Digital Commons Network^™

Guitar Amplifier Directivity, Rachel C. Edelman, Brian E. Anderson, Samuel D. Bellows, Timothy W. Leishman

Directivity

No abstract provided.

Trustworthy Multimodal Ai For Medical Imaging: Enhancing Diagnosis, Reasoning, And Human-Agent Interaction In Extended Reality, Jai Prakash Veerla

Computer Science and Engineering Dissertations

The transition from traditional microscopy to digital pathology has digitized diagnostic data, yet clinical workflows remain constrained by two-dimensional screens and passive, opaque analysis tools that fail to capture the spatial complexity of biological systems. While Foundation Models now promise to reason across histology and genomics, a critical disconnect persists between the richness of this data and the limited cognitive bandwidth of clinicians, who currently lack the immersive interfaces and trustworthy agents necessary to utilize it effectively. This dissertation presents a unified framework for "Embodied Agentic AI," establishing a pipeline that augments physician capabilities through immersive visualization, robust security, and …

Modeling French Language Preservation: An Optimal Control Problem, Charlotte Blasi

Scripps Senior Theses

The French language is one of the most globally spoken languages, with over 300 million speakers and designated the official language of 29 nations. French continues to prosper as a result of its titular nations' imperialist history that emphasized linguistic diffusion as well as the support of international organizations dedicated to promoting both the language and the culture of French-speaking nations. In this thesis, we explore the nuanced history of French-speaking countries and one institution dedicated  to promoting the French language, the OIF. We further examine the media mechanism of the OIF and construct a system of Ordinary Differential Equations …

An Introduction To Modern Conversations On Knot Invariants, Stella Shah

Scripps Senior Theses

Knot Theory is a vast and diverse subfield of modern mathematics involving the classification and abstraction of knots and links. In this thesis, we wish to provide the necessary background for and an explanation of two papers in different subfields of knot theory, The Forbidden Quiver of a Link, and Biquandle Fares and Link Invariants.

In Chapter I, we begin with an introduction to knot theory and knot invariants. We continue to present the example of Fox Colorings, and conclude the chapter with an example of the Fox Coloring Number Invariant.

In Chapter II, we explore the derivation and utilization …

Balancing Wood And Food: Assessing The Drivers And Spatiotemporal Conflicts Of Eucalyptus Plantation Expansion In Guangxi, China, Wen H. Cai, Qiuxia Huang, Jian Yang, Le Yu, Yuanzheng Yang, Jiaxing Zu, Jiali Wang, Zhenxian Li

Forestry and Natural Resources Faculty Publications

Eucalyptus has become one of the most widely cultivated tree genera in subtropical China, generating significant economic returns but raising land-use conflicts with agriculture. Understanding the driving mechanisms behind this expansion is crucial for sustainable land-use management. To inform strategies for balancing wood production and agricultural stability, we investigated the spatiotemporal expansion dynamics and predicted the potential suitable habitat distribution of Eucalyptus plantations using a Boosted Regression Tree (BRT) model. Our analysis revealed three distinct spatiotemporal expansion phases. Crucially, this expansion has progressively shifted from marginal sloped terrain onto flat valley bottoms, intensifying the agriculture-forestry conflict in the region. Climatic …

Evaluating Sampling Strategies To Monitor Southern Fox Squirrel (Sciurus Niger Niger) Populations, Casey Robin Hitchens

Theses, Dissertations and Capstones

Reliable population monitoring is essential for evaluating wildlife translocations and informing conservation management, yet traditional monitoring approaches are often labor intensive and require prolonged sampling. This study evaluated marking techniques, survey methods, and population estimation approaches for monitoring a translocated population of southern fox squirrels (Sciurus niger niger) at Marine Corps Recruit Depot Parris Island, South Carolina, USA (MCRDPI). From January-June 2023, I conducted six live trapping and camera trapping sessions across five survey sites. I compared the performance of color-coded collars and tail shaves for individual identification and the recapture probability between live traps and camera traps. Logistic mixed-effects …

Impact Of Cross-Client Heterogeneity In Federated Learning For Real-World Plant Disease Classification, Ritesh Janga

All Graduate Theses, Dissertations, and Other Capstone Projects

Deep learning applications are being adopted in agricultural image analysis that include challenges of data privacy and limited institutional data and heterogeneity of different types of architectures. However, Federated Learning is a model that allows collaborative training on data that does not have to be shared among parties. Therefore, Federated Learning is an effective method of collaborative training; however, its comparative effectiveness as compared to individual (local) training on diverse architectures has never been examined in an agricultural context. The objective of this study was to examine Federated Learning for the purpose of crop disease classification on extreme non-IID distributed …

