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Toward memristive in-memory computing:principles and applications

Frontiers of Optoelectronics 2022年第2期15卷 101-125页

作者： Han Bao Houji Zhou Jiancong Li Huaizhi Pei Jing Tian Ling Yang Shengguang Ren Shaoqin Tong Yi Li Yuhui He Jia Chen Yimao Cai Huaqiang Wu Qi Liu Qing Wan Xiangshui Miao School of Integrated Circuits School of Optical and Electronic InformationWuhan National Laboratory for OptoelectronicsOptics Valley LaboratoryHuazhong University of Science and TechnologyWuhan 430074China Hubei Yangtze Memory Laboratories Wuhan430205China AI Chip Center for Emerging Smart Systems InnoHK CentersHong Kong Science ParkHong KongChina School of Integrated Circuits Peking UniversityBeijing 100871China School of Integrated Circuits Beijing National Research Center for Information Science and Technology(BNRist)Tsinghua UniversityBeijing 100084China Frontier Institute of Chip and System Fudan UniversityShanghai 200433China School of Electronic Science and Engineering and Collaborative Innovation Centre of Advanced MicrostructuresNanjing UniversityNanjing 210093China

With the rapid growth of computer science and big data,the traditional von Neumann architecture suffers the aggravating data communication costs due to the separated structure of the processing units and *** in-memory computing paradigm is considered as a prominent candidate to address these issues,and plentiful applications have been demonstrated and *** applications can be broadly categorized into two major types:soft computing that can tolerant uncertain and imprecise results,and hard computing that emphasizes explicit and precise numerical results for each task,leading to different requirements on the computational accuracies and the corresponding hardware *** this review,we conduct a thorough survey of the recent advances of memristive in-memory computing applications,both on the soft computing type that focuses on artificial neural networks and other machine learning algorithms,and the hard computing type that includes scientific computing and digital image *** the end of the review,we discuss the remaining challenges and future opportunities of memristive in-memory computing in the incoming Artificial Intelligence of Things era.

关键词： Memristor In-memory computing Matrix-vector multiplication Machine learning Scientific computing Digital image processing

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EyeHealer:A large-scale anterior eye segment dataset with eye structure and lesion annotations

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Precision Clinical Medicine 2021年第2期4卷 85-92页

作者： Wenjia Cai Jie Xu Ke Wang Xiaohong Liu Wenqin Xu Huimin Cai Yuanxu Gao Yuandong Su Meixia Zhang Jie Zhu Charlotte L.Zhang Edward E.Zhang Fangfei Wang Yun Yin Iat Fan Lai Guangyu Wang Kang Zhang Yingfeng Zheng State Key Laboratory of Ophthalmology Zhongshan Ophthalmic CenterSun Yat-sen UniversityGuangzhou 510060China Beijing Institute of Ophthalmology Capital Medical UniversityBeijing Tongren HospitalBeijing 100730China Department of Computer Science and Technology&bnrist Tsinghua UniversityBeijing 100084China Center for Biomedicine and Innovations Faculty of MedicineMacao University of Science and Technology and University HospitalMacao 999078China Guangzhou Women and Children’s Medical Center Guangzhou Medical UniversityGuangzhou 510623China Center for Translational Innovations West China Hospital and Sichuan UniversityChengdu 610041China Bioland Laboratory Guangzhou 510005China School of Business Macao University of Science and TechnologyMacao 999078China Ophthalmic Center Kiang Wu HospitalMacaoChina School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China

Anterior segment eye diseases account for a significant proportion of presentations to eye clinics worldwide,including diseases associated with corneal pathologies,anterior chamber abnormalities(*** or inflammation),and lens *** construction of an automatic tool for segmentation of anterior segment eye lesions would greatly improve the efficiency of clinical *** research on artificial intelligence progressing in recent years,deep learning models have shown their superiority in image classification and *** training and evaluation of deep learning models should be based on a large amount of data annotated with expertise;however,such data are relatively scarce in the domain of ***,the authors developed a new medical image annotation system,called *** is a large-scale anterior eye segment dataset with both eye structures and lesions annotated at the pixel *** experiments were conducted to verify its performance in disease classification and eye lesion *** results showed that semantic segmentation models outperformed medical segmentation *** paper describes the establishment of the system for automated classification and segmentation *** dataset will be made publicly available to encourage future research in this area.

