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Articles 8581 - 8610 of 197948
Full-Text Articles in Engineering
Design, Modeling, Control, And Analysis Of A Modular Two-Wheeled Self-Balancing Robotic System, Mishek Jair Musa
Design, Modeling, Control, And Analysis Of A Modular Two-Wheeled Self-Balancing Robotic System, Mishek Jair Musa
Graduate Theses and Dissertations
Two-wheeled self-balancing robots have garnered substantial attention within the realms of research and innovation in academia and industrial settings. In particular, advances in control algorithms, machine learning, reinforcement learning, and sensor technologies have played a pivotal role in their development. Although primarily recognized for their utility in personal transportation in the commercial sector, these robots possess potential applications across various domains, including search and rescue, healthcare, material handling, logistics, etc., due to their active stabilization and exceptional maneuvering capabilities. A particular area of interest lies in the creation of modular self-balancing robots designed for seamless reconfiguration and enhanced human interaction. …
Decoding Anisotropic Porous Medium: A Synergy Of Lattice Boltzmann Modelling And Operator Learning To Predict Permeability As A Function Of Orientation, Soumya Shouvik Bhattacharjee
Decoding Anisotropic Porous Medium: A Synergy Of Lattice Boltzmann Modelling And Operator Learning To Predict Permeability As A Function Of Orientation, Soumya Shouvik Bhattacharjee
Open Access Theses & Dissertations
Understanding the directional properties of porous media is essential for accurately predicting flow behavior, reactive transport, and fluid-solid interactions in systems ranging from geothermal reservoirs to energy storage devices and biological tissues. Directional variations in permeability - reflecting a medium's response to flow at different angular orientations - are particularly important for complex, inherently anisotropic geometries. In this study, we employ a Lattice Boltzmann (LBM) model to calculate directional permeabilities from porous media images subjected to varying flow inlet angles. Three classes of porous media were investigated: (1) synthetic media with circular grains, serving as isotropic baselines; (2) synthetic media …
Elucidation Of Nano-Mechanical Property Evolution Of 3d-Printed Zirconia, Diana Hazel Leyva Marquez
Elucidation Of Nano-Mechanical Property Evolution Of 3d-Printed Zirconia, Diana Hazel Leyva Marquez
Open Access Theses & Dissertations
This dissertation presents an in-depth look at the mechanical behavior, size changes, and process improvement of ceramic and polymer materials made with additive manufacturing (AM). The work consists of four separate but related studies, each tackling important challenges in fabrication, characterization, and predictive modeling. Chapter 1 examines the nano-mechanical property changes of 3D-printed zirconia made using digital light processing (DLP). By employing nanoindentation and scanning electron microscopy (SEM), the effects of print orientation and sintering on hardness, elastic modulus, and microstructure are revealed. The results indicate that 0°-oriented sintered samples have up to 140% higher hardness compared to preconditioned samples, …
Effects Of Environmental Stressors On Human Tissue-On-A-Chip Platforms, Andie Padilla
Effects Of Environmental Stressors On Human Tissue-On-A-Chip Platforms, Andie Padilla
Open Access Theses & Dissertations
As space exploration begins to extend beyond low earth orbit, it has become increasingly critical to understand the interaction of the extreme environment of space flight with human systems. While it is known that space-travel induces a vast array of complications to cardiac, neural, musculoskeletal, and immune systems, the mechanisms by which these complications occur are poorly understood. Current research to study the effects of microgravity and radiation are limited to ground simulations, which rarely account for the multifactorial stressors experienced during spaceflight, or long duration studies aboard the International Space Station. Similarly, traditional two-dimensional (2D) models lack the ability …
Enhancing Credit Path Planning With Llm-Based Multi-Agent Systems, Sahar Yarmohammadtoosky
Enhancing Credit Path Planning With Llm-Based Multi-Agent Systems, Sahar Yarmohammadtoosky
Dissertations
This work explores applying Multi-Agent (MA) Large Language Models (LLMs) to enhance credit card management, an underexplored area for their multi-step reasoning capabilities. Focusing on Equifax’s Optimal Path™ model [1]—a personalized solution for credit score optimization—the study addresses two key challenges: first, designing a natural language interface for financial credit models to improve accessibility and aid customer decision-making, and second, enhancing the reliability and real-world applicability of complex financial models prone to generating invalid or unfeasible recommendations caused by a lack of practical interpretability and susceptibility to edge cases. To tackle these, we propose and evaluate various MA designs, including …
