Physical Sciences and Mathematics Commons^™

From Shock To Routine: The Evolving Impact Of Shutdown-Related Sentiment On Stock Markets, Yiran Shao

Honors Theses

To address gaps in existing research, this paper selects two U.S. government shutdown periods, 2018-2019 and 2025, as research samples to explore the effect of policy uncertainty on sentiment. This paper primarily analyzes the following two research questions.

First, what is the correlation between government shutdown-related sentiment during the shutdown period and daily market fluctuations? Specifically, can the sentiment index constructed from shutdown-related news effectively predict the next-day stock return during the event period?

Second, does the market have a learning effect? That is, between 2018-2019 and 2025, has the relationship between shutdown-related emotions and market outcomes weakened, shortened the …

Mathematical Model Of Graphene, Douglas M. Sanor

Williams Honors College, Honors Research Projects

Graphene, a single-atom-thick layer of carbon arranged in a hexagonal lattice, exhibits exceptional mechanical, electrical, and thermal properties that make it a promising material for a wide range of engineering applications. This paper presents a mathematical framework for modeling the mechanical behavior of graphene, with a focus on atomistic-to-continuum approaches. We begin with a onedimensional Frenkel-Kontorova model that represents graphene as a discrete chain of particles interacting with both their nearest neighbors through harmonic spring potentials and an underlying substrate through van der Waals forces. Numerical simulations of this discrete model demonstrate the commensurate-toincommensurate phase transition, revealing how geometric mismatch …

The Distribution Of A-Numbers Of Hyperelliptic Curves In Characteristic Three, Derek Garton, Jeffrey Lin Thunder, Colin Weir

Mathematics and Statistics Faculty Publications and Presentations

In this paper we present a new approach to counting the proportion of hyperelliptic curves of genus g defined over a finite field Fq with a given a-number. In characteristic three this method gives exact probabilities for curves of the form Y 2 = f(X) with f(X) ∈ Fq[X] monic and cubefree, probabilities that match the data presented by Cais et al. in previous work. These results are sufficient to derive precise estimates (in terms of q) for these probabilities when restricting to squarefree f. As a consequence, for positive integers a and g we show that the nonempty strata …

Algorithmic Trading In Idiosyncratic-Payoff Markets: A Multi-Agent System For On-Chain Prediction Contracts, Saif Aldeen A.K. Agha

CMC Senior Theses

This thesis documents the design, deployment, and forward-test evaluation of an evolutionary multi-agent algorithmic trading system on Polymarket, the largest decentralized prediction market. The system pairs a locally-hosted 72-billion-parameter language model with a gradient-boosted statistical filter and an evolutionary selection mechanism that maintains a population of approximately 500 autonomous trading agents. Each agent generates a probability estimate for an event, compares it to the prevailing market price, and trades the resulting disagreement.

The central empirical exercise estimates a panel regression of trade-level profit on the absolute disagreement between the agent's probability estimate and the market price, controlling for agent identity, …

From Physical Correlation To Emotional Connection: The Role Of Passive Haptics On Empathy In Virtual Reality, Jemely Robles

Dartmouth College Master’s Theses

Virtual reality is increasingly explored as a tool for cultivating empathy, and haptic feedback as a tool for enhancing immersion. This paper investigates the effects of combining the two.  Fifty-two participants experienced a custom-built VR scene in which a character was shown packing up a room. Participants were assigned to either a haptic condition, receiving passive haptic feedback corresponding to the character's actions, or a non-haptic control condition that did not receive any haptic input. Trait empathy was measured beforehand, and state empathy and engagement were measured after the experience. Thematic analysis was conducted on post-study interviews, and headset recordings …

Pressure Field Estimation From 2d-Piv Measurements: A Case Study Of Fish Suction-Feeding, Jensine C. Coggin, Duvall Dickerson-Evans, Erin E. Hackett, Roi Gurka