关键词： anterior segment eye diseases artificial intelligence annotation

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An optimal medicinal and edible Chinese herbal formula attenuates particulate matter-induced lung injury through its anti-oxidative,anti-inflammatory and anti-apoptosis activities

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Chinese Herbal Medicines 2023年第3期15卷 407-420页

作者： Huan Zhang Jun Kang Wuyan Guo Fujie Wang Mengjiao Guo Shanshan Feng Wuai Zhou Jinnan Li Ayesha T.Tahir Shaoshan Wang Xinjun Du Hui Zhao Weihua Wang Hong Zhu Bo Zhang TCM Network Pharmacology Department Tianjin Key Laboratory of Early Druggability Evaluation of Innovative DrugsTianjin International Joint Academy of BiomedicineTianjin 300457China School of Life Sciences Tianjin UniversityTianjin 300072China Chunfeng(Beijing)Health Technology Co. Ltd.Beijing 100176China Institute for TCM-X MOE Key Laboratory of BioinformaticsBioinformatics DivisionBNRistDepartment of AutomationTsinghua UniversityBeijing 100084China Department of Biosciences COMSAS University IslamabadIslamabad 44000Pakistan Tianjin Binhai New Area Han Gu Traditional Chinese Medical Hospitals Tianjin 300480China Key Laboratory of Food Nutrition and Safety Ministry of EducationTianjin University of Science and TechnologyTianjin 300457China School of Biotechnology and Food Science Tianjin University of CommerceTianjin 300134China Center of Pharmaceutical Technology Tsinghua UniversityBeijing 100084China Beijing Intelligent Medicine and Network Pharmacology Co. LtdBeijng 100020China

Objective:Identifying novel strategies to prevent particulate matter(PM)-induced lung injury is crucial for the reduction of the morbidity of chronic respiratory *** combined intervention represented by herbal formulae for simultaneously targeting multiple pathological processes can provide a more beneficial effect than the single *** aim of this paper is therefore to design a safe and effective medicinal and edible Chinese herbs(MECHs)formula against PM-induced lung ***:PM-induced oxidative stress,inflammatory response and apoptosis A549 cell model were used to screen anti-oxidant,anti-inflammatory and anti-apoptotic MECHs,respectively.A network pharmacology method was utilized to rationally design a novel herbal *** performance liquid chromatography-mass spectrometer was utilized to assess the quality control of MECHs *** excretion of magnetic iron oxide nanospheres of the MECHs formula was estimated in *** MECH formula against PM-induced lung injury was investigated with mice ***:Five selected herbs were rationally designed to form a new MECH formula,including Citri Exocarpium Rubrum(Juhong),Lablab Semen Album(Baibiandou),Atractylodis Macrocephalae Rhizoma(Baizhu),Mori Folium(Sangye)and Polygonati Odorati Rhizoma(Yuzhu).The formula effectively promoted the magnetic iron oxide nanospheres excretion in *** mid/high dose formula significantly prevented PM-induced lung damage in mice by enhancing the activity of SOD and GSH-Px,reducing the MDA and ROS level and attenuating the upregulation of pro-inflammatory cytokine(IL-6,IL-8,IL-1βand TNFa),down regulating the protein expression of NF-κB,STAT3 and ***:Our findings suggest that the effective MECHs formula will become a novel strategy for preventing PM-induced lung injury and provide a paradigm for the development of functional foods using MECHs.

