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The Antioxidant Potential Of Rosemary Leaf-Derived Nanovesicles, Shani Akila Griffin May 2025

The Antioxidant Potential Of Rosemary Leaf-Derived Nanovesicles, Shani Akila Griffin

Master's Theses

Human dermal fibroblasts are essential for maintaining skin homeostasis. However, exposure to exogenous and endogenous stressors can lead to fibroblast instability, extracellular matrix degradation, and excessive reactive oxygen species (ROS) production. These factors contribute to skin aging and ROS-induced skin disorders leading to hair loss. Adverse effects from synthetic treatments have driven interest in natural alternatives like plant extracts for skin therapy. However, the polyphenols in these treatments require an effective delivery system to ensure their stability and targeted application. Plant derived nanovesicles (PDNVs) are emerging as a promising natural alternative for therapeutic applications. Their biocompatibility, stability, and encapsulated compounds …


A Joint Geometric Topological Analysis Network (Jgta-Net) For Detecting And Segmenting Intracranial Aneurysms, Xinyue Zhang, Zonghan Lyu, Yang Wang, Bo Peng, Jingfeng Jiang May 2025

A Joint Geometric Topological Analysis Network (Jgta-Net) For Detecting And Segmenting Intracranial Aneurysms, Xinyue Zhang, Zonghan Lyu, Yang Wang, Bo Peng, Jingfeng Jiang

Michigan Tech Publications

Objective: The rupture of intracranial aneurysms leads to subarachnoid hemorrhage. Detecting intracranial aneurysms before rupture and stratifying their risk is critical in guiding preventive measures. Point-based aneurysm segmentation provides a plausible pathway for automatic aneurysm detection. However, challenges in existing segmentation methods motivate the proposed work. Methods: We propose a dual-branch network model (JGTANet) for accurately detecting aneurysms. JGTA-Net employs a hierarchical geometric feature learning framework to extract local contextual geometric information from the point cloud representing intracranial vessels. Building on this, we integrated a topological analysis module that leverages persistent homology to capture complex structural details of 3D objects, …


Emerging Investigator Series: Are We Undervaluing Septage? Rethinking Septage Management For Nutrient Recovery And Environmental Protection, Kevin Orner, Stetson Rowles, Sara F. Heger, Ben Howard May 2025

Emerging Investigator Series: Are We Undervaluing Septage? Rethinking Septage Management For Nutrient Recovery And Environmental Protection, Kevin Orner, Stetson Rowles, Sara F. Heger, Ben Howard

Civil Engineering & Construction: Faculty Publications

An estimated 20–25% percent of households in the US rely on on-site sanitation via septic tanks to manage their wastewater. Septage management strategies such as land application, treatment at wastewater treatment plants, and treatment at independent septage treatment plants are common regulated and protective processes for managing septage. There can, however, be potentially negative environmental impacts such as groundwater contamination if septic systems are failing or improperly designed. In this perspective, we reimagine septage management at each step of the septage value chain, identify barriers to change, and propose solutions to overcome these existing barriers. Reimagined septage management can take …


A Causal-Comparative Study Between The Aeronautical Decision-Making Skills Of Collegiately And Non-Collegiately Trained Private Pilots, Karl P. Winters May 2025

A Causal-Comparative Study Between The Aeronautical Decision-Making Skills Of Collegiately And Non-Collegiately Trained Private Pilots, Karl P. Winters

Doctoral Dissertations and Projects

The purpose of this quantitative causal-comparative design study was to examine the relationship between private pilots’ flight training background (collegiate or non-collegiate) and aeronautical decision-making (ADM) skills among recently certificated private pilots enrolled in a commercial pilot flight training course at a Part 141 flight training program in a large, private, mid-Atlantic university. The problem is that although deficient ADM is a known major contributor to fatal general aviation (GA) accidents, it is unknown if there is a difference in the ADM skills of collegiately and non-collegiately trained private pilots. This study, built on the framework of dual-process theory and …


Skin Cancer Diagnosis Utilizing Hybrid Discrete Cosine Transform And High-Performance Convolutional Neural Networks, Mohammed M. Abo-Zahhad, Mohammed Abo-Zahhad May 2025

