Physical Sciences and Mathematics Commons^™

Feasibility Study Of Transitioning From Thick Plates (0.250”) Mounted On 30-Point Pvc Carriers To Thinner Plate Technologies Mounted On Recyclable Foam And Pet (0.155”) For Post-Print Corrugated, Nathaniel J. Poole

All Theses

In the United States, the most common press configuration for brown-box printing is a 0.280” undercut press. These press configurations have long relied on thick 0.250” plates mounted on 0.030” PVC sheets to print onto corrugated substrates. Each year, around twenty million pounds of waste are produced by the printing industry, through paper waste, plate waste, among other materials. One large factor of that waste is flexographic plate waste, which either ends its life in a landfill or is repurposed into other products. This study establishes a comparison between traditionally used 0.250” plates on 30pt PVC versus 0.155” plates mounted …

Base Running: A Lost Art In Baseball, Ethan York

Departmental Honors & Graduate Capstone Projects

In an era of baseball dominated by home runs and launch angles, the subtle art of baserunning is often overlooked, despite its measurable impact on winning games. Baserunning Runs (BsR) addresses this gap by quantifying the number of runs a player contributes through performance on the basepaths, capturing value beyond traditional metrics like stolen bases. This study constructs multiple regression models that predict BsR for Major League Baseball (MLB) players based on baserunning-related statistics. The primary objective is to examine the association between BsR and key predictors, including stolen bases (SB), extra bases taken (EB), and sprint speed (SS), while …

Analyzing The Evolution Of Science: Topological Cycles And Community Detection In Knowledge Networks, Frances C. Mcconnell

Mathematics, Statistics, and Computer Science Honors Projects

How scientific knowledge grows and organizes itself is a central question in the study of science. This thesis uses tools from topology and network science to detect and characterize knowledge gaps—places in a field’s literature where related concepts do not co-occur. We develop a metric to quantify the degree of interdisciplinarity of each gap, using the community structure of the underlying network as a proxy for subfields. Across a wide range of fields, gaps reliably span multiple subfields and evolve in recognizable temporal patterns, highlighting new insights into how scientific fields are structured and their stage of development.

Understanding Delays In Emergency Department Care: A National Analysis Of Wait Times, Gregory Forsberg

Mathematics, Statistics, and Computer Science Honors Projects

Emergency department (ED) wait times remain a persistent bottleneck in the United States healthcare system, impacting patient outcomes, hospital efficiency, and equitable access to care. This study analyzes nationally representative data from the National Hospital Ambulatory Medical Care Survey (NHAMCS), a complex, multi-stage probability sample. Using survey-weighted analyses and predictive modeling, we examine the effects of patient characteristics, triage acuity, and visit timing. Results indicate that operational and system-level factors, including hospital capacity, geographic region, and temporal variation, are among the most influential predictors of ED wait times

Pattern Dynamics And Stochasticity Of Brain Rhythms And Spike Trains In A Tauopathy Mouse Model Of Alzheimer’S Disease, Clarissa M. Hoffman

Dissertations and Theses (Open Access)

Systems neuroscience posits that every aspect of perceived physical reality, every aspect of animal and human behavior, and every cognitive phenomenon emerges from patterns of neuronal activity. While most researchers embrace this idea, there are major difficulties in describing and analyzing these complex neuronal dynamics—spike flows produced by cells ensembles, synchronized extracellular field oscillations, and other patterns—which limits our understanding of how the activity of individual neurons and the whole-animal cognition and behavior might be connected. In particular, we lack the approaches and even the semantics for connecting the individual cell outputs and the integrated results of their activity. Current …

Explainability In Deep Learning For Density Regression, Dalton James Oxford

Graduate Theses and Dissertations

Classical statistical methods focus on explainability and inferential power. Machine learning and deep learning can handle non-linear, high-dimensional data better than traditional methods. In modeling, a clear understanding and interpretation are essential to decision-making. Recent work in quantile regression and extreme modeling has begun to use deep learning due to its performance on high-dimensional, non-linear data. Semi-Parametric Quantile Regression (SPQR) is a nonparametric spline-based approach to quantile regression that estimates the conditional PDF and CDF of the response. Semi-Parametric Quantile Regression for Extremes (SPQRx) is a recent extension of SPQR that provides two features: out-of-sample estimation and accurate extreme-tailed estimation. …

