检索结果-内蒙古大学图书馆

12th European Conference on Antennas and Propagation, EuCAP 2018

作者： Hammoodi, Ali I. Bakr, Mustafa S. Khaleel, Haider Milanova, Mariofanna Department of Systems Engineering University of Arkansas at Little Rock Little Rock United States School of Electronic and Electrical Engineering University of Leeds Leeds United Kingdom Institute of Microwave and Phonetic Engineering Graz University of Technology Austria Physics Department Xavier University CincinnatiOH United States Department of Computer Science University of Arkansas at Little Rock Little Rock United States

ISBN: (纸本)9781785617911

This paper presents the design of antenna array with decoupling structure to enhance the isolation between two closely spaced rectangular patches. The design is built on RO3003 substrate with a relative permittivity of 3 and a thickness of 1.52 mm. The decoupling structure is a rectangular strip with one dimensional periodic structure of circular slots placed orthogonally between the two patches. A single via is inserted at the center of the rectangular strip to discharge the mutual current to the ground plane underneath. The array achieved a coupling reduction of 13 dB at 5.8 GHz with edge-to-edge separation of 0.19 λo. The measured gain of single antenna after the decoupling is 6.3 dBi. The array is suitable for MIMO applications where high isolation and compact size array are required. © Institution of engineering and *** Rights Reserved.

关键词： Periodic structures

来源：评论

学校读者我要写书评

暂无评论

Corrigendum to “Unpacking the drivers of diurnal dynamics of sun-induced chlorophyll fluorescence (SIF): Canopy structure, plant physiology, instrument configuration and retrieval methods” [Remote Sensing of Environment 265 (2021) 112672]

引用

Remote Sensing of Environment 2022年 268卷

作者： Christine Y. Chang Jiaming Wen Jimei Han Oz Kira Julie LeVonne Jeffrey Melkonian Susan J. Riha Joseph Skovira Sharon Ng Lianhong Gu Jeffrey D. Wood Paul Näthe Ying Sun USDA Agricultural Research Service Adaptive Cropping Systems Laboratory Beltsville MD USA School of Integrative Plant Science Soil and Crop Sciences Section Cornell University Ithaca NY USA Department of Atmospheric and Earth Sciences Cornell University Ithaca NY USA Department of Electrical and Computer Engineering Cornell University Ithaca NY USA Environmental Sciences Division and Climate Change Science Institute Oak Ridge National Laboratory Oak Ridge TN USA School of Natural Resources University of Missouri Columbia MO USA JB Hyperspectral Devices GmbH Düsseldorf Germany

来源：评论

学校读者我要写书评

暂无评论

11.0 Tera-FLOP/second photonic convolutional accelerator for deep learning optical neural networks

TechRxiv

引用

TechRxiv 2020年

作者： Moss, David J. Xu, Xingyuan Tan, Mengxi Corcoran, Bill Wu, Jiayang Boes, Andreas Nguyen, Thach G. Chu, Sai T. Little, Brent E. Hicks, Damien G. Morandotti, Roberto Mitchell, Arnan Optical Sciences Centre Swinburne University of Technology HawthornVIC3122 Australia Department of Electrical and Computer Systems Engineering Monash University ClaytonVIC3800 Australia School of Engineering RMIT University MelbourneVIC3001 Australia Department of Physics City University of Hong Kong Tat Chee Avenue Hong Kong Hong Kong Xi’an Institute of Optics and Precision Mechanics Precision Mechanics of CAS Xi’an China Bioinformatics Division Walter & Eliza Hall Institute of Medical Research ParkvilleVIC3052 Australia INRS-Énergie Matériaux et Télécommunications 1650 Boulevard Lionel-Boulet VarennesQCJ3X 1S2 Canada Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu610054 China

Convolutional neural networks (CNNs), inspired by biological visual cortex systems, are a powerful category of artificial neural networks that can extract the hierarchical features of raw data to greatly reduce the network parametric complexity and enhance the predicting accuracy. They are of significant interest for machine learning tasks such as computer vision, speech recognition, playing board games and medical diagnosis [1-7]. Optical neural networks offer the promise of dramatically accelerating computing speed to overcome the inherent bandwidth bottleneck of electronics. Here, we demonstrate a universal optical vector convolutional accelerator operating beyond 10 Tera-FLOPS (floating point operations per second), generating convolutions of images of 250,000 pixels with 8-bit resolution for 10 kernels simultaneously — enough for facial image recognition. We then use the same hardware to sequentially form a deep optical CNN with ten output neurons, achieving successful recognition of full 10 digits with 900 pixel handwritten digit images with 88% accuracy. Our results are based on simultaneously interleaving temporal, wavelength and spatial dimensions enabled by an integrated microcomb source. This approach is scalable and trainable to much more complex networks for demanding applications such as unmanned vehicle and real-time video recognition. © 2020, CC BY.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

