Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Theses and Dissertations

Discipline
Institution
Keyword
Publication Year
File Type

Articles 1 - 30 of 7824

Full-Text Articles in Physical Sciences and Mathematics

Differential Elliptic Flow Analysis Of Hadrons With Different Wuark Content In Simulated Pp Collisions, Elhussein Osama Jun 2024

Differential Elliptic Flow Analysis Of Hadrons With Different Wuark Content In Simulated Pp Collisions, Elhussein Osama

Theses and Dissertations

According to current physics theories, it is assumed that in the first microsecond after the big bang, the universe was in a state of matter called Quark-Gluon Plasma (QGP), where the fundamental consistent of matters (quarks and leptons), were highly energetic, and floating around freely. Searching for such phase of matter; as the possible earliest signatures after the big bang, and among many other interesting experimental measurements, the jet quenching and elliptic flow are the most important ones, in the heavy ion collisions at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC) experiments.

The azimuthal anisotropy …


Unraveling The Physics Of Quasar Jets Using Hst Polarimetry, Devon Clautice May 2024

Unraveling The Physics Of Quasar Jets Using Hst Polarimetry, Devon Clautice

Theses and Dissertations

We present a multiwavelength study of three high-power FR II (quasar) jets -- 3C 273, PKS 0637-752, and 1150+497 -- with an emphasis on new high-quality Hubble Space Telescope (HST) optical polarimetry and Chandra X-ray Observatory imaging. Relativistic jets from active galactic nuclei transport energy and mass from the supermassive black hole’s accretion region out to Megaparsec-scale lobes, with effects that feedback into galaxy formation and cluster energetics. We build on recent work which has called into question our fundamental understanding of FR II jet physics, and suggest that highly-efficient particle acceleration must be taking place in situ …


A Statistical Fetch Model For Water Wave Glint Correction Using Worldview-3 Imagery, Amanda Jade Quintanilla May 2024

A Statistical Fetch Model For Water Wave Glint Correction Using Worldview-3 Imagery, Amanda Jade Quintanilla

Theses and Dissertations

Sun glint in satellite imagery of the water surface contaminates the upwelling signal received by a detector. Many models exist that attempt to correct for this wave facet effect and phenomena. In this work a model for sun glint correction is created using the comparison of image transects between two nearly simultaneously collected images of the same area, although with differing sensor geometry. One image utilized in this research is almost entirely glint free while the other is contaminated by water wave facet glint. Although many models for removing sun glint exist based on various techniques, none are completely accurate, …


Predictability Of The Overland Reintensification Of North Atlantic Tropical Cyclone Erin (2007), Ariel Tickner-Ernst May 2024

Predictability Of The Overland Reintensification Of North Atlantic Tropical Cyclone Erin (2007), Ariel Tickner-Ernst

Theses and Dissertations

Tropical cyclones (TC) typically decrease in intensity upon interacting with land because of increased surface roughness and decreased surface evaporation. However, several studies have documented cases in which TCs maintain their intensity or even intensify over land within non- or weakly baroclinic environments. Yet, our understanding of the precise physical processes that support maintenance or intensification over land in non- or weakly baroclinic environments remains limited, and the predictive skill for these outcomes has yet to be quantified.

We begin this process by quantifying the predictive skill and forecast uncertainty of the overland intensification of North Atlantic Tropical Storm Erin …


Applying Mathematical Modeling To The Study Of Family Systems, Dahlia Maxwell Apr 2024

Applying Mathematical Modeling To The Study Of Family Systems, Dahlia Maxwell

Theses and Dissertations

Mathematical modeling provides a powerful framework for insight into current scientific theories as well as hypothesis generation for further research. Despite its undeniable potential to enrich scientific advancement, the application of mathematical modeling remains conspicuously scarce in the field of family science. The complexity inherent in family dynamics, coupled with the intricate interplay of emotions in the individual, underscores the necessity of a robust analytical approach. Addressing this critical gap in the literature, this thesis introduces a sophisticated mathematical model of family dynamics integrating essential elements from family systems theory, emotion dynamics, and appraisal theory. The model is implemented as …


Advancing Single-Cell Proteomics Through Innovations In Liquid Chromatography And Mass Spectrometry, Kei Grant Isaac Webber Apr 2024