Marine Science

Particle image velocimetry (PIV) flow measurements are common practice in laboratory settings in a wide variety of fields involving fluid dynamics, including biology, physics, engineering, and medicine. Dynamic fluid pressure is a notoriously difficult property to measure non-intrusively, yet its variation is a driving flow force and critical to model correctly. Techniques have been developed to estimate the pressure from velocity and velocity gradient measurements. Here, we highlight a novel application of boundary conditions when applying such pressure estimation techniques based on two-dimensional PIV data; the novel method is especially relevant to problems with complex boundary conditions. As such, it …

Gone But Not Forgotten: Collaborative Telemetry Network Provides Insight Into Out-Of-System Movements Of Common Snook, Victoria S. Goldner, Mack White, Cody W. Eggenberger, Alia A. Jones, Cameron C. Atkinson, Jonathan R. Rodemann, W. Ryan James, Jordan A. Massie, Andrea M. Kroetz, Patrick M. O’Donnell, Ross E. Boucek, Rolando O. Santos, Jennifer S. Rehage

Marine Science

Objective The objective of this study was to examine the movements of Common Snook Centropomus undecimalis, a tropical euryhaline species, out of the Shark River, Everglades National Park, Florida, USA, and gain a better understanding of their long-distance regional movements. Methods This study used 7 years (2017–2023) of acoustic telemetry data from the Shark River Florida Coastal Everglades Array and from five other collaborative telemetry arrays in southwestern Florida to assess out-of-system movements for 119 Common Snook. Generalized linear models were used to assess the relationships between out-of-system movements and biological and environmental variables. Results Most Common Snook departures took …

Investigating The Connection Between Als Through The Mutation R522s In The Rna Binding Protein, Dennia Estrella-Vargas, Lydia Uptain

Mathematics

Amyotrophic lateral sclerosis (ALS) is a fatal disease that causes the deterioration of motor neurons , death is usually due to respiratory paralysis. The variant R522S was chosen because it is near a hot spot of pathogenic variants. It is an arginine-to-serine swap, this swap is present in pathogenic variants near the 522 position, such as R514S, R521S, R524S. Recent evidence suggests that arginine-deficiency can influence disease progression.

Asymmetric Synthesis Of The Hiv Protease Inhibitor Tmc-126, A Pmx Antimalarial Protease Inhibitor, And A Putative Covid-19 Inhibitor Using A Highly Stereoselective Glycolate Aldol Addition Reaction Pathway, Kweku Amaning Affram, Austin Carter, April Breede, Alexandra Kimsey, Godson Hemeson, Bader Semakieh, Moses Martinez, Emmanuel Ayim, Joy Odeh, Shawn R. Hitchcock

Faculty Publications – Chemistry

An asymmetric glycolate aldol addition pathway was developed for the synthetic preparation of a series of protease inhibitors based on the hydroxyethylamine structural motif. A single glycolate aldol adduct derived from a highly diastereoselective (≥95:5 d.r.) asymmetric aldol reaction served as the starting point for the synthesis of the inhibitors. The starting material is easily prepared and purified via recrystallization on multigram scales. This work describes the synthesis of the HIV protease inhibitor TMC-126, the Plasmepsin X (PMX) inhibitor 49c for the treatment of malaria, and a computationally derived inhibitor for the 3CLpro of the SARS-CoV-2 from a single common …

The Scattering Algebra Of Physical Space: Squared Massive Constructive Amplitudes, Moab Croft, Neil Christensen

Faculty publications – Physics

The Algebra of Physical Space (APS) is used to explore the Constructive Standard Model (CSM) of particle physics. Namely, this paper connects the spinor formalism of the APS to massive amplitudes in the CSM. A novel equivalency between traditional CSM and APS-CSM formalisms is introduced, called the Scattering Algebra (SA), with example calculations confirming the consistency of results between both frameworks. Through this all, two significant insights are revealed: The identification of traditional CSM spin spinors with Lorentz rotors in the APS, and the connection of the CSM to various formalisms through ray spinor structure. The CSM’s results are …

