Digital Commons Network^™

Optimizing Human Fcrn Mouse Models To Improve Pharmacokinetic Evaluation Of Antibody Drug Candidates., Gregory J. Christianson, Zachary M Howard, Samantha Kenney, Emily Lowell, Nijaguna Bethur, Derry C. Roopenian, Elena Gonzalo-Gil

Faculty Research 2026

The use of animal models that can reliably predict drug performance in human patients is critical to antibody therapeutic development. Along with assessing toxicity and efficacy, determining the pharmacokinetic (PK) properties of therapeutics in Tg32 and Tg276 mice is essential to preclinical characterization. While Tg32 mice have been well established as indispensable in their ability to model the PK properties of antibody therapeutics, their intact immunity leaves them capable of mounting anti-drug antibody responses that interfere with PK interpretation. Here, we demonstrate the negative impact anti-drug responses can have on PK parameters derived from Tg32 mice, and provide strong evidence …

Optimizing Human Fcrn Mouse Models To Improve Pharmacokinetic Evaluation Of Antibody Drug Candidates., Gregory J. Christianson, Zachary M Howard, Samantha Kenney, Emily Lowell, Nijaguna Bethur, Derry C. Roopenian, Elena Gonzalo-Gil

Faculty Research 2026

The use of animal models that can reliably predict drug performance in human patients is critical to antibody therapeutic development. Along with assessing toxicity and efficacy, determining the pharmacokinetic (PK) properties of therapeutics in Tg32 and Tg276 mice is essential to preclinical characterization. While Tg32 mice have been well established as indispensable in their ability to model the PK properties of antibody therapeutics, their intact immunity leaves them capable of mounting anti-drug antibody responses that interfere with PK interpretation. Here, we demonstrate the negative impact anti-drug responses can have on PK parameters derived from Tg32 mice, and provide strong evidence …

Sustainable – Low-Cost - Upgrade Of Activated Sludge Process For Nitrogen And Phosphorus (N&P) Removal From Wastewater, Abanoub N. Basta

Theses and Dissertations

Many municipal wastewater treatment plants (WWTPs) in developing countries were designed primarily for organic matter and suspended solids removal and therefore face increasing difficulty in meeting modern nitrogen (N) and phosphorus (P) discharge requirements. Conventional biological nutrient removal upgrades commonly require additional reactor volume, recirculation systems, aeration energy, and capital investment. Accordingly, sustainable retrofit strategies that improve nutrient removal within existing treatment footprints are increasingly needed, particularly in water-scarce and land-constrained regions.

This study investigated the integration of water hyacinth (Eichhornia crassipes) into the aeration stage of an activated sludge process as a hybrid nature-based enhancement for nitrogen and phosphorus …

Limosilactobacillus Reuteri Promotes Melatonin Release From Human Intestinal Organoids Via 5′Ectonucleotidase Activity, Micah D Forshee, Erika J Nachman, Esha R Shenoy, Heather A Danhof, Ludwig Ermann Lundberg, Stefan Roos, Robert A Britton

Faculty, Staff and Students Publications

Strains of Limosilactobacillus reuteri have been used to prevent or treat various conditions; however, the mechanisms by which they exert beneficial effects are not completely understood. Infant colic is one example in which L. reuteri DSM 17938 reduces clinical symptoms. While the etiology of colic is unknown, abnormal melatonin levels in infants have been suggested as a possible contributor. L. reuteri DSM 17938 has been shown to produce adenosine from AMP via production of the extracellular enzyme 5′ectonucleotidase (5′NT). Adenosine is a potent signaling molecule that impacts several important aspects of host physiology, including the release of melatonin from the …

Using Randomization To Compare Ai And Expert-Generated Formative Assessment Questions In Medical Education, Akshat Kumar, Katie Stinson, Litao Wang, Elizabeth Nugent, Yongsu Lee, Mark Hormann, Latanya Jones Love, Toufeeq Ahmed Syed

Faculty, Staff and Student Publications

Background: AI-generated content is being used across the education spectrum and is beneficial for creating complex multiple-choice questions, such as those used in medical education. However, evaluating AI-generated content is challenging, and existing testing and evaluation methods are falling short. This study uses randomization to compare medical students' performance on and subjective evaluation of AI versus expert-generated questions. We hypothesized that there would be no difference in student performance or subjective evaluation of AI vs expert-generated questions.

