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2022 International Conference on Blockchain technology and Information Security, ICBCTIS 2022

作者： Wang, Yang Cao, Tieyong Yang, Jibin Zheng, Yunfei Fang, Zheng Yang, Zhen Institute of Command-and-Control Engineering Army Engineering University of Pla Jiangsu Nanjing China The Army Artillery and Defense Academy of Pla Jiangsu Nanjing China The Key Laboratory of Polarization Imaging Detection Technology Anhui Hefei China

ISBN: (数字)9781665496919

ISBN: (纸本)9781665496919

Convolution neural networks (CNN) are vulnerable to adversarial attack, which brings security risks to the application of convolutional neural networks in reality. Adversarial attacks are usually done by adding subtle perturbations in images to fool models to output wrong results. In black-box conditions, the transferability of attack method is mostly focused to fool more model. To enhance the transferability of adversarial attack, we proposed an attack method against the commonly used 1× 1 convolution operator (1ConvA, 1× 1 Convolution Attack), which exists in many convolutional networks for improving the complexity of the model and the gradient flow. Experiments on many CNNs demonstrate 1ConvA can generate adversarial examples with better transferability. © 2022 IEEE.

关键词： Convolution

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Self-Knowledge Distillation for the Object Segmentation Based on Atrous Spatial Pyramid 5

Self-Knowledge Distillation for the Object Segmentation Base...

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2022 5th International Symposium on Big Data and Applied Statistics, ISBDAS 2022

作者： Wang, Xiaobing Zheng, Yunfei Zhang, Xiongwei Cao, Tieyong Li, Chenming Wang, Xiulai Wang, Yong Fang, Zheng Wang, Yang Army Engineering University PLA Nanjing210016 China PLA Army Academy of Artillery and Air Defense Hefei230022 China Key Laboratory of Polarization Imaging Detection Technology Hefei230022 China Medical Information Data Room Jinling Hospital Nanjing210018 China

This paper presents an effective Self-Knowledge Distillation (SKD) framework via Atrous Spatial Pyramid Structure (ASPS), which is able to enhance the performance of the object segmentation network without increasing network parameters. In the framework, a lightweight object segmentation network is constructed to achieve the pixel-level object segmentation efficiently. A SKD learning model, including the SKD representation structure based on ASPS and loss function, is proposed to transfer the knowledge in the ASPS into our object segmentation network and improve its generalization ability. The experimental results confirm that compared with recent typical object segmentation networks, our object segmentation network contains the fewest parameters but achieves better performance. Moreover, the proposed SKD method achieves the best performance-boosting compared with recent SKD methods © Published under licence by IOP Publishing Ltd.

关键词： Distillation

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Molecular exchange and passivation at interface afford high-performing perovskite solar cells with efficiency over 24%

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Journal of Energy Chemistry 2023年第7期82卷 219-227,I0005页

作者： Jianjun Sun Wangchao Chen Yingke Ren Yunjuan Niu Zhiqian Yang Li'e Mo Yang Huang Zhaoqian Li Hong Zhang Linhua Hu Key Laboratory of Photovoltaic and Energy Conservation Materials Institute of Solid State PhysicsHFIPSChinese Academy of SciencesHefei 230031AnhuiChina School of Chemistry and Chemical Engineering Anhui Province Key Laboratory of Advanced Catalytic Materials and Reaction EngineeringHefei University of TechnologyHefei 230009AnhuiChina College of Science Hebei University of Science and TechnologyShijiazhuang 050018HebeiChina Hebei Computational Optical Imaging and Photoelectric Detection Technology Innovation Center Hebei International Joint Research Center for Computational Optical Imaging and Intelligent SensingSchool of Mathematics and Physics Science and EngineeringHebei University of EngineeringHandan 056038HebeiChina University of Science and Technology of Chin1 Anhui 230026HefeiChina

