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Delivery Of Tgfβ3 From Magnetically Responsive Coaxial Fibers Reduces Spinal Cord Astrocyte Reactivity In Vitro, Jessica L. Funnell, Jasper Fougere, Diana Zahn, Silvio Dutz, Ryan J. Gilbert

Chemical and Biochemical Engineering Faculty Research & Creative Works

A spinal cord injury (SCI) compresses the spinal cord, killing neurons and glia at the injury site and resulting in prolonged inflammation and scarring that prevents regeneration. Astrocytes, the main glia in the spinal cord, become reactive following SCI and contribute to adverse outcomes. The anti-inflammatory cytokine transforming growth factor beta 3 (TGFβ3) has been shown to mitigate astrocyte reactivity; however, the effects of prolonged TGFβ3 exposure on reactive astrocyte phenotype have not yet been explored. This study investigates whether magnetic core-shell electro spun fibers can be used to alter the release rate of TGFβ3 using externally applied magnetic fields, …

A Theoretical Framework For Resilience In Complex System Governance (Csg), Susan A. Caskey

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation addresses a critical gap in resilience research within complex systems by developing a theoretical framework for governance resilience—an underexplored area despite governance's crucial role in maintaining system resilience. Using the Complex System Governance (CSG) framework (Keating, Katina, Chesterman, et al., 2022; Keating & Katina, 2019), resilience is conceptualized as a system's ability to absorb disturbances while sustaining performance and enabling adaptive transformation. This involves three main capabilities: persistence, adaptability, and transformation in response to both internal and external pressures.

Through a constructivist grounded theory approach involving iterative coding, memoing, and theory development, this study inductively constructs a governance …

Feasibility Study Of Oyster Shell Filtration Media For Stormwater Pollutants Removal, Sadiq Omer

Civil & Environmental Engineering Theses & Dissertations

The depletion of resources has raised interest in reusing or incorporating by-products into alternative materials. In the effort for net zero emissions, waste reduction, and a circular economy, it is crucial to reinvent the alternative utilization strategy for by-products as construction materials sustainably. This research examines the alternative utilization strategy for oyster shell by-products in regular stormwater pollutant removal best management practices (BMPs).

Numerous research has examined the utilization of oyster shell waste as a construction material in Asia and Europe, specifically focusing on the physical properties of crushed oyster shells as alternatives for aggregates. No studies have been identified …

Real-Time Navigation System For Breast Cancer Surgery With Pre- And Intra-Operative Imaging Using Neural Networks, Motaz Alqaoud

Biomedical Engineering Theses & Dissertations

Breast cancer is one of the most frequently diagnosed malignancies in women worldwide, necessitating precise diagnosis and treatment. Breast-conserving surgery (BCS) is the primary treatment for nonpalpable cases, yet current approaches often lack accuracy due to the absence of real-time 3D imaging during surgery. This limitation impairs surgeons’ ability to visualize tumor locations, compromising outcomes and potentially leading to repeat surgeries with higher risks, undesirable cosmetic results, increased costs, and, in some cases, mastectomy. Thus, there is a critical need for a navigation system to facilitate accurate tumor excision in nonpalpable breast cancer through real-time patient-specific 3D tracking.

This study …

Machine Learning And Simulation Techniques For Detecting Buoys From Lidar Data, Christopher Adolphi

Electrical & Computer Engineering Theses & Dissertations

Maritime autonomy, specifically the use of autonomous and semi-autonomous maritime vessels, is a key enabling technology supporting a set of diverse and critical research areas, including coastal and environmental resilience, assessment of waterway health, ecosystem/asset monitoring and maritime port security. Critical to the safe, efficient and reliable operation of an autonomous maritime vessel is its ability to perceive the external environment through onboard sensors. The main sensor utilized in this research is a LiDAR sensor. This sensor is able to generate point clouds of the surrounding environment, of which a machine learning model is used to label each point in …

An Integrated Theoretical Socio-Technical Framework For Implementing Service Robots’ Integration In Healthcare, Sujatha Alla

