Physical Sciences and Mathematics Commons^™

A Transmission Electron Microscopy Study Of Structural Design And Modifications Of Li And Na – Ion Battery Cathodes For Performance Optimization, Maksim Andreyevich Sultanov

Graduate Research Theses & Dissertations

The importance of Li ion batteries as an energy storage device cannot be understated. The industry around energy storage has been steadily growing over the last few decades and continues to grow. However, the design of these devices has run into a bottleneck as both academics and industry specialists try to achieve even higher performance parameters, as well as trying to supplement critical materials such as Co, Li and Ni while maintaining cost and energy density. In particular, energy density, capacity retention, thermal and mechanical stability have become very important to improve. These critical parameters within the device are dominated …

Dynamic Aperture Maximization Methods, Kevin J. Hamilton

Graduate Research Theses & Dissertations

Particle accelerators consist of some of the most prolific machines for achieving a long-standing history of successful experiments that have progressed fields such as particle physics, nuclear physics, solid state physics, and medical physics. In recent years, multiple studies have been conducted on how further progress in these fields can be made and the beams physics community has concluded that developing new accelerators to minimize the loss of particles, induce high intensity beams, and remain stable under perturbations is essential to the continued success of physics research. Each of these qualities correspond to finding methods to increase the so-called dynamic …

The Deposition, Prevalence, And Persistence Of Gunshot Residue In Standard And Less Lethal Ammunition, Liliana Claire Barbosa

Graduate Theses, Dissertations, and Problem Reports (ETD)

During the discharge of a firearm, gunshot residue (GSR) is released and settles into nearby surfaces, leaving traces that can provide valuable information for forensic investigations. This study aims to improve understanding of the deposition, prevalence, and persistence of standard and less-lethal ammunition through an analytical framework that examines collection and analysis protocols, revealing connections among multiple traces for effective use in investigations and courtroom proceedings.

Research into the chemical residues of less lethal ammunition (LLA) is a critical frontier in shooting investigations. While standard leaded ammunition has over a century of established literature, the chemical fingerprints of LLA residues …

Sedimentological And Geochemical Investigation Of The Origin Of Upper Pennsylvanian Black Shales, East-Central Appalachian Basin, Tyler Hickey

Graduate Theses, Dissertations, and Problem Reports (ETD)

In the east-central Allegheny foreland basin, laminated black shales overlying Upper Pennsylvanian Glenshaw Fm. coal seams record paleoenvironmental conditions associated with the termination of peat swamp deposition before, during, and after the Carboniferous Coal Forest Collapse (CCFC), a major paleobotanical evolutionary event during the Late Paleozoic Ice Age (LPIA) that contributed to extinction of lepidodendrons near the Desmoinesian-Missourian boundary (~306 Ma). Previous investigations of the CCFC commonly implicate an episode of aridification during intensification of LPIA glaciation that stressed the lepidodendrons beyond their ecological tipping point; however, the cause of this aridification is unclear. An investigation of Glenshaw Fm. black …

Nh State Shoreland Water Quality Protection Act (Landscaping For Water Quality Workshop - 2026), Jay Aube

UNH Cooperative Extension

No abstract provided.

Rntuple For Atlas Analysis Workflow, Fatima Ariana Rodriguez

Graduate Research Theses & Dissertations

RNTuple is the new data storage format set to replace TTree at the start of the High-Luminosity LHC. An investigation was conducted to evaluate how analysis workflows for ATLAS researchers will change with RNTuple, using reading speed, writing speed, disk space, and memory consumption as metrics. In this study, all metrics were measured using converted RNTuple inputs from ATLAS Open Data, compared to their TTree equivalents. Additionally, RNTuples produced with the LZ4 compression algorithm were generated and compared with those produced using ZSTD. Finally, two new versions of the Analysis Grand Challenge (AGC) using ATLAS Open Data were completed for …

The Effects Of Problem-Based Learning On Mathematical Creativity And Self-Efficacy Of High School Students, Margaret Remus

Graduate Research Theses & Dissertations

Mathematical creativity is recognized as an important component of mathematics education; however, there is limited understanding of how instructional approaches can effectively support this skill among high school students, particularly through problem-based learning (PBL). This study examined the effects of problem-based learning on mathematical creativity among high school students.