Sensitivity Analysis Of Flexible Pavement For South Carolina Conditions, Shilpa Girish
Sensitivity Analysis Of Flexible Pavement For South Carolina Conditions, Shilpa Girish
All Dissertations
The objective of the study was to evaluate the sensitivity of various input variables on the flexible pavement design thickness of high-speed, high-traffic routes in South Carolina using the Mechanistic-Empirical Pavement Design Guide (MEPDG) by means of the AASHTOWare Pavement ME Design software using global calibration coefficients with a focus on bottom-up fatigue cracking. The variables considered in this investigation included two-way average annual daily truck traffic (AADTT), asphalt mix type, climate station, subgrade type and resilient modulus, and aggregate base thickness. The study includes comparative analysis using older methods like the AASHTO 1993 method and the South Carolina DOT …
Integration And Testing Of A Quadruped Robot With Ros2, Jeremy S. West
Integration And Testing Of A Quadruped Robot With Ros2, Jeremy S. West
Master's Theses
The Cal Poly Legged Robotics Group has been developing research and teaching platforms for agile legged robotics since 2020. These platforms are expected to provide students with opportunities to develop complete legged-robot systems from low-level control to advanced robotics tasks such as motion planning and decision making. However, the current prototyped quadruped robot lacked the software and sensing capabilities for high-level quadrupedal gaits and advanced robotic research.
To address these challenges, this project developed Switch, a robotic platform that builds upon the previous BRUCE platform with significant hardware and software upgrades. Switch features a modular design that allows individual software …
Development Of A Control System For An 8-Dof Quadrupedal Robotic Research Platform, Jack Butler
Development Of A Control System For An 8-Dof Quadrupedal Robotic Research Platform, Jack Butler
Master's Theses
Quadrupedal robots offer a versatile locomotion option that can extend the operating space of a robot into uneven terrains. However, controlling these systems presents significant challenges due to nonlinearities introduced by various factors.
In this thesis, model-predictive control (MPC) is applied to an 8-DOF legged robot developed by Cal Poly’s Legged Robotics group. The MPC framework employs a lumped rigid-body model that treats the robot as a single rigid body with forces applied directly at the foot contact points. The controller is developed within the ROS2 environment, with integration of state estimation and gait-pattern generation, to provide maximum modularity and …
Real-Time Fiducial Marker Based Localization For Autonomous Unmanned Aerial Vehicle Navigation, Sourav Raxit
Real-Time Fiducial Marker Based Localization For Autonomous Unmanned Aerial Vehicle Navigation, Sourav Raxit
LSU New Orleans Theses and Dissertations
By harnessing fiducial markers as visual landmarks in the environment, Unmanned Aerial Vehicles (UAVs) can rapidly build precise maps and navigate spaces safely and efficiently, unlocking their potential for fluent collaboration and coexistence with humans. Existing fiducial marker methods rely on handcrafted feature extraction, which sacrifices accuracy. On the other hand, some deep learning pipelines for marker detection fail to meet real-time runtime constraints crucial for navigation applications. In this work, I propose YoloTag- a real-time fiducial marker-based localization system. YoloTag uses a lightweight YOLO v8 object detector to accurately detect fiducial markers in images while meeting the runtime constraints …
Ai-Driven Uncertainty Quantification & Multi-Physics Approach To Evaluate Cladding Materials In A Microreactor, Alexander Foutch, Kazuma Kobayashi, Ayodeji Babatunde Alajo, Dinesh Kumar, Syed Bahauddin Alam
Ai-Driven Uncertainty Quantification & Multi-Physics Approach To Evaluate Cladding Materials In A Microreactor, Alexander Foutch, Kazuma Kobayashi, Ayodeji Babatunde Alajo, Dinesh Kumar, Syed Bahauddin Alam
Nuclear Engineering and Radiation Science Faculty Research & Creative Works
The pursuit of enhanced nuclear safety has spurred the development of accident-tolerant cladding (ATC) materials for light water reactors (LWRs). This study investigates the potential of repurposing these ATCs in advanced reactor designs, aiming to expedite material development and reduce costs. The research employs a multi-physics approach, encompassing neutronics, heat transfer, thermodynamics, and structural mechanics, to evaluate four candidate materials (Haynes 230, Zircaloy-4, FeCrAl, and SiC–SiC) within the context of a high-temperature, sodium-cooled microreactor, exemplified by the Kilopower design. While neutronic simulations revealed negligible power profile variations among the materials, finite element analyses highlighted the superior thermal stability of SiC–SiC …