Engineering Management & Systems Engineering Theses & Dissertations

Healthcare workers, either clinical or non-clinical, are obligated to serve patients. However, lack of a sufficient number of professionals leads to burnout, severe stress, and, consequently, decreased quality of services. In this context, very few countries have been successful in employing service robots to perform dull, dirty, and/or dangerous tasks related to patient wellbeing/healthcare, while most countries are still skeptical about it. As robotics advances, there is an opportunity for healthcare to take advantage of this technology to reduce personnel workload and to reduce the possibility of exposure to contagious pathogens. However, healthcare is a vulnerable environment and requires critical …

Intercellular Mitochondrial Transfer Contributes To Microenvironmental Fate Redirection Of Mammary Cancer Cells, Julie Sofie Bjerring

Biomedical Sciences Theses & Dissertations

The dynamic cellular microenvironment, made up of resident cells and various macromolecules, differs markedly across tissues in the body. The multidirectional signals that cells receive from this microenvironment, along with the signaling they send back, heavily influence their physiology and behavior. Recent important findings have further validated this notion as the mammary microenvironment has been shown to suppress tumor progression by redirecting cancer cells to adopt a normal mammary epithelial progenitor fate in vivo. However, the mechanism(s) driving changes in metabolic reprogramming and cancer fate redirection is understudied. The work presented in this dissertation focuses on exploring the impact of …

Thermal Management For Optimal Performance Of Unitized Regenerative Fuel Cells, Mythy T. Tran

Mechanical & Aerospace Engineering Theses & Dissertations

As the race to net zero energy intensifies around the world, hydrogen production and fuel cell technologies are attracting more attention, and the technologies are growing rapidly. Together, hydrogen production and fuel cell technologies hold potential for a reliable, green, and sustainable energy system. Hydrogen is an excellent energy carrier and can be produced from various sources, especially green and renewable sources. Fuel cells generate electricity and water from hydrogen and oxygen. In reverse mode, fuel cells operate as electrolyzers to produce hydrogen and oxygen from electricity and water. However, the major drawback that keeps hydrogen and fuel cells from …

Simulating The Compound Impacts Of Climate Change And Sea-Level Rise On Coastal Shallow Groundwater Using An Integrated Surface-Subsurface Hydrologic Model, Zhaoyi Cai

Civil & Environmental Engineering Theses & Dissertations

As climate change intensifies and sea levels rise, coastal aquifers become increasingly vulnerable to interacting oceanic and terrestrial processes. This dissertation examines the combined impacts of climate change and sea-level rise (SLR) on coastal shallow groundwater using an integrated surface-subsurface hydrologic model, focusing on the low-lying Little Creek watershed (LCW) in Norfolk, Virginia. The SWAT-MODFLOW model, a coupled system, unifies land surface, streamflow, and groundwater processes, providing a comprehensive framework for watershed-aquifer analysis. Model parameters were derived from U.S. Geological Survey datasets, relevant literature, station records, and technical reports, followed by meticulous calibration. The validated model first simulated baseline groundwater …

An Agent-Based Approach For Designing A Sustainable Supplier Selection In Stochastic Environment: A Simulation Study, Sheida Etemadidavan

Engineering Management & Systems Engineering Theses & Dissertations

In the 21st century, businesses are constantly striving for competitive advancement and increasing their economic performance in the rapidly changing market. Collaboration with other businesses and partnerships with them are becoming more common. As such, businesses are starting to invest in finding the right partners to stay competitive in an ever-changing business landscape. Suppliers play a crucial role in businesses' decision-making as they provide the materials, goods, and services necessary for a company to operate and succeed. Therefore, their selection, management, and relationship must be carefully considered to ensure optimal performance and profitability. A sustainable framework in a business's relationship …

Roles Of The His-Purkinje System In Long Qt Syndrome Mediated Arrhythmias, Anthony Owusu-Mensah