Ordo Ab Chao: Crystallographic Disorder As A Window Into Ionic Liquid Structure, Joseph Cooper, Marija Scheuren, Lara I. Teodoro, Christopher M. Butch, Raychell A. Jerdo, Kylie M. Allen, Mariana E. Toner, Matthias Zeller, Arsalan Mirjafari, Patrick C. Hillesheim

Faculty Publications – Chemistry

Despite being intended to resist crystallization, ionic liquids (ILs) quite frequently form solids, albeit with low melting points. The design motifs that lower melting points can leave measurable signatures in the solid state, manifesting as crystallographic disorder, and often give rise to metastable liquid states. While sometimes treated as experimental complications, such features provide a valuable window into the structural origins of IL phase behavior. Herein, we report a crystallographic study of a series of benzylated ILs that crystallize either directly or from long-lived supercooled melts. Single-crystal X-ray diffraction, supported by computational modeling and statistical analyses, provides structural evidence that …

Classifying Mathieu-Zhao Subspaces In Products Of Cyclic Rings, Sarah A. Huber

Theses and Dissertations

Mathieu-Zhao subspaces are a generalization of ideals in an algebra and were introduced by Wenhua Zhao in connection to the Jacobian conjecture and its variants. These subspaces have interesting properties, and often the problem of classification is hard. In this thesis, we investigate the structure of Mathieu-Zhao subspaces of the cartesian product of integers modulo powers of a prime p, Zpr × Zps . We will give a complete classification of the subgroups, maximal subgroups, Mathieu-Zhao subspaces, and maximal Mathieu-Zhao subspaces in these rings.

Fuchs' Problem For Quasi-Cyclic Groups, Dalen F. Elliott

Theses and Dissertations

Fuchs’ problem asks which groups can arise as the group of units of a ring. Although the finite cyclic case has been completely classified, much less is known in the infinite setting. This thesis contributes to this problem by investigating quasi-cyclic. (Pr¨ufer) groups and their finite direct products. We show that for every odd prime p, there is no commutative ring R such that R×∼= Cp∞. This obstruction arises from characteristic restrictions and the algebraic structure of finite fields. More generally, we prove that any group in which every element has order a power of an odd prime p and …

Managing Multi-Drug Resistance: An Evolutionary Game Theory And Optimal Control Approach, Shukhrat Nasrulloev

Theses and Dissertations

Multi-drug resistance is an evolutionary process in which treatment eliminates sensitive cells, allowing resistant clones to dominate. This thesis investigates this process using a framework integrating population dynamics, evolutionary game theory, and optimal control theory. We develop a two-population logistic growth model describing competition between drug-sensitive and drug-resistant cells under treatment, construct dose-dependent payoff matrices and replicator dynamics to characterize evolutionary competition, and derive a critical drug level D_crit = (r_S - rR)/(dS - d_R) at which resistant cells gain a fitness advantage. An optimal control problem is formulated via Pontryagin's Maximum Principle to identify schedules …

Data-Driven Partitioning In Distributed Optimization For Networked Systems, Prosper Azameti

Theses and Dissertations

The convergence behavior of distributed optimal power flow (OPF) depends strongly on how the power network is partitioned into regions. Classical graph-based methods such as METIS are widely used, but they rely mainly on static topological criteria and do not explicitly incorporate operating-point-dependent information that may affect distributed optimization performance. This thesis develops a data-driven partitioning framework for distributed OPF using graph neural networks (GNNs). Each OPF scenario is represented as a graph in which buses are nodes and transmission lines are edges. Node and edge features capture both structural and operational characteristics of the network. Partition prediction is formulated …

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, …

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.