关键词： apoptosis inflammatory response lung injury medicinal and edible Chinese herbs oxidative stress particulate matter

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基于PI控制的多智能体系统可一致性充要条件:广义Nyquist判据

基于PI控制的多智能体系统可一致性充要条件:广义Nyquist判据

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第32届中国过程控制会议(CPCC2021)

作者：郜晨何潇王子栋周东华清华大学自动化系北京信息科学与技术国家研究中心(bnrist) 英国布鲁奈尔大学计算机科学系山东科技大学电气与自动化工程学院

本文针对一类线性连续多智能体系统(Multi-agent systems,MASs),设计了一种基于状态反馈的比例积分(Proportion-integration,PI)型控制律,并从频域的角度对MASs的一致性进行分析.首先利用Laplace变换,将MAS模型从时域转换到频域,再利用K... 详细信息

本文针对一类线性连续多智能体系统(Multi-agent systems,MASs),设计了一种基于状态反馈的比例积分(Proportion-integration,PI)型控制律,并从频域的角度对MASs的一致性进行分析.首先利用Laplace变换,将MAS模型从时域转换到频域,再利用Kronecker积,将MAS的一致性问题转化为一个多输入多输出(Multi-input multi-output,MIMO)系统的稳定性问题.借助频域中广义Nyquist判据对MIMO系统的稳定性进行分析,进而得到MAS可一致性的判据.本文从频域的角度揭示了拓扑结构对一致性的影响,并重点解决了有向图下的MASs一致性PI控制难题,得到了MASs可一致性的充要条件.最后,通过对比仿真实验说明了所提PI型控制律在应对时不变/缓变故障方面的优势.

关键词：多智能体一致性 PI控制广义Nyquist判据

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Introduction to bioimaging-based spatial multi-omic novel methods

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Quantitative Biology 2023年第3期11卷 231-245页

作者： Yan Yan Liheng Yang Leyuan Meng Haochen Su Cheng Zhou Le Yu Zhengtu Li Xu Zhang Huihua Cai Juntao Gao MOE Key Laboratory of Bioinformatics Tsinghua UniversityBeijing 100084China Center for Synthetic&Systems Biology Tsinghua UniversityBeijing 100084China Seaver College Pepperdine UniversityMalibuCA 90263USA College of Animal Sciences Heping campusJilin UniversityJilin 130062China Sidney Sussex College Sidney StreetCambridge CB23HUUnited Kingdom Department of Radiation Oncology Nanfang HospitalSouthern Medical UniversityGuangzhou 510515China Foshan Protogene Tech.Co.Ltd Foshan 510168China State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory DiseaseGuangzhou Institute of Respiratory Healththe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510120China Beijing Institute of Collaborative Innovation Beijing 100094China Department of Automation Tsinghua UniversityBeijing 100084China Department of Obstetrics and Gynecology Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 511436China Bioinformatics Division BNRistTsinghua UniversityBeijing 100084China Institute for TCM-X Tsinghua UniversityBeijing 100084China

Background: Spatial multi-omics are demonstrated to be a powerful method to assist researchers on genetic studies. In this review, bioimaging-based spatial multi-omics techniques such as seqFISH+, merFISH, integrated DNA seqFISH+, DNA merFISH, and MINA are introduced along with each technique’s probe design, development, and imaging ***: seqFISH employed 4–5 fluorophores to barcode and conducted multiple rounds of hybridization, in order that mRNA can be identified through color-coding. seqFISH+ added 60 pseudo-color and distributed them equally into three channels to enhance imaging power, in order that i.e., 24,000 genes can be imaged in total. merFISH utilized 4 out 16 Hamming distance to innovatively provide a robust error-detecting method. MINA, a methodology combining merFISH (multiplexed error-robust fluorescence in situ hybridization) and chromosomal tracing, enabled multiplexed genomic architecture imaged in mammalian single cells. Optical reconstruction of chromatin architecture (ORCA) a method that could conduct DNA path tracing in nanoscale manner with kilobase resolution, an FISH variation that improved genetic resolution, enable high-precision fiducial registration and sequential imaging, and utilized Oligopaint probe to hybridize the short genomic region ranging from 2 to 10 kilobase. ORCA then prescribes these short section primary probes with individual barcodes to attach fluorophore and to be ***: This review concentrated on providing a comprehensive overview for these spatial-multi-omics techniques with the intention on helping researchers on selecting appropriate technique for their research.

