Digital Commons Network^™

Final Butte Priority Soils Operable Unit (Bpsou) Unreclaimed (Ur) Sites: Ur-35 Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

2022 Annual Operations And Maintenance Report 2022 Bres Annual Summary Report For Work Completed In Quadrant 2, Butte-Silver Bow Department Of Reclamation And Environmental Services

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Understanding The Impact Of Ransomware On Biotechnology, Tswvyim Vang

Electronic Theses, Projects, and Dissertations

Biotechnology encompasses the use of research on both biology and technology to create products that can advance in areas such as healthcare and agriculture. Because of the technology and products that arise from the use of biotechnology, the industry is especially targeted by cyber-attacks. A prominent type of cyber-attack that is utilized by cyber criminals on biotechnology is ransomware. The goal of this project is to determine the impact of ransomware on biotechnology. The research questions posed are: Q1) What are real examples of ransomware attacks that have occurred on biotechnology companies and what patterns can be identified by these …

Explainable Ai (Xai) For A Machine Learning Heart Disease Prediction Model, Sai Abhishek Sanchula

Electronic Theses, Projects, and Dissertations

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, necessitating the development of accurate and interpretable machine learning (ML) models for early diagnosis and risk assessment (World Health Organization, 2021). While ML algorithms such as logistic regression, decision trees, support vector machines (SVM) (Cortes & Vapnik, 1995), and deep learning models (LeCun et al., 2015) have demonstrated high predictive accuracy, their adoption in clinical practice is hindered by their black-box nature (Rudin, 2019). Explainable AI (XAI) techniques, including SHapley Additive Explanations (SHAP) (Lundberg & Lee, 2017), Local Interpretable Model-agnostic Explanations (LIME) (Ribeiro et al., 2016), and feature importance analysis …

On Bed Posture Recognition Using Deep Learning With Pressure Sensors, Farheen Akhter Ms

Electronic Theses, Projects, and Dissertations

In healthcare applications such as disease prevention, sleep quality evaluation, and patient monitoring, bed posture recognition is essential. Using pressure sensor arrays placed on top of or embedded in mattresses, this study investigates the application of deep learning models for non-invasive posture classification. Although they have been widely employed, traditional machine learning approaches like support vector machines (SVM) and k-nearest neighbors (KNN) sometimes struggle with feature extraction and real-time performance necessitating considerable processing resources. I implemented a model using conventional approaches to get over these restrictions, then fine-tuned it using the following deep learning architectures for bed posture recognition: ResNet-50, …

Silver Nanoparticles In Ammonia Sensing And Photovoltaics, Madhuka Liyanage

All Dissertations

Nanocomposite films (NCF) containing silver nanoparticles (AgNPs), separated by thin layers of silica/poly-4-vinylpyridine/polyvinylpyrrolidone, were fabricated via drop casting, spin coating, dip coating on glass substrate and drop casting on nylon filter membranes. The more uniform films were produced by drop casting on nylon filter membranes due to their solvent wicking properties. The films demonstrate electrical conductivity that varies in response to moist ammonia and water vapors. The changes in conductivity are attributed to hydrogen bonding between ammonia and water molecules with the silica/polymer layers, as well as the direct adsorption of ammonia onto the silver surface. Notably, NCFs with polyvinylpyrrolidone …

Qualitative And Quantitative Analysis Of New Psychoactive Substances And Related Metabolites Using Liquid Chromatography-Ion Mobility-Mass Spectrometry (Lc-Im-Ms), Ralph Aderorho

All Dissertations

The increasing prevalence of novel psychoactive substances (NPS) in illicit drug markets has posed significant challenges for forensic and clinical toxicology, primarily due to the structural similarity and diversity among these compounds. This dissertation investigates the application of advanced liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS/MS) techniques, using the high-resolution Structures for Lossless Ion Manipulations (SLIM) platform and the drift tube ion mobility spectrometry (DT-IMS), for the qualitative and quantitative analysis of various types of synthetic opioids, synthetic cannabinoids, psychedelics and xylazine. By combining IMS separations with mass spectrometry and targeted chemical derivatization, this work enhances the ability to distinguish and characterize …