Scalable Roof Polygon Extraction And Geometric Characterization From Remotely-Sensed Data For Snow Load Assessment, Jashon Newlun

All Graduate Theses and Dissertations, Fall 2023 to Present

Heavy snow accumulation on rooftops is a serious structural risk in cold climates, and understanding how much snow builds up on different types of roofs is essential for safe building design. Currently, most data on roof snow loads comes from small, labor-intensive field surveys that cover only a handful of buildings at a time. This results in far too few measurements of buildings to draw confident conclusions about how snow behaves across communities. This thesis develops and demonstrates a new automated approach for measuring roof snow accumulation and extracting key building characteristics across thousands of buildings at once using airborne …

Research Remix: Teams, Tech, And Texts, Jaime Carbajal

UNLV Best Teaching Practices Expo

The pedagogical innovation that enhanced student learning in the Research Methodologies in Health Sciences course is described as Integrated Digital Collaborative Inquiry-Based Learning (IDCIBL). The IDCIBL approach leveraged digital tools (lecture videos, podcasts, recorded poster presentations, and Artificial Intelligence (AI) platforms), integrated journal article analysis, utilized research-informed active learning, and included team-based learning activities. The combination of multiple innovative strategies into the IDCIBL model intentionally transforms the educational environment and optimizes the student learning experience, relating to the TLC priority area of teaching and assessments in the age of Gen AI.

Coexistence Of“Emotion”And“Rationality”：Analysis Of The Impact Mechanism Of Frequent Reversal Events On The Evolution Of Online Public Opinion, Liqiang Wang, Xueqi Li, Yixian Wang

Journal of Scientific Information Research

[Purpose/significance] In recent years, frequent reversal events have negatively impacted the online media environment, leading to an increasing number of skeptical voices during the evolution of public opinion.These doubts are no longer merely emotional outbursts but also involve rational understanding of the event's authenticity. This study aims to gain a deeper understanding of this phenomenon and attempts to reveal the impact mechanism of frequent reversal events on the evolution of online public opinion. [Method/process] Through surveys and computer simulation experiments, the study analyzes various elements such as individuals, media environment, and evolution patterns in online public opinion,then according to the …

The Item Response Warehouse: What It Is, How To Use It, And Targets For Potential Improvements, Savira D. Nadela, Hansol Lee, Nishka Jain, Ayaan Gupta, Xingyi Zhang, Benjamin W. Domingue

Chinese/English Journal of Educational Measurement and Evaluation | 教育测量与评估双语期刊

The Item Response Warehouse (IRW) is a repository of harmonized item response datasets designed to support secondary analysis and methodological research in psychological and educational measurement. This paper serves as a practical guide for researchers interested in using the IRW. We describe the structure of IRW datasets and the quantitative and qualitative metadata available for dataset selection, and we demonstrate how researchers can navigate the IRW website to explore and compare available tables. We further show how the IRW R and Python packages can be used to filter datasets programmatically, download response-level data, and generate standardized citations for reproducible research …

Ma(1) Or White Noise?, Orithea Regn, Ferebee Tunno

Create@State

This project provides an over of testing an MA(1) process confidence interval while keeping the margin of error to a minimum, even for small sample sizes.

