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USF Tampa Graduate Theses and Dissertations

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Full-Text Articles in Physical Sciences and Mathematics

Concentration And Composition Of Organic Contaminants In Blackfin Tuna, Yellowfin Tuna, And The Common Clubhook Squid In The Western Gulf Of Mexico, Lisa Rose-Mann Jul 2025

Concentration And Composition Of Organic Contaminants In Blackfin Tuna, Yellowfin Tuna, And The Common Clubhook Squid In The Western Gulf Of Mexico, Lisa Rose-Mann

USF Tampa Graduate Theses and Dissertations

Cephalopods are an important component of pelagic food webs. They play ecological roles not only as predators but also as prey. However, their role as prey in the trophic transfer of organic contaminants to apex predators such as tunas in the Gulf of Mexico (GoM) is not well known. To investigate the importance of cephalopods in tuna diets, stomach samples were collected in February 2020 from tunas caught by rod and reel aboard the F/V Gulf Eagle near two large offshore floating oil/gas platforms in the northwestern GoM. Cephalopod samples were obtained from gut content analysis of 41 tunas caught …


Exploring System Identification Of Non-Linear Dynamics Using The Weighted Composition Operator And The Liouville Operator, Chukwuebuka Amagwula Jul 2025

Exploring System Identification Of Non-Linear Dynamics Using The Weighted Composition Operator And The Liouville Operator, Chukwuebuka Amagwula

USF Tampa Graduate Theses and Dissertations

System identification is the process of determining mathematical models that describe the dynamics of a system from data. Dynamic Mode Decomposition (DMD) and Sparse Identification of Nonlinear Dynamical Systems (SINDy) are two distinct approaches used for this purpose.

DMD identifies dominant spatiotemporal modes and eigenvalues that describe the evo lution of a system. It assumes a near-linear representation of dynamics and is closely linked to the Koopman operator, making it ideal for analyzing fluid flows, oscillatory systems, and modal structures. The DMD method uses time series data where each data point is referred to as a snapshot and represents the …


Beyond The Hype: The Fundamental Challenges Of Machine Learning-Based Android Malware Detection In Cybersecurity, Guojun Liu Jun 2025

Beyond The Hype: The Fundamental Challenges Of Machine Learning-Based Android Malware Detection In Cybersecurity, Guojun Liu

USF Tampa Graduate Theses and Dissertations

Machine learning (ML) algorithms have achieved remarkable success across various domains, including cybersecurity. Inspired by these advancements, the academic security community has explored numerous ML-based approaches for Android malware detection. While ML holds significant promise in this domain, its practical deployment faces substantial challenges, including data collection, feature selection, app representation across different models, performance instability across datasets, and inherent limitations of learning-based malware detection. These challenges can lead to overly optimistic detection results and weaken the reliability of malware detection frameworks.

Android malware detection has been extensively studied using both traditional ML and deep learning (DL) approaches. Although many …


Phosphorus: From The Origins Of Life To The Origin Of An Industry, Joshua Abbatiello Jun 2025

Phosphorus: From The Origins Of Life To The Origin Of An Industry, Joshua Abbatiello

USF Tampa Graduate Theses and Dissertations

The element phosphorus is a key biogenic element that is often the limiting reagent for life. Phosphorus is quickly bound by metal divalent cations making it virtually insoluble and inert in water (forming the phosphate mineral apatite). Due to this, it becomes imperative to understand alternative pathways to increase biogenically available phosphorus in environments. To that end, this dissertation involved examining olivine as an alternative source of phosphorus to apatite, analyzing a novel grain of iron silicide found via lightning reduction in a fulgurite, and finally sought to understand the impact of phosphate mining through phosphogypsum stacks. Olivine is a …


The Synthesis Of A Photo-Affinity Probe Library For The Fatty Acid Amide Proteome And The Endocannabinoid System Within, Robert E. Feeney Iii Jun 2025

The Synthesis Of A Photo-Affinity Probe Library For The Fatty Acid Amide Proteome And The Endocannabinoid System Within, Robert E. Feeney Iii

USF Tampa Graduate Theses and Dissertations

Fatty acid amides are a large family of endogenous metabolites with significant biological activity, including that of the endocannabinoid system. Currently little is known about how this system of tightly regulated compounds works within humans. This work lays the foundation to explore the structure-activity relationship driving the selectivity of ligand-protein interactions involved with fatty acid amides. A library of activity-based proteomic profiling probes for fatty acid amides has been synthesized to this end. Additionally, progress towards phytocannabinoid probes has been made as well.


