Underclosed Posets,
2026
University of San Diego
Underclosed Posets, Richard Ngo
McNair Summer Research Program
Underclosed complexes are a recent generalization of interval graphs to higher dimensions. Motivated by underclosed complexes, we define and study underclosed posets. Order ideals of these posets correspond to pure underclosed complexes. We classify which principal order ideals are rank-symmetric (and in fact are self-dual).
A Modeling Scenario For Cooling A Hot Vehicle In Florida,
2026
Florida Polytechnic University
A Modeling Scenario For Cooling A Hot Vehicle In Florida, Jared Bunn, Bernadette Mullins, Elizabeth Hale, Jaeyoun Oh
CODEE Journal
This paper presents a group project assigned in a Calculus 2 course that has students work to develop, analyze, and draw conclusions about a modeling scenario for cooling a hot car. Using a modeling-first approach, instructors supported the students in class throughout the beginning of the project, enabling the groups to complete the remainder of the project on their own. Students used parameter estimation to tune their models to provided data: one for windows being up, and one for windows being down. This project provides an example of how modeling can be introduced early in a calculus course, rather than …
Curious Patterns And Identities Involving Consecutive Integers,
2026
The University of Texas Rio Grande Valley
Curious Patterns And Identities Involving Consecutive Integers, Carlo Cattani, Mrinal Kanti Roychowdhury
School of Mathematical & Statistical Sciences Faculty Publications
Consecutive integers exhibit numerous surprising patterns and elegant identities. In this article, we investigate several classical properties involving products, sums, divisibility, perfect squares, cubes, pronic numbers, triangular numbers, sums of squares, and Pythagorean triples. Using only elementary algebra, symmetry arguments, and mathematical induction, we establish a collection of identities that reveal rich connections among these classical topics. The exposition is intended for students, teachers, and recreational mathematicians, illustrating how simple observations about consecutive integers can lead to beautiful mathematical patterns and deeper insights into elementary number theory.
The Mathematics Of Calendar Patterns: Day-Of-Week Phenomena, Number Patterns, And Recreational Investigations,
2026
The University of Texas Rio Grande Valley
The Mathematics Of Calendar Patterns: Day-Of-Week Phenomena, Number Patterns, And Recreational Investigations, Vijender Nallapu, Mrinal Kanti Roychowdhury
School of Mathematical & Statistical Sciences Faculty Publications
Calendars are among the most familiar mathematical structures encountered in everyday life. Beyond their practical use in organizing dates and measuring time, calendars contain a rich collection of numerical patterns, symmetries, and arithmetic relationships. Many of these patterns can be explored using only elementary mathematics, making calendars an attractive subject for recreational investigation and mathematical enrichment.
In this article we examine several mathematical properties arising from the structure of monthly calendars. We investigate arithmetic patterns associated with rows, columns, and rectangular blocks of dates, establish properties of calendar squares, and explore connections with modular arithmetic through day-of-week calculations. We also …
Vedic Mathematics And Mental Computation: Fast Multiplication Techniques, Algebraic Foundations, And Historical Perspectives,
2026
The University of Texas Rio Grande Valley
Vedic Mathematics And Mental Computation: Fast Multiplication Techniques, Algebraic Foundations, And Historical Perspectives, Rakesh Bhatia, Mrinal Kanti Roychowdhury
School of Mathematical & Statistical Sciences Faculty Publications
Mental computation has fascinated mathematicians, educators, and students for centuries. Various computational techniques allow arithmetic calculations to be performed rapidly without the use of calculators or computers. Among these methods, several popular techniques are associated with what is commonly known as Vedic Mathematics. In this article, we examine a collection of fast multiplication techniques, including multiplication near powers of ten, multiplication by eleven, squaring numbers ending in five, and the vertical-and-crosswise method. For each technique, we provide elementary mathematical explanations based on algebraic identities and place-value representations.
Hidden Symmetries Of The Classical 3×3 Magic Square,
2026
The University of Texas Rio Grande Valley
Hidden Symmetries Of The Classical 3×3 Magic Square, Vijender Nallapu, Mrinal Kanti Roychowdhury
School of Mathematical & Statistical Sciences Faculty Publications
The classical 3×3 magic square is one of the most famous objects in recreational mathematics. Its defining feature is that every row, every column, and the two main diagonals have the same sum. However, beyond this well-known property, the square contains several hidden symmetries involving rotations, reflections, complementary pairs, parity, and balance around the central entry. In this article, we present an elementary exploration of these symmetries and show how the classical magic square provides a beautiful introduction to mathematical structure and pattern recognition.
