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arXiv 2020年

作者： Ji, Zijie Yeoh, Phee Lep Chen, Gaojie Pan, Cunhua Zhang, Yan He, Zunwen Yin, Hao Li, Yonghui The School of Information and Electronics Beijing Institute of Technology Beijing100081 China The School of Electrical and Information Engineering University of Sydney SydneyNSW2006 Australia The Department of Engineering University of Leicester LeicesterLE1 7RH United Kingdom The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Institute of China Electronic System Engineering Corporation Beijing100141 China

In this letter, we propose a novel encrypted data transmission scheme using an intelligent reflecting surface (IRS) to generate secret keys in wireless communication networks. We show that perfectly secure one-time pad (OTP) communications can be established by using a simple random phase shifting of the IRS elements. To maximize the secure transmission rate, we design an optimal time slot allocation algorithm for the IRS secret key generation and the encrypted data transmission phases. Moreover, a theoretical expression of the key generation rate is derived based on Poisson point process (PPP) for the practical scenario when eavesdroppers' channel state information (CSI) is unavailable. Simulation results show that employing our IRS-based scheme can significantly improve the encrypted data transmission performance for a wide-range of wireless channel gains and system parameters. Copyright © 2020, The Authors. All rights reserved.

关键词： Cryptography

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Smart radio environments

arXiv

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arXiv 2021年

作者： Gradoni, Gabriele Renzo, Marco Di Díaz-Rubio, Ana Tretyakov, Sergei A. Caloz, Christophe Gradoni, Gabriele Peng, Zhen Alu, Andrea Lerosey, Geoffroy Fink, Mathias Galdi, Vincenzo Cui, Tie Jun Frazier, Benjamin W. Anlage, Steven M. Salucci, Marco Massa, Andrea Cheng, Qiang Wang, Jinghe Jin, Shi Dardari, Davide Decarli, Nicoló Yurduseven, Okan Matthaiou, Michail Kenney, Mitchell Gordon, George Georgiou, Orestis Nguyen, Cam Ly Martini, Enrica Maci, Stefano Wakatsuchi, Hiroki Phang, Sendy School of Mathematical Sciences Department of Electrical and Electronic Engineering University of Nottingham Nottingham United Kingdom Laboratoire des Signaux et Systémes CNRS CentraleSupélec Université Paris-Saclay Gif-sur-Yvette Paris France Department of of Electronics and Nanoengineering Aalto University Espoo Finland META Research Group KU Leuven Belgium School of Mathematical Sciences Department of Electrical and Electronic Engineering University of Nottingham University Park NG72RD United Kingdom Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign IL United States Advanced Science Research Center City University of New York United States Greenerwave 6 rue Jean Calvin Paris75005 France Institut Langevin 1 rue Jussieu Paris75005 France Fields & Waves Lab Department of Engineering University of Sannio Benevento Italy State Key Laboratory of Millimeter Waves Southeast University Nanjing China Applied Physics Laboratory Johns Hopkins University LaurelMD20723 United States Department of Electrical and Computer Engineering Department of Physics Quantum Materials Center University of Maryland College ParkMD20742 United States Trento Italy Chengdu China Beijing China Institute of Electromagnetic Space State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China National Mobile Communications Research Laboratory Southeast University Nanjing China University of Bologna Bologna Italy Bologna Italy Centre for Wireless Innovation Institute of Electronics Communications and Information Technology Queen’s University Belfast Belfast United Kingdom Department of Electrical and Electronic Engineering University of Nottingham Nottingham United Kingdom Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Wireless System Laboratory Corporate Research & Development Center Toshiba Corporation Kawasaki Japan Department of Information Engineering an

This Roadmap takes the reader on a journey through the research in electromagnetic wave propagation control via reconfigurable intelligent surfaces. Meta-surface modelling and design methods are reviewed along with physical realisation techniques. Several wireless applications are discussed, including beam-forming, focusing, imaging, localisation, and sensing, some rooted in novel architectures for future mobile communications networks towards 6G. © 2021, CC BY.

