Digital Commons Network^™

Method Validation Of The Cdc Bottle Bioassay And A Historical Record Of Polycyclic Aromatic Hydrocarbons In Glacier National Park, Evah F. Peard

All Graduate Theses and Dissertations, Fall 2023 to Present

Certain contaminants can persist in the environment for long periods of time, build up within living tissues, travel far from their origin, and harm both ecosystems and organisms. This thesis focuses on two types of contaminants: insecticides and polycyclic aromatic hydrocarbons (PAHs). Insecticides are manufactured to control pests while PAHs are found in oil and gas products and can be produced by industry, vehicle engines, and wildfires. Understanding how harmful these contaminants are and where they end up in the environment is critical for protecting environmental health.

First, I evaluated a widely used test developed by the Centers for Disease …

Assessing Ecological Integrity Of Streams Across The Western U.S., Jennifer L. Courtwright

All Graduate Theses and Dissertations, Fall 2023 to Present

Large-scale assessments of stream health (ecological integrity) are required by policies such as the U.S. Clean Water Act and provide critical information needed to properly manage public lands. Our ability to quantify the ecological condition of streams in the western U.S. and identify the causes of degraded conditions has previously been impeded by a lack of standardized large-scale datasets, high natural temporal and spatial variability of ecological attributes, and poor-quality land use data. I compiled large-scale monitoring datasets and built models to predict the values of ecological attributes (metrics) at a given site in the absence of human impacts. In …

Understanding And Predicting Precipitation Characteristics In The United States Through Machine Learning, Numerical Modeling And Measurements, Cody Luther Ratterman

All Graduate Theses and Dissertations, Fall 2023 to Present

Precipitation is one of the most important yet uncertain variables in the climate system. It varies dramatically in terms of timing, accumulation, rate, and phase, depending on location, season, circulation patterns, and atmospheric conditions. Precipitation forecasts, especially snowfall, are essential to supporting drought mitigation and water management in the Intermountain West. Because rainfall and snowfall lead to opposite effects on snowpack, accurately partitioning rain and snow is important to estimate snowpack levels, winter recreation, mountain ecosystems and runoff. The research findings in this dissertation have advanced the understanding and prediction of precipitation and snowpack in the U.S. by addressing the …

The Role Of Heterogeneity In Earthquake Rupture Dynamics: Insights From Friction Experiments On A 1-Meter Laboratory Fault, Alejandro Aguilar

All Graduate Theses and Dissertations, Fall 2023 to Present

Tectonic faults are made of many kinds of rocks and minerals, creating natural weak and strong zones along faults where earthquakes occur. These differences can affect how faults move, including whether slip occurs slowly and quietly or suddenly and destructively during an earthquake. However, it is not fully understood how these variations influence when earthquakes start, how fast they spread, and whether they stop or grow into large ruptures. This research studies how different fault materials interact during earthquake slip. Using a large laboratory machine that simulates fault movement under realistic conditions, we recreate earthquake processes and closely measure how …

Investigation Of Yy Production Methods For Invasive Channel Catfish Ictalurus Punctatus Population Management, Andrew M. Wisniewski

All Graduate Theses and Dissertations, Fall 2023 to Present

Aquatic invasive species are one of the leading causes of native fish declines in the Southwestern United States. Channel Catfish Ictalurus punctatus were introduced into the Colorado River Basin, including the San Juan River, New Mexico, Colorado, and Utah for fishery enhancement during the 20th century. This introduction has contributed to the decline of native species and despite intensive mechanical removal efforts, the Channel Catfish population has persisted in the San Juan River. The Trojan Sex Chromosome approach is a promising eradication strategy that proposes the production and release of Trojan sex chromosome carriers (YY) to skew a targeted population’s …

Mapler: An R Package For Estimating The Impact Of Climate Change On Maple Syrup Production, Matthew T. White

