Digital Commons Network^™

History Is Durable: A Mixed-Methods Study Exploring Stakeholder Perceptions Of The Degree And Career Relevance, Hala Al-Tinawi, Damali Curry, Tonya S. Hall, Sharrie A. Merritte

Doctor of Education Capstones

Declining undergraduate enrollments in history departments reflect a national trend that many institutions have struggled to reverse. This capstone project, conducted in partnership with the Virginia Commonwealth University Department of History (VCUDOH), examines a specific and addressable dimension of that challenge: a communication gap in how the career value of a history degree is conveyed to students in introductory-level courses. Using improvement science principles and a mixed-methods case study design, the capstone team investigated how introductory history instructors communicate durable skills and career applicability, how students perceive the relevance of introductory history coursework to their career plans, and why students …

Oppression On The Blockchain, Erwin J. Kwok, Moin A. Yahya

Emory Business Law Review

When Ethereum (ETH) shifted from a Proof of Work (PoW) protocol to a Proof of Stake (PoS) protocol, not all users were enthused. We use Ethereum’s shift from PoW to PoS as a case study for the broader question of whether developers of a blockchain owe its members certain fiduciary or fiduciary-like duties. We argue that if done properly, in accordance to the rules governing the blockchain, then developers do not necessarily owe fiduciary responsibility to other members of the chain, but they nonetheless may owe fiduciary-like responsibilities to users inadvertently and negatively impacted. We argue these users may be …

No 'Dexit': Delaware's New Statutory Corporate Law Loosens The Restrictions On Controlling Shareholder Transactions In Response To Corporate Outlash Following Tornetta V. Musk, Reid A. Manabat

Emory Business Law Review

The recent Tornetta v. Musk decisions caused upheaval in the Delaware corporate community. Throughout 2024, shareholder executives have left or threatened to leave Delaware to incorporate elsewhere in a move termed “DExit.” The threat did not go unnoticed by Delawareans and lawmakers who contemplated a two-billion-dollar loss to the state’s tax revenue. Despite the courts’ willingness to require heightened scrutiny for conflicted-controller transactions, in recent years lawmakers have lowered the bar. I argue that Delaware’s new statutory corporate law does not adequately protect minority shareholders from conflicted controllers. First, the new statutory cleansing mechanisms ignore the unique dangers of conflicted-controller …

Report 17—Revisions To The Articles Of Organization And Procedure Of The Commission On Stratigraphic Nomenclature Of The Americas, Lynn T. Dafoe, Robert B. Macnaughton, Marie-Perre Aubry, Carlton E. Brett, James R. Lehane, Fernando Núñez-Useche, Randall C. Orndorff, Frank Brunton, Lucy E. Edwards, Richard H. Fluegeman, Howard Harper, Robert Matthew Joeckel, Norman P. Lasca, B. H. Tew

Conservation and Survey Division: Faculty and Staff Publications

Several revisions to the Articles of Organization and Procedure for the North American Commission on Stratigraphic Nomenclature have been adopted following the 75th, 79th, and 80th annual meetings of the Commission in 2020, 2024 and 2025, respectively. Of these, the most substantial change was revision of Article III regarding membership composition of the Commission and the addition of new member organizations from Central and South America and the Caribbean region. As a result, the Commission also voted to change its name to be more inclusive of the expanding membership, with approval of the name: Commission on Stratigraphic Nomenclature of the …

Hydroponics In The Classroom: Cultivating Plants, Captivating Young People, Stacy A. Adams, Christian Stephenson, Theresa James, Kim Todd

Department of Agronomy and Horticulture: Faculty Publications

Few students take the initiative to pursue coursework beyond that required for progression to graduation. Limited are opportunities that connect educational content to industry application, potentially inspiring young people towards impactful careers. The United States government has emphasized the importance of STEM education to ensure national security and to maintain economic competitiveness globally. STEM education is not a defined discipline but an approach for building knowledge through application and engagement. Developing and managing a hydroponics prototype provides numerous opportunities for embedding STEM content into a fun and interactive project. This poster provides inspiration for constructing a simple deep water culture …

Assessment Of Soybean Response To Irrigation Variability In Eastern Nebraska Using The Aquacrop Model, Anmol Singh, Saleh Taghvaeian, Yufeng Ge, Derek M. Heeren, Frank Bai