The interface is crucial for perovskite solar cells(PSCs).However,voids at interfaces induced by the trapped hygroscopic dimethyl sulfoxide(DMSO)can reduce charge extraction and accelerate the film degradation,seriously damaging the efficiency and *** this work,4,4’-dinonyl-2,2’-dipyridine(DN-DP),a Lewis base with long alkyl chains is introduced to solve this *** calculated and experimental results confirm that the dipyridyl group on DN-DP can more strongly coordinate with Pb^(2+)than that of the S=O group on *** strong coordination effect plays a crucial role in removing the DMSO-based adduct and reducing the formation of *** to the electron-donating properties of pyridine,the existence of DN-DP in the perovskite film can passivate the defects and optimize the energy level alignment of the perovskite *** open-circuit voltage(VOC)of the DN-DP-based PSC is improved from 1.107 V(control device)to 1.153 V,giving rise to a power conversion efficiency(PCE)of24.02%.Furthermore,benefiting from the moisture resistance stemming from the hydrophobic nonyl group,the PCE retains 90.4%of the initial performance after 1000 h of storage in the ambient condition.

关键词： Perovskite solar cell Anti-solvent 4 4′-Dinonyl-2 2′-dipyridine Optimized interfaceStability

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Ultrasensitive and point-of-care detection of plasma phosphorylated tau in Alzheimer’s disease using colorimetric and surface-enhanced Raman scattering dual-readout lateral flow assay

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Nano Research 2023年第5期16卷 7459-7469页

作者： Liding Zhang Ying Su Xiaohan Liang Kai Cao Qingming Luo Haiming Luo Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for OptoelectronicsHuazhong University of Science and Technology(HUST)Wuhan 430074China MoE Key Laboratory for Biomedical Photonics School of Engineering SciencesHuazhong University of Science and TechnologyWuhan 430074China Department of Neurology Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Biomedical Engineering of Hainan Province School of Biomedical EngineeringHainan UniversityHaikou 570228China Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging Chinese Academy of Medical SciencesHUST-Suzhou Institute for BrainsmaticsJiangsu Industrial Technology Research Institute(JITRI)Suzhou 215123China

Phosphorylation of tau at Ser(396,404)(p-tau^(396,404))is one of the earliest phosphorylation events,plasma p-tau^(396,404) level appears to be a potentially promising biomarker of Alzheimer’s disease(AD).The low abundance and easy degradation of p-tau in the plasma make the lateral flow assay(LFA)a suitable choice for point-of-care detection of plasma p-tau^(396,404) ***,based on our screening of a pair of p-tau^(396,404)-specific antibodies,we developed a colorimetric and surface-enhanced Raman scattering(SERS)dual-readout LFA for the rapid,highly sensitive,robust detection of plasma p-tau^(396,404) *** LFA realized a detection limit of 60 pg/mL by the naked eye or 3.8 pg/mL by SERS without cross-reacting with other tau *** importantly,LFA rapidly and accurately differentiated AD patients from healthy controls,suggesting that it has the potential for clinical point-of-care application in AD *** dual-readout LFA has the advantages of simple operation,rapid,ultra-sensitive detection,providing a new way for early AD diagnosis and intervention,especially in primary and community AD screening.

关键词： Alzheimer’s disease p-tau^(396,404) plasma detection surface-enhanced Raman scattering lateral flow assay

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An improvement method of a lossless compression scheme for the datacube from Geostationary Interferometric Infrared Sounder (GIIRS) and its FPGA implementation 9

An improvement method of a lossless compression scheme for t...