Skin Cancer Diagnosis Utilizing Hybrid Discrete Cosine Transform And High-Performance Convolutional Neural Networks, Mohammed M. Abo-Zahhad, Mohammed Abo-Zahhad

Mansoura Engineering Journal

Detecting skin cancer early and accurately is crucial for successfully treating this potentially fatal disease. Enhancing the accuracy of visual inspection techniques is often necessary to improve clinical decision-making and increase the chance of successful treatment outcomes. In this research, high-performance deep learning (DL) models for automated skin cancer categorization and early skin cancer diagnosis screening are developed and evaluated in conjunction with the discrete cosine transform (DCT). For this purpose, features are extracted from medical images using both techniques. The DCT is used for feature extraction and dimensionality reduction, while deep learning (DL) trains fully connected models for classification …


Causation Analysis Of Crane-Related Accident Reports By Utilizing Chatgpt And Complex Networks, Yifan Wang, Junyu Chen, Bo Xiao, Shane T. Mueller, Jingjing Guo May 2025

Causation Analysis Of Crane-Related Accident Reports By Utilizing Chatgpt And Complex Networks, Yifan Wang, Junyu Chen, Bo Xiao, Shane T. Mueller, Jingjing Guo

Michigan Tech Publications

This study integrates ChatGPT and complex network (CN) techniques into an accident analysis framework designed to reduce manual effort in accident causation analysis. The proposed framework supports construction stakeholders in extracting causal factors (CFs) from accident reports and identifying both critical CFs and key causal paths. A multistep research design was adopted to develop and validate this novel framework for analyzing crane-related construction accident reports using ChatGPT and CN techniques. First, ChatGPT was prompted to extract CFs from a database of crane-related accident reports. Second, evaluation metrics and an expert questionnaire survey were developed to assess ChatGPT’s performance in CF …


Engineering The Immune Response To Biomaterials, Abolfazl Salehi Moghaddam, Mehran Bahrami, Einollah Sarikhani, Rumeysa Tutar, Yavuz Nuri Ertas, Faleh Tamimi, Ali Hedayatnia, Clotilde Jugie, Houman Savoji, Asma Talib Qureshi, Muhammad Rizwan, Chima V. Maduka, Nureddin Ashammakhi May 2025

Engineering The Immune Response To Biomaterials, Abolfazl Salehi Moghaddam, Mehran Bahrami, Einollah Sarikhani, Rumeysa Tutar, Yavuz Nuri Ertas, Faleh Tamimi, Ali Hedayatnia, Clotilde Jugie, Houman Savoji, Asma Talib Qureshi, Muhammad Rizwan, Chima V. Maduka, Nureddin Ashammakhi

Michigan Tech Publications

Biomaterials are increasingly used as implants in the body, but they often elicit tissue reactions due to the immune system recognizing them as foreign bodies. These reactions typically involve the activation of innate immunity and the initiation of an inflammatory response, which can persist as chronic inflammation, causing implant failure. To reduce these risks, various strategies have been developed to modify the material composition, surface characteristics, or mechanical properties of biomaterials. Moreover, bioactive materials have emerged as a new class of biomaterials that can induce desirable tissue responses and form a strong bond between the implant and the host tissue. …


Experimental Characterisation Of Laser Cladding Of Crniw And Crnifealzr Powders On H13 Tool Steel And Optimisation Of Process Parameters, Martin Vinoth S May 2025

Experimental Characterisation Of Laser Cladding Of Crniw And Crnifealzr Powders On H13 Tool Steel And Optimisation Of Process Parameters, Martin Vinoth S

Theses and Dissertations

In this work, laser cladding on H13 steel substrate with two different powder compositions CrNiW and CrNiFeAlZr has been carried out. The laser power, powder feed rate, and scanning speed were varied and the clad dimensions, aspect ratio, and dilution percentage were measured. The microhardness found in the CrNiW clad is 834 ± 20 HV0.5, which is higher than that of the CrNiFeAlZr clad (780 ± 20 HV0.5) as well as the substrate (548 ± 20 HV0.5).

