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Functional Separators: Rational design of Nanostructured Functional Interlayer/Separator for advanced Li–S Batteries (Adv. Funct. Mater. 38/2018)

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advanced Functional Materials 2018年第38期28卷

作者： Yo Chan Jeong Jae Ho Kim Seunghoon Nam Chong Rae Park Seung Jae Yang Carbon Nanomaterials Design Laboratory Research Institute of Advanced Materials and Department of Materials Science and Engineering Seoul National University Seoul 151‐744 Republic of Korea Department of Applied Nano Mechanics Nano Mechanical Systems Research Division Korea Institute of Machinery and Materials (KIMM) Daejeon 34103 Republic of Korea WCSL of Integrated Human Airway‐on‐a‐chip Department of Chemical Engineering Inha University Incheon 402‐751 Republic of Korea

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Author Correction: The power of genetic diversity in genome-wide association studies of lipids

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Nature 2023年第7965期618卷 E19-E20页

作者： Sarah E Graham Shoa L Clarke Kuan-Han H Wu Stavroula Kanoni Greg J M Zajac Shweta Ramdas Ida Surakka Ioanna Ntalla Sailaja Vedantam Thomas W Winkler Adam E Locke Eirini Marouli Mi Yeong Hwang Sohee Han Akira Narita Ananyo Choudhury Amy R Bentley Kenneth Ekoru Anurag Verma Bhavi Trivedi Hilary C Martin Karen A Hunt Qin Hui Derek Klarin Xiang Zhu Gudmar Thorleifsson Anna Helgadottir Daniel F Gudbjartsson Hilma Holm Isleifur Olafsson Masato Akiyama Saori Sakaue Chikashi Terao Masahiro Kanai Wei Zhou Ben M Brumpton Humaira Rasheed Sanni E Ruotsalainen Aki S Havulinna Yogasudha Veturi QiPing Feng Elisabeth A Rosenthal Todd Lingren Jennifer Allen Pacheco Sarah A Pendergrass Jeffrey Haessler Franco Giulianini Yuki Bradford Jason E Miller Archie Campbell Kuang Lin Iona Y Millwood George Hindy Asif Rasheed Jessica D Faul Wei Zhao David R Weir Constance Turman Hongyan Huang Mariaelisa Graff Anubha Mahajan Michael R Brown Weihua Zhang Ketian Yu Ellen M Schmidt Anita Pandit Stefan Gustafsson Xianyong Yin Jian'an Luan Jing-Hua Zhao Fumihiko Matsuda Hye-Mi Jang Kyungheon Yoon Carolina Medina-Gomez Achilleas Pitsillides Jouke Jan Hottenga Gonneke Willemsen Andrew R Wood Yingji Ji Zishan Gao Simon Haworth Ruth E Mitchell Jin Fang Chai Mette Aadahl Jie Yao Ani Manichaikul Helen R Warren Julia Ramirez Jette Bork-Jensen Line L Kårhus Anuj Goel Maria Sabater-Lleal Raymond Noordam Carlo Sidore Edoardo Fiorillo Aaron F McDaid Pedro Marques-Vidal Matthias Wielscher Stella Trompet Naveed Sattar Line T Møllehave Betina H Thuesen Matthias Munz Lingyao Zeng Jianfeng Huang Bin Yang Alaitz Poveda Azra Kurbasic Claudia Lamina Lukas Forer Markus Scholz Tessel E Galesloot Jonathan P Bradfield E Warwick Daw Joseph M Zmuda Jonathan S Mitchell Christian Fuchsberger Henry Christensen Jennifer A Brody Mary F Feitosa Mary K Wojczynski Michael Preuss Massimo Mangino Paraskevi Christofidou Niek Verweij Jan W Benjamins Jorgen Engmann Rachel L Kember Roderick C Slieker Ken Sin Lo Nuno R Zilhao Phuong Le Marcus E Kleber Graciela E Delgado Shaofeng Huo Dai Department of Internal Medicine Division of Cardiology University of Michigan Ann Arbor MI USA. VA Palo Alto Health Care System Palo Alto CA USA. Department of Medicine Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Department of Biostatistics and Center for Statistics Genetics University of Michigan Ann Arbor MI USA. Department of Genetics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Clinical Pharmacology William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK. Endocrinology Boston Children's Hospital Boston MA USA. Medical and Population Genetics Broad Institute Cambridge MA USA. Department of Genetic Epidemiology University of Regensburg Regensburg Germany. McDonnell Genome Institute and Department of Medicine Washington University St Louis MO USA. Department of Precision Medicine Division of Genome Science National Institute of Health Cheongju-si South Korea. Tohoku Medical Megabank Organization Tohoku University Sendai Japan. Sydney Brenner Institute for Molecular Bioscience Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa. Center for Research on Genomics and Global Health National Human Genome Research Institute National Institutes of Health Bethesda MD USA. Blizard Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Wellcome Sanger Institute Hinxton UK. Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA. Atlanta VA Health Care System Decatur GA USA. Malcolm Randall VA Medical Center Gainesville FL USA. Division of Vascular Sur

