Physical Sciences and Mathematics Commons^™

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 …

Global Energy Consumption: An Analysis Of Variables That Shape Per Capita Usage, Or How Pump Price, Urbanization, And Fossil Fuels Imports Impact Fossil Fuels Consumption Per Capita Across Oecd Countries, Mila Demchyk Savage

Graduate Program in International Studies Theses & Dissertations

Among reasons explaining the importance of studying fossil fuel consumption are: crude oil is a subject of the international commodities market, thus, any fluctuation related to its' availability or price would impact the rest of the World; natural resources like oil, gas, and coal are limited; the extensive use of fossil fuels harms our surroundings, creating many environmental concerns; every human (on average) has been using more energy since 1971 and the trend is expected to continue. The upward trend is not consistent among individual countries. Therefore, the core question of my research is, `Why do some countries consume less …

Concentration Theorems For Orthonormal Sequences In A Reproducing Kernel Hilbert Space, Travis Alvarez

All Dissertations

Let H be a reproducing kernel Hilbert space with reproducing kernel elements {Kx} indexed by a measure space {X,mu}. If H can be embedded in L2(X,mu), then H can be viewed as a framed Hilbert space. We study concentration of orthonormal sequences in such reproducing kernel Hilbert spaces.

Defining different versions of concentration, we find quantitative upper bounds on the number of orthonormal functions that can be classified by such concentrations. Examples are shown to prove sharpness of the bounds. In the cases that we can add "concentrated" orthonormal vectors indefinitely, the growth rate of doing so is shown.

Nonlinear Charge And Spin Currents In Non-Centrosymmetric Electron Systems, Aniruddha Pan

All Dissertations

In this thesis, we discuss the existence of spin and charge currents in systems with broken spin inversion symmetry proportional to the magnitude square of the driving electric and thermal fields. This outcome is predicated on symmetry considerations in the momentum space, whereby the product between the current operator and the out-of-equilibrium distribution function has to be even.

First, we derive the second-order correction to the particle distribution function $\delta f^{(2)}$ in a semi-classical approximation, considering the local change in the equilibrium distribution function caused by external fields. Our approach departs significantly from the previous theory where $\delta f^{(2)}$ is …

Innovations In Geospatial Technologies For Water And Environmental Resource Protection, Madeleine Bolick

All Dissertations

New technologies and applications of technologies are critical to protecting environmental and water resources. Students need to be aware of these new technologies so they can be prepared to utilize them in their future careers. One such technology is using Unmanned Aerial Vehicles (UAVs) because it can be applied to a wide variety of fields such as engineering, construction, wildlife biology, agriculture, and many more. Chapter two discusses the creation of an online teaching module to introduce students to using UAVs in natural resource research and evaluates how well students respond to the education module. Overall, student familiarity with UAVs …

Electron-Transfer Mediated Photo-Switching In Nanoparticles, Liaoran Cao

All Dissertations

Previous publications from our lab demonstrated viable approaches to design a photo-switching nanoparticle with arguably superior brightness and photostability resulting in an improved resolution in localization-based microscopy, as compared to other photo-switching dyes or particles. As a follow-up, this dissertation is focused on two major tasks: first, developing nanoparticles with better photo-switching properties for super-resolution imaging; second, trying to achieve a better physical picture of the mechanisms involved in photo-switching, including polaron dynamics, charge transfer, and energy transfer. A new class of photo-switchable nanoparticles was developed by blending conjugated polymer semiconductor with fullerene-based electron acceptors, and further blending with polystyrene …

Expansion Of The Diazacyclobutene Motif For Antiparasitic Evaluation, Brock Alexander Miller

All Dissertations

Molecules containing N-heterocycles are prevalent in pharmaceutical settings. The ability to generate highly functionalized molecules containing N-heterocycles in very few synthetic operations is valuable for drug discovery. Our group has developed a two-step synthesis to access a rarely studied diazacyclobutene scaffold via a formal [2+2] cycloaddition between 4-phenyl-1,2,4-triazolinedione and electron-rich thioalkynes. Our interest in this scaffold increased exponentially from promising preliminary biological evaluations against a protozoan parasite, Trypanosoma brucei. While we were able to double the number of historical examples of this scaffold, there were significant limitations in our methodology. The most notable limitations were the lack …