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Soybean [Glycine max (L.) Merr.] is a major irrigated crop in eastern Nebraska, where recent expansions in irrigated agriculture and projected trends in irrigation demand necessitate thorough investigations of approaches that can optimize its irrigation management. In this study, the AquaCrop model was calibrated and validated using 19 variable irrigation treatments from a five-year field experiment. The model accurately simulated canopy cover, soil water content, and grain yield, with validation normalized root mean square error (nRMSE) of 12%, 7%, and 7%, respectively. The model was subsequently applied to estimate soybean yield and water requirement during a 15-year period (2010–2024) …

Dataset: The Impact Of External Resource Use On The Validity Of Score Interpretation For A Biology Concept Assessment Administered Out-Of-Class, Tiffany J. Burgess, Crystal Uminski, Gia Alicea, Brian A. Couch

School of Biological Sciences: Faculty Publications

Instructors use concept assessments to gauge student knowledge and guide course improvement. Many instructors experience time and logistical constraints around administering these assessments in class. For this reason, administering concept assessments outside of class can help increase feasibility. While previous studies have cautioned that the use of external resources (e.g., internet, course notes, peers) in the out-of-class setting may inflate assessment scores, the extent to which undergraduate students access various resources when completing concept assessments is unknown. The current study uses two survey question formats to better understand whether students engage with external resources when taking a biology concept assessment …

Dataset: Participation Versus Points: Examining The Impact Of Grading Conditions On Student Resource Use During An Out-Of-Class Biology Concept Assessment, Tiffany J. Burgess, Crystal Uminski, Brian A. Couch

School of Biological Sciences: Faculty Publications

Instructors use concept assessments to collect diagnostic information regarding student learning and to inform decisions surrounding instructional interventions and course modifications. Administering concept assessments out-of-class helps preserve already limited instructional time, but instructors still must consider whether to apply a lower-stakes (i.e., participation) versus higher-stakes (i.e., correctness) grading scheme. An increase in stakes is likely to prompt additional effort, but it may also increase undesired behaviors and inadvertently prompt external resource use, such as students leveraging their notes, the internet, or their peers. In the present study, we compared student self-reported resource use on a biology concept assessment administered under …

Visual Analytics For Interpretable Quantum Computing, Shaolun Ruan

Dissertations and Theses Collection (Open Access)

Quantum computing has entered a stage of increasing practicality. Many quantum hardware vendors such as IBM, Rigetti, Honeywell, and IonQ now enable experiments on real devices in the Noisy Intermediate-Scale Quantum (NISQ) era. These platforms show computational advantages in domains such as optimization, machine learning, and materials science. However, they remain limited by hardware noise and the absence of human-interpretable information. Existing visual metaphors, such as the Bloch Sphere for single-qubit states or circuit schematics for algorithm design, struggle to convey multi-qubit entanglement or measurement probabilities in ways accessible to human reasoning. Likewise, the rise of variational quantum circuits and …

Constrained Reinforcement Learning: From Single-Agent Safety To Multi-Agent Coordination, Hao Jiang

Dissertations and Theses Collection (Open Access)

Real-world decision-making systems such as autonomous driving and largescale ride-pooling must operate under strict safety and resource constraints. Traditional Reinforcement Learning (RL) methods, while powerful in simulation, often fail to guarantee such constraints, limiting their real-world deployment. The fundamental challenge lies in integrating constraint satisfaction with long-term reward optimization, especially when outcomes are stochastic and interdependent across multiple agents.

This dissertation advances the field of Constrained Reinforcement Learning (CRL) from both single-agent safety and multi-agent coordination perspectives. In the single-agent setting, we introduce a Reward Penalty framework that augments the state space with cumulative cost and penalizes only trajectories that …

Excision Followed By Standing Cone Deformity Repair Is Tissue Conservative, Henry Lim, Christian Scheufele, Marshall Hall, Stephen Weis, Dustin Wilkes

North Texas GME Research Forum 2026

Introduction Elliptical excisions are the most common method to treat benign and malignant tumors in dermatologic surgery. This standardized design is traditionally 3 to 4.5 times longer than the excisional width to prevent unsightly protrusions of skin after primary closure, known as “standing cone,” “Burow’s triangles” or “dog ear” deformities. This results in a scar significantly longer than the original tumor that may be less easily concealed.

Objective To compare the final repair length of a tissue conservative method to remove skin tumors and close resultant defects against predicted repair length of traditional elliptical excision.

