Physical Sciences and Mathematics Commons^™

Investigation Of Protein-Ligand Binding Interactions Through The Computational Methods Of Molecular Dynamics And Graph Neural Networks, Alexander Benjamin Wroe

Graduate Theses, Dissertations, and Problem Reports (ETD)

Studies in protein ligand binding are a significant focus in the field of medicinal chemistry

and biochemistry, facilitating a greater understanding of the structure-function relationship

of the protein and controlling function via drug development. In this research, we identify

new binding sites for lipids on the microbial membrane protein, proteorhodopsin, and apply

machine learning approaches to accelerate the generation of binding affinity-like data for the

use in the identification of potential small molecule drugs. The platelet activating factor

receptor. Cardiolipin, a lipid in membranes, and proteorhodopsin, a microbial proton pump,

are both commonly found in microbial membranes, but little is …

Three Essays On Sustainability Economics, Hélène Flore Nguemgaing

Graduate Theses, Dissertations, and Problem Reports (ETD)

As global economies face increasing resource dependencies and supply chain challenges, it becomes essential to understand the vulnerabilities that threaten economic stability. This dissertation investigates three empirical issues in agribusiness and critical minerals using econometric models to estimate the following: 1) the impact of supply chain disruptions on stock market returns during COVID-19; 2) the extraction of rare earth elements from acid mine drainage treatment by investigating the impacts of ownership and legislation in West Virginia and Pennsylvania; 3) China-to�FOBb (Free-on-Board) price transmission in rare earth elements markets: a copula-based dynamic tail dependence analysis.

The first essay evaluates how events …

Mathematical Contributions To The Study Of Chemotaxis And Cell Signaling, Hajr Zam

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation presents results from two mathematical projects concerned with the biology of cells. Chapter 1 provides biological background and places the two mathematical problems in the context of cell signaling. The larger project, with Prof. H. Hattori on a chemotaxis model is presented in Chapters 3 and 4. Work with Prof. \'{A}. Hal\'{a}sz on a chemical reaction network system with linear multimers and two types of labels is presented in Chapter 2. The chemotaxis system describes the one-dimensional dynamics of a species of cells with two chemical species, a chemo-attractant and chemo-repellent. The goal is to analyze the behavior …

Late Ordovician Evolution Of Sea Scorpions: Eurypterids Of The Big Hill Lagerstätte, Joseph Donaldson Bingham Jr.

Graduate Theses, Dissertations, and Problem Reports (ETD)

Eurypterids are a group of diverse chelicerates that first appeared during the Middle Ordovician (467.3 Ma) and went extinct at the end of the Permian (251.9 Ma). The fossil record of eurypterids during the Ordovician is relatively sparce, comprising only 12 species representing the Megalograptidae, a ‘waeringopterid’ clade, Rhenopteridae, Onychopterellidae, Adelophthalmoidea, and Eurypteroidea clades. This study describes early eurypterids from the Katian aged (~452 Ma) Big Hill Lagerstätte of Michigan. The described material represents two new species, herein named Machipterus margaritae sp. nov. (based on 21 specimens preserving the ventral prosoma and prosomal appendages, and opisthosoma) and Dikranopterus lysinae sp. …

The Effect Of Facial Phenotypes On Differential Performance Of Facial Recognition, Evan R. Garrett

Graduate Theses, Dissertations, and Problem Reports (ETD)

Facial recognition technology is utilized in many facets of life. As the use has become more widespread these systems have improved in reliability and performance approaching the level of human accuracy. With these improvements the problem of bias still remains as a persistent problem. Efforts have been made to minimize the bias prevalent in the systems via studies into various demographic factors, creating training datasets that have a more uniform distribution of subjects, and other methods. As facial recognition is one of the most utilized forms of biometric recognition it is vital to analyze potential causes of bias to help …

Developing Consensus-Based Methods For The Examination And Interpretation Of Contemporary Vehicle, Architectural, And Portable Electronic Device Glasses By Micro-X-Ray Fluorescence Spectrometry, Zachary Bailey Andrews

Graduate Theses, Dissertations, and Problem Reports (ETD)