All Graduate Theses and Dissertations, Fall 2023 to Present

Successful maple sap tapping depends on the freeze/thaw cycle (i.e., temperatures fluctuating above/below freezing) during the winter and spring. Climate change threatens to alter the timing and duration of the tapping season. This necessitates research into how maple sap tapping will be impacted by climate change in order to help maple syrup producers prepare for the future. We define a sap day as a day where the freeze/thaw cycle occurred. Using information climate scientists use to predict future temperatures, we calculate how many sap days could occur each year. We develop software to analyze these sap day calculations to determine …

A Social-Ecological Systems Approach To Integrating Outdoor Recreation And Black Bear Management: A Michigan Case Study, Megan Dorothy Stone

All Graduate Theses and Dissertations, Fall 2023 to Present

Outdoor recreation sits at the intersection of social and ecological systems, representing one of the primary ways in which humans directly interact with their natural environment. As a result, outdoor recreation management must balance providing high-quality outdoor recreation opportunities while simultaneously protecting natural resources in protected areas. Balancing these concurrent management goals has become more challenging in recent years as participation in outdoor recreation increases. This can lead to numerous negative impacts on the environment, such as wildlife disturbance. In this study, I explore the challenges and opportunities for collaboration between managers of outdoor recreation and black bears in the …

Drought And Diet Breadth: Does Insect Specialization Influence Herbivory When Plants Are Under Stress?, Jakob Palmer

All Graduate Theses and Dissertations, Fall 2023 to Present

Climate change will alter precipitation worldwide, causing more frequent and severe drought events worldwide. Drought affects many ecological processes, including plant-herbivore interactions, which are critical to biodiversity and ecosystem health. A variety of plant characteristics can influence herbivory – such as how hairy, nutritious, or toxic a leaf is – and drought has been shown to alter many of these traits. Unique characteristics of herbivore species are also important: herbivores can either feed on a variety of plants (generalists) or a group of closely related plants (specialists). Specialists can cope with traits of the plants they eat, while generalists are …

Fostering Safe Space For Children In Online Navigation And Parent-Child Interactions, Rizu Paudel

All Graduate Theses and Dissertations, Fall 2023 to Present

As children and teenagers spend increasingly more time online, digital devices have become a major source of family friction. Disagreements frequently arise over privacy boundaries, and online activities. When these conflicts are unresolved, they often lead to broken trust and secretive behavior, leaving children vulnerable to digital harms like cyberbullying, toxic content, or account hacking. Therefore, it is important to create a safe and open environment for children where in order for them to share their feelings with parents. This dissertation investigates the human and technological dynamics of parent-child interactions, developing new ways to support collaborative conflict resolution and online …

A Data-Driven Nutrient Density Scoring Framework For Beef Using Principal Component Analysis, Teja Vuppala

All Graduate Theses and Dissertations, Fall 2023 to Present

Beef is one of the most nutrient-rich foods in the human diet, providing high-quality protein, iron, omega-3 fatty acids, B vitamins, and a wide range of other compounds important to health. However, current nutrition scoring systems used on food labels were designed to compare different foods to one another — for example, beef versus broccoli — and do not work well for judging the nutritional quality of different beef samples relative to each other. A grass-fed steak and a conventionally-finished steak can carry nearly identical Nutrition Facts panels while differing substantially in their content of omega-3 fatty acids, vitamins, and …

Optimizing Urban Forestry Through Green Infrastructure: Tree Health And Water Retention In Ciudad Juarez Rain Gardens, Tomas Rogelio Lizarraga Ruiz

Open Access Theses & Dissertations

Urban green spaces (UGS) in arid regions face significant challenges due to water scarcity and extreme thermal demand. This study evaluates the efficacy of Nature Based Solutions (NBS), rain gardens and median strips, in enhancing the physiological resilience of urban trees in Ciudad Juárez, Mexico. Using a comparative framework, the research monitored a native evergreen (Dermatophyllum secundiflorum) and an introduced deciduous species (Morus sp.) across six planting treatments. Statistical analysis reveals that green infrastructure (GI) acts as a critical physiological accelerant. Trees situated within rain gardens and medians significantly outperformed those in restricted pot and sidewalk settings, maintaining higher stomatal …

Learning To Unlearn: Unlearning And Meta-Unlearning For Continually Adapting Cybersecurity Threat Detectors, Daniel Lucio

