Physical Sciences and Mathematics Commons^™

Applying Machine Learning Methods To Generate Understandings Of Differential Item Functioning In A Flu Knowledge Assessment, William L. Romine, Tanvi Banerjee, Derrick Cox

Computer Science and Engineering Faculty Publications

Current influenza trends, including the severity of the 2025 flu season and the prevalence of H5 bird flu in livestock, necessitate efforts to better understand how to educate students about its transmission. Although validated assessments of influenza knowledge exist, these have not been evaluated for affective and demographic biases. We explore differential item functioning (DIF) effects in four items focused on specific aspects of flu transmission derived from a validated influenza knowledge assessment. In doing so, we introduce and utilize a machine learning framework for exploration of DIF which offers greater flexibility than traditional statistical approaches in terms of studying …

Extraction Of Patient Subtypes Using Llm Generated Knowledge Graphs Integrated With A Transformer Architecture, Benjamin Holmes, Cogan Shimizu

Computer Science and Engineering Faculty Publications

Extracting patient subpopulations (clinically relevant cohorts of individuals who share overlapping symptoms, risk factors, or diagnostic criteria) from unstructured medical notes is an ongoing challenge due to the variability of clinical language and the complex nature of patient conditions. We demonstrate a pipeline that combines named entity recognition (NER), transformer embeddings, guided dimensionality reduction, and LLM-mediated knowledge graph integration to enhance patient extraction. The approach begins with NER using the UMLS metathesaurus [1] to extract clinical terms, followed by transformation into vector embeddings using a biomedical transformer. These embeddings are augmented with structured knowledge graph representations generated through an LLM-driven …

Ontology-Based Data Organization For The Enslaved.Org Project, Cogan Shimizu, Pascal Hitzler

Computer Science and Engineering Faculty Publications

The men, women, and children forced into slavery in the Atlantic world came from diverse African societies with long histories of political, economic, and cultural development. They were taken from the trading centers of the Hausa city-states, the farming and artisanal communities of Senegambia, the Kongo and Mbundu polities of West Central Africa, and many other regions. They carried with them agricultural expertise, metallurgical skills, medical knowledge, religious traditions, and oral histories that helped sustain communities in the face of displacement and enslavement.Enslavement did not erase this intellectual and cultural inheritance, nor did it render its victims passive numbers in …

Ontology Population Using Llms, Sanaz Saki Norouzi, Adrita Barua, Antrea Christou, Nikita Gautam, Andrew Eells, Pascal Hitzler, Cogan Shimizu

Computer Science and Engineering Faculty Publications

No abstract provided.

Usf St. Petersburg Campus Water Refill Station Inventory Appendix A, Haley Mcgehee, Carolyn Mazur, Mohammad Shafayet H. Khan, Theresa G. Burress

Student Green Energy Fund (SGEF) Water Refill Stations

Appendix supporting University of South Florida St. Petersburg Campus Water Refill Station dataset with reference images by location.

Usf St. Petersburg Campus Water Refill Station Inventory, Haley Mcgehee, Carolyn Mazur, Mohammad Shafeyet H. Khan, Theresa G. Burress

Student Green Energy Fund (SGEF) Water Refill Stations

Data inventory of University of South Florida St. Petersburg Campus water refill stations, accounting for presence of Elkay water refill stations, ticker numbers for bottles saved by its use, location descriptors, etc.

Usf St. Petersburg Campus Water Refill Station Inventory Readme, Carolyn Mazur, Theresa G. Burress

Student Green Energy Fund (SGEF) Water Refill Stations

ReadMe file supporting the University of South Florida St. Petersburg Campus Water Refill Station dataset.

Knörr Lattices For Elementary Abelian Groups Over Unramified Extensions Of Z_P, Marie Swartz

Graduate Research Theses & Dissertations

In this dissertation, we examine the existence of positive height Knörr RD-lattices for D an elementary abelian p-group and R an unramified extension of the p-adics Zp. Knörr lattices form an important subclass of the absolutely indecomposable lattices and have close connections to modular representation theory’s “local to global” behavior. We generalize many prior results, shown only when p = 2, to odd p when |D| = p3. Further, when p = 3, we show that a positive height Knörr RD lattice must have a projective summand when restricted to any maximal subgroup of D. The proof of this requires …

