Digital Commons Network^™

Structured Dynamic Factor Analysis Of Environmental Time Series With Application To Morro Bay Estuary, Jose Garcia

Master's Theses

This thesis develops a structured dynamic factor analysis (sDFA) framework for decomposing multivariate environmental time series into latent biological and physical components. The methodology is applied to five years of high-resolution passive monitoring data collected from two sites in Morro Bay, California from 2020 through 2024. Relative contribution indices are developed based on the structured DFA that measure how much each latent process contributes to each observed variable at any given time. Structured DFA models fit to the application data suggest site-specific patterns in how biological and physical processes affect water quality variables. At the bay mouth location, physical processes …

A2s Uplink Latency Minimization For Wildfire Monitoring Systems Using Mbse And Stochastic Modeling, Luis Giovanni Wang

Master's Theses

Wildfire response depends on how quickly a detection reaches the people who act on it, and the slowest remaining step is often the link that carries an alert from a remote sensing platform to a satellite. This thesis models the latency of that link, the Air-to-Space uplink, for a wildfire-monitoring UAV that carries a Starlink terminal and sends an ALERT packet to a serving Low Earth Orbit satellite. The uplink is difficult to predict because both the UAV and the satellite move, and because the wildfire environment degrades the channel at the moment the data matters most.

The thesis uses …

Multimodal Machine Learning For Soil Burn Severity Mapping Across California Wildfires, Sanjana Checker

Master's Theses

Accurate mapping of soil burn severity (SBS) is critical for post-fire watershed management, erosion risk assessment, and ecological recovery planning, yet traditional field-based approaches remain costly, time-intensive, and spatially limited. This thesis presents a machine learning pipeline for wall-to-wall SBS classification across California wildfires using multi-sensor satellite imagery, terrain derivatives, and bioclimatic covariates. Field-collected SBS observations (n = 2,180) from 52 wildfires occur- ring between 2013 and 2025, sourced from the U.S. Forest Service and CAL FIRE, were used to train and evaluate multiple classification architectures within a Google Earth Engine and Google Cloud-based prediction framework. After upsampling the unburned …

Thermally Induced Color Changes In Iron Oxide Pigments Used In Architectural Coatings, Han Diep

Master's Theses

The 2025 Palisades Fire was one of the most destructive wildfires in the history of Los Angeles, destroying thousands of structures and severely impacting the communities after. This widespread destruction demonstrated an urgent need for more effective wildfire prevention strategies. Architectural coatings do not only provide aesthetics and protection against environmental conditions but can also function as a thermal indicator when a fire breaks out. This study examines the thermally induced color transformation of iron oxide pigments, commonly used in earthtone paint, to provide information relevant to CAL FIRE for improved analysis of wildland-urban interface (WUI) fire behavior and mitigation …

Linking Fishery Productivity To Child Health In The Coastal Tropics, Francisco Flores-Mejia

Master's Theses

Fish are a primary source of calories, macronutrients, and income for coastal communities around the world, but overfishing and environmental changes have dramatically reduced productivity in the majority of small-scale fisheries. The social costs of these losses are believed to be large, particularly in poorer communities, but most estimates of fishery productivity effects on households are contextual and difficult to generalize. We combine a remote sensing measure of pelagic fishery productivity with geolocated child health and growth data from 34 countries in the coastal tropics. We estimate that the difference between sustainedly good versus bad fishing conditions corresponds up to …

Meeting Their Needs: Experiences Of Uc Berkeley International Graduate Students Navigating Financial Strain, Ryann M. Hirt

Master's Theses

Of prior research on student experiences with financial strain, little has specifically focused on international student experiences in higher education while studying in the U.S., in tandem with financial strain. This qualitative study, through utilization of narrative methodology, explores the ways in which international students–in particular, graduate students–experience and navigate financial strain during their studies at a large, R1: Doctoral university: the University of California, Berkeley. The research was guided by three questions: (a) What are UC Berkeley international students’ stories of navigating financial strain? (b) What are the experiences of UC Berkeley international students with external and internal (campus) …

Lateral Thinking In Large Language Models: Benchmarking And Fine-Tuning For Puzzle Solving And Generation, Ashish Khadka

