Physical Sciences and Mathematics Commons^™

Investigating Liquid-Liquid Phase Separation In Lipid Bilayers: A Multi-Modal Approach Utilizing Spectroscopy, Microscopy, And Cryo-Em, Karan D. Sharma

Doctoral Dissertations

This thesis explores the characterization of liquid-liquid phase separation in model lipid bilayers using fluorescence, optical microscopy, and cryo-electron microscopy (cryo-EM) integrated with machine learning (ML) analysis. The plasma membrane has a complex composition, lateral heterogeneity and dynamic structure which makes it challenging to study. Simplified model membranes containing three or four-component lipid mixtures, typically comprising low- and high-melting lipids along with cholesterol, form phase separated systems that mimic lateral heterogeneity/lipid rafts in biomembranes. In living cells, lipid rafts are thought to form nanoscopic domains smaller than 200 nm. These domains cannot be resolved by conventional optical microscopy. For a …

Molecule-Based Quantum Materials Under Extreme Conditions, Avery Leon Blockmon

Doctoral Dissertations

Molecule-based quantum materials are a class of compounds with competition between the spin, orbitals, charge, and lattice. They feature flexible architectures and structural designs that can be easily modified for different functionalities. As a result of their overall low energy scales, they can be easily tuned with external stimuli like magnetic field or pressure to reveal new states and properties. This dissertation presents a high magnetic field investigation of three different molecule-based quantum materials under extreme conditions revealing insights into their structural, electronic, and magnetic properties.

My initial study analyzes decoherence pathways in spin qubit Na₉[Ho(W₅O …

Extending Application Runtime Systems For Effective Data Tiering On Complex Memory Platforms, Brandon Kammerdiener

Doctoral Dissertations

Computing platforms that package multiple types of memory, each with their own performance characteristics, are quickly becoming mainstream. To operate efficiently, heterogeneous memory architectures require new data management solutions that are able to match the needs of each application with an appropriate type of memory. As the primary generators of memory usage, applications create a great deal of information that can be useful for guiding memory tiering, but the community still lacks tools to collect, organize, and leverage this information effectively. To address this gap, this work introduces a novel software framework that collects and analyzes object-level information to guide …

Enhancing Code Portability, Problem Scale, And Storage Efficiency In Exascale Applications, Nigel Tan

Doctoral Dissertations

The growing diversity of hardware and software stacks adds additional development challenges to high-performance software as we move to exascale systems. Re- engineering software for each new platform is no longer practical due to increasing heterogeneity. Hardware designers are prioritizing AI/ML features like reduced precision that increase performance but sacrifice accuracy. The growing scale of simulations and the associated checkpointing frequency exacerbate the I/O overhead and storage cost challenges already present in petascale systems. Moving forward, the community must address performance portability, precision optimization, and data deduplication challenges to ensure that exascale applications efficiently deliver scientific discovery. In this dissertation, …

Transfer Learning For Predictive Maintenance: A Case Study, Colter A. Swanson

Masters Theses

In light of recent strides in high-performance computing, the concept of transfer learning has emerged as a prominent paradigm within the realm of Artificial Intelligence and Machine Learning methodologies. Analogous to the human brain's capacity to assimilate information across related domains for pattern recognition, transfer learning has swiftly asserted its dominance, particularly in deep learning applications such as image classification and natural language processing. Despite its ascendancy in these domains, there exists a lack of comprehensive investigations in alternative domains, notably those encompassing tabular data formats. This thesis seeks to redress this gap by conducting an empirical examination of transfer …

Neural-Network-Based Detection Of Radiopharmaceutical Extravasation In Pet/Ct Data, Elijah D. Berberette

Masters Theses

The immediate identification of PET/CT radiopharmaceutical extravasation can eliminate many adverse effects such as misdiagnosis and improper therapy. Radiopharmaceutical extravasation is the leakage of an injected radiotracer from the patient’s intended vein into surrounding tissues. The detection of this phenomenon often requires the use of an external monitoring device; due to a lack of robust visual features that can provide indication that it has occurred. In this thesis, the feasibility of using neural networks trained on PET/CT data to identify extravasation is explored. This approach begins with a novel preprocessing methodology that automatically extracts body weight normalized standard uptake values …

