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Pan-Cancer Analysis Of Rna Dysregulation, Somatic Mutations, And Matrix Stiffness Using Bioinformatics Approaches, Gongyu Tang
Pan-Cancer Analysis Of Rna Dysregulation, Somatic Mutations, And Matrix Stiffness Using Bioinformatics Approaches, Gongyu Tang
McKelvey School of Engineering Graduate Student Theses & Dissertations
Cancer is a complex disease driven by genetic mutations, epigenetic modifications, and alterations in the tumor microenvironment. Understanding these intricate molecular mechanisms is crucial for advancing cancer diagnosis, prognosis, and treatment. RNA sequencing (RNA-seq) has emerged as a powerful tool to study cancer by providing comprehensive insights into gene expression, alternative splicing, and mutations at the transcriptome level. This dissertation leverages RNA-seq data to explore different dimensions of cancer biology through multi-omics integration and computational approaches. The research is divided into three main projects. First, I developed OncoDB, an interactive database to analyze gene expression, methylation patterns, and viral interactions …
The Encoding Of Decision Variables In Orbitofrontal Cortex (Ofc) Is Longitudinally Stable And Varies By Cortical Layer, Manning Zhang
The Encoding Of Decision Variables In Orbitofrontal Cortex (Ofc) Is Longitudinally Stable And Varies By Cortical Layer, Manning Zhang
McKelvey School of Engineering Graduate Student Theses & Dissertations
Economic choices entail computing the values of different options and then making choice by comparing values. Work in primates and rodents has shown that these mental processes rely on the OFC. Neurophysiology studies identified in OFC distinct groups of neurons encoding the value of individual options, the binary choice outcome, and the chosen value. These variables capture both the input and the output of the decision process, suggesting a decision circuit existing in OFC. A primary challenge for the field is to assess the structure and mechanisms governing this circuit. A first fundamental question is whether the circuit is stable …
Terpene Bioproduction From Non-Model Yeast: Omics Analysis And Metabolic Modeling For Guiding Scaleup Optimization, Alyssa Worland
Terpene Bioproduction From Non-Model Yeast: Omics Analysis And Metabolic Modeling For Guiding Scaleup Optimization, Alyssa Worland
McKelvey School of Engineering Graduate Student Theses & Dissertations
Sustainability efforts have driven significant advancements in synthetic biology, particularly through the development of microbial cell factories designed for waste reduction and resource conservation. This dissertation seeks to characterize a microbial biorefinery platform for the biosynthesis of terpene compounds from yeast, with an emphasis on the industrial bioconversion of waste lipids. Terpene compounds play crucial roles in various industrial applications; however, traditional methods of terpene production have sustainability and productivity challenges that could be overcome by using microbial biosynthesis. The yeast Yarrowia lipolytica is a microbial host well suited for converting waste oils into value-added terpenes due to its native …
Quantitative Approaches To Dissect Bivalent Antibody Binding And Detect Viruses From Aerosolized Samples, Ananya Benegal
Quantitative Approaches To Dissect Bivalent Antibody Binding And Detect Viruses From Aerosolized Samples, Ananya Benegal
McKelvey School of Engineering Graduate Student Theses & Dissertations
Influenza A virus (IAV) poses substantial epidemiological burdens around the world, with an estimated annual global mortality rate in the hundreds of thousands. Its rapid rate of mutation gives it a propensity for causing seasonal epidemics and occasional pandemics. As an airborne virus, IAV is most commonly transmitted through droplets and aerosols. Antibodies play a crucial role in the immune defense against IAV infection. By understanding the mechanisms of antibody-mediated defense and the transmission dynamics of IAV, we can better inform strategies for prevention, vaccination, and treatment, ultimately mitigating its impact on public health. The work encompassed in this dissertation …
Integrating Physics And Deep Learning For Transmission-Less Attenuation Compensation In Clinical Spect, Zitong Yu
McKelvey School of Engineering Graduate Student Theses & Dissertations
Attenuation compensation (AC) is beneficial for visual interpretation and serves as a prerequisite for quantification tasks in single-photon emission computed tomography (SPECT) imaging. However, conventional AC methods typically rely on a separate X-ray CT component, leading to multiple challenges. In this context, studies have shown that scatter-window projection data contains information to estimate the attenuation distribution. Furthermore, large amounts of SPECT emission data in both photopeak and scatter-energy windows and corresponding CT scans are available. The ability of deep learning (DL) to model complex relationships by leveraging large datasets motivates its use for transmission-less AC in SPECT. Building upon the …
