A widespread assertion has existed for a long time, believing the external field of an infinitely long solenoid should be zero, but it is proofed to be wrong in this work. The components of magnetic flux density of cu...A widespread assertion has existed for a long time, believing the external field of an infinitely long solenoid should be zero, but it is proofed to be wrong in this work. The components of magnetic flux density of current-carrying, closely wound cylindrical solenoids are calculated. At a distant field point, the external field definitely has a nonzero component, being equal to that of a straight wire of equal length. Since this equivalence is length-independent, it still holds true for ideal solenoids having infinite length. Hence the incorrect and still spreading inference about long solenoids should be rectified. Furthermore, theoretical and experimental discussions involving solenoids should be reviewed again carefully.展开更多
Artificial neural networks have shown great proficiency in transforming low-resolution microscopic images into high-resolution images.However,training data remains a challenge,as large-scale open-source databases of m...Artificial neural networks have shown great proficiency in transforming low-resolution microscopic images into high-resolution images.However,training data remains a challenge,as large-scale open-source databases of microscopic images are rare,particularly 3D data.Moreover,the long training times and the need for expensive computational resources have become a burden to the research community.We introduced a deep-learning-based self-supervised volumetric imaging approach,which we termed“Self-Vision.”The self-supervised approach requires no training data,apart from the input image itself.The lightweight network takes just minutes to train and has demonstrated resolution-enhancing power on par with or better than that of a number of recent microscopybased models.Moreover,the high throughput power of the network enables large image inference with less postprocessing,facilitating a large field-of-view(2.45 mm×2.45 mm)using a home-built two-photon microscopy system.Self-Vision can recover images from fourfold undersampled inputs in the lateral and axial dimensions,dramatically reducing the acquisition time.Self-Vision facilitates the use of a deep neural network for 3D microscopy imaging,easing the demanding process of image acquisition and network training for current resolutionenhancing networks.展开更多
A wearable micro-sensor motion capture system with 16 IMUs and an error-compensatory complementary filter algorithm for real-time motion estimation has been developed to acquire accurate 3D orientation and displacemen...A wearable micro-sensor motion capture system with 16 IMUs and an error-compensatory complementary filter algorithm for real-time motion estimation has been developed to acquire accurate 3D orientation and displacement in real life activities.In the proposed filter algorithm,the gyroscope bias error,orientation error and magnetic disturbance error are estimated and compensated,significantly reducing the orientation estimation error due to sensor noise and drift.Displacement estimation,especially for activities such as jumping,has been the challenge in micro-sensor motion capture.An adaptive gait phase detection algorithm has been developed to accommodate accurate displacement estimation in different types of activities.The performance of this system is benchmarked with respect to the results of VICON optical capture system.The experimental results have demonstrated effectiveness of the system in daily activities tracking,with estimation error 0.16 ± 0.06m for normal walking and 0.13 ± 0.11m for jumping motions.展开更多
文摘A widespread assertion has existed for a long time, believing the external field of an infinitely long solenoid should be zero, but it is proofed to be wrong in this work. The components of magnetic flux density of current-carrying, closely wound cylindrical solenoids are calculated. At a distant field point, the external field definitely has a nonzero component, being equal to that of a straight wire of equal length. Since this equivalence is length-independent, it still holds true for ideal solenoids having infinite length. Hence the incorrect and still spreading inference about long solenoids should be rectified. Furthermore, theoretical and experimental discussions involving solenoids should be reviewed again carefully.
基金National Natural Science Foundation of China(62105353,81927803,82071972,91959121,92159104)Natural Science Foundation of Guangdong Province(2019A1515011746,2020B121201010,2021A1515012022)+1 种基金Scientific Instrument Innovation Team of Chinese Academy of Sciences(GJJSTD20180002)Shenzhen Basic Research Program(RCJC20200714114433058,RCYX20210609104445093,ZDSY20130401165820357)。
文摘Artificial neural networks have shown great proficiency in transforming low-resolution microscopic images into high-resolution images.However,training data remains a challenge,as large-scale open-source databases of microscopic images are rare,particularly 3D data.Moreover,the long training times and the need for expensive computational resources have become a burden to the research community.We introduced a deep-learning-based self-supervised volumetric imaging approach,which we termed“Self-Vision.”The self-supervised approach requires no training data,apart from the input image itself.The lightweight network takes just minutes to train and has demonstrated resolution-enhancing power on par with or better than that of a number of recent microscopybased models.Moreover,the high throughput power of the network enables large image inference with less postprocessing,facilitating a large field-of-view(2.45 mm×2.45 mm)using a home-built two-photon microscopy system.Self-Vision can recover images from fourfold undersampled inputs in the lateral and axial dimensions,dramatically reducing the acquisition time.Self-Vision facilitates the use of a deep neural network for 3D microscopy imaging,easing the demanding process of image acquisition and network training for current resolutionenhancing networks.
基金supported by the National Natural Science Foundation of China(Nos.61431017,81272166)
文摘A wearable micro-sensor motion capture system with 16 IMUs and an error-compensatory complementary filter algorithm for real-time motion estimation has been developed to acquire accurate 3D orientation and displacement in real life activities.In the proposed filter algorithm,the gyroscope bias error,orientation error and magnetic disturbance error are estimated and compensated,significantly reducing the orientation estimation error due to sensor noise and drift.Displacement estimation,especially for activities such as jumping,has been the challenge in micro-sensor motion capture.An adaptive gait phase detection algorithm has been developed to accommodate accurate displacement estimation in different types of activities.The performance of this system is benchmarked with respect to the results of VICON optical capture system.The experimental results have demonstrated effectiveness of the system in daily activities tracking,with estimation error 0.16 ± 0.06m for normal walking and 0.13 ± 0.11m for jumping motions.
