Physical Sciences and Mathematics Commons^™

Frontiers In Fast Voltammetry: Novel Analytes And Applications, Jordan Holmes

Theses and Dissertations

Electrochemical sensors are beneficial towards the development and advancement of monitoring devices. As this type of technology progresses, so does our ability to create state-of-the-art sensing strategies to probe environmental and biological systems at the source. In the environment, it is essential to monitor particularly harmful contaminants like trace metals in order to better mitigate risk. Additionally, biological molecules are often times challenging to measure because matrices are complex and difficult to probe; Recent advancements in chemical ex vivo and in vivo sensing platforms have offered insight into physiological processes. The brain in particular requires a sophisticated, implantable sensor as …

Improving Person-Independent Facial Expression Recognition Using Deep Learning, Jie Cai

Theses and Dissertations

Over the past few years, deep learning, e.g., Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs), have shown promise on facial expression recog- nition. However, the performance degrades dramatically especially in close-to-real-world settings due to high intra-class variations and high inter-class similarities introduced by subtle facial appearance changes, head pose variations, illumination changes, occlusions, and identity-related attributes, e.g., age, race, and gender. In this work, we developed two novel CNN frameworks and one novel GAN approach to learn discriminative features for facial expression recognition.

First, a novel island loss is proposed to enhance the discriminative power of learned deep …

Designing, Constructing, And Employing Two-Dimensional Ultrafast Spectroscopy To Resolve Complex Kinetics, Jason R. Darvin

Theses and Dissertations

Multiple population-period transient spectroscopy (MUPPETS) is a two dimensional ultrafast time resolved spectroscopy technique. MUPPETS uses three pairs of optical pulses over two time periods to separate homogeneous and heterogeneous causes of rate dispersion. This dissertation details improvements to the MUPPETS optical assembly enabling measurements on systems that previously fell outside of the MUPPETS 2-ns time window. In addition, the theoretical groundwork is laid to unveil the hidden coordinate controlling rate exchange using 2D and 3D correlation functions.

The first project details improvements made to the MUPPETS assembly. A detailed method was developed to eliminate astigmatism, coma, and spherical aberration …

Study Of Transition State Stabilization Using Molecular Rotors, Erik Carl Vik

Theses and Dissertations

Molecular devices that function as rotors and measurement devices are the main topic of this dissertation. Each study contains a device based on an N-phenylimide framework, which has restricted rotation about the N-C (imide-phenyl) single bond due to a steric clash from the imide carbonyl and the phenyl rings ortho substituent. In general, two ground states are observed by 1H NMR, which are separated by a single transition state (TS). Incorporation of non-covalent interactions into the TS led to measurable changes in the rate for rotation. While the molecules in this dissertation revealed details that could not have been predicted, …

Studies On The Mechanism And Application Of Steam Thermography, Raymond Gerard Belliveau Iii

Theses and Dissertations

The detection of blood on fabrics for forensic purposes is a widely studied topic in forensic science, and to that end, effort in this laboratory has been devoted to developing a thermal imaging method called steam thermography. Steam thermography is a method used to enhance chemical contrast in thermographic images by exposing a surface to water vapor during imaging. The exposure of water vapor to the surface generates heat, and can differentially increase the thermographically measured apparent temperature of imaged surfaces. This can result in thermographic contrast between surfaces with different chemical properties. Previously reported proposed mechanisms to describe the …

Properties, Learning Algorithms, And Applications Of Chain Graphs And Bayesian Hypergraphs, Mohammad Ali Javidian

Theses and Dissertations

Probabilistic graphical models (PGMs) use graphs, either undirected, directed, or mixed, to represent possible dependencies among the variables of a multivariate probability distri- bution. PGMs, such as Bayesian networks and Markov networks, are now widely accepted as a powerful and mature framework for reasoning and decision making under uncertainty in knowledge-based systems. With the increase of their popularity, the range of graphical models being investigated and used has also expanded. Several types of graphs with dif- ferent conditional independence interpretations - also known as Markov properties - have been proposed and used in graphical models.

