Digital Commons Network^™

The Pure Yang Mills Field V2, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

We construct a pure Yang-Mills field based on a non-Abelian simple gauge group.

Axioms and the mass gap are satisfied.

Measurement Of 18f(Alpha,P)21ne With The Array For Nuclear Astrophysics And Structure With Exotic Nuclei (Anasen), Keilah S. Davis

LSU Doctoral Dissertations

Certain (α,p) reactions on proton-rich nuclei are among the most important nuclear reactions occurring during Type I X-ray bursts, as well as being impactful in stellar explosions during the Asymptotic Giant Branch (AGB) phase and on accreting white dwarfs (WD). However, large uncertainties remain for reaction rates on some radioactive nuclei due to the lack of direct measurements. The Array for Nuclear Astrophysics and Structure with Exotic Nuclei (ANASEN) is a gas target and charged-particle detector designed for direct measurements of (α,p) reactions. ANASEN was redesigned with two hexagonal barrels of 100-µm-thick silicon strip surrounding the beam axis over a …

Jiving With Llms: Assessing First Year Students’ Computer Programming Self Efficacy After Reading Code With Llms, Michelle Jarvie-Eggart, Joseph Roy Teahen, Daniel T. Masker, Jose Padilla, Leo C. Ureel Ii, Laura E. Brown, Scott Pomerville, Jon Sticken

Michigan Tech Publications

This study investigated the impact of leveraging generative artificial intelligence (GenAI) to assist 1st-year engineering and computer science (CS) students in reading code in a new (to them) language. Students were asked to comment code in FORTRAN. They were then asked to run the code through ChatGPT-4.0 for its comments and reflect on what they learned from the experience. Participants completed survey items from Ramalingam and Wiedenbeck’s Computer Programming Self-Efficacy Scale (CPSES) prior to and after the intervention. Additional open-ended reflective (qualitative) questions were added to the quantitative questions in the postintervention questionnaire. This study documents increases in self-efficacy for …

Metacommunity Coupled Epidemiological And Biophysical Modeling Of An Emergent Coral Disease, Benjamin Holmes Farmer

LSU Doctoral Dissertations

Emerging infectious diseases pose imminent risk to the marine realm and coral reefs in particular. Since its emergence in 2014, stony coral tissue loss disease (SCTLD) has dramatically reduced living coral cover in Florida and charted a similar course in the Caribbean. SCTLD is by far the most severe coral disease in history and has driven highly susceptible species to local extinction, yet the mechanisms driving the regional epizootic are not well understood. Here, we developed reef-scale parameterizations of disease spread using model sites in the lower Florida Keys, developed extensive metacommunity habitat maps for the US Caribbean, and then …

Re: Conditional Approval Letter For The Draft Final Butte Reduction Works (Brw) Smelter Area Mine Waste Remediation And Contaminated Groundwater Hydraulic Control Site Pre-Design Investigation (Pdi) Evaluation Report (Dated September 12, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Qualitative And Numerical Observations Into The Career Trajectories Of Early Career Academics: A Mathematical Model Approach, Oluwatayo M. Ogunmiloro

Tanzania Journal of Science

This study develops and analyzes a mathematical model that describes the interplay among different researcher groups within academia by focusing on how variables such as mentorship, access to funding, and academic peer influence affect the career trajectories of early-career, experienced, redundant, and successful researchers. Using stability theory and relevant theorems of differential equations, this study ensures the existence, uniqueness, positivity, and boundedness of the model's solutions. Additionally, the model’s equilibrium states, are analyzed to determine the local asymptotic stability. Numerical simulations using the Runge-Kutta fourth-order (RK4) method, implemented in Python, are performed to illustrate issues related to career growth within …

Re: Comment Letter For Draft Clark Tailings Consolidated Waste Management Area (Ctcwma) 2024 Data Summary Report (Dated October 15, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Data-Driven Prediction Of Superconducting Critical Temperature: A Linear And Regularized Linear Modeling Approach, Dipok Deb