Methods: We designed a single-center, randomized study where medical student participants received either one AI- or expert-generated question per day over four weeks. …

A Comparative Study: Force Majeure And The Theory Of Unforeseen Circumstances Across Different Jurisdictions In The Middle East, Omar Hamed Sawan

Theses and Dissertations

The motivation behind this study stems from recent global disruption events that impact construction projects worldwide. These events vary across a wide spectrum, whether they are political events such as the Russo-Ukraine war or the war in the Middle East, economic events such as inflation or currency devaluations; or environmental events such as climate change and the emergence of public health crises like the Covid-19 pandemic. These series of events underscore the growing importance of understanding how the different legal frameworks address unforeseeable events in the construction industry. In this context, force majeure and the theory of unforeseen circumstances (also …

Steroid Receptor Coactivator 3-Deficient Regulatory T Cells Eradicate Multiple Solid Tumors In Syngeneic Mouse Models, Nuri Sung, Eunsu Kim, Yosef Gilad, Yuri Park, Adam M Dean, Yan Xia, Jianming Xu, Clifford C Dacso, David M Lonard, Sang Jun Han

Faculty, Staff and Students Publications

Steroid receptor coactivator 3 (SRC-3) is highly expressed in regulatory T cells (Tregs) and is important for their immunosuppressive activity. Recently, we demonstrated that disrupting SRC-3 expression in Tregs eliminates triple-negative breast cancer (TNBC) and prostate cancer in syngeneic animal models by generating an anti-tumor immune microenvironment without inducing immune-related adverse events (irAEs). Further analysis of these mice revealed that SRC-3 knockout (KO) Tregs infiltrated breast tumors and facilitated the infiltration of CD8

Enhancing Shipboard Safety Management Under The Ism Code: An Innovative Risk Assessment Framework With A Stern Tube Case Study, Pi-Yen Lin

Journal of Marine Science and Technology–Taiwan

The shipboard safety management system (SMS) is designed to enhance safe operations, risk management, and emergency response to improve overall ship safety and efficiency. This paper demonstrates the use of an engine room simulator (ERS) for collecting failure modes and applies it to a comprehensive failure analysis of the stern tube lubricating oil system. A new risk closeness coefficient method was developed, integrating expert background knowledge and weighted risk assessments. The analysis, based on multiple expert evaluations, covered five subsystems, eight main components, 23 failure modes, and 112 failure causes. This study presents 26 recommendations for maritime practitioners and onboard …

Surveillance And Comparative Genomics Of Bacteria From Hospital And Human Reservoirs, Emily E. Benedict

WUSM Theses and Dissertations – All Programs

Bacteria are diverse and adaptable and, consequently, present in a wide variety of environments. They are capable of growing under intense pressures, including those brought on by the human immune system and disinfection strategies. To survive these pressures, bacteria develop resistances. Antimicrobial resistance, which occurs when a microbe is no longer responsive to the antibiotic intended to control it, is one such adaptation that presents an especially serious threat, as it limits treatment options for infections caused by antimicrobial resistant microbes. Similarly, the ability of bacteria to survive in environments subjected to heavy disinfection efforts, such as intensive care units …

Port And Vessel Communication Traffic Intrusion Detection: A Variational Autoencoder‑Enhanced Multilayer Perceptron Approach, Chien-Lin Chiang, Hsien-Cheng Chou, Ming-Yuan Peng, Yi-Yuan Chiang, Yu-Shun Liu