The graphical structure of a …

Investigation Of Electrostatic Interactions Towards Controlling Silylation-Based Kinetic Resolutions And Exploring The Effect Of The Polymer Backbone On Silylation-Based Kinetic Resolutions Employing A Polymer-Supported Triphenylsilyl Chloride, Tian Zhang

Theses and Dissertations

This dissertation focuses on studies of silylation-based kinetic resolution methodology developed by the Wiskur group, which is a powerful method for the separation of a single enantiomer from a mixture of racemic secondary alcohols. Chapter 1 introduces the background of our silylation-based kinetic resolution..

Chapter 2 involves mechanistic studies of electrostatic interactions in controlling enantioselectivities of our silylation-based kinetic resolution. Electrostatic interactions between a silylated isothiourea intermediate and an ester π system is determined via linear free energy relationship study. To be specific, how variations in sterics and electronics affect the selectivity of a silylation-based kinetic resolution.

Chapter 3 is …

Person Identification With Convolutional Neural Networks, Kang Zheng

Theses and Dissertations

Person identification aims at matching persons across images or videos captured by different cameras, without requiring the presence of persons’ faces. It is an important problem in computer vision community and has many important real-world applica- tions, such as person search, security surveillance, and no-checkout stores. However, this problem is very challenging due to various factors, such as illumination varia- tion, view changes, human pose deformation, and occlusion. Traditional approaches generally focus on hand-crafting features and/or learning distance metrics for match- ing to tackle these challenges. With Convolutional Neural Networks (CNNs), feature extraction and metric learning can be combined in …

Cdse Quantum Dot Surface Chemistry Thermodynamics Via Isothermal Titration Calorimetry: An Emphasis On The Fundamentals, Megan Y. Gee

Theses and Dissertations

For several decades, the study and development of colloidal semiconductor nanocrystals, or quantum dots (QD), has become a rich field heralding improved integration into applications ranging from photovoltaics and photocatalysis to biomedical imaging and drug delivery. CdxSey is the most extensively studied QD system, however numerous compositional details still confound the nanocrystal field. Although CdSe QDs with native ligand coatings can show high fluorescence quantum yield and may be suitable for some applications, often times these original ligand layers are comprised of long aliphatic chains that preclude incorporation into biological matrices or severely impede charge transfer – depending on the …

Studies Of Ch Activation In Unsaturated Amides And Esters By Trinuclear Metal Carbonyl Clusters Of Osmium, Morteza Maleki

Theses and Dissertations

The chemistry of the reaction of Os3(CO)10(NCCH3)2 with representatives of unsaturated amides and esters, RCOCHCH2 (R=(CH3)2N, CH3O) has been investigated. In these reactions, it has been observed that a CH bond on the β-carbon atom is readily activated by triosmium carbonyl clusters. The activation of β-carbon C-H bond in unsaturated amides and esters provides a robust platform for studying multicenter C-H bond transformations and for C-C bond formation via hydrogen shift and CO insertion processes. In this work, proposed mechanistic approaches have been taken in order to better understand and study the relationship between the characterized species. In addition, a …

Green Forest Businesses As A Method To Improve Communities In Unesco’S East Usambara Biosphere Reserve In Tanzania, Myoung Su Ko

Theses and Dissertations

A number of developing countries, especially those in Africa which have experienced former colonization, are still struggling with exploitation of their natural resources. Throughout the development of environmental management, the strategy of natural resource management has evolved from mistreating the environment for economic and social development, to separating human activities from the environment for extreme environmental protection, to ensuring the interaction between human life and environment for sustainable development. Although an abundance of natural resources, and particularly forests, exist in the protected areas, the residents in communities surrounding protected areas are usually economically and socially poor.

With this situation, the …

Semantic Segmentation Considering Image Degradation, Global Context, And Data Balancing, Dazhou Guo

Theses and Dissertations

Recently, semantic segmentation – assigning a categorical label to each pixel in an im- age – plays an important role in image understanding applications, e.g., autonomous driving, human-machine interaction and medical imaging. Semantic segmentation has made progress by using the deep convolutional neural networks, which are sur- passing the traditional methods by a large margin. Despite the success of the deep convolutional neural networks (CNNs), there remain three major challenges.