Data Science and Data Mining

This study adopts a data-driven approach to estimate the critical temperature of superconducting materials using linear machine learning models. A comprehensive dataset derived from material physico-chemical properties was analyzed after systematic preprocessing and standardization. Three linear modeling strategies—Linear Regression, Ridge Regression, and Linear Regression with Subset Selection—were developed and evaluated using standard regression performance metrics. The findings demonstrate that both basic and regularized linear models can effectively capture the relationship between material features and superconducting behavior, offering robust and interpretable predictions. While feature selection enhances model transparency, it comes with a modest reduction in predictive capability. Overall, this work emphasizes …

Thermal Performance And Specific Energy Consumption Of Traditional Tobacco Curing Barns In Tanzania, Seuri S. Kilakoi, Baraka Kichonge, Thomas Kivevele, Mtaki T. Maagi, Jacob B. Lisuma

Tanzania Journal of Science

Traditional tobacco curing barns remain the dominant technology in Tanzania due to their low construction cost and accessibility, particularly in major producing regions such as Tabora. However, their thermal inefficiency results in excessive firewood use and environmental degradation. This study presents a field-based performance evaluation of a traditional flue-curing barn at the Tobacco Research Institute of Tanzania. Environmental parameters and fuel consumption were monitored at 15- minute intervals throughout the yellowing, leaf drying, and stem drying stages. The curing process handled 429 kg of fresh tobacco using 1,016 kg of firewood, equivalent to 16,256 MJ of energy input. The specific …

Rogue Waves In Extended Gross-Pitaevskii Models With A Lee-Huang-Yang Correction, Sathyanarayanan Chandramouli, S. I. Mistakidis, G. C. Katsimiga, D. J. Ratliff, D. J. Frantzeskakis, P. G. Kevrekidis

Physics Faculty Research & Creative Works

We explore the existence and dynamical generation of rogue waves (RWs) within a one-dimensional quantum droplet-bearing environment. RWs are computed by deploying a space-time fixed point scheme to the relevant extended Gross-Pitaevskii equation (eGPE). Parametric regions where the ensuing RWs are different from their counterparts in the nonlinear Schrödinger equation are identified. To corroborate the controllable generation—relevant to ultracold atom experiments—of these rogue patterns, we exploit two different protocols. The first is based on interfering dam break flows emanating from Riemann initial conditions, and the second refers to the gradient catastrophe of a spatially localized waveform. A multitude of possible …

High Spatiotemporal Resolution Monitoring Of Crop Water Stress Across The Contiguous United States Using Harmonized Landsat And Sentinel-2 Data, Na Chen, Yanlei Feng, Na Wang, Jevan Yu, Mohammad Reza Alizadeh, Yifeng Cui, Ning Ye, Wenzhe Jiao, Joshua B. Fisher, César Terrer

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Accurate and timely monitoring of crop water stress is essential for efficient agricultural water management, ultimately maintaining and improving crop productivity. While Landsat has been used for this purpose, its temporal resolution hampers timely detection of crop water stress. The recently released Harmonized Landsat and Sentinel-2 Version 2.0 dataset, which enables a higher-frequency time series of satellite observations (2–3 days, 30 m), offers a promising solution to this challenge. However, its potential for crop stress monitoring remained unexplored. In this study, we utilized 923 HLS satellite tiles to assess crop water stress across the contiguous United States (CONUS). Crop water …

Datamut: Deterministic Algorithms For Time-Delay Attack Detection In Multi-Hop Uav Networks, Keiwan Soltani, Federico Corò, Punyasha Chatterjee, Sajal K. Das

Computer Science Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs), also known as drones, have gained popularity in various fields such as agriculture, emergency response, and search and rescue operations. UAV networks are susceptible to potential security threats, such as wormhole attacks, jamming, spoofing, and false data injection. Time-Delay Attack (TDA) is a unique attack in which malicious UAVs intentionally delay packet forwarding, posing significant threats, especially in time-sensitive applications. It is challenging to distinguish malicious delay from benign network delay due to the dynamic nature of UAV networks, intermittent wireless connectivity, or the Store-Carry-Forward (SCF) mechanism during multi-hop communication. Some existing works propose machine learning-based …

