Physical Sciences and Mathematics Commons^™

Cruise Network Design Under Sequential Duopolistic Entry, Ta-Hui Yang, Ching-Hui Tang, Wan-Tien O

Journal of Marine Science and Technology–Taiwan

This study addresses the network design for international cruise services in a duopolistic market, where carriers enter and make decisions sequentially. The leader, who makes the first move, makes decisions as there is no competitor in the market. The follower, who makes decisions later, has to design their network considering the existing leader’s network. The leader’s model is a mixed integer linear problem while the follower’s model is a mixed integer nonlinear problem. Therefore, a heuristic is proposed to solve the problem. The commercially available general algebraic modeling system is used in conjunction with its different solvers to solve the …

Effect Of Heat Treatment On The Corrosion And Wear Behavior Of 17-4 Ph Stainless Steel For Marine Applications, Syuan Tai, I-Kon Lee, Ming-Yuan Lin, Kang-Yu Liao, Chin-Chun Chang, Hung-Bin Lee

Journal of Marine Science and Technology–Taiwan

This study explores the tribocorrosion behavior of conventionally cast 17-4 PH stainless steel under real seawater conditions, focusing on the effects of three heat treatments (Solution, H900, H1100). Electrochemical tests, tribocorrosion experiments, SEM, XPS, and quantitative analysis were used to establish a three-stage tribocorrosion mechanism. Results show that H900 exhibits superior corrosion and wear resistance, while H1100 suffers increased material loss and surface cracking at high potentials. Elemental analysis revealed NbC migration forming third-body particles, which, although briefly reducing friction, induced local stress concentration and crack initiation. The findings highlight the critical influence of microstructure, passive film stability, and third-body …

Enhancing Underwater Imagery And Organism Detection Using Reinforcement Learning, K. Arul Deepa, P. Ramya, Karpaga Vinodha, Dharmaraja C

Journal of Marine Science and Technology–Taiwan

Underwater environments pose significant challenges in assessing image quality and organism detection due to light scattering and absorption, which limits visibility and color fidelity. Existing solutions often fail to effectively address these challenges, resulting in suboptimal image quality and hindering organism identification. This paper examines the problem through a dual-focused approach: enhancing underwater images and detecting organisms using the Underwater Image Enhancement Benchmark (UIEB) dataset. The first step introduces a state-of-the-art method for image enhancement by applying reinforcement learning (RL) principles. By formulating the enhancement process as a Markov Decision Process (MDP)—where states are represented by image features and actions …

Gender Differences In The Association Between Adverse Childhood Experiences And Drug Use: Findings From A Community-Based Survey In China, Hongyun Fu, Elizabeth Monk-Turner, Xiushi Yang

Department of Pediatrics Faculty Publications

Background

While adverse childhood experiences (ACEs) are widely recognized risk factors for behavioral health problems, including drug use, prior research has largely been conducted in Western countries, focused primarily on males, and relied on convenience samples without comparison groups of nonusers. Limited work has examined the impact of ACEs on drug use in non-Western contexts. This study examines gender differences in the relationship between ACEs and drug use in China, using data from a population-based probability sample survey.

Methods:

Cross-sectional data were collected in 2019 from one city in Yunnan Province in Southwest China and one city in Guangdong Province …

All Games Have Equilibria, M. Ali Khan, Arthur Paul Pedersen, Maxwell B. Stinchcombe

Publications and Research

Research on Nash equilibrium existence for infinite games has grown into a patchwork of technical preconditions and counterexamples. This paper presents a unified program in equilibrium theory by revising the predominant model of mixed strategies based on countable additivity. A game is specified by a nonempty set of players and, for each player, a nonempty action set and a bounded von Neumann-Morgenstern utility function. Every such game is shown to admit a Nash equilibrium in finitely additive mixed strategies. In addition, the equilibrium correspondence for any such game is shown to be nonempty, compact-valued, and upper hemicontinuous, and the same …

Understanding How Erosion And Unit Thickness Alter The Deformation Of Fold-Thrust Belts, Kaitlyn E. Gallis, Caroline M. Burberry

Nebraska Academy of Sciences: Programs and Proceedings

When a collision of two tectonic plates occurs, fold thrust belts develop, which are widely recognized as the most common mode in which the crust accommodates shortening. Most analog models do not consider erosion when documenting fold thrust belt formation. The lack of experiments on this topic means there are limited consistent studies on the relationship between erosion and deformation. Preliminary experiments suggest that the typical forward breaking thrust sequence is altered by eroding the hinterland, something this experiment series aims to prove or disprove. The new contribution of this work is a systematic evaluation of the variation in initial …