Open Access Theses & Dissertations

Machine learning (ML) models deployed in non-stationary environments must continually adapt to evolving data distributions. This challenge is particularly critical in cybersecurity, where malware, intrusion techniques, and adversarial behaviors evolve over time. Continual learning primarily enables incorporating new knowledge while preserving prior knowledge, however, indiscriminately retaining obsolete and harmful information can hinder future adaptation and consume limited model capacity. We argue that effective adaptation should not only acquire new knowledge, but also selectively discard obsolete and less useful historical knowledge before learning from a new distribution. In this work, we propose a meta-learning framework that learns what to forget to …

Unsupervised Learning For Minimum Error Adaptive Sampling Of Atmospheric Vertical Temperature Profiles, Alejandro Medina

Open Access Theses & Dissertations

Uncrewed aerial systems (UAS) collect atmospheric data on fixed schedules, and endurance limits make blind searching costly. This thesis develops an unsupervised representation that summarizes a multi-decade radiosonde archive into a compact library of atmospheric states, giving a UAS an expectation of the column before it flies. The method standardizes both axes of a profile against the sounding's own surface conditions, which makes the representation independent of season and of station elevation. Applied to 27,270 soundings from Norman, Oklahoma, over the lowest 1.5 km of the atmosphere, 12 representative profiles reconstruct the record to within 1.0 °C of mean absolute …

Hfir Antineutrino Flux Mapping With Scale Mesh Tallies, Jacob Adam Mireles

Open Access Theses & Dissertations

This thesis develops and demonstrates a workflow for mapping the spatial distribution of reactor electron antineutrino flux around the High Flux Isotope Reactor (HFIR) using three-dimensional mesh tallies from the SCALE 6.3.1 Monte Carlo transport suite. A detailed HFIR model is executed with KENO, and the mesh-tally output is post-processed to construct a voxelized antineutrino source term. The source field is normalized to reactor power and propagated to sampled spatial points surrounding the reactor to generate three-dimensional source-side flux maps. The main analysis focuses on how the mesh-based HFIR antineutrino flux differs from an ideal point-source approximation. In the point-source …

Transnational Indigenous Environmental Justice: A Distant Comparative Study Of Nepali And U.S. Environmental Policies And Counter-Archives In Technical Communication, Shankar Paudel

Open Access Theses & Dissertations

This dissertation investigates how institutional communication, state bureaucracy, and Indigenous sovereignty intersect within Rhetoric and Writing Studies (RWS) and Technical and Professional Communication (TPC). Current TPC research increasingly focuses on social justice; however, the field still lacks ethical frameworks to deal with the complicated dynamics of transnational Indigenous Environmental Justice Communication (IEJC). This study addresses this gap by examining how two distinct Indigenous communities - the Tharus of Chitwan, Nepal, and the Ysleta del Sur Pueblo Tigua Indians of El Paso, Texas - communicatively navigate, contest, and resist state environmental policies.

Grounded in decolonial Distant Comparativism, Mestiza Consciousness, Rhetoric of …

Assessing The Health Impacts Of Pm2.5 And Ozone Exposure: A Study Of Hospitalizations In El Paso, Alexia Breanna Reyes

Open Access Theses & Dissertations

Air pollution has been widely associated with adverse cardiovascular health outcomes; however, most research in arid regions has focused on high-intensity dust events rather than routine, non-dust conditions. This study aimed to evaluate the association between non-dust air pollution and cardiovascular hospitalizations in El Paso County, Texas. A time series analysis was conducted using hospitalization data from 2010 to 2014. Daily counts on non-dust event days of cardiovascular hospitalizations, including hypertensive diseases, ischemic heart disease, cerebrovascular disease, and diseases of pulmonary circulation, were examined in relation to ambient concentrations of fine particulate matter (PM2.5) and ozone. Quasi-Poisson regression models with …

From Screening To Risk: Assessment Of Potentially Toxic Elements In Children's Toys Along The El Paso, Tx, U.S.A.-Ciudad Juarez, Chih, Mex Border Region, Jesus Rodriguez-Loya