Rockin’ Rover On The Rainbow Road,
2026
Palm Beach Atlantic University
Rockin’ Rover On The Rainbow Road, Michael Kolta, Lawrence Burgee, Ying Yuan
Transformations
This paper presents a progressive series of age-appropriate lesson plans for grades K-12 that all use the same interdisciplinary activity to educate students about Science, Technology, Engineering, Art, and Mathematics (STEAM) simultaneously. Technology from Texas Instruments (TI) was employed including a TI Nspire graphing calculator that can run Python programs, a TI Innovator Hub, and a TI Rover. The TI Rover is a small, robotic car that has sensors and is controlled by the calculator via the Hub hardware interface. A Python program was developed that uses the color sensor in the Rover to detect the color on colored paper …
The 2025 Measles Outbreak In Texas,
2026
The University of Texas Rio Grande Valley
The 2025 Measles Outbreak In Texas, Tamer Oraby, Martial L. Ndeffo-Mbah
School of Mathematical & Statistical Sciences Faculty Publications
Background: In 2025, Texas experienced its largest measles outbreak in decades, reporting 762 cases by mid-August. Measles is a highly contagious but vaccine-preventable infection transmitted mainly among unvaccinated individuals and capable of causing severe outcomes.
Methods: We investigate counterfactual measles control scenarios based on daycare and school closures and reactive vaccination of infants and children, including mixed interventions. We analyze the 2025 Texas outbreak using an age-structured multi-stage SEIR model formulated as a system of ordinary differential equations. The model is fit to case data using Bayesian inference to estimate the effective reproduction number and generate posterior predictive trajectories under …
From Reluctance To Resilience: The Link Between Attitude And Growth Mindset In Calculus Students,
2026
College of Charleston
From Reluctance To Resilience: The Link Between Attitude And Growth Mindset In Calculus Students, Olivia Valente, Kathryn E. Pedings-Behling, Amy N. Langville
Journal of Educational Research and Practice
Many postsecondary students enter general education mathematics courses with negative attitudes, shaping their willingness to engage with the content. This study explores the relationship between students’ attitudes towards mathematics and their growth mindset, revealing effective strategies to enhance learning experiences, particularly for students who are reluctant learners. The research investigates two questions: (1) How do students’ Attitude Toward Mathematics Inventory (ATMI) scores and Growth Mindset Scale (GMS) scores relate? and (2) Do gender or course modality affect this relationship? This study addresses a gap in literature by examining how enjoyment, motivation, self-confidence, and perceived value connect with growth mindset. The …
Algebraic And Topological Methods In Computational Neuroscience,
2026
Florida Atlantic University
Algebraic And Topological Methods In Computational Neuroscience, Trong-Thuc Trang
Electronic Theses and Dissertations 2020 - Present
Neural data is incredibly rich in combinatorial, topological, and geometrical information, reflecting the intricate shape and connectivity of neural firing patterns. To decipher these structures, neuroscience increasingly relies on advanced mathematical tools to analyze neural activity. Here we study (1) neural codes within the poset PCode of neural codes and (2) the connectivity of neural population activity within the insular cortex when responding to interoceptive information. In (1), we establish combinatorial constructions for all upward covering relations based on what we call “isolated subsets” with supporting theorems and give a slight modification of the existing downward covering relations. We …
Applications Of Machine Learning To Gas Plume Analysis In Longwave Infrared Hyperspectral Images,
2026
Utah State University
Applications Of Machine Learning To Gas Plume Analysis In Longwave Infrared Hyperspectral Images, Scout C. Jarman
All Graduate Theses and Dissertations, Fall 2023 to Present
Each pixel from a hyperspectral camera measures the intensity of light over a continuous range of wavelengths, which is in contrast to traditional color cameras, which just measure the intensity of red, green, and blue wavelengths of light. Longwave infrared hyperspectral images can be used to detect gases from a distance by measuring how different materials emit and absorb heat. This makes them useful for applications such as monitoring industrial emissions or locating hazardous gas leaks. In practice, however, gas signatures in these hyperspectral images are often weak and easily obscured by variations in the background scene, making reliable identification …
Spatial Prediction Under Uncertainty: Methodological And Computational Advances In Bayesian Maximum Entropy,
2026
Utah State University
Spatial Prediction Under Uncertainty: Methodological And Computational Advances In Bayesian Maximum Entropy, Kinspride K. Duah
All Graduate Theses and Dissertations, Fall 2023 to Present
Environmental decisions such as infrastructure design, water management, and snow load estimation depend on spatial data that are often incomplete or uncertain. In many cases, measurements are not exact values but ranges, reflecting limitations in data collection methods. Traditional mapping techniques typically simplify these uncertain measurements, which can lead to less accurate predictions. This dissertation introduces improved statistical tools for making spatial predictions when data are uncertain or partially known. By utilizing a framework called Bayesian Maximum Entropy (BME), this research demonstrates how exact measurements and range-based data can be combined in a mathematically consistent way. The work demonstrates that …
Positive Curvature And Discrete Abelian Symmetry,
2026
Syracuse University
Positive Curvature And Discrete Abelian Symmetry, Lee Kennard, Elahe Khalili Samani, Catherine Searle
Mathematics
By replacing the torus with an elementary abelian two-group, we generalize Grove and Searle’s maximal symmetry result and Wilking’s half-maximal symmetry result for positively curved manifolds with an isometric torus action. © The Author(s) 2026.