Development Of Computational Imaging Pipelines To Advance Quantitative Co-Clinical Imaging And Pathology, Kaushik Dutta
Development Of Computational Imaging Pipelines To Advance Quantitative Co-Clinical Imaging And Pathology, Kaushik Dutta
McKelvey School of Engineering Graduate Student Theses & Dissertations
Deep learning driven computational methods have profoundly impacted medical imaging by advancing feature extraction, and by establishing a critical foundation for downstream image analysis and interpretation. Co-clinical trials are an emerging area of investigation in which a clinical trial is coupled with a corresponding preclinical study to inform the corresponding clinical trial to enhance translational accuracy and therapeutic development. Within this framework, quantitative imaging and pathology plays a fundamental role in both clinical and preclinical arms of co-clinical trials. Quantitative imaging enables enabling identification and validation of imaging biomarkers which are leveraged to predict therapeutic response, characterize disease phenotypes, and …
Developing Naturalistic Precision Functional Mapping For High-Density Diffuse Optical Tomography, Aahana Bajracharya
Developing Naturalistic Precision Functional Mapping For High-Density Diffuse Optical Tomography, Aahana Bajracharya
McKelvey School of Engineering Graduate Student Theses & Dissertations
Advancements in non-invasive imaging have enabled extensive research into higher-order cognitive functions of the brain. Functional Magnetic Resonance Imaging (fMRI) has provided valuable insights into brain networks underlying various cognitive processes. However, limitations such as confined environments and scanner noise pose challenges for fMRI to be broadly applicable across all demographics and experimental conditions, especially in speech and language studies. Because of this, there is a need for complementary techniques that can help understand the brain as it functions during everyday scenarios. High Density Diffuse Optical Tomography (HD-DOT) is an emerging functional near-infrared spectroscopy-based technique with comparative advantages over fMRI, …
Bone-Ivd Crosstalk And The Role Of Rage Signaling In An Ivd Injury Model, Remy Walk
Bone-Ivd Crosstalk And The Role Of Rage Signaling In An Ivd Injury Model, Remy Walk
McKelvey School of Engineering Graduate Student Theses & Dissertations
Low back pain (LBP) is the number one musculoskeletal cause of disability with a lifetime prevalence of up to 85%. The causes of LBP are multifactorial with potential contributions from factors such as tissue injury and degeneration as well as social economic and psychological factors. Intervertebral disc (IVD) degeneration is associated with 26-40% of LBP cases and in a 2015 meta-analysis, it was estimated that a total 403 million people suffer from symptomatic IVD degeneration. IVD degeneration is characterized by loss of hydration in the nucleus pulposus (NP), damage accumulation in the annulus fibrosus (AF) and calcification of the cartilaginous …
Defining The Chondrocyte “Mechanome”: How Mechanosensitive Ion Channels Trpv4 And Piezo1 Drive Changes In Gene Expression To Affect Cell Behavior And Cartilage Health, Daniel Raymond Palmer
Defining The Chondrocyte “Mechanome”: How Mechanosensitive Ion Channels Trpv4 And Piezo1 Drive Changes In Gene Expression To Affect Cell Behavior And Cartilage Health, Daniel Raymond Palmer
McKelvey School of Engineering Graduate Student Theses & Dissertations
Chondrocytes, the only native cell population of cartilage, utilize mechanosensitive transmembrane ion channels to sense mechanical forces. Transient Receptor Potential Vanilloid 4 (TRPV4) is activated by physiologic levels of load (resulting in ~10% tissue deformation) while PIEZO1 is activated by supraphysiologic levels of load (resulting in >50% tissue deformation). TRPV4 activation promotes the expression of a limited number of chondrogenic genes and the production of vital cartilaginous matrix proteins, while PIEZO1 activation drives cell death and senescence, cytoskeletal weakening, and production of catabolic mediators, which contribute to the development of osteoarthritis (OA). However, the path connecting activation of these channels …
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
McKelvey School of Engineering Graduate Student Theses & Dissertations
