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Applications of nanogenerators for biomedical engineering and healthcare systems

InfoMat 2022年第2期4卷 53-109页

作者： Wanli Wang Jinbo Pang Jie Su Fujiang Li Qiang Li Xiaoxiong Wang Jingang Wang Bergoi Ibarlucea Xiaoyan Liu Yufen Li Weijia Zhou Kai Wang Qingfang Han Lei Liu Ruohan Zang Mark HRümmeli Yang Li Hong Liu Han Hu Gianaurelio Cuniberti College of Electrical Engineering Qingdao UniversityQingdaoChina Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of Shandong Institute for Advanced Interdisciplinary Research(iAIR)University of JinanJinanChina College of Electronic Information Qingdao UniversityQingdaoChina Department of Pediatric Surgery The Affiliated Hospital of Qingdao UniversityQingdaoChina College of Physics Qingdao UniversityQingdaoChina Institute for Materials Science and Max Bergmann Center of Biomaterials Technische Universität DresdenDresdenGermany Center for Advancing Electronics Dresden Technische Universität DresdenDresdenGermany College of Biological Science and Technology University of JinanJinanChina School of Chemistry and Chemical Engineering University of JinanShandongJinanChina College of Energy Soochow Institute for Energy and Materials InnovationsSoochow UniversitySuzhouChina Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province Soochow UniversitySuzhouChina Centre of Polymer and Carbon Materials Polish Academy of SciencesZabrzePoland Institute for Complex Materials IFW DresdenDresdenGermany Institute of Environmental Technology VŠB-Technical University of OstravaOstravaCzech Republic School of Information Science and Engineering University of JinanJinanChina Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of JinanJinanChina State Key Laboratory of Crystal Materials Center of Bio&Micro/Nano Functional MaterialsShandong UniversityJinanChina College of Chemical Engineering China University of Petroleum(East China)QingdaoChina Dresden Center for Computational Materials Science Technische Universität DresdenDresdenGermany The Dresden Center for Intelligent Materials(DCIM) Technische Universität DresdenDresdenGermany

The dream of human beings for long living has stimulated the rapid development of biomedical and healthcare ***,conventional biomedical and healthcare devices have shortcomings such as short service life,large equipment size,and high potential safety ***,the power supply for conventional implantable device remains predominantly *** emerging nanogenerators,which harvest micro/nanomechanical energy and thermal energy from human beings and convert into electrical energy,provide an ideal solution for self-powering of biomedical *** combination of nanogenerators and biomedicine has been accelerating the development of self-powered biomedical *** article first introduces the operating principle of nanogenerators and then reviews the progress of nanogenerators in biomedical applications,including power supply,smart sensing,and effective ***,the microbial disinfection and biodegradation performances of nanogenerators have been ***,the protection devices have been discussed such as face mask with air filtering function together with real-time monitoring of human health from the respiration and heat ***,the nanogenerator devices have been categorized by the types of mechanical energy from human beings,such as the body movement,tissue and organ activities,energy from chemical reactions,and gravitational potential ***,the challenges and future opportunities in the applications of nanogenerators are delivered in the conclusive remarks.

关键词： biomedical engineering healthcare implantable devices nanogenerators self-powered devices sensors

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Flux variations of cosmic ray air showers detected by LHAASO-KM2A during a thunderstorm on June 10,2021

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Chinese Physics C 2023年第1期47卷 193-203页