Advancing Single-Cell Proteomics Through Innovations In Liquid Chromatography And Mass Spectrometry, Kei Grant Isaac Webber

Theses and Dissertations

Traditional proteomics studies can measure many protein biomarkers simultaneously from a single patient-derived sample, promising the possibility of syndromic diagnoses of multiple diseases sharing common symptoms. However, precious cellular-level information is lost in conventional bulk-scale studies that measure tissues comprising many types of cells. As single cells are the building blocks of organisms and are easier to biopsy than traditional bulk samples, performing proteomics on a single-cell level would benefit clinicians and patients. Single-cell proteomics, combined with mass spectrometry imaging, can be used to analyze cells in their microenvironment, preserving spatial information. We have previously used laser-capture microdissection to isolate …


Robot Proficiency Self-Assessment Using Assumption-Alignment Tracking, Xuan Cao Apr 2024

Robot Proficiency Self-Assessment Using Assumption-Alignment Tracking, Xuan Cao

Theses and Dissertations

A robot is proficient if its performance for its task(s) satisfies a specific standard. While the design of autonomous robots often emphasizes such proficiency, another important attribute of autonomous robot systems is their ability to evaluate their own proficiency. A robot should be able to conduct proficiency self-assessment (PSA), i.e. assess how well it can perform a task before, during, and after it has attempted the task. We propose the assumption-alignment tracking (AAT) method, which provides time-indexed assessments of the veracity of robot generators' assumptions, for designing autonomous robots that can effectively evaluate their own performance. AAT can be considered …


N-H Nhc Palladium Catalysts Derived From Unique 2-Phosphinoimidazole Precursors For C-C Cross Coupling Reactions And Application Of Slow Releasing Polymers Impregnated With Gibberellic Acid To Overcome Seed Dormancy For Land Reclamation, Alexandra Jean Setelin Larson Mar 2024

N-H Nhc Palladium Catalysts Derived From Unique 2-Phosphinoimidazole Precursors For C-C Cross Coupling Reactions And Application Of Slow Releasing Polymers Impregnated With Gibberellic Acid To Overcome Seed Dormancy For Land Reclamation, Alexandra Jean Setelin Larson

Theses and Dissertations

Organometallic chemistry is highly dependent upon the ligands which are employed on a metal's surface. These ligands control steric bulk and electronics of the metal center which can change the reactivity of the organometallic complex. Ligands that are standard in organometallic chemistry include phosphine ligands. These phosphine ligands have been utilized in the field since the 1960's and have shaped the development of many key organometallic catalysts. Phosphine ligands are easily functionalized and highly reactive. This increased reactivity, however, causes severe limitations as phosphine ligands are often unstable under standard benchtop conditions and must be handled both air and moisture …


Gt-Ches And Dycon: Improved Classification For Human Evolutionary Systems, Joseph S. Johnson Mar 2024

Gt-Ches And Dycon: Improved Classification For Human Evolutionary Systems, Joseph S. Johnson

Theses and Dissertations

The purpose of this work is to rethink the process of learning in human evolutionary systems. We take a sober look at how game theory, network theory, and chaos theory pertain specifically to the modeling, data, and training components of generalization in human systems. The value of our research is three-fold. First, our work is a direct approach to align machine learning generalization with core behavioral theories. We made our best effort to directly reconcile the axioms of these heretofore incompatible disciplines -- rather than moving from AI/ML towards the behavioral theories while building exclusively on AI/ML intuition. Second, this …


Development Of Bifunctional Peptides As Scaffolds For Bifunctional Catalysis And A Novel Method Of Peptide Stapling Using Squaric Esters, Adam X. Wayment Mar 2024

Development Of Bifunctional Peptides As Scaffolds For Bifunctional Catalysis And A Novel Method Of Peptide Stapling Using Squaric Esters, Adam X. Wayment

Theses and Dissertations

Enzymes are some of nature's most powerful tools in chemical processes. However, their molecular complexity makes them difficult to synthesize and complicates their application in traditional organic synthesis. Peptides, a building block of enzymes, can be rapidly synthesized and have been used as a possible alternative in achieving enzyme-like catalysis. However, most peptide-based catalysts are limited in reaction-scope and are unable to incorporate traditional organic catalysts. We have designed a helical peptide scaffold capable of being functionalized with a wide variety of organocatalysts as well as transition-metal based catalysts. In order to understand how the peptide structure effects reactivity and …