Evaluating Llms For Cpe Identification In Iot Reconnaissance, Christopher Davisson

EWU Masters Thesis Collection

Vulnerability identification during penetration testing relies on rigid string-matching to map network scan data to Common Platform Enumeration (CPE) identifiers and downstream Common Vulnerabilities and Exposures (CVEs). The approach frequently fails on physical Internet of Things (IoT) devices, which produce non-standard, irregular service banners that resist deterministic parsing. Large Language Models can reason through these fuzzy associations, but cloud-hosted models introduce cost, latency, and operational security concerns when processing reconnaissance data from live networks. This thesis asks whether locally-hosted open-weight Large Language Models (LLMs) can perform this task well enough to be useful, and how performance varies with model scale, …

Tree-Based Graph Neura Networks For Natural Language Inference: From Structure-Only To Hybrid Architectures, Jason P. Lunder

EWU Masters Thesis Collection

Large transformer models achieve strong performance on natural language understanding tasks but require hundreds of millions of parameters and extensive pretraining. This thesis investigates whether graph neural networks operating on dependency parse trees can provide more parameter-efficient sentence representations for natural language inference, evaluated on two NLI tasks: entailment classification and semantic textual similarity.

Tree Matching Networks (TMN) adapt Graph Matching Networks to linguistic dependency trees with rich node and edge features, evaluated against a BERT baseline at matched parameter counts on identical training data. Tree Transformer Networks (TTN) extend TMN with transformer-based aggregation and tree-aware positional encodings, with component …

Learning Design To Advance Human-Ai Collaboration In K-12 Education, Wing Sha Chan, Jinhee Kim, Seongryeong Yu, Rita Kay Detrick

STEMPS Faculty Publications

This chapter explores key components for designing effective Human-AI Collaboration (HAC) in K–12 education, addressing the current lack of theoretical and conceptual frameworks for structuring and implementing HAC in teaching and learning. It examines four essential areas: curriculum design, student and teacher–AI interaction, learning environments, and the evolution of HAC over time. The chapter introduces the concept of HAC in K–12 contexts, highlighting how humans and AI can leverage each other's strengths through co-evolutionary processes that foster mutual learning and collaboration. It reviews current HAC practices in schools and discusses their contributions to both teaching and learning. Finally, it presents …

Impacts Of Segmenting Principle On Learner Performance And Attitude In A 3d Environment: A Mixed-Method Multiple Case Study, Kristin Herman, Mohan Yang, Jim Shifflet, Noah Glaser

STEMPS Faculty Publications

This study presents a conceptual replication of Moreno’s (Appl Cogn Psychol 21:765–781. 10.1002/acp.1348, 2007) study on the benefits of adhering to the segmentation principle when utilizing multimedia learning objects. Furthermore, this study expands upon the original by taking place in a low-immersive virtual reality environment, allowing for further understanding on the extent to which multimedia principles are still relevant. Both a synchronous and an asynchronous case are presented. Results indicate benefits for both cases in far transfer of learning. Furthermore, synchronous learners indicated a significant reduction in cognitive load and increased overall attitudes towards learning due to segmented instruction.

Decomposing Shadow Prices Under Climate-Driven Growth Scenarios: Insights From An Elk Herd Case Study, Ranjit Bawa, Drew Bennett, Wai Yan Siu, Bailey Kirkland, David Finnoff, Jacob Hochard

ODU Articles

Natural capital accounting provides a framework for integrating ecological processes with economic valuation, but the mechanics of shadow price formation often remain opaque to resource managers and policymakers. Using the Clarks Fork elk herd in northwestern Wyoming as a case study, we decompose the shadow price of natural capital into its ecological, economic, and institutional components. Population dynamics are estimated using a linearized Ricker model and projected forward using a logistic projection, incorporating climate-driven reductions in intrinsic growth rates. These ecological scenarios are linked to a shadow pricing formulation that explicitly accounts for marginal benefits, harvest policy responses, discounting, and …

Agricultural Productivity Under Energy Development: Insights From California, Wai Yan Siu, Sherzod B. Akhundjanov

ODU Articles

This paper examines how agricultural productivity patterns in Kern County, California, a leading region for both agricultural production and oil and gas development, co-vary with the spatial and temporal expansion of hydraulic fracturing and associated energy infrastructure. Using parcel- and county-level analyses, we characterize how agricultural productivity differs across proximity to energy development and across spatial scales. The results reveal spatially heterogeneous and scale-dependent patterns: parcel-level evidence indicates lower Enhanced Vegetation Index-based vegetation productivity within the 20-mile proximity zone around fracking wells, while county-level results show heterogeneous crop-specific yield changes during the post-expansion period. Together, these findings highlight the importance …