The first challenge is how to segment the degraded images semantically, i.e., de- graded image semantic segmentation. In general, image degradations increase the difficulty of semantic segmentation, usually leading to …

Moving Off Collections And Their Applications, In Particular To Function Spaces, Aaron Fowlkes

Theses and Dissertations

The main focus of this paper is the concept of a moving off collection of sets. We will be looking at how this relatively lesser known idea connects and interacts with other more widely used topological properties. In particular we will examine how moving off collections act with the function spaces Cp(X), C0(X), and CK (X). We conclude with a chapter on the Cantor tree and its moving off connections.

Many of the discussions of important theorems in the literature are expressed in terms that do not suggest the concept …

Stacked Modelling Framework, Kareem Abdelfatah

Theses and Dissertations

The thesis develops a predictive modeling framework based on stacked Gaussian processes and applies it to two main applications in environmental and chemical en- gineering. First, a network of independently trained Gaussian processes (StackedGP) is introduced to obtain analytical predictions of quantities of interest (model out- puts) with quantified uncertainties. StackedGP framework supports component- based modeling in different fields such as environmental and chemical science, en- hances predictions of quantities of interest through a cascade of intermediate predic- tions usually addressed by cokriging, and propagates uncertainties through emulated dynamical systems driven by uncertain forcing variables. By using analytical first and …

Cybersecurity Issues In The Context Of Cryptographic Shuffling Algorithms And Concept Drift: Challenges And Solutions, Hatim Alsuwat

Theses and Dissertations

In this dissertation, we investigate and address two kinds of data integrity threats. We first study the limitations of secure cryptographic shuffling algorithms regarding preservation of data dependencies. We then study the limitations of machine learning models regarding concept drift detection. We propose solutions to address these threats.

Shuffling Algorithms have been used to protect the confidentiality of sensitive data. However, these algorithms may not preserve data dependencies, such as functional de- pendencies and data-driven associations. We present two solutions for addressing these shortcomings: (1) Functional dependencies preserving shuffle, and (2) Data-driven asso- ciations preserving shuffle. For preserving functional dependencies, …

Ultra-Fast Sensors To Study The Fundamental Neurochemistry Underlying Disease, Alyssa West

Theses and Dissertations

Serotonin is a vital neurotransmitter whose exact roles are ill-defined. Dysfunctions in serotonin signaling are thought to underlie a myriad of neurological problems including depression and autism spectrum disorder (ASD). Prior to investigating serotonin’s role in disease states, one must understand more about the functionality of serotonin in healthy in vivo models. To study serotonin in vivo, fast-scan cyclic voltammetry (FSCV) and fast- scan controlled adsorption voltammetry (FSCAV) are employed to measure evoked and basal serotonin concentration, respectively. These methods, combined with mathematical modeling, provide information regarding regulatory mechanisms of serotonin neurotransmission. FSCV and FSCAV are first applied to …

Synthesis And Characterization Of Hyaluronic Acid Based Biomaterials For Drug Delivery And Virus Modification, Amanda Wagner

Theses and Dissertations

In this thesis, hyaluronic acid based biomaterials are studied. The properties and potential applications of these polymers are characterized and discussed.

In Chapter 1, biomaterials are introduced as well as hydrogels and nanogels. Hyaluronic acid is highlighted as a remarkable bio-polymer. The overall objectives of my research are also discussed.

Chapter 2 is focused around trials for utilizing graphene oxide as a nanomaterial for controlling the drug release of an aromatic compound. Hyaluronic acid based hydrogels were synthesized as a delivery vessel. The results of the drug release profiles are examined and discussed.

A different direction is taken in Chapter …

Numerical Methods For A Class Of Reaction-Diffusion Equations With Free Boundaries, Shuang Liu

Theses and Dissertations

The spreading behavior of new or invasive species is a central topic in ecology. The modelings of free boundary problems are widely studied to better understand the nature of spreading behavior of new species. From mathematical modeling point of view, it is a challenge to perform numerical simulations of free boundary problems, due to the moving boundary, the stiffness of the system and topological changes.

