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Informationally-Optimal Measurements On Single-Qubit Systems, Adam V. Preston

Electronic Theses & Dissertations (2024 - present)

This thesis will focus on deriving informationally-optimal quantum state tomographic measurements on single-qubit systems, with the definition of informationally optimal to be defined as those measurements which maximize the average information gain. The informationally-optimal measurements that will be covered include projective measurements (formally building off of the work of [1] and putting it on firm, information-theoretic foundations), and more general types of quantum measurements called directional (also known as rank-one) positive operator-valued measure (POVM) measurements, and, finally, adaptive directional POVM measurements.

For projective measurements, we build on the work of Wootters and Fields ([1]) and show, via analytical methods and …

Development Of Photolabile Coumarin Linker For Rna Synthesis And Crisprcas9 Applications, Ian Mcclain

Electronic Theses & Dissertations (2024 - present)

The scope of RNA-based therapeutics continues to expand as more siRNA, mRNA, and CRISPR-based treatments are approved for various medical applications. Purification of synthetic RNA drugs is inherently challenging and requires considerable time and resources. New cost-effective and efficient purification strategies will expedite drug development process and will lower the drug costs. In this thesis I describe two generations of photolabile linkers for the non-chromatographic purification of therapeutic RNAs. In addition, the photolabile linker was utilized for regulation CRISPR-Cas9 gene editing. In the first part of the thesis, I describe the first generation of the photolabile coumarin-based linker for non-chromatographic …

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 …

The Effects Of Downdraft And Radial Ventilation In Hurricanes Earl (2010) And Edouard (2014), Jacob Vile

Electronic Theses & Dissertations (2024 - present)

Tropical cyclone (TC) intensity change in moderate vertical wind shear (VWS) is difficult to predict. Specifically, ventilation, the intrusion of dry and/or cool (i.e., low equivalent potential temperature (theta-e) air inside the TC, can have differing effects on TCs. Downdraft ventilation is the downward transport of below-mean  theta-e air by downdrafts, and radial ventilation is the inward transport of below-mean theta-e air by storm-relative radial winds. If this low theta-e air is able to get ingested by updrafts, it can result in a reduction of convection in the TC, thereby reducing intensity. Although most studies of ventilation have been conducted …

An Evaluation Of Current And Future Extreme Precipitation Events In The South American Altiplano Using Convective-Permitting Model Simulations, Karen R. Conron Chamberlain

Electronic Theses & Dissertations (2024 - present)

Extreme precipitation events in the South American Altiplano present significant hazards to communities in the Andean region, yet their future characteristics under anthropogenic climate change remain uncertain because of complex terrain and limitations of course-resolution climate models. This study evaluates the ability of South America Affinity Group Weather Research and Forecasting (SAAG-WRF) model with 4-km grid-spacing to reproduce 2000-2015 temperature, precipitation, and extreme precipitation events over the Altiplano. Examination of projected future changes is completed using the SAAG-WRF pseudo global warming (WRF PGW) simulation representing an approximately 3°C warmer global climate. The historical/control simulation (WRF CTL) was evaluated against DECADE …

Key Processes Involved In The Vortex Alignment Of Sheared Tropical Cyclones, Luis O. Hernandez

Electronic Theses & Dissertations (2024 - present)

Tropical cyclones (TCs) are challenging to forecast when under vertical wind shear (VWS). VWS tilts a TC’s vortex, creating asymmetries in its structure that impedes intensification. Although work has been done to conceptualize and understand how TCs evolve under shear and how they axisymmetrize and intensify, vortex alignment remains a complex and unresolved topic. The goal of this study is to assess what physical processes are important to tilt reduction and how these processes evolve in weak TCs. Using the Hurricane Analysis Forecast System Model-B (HAFS-B) 2.1, a case study on two storms, Hurricane Earl (2022) and Hurricane Lee (2023) …

When Helpfulness Becomes Harmful: Jailbreaking Llms For Malicious Code Generation, Noelle Capodieci

Electronic Theses & Dissertations (2024 - present)

Generative AI (GenAI) and Large Language Models (LLMs) have made large strides in coding task capabilities, with many software developers integrating agentic engineering into their workflow. While GenAI has largely benefited professional software engineers who can automate their work, it has also created room for those with little coding expertise to also create fully fledged programs and applications. It is commonly noted that GenAI is trained with two major goals in mind: to be as helpful as possible, and be as harmless as possible. There exist moments where helpfulness may be prioritized over harmlessness when these goals conflict. LLMs may …

Hydroclimate Variability And Itcz Migration Over The Last Millennium Inferred From A New Speleothem Record In Central Colombia Using Paleo Data Assimilation, Derick Appiah Kubi