关键词： Electromagnetic wave propagation

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Transverse Patterns and Dual-Frequency Lasing in a Low-Noise Nonplanar-Ring Orbital-Angular-Momentum Oscillator

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Physical Review Applied 2020年第2期13卷 024067-024067页

作者： Yaqin Cao Ping Liu Cuifang Hou Yanne K. Chembo Zehuang Lu Guoping Lin MOE Key Laboratory of Fundamental Physical Quantities Measurement Hubei Key Laboratory of Gravitation and Quantum Physics PGMF and School of Physics Huazhong University of Science and Technology Wuhan 430074 China Institute for Research in Electronics and Applied Physics (IREAP) and Department of Electrical and Computer Engineering University of Maryland College Park Maryland 20742 USA Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System School of Science Harbin Institute of Technology Shenzhen 518055 China

Monolithic optical cavities employing total internal reflections are appealing compact platforms for a wide range of applications from fundamental physics to industry applications. We characterize the transverse patterns of a millimeter-size monolithic nonplanar ring vortex laser pumped by a Gaussian beam. Vortex beams carrying orbital angular momentum (OAM) up to 30 together with vortex crystals and petal patterns are observed. The rigid nature of the monolithic cavity brings along its low-noise lasing performance for these beams. A frequency noise floor as low as 0.1Hz/Hz1/2 corresponding to sub-Hz instantaneous linewidth is measured. Furthermore, we demonstrate low-noise dual-frequency lasing with phase noise as low as −118dBc/Hz at 10-kHz offset for the beatnote at 8.2 GHz. We expect that such versatile and compact OAM laser sources can facilitate multiple applications including optical communications, optical tweezers, and laser metrology such as dual-frequency Doppler lidar.

关键词： Angular momentum of light Optical quantum information processing Optical sources & detectors Optical vortices Photonics Solid state lasers Spatial profiles of optical beams Cavity resonators

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The 2022 report of the Lancet Countdown on health and climate change: health at the mercy of fossil fuels (vol 400, pg 1619, 2022)

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LANCET 2022年第10365期400卷 1766-1766页

作者： Romanello, M. Di Napoli, C. Drummond, P. Institute for Global Health University College London London UK School of Agriculture Policy and Development University of Reading Reading UK Institute for Sustainable Resources University College London London UK Department of Global Health Centre for Health and the Global Environment University of Washington Seattle WA USA UCL Energy Institute University College London London UK Department of Health Sciences University of York York UK Department of Meteorology University of Reading Reading UK Institute for Risk and Disaster Reduction University College London London UK School of Earth and Environment University of Leeds Leeds UK Centre on Climate Change and Planetary Health London School of Hygiene & Tropical Medicine London UK School of Population Health University of Melbourne Melbourne VIC Australia Department of Earth System Science Tsinghua University Beijing China Mercator Research Institute on Global Commons and Climate Change Berlin Germany Department of Environment Climate Change and Health World Health Organization Geneva Switzerland Institute of Environmental Sciences University of Geneva Geneva Switzerland Cardiovascular Epidemiology Unit Department of Public Health & Primary Care University of Cambridge Cambridge UK School of Government University of Birmingham Birmingham UK Economic Analysis of Climate Impacts and Policy Division Centro Euro-Mediterraneo sui Cambiamenti Climatici Venice Italy Institute for Environmental Design and Engineering University College London London UK Natural Resources Institute University of Greenwich London UK Department of Environmental Health Sciences and Yale Center on Climate Change and Health Yale University New Haven CT USA Department of Civil and Environmental Engineering Northeastern University Boston MA USA Department of Fish and Wildlife Conservation Virginia Polytechnic Institute and State University Blacksburg VA USA Department of Geography University College London London UK NU

