Digital Commons Network^™

Survey-Weighted Ordinal Modeling Of Alcohol-Associated Liver Disease Severity Through Social Determinants Of Health, Jaylene Viveros Cruz

Selected Full-Text Master Theses 2021-

Alcohol-associated liver disease (ALD) is a condition that describes the spectrum of disease and liver injury attributed to the consumption of alcohol. ALD diagnosis is heavily dependent on alcohol use, making it challenging to test for, as alcohol use is often self-reported, and early-stage ALD can present asymptomatically. This study aims to explore how social determinants of health associated with alcohol use behaviors predict ALD-related liver stress risk. MEC participants included in the two two-year cycles of the National Health and Nutrition Examination Survey (NHANES), 2014-2014 and 2015-2016, were assigned liver stress labels based on clinical thresholds for ALD diagnosis. …

The Relationship Between Pillar[5]Arene And Pillar[6]Arene In The Synthetic Route To A Water-Soluble Pillar[6]Arene: A Case Of Kinetic And Thermodynamic Products Or Two Distinct, Competing Reactions, Helice A. Gillis

Open Access Dissertations

Pillar[n]arenes, discovered in 2008, have already made their mark as a formidable addition to the field of supramolecular chemistry, largely due to their host-guest chemistry. While the synthesis of pillar[5]arene is well established, the synthesis of pillar[6]arene, with its larger core, has not been so straightforward and mainly accomplished through the use of bulky solvents. Here we present an optimized method for a reproducible, acid-catalyzed synthesis for a brominated pillar[6]arene, starting with a brominated monomer and using chloroform as the templating solvent. Our studies have demonstrated the ratio of brominated pillar[6]arene to brominated pillar[5]arene increases with both decreasing concentration of …

Probing Biomolecular Structure And Dynamics Via Infrared Action Spectroscopy, Madeline Schultz

Open Access Dissertations

Biomolecular structure is supported by a network of inter- and intramolecular interactions, which can be inherently complex in the condensed phase. Isolating biomolecules from the condensed phase to vacuum, via electrospray ionization (ESI), can afford precise control over experimental conditions, yielding additional structural insight. However, the loss of solvation inherent to the ESI process can drive structural rearrangement, particularly at charge sites.

Microsolvation reagents can be used to partially mimic the solvation of charged moieties in solution as they are brought into the gas phase through complexation. This serves two primary functions: 1) reducing propensity for structural rearrangement of systems …

Characterization Of Methodological Variability In Compound Specific Isotope Analysis Of Amino Acids (Csia-Aa), Audreyana Brown-Nash

Open Access Dissertations

The use of isotopes in the natural sciences stems from the principle that chemical reactions predictably alter the isotopic composition of a given sample. Recent advances in compound specific isotope analysis of amino acids (CSIA-AA) have paved the way for studies of increasingly complex ecological relationships, including the identification and characterization of organismal physiology, consumer-resource linkages, biogeochemical cycling, and movement ecology. The analytical power of CSIA-AA has caused an exponential increase in the number of application-based studies since its inception in the 1990s. With the technique constantly evolving to accommodate new research goals, it is important to understand how variation …

Incorporating Time-Varying Parameters And Climate Drivers Into Fisheries Models, Rachel Catherine Marshall

Open Access Dissertations

Commercial fishing is a highly valuable industry in the United States and globally, and as such, managing based on the best available science is necessary to maintain important fish stocks. Some parameters in stock assessment models that are assumed to be constant over age and time may actually vary to an extent that stock assessment modeling results could be improved by allowing the parameters to vary in the models. In the present dissertation, two stock assessment parameters that are typically held constant are explored for potential time or age variance. Potential environmental drivers of nonstationary parameters are also explored. Productivity, …

Physicists As Environmental Experts, Rachel Rothschild

Articles

The question of which scientists are qualified to provide expert guidance in legal controversies is a perennial debate among scholars, judges, and lawyers. Scientists who participate in legal disputes can achieve enormous power and influence, not only over the case at hand but over long-term developments in legal doctrine. While these issues arise in many areas of the law, environmental litigation has been a particularly active site of contestations over epistemic authority. Courts have frequently relied on scientists to understand whether the government is justified in regulating pollution and who may be liable for environmental and public health harms.