Lithium Slag As A Supplementary Cementitious Material For Sustainable Concrete: A Review, Sajad Razzazan, Nuha S. Mashaan, Themelina Paraskeva
Lithium Slag As A Supplementary Cementitious Material For Sustainable Concrete: A Review, Sajad Razzazan, Nuha S. Mashaan, Themelina Paraskeva
Research outputs 2022 to 2026
The global cement industry remains a significant contributor to carbon dioxide (CO2) emissions, prompting substantial research efforts toward sustainable construction materials. Lithium slag (LS), a by-product of lithium extraction, has attracted attention as a supplementary cementitious material (SCM). This review synthesizes experimental findings on LS replacement levels, fresh-state behavior, mechanical performance (compressive, tensile, and flexural strengths), time-dependent deformation (shrinkage and creep), and durability (sulfate, acid, abrasion, and thermal) of LS-modified concretes. Statistical analysis identifies an optimal LS dosage of 20–30% (average 24%) for maximizing compressive strength and long-term durability, with 40% as a practical upper limit for tensile and flexural …
Reinforcement Learning And Virtual Human Animation: A Novel Approach To Data-Driven Animation, Portraying Dynamic, Flexible Human-Like Behaviours, Vihanga Gamage
Dissertations
Virtual characters require animation capable of portraying dynamic, context-sensitive human-like behaviours. Several approaches to generating such animation have been developed, but each carries limitations. Motion capture can produce high-fidelity animation but is expensive and ill-suited to systems that must respond in real time. Physics-based reinforcement learning (RL) enables flexible, dynamic behaviour portrayal, yet relies on simulation feedback signals that are unavailable for social gestures. Supervised approaches can learn social behaviours from motion capture data but yield agents with limited flexibility and generalisation.
This thesis presents RLAnimate, a model-based, data-driven RL framework for character animation that enables a single agent to …
Autoregressive Temporal Modeling For Advanced Tracking-By-Diffusion, Pha Nguyen, Rishi Madhok, Bhiksha Raj, Khoa Luu
Autoregressive Temporal Modeling For Advanced Tracking-By-Diffusion, Pha Nguyen, Rishi Madhok, Bhiksha Raj, Khoa Luu
Electrical Engineering and Computer Science Faculty Publications and Presentations
Object tracking is a widely studied computer vision task with video and instance analysis applications. While paradigms such as tracking-by-regression,-detection,-attention have advanced the field, generative modeling offers new potential. Although some studies explore the generative process in instance-based understanding tasks, they rely on prediction refinement in the coordinate space rather than the visual domain. Instead, this paper presents Tracking-by-Diffusion, a novel paradigm for object tracking in video, leveraging visual generative models via the perspective of autoregressive models. This paradigm demonstrates broad applicability across point, box, and mask modalities while uniquely enabling textual guidance. We present DIFTracker, a framework that utilizes …
Owl Solar-Powered Link: Duck Radio Mesh For Autonomous Monitoring, Jaden Tran, Shane Williams
Owl Solar-Powered Link: Duck Radio Mesh For Autonomous Monitoring, Jaden Tran, Shane Williams
Electrical Engineering
The Solar Duck Sensor Node transforms a standard DuckLink into a fully self-sustaining environmental monitor. A compact solar panel / power bank module plugs into the power ports of both the DuckLink and the Raspberry Pi Zero 2 W, keeping them charged through day-night cycles. The Pi Zero 2 W will perform local processing of sensor data. Sensor output will come from the Raspberry Pi AI Camera and its object detection capabilities. This output will be distilled into metadata and advertised over BLE. The DuckLink captures these packets, encapsulates them into LoRa payloads, and forwards them across the ClusterDuck mesh …
Simulation Of Photochemical Effects On Air Quality, Grace Li
Simulation Of Photochemical Effects On Air Quality, Grace Li
Chemical Engineering Undergraduate Honors Theses
Nitrogen dioxide (NO2) and ozone (O3) are both EPA criteria air pollutants in the troposphere, largely generated by combustion and therefore present in significant concentrations in urban areas. Sunlight facilitates chemical reactions between pollutants and ambient air. Aerosols modulate the amount of available energy required to drive such photochemical reactions, ultimately impacting air quality. Simulating photolysis rates with FastJX software is a resource-efficient strategy to study how these aerosols can affect air quality.