Electronic Theses & Dissertations (2024 - present)

Hydroclimate variability over tropical South America is strongly influenced by meridional shifts in the Intertropical Convergence Zone (ITCZ), yet the spatial expression and dynamical controls of these changes during the last millennium remain poorly understood. This work investigates hydroclimate variability and ITCZ migration over the last millennium (850-1850 CE) using a new isotope-enabled data assimilation (DA) reconstruction made from a suite of speleothem δ¹⁸O records from the neotropics on both sides of the ITCZ. The reconstruction targets the March-August (MAMJJA) season in order to capture the rainfall regimes most relevant to central Colombia and northeastern Brazil. The focus on these …

Weather-Related Road Condition Detection Using Co-Developed Machine Learning Methods, Carly Sutter

Electronic Theses & Dissertations (2024 - present)

Transportation agencies make critical operational decisions during hazardous weather events, including assessment of road conditions and resource allocation. In this study, machine learning models are developed to provide additional support for the New York State Department of Transportation (NYSDOT) by automatically classifying road conditions across the state. Convolutional neural networks and random forests are trained on NYSDOT roadside camera images and weather data to predict road surface conditions. This task draws critically on a labeled dataset of 22,000 camera images containing six road surface conditions (severe snow, snow, wet, dry, poor visibility, and obstructed) generated from an iterative hand-labeling process …

The Impact Of Downdraft Ventilation On Tropical Cyclone Intensity And Structure Using Aerial Reconnaissance Observations, Nicholas E. Johnson

Electronic Theses & Dissertations (2024 - present)

Tropical cyclone (TC) intensity can be challenging to predict since it is modulated by many physical processes. One of these processes is ventilation: the injection of relatively cool, dry environmental air into the warm core of a TC that acts as “anti-fuel”, inhibiting intensification and increasing uncertainty with intensity forecasts. While ventilation has been examined in numerical modeling studies, there have been a limited number of observational studies investigating ventilation. The two primary objectives of this dissertation are to develop methods for measuring downdraft ventilation from aerial reconnaissance observations and to use those observations to better understand how ventilation affects …

The Ellipsoidal Principal Semi-Axis Geometry Of The Solution To An Ivp For A Matrix Diffusion Pde, Brandon M. Fox

Electronic Theses & Dissertations (2024 - present)

We analyze the underlying geometry of the solution to an IVP for a matrix diffusion PDE. We first derive the fundamental solution to the PDE. We then determine the unique solution to the IVP. From there, we begin analyzing its underlying geometry. We first observe that the geometry exhibits an ellipsoidal nature. Furthermore, we observe that it is described by the principal semi-axis geometry of the ellipsoids associated with the solution. This conclusion follows from applying the Principal Axis Theorem to the associated ellipsoids to establish their principal semi-axis geometry, as governed by the eigenstructure of the matrix. This thesis …

Concerted Proton Transfer In Homogeneous And Heterogeneous Cyclic Hydrogen-Bonded Clusters Of H2o, Hf, And Hcl, Max R. Tucker, Yuan Xue, Nathan R. Speake, Eden Nickolson, Jeremy M. Carr, Gregory S. Tschumper

Chemistry Faculty Research & Creative Works

This work examines various homogeneous and heterogeneous clusters of hydrogen-bonded (HF)x(H₂O)y(HCl)z complexes, where x + y + z = 3 or 4. For each unique cyclic structure associated with the xyz permutations, the geometries of the reactant, product, and transition state (TS) for concerted proton transfer (CPT) were fully optimized using second-order Møller-Plesset perturbation theory (MP2) with a mixed basis set consisting of cc-pVTZ for H atoms and aug-cc-pVTZ for O, Cl, and F atoms (denoted haTZ). Harmonic vibrational frequencies were also computed at the same level of theory to verify the nature of the stationary points. Intrinsic …

Scalable Transfer Of Dna Origami–Directed Nanoparticle Arrays Onto Functional Surfaces Using Thermal Release Tape, Yuwei Zhang, Chikadibia Genevieve Edward, Ethan Keuhn, Shelley D. Minteer, Risheng Wang

Chemistry Faculty Research & Creative Works

Precise integration of DNA origami nanostructures onto functional substrates is essential for advancing electronics, photonics, and biosensing. However, most surface-assembly methods are highly sensitive to substrate type, limiting their broader applications. Here, we introduce a thermal release tape (TRT)-assisted transfer method that enables efficient, large-area printing of DNA origami-guided gold nanoparticle (AuNP-DNA origami) arrays from mica onto diverse surfaces. The method relies on differential adhesion: AuNP-DNA origami arrays form strong electrostatic and hydrogen-bonding interactions with 3-aminopropyltriethoxysilane (APTES)-functionalized receiver substrates, while the TRT adhesive weakens upon heating to 120°C, allowing release from the tape. Using this approach, well-ordered AuNP-DNA origami arrays …