The X-ray Diffraction (XRD) patterns identified the common phase creation of Ni3C and Fe3C for CrNiFeAlZr and CrNiW coatings, while the oxide formation …


Sharc: Simulator For Hardware Architecture And Real-Time Control, Paul K. Wintz, Yasin Sonmez, Paul Griffioen, Mingsheng Xu, Surim Oh, Heiner Litz, Ricardo G. Sanfelice, Murat Arcak May 2025

Sharc: Simulator For Hardware Architecture And Real-Time Control, Paul K. Wintz, Yasin Sonmez, Paul Griffioen, Mingsheng Xu, Surim Oh, Heiner Litz, Ricardo G. Sanfelice, Murat Arcak

Faculty Work Comprehensive List

Tight coupling between computation, communication, and control pervades the design and application of cyber-physical systems (CPSs). Due to the complexity of these systems, advanced design procedures that account for these tight interconnections are paramount to ensure the safe and reliable operation of control algorithms under computational constraints. This paper presents the Simulator for Hardware Architecture and Real-time Control (Sharc) to assist in the co-design of control algorithms and the computational hardware on which they are run. Sharc simulates the execution of a user-specified control algorithm on a given processor microarchitecture configuration, evaluating how computational constraints affect the dynamical properties of …


Research On Modeling, Optimization And Application Of Aeroengine Oil System, Shijie Huang, Zhensheng Zhang, Jing Cai, Rui Zhang May 2025

Research On Modeling, Optimization And Application Of Aeroengine Oil System, Shijie Huang, Zhensheng Zhang, Jing Cai, Rui Zhang

Journal of System Simulation

Abstract: In response to the high cost and long cycle of using experimental methods for monitoring, diagnosing, and predicting lubricating oil system, a simulation model for oil system is constructed and optimized, and the application of the model in health management of oil system is proposed. Based on the physical characteristics of the components in the oil system, subsystem models for ventilation, oil supply, thermodynamics, and oil return are constructed using a certain engine oil system as an example, and the whole oil system model is constructed and solved iteratively. The model is optimized by combining particle swarm optimization and …


Experimentally Driven Numerical Model Of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using A New Figure Of Merit, Kyrillos Selim, Ziad Khalifa, Amira Ali, Sameh O. Abdellatif May 2025

Experimentally Driven Numerical Model Of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using A New Figure Of Merit, Kyrillos Selim, Ziad Khalifa, Amira Ali, Sameh O. Abdellatif

Electrical Engineering

This study presents an experimentally driven numerical model for evaluating carbon/polyaniline (PANI)-based glucose monitoring sensors (GMSs), focusing on innovative configurations using graphene-PANI and carbon nanotube (CNT)-PANI composites. We performed a thorough analysis of the morphological, electrophysical, and electrical properties of these materials, ultimately leading to the extraction of key electrical parameters for integration into a finite element model (FEM). This model simulates the entire sensor, enabling the estimation of critical performance metrics such as sensitivity, limit of detection (LOD), linearity, and power consumption. Our findings demonstrate that the CNT-PANI configuration significantly outperforms the laser-induced graphene (LIG)-PANI electrode, achieving a figure …


Leveraging Artificial Intelligence In Education To Drive Cross-Sector Innovation, Brent Terwilliger, John Faraca May 2025

Leveraging Artificial Intelligence In Education To Drive Cross-Sector Innovation, Brent Terwilliger, John Faraca

Publications

As artificial intelligence (AI) reshapes educational practices, particularly in technical fields such as uncrewed systems, robotics, and aviation/ aerospace, its integration raises promise and complexity. This exploratory study features an investigation of the impact AI tools adoption has on instruction, curriculum support, and workforce preparation, with a focus on online learning environments. Drawing from pilot survey data across aviation and aerospace education stakeholders and hands-on evaluation of AI video production platforms, findings reveal diverse applications, perceived benefits, and critical concerns, including ethical, pedagogical, and institutional challenges. Additionally, the analysis explored how AI-enabled education intersects with broader industry and government innovation …


