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arXiv 2020年

作者： Cui, Shaowei Wang, Rui Wei, Junhang Li, Fanrong Wang, Shuo State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Further Technology Universty of Chinese Academy of Sciences Beijing100190 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

Humans can quickly determine the force required to grasp a deformable object to prevent its sliding or excessive deformation through vision and touch, which is still a challenging task for robots. To address this issue, we propose a novel 3D convolution-based visual-tactile fusion deep neural network (C3D-VTFN) to evaluate the grasp state of various deformable objects in this paper. Specifically, we divide the grasp states of deformable objects into three categories of sliding, appropriate and excessive. Also, a dataset for training and testing the proposed network is built by extensive grasping and lifting experiments with different widths and forces on 16 various deformable objects with a robotic arm equipped with a wrist camera and a tactile sensor. As a result, a classification accuracy as high as 99.97% is achieved. Furthermore, some delicate grasp experiments based on the proposed network are implemented in this paper. The experimental results demonstrate that the C3D-VTFN is accurate and efficient enough for grasp state assessment, which can be widely applied to automatic force control, adaptive grasping, and other visual-tactile spatiotemporal sequence learning problems. Copyright © 2020, The Authors. All rights reserved.

关键词： Deformation

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High SNR Φ-OTDR Based on Frequency and Wavelength Diversity with Differential Vector Aggregation Method

IEEE Photonics Journal

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IEEE Photonics Journal 2020年第6期12卷 1页

作者： Gu, Jinfeng Lu, Bin Yang, Junqi Wang, Zhaoyong Ye, Lei Ye, Qing Qu, Ronghui Cai, Haiwen Key Laboratory of Space Laser Communication and Detection Technology Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing100049 China

Phase-demodulated phase-sensitive time domain reflectometer (Φ-OTDR) has attracted much attention because of its linear relationship between the phase variation and the amplitude of the vibration. However, it suffers from limited signal-to-noise ratio (SNR) and signal fading, due to the inherent low Rayleigh scattering coefficient and randomly spatial non-uniform distribution of the refractive index. Here, a Φ-OTDR system based on wavelength diversity is demonstrated, which can enhance the SNR and reduce signal fading simultaneously by using differential vector aggregation method. A theoretical model is built, and the linear relationship between SNR improvement and diversity scale is analyzed. The verification experiment is conducted, and in the further experiments, the frequency and wavelength diversity technology are cascaded to achieve a diversity scale of 20. After differential vector aggregation method, the external disturbance signal is well reconstructed and the noise floor is reduced by 13.4 dB, which is basically consistent with the theoretical analysis. © 2009-2012 IEEE.

关键词： Signal to noise ratio

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Dynamic Multi-Dimensional Scaling of 30+ Year Evolution of Chinese Urban Systems: Patterns and Performance

SSRN

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SSRN 2022年

作者： Ning, Ying Liu, Shuguang Smith, Andrew R. Qiu, Yi Gao, Haiqiang Lu, Yonglong Yuan, Wenping Feng, Shuailong Changsha410004 China College of Life Science and Technology CSUFT Changsha410004 China Environment Centre Wales School of Natural Sciences Bangor University BangorLL57 2UW United Kingdom College of Business CSUFT Changsha410004 China State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing100085 China School of Atmospheric Sciences Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Sun Yat-sen University Guangdong Zhuhai510245 China

Understanding the co-evolution and organizational dynamics of urban properties (i.e., urban scaling) is the science base for pursuing synergies toward sustainable cities and society. The generalization of urban scaling theory yet requires more studies from various developmental regimes and across time. Here, we extend the universality proposition by exploring the evolution of longitudinal and transversal scaling of Chinese urban attributes between 1987 and 2018 using a global artificial impervious area (GAIA) remotely sensed dataset, harmonized night light data (NTL), and socioeconomic data, and revealed agreements and disagreements with theories. The superlinear relationship of urban area and population often considered as an indicator of wasting land resources (challenging the universality theory βc=2/3), is in fact the powerful impetus (capital raising) behind the concurrent superlinear expansion of socio-economic metabolisms (e.g., GDP, total wage) in a rapidly urbanizing country that has not yet reached equilibrium. Similarly, infrastructural variables associated with public services, such as hospitals and educational institutions, exhibited some deviations as well and were scaled linearly. However, the temporal narrowing of spatial deviations, such as the decline in urban land diseconomies of scale and the stabilization of economic output, clearly indicates the Chinese government’s effort in charting urban systems toward balanced and sustainable development across the country. More importantly, the transversal sublinear scaling of areal-based socio-economic variables was inconsistent with the theoretical concept of increasing returns to scale, thus validating the view that a single measurement cannot unravel the intricate web of diverse urban attributes and urbanization. Our dynamic urban scaling analysis across space and through time in China provides new insights into the evolving nexus of urbanization, socioeconomic development, and national policies. © 202