This study employed a mixed-methods approach using an alternating treatment design with two groups of participants. Group 1 received the PBL intervention followed by a control condition, while Group 2 received the control condition followed by the PBL intervention. Quantitative data were collected through a mathematical creativity test measuring flexibility, fluency, …

Evaluating Planting Methods For Native Seed Production And Exploring Granivory In The Northern Great Plains, Allison Dollen

Electronic Theses and Dissertations

Temperate grasslands have faced immense losses due to land use change in the last 150 years and less than half of the overall grasslands that once covered North America remain today. A portion of historic and remaining U.S. grasslands are located within the northern Great Plains (NGP) region which is home to over 1,600 species of native plants and provides many ecosystem services and economic benefits. Initiatives to restore grasslands and their ecosystem services are currently underway, but barriers such as limited native seed supply and granivory hinder restoration efforts. My first chapter addresses knowledge gaps in planting methods for …

Time Series Decomposition And Forecasting Of Alzheimer’S Disease Mortality Using A Kolmogorov-Zurbenko Filter, Jack D. Farrell

Electronic Theses & Dissertations (2024 - present)

Alzheimer’s disease mortality has substantially risen in recent history, placing a significant burden on public health infrastructure and highlighting the need for improved analytical methods to better understand mortality data patterns and offer reliable predictions. Time series methods often struggle to balance both accuracy and interpretability, which hinders the ability to gather meaningful insights from time series data. To address these limitations, this study applies the Kolmogorov-Zurbenko (KZ) filter to monthly U.S. Alzheimer’s mortality data spanning from 1999 to 2023 and decomposes the series into long-term trend, seasonal, and noise components on a logarithmic scale. Long-term trend accounts for 86.49% …

Spectral Analysis Of Traffic Accidents In New York's Capital Region, Michael Barr

Electronic Theses & Dissertations (2024 - present)

In this paper we estimate the spectral density of traffic accident events in the Capital Distict, NY area using a band-pass filter known as the Kolmogorov-Zurbenko Fourier Transform (KZFT). The source data is provided by Moosavi, et al. (2019) and originally captured from various public entities and sensors in the road network. Spectral density estimation with KZFT suppresses noise to reveal the constituent frequencies embedded in the noisy signal. Signal reconstruction based on KZFT produces an approximate weekly accident arrivals for this noisy signal, or in other words a pattern which is proportionate to the event expectation viewed over a …

Entropic Dynamics Approach To The Classical Limit Of Quantum Mechanics: Decoupling Of The Center Of Mass Motion For A Mesoscopic Particle, Fatimah Judayba

Electronic Theses & Dissertations (2024 - present)

In the Entropic Dynamics (ED) approach, quantum mechanics is derived from the principles of entropic inference and information geometry. The ED approach differs from other interpretations by making a clear commitment to distinguishing which variables are ontic (real) and which are epistemic. The classical limit for the center of mass (CM) coordinate is achieved for a large number of particles, M →∞, while Planck’s constant ℏ remains finite. Typically, the emergence of the classical limit requires decoherence through interactions with the external environment. In this work, we investigate whether the classical behavior of the CM coordinate in a mesoscopic system …

On Quantum Processes And The Epistemic Constraints, Varun Immanuel Premkumar Immanuel

Electronic Theses & Dissertations (2024 - present)

This doctoral dissertation on the foundations of quantum theory tells the story of a conceptual protagonist I have called “Epistemic Constraint.” Here, epistemic constraints are the definite, intersubjectively agreeable, ordinary-language conditions under which experiments are described.

The usual formulation of the quantum measurement problem, which I call the Schrodingerian measurement problem, has the structure of an anomaly: if we take quantum theory at face value, we expect no definite values, and yet we see definite values in experiments. The responses to this problem have been either to solve it or to dissolve it. These responses, which have taken the form …

Quantum Mechanics As A Framework For Data Assimilation And Its Application To Atmospheric Parameterization, David Freeman

Dartmouth College Ph.D Dissertations

Quantum mechanics, as a mathematical system, can be understood as a generalization of classical probability theory. Quantum Mechanical Data Assimilation (QMDA) is a method in which classical dynamical systems are embedded into a quantum mechanical setting, with an associated data assimilation scheme leveraging the operator algebraic setting. In this dissertation, the algebraic structure underlying the operator theoretic formulation of QMDA is discussed. A procedure for closure of dynamical systems based on QMDA, known as Quantum Mechanical Closure (QMCl), is then constructed, and the procedures for constructing the quantum embeddings and implementing QMCl in practice are laid out and implemented for …