An Exploratory Analysis Of Automated Deception Detection For Mental Health Applications, Sayde Leya King Jun 2025

An Exploratory Analysis Of Automated Deception Detection For Mental Health Applications, Sayde Leya King

USF Tampa Graduate Theses and Dissertations

Deception in mental health settings can undermine therapeutic relationships, compromise treatment efficacy, and impact patient outcomes. Yet, research shows that mental health clinicians often perform no better than chance at detecting deceptive behavior in therapy. Automated deception detection, leveraging artificial intelligence (AI) and multimodal behavioral cues—such as eye gaze, body gestures, and facial expressions—offers a promising alternative. However, most existing research focuses on high-stakes legal contexts, limiting its applicability to mental health settings.

This dissertation addresses this gap by pursuing three key research objectives using a mixed-methods approach. First, we investigate mental health clinicians’ perspectives on AI-assisted deception detection through …


Efficient Methods And Algorithms For Analyzing Stochastic Systems, Mohammad Ahmadi Jun 2025

Efficient Methods And Algorithms For Analyzing Stochastic Systems, Mohammad Ahmadi

USF Tampa Graduate Theses and Dissertations

This dissertation addresses the challenges of stochastic analysis of safety-critical systems with biological components, where unexpected behavior can lead to catastrophic events. Two fundamental challenges hinder the analysis of such systems: their typically large or infinite state spaces, and the extreme rarity of error states of interest. While Monte Carlo simulation can analyze biochemical systems without storing the state space, accurately estimating rare event probabilities becomes computationally prohibitive. Conversely, probabilistic model checking excels at analyzing extremely low probability events but becomes impractical for systems with large or infinite state spaces due to memory constraints.This work proposes two main contributions to …


Isotopic Fingerprints Of The Coastal Margins: Tracing Dissolved Iron Sources From Land To Sea, Hannah R. Hunt Jun 2025

Isotopic Fingerprints Of The Coastal Margins: Tracing Dissolved Iron Sources From Land To Sea, Hannah R. Hunt

USF Tampa Graduate Theses and Dissertations

Dissolved iron (dFe) is an essential micronutrient for sustaining life in the surface ocean. Nearly four decades of research dedicated to understanding sources, cycling and biogeochemical modifications of Fe sources in the global oceans has generated a significant body of research supporting the idea that the concentration of Fe in the surface ocean exerts significant controls on primary production and carbon uptake in the surface ocean. Creation of the GEOTRACES program greatly increased the spatial and temporal resolution of high-quality trace element and trace element isotope data revealing new insights into the global Fe cycle, especially through the use of …


Applications Of Contracting Self-Similar Groups To Cryptography And Scale Groups, Arsalan Akram Malik Jun 2025

Applications Of Contracting Self-Similar Groups To Cryptography And Scale Groups, Arsalan Akram Malik

USF Tampa Graduate Theses and Dissertations

Given their peculiar properties, self-similar groups are of great interest both from applications and theoretical standpoints. In this work we study the scope of their applications in post-quantum cryptography and in constructing scale groups via lifting maps.

