Physical Sciences and Mathematics Commons^™

Progress Towards Next Generation Modulators Of Ctbp's Oncogenic Effects, Jacqueline L. West

Theses and Dissertations

Human C-terminal binding proteins (CtBP1 and CtBP2) are transcriptional coregulators of multiple genes in the human genome, including tumor suppressor genes (e.g., Bik, PTEN, BRCA1, and E-cadherin) as well as oncogenes (e.g. MDR1 and Tiam1). Both homologues of CtBP are overexpressed in many types of cancer, including breast cancer (92%), ovarian cancer (83%), colorectal cancer (64%), hepatocellular carcinoma (60%), gastric cancer, prostate cancer, and pancreatic adenocarcinoma. Further, expression levels of CtBP correlate with worse prognostic outcomes and more aggressive tumor features because it promotes proliferation, epithelial-mesenchymal transition, and cancer stem cell self-renewal activity.

Our laboratory has identified a lead inhibitor …

Role Of Inhibition And Spiking Variability In Ortho- And Retronasal Olfactory Processing, Michelle F. Craft

Theses and Dissertations

Odor perception is the impetus for important animal behaviors, most pertinently for feeding, but also for mating and communication. There are two predominate modes of odor processing: odors pass through the front of nose (ortho) while inhaling and sniffing, or through the rear (retro) during exhalation and while eating and drinking. Despite the importance of olfaction for an animal’s well-being and specifically that ortho and retro naturally occur, it is unknown whether the modality (ortho versus retro) is transmitted to cortical brain regions, which could significantly instruct how odors are processed. Prior imaging studies show different …

Analysis Of Microdroplets And Microorganisms By Single Entity Electrochemistry, Junaid U. Ahmed

Theses and Dissertations

Single Entity Electrochemistry (SEE) is an emerging electrochemical technique that has been used to characterize discrete entities by measuring the change in current or potential during individual stochastic events (collision or adsorption) of an entity with an ultramicroelectrode (UME) of similar dimensions. The shape and magnitude of the SEE signal depend on the underlying mechanism of interaction with the UME surface. There is a critical need for quantitative models that correlate the SEE signal with properties of the entity-UME system, including effects of acquisition instrumentation, to prevent misinterpretation of data.

This research focused on integrated experiments and simulations to quantify …

Estimating The Statistics Of Operational Loss Through The Analyzation Of A Time Series, Maurice L. Brown

Theses and Dissertations

In the world of finance, appropriately understanding risk is key to success or failure because it is a fundamental driver for institutional behavior. Here we focus on risk as it relates to the operations of financial institutions, namely operational risk. Quantifying operational risk begins with data in the form of a time series of realized losses, which can occur for a number of reasons, can vary over different time intervals, and can pose a challenge that is exacerbated by having to account for both frequency and severity of losses. We introduce a stochastic point process model for the frequency distribution …

Molten Salt Technologies For Advanced Nuclear Fuel Cycles And Molten Salt Reactors, Dimitris Killinger

Theses and Dissertations

This dissertation provides five topics—an assessment of different monitoring and analytical techniques often cited in the literature for molten salt systems and designs for nuclear engineering applications. First, we explored commonly used materials for quasi-reference electrodes in molten chloride salts. Second, the limitations of the electrochemical analysis known as cyclic voltammetry due to the concentration of uranium(III) present were being investigated. Third, we provided an experimental assessment on the development of a spectroelectrochemical cell for interrogating various spectroelectrochemical techniques, namely chronoabsorptometry and chronofluorometry, and their limitations due to the presence of uranium(III) ions. Fourth, a study on the corrosion resistance …

Antiviral Effects Of Metalloshielding: Differential Antiviral Activity Of Polynuclear Platinum And Cobalt Compounds, Mary Zoepfl