This …

The Future Of Ai Regulation In Drug Development: A Comparative Analysis, Gabriela Lenarczyk, Timo Minssen, W. Nicholson Price Ii, Arti Rai

Articles

As artificial intelligence (AI) transforms drug development, regulatory frameworks are evolving to oversee its implementation, particularly at the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA). This paper makes three contributions to understanding emerging regulatory approaches. First, we offer a comparative analysis of how these agencies have responded to AI-driven advances, incorporating new US executive orders and the European Union (EU)’s AI Act. Second, we propose a novel analytical framework to understand regulatory divergence: the FDA’s flexible, dialog-driven model contrasts with the EMA’s structured, risk-tiered approach, reflecting broader institutional and political-economic differences. While the former encourages …

Approaches To The Synthesis Of Highly Substituted Arenes, Kh Tanvir Ahmed

Graduate Theses, Dissertations, and Problem Reports (ETD)

While benzene rings and their derivatives are among the most frequently encountered ring systems in natural products, pharmaceuticals, agrochemicals, dyes, and functional materials, polysubstituted arenes are relatively scarce. The analysis of FDA-approved small molecules provides valuable insights into the characteristics of successful drugs while also highlighting gaps in the availability of synthetic methods capable of efficiently accessing diverse substitution patterns on aromatic rings. Highly substituted arenes are typically synthesized through sequential modification of a pre-existing benzene core; however, this stepwise approach becomes increasingly challenging with each additional substitution. An alternative strategy involves the direct construction of benzene rings via annulation …

Comparison Of Convolutional Neural Network Architectures For The Classification Of Microscopic Images: Performance Evaluation Of Lightweight Models., Cristian Ricardo Gonzalez Donoso

ICT

This study evaluates lightweight convolutional neural networks (CNNs) for multi-class classification of microscopic fungi images in CPU-only environments, addressing resource-limited laboratories and educational settings. Four pre-trained models—EfficientNetV2-B0, MobileNetV3-Small, MobileNetV2, and NASNetMobile—were compared on the DeFungi dataset (9,114 images, five fungal classes) using stratified training, realistic data augmentation, and two-stage transfer learning. Performance was measured via accuracy, macro-F1, precision, recall, and efficiency metrics including training time, inference latency, model size, and FLOPs. EfficientNetV2-B0 achieved the highest accuracy, while MobileNetV3-Small provided the best macro-F1 and lowest computational cost, making it the optimal choice for CPU-only deployment. Findings highlight the trade-off between predictive …

Improving The Completeness Of Food Composition Databases Using Predictive Analysis., Carla Arenhart

ICT

This study investigates the use of machine learning regression models to impute missing micronutrient values in Food Composition Databases (FCDBs), focusing on the FAO/INFOODS dataset. A cascading prediction methodology leverages nutrient interdependencies to systematically estimate missing values. Four models—Random Forest (RF), Support Vector Machine (SVM), Gradient Boosting Machines (GBM), and Deep Neural Networks (DNN)—were evaluated using MAE, MSE, RMSE, and R². RF and GBM achieved the highest predictive accuracy for protein, phosphorus, calcium, and magnesium, demonstrating that ML-based predictive analytics can provide a more reliable alternative to traditional imputation methods. These findings support improved dietary assessments, nutritional research, and data-driven …

Towards Developing Glut2 Specific Probes For Biochemical And Biomedical Applications, Abdelrahman Ismail

Dissertations, Master's Theses and Master's Reports

Facilitated Glucose transporters (GLUTs) are membrane proteins responsible for the uptake of simple sugars and other structurally similar metabolites in all mammalian cells. One of the hallmarks of cancer is dysfunctional sugar metabolism, known as the Warburg effect, and one of the manifestations of that effect is abnormal GLUT expression. There are 14 known GLUT proteins with different expression patterns in different tissues, and tumors tend to express certain GLUTs that are not present in surrounding healthy tissue. Therefore, selective targeting of GLUTs presents a potentially powerful tool for diagnostics and treatment of cancer and other diseases. This has been …

Hybrid Mixtures Of Factor Analyzers For High Dimensional Data, Kazeem Abiodun Kareem

Dissertations, Master's Theses and Master's Reports

Factor analysis is a powerful tool for modeling latent structures in high-dimensional data, traditional approaches assume a single global structure, limiting their ability to capture heterogeneity. The Mixture of Factor Analyzers (MFA) extends classical factor analysis by modeling data as a mixture of Gaussian-distributed local subspaces, effectively uncovering cluster-specific latent structures. However, MFA relies on Gaussian mixtures, making it sensitive to outliers and ill-suited for heavy-tailed data. The Mixture of $t$-Factor Analyzers (M$t$FA) addresses these limitations by incorporating multivariate $t$-distributions, improving robustness. Despite their advantages, both MFA and M$t$FA face significant computational challenges in high-dimensional settings, particularly due to costly …

