Physical Sciences and Mathematics Commons^™

Modeling The Spatiotemporal Dynamics Of Active Regions On The Sun Using Deep Neural Networks, Godwill Amankwa

Open Access Theses & Dissertations

Solar active regions are areas on the Sun's surface that have especially strong magnetic fields. Several phenomena that can have significant negative effects on technology and subsequently on human life, such as solar flares and coronal mass ejections (CMEs), are often associated with active regions.Since the physical phenomena underlying the evolution of active regions are still poorly understood, the accurate prediction of solar flares and coronal mass ejections remains an open problem.

Extracting insights from the available datasets of solar activity that can lead to a better understanding of solar active regions has been an important research goal at the …

Molecular Dynamics Of Nucleic Acids, Proteins, And Their Complexes: From Atomistic And Coarse-Grained Descriptions To New Methodologies, Parth Chaturvedi

Open Access Theses & Dissertations

Computational modeling of biological macromolecules through molecular dynamics (MD) simulations is becoming increasingly useful to interpret the experimental results and guide the future experiments. Over the last decade, MD simulations have become much more powerful and accessible due to advancements in fields of structural biology, computer science and integrated chip design. In this Thesis, I utilize different MD simulation techniques to model interaction of and antiviral mechanisms. Within the framework of nucleic acid modelling, we describe first dynamics of small circular single stranded nucleic acids and highlight key dynamical differences of backbone behavior in solution between DNA and RNA and …

Study Of Weakly Bound Cluster Anions Using Self Interaction Corrected Density Functional Scheme, Peter Obinna Ufondu

Open Access Theses & Dissertations

The Kohn–Sham formulation of density functional theory (DFT) is a widely used quantum mechanical theory to study chemical and materials properties. The practical application of DFT requires an approximation to the exchange–correlation (XC) functional. These approximations suffer from self-interaction errors due to the incomplete cancellation of the self-Coulomb energy with the approximate self-exchange and correlation energy for one-electron densities. Systems with weakly-bound electrons impose great challenges to semi-local density functional approximations. We use recently developed local scaled self-interaction correction (LSIC) by Zope et al and the Perdew-Zunger SIC method using the Fermi-Löwdin orbitals to calculate the vertical detachment energies (VDEs) …

Hardware For Quantized Mixed-Precision Deep Neural Networks, Andres Rios

Open Access Theses & Dissertations

Recently, there has been a push to perform deep learning (DL) computations on the edge rather than the cloud due to latency, network connectivity, energy consumption, and privacy issues. However, state-of-the-art deep neural networks (DNNs) require vast amounts of computational power, data, and energyâ??resources that are limited on edge devices. This limitation has brought the need to design domain-specific architectures (DSAs) that implement DL-specific hardware optimizations. Traditionally DNNs have run on 32-bit floating-point numbers; however, a body of research has shown that DNNs are surprisingly robust and do not require all 32 bits. Instead, using quantization, networks can run on …

An Exploration Of Passive Seismology: Applying Seismic Methods For Traditional And Exotic Source Characterization, David Lewis Guenaga

Open Access Theses & Dissertations

As seismology continues to develop both theoretical and observational, so does its ability to be used in various applications. In this Dissertation, I develop and apply new approaches to five distinct projects (chapters 2-6), leveraging large and small high-quality targeted datasets to decipher fundamental and applied processes utilizing the full seismic wavefield. The first chapter introduces this Dissertation by providing broad context, continuity, and technical information about each of the five projects. Specifically, chapter 2 explores a seismic sensorâ??s ability to detect opera in Oak Ridge National Laboratory, TN, using a misfit power spectral density detector. Chapter 3 outlines work …

Studies Of The Planetary Boundary Layer And Their Impact On Air Pollution In A Semi-Arid Region With Complex Terrain, Nakul Nitin Karle

Open Access Theses & Dissertations

The adjacent cities of El Paso-Juárez, located in the Rio Grande Rift Valley and surrounded by complex mountainous terrain, have undergone rapid urbanization and industrial growth in the last few decades, accompanied by increasing substandard air quality episodes. Although numerous air quality studies were conducted in this semi-arid region in the past, none focused extensively on the Planetary Boundary Layer (PBL) contribution and impact on air pollutant concentrations. In this work, both the high and low ozone episodes from 2015 to 2020 were examined. Both modeling and experimental data of the PBL height (PBLH) were obtained and related to atmospheric …

