Physical Sciences and Mathematics Commons^™

Machine Learning Methods For Pattern Recognition Analysis Of Genomic And Molecular Data, Kuang Du

Dissertations

While immune therapies achieve remarkable success in treating various cancers, only a subset of patients achieves a durable clinical response, and many exhibit innate or acquired resistance. Precision medicine aims to tailor treatments to individual patients based on specific biological markers, ensuring that each patient receives the therapy most likely to be effective. Predictive biomarkers and gene signatures offer potential for more personalized treatment strategies by identifying patients likely to benefit. Recent studies suggest that gene signatures, comprising sets of genes, hold predictive value for certain clinical variables. Typically derived from biological expert knowledge, these signatures demonstrate substantial predictive potential, …

Knowledge Diffusion In Networks Of Artificial Learners, Ehsan Beikihassan

Dissertations

The dissertation draws inspiration from the topic of peer learning in the social sciences and the study of information dissemination and knowledge diffusion in network science. In particular, it introduces and studies a setting involving a population or network of artificial learners, with the objective of optimizing aggregate performance measures under constraints on training resources. In this context, natural knowledge diffusion processes in networks of interacting artificial learners are studied. The term "natural" refers to processes that emulate human peer learning, where the internal state and learning processes of students remain largely opaque, and the main degree of freedom lies …

Interactive Visualization Workflows For Mitigating Analytical Uncertainty, Kaustav Bhattacharjee

Dissertations

This dissertation takes a process-centric and stakeholder-first perspective for handling analytical uncertainty: the form of uncertainty that confronts data analysts' insight-generation processes in high-consequence decision-making scenarios. The cost of an incorrect decision when data is used for movie recommendations as opposed to when personal data is used to drive insights or when data-driven modeling is used to drive real-time decisions for maintaining the health of a grid are vastly different in terms of consequences. This dissertation looks at analytical uncertainty in two real-world scenarios: i) how sensitive information leakage can be prevented during the open data release process with data …

Visual Analytic Techniques For Interpretable Algorithmic Ranking Systems, Jun Yuan

Dissertations

Rankings have a profound impact on the increasingly data-driven society. From leisurely activities like the movies to watch, the restaurants to patronize; to highly consequential decisions, like making educational and occupational choices or getting hired by companies— these are all driven by sophisticated yet mostly opaque algorithmic rankers. A small change in how these rankers order the data items can have profound consequences, like deterioration of the prestige of a university or a job applicant missing out on being on the list of the top candidates for an organization. These scenarios necessitate data-driven and human-centered innovation to make rankers accessible, …

Crowd-Sourced Learning For Computer Graphics Applications, Yunhao Zhang

Dissertations

Computer Graphics (CG) revolves around virtual content creation using computational methods, spanning applications from games to visual effects. Typically, the creation of CG content is led by expert practitioners who guide computational algorithms towards satisfactory results. Thus, creating CG content often requires manual iterations encompassing algorithm design, parameter tuning, and aesthetic feedback. This work investigates how to leverage crowd-sourcing to streamline such creation processes, focusing on animation and simulation. In animation, a novel crowd-sourcing framework is proposed for combat animation, enabling users to analyze motion similarities, and retrieve matching motions using novel crowd-sourced motion features. Such features enable quantifying previously …

Establishment Of Structure-Property-Processing Relationships For Design Of Sprayable Hydrogels And Amyloid/Peo Electrospun Composites, Xianjun Wang

Dissertations

The focus of this dissertation is the design, synthesis, characterization, and prototyping of bio-inspired materials to understand the role of structure, intermolecular interactions, and processing technique on the self-assembly, bioactive properties, and mechanical properties of the biomaterials. This work is divided into three research areas: 1) sprayable and adhesive glycopolymer based hydrogels; 2) decapeptide-based composite nanofiber mats; and 3) prototyping sutures and meshes via electrospinning. The established structure-property-processing relationships provide a foundation for designing biomaterials in the future.