Finite Volume Incompressible Lattice Boltzmann Framework For Non-Newtonian Flow Simulations In Complex Geometries, Akshay Dongre, John Ryan Murdock, Song Lin Yang May 2025

Finite Volume Incompressible Lattice Boltzmann Framework For Non-Newtonian Flow Simulations In Complex Geometries, Akshay Dongre, John Ryan Murdock, Song Lin Yang

Michigan Tech Publications

Arterial diseases are a leading cause of morbidity worldwide, necessitating the development of robust simulation tools to understand their progression mechanisms. In this study, we present a finite volume solver based on the incompressible lattice Boltzmann method (iLBM) to model complex cardiovascular flows. Standard LBM suffers from compressibility errors and is constrained to uniform Cartesian meshes, limiting its applicability to realistic vascular geometries. To address these issues, we developed an incompressible LBM scheme that recovers the incompressible Navier–Stokes equations (NSEs) and integrated it into a finite volume (FV) framework to handle unstructured meshes while retaining the simplicity of the LBM …


Evaluation Of Schoenoplectus Californicus In An Artificial System For E. Coli Removal, Kimia Ahmadiyehyazdi May 2025

Evaluation Of Schoenoplectus Californicus In An Artificial System For E. Coli Removal, Kimia Ahmadiyehyazdi

Masters Theses (Archived)

Green technologies and nature-based solutions like constructed wetlands have be come more popular due to their environmentally friendly approach to remediation, low cost of construction, and maintenance. Also, they have shown efficiency in removing a wide range of contaminants. However, choosing a suitable aquatic plant for this system is one of the questions that should be answered wisely. Schoenoplectus californicus– Giant Bulrush is an aquatic plant that was tested in this controlled constructed wetland, and the final concentration of the targeted microbial contamination, which is E. coli, was reduced remarkably. Also, for this study, soil was removed from the …


Uhpc Incorporated With Non-Metallic/ Hybrid Fibers And Industrial Wastes - A Comprehensive Study On The Physical, Mechanical Properties And Performance, Sujitha Magdalene P May 2025

Uhpc Incorporated With Non-Metallic/ Hybrid Fibers And Industrial Wastes - A Comprehensive Study On The Physical, Mechanical Properties And Performance, Sujitha Magdalene P

Theses and Dissertations

The demand for sustainable and high-performance construction materials has led to the exploration of alternative fine aggregates and fiber reinforcements for Ultra-High-Performance Concrete (UHPC). This study investigates the feasibility of using iron ore tailings (IOT), manufactured sand (MS), and copper slag (CS) as partial replacements for river sand (RS), along with various fiber reinforcements, to enhance mechanical properties, durability, and microstructural integrity in UHPC.

The results indicate that IOT at a 30% replacement level (IOT1) exhibited the highest 56-day compressive strength, outperforming MS and CS. Copper slag was found unsuitable for UHPC due to its lower long-term strength. While both …


Removal Of Diisopropylamine From Water Using Ultraviolet- And Thermal-Activated Persulfate Degradation, Eric Soliz May 2025

Removal Of Diisopropylamine From Water Using Ultraviolet- And Thermal-Activated Persulfate Degradation, Eric Soliz

Masters Theses (Archived)

UV light-activated persulfate degradation of diisopropylamine (DIPA) was explored as a means for improving water quality in product water derived from oil and natural gas produced water. A set of temperature swing solvent extraction (TSSE) tests was conducted to investigate the effect of varying ratios of DIPA to feed ratios on water recovery and conductivity and also to reinforce available data suggesting that TSSE may remove saline ions from synthetic produced water enough to improve water quality sufficient enough at sufficient quantities enough for reuse. TSSE may result in residual DIPA remaining in the product water. A three-part test to …


Sustainability In The Cruising Industry: Innovations In Air Quality, Energy Efficiency, And Waste Management, Fikret Durmus, Mi Ran Kim May 2025

Sustainability In The Cruising Industry: Innovations In Air Quality, Energy Efficiency, And Waste Management, Fikret Durmus, Mi Ran Kim

