Digital Commons Network^™

Improving Electrochemical Measurements And Informing Future Reprocessing Of Advanced Nuclear Fuels, J. Marvin Torrie

Theses and Dissertations

This research promotes the application of molten salts through developing analytical tools in electroanalytical studies and in the data analysis of vapor pressure data. The electrochemical community lacks standardized, stable, and repeatable reference electrode designs which threaten the reliability of measured thermophysical properties and repeatability of published studies. This work confirms the application of a saturated reference electrode design for molten chlorides systems that outperforms traditional Ag+/Ag reference electrodes. In the field of thermal physical property measurements, vapor pressure data for chloride salts are diffused throughout the literature, uncertainty quantification is absent or limited, and all previous studies rely on …

A Treatise On Tool Development: The Arthroscope’S Cultural, Technological, And Metascientific Translation, Montgomery F. Waterer

Honors Theses

The arthroscope was a revolutionary development in the fields of medicine, engineering, and ethics. There are many valuable lessons to be learned from the story of its development and translation that are relevant to the future of medicine and society. Beginning with a brief description of the tool’s design, this paper will examine a period within the history of the arthroscope. This window contains multiple innovators and ends with the life and work of Dr. Robert Jackson. In examining the relevant historical facts of its development, this paper will then briefly address the importance of sports medicine in the development …

Comparison Of Pfas-Free Hydrophobic Layer-By-Layer Coatings For Cellulosic Textiles: Evaluation Of Water Repellency, Mechanical Durability, And The Effects Of Fabric Construction, Elvira Isenzhulova, Radika Bhaskar

School of Design and Engineering Papers

Environmentally safe water-repellent coatings are urgently needed for the textile industry as an alternative to PFAS-based finishes. Challenges include development of coatings that are effective in imparting both water repellency and mechanical durability, with relatively simple synthesis to promote industry use. This study compared the performance and abrasion resistance of two different bio-based, layer-by-layer (LbL) self-assembled hydrophobic coatings for cellulosic fibers. Textile samples were coated with bilayers composed of negatively charged plant-derived carnauba wax and a positively charged component: either poly-L-lysine or lower-cost zinc oxide nanoparticles. To investigate the influence of surface microroughness on coating adhesion and performance, two different …

Opportunistic Breast Cancer Detection With Photon-Counting Ct: A Quantitative Pilot Study Of Reconstruction-Dependent Image Quality, Graham Hannon

McKelvey School of Engineering Graduate Student Theses & Dissertations

Photon-counting computed tomography (PCCT) has emerged as a promising imaging modality with improved spatial resolution and contrast capabilities compared to conventional energy-integrating detector systems. These advantages present an opportunity for opportunistic detection of breast cancer in routine thoracic CT scans that include breast tissue. In this pilot study, we evaluated the feasibility of opportunistic breast cancer detection using clinical PCCT data through quantitative image analysis. Two patients with confirmed breast malignancies and corresponding thoracic PCCT scans were retrospectively analyzed. Dedicated reconstructions were performed with varying convolution kernels, field-of-view sizes, and virtual monoenergetic spectra. Image quality was assessed using signal-to-noise ratio …

Analyzing Proposed Unmanned Aerial System Regulations And Their Impact On Manned Aircraft Operations, Kordell Irish

Honors Theses

The purpose of the thesis is to investigate the current state of the proposed Part 108 regulations and to find possible solutions to the problems faced by Part 108 implementation, with a focus on the interactions between manned and unmanned aircraft. The thesis covers upcoming changes to federal aviation regulations by the Federal Aviation Administration (FAA) regarding unmanned aircraft systems and their integration into the national airspace system. Currently, most unmanned aircraft systems (UAS) are regulated under Part 107 of the federal aviation regulation. A brief literature review will provide a background and timeline in the lead-up to the Part …