A Stabilized Weighted Interior Penalty Method For Thermal Convection Model In Heterogeneous Porous Media,
2026
Missouri University of Science and Technology
A Stabilized Weighted Interior Penalty Method For Thermal Convection Model In Heterogeneous Porous Media, Yuanyuan Hou, Qianqian Ding, Xiaoming He, Yanping Lin
Mathematics and Statistics Faculty Research & Creative Works
In this article, we propose and analyze a stabilized weighted interior penalty method for solving the thermal convection problems in heterogeneous porous media. We first transform the thermal convection model into the pressure primal form with homogeneous Neumann boundary condition and develop a symmetric weighted interior penalty method to handle the discontinuous Darcy number and automatically adjust the penalty coefficient corresponding to the varying permeability. Then we recover the velocity by a stabilized method and incorporate it into the energy equation to obtain the temperature. The stability and convergence rates of the numerical solutions are rigorously proved and verified by …
Learning Latent Structure In High-Dimensional Data Via Geometry And Graphs,
2026
Utah State University
Learning Latent Structure In High-Dimensional Data Via Geometry And Graphs, Haozhe Chen
All Graduate Theses and Dissertations, Fall 2023 to Present
Modern datasets often contain many measured variables for each observation, such as gene-expression levels, brain activity signals, or features in tabular data. These data are also often noisy, meaning that useful patterns are mixed with measurement error or irrelevant variation. Although such datasets can appear complex, they are frequently represented by simpler hidden structures, such as trajectories, clusters, or relationships between observations. This dissertation develops methods for uncovering these hidden structures by learning geometric and graph-based representations directly from data. The first part introduces Functional Information Geometry, which represents local patterns in high-dimensional data using functional features and constructs a …
Fixed Points For Fitted Lines,
2026
Rochester Institute of Technology
Fixed Points For Fitted Lines, David L. Farnsworth
Articles
For many fitting methods for lines in the plane, each observation possesses an associated point in the plane, or at infinity for particular observations. These associated points are called “fixed points,” because properly chosen replacement points for the originally selected observation create other fitted lines that contain the same fixed point. Simple linear regression and orthogonal least-squares regression are investigated as examples. The phenomenon has been previously noted for simple regression, where the properly selected replacement points are related to regression diagnostics and the determination of outliers. Orthogonal regression lines are fundamental to principal component analysis. Mechanical devices for simple …
Some Results About Orthogonal Least-Squares Lines,
2026
Monroe Community College
Some Results About Orthogonal Least-Squares Lines, Steven J. Kilner, David L. Farnsworth
Articles
A set of quantitative bivariate data is augmented with one additional point. Orthogonal least-squares fitting is used for the original set and the augmented set. The possible locations of the two lines, the points of means of the two sets, and the augmenting point are examined.
Ramsey Chains In Graphs,
2026
Western Michigan University
Ramsey Chains In Graphs, Ritabrato Chatterjee
Dissertations
The research in this work deals with decomposition of graphs and Ramsey theory, two popular areas of research in graph theory due to numerous fascinating problems and the sheer mathematical beauty of the subjects. A decomposition {G1, G2, ..., Gk} of a graph G into subgraphs of G is ascending if the subgraph Gi is isomorphic to a proper subgraph of Gi+1 for i = 1, 2, ..., k − 1. The well-known and long-standing of Ascending Subgraph Decomposition Conjecture states that every graph has an ascending subgraph …
Unifying And Expanding Global And Local Variable Importance Methods For Explainable Machine Learning,
2026
Utah State University
Unifying And Expanding Global And Local Variable Importance Methods For Explainable Machine Learning, Kelvyn K. Bladen
All Graduate Theses and Dissertations, Fall 2023 to Present
Machine learning methods are powerful analytical tools used across all scientific disciplines and many other fields of investigation for prediction and inference from diverse data sources. Despite their broad applicability, machine learning methods are often highly complex and difficult to interpret. Developing a greater understanding of which variables most influence a response is essential for increasing the interpretability of these models and supporting informed decision-making. This research focuses on improving how we evaluate the importance of these variables.
One common approach is to shuffle the values of a variable and see how much the model accuracy gets worse. Another approach …
Mapler: An R Package For Estimating The Impact Of Climate Change On Maple Syrup Production,
2026
Utah State University
Mapler: An R Package For Estimating The Impact Of Climate Change On Maple Syrup Production, Matthew T. White
All Graduate Theses and Dissertations, Fall 2023 to Present
Successful maple sap tapping depends on the freeze/thaw cycle (i.e., temperatures fluctuating above/below freezing) during the winter and spring. Climate change threatens to alter the timing and duration of the tapping season. This necessitates research into how maple sap tapping will be impacted by climate change in order to help maple syrup producers prepare for the future. We define a sap day as a day where the freeze/thaw cycle occurred. Using information climate scientists use to predict future temperatures, we calculate how many sap days could occur each year. We develop software to analyze these sap day calculations to determine …
