Physical Sciences and Mathematics Commons^™

Mending Trust In Ai: Trust Repair Policy Interventions For Large Language Models In Visual Data Journalism, Hangxiao Zhu

McKelvey School of Engineering Theses & Dissertations

Trust in Large Language Models (LLMs) emerged as a pivotal concern. This is because, despite the transformative potential of LLMs in enhancing the interpretability and interactivity of complex datasets, the opacity of these models and instances of inaccuracies or biases have led to a significant trust deficit among end-users. Moreover, there is a tendency for people to personify AI tools that utilize these LLMs, attributing abilities and sensibilities that they do not truly possess. This thesis exploits this personification and proposes a comprehensive framework of trust repair policies tailored to address the challenges inherent in LLM annotations within data journalism …

Characteristics Based Factor Models - Comparison Of Estimation Procedures, Henri Ohl

McKelvey School of Engineering Theses & Dissertations

Understanding cross-sectional and time series variation of asset returns is fundamental in finance, particularly in asset pricing. This thesis explores the integration of factor theory with machine learning to deepen our comprehension of these dynamics. Characteristics based factor models offer a systematic framework for quantifying an asset's underlying risk-return structure, leveraging time-varying conditional information on model parameters carried by firm-specific characteristics. These models serve as valuable tools for discerning the driving components of an asset's expected excess return. Recent research established a novel methodology for consistent parameter estimation within this framework, only requiring a large cross-section but not a long …

Evaluating Neuroimaging Modalities In The A/T/N Framework: Single And Combined Fdg-Pet And T1-Weighted Mri For Alzheimer’S Diagnosis, Peiwang Liu

McKelvey School of Engineering Theses & Dissertations

With the escalating prevalence of dementia, particularly Alzheimer's Disease (AD), the need for early and precise diagnostic techniques is rising. This study delves into the comparative efficacy of Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) and T1-weighted Magnetic Resonance Imaging (MRI) in diagnosing AD, where the integration of multimodal models is becoming a trend. Leveraging data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we employed linear Support Vector Machines (SVM) to assess the diagnostic potential of these modalities, both individually and in combination, within the AD continuum. Our analysis, under the A/T/N framework's 'N' category, reveals that FDG-PET consistently outperforms T1w-MRI across …

Information-Rich 6d Single-Molecule Imaging Design Using Optimization, Tingting Wu

McKelvey School of Engineering Theses & Dissertations

When studying biochemical processes, localizing the targets alone will not paint a complete picture. We also need techniques to probe how biomolecules interact with one another, including how molecules are organized into larger structures, how they are oriented with respect to surrounding molecules, and how local chemical parameters, like pH and hydrophobicity, vary spatially and temporally. My dissertation focuses on single-molecule orientation localization microscopy (SMOLM, Chapter 1). The objective is to develop imaging techniques for measuring how molecules are oriented with respect to their surrounding molecules, namely, 3D orientation. Achieving optimal imaging performance requires careful design of both the forward …

A Review Of Recent Gene Expression-Based And Dna Methylation-Based Mathematical Cell Type Deconvolution Methods, Chenxiao Tian

Arts & Sciences Electronic Theses and Dissertations

In recent years, many cell type deconvolution methods based on DNA methylation data and gene expression data have been developed. Both of these two methods have its special advantages and disadvantages, e.g., DNA methylation-based methods’ data source is usually more stable than gene expression and DNA methylation is easier to measure in FFPE tissues or formalin-fixed paraffin-embedded, while some gene-expression data like scRNA-seq data usually has high cost and complexity. On the other hand, gene expression-based deconvolution methods currently have many more available methods than DNA methylation-based deconvolution methods, which leads to DNA methylation-based methods in many cases can learn …

Non-Adjacent Anti Cyclobutane Pyrimidine Dimers As Intrinsic Probes Of Non-B Form Secondary Structures Of Dna, Natalia Eugenia Gutierrez Bayona

Arts & Sciences Electronic Theses and Dissertations

G-quadruplexes are four-stranded structures of DNA composed of G-quartets that have been proposed to play an extremely important role in replication, transcription, and translation. It has, however, been extremely difficult to unequivocally demonstrate that G-quadruplexes form in living cells due to the lack of probes that would allow for their unambiguous detection and location without disrupting the DNA or the cellular environment. To circumvent these problems, it was proposed that DNA itself could be used as an intrinsic photoprobe for certain classes of G-quadruplex structures and other non-B DNA conformations in vivo. Recently, we discovered that UVB irradiation of human …

