Physical Sciences and Mathematics Commons^™

Oscars Vs. Ozone: The Motion Picture Industry’S Impact On Climate Change And What They Are Doing About It, Alexis J. Simpson

Senior Theses

This thesis focuses on demonstrating that the motion picture industry, which includes film and television production (and thus will also be called ‘the film and television industry’), has notably contributed to the global effects of climate change. Such contributions can stem from the industry’s emissions and waste, with examples including travel for cast and crew, energy use for production equipment (some of which run on diesel), and disposable physical sets and costumes. The intention here is to give an accurate picture of current production practices and share examples of progress in the industry that are combating the negative impacts of …

Understanding The Role Of The Jet Streams And Gulf Stream Eddies On The Northwest Atlantic Marine Heatwaves, Lydia Rose Duncan Sims

Theses and Dissertations

The Northwest (NW) Atlantic is one of the fastest warming regions in the global ocean and in the recent decade has experienced several extreme temperature events. These extreme anomalous temperature events are known as Marine Heatwaves (MHWs), which are forced by a variety of physical processes that affect the heat source and sink of the water column. These MHWs have been increasing globally in duration and frequency due to anthropogenic warming, and have increased ecological damage seen in mass mortality events of economically viable species. Within the NW Atlantic, several key processes encourage the formation of MHWs, such as the …

A Method For Single-Particle Magnetic Particle Spectroscopy With A Nanofabricated Coplanar Stripline, Jacob Martin

Theses and Dissertations

Drawing from magnetic particle imaging principles, magnetic particle spectroscopy (MPS) serves as a valuable tool employing superparamagnetic iron-oxide nanoparticles (SPIONs) in diverse applications ranging from medical imaging to biosensing and the comprehensive study of magnetic particles’ characteristics. MPS leverages the nonlinear response exhibited by SPIONs when a external magnetic field is applied, enabling a highly sensitive method for examining biological systems and more. However, conventional MPS setups demand a high particle concentration of approximately 10^15 particles per liter to generate a detectable response. The first objective of this work is to simulate the dynamics of a system with the ability …

Enhancing Relation Database Security With Shuffling, Tieming Geng

Theses and Dissertations

Database security holds paramount importance as it safeguards an organization's most valuable assets: its data. In an age marked by escalating cyber threats, protecting sensitive information stored in databases is essential to preserve trust, prevent financial losses, and maintain legal compliance. In this dissertation, an exploration into the realm of relation database security is undertaken. The research introduces a cryptographic secure shuffling algorithm designed to fortify database security. Additionally, the dissertation presents a series of innovative solutions aimed at bolstering both the security and efficiency of the shuffling algorithm. Encryption algorithms have long served as a mean of safeguarding sensitive …

Robust Underwater State Estimation And Mapping, Bharat Joshi

Theses and Dissertations

The ocean covers two-thirds of Earth, which is relatively unexplored compared to the landmass. Mapping underwater structures is essential for both archaeological and conservation purposes. This dissertation focuses on employing a robot team to map underwater structures using vision-based simultaneous localization and mapping (SLAM). The overarching goal of this research is to create a team of autonomous robots to map large underwater structures in a coordinated fashion. This requires maintaining an accurate robust pose estimate of oneself and knowing the relative pose of the other robots in the team. However, the GPS-denied and communication-constrained underwater environment, along with low visibility, …

A Field-Programmable Metamaterial Using Memristor As A Stable Switcher, Taekuk Hong

Theses and Dissertations

Before the memristor was discovered, there were RLC circuits as representative passive devices. However, the fourth fundamental two-terminal circuit has been discovered by Dr. Leon Chua in 1971 and has been called a memristor. The memristor is a compound word of memory and resistor, and is an element whose resistive value is not constant and whose resistive value changes depending on the applied voltage and is recorded as a memory. It is mainly used in resistive switching and is the center of this research theme. A metamaterial is artificially created material that has never been found in nature. The theory …

Computerized Psychological Testing: Designing And Developing An Efficient Test Suite Using Hci And Reinforcement Learning Techniques, William Henry Hoskins

