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https://www.selleckchem.com/products/poly-l-lysine.html in (H2O2 + AgNO3)-treated seedlings, without significantly compromising the total levels of glyceollins, compared to (ROS + R)-treated seedlings. The most abundant prenylated isoflavone induced was 6-prenyl daidzein, which constituted 60% of the total isoflavones. The prenylated coumestan, phaseol, was also induced in the (H2O2 + AgNO3)-treated and microbially elicited seedlings. Based on previously developed quantitative structure-activity relationship (QSAR) models, 6-prenyl daidzein and phaseol were predicted to be promising antibacterials. Overall, we show that treatment with H2O2 and AgNO3 prior to microbial elicitation leads to the production of promising antibacterial isoflavonoids from different subclasses. Extracts rich in prenylated isoflavonoids may potentially be applied as natural antimicrobial agents.The threat assessment process is a crucial part of intelligent vehicles (IVs) for evaluating the levels of criticality and taking possible measures to avoid the collision, especially for the collision avoidance systems (CAS). In this study, a novel threat assessment framework based on the driver's evasive behavior, namely the CPIC, is proposed, which integrates the crash probability (CP) and inevitable crash (IC) state to be widely used by different CAS in different scenarios. In the first step of the CPIC framework, the detailed evasive driver behavior models (E-DBMs) in the form of probability density functions (PDFs) were introduced to generate more realistic collision-avoidance trajectories. Two techniques for sampling these trajectories, namely the Markov Chain Monte Carlo (MCMC) and adaptive Gaussian mixture framework (GMM) methods, were utilized to ensure the samples were from the area of high probability density in the E-DBMs. The CP value could be derived by considering multiple collision-avoidance trajectories. To confirm the IC state in step 2, the CPIC framework employed the driving limit-

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