Master's Theses

Recent progress in large language models has produced reasoning-oriented systems that allocate additional computation at inference time (e.g., deliberation, verification, and self-correction), raising the question of whether these gains can solve tasks requiring creative and lateral thinking. In this thesis, we study such capabilities using two popular word-association games—LinkedIn Pinpoint and New York Times (NYT) Connections—which require identifying non-obvious patterns or relationships. We first benchmark some light-weight open models and analyze their performance trends with respect to puzzle release dates and approximate model knowledge cutoffs to distinguish memorization effects from genuine inference. Our results show that accuracy of traditional embedding-based …

Investigating The Taxonomic Uncertainties Of Potentilla Rupincola, Natalie Elizabeth Hieber

Master's Theses

Landscape stewardship is an integral role for land managers that becomes more important when rare or endangered species occur within managed areas. Conservation across the landscape is a primary concern for land managers, but resources allocated for conservation can be limited due to many competing goals. Taxonomic uncertainty surrounding rare and endangered taxa, particularly plant taxa, that have historically been classified solely using morphological features further complicates conservation planning. One such taxon is Potentilla rupincola, a rare plant endemic to the eastern Rocky Mountains in Colorado. For over a century, botanists have debated whether P. rupincola is a distinct species …

Comparative Development Of Mof‑Based And Mof‑Free Agnp Functionalized Zno Nanorod–Cotton Fabric Composites For Photocatalytic Applications, Md Al Mamun

Master's Theses

Photocatalysis offers a cost‑effective and environmentally friendly strategy for degrading organic pollutants and addressing energy and environmental challenges. This study initially explored MOF‑based cotton‑fabric‑supported ZnO nanorod composites but found that the MOF component primarily acted as an adsorbent rather than an effective photocatalyst. Consequently, MOF‑free composites were developed by directly growing ZnO nanorods on cotton fabric and functionalizing them with silver nanoparticles. Photocatalytic testing revealed that AgNP‑modified ZnO nanorods, particularly at 10 mM AgNP, exhibited superior dye degradation efficiency, thereby demonstrating a scalable and effective photocatalytic platform.

Morphological Variation Of Lingual Glands In Wild American Alligator (Alligator Mississippiensis) Populations, Benjamin Angalet

Master's Theses

American alligators (Alligator mississippiensis) inhabit diverse aquatic ecosystems including freshwater wetlands, swamps, and estuarine rivers. As apex predators, their physiological resilience has implications for ecosystem stability and long-term conservation. With projected sea-level rise and increasing saltwater intrusion into coastal freshwater habitats, understanding the osmoregulatory capacity of alligators is increasingly important. Unlike marine-tolerant crocodilians such as the saltwater crocodile (Crocodylus porosus), which possess specialized salt-secreting lingual glands in addition to renal and cloacal mechanisms, the morphology and physiological significance of lingual glands in wild American alligators remain poorly understood. This study examined lingual gland morphology and plasma …

A Novel Approach To Creativity Assessment: Forced Pairwise Ranking With Large Language Models, Phillip R. Gregory Jr

Master's Theses

Assessing creativity at scale remains a persistent challenge in cognitive science, as human raters are costly, slow, and often inconsistent in their judgments. This thesis introduced a novel framework for automated scientific creativity assessment using forced pairwise ranking, in which fine-tuned large language models compared response pairs and determined which was more creative. Five empirical studies were conducted using Llama-2-7B and Llama-2-13B models adapted via LoRA fine-tuning and benchmarked against human scored responses from the Scientific Creative Thinking Test. A regression baseline achieved Pearson �� = .74 on the test set, matching the human inter-rater ceiling reported in the literature. …

Quantifying Discard Mortality Of Undersized And Ovigerous Crabs In The Gulf Of Mexico Blue Crab Fishery, Micayla Cochran

Master's Theses

Blue crabs support a valuable commercial fishery in the Gulf of Mexico. Most states require the release of undersized and ovigerous blue crabs, yet mortality of these discarded crabs is an understudied component of total mortality. The first objective of this project was to quantify discard mortality of non-target crabs using bycatch surveys across the Lake Pontchartrain–Mississippi Sound coastal system. Ovigerous crabs were most common at high salinities and temperatures, whereas undersized crab presence was inversely correlated with soak time, temperature, and the number of crabs per trap, and also varied among geographic locations. A reflex action mortality prediction assessment …

Evaluating Modern Neural Network Architectures For Suicide Prediction, Kyle Brown

Master's Theses

Suicide remains a leading cause of death among adolescents despite more access to healthcare information than ever before. Medical professionals struggle to make accurate diagnoses and catch warning signs with the overwhelming amount of data available. Machine learning algorithms, including neural networks, have previously been employed for this task, yet it remains an understudied domain.