Cyber-physical systems (CPS), including autonomous vehicles, drones, and mobile robots, rely on intricate sensors, actuators, and machine learning algorithms to perceive the physical world and execute actions within their surroundings. In the context of vision-driven CPS, achieving this demands processing a substantial volume of visual data captured by on-board cameras. The data is subsequently channeled through digital processors and harnessed by deep neural networks for tasks such as image classification, object detection, and depth perception. This data-centric, machine-vision-infused CPS fosters intelligent decision-making, thereby enhancing overall system performance. Trustworthiness, encompassing the robustness of the entire machine-vision pipeline, and system-level efficiency are …
Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar
Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar
McKelvey School of Engineering Graduate Student Theses & Dissertations
Alzheimer’s Disease (AD) is the leading cause of dementia, characterised by cognitive and functional impairments that disrupt daily activities. Different clinical modalities such as neuroimaging biomarkers, cognitive assessments, fluid biomarkers and genetic data provide unique and complementary information, contributing to a more comprehensive understanding of disease progression and heterogeneity in disease characteristics. With recent advancements in computational capabilities, particularly in deep learning, multimodal representation learning frameworks aim to integrate diverse clinical modalities into a cohesive framework, capturing the most significant patterns within each modality. Existing data-driven multimodal representation learning frameworks in AD research have two major limitations. First, AD progresses …
Integrating Physics And Deep Learning For Transmission-Less Attenuation Compensation In Clinical Spect, Zitong Yu
McKelvey School of Engineering Graduate Student Theses & Dissertations
Attenuation compensation (AC) is beneficial for visual interpretation and serves as a prerequisite for quantification tasks in single-photon emission computed tomography (SPECT) imaging. However, conventional AC methods typically rely on a separate X-ray CT component, leading to multiple challenges. In this context, studies have shown that scatter-window projection data contains information to estimate the attenuation distribution. Furthermore, large amounts of SPECT emission data in both photopeak and scatter-energy windows and corresponding CT scans are available. The ability of deep learning (DL) to model complex relationships by leveraging large datasets motivates its use for transmission-less AC in SPECT. Building upon the …
The Encoding Of Decision Variables In Orbitofrontal Cortex (Ofc) Is Longitudinally Stable And Varies By Cortical Layer, Manning Zhang
The Encoding Of Decision Variables In Orbitofrontal Cortex (Ofc) Is Longitudinally Stable And Varies By Cortical Layer, Manning Zhang
McKelvey School of Engineering Graduate Student Theses & Dissertations
Economic choices entail computing the values of different options and then making choice by comparing values. Work in primates and rodents has shown that these mental processes rely on the OFC. Neurophysiology studies identified in OFC distinct groups of neurons encoding the value of individual options, the binary choice outcome, and the chosen value. These variables capture both the input and the output of the decision process, suggesting a decision circuit existing in OFC. A primary challenge for the field is to assess the structure and mechanisms governing this circuit. A first fundamental question is whether the circuit is stable …
Terpene Bioproduction From Non-Model Yeast: Omics Analysis And Metabolic Modeling For Guiding Scaleup Optimization, Alyssa Worland
Terpene Bioproduction From Non-Model Yeast: Omics Analysis And Metabolic Modeling For Guiding Scaleup Optimization, Alyssa Worland
McKelvey School of Engineering Graduate Student Theses & Dissertations
Sustainability efforts have driven significant advancements in synthetic biology, particularly through the development of microbial cell factories designed for waste reduction and resource conservation. This dissertation seeks to characterize a microbial biorefinery platform for the biosynthesis of terpene compounds from yeast, with an emphasis on the industrial bioconversion of waste lipids. Terpene compounds play crucial roles in various industrial applications; however, traditional methods of terpene production have sustainability and productivity challenges that could be overcome by using microbial biosynthesis. The yeast Yarrowia lipolytica is a microbial host well suited for converting waste oils into value-added terpenes due to its native …
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
McKelvey School of Engineering Graduate Student Theses & Dissertations