Journal of Marine Science and Technology–Taiwan

Port and vessel networks increasingly operate on IP/Ethernet backbones with high‑noise, high‑dimensional traffic. We present a lightweight hybrid intrusion‑detection model that couples a variational autoencoder (VAE) with a multilayer perceptron (MLP) and augments training with a boundary‑oriented latent‑space mixup strategy. The VAE models the distribution of normal traffic and identifies anomalies through reconstruction errors. Subsequently, it generates robust latent vectors, enabling the MLP to perform highly accurate supervised classification. On the UNSW‑NB15 dataset, the proposed pipeline attains ≥97% accuracy and an outstanding recall of 99.56% in binary intrusion detection, and visualization of the latent space (PCA) together with reconstruction‑error analyses …

Sar Ship Detection Based On Shallow Feature Guidance, Chenxu Xia, Peng Chen, Ya Zhang, Ying Li

Journal of Marine Science and Technology–Taiwan

Maritime ship detection is of great significance for both military security and civilian applications. Synthetic Aperture Radar (SAR), with its all-weather and all-day imaging capability, plays a vital role in maritime surveillance. Nevertheless, SAR ship targets typically appear small in scale, embedded in complex backgrounds, blurred at boundaries, and easily confused with near-shore features, which pose substantial challenges for accurate detection. To address these issues, we propose a SAR ship detection network that integrates dual enhancements of small-object representation and edge information. The network introduces two key components: the Small Target Refine Pyramid (STRP) to strengthen shallow feature representation for …

Comparative Assessment Of Agmd And Vmd Systems Configured With Flat Sheet And Hollow Fibre Membranes: An Energy And Exergy, Thermo-Economic, And Environmental Analysis, Hamed Kariman, Mehdi Khiadani

Research outputs 2022 to 2026

Membrane Distillation (MD) systems, particularly Air Gap Membrane Distillation (AGMD) and Vacuum Membrane Distillation (VMD) in Flat Sheet (FS) and Hollow Fibre (HF) configurations, demonstrate strong potential for freshwater production, Yet, there remains a lack of comparative studies evaluating their energy, exergy, economic and environmental performance under similar conditions. This study presents a comparative analysis of four MD systems under similar operating conditions: FS-AGMD, HF-AGMD, FS-VMD and HF-VMD, and considers their respective costs and operation in Western Australia. The analysis was performed for single-stage and multi-stage configurations of up to ten modules, both with and without Heat Recovery (HR), to …

Social Procurement As A Catalyst For Dei In Construction: Some Takeaways For Hrm?, Jennifer Waterhouse, Robyn Keast, Judy Lundy, Martin Loosemore

Research outputs 2022 to 2026

Purpose: Diversity, equity and inclusion (DEI) initiatives aim to foster workplaces where all employees feel valued and can add value. Increasingly, the success of these initiatives is influenced by environments and interactions beyond organisational boundaries, including recent backlash. Despite this, most DEI research remains focused on intra-organisational aspects and human resource management (HRM) activities. The purpose of this paper is to introduce social procurement as a novel and promising framework for advancing DEI in theory and practice through a collaborative, inter-organisational approach that has the potential to overcome institutional barriers and mitigate backlash. Design/methodology/approach: Data were collected through 15 in-depth …

Public Procurement’S Role In Shaping Supply Markets: A Taxonomy Of Local Contracting Authorities’ Approaches Using The Awareness-Motivation-Capability Framework, Steven Borobia, Frederik G.S. Vos, Louise Knight, Esmee Peters, Fons Wijnhoven, Niels Uenk

Business Faculty Publications and Presentations

Purpose: Public procurement is increasingly recognised as a tool for governing and shaping supply markets. Yet we still know little about how local authorities engage in market shaping through contracting practices, especially in newly decentralized markets. This study investigates the role of awareness, motivation and capabilities (AMC) in how municipalities influence (or fail to influence) social care markets, and how these dynamics manifest in contracting practice. Design/methodology/approach We combine secondary data with semi-structured interviews conducted with procurement professionals across municipalities, regional consortia, and expert organizations. The case context is Dutch social services procurement, which transitioned to a decentralised market in …