With advancements in the science of detection and attribution studies, the influence of climate change over many events has now been quantified. Because of the rapidly increasing temperatures, vulnerable populations (adults older than 65 years, and children younger than one year of age) were exposed to 3·7 billion more heatwave days in 2021 than annually in 1986–2005 (indicator 1.1.2), and heat-related deaths increased by 68% between 2000–04 and 2017–21 (indicator 1.1.5), a death toll that was significantly exacerbated by the confluence of the COVID-19 pandemic. Despite the local cooling and overall health benefits of urban greenspaces, only 277 (27%) of 1038 global urban centres were at least moderately green in 2021 (indicator 2.2.3), and the number of households with air conditioning increased by 66% from 2000 to 2020, a maladaptive response that worsens the energy crisis and further increases urban heat, air pollution, and greenhouse gas emissions. [...]millions of people do not have access to the energy needed to keep their homes at healthy temperatures, preserve food and medication, and meet the seventh Sustainable Development Goal (to ensure access to affordable, reliable, sustainable, and modern energy for all). Aggravating this situation even further, governments continue to incentivise fossil fuel production and consumption: 69 (80%) of 86 countries reviewed had net-negative carbon prices (ie, provided a net subsidy to fossil fuels) for a net total of US$400 billion

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Range Verification using Prompt Gamma-rays with Energy Spectral Analysis in Geant4 Based Proton Therapy Simulation

Range Verification using Prompt Gamma-rays with Energy Spect...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Tsukasa Aso Hiroki Oke Teiji Nishio Department of Electronics and Computer Engineering National Institute of Technology Toyama College Japan Control Information System Engineering Program Advanced Course National Institute of Technology Toyama College Japan Department of Medical Physics Tokyo Women’s Medical University Japan

ISBN: (数字)9781728141640

ISBN: (纸本)9781728141657

Range verification of therapeutic proton beam is crucial in proton therapy to confirm the irradiation field for ensuring effects and safety of the treatment. The irradiation field reconstruction using prompt gamma-rays generated from excited nuclides by proton beam has being studied for the purpose of precision medicine. A simulation tool based on fundamental physics processes employs an important role to understand intermediate relationship between physics interactions and detected observables, and to optimize a detector system with its analysis method. Previously, we reported on the simulation study about an irradiation field reconstruction by using prompt gamma-rays of whole energy range. In this study, we analyzed the energy spectrum and reconstructed the image of irradiation field by using prompt gamma-rays corresponding to a particular energy peak. The simulation was performed for proton beam with a target placed at the isocenter by using Geant4 based particle therapy system simulation framework. A simple tubular detector was placed around the target, in which the kinetic energy and the detected position of each gamma-ray were recorded. The irradiation field was then reconstructed in the ordered subset expectation maximization method. The reconstructed irradiation fields were compared with the dose distribution in the target. The peak positions of these depth distributions were compared each other and discussed about the range verification of therapeutic proton beam.

关键词： Image reconstruction Radiation effects Gamma-rays Particle beams Medical treatment Detectors

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DeePMD-kit v2: A software package for Deep Potential models