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Swarm Intelligence Algorithm Inspired by Route Choice Behavior

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Journal of Bionic engineering 2016年第4期13卷 669-678页

作者： Daxin Tian Junjie Hu Zhengguo Sheng Yunpeng Wang Jianming Ma Jian Wang Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China School of Transportation Science and Engineering Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beihang University Beijing 1 O0191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Nanjing 210096 China Department of Engineering and Design University of Sussex Brighton BN1 9RH UK The Texas Department of Transportation Austin TX78750 USA College of Computer Science and Technology Jilin University Changchun 130012 China

Travelers＇ route choice behavior, a dynamical learning process based on their own experience, traffic information, and influence of others, is a type of cooperation optimization and a constant day-to-day evolutionary process. Travelers adjust their route choices to choose the best route, minimizing travel time and distance, or maximizing expressway use. Because route choice behavior is based on human beings, the most intelligent animals in the world, this swarm behavior is expected to in- corporate more intelligence. Unlike existing research in route choice behavior, the influence of other travelers is considered for updating route choices on account of the reality, which makes the route choice behavior from individual to swarm. Anew swarm intelligence algorithm inspired by travelers＇ route choice behavior for solving mathematical optimization problems is introduced in this paper. A comparison of the results of experiments with those of the classical global Particle Swarm Optimization （PSO） algorithm demonstrates the efficacy of the Route Choice Behavior Algorithm （RCBA）. The novel algorithm provides a new approach to solving complex problems and new avenues for the study of route choice behavior.

关键词： swarm intelligence route choice behavior particle swarm optimization mathematical optimization

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design and kinematic simulation of a novel exoskeleton rehabilitation hand robot

Design and kinematic simulation of a novel exoskeleton rehab...

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IEEE International Conference on Mechatronics and Automation

作者： Shuxiang Guo Weijie Zhang Jian Guo Jiange Gao Yuye Hu Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Biomedical Robot Laboratory Tianjin University of Technology Tianjin China Intelligent Mechanical Systems Engineering Department Kagawa University Takamatsu Japan Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System Tianjin China

ISBN: (纸本)9781509023974

The rehabilitation exoskeleton robot is more and more used in the assisting stroke patients in implementing rehabilitation training. In this paper, a novel exoskeleton hand robot which was driven by cable has been proposed to aim at helping varieties of paralyses patients recover motor function. This exoskeleton hand rehabilitation robot system mainly consists of exoskeleton hand robot, EEG system, motor controllers unit, some sensors and a workstation. And the hand exoskeleton mechanism was portable, wearable and adjustable for patients doing home rehabilitation training. Based on the parameters from human hand, the kinematic model of hand robot was established to be used in designing and the kinematic simulation experiments about this exoskeleton hand robot were done. Through the simulation software ADAMS (Automatic Dynamic Analysis of Mechanical systems), the parameters of position, angle velocity and angle accelerated velocity (PVA) of proximate inter-phalanger (DIP) distal inter-phalanger joint were simulated. And then, the movement situation of the DIP joint was obtained according to the data from the position encoder. So the velocity curve and accelerated velocity curve were obtained by calculating the actual position function derivation. The simulated results showed that this exoskeleton hand robot has high movement ability to finish the continuous passive motion (CPM). Beside that, a comparison test was done to verify whether there were some motion blocks in wearing exoskeleton robot. Through analyzing the experimental data, the error between the actual position and the simulated position of the PIP joint of the finger was very small which verified the small interference of robot. These experiments demonstrated that the exoskeleton hand robot has high efficiency movement ability for stroke patients who need to do the finger rehabilitation training. In the future, the optimization design of the exoskeleton hand robot will be done in order to improve more mov

关键词： Exoskeletons Thumb Robot sensing systems Joints Training

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design of the structural optimization for the upper limb rehabilitation robot

Design of the structural optimization for the upper limb reh...

