Mathematics-Ai Based Phylogenetic Analysis Of Influenza Virus Mutation Data,
2025
University of Arkansas, Fayetteville
Mathematics-Ai Based Phylogenetic Analysis Of Influenza Virus Mutation Data, Emilee Walden
Mathematical Sciences Undergraduate Honors Theses
The influenza virus is one of the most common viral infections each year and can mutate rapidly. Viral mutations pose significant threats to public health by increasing infectivity and strengthening vaccine resistance. To track these evolving patterns, agencies like the CDC annually evaluate thousands of virus strains to understand viral mutagenesis and evolution in depth. Therefore, a computational method for analyzing high-dimensional, noisy virus data could aid in the rapid identification of antigens essential for an effective influenza vaccine for the upcoming season. Through the integration of genomic analysis, clustering, and dimensionality reduction methods, this study specifically aims to develop …
Studies Of Pathways To T2d And Interventions Through A Dynamical System Model.,
2025
University of Louisville
Studies Of Pathways To T2d And Interventions Through A Dynamical System Model., Rafiqul Islam
Electronic Theses and Dissertations
Existing mathematical models investigating the progression of type 2 diabetes (T2D) over time primarily focus on glucose, insulin, β-cell mass, and other related factors, while often omitting fatty acids (FA) as an explicit variable—despite FA being a major energy source for the body. There exists a complex network of dynamical interactions among glucose, insulin, FA, and β-cell mass. To gain deeper insights into the metabolic dynamics and pathophysiology of T2D, it is essential to incorporate FA into such models. In this study, we extend the classic Topp’s GIβ model by explicitly incorporating FA and exploring its interactions with glucose, insulin, …
Robust And Efficient Solvers For Physics-Based Pde’S,
2025
Clemson University
Robust And Efficient Solvers For Physics-Based Pde’S, Elizabeth Hawkins
All Dissertations
This work was partially supported by the U.S. Department of Energy under award DE- SC0025292, by NSF grant DMS 2152623, and by NSF grant DMS 2011490.
This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Mathematical Multifaceted Integrated Capability Centers (MMICCs) program, under Field Work Proposal 22-025291 (Multifaceted Math- ematics for Predictive Digital Twins (M2dt)), Field Work Proposal 23-020467, and Computing and Information Sciences (CIS) investment area in the Laboratory Directed Research and Development program at Sandia National Laboratories. This written work is authored by an employee …
Domain Decomposition For Coupled Systems Of Fluid-Structure Interaction And Numerical Modeling For Thin Film Polymers,
2025
Clemson University
Domain Decomposition For Coupled Systems Of Fluid-Structure Interaction And Numerical Modeling For Thin Film Polymers, Amy De Castro
All Dissertations
We consider two primary areas of physical application in this work: fluid interaction systems with either linear elastic structures or with poroelastic structures, and thin film polymers, where the majority of the work focuses on the fluid-structure interaction systems.