The glycolytic reaction PGAM restrains Th17 pathogenicity and Th17-dependent autoimmunity

引用

Cell reports 2025年第6期44卷 115799页

作者： Chao Wang Allon Wagner Johannes Fessler David DeTomaso Sarah Zaghouani Yulin Zhou Kerry Pierce Raymond A Sobel Clary Clish Nir Yosef Vijay K Kuchroo Biological Sciences Platform Sunnybrook Research Institute Toronto ON M4N 3M5 Canada Department of Immunology University of Toronto Toronto ON M5S 1A8 Canada. Electronic address: chao.wang@sri.utoronto.ca. Department of Electrical Engineering and Computer Sciences University of California Berkeley Berkeley CA 94720 USA Department of Molecular and Cell Biology University of California Berkeley Berkeley CA 94720 USA Center for Computational Biology University of California Berkeley Berkeley CA 94720 USA. Division of Immunology Otto Loewi Research Center Medical University of Graz Graz Austria. The Gene Lay Institute of Immunology and Inflammation Brigham and Women's Hospital Mass General Hospital and Harvard Medical School Boston MA 02115 USA. Department of Immunology University of Toronto Toronto ON M5S 1A8 Canada. Broad Institute of MIT and Harvard Cambridge MA 02142 USA. Palo Alto Veteran's Administration Health Care System and Department of Pathology Stanford University School of Medicine Stanford CA 94305 USA. Department of Systems Immunology Weizmann Institute of Science Rehovot Israel. Electronic address: nir.yosef@weizmann.ac.il. The Gene Lay Institute of Immunology and Inflammation Brigham and Women's Hospital Mass General Hospital and Harvard Medical School Boston MA 02115 USA Broad Institute of MIT and Harvard Cambridge MA 02142 USA. Electronic address: vkuchroo@bwh.harvard.edu.

Glucose metabolism is a critical regulator of T cell function, largely thought to support their activation and effector differentiation. Here, we investigate how individual glycolytic reactions determine the pathogenicity of T helper 17 (Th17) cells using Compass, an algorithm we previously developed for inferring metabolic states from single-cell RNA sequencing. Surprisingly, Compass predicted that the metabolic shunt between 3-phosphoglycerate (3PG) and 2-phosphoglycerate (2PG) is inversely correlated with pathogenicity in Th17 cells. Indeed, perturbation of phosphoglycerate mutase (PGAM), the enzyme catalyzing 3PG to 2PG conversion, induces a pathogenic gene expression program by suppressing a gene module associated with the least pathogenic state of Th17 cells. Finally, PGAM inhibition in Th17 cells exacerbates neuroinflammation in the adoptive transfer model of experimental autoimmune encephalomyelitis, consistently with PGAM promoting the non-pathogenic phenotype of Th17 cells. Overall, our study identifies PGAM, contrary to other glycolytic enzymes, as a negative regulator of pathogenic Th17 cell differentiation.

关键词： CP: Immunology CP: Metabolism EGCG PGAM PGM T helper 17 central carbon metabolism epigallocatechin-3-gallate glycolysis immune metabolism immunometabolism phosphoglycerate mutase

来源：评论

学校读者我要写书评

暂无评论

Photonic radio frequency and microwave integration based on a multi-wavelength 49GHz Kerr microcomb source

arXiv

引用

arXiv 2020年

作者： Xu, Xingyuan Tan, Mengxi Wu, Jiayang Boes, Andreas Corcoran, Bill Nguyen, Thach G. Chu, Sai T. Little, Brent E. Morandotti, Roberto Mitchell, Arnan Moss, David J. Centre for Micro-Photonics Swinburne University of Technology HawthornVIC3122 Australia School of Engineering RMIT University MelbourneVIC3001 Australia Department of Electrical and Computer Systems Engineering Monash University ClaytonVIC3800 Australia Department of Physics City University of Hong Kong Tat Chee Avenue Hong Kong Hong Kong State Key Laboratory of Transient Optics and Photonics Xi'an Institute of Optics and Precision Mechanics Chinese Academy of Science Xi'an China INSR-Énergie Matériaux et Télécommunications 1650 Boulevard Lionel-Boulet VarennesQCJ3X 1S2 Canada

We demonstrate a photonic RF integrator based on an integrated soliton crystal micro-comb source. By multicasting and progressively delaying the input RF signal using a transversal structure, the input RF signal is integrated discretely. Up to 81 wavelengths are provided by the microcomb source, which enable a large integration time window of ~6.8 ns, together with a time resolution as fast as ~84 ps. We perform signal integration of a diverse range of input RF signals including Gaussian pulses with varying time widths, dual pulses with varying time intervals and a square waveform. The experimental results show good agreement with theory. These results verify our microcomb-based integrator as a competitive approach for RF signal integration with high performance and potentially lower cost and footprint. Copyright © 2020, The Authors. All rights reserved.