关键词： Urban growth

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Task-feature collaborative learning with application to personalized attribute prediction

arXiv

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arXiv 2020年

作者： Yang, Zhiyong Xu, Qianqian Cao, Xiaochun Huang, Qingming State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen518055 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China University of Chinese Academy of Sciences Beijing101408 Peng Cheng Laboratory Shenzhen518055 China

As an effective learning paradigm against insufficient training samples, Multi-Task Learning (MTL) encourages knowledge sharing across multiple related tasks so as to improve the overall performance. In MTL, a major challenge springs from the phenomenon that sharing the knowledge with dissimilar and hard tasks, known as negative transfer, often results in a worsened performance. Though a substantial amount of studies have been carried out against the negative transfer, most of the existing methods only model the transfer relationship as task correlations, with the transfer across features and tasks left unconsidered. Different from the existing methods, our goal is to alleviate negative transfer collaboratively across features and tasks. To this end, we propose a novel multi-task learning method called Task-Feature Collaborative Learning (TFCL). Specifically, we first propose a base model with a heterogeneous block-diagonal structure regularizer to leverage the collaborative grouping of features and tasks and suppressing inter-group knowledge sharing. We then propose an optimization method for the model. Extensive theoretical analysis shows that our proposed method has the following benefits: (a) it enjoys the global convergence property and (b) it provides a block-diagonal structure recovery guarantee. As a practical extension, we extend the base model by allowing overlapping features and differentiating the hard tasks. We further apply it to the personalized attribute prediction problem with fine-grained modeling of user behaviors. Finally, experimental results on both simulated dataset and real-world datasets demonstrate the effectiveness of our proposed method. Copyright © 2020, The Authors. All rights reserved.

关键词： Knowledge management

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A Statistical analysis of the Returning Flux Tubes in the Jovian Magnetosphere Based on Juno Observations

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The Astrophysical Journal 2025年第2期986卷 115-115页

作者： Dong-Wen He Chao Yue Hao-Bo Fu Fan Yang Michel Blanc Xu-Zhi Zhou Qiu-Gang Zong School of Earth and Space Sciences Peking University Beijing People’s Republic of China yuechao@*** State Key Laboratory of Solar Activity and Space Weather National Space Science Center Chinese Academy of Sciences Beijing People’s Republic of China Institut de Recherche en Astrophysique et Planetologie (IRAP) CNRS-Universite Toulouse III Paul Sabatier-CNES Toulouse France State Key Laboratory of Lunar and Planetary Sciences Macau University of Science and Technology Macau People’s Republic of China

The interchange process is an important mechanism for radial transport of plasma in the magnetospheres of the gas giants, namely Jupiter and Saturn. During this process, dense and cold flux tubes that move outwards are replaced by returning flux tubes with warm and tenuous plasma. In this study, we conduct a statistical analysis of the magnetic variation and plasma properties inside the returning flux tubes, based on the observations from magnetometer (MAG) and JADE onboard the Juno spacecraft during its first 45 perijove traverses. We detect the returning flux tubes by recognizing the low-energy electron flux sudden drop, within the range of M < 20 R_J (Jupiter radii). The results have illustrated that the flux tubes with increased magnetic field account for the majority of the events. There is no significant relationship between the events with increased or decreased magnetic field and magnetic latitude, and both types of events are observed mostly near the equatorial plane, while events with depressed magnetic field are more frequently observed at larger distances from Jupiter with longer time duration (or larger flux tube volume). Furthermore, the crossover energy separating decreased low-energy electron flux and increased high-energy electron flux of the returning flux tubes is around several keV, depending on the type of magnetic field variation. These results provide great insight into the mass and magnetic flux transport in the inner Jovian magnetosphere.

