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Raman Spectroscopy as a Diagnostic Tool for the Detection of Tomato Brown Rugose Fruit Virus
No full textTomatoes and peppers together constitute a billion-dollar industry in the United States alone, which speaks highly of their importance to growers and the United States Department of Agriculture (USDA) alike. These crops, however, are host to a destructive virus, tomato brown rugose fruit virus (ToBRFV). Due to its ability to overcome all tobomovirus resistance genes, including Tm-2��, there are no known resistant varieties for ToBRFV. Therefore, many regulations are in place in hopes of controlling its spread, yet it continues to spread to many areas around the world, constituting a global epidemic. Raman spectroscopy (RS) is a noninvasive tool that scans a sample and uses the interaction of light and molecules to give a resulting spectrum of scattered light that can be used for analysis. This tool for detecting chemical compounds is already popular in many fields and has recently even been a growing research endeavor for disease diagnostics in plant pathology, where it has shown great promise with a wide variety of diseases. In this study, we examine ToBRFV as well as tobacco mosaic virus (TMV) and aim to determine if RS can be used as a diagnostic method to aid in management practices. We hypothesize that we will be able to observe differences in spectral peaks between healthy and infected plant/seed tissue with control, TMV, and ToBRFV groups. After inoculation, scanning, and Matlab analysis, it was demonstrated that there were spectral differences between healthy and infected plants, as well as differences between TMV and ToBRFV-infected plants. Additionally, this experiment was done on pepper seeds and preliminary data was obtained which displayed spectral differences between pepper seeds infected with ToBRFV and control seeds, showing potential support for this notion on seed tissue as well. Results suggest that RS does show promise to be incorporated as a diagnostic method and may provide useful insight into virus distribution throughout plants. Based on the results obtained in this study, there is potential for future work to take place on the basis of this data
Beam Hardening and Scatter Artifact with Metal Objects Inside and Outside the Field of View in CBCT Imaging
No full textIntroduction: This study compares the objective and subjective appearance of artifacts produced by metal objects inside and outside the limited field of view (FOV) of a common region of interest (ROI).
Methods: Metal objects (titanium rods, zirconium rods, zirconium crucibles) were positioned in the human cadaver���s left maxilla and imaged using Accuitomo 170 CBCT with limited FOV. Sixteen scans (7 with metal inside the FOV, 7 with metal outside the FOV, and two controls) were obtained. The artifacts were objectively evaluated by calculating the standard deviation (SD) of grayscale values using ImageJ software. For the subjective test, two observers rated paired images for beam hardening/scatter artifacts.
Results: The Wilcoxon signed rank test showed no difference in the SD of grayscale values with the metal objects inside or outside the FOV (p=.2882). However, a subjective comparison of the two image groups (metal objects inside and outside FOV) showed subtle differences in beam hardening intensity in the region immediately adjacent to the metal objects. The SD of grayscale values for slices at the level of metal objects were higher than those apical to the level of metal objects (p<0.001). Conclusion: Strategic repositioning of a limited FOV CBCT to avoid metal objects did not significantly reduce the image noise. However, it reduced the beam hardening artifact on the area of the image immediately adjacent to the metal object. Additionally, selectively tilting the patient���s chin to keep metal objects in a different horizontal plane from ROI may reduce artifact appearance
Investigation of Co-resident Attacks in Serverless Cloud Environment
No full textIn the rapidly evolving landscape of cloud computing, serverless environments have gained prominence for their scalability and efficiency. However, the security of such environments re-mains a critical concern given how ubiquitous their implementation is in both academic and industrial settings. This study delves into the realm of co-resident attacks within serverless cloud con-texts, aiming to exploit the weak isolation within software infrastructure implementation. Specifically, this research investigates the potential flaws in the Function as a Service (FaaS) framework and sheds light on the vulnerabilities that arise when multiple tenants share the same underlying hardware. By identifying these vulnerabilities, this research aims to improve the security of serverless cloud domain and explores avenues to protect against co-resident attacks. This work specifically investigates the feasibility of cache covert channel attacks within serverless environments deployed on commercial cloud platforms. In this study, the open-source Apache OpenWhisk function-as-a-service (FaaS) is deployed on top of a Kubernetes (K8s) cluster. The cluster is pro-visioned and managed using Google Kubernetes Engine (GKE) on