Physical Sciences and Mathematics Commons^™

Flowdb: A Complete Method For Extracting Queries From Functional Programs, Koby J. Lewis

Theses and Dissertations

Programmers working on database-backed applications frequently face trade-offs between designing maintainable software and efficient software due to the overhead of querying a database. We demonstrate FlowDB, an analysis for database-backed programs that can aid in program transformations that allow a program to be written in a maintainable style while still being performant. FlowDB employs demand-driven control flow analysis (DCFA) to produce a set of query sites that may be evaluated during the execution of a program. This set of query sites may then be used by a developer or compiler to cache needed results.

The Effect Of An Invasive Species (Lantana Camara) And A Fast-Growing Herb (Acanthus Pubescens) On The Plant And Animal Communities In Kibale National Park, Uganda, Kathleen Bufka

Theses and Dissertations

Fast-growing plant species, like Lantana camara and Acanthus pubescens, could threaten biodiversity in Kibale National Park, Uganda. I surveyed plants and wildlife in areas where these plants were frequently encountered compared to those areas where they are infrequent. I found mixed results based on plant traits and the animals considered. My findings support management efforts on these two species to prevent forest degradation.

Congruences For Quotients Of Klein Forms, Jeffery Opoku

Theses and Dissertations

This dissertation investigates the arithmetic properties of some modular forms and eta quotients, focusing on the divisibility properties and congruence relations satisfied by these. The first part examines quotients of the Rogers-Ramanujan and Rogers-Selberg functions, defined by \[ f(\tau) = q^{r} (q^5; q^5)^{a_0} (q, q^4; q^5)^{a_1} (q^2, q^3; q^5)^{a_2}= \sum_{n=r}^{\infty} P_{a_0,a_1,a_2}(n-r) q^n, \] and \[ g(\tau) = q^{s} (q^7; q^7)^{a_0} (q, q^6; q^7)^{a_1} (q^2, q^5; q^7)^{a_2} (q^3, q^4; q^7)^{a_3}= \sum_{n=s}^{\infty} P_{a_0,a_1,a_2,a_3}(n-s) q^n, \] respectively. We establish conditions on the exponents \(a_0, a_1, a_2, a_3\) and residue classes \(r\) and $s$ modulo $p$ such that \(P_{a_0, a_1, a_2}(pn - r) \equiv …

Arginine Vasotocin And Corticosterone In Nesting And Non-Nesting Loggerhead Sea Turtles In X’Cacel-X’Cacelito Sanctuary, Krista Blair Reed

Theses and Dissertations

Sea turtles exhibit distinct behaviors before and after egg laying, however, not all individuals successfully oviposit. Some females display disruptions in their typical nesting behavior, returning to the water without laying eggs, which is referred to as a non-nesting emergence (NNE). NNEs can be due to external disturbances on the beach, but why they occur is often unclear. Arginine vasotocin (AVT) is a neuropeptide involved in various physiological processes, including stimulating smooth muscle contraction of the oviduct to facilitate egg deposition in nesting sea turtles. On the other hand, corticosterone is the primary stress hormone in sea turtles and is …

Comparative Analysis Of Sequential And Non-Sequential Modeling Techniques For Ddos Attack Detection With Explainable Ai, Vincent Agbenyeavu

Theses and Dissertations

Cybersecurity is known today as one of the greatest challenges of the modern era. Among the various types of cyber-attacks that threaten our security, the Distributed Denial of Service (DDoS) attack is among some of the most common, effective, and well-recognized attack strategies. Since this form of attack is meant to disrupt the availability factor covertly, it can be detrimental to the targeted machines and difficult to discover. Because of that, there have been several approaches, as well as solutions that have been devised to detect it as accurately and efficiently as possible. In this study, four sequential data modeling …

Machine Learning Applications For Evaporation Predictions From Small Reservoirs: Potential Water Savings For Lower Rio Grande Valley, Texas, Syed Muhammad Fahad Abdullah

Theses and Dissertations

Local-scale reservoirs are important to regional water balance, but these are often overlooked. This study presents a robust machine learning (ML) approach leveraging reanalysis datasets to estimate daily evaporation for local-scale reservoirs in semi-arid South Texas. Selected models were trained with daily lake evaporation model (DLEM) estimates and used climatic and reservoir-specific properties as feature input variables. The multi-reservoirs training approach ensured applicable model generalization. Results show promising predictive performance with R² values ranging from 0.55–0.67 (testing) and 0.64–0.78 (validation), NSE values ranged from 0.54 0.67 (testing) and 0.64–0.78 (validation), and RMSE values ranged between 1.52–1.80 mm/day (testing) and 1.22–1.58 …