ICHRIE Research Reports

The cruise industry, a cornerstone of the global hospitality and tourism sector, faces increasing scrutiny over its environmental impact. As passenger numbers grow, so does the industry's responsibility to adopt sustainable practices. This report examines key innovations in air quality management, energy efficiency, and waste management, highlighting the industry's transition from historically high emissions and waste production to advanced sustainability initiatives. Key focus areas include evolving maritime regulations, adopting cleaner propulsion technologies, integrating energy-efficient solutions, and improving waste treatment practices. Findings indicate that industry leaders are investing in liquefied natural gas engines, exhaust gas cleaning systems, and onshore power supply …


An Artificial Neural Network-Based Battery Management System For Lifepo4 Batteries, Roger Painter, Ranganathan Parthasarathy, Lin Li, Irucka Embry, Lonnie Sharpe, S. Keith Hargrove May 2025

An Artificial Neural Network-Based Battery Management System For Lifepo4 Batteries, Roger Painter, Ranganathan Parthasarathy, Lin Li, Irucka Embry, Lonnie Sharpe, S. Keith Hargrove

Civil and Architectural Engineering Faculty Research

We present a reduced-order battery management system (BMS) for lithium-ion cells in electric and hybrid vehicles that couples a physics-based single-particle model (SPM) derived from the Cahn–Hilliard phase-field formulation with a lumped heat-transfer model. A three-dimensional COMSOL® 5.0 simulation of a LiFePO4 particle produced voltage and temperature data across ambient temperatures (253–298 K) and discharge rates (1 C–20.5 C). Principal component analysis (PCA) reduced this dataset to five latent variables, which we then mapped to experimental voltage–temperature profiles of an A123 Systems 26650 2.3 Ah cell using a self-normalizing neural network (SNN). The resulting ROM achieves real-time prediction accuracy comparable …


Bounding Case Requirements For Power Grid Protection Against High-Altitude Electromagnetic Pulses, Connor A. Lehman, Darrell Robinette, Wayne Weaver, David G. Wilson May 2025

Bounding Case Requirements For Power Grid Protection Against High-Altitude Electromagnetic Pulses, Connor A. Lehman, Darrell Robinette, Wayne Weaver, David G. Wilson

Michigan Tech Publications

Securing the power grid is of extreme concern to many nations as power infrastructure has become integral to modern life and society. A high-altitude electromagnetic pulse (HEMP) is generated by a nuclear detonation high in the atmosphere, producing a powerful electromagnetic field that can damage or destroy electronic devices over a wide area. Protecting against HEMP attacks (insults) requires knowledge of the problem’s bounds before the problem can be appropriately solved. This paper presents a collection of analyses to determine the basic requirements for controller placements on a power grid. Two primary analyses are conducted. The first is an inverted …


Load Forecasting And Modeling For Power System, Han Guo May 2025

Load Forecasting And Modeling For Power System, Han Guo

Electrical Engineering Theses and Dissertations

Accurate load forecasting and modeling play a pivotal role in ensuring the stability, reliability, and economic efficiency of modern power systems. With the increasing integration of renewable energy sources, distributed energy resources, and demand-side management strategies, power systems are becoming more dynamic and complex, making traditional load forecasting methods inadequate. This dissertation introduces two novel approaches to address the challenges associated with day-ahead load forecasting and load modeling.

First, a Diffusion Model-Based Probabilistic Day-Ahead Load Forecasting (PDALF) Framework is proposed to enhance the accuracy and robustness of load forecasting. By employing a conditional denoising diffusion probabilistic model (DDPM), the framework, …


A Highly Sensitive Electrochemical Immunosensor For Cortisol Detection, Pritu Sarkar, Ali Ashraf, Ahmed Hasnain Jalal, Fahmida Alam, Nazmul Islam May 2025

A Highly Sensitive Electrochemical Immunosensor For Cortisol Detection, Pritu Sarkar, Ali Ashraf, Ahmed Hasnain Jalal, Fahmida Alam, Nazmul Islam