Erk Builds A Population Of Short-Lived Nascent Adhesions That Produce Persistent Edge Protrusion And Cell Migration, Andrew P. Shepherd, Keith R. Carney, Majid Rostami, Jakaria Shawon, Andrew Elliott, Shiela C. Samson, Sangyoon J. Han, Michelle C. Mendoza

Michigan Tech Publications

Cell migration is realized through the fast and persistent protrusion of a leading edge in the direction of movement. The actin and adhesion structures that build edge protrusions are integrated such that pro-migration signaling pathways must control both assemblies to induce protrusion. Understanding the contribution of adhesion regulation has been complicated by the inability to selectively assay the nascent adhesions that promote edge protrusion. Here, we dissect how the core RAS → RAF → MEK → ERK pathway’s control of nascent adhesions contributes to edge protrusion and cell migration by targeting an ERK FRET biosensor to adhesions and quantifying ERK’s …

Integration Of Bayesian Networks And Neural Networks For High-Dimensional Data Analysis, Cooper Schmer

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

High-dimensional biomedical datasets, such as omics data, present significant challenges for predictive modeling due to noise, redundancy, and computational complexity. This thesis proposes a hybrid framework that integrates Bayesian Networks (BNs) and Artificial Neural Networks (NNs) to improve classification performance of such data sets while reducing input dimensionality. Central to this work is a novel feature selection method based on d-separation, a structural property of Bayesian networks that encodes conditional independence relationships.

The proposed approach introduces a count-based d-separation metric to quantify the relevance of variables to a target outcome, along with a thresholding scheme to balance feature selection robustness …

Swosu Research And Scholarly Activity Fair 2026, Swosu Office Of Sponsored Programs

SWOSU Research and Scholarly Activity Fair Programs

On behalf of the University Research and Scholarly Activity Committee (URSAC) and the Office of Sponsored Programs (OSP) at Southwestern Oklahoma State University, we are pleased to welcome you to the Thirty-Fourth SWOSU Research and Scholarly Activity Fair.

Uptake And Fate Of Silver And Zinc Engineered Nanoparticles In Maize Under Single And Binary Dosing Soil Ecosystems, Lei Xu, Qingbo Yang, Xingmao Ma, Honglan Shi, John Yang, Hu Yang, Samira Mahdi, Ying Wang, Young Shin Jun

Chemistry Faculty Research & Creative Works

Recent agricultural applications of engineered metallic nanoparticles (ENPs) have raised concerns about their uptake and fate in plants. To understand this critical issue, this study investigated the fate and uptake of silver (Ag) and zinc oxide (ZnO) ENPs in maize (Zea mays L.) after single or binary ENP exposure in soil. Results indicated that both Zn and Ag elemental concentrations in roots increased with increasing ENP dosage. Ag NPs in the tissues were detected, but not Zn NPs. Ag NP concentration was 3 times higher in the roots than in the shoots at low Ag NP dosing, while Ag NP …

Evaluating The Impact Of Residential Landscape Audits Using 5-Second Water Use Data, Mahmud Aveek, Camilo J. Bastidas Pacheco, David E. Rosenberg, Jeffery S. Horsburgh, Kelly Kopp, Belize A. Lane

Civil and Environmental Engineering Student Research

We used 5-s water use data to evaluate the effectiveness of residential landscape water audits in summer 2022. Fifty-nine households in two northern Utah cities were monitored for 2–5 weeks before and 3–10 weeks after an audit. We found that the distribution of weekly irrigation volumes postaudit was statistically less than the distribution preaudit (significant at the 1.9E10-5 level). Collectively, the participants reduced their landscape irrigation water use by approximately 379,000 L per week (100,300 gal per week; 0.3 acre-feet per week). We also analyzed changes in irrigation event volume, duration, frequency, and the number of days between events at …

The Digital Neuron: Neural Cellular Automata For Neural–Symbolic Translation, Nicole Assenza

