Engineering Commons^™

Induced Reduction Of N-Glycosylation Leads To Heart Failure, Anthony M. Young

Browse all Theses and Dissertations

Cardiovascular disease is the leading cause of death and contributes to the increasing global prevalence of heart failure (HF). N-glycosylation is a common co-/post-translational modification where branching oligosaccharides are bound to the extracellular domain of membrane proteins. This creates a diverse range of glycan structures and requires the coordination of hundreds of regulated genes. Inherited mutations in glycan synthesis frequently present with cardiomyopathies leading to HF with reduced ejection fraction (HFrEF). Additionally, gene expression studies of HFrEF patients have shown altered expression of glycosylation-related genes, including alpha-1,3-mannosyl-glycoproten 2-beta-N acetlyglucosaminyltransferase (Mgat1). This gene encodes N-acetylglucosaminyl transferase 1 (GlcNAcT1) which is required …

A Secure Ml-Assisted Framework For Resilient And Efficient Prediction Of Physiotherapy Sequence In Bilateral Carpal Tunnel Syndrome, Pratik Pandurang Kharat

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Bilateral idiopathic carpal tunnel syndrome (CTS) is a neuromuscular disorder characterized by compression of the median nerve at both wrists, leading to symptoms such as pain, numbness, tingling, and muscle weakness. Unlike unilateral cases, bilateral idiopathic CTS presents distinct therapeutic challenges due to the simultaneous involvement of both hands and the lack of an identifiable underlying cause. This study explores the application of machine learning techniques to predict the optimal sequence of physiotherapeutic interventions Stretching followed by Myofascial Mobilization (S/M) or the reverse (M/S) in female patients with bilateral idiopathic CTS and right hand dominance. Data were drawn from a …

The Impact Of Ahr And Hs1.2 Enhancer Genetic Variations On Igh Expression And Antibody Production In Human B Cells, Mili Santosh Bhakta-Yadav

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Antibody production is an essential component of the immune response against pathogens. The immunoglobulin heavy chain (IgH) gene codes for the heavy chain of antibodies. The IgH constant regions Cμ, Cδ, Cγ1-4, Cα1-2, and Cε encode the five major classes of antibodies, i.e., IgM, IgD, IgG1-4, IgA1-2, and IgE, respectively. The transcription of the IgH gene and class switch from IgM to other isotypes is regulated by two 3’ IgH regulatory regions (3’IgHRRs), each of which is a cluster of three enhancer regions (hs3, hs1.2 and hs4). The genetic variations in the hs1.2 enhancer have been identified; a ~53 bp …

Learning Under Data Scarcity: Reasoning And Negative Distillation For Texts And Graphs, Calvin T. Greenewald

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Modern machine learning (ML) models rely on large amounts of high-quality labeled data to achieve optimal performance. However, in many real-world domains, such as cyber security, acquiring sufficient labeled data is often infeasible due to cost, privacy concerns, and the rapid evolution of underlying phenomena. This challenge underscores the importance of learning under data scarcity. This thesis addresses this challenge by proposing distinct, modality-specific techniques for text and graph domains, which allow models to generalize effectively with minimal data. For text classification task, we incorporate distilled rationales from large language models and adversarial perturbations into the input space to improve …

Molecular Modeling Methods And Applications For Accelerating Polymerization And Pyrolysis Studies, Joshua D. Kemppainen

Dissertations, Master's Theses and Master's Reports

Polymer matrix composites and carbon-carbon composites play critical roles in the aerospace, automotive, and construction industries. Different matrix materials and processing conditions can lead to a large variety of composite materials and composite properties. Integrated computational materials engineering has been used to tailor PMC matrix materials and processing conditions to specific properties and manufacturing techniques. The integrated computational materials engineering process modeling framework uses molecular dynamics at the nanometer length scale to characterize the evolving thermo-mechanical properties of the polymer as it cures. Then finite element analysis is used at the micrometer length scale to adjust cure cycles to tailor …

Characterization Of Krypton Performance In A Laboratory 300 W Magnetically Shielded Hall-Effect Thruster, Jacob Henry Knott

