Comparing 3-Connectedness And Roundness In Matroid Theory, Blanca Delia Larios

Electronic Theses, Projects, and Dissertations

A matroid is a discrete mathematical object that abstracts and connects the various notions of independence found throughout mathematics. Such notions of independence include linear independence, algebraic independence, as well as notions of independence that arise in graph theory. There are many broad classes of matroids. Important examples include binary matroids, graphic matroids, regular matroids, uniform matroids, and various levels of connected matroids. Some of the most important problems in matroid theory involve characterizing classes of matroids so that such characterizations can be used to prove results concerning these matroid classes. This thesis is a study of two important classes …

The Relativity Of Education: Student Perspectives On Artificial Intelligence In Community College, Ashley Greta Magana

Electronic Theses, Projects, and Dissertations

This hermeneutic phenomenological study examined how diverse community college students experience and make meaning of the integration of generative artificial intelligence (AI) into their educational contexts. Although AI is quickly transforming higher education through automated grading, personalized learning systems, and new models of assessment, the discourse surrounding its implementation remains dominated by administrators, faculty, and institutional stakeholders, while the perspectives of students, specifically community college students who are often historically underrepresented and economically marginalized, are systematically excluded. Most existing research is quantitative and centered on universities, leaving a critical gap in qualitative understanding of the most diverse population in higher …

Developing Solvent Tolerant Microbial Membranes: Lipid Extraction And Laurdan Fluorescence Approaches For Biofuel Optimization, Gladstone Anku

Electronic Theses and Dissertations

The high demand for sustainable energy has increased interest in advanced biofuels, though production is limited by solvent toxicity to microbial hosts. This study investigated the role of lipid composition in modulating membrane fluidity and solvent tolerance using Bacillus subtilis as a model organism. Five strains were cultured, and membrane lipids were extracted and analyzed using thin-layer chromatography and gas chromatography–mass spectrometry; however, inconsistent results limited compositional characterization. To address this problem, reconstituted vesicles composed of phosphatidylglycerol (PG) and phosphatidylethanolamine (PE) were used as model membranes. Membrane fluidity was assessed using Laurdan fluorescence spectroscopy by measuring generalized polarization (GP) values …

A Large And Robust Legless Lizard (Squamata, Anguinae) From The Gray Fossil Site Of Eastern Tennessee, Justice D. Lamer

Electronic Theses and Dissertations

The early Pliocene Gray Fossil Site in Tennessee preserved an abundance of microfossils, including numerous anguid lizard specimens. This includes the following elements: dentaries, a pterygoid fragment, a jugal, frontals, parietal fragments, dorsal and caudal vertebrae, and many osteoderms. Because these specimens had not been placed taxonomically beyond the subfamily level, comparative anatomy of similar elements from extant anguids and some quantitative data were used to provide more refined identifications. Using these methods, it was determined that a new, robust type of Ophisaurus is represented at the Gray Fossil Site. Important novel features include relatively robust dentaries, fewer but broader …

Student Attitudes And Perceptions Of Proof In Mathematics, Emelin G. Sibrian Marquez

Electronic Theses, Projects, and Dissertations

Traditionally, mathematical proof is viewed primarily as a tool for validation or verification. However, proof holds many other important roles such as discovery, reasoning, explanation, and justification. For many students, these other roles are not always obvious. Those encountering rigorous proof for the first time often find the process abstract, intimidating or disconnected from their previous learning. This disconnect can lead to negative attitudes as students transition from computational mathematics to advanced proof-based mathematics. Utilizing a mixed-methods approach, this study examined undergraduate and graduate mathematics students at a Hispanic-Serving Institution (HSI) in Southern California. We investigated what students perceive the …

Analysis Of Terpenes In Cannabis Flowers Using Gas Chromatography Via Headspace-Solid Phase Microextraction (Hs-Spme), Hannah I. Bergner

Forensic Science Master's Projects

As cannabis commercialization grows, rigorous profiling of cannabinoids, terpenes, and chemical contaminants is legally required for industry standardization and consumer safety. Terpenes are highly volatile components that dictate the unique aromatic profiles and therapeutic properties of cannabis via receptor pathways. This project focused on a gas chromatography-flame ionization detector/mass selective detector (GC-FID/MSD) combined with headspace-solid phase microextraction (HS-SPME) sampling to analyze terpenes present in four cannabis samples. Cannabis samples were tightly sealed in vials (10 mL) and heated to vaporize terpenes in the headspace above the samples, followed by the extraction of the vaporized terpenes using a polydimethylsiloxane (PDMS)-coated SPME …

Quantifying Dust Structure In An Elliptical Galaxy Via Optical–Near-Infrared Color Mapping: A Detailed Study Of Ngc 6251, Luke Reed

Theses and Dissertations

The giant elliptical galaxy NGC 6251 is a well-studied active radio galaxy that hosts one of the largest known relativistic jet systems, with a projected size of approximately 3 Mpc. In addition to its large-scale radio structure, the galaxy hosts a prominent circumnuclear dust feature surrounding the active nucleus, previously interpreted as a warped dust disk. This thesis focuses on the inner morphology and dust structure of NGC 6251 using archival Hubble Space Telescope observations obtained with the WFPC2 and NICMOS instruments.

