Digital Commons Network^™

The Nature Of Students' Justifications In Geometry: The Impact Of Using Dynamic Geometry Software, Anek Janjaroon

Doctoral Dissertations

Mathematical justification is a process that reflects how students demonstrate and accept the truth of mathematical statements. The purpose of this study was to investigate the nature of students’ justifications when allowed to use dynamic geometry software in the justification process. The justifications of 18 preservice teachers in response to two geometric conjectures were analyzed to identify characteristics of justifications based on Harel and Sowder’s (1998) framework of proof schemes. The results inform us of the impact of the dynamic software in students’ justifications and the overall nature of students’ work when they use the software to learn geometric ideas. …

Global Imaging Of The Magnetoshpere: An In-Depth Analysis Of The Magnetosphere-Ionosphere Coupling, Mayowa Adewuyi

Doctoral Dissertations

Magnetosphere – Ionosphere (MI) coupling plays an important role in Earth’s overall space environment. MI coupling influences ion dynamics in the plasma sheet, the evolution of ring current ions, and field aligned currents during storm time events. The coupling of these two regions makes it important to understand both as a whole, rather than individually. Understanding the importance of the magnetosphere-Ionospheric system and how the coupling affects earth’s space environment is made difficult due to the reliance on localized in-situ measurements and the spacecraft being at the right location at the right time.

The Two Wide-Angle Imaging Neutral-Atom Spectrometers (TWINS), …

A Physics-Based Material Model Incorporating Strain Gradient Plasticity Formulations In A Mean-Field Framework To Predict Spatial Fluctuation Of Material Properties, Zhangxi Feng

Doctoral Dissertations

With the market expansions and increasing number of scientific explorations, the demands for manufacturing metallic parts to satisfy specific requirements continue to increase. A slight improvement in the manufacturing process can result in great cost savings in time and energy. The research and development time to identify these areas of improvements can be greatly reduced using numerical models. One such model is the mean-field elastoplastic self-consistent (EPSC) framework studied extensively and advanced in this dissertation. In the past two decades, many material behavior formulations were implemented in EPSC, and the model has shown versatility and accuracy in predicting a wide …

“Why You Understand The Why”: A Qualitative Characterization Of The Metacognitive Competence Of Introductory Stem Peer Coaches, Jonathan Kustina

Doctoral Dissertations

The processes of metacognition are vital for students’ development of critical thinking skills and productive learning mindsets, yet many students never receive the direct instruction that would allow them to formally develop their metacognition. As instructors are typically not providing this instruction, there may be an alternate source to facilitate the learning of metacognition to students. This research study will investigate the viability of having peer coaches, undergraduate peer educators who help facilitate learning and problem solving in introductory STEM courses, facilitate metacognition to their students. Specifically, this research study aims to understand and characterize the metacognitive competence of the …

Navigating The Complexities Of Time: Innovative Approaches For Accurate And Resilient Time Series Modeling, Sepideh Koohfar

Doctoral Dissertations

The application of time series data has a rich history, and its relevance continues to expand due to recent advancements in artificial intelligence (AI) and autonomous systems. These technological developments have driven the collection and utilization of time series data to new heights, propelling its significance to unparalleled levels. Deriving insights from time series data has become indispensable for effective decision-making in various domains, as it enables the identification of patterns, trends, and fluctuations that inform strategic actions and optimize outcomes. The core challenge lies in developing precise and reliable predictive models that effectively leverage the input data for accurate …

Artificial Intelligence Driven Magnetic Materials Discovery: From Data Extraction To Property Prediction, Yibo Zhang

Doctoral Dissertations

This dissertation presents an integrated artificial intelligence framework aimed at accelerating magnetic materials discovery by addressing key challenges in materials science: improving experimental characterization techniques, efficiently extracting structured data from scientific literature, developing comprehensive materials databases, and creating reliable predictive models.

We first develop a UNet-enhanced vector field electron tomography (VFET) approach for three-dimensional magnetic structure reconstruction. This method addresses the missing wedge problem in experimental data collection while maintaining computational efficiency, providing reliable experimental data crucial for materials research.