Spectroscopy Of Highly Charged Ions For Astrophysical And Laboratory Plasma Diagnostics, Yang Yang

All Dissertations

Electron beam ion traps (EBITs) are small-scale laboratory devices that create and trap highly charged ions (HCI) for spectroscopic studies. These devices create plasma conditions resembling astrophysical environments like stellar winds and supernova remnants, providing valuable insights into astrophysical plasma. Theoretical models for such systems require incorporating relativistic and quantum electrodynamics effects, making experimental studies of HCIs essential for benchmarking these theories.

Spectral analysis of astrophysical and laboratory plasma requires understanding the ionization balance. Accurate atomic data, including excitation, ionization, and recombination cross sections, along with precise knowledge of operating conditions such as electron beam density, electron beam energy, and …

Asymptotic Cones Of Quadratically Defined Sets And Their Applications To Qcqps, Alexander Joyce

All Dissertations

Quadratically constrained quadratic programs (QCQPs) are a set of optimization problems defined by a quadratic objective function and quadratic constraints. QCQPs cover a diverse set of problems, but the nonconvexity and unboundedness of quadratic constraints lead to difficulties in globally solving a QCQP. This thesis covers properties of unbounded quadratic constraints via a description of the asymptotic cone of a set defined by a single quadratic constraint. A description of the asymptotic cone is provided, including properties such as retractiveness and horizon directions.

Using the characterization of the asymptotic cone, we generalize existing results for bounded quadratically defined regions with …

Improving The Design And Conduct Of Aquatic Toxicity Studies With Oils Based On 20 Years Of Croserf Experience, Wa Stubblefield, M Barron, G Bragin, Me Delorenzo, B De Jourdan, B Echols, Dp French-Mccay, P Jackman, Jr Loughery, Tf Parkerton, D. Abigail Renegar, Jl Rodriguez-Gil

Marine & Environmental Sciences Faculty Articles

Laboratory toxicity testing is a key tool used in oil spill science, spill effects assessment, and mitigation strategy decisions to minimize environmental impacts. A major consideration in oil toxicity testing is how to replicate real-world spill conditions, oil types, weathering states, receptor organisms, and modifying environmental factors under laboratory conditions. Oils and petroleum-derived products are comprised of thousands of compounds with different physicochemical and toxicological properties, and this leads to challenges in conducting and interpreting oil toxicity studies. Experimental methods used to mix oils with aqueous test media have been shown to influence the aqueous-phase hydrocarbon composition and concentrations, hydrocarbon …

Seismic Analysis Of The Upper & Lower Falls Of The Yellowstone River, Loring Schaible

Earth and Planetary Sciences ETDs

Twelve years of concurrent hydrologic and continuous seismic data along with temporary seismic data demonstrate that the Upper and Lower Falls of the Grand Canyon of the Yellowstone River comprise a highly localized source of 0.5-5 Hz seismic energy that overwhelms anthropogenic contributions. In aggregate, seismic amplitude from 2008-2019 is linearly related to discharge with a correlation coefficient of 0.96. Repeated deviations from this linear relationship persist for 1-2 weeks prior to the date that Yellowstone Lake becomes clear of winter ice coverage. Seismic efficiency increases by ~50-250% during this period of ice-breakup, during which lake ice flows into the …

Seismic Shadow Zone Investigation In The Upper Magma Reservoir Of The Yellowstone Caldera, Sarah Nolt-Caraway

Earth and Planetary Sciences ETDs

This study investigates whether the Yellowstone Caldera has enough melt to mute S-waves, creating a seismic shadow zone. Using a dense nodal deployment of ~650 stations, 7-9 earthquakes during the nodal deployment, and 21 broadband stations with 3,000-4,000 events per station; amplitude and noise maps, seismograms, and automatic phase picks probabilities from a deep learning model were analyzed to assess the potential role of melt, crustal attenuation, and noise in affecting body waves, particularly S-phases. The results are inconclusive, with unclear evidence whether observed amplitude decay is normal signal decay due to distance, noise-related, melt, or from scattering and intrinsic …