Microwave Assisted Syntheses And Characterizations Of Near-Infrared Ratiometric Probes For Mitochondrial Ph Detection And Monitoring, Ronald J. Schwandt

Dissertations, Master's Theses and Master's Reports

Within the field of biochemistry, there has been a significant development of ratiometric fluorescent probes designed for mitochondrial pH detection; however, many of these probes have emissions within the visible spectrum and require long synthesis times with low-yield reactions. However, in recent years, microwave-assisted syntheses of organic molecules have led to significant increases in reaction yields and quicker reaction times. In this work, two common reactions in probe synthesis, Heck coupling, and Knoevenagel condensations are investigated using microwave-assisted synthesis. It was found the low-concentration Heck coupling reactions using palladium (II) acetate led to extremely efficient Heck coupling. Also, a novel …

Development Of Near-Infrared Probe For The Detection Of Nadh And Nad(P)H In Live Cells And D. Melanogaster Larvae, Sophia J. Jaeger

Dissertations, Master's Theses and Master's Reports

A near-infrared fluorescent probe, A, was designed by substituting the carbonyl group of the coumarin dye’s lactone with a 4-cyano-1-methylpyridinium methylene group and then attaching an electron-withdrawing NADH-sensing methylquinolinium acceptor via a vinyl bond linkage to the coumarin dye at the 4-position. The probe exhibits primary absorption maxima at 603, 428, and 361 nm, and fluoresces weakly at 703 nm. The addition of NAD(P)H results in a significant blue shift in the fluorescence peak from 703 to 670 nm, accompanied an increase in fluorescence intensity. This spectral shift is attributed to the transformation of A−π–A−π–D configuration to D−π–A−π–D pyridinium platform …

Dam It All: A Multi-Scalar Investigation Into The Ecological Role And Function Of Beaver Dams, Kenneth Larsen

Dissertations, Master's Theses and Master's Reports

The central theme of this dissertation is ecological scaling, which examines how small, localized features, such as beaver ponds, contribute to large-scale watershed processes and how different modeling approaches at various scales reveal distinct insights. Through a combination of probabilistic modeling and high-resolution empirical research, this work demonstrates that small ponded systems, particularly those created by beavers (Castor canadensis), serve as critical biogeochemical control points, whose contributions to sediment and nutrient dynamics have been historically underestimated.

In Chapter 1, I contextualize this research within the broader fields of freshwater ecology, watershed modeling, and ecological restoration. I introduce the …

Multiscale Computational Chemistry Studies Of The Catalytic Mechanisms Of Non-Heme Fe(Ii)/2-Oxoglutarate-Dependent Oxygenases, Simahudeen Bathir Jaber Sathik Rifayee

Dissertations, Master's Theses and Master's Reports

Enzymes catalyze complex biological transformations. Non-heme Fe(II)/2-oxoglutarate (2OG)–dependent enzymes are highly versatile catalysts capable of selective C–H oxidation, enabling transformations such as hydroxylation, halogenation, desaturation, demethylation, ring rearrangements, epoxidation, and electrophilic aromatic substitution. These enzymes are involved in various biological processes, including fatty acid metabolism, hypoxic signaling, collagen maturation, and transcriptional regulation. Computational Modeling provides detailed knowledge of the enzymes including atomistic details of the important catalytic species, conformational and electronic effects, which are crucial to enzyme engineering and drug design efforts. This dissertation implements advanced multi-scale molecular modelling techniques including Molecular dynamics and Quantum Mechanic / Molecular Mechanics calculations …

Valorizing Municipal Solid Waste For Sustainable Aviation Fuel And Polyhydroxyalkanoate Bioplastics: Pyrolysis And Microbial Pathways, Emon Das

Theses and Dissertations--Biosystems and Agricultural Engineering

The escalating global burden of municipal solid waste (MSW), projected to reach 3.88 billion tons annually by 2050, calls for innovative valorization strategies to mitigate environmental impacts and promote a circular bioeconomy. This thesis investigates the conversion of MSW into two high-value products: sustainable aviation fuel (SAF) and polyhydroxyalkanoate (PHA) bioplastics. Chapter one presents comprehensive physicochemical characterization and pyrolysis-GC/MS analysis of MSW feedstocks. The physicochemical results reveal that densification enhances handling and storage properties, while pyrolysis-GC/MS analysis indicates that plastic-rich MSW streams produce bio-oils with favorable hydrocarbon profiles suitable for SAF production, potentially contributing to decarbonization efforts in the aviation …

The Impacts Of Land Use And Groundwater Inputs On Stream Health And Habitat Of Jennings Creek, Bowling Green, Kentucky, Allison Francis

Mahurin Honors College Capstone Experience/Thesis Projects

In Bowling Green, Kentucky, the Jennings Creek watershed encompasses the entire city and surrounding area; however, little work has been completed focused on assessing the Creek’s water quality, habitat, and biological indicators. Jennings Creek is fed by several karst groundwater springs, making it highly vulnerable to contamination due to the rapid connection between the surface and subsurface via sinkholes and underground rivers. An examination of Jennings Creek’s water quality, habitat, and biological indicators provides an assessment of the watershed’s health.

