Digital Commons Network^™

Intelligent Microfluidic Systems For Precision Manipulation And Real-Time Recognition Via Dielectrophoresis And Deep Learning, Negar Danesh

Mechanical and Aerospace Engineering Dissertations - Archive

This dissertation introduces intelligent microfluidic platforms by combining advanced DEP-based manipulation with real-time visual feedback. A DEP device featuring circular corral traps and dual-plane electrodes enables precise submicron particle trapping, high-resolution particle separation, and cell-particle co-assembly. Simulations and experiments confirm enhanced electric field control and stable confinement. To enable adaptive operation in EWOD systems, a deep learning model (U-Net) was developed for real-time droplet meniscus segmentation. The model achieved 98% accuracy and remained robust under noisy, low-contrast conditions. A live video pipeline was implemented, enabling consistent frame-by-frame feedback for closed-loop control. Together, these innovations establish a foundation for autonomous, high-performance …

Deep Neural Network Models For Heatsink Performance Prediction And Optimization In Single Phase Immersion Cooling: Framework For Future Design Tools And Digital Twin Integration, Braxton J. Smith

Mechanical and Aerospace Engineering Theses - Archive

The rapidly rising computational power of modern computing components combined with the advanced packaging techniques being implemented has resulted in exponentially increasing thermal design powers (TDP) from CPUs and GPUs. Traditional air-cooling methods are approaching their effective cooling limits for many of these components, requiring lower supply air temperatures, higher supply air flowrates, and much larger heatsinks to remain feasible. Transitioning from air-cooling to single-phase immersion cooling offers numerous benefits in thermal performance, data-center size reduction, and energy efficiency. To leverage the merits of immersion cooling, the performance of a given heatsink must be predicted and optimized for best performance …

Strategies For Enhanced Meg Data Analysis In Clinical Practice And Emerging Frontiers, Pegah Askari

Bioengineering Dissertations - Archive

Epilepsy and dementia are debilitating neurological disorders that pose substantial challenges for patients, caregivers, and healthcare systems. Advances in magnetoencephalography (MEG) and signal processing offer new opportunities to improve diagnostic accuracy, surgical planning, and treatment monitoring. This dissertation presents a unified body of work comprising artifact removal, automated event detection, and deep learning-based biomarker discovery. These approaches collectively enhance the clinical utility of MEG for diverse patient populations.

The first study addresses a significant technical obstacle in the management of drug-resistant epilepsy. Patients receiving responsive neurostimulation (RNS) have historically been excluded from MEG as the data is contaminated by device-related …

Functional Enhancement Of Pancreatic Islets Through Photobiomodulation For Potential Diabetes Therapeutics, Kelli Fowlds

Bioengineering Dissertations - Archive

Islet transplantation is a potential therapeutic route for type 1 diabetic patients facing chronic ketoacidosis and/or hypoglycemia unable to be properly regulated with standard insulin administration. However, successful engraftment is hampered by a multitude of factors. Harvested islets face rapid, substantial degradation due to hypoxia and nutrient depletion once isolated. Transplanted islets are additionally susceptible to the instant blood-mediated inflammatory reaction (IBMIR). This combination of factors leads to more than half of transplanted islets failing to engraft post-surgery. Many areas of research are dedicated to investigating alternative approaches or supplemental treatments to improve the success rate of engraftment and insulin …

Novel Electrophysiological Biomarkers In Pediatric Drug Resistant Epilepsy And Genetic Epilepsy Syndromes, Sakar Rijal

Bioengineering Dissertations - Archive

Pediatric epilepsies, particularly those that are drug-resistant or genetically driven, represent some of the most complex neurological disorders encountered in childhood. Central to their pathophysiology is a disruption in the delicate balance between cortical excitation and inhibition (E/I), often resulting from impaired GABAergic interneuron function. This imbalance manifests as aberrant network dynamics and altered neural oscillations, giving rise to seizures and long-term cognitive impairments. In this thesis, we developed a translational framework to identify electrophysiological biomarkers that (i) assess cortical E/I imbalance and (ii) map epileptogenic zones, with the aim of enhancing diagnosis, guiding surgical planning, and informing therapeutic monitoring …

