Digital Commons Network^™

Remediation Impacts Metal Concentrations And Metal Tolerant Bacteria In Soils Of The Missouri Tri-State Mining District, Ophelia R. Pettington

Graduate Theses/Dissertations

After over 100 years of Zn and Pb mining in the Tri-State mining district (TSMD), former mines continue to be sources of metals. Metal contaminated soils can be remediated using plant-microbe interactions. Plants manipulate their microbiome and recruit microbes to increase metal tolerance. Remediating bacteria are site-specific and identifying native microbes can accelerate remediation efforts. Studies relating microbes and metal concentrations in remediated areas in the TSMD are scarce. I collected root and bulk zone soils associated with Andropogon virginicus from remediated and non-remediated sites in Webb City, MO. I used 16S rRNA gene amplicon sequencing to evaluate the bacterial …

Synthesis And Characterization Of The New G3 Family Of Organoantimony(V) Cyanoximates, Thao Trang Phan

Graduate Theses/Dissertations

Bacterial infections pose a serious threat to humans by developing resistance, rendering antibiotics ineffective. Of the 12 antibiotics recently approved since 2017, 10 belong to an already existing class. Various resistance mechanisms, such as reduced drug uptake, active efflux, drug inactivation, and target modification, can significantly reduce the efficacy of entire classes of antibiotics. Discovering novel strategies to overcome diverse mechanisms of resistance and improve therapeutic efficacy is in high demand. Inorganic compounds with organic ligands (both complexes and organometallics) represent a new class of compounds against which antimicrobial resistance has not yet been established. Recently, we discovered two series …

Evops: Evolutionary Patch Selection In The Embedding Space Of Whole Slide Images, Saya Hashemian

Theses and Dissertations (Comprehensive)

Computational pathology increasingly relies on the analysis of Whole-Slide Images (WSIs), which capture tissue specimens at gigapixel resolution. Because a single slide is far too large to process directly, the

prevailing paradigm decomposes each WSI into thousands of small patches and encodes them as high- dimensional feature embeddings using deep learning backbones. While effective, this paradigm carries a

substantial cost: the resulting collections of patch embeddings are computationally expensive to store and process, and they are frequently dominated by redundant, homogeneous, or otherwise uninformative tissue regions that dilute the diagnostic signal. Existing patch selection methods largely depend on heuristic or …

Theoretical Study Of Long-Range Molecular Interactions, Adrian Luis Batista-Planas

Doctoral Dissertations

Describing intermolecular forces is fundamental to modeling and predicting the behavior of molecular systems. In particular, long-range molecular interactions—with electrostatic, induction, and dispersion as main components—play a critical role, especially for low-temperature and low-density regimes. Long-range interactions are often described through perturbation theory, representing the electronic charge distribution via multipolar series of the moments and polarizability tensors corresponding to each molecule. However, while the theory is well-established, obtaining the resulting analytical expressions (and their practical implementation) constitutes a highly complex and system-dependent task. To address this challenge, we developed Long-Range-Fit (LRF), an interactive and user-friendly software package designed to automate …

Milankovitch Paleoclimatic Signals In Upper Permian–Lower Triassic Fluvial-Lacustrine Records, Bogda Mountains, Greater Turpan-Junggar Intracontinental Rift Basin, Nw China, Wentao Zhang

Doctoral Dissertations

"The objective of this study is to understand whether Milankovitch climatic and/or tectonic processes influenced the sedimentation of the upper Permian–Lower Triassic fluvial-lacustrine cyclic deposits in Bogda Mountains, greater Turpan-Junggar intracontinental rift basin, Xinjiang Uygur Autonomous Region, NW China. This study carried out gamma analysis, gamma and astronomical tuning, and spectral analysis on the Wutonggou, Jiucaiyuan, and Shaofanggou low-order cycles of the South and Central Taodonggou, South and North Tarlong, Dalongkou, and Zhaobishan sections. Stable and positive gamma values support the assumption of facies-dependent sedimentation rates for non-marine facies. The sedimentation rates range from 0.04 to 2.43 m/kyr, and 0.21 …