An Assistive Interface For Displaying Novice's Code History, Ruiwei Xiao

McKelvey School of Engineering Theses & Dissertations

As Teaching Assistant (TA) programs grow in number and size in introductory CS courses, TAs play a significant role in novice programmers' experience and contribute to their success. However, many TAs are also relative beginners themselves and thus have limited experience in programming and teaching. Thus the effectiveness and consistency of their guidance can vary significantly. To improve interaction quality and assist TAs in providing better support, we examine the difficulties encountered by inexperienced TAs in previous literature and then identify the potential for the high cognitive load as an unaddressed difficulty that may prevent new TAs from initiating effective …

Feature Selection From Clinical Surveys Using Semantic Textual Similarity, Benjamin Warner

McKelvey School of Engineering Theses & Dissertations

Survey data collected from human subjects can contain a high number of features while having a comparatively low quantity of examples. Machine learning models that attempt to predict outcomes from survey data under these conditions can overfit and result in poor generalizability. One remedy to this issue is feature selection, which attempts to select an optimal subset of features to learn upon. A relatively unexplored source of information in the feature selection process is the usage of textual names of features, which may be semantically indicative of which features are relevant to a target outcome. The relationships between feature names …

Synthesis And Characterization Of Sodium Cathode Materials, He Zhou

McKelvey School of Engineering Theses & Dissertations

As sodium batteries hold great promise as a next-generation energy storage device to replace lithium batteries, the development of sodium battery materials has become increasingly urgent. The current study aims to investigate two potential sodium-ion battery cathode materials, Sodium Vanadium Phosphate, and Sodium Manganese Hexacyanoferrate, optimize the experimental procedures, conduct a systematic analysis of material properties and characterization, and ultimately determine the ideal synthesis conditions for these materials.

In the first part of the study, we focused on optimizing the synthesis of Sodium Vanadium Phosphate. By investigating various synthesis conditions, such as annealing temperature, pressure, ascorbic acid content, and material …

Effects Of Functional Network Model Definition On Biomarker Outcome Prediction, Xinyang Feng

Arts & Sciences Electronic Theses and Dissertations

Machine learning (ML) models are widely used to investigate the human connectome and to predict and understand behavior, emotion, and cognition. Prior research has organized pediatric connectome data using adult functional network models. However, this assumes that adult functional network models are appropriate and useful for prediction developmental outcomes from pediatric connectome data. We hypothesize that the application of adult brain network models could result in poor model fit, limiting the generalizability of results. Here, we test whether prediction of biological age is improved by concordant brain network models matching underlying functional connectome data. To quantify the difference in age …

Understanding Societal Values Of Chatgpt, Yidan Tang

McKelvey School of Engineering Theses & Dissertations

As Large language models (LLMs) become increasingly pervasive in various domains, it is crucial to ensure that their outputs adhere to societal values and ethical considerations. In this thesis, we investigate the alignment of ChatGPT, a recent state-of-the-art large language model developed by OpenAI, with societal values. Specifically, we define the problem of societal values of LLMs and assemble a representative collection of 7 datasets covering 4 topics related to societal values. In-context learning techniques are applied and appropriate prompts are designed. The performance of each dataset is measured using a standardized evaluation system focused on accuracy. We then display …

Evaluating The Problem Solving Abilities Of Chatgpt, Fankun Zeng

McKelvey School of Engineering Theses & Dissertations

This thesis addresses the need for a fair evaluation of language models' problem solving abilities by presenting a unified evaluation framework for ChatGPT on 16 problem solving datasets (e.g., NaturalQA, HellaSwag, MMLU, etc.). We evaluate the model's performance using F1, exact match, and quasi-exact match metrics and find that ChatGPT is highly accurate in solving tasks that require commonsense and knowledge. However, we also identify truncated text bias and few-shot scenarios as challenges that may impact ChatGPT's performance. Our research highlights the importance of standardizing datasets and developing a unified evaluation system for the fair evaluation of language models. Overall, …

Synthesis, Radiolabeling And Evaluation Of A Suite Of Tracers With 44Sc For Detecting Extracellular Dna, Zhiyao Li

