Engineering Commons^™

The Effects Of Membrane Structure And Filtration Conditions On Virus Filtration, Wenbo Xu, Xianghong Qian, Hironobu Shirataki, Daniel Strauss, Sumith R. Wickramasinghe

Biomedical Engineering Faculty Publications and Presentations

Virus filtration is used for validation of virus clearance in the manufacture of monoclonal antibodies. Requirements for this size exclusion process include 10,000-fold reduction of virus particles and at least 95 % recovery of the monoclonal antibody in the permeate. The size difference between the rejected parvovirus particles, 25 nm, and monoclonal antibody, 10-12 nm, is about two. Membranes are designed with pore sizes around the average size of the parvovirus. Given the polydispersity in membrane pore size and virus particles, filter performance is dependent on membrane properties, feed and operating conditions. Compromised performance usually occurs due to product related …

Development Of Alternative Plasma Etching Techniques For The Selective Removal Of Tan With Respect To Sioch Dielectric Materials To Enable Future Back-End-Of-The-Line Scaling, Ivo Otto Iv

Electronic Theses & Dissertations (2024 - present)

Transistor scaling has continued according to Moore’s Law for over fifty years. As transistor size decreases, adequate power delivery is required to enable transistor scaling without performance loss. Power delivery is provided by a metal interconnect network with insulating dielectric that connects the transistor level to the power source, the signal speed within this metal line network limiting transistor level switching speeds. Reduction of signal delay has moved from primarily dimension-based improvement towards adoption of conductor and dielectric materials with lower resistivity and a reduced dielectric constant value, respectively: transitioning from Al/SiO₂ to Cu/low-κ SiOCH. With this transition comes …

Solar Charging Chair, Joseph Austrian , ‘26, Jude Hemmins , ‘26, Neghemi Micah , ‘26

Senior Theses, Projects, and Awards

For our E90 project, we constructed an outdoor Adirondack-style chair with a built-in battery and solar panel, so users can charge their devices while sitting outside. Through data collection and analysis, we were able to verify that our solar energy system, consisting of a 30W panel, 96Whr battery, MPPT charge controller, and DC-AC inverter, performs better than theoretically expected. The chair was built using pressure-treated lumber with the electrical components in a weatherproof box and solar panel attached to the back rest. The total cost was $667.15.

Handwriting Recognition In Vr, Dominique Mosley

EWU Masters Thesis Collection

Virtual Reality (VR) is slowly becoming more popular for more than just entertainment. VR can be found in educational, office, and even healthcare settings to help discover more intuitive ways to teach, collaborate, and treat patients. Outside of the virtual world, these environments typically rely on writing for communicating or note-taking. Currently, VR input forces users to rely on clunky on-screen keyboards which disrupts the user’s immersion and breaks the flow of natural interaction. This thesis explores the potential of VR as a learning platform by combining it with artificial intelligence (AI). It aims to develop a VR-enhanced handwriting practicing …

Yk-4-250 Mitigates Gastrointestinal Radiation Syndrome And Promotes Overall Survival Following Partial Body Radiation Injury, Vidya P. Kumar, Yali Kong, Kan Wang, Asa R. Britton-Jenkins, Stanton Dulan, Landon L. Moore, Debra Saunders, Randal May, Rheal Towner, Sanchita P. Ghosh, Courtney W. Houchen, Milton L. Brown

Department of Biomedical and Translational Sciences Faculty Publications

Acute gastrointestinal radiation syndrome (GI-ARS) is a significant health threat following high-dose ionizing radiation (IR) exposure, leading to severe morbidity and mortality. The syndrome is characterized by gastrointestinal tissue damage caused by angiotensin II (Ang II) and reactive oxygen species (ROS), resulting in impaired GI function, systemic bacteremia, multi-organ failure, and eventual death. Dysregulation of the renin-angiotensin system (RAS) via Ang II exacerbates ROS production through activation of the Angiotensin II type 1 receptor (AT1R). This underscores the need for agents capable of both scavenging ROS and inhibiting AT1R activity. To address this, we developed YK-4-250, a Tempol-conjugated angiotensin receptor …

Yk-4-250, A Synthetic Telmisartan-Tempol Conjugate: Crystal Structure Of A Stabilized Free Radical Containing An Angiotensin At₁ Receptor Inhibitor, Simon Friedrich, Yali Kong, Faik N. Musayev, Milton L. Brown, B. Frank Gupton

Department of Biomedical and Translational Sciences Faculty Publications

We report the first crystal structure of the telmisartan-tempol conjugate 2,2,6,6-tetramethyl-1-(λ'-oxidaneyl)piperidin-4-yl 4'-[(1,7'-dimethyl-2'-propyl-1H,3'H-[2,5'-bibenzo[d]imidazol]-3'-yl)methyl]-[1,1'-biphenyl]-2-carboxylate free radical (YK-4-250, C₄₂H₄₆N₅O₃), a dual-function inhibitor designed to target both the angiotensin II type 1 receptor (AT₁R) and reactive oxygen species (ROS). Structural analysis reveals a unique crystal architecture in which the nitroxide radical is stabilized within a sterically protected environment while preserving the telmisartan pharmacophore essential for high-affinity receptor antagonism. YK-4-250 is a novel small-molecule conjugate of telmisartan and tempol that incorporates a catalytic stabilized nitroxide radical and was rationally designed to mitigate gastrointestinal acute radiation syndrome (GI-ARS).

Learning-Based Graph Shrinking For Quantum Optimization Of Constrained Combinatorial Problems, Monit Sharma, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Graph shrinking has recently emerged as a powerful preprocessing technique for hybrid classical–quantum optimization, enabling variable and constraint reduction before quantum solving. Conventional approaches rely on Semi-Definite Programming (SDP) relaxations to compute vertex correlations, but these methods suffer from high computational overhead, instance-specific tuning, and limited generalizability. In this work, we replace the handcrafted SDP correlation stage with a reinforcement learning (RL) based correlation estimator, trained to predict merge quality directly from graph structure. We reformulate the graph shrinking process as a Markov Decision Process (MDP), design a Graph Neural Network (GNN) policy to guide vertex merging, and integrate the …

Hybrid Learning And Optimization Methods For Solving Capacitated Vehicle Routing Problem, Monit Sharma, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We propose a hybrid quantum–classical framework for the Capacitated Vehicle Routing Problem (CVRP) that integrates the Augmented Lagrangian Method (ALM) with deep reinforcement learning (RL). Directly solving CVRP via Variational Quantum Eigensolver (VQE) requires a slack-based QUBO formulation, where converting inequalities to equalities greatly increases the qubit count. To circumvent this, we employ an ALM-based reformulation that enforces constraints through Lagrange terms instead of slack variables, drastically reducing quantum resource demands. An RL agent, trained with Soft Actor–Critic, adaptively tunes the Lagrange penalties to improve convergence and feasibility. Experiments show that RL-Q-ALM outperforms static-penalty and plain VQE baselines in both …

Experimental Investigation Into The Effects Of Air Staging On Fouling In A Fixed-Bed Biomass Combustor, Akram Elsebaie

Theses: Doctorates and Masters

Biomass offers significant potential as a sustainable and renewable substitute for fossil fuels in energy generation, playing a critical role in the reduction of global warming. However, despite its environmental benefits, biomass combustion faces persistent operational challenges, particularly fouling, which reduces efficiency and increases maintenance costs. Although fouling mechanisms have been studied in various combustion systems, there is limited research which addresses its formation and behaviour in fixed-bed biomass combustors under different air staging conditions. This research investigates fouling behaviour in a counter-current combustor, focusing on the influence of design (secondary air location), operational (air staging flowrates between the primary …

Synergistic Removal Of Microplastic Fibres: Integrating Chitosan Coagulation In Hybrid Water Pre-Treatment Systems, Jayasuriya Arachchilage Nimesha Thathsarani

Theses: Doctorates and Masters

Microplastic fibres (MPFs) are the most prevalent form of microplastics detected in the influents of water and wastewater treatment plants. Owing to their elongated shape and low density, MPFs frequently evade removal even during tertiary processes such as membrane filtration. Enhancing pretreatment, particularly through cost-effective coagulation-flocculation can reduce the treatment burden on downstream systems. However, conventional inorganic coagulants often necessitate high dosages and can leave residual ions, posing environmental concerns.