Security And Energy-Efficiency In Federated Learning, Priyesh Ranjan

Doctoral Dissertations

Federated Learning (FL), which facilitates collaborative model training and protects users' privacy, has drawn great interest from the research community. With FL, the participants train their models on local data and submit the corresponding updates for aggregation to a server. While concealing the participants' identities, FL may attract adversaries aiming to hamper the underlying model. These adversaries aim to submit malicious weight updates that corrupt the performance of the server model. Further, these models when communicated to the participating clients extend the behavior which is undesirable. Additionally, FL suffers from increased energy consumption at the edge device level due to …

Trust-Aware Algorithms For Stackelberg Ground Vehicle Routing, Doris Evelyn Meredith Brown

Doctoral Dissertations

Despite decades of research focused on reducing ground vehicle traffic congestion, urban traffic networks worldwide continue to experience traffic flows that lead to increased network travel times, largely resulting from the routing decisions of individual vehicles. To address this challenge, this work leverages a Stackelberg game framework to model the interaction between a vehicle agent and a routing authority as a leader–follower game, in which the routing authority proposes routing interventions to which the agent responds. This research contributes to existing traffic mitigation literature by exploring the role of trust in route decision-making and providing trust-aware algorithms that influence vehicle …

An Energy-Stable Mixed Cg-Dg Scheme For A Full Shliomis Phase Field Model Of Two-Phase Ferrofluid Flows, Mahdi Gharehbaygloo

Doctoral Dissertations

"Ferrofluids are magnetic nanoparticle suspensions whose motion couples surface tension, flow field, magnetostatics, and magnetization dynamics. This dissertation develops, analyzes, and validates an energy-stable finite element method for a two-phase ferrofluid model that couples the Cahn-Hilliard equations with the full Shliomis model of single-phase ferrofluids, retaining its damping torque term, magnetic torque term, and magnetic stress term.

The spatial discretization is a mixed continuous Galerkin (CG) and discontinuous Galerkin (DG) formulation. It uses continuous ��2 elements for the phase field, chemical potential, velocity, and magnetostatic potential, discontinuous ��2 elements for the magnetization, and discontinuous ��1 elements for the pressure. The …

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 …

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 …

An Incidental Standard For Medical Ai, Nicholson W. Price Ii

Articles

Medical AI is poised to make a major difference in the provision of health. It brings major challenges, though: how can developers and implementers ensure that it will work safely and effectively—especially within the context of complex and highly variable health-care systems? Standards provide one key tool, potentially providing guidelines for everything from privacy to accuracy to how AI interacts with human clinicians. This Essay considers the last of these, describing a powerful quasi-standard from a surprising source: an FDA guidance document that tells developers when certain AI systems are not considered medical devices, and are therefore not regulated by …

Investigation Of Reey Concentrations In Argillaceous Rocks Associated With Coal Beds In Southwestern West Virginia, Alyssa Cameron Long

Theses, Dissertations and Capstones

Rare earth elements (REEs) and Yttrium are classified as “critical minerals” that are used in many industries and are typically extracted from carbonatites and related alkaline plutonic rocks. The limited availability of REE+Y requires finding alternate sources such as coal fly ash, tonstein, fireclays, and shales. This study investigates the potential enrichment of shales, fireclays, and siltstones interbedded with coal from southwestern WV in REEY, and the mechanisms of such enrichment. Using ICP-AES analysis of various rock types shows that shales, silty shales, and siderite nodules interbedded with Fire Clay and Chilton Coal beds in the Kanawha Formation record the …

An Exploration Of Geomagnetically Induced Currents And The Accessibility Of Geomagnetic Data Collection, Richard Le

Physics Theses

Geomagnetically Induced Currents (GICs) are electrical currents induced in long grounded conductors during geomagnetic disturbances. They represent one of the primary space weather hazards to critical infrastructure, particularly high-voltage power transmission systems and other grounded conductor networks such as pipelines. As modern society becomes more dependent on these systems, understanding and mitigating the impacts of space weather has become increasingly important. This thesis examines the physical mechanisms that generate GICs, from the interaction of the solar wind with Earth’s Magnetosphere to Magnetosphere-Ionosphere-Thermosphere (MIT) coupling and the current systems that drive geomagnetic disturbances (GMDs). Case studies from Zimbabwe and Finland illustrate …

An Ensemble Classifier For Ordinal Outcomes In High-Dimensional Genomics Data, Heranga K. Rathnasekara, Sinjini Sikdar