Theses and Dissertations

In this work we discuss the design and development of the Carolina Automated Reading Evaluation (CARE), created to facilitate the finding of deficits in the reading ability of children from four to nine years of age. Designed to automate the process of screening for reading deficits, the CARE is an interactive computer-based tool that helps eliminate the need for one-on-one evaluations of pupils to detect dyslexia and other reading deficits and facilitates the creation of new reading tests within the platform. While other tests collect specific data points in order to determine whether a pupil has dyslexia, they typically focus …

Investigation, Synthesis And Rational Design Of Novel Transuranic Containing Extended Structures, Adrian Thomas Hines

Theses and Dissertations

The use of nuclear technology has proven useful for energy generation and for weapons manufacturing, but disposal and storage of nuclear waste is an ongoing problem. The accumulation of nuclear waste over the past decades has yielded a vast amount of waste that must be dealt with, and with space at interim storage facilities diminishing, it has become increasingly important to find solutions to nuclear waste storage. The vitrification process has been widely accepted as a viable route for immobilization of high-level waste; however, the process is inadequate for complex waste streams and has many drawbacks such as limited waste …

Deep Learning For Studying Materials Stability And Solving Thermodynamically Consistent Pdes With Dynamic Boundary Conditions In Arbitrary Domains, Chunyan Li

Theses and Dissertations

Deep learning has achieved remarkable success in various fields, including image processing, natural language processing, and signal processing, ushering in a transformative era in research and real-life applications. This rise underscores the transformative capabilities of deep learning, with its innovative approach to function approximation. Traditionally, approximation theory relied on additive constructions, but deep neural networks have introduced a compositional approach, reshaping the landscape of function approximation. This thesis explores the efficacy of this compositional construction within the realm of material science and the solution of thermodynamically consistent partial differential equations with thermodynamically consistent dynamic boundary conditions in arbitrary domains. As …

Reactive Molecular Dynamics Of Large Systems: Quantum Dynamics With Adaptable Gaussian Bases; Hydroxide Diffusion In A Polymeric Environment, Mohottige Sachith Prasanga Wickramasinghe

Theses and Dissertations

This dissertation describes our research in theory and applications of reactive molecular dynamics. Quantum dynamics provides the foundation for understanding chemical processes. However, the computational cost of describing a general quantum system scales exponentially with the system size. Thus, an efficient basis representation of wavefunctions is essential. Time-dependent Gaussian bases are often employed to describe the large-amplitude motion of high-dimensional systems. The time dependence of such bases is typically determined by (i) the variational principle or by (ii) classical dynamics. But those approaches have shortcomings due to intrinsic singularity of the variational equations in the full basis limit or due …

Recovering Lost Exposure From The Majorana Demonstrator And Testing Data Selection Assumptions, Thomas Lannen

Theses and Dissertations

The Majorana Demonstrator recently concluded its search for neutrinoless double beta decay using an array of up to 40.4kg of germanium detectors, 27kg of which were enriched in ⁷⁶Ge and housed inside a copper and lead compact shield located at the 4850 foot level in a clean room in the Davis Campus of the Sanford Underground Research Facility (SURF) in Lead, South Dakota. This search proceeded from June 26, 2015 until March 3, 2021 and 64.5 kg yr of enriched active exposure was acquired while achieving a world leading energy resolution of 0.12% FWHM at 2039 keV, one of …

Examination And Application Of Body Condition Methods In Cetaceans, Kira Anne Telford

Theses and Dissertations

Body condition assessments are a valuable tool for evaluating the relative health of a population through various metrics, indexes, or proxies. Long-term data collection can be used to examine the relationship between fluctuations in body condition and natural or anthropogenic drivers. Application of this information is vital for monitoring the success of the conservation management decisions for a species or population. Cetaceans have a variety of methods available to assess body condition, including invasive methods like biopsies and necropsies or observational methods such as photogrammetry. Exploration of the application of these methods in the literature revealed an emphasis on necropsies …

