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Articles 31 - 60 of 1369
Full-Text Articles in Engineering
Utilizing Optimization Tools For Passive Flow Control Passage Loss Reduction In Low-Pressure Turbines, Bryant Robert Duane Burton
Utilizing Optimization Tools For Passive Flow Control Passage Loss Reduction In Low-Pressure Turbines, Bryant Robert Duane Burton
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Low-pressure turbines (LPTs) play a crucial role in fuel efficiency and thrust generation of aero-engines. Traditional LPT designs, however, involve multiple stages and numerous blades, resulting in increased weight and manufacturing costs. The challenge of modern- day researchers is to reduce the weight and cost but maintain the high efficiency of LPTs. To address this, one approach is to increase the aerodynamic loading of individual blades, reducing the blade count. However, this can lead to increased secondary losses caused by flow separation, particularly in the endwall regions. This research focuses on optimizing the blade profile at the junction with the …
Quantification Of Porosity In Hfb2–20%Sic Using Convolutional Neural Networks, Cameron J. Floyd
Quantification Of Porosity In Hfb2–20%Sic Using Convolutional Neural Networks, Cameron J. Floyd
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Ultra-high-temperature ceramics, commonly used in aerospace applications, operate in high-temperature oxidizing environments where a surface scale forms and regulates oxy gen access. For hafnium diboride–silicon carbide (HfB2–SiC), that scale consists of a borosilicate glass layer over a porous HfO2 skeleton. Oxygen transport through this poros ity governs the kinetics of mechanistic models, requiring reproducible inputs for accurate pore fraction (PF), pore-size distributions, and ultimately tortuosity. This thesis replaces rule-based SEM thresholding with a convolutional neural network that segments pores and predicts the pore-radius distribution for transport models. The resulting calibrated porosity maps and size distributions transfer within the acquisition domain …
Effect Of Build Orientation And Environmental Conditions On Mechanical And Geometric Properties Of Polymeric Parts Fabricated By The Powder Bed Fusion Process, Adedamola O. Adeyemi
Effect Of Build Orientation And Environmental Conditions On Mechanical And Geometric Properties Of Polymeric Parts Fabricated By The Powder Bed Fusion Process, Adedamola O. Adeyemi
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Polyamide-12 (aka PA12) is a synthetic thermoplastic polymer that has been used in various applications, including the electronic and electrical, oil and gas industrial manufacturing and automotive industry. There are several ways to manufacture parts with PA12 and PA12 based composites. Injection molding, a traditional manufacturing process, has been the standard manufacturing route for polymers for a long time. Recently, however, additive manufacturing (AM) processes, such as powder bed fusion (PBF) and material extrusion (ME) have been introduced. PBF is a manufacturing process characterized by the selective sintering of successive layers of powdered material. It is the most effective AM …
Generative Adversarial Networks (Gans) For High-Dimensional Biological Data, Harigovind Harikumar
Generative Adversarial Networks (Gans) For High-Dimensional Biological Data, Harigovind Harikumar
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This thesis investigates the application of Generative AI models, mainly Generative Adversarial Network (GAN) models to high dimensional and low sample size biological datasets like Motion Sickness, Breast Cancer, Crohn, and Melanoma. We utilized and compared three generative AI frameworks: Vanilla GAN, Wasserstein GAN (WGAN), Locality-Sensitive Hashing GAN (LSH-GAN) and Omics GAN. To address the challenges associated with high-dimensionality and low sample size, which was leading to very poor outputs of biological synthetic samples, we came up with an approach to stop the model when it reaches its saturation level. That is, we printed the loss plots to see where …
The Role Of Trpm7 In Mouse Development And Immune Cell Function, Jananie Rockwood
The Role Of Trpm7 In Mouse Development And Immune Cell Function, Jananie Rockwood
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Transient receptor melastatin 7 (TRPM7) functions both as an ion channel and a protein kinase. TRPM7 has been implicated in Mg2+ homeostasis, embryogenesis, cardiac automaticity, and immunity. The purpose of this research was to deepen our understanding of TRPM7 channel and kinase functions. To this end, we used two transgenic mouse models: the TRPM7 gain-of-function (GOF) and TRPM7 kinase-dead (KD) mice to address the consequences of increased channel activity and kinase inactivation, respectively. Global deletion of TRPM7 or the kinase domain alone are embryonic lethal, therefore, we used the TRPM7 GOF mouse to investigate germline transmission. We examined embryo development …