We introduce GPTArticleExtractor, a novel workflow leveraging large language models to automatically extract key information from scientific literature. Applied to …

Improving Understanding Of Fluvial Reach-Scale Solute Transport And Uptake Using A Particle Tracking Model And Random Forest Machine Learning Model, Jiaying Liu

Doctoral Dissertations

In addition to transporting flowing water, river systems carry dissolved nutrients and pollutants, which can experience chemical reactions, biological uptake, or retention in surface or hyporheic zones. This dissertation enhances our understanding of solute transport and uptake in river reaches through three main components. The first component involves the development of a novel curve-fitting model designed to capture the characteristics of pulse-release breakthrough curves (BTCs) from tracer studies with conservative solutes. The model, which was found to be applicable to a wide range of field studies, enables the rapid comparison of transport parameters among diverse field studies obtained under a …

Deformation-Induced Bonding Of Glassy Polymeric Films And The Diluent Effect, Ajay Vallabh

Doctoral Dissertations

Bonding between two polymer films can be achieved through various heat- or chemical-based methods. Recently, our group has discovered the novel phenomenon of deformation-induced bonding (DIB) for solid-state glassy polymers in time on the scale of a fraction of a second at ambient temperatures substantially below the bulk glass transition temperatures (T_g). DIB is achieved by bulk plastic compression, which triggers the molecular mobility of polymer chains to cause interpenetration across the interface even in a glassy regime.

First, we performed a series of experiments to evaluate solid-state, deformation-induced bonding in organic polymer blends composed of films of hydroxypropyl methylcellulose …

Simulations, Modeling And Data Analysis Of Parity Violating Electron Scattering Experiments, Yufan Chen

Doctoral Dissertations

In the Standard Model (SM) of nuclear and particle physics, parity violation is incorporated through the representation of the weak interaction as a chiral gauge interaction. Only the left-handed components of particles and right-handed components of antiparticles participate in weak interactions in the Standard Model. This implies that parity is asymmetric for the weak interaction. Parity violating electron scattering (PVES) experiments are designed to probe the physics parameters related to the SM, with the possibility to discover physics beyond the SM (BSM) by measuring the parity violating asymmetry 𝐴𝑃𝑉 of longitudinally polarized electrons scattered off unpolarized targets with high precision. …

Measurement Of Multi-Jet Ratios In The Atlas Experiment, Zahra Farazpay

Doctoral Dissertations

This dissertation presents a comprehensive study of multi-jet cross-section ratios using proton-proton collision data collected by the ATLAS detector during Run 2 of the Large Hadron Collider (LHC) at a center-of-mass energy of √ s = 13TeV. By examining these ratios across different energy scales, the analysis provides valuable insights into the running of the strong coupling constant, αs, a fundamental parameter in Quantum Chromodynamics (QCD) that dictates the strength of the strong interaction. The running of αs—its variation with energy—is crucial for understanding QCD, yet it remains one of the least precisely known aspects of the theory. In this …

Computational Design Of Complex Concentrated Alloys, Hamid Sharifi

Doctoral Dissertations

A high-throughput parameterization of modified embedded atom model (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn was carried out using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics. Utilizing the MEAM interatomic potentials and a Monte Carlo scheme, phase segregation in the CrNiCo, CuNiCr and CuNiCo fcc alloys …

Reducible Operators, Irreducible Operators, And Generators In Von Neumann Algebras, Sukitha Adappa

Doctoral Dissertations

Let $\mathcal{H}$ be a complex Hilbert space, and let $\mathcal{B(H)}$ be the set of all bounded linear operators on $\mathcal{H}$. An operator $T\in\mathcal{B(H)}$ is said to be reducible if there exists a nontrivial projection that commutes with $T$. Otherwise, it is said to be an irreducible operator in $\mathcal{B(H)}$. Halmos showed that the set of irreducible operators is an operator norm-dense subset in $\mathcal{B(H)}$ and raised the question of whether the set of reducible operators is an operator norm-dense subset in $\mathcal{B(H)}$. In this dissertation, we extend the notion of reducible and irreducible operators in the von Neumann algebra setting …