Synergistic Enhancement Of Tribological Behavior And Colloidal Stability In Cuo Nanolubricants Via Ligand Tuning, Sherif Elsoudy, Sayed Akl Akl Dr, Sayed Akl A. Akl Dr, Esm Lane, Abas Hadawey, Philip D. Howes
Synergistic Enhancement Of Tribological Behavior And Colloidal Stability In Cuo Nanolubricants Via Ligand Tuning, Sherif Elsoudy, Sayed Akl Akl Dr, Sayed Akl A. Akl Dr, Esm Lane, Abas Hadawey, Philip D. Howes
Mechanical Engineering
Nanoparticle-based lubricants, or nanolubricants, can exhibit superior tribological properties compared to unmodified base oils. However, these performance gains are highly dependent on the nanoparticle surface chemistry, particularly in maintaining stable colloidal dispersions. This study explores the influence of oleic acid (OA) and oleylamine (OAm) functionalization on the tribological and colloidal properties of CuO nanoparticles dispersed in an SAE 20W50 base oil. We present a hybrid optimization framework combining Response Surface Methodology (RSM) with Bayesian Optimization (BO) to identify the optimal OA to OAm ratio (OA–OAm) for CuO nanolubricants. Unlike prior studies that employed either RSM alone or trial-and-error approaches, this …
Navigating Transportation Barriers: Older Adults’ Familiarity With New Mobility Options And Perceptions Toward Autonomous Vehicles In Arkansas, Arna Nishita Nithila, Suman Kumar Mitra, Michelle Gray, Alishia Juanelle Ferguson, Jennifer D. Webb
Navigating Transportation Barriers: Older Adults’ Familiarity With New Mobility Options And Perceptions Toward Autonomous Vehicles In Arkansas, Arna Nishita Nithila, Suman Kumar Mitra, Michelle Gray, Alishia Juanelle Ferguson, Jennifer D. Webb
Civil Engineering Faculty Publications and Presentations
The objective of this study is to analyze older adults’ familiarity with new transportation options (ride-hailing services, bike-share services, and shared e-scooter services) and their perception towards autonomous vehicles (fully autonomous cars), as well as how transportation barriers influence their familiarity and perceptions, in Arkansas, a predominantly rural state. Data from 775 older adults aged 60 years or older were collected between October 2021 and October 2022. To fulfill the study objective, the study used Latent Class Cluster Analysis to segment older adults into classes based on their familiarity with new transportation options and their perceptions of autonomous vehicles. The …
Pressure Recovery Analysis Downstream Of Valves And Meters: An Experimental And Numerical Investigation, Stephen J. Sanders
Pressure Recovery Analysis Downstream Of Valves And Meters: An Experimental And Numerical Investigation, Stephen J. Sanders
All Graduate Theses and Dissertations, Fall 2023 to Present
In pressurized water systems, flow control devices such as valves and meters cause pressure losses that can affect energy efficiency and measurement accuracy. Industry standards assume that all devices recover within the same distance downstream, but this may not be true for all device types. In this study we used laboratory testing and computer modeling to determine how far downstream pressure stabilizes after flowing through various valves and meters. Devices like Venturi meters recovered pressure quickly, while orifice plates required longer distances and resulted in greater permanent energy loss. In most cases, pressure recovered within four to six pipe diameters. …
Drift Dynamics Of Early Life-Stage Invasive Carps, Saurav Karki
Drift Dynamics Of Early Life-Stage Invasive Carps, Saurav Karki
Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research
Asian carp species pose significant ecological threats to North American freshwater systems due to their invasive nature and prolific reproduction. Their semi buoyant eggs develop while drifting downstream with the river current. Understanding early life-stage transport is therefore critical for predicting recruitment potential and guiding management efforts. Existing fluvial egg drift models, including those relying on 1-D hydraulics and fully 3-D CFD-based models, are either inadequate for complex braided rivers or too computationally demanding for large-scale application. The Platte River in Nebraska, characterized by wide, shallow, multi-threaded channels, is dominated by two-dimensional flow conditions, making a depth-averaged 2-D modeling approach …
Impact Of Humidity From Shrink (Wrap) Tunnels On Refrigeration Systems: Comparing Economic And Environmental Impact Of Natural Gas And Electric, Segun Samuel Oladipo
Impact Of Humidity From Shrink (Wrap) Tunnels On Refrigeration Systems: Comparing Economic And Environmental Impact Of Natural Gas And Electric, Segun Samuel Oladipo
Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research
This thesis examines the economic and environmental effects of electric and steam shrink-wrapping tunnels used in beef packaging processes, paying particular attention to the indirect refrigeration loads caused by the heat and humidity that each system releases. Traditional sustainability evaluations frequently ignore these indirect impacts, which are especially important in meat processing facilities where 45–55% of electricity use is attributed to refrigeration. Life cycle assessment (LCA), field measurements, and thermodynamic modeling are all used in this work to offer a thorough analysis of both tunnel types.