Theses and Dissertations

The majority of antiviral drug development has focused on virus-specific discovery targeting discrete steps in the individual life cycles. Although great strides have been made for a number of clinically relevant diseases such as human immunodeficiency virus, influenza virus, and hepatitis B, broad spectrum antivirals do not exist. Broad spectrum antivirals would offer (1) treatment for viruses without specifically-targeted antivirals, (2) treatment for viruses which have developed resistance to their available treatments, and (3) a rapidly deployable treatment option in viral epidemics. Many viruses including human cytomegalovirus (HCMV), HIV, and SARS-CoV-2. rely on heparan sulfate (HS), a highly sulfated glycosaminoglycan …

Multi-Modality Automatic Lung Tumor Segmentation Method Using Deep Learning And Radiomics, Siqiu Wang

Theses and Dissertations

Delineation of the tumor volume is the initial and fundamental step in the radiotherapy planning process. The current clinical practice of manual delineation is time-consuming and suffers from observer variability. This work seeks to develop an effective automatic framework to produce clinically usable lung tumor segmentations. First, to facilitate the development and validation of our methodology, an expansive database of planning CTs, diagnostic PETs, and manual tumor segmentations was curated, and an image registration and preprocessing pipeline was established. Then a deep learning neural network was constructed and optimized to utilize dual-modality PET and CT images for lung tumor segmentation. …

Direction Modulated Brachytherapy For The Treatment Of Cervical Cancer, Dylan Richeson

Theses and Dissertations

Purpose: To evaluate and compare the performance of 9 experimental DMBT tandem models of varying physical dimensions in relation to 24 previously planned HDR cervical cancer treatment plans from multiple institutions that used conventional tandem and rings or ovoid applicators.

Methods and Materials: The DMBT tandem is designed to be used concurrently with IGABT and is made from an MRI-compatible tungsten-alloy rod with 6 channels grooved out of its periphery. 9 experimental DMBT tandem prototypes were provided. Each of the models was of equal lengths but varied in thickness, channel diameter size, and circle channel diameter size. Replanning …

Periodic Trends In The Infrared And Optical Absorption Spectra Of Metal Chalcogenide Clusters, Alain Ward

Theses and Dissertations

We have investigated the Optical absorption, Infrared spectra, Binding Energies, and various other cluster properties to determine the existence of periodic trend for Transition Metal Chalcogenide Clusters ligated with CO ligands. We were motivated to answer the question of whether periodic behavior can be observed in properties of octahedral metal-chalcogenide clusters. We have used the Amsterdam Density Functional code to calculate the electronic structure of Transition Metal Chalcogenide Clusters using gradient-corrected density functional theory. We determined the existence of several periodic trends in properties of octahedral Transition Metal Chalcogenide Clusters TM₆Se₈(CO)₆. To investigate these …

Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel

Theses and Dissertations

This thesis presents a learning from demonstration framework that enables a robot to learn and perform creative motions from human demonstrations in real-time. In order to satisfy all of the functional requirements for the framework, the developed technique is comprised of two modular components, which integrate together to provide the desired functionality. The first component, called Dancing from Demonstration (DfD), is a kinesthetic learning from demonstration technique. This technique is capable of playing back newly learned motions in real-time, as well as combining multiple learned motions together in a configurable way, either to reduce trajectory error or to generate entirely …

Development Of Novel Intracavitary Intensity Modulated Brachytherapy Applicators For Optimizing The Target Coverage In Gynecologic Malignancies, Monte Carlo Simulation Dosimetry, Moeen Meftahi

Theses and Dissertations

Gynecologic brachytherapy (GYN-BT) is essential for treating cervical and endometrial cancers, the most prevalent female reproductive cancers. This technique enables high radiation doses to a target with rapid dose fall-off to protect adjacent healthy organs. This dissertation aims to address some of the limitations of intracavitary GYN-BT using an intensity modulated brachytherapy (IMBT) technique and Monte Carlo (MC) simulations.