Simultaneous Forecasting Of Yield Curves For Multiple Zero-Coupon Bonds Using The Heath-Jarrow-Morton Model, Ebenezer Nkum

Open Access Theses & Dissertations

Market diversification is a strategy according to which a company seeks growth by addingproducts and markets that are in a certain sense "uncorrelated" to its existing products and markets. Bonds play a major role in a well-balanced diversified portfolio because of their low correlation to other asset classes. While the correlations vary widely over time, bonds are not highly correlated with any other asset classes. Even in the simplest diversified portfolio, bonds can reduce volatility due to their low or negative correlation with stocks. Because companies can create robust diversified portfolios with bonds it is imperative that different bonds are …

Discrepancy-Based Analysis Of Measurement Sampling Points In Compressive Sensing, Felipe Batista Da Silva

Open Access Theses & Dissertations

Compressive sensing (CS) is a technique in signal processing that under certain conditions allows someone to reconstruct sparse signals from fewer linear measurements. A problem in CS is modeled in terms of an underdetermined linear system, whose associated matrix is previously designed. Then, it is of interest in CS to know what a good sampling defined by the sensing matrix is and how to measure it. In this work, we provided analytical proofs of properties of the metric discrepancy that allow us to propose a fast algorithm for discrepancy calculation. Such metric measures the quality of the sampling measurement points …

Application Of Machine Learning In Flood Depth Prediction, Armando Esquivel

Open Access Theses & Dissertations

Machine learning technologies have helped provide answers for problems with a high degree of complexity. Machine learning has been utilized by various disciplines within the Civil Engineering profession and has proven to be efficient in solving complex problems. Although machine learning is being used in the Civil Engineering profession, a formal framework on developing and integrating machine learning has not been developed for flood depth prediction. The proposed word uses machine learning to predict the depth of flood at Houston, TX, due to a 100-year 24-hour storm. The proposed work can be used to collect, store and analyze data to …

The Hybridizing Ions Treatment (Hit) Method Development And Computational Study On Sars-Cov-2 E Protein., Shengjie Sun

Open Access Theses & Dissertations

Fast and accurate calculations of the electrostatic features for highly charged biomolecules such as DNA, RNA, highly charged proteins, are crucial but challenging tasks. Traditional implicit solvent methods calculate the electrostatic features fast, but they are not able to balance the high net charges in the biomolecules effectively. Explicit solvent methods add unbalanced ions to neutralize the highly charged biomolecules in molecular dynamic simulations, which require more expensive computing resources. Here we developed a novel method, the Hybridizing Ions Treatment (HIT) method, which hybridizes the implicit solvent method with the explicit method to realistically calculate the electrostatic potential for highly …

Making Valid Inferences With Decision Tree, George Ekow Quaye

Open Access Theses & Dissertations

HypoThesis testing and Confidence Interval (CI) estimates are key statistics in predicting future values in data analysis. Most often, CI estimates are directly obtained from the summary statistics of a particular statistical methodology output. However, when it comes to the summary of decision tree outputs, these CI estimates are not directly obtained. So a na\"{i}ve way of making node-level inference is to construct a $(1-\alpha) \times 100\%$ confidence interval for a node mean $\bar{y}_t$ using the relation: $\bar{y}_t \, \pm \, z_{1-\alpha/2} \, \frac{s_t}{\sqrt{n_t}}$, where $\bar{y}_t$ is the node mean and $s_t$ is the standard deviation estimates from the decision …

Organic Synthesis For Solving Clinical Conundrums Of Drug Activation And For Facilitating Natural Product Drug Discovery, Elkin Libardo Romero

Open Access Theses & Dissertations

Organic chemistry is an exploratory world in which chemists translate their knowledge by creating new molecules and explore their biological and physical properties. For the past three years, our research has been focused on organic synThesis and chemical biology to solve challenges in this area. Two major approaches have been faced: First, the chemical synThesis of the active metabolite of antithrombotic prodrug Plavix (clopidogrel). Clopidogrel (CPG) has been widely used as an antithrombotic prodrug, which undergoes extensive metabolism in patients; among it, only a trivial portion is converted through a series of cytochrome P450 (CYP)-catalyzed thiophene degradation to form active …

High Frequency Electron Spin Resonance Investigations On Quasi-Two-Dimensional Chromium Halide Magnets, Christian Saiz

