Mathematics Commons^™

Modeling The Clonal Rosette Composition Of A Bromeliaceae Genet: A Combinatorial Approach, Layla K. Lammers, Erin N. Bodine

Spora: A Journal of Biomathematics

Bromeliaceae, a neo-tropical plant family encompassing over 3,000 species, exhibit two modes of reproduction: sexual reproduction via flowers and seeds, and asexual reproduction via genetically identical clonal rosettes. The vegetative bodies of bromeliads form rosettes with new leaves emerging from the center and clonal rosettes emerging above a single leaf in the rosette, resulting in a genetic individual consisting of a seed-grown rosette and multiple iterations of clonal rosettes. This research develops a combinatorial model of probability that a single genetic individual will include at least n clonal rosettes when a single rosette can produce at most 1 or 2 …

Principal Leadership As A Predictor Of Teacher Performance: Evidence From An Indonesian Elementary School, Irminapinem Pinem, Antonius Remigius Abi, Hamela Sari Sitompul

Jurnal Pendidikan Sains

Teacher performance is a critical determinant of educational quality and student achievement, making the identification of factors that influence teacher effectiveness an important area of educational research. Among these factors, principal leadership has been recognized as a key organizational variable that shapes teachers’ professional practices and instructional performance. This study aimed to examine the relationship between principal leadership and teacher performance at State Elementary School Raya Kahean, Simalungun Regency, Indonesia. The study employed a quantitative correlational research design involving 52 teachers selected through total sampling. Data were collected using two structured questionnaires measuring principal leadership and teacher performance. The principal …

Comparing The Effects Of Project-Based Learning, Inquiry Learning, And Conventional Instruction On Students' Learning Motivation In Biology, Yeyen Angraini, Irwandi Irwandi, Jayanti Syahfitri

Jurnal Pendidikan Sains

Learning motivation is an important factor influencing students’ engagement, persistence, and success in Biology learning. However, classroom instruction at the senior high school level is often dominated by teacher-centered approaches, which may limit students’ active participation and motivational development. This study aimed to compare students’ learning motivation across Project-Based Learning (PjBL), Inquiry Learning, and conventional instructional approaches in Biology learning. The study employed a quantitative quasi-experimental design with a pretest–posttest approach involving three groups. Participants consisted of 85 Grade XI students from SMA Negeri 1 Talang Padang, South Sumatra, distributed across three classes: PjBL (n = 28), Inquiry (n = …

The Effect Of Project-Based Learning Model On Entrepreneurship (Pjbl-E) With A Deep Learning Approach On Students' Problem-Solving And Cognitive Skills, Ricce Oktasari, Irwandi Irwandi, Siti Darwa Suryani

Jurnal Pendidikan Sains

This study aims to examine the effect of the Entrepreneurship-based Project Based Learning (PjBL-E) model integrated with a pedagogical Deep Learning approach on students’ problem-solving skills and cognitive learning outcomes in biology learning. The novelty of this study lies in the integration of entrepreneurship values and pedagogical deep learning principles into Project Based Learning to create contextual and meaningful learning experiences. Entrepreneurship integration encourages students to develop innovative products, identify real-world problems, and apply biological concepts in practical and socio-economic contexts. Meanwhile, the pedagogical Deep Learning approach promotes reflective thinking, conceptual understanding, critical analysis, and the ability to connect theory …

Student Worksheets Based On The Local Wisdom Of Besilek Serawai For Sixth-Grade Elementary Science Learning, Mice Agustin, Tomi Hidayat, Irwandi Irwandi

Jurnal Pendidikan Sains

This study aims to develop a Student Worksheet (Lembar Kerja Peserta Didik [LKPD]) based on the local wisdom of Besilek Serawai for sixth-grade elementary science education and to evaluate its validity. The study employed the ADDIE development model, consisting of five stages: Analyze, Design, Develop, Implement, and Evaluate. The developed LKPD integrates Besilek Serawai, a traditional martial art of the Seluma community, with the concept of the human locomotor system in science instruction. The worksheet was validated by two subject-matter experts and two media experts. Material validation yielded an average score of 4.26, equivalent to a validity percentage of 85.2%, …

Cardiovascular Disease Subtypes And Alzheimer's Disease: Phenotypic And Genetic Associations In The Uk Biobank And All Of Us Research Program, Aili Toyli, Chen Zhao, Kuan Jui Su, Hui Shen, Hong Wen Deng, Qing Hui Chen, Qiuying Sha, Weihua Zhou