Glass is a trace material that is commonly encountered during investigations of violent crimes. When glass is recovered at crime scenes, it can be used to establish links between suspects, victims, and the scene itself. The most discriminatory form of analysis for glass evidence is elemental analysis, and micro-X-ray fluorescence spectrometry (µXRF) is becoming an increasingly common technique used for this purpose. Recent advances in µXRF technology, such as the introduction of silicon drift detectors (SDD) and improved polycapillary optics are promising in enhancing the capabilities for the examination of glass evidence in forensic investigations. However, along with these advances …

A Wall Of Smoke: Understanding The Drivers Of The June 2023 Canadian Wildfire Smoke Event For New York City, Gregory S. Randazzo

Dissertations and Theses

The 2023 Canadian wildfire season was notable for its extent and the dense smoke it produced. Motivated by the resulting air quality impacts in the New York City region, we explore how the total particulate matter output from the Quebec fires influenced PM2.5 concentrations downstream in New York City. Using injection height data from the Regional Advanced Baseline Imager + VIIRS Emissions dataset, we relate the tropospheric injection heights of the fires with the broader synoptic context and surface PM2.5 concentrations. Using data from the NYS Mesonet Profiler Network, radiosondes, and ERA5 reanalysis, we document the connection between an anomalous …

Using Trace Gas Measurements As A Transport Diagnostic For Tropical Convection: A Combined Model And Observation Study, Albane Hoxha

Dissertations and Theses

No abstract provided.

Explorations Of Dna-Single-Walled Carbon Nanotube Interactions To Develop Multiplexed Molecularly Specific Biosensors For Inflammation, Amelia K. Ryan

Dissertations and Theses

Inflammatory cytokines such as interleukin-6 (IL-6) and interleukin-12 (IL-12) are central regulators of immune signaling and key biomarkers of disease, yet existing assays for their detection remain slow, invasive, and lack multiplexing ability. This dissertation advances the development of single-walled carbon nanotube (SWCNT) optical nanosensors capable of real-time, multiplexed, and molecularly specific cytokine detection through innovative use of single-stranded DNA (ssDNA) interfaces.

First, an IL-6-specific DNA aptamer was employed as both a dispersing agent and recognition probe for SWCNT fluorescence sensing. Sequence modifications, including anchor domains, truncations, and thermally induced refolding, were systematically tested to optimize sensitivity and selectivity. The …

Development Of An Quadcopter Unmanned Aerial Vehicle For Atmospheric Remote Sensing, Omar J. Addasi

Dissertations and Theses

This paper explores the development of a quadcopter unmanned aerial vehicle (UAV, a.k.a. drone) for atmospheric remote sensing of temperature, pressure, humidity, and PM2.5 particulate matter quantities. A 3-D printed drone body is designed and flight tuning is performed. An optimal length for an upward extending mast for the drone body is determined. Low cost, lightweight sensors are compared against higher precision sensors in both static and dynamic conditions. In addition, an initial investigation into the design of a pressure sensor based anemometer is performed.

Classification Of Variable Stars Using Convolutional Neural Network, Abhina Premachandran Bindu

Dissertations and Theses

This research focuses on developing Convolutional Neural Networks (CNNs), for the process of classifying and identifying variable stars through the analysis of unprocessed light curves from Transiting Exoplanet Survey Satellite (TESS). As astronomical data is becoming increasingly complex, and as advanced missions deploy sophisticated instruments for data collection, both the quality and quantity of the data are improving at a rapid pace. This has created an urgent need to automate the analysis process using efficient and effective methods, such as those based on machine learning. While previous research has explored machine learning approaches, there has been limited focus on implementing …

Metasurfaces And Their Applications In Photonic Devices, Shuwei Guo

Dissertations and Theses

Metasurfaces are flat artificial optical elements composed of dielectric and/or metallic nanostructures. They can manipulate light in unprecedented ways by altering amplitude, phase, and polarization at subwavelength scales. The ability of these two-dimensional elements to perform multiple optical functions within compact optical systems—while offering high functionality, small form factors, and easy integration into optoelectronic devices—has sparked significant interest across various fields and industries. These applications span imaging, sensing, nonlinear and quantum optics, optical computing, automotive technology, augmented and virtual reality, and more.