Biomedical Engineering Theses & Dissertations

Long QT syndrome (LQTS) is a genetic or drug-induced electrophysiological disorder in the heart that prolongs the QT interval on the electrocardiogram. LQTS is present in considerable proportions (1:3000 to 1:5000) of the general population. LQTS has a high incidence of malignant ventricular arrhythmias during physical and emotional stress and is a significant cause of sudden death in younger subjects. This poses a substantial medical burden on the healthcare system in terms of morbidity, mortality, and finances. Despite extensive genetic research into LQTS, the mechanisms underlying spontaneous initiation and maintenance of arrhythmias are not fully understood. Beta-blockers are the standard …

Mannosylated Pamam G2 Dendrimers Mediated Rate Programmed Delivery Of Efavirenz Target Hiv Viral Latency At Reservoirs, Rohini Kharwad, Mohsin Kazi, Nilesh Mahajan, Payal Badole, Sachin More, Asaad Kayali, Md Noushad Javed, Mohammed Kaleem

Mechanical Engineering Faculty Publications

In this current research, we conceptualized a novel nanotechnology-enabled synthesis approach of targeting HIV-harboring tissues via second-generation (G2) polyamidoamine (PAMAM) mannosylated (MPG2) dendrimers for programmed delivery of anti-HIV drugs efavirenz (EFV) and ritonavir (RTV). Briefly, here mannose served purpose of ligand in this EFV and RTV-loaded PAMAM G2 dendrimers, synthesized by divergent techniques, denoted as MPG2ER. The developed nanocarriers were characterized by different analytical tools FTIR, NMR, zeta potential, particle size, and surface morphology. The results of confocal microscopy showed substantial alterations in the morphology of H9 cells, favored by relatively higher drug uptake through the MPG2ER. Interestingly, the drug …

Unveiling Similarities In The Code Of Life: A Detailed Exploration Of Dna Sequence Matching Algorithm, Mahmoud Y. Shams, Romany M. Farag, Dalia A. Aldawody, Huda E. Khalid, Ahmed K. Essa, Hazem M. El-Bakry, A. A. Salama

Neutrosophic Systems with Applications

Identifying similar DNA sequences is crucial in various biological research endeavors. This paper delves into the intricate workings of a specific algorithm designed for this purpose. We provide a systematic explanation, exploring how the algorithm handles user input, reads stored DNA sequences, utilizes the Word2Vec model for vector representation, and calculates sequence similarity using diverse metrics like Cosine Similarity and Neutrosophic Distance. Additionally, the paper explores the incorporation of neutrosophic values to account for uncertainty in the comparisons. Finally, we discuss the extraction of results, including matched sequences, similarity scores, and accuracy measures. This in-depth exploration provides a clear understanding …

Neutrosophic Approach To Water Quality Assessment: A Case Study Of Gomati River, The Largest River In Tripura, India, Ajoy Kanti Das, Nandini Gupta, Carlos Granados, Rakhal Das, Suman Das

Neutrosophic Systems with Applications

This study addresses the complexity of assessing river water quality, a multifaceted process influenced by numerous water quality parameters (WQPs) characterized by inherent uncertainties and diverse judgment information from decision-makers. These uncertainties and diverse judgment information can be effectively represented and simulated using Neutrosophic sets. In this study, we propose an effective water pollution rating system, the Neutrosophic water quality index (NWQI), to derive a water pollution score (NWQI-score) for rating water pollution levels. We demonstrate the application of our methodology through an assessment of water quality indices for rating pollution in the Gomati River, the largest river in Tripura, …

Evaluation Of Renewable Energy Sources For A Sustainable Future: A Multi-Criteria Decision-Making Approach, Mai Mohamed, Asmaa Elsayed