Simulation And Projection Of Glaciers And Their Runoff In Xinjiang Based On Tgsgs, Zhongqin Li, Yefei Yang, Bowen Liu, Huilin Li, Zexin Zhan, Feiteng Wang, Chunhai Xu, Weibo Zhao

Bulletin of Chinese Academy of Sciences (Chinese Version)

Glaciers are large flowing ice bodies formed from snowfall in cold regions. Due to the intrinsic physical properties of ice and the complexity of boundary conditions, physically based modelling of glacier change remains a global challenge. With support from the Chinese Academy of Sciences’ key science infrastructure program for the field station, the Tianshan Glaciological Station completed the Tianshan Glacier Station Glacier Simulator (TGSGS) in 2025. TGSGS features advanced representations of the physical mechanisms driving glacier change and multi-scale ensemble strategy, and is integrated with a reference glacier observation network based on terrestrial laser scanning (TLS), a low-temperature laboratory for …

A Computer Vision Approach To Analyzing Taxane Effects On Prostate Cancer Cells, Diana Elizabeth Dancea

Electronic Theses and Dissertations

Actin is a family of proteins that help create the structure of the cytoskeleton, which gives shape to the cell. In many chemotherapy treatments, researchers target actin because it controls the cell division process. Therefore, if they are able to understand the actin fibers, that may help in formulating methods to stop or slow down cancer cells from reproducing. Another important protein is PAK6, which regulates actin. In our research, a collaborative effort with Prof. Michael Lu’s lab at Florida Atlantic University, we use machine learning techniques to analyze cells which had their PAK6 protein knocked out, and compare them …

Ownership Duration In The U.S. Business Jet Market, Yuchen Hu

SACAD: Scholarly Activities

This study analyzes ownership duration in the U.S. business jet market using FAA registry data as of February 16, 2026 (N=12,359). The analysis reveals a structured distribution with a mean of 5.86 years and a median of 5.00 years. Crucially, retention varies by acquisition status: new aircraft owners exhibit an average hold of 7.36 years, whereas pre-owned aircraft holders show a significantly higher turnover of 5.11 years, with most resales occurring within a 3–7-year window. These findings suggest that ownership behavior is driven by structured asset management and lifecycle planning, providing a predictive framework for identifying aircraft replacement and trade-in …

Drainage Proximity And Sinkhole Occurrence In Sivrihisar (Central Turkey): A Comparative Analysis Of Linear, Poisson, And Negative Binomial Regression Models, Bilge Bingül, Emrah Pekkan, Resul Çömert

International Journal of Speleology

This study investigates the relationship between sinkhole occurrence and distance to drainage in the Sivrihisar region (Central Turkey) and evaluates the suitability of different regression approaches for modeling clustered count data in karst terrains. A comprehensive inventory of 104 sinkholes developed within the Neogene lacustrine limestones of the Akpınar Formation was compiled using official records, remote sensing analyses, and detailed field surveys. Sinkhole occurrences were analyzed relative to a drainage network derived from a high-resolution Digital Surface Model and grouped by proximity to drainage lines. Linear Regression (LM), Poisson Regression (PR), and Negative Binomial Regression (NBR) models were comparatively applied …

Irreversible K-Threshold Dynamics On Corona And Base-B Corona Product Graphs, Eric J. Moon, Soumya Bhoumik, Paul Flesher

SACAD: Scholarly Activities

This poster studies the irreversible k-threshold process on corona-type graph products, where a vertex becomes colored once at least k of its neighbors are colored and then remains colored permanently. We focus on corona, double corona, and base-b corona product graphs built from cycles and complete graphs, with particular attention to how graph structure affects complete activation from a minimum seed set.

A generalized reduction lemma is used to relate threshold dynamics on layered corona graphs to smaller residual graphs, yielding explicit formulas for the irreversible k-threshold conversion number on both corona and double corona families. The …

Complex Systems Mapping Of Fiscal Growth Dynamics At Strategic Maritime Chokepoints Using Time-Series Slopes, Rahul Balamurugan, Preethi Nanjundan, Avichal Sharma

Northeast Journal of Complex Systems (NEJCS)

This study examines how maritime and trading states allocate public resources between defence, health, and economic growth around three strategic chokepoints the Strait of Malacca, the Strait of Hormuz, and the Suez Canal. The analysis extends the classic “guns versus butter” framing by treating defence and health spending as co-evolving components of an interconnected fiscal-growth system. Using World Development Indicators data (1999-2024), trend slopes are estimated for military spending (% of GDP), healthcare spending (% of GDP), and GDP growth (annual %). Two derived indicators are computed, a defence-to-health slope ratio (military slope/health slope) and a fiscal-balance proxy (health slope …