Hf Radar: Shining A Light On Ocean Currents, Douglas Cahl

Theses and Dissertations

High Frequency (HF) radar systems are commonly used to estimate surface ocean currents over the coastal ocean. Their range depends on their operational frequency and low frequency systems (≤ 10 MHz) can reach distances up to 200 km from the coastline. These systems are used to estimate surface currents by measuring the phase speed of wind-driven waves and comparing the measured speed with that expected theoretically; deviations from the theoretical still-water phase speed are attributed to ocean surface currents. Although HF radar systems are considered a mature technology and the accuracy of the radar-derived surface current estimates is well studied, …

Identification Of New Disinfection Byproducts In Drinking Water And Impacts Of Algae, Md. Tareq Aziz

Theses and Dissertations

The disinfection of water has been hailed as one of the most important triumphs for public health in the 20th century. Drinking water treatment plants produce safe drinking water by inactivating microorganisms through the use of disinfectants, including chlorine, chloramine, chlorine dioxide, UV irradiation, and ozone. However, these disinfectants also produce toxic disinfection by-products (DBPs), through reactions with natural organic matter and anthropogenic pollutants, as well as bromide and iodide present in source waters. The presence of bromide and iodide results in the formation of bromo- and iodo-DBPs which are much more toxic than DBPs containing chlorine. DBPs are always …

Widely Digitally Delicate Brier Primes And Irreducibility Results For Some Classes Of Polynomials, Thomas David Luckner

Theses and Dissertations

This dissertation considers three different sections of results. In the first part of the dissertation, a result on consecutive primes which are widely digitally delicate and Brier numbers is discussed. Making use of covering systems and a theorem of D. Shiu, M. Filaseta and J. Juillerat showed that for every positive integer k, there exist k consecutive widely digitally delicate primes. They also noted that for every positive integer k, there exist k consecutive primes which are Brier numbers. We show that for every positive integer k, there exist k consecutive primes that are both widely digitally …

A Bayesian Spatial Scan Statistic For Normal Data, Laasya Velamakanni

Theses and Dissertations

Scan statistics are useful methods for detecting spatial clustering. While they were initially developed to detect regions with an excess of binomial or Poisson events, spatial scan statistics have been extended to detect hotspots in other types of data including continuous data. They have many applications in different fields such as epidemiology (e.g. detecting disease outbreaks), sociology (e.g. detecting crime hotspots), and environmental health (e.g. detecting high-pollution areas). Spatial scan statistics identify a ‘most likely cluster’ and then use a likelihood ratio test to determine if this cluster is statistically significant. Spatial scan statistics have been extended to the Bayesian …

Deep Learning Methods For Some Problems In Scientific Computing, Yuankai Teng

Theses and Dissertations

Deep learning has emerged as a powerful approach for solving complex problems in scientific computing due to the increasing availability of large-scale data and computational resources. This thesis explores the potential of deep learning methods for three specific problems in scientific computing: (i) reducing the dimensions of variables in function approximation, (ii) solving linear reaction-diffusion equations, and (iii) finding the parametric representations of parameters in the numerical schemes for solving time-dependent partial differential equations.

For the first problem, a novel deep learning architecture is developed for reducing the dimensions of variables in function approximation. The proposed method achieves state-of-the-art performance …

Extending The Convolution In Graph Neural Networks To Solve Materials Science And Node Classification Problems, Steph-Yves Mike Louis

Theses and Dissertations

The usage of graph to represent one's data in machine learning has grown in popularity in both academia and the industry due to its inherent benefits. With its flexible nature and immediate translation to real life observed objects, graph representation had a considerable contribution in advancing the state-of-the-art performance of machine learning in materials.