In the first chapter, we present a strongly coupled partitioned method for fluid structure interaction (FSI) problems based on a monolithic formulation of the system which employs a Lagrange multiplier (LM). We prove that both the semi-discrete and fully discrete formulations are well-posed. To derive the partitioned scheme, a Schur complement equation, which implicitly expresses the Lagrange multiplier and the fluid …
Analysing Bell Experiments Through Test Factors: Applications To Randomness And Strength Of Nonlocality,
2025
LSU New Orleans
Analysing Bell Experiments Through Test Factors: Applications To Randomness And Strength Of Nonlocality, Soumyadip Patra
LSU New Orleans Theses and Dissertations
This work presents practical tools to analyse Bell experiments---experiments demonstrating correlations that defy classical explanations and proving that nature violates local realism. We begin by showing that in the Bell scenario specified by n parties with each party having a choice of m binary-outcome measurements---the (n,m,2) scenario---projecting weakly-signalling settings-conditional outcome distributions onto the smallest-dimensional affine subspace (containing the no-signalling set) via an L^2-distance-minimising map preserves correlators. This result ensures that Bell inequalities written in terms of correlators remain invariant under such projections, and we provide an efficient construction method for the projection operator that avoids computationally costly steps such as …
A Spectroscopic Survey Of Atmospheres Of Super-Earths,
2025
The University of Southern Mississippi
A Spectroscopic Survey Of Atmospheres Of Super-Earths, Luke Brust
Honors Theses
Recent research has made it possible to use spectroscopy to analyze the composition of the atmospheres of exoplanets, planets that orbit other stars. Most projects thus far have focused on the atmospheres of gas giants, as it is less challenging to observe them with available equipment. This project studies the atmospheres of four Super- Earths, planets that have a mass greater than the Earth but smaller than Neptune. This is accomplished by processing the raw spectroscopic data from the Hubble Space Telescope and modeling the atmosphere using the program 𝝉-Rex3. This survey found clear results from two of the selected …
Globally Adaptive Exponential Integrators For Stiff Systems Of Odes,
2025
University of Southern Mississippi
Globally Adaptive Exponential Integrators For Stiff Systems Of Odes, Anzhelika Vasilyeva
Honors Theses
This thesis introduces a novel method for solving systems of Ordinary Differential Equations (ODEs) resulting from the spatial discretization of Partial Differential Equations (PDEs). The proposed approach builds upon an existing technique that employs Krylov projection, which requires evaluating a matrix function at each timestep. The innovation of the new method lies in its reuse strategy, which shifts the perspective from direct matrix function evaluation to polynomial interpolation. Numerical experiments conducted on constant and variable coefficient heat equations, with both smooth and discontinuous initial data, demonstrate the computational time advantage of the new approach. The results indicate that this method …
Improving Research Software Engineering In Mathematics,
2025
University of South Alabama
Improving Research Software Engineering In Mathematics, Abram Miller
Honors Theses
Research Software Engineering is critical to modern mathematical research, enabling the creation, maintenance, and dissemination of computational tools that bridge theory and practice. However, the field faces systemic challenges, including insufficient funding, lack of institutional recognition, and gaps in training and infrastructure. This thesis investigates these challenges through two approaches: (1) a comparative survey study focused on mathematicians and (2) hands-on contributions to an open-source research software project.
The Improving Research Software Engineering in Mathematics survey, conducted from September 2024 to January 2025, adapts the survey framework developed by Carver et al. in A survey of the state of the …
Quantitative Runtime Monitoring Of Ethereum Transaction Attacks,
2025
Singapore Management University
Quantitative Runtime Monitoring Of Ethereum Transaction Attacks, Xinyao Xu, Ziyu Mao, Jianzhong Su, Xingwei Lin, David Basin, Jun Sun, Jingyi Wang
Research Collection School Of Computing and Information Systems
The rapid growth of decentralized applications, while revolutionizing financial transactions, has created an attractive target for malicious attacks. Existing approaches to detecting attacks often rely on predefined rules or simplistic and overly-specialized models, which lack the flexibility to handle the wide spectrum of diverse and dynamically changing attack types. To address this challenge, we present a general and extensible framework, MoE (Monitoring Ethereum), that leverages runtime verification to detect a wide range of attacks on Ethereum. MoE features an expressive attack modeling language, based on Metric First-order Temporal Logic (MFOTL), that can formalize a wide range of attacks. We integrate …
Modeling Dna Repair In Escherichia Coli Using A Boolean And Stochastic Framework,
2025
Clemson University
Modeling Dna Repair In Escherichia Coli Using A Boolean And Stochastic Framework, Gabrianne Ivey
All Theses
DNA can be damaged through both internal and external sources. Therefore, cells have created methods to repair DNA damage. In Escherichia coli, the system responsible for DNA repair is termed the SOS response. This system consists of more than 50 genes and contains three main repair pathways: nucleotide excision repair, translesion synthesis, and homologous recombination. The response is initiated when DNA lesions result in the accumulation of single-stranded DNA (ssDNA). The protein RecA is activated by binding to ssDNA and is then denoted RecA*. RecA* assists in the auto-cleavage of LexA which is the primary repressor protein involved in …
Efficient Solvers And Anderson Acceleration For The Bingham Equations,
2025
Clemson University
Efficient Solvers And Anderson Acceleration For The Bingham Equations, Victoria L. Fisher
All Theses
This work studies two techniques utilized to solve the Bingham equations that model viscoplastic flow. An Uzawa-type iterative procedure is first analyzed and tested for poor convergence of velocity and stress. We apply Anderson acceleration (AA) to this method and show improved convergence rates for both velocity and stress. A solver utilizing regularization is introduced, and AA is also applied to display better convergence results. We propose a new method that combines these two solvers and applies Anderson acceleration.