SMU Data Science Review

A neural cellular automata (NCA) architecture, referred to as Pluto’s NCA, was developed to characterize bilateral communication and semantic reciprocity between symbolic representations and a spatially distributed update field. The architecture employs an encoder–automata–decoder pipeline that maps symbolic inputs into a multichannel state field and reconstructs them through agreement-driven attractor convergence within a stable semantic attractor landscape. System behavior was evaluated under controlled perturbations, including rhythmic desynchronization, graded ablations, correlated and independent noise, and percolation-based structural degradation. Quantities such as Agreement(t), internal coherence Aᵢ(t), the recovery time constant τ, and the critical percolation threshold pc were measured to assess stability, …

Bio-Inspired Materials And Metamaterials For Tunable Biomimetic Properties In Diverse Engineering Applications, Sandeep Suresh Babu

Thesis/ Dissertation Defenses

Nature has always played the role of a design cue for several targeted engineering applications, with designers attempting to mimic the characteristics of natural organisms to have significant advantages in the engineering performance cycle. This dissertation explores the relationship between bioinspired design parameters and material compositions in diverse engineering applications, ranging from mechanical energy absorption to tissue engineering applications. A two-fold objective was followed in the study, where the initial focus was based on the structural design of metamaterial lattices based on geometrical cues observed in the horn structure of bighorn sheep and cuttlebone microstructure of cuttlefish. The advances made …

Efficient Intrusion Detection For Iomt: Integrating Machine Learning, Feature Selection, And Fuzzy Logic, Ghaida Mansour Balhareth

Electronic Theses and Dissertations

The internet of medical things (IoMT) has transformed healthcare by enabling real-time patient monitoring, remote diagnoses, and effective data exchange among connected medical devices and clinical systems. The increasing reliance on interconnected medical equipment has also intensified cybersecurity risks, as resource-constrained devices and wireless communication channels are vulnerable to attacks such as man-in-the-middle, spoofing, data injection, and ransomware. Intrusion Detection Systems (IDSs) play a critical role in mitigating these threats; however, traditional IDS approaches often struggle with high-dimensional IoMT data, class imbalance, and uncertainty in traffic patterns, which can increase false alarms and reduce reliability in safety-critical environments. This dissertation …

Toward Human-Like Robot Behavior In Co-Manipulation: Learning From Human Dyad Performance, Adam Kenneth Jackson

Theses and Dissertations

Co-manipulation requires two or more agents to coordinate through a shared object while exchanging information through motion and force. Although this capability is routine for humans, robotic systems still struggle to participate in such interaction naturally and effectively. This thesis addresses that gap by studying human co-manipulation behavior, developing methods to quantify performance, collecting a leader-follower dataset that isolates haptic communication, and training data-driven controllers from human demonstrations. First, cumulative and real-time metrics were developed to quantify human dyad performance. In particular, the behavioral modes "quickly" and "smoothly" were formulated as measurable performance objectives using completion time and squared jerk. …

Effects Of Solvent Type, Storage Time, And Storage Temperature On Free Radical Stability And Concentration In Model Radical Systems And Complex Vegetable Oil Matrices, Rachid Ismail Daboussi

Thesis/ Dissertation Defenses

Free radicals are reactive species with unpaired electrons that occur and form within a range of biological, physical, and chemical systems. These highly reactive entities can interact with each other and/or with other molecules present in a mixture, often leading to significant changes in the system. Control over free radical concentration and free radical reactions is necessary in various fields depending on the aim of the process. For instance, free radical addition reactions play an essential role in the synthesis of polymers, where controlled radical behavior is necessary. However, in the thermal cracking of oil, free radical addition reactions are …

Predictive Analytics In Oncology And Ophthalmology: Machine Learning Applications For Diabetic Retinopathy And Breast Cancer, Ali Abidalkareem

Electronic Theses and Dissertations

The convergence of artificial intelligence and healthcare represents one of the most transformative developments in modern medicine, with deep learning technologies emerging as powerful tools for addressing complex diagnostic challenges. This dissertation develops and validates machine learning frameworks that address critical challenges in medical diagnosis through innovative approaches to data augmentation, feature learning, and classification, focusing on two fundamental problems: Diabetic Retinopathy (DR) severity classification using multi-model convolutional neural networks (CNNs), and breast cancer stage identification using microRNA (miRNA) gene expression biomarkers. For diabetic retinopathy classification, this work proposes an ensemble deep learning framework that integrates Diffusion-based data augmentation for …