Toward The Application Of Natural Language Processing In Electronic Health Record Analysis For Taxonomy Development, Latoya Mcdonald

All Dissertations

Electronic health records (EHRs) are pivotal resources for nurse practice because they increase the timeliness and reliability of patient information at the point of care and support access by multiple healthcare providers and the individual patients themselves. However, it is widely recognized that data extraction from EHRs is challenging due to the variability in the language used in clinical care notes and the lack of standardized terminology across healthcare systems. The broad objective of this dissertation is to develop taxonomy-based classification models for nursing care by applying feature engineering approaches to EHRs that include nursing care of ostomy patients following …

Development Of Small-Molecule Inhibitors For Bacteroides, Naegleria, And Toxoplasma Microorganisms And Synthesis Of N-Heterocycles From Thiolated Ene-Ynes And Azodicarboxylates, Samuel Kwain

All Dissertations

Humans and microorganisms are intricately interconnected, with microbes constituting an essential component of human biology and ecology. This interdependence necessitates a delicate balance between leveraging beneficial microbes and mitigating the impact of harmful ones. The human gut microbiome, home to trillions of microorganisms, predominantly comprises commensal species that support health. However, dysbiosis within this ecosystem has been linked to serious diseases. For instance, an overrepresentation of Bacteroides species is associated with Type I diabetes mellitus (T1D) and various chronic gut disorders, including ulcerative colitis, inflammatory bowel disease, celiac disease, and colorectal cancer. Similarly, Naegleria fowleri, a free-living amoeba, causes …

Climate Prediction As An Adaptive Force-Multiplier: Reasons For Hope In A Rapidly Changing World, Matthew D. Laplante

All Graduate Theses and Dissertations, Fall 2023 to Present

It's not unreasonable to feel pessimistic about our future under climate change. But "believing the science" doesn't require you to accept that we are headed toward apocalypse. It is true that human-caused climate change is real, it is underway, and our societies face many increased risks because of it. But that's just part of what climate science tells us about our future world. This same field is responsible for the recent and rapid development of tools and techniques that permit the identification of patterns in our oceans and atmosphere that will aid us in making increasingly accurate predictions about climate—the …

Potamogeton Crispus Invasion: Impacts On Native Aquatic Plants And Associated Faunal Habitat, Meghan-Grace Slocombe

All Graduate Theses and Dissertations, Fall 2023 to Present

Aquatic invasive plants are non-native plants that invade a water body and displace native aquatic plants. Invasion depletes the native plant community's ability to provide ecosystem services, including improved water quality, decreased problematic algae, and increased animal habitat. The loss of these ecosystem services reduces the value of fishing, boating, and swimming opportunities in aquatic ecosystems. The potential changes in plant communities and services are particularly important at sites targeted for restoration because project goals typically include increasing ecosystem services, including wildlife habitat. Curly-leaf pondweed (Potamogeton crispus L.) is a problematic invasive species in North America. To better manage …

To Bee Or Not To Bee: Investigating Pesticide Behavior Inside And Outside Of Semi-Field Cages, Mallory Bingham

Undergraduate Honors Capstone Projects

Bees play an important role in ecosystems and food production through pollination. One such bee, the alfalfa leaf cutting bee (ALCB) is a very efficient pollinator and is essential in alfalfa seed production. However, bees face increasing harm, most notably due to the deleterious effect of pesticides used in agriculture, and much research is dedicated to investigating the extent of effects that pesticides have on different bee populations. One common tool used to study the effects of pesticide exposure on bees is semi-field cages. These cages have some key advantages, such as restricting bee foraging to plots sprayed with pesticides …

Cache-Augmented Generation In Rag Pipelines: Fast And Memory-Efficient Approach To Multi-Agent Knowledge Query Systems, Yaju Gopal Shrestha

