Facilitating Effects of Reductive Soil Disinfestation on Soil Health and Physiological Properties of Panax ginseng.

Chemical soil fumigation (CSF) and reductive soil disinfestation (RSD) have been proven to be effective agricultural strategies to improve soil quality, restructure microbial communities, and promote plant growth in soil degradation remediation. However, it is still unclear how RSD and CSF ensure soil and plant health by altering fungal communities. Field experiments were conducted to investigate the effects of CSF with chloropicrin, and RSD with animal feces on soil properties, fungal communities and functional composition, and plant physiological characteristics were evaluated. Results showed that RSD and CSF treatment improved soil properties, restructured fungal community composition and structure, enhanced fungal interactions and functions, and facilitated plant growth. There was a significant increase in OM, AN, and AP contents in the soil with both CSF and RSD treatments compared to CK. Meanwhile, compared with CK and CSF, RSD treatment significantly increased biocontrol Chaetomium relative abundance while reducing pathogenic Neonectria relative abundance, indicating that RSD has strong inhibition potential. Furthermore, the microbial network of RSD treatment was more complex and interconnected, and the functions of plant pathogens, and animal pathogen were decreased. Importantly, RSD treatment significantly increased plant SOD, CAT, POD activity, SP, Ca, Zn content, and decreased MDA, ABA, Mg, K, and Fe content. In summary, RSD treatment is more effective than CSF treatment, by stimulating the proliferation of probiotic communities to further enhance soil health and plant disease resistance.

A Novel V2V Cooperative Collision Warning System Using UWB/DR for Intelligent Vehicles.

The collision warning system (CWS) plays an essential role in vehicle active safety. However, traditional distance-measuring solutions, e.g., millimeter-wave radars, ultrasonic radars, and lidars, fail to reflect vehicles' relative attitude and motion trends. In this paper, we proposed a vehicle-to-vehicle (V2V) cooperative collision warning system (CCWS) consisting of an ultra-wideband (UWB) relative positioning/directing module and a dead reckoning (DR) module with wheel-speed sensors. Each vehicle has four UWB modules on the body corners and two wheel-speed sensors on the rear wheels in the presented configuration. An over-constrained localization method is proposed to calculate the relative position and orientation with the UWB data more accurately. Vehicle velocities and yaw rates are measured by wheel-speed sensors. An extended Kalman filter (EKF) is applied based on the relative kinematic model to combine the UWB and DR data. Finally, the time to collision (TTC) is estimated based on the predicted vehicle collision position. Furthermore, through UWB signals, vehicles can simultaneously communicate with each other and share information, e.g., velocity, yaw rate, which brings the potential for enhanced real-time performance. Simulation and experimental results show that the proposed method significantly improves the positioning, directing, and velocity estimating accuracy, and the proposed system can efficiently provide collision warning.