Neutrosophic Systems with Applications

The urgent global challenges of climate change, energy security, and environmental degradation highlight the need for sustainable energy solutions. Renewable energy sources (RES) present a viable pathway towards sustainability by mitigating greenhouse gas emissions, reducing reliance on fossil fuels, and fostering economic resilience. Purpose: The purpose of this paper is to propose an advanced Multi-Criteria Decision-Making (MCDM) approach to evaluate various RES by integrating environmental, economic, technological, social acceptance, and resource availability criteria, to identify the most suitable RES for sustainable energy solutions. Methodology: The study employs a hybrid method combining Type-2 Neutrosophic Numbers (T2NN) with LOPCOW (Logarithmic Percentage Change …

Final Report - Mixed Reality For Beyond Visual Line-Of-Sight Bridge Inspection Using Robot-Assisted Nondestructive Evaluation, Genda Chen, Joel Runji

Project IM-5

To improve data consistency, work efficiency, inspector safety, and cost effectiveness during routine inspections, drones have been increasingly used in recent years to support imaging and scanning over the surface of various elements in a bridge for surface condition assessment. Most drones are operated manually within a visual line of sight and unable to inspect river-crossing bridges completely since not all elements can be viewed by a drone operator using a binocular. Even for autonomous drones with collision-avoidance features, physical interaction with a bridge for nondestructive evaluation (NDE) is currently impossible in practice. An alternative solution with robot-assisted remote nondestructive …

Final Report - Probability Of Detection In Corrosion Monitoring With Fe-C Coated Lpfg Sensors, Genda Chen, Ying Zhou, Pengfei Ma

Project SN-8

This project aimed to develop and evaluate two statistical methods for determining the probability of detection (POD) in corrosion monitoring using Fe–C coated long-period fiber grating (LPFG) sensors. These methods, referred to as the Size-of-Damage-at-Detection (SODAD) method and the Random Parameter Model (RPM), addressed limitations in traditional POD models by considering the time dependency inherent in sensor data. The goal was to assess steel mass loss at 90% detection probability and establish the largest undetectable mass loss threshold at a 95% lower confidence bound. Both methods were assessed for computational efficiency, sensitivity to distribution assumptions, and robustness under varying model …

Final Report - Hyperspectral Imaging And Analysis For Steel Paint Condition Assessment, Hongyan Ma, Genda Chen, Pengfei Ma

Project SN-9

This project aimed to understand the durability of multiple coating settings that had been widely used in highway bridges. Coatings can prevent their substrate from being contacted by aggressive particles and thus corrosion to preserve structural components. However, the wide selection of coatings for steel girders or truss can greatly impact the serviceability of bridges. This project studied four types of top-coat materials (epoxy, Alkyd, acrylic, and polyurethane) and two types of under-coat materials (epoxy and acyclic). The coatings were configured as two-layer and three-layer systems to evaluate their difference in durability. The degradation process of the coatings was monitored …

Final Report - Robot-Assisted Underwater Acoustic Imaging For Bridge Scour Inspection, Genda Chen, Peter Ogunjinmi, Son Nguyen

Project AS-8

This report details the development and testing of an innovative robotic system for underwater mapping and bridge scour inspection, integrating a 3D sonar with a modified remotely operated vehicle (ROV). The system addresses limitations in traditional scour monitoring methods, such as safety concerns and poor visibility after flooding. The research approach included laboratory experiments, pool testing, and field trials at two bridge sites in Missouri, with procedures developed for both water surface and underwater deployments. The system effectively mapped underwater structures and scour conditions, especially in hard-to-reach areas, revealing critical scouring, exposed pier footings and debris accumulation. The water surface …

Final Report - Bridge Inspection Robot Deployment Systems (Birds), Genda Chen, Son Nguyen, Alec Reven, Bo Shang

Project AS-4

This study aims to develop and evaluate Bridge Inspection Robot Deployment Systems (BIRDS) that support automated bridge inspection. BIRDS include uncrewed aerial vehicles (UAVs), structural crawlers, and/or their combination. A particular type of the BIRDS, which is a hybrid flying and traversing system called BridgeBot, is designed to aid in the inspection of steel and concrete girder bridges. BridgeBot has evolved in four prototypes (I-IV) for improved structural, mechanical, electronic, and control systems over the past five years. The first two prototypes built in Phases I and II were tested in laboratory to understand the feasibility of hybrid flying and …

