Digital Commons Network^™

Richard Victor Alvarus Mattessich [Inducted 2026], American Accounting Association

Accounting Hall of Fame Brochures

No abstract provided.

Anti-Sars-Cov-2 Nucleoprotein Iga Is Associated With Worse Disease Severity In Critically Ill Covid-19 Pneumonia Patients, David Brett-Major, Dylan S. George, Eric D. Morrell, Carmen Mikacenic, Julie Carstens, Laura E. Evans, Mark M. Wurfel, Pavan K. Bhatraju, M. Jana Broadhurst

Journal Articles: Epidemiology

While humoral responses to vaccination and infection have largely focused on IgG, there is an evolving literature on ways in which IgA may drive neutrophil activity in lung injury secondary to viral infections, including COVID-19. We evaluated 238 immune-naïve, critically ill patients in the first year of the COVID-19 pandemic. Employing a laboratory-developed, multiplexed antibody testing, clinical history, medical record, and machine learning, we pursued relationships between systemic IgA and disease severity. Individuals with elevated anti-N IgA had 4-fold odds of more severe disease. This work emphasizes the importance of continued work to understand how different elements of the immune …

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 …

Examining The Effectiveness Of Icu Diaries In Reducing Post–Intensive Care Syndrome (Pics) Psychological Symptoms: A Rapid Review Of United States–Based Studies, Lananh Tran

Honors Undergraduate Theses

Background: The growing recognition of Post-Intensive Care Syndrome (PICS) has prompted investigation into interventions, such as ICU diaries, to mitigate the long-term psychological effects of PICS. Intensive care unit (ICU) diaries – journals written by clinicians and loved ones during an ICU admission – are a tool that can help patients reconstruct the events of their critical care experience. Entries in the diary may include clinical updates, explanation of treatments, and encouraging words from loved ones or staff. Previous research in European countries found ICU diaries may be effective in reducing psychological effects post ICU admission.

Research question: The aim …

Pati Hill Collection Finding Aid, Arcadia University

Finding Aids

No abstract provided.

The New Neccesity, Ezra Rosser

Scholarly Articles in Law Reviews & Journals

According to the U.S. Supreme Court, cities are free to criminalize homelessness. The 2024 case City of Grants Pass v. Johnson is the most important homelessness case in decades and was a significant blow to advocates for the unhoused. The conservative majority rejected the idea that city ordinances criminalizing sleeping in public amounted to cruel and unusual punishment insofar as they penalized status. There is no sidestepping the loss. But within the faint glow of the embers of the oral argument and of the decision itself, there is the possibility that a new understanding of necessity, supported by the same …

Effects Of Large Woody Debris On Salmonid Spawning Habitat And Activity, Matt Knoedelseder

IdeaFest 2026

I am studying the effects of large woody debris (LWD) placement in a salmon-bearing stream in Southern Humboldt. My hypothesis is that the placement of LWD will improve salmon spawning activity by 1) recruiting and sorting appropriate gravel substrate and 2) increasing dissolved oxygen concentrations within the substrate. I predict that streams with LWD treatments will exhibit higher salmonid with abundance and density.

The Anonymous Officer, Shawn E. Fields

Faculty Scholarship

(Forthcoming 2026) Masked, plainclothes immigration agents in unmarked vans have terrorized communities in Chicago, Los Angeles, Minneapolis, and beyond. The indiscriminate violence committed by federal officers who at times appear indistinguishable from paramilitary units has forced immigrants into hiding and left lawmakers scrambling to address a growing and largely legal anonymity crisis in law enforcement. This Article explores the undertheorized implications of anonymous law enforcement, situating the rise of masked policing within a larger project of democratic retrogression and executive aggrandizement. Anonymity in policing and immigration enforcement frustrates core democratic norms of transparency, accountability, and legitimacy, providing the opacity needed …

Trump's War On Diversity, Equity, And Inclusion, Nancy C. Marcus

Faculty Scholarship

Among the many head-spinning developments that have occurred from the first days of President Trump’s second presidency are his attacks on DEI (diversity, equity, and inclusion), including anti-DEI edicts targeting educational institutions. This article provides a chronology and analysis of the early 2025 Trump administration’s attacks on DEI targeting schools nationwide, the resulting harms, and responses thereto, including litigation. A discernible refrain in the early litigation challenging President Trump’s anti-DEI attacks targeting educational institutions across the country has been how those attacks cross a clear constitutional line: the prohibition of unconstitutionally obscure governmental mandates. At its core, the void-for-vagueness doctrine …

Police Reform As System Justification, Shawn E. Fields

Faculty Scholarship

System Justification Theory (SJT) provides a useful lens through which to critique recent police reform efforts. SJT posits that members of society tend to justify and maintain existing social and political systems even when those systems disadvantage them, because the predictability of the status quo provides palliative, epistemic, and existential comfort in what otherwise appears to be an unjust and inequitable societal structure. Contrary to “false consciousness” theories, SJT claims that disadvantaged groups may intentionally rationalize what they know to be an unfair status quo, because doing so reduces social anxiety and threat while providing much desired order and meaning …

Post-Chevron Deference In Asylum Proceedings, Shawn E. Fields

Faculty Scholarship

The Supreme Court held for four decades that Chevron deference should apply in all immigration proceedings. How, then, will asylum proceedings change in a post-Chevron world? When, and under what circumstances, will courts continue to defer to the findings of immigration judges and the Board of Immigration Appeals (BIA)? And why does it matter? This Article answers those questions.

