Digital Commons Network^™

Temporal Modeling And Forecasting Of Blood Glucose Dynamics In Individuals With Diabetes Mellitus, Mj Ruff

University Honors Theses

People living with Diabetes Mellitus face significant health risks, including an increased likelihood of heart disease, stroke, and fluctuations in blood glucose levels. The unpredictable nature of glucose levels can lead to dangerous conditions such as ketoacidosis and hypoglycemia. This study employs advanced time series analysis tools to forecast the glucose levels for an individual diagnosed with Type 1 Diabetes Mellitus.

A Proposal To Explore Geometry With Geogebra: Graphical Exploration And Formal Demonstration Of The Collinearity Of The Barycenters Of A Polygon, Saulo Mosquera Lopez, Marlio Paredes, Walter Castro

School of Mathematical & Statistical Sciences Faculty Publications

This paper illustrates an example of a mathematical activity that teachers and students can replicate to create an experience that resembles professional mathematical activity. We extend the property “Consider a triangle ABC, any straight line and let A’, B’, C’ be the reflections of the points A, B, C on the straight line then the barycenters of the triangles ABC, A’BC, AB’C and ABC’ are collinear and the line of collinearity is perpendicular to the straight line” for any quadrilateral. It is proved that there are four additional triangles, for a total of eight, whose barycenters are collinear and that …

Comprehensive Insights Into The Cholesterol-Mediated Modulation Of Membrane Function Through Molecular Dynamics Simulations, Ehsaneh Khodadadi, Ehsan Khodadadi, Parth Chaturvedi, Mahmoud Moradi

Chemistry & Biochemistry Faculty Publications and Presentations

Cholesterol plays an essential role in biological membranes and is crucial for maintaining their stability and functionality. In addition to biological membranes, cholesterol is also used in various synthetic lipid-based structures such as liposomes, proteoliposomes, and nanodiscs. Cholesterol regulates membrane properties by influencing the density of lipids, phase separation into liquid-ordered (Lo) and liquid-disordered (Ld) areas, and stability of protein-membrane interactions. For planar bilayers, cholesterol thickens the membrane, decreases permeability, and brings lipids into well-ordered domains, thereby increasing membrane rigidity by condensing lipid packing, while maintaining lateral lipid mobility in disordered regions to preserve overall membrane fluidity. It modulates membrane …

Refinement And Application Of The Absorption Cross-Section Of Molecular Bromine With Relevance To Atmospheric Chemistry, Callum Flowerday, Ryan Thalman, Jaron C. Hansen, Eric T. Sevy, Jason J. Sorensen, Matthew C. Asplund

ScholarsArchive Data

Defined Br2 XS - is the defined absorption cross-section using the UVvis spectrophotometer.

BBCEAS - This is raw absorption data measured using the BBCEAS (see article for details).

UVvis raw - This is the raw absorption data measured using the UVvis spectrophotometer.

Forecasting Influenza Rates Using Machine Learning: A Study Of Chatgpt's Predictive Accuracy, Sara Saleh

University Honors Theses

This study evaluates ChatGPT's ability to forecast influenza rates, such as the number of flu cases, hospitalizations, and death during peak season periods using CDC data, and comparing forecasts against actual results to calculate statistical accuracy and consistency. Influenza forecasting is essential for public health planning, but traditional methods may not always provide timely or accurate predictions. In this research study, ChatGPT was utilized to predict the influenza rates for the following week based on the previous week's data obtained from the FluView surveillance system. The predicted rates were compared to the actual influenza rates to assess the model's overall …

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 …

Electrochemically-Assisted Low Power Density Laser Writing On Stainless Steel Via Enrichment Of Chromium Oxides, Zechariah J. Pfaffenberger, Lianlian Liu, Tae Kyong John Kim, Vignesh Venkataramani, Lydia Kisley