关键词： FISH multiplex FISH super-resolution imaging gene regulation

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Understanding the phase separation characteristics of nucleocapsid protein provides a new therapeutic opportunity against SARS-CoV-2

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Protein & Cell 2021年第9期12卷 734-740页

作者： Dan Zhao Weifan Xu Xiaofan Zhang Xiaoting Wang Yiyue Ge Enming Yuan Yuanpeng Xiong Shenyang Wu Shuya Li Nian Wu Tingzhong Tian Xiaolong Feng Hantao Shu Peng Lang Jingxin Li Fengcai Zhu Xiaokun Shen Haitao Li Pilong Li Jianyang Zeng Institute for Interdisciplinary Information Sciences Tsinghua UniversityBeijing 100084China Beijing Advanced Innovation Center for Structural Biology Frontier Research Center for Biological Structure School of Life SciencesTsinghua UniversityBeijing 100084China Winghua-Peking Center for Life Sciences Tsinghua UniversityBeijing 100084China Silexon Al Technology Co. LtdNanjing 210033China NHC Key Laboratory of Enteric Pathogenic Microbiology Jiangsu Provincial Center for Diseases Control and PreventionNanjing 210009China Bioinformatics Division BNRIST/Department of Computer Science and TechnologyTsinghua UniversityBeijing 100084China Protein Preparation and Identification Facility Technology Center for Protein ScienceTsinghua UniversityBeijing 100084China Institute of Pathology Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430074China Center for Global Health Nanjing Medical UniversityNanjing 210009China Convalife(Shanghai)Co. LtdShanghai 201203China Ministry of Education Key Laboratory of Protein Sciences Beijing Advaneed Innovation Center for Structural BiologyBeijing Frontier Research Center for Biological StructureDepartment of Basic Medical SciencesSchool of MedicineTsinghua UniversityBeijing 100084China

Dear Editor To date,tens of millions of people have been infected with severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),causing the outbreak of the respiratory disease named the coronavirus disease 2019(COVID-19).As a newly emerged member of the coronavirus family,SARS-CoV-2 is an enveloped positive-strand RNA virus,which has probably the largest genome(approximately 30 kb)among all RNA *** nucleocapsid(N)protein of SARS-CoV-2 is mainly responsible for recognizing and wrapping viral RNA into helically symmetric structures(Malik,2020).

关键词： respiratory acute therapeutic

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Micromesh reinforced strain sensor with high stretchability and stability for full-range and periodic human motions monitoring

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InfoMat 2024年第4期6卷 124-139页

作者： Haidong Liu Chang Liu Jinan Luo Hao Tang Yuanfang Li Houfang Liu Jingzhi Wu Fei Han Zhiyuan Liu Jianhe Guo Rongwei Tan Tian-Ling Ren Yancong Qiao Jianhua Zhou School of Biomedical Engineering Shenzhen Campus of Sun Yat-sen UniversityShenzhenGuangdongthe People's Republic of China Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province School of Biomedical EngineeringSun Yat-sen UniversityGuangzhouthe People's Republic of China School of Integrated Circuits and Beijing National Research Center for Information Science and Technology(bnrist) Tsinghua UniversityBeijingthe People's Republic of China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences(CAS)Shenzhenthe People's Republic of China Guangdong Engineering Technology Research Center of Implantable Medical Polymer Shenzhen Lando Biomaterials Co.Ltd.Shenzhenthe People's Republic of China