As a sustainable alternative, the use of environmentally friendly coagulants such as Chitosan has gained attention for MPF removal. While Chitosan exhibits favourable qualities, its practical application is hindered by …

Plant-Wide Process Modeling, Techno-Economic Optimization, And Bayesian Uncertainty Quantification For Manufacturing Value-Added Products From Lignocellulosic Biomass, Poulomi Das

Graduate Theses, Dissertations, and Problem Reports (ETD)

For decades, many chemicals have been produced from fossil resources, contributing to resource depletion, pollution from extraction and refining, and hazardous byproducts. Growing environmental concerns and declining fossil reserves have intensified the search for sustainable sources of fuels, energy, and chemicals. Lignocellulosic biomass, the only abundant renewable carbon source, is therefore being explored as a feedstock for second-generation biofuels and high-value chemicals.

Currently, global wood-panel industry heavily depends on petroleum-derived commercial adhesives like phenol-formaldehyde, urea-formaldehyde, etc. These formaldehyde-based chemicals cause hazards to both human health and environment through emission of toxic volatile organic compounds. Typically, lignin is considered as one …

Architecture And Mechanistic Engineering Of Nanocomposite Steam Electrodes For High-Performance Metal-Supported Protonic Ceramic Cells, Xuemei Li

Graduate Theses, Dissertations, and Problem Reports (ETD)

The advancement of proton-conducting ceramic cells (PCCs) is crucial for efficient energy conversion in hydrogen- and/or ammonia-based energy carrier systems. However, a bigger success requires significant progress in cell fabrication, interfacial stability, fast electrode kinetics, and high Faradaic efficiency. This study investigates the rational design, fabrication, and performance breakthroughs of PCCs, with a focus on electrode architecture engineering, material interfacial coupling, and mechanistic understanding of electrochemical processes.

The metal-supported fuel electrode structure of PCFCs was systematically optimized, revealing the significant influence of Ni diffusion on cell performance and durability. High power density and stable ammonia-fueled operation were achieved. A heterointerface-rich …

Multi-Sensor Fusion For Manual Wheelchair State Estimation, Kathylee Pinnock Branford

Graduate Theses, Dissertations, and Problem Reports (ETD)

Kathylee Pinnock Branford Manual wheelchairs are essential to mobility and independence, yet accurately characterizing wheelchair motion in real-world environments remains challenging. Inertial measurement units (IMUs) provide a practical means of estimating wheelchair kinematics, but existing trajectory-reconstruction studies have largely been limited to short, controlled trials. This report developed and evaluated a four-IMU framework comprising one sensor on each rear wheel and two sensors on the wheelchair frame. Three orientation algorithms (VQF, Mahony AHRS, and Madgwick AHRS), two accelerometer ranges (±2 g and ± 4 g), and calibrated and uncalibrated sensor data were evaluated during indoor motion-capture trials and a outdoor …

Physics-Informed Machine Learning Methods To Predict Heavy-Duty Diesel Engine Performance And Emissions, Sandeep Guguloth

Graduate Theses, Dissertations, and Problem Reports (ETD)

The development of internal combustion engines for increased efficiency and reduced emissions demands improved design tools that are cost-effective, fast, and easy to integrate into existing engineering workflows. Low-dimensional physically based engine models serve this role by reducing the need for iterative experimental prototyping but historically rely on empirical correlations that sacrifice fidelity compared to CFD. Machine learning (ML) approaches, conversely, achieve high predictive accuracy but lack interpretability and generalize poorly beyond their training data. Physics-informed machine learning (PIML) bridges this gap by constraining the solution space to physically feasible predictions, offering a more reliable way to model in-cylinder phenomena. …

Swarm Of One: Self-Organization In Multicellular Robots, Trevor Riley Smith

Graduate Theses, Dissertations, and Problem Reports (ETD)

Designing robots traditionally relies on centralized, top-down methods that constrain adaptability and resiliency, producing systems optimized for specific tasks. However, such systems often fail in complex environments, such as extraterrestrial, disaster, or natural settings, where designers cannot foresee every scenario a robot may encounter. Achieving autonomy in these contexts requires robots that are resilient and capable of adapting to the unknown. Multicellular organisms exhibit this adaptability through self-organization, where complex structures and behaviors emerge from local interactions among their cells. Such organisms can be viewed simultaneously as a single entity and a swarm of cooperating cells, i.e., a Swarm-of-One.