Firms’ Darq Readiness And Marketing Implications: A Systematic Literature Review, Ali N. Tehrani, K. Roy, Richard Gruner

Research outputs 2022 to 2026

Purpose – This study aims to systematically review literature across diverse disciplines, including marketing, management and information systems, to synthesise insights on firms’ readiness to adopt and implement DARQ technologies and their marketing implications. DARQ technologies are emerging and cutting-edge technologies, including Distributed Ledger Technology, Artificial Intelligence, Extended Reality and Quantum Computing (hence, DARQ). Design/methodology/approach – Through a systematic review of over 2, 500 papers across three databases, this study distilled a focused sample of 88 papers. It comprehensively explores the reported dimensions, antecedents, outcomes and marketing implications of firms’ readiness for DARQ technologies. Findings – This study identified three …

Knowledge, Attitudes, And Practices (Kap) Of Parents Regarding The Prevention And Control Of Childhood Iron Deficiency Anemia In Egypt: A Cross-Sectional Study, Omnia Soliman

Theses and Dissertations

Childhood Iron Deficiency Anemia (IDA) remains a major public health challenge in Egypt, where its persistently high and rising prevalence carries substantial consequences for child growth, cognitive development, immunity, and long-term health outcomes. Globally, approximately 40% of children aged 6–59 months are affected by anemia (World Health Organization, 2025), and Egypt mirrors this burden, with national data showing a worsening trend in recent years. In Egypt, national strategies have traditionally focused on biomedical interventions such as iron supplementation and food fortification, while less attention has been directed toward behavioral and household-level determinants, particularly parental knowledge, attitudes, and practices (KAP) related …

The Economics Of Modern Basketball Fandom, Holden Velasco

Capstones

In an increasingly money-sucking economy, many Americans are feeling the aching of their wallets. Basketball, once serving as an escape from the outside world, has now turned into a money-making machine where fans are paying to keep it running. It’s inescapable, whether it’s the rising costs to watch the professionals, forking thousands of dollars for children to play or sports gambling being plastered everywhere. Basketball no longer feels like basketball.

Enhancing Agricultural Sustainability Under Climate Change: A Multi-Scale Framework Integrating Climate Extremes, Resource Efficiency, And Data-Driven Modeling, Shahryar Fazli

Computational and Data Sciences (PhD) Dissertations

Agricultural systems are increasingly challenged by climate variability, where shifting temperature regimes, hydrological variability, and the rising frequency of compound and cascading extremes threaten global food security and resource sustainability. Addressing these challenges requires integrated frameworks that bridge biophysical monitoring, predictive modeling, and adaptive decision-making. This dissertation develops a data-driven, multi-scale framework to quantify and enhance agricultural resilience by integrating remote sensing, climate analytics, and machine learning across the United States, with a focus on California and the Western U.S.

First, hyperspectral and thermal remote sensing data from EMIT and OpenET are integrated to characterize crop nitrogen–water interactions and assess …

Long Range Battery-Free Wireless Power Transfer Testbed For Underground Mines Iot And Lpwan Devices, Anabi Hilary Kelechi, Samuel Frimpong, Sanjay Madria

Mining Engineering Faculty Research & Creative Works

Underground mines are susceptible to occasional roof falls and cave-ins, temporarily destroying the existing wireless communications and telemetry infrastructure. During this temporary outage, intermittent provision of electrical energy wirelessly to the already deployed low-power wireless area networks (LPWAN) and Internet of Things (IoT) devices assumes a fundamental requirement. In this article, we propose and design a long-range far-field radio frequency (RF) wireless power transfer (WPT) testbed to power LPWAN and IoT devices at 35 m in an underground mines facility. Class AB external power amplifier (PA) was introduced to achieve a long-distance RF WPT, in the 880 MHz band. Thus, …

Evaluating The Impact Of Research Equipment Availability On Scientific Rigor, Reproducibility, And Innovation Across Stem Disciplines, Lyndi G. Hraban