Methods Eighteen cases are presented …

Improving Pid Control With Bayesian Optimization For Adversarially Robust Federated Learning, Adrian Pena, Sergei Chuprov, Raman Zatsarenko, Leon Reznik

Computer Science Faculty Publications

Federated Learning (FL) often suffers from unstable convergence and reduced robustness under non-IID data and malicious attacks. In this paper, we present FedPIDAvg_tuned, a control-theoretic aggregation framework for improving stability and adversarial robustness in FL. In particular, our approach combines a server-side Proportional–Integral–Derivative (PID) controller with Bayesian optimization to tune controller gains for different data and attack conditions. The PID controller regulates global model updates through feedback on loss dynamics, providing adaptive scaling that improves stability and convergence. The tuned gains are applied within a trust-weighted trimmed-mean mechanism to remove adversarial or outlier updates. Using the Flower framework, we evaluate …

Cohabitation And Child Educational Outcomes: An Examination Of Family Stability And Transition In Australia, Shana Pribesh, Emily E. Pulsipher, Mikaela J. Dufur, Jonathan A. Jarvis, Ashley Weisman, Yuanyuan Yue

STEMPS Faculty Publications

Cohabitation has become an increasingly common context for childrearing, yet children living with cohabiting parents often exhibit poorer academic outcomes than peers with married parents. This study examines whether these disparities stem from cohabitation itself, subsequent family transitions, or underlying mechanisms related to resources, stress, or selectivity. Using data from the Growing Up in Australia: Longitudinal Study of Australian Children (LSAC), we follow 920 children born to cohabiting parents and track family structure changes alongside teacher-rated literacy and mathematics performance from ages 6 to 11 years. Generalized estimating equation models show that, although children whose parents transitioned to single-parent or …

Redefining Educational Technology: A Critical Collaborative Inquiry, Aras Bozkurt, Helen Crompton, Robert Farrow, Agnes Kukulska-Hulme, Jon Dron, Richard West, Agnieszka (Aga) Palalas, Matth Bower, Junhong Xiao, Ahmed Tlili, Danah Henriksen, Angelica Pazurek, Henk Huijser, Thomas K. F. Chiu, Petar Jandrić, Katy Jordan, John Curry, Royce Kimmons, Mutlu Cukurova, Thomas Reeves, Gwo-Jen Hwang, Peter Shea, Jason Lodge, Martin Weller, Davy Ng, Tutaleni Iita Asino

STEMPS Faculty Publications

Educational technologists have not settled on a fixed definition of the field and likely never will. However, attempting to define the field helps to understand the epistemological meanings that shape what the field sees, values, and considers worth pursuing. Through a critical historical review spanning over a century, alongside theoretical engagement with the concepts of entanglement and distributed agency, this paper identifies three key insufficiencies in current educational technology frameworks. These are the persistence of an instrumental-facilitative paradigm that treats technology as a resource deployed by human agents; the theoretical dissolution of the pedagogy-technology dichotomy that existing definitions have not …

State Climate Superfunds, Rachel Rothschild

Articles

The harmful effects of climate change have already arrived in cities and states across America, with disasters increasing markedly in recent years along with more gradual environmental changes like sea-level rise and drought. To protect populations and natural resources, significant funding will be necessary for preventative measures as well as disaster response.

At present, it is states and ordinary taxpayers who must shoulder the enormous costs and planning for climate adaptation. A number of state legislators, however, have recently proposed enacting new laws that would require the companies who have most profited from fossil fuel usage to assist in funding …

Ai-Powered Lawyering: Ai Reasoning Models, Retrieval Augmented Generation, And The Future Of Legal Practice, Daniel Schwarcz, Sam Manning, J. J. Prescott, Patrick Barry, David R. Cleveland, Beverly Rich

Articles

Generative AI is set to transform the legal profession, though its most promising uses and ultimate effects are still unclear. While AI models like GPT-4 improve efficiency, they can also “hallucinate” and may undermine legal judgment, particularly in complex tasks typically handled by skilled lawyers. This article examines two emerging AI innovations that may mitigate these concerns: Retrieval Augmented Generation (RAG), which grounds AI-powered analysis in legal sources, and AI reasoning models, which structure complex reasoning before generating output. We conduct the first randomized controlled trial assessing these technologies, assigning upper-level law students to complete legal tasks using a RAG-powered …

Monitoring, Oversight, And Learning In Medical Ai, W. Nicholson Price Ii

Articles

When medical AI errs, it often goes unnoticed. If there’s a specific patient injury, and the link to AI is obvious, that problem might be reported to the Food and Drug Administration (FDA), but not always. And many other types of problems, like worse performance on specific groups or ineffective integration into health system workflows, simply don’t fall within the contours of regularized reporting. Even if they are noticed by the health system—far from a given—there’s no obvious way to share that information more broadly. Against this backdrop, there are justified calls for better oversight and reporting. But there’s the …

The Classical Limit In Geometric Quantization By Group Extension, Paul Bracken

School of Mathematical & Statistical Sciences Faculty Publications

Physical systems as a rule are associated with a symmetry group. The group approach to geometric quantization makes use of this to introduce a quantization by means of group extension. This procedure is discussed and applied to a physical system whose group law has its origin with the Galilean group. The main intention is to investigate the classical limit and its relationship under this approach to geometric quantization. The classical quantization conditions are obtained based on a deeper foundation.