Testing The Niche Center Hypothesis In The Fossil Record Of Atlantic Bivalves, Rhiannon Z. Nolan

Earth and Planetary Sciences ETDs

Paleoecological analyses of six shallow marine bivalves were conducted to test the Abundant Center Hypothesis using data from the fossil record of the Pleistocene through modern day. This hypothesis predicts the highest abundance of a species is at the center of the geographic or environmental range, decreasing toward the edges. In geographic space, distances to a centerline within a geographic range were variably correlated with population abundances, and some species displayed a sharp drop-off in abundance as distance increased. In environmental space, bivalve species showed moderate correlations between abundance and centrality when measured using cumulative data across the last 2.8 …

Super-Resolution Microscopy With Color Centers In Diamond, Forrest A. Hubert

Optical Science and Engineering ETDs

This dissertation explores the development and application of diamond color centers, specifically the silicon-vacancy (SiV) and nitrogen-vacancy (NV) centers, in super-resolution microscopy and magnetic imaging techniques. It demonstrates the potential of SiV centers as photostable fluorophores in stimulated emission depletion (STED) microscopy, with a resolution of approximately 90 nm. The research also presents a method for nanoscale magnetic microscopy using NV centers by combining charge state depletion (CSD) microscopy with optically detected magnetic resonance (ODMR) to image magnetic fields produced by 30 nm iron-oxide nanoparticles. The individual magnetic feature width reaches ~100 nm while resolving magnetic field patterns from nanoparticles …

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 …

Two-Dimensional Crystal Phases Of Graphene Monoxide & Interaction Of Lithium With Graphene Monoxide, Danylo Radevych

Theses and Dissertations

This work explores the possible existence, properties, and potential applications of different polytypes of graphene monoxide (GmO) - two-dimensional crystalline monolayers composed of equal numbers of O and C atoms. In addition to previously experimentally discovered and theoretically modeled α phase, prediction and discovery of the second phase - β-GmO - is reported along with evaluation of six other possible phases. Structural parameters, electronic and mechanical properties of all the phases, including α-GmO, are determined using density functional calculations and compared. It is suggested that multiple phases of GmO can co-exist in the same composite, and developing a synthesis process …

Construction Of Zinc Oxide And Magnesium Oxide Heterostructures By Atomic Layer Deposition, Netra Sharma

Theses and Dissertations

Zinc oxide (ZnO) has gained wide technological interest due to its direct bandgap of ~3.37 eV and high exciton binding energy of ~60 meV and has exhibited promise for numerous electronics and opto-electronics applications. ZnO can also be alloyed with materials like magnesium oxide (MgO) to tailor the bandgap. Such heterostructures (Zn, Mg)O can be used in optoelectronic devices like quantum well lasers, photodetectors, etc.In this work, we studied the physical properties of zinc oxide (ZnO), magnesium oxide (MgO) and the heterostructures of zinc and magnesium oxide (Zn,Mg)O grown by atomic layer deposition (ALD) using a homemade viscous flow type …

Cooler Forests In Clean Air, Liang Chen

Department of Earth and Atmospheric Sciences: Faculty Publications

Improving air quality by reducing atmospheric aerosols can bring valuable health benefits, but also generally leads to warming. Now, research suggests that in cleaner air the local cooling effect of planting trees may be stronger in middle and low latitude regions.