2026 Revised Draft Final Bpsou Backfill And Cover Material Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Optimizing Proaftn Classifier With Ant Colony Algorithm: Enhanced Diabetes Detection Benchmarking, Feras Al-Obeidat

All Works

The increasing global prevalence of diabetes highlights the need for accurate diagnostic tools to improve early detection and effective treatment planning. Traditional classification models often struggle to achieve optimal performance due to limitations in parameter tuning and adaptability to complex datasets. To address these limitations, this article introduces PROAnt, an innovative learning approach designed to enhance the robustness and efficiency of the PROAFTN multicriteria classification method. PROAnt leverages the computational power of ant colony optimization (ACO) to dynamically fine-tune and optimize the key parameters, such as intervals and weights, at the core of the PROAFTN classification process. This learning methodology …

The Sunday Math Circle, Nathan Pflueger

Journal of Math Circles

Bob and Ellen Kaplan envisioned and organized a style of math circle centered on the idea that children of all ages can work like mathematicians do: creatively, collaboratively, and ecstatically. This article surveys four sample topics covered during a Sunday morning math circle in the Boston area, based on Bob and Ellen's invaluable guidance. I also offer some reflections on what I learned from Bob and Ellen, and how it is reflected in these math circles.

Flux Crystal Growth Of Potassium Lanthanide Double Vanadates With Lanthanide-Dependent Coordination Number Variance, Hunter B. Tisdale, Hans Conrad Zur Loye

Faculty Publications

A series of potassium rare earth double vanadates is presented. Single crystals of double vanadates with stoichiometry K₃Ln(VO₄)₂ (Ln = La, Pr, Nd, and Sm) and crystallizing in the glaserite structure type were synthesized via a molten alkali chloride/fluoride flux reaction. Different structures were observed depending on the constituent rare earth: K₃La(VO₄)₂ crystallizes in an as-of-yet unreported modification of the typical glaserite structure in the space group P2₁/c, likely due to its larger ionic size that results in an increase in the lanthanide coordination number …

Multivariate Stochastic Mine Scheduling Targeting Stationary Grades Considering Risk Uncertainty And Hierarchical Variables, Augusto A. T. Toledo, Joao F. C. L. Costa, Diego M. Marques, Luciano N. Capponi

Journal of Sustainable Mining

In short-term mine planning for deposits characterized by multiple variables, sequential diglines are generated with an emphasis on maintaining consistent grade distributions across mining periods. This research integrates an array of mineral variables, including deleterious elements, to facilitate the establishment of excavation geometries that enable precise grade and volume control within operational production zones. Through the systematic application of geostatistical analysis coupled with process optimization, geological risks associated with grade uncertainties are minimized, and an optimized operational sequence for the extraction of mineral blocks is pursued. The main point of this approach is maintaining grade distributions aligned with the historical …

An Innovative Implicit Modeling Technique To 3d Deposit Modeling: A Case Study Of The Chromite Mine, Ali Can Ozdemir Ozdemir, Yavuz Tore

Journal of Sustainable Mining

The location of an orebody known to show regional variability in space is determined only through 3D geological modeling. A reliable 3D orebody model must be obtained to ensure resource efficiency and sustainability in the mining industry. In addition, 3D geological modeling has become indispensable in intelligent mining, smart mining, and mining 4.0. In previous years, explicit methods were widely used for 3D geological modeling. However, the validity of geological models produced with these methods has been debated. It has been understood that they are inadequate in modeling vein-type mineralizations with complex geometry in particular. For this reason, implicit modeling …

Integrated Optimization Of Underground Mine Ventilation Using Hardy Cross, Monte Carlo Simulations, And Machine Learning Techniques: A Step Toward Sustainable Mining, Hussein A. Saleem

Journal of Sustainable Mining

Underground mine ventilation is crucial for ensuring worker safety, air quality, and operational efficiency. Effective optimization of ventilation systems reduces energy consumption, enhances airflow distribution, and minimizes risks associated with harmful gases and fire hazards. This study proposed an integrated framework combining the Hardy Cross (HC) method, Monte Carlo (MC) simulations, and machine learning (ML) techniques to optimize the ventilation system at the Jabal Sayid mine in Saudi Arabia. The HC method was employed to provide deterministic baseline airflow calculations, while the MC simulations accounted for uncertainties in resistance values and environmental conditions, generating probabilistic distributions of key parameters. Among …