Mathematical Modeling And Numerical Approximations Of Combustion Instability Frequencies And Growth Rates, Harvey B. Ring Iii

Doctoral Dissertations

This dissertation presents a mathematical model and numerical simulations to determine the resonant frequencies and their associated growth rates for longitudinal modes in a combustion system similar to that found in a rocket engine. The mathematical model, which is applicable to a two-duct system with a thin flame between the two ducts, each of which having constant area and properties, considers the case of axial mean velocity and uses a vibrating wall at the inlet to select the frequency so that all modes may be found. The model is applied to the acoustics equations describing pressure and velocity fluctuations, derived …

Recommendations Of Research Articles By Experts: Visualizing Relationships And Expertise, Peiling Wang, Scott Eugene Shumate, Pinghao Ye, Chad Mitchell

School of Information Sciences -- Faculty Publications and Other Works

The paper applied data analytics and network visualization to show the potentials of employing Faculty Opinions beyond literature recommendations by domain experts. Based on a set of highly recommended articles by at least four experts with a sum of 10 or more stars (A recommended article is assigned a score between one to three stars by the recommender.), this study tests the new ideas and methods of identifying and visualizing relationships between scientific papers, experts, and categories. Despite of the available dataset in the study is small, the findings show that a platform designed for recommending and retrieving publications has …

Thermal Hydraulic Analysis For Different Subchannels Of Generic Vver-1200, Mosaddak Ahamed Zahid, Md. Imam Mehedi, Shamsul Arefin Shibly, A. S. Mollah

International Journal of Nuclear Security

The demand for nuclear energy is steadily increasing all over the world. Most nuclear power is used for peaceful applications such as power generation, healthcare, agriculture, food security, industry, and research. One of the primary applications of nuclear energy is the generation of electricity through nuclear power plants based on nuclear reactors. Many developing countries around the world (such as Bangladesh) are moving toward nuclear power plants because they have huge advantages, including low-cost energy, reliable energy sources, zero carbon emissions, and high energy concentration. As a result, the demand for nuclear reactor protection and operational protection of nuclear power …

Enhancing Security And Usability In Password-Based Web Systems Through Standardized Authentication Interactions, Anuj Gautam

Doctoral Dissertations

Password-based authentication is the predominant method for securing access on the web, yet it is fraught with challenges due to the web’s lack of inherent design for authentication. Password managers have emerged as auxiliary tools to assist users in generating, storing, and inputting passwords more securely and efficiently. But both the browser and the server are oblivious of the password manager’s presence, leading to usability and security issues. However, because the web wasn’t originally built to accommodate password-based authentication, password managers serve as a temporary fix and encounter several usability and security problems that limit their widespread use. This dissertation …

Bridging Biological Systems With Social Behavior, Conservation, Decision Making, And Well-Being Through Hybrid Mathematical Modeling, Maggie Renee Sullens

Doctoral Dissertations

Mathematical modeling can achieve otherwise inaccessible insights into bio-logical questions. We use ODE (ordinary differential equations) and Game Theory models to demonstrate the breadth and power of these models by studying three very different biological questions, involving socio-behavioral and socio-economic systems, conservation biology, policy and decision making, and organismal homeostasis.

We adapt techniques from Susceptible-Infected-Recovered (SIR) epidemiological models to examine the mental well-being of a community facing the collapse of the industry on which it’s economically dependent. We consider the case study of a fishing community facing the extinction of its primary harvest species. Using an ODE framework with a …

Investigation Of Magnetic, Spectroscopic, And Structural Properties Of Molecular Metal Compounds, Alexandria Bone

Doctoral Dissertations

Compounds exhibiting single-molecule magnetism (SMM) are of current interest for potential use in molecular data storage and quantum computing applications. However, rapid magnetic relaxation at desired operating temperatures currently limits the use of these materials, and a more thorough understanding of the magnetic and vibrational transitions that affect magnetic memory is required to inform SMM design. The primary focus of this dissertation is the study of magnetic and vibrational modes in molecular magnetic compounds via advanced spectroscopic techniques such as inelastic neutron scattering (INS), far-IR magneto-spectroscopy (FIRMS), and high-field, high-frequency electron paramagnetic resonance (HFEPR) to directly observe transitions among zero-field …