Pixmix Attack: Implementation And Evaluation Of A Novel Pixel Injection On Digital Video Port (Dvp) Interface In Embedded Camera Systems With Pcb Hardware Trojan, Sayed Md Tashfi Nowroz
Pixmix Attack: Implementation And Evaluation Of A Novel Pixel Injection On Digital Video Port (Dvp) Interface In Embedded Camera Systems With Pcb Hardware Trojan, Sayed Md Tashfi Nowroz
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Image sensors are at the heart of machine vision systems in robotics, industrial automation, and surveillance systems which ideally operate with minimal human supervision and only occasional maintenance. The image sensors convert visible light into electrical signals which are locally decoded to image on the printed circuit board (PCB) by an ordinary embedded processor System on Chip (SoC). This thesis investigates a critical vulnerability in such systems, targeting the communication protocol at the signal level during runtime. Specifically, it focuses on a novel attack in the Digital Video Port (DVP) protocol, possible to exploit with PCB-based hardware Trojans, to craft …
Induced Reduction Of N-Glycosylation Leads To Heart Failure, Anthony M. Young
Induced Reduction Of N-Glycosylation Leads To Heart Failure, Anthony M. Young
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Cardiovascular disease is the leading cause of death and contributes to the increasing global prevalence of heart failure (HF). N-glycosylation is a common co-/post-translational modification where branching oligosaccharides are bound to the extracellular domain of membrane proteins. This creates a diverse range of glycan structures and requires the coordination of hundreds of regulated genes. Inherited mutations in glycan synthesis frequently present with cardiomyopathies leading to HF with reduced ejection fraction (HFrEF). Additionally, gene expression studies of HFrEF patients have shown altered expression of glycosylation-related genes, including alpha-1,3-mannosyl-glycoproten 2-beta-N acetlyglucosaminyltransferase (Mgat1). This gene encodes N-acetylglucosaminyl transferase 1 (GlcNAcT1) which is required …
A Secure Ml-Assisted Framework For Resilient And Efficient Prediction Of Physiotherapy Sequence In Bilateral Carpal Tunnel Syndrome, Pratik Pandurang Kharat
A Secure Ml-Assisted Framework For Resilient And Efficient Prediction Of Physiotherapy Sequence In Bilateral Carpal Tunnel Syndrome, Pratik Pandurang Kharat
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Bilateral idiopathic carpal tunnel syndrome (CTS) is a neuromuscular disorder characterized by compression of the median nerve at both wrists, leading to symptoms such as pain, numbness, tingling, and muscle weakness. Unlike unilateral cases, bilateral idiopathic CTS presents distinct therapeutic challenges due to the simultaneous involvement of both hands and the lack of an identifiable underlying cause. This study explores the application of machine learning techniques to predict the optimal sequence of physiotherapeutic interventions Stretching followed by Myofascial Mobilization (S/M) or the reverse (M/S) in female patients with bilateral idiopathic CTS and right hand dominance. Data were drawn from a …
The Impact Of Ahr And Hs1.2 Enhancer Genetic Variations On Igh Expression And Antibody Production In Human B Cells, Mili Santosh Bhakta-Yadav
The Impact Of Ahr And Hs1.2 Enhancer Genetic Variations On Igh Expression And Antibody Production In Human B Cells, Mili Santosh Bhakta-Yadav
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Antibody production is an essential component of the immune response against pathogens. The immunoglobulin heavy chain (IgH) gene codes for the heavy chain of antibodies. The IgH constant regions Cμ, Cδ, Cγ1-4, Cα1-2, and Cε encode the five major classes of antibodies, i.e., IgM, IgD, IgG1-4, IgA1-2, and IgE, respectively. The transcription of the IgH gene and class switch from IgM to other isotypes is regulated by two 3’ IgH regulatory regions (3’IgHRRs), each of which is a cluster of three enhancer regions (hs3, hs1.2 and hs4). The genetic variations in the hs1.2 enhancer have been identified; a ~53 bp …
Learning Under Data Scarcity: Reasoning And Negative Distillation For Texts And Graphs, Calvin T. Greenewald
Learning Under Data Scarcity: Reasoning And Negative Distillation For Texts And Graphs, Calvin T. Greenewald
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Modern machine learning (ML) models rely on large amounts of high-quality labeled data to achieve optimal performance. However, in many real-world domains, such as cyber security, acquiring sufficient labeled data is often infeasible due to cost, privacy concerns, and the rapid evolution of underlying phenomena. This challenge underscores the importance of learning under data scarcity. This thesis addresses this challenge by proposing distinct, modality-specific techniques for text and graph domains, which allow models to generalize effectively with minimal data. For text classification task, we incorporate distilled rationales from large language models and adversarial perturbations into the input space to improve …