This …

Process Optimization And Quality Control In Manufacturing Of Frp Composites By Vartm, Mohamed Emadeldin Omar Abdelhadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Railroad tank cars, being one of the most used means of transportation of hazardous material across the country, have not been structurally upgraded for a long time. Thus, the Pipeline and Hazardous Materials Safety Administration (PHMSA), a United States Department of Transportation (USDOT) agency, released a rule for safer transportation of highly hazardous and flammable liquids by railroad to enhance the design specifications of both the new and existing tank cars in May 2015. A multifunctional composite jacket is proposed as a new material to structurally enhance the railroad tank cars to withstand any accidents that could happen en route. …

Semantic-Weighted Lidar–Camera Slam For Robust Mapping In Vegetation-Rich Environments, David Aigbovboise Akhihiero

Graduate Theses, Dissertations, and Problem Reports (ETD)

Many LiDAR odometry and SLAM methods are lightweight and effective, but they assume that all LiDAR point returns are equally reliable. In practice, this assumption is often violated in vegetation rich or semi transparent environments, where in a single beam footprint, LiDAR beams may intersect multiple scattering surfaces like leaves, branches or glass. These ambiguities in returns produces probabilistic or biased range measurements that violate the assumptions of most geometric registration frameworks and can lead to drift and inconsistency.

To address this challenge, this dissertation proposes a semantic-weighted LiDAR-camera SLAM framework that integrates class dependent weights into a front-end LiDAR …

Ai-Based Smart Proxy Models For Flow Assurance, Integrating Oil Rate Prediction, Pipeline Monitoring, And Leak Detection, Ali Sajedian

Graduate Theses, Dissertations, and Problem Reports (ETD)

Oil and gas pipeline networks operate under complex multiphase flow conditions and dynamic transient regimes that present significant challenges for traditional monitoring, anomaly detection, and operational decision-making methodologies. Many existing monitoring approaches rely on high-fidelity physics-based transient flow simulations to accurately represent system behavior. However, these models are computationally intensive and therefore difficult to implement in real-time operational environments.

This dissertation presents a physics-guided artificial intelligence framework for intelligent pipeline monitoring and integrity management based on the concept of Smart Proxy Modeling. By integrating first principles engineering knowledge with machine learning techniques, the proposed framework develops computationally efficient surrogate models …

Development Of A 3d-Printed Hemodynamic Model To Characterize Doppler Signatures Of Obstructed Tapvr, Michael R. Turner, Maher R. Saadeh, Holly D. Bauser-Heaton, Vahid Serpooshan

Summer Research Program Abstracts

No abstract provided.

Bioprinted Scaffolds For Investigating Fibroblast Alignment, Lillian Thro, Daeha Joung Ph.D.

UROP Posters

Fibroblasts play a vital role in tissue repair, ECM remodeling, and maintaining structural integrity in human tissues. However, their behavior in engineered 3D microenvironments remains poorly understood. Traditional 2D cultures fail to capture the complex cell-cell and cell-matrix interactions that govern fibroblast alignment, migration, and proliferation in vivo. To address this gap, this project uses bioprinted scaffolds that mimic native ECM structures and provide a platform for studying fibroblast behavior in controlled microenvironments. The project focuses on varying scaffold channel properties—such as width, depth, and geometry—to investigate how physical cues influence fibroblast organization and collective migration. A biodegradable gelatin-based ECM …

Infrared Simulation, Sophia Zhou, Ashton Hoo, Tyler Ricks, Sebastian Fox, Kathy Phu

UROP Posters

Infrared image recognition is more difficult than visible-spectrum recognition due to limited high-quality training data. This project addresses that challenge by generating simulated infrared images using temperature-driven rendering in Unreal Engine and other 3D software. These simulations can support applications such as health monitoring, heat detection in mechanical and structural systems, thermal regulation, and engineering process control.