Classifying Facial Expressions Of Students Being Tutored In A Gateway College Math Course, Kriss Gabourel

Doctoral Dissertations

When it comes to tutoring, computers have not quite been able to achieve the success that humans have in helping students improve learning outcomes. This research sought to address one aspect of what makes human tutors more effective, the ability to identify and to interpret facial expressions. When a student is feeling anxious, confused, distracted or frustrated, or when a student has an ‘aha’ moment, human tutors can identify the student’s facial expressions and adjust their tutoring approach as necessary. This study sought to determine if, in the context of a gateway college math course, these particular learning-centered affects could …

Multi-Objective Radiological Analysis In Real Environments, David Raji

Doctoral Dissertations

Designing systems to solve problems arising in real-world radiological scenarios is a highly challenging task due to the contextual complexities that arise. Among these are emergency response, environmental exploration, and radiological threat detection. An approach to handling problems for these applications with explicitly multi-objective formulations is advanced. This is brought into focus with investigation of a number of case studies in both natural and urban environments. These include node placement in and path planning through radioactivity-contaminated areas, radiation detection sensor network measurement update sensitivity, control schemes for multi-robot radioactive exploration in unknown environments, and adversarial analysis for an urban nuclear …

Jet Production And Rppb In Pp Collisions At Sqrt(S) = 8 Tev And P--Pb Collisions At Sqrt(Snn) = 8.16 Tev Using The Alice Detector, Austin Schmier

Doctoral Dissertations

At the CERN Large Hadron Collider, protons and heavy ions are collided at relativistic
speeds in order to study the behavior and processes of Quantum Chromodynamics (QCD). One such process is the production of collimated sprays of particles called jets resulting from the hard scattering of two partons. Jets are an important probe that provide a window into the early stages of the collision.

Measurements in small systems such as proton-proton (pp) and proton-lead (p–Pb)
collisions are important in order to provide constraints on nuclear parton distribution
functions and the strong coupling constant αS [55]. Measurements at different center of …

Graph-Based And Anomaly Detection Learning Models For Just-In-Time Defect Prediction, Aradhana Soni

Doctoral Dissertations

Efficiently identifying and resolving software defects is essential for producing high quality software. Early and accurate prediction of these defects plays a pivotal role in maintaining software quality. This dissertation focuses on advancing software defect prediction methodologies and practical applications by incorporating graph-based learning techniques and generative adversarial-based anomaly detection techniques. First, we present a novel approach to software defect prediction by introducing a graph-based defect ratio (GDR). This innovative metric leverages the intricate graph structure that captures the interdependencies among developers, commits, and repositories, offering a promising alternative to standard traditional features. This study highlights the potential for graph-based …

Towards Continuous Variable Quantum Computation Of Lattice Gauge Theories, Shane Nicklaus Thompson

Doctoral Dissertations

The calculation of physical quantities in a relativistic quantum field theory (rQFT) is a computationally demanding task due to the presence of an infinite number of degrees of freedom. This problem carries over to discretized versions of these theories, i.e. lattice field theories, where the Hilbert space size increases exponentially with the size of the lattice. Despite the success of some classical techniques such as Monte Carlo, their applicability is limited. For instance, Monte Carlo is associated with a sign problem that makes real-time evolution and high-fermion-density systems particularly challenging to compute. Quantum computation is a promising avenue thanks to …

Investigating Small Molecule Behavior In Living Bacterial Membranes With Second Harmonic Scattering, Marea J. Blake

Doctoral Dissertations

A molecule's entry into a cell is impeded primarily at the surface of Gram-positive bacteria. This interface serves as the boundary separating cellular contents from the external environment and is composed of a thick layer of peptidoglycan and a lipid bilayer equipped with protein and lipid species with various roles including that of small-molecule transport. As such, understanding these molecule-membrane interactions is imperative to examine in order to design novel drugs or adjuvants to combat the global antibiotic resistance predicament. Knowledge regarding passive diffusion and overall organization of small molecules in the lipid bilayer of living Gram-positive cells is limited …