Honors Theses

This thesis presents an implementation and evaluation of Cache-Augmented Generation (CAG) for knowledge query systems, building upon the approach introduced by Chan et al. (2024). Traditional Retrieval-Augmented Generation (RAG) systems (Lewis et al., 2020) face challenges including high latency, excessive memory usage, and complex infrastructure requirements. By implementing a cache-augmented architecture that preloads relevant knowledge and eliminates real-time retrieval, our approach significantly improves response time while reducing resource requirements. The research demonstrates the effectiveness of CAG through a comprehensive implementation for The University of Southern Mississippi's chatbot system, achieving a 49.02% improvement in response time compared to traditional RAG approaches. …

Navigating The Challenges Of Coccidioides Surveillance: Insights From The Environment Of El Paso County, Texas, Tanzir Hossain

Open Access Theses & Dissertations

Coccidioidomycosis, or Valley fever, is a fungal infection resulting from the inhalation of spores from the Coccidioides species (C. immitis and C. posadasii), native to arid areas of the Western Hemisphere. Coccidioidomycosis presents considerable health hazards and can be fatal. It affects between 206,000 and 360,000 individuals annually, leading to 700 to 1,100 fatalities in the United States alone. In response to these issues, extensive research has concentrated on therapeutic goals for this infectious disease. Nonetheless, more limited research has focused on the environmental detection of its causative fungi, which is crucial for forecasting treatment needs and formulating preventive strategies. …

Enhancing Security And Resiliency In Operational Technology Environments Through Network Slicing And Federated Learning, Brian Giovanni Rodiles Delgado

Open Access Theses & Dissertations

The growing convergence of Information Technology (IT) and Operational Technology (OT) within Industry 4.0 environments has introduced new demands on industrial network infrastructure. As cyber-physical systems become increasingly interconnected, ensuring the secure, timely, and efficient exchange of critical data is essential. This thesis explores how network slicing, a method of creating isolated virtual network segments, can be applied within OT environments to address challenges such as latency, security, and resource allocation.

The first research question addressed in this thesis is: How can OT networks take advantage of NFV and SDN technology to become cyber resilient? This study examines the operational, …

A Sociocognitive Perspective On The Activation Of Productive Epistemic Resources In College Students' Understanding Of Chemical Equilibrium, Henk Steven Van Den Bogaard

Open Access Theses & Dissertations

Science education, particularly in higher education, has a content coverage problem: it has long been described as "a mile wide, an inch deep" in various consensus documents from the National Academies. In chemistry education, the most common general chemistry curriculum covers topics as chapters based on the popular Sienko and Plane 1960's general chemistry textbook. The limited time available in such fast-paced coverage may limit the instructor's modeling and assessment of key performances in developing a mechanistic understanding of complex chemistry phenomena. In this sociocognitive, qualitative investigation, general chemistry II students' responses to assessment prompts were used to activate cognitive …

A Profile Wald Test In M-Estimation, Reagan Kesseku

Open Access Theses & Dissertations

Despite the growing popularity of machine learning-based inference, classical statistical inference remains highly relevant in modern data science due to its interpretability and theoretical rigor. Among its core tools, the likelihood ratio test, Wald test, and score test are foundational methods for hypothesis testing within the maximum likelihood framework. Although these tests are asymptotically equivalent under regularity conditions, each offers distinct advantages depending on the context, computational demands, and the availability of parameter estimates. In this dissertation, we introduce a fourth method, the Profile Wald Test (PWT), within the broader M-estimation framework. The PWT is based on profile estimators of …

Clinicogenomic Insights For Prostate Cancer Progression, Kelvin Ofori-Minta

Open Access Theses & Dissertations

Prostate cancer (PrCa) remains a critical challenge in precision oncology due to several reasons including its apparent heterogenous condition, recurrence following treatment and rapid progressive forms. Therefore, identifying patients at risk of progression is essential to fast-track therapeutic decisions and improve outcomes. Despite recent advances in genomic and molecular profiling, conventional PrCa risk assessment tools heavily rely on a few clinical parameters, neglecting the prognostic potential of genomic biomarkers in the presence of clinical biomarkers. This study presents a computational pipeline to harmonize and evaluate the prognostic value of clinicogenomic profiles of patients in modelling progression free survival (PFS). PFS, …