Mapping Leo Satellite Internet Performance Using Mobile Starlink Deployment, Annika Govil, Jacob Gray

UROP Posters

High-speed, low-latency internet connectivity on the move is a critical challenge for applications in connected vehicles, disaster response, and remote education. While terrestrial networks such as 4G or 5G are widespread, they lack coverage in remote or rural geographic areas.

Low Earth Orbit (LEO) satellite constellations, such as SpaceX's Starlink, promise global high-bandwidth, low-latency internet. However, their performance is well-documented in stationary scenarios, while data for *mobile* applications is scarce. This project explores the feasibility and real-world performance of LEO satellite internet while in motion.

Current research documents the performance of LEO satellite constellations in stationary settings. However, data concerning …

Using Nature-Inspired Sustainable Design Via Biomimicry Of The Peregrine Falcon To Improve The Development Of Japan’S F-X Fighter Jet, Tvisha Datta

UROP Posters

Modern fighter jets face a persistent challenge when it comes to improving aerodynamic efficiency without having to sacrifice high-speed performance or long-term sustainability. These aircraft rely heavily on high thrust and agility, and in doing so, they consume substantial amounts of fuel due to aerodynamic drag and limited energy efficiency. As a result of these constraints, advanced military defense development projects, such as Japan’s Mitsubishi F-X fighter jet program, have been delayed. This highlights the need for more sustainable solutions. Biologically inspired design, or biomimicry, has emerged as a potential and promising alternative. The peregrine falcon, notably the fastest bird …

C.A.S. Full Assessment Report: State Of Florida Government Portal, Delante Clark

Graduate Scholarship and Creative Works

The purpose of this assessment is to evaluate the cognitive overhead, transparency, and attentional integrity of

official State of Florida digital interfaces using the Cognitive Attentional Standards (C.A.S.) platform.

While the Florida Digital Bill of Rights (FDBR) establishes strict regulatory guardrails for consumer data

transparency, tracking opt-outs, and attentional safeguards, the State of Florida explicitly exempts its own

government agencies, public universities, and non-profit entities from complying with these rules.

This assessment serves to investigate the tension between legislative intent and government execution. By

analyzing public sector websites through the C.A.S. platform, this project will establish a “state-enforced vs.

state-executed” …

A Novel Federated Llm Framework For Distributed Traffic Modelling In Intelligent Transportation Systems, Seerat Kaur

Theses and Dissertations (Comprehensive)

Intelligent transportation systems (ITS) depend on accurate traffic prediction to support congestion management, infrastructure planning, and real-time operational decisions. Despite substantial progress in data-driven forecasting, several challenges continue to limit practical deployment: traffic data is distributed across independent regional authorities, making centralized aggregation infeasible, standard federated aggregation strategies ignore traffic-specific characteristics that meaningfully affect model quality, and existing models produce only numerical outputs without interpretable reasoning that urban planners can act upon. This thesis addresses these challenges through four contributions that collectively advance privacy-preserving, explainable, and scalable traffic forecasting.

The first contribution provides a systematic review of 129 peer-reviewed publications, …

Taylorkan-Vit: Parameter-Efficient Vision Transformers For Medical Image Classification, Kaniz Fatema, Dr. Emad Mohammed, Dr. Sukhjit Singh Sehra

Theses and Dissertations (Comprehensive)

Effective and interpretable classification of medical images remains a critical challenge in computer-aided diagnosis, particularly in data-scarce and resource-constrained clinical settings where traditional deep learning models prove impractical. This study addresses the fundamental barrier to Vision Transformer adoption in medical imaging—massive parameter counts and data requirements—through a systematic two-phase methodology. Phase 1 evaluates three spline-based Kolmogorov–Arnold Network (KAN) variants to identify the optimal nonlinear approximation function for parameter-efficient medical image classification: SBTAYLOR-KAN (B-splines with Taylor series), SBRBF-KAN (B-splines with Radial Basis Functions), and SBWAVELET-KAN (B-splines with Morlet wavelets). Comprehensive experiments across brain MRI, chest X-rays, and tuberculosis datasets—without any image …