Faculty Scholarship

Laser color marking produces nearly permanent, environmentally friendly, vibrant colors on surfaces. However, previous work has used high-power-density pulsed lasers to induce the physicochemical reactions for marking. Here, laser color marking on stainless steel 304 (SS304) is performed with a less expensive continuous wave (CW) laser and a power density five orders of magnitude below that previously reported by combining an electrochemical cell with a fluorescence microscope. Using a combination of optical microscopy, x-ray photoelectron spectroscopy, and bulk electrochemistry, it is demonstrated that the laser-induced luminescence and colors are due to enrichment (32 ± 9% increase) of Cr₂O₃ in the …

A Framework For Scalable And Controlled Hallucination Data Collection, Lin Ting Liang

Computer Science Senior Theses

This thesis addresses a key bottleneck in hallucination research: the scarcity and limitations of hallucination benchmark datasets. Existing datasets typically focus on a single type of hallucination and are expensive to produce due to the need for manual prompt creation and annotation. To overcome these challenges, we propose a novel mixture-of-experts (MoE) adversarial framework that actively induces hallucinations. Our framework employs three large language model (LLM) agents that iteratively and adversarially revise prompts to provoke hallucinated responses from a target question-answering model. It automates the generation of both intrinsic hallucinations (logical inconsistencies) and extrinsic hallucinations (inclusion of unverifiable external information). …

Measurements Lab Quiz – Exported As Brightspace Package, Vasiliy Znamenskiy

Open Educational Resources

This Brightspace-ready quiz assesses foundational measurement skills in physics laboratory settings. It includes 16 questions covering key concepts such as random and systematic errors, least counts of measurement tools (micrometer, Vernier caliper, meter stick, graduated cylinder, and triple-beam balance), and data interpretation from physical instruments. The quiz features multiple-choice and numerical answer formats, including visual instrument reading exercises via linked images. Designed for use in college-level introductory physics courses, this package supports automated grading and student feedback within the Brightspace LMS environment.

K-Mshc: Unmasking Minimally Sufficient Head Circuits In Large Language Models With Experiments On Syntactic Classification Tasks, Pratim Chowdhary, Peter Chin, Deepernab Chakrabarty

Computer Science Senior Theses

Understanding which neural components drive specific capabilities in mid-sized language models ($\leq$10B parameters) remains a key challenge. We introduce the $(\bm{K}, \epsilon)$-Minimum Sufficient Head Circuit ($K$-MSHC), a methodology to identify minimal sets of attention heads crucial for classification tasks as well as Search-K-MSHC, an efficient algorithm for discovering these circuits. Applying our Search-K-MSHC algorithm to Gemma-9B, we analyze three syntactic task families: grammar acceptability, arithmetic verification, and arithmetic word problems. Our findings reveal distinct task-specific head circuits, with grammar tasks predominantly utilizing early layers, word problems showing pronounced activity in both shallow and deep regions, and arithmetic verification demonstrating a …

A First Look Into Parental Strategies, And Challenges Around Children’S Device Usage In Urban Nepal, Rizu Paudel, Prakriti Dumaru, Ankit Shrestha, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

There have been substantial changes in the landscape of technology use by children in Global South during COVID-19, when the shift to online learning platforms necessitated parents to avail personal devices (e.g., smartphones, computers) for their children to fulfill their educational needs. However, the use of devices by children are not limited to serving educational purpose only. Our study positions itself in a critical post-pandemic period in Nepal, characterized by the increase in device use by children, while a little study to date, investigated parental mediation in this developing country. To this end, we conducted semi-structured interviews with 20 parents, …

An Approach To Stylometry Using Causal Language Models, Harrison F. Stropkay

Computer Science Senior Theses

We present a novel stylometric approach using large language models. By training separate models on individual authors' works, we find that each model achieves lower cross-entropy loss when predicting text from its training author compared to other authors' texts. Moreover, for any given text, the model trained on its true author’s corpus yields the lowest loss. We suggest that, in this way, a model trained on one author's works embodies the unique writing style of that author. We demonstrate our approach on works by eight known authors. This approach also confirms that R. P. Thompson wrote the well-studied 15th book …

