questions, it not only misleads the public but also poses legal risks. This highlights new demands for monitoring and preventing such irresponsible behaviors. Existing efforts attempt to monitor LLMs from multiple aspects, such as lying, jailbreaks, and toxic content, while overlooking out-of-domain behaviors. In this work, we propose an innovative LLM domain monitoring …