In this dissertation, we explore and design new multifunctional metasurfaces with a focus on manipulating spectral responses. First, …

Using Deep Neural Nets In Writer Identification & Analysis, Aditya Majithia

Dissertations and Theses

This thesis focuses on developing automated deep learning methods for writer identification and writer attribute prediction from handwriting. It introduces two novel architectures: Convolutional Transformer Encoder (CTE) and Convolutional Swin Encoder (CSE). CTE is designed for determining authorship from handwritten text, be it modern or historical handwriting. CTE tracks subtle features and cues from handwriting strokes to distinguish authorship. It is the first of its kind capable to operate on historical handwritten fragments, setting it apart from existing methods that rely on entire document pages. CSE is designed to determine multiple attributes of an author such as authorship, gender, age …

Utilizing Deep Learning Audio Models For Blind And Low Vision Crosswalk Assistance, Wayne Lam

Dissertations and Theses

Navigating urban environments poses significant challenges for blind and low vision (BLV) individuals, particularly at street intersections where determining when it is safe to cross can be life-threatening. In New York City, where pedestrian fatalities are on the rise and only 2% of intersections are equipped with Accessible Pedestrian Signals (APS), alternative solutions are urgently needed. This thesis proposes an audio-based deep learning approach to support BLV individuals at crosswalks by detecting traffic movement direction and idling states using spatial sound. With 4-channel audio capturing capabilities of wearables, such as Meta Project Aria glasses, we explore state-of-the-art sound event localization …

Fault And Cyberattack Diagnosis And Handling Via Large Language Models And State Prediction For Manufacturing And Quantum Systems, Jihan Abou Halloun

Wayne State University Dissertations

In the digitalization era and Smart Manufacturing, companies are harnessing the power of artificial intelligence (AI) and machine learning (ML) across multiple sectors, including process engineering optimization, process control and fault detection, to enhance efficiency and engineering decision making. Although AI and ML are widely used in anomaly detection and handling, there are still areas where it has been less explored. One of the major areas where AI’s potential in manufacturing needs to be characterized is with respect to the applications of large language models (LLMs) in manufacturing troubleshooting for fault/attack handling. A second major area where the potential of …

How Do Selected Biomedical And Health Sciences Journals React To Submissions Of Artificial Intelligence (Ai) Assisted Manuscripts?, Misa Mi, Lin Wu, Yingting Zhang, Wendy Wu

Library Scholarly Publications

Background and Objectives: Generative artificial intelligence (GenAI) increasingly impacts research and scholarly communication. Given the evolving application of ChatGPT and other AI tools in scholarly communications, health sciences librarians must become cognizant of any existing journal publishing guidelines for AI-created or assisted manuscripts. The study aims to examine how scholarly biomedical and health sciences journals and publishers respond to submissions of these manuscripts and what requirements or policies have been put in place to guide and instruct authors on AI use.

Methods: We first retrieved and consolidated a list of journals representing disciplines in biomedical and health sciences from four …

Maritime Digitalization And Decarbonization: A Sustainable Future, World Maritime University, Korea Research Institute Of Ships And Ocean Engineering, Korea Maritime Institute

Books

The book with the title “Maritime Digitalization and Decarbonization: A Sustainable Future” is the second major outcome following the publication of the Proceedings of WMU Maritime Week (WMW) 2024.

The purpose of WMU Maritime Week 2024 (WMW) was to convene experts from diverse sectors to discuss contemporary maritime issues, generate practical and academic insights, and contribute to the advancement of the international maritime community. Following the success of WMW 2024, the aim is to deliver a top-notch annual conference in the maritime field, producing practical and academic outputs through in-depth discussions of critical contemporary issues in the maritime field. …

Multi-Attribute Characterization Of Polymeric And Lipid-Based Drug Delivery Systems By Column Switching Liquid Chromatography-Mass Spectrometry, Brady W. Drennan

