Coordinated Formation Control for Intelligent and Connected Vehicles in Multiple Traffic Scenarios

In this paper, a unified multi-vehicle formation control framework for Intelligent and Connected Vehicles (ICVs) that can apply to multiple traffic scenarios is proposed. In the one-dimensional scenario, different formation geometries are analyzed and the interlaced structure is mathematically modelized to improve driving safety while making full use of the lane capacity. The assignment problem for vehicles and target positions is solved using Hungarian Algorithm to improve the flexibility of the method in multiple scenarios. In the two-dimensional scenario, an improved virtual platoon method is proposed to transfer the complex two-dimensional passing problem to the one-dimensional formation control problem based on the idea of rotation projection. Besides, the vehicle regrouping method is proposed to connect the two scenarios. Simulation results prove that the proposed multi-vehicle formation control framework can apply to multiple typical scenarios and have better performance than existing methods

Improved hatchability and efficient protection after in ovo vaccination with live-attenuated H7N2 and H9N2 avian influenza viruses

Mass in ovo vaccination with live attenuated viruses is widely used in the poultry industry to protect against various infectious diseases. The worldwide outbreaks of low pathogenic and highly pathogenic avian influenza highlight the pressing need for the development of similar mass vaccination strategies against avian influenza viruses. We have previously shown that a genetically modified live attenuated avian influenza virus (LAIV) was amenable for in ovo vaccination and provided optimal protection against H5 HPAI viruses. However, in ovo vaccination against other subtypes resulted in poor hatchability and, therefore, seemed impractical. In this study, we modified the H7 and H9 hemagglutinin (HA) proteins by substituting the amino acids at the cleavage site for those found in the H6 HA subtype. We found that with this modification, a single dose in ovo vaccination of 18-day old eggs provided complete protection against homologous challenge with low pathogenic virus in ≥70% of chickens at 2 or 6 weeks post-hatching. Further, inoculation of 19-day old egg embryos with 106 EID50 of LAIVs improved hatchability to ≥90% (equivalent to unvaccinated controls) with similar levels of protection. Our findings indicate that the strategy of modifying the HA cleavage site combined with the LAIV backbone could be used for in ovo vaccination against avian influenza. Importantly, with protection conferred as early as 2 weeks post-hatching, with this strategy birds would be protected prior to or at the time of delivery to a farm or commercial operation

Resistance Assessment for Oxathiapiprolin in Phytophthora capsici and the Detection of a Point Mutation (G769W) in PcORP1 that Confers Resistance

The potential for oxathiapiprolin resistance in Phytophthora capsici was evaluated. The baseline sensitivities of 175 isolates to oxathiapiprolin were initially determinated and found to conform to a unimodal curve with a mean EC50 value of 5.61×10-4 μg/ml. Twelve stable oxathiapiprolin-resistant mutants were generated by fungicide adaption in two sensitive isolates, LP3 and HNJZ10. The fitness of the LP3-mutants was found to be similar to or better than that of the parental isolate LP3, while the HNJZ10-mutants were found to have lost the capacity to produce zoospores. Taken together these results suggest that the risk of P. capsici developing resistance to oxathiapiprolin is moderate. Comparison of the PcORP1 genes in the LP3-mutants and wild-type parental isolate, which encode the target protein of oxathiapiprolin, revealed that a heterozygous mutation caused the amino acid substitution G769W. Transformation and expression of the mutated PcORP1-769W allele in the sensitive wild-type isolate BYA5 confirmed that the mutation in PcORP1 was responsible for the observed oxathiapiprolin resistance. Finally diagnostic tests including As-PCR and CAPs were developed to detect the oxathiapiprolin resistance resulting from the G769W point mutation in field populations of P. capsici

Rethinking IoU-based Optimization for Single-stage 3D Object Detection

Since Intersection-over-Union (IoU) based optimization maintains the consistency of the final IoU prediction metric and losses, it has been widely used in both regression and classification branches of single-stage 2D object detectors. Recently, several 3D object detection methods adopt IoU-based optimization and directly replace the 2D IoU with 3D IoU. However, such a direct computation in 3D is very costly due to the complex implementation and inefficient backward operations. Moreover, 3D IoU-based optimization is sub-optimal as it is sensitive to rotation and thus can cause training instability and detection performance deterioration. In this paper, we propose a novel Rotation-Decoupled IoU (RDIoU) method that can mitigate the rotation-sensitivity issue, and produce more efficient optimization objectives compared with 3D IoU during the training stage. Specifically, our RDIoU simplifies the complex interactions of regression parameters by decoupling the rotation variable as an independent term, yet preserving the geometry of 3D IoU. By incorporating RDIoU into both the regression and classification branches, the network is encouraged to learn more precise bounding boxes and concurrently overcome the misalignment issue between classification and regression. Extensive experiments on the benchmark KITTI and Waymo Open Dataset validate that our RDIoU method can bring substantial improvement for the single-stage 3D object detection.Comment: Accepted by ECCV2022. The code is available at https://github.com/hlsheng1/RDIo