Evaluation Of A Novel Re-Crosslinkable Preformed Particle Gel For Conformance Control In Ultra-High Temperature Reservoirs, Yanbo Liu, Tao Song, Caleb Kwasi Darko, Thomas P. Schuman, Mingzhen Wei, Baojun Bai

Chemistry Faculty Research & Creative Works

Preferential fluid flow remains a major challenge in subsurface energy production and gas storage operations, resulting in excessive water production in mature oil fields, reduced heat extraction in geothermal reservoirs, and low sweep and storage efficiency in CO₂-EOR projects. Polymer gels are widely used to mitigate high-permeability channels; however, conventional systems exhibit limited plugging efficiency and short lifetimes in ultra-high-temperature reservoirs due to poor thermal stability. This study presents a novel ultra-high-temperature-resistant preformed particle gel (UHT-PPG) developed for conformance control in reservoirs with temperatures of 150–275 °C and severe super-K or channeling problems. The material was evaluated in …

Volatile Organic Compound Analysis Of Humboldt Penguin (Spheniscus Humboldti) Preen Oil: A Pilot Study, Dante E. Rojas, Mitchell M. Mccartney, Eva Borras, Michael O. Eze, Abigail Pietrow, Jennifer J. Valvo, Cristina E. Davis

Chemistry Faculty Research & Creative Works

Avian olfaction has gained prominence in recent decades for its roles in social communication and behavior. In penguins, the chemical characterization of preen oil remains limited. In this exploratory study, we characterized the volatile organic compound (VOC) profile of preen oil from Humboldt Penguins (Spheniscus humboldti). Preen oil from 12 captive individuals was analyzed using headspace sorptive extraction (HSSE) coupled to gas chromatography–mass spectrometry (GC–MS). Chemometric analyses examined variation in VOC profiles by sex, age class, and breeding activity. We detected 54 compounds (20 tentatively identified), including linear alcohols, methyl ketones, carboxylic acids, saturated hydrocarbons, oxygenated and nitrogen-containing organics, prenolipids, …

Synthesis Of The Naga(S1−Xsex)2 Solid Solution From Mechanically Activated Precursors, Louisiane Verger, Julien Trébosc, Santhoshkumar Sundaramoorthy, Amitava Choudhury, Olivier Hernandez, Eric Furet, Sébastien Chenu, David Le Coq, Laurent Calvez, Olivier Lafon

Chemistry Faculty Research & Creative Works

NaGaS₂ and NaGaSe₂ are two recently discovered compounds that crystallize in the same structure type. In this work, NaGa(S_1−xSe_x)₂ (x = 0.5, 0.75 and 1) are prepared using an alternative synthesis route, mechanochemistry followed by heat treatment. Na₂S, Na₂Se, Ga₂S₃ and Ga₂Se₃ are milled in stoichiometric proportions. Differential scanning calorimetry, X-ray diffraction and solid-state nuclear magnetic resonance (²³Na and ⁷¹Ga) show that the compounds after milling are composed of crystalline NaGa(S_1−xSe_x)₂ with an amorphous part. …

Progression Toward Terminal Oxidation Of Starch Via Hybrid Organic–Enzymatic Bioanode For Renewable Carbohydrate Conversion, Adam Milam, Jose Intano, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

The performance of starch-based biofuel cells is fundamentally limited by inefficient utilization of the fuel's inherent energy density. Sequential oxidation of carbohydrate fuels, such as glucose, the monomeric unit of starch, using minimal catalyst systems has therefore emerged as a promising strategy to improve biofuel cell efficiency. Here, we extend a previously reported three-catalyst, organic–enzymatic glucose oxidation cascade to polymeric carbohydrate fuels by integrating enzymatic starch depolymerization with downstream electrochemical oxidation. To our knowledge, this represents the first demonstration of a defined hybrid organic–enzymatic cascade designed to drive progression of starch-derived glucose equivalents toward terminal oxidation using a minimal catalyst …

Soft-Chemical Scalable One-Pot Aqueous-Medium Synthesis Of Na3(Vo)2(Po4)2f-Based Cathodes: Compositional Tuning And Electrochemical Performance In Na- And Li-Ion Batteries, Prashanth Sandineni, Subal Chandra Manna, Sutapa Bhattacharya, Santhoshkumar Sundaramoorthy, Ramesh Deokate, Milad Aghayi-Anaraki, George E. Sterbinsky, Kartik Ghosh, Amitava Choudhury

