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Articles 1591 - 1620 of 53023
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Temporal Evolution Of Workforce Fatality-Linked Factors In The Transportation Construction Sector, Mariam Elazhary, Islam H. El-Adaway
Temporal Evolution Of Workforce Fatality-Linked Factors In The Transportation Construction Sector, Mariam Elazhary, Islam H. El-Adaway
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Despite advancements in safety measures, fatalities in the transportation sector remain disproportionately higher than in other industries. Transportation sector fatalities arise from a combination of demographic, environmental, and occupational factors that amplify the overall risk. While strides have been made in understanding the factors contributing to fatalities, there remains a critical gap in research focused on their temporal evolution. The goal of this study is to investigate the temporal evolution of fatality-linked association factors in the transportation construction sector. The methodology encompassed three stages. Stage 1 was preprocessing the data: the US Census of Fatal Occupational Injuries, covering 3,792 fatality …
Price Adjustment Clauses: Enhanced Price Volatility Forecasting For Construction Materials, Ahmed Shiha, Mariam Elazhary, Islam H. El-Adaway
Price Adjustment Clauses: Enhanced Price Volatility Forecasting For Construction Materials, Ahmed Shiha, Mariam Elazhary, Islam H. El-Adaway
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Price adjustment clauses (PACs) are used by state departments of transportation (DOTs) to share the risk of material price fluctuations. Existing models that depict the price fluctuations of materials forecast a mean within a horizon while relying on the assumption of a constant volatility throughout that horizon. However, none of them examine whether the prices of construction material exhibit similar volatility following a sudden price surge or a price drop. The prospect of PACs and their associated trigger values is hindered in the absence of empirical assessments of their capacity to capture the volatilities in material prices. This paper fills …
Labor Productivity Losses Across Construction Trades: A Machine Learning Approach, Tamima Elbashbishy, Islam H. El-Adaway
Labor Productivity Losses Across Construction Trades: A Machine Learning Approach, Tamima Elbashbishy, Islam H. El-Adaway
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Labor productivity is a major concern in the construction industry. Existing research on construction labor productivity (CLP) within specific trades has produced inconsistent findings due to differences in the factors analyzed. This lack of consistency makes it difficult to identify the most critical drivers of productivity losses across trades. To address this gap, this study adopts a cross-trade analytical approach to systematically identify and evaluate the inefficiencies impacting labor productivity in multiple construction trades. Specifically, the study (1) identified common organizational and project-level inefficiencies that influence labor performance; (2) conducted an expert-based survey to measure the frequency and perceived impact …
Risk Allocation Model For Price Escalations In Construction Projects: Integrating Bargaining Game Theory And Probabilistic Bayesian Modeling, Yasser Jezzini, Rayan H. Assaad, Islam H. El-Adaway
Risk Allocation Model For Price Escalations In Construction Projects: Integrating Bargaining Game Theory And Probabilistic Bayesian Modeling, Yasser Jezzini, Rayan H. Assaad, Islam H. El-Adaway
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Economic market uncertainties, like those witnessed during pandemics and supply chain-related challenges, introduce complexity in ascertaining precise price estimates for construction materials. Despite some studies on risk allocation in construction projects utilizing quantitative and qualitative approaches, these studies fail to explain the underlying process of risk allocation due to a lack of theoretical support, indicating a need for a more structured and theoretically grounded approach to understanding risk allocation, specifically under volatile market conditions. To bridge this knowledge gap, this study proposes a novel game-theoretical model integrating Bayesian statistics and bargaining game theory dynamics, offering a robust framework for optimal …