Cyber-physical systems (CPS), including autonomous vehicles, drones, and mobile robots, rely on intricate sensors, actuators, and machine learning algorithms to perceive the physical world and execute actions within their surroundings. In the context of vision-driven CPS, achieving this demands processing a substantial volume of visual data captured by on-board cameras. The data is subsequently channeled through digital processors and harnessed by deep neural networks for tasks such as image classification, object detection, and depth perception. This data-centric, machine-vision-infused CPS fosters intelligent decision-making, thereby enhancing overall system performance. Trustworthiness, encompassing the robustness of the entire machine-vision pipeline, and system-level efficiency are …
Development Of Computational Imaging Pipelines To Advance Quantitative Co-Clinical Imaging And Pathology, Kaushik Dutta
Development Of Computational Imaging Pipelines To Advance Quantitative Co-Clinical Imaging And Pathology, Kaushik Dutta
McKelvey School of Engineering Graduate Student Theses & Dissertations
Deep learning driven computational methods have profoundly impacted medical imaging by advancing feature extraction, and by establishing a critical foundation for downstream image analysis and interpretation. Co-clinical trials are an emerging area of investigation in which a clinical trial is coupled with a corresponding preclinical study to inform the corresponding clinical trial to enhance translational accuracy and therapeutic development. Within this framework, quantitative imaging and pathology plays a fundamental role in both clinical and preclinical arms of co-clinical trials. Quantitative imaging enables enabling identification and validation of imaging biomarkers which are leveraged to predict therapeutic response, characterize disease phenotypes, and …
Spatial Insight Of Kidney Sex-Dimorphism And Tumor Evolution, Chia-Kuei Mo
Spatial Insight Of Kidney Sex-Dimorphism And Tumor Evolution, Chia-Kuei Mo
McKelvey School of Engineering Graduate Student Theses & Dissertations
The landscape of spatial biology research has transformed drastically in recent years allowing a comprehensive understanding of cellular organization and molecular mechanisms in various biological context. This thesis presents three complementary studies that advance our understanding of spatial organization in normal tissue biology and tumor evolution, utilizing cutting-edge spatial multi-omics approaches. The first study presents a comprehensive investigation of kidney sexual dimorphism across the lifespan, integrating six distinct technological platforms: single-nucleus transcriptomics, epigenomics, Visium spatial transcriptomics, Xenium single-cell resolution spatial transcriptomics, conventional immunofluorescence imaging, and co-detection by indexing (CODEX) multiplexed protein imaging. This multi-modal approach reveals that proximal tubules exhibit …
Discrete Element Method For Mining Industrial Applications: Solving The Clumping Problem Caused By Bulk Cohesive Particles In An Iron Ore Beneficiation Process, Shuang Liu
McKelvey School of Engineering Graduate Student Theses & Dissertations
The discrete element method (DEM) is a widely used numerical approach for simulating and analyzing the behavior of granular materials in various applications. This research focuses on the iron ore beneficiation process, addressing the clumping issue in cohesive iron ores from existing crushing processes through a novel double-layered disperser design. The significance of this study lies in its potential to enhance the efficiency of the existing crushing phase and improve the linkage to subsequent purification stages that target smaller-sized iron ore pellets, thereby enhancing the overall efficiency of the ore beneficiation process and achieving significant energy savings. This research adopts …
Pan-Cancer Analysis Of Rna Dysregulation, Somatic Mutations, And Matrix Stiffness Using Bioinformatics Approaches, Gongyu Tang
Pan-Cancer Analysis Of Rna Dysregulation, Somatic Mutations, And Matrix Stiffness Using Bioinformatics Approaches, Gongyu Tang
McKelvey School of Engineering Graduate Student Theses & Dissertations
Cancer is a complex disease driven by genetic mutations, epigenetic modifications, and alterations in the tumor microenvironment. Understanding these intricate molecular mechanisms is crucial for advancing cancer diagnosis, prognosis, and treatment. RNA sequencing (RNA-seq) has emerged as a powerful tool to study cancer by providing comprehensive insights into gene expression, alternative splicing, and mutations at the transcriptome level. This dissertation leverages RNA-seq data to explore different dimensions of cancer biology through multi-omics integration and computational approaches. The research is divided into three main projects. First, I developed OncoDB, an interactive database to analyze gene expression, methylation patterns, and viral interactions …
