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Corrigendum to “Groove-shape-induced bandwidth expansion of spoof surface plasmon polaritons on planar corrugated Goubau line in millimeter-wave range” [Opt. Commun. 380 (2016) 352–356]

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Optics Communications 2018年 407卷 424-424页

作者： Peng Wei XuGuang Guo Cheng Zhang Rui Yang YiMing Zhu Engineering Research Center of Optical Instrument and System Ministry of Education and Shanghai Key Lab of Modern Optical System University of Shanghai for Science and Technology Shanghai 200093 China Key Laboratory of Terahertz Solid-State Technology Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences 865 Changning Road Shanghai 200050 China BOCOM Smart Network Technologies Inc. 20F Guangqi Mansion No. 456 Hongcao Road Xuhui District Shanghai 200030 China

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基于MapReduce的不确定子图查询处理

基于MapReduce的不确定子图查询处理

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第29届中国数据库学术会议

作者： Han Lu 韩璐 Wang Chaokun 王朝坤 Ruan Wenjing 阮文静 Ou Xiaoping 欧晓平 Qiu Ping 仇萍 School of Software Tsinghua University Beijing 100084 清华大学软件学院北京 100084 Tsinghua National Laboratory for Information Science and Technology Beijing 100084 清华信息科学与技术国家实验室(筹) 北京 100084 Key Laboratory for In formation System Security Ministry of Education Beijing 100084 信息系统安全教育部重点实验室(清华大学)北京 100084

图数据结构具有较强的模拟复杂结构的能力，能够很好地表达数据对象之间的关联，广泛地用于各领域非结构化数据建模。为解决大量数据子图查询处理中的不确定情况，本文提出了基于MapReduce的双向匹配查询算法，并提出了有效的索引结构... 详细信息

图数据结构具有较强的模拟复杂结构的能力，能够很好地表达数据对象之间的关联，广泛地用于各领域非结构化数据建模。为解决大量数据子图查询处理中的不确定情况，本文提出了基于MapReduce的双向匹配查询算法，并提出了有效的索引结构以提高查询算法的效率。最后，在真实数据集和合成数据集上的实验结果证明了算法的正确性、高效性和扩展性。

关键词：不确定图数据双向匹配查询算法信息管理性能测试

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Flexible Ferroelectrics: Periodic Wrinkle‐Patterned Single‐Crystalline Ferroelectric Oxide Membranes with Enhanced Piezoelectricity (Adv. Mater. 50/2020)

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Advanced Materials 2020年第50期32卷 2070377-2070377页

作者： Guohua Dong Suzhi Li Tao Li Haijun Wu Tianxiang Nan Xiaohua Wang Haixia Liu Yuxin Cheng Yuqing Zhou Wanbo Qu Yifan Zhao Bin Peng Zhiguang Wang Zhongqiang Hu Zhenlin Luo Wei Ren Stephen J. Pennycook Ju Li Jun Sun Zuo‐Guang Ye Zhuangde Jiang Ziyao Zhou Xiangdong Ding Tai Min Ming Liu The Electronic Materials Research Laboratory Key Laboratory of the Ministry of Education & International Center for Dielectric Research School of Electronic Science and Engineering State Key Laboratory for Mechanical Behavior of Materials the International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi'an Jiaotong University Xi'an 710049 China State Key Laboratory for Mechanical Behavior of Materials Xi'an Jiaotong University Xi'an 710049 China Center for Spintronics and Quantum System State Key Laboratory for Mechanical Behavior of Materials School of Materials Science and Engineering Xi'an Jiaotong University Xi'an 710049 China Department of Materials Science and Engineering National University of Singapore Singapore 117574 Singapore School of Electronic and Information Engineering Tsinghua University Beijing 100084 China State Key Laboratory of Electrical Insulation and Power Equipment Xi'an Jiaotong University No. 28 Xianning West Road Xi'an Shaanxi Province 710049 China National Synchrotron Radiation Laboratory & CAS Key Laboratory of Materials for Energy Conversion Department of Physics University of Science and Technology of China Hefei 230026 China Department of Nuclear Science and Engineering and Department of Materials Science and Engineering Massachusetts Institute of Technology Cambridge MA 02139 USA Department of Chemistry & 4D LABS Simon Fraser University Burnaby BC V5A 1S6 Canada The State Key Laboratory for Manufacturing Systems Engineering the International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi'an Jiaotong University Xi'an 710049 China

In article number 2004477, Ziyao Zhou, Xiangdong Ding, Tai Min, Ming Liu, and co‐workers present a periodically wrinkled structure that combines flexible ferroelectric membranes and organic elastomers. Enhanced piezoelectricity is observed at the sites of the peaks and valleys of the wrinkles where the largest strain gradient is generated. The wrinkle‐patterned ferroelectric membranes offer an ideal platform to explore the periodic‐electric‐potential‐induced functions in flexible electrical and optical devices.