Fifty Years Of Research In The Commonwealth Of The Bahamas: A Quantitative Thematic Analysis Of Scholarly Output, Amina Moss, Krista D. Sherman, Williamson Gustave, Kathleen Sullivan Sealey, Charlotte Dunn, Nicola Simone Smith, Lindy Knowles, Christy Gibson

Gulf and Caribbean Research

This study presents the first longitudinal bibliometric mapping of peer—reviewed research on The Bahamas, analyzing 12,113 Web of Science records (1975–2025) using CiteSpace v.6.4.R2. We identified 36 co—citation clusters (modularity Q = 0.7967; silhouette = 0.9231) and 28 keyword clusters (Q = 0.7523; silhouette = 0.8695), revealing 8 thematic trajectories over 5 decades. Early research (prior to 1990) focused on carbonate geology and sea—level dynamics across the northwestern Bahama Platform and Blake—Bahama Basin (Cluster#0, silhouette = 0.939). From the 1990s–mid—2000s, attention shifted to marine fisheries, Aliger gigas, coral reefs, and ecological resilience (Cluster #1, n = 203). In the …

Cybercrime, Vulnerability And Digital Guardianship: Opportunity Structures And Prevention In A Changing Online Landscape, Mike Toro-Alvarez, Amy Lim

International Journal of Cybersecurity Intelligence & Cybercrime

No abstract provided.

Analyzing Modern Scam Typologies: From Pig-Butchering And Nigerian Advance-Fee Fraud To Crypto Airdrop Schemes, Katalin Parti, Sinyong Choi, Thomas Dearden

International Journal of Cybersecurity Intelligence & Cybercrime

Rapid advancements in digital infrastructure and decentralized networks have fundamentally altered the nature of contemporary cybercrime, making comprehensive empirical and technical analysis more crucial than ever. To address these challenges, this editorial summarizes the research contributions featured in this issue of the International Jour nal of Cybersecurity Intelligence and Cybercrime. The included papers examine the structural on-chain dynamics of sanctioned pig-butchering operations, the representational production and AI-driven evolution of the “Nigerian scam” label, the critical transaction-authorization factors driving losses in crypto airdrop schemes, and the optimization of sentence-transformer models for automated Host Intrusion Detection System (HIDS) alert enrichment. Together, these …

Three-Tier On-Chain Transaction Architecture In A Sanctions-Linked Pig-Butchering Network: A Blockchain-Forensics Case Study, Matthew Stern, Kyung-Shick Choi

International Journal of Cybersecurity Intelligence & Cybercrime

n October 2025, the U.S. Department of the Treasury’s Office of Foreign Assets Control (OFAC) sanctioned 29 Bitcoin addresses asso ciated with the Prince Group and Chen Zhi, providing an opportunity to examine the internal on-chain structure of a sanctions-linked pig-butchering network. This blockchain-forensics case study analyzes the group of 29 addresses using blockchain tracing, cross-plat form attribution checks across multiple commercial analytics platforms, exposure screening, and thematic analysis of transaction be havior. Because the case rests on OFAC designations and DOJ allegations, the traced flows are interpreted as patterns consistent with suspected laundering rather than adjudicated crimes; no fiat …

Attribution Post ‘Aura’ Loss: A Qualitative Discourse Analysis Of The Nigerian Scam Label And Fraud Attribution, Emaediong Akpan

International Journal of Cybersecurity Intelligence & Cybercrime

In this essay, I employ qualitative discourse analysis of eleven purposively selected literature to examine how “Nigerian scam” became an established yet detached signifier of advance-fee fraud in global discourse. I do not treat this association as a reflection of offender identity or national inclination. Instead, the analysis traces how attribution is produced through representational repetition, institu tional uptake, and the circulation of familiar narrative cues. Using qualitative discourse analysis and an interpretive approach, this paper distinguishes among the socio-technical conditions that enable fraud, the institutional processes that stabilize attribution, and the semiotic dynamics through which national categories acquire durability. …

Charge Transport Modeling Of Multifunctional Molecular Transistors, Romena Akter

Graduate Studies Theses and Dissertations 2026

Distinguishing between the current–voltage characteristic curves associated with different transport mechanisms in a molecular electronic device and an artifact arising from device-level disorder is a central challenge in the study of molecular electronics. Characterizing these mechanisms and connecting them qualitatively to molecular-level orbital alignment, electrode coupling, voltage division, energetic disorder, and reorganization energy requires not only experimental data but also a rigorous theoretical framework for extracting physically meaningful parameters from measured transfer characteristics. This dissertation addresses this challenge in Chapters 2, 3, and 4 by developing and applying four complementary transport models —Simmons tunneling, single-level Landauer, Marcus hopping, and McConnell …

Improving The Quality Of Physics Practice, Wyatt W. Thompson

All Graduate Theses, Dissertations, and Other Capstone Projects

This case study started with personal observations and experiences. As a lab teaching assistant, I observed on many occasions that students do not like their current homework platforms, often venting to me about their frustrations during lab time. As a student, I shared similar sentiments with them. To develop a possible solution to these observations, a theory of reasoning was chosen as the foundation. The heuristic-analytic theory of reasoning (HATR) suggests that people present an epistemic model (beliefs and ideas about a phenomenon) through a heuristic process (generation from memory) and engage in an analytic process to validate the epistemic …

An Analysis Of Slms For Machine Translation Of Healthcare Documents, Wyatt Clausen

All Graduate Theses, Dissertations, and Other Capstone Projects

The language barrier creates significant healthcare challenges for patients who struggle with English. While large language models (LLMs) have advanced machine translation, their high computational costs, environmental impact, and risk of data breaches have raised concerns. Small language models (SLMs) can address these concerns and be further adapted to specific tasks through parameter-efficient fine-tuning (PEFT) methods, including Quantized Low-Rank Adaptation (QLoRA). This study compares the Spanish-to-English translation quality of two 7-billion-parameter SLMs, Mistral and Llama 2 7B, in the medical domain, using BLEU, chrF, and COMET as evaluation metrics. It further investigates whether QLoRA fine-tuning and Retrieval-Augmented Generation (RAG) on …

A Comparative Analysis Of The Ecophysiology Between The Invasive Macroalgae Starry Stonewort And The Native Macroalgae Chara To Predict Invasion Potential, Thomas J. Zellmer

All Graduate Theses, Dissertations, and Other Capstone Projects

Starry stonewort (Nitellopsis obtusa) is an invasive macroalga from Eurasia. Currently, starry stonewort’s invasive range consists of the upper Midwest and Great Lakes region, including the Mississippi River. Starry stonewort poses recreational and ecological problems by forming dense canopies that extend through the water column. Starry stonewort occupies a late-season niche space with dense biomass occurring in late July and persisting well into autumn. There is a lack of information on the ecophysiology of starry stonewort. In this study, two populations of starry stonewort, Minnesota and New York, were analyzed to compare regional differences in ecophysiology, along with chara (native …

Evops: Evolutionary Patch Selection In The Embedding Space Of Whole Slide Images, Saya Hashemian

Theses and Dissertations (Comprehensive)

Computational pathology increasingly relies on the analysis of Whole-Slide Images (WSIs), which capture tissue specimens at gigapixel resolution. Because a single slide is far too large to process directly, the

prevailing paradigm decomposes each WSI into thousands of small patches and encodes them as high- dimensional feature embeddings using deep learning backbones. While effective, this paradigm carries a

substantial cost: the resulting collections of patch embeddings are computationally expensive to store and process, and they are frequently dominated by redundant, homogeneous, or otherwise uninformative tissue regions that dilute the diagnostic signal. Existing patch selection methods largely depend on heuristic or …

Variance Shrinkage In Dunnett-Type Multiple Comparisons With Missing Data, Md Habibullah

UNF Graduate Theses and Dissertations

Dunnett’s procedure is widely used for comparing multiple treatments with a control, but its application becomes challenging in the presence of missing data and multiple com- parisons. An improved Dunnett-type procedure addresses this by using multiple imputation under Rubin’s framework and constructing unified confidence intervals based on a multi- variate t distribution, allowing valid simultaneous inference while controlling the family-wise error rate (FWER). This work further extends the method by incorporating shrinkage-based variance estimation. Specifically, individual group variances are shrunk toward a common value to improve stability. This approach is particularly effective when group variances are similar or moderately different, …

Ridit-Based Adaptive Allocation In Two-Stage Clinical Trials With Binary Outcomes, Dewan Fahim

UNF Graduate Theses and Dissertations

This study explores better ways to assign patients to treatments in clinical trials with binary outcomes, such as success or failure. Adaptive methods are used to learn from early results and adjust treatment assignments during the trial, helping more patients receive better performing treatments while maintaining reliable conclusions. We focus on trials comparing multiple treatments using a two-stage design. In the first stage, several treatments are tested to identify the most promising one; in the second stage, that treatment is compared with a control. Unlike traditional equal assignment, we use adaptive allocation in the second stage to make better use …

Two-Stage Response-Adaptive Randomization Designs For Multi-Arm Trials With Normal Outcome, Tanjin Tamanna Happy

UNF Graduate Theses and Dissertations

This study focuses on improving how clinical trials compare new treatments with a standard treatment, when the response is quantitative (normally distributed). In a common two-stage design, several new treatments are first evaluated, and the best-performing one is selected if it appears better than the standard. In the second stage, this selected treatment is compared again with the standard using additional data to confirm its effectiveness. This approach is known to be efficient in terms of accuracy and sample size savings. We extend this design by introducing an adaptive method for assigning patients to treatments in the second stage. Instead …

A Stability Analysis Of The Phase-Lock Equations, Brian M. Sunguza

UNF Graduate Theses and Dissertations

Ginzburg and Landau have provided a set of equations that relate superconductivity to magnetic fields. Through a transformation process, Zhan has derived what are now called the phase-lock equations. A stability analysis of the spatially-independent phase-lock equations is the purpose of this presentation. This simplification is significant since it allowed for the analytical determination of equilibria, their stability, and the influence of a periodic forcing function. Through the use of an original code, numerical simulations are shown to corroborate the analytical results described above.

This analysis includes novel Lyapunov functions that allowed for the analytical determination of the instability region. …

Energy-Efficient Security For Narrowband Iot Using Blockchain And Ep-Cumac, Hafizullah Kakar

UNF Graduate Theses and Dissertations

The Narrowband Internet of Things (NB-IoT) continues to expand but faces challenges such as cryptographic overhead and energy consumption. Security frameworks such as blockchain and Energy-Performance Cumulative Message Authentication Codes (EP-CuMAC) rely heavily on SHA-256, which is not optimized for energy-limited devices.

This work unifies two complementary approaches, a hybrid blockchain-based NB-IoT framework and an EP-CuMAC-based framework, by engineering their cryptographic core with an Energy Complexity Model-optimized SHA-256 (ECM-SHA256). ECM applies parallel memory-bank mapping and block-level access optimization to reduce redundant power usage while preserving algorithmic integrity.

Experimental evaluation on identical Intel DDR3 systems using pyRAPL shows energy savings of …

The Law Of The Mid-Transition, Alison Gocke

Michigan Law Review

To address climate change, our energy systems need to transition from fossil fuels to clean energy resources. There is a tendency to think this transition will occur in a linear, seamless progression: We will move from the (old) fossil fuel system at Time A to a (new) clean energy system at Time B. But this belies the reality that an energy transition involves not just building a new energy system, but also unwinding an old one. Crucially, both processes will take time. That means there will be a significant period in which both energy systems coexist.

In the engineering literature, …

Algorithmic Medicine And The Duty To Disclose: Informed Consent Through The Lens Of Radiology, Lee Rodriguez

Michigan Law Review

Informed consent is the law’s mechanism for protecting patient autonomy by requiring disclosure of facts that bear on the decision to accept or refuse care. Artificial intelligence now helps decide what is medically true for patients, yet informed consent law still assumes that diagnostic judgment is rendered by a human mind whose reasoning is at least in principle communicable. Radiology has become the leading setting for this tension. AI systems triage worklists, flag suspected abnormalities, and anchor first-pass impressions in ways that guide radiologists’ attention and, in practice, can coauthor diagnostic conclusions while remaining invisible to patients. When patients are …