The central structure of the galaxy was investigated across multiple wavelengths through image calibration, PSF modeling and subtraction, …

Ai-Driven Segmentation And Volumetric Response Modeling Of Liver Regions To Radiotherapy, Aashish Chandra Gupta

Dissertations and Theses (Open Access)

In liver-directed radiotherapy (RT), liver regions receiving higher doses typically undergo atrophy while contralateral/adjacent lower-dose regions may exhibit compensatory hypertrophy through regeneration of healthy tissue. Optimizing the RT plan to promote regional hypertrophy while minimizing the risk of developing atrophy has the potential to enhance post-RT liver function and long-term survivorship. However, current clinical practice largely relies on global liver dose-volume metrics during RT-planning, which may obscure favorable dose-response correlation and limit actionable guidance for clinicians. Therefore, we hypothesized that post-RT regional liver response is governed by a combination of region-specific dose-volume and patient clinical features, and that these responses …

Evaluation Of Dredged Sediments As A Partial Replacement For Fine Aggregate In Mortar And Concrete, Ashish Gautam

Graduate Theses and Dissertations (2019 - present)

The feasibility of using dredged sediment from the Mobile River as a partial replacement for fine aggregate in mortar and concrete was investigated through a series of laboratory characterization and performance evaluation. Three dredged sediment samples (A, B and C) were initially examined, and Sample A was selected for further evaluation due to its closer resemblance to natural fine aggregate. This sample exhibited lower moisture content, higher sand equivalent values, higher specific gravity, and lower absorption. Mortar mixtures with 0, 10, 20, 30, 50, 75 and 100% dredged sediment replacement showed decreasing workability as the replacement level increased. The 20% …

Lessons From The Club Homeschool Capstone: Testing, Data Discipline, And The Computer Science Curriculum, Shane Brown

University Honors Theses

This thesis looks at the CLUB Homeschool Capstone project to argue that Portland State University's Computer Science curriculum should introduce testing and data quality discipline earlier and more intentionally than it does now. As team lead of a seven-person team, I coordinated sprint planning, communicated with the sponsor, and developed custom Discourse plugins that enhanced an existing forum platform instead of creating a separate application database, as requested by the sponsor. The project's requirements document called for a formal testing plan, but our team lacked the practical experience to implement one. This gap became evident through my internships as a …

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 …

Modeling Mean And Variability Of Anxiety In Ecological Momentary Assessment Data Using Mixed-Effects Location–Scale Models, Trenzy Odero

Electronic Theses and Dissertations

Ecological Momentary Assessment is a method of collecting repeated measures of people in real time within natural environments. This results in hierarchical data that has a significant amount of variation at the person level. The traditional linear mixedeffects models assume that the residual variance is constant, which might not be true when the residual variance varies among individuals as well as in time. This thesis uses mixed-effects location-scale (MELS) models to model the mean and variance of an EMA outcome together. By introducing the possibility of variability in residual variance within and across individuals and with covariates, the MELS framework …

Enabling Multi-Task Neural Network Inference On Heterogeneous Edge Devices, Redwanul Islam Arif

Master's Theses

Deep neural networks are increasingly required to run on the devices that generate the data. If such a device must perform more than one task, the standard practice is deploying one model per task, which makes memory grow linearly with task count, which is unacceptable when the entire budget is kilobytes. This thesis asks one question in three settings: how much capability can a network acquire without incurring deployment cost?