Applications Of Bayesian Functional Data Analysis, Zhexuan Yang

Graduate Research Theses & Dissertations

Functional Data Analysis (FDA) is a statistical approach used to analyze data that vary across a domain, such as curves or functions. This dissertation investigates Bayesian Functional Data Analysis (BFDA) through three applications. First, we explore the use of BFDA in outcome-dependent follow-up (ODFL) studies. After conducting simulation studies, we apply our model to cardiotoxicity and kidney function data. Second, we extend BFDA to genetic data by modeling DNA methylation levels with a three-parameter skew-normal distribution and an alpha-skew generalized normal distribution. This study also introduces a novel Multistage Markov Chain Monte Carlo (MMCMC) method with the goal of identifying …

Covariance Matrix Forecasting Of Equity Portfolios, Michael Nebor

Graduate Research Theses & Dissertations

This dissertation consists of two papers. The first paper introduces DCC-SVR, a hybrid Dynamic Conditional Correlation (DCC) and Support Vector Regression (SVR) method of forecasting the covariance matrix. This paper shows that DCC-SVR is able to outperform the traditional methods of DCC and rolling historical on multiple data sets. Performance is shown for both standard GARCH and GJR-GARCH methods. This paper also analyzes performance when dimensions are increased to 49 dimensions and when an application using equal weighted portfolio allocation is used.

The second paper introduces a covariance matrix forecasting method based on copula-GARCH simulated returns. The accuracy of this …

Water Quality And Microplastic Contamination In An Urbanizing City Nakhon Pathom, Thailand, Boonyarak Chuanchit

Graduate Research Theses & Dissertations

Microplastics (MPs) are synthetic polymer particles less than 5 mm in size that originate from both primary manufacturing and the breakdown of larger plastics. Extensive studies have examined their occurrence in other environments, while little is known about their presence and behavior in groundwater, especially in urbanizing regions in Southeast Asia. This study investigates the occurrence and abundance of microplastics within groundwater systems of Nakhon Pathom, an urbanizing province in central Thailand.

Groundwater was collected representing shallow and deep aquifers between May 2023 and May 2025. The analyses included physical-chemical parameters, major ions, heavy metals, and microplastic abundance and composition. …

Geometric Function Theory On Uniformly Quasiconformally Homogeneous Domains, Allyson Mackenzie Hahn

Graduate Research Theses & Dissertations

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Uniformly quasiconformally homogeneous domains in $\mathbb{R}^n$ carry a transitive collection of $K$-quasiconformal maps for a fixed $K\geq 1.$ In this dissertation we investigate three questions in this setting. The first is to show that quasiconformality and quasisymmetry with respect to the quasihyperbolic metric are equivalent. The second is to study normal quasiregular maps from such a domain into $S^n$ or $\mathbb{R}^n$ and determine they hold geometric properties such as a uniform Hölder condition. The third is to study preimages of a power-type mapping and show they are well-distributed in a precise sense.

Efficient Algorithms For Nearest Correlation Matrix Computation With Missing Data, Ibrahim Eniola Oyeyinka

Graduate Research Theses & Dissertations

This thesis investigates efficient algorithms for computing the Nearest Correlation Matrix (NCM) under incomplete financial data. Correlation matrices are vital in portfolio optimization and risk management, yet empirical estimates often violate symmetry, positive semidefiniteness, and unit diagonal conditions due to missing observations. Two projection-based methods are analyzed: the Modified Alternating Projections (MAP) and Anderson Acceleration (AA). Theoretical analysis using convex optimization and normal cone characterization supports numerical evaluation on synthetic and real-world stock-return matrices (550×550, 2020–2025). Missing data are modeled through Missing Completely at Random (MCAR) and Not Missing at Random (NMAR) mechanisms. The results show that AA converges faster …

Deep Underground Neutrino Experiment Data Caching With Frontier, Alexander Rahe

Graduate Research Theses & Dissertations

The Deep Underground Neutrino Experiment (DUNE) is an unprecedented long baseline neutrino experiment that aims to measure various neutrino mixing parameters. With state-of-the-art technology, DUNE will measure neutrino mixing angles (θ13, θ12, θ23) and a Charge-Parity (CP) violating phase (δcp) with precision and will determine the elusive mass ordering. In order to accomplish these goals, scientists all over the world must have quick and reliable access to the data provided by the DUNE detectors. The data caching system known as Frontier is a distributed database caching system that was previously used in other large particle physics experiments for this purpose. …

