Physical Sciences and Mathematics Commons^™

Computational Analysis Of Antibody Binding Mechanisms To The Omicron Rbd Of Sars-Cov-2 Spike Protein: Identification Of Epitopes And Hotspots For Developing Effective Therapeutic Strategies, Mohammed Alshahrani

Computational and Data Sciences (PhD) Dissertations

The advent of the Omicron strain of SARS-CoV-2 has elicited apprehension regarding its potential influence on the effectiveness of current vaccines and antibody treatments. The present investigation involved the implementation of mutational scanning analyses to examine the impact of Omicron mutations on the binding affinity of four categories of antibodies that target the Omicron receptor binding domain (RBD) of the Spike protein. The study demonstrates that the Omicron variant harbors 23 unique mutations across the RBD regions I, II, III, and IV. Of these mutations, seven are shared between RBD regions I and II, while three are shared among RBD …

Ocean Wave-Coherent Temperature And Humidity Near-Surface Vertical Distributions And Their Effect On Radar Performance Over The Ocean, Mathew James Stanek

Electronic Theses and Dissertations

Large knowledge gaps concerning the effect of ocean surface waves on near-surface vertical distributions of temperature and humidity in the marine atmospheric surface layer exist due to practical limitations and sensor fidelity challenges of direct measurements. Wave effects on these distributions between the wave trough and crest are least studied within the literature. These scalar distributions influence atmospheric refractivity, which can lead to anomalous propagation of electromagnetic energy. Measurements of temperature and humidity are classically made using rocket- or radiosondes and fixed weather stations, and can utilize tethered profiling systems. However, these measurement systems have limitations when obtaining measurements near …

Functional Nanocomposite Coatings For Use In Food Packaging, Camden N. Webb

Master's Theses

Plastics are a class of materials known for their cost and property advantages, increasing significantly in their usage worldwide. Unfortunately, these benefits come with an increasingly concerning environmental impact. A combination of inadequate disposal options and combinations of materials have led to environmental disasters that will impact generations. One of the worst areas for plastic waste is food packaging. Plastic as a material generally excels at durability and longevity, but as food packaging, it outlives its intended purpose by several orders of magnitude. This leads to plastic food packaging materials sitting in landfill or leading to the environment for hundreds …

Visualizing Transaction-Level Modeling Simulations Of Deep Neural Networks, Nataniel Farzan, Emad Arasteh

Engineering Technical Reports

The growing complexity of data-intensive software demands constant innovation in computer hardware design. Performance is a critical factor in rapidly evolving applications such as artificial intelligence (AI). Transaction-level modeling (TLM) is a valuable technique used to represent hardware and software behavior in a simulated environment. However, extracting actionable insights from TLM simulations is not a trivial task. We present Netmemvisual, an interactive, cross-platform visualization tool for exposing memory bottlenecks in TLM simulations. We demonstrate how Netmemvisual helps system designers rapidly analyze complex TLM simulations to find memory contention. We describe the project’s current features, experimental results with two state-of-the-art deep …

Revisiting The Diffuse Layer Polarization Of A Spherical Grain In Electrolytes With Numerical Solutions Of Nernst-Planck-Poisson Equations, Qifei Niu

Geosciences Faculty Publications and Presentations

Induced polarization (IP) has been frequently used in solid earth geophysics, hydrology, and environmental sciences. A mechanistic understanding of the IP responses of geological materials is crucial for correctly interpreting field IP measurements. In this study, the fully-coupled, nonlinear Nernst-Planck-Poisson equations are numerically solved to analyze the electrochemical mechanism of diffuse layer polarization around a spherical grain immersed in electrolytes. The numerical results show diffuse layer polarization is formed by the charge separation between counterions in the diffuse layer and charges on the grain surface. Both tangential and normal movements of counterions in the diffuse layer are involved in the …

Whitewater Sound Dependence On Discharge And Wave Configuration At An Adjustable Wave Feature, Taylor A. Tatum, Jacob F. Anderson, Timothy J. Ronan

Geosciences Faculty Publications and Presentations

Stream acoustics has been proposed as a means of monitoring discharge and wave hazards from outside the stream channel. To better understand the dependence of sound on discharge and wave characteristics, this study analyzes discharge and infrasound data from an artificial wave feature which is adjusted to accommodate daily changes in recreational use and seasonal changes in irrigation demand. Monitorable sound is only observed when discharge exceeds ∼35 m³/s, and even above that threshold the sound-discharge relationship is non-linear and inconsistent. When sound is observed, it shows consistent dependence on wave type within a given year, but the …