Study On Visualization Simulation And System Dynamic Optimization Of The Ore Drawing Process In Mine Chutes, Liang Juan, Zhu Quanjie, Hao Yingnan, Quan Zhongxue, Zhang Zhiwu, Liu Xiaohuic, Ouyang Zhihua

Journal of Sustainable Mining

The ore release process in metal mine chutes is a critical part of the mining operation. Based on the urgent demand for intelligent mining construction, this paper proposes a visualization simulation and dynamic optimization method for the mine chute ore release process using the open-source programs Python and Blender. The main research content includes: designing the simulation method and model for the ore release process, including the main control program, process subprograms, etc.; proposing a visualization simulation method for the mine chute ore release process based on Blender, studying the impact of ore shape and size on ore release efficiency, …

Intrinsically Safe Pneumatic Seismic Source For Controlled Rock Mass ,Monitoring And Imaging In Underground Mining, Przemysław Sierodzki, Leszek Remiorz, Mateusz Ćwiękała, Krzysztof Krawiec

Journal of Sustainable Mining

This article explores the technical principles of pneumatic seismic sources, focusing on their application in underground mining operations, including environments prone to fire hazards. It introduces an intrinsically safe pneumatic seismic source as a cost-effective solution for quasi-continuous seismic excitation, useful for detecting stress concentrations in mining settings. These stress concentrations are identified through anomalies in seismic wave velocity, which may indicate potentially hazardous deformations in the rock mass. The developed system enables fully remote operation from the surface and integrates with a seismic monitoring system to capture high-resolution waveforms. The study provides an overview of the pneumatic system’s technical …

Ai In Society: A Regulatory Framework For Responsible Integration, Ziad Doughan, Sari Itani, Hadi Al Mubasher

BAU Journal - Science and Technology

This review paper studies the influence of Artificial Intelligence (AI) and Machine Learning (ML) on society in various categories in detail. AI and ML have developed rapidly in the past two decades, thus changing our lifestyles. These developments have various positive and negative impacts on society. This paper explores the many societal impacts of AI and ML, in economics, social aspects, ethics, and policy, shedding light on the opportunities and challenges that arise. An interdisciplinary insight is capable of understanding the challenges society faces when it uses AI and ML, locking opportunities that lie ahead and identifying promising paths towards …

Electronic Structure With Rovibrational Calculation For The Molecule Ali, Including The Spin-Orbit Coupling Effect, Hana Abdelnabi, Ghassan Younes, Dunia Houlla, Mahmoud Korek

BAU Journal - Science and Technology

The adiabatic potential energy curves for the lowest singlet and triplet electronic states in the representations 2S+1Λ+/- and Ω(+/-) (with and without spin-orbit coupling) of the molecule AlI have been computed by using the complete active space self-consistent field (CASSCF) with multireference configuration interaction (MRCI+Q) method. The spectroscopic constants ωe, Re, Be, and Te have been calculated. Using the canonical quantum mechanics approach, the rovibrational constants Ev, Bv, Dv, Rmin, and Rmax were calculated for the low-lying electronic states with and without spin-orbit coupling. A comparison between our calculated values and those available in the literature reveals excellent agreement.

Parameter-Free Determination Of Au Nanorod Dimensions Using Depolarized Dls And Genetic Optimization, Nehal Nupnar, Geofrey Nyabere, Claire M.B. Bolding, Kiril A. Streletzky, Michael J.A. Hore

Physics Faculty Publications

Gold nanorods (AuNRs) have received considerable attention for their distinctive optical properties and well-defined, low-polydispersity dimensions. These characteristics position them as promising candidates for diverse applications in imaging, sensing, and treating diseases. However, accurate characterization of AuNRs in their native solution state, which is crucial to many applications, presents many challenges─especially if AuNRs are coated with surface layers (e.g., surfactants or grafted polymers). When applied to AuNRs with functionalized surfaces, common techniques such as transmission electron microscopy (TEM), small-angle scattering, and dynamic light scattering (DLS) can present limitations such as small sample sizes, the inability to detect light elements, a …

