Physical Sciences and Mathematics Commons^™

Climate Change And The Field Of Farm Labor In The Lower Rio Grande Valley, Texas, Cody Richard Mortell

Theses and Dissertations

Farm workers in the United States are often vulnerable to adverse impacts of climate change, particularly extreme heat. This study explores farm workers’ climate change perceptions (CCP) as a mediating force in climate adaptation. Using latent class analysis, in-person survey data (n=404) from Lower Rio Grande Valley, TX (2024) and NOAA data were analyzed. Results were interpreted using Bourdieu’s field analysis framework and his notions of capital and symbolic power. Findings include: a social hierarchy with three latent classes of workers based on economic, cultural, social, and symbolic capital, which statistically significantly affected CCP. Workers in higher structural positions were …

Comparison And Evaluation Of Overlay And Leveling Binder In Traffic Circle Construction, Pratik Neupane

Graduate Theses and Dissertations (2019 - present)

Traffic circles play a vital role in managing traffic flow and ensuring safety, yet their unique traffic conditions make them prone to early cracking and deformation. This study evaluated the performance of overlay and leveling binder asphalt mixtures for a reconstructed traffic circle at the University of South Alabama, using plant-mixed laboratory-compacted (PMLC) specimens. Volumetric analyses were performed to determine maximum specific gravity (Gmm), bulk specific gravity (Gmb), and air voids content. Laboratory tests were conducted on both the overlay and leveling binder layers using indirect tensile cracking test (IDEAL-CT) and indirect tensile rutting test (IDEAL-RT) to assess cracking tolerance …

Protein Structural Changes Of Envelope Glycoprotein In Human Immunodeficiency Virus Type 1, Abigail S. Bridges

Chemistry & Biochemistry Undergraduate Honors Theses

The envelope glycoprotein (Env), present on the viral surface of human immunodeficiency virus type 1 (HIV-1) facilitates host cell infection, making it a critical target for immune responses and vaccine development. Env is able to transition through three prevalent prefusion conformational states, state-1 (pre-triggered), state-2 (closed), and state-3 (open). By transitioning through these conformation states, Env can successfully evade immune responses and initiate viral entry into the host cell. This study uses molecular dynamics (MD) simulations to analyze the conformational dynamics of the mature, cleaved Env glycoprotein in the state-2 conformation (PDB ID: 4ZMJ). Simulations were conducted with five replicates, …

Using Gaussian Process Regression To Learn Thermodynamic Equations Of State With Uncertainty Quantification, Austen T. Lee

Chemical Engineering Undergraduate Honors Theses

This study investigates the use of derivative-informed Gaussian Process (GP) models to estimate thermodynamic behavior across temperature and density by building a Helmholtz-based equation of state. Argon, a stable monatomic gas, was chosen as a case study within the vapor region. The GP model was trained using values of experimentally measurable properties found by taking first and second derivatives of the original potential function. Results show that while the GP model offered uncertainty quantification and informed thermodynamic behavior, it predicted values that deviated from the ground truth depending on the property. The model exhibited high confidence in regions with substantial …

2-Segal Sets And Pseudomonoids In The Bicategory Of Spans, Sophia E. Marx, Rajan Amit Mehta

Mathematics Sciences: Faculty Publications

In this survey article, we give an introduction to the notion of a 2-Segal set and prove that 2-Segal sets are equivalent to pseudomonoids in the bicategory of spans. The proof utilizes graphical techniques for 2-Segal sets and spans that should be useful in more general settings.
There are procedures for obtaining an associative algebra from a 2-Segal set (satisfying finiteness conditions). We describe these procedures and give several examples of algebras arising from 2-Segal sets.
Wherever possible, we avoid higher category theory so as to make the paper accessible to a wide audience.

Learning Educational Technology Prototyping With Generative Ai, Justin Olmanson, Azadeh Hassani, Gretchen K. Larsen

Department of Teaching, Learning, and Teacher Education: Faculty Publications

In this study, we use ethnographic methods, grounded theory, and an iterative analytical approach to explore participant experiences and strategies for engaging generative AI in support of both learning how to prototype educational technologies and learning to code. We examine how ChatGPT and Giuseppe (a scaffolded co-coding interface of our own design) influence students’ approaches to prototyping and programming. This study contributes to the field by: identifying specific challenges and affordances of generative AI in prototyping and educational technology development contexts; and offering insights into how educators, students, and learning technology developers can integrate generative AI in formative educational technology …

Achieving Fairness In Zoning Laws With Machine Learning, William Schimitsch

College Honors Program

Zoning is a powerful regulatory tool that determines how municipalities use and develop land. The goal of zoning is to classify land use (e.g., residential, commercial, industrial) to maximize compatibility among neighboring parcels. Local zoning decisions, however, are made by small-sized boards, often through an opaque process, which raises concerns about bias and fairness. In the United States, zoning has historically prioritized single-family housing and thus created economic barriers that limit access to certain communities. Given the task of classifying land use and the wealth of geographical, demographic, and infrastructural data describing each parcel, the problem of bias in zoning …