We propose self-similar contracting groups as a platform for cryptographic schemes based on simultaneous conjugacy search problem (SCSP). This class of groups admits fast polynomial-time algorithms for the word problem and element multiplication that can be used for effective encryption and decryption of messages. It contains extraordinary examples like the Grigorchuk group, which is known to be non-linear, thus making some of existing …


On Some Hypergraph Coloring Algorithms, Boyoon Lee Jun 2025

On Some Hypergraph Coloring Algorithms, Boyoon Lee

USF Tampa Graduate Theses and Dissertations

Of a given bipartite graph G = (V, E), it is elementary to construct a bipartition in timeO(|V |+|E|). For a given k-graph H = H(k) with k ≥ 3 fixed, Lovász proved that deciding whether H is bipartite is NP-complete. In this thesis, we consider the average running time of this problem. For that, let B_n = (B^(k))_n be the collection (family) of all bipartite k-graphs H on the fixed vertex set [n] = {1, ...., n}. We construct, of a given H ∈ B_n, a bipartition in time averaging O(n^k) over the class B_n. We provide two proofs …


The Only Constant Is Change: The Role Of Genetic Diversification In Cancer And Beyond, Malgorzata Tyczynska Weh Jun 2025

The Only Constant Is Change: The Role Of Genetic Diversification In Cancer And Beyond, Malgorzata Tyczynska Weh

USF Tampa Graduate Theses and Dissertations

Genetic diversification, the process by which genetic variation arises in a population, is fundamental to evolution by natural selection. Mutation, a central diversification process, fuels adaptation across species, including in cancer. Yet most new mutations are neutral or deleterious on cell fitness, raising the question of how mutation-driven adaptation persists. To explore this paradox, I developed a spatial agent-based model (ABM) in which population fitness emerges from individual cells acquiring mutations at varied rates and with diverse fitness effects. I evaluated model behavior across adaptive states, mutation rates, and distributions of fitness effects. The results show that high mutation rates …


Sea Turtle Nesting On Nourished Beaches With Different Construction Designs: A Case Study In Southeast Florida, Usa., Lara Novalvos Hernandez Jun 2025

Sea Turtle Nesting On Nourished Beaches With Different Construction Designs: A Case Study In Southeast Florida, Usa., Lara Novalvos Hernandez

USF Tampa Graduate Theses and Dissertations

This study examines the influences of different beach nourishment designs and subsequent post-nourishment profile adjustments on loggerhead (Caretta caretta) and green (Chelonia mydas) sea turtles nest survival and reproductive success. Data on time-series post-nourishment beach-profile changes, positions and elevations of turtle tracks and nest/false-crawl apices, and sea turtle nest hatch/emergence success were collected on five high density nesting beaches along the east coast of Florida: Melbourne Beach, Jensen Beach, Jupiter Island Beach, Juno Beach, and South Hutchinson Island Beach. The field data collection was conducted in 2018, 2019, 2021, and 2022 with the main goal of documenting and comparing turtle …


Behavior And Land Use Of Eastern Gray Squirrels In Urban And Suburban Environments, Laura F. Engel Jun 2025

Behavior And Land Use Of Eastern Gray Squirrels In Urban And Suburban Environments, Laura F. Engel

USF Tampa Graduate Theses and Dissertations

Urbanization has significantly altered natural habitats, impacting wildlife behavior and distribution. This study examines the behavior and land use of eastern gray squirrels (Sciurus carolinensis) in urban and suburban environments at the University of South Florida. Using a combination of point count surveys and time-activity budgets, squirrel presence was assessed in relation to tree genera, nest locations, human activity, and infrastructure. Results indicate a significant association between squirrel presence and tree genera, with a preference for Quercus species, as well as a strong positive correlation between human infrastructure and squirrel presence. However, no significant relationship was found between human presence …


Quantifying Wellbore Effects During Co2 Sequestration In A Saline Aquifer, Uzoma Johnpaul Ajugwe Jun 2025

Quantifying Wellbore Effects During Co2 Sequestration In A Saline Aquifer, Uzoma Johnpaul Ajugwe

USF Tampa Graduate Theses and Dissertations

Carbon capture and storage (CCS) is a strategy for mitigating climate change by reducing greenhouse gas emissions from large stationary sources like fossil-fuel-fired power stations. One method of CCS involves carbon dioxide (CO2) sequestration in deep saline aquifers, where supercritical CO2 is injected into an aquifer. The success of such projects depends on accurate predictions of CO2 behavior within the subsurface, which are obtained through numerical simulations.