Rethinking Ai Literacy Education In Higher Education: Bridging Risk Perception And Responsible Adoption, Shasha Yu, Fiona Carroll, Barry L. Bentley

School of Professional Studies

As AI becomes increasingly embedded across societal domains, understanding how future AI practitioners—particularly technology students—perceive its risks is essential for responsible development and adoption. This study analyzed responses from 139 students in Computer Science, Data Science/Data Analytics, and other disciplines using both explicit AI risk ratings and scenario-based assessments of risk and adoption willingness. Four key findings emerged: (1) Students expressed substantially higher concern for concrete, explicitly stated risks than for abstract or scenario-embedded risks; (2) Perceived risk and willingness to adopt AI demonstrated a clear inverse relationship; (3) Although technical education narrowed gender differences in risk awareness, male students …

Computationally Modelling Nmda Blockages Within A Neural Network, Anya Raetsch

UNH URC Open (2026 and after)

The N-Methyl-D-Aspartate (NMDA) Receptor is fundamentally important to memory formation within the brain due to its control of calcium entry into the cell.  In recent years, there has been an increased interest in long-term effects of NMDA blockages on the brain, due to the “re-wiring” of communication channels (synapses) between neurons. This project models the effects of NMDA blockages due to drugs such as Ketamine, and how the blocking of NMDA receptors affects firing rates, which can then be applied to studying long-term plasticity within the neural hierarchies. Using the Nest Online Simulator, a 50x50 grid of neurons was created …

Soil Organic Carbon And Soil Health Property Responses To Land Management Across Topographic Positions, Mia D. Makovsky

All Graduate Theses, Dissertations, and Other Capstone Projects

uring the last ice age, ice sheets advanced and retreated across the upper Midwest, leaving behind a landscape characterized by poorly drained hummocky topography. Well-aerated soils have formed on uplands and lowlands are dominated by hydric soils. These wetlands and hydric soils have potential to store large quantities of carbon, particularly compared to the well-aerated uplands, but many have been drained and cultivated for decades. Conservation agriculture methods have emerged to protect and conserve soil health from negative effects due to cultivation.The purpose of this study is to determine how agricultural management practices and landscape properties (e.g, topographic position) affect …

Reinforcement Learning-Enabled Control And Design Of Rigid-Link Robotic Fish: A Comprehensive Review, Nhat Dinh, Darion Vosbein, Yuehua Wang, Qingsong Cui

Faculty Publications

With the rising demand for maritime surveys of infrastructure, energy resources, and environmental conditions, autonomous robotic fish have emerged as a promising solution with their biomimetic propulsion, agile motion, efficiency, and capacity for underwater inspection, monitoring, data collection, and exploration tasks in complex aquatic environments. Inspired by fish spines, rigid-link fish robots (RLFRs), a category of robotic fish, are widely utilized in robotics research and applications. Their rigid, actuated joints enable them to reproduce the undulatory locomotion and high maneuverability of biological fishes, while the modular nature of rigid links between joints makes them cost-effective and easy to assemble. This …

Fulbright Project In Iceland In The Summer Of 2026, Irina Filina

Nebraska Academy of Sciences: Programs and Proceedings

This upcoming Fulbright project is inspired by an ongoing debate in the scientific community about the tectonic origin of Iceland. A long-standing theory of Iceland’s formation by excessive magmatism at the Mid-Atlantic spreading center over the well-known hot spot (i.e., oceanic crustal affinity) was recently challenged by the alternative hypothesis that the Icelandic crust is continental in nature and is being stretched and gradually modified by magmatic processes. Based on this hypothesis, a new sunken continent, Icelandia, has been proposed. One of the foundations for the proposed Icelandia is the presence of felsic lavas (indicative of continental flavor in the …

Ordered Mini-Batch Training For Differentially Private And Encrypted Logistic Regression, Ryan Leone

Theses, Dissertations and Culminating Projects

Logistic regression has found extensive use as a supervised machine learning algorithm due to its simplicity and efficiency in binary and multivariate classification tasks. As data sharing grows across connected devices, safeguarding sensitive personal and industrial information is of increased importance. Privacy-preserving machine learning techniques such as differential privacy and homomorphic encryption offer mathematically rigorous security guarantees, but introduce difficult accuracy, privacy loss, and computational overhead issues. This thesis investigates PPML for logistic regression through a collaborative mini-batch training framework. I propose and implement an ordered mini-batch strategy, compare it to standard shuffled methods, then integrate differential privacy noise injection …