Failure Analysis Of Prestressed Concrete Girder Bridges Under Over-Height Truck Impacts, Mohamed T. Elshazli, Mohamed Elgawady, Tao Xing, Ahmed Ibrahim
Failure Analysis Of Prestressed Concrete Girder Bridges Under Over-Height Truck Impacts, Mohamed T. Elshazli, Mohamed Elgawady, Tao Xing, Ahmed Ibrahim
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Accidental collisions between over-height trucks and bridge superstructures are a common threat to existing bridge infrastructure. These incidents often stem from illegal over-height vehicles or truck operators' unawareness of clearance limits, posing serious safety risks and causing substantial structural damage. This study presents a comprehensive numerical investigation of the dynamic response of prestressed concrete girder bridges subjected to over-height truck impacts. Large-scale finite element models were developed in LS-DYNA, with validation conducted against experimental results. The parametric study explored impact speeds ranging from 16 to 113 km/h (10 to 70 mph), impactor masses between 2 and 6 tons, impact locations, …
In Situ High-Temperature Raman Spectroscopy For Online Eaf Slag Analysis, Bohong Zhang, Hanok Tekle, Ronald J. O'Malley, Jeffrey D. Smith, Farhan Mumtaz, Jie Huang
In Situ High-Temperature Raman Spectroscopy For Online Eaf Slag Analysis, Bohong Zhang, Hanok Tekle, Ronald J. O'Malley, Jeffrey D. Smith, Farhan Mumtaz, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
Real-time monitoring of slag chemistry is critical for optimizing Electric Arc Furnace (EAF) steelmaking operations, where dynamic variations in slag composition directly influence slag foaming, refractory degradation, and thermal efficiency. Conventional techniques such as X-ray fluorescence (XRF), Fourier-transform infrared (FTIR), and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS) are commonly used to analyze slag composition, but their offline nature and equipment constraints limit their applicability for online monitoring in harsh industrial environments. To address this challenge, we present an in situ, high-temperature analytical approach that integrates Raman spectroscopy with a custom-designed fiber-optic probe for real-time slag characterization at …
The Application Of Vetiver Grass In Natural Disaster Mitigation And Environmental Protection In Vietnam: A Bibliometric Analysis And Literature Review, Truc Phan, Tan Nguyen, Thang Pham, Bich T. Luong, Huong Nguyen
The Application Of Vetiver Grass In Natural Disaster Mitigation And Environmental Protection In Vietnam: A Bibliometric Analysis And Literature Review, Truc Phan, Tan Nguyen, Thang Pham, Bich T. Luong, Huong Nguyen
Civil Engineering Faculty Publications
Vetiver grass (Vetiveria zizanioides or Chrysopogon zizanioides) is a versatile tropical plant widely recognized for its applications in environmental protection and natural disaster mitigation. In Vietnam, where natural disasters such as floods and landslides are frequent, particularly along highways, Vetiver grass has proven to be an effective bioengineering solution. This paper provides a comprehensive review of the applications and benefits of Vetiver grass in preventing soil erosion and stabilizing slopes along Vietnam’s transportation systems. A bibliometric analysis of 555 Scopus-indexed publications (2000 – 2024) was conducted using VOSviewer software to identify research trends, key themes, and knowledge gaps. The findings …
Identification Of Flow Regime In A Co-Current Upflow Packed Bed Reactor (U-Pbr) Using Gamma-Ray Densitometry (Grd), Youssef Yatimi, Ahmed Alalou, Muthanna H. Al-Dahhan
Identification Of Flow Regime In A Co-Current Upflow Packed Bed Reactor (U-Pbr) Using Gamma-Ray Densitometry (Grd), Youssef Yatimi, Ahmed Alalou, Muthanna H. Al-Dahhan
Chemical and Biochemical Engineering Faculty Research & Creative Works
Owing to their significant impact on the reaction rate, the comprehensive understanding of the hydrodynamics in any novel design of the Upflow Packed Bed Reactor (U-PBR) is essential for the optimization of its throughput. In this regard, the identification of the flow regime is of paramount importance. Therefore, in this work, we use the photon counts time-series data obtained using the non-invasive Gamma-ray densitometry (GRD) to identify, for the first time, the flow regimes and their transition velocities at two axial locations (Z/D=0.8,1.56) and five radial locations (r/R=0,±0.5,±0.9) within the packed catalysts' bed of U-PBR with a novel plenum design …
Understanding The Relationship Between Structural Failure And Fatalities In Tornadoes: A Quantitative Investigation Of The 2021 Midwest Tornado Outbreak, Yi Zhao, Ruwen Qin, John W. Van De Lindt, Justin Sharpe, Grace Yan
Understanding The Relationship Between Structural Failure And Fatalities In Tornadoes: A Quantitative Investigation Of The 2021 Midwest Tornado Outbreak, Yi Zhao, Ruwen Qin, John W. Van De Lindt, Justin Sharpe, Grace Yan
Engineering Management and Systems Engineering Faculty Research & Creative Works
During 1950-2011, the number of fatalities caused by tornadoes in the U.S. significantly exceeded the fatalities caused by both hurricanes and earthquakes. To reduce tornado induced fatalities, it is essential to understand how structures/building failures correlate with fatalities and who are more vulnerable to tornadoes. Insights from this study are intended to help provide information to decision-makers on where to allocate limited resources for enhancing tornado resilience. By examining both the fatality data and structural damage data in the 2021 Midwest Tornado Outbreak, the objective of this study is to examine the occurrence of fatalities during tornadoes across various types …
Predicting Groundwater Withdrawals Using Machine Learning With Limited Metering Data: Assessment Of Training Data Requirements, Dawit Asfaw, Ryan G. Smith, Sayantan Majumdar, Katherine Grote, Bin Fang, B. B. Wilson, V. Lakshmi, J. J. Butler
Predicting Groundwater Withdrawals Using Machine Learning With Limited Metering Data: Assessment Of Training Data Requirements, Dawit Asfaw, Ryan G. Smith, Sayantan Majumdar, Katherine Grote, Bin Fang, B. B. Wilson, V. Lakshmi, J. J. Butler
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
The future of major aquifer systems supporting irrigated agriculture is threatened due to unsustainable groundwater pumping. Metering of pumping is key for implementing robust groundwater management, but metering is limited in most aquifers. Although machine learning methods have been used to estimate pumping over certain regions, these studies have not fully demonstrated the data quantity and input parameter requirements to accurately estimate regional groundwater pumping. This study determined the data quantity required and identified relevant features to develop Random Forests-based annual groundwater pumping estimates (2008–2020) over the Kansas High Plains aquifer. We predicted pumping at two spatial scales, i.e., point …
Preliminary Investigation Of The Potential Health Risks Of Non-Formfitting Body Armor With A Focus On Female Warfighters, Melissa Sutter, Catherine E. Johnson
Preliminary Investigation Of The Potential Health Risks Of Non-Formfitting Body Armor With A Focus On Female Warfighters, Melissa Sutter, Catherine E. Johnson
Mining Engineering Faculty Research & Creative Works
Introduction Body armor is an important piece of protective equipment for warfighters in battlefield environments. With more women now filling military roles, body armor designs may need to be further refined to accommodate the female anatomy instead of the male-based unisex designs. Unisex designs have been found to have negative effects on female warfighter performance, resulting in discomfort, breathing difficulty, and air gaps forming between the armor and torso. This study aimed to investigate increased injury risk because of air gaps from shock wave exposure on warfighters wearing nonform-fitting armor and the influence of material properties. Based on literature, lowered …
Comprehensive Review Of In Vitro Approaches For Environmental Heavy Metal Exposure, Manas Warke, Madeline English, Camila Padilla, Lexie Gasco, Wendy Leisner, Rupali Datta, Smitha Rao
Comprehensive Review Of In Vitro Approaches For Environmental Heavy Metal Exposure, Manas Warke, Madeline English, Camila Padilla, Lexie Gasco, Wendy Leisner, Rupali Datta, Smitha Rao
Michigan Tech Publications
Heavy metals are ubiquitous environmental pollutants, contaminating air, soil, and water via the erosion of natural deposits, as well as originating from anthropogenic sources, such as agriculture, industries, transportation, and landfills. The increasing utilization of heavy metals over the years, combined with the persistent nature of metals in the environment poses a direct threat to human and environment health. Although regulatory limits have been established for toxic metals, assessing the associated health risks using real-life exposure scenarios remains challenging. In this review, we summarize the development and use of in vitro models based two- and three-dimensional cell culture systems, focusing …
Toward A Generalizable Perceptual Hashing Framework For Image Manipulation Detection, Priyanka Samanta
Toward A Generalizable Perceptual Hashing Framework For Image Manipulation Detection, Priyanka Samanta
Dissertations, Theses, and Capstone Projects
This thesis contributes to research in adversarial image manipulation detection. The primary motivation is the increasing need to verify digital images, especially for legal evidence, journalistic proof, or social media content—where manipulated or fabricated images can mislead, defame, or distort reality. A key application and contribution of this work is the development of eWitness, a blockchain application that generates and registers image provenance at capture time to enable independent verification of authenticity. The secret sauce behind the system is SmartHash, a novel and efficient perceptual hashing algorithm designed for real-world deployment in systems like eWitness. Unlike existing algorithms, SmartHash targets …
Text-Based Propaganda Detection, Vivek Sharma
Text-Based Propaganda Detection, Vivek Sharma
Dissertations, Theses, and Capstone Projects
In the digital age, the swift consumption of news and the widespread dissemination of propaganda significantly threaten democratic principles and informed decision-making. News organizations, often aligned politically, tailor their content to appeal to specific audiences, thereby perpetuating biases. Despite advancements in detecting propaganda through various computational techniques, including Large Language Models(LLM) and BERT-based approaches, significant challenges persist concerning data availability and the effectiveness of detection tools. This thesis explores the landscape of text-based propaganda and reviews related research in textual analysis. It introduces a novel method for collecting a social-media based dataset, which includes analysis of journalists' tweets to discern …
Wind Turbine Rotor Design Using High-Fidelity Aerostructural Optimization, Marco Mangano, Sicheng He, Yingqian Liao, Denis-Gabriel Caprace, Andrew Ning, Joaquim R. R. A. Martins
Wind Turbine Rotor Design Using High-Fidelity Aerostructural Optimization, Marco Mangano, Sicheng He, Yingqian Liao, Denis-Gabriel Caprace, Andrew Ning, Joaquim R. R. A. Martins
Faculty Publications
Large wind turbines yield more energy but demand careful aeroelastic blade design. Coupled multiphysics design strategies can reduce wind energy costs exploiting fluid-structure interactions. This work presents the first high-fidelity aerostructural optimization study of a large wind turbine rotor.We use blade-resolved fluid dynamics and structural solvers in a monolithic gradient-based optimization framework to explore steady-state torque and blade mass trade-offs. The coupled-adjoint approach computes gradients efficiently, enabling the optimization of over 100 structural and geometric parameters simultaneously. Our optimization study modifies a DTU 10 MW benchmark with a simplified structure and isotropic material properties. The tightly coupled optimizations increase torque …
Multimodal Learning In Real-World Application: Enhancing Feature Representation And Training Strategies, Nana Lin
Graduate Doctoral Dissertations
Multimodal learning has emerged as a critical paradigm for developing intelligent systems that can understand and reason across diverse inputs such as images, text, and audio data. Despite significant advances, effective deployment of multimodal models in practice remains a challenging task. This dissertation explores how multimodal learning can be effectively applied to high-stakes, real-world scenarios, with a focus on enhancing feature representation and training efficiency. Specifically, this research investigates multimodal learning strategies in two key domains: healthcare and surveillance.