The first chapter provides an introductory overview of the requirements necessary for the development of hydrogels, glycopolymers, and peptides, including relevant processing …

Investigation Of Polybenzoxazine Vitrimers Based On Dynamic Transesterification Exchange, Jaylen Davis

Dissertations

With the ever-increasing issue of plastic waste production, a greener approach to synthetic processes and increased sustainability in plastic materials is still a high demand. Thermosets, which find uses in applications such as coatings, adhesives, and aerospace composites account for 15% of global plastics production, are particularly problematic in this context, as covalent crosslinks within the material serve both as a source of high-performance stability during use and as a barrier to conventional recycling after use. Therefore, our efforts focus on the incorporation of dynamic transesterification exchange chemistry into polybenzoxazine thermosets, which allows these materials to undergo reprocessing. This investigation …

Influence Of Glycopolymer Structure On Amphiphilic, Hybrid, Linear Branched Block Copolymer Properties For Use In Biomedical Applications, Kevin Green

Dissertations

The focus of this dissertation is evaluating and adding fundamental knowledge regarding the structure-property relations of glycopolymers used in the design of hybrid block copolymers (HBC) that are cable of self-assembling into delivery vehicles for biomedical applications. A shift to the utilization of natural materials in the design and fabrication of drug-delivery vehicles has garnered significant attention. Understanding the effects of linear glycopolymers content and composition on the resulting HBCs properties can provide valuable insight into how these materials may be tailored for use in targeted biological applications.

The first chapter introduces current literature on the need for improvement in …

Sedimentary Characteristics Of Flood Deposits In Coastal And Fluvial Environments: Examples From Washover Fans (North Carolina, Usa) And Floodplain Deposits (Mississippi, Usa), Shara Gremillion

Dissertations

Extreme flooding from severe and prolonged meteorological events and / or overbanking rivers are some of the most deadly and expensive disasters globally, impacting millions of lives, the environment, and property. People living in vulnerable areas, such as near coasts and rivers, are the first to be impacted with effects of these flood hazards. Scientific studies and their results can aid communities and officials in planning and preparing for those flood impacts. In this three-part study, flood impacts from coastal storms in North Carolina, and flooding along the Mississippi River (MSR) in the state of Mississippi, USA are assessed from …

Single-Shot Mev-Resolution Hard X-Ray Spectrograph For Cavity-Based X-Ray Free Electron Laser, Keshab Kauchha

Dissertations

The Cavity-Based X-ray Free Electron Laser (CBXFEL) is a possible future direction in the development of fully coherent hard X-ray sources of high spectral brilliance, a narrow spectral bandwidth of ≃ 1 − 100 meV, and a high repetition rate of ≃ 1 MHz. A diagnostic tool is required to measure CBXFEL spectra with a meV resolution on a shot-to-shot basis.

The CBXFEL hard X-ray spectrograph is designed to image 9.831 keV X-rays in a ≃ 200 meV spectral window and with a spectral resolution of a few meV using an LCLS XFEL (Linac Coherent Light Source X-ray Free Electron …

Tackling Toxicity And Harassment In Online Environments Through The Use Of Artificial Intelligence, Heba Saleous

Dissertations

With the increase in popularity of online communities, such as social media platforms, online games, and chatroom servers, there is a need to improve chat and content moderation. Platforms have reported an increase in the prevalence of toxic behavior and hate speech. Meanwhile, moderators are reporting difficulties in keeping up with the amount of data to check as well and the type of content they are exposed to, which further harms their own mental health. The main objective of this work is to address the challenges that exist within online communities with the rising prevalence of hate speech. Additionally, some …

The Implementation Of Stream In Mathematics Classrooms In Abu Dhabi Primary Schools: Prospects, Priorities, Processes, And Problems, Nadeia Rashed Alalawi

Dissertations

This study shed light on implementing science, technology, reading and writing, engineering, art, and mathematics (STREAM) in mathematics classrooms in Abu Dhabi primary schools. The study aimed to explore mathematics teachers’ views on the prospects, priorities, processes, and problems of the implementation of STREAM in their classrooms. The study employed qualitative methods to collect and analyze data to support the findings using interviews, classroom observations, and document analysis. Fifteen in-service mathematics teachers were interviewed to explore their views about the application of STREAM in their classrooms regarding prospects, priorities, processes, and problems (4 Ps). Then, three of them were observed …