Dissertations, Master's Theses and Master's Reports

Xenon has long been the propellant of choice in Hall Thrusters; however, significant work has been performed to produce thrusters capable of utilizing alternate propellants due to xenon’s price and scarcity. Krypton is the most similar alternative propellant to xenon. This work examines the performance of a sub-kilowatt magnetically shielded Hall Thruster operating on both xenon and krypton. Krypton produced lower thrust, specific impulse, and was less efficient than xenon. Specifically, the absolute xenon-krypton efficiency gap was 6 to 24 % . Krypton’s inferior efficiency is primarily attributable to differences in mass utilization and beam divergence losses. The impacts of …

Measuring Occupant Controlled Ventilation And Cooking Frequency To Aid In Modeling Energy Performance Of Northern Michigan Homes, Jacob J. Chizek

Dissertations, Master's Theses and Master's Reports

This research investigates the real-world interplay between energy efficiency and indoor air quality. We explore how home ventilation strategies, heating systems, and weatherization levels in rural homes interact. As part of a larger study on air quality, 17 homes participated in the study. Specifically, this research shows the results and methods for monitoring cooking frequency, kitchen range hood use, and bathroom fan use over two, month-long study periods to build accurate energy and contaminant transport models of homes that were studied. Energy audits to document home characteristics were conducted, including blower door testing and detailed qualitative data regarding the homes’ …

Analysis Of Lava Flow Paths Using Remote Sensing And Geomorphological Techniques, Oluwatosin Oluyemisi Ayo

Dissertations, Master's Theses and Master's Reports

Lava flows have severe impacts on the Earth’s surface, communities, and natural habitats. Accurate modeling of lava flow paths is crucial for volcanic hazard assessment and risk mitigation. This research integrated remote sensing, geographic information systems, geomorphological techniques, and hydrologic analysis to numerically determine the optimal ground sample distance (GSD) of digital elevation models (DEMs) for delineating lava flow paths. Two volcanic regions were analyzed: the Afar Region of Ethiopia (Alu, Dalaffilla, and Erta Ale volcanoes) and the Reykjanes Peninsula of Iceland (Fagradalsfjall volcano). Forward and backward modeling methods were used to simulate potential lava flow paths. Remote sensing data, …

Numerical Modelling And Co-Optimization Of Gasoline Fuels For Gasoline Compression Ignition Using Multi Component Approach, Ashwin Karthik Purushothaman

Dissertations, Master's Theses and Master's Reports

Future mobility is expected to rely on a broad spectrum of powertrain technologies, including battery electric vehicles (BEVs), hybrid electric vehicles (HEVs), fuel cell electric vehicles (FCEVs) and traditional internal combustion engine (ICE) vehicles. Despite the shift toward electrification, internal combustion engines are projected to remain a key component of future powertrains, either as the primary power source or as range extenders to generate electricity in hybrid systems. As such, significant research efforts continue to focus on enhancing the efficiency and reducing the emissions of ICEs to meet increasingly stringent regulatory and environmental targets. Gasoline compression ignition (GCI) has been …

Effects Of Invigorating And Relaxing Music On Heart Rate, Blood Pressure, And Heart Rate Variability, Matthew Joshua Faur

Honors Undergraduate Theses

Heart-rate variability (HRV) has been documented to correlate with several health measures, including autonomic nervous system longevity and athletic performance (Zulfiqar, 2010). While increasing age does not affect heart rate, there is a steady decline in HRV, which is a biological marker of aging and the decline of autonomic nervous system function. Furthermore, men who exercise regularly tend to have increased HRV, suggesting a mitigation of the typical age-dependent loss of HRV (Kristal-Boneh et al., 1995). Previous studies have suggested that music may have a physiological effect (e.g., fluctuating vitals, emotional changes) on cardiovascular parameters. However, little is known about …

The Aerodynamics Of Bird Perching: Understanding Wing And Body Interactions In Pigeon Flight, Anirudh Sriram

Honors Undergraduate Theses

During landing, birds often execute a perching maneuver. The perching maneuver refers to the complex series of actions that birds, and pigeons in particular, will perform when landing. They will typically decelerate by pitching their body to a high angle of attack and spreading their wings. It is believed to help achieve better control and reach optimal lift and drag coefficients. This study seeks to better understand the vortex interactions between the main and tail wings during this maneuver. However, it is still an unexplored phenomenon. Thus, two bird models were conceived to analyze it, one with and one without …

