We analyze the endocytosis process of COVID-19 (coronavirus disease 2019) virus SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) using a mechanical-thermodynamic model. The virus particle is designed to interface with the cell membrane as a hard sphere. The role of cytoplasmic BAR (Bin/Amphiphysin/RVs) proteins is considered in the endocytosis. Interestingly, the Endophilin N-BAR cytoplasmic proteins show resistance in participating endocytosis, whereas F-BAR, Arfaptin BAR, Amphiphysin N-BAR, and PX-BAR proteins participate in endocytosis. The increase in membrane tension, concentrated force between the cell membrane receptor, and spike glycoprotein present on the surface of virus particle promote the endocytosis. Also, the increase in the bending modulus of membrane leads to the two-phase solution of BAR protein concentration on the interior of cell membrane surface. We observe an unstable region of protein concentration, which may help one to retard the endocytosis process and thus the viral infection. Though the present study is focused on SARS-CoV-2, it can be extended to understand any other viral infections, involving endocytosis process.

Coordination of Active Front Steering (AFS) and Direct Yaw Moment Control (DYC) has been widely used for non-autonomous vehicle lateral stability control. Recently, some researchers used it (AFS/DYC) for path-following of autonomous vehicles. However, current controllers are not robust enough with respect to uncertainties and different road conditions to guarantee lateral stability of Autonomous Four In-wheel Motor Drive Electric Vehicles. Thus, a coordinated control is proposed to address this issue. In this paper, a two-layer hierarchical control strategy is utilized. In the upper-layer, a self-tunable super-twisting sliding mode control is utilized to deal with parametric uncertainties, and a Model Predictive Control (MPC) is used in order to allocate the control action to each AFS and DYC. Parametric uncertainties of tires' cornering stiffness, vehicle mass and moment of inertia are considered. Simulations with different road conditions for path-following scenario have been conducted in MATLAB/Simulink. An autonomous vehicle equipped with Four In-wheel Motor and two degrees of freedom vehicle dynamics model is used in this study. In the end, the performance of the proposed controller is compared with the MPC controller. Simulation results reveal that the proposed controller provides better path-following in comparison with the MPC controller.

The deformability of cells has been used as a biomarker to detect circulating tumor cells (CTCs) from patient blood sample using microfluidic devices with microscale pores. Successful separations of CTCs from a blood sample requires careful design of the micropore size and applied pressure. This paper presented a parametric study of cell squeezing through micropores with different size and pressure. Different membrane compressibility modulus was used to characterize the deformability of varying cancer cells. Nucleus effect was also considered. It shows that the cell translocation time though the micropore increases with cell membrane compressibility modulus and nucleus stiffness. Particularly, it increases exponentially as the micropore diameter or pressure decreases. The simulation results such as the cell squeezing shape and translocation time agree well with experimental observations. The simulation results suggest that special care should be taken in applying Laplace-Young equation (LYE) to microfluidic design due to the nonuniform stress distribution and membrane bending resistance.