Evaluation And Modulation Of The Circadian Clock In Human Keratinocytes And Epidermal Skin, William Harold Cvammen Iv
Evaluation And Modulation Of The Circadian Clock In Human Keratinocytes And Epidermal Skin, William Harold Cvammen Iv
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The circadian clock is a fundamental biological mechanism that regulates various physiological processes, including DNA repair, to synchronize with the day-night cycle. In human skin, exposure to ultraviolet (UV) light poses a significant challenge, inducing DNA damage that must be efficiently repaired to maintain genomic integrity and prevent carcinogenesis. This study delved into the complex interplay between the circadian clock, UV light exposure, DNA repair, and modulation of circadian transcriptional machinery in human skin. Initially, we examined the transcriptomic profile of the circadian clock in humans through in silico-based approaches and in vivo studies, revealing that core clock gene expression …
Understanding Patient Profiles In Sickle Cell Disease Using Unsupervised Machine Learning, Raj Kamal Somavarapu
Understanding Patient Profiles In Sickle Cell Disease Using Unsupervised Machine Learning, Raj Kamal Somavarapu
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Sickle Cell Disease (SCD) is one of the most prevalent genetic blood disorders affecting millions of people worldwide. It is often accompanied by acute and/or chronic pain leading to increased healthcare costs and adverse outcomes. Effective management of SCD requires an understanding of the diverse physiological profiles. This study employs unsupervised machine learning, specifically K-means clustering to categorize the patients suffering with SCD into different clusters based on their vital signs. The main aim is to identify the groups that reflect similarities in physiological and pain profiles, allowing an in-depth analysis to reveal distinctive features distinguishing patient clusters. The project …
Enhancing Robustness Of Graph Neural Network Against Adversarial Attacks By Balancing Local And Global Perspectives, Bibek Raj Joshi
Enhancing Robustness Of Graph Neural Network Against Adversarial Attacks By Balancing Local And Global Perspectives, Bibek Raj Joshi
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Graph Neural Networks (GNNs) have increasingly gained popularity as tools for analyzing graph data in areas like biology, knowledge-graphs, social networks, biology, and recommendation systems. However, their vulnerability to adversarial attacks - small, targeted manipulations of graph structures or node features - raises serious concerns about their reliability in real-world applications. Existing defense strategies, such as adversarial training, edge filtering, low-rank approximations, and randomization-based methods, often suffer from high computational costs, scalability issues, or reduced clean-data performance. Unlike these methods, the proposed approach integrates multi-hop relationships, applies adaptive regularization, and maintains a balance between feature-based and structural embeddings, ensuring improved …
Meta-Learning-Based Model Stacking Framework For Hardware Trojan Detection In Fpga Systems, Mani Rupak Gurram
Meta-Learning-Based Model Stacking Framework For Hardware Trojan Detection In Fpga Systems, Mani Rupak Gurram
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In today's technological landscape, hardware devices are integral to critical applications such as industrial automation, autonomous vehicles, and medical equipment, relying on advanced platforms like FPGAs for core functionalities. However, the multi-stage manufacturing process, often distributed across various foundries, introduces substantial security risks, notably the potential for hardware Trojan insertion. These malicious modifications compromise the reliability and safety of hardware systems. This research addresses the detection of hardware Trojans through side-channel analysis, utilizing power and electromagnetic signal data, combined with meta-learning techniques, specifically model stacking. By employing diverse base models and a meta-model to consolidate predictions, this non-invasive approach effectively …
Production Of Cerium Oxide And Zinc Sulfide Composites, Ted Autore
Production Of Cerium Oxide And Zinc Sulfide Composites, Ted Autore
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Zinc sulfide has an infrared cutoff in the LWIR, but its low hardness makes it susceptible to rain erosion and abrasion. A composite of cerium oxide and zinc sulfide that retains an infrared cutoff in the LWIR, and with hardness higher than pure zinc sulfide is a potential solution to the rain erosion and abrasion issue. Several different processes were undertaken in this project to produce such a composite. The different reactions between ZnS and CeO2 were researched, along with the effects of different processing parameters. Composite samples were made that had a better hardness than zinc sulfide but did …