Stability Of Quantum Computers, Samudra Dasgupta

Doctoral Dissertations

Quantum computing's potential is immense, promising super-polynomial reductions in execution time, energy use, and memory requirements compared to classical computers. This technology has the power to revolutionize scientific applications such as simulating many-body quantum systems for molecular structure understanding, factorization of large integers, enhance machine learning, and in the process, disrupt industries like telecommunications, material science, pharmaceuticals and artificial intelligence. However, quantum computing's potential is curtailed by noise, further complicated by non-stationary noise parameter distributions across time and qubits. This dissertation focuses on the persistent issue of noise in quantum computing, particularly non-stationarity of noise parameters in transmon processors. It …

Understanding The Impact Of Divertor And Main Chamber Ion Fluxes On Divertor Closure In The Diii-D Tokamak, Kirtan M. Davda

Doctoral Dissertations

The diverted tokamak redirects extreme heat and particles to targets, a plasma-facing component designed for such loads. Here, the local fluxes produce strong particle recycling and sputtering. Recycled neutrals can “leak” into the region between the core and wall, the scrape-off-layer (SOL), impacting plasma performance. Increasing divertor closure can reduce leakage by containing neutrals within the divertor. However, there exists a need to quantify divertor baffle restrictions and understand closure directly from empirical data as opposed to indirectly through modeling.

Our study introduces the Geometric Restriction Parameter (GRP) based on simplifying neutral transport to ballistic pathways. Specifically, it considers the …

Multimodal Data Fusion And Machine Learning For Advancing Biomedical Applications, Md Inzamam Ul Haque

Doctoral Dissertations

This dissertation delves into the intricate landscape of biomedical imaging, examining the transformative potential of data fusion techniques to refine our understanding and diagnosis of health conditions. Daily influxes of diverse biomedical data prompt an exploration into the challenges arising from relying solely on individual imaging modalities. The central premise revolves around the imperative to combine information from varied sources to achieve a holistic comprehension of complex health issues.

The chapters included here contain articles and excerpts from published works. The study unfolds through an examination of four distinct applications of data fusion techniques. It commences with refining clinical task …

Novel Energy Scale Calibration Strategies For The Prospect-Ii Experiment, Xiaobin Lu

Doctoral Dissertations

Nuclear reactors contributed to the first discovery of the elusive neutrino particle and continue to play a significant role in our understanding of neutrino masses and oscillations. The PROSPECT reactor neutrino experiment, the Precision Reactor Oscillation and SPECTrum Experiment, took data at the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory. This work discusses calibration procedures and the establishment of an energy scale model, and details the development of efficient analysis cuts and subsequent selection cut optimization. The precise energy scale calibration and efficient analysis cuts produced a high quality dataset of neutrino interactions of more than 50,000 …

Experimental Quantum Key Distribution In Turbulent Channels, Kazi Mh Reaz

Doctoral Dissertations

Quantum Key Distribution (QKD) ensures security by relying on the laws of quantum physics rather than the mathematical intricacy of encryption algorithms. The transmission medium is a critical restricting factor for any quantum communication protocol. Fiber-based optical networks suffer great losses, making quantum communication impossible beyond metropolitan scales. Here free-space quantum communication can be a great alternative for long-distance communication. Even though modern Communications are mostly wireless the atmosphere poses a challenge for QKD. So QKD must be resistant to both atmospheric loss and variations in transmittance. In this thesis we conduct an experiment to strengthen the BB84 protocol's resistance …

Evaluation Of Avian Use Of Agricultural Cover Crops During The Winter, Migration Stopover, And The Breeding Season In Tennessee, Brittany Panos

Masters Theses

The U.S. Department of Agriculture Natural Resources Conservation Service administers the cover crop program to provide technical and financial assistance to agricultural producers to sow herbaceous plant seeds to establish cover crops to protect agricultural fields from soil erosion during the non-growing season (late fall through spring). Soil retention and water quality benefits have been documented, but potential benefits for avian wildlife remain largely unknown. I used line-transect avian and vegetation surveys to examine use of cover crop fields by birds during the non-breeding period (winter), migration, and the breeding season. I compared avian use of cover crop fields with …

Easier Air Alert Platform: A Design And Approach To Creating A Distributed Air Quality Monitoring And Alert System, Bryceton Bible