Development And Benchmark Of Polarizable Models For Ions, Luke Landry

Dissertations

Metalloproteins are ubiquitous in biology, playing crucial roles in diverse processes. Meanwhile, molecular simulations have become an important tool in scientific research. To accurately simulate metalloprotein systems, accounting for polarization and charge transfer effects is required. The fluctuating charge (FQ) model can effectively simulate the charge transfer effect, but the existing models often lack specificity for metalloproteins. In our research, a tailored FQ model for zinc-containing metalloproteins, leveraging the extended charge equilibration (EQeq) scheme, was introduced. CM5 charges were used as the target in our model parameterization, which offers advantages over RESP/CHELPG charges. Most notably, CM5 charges hold independence over …

Reclaiming Healing Spaces: A Phenomenological Study On The Transformative Power Of Outdoor Therapy From The Lived Experiences Of Black Clinicians Working With Black Clients, Lynn Murphy

Dissertations

This phenomenological study involved assessing the experiences of Black therapists who engaged Black clients in outdoor therapeutic contexts. The study was founded on the existing literature that shows the quality of the therapeutic relationship is pivotal for client retention and the Western standards that have historically favored treatment within indoor environments. To contextualize this research, a comprehensive literature review was commenced, covering topics such as the decolonization of therapy, the historical and present-day relationship between Blacks and the outdoors in the United States, sedentary lifestyles, the psychological benefits of time spent in nature, various types of outdoor therapy, and the …

Multi-Label Classification Using Conformal Prediction, Chhavi Tyagi

Dissertations

In many machine learning applications, such as image tagging, document classi-fication, and medical diagnosis, a data instance can be associated with multiple classes in parallel so that each instance is associated with multiple response variables simultaneously defining multi-label classification. Standard multi-label classification methods that provide point predictions have been developed. They lack in quantifying the uncertainty of predictions. These methods also lack in accounting for label dependencies and are very computationally expensive. This dissertation develops two methods of multi-label classification using conformal prediction that quantify the uncertainty of predictions. Chapter 1 introduces notations and tools that have been used in …

A Micromagnetic Study Of Skyrmions In Thin-Film Multilayered Ferromagnetic Materials, Nicholas J. Dubicki

Dissertations

Magnetic skyrmions are topologically protected, localized, nanoscale spin textures in non-centrosymmetric thin ferromagnetic materials and heterostructures. At present they are of great interest to physicists for potential applications in information technology due to their particle-like properties and stability. In a system of multiple thin ferromagnetic layers, the stray field interaction was typically treated with various simplifications and approximations. It is shown that extensive analysis of the micromagnetic equations leads to an exact representation of the stray field interaction energy in the form of layer interaction kernels, a so-called 'finite thickness' representation. This formulation reveals the competition between perpendicular magnetic anisotropy …

Enhancing Community Flood Resilience By Incorporating Landscape Hydrological Sensitivity And Connectivity, Wenlong Feng

Dissertations

Rapid urban expansion and dramatic climate change have significantly increased the intensity and frequency of floods worldwide. With rising flood risks, conventional flood defense strategies that rely on structural measures become ineffective. The present designations for flood-prone areas, such as FEMA's flood maps, are becoming unreliable. Flood risk management is shifting toward enhancing community flood resilience, highlighting the importance of non-structural approaches. Landscape resilience has become a foundation of community flood resilience. However, past urban development typically undermined natural hydro-ecological functions and landscape resilience because of poor recognition of landscapes' ecological role, hydrological sensitivity, and hydrological connections. This study aims …

Certifying Stability In Runge-Kutta Schemes: Algebraic Conditions And Semidefinite Programming, Austin Juhl

Dissertations

Numerical stability is a critical property for a time-integration scheme. In the context of Runge-Kutta methods applied to stiff differential equations, A-stability is one of the most basic and practically important notions of stability. Dating back to the work of Dahlquist, it has been known that A-stability is equivalent to the Runge-Kutta stability function satisfying a particular convex feasibility problem. Specifically, up to a transformation, the stability function lies in the convex cone of positive functions. In recent years, sum-of-squares optimization and semidefinite programming have become valuable tools in developing rigorous certificates of stability in dynamical systems. Therefore, it is …

Federated Learning Systems For Mobile Sensing Data, Xiaopeng Jiang

Dissertations

Federated Learning (FL) has emerged as a new distributed Deep Learning (DL) paradigm that enables privacy-aware training and inference on mobile devices with help from the cloud. This dissertation presents a comprehensive exploration of FL with mobile sensing data, covering systems, applications, and optimizations.