Towards Mitigation Of The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Jaime Merin Guzman

Open Access Theses & Dissertations

Detecting and localizing faults in communication networks is critical to maintaining reliable and efficient network operations. The Network Link Outlier Factor with Most Likely Link (NLOF: MLL) algorithm has demonstrated its potential to automate this task but suffers from significant performance degradation under low network load conditions, where limited network flow data reduces its ability to localize faults. This thesis proposes and evaluates the performance of a synthetic traffic generation algorithm to be used with NLOF:MLL. This algorithm strategically injects synthetic flows that supplement the insufficient real network flows, thereby improving NLOF:MLL's performance under low-load conditions. Specifically, we select network …

Development Of Saddlepoint Methodologies For Sparse Sample Multiple Parameter Generalized Linear Models And Correlated Data Scenarios, Christopher Johnson

All Graduate Theses and Dissertations, Fall 2023 to Present

Parameter estimation using maximum likelihood techniques may be biased when sample sizes are small, event rates are low, or otherwise sparse counts exist in a parametric model. This in turn may lead researchers to draw invalid statistical conclusions when conventional methods are utilized. The saddlepoint approximation has potential to lessen the degree of bias in sparse data conditions through its use of moments beyond the mean and variance, which allows for more accurate approximations using a smaller number of observations. We propose two novel saddlepoint methods for use in practical analysis scenarios, as an alternative to maximum likelihood estimation. First, …

Machine Learning And Protein Engineering Approaches To Understanding Kinesin-5 Activity, Jason Eden Sanchez

Open Access Theses & Dissertations

Cancer is a term describing a collection of diseases that result in uncontrolled cell growth. Cancer has manifold etiologies and underlying cancers are rouge biochemical pathways involving many different proteins. In the current work, two approaches are used to enhance knowledge of kinesin-5, a potential cancer target involved in cell division. Kinesin-5 promotes cell division by cross-linking and separating microtubules in dividing cells. The first approach uses machine learning (ML) to identify small molecule inhibitors for kinesin-5. Though decades of research have uncovered classes of small-molecules which inhibit kinesin-5 in vitro and in vivo, no candidates have reached phase III …

Machine Learning And Time Series Forecasting For Hydropower Predictions, Jose Reynaldo Vega

Open Access Theses & Dissertations

Recent advancements in machine learning have led to the design of many neural network architectures aimed at solving real-world problems. Each network works to make predictions by finding patterns in the provided data. One common application is time series forecasting, where a model predicts future events based on historical time series data. Time series forecasting is used in a variety of fields, one example being in predicting water releases of Hybrid Floating Photovoltaic-Hydropower (HFPVH) systems. As global population growth drives an increase in energy demand, the need for resilient and sustainable energy generation has become urgent. HFPVH systems have emerged …

Yield Prediction Of Pv Solar Energy Systems And Its Application In The Energy Grid For Operational Efficiency, Pablo Bustamante

Open Access Theses & Dissertations

The generation of power from photovoltaic (PV) solar panels is influenced by a multitude of factors. These include the tilt and orientation of the solar panels, the latitude of their location, and the prevailing climate and weather conditions. Additionally, shading at specific locations, particularly if the panels are not part of a solar facility, can significantly impact their efficiency. The quality and efficiency of the panels themselves, along with the preventive maintenance of both the solar panels and associated components such as inverters and trackers, are also critical. Finally, the overall system design and installation play a vital role in …

Cyber Resiliency Framework And Mechanisms For Software Defined Tactical Networks, Anthony Castanares