Using Machine Learning To Detect Vault (Anti-Forensic) Apps, Michael N. Johnstone, Wencheng Yang, Mohiuddin Ahmed

Research outputs 2022 to 2026

Content hiding, or vault applications (apps), are designed with a secondary, often concealed purpose, such as encrypting and storing files. While these apps may serve legitimate functions, they unequivocally present significant challenges for law enforcement. Conventional methods for tackling this issue, whether static or dynamic, prove inadequate when devices—typically smartphones—cannot be modified. Additionally, these methods frequently require prior knowledge of which apps are classified as vault apps. This research decisively demonstrates that a non-invasive method of app analysis, combined with machine learning, can effectively identify vault apps. Our findings reveal that it is entirely possible to detect an Android vault …

Using Natural Language Processing And Machine Learning To Detect Online Radicalisation In The Maldivian Language, Dhivehi, Hussain Ibrahim, Ahmed Ibrahim, Michael N. Johnstone

Research outputs 2022 to 2026

Early detection of online radical content is important for intelligence services to combat radicalisation and terrorism. The motivation for this research was the lack of language tools in the detection of radicalisation in the Maldivian language, Dhivehi. This research applied Machine Learning and Natural Language Processing (NLP) to detect online radicalisation content in Dhivehi, with the incorporation of domain-specific knowledge. The research used Machine Learning to evaluate the most effective technique for detection of radicalisation text in Dhivehi and used interviews with Subject Matter Experts and self-deradicalised individuals to validate the results, add contextual information and improve recognition accuracy. The …

The Sonora Substellar Atmosphere Models. V. A Correction To The Disequilibrium Abundance Of Co2 For Sonora Elf Owl, Nicholas F. Wogan, James Mang, Natasha E. Batalha, Kevin Zahnle, Sagnick Mukherjee, Channon Visscher, Jonathan J. Fortney, Mark S. Marley, Caroline V. Morley

Faculty Work Comprehensive List

To aid the interpretation of observations of substellar atmospheres, S. Mukherjee et al. created the Sonora Elf Owl grid of model atmospheres, simulations that accounted for disequilibrium quench chemistry. However, Sonora Elf Owl did not accurately estimate CO₂ quenching because the models quenched the gas with respect to the full atmosphere equilibrium, but CO₂ should have instead been quenched with respect to the disequilibrium (i.e., quenched) abundance of CO. As a result, Sonora Elf Owl under-predicted the CO₂ abundance by several order of magnitude in some instances, an amount that JWST is sensitive to. Here, we release …

Inferring Feeding Biology In Extinct Shrews (Soricidae: Mammalia): Application Of A Linear Morphometric Approach, Derek J. Den Ouden

Electronic Theses and Dissertations

Linear morphometrics have been used extensively to infer the ecology of fossil organisms, but shrews have not yet been thoroughly explored using this technique. Often considered to have a homogenous insectivorous diet, direct dietary observation suggests shrew dietary diversity is substantial. Diversity of this nature is well established to have influenced skull morphology in other mammal clades, so similar patterns are hypothesized to be detectable in shrews. To test this, I examined the link between known diet and morphological disparity in extant shrews using linear morphometrics and then utilized that framework to infer the dietary ecology of several fossil taxa. …

Revealing Hidden Histories: A Multi-Sensor Aerial Survey For Detecting Unmarked Burials At Sinking Spring Cemetery, Abingdon, Va, Noah Hall

Electronic Theses and Dissertations

The Sinking Spring Cemetery, established in 1773 in Abingdon, Virginia, spans 11 acres and is divided by a road. The 9-acre southern section was reserved for white church members. Enslaved individuals and free people of color were buried in the smaller northern section, where few headstones remain today. This study aimed to map the unmarked graves using thermal, multispectral, and Light Detection and Ranging (LiDAR) sensors deployed on unmanned aerial systems. Graves were characterized by subtle topographic depressions mapped by LiDAR and cooler radiant temperature anomalies in thermal imagery. Thermal data collected at different times of the day and year …

Car Price Prediction Using Machine Learning: Analyzing The Dvm-Car Dataset, Yaman Abu Ghareebaih

Electronic Theses and Dissertations

The objective of this study is to predict car prices using machine learning models and the DVM-CAR dataset, which includes over 1.4 million images and car specifi- cations from 899 car models. Key factors such as mileage, engine power, and year of registration were analyzed for their correlation with car prices. Extensive data cleaning was performed, including filling missing values, identifying outliers, and normalizing numerical variables. Discrete variables like car make and body type were encoded using one-hot encoding. Linear relationships were analyzed with Multiple Logistic Regression, and Random Forest models were used for nonlinear patterns. Model performance was evaluated …