arXiv

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arXiv 2023年

作者： Zeng, Jinzhe Zhang, Duo Lu, Denghui Mo, Pinghui Li, Zeyu Chen, Yixiao Rynik, Marián Huang, Li'ang Li, Ziyao Shi, Shaochen Wang, Yingze Ye, Haotian Tuo, Ping Yang, Jiabin Ding, Ye Li, Yifan Tisi, Davide Zeng, Qiyu Bao, Han Xia, Yu Huang, Jiameng Muraoka, Koki Wang, Yibo Chang, Junhan Yuan, Fengbo Bore, Sigbjørn Løland Cai, Chun Lin, Yinnian Wang, Bo Xu, Jiayan Zhu, Jia-Xin Luo, Chenxing Zhang, Yuzhi Goodall, Rhys E.A. Liang, Wenshuo Singh, Anurag Kumar Yao, Sikai Zhang, Jingchao Wentzcovitch, Renata Han, Jiequn Liu, Jie Jia, Weile York, Darrin M. Weinan, E. Car, Roberto Zhang, Linfeng Wang, Han Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China College of Electrical and Information Engineering Hunan University Changsha China Yuanpei College Peking University Beijing100871 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08540 United States Department of Experimental Physics Comenius University Mlynská Dolina F2 Bratislava842 48 Slovakia Center for Quantum Information Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Center for Data Science Peking University Beijing100871 China ByteDance Research Zhonghang Plaza No. 43 North 3rd Ring West Road Haidian District Beijing China College of Chemistry and Molecular Engineering Peking University Beijing100871 China Baidu Inc. Beijing China Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University Zhejiang Hangzhou China Westlake AI Therapeutics Lab Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Hangzhou China Department of Chemistry Princeton University PrincetonNJ08544 United States SISSA Scuola Internazionale Superiore di Studi Avanzati Trieste34136 Italy Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Department of Physics National University of Defense Technology Hunan Changsha410073 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Electronics Engineerin

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments. © 2023, CC BY-NC-ND.

关键词： Molecular dynamics

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Real-time multi-target path prediction and planning for autonomous driving aided by FCN

arXiv

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arXiv 2019年

作者： Zhou, Hongtu Yang, Xinneng Zhang, Enwei Zhao, Junqiao Cai, Lewen Ye, Chen Wu, Yan Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai Institute of Intelligent Vehicle Tongji University Shanghai Department of Computer Science Nanjing University Nanjing China

Real-time multi-target path planning is a key issue in the field of autonomous driving. Although multiple paths can be generated in real-time with polynomial curves, the generated paths are not flexible enough to deal with complex road scenes such as S-shaped road and unstructured scenes such as parking lots. Search and sampling-based methods, such as A* and RRT and their derived methods, are flexible in generating paths for these complex road environments. However, the existing algorithms require significant time to plan to multiple targets, which greatly limits their application in autonomous driving. In this paper, a real-time path planning method for multi-targets is proposed. We train a fully convolutional neural network (FCN) to predict a path region for the target at first. By taking the predicted path region as soft constraints, the A* algorithm is then applied to search the exact path to the target. Experiments show that FCN can make multiple predictions in a very short time (50 times in 40ms), and the predicted path region effectively restrict the searching space for the following A* search. Therefore, the A* can search much faster so that the multi-target path planning can be achieved in real-time (3 targets in less than 100ms). Copyright © 2019, The Authors. All rights reserved.

关键词： Autonomous vehicles

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High-density implantable neural electrodes and chips for massive neural recordings

Brain-X

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Brain-X 2024年第2期2卷

作者： Wang, Longchun Suo, Yanxing Wang, Jiahao Wang, Xuanqi Xue, Kai An, Jingjing Sun, Xun Chen, Qinyu Tang, Xiaochen Zhao, Yang Ji, Bowen Liu, Jingquan Department of Micro/Nano Electronics Shanghai Jiao Tong University Shanghai China National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai Jiao Tong University Shanghai China DCI Joint Team Collaborative Innovation Center of IFSA Shanghai Jiao Tong University Shanghai China Unmanned System Research Institute Northwestern Polytechnical University Shaanxi Xi'an China National Key Laboratory of Unmanned Aerial Vehicle Technology Shaanxi Xi'an China Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace School of Mechanical Engineering Northwestern Polytechnical University Shaanxi Xi'an China Institute of Guizhou Aerospace Measuring and Testing Technology Guizhou Guiyang China Leiden Institute of Advanced Computer Science (LIACS) Leiden University Leiden Netherlands Klipsch School of Electrical and Computer Engineering New Mexico State University Las Cruces NM United States