Low-Cost Monitoring And Fingerprinting Of High-Powered Electric Systems, Kwabena Buamono Aboagye-Otchere

Theses and Dissertations

Electric motors are vital to industry, transport, and energy, yet their maintenance challenges persist. While traditional reactive maintenance leads to costly downtime and safety risks, predictive maintenance, especially through IoT and machine learning offers early fault detection and operational efficiency. However, this shift introduces security concerns due to unintended magnetic emissions from motors. These emissions, though useful for non-intrusive monitoring, can be exploited to eavesdrop on sensitive industrial processes. This dissertation explores the dual nature of magnetic emissions: their value in motor diagnostics and their potential as a security vulnerability. It demonstrates how emissions can identify motors, monitor health, and …

Computational Calculations On Zno (0001) And Zno (1010) Surfaces With And Without Pd Adatoms, Amit Aich

Theses and Dissertations

In this research work, first-principles density functional theory (DFT) was used to study O-terminated, Zn-terminated ZnO (0001) surfaces and non-polar ZnO (1010) surfaces. Both clean surfaces and those with Pd or PdO adatoms were examined. Adsorption was considered at O, Zn and hollow sites. After structural relaxation, we analyzed the electronic, optical and adsorption properties. The O-terminated ZnO (0001) surface has a larger band gap of 0.76 eV and p-type conduction. The Zn-terminated surface has a smaller band gap of 0.15 eV and shows n-type behavior. Pd adsorption modifies ZnO’s electronic structure in a site-dependent manner. On O-terminated surfaces, it …

Advancing Real-World Implementation Of The Well Optimized Linear Finder (Wolf) High-Speed Atmospheric Turbulence Compensation Method, Timothy Evan Coon

Theses and Dissertations

This dissertation advances the real-world implementation of the Well Optimized Linear Finder (WOLF) method for high-speed Atmospheric Turbulence Compensation (ATC). Atmospheric turbulence introduces phase aberrations into optical wavefronts and degrades image quality in terrestrial imaging systems. Traditional phase diversity methods are computationally intensive and poorly suited to real-time operation. The WOLF method addresses these limitations through a novel, point-wise formulation of the optical transfer function (OTF) as a structured autocorrelation of the generalized pupil function (GPF). This formulation enables the estimation of phase aberrations at individual spatial coordinates with distributed computational complexity.

The research begins by developing a MATLAB-based simulation …

Investigating Global Lightning Observed From Ground And Space, And Its Relationship To Solar Activity, Megan Diane Mark

Theses and Dissertations

The extremes of lightning, specifically lightning with long-lasting continuing currents and lightning with extremely high peak currents, are investigated from both ground- and space-based observations. Additionally, the potential solar influence on lightning is investigated on large spatial scales.

Continuing currents may occur following the impulsive flow of current during a cloud-to-ground (CG) return stroke and are usually low amplitude (from a few amperes to a few kiloamperes) and long duration (several to hundreds of milliseconds). Remotely estimating their duration from the electromagnetic fields measured by existing ground-based lightning locating systems (LLSs) is not possible, but some space-based lightning detection systems …

Secure Frameworks For User Motion Data In Virtual Reality, Jayasri Sai Nikitha Guthula

Theses and Dissertations

Virtual Reality is an innovative technology transforming industries such as gaming, healthcare, and remote collaboration. The increasing deployment of these systems results in the continuous collection of telemetry data, including motion patterns, hand gestures, and spatial interactions. This data is valuable for enhancing user experiences and optimizing system performance. However, it also introduces significant privacy risks. Unlike traditional digital footprints, motion data captures fine-grained physical behaviors that can be linked to individual users, making anonymization ineffective in preventing re-identification.This research introduces secure frameworks for user motion data in virtual reality, each proposed framework addressing privacy preservation from a different angle. …

Transformation With Genes To Improve Lipid Production And Barcoding To Identify Unknown Algal Species, Michelle T. Rada

Theses and Dissertations

With the rising demand for alternative fuels, algal-based biofuels are a promising, sustainable source that meets commercial interest while producing lower greenhouse gas emissions compared to fossil fuels. This thesis explored two studies, evaluating microalgae for their future potential in lipid yield for biofuel production.