Investigating The Impact Of Stress And Irradiation Flux On Latent Track Formation In Tio2 Under Swift Heavy Ion Irradiation: A Phase Field Study, Ebrahim Ebrahimi
Investigating The Impact Of Stress And Irradiation Flux On Latent Track Formation In Tio2 Under Swift Heavy Ion Irradiation: A Phase Field Study, Ebrahim Ebrahimi
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Swift Heavy Ions (SHI) irradiation, characterized by high kinetic energy ions, induces significant material/structural modification, e.g., latent track. However, the intricate interaction among various physics, i.e., mechanical stress, phase transition, and heat transfer, has been ignored in the continuum-based approaches in favor of simplicity. Here, we developed a two-dimensional coupled phase-field inelastic-thermal spike (PF-iTS) model to investigate the effect of thermal crosstalk, elastic energy, and irradiation flux on latent track formation. A particular focus is placed on investigating the influence of internal mechanical stress on latent track formation. Simulation results reveal a shift in critical stopping energy and a reduction …
Architectural Optimization Of Emulator Embedded Neural Networks For Aerospace Vehicle Design, James L. Schmitz Ii
Architectural Optimization Of Emulator Embedded Neural Networks For Aerospace Vehicle Design, James L. Schmitz Ii
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An approach for the architecture optimization of emulator embedded neural networks is proposed. While the emulator embedded neural network has been shown to provide accurate predictions with suitable emulators, there is still a challenge regarding how to select the optimal hyperparameters of network architectures, such as, the number of neurons, layers, types of activation functions, etc. The selection of hyperparameters greatly affects the performance of the neural network model training both in terms of accuracy and efficiency. To address this challenge, this study proposes an algorithm that tests a range of hyperparameters and selects the best performing set. The algorithm …
Using Unsupervised Machine Learning To Reduce The Energy Requirements Of Active Flow Control, Jared N. Kerestes
Using Unsupervised Machine Learning To Reduce The Energy Requirements Of Active Flow Control, Jared N. Kerestes
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It is generally accepted that there exist two types of laminar separation bubbles (LSBs): short and long. The process by which a short LSB transitions to a long LSB is known as bursting. In this research, large eddy simulations (LES) are used to study the evolution of an LSB that develops along the suction surface of the L3FHW-LS at low Reynolds numbers. The L3FHW-LS is a new high-lift, high-work low-pressure turbine (LPT) blade designed at the Air Force Research Laboratory. The LSB is shown to burst over a critical range of Reynolds numbers. Bursting is discussed at length and its …
A Pade-Eno Flux Reconstruction For High-Speed Flows, Blake Martin
A Pade-Eno Flux Reconstruction For High-Speed Flows, Blake Martin
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The development of high order numerical schemes has been instrumental in advancing computational fluid dynamics (CFD), particularly for applications requiring high resolution of discontinuities and complex flow phenomena prevalent in high-speed flows. This thesis introduces the Pade-ENO scheme, a high-order method that integrates Essentially Non-Oscillatory (ENO) techniques with compact Pade stencils to achieve superior accuracy, up to 7th order, while maintaining stability in harsh environments. The scheme’s performance is evaluated through benchmark tests, including the advection equation, Burgers’ equation, and the Euler equations. For high Mach number flows, such as the sod shock tube the Pade-ENO method demonstrates its ability …
Advanced Digital Wideband Receiver Design: High Dynamic Range And Enhanced Multi-Signal Detection With Fpga-Based Custom Fft And Nyquist Folding, Kiran Jayarama
Advanced Digital Wideband Receiver Design: High Dynamic Range And Enhanced Multi-Signal Detection With Fpga-Based Custom Fft And Nyquist Folding, Kiran Jayarama
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In modern wideband receiver standards, efficient frequency spectrum utilization is essential to meet demands for high data rates, reduced latency, and enhanced connectivity. The Fast Fourier Transform (FFT) stands as a pivotal technology, particularly in radar signal processing, where it supports tasks such as target detection, range estimation, and velocity estimation by analyzing the frequency content of the received radar signals. This dissertation introduces the design of an advanced digital wideband receiver featuring a high dynamic range for multiple signals, with a focus on improved performance, compact size, and reduced power consumption, implemented on an FPGA using custom hardware. Key …