Discrete Element Method For Mining Industrial Applications: Solving The Clumping Problem Caused By Bulk Cohesive Particles In An Iron Ore Beneficiation Process, Shuang Liu
McKelvey School of Engineering Graduate Student Theses & Dissertations
The discrete element method (DEM) is a widely used numerical approach for simulating and analyzing the behavior of granular materials in various applications. This research focuses on the iron ore beneficiation process, addressing the clumping issue in cohesive iron ores from existing crushing processes through a novel double-layered disperser design. The significance of this study lies in its potential to enhance the efficiency of the existing crushing phase and improve the linkage to subsequent purification stages that target smaller-sized iron ore pellets, thereby enhancing the overall efficiency of the ore beneficiation process and achieving significant energy savings. This research adopts …
Re: Butte Mine Flooding Operable Unit Berkeley Pit And Discharge Pilot Project – November 2024 Monthly Discharge Monitoring Report, Mark Thompson, Dave Griffis
Re: Butte Mine Flooding Operable Unit Berkeley Pit And Discharge Pilot Project – November 2024 Monthly Discharge Monitoring Report, Mark Thompson, Dave Griffis
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Unreclaimed Sites And Insufficiently Reclaimed Areas – Racetrack Borrow Material Usage (Dated December 19, 2024), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Importance Of Social Support During Pregnancy For Girls With Limited Education, Mairo V. Bello
Importance Of Social Support During Pregnancy For Girls With Limited Education, Mairo V. Bello
Walden Dissertations and Doctoral Studies
Social support signifies a system that provides for family, relatives, and friends or is derived from external sources such as social services or health promotion networks and can reduce depression and increase well-being. Absent from the literature was the understanding of the significance of social support for young women with limited education aged 18-25 on the journey from conception to the postpartum period in Nigeria. In this qualitative phenomenological study, the individual perception, attitude, and social support received by young women with limited education during pregnancy in Wudil LGA of Kano state in northern Nigeria were examined. The study addressed …
A Comprehensive Usability And Economic Analysis Of Heat-Related Wearable Technologies: Applications To Occupational Health, Ryan T. Cannady
A Comprehensive Usability And Economic Analysis Of Heat-Related Wearable Technologies: Applications To Occupational Health, Ryan T. Cannady
Theses & Dissertations
The purpose of this research was to analyze the usability and economic considerations of real-time wearable technologies that are implemented in occupational settings to assess risk of heat stress and heat strain. The study population included current agriculture workers and Department of Energy (DOE), Environmental Management (EM) contractors. We employed a mixed-methods approach to comprehensively analyze the usability and economic considerations of heat-related technologies. Specifically, our approach assessed three distinct aspects the applications of these technologies in occupational settings to comprehensively address our research objective: (1) worker perceptions of heat-related wearable technologies, (2) field-based assessment of these heat-related wearable technologies, …
Enhancing Concrete Sustainability With Self-Healing Technologies, Al Shimaa Abdullatif
Enhancing Concrete Sustainability With Self-Healing Technologies, Al Shimaa Abdullatif
Theses and Dissertations
Thanks to its strength, durability and affordability, Portland cement concrete is the most commonly used building material worldwide. However, concrete cracking is inevitable due to numerous factors including shrinkage, exposure to external chemicals, internals reactions, excessive loads, to name but a few. Self-healing is a promising technique that can enable concrete to autogenously heal cracks and alleviate much of the damage. Such healing can without a doubt extend the service life with less need for external repair works therefore it contributes to sustainability. Over the years, several means of self-healing agents have been explored including bio-based procedures and the incorporation …
On Relationship Between Experiment And Theory In Basic Scientific Research, Changpu Sun
On Relationship Between Experiment And Theory In Basic Scientific Research, Changpu Sun
Bulletin of Chinese Academy of Sciences (Chinese Version)