Holistic Stormwater Management In The Bound Brook River Basin, New Jersey, Sana Mirza

Theses, Dissertations and Culminating Projects

This dissertation presents a holistic framework for stormwater management in the Bound Brook River Basin, an urban watershed in central New Jersey that faces chronic nutrient enrichment and climate-driven hydrologic changes. The research integrates water-quality trend analysis, hydrologic modeling, and low-impact development (LID) optimization to assess current and projected watershed responses. By combining empirical monitoring data with downscaled climate simulations and spatial prioritization, the study utilizes a holistic approach for stormwater management planning. The first objective was to characterize nutrient dynamics and hydrologic transport pathways for nitrogen, phosphorus, and total suspended solids (TSS) from 2004 to 2019. Using bi-monthly monitoring …

An Integrated Approach To Groundwater Management In Northern New Jersey Watersheds, Toritseju Oyen

Theses, Dissertations and Culminating Projects

Groundwater deterioration has emerged as a pressing global concern, with widespread observations of declining water quality in various regions. The predominant cause of this deterioration is attributed to anthropogenic activities, which are deeply intertwined with daily human practices that contaminate water resources. Over the decades, many forested and wetland areas have been converted mainly for increased urbanization and industrialization use in northern New Jersey. The region’s watershed, already characterized as a low-yield aquifer, is facing deterioration because of continuous change in land cover. Anthropogenic activities aimed at providing solutions to problems, such as food scarcity, icy roads during the winter …

Hierarchy And Ideology Antagonism: Artificial Intelligence In Ridley Scott's Alien, Grace Anastasia Pula

Theses, Dissertations and Culminating Projects

This thesis examines the objectively threatening structure of artificial intelligence (AI) in the narrative plot of Alien and how it exerts control over the humans. Using a structuralist approach with Louis Althusser's Ideological State Apparatuses (ISAs), I will examine the character relationships and how an android, Ash, enforces a patriarchal, hierarchical system. Drawing on Mark Coeckelbergh’s AI Ethics and Jacques Ellul’s The Technological Society, I will outline broader fears that technology will surpass human intellect and serve a destructive function within an oppressive system. Analyzing two examples of AI characters, the film showcases capitalist ambitions through technological identities and their …

A Deep Learning Approach For Mapping Shrubs, Wet Tundra And Surface Water In Arctic Tundra With Very High Resolution Satellite Imagery, Darko Radakovic

Theses, Dissertations and Culminating Projects

Arctic shrub expansion threatens to accelerate permafrost thaw through complex feedbacks, yet whether shrubs primarily indicate or drive degradation remains unresolved. This dissertation integrates deep learning analysis of two decades of satellite imagery with LiDAR canopy structure and radar soil moisture data to reveal that shrubs play a dual role: young, expanding shrubs signal active permafrost thaw, while mature, tall shrubs stabilize underlying permafrost through insulation. By demonstrating that vertical canopy structure predicts thaw depth better than cover extent alone, this work establishes a scalable framework for monitoring permafrost vulnerability across the rapidly changing Arctic. Arctic shrub expansion is accelerating …

Preliminary Investigation Of The Carbon Storage Potential In The Fort Worth Basin: Reservoir Characterization And Modeling Of The Lower Atoka Grant South Sand In Tarrant County, Texas, Mary Ann M. Moody

Earth & Environmental Sciences Theses

Carbon capture and storage (CCS) is crucial for mitigating atmospheric carbon dioxide (CO₂) emissions that rise from industrial activities. Paleozoic sedimentary basins in Texas are significant reservoirs for hydrocarbon production, and when depleted, show promise for CCS. Long-term reservoir storage suitability requires a multifaceted approach, including site screening and ranking, as well as reservoir characterization, modeling, and simulation. This project first evaluates the CCS potential for the Fort Worth Basin in North Central Texas, then focuses on reservoir characterization of the Lower Atoka Grant South (STH) Sand in Tarrant County and finally assesses the sand’s CO₂ storage …

Developing Collaboration And Community Through An Online Virtual Modality: Participatory Action Research, Jennifer Reed

Doctor of Education Dissertations

This action research study examined educators’ perceptions of collaboration and community within a virtual professional learning community and investigated how participation influenced collaborative actions over time. The study also compared the needs and goals of secondary and postsecondary educators participating in a shared VPLC model. Grounded in the Community of Inquiry and Online Collaborative Learning theoretical frameworks, this study addressed a growing need for effective, flexible professional learning structures that support collaboration across educational contexts. Data were collected from six educators, including three secondary and three postsecondary instructors, through pre- and post-administration of the Professional Learning Community Assessment–Revised, recorded virtual …