Honors Program: Senior Projects (Public)

Research infrastructure plays a central role in shaping the quality and innovative capacity of scientific research. This study evaluates how the availability of research equipment influences scientific rigor, reproducibility, and innovation across STEM disciplines. Drawing on literature from science-to-science research, policy studies, and discipline-specific analyses, this project synthesizes existing scholarship to explore the relationship between access to infrastructure and key research outcomes. Findings across the literature indicate that access to advanced and well-maintained equipment can strengthen scientific rigor by enabling more precise measurements, improved experimental control, and the implementation of standardized research protocols. Shared and centralized facilities are also associated …

Methods For Tagging Whale Sharks: Insights Into Performance And Best Practices With A Focus On Clamp Attachments, Freya C. Womersley, Sofia Green, Alberto Garcia-Baciero, Ronan Conlon, Amy L. Jeffries, Matt J. Waller, Sara S. Ratão, Nuno Queiroz, Pedro Afonso, Gonzalo Araujo, Adam Barnett, Christine Barry, Michael L. Berumen, Farukhkha Bloch, Ginevra Boldrocchi, Camrin D. Braun, Ryan Caillouet, Constance Chapman, Jesse E.M. Cochran

Faculty Publications

Background: Biologging and telemetry have transformed our understanding of marine megafauna movement ecology. Yet, methodological constraints continue to limit data quality and deployment duration. Devices recording whale shark (Rhincodon typus) behaviours and movements have been used for decades, but they remain challenging to deploy and vary in success. Recently, spring-loaded clamp-based systems have emerged as one of the most widely used approaches to attach electronic tags to the fins of this globally endangered species. Currently, however, no consensus guidelines exist as to how to optimise this approach, potentially leading to continued underperforming deployments limiting analysis potential. Here, we synthesise experiences …

Pieces Solving A Puzzle: Emerging Roles And Cross-Field Analogies During A Distributed Epistemic Game, Jenna Matthews

All Graduate Theses and Dissertations, Fall 2023 to Present

In an effort to describe why some problems can’t be solved, a character compared them to a cubic meter of platinum - a block so dense that all the people who could squeeze around it still couldn’t lift it off the ground. In the same way, these problems simply can’t have enough people gathered around and communicating about them - and so they remain unsolved.

This research looks at the first Polymath Project (2009) as an example of a distributed epistemic game to examine how groups engage with complex problems. and without a locally omniscient individual. In this setting of …

Smart Medical System Integrating Clinical Workflows For Robust Skin Cancer Detection Across Heterogeneous Pathologies, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi

All Works

Skin cancer is among the most prevalent and life-threatening dermatological diseases worldwide, with melanoma responsible for a substantial proportion of skin cancer–related deaths due to delayed and unreliable diagnosis. Conventional clinical screening based on visual inspection and expert interpretation is inherently subjective and often affected by inter-observer variability, lesion heterogeneity, and imaging artifacts, highlighting the need for accurate and generalizable automated diagnostic systems. This study proposes a novel hybrid deep learning architecture for skin cancer classification that integrates an attention-guided autoencoder with a transformer-inspired global context modeling module, forming a unified and robust representation learning framework. The encoder–decoder structure is …

Power At Sea Develop Phase, Jake Lauer, Isabella Heinemann, Bailey Gargasz, Zachery Boyer

Mechanical Engineering

This project develops a renewable, wave-powered charging system designed to extend the mission duration of Autonomous Underwater Vehicles by eliminating the need for frequent manual battery replacement. Building upon a prior oscillating water column prototype from the CONCEPT phase, the team redesigned and tested an improved system capable of converting wave-induced air motion into electrical power using a Wells turbine. Key enhancements include doubling the column diameter to increase displaced air volume, integrating a flared inlet and bi-directional nozzle to improve airflow, and selecting corrosion-resistant materials suitable for long-term deployment in marine environments. Multiple prototypes were constructed and evaluated through …

When Lawyers Attack The Rule Of Law: The Rise Of Autocracy In America, Scott L. Cummings

Hofstra Law Review

No abstract provided.