The development of strain sensors with high stretchability and stability is an inevitable requirement for achieving full-range and long-term use of wearable electronic ***,a resistive micromesh reinforced strain sensor(MRSS)with high stretchability and stability is prepared,consisting of a laser-scribed graphene(LSG)layer and two styrene-block-poly(ethylene-ran-butylene)-block-poly-styrene micromesh layers embedded in *** micromesh reinforced structure endows the MRSS with combined characteris-tics of a high stretchability(120%),excellent stability(with a repetition error of 0.8%after 11000 cycles),and outstanding sensitivity(gauge factor up to 2692 beyond 100%).Impressively,the MRSS can still be used continauously within the working range without damage,even if stretched to 300%.Furthermore,compared with different structure sensors,the mechanism of the MRSS with high stretchability and stability is ***'s more,a multilayer finite element model,based on the layered structure of the LSG and the morphology of the cracks,is proposed to investigate the strain sensing behavior and failure mechanism of the ***,due to the outstanding performance,the MRSS not only performes well in monitoring full-range human motions,but also achieves intelligent recognitions of various respiratory activities and ges-tures assisted by neural network algorithms(the accuracy up to 94.29%and 100%,respectively).This work provides a new approach for designing high-performance resistive strain sensors and shows great potential in full-range and long-term intelligent health management and human-machine interac-tions applications.

关键词： flexible strain sensor excellent stretchability and stability layered laser-scribed graphene micromesh reinforced structure multilayer finite element model

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From complexity to clarity: development of CHM-FIEFP for predicting effective components in Chinese herbal formulas by using big data

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Cancer Biology & Medicine 2024年第11期 1067-1077页

作者： Boyu Pan Han Zhu Jiaqi Yang Liangjiao Wang Zizhen Chen Jian Ma Bo Zhang Zhanyu Pan Guoguang Ying Shao Li Liren Liu Department of Molecular Pharmacology Tianjin Medical University Cancer Institute & Hospital National Clinical Research Center for Cancer Key Laboratory of Cancer Prevention and TherapyTianjin Tianjin's Clinical Research Center for Cancer College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Department of General Surgery Tianjin Haihe Hospital Beijing Intelligent Medicine and Network Pharmacology Co. Ltd Institute for TCM-X MOE Key Laboratory of Bioinformatics Bioinformatics Division BNRist Department of AutomationTsinghua University Department of Integrative Oncology Tianjin Medical University Cancer Institute and Hospital Laboratory of Cancer Cell Biology Tianjin Medical University Cancer Institute & Hospital

Objective: The presence of complex components in Chinese herbal medicine(CHM) hinders identification of the primary active substances and understanding of pharmacological principles. This study was aimed at developing a big-data-based, knowledgedriven in silico algorithm for predicting central components in complex CHM ***: Network pharmacology(TCMSP) and clinical(GEO) databases were searched to retrieve gene targets corresponding to the formula ingredients, herbal components, and specific disease being treated. Intersections were determined to obtain diseasespecific core targets, which underwent further GO and KEGG enrichment analyses to generate non-redundant biological processes and molecular targets for the formula and each component. The ratios of the numbers of biological and molecular events associated with a component were calculated with a formula, and entropy weighting was performed to obtain a fitting score to facilitate ranking and improve identification of the key components. The established method was tested on the traditional CHM formula Danggui Sini Decoction(DSD) for gastric cancer. Finally, the effects of the predicted critical component were experimentally validated in gastric cancer ***: An algorithm called Chinese Herb Medicine-Formula vs. Ingredients Efficacy Fitting & Prediction(CHM-FIEFP) was developed. Ferulic acid was identified as having the highest fitting score among all tested DSD components. The pharmacological effects of ferulic acid alone were similar to those of ***: CHM-FIEFP is a promising in silico method for identifying pharmacological components of CHM formulas with activity against specific diseases. This approach may also be practical for solving other similarly complex problems. The algorithm is available at http://***/.