Cyber Attack Surface Mapping For Offensive Security Testing, Douglas Everson

All Dissertations

Security testing consists of automated processes, like Dynamic Application Security Testing (DAST) and Static Application Security Testing (SAST), as well as manual offensive security testing, like Penetration Testing and Red Teaming. This nonautomated testing is frequently time-constrained and difficult to scale. Previous literature suggests that most research is spent in support of improving fully automated processes or in finding specific vulnerabilities, with little time spent improving the interpretation of the scanned attack surface critical to nonautomated testing. In this work, agglomerative hierarchical clustering is used to compress the Internet-facing hosts of 13 representative companies as collected by the Shodan search …

Towards A Comprehensive Data Infrastructure For Redox-Active Organic Molecules Targeting Nonaqueous Redox Flow Batteries, Rebekah Duke, Vinayak Bhat, Parker Sornberger, Susan A. Odom, Chad Risko

Chemistry Faculty Publications

The shift of energy production towards renewable, yet at times inconsistent, resources like solar and wind have increased the need for better energy storage solutions. An emerging energy storage technology that is highly scalable and cost-effective is the redox flow battery comprised of redox-active organic materials. Designing optimum materials for redox flow batteries involves balancing key properties such as the redox potential, stability, and solubility of the redox-active molecules. Here, we present the data-enabled discovery and design to transform liquid-based energy storage (D³TaLES) database, a curated data collection of more than 43 000 redox-active organic molecules that are …

Mapping Roles Of Active Site Residues In The Acceptor Site Of The Pa3944 Gcn5-Related N-Acetyltransferase Enzyme, Cillian Variot, Daniel Capule, Xhulio Arolli, Jackson Baumgartner, Cory T. Reidl, Charles Houseman, Miguel Ballicora, Daniel P. Becker Ph.D., Misty L. Kuhn

Chemistry: Faculty Publications and Other Works

An increased understanding of how the acceptor site in Gcn5-related N-acetyltransferase (GNAT) enzymes recognizes various substrates provides important clues for GNAT functional annotation and their use as chemical tools. In this study, we explored how the PA3944 enzyme from Pseudomonas aeruginosa recognizes three different acceptor substrates, including aspartame, NANMO, and polymyxin B, and identified acceptor residues that are critical for substrate specificity. To achieve this, we performed a series of molecular docking simulations and tested methods to identify acceptor substrate binding modes that are catalytically relevant. We found that traditional selection of best docking poses by lowest S scores …

Contributions To Robust Statistical Learning And Its Applications In Biological Spectral Imaging, Ruogu Wang

Legacy Theses & Dissertations (2009 - 2024)

This thesis investigates robust statistical learning and its applications in biological spectral imaging. The first part of this thesis addresses the challenges raised in the statistical learning of robust expectile regression. Expectiles can be obtained through empirical risk minimization (\acrshort{erm}), which minimizes the sum of asymmetrically weighted squared deviations. However, this \acrshort{erm} scheme lacks robustness to abnormal observations and flexibility. To overcome these limitations, we adopt the empirical gain maximization (\acrshort{egm}) scheme that learns expectiles using an asymmetric Gaussian \acrshort{egm} approach. The corresponding \acrshort{erm} can be formulated with a robust expectile loss, which is bounded and nonconvex. Through a learning …

An Analysis Of The Predictability Of The February 2021 Cold Air Outbreak At S2s Timescales, Grace Dines

Legacy Theses & Dissertations (2009 - 2024)

The February 2021 cold air outbreak (CAO) brought long-lasting, freezing temperatures and extreme winter weather to the United States and Canada. The event resulted in major societal and economic impacts, including millions of power outages, hundreds of fatalities, and approximately $25 billion in losses. This thesis first analyzes the synoptic evolution of this CAO in order to explain how Arctic air arrived and stalled over central North America. Given the synoptic context, the analysis next considers the subseasonal-to-seasonal (S2S) predictability of this CAO by examining S2S ensemble model predictions from both high-top and low-top models. The S2S predictability analysis is …

An Assessment Of Coastal Impacts To The Natural And Built Assets Of The New York State Office Of Parks, Recreation And Historic Preservation, Kelsey Ruffino

Legacy Theses & Dissertations (2009 - 2024)