关键词：

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Traffic Control Task Scheduling Optimization Approach of Urban Road Intersection Based on Edge Computing

Traffic Control Task Scheduling Optimization Approach of Urb...

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Artificial Intelligence, Networking and Information technology (AINIT), International Seminar on

作者： Xiang Fu Fei Wang Nan Ji Yilong Ren School of Transportation Science and Engineering Beihang University BUAA Beijing China Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing China Intelligent Transport System (ITS) R & D Center Shanghai Urban Construction Design and Research Institute (Group) Co. Ltd. Shanghai China

ISBN: (纸本)9781665412971

With the development of Connected Automated Vehicles (CAV), there will be a long period of mixed driving, which causes the traffic control task at intersections becomes much more complicated. The control tasks would include not only the traffic signal timing optimization but also the computing tasks for different levels of vehicles. Current control task management methods are proved to be inferior to solve this problem. In this paper, we propose an intersection control task scheduling optimization approach based on edge computing. Firstly, the traffic control edge computing system for intersections is constructed. Then, different types of control tasks are listed. Criticality and timeliness are introduced to calculate the control task's dynamic priority. The control task scheduling optimization model, which considering these two parameters is proposed. At last, the improved Hungarian algorithm is applied to solve the proposed task scheduling optimization model. Simulation results show that our proposed methods can effectively reduce task processing costs and ensure the critical tasks execute firstly.

关键词： Processor scheduling Computational modeling Heuristic algorithms Traffic control Scheduling Timing Task analysis

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ScMicrobesAtlas: A comprehensive microbial atlas at single-cell resolution in human disease contexts

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Genes & Diseases 2025年

作者： Jinyang Liu Rui Hou Lei Ji Yue Gong Pan Li Peiwen Liu Jinxin Dong Hongzhe Guo Yun Zhang Junlin Xu Tingting Hui Haotian Tian Yankun Liu Meijun Zhang Geng Tian Jialiang Yang Geneis Beijing Co. Ltd. Beijing 100102 China College of Computer Science and Electronic Engineering Hunan University Changsha Hunan 410082 China Beijing Zhilan Technology Co. Ltd. Beijing 102206 China Department of Medical Molecular Diagnosis Tangshan People's Hospital Tangshan Hebei 063001 China Tangshan Key Laboratory of Precision Medicine Testing Tangshan People's Hospital Tangshan Hebei 063001 China

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Vacuum-tuned-atmosphere induced assembly of Au@Ag core/shell nanocubes into multi-dimensional superstructures and the ultrasensitive IAPP proteins SERS detection

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Nano Research 2019年第6期12卷 1375-1379页

作者： Meng Xu Guopeng Tu Muwei Ji Xiaodong Wan Jiajia Liu Jia Liu Hongpan Rong Yanlian Yang Chen Wang Jiatao Zhang Beijing Key Laboratory of Construction-Tailorable Advanced Functional Materials and Green Applications Experim ental Center of Advanced Materials School of Materials Science & EngineeringBeijing Institute of TechnologyBeijing 100081China Institute of Low-dimensional Materials Genome Initiative College of chemistry and environmental engineeringShenzhen UniversityGuangdong Shenzhen 518060China Graduate School at Shenzhen Tsinghua UniversityShenzhen 518055China National Center for Nanoscience and Technology (NCNST) Chinese Academy of SciencesBeijing 100190China

Utilizing vacuum-tuned-atmosphere induced dip coating method,we achieve the cross-dimensional macroscopic diverse self-assemblies by using one building block with one chemical *** modulating the vacuum degree,colloid concentration and evaporation atmosphere,Au@Ag core/shell nanocubes (NCs) can controllably assemble into diverse multi-dimensional *** 0.08 MPa,we obtained the two-dimensional (2D) stepped superstructures with continuously tunable step *** addition,we generated a series of tailorable nanoscale-roughened 2D Au@Ag NCs superstructures at 0.04 MPa,which exhibited the label-free ultrasensitive SERS detection for the different mutants of IAPP8-37 *** 0.01 MPa,we obtained the cross-dimensional tailorable Au@Ag NCs assemblies from random to macroscale 2D and three-dimensional (3D) densest superstructures by adjusting the capping ligand-environmental molecule *** is a flexible method to generate as-prepared Au@Ag core/shell NCs into well-defined macroscopic diverse superstructures and to promote the exploitation into biological applications.