In this work, we design numerical methods to investigate the spreading behavior of new species for a diffusive logistic model with a free boundary and a diffusive competition system with free boundaries. We develop a …

Machine Learning Based Ultra High Carbon Steel Image Segmentation, Sumith Kuttiyil Suresh

Theses and Dissertations

Mechanical and structural properties of ultra-high carbon steel are determined by their microstructures composed of constituents such as pearlite and spheroidites. Locating micro constituents and quantitatively measuring its presence is key for material researchers to study the physical properties of the carbon steel materials. This micrograph analysis is currently done manually and subjectively by material scientists, which is tedious and time-consuming. Here we propose to apply the image segmentation algorithm called U-Net to achieve automated labeling of steel microstructures on a subset of ultra- high carbon steel image dataset containing pearlite and spheroidite as the primary micro constituents. Our work …

Phylogenetic Reconstruction Analysis On Gene Order And Copy Number Variation, Ruofan Xia

Theses and Dissertations

Genome rearrangement is known as one of the main evolutionary mechanisms on the genomic level. Phylogenetic analysis based on rearrangement played a crucial role in biological research in the past decades, especially with the increasing avail- ability of fully sequenced genomes. In general, phylogenetic analysis aims to solve two problems: Small Parsimony Problem (SPP) and Big Parsimony Problem (BPP). Maximum parsimony is a popular approach for SPP and BPP which relies on itera- tively solving a NP-hard problem, the median problem. As a result, current median solvers and phylogenetic inference methods based on the median problem all face se- rious …

Insider’S Misuse Detection: From Hidden Markov Model To Deep Learning, Ahmed Saaudi

Theses and Dissertations

Malicious insiders increasingly affect organizations by leaking classified data to unautho- rized entities. Detecting insiders’ misuses in computer systems is a challenging problem. In this dissertation, we propose two approaches to detect such threats: a probabilistic graph- ical model-based approach and a deep learning-based approach. We investigate the logs of computer-based activities to discover patterns of misuse. We model user’s behaviors as sequences of computer-based events.

For our probabilistic graphical model-based approach, we propose an unsupervised model for insider’s misuse detection. That is, we develop Stochastic Gradient Descent method to learn Hidden Markov Models (SGD-HMM) with the goal of analyzing …

A Spatial Heterodyne Spectrometer For Raman Imaging And Remote Spectroscopy, Ashley Nicole Allen

Theses and Dissertations

Raman and Laser-Induced Breakdown Spectroscopy (LIBS) are optical techniques that provide information about the chemical makeup of a sample without any preparation or physical contact with it. For this reason, Raman and LIBS spectrometers are among the instruments selected for NASA’s Mars 2020 rover mission and are being considered for future missions to the Jovian moons, asteroids and comets. Such future missions will require smaller, more ruggedized Raman and LIBS spectrometers, and the new type of spectrometers discussed here, the spatial heterodyne Raman and LIBS spectrometers are being developed for this purpose. The SHS is a wide-field, Fourier transform, stationary …

Cationic Cobaltocene Derivatives And Polyelectrolyte Membranes For Energy Storage Applications, Tianyu Zhu

Theses and Dissertations

Metal-containing polyelectrolytes (or metallo-polyelectrolytes) represent a new class of polymeric materials with distinct properties compared to traditional organo- polyelectrolytes or neutral metallopolymers. This emerging class of synthetic materials is ubiquitous for a myriad of utilities ranging from traditional electrolyte chemistry to biomedicals to sustainable applications, to name just a few. This dissertation work is focused on the design, synthesis, characterization and application of advanced metallo- cations and metallo-polyelectrolytes for energy storage applications. First, a template method to prepare metallo-polyelectrolytes based on cationic cobaltocene and polyethylene backbone was described. The resulting membranes are mechanically tough, ionically conductive and chemically inert. Second, …

Elucidating The Mechanism Of Bone Morphogenetic Protein (Bmp) -Mediated Sox2 Downregulation In Ovarian Cancer, Zainab Motolani Shonibare

Theses and Dissertations

Sex determining region Y-box 2 (Sox2) is a transcription factor essential for maintaining self-renewal and pluripotency of undifferentiated embryonic stem cells. Sox2 is involved in multiple processes of cancer cells, however, regulation of Sox2 expression and the consequences of that regulation in cancer remains elusive. Previously, we demonstrated that BMP9/GDF2 is significantly reduced in expression in ovarian cancer (OVCA) cells, methylated in patient tumors and, promoted anoikis resistance in both breast and OVCA cell lines. In an attempt to identify genes downstream of BMP9 that may provide anoikis resistance, transcriptomics was performed leading to the identification of Sox2, a developmental …

Self-Assembly And Emergent Properties Of Urea Tethered Triphenylamines For The Formation Of Regenerable Radicals, Ammon J. Sindt