A Pipeline For Creating Obfuscated Binary Samples To Train Ai-Powered Detection Models, Luka R.H. Wilmink

Theses and Dissertations

The analysis of binary files is a critical component of antivirus software and is one of the most important tools for incident response teams across the industry. In the field, malware is often obfuscated, a practice in which the compilation process is transformed with different techniques to hinder decompilation and reverse engineering. Artificial Intelligence and Machine Learning techniques can assist, but models need to be trained on well constructed datasets first. This paper outlines a pipeline for creating such a dataset and builds a proof-of-concept machine learning classification model. All associated data and code are supplied in the project GitHub …

Machine Learning For Predicting Prosthetic Limb Movements, Jessica Alexandra Cegarra Arraiz

Theses and Dissertations

This thesis develops and evaluates a deep learning-based prediction model capable of identifying intended limb movement from surfaced electromyography (sEMG) signals using sequence learning techniques. sEMG signals change over time due to multiple factors such as muscle fatigue or user variability. Traditional prosthetics control methods rely on static feature extraction, ignoring how signals change over time, thereby limiting their ability to capture the temporal changes of muscle activity. As a result, these approaches often lead to poor accuracy, robustness, and generalization. Limited experimental validation has been conducted on sequence-based machine learning approaches using temporal sEMG data from publicly available datasets …

Characterizing A Low-Gradient Stream In Central Illinois As Gaining Or Losing And Observing Seasonal Changes In This Behavior, Eric Timothy Brunner

Theses and Dissertations

While the seasonal behaviors of low-gradient streams have been studied, the behavior of surface water and groundwater interactions within low-gradient streams in glaciated terrain is not fully understood. A third order, low-gradient glacial stream with a saturated riparian buffer in central Illinois was studied to determine the direction of flow between the surface water and groundwater. The goals of this study were to determine 1) whether the stream was gaining or losing water, and 2) whether the gaining or losing nature of the stream-aquifer system changes seasonally. At both an upgradient and downgradient location, two wells were installed: one in …

Symmetry In Latin Hypercubes, Levi Neiburger

Theses and Dissertations

Let [n] = {1, ..., n}. A hypercube H of order n and dimension d is a d-dimensional array whose nᵈ cells are indexed by [n]ᵈ. A hyperplane in H is obtained by fixing one coordinate, while allowing the remaining d–1 coordinates to vary. We wish to color each cell of H from a palette of n^d-1 colors such that each hyperplane is polychromatic.

Our main result is the following. Let n be sufficiently large. There exists a symmetric coloring of the d-dimensional hypercubes of order n whose all hyperplanes are polychromatic if and only if: …

Data Defines Success: Algorithm For Dataset Quality Assessment In Deep Learning For Malware Detection, Matei Ionescu

Theses and Dissertations

The field of artificial intelligence is based upon the premise of constructing architectures through which to propagate training data. However, the majority of existing research literature is focused on architecture. While necessary, the attention devoted to the architecture should not so precipitously exceed that of the data. It should be noted that this disparity is not without reasonable cause. Data quality is often exceedingly difficult to verify due to particularities of the field or subfield; LLM repositories of text are distinct from image recognition pictures of dog breeds which are distinct from EEG waveforms of human brains which are distinct …

Chemical Load: An Unseen Herbicide Filter In Restored Prairies?, Rylie Franklin

Electronic Theses and Dissertations

Community Assembly Theory is a framework used to describe the process by which species from a regional species pool disperse and encounter various abiotic and biotic conditions that act as filters, limiting which species will populate a specific local community. Prairie restoration success can be improved by understanding abiotic and biotic filters. As agricultural practices have adopted integrated weed management plans, that include the use of both chemical and non-chemical techniques, another filter needs to be considered during restoration: the chemical load of soils, i.e., herbicide residue from recent on-site applications and herbicide drift from adjacent areas. To examine the …