Vendor-Independent B0 Shimming Framework With Application To Metabolic Mri In Human Gliomas, Mahrshi Jani

Bioengineering Dissertations - Archive

High and ultra-high field MRI and MRSI offer markedly improved signal-to-noise ratio and spectral dispersion, enabling in-vivo characterization of tumor metabolism with unprecedented detail. However, these benefits are tightly coupled to high demands on static magnetic field (B₀) homogeneity, particularly in the brain where susceptibility interfaces near the skull base and paranasal sinuses generate complex, higher-order field perturbations. In glioma patients, additional susceptibility variations arise from surgical cavities, hemorrhage, calcifications, and cystic components, further degrading B₀ homogeneity. As a result, shimming often become the main bottleneck limiting robust, whole-brain spectroscopic imaging and, consequently, our ability to map metabolic …

Engineered Biomimetic Muscle Graft For Skeletal Muscle Regeneration, Julia O. Aguirre

Bioengineering Theses - Archive

This study aims to develop a synthetic muscle graft that closely mimics the architecture, viscoelastic properties, and bio-signaling characteristics of natural skeletal muscle. By analyzing the native skeletal muscle microstructure, biochemical, and mechanical properties, we establish design parameters for a biomimetic scaffold. The engineered graft integrates tunable mechanical compliance, aligned microarchitecture, and signaling cues to promote cell recruitment, adhesion, proliferation, and maturation. To further enhance biofunctionality, an electrically conductive polymer was incorporated to improve the electrical conductivity, and the graft was loaded with the bioactive lipid signaling mediator “Prostaglandin E2” (PGE2) to support myogenesis during muscle regeneration. The grafts were …

Quantifying Multidimensional Effects Of Physicochemical Parameters On Pfas Adsorption Using A Hybrid Response Surface Methodology-Machine Learning Approach, Harsh V. Patel, Jazmin Green, John Park, Stephanie Luster-Teasley Pass, Renzun Zhao

Engineering Management & Systems Engineering Faculty Publications

Per- and polyfluoroalkyl substances (PFAS) contamination has posed a significant environmental and public health challenge due to their ubiquitous nature. Adsorption has emerged as a promising remediation technique, yet optimizing adsorption efficiency remains complex due to the diverse physicochemical properties of PFAS and the wide range of adsorbent materials. Traditional modeling approaches, such as response surface methodology (RSM), struggled to capture nonlinear interactions, while standalone machine learning (ML) models required extensive datasets. This study addressed these limitations by developing hybrid RSM-ML models to improve the prediction and optimization of PFAS adsorption. A comprehensive dataset was constructed using experimental adsorption data, …

Study On Motion Prediction Analysis Of Large Vessels Entering Kaohsiung Port Second Harbor, Li-Heng Cheng, Hsing-Yu Wang

Journal of Marine Science and Technology–Taiwan

Pilotage is a primary service offered by ports, ensuring the safe passage of entering and exiting vessels. This study applied motion prediction analysis to large vessels navigating the constrained waterways of Kaohsiung Port’s second harbor. To address the needs of pilots and port operators, a simplified planar motion equation was developed that incorporated speed over ground and rate of turn (ROT) as primary variables. The model relied on inputs of limited navigational data, enabling pilots to predict changes in heading and position over time and determine the conditions for safe harbor entry. Vessel paths and turning angles were analyzed to …

Optimal Tissue Clearing Of Gastric Cancerous Organoids Imaged Via High Resolution Light Sheet Microscopy, Lauren D. Lieu