the Google Cloud Platform (GCP) to emulate a real-world scenario. With this, the potential of malicious actors establishing covert communication channel across co-resident functions is investigated. The research is conducted in a shared host environment within GCP, emphasizing on virtual CPU (vCPU) resource sharing. Dedicated hosts are intentionally avoided to simulate real-world cloud deployment scenarios. Our findings indicate that commercial-grade clouds like GCP inherently provide a degree of security obfuscation, making covert channel establishment more challenging. While attacks may be more feasible on dedicated single-tenant machines, the shared nature of commercial cloud environments adds a layer of complexity. Serverless frameworks, while introducing new abstractions, ultimately rely on the same underlying infrastructure; therefore, they introduce additional noise rather than fundamentally altering the attack surface. While effective defense mechanisms can be implemented, they invariably introduce performance overheads
A New Galerkin Quadrature Method Without the Requirement of Matrix Inverse
No full textA new method of forming the scattering source of the Boltzmann neutron transport equation for anisotropic scattering is proposed through the use of Grahm-Schmidt orthogonalization. This new method builds upon two previous methods but differentiates itself by lowering the computational burden of the calculation and potentially admitting more general types of quadratures. It is hoped that this method will gain greater traction in codes solving the Boltzmann neutron transport because of its lower cost and wider applicability. The Galerkin Quadrature method is required for highly anisotropic scattering, which characterizes charged particle transport, and was originally developed for this purpose. This thesis presents the sum of research into the new Galerkin Quadrature method in the form of a paper submitted to the Journal of Nuclear Science and Engineering, 2024. The derivation of all 3 Galerkin Quadrature methods are defined, the test problems are stated with their results, and conclusions drawn. An additional summary section details the conclusions of the overall work
Optimizing Markov Decision Process Models of Intermittently-Observed Multi-Agent Systems
No full textA challenging category of robotics problems arises when sensing incurs substantial costs. This thesis examines settings in which a robot wishes to limit its observations of state, for instance, motivated by specific considerations of energy management, stealth, or implicit coordination between multiple agents. We consider the problem of planning under uncertainty when a robot���s observations are intermittent under two specific circumstances. In one, their timing is known via a pre-declared schedule, whereas in the other the timing arises dynamically from multiple robots working together to generate observations.
After establishing the appropriate notion of an optimal policy for each setting, we find that the pre-declared case requires tackling the problem of joint optimization of the cumulative execution cost and the number of state observations, both in expectation under discounts. To approach this multi-objective optimization problem, we introduce an algorithm that can identify the Pareto front for a class of schedules that are advantageous in the discounted setting. The algorithm proceeds in an accumulative fashion, prepending additions to a working set of schedules and then computing incremental changes to the value functions. Because full exhaustive construction becomes computationally prohibitive for moderate-sized problems, we propose a filtering approach to prune the working set. Empirical results demonstrate that this filtering is effective at reducing computation while incurring only negligible reduction in quality. In summarizing our findings, we provide a characterization of the run-time vs quality trade-off involved.
We explore as well the dynamic observation scenario, by developing a formulation for renegotiation of observations throughout execution. The formulation is additionally expanded to support the navigation of multiple agents in a single, joint MDP. We conclude with a hardware demonstration featuring two robots maintaining formation whilst moving down a corridor, subject to motion uncertainty and turning to look at each other intermittently to gauge their states
NAC1 Restrains T Cell Memory Formation through Metabolism Regulation During Viral Infection
No full textOur recent studies uncovered the important roles of nucleus accumbens-associated protein 1 (NAC1), a transcriptional co-factor, in regulating the activity of regulatory T cells, and antitumor immunity. Little is known about how NAC1 interrupts T cell memory, despite its significance in the host's defensive response to invading pathogens. Many factors interrupt T cell memory formation, such as transcriptional factors, virus types, cell metabolism, and autophagic status.
In the current study, we analyzed T cells from wild-type (WT) and NAC1-deficient (-/-) mice and observed that NAC1 is essential for both CD8��� and CD4��� T cell metabolism including glycolysis and oxidative phosphorylation and supports T cell survival in vitro.