Mechanical Engineering Faculty Publications

In this research, an interdigitated gear-shaped working electrode is presented for cortisol sensing. Overall, the sensor was designed in a three-electrode system and was fabricated using direct laser scribing. A synthesized conductive ink based on graphene and polyaniline was further employed to enhance the electrochemical performance of the sensor. Scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy were employed for physicochemical characterization of the laser-induced graphene (LIG) sensor. Cortisol, a biomarker essential in detecting stress, was detected both in phosphate-buffered saline (PBS, pH = 7.4) and human serum within a linear range of 100 ng/mL to 100 µg/mL. …


Machine Learning-Driven Optimization Of Piezoelectric Energy Harvesters For Low-Frequency Applications, Kyrillos Selim, Login Moustafa, Sameh O. Abdellatif May 2025

Machine Learning-Driven Optimization Of Piezoelectric Energy Harvesters For Low-Frequency Applications, Kyrillos Selim, Login Moustafa, Sameh O. Abdellatif

Electrical Engineering

To enhance energy harvesting efficiency, this paper explores the optimization of a cantilever-based piezoelectric energy harvester by integrating advanced machine learning (ML) methodologies. Leveraging a meticulously trained model on data sourced from a sophisticated two-dimension (2D) COMSOL Multiphysics numerical simulation, the study focuses on the critical input parameters, particularly the dimensions of the piezoelectric thin film. Through extensive simulations, the analysis delves into power density extraction and resonance frequency for various configurations. The culmination of rigorous simulations and analysis has led to the identification of an optimal design configuration for the cantilever piezoelectric energy harvester, characterized by a length of …


Enhancing Water Supply Resilience & Sustainability: Potential Solutions To Address Water Scarcity In Bogotá, Colombia, Sophia Alvarez Wong May 2025

Enhancing Water Supply Resilience & Sustainability: Potential Solutions To Address Water Scarcity In Bogotá, Colombia, Sophia Alvarez Wong

Master's Projects and Capstones

Municipal water utilities are in urgent need of adapting to the intensifying impacts of climate change and population growth—key drivers of urban water scarcity worldwide. In rapidly expanding cities like Bogota, Colombia, these pressures have contributed to a severe water crisis driven by prolonged droughts, ecosystem degradation, increasing water demands, and overdependence on limited water sources. This study explores potential adaptation and management strategies that utilities can implement to sustainably strengthen supply system resilience and enhance water security, in the context of low- to middle-income regions. A series of comparative and case study analyses were conducted to assess the feasibility …


Wildfire Hydrologic Impacts, Kathleen E. Inman May 2025

Wildfire Hydrologic Impacts, Kathleen E. Inman

Theses and Dissertations

Wildfires are essential processes for certain ecosystems but are increasing in severity and occurrence. These increases are negatively changing hydrology. Anticipating the hydrologic changes is necessary for management of effected watersheds, infrastructure, and downstream users. This study hypothesized land cover changes post-fire would increase water temperature and discharge in burned watersheds located in the Willamette Basin. This study (1) evaluated the change in estimated curve numbers (CN) from land cover pre-fire and post-fire to assess expected runoff impacts in watersheds, and (2) identified the significance of actual water temperature and discharge changes using non-parametric statistical analysis. An unburned watershed and …


06.16.2025 Ored Connect, Liz Williamson May 2025

06.16.2025 Ored Connect, Liz Williamson

ORED Newsletter

Email address Matters with SPAN and ARC Forms

Participant Support Costs training for PIs available in Blackboard


Development Of Non-Precious Iron-Cobalt Alloy Catalyst For Electrocatalytic Reaction, Harsh Panchal May 2025

Development Of Non-Precious Iron-Cobalt Alloy Catalyst For Electrocatalytic Reaction, Harsh Panchal

Electronic Theses & Dissertations

The development of a FeCo alloy catalyst with tunable Fe/Co ratios is examined to improve electrocatalytic performance in reactions like the oxygen evolution reaction (OER), hydrogen evolution reaction (HER), and oxygen reduction reaction (ORR). Many energy conversion devices, such as fuel cells, metal-air batteries, and water-splitting systems, depend on these interactions to function. These technologies have huge potential to meet the increasing need for hydrogen production and renewable energy sources worldwide, which are critical to attaining a sustainable energy future. When compared with noble metal-based catalysts, the FeCo alloy catalyst shows much higher catalytic activity, according to previous studies. Hydrothermal …