Design Of An Above Pavement Wireless Sensor Node (Apwsn) For Real-Time Roadway Monitoring Using Piezoelectric Energy-Harvesting, Jochy Jonathan Perez

Theses and Dissertations

The evolution of Smart Highway and Internet of Things (IoT) technologies offers new opportunities to improve the safety and efficiency of vehicular traffic on roads. This research effort describes the development of a wireless pavement sensor that provides a novel method to detect key pavement parameters while incorporating low-power energy harvesting that leverages the kinetic energy generated by vehicular traffic. The Above Pavement Wireless Sensor Node (APWSN) is the embodiment of the approach. APWSN can facilitate the strategic deployment of sensors on a wide variety of roads to enable real-time data collection to support decision-making processes for road infrastructure maintenance …

Boosting Predictive Accuracy Of Single Particle Models For Lithium-Ion Batteries Using Machine Learning, Emmanuel Olugbade, Jonghyun Park

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The accuracy of single particle (SP) models for lithium-ion batteries at high C-rates is constrained by lithium concentration gradients in the electrolyte, which affect ionic conductivity, overpotential, and reaction rates. This study addresses these limitations using extreme gradient boosting machine learning (ML). By training our ML model with data from a comprehensive electrochemical (P2D) model and performing sensitivity analysis on key battery parameters, we enhance predictive accuracy. Compared to conventional SP and P2D models under constant current loading, our ML-based SP model achieves similar predictive accuracy to P2D, with significant improvements in computational efficiency. Additionally, the ML-based SP model demonstrates …

A Novel Approach To Evaluate Seatbelt Non-Compliance Of Drivers In New Jersey, Md Arifuzzaman Nayeem

Theses and Dissertations

This study intends to investigate the non-compliant behavior of drivers with seatbelt use in New Jersey. By examining various factors such as temporal and roadway characteristics, this study seeks to identify the underlying causes of this seatbelt non-compliance behavior. To overcome the limitations of traditional methods like cross-sectional data collection, a novel approach known as moving vehicle method was employed. To gain further insights, hypothesis tests were performed across the entire dataset to pinpoint significant temporal, roadway, and geometric factors contributing to non-compliant behaviors. In the subsequent step, the association of other risky behaviors like speeding and distracted driving with …

Aging Characteristics Of Lithium-Ion Battery Under Fast Charging Based On Electrochemical-Thermal-Mechanical Coupling Model, Dong-Xu Zuo, Pei-Chao Li

Journal of Electrochemistry

The aging characteristics of lithium-ion battery (LIB) under fast charging is investigated based on an electrochemical-thermal-mechanical (ETM) coupling model. Firstly, the ETM coupling model is established by COMSOL Multiphysics. Subsequently, a long cycle test was conducted to explore the aging characteristics of LIB. Specifically, the effects of charging (C) rate and cycle number on battery aging are analyzed in terms of nonuniform distribution of solid electrolyte interface (SEI), SEI formation, thermal stability and stress characteristics. The results indicate that the increases in C rate and cycling led to an increase in the degree of nonuniform distribution of SEI, and thus …

Nanopore Signal Deviations From Pseudouridine Modifications In Rna Are Sequence-Specific: Quantification Requires Dedicated Synthetic Controls, Amr Makhamreh, Sepideh Tavakoli, Ali Fallahi, Xinqi Kang, Howard Gamper, Mohammad Nabizadehmashhadtoroghi, Miten Jain, Ya-Ming Hou, Sara H Rouhanifard, Meni Wanunu

Department of Biochemistry and Molecular Biology Faculty Papers

Chemical modifications to mRNA respond dynamically to environmental cues and are important modulators of gene expression. Nanopore direct RNA sequencing has been applied for assessing the presence of pseudouridine (ψ) modifications through basecalling errors and signal analysis. These approaches strongly depend on the sequence context around the modification, and the occupancies derived from these measurements are not quantitative. In this work, we combine direct RNA sequencing of synthetic RNAs bearing site-specific modifications and supervised machine learning models (ModQuant) to achieve near-analytical, site-specific ψ quantification. Our models demonstrate that the ionic current signal features important for accurate ψ classification are sequence …

2024 Kentucky Water Resources Annual Symposium, Kentucky Water Research Institute

Kentucky Water Resources Annual Symposium

The program and proceedings contains details of the 2024 Kentucky Water Resources Symposium, including presentations, award winners, and poster presentations.