The first study involved developing a cost-efficient electroporation protocol that allowed for the genetic transformation of Chlamydomonas reinhardtii using the pChlamy_4 vector, which supports future cloning of genes to enhance lipid production. Parameters affecting DNA uptake and integration into algal genomes were studied: the effect of cell density, the settings of the electroporation device, and …

Math Information Retrieval From Images Via Formula Extraction, Vector Embedding, And Multimodal Llm-Based Question Answering, Angel Wheelwright Crawford

Theses and Dissertations

Math Information Retrieval (MIR) aims to revolutionize the retrieval of math information by addressing the challenges in representing, retrieving, and producing highly specialized math content. In order to develop a robust MIR system, designers must be able to process math equations (MEs) to a format that different systems can use, which is difficult due to various formats math information are stored in, including visual images and document texts. To improve the usage of math information in varied forms for people who are learning and utilizing math, we propose three different methods of handling ME data. The first method is a …

Study Of Anomalous Variations In Seismic And Non-Seismic Parameters Using Machine Learning Techniques To Develop The Earthquake Forecasting Model In The Himalayan Belt, Senthil Kumar M

Theses and Dissertations

Understanding and forecasting earthquakes is not just about science it’s about saving lives, even as the dynamic and hidden nature of Earth's tectonic processes makes this an intricate challenge. The Himalayan belt is one of the most seismically active regions globally due to the collision of the Indian and Eurasian tectonic plates. Investigating this region is essential for understanding highly complicated tectonic mechanisms and reducing substantial hazards posed to millions of people by persistent and intense seismic events. This study aims to enhance forecasting methodologies by applying machine learning techniques while dealing with the inherent challenges of geological complexity and …

Design And Investigation Of Triarylamine Functionalized Luminophores For Multi-Functional And Stimuli-Responsive Applications, Sasikala R

Theses and Dissertations

Organic solid-state fluorescent materials have garnered attention over many decades in virtue of their contribution in the development of LED devices and biomedical applications. Nevertheless, the potential of fluorescent molecules in device applications was underused due to aggregation-caused quenching (ACQ) effect. The ACQ effect commonly quenches the organic molecules fluorescence intensity in the aggregated or condensed state, which can significantly influence their performance in practical applications.

The organic polyaromatic fluorophores exhibit strong fluorescence in the solution state. After culmination of years of work, Prof. Tang’s research group discovered a new phenomenon of aggregation-induced emission (AIE) in the fluorescence molecules constructed …

Source Characterization From Near-Field Acoustic Intensity On Moving Launch Vehicles, Carson F. Cunningham

Theses and Dissertations

Rocket launches generate extremely high acoustic levels, particularly in the low-frequency range, posing risks to both launch vehicle integrity and surrounding infrastructure. This thesis investigates the use of near-field acoustic intensity measurements to localize sound sources on moving launch vehicles, with a focus on characterizing source behavior during the early phases of liftoff. Using data from the Antares 230 NG-19 mission, acoustic pressure was recorded at multiple stations surrounding the pad, and the Phase and Amplitude Gradient Estimator (PAGE) method was employed to compute intensity vectors as a function of frequency and time. Signal processing parameters were systematically evaluated, including …

A Machine Learning Approach To Quantitative X-Ray Diffraction Analysis, Spencer Snow Chandler

Theses and Dissertations

X-ray Powder Diffraction (XRPD) is a powerful method in material sciences that gives insights into the atomical and crystallographic structure of a material, revealing information into the material's properties and suitability for industrial and scientific application. In geology, XRPD analysis is frequently leveraged to identify and quantify the present mineral phases in an unknown mixture. Despite it's widespread use, interpreting XRPD patterns requires highly-specialized knowledge, making the analysis largely dependent upon the background experience of the analyst. To assist experts, computational methods have been developed over the years. Some of these techniques involve fitting diffraction patterns using pseudo-Voigt functions, which …

Approximating Transport Maps Using Minibatch Optimal Transport Plans, Dawson Collins