Measuring Achilles Tendon Stiffness And Kinetics In-Vivo, Chloe L. Pinkston

Honors Undergraduate Theses

This study aims to measure the gastrocnemii Achilles subtendon passive stiffness and energy storage during walking. Stiffness was first determined using a noninvasive method that combines ultrasound, motion capture, musculoskeletal modeling, and a force transducer. Eight healthy participants were tested using this method to obtain the passive force-displacement relationship of the Achilles tendon at two different knee angles to calculate stiffness of the gastrocnemii subtendon. A gait analysis session was then performed using ultrasound, motion capture, and an instrumented treadmill at self-selected slow, normal, and fast walking speeds, using stiffness to calculate the subtendon’s force and energy storage. Gastrocnemii Achilles …

Effect Of Metal Ions On The Reactive Oxygen Species Scavenging Capabilities Of Cerium Oxide For Biological Applications, Agastya Mittal

Honors Undergraduate Theses

Ceria nanoparticles' capabilities to defend cells against oxidative stress through superoxide dismutase activity are well-documented. Ceria nanoparticles demonstrate a ratio between 3⁺/4⁺ oxidative states on the surface of the particles to exhibit oxygen vacancies, a feature that allows these particles to scavenge Reactive Oxygen Species (ROS) in times of Oxidative Stress. Oxidative stress arises from many wounds in the body, such as wounds in the skin, and can have significant impacts on the health of an individual. Even when receiving treatment for the skin wound, ROS can circulate from around the wound, be generated from an imbalance …

Synthesis And Characterization Of Multifunctional Cerium Oxide Containing Nanoparticles For Biomedical Applications, Ishaan Patel

Honors Undergraduate Theses

This study presents the synthesis and comprehensive characterization of a novel core-shell nanoparticle composed of a maghemite (γ-Fe₂O₃) core and a europium-doped cerium oxide (EuCNP) shell, developed for potential use in cancer theranostics. Using a co-precipitation method, Fe₂O₃–EuCNP core-shell nanoparticles were synthesized and compared against control samples of CNPs, EuCNPs, and Fe₂O₃. A variety of characterization techniques, including UV-Vis spectroscopy, fluorescence spectroscopy, TEM, XRD, XPS, DLS, TGA, and DSC confirmed the successful synthesis of core-shell architecture and europium doping. Moreover, Fe₂O₃–EuCNPs demonstrating strong colloidal …

Utilizing Pneumatic Artificial Muscles To Simulate Wingbeat Kinematics For Morphing Uav Wings, Vireli S. Anbarasu

Honors Undergraduate Theses

The controlling muscles of a bird wing change stiffness and length to provide high efficiency when executing a flight maneuver. This variable stiffness allows the muscles to cycle between increasing energy, transmitting it, and restoring it, allowing an overall increase in mechanical and aerodynamic efficiency. Inspired by this, we have developed a system that uses pneumatic artificial muscles (PAMs) to actuate a morphing wing. The stiffness in the PAMS can be controlled to mimic the changes bird flight muscles undergo when executing a forward flapping maneuver. We will evaluate the performance of the PAMs in actuating a morphing wing through …

Methods Of Variability Reduction In Ramjet Fuel Injection Using Fluid-Structure Interactions, Egan J. Rigney

Honors Undergraduate Theses

The Liquid Jet in Crossflow (LJIC) method of fuel injection in ramjet engines is widely used and well-studied. However, they experience variation in their behavior at different altitudes and flight speeds due to the varied flow conditions following the inlet. This variation becomes more noticeable at high-temperature and high-speed airflow conditions. The optimized and consistent breakup of liquid fuel is a key component in ramjet engine design as there is a minimum surface area requirement of the droplets for combustion to occur. Local equivalence ratios also have a significant influence on the effectiveness of combustion. As such, researchers at the …

Quantized Average Agreement Algorithms With Error Correction For Digraphs, Shuaib A. Mughal

Honors Undergraduate Theses

Multi-agent systems have become more and more prevalent as technology increasingly gets integrated into our daily lives. Some of these technological systems are large in size; for example, the smart grid where multiple devices are used to monitor and control different aspects of the energy grid. Another example is a team of autonomous systems deployed for a specific task. When these systems are spatially distributed, an important component of distributed algorithms is the ability for the agents to reach consensus on the global state of the system. Reaching agreement enables the spatially distributed agent make decisions or determine the next …

A Signal Processing And Mechanical Design Approach To Understanding Triboelectric And Piezoelectric Nanogenerators’ Output, Nicholas Rose