Psychosocial Mediators Of A Physical Activity And Dietary Intervention In Pregnant Women With Overweight Or Obesity, Meghan Baruth, Sarah Wilcox, Jihong Liu, Rebecca Schlaff

Faculty Publications

Background

Mediation analyses provide insight into both ‘pieces’ of the mediation chain; they allow us to look into the ‘black box’ that is behavior change. They allow researchers to better understand the ‘how’ of an intervention’s effects and/or the ‘why’ behind why an intervention worked or did not work. The lack of publications in pregnant populations highlights the need for additional studies to be conducted and published. The purpose of this study is to examine the psychosocial mediators of physical activity and dietary outcomes in a sample of pregnant women with overweight or obesity participating in the Health in Pregnancy …

Preliminary Sonification Of Enso Using Traditional Javanese Gamelan Scales, Sandy Hs Herho, Rusmawan Suwarman, Nurjanna J. Trilaksono, Iwan P. Anwar, Faiz R. Fajary

Northeast Journal of Complex Systems (NEJCS)

Sonification—the mapping of data to non-speech audio—offers an underexplored channel for representing complex dynamical systems. We treat El Niño-Southern Oscillation (ENSO), a canonical example of low-dimensional climate chaos, as a test case for culturally-situated sonification evaluated through complex systems diagnostics. Using parameter-mapping sonification of the Niño 3.4 sea surface temperature anomaly index (1870–2024), we encode ENSO variability into two traditional Javanese gamelan pentatonic systems (pelog and slendro) across four composition strategies, then analyze the resulting audio as trajectories in a two- dimensional acoustic phase space. Recurrence-based diagnostics, convex hull ge- ometry, and coupling analysis reveal that the sonification …

Sex-Specific Differences In Lung Mitochondrial Function And Injury In Rats Exposed To Hyperoxia, Taheri Pardis, Abraham G. Taye, Devanshi D. Dave, Elizabeth R. Jacobs, Guru Prasad Sharma, Anne V. Clough, Ranjan K. Dash, Said H. Audi

Mathematical and Statistical Science Faculty Research and Publications

Hyperoxia is both an essential therapy and a contributor to lung injury in acute respiratory distress syndrome. We hypothesized that adult female rats are relatively protected from hyperoxia-induced acute lung injury (HALI) compared with males and that this protection is associated with sex-dependent differences in lung mitochondrial bioenergetics and H₂O₂ production. Adult rats were exposed to room air (normoxia) or hyperoxia (>95% O₂) for up to 60 h. Lung injury was assessed by pleural effusion, lung wet weight, pulmonary vascular filtration coefficient (K_f), histologic injury scores, and cleaved caspase-3 (CC3) staining. …

Empirical Benchmarks For Interpreting Effect Sizes In Violent Crime Interventions, Kohta James Matsukawa Hansen

Theses and Dissertations

Criminal justice researchers apply Cohen’s (1988) benchmarks to classify effect sizes as small, medium, or large, despite these standards never being meant for broad, decontextualized use (Cohen, 1988; Gies et al., 2024; Goulet-Pelletier & Cousineau, 2018; Lakens, 2013; Milner et al., 2023). Repeatedly doing so may weaken statistical validity, distort findings, and impede effective policymaking. This study introduces the first effect size benchmarks specifically designed for violent crime interventions.