TOUGHREACT, a renowned simulation tool, models subsurface fluid flow, geochemical interactions, and solute transport, providing insights into the feasibility of CO2 sequestration projects. A critical aspect of these simulations is the apportioning of …


A Community-Based Study To Investigate Persistent Ambient Odors In Childs Park, Fl, Gennaro Saliceto Jun 2025

A Community-Based Study To Investigate Persistent Ambient Odors In Childs Park, Fl, Gennaro Saliceto

USF Tampa Graduate Theses and Dissertations

For many years, residents in Childs Park, Saint Petersburg, Florida, have reported unpleasant odors. Although there have been prior efforts to address the issue, the odors continue to be a concern for the community, who worry about possible health implications. This research aimed to equip residents with information to address the issue by identifying the presence of airborne pollutants that generate odors, quantifying the concentrations of toxic organic pollutants, and exploring the sources and environmental conditions that contribute to odors and their perception.

To accomplish these aims, the study utilized different methods. First, two walking measurement campaigns were conducted to …


Development And Photophysical Characterization Of Bioinspired Materials, Qaisar Maqbool Jun 2025

Development And Photophysical Characterization Of Bioinspired Materials, Qaisar Maqbool

USF Tampa Graduate Theses and Dissertations

Porphyrins are versatile aromatic macrocycles with unique photophysical properties that make them attractive for applications in light harvesting, photocatalysis, and sustainable energy conversion. Incorporating porphyrins into metal-organic frameworks (MOFs) offers a unique opportunity to modulate their photophysical behavior through spatial confinement and host–guest interactions. This thesis explores how structural modifications influence porphyrin excited-state behavior through a multi-stage investigation. The work begins by comparing the photophysical properties of two cationic porphyrins: tetra(N-methylpyridyl) porphyrin(TMPyP) and tetra(4-N,N,N-trimethylanilinium) porphyrin(4TANP). While TMPyP exhibits significant singlet–charge transfer (S₁–CT) state mixing due to charge delocalization onto peripheral pyridinium groups, 4TANP lacks comparable behavior. The localized nature of …


Topics In Knot, Quandle, And Quiver Theory, Brooke Jones Apr 2025

Topics In Knot, Quandle, And Quiver Theory, Brooke Jones

USF Tampa Graduate Theses and Dissertations

This dissertation explores the algebraic and combinatorial structures arising from the study of knot theory through the lens of quandles, their colorings, and associated quiver and ring constructions. It is organized around three central themes: the analysis of quandle coloring quivers for torus links, the development of polynomial invariants and quiver invariants for stuck knots and links, and the algebraic and graphical study of quandle rings. The first chapter begins with an introduction to relevant concepts throughout the dissertation.

In the second chapter, we classify quandle coloring quivers of torus links using dihedral quandles. We describe these quivers as weighted …


Enhancing State-Of-The-Art Motor Imagery Classification With Reinforcement Learning, Anton Shepelev Apr 2025

Enhancing State-Of-The-Art Motor Imagery Classification With Reinforcement Learning, Anton Shepelev

USF Tampa Graduate Theses and Dissertations

One of the key obstacles to the rapid adoption of non-invasive Brain-Computer Interfaces (BCIs) for Motor Imagery (MI) is the low signal-to-noise ratio, and the substantial data requirements which can be mentally taxing for users. EEGNet, a compact Convolutional Neural Network (CNN), has long been considered the state-of-the-art (SOTA) for MI classification, demonstrating strong performance even with limited data. However, recent studies advocate for integrating Deep Reinforcement Learning (RL) to further enhance classification accuracy by dynamically optimizing feature extraction and decision-making processes. Despite this potential, practical implementations remain scarce due to challenges in stabilizing RL training and adapting it to …


