Viral contamination of drinking water due to fecal contamination is difficult to detect and treat effectively, leading to frequent outbreaks worldwide. The purpose of this paper is to report on the molecular mechanism for unprecedented high virus removal from a practical sand filter. Sand filters functionalized using a water extract of Moringa oleifera (MO) seeds, functionalized sand (f-sand) filters, achieved a ∼7 log10 virus removal. These tests were conducted with MS2 bacteriophage, a recognized surrogate for pathogenic norovirus and rotavirus. We studied the molecular mechanism of this high removal since it can have important implications for sand filtration, the most common water treatment technology worldwide. Our data reveal that the virus removal activity of f-sand is due to the presence of a chitin-binding protein, M. oleifera chitin-binding protein (MoCBP) on f-sand. Standard column experiments were supported by proteomic analysis and molecular docking simulations. Our simulations show that MoCBP binds preferentially to MS2 capsid proteins demonstrating that specific molecular interactions are responsible for enhanced virus removal. In addition, we simplified the process of making f-sand and evinced how it could be regenerated using saline water. At present, no definitive solution exists for the challenge of treating fecally contaminated drinking and irrigation water for viruses without using technologies that demand high energy or chemical consumption. We propose functionalized sand (f-sand) filters as a highly effective, energy-efficient, and practical technology for virus removal applicable to both developing and developed countries.

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Model predictive control is one of the main methods used in path tracking for autonomous vehicles. To improve the path tracking performance of the vehicle, a path tracking method based on model predictive control with variable predictive horizon is proposed in this paper. Based on the designed model predictive controller for path tracking, the response analysis of path tracking control system under the different predictive horizons is carried out to clarify the influence of predictive horizon on path tracking accuracy, driving comfort and real-time of the control algorithm. Then, taking the lateral offset, the steering frequency and the real-time of the control algorithm as comprehensive performance indexes, the particle swarm optimization algorithm is designed to realize the adaptive optimization for the predictive horizon. The effectiveness of the proposed method is evaluated via numerical simulation based on Simulink/CarSim and hardware-in-the-loop experiment on an autonomous driving simulator. The obtained results show that the optimized predictive horizon can adapt to the different driving environment, and the proposed path tracking method has good comprehensive performance in terms of path tracking accuracy of the vehicle, driving comfort and real-time.

The vehicle semi-active suspension with Magneto-Rheological Damper (MRD) has been a hot research topic of this decade, featuring the challenging task of the robust control with actuator time delay considerations. In this study, a delay dependent sliding mode variable structure control, based on the Linear Matrix Inequality (LMI), is proposed to suppress the vibration of the Magneto-Rheological Semi-Active Suspension (MRSS) control system. In accordance with the nonlinear characteristics of MRD, a dynamic model of automotive semi-active suspension system, considering time delay, is established. By defining a parameter-dependent Lyapunov switching functional, the conditions for asymptotic stability of closed-loop time delay system are derived, while the sliding mode variable structure control with reduced conservatism is designed. According to the method of LMI, the asymptotic stability problem of sliding mode is transformed into a feasibility problem, which can be solved by the solver 'feasp' in LMI toolbox. In addition, the calculation of the critical time delay of MRSS is expressed as a generalized eigenvalue optimization problem. For comparison purposes, three representative controllers, including a conventional sliding mode controller, a delay dependent controller, and a smith compensation, are studied. Simulation and real vehicle testing on bump and random road responses show that, the designed delay dependent controller can ensure the stability of the suspension system, weaken the influence of time delay on the control performance and effectively improve the ride comfort of the vehicle.INDEX TERMS Semi-active suspension, magneto-rheological damper, time delay, sliding mode variable structure control, linear matrix inequality.