Wheat powdery mildew caused by Blumeria graminis f.sp.tritici(Bgt)is an important disease worldwide.Detection of latent infection of leaves by the pathogen in late autumn is valuable for estimating the inoculum potent...Wheat powdery mildew caused by Blumeria graminis f.sp.tritici(Bgt)is an important disease worldwide.Detection of latent infection of leaves by the pathogen in late autumn is valuable for estimating the inoculum potential to assess disease risks in the spring.We developed a new tool for rapid detection and quantification of latent infection of seedlings by the pathogen.The method was based on recombinase polymerase amplification(RPA)coupled with an end-point detection via lateral flow device(LFD).The limit of detection is 100 agμL^(-1)of Bgt DNA,without noticeable interference from either other common wheat pathogens or wheat material(Triticum aestivum).It was evaluated on wheat seedlings for this accuracy and sensitivity in detecting latent infection of Bgt.We further extended this RPALFD assay to estimate the level of latent infection by Bgt based on imaging analysis.There was a strong correlation between the image-based and real-time PCR assay estimates of Bgt DNA.The present results suggested that this new tool can provide rapid and accurate quantification of Bgt in latently infected leaves and can be further development as an on-site monitoring tool.展开更多
This paper proposes a novel approach for physical human-robot interactions(pHRI), where a robot provides guidance forces to a user based on the user performance. This framework tunes the forces in regards to behavior ...This paper proposes a novel approach for physical human-robot interactions(pHRI), where a robot provides guidance forces to a user based on the user performance. This framework tunes the forces in regards to behavior of each user in coping with different tasks, where lower performance results in higher intervention from the robot. This personalized physical human-robot interaction(p2HRI) method incorporates adaptive modeling of the interaction between the human and the robot as well as learning from demonstration(LfD) techniques to adapt to the users' performance. This approach is based on model predictive control where the system optimizes the rendered forces by predicting the performance of the user. Moreover, continuous learning of the user behavior is added so that the models and personalized considerations are updated based on the change of user performance over time. Applying this framework to a field such as haptic guidance for skill improvement, allows a more personalized learning experience where the interaction between the robot as the intelligent tutor and the student as the user,is better adjusted based on the skill level of the individual and their gradual improvement. The results suggest that the precision of the model of the interaction is improved using this proposed method,and the addition of the considered personalized factors to a more adaptive strategy for rendering of guidance forces.展开更多
基金supported by the funding from the National Natural Science Foundation of China(32072359)。
文摘Wheat powdery mildew caused by Blumeria graminis f.sp.tritici(Bgt)is an important disease worldwide.Detection of latent infection of leaves by the pathogen in late autumn is valuable for estimating the inoculum potential to assess disease risks in the spring.We developed a new tool for rapid detection and quantification of latent infection of seedlings by the pathogen.The method was based on recombinase polymerase amplification(RPA)coupled with an end-point detection via lateral flow device(LFD).The limit of detection is 100 agμL^(-1)of Bgt DNA,without noticeable interference from either other common wheat pathogens or wheat material(Triticum aestivum).It was evaluated on wheat seedlings for this accuracy and sensitivity in detecting latent infection of Bgt.We further extended this RPALFD assay to estimate the level of latent infection by Bgt based on imaging analysis.There was a strong correlation between the image-based and real-time PCR assay estimates of Bgt DNA.The present results suggested that this new tool can provide rapid and accurate quantification of Bgt in latently infected leaves and can be further development as an on-site monitoring tool.
文摘This paper proposes a novel approach for physical human-robot interactions(pHRI), where a robot provides guidance forces to a user based on the user performance. This framework tunes the forces in regards to behavior of each user in coping with different tasks, where lower performance results in higher intervention from the robot. This personalized physical human-robot interaction(p2HRI) method incorporates adaptive modeling of the interaction between the human and the robot as well as learning from demonstration(LfD) techniques to adapt to the users' performance. This approach is based on model predictive control where the system optimizes the rendered forces by predicting the performance of the user. Moreover, continuous learning of the user behavior is added so that the models and personalized considerations are updated based on the change of user performance over time. Applying this framework to a field such as haptic guidance for skill improvement, allows a more personalized learning experience where the interaction between the robot as the intelligent tutor and the student as the user,is better adjusted based on the skill level of the individual and their gradual improvement. The results suggest that the precision of the model of the interaction is improved using this proposed method,and the addition of the considered personalized factors to a more adaptive strategy for rendering of guidance forces.
