Physical Sciences and Mathematics Commons^™

Large Deviations For Self Intersection Local Times Of Ornstein-Uhlenbeck Processes, Apostolos Gournaris

Doctoral Dissertations

In the area of large deviations, people concern about the asymptotic computation of small probabilities on an exponential scale. The general form of large deviations can be roughly described as: P{Yn ∈ A} ≈ exp{−bnI(A)} (n → ∞), for a random sequence {Yn}, a positive sequence bn with bn → ∞, and a coefficient I(A) ≥ 0. In applications, we often concern about the probability that the random variables take large values, that is we concern about the P{Yn ≥ λ}, where λ > 0. Here, we consider the Ornstein-Uhlenbeck process, study the properties of the local times and self intersection …

Explicit Constructions Of Canonical And Absolute Minimal Degree Lifts Of Twisted Edwards Curves, William Coleman Bitting Iv

Doctoral Dissertations

Twisted Edwards Curves are a representation of Elliptic Curves given by the solutions of bx^2 + y^2 = 1 + ax^2y^2. Due to their simple and unified formulas for adding distinct points and doubling, Twisted Edwards Curves have found extensive applications in fields such as cryptography. In this thesis, we study the Canonical Liftings of Twisted Edwards Curves and the associated lift of points Elliptic Teichmu ̈ller Lift. The coordinate functions of the latter are proved to be polynomials, and their degrees and derivatives are computed. Moreover, an algorithm is described for explicit computations, and some properties of the general …

The Development Of Tailored Amphiphilic Copolymers For Detergent-Free Integral Membrane Protein Extraction, Cameron Edward Workman

Doctoral Dissertations

Integral membrane proteins are prolific targets for the design, development, and delivery of pharmaceuticals. In fact, over 60% of all currently available drugs target these proteins to accomplish their therapeutic effect. However, integral membrane proteins remain the least characterized class of all proteins, accounting for only ~2% of all solved protein structures. One of the primary reasons for this low number of solved protein structures is that many membrane proteins lose their native conformation when extracted using conventional methods (e.g. detergents), convoluting accurate structure determination. In contrast, amphiphilic styrene-maleic acid copolymers (SMAs) were recently discovered to readily isolate membrane proteins …

Development Of Artificial Lipids For Metal Ion-Responsive Liposomes And Related Medicinal Applications, Ruhani Sagar

Doctoral Dissertations

Liposomes are synthetic vesicles made of phospholipids that are effective for wide-ranging applications in drug delivery and studying biological membranes. Understanding and controlling membrane properties such as fluidity and permeability is crucial for designing liposomes for specific biomedical applications. Pathological changes in these properties can also help us gain insights into disease mechanisms and develop effective treatments. In this dissertation, we describe the design, synthesis, and study of several lipid analogs for a range of applications including liposome triggered cargo release and therapeutic treatment related to lipids.

In Chapters 2-3, we developed smart liposome platforms that can respond to changes …

Probing Gas Transport Structure-Property Relationships In Vinyl-Addition Polynorbornenes, Trevor Jonas Wilson

Doctoral Dissertations

Polynorbornenes are ideal materials for systematic structure-property investigations designed to correlate gas-transport properties to polymer structure. The modular nature of norbornene-derived systems provides a facile route towards the synthesis of diverse polymeric materials, whose structure may be systematically altered through targeted design of monomers, alterations in polymerization mechanism, or some combination of these two strategies. Though many valuable correlations between gas-permeability and polynorbornene structure have been summarized in prior literature, many of these efforts have focused on homopolymer materials with structural changes imposed — almost exclusively — through modifications in substituent chemistry, or through targeted modulation of molar ratios in …

Development Of Surface-Modified Liposomes For Drug Delivery Applications, Megan Louise Qualls

Doctoral Dissertations

Liposomes are spherical vesicles composed of a lipid bilayer membrane that assembles around an internal aqueous core. This duality gives liposomes the ability to encapsulate both hydrophobic cargo within the lipid bilayer and hydrophilic cargo in the aqueous core, making them versatile molecular carriers for drug delivery. Liposome platforms have many advantages and are promising drug delivery carriers, and research is ongoing to improve their designs for continued clinical applications. Many liposome types have been developed, but further work is needed to improve surface modification, site-specific targeting, and triggered cargo release in order to further the therapeutic applications of these …

Interactive Data Analysis Of Multi-Run Performance Data, Vanessa Lama

Masters Theses

Multi-dimensional performance data analysis presents challenges for programmers, and users. Developers have to choose library and compiler options for each platform, analyze raw performance data, and keep up with new technologies. Users run codes on different platforms, validate results with collaborators, and analyze performance data as applications scale up. Site operators use multiple profiling tools to optimize performance, requiring the analysis of multiple sources and data types. There is currently no comprehensive tool to support the structured analysis of unstructured data, when holistic performance data analysis can offer actionable insights and improve performance. In this work, we present thicket, a …

Impact Of Cover Crop Species Diversity On Soil Nutrient Availability And Crop Productivity, Amanda Kramer

Masters Theses

Cover crops provide multiple environmental benefits that improve both soil and water quality; however, farmers only utilize them on approximately 5% of harvested U.S. cropland. Low adoption rates are attributed to yield impact concerns, seed and planting costs, and lack of advocacy. This study, which began in October 2019, assessed the effects of nitrogen rate and cover crop diversity on weed biomass, soil coverage, in-situ residue decomposition, soil nitrogen and phosphorus availability, and cash crop yield to better understand the costs and benefits of cover crop adoption at two locations in Tennessee (Milan and Spring Hill). Treatments were replicated 4 …

Coefficients Of Modular Forms And Applications To Partition Theory, Michael Anthony Hanson

Doctoral Dissertations

We begin with an overview of the theory of modular forms as well as some relevant sub-topics in order to discuss three results: the first result concerns positivity of self-conjugate t-core partitions under the assumption of the Generalized Riemann Hypothesis; the second result bounds certain types of congruences called "Ramanujan congruences" for an infinite class of eta-quotients - this has an immediate application to a certain restricted partition function whose congruences have been studied in the past; the third result strengthens a previous result that relates weakly holomorphic modular forms to newforms via p-adic limits.

Unlocking The Potential Of Machine Learning In The Derivation Of Low-Energy Models For Metallic Magnets, Vikram Sharma

Doctoral Dissertations

Condensed matter physics often grapples with complex many-particle problems lacking definitive closed-form solutions, necessitating approximation strategies to investigate low-energy sectors of the Hilbert space. Perturbation theory, though widely used for this purpose, is limited when expansion terms diverge. This work introduces a machine learning (ML) assisted protocol to extract effective low-energy models for lattice models of fermions interacting with classical fields, specifically focusing on the Kondo Lattice Model (KLM).

Skyrmions, featuring whirling spin texture and topological protection, are promising candidates for future spintronic devices. Materials featuring conduction electrons coupled to localized $f$-electrons' net moment are ideal for realizing skyrmions and …

A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb

Masters Theses

One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …

Evaluating Bulk Carbon And Nitrogen Isotope Compositions Of Acidic Hydrothermal Sediments On Earth– Implications For Mars Astrobiology, Chance Sturrup

Masters Theses

Carbon isotopes have been widely used as unique biosignatures because biologic processes commonly result in distinctive negative delta ¹³C values (-35 to -10 ‰) within organic material on Earth. However, the bulk delta ¹³C analysis in Gale crater sediments on Mars revealed a wider range of values, from -25 to +56 ‰ (Franz et al., 2020), which suggests a more complex origin. To determine if bulk isotope analysis can be successfully used to detect a microbial signature in a martian analog environment, we analyzed concentrations and isotope compositions of C within hydrothermal sediments in Iceland (Námafjall, Krýsuvík, Hveragerdi) …

Development And Study Of Small Database For The Activation Of Nitrous Oxide Towards Formation Of Iron(Iv)-Oxo Species, Tobias Barthalomew Robertson

Masters Theses

Nitrous oxide (N₂O) can undergo an oxygen atom transfer (OAT) reaction resulting in inert nitrogen gas (N₂O) while transferring an oxygen atom to a molecular complex or material. This process is of catalytic importance since this OAT reaction can be leveraged to form iron(IV)-oxo sites, which are known to be catalytic intermediates. Here, an investigation of the ligand field effects on primarily iron(II) complexes for the formation of iron(IV)-oxo sites with nitrous oxide as the oxidant is reported. An initial database of sixty-four molecular complexes with ligand environments varying in field strength and coordination geometry was …

Survey Of Input Modalities In The Western World, John Ezat Sadik

Masters Theses

Having your account compromised can lead to serious complications in your life. One
way accounts become compromised is through the security risks associated with weak
passwords and reused passwords [22,23]. In this thesis, we seek to understand how
entering passwords on non-PC devices contributes to the problems of weak and reused
passwords. To do so, we conducted a survey that was distributed to people in the
the Western World. In our survey results, we found that users commented about
how the current password model was not created with a variety of device types in
mind, which created frustrations and complexity …

Analysis Of A Controlled Approximation For Explicit Integrations Of Stiff Thermonuclear Networks, Nicholas Brey

Masters Theses

The current standard method to solve stiff coupled differential equations relies on implicit integration methods. Explicit methods are generally avoided due to the extremely small and limiting timesteps they allow when the equations are stiff. However, implicit methods are computationally expensive because of the complex calculations that need to be done at each time step. An explicit integration method can do these calculations quicker and, if allowed to take comparable timesteps to the implicit ones, would allow the entire calculation to be done faster. Previous work by Dr. Guidry, Dr. Endeve, Dr. Hix and Dr. Billings has shown that, in …

Adaptive And Topological Deep Learning With Applications To Neuroscience, Edward Mitchell

Doctoral Dissertations

Deep Learning and neuroscience have developed a two way relationship with each informing the other. Neural networks, the main tools at the heart of Deep Learning, were originally inspired by connectivity in the brain and have now proven to be critical to state-of-the-art computational neuroscience methods. This dissertation explores this relationship, first, by developing an adaptive sampling method for a neural network-based partial different equation solver and then by developing a topological deep learning framework for neural spike decoding. We demonstrate that our adaptive scheme is convergent and more accurate than DGM -- as long as the residual mirrors the …

Computational Aspects Of Mixed Characteristic Witt Vectors And Denominators In Canonical Liftings Of Elliptic Curves, Jacob Dennerlein

Doctoral Dissertations

Given an ordinary elliptic curve E over a field 𝕜 of characteristic p, there is an elliptic curve E over the Witt vectors W(𝕜) for which we can lift the Frobenius morphism, called the canonical lifting of E. The Weierstrass coefficients and the elliptic Teichmüller lift of E are given by rational functions over 𝔽_p that depend only on the coefficients and points of E. Finotti studied the properties of these rational functions over fields of characteristic p ≥ 5. We investigate the same properties for fields of characteristic 2 and 3, make progress on …

A Natural Resource Management Plan For The Historic Ramsey House, Brianna Saylor, Cole Oakey, Devin Hevener, Everett Williams, Haley Cox, Rachel Carpenter

Chancellor’s Honors Program Projects

No abstract provided.

Anxiety-Like Behavior In C57bl/6j Mice Is Sexually Dimorphic And Altered By Buprenorphine, Ohm Sharma

Chancellor’s Honors Program Projects

No abstract provided.

Pressure - Temperature Phase Diagram Of Crsite3, J L. Musfeldt, David Mandrus, Zhenxian Liu

Chemistry Publications and Other Works

van der Waals solids are well known to host remarkable phase diagrams with competing phases, unusual energy transfer processes, and elusive states of matter. Among this class of materials, chalcogenides have emerged as the most flexible and relevant platforms for unraveling charge-structure-function relationships. In order to explore the properties of complex chalcogenides under external stimuli, we measured the far infrared spectroscopic response of CrSiTe3 under extreme pressure-temperature conditions. Analysis of the 368 cm−1 Si-Te stretching mode and the manner in which it is screened by the closure of the indirect gap reveals that the insulator-metal transition takes place immediately after …

Core-Collapse Supernova Simulations With Spectral Two-Moment Neutrino Transport, Ran Chu

Doctoral Dissertations

The primary focus of this dissertation is to develop a next-generation, state-of-the-art neutrino kinetics capability that will be used in the context of the next-generation, state-of-the-art core-collapse supernova (CCSN) simulation frameworks \thornado\ and \FLASH.\index{CCSN} \thornado\ is a \textbf{t}oolkit for \textbf{h}igh-\textbf{or}der \textbf{n}eutrino-r\textbf{ad}iation hydr\textbf{o}dynamics, which is a collection of modules that can be incorporated into a simulation code/framework, such as \FLASH, together with a nuclear equation of state (EOS)\index{EOS} library, such as the \WeakLib\ EOS tables. The first part of this work extends the \WeakLib\ code to compute neutrino interaction rates from~\cite{Bruenn_1985} and produce corresponding opacity tables.\index{Bruenn 1985} The processes of emission, …

Constrained Collective Movement In Human-Robot Teams, Joshua Fagan

Doctoral Dissertations

This research focuses on improving human-robot co-navigation for teams of robots and humans navigating together as a unit while accomplishing a desired task. Frequently, the team’s co-navigation is strongly influenced by a predefined Standard Operating Procedure (SOP), which acts as a high-level guide for where agents should go and what they should do. In this work, I introduce the concept of Constrained Collective Movement (CCM) of a team to describe how members of the team perform inter-team and intra-team navigation to execute a joint task while balancing environmental and application-specific constraints. This work advances robots’ abilities to participate along side …

Elucidating The Importance Of Structure, Surfaces, And Interfaces In Polymer Nanoparticles And Nanocomposites, Jacob E. Fischer

Doctoral Dissertations

This dissertation details research conducted to elucidate the importance of structure, surfaces, and interfaces in both polymeric nanoparticles and polymer nanocomposites. The fundamental understanding that is garnered in these studies provides a foundation to rationally develop nanocomposites tailored for unique functionalities, performance and applications.

Soft polymeric nanoparticles, have shown to imbue non-traditional diffusive properties, the strength of which decreases with crosslinking density of the nanoparticle. The crosslinking dependent morphology of these nanoparticles is first characterized in a dilute solution of good solvent (Chapter 2). The scattering results revealed that the structure ranges from a swollen polymer in good solvent (0% …

Controlling Polymer Molecular Structure And Morphology: From Illumination Of Conjugated Polymers To Polymer Chain Depolymerization, Josh Moncada

Doctoral Dissertations

Polymers remain a prominent component of our lives, and finding methods to control their structure or morphology are needed to tune material properties. This dissertation reports methods to alter the conformation, morphology, or structure of polymeric materials. Chapter two describes the impact of exposure to white light during annealing of conjugated polymer blends on their morphology and optoelectronic performance. The observed changes in the morphology correlate strongly to the variation in photoluminescence (PL) with illumination, including that the PL varies less with illumination at higher Poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] loadings, offering foundational understanding to guide the structure and optoelectronic performance of conjugated polymer …

Intra-Skeletal Variation In Stable Isotopes Through Non-Destructive Approaches: Applications Of The Patterns Of Skeletal Remodeling To Biological Anthropology, Armando Anzellini