Artificial Intelligence Adoption In The Workplace. An Exploration Of Augmentation, Oyinkansola O. Sodiya

Management Dissertations

As collaborative work with artificial intelligence (AI augmentation) gains interest, it is crucial to investigate factors that affect how employees perceive and use AI tools at work. Drawing on task-technology fit and technology adoption theories, this dissertation examines the ways in which task dimensions, organizational contexts, and individual differences affect the perceived usefulness of working with AI tools. This dissertation demonstrates that task-technology fit is fundamental. Employees in jobs with high information processing demands are likely to positively perceive the usefulness of AI augmentation relative to employees in jobs with high interpersonal demands. Employees with more proactive personalities perceive greater …

Toward Interpretable Multi-Omics Multimodal Biomedical Artificial Intelligence, Yanjun Lyu

Computer Science and Engineering Dissertations

The complexity of human disease arises from biological processes that unfold across multiple scales, from molecular variation through cellular function, tissue organisation, brain phenotypes, each of which is associated with distinct measurement modalities, regularities, and characteristic. Contemporary biomedical artificial intelligence has brought the opportunity to reveal the complexity with in; however, its methodological default, in which models are trained on most readily available modality, does not adequately engage with the multi-scale connected structure by which biological meaning is constituted. The research area of multi-omics and multi-modal AI for biomedicine remains at an early exploratory stage, and the work presented in …

Uncertainty Quantification, Propagation & Conjunction Assessment In Orbital Mechanics Using Generalized Polynomial Chaos Expansion & 2-Dimensional Conjunction Plane Analysis Techniques, Monalisa Karim

Mechanical and Aerospace Engineering Theses

Uncertainties, that are inherent to dynamic models, can be associated with state initial conditions, force modelling errors, navigation and actuation errors. In system modelling stochastic differential equations are used to represent dynamic phenomena with uncertainties, for which the solutions are probability density functions of quantities of interest characterizing the realization of the stochastic processes. In Polynomial Chaos Expansion (PCE) propagation, these solutions are represented as weighted sums of multivariate spectral polynomials that are functions of the input random variables. Generalized polynomial chaos expansion (gPC) is an extension to the original homogenous PCE which projects the random solution onto a basis …

Flow Injection Determination Of Fluoride For Total Organic Fluorine Analysis, Memona Zulafiqar

Chemistry & Biochemistry Theses

Poly- and perfluoroalkyl substances (PFAS) are anthropogenic chemicals that have gained increasing attention due to their association with a wide range of adverse health effects. These compounds are highly diverse, with approximately 15,000 PFAS reported. Their exceptional environmental stability and strong tendency to bioaccumulate result in environmentally relevant concentrations that typically occur at very low levels, often in the ng L⁻¹ range. This chemical diversity presents a major analytical challenge, as reference standards are available for only a limited number of PFAS. Consequently, conventional targeted analytical methods frequently quantify less than 1% of the total PFAS present, leading to a …

Liutex - A Fluid Vortex, Oscar Alvarez

Mathematics Dissertations

Fluid vortices are found everywhere in our universe. A vortex can take the form of almost anything - from the classical spiral vortex to chaotic plumes. Defining a vortex physically and mathematically is absolutely necessary if we desire to study vortices and their interactions with each other as well as our physical world. Fluid vortices are incredibly important in the study of turbulent flows. From determining wear, optimizing design for better flow, efficiency, etc., to even predicting the weather on Earth or other planets, having the ability to measure vortices in fluid flow is invaluable. In this study, I investigate …

An Investigation On Downwind Impacts Of The Keweenaw Peninsula On Lake-Effect Snow Events, Thomas M. Pavell

Dissertations, Master's Theses and Master's Reports

Lake-effect snow (LES) produces copious amounts of snow across the Great Lakes region. While mechanisms and impacts are well-understood, they remain difficult to observe and study over Lake Superior and the Upper Peninsula of Michigan due to a large gap in radar coverage and sparse in-situ measurements. The goal of this project aimed to characterize variables present across Lake Superior and counties on and downstream of the Keweenaw Peninsula that contribute to the formation and evolution of lake-effect snowbands. Nine different lake-effect snow events were analyzed in this project, identifying structures and features resulting from upstream passage over the Keweenaw …

Adaptive Control For A Robotic Bipedal Device Using A Hybrid Discrete-Continuous Reinforcement Learning Strategy, Karla Rincon-Martinez, Wen Yu, Isaac Chairez