Open Access Theses & Dissertations

Children are uniquely vulnerable to potentially toxic elements (PTEs), absorbing them more readily than adults and encountering them through the hand-to-mouth behaviors of early childhood. Exposure carries element-specific consequences: lead (Pb) impairs cognitive development with no established safe threshold; cadmium (Cd) damages the kidneys and reduces bone mineralization; arsenic (As) is a recognized carcinogen and developmental neurotoxicant; hexavalent chromium (Cr) is carcinogenic and induces allergic dermatitis; nickel (Ni) is the leading cause of allergic contact dermatitis in children; and excess zinc (Zn) disrupts copper absorption and causes gastrointestinal distress. Toys are a distinctive source of such exposure, yet none had …

Integrated Framework For Tsn-Enabled Ot Networks And Scalable Edge Computing To Enable Real-Time Feedback Loop, Taposh Kumer Sarker

Open Access Theses & Dissertations

The advent of Industry 5.0 envisions smart manufacturing characterized by human centricity, sustainability, and systemic resilience. Realizing this vision requires the seamless convergence of Information Technology (IT) and Operational Technology (OT) networks. However, integrating massive, stochastic IT edge computing workloads with deterministic physical control loops introduces severe architectural friction, inherently threatening the safety guarantees required by industrial machinery. To resolve this fundamental incompatibility, this dissertation proposes the Edge-Augmented Real-Time Industrial Control System (EA-RICS).

EA-RICS is a comprehensive, multi-layered architecture designed to dismantle systemic bottlenecks across the physical data plane, the centralized control plane, and the edge operating system. First, the …

Bpsou Grove Gulch Sedimentation Bay Draft Remedial Action Construction Completion Report (Ccr), Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Sludge-To-Sod: Sustainability In Action At Bull Creek Water Treatment Plant, Ava Baker

Goal 6: Clean Water and Sanitation

No abstract provided.

Protecting Wetlands In Georgetown County, Sophia Harrison

Goal 6: Clean Water and Sanitation

No abstract provided.

An Open-Source Evaluation Framework For Risc-V Co-Design-Based Decimal Arithmetic, Riaz Ul Haque Mian, Michiko Inoue

Research outputs 2022 to 2026

Hardware–software co-design is a balanced strategy for computationally intensive algorithms such as decimal computing. It can provide several Pareto points for the development of embedded systems in terms of hardware cost and performance. In this study, we propose an efficient and accurate evaluation framework for decimal computing. The framework was designed and developed for hardware–software co-design decimal arithmetic using the RISC-V ecosystem. New binary and decimal-oriented instructions supported by an accelerator were developed. The framework can perform cycle-accurate analysis for performance and assess hardware overhead for co-design-based decimal arithmetic. Unlike previous studies that focused primarily on implementing and evaluating individual …

Efficient And Universal Watermarking For Llm-Generated Code Detection, Boquan Li, Zirui Fu, Mengdi Zhang, Peixin Zhang, Jun Sun, Xingmei Wang

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have significantly enhanced the usability of AI-generated code, providing effective assistance to programmers. This advancement also raises ethical and legal concerns, such as academic dishonesty and the generation of malicious code. For accountability, it is imperative to detect whether a piece of code is AI-generated. Watermarking is broadly considered a promising solution and has been successfully applied to identify LLM-generated text. However, existing efforts on code are far from ideal, suffering from limited universality and excessive time and memory consumption. In this work, we propose a plugand- play watermarking approach for AI-generated code detection, named ACW …

Continuous Query For Top-K Maximal Sum Intervals Over Streaming Data, Zhongshuai Zhang, Xiaochun Yang, Baihua Zheng, Rui Zhu, Haomin Li, Bin Wang

Research Collection School Of Computing and Information Systems

The continuous identification of top-k maximal sum intervals using a sliding window over a data stream is a critical operation for applications in IoT and beyond. A maximal sum interval is a non-overlapping, contiguous subsequence with the maximal sum in a sequence of signed values. Existing algorithms are ill-suited for streaming contexts: they either exhaustively enumerate all intervals even for small k values, or depend on indexes that require frequent and costly restructuring. We propose a novel partition-based strategy. Our core insight is a partitioning scheme that guarantees that any maximal sum interval is fully contained within a single partition, …