The first study takes an ImageNet-pretrained ResNet-18, sweeps the branch point across every residual stage and the classification-head depth across one, ten, and twenty layers, and deploys the resulting multi-head …

Federated Learning For Early Medical Diagnosis: Enhanced Diabetic Retinopathy Detection In Smart Healthcare, Mohammad Nasajpour Esfahani

Master's Theses

This thesis investigates the role of federated learning as a privacy-preserving solution for modern healthcare challenges. In traditional machine learning, sensitive medical data must be centralized for model training, raising concerns about privacy, security, and regulatory compliance. Federated learning offers an alternative by allowing hospitals, clinics, and personal health devices to collaboratively train shared models without exchanging raw patient data. The study first explores how federated learning is being used across various healthcare domains, including cancer detection, medical imaging, and disease prediction— highlighting its potential to support secure collaboration across institutions. It addresses key benefits such as data privacy, scalability, …

Dbssnet: Dual-Branch Spectral-Spatial Network With Data-Driven And Knowledge-Guided Band Selection For Uav Hyperspectral Wheat Rust Detection, Subin Kim

All Graduate Theses and Dissertations, Fall 2023 to Present

Wheat rust is a serious plant disease that can reduce crop yield and quality. In practice, the disease is often noticed only after visible symptoms appear, when some damage may already be difficult to reverse. This thesis studies whether drone-based imaging can help detect wheat rust earlier and more reliably in field environments. 

Unlike an ordinary color photograph, a hyperspectral image records reflected light at many narrow wavelengths. These measurements can reveal useful information about plant condition, but they are also high dimensional, noisy, and difficult to analyze when only a limited number of labeled field samples are available. To …

Visualizing The Phase Space Of Two Interacting Spherical Magnets Via Lagrangian Descriptors, Matthew Pontius

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis studies the motion of one spherical magnet sliding on another fixed spherical magnet. Although the setup is simple, the resulting motion can range from regular and predictable to chaotic as the energy increases. To understand this behavior, mathematical tools are used to visualize how all possible motions are organized in phase space. These methods reveal patterns such as stable regions, repeating motions, and chaotic trajectories. The results show how order and chaos coexist in this system and provide insight into how small changes in the initial conditions can lead to very different outcomes.

Pesticide Dissipation In Agroecosystems – Exploring Pesticide Fate And Transport Mechanisms To Protect Alternative Pollinators, Calvin Luu

All Graduate Theses and Dissertations, Fall 2023 to Present

Honey bees are the most well-known pollinators, but there exists thousands of other bee species that contribute to pollination; one such group of bees are the solitary bees. True to their namesake, solitary bees do not live in hives like honey bees. Some solitary bees, like alfalfa leafcutting bees (ALCB) and blue orchard bees, can pollinate crops more efficiently than honey bees. However, since they live solitary lives, pesticide exposure is much more harmful to their overall population. If one honey bee dies from pesticide exposure, the hive can still survive, and the queen bee will continue producing offspring. If …

Applications Of Machine Learning To Gas Plume Analysis In Longwave Infrared Hyperspectral Images, Scout C. Jarman

All Graduate Theses and Dissertations, Fall 2023 to Present

Each pixel from a hyperspectral camera measures the intensity of light over a continuous range of wavelengths, which is in contrast to traditional color cameras, which just measure the intensity of red, green, and blue wavelengths of light. Longwave infrared hyperspectral images can be used to detect gases from a distance by measuring how different materials emit and absorb heat. This makes them useful for applications such as monitoring industrial emissions or locating hazardous gas leaks. In practice, however, gas signatures in these hyperspectral images are often weak and easily obscured by variations in the background scene, making reliable identification …

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 …

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 …

Understanding The Correlation Between Prediction Performance And Trust In Ai Through Scenario-Based Tasks, Likhitha Kammara

Theses and Dissertations

Trust in artificial intelligence is commonly assessed through self-reported scales or behavioral reliance, yet behavioral reliance is retrospective and can only be observed after a decision has already been made. This thesis examines whether prediction accuracy — a user's ability to predict what an AI system will recommend before its output is revealed — can serve as a prospective correlate of trust in the same empirical sense as behavioral reliance. The study was conducted in two phases using scenario-based AI decision tasks across disaster response, healthcare, and infrastructure restoration contexts, employing a between-group design in which participants either predicted AI …

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 …

On The Operation Of A Proteomics Core Facility: Selected Mass Spectrometric Studies And Methods, Rachel E. Muriph

Graduate Doctoral Dissertations

Mass spectrometry has become an indispensable analytical platform for investigating complex biological systems owing to its sensitivity, selectivity, and molecular specificity. This Dissertation demonstrates the versatility of liquid chromatography-tandem mass spectrometry (LC-MS/MS) through three studies focused on nanoparticle characterization, protein structural analysis, and plasma proteomics. In Chapter 2, LC-MS methods were developed to characterize novel lipidoid incorporated into lipid nanoparticles (LNPs) and to evaluate their in vivo biodistribution following systematic administration. Comparative proteomic analysis of the resulting protein coronas revealed distinct differences between liver and lung targeting LNP formulations, providing insight into the potential role of adsorbed blood proteins in …

Evaluating Machine Learning Models On Classification Of Novel Cyber Attacks In The Healthcare Domain, Promise Ehimen