Mathematics Faculty Publications

This research develops and implements a novel reinforcement learning (RL) architecture to address the trajectory-tracking problem in bipedal robotic systems under articulated-joint constraints. The proposed RL framework extends previously designed adaptive controllers characterized by state-dependent gain structures. The learning mechanism comprises two hierarchical adaptation layers: the first employs an adaptive dynamic programming (ADP) formulation to approximate the Bellman value function using a class of continuous-time dynamic neural networks. In contrast, the second uses an iterative optimization scheme based on the deep deterministic policy gradient (DDPG) algorithm. The resulting control strategy minimizes a robust performance index defined over the tracking trajectories …

A Note On Asymptotics Of Estimators For Axially Symmetric Processes On The Sphere, Haimeng Zhang, Chunfeng Huang, Xiaohuan Xue, A.L.A.R.R. Thanuja, Bukola O. Adaramola

Research, Publications & Creative Work

Axially symmetric processes, those stationary in longitude but nonstationary across latitude, provide a flexible and physically meaningful class of models for global environmental data. Despite their wide use, the asymptotic properties of classical method-of-moments (MOM) estimators for these processes remain largely unexamined. In this work, we investigate MOM estimators of covariances and cross-variograms for axially symmetric Gaussian processes observed on regular latitude-longitude grids. First, we show that MOM covariance estimators are asymptotically biased. We then examine MOM estimators of cross-variograms, and prove that they are unbiased. However, using the block circulant structure of the covariance matrix and its Fourier diagonalization, …

Differential Impact Of Admission Type And Clinical Complexity On Diabetes Hospitalization Costs Among African American And Hispanic Patients In Southeastern Virginia, Ismail El Moudden, Asra Amidi, Reem Sharaf-Alddin, Michael C. Bittner, Qi Zhang

Department of Obstetrics & Gynecology Faculty Publications

Background

Diabetes mellitus (DM) imposes substantial healthcare costs with documented disparities among African Americans and Hispanic patients. To inform care delivery and resource allocation, this study identified hospitalization cost predictors among African American and Hispanic patients with diabetes in Southeastern Virginia.

Methods

We analyzed 6,011 hospital discharges from the Virginia Health Information database (2016-2020) for adults aged 18-85 with diabetes. Discharges were classified by Medicare Severity Diagnosis-Related Groups: DM with complications/comorbidities (DCC, n = 3,328), DM with major complications/comorbidities (DMCC, n = 1,518), and DM without major complications/comorbidities (DWO, n = 1,165). Because cost distributions were right-skewed (skewness 3.5-8.24), we …

Consensus And Controversies Of International Guidelines For The Diagnosis, Surveillance, And Management Of Fetal Growth Restriction: An Updated Comparison, Daniele Diane Mascio, Suneet P. Chauhan, Tullio Ghi, Asma Khalil, Juliana G. Martins, Sara Sorrenti, Tamara Stampalija, Fabrizio Zullo, Francesc Figueras

Department of Obstetrics & Gynecology Faculty Publications

OBJECTIVE: To compare areas of consensus and disagreements across contemporary international and national guidelines on the diagnosis, surveillance, and management of fetal growth restriction (FGR).

DATA SOURCES: Electronic searches of MEDLINE from database inception up to March 2026 using MeSH terms and keywords related to FGR and guidelines. STUDY ELIGIBILITY CRITERIA: Critical, structured comparison of national or international guidelines on FGR published since 2010. Final inclusion required unanimous agreement from all authors.

STUDY APPRAISAL AND SYNTHESIS METHODS: Pre-specified extraction across domains: definition; prediction/prevention; surveillance tools and frequency; delivery timing and mode; and labor induction methods. Dual data …

Event-Based Predefined-Time Synchronization For Complex Networks With Deception Attacks: An Asynchronously Intermittent Strategy, Lei Xue, Jiong Yu, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article studies the practical predefined-time synchronization (PPTS) for complex networks (CNs) under deception attacks based on the asynchronously intermittent event-triggered control (AIE-TC). Notably, AIE-TC effectively integrates the advantages of asynchronously intermittent control (AIC) and event-triggered control, where AIC provides each subsystem node with independent control and rest intervals. Besides, all synchronization errors of the CNs converge to an adjustable neighborhood within the predefined time by designing a bounded time-varying function into the controller. Moreover, this article considers that the transmission network is subjected to stochastic deception attacks modeled by a Markov process, which captures the state-driven dynamic transition characteristics …