Solution Of Preconditioned Nonsymmetric Saddle Point Systems Through Modified Conjugate Gradient Iteration,
2025
The University of Southern Mississippi
Solution Of Preconditioned Nonsymmetric Saddle Point Systems Through Modified Conjugate Gradient Iteration, Samson Ayo
Dissertations
In this dissertation, we present an iterative method (Preconditioned Nonsymmetric Saddle Point Conjugate Gradient) for simultaneously solving forward ($A{\bf x}={\bf b}$) and adjoint ($A^T{\bf y}={\bf g}$) linear systems. Our approach involves constructing an augmented nonsymmetric saddle point matrix that has a real positive spectrum and developing a conjugate gradient-like iteration for this matrix. We investigate the use of Schur Complement preconditioners with block-diagonal factorization computed by an incomplete QR factorization of $A$ to speed up the convergence of our method and compare the results to the preconditioned generalized least squares residual (GLSQR) and quasi-minimal residual (QMR) methods. We develop quadrature …
Using Permutation Groups To Identify Family Of Capacity Achieving Codes,
2025
University of Nebraska-Lincoln
Using Permutation Groups To Identify Family Of Capacity Achieving Codes, Daniel Joseph Welchons
Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–
When communicating over a noisy channel, the probability of message interference sets a maximum possible transmission rate known as the channel capacity. Any family of codes which have rates converging to the channel capacity and arbitrarily low probability of decoding failure is called capacity achieving. Such codes have been known to exist since the birth of information theory but are difficult to find explicitly. It has recently been shown that the permutation groups of a family of codes can be used to show that the family is capacity achieving on the q-ary erasure channel.
This this thesis seeks to …
Decoding The Algorithm: The Mathematics Behind Tiktok’S Short-Form Content Success,
2025
University of Connecticut
Decoding The Algorithm: The Mathematics Behind Tiktok’S Short-Form Content Success, Ashley N. Lynch
Honors Scholar Theses
Within the realm of social networks, TikTok has become the central hub for short-form video content. The network’s unique ability to capture individual preferences using predictive analytics has greatly contributed to its massive success, allowing the company to optimize its performance and content personalization. In an age where digital media have such a significant influence on society, it is essential that users develop an understanding of how social network algorithms function to make more informed online decisions. Although TikTok’s technological system is primarily undisclosed, the platform certifiably leverages several key mathematical principles within its algorithm to achieve its core goals …
Evaluating Risk And Return Of Corn And Soybean Marketing Strategies Using Monte Carlo Simulation Methods,
2025
University of Nebraska-Lincoln
Evaluating Risk And Return Of Corn And Soybean Marketing Strategies Using Monte Carlo Simulation Methods, Johanna Ilves
Department of Agricultural Economics: Dissertations, Theses, and Student Research
This study evaluates the performance of pre-harvest marketing strategies for corn and soybeans, using Monte Carlo simulation techniques. Given the increasing volatility in commodity prices and the evolving landscape of agricultural markets, producers face growing challenges in developing effective marketing plans that manage risk and enhance profitability. This thesis examines thirteen marketing strategies from 2008 to 2024, including benchmark harvest-only sales and various pre-harvest futures contract approaches. Historical futures price data for December corn and November soybean contracts were used to simulate 1,000 marketing outcomes per strategy per year, capturing a broad range of market conditions. Key performance indicators such …
Using Permutation Groups To Identify Families Of Capacity Achieving Codes,
2025
University of Nebraska-Lincoln
Using Permutation Groups To Identify Families Of Capacity Achieving Codes, Daniel Welchons
Department of Mathematics: Dissertations, Theses, and Student Research
When communicating over a noisy channel, the probability of message interference sets a maximum possible transmission rate known as the channel capacity. Any family of codes which have rates converging to the channel capacity and arbitrarily low probability of decoding failure is called capacity achieving. Such codes have been known to exist since the birth of information theory, but are difficult to find explicitly. It has recently been shown that the permutation groups of a family of codes can be used to show that the family is capacity achieving on the q-ary erasure channel.