The methodology closely followed the methods for assessing habitat by Kentucky’s Energy and Environment Cabinet and was approved for the …

Development Of Software For Genetic Distances, Genotyping, And Phylogenetics Using Rna-Seq Data, Andrew C. Tapia

Theses and Dissertations--Computer Science

This dissertation concerns a new application of RNA-seq data—computation of pairwise genetic distance matrices. RNA-seq captures sequences of RNA molecules in some cells or tissues of interest. RNA-seq provides data are well-suited to studies examining gene expression, and its use for this purpose is currently widespread. A pairwise genetic distance matrix, the main topic of this dissertation, quantifies differences in the genomes of every pair of samples (e.g., individuals) in a given set. Genetic distance matrices are versatile; they can be used for various kinds of downstream analyses, including genotyping, phylogenetics, and genetic diversity measurement. Although DNA sequence data are …

Communiqué: College Of Humanities, Arts & Sciences Alumni Magazine, Volume 11, 2025, University Of Northern Iowa. College Of Humanities, Arts, And Sciences.

Communiqué: College of Humanities, Arts & Sciences Alumni Magazine

Contents:

EVERY ISSUE
Message from the Dean --- 4
Donor Feature --- 5
CHAS Briefs --- 36
Class Notes --- 38

FEATURES
Engineering Advances --- 6
Japan Water Quality Trip --- 10
Theatre Outreach --- 14
A Future in Physics --- 18
International Teaching --- 24

STORIES
SLP Community Partnership --- 22
Professional Readiness --- 28
Syndaver Lab --- 30
Art Teaching Sisters --- 32
Math Alum Now NBA Coach --- 34

A Mathematical Modeling Approach To Investigate The Impacts Of Post-Infection Mortality And Partial Immunity On Disease Endemicity, Brendan M. Shrader

Honors Undergraduate Theses

A number of infectious diseases cause post-infection conditions or complications, such as COVID- 19, Q fever, and Polio. These conditions result in recovered individuals having a higher mortality rate than susceptibles, and this can impact disease dynamics. An existing mass-action model in the literature that incorporated post-infection mortality was shown to have limit cycles, or persistent oscillations, in the infected population. To better understand what causes these limit cycles, we develop and analyze a new epidemiological model with standard incidence. We show standard results, including the existence, uniqueness, and stability of the disease-free and endemic equilibria, and we rule out …

The Chemical Nature Of Colors, Bryant Corbin, Bryant Corbin

Longwood Senior Thesis Proposal

No abstract provided.

Assessing Iot Intrusion Detection Computational Costs When Using A Convolutional Neural Network, Mathew Nicho, Brian Cusack, Christopher D. Mcdermott, Shini Girija

All Works

IoT systems face vulnerabilities due to their data processing requirements and resource constraints. With 13 billion connected devices globally, this research investigates the economic viability of AI-based intrusion detection systems (IDSs), specifically analyzing the automation costs of implementing a Convolutional Neural Network (CNN) with Long Short-Term Memory (LSTM) for classifying malicious sensor traffic. This study introduces an innovative framework that evaluates six distinct architectural components of CNN and LSTM: image input processing, convolutional layer operations, max pooling layer functionality, fully connected layer characteristics, softmax output activation, and class determination mechanisms. The framework employs six metrics: matrix size, feature vector number, …

Automating The Amino Acid Identification In Elliptical Dichroism Spectrometer With Machine Learning, Ridhanya Sree Balamurugan, Yusuf Asad, Tommy Gao, Dharmakeerthi Nawarathna, Umamaheswara Rao Tida, Dali Sun

Electrical & Computer Engineering Faculty Publications

Amino acid identification is crucial across various scientific disciplines, including biochemistry, pharmaceutical research, and medical diagnostics. However, traditional methods such as mass spectrometry require extensive sample preparation and are time-consuming, complex and costly. Therefore, this study presents a pioneering Machine Learning (ML) approach for automatic amino acid identification by utilizing the unique absorption profiles from an Elliptical Dichroism (ED) spectrometer. Advanced data preprocessing techniques and ML algorithms to learn patterns from the absorption profiles that distinguish different amino acids were investigated to prove the feasibility of this approach. The results show that ML can potentially revolutionize the amino acid analysis …