Using a quasi-meta-analysis framework, 1,605 effect sizes from 104 violent crime intervention studies from the CrimeSolutions clearinghouse were converted to Cohen’s d. Three new discrete benchmarking methods were created using a …

The Kaczmarz Algorithm In Hilbert C∗-Modules, Daniel Alpay, Chad Berner, Eric S. Weber

Mathematics and Statistics Faculty Research & Creative Works

The Kaczmarz algorithm in Hilbert spaces is a classical iterative method for stably recovering vectors from inner product data. In this paper, we extend the algorithm to the setting of Hilbert C^∗-modules and establish analogues of its effectiveness in both finite-dimensional and stationary cases. Consequently, we demonstrate that continuous families of elements in a Hilbert space can be uniformly recovered using the Kaczmarz algorithm. Additionally, we develop a normalized Cauchy transform for continuous families of measures and use it to provide sufficient conditions under which standard frames in Hilbert C(X)-modules can be generated by the Kaczmarz algorithm and …

Sequences That Do Frame Reconstruction, Chad Berner

Mathematics and Statistics Faculty Research & Creative Works

Frames allow all elements of a Hilbert space to be reconstructed by inner product data in a stable manner. Recently, there is interest in relaxing the definition of frames to understand the implications for stable signal recovery. In this paper, we relax the definition of a frame by allowing the operator in the frame decomposition formula to not be invertible. We provide a complete classification of sequences that allow this decomposition via a type of frame operator. In addition, we provide several examples of sequences that allow this reconstruction property that are not frames and illustrate in which ways they …

Maddenlite, Sergio Pena

Presentations - 2026

Problem •“What If” scenarios impossible to test accurately •Commercial games rely on arcade physics •Spreadsheets lack visual engagement

Motivation •Passion for football analytics •Desire to simulate cross-era matchups •Apply math models to real-world sports data

Solution •Python based simulation engine using historical play-by-play data •Simulates outcomes based on probability

Deep Learning Frameworks For Biological Data Integration And Generation, Alexa Beachum

Statistical Science Theses and Dissertations

Data integration represents a key area of research for analyzing the rapidly growing volume of high-dimensional biological data across sources, stages, and modalities. To model and understand these complex, often non-linear relationships, deep learning has become an increasingly powerful tool. Here, we present two novel deep learning frameworks that address distinct but complementary integration challenges. The first framework aligns single-cell omics data across temporal stages, and the second bridges imaging and omics modalities to generate patient-level molecular profiles.

In Chapter 1, we briefly summarize existing approaches---both statistical and deep learning-based---for single-cell omics data integration and discuss their limitations for handling …

Next-Generation Democratic Cyber Statecraft - Balancing The Signal: Shutdown Shocks And Democratic Digital Governance, Scott M. Di Panni

School of Public Policy Capstones

This paper develops Next-Generation Democratic Cyber Statecraft (NG-DCS), a unified strategic doctrine for democratic governments to contest the cognitive domain against authoritarian adversaries. Drawing on twenty-six years of cross-national panel data (1999–2024) spanning 213 countries, game-theoretic modeling, and qualitative case analysis, the paper establishes three interconnected empirical and theoretical foundations. First, cross-national OLS regression across 160+ countries demonstrates that regime type is the dominant structural determinant of internet freedom (R²=0.615, β=2.513, p< 0.001), explaining more than twice the variance attributable to per-capita wealth (R²=0.268). Democratic governance, not economic development, produces open digital environments. Second, a two-way fixed effects (TWFE) difference-in-differences study exploiting government-ordered internet shutdowns as discrete policy interventions finds that digital restrictions causally degrade V-Dem governance quality by 0.21–0.38 standard deviations (p< 0.001 across all specifications). Treatment effects are immediate (β=−0.302 at k=0) and persist through five post-treatment years (β=−0.246 at k=+5), indicating structural rather than transitory governance damage. Parallel trends validation (p=0.352) and Callaway–Sant’Anna heterogeneity-robust estimation (ATT=−0.230, SE=0.077) support causal identification. Instrumental variable triangulation (2SLS β=−0.949, p=0.005) confirms that simultaneity was attenuating, not inflating, the primary estimates. Third, formal game-theoretic analysis reveals that the current U.S.–adversary equilibrium is (Restrain, Escalate)—the risk-dominant but Pareto-inferior outcome of a Stag Hunt structure. China, Russia, North Korea, and Venezuela each occupy structurally distinct positions (Stackelberg commitment, asymmetric two-level, autarky, and reactive trigger, respectively), requiring differentiated doctrinal responses rather than a uniform strategic playbook. Generative AI and algorithmic governance are shown to accelerate cognitive vulnerability by collapsing influence operation costs and exploiting engagement-optimized platform architectures that systematically degrade deliberative capacity in democratic populations.