McKelvey School of Engineering Theses & Dissertations

Neutrophil extracellular traps involve the rapid translocation of DNA to the outside of the cell under certain stimuli. This structure forms a fibrous network that is able to limit the spread of pathogens and to kill microorganisms. It has also been shown to be present in various pathological processes such as inflammation, autoimmune diseases, and cancer metastasis. Currently, the formation process of NETs in vivo is being extensively studied. However noninvasive detection and quantitation has yet to be achieved. A class of PET tracers are described here that consists of a DNA dye as the backbone that is labeled with …

The Quantitative Microanalysis Explorer: Introducing Web-Based Visualization For Optical, Electron, And Quantitative X-Ray Maps For Studying Lunar Samples, Angelina Minocha

Senior Honors Papers / Undergraduate Theses

Modern sample imaging techniques produce data in the form of large mosaics, wherein every pixel contains valuable mineralogical information. These heavy data files are challenging for most computers to load and process, furthermore access to lunar and other extraterrestrial samples is limited. We developed the QME Tool to display optical, electron, and quantitative x-ray maps in conjunction with one another to overcome these challenges and advance mineralogy data presentation and analysis. The images and quantitative data was collected using specialized techniques, followed by an extensive image co-registration process. The interface was developed using OpenSeadragon, “An open-source, web-based viewer for high-resolution …

Geometry And Dynamics Of Rolling Systems, Bowei Zhao

Arts & Sciences Electronic Theses and Dissertations

Billiard systems, broadly speaking, may be regarded as models of mechanical systems in which rigid parts interact through elastic impulsive collision forces. When it is desired or necessary to account for linear/angular momentum exchange in collisions involving a spherical body, a type of billiard system often referred to as no-slip has been used. Previous work indicated that no-slip billiards resemble non-holonomic systems, specifically, systems consisting of a ball rolling on surface. In prior research, such connections were only observed numerically and were restricted to very special surfaces. In this thesis, it is shown that no-slip billiard and rolling systems are …

Kernel Estimation Of Spot Volatility And Its Application In Volatility Functional Estimation, Bei Wu

Arts & Sciences Electronic Theses and Dissertations

It\^o semimartingale models for the dynamics of asset returns have been widely studied in financial econometrics. A key component of the model, spot volatility, plays a crucial role in option pricing, portfolio management, and financial risk assessment. In this dissertation, we consider three problems related to the estimation of spot volatility using high-frequency asset returns. We first revisit the problem of estimating the spot volatility of an It\^o semimartingale using a kernel estimator. We prove a Central Limit Theorem with an optimal convergence rate for a general two-sided kernel under quite mild assumptions, which includes leverage effects and jumps of …

Dealing With Dimensionality: Problems And Techniques In High-Dimensional Statistics, Cezareo Rodriguez

Arts & Sciences Electronic Theses and Dissertations

In modern data analysis, problems involving high dimensional data with more variables than subjects is increasingly common. Two such cases are mediation analysis and distributed optimization. In Chapter 2 we start with an overview of high dimensional statistics and mediation analysis. In Chapter 3 we motivate and prove properties for a new marginal screening procedure for performing high dimensional mediation analysis. This screening procedure is shown via simulation to perform better than benchmark approaches and is applied to a DNA methylation study. In Chapter 4 we construct a cryptosystem that accurately performs distributed penalized quantile regression in the high-dimensional setting …

Effects Of Surface Ligation On Charge Extraction From Wurtzite Cadmium Selenide Quantum Platelets And Quantum Belts, Hailey Meyer

Arts & Sciences Electronic Theses and Dissertations

This dissertation presents the synthesis of flat, colloidal wurtzite CdSe quantum platelets and quantum belts for ligand exchange to novel and existing organic and inorganic L-, X-, and Z- type ligands. Use of these ligands in conjunction with the semiconductor nanocrystals allows for examination of their ligand exchange abilities, photoluminescence quenching efficiencies, and charge transfer properties.