Climate change is expected to cause an increase in heavy precipitation events, flooding, and sea level rise in New York State, which will have significant impacts on coastal areas. Almost half of New York's state parks and historic sites, which are managed by the New York State Office of Parks, Recreation and Historic Preservation (OPRHP), are located in major coastal areas, including the Atlantic Ocean, Hudson River, Lake Erie, and Lake Ontario. As the effects of climate change become more pronounced in these areas, a selection of OPRHP’s infrastructure and natural, cultural, and historic resources will be at risk. To …

Variations And Approximations Of Interleaving Distances, Robert Cardona

Legacy Theses & Dissertations (2009 - 2024)

We present three different topics covering (1) presentation-based distances, (2) approximate nerve theorems, and (3) networks and persistence.We present seven main results (A) - (G).

Near-Optimal Motion Planning Algorithms Via A Topological And Geometric Perspective, Aakriti Kumari Upadhyay

Legacy Theses & Dissertations (2009 - 2024)

Motion planning is a fundamental problem in robotics, which involves finding a path for an autonomous system, such as a robot, from a given source to a destination while avoiding collisions with obstacles. The properties of the planning space heavily influence the performance of existing motion planning algorithms, which can pose significant challenges in handling complex regions, such as narrow passages or cluttered environments, even for simple objects. The problem of motion planning becomes deterministic if the details of the space are fully known, which is often difficult to achieve in constantly changing environments. Sampling-based algorithms are widely used among …

An Evaluation Of High-Resolution Model Simulations Of Orographic Precipitation, Snowpack, Atmospheric Rivers, And Their Climate Sensitivities In The Southern Andes, Erin Potter

Legacy Theses & Dissertations (2009 - 2024)

Orographic precipitation and snowpack are important for water resources and hydrometeorological hazards in the Andes Mountain range. As the climate warms, South American atmospheric rivers (ARs) are expected to increase in frequency and intensity, leading to increased orographic precipitation. Improved understanding of orographic precipitation and snowpack, and their association with ARs, in a warming climate is needed to provide a foundation for understanding future hydroclimate change over the Andes. The goal of this research is to evaluate how well variations in high-resolution regional climate simulations over the southern Andes (30-55°S), agree with observations of (1) orographic precipitation and (2) snowpack …

Exploiting Natural Rna 2′-5′-Linkage In Nucleic Acid Aptamers And Dna Nanostructures, Johnsi Mathivanan

Legacy Theses & Dissertations (2009 - 2024)

Developments in chemical synthesis of nucleic acid sequences and modifications have aided in the study of biomolecular interactions and the roles of modified nucleic acids in biology, medicine, and nanotechnology. This work describes some of the aspects of such developments, from synthesis of chemically modified RNA and DNA aptamers that can bind antibiotics and metal ions to the use of nucleic acids with novel backbone linkages in the construction of nanostructures. Analysis of such nucleic acid structures inform us on the basic structure of these molecules and the resulting functions that are applicable in fields such as biosensing, drug screening …

Scenario Planning In A Post-Pandemic World: Karner Blue Butterfly And The Albany Pine Bush, Senia Quevedo

Legacy Theses & Dissertations (2009 - 2024)

This study outlines four future scenarios for the Karner blue butterfly and the Albany PineBush in a post-pandemic world. Management changes and modifications are becoming more necessary due to the changing climate conditions and habitat loss. The COVID-19 pandemic has changed certain conditions that affect the Karner blue butterfly and its habitats, such as noise and air pollution, increased outdoor recreation, and pausing development along the pine bush borders. A scenario planning model was used to better understand how policy and lockdown restrictions being lifted will affect the Karner blue butterfly population after the Albany Pine Bush surveyed a record-high …

The Development Of A Statistical Postprocessing Algorithm By Two-Step Space-Time Eof Analysis, William David Stikeleather

Legacy Theses & Dissertations (2009 - 2024)

Model prediction for extended range forecasts is fraught with shortcomings that generate forecast error and decrease skill. Biases in Numerical Weather Prediction (NWP) models generate patterns of error that grow larger with time. These inherent biases systematically alter the modeled positioning of atmospheric features that emerge as synoptic or subseasonal error. While individual weather events and anomalous patterns will generate model noise, it is computationally possible to separate the signal behind this error from noise. For 200 hPa Geopotential Height (Z200), systematic biases in model forecasts often manifest themselves as errors in atmospheric wave patterns in the high latitudes, including …