关键词： ferroelectrics flexoelectricity freestanding oxides piezoelectricity wrinkles

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[email protected] x core-shell nanowires as a non-precious electrocatalyst for upgrading 5-hydroxymethylfurfural into 2,5-furandicarboxylic acid

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Applied Catalysis B: Environmental 2020年 261卷

作者： Lifang Gao Zhenbang Liu Jinling Ma Lijie Zhong Zhongqian Song Jianan Xu Shiyu Gan Dongxue Han Li Niu Center for Advanced Analytical Science School of Chemistry and Chemical Engineering Guangzhou University Guangzhou 510006 PR China School of Civil Engineering Guangzhou University Guangzhou 510006 PR China State Key Laboratory of Electroanalytical Chemistry c/o Engineering Laboratory for Modern Analytical Techniques Changchun Institute of Applied Chemistry Chinese Academy of Sciences Changchun 130022 Jilin PR China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing City 400044 PR China

A key challenge for the conversion of 5-hydroxymethylfurfural (HMF) into value-added 2,5-furandicarboxylic acid (FDCA) is improving the sluggish kinetics of selective oxidation alcohol groups. Electrocatalysis has been proved to be a green and efficient strategy for heterogeneous synthetic chemistry. Herein, we report an electrocatalyst of [email protected] x core-shell nanowires for efficiently upgrading HMF into FDCA. The [email protected] x features conductive NiSe nanowires as a core and active NiO x as a shell, showing a smaller Tafel slope of 23 mV dec −1 accompanying with a near-quantitative yield of FDCA and 99% Faradaic efficiency (FE). X-ray photoelectron spectroscopy unveils the high valence of Ni species in the NiO x shell may be the active sites. Further integrated electrolyzer can produce FDCA and hydrogen simultaneously, showing a 100% FE even after six successive cycles, disclosing robust stability. All these results demonstrate [email protected] x core-shell nanowires as a promising robust non-precious electrocatalyst for highly efficient biomass transformation.

关键词： Electrocatalysis 5-hydroxymethylfurfural [email protected] x core-shell Robust stability 2,5-furandicarboxylic acid

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Spike-burst chimera states in an adaptive exponential integrate-and-fire neuronal network

arXiv

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arXiv 2019年

作者： Santos, Moises S. Protachevicz, Paulo R. Iarosz, Kelly C. Caldas, Iberê L. Viana, Ricardo L. Borges, Fernando S. Ren, Hai-Peng Szezech, José D. Batista, Antonio M. Grebogi, Celso Department of Physics Federal University of Paraná CuritibaPR80060-000 Brazil Graduate in Science Program - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology Xi'an710048 China Xian Technological University Xi'an710021 China Graduate in Science Program - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute for Complex Systems and Mathematical Biology King's College University of Aberdeen AberdeenAB24 3UE United Kingdom

Chimera states are spatiotemporal patterns in which coherence and incoherence coexist. We observe the coexistence of synchronous (coherent) and desynchronous (incoherent) domains in a neuronal network. The network is composed of coupled adaptive exponential integrate-and-fire neurons that are connected by means of chemical synapses. In our neuronal network, the chimera states exhibit spatial structures both with spikes and bursts activities. Furthermore, those desynchronised domains not only have either spike or burst activity, but we show that the structures switch between spikes and bursts as the time evolves. Moreover, we verify the existence of multicluster chimera states. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural networks

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Brain–Machine Interfaces: Silk-Enabled Conformal Multifunctional Bioelectronics for Investigation of Spatiotemporal Epileptiform Activities and Multimodal Neural Encoding/Decoding (Adv. Sci. 9/2019)

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Advanced science 2019年第9期6卷 1970056-1970056页

作者： Zhifeng Shi Faming Zheng Zhitao Zhou Meng Li Zhen Fan Huanpeng Ye Shan Zhang Ting Xiao Liang Chen Tiger H. Tao Yun-Lu Sun Ying Mao Department of Neurosurgery Huashan Hospital of Fudan University Wulumuqi Zhong Road 12 Shanghai 200040 China State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China The Rowland Institute Harvard University Cambridge MA 02142 USA State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai 200240 China School of Graduate Study University of Chinese Academy of Sciences Beijing 100049 China The Key Laboratory of Resource Chemistry of Ministry of Education Shanghai Normal University Shanghai 200234 China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing 100049 China School of Physical Science and Technology Shanghai Tech University Shanghai 200031 China State Key Laboratory of Integrated Optoelectronics College of Electronic Science and Engineering Jilin University 2699 Qianjin Street Changchun 130012 China