Open Access Theses & Dissertations

Traditional tactical networks fail to achieve cyber resiliency for many reasons, but the most prevalent causes include flat designs, the absence of cyber detection capabilities at the lowest level, and immutable resource allocations after instantiation. These design choices allow network threats direct visibility to each device on the network, and the lack of detection allows infections to proliferate. Furthermore, tactical battlefield networks are difficult to secure because of the lack of persistent oversight by an intelligent agent that can exercise control over the network's topology or resources in real-time. However, advances in software-defined networking (SDN) provide an opportunity to address …

2023 Annual Operations And Maintenance Report 2023 Bres Annual Summary Report For Work Completed In Quadrant 3, Butte-Silver Bow Department Of Reclamation And Environmental Services

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Quantifying The Effects Of Urbanization On Stream Nutrient Loads And Decomposition, Caroline Anscombe

Graduate Theses and Dissertations

Urban stream syndrome (USS) refers to the common symptoms of degradation in urban streams globally. Two symptoms of USS are increased nutrient and salt concentrations in streams, affecting ecosystem structure and function. Excess nutrients negatively impact freshwater ecosystems, placing downstream habitats at risk of eutrophication and harmful algal blooms. Excess salt runoff, derived from road salt application, is toxic to freshwater organisms and affects leaf litter decomposition, the base of aquatic food webs. Here, I aimed to quantify the effects of nutrient pollution and salinization on urban water quality and ecosystem function. Despite the widespread consequences of nutrient pollution, most …

Exploring Latent Mediation Through Bayesian Regularization Methods Of Lasso, Ridge, Horseshoe, Spike-And-Slab, Ethan Harris

Graduate Theses and Dissertations

Regularization is a powerful tool to combat overfitting and drive sparsity in complex models. Regularization was initially applied in regression modeling but has been increasingly utilized in structural equation modeling where its utility in identifying the essential components has helped improve modeling. As structural equation models have increased in complexity both in the number of indicators but also the number of latent factors, researchers have begun to investigate how applying Bayesian regularization to these systems can further push the limits on modeling complex models with limited sample sizes. One area where research is limited is the application of Bayesian regularizations …

Achieving Flexible Fairness And Privacy In Federated Learning, Alycia N. Carey

Graduate Theses and Dissertations

Having access to large, high-quality datasets is crucial for training machine learning models that achieve satisfactory performance. Unfortunately, it is common that a single entity (e.g., mobile device or organization) does not have access to such datasets due to monetary or resource constraints. Traditional machine learning requires that all training data reside in a centralized location during the entire duration of model training, however, in many circumstances it is difficult or even impossible (e.g., due to governmental regulations) for multiple parties to combine their data to meet this constraint. Federated learning is a machine learning paradigm that facilitates the joint …

Geochemical Analysis For Potential Critical Mineral Resources In Carbon Fly Ash, Korei D. Patterson Teer

Graduate Theses and Dissertations

The growing demand for critical minerals, coupled with the increasing supply chain vulnerabilities, has intensified the need for alternative domestic resources of critical minerals beyond traditional mining. Many of these critical minerals are essential for advanced technologies, energy storage, and national security, yet the United States remains heavily dependent on foreign imports, particularly from China. This study evaluates the economic potential of critical mineral recovery from Carbon Fly Ash (CFA), a byproduct of coal combustion, to determine its viability as a secondary source of critical minerals. A geochemical and mineralogical assessment was conducted on CFA samples from various storage sites …

Conservation Agriculture Practice Effects On Greenhouse Gas Emissions From Fine-Textured Soils In Arkansas, Lauren Gwaltney

Graduate Theses and Dissertations

Biochar application and reduced tillage (RT) are both practices within the conservation agriculture framework, but specific impacts of these practices on direct greenhouse gas (GHG) emissions still require investigation in varied agricultural systems. This research aimed to evaluate the effects of biochar source (i.e., powder- and pellet-sized) and application rate (i.e., 0, 2.5, and 5 Mg ha^-1) on GHG production in simulated furrow-irrigated rice (Oryza sativa) in a greenhouse experiment, and to evaluate the effects of RT relative to conventional tillage (CT) on GHG production in soybean (Glycine max) in southeast Arkansas. Both studies …