Circulating Biomarker Results From A Phase 2 Study Of Seralutinib In Pulmonary Arterial Hypertension, Robin Osterhout, Athénaïs Boucly, Raymond L. Benza, Richard N. Channick, Kelly M. Chin, Robert P. Frantz, Anna R. Hemnes, Luke S. Howard, Vallerie V. Mclaughlin, Olivier Sitbon, Jean-Luc Vachiéry, Rotham T. Zamanian, Richard Aranda, Matt Cravets, Zhaoqing Ding, Thao Duong-Verlé, David Mattola, Robert F. Roscigno, Ravikumar Sitapara, Lawrence S. Zisman, Jean-Marie Bruey, Hossein-Ardeschir Ghofrani

Department of Medicine Faculty Publications

[Introduction] To the Editor: Pulmonary arterial hypertension (PAH) is a progressive disease characterized by obstructive pulmonary arterial remodeling (1). Seralutinib, an investigational inhaled tyrosine kinase inhibitor, potently and selectively targets kinases relevant to PAH pathobiology including platelet-derived growth factor receptors (PDGFR) α and β, colony stimulating factor 1 receptor (CSF1R), and mast/stem cell growth factor receptor kit (c-KIT) (2). In preclinical models, seralutinib improved cardiopulmonary hemodynamics, reversed pulmonary vascular pathology and decreased right ventricular hypertrophy (3). In TORREY, a phase 2, multicenter, double-blind, randomized, placebo-controlled trial in PAH, seralutinib significantly reduced pulmonary vascular resistance (PVR) after 24 weeks with good …

Dietary Intake Of Micro- And Nanoplastics: Potential Adverse Gi Effects On Microbiome, Inflammation, And Neoplasia, Michael Saadeh, Gordon Hong, Sana Rabeeah, Priyata Dutta, Edward C. Oldfield, Iv, David A. Johnson

Department of Medicine Faculty Publications

Micro- and nanoplastics (MNPs) are pervasive in food-contact environments and the human diet, positioning the gastrointestinal (GI) tract as the primary portal of entry and a plausible site of early biological effects. Human exposure is supported by detection of microplastics in stool and colon tissue, and emerging clinical studies report associations between fecal microplastic burden and GI disease states, including inflammatory bowel disease (IBD) and colorectal cancer (CRC). Preclinical studies provide mechanistic plausibility, reporting that ingested MNPs can modulate microbial ecology, alter mucus membrane integrity, increase intestinal permeability through changes in cellular tight junction biology, and induce inflammatory gene expression. …

Performance Assessment And Design Improvements For An Urban Coastal Detention Basin Under Intensifying Rainfall Extremes, Imiya Mudiyanselage Chathuranika, Agyare Asante, Faeghe Borhani, Xixi Wang, Mujde Erten-Unal, Dalya Ismael

Civil & Environmental Engineering Faculty Publications

Coastal urban areas are increasingly exposed to flooding driven by more frequent and intense rainfall events, rising sea levels, and expanding impervious surfaces. Norfolk, Virginia, a low-lying coastal city with aging stormwater infrastructure, faces heightened vulnerability to these hydrologic pressures. This study evaluates the hydraulic performance of an existing urban detention basin within the Edgewater–Larchmont catchment under 10-, 50-, and 100-year, 2-h design storms using the U.S. Environmental Protection Agency’s Storm Water Management Model (SWMM). Simulations were conducted for both pre- and post-development conditions to assess changes in peak discharge, storage capacity, and water level dynamics. Results show that urbanization, …

Optimizing Maintenance Routes For Highway Infrastructure Using Leader-Follower Autonomous Vehicles, Qing Tang, Chenxi Chen, Xianbiao Hu, Yuxin Ding, Tianjia Yang

Civil & Environmental Engineering Faculty Publications

The Autonomous Truck Mounted Attenuator (ATMA), a leader–follower style connected and automated vehicle system, enhances safety during transportation infrastructure maintenance in work zones. However, the significantly lower speed of ATMA, compared to regular vehicles, causes moving bottlenecks that reduce roadway capacity and prolong queuing, leading to further delays. Different ATMA routes lead to varying patterns of time-dependent capacity drop, affecting the user equilibrium traffic assignment and resulting in differing system costs. This study aims to optimize ATMA routing within a network to minimize the system cost associated with its slow-moving operation. To this end, a queuing-based traffic assignment approach is …