First, a novel non-invasive shielded vaginal cylinder (VC) applicator was designed to provide optimized radiation coverage for the target volume at vaginal apex, site of most recurrences without BT, for endometrial cancer BT. Physical limitations of current applicators and their resulting …

Incorporating Ontological Information In Biomedical Entity Linking Of Phrases In Clinical Text, Evan French

Theses and Dissertations

Biomedical Entity Linking (BEL) is the task of mapping spans of text within biomedical documents to normalized, unique identifiers within an ontology. Translational application of BEL on clinical notes has enormous potential for augmenting discretely captured data in electronic health records, but the existing paradigm for evaluating BEL systems developed in academia is not well aligned with real-world use cases. In this work, we demonstrate a proof of concept for incorporating ontological similarity into the training and evaluation of BEL systems to begin to rectify this misalignment. This thesis has two primary components: 1) a comprehensive literature review and 2) …

Biotic Characteristics Of Managed And Unmanaged Coastal Dunes In The Outer Banks, North Carolina, Andrew E. White

Theses and Dissertations

Under future climate change and sea level rise scenarios, Natural and Nature-Based Features (e.g., dunes) that protect coastal habitat and infrastructure will be exposed to increased wave energy and storm surge. Understanding how these forces will impact coastal dunes is necessary for their continued use as protective features. Coastal dunes develop through feedback between vegetation and sediment deposition, a process complicated by species-specific growth rates and responses to burial. Wave flume studies have tested the effects of dune vegetation on erosion and found multiple plant organs across several functional types to be important for resisting erosion. Although dune building and …

Approximating Bayesian Optimal Sequential Designs Using Gaussian Process Models Indexed On Belief States, Joseph Burris

Theses and Dissertations

Fully sequential optimal Bayesian experimentation can offer greater utility than both traditional Bayesian designs and greedy sequential methods, but practically cannot be solved due to numerical complexity and continuous outcome spaces. Approximate solutions can be found via approximate dynamic programming, but rely on surrogate models of the expected utility at each trial of the experiment with hand-chosen features or use methods which ignore the underlying geometry of the space of probability distributions. We propose the use of Gaussian process models indexed on the belief states visited in experimentation to provide utility-agnostic surrogate models for approximating Bayesian optimal sequential designs which …

Universal Design In Bci: Deep Learning Approaches For Adaptive Speech Brain-Computer Interfaces, Srdjan Lesaja

Theses and Dissertations

In the last two decades, there have been many breakthrough advancements in non-invasive and invasive brain-computer interface (BCI) systems. However, the majority of BCI model designs still follow a paradigm whereby neural signals are preprocessed and task-related features extracted using static, and generally customized, data-independent designs. Such BCI designs commonly optimize narrow task performance over generalizability, adaptability, and robustness, which is not well suited to meeting individual user needs. If one day BCIs are to be capable of decoding our higher-order cognitive commands and conceptual maps, their designs will need to be adaptive architectures that will evolve and grow in …

Behavioral Screening And Chiral Bioanalysis Of Emerging Stimulant-Type Drugs In Rats, Tyson R. Baird

Theses and Dissertations

The epidemic of drug use in the United States and elsewhere in the world has resulted in tragic loss of life and substantial economic costs. Novel psychoactive substances (NPS) are one of the contributors to this problem, and the lack of information about many of these drugs compounds their risk. This dissertation proposes a strategy to use intracranial self-stimulation (ICSS) as a behavioral screening tool to assess emerging drugs of abuse for their abuse potential in order to generate a proactive threat assessment. A series of stimulant-type drugs including methcathinone, α-pyrrolidinohexanophenone (α-PHP), cocaine, and the phenyltropane analogs of cocaine WIN35428 …

Smart City Management Using Machine Learning Techniques, Mostafa Zaman

Theses and Dissertations

In response to the growing urban population, "smart cities" are designed to improve people's quality of life by implementing cutting-edge technologies. The concept of a "smart city" refers to an effort to enhance a city's residents' economic and environmental well-being via implementing a centralized management system. With the use of sensors and actuators, smart cities can collect massive amounts of data, which can improve people's quality of life and design cities' services. Although smart cities contain vast amounts of data, only a percentage is used due to the noise and variety of the data sources. Information and communication technology (ICT) …