Chemistry & Biochemistry Dissertations - Archive

Drug delivery systems (DDS) are an increasingly relevant technology, owing to their ability to provide controlled release and to enable the use of otherwise toxic or labile therapeutics. However, these modalities are complex, containing a multitude of species with diverse chemical and physical properties. Their characterization, which involves the assessment of critical quality attributes (CQAs), requires numerous analytical techniques. The high-throughput demands of the biopharmaceutical industry have driven the need to consolidate these characterizations into a single analytical method. Consequently, novel analytical technologies are needed to support multi-attribute characterization. A multimodal liquid chromatography–mass spectrometry (LC–MS) system was developed to facilitate …

Structure–Property Relationships Mediated By Lone Pairs And Vacancies In Oxychalcogenides: A Combined Experimental And Theoretical Study, Hoa Hn Nguyen

Chemistry & Biochemistry Dissertations - Archive

Structure–property relationships in some oxychalcogenide materials are strongly governed by the interplay between stereochemically active lone pairs and anion vacancy formation. Through a combination of density functional theory (DFT), synchrotron and neutron total scattering and optical characterization, this work elucidates how local symmetry breaking, chemical substitution, and vacancy dynamics influence electronic and optical behavior across several lone pair-containing systems. In crystalline TeO₂, all three polymorphs exhibit wide band gaps with Te⁴⁺ 5s² lone pairs contributing significantly near the valence band edge. Oxygen vacancy formation is thermodynamically favorable and induces asymmetric charge redistribution and enhanced polarizability, supporting …

Tallgrass Prairie Center 2024-2025 Highlights, University Of Northern Iowa. Tallgrass Prairie Center.

Annual Reports

Contents:

--- Staff
--- From our Director
--- Iowa Roadside Management: Enhancing our public roadsides
--- Research and Restoration: Native seeds and methods for prairie reconstruction
--- Plant Materials: A prairie pedigree for Iowa’s roadsides and beyond
--- Irvine Prairie: Restoring a piece of the original Iowa landscape
--- Prairie on Farms: Making prairie practical
--- Prairie Roots Project: A deeper appreciation of the prairie ecosystem
--- Green Iowa AmeriCorps: Service members expand TPC capacity
--- A Hidden Gem - UNI's Biological Preserves: A legacy of service and partnership
--- UNI Students at the TPC: Practical experience in support of …

Orientable Quadrilateral Embeddings Of Cartesian Products Of Graphs, Matthew Farnsworth, Max Goskie, Adrian Volpe, Jackson Sayre

SPARK Symposium Presentations

In the spirit of Pisanski (1989) we consider orientable quadrilateral embeddings of Cartesian products of cycles on surfaces. We offer a constructive example of such an embedding of three low-order cycles. Then we show more generally that such embeddings exist for the product of a 2-cycle, and even cycle, and an arbitrary third cycle. We represent our graphs using rotation schemes to show this existence. Use of rotation schemes led to the ultimate characterization of our findings visually, providing conjectures for generalizations of products of three cycles.

Σ-Ary, Minnesota State University Moorhead, Mathematics Department

Math Department Newsletters

No abstract provided.

Topographic Forcing Of Submesoscale Instability In The Antarctic Circumpolar Current, Laur Ferris, Donglai Gong, John Klinck

CCPO Publications

Subpolar frontal zones are characterized by energetic storms, intense seasonal cycles, and close connectivity with surrounding continental shelf topography. At the same time, predicting the ocean state depends on appropriate partition of resolved and parameterized dynamics, the latter of which requires understanding the dynamical processes generating diffusivity throughout the water column. While submesoscale frontal instabilities are shown to produce turbulent kinetic energy (TKE) and mixing in the surface boundary layer (SBL) of the global ocean, their development in complex dynamical regimes (e.g., elevated preexisting turbulence, large ageostrophic shear, or in proximity to topographic boundaries) is less understood. This study investigates …

Estimating Pedestrian Crossing Times At Scramble Crossings Via Machine Learning And Agent-Based Modeling, Sho Takami

CURE Proceedings

Scramble crosswalks differ from conventional crosswalks in their ability for pedestrians to cross diagonally. This research compares the average crossing times and investigates the walking behaviors that pedestrians adopt to produce the speediest times in the two crosswalk configurations. Identification of the most efficient set of walking behaviors is done through an agent-based model, whereas producing polynomials relating crossing times to the most prominent walking behaviors is done through regression algorithms in machine learning. With the combination of these two approaches, it is revealed that pedestrians must adopt a relaxed walking style to make each crosswalk configuration efficient. Additionally, between …