Bytes, Banter, And The Bible: An Interdisciplinary Account Of Objective Meaning, Cameron Bonin

Senior Honors Theses

The claim that the Bible has objective meaning is contested in a postmodern world. This claim can be more persuasively defended when it is addressed by insights from multiple disciplines. In particular, the field of computer science is apt to illuminate the concept of meaning through its reflection on the nature of languages and its concern with the accurate transmission of information. By synthesizing insights from the field of computer science, such as that of Claude Shannon, with Nicholas Wolterstorff’s use of speech-act theory, the concept of meaning can be understood more clearly. Consequently, this synthesis assists in answering questions …

Chemoproteomic Profiling Of A Carbon-Stabilized Gold(Iii) Macrocycle Reveals Cellular Engagement With Hmox2, Sailajah Gukathasan, Chibuzor Ngozi Olelewe, Libby Ratliff, Jong H. Kim, Alyson M. Ackerman, J. Robert Mccorkle, Sean Parkin, Gunnar F. Kwakye, Jill M. Kolesar, Samuel G. Awuah

Chemistry Faculty Publications

In this work, we discovered a novel organometallic gold(III) macrocycle, Au-Mac1, that demonstrates anticancer potency in a panel of triple-negative breast cancer cells (TNBC), and based on this complex, a biotinylated-Au-Mac1 probe was designed for target identification via chemoproteomics, which uncovered the engagement of HMOX2 of the heme-energy metabolism pathway. Using orthogonal chemical biology and molecular biology approaches, including immunoblotting, flow cytometry, and cellular thermal shift assays, it was confirmed that Au-Mac1 engages HMOX2 in cells. Downstream effects of Au-Mac1 on the depletion of mitochondrial membrane proteins and bioenergetics point to the potential role of HMOX2 in cancer. Importantly, Au-Mac1 …

Electrochemical Observation And Ph Dependence Of All Three Expected Redox Couples In An Extremophilic Bifurcating Electron Transfer Flavoprotein With Fused Subunits, Debarati Das, Wassim El Housseini, Monica Brachi, Shelley D. Minteer, Anne-Frances Miller

Chemistry Faculty Publications

Bifurcating enzymes employ energy from a favorable electron transfer to drive unfavorable transfer of a second electron, thereby generating a more reactive product. They are therefore highly desirable in catalytic systems, for example, to drive challenging reactions such as nitrogen fixation. While most bifurcating enzymes contain air-sensitive metal centers, bifurcating electron transfer flavoproteins (bETFs) employ flavins. However, they have not been successfully deployed on electrodes. Herein, we demonstrate immobilization and expected thermodynamic reactivity of a bETF from a hyperthermophilic archaeon, Sulfolobus acidocaldarius (SaETF). SaETF differs from previously biochemically characterized bETFs in being a single protein, representing a …

Functional Utility Of Gold Complexes With Phosphorus Donor Ligands In Biological Systems, Adedamola S. Arojojoye, Samuel G. Awuah

Chemistry Faculty Publications

Metallo-phosphines are ubiquitous in organometallic chemistry with widespread applications as catalysts in various chemical transformations, precursors for organic electronics, and chemotherapeutic agents or chemical probes. Here, we provide a comprehensive review of the exploration of the current biological applications of Au complexes bearing phosphine donor ligands. The goal is to deepen our understanding of the synthetic utility and reactivity of Au-phosphine complexes to provide insights that could lead to the design of new molecules and enhance the cross-application or repurposing of these complexes.

Estimating The Gender Wage Gap: A Comparative Analysis Of Different Estimators, Xinran Zhang

Mathematics, Statistics, and Computer Science Honors Projects

The gender wage gap between males and females has been well studied by labor economists. We take a multi-prong approach to evaluate three estimators —a regression-imputation estimator, a weighting estimator, and a doubly robust estimator—in estimating the gender wage gap. Using the Panel Study of Income Dynamics, we conduct an empirical study of the estimators’ performances. In a simulation study, we evaluate the properties of estimators and study whether bootstrapping is an appropriate measure of the uncertainty of each estimator. The findings show that while the estimators provide different results, the doubly robust estimator provides reliable and consistent results under …