These issues require urgent examination for three reasons. First, they directly confront an issue pending before the U.S. Supreme Court in Urias-Orellana v. Bondi: Without the protection of Chevron insulating BIA decisions from meaningful judicial review, can certain legal questions like …

Rewards That Resonate- How Incentivized Online Reviews Shape Customer Loyalty And Review Outcomes, Sameeha Khizindar

Marketing Dissertations

In today’s competitive marketplace, online reviews have become a central feature of consumer decision-making and business strategy. Research consistently documents that online reviews have a positive impact on outcomes such as review volume and product sales, underscoring their critical role in shaping firm performance. However, the majority of consumers do not voluntarily write reviews, posing a challenge for companies that rely on user-generated content. To address this issue, companies often offer incentives to motivate customers to write reviews. Despite their widespread use, research on their impact remains limited. This dissertation is comprised of two essays that examine the impact of …

A Comparative View Of Artificial Intelligence Regulation In The European Union, Japan, People's Republic Of China, And The United States Of America, James Cooper, Kashyap Kompella

Faculty Scholarship

The Article analyzes the divergent regulatory architectures governing artificial intelligence across the European Union, the United States, Japan, and the People’s Republic of China, tracing their evolution from early data-protection frameworks to contemporary system-level governance. The Article demonstrates how the EU’s AI Act operationalizes a comprehensive risk-based regulatory model that imposes ex-ante obligations, categorical prohibitions, and conformity assessments to structure market behavior. The U.S. trajectory is defined by sectoral statutes, oscillating executive priorities, and a persistent absence of federal coherence, producing a permissive environment punctuated by episodic soft-law interventions and subsequent deregulatory shifts under the 2025 administration. Japan advances an …

End-To-End Development And Experimental Validation Of A 1/10-Scale Autonomous Vehicle, Rikkin Pankaj Panchal

Electrical Engineering Theses

Autonomous vehicle development demands vast resources, making scaled down platforms a critical alternative for solving core algorithmic challenges. The primary contribution of this thesis is the end to end development and validation of a complete real time autonomous driving pipeline deployed on a one tenth scale vehicle. To streamline platform development, an AI assisted annotation framework automates dataset generation, significantly reducing manual labor while improving training data quality. The system perception stack features a reinforcement learning guided online multi camera calibration framework that enables adaptive surround view stitching without the need for offline recalibration. This is paired with robust lane …

Lunch Shaming And The Right To Privacy, Ira P. Robbins

Scholarly Articles in Law Reviews & Journals

Lunch shaming is the practice of penalizing students who cannot afford to pay for their meals, resulting in them being denied food, served alternative meals, or publicly identified. The origins of lunch shaming can be traced to the financial pressures faced by school districts that struggle to balance tight budgets with the mandate to provide free or reduced-price meals to eligible students. Despite legislative efforts and advocacy campaigns aimed at mitigating the problems associated with lunch shaming, the practice persists, exacerbated by rising food costs and the expiration of pandemic-era food programs.

Many law journal and other articles have correctly …

Undermining Discretion: The Selective Attacks On Progressive Prosecutors, Angela J. Davis

Scholarly Articles in Law Reviews & Journals

Prosecutors are the most powerful officials in the criminal legal system. They decide whether to bring criminal charges and what those criminal charges should be. These decisions are totally within their discretion. The U.S. Supreme Court has consistently protected the power and discretion of prosecutors in making these decisions, and legal challenges to the exercise of prosecutorial discretion have been largely unsuccessful.

In recent years, a growing number of individuals have successfully run for chief prosecutor on platforms of reducing the prison and jail populations, consistent with public safety. They pledged to use their power and discretion to implement policies …

Originalism As Disruption, Susan D. Carle

Scholarly Articles in Law Reviews & Journals

This Article challenges the conventional understanding of originalism as a method that promotes unchanging constitutional meanings. Drawing on four and a half decades of experience since Attorney General Edwin Meese first championed originalism as a conservative project, this Article demonstrates that originalism has generally proven destabilizing rather than stabilizing to constitutional law. Landmark cases such as New York State Rifle & Pistol Association v. Bruen, Students for Fair Admissions, Inc. v. President & Fellows of Harvard College, and Shelby County v. Holder show that the Supreme Court frequently deploys originalism when it seeks to upend settled constitutional doctrine, contradicting claims …

Mechanisms Of Vascular Acetylcholine Reactivity In Cardiac Hypertrophy: The Role Of Calcium Channels And Endothelial Pi3k/Akt/Enos Signaling In Rats, Rebwar Tahir Mohammed, Ismail Mustafa Maulood