Electrophoretic Deposition Of Chitosan-Based Coatings On Magnesium Alloys For Implant Applications: A Review, M. H. Payampur, D. Azimi, W. W. Milligan, M. Razzaghi, H. R. Bakhsheshi-Rad, J. Drelich

Michigan Tech Publications

Magnesium (Mg) alloys are highly promising materials for biomedical applications due to their excellent mechanical properties and biocompatibility. However, their rapid corrosion in physiological environments remains a significant barrier to their use in implantable devices. Surface modification techniques, particularly chitosan (CS)-based coatings, have shown considerable potential in addressing these challenges. CS, as a biopolymer, not only reduces the corrosion rate of Mg alloys but also enhances their biological performance. Electrophoretic deposition (EPD) is a highly versatile technique that enables the uniform deposition of CS and CS-composite coatings on Mg alloys. This review provides a comprehensive analysis of depositing CS and …

Implantable, Sensor-Embedded Vascular Graft Towards Wireless Monitoring Of Stenosis, Nnamdi Dike

LSU Master's Theses

Arteriovenous (AV) grafts are commonly used to provide vascular access for hemodialysis in patients with end-stage renal disease. Despite their widespread use, AV grafts are prone to complications such as stenosis and thrombosis. Early detection of these conditions remains challenging with current monitoring methods too costly or insufficient. This work presents the design, fabrication, and validation of an LC pressure sensor embedded within a model AV graft to enable real-time monitoring. The proposed system integrates a parallel-plate capacitive pressure sensor with a spiral inductor to form an LC circuit embedded within an elastomeric graft wall. The Ecoflex 00-30 dielectric layer …

Analysis Of Soda Production Processes In Ammonia-Soda Production, Nadirbek Rustambekovich Yusupbekov Professor, Djalolitdin Paxritdinovich Mukhitdinov Professor, Fatima Faxritdinovna Iskhakova

Technical science and innovation

This paper provides a comprehensive analysis of the fundamental principles of the classical Solvay process, a key component in the industrial production of soda ash. It is noted that despite its widespread use and technological maturity, the process has a number of significant technological, energy, and environmental limitations associated with high raw material and energy consumption, the generation of significant industrial waste, and CO₂ emissions. The need to modernize the traditional production process to improve efficiency, resource conservation, and environmental sustainability is substantiated. The review systematically summarizes current approaches to process improvement, including modified versions of the Solvay process, the …

Security Risks Of Ai-Generated Code In Software Development, Maame Agyekum

Cybersecurity Undergraduate Research Showcase

Artificial Intelligence(AI) has recently forced change globally, public Institutions and as well as national security. Advancement in machine learning, mixed datasets have enabled significantly powerful systems while being capable of operating at a large scale. As innovation and technological advancement increases at rapid pace, issues like a regulation gap where scientific development far exceeds the government’s ability to regulate and establish an effective oversight. As a result, Artificial Intelligence has been controlled by private companies, leading to an industry where speed and profit often outweigh safety and ethical responsibility.

Growth Potential Of Materials For Decarbonization: Insights From The Cement Industry Value Chain, Noha Mostafa

Mechanical Engineering

To meet the Paris Agreement objectives and limit global warming to 1.5˚C compared to preindustrial levels, it is estimated that the built sector must cut its total emissions by 50% before the year 2030 and fully decarbonize it by 2050. The built environment is estimated to be responsible for 40% of global energy and emissions. These global carbon emissions include both operational carbon—the day-to-day carbon emissions generated through the operation and maintenance of buildings—and embodied carbon. With its recorded high emissions, cement manufacturing is a key area of interest for the decarbonization efforts. To meet the increasing demand for sustainably …

