A B S T R A C TThis study employed a multi-component Eulerian-Lagrangian approach to model the evaporation and dispersion of cough droplets in quiescent air. The approach is featured with a continuity equation being explicitly solved for water vapor, which allows comprehensively considering the effects of inhomogeneous humidity field on droplets evaporation and movement. The computational fluid dynamics (CFD) computations based on the approach achieved a satisfactory agreement with the theoretical models reported in the literature. The results demonstrated that the evaporation-generated vapor and super-saturated wet air exhaled from the respiratory tracks forms a "vapor plume" in front of the respiratory track opening, which, despite the short life time, significantly impedes the evaporation of the droplets captured in it. The study also revealed that due to the droplet size reduction induced by evaporation, both the number density of airborne droplets and mass concentration of inhalable pathogens remarkably increased, which can result in a higher risk of infection. Parametric studies were finally conducted to evaluate the factors affecting droplet evaporation. Summary: The study demonstrated the importance of considering inhomogeneous humidity field when modelling the evaporation and dispersion of cough droplets. The multi-component Eulerian-Lagrangian model presented in this study provides a comprehensive approach to address different influential factors in a wide parametric range, which will enhance the assessment of the health risks associated with droplet exposure.

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Frequency-difference electrical impedance tomography (fdEIT) reconstructs frequency-dependent changes of a complex impedance distribution. It has a potential application in acute stroke detection because there are significant differences in impedance spectra between stroke lesions and normal brain tissues. However, fdEIT suffers from the influences of electrode-skin contact impedance since contact impedance varies greatly with frequency. When using fdEIT to detect stroke, it is critical to know the degree of measurement errors or image artifacts caused by contact impedance. To our knowledge, no study has systematically investigated the frequency spectral properties of electrode-skin contact impedance on human head and its frequency-dependent effects on fdEIT used in stroke detection within a wide frequency band (10 Hz-1 MHz). In this study, we first measured and analyzed the frequency spectral properties of electrode-skin contact impedance on 47 human subjects’ heads within 10 Hz-1 MHz. Then, we quantified the frequency-dependent effects of contact impedance on fdEIT in stroke detection in terms of the current distribution beneath the electrodes and the contact impedance imbalance between two measuring electrodes. The results showed that the contact impedance at high frequencies (>100 kHz) significantly changed the current distribution beneath the electrode, leading to nonnegligible errors in boundary voltages and artifacts in reconstructed images. The contact impedance imbalance at low frequencies (<1 kHz) also caused significant measurement errors. We conclude that the contact impedance has critical frequency-dependent influences on fdEIT and further studies on reducing such influences are necessary to improve the application of fdEIT in stroke detection.