Investigation Into Thermodynamic And Kinetic Phenomena In Arylation Reactions With Diaryliodonium Salts, Soocheta Jha

Dissertations and Theses

Benzenoid rings are fundamental structural motifs in organic chemistry, widely recognized for their prevalence in natural products, pharmaceuticals, agrochemicals, and functional materials. Transition metal-catalyzed arylation, using catalysts such as palladium, nickel, or copper, has revolutionized C-C, C-O, and C-N bond formation, offering broad substrate scope and high efficiency. Among the reagents developed for efficient aryl group transfer, diaryliodonium salts have emerged as particularly powerful tools. Diaryliodonium salts facilitate metal-free arylations across a broad spectrum of nucleophiles, offering high reactivity, operational simplicity and environmental compatibility. The versatility of diaryliodonium salts has led to their widespread adoption as efficient arylating reagent in …

Detecting Physical Activity Using Wearable Sensor Data, Dipok Deb

Data Science and Data Mining

This study focuses on detecting physical activity using wearable sensor data, specifically distinguishing between walking and running. A dataset comprising accelerometer and gyroscope readings is used to train and evaluate various machine learning models, including logistic regression, random forest, k-nearest neighbors, naïve Bayes, and XGBoost. Extensive preprocessing, such as creating lag features and rolling statistics, is performed to enhance temporal data representation. The models are evaluated using metrics like accuracy, precision, recall, and F1 score. Incorporating lag and rolling features significantly improves model performance, with logistic regression achieving perfect scores across all metrics. These findings demonstrate the effectiveness of enhanced …

Artificial Intelligence And Astronomy: Lab Manual For Generative Ai-Based Learning Activities, Vasiliy Znamenskiy

Open Educational Resources

This lab manual introduces community college students to the intersection of artificial intelligence (AI) and astronomy through hands-on, inquiry-based activities. It explores how generative AI platforms—ranging from text-based chat systems to image and video generators—can enhance scientific understanding, creativity, and critical thinking in space science education. Students engage with tools such as ChatGPT, Gemini, DALL·E, and Synthesia to formulate and evaluate astronomy-related questions, generate scientifically inspired visualizations, and produce dynamic representations of cosmic phenomena. Through structured exercises, the manual promotes digital literacy, fosters analytical skills, and illustrates how AI assists in astronomical research, including data analysis, image enhancement, spacecraft autonomy, …

Biomarker-Guided Imaging And Ai-Augmented Diagnosis Of Degenerative Joint Disease, Rahul Kumar, Kyle Sporn, Aryan Borole, Akshay Khanna, Chirag Gowda, Phani Paladugu, Alex Ngo, Ram Jagadeesan, Nasif Zaman, Alireza Tavakkoli

Department of Medicine Faculty Papers

Degenerative joint disease remains a leading cause of global disability, with early diagnosis posing a significant clinical challenge due to its gradual onset and symptom overlap with other musculoskeletal disorders. This review focuses on emerging diagnostic strategies by synthesizing evidence specifically from studies that integrate biochemical biomarkers, advanced imaging techniques, and machine learning models relevant to osteoarthritis. We evaluate the diagnostic utility of cartilage degradation markers (e.g., CTX-II, COMP), inflammatory cytokines (e.g., IL-1β, TNF-α), and synovial fluid microRNA profiles, and how they correlate with quantitative imaging readouts from T2-mapping MRI, ultrasound elastography, and dual-energy CT. Furthermore, we highlight recent developments …

Siliciclastic Cave Or Diamond Mine? Multiapproach Investigation In Igatu Village, Chapada Diamantina, Northeastern Brazil, Raphael Parra, Ricardo G. F. De A. Pereira, Leonardo F. Vieira, Rubson P. Maia

International Journal of Speleology

The territory around Igatu, as that of many villages in southeastern Chapada Diamantina (Bahia, Brazil), was deeply modified by diamond mine activity. Caves were special targets for miners, since they can act as diamond-bearing sediment traps, and the Canal da Fumaça Cave was one of the most important and rich of them. The question that arises is whether the formation is a natural cave or an artificial diamond mine. In order to answer this question, we developed speleological and geological studies with detailed cave surveys, remote sensing and field measurements for structural analysis, optical and electronic microscope for petrographic characterization, …