First, a mobile-cloud FL system, FLSys, is designed to balance model performance with resource consumption, tolerate communication failures, and achieve scalability. In FLSys, different DL models with different FL aggregation methods can be trained and accessed concurrently by different apps. In addition, FLSys provides advanced privacy-preserving mechanisms and a common API for third-party app developers to …

Data Driven Decision Making For Sustainable Planning And Operations Of Large Scale Networks, Bahareh Kargar

Dissertations

This dissertation explores data-driven decision-making networks, focusing on sustainable planning and operations for large-scale systems such as healthcare supply chains and power systems. One significant application in healthcare is the optimization of vaccine supply chains. An agent-based simulation-optimization modeling framework is developed to enhance the efficiency and sustainability of vaccine distribution. First, an agent-based epidemiological model of COVID-19 is extended to capture disease transmission dynamics and forecast the number of susceptible individuals and infections. Then, a sustainable vaccine supply chain considering the impacts of greenhouse gases is developed and integrated with the simulation model to minimize total costs and environmental …

Electrified Membrane For Water Treatment And Resource Recovery: Advancing Multiscale Strategies In Gas-Involving Reactions, Jianan Gao

Dissertations

Multifunctional, modular, and scalable water treatment technologies that operate without chemical additives are crucial for addressing global water pollution challenges. While traditional membrane-based separation processes are crucial for ensuring clean water supplies, they primarily focus on pollutant removal rather than on the upcycling of pollutants into valuable resources. Electrified membrane filtration presents a robust alternative, utilizing minimal or no chemical additives and harnessing electrical power to directly reduce contaminants or produce reactive oxidants or reductants on-site.

This dissertation is dedicated to the development of innovative electrochemically reactive membranes designed to address three major challenges: (1) the engineering of electrocatalysts with …

A Methodological Framework For Ontology Development, Enrichment, And Application In Natural Language Processing Tasks, Navya Martin Kollapally

Dissertations

Electronic Health Records (EHRs) have been widely used in healthcare to record demographics, vital signs, test results, immunizations, medical imaging reports, differential diagnoses, etc. It is now accepted that non-clinical (e.g., social) factors have a substantial influence on health outcomes. Hence, it is desirable to record these Social and Commercial Determinants of Health (SDoH & CDoH) in an EHR. The "non-text parts" of EHR notes (e.g., data tables) rely on coded terms from underlying ontologies or terminologies to facilitate semantic interoperability. Ontologies help define concepts, the relationships between them, and instances that can be utilized in research.

The first accomplishment …

Microwave Catalysis-Enabled Membrane Processes For Microbial Inactivation, Fangzhou Liu

Dissertations

The COVID-19 pandemic has highlighted the urgent need for advanced technologies to combat virus transmission. Traditional membrane filtration technologies primarily serve as physical barriers, capturing pollutants but failing to inactivate microbial agents such as bacteria and viruses. These membranes typically target larger particles but are ineffective against sub-micrometer viral particles. Thus, there's a critical demand for membrane filtration processes that combine robust filtration with antifouling and reaction -enabled functions for efficient pathogen disinfection. This research explores a novel microwave-assisted membrane filtration process incorporating catalytic reactions to enhance microbial disinfection and prevent membrane fouling, offering a groundbreaking solution to global challenges …

Numerical Techniques For Improving Simulations Of Tropical Cyclones, Yassine Tissaoui

Dissertations

The increasing frequency and intensity of tropical cyclones (TCs) due to climate change pose significant challenges for forecasting and mitigating their impacts. Despite advancements, accurately predicting TC rapid intensification (RI) remains a challenge. Large eddy simulation (LES) allows for explicitly resolving the large eddies involved in TC turbulence, thus providing an avenue for studying the mechanisms behind their intensification and RI. LES of a full tropical cyclone is very computationally expensive and its accuracy will depend on both explicit and implicit dissipation within an atmospheric model. This dissertation presents two novel numerical methodologies with the potential to improve the efficiency …

Large Deviation Theory In Stochastic Processes: Applications To Biological Modeling, Moshe C. Silverstein

Dissertations

This dissertation delves into developing and applying stochastic models to analyze complex biological systems. It leverages Large Deviation Theory (LDT) to gain insights into these systems, focusing on two key examples: neural networks and calcium signaling dynamics. Traditional deterministic methods frequently fail to capture biological processes' randomness and inherent variability. Meanwhile, many stochastic approaches struggle to be mathematically tractable or provide accessible insights. The approach introduced in this study provides rigorous mathematical frameworks to enhance understanding of these stochastic behaviors while remaining tractable and insightful.