Chemistry Faculty Research & Creative Works

One of the most important cathode materials for Na-ion batteries, Na₃(VO)₂(PO₄)₂F, and its compositional variants have been synthesized using four different and facile one-step soft chemical routes. The as-synthesized compounds, Na_2.95(VO)₂(PO₄)₂F (I), Na_2.93(VO)₂(PO₄)₂F (II), and Na_2.58(VO)₂(PO₄)₂F (IV), crystallize in the tetragonal crystal system in the P4₂/mnm space group, while Na₃(VO)₂(PO₄)₂F (III) crystallizes in the orthorhombic crystal system in …

Closing The Nitrogen Loop In Groundwater With Biohybrid Technologies, Linjie Zhou, Biao Li, Jianhua Guo, Shelley D. Minteer, Yifeng Zhang

Chemistry Faculty Research & Creative Works

Nitrate in groundwater should be treated as a nitrogen source rather than a contaminant. Biohybrid technologies coupling microbial selectivity with renewable electro(photo)chemical energy offer opportunities to convert nitrate to value-added ammonium, although challenges remain in scalability, microbial stability, material–microbe integration, process engineering, regulatory compliance, and economic feasibility.

Handwriting Recognition In Vr, Dominique Mosley

EWU Masters Thesis Collection

Virtual Reality (VR) is slowly becoming more popular for more than just entertainment. VR can be found in educational, office, and even healthcare settings to help discover more intuitive ways to teach, collaborate, and treat patients. Outside of the virtual world, these environments typically rely on writing for communicating or note-taking. Currently, VR input forces users to rely on clunky on-screen keyboards which disrupts the user’s immersion and breaks the flow of natural interaction. This thesis explores the potential of VR as a learning platform by combining it with artificial intelligence (AI). It aims to develop a VR-enhanced handwriting practicing …

Optimal Quantization On Spherical Surfaces: Continuous And Discrete Models—A Beginner-Friendly Expository Study, Mrinal Kanti Roychowdhury

School of Mathematical & Statistical Sciences Faculty Publications

This expository paper provides a unified and pedagogical introduction to optimal quantization for probability measures supported on spherical curves and discrete subsets ofthe sphere, emphasizing both continuous and discrete settings. We first present a detailedgeometric and analytical foundation for intrinsic quantization on the unit sphere, includingdefinitions of great and small circles, spherical triangles, geodesic distance, Slerp interpolation,the Fréchet mean, spherical Voronoi regions, centroid conditions, and quantizationdimensions. Building upon this framework, we develop explicit continuous and discretequantization models on spherical curves, namely great circles, small circles, and greatcircular arcs—supported by rigorous derivations and pedagogical exposition. For uniformcontinuous distributions, we compute optimal …

Fully Discrete Finite Element Methods For The Stochastic Kuramoto–Sivashinsky Equation With Multiplicative Noise, Hung D. Nguyen, Liet Vo

School of Mathematical & Statistical Sciences Faculty Publications

We investigate a fully discrete finite element approximation for the stochastic Kuramoto–Sivashinsky equation, combining the standard finite element methods in spatial discretization with the implicit Euler–Maruyama scheme in time. Rigorous error estimates are established for two distinct noise regimes. In the case of bounded multiplicative noise, we prove optimal strong convergence rates in full expectation. The analysis relies crucially on a stochastic Gronwall inequality and an exponential stability estimate for the PDE solution, which together control the interplay between the nonlinear drift and the multiplicative stochastic forcing. For general multiplicative noise, where boundedness no longer holds, we derive sub-optimal convergence …

The Maxima Method For Identification Of Principal Periodic Components In Time Series Analysis, Megan Di Maio

Electronic Theses & Dissertations (2024 - present)

This dissertation investigates methods for mean estimation in periodically correlated time series, focusing on the Variable Bandpass Periodic Block Bootstrap (VBPBB) and a novel data-driven maxima method. Time series require specific methods because of the temporal correlation in the data. Traditional methods like the General Seasonal Block Bootstrap (GSBB) account for this correlation but often produce wide confidence intervals because they cannot isolate multiple periodicities, allowing noise and other frequencies to interfere with analysis. The VBPBB method addresses this by applying a Kolmogorov-Zurbenko Fourier Transform (KZFT) filter to the data before bootstrapping, which suppresses interfering frequencies and results in narrower, …

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% …

On-Device Artificial Intelligence Solutions With Applications To Smart Environments, Fabrizio De Vita, Dario Bruneo, Sajal K. Das