Mathematics & Statistics Faculty Publications

Analysis of genomics data for predicting disease outcomes is a fast-growing field in medical research. There often exist categorical, specifically, ordinal outcomes that need to be predicted based on genomic profiles. This has led to recent development of some high-dimensional ordinal classification methods that can address the large dimensionality of the genomic covariate set. These high-dimensional ordinal models tend to vary widely in their performance depending on the data they are applied to and the evaluation criteria used. In this article, we outline an ensemble ordinal classifier that integrates different ordinal modeling approaches through bootstrap-based model evaluation, multi-metric performance assessment, …

Three Decades Of Classifying Threatened Species: Lessons Learned From And About The Iucn Red List Criteria For Quantifying Extinction Risk, H. Resit Akçakaya, E. J. Milner-Gulland, Mike Hoffmann, Helen M. Regan, Ilona Naujokaitis-Lewis, Andre E. Punt, Kevin J. Gaston, David A. Keith, Stuart H. M. Butchart, Simon N. Stuart, Nigel J. Collar, Moreno Di Marco, Monika Bohm, Alex J. Berryman, David P. Mallon, Axel Hochkirch, Nicholas K. Dulvy, Malin Rivers, Thomas M. Brooks, James R. S. Westrip, Jonathan Paul Rodriguez, Craig Hilton-Taylor, Janet Scott, Simon Tarr, Sophie H. Ledger, Christi Linardich

Biological Sciences Faculty Publications

The IUCN Red List of Threatened Species, the most widely used global system for assessing species' extinction risk, has become a foundational source of information for conservation management, policy and research. Since the adoption of quantitative extinction risk criteria more than three decades ago, the Red List has expanded substantially in scope and influence, informing decisions ranging from species conservation and protected area designation to international agreements, corporate risk assessments and global biodiversity indicators. Given its central role, maintaining scientific rigour, transparency and trust in the Red List system is essential. Feedback from users, emerging from evolving applications and scientific …

Characterization Of Phytoplankton-Excreted Metabolites Mediating Carbon Flux Through The Surface Ocean, Yuting Zhu, Hanna S. Anderson, Eli Salcedo, Samuel E. Miller, Krista Longnecker, Melissa C. Kido Soule, Sheean T. Haley, Gretchen J. Swarr, Rogier Braakman, Sonya T. Dyhrman, Elizabeth B. Kujawinski

Chemistry & Biochemistry Faculty Publications

The marine labile dissolved organic carbon (DOC) pool is a dynamic reservoir of thousands of molecules that cycles approximately one-quarter of Earth’s primary production within days to weeks. After excretion by phytoplankton and other microbes, metabolites are rapidly consumed, resulting in low standing concentrations (picomolar to low nanomolar). Despite the decades-long search for labile DOC sources and molecular identities, marine phytoplankton exometabolomes are not well characterized, largely due to difficulties in measuring small polar molecules in saline water. Here, we profiled the exometabolomes of six axenic phytoplankton species representing key functional groups including a diatom (Thalassiosira pseudonana CCMP1335), a …

Nonpyrogenic "Black" Nitrogen Likely Plays A Major Yet Underrecognized Role In The Global Nitrogen Cycle, João Vitor Dos Santos, Aleksandar I. Goranov, Kyle M. Lambert, Theodoro Da Rosa Salles, Susan J. Carter, Ann Pearson, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

Condensed aromatic nitrogen (ConAN) is commonly found in soil and aquatic environments. ConAN is broadly viewed by the biogeochemistry community as a combustion-derived product leading to its frequent designation as pyrogenic “black” nitrogen. Here, we provide evidence that ConAN can also form through nonpyrogenic pathways. In an experiment simulating biomass oxidation, pine wood boards assembled with iron nails were exposed to 12 years of natural environmental conditions. Nitrogen concentrations increased from 0.2 to 1.2 wt % with increasing proximity to the nail. Ultrahigh resolution mass spectrometry showed enrichment of nitrogen-containing compounds within the lignin and condensed aromatic domains. X-ray spectroscopic …

Land Use Influences Dissolved Organic Matter Composition In The U.S. Coastal Critical Zone Network, Aleksandar I. Goranov, Elizabeth V. Whitney, Brian R. Moyer, Katherine L. Tully, Patrick G. Hatcher, Yu-Ping Chhin

