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Item Neuromorphic Computing with Antiferromagnetic Artificial Neurons(2024-01-01) Bradley, Hannah D; Tyberkevych, Vasyl; Tyberkevych, Vasyl; Slavin, Andrei; Khain, Evgeniy; Bozhko, DmytroThe increasing focus on Artificial Intelligence (AI) presents notable challenges, especially in the power requirements essential for training AI models. Consequently, there is a growing emphasis on neuromorphic computing, which aims to construct Artificial Neural Networks (ANNs) from artificial neurons to replicate the speed and efficiency of the human brain. With their significantly lower power consumption, spintronic devices acting as artificial neurons offer the potential for ANNs that rival conventional components. This innovative approach not only tackles the energy efficiency challenges but also paves the way for advancements in neuromorphic computing by integrating magnetic materials and spin-dependent effects. Antiferromagnetic (AFM) materials, characterized by their inherent THz frequencies, provide a unique opportunity for spintronic devices with ultra-fast dynamics. There's a proposal to utilize AFM materials to craft ultra-fast spin-Hall oscillators. These oscillators emit spiking signals resembling those of biological neurons, indicating their potential as artificial neurons. AFM oscillators exhibit exceptionally fast characteristics, including picosecond-scale spike widths and unique features absent in conventional artificial neuron models. This research examines the utilization of AFM oscillators as artificial neurons and their significance in the realm of neuromorphic computing. This dissertation begins with a comprehensive overview of relevant topics, covering the principles of spintronics, AFM materials, and neuromorphic computing. It examines the unique dynamics of AFM neurons, such as response latency and refraction time, which arise from an effective internal inertia. Then, it explores innovative AFM neuron circuits that exhibit functionalities unattainable by conventional artificial neurons, such as non-monotonic inhibition. Additionally, conventional learning algorithms like backpropagation are use to train AFM ANNs for pattern recognition. Finally, it leverages the similarities between AFM and biological neurons to model the biological neural network responsible for the withdrawal reflex. With their simplistic design and high speeds, AFM neurons exhibit energy efficiencies several orders of magnitude higher than traditional artificial neurons and even other spintronic designs. This suggests that AFM ANNs will excel at training AI models while addressing the energy crisis impeding technological progress. As a result, AFM neurons drive forward the progress of spintronic neuromorphic computing, providing a promising alternative for future technological developmentItem Cerebral Waste Clearance: Measurements and Applications(2023-01-01) Kaur, Jasleen; Xia, Yang; Roth, Bradley J; Zhang, Li; Zhang, Zhenggang; Chopp, MichaelCerebral Waste clearance (CWC) is an essential process for brain homeostasis, which is required for the healthy functioning of all cerebrovascular and parenchymal brain cells. This dissertation features our current understanding of CWC, both within and external to the brain parenchyma. We describe the role of the cerebrospinal fluid (CSF) and its exit routes in mediating CWC. Recent discoveries of the glymphatic system and meningeal lymphatic vessels (mLVs), and their relevance to CWC and various neurological conditions are highlighted. Controversies related to CWC research and potential future directions are presented. This dissertation is divided into seven chapters that discuss investigations that used magnetic resonance imaging (MRI) and confocal microscopy imaging to evaluate the recently identified CWC routes, namely the glymphatic system and the mLVs. The dissertation begins with an introduction (Chapter- 1). It proceeds with background (Chapter- 2) based on two published peer-reviewed ‘review’ articles, and three research projects based on one submitted, one published ‘original research’ articles (Chapters- 3, 4) and one project with negative results (Chapter- 5). Among the three projects described in this dissertation, the first project (Chapter- 3) aimed to investigate the controversy of glymphatic convective bulk flow in the interstitial spaces and explore the association of perivascular macrophages (PVMs) in assisting the glymphatic system for CWC. Our findings solidify the glymphatic system hypothesis and indicate the interaction of PVMs with the glymphatic CSF influx along the arteries and glymphatic CSF efflux along the veins. The second project (Chapter- 4) aimed to examine the changes in the glymphatic system in rats with glioblastoma multiforme (GBM) and our results identify reduced glymphatic influx and clearance due to GBM. The third project (Chapter- 5) aimed to assess the mLVs as a potential efflux pathway of the glymphatic system under healthy and diabetic mellitus (DM) conditions. Our results suggest that mLVs are not the major efflux pathway of the glymphatic system, which is a negative result. The dissertation then discusses a translational issue for clinical