Computer Science Faculty Research & Creative Works

Recent advances in Artificial Intelligence (AI) and the increasing availability of computational power have accelerated the diffusion of Intelligent Cyber-Physical Systems (ICPSs), enabling smart applications with reasoning capabilities. However, the limited resources of embedded and Edge devices significantly constrain the complexity of deep learning models that can be effectively deployed. Traditional approaches rely on cloud-based training and edge-only inference, a paradigm that becomes inadequate when low latency, privacy, security, and high customization are required. In this context, On-device AI is emerging as a new paradigm in which both training and inference are performed directly on the device, avoiding data transfer …

Fairrfl: Fair And Robust Federated Learning In The Presence Of Selfish Clients, Andrea Augello, Ashish Gupta, Giuseppe Lo Re, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL) is a paradigm that enables collaborative machine learning without disclosing the local data of the participants. However, in real-world FL deployment scenarios, some unscrupolous clients may alter the training process to skew the global model towards their local optimum, unfairly prioritizing their data distribution. Their influence can degrade overall model performance for normal clients and reduce fairness in the system. We call this novel category of misbehaving clients 'selfish'. This work proposes a Fair and Robust strategy for aggregation in the Federated Learning (FL) server to mitigate the effect of Selfish clients (FairRFL). FairRFL incorporates a novel …

Smartflow: A Communication-Efficient Sdn Framework For Cross-Silo Federated Learning, Osama Abu Hamdan, Hao Che, Engin Arslan, Md Arifuzzaman

Computer Science Faculty Research & Creative Works

Cross-silo Federated Learning (FL) enables multiple institutions to collaboratively train machine learning models while preserving data privacy. In such settings, clients repeatedly exchange model weights with a central server, making the overall training time highly sensitive to network performance. However, conventional routing methods often fail to prevent congestion, leading to increased communication latency and prolonged training. Software-Defined Networking (SDN), which provides centralized and programmable control over network resources, offers a promising way to address this limitation. To this end, we propose SmartFLow, an SDN-based framework designed to enhance communication efficiency in cross-silo FL. SmartFLow dynamically adjusts routing paths in response …

Utility-Preserving Federated Graph Learning With Dual-Perspective Fairness, Renqiang Luo, Huafei Huang, Shuo Yu, Fengqi Yu, Feng Xia, Sajal K. Das, Chengqi Zhang

Computer Science Faculty Research & Creative Works

Fairness-aware federated graph neural networks (FedGNNs) necessitate consideration of both the server and the clients. However, fairness-aware methods struggle to enhance dual-perspective (i.e., server and clients) fairness without sacrificing utility due to the distributed learning framework. As a consequence, the utility sacrifices of fairness-aware graph learning methods are even exacerbated in federated frameworks. In this work we propose F3GL, a dual-perspective fairness federated graph learning method that enhances both global (for the server) and local fairness (for clients) while preserving utility. Through theoretical analysis, we delineate the similarity between original sensitive features and those after convolution under different spectra. Our …

An Introduction To Field Excursions For The 2026 Geological Society Of America Cordilleran Section Meeting In Loreto, Baja California Sur, México, Scott E.K. Bennett, Michael H. Darin, Genaro Martínez Gutiérrez

Geology Faculty Publications and Presentations

The 122nd annual meeting of the Geological Society of America (GSA) Cordilleran Section will be held in Loreto, Baja California Sur, México, an idyllic and historic Sonoran Desert city nestled on the eastern shore of the Baja California peninsula. The 2026 Loreto meeting marks a milestone for GSA as it is the first time in the Section’s century-plus history that the meeting has been held on the Baja California peninsula and only the third time that the meeting has been held in México. Thus, the 2026 Loreto meeting and related field trips represent a meaningful expansion of the Section’s engagement …

Dynamic Modeling Of The Earth's Trapped Proton Environment, Xiaojing Xu, Steve R. Blattnig, Francis F. Badavi, Martha S. Clowdsley, Edward J. Semones

Physics Faculty Publications

Context: Reliable prediction of space radiation exposure is critical for safeguarding spacecraft systems and ensuring astronaut health during missions. Accurate radiation risk assessment for space mission requires advanced models of the Earth’s trapped proton environment. These models must reflect temporal variations driven by geomagnetic field evolution and solar cycle modulation. Existing static models, such as AP8 and IRENE-AP9, are not designed to fully capture these evolving conditions. Aims: This paper presents a dynamic modeling method for the prediction of trapped proton fluxes, which incorporate time-dependent variations due to geomagnetic field evolution and solar cycle fluctuations. Methods: The …