Theses and Dissertations

Self-assembly of photoactive compounds in the solid-state can give rise to new photophysical properties. Key to these properties, is how these compounds can be organized in a uniform way. For this, hydrogen bonding building blocks can be used to guide the assembly of these compounds into organized structures. For instance, ureas, thioureas, and squaramides which contain both hydrogen bond donors and acceptors can guide the assembly of small m-xylene macrocycles in three distinct manners: 1-D columns, edge-to-face Herringbone patterns, and interdigitated networks. The former of these is commonly employed in our group to make either linear or macrocyclic dimers …

Heterogeneous Ozonation Of Model Drinking Water Contaminants Using Cbv-720 Zeolite, Benson Maxwell Solomon

Theses and Dissertations

Advanced Oxidation Processes (AOPs) are designed to remove aqueous organic contaminants through their reaction with hydroxyl radicals (HO∙). Ozone is classified as an AOP due to its ability to produce hydroxyl radicals, as well as its ability to oxidize a wide range of organic contaminants. Due to the unselective nature of hydroxyl radicals, many organic and inorganic co-solutes can act as scavengers, reducing the efficiency of an AOP. Here we show a probe system for testing the hypothesis that adsorptive ozonation of contaminants may yield a more selective environment that favors neutral contaminant oxidation over oxidation of co-solutes.

Initial experiments …

Time Series Analysis Of Weather Data In South Carolina, Geophrey Odero

Theses and Dissertations

This thesis discusses time series analysis of weather data in South Carolina for the last fifteen years (January 2003 to December 2017) for Columbia, Greenville and North Myrtle Beach. The first part presents a brief overview of different variables that are used in the analysis. That is, temperature, dew point, humidity and sea level pressure. A short discussion of time series data is also introduced. The second part is about modeling the variables. The models of choice are presented, fitted and model diagnostics is carried out. In the third part, we discuss background on climates of the cities and model …

The Development Of Multi-Functional System That Combine Patterned Hydrogels, Plasmin-Degradable Nanoparticles And Stem Cells For Applications In Tissue Engineering And Growth Factors Delivery, Safaa I. Kader

Theses and Dissertations

This thesis spots the light on the development of a novel multi-functionalized system for application in tissue engineering and on-demand morphogens delivery. Three types of materials used in this study are synthetic polymer, biopolymer, and nanomaterials. Polyethylene glycol (PEG), a synthetic polymer was chosen in this study because of its high biocompatibility, non-immunogenicity, inert nature, ease of modification, and reduces protein denaturation to provide a wide range of physical and mechanical properties. Here, PEG is used one time as a hydrogel, linear polyethylene glycol-co-lactide (LPELA), and another time as peptide-PEG based nanoparticles (PxSPCP). Gelatin, a natural polymer has been widely …

Challenges In Large-Scale Machine Learning Systems: Security And Correctness, Emad Alsuwat

Theses and Dissertations

In this research, we address the impact of data integrity on machine learning algorithms. We study how an adversary could corrupt Bayesian network structure learning algorithms by inserting contaminated data items. We investigate the resilience of two commonly used Bayesian network structure learning algorithms, namely the PC and LCD algorithms, against data poisoning attacks that aim to corrupt the learned Bayesian network model.

Data poisoning attacks are one of the most important emerging security threats against machine learning systems. These attacks aim to corrupt machine learning models by con- taminating datasets in the training phase. The lack of resilience of …

Macromolecular Engineering Of Biomass Polymers And Stimuli-Responsive Materials Towards Enhanced Thermomechanical Properties, Meghan E. Lamm

Theses and Dissertations

Commodity polymers are used in every aspect of daily life, and most of these polymeric materials are synthesized using petroleum-derived sources. There are direct environmental consequences to this petroleum dependence including greenhouse gas emissions and climate change. Biomass-based polymers show promise for the mitigation on negative environmental impact, in comparison with petroleum-derived counterparts. However, some biopolymers suffer from low chain entanglement due to bulky or long side chain structures, resulting in poor mechanical properties. In this dissertation work, macromolecular engineering is used to design biomass-derived polymers featuring a variety of structures and functionalities. Additionally, biopolymer properties (including thermomechanical enhancement) and …