Dielectric elastomer actuators (DEAs) artificial muscle is a typical interdisciplinary research category, which has developed by leaps and bounds in the past 20 years, showing great application prospects in various fi...Dielectric elastomer actuators (DEAs) artificial muscle is a typical interdisciplinary research category, which has developed by leaps and bounds in the past 20 years, showing great application prospects in various fields. Upon external electrical stimulation, dielectric elastomers (DEs) display large deformation, high energy density and fast response, affording a promising material candidate for soft robotics. Herein, the working mechanisms, commonly used materials as well as the concepts for improving the performance of DEA materials are introduced. Various DEA driven soft robots, including soft grippers, bioinspired artificial arms, crawling/walking/underwater/flying/jumping soft robots and tunable lenses, are then described in detail. Finally, the main challenges of DEA driven soft robots are summarized, and some perspectives for promoting the practical application of DEAs are also proposed.展开更多
Elastic or plastic bendable organic crystals have attracted increasing attention in the field of crystal engineering.For the application of flexible materials,the applicable temperature range can not be ignored.Howeve...Elastic or plastic bendable organic crystals have attracted increasing attention in the field of crystal engineering.For the application of flexible materials,the applicable temperature range can not be ignored.However,studies on the flexible organic crystals reported so far have not involved the effect of temperature on the mechanical properties of these materials.Here,organic crystals of 9,10-bis(phenylethynyl)anthracene with phase-dependent mechanical properties over wide temperature ranges are reported.展开更多
Medical image segmentation is of critical importance in the domain of contemporary medical imaging.However,U-Net and its variants exhibit limitations in capturing complex nonlinear patterns and global contextual infor...Medical image segmentation is of critical importance in the domain of contemporary medical imaging.However,U-Net and its variants exhibit limitations in capturing complex nonlinear patterns and global contextual information.Although the subsequent U-KAN model enhances nonlinear representation capabilities,it still faces challenges such as gradient vanishing during deep network training and spatial detail loss during feature downsampling,resulting in insufficient segmentation accuracy for edge structures and minute lesions.To address these challenges,this paper proposes the RE-UKAN model,which innovatively improves upon U-KAN.Firstly,a residual network is introduced into the encoder to effectively mitigate gradient vanishing through cross-layer identity mappings,thus enhancing modelling capabilities for complex pathological structures.Secondly,Efficient Local Attention(ELA)is integrated to suppress spatial detail loss during downsampling,thereby improving the perception of edge structures and minute lesions.Experimental results on four public datasets demonstrate that RE-UKAN outperforms existing medical image segmentation methods across multiple evaluation metrics,with particularly outstanding performance on the TN-SCUI 2020 dataset,achieving IoU of 88.18%and Dice of 93.57%.Compared to the baseline model,it achieves improvements of 3.05%and 1.72%,respectively.These results fully demonstrate RE-UKAN’s superior detail retention capability and boundary recognition accuracy in complex medical image segmentation tasks,providing a reliable solution for clinical precision segmentation.展开更多
基金support from the National Natural Science Foundation of China(Grant No.51525301)the Talent Cultivation of State Key Laboratory of Organic-Inorganic Composites(No.OIC-D2021002).
文摘Dielectric elastomer actuators (DEAs) artificial muscle is a typical interdisciplinary research category, which has developed by leaps and bounds in the past 20 years, showing great application prospects in various fields. Upon external electrical stimulation, dielectric elastomers (DEs) display large deformation, high energy density and fast response, affording a promising material candidate for soft robotics. Herein, the working mechanisms, commonly used materials as well as the concepts for improving the performance of DEA materials are introduced. Various DEA driven soft robots, including soft grippers, bioinspired artificial arms, crawling/walking/underwater/flying/jumping soft robots and tunable lenses, are then described in detail. Finally, the main challenges of DEA driven soft robots are summarized, and some perspectives for promoting the practical application of DEAs are also proposed.
基金supported by the National Natural Science Foundation of China(no.51773077).
文摘Elastic or plastic bendable organic crystals have attracted increasing attention in the field of crystal engineering.For the application of flexible materials,the applicable temperature range can not be ignored.However,studies on the flexible organic crystals reported so far have not involved the effect of temperature on the mechanical properties of these materials.Here,organic crystals of 9,10-bis(phenylethynyl)anthracene with phase-dependent mechanical properties over wide temperature ranges are reported.
文摘Medical image segmentation is of critical importance in the domain of contemporary medical imaging.However,U-Net and its variants exhibit limitations in capturing complex nonlinear patterns and global contextual information.Although the subsequent U-KAN model enhances nonlinear representation capabilities,it still faces challenges such as gradient vanishing during deep network training and spatial detail loss during feature downsampling,resulting in insufficient segmentation accuracy for edge structures and minute lesions.To address these challenges,this paper proposes the RE-UKAN model,which innovatively improves upon U-KAN.Firstly,a residual network is introduced into the encoder to effectively mitigate gradient vanishing through cross-layer identity mappings,thus enhancing modelling capabilities for complex pathological structures.Secondly,Efficient Local Attention(ELA)is integrated to suppress spatial detail loss during downsampling,thereby improving the perception of edge structures and minute lesions.Experimental results on four public datasets demonstrate that RE-UKAN outperforms existing medical image segmentation methods across multiple evaluation metrics,with particularly outstanding performance on the TN-SCUI 2020 dataset,achieving IoU of 88.18%and Dice of 93.57%.Compared to the baseline model,it achieves improvements of 3.05%and 1.72%,respectively.These results fully demonstrate RE-UKAN’s superior detail retention capability and boundary recognition accuracy in complex medical image segmentation tasks,providing a reliable solution for clinical precision segmentation.