Theses and Dissertations

Optimal Transport theory (OT) has gained much attention in the past decades due to its rich mathematical content and striking connections to other areas of math. It has also naturally found a place in data science as a way to compare and transform probability measures. Unfortunately, there remain significant computational burdens that restrict its effectiveness in large-scale data regimes. In this thesis, we consider Minibatch Optimal Transport (MiniOT), which breaks up the task of computing the optimal transport plan between datasets into several smaller tasks of computing the optimal transport plan between minibatches of the datasets. After obtaining the minibatch …

The Role Of The Cytosolic Chaperonin Cct In The Folding And Assembly Of G Protein Complexes, Mikaila I. Sass

Theses and Dissertations

All organisms depend on cellular signaling pathways to dictate cell growth, responses to stimuli, and all other cellular functions necessary to maintain health and survival. Many of these signals rely on G protein coupled receptors (GPCRs) and their associated heterotrimeric G proteins for signal detection and transduction. To perform this function, the three subunits of the G protein must be assembled after synthesis on the ribosome. This process requires additional proteins called molecular chaperones to assist in folding of the subunits and assembly into the G protein heterotrimer. Among these chaperones, the cytosolic chaperonin CCT plays an essential role in …

A New Approach To Stability Of Delay Differential Equations With Time-Varying Delays Via Isospectral Reduction, Quinlan Leishman

Theses and Dissertations

Understanding how time delays impact the stability of a delay differential equation is important for modeling many natural and technological systems that experience time delays. Here we introduce a new stability criterion for delay-independent stability of these equations, called intrinsic stability, showing global exponential stability for a large class of nonautonomous nonlinear systems. Our approach is able to incorporate bounded time-varying delays, including those with certain types of discontinuities. The approach we take to prove this result is novel, associating the delay differential equation with a sequence of finite-dimensional matrices of increasing size and using the graph-theoretic technique of isospectral …

Math 112 At Byu: Student Averages On Various Exam Questions, Makayla Mcleod

Theses and Dissertations

In Math 112 at BYU, exams play a crucial role in evaluating students' understanding of the course content. Traditionally, these exams are a combination of multiple-choice and free-response questions, with the latter serving as a means to assess a student's thought process while solving problems. Will students perform as well on a multiple-choice exam? Or will students' averages be higher on free-response exams? In this thesis, we test 7 hypotheses related to these questions to provide more insight into the answer. We examine other factors that may affect students' averages, including various Calculus 1 topics, modes of questioning, and difficulty …

Synthesis And Evaluation Of Novobiocin Analogues As Potential Inhibitors Of Polymerase Theta Polθ In Dna Damage And Repair, Mohammed Essam Albuhluli

Theses and Dissertations

Killing tumors while leaving normal cells unharmed is the goal of precision cancer therapy, a challenging feat that is enabled by targeting tumor-specific vulnerabilities [1]. Targeting Polθ potentiates PARP inhibitors (PARPi) in specifically killing homology-directed repair (HDR)-deficient tumor cells and re-sensitize PARPi resistant tumor cells [1]. The induced essentiality between Polθ and HDR-deficiency underscores the value of Polθ as a therapeutic target in the context of tumors with HDR genetic mutations [1]. The helicase-like domain (HLD) is a super family 2 (SF2)-type domain with DNA-dependent ATPase activity [1]. We previously discovered that the antibiotic NVB acts as an inhibitor of …

Synthesis Of Inorganic Actinide Compounds With Neptunium, Plutonium, And Americium, Travis Kelly Deason

Theses and Dissertations

There is a rush of countries around the world making the switch to greener energy sources. Nuclear energy power plants are an integral part of the shift from fossil fuels, but there are concerns over the best way to handle nuclear waste. Most of the nuclear waste is currently disposed of by incorporating the waste into a glass form through vitrification, but research into alternative waste forms, such as promising crystalline materials, could provide a more robust method of containment. Research on actinide materials is lacking due to the dangers of working with radioactive material and there are few labs …

Process-Grounded Knowledge-Infused Learning And Decision Making, Kaushik Roy

Theses and Dissertations

This dissertation introduces process-grounded knowledge-infused learning and reasoning, a novel framework for integrating domain-expertise-based process knowledge into the learning and reasoning mechanisms of artificial intelligence systems. This approach is designed to produce controlled, transparent, and reliable predictions in critical tasks such as medical diagnosis and recommendation. By focusing on the case study of mental illness diagnosis and recommendation—where decision-making must be grounded in processes such as disorder-specific diagnostic criteria—this work demonstrates methods to embed structured decision-making directly into the system architecture during both training and inference. This integration facilitates end-to-end training and reasoning while ensuring that outputs strictly adhere to …