Michigan Tech Publications

BACKGROUND: Cardiovascular disease (CVD) and Alzheimer's disease (AD) are major public health concerns that share overlapping risk factors and potential mechanistic pathways. Although vascular contributions to cognitive decline are well documented, the specific relationships between AD and different CVD subtypes remain poorly understood. METHODS: In this cross-sectional study, we examined associations between AD and 11 CVD subtypes using logistic regression models in 2 large biobanks: the UK Biobank (n=502 133) and the All of Us Research Program (n=287 011). Models were adjusted for demographic, lifestyle, and clinical covariates. We also explored genetic overlap between AD and CVD traits through proximity-based …

Beyond The Best Fit: Fitting Sir-Style Models To Data While Prioritizing Biological Meaning, Meredith L. Greer

CODEE Journal

Many students find comfort in mathematics because math classes have been a place where they can find the “right answer” to exercises. Modeling courses typically emphasize more nuance, teaching students to try modeling approaches, compare back with real-world mechanisms and data, and then refine their models, in an ongoing cycle. One topic, however, can cause students to quickly revert into “right answer” mode: fitting a model to data. Phrases such as best fit and minimize the distance suggest there is one optimal solution that can be determined by an algorithm, and these algorithms typically have no relationship to the biology …

Computational Insights Into Nucleosome Dynamics In Epigenetics Using Molecular Dynamics Simulations, Rutika Patel

Dissertations, Theses, and Capstone Projects

Nucleosome core particles (NCP) are the building blocks that form a highly organized and compact chromatin structure. Nucleosomes package DNA in the nucleus of eukaryotic cells. The NCP consists of about 147 base pairs of DNA wrapped around the histone octamer, with 1.65 superhelical turns in a left-handed manner. The histone octamer is composed of two copies of H3, H4, H2A, and H2B. Together with histone H1 and linker DNA, they further assemble into a higher-order chromatin structure. The nucleosome complex is stabilized by electrostatic interactions between positively charged histone residues and the negatively charged DNA backbone. To effectively access …

Identifying Textual Predictors Of Early Termination In Clinical Trials In Medicine: An Explainable Machine-Learning Study, Rohan Ramnarain

Dissertations, Theses, and Capstone Projects

About one in five clinical trials in medicine ends early, wasting valuable resources and reducing the evidence available for developing life-saving medical treatments. This project uses a method called Trial2Vec, which is a self-supervised machine-learning method that converts clinical trial documents into dense numerical representations that capture their key design and clinical characteristics, to turn each proposed clinical trial’s written protocol into a compact numerical profile (a process referred to as embedding). These profiles are then paired with a predictive machine learning models to identify the words and phrases in the trial documents that can signal a higher risk of …

Dynamic Homeostasis In Relaxation And Bursting Oscillations, Christopher J. Ryzowicz

Biology and Medicine Through Mathematics Conference

No abstract provided.

Dynamical Systems Modeling To Determine The Role Of Crosstalk In Shaping Stat Signaling Profiles, Laura F. Strube, Anamarie Martinez, Neha Cheemalavagu, Karsen Shoger, James Faeder, Rachel Gottschalk

Biology and Medicine Through Mathematics Conference

No abstract provided.

Volume 17, Christian O’Neill, Kyara Greene, Savva Sidorov, Laura Bisaillon, Luke Clemmer, Hannah Gordon, Kitt Benson, Taylor Blount, Rachel Danzitz, Nicholas Duellman, Chase Gionis, Hima Fernando, Seth Franzyshen, Onyx Gonzalez, Bryan Lin, Samantha Start, Ysabel Wells, Maggie Duncan

Incite: The Journal of Undergraduate Scholarship

Introduction Dr. Amorette Barber, Director, Office of Student Research

From the Editor Dr. Hannah Dudley-Shotwell

Cover Artist’s Statement Maggie Duncan

On Mentoring Dr. Yulia Uryadova

Ukrainian Resistance in the Face of Russification: Nestor Makhno and Anarchism

by Christian O’Neill

Life Vest by Kyara Greene

Isolation and 16S rRNA Identification of Bacteria from Fire Department Connection Pipe by Savva Sidorov

The Effectiveness of Planned Exercise in Reducing ADHD Symptoms in Children by Laura Bisaillon & Luke Clemmer

Linguistic Analysis on Confidence and Communication Strategies with Disparities Between Sign Fluency and Hearing Impairment by Hannah Gordon