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IEEE International Conference on Mechatronics and Automation

作者： Shuxiang Guo Jiange Gao Jian Guo Weijie Zhang Yuye Hu Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Biomedical Robot Laboratory Tianjin University of Technology Tianjin China Intelligent Mechanical Systems Engineering Department Kagawa University Takamatsu Japan Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System Tianjin China

ISBN: (纸本)9781509023974

The exoskeleton robotic rehabilitation training system is a branch of the field of robotics, it is the external mechanical system that is consistent with the similar joints of the human body, and attached to the human body. With the development of exoskeleton rehabilitation robotic system, the biomechanics influence of device should be considered in rehabilitation training. This paper proposes a novel upper limb exoskeleton rehabilitation device based on biomechanics, which can be used in rehabilitation of upper limb for hemi paralysis patients. This system aims at helping hemi paralysis patients recover motor function of upper limb; in addition it is suitable for variety of patients. This system is portable and wearable, which consists of exoskeleton device, hepatic device (PHANTOM Premium), motor controllers and work station (computer). This paper proposes a structural optimization scheme in order to solve some problems of bowl's structure of the rehabilitation robot. The Pro/ENGINEER Wildfire (Pro/E) software is applied to get a three-dimensional modelling, kinematics simulation and dynamic analysis of the rehabilitation robot. From the analysis, the robot end motion simulation curves were obtained to verify the optimization structure reasonable and better motion characteristics. In the future, this structure will have a wide application prospect in the rehabilitation therapy field.

关键词： Robots Exoskeletons Wrist Jacobian matrices Gears Optimization Acceleration

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The effects of ultrasonic vibration in hot pressing for microgrooves 12th

The effects of ultrasonic vibration in hot pressing for micr...

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12th Asia-Pacific Conference on Materials Processing, APCMP2016

作者： Xie, Jia Qing Zhou, Tian Feng Liu, Yang Kuriyagawa, Tsunemoto Wang, Xi Bin School of Mechanical Engineering Beijing Institute of Technology No.5 Zhongguancun South Street Haidian District Beijing100081 China Key Laboratory of Fundamental Science for Advanced Machining Beijing Institute of Technology No.5 Zhongguancun South Street Haidian District Beijing100081 China Department of Mechanical Systems and Design Tohoku University Aoba 6-6-01 Aramaki Aoba-ku Sendai980-8579 Japan

ISBN: (纸本)9783038356349

Microgrooves with a pitch at wave length level are increasingly needed in the optical system. Conventional, the microgroove forming accuracy is low due to the incomplete filling of the material in the cavity of microgroove mold, and surface flaws occur easily due to the adhesion of the resin material to the mold surface. In this research, the response behavior of resin material subjected to alternating stress is resolved based on Generalized Maxwell model. Finite Element Method (FEM) simulation is carried out to test the microgroove forming effects under the pressing condition without and with ultrasonic vibration. An ultrasonic assisted pressing machine is developed and used to fabricate microgrooves on methacrylic resin surface. Form accuracy and surface quality of microgrooves are confirmed to be improved by comparing the ultrasonic assisted pressing with the conventional forming. © 2016 Trans Tech Publications, Switzerland.