First, zinc and cadmium dithiocarbamate compounds [M(S2CNR1R2)2] are used as ligands on wurtzite CdSe quantum belts. Complete ligand exchange is achieved when the belts are initially ligated with Cd(oleate)2, a Z-type ligand, prior to the exchange, as opposed to n-octylamine or ammonia, which are …

Local Spectroscopy Data Infrastructure: Solid State Nmr Crystallography With Experiment, First-Principal Analysis And Machine Learning, He Sun

Arts & Sciences Electronic Theses and Dissertations

Solid-state magnetic resonance (SSNMR) spectroscopy is a powerful tool for obtaining precise information about the local bonding and morphology of materials. The detailed local structure of crystalline materials cannot be easily solved by traditional experimental methods such as X-ray diffraction (XRD). SSNMR combined with first principal calculation methods such as density functional theory (DFT) can be of great use in this research area. The methodology that is called “NMR crystallography” today has been widely applied to the determination of a wide range of solid materials with an increasing amount of computationally simulated NMR spectra. The construction of a well-established computational …

The Isotropic And Anisotropic Structure Of Antarctica From Seismic Inversion, Zhengyang Zhou

Arts & Sciences Electronic Theses and Dissertations

This dissertation utilizes multiple techniques of earthquake tomography to investigate the seismic structure of the crust and mantle beneath Antarctica. The isotropic structure of the Antarctic crust and upper mantle is now constrained by several seismic studies, but until now few studies have investigated the anisotropic structure. Therefore, in this study, I focus on the anisotropic structure, which is crucial information to understanding current or historic deformation and flow patterns, as well as the organic process of Antarctica. I use the data from the seismic stations deployed on the Antarctica continent during the past 20 years, as well as other …

Contribution To Data Science: Time Series, Uncertainty Quantification And Applications, Dhrubajyoti Ghosh

Arts & Sciences Electronic Theses and Dissertations

Time series analysis is an essential tool in modern world statistical analysis, with a myriad of real data problems having temporal components that need to be studied to gain a better understanding of the temporal dependence structure in the data. For example, in the stock market, it is of significant importance to identify the ups and downs of the stock prices, for which time series analysis is crucial. Most of the existing literature on time series deals with linear time series, or with Gaussianity assumption. However, there are multiple instances where the time series shows nonlinear trends, or when the …

A Synthesis-Based Approach To The Study Of Fe(Ii) Oxidation In Smectites, Robert Joe Kupper Ii

Arts & Sciences Electronic Theses and Dissertations

Smectite clay minerals are present in diverse environments on Earth as a major product of silicate weathering. Although smectites are compositionally varied, they almost always incorporate iron. Iron-bearing smectites are an important component of the biogeochemical iron cycle, serving as a major iron fraction in many soils and altered rocks as well as participating in redox reactions within the surrounding environment. Iron incorporates into smectites in the ferric [Fe(III)] form at the modern, oxygenated surface of Earth but clays forming in anoxic settings instead incorporate ferrous iron [Fe(II)]. Owing to their ubiquity at the surface of the modern Earth, the …

Systems Level Analysis Of Organelle Biogenesis In Saccharomyces Cerevisiae, Kiandokht Panjtan Amiri

Arts & Sciences Electronic Theses and Dissertations

Eukaryotic cells contain hundreds of subcellular structures that serve different functions to maintain cellular homeostasis. A hallmark of Eukaryotic cells is its compartmentalization into membrane-bound organelles. One of the grand challenges in quantitative cell biology is understanding the precision with which cells assemble and maintain subcellular organelles. Despite identification of numerous molecular factors that regulate organelle sizes we lack insight into the quantitative principles underlying organelle size control. We examine organelle sizes from Saccharomyces cerevisiae and human iPS cells with mathematical theory to show that cells can robustly control average fluctuations in organelle size. By demonstrating that organelle sizes obey …

The Physics Of Associative Polymers And Applications To Biomolecular Condensates, Furqan Dar

Arts & Sciences Electronic Theses and Dissertations

Biomolecular condensates represent a new and ubiquitous class of membraneless organelles (MLOs) that are essential for healthy cellular functioning. The constituent molecules of such condensates span a vast bio-macromolecular gamut from intrinsically disordered regions and proteins (IDPs/IDRs), to RNA and RNA-binding proteins (RNPs), to polymerases and DNA etc. Apart from being part of the regular healthy cell cycle, these condensates are also implicated in many diseases, most notably progressive neurodegenerative diseases like Amyotropic Lateral Sclerosis (ALS) and Huntingtin's Disease (HD). Since the constituent molecules of these condensates span a broad range of length scales and modes of interaction, uncovering a …