Open Access Theses & Dissertations

Broadening the knowledge and understanding on the magnetic correlations in van der Waals layered magnets is critical in realizing their potential next-generation applications in devices such as spintronics. In this study, we employ high frequency (ν = 120 GHz, 240 GHz) electron spin resonance (ESR) spectroscopy on plate-like CrX3 (where X = Cl, Br, I) to gain insight into the magnetic interactions as a function of temperature (200 – 4.4 K) and the angle of rotation θ (degrees). We find that the temperature dependence of the ESR linewidth is well described by the Ginzburg-Landau critical model, indicative of antiferromagnetic correlations …

Multiplicative And Additive Arithmetic Functions And Formal Power Series, John Byron Snell

Open Access Theses & Dissertations

The theory of arithmetic functions and the theory of formal power series are classical andactive parts of mathematics. Algebraic operations on sets of arithmetic functions, called convolutions, have an important place in the theory of arithmetic functions. The theory of formal power series also has its place firmly anchored in abstract algebra. A first goal of this Thesis will be to present a parallelism of known characterizations of the concepts of multiplicative and additive for arithmetic functions (Theorems 2.1.2 and 2.2.3) on the one hand and for formal power series on the other (Theorems 3.4.3 and 3.4.4). Therefore, in Chapter …

Digital Twin Technology Applications For Transportation Infrastructure - A Survey-Based Study, Hector Cruz

Open Access Theses & Dissertations

In the past couple of decades, various industries have taken advantage of emerging advanced technologies, such as digital twin (DT), to find more effective solutions in their respective areas. In the transportation infrastructure sector, the concept and implementation of DT technologies are slowly gaining traction but lagging behind other major industries. To better understand the limitations, opportunities and challenges for the adoption of DT in this sector, a survey questionnaire was distributed to collect information from industry professionals involved in transportation infrastructure projects. The purpose of this study is to understand how DT technology is being perceived by the industry. …

Novel N-Derivatized-7-Nitroindolines For The Synthesis Of Photocleavable Crosslinkers, And For Solid Phase Peptide Synthesis, Hector Patricio Del Castillo

Open Access Theses & Dissertations

7-Nitroindoline-based photochemistry has focused mostly on N-acyl-7-nitroindolines, which have been used as photocleavable protecting groups for carboxylic acids that can be efficiently removed by illumination with UV-light. They offer an alternative to the more commonly used o-nitrobenzyl-based photocleavable protecting groups. N-acyl-7-nitroindolines can also be used as photochemical acylating agents in inert solvents. For example, they have found application in peptide fragment condensation, the convergent synThesis of N-glycopeptides, and the synThesis of peptide thioesters, forming amide and thioester bonds with amine and thiol nucleophiles, respectively, under neutral conditions. The photochemical activation of N-acyl-7-nitroindolines can occur with UV light (λ = 350 …

Impact Of Various Hydrophobic Cargoes On The Structural Properties Of Pluronic-F127 Based Micelles Near The Standard Critical Transition Zone, Tahmida Raheen Iqbal

Open Access Theses & Dissertations

Pluronic F-127 is a triblock copolymer (PEO-PPO-PEO) that can form a micelle at critical micelle concentration (CMC). CMC for Pluronic F-127 is 0.7% at 25 0C. Micelles are lipid molecules that can arrange themselves in a spherical form in an aqueous solution with a hydrophobic core and hydrophilic shell. Pluronic F-127 can encapsulate poor water-soluble drugs and administrate the medicine to the targeted area with a controlled drug release rate and low toxicity. The purpose of this study is to understand the structural variation in Pluronic F-127 micelles after loading with different hydrophobic cargoes (alkanes, fatty acids, anticancer therapeutic agents). …

On Using Demographic Data With Deprivation Index For Predicting Chronic Diseases, Olugbenga Temitope Iyiola

Open Access Theses & Dissertations

Researchers have worked on modeling and predicting the likelihood of developingchronic diseases, such as diabetes and high blood pressure, using medical data (e.g., heart-rate, blood sugar). However, many of these diseases demonstrate strong links with demographics and socio-economic status (e.g., race, gender, income). It is also less time-consuming to retrieve demographic and socio-economic data, some of which are publicly available through US Census Bureau, than to carry out medical tests. Hence, demographic data can give a quicker estimate of the susceptibility of a person to a chronic disease.