Polytechnic Journal

Cardiac hypertrophy alters vascular function and promotes myocardial damage via oxidative stress and inflammation, with calcium channels and the PI3K/AKT/eNOS signalling pathway being pivotal in vascular reactivity. Nonetheless, their precise role in acetylcholine (ACh)-mediated vascular responses during hypertrophy remains little elucidated. The study aims to investigate calcium channel functions and endothelial PI3K/AKT/eNOS signalling in modulating vascular reactivity in a rat model of cardiac hypertrophy. Aortic rings from control and ISO-treated rats were mounted in organ baths. Cumulative ACh dose–response curves (DRC) were obtained at baseline and after preincubation with Nω-nitro-L-arginine methyl ester (L-NAME), a nitric oxide synthase (NOS) blocker, PI3K …

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 …

From Financial Education To Financial Decisions: Evidence On College Financing, Personal Finance Behavior, And Student Attitudes, Dongwei Shi

University of Kentucky Doctoral Dissertations

I examine how financial education shapes students’ financial knowledge, college financing decisions, and longer-term financial behavior.

The first chapter studies whether taking high school financial education in Kentucky affects students’ college financing decisions using linked administrative records on high school course-taking and postsecondary financial aid. Using school-level financial education course availability as an instrument, the chapter evaluates whether exposure to financial education is associated with differences in student loan borrowing and receipt of need-based aid.

The second chapter examines whether exposure to state high school financial education mandates improves financial literacy and longer-term personal finance behavior among U.S. adults. Using …

Development Of A Semi-Mechanistic Population Pharmacokinetic Model For Predicting Tenofovir Disoproxil Fumarate And Tenofovir Alafenamide Exposure In Plasma And Cellular Matrices During Pregnancy And Postpartum, Yifan Yu, Kristina M. Brooks, Gustavo F. Doncel, Brookie M. Best, Mark A. Marzinke, Mark Mirochnick, Peter Anderson, Landon Myer, Connie Celum, Renee Heffron, Jenell Coleman, Dvora Joseph Davey, Craig W. Hendrix, Jeremiah D. Momper, Robert Bies, Rachel K. Scott

CONRAD Publications

Background and Objective

Tenofovir (TFV)-based regimens are backbones of both HIV treatment and pre-exposure prophylaxis during pregnancy. Multiple studies have shown up to one-third decreases in dried blood spot tenofovir-diphosphate concentrations during pregnancy among participants taking tenofovir disoproxil fumarate (TDF). Currently, there are no mechanism-based models describing the pharmacokinetics of tenofovir diphosphate (the active anabolite) in peripheral blood mononuclear cells (PBMCs) of pregnant individuals receiving TDF or tenofovir alafenamide (TAF), and the mechanisms behind observed differences between dried blood spots and PBMCs remain unclear.

Methods

To address this gap, we developed a semi-mechanistic model to simultaneously describe the pharmacokinetics of …

Elevating Teacher Agency In School Decision-Making Through Trust-Building: Applying Appreciative Inquiry Within A Mixed Methods Action Research Framework, Alison S. Bellamy

University of Kentucky Doctoral Dissertations

This mixed methods action research (MMAR) study examined how Appreciative Inquiry–based professional learning influenced relational trust, teacher voice, and teacher agency in elementary school decision-making within New Hanover County Schools. Grounded in Teacher Agency Theory, Distributed Leadership Theory, and Appreciative Inquiry, the study addressed the gap between teachers’ perceptions of trust and their opportunities to influence school-level decisions. The study was conducted across three mid-quintile elementary schools using a concurrent QUAN–QUAL design. Quantitative data was collected through pre- and post-intervention relational trust surveys. Qualitative data included focus groups, participant reflections, field notes, and collaborative dialogue from two professional learning sessions …

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 …

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. …

Monstrous Women In Greek Mythology: Victims Of The Patriarchy, Savannah Watson, Savannah Watson

Integrated Studies

This paper is an exploration into the women of Greek mythology and how they are viewed through the eyes of the patriarchy within the original texts. The focus of the paper will be on the mythological women who are considered monsters, both in a physical and characteristic sense. The women-monster hybrids will include gorgons, nymphs, sirens, furies, harpies, and specific mythological women like Medusa, Medea, Circe, Lamia, Scylla will also be discussed. By learning about who these monstrous women are and finding out why they behave in the way they had to, the analysis will reveal how the real monster …

An Optimization-Driven Approach For Accurate Prediction Of Diabetes Mellitus, H El Bouhissi, Sb Xu, John H Wang

Department of Information Management and Business Analytics Faculty Scholarship and Creative Works

Diabetes mellitus is a progressive metabolic disorder requiring timely identification to prevent severe complications and reduce healthcare burdens. This paper proposes an optimization-driven deep learning framework for accurate diabetes prediction, integrating Long Short-Term Memory selection and hyperparameter tuning. The framework is conceptualized as a decision-support system embedded within electronic health records and clinical workflows, supporting physicians, nurses, case workflow integration, governance, and privacy-are addressed to ensure alignment with real-world organizational contexts. The results demonstrate both technical feasibility and practical relevance, linking predictive analytics capability with human-AI collaboration, adoption factors, and operational decision-making in healthcare organizations.