"None Of This Is Normal": The Golden Age Of Legal Bribery, James J. Sample

Hofstra Law Review

No abstract provided.

Scalable And Interpretable Fraud Detection In Fintech: Evidence From A Hybrid Tabnet–Graph Neural Network Framework, Haseeb Ahmad, Istiaque Bhuiyan, Tanvir Bhuiyan, Ariful Hoque

Research outputs 2022 to 2026

This study proposes a fraud detection framework for FinTech that integrates tabular deep learning with relational graph reasoning. We address a key limitation of state-of-the-art tabular fraud models: their assumption that transactions are independent, despite evidence that modern fraud often arises from coordinated infrastructure reuse (e.g., shared devices, email domains, accounts, and addresses). Using the IEEE-CIS Fraud Detection dataset (≈590,540 e-commerce transactions), we develop a hybrid architecture that combines TabNet, chosen for its built-in interpretability on tabular data, with a GraphSAGE encoder trained on a leakage-free heterogeneous entity graph constructed strictly from historical training transactions. Unseen entities in validation and …

A Deep Learning Ensemble Framework For Multi-Subtype Renal Tumor Classification Using Contrast-Enhanced Ct, Hisham Abdeltawab, Ahmed Alksas, Mohamed Ghazal, Ashraf Khalil, Norah Saleh Alghamdi, Rasha T. Abouelkheir, Ahmed Elmahdy, Mohamed Abou El-Ghar, Sohail Contractor, Ayman El–Baz

All Works

Renal cell carcinoma (RCC) is considered the most aggressive and common form of renal cancer. Therefore, early detection is crucial to ensure appropriate and effective treatment planning. In our study, we propose a novel computer-aided diagnostic (CAD) approach which incorporates a deep learning ensemble to differentiate between five renal tumor subtypes, utilising the modality of contrast-enhanced computed tomography (CE-CT). The addressed renal lesions are malignant tumors (chromophobe RCC (chRCC), papillary RCC (pRCC), and clear cell RCC (ccRCC)) and benign tumors (renal oncocytoma (RO) and angiomyolipoma (AML)). Our study includes 280 patients who underwent renal biopsy, 112 patients were diagnosed with …

Integrating Machine Learning And Explainable Ai For Employee Attrition Prediction In Hr Analytics, Maytha Al-Ali, Majed Alwateer, Shatha Abed Alsaedi, Hossam Magdy Balaha, Mahmoud Badawy, Mostafa A. Elhosseini

All Works

Employee attrition poses significant challenges to organizations, impacting productivity, morale, and financial stability. Predicting attrition and understanding its underlying drivers are critical for implementing effective retention strategies. In this study, we propose a comprehensive framework that utilizes advanced machine learning techniques to predict employee attrition and job change likelihood. The framework integrates robust preprocessing pipelines, state-of-the-art predictive models, and explainability tools such as SHAP (SHapley Additive exPlanations) to ensure transparency and fairness in HR analytics. By addressing key challenges such as class imbalance, feature selection, and model interpretability, our approach provides actionable insights for proactive talent management. We evaluate the …

Engineering Sulfur Concrete Mixes: A Data-Driven Approach To Aggregate Packing And Binder Efficiency, Vasilia Al Khaldi, Abdel Hamid I. Mourad, Maisa El Gamal

All Works

Processing window (mass loss < 3%). A first-order, order-of-magnitude carbon-footprint estimate—presented with explicit caveats rather than as a full life-cycle assessment—indicates that replacing Portland cement with by-product sulfur is the dominant contributor to a substantial reduction in embodied CO₂ per cubic metre relative to equivalent-strength Portland cement concrete. The valorization of steelmaking by-products aligns with circular economy principles, enabling high-performance, recyclable, and low-carbon construction materials without chemical binder modification.