In the healthcare domain, we explored the data fusion and alignment approaches for cognitive decline diagnoses. First, we propose the LOVEMA …
The Emergence Of Ai Chatbots In Education, Trek Martin
The Emergence Of Ai Chatbots In Education, Trek Martin
Journal of Graduate Education Research
The recent advent of popular AI applications in educational contexts has sparked renewed interest in the question of AI and guided learning platforms as teaching tools. What are the possibilities for learning? In the attempt to answer that question, limitations of the field must be brought to full attention, as well an understanding of whether or not those limitations will continue into the immediate future; this research examines the technical evolution of artificial intelligence in education, from early symbolic reasoning systems to modern machine-learning-based chatbots. It then examines that evolution in terms of the key challenges it faced throughout, and …
Smart Mobility Technologies In Urban Areas Of Emerging Economies: A Bibliometric Analysis, Peter Mugisha, Rose Luke, Joash Mageto, Hossana Twinomurinzi
Smart Mobility Technologies In Urban Areas Of Emerging Economies: A Bibliometric Analysis, Peter Mugisha, Rose Luke, Joash Mageto, Hossana Twinomurinzi
African Conference on Information Systems and Technology
Despite the adoption of smart mobility solutions in emerging economies, challenges such as traffic congestion, pollution and inadequate infrastructure still persist. This study analyses 540 scholarly articles published between 2003 and 2024 to evaluate how smart mobility technologies – such as Intelligent Transportation Systems (ITS), Internet of Things (IoT) and Artificial Intelligence (AI) – have been implemented in these regions. Data was retrieved from Scopus and Web of Science and analysed using Biblioshiny for bibliometric mapping and Atlas.ti for thematic analysis. The review identifies research trends and gaps, showing how ITS has improved transport management in cities like Nairobi, and …
Modeling, Control, And Learning For Whole-Body Manipulation With Large-Scale Soft Robots, Curtis C. Johnson
Modeling, Control, And Learning For Whole-Body Manipulation With Large-Scale Soft Robots, Curtis C. Johnson
Theses and Dissertations
This dissertation addresses the challenge of enabling soft robots to perform contact-rich manipulation tasks by overcoming limitations in hardware, modeling, control, and learning. First, we present hardware advancements with PneuDrive, a pneumatic control system for actuating soft robots. We also introduce Baloo, a hybrid soft-rigid robotic torso which achieves a single-arm payload capacity of 19.3 kg and robust whole-body grasping capabilities. We also develop a full-body tactile sensing system enabling piezoresistive sensor arrays to cover large areas (1 square meter) with over 8000 distributed sensing points. Second, we focus on developing tractable dynamic models based on the Recursive Newton-Euler algorithm …
Predicting The Response Of Tendon-Driven Prosthetic Finger With Hyperelastic Joints, Lucas Gallup, Mohamed Trabia, Brendan O'Toole
Predicting The Response Of Tendon-Driven Prosthetic Finger With Hyperelastic Joints, Lucas Gallup, Mohamed Trabia, Brendan O'Toole
Mechanical Engineering Faculty Research
Properly designed prosthetics hands can enhance the quality of life for those suffering from limb loss. Recently, 3D-printed prosthetic hands are becoming common. In these prostheses, fingers flex through the tendons that are activated by motion of the wrist. To provide spring action, thermoplastic polyurethane (TPU) hyperelastic joints are used to connect digits to each other as well as to the wrist. While these designs are common, no model for the relationship between tendon tension and joint flexion is available. This work has developed a quasi-static virtual work-based model to predict the relationship between tendon forces and the flexion of …
Pressure And Force Dynamics In Artificial Muscle Actuators: A State-Space And Optimization-Based Approach, Mohammad Elzein
Pressure And Force Dynamics In Artificial Muscle Actuators: A State-Space And Optimization-Based Approach, Mohammad Elzein
Dissertations and Theses