Freedmen in Indian Territory by Kitt …

Tipping Points In Crayfish Management: Exploring Population Dynamics With The Bifurcations Activity In Slopes, Evan Inrig, Benjamin Lucas

Seaver College Research And Scholarly Achievement Symposium

Slopes is an interactive environment for exploring numerical methods and graphical solutions to ordinary differential equations. The app launched with five activities for exploration: slopefields, phase planes, oscillations, solutions to systems, and numerical methods for approximation. Bifurcations is a new sixth activity that we designed to investigate changes in the long term behavior of solutions to autonomous differential equations. This activity displays a slopefield and implements the ability to add solutions, but also introduces two new views that show how varying a single parameter impacts the values and stability of equilibrium solutions. We demonstrate the value of the new bifurcations …

Literature Review Of Local Culture-Based Mathematics E-Module With Islamic Values In Probability, Maya Puspita Sari, Surya Sari Faradiba

Jurnal Pendidikan Sains

This study is grounded in the need to address the limitations of probability learning that is often procedural, decontextualized, and disconnected from students’ cultural and religious values. It aims to develop a comprehensive understanding of how local cultural contexts and Islamic values can be systematically integrated into mathematics e-modules, particularly for probability learning, and to formulate structured design principles and quality indicators for their development. This paper adopts a Systematic Literature Review (SLR) approach by analyzing empirical studies published between 2020 and 2025, using a structured selection process involving identification, screening, eligibility, and inclusion stages. A total of 11 high-quality …

The Effect Of Virtual Laboratories On Students Interest And Learning Outcomes In Spermatophyta At Sma Negeri 1 Sojol, Ismawati Ismawati, Sutrisnawati Sutrisnawati, Manap Trianto, Masrianih Masrianih, Abd Rauf, Musdalifah Nurdin

Jurnal Pendidikan Sains

Limited access to physical laboratory facilities and the abstract nature of Spermatophyta material reduce students’ learning interest and outcomes, necessitating the use of innovative digital learning media such as virtual laboratories. This study aims to analyze the effect of Virtual Laboratory (V-Lab) implementation on students’ learning interest and cognitive learning outcomes in Spermatophyta material at the senior high school level. A quantitative quasi-experimental design with a posttest-only control group was employed involving 66 eleventh-grade students divided into experimental and control classes; data were collected using a learning interest questionnaire and a multiple-choice test, and analyzed using independent samples t-test after …

Evolution As Spatial Projection, Charles H. Smith, Ngoc Nguyen

Faculty/Staff Personal Papers

A theory combining explanations for the nature of three-dimensional systems and evolutionary processes is advanced, set to a geometric simulation, and then discussed in the context of several empirical studies bearing on its validity. The concept “evolution” is first discussed, then related to Baruch de Spinoza’s ideas on natural philosophy, including his concept of the conatus. These ideas are then extended by posing the possible existence of a general form of natural systems subsystemization leading to the extended space condition. A geometrical/topological simulation study projecting spatial relations among subsystem structures interpretable through entropy maximization and multidimensional scaling methods is presented, …

Preferences For Mathematics And Science Education Majors Among Senior High School Students In Bataan, Zydrick L. Avelino

Jurnal Pendidikan Sains

This study examines the factors influencing Senior High School students’ preferences for Bachelor of Secondary Education (BSEd) majors in Bagac and Morong, Bataan, with particular focus on the low interest in Mathematics and Science specializations despite increasing demand for STEM educators. Using a descriptive quantitative design, data were collected from 369 students through a structured survey and analyzed using frequency and percentage distributions. The results reveal a strong preference for non-STEM majors, with Social Studies (42.12%) and English (35.04%) dominating, while Science (15.43%) and Mathematics (7.395%) received significantly lower interest. Personal interest emerged as the primary determinant (58.8%), followed by …

Predicting Tart Cherry Stem Water Potential Using Uav Multispectral Imagery And Environmental Data Via Symbolic Regression, Anderson L. S. Safre, Alfonso Torres-Rua, Kurt Wedegaertner, Brent Black, Brennan Bean, Burdette Barker, Matt Yost