Doctoral Dissertations

Stable isotope analysis is a well-established method in biological anthropology used to deliver data on residence, diet, and life history. Samples for these analyses are often collected from the diaphyses of long bones with an assumption of an expected rate of turnover between five and ten years, depending on the skeletal element. However, the biological foundations of this assumption are still uncertain, especially concerning the intra-skeletal and intra-element variation of isotopic signatures that may relate to patterns of remodeling. Exploring these gaps in intra-element isotopic variation requires fine-grained work using multiple bones from multiple individuals, but such work is limited …

Light Matter Interactions: A Study Of Soft Materials Using Linear And Nonlinear Spectroscopy, Muhammad Redwan Hassan

Doctoral Dissertations

The adoption of complex fluids for various industrial applications is becoming normal. Complex fluids offer tunability, wide range solubility, and chemical and thermal stability which are the factors that conventional polar and non-polar solvents often lack. However, fundamental studies of these fluid systems are still lacking which is limiting the appropriate use of these complex fluids in many applications. The goal of this dissertation was to study and characterize complex fluids for application in electrolytes for redox flow batteries. Chapter 3 and chapter 4 feature the study of microemulsions and deep eutectic solvents (DES) by fluorescence techniques. Fluorescence studies of …

Geochemical And Climatic Controls On The Sulfur Cycle In Volcanic Settings: Implications For The Origin Of Sulfur-Rich Deposits Investigated By The Spirit And Opportunity Rovers On Mars, Rhianna D. Moore

Doctoral Dissertations

On Earth, volcanic activity with elevated sulfur (S) degassing in the presence of water leads to the formation of hydrothermal deposits enriched in S-bearing minerals. Similar processes may have been an important source of S on Mars. The landing sites of Gusev crater and Meridiani Planum investigated by the Spirit and Opportunity rovers, respectively, showed elevated SO₄^2- [sulfate] concentrations, suggesting high- and low-temperature aqueous processes. However, the SO₄^2- contribution from subsequent aqueous weathering of hydrothermal S deposits has been poorly constrained, thus its importance to regional S cycling in the landing sites is unclear. In this …

Analytical Techniques For The Analysis Of Uranium Bearing Materials, Nathaniel D. Fletcher

Doctoral Dissertations

The interest in the use of nuclear power has increased drastically in recent years. This is due to significantly increased efficiency at producing energy when compared to fossil fuels. With the increased use of nuclear power comes an increased need to for monitor for uranium bearing materials outside of regulatory control. This dissertation covers four projects aimed at improving the analysis of these materials. The first projects aims to develop a method that allows for the analysis of elements that exist in nature as anions by triple quadrupole ICP – MS. This would allow for the ability to measure more …

Towards Reduced-Order Model Accelerated Optimization For Aerodynamic Design, Andrew L. Kaminsky

Doctoral Dissertations

The adoption of mathematically formal simulation-based optimization approaches within aerodynamic design depends upon a delicate balance of affordability and accessibility. Techniques are needed to accelerate the simulation-based optimization process, but they must remain approachable enough for the implementation time to not eliminate the cost savings or act as a barrier to adoption.

This dissertation introduces a reduced-order model technique for accelerating fixed-point iterative solvers (e.g. such as those employed to solve primal equations, sensitivity equations, design equations, and their combination). The reduced-order model-based acceleration technique collects snapshots of early iteration (pre-convergent) solutions and residuals and then uses them to project …

Enhancing The Performance Of The Mtcnn For The Classification Of Cancer Pathology Reports: From Data Annotation To Model Deployment, Kevin De Angeli

Doctoral Dissertations

Information contained in electronic health records (EHR) combined with the latest advances in machine learning (ML) have the potential to revolutionize the medical sciences. In particular, information contained in cancer pathology reports is essential to investigate cancer trends across the country. Unfortunately, large parts of information in EHRs are stored in the form of unstructured, free-text which limit their usability and research potential. To overcome this accessibility barrier, cancer registries depend on expert personnel who read, interpret, and extract relevant information. Naturally, as the number of stored pathology reports increases every day, depending on human experts presents scalability challenges. Recently, …