Novel Applications Of Enhanced Raman Spectroscopy For Drug Discovery, Mrna Vaccine Stability Assessment, And Forensic Purposes, Lamyaa M. Almehmadi

Legacy Theses & Dissertations (2009 - 2024)

The main focus of this dissertation was to apply enhanced Raman spectroscopy techniques to a variety of applications, ranging from drug discovery, mRNA vaccine stability, to forensic analysis. There are five chapters in this dissertation. The first chapter discusses the basics of enhanced Raman spectroscopy techniques and their relevance. The second chapter is focused on the use of surface-enhanced Raman spectroscopy (SERS) for drug discovery. The third chapter introduces the use of deep ultraviolet resonance Raman (DUVRR) spectroscopy for the detection of mRNA degradation in a mRNA vaccine model. The fourth chapter introduces the use of stand-off Raman spectroscopy in …

Distinguishing Between Living And Dead Plant Material From The Red Spruce Using Atr Ft-Ir Spectroscopy, Bailey Ann Hoplight

Legacy Theses & Dissertations (2009 - 2024)

Spectroscopic methods have recently been used to analyze plant species and maturation. However, there is a lack of research into employing spectroscopy for distinguishing living plant material and dead plant material, which is important for the agriculture and environmental health fields. Here in this study, we have shown the potential of ATR-FT IR (Attenuated total reflectance Fourier transformed infrared spectroscopy) to classify plant materials as living or dead through the help of multivariate statistical analysis methods. Plant samples were from the roots and needles of picea rubens, more commonly known as the red spruce tree. The samples were classified by …

Proceedings Of The 2023 Berry Summer Thesis Institute, University Of Dayton. University Honors Program

Proceedings of the Berry Summer Thesis Institute (2013-Present)

Thanks to a gift from the Berry Family Foundation and the Berry family, the University Honors Program launched the Berry Summer Thesis Institute in 2012. The institute introduces students in the University Honors Program to intensive research, scholarship opportunities and professional development. Each student pursues a 12-week summer thesis research project under the guidance of a UD faculty mentor. This contains the product of the students' research.

Contents:

• “How Porous Materials Affect the Boundary-Layer Transition of Hypersonic Flight Vehicles” (Megan C. Sieve)
• “Ultra-Stretchable, Self-Healing, DLP 3D-Printed Elastomers for Damage-Resistant Soft Robots: A Review” (Robert M. A. Drexler)
• “Extrapolation of Scalar …

Fostering A Sense Of Wonder: Promoting Experiential Learning Through Outdoor Discoveries On The Coast Of Maine, Joslyn Primicias

Honors Theses

Recent generations of children have been experiencing a decrease in connection to Nature, causing various negative effects on personal development and well-being. Researchers are studying the impact of environmental education programs as a potential resolution to this issue dubbed “nature deficit disorder.” Studies have shown that while citizen science by youth is rapidly expanding, little research addresses conservation science with environmental education. Recognizing this gap, the summer camps at Wells NERR are designed to ensure children’s environmental stewardship as they learn about estuarine ecology alongside environmental issues. This educational study focuses on how environmental education through estuarine activities at summer …

Knowledge Representation For Conceptual, Motivational, And Affective Processes In Natural Language Communication, Seng Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria

Research Collection School Of Computing and Information Systems

Natural language communication is an intricate and complex process. The speaker usually begins with an intention and motivation of what is to be communicated, and what outcomes are expected from the communication, while taking into consideration the listener’s mental model to concoct an appropriate sentence. Likewise, the listener has to interpret the speaker’s message, and respond accordingly, also with the speaker’s mental model in mind. Doing this successfully entails the appropriate representation of the conceptual, motivational, and affective processes that underlie language generation and understanding. Whereas big-data approaches in language processing (such as chatbots and machine translation) have performed well, …

Transferable Curricula Through Difficulty Conditioned Generators, Sidney Tio, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Advancements in reinforcement learning (RL) have demonstrated superhuman performance in complex tasks such as Starcraft, Go, Chess etc. However, knowledge transfer from Artificial "Experts" to humans remain a significant challenge. A promising avenue for such transfer would be the use of curricula. Recent methods in curricula generation focuses on training RL agents efficiently, yet such methods rely on surrogate measures to track student progress, and are not suited for training robots in the real world (or more ambitiously humans). In this paper, we introduce a method named Parameterized Environment Response Model (PERM) that shows promising results in training RL agents …