Toward Enhancing The Synthesis Of Renewable Polymers: Feedstock Conversions And Functionalizable Copolymers, Tedd Casey Wiessner

Arts & Sciences Electronic Theses and Dissertations

This thesis describes research under the rubric of the Center for Sustainable Polymers that is aimed at two separate goals. The goal of the first project (Chapters 1 and 2) was to develop a deeper mechanistic understanding of a method for the synthesis of linear α-olefins, while the second aimed at synthesizing statistical copolymers that incorporate olefin-containing monomers through ring-opening transesterification polymerization and showing that these copolymers could be functionalized. In Chapter 1, published methods for the conversion of fatty acids to linear α-olefins are reviewed to provide context for the mechanistic work we accomplished (Chapter 2). In Chapter 2 …

Functionalized Plasmonic Nanostructures For Ultrasensitive Single Cell Analysis, Priya Rathi

Arts & Sciences Electronic Theses and Dissertations

Ultrasensitive detection and quantification of soluble, secreted and cell surface-bound proteins is critical for advancing our understanding of cellular systems, enabling effective drug development, novel therapies, and bio-diagnostics. However, exiting technologies are largely limited by their sensitivity, making the detection and quantification of low-abundant proteins extremely challenging. This forms a major barrier in various fields of biology and biomedical sciences. In this work, we introduce novel cellular analysis methodologies based on plasmon-enhanced fluorescence for analyzing cell structure and probing surface and secreted proteins from cells. In the first part, we introduce plasmon-enhanced expansion microscopy and demonstrate the effectiveness of employing …

Quasiparticle And Excitonic Effects In Two-Dimensional Van Der Waals Materials, Linghan Zhu

Arts & Sciences Electronic Theses and Dissertations

Since their discovery, low dimensional van der Waals materials have attracted increasing research interests. They serve as ideal platforms to study novel physics in reduced-dimensional systems, and are critical in nowadays’ nanotechnology applications. Due to the reduced dielectric screening in low dimensions, strong excited state properties dictate their electronic, transport and optical properties, the study of which calls for a description of the many-particle interactions beyond the traditional density functional theory. This is where the many-body perturbation theory comes into play. In this thesis, I will present a comprehensive study of the quasiparticle and excitonic properties of a variety of …

Development Of Redox-Responsive Phenazine-Based Foldamers. Acylative Kinetic Resolution Of Hydroxamic Acids, Jingwei Yin

Arts & Sciences Electronic Theses and Dissertations

Two different research directions have been presented in this thesis. The first project is about phenazine-based foldamers as molecular actuators. Researchers have been interested in the design and synthesis of foldamers and molecular actuators for years. We began our exploration by demonstrating that phenazine-1,6-dicarboxamides can function as redox-responsive molecular switches. We then designed and synthesized two generations of phenazine-based interleafed foldamers and studied their stability and redox behaviors under chemical and electrochemical conditions. In the second project, we have developed the first acylative kinetic resolution on hydroxamic acids. Although chiral hydroxamic acids have extensive applications, synthetic methods towards them are …

The Effect Of Ionization Density In Applications Of Radiation Detection, Dosimetry, And Therapy, Daniel Mulrow

Arts & Sciences Electronic Theses and Dissertations

This dissertation covers a wide range of topics but is linked by the common theme of radiation interacting with materials and studying the result of those interactions. The introduction describes the fundamentals of how radiation interacts with material and how we are able to detect that radiation and the application of how we use those interactions in radiation oncology. The thesis starts with a chapter detailing the temperature dependence of the photophysics in two organic scintillators. This chapter is the foundation for a future study that will look the degree to which these scintillators can distinguish between gammas and neutrons …

Investigating Applications Of Deep Learning For Diagnosis Of Post Traumatic Elbow Disease, Hugh James

McKelvey School of Engineering Theses & Dissertations

Traumatic events such as dislocation, breaks, and arthritis of musculoskeletal joints can cause the development of post-traumatic joint contracture (PTJC). Clinically, noninvasive techniques such as Magnetic Resonance Imaging (MRI) scans are used to analyze the disease. Such procedures require a patient to sit sedentary for long periods of time and can be expensive as well. Additionally, years of practice and experience are required for clinicians to accurately recognize the diseased anterior capsule region and make an accurate diagnosis. Manual tracing of the anterior capsule is done to help with diagnosis but is subjective and timely. As a result, there is …