作者： F.Aharonian 安琪阿西克古白立新白云翔包逸炜 D.Bastieri 毕效军毕玉江蔡金庭曹喆曹臻常进常劲帆陈恩生陈良陈亮陈龙陈明君陈玛丽陈素弘陈松战陈天禄陈学健陈阳程皓麟程宁程耀东崔树旺崔晓红崔昱东戴本忠代洪亮戴子高单增罗布 D.della Volpe 段凯凯樊军辉范一中范志香方军方堃冯存峰封莉冯少辉丰晓婷冯有亮高博高川东高林青高启高卫高伟康葛茂茂耿利斯龚光华苟全补顾旻皓郭福来郭俊广郭晓磊郭义庆郭莹莹韩毅昂何会海贺昊宁何思乐何新波何钰 M.Heller 贺远强侯超侯贤胡红波胡铨胡森胡世聪呼晓军黄代绘黄文昊黄性涛黄晓渊黄勇黄志成季筱璐贾焕玉贾康江琨姜泽军金敏康明铭柯通 D.Kuleshov 李兵兵李澄李骢李飞李海波李会财李华阳李军李剑李捷李凯李文龙李秀荣李昕李新李一卓李哲黎卓梁恩维梁云峰林苏杰刘冰刘成刘栋刘虎刘海东刘佳刘江来刘佳松刘金艳刘茂元柳若愚刘四明刘伟刘怡刘以农龙文杰鲁睿罗晴吕洪魁马伯强马玲玲马欣华毛基荣 A.Masood 闵振 W.Mitthumsiri 南云程区子维庞彬宇 P.Pattarakijwanich 裴致远齐孟尧祁业情乔冰强秦家军 D.Ruffolo A.Sáiz 邵澄宇邵琅 O.Shchegolev 盛祥东石京燕宋慧超 Yu.V.Stenkin V.Stepanov 苏扬孙秦宁孙晓娜孙志斌谭柏轩唐泽波田文武王博东王超王辉王洪光王建成王界双王利苹王玲玉王冉王润娜王为王祥高王祥玉王阳王玉东王岩谨王亚平王忠海王仲翔王振王铮韦大明魏俊杰魏永健文韬吴超勇吴含荣武莎吴雪峰吴雨生席邵强夏捷夏君集项光漫肖迪泫肖刚辛广广辛玉良邢祎熊峥徐东莲徐仁新薛良闫大海颜景志杨朝文杨冯帆杨何文杨佳盈杨莉莉杨明洁杨睿智杨深邦姚玉华姚志国叶一锰尹丽巧尹娜游晓浩游智勇于艳红袁强岳华曾厚敦曾婷轩曾玮曾宗康查敏翟徐徐张彬彬张丰张海明张恒英张建立张丽霞张力张路张鹏飞张佩佩张瑞张少博张少如张寿山张潇张笑鹏张云峰张月雷张毅张勇赵兵赵静赵雷赵立志赵世平郑福郑应周斌周浩周佳能周平周荣周勋秀祝成光祝凤荣朱辉朱科军左雄 Key Laboratory of Particle Astrophyics&Experimental Physics Division&Computing Center of Sciences Beijing 100049China University of Chinese Academy of Sciences Beijing 100049China TIANFU Cosmic Ray Research Center ChengduSichuanChina Dublin Institute for Advanced Studies 31 Fitzwilliam Place2 DublinIreland Max-Planck-Institut for Nuclear Physics P.O.Box 10398069029 HeidelbergGermany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Hefei 230026China School of Physical Science and Technology&School of Information Science and Technology Southwest Jiaotong UniversityChengdu 610031China College of Physics Sichuan UniversityChengdu 610065China School of Astronomy and Space Science Nanjing UniversityNanjing 210023China Center for Astrophysics Guangzhou UniversityGuangzhou 510006China Key Laboratory of Dark Matter and Space Astronomy&Key Laboratory of Radio Astronomy Purple Mountain ObservatoryChinese Academy of SciencesNanjing 210023China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical ObservatoryChinese Academy of SciencesShanghai 200030China Key Laboratory of Cosmic Rays(Tibet University) Ministry of Education850000 LhasaTibetChina National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China Hebei Normal University Shijiazhuang 050024China School of Physics and Astronomy(Zhuhai)&School of Physics(Guangzhou)&Sino-French Institute of Nuclear Engineering and Technology(Zhuhai) Sun Yat-sen University519000 Zhuhai&510275 GuangzhouGuangdongChina Dipartimento di Fisica dell’Universitàdi Napoli"Federico II" Complesso Universitario di Monte Sant’Angelovia Cinthia80126 NapoliItaly School of Physics and Astronomy Yunnan UniversityKunming 650091China D´epartement de Physique Nucléaire et Corpusculaire Facultéde SciencesUniversitéde Genève24 Quai Ernest Ansermet1211 GenevaSwitzerland Institute of Frontier and Interdisciplinary Science Shandong UniversityQingdao 266237China Depar

The Large High Altitude Air Shower Observatory(LHAASO)has three sub-arrays,KM2A,WCDA,and *** flux variations of cosmic ray air showers were studied by analyzing the KM2A data during a thunderstorm on June 10,*** number of shower events that meet the trigger conditions increases significantly in atmospheric electric fields,with a maximum fractional increase of 20%.The variations in trigger rates(increases or decreases)were found to be strongly dependent on the primary zenith *** flux of secondary particles increased significantly,following a trend similar to that of shower *** better understand the observed behavior,Monte Carlo simulations were performed with CORSIKA and G4KM2A(a code based on GEANT4).We found that the experimental data(in saturated negative fields)were in good agreement with the simulations,assuming the presence of a uniform electric field of-700 V/cm with a thickness of 1500 m in the atmosphere above the observation *** to the acceleration/deceleration by the atmospheric electric field,the number of secondary particles with energy above the detector threshold was modified,resulting in the changes in shower detection rate.