Exploring Physics Teacher Identity: Pathways Toward Equitable Instruction Among Teachers, Clausell Mathis, Jomo Mutegi, Turhan Carroll, Maya Patel, Andrea Wooley

Teaching & Learning Faculty Publications

Physics teacher identity encompasses teachers' beliefs and views toward being a physics teacher. Physics teacher identity is influenced by teachers' perspectives on physics teaching and learning. Previous studies on teacher identity in general suggest that the construct is complex and malleable. Studies further suggest that it influences instructional methods, student engagement, and classroom environment. However, within physics education, there has yet to be an examination of how physics teacher identity influences "equitable" teaching approaches. This qualitative study sought to identify various dimensions of physics teacher identity and its implications for physics education research. We interviewed secondary and postsecondary physics teachers …

Plasma And Magnetic Coil Optimization, William Lee Austin, Lachlan Dean

Undergraduate Theses, Professional Papers, and Capstone Artifacts

Lachlan Dean Coil Optimization for a High-Beta Stellarator-Tokamak Hybrid Magnetic coil configurations are developed for a tokamak-stellarator hybrid that is stable to both pressure- and current-driven modes for high values of beta. Previous work on this configuration [A. S. Ware, et al., Phys. Rev. Lett, 89, 125003 (2002)] was carried out using a fixed-boundary equilibrium (i.e., with no set of external coils) and prior attempts to develop an initial coil set using the COILOPT code were not successful. In this work, the recently developed SIMSOPT code [M. Landreman, et. al., J. Open Source Software 6, 3525 (2021)] is used to …

Application Of Large Language Model Methods In Scientific And Technical Intelligence Practice, Bolin Hua, Yingze Wang

Journal of Scientific Information Research

[Purpose/significance]With the strong ability to process large-scale datasets and outstanding performance in various natural language processing tasks, large language models (LLMs) have excelled across multiple industries.Since scientific and technical intelligence primarily relies on textual data, LLMs are naturally well-suited for this field, ushering in a new wave of transformative changes. [Method /process]This article discusses the advantages of LLMs from five perspectives: low-dimensional dense vector representations of text, large-scale pre-trained models,fine-tuning and prompt learning, high-quality large-scale training data, and human alignment techniques. [Result/conclusion]LLMs have extensive applications in tasks such as intelligence identification, intelligence tracking, intelligence evaluation, and intelligence prediction, resulting in …

The Math Mind Measures: A User Guide, H. Colleen Sinclair, Stacey R. Terrio, Youn Kyoung Kim

Reports

The development of the Math Mind Measures survey originated from a research-practitioner partnership (RPP) project funded by The Gates Foundation (namely the R+D Partnership for Math Equity). As a part of the project, our team wanted to understand what contributes to math motivation in students. Unfortunately, when looking for instruments to assess motivation we could find little consensus on which motivational factor(s) mattered most and how to measure them.

Long forms: Consequently, we integrated and strengthened existing measures – where available – of 10 different motivational variables, developing a pool of 138 items. We call this collection of items the …

Identifying Intangible And Biocultural Heritage Elements Toward Environmental Understanding: Engaging Stakeholders Through Art, Martha B. Lerski

Publications and Research

Grounded in a case study in Barbuda in the Caribbean, this research examines sustainability from the perspective of what arts and heritage can contribute to community engagement and local and broader understandings about the environment. This article documents a growing body of literature recognizing the role of arts and culture, including local knowledge and traditional ecological knowledge (TEK), in climate change endeavors. Art and TEK present expansive world views. Contextual information situates research done on the island of Barbuda pre- and post-Hurricane Irma. Visual arts workshops engaged community members in mixed methods research. Results documented cultural elements, particularly intangible and …

Raw Data For Tailoring High Entropy Borides For Hydrogenation: The Influence Of Crystal Morphology And The Exploration Of Catalytic Pathways, Michael Yeung, Ting Wang

Chemistry Department Faculty Scholarship

The high entropy boride (HEB) Al0.2Nb0.2Pt0.2Ta0.2Ti0.2B2, with its unique crystal structure and high coordination (platinum coordinated to 12 borons), has been shown in our previous work to exhibit exceptional catalytic properties, especially in sulfur-rich environments, where traditional platinum catalysts would succumb to sulfur-poisoning. In this work, we investigate the mechanism of the HEB catalyst, first by comparing the synthesis by flux growth, as previously reported, to an arc melted preparation. It is evident that the aluminum flux growth synthesis encourages the growth of single crystals, with clear and defined crystal facets, whereas the arc melted sample results in poorly defined …

Raw Data For A Mild Alkaline Hydrothermal Etchant For Mbene Exfoliation, Michael Yeung

Chemistry Department Faculty Scholarship

Abstract for data:

Raw data for the journal publication, A Mild Alkaline Hydrothermal Ethant for MBene Exfoliation. ReadMe file provided.