Lateral Control Of Autonomous Vehicle Using Deep Cnn And Ampc, Iffat Ara Ebu May 2025

Lateral Control Of Autonomous Vehicle Using Deep Cnn And Ampc, Iffat Ara Ebu

Theses and Dissertations

Autonomous functionalities are pivotal for the advancement of Advanced Driver Assistance Systems (ADAS), driving towards collision-free and environmentally sustainable transportation. This thesis presents two distinct studies addressing critical aspects of autonomous vehicle control: lane centering via deep learning and lateral vehicle control using model predictive control. The first study explores end-to-end learning f or autonomous s teering command generation, focusing on lane centering. A convolutional neural network (CNN) model, inspired by NVIDIA’s PilotNet, is employed to directly map raw camera pixel inputs to steering commands, eliminating the need for intermediate feature engineering. The model is trained and validated using datasets …


Finite Element Analysis Of Hydroxyapatite (Ha) Coated Porous We43 Magnesium Scaffolds For Simulating Long-Time In Vitro Degradation Using A Continuum Damage Model, Dam Kim May 2025

Finite Element Analysis Of Hydroxyapatite (Ha) Coated Porous We43 Magnesium Scaffolds For Simulating Long-Time In Vitro Degradation Using A Continuum Damage Model, Dam Kim

Theses and Dissertations

While magnesium and its alloys are viable biodegradable implant candidates for its similarity of Young’s modulus with human bone and its strong biocompatibility, a pure magnesium scaffold degrades too rapidly to be used in many orthopedic implications. Overcoming this high degradation rate has been one of the biggest technical challenges for Mg-based biomedical applications. This research focuses on validating a finite element analysis framework using a continuum damage model and its application to simulate the degradation process of non-coated additively manufactured WE43 and HA-coated WE43 magnesium scaffolds. This work includes determining model input parameters by matching in vitro experiment results …


An In Depth Examination Of Educational, Family, Economic, And Personal Determinants On Academic Performance, Engagement, And Stress: A Comprehensive Study Among Engineering Students, Oumaima Larif May 2025

An In Depth Examination Of Educational, Family, Economic, And Personal Determinants On Academic Performance, Engagement, And Stress: A Comprehensive Study Among Engineering Students, Oumaima Larif

Theses and Dissertations

This study explores the effects of family, education, economic, and personal factors on students’ decisions to pursue engineering as a profession and their long-term impact on performance as engineering students. We adopted a mixed-method approach, collecting data through surveys administered to undergraduate and graduate engineering students at Mississippi State University. The study results revealed that family, education, economic, and personal factors profoundly influence students' decisions to study engineering. We found that parental expectations, background information, and socioeconomic status, in conjunction with cultural norms, values, gender expectations, and religious beliefs, affect students. Additionally, this study identified gaps in the existing literature …


Removal Of Harmful Algal Bloom Toxin, Microcystin-Lr Via Graphene Coated Polymers, Justin Douglas Puhnaty May 2025

Removal Of Harmful Algal Bloom Toxin, Microcystin-Lr Via Graphene Coated Polymers, Justin Douglas Puhnaty

Theses and Dissertations

This study investigates a novel 3D-printed graphene-coated polymer (GCP) for the removal of Microcystin-LR (MC-LR), a harmful cyanotoxin produced during harmful algal blooms (HABs). While graphene nanoplatelets (GnPs) exhibit high adsorption capacity, their powdered form limits practical application. To address this, GnPs were coated onto 3D-printed poly(lactic acid) (PLA) substrates, enabling enhanced handling for field deployment. Surface characterization using laser confocal microscopy, Raman spectroscopy, and thermogravimetric analysis confirmed GnP distribution and coating uniformity. Batch adsorption experiments revealed pseudo-second-order kinetics, a maximum adsorption capacity (qmax) of 596 μg/g, and adsorption behavior best described by the Langmuir isotherm. Statistical analysis and comparison …