Neural Retrieval Through Entities And Text Understanding, Pooja Himanshu Oza

Doctoral Dissertations

For various artificial intelligence systems, automatic text understanding algorithms that go beyond mere pattern recognition are helpful. For instance, understanding web pages is beneficial for Information Retrieval (IR) systems to retrieve relevant information. In the most common form, IR systems retrieve relevant information as entities or documents in response to keywords-based queries. Traditional IR models use lexical matching between the query terms and document terms to identify relevant documents. With the emergence of neural networks, Neural IR approaches utilize deep learning techniques to learn high-dimensional representations of documents and queries that go beyond term matching.

On the other hand, with …

Algebraically Doubly Stochastic Matrices Over Principal Ideal Domains, Eric Davis

Doctoral Dissertations

A doubly stochastic matrix over the real numbers is a matrix $A=[a_{ij}]$ such that $0\leq a_{ij}\leq1$ for all $i,j$ and all rows and columns sum to 1. The classical Birkhoff-von Neumann theorem states that every doubly stochastic matrix over $\R$ can be expressed as an affine combination of permutation matrices, matrices with a single 1 in each row and column and 0's elsewhere. Over a general commutative ring with identity $R$ we drop the condition that $0\leq a_{ij}\leq1$ and consider matrices with only the row and column sum condition; we refer to such matrices as \textit{algebraically doubly stochastic} and denote …

Evaluation Of Rockfall Trajectories Using Smart Rocks And Measurement While Drilling, Bruma Morganna Mendonca De Souza

Doctoral Dissertations

This doctoral research investigates rockfall movement under laboratory and field-controlled conditions as well as in situ natural field environments in an effort to better understand the movement described by falling blocks. Although previously published research identified several factors that affect rockfall movement (block characteristics, ground characteristics, and impact kinematics), the lack of a standardized methodology to evaluate rockfall behavior upon impact on different ground materials increases the difficulty of establishing realistic parameters in modeling approaches and ultimately in selecting representative model input parameters. In order to measure rockfall movement under different test conditions, concrete fabricated test blocks ranging in mass …

Innovative Approaches To Dna-Based Materials: Development Of Bottlebrush Polymers, Supramolecular Hydrogels, And Psoralen-Enhanced 3d Printing Of Dna Bioinks, Nicholas Pierini

Doctoral Dissertations

This thesis explores innovative approaches to enhancing the functionality and applications of DNA-based materials through the development of DNA bottlebrush polymers (BBPs), DNA-intercalating supramolecular hydrogels (DISHs), and psoralen-based 3D printing techniques. The first chapter presents the synthesis and characterization of linear and cyclic DNA BBPs using a grafting-to approach. Plasmid DNA (pDNA) is used as the polymeric backbone, grafted with polyethylene glycol (PEG) side chains of varying molecular weights (750 Da, 2000 Da, and 5000 Da) to improve stability and functionality. Achieving high graft densities, up to 24% for mPEG750-CEA, and purifying the PEG-DNA conjugates were significant challenges addressed through …

Women Strength: Using Photovoice To Explore Female Chinese International Students’ Experiences, Yue Cai

Doctoral Dissertations

Female Chinese international students face discrimination and stereotypes in Western academia based on race and gender, yet they possess unique “Women Strength” characterized by agency, resilience, and self-advocacy. This study explores how these students navigate cultural differences and develop their strengths while studying in the U.S. Drawing upon “Women Strength” as a theoretical framework, including Community Cultural Wealth, Critical Feminist Theory- Chinese feminism, decolonial feminism, and transnational feminism, transformative agency, resilience theory, and self-advocacy theory, this research employs a qualitative approach, including Photovoice and autoethnography. Three research questions guide the study: 1) What cultural differences do female Chinese international students …

Trauma-Informed Teaching With Adult English Language Learners: A Study In A Community-Based Organization, Elizabeth Eastman