Honors Undergraduate Theses

Scalable energy harvesters—capable of converting motion into electrical output—provide promising solutions to increasing energy demands. This thesis was inspired by the potential biomedical applications of piezoelectric nanogenerators (PENG) and triboelectric nanogenerators (TENG). In theory, these devices could convert mechanical energy from the body into usable electricity for self-powered electronics such as pacemakers or cochlear implants. In line with this goal, this project worked to design a sustainable and biocompatible PENG; however, early devices produced inconsistent voltage. These output inconsistencies motivated an exploration of device reproducibility, but characterizing piezoelectric output signals is a particular challenge in the field. Subtle to significant …

Behavior Analysis Of Simple And Complex Workloads, Davi D. Dantas

Honors Undergraduate Theses

Complex tasks have evolved rapidly in recent times due to tremendous advancements in computational power and data availability. With the ever-increasing presence of complex applications, this paper attempts to distinguish between complex and simple applications. This paper explored side-channel analysis as a method to differentiate complex workloads from simple workloads by monitoring system-level metrics such as power consumption, cache behavior, and memory accesses. By leveraging side-channel effects such as power analysis and memory access, this study seeks to establish unique hardware signatures for complex workloads. Using tools such as Intel Pin, the data will be collected from complex and simple …

Effects Of Changes In Strouhal And Reynolds Numbers On Beetle Wing Aerodynamics, Keith L. Thiha

Honors Undergraduate Theses

Insect flight has long been a subject of interest across the scientific community, largely due to the exceptional aerodynamic performance insects demonstrate relative to their size. Insects tend to have very high aerodynamic performance characteristics like thrust and lift generation compared to their size. This has many potential applications in improving aircraft performance, however the flow phenomena concerning insect wing aerodynamics is still an area of ongoing research. This study aims to investigate how variations in key nondimensional flow parameters—specifically the Reynolds number and Strouhal number—affect the aerodynamic performance of beetle wings. Strouhal numbers ranging from 0.2 to 0.6 were …

Exploring The Dynamics Of Cislunar Space: A Detailed Study Of Periodic Orbits And Their Applications In The Circular Restricted Three-Body Problem, Nicole Weeden

Honors Undergraduate Theses

Ever since NASA announced the Artemis program in 2019, the cislunar space, a region between Earth and the Moon, has attracted substantial research interest. Nonetheless, understanding the complex multipart physics that guides our solar system is not a new area of interest. The ThreeBody Problem was first formulated by Lagrange in ”Essai sur le Probleme des Trois Corps” in 1772 and had additional refinements done by mathematicians like Poincare. However, it was not until NASA’s Apollo program that the cislunar space gained traction, and the Circular Restricted Three-Body Problem (CR3BP) model became more prominent. By deriving and explaining the necessary …

3d Printing Of A Solid-State Battery, Maurizio A. Brozzi

Honors Undergraduate Theses

Solid-state battery research has gained significant attention in recent years, as it provides a unique solution for several common issues in conventional Li-ion batteries. Additionally, as additive manufacturing technologies continue to advance, they have the potential to fabricate solid-state batteries with new materials. The objective of this study is to explore the feasibility of 3D printing of a solid-state battery. By creating an initial PEO-PSF hybrid polymer matrix dissolved in DMSO and adding a lithium salt, the base electrolyte ink was formed. With the addition of conductive additives and active material, electrode inks were also produced. Super P was used …

Microplastics Detection, Characterization, And Cytotoxicity Evaluation Via Lab-On-Chip, Liyuan Gong

Open Access Dissertations

Microplastics (MPs) pose a growing challenge to the ecological system, prompting increasing research efforts in diverse directions. Accurate characterization of MPs is essential for understanding their properties, relying on efficient sampling and detection techniques. Additionally, studying the cytotoxic effects of MPs is critical for evaluating their impact on biological systems. Lab-on-chip (LoC) systems offer significant advantages for precise particle manipulation and compatibility with advanced analytical instrumentation, making them valuable for MP detection and characterization. Microfluidic-based on-chip cell-culturing systems provide a controllable, physiologically relevant microenvironment for more realistic in vitro tissue modeling. By leveraging advanced LoC concepts and integrating state-of-the-art machine …

Comprehensively Understanding And Manipulating The Heat Transfer Mechanisms In Next-Generation Battery Materials, Connor Jaymes Dionne

Open Access Dissertations

Rechargeable batteries are paramount to the further development of green energy infrastructure as they allow for energy storage during peak production times, energy distribution during off-peak times, and provide the impetus to transition away from standard combustion engines in the transportation sector. The ability for rechargeable batteries to safely charge and discharge over multiple cycles is key to their successful application and long-term use. Moreover, the growing use of rechargeable batteries necessitates designs utilizing materials that are abundant and accessible to meet the ever-increasing demands required by the green energy and transportation sectors.