Efficacy Analysis In Clinical Trials: A Comprehensive Review Of Statistical And Machine Learning Approaches, Dhrubajyoti Ghosh, Samhita Pal

Faculty Articles

Efficacy testing is a cornerstone of clinical trials, ensuring that medical interventions achieve their intended therapeutic effects. Over the decades, a wide range of statistical methodologies have been developed to address the complexities of clinical trial data, including parametric, nonparametric, Bayesian, and machine learning approaches. Parametric methods, such as t-tests, ANOVA, and LMMs, have traditionally been the foundation of efficacy testing due to their efficiency under well-defined assumptions. Nonparametric techniques, including the Friedman test, Brunner-Munzel test, and modern extensions like nparLD, have emerged as robust alternatives, particularly for skewed, ordinal, or non-normal data. Bayesian methodologies have enabled the incorporation of …

Bayesball : A Comprehensive Framework For Predicting Ucl Injury, Brady M. Pinter, Will Best Ph.D.

SPARK Symposium Presentations

Ulnar Collateral Ligament (UCL) reconstruction, commonly referred to as Tommy John Surgery, has seen a significant rise among Major League Baseball (MLB) pitchers, prompting growing interest in identifying the mechanical and performance-based factors that contribute to injury risk. While previous studies have examined these relationships using traditional frequentist approaches separately, this study combines multiple different model techniques to present a broad framework for finding significant predictors of UCL Surgery. These models include Lasso and Ridge Regression,  Principal Component Regression (PCR) , Partial Least Squares Regression (PLS) , Random Forest, Multiple Linear Regression, and a Bayesian Statistical Model. Using these models, …

Factors Associated With Lapses In Care Among People Living With Hiv In South Carolina, Xueying Yang Ph.D., Fanghui Shi, Shujie Chen, Gavi Samuel, Bankole Olatosi Ph.D., Sharon Weissman, Xiaoming Li Ph.D., Jiajia Zhang Ph.D.

Faculty Publications

Utilizing statewide electronic health records (EHR) data, this study aims to assess the factors determining the occurrence of lapses in HIV care among people with HIV (PWH) in South Carolina (SC). All adult (≥ 18 years old) PWH who were diagnosed with HIV between 2006 and 2018 with at least two HIV care encounters and at least 1-year follow-up record were included in the analysis. The outcome, a lapse in care, was defined as a repeated measure of HIV care encounter that occurs over a year following the previous visit. Generalized Estimation Equation models were employed. The study cohort had …

Implementation And Costs Of A Food Insecurity Resource Navigation Program For Primary Care Patients With Diabetes And Hypertension In South Carolina, Deeksha Gupta, Darin Thomas, Stella Coker Watson Self Ph.D., Ms, Edward A. Frongillo Jr. Ph.D., Alain H. Litwin, Joseph A. Ewing, Lynnette Ramos-Gonzalez, Lynnette Ramos-Gonzalez

Faculty Publications

Objective

To examine food insecurity resource navigation program costs and how navigation intensity relates to clinical outcomes, healthcare costs, and quality of life (QOL) for diabetes and/or hypertension patients.

Methods

This retrospective study included patients receiving resource navigation (July 12, 2021-December 31, 2022 with twelve-month follow-up) across three primary care practices in South Carolina's largest health system. Participants were 18+ years old (from electronic medical records/Epic), had food insecurity (from Hunger Vital Sign™), and diabetes and/or hypertension (from Epic registries). Matched controls came from food insecurity screening-only practices. Patients in each group (n= 219) had diabetes (9.13%), hypertension …