In this dissertation proposal, we discuss how machines can learn from graph encoded data and provide excellent results through graph neural networks (GNN). Notably, we focus our adaptation of graph neural networks on three tasks: predicting crystal materials properties, nullifying the negative impact of inferior graph …

Groundwater Flow And Salt Marsh Migration: The Forest/Marsh Boundary, Camille Rossiello

Theses and Dissertations

Salt marshes migrate landward in response to sea level rise, but the rate of this migration is not constant and can be influenced by pulse disturbances. Long term observations at Sapelo Island, Georgia, show that salt marsh migration has occurred during droughts, but the mechanism for this migration is unclear. Drought is thought to influence salt marsh migration by reducing fresh groundwater discharge from the upland. Rising sea level also encroaches on the upland, which could cause movement of the freshwater lens inland. A two-dimensional numerical model was built to simulate groundwater flow and solute transport based on the Marsh …

Study Of Non-Covalent Interactions Using Molecular Rotors And Balances, Daniel Onyekachi Madukwe

Theses and Dissertations

The main focus of this dissertation is on the quantification of non-covalent interactions using molecular rotors and balances. While molecular rotors were used to measure kinetic effects of weak non-covalent interactions, molecular balances were used to measure their thermodynamic effects. Chapters 1 and 2 focus on the use of molecular rotors in measuring and studying the kinetic effects of the hydrogen bonding interaction on the bond rotation transition states. Chapters 3 and 4 focus on the quantification of lone pair – lone pair and sp²-CH/π interactions respectively, using molecular balances. These studies were carried out in the …

The Synthesis Of Novel Rare Earth Thiosilicates Using The Boron Chalcogen Mixture Method For An Interest In Their Magnetic And Optical Properties, Adam Alexander King

Theses and Dissertations

The chalcogens or the group sixteen elements excluding oxygen, are of interest due to their wide variety of structures and compositions, which gives the potential for a plethora of desired physical properties. This is due to their increased ability to catenate, forming stable chalcogen-chalcogen bonds. When the chalcogens combine with certain main group elements and transition metals they form anionic framework building blocks known as chalcometallates. One such chalcometallate of interest is the thiosilicates, compounds containing Si-S bonds as the anionic frameworks. These compounds are of interest due to their potentials in both their optical and magnetic properties. However, traditional …

Approaches To Detecting And Modeling Over-And Underdispersion In Alternative Count Data Distributions And An Application Of Logistic Regression And Random Forest Modeling To Improve Screening Tools For Tic Disorders In Children, Rebecca C. Wardrop

Theses and Dissertations

This dissertation focuses on theory and application of discrete data methods, particularly approaches to over- and underdispersion relative to the Poisson distribution and an application of random forest and logistic regression modeling. The first chapter derives a score test for over- and underdispersion in the heaped generalized Poisson distribution. Equi-, over-, and underdispersed heaped generalized Poisson and heaped negative binomial data are simulated to evaluate the performance of the score test by comparing the power it achieves to that of Wald and likelihood ratio tests. We find that the score test we derive performs comparably to both the Wald and …

Computational Studies Of Bond Dissociation Energies And Organic Reaction Mechanisms, Shehani Thishakkya Wetthasinghe

Theses and Dissertations

This dissertation presents the progress of two independent projects. Chapter 2 and Chapter 3 focus on the first project, which involves material exploration utilizing machine learning techniques. We explore the potential use of cobaltocenium (CoCp⁺₂) derivatives as metal cations in anion exchange membranes (AEMs) for alkaline fuel cells, highlighting their superior thermal and alkaline stability compared to ammonium derivatives. The stability of CoCp⁺₂ can be fine-tuned by varying the substituent groups attached to the cyclopentadienyl ring (Cp) in CoCp⁺₂ .These derivatives encompass a variety of electron-donating and electron-withdrawing groups as substituents on both …

Statistical Methods For Single Cell Sequencing Data Analysis, Fei Qin

Theses and Dissertations

The recent emergence of single cell sequencing (SCS) technology has provided us with single-cell DNA or RNA sequencing (scDNA/RNA-seq) information to investigate cellular evolutionary relationships. Despite many analysis methods have been developed to infer intra-tumor genetic heterogeneity, cluster cellular subclones, detect genetic mutations, and investigate spatially variable (SV) genes, exploring SCS data remains statistically challenging due to its noisy nature.