This research aims to evaluate the capabilities of Multi-Layer Perceptron (MLP) and a selection of its successors, ResNet and MLP with a category embedding layer, at the task of predicting suicidal ideation among high-school students. This research finds ResNet to be the most capable at …

Modeling The Effects Of Low-Pressure Atmospheric Fronts On Sediment Transport Through Mississippi Sound Barrier Island Inlets, Nicholas J. Gagliano

Master's Theses

Coastal sediment dynamics in the Mississippi Sound are strongly influenced by tropical cyclones and the more frequent passage of low-pressure atmospheric fronts. While hurricanes are well recognized for reshaping barrier islands and altering sediment budgets, the cumulative role of recurrent fronts remains poorly quantified. This thesis investigates the impacts of six low-pressure atmospheric fronts (2015–2017) on sediment flux through six barrier island inlets in the Mississippi Sound.

A high-resolution application of the Regional Ocean Modeling System with the Community Sediment Transport Modeling System was developed to simulate tidal circulation, wind-driven currents, and sediment dynamics. Waves were excluded from the simulations. …

Redeveloping Mississippi: A Case Study On Brownfields In Central & Southern Mississippi, Sahrah R. Yeroozedek

Master's Theses

Brownfields, or properties that are or possibly are contaminated with dangerous materials, represent a common obstacle for communities in Mississippi. The real or potential presence of contaminants at these sites often deters investors due to costly cleanup requirements (EPA, n.d. -b). The Environmental Protection Agency (EPA), through its Brownfield Revitalization Program, implemented guidelines for covering the costs and labor associated with the remediation of these properties. The EPA is not, however, responsible for redevelopment that supports long-term environmental and economic sustainability. Although the EPA maintains inventories of all Brownfields, there is also no comprehensive database of Brownfields and their current …

The Impact Of Place-Based Education Professional Development On Faculty Identity And Perceptions Of Nature-Culture Dichotomies, Reyt Middleton

Master's Theses

This qualitative study analyzes how implementing place-based education (PBE) in undergraduate coursework shapes faculty identity narratives and nature–culture positionalities across conceptual lenses of past, present, and future. Three faculty members at a regional Mississippi university engaged in a PBE professional development program; narratively driven pre- and post-implementation interviews were given to participants, then examined via thematic analysis. Framed primarily through lenses of constructivism, with support from critical pedagogy of place, relational and ecological epistemologies, and scholarship on faculty identity, this study posits two research questions—1: How does teaching PBE influence faculty identity narratives across past, present, and future temporalities? 2: …

Assessment Of Mississippi Landfill Capacity In Relation To Waste Generation And Land-Use Constraints, Jason C. Anderson

Master's Theses

Municipal solid waste (MSW) management presents a growing challenge in Mississippi as population trends, socioeconomic change and regional development continue to place pressure on existing landfill capacity. This thesis examines waste generation and disposal patterns from 2000 through 2022 across Mississippi counties, with projections extending to 2050. Historical landfill tonnage data was gathered and compiled from the Mississippi Department of Environmental Quality (MDEQ) and analyzed using regression models in Excel and RStudio, with forecasts generated for both in-state and out-of-state waste flow. Results highlight significant variations among landfills, including differing closure timelines, changing county service areas and notable shifts in …

Design And Reliability Analysis Of A Radiation-Tolerant On-Board Computer System For Martian Surface Missions, Jack Ryan

Master's Theses

Space environments present complex challenges for electronic devices, perhaps most notably in the form of radiation effects; the natural protections provided by Earth’s atmosphere and magnetosphere are largely absent in deep space and extraterrestrial environments, making single-event effects (SEE) a critical concern. Although radiation-hardened components offer near-immunity to SEE, they possess tremendous drawbacks in both cost and performance. To circumvent such issues, this thesis investigates the feasibility of leveraging a commercial-off-the-shelf (COTS) device, the AMD KRIA K24 system-on-module (SOM), for use in Martian surface missions.