Computational Analysis Of Drug Targets And Prediction Of Protein-Compound Interactions, Sina Ghadermarzi

Theses and Dissertations

Computational prediction of compound-protein interactions generated a substantial amount of interest in the recent years owing to the importance of the knowledge of these interaction for drug discovery and drug repurposing efforts. Research suggests that the currently known drug targets constitute only a fraction of a complete set of drug targets, limiting our ability to identify suitable targets to develop new drugs or to repurpose current drugs for new diseases. These efforts are further thwarted by our limited knowledge of protein-drug (and more generally protein-compound) interactions, where only a subset of drug targets is typically known for the currently used …

Asymmetric Cuh-Catalyzed Reductive Coupling Of Alleneamides With Carbonyl Electrophiles And The Mechanistic Investigation Into The Suzuki-Miyaura Cross-Couplings Of Electron-Deficient Systems, Samantha L. Gargaro

Theses and Dissertations

Most natural products and other biologically active small molecules contain multiple stereogenic heteroatoms throughout their carbon scaffold. As a result, methods to install these multi-heteroatom functionalities efficiently are highly desirable. Reductive coupling reactions have been studied extensively, and reductive allylation has been a key method for generating chiral secondary and tertiary allylic alcohols. This work focuses on utilizing naturally abundant and inexpensive Cu for the asymmetric reductive coupling of alleneamides with carbonyl electrophiles to access highly functionalized multi-heteroatom scaffolds that are difficult to produce via traditional methods. Described herein are methods for these asymmetric reductive coupling reactions. Chapter 1 describes …

A Study On Developing Novel Methods For Relation Extraction, Darshini Mahendran

Theses and Dissertations

Relation Extraction (RE) is a task of Natural Language Processing (NLP) to detect and classify the relations between two entities. Relation extraction in the biomedical and scientific literature domain is challenging as text can contain multiple pairs of entities in the same instance. During the course of this research, we developed an RE framework (RelEx), which consists of five main RE paradigms: rule-based, machine learning-based, Convolutional Neural Network (CNN)-based, Bidirectional Encoder Representations from Transformers (BERT)-based, and Graph Convolutional Networks (GCNs)-based approaches. RelEx's rule-based approach uses co-location information of the entities to determine whether a relation exists between a selected entity …

Temporal Disambiguation Of Relative Temporal Expressions In Clinical Texts Using Temporally Fine-Tuned Contextual Word Embeddings., Amy L. Olex

Theses and Dissertations

Temporal reasoning is the ability to extract and assimilate temporal information to reconstruct a series of events such that they can be reasoned over to answer questions involving time. Temporal reasoning in the clinical domain is challenging due to specialized medical terms and nomenclature, shorthand notation, fragmented text, a variety of writing styles used by different medical units, redundancy of information that has to be reconciled, and an increased number of temporal references as compared to general domain texts. Work in the area of clinical temporal reasoning has progressed, but the current state-of-the-art still has a ways to go before …

Metal Nanoparticle Synthesis Via Laser-Induced Photochemical Reduction Of Metal Salts, Laysa M. Frias Batista

Theses and Dissertations

Significant attention has been focused on metal nanoparticles (MNPs) due to their unique optical, catalytic, and electronic properties. In the last two decades, laser synthesis techniques have emerged as versatile routes to MNPs that enable control over particle size, shape, and surface chemistry without the use of chemical reducing agents or surface-blocking capping ligands. A method gaining increasing attention is the direct laser-driven reduction of metal salts, called Laser Reduction in Liquid (LRL). LRL typically involves the use of intense laser pulses of picosecond or femtosecond duration to ionize and dissociate solvent molecules, generating plasmas with reactive chemical species such …

Estimating Weighted Panel Sizes For Primary Care Providers: An Assessment Of Clustering And Novel Methods Of Panel Size Estimation On Electronic Medical Records, Martin A. Lavallee