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Hybrid Chloroantimonates(III): Thermally Induced Triple‐Mode Reversible Luminescent Switching and Laser‐Printable Rewritable Luminescent Paper

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Angewandte Chemie 2019年第29期131卷

作者： Zeping Wang Zhizhuan Zhang Luqi Tao Nannan Shen Bing Hu Liaokuo Gong Jianrong Li Xianping Chen Xiaoying Huang State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of Matter The Chinese Academy of Sciences Fuzhou Fujian 350002 P. R. China Key Laboratory of Optoelectronic Technology & Systems Education Ministry of China Chongqing University and State Key Laboratory of Power Transmission Equipment and System Security Chongqing University Chongqing 400044 P. R. China College of Chemistry and Materials Science Fujian Normal University Fuzhou Fujian 350002 P. R. China University of Chinese Academy of Sciences Beijing 100049 P. R. China

Two hybrid chloroantimonates(III), [Bzmim] 3 SbCl 6 ( 1 , Bzmim=1‐benzyl‐3‐methylimidazolium, T m1 =410 K) and [Bzmim] 2 SbCl 5 ( 2 , T m2 =348 K) are presented. 1 exhibits green emission (quantum efficiency of 87.5 %); 2 exhibits blue and red emissions under the irradiation of 310 and 396 nm light, respectively. Using different cooling methods, crystalline 1 and IL@2 (IL=ionic liquid of [Bzmim]Cl) could be generated from the molten 1 . Reversible structural and PL transformation triggered by moisture or heat was observed between 1 and IL@2 . Such PL switching, combined with the crystallization‐induced PL properties of 1 and 2 , resulted in the firstly reported triple‐mode reversible PL switching, that is, on–off (T>T m1 ), color switching (T

关键词： Antimon Fälschungsbekämpfung Photolumineszenzschalten Reversible Strukturumwandlung Thermisches Schreiben

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The Study of Quantitative Assessment of Regional Eco-environmental Vulnerability Based on Multi-source Remote Sensing

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IOP Conference Series: Earth and Environmental science 2017年第1期94卷

作者： Wu Xu He Binbin Kan Aike Cirenluobu Yang Xiao College of Resources and Environment University of Electronic Science and Technology of China Chengdu No.2006 XiYuan Avenue P.R.China College of Information Science & Technology Chengdu University of Technology Chengdu Dongsanlu Erxianqiao P.R.China Institute of Information Science and Technology of Tibet Autonomous Region Lhasa No.19 West Beijing Road P.R.China College of Geophysics Chengdu University of Technology Chengdu Dongsanlu Erxianqiao P.R.China State Key Laboratory of Resource and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Beijing No.11 Datun Road P.R.China

How to estimate vulnerability of eco-environment quickly and accurately is an important research to predict the trend of environmental change in the future. Based on the analysis of the previous methods of eco-environment assessment, we tried to build a quantitative assessment model of eco-environment vulnerability by multi-source remote sensing data. The model focuses on extracting the change information of vegetation and land cover types from remote sensing (RS) data, and reveals the law of eco-environment vulnerability change. In the process of building the model, the correlation between normalized difference vegetation index (NDVI) and topographic data was analysed. The nonlinear regression method was used to estimating vegetation coverage taken as one of the main parameters of the model. And then, the model was applied to a specific study area. The quantitative assessment used Multi temporal data obtained to calculate the vulnerability values. It described the spatial distribution and variation characteristics of eco-environmental vulnerability in this region. We also estimate the accuracy and stability of the model. The calculation results show that we can quickly evaluate regional eco-environmental vulnerability and improve the efficiency of ecological environment monitoring through our proposed model.

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Solar Driven Spintronics: Sunlight Control of Interfacial Magnetism for Solar Driven Spintronic Applications (Adv. Sci. 24/2019)

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Advanced science 2019年第24期6卷 1970147-1970147页

作者： Yifan Zhao Shishun Zhao Lei Wang Ziyao Zhou Junxue Liu Tai Min Bin Peng Zhongqiang Hu Shengye Jin Ming Liu Electronic Materials Research Laboratory Key Laboratory of the Ministry of Education and International Center for Dielectric Research School of Electronic and Information Engineering and State Key Laboratory for Mechanical Behavior of Materials Xi'an Jiaotong University Xi'an 710049 China International Joint Laboratory for Micro/Nano Manufacture and Measurement Technology Xi'an Jiaotong University Xi'an 710049 China Center for Spintronics and Quantum System State Key Laboratory for Mechanical Behavior of Materials School of Materials Science and Engineering Xi'an Jiaotong University Xi'an Shaanxi 710049 China State Key Laboratory of Molecular Reaction Dynamics and Collaborative Innovation Center of Chemistry for Energy Materials (iChEM) Dalian Institute of Chemical Physics Chinese Academy of Sciences 457 Zhongshan Rd. Dalian 116023 China

In article number https://***/10.1002/advs.201901994 , Ziyao Zhou, Ming Liu, and co‐workers propose a prototype photovoltaic spintronic device with an optical‐magneto‐electric tri‐coupled photovoltaic/magnetic thin film heterojunction, where magnetism can be manipulated directly by sunlight. Both in situ experiments and the first principle calculation results reveal that the photogenerated electrons doping in the cobalt film alter the band filling of this ferromagnetic film and manipulate the magnetization and magnetic anisotropy effectively.