Forests provide a substantial sink for atmospheric carbon and therefore have great potential for contributing to climate change mitigation globally.¹ Meanwhile, forests play an important role in local and regional climate through their effects on albedo, evapotranspiration, and surface roughness.² The biogeophysical mechanisms driving forest-climate feedback depend strongly on the local background climate. But it remains unclear …

Aerosol Mutagenicity In San Bernardino, California Via Bacterial Fluctuation Tests, Sean Murphy

Electronic Theses, Projects, and Dissertations

San Bernardino, California’s poor air quality is a health risk to its population with some of the highest concentrations of ozone and aerosol in the United States. Aerosols are solid or liquid particles suspended in the air. Smaller aerosol particles are the most harmful as they are more likely to penetrate further into the respiratory system. These aerosols can cause respiratory issues and contain toxic compounds. One measure of aerosol toxicity is to study the mutagenicity of the aerosol. To study the mutagenicity of aerosol samples collected in San Bernardino in 2022, fluctuation tests (based on the Ames test for …

Geospatial Wildfire Risk Prediction Using Deep Learning, Abner Alberto Benavides

Electronic Theses, Projects, and Dissertations

This report introduces a thorough analysis of wildfire prediction using satellite imagery by applying deep learning techniques. To find wildfire-prone geographical data, we use U-Net, a convolutional neural network known for its effectiveness in biomedical image segmentation. The input to the model is the Sentinel-2 multispectral images to supply a complete view of the terrain features.

We evaluated the wildfire risk prediction model’s performance using several metrics. The model showed high accuracy, with a weighted average F1 score of 0.91 and an AUC-ROC score of 0.972. These results suggest that the model is exceptionally good at predicting the location of …

Restaurant Management Website, Akhil Sai Gollapudi

Electronic Theses, Projects, and Dissertations

In the ever-evolving corporate landscape of today, it is crucial to respond to customer needs as efficiently and in a timely manner as possible. The project's primary objective is to create a method for clients to make reservations for restaurants online. This makes life easier for busy customers in their daily life.

Today, people are looking for comfort thanks to rapidly developing technology. As we can see, people invent and implement new technologies in all fields according to customer needs.

We got a unique restaurant idea that helps people save time. People prefer quick methods to get things done. With …

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 …

Exploring Experimental Design And Multivariate Analysis Techniques For Evaluating Community Structure Of Bacteria In Microbiome Data, Kelsey Karnik

Department of Statistics: Dissertations, Theses, and Student Work

The gut microbiome plays a crucial role in human health, and by working collaboratively with microbiologists, we aim to further our understanding of the human gut and its impact on human health. Promoting a diverse microbiome is emphasized throughout microbiology literature, and involving a statistician in designing experiments to relate gut bacteria and some measured health outcome is crucial for ensuring valid and accurate results. By adopting new experimental design and analysis methods, researchers can begin to gain a deeper understanding of how the genetics of our food affect the composition of taxa within the gut microbiome. This dissertation is …

Advances In One-Electron Self-Interaction-Correction Methods For Accurate And Efficient Self-Interaction-Free Density Functional Calculations, Selim Romero

Open Access Theses & Dissertations

Density functional theory (DFT) is a widely used computational method for studying electronic structures of atoms, molecules, and solids. It provides an exact theory for obtaining ground state energy from the ground state density. However, since the exact exchange-correlation functional remains unknown, approximate exchange-correlation functionals called approximate density approximations (DFAs) are used. The foundation of many DFAs is the local spin density approximation (LSDA). It serves as the starting point for constructing various DFAs. However, DFAs are prone to self-interaction errors (SIE) due to the improper cancellation of the approximate exchange energy and the Coulomb energy. This issue impacts the …

Self-Calibrating Optical Galaxy Cluster Selection Bias Using Cluster, Galaxy, And Shear Cross-Correlations, Chenxiao Zeng, Andrés N. Salcedo, Hao-Yi Wu, Christopher M. Hirata

Physics Faculty Publications and Presentations

The clustering signals of galaxy clusters are powerful tools for self-calibrating the mass–observable relation and are complementary to cluster abundance and lensing. In this work, we explore the possibility of combining three correlation functions – cluster lensing, the cluster–galaxy cross-correlation function, and the galaxy autocorrelation function – to self-calibrate optical cluster selection bias, the boosted clustering and lensing signals in a richness-selected sample mainly caused by projection effects. We develop mock catalogues of redMaGiC-like galaxies and redMaPPer-like clusters by applying halo occupation distribution models to N-body simulations and using counts-in-cylinders around massive haloes as a richness proxy. In addition …