Deep Spiking Neural Network Autoencoders For Efficient Temporal Data Compression, Shruti Bhandari

ATU Scholars Symposium

High dimensional temporal data processing, such as that required for neuroprosthetics and remote physiological monitoring presents significant challenges for real time deployment because transmitting and storing raw signals is computationally demanding and energy intensive. Effective data compression is essential to act as a "biological zip file," reducing transmission bandwidth while preserving the critical temporal features required for accurate signal reconstruction and analysis. This study proposes a deep Spiking Neural Network (SNN) Autoencoder designed for high-fidelity data compression by utilizing the event-driven firing behavior of Leaky Integrate-and-Fire (LIF) neurons, which ensures extreme computational efficiency compared to traditional models. The model is …

Re-Purposing Pre-Existing Tilapia Aquaculture Open-Design System For Zebrafish Biomedical Research Purposes, Luke Cantu, David Sierra, Skyleigh Curtis, Maya Avila

ATU Scholars Symposium

Title: Re-purposing pre-existing tilapia open-design aquaculture systems for zebrafish biomedical research purposes.

Background: Zebrafish (Danio rerio) models are gaining popularity in biomedical research; however, the high infrastructure cost, at approximately $20,000 per unit, is a significant hurdle for primary undergraduate institutions (PUIs) establishing zebrafish facilities. This study assesses if repurposing existing tilapia open-design aquaculture systems could be a cost-effective method for zebrafish facility establishment.

Methods: Between November-2025 to February-2026, the study used a pre-existing tilapia aquaculture open-design system with personnel modified outlet filters. The water quality of this system was monitored and recorded. The study compared the stabilization phase or …

Systematic Design And Optimization Of Porous Bone Plates Using Taguchi Method And Finite Element Analysis, Aliaa A. Farraj, Tawakol A. Enab, Hanan M. Amer, Mostafa A. Elbahloul

Mansoura Engineering Journal

Solid bone fixation plates, although clinically effective, often induce stress shielding and impair periosteal blood flow due to their mismatch in stiffness with cortical bone. To overcome these limitations, this study proposes lattice-engineered porous bone plates designed to balance mechanical integrity and biological compatibility. A systematic parametric investigation was conducted by varying three design variables: crystal structure type (diamond, fluorite, and gyroid), porosity levels (50%, 70%, and 90%), and structure layout. Three-dimensional models were developed using nTopology, and finite element analysis (FEA) was performed under a static compressive load to evaluate stress distribution. A Taguchi L9 orthogonal array was employed …

Approach To Physics Education Using Local Ai With Rag For Open Educational Materials Generation, Dmitriy Beznosko

All Things Open

The new tool that starts to enter all parts of our life is AI – and it enters education as well. There are two standing large concerns with using AI for education – the safety of students’ data and the AI missing specific knowledge about the given class. The approach of using the Retrieval Augmented Generation (RAG) provides the user data to the locally run LLM model (using Ollama framework, a free and open-source tool that allows you to run large language models locally on your system) as a context for the generation of the OER materials. As this AI …

Biomass Demineralization: A Critical Need For Future Biorefineries, Leoncio Santiago-Martínez, Styliani Avraamidou, Alejandro Ayala-Cortés, Ruth Azike, Santanu Bakshi, Chumki Banik, Ezra Bar Ziv, Fei Long, Rebecca Ong, Et Al.