Ocular Surface Disease Following Lasik And Cataract Surgery: A Review Of Their Interrelated Complications, Matthew D. Spangler, Nila Kirupaharan, John D. Sheppard

Department of Ophthalmology Faculty Publications

Background: Ocular surface disease is a multifactorial condition that is very commonly caused by dry eye disease (DED). Ophthalmic procedures intended to improve visual outcomes, laser-assisted in situ keratomileusis (LASIK) and cataract surgery, can paradoxically cause or exacerbate underlying ocular surface disease. This results in worsening vision and quality of life.

Areas covered: This review examines the pathophysiological mechanisms contributing to ocular surface disease development following LASIK and cataract surgery. Both procedures are associated with the transection of corneal nerves, leading to decreased tear production, surface instability, altered neurotrophin production, and impairment of the blink reflex. Furthermore, these incisional procedures …

Promptable Segmentation For Adaptive And Data-Efficient Medical Image Analysis, Tyler Ward

University of Kentucky Doctoral Dissertations

Image segmentation is a fundamental task in computer vision. While segmentation models have traditionally been trained in a fully-supervised manner, recent approaches have leveraged large-scale pre-training and prompting mechanisms to great effect. However, the performance of such approaches often degrades when applied to domain-specific tasks like medical image analysis. A major reason for this lies is that these models are trained on large, labeled datasets of natural images, which have drastically different characteristics compared to medical images, limiting the generalizability of the methods when applied to medical data. This dissertation presents several data-efficient, adaptive, and promptable medical image segmentation models. …

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 …

Multi-Grade Deep Learning, Yuesheng Xu

Mathematics & Statistics Faculty Publications

Deep learning requires solving a nonconvex optimization problem of a large size to learn a deep neural network (DNN). The current deep learning model is of a single-grade, that is, it trains a DNN end-to-end, by solving a single nonconvex optimization problem. When the layer number of the neural network is large, it is computationally challenging to carry out such a task efficiently. The complexity of the task comes from learning all weight matrices and bias vectors from one single nonconvex optimization problem of a large size. Inspired by the human education process which arranges learning in grades, we …

Utilizing Machine Learning Techniques For Computer-Aided Covid-19 Screening Based On Clinical Data, Honglun Xu, Andrews T. Anum, Michael Pokojovy, Sreenath Chalil Madathil, Yuxin Wen, Md Fashiar Rahman, Tzu-Liang (Bill) Tseng, Scott Moen, Eric Walser

Mathematics & Statistics Faculty Publications

The COVID-19 pandemic has highlighted the importance of rapid clinical decision-making to facilitate the efficient usage of healthcare resources. Over the past decade, machine learning (ML) has caused a tectonic shift in healthcare, empowering data-driven prediction and decision-making. Recent research demonstrates how ML was used to respond to the COVID-19 pandemic. This paper puts forth new computer-aided COVID-19 disease screening techniques using six classes of ML algorithms (including penalized logistic regression, random forest, artificial neural networks, and support vector machines) and evaluates their performance when applied to a real-world clinical dataset containing patients’ demographic information and vital indices (such as …

Changepoint Analyses Confirms Global Tropical Cyclone Frequency Decline, Michael Wehner, Thomas Fisher, Norou Diawara, Robert Lund

Mathematics & Statistics Faculty Publications

Changes in tropical cyclone frequencies as the climate warms is a topic of significant current debate [1, 2]. There is no accepted theory of how tropical cyclogenesis might respond to a warmer ocean-atmosphere system as multiple controlling factors exist [3–7]. Anthropogenic warming of surface ocean temperatures due to increased greenhouse gas concentrations [8] increases the potential for tropical cyclogenesis [9–11]; however, realized cyclogenesis also requires an initial local disturbance [12–16] to develop. Most multi-decadal tropical cyclone permitting climate models (i.e. resolutions of 15-50km) exhibit frequency decreases in warmer climates, despite the increase in tropical cyclogenesis potential [17–25]. In this paper, …