This two-part investigation explores the dynamic behavior of braided pneumatic actuators (BPAs) under bio-inspired pulse modulation, with the aim of improving their biomimetic force output and control. The first study examines the effect of pulse length and inter-pulse timing on BPA performance, revealing that force output is highly sensitive to the temporal structure of input pulses mirroring biological muscle behavior. Using dual-pulse actuation schemes, the results demonstrate that force responses exceed the additive contributions of individual pulses, with peak amplification occurring consistently at a 27 ms inter-pulse gap. Shorter pulse lengths (10–20 ms) yielded the highest normalized force increases, up …
Hydrosocial Ocean Commons: Offshore Wind Energy In Oregon, Bryce Ashlyn Sprauer
Hydrosocial Ocean Commons: Offshore Wind Energy In Oregon, Bryce Ashlyn Sprauer
Dissertations and Theses
The ocean has been culturally and legally conceptualized as a commons, a space of subsistence inherited by all. Enclosure or privatization creates overlapping jurisdictions of ocean space. The ocean is also the world's most significant carbon capture, absorbing billions of tons of anthropogenic carbon dioxide since the Industrial Revolution. Now, the ocean offers an additional opportunity to decarbonize energy production and reduce greenhouse gas emissions through 'new frontiers' of offshore wind technology; however, this potential is entangled within neoliberalism. Offshore wind is entering a fragmented legal landscape where the social-legal process of ocean jurisdiction remains contested. As the "new frontier" …
Free-Running Ring Oscillators For Crystal-Free Communication Systems: Design, Simulation Challenges, And Frequency Stability Improvements, Haziq Rohail
Dissertations and Theses
This thesis presents techniques for enhancing the frequency stability of ring oscillators (ROs) for crystal-free wireless communication systems. The first major contribution is a tutorial-style study of frequency stability metrics, providing clear definitions, conversions methods, and comparative analysis of commonly used figures of merit such as phase noise, Allan deviation, and jitter. The second contribution addresses the challenges of simulating phase noise in free-running ROs. Key techniques including Periodic Steady-State Noise (PNoise), Harmonic Balance Noise (HBNoise), and transient noise analysis are evaluated in terms of accuracy, convergence behavior, and simulation runtime. Based on these results, practical guidelines are offered for …
Exploring Arabic Large Language Models: A Comprehensive Review, Lamar Aljahdali, Joud Kaki
Exploring Arabic Large Language Models: A Comprehensive Review, Lamar Aljahdali, Joud Kaki
Effat Undergraduate Research Journal
This paper presents a comprehensive review of Arabic large language models (LLMs), exploring their capabilities, limitations, and potential impact on the Arabic NLP landscape. We analyze the performance of prominent LLMs, including JAIS, AraBERT, and BLOOM, highlighting their strengths and weaknesses on various NLP tasks. The review delves into critical challenges faced by Arabic LLMs, such as domain adaptation, cross-lingual capabilities, and ethical considerations. Additionally, the paper emphasizes the importance of responsible development and deployment practices for LLMs, ensuring fairness, transparency, and cultural sensitivity.
Equilibration And Transport Of Binary Mixtures On Planar And Porous Nanomaterials, Andrew Torres
Equilibration And Transport Of Binary Mixtures On Planar And Porous Nanomaterials, Andrew Torres
Electronic Theses and Dissertations
We present results of a Kinetic Monte Carlo investigation of the adsorption dynamics of binary gas mixtures on planar and porous sorbents, with a focus on identifying and characterizing kinetic processes involved in uptake evolution and how they influence equilibrium conditions. We also investigate varying thermodynamic simulation parameters such as interactions, alkane lengths, partial pressures and pore configurations to determine how they impact these kinetic processes as well as equilibrium properties. This study matters both for better understanding how kinetics and equilibrium are connected and for improving practical techniques in separation applications. For planar surfaces, weak species overshoot kinetic processes …
Developing Deep Learning Methods For Cognitive Impairment Detection Based On Non-Invasive Data, Muath Alsuhaibani
Developing Deep Learning Methods For Cognitive Impairment Detection Based On Non-Invasive Data, Muath Alsuhaibani
Electronic Theses and Dissertations