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Two-dimensional materials for future information technology: status and prospects

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Science China(Information Sciences) 2024年第6期67卷 1-147页

作者： Hao QIU Zhihao YU Tiange ZHAO Qi ZHANG Mingsheng XU Peifeng LI Taotao LI Wenzhong BAO Yang CHAI Shula CHEN Yiqi CHEN Hui-Ming CHENG Daoxin DAI Zengfeng DI Zhuo DONG Xidong DUAN Yuhan FENG Yu FU Jingshu GUO Pengwen GUO Yue HAO Jun HE Xiao HE Jingyi HU Weida HU Zehua HU Xinyue HUANG Ziyang HUANG Ali IMRAN Ziqiang KONG Jia LI Qian LI Weisheng LI Lei LIAO Bilu LIU Can LIU Chunsen LIU Guanyu LIU Kaihui LIU Liwei LIU Sheng LIU Yuan LIU Donglin LU Likuan MA Feng MIAO Zhenhua NI Jing NING Anlian PAN Tian-Ling REN Haowen SHU Litao SUN Yue SUN Quanyang TAO Zi-Ao TIAN Dong WANG Hao WANG Haomin WANG Jialong WANG Junyong WANG Wenhui WANG Xingjun WANG Yeliang WANG Yuwei WANG Zhenyu WANG Yao WE... School of Electronic Science and Engineering Nanjing University School of Integrated Circuits Interdisciplinary Research Center for Future Intelligent Chips (Chip-X)Nanjing University School of Integrated Circuit Science and Engineering Nanjing University of Posts and Telecommunications State Key Laboratory of Infrared Physics Shanghai Institute of Technical Physics Chinese Academy of Sciences School of Physics and Key Lab of Quantum Materials and Devices of the Ministry of Education School of Electronic Science & EngineeringSoutheast University College of Integrated Circuits State Key Laboratory of Silicon and Advanced Semiconductor MaterialsZhejiang University Suzhou Laboratory State Key Laboratory of Integrated Chips and Systems School of MicroelectronicsFudan University Shaoxin Laboratory Department of Applied Physics The Hong Kong Polytechnic University Key Laboratory for Micro-Nano Physics and Technology of Hunan Province College of Materials Science and EngineeringHunan University College of Integrated Circuits Zhejiang University Shenzhen Geim Graphene Center Shenzhen Key Laboratory of Layered Materials for Value-Added ApplicationsTsinghua-Berkeley Shenzhen Institute & Institute of Materials ResearchTsinghua Shenzhen International Graduate SchoolTsinghua University State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and EngineeringInternational Research Center for Advanced PhotonicsZijingang CampusZhejiang University National Key Laboratory of Materials for Integrated Circuits Shanghai Institute of Microsystem and Information TechnologyChinese Academy of Sciences CAS Key Laboratory of Nanophotonic Materials and Devices & Key Laboratory of Nanodevices and Applications i-LabSuzhou Institute of Nano-Tech and Nano-Bionics (SINANO)Chinese Academy of Sciences College of Chemistry and Chemical Engineering Hunan University Key Laboratory of Quantum State Construction and Manipulation (Ministry of Education) Department of PhysicsRenmin University of China School

Over the past 70 years, the semiconductor industry has undergone transformative changes,largely driven by the miniaturization of devices and the integration of innovative structures and materials. Two-dimensional(2D) materials like transition metal dichalcogenides(TMDs) and graphene are pivotal in overcoming the limitations of silicon-based technologies, offering innovative approaches in transistor design and functionality, enabling atomic-thin channel transistors and monolithic 3D integration. We review the important progress in the application of 2D materials in future information technology, focusing in particular on microelectronics and optoelectronics. We comprehensively summarize the key advancements across material production, characterization metrology, electronic devices, optoelectronic devices, and heterogeneous integration on silicon. A strategic roadmap and key challenges for the transition of 2D materials from basic research to industrial development are outlined. To facilitate such a transition, key technologies and tools dedicated to 2D materials must be developed to meet industrial standards, and the employment of AI in material growth, characterizations, and circuit design will be essential. It is time for academia to actively engage with industry to drive the next 10 years of 2D material research.

关键词： two-dimensional (2D) materials information technology production technology standardization of characterization microelectronic devices optoelectronic devices multi-functional integration

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