The case study facility in Nebraska operates both steam and electric shrink tunnels to …
Hardware And Software Design For A Portable Surgical Training Simulator, Victoria Nelson
Hardware And Software Design For A Portable Surgical Training Simulator, Victoria Nelson
Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research
More than 51 million surgeries are performed on patients annually in the United States. That number grows to 310 million surgeries performed globally each year. Most surgeons go through a minimum of five years of residency – where they train and hone their surgical skills. It is important during this time, and throughout their careers, that they get plenty of practice. Surgical training is time intensive, expensive, and frequently under-resourced. There are finite amounts of surgical training modules for students to share at their facilities. The problem of getting adequate surgical training time continues to exist after surgeons begin their …
Traffic Prediction For Research And Education Networks: Anomaly-Aware Deep Learning And Benchmarking, Mohammad Arafath Uddin Shariff
Traffic Prediction For Research And Education Networks: Anomaly-Aware Deep Learning And Benchmarking, Mohammad Arafath Uddin Shariff
School of Computing: Dissertations, Theses, and Student Research
Research and Education Networks (RENs) and High-Performance Computing (HPC) environments are critical infrastructures for modern scientific discovery, demanding sustained high-throughput and low-latency data transfers. Unlike commercial networks, RENs exhibit unique traffic characteristics, including predominant “elephant flows,” inherent burstiness, and complex temporal-spatial dynamics often decoupled from human-driven cycles. Traditional traffic forecasting methods, tailored for commercial Wide Area Networks (WANs), consistently fail to capture these distinct REN dynamics, leading to inefficient resource management and potential impediments to scientific progress.
This thesis addresses this critical gap by developing and validating a robust, scalable, and anomaly-aware traffic forecasting framework specifically tailored for REN/HPC networks. …
Development Of A Homogenized Material Model For Carbon Fiber–Aluminum Transition Joints Using Fea And Optimization, Nicholas M. Couch
Development Of A Homogenized Material Model For Carbon Fiber–Aluminum Transition Joints Using Fea And Optimization, Nicholas M. Couch
All Theses
The integration of metals and composites in automotive structures improves manufacturability and overall structural performance. The proposed Ultrasonic Additive Manufacturing (UAM) joint provides a promising solution for joining aluminum and carbon fiber; however, modeling its behavior across an entire vehicle can be computationally expensive. To address this challenge, a homogenized material card is developed to efficiently capture the joint’s mechanical response while maintaining computational efficiency. A novel characterization method is implemented, employing implicit simulations and optimization techniques to determine the effective material properties of the UAM transition joint. This approach enables rapid iteration of material parameters, facilitating the efficient evaluation …
Evaluating (Bio)Degradation Of Carbon Tetrachloride In Fe(Iii)-Reducing Environments, Adam Rogers
Evaluating (Bio)Degradation Of Carbon Tetrachloride In Fe(Iii)-Reducing Environments, Adam Rogers
All Theses
Understanding degradation of carbon tetrachloride in-situ is vital for many remediation projects across the world, yet conclusive evidence of its feasibility is lacking in previous studies.