In vivo, compared with wild-type (WT) mice, NAC1-/- mice exhibit a slow decrease of viral antigen (Ag)-specific CD8��� T cells. Additionally, we observed that the NAC1-/- mice demonstrated a stronger memory formation of VACV-specific CD8��� T cells post-viral infection. Mechanically, we identified that compared with WT CD8��� T cells, the Interferon Regulatory Factor 4 (IRF4), a key transcription factor in T cell development, was highly expressed in NAC1-/- CD8��� T cells. For CD4��� T cells, we further demonstrated that deficiency of NAC1 downregulates glycolysis in CD4��� T cells through modulation of the AMPK-mTOR pathway. Moreover, loss of NAC1 reduces the expression of ROCK1, the phosphorylation and stabilization of BECLIN1. Furthermore, forced expression of ROCK1 in NAC1-/- CD4��� T cells results in the restoration of autophagy as well as the activity of the AMPK-mTOR pathway. In animal experiments, adoptively transferred NAC1-/- CD4��� T cells or NAC1-/- mice challenged with VACV show enhanced formation of the VACV-specific CD4��� memory T cells as compared with adoptively transferred WT CD4��� T cells or WT mice, but this enhancement of memory T cell formation can be abrogated by forced expression of ROCK1.
Overall, the results of this study reveal the novel role of NAC1 as a suppressor of T cell memory formation and imply that targeting NAC1 may be exploited as a new approach to promoting memory T cell development
Higher-Dimensional Data in Powder-Bed Fusion Additive Manufacturing: A Path to Improved Printability Predictions
No full textThis dissertation explores the optimization of alloy design and process parameters in metal additive manufacturing (AM), specifically focusing on powder bed fusion (PBF) processes like laser powder bed fusion (L-PBF) and electron beam powder bed fusion (EB-PBF). Conventionally, process parameters for well-known alloys were optimized in hopes of achieving properties similar to those obtained using traditional manufacturing methods. However, the potential of AM processes, particularly PBF, demands the development of alloys tailored to exploit these unique benefits. The complexity of PBF systems, with numerous design degrees of freedom, necessitates a strategic approach to alloy design and process parameter optimization.
To address these challenges, this dissertation introduces two frameworks centered around the use of higher-dimensional data. The first framework is a purely data-driven model that efficiently explores composition and process parameter spaces. Drawing from a database collected from the literature and in-house experiments, this screening tool incorporates classification techniques to predict process defects and identify regions conducive to good printability. Alloys with larger printability regions are better suited to be fabricated using PBF processes.
The second framework is a physics-based model for the fine-tuning of metal alloy printability. Overcoming challenges present in current frameworks, this model employs dimensionality reduction techniques and regression methods to predict higher-dimensional spatial thermal field outputs instead of relying on lower-dimensional melt-pool dimensions. This approach allows for predicting melt-pool dimensions at varying layer thicknesses and beam spot sizes without the need for additional experiments. This allows for the exhaustive exploration of the process parameter design space.
Overall, the dissertation���s focus on leveraging higher-dimensional data provides a comprehensive and efficient methodology for advancing alloy design and optimizing process parameters in PBF processes, contributing to the evolution of metal additive manufacturing
Triple-Tuned Radiofrequency Coil Designs for Magnetic Resonance Imaging and Spectroscopy
No full textMulti-nuclear MRI/S has been shown to be a powerful tool for both diagnostics and the study of disease. While the potential of this technology has been recognized for decades, widespread clinical adoption of these techniques has been limited in large part due to the continued inaccessibility of multi-nuclear hardware. The work presented here aims to address the many design considerations of multi-nuclear RF coil designs, which are necessary to support biomarker development for Duchenne muscular dystrophy (DMD).
This work specifically details the design, construction, and characterization of several triple-tuned coil designs. First, a triple-tuned nested volume coil design composed of a pair of nine-leg birdcages designed to create parallel fields and an orthogonal saddle coil insert at 4.7T. The nine-leg birdcage pair was designed such that it could geometrically decouple from any orthogonal insert coil, either a dedicated planar receive coil or an orthogonal volume coil to operate in either the double- or triple-tuned configurations. SNR comparisons were specifically drawn between geometric decoupling design and active detuning.
Next, a truly simultaneous triple-tuned trap design was investigated for the use in scalable receiver arrays. This design proposes a parallel trap network in place of a more conventional series design to theoretically decrease the equivalent series resistance of the resultant trap network. A roughly 20% improvement in SNR was seen for 1H, but the theoretical sensitivity gains for the X-nuclei frequencies could not be fully resolved. The parallel trap network was compared to both a double- and triple-tuned series trap designs. X-nuclei sensitivities were close in both the double- and triple-tuned reference coils, indicating the additional losses from triple-tuning are minimal in comparison.