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9th IEEE Joint International Information technology and Artificial Intelligence Conference, ITAIC 2020

作者： Yang, Minzhu Hernandez, Raul Guerra Han, Changpei Feliciano, Jose Francisco Lopez China Jiliang University Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province College of Information Engineering Hangzhou China Instituto Universitario de Microelectrónica Aplicada Universidad de Las Palmas de Gran Ganaria Las Palmas Spain Chinese Academy of Science Key Laboratory of Infrared System Detection and Imaging Technology Shanghai China

This paper briefly described an improved method for the original proposed scheme based on Vector Quantization and Linear Prediction to further enhance the compression ratio while reduce the time cost. Given the fact that the interferograms belong to the same datacube are similar to each other, there are two obvious modifications in this paper: predict only once to get the general predicted coefficients for the same datacube;along with treat datacube rather than sequence as the encoded unit. The time consumption spent by Linear Prediction part will shrink about 35.55% by predicting just once. Moreover, the change of the encoded object makes the final compression ratio get a further rise range from 2.62% to 3.711%. © 2020 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Remodel the perifollicular microenvironment via Minoxidil-loaded microneedle patch and cold atmospheric plasma for treating androgenetic alopecia

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Nano Research 2024年第7期17卷 6411-6419页

作者： Hao Chen Xianzhe Tang Yueye Huang Chen Chen Yuheng Yang Chaojie Hao Wenqi Xie Tingjing Huang Xiaofeng Cheng Qingnan Xu Shicong Huang Zhi Ye Xucong Lin Zhaowei Chen Zhitong Chen MOE Key Laboratory for Analytical Science of Food Safety and Biology and New Cornerstone Science LaboratoryCollege of ChemistryFuzhou UniversityFuzhou 350108China Institute of Biomedical and Health Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Advanced Therapeutic Center National Innovation Center for Advanced Medical DevicesShenzhen 518000China Department of Chemistry University College LondonLondon WC1H 0AJUK Engineering Technology Research Center on Reagent and Instrument for Rapid Detection of Product Quality and Food Safety in Fujian Province College of ChemistryFuzhou UniversityFuzhou 350108China Key Laboratory of Biomedical Imaging Science and System Chinese Academy of SciencesShenzhen 518055China

Androgenetic alopecia(AGA)is a chronic and progressive form of hair loss characterized by vascular degeneration in the perifollicular microenvironment,leading to cell apoptosis and eventual loss of hair follicles(HFs).Traditional therapeutic formulations,such as Minoxidil(MXD)tincture,have limitations in reshaping the perifollicular microenvironment and exhibit limited ***,we report a multi-synergistic therapeutic platform for high-performance hair regeneration *** platform combines microneedle(MN)patches loaded with MXD-encapsulated nanostructured lipid carriers(MXD-NLC-MNs)and cold atmospheric plasma(CAP).The MNs’mechanical strength enables efficient transdermal delivery of MXD to the targeted dermal papilla cells,promoting cell ***,in collaboration with MXD,the mechanical stimulation exerted by MN application synergistically upregulates the expression of vascular endothelial growth factor,leading to ***,the transient microchannels in the skin created by MNs facilitate the transdermal delivery of CAPgenerated nitric oxide(NO)to the sites of HF lesions,whereby the synergistic interaction between MXD and NO boosts perifollicular ***,the perifollicular microenvironment can be effectively reshaped to accelerate hair regeneration in AGA murine *** multi-synergistic combination therapy strategy would hold great promise for effectively treating AGA and promoting hair regrowth.

关键词： nanomedicine androgenetic alopecia microneedle cold atmospheric plasma drug delivery

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Coded Excitation System for Stationary Target detection Using Multi Segment Coding

Coded Excitation System for Stationary Target Detection Usin...

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2014 International Conference on Industrial Engineering and Information technology

作者： Jie LI Kai ZHAN Pan-pan LIU Xiao-nian HE Zheng-di QIN National-Regional Key Technology Engineering Laboratory of China for Medical Ultrasound Guangdong Province Key Laboratory for Biomedical Information Detection and Ultrasound Imaging Department of Biomedical Engineering Health Science CenterShenzhen University

In ultrasound systems,the analysis of inherent signal-to-noise(SNR) is one of the eternal *** signal improvements of approximately 10 times are theoretically possible for ultrasonic testing(UT) using coded *** applying the coded excitation into the ultrasound pulse-echo system,codes selection is important as the limited time duration of the transmission *** selected code sequences can hardly get a good auto-correlation *** earlier reports,a technique called Truncated Long Code(TLC) was proposed for dynamic signal detection [1][2][3].Good auto-correlation property has been acquired as the parameter estimation time window can be much longer than the single pulse *** this report,we use the same approach to form a multi-segment coding scheme to detect the stationary objects in ultrasound pulse-echo *** importance of this study are to confirm the efficacy of this new scheme and try to find possible uses in biomedical and industrial applications as well.