The Ai Revolution In Virtual Try-Ons: A Means-End Chain Model Perspective, Ju-Young M. Kang, Ji Young Lee, Dooyoung Choi, Sumin Helen Koo, Jeehyun Song, Youngjin Bahng

Educational Leadership & Workforce Development Faculty Publications

Leading brands have begun to implement artificial intelligence-driven virtual try-on (AI VTO) technology, which helps reduce returns and increase conversion rates, repeat purchases, and customer loyalty. This research aimed to examine how retail user experience with specific perceived quality factors of AI VTOs influences users’ value equity and downstream loyalty and to investigate the moderating effects of clothing in relation to the self as structure and concern for physical appearance, based on a Means–End Chain model. Data were collected from 509 U.S. online apparel shoppers using a consumer panel. Structural equation modeling and multigroup analysis were used for data analysis. …

Ai Tips And Traps, Patrick Barry

Books

Based on a series of popular courses and workshops that Professor Patrick Barry has created for students, professionals, and anyone else interested in taking a skills-based approach to artificial intelligence, this book gives you a chance to engage with important AI concepts, experiment with exploratory AI exercises, and then ultimately develop your own customized list of AI traps to try as well as AI traps to avoid.

Deep Learning-Based Co-Current Upward Gas-Liquid Two-Phase Flow Regime Identification In An Annular Conduit, Joshua Robert Macomber

Graduate Theses, Dissertations, and Problem Reports (ETD)

Flow regime identification in co-current upward gas-liquid flow through annular conduits remains a significant challenge in petroleum engineering, with major safety and operational implications. It is also important across industries involving the transport of multiphase fluids. Misidentifying flow regimes can introduce major operational risk, yet regime boundaries in annular gas-liquid flow are often visually complex and context dependent.

The objective of this study was to evaluate the utility of convolutional neural network (CNN) classifiers for flow regime identification. The CNN was trained using annular flow image dataset published by Texas A&M University. The dataset consists of approximately 947 RGB images …

Generating Template Banks For Intermediate Duration Gravitational Waves, Michael St. Pierre

Open Access Dissertations

There are a multitude of astrophysical sources which carry the potential to produce perturbations in spacetime, known as gravitational waves, across a wide spectrum of frequencies. Over the brief history of gravitational wave astronomy, short-duration “chirp” signals emitted from black hole mergers, highly energetic “burst” signals emitted from supernovae and Gamma-Ray Bursts (GRBs), and long duration “continuous” signals emitted from galactic neutron stars and the stochastic gravitational wave background have traditionally been at the forefront of search development, leaving a class of intermediate duration  ($10² - 10⁴ seconds) gravitational wave signals poorly suited for detection. The conventional way …

Submesoscale Dynamics Of Phytoplankton And Carbon Export Revealed By High-Resolution Airborne And Satellite Remote Sensing Of Currents And Ocean Color, Sarah E. Lang

Open Access Dissertations

Satellites and airborne sensors reveal submesoscale (1 - 10 km) variability in ocean color in the form of filaments, eddies, and patches. The variability in ocean color is closely tied to the physical dynamics that restructure phytoplankton distributions and drive active biological responses like changes in primary productivity and community structure. As the base of the marine food web and a key component of the biological carbon pump, phytoplankton are crucial to the overall health of marine ecosystems and to the ocean's role in climate. This dissertation focuses on the use of airborne and satellite remote sensing to study the …

Toward Completeness Theorem For Guarded Kleene Algebra With Tests, Hung Pham

Honors Theses

Code refactoring is a fundamental practice in software engineering, in which a program is restructured without changing the actions it performs and the results it produces. To carry out refactoring with confidence, one requires a formal method for verifying that two programs are equivalent. Guarded Kleene Algebra with Tests (GKAT) provides such a framework, an algebraic system designed to reason about a natural class of programs, namely those in which every branch and loop is governed by a Boolean condition, such as if–else and while statements. Central to GKAT is a finite set of algebraic axioms for deriving program equivalences. …