Envisioning The Role Of Community-Owned Stores & Aligning Federal Food Policies: A Participatory Approach To Food Security And Food Sovereignty In Sambaa K’E, Denendeh (Northwest Territories, Canada), Narayan Subramoniam

Theses and Dissertations (Comprehensive)

Northern Indigenous communities have relied on traditional food systems for meaningful, nutritious diets since time immemorial. But many Indigenous communities in remote northern regions of Canada still face disproportionately elevated levels of food insecurity due to climate change radically altering the availability for traditional foods, colonial food policies imposing Western diets, and the high costs of transporting store-bought foods. Extreme weather events such as wildfires further isolate fly-in remote communities increasing both the costs of transporting store-bought foods and the difficulties of harvesting traditional foods. There are many examples of community-based initiatives for supporting traditional and locally grown foods, however, …

Science Fiction Cinema And The Technological Sublime: Spectacle And The Infinite From Early Cinema To Digital, David Jackson Dr.

Theses and Dissertations (Comprehensive)

This dissertation examines how science fiction cinema constructs and reimagines the technological sublime in the twentieth century: the experience of awe, terror, and admiration provoked by human-made power and scale. Drawing on the philosophical foundations of the sublime in Edmund Burke and Immanuel Kant and extending through Leo Marx’s and David E. Nye’s theorization of the technological sublime, I propose an aesthetic mode in which representation inflected with affect translates technological spectacle into examinations of humanity’s role and agency in the face of overwhelming technologized worlds and in some cases, even the universe itself.

Through three distinct historical periods …

Implementation Of A 3-Dimensional Hydrodynamic Numerical Model On A Large Northern Lake, Kirin Lorente

Theses and Dissertations (Comprehensive)

Climate change is impacting high latitude regions disproportionately more than those at a lower latitude. With polar lakes being highly sensitive to changes in the climate, shifts in lake ice dynamics and hydrodynamics are indicators of such changes in regional and global climates. These changes impact future seasons in a positive feedback loop, where changes in winter ice cover impact open water nutrients levels and lake thermal structure. This highlights the importance for long-term monitoring. Despite the abundance of lakes distributed across Northern Canada, there has been limited research conducted on these sentinels of climate change.

Specifically, Great Bear Lake …

Cognitive Load Classification Using Functional Near-Infrared Spectroscopy, Pratham Shah

Theses and Dissertations (Comprehensive)

This thesis investigates the classification of cognitive load using functional near-infrared spectroscopy (fNIRS) signals recorded during an N-back working memory task. The study introduces a novel short-channel correction layer designed to suppress superficial physiological noise adaptively, addressing limitations of traditional General Linear Model (GLM) based regression. A single participant dataset comprising 69 validated sessions was analyzed using both conventional machine learning and deep learning approaches. Traditional classifiers: Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Random Forests, and Gradient Boosting were first evaluated using statistical features (mean, variance, peak, and slope). Among these, Gradient Boosting achieved the highest accuracy (55.6%), …

A Novel Federated Llm Framework For Distributed Traffic Modelling In Intelligent Transportation Systems, Seerat Kaur

Theses and Dissertations (Comprehensive)

Intelligent transportation systems (ITS) depend on accurate traffic prediction to support congestion management, infrastructure planning, and real-time operational decisions. Despite substantial progress in data-driven forecasting, several challenges continue to limit practical deployment: traffic data is distributed across independent regional authorities, making centralized aggregation infeasible, standard federated aggregation strategies ignore traffic-specific characteristics that meaningfully affect model quality, and existing models produce only numerical outputs without interpretable reasoning that urban planners can act upon. This thesis addresses these challenges through four contributions that collectively advance privacy-preserving, explainable, and scalable traffic forecasting.