Integrative Multi-Omics And Clinical Data Analysis For Predicting Recurrence And Survival In Uterine Cancer, Varun Sai Raigir Mar 2025

Integrative Multi-Omics And Clinical Data Analysis For Predicting Recurrence And Survival In Uterine Cancer, Varun Sai Raigir

USF Tampa Graduate Theses and Dissertations

The prediction of uterine cancer recurrence is very important for assisting women in reducing the cancer risks and also for the growing field of personalized medicine. The primary aim of this thesis is to investigate the integration of various omics data alongside clinical and therapeutic information to predict survival in uterine cancer. The combination is very important for understanding the risk factors, including clinical aspects, genetics, and the treatment schedule, in order to prescribe the appropriate way to reduce the risk of recurrence, make clinical interactions easier, and enhance personalized patient care. This study utilizes the publicly accessible TCGA dataset, …


Automated Data Analysis For Concussion Patient Records: A Flutter-Based Desktop Application, Fhaheem Tadamarry Mar 2025

Automated Data Analysis For Concussion Patient Records: A Flutter-Based Desktop Application, Fhaheem Tadamarry

USF Tampa Graduate Theses and Dissertations

Concussions are a prevalent and complex medical condition requiring careful clinical assessment and data-driven insights for effective management. This thesis presents the development of an automated data analysis system for concussion patient records, integrating Flutter-based desktop application development with SQL-driven data processing. The system provides a streamlined, interactive interface for clincians and researchers to upload, visualize, and analyze patient data efficiently.

The proposed solution automates data cleaning, preprocessing, and statistical analysis, ensuring robust and reliable insights into demographic, clinical, and recovery-related factors. Key analyses include sex-based differences injury mechanisms, prior head injury impact, mood disorder correlations, and time-to-treatment variations. The …


Multimodal Ai-Driven Biomarker For Early Detection Of Cancer Cachexia, Sabeen Ahmed Mar 2025

Multimodal Ai-Driven Biomarker For Early Detection Of Cancer Cachexia, Sabeen Ahmed

USF Tampa Graduate Theses and Dissertations

Cancer cachexia is a metabolic syndrome characterized by substantial skeletal muscle loss, impacting cancer patients' survival and quality of life. Despite its clinical significance, early detection remains a challenge due to the lack of standardized diagnostic criteria and the reliance on indirect markers. This work presents an AI-driven approach to enhance cachexia detection and monitoring by integrating multiple deep learning methodologies. We explore transformer architectures for time-series analysis to model sequential medical data, enabling disease prediction and progression modeling. To ensure robust and reliable decision-making in clinical settings, we explore Bayesian deep neural networks for uncertainty estimation. Additionally, we introduce …


Textbook Content Analysis For Statistical Content Standards For 8th-Grade Math: Commercial Publishers, Curriculum Software Supplement, And An Open Educational Resource, Matthew M. O'Brien Mar 2025

Textbook Content Analysis For Statistical Content Standards For 8th-Grade Math: Commercial Publishers, Curriculum Software Supplement, And An Open Educational Resource, Matthew M. O'Brien

USF Tampa Graduate Theses and Dissertations

This dissertation examined the vertical and horizontal content analysis of statistical content within current 8th-grade mathematics instructional materials to determine the extent to which students are provided with opportunity to learn high cognitive instances and the usage of the four phases of statistical problem-solving across two commercial publishers, one open educational resource, and one curriculum software supplement. All previous analyses of statistics education content textbooks have only examined textbooks from commercial publishers or those published by national governments. The horizontal content textbook analysis investigated the textbook's background information and overall structure. The vertical content textbook analysis examined the cognitive level …


Exploring Corona Discharge In Electrostatic Printing For Electronics And In Other Application, Zijian Weng Mar 2025

Exploring Corona Discharge In Electrostatic Printing For Electronics And In Other Application, Zijian Weng

USF Tampa Graduate Theses and Dissertations

The field of printed electronics (PEs) is expanding rapidly, driven by increasing market demand. According to reports, the global market for PEs is expected to reach $23 billion by 2026, with a compound annual growth rate of 18.3% from 2023 to 2028. This growth necessitates the development of innovative printing technologies that can meet these demands efficiently, delivering high-quality, high-resolution PEs suitable for applications in health, environmental monitoring, sports, aerospace, and more.