关键词： thunderstorm cosmic rays extensive air showers LHAASO-KM2A

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Uncertainty-Aware Relational Graph Neural Network for Few-Shot Knowledge Graph Completion

arXiv

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arXiv 2024年

作者： Li, Qian Guo, Shu Chen, Yingjia Ji, Cheng Sheng, Jiawei Li, Jianxin Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China The State Key Laboratory of Software Development Environment Beihang University Beijing100083 China National Computer Network Emergency Response Technical Team Coordination Center of China Beijing100083 China School of Mathematics Edinburgh University Edinburgh United Kingdom Institute of Information Engineering Chinese Academy of Sciences Beijing100083 China School of Cyber Security University of Chinese Academy of Sciences Beijing100083 China

Few-shot knowledge graph completion (FKGC) aims to query the unseen facts of a relation given its few-shot reference entity pairs. The side effect of noises due to the uncertainty of entities and triples may limit the few-shot learning, but existing FKGC works neglect such uncertainty, which leads them more susceptible to limited reference samples with noises. In this paper, we propose a novel uncertainty-aware few-shot KG completion framework (UFKGC) to model uncertainty for a better understanding of the limited data by learning representations under Gaussian distribution. Uncertainty representation is first designed for estimating the uncertainty scope of the entity pairs after transferring feature representations into a Gaussian distribution. Further, to better integrate the neighbors with uncertainty characteristics for entity features, we design an uncertainty-aware relational graph neural network (UR-GNN) to conduct convolution operations between the Gaussian distributions. Then, multiple random samplings are conducted for reference triples within the Gaussian distribution to generate smooth reference representations during the optimization. The final completion score for each query instance is measured by the designed uncertainty optimization to make our approach more robust to the noises in few-shot scenarios. Experimental results show that our approach achieves excellent performance on two benchmark datasets compared to its competitors. Copyright © 2024, The Authors. All rights reserved.

关键词： Graph neural networks

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Upper Security Bounds for Coherent-One-Way Quantum key Distribution

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Physical Review Letters 2020年第26期125卷 260510-260510页

作者： Javier González-Payo Róbert Trényi Weilong Wang Marcos Curty Escuela de Ingeniería de Telecomunicación Department of Signal Theory and Communications University of Vigo Vigo E-36310 Spain State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan 450001 China Henan Key Laboratory of Network Cryptography Technology Zhengzhou Henan 450001 China

The performance of quantum key distribution (QKD) is severely limited by multiphoton pulses emitted by laser sources due to the photon-number splitting attack. Coherent-one-way (COW) QKD has been introduced as a promising solution to overcome this limitation, and thus extend the achievable distance of practical QKD. Indeed, thanks to its experimental simplicity, the COW protocol is already used in commercial applications. Here, we derive simple upper security bounds on its secret key rate, which demonstrate that it scales at most quadratically with the system’s transmittance, thus solving a long-standing problem. That is, in contrast to what has been claimed, this approach is inappropriate for long-distance QKD transmission. Remarkably, our findings imply that all implementations of the COW protocol performed so far are insecure.

关键词： Quantum communication Quantum cryptography

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Robust Optimization for Quantum Reinforcement Learning Control using Partial Observations

arXiv

引用

arXiv 2022年

作者： Jiang, Chen Pan, Yu Wu, Zheng-Guang Gao, Qing Dong, Daoyi State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou310027 China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China The School of Engineering and Information Technology University of New South Wales CanberraACT2600 Australia

The current quantum reinforcement learning control models often assume that the quantum states are known a priori for control optimization. However, full observation of quantum state is experimentally infeasible due to the exponential scaling of the number of required quantum measurements on the number of qubits. In this paper, we investigate a robust reinforcement learning method using partial observations to overcome this difficulty. This control scheme is compatible with near-term quantum devices, where the noise is prevalent and predetermining the dynamics of quantum state is practically impossible. We show that this simplified control scheme can achieve similar or even better performance when compared to the conventional methods relying on full observation. We demonstrate the effectiveness of this scheme on examples of quantum state control and quantum approximate optimization algorithm. It has been shown that high-fidelity state control can be achieved even if the noise amplitude is at the same level as the control amplitude. Besides, an acceptable level of optimization accuracy can be achieved for QAOA with noisy control Hamiltonian. This robust control optimization model can be trained to compensate the uncertainties in practical quantum computing. © 2022, CC BY.