Detailed models were used to predict SEE rates in the system, and system-level fault tree …

An Investigation Of Data Granularity In Rag Pipelines For Personalized Medicine, Paritosh Pandey

Master's Theses

Generative AI, exemplified by large language models like the OpenAI GPT and Meta LLaMA families, can produce diverse content in response to prompts. This capability offers a promising solution to challenges in precision medicine, which seeks to tailor treatments to individual clinical profiles but often struggles with data collection, cost, and privacy concerns. By generating realistic, privacy-preserving patient data, generative AI has the potential to transform patient-centric healthcare. With such motivation, this research develops a comprehensive Generative AI pipeline emphasizing data granularity for accurate prediction of personalized treatments. The pipeline features a central Large Language Model interacting with a Machine …

Agentcite: Trustworthy Ai Agents For Information Verification Across Referenced Documents, Eymen Yigit

Master's Theses

This thesis presents AgentCite, a multi-agent framework for automated verification of referenced numerical data in research documents. The framework employs a hybrid design in which LLM-based agents handle document understanding and evidence retrieval, while deterministic components manage structured parsing and value comparison, improving consistency and reproducibility while reducing token consumption and execution time compared to fully agentic approaches.

AgentCite consists of three autonomous agents: a Negotiator, a Main Document Agent, and a Source Documents Agent, coordinated through a fixed tool-call pipeline. The Negotiator orchestrates verification by extracting tabular data from the main document, retrieving evidence from per-source vector stores, and …

Probing Representational Emergence In Large Language Models, Shawn Ismail

Master's Theses

This thesis investigates whether abrupt behavioral gains in large language models under scaling are accompanied by systematic changes in internal representations. It combines a behavioral screen of 65 tasks per family with targeted layerwise probing across eight decoder-only, open-weight model families. Behavioral emergence is defined for each family-task trajectory using an empirical jump detector, with segmented regression retained only as a diagnostic. The representational follow-up analyzes 27 selected MMLU subtasks shared across all families, spanning 37 checkpoints and 216 family-task units.

For each follow-up checkpoint, frozen linear probes are trained on every layer's hidden states to measure how much task-relevant …

Long Run Effect Of Industrial Place-Based Policy On County Level Complexity, An Investigation Of The Tennessee Valley Authority, Anita Ifeyinwa Umunnah

Master's Theses

This paper studies the long-term effects of large federal investments in place-based industrial policies on regional economic development, contributing new evidence on how industrial policies shape regional local productive capabilities over time. While extensive research show that industrial policies impact regional development by advancing productive technology (capabilities), the fundamental question remains how to measure this technological transformation. The study employs the use of Economic Complexity Index (ECI) as a measure of “technological advancements” resulting from large federal investments in place-based industrial policies. Previous evaluations of such investment were based on livelihood, employment and income outcomes, with productive capability of receiving …

Analysis Of Lateral Load Distribution In Steel Girder–Concrete Deck Bridges: Influence Of Diaphragm Behavior Under Wind And Vessel Collision Loads, Bhupesh Chand

Master's Theses

Bridges are critical components of modern transportation infrastructure, and their structural response under extreme loading conditions is essential for ensuring safety and serviceability. A key challenge in current bridge engineering practice is accurately understanding and predicting the lateral load distribution in steel girder–concrete deck bridge systems subjected to wind and vessel collision loads. While the AASHTO LRFD Bridge Design Specifications provide well-established provisions for vertical load distribution, magnitudes and load combinations (Article 3.4), they do not explicitly define lateral load distribution factors (LLDFs) for such extreme lateral loading conditions or address the role of the deck in redistributing these loads …

Using Ensemble Disagreement To Stabilize Conformal Prediction Under Distribution Shift, Patrick D. Murphy

Master's Theses

Semantic segmentation of eelgrass from drone imagery is crucial for coastal habitat monitoring, restoration, and management, as these habitats continue to see rapid changes due to climate change and human influence. However, the reliability of generalizing a deployed classification model relies on both high-accuracy segmentation as well as robust uncertainty quantification that holds up when conditions change over years or locations. Conformal prediction (CP) is a method that converts a classifier's output into prediction sets with a guaranteed average coverage level for in-distribution data. However, the “vanilla” conformal score can often under-cover in hard or out-of-distribution (OOD) regions under drift. …

Neurosymbolic Counterpoint Generation, Paul D. Jarski

Master's Theses

Recent advancements in generative artificial intelligence have revolutionized music generation, yet research has predominantly focused on raw audio synthesis over music in symbolic form, i.e. a score. This thesis presents the first neurosymbolic model designed to generate imitative Renaissance counterpoint in symbolic (MIDI) format. By leveraging an autoregressive Transformer architecture, this research explores the capacity of deep learning models to manage independent voices and strict stylistic constraints.