Proxy Hunting: Understanding And Characterizing Proxy-Based Upgradeable Smart Contracts In Blockchains, William E Iii Bodell, Sajad Meisami, Yue Duan

Research Collection School Of Computing and Information Systems

Upgradeable smart contracts (USCs) have become a key trend in smart contract development, bringing flexibility to otherwise immutable code. However, they also introduce security concerns. On the one hand, they require extensive security knowledge to implement in a secure fashion. On the other hand, they provide new strategic weapons for malicious activities. Thus, it is crucial to fully understand them, especially their security implications in the real-world. To this end, we conduct a large-scale study to systematically reveal the status quo of USCs in the wild. To achieve our goal, we develop a complete USC taxonomy to comprehensively characterize the …

Decompiling X86 Deep Neural Network Executables, Zhibo Liu, Yuanyuan Yuan, Shuai Wang, Xiaofei Xie, Lei Ma

Research Collection School Of Computing and Information Systems

Due to their widespread use on heterogeneous hardware devices, deep learning (DL) models are compiled into executables by DL compilers to fully leverage low-level hardware primitives. This approach allows DL computations to be undertaken at low cost across a variety of computing platforms, including CPUs, GPUs, and various hardware accelerators. We present BTD (Bin to DNN), a decompiler for deep neural network (DNN) executables. BTD takes DNN executables and outputs full model specifications, including types of DNN operators, network topology, dimensions, and parameters that are (nearly) identical to those of the input models. BTD delivers a practical framework to process …

Hyperbolic Graph Topic Modeling Network With Continuously Updated Topic Tree, Ce Zhang, Rex Ying, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Connectivity across documents often exhibits a hierarchical network structure. Hyperbolic Graph Neural Networks (HGNNs) have shown promise in preserving network hierarchy. However, they do not model the notion of topics, thus document representations lack semantic interpretability. On the other hand, a corpus of documents usually has high variability in degrees of topic specificity. For example, some documents contain general content (e.g., sports), while others focus on specific themes (e.g., basketball and swimming). Topic models indeed model latent topics for semantic interpretability, but most assume a flat topic structure and ignore such semantic hierarchy. Given these two challenges, we propose a …

An Adaptive Large Neighborhood Search For Heterogeneous Vehicle Routing Problem With Time Windows, Minh Pham Kien Nguyen, Aldy Gunawan, Vincent F. Yu, Mustafa Misir

Research Collection School Of Computing and Information Systems

The heterogeneous vehicle routing problem with time windows (HVRPTW) employs various vehicles with different capacities to serve upcoming pickup and delivery orders. We introduce a HVRPTW variant for reflecting the practical needs of crowd-shipping by considering the mass-rapid-transit stations, as the additional terminal points. A mixed integer linear programming model is formulated. An Adaptive Large Neighborhood Search based meta-heuristic is also developed by utilizing a basic probabilistic selection strategy, i.e. roulette wheel, and Simulated Annealing. The proposed approach is empirically evaluated on a new set of benchmark instances. The computational results revealed that ALNS shows its clear advantage on the …

Experimental Study Of Linux Flightsize Estimation, Mingrui Zhang

School of Computing: Dissertations, Theses, and Student Research

Transmission Control Protocol (TCP) is a fundamental Internet protocol responsible for controlling and coordinating the Internet traffic. As a result, TCP significantly influences the overall performance and stability of the Internet. One critical information required by a TCP connection to make decisions is FlightSize, which is the total amount of outstanding data contributed by the connection to the Internet. The FlightSize information is used by a TCP connection to determine its future sending rate and also avoid traffic congestion and collapse in the Internet. Consequently, an inaccurate estimation of FlightSize can result in degraded performance and instability of the Internet. …

Seek And Classify: End-To-End Joint Multi-Signal Detection And Classification Using Deep Learning, Prashant Subedi

School of Computing: Dissertations, Theses, and Student Research

The rise in the use of wireless communication has led to the problem of spectrum scarcity in licensed bands. The popularity of Internet of Things (IoT) requires innovative solutions that maximize the use of available spectrum to support the increasing number of connected devices. This thesis tackles two significant problems in wireless communication: the need for efficient spectrum sensing techniques and the scarcity of large, diverse raw in-phase (I) and quadrature (Q) datasets.

The ability to detect and classify modulation of the signals efficiently can enable a cognitive radio to monitor the spectrum activity in real time and utilize unused …