关键词： Hot pressing

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Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

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Scientific data 2021年第1期8卷 72页

作者： Gilberto Pastorello Carlo Trotta Eleonora Canfora Housen Chu Danielle Christianson You-Wei Cheah Cristina Poindexter Jiquan Chen Abdelrahman Elbashandy Marty Humphrey Peter Isaac Diego Polidori Markus Reichstein Alessio Ribeca Catharine van Ingen Nicolas Vuichard Leiming Zhang Brian Amiro Christof Ammann M Altaf Arain Jonas Ardö Timothy Arkebauer Stefan K Arndt Nicola Arriga Marc Aubinet Mika Aurela Dennis Baldocchi Alan Barr Eric Beamesderfer Luca Belelli Marchesini Onil Bergeron Jason Beringer Christian Bernhofer Daniel Berveiller Dave Billesbach Thomas Andrew Black Peter D Blanken Gil Bohrer Julia Boike Paul V Bolstad Damien Bonal Jean-Marc Bonnefond David R Bowling Rosvel Bracho Jason Brodeur Christian Brümmer Nina Buchmann Benoit Burban Sean P Burns Pauline Buysse Peter Cale Mauro Cavagna Pierre Cellier Shiping Chen Isaac Chini Torben R Christensen James Cleverly Alessio Collalti Claudia Consalvo Bruce D Cook David Cook Carole Coursolle Edoardo Cremonese Peter S Curtis Ettore D'Andrea Humberto da Rocha Xiaoqin Dai Kenneth J Davis Bruno De Cinti Agnes de Grandcourt Anne De Ligne Raimundo C De Oliveira Nicolas Delpierre Ankur R Desai Carlos Marcelo Di Bella Paul di Tommasi Han Dolman Francisco Domingo Gang Dong Sabina Dore Pierpaolo Duce Eric Dufrêne Allison Dunn Jiří Dušek Derek Eamus Uwe Eichelmann Hatim Abdalla M ElKhidir Werner Eugster Cacilia M Ewenz Brent Ewers Daniela Famulari Silvano Fares Iris Feigenwinter Andrew Feitz Rasmus Fensholt Gianluca Filippa Marc Fischer John Frank Marta Galvagno Mana Gharun Damiano Gianelle Bert Gielen Beniamino Gioli Anatoly Gitelson Ignacio Goded Mathias Goeckede Allen H Goldstein Christopher M Gough Michael L Goulden Alexander Graf Anne Griebel Carsten Gruening Thomas Grünwald Albin Hammerle Shijie Han Xingguo Han Birger Ulf Hansen Chad Hanson Juha Hatakka Yongtao He Markus Hehn Bernard Heinesch Nina Hinko-Najera Lukas Hörtnagl Lindsay Hutley Andreas Ibrom Hiroki Ikawa Marcin Jackowicz-Korczynski Dalibor Janouš Wilma Jans Rachhpal Jassal Shicheng Jiang Tomomichi Kato Myr Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. gzpastorello@lbl.gov. DIBAF University of Tuscia Viterbo 01100 Italy. Euro-Mediterranean Centre on Climate Change Foundation (CMCC) Lecce 73100 Italy. Climate & Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Department of Civil Engineering California State University Sacramento CA 95819 USA. Department of Geography Environment and Spatial Sciences Michigan State University East Lansing MI 48823 USA. Department of Computer Science University of Virginia Charlottesville VA 22904 USA. TERN Ecosystem Processes Menzies Creek VIC3159 Australia. Max Planck Institute for Biogeochemistry Jena 07701 Germany. Laboratoire des Sciences du Climat et de l'Environnement (LSCE) CEA CNRS UVSQ UPSACLAY Gif sur Yvette 91190 France. Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China. Department of Soil Science University of Manitoba Winnipeg MB R3T2N2 Canada. Department of Agroecology and Environment Agroscope Research Institute Zürich 8046 Switzerland. School of Geography and Earth Sciences McMaster University L8S4K1 Hamilton ON Canada. Department of Physical Geography and Ecosystem Science Lund University Lund 22362 Sweden. Department of Agronomy and Horticulture University of Nebraska-Lincoln Lincoln NE 68583 USA. School of Ecosystem and Forest Sciences The University of Melbourne Richmond VIC3121 Australia. Department of Biology Research Group PLECO University of Antwerp Antwerp 2610 Belgium. Joint Research Centre European Commission Ispra 21027 Italy. TERRA Teaching and Research Center University of Liege Gembloux B-5030 Belgium. Finnish Meteorological Institute Helsinki 00560 Finland. ES

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3D Ear Shape Matching Using Joint -Entropy

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Journal of Computer Science & Technology 2015年第3期30卷 565-577页