2025 Fall Honors Capstones Projects - Archive

While the rate of surviving a myocardial infarction has increased in the past 60 years from 60% to 90%, the rate of Americans developing chronic heart disease such as heart failure, arrhythmias, and hypertensive heart disease has risen. This has led to the development of imaging technology such as Light Sheet Microscopy (LSM) and Light Field Microscopy (LFM) to study heart contractility and congenital heart disease via models such as cancerous organoids or Zebrafish. However, LSM and LFM results are highly dependent on the quality of the staining and cleared samples. This study looks to add to the growing field …

Signal Analysis Of Calcium Dynamics In Pancreatic Cells, Abhidha Kunwar

2025 Fall Honors Capstones Projects - Archive

Calcium (Ca²⁺) signaling plays a critical role in insulin secretion from pancreatic βcells. Photo-biomodulation (PBM) of red or near-infrared wavelengths is applied to enhance cellular metabolism and Ca²⁺ activity in pancreatic cells. This study aims to rigorously analyze how PBM influences calcium dynamics in pancreatic cells by applying the Fast Fourier Transform (FFT), converting Ca²⁺ spiking patterns to the frequency domain to determine dominant oscillatory behaviors. Using a calcium-binding fluorophore, Ca²⁺ activity was acquired before and after PBM at 810 nm, processed with a machine learning algorithm, and further analyzed in MATLAB using FFT to assess changes in calcium signal …

Medical Ai: Solving Healthcare Challenges And Inspiring Ai Innovation, Xiaowei Yu

Computer Science and Engineering Dissertations - Archive

Artificial Intelligence (AI) is transforming healthcare by enabling large-scale analysis of medical data and integrating multimodal information for more comprehensive diagnostics. I present my work addressing fundamental and challenging problems in developing state-of-the-art AI models for medical data analysis, including multimodal brain data and other medical datasets. Additionally, I design brain-inspired AI models by integrating insights from organizational principles of brain networks. Specifically, my research tackles three critical aspects: (1) AI in Computational Neuroscience, where I design deep learning models for brain network analysis to uncover the organizational principles of brain networks; (2) Brain-Inspired AI, where I integrate superior brain …

3d Perception, Mapping, And Navigation For Mobile Cobot, Tuan T. Dang

Computer Science and Engineering Dissertations - Archive

Service robots are migrating from tightly controlled factory lines into offices, hospitals, and homes, where they must perceive, remember, and act amid people, clutter, and perpetual change. Humans solve this daily by forming compact, task-relevant “cognitive maps”: we sample just enough sensory detail to guide the moment, stitch those snapshots into a sparse topological scaffold, and continuously refine it as we move. Guided by that insight, this dissertation proposes a biologically inspired mapping framework that turns partial RGB-D observations into a hybrid temporal-spatial memory—locally metric for centimeter-scale navigation yet globally topological for room-to-building navigation. The system first distills raw depth …

Excitation And Polarization Of Isolated Neurons By High-Frequency Sine Waves For Temporal Interference Stimulation, Iurii Semenov, Vitalii Kim, Giedre Silkuniene, Andrei G. Pakhomov

Bioelectrics Publications

The capacity of temporal interference (TI) stimulation to target deep brain regions without affecting nearby surface electrodes remains uncertain. Using artifact-free optical recording, we compare excitation patterns and thresholds in hippocampal neurons stimulated by “pure” and amplitude-modulated sine waves, representing TI waveforms near electrodes and at the target, respectively. We show that pure 2- and 20-kHz sine waves induce repetitive firing at rates that increase up to 60–90 Hz with stronger electric fields. Beyond this limit, action potentials merge into sustained depolarization, resulting in an excitation block. Modulating the sine waves at 20 Hz aligns firing with amplitude “beats” and …

Ease Of Product Disassembly Through A Systematic Structured Time-Based Design For Disassembly Methodology, Emeka S. Igwe

College of Graduate Studies: Theses & Dissertations

This research introduces a systematic time-based design for disassembly (DfD) framework aimed at optimizing product disassembly by addressing important features like liaisons between components in product, component accessibility and the overall modularity of the product. This study specifically covers electromechanical and mechatronic systems in both household and industrial setup, identifying their disassembly challenges and high value pointers for improvement. The methodology involves using a design for disassembly framework called LeanDfD in carrying out a holistic disassembly process and evaluating quantitative metrics like disassembly time and complexity and suggesting further redesign strategies to minimize disassembly time and cost. Adopting this systematic …

