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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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Hamiltonian Hopping for Efficient Chiral Mode Switching in Encircling Exceptional Points

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Physical Review Letters 2020年第18期125卷 187403-187403页

作者： Aodong Li Jianji Dong Jian Wang Ziwei Cheng John S. Ho Dawei Zhang Jing Wen Xu-Lin Zhang C. T. Chan Andrea Alù Cheng-Wei Qiu Lin Chen Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan 430074 China Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore Engineering Research Center of Optical Instrument and Systems Ministry of Education and Shanghai Key Lab of Modern Optical System University of Shanghai for Science and Technology No. 516 Jungong Road Shanghai 200093 China State Key Laboratory of Integrated Optoelectronics College of Electronic Science and Engineering Jilin University Changchun 130012 China Department of Physics The Hong Kong University of Science and Technology Clear Water Bay Hong Kong 999077 China Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Physics Program Graduate Center City University of New York New York New York 10016 USA

Dynamically encircling exceptional points (EPs) can lead to chiral mode switching as the system parameters are varied along a path that encircles EP. However, conventional encircling protocols result in low transmittance due to path-dependent losses. Here, we present a paradigm to encircle EPs that includes fast Hamiltonian variations on the parameter boundaries, termed Hamiltonian hopping, enabling ultrahigh-efficiency chiral mode switching. This protocol avoids path-dependent loss and allows us to experimentally demonstrate nearly 90% efficiency at 1550 nm in the clockwise direction, overcoming a long-standing challenge of non-Hermitian optical systems and powering up new opportunities for EP physics.

关键词： Open quantum systems & decoherence PT-symmetric quantum mechanics Photonics Waveguides

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THz generation by exchange-coupled spintronic emitters

npj Spintronics

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npj Spintronics 2024年第1期2卷 1-8页

作者： Roman Adam Derang Cao Daniel E. Bürgler Sarah Heidtfeld Fangzhou Wang Christian Greb Markus Büscher Claus M. Schneider Jing Cheng Debamitra Chakraborty Ivan Komissarov Roman Sobolewski Martin Mikulics Hilde Hardtdegen Peter Grünberg Institute Research Centre Jülich Jülich Germany College of Physics Qingdao University Qingdao China Faculty of Physics University Duisburg-Essen Duisburg Germany Institut für Laser- und Plasmaphysik Heinrich-Heine Universität Düsseldorf Düsseldorf Germany Materials Science Graduate Program University of Rochester Rochester NY USA Laboratory for Laser Energetics University of Rochester Rochester NY USA Department of Electrical and Computer Engineering University of Rochester Rochester NY USA Ernst Ruska Centre Research Centre Jülich Jülich Germany

The mechanism of THz generation in ferromagnet/metal (F/M) bilayers has been typically ascribed to the inverse spin Hall effect (ISHE). Here, we fabricated Pt/Fe/Cr/Fe/Pt multilayers containing two back-to-back spintronic THz emitters separated by a thin (tCr≤ 3nm) wedge-shaped Cr spacer. In such an arrangement, magnetization alignment of the two Fe films can be controlled by the interplay between Cr-mediated interlayer exchange coupling (IEC) and an external magnetic field. This in turn results in a strong variation of the THz amplitudeA, withA↑↓reaching up to 14 timesA↑↑(arrows indicate the relative alignment of the magnetization of the two magnetic layers). This observed functionality is ascribed to the interference of THz transients generated by two closely spaced THz emitters. Moreover, the magnetic field dependenceA(H) shows a strong asymmetry that points to an additional performance modulation of the THz emitter via IEC and multilayer design.

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A biometric based medical information system for the identification of comorbidity in Covid-19 patients

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AIP Conference Proceedings 2021年第1期2387卷

作者： V. Kumaresan K. Punitha S. Ragupathy B. Priestly Shan T. Gunasekaran 1Department of Electrical and Electronics Engineering Kongu Engineering College Perundurai Tamilnadu India 2School of Computer Science and Engineering Vellