Physical Sciences and Mathematics Commons^™

Multi-Scale Simulations Of Dynamic Protein Structures And Interactions, Yumeng Zhang

Doctoral Dissertations

Intrinsically disordered proteins (IDPs) are functional proteins that lack stable tertiary structures in the unbound state. They frequently remain dynamic even within specific complexes and assemblies. IDPs are major components of cellular regulatory networks and have been associated with cancers, diabetes, neurodegenerative diseases, and other human diseases. Computer simulations are essential for deriving a molecular description of the disordered protein ensembles and dynamic interactions for mechanistic understanding of IDPs in biology, diseases, and therapeutics. However, accurate simulation of the heterogeneous ensembles and dynamic interactions of IDPs is extremely challenging because of both the prohibitive computational cost and demanding force field …

An Efficient Privacy-Preserving Framework For Video Analytics, Tian Zhou

Doctoral Dissertations

With the proliferation of video content from surveillance cameras, social media, and live streaming services, the need for efficient video analytics has grown immensely. In recent years, machine learning based computer vision algorithms have shown great success in various video analytic tasks. Specifically, neural network models have dominated in visual tasks such as image and video classification, object recognition, object detection, and object tracking. However, compared with classic computer vision algorithms, machine learning based methods are usually much more compute-intensive. Powerful servers are required by many state-of-the-art machine learning models. With the development of cloud computing infrastructures, people are able …

Automated Identification And Mapping Of Interesting Mineral Spectra In Crism Images, Arun M. Saranathan

Doctoral Dissertations

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has proven to be an invaluable tool for the mineralogical analysis of the Martian surface. It has been crucial in identifying and mapping the spatial extents of various minerals. Primarily, the identification and mapping of these mineral spectral-shapes have been performed manually. Given the size of the CRISM image dataset, manual analysis of the full dataset would be arduous/infeasible. This dissertation attempts to address this issue by describing an (machine learning based) automated processing pipeline for CRISM data that can be used to identify and map the unique mineral signatures present in …

Data To Science With Ai And Human-In-The-Loop, Gustavo Perez Sarabia

Doctoral Dissertations

AI has the potential to accelerate scientific discovery by enabling scientists to analyze vast datasets more efficiently than traditional methods. For example, this thesis considers the detection of star clusters in high-resolution images of galaxies taken from space telescopes, as well as studying bird migration from RADAR images. In these applications, the goal is to make measurements to answer scientific questions, such as how the star formation rate is affected by mass, or how the phenology of bird migration is influenced by climate change. However, current computer vision systems are far from perfect for conducting these measurements directly. They may …

Policy Gradient Methods: Analysis, Misconceptions, And Improvements, Christopher P. Nota

Doctoral Dissertations

Policy gradient methods are a class of reinforcement learning algorithms that optimize a parametric policy by maximizing an objective function that directly measures the performance of the policy. Despite being used in many high-profile applications of reinforcement learning, the conventional use of policy gradient methods in practice deviates from existing theory. This thesis presents a comprehensive mathematical analysis of policy gradient methods, uncovering misconceptions and suggesting novel solutions to improve their performance. We first demonstrate that the update rule used by most policy gradient methods does not correspond to the gradient of any objective function due to the way the …

Multi-Slam Systems For Fault-Tolerant Simultaneous Localization And Mapping, Samer Nashed

Doctoral Dissertations

Mobile robots need accurate, high fidelity models of their operating environments in order to complete their tasks safely and efficiently. Generating these models is most often done via Simultaneous Localization and Mapping (SLAM), a paradigm where the robot alternatively estimates the most up-to-date model of the environment and its position relative to this model as it acquires new information from its sensors over time. Because robots operate in many different environments with different compute, memory, sensing, and form constraints, the nature and quality of information available to individual instances of different SLAM systems varies substantially. `One-size-fits-all' solutions are thus exceedingly …

Quantum Chaos, Integrability, And Hydrodynamics In Nonequilibrium Quantum Matter, Javier Lopez Piqueres

Doctoral Dissertations

It is well-known that the Hilbert space of a quantum many-body system grows exponentially with the number of particles in the system. Drive the system out of equilibrium so that the degrees of freedom are now dynamic and the result is an extremely complicated problem. With that comes a vast landscape of new physics, which we are just recently starting to explore. In this proposal, we study the dynam- ics of two paradigmatic classes of quantum many-body systems: quantum chaotic and integrable systems. We leverage certain tools commonly employed in equilibrium many-body physics, as well as others tailored to the …

High Resolution Mass Spectrometry As A Platform For The Analysis Of Polyoxometalates, Their Solution Phase Dynamics, And Their Biological Interactions., Daniel T. Favre

Doctoral Dissertations

Polyoxometalates (POMs) are a class of inorganic molecule of increasing interest to the inorganic, bioinorganic and catalytic communities among many others. While their prevalence in research has increased, tools and methodologies for the analysis of their fundamental characteristics still need further development. Decavanadate (V10) specifically has been postulated to have several unique properties that have not been confirmed independently. Mass spectrometry (MS) and its ability to determine the composition of solution phase species by both mass and charge is uniquely well suited to the analysis of POMs. In this work we utilized high-resolution mass spectrometry to characterize V10 in aqueous …

Toltec: A New Multichroic Imaging Polarimeter For The Large Millimeter Telescope, Nat S. Denigris

Doctoral Dissertations

The TolTEC camera is a new millimeter-wave imaging polarimeter designed to fill the focal plane of the 50-m diameter Large Millimeter Telescope (LMT). Combined with the LMT, TolTEC offers high angular resolution (5", 6.3", 9.5") for simultaneous, polarization-sensitive observations in its three wavelength bands: 1.1, 1.4, and 2.0 mm. Additionally, TolTEC is designed to reach groundbreaking mapping speeds in excess of 1 deg²/mJy²/hr, which will enable the completion of deep surveys of large-scale structure, galaxy evolution, and star formation that are currently limited when considering practical observation times for other ground-based observatories. This thesis covers the …

Development Of A Decision Support System Webtool For Historic And Future Low Flow Estimation In The Northeast United States With Applications Of Machine Learning For Advancing Physical And Statistical Methodologies, Andrew F. Delsanto

Doctoral Dissertations

Droughts are a global challenge and anthropogenic climate change is expected to increase the frequency and severity of extreme low flow events. A major challenge for resource managers is how best to incorporate future climate change projections into low flow event estimations, especially in ungaged basins. Using both physically based hydrology models and statistical models, this dissertation contributes novel methodologies to three key challenges associated with 7-day, 10-year low flow (7Q10) estimation in the northeast United States. Chapter 2 builds upon statistically based 7Q10 estimation in ungaged basins by comparing multiple machine learning algorithms to classical statistical methodologies. This chapter’s …

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

Doctoral Dissertations

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

Synthesis And Characterization Of Quantum Materials, Yunsheng Qiu

Doctoral Dissertations

"In this study, attempts were made to grow quantum materials that have recently undergone a profound change of perspective. These materials are involved in intricate macroscopic properties rooted in the subtle nature of quantum physics. To explore our understanding of quantum materials, this study includes three projects: Magnetic Topological Insulators, Topological Superconductors, and high-temperature superconductors.

A Cr-doped Sb₂Te₃ is added to the category for the magnetic topological insulators project. Their transport properties are studied, and the origin of ferromagnetism is studied. Anomalous Hall effect is observed in the Hall measurements, and serval factors (cooling rate, dopant deficiency) …

Design, Synthesis, And Characterization Of Complex Chalcogenides For Energy Storage And Energy Conversion Applications, Srikanth Balijapelly

Doctoral Dissertations

"Through this investigation, complex chalcogenides with the combination of main group metals, transition metals, and rare earth metals have been synthesized using the building block approach and their structure-property relationships are evaluated. The main emphasis of research is on rationally designing new materials for applications in sodium and lithium ion conducting solid electrolytes, cathodes, thermoelectrics, and nonlinear optics. Along with the experimental studies, theoretical calculations are also employed to better understand the physicochemical properties of the synthesized compounds.

The first part of the research will discuss designing alkali ion containing complex chalcogenides using the building block approach. This investigation resulted …

Chirality Determination Using Three-Wave Mixing Microwave Spectroscopy, Nicole Taylor Moon

Doctoral Dissertations

"Rotational spectroscopy has established itself as a reliable gas-phase spectroscopic technique for the structural determination of molecules. This reliability has stemmed from both advancements in microwave technology and a willingness from the community to push the boundaries of the field. In this dissertation, the boundaries are tested in both how well the technique can determine the structure of molecules exhibiting large amplitude motion and through chirality determination. The first half of this dissertation explores the use of deep averaging to determine the structure of silicon containing molecules in collaboration with Dr. Guirgis from the College of Charleston. For each of …

Experimental Investigation Of High-Temperature Brine-Shale Interactions, Anna Atasha Hoffmann

Doctoral Dissertations

"Hydrofracturing (fracking), a common practice in the Petroleum Industry to induce or improve fluid flow in tight formations, creates chemical disequilibrium that further alters the porosity and permeability of host rocks and results in the production of saline and contaminated produced waters (PW). The PW of the Tuscaloosa Marine Shale (TMS) are Na-Ca-Mg-K-Cl brines with mean concentrations of approximately 16% Total Dissolved Solids (TDS) and circumneutral pH. Analysis of composition suggests the PW result from a 20 to 80% dilution of formation waters (relict brines of the Louann Salt) by fracking fluid. Trace element concentrations generally show moderate to strong …

Re-Evaluating Missouri’S Strategic Element Potential: A Geochemical Study Of The Mesoproterozoic Fe-Cu-Co-Ree Deposits In Southeast Missouri, Usa, Brandon James Sullivan

Doctoral Dissertations

"Iron-oxide-copper-gold (IOCG) deposits are poorly understood mineral systems. For example, we do not know why Cu- and Co-rich IOCG deposits typically occur proximal to Fe ore deposits that are notably Cu and Co-poor, such as Iron Oxide Apatite (IOA) deposits. To better understand the formation of IOA and IOCG deposits in Missouri, USA, this PhD thesis examines the genesis of the Kratz Spring IOA and the Boss Central Dome IOCG deposits. This study presents the first constraints on formation conditions and fluid sources in the studied deposits using integrated petrographic, mineral composition, and Fe isotope analyses of oxide minerals. Observations …

The Science Of Gravitational-Wave Sources And Beyond Compact Binary Coalescences, Yanyan Zheng

Doctoral Dissertations

"This work focuses on the field of gravitational-wave astronomy by extending the scope of detectable sources beyond compact binary coalescences, All the gravitational-wave detections so far come from compact binary coalescences. Focusing on core-collapse supernovae as promising sources for short gravitational-wave transients, this work reports optically targeted searches for gravitational-wave emitted by core-collapse supernovae during the third observing run of the LIGO and Virgo detectors. It also predicts the search sensitivity for the ongoing fourth and forthcoming fifth observing runs. Moreover, the work introduces a novel computational framework for testing the spatial distribution of binary black hole sources, allowing for …

Generalized Differentiable Neural Architecture Search With Performance And Stability Improvements, Emily J. Herron

Doctoral Dissertations

This work introduces improvements to the stability and generalizability of Cyclic DARTS (CDARTS). CDARTS is a Differentiable Architecture Search (DARTS)-based approach to neural architecture search (NAS) that uses a cyclic feedback mechanism to train search and evaluation networks concurrently, thereby optimizing the search process by enforcing that the networks produce similar outputs. However, the dissimilarity between the loss functions used by the evaluation networks during the search and retraining phases results in a search-phase evaluation network, a sub-optimal proxy for the final evaluation network utilized during retraining. ICDARTS, a revised algorithm that reformulates the search phase loss functions to ensure …

Material Formulation And Process Optimization Towards Fabricating Robust 3d Printed Structures, Austin Riggins

Doctoral Dissertations

This dissertation focuses on understanding and addressing the fundamental physicochemical phenomena that lead to weak interfaces and structural warpage in material extrusion 3D printing. Polymeric feedstocks used for this manufacturing technique were manipulated through the incorporation of additives that alter the dynamics of the matrix during and after printing. In Chapter II, adhesion between layers of structures printed from PEEK was strengthened through a combination of low-molecular weight additive incorporation and post-printing thermal annealing. Chapter III reports a method for decreasing the irreversible thermal strain of structures printed from poly(lactic acid) by introducing nanographene and photoinitiator additives into the feedstock …

Static And Dynamic State Estimation Applications In Power Systems Protection And Control Engineering, Ibukunoluwa Olayemi Korede

Doctoral Dissertations

The developed methodologies are proposed to serve as support for control centers and fault analysis engineers. These approaches provide a dependable and effective means of pinpointing and resolving faults, which ultimately enhances power grid reliability. The algorithm uses the Least Absolute Value (LAV) method to estimate the augmented states of the PCB, enabling supervisory monitoring of the system. In addition, the application of statistical analysis based on projection statistics of the system Jacobian as a virtual sensor to detect faults on transmission lines. This approach is particularly valuable for detecting anomalies in transmission line data, such as bad data or …

Atomic-Level Mechanisms Of Fast Relaxation In Metallic Glasses, Leo W. Zella

Doctoral Dissertations

Glasses are ubiquitous in daily life and have unique properties which are a consequence of the underlying disordered structure. By understanding the fundamental processes that govern these properties, we can modify glasses for desired applications. Key to understanding the structure-dynamics relationship in glasses is the variety of relaxation processes that exist below the glass transition temperature. Though these relaxations are well characterized with macroscopic experimental techniques, the microscopic nature of these relaxations is difficult to elucidate with experimental tools due to the requirements of timescale and spatial resolution. There remain many questions regarding the microscopic nature of relaxation in glass …

Exploring Soil Microbial Dynamics In Southern Appalachian Forests: A Systems Biology Approach To Prescribed Fire Impacts, Saad Abd Ar Rafie

Doctoral Dissertations

Prescribed fires in Southern Appalachian forests are vital in ecosystem management and wildfire risk mitigation. However, understanding the intricate dynamics between these fires, soil microbial communities, and overall ecosystem health remains challenging. This dissertation addresses this knowledge gap by exploring selected aspects of this complex relationship across three interconnected chapters.

The first chapter investigates the immediate effects of prescribed fires on soil microbial communities. It reveals subtle shifts in porewater chemistry and significant increases in microbial species richness. These findings offer valuable insights into the interplay between soil properties and microbial responses during the early stages following a prescribed fire. …

A Measurement Of Neutron Polarization And Transmission For The Nedm@Sns Experiment, Kavish Imam

Doctoral Dissertations

The D.O.E Nuclear Science Advisory Committee Long Range Plan has called for experimental programs to explore fundamental symmetry violations and their implications in nuclear, particle and cosmological physics. The neutron electric dipole moment experiment at the Spallation Neutron Source (nEDM@SNS) aims to search for new physics in the Time-reversal (T) and Charge-Parity (CP) symmetry violating sector by setting a new limit on the nEDM down to a few x 10^-28 e·cm using a novel cryogenic technique, which combines the unique properties of polarized Ultracold Neutrons (UCN), polarized ³He, and superfluid ⁴He. The experiment will employ a cryogenic …

Towards Safer Code Reuse: Investigating And Mitigating Security Vulnerabilities And License Violations In Copy-Based Reuse Scenarios, David Reid

Doctoral Dissertations

Background: A key benefit of open source software is the ability to copy code to reuse in other projects. Code reuse provides benefits such as faster development time, lower cost, and improved quality. There are several ways to reuse open source software in new projects including copy-based reuse, library reuse, and the use of package managers. This work specifically looks at copy-based code reuse.