An Overview Of Video Game Biometrics Collection And Considerations For Cyberbiosecurity, Lucas Potter, Christen Westberry, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Over the past fifty years, the global cost of consumer electronics has significantly decreased, leading to greater accessibility to both biosensing systems and interactive entertainment platforms. This increased access has naturally resulted in higher usage of medical and entertainment electronics. However, the intersection of these technologies, combined with invasive data harvesting practices, has raised concerns about the potential misuse of biological signals to manipulate individuals' behavior both within and beyond the video game environment. Currently, biometric data in video games are employed in various ways, such as using Heart Rate Variability (HRV) as a performance metric and integrating eye tracking …

Problem-Based Learning And Artificial Intelligence, Varna Taranikanti, Srineil Vuthaluru

Books and Book Chapters

In the current digital era, significant advancements in Artificial Intelligence (AI) have influenced various fields worldwide, particularly within the health professional education sector. This progress has also percolated into the medical education system, where Problem-Based Learning (PBL) is routinely used as a key pedagogical strategy. In PBL, students are able to fully exert their exploratory skills by solve problems through a student-centered learning approach. PBL also fosters critical thinking and encourages self-directed learning through the inquiry of clinical case scenarios. This chapter investigates the integration of AI, specifically tools like ChatGPT, into PBL frameworks to enhance learning outcomes for medical …

From Cyclones To Cybersecurity: A Call For Convergence In Risk And Crisis Communications Research, Ann Marie Reinhold, Ross J. Gore, Barry Ezell, Clemente I. Izurieta, Elizabeth A. Shanahan

VMASC Publications

Effective risk and crisis communication can improve health and safety and reduce harmful effects of hazards and disasters. A robust body of literature investigates mechanisms for improving risk and crisis communication. While effective risk and crisis communication strategies are equally desired across different hazard types (e.g., natural hazards, cyber security), the extent to which risk and crisis communication experts utilize the “lessons learned” from scientific domains outside their own is suspect. Therefore, we hypothesized that risk and crisis communication research is siloed according to academic disciplines at the detriment to the advancement of the field of risk communications research writ …

Coupling Remote Sensing And Modelling To Monitor The Spatial Distribution And Trends Of Surface Temperature And Ice Thickness On Sub-Arctic Lakes, Gifty Attiah

Theses and Dissertations (Comprehensive)

Lake surface temperature (LST), lake ice thickness (LIT), and lake ice phenology (LIP) play significant roles in the diverse regional processes of freshwater in cold regions. They offer direct indications of regional weather and climate conditions, and their interactions with the atmosphere impact climate processes. Furthermore, lake ice is valuable to northern communities, such as those in the Northwest Territories (NWT). Ice roads, including the longest ice road in the NWT, spanning over 80 lakes, are constructed during winter to haul goods to and from industrial establishments (e.g., mines) and for travel within and between communities. A significant challenge to …

Investigating The Thermal Stratification Patterns Of A Shallow Polymictic Boreal Shield Lake And The Effectiveness Of Models In Predicting Shallow Lake Thermal Profiles, Matthew Roberts

Theses and Dissertations (Comprehensive)

Thermal stratification is a core process of lakes which plays a critical role in shaping the ecological dynamics of lakes, influencing major processes like nutrient cycling and oxygen availability. For shallow polymictic lakes, thermal stratification patterns present some unique differences due to the complex and variable nature of these lakes. In this thesis, I examined thermal stratification in a shallow polymictic lake in northwestern Ontario during the ice-free season of 2019 to investigate the frequency, duration, and driving factors of thermal stratification. The lake underwent 146 separate stratification events, with a median duration of 2 hours per event, with a …

Using Landscape Ecology And Spatial Statistics To Examine The Impacts Of Proposed Removals To Natural Heritage System And The Agricultural System Of Ontario’S Greenbelt, Brianna Downey

Theses and Dissertations (Comprehensive)

The 2022 proposed removals from the Greater Toronto Area (GTA), Southern Ontario’s Greenbelt would have resulted in negative impacts including, reductions to the size and functionality of the Agricultural System and Natural Heritage System, which are components of protected Greenbelt area. Several removal sites were located either on or in close proximity to corridor areas of the NHS, reducing connectivity and negatively impacting the surrounding ecological area. The removal of Agricultural land primarily consisted of corn and soybeans, as well as large removals of woodland, wetland, and shrubland class areas. The removal sites on local Agricultural composition and configuration were …