Metallic Nanoparticles And Cosmetics: The Role Of Mitochondria And Premature Aging, Veronica Montesinos-Cruz, Justin Olmanson

Department of Teaching, Learning, and Teacher Education: Faculty Publications

The cosmetic industry has developed and commercialized numerous products using new technologies, making them increasingly appealing to the public. The use of metallic nanoparticles (MtNPs) as key ingredients in cosmetics has become more widespread due to their demonstrated benefits. However, the use of these products remains controversial, as some studies have shown that MtNPs can penetrate the deeper layers of the skin and disrupt homeostatic balance. It has also been demonstrated that the interaction between MtNPs and keratinocytes increases the generation of reactive oxygen species (ROS), which can lead to oxidative stress, a condition associated with premature aging. Mitochondria, as …

Design And Evaluation Of A Thai Speech Emotion Recognition Corpus With Ambiguous Annotations, Chompakorn Chaksangchaichot

Chulalongkorn University Theses and Dissertations (Chula ETD)

THAI-SER is the first large-scale Thai speech emotion recognition corpus, comprising 41.6 hours (27,854 utterances) from 100 recordings across diverse environments (Zoom and studio). The data includes both scripted and improvised speech by 200 professional actors (112 females, 88 males, aged 18–55), covering five emotions: neutral, angry, happy, sad, and frustrated. Utterances were labeled via crowdsourcing, with rigorous quality control ensuring a majority agreement score above 0.71. Annotation reliability, measured by Krippendorff’s alpha, reached 0.692 (above the 0.667 threshold), and human emotion recognition accuracy reached 0.772 after filtering. We also report benchmark results from models trained and evaluated on both …

Transfection Of Ionizable Lipid Nanoparticles On Raw 264.7 And Mda-Mb-231, Lavanya Bhargava

Masters Theses

"This thesis investigates the preparation, characterization, and transfection efficiency of various ionizable lipid nanoparticles (LNPs) formulated for the delivery of mRNA encoding enhanced green fluorescent protein (EGFP) in RAW 264.7 macrophages and MDA-MB-231 breast cancer cell lines. The ionizable cationic lipid studied are ALC-035, C12-200, C14-4, PPZ-A10, DLin-MC3-DMA. The study addresses the need for effective gene delivery systems to provide a safe and versatile platform that protects and transports nucleic acids into target cells. LNPs were synthesized using microfluidic mixing methods, incorporating lipid components such as the cationic lipids, DSPE, DOPE, cholesterol and PEG lipids to achieve controlled particle sizes, …

Power Quality Event Diagnosis Using Multi-Rate Neural Networks, Jordan D. Lloyd

Electrical Engineering Theses - Archive

Power quality disturbances (PQDs) are among the primary challenges facing modern electrical systems, as they degrade the performance and lifespan of connected equipment. This thesis investigates the relationship between the rate at which voltage waveform data are sampled, the reliability of these measurements, and the ability of deep neural networks to classify PQDs accurately. A one-dimensional convolutional neural network (CNN) was trained and evaluated across multiple sampling rates and signal-to-noise ratios to quantify how information loss in the temporal and spectral domains affects classification reliability. The results demonstrate that model accuracy degrades nonlinearly as sampling rate and signal-to-noise ratio (SNR) …

Integrating Data Management Plans Into The Unified Architecture Framework Standards Views, Cansu Yalim, Holly A. H. Handley

Engineering Management & Systems Engineering Faculty Publications

System Architecting translates an operational concept into a model of the system to be realized. There is a need for a Data Management Plan (DMP) to be included in the overall system engineering process with the advent of Digital Engineering. Data longevity, accessibility, and integrity can all be improved throughout the system's lifecycle by a well-defined DMP. System engineers use an architecture framework to arrange the system data into several sets of viewpoints. Incorporating a DMP at this point specifies the procedures for gathering, storing, retrieving, and maintaining data to ensure that all interested parties have access to current, correct …