Rapid Charging Lithium-Ion Batteries: Structure, Morphology, And Methodology, Sean Cade Wechsler

Theses and Dissertations

The initial commercialization and subsequent development of the lithium-ion battery (LIB) in 1991 has revolutionized the way that humans power devices, cars, and homes and led to the advent of many technologies that seemed impossible just half a century ago. As LIBs are integrated into more of daily life through handheld devices, wearable medical devices, transportation, and grid-level energy storage, the demand for fast charging and high energy density increases rapidly. To design a battery with these favorable qualities, an understanding of the effect of electrode crystal structure and electrode morphology on the ionic/electronic transport and failure modes must be …

Statistical Power To Detect Simultaneous Violation Of Proportionality In Hazards And Additive Assumption In Cox Regression Model, Lawrence Mensah Agbota

Theses and Dissertations

The Cox proportional hazards regression model is a widely employed semi-parametric tool in epidemiological and medical research for analyzing time-to-event data and assessing the relationship between patient survival times and one or more predictors. This method involves regression analyses necessitating a meticulous approach to careful examination of the covariates and the relationship among covariates included in the model through a series of critical decisions and steps. Violation of the additivity of the effects and the proportionality in hazards (PH) assumption can lead to biased results and misleading scientific findings. We conducted a Monte Carlo simulation study to assess the performance …

P-Adic Cellular Neural Networks With Delay, Baboucarr Dibba

Theses and Dissertations

This dissertation presents a novel framework for p-adic reaction-diffusion cellular neural networks (CNNs) with delay, offering new insights into the stability and dynamic behavior of these networks. Through numerical simulations, we explore their response to various conditions, highlighting their capability to model complex systems. Additionally, this work reviews cutting-edge developments in p-adic CNNs, particularly their application to advanced image processing tasks such as edge detection and noise filtering, demonstrating their effectiveness in preserving critical image features while filtering out noise. This dissertation is written in collaboration with my Ph.D supervisor and Dr. Zambrano-Luna, Brian.

A Study Of Quasigroups, A Computational Approach On Isotopism And Isomorphism Hierarchical Structure, Runaldo Montrose

Theses and Dissertations

Quasigroups morphism classification can present a real computational challenge. As of today, the number of quasigroups that can be generated from a finite set S of cardinality n is known for very small value of n. Though we know the number of quasigroups for small n, generating them in real time is a whole other issue that leads to a bigger challenge of building their isomorphy classes, because the algorithm used required large computing memory resources. In this paper we will expose the computational complexity of constructing their hierarchical morphism structure from isotopism to isomorphism. As an improvement, …

Electrocatalytic Degradation Of Methylene Blue Using Graphene Oxide, Antimony Oxide, And Graphene Oxide-Supported Antimony Oxide Ink-Based Electrodes, Maria Irene Myers Armas

Theses and Dissertations

This study investigates the electrocatalytic degradation of methylene blue (MB) using copper mesh electrodes coated with graphene oxide (GO), antimony oxide (Sb₂O₃), and their composite (GO/Sb₂O₃). These materials were evaluated across a pH range of 2 to 8 using sodium sulfate as the supporting electrolyte. UV-Vis spectroscopy at 665 nm confirmed dye degradation, with removal efficiencies reaching up to 95% at pH 2. However, degradation decreased at higher pH, with 40 – 60% removal at pH 8, depending on the electrode. Kinetic analyses revealed optimum performance under acidic conditions. GO/Sb₂O₃ electrodes demonstrated the most consistent and effective performance across all …

Predicting Enzyme-Substrate Association Using Heterogeneous Knowledge Graph, Jannatul Ferdaus

Theses and Dissertations

Phosphorylation and dephosphorylation are dynamic processes that control many aspects of cellular activity, such as metabolic pathways, cell cycle progression, and signal transduction. Protein activity and interactions are modulated by the reversible addition or removal of phosphate groups, which allows cells to react abruptly to evolving conditions. Although kinase-specific phosphorylation site prediction has advanced, phosphatase-specific dephosphorylation site computational prediction is still a major obstacle that prevents us from fully comprehending the extent of cellular regulation. In this study, we constructed a knowledge graph for the prediction of enzymes (kinases and phosphatases) and their associated substrates with specific phosphosites. As part …