To address these needs, we first investigate …

Machine Learning Guided Insights Into Phonon Scattering Mechanisms For Tunable Thermal Transport In Materials From First-Principles, Niraj Bhatt

Open Access Dissertations

As device dimensions shrink in the current era of miniaturization, effective thermal management at the material level has become critical. In ultrasmall device lengths, traditional electronic heat transport becomes severely limited as boundary scattering effects curtail the electronic transport because the electronic mean free paths substantially exceed those of phonons. The resulting high-power- density devices generate thermal hot spots that compromise both performance and long-term reliability. This challenge has intensified the search for materials with superior phonon-mediated heat transport, a key requirement for effective thermal management in next-generation nanoelectronics. Accurately predicting thermal transport properties with near-experimental accuracy is therefore essential. …

Rift - Reddit Information Falsity Tagger, Parth Joshi

Master's Projects

Social media platforms such as Reddit are widely used for sharing and consuming information. User-generated content poses a great risk for misinformation creation and dissemination on these platforms. “Fake news”, as it is commonly referred to, has far-reaching social implications, swaying public perception, making political viewpoints more radical, and adversely impacting health decisions. The covariable features that come with fake news make it even harder to detect because it is presented in the form of text, images, videos, and even social interactions. This paper describes a novel method for detecting fake news on Reddit: RIFT, short for Reddit Information Falsity …

Application Of Advanced Convolutional Neural Network With Robust Hashing On Obfuscated Image Based Malware Dataset, Sanket Shekhar Kulkarni

Master's Projects

This project report provides in-depth details on the creation of a malware classification system that makes use of Convolutional Neural Networks (CNNs) that have been strengthened by data set obfuscation and strong hashing. We test many CNN architectures, including MobileNet, ResNet, and DenseNet, using rigorous hashing and obfuscation techniques on datasets. The entire pipeline is described in this research, which ranges from the gathering and preprocessing of data sets to the application of novel hashing techniques that boost overall accuracy in classification and increase resilience against malicious attacks. Parallel to this, we show that dataset obfuscation adds an additional level …

Reinforcement Learning-Based End-To-End Monitoring Path Selection In Multi-Domain Optical Networks, Soham Choudhury

Master's Projects

This paper presents a novel approach for optimizing network monitoring in optical communication systems using Reinforcement Learning (RL). Assuming a multi-domain architecture with limited domain visibility, we simulate multiple optical connections using an optical communications simulation software, GNPy, obtaining key network metrics to model the system. We developed two RL agents: the first agent selects near-optimal monitoring paths based on network states, and the second agent dynamically adapts its selected paths in response to state changes, such as fiber failures or issues with ROADMs. This adaptive approach allows for continuous improvement of network monitoring, ensuring resilience and efficient fault detection. …

Multilingual Sentiment Analysis Using Ensemble Learning, Farhan Ansari

Master's Projects

The widespread use of multiple social media platforms has amplified the expression of public opinions over the Internet in languages such as English, Hindi and Spanish. With the aid of technological advancements in machine learning, we can analyze opinions posted on the Internet and gauge public sentiments. There are organizations and businesses that are interested in the evaluation of these sentiments as these type of data can generally be used to obtain the opinion of a product, restaurant, a candidate, etc. In this study, we perform a comparative analysis of three popular ensemble learning methodologies (Boosting, Bagging and Stacking) based …

Fault Identification And Localization In Distribution Grids Based On An Attention-Hybrid Graph Neural Network, Xingjian Shan

Theses and Dissertations--Electrical and Computer Engineering

This thesis proposes a multi-task fault diagnosis framework for distribution systems based on Graph Convolutional Networks (GCN) and an enhanced Graph Attention Network (GATv2). By representing the power grid as a graph with electrical features and topological connections, the model simultaneously performs fault type classification and fault location prediction. The architecture incorporates residual connections, multi-head attention, and a Jumping Knowledge module to capture multi-scale structural patterns, while dynamic loss weighting ensures balanced task optimization under noise and sparsity. Experimental results on the IEEE 123-node test feeder demonstrate a fault classification accuracy of 96.43%, and fault localization accuracies of 84.64% (strict), …