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The existing literature primarily examined the impact of unexpected events on the stock market at a single scale, posing the challenge of a lack of multiscale analysis. This paper investigates the impact of COVID-19 on stock markets (China, the U.S., and Hong Kong) from a multiscale perspective using an improved ensemble empirical mode decomposition (EEMD)-based event analysis method. First, the stock price series is decomposed into several independent intrinsic mode functions (IMFs) and a residue. Second, a novel composition method is proposed to reconstruct the IMFs into three components: high-frequency, low-frequency, and long-term trend. We find that the composition of low-frequency and long-term trend components is dominant, which is used to estimate the strength of COVID-19 impact on the stock markets. In addition, the outbreak of COVID-19 significantly increased the intensity of short-term fluctuations in stock prices. Finally, the high-frequency component is analyzed to capture the volatility spillover effects among the three stock markets by the BEKK(Baba-Engle-Kraft-Kroner)-GARCH model. The results show that before the outbreak, there are two-way volatility spillovers between any two of the three markets. After the outbreak, there is no spillover effect between China and Hong Kong, and Hong Kong has no spillover effect on the U.S. However, volatility in the U.S. market still has a significant spillover effect on the other two markets, implying that a mature market can absorb new information more quickly. [ABSTRACT FROM AUTHOR]

Pseudomonas aeruginosa , a versatile bacterium, has dual significance because of its beneficial roles in environmental soil processes and its detrimental effects as a nosocomial pathogen that causes clinical infections. Understanding adaptability to environmental stress is essential. This investigation delves into the complex interplay of two-component system (TCS), specifically ParRS and CprRS, as P. aeruginosa interprets host signals and navigates stress challenges. In this study, through phenotypic and proteomic analyses, the nuanced contributions of ParRS and CprRS to the pathogenesis and resilience mechanisms were elucidated. Furthermore, the indispensable roles of the ParS and CprS extracellular sensor domains in orchestrating signal perception remain unknown. Structural revelations imply a remarkable convergence of TCS sensors in interacting with host peptides, suggesting evolutionary strategies for bacterial adaptation. This pioneering work not only established links between cationic antimicrobial peptide (CAMP) resistance-associated TCSs and virulence modulation in nosocomial bacteria, but also transcended conventional boundaries. These implications extend beyond clinical resistance, permeating into the realm of soil revitalization and environmental guardianship. As it unveils P. aeruginosa intricacies, this study assumes a mantle of guiding strategies to mitigate clinical hazards, harness environmental advantages, and propel sustainable solutions forward. [Display omitted] • ParRS and CprRS regulate the resistance and pathogenesis of P. aeruginosa. • Dynorphin increases adaptive resistance to polymyxins in P. aeruginosa. • ParS and CprS sense dynorphin through the sensor domain. • The ParS SD -like HK sensor domain recognize dynorphin is conserved in bacterial TCS. [ABSTRACT FROM AUTHOR]