Effects Of Ph On Product Yield Of One-Electron Oxidation To Guanine Derivatives, Abdul-Kadir Ibrahim

Electronic Theses and Dissertations

One-electron oxidation plays a major role in oxidative DNA damage in biological cells. Guanine, the most oxidizable DNA base, has been the major focus of studies on oxidative damage to DNA initiated by one-electron oxidation (OEO). The current study aims at understanding the mechanisms of photooxidation of guanine derivatives with OEO in acidic medium. D1A* and D1B*, which are the products of dGuo in acidic medium, were obtained from dGuo upon photolysis at 485 nm of the reaction mixture in the presence of S₂O₈^2- as the oxidant and Ru(II)(bpy)₃²⁺ as a photosensitizer. D1A* and …

Sliding Window Method For Simulating Action Potentials In Axons, Hayden Reed

Honors Theses

ABSTRACT Hodgkin and Huxley’s nonlinear partial differential equations model the excitation and propagation of action potentials in neurons, and there have been numerous attempts at finding the best numerical solution method. This thesis proposes a novel approach to solving these equations: the Sliding Window method, in which a fixed sub-interval is found through capturing the signal’s head and tail. The system is then solved on the sub-interval instead of the entire interval. Using the Sliding Window technique also involves implementing the backward and forward Euler methods and the finite difference method. It will be demonstrated that, in utilizing the Sliding …

Synthesis, Characterization, And Redox Properties Of Select 1,4-Diazocine-6,11-Diones Towards An Electrochromic Dye-Set, Jeffrey Scott Richards

Open Access Theses & Dissertations

The daily consumption of personalized digital visual information depends on the current purview of electronic-based displays. Present manufacturers utilize modern technologies, such as LCD, OLED, QLED, and electronic ink, or "E Ink," in their devices to display text, pictures, and other forms of media to individual users. However, as modern society continues to rely on the use of digital displays, the demand for low-power alternatives will continue to rise as their application in varying scenarios is realized. Currently, "E Ink" technology continues to grow as the dominant solution in the e-readers and digital signage marketplace, and can even be seen …

Kernel Density Estimation And Convolution, Nicholas Tenkorang

Open Access Theses & Dissertations

Kernel Density Estimation (KDE) is a widely used technique for estimating the probability density function of a random variable. In this study, we revisit KDE through the lens of convolution and extend this perspective to special cases such as positive, bounded and heavy tailed random variables. Building on this foundation, we propose a novel simulation-based density estimation method that generates new data by adding noise to observed values and then smoothing the resulting histogram using splines. A minor adjustment to natural cubic splines is required to ensure nonnegative estimates. The noise is drawn from a class of bounded polynomial kernel …

Impact Of Magnetic Fields On Cosmic Ray Density In Molecular Clouds, Byron Jesus Encinas Velazquez

Open Access Theses & Dissertations

We investigate the effects caused by Cosmic Rays (CRs) in a Molecular Clouds (MCs) environment and the effects of varied magnetic field configurations in the core (r = 1 Pc ) of a MC. We take as initial conditions for the interstellar medium a product of various supernova explosions as injected initial perturbation and observe the evolution during the timescale of ~4.5 Myrs. We compute the CR reduction factor R as a measure of the density of a distribution of particles traveling with a guiding center along randomized field lines near the core and discuss their impact on the ionization …

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 …

From Text To Utility: Distance-Aware Contrastive Learning For Detection-Ready And Shareable Malware Descriptions, Ivan Alejandro Montoya Sanchez

Open Access Theses & Dissertations

The rapid rise of sophisticated malware variants poses significant challenges for cybersecurity analysts, particularly due to the scarcity of data on newly emerging threats. Due to privacy, legal, and operational constraints, malware samples are often not shareable; instead, organizations publish cyber threat intelligence (CTI) in natural language. However, these reports are typically unstructured and inconsistent, limiting their utility in machine learning (ML) models. This thesis explores whether high-fidelity, shareable threat intelligence can be automatically generated from structured malware behaviors to supplement ML models when direct access to malware samples is limited. Two central questions are addressed:(i) How can descriptions be …

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 …

Hidden Layer Reshaping On Convolutional Neural Network, Alan Delgado

Open Access Theses & Dissertations

Artificial Intelligence (AI) technologies have become really popular in recent years. From ChatGPT to Tesla cars, many applications can benefit from these type of technologies. Automotive, healthcare, biomedical, cybersecurity, finances, and retail are some of the fields that take advantage of it. It has been seen that AI can solve complex problems, but there is still work to be done to optimize it. A deep learning neural network (DLNN) tries to simulate how a human brain operates. These DLNNs are made up of artificial neurons which are connected by weight that are modified when the network is trained. These networks …