To identify subclones with scDNA-seq data, many existing studies use an independent statistical model to detect copy number profile in the first step, followed by classical clustering methods for subclone identification in downstream analyses. However, spurious results might be generated …

Measurement Of The Total Cross-Section Of Muon Neutrino Charged-Current Coherent Pion Production In Nova Near Detector, Kuruppumullage Don Chatura Dilshan Kuruppu

Theses and Dissertations

Charged Current (CC) coherent neutrino-nucleus pion production is characterized by small momentum transferred to the nucleus, which is left in its ground state. Despite the relatively large uncertainties on the production cross-section, coherent production of mesons by neutrinos represents an important process, as it can shed light on the structure of the weak current and can also constitute a potential source of background for modern neutrino oscillation experiments and searches for Beyond Standard Model (BSM) physics. This Ph.D. thesis presents a new measurement of CC coherent pion production in the NOvA near detector at the Fermi National Accelerator Laboratory (Fermilab). …

Expanding On The Solid State Chemistry Of F-Element Chalcogenides, Logan Skyler Breton

Theses and Dissertations

An overarching goal in solid state chemistry is to achieve predictability regarding the synthesis of compounds with desired properties. While this goal is far from being reached, solid state chemists are hard at work synthesizing and characterizing new materials to further our understanding of structure-property relationships, and to expand our fundamental knowledge to rationalize the outcomes of solid-state syntheses. With the advent of new solid state synthetic methods, novel compounds exhibiting exciting properties are still being discovered today. The infancy of these synthetic methods promises a myriad of undiscovered compounds with potentially interesting properties which has resulted in a recent …

Predicting Material Structures And Properties Using Deep Learning And Machine Learning Algorithms, Yuqi Song

Theses and Dissertations

Discovering new materials and understanding their crystal structures and chemical properties are critical tasks in the material sciences. Although computational methodologies such as Density Functional Theory (DFT), provide a convenient means for calculating certain properties of materials or predicting crystal structures when combined with search algorithms, DFT is computationally too demanding for structure prediction and property calculation for most material families, especially for those materials with a large number of atoms. This dissertation aims to address this limitation by developing novel deep learning and machine learning algorithms for effective prediction of material crystal structures and properties. Our data-driven machine learning …

Machine-Learning Classification To Predict The Dimensionality Of Hybrid Organic-Inorganic Halide Perovskites, Yatiwelle Koralalage Samuditha Sandaru Yatiwella

Theses and Dissertations

Low dimensional hybrid perovskites have demonstrated remarkable performance in photovoltaic applications, primarily due to their exceptional optical and electronic properties. As the search for potential candidates for novel materials continues, understanding the structure of these materials is crucial for investigating their stability. In this study, we implement a framework to find novel material based on a machine-learning model. The machine learning model was trained to predict the dimensionality of the polyhedral network based on the connectivity of the polyhedral network in different directions. The polyhedral connectivity of low-dimensional structures can be classified into three dimensions: 0D, 1D, and 2D. This …

Yield Extraction For The Γd → Λ X Reaction, K H P Nishadi Hasarangi Silva

Theses and Dissertations

Improving and adding new experimental measurements of hyperon-nucleon (YN) and hyperon-deuteron (Yd) cross sections is an active area in nuclear physics research. Scientists use such cross-section data to understand the composition of neutron stars and develop a comprehensive picture of the baryon-baryon interaction. Using high luminosity photon beam incident on a long liquid deuterium target and the CEBAF Large Acceptance Spectrometer (CLAS) at the Thomas Jefferson National Accelerator Facility (JLab), a sample of hyperon-deuteron elastic scattering events was previously identified. The E06-103 (g13) experiment was originally designed to address the scarcity of experimental data on hyperon photoproduction off the neutron …

Sustainable Approaches To Photo-, Thermo-, And Electro-Chemical Reactions Of Amines, James David Sitter

Theses and Dissertations

In recent years, sustainable routes for chemical synthesis have garnered renewed interest. As the world continues to fight pollution and rising costs, it is imperative that new routes of synthesis that continuously fight the issues of pollution and waste are discovered, defined and explored. While traditional synthesis routes that require energy input typically require the burning of fossil fuels to produce heat, the amount of resources that go into the production of these fossil fuels and the sequestration of its waste to minimize its impact on the carbon footprint is enormous. Furthermore, sustainable chemistry research aims to decrease and minimize …