Masters Theses

This thesis presents the design approach, development and implementation of the Elders Alert System for Imminent Environmental Risk (EASIER) project, an air quality monitoring and alert system aiming to improve the health and wellness of under-served elder communities, as a part of the Tennessee Valley Authority Connected Communities initiative for Environmental Justice. The EASIER project provides homes with a fully integrated, connected system capable of real-time air quality monitoring, notifications and descriptions of potential air quality risks, and educational material to empower these community members to take charge of their own air health. Further, EASIER aims to inform relevant family/friends …

Mapping Arbitrary Spiking Neural Networks To The Ravens Neuroprocessor, Jongheon Park

Masters Theses

In neuromorphic computing, a hardware implementation of a spiking neural network is used to provide improved speed and power efficiency over simulations of the networks on a traditional Von Neumann architecture. These hardware implementations employ bio-inspired architecture usually consisting of artificial neurons and synapses implemented in either analog, digital, or mixed-signal circuits. Since these hardware spiking neural networks are designed to support arbitrary networks under the constraints imposed by the available hardware resource, they have to be programmed by off-chip software with awareness of those constraints. The TENNLab research group at the University of Tennessee, Knoxville has recently developed the …

Mercury Biomagnification In Aquatic Food Webs Of Great Smoky Mountains National Park, Zachary Winston Clark

Masters Theses

Mercury is a widespread pollutant threatening human, fish, and ecosystem health on a global scale. Biomagnification concentrates mercury in upper trophic level organisms including predatory fishes, a primary route of dietary mercury exposure for humans. However, mercury biomagnification is not well understood in stream ecosystems, especially in places with no known point sources of contamination. A 2016 study revealed that Smallmouth Bass Micropterus dolomeiu mercury concentrations varied between three streams in Great Smoky Mountains National Park (GSMNP), Tennessee USA. However, the reason for this spatial variation in mercury concentrations is not understood. Our objectives were to (1) measure environmental and …

Winter Roost Selection Of Eastern Red Bats And Impacts Of Non-Growing Season Prescribed Fire On Foraging Activity Of Forest Roosting Bats In Tennessee, Ashley D. Epstein

Masters Theses

With an increase in wind energy development and continued deforestation and habitat degradation, eastern red bats (Lasiurus borealis; LABO) and other migratory foliage roosting bats (hoary bat [Lasiurus cinereus; LACI], silver-haired bat [Lasionycteris noctivagans; LANO]) are at risk of severe population declines, potentially leading to the need for protection under the Endangered Species Act. While studies have been done examining the ecology of these species, there is still a lack of research on winter roosting and foraging behaviors. This research aims to fill some of those knowledge gaps by 1) Examining roost use (i.e., trees vs. litter) …

Genetic Algorithm Optimization Of Experiment Design For Targeted Uncertainty Reduction, Alexander Amedeo Depillis

Masters Theses

Nuclear cross sections are a set of parameters that capture probability information about various nuclear reactions. Nuclear cross section data must be experimentally measured, and this results in simulations with nuclear data-induced uncertainties on simulation outputs. This nuclear data-induced uncertainty on most parameters of interest can be reduced by adjusting the nuclear data based on the results from an experiment. Integral nuclear experiments are experiments where the results are related to many different cross sections. Nuclear data may be adjusted to have less uncertainty by adjusting them to match the results obtained from integral experiments. Different integral experiments will adjust …

Evaluation Of Regression Methods And Competition Indices In Characterizing Height-Diameter Relationships For Temperate And Pantropical Tree Species, Sakar Jha

Masters Theses

Height-diameter relationship models, denoted as H-D models, have important applications in sustainable forest management which include studying the vertical structure of a forest stand, understanding the habitat heterogeneity for wildlife niches, analyzing the growth rate pattern for making decisions regarding silvicultural treatments. Compared to monocultures, characterizing allometric relationships for uneven-aged, mixed-species forests, especially tropical forests, is more challenging and has historically received less attention. Modelling how the competitive interactions between trees of varying sizes and multiple species affects these relationships adds a high degree of complexity. In this study, five regression methods and five distance-independent competition indices were evaluated for …