Finally, a modular multi-nuclear array was designed and characterized to enable a biomarker study on canine models of DMD. This design used a series PIN diode as a broadband active detuning network to enable decoupling independent of both position and frequency for stacked receive coils. Comparisons were specifically made between this broadband network and a conventional narrow band trap detuning mechanism. Comparisons were also made between a single larger loop and an inscribed array for 1H, 31P, and 23Na
Common Operating Picture Enhancement for Cyber-Physcial Data and Under Contingencies
No full textThe power grid is the foundation of contemporary society's infrastructure, so it is crucial to take strong cybersecurity precautions to guard against potential disruptions that could have a significant impact on the stability and functionality of society. The power grid is particularly vulnerable to new cyber threats that pose a growing threat to its resilience.
This research explores the crucial role of common operating pictures in bolstering the cybersecurity of critical infrastructure with easily understandable data. The primary approach to depicting the common operating picture involves the utilization of Graphical User Interfaces (GUIs), which serve as digital platforms enabling operators to engage with physical equipment via visual graphics and graphical icons. The study investigates the Cyber-Physical Resilient Energy Systems Energy Management System (CYPRES EMS) and places a significant emphasis on Cyber-Physical Situational Awareness (CyPSA).
Furthermore, the study illuminates the advantages of integrating a risk matrix graph within and environment called CYPSA live environment. This integration utilizes data on common vulnerabilities and exposures sourced from the National Vulnerabilities Database (NVD). The inclusion of the risk matrix graph provides heightened clarity on the intricacies of the risk landscape, equipping users with discerning options for informed decision-making.
This study builds upon established analytical methodologies, such as attack tree graphs and a method called Failure Modes, Effects, and Criticality Analysis (FMECA), to comprehensively identify and address potential risks and threats to the system.
In conclusion, the results underscore the potential insights derived from combining these technologies, offering a more effective means to protect critical infrastructure from evolving cyber threats and vulnerabilities. The findings contribute to the growing body of knowledge aimed at bolstering cybersecurity measures for vital systems
Effect of Feedstock Chemistry and Melt Pool Dynamics on Realizing Superior Strength and Surface Quality in Additively Manufactured Ultra-High Strength Steels
No full textAdditive manufacturing (AM) methods generally utilize a layer-by-layer process, fabricating parts from the bottom up which differs from conventional subtractive manufacturing methods. The current focus of AM development involves the production of complex, functional parts. Due to an increase in demand from industries such as aerospace, biomedical and automotive, metal AM has become increasingly popular. Laser powder bed fusion (L-PBF) is widely regarded as the most versatile metal AM process, utilizing high energy density laser to selectively melt powder particles into highly intricate designs.
Laser powder bed fusion (L-PBF) of a newly developed high strength steel known as AF96 has received notable attention due to its unique microstructure and superior mechanical properties. The current study investigates the influence of initial alloy carbon content and decarburization on the mechanical properties of AF96 fabricated via L-PBF. A process parameter development study was first performed to determine optimal processing parameters that result in near defect-free as-printed parts. Test specimens were then fabricated using optimized parameter combinations for mechanical and microstructural characterization. This process was completed for three compositions of AF96 powder containing varying amounts of initial carbon content. Preliminary results show a significant increase in both yield strength and ultimate tensile strength with increasing initial carbon content.
Spatter, an inherent by-product of conventional laser welding, DED, and L-PBF (Laser Powder Bed Fusion), significantly impacts part quality. This research investigates spatter's mechanisms, effects, and in-situ monitoring techniques within the context of L-PBF. Spatter, classified into droplet (hot) and powder (cold) types, originates from vapor-driven entrainment and recoil pressure, impacting surface quality and creating internal flaws. Spatter redeposition during printing leads to recoater impediment, defect formation, and porosity, affecting mechanical properties and surface roughness. In-situ monitoring techniques encompass visible-light high-speed camera imaging, Schlieren video imaging, X-ray video imaging, and infrared video imaging, each revealing various aspects of spatter behavior. A specialized visible-light high-speed camera system for EOS M290 L-PBF, developed for this study, provides insights into spatter ejection behavior. Technical challenges in camera operation and video acquisition were addressed, achieving successful high-speed video imaging capturing spatter movement. Optical microscopy analysis of L-PBF-fabricated AF96-29 cubes reveals varied surface qualities, correlating with spatter distribution in different printability map regions. This study underscores the complexities of spatter behavior, its detrimental effects, and the significance of tailored in-situ monitoring techniques for understanding and mitigating spatter-related issues in L-PBF