Spectral Theory And The Gelfand Transform, Brenden Schlader

All Graduate Theses, Dissertations, and Other Capstone Projects

The overall goal of this thesis is to study spectral and Gelfand theory as it relates to unital Banach and C∗-algebras. In the first part, we develop the necessary algebraic, analytic, and topological background relevant to the content of this work. We also discuss concrete examples of algebras frequently used in the subsequent sections. In the second part of this thesis, we develop spectral theory by first defining the spectrum of an algebra through the characterization of the invertible and noninvertible elements. In particular, we establish properties of the commutative unital Banach algebra ℓ1(Z). We also establish fundamental results such …

Integrating Sentiment Analysis In Predictive Models: A Comparative Study On Game Popularity On Steam, Khaleefa Alhemeiri

CMC Senior Theses

Over the past decades, the gaming industry has managed to evolve into a multi-billion-dollar enterprise. Gaming platforms such as Steam foster unprecedented amounts of engagement among players worldwide daily. In this thesis, we investigate the effect of incorporating sentiment-driven metrics, specifically YouTube view counts and positive reviews, into predictive models for game popularity. In addition, by comparing our linear regression sentiment-based approach to the Bayesian hierarchical folded normal model used by De Luisa et al. (2021), we can understand the many differences, strengths, and limitations of each methodology. In our thesis, we focus on three games. Each is of varying …

Forecasting Equity Betas Using Option-Implied Moments, Ivan Kolesnikov

CMC Senior Theses

Traditional beta estimates are constructed from historical stock‑and‑market returns and therefore adjust only as fast as realized data accrue. This thesis investigates whether the forward‑looking information embedded in equity‑option prices can enhance beta forecasts. Using near‑end‑of‑day quotes for 236 S&P 500 firms between 2007 and 2024, I extract risk‑neutral variance and skewness, construct five alternative beta estimators (historical, option‑implied, and three hybrids), and evaluate them against realized betas over six‑, twelve‑, and twenty‑four‑month windows. Rolling‑OLS beta remains the most accurate benchmark at short horizons, yet option‑implied moments add economically and statistically significant value when systematic exposure is expected to change …

Cmc Thesis Chatbot, Luis Gomez

CMC Senior Theses

This GitHub repo is a senior thesis for Claremont McKenna College; it is a thesis about theses. The project is an interactive RAG-based chatbot that helps students, researchers, and faculty explore Claremont McKenna College senior theses. The goal was to create a domain-specific chatbot to show that it is possible to combat the limitations of AI, including hallucinations, outdated data, and lack of domain expertise. The website link is:

CMCThesisChatbot

Analyzing Political Sentiment On Micro-Blogging Data: A Lexicon And Machine Learning Approach To The 2024 U.S. Presidential Election, Ava Grey

CMC Senior Theses

This paper explores the trends in sentiment towards U.S. presidential candidates Kamala Harris and Donald Trump through micro-blogging social media text during the five months leading up to the election. Two datasets of varying sizes and origins were used to contextualize and validate analysis findings. The analyses include both a lexicon-based approach and a machine learning predictive method. Common sentiment analysis techniques like term frequency, term frequency inverse, various lexicons, and n-grams were utilized during the lexicon approach. During the modeling, a random forest was utilized in addition to the methods used during the lexicon approach. Results showed that overall …

Neural Correlates Of Attentional Biases In Dietary Choice: Role Of Childhood Socioeconomic Status, Justine Jamie N. Gotico

CMC Senior Theses

Childhood poverty has been shown to increase adult risk for obesity above and beyond its direct effects on adult socioeconomic status (SES). One proposed mechanism of these effects is by shifting behavioral patterns of dietary consumption and choice, for example by increasing rapid attention to high-calorie unhealthy foods. Yet, whether such neural mechanisms can explain observed differences in dietary behavior based on childhood SES remains an open question. Here we used event-related potentials (ERPs) to examine early attentional correlates of low childhood SES during a dietary choice task, based on research suggesting that early attentional biases toward high-calorie foods emerge …