Seasonal Variation Of The Stream’S Autogenic Sediment Transport Regime, Melissa Beckman

Theses and Dissertations--Civil Engineering

This thesis investigates the autogenic sediment transport regime in a low-gradient stream system in the inner bluegrass region of central Kentucky, USA The seasonality of sediment transport seasonality was not well addressed in prior research for baseflow and low flow periods, to our knowledge, due to the assumption that low flows do not account for considerable fluid transport capacity to move sediment. The hypothesis is that during the autogenic regime the sediment transport in the low-gradient system is being driven by geophysical, biogeochemical, and biological processes. We hypothesize that crayfish are one mechanical driver of sediment transport during these periods. …

U.S. Perspectives On Deconstruction And Reuse Of Structural Wood Products, Fiona A. O'Donnell, N. L. Post, J. J. Lesko, Amelia E. Landry , '26, Abigail R. Peters , '26, Zoe A. E. Sperduto , '26

Engineering Faculty Works

This paper identifies barriers, challenges, and requirements to the widespread adoption of Design for Deconstruction and Reuse (DfDR) of wood and engineered wood products in the United States (U.S.) to increase circularity in the built environment. A series of interviews with industry representatives were performed to summarize the state-of-the-art related to DfDR and gain insight into the perspectives and attitudes of the primary stakeholders; the results of these interviews were compared to the current academic literature. Results indicate that further emphasis is needed on closing the loop through the reuse phase, which is limited by a lack of regulations and …

Fetal Acidosis Prediction Using Attention Enhanced Convolutional Neural Networks, Anusha Adhikari

Masters Theses

This study explores the integration of spectral mixtures of fetal heart rate (FHR) and uterine contraction (UC) signals to enhance the prediction of fetal acidosis, utilizing the CTU-CHB dataset. Several classification models were trained using two distinct oversampling techniques and inputs, demonstrating that models incorporating spectral mixtures significantly outperform those using raw signals. These models, particularly when combined with convolutional neural networks (CNNs) and attention mechanisms, achieved a notable F1-score of 0.98, with the highest model achieving an area under the Receiver Operating Characteristic (ROC) curve of 0.95. The research employs a variety of techniques including short-time Fourier transform and …

Application Of Artificial Intelligence Techniques To Improve Leadership Decision Making With Uncertainty, Michael David Parrish

Doctoral Dissertations

"Every good leader is a good manager, but not every good manager is a good leader. The difference between the leader and the manager is critical decision-making. Today’s decision-making environment is characterized as Volatile, Uncertain, Complex, and Ambiguous (VUCA). With the exponential increase in the technical capabilities of systems, the human has become the weakest link in the use of such systems. To remain relevant, good leaders must continuously adapt to new advances in technology and processes.

The research contributions of this work provide several unique and novel solutions for leaders to utilize artificial intelligence tools to improve and optimize …

Implications Of Nutrient Fate And Transport Following Nanopesticide Applications In Agricultural Field Plots In Central Kentucky, William Rud, Manuel D. Montaño, Daniel M. Miller, Wayne T. Sanderson, Carmen Agouridis, Brianna F. Benner, Tiffany L. Messer

Biosystems and Agricultural Engineering Faculty Publications

The potential benefits of nanopesticide use over standard pesticides include more precise application at reduced application rates, lower premature degradation, and decreased direct impacts to target organisms. However, field scale investigations of the fate and transport of common nanopesticides such as copper (II) hydroxide and imidacloprid combinations, remain limited. A field study evaluating nano-scale copper (II) hydroxide (Cu), standard imidacloprid (I), nanoimidicloprid (NI), and nano-scale copper (II) hydroxide and imidacloprid (CuNI) compared to control (C) plots was conducted using thirty 14.6 m² field plots to determine the impacts of nanopesticide applications on nutrient cycling and quantify the persistence of …