Arts-Based Sustainability: From New York To Malawi, Martha B. Lerski

Publications and Research

Recognizing that libraries serve multiple constituencies and subject areas, this chapter documents and advocates for development of transdisciplinary arts-based research (ABR) and culture-related projects linked to environmental challenges. Libraries contribute collections and spaces, as well as the research of library and information scientists. Libraries are currently among invisible contributors to sustainability planning and services. The chapter will link this invisibility to the value of what visual arts refer to as negative space elements in subjects ranging from traditional ecological knowledge to environmental science. Library collections, projects, and research contribute to education for sustainable development (ESD) as required to achieve the …

Efficient Signal Synthesis For Data Augmentation Using Generative Ai, Yagna Veera Narayan Kaasaragadda

Theses and Dissertations

Modern signal processing AI applications face increasing demands for diverse training data while operating under computational constraints. State-of-the-art generative models, though effective, often require prohibitive resources, limiting their deployment in real-time or embedded systems. This thesis proposes a computationally efficient framework for synthetic signal generation using a two-stage architecture that combines a Vector Quantized Variational Autoencoder (VQ-VAE) with either a decoder-only transformer or a discrete diffusion model. The VQ-VAE encodes high-dimensional signals into discrete latent tokens, significantly reducing model complexity while enabling symbolic sequence modeling. These discrete representations are then modeled using transformer-based autoregressive models or Score Entropy Discrete Diffusion …

"Opting Out Of Ai”: Exploring Perceptions, Reasons, And Concerns Behind Faculty Resistance To Generative Ai, Aya Shata

Hank Greenspun School of Journalism and Media Studies Faculty Research

Research on Generative Artificial Intelligence (GAI) in higher education primarily focuses on faculty use and experiences, with limited attention given to why some abstain from using it. Drawing from Innovation Resistance Theory, this study aims to address this gap by exploring the perceptions of both faculty users and non-users of GAI, identifying the reasons and concerns why they avoid GAI. A survey of 294 full-time higher education faculty from two mid-size U.S. public universities was conducted. Using qualitative and quantitative analysis, results show that over one-third of the faculty members opted out of using GAI for five primary reasons: not …

Financial Data Stewardship: A Librarian's Approach To Data Discovery And A Call For Coding As A Path To Data Comprehension And Verification, Lip Hwe Tee

Research Collection Library

This conference presentation calls to advocate and emphasise coding as a means to understand datasets, to be able to correctly interpret table structure and relevant fields to extract the correct data, to ensure accuracy and relevance.

Ai Assisted Literature Review Tools For Undergraduates: Restrict, Embrace Or Curate?, Aaron Tay

Research Collection Library

As AI-driven literature review tools become widespread, academic librarians must grapple with a fundamental question—should we ban these tools, selectively curate their use, or embrace them fully? This keynote explores the three competing schools of thought shaping AI’s role in undergraduate literature reviews.

The Restrict school argues that students who have not proven capable of writing quality literature review should be restricted from use of such tools. Much like handing a preschooler a calculator before they understand basic arithmetic will affect the learning of arithmetic, premature use of such tools has the potential to shortcut the research learning process. If …

Ceno: Non-Uniform, Segment And Parallel Zero-Knowledge Virtual Machine, Tianyi Liu, Zhenfei Zhang, Yuncong Zhang, Wenqing Hu, Ye Zhang

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we explore a novel Zero-knowledge Virtual Machine (zkVM) framework leveraging succinct, non-interactive zero-knowledge proofs for verifiable computation over any code. Our approach divides the proof of program execution into two stages. In the first stage, the process breaks down program execution into segments, identifying and grouping identical sections. These segments are then proved through data-parallel circuits that allow for varying amounts of duplication. In the subsequent stage, the verifier examines these segment proofs, reconstructing the program's control and data flow based on the segments' duplication number and the original program. The second stage can be further attested …