A Composite Narxnn Approach To Photovoltaic Power Forecasting With Integrated Weather Inputs And Uncertainty Quantification, Denisse Urenda Castañeda, Sharmin Abdullah, Jackson Morgan, Honglun Xu, Michael Pokojovy, Tzu-Liang Tseng

Mathematics & Statistics Faculty Publications

Solar photovoltaics (PV) are a major source of sustainable energy. Yet, their power output is highly sensitive to environmental variability, particularly solar irradiance, cloud cover, wind, and temperature. Accurate forecasting of PV power is essential for efficient grid integration and energy planning, especially in applications requiring reliable longer-term forecasting rather than one-step-ahead predictions. This study presents a PV power forecasting approach using Nonlinear Autoregressive models with Exogenous Inputs (NARX), integrating large-scale numerical weather historical data as exogenous variables. Although NARX models effectively capture temporal dependencies, they can become overly dependent on historical power values, reducing responsiveness to real-time weather changes. …

31p Solution Nmr Investigation Of Abasic Dna, Clarissa R. Krimmel

Graduate Theses/Dissertations

Base excision repair (BER) mechanisms fix single base lesions in DNA, such as T:G mismatches. During the base excision repair mechanism, an abasic site (AP site) is formed as an intermediate. AP sites are unstable and highly mutagenic; they can stop DNA replication. This research investigates how the conformational properties of abasic sites in DNA affect the binding recognition of enzymes involved in DNA repair mechanisms, including BER. Three different abasic sequences are being analyzed for this research project. A second project looks at the effects of a naturally occurring purine derivative, hypoxanthine, on the DNA backbone. These hypoxanthine lesions …

Remediation Impacts Metal Concentrations And Metal Tolerant Bacteria In Soils Of The Missouri Tri-State Mining District, Ophelia R. Pettington

Graduate Theses/Dissertations

After over 100 years of Zn and Pb mining in the Tri-State mining district (TSMD), former mines continue to be sources of metals. Metal contaminated soils can be remediated using plant-microbe interactions. Plants manipulate their microbiome and recruit microbes to increase metal tolerance. Remediating bacteria are site-specific and identifying native microbes can accelerate remediation efforts. Studies relating microbes and metal concentrations in remediated areas in the TSMD are scarce. I collected root and bulk zone soils associated with Andropogon virginicus from remediated and non-remediated sites in Webb City, MO. I used 16S rRNA gene amplicon sequencing to evaluate the bacterial …

Flood-Regime Shifts Across The Lower Midwest, Usa: Identifying Patterns Through Flood Magnitude–Frequency Analysis And Clustering, Kaiser Mostafiz

Graduate Theses/Dissertations

Flood regimes describe how flood behavior changes in magnitude, recurrence, and occurrence through time. Changes in these flood characteristics can affect flood hazards, river systems, infrastructure, and floodplain management. This thesis examines flood-regime change across the Lower Midwest, focusing on Nebraska, Iowa, Kansas, and Missouri from 1961 to 2020. Records from 1,452 U.S. Geological Survey gaging stations were initially compiled, and 208 stations were retained after screening for record availability and analytical consistency. Flood-regime change was evaluated between two 30-year study periods: Period 1 (1961–1990) and Period 2 (1991–2020). The analysis combined Log-Pearson Type III flood-frequency analysis using L-moments in …

A Geospatial Assessment Of Groundwater Salinization In A Multi-Aquifer System: Durango, Mexico, Juan Lopez-Sierra

Graduate Theses/Dissertations

Groundwater salinization poses a critical environmental concern for water resource sustainability in arid and semi-arid regions. This study evaluates spatial and temporal patterns of groundwater salinity across the state of Durango, Mexico, using total dissolved solids (TDS), sodium adsorption ratio (SAR), as salinity indicators and nitrate-nitrogen (NO₃–N) as an anthropogenic indicator. Groundwater quality data were obtained from (CONAGUA), a Mexican water agency. To assess salinity variations with respect to time, while minimizing interannual sampling bias, two multi-year sampling periods were selected: 2012-2013, and 2020-2021. Final datasets consisted of 122 wells for 2012–2013 and 131 wells for 2020–2021. The wells were …

Considerations For Assigned Water After Expiration Of The 2007 Guidelines, Kathryn Sorensen, Sarah Porter, Anne Castle, John Fleck, Eric Kuhn, Jack Schmidt, Katherine Tara