Understanding how experiments in basic scientific research “confirm” theories is crucial for upholding the spirit of science and fostering technological innovation. Mr. Zhou Guangzhao conducted an in-depth discussion on this topic in his early work. This study further analyzes the issue from the perspective of the philosophy of science. We derive falsificationism from a Bayesian perspective, providing a philosophical understanding of the proper handling of the relationship between scientific theory and experiment. By examining the relationship between theory and experiment in physics, this study proposes a philosophy of science concept of progressive falsifiability, emphasizing that through Bayesian methods, experiments can …
Overall Promotion Of Integrated Management And Utilization Of Saline-Alkali Land In Northwest China: Conditions, Challenges, And Recommendations, Qi Feng, Xinwei Yin, Meng Zhu, Jutao Zhang, Wei Liu, Haiyang Xi, Tengfei Yu, Linshan Yang, Wen Liu, Zhixiang Lu
Overall Promotion Of Integrated Management And Utilization Of Saline-Alkali Land In Northwest China: Conditions, Challenges, And Recommendations, Qi Feng, Xinwei Yin, Meng Zhu, Jutao Zhang, Wei Liu, Haiyang Xi, Tengfei Yu, Linshan Yang, Wen Liu, Zhixiang Lu
Bulletin of Chinese Academy of Sciences (Chinese Version)
Cultivated land is the lifeblood of grain production and the foundation for food security. Saline-alkali land in Northwest China is an important cultivated land reserve resource and a potential granary for guaranteeing national food security, so the high-quality promotion of comprehensive management and utilization of saline-alkali land in Northwest China is a strategic measure to achieve the goal of “storing grain in land and technology”. Based on a profound understanding of the great significance for promoting the integrated management and utilization of saline-alkali land in Northwest China, this study systematically summarizes the quantity, distribution pattern, and utilization potential of saline-alkali …
China’S Rare Earths Trade Flow Analysis: Trade Patterns And Strategic Insights, Linbin Tang, Peng Wang, Wei Chen, Yawen Han, Yuning Jin, Zilong Peng, Weiqiang Chen
China’S Rare Earths Trade Flow Analysis: Trade Patterns And Strategic Insights, Linbin Tang, Peng Wang, Wei Chen, Yawen Han, Yuning Jin, Zilong Peng, Weiqiang Chen
Bulletin of Chinese Academy of Sciences (Chinese Version)
Rare earth elements are strategic critical metals that support low-carbon energy, aerospace, and defense technologies. Currently, China’s rare earth industry lacks competitiveness and faces the risk of “multidimensional pressures” in global competition. Therefore, it is crucial to systematically analyze the supply-demand and trade patterns of rare earths, accurately identify the bottlenecks and pain points in China’s entire rare earth industry chain, and provide strategies to transform China’s rare earth resource advantage into a strategic competitive edge. Based on customs trade data, this study traces the trade flows of various forms of rare earth products across the full industry chain in …
How Should China Respond To “Pan-Data Sovereignty” Competition Among China, U.S., And Eu—An Analysis Based On The Digital Stack Model?, Yan Liu, Congjing Ran
How Should China Respond To “Pan-Data Sovereignty” Competition Among China, U.S., And Eu—An Analysis Based On The Digital Stack Model?, Yan Liu, Congjing Ran
Bulletin of Chinese Academy of Sciences (Chinese Version)
Data sovereignty has become deeply intertwined with various economic and social development factors such as technology, trade, economy, culture, society, and politics, leading to a “Pan-Data Sovereignty” competition pattern in the digital space. Through the digital stack model, which examines digital technologies in a layered framework, we can more clearly assess the competitive capacities in“Pan-Data Sovereignty” of China, United States, and European Union. The analysis identifies a three-tiered global “Pan-Data Sovereignty” competition structure among China, U.S., and EU, with each entity holding distinct advantages across various layers of the digital stack. Intense future competition is anticipated in fields such as …
Fail-Safe Logic Design Strategies Within Modern Fpga Architectures, Priya A. Bhakta
Fail-Safe Logic Design Strategies Within Modern Fpga Architectures, Priya A. Bhakta
Electrical and Computer Engineering ETDs
Field Programmable Gate Arrays (FPGAs) are vulnerable to radiation-induced single event upsets (SEUs) and fault injection attacks, requiring the use of redundancy techniques such as fail-safe computing. Fail-safe computing refers to computing systems that revert to a non-operational safe state when a fault occurs. This work investigates circuit-level techniques and implements fail-safe computing processes as mitigation for SEUs and fault injection attacks on FPGAs. The analysis reveals vulnerabilities that exist in FPGAs over those in application-specific integrated circuits (ASIC); thus, requiring a more elaborate network of redundant circuits and checking logic. The reconfiguration capability of FPGAs adds complexity to fail-safe …