Toward Integrated Urban Observatories: Synthesizing Remote And Social Sensing In Urban Science, Danlin Yu

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Urbanization is reshaping landscapes and posing unprecedented sustainability challenges, necessitating more integrative approaches to urban observation. This review synthesizes recent advancements in traditional remote sensing and emerging social sensing technologies, emphasizing their convergence within urban science. A systematic thematic analysis of 667 peer-reviewed articles highlights the methodological progress, practical applications, and theoretical innovations arising from this integration. Traditional remote sensing effectively captures urban physical features but lacks insights into human behaviors. Conversely, social sensing, leveraging digital traces from social media and mobile data, introduces essential human-centered dimensions into urban monitoring. The fusion of these complementary paradigms through advanced data analytics …

Forging The Future, Kenneth Benoit

Asian Management Insights

How AI is rewriting the rules of knowledge, expertise, and practice.

Strategy And Stewardship In An Uncertain World, Havovi Joshi

Asian Management Insights

This issue, as we continue to celebrate Singapore Management University’s (SMU) 25th anniversary, we explore leadership in higher education, the rise of artificial intelligence (AI), ethical stewardship, and other challenges, highlighting how they intersect in our increasingly complex, fast-changing world.

Reducing Carbon Emissions Through Sustainable Food Consumption: Applying An A-S-I Framework On Beijing Residents, Xuan Yang, Jiaxin Zou, Jingyao Gao, Shu Yang

Student Publications

The food sector represents one of the largest contributors to global climate change, making it urgent for the public to transform their food consumption behavior. However, food consumption behaviors that can facilitate carbon reduction, and how to classify these behaviors from the perspective of behavioral science, have not been deeply explored. This study pioneers a novel categorization of carbon-mitigating food consumption behaviors based on an A-S-I framework (i.e., “Avoid” food loss and waste, “Shift” to low-carbon alternatives, and “Improve” dietary structure). Such a classification not only encompasses the full spectrum of emission-altering behaviors but also enables identification of common determinants …

Minifying Deep Denoising Networks With Knowledge Distillation, Antonio L. Rozzi

Master's Theses

Hearing loss is a prevalent condition, affecting hundreds of millions globally, with a higher incidence among older adults. While hearing aids are the standard treatment, the majority of those who could benefit from hearing aids choose not to wear them, attributing this decision in large part to their inability to perform well in conversations in large groups and in noisy situations. To date, no denoising systems on commercial hearing aids are able to improve speech intelligibility. Recent advances in artificial intelligence research have shown that large deep-learning models can in fact improve speech intelligibility by removing background noise from audio. …

A Decision Support System For Conference Session Selection Using Natural Language Processing, Tillman E. Erb

Master's Theses

Conference attendees are faced with selecting from hundreds to thousands of presentations and sessions in pursuit of new findings and methods relevant to their area of interest, an overwhelming amount of information from which to clearly make a decision. To address this, we developed a decision support system leveraging natural language processing (NLP) techniques such as semantic matching. By creating and matching embeddings of conference presentation abstracts and titles, the application provides improved query matching compared to keyword searching. We introduce Session Scout, a novel conference decision support system built upon a semantic retrieval framework. Session Scout is designed to …

Topiarism: The Kernel Embedding Of Distributions Applied To Modern Portfolio Theory, Stephen G. Cook

Master's Theses

The method of kernel embedding of distributions on a set $\Omega$ into a reproducing kernel Hilbert space is a method of studying the space of measures on a set $\Omega$ using Hilbert space geometry. Because positively weighted portfolios can be interpreted as nonnegative probability measures on the space of assets, we are able to apply this technique to portfolio theory. In this thesis, we discuss the theory of "topiarism", the study of positively weighted probability measures on compact sets under the kernel embedding of distributions. Given a specific payoff function $\psi$ on the set of assets $\Omega$, we optimize a …