In this work, we study the effect of using medical vs. demographics …

Robust Variable Selection In Multiple Linear Regression Via Penalized Least Trimmed Squares., Reagan Kesseku

Open Access Theses & Dissertations

Variable selection has been studied using different approaches. Its growing importance lies in numerous applications to high-dimensional data from experiments and natural phenomena. Often, models are to be constructed from such data based on significant variables for estimation or prediction purposes. This demands not just any variable selectionmethod, but one that is robust, computationally efficient and with other desirable statistical properties. Besides the high-dimensionality of such data, the presence of outliers is common due to heterogeneous sources. Though outliers often contain useful information, they can unduly influence non-robust estimators to produce misleading results. This is the case for ordinary least …

Gene Selection And Classification In High-Throughput Biological Data With Integrated Machine Learning Algorithms And Bioinformatics Approaches, Abhijeet R Patil

Open Access Theses & Dissertations

With the rise of high throughput technologies in biomedical research, large volumes of expression profiling, methylation profiling, and RNA-sequencing data are being generated. These high-dimensional data have large number of features with small number of samples, a characteristic called the "curse of dimensionality." The selection of optimal features, which largely affects the performance of classification algorithms in machine learning models, has led to challenging problems in bioinformatics analyses of such high-dimensional datasets. In this work, I focus on the design of two-stage frameworks of feature selection and classification and their applications in multiple sets of colorectal cancer data. The first …

How Does Land Cover Classification In Google Earth Engine Compare With Traditional Methods Of Land Cover Classification? What Are The Tradeoffs?, Carlos Sebastian Reyes

Open Access Theses & Dissertations

The project focuses on comparing land cover classification of traditional methods such as ArcGIS with newer ones such as Google Earth Engine (GEE) as well as discussing any potential tradeoffs. Two studies were performed in both platforms, the first involved analyzing land cover change in the Middle Rio Grande (MRG) region of southern New Mexico, far west Texas, and northern Chihuahua, Mexico. The MRG study focused on urban and agricultural change in the region using two different classification methods. The second study focused on creating a post-hurricane damage assessment (PDA) with the goal of developing an automated method of estimating …

A Study Of The Frustrated Honeycomb Battery Material Na2ni2teo6, Nathan Christopher Episcopo

Open Access Theses & Dissertations

The P2-type layered hexagonal compound Na2Ni2TeO6 with Ni2+ on a honeycomb lattice was synthesized by the standard solid-state route. Structural characterization chemical phase purity was confirmed by Rietveld refinement of laboratory and synchrotron data. The crystal structure refines well in the P63/mcm space group. Single crystal growth trials using the self-flux-melt method were conducted with limited success. The magnetic transition temperature pertaining to Ni2+ lattice was confirmed by analysis of specific heat capacity to be . The magnetic susceptibility remains largely unchanged in magnetic field of and external pressure of . There is an almost linear response in isothermal magnetization …

Geological Problems With Microbiological Solutions: Deciphering The Authigenesis Of Calcite, Dolomite, And Native Sulfur In Salty Environments, Amanda L. Labrado

Open Access Theses & Dissertations

Microbial activity is known to impact the formation and alteration of many different rock types. For carbonate caprock (CCR), a lithology found on salt diapirs, it is generally accepted that microbial activity drives the precipitation of carbonate minerals, forming limestone and/or dolomite and native (elemental) sulfur. It appears that there are two types of CCR: 1) limestone associated with native sulfur (S0) and 2) limestone associated with dolomite. The mechanics of CCR formation are poorly understood. For example, it is unclear why native sulfur and dolomite are rarely found in the same CCR assemblage, and why either are formed at …

Addressing Challenges In Aggregating And Analyzing Agroecological Data, Sarah E. Mccord

Open Access Theses & Dissertations

Agroecosystems face multiple threats including land degradation and climate change, changing and competing land uses, invasive species and disease spread, and biodiversity loss. While scientists seek to understand rapidly changing ecosystems, land managers are struggling to maintain ecosystem services amid transitions to novel ecosystem states. Understanding agroecosystem drivers and ensuing responses requires quality information about ecosystems that span biomes, trophic scales, ecological processes, spatiotemporal scales, land use, and land ownership. Yet, using multi-scale agroecosystem information can be frustrating for both scientific researchers and land managers as it is difficult to locate data that are trustworthy, easily accessible, standardized, and connected …

High-Dimensional Random Forests, Roland Fiagbe

Open Access Theses & Dissertations

The significant advances in technology have enabled easy collection and management of high-dimensional data in many fields, however, the process of modeling these data imposes a huge problem in the field of data science. Dealing with high-dimensional data is one of the significant challenges that degenerate the performance and precision of most classification and regression algorithms, e.g., random forests. Random Forest (RF) is among the few methods that can be extended to model high-dimensional data; nevertheless, its performance and precision, like others, are highly affected by high dimensions, especially when the dataset contains a huge number of noise or noninformative …