We compare multiple data representation strategies with distinct tokenization methods. The proposed model incorporates a symbolic component that enforces fundamental contrapuntal rules. Additionally, this thesis contributes a preprocessed dataset of Renaissance polyphony, in …

Evaluating Carbon Risk And Benefit Under Improved Forest Management Prescriptions In A California Mixed Conifer Stand, Jonathan A. Garcia

Master's Theses

Improved forest management (IFM) prioritizes carbon accumulation through practices such as extended rotations and retention harvesting. These management strategies, increase fuel loads and elevate the potential fire intensity, may offset the benefits of carbon sequestration. Additionally, IFMs use spatially complex silvicultural treatments that may introduce prediction errors into the simulation processes used for long-term projections, and carbon accounting.

We evaluated the extent to which calibration in the Forest Vegetation Simulator (FVS) reduces error in aboveground carbon stock predictions and tested whether modeling approaches and calibration influence the magnitude and direction of basal area increment (BAI) prediction error using generalized mixed-effects …

Time-Dependent Amplification Of Growth Rates In A Plankton-Oxygen Model, Rapha Coutin

Master's Theses

Near-bottom hypoxia occurs when dissolved oxygen levels drop to a level that is harmful to marine biology, creating biological dead zones along the ocean floor. Recent years have seen a dramatic increase in the percentage of coastal, near-bottom, hypoxic water, with the average in 2021 nearly double that of the average from 2009 to 2018 and about twenty-eight times the average from 1950 to 1980. Recent literature has linked this increase in oceanic hypoxia to the increase in upwelling-favorable winds caused by climate change. Upwelling brings low-oxygen, nutrient-rich water up to the surface, leading to plankton blooms and mass consumption …

Video Generation Techniques For Novel View Synthesis With Flow-Matching Transformers, Xiuyuan Qiu

Master's Theses

Novel view synthesis (NVS) aims to generate images of a scene from unseen camera viewpoints. Recent work, such as Stable Virtual Camera, shows that large-scale image diffusion models like Stable Diffusion can be adapted for pose-conditioned view synthesis by incorporating video-generation techniques with camera conditioning. In this thesis, we introduce MVFlow, a new NVS model that extends this approach to a different image generation architecture: a flow-matching diffusion transformer, specifically FLUX.1, which has demonstrated strong performance in image synthesis. We evaluate MVFlow under varying input view counts and pose distance settings. Our results show that this architectural transfer is feasible; …

A Scalable Iteration Of The Horizon Simulation Framework Using Multithreading Techniques, Jason E. Beals

Master's Theses

The Horizon Simulation Framework (HSF) occupies a unique space in the modern aerospace modeling landscape, enabling flexible, modular modeling of mission-level agent behavior through an object-oriented, hierarchical design. HSF's hallmark breadth-first search scheduling algorithm explores a "multiverse" of possible mission execution pathways, enabling exhaustive evaluation of schedule combinations against user-defined heuristics.

As aerospace systems become increasingly complex, HSF faces critical challenges in establishing verifiable, deterministic behavior. The framework's core scheduling algorithm had not undergone systematic validation, leaving questions about temporal consistency, state management correctness, and reproducibility across different program executions. Furthermore, the exponential growth of schedule combinations creates computational bottlenecks …

The Application, Construction, And Validation Of Hidden Markov Model Profiles For Carbonic Anhydrase Enzymes, Samuel F. Kaplan

Master's Theses

Carbonic anhydrases (CAs) catalyze the reversible hydration of CO2 and have evolved independently at least eight times, resulting in structurally distinct enzyme families (α, β, γ, δ, ζ, η, θ, ι). Traditional sequence alignment methods struggle to classify these convergently evolved proteins because their sequential similarity does not reliably indicate functional or evolutionary relationships. Many CA sequences in public databases are annotated generically without family assignments, and prior computational approaches have focused predominantly on the three well characterized families (α, β, γ), leaving the five recently discovered classes without robust classification tools. Family level assignment is often a prerequisite for …