Modelling Galaxy Cluster Triaxiality In Stacked Cluster Weak Lensing Analyses, Hao-Yi Wu

Physics Faculty Publications and Presentations

Counts of galaxy clusters offer a high-precision probe of cosmology, but control of systematic errors will determine the accuracy of this measurement. Using Buzzard simulations, we quantify one such systematic, the triaxiality distribution of clusters identified with the redMaPPer optical cluster finding algorithm, which was used in the Dark Energy Survey Year-1 (DES Y1) cluster cosmology analysis. We test whether redMaPPer selection biases the clusters’ shape and orientation and find that it only biases orientation, preferentially selecting clusters with their major axes oriented along the line of sight. Modelling the richness–mass relation as log-linear, we find that the log-richness amplitude …

Precipitation Variability And Predictability Over The Arabian Peninsula, Central Southwest Asia, And Southern Africa, Matthew Francis Horan

Doctoral Dissertations

The Northern Hemisphere winter is the main rainy season for the Arabian Peninsula (AP), Central Southwest Asia (CSWA), and Southern Africa (SF), where precipitation predictability is limited or understudied. This dissertation research focuses on improving our understanding of these regions' wet-season precipitation characteristics and predictability.

First, I have identified the AP's key moisture sources through a Lagrangian back-trajectory algorithm. Mid-latitude land and water bodies, such as the Mediterranean and Caspian Seas, are the primary moisture sources in the northern region. Areas further south rely on moisture transport from the Western Indian Ocean and the African continent. A significant drying trend …

Arabic Dysarthric Speech Recognition Using Adversarial And Signal-Based Augmentation, Massa Baali, Ibrahim Almakky, Shady Shehata, Fakhri Karray

Machine Learning Faculty Publications

Despite major advancements in Automatic Speech Recognition (ASR), the state-of-the-art ASR systems struggle to deal with impaired speech even with high-resource languages. In Arabic, this challenge gets amplified, with added complexities in collecting data from dysarthric speakers. In this paper, we aim to improve the performance of Arabic dysarthric automatic speech recognition through a multi-stage augmentation approach. To this effect, we first propose a signal-based approach to generate dysarthric Arabic speech from healthy Arabic speech by modifying its speed and tempo. We also propose a second stage Parallel Wave Generative (PWG) adversarial model that is trained on an English dysarthric …

S2cd: Self-Heuristic Speaker Content Disentanglement For Any-To-Any Voice Conversion, Pengfei Wei, Xiang Yin, Chunfeng Wang, Zhonghao Li, Xinghua Qu, Zhiqiang Xu, Zejun Ma

Machine Learning Faculty Publications

In this paper, we propose a Self-heuristic Speaker Content Disentanglement (S2CD) model for any to any voice conversion without using any external resources, e.g., speaker labels or vectors, linguistic models, and transcriptions. S2CD is built on the disentanglement sequential variational autoencoder (DSVAE), but improves DSVAE structure at the model architecture level from three perspectives. Specifically, we develop different structures for speaker and content encoders based on their underlying static/dynamic property. We further propose a generative graph, modelled by S2CD, so as to make S2CD well mimic the multi-speaker speech generation process. Finally, we propose a self-heuristic way to introduce bias …

A Language Framework For Modeling Social Media Account Behavior, Alexander C. Nwala, Alessandro Flammini, Filippo Menczer

Arts & Sciences Articles

Malicious actors exploit social media to inflate stock prices, sway elections, spread misinformation, and sow discord. To these ends, they employ tactics that include the use of inauthentic accounts and campaigns. Methods to detect these abuses currently rely on features specifically designed to target suspicious behaviors. However, the effectiveness of these methods decays as malicious behaviors evolve. To address this challenge, we propose a language framework for modeling social media account behaviors. Words in this framework, called BLOC, consist of symbols drawn from distinct alphabets representing user actions and content. Languages from the framework are highly flexible and can be …