Chemistry & Biochemistry Faculty Publications

Coastal watersheds are highly productive biogeochemical systems supporting robust coastal fisheries and contributing significantly to the marine gross primary production flux. These ecosystems are comprised of civil infrastructure, farms, forests, and marshes, and their diversity is reflected in the quantity and quality of dissolved organic matter (DOM). Here, we assess the role of farming in influencing DOM from surface waters of six coastal tidal creeks adjacent to forest and farm sites in the US Critical Zone Network. Molecular fingerprinting using electrospray ionization - Fourier transform - ion cyclotron resonance - mass spectrometry revealed that farm-influenced DOM was enriched in nitrogen-, …

Decomposing Shadow Prices Under Climate-Driven Growth Scenarios: Insights From An Elk Herd Case Study, Ranjit Bawa, Drew Bennett, Wai Yan Siu, Bailey Kirkland, David Finnoff, Jacob Hochard

ODU Articles

Natural capital accounting provides a framework for integrating ecological processes with economic valuation, but the mechanics of shadow price formation often remain opaque to resource managers and policymakers. Using the Clarks Fork elk herd in northwestern Wyoming as a case study, we decompose the shadow price of natural capital into its ecological, economic, and institutional components. Population dynamics are estimated using a linearized Ricker model and projected forward using a logistic projection, incorporating climate-driven reductions in intrinsic growth rates. These ecological scenarios are linked to a shadow pricing formulation that explicitly accounts for marginal benefits, harvest policy responses, discounting, and …

Amorphous Selenium Photodetectors For Liquid Noble Detectors, Michael Rooks

Physics Dissertations - Archive

Physics offers a way to connect deeply with the mysteries that surround us. Advances in detector physics, particularly in neutrino experiments and rare-event searches, have expanded our ability to probe phenomena that challenge how we describe the universe. Each discovery brings us closer to understanding the unknown, returning us to a sense of wonder that motivates exploration. My work on detector technology was inspired by a concept paper from Professor David Nygren, in which he noted the speculative possibility of integrating photon detection into a charge readout for pixelated liquid argon time projection chambers (LArTPCs) using the photoconductor amorphous selenium …

Tackling The Societal And Regulatory Challenges Of Emerging Technologies: A Case Study Of Deepfake, Jingyao Li

2026

Governing emerging technologies such as Artificial Intelligence (AI) poses enduring challenges for policymakers, industries, and societies. Early-stage governance is often hindered by limited understanding of technological implications, rapid innovation cycles, and resistance from powerful industry actors who favor minimal oversight. Yet, timely and effective governance is essential, as new technologies are most malleable in their formative stages. This dissertation examines how emerging technologies can be governed effectively by using deepfakes technology as a focal case. This dissertation comprises three interrelated studies.

The first paper reviews the literature on deepfakes and emerging technology governance, identifying the distinct characteristics of deepfake technology …

A Specification-Driven Framework For Self-Supervised Learning In Specialized Vision Domains, Mahmut S. Gokmen

Theses and Dissertations--Computer Science

Self-supervised learning (SSL) has emerged as a principled approach to visual representation learning that derives supervisory signal directly from unlabeled data, enabling foundation models to be trained at scale without manual annotation. Deployments in medical imaging and biometric recognition have demonstrated the potential of this paradigm, yet the assumptions that make SSL effective on natural image benchmarks fail systematically in specialized domains. Generic SSL pipelines encode a tacit assumption that the most informative correspondence is spatial proximity within a single acquisition. In specialized domains this assumption breaks at the level of the data-generating process: the signal that carries domain-specific information …

Local Energy Decay For Non-Stationary Damped Wave Operators, Nicholas Dj Arsenault

Theses and Dissertations--Mathematics

This work establishes integrated local energy decay (ILED) estimates for the damped wave equation on certain non-stationary spacetimes. The main technical result is a high frequency estimate that holds in great generality, provided that null geodesics trapped in a compact region are sufficiently damped. This is combined with low- and medium-frequency estimates to establish full local energy decay. We conclude by providing a counterexample where the damping assumption fails and local energy decay does not hold.