Fabricating And Analyzing Liquid And Polymer Electrolytes For Sodium Ion Batteries, Kekule Augustine
Fabricating And Analyzing Liquid And Polymer Electrolytes For Sodium Ion Batteries, Kekule Augustine
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The abundance and the cost-effectiveness of sodium resources have made sodium-ion batteries (SIBs) viable alternatives to lithium-ion batteries. Developing low-cost and high-performance electrolytes is one of the key areas for the advancement of SIB technology. The highly conductive liquid or solid electrolytes have the potential for practical sodium-ion battery applications. Long-term stability, alternative polymers, and full-cell integrations are other avenues that need further research to improve scalability and performance for SIBs. This research covers preparing and evaluating liquid and polymer electrolytes, with a focus on ionic conductivities. Liquid electrolytes were prepared by the dissolution of different sodium salts including NaCl, …
An Efficient And Trusted Deep Learning Framework For Real-Time Ppe Detection In Secure Iomt Environment, Anusha Verma
An Efficient And Trusted Deep Learning Framework For Real-Time Ppe Detection In Secure Iomt Environment, Anusha Verma
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Occupationally-acquired infections impact thousands of healthcare workers (HCWs) in the U.S., with many cases preventable through proper use of personal protective equipment (PPE). This study seeks to develop a robust system to enhance PPE compliance and reduce infection risks among HCWs. The objectives of this thesis are twofold: (1) to create a hybrid machine learning model that combines object detection and keypoint detection to ensure correct donning and doffing of PPE, and (2) to design a real-time feedback system using LED indicators and a display interface to offer actionable guidance to HCWs during PPE usage. The goal is to optimize …
An Enhanced Real-Time Object Detection Of Helmets And License Plates Using A Lightweight Yolov8 Deep Learning Model, Mounika Thatikonda
An Enhanced Real-Time Object Detection Of Helmets And License Plates Using A Lightweight Yolov8 Deep Learning Model, Mounika Thatikonda
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Traffic surveillance and enforcement heavily depend on the real-time detection of helmets and license plates, particularly in high-density urban environments. This study presents a dynamic and optimized lightweight model, the proposed G-YOLOv8n, designed for resource constrained edge devices like the Raspberry Pi. By integrating the GhostNet module into the YOLOv8n architecture, this research achieves a nearly 50% reduction in model size and computational load, while maintaining comparable detection accuracy to the original YOLOv8n. These enhancements enable real-time processing capabilities crucial for traffic monitoring operations. The growing demand for real-time, low-power solutions in intelligent transportation systems necessitates lightweight, efficient detection models. …
Void Fraction And Quality Correlation Analysis Using The Separated Flow Model For Pulsed-Power Heat Loads, Zachary Joseph Carner
Void Fraction And Quality Correlation Analysis Using The Separated Flow Model For Pulsed-Power Heat Loads, Zachary Joseph Carner
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Aircraft platforms are continually upgraded with increasingly high quantities of high-powered electronics. As such, efficient thermal management systems are crucially important to overcome system instabilities and support pulsed power profiles. To create effective thermal control systems, it is imperative to thoroughly examine and account for a variety of potential system behaviors caused by transient changes in the flow regime. If left unconstrained, these changes will create thermal instabilities, which can severely damage electronics and hurt the overall reliability of the aircraft. These instabilities can be described by both void fraction and quality. Electrical Capacitance Tomography (ECT) allows for the collection …
Mechanical Reliability Of Aerosol Jet Printed Sensors And Interconnects, Lemuel A. Duncan
Mechanical Reliability Of Aerosol Jet Printed Sensors And Interconnects, Lemuel A. Duncan
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Heterogeneous integration (HI) is currently being investigated to maintain the pace of technological progress in the electronics industry. With the recent acceleration witnessed in additive manufacturing (AM) technology, interest has been expressed in introducing aerosol jet (AJ) printing to the fabrication process for sensors and electronic packages. Integrating AM technology in these areas promises design flexibility and minimal material waste. Three AJ printed applications investigated in this work include strain sensors, electrical interconnects, and metal embedded chip assemblies. Before moving forward with the use of AJ printing in these applications, it is necessary to evaluate their performance under standard mechanical …