A stochastic model for a random biological neural network is constructed that addresses the dependencies …

Efficient Numerical Methods For Monge-Ampere Type Equations, Jake S. Brusca

Dissertations

Current numerical methods for Monge-Ampere-type equations and Optimal Transport problems face challenges when handling higher dimensions and large-scale data. This dissertation aims to develop and analyze efficient, highly parallelizable numerical algorithms for solving the Monge-Ampere equation to address these issues. Two approaches are employed:

(1) The discretization method is enhanced by introducing an integral repre-sentation of the Monge-Ampere operator. This integral can be discretized using higher-order quadrature, yielding a more efficient, higher-order monotone scheme that allows for narrower stencils. An additional advantage of this discretization is its natural extension to arbitrary dimensions.

(2) The nonlinear solvers for this scheme are …

Delta-Shaped Approximation Based Homotopy Analysis Method For Nonlinear Poisson-Type Partial Differential Equations, Cyril Ocloo

Dissertations

This research aims to solve nonlinear Poisson-type partial differential equations (PDEs) by the approach of the homotopy analysis method (HAM) incorporated with approximate particular solutions (APS) using Delta-shaped basis (DSB) approximations.

With the inclusion of the h auxiliary parameters, we tackle nonlinear problems by studying the mathematical characteristics of the h curve. This is to ensure the numerical convergence of the HAM.

In the solution process, we use the homotopy analysis method to convert a nonlinear PDE into linear inhomogeneous PDEs, which are solved using the method of approximate particular solutions with DSB.

A proper value of the h is …

Localized Hermite Method Of Approximate Particular Solutions, Kwesi Acheampong

Dissertations

A localized Hermite method of approximate particular solutions (LHMAPS) is presented in this dissertation. This method is designed to improve the accuracy of the localized method of approximate particular solutions (LMAPS) for solving partial differential equations. LMAPS is a strong-form method that defines local radial basis function approximations to the solution values at a group of collocation points before applying the differential operator to this approximation function. Based on the LMAPS's local scheme, LHMAPS seeks Hermite-type local approximations based on both function values and derivatives. Numerical experiments validate the superior accuracy of the proposed method to the LMAPS by solving …

Elevating Commodity Polymers To Advanced Applications In Polymer Photonics And Polymer-Derived Porous Materials, Mark Robertson

Dissertations

Since the inception of synthetic polymers, polymer-derived materials have permeated into essentially all aspects of our daily lives. The most commonly thought of examples of polymer materials involve single-use, disposable products to increase shelf lives of perishable items, act as personal protective equipment, or provide some degree of convenience for the consumer. However, as we have furthered our understanding of polymer chemistry and polymer physics to develop increasingly sophisticated polymer systems, polymer materials have been employed in incredibly advanced applications. These include solid electrolytes for energy storage, matrices for aerospace grade carbon fiber-reinforced composites, membranes for liquid and gas separations, …

Scalable Solution Of Time-Dependent Pdes Through Component-Wise Exponential Integrator, Chelsea Drum

Dissertations

Exponential integrators, such as exponential Runge-Kutta or Rosenbrock methods, are designed specifically for the time integration of stiff systems of ordinary differential equations (ODEs) and allow the use of larger time steps than other general-purpose ODE solvers. However, these methods rely on computing matrix function-vector products that are traditionally computed using a Krylov projection, such as Lanczos or Arnoldi iteration, that involves substantial computational expense at high spatial resolution. Krylov Subspace Spectral (KSS) methods' frequency-dependent approach, designed to circumvent stiffness in linear problems, computes these products with greater scalability. We propose the combination of such KSS methods with exponential integrators …