Low power microwave can effectively deactivate influenza type A virus through the nonthermal structure-resonant energy transfer effect, at a frequency matching the confined-acoustic dipolar mode frequency of the virus. Currently, aerosol is considered the major route for SARS-CoV-2 transmission. For the potential microwave-based sterilization, the microwave-resonant frequency of SARS-CoV-2 must be unraveled. Here we report a microwave absorption spectroscopy study of the SARS-CoV-2 and HCoV-229E viruses through devising a coplanar-waveguide-based sensor. Noticeable microwave absorption can be observed, while we identified the resonant frequencies of the 1st and 2nd dipolar modes of SARS-CoV-2 virus as 4 and 7.5 GHz respectively. We further found that the resonant frequencies are invariant to the virus titer, and we also studied the microwave absorption of HCoV-229E in weak acidity medium to simulate the common pH value in fluid secretion. Our results suggest the possible radiation frequency for the recently proposed microwave sterilization devices to inactivate SARS-CoV-2 virus through a nonthermal mechanism so as to control the disease transmission in the post-pandemic era.

An approach to apply the fractal concept to estimate hydrologic response is proposed in this paper by matching suitable self-similar networks (SSNs) to a specific watershed, and modeling the runoff with a width-function based geomorphologic instantaneous unit hydrograph (WF-GIUH). In order to work out the identification between a specific basin and SSNs that are generated by an interior generator cooperating with an exterior generator, a generalized width function is derived. Subsequently, cumulative width functions on the basis of the derived function, as well as the informational entropies are used as criteria to decide the best patterns of the two cooperating generators for the specific watershed. The WF-GIUH model is then applied to calculate the runoff of this watershed as an outcome of the estimation. To assess the adaptability of the estimation model, San-Hsia watershed of Northern Taiwan is selected as a study area, where the analytical results of the outflow estimation indicate that the fractal algorithm has been implemented successfully for the calculation of hydrologic responses.

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