Abstract for journal publication:

MoBene (the boride equivalent of MXenes) has been a synthetic challenge because borides degrade in common etching media. Inspired by the intercalation of lithium ions into AlOOH, we hypothesized that a hydrothermal route enables lithium ions to intercalate the aluminum layer of MoAlB and further separate the MoB sheet apart. Here, MoBene is first synthesized through a mild hydrothermal etching method with dilute lithium hydroxide. X-ray diffraction showed a peak at 8.9°, confirming an exfoliated layered …

Digital Infrastructure Development Through Digital Infrastructuring Work: An Institutional Work Perspective, Adrian Yeow, Wee-Kiat Lim, Samer Faraj

CCX Research

Being able to understand and characterize the digital infrastructure development (DID) process has become even more pressing today due to the rapid advent and implementation of new digital infrastructure (DI) in organizations as well as since the COVID-19 crisis. While information systems (IS) research has begun to recognize the institutional nature of such digital infrastructures, there remains a gap in our understanding of how such developments unfold from an institutional perspective. Through our field study of a digital infrastructure development project involving the implementation of an enterprise-wide electronic medical record system at a large US medical facility, we show how …

Why Ai Monitoring Faces Resistance And What Healthcare Organizations Can Do About It: An Emotion-Based Perspective, Karl Werder, Lan Cao, Eun Hee Park, Balasubramaniam Ramesh

Information Technology & Decision Sciences Faculty Publications

Continuous monitoring of patients' health facilitated by artificial intelligence (AI) has enhanced the quality of health care, that is, the ability to access effective care. However, AI monitoring often encounters resistance to adoption by decision makers. Healthcare organizations frequently assume that the resistance stems from patients' rational evaluation of the technology's costs and benefits. Recent research challenges this assumption and suggests that the resistance to AI monitoring is influenced by the emotional experiences of patients and their surrogate decision makers. We develop a framework from an emotional perspective, provide important implications for healthcare organizations, and offer recommendations to help reduce …

Dataset For "The Role Of Metacognition And Confidence In Quantitative Reasoning In College Biology Courses", Joseph Dauer, Anum Khushal, Brian A. Couch, Robert L. Mayes, Kent Rittschof

School of Natural Resources: Faculty Publications

Quantitative modelling is a fundamental skill for biology students with performance determined by a host of cognitive and metacognitive resources and requiring instructors to integrate key quantitative dimensions into teaching biology. Using an assessment of quantitative modelling in biology, we explored biology students’ (n = 930 higher education students) modelling practices (i.e., abilities to create, test, revise), metacognition about the nature of models and confidence in their capabilities to model. Students performed best on items related to understanding variables used in models and performed more poorly on items related to interpreting, creating, and using models to understand biological phenomena. …

Toward Biocompatible Assessment Of N-15 Hyperpolarized Metronidazole For Hypoxia Sensing, Faisal Asif

Wayne State University Theses

Recent advances in hyperpolarization, particularly Signal Amplification by Reversible Exchange (SABRE), have enhanced molecular magnetic resonance imaging (MRI) for in vivo applications. This study investigates [15N3]metronidazole, a tri-nitrogen-labeled derivative of an FDA-approved antibiotic, as a hypoxia-sensitive imaging agent. Under hypoxic conditions, the nitroimidazole group undergoes stepwise reduction to an amino group, inducing significant 15N chemical shift changes (30–600 ppm). We aim to develop an iridium catalyst-free, biocompatible hyperpolarized (HP) [15N3]metronidazole formulation exhibiting robust polarization (up to 15%) and extended T1 lifetimes (~10 min). Three specific objectives guide this work: (1) formulation of a HP injectable with enhanced 15N detection, (2) …