Doctoral Dissertations

Often, immigrants in the United States have suffered traumatic experiences in their home country, on their journey to the U.S., and/or in their process of acculturation. In English for Speakers of Other Languages (ESOL) classes, symptoms of trauma can interfere with learning and acculturation. Trauma-Informed teaching can meet the needs of students who have been impacted by trauma but it is not often used in ESOL classes. This is due to a lack of teacher training, and a gap in the literature on the effects of the approach and studies that explore the perspectives of the students. Based in phenomenology …

Impact Of Student Beliefs And Self-Efficacy On Performance In Higher Education Stem Courses, Lauren Nicole Fogg

Doctoral Dissertations

In engineering education, students often face feelings of inadequacy, leading to academic struggles and potential dropout. This dissertation investigates the impact of interactive course materials on students' confidence and self-efficacy in problem-solving, focusing on an Engineering Materials class at Louisiana Tech University. Over four quarters, involving seven sections and 218 students, a 13-question Likert scale survey was administered repeatedly, alongside demographic data and textbook usage surveys. The study aims to compare students’ attitudes and beliefs when not using a textbook versus when using an interactive web-native book. Hypotheses suggest that the interactive book will enhance problem-solving beliefs, confidence, and grades. …

Voiculescu's Theorem In Properly Infinite Factors, Minghui Ma

Doctoral Dissertations

This dissertation investigates Voiculescu’s theorem on approximate equivalence in separable properly infinite factors. We establish the norm-denseness of the set of all reducible operators and prove Voiculescu’s bicommutant theorem. Additionally, we extend these results to the multiplier algebras within separable type III factors.

Binary Neutron Star Mergers: Magnetohydrodynamics And Neutrino Physics Of General Relativistic Simulations Of Binary Neutron Star Mergers, Alexander Lee Knight

Doctoral Dissertations

Binary neutron star mergers are some of the most extreme events to happen in our universe. From observations of these mergers, we can obtain information about the properties of matter at densities much larger than those accessible within the solar system, as well on the origin of heavy elements. Studying these events poses challenges, so we use simulations to model the merger. State-of-the-art methods and models still have to make assumptions or simplifications, so new methods improving either the accuracy of the simulations, or reducing the computational cost are desired. My research contains three projects, aiming to improve simulations by …

Aspects Of Mirror Symmetry For Non-Fano Toric Varieties, Michael John Samuel Lathwood

Doctoral Dissertations

Correlation functions in the topological A-model can be computed with open Gromov-Witten invariants whereas the mirror topological B-model admits a simpler description in terms of period integrals. We first review preliminary material in Chapter 1. Then in Chapter 2 we use tropical geometry to construct the Duistermaat-Heckman measure for non-Fano toric varieties. This allows one to compute the asymptotic terms of period integrals. In Chapter 3 we solve the generalized Picard-Fuchs system for the Hirzebruch surfaces, and hence compute periods to all orders of the mirror complex structure moduli. Near the large complex structure limit point, we use toric degenerations, …

Mathematical Explorations Into The Inner Workings Of Neural Networks, Xiang Li

Doctoral Dissertations

Neural network applications are everywhere in our lives today. We can now design and train large neural networks with billions of parameters for a multitude of complex tasks. However, it is still extremely challenging for us to explain the theoretical underpinnings that have led to the successful use of neural networks for a wide range of applications. This dissertation focuses on the mathematical foundations of neural networks.

In Chapter 2, we investigate the error function of fully connected neural networks with the rectifier linear unit (ReLU) activation functions. We prove that for any linear neural network with a single hidden …

On Entropic Van Der Corput’S Difference Theorem, Weichen Gu

Doctoral Dissertations

We prove an entropic version of van der Corput’s difference theorem: the entropy of a sequence is equal to the entropy of its differences. This reveals a correspondence between the theory of uniform distribution mod 1 and entropy. As applications, we establish several entropic versions of other uniform distribution theorems.