Integrating Knowledge Graphs With Large Language Models For Natural Language Querying, Rakesh Kandula
Integrating Knowledge Graphs With Large Language Models For Natural Language Querying, Rakesh Kandula
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This research explores the integration of knowledge graphs with large language models that have already been trained on a vast pool of unstructured text data. Large language models trained on this type of data have a tendency to hallucinate and produce factually inaccurate results. This behavior is primarily due to the data being trained is unstructured and huge text corpus, and large language model uses predictive text analysis methods to obtain a response. These issues can be addressed by applying Retrieval Augmented Generation and Fine-tuning to large language models, employing an underlying domainspecific knowledge graph. Integrating knowledge graph and large …
Prediction Interpretations Of Ensemble Models In Chronic Kidney Disease Using Explainable Ai, K M Tawsik Jawad
Prediction Interpretations Of Ensemble Models In Chronic Kidney Disease Using Explainable Ai, K M Tawsik Jawad
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Chronic Kidney Disease (CKD) poses significant health and financial threat to millions of patients all around the world. The irreversible nature of this disease not just leads to comorbid diseases like Diabetes Mellitus, Hypertension, Anemia, Bone Disease, Neurological Implants etc. It can permanently damage the kidney by progressing to Acute Kidney Injury (AKI) or End Stage Renal Diseases (ESRD). The risk factors of CKD become more dangerous as patients suffering from it have little to no idea about the presence of CKD in their body until it takes the shape of AKI or ESRD. There are severe economic burdens for …
Biomechanical Simulation Of Cardiovascular Implantable Electronic Device Leads With Residual Properties, Anmar Mahdi Salih
Biomechanical Simulation Of Cardiovascular Implantable Electronic Device Leads With Residual Properties, Anmar Mahdi Salih
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Implantable leads used in pacemakers, defibrillators, and cardiac resynchronization therapy are designed for in-vivo applications, yet their longevity is inevitably shaped by the conditions within the human body. The mechanical behavior of these leads can be affected over time, necessitating the evaluation of their residual properties. Two main insulators, silicone, and polyurethane are commonly used for the outer insulation of cardiac leads. Understanding the long-term performance of these insulators is crucial for ensuring the reliability and safety of cardiac implantable devices. The research aims to assess the long-term mechanical properties and performance of implantable leads utilized in cardiovascular implantable electronic …
Potential Role Of Ttt Complex In Regulating Dna Replication Checkpoint In The Fission Yeast Schizosaccharomyces Pombe, Sankhadip Bhadra
Potential Role Of Ttt Complex In Regulating Dna Replication Checkpoint In The Fission Yeast Schizosaccharomyces Pombe, Sankhadip Bhadra
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DNA replication can be perturbed by various agents that slow or stall the replication forks, causing replication stress. If undetected, stressed forks may collapse, causing mutagenic DNA damage or cell death. In response to replication stress and DNA damage, the eukaryotic cell activates the DNA replication checkpoint (DRC) and DNA damage checkpoint (DDC) pathways to promote DNA synthesis, repair, and cell survival. The two cell cycle checkpoint pathways are controlled by the protein sensor kinases Rad3 (hATR/scMec1) and Tel1 (hATM/scTel1) in fission yeast, although Tel1 plays a minimal role in checkpoint functions. Rad3 and Tel1 belong to a family of …
An Ml-Assisted Golden-Free Hardware Trojan Localization And Detection Approach For Trusted Microelectronics, Ashutosh Ghimire
An Ml-Assisted Golden-Free Hardware Trojan Localization And Detection Approach For Trusted Microelectronics, Ashutosh Ghimire
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Hardware Trojans are malicious circuits, hidden in integrated circuits (ICs) which pose a significant threat to security. Detection of hardware Trojans is important to build trust, verify, and make the semiconductor ICs process secure. The existing hardware Trojan detection methods are generally destructive, require intricate comparisons, or require a long time for reverse engineering. In the initial phase of this study, the substitution of supervised hardware Trojan detection methods in ASICs chips is explored with unsupervised approaches, thereby eliminating the dependence on golden references. The Trojan detection uses a ring oscillator (RO) based on NAND as the power monitor. Frequency …