Michigan Tech Publications

Biomass contains up to 14 essential elements that serve as nutrients for plant growth and development, including photosynthesis and enzyme functionalities. These elements in different chemical forms (e.g., minerals) constitute the inorganic fraction of biomass and can cause operational issues in thermal and biochemical biomass conversion technologies. In biomass gasification and pyrolysis processes, for instance, inorganics can cause fouling, tar formation, and corrosion. In catalytic and biochemical processes, inorganics can poison catalysts, alter biochemical pathways, and modify product yields and selectivity. This review provides an overview of the inorganic content in biomass feedstocks, the critical role inorganics play in plant …

Analysis Of The Effects Of Magnetic Field, Heat Transfer, And Thermal Radiation On Blood Flow Through Bifurcated Artery To Enhance Tumor Treatments, Abdullahi Isah, Dauda Gulibur Yakubu, Ali Musa

Tanzania Journal of Science

The work presents the effects of some pertinent parameters on blood flow through bifurcated artery to enhance tumor treatments. Combining appropriately the basic equations, together with the fractionalized Maxwell fluid model allow us to determine the velocity, temperature and concentration of blood flow through bifurcated artery. The study adopted the Atangana-Baleanu fractional time derivative on fluid model to describe the non-Newtonian behavior of blood flow. The numerical simulations were performed using the combined Laplace transform and the method of undetermined coefficients and the results obtained with the aid of Mathcad software were simulated and presented graphically. From the graphical results, …

Self-Assembly Interactions In Magnetite-Coated Cellulose Nanocrystals: Implications For Magnetic Hyperthermia Applications, Mohammad J. Hasan, Erin L. Mcneill, Kishore Chand, Juganta Roy, Monishita Deb, Katherine Schlaak, Sydney Herzog, Yvonne Sun, Sarah Watzman, Esteban E. Ureña-Benavides, Erick S. Vasquez-Guardado

Chemical and Materials Engineering Faculty Publications

Magnetic cellulose nanocrystal (MCNC) nanocomposites are promising sustainable and biocompatible platforms for magnetic hyperthermia; however, the molecular mechanisms governing Fe3O4 adsorption and deposition onto CNCs remain poorly understood. Here, sulfated (S-CNC) and TEMPO-oxidized CNCs (T-CNC) were used to prepare nanocomposites at 1:2 and 1:4 CNC:Fe3O4 mass ratios, enabling a systematic evaluation of how surface chemistry and nanoparticle loading dictate interfacial interactions and magneto-colloidal behavior. Bare magnetite nanoparticles were 21 ± 5 nm by TEM but grew to 144 ± 18 in the DLS measurement at pH 7. The S-CNC nanocomposites had hydrodynamic sizes between 144 and 210 nm, not much …

Ai Method For Classification Of Diagnosis Of Near-Infrared Breast Lesion Images, Kaiquan Chen, Fangyang Shen, Honggang Wang, Zhengchao Dong, Jizhong Xiao, Ming Ma, Afroza Aktar, Christopher Chow, Wenxiong Zhang

Publications and Research

In near-infrared optical breast lesion screening and diagnosis systems, high-speed four-dimensional scanners can dynamically acquire tens of thousands of lesion images within a five-minute period. Currently, manual computer annotation is required to generate standard samples from these scanned breast lesion images, a process that depends heavily on physicians with clinical expertise. On average, a single physician can annotate only approximately ten samples per working day. As a result, this process is time-consuming and labor-intensive, and the collected samples often suffer from low accuracy, large variability, and limited diagnostic reliability. Several AI-based annotation tools, such as QuPath, HALO AI™, and X-AnyLabeling, …

Behavioral Biases As Drivers Of Complexity In Stock Markets: An Agent-Based Modeling Approach, David Joseph Dr, Alwin Joseph, Blesson James, Kajal Dass

Northeast Journal of Complex Systems (NEJCS)

By modeling financial systems as Complex Adaptive Systems, this study investigates how behavioral biases influence emergent complexity in stock markets. The study integrates heterogeneous agents, such as rational traders, herding agents, overconfident traders, and anchoring/disposition-driven investors, within a Limit Order Book framework calibrated to both U.S. and Indian market conditions using an Agent-Based Modeling (ABM) approach implemented through the high-fidelity ABIDES simulation environment. Price dynamics, volatility patterns, and liquidity structures were analyzed by Monte Carlo simulation experiments with different behavioral compositions. The results show that behavioral biases cause nonlinear price reactions, produce heavy-tailed return distributions that distort order-book complexity, and …