The Traveling Wilburys of the Colorado River

As Colorado River supplies and demands reach razor-thin margins, new tools to provide adaptive capacity will play a critical role in sustaining communities across the West. We must reduce our consumption of water, while finding ways to cushion the impact. One of the most innovative tools for doing this, developed over the last two decades, is “Assigned Water” - giving users the ability to store conserved water earmarked for their own future use. Originally developed as “Intentionally Created Surplus” in the 2007 Colorado River Interim Guidelines, Assigned Water has been revised and expanded through U.S. Mexico Treaty Minutes and as …

Improving Human Dimensions Of Conservation Planning: Challenges And Opportunities For Sustainable Conservation Outcomes, Vivian Hulugh

Electronic Theses and Dissertations

Conservation planning is important to ensure both ecological and social benefits of natural resources, including the maintenance of functional ecosystems and stable wildlife populations as well as the provision of resources that communities rely on. Yet, the integration of the human dimensions of conservation planning remains limited in practice. This thesis examines conservation planning in South Dakota and within Joint Venture (JV) partnerships, using qualitative methods to identify challenges and opportunities for more effective and coordinated planning. In chapter one, I examine how collaboration, public participation, and the use of climate information are integrated conservation planning in South Dakota and …

The Spacetime Finite Element Method For Investigations Into Physics Ghost Systems And Time Parallel Preconditioning, Jax Wysong

Electronic Theses and Dissertations

This work operates on two fronts, focusing on interesting physical phenomena before turning our attention to an interesting numerical math problem. First, using the spacetime finite element method (FEM), we investigate a PDE system consisting of two Klein Gordon equations, which are coupled nonlinearly through the potential energy. The system contains a ghost (negative kinetic energy term). Systems such as these are generally deemed physically unstable, resulting in infinite energy in finite time. However, recent work has shown that this is not always the case. We investigate multiple scenarios arising from different initial conditions to characterize if/when a ghost system …

Modeling The Effects Of Subsurface Tile Drainage On Atrazine And Nitrate Transport In Till Soils Of Iowa, Madison Hobbs

West Chester University Graduate Theses, Dissertations, and Final Projects

Tile drainage design influences groundwater flow pathways, residence time, and agrochemical transport in agricultural soils. This study evaluates how differences in drainage design affect subsurface flow behavior and contaminant transport in glacial till soils. A groundwater model was developed to compare conventional and controlled drainage systems with a shallow drainage system, and particle tracking was used to examine flow paths and residence times.

The results show that tile drainage creates distinct shallow and deeper flow pathways. In the conventional and controlled model, 88% of particles were captured by drains, while 12% reached the general head boundary. The shallow system drains …

Shrinking Attachment Spaces, Anastasia M. Clements

West Chester University Graduate Theses, Dissertations, and Final Projects

Gluing constructions such as pushouts and other colimits are often used to attach spaces to- gether in algebraic topology. The weak topology is a natural choice of topology for attachment spaces in the context of CW-complexes and simplicial complexes because of its universal property but is insufficient for gluing together infinitely many spaces and preserving topological properties like compactness or metrizability. In this thesis, we introduce a modification of the weak topology called the shrinking attachment topology, which is defined on a space Y constructed by attaching an infinite sequence of spaces B₁, B₁, B_{3 …}

Connecting Classroom Physics To Real-World Research: A Citizen Science Approach In Ap Physics 1, Heather M. Landgarten

West Chester University Graduate Theses, Dissertations, and Final Projects

Advanced Placement (AP) Physics 1 emphasizes evidence-based reasoning, quantitative modeling, and scientific inquiry. However, secondary science instruction often remains focused on procedural problem solving and standardized assessment rather than authentic scientific practice. This study examined the integration of citizen science projects into an AP Physics 1 curriculum to provide students with authentic research experiences while reinforcing physics concepts during the post-AP examination instructional period.

Using a classroom-based mixed-methods pre–post design, students participated in citizen science activities through publicly available research platforms, including Zooniverse. Students collected and classified authentic scientific data, analyzed real-world datasets, developed research questions, compared observations with theoretical …

A Dual-Emission Polymer-Dots/Gold-Nanoclusters Nanohybrid For Ratiometric Fluorescence Detection Of Hg²⁺, Sha Wu

Dissertations and Theses

Heavy metals, such as Hg, Cd, Pb, and Cr, become a serious environmental problem because they are highly toxic, bioaccumulation, and long-term persistence, required a high sensitivity and selectivity detection method. Although laboratory testing instruments, such as inductively coupled plasma mass spectrometry, offer high sensitivity, their practical application is limited because they rely on large-scale equipment and complex sample pre-treatment processes. Single-emission fluorescence probes are simpler but can be affected by variations in probe concentration, excitation intensity, and measurement conditions. In this study, a dual-emission nanohybrid that consists of poly(9,9-di-n-hexylfluorenyl-2,7-diyl) (PDHF) and bovine serum albumin (BSA), termed as PDHF-Pdots/BSA-AuNCs nanohybrid, …

Linking Boundary Type, Storm Mode, And Tornado Intensity In Illinois, Jakob Barton

A with Honors Projects

A large dataset of tornadoes across Illinois from 2007-2024 were analyzed for different characteristics of thunderstorms and tornadoes, these characteristics were then compared with each other to find correlation and trends.

Final Annual Operations And Maintenance (O&M) Report: Butte Treatment Lagoon (Btl) System – 2023, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Ai-Assisted Surface-Enhanced Raman Spectroscopy For Cardiovascular Diagnostics: From Plasmonic Materials To Clinical Translation, Anju Joshi, Gymama Slaughter

Center for Bioelectronics Publications

Raman spectroscopy (SERS) has emerged as a powerful analytical technique, offering molecular fingerprint specificity and ultrasensitive detection of cardiac biomarkers. Recent advances in plasmonic nanostructures, surface functionalization strategies, and flexible sensing platforms have significantly improved the analytical performance of SERS-based biosensors. In parallel, the integration of artificial intelligence (AI) and machine learning has enabled robust interpretation of complex spectral datasets, facilitating automated biomarker classification and improved diagnostic accuracy in heterogeneous biological environments. Despite these advances, the field remains fragmented, with limited integration between nanomaterial design, biomarker selection, and data-driven analysis, and persistent challenges related to reproducibility, standardization, and clinical validation. …

Image-Derived 3d Hepatic Lobule Modeling Of Acetaminophen-Induced Hepatotoxicity, Rebecca Lauren Strauss

Selected Full-Text Master Theses 2021-

The liver’s highly structured vascular microarchitecture governs blood perfusion, metabolic zonation, and the spatial distribution of xenobiotic toxicity. Current computational models of hepatic drug metabolism often oversimplify this geometry, limiting their ability to capture realistic flow dynamics and cellular injury patterns. This study develops a multiscale computational framework to predict acetaminophen-induced hepatotoxicity using image-derived, three-dimensional hepatic lobule geometries. The model integrates computational fluid dynamics (CFD) with a mechanistic cellular injury module to simulate the interplay between perfusion, metabolism, and hepatocellular viability.

Realistic vascular reconstruction was achieved from histopathology liver slices, and the resulting geometry was meshed and solved using ANSYS …

Deep Learning For Eeg-Based Emotion Recognition With Temporal And Spectral Interpretability, Shruti Rameshbhai Shingala

Selected Full-Text Master Theses 2021-

Electroencephalography (EEG)-based emotion recognition has emerged as a critical component of affective computing and clinical neuroscience. Existing approaches to this problem primarily reduce the multi-dimensional EEG time series to a single averaged feature vector, thereby discarding the temporal structure of the emotional response. The present work addresses three identified gaps in the literature: the absence of temporal interpretability, the uniform use of frequency bands, and the use of single-scale temporal feature extraction. A deep learning architecture, MST-Mamba-Asym, is proposed, comprising four components: Asymmetry Attention, which encodes hemispheric asymmetry by computing signed left–right channel differences, FreqBandAttention, which learns differential weights across …

Machine Learning Prediction Of Federal Appellate Court Outcomes: A Multi-Circuit Analysis With Administrative Law Implications, Nicky Nuertey Apenahier

Dissertations and Theses

Federal appellate courts are the final arbiters in many cases, yet systematic machine learning analysis across all twelve circuits remains largely absent from the computational law literature. With courts of appeals deciding tens of thousands of cases annually and the Supreme Court reviewing only a fraction, understanding what predicts reversal outcomes has both theoretical importance and practical consequences for litigants, attorneys, and judicial administrators. This study addresses that gap using eleven years of federal appellate decisions from the Federal Judicial Center’s Integrated Database. A systematic comparison of twenty-five machine learning models, spanning five algorithms and five class-imbalance correction strategies, identifies …