Civil and Environmental Engineering Faculty Publications

Tart cherry is an important fruit crop in Utah, where irrigation is essential due to arid conditions. Precision irrigation requires reliable indicators of plant water status, and stem water potential (Ψ_stem), is among the most sensitive though labor-intensive and spatially limited. This study develops Ψ_stem estimation models using high-resolution multispectral Unmanned Aerial Vehicle (UAV) imagery combined with meteorological and soil moisture data, applying Symbolic Regression (SR). Results show a stronger correlation between optical bands and Ψ_stem during the pre-harvest period. Among 85 vegetation indices, the Red Chromatic Coordinate (RCC) index performed best (R² = 0.67). …

Systematic Synthesis Of Crispr/Cas Applications For Enhancing Salt Tolerance In Crops: A Decade Of Progress And Challenges, Xindi Sun, Fusheng Wu, Zhuanzhuan Ma, Guohao Liang, Shumei Chen, Xutong Hu, Shugao Fan, Ying Zhao

School of Mathematical & Statistical Sciences Faculty Publications

Soil salinity is a major constraint on global crop productivity, driving the need for salt-tolerant varieties. While CRISPR-Cas genome editing offers targeted solutions for trait improvement, significant biological and technical bottlenecks limit its application in conferring salt stress resilience. This systematic summarizes findings from 83 peer-reviewed studies (2015–2024) employing CRISPR/Cas technologies to improve salt tolerance in five major crops (rice, wheat, maize, sorghum, barley). Our systematic review reveals that early single-gene edits achieved modest gains (30–50% Na⁺ exclusion) but often showed limited yield gains in field settings, potentially due to compensatory regulation and environmental variation. The literature suggests that multiplex …

Delaying Cancer Progression By Integrating Toxicity Constraints In A Model Of Adaptive Therapy, Jana L. Gevertz, Harsh Vardhan Jain, Irina Kareva, Kathleen P. Wilkie, Joel Brown, Yitong Pepper Huang, Eduardo Sontag, Vladimir Vinogradov, Mark Davies

Mathematics Sciences: Faculty Publications

Cancer therapies often fail when intolerable toxicity or drug-resistant cancer cells undermine otherwise effective treatment strategies. Over the past decade, adaptive therapy has emerged as a promising approach to postpone emergence of resistance by altering dose timing based on tumor burden thresholds. Despite encouraging results, these protocols often overlook the crucial role of toxicity-induced treatment breaks, which may permit tumor regrowth. Herein, we explore the following question: would incorporating toxicity feedback improve or hinder the efficacy of adaptive therapy? To address this question, we propose a mathematical framework for incorporating toxic feedback into treatment design. We and that the degree …

A Mathematical Frameworks For Singular, Nonlinear Phenomena: Applications To Nematocyst Firing And Inhomogeneous Nls With Coulomb Potential, Abdulrahman Alharbi

Theses and Dissertations

Nematocysts are specialized cellular organelles found in all cnidarians, including corals and jellyfish, as well as in some single-celled protists such as dinoflagellates. These organelles display remarkable diversity in morphology and function, playing roles in prey capture and defense. The firing of a nematocyst is one of the fastest accelerations in nature, yet the underlying physical mechanisms remain not fully understood. In this work, we address key questions: how sufficient force is generated to overcome the fluid boundary layer, whether fluid–structure interaction models can reproduce observed dynamics, and what mechanisms trigger discharge.

Our research investigates models based on osmotic pressure …

Identifying Relevant Covariates In Rna-Seq Analysis By Pseudo-Variable Augmentation, Yet Nguyen, Dan Nettleton

Mathematics & Statistics Faculty Publications

RNA-sequencing (RNA-seq) technology allows for the identification of differentially expressed genes, which are genes whose mean transcript abundance levels vary across conditions. In practice, RNA-seq datasets often include covariates that are of primary interest in addition to a set of covariates that are subject to selection. Some of these covariates may be relevant to gene expression levels, while others may be irrelevant. Ignoring relevant covariates or attempting to adjust for the effect of irrelevant covariates can compromise the identification of differentially expressed genes. To address this issue, we propose a variable selection method that uses pseudo-variables to control the expected …

Integration Of Islamic Values In Mathematics Learning, Ai Mulya, Surya Faradiba

Jurnal Pendidikan Sains

This study aims to identify the integration of Islamic values in mathematics learning and its contribution to student character development. The method used is a systematic literature study by reviewing relevant accredited scientific articles. The results of the study indicate that the integration of Islamic values is carried out through the preparation of Islamic-context-based mathematics problems, linking concepts to verses of the Qur'an and hadith, the application of ethnomathematics with Islamic cultural nuances, and the introduction of Islamic economic concepts. The dominant values that emerge include honesty, responsibility, discipline, justice, and piety. These findings indicate that the integration of Islamic …