Currently, PEs manufacturing relies on two main groups of printing technologies. Contact printing methods offer high-speed production but struggle with precision, while non-contact methods provide high resolution but …


The Asset Management Optimization Engine: An Ai And Machine Learning Model Approach To Pavement Asset Management, Matt Versdahl Mar 2025

The Asset Management Optimization Engine: An Ai And Machine Learning Model Approach To Pavement Asset Management, Matt Versdahl

USF Tampa Graduate Theses and Dissertations

While state Departments of Transportation (DOT) face major funding challenges, the need to find optimal ways to preserve and maintain pavement assets remains. Asset management employs a lowest cost lifecycle method to analyze asset costs and determine the best investment strategies to preserve it throughout its lifecycle. As new technology emerges, so do opportunities to leverage it. DOTs collect a significant amount of performance data on pavement and use it to decide how to keep it in a state of good repair. The literature in this area focuses on engineering techniques applied to treatment strategies. This dissertation research focuses on …


New Petrographic And Geochemical Constraints On Pre-Eruptive Storage Conditions And Their Control On Eruptive Styles In Martinique’S Recent Volcanic Systems, Abigail Martens Mar 2025

New Petrographic And Geochemical Constraints On Pre-Eruptive Storage Conditions And Their Control On Eruptive Styles In Martinique’S Recent Volcanic Systems, Abigail Martens

USF Tampa Graduate Theses and Dissertations

This dissertation investigates the volcanic systems of Martinique Island, focusing on magma storage conditions, magmatic evolution, and eruption dynamics. Chapter 3 presents a petrographic analysis of volcanic rocks from the island’s old, intermediate, and recent arcs, examining the evolution of plagioclase textures and the increasing abundance of other mineral phases, such as pyroxene, amphibole, olivine, and quartz, which provide insights into changing magmatic conditions. The main research is divided into two projects. Chapter 4 addresses the pre-eruptive storage conditions (pressure and temperature) of magmas beneath recent (<5 Ma) volcanic complexes (Morne Jacob, Piton du Carbet, Trois Îlets, Mt. Conil, and Mt. Pelée), exploring magma evolution, crystallization, and the role of lower crustal injections and flank collapses in triggering eruptions. Results reveal variable magma storage depths (<6 km), with significant temperature and pressure variations, indicating complex magmatic systems. Chapter 5 focuses on the Roches-Genty ignimbrite in southwestern Martinique, investigating its stratigraphy, geochemistry, and age using field mapping, grain size analysis, and 40Ar/39Ar dating. The study identifies two distinct sub-Plinian eruptive phases associated with the Dizac ignimbrite, with ages of 3.37 ± 0.14 Ma and 2.10 ± 0.26 Ma, providing insights into past explosive volcanic activity. Geochemical analysis confirms an andesitic composition, similar to regional volcanic systems. This dissertation enhances understanding of Martinique’s volcanic history, providing valuable insights into magmatic processes and eruption dynamics, with implications for volcanic hazard assessments in the Lesser Antilles.


