Stretchable color-changing fibers are urgently demanded for smart textiles/clothing due to their perfect implantability,permeability of vapor and heat,and flexibility/stretchability.Herein,stretchable electrothermochr...Stretchable color-changing fibers are urgently demanded for smart textiles/clothing due to their perfect implantability,permeability of vapor and heat,and flexibility/stretchability.Herein,stretchable electrothermochromic fibers were fabricated with unconventional stretchable conductive fibers as core layers and thermochromic coatings as shell layers.In the stretchable conductive fibers,hierarchical porous structures with percolative one-dimensional(1 D)conductive networks were constructed through phase inversion of carbon nanotube/polyurethane(CNT/PU)solutions.With the deposition of silver nanoparticles(AgN Ps)on the surface of micro-pores,electrically conductive dual-pathways consisting of0 D AgN Ps and 1 D CNTs were formed to significantly enhance the electric conductivity and thus improve the electrothermal performance of the fibers.More importantly,because of the connective CNTs and AgN Ps,such dual-pathways ensured the electron transport under the stretching state,preventing the sharp decay of conductivity and electrothermal performance.Through the continuous wet-spinning method,the stretchable conductive fibers can be easily obtained with the length up to several meters.At last,stretchable electrothermochromic fibers were prepared with two color-changing modes and implanted into textile perfectly,advancing their applications in wearable display and military adaptive camouflage of smart clothing.展开更多
In this study, we explored the neural mechanism of global topological perception in the human visual system. We showed strong evidence that the retinotectal pathway in the archicortex of the human brain is responsible...In this study, we explored the neural mechanism of global topological perception in the human visual system. We showed strong evidence that the retinotectal pathway in the archicortex of the human brain is responsible for global topological perception, and for modulating the local feature processing in the classical ventral visual pathway. Inspired by this recent cognitive discovery,we developed a novel CogNet architecture to emulate the global-local dichotomy of human visual cognitive mechanisms. The thorough experimental results indicate that the proposed CogNet not only significantly improves image classification accuracies but also effectively addresses the texture bias problem observed in baseline CNN models. We have also conducted mathematical analysis for the generalization gap for general neural networks. Our theoretical derivations suggest that the Hurst parameter, a measure of the curvature of the loss landscape, can closely bind the generalization gap. A larger Hurst parameter corresponds to a better generalization ability. We found that our proposed CogNet achieves a lower test error and attains a larger Hurst parameter,strengthening its superiority over the baseline CNN models further.展开更多
基金supported by the National Natural Science Foundation of China(51672043)Donghua University Distinguished Young Professor Program(LZB2019002)+1 种基金Young Elite Scientists Sponsorship Program by China Association for Science and Technology(2017QNRC001)the Fundamental Research Funds for the Central Universities(CUSF-DH-D-2018006)。
文摘Stretchable color-changing fibers are urgently demanded for smart textiles/clothing due to their perfect implantability,permeability of vapor and heat,and flexibility/stretchability.Herein,stretchable electrothermochromic fibers were fabricated with unconventional stretchable conductive fibers as core layers and thermochromic coatings as shell layers.In the stretchable conductive fibers,hierarchical porous structures with percolative one-dimensional(1 D)conductive networks were constructed through phase inversion of carbon nanotube/polyurethane(CNT/PU)solutions.With the deposition of silver nanoparticles(AgN Ps)on the surface of micro-pores,electrically conductive dual-pathways consisting of0 D AgN Ps and 1 D CNTs were formed to significantly enhance the electric conductivity and thus improve the electrothermal performance of the fibers.More importantly,because of the connective CNTs and AgN Ps,such dual-pathways ensured the electron transport under the stretching state,preventing the sharp decay of conductivity and electrothermal performance.Through the continuous wet-spinning method,the stretchable conductive fibers can be easily obtained with the length up to several meters.At last,stretchable electrothermochromic fibers were prepared with two color-changing modes and implanted into textile perfectly,advancing their applications in wearable display and military adaptive camouflage of smart clothing.
基金supported by the National Key Research and Development Project of China (Grant No. 2020AAA0105600)the National Natural Science Foundation of China (Grant Nos. U21B2048 and 62276208)+1 种基金Shenzhen Key Technical Projects (Grant No. CJGJZD2022051714160501)the Chinese Academy of Sciences (Grant Nos. 2021091 and YSBR-068)。
文摘In this study, we explored the neural mechanism of global topological perception in the human visual system. We showed strong evidence that the retinotectal pathway in the archicortex of the human brain is responsible for global topological perception, and for modulating the local feature processing in the classical ventral visual pathway. Inspired by this recent cognitive discovery,we developed a novel CogNet architecture to emulate the global-local dichotomy of human visual cognitive mechanisms. The thorough experimental results indicate that the proposed CogNet not only significantly improves image classification accuracies but also effectively addresses the texture bias problem observed in baseline CNN models. We have also conducted mathematical analysis for the generalization gap for general neural networks. Our theoretical derivations suggest that the Hurst parameter, a measure of the curvature of the loss landscape, can closely bind the generalization gap. A larger Hurst parameter corresponds to a better generalization ability. We found that our proposed CogNet achieves a lower test error and attains a larger Hurst parameter,strengthening its superiority over the baseline CNN models further.