The main objective of this research is to assess the potential for carbon tetrachloride attenuation by biological, abiotic, and combined processes in a Fe(III)-reducing aquifer. In doing so, it assesses the effect of pH and stoichiometric ratio on abiotic degradation of carbon tetrachloride using various reducing agents, evaluates iron-mediated versus direct biotic degradation of carbon tetrachloride using pure cultures under resting and growth conditions, and characterizes the effects of culture strain, electron acceptors and …
Machine Learning Based Medical Ultrasound Image Classification And Grad-Cam Interpretation, Victoria C. Hemphill
Machine Learning Based Medical Ultrasound Image Classification And Grad-Cam Interpretation, Victoria C. Hemphill
All Theses
This work takes a step in creating a diagnostic tool for the classification decision process of Achilles tendinopathy using ultrasound images. An attention-based multiple instance learning model is developed to classify the images. Typically, doctors capture multiple ultrasound images of the Achilles tendon during a study to determine a complete diagnosis. Multiple instance models adopt this behavior by providing a single label for a set of instances (images). The images are grouped into ”bags” at the study level and passed into the model. The MIL model then uses its attention property to assign an importance score to each image to …
Visor-Zt: A Visibility, Simulation, And Operational Resilience Framework For Zero Trust Security In Ros 2, Noah Tinker
Visor-Zt: A Visibility, Simulation, And Operational Resilience Framework For Zero Trust Security In Ros 2, Noah Tinker
All Theses
Robotic systems are becoming more and more prevalent in modern society, with Robot Operating System 2 (ROS 2) being the dominant operating system for these implementations. Its popularity can be attributed to its design, which is purpose-built for distributed systems and asynchronous communications. However, ROS 2 security is static and therefore less capable of responding to contemporary threats and network behavior. This becomes a greater issue when considering its applications in the military and defense sectors, where security is of the highest importance. In recent years, the U.S. Department of Defense (DoD) has implemented zero trust (ZT) security based on …
A Generalizable And Privacy-Preserving Framework For Anomaly Detection In Heterogeneous Iot Environments, Mahshid Rezakhani
A Generalizable And Privacy-Preserving Framework For Anomaly Detection In Heterogeneous Iot Environments, Mahshid Rezakhani
All Theses
With the rapid growth of Internet of Things (IoT) devices across various sectors, detecting anomalies in such systems has become increasingly challenging. IoT environments produce diverse and evolving data streams, often lacking labeled examples, which limits the effectiveness of traditional machine learning models. These models typically require frequent retraining and struggle to adapt to new deployment conditions. This thesis proposes a flexible, privacy-aware framework for anomaly detection in multivariate time series data generated by heterogeneous IoT systems. The approach integrates a long short-term memory variational autoencoder (LSTM-VAE) with contrastive learning and adversarial adaptation, enabling the model to generalize across domains, …
Polyphenols For The Mitigation Of Vascular Calcification; In Vitro And In Vivo Studies, Abdullah Altuhami
Polyphenols For The Mitigation Of Vascular Calcification; In Vitro And In Vivo Studies, Abdullah Altuhami
All Theses
Globally, cardiovascular diseases, in most cases associated with calcification, are the main cause of death. However, currently, the only effective cure is to undergo surgery to augment or receive a healthy donor heart, which could be very difficult due to the long waiting list and the associated risks. The possibility of body rejection of the foreign organs is attributed to immunoreaction or the risk of infection, since the donor must be on immunosuppressant drugs that lower the body's immunity and facilitate the body's acceptance of the new organ as one of its own. Taking that into consideration, using tissue-engineered vascular …
Grain Boundary Migration And Radiation Induced Segregation In Fe-Cr Alloys, Mohit Dhoriya
Grain Boundary Migration And Radiation Induced Segregation In Fe-Cr Alloys, Mohit Dhoriya
All Theses
Radiation-induced segregation (RIS) is a significant phenomenon that occurs in alloys subjected to irradiation, particularly in environments such as nuclear reactors. This thesis investigates RIS in ferritic Fe- Cr alloys through the use of Atomic Kinetic Monte Carlo (AKMC) simulations, focusing on the interaction between solute atoms and migrating grain boundaries. The study explores the influence of temperature, solute concentration, and grain boundary velocity on solute drag, a critical process driving RIS. The results show that solute migration is strongly influenced by the presence of vacancies and interstitials generated under irradiation, which are absorbed by grain boundaries and other defect …
Effect Of Cigarette Smoke Extract And Nutrient Deficiency On Energy Metabolism And Biosynthesis: An In Vitro Intervertebral Disc Explant Culture Study, Avery E. Madden
Effect Of Cigarette Smoke Extract And Nutrient Deficiency On Energy Metabolism And Biosynthesis: An In Vitro Intervertebral Disc Explant Culture Study, Avery E. Madden
All Theses
Low back pain consistently ranks among the leading causes of disability worldwide, with degenerative changes in spinal intervertebral discs (IVDs) recognized as a key contributor. Degeneration arises from the disruption of mechanical and biological cues within the disc’s cartilaginous tissue, often exacerbated by aging or injury. In recent decades, cigarette smoking has also been identified as a significant risk factor, as IVD degeneration is more prevalent among individuals with a history of smoking. Smoke inhalation is thought to promote degeneration both directly, by exposing cells to water-soluble toxic chemicals in smoke; and indirectly, through nutrient deficiency resulting from vasoconstriction and …