Development Of Salinomycin Derivatives As Potential Anticancer Agents, Viren Soni Feb 2024

Development Of Salinomycin Derivatives As Potential Anticancer Agents, Viren Soni

Theses and Dissertations

Salinomycin is a poly-ionophore antibiotic that was originally isolated from Streptomyces albus by Miyazaki and colleagues from Kaken Chemicals Co., Ltd., Tokyo, Japan. Salinomycin exhibits antimicrobial activity against Gram-positive bacteria including Bacillus subtilis, Staphylococcus aureus, Micrococcus flavus, Sarcina lutea, Mycobacterium spp. Some filamentous fungi, Plasmodium falciparum, and Eimeria spp. as well as protozoan parasites responsible for the poultry disease coccidiosis. Hence, it is used in veterinary medicine. In 2009 Gupta et al demonstrated that salinomycin selectively killed human breast cancer stem cells (CSCs) with great efficacy, and the mechanism of action of this novel CSCs molecule was explored. To name …


Mri Image Regression Cnn For Bone Marrow Lesion Volume Prediction, Kevin Yanagisawa Feb 2024

Mri Image Regression Cnn For Bone Marrow Lesion Volume Prediction, Kevin Yanagisawa

Theses and Dissertations

Bone marrow lesions (BMLs), occurs from fluid build up in the soft tissues inside your bone. This can be seen on magnetic resonance imaging (MRI) scans and is characterized by excess water signals in the bone marrow space. This disease is commonly caused by osteoarthritis (OA), a degenerative join disease where tissues within the joint breakdown over time [1]. These BMLs are an emerging target for OA, as they are commonly related to pain and worsening of the diseased area until surgical intervention is required [2]–[4]. In order to assess the BMLs, MRIs were utilized as input into a regression …


New Mathematics Teachers' Goals, Orientations, And Resources That Influence Implementation Of Principles Learned In Brigham Young University's Teacher Preparation Program, Caroline S. Gneiting Feb 2024

New Mathematics Teachers' Goals, Orientations, And Resources That Influence Implementation Of Principles Learned In Brigham Young University's Teacher Preparation Program, Caroline S. Gneiting

Theses and Dissertations

Research in mathematics education shows that new mathematics teachers struggle to implement reform teaching practices that they learned in their teacher preparation programs. In this study, the researcher observed and interviewed three new mathematics teachers (within five years of graduation) to further explore the question of why new teachers use or do not use what they learned in their teacher preparation program. The study uses an expanded version of Schoenfeld's decision-making theory of Orientations, Goals, and Resources. This theory proved useful in the analysis of the research data, providing a framework to incorporate and organize the numerous reasons suggested by …


Usability-Driven Security Enhancements In Person-To-Person Communication, Tarun Kumar Yadav Feb 2024

Usability-Driven Security Enhancements In Person-To-Person Communication, Tarun Kumar Yadav

Theses and Dissertations

In the contemporary digital landscape, ensuring secure communication amid widespread data exchange is imperative. This dissertation focuses on enhancing the security and privacy of end-to-end encryption (E2EE) applications while maintaining or improving usability. The dissertation first investigates and proposes improvements in two areas of existing E2EE applications: countering man-in-the-middle and impersonation attacks through automated key verification and studying user perceptions of cryptographic deniability. Insights from privacy-conscious users reveal concerns about the lack of E2EE support, app siloing, and data accessibility by client apps. To address these issues, we propose an innovative user-controlled encryption system, enabling encryption before data reaches the …


Analyzing Novel Metal Alloys For Glucose Sensing And Electrocatalysis, Anna Grace Boddy Jan 2024

Analyzing Novel Metal Alloys For Glucose Sensing And Electrocatalysis, Anna Grace Boddy

Theses and Dissertations

In pharmaceutical and medicinal chemistry, metals and metal alloys often receive less attention compared to biological or organic compounds due to many factors including toxicity in the body for drug development or the cost of these metals. However, metals can play an important role in pharmaceuticals, having an impact on original cancer drugs, such as platinum used for head and neck tumors. Electrocatalysis is also another topic that receives less attention over topics such as chromatography in pharmaceuticals due to its potential toxic catalysts and voltages that could be harmful to the body. Electrocatalytic sensors can play an important role …


Open System Neural Networks, Bradley Hatch Jan 2024

Open System Neural Networks, Bradley Hatch

Theses and Dissertations

Recent advances in self-supervised learning have made it possible to reuse information-rich models that have been generally pre-trained on massive amounts of data for other downstream tasks. But the pre-training process can be drastically different from the fine-tuning training process, which can lead to inefficient learning. We address this disconnect in training dynamics by structuring the learning process like an open system in thermodynamics. Open systems can achieve a steady state when low-entropy inputs are converted to high-entropy outputs. We modify the the model and the learning process to mimic this behavior, and attend more to elements of the input …


Adaptive Multi-Label Classification On Drifting Data Streams, Martha Roseberry Jan 2024

Adaptive Multi-Label Classification On Drifting Data Streams, Martha Roseberry

Theses and Dissertations

Drifting data streams and multi-label data are both challenging problems. When multi-label data arrives as a stream, the challenges of both problems must be addressed along with additional challenges unique to the combined problem. Algorithms must be fast and flexible, able to match both the speed and evolving nature of the stream. We propose four methods for learning from multi-label drifting data streams. First, a multi-label k Nearest Neighbors with Self Adjusting Memory (ML-SAM-kNN) exploits short- and long-term memories to predict the current and evolving states of the data stream. Second, a punitive k nearest neighbors algorithm with a self-adjusting …


Towards Machine Learning-Based Control Of Autonomous Vehicles In Solar Panel Cleaning Systems, Farima Hajiahmadi Jan 2024

Towards Machine Learning-Based Control Of Autonomous Vehicles In Solar Panel Cleaning Systems, Farima Hajiahmadi

Theses and Dissertations

This thesis presents a machine learning (ML)-based approach for the intelligent control of Autonomous Vehicles (AVs) utilized in solar panel cleaning systems, aiming to mitigate challenges arising from uncertainties, disturbances, and dynamic environments. Solar panels, predominantly situated in dedicated lands for solar energy production (e.g., agricultural solar farms), are susceptible to dust and debris accumulation, leading to diminished energy absorption. Instead of labor-intensive manual cleaning, robotic cleaners offer a viable solution. AVs equipped to transport and precisely position these cleaning robots are indispensable for efficient navigation among solar panel arrays. However, environmental obstacles (e.g., rough terrain), variations in solar panel …


Towards Energy-Efficient Edge Computing For Tiny Ai Applications, Vamsi Krishna Bhagavathula Jan 2024

Towards Energy-Efficient Edge Computing For Tiny Ai Applications, Vamsi Krishna Bhagavathula

Theses and Dissertations

As artificial intelligence (AI) applications become more common on the edge of networks, like Raspberry Pi servers, it is crucial to optimize their energy use. This research project investigates how AI algorithms affect energy efficiency and resource usage on Raspberry Pi servers. Two models were created: one predicts resource usage, and the other predicts power consumption of AI algorithms on Raspberry Pi. Several factors are considered like CPU and memory use, algorithm speed, dataset size, and types of algorithms and datasets. Using regression-based methods, we model how these factors affect energy use. By converting categorical factors into numerical ones, we …


Understanding The Origin, Evolution, And Dynamics Of Transneptunian Binaries, Benjamin C N Proudfoot Dec 2023

Understanding The Origin, Evolution, And Dynamics Of Transneptunian Binaries, Benjamin C N Proudfoot

Theses and Dissertations

This dissertation discusses research that focuses on understanding transneptunian objects (TNOs) using a variety of techniques and approaches. In Chapter 1, I introduce the main concepts used throughout this dissertation and discuss the current understanding of the transneptunian region. In Chapter 2, I discuss my efforts to understand how Neptune's late stages of migration affect the Haumea family, the only known collisional family in the transneptunian region. Using advanced simulations of Neptune migration, I find that the Haumea family can plausibly form before the termination of giant planet migration and show that this extensively mixes the family. The simplest explanation …


Simulating Government Institutions In Networked Societies, Michael Richards Dec 2023

Simulating Government Institutions In Networked Societies, Michael Richards

Theses and Dissertations

Modern human societies give rise to the expression of complex group dynamics between the members of said society due to the abundance of continued interactions. Of particular interest are how institutions affect these interactions between societal members, alter the resulting group dynamics, and impact society as a whole through their rules. Simulating these dynamics allows for greater insight into how these institutions function and allows researchers to pose interesting questions and test hypotheses within a laboratory setting. We present a novel approach to simulating institutions, particularly governments, within a networked society. This approach builds upon the Junior High Game, which …


Local Atomic And Magnetic Structure Of Multiferroic (Sr,Ba)(Mn,Ti)O3, Braedon Jones Dec 2023

Local Atomic And Magnetic Structure Of Multiferroic (Sr,Ba)(Mn,Ti)O3, Braedon Jones

Theses and Dissertations

We present a detailed study of the local atomic and magnetic structure of the type-I multiferroic perovskite system (Sr,Ba)(Mn,Ti)O3 using x-ray and neutron pair distribution function (PDF) analysis, polarized neutron scattering, and muon spin relaxation (μSR) techniques. The atomic PDF analysis reveals widespread nanoscale tetragonal distortions of the crystal structure even in the paraelectric phase with average cubic symmetry, corresponding to incipient ferroelectricity in the local structure. Magnetic PDF analysis, polarized neutron scattering, and μSR likewise confirm the presence of short-range antiferromagnetic correlations in the paramagnetic state, which grow in magnitude as the temperature approaches the magnetic transition. We show …


Progress Towards The Development Of Asymmetric Conditions For Intramolecular Heteroatom/Dehydro-Diels-Alder Reactions For Synthesizing Furo[3,4-C] Pyranones And Anticancer Podophyllotoxins, Peter Mpaata Dec 2023

Progress Towards The Development Of Asymmetric Conditions For Intramolecular Heteroatom/Dehydro-Diels-Alder Reactions For Synthesizing Furo[3,4-C] Pyranones And Anticancer Podophyllotoxins, Peter Mpaata

Theses and Dissertations

Furo[3,4-c] pyranone is a unique bicyclic molecular structure found in bioactive sesquiterpene isobolivianine and in artificial cytotoxic stilbene derivatives. The structure of furo[3,4-c] pyranone is analogous to cyclopenta[c] pyran structure found in potent cytotoxic iridoids like catapol. Chiral substrates for intramolecular hetero-Diels-Alder (IHDA) reaction have been synthesized in yields ranging from 39% to 81%. These compounds undergo [4+2] cycloaddition via ambimodal/ bispericyclic process to give a mixture of furo[3,4-c] pyranone in yields ranging 40-70% and aryl tetralin lactone derivatives. Density functional theory (DFT) calculations have been performed to gain insight into the mechanism leading to the formation of these compounds. …


In-Depth Geochemical Analysis Of Turbidite-Associated Shales Of The Pindos Basin, Greece, Jonathon Michael Sevy Dec 2023

In-Depth Geochemical Analysis Of Turbidite-Associated Shales Of The Pindos Basin, Greece, Jonathon Michael Sevy

Theses and Dissertations

Detailed geochemical analysis of the turbidite-associated shales of the Cretaceous Katafito Formation, Greece, reveals important details regarding the paleoenvironment, paleoproductivity, and regional tectonics of the Pindos Basin. The Katafito Formation was deposited along an active margin at the early onset of closure of the Tethys Sea in the Pindos sub-basin. While careful studies of the coarse clastic component of turbidites are common, this study consisted of a detailed geochemical characterization of the fine-grained portions, which helped reveal paleoenvironmental information about the basin. This study combined organic and inorganic geochemistry utilizing elemental, mineralogical, and organic chemical signatures from fine-grained turbidite-associated sediments …


Synthesis Of Yaku'amide A Analogues And Progress Toward Synthesis Of Virosine A, Alexander S. Ramos Dec 2023

Synthesis Of Yaku'amide A Analogues And Progress Toward Synthesis Of Virosine A, Alexander S. Ramos

Theses and Dissertations

The first project in this dissertation endeavors to outline the total synthesis of yaku'amide A and its analogs. Yaku'amide A is a natural product comprised of dehydroamino acids, including E-dehydro isoleucine, and unprecedented Z-dehydro isoleucine. These amino acids present a significant challenge to their synthesis owing to their unsymmetrical nature. To simplify the synthesis process, we synthesized analogs by substituting the E and Z dehydroamino acids with symmetrical subunits. This substitution facilitated the synthesis process and enabled us to obtain a similar three-dimensional structure to that of the natural product. Furthermore, biological testing of the simplified analogs revealed potency similar …


Designing An Artificial Immune Inspired Intrusion Detection System, William Hosier Anderson Dec 2023

Designing An Artificial Immune Inspired Intrusion Detection System, William Hosier Anderson

Theses and Dissertations

The domain of Intrusion Detection Systems (IDS) has witnessed growing interest in recent years due to the escalating threats posed by cyberattacks. As Internet of Things (IoT) becomes increasingly integrated into our every day lives, we widen our attack surface and expose more of our personal lives to risk. In the same way the Human Immune System (HIS) safeguards our physical self, a similar solution is needed to safeguard our digital self. This thesis presents the Artificial Immune inspired Intrusion Detection System (AIS-IDS), an IDS modeled after the HIS. This thesis proposes an architecture for AIS-IDS, instantiates an AIS-IDS model …


A Conceptual Decentralized Identity Solution For State Government, Martin Duclos Dec 2023

A Conceptual Decentralized Identity Solution For State Government, Martin Duclos

Theses and Dissertations

In recent years, state governments, exemplified by Mississippi, have significantly expanded their online service offerings to reduce costs and improve efficiency. However, this shift has led to challenges in managing digital identities effectively, with multiple fragmented solutions in use. This paper proposes a Self-Sovereign Identity (SSI) framework based on distributed ledger technology. SSI grants individuals control over their digital identities, enhancing privacy and security without relying on a centralized authority. The contributions of this research include increased efficiency, improved privacy and security, enhanced user satisfaction, and reduced costs in state government digital identity management. The paper provides background on digital …


Study Of Augmentations On Historical Manuscripts Using Trocr, Erez Meoded Dec 2023

Study Of Augmentations On Historical Manuscripts Using Trocr, Erez Meoded

Theses and Dissertations

Historical manuscripts are an essential source of original content. For many reasons, it is hard to recognize these manuscripts as text. This thesis used a state-of-the-art Handwritten Text Recognizer, TrOCR, to recognize a 16th-century manuscript. TrOCR uses a vision transformer to encode the input images and a language transformer to decode them back to text. We showed that carefully preprocessed images and designed augmentations can improve the performance of TrOCR. We suggest an ensemble of augmented models to achieve an even better performance.


Phenotyping Cotton Compactness Using Machine Learning And Uas Multispectral Imagery, Joshua Carl Waldbieser Dec 2023

Phenotyping Cotton Compactness Using Machine Learning And Uas Multispectral Imagery, Joshua Carl Waldbieser

Theses and Dissertations

Breeding compact cotton plants is desirable for many reasons, but current research for this is restricted by manual data collection. Using unmanned aircraft system imagery shows potential for high-throughput automation of this process. Using multispectral orthomosaics and ground truth measurements, I developed supervised models with a wide range of hyperparameters to predict three compactness traits. Extreme gradient boosting using a feature matrix as input was able to predict the height-related metric with R2=0.829 and RMSE=0.331. The breadth metrics require higher-detailed data and more complex models to predict accurately.


An Investigation Into Applications Of Canonical Polyadic Decomposition & Ensemble Learning In Forecasting Thermal Data Streams In Direct Laser Deposition Processes, Jonathan Storey Dec 2023

An Investigation Into Applications Of Canonical Polyadic Decomposition & Ensemble Learning In Forecasting Thermal Data Streams In Direct Laser Deposition Processes, Jonathan Storey

Theses and Dissertations

Additive manufacturing (AM) is a process of creating objects from 3D model data by adding layers of material. AM technologies present several advantages compared to traditional manufacturing technologies, such as producing less material waste and being capable of producing parts with greater geometric complexity. However, deficiencies in the printing process due to high process uncertainty can affect the microstructural properties of a fabricated part leading to defects. In metal AM, previous studies have linked defects in parts with melt pool temperature fluctuations, with the size of the melt pool and the scan pattern being key factors associated with part defects. …