关键词： ferromagnetic resonance low power magnetoelectric coupling organics solar cells

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Advancing image understanding in poor visibility environments: A collective benchmark study

arXiv

引用

arXiv 2019年

作者： Yang, Wenhan Yuan, Ye Ren, Wenqi Liu, Jiaying Scheirer, Walter J. Wang, Zhangyang Zhang, Taiheng Zhong, Qiaoyong Xie, Di Pu, Shiliang Zheng, Yuqiang Qu, Yanyun Xie, Yuhong Chen, Liang Li, Zhonghao Hong, Chen Jiang, Hao Yang, Siyuan Liu, Yan Qu, Xiaochao Wan, Pengfei Zheng, Shuai Zhong, Minhui Su, Taiyi He, Lingzhi Guo, Yandong Zhao, Yao Zhu, Zhenfeng Liang, Jinxiu Wang, Jingwen Chen, Tianyi Quan, Yuhui Xu, Yong Liu, Bo Liu, Xin Sun, Qi Lin, Tingyu Li, Xiaochuan Lu, Feng Gu, Lin Zhou, Shengdi Cao, Cong Zhang, Shifeng Chi, Cheng Zhuang, Chubin Lei, Zhen Li, Stan Z. Wang, Shizheng Liu, Ruizhe Yi, Dong Zuo, Zheming Chi, Jianning Wang, Huan Wang, Kai Liu, Yixiu Gao, Xingyu Chen, Zhenyu Guo, Chang Li, Yongzhou Zhong, Huicai Huang, Jing Guo, Heng Yang, Jianfei Liao, Wenjuan Yang, Jiangang Zhou, Liguo Feng, Mingyue Qin, Likun Wangxuan Institute of Computer Technology Peking University Beijing100080 China Department of Computer Science and Engineering Texas A&M University TX77843 United States State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Department of Computer Science and Engineering University of Notre Dame Notre DameIN46556 United States Department of Mechanical Engineering Zhejiang University Hangzhou310027 China Hikvision Research Institute Hangzhou310051 China Mtlab Meitu Inc. Beijing100080 China Insitute of Information Science Beijing Jiaotong University Beijing100044 China Department of Computer Science and Technology Tongji University Shanghai201804 China XPENGMOTORS Beijing China School of Computer Science and Engineering at South China University of Technology Guangzhou510006 China Tencent AI Lab Shenzhen518000 China Institute of Automation Chinese Academy of Sciences Beijing100190 China Northeastern University Shenyang110819 China Nanyang Technological University Singapore639798 Big Data Center State Grid Corporation of China Beijing China Winsense Inc. Beijing100080 China University of Chinese Academy of Sciences Beijing100049 China Department of Informatics Technical University of Munich Garching85748 Germany Institute of Microelectronics Chinese Academy of Sciences Beijing100190 China China Electric Power Research Institute Beijing100031 China Westlake University Hangzhou310024 China Department of Computer Science Durham University Durham United Kingdom Australian National University ActonACT0200 Australia Sunway-AI Co. Ltd Zhuhai China Chinese Academy of Sciences R&D Center for Internet of Things Wuxi214200 China

Existing enhancement methods are empirically expected to help the high-level end computer vision task: however, that is observed to not always be the case in practice. We focus on object or face detection in poor visibility enhancements caused by bad weathers (haze, rain) and low light conditions. To provide a more thorough examination and fair comparison, we introduce three benchmark sets collected in real-world hazy, rainy, and lowlight conditions, respectively, with annotated objects/faces. We launched the UG2+challenge Track 2 competition in IEEE CVPR 2019, aiming to evoke a comprehensive discussion and exploration about whether and how low-level vision techniques can benefit the high-level automatic visual recognition in various scenarios. To our best knowledge, this is the first and currently largest effort of its kind. Baseline results by cascading existing enhancement and detection models are reported, indicating the highly challenging nature of our new data as well as the large room for further technical innovations. Thanks to a large participation from the research community, we are able to analyze representative team solutions, striving to better identify the strengths and limitations of existing mindsets as well as the future directions. Copyright © 2019, The Authors. All rights reserved.

关键词： Object detection

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