Neuroinflammatory Signaling And Immune Cell Infiltration Differ In Brains Of Rats Exposed To Space Radiation And Social Isolation, Austin M. Adkins, Zachary N. M. Luyo, Alea F. Boden, Riley S. Heerbrandt, Richard A. Britten, Laurie L. Wellman, Larry D. Sanford

Center for Integrative Neuroscience and Inflammatory Diseases (CINID) Faculty Publications

Astronauts on the proposed Mars missions will be exposed to extended periods of social isolation (SI) and space radiation (SR). SI and SR-induced immune dysregulation can result in persistent neuroinflammation and neuronal damage which could negatively impact an astronaut’s health and ability to maintain adequate levels of performance. The synergistic effects of combined SI and SR on immune system functionality and the brain remain unknown. Determining how single and combined inflight stressors modulate the immune system is crucial for fully understanding pathways impacting astronaut health and performance. We used ground-based analogs of SI and SR in rodent models to investigate …

Lifelong Machine Learning With Adaptive Resonance Theory, Sasha Petrenko

Doctoral Dissertations

"This publication option dissertation is composed of three papers concerning the study of the problem lifelong machine learning with Adaptive Resonance Theory (ART) algorithms. Lifelong learning (L2) is a challenging machine learning paradigm that both encompasses and formalizes the fields of continual learning and incremental learning. The field is concerned with the mitigation of the phenomenon of catastrophic forgetting whereby learning agents that are faced with incrementally novel information deleteriously overwrite previous knowledge if that learning process is not regularized to counteract this consequence. ART algorithms solve this stability-plasticity dilemma by optimally assigning learning to categories or instantiating new knowledge …

Electronic Propulsion Engines: Revolutionizing Space Travel, Isaiah Echeverria

Undergraduate Honors Theses

Most spacecrafts rely on chemical propulsion to generate thrust and venture into the depths of outer space. They rely on principles from Newton’s three laws of motion, conservation of momentum-energy, and atomic physics. However, an electronic form of propulsion also exists providing spacecrafts an alternative opposed to the sole use of chemical energy. Electronic propulsion systems or engines last longer than current chemical spacecraft engines and are improving to produce greater amount of thrusts.

Comparing the two types of spacecraft engines shows the benefits and disadvantaged obtained by using either option as well as the main differences and similarities shared …

Swosu Research And Scholarly Activity Fair 2025, Swosu Office Of Sponsored Programs

SWOSU Research and Scholarly Activity Fair Programs

On behalf of the members of the University Research and Scholarly Activity Committee (USRAC) and the Office of Sponsored Programs (OSP) at Southwestern Oklahoma State University (SWOSU) — welcome to the Thirty-Third SWOSU Research and Scholarly Activity Fair!

This year’s event features 99 poster presentations and 9 oral presentations, showcasing the work of over 170 student and faculty researchers, writers, presenters, artists, collaborators, and faculty sponsors. These presentations represent a wide array of scholarly and academic activity from across SWOSU’s academic community, including the Departments of Art, Communication, and Theatre; Allied Health Sciences; Biological Sciences; Business; Chemistry & …

Navigating Wastewater: Minnesota Mining Wastewater Permit Challenges And Evolving Compliance Standards, Madelaine Adamich

Journal of Earth and Life Science

February of 2021 marked the beginning of Minnesota clearly establishing that groundwater qualifies as a Class 1 water in a legal battle involving United States Steel, the Minnesota Pollution Control Agency, WaterLegacy, Fond du Lac Band of Lake Superior Chippewa, the Minnesota Court of Appeals, and eventually the Minnesota Supreme Court (MNSC). Minnesota has a water classification system, as required by the federal Clean Water Act, with 7 classes of use. Class 1 waters are waters used for domestic consumption (MPCA 4, n.d.). According to Minnesota Statute § 7050.0220, the acceptable level for sulfate is 250 mg/L in Class 1 …