关键词： Robust control

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A biologically plausible audio-visual integration model for continual learning

arXiv

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arXiv 2020年

作者： Chen, Wenjie Du, Fengtong Wang, Ye Cao, Lihong State Key Laboratory of Media Convergence and Communication Communication University of China Beijing China Neuroscience and Intelligent Media Institute Communication University of China Beijing China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China

The problem of catastrophic forgetting has a history of more than 30 years and has not been completely solved yet. Since the human brain has natural ability to perform continual lifelong learning, learning from the brain may provide solutions to this problem. In this paper, we propose a novel biologically plausible audio-visual integration model (AVIM) based on the assumption that the integration of audio and visual perceptual information in the medial temporal lobe during learning is crucial to form concepts and make continual learning possible. Specifically, we use multi-compartment Hodgkin-Huxley neurons to build the model and adopt the calcium-based synaptic tagging and capture as the model’s learning rule. Furthermore, we define a new continual learning paradigm to simulate the possible continual learning process in the human brain. We then test our model under this new paradigm. Our experimental results show that the proposed AVIM can achieve state-of-the-art continual learning performance compared with other advanced methods such as OWM, iCaRL and GEM. Moreover, it can generate stable representations of objects during learning. These results support our assumption that concept formation is essential for continuous lifelong learning and suggest the proposed AVIM is a possible concept formation mechanism. Copyright © 2020, The Authors. All rights reserved.

关键词： Brain

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Personalized PBPK modeling can reduce uncertainty of the dose prediction in radiopharmaceutical therapy (RPT): a simulation study

Personalized PBPK modeling can reduce uncertainty of the dos...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： R. Hu J. Luo B. Saboury P. Heidari Q. Li H. Liu N. Guo Massachusetts General Hospital/Harvard Medical School The Center for Advanced Medical Computing and Analysis Boston Massachusetts United States of America Department of Optical Engineering Zhejiang University State Key Laboratory of Modern Optical Instrumentation Hangzhou China Department of Radiology Bethesda NIH Clinical Center Maryland United States of America Department of Radiology Massachusetts General Hospital/Harvard Medical School Boston Massachusetts United States of America

Physiologically based pharmacokinetic modeling plays a crucial role in optimizing dosimetry estimates for radiopharmaceutical therapy (RPT) on cancer patients. Presently, PBPK applications in RPT predominantly depend on population-level parameters, leading to large uncertainties on the dose prediction. These uncertainties can result in sub-optimal therapeutic effects, increase toxicity, and compromise treatment planning. In this study, we developed a whole body PBPK model, incorporating a Tumor compartment, to predict the dose in different organs. By personalizing certain anatomical and physiological parameters that could be potentially derived from pre-treatment PET/CT and blood test, we observed a substantial decrease in the uncertainty of dose prediction when utilizing personalized PBPK modeling.

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Metal-organic-framework-derived formation of Co–N-doped carbon materials for efficient oxygen reduction reaction

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Journal of Energy Chemistry 2020年第1期29卷 137-143,I0005页

作者： Hao Tian Chi Zhang Panpan Su Zhangfeng Shen Hao Liu Guoxiu Wang Shaomin Liu Jian Liu State Key Laboratory of Catalysis iChEMDalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023LiaoningChina Department of Chemical Engineering Curtin UniversityPerthWA 6845Australia Centre for Clean Energy Technology School of Mathematical and Physical SciencesFaculty of ScienceUniversity of Technology SydneyBroadwaySydneyNSW 2007Australia Joint International Laboratory on Environmental and Energy Frontier Materials School of Environmental and Chemical EngineeringShanghai UniversityShanghai 200444China DICP-Surrey Joint Centre for Future Materials Department of Chemical and Process Engineeringand Advanced Technology InstituteUniversity of SurreyGuilfordSurrey GU27XHUK State Key Laboratory of Catalysis iChEMDalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023 LiaoningChina