Understanding Möbius Inversion As Composite Of Dual Pairs, Isaac B. Kochmaan

Theses and Dissertations--Mathematics

Möbius inversion is a well-studied computational tool in number theory and combinatorics, but it exhibits a pattern which may be familiar to those who study categorical traces. In 2016, Kate Ponto and Michael Shulman characterized duality and traces in the bicategory of profunctors for a particularly nice class of one-cells. We extend these results. Consequently, we construct, for a given poset, a profunctor whose Euler characteristic is the Möbius function of said poset. In light of this, we propose a categorical notion of Möbius inversion.

Exploring The Limitations Of Substrate Scope In Dimethylallyltryptophan Synthases, Evan T. Miller

Theses and Dissertations--Pharmacy

Natural products (NPs), are the largest source of bioactive compounds in Nature, and are essential to the treatment of human disease. Nearly 50% of drugs approved for use from 1981 to 2019 owe some aspect of their development to NPs, either in terms of their structure, pharmacophore, or mechanism of action. However, NPs are difficult to structurally optimize. Chemoenzymatic methods for NP derivatization have been increasingly seen as practical alternatives to traditional synthetic methods. Prenyltransferases (PTs) are involved in the primary and secondary metabolism of plants, bacteria, and fungi, and they are key enzymes in the biosynthesis of many clinically …

Using Camera-Based Unmarked Spatial Capture-Recapture Modeling To Estimate Reintroduced Elk (Cervus Canadensis) Population Parameters And Distribution In Southeastern Kentucky, Claire Marie Muia

Theses and Dissertations--Forestry and Natural Resources

Estimation of population parameters is important for wildlife management decisions. Elk reintroduced to southeastern Kentucky experienced early irruptive population growth and are currently monitored using a statewide harvest-based statistical population reconstruction model (SPR) across the Kentucky Elk Restoration Zone (KERZ). Because the SPR model is spatially coarse and difficult to scale to the smaller management units comprising the KERZ, we conducted a spatially explicit capture-recapture study using a clustered camera-trapping array deployed for 10 weeks from June–August 2024 to estimate elk population parameters within Management Unit 4. Due to a lack of resights of GPS-marked elk, population parameters were estimated …

Microbial Community Structure In Global Soils, Matthew Jabro

CMC Senior Theses

Soil harbors the most diverse microbial communities on Earth, yet whether predictable community types exist across biomes and whether taxonomic composition encodes habitat of origin remain open questions at global scale. This thesis addresses both questions by applying unsupervised clustering and supervised classification to transformed 16S ribosomal RNA (rRNA) amplicon profiles from two independent datasets: the global topsoil survey of Bahram et al. (193 samples) and the Earth Microbiome Project (EMP) soil subset of Thompson et al. (2,209 samples). Application of a sample clustering method based on a mixture of Gaussian Graphical Models (MixGGM) identified 19 clusters in the topsoil …

Online Lifelong Optimal Adaptive Control Of Partially Uncertain Strict Feedback Discrete-Time Systems With Application To Quadrotor Uavs, Maxwell Geiger, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article considers the infinite time horizon optimal adaptive tracking control of partially uncertain strict feedback discrete-time (DT) systems with application to quadrotor uncrewed aerial vehicles (UAVs). First, the strict feedback DT system is transformed into an equivalent affine nonlinear DT system in terms of the tracking error dynamics. The optimal adaptive tracking control problem is solved using an augmented system approach, where a horizon of future bounded reference trajectory points is used in the augmented state, when compared to using a single point. It is assumed that the internal dynamics of the strict feedback system are unknown, but the …

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 …

An Empirical Framework For Evaluating Semantic Preservation Using Hugging Face, Nan Jia, Anita Raja, Raffi Khatchadourian

Publications and Research

As machine learning (ML) becomes an integral part of high-autonomy systems, it is critical to ensure the trustworthiness of learning-enabled software systems (LESS). Yet, the nondeterministic and run-time-defined semantics of ML complicate traditional software refactoring. We define semantic preservation in LESS as the property that optimizations of intelligent components do not alter the system's overall functional behavior. This paper introduces an empirical framework to evaluate semantic preservation in LESS by mining model evolution data from HuggingFace. We extract commit histories, $\textit{Model Cards}$, and performance metrics from a large number of models. To establish baselines, we conducted case studies in three …