Theses and Dissertations

Primary Care is on the frontlines of healthcare, thus they see the most diverse set of patients. In order to achieve high functioning primary care, a practice must establish empanelment, the pairing of patients to providers. Enumeration of empanelment, or estimating panel sizes, helps ensure that the demands of the patients demand the supply of providers and optimize the balance of primary care resources to improve quality of care. Further we can adjust panel sizes by using patient-level data on healthcare utilization and complexity extracted from the electronic medial record to determine the amount of care or burden of work …

Improving College Students’ Views And Beliefs Relative To Mathematics: A Systematic Literature Review Followed By A Multiple Case Mixed Methods Exploration Of The Experiences That Underpin Community College Students’ Attitudes, Self-Efficacy, And Values In Mathematics, Marquita H. Sea

Theses and Dissertations

Mathematics is particularly important due to its relevance in our daily lives. It is a general requirement throughout schooling. Unfortunately, many students openly declare negative views/beliefs regarding math in their personal and academic lives. These in turn, negatively influence students’ achievement related behaviors and outcomes. First, a systematic literature review was conducted to determine what types of studies/initiatives have aimed to enhance students’ views/beliefs relative to mathematics, including domain general and specific perceptions of math as well as their judgements of who is successful in mathematics and if they themselves can be successful. Specifically, the review centered on the components …

Mathematical Models Of Infection Prevention Programs In Hospital Settings, Kelly A. Reagan

Theses and Dissertations

Hospitals play a vital role in providing for the healthcare needs of a community. Patients can develop hospital-acquired infections (HAIs) during their hospitalization due to exposure to foreign bacteria, viruses, and fungi. Infection prevention programs target and reduce HAIs, but implementing the infection prevention programs often comes with a cost. The goal of my research is to use mathematical models to quantify the impact of infection prevention programs on cases of HAIs and total healthcare costs. First, I use a Markov chain model to quantify how one infection prevention program reduces general HAIs in the hospital. Then, I calculate the …

Synthesis And Modeling Of Manganese Ferrite Nanoparticles For Magnetic Hyperthermia Applications, Margaret E. Thornton

Theses and Dissertations

Biologically targeted magnetic hyperthermia (MH) is a promising cancer therapeutic that is both non-invasive and has the potential to serve as a single-modality cancer treatment. MH operates through the elevation of temperatures between 40-43 °C to induce apoptosis in malignant tumor cells, while the small size of the magnetic nanoparticles preserves the healthy surrounding tissue. At present, MH is limited by low heating efficiency and heterogenous outcomes, and treatment requires direct-injection of the nanoparticles, excluding deep-tissue and metastatic tumors from the therapy. The most popular candidates for MH are the spinel ferrites iron oxide and manganese iron oxide (MFO). These …

Automated Conjecturing On The Independence Number And Minimum Degree Of Diameter-2-Critical Graphs, Joshua R. Forkin

Theses and Dissertations

A diameter-2-critical (D2C) graph is a graph with diameter two such that removing any edge increases the diameter or disconnects the graph. In this paper, we look at other lesser-studied properties of D2C graphs, focusing mainly on their independence number and minimum degree. We show that there exist D2C graphs with minimum degree strictly larger than their independence number, and that this gap can be arbitrarily large. We also exhibit D2C graphs with maximum number of common neighbors strictly greater than their independence number, and that this gap can be arbitrarily large. Furthermore, we exhibit a D2C graph whose number …

Evaluating Long-Range Transportation Plans For Mainstreaming Of Climate Adaptation Among Virginia Mpos, Sebastian L. Shetty

Theses and Dissertations

Despite the strides made towards addressing climate change through greenhouse gas (GHG) emissions reduction strategies, it has become increasingly apparent that attempting to mitigate the crisis in such a manner alone is insufficient. This thesis joins a growing body of research on how our societies must adapt to a changing climate, contributing more evidence on common barriers to adaptation and how they might be overcome. Through an attempt to evaluate the progress made towards mainstreaming, or integrating, climate change concerns into five Virginia MPOs’ long-range transportation plans (LRTPs), this study provides support for prior hypotheses around the potential for MPOs …