Non-precious metal nitrogen-doped carbonaceous materials have attracted tremendous attention in the field of electrochemical energy storage and ***,we report the designed synthesis of a novel series of Co-N-C nanocomposites and their evaluation of electrochemical *** yolkshell structured Co nanoparticles@polymer materials are fabricated from the facile coating polymer strategy on the surface of *** calcination in nitrogen atmosphere,the Co–N–C nanocomposites in which cobalt metal nanoparticles are embedded in the highly porous and graphitic carbon matrix are successfully *** cobalt nanoparticles containing cobalt metal crystallites with an oxidized shell and/or smaller(or amorphous)cobalt-oxide deposits appear on the surface of graphitic *** prepared Co–N–C nanoparticles showed favorable electrocatalytic activity for oxygen reduction reactions,which is attributed to its high graphitic degree,large surface area and the large amount existence of Co–N active sites.

关键词： Metal-organic-framework Resin polymer Oxygen reduction reaction Electrocatalysts

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Quantum Squeezing Induced Optical Nonreciprocity

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Physical Review Letters 2022年第8期128卷 083604-083604页

作者： Lei Tang Jiangshan Tang Mingyuan Chen Franco Nori Min Xiao keyu Xia College of Engineering and Applied Sciences National Laboratory of Solid State Microstructures and Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing 210093 China RIKEN Quantum Computing Center RIKEN Cluster for Pioneering Research Wako-shi Saitama 351-0198 Japan Physics Department The University of Michigan Ann Arbor Michigan 48109-1040 USA Department of Physics University of Arkansas Fayetteville Arkansas 72701 USA Jiangsu Key Laboratory of Artificial Functional Materials Nanjing University Nanjing 210023 China

We propose an all-optical approach to achieve optical nonreciprocity on a chip by quantum squeezing one of two coupled resonator modes. By parametric pumping a χ(2)-nonlinear resonator unidirectionally with a classical coherent field, we squeeze the resonator mode in a selective direction due to the phase-matching condition, and induce a chiral photon interaction between two resonators. Based on this chiral interresonator coupling, we achieve an all-optical diode and a three-port quasicirculator. By applying a second squeezed-vacuum field to the squeezed resonator mode, our nonreciprocal device also works for single-photon pulses. We obtain an isolation ratio of >40 dB for the diode and fidelity of >98% for the quasicirculator, and insertion loss of <1 dB for both. We also show that nonreciprocal transmission of strong light can be switched on and off by a relative weak pump light. This achievement implies a nonreciprocal optical transistor. Our protocol opens up a new route to achieve integrable all-optical nonreciprocal devices permitting chip-compatible optical isolation and nonreciporcal quantum information processing.

关键词： Light-matter interaction Nonlinear optics Quantum optics

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Privacy-Preserving Decision Protocols Based on Quantum Oblivious key Distribution

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Computers, Materials & Continua 2020年第9期64卷 1915-1928页

作者： Kejia Zhang Chunguang Ma Zhiwei Sun Xue Zhang Baomin Zhou Yukun Wang School of Computer Science and Technology Harbin Engineering UniversityHarbin150001China School of Mathematical Science Heilongjiang UniversityHarbin150080China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China Center for Quantum Computing Peng Cheng LaboratoryShenzhen518055China College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China School of Artificial Intelligence Shenzhen PolytechnicShenzhen518055China Department of Electrical and Computer Engineering National University of Singapore117583Singapore

Oblivious key transfer(OKT)is a fundamental problem in the field of secure multi-party *** makes the provider send a secret key sequence to the user obliviously,i.e.,the user may only get almost one bit key in the sequence which is unknown to the ***,a number of works have sought to establish the corresponding quantum oblivious key transfer model and rename it as quantum oblivious key distribution(QOKD)from the well-known expression of quantum key distribution(QKD).In this paper,a new QOKD model is firstly proposed for the provider and user with limited quantum capabilities,where both of them just perform computational basis measurement for single *** we show that the privacy for both of them can be protected,since the probability of getting other’s raw-key bits without being detected is exponentially ***,we give the solutions to some special decision problems such as set-member decision and point-inclusion by announcing the improved shifting strategies followed ***,the further discussions and applications of our ideas have been presented.

关键词： Quantum cryptography quantum computing privacy-preserving quantum oblivious key distribution set-member decision point-inclusion decision

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