Cognitive impairment detection is on the rise to help reduce the burden of healthcare costs on institutions and individuals. Mild Cognitive Impairment (MCI) is an early stage of cognitive decline progressing to Alzheimer’s disease (AD) or AD-related Dementia (ADRD). Detecting the early stages of AD/ADRD is crucial for early interventions among older adults to mitigate cognitive decline over time. However, the current diagnostic methods are often costly and/or invasive, such as MRI and PET scans. Thus, the search for non-invasive and cost-effective screening tools for the early detection of cognitive impairment using speech, language, visual, and motor data is growing. …
Surgeon Ergonomics While Performing Total Knee Arthroplasty, Cameron Dahman
Surgeon Ergonomics While Performing Total Knee Arthroplasty, Cameron Dahman
Electronic Theses and Dissertations
One of the most prevalent hazards to orthopedic surgeons are musculoskeletal disorders with 97% of arthroplasty surgeons reporting procedural-related musculoskeletal pain and 66% of orthopedic surgeons reporting procedural-related musculoskeletal injury [1], [2], [3]. With the annual number of total knee arthroplasties (TKA) on the rise, orthopedic surgeons are taking on larger annual caseloads and retiring later in life [4], [5]. The goal of this study was to quantify postural demand for 11 discrete surgical steps of TKA to identify ergonomically unfavorable positions surgeons experience while operating. Four orthopedic surgeons performed TKA while their motions were recorded using marker-based motion capture. …
Influence Of Obesity On Knee Joint Mechanics: A Subject-Specific Musculoskeletal Modeling Approach, Ryan C. Knowles
Influence Of Obesity On Knee Joint Mechanics: A Subject-Specific Musculoskeletal Modeling Approach, Ryan C. Knowles
Electronic Theses and Dissertations
Obesity has been consistently linked to knee osteoarthritis (KOA), a debilitating joint disease. While prior work has shown that obese individuals often walk with altered biomechanics compared to normal-weight (NW) individuals, which may accelerate KOA progression, less is known about how these mechanics affect load distribution between the medial and lateral tibiofemoral (TF) compartments, particularly during higher-demand activities. This study developed subject-specific musculoskeletal models of five obese and five NW individuals, incorporating CT-based bone measurements and individualized joint contact points. Simulations were driven by six degree-of-freedom (6DOF) kinematics obtained from high-speed stereo radiography (HSSR) to predict TF loading and associated …
Cost-Effectiveness Model For Reservoir Sediment Management Economics, Connor Ronald Hale
Cost-Effectiveness Model For Reservoir Sediment Management Economics, Connor Ronald Hale
Theses and Dissertations
Reservoir sediment deposition poses a challenge to sustainable water supplies around the world. Sediment management has proven to be an expensive endeavor. Two models have been developed to guide economic analysis for reservoir sediment management, namely the Reservoir Sediment Economics Model (RSEM) and the Reservoir Conservation Model 2 (RESCON 2). While these are helpful tools for benefit-cost prefeasibility studies, they rely heavily on sometimes elusive estimations of the benefits of water supply. In this study, a new method for economic analysis is proposed that foregoes benefit-cost analysis in favor of a cost-effectiveness approach. The Sediment Management Cost-Effectiveness Model ranks sediment …
Detection Of Bacterial Genomic Dna Fragments Using The Mxene Crispr-Cas9 Field-Effect Transistor, Jiaoli Li, Ali Taheri, Weijia Liu, Ying Zhuo, Pengfei Ma, Chenglin Wu
Detection Of Bacterial Genomic Dna Fragments Using The Mxene Crispr-Cas9 Field-Effect Transistor, Jiaoli Li, Ali Taheri, Weijia Liu, Ying Zhuo, Pengfei Ma, Chenglin Wu
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Clustered regularly interspaced short palindromic repeats (CRISPR)-based field-effect transistor (FET) sensors provide a promising platform for highly specific and amplification-free nucleic acid detection. However, their direct application in identifying target sequences within intact genomic DNA remains underexplored. We developed a CRISPR-Cas9 FET sensor for detecting DNA sequences by immobilizing Cas9 onto a graphene-MXene sensing interface via (3-aminopropyl)triethoxysilane (APTES) functionalization. The sensor targeted Stx1, a 440 bp laboratory-amplified fragment associated with Shiga toxin production in pathogenic E. coli. Gel electrophoresis confirmed the precise cleavage of Stx1, while the nontarget sequence Stx2 remained undetected. FET measurements further validated the sensor's specificity, showing …