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Aerosol particle transport and deposition in vertical and horizontal turbulent duct flows in the presence of different gravity directions are studied. The instantaneous fluid velocity field is generated by the direct numerical simulation of the Navier-Stokes equation via a pseudospectral method. A particle equation of motion including Stokes drag, Brownian diffusion, lift and gravitational forces is used for trajectory analysis. Ensembles of 8192 particle paths are evaluated, compiled, and statistically analysed. The results show that the wall coherent structure plays an important role in the particle deposition process. The simulated deposition velocities under various conditions are compared with the available experimental data and the sublayer model predictions. It is shown that the shear velocity, density ratio, the shear-induced lift force and the flow direction affect the particle deposition rate. The results for vertical ducts show that the particle deposition velocity varies with the direction of gravity, and the effect becomes more significant when the shear velocity is small. For horizontal ducts, the gravitational sedimentation increases the particle deposition rate on the lower wall.

a b s t r a c tIn this paper, we study the interplay between the epidemic spreading and the diffusion of awareness in multiplex networks. In the model, an infectious disease can spread in one network representing the paths of epidemic spreading (contact network), leading to the diffusion of awareness in the other network (information network), and then the diffusion of awareness will cause individuals to take social distances, which in turn affects the epidemic spreading. As for the diffusion of awareness, we assume that, on the one hand, individuals can be informed by other aware neighbors in information network, on the other hand, the susceptible individuals can be self-awareness induced by the infected neighbors in the contact networks (local information) or mass media (global information). Through Markov chain approach and numerical computations, we find that the density of infected individuals and the epidemic threshold can be affected by the structures of the two networks and the effective transmission rate of the awareness. However, we prove that though the introduction of the self-awareness can lower the density of infection, which cannot increase the epidemic threshold no matter of the local information or global information. Our finding is remarkably different to many previous results on single-layer network: local information based behavioral response can alter the epidemic threshold. Furthermore, our results indicate that the nodes with more neighbors (hub nodes) in information networks are easier to be informed, as a result, their risk of infection in contact networks can be effectively reduced.

h i g h l i g h t s• A new SIS network model obtained by introducing an information variable is proposed. • The diseases can be controlled through high efficiency of implementation.• The introduced parameters have significant impact on the final prevalence density.• The results may suggest effective control strategies incorporating media coverage. a b s t r a c t An SIS network model incorporating the influence of media coverage on transmission rate is formulated and analyzed. We calculate the basic reproduction number R 0 by utilizing the local stability of the disease-free equilibrium. Our results show that the disease-free equilibrium is globally asymptotically stable and that the disease dies out if R 0 is below 1; otherwise, the disease will persist and converge to a unique positive stationary state. This result may suggest effective control strategies to prevent disease through media coverage and education activities in finite-size scale-free networks. Numerical simulations are also performed to illustrate our results and to give more insights into the dynamical process.