关键词： Multicasting

来源：评论

学校读者我要写书评

暂无评论

AGlobal benchmark of algorithms for segmentinglate gadolinium-enhanced cardiac magnetic resonance imaging

arXiv

引用

arXiv 2020年

作者： Xiong, Zhaohan Xia, Qing Hu, Zhiqiang Huang, Ning Bian, Cheng Zheng, Yefeng Vesal, Sulaiman Ravikumar, Nishant Maier, Andreas Yang, Xin Heng, Pheng-Ann Ni, Dong Li, Caizi Tong, Qianqian Si, Weixin Puybareau, Elodie Khoudli, Younes Géraud, Thierry Chen, Chen Bai, Wenjia Rueckert, Daniel Xu, Lingchao Zhuang, Xiahai Luo, Xinzhe Jia, Shuman Sermesant, Maxime Liu, Yashu Wang, Kuanquan Borra, Davide Masci, Alessandro Corsi, Cristiana De Vente, Coen Veta, Mitko Karim, Rashed Preetha, Chandrakanth Jayachandran Engelhardt, Sandy Qiao, Menyun Wang, Yuanyuan Tao, Qian Nuñez-Garcia, Marta Camara, Oscar Savioli, Nicolo Lamata, Pablo Zhao, Jichao Auckland Bioengineering Institute University of Auckland Auckland New Zealand State Key Lab of Virtual Reality Technology and Systems Beihang University Beijing China School of Electronics Engineering and Computer Science Peking University Beijing China SenseTime Inc Shenzhen China Tencent Jarvis Laboratory Shenzhen China Pattern Recognition Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Shenzhen University Shenzhen China School of Computer Science Wuhan University Wuhan China Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Epita Research and Development Laboratory Paris France Department of Computing Imperial College London London United Kingdom School of Naval Architecture Shanghai Jiao Tong University Ocean & Civil Engineering Shanghai China School of Data Science Fudan University Shanghai China Epione Research Group Universite Cote d'Azur Inria Sophia Antipolis France Harbin Institute of Technology School of Computer Science and Technology Harbin China Department of Electric University of Bologna Electronic and Information Engineering Cesena Italy Department of Biomedical Engineering Eindhoven University of Technology Eindhoven Netherlands School of Biomedical Engineering and Imaging Sciences Kings College London London United Kingdom Faculty of Electrical Engineering and Information Technology University of Magdeburg Magdeburg Germany Heidelberg University Hospital Germany Biomedical Engineering Center Fudan University Shanghai China Department of Radiology Leiden University Medical Center Leiden Netherlands Department of Information and Communication Technologies Universitat Pompeu Fabra Barcelona Spain D

Segmentation of cardiac images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI)widely used for visualizing diseased cardiacstructures, is a crucial first step for clinical diagnosis and treatment. However, direct segmentation ofLGE-MRIsischallenging due to *** most clinical studies have relied on manual and labor-intensive approaches, automatic methods are of high interest, particularly optimized machine learning *** address this, we organized the "2018 Left Atrium Segmentation Challenge" using 154 3D LGE-MRIs, currently the world's largest cardiac LGE-MRI dataset, and associated labels of the left atriumsegmented by three medical experts,ultimately attractingthe participation of27 international teams. In this paper, extensive analysis of the submitted algorithms using technical and biological metrics was performed by undergoing subgroup analysis and conducting hyper-parameter analysis,offeringan overall picture ofthe major design choices of convolutional neural networks(CNNs) and practical considerations for achieving state-of-the-art left atrium segmentation. Results show the top methodachieved a dice score of 93.2%and a mean surface to a surface distance of 0.7mm, significantly outperforming prior state-of-the-art. Particularly, our analysisdemonstrated that double, sequentially usedCNNs, in which a first CNN is used for automatic region-of-interestlocalization and a subsequent CNN is used for refinedregional segmentation, achieved far superiorresults than traditional methods and pipelinescontaining *** findings from this study can potentially be extended to other imaging datasets and modalities, having an impact on the wider medical imaging *** large-scale benchmarking study makes a significant step towards much-improved segmentation methods for cardiac LGE-MRIs, and will serveas animportant benchmark for evaluating and comparing the future works in the field. Copyright © 2020, Th

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

Efficient Inverse Kinematics for Redundant Manipulators with Collision Avoidance in Dynamic Scenes

Efficient Inverse Kinematics for Redundant Manipulators with...