Streamer Dynamics In Thunderstorm And Near-Ionospheric Environments, Jacob Koile

Doctoral Dissertations

Streamers are self-consistent ionization waves that are generated within an electric field. Since they were first proposed in the theory of spark breakdown developed in the 1930s by Raether, Loeb, and Meek [Raether, 1939; Loeb and Meek, 1940], they have demanded the attention of scientists across many different fields. They are crucial to the Earth environment because of their natural occurrence in the form of sprites, at near-ionosphere altitudes above a thunderstorm, and their proposed roles in the formation and propagation of lightning. % that can occur above a thunderstorm, or However, they also play a role in the human …

Asymptotic Spectral Analysis Of A Coupled Bending-Torsion Beam Energy Harvester, Chris Vales

Doctoral Dissertations

A piezoelectric energy harvester is a device that utilizes the properties of piezoelectric materials to convert mechanical strain energy into electric energy. The present work is concerned with the asymptotic spectral analysis of a piezoelectric harvester extracting energy from the mechanical vibration of a coupled bending-torsion beam. After placing the model in the appropriate operator setting, we prove that the addition of piezoelectric energy harvesting constitutes a weak perturbation of the underlying beam dynamics, in the sense that the model’s piezoelectric parameters do not appear in the first two orders of magnitude of the asymptotic approximation of the governing operator’s …

On The Kernel Elements Of Unimodular Vectors, Thomas Nocera

Doctoral Dissertations

For a commutative ring $R$ with identity, the set of unimodular vectors $Um_n(R)$ contains all column vectors $\alpha\in R^n$ so that $\alpha^T\beta=1$ for some $\beta\in R^n$. The set of completable vectors $Umc_n(R)$ is the set of unimodular vectors in $R^n$ that appear as the first column of an invertible matrix in $GL_n(R)$. Determining the conditions in which unimodular vectors are completable is fundamental to problems in algebraic geometry and module theory. In this work, we generalize the usual dimension $3$, real vector cross product to commutative rings and characterize all completable vectors in $Umc_3(R)$ in terms of the cross product. …

The Effectiveness Of Mind Maps As An Instructional Approach For Developing Critical-Thinking Skills And Dispositions: A Meta-Analysis, Carmen De Jesus

Doctoral Dissertations

Mind mapping is the most flexible visual learning and active instructional approach. It has many applications, such as brainstorming, taking notes, memorizing, and conceptualizing complex topics using associations between images and keywords, colors, and visuospatial characteristics. Students can elaborate mind maps individually and collaboratively, digitally or nondigitally. Teachers can also elaborate mind maps for studying purposes. This meta-analysis aims to investigate the effectiveness of mind mapping as an instructional approach for developing critical-thinking skills and dispositions. With 22 studies (20 of which are international) and 1,535 participants, all employing a quasi- experimental study design, this meta-analysis is a comprehensive exploration. …

Exploring The Experiences Of Chinese Heritage Language Learners In California Public High Schools: A Mixed Methods Study, Min Chuan Jasmine Wang

Doctoral Dissertations

The purpose of this study was to comprehend the motivations and learning experiences of Chinese Heritage Language Learners (CHLLs) who study in Chinese programs in California public high schools where Chinese American students are under-studied and their voices are not heard. The study used Gardner’s Socio-educational Model, Fishman’s Reversing Language Shift (RLS), and Asian Critical Theory (AsianCrit) as the theoretical frameworks for the investigation. The methodology of this study applied the mixed-methods sequential explanatory design, starting with an online survey data collection and following up with interviews with CHLLs and language teachers. The researcher then conducted classroom observations to support …

Development Of An Integrated Workflow For Nucleosome Modeling And Simulations, Ran Sun

Doctoral Dissertations

Nucleosomes are the building blocks of eukaryotic genomes and thus fundamental to to all genetic processes. Any protein or drug that binds DNA must either cooperate or compete with nucleosomes. Given that a nucleosome contains 147 base pairs of DNA, there are approximately 4^147 or 10^88 possible sequences for a single nucleosome. Exhaustive studies are not possible. However, genome wide association studies can identify individual nucleosomes of interest to a specific mechanism, and today's supercomputers enable comparative simulation studies of 10s to 100s of nucleosomes. The goal of this thesis is to develop and present and end-to-end workflow that serves …