Development Of Porous Separators For Lithium-Ion Batteries Via 3d Printing And Thermally Induced Phase Separation, Abraham Enchinton

Open Access Theses & Dissertations

Additive manufacturing processes allow the development of custom-shape rechargeable batteries, but research in custom filaments for fused deposition modeling (FDM) of battery separators has remained limited until now. This study discusses the development and optimization of a composite thermoplastic filament feedstock to 3D print separator membranes. A number of post-processing steps - leveraging the thermally induced phase separation (TIPS) of the composite filament - are introduced in tandem with FDM to promote microporosity formation through the removal of the sacrificial diluent phase within 3D printed samples. Three distinct compositions of varying polymer/diluent ratios were developed and thoroughly investigated through thermogravimetric …

Investigation Of High-Frequency Electron Spin Dynamics In The Kagome-Lattice Ymn6sn6 Crystal, Lovia Ofori

Open Access Theses & Dissertations

Kagome magnetic crystals received a great deal of research attention in the recent past for their intriguing magnetic properties. Recently, YMn6Sn6 (Y166) has shown to exhibit several nontrivial magnetic phases (such as the Distorted Spiral (DS) phase, Transverse Conical Spiral (TCS) phase, Fan-like (FL) phase and the Forced-Ferromagnetic (FF) phase) and complex magnetic interactions. In this work, we employed very high-frequency electron paramagnetic resonance (VHF-EPR) spectroscopy to investigate the local microscopic magnetic interactions of Mn ions in the Kagome Crystal Y166 to better understand the new observed magnetic phases. Particularly, we studied the temperature-dependent EPR behavior at variable very-high microwave …

A Numerical Study Of Self-Assembling Amphiphilic Systems, Joshua Albert Sackey

Open Access Theses & Dissertations

Mixing processes in ternary mixtures involve immiscible fluids such as oil and water, and a surface-active molecule called surfactant. These physical processes find applications in various fields, including enhanced oil recovery, drug delivery design systems, and the formulation of cleaning products. Even though this process has several applications, the mathematical models describing it and the numerical methods solving it are not well understood. The underlying mathematical model is a nonlinear initial-boundary value problem involving sixth-order derivatives and belongs to the class of sixth-order Cahn-Hilliard equations. Authors Sharma and Tierra recently proposed a numerical method to approximate its solutions in two …

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 …

Generative Ai For 3d Printed Antenna Design, Jennifer Ann Chavez

Open Access Theses & Dissertations

This research explores the integration of generative artificial intelligence (AI) with a physics-informed particle swarm optimizer (PSO) to develop 3D printable microstrip patch antennas. A neural network was trained on a dataset of microstrip patch antenna geometries and their corresponding performance metrics: return loss and gain. The PSO used a fitness function prioritizing low return loss in potential antennas, eventually yielding novel antenna geometries with parasitic components. 3D printing constraints were also hard coded into the framework, thus preventing any geometries being generated that cannot be fabricated. When simulated using Ansys HFSS, the AI generated microstrip patch antennas exceeded the …

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.

Characterization Of Residual Mineral Content Of Bauxite Stockpiles In Saline County, Arkansas: An Xrd Analysis Approach, Andrew Kaze Sezibera

Electronic Theses and Dissertations

The Saline Mining District of central Arkansas once led U.S. alumina production and hosts extensive bauxite and nepheline syenite deposits. With the depletion of highgrade ore, renewed interest in bauxite stockpiles has focused on critical mineral potential. Previous X-ray Fluorescence studies have identified critical elements in significant concentrations, including uranium (U), thorium (Th), gallium (Ga), molybdenum (Mo), and lanthanides (Ln). This study examines five stockpiles (SP1, Clay, SP2, SP3, and SP4) in Section 20 of the Aluminum Company of America (ALCOA) Saline County bauxite mine, using Xray Diffraction (XRD) on 25 samples to characterize mineral phases and compare them with …

Lidar-Based Delineation Of Karst Features In The Gypsum Plain, Eddy County, New Mexico And Culberson County, Texas, Kaitlyn Rae Levassar

Electronic Theses and Dissertations

The Gypsum Plain of the Delaware Basin encompasses approximately 1,800 km² of massive to laminated gypsum (anhydrite in the subsurface) outcrop of early Ochoan Castile and Salado strata. These extensive Permian-age evaporites host significant karst phenomena as a result of the region's complex hydrogeologic system which has continuously evolved since the early Paleogene. Karst features that manifest surficially as sinkholes when breached range from extensive hypogene cave systems to epigene features and suffosion caves. In contrast, paleo-collapse structures forming breccia pipes attesting to more ancient karst within these strata often manifest as topographic highs across the Gypsum Plain.

Until …