High-density neural recordings with superior spatiotemporal resolution powerfully unveil cellular-scale neural communication, showing great promise in neural science, translational medicine, and clinical applications. To achieve such, many design and fabrication innovations enhanced the electrode, chip, or both for biocompatibility improvement, electrical performance upgrade, and size miniaturization, offering several thousands of recording sites. However, an enormous gap exists along the trajectory toward billions of recording sites for brain scale resolution, posing many more design challenges. This review tries to find possible insight into mitigating the gap by discussing the latest progress in high-density electrodes and chips for neural recordings. It emphasizes the design, fabrication, bonding techniques, and in vivo performance optimization of high-density electrodes. It discusses the promising opportunities for circuit-level and architecture-level multi-channel chip design innovations. We expect that joint effort and close collaboration between high-density electrodes and chips will pave the way to high-resolution neural recording tools supporting cutting-edge neuroscience discoveries and applications. © 2024 The Author(s). Brain-X published by John Wiley & Sons Australia, Ltd on behalf of Ainuohui Medical Technology.

关键词： brain-computer interface high density implantable chips implantable electrodes massive neural recording

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Attitude and Horizontal Speed Control system on Unmanned Aerial Vehicle Using LQR

Attitude and Horizontal Speed Control System on Unmanned Aer...

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International Conference on Science and Technology-computer (ICST)

作者： Andi Dharmawan Lazuardi Ichsan Hanif Baskoro Jazi Eko Istiyanto Ariesta Martiningtyas Handayani Electronics and Instrumentation Research Laboratory Universitas Gadjah Mada Yogyakarta Indonesia Computer System and Networking Research Laboratory Universitas Gadjah Mada Yogyakarta Indonesia Department of Electrical and Informatics Engineering Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9781728123691

ISBN: (纸本)9781728123707

Unmanned Aerial Vehicles (UAV) or drones are expected to fly automatically, especially in performing basic maneuvers. The necessary maneuver is to fly straight and level, where no rotation occurs on the roll, pitch, and yaw axes that work on the plane. Also, to free from rotational motion, the aircraft needs to maintain its horizontal speed to prevent the vehicle from losing lift and free-fall. This research uses a Linear Quadratic Regulator (LQR) control method to obtain full-state feedback K gain from the control system. The gain of the full-state feedback is used to control the output, which is converted into Pulse Width Modulation to control the rotational speed of the brushless motor, and the angle of servo. The result of this research is that system response obtained is optimum with the desired specification.

关键词： Control systems Angular velocity Unmanned aerial vehicles Mathematical model Attitude control Force Torque

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Auto Landing system on A Fixed Wing Unmanned Aerial Vehicle Using Linear Quadratic Approach

Auto Landing System on A Fixed Wing Unmanned Aerial Vehicle ...

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International Conference on Science and Technology-computer (ICST)

作者： Andi Dharmawan Ahmad Ashari Ariesta Martiningtyas Handayani Riarsari Meirani Utami I Made Tresnayana Electronics and Instrumentation Research Laboratory Universitas Gadjah Mada Yogyakarta Indonesia Computer System and Networking Research Laboratory Universitas Gadjah Mada Yogyakarta Indonesia Department of Electrical and Informatics Engineering Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9781728123691

ISBN: (纸本)9781728123707

The primary control issue on Unmanned Aerial Vehicle (UAV) is to control the rotation motion in the form of pitch, roll, and yaw. These rotational movements are used for various flight phases. The flight phases are at least divided into 3, consisting of taking off, cruising, and landing phases. The landing phase is one of the most critical phases. If the flight control of a UAV in this phase is not optimal, then it can crash. The landing phase control system in this research uses the Linear Quadratic Regulator (LQR) method. This method works on a full-state feedback control system. This control system will produce style and torque, both of which will be converted to PWM (Pulse Width Modulation) signals and the servos deflection angle values. The PWM signals play a role in regulating how fast the brushless motor rotates. The control system is used to maintain the stability of the UAV upon landing so that the UAV does not experience undesirable things. Landing phase testing results show that the control system has been able to land the UAV with an optimal control response.

关键词： Unmanned aerial vehicles Control systems Sensors Nose Force Angular velocity Elevators

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