The first contribution provides a systematic review of 129 peer-reviewed publications, …

Taylorkan-Vit: Parameter-Efficient Vision Transformers For Medical Image Classification, Kaniz Fatema, Dr. Emad Mohammed, Dr. Sukhjit Singh Sehra

Theses and Dissertations (Comprehensive)

Effective and interpretable classification of medical images remains a critical challenge in computer-aided diagnosis, particularly in data-scarce and resource-constrained clinical settings where traditional deep learning models prove impractical. This study addresses the fundamental barrier to Vision Transformer adoption in medical imaging—massive parameter counts and data requirements—through a systematic two-phase methodology. Phase 1 evaluates three spline-based Kolmogorov–Arnold Network (KAN) variants to identify the optimal nonlinear approximation function for parameter-efficient medical image classification: SBTAYLOR-KAN (B-splines with Taylor series), SBRBF-KAN (B-splines with Radial Basis Functions), and SBWAVELET-KAN (B-splines with Morlet wavelets). Comprehensive experiments across brain MRI, chest X-rays, and tuberculosis datasets—without any image …

Permafrost Microtopography And Active Layer Hydrology In The Western Canadian Arctic, Tobias L. Leonhard

Theses and Dissertations (Comprehensive)

The growing interest in Arctic regions will likely increase the use of nuclear energy in the Arctic. While this energy source has a high potential to improve economic opportunities in the Arctic, it also increases the release of radioactive material (radionuclides). Radionuclides are already found in the Arctic and are traced back to natural as well as anthropogenic sources. Water is one of the dominant transport vectors for solutes such as radionuclides or other contaminants. Therefore, improving our understanding of Arctic hydrology is important for assessing future environmental risks such as the release of radionuclides. Topographic and microtopographic features are …

Memory Effects In Many-Body Systems, Jeffrey Beckstrand

Master's Projects

This thesis investigates memory effects in many-body systems through the MoriZwanzig Formalism for projected dynamics of a Hamiltonian System which yields the Generalized Langevin Equation (GLE). The GLE is a stochastic differential equation (SDE) that studies the dynamics of observables under the effects of many other observables in the system. Although satisfying, the GLE has a term called the Memory Kernel that encodes the past of the system and introduces a computational challenge by introducing a non-Markovian property to the equation. The kernel is often approximated by introducing a delta function, which simplifies the computation, but at the loss of …

Javatutor: An Integrated Llm Framework For Structured Programming Tutoring And Problem-Solving In Java, Amey Makarand Dhongade

Master's Projects

Large Language Models (LLMs) are being adopted more actively to assist in pro- gramming tasks, but much of the available AI code assistants devices are encouraging the rapid generation of solutions, as opposed to assisting students in developing an understanding. As a result, they can give the students correct code without teaching on how to judge a problem and how to build solutions or how to debug their programs themselves. This study describes JavaTutor, an LLM-based tutoring system that is used to assist learners in the learning process in a three-step process of understand- ing, generating a solution, and refining …

Safe-R2r: A Safety-Aware And Budget-Optimized Retrieval Controller For Rag Systems, Mandar Sunil Gondane

Master's Projects

Retrieval-Augmented Generation (RAG) improves factual grounding in large language models by incorporating external evidence during inference. However, most RAG systems rely on fixed retrieval strategies that ignore query difficulty, computational cost, and prediction uncertainty. This project introduces SAFE-R2R (Safety-Aware and Budget-Optimized Reason-to-Retrieve), a retrieval controller that treats retrieval as a query-dependent decision problem. SAFE-R2R organizes retrieval into a multi-rung ladder ranging from no retrieval to deeper retrieval with reranking. At each rung, the system generates an answer, computes reliability signals, and combines them into a risk score used within a conformal calibration framework to decide whether to accept the answer …

Multimodal Emotion Detection System, Shubhankar Sameer Munshi

Master's Projects

Trying to understand emotion from speech is a problem that is present in human computer interaction. Nevertheless, there are still some shortcomings in current SER methods. Text-based systems may miss vital vocal cues, such as sarcasm, tone changes, and delivery. On the other hand, purely audio-based systems are prone to noise and unstable acoustic features. The combination of linguistic and acoustic features in multimodal approaches partially solves this problem, but many existing approaches use inflexible multimodal fusion techniques that cannot adjust their behaviors according to the quality of input signals. In this work, we propose a multimodal approach based on …

Modeling Sealed Deck Construction In Collectible Card Games Using Learning-To-Rank Approach, Michael Dinh Nguyen

Master's Projects

Artificial intelligence has demonstrated strong performance in complex decision-making domains such as chess and Go, motivating research into its application for games with even richer rules and combinatorial complexity. In collectible card games like Magic: The Gathering, deck construction from a constrained card pool is a critical and challenging task that requires evaluating card strength, synergy, and resource balance. This project explores whether machine learning, specifically learning-to-rank (LTR), can effectively model these human decision processes to construct competitive decks in a sealed format. The results found here can also be applicable to other areas of note, such as sports drafting …