For scanning electronmicroscopes with high resolution and a strong electric field,biomass materials under observation are prone to radiation damage from the electron beam.This results in blurred or non-viable images,w...For scanning electronmicroscopes with high resolution and a strong electric field,biomass materials under observation are prone to radiation damage from the electron beam.This results in blurred or non-viable images,which affect further observation of material microscopic morphology and characterization.Restoring blurred images to their original sharpness is still a challenging problem in image processing.Traditionalmethods can’t effectively separate image context dependency and texture information,affect the effect of image enhancement and deblurring,and are prone to gradient disappearance during model training,resulting in great difficulty in model training.In this paper,we propose the use of an improvedU-Net(U-shapedConvolutional Neural Network)to achieve image enhancement for biomass material characterization and restore blurred images to their original sharpness.The main work is as follows:use of depthwise separable convolution instead of standard convolution in U-Net to reduce model computation effort and parameters;embedding wavelet transform into the U-Net structure to separate image context and texture information,thereby improving image reconstruction quality;using dense multi-receptive field channel modules to extract image detail information,thereby better transmitting the image features and network gradients,and reduce the difficulty of training.The experiments show that the improved U-Net model proposed in this paper is suitable and effective for enhanced deblurring of biomass material characterization images.The PSNR(Peak Signal-to-noise Ratio)and SSIM(Structural Similarity)are enhanced as well.展开更多
This paper presents a precision centimeter-range positioner based on a Lorentz force actuator using flexure guides.An additional digital-to-analog converter and an operational amplifier(op amp)circuit together with a ...This paper presents a precision centimeter-range positioner based on a Lorentz force actuator using flexure guides.An additional digital-to-analog converter and an operational amplifier(op amp)circuit together with a suitable controller are used to enhance the positioning accuracy to the nanometer level.First,a suitable coil is designed for the actuator based on the stiffness of the flexure guide model.The flexure mechanism and actuator performance are then verified with finite element analysis.Based on these,a means to enhance the positioning performance electronically is presented together with the control scheme.Finally,a prototype is fabricated,and the performance is evaluated.This positioner features a range of 10 mm with a resolution of 10 nm.The proposed scheme can be extended to other systems.展开更多
In this paper,the host-guest interaction of cucurbit[7]uril(Q[7]) and chromone(CMO) has been developed as a fluorescent probe for the highly selective detection of Zn2+ and Cd^(2+) in water based on a chelation-enhanc...In this paper,the host-guest interaction of cucurbit[7]uril(Q[7]) and chromone(CMO) has been developed as a fluorescent probe for the highly selective detection of Zn2+ and Cd^(2+) in water based on a chelation-enhanced fluorescence(CHEF) mechanism.There was a good linear relationship between the fluorescence intensity of the CMO@Q[7] probe and the concentration of Zn^(2+ )or Cd^(2+) in the range of 0-3.0×10^(-5) mol/L and the detection limit for Zn^(2+) and Cd2+ was found to be 2.03×10^(-6) mol/L and 1.89×10^(-6)mol/L,respectively.The X-ray crystal structure indicated that different coordination fashions were triggered by Zn^(2+) and Cd^(2+ )in the CMO@Q[7] complexes,respectively.However,both metal ions coordinated with the carbonyl oxygen of CMO,which was encapsulated in the cavity of Q[7],thus leading to the enhancement of recognition fluorescence emission of CMO.展开更多
基金supported by the Fundamental Research Funds for Higher Education Institutions of Heilongjiang Province(135409505,135509315,135209245)the Heilongjiang Education Department Basic Scientific Research Business Research Innovation Platform“Scientific Research Project Funding of Qiqihar University”(135409421)the Heilongjiang Province Higher Education Teaching Reform Project(SJGY20190710).
文摘For scanning electronmicroscopes with high resolution and a strong electric field,biomass materials under observation are prone to radiation damage from the electron beam.This results in blurred or non-viable images,which affect further observation of material microscopic morphology and characterization.Restoring blurred images to their original sharpness is still a challenging problem in image processing.Traditionalmethods can’t effectively separate image context dependency and texture information,affect the effect of image enhancement and deblurring,and are prone to gradient disappearance during model training,resulting in great difficulty in model training.In this paper,we propose the use of an improvedU-Net(U-shapedConvolutional Neural Network)to achieve image enhancement for biomass material characterization and restore blurred images to their original sharpness.The main work is as follows:use of depthwise separable convolution instead of standard convolution in U-Net to reduce model computation effort and parameters;embedding wavelet transform into the U-Net structure to separate image context and texture information,thereby improving image reconstruction quality;using dense multi-receptive field channel modules to extract image detail information,thereby better transmitting the image features and network gradients,and reduce the difficulty of training.The experiments show that the improved U-Net model proposed in this paper is suitable and effective for enhanced deblurring of biomass material characterization images.The PSNR(Peak Signal-to-noise Ratio)and SSIM(Structural Similarity)are enhanced as well.
基金Project supported by the National Key Research and Development Plan of China(No.2017YFB1303101)。
文摘This paper presents a precision centimeter-range positioner based on a Lorentz force actuator using flexure guides.An additional digital-to-analog converter and an operational amplifier(op amp)circuit together with a suitable controller are used to enhance the positioning accuracy to the nanometer level.First,a suitable coil is designed for the actuator based on the stiffness of the flexure guide model.The flexure mechanism and actuator performance are then verified with finite element analysis.Based on these,a means to enhance the positioning performance electronically is presented together with the control scheme.Finally,a prototype is fabricated,and the performance is evaluated.This positioner features a range of 10 mm with a resolution of 10 nm.The proposed scheme can be extended to other systems.
基金support from the Science and Technology Support Plan of Guizhou Province [Guizhou Science and Technology Cooperation Support (2020) 4Y218]。
文摘In this paper,the host-guest interaction of cucurbit[7]uril(Q[7]) and chromone(CMO) has been developed as a fluorescent probe for the highly selective detection of Zn2+ and Cd^(2+) in water based on a chelation-enhanced fluorescence(CHEF) mechanism.There was a good linear relationship between the fluorescence intensity of the CMO@Q[7] probe and the concentration of Zn^(2+ )or Cd^(2+) in the range of 0-3.0×10^(-5) mol/L and the detection limit for Zn^(2+) and Cd2+ was found to be 2.03×10^(-6) mol/L and 1.89×10^(-6)mol/L,respectively.The X-ray crystal structure indicated that different coordination fashions were triggered by Zn^(2+) and Cd^(2+ )in the CMO@Q[7] complexes,respectively.However,both metal ions coordinated with the carbonyl oxygen of CMO,which was encapsulated in the cavity of Q[7],thus leading to the enhancement of recognition fluorescence emission of CMO.