This symposium was planned and conducted as a part of the state water resources research institute annual program that is supported by Grant/Cooperative Agreement Number G21AP10631-02 from the United States Geological Survey (USGS). The contents of this proceedings document and the views and conclusions presented at the symposium are solely the responsibility of the individual authors and presenters and do not represent the official views of the USGS or of the symposium organizers and sponsors. This publication is produced with …

2024 Kentucky Water Resources Annual Symposium, Kentucky Water Research Institute

Kentucky Water Resources Annual Symposium

No abstract provided.

Multi-Functional Gelatin-Dithiolane Hydrogels For Tissue Engineering, Saad Asim, Cody Tuftee, Asma Talib Qureshi, Rachel Callaghan, Moira L. Geary, Mithun Santra, Vaibhav Pal, Ilayda Namli, Gary Hin Fai Yam, Ibrahim T. Ozbolat, Muhammad Rizwan

Michigan Tech Publications

Biomaterials that integrate multiple functionalities, mimic the extracellular matrix (ECM) microenvironment to support cellular growth, and adhere robustly to damaged tissues are highly needed to advance tissue engineering. Protein-based biomaterials are promising due to their inherent biocompatibility, biomimicry, biodegradation, and cell-supportive properties. Herein, by leveraging the unique ability of dithiolanes to generate on-demand in situ thiols, a new class of dithiolane-modified, protein-based biomaterial that combines unique, seemingly opposing functions for tissue engineering is developed. Dithiolane-modified gelatin, a model protein used herein, enabled photoinitiator-free photo-crosslinking to form multi-functional gelatin-dithiolane (GelDT) hydrogels, which displayed exceptional long-term stability in cell culture media ( …

A Novel Model Of Autologous Tooth Transplantation For The Study Of Nerve Recruitment, Teresa E. Fowler, Doan T. Bloomquist, Caroline Glessner, Poonam Patel, Jeffrey N. James, Kathryn Bollinger, Lynnette P. Mccluskey, Ryan F. Bloomquist

School of Dentistry Faculty Publications

Background: Limited treatment options exist for damaged nerves and despite impressive advances in tissue engineering, scientists and clinicians have yet to fully replicate nerve development and recruitment. Innervation is a critical feature for normal organ function. While most organs are innervated prior to birth, a rare example of postnatal nerve recruitment occurs in the natural development of secondary teeth during adolescence. Many animals undergo postnatal shedding of deciduous teeth with development and eruption of secondary teeth, a process requiring recruitment of nerve and vasculature to each tooth pulp for viability. Here, the investigators created a novel model for the study …

Ai-Enhanced Decision-Making For Course Modality Preferences In Higher Engineering Education During The Post-Covid-19 Era, Amirreza Mehrabi, Jason Morphew, Babak Nadjar Araabi, Negar Memarian, Hossein Memarian

School of Engineering Education Faculty Publications

The onset of the COVID-19 pandemic has compelled a swift transformation in higher-education methodologies, particularly in the domain of course modality. This study highlights the potential for artificial intelligence and machine learning to improve decision-making in advanced engineering education. We focus on the potential for large existing datasets to align institutional decisions with student and faculty preferences in the face of rapid changes in instructional approaches prompted by the COVID-19 pandemic. To ascertain the preferences of students and instructors regarding class modalities across various courses, we utilized the Cognitive Process-Embedded Systems and e-learning conceptual framework. This framework effectively delineates the …