Dissertations, Theses, and Projects

The increasing adoption of the Internet of Medical Things (IoMT) has improved healthcare delivery through connected medical devices while simultaneously expanding the cybersecurity risks facing healthcare organizations. Although machine learning based intrusion detection systems have demonstrated high detection accuracy, their ability to respond reliably to previously unseen cyberattacks remains uncertain. This study investigated how a Neural Network model and a Logistic Regression model classified novel cyberattacks within the IoMT environment. The Neural Network and Logistic Regression models were both trained and tested using a subset of the CICIoMT2024 benchmark dataset. The Neural Network achieved 99.82% test accuracy and a 0.94 …

The Study Of Hydrophobic Biomolecules With Matrix Assisted Laser Desorption Ionization Mass Spectrometry And Atomic Force Microscopy, Brandy L. Perkins

LSU Doctoral Dissertations

Abstract

Matrix assisted laser desorption ionization (MALDI) mass spectrometry (MS) can be used to obtain localization and chemical information of hydrophobic biomolecules on tissue samples.  A technique has been developed to modify a standard MALDI matrix that improves the selectivity for hydrophobic biomolecules on the tissue sample. The modification involves the use of a Group of Uniform Materials Based on Organic Salts (GUMBOS). GUMBOS are ionic liquids (IL) that are bulky organic ions with a counter ion that can be changed for tuning.  They are more stable than traditional matrices under vacuum.  Unlike traditional IL’s, the GUMBOS melting point ranges …

A Data-Driven Framework For Mitigating Breast Cancer Overdiagnosis: From Estimation To Risk-Adjusted Computer-Aided Diagnosis, William M. Brown Jr.

LSU Doctoral Dissertations

In Computer-Aided Diagnosis (CAD) of cancer, standard cost metrics (false-positives and false-negatives) fundamentally fail to account for overdiagnosis. Overdiagnosis is a critical scenario where a disease is correctly detected (true-positive) but is biologically indolent and would never have caused the patient harm or symptoms. While widely recognized in the medical community as a major healthcare crisis driving stressful and invasive overtreatment, overdiagnosis remains severely under-researched within computer science and engineering. This dissertation addresses this interdisciplinary gap by defining the three key computational challenges of overdiagnosis: (i) accurate estimation, (ii) harm quantification, and (iii) algorithmic mitigation. To overcome the estimation challenge, …

Mining Legacy And Wildfires: Interfacial Reactions Affecting Metal Mobility, Eresay Alcantar-Velasquez

Earth and Planetary Sciences ETDs

We identified water labile interfacial reactions between laboratory burned pinewood ash and mine waste solids that influence metal mobilization. The Upper Gallinas Creek Watershed in New Mexico is affected by wildfires and mining legacy. Pinewood and mine waste sediments were sampled from the area, and the pinewood was burned at 350°C to simulate medium burn intensity ignition. Rapid desorption and gradual dissolution of Mn and Fe was detected by ICP-MS as pH decreased over time. After reacting 18 MΩ ultra-pure water with a mixture of pinewood ash and mine waste sediments Fe (143%) and Mn (89.2%) concentrations increased over time. …

Mapping Along-Strike Changes In Shallow Subduction Zone Geometry At The Alaska Subduction Zone Using Seismic Reflection And Tectono-Geomorphic Analysis, Madelyn K. Hurd

Earth and Planetary Sciences ETDs

The Alaska subduction zone, where the oceanic Pacific plate subducts beneath the continental North American plate at a rate of 60-66 mm/yr, has hosted more >M8 earthquakes over the last century than any other subduction zone globally. The largest of these, the 1964 M9.2 Alaska earthquake, ruptured 800 km of the margin, including a high slip patch near the trench offshore Kodiak Island. The 1964 rupture area may have overlapped with the 1938 M8.3 Semidi earthquake rupture zone that lies to the west. Slip propagation near the subduction trench during large earthquakes can control tsunamigenesis, and differences in wedge geometry …

Information Theory Analysis Of Water Vapor Stable Isotopes From The Sail Campaign, Matthew John Rybecky

Earth and Planetary Sciences ETDs

Understanding the processes that control water vapor isotopic composition in mountain environ- ments is essential for interpreting isotope records and predicting water resource responses to cli- mate change. This thesis applies information theory to continuous, high-resolution water vapor stable isotope measurements from the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in the East River watershed of Colorado’s Upper Gunnison Basin, spanning the winter- to-spring transition of 2022–2023. The analysis employs Shannon entropy, mutual information, transfer entropy, and joint transfer en- tropy (JTE) to quantify how environmental variables, including surface meteorology, radiation, tur- bulent fluxes, and ERA5 reanalysis products, transfer information …