Face Value: A Computational Approach To Subjective Impressions Of Faces, Kevin Kpankou

Undergraduate Research Symposium

Various computational models of first impressions have been developed to uncover the mechanisms driving these judgments. However, the implicit notion of a singular ``human'' often overlooks meaningful individual differences in beliefs, attitudes, and associations, as well as culturally grounded group-level constructs. In this paper, we extend Cultural Consensus Theory (CCT) to estimate culturally shared beliefs about faces by incorporating latent constructs structured around interpretable facial features extracted via computer vision algorithms. We apply our model to a large-scale dataset of people’s first impressions of faces. Our approach reveals a robust mapping between facial features and culturally constructed impressions, allowing us …

Wacsaw: An Adaptive, Statistical Method To Classify Movement Into Sleep And Wakefulness States, Austin Vandegriffe, V. A. Samaranayake, Matthew S. Thimgan

Mathematics and Statistics Faculty Research & Creative Works

Wearable actimeters can improve our understanding of sleep in the natural environments. Current algorithms may produce inaccuracies in specific individuals and circumstances, such as quiet wakefulness. New hardware allows data collection at higher frequencies enabling sophisticated analytical methods. We have developed a novel statistical algorithm, the Wasserstein Algorithm for Classifying Sleep and Wakefulness (WACSAW), to identify behavioral states from recordings of everyday movement. WACSAW employs optimal transport techniques to identify segments with differing activity variability. Functions characterizing the segments' movement distributions were clustered into two groups using a k-nearest neighbors and labeled as sleep or wake based on their proximity …

Robustness Of Network Inference Algorithms Under Network Class Misspecification, Roberto Ceja

Electronic Theses, Projects, and Dissertations

Inferring phylogenies in the presence of hybridization remains a difficult problem. As a result, many current methods for reconstructing phylogenetic networks are restricted to a simple class of networks known as level-1. This restriction arises from theoretical considerations rather than empirical evidence, with real data possibly arising from complex networks. In this work, we evaluate the robustness of two level-1 network inference methods, SNaQ and NANUQ+, through a simulation study, when the input data originates from a more complex network. Specifically, we investigate whether these methods can accurately recover important features of the true species network, such as the circular …

A Persistent Homology Framework For Scrna-Seq: Assessing Clustering Robustness And Quantifying Preprocessing And Integration Effects On Topological Features., Jonah Daneshmand

Electronic Theses and Dissertations

As single-cell RNA sequencing (scRNA-seq) data expands, robust methods for integrating diverse datasets are critical. This dissertation applies Persistent Homology (PH), a technique from Topological Data Analysis (TDA), to a collection of scRNA-seq datasets spanning eight tissue types to quantify how data integration affects topological features and biological interpretability. We assessed global topological structure using Betti curves, Euler characteristics, and persistence landscapes across raw, normalized, and integrated data representations. Our analysis revealed a performance inversion: while conventional methods excelled on unintegrated data, high-granularity topological methods, particularly those sensitive to global data structure, became superior after integration. This suggests a synergy …

Comparing Machine Learning, Deep Learning, And Reinforcement Learning Performance In Culex Pipiens Predictive Modeling, Wei Yin, Sanad H. Ragab, Michael G. Tyshenko, Teresa Patricia Feria-Arroyo, Tamer Oraby

School of Mathematical & Statistical Sciences Faculty Publications

Several machine learning (ML) and deep learning (DL) methods have been used to predict the presence of species in classification problems. Another set of methods, called reinforcement learning (RL), has been used in training agents to perform various tasks, but not in predicting species distribution. Culex pipiens (Diptera: Culicidae), commonly known as the common house mosquito, is a globally distributed species prevalent in temperate and subtropical regions. They serve as a primary vector for West Nile Virus (WNV), a mosquito-borne pathogen that affects humans and other animals. The study objective is to compare the performance of logistic regression, random forest …

Modeling Synaptic Dysfunction As Neural Contagion: A Graph-Based Sedr Framework For Simulating Signal Spread, Michelle Marfo, Dr. Padmanabhan Seshaiyer, Alonso Ogueda-Oliva

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Modeling The Probability Of N Clonal Rosettes In A Bromeliaceae Genetic Individual, Erin N. Bodine, Layla K. Lammers

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.