This thesis seeks to apply the …
Random Processes With High Variance Produce Scale Free Networks,
2025
Boise State University
Random Processes With High Variance Produce Scale Free Networks, Josh Johnston
Boise State University Theses and Dissertations
The degree distribution of a real world network --- the number of links per node --- often follows a power law, so some hubs have many more links than traditional graph generation methods predict. For years, preferential attachment and growth have been the proposed mechanisms leading to these scale free networks, exemplified by the Barabási–Albert model. This dissertation provides an alternative model using a randomly stopped linking process, showing that mixtures of geometric distributions can lead to power laws, an intuition suggested by the Central Limit Theorem for distributions with infinite variance. Having a collection of Bernoulli trials with high …
The Herzog-Takayama Resolution Over A Skew Polynomial Ring,
2025
The University of Texas Rio Grande Valley
The Herzog-Takayama Resolution Over A Skew Polynomial Ring, Linoy Utkina
Theses and Dissertations
Let k be a field, and let I be a monomial ideal in the polynomial ring R = k[x1,..., xn]. In her thesis, Taylor introduced a complex that yields a finite free resolution of R/I as an R-module. Building on Taylor’s work, Ferraro, Martin, and Moore extended this construction to monomial ideals in skew polynomial rings. Because the Taylor resolution is typically not minimal, subsequent research efforts went into identifying specific classes of ideals whose minimal free resolutions can be constructed more simply. In 1990, Eliahou and Kervaire devised an approach for handling minimal resolutions of …
Congruences In Arithmetic Progression For Coefficients Of Gaussian Polynomials And Crank Statistics,
2025
The University of Texas Rio Grande Valley
Congruences In Arithmetic Progression For Coefficients Of Gaussian Polynomials And Crank Statistics, Joselyne Aniceto
Theses and Dissertations
The study of partition congruences, inspired by Ramanujan’s discoveries for ��(��) over a century ago, remains a central topic in this field. This dissertation examines congruence properties in two restricted partition functions: ��(��,��), which counts partitions of �� into at most �� parts, and ��(��,��,��), which further limits the size of the largest part to be at most ��. Building on Kronholm’s 2007 result, now known as the Interval Theorem, and a recent result by Eichhorn, Engle, and Kronholm, we establish new infinite families of congruences for ��(��,��,��). This dissertation extends not only the recent results of Eichhorn, Engle, …
Implementing And Evaluating An Ai-Powered Visual Decision Support System To Improve Antibiotic Usage Among Physicians With A Built-In Early Warning System,
2025
The University of Texas Rio Grande Valley
Implementing And Evaluating An Ai-Powered Visual Decision Support System To Improve Antibiotic Usage Among Physicians With A Built-In Early Warning System, Akua Sekyiwaa Osei-Nkwantabisa
Theses and Dissertations
The widespread misuse and excessive prescription of antibiotics have played a pivotal role in the emergence and proliferation of antibiotic-resistant bacteria, posing a critical global public health crisis. Addressing this challenge necessitates innovative solutions that enhance antimicrobial stewardship. This study presents the development and implementation of a visual decision support system designed to monitor and optimize antibiotic usage among healthcare providers. The proposed system integrates advanced machine learning algorithms with real-time data analytics to provide a dynamic, evidence-based decision support tool. Specifically, a neural network model was developed after evaluating multiple machine learning approaches, including Random Forest, Logistic Regression and …
