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Co/biphenyldithiol (BPDT)/Co nanolayer sandwiches are synthesized by metal sputter deposition and molecular sublimation. These results indicate molecular-nanolayer-induced effects on the morphology and chemistry, of interest for hybrid nanolaminates. 

Abstract One of the common mechanisms to trigger plant innate immunity is recognition of pathogen avirulence gene products directly by products of major resistance (R) genes in a gene for gene manner. In the USA, theRgenes,Pik-s, PiKh/m, andPi-ta, Pi-39(t), andPtrgenes have been effectively deployed to prevent the infections ofM. oryzaeraces, IB49, and IC17 for some time.Pi-9is only recently being deployed to provide overlapped and complimentary resistance toMagnaporthe oryzaeraces IB49, IC17 and IE1k in the USA. Pi-ta, Pi-39(t), Pi9 are major nuclear binding site-leucine rich (NLR) proteins, and Ptr is an atypical R protein with 4 armadillo repeats. AlphaFold is an artificial intelligence system that predicts a protein 3D structure from its amino acid sequence. Here we report genome sequence analyses of the effectors and avirulence (AVR) genes,AVR-PitaandAVR-Pik, andAVR-Pi9, in 3 differentialM. oryzaeraces. Using AlphaFold 2 and 3 we find strong evidence of direct interactions of products of resistance genesPi-taandPikwithM. oryzaeavirulence (AVR) genes,AVR-PitaandAVR-Pikrespectively. We also found that AVR-Pita interacts with Pi-39(t) and Ptr, and Pi9 interacts with both AVR-Pi9 and AVR-Pik. Validation of direct interactions of two pairs of R and AVR proteins supported a direct interaction mechanism of plant innate immunity. Detecting interaction of both Ptr and Pi39(t) with AVR-Pita, and Pi-9 with both AVR-Pi9 and AVR-Pik, revealed a new insight into recognition of pathogen signaling molecules by these host R genes in triggering plant innate immunity. 

Edge computing has emerged as the dominant communication technology connecting IoT and cloud, offering reduced latency and harnessing the potential of edge devices. However, its widespread adoption has also introduced various security vulnerabilities, similar to any nascent technology. One notable threat is the denial of service (DoS) attack, including its distributed form, the distributed denial of service (DDoS) attack, which is the primary focus of this research. This paper aims to explore the impact of different types of DoS and DDoS attacks on edge computing layers by examining the vulnerabilities associated with various edge peripherals. Addition ally, existing detection and prevention mechanisms are investigated to address these weaknesses. Furthermore, a theoretical architecture is proposed to mitigate distributed denial of service attacks targeting edge systems. By comprehensively analyzing and addressing the security concerns related to DoS and DDoS attacks in edge computing, this research aims to contribute to the development of robust and secure edge computing systems. 

In this work, we present the design and plan of Quantum machine learning (QML) course in a computer science (CS) University program at senior undergraduate level / first year graduate level. Based on our survey, there is a lack of detailed design and assessment plan for the delivery of QML course. In this paper we have presented the QML course design with week by week details of QML concepts and hands on activities that are covered in the course. We also present how this QML course can be assessed from CS program learning outcomes perspective.