Synthesis And Characterization Of Functiona Materials For 3d Printed Composites, Elizabeth Irene Reza

Open Access Theses & Dissertations

The following body of work encompasses the synThesis, upscaling, additive manufacturing, and characterization of microspheres as functional fillers incorporated into polymer syntactic foams. Synthesizing microspheres permits control over morphology, dispersion of particles, and size while the use of direct write manufacturing allowed for the controllability of filler orientation. Two different syntactic foams were developed from similar methodologies: (1) a silicone syntactic foam (2) epoxy syntactic foam. The silicone epoxy foam showed an increasing in damping and elastic modulus. The epoxy syntactic foams showed an enhanced thermal and electrical properties.

Refined Moderation Analysis With Binary Outcomes, Eric Anto

Open Access Theses & Dissertations

With the growing interest in personalized or precision medicine, it is indispensable thatmoderation analysis which is primarily related to the study of differential treatment effects among patients with different characteristics, also serves as the bedrock for precision medicine is taken more seriously. Concerning moderation analysis with binary outcomes, we start with an interesting observation, which shows that heterogeneous treatment effects could be equivalently estimated via a role exchange between the outcome and the treatment variable. The result holds for both experimental data and observational data, yet with an important difference in interpretation. Two estimators of moderating effects corresponding to two …

Two Developments For Efficient And Accurate Density Functional Theory Calculations, Zachary John Buschmann

Open Access Theses & Dissertations

Density functional theory (DFT) has long been the workhorse of quantum chemists and materials scientists. As the ability of modern DFT codes to address larger and more complex molecular systems has grown, so too has the computational cost, with cutting edge simulations requiring thousands of hours of wall time on the worldâ??s fastest supercomputers.For this reason, efficiency in both memory and time is critical at every step of the process. In fact, the increasing scope of physical systems that can be modeled is as much a function of computational elegance as of the physical fidelity of the simulation. The continuing …

Stability Of Blood Lead Levels In Children With Chronic Low-Level Lead Absorption, Michelle Del Rio

Open Access Theses & Dissertations

Background and Significance: Despite the many historical efforts by the U.S. to reduce lead (Pb) in the environment, childhood Pb poisoning continues to be a public health issue today. Pb has been identified as a child hazard because children are highly vulnerable to the effects even at lower levels of exposure (blood lead levels (BLLs) < 10 μg/dL), and these effects can be physical, cognitive, and behavioral. Current state and federal blood lead level screening guidelines for identifying exposed children are based on assumptions that BLLs < 10 μg/dL will remain stable or decline over time (with age); disregard the effects of lowest-range Pb exposure; and disregard Pb levels in children older than approximately age 6. We have observed in past clinical studies that in one U.S./Mexico border community, children in high-risk neighborhoods experienced substantially higher proportions of elevated blood lead levels (CDC reference level of ≥ 5 μg/dL) than the rest of the U.S., and a large proportion of children had detectable blood lead levels. To test current policy assumptions regarding child blood lead level screening, this study examined whether time and/or other possible factors over time, predicted child blood lead levels in children with chronic low-level Pb absorption. Whether time was a significant predictor was examined, and also whether age, sex, and living in families with incomes below the U.S. poverty line, living in an older home, and living near industries predicted child blood lead levels.

Aims and Objectives: Changes in current policy must be evidence-based. The over-arching goal of this study was to test current assumptions that one blood lead level test is sufficient to rule out child lead exposure, and that lead exposure and risk of lead exposure, reliably …

Seismic Tomographic Modeling Of The Coast Mountains Batholith, British Columbia, Canada, Sarah M. Quinonez

Open Access Theses & Dissertations

The Coast Mountains Batholith on the west coast of British Columbia, Canada, comprises a series of granitic to tonalitic plutons. The felsic continental crust is generated from mafic oceanic crust subduction by partial melting and fractionation, leaving ultra-mafic roots. In July of 2009, a sizeable controlled-source experiment was conducted along a 400km east-west transect from Bella Bella into central British Columbia. Student volunteers from multiple universities deployed 1,800 one-component and 200 three-component geophones connected to Texan data recorders with 200-m spacing intervals and shot spacing at 30-km. The 18-point sources ranged from 160 to 1,000 kg of high yield explosives. …