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In this paper, a mathematical model to study the impact of Twitter in controlling infectious disease is proposed. The model includes the dynamics of “tweets” which may enhance awareness of the disease and cause behavioral changes among the public, thus reducing the transmission of the disease. Furthermore, the model is improved by introducing a time delay between the outbreak of disease and the release of Twitter messages. The basic reproduction number and the conditions for the stability of the equilibria are derived. It is shown that the system undergoes Hopf bifurcation when time delay is increased. Finally, numerical simulations are given to verify the analytical results. [ABSTRACT FROM AUTHOR]

In the article, an iterative reconstruction algorithm based on total variation minimization and POCS optimization for non-Cartesian K-space data is proposed. The proposed algorithm interpolates non-Cartesian data onto a 2D Cartesian grid using gridding method first, and then during the iterative process of total variation minimization, the frequency values on grid points near the measured data are replaced with the interpolated ones according to POCS. The experiments on simulated and real data show that the proposed method can reconstruct image more accurately and rapidly than constrained total variation minimization method.