Motivation: Code reuse has many benefits, but also has inherent risks, including security and legal risks. The reused code may contain security vulnerabilities, license violations, or other issues. Security vulnerabilities may persist in projects that copy …

Characterizing Silicate Materials Via Raman Spectroscopy And Machine Learning: Implications For Novel Approaches To Studying Melt Dynamics, Blake O. Ladouceur

Doctoral Dissertations

Silicate melt characteristics impose dramatic influence over igneous processes that operate, or have operated on, differentiated bodies: such as the Earth and Mars. Current understanding of these melt properties, such as composition, primarily comes from investigations on their volcanic byproducts. Therefore, it is imperative to innovate on modalities capable of constraining melt information in environments where a reliance on laboratory methods is severed. Recent investigations have turned to Raman Spectroscopy and amorphous volcanics as a suitable pairing for exploring these ideas. Silicate glasses are a proxy for igneous melts; and Raman spectroscopy is a robust analytical technique capable of operating …

Integration Of Raman Spectroscopy And Python-Based Data Analysis For Advancing Neurobiological Research, Natalie E. Dunn

Doctoral Dissertations

The field of Raman spectroscopy continues to expand into biological applications due to its usefulness as a non-invasive technique that can be utilized qualitatively and quantitatively. However, the inherent weakness of Raman scattering leads to the need for each collected spectra to undergo a preprocessing step to remove noise, background drift, and cosmic rays. Biological research in particular needs large datasets due to the increased variability in samples. As datasets grow, the need to perform preprocessing on each individual spectra becomes daunting. Often, these steps are done by hand with the help of specialized software programs. Preprocessing can be accelerated …

Towards Expressive And Versatile Visualization-As-A-Service (Vaas), Tanner C. Hobson

Doctoral Dissertations

The rapid growth of data in scientific visualization has posed significant challenges to the scalability and availability of interactive visualization tools. These challenges can be largely attributed to the limitations of traditional monolithic applications in handling large datasets and accommodating multiple users or devices. To address these issues, the Visualization-as-a-Service (VaaS) architecture has emerged as a promising solution. VaaS leverages cloud-based visualization capabilities to provide on-demand and cost-effective interactive visualization. Existing VaaS has been simplistic by design with focuses on task-parallelism with single-user-per-device tasks for predetermined visualizations. This dissertation aims to extend the capabilities of VaaS by exploring data-parallel visualization …

Short Range Correlation Measurements In The Quasielastic Region With An 11 Gev Beam, Casey Morean

Doctoral Dissertations

Electron scattering is a significant means of studying internal high momentum
nucleon and quark distributions in nuclei. Thomas Jefferson National Accelerator
Facility (JLab) with its 11GeV beam is capable of studying high momentum nucleons
with unmatched precision. The role of short range nucleon configurations and
quark distributions is significant for understanding the dynamics of nuclei and their
underlying components. Scattering cross section measurements in the kinematic
regime x > 1, where the free nucleon is forbidden, are sensitive to high momentum
nucleons, which are believed to come from short range correlations (SRCs). SRCs are
strongly interacting, high momentum nucleons with a …

Exact Models, Heuristics, And Supervised Learning Approaches For Vehicle Routing Problems, Zefeng Lyu

Doctoral Dissertations

This dissertation presents contributions to the field of vehicle routing problems by utilizing exact methods, heuristic approaches, and the integration of machine learning with traditional algorithms. The research is organized into three main chapters, each dedicated to a specific routing problem and a unique methodology. The first chapter addresses the Pickup and Delivery Problem with Transshipments and Time Windows, a variant that permits product transfers between vehicles to enhance logistics flexibility and reduce costs. To solve this problem, we propose an efficient mixed-integer linear programming model that has been shown to outperform existing ones. The second chapter discusses a practical …

Generative Adversarial Game With Tailored Quantum Feature Maps For Enhanced Classification, Anais Sandra Nguemto Guiawa

Doctoral Dissertations

In the burgeoning field of quantum machine learning, the fusion of quantum computing and machine learning methodologies has sparked immense interest, particularly with the emergence of noisy intermediate-scale quantum (NISQ) devices. These devices hold the promise of achieving quantum advantage, but they grapple with limitations like constrained qubit counts, limited connectivity, operational noise, and a restricted set of operations. These challenges necessitate a strategic and deliberate approach to crafting effective quantum machine learning algorithms.

This dissertation revolves around an exploration of these challenges, presenting innovative strategies that tailor quantum algorithms and processes to seamlessly integrate with commercial quantum platforms. A …