MRI evaluation of the glymphatic system (Chapter- 6) based on a submitted ‘review’ article and concludes with a summary and future directions (Chapter- 7).Item Experimental and Computational Studies of Articular Cartilage at High Resolutions(2023-01-01) Batool, Syeda S.; Xia, Yang; Roth, Bradley John; Bowyer, Susan; Puwal, Steffan; Tonyushkin, AlexeyArticular cartilage is a thin layer of connective tissue covering the ends of bones in diarthrodial joints to minimize friction and distribute loads. The degradation of articular cartilage is the hallmark of osteoarthritis (OA), a complex joint disease that ranks as the number one cause of disability in the adult population. Conceptually, cartilage can be divided into three sub-tissue zones (the superficial zone SZ, the transitional zone TZ, and the radial zone RZ) across its thin thickness (depth), where each zone has a set of unique depth-dependent properties. These uneven structural and compositional variations across its thin thickness imply that any diagnostic technique should ideally have high resolution in imaging; otherwise, volume averaging within an image pixel could obscure any possibility of early disease detection.In this dissertation, we used quantitative microscopic magnetic resonance imaging (µMRI) combined with polarized light microscopy (PLM) to study the articular cartilage in rabbits and its potential use as an animal model for OA. The utilization of animals plays a vital role in OA research, which enables the examination of the degradation of OA before any procedures are used on humans in the clinic. This dissertation has six chapters. Chapters 1 and 2 contain the introduction, the background, and the literature review. Chapter 3 is an experimental MRI and PLM study of rabbit cartilage at sub-10 µm resolution, which established quantitatively the baseline characteristics of healthy rabbit cartilage between µMRI and PLM. The results, which are useful for the future investigation of OA using the rabbit model, have been published in the Journal of Orthopaedic Research (Batool & Xia, 2020). Chapter 4 is an experimental study to characterize the structural variations at different anatomical locations of femoral cartilage in young rabbits (12-14 weeks old) using µMRI and PLM. Knowledge of location-specific structural differences in the collagen network over the joint surface can improve the understanding of local mechanobiology and provide insights into tissue engineering, and degradation repairs This study has been published in the journal Cartilage (Batool & Xia, 2022). Chapter 5 presents a computational study that used a mathematical model to describe the role of collagen fibril mechanics in articular cartilage under 1D axial compression. This study is being finalized for a peer-reviewed journal. The final Chapter 6 summarizes this dissertation.Item Structural Characteristics of Articular Cartilage in the Early Detection of Post-Traumatic Osteoarthritis by Microscopic Imaging Techniques(2023-01-01) Mantebea, Hannah; Xia, Yang; Roth, Bradley j; Khain, Evgeniy; Surdutovic, Eugene; Quan, JiangCartilage is a specialized form of connective tissue that provides support and cushioning to adjacent tissues in the body. Cartilage is of three types: Hyaline, fibrocartilage, and elastic. The articular cartilage is a hyaline type and is the most found throughout the animal and human bodies. Articular cartilage is composed of a dense extracellular matrix (ECM) with specialized cells, and chondrocytes, which are sparsely distributed. The ECM is primarily made up of collagen, proteoglycan, water, non-collagenous proteins, and glycoproteins. The components of the ECM are subject to change in the disease state, especially in osteoarthritis. As a result of the complex and unique nature of the articular cartilage, early detection, treatment, and repair pose a challenge in clinic. Imaging techniques such as magnetic resonance imaging (MRI) has been used in the noninvasive evaluation of the cartilage structure, and polarized light microscopy (PLM) allows the examination of the molecular organization at optical resolution.The first project in this dissertation aimed to study the structural characteristics of the articular cartilage in the patella and the fibrocartilage of the suprapatella in the knee joint. This was achieved quantitatively using µMRI and PLM at both low and high resolutions. The second project in this dissertation aimed to compare the structures between the immature and mature articular cartilage of the femur and humerus qualitatively and quantitatively using µMRI and PLM. The third project in this dissertation was aimed at the structural characteristics of the articular cartilage in the disease state. Specifically qualitative and quantitative characteristics from traumatized joints (post-traumatic osteoarthritis) were studied using µMRI and PLM at high resolutions. These studies confirmed the ability of µMRI and PLM to examine the cartilage structure quantitatively and qualitatively in a healthy state and in a diseased state. The ability to study the microscopic anatomy of cartilage and pathology (osteoarthritis) in the early stage will contribute to the treatment and early diagnosis of arthritis.