作者：孙晓鹏李思慧韩枫魏小鹏 Institute of Computer Systems School of Computer and Information Technology Liaoning Normal University Dalian 116029 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing 100876 China School of Mechanical and Engineering Dalian University of Technology Dalian 116024 China Key Laboratory of Advanced Design and Intelligent Computing Dalian University Dalian 116622 China

In this article, we investigate the use of joint a-entropy for 3D ear matching by incorporating the local shape feature of 3D ears into the joint a-entropy. First, we extract a sut^cient number of key points from the 3D ear point cloud, and fit the neighborhood of each key point to a single-value quadric surface on product parameter regions. Second, we define the local shape feature vector of each key point as the sampling depth set on the parametric node of the quadric surface. Third, for every pair of gallery ear and probe ear, we construct the minimum spanning tree （MST） on their matched key points. Finally, we minimize the total edge weight of MST to estimate its joint a-entropy the smaller the entropy is, the more similar the ear pair is. We present several examples to demonstrate the advantages of our algorithm, including low time complexity, high recognition rate, and high robustness. To the best of our knowledge, it is the first time that, in computer graphics, the classical information theory of joint a-entropy is used to deal with 3D ear shape recognition.

关键词： joint a-entropy minimum spanning tree local shape feature ear matching ear recognition

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On the Mechanical Stresses of Cu Through-Silicon Via (TSV) Samples Fabricated by SK Hynix vs. SEMATECH – Enabling Robust and Reliable 3-D Interconnect/Integrated Circuit (IC) Technology

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Procedia engineering 2016年 139卷 101-111页

作者： Tian Tian R. Morusupalli H. Shin H.-Y. Son K.-Y. Byun Y.-C. Joo R. Caramto L. Smith Y-L. Shen M. Kunz N. Tamura A.S. Budiman Maxim Integrated San Jose CA Component Quality and Technology (CQT) Cisco Systems San Jose CA 95134 Department Of Materials Science & Engineering Seoul National University (SNU) Republic of Korea PKG Development Group R&D Division Hynix Semiconductor Inc. Republic of Korea SEMATECH Albany NY 12203 Department Of Mechanical Engineering University of New Mexico (UNM) Albuquerque NM 87131 Advanced Light Source (ALS) Lawrence Berkeley National Laboratory (LBNL)Berkeley CA 94720 Singapore University of Technology and Design (SUTD) Singapore 487372

One of the key enablers for the successful integration of 3-D interconnects using the Through-Silicon Via (TSV) schemes is the control of the mechanical stresses in the Cu TSV itself as well as in the surrounding silicon substrate. The synchrotron-sourced X-ray microdiffraction technique has been recognized to allow some important advantages compared to other techniques in characterization of the mechanical stresses in a TSV sample. This approach have been used to study Cu TSV samples from SK Hynix, Inc. earlier as well as more recently from SEMATECH, and we have found interesting differences in the stress states of the Cu TSV. We proposed a possible explanation of the observed differences. This fundamental understanding could lead to improved stress control and hence reliability in the Cu TSV samples, as well as to reduce its impact to the silicon electron mobility and hence to device performance in general.

关键词： 3-D interconnects Cu TSV X-ray microdiffraction

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design of a general resilient robotic system based on axiomatic design theory

Design of a general resilient robotic system based on axioma...

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IEEE/ASME (AIM) International Conference on advanced Intelligent Mechatronics

作者： Tan Zhang Dan Zhang Madan M. Gupta Wenjun Zhang Advanced Engineering Design Laboratory University of Saskatchewan Canada Robotics & Automation Laboratory University of Ontario Institute of Technology Canada Intelligent Systems Research Laboratory University of Saskatchewan Canada

Resilient robotic systems are a kind of robotic system that is able to recover their original function after partial damage of the system. This is achieved by making changes on the partially damaged robot. The general resilient robot, which makes sense by including active joints, passive joints, passive links, and passive adjustable links, was proposed in order to explore its resilience. The axiomatic design theory (ADT) is applied to develop the resilient robot. First, a general architecture of robots was proposed, which is characterized as under-actuated robot. Second, a docking system was developed, which is the key part of incorporating the proposed architecture in the design of the mechanical system of the resilient robot, and this thus enables the realization of the proposed architecture.

关键词： Joints Context Robot sensing systems Resilience Redundancy Connectors

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