关键词： Coded excitation,multi-segment coding,pulse-echo,ultrasound system

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Deep learning-based large-scale named entity recognition for anatomical region of mammalian brain

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Quantitative Biology 2022年第3期10卷 253-263页

作者： Xiaokang Chai Yachao Di Zhao Feng Yue Guan Guoqing Zhang Anan Li Qingming Luo Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for OptoelectronicsMoE Key Laboratory for Biomedical PhotonicsHuazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Biomedical Engineering of Hainan Province School of Biomedical EngineeringHainan UniversityHaikou 570228China CAS Key Laboratory of Computational Biology Bio-Med Big Data CenterShanghai Institute of Nutrition and HealthUniversity of Chinese Academy of SciencesShanghai 200031China Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging Chinese Academy of Medical SciencesHUST-Suzhou Institute for BrainsmaticsJITRISuzhou 215123China CAS Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesShanghai 200031China

Background:Images of anatomical regions and neuron type distribution,as well as their related literature are valuable assets for neuroscience *** are vital evidence and vehicles in discovering new phenomena and knowledge refinement through image and text big *** knowledge acquired from image data generally echoes with the literature accumulated over the *** knowledge within the literature can provide a comprehensive context for a deeper understanding of the image ***,it is quite a challenge to manually identify the related literature and summarize the neuroscience knowledge in the large-scale ***,neuroscientists are in dire need of an automated method to extract neuroscience knowledge from large-scale ***:A proposed deep learning model named BioBERT-CRF extracts brain region entities from the WhiteText *** model takes advantage of BioBERT and CRF to predict entity labels while ***:The proposed deep learning model demonstrated comparable performance against or even outperforms the previous models on the WhiteText *** BioBERT-CRF model has achieved the best average precision,recall,and F1 score of 81.3%,84.0%,and 82.6%,*** used the BioBERT-CRF model to predict brain region entities in a large-scale PubMed abstract dataset and used a rule-based method to normalize all brain region entities to three neuroscience ***:Our work shows that the BioBERT-CRF model can be well-suited for brain region entity *** rankings of different brain region entities by their appearance in the large-scale corpus indicate the anatomical regions that researchers are most concerned about.

关键词： brain region entity extraction literature mining WhiteText deep learning

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Infrared polarization Image Fusion and detection System for Ship Target

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Journal of Physics: Conference Series 2021年第2期1802卷

作者： Haonan Tuo Guochuan Shi Xiaolin Luo Army Artillery and Air Defense Academy Heifei China Anhui province Key Laboratory of Polarization Imaging Detection Technology Hefei China

In order to realize the fusion and detection of ship targets, infrared polarization image fusion and detection technology is adopted in this paper, and a design scheme of infrared polarization image fusion and detection system based on ship targets is proposed, which solves the key technologies such as processing system and fusion and detection algorithm, and the image detection rate is high. The proposed system can be used as a laboratory standby system.

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detection Method of Ship Target Infrared polarization Image

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Journal of Physics: Conference Series 2021年第2期1802卷

作者： Haonan Tuo Guochuan Shi Xiaolin Luo Army Artillery and Air Defense Academy Heifei China Anhui province Key Laboratory of Polarization Imaging Detection Technology Hefei China

In the face of complex background and severe weather environment, infrared polarization detection has obvious advantages. In this paper, the ship target detection method based on infrared polarization image is studied and the ship target infrared polarization image detection method based on local contrast is proposed. The ship target detection accuracy of the proposed algorithm is 0.956, and the false alarm rate of the ship detection is low, which verifies the effectiveness of the detection algorithm in detecting the ship target, which has great application value in military applications.

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