Audeter: A Large-Scale Dataset For Deepfake Audio Detection In Open Worlds, Qizhou Wang, Hanxun Huang, Guansong Pang, Sarah Erfani, Christopher Leckie

Research Collection School Of Computing and Information Systems

Speech synthesis systems can now produce highly realistic vocalisations that pose significant authenticity challenges. Despite substantial progress in deepfake detection models, their real-world effectiveness is often undermined by evolving distribution shifts between training and test data, driven by the complexity of human speech and the rapid evolution of synthesis systems. Existing datasets suffer from limited real speech diversity, insufficient coverage of recent synthesis systems, and heterogeneous mixtures of deepfake sources, which hinder systematic evaluation and open-world model training. To address these issues, we introduce AUDETER (AUdio DEepfake TEst Range), a large-scale and highly diverse deepfake audio dataset comprising over 4,500 …

Left: Learnable Fusion Of Tri-View Tokens For Unsupervised Time Series Anomaly Detection, Dezheng Wang, Tong Chen, Guansong Pang, Congyan Chen, Shihua Li, Hongzhi Yin

Research Collection School Of Computing and Information Systems

As a fundamental data mining task, unsupervised time series anomaly detection (TSAD) aims to build a model for identifying abnormal timestamps without assuming the availability of annotations. A key challenge in unsupervised TSAD is that many anomalies are too subtle to exhibit detectable deviation in any single view (e.g., time domain), and instead manifest as inconsistencies across multiple views like time, frequency, and a mixture of resolutions. However, most cross-view methods rely on feature or score fusion and do not enforce analysis–synthesis consistency, meaning the frequency branch is not required to reconstruct the time signal through an inverse transform, and …

Timeradar: A Domain-Rotatable Foundation Model For Time Series Anomaly Detection, Hui He, Hezhe Qiao, Yutong Chen, Kun Yi, Guansong Pang

Research Collection School Of Computing and Information Systems

Current time series foundation models (TSFMs) primarily focus on learning prevalent and regular patterns within a predefined time or frequency domain to enable supervised downstream tasks (\eg, forecasting). Consequently, they are often ineffective for inherently unsupervised downstream tasks—such as time series anomaly detection (TSAD), which aims to identify rare, irregular patterns. This limitation arises because such abnormal patterns can closely resemble the regular patterns when presented in the same time/frequency domain. To address this issue, we introduce TimeRadar, an innovative TSFM built in a fractional time–frequency domain to support generalist TSAD across diverse unseen datasets. Our key insight is that …

Insect Abundance And Bat Use Of Fields For Foraging In The Cumberland Plateau, Caroline M. Abramowitz

All Theses

Bat populations and their insect prey are declining, making it urgent to understand how habitat features and management support both groups. Early successional habitat (ESH), grasslands and shrublands with reduced vegetative clutter and abundant flowering resources, may benefit foraging bats and nocturnal insects. This study examined how landscape context, patch characteristics, microhabitat features, and management (mechanical mastication and prescribed burns) affected insects and bats across 29 managed fields in Big South Fork National River and Recreation Area (TN/KY) from 2024–2025. Flight-intercept traps collected 25,297 insects across five orders. Though results were order-specific, vegetative composition and height were the strongest predictors …

When The Best-Fit Model Is Not Best: The Glass Slipper Fallacy And Latent Growth Mixture Modelling, Jonathan L. Chia, Markus Wettstein, Andree Hartanto

Research Collection School of Social Sciences

Despite the use of latent growth mixture modelling (LGMM) to study longitudinal changes, existing practices may inadvertently impede this very investigation. Although subgroup trajectories may theoretically differ in their structure (e.g., some subgroups being linear, some curvilinear), the current convention advocates overreliance on the baseline model to derive subsequent profile trajectories, which may obscure these structural differences. In this article, we provide a brief description of extant LGMM practices, after which we explicate the pitfalls of the current approach. Finally, we provide a principled approach for LGMM research moving forward. Specifically, we recommend specifying a set of theoretically plausible models …