引用

IEEE International Conference on robotics and Biomimetics

作者： Liangliang Zhao Jingdong Zhao Hong Liu Dinesh Manocha Department of Computer Science and Electrical & Computer Engineering University of Maryland at College Park MD USA State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (纸本)9781728103785;9781728103778

We present a novel iterative algorithm for inverse kinematics of redundant manipulators in dynamic environments. Our approach uses an iterative approach to generate valid configurations and selects an inverse kinematics solution using a rank-based selection strategy. To avoid the moving obstacles, we combine our inverse kinematics method with a collision avoidance scheme. We highlight the performance of our algorithm on different high DOF manipulators in a dynamic scene.

关键词： Kinematics Manipulator dynamics Collision avoidance Iterative methods End effectors Trajectory

来源：评论

学校读者我要写书评

暂无评论

Reconstruction from deletions in racetrack memories

Reconstruction from deletions in racetrack memories

引用

2018 IEEE Information Theory Workshop, ITW 2018

作者： Chee, Yeow Meng Gabrys, Ryan Vardy, Alexander Vu, Van Khu Yaakobi, Eitan School of Physical and Mathematical Sciences Nanyang Technological University Singapore Spawar Systems Center San Diego San DiegoCA92115 United States Department of Electrical and Computer Engineering University of California San Diego San DiegoCA92093 United States Department of Computer Science Technion - Israel Institute of Technology Haifa32000 Israel

ISBN: (纸本)9781538635995

In this work, we study a special case of the reconstruction problem in order to combat position errors in racetrack memories. In these memories, the information is stored in magnetic cells that can be sensed by shifting them under read heads. However, since this shifting operation is not error free, recent work has been dedicated towards correcting these so-called position errors, which manifest themselves as deletions and sticky insertions. A deletion is the event where the cells are over-shifted, and a sticky insertion occurs when the cells are not shifted. We first present a code construction that uses two heads to correct two deletions with at most log2(log2 n) + 4 redundant bits. This result improves upon a recent one that requires roughly log2 n redundant bits. We then extend this construction to correct d deletions using d heads with at most log2(log2 n) + c redundant bits. Lastly, we extend our results and derive codes for the classical reconstruction problem by Levenshtein over the insertion/deletion channel. © 2018 IEEE Information Theory Workshop, ITW 2018. All rights reserved.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

Jamming in multiple independent Gaussian channels as a game

arXiv

引用

arXiv 2018年

作者： Fasoulakis, Michail Traganitis, Apostolos Ephremides, Anthony Greece Department of Computer Science University of Crete Greece Department of Electrical and Computer Engineering Institute for Systems Research University of Maryland College Park United States

We study the problem of jamming in multiple independent Gaussian channels as a zero-sum game. We show that in the unique Nash equilibrium of the game the best-response strategy of the transmitter is the waterfilling to the sum of the jamming and the noise power in each channel and the best-response strategy of the jammer is the waterfilling only to the noise power. Copyright © 2018, The Authors. All rights reserved.

关键词： Jamming

来源：评论

学校读者我要写书评

暂无评论

Printing biological liquid on hydrophobic 3D electrodes

Printing biological liquid on hydrophobic 3D electrodes

引用

2018 Solid-State Sensors, Actuators and Microsystems Workshop, Hilton Head 2018

作者： Chu, S. Lerman, M.J. Culver, J.N. Fisher, J.P. Ghodssi, R. Institute for Systems Research Department of Electrical and Computer Engineering University of Maryland College ParkMD United States Fischell Department of Bioengineering University of Maryland College ParkMD United States Department of Materials Science and Engineering University of Maryland College ParkMD United States Institute for Bioscience and Biotechnology Research Department of Plant Science and Landscape Architecture University of Maryland College ParkMD United States

ISBN: (纸本)9781940470030

This paper presents for the first time a programmable and scalable 3D electro-bioprinting (3D-EBP) process for patterning bionanoreceptors, cysteine-modified Tobacco mosaic virus (TMV1cys), on high-density micropillar array electrodes. The structural hydrophobicity in high aspect ratio geometries of micro/nano devices poses a critical challenge for assembling 3D biomaterial-device interfaces. Here, we have successfully integrated electrowetting principles with a modified state-of-the-art bioprinter for automated, high-throughput, and large-scale patterning of TMV1cys particles on hydrophobic 3D electrodes. The 3D-EBP processed bionanoreceptors maintained both structural and chemical functions as characterized via SEM and fluorescence microscopy. Overall, the innovative 3D biomanufacturing process creates excellent opportunities for advancing on-demand bio-integrated devices including multiplexed biosensors and bioenergy harvesting devices. © 2016 TRF

关键词： Fluorescence microscopy

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：