关键词： superstructure Au@Ag core/shell nanocubes (NCs) self-assembly surface enhanced Raman scattering (SERS) detection islet arnyloid-like polypeptide

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Allying cobalt nanoclusters with carbon nanofibers for selectively electrocatalytic hydrogenation of unsaturated aldehyde with water as hydrogen source

Materials Today Catalysis

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Materials Today Catalysis 2025年 9卷

作者： Xinyu Yang Sheng-Hua Zhou Xiaofang Li Xin-Tao Wu Qi-Long Zhu State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences (CAS) Fuzhou 350002 China University of Chinese Academy of Sciences Beijing 100049 China School of Chemistry and Chemical Engineering Jiangsu University of Technology Changzhou 213001 China School of Materials Science and Engineering Zhejiang Sci-Tech University Hangzhou 310018 China

The electrocatalytic hydrogenation of α, β-unsaturated aldehydes has attracted significant attention, yet the design of electrocatalysts with selective adsorption over C C or C O bond remaining a challenging task. In this study, the Co nanoclusters anchored onto the nitrogen-doped porous carbon nanofibers were elaborately fabricated for efficient electrocatalytic hydrogenation. A kinetically driven mono-micelle-oriented self-assembly method was applied to synthesize the polymer nanofibers as the accommodation for Co 2 + . The stepwise pyrolysis of Co 2+ /polymer nanofibers with dicyandiamide yielded the evenly distributed Co nanoclusters with an average size of ∼4 nm over the nitrogen-doped porous carbon nanofibers. Benefited from the high activity of the Co nanoclusters and their rapid electron communication with the nitrogen-doped porous carbon nanofibers, this electrocatalyst demonstrated excellent performance in the selectively electrocatalytic hydrogenation of cinnamaldehyde to hydrocinnamaldehyde, achieving a high selectivity of 90.9 % and a conversion of 68.2 % at 12 mA cm −2 . The further in-situ spectroscopy analysis and density functional theory calculations revealed the more preferred adsorption of C C bond and easier water dissociation to give the active H atoms over the Co nanoclusters, which shed light on the hydrogenation mechanism over this electrocatalyst. Our study can provide a new insight in catalyst design for electrocatalytic hydrogenation reaction.

关键词： Nanoclusters Nitrogen-doped carbon nanofibers Cinnamaldehyde Hydrocinnamaldehyde Selectively electrocatalytic hydrogenation

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Deep Insights into the Failure Mechanisms in Field-cycled Ferroelectric Hf0.5Zr0.5O2 Thin Film: TDDB Characterizations and First-Principles Calculations

Deep Insights into the Failure Mechanisms in Field-cycled Fe...

引用

International Electron Devices Meeting (IEDM)

作者： Wei Wei Weiqiang. Zhang Fei Wang Xiaolei Ma Qianwen Wang Pengpeng Sang Xuepeng Zhan Yuan Li Lu Tai Qing Luo Hangbing Lv Jiezhi Chen School of Information Science and Engineering Shandong University Qingdao China Key Laboratory of Microelectronic Devices and Integrated Technology Institute of Microelectronics of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728188881

ISBN: (纸本)9781728188898

To address the failure mechanisms in ferroelectric devices, this work presents a systematical study on Hf 0.5 Zr 0.5 O 2 -based ferroelectric memory. Firstly, by detail electrical characterizations of P-V and C-V curves in field-cycled devices, three dominant failure modes can be well distinguished. Then, by combining the TDDB measurements and first-principles calculations, it is found that, 1) the annealing temperature has large impacts on the initial defects concentrations while weakly affect the trap generation rate; 2) the breakdown paths take place mainly in the amorphous regions, which could generate reconfigurable filaments and cause RRAM properties; 3) temporary recovered ferroelectricity during cycling can be explained by considering the unstable breakdown paths generated at the grain boundary.

关键词： Temperature measurement Annealing Voltage measurement Capacitance-voltage characteristics Current measurement Failure analysis Weibull distribution

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