Context And Interpretability In Affective Computing Applications, Saandeep Aathreya Sidhapur Lakshminarayan Mar 2025

Context And Interpretability In Affective Computing Applications, Saandeep Aathreya Sidhapur Lakshminarayan

USF Tampa Graduate Theses and Dissertations

Affective Computing (AC) is a subdomain of AI that primarily deals with recognizing and interpreting human emotions. This field inherently intersects with psychological studies, as the comprehension of human emotions and behaviors necessitates an understanding of their underlying cognitive processes. One such concepts that lends itself from psychology is context. Roughly speaking, context in AC is defined as any meta information (e.g., environment) that can be utilized to describe the interaction between a user and a model to solve a particular application (e.g., emotion recognition). This doctoral dissertation comprises of two distinct yet interconnected components (Part I and II), the …


Springscape: The Nature Coast And The Making Of Modern Florida, 1820s-Present, Douglas E. Ponticos Mar 2025

Springscape: The Nature Coast And The Making Of Modern Florida, 1820s-Present, Douglas E. Ponticos

USF Tampa Graduate Theses and Dissertations

According to an oft-repeated tale, the Florida we know today emerged as a dreamscape of tourism, retirement, and suburbanization during the second half of the twentieth century. Growth victimized nature. This dissertation deeply unsettles that story. The history of the Nature Coast exposes not just nature’s agency but its primacy in the development of modern Florida.

Using surveys, maps, census data, personal correspondence, government documents, business records, timber reports, advertising materials, and hydrological research, this dissertation follows time and water across landscapes, into the Upper Floridan Aquifer, and back out again. Each chapter explores a single landscape within the Nature …


Fractional Calculus Approach For Learning Unknown Dynamic System, Haowei(Alice) Chen Mar 2025

Fractional Calculus Approach For Learning Unknown Dynamic System, Haowei(Alice) Chen

USF Tampa Graduate Theses and Dissertations

The rapidly growing interest in data-driven modeling and fractional-order systems highlights a keychallenge in modern science and engineering: capturing long-memory effects and nonlinear behaviors in real-world dynamical processes. Conventional integer-order methods, while powerful, often overlook the history-dependent nature of many phenomena—ranging from viscoelastic materials to anomalous diffusion and hereditary feedback systems. This dissertation addresses that gap by blending fractional calculus with cutting-edge machine learning to create robust, memory-aware modeling and control frameworks.

Beginning with an extension of Dynamic Mode Decomposition (DMD) to fractional-order systems, we introduce Fractional Dynamic Mode Decomposition (F-DMD) as a data-driven tool that leverages Mittag- Leffler functions …


Applications Of Linear Discriminant Analysis In The Biomechanics Of Anterior Cruciate Ligament Injury, Taofeek Braimoh Mar 2025

Applications Of Linear Discriminant Analysis In The Biomechanics Of Anterior Cruciate Ligament Injury, Taofeek Braimoh

USF Tampa Graduate Theses and Dissertations

Anterior cruciate ligament (ACL) injury is a prevalent and significant concern in sports medicine, often resulting in long-term consequences that affect quality of life. Despite advancements in medical technology, current methods for addressing the problem of ACL injuries remain inefficient, subjective, and limited in their predictive power. This study explores the potential of Linear Discriminant Analysis (LDA), a supervised machine learning (ML) technique, to improve the diagnosis and risk profiling of ACL injuries. This research aims to create an objective, effective, and precise technique for determining the risk of ACL injuries by examining key biomechanical, physical, and demographical features. The …


Development Of S(Vi) And S(Iv) Chemistry: From Asymmetric Synthesis To Covalent Reactive Groups, Chuan Shan Mar 2025

Development Of S(Vi) And S(Iv) Chemistry: From Asymmetric Synthesis To Covalent Reactive Groups, Chuan Shan

USF Tampa Graduate Theses and Dissertations

This dissertation mainly covers the development of synthetic methodologies related to several heteroatom functional groups, including phosphonates P(V), sulfoximines S(VI), sulfonimidamides S(VI), sulfonimidoyl fluorides S(VI), and sulfinamides S(IV). The interests in these functionalities are not only out of chemistry curiosity but also due to their pharmaceutical importance indicated by the existing drug molecules that contain these functional groups. The first chapter introduced the importance of phosphonates in biochemistry and organic synthesis, also provided some essential background of our synthetic efforts. The second chapter described the phosphonate synthesis from commercially available starting materials, with the purpose to obtain heterocyclic phosphonates in …