Digital Commons Network^™

Non-Traditional Rare-Earth-Doped Oxide Glass As A Gain Medium, Jared S. Tolliver

Optical Science and Engineering ETDs

There is a need for mid-infrared(MIR) lasers in defense, medical, and environmental monitoring. A large part of this technological development is the study of gain media. One class of materials of special interest is glasses with a low maximum phonon energy. These have the fiberization and broad spectral features of glass, whereas glasses with high maximum phonon energy exhibit higher rates of multi-phonon relaxation and can be opaque in the MIR, both of which are detrimental to laser operation. Recent advances in container-less processing have allowed for the study of new glasses that aren’t possible with conventional fabrication techniques. One …

Ionophore-Based Plga Nanosensor For Selective Ion Detection And Imaging, Zhiyu Tang

Electronic Theses and Dissertations

Accurate detection of electrolyte ions is essential for biological research, disease diagnosis, and the investigation of cellular function. In this study, we developed ionophore-based PLGA nanosensors for the optical detection of biologically important ions. The nanosensors were prepared by encapsulating ionophores, chromoionophore III, and ion exchangers within PLGA nanoparticles. The resulting nanosensors showed uniform morphology, good colloidal stability, and concentration-dependent optical responses toward Na⁺, K⁺, and Ca²⁺ over the range of 10⁻⁶ to 10⁻¹ M. Reversible fluorescence responses under repeated ion concentration changes confirmed the stability and robustness of the sensors. The nanosensors also demonstrated reliable analytical performance for K⁺ …

Measurements And Studies For Rare Event Searches Using Directional Detectors, Elizabeth Tilly

Physics & Astronomy ETDs

Measuring topology and initial direction of low-energy (keV-MeV) particle tracks is interesting to rare-event searches. While directional dark matter searches have been one of the largest drivers for R&D for low-energy directional detectors, this work is interested in its application to Migdal searches. The Migdal effect—a nuclear recoil and an electron recoil sharing a vertex—has been used as a detection channel for low-mass dark matter but has only recently been measured. Low-energy directional detectors are ideal to measure the canonic Migdal topology. This dissertation discusses 3D reconstruction algorithms developed for the Migdal In Galactic Dark mAtter expLoration (MIGDAL) experiment and …

Exploring The Role Of A Mushy, Crustal Compliant Region In Volcano Deformation, Grant A. Block

Physics & Astronomy ETDs

Volcanoes are both creative and destructive forces that have shaped and continue to shape our world from early geologic time to the present day. Continued study of volcanic processes not only better prepares us for monitoring volcanic hazards but also allows us to better understand processes fundamental to Earth as we know it, such as the generation of the atmosphere and accretion of the continents. This dissertation focuses on an integral part of volcanic processes: the trans-crustal magmatic transport system. Specifically, we investigate regions of these transport systems where magma pools in melt-rich lenses within broader regions of low melt-fraction, …

Final 2022 Unreclaimed Sites Sampling: Ur-07 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Dynamic Reconstruction Engineering Of Anti-Corrosion Ni-Based Anodes For Alkaline Seawater Electrolysis, Yi-Gang Zhang, Wen-Wen Xu, Tian-Yu Zhang, Zhi-Yi Lu

Journal of Electrochemistry

Green hydrogen production via alkaline seawater electrolysis offers an environmentally sustainable and potentially cost-effective route to address both energy and climate challenges. Achieving long-term anode stability under complex ionic environments and industrial current densities remains a central bottleneck. Specifically, Ni-based anodes exhibit intense surface reconstruction during the oxygen evolution reaction, necessitating dynamic anti-corrosion strategies. This mini review systematically summarizes reconstruction engineering approaches to develop anti-corrosion Ni-based anodes of alkaline seawater electrolysis across increasingly complex ionic environments from simulated seawater to real seawater: (i) Cl^– dominated; (ii) Cl^– with co-existing oxyanions, and (iii) Cl^–  with co-existing Br^{– …}

Preparation And Performance Study Of In-Situ Self-Assembled Biphasic Smmn2O5-Nimn2O4 Composite Cathode, Neng-Chu Xia, Yu Zhou, Qin Wang, Jia-You Zhang, Chun Yu, Yang Zhang, Wan-Bing Guan, Jian-Xin Wang

Journal of Electrochemistry

Mullite-structured oxides exhibit excellent oxygen reduction reaction activity, possess a low thermal expansion coefficient due to their unique crystal structure, and can eliminate the need for a barrier layer and simplify the preparation process as they contain no alkaline earth elements. Thus, they hold great promise as novel cathode materials for solid oxide fuel cells. In this work, a mullite-spinel-structured SmMn₂O₅-NiMn₂O₄ (SMO-NMO) composite cathode was one-step synthesized via a solid-liquid composite route, and its in-situ self-assembly enabled good compatibility with the electrolyte without any barrier layer. Characterization results showed that the SMO:NMO = …

Simulations Of Atmospheric Pressure Streamer Discharges: Mechanisms Of Streamer Propagation And Related Physics, Dejan Nikic

Electrical and Computer Engineering ETDs

Gas discharge simulations are performed with particular focus on photoionization process in a positive streamer discharge. The effects of this process are investigated by isolating the change in photoionization mean free path (MFP) and keeping the additional processes constant. Furthermore, comparison are made between various effects of simulation parameters, such as initial conditions, geometry extent, simula- tion particle count etc. All of these simulations are performed using a modern Direct Simulation Monte Carlo Particle-in-Cell (DSMC-PIC) code developed by Sandia Na- tional Laboratories. Large scale simulations including 1 cm and 5 cm electrode gaps are performed under standard atmospheric condition air. …

A Hybrid Deep Learning Model Combining Cnn And Extreme Learning Machine For Cyberattack Classification, Israa S. Kamil

Journal of Intelligent Informatics, Networking, and Cybersecurity

As ransomware attacks and zero-day exploits grow sophisticated, the need for intelligent, accurate systems to detect such threats becomes clearer. In this paper, a hybrid learning model based on Convolutional Neural Networks (CNNs) and Extreme Learning Machine (ELM) is presented to improve multiclass classification performance for cybersecurity applications. The framework combines CNNs' hierarchical feature learning with ELMs' fast classification. An attention mechanism that assigns weights to each feature based on importance is included in the final model. The hybrid model performed well on the metrics: precision = 0.97, recall = 0.98, and F1- score = 0.97, and, as expected from …

Towards Intelligent Iot-Ndn Security: Ai-Driven Pit Attack Detection And Cache Attack Analysis, Sura Haidar Ali, Alaa Shawqi Jaber

Journal of Intelligent Informatics, Networking, and Cybersecurity

Beginning with Named Data Networking (NDN), an early form of information-centric networks, the paradigm of how data is transmitted over a network was changed through the use of ``content-based'' communication instead of ``host-based'', while creating native caching at intermediate points along the path to each destination, and improving upon the security of all previous paradigms. NDN contains many inherent benefits such as caching, security, etc., but like any other paradigm, NDN creates new types of vulnerabilities, particularly within some of the key elements of this paradigm; namely the Content Store (CS), Pending Interest Table (PIT), and the Forwarding Information Base …

Stop Blaming My Users: Illumination Of The Technocentric Mythos Bias, Ervin H. Frenzel, Richard Lightcap

Journal of Cybersecurity Education, Research and Practice

 Abstract -This conceptual essay addresses the need for systemic and systematic transdisciplinary analytical techniques within cybersecurity and technical security. This conceptual essay is contingent upon recognition that cybersecurity is not simply technical in nature, it does not need an adversary, and more importantly it is based upon systems engineering and systems thinking.  The essay contributes a socio-technical attribution chain and field-specific ontology/taxonomy which distinguish user-triggered events from root causes, latent conditions, technical debt, validation failures, governance failures, and attribution bias before assigning responsibility to end users. It systematically defines an ontology inclusive of developer technical debt, organizational debt arising from …

Escaping The Cyberstorm: A Gamified Social Engineering Training Program, Noah Mcclanahan, Fadi Abu-Amara, Ali Khattab, Travis Jett, Andre Jackson

Journal of Cybersecurity Education, Research and Practice

In this research work, we explored the effectiveness of gamification in improving cybersecurity awareness and training users on targeted social engineering attacks. Traditional cybersecurity training focuses on lectures and videos. These training methods may not actively engage employees, which reduces their knowledge retention and ability to recognize social engineering attacks. This lack of involvement is a concern, as social engineering continues to be one of the most prevalent attack methods faced by end-users. A gamified training program, Escaping the Cyberstorm, was developed using the Godot game engine to address key challenges in spreading cybersecurity awareness. The game includes real-life …

Accessibility Fairness Practices In Ai Applications For People With Disabilities, Megan Gross

Master's Theses

Advancements in artificial intelligence (AI) improve the lives of people every day with tools like the auto-captioning of videos, improved screen-reader capabilities, and advanced mobility control through speech. However, are all groups of people benefiting from AI or are some being overlooked and left out? Although AI tools made for people with disabilities (PWDs) have improved their lives, AI for the general population generally ignores the experiences of PWDs, making them unable to interact with and benefit from technology. This research evaluates ChatGPT and Gemini in Gmail for usability fairness and analyzes how current regulations and development processes fail to …

Artificial Intelligence Mechanisms In The Limit Of Crimes And Law Enforcement, Saad Mefleh Alsuwaileh

Journal of Police and Legal Sciences

This study explores the potential of employing technological mechanisms and modern innovations brought about by the Fourth Industrial Revolution, particularly advancements in the field of information technology, in the domains of criminal investigation, crime prevention, and law enforcement. It aims to analyze the impact of these technologies on crime control efforts and the promotion of justice.

The significance of the study lies in highlighting the power of technology in processing and analyzing massive volumes of data with greater speed and accuracy, thereby enhancing the efficiency of criminal investigations and the ability to predict and prevent crimes. The core research question …

Applying Artificial Intelligence Within Decision Support Systems And Its Role In Improving Proactive Thinking And Reducing Security Threats: The Mediating Role Of Data Quality, Hany Shaaban El Anany

Journal of Police and Legal Sciences

The study aimed to identify the impact of applying artificial intelligence within decision support systems in improving the level of proactive thinking and reducing security threats in government institutions in the Arab Republic of Egypt, as well as to examine the mediating role of data quality in this relationship, at a significance level of (α ≤ 0.05). The study sample consisted of (360) participants working in the departments of information technology, decision support, and cybersecurity within government institutions and national authorities that rely on AI-enhanced decision support systems.

The study adopted the descriptive analytical method and used a questionnaire as …

Spatial Heterogeneity And Temporal Trends Of California Extreme Heat Using High-Resolution Earth System Model Simulations, Eleni Konstantelos

Master's Theses

Extreme heat threatens California’s diverse landscapes and populations through intensifying and geographically shifting patterns. This study examined the temporal trend and spatial heterogeneities of California’s extreme heat for 1994–2015. The analysis was based on the fully coupled Energy Exascale Earth System Model version 2 (E3SMv2), specifically its 25-km regionally refined configuration. While the Desert/Inland region exhibited the highest number of days ≥ 35 °C and the highest heatwave severity, Central Valley showed the fastest increase in the number of days ≥ 35 °C and heatwave events, as well as the fastest increases of days exceeding various heat index thresholds over …

Error-Tolerant Metric Dimension, Leander Ten Hoff

Master's Theses

Metric dimension is a graph parameter that measures the smallest distance-based unique coordinate system on a graph. Fault-tolerant metric dimension is a variant that requires redundancy. Inspired by this idea, we propose and investigate a new variant we call error-tolerant metric dimension. We first prove some fundamental results to gain familiarity with this more complex variant. Then, we use these tools to study relative behaviors of error-tolerant metric dimension. We prove explicit computations for simple graph families, including bipartite complete graphs and paths. Finally, we extend extremal results from previous papers on metric dimension, including a full correction of an …

Probabilistic Metric Dimension, Kyle Worley

Master's Theses

The metric dimension of a graph G is the smallest number of unique vertices (often called “marked vertices” or “landmarks”) such that each vertex has a unique distance to the marked vertices. If a set of vertices S ⊆ V (G) when marked gives all vertices unique distances, it is called a resolving set. Hence if G is a graph with a resolving set S, then for all v, u ∈ V (G) there exists s ∈ S such that d(v, s) ̸= d(u, s). The metric dimension dim(G) = min(|S|). Two widely studied variants exist, one where edges are …

The Relationship Between Foliations Of The Plane, Kaplan Diagrams, And Non-Hausdorff 1-Manifolds, Monique Justine Howe

Master's Theses

In this paper we seek to explain the relationship between foliations of the plane, Kaplan diagrams, and simply connected non-Hausdorff 1-manifolds with countable basis that are orientable with an ordering on branch points. We will walk the reader through the definitions of all of these objects, and provide examples with a focus on the motivating example of the Reeb foliation. This paper will describe and define the known bijection from the set of foliations of the plane, F, to the set of Kaplan diagrams, K, its inverse, and the one-to-one map from F to the set of simply connected non-Hausdorff …

Monoids With K-Strictly Local Geodesic Languages, William M. Hong

Master's Theses

A paper by Gilman, Hermiller, Holt and Rees (2011) prove that a group G finitely generated by X is virtually free if and only if the language of geodesics words in G over X is k-strictly local if and only if the word problem is context-free. If M is a monoid finitely generated by X, we define Γu(M,X) to be the underlying, undirected graph of Γ(M,X). We prove that if the language of geodesics in Γu(M,X) based at the identity is k-strictly local, then the monoid and semi-group word problems are context-free.

Rewriting The Calculus 3 Workshop At San José State University, Moorea Lippert

Master's Theses

Calculus 3 at San José State University is a very important course for any student pursuing a STEM degree. However, the course is very challenging, so the university offers a supplemental workshop course for Calculus 3 students. Unfortunately, this workshop has not aligned with modern research in math education. This thesis documents efforts to recreate the workshop to better align with this modern research.

Fermat's Last Theorem Over Quadratic Number Fields, Richie Tay

Master's Theses

Fermat’s Last Theorem states that the equation xn + yn = zn has no nontrivial integer solutions for n ≥ 3. While the rational case is completely solved, the situation over quadratic number fields is not as straightforward. For some exponents nontrivial solutions exist, while for others they do not. This thesis studies Fermat-type equations over quadratic number fields, combining classical methods with more modern techniques from the theory of elliptic curves. The thesis first reviews the rational cases n = 2, n = 3, n = 4, then develops the necessary background on quadratic number fields, including rings of …

Rational Non-Euclidean Triangles And Elliptic Curves, Tyler Morales

Master's Theses

We say a triangle △ is rational if its side lengths are rational. For a geometry of constant curvature κ, we say △ is a rational triangle if the generalized tangents of its side lengths are rational. We are able to parameterize rational triangles having the same inradius and semiperimeter on an plane curve, write a bijection between the rational points on this curve and triples of side lengths, and show that this curve is an elliptic curve. Then, we write a general transformation for our plane curve to short Weierstrass form to compute ranks and add points easily using …

Match Made In Ml: Developing Compatibility Relationships In Evidential Reasoning Approaches With Machine Learning, Ella Jolie Thomas

Master's Theses

The presented expectation maximization informed evidential reasoning model extends the ability of the evidential reasoning calculus to support decision making by integrating an adaptive model learning capability. Compatibility relationships in Evidential Reasoning models are traditionally built by human domain experts. This process is labor-intensive, especially for large and complex models. Additionally, when new data becomes available, compatibility relationships must be reconstructed. Using machine learning and the expectation maximization algorithm, it is demonstrated that compatibility relationships can be constructed that learn relationships between domain knowledge that is used to make decisions. Using drug development as a domain of application, a traditional …

Math 141 Calculus I (Queens College), Anisha Clarke

Open Educational Resources

This syllabus provides the outline for a calculus one course using OpenStax Calculus Volume I and no graphing calculator.

Superresolution Spectroscopy Of Atomically Thin Semiconductors And Moiré Heterostructures, Chien-Chu (Charity) Wei

Master's Theses

Atomically thin semiconductors and moir’e heterostructures provide an important platform for studying quantum phenomena shaped by reduced dimensionality, interlayer coupling, strain, and local structure. In MoS2, the transition from bulk to monolayer form changes the material from an indirect to a direct band gap, while stacked and strain-engineered systems can produce spatially varying moir’e potentials on nanometer length scales. Because these effects are highly localized, conventional far-field optical spectroscopy is often limited in its ability to resolve them directly. This thesis explores superresolution vibrational spectroscopy as a route toward probing local behavior in atomically thin semiconductors and moir’e heterostructures. Far-field …

The Characterization Of Bridging Waters And Ions In Protein-Rna Complexes, Leslie Duong

Master's Theses

Here we explore the role of bridging waters and ions in protein-RNA complexes. From an initial set of 33 high-resolution X-ray crystal structures, 17 were identified such that protein-RNA complex and component protein and RNA chains were found within 1 pH unit as indicated by crystallization conditions and their diffraction temperatures meeting one of two ranges: above or below freezing. To define an even more realistic set, 12 unbound-unbound and unbound-pseudo-unbound complexes from the 17-set were studied, showing the large fraction of complexes indicating more protein and RNA water hydrogen bonding in their actual interfacial regions as opposed to those …

Diagrammatic Methods For Calculating Correlation Functions In Low-Dimensional Quantum Gravity, Nicholas A. Parrilla

Master's Theses

This thesis investigates connections between random matrix theory and low-dimensional quantum gravity through the spectral form factor (SFF), a well-studied function that characterizes correlations in the eigenvalue spectrum of an operator. In random matrix ensembles, a feature of the SFF known as the “ramp” is governed by universal spectral correlations, and in Jackiw–Teitelboim (JT) gravity this regime is due to the double-trumpet wormhole geometry. We study the connected correlation functions underlying the SFF using combinatorial, diagrammatic methods from a mathematical formalism known as second-order free probability theory, where they are expressed in terms of annular noncrossing permutations. To access a …

Hydrus Modeling Of A Sahelian Agroforestry System: An Investigation Of Local Water Balance, Nicole A. Butler

Master's Theses

Effects of drought can devastate agricultural productivity in the West African Sahel. Climate complexities, such as lower-than-average rainfall and high winds, can lead to crop failure and low yields, thereby creating food security issues. Agriculture in the Sahel is primarily rainfed, and the rain is becoming increasingly unpredictable due to the changing climate. The method of intercropping groundnut (Arachis hypogea) and pearl millet (Pennisetum glaucum) with the shrub species Piliostigma reticulatum can combat the effects of climate change and restore degraded soil. Intercropping can increase water availability and crop yield when compared to crops grown in the absence of shrubs. …

Reskilling And Retraining The Water Technology Workforce: An Agentic Generative Ai Framework For Water Purification, Nano‑Mems, And Curriculum Development, Satyadhar Joshi, Noor Zulfiqar

Harrisburg University Other Works

The rapid digitalization of water infrastructure is bringing artificial intelligence, advanced sensing, and membrane materials science into routine water treatment practice. At the same time, utilities, regulators, and training institutions face a persistent workforce challenge: many operators, engineers, and managers are being asked to adopt data-driven tools without a coherent educational pathway that links AI literacy to real treatment workflows. This article synthesizes recent literature on agentic generative AI, reinforcement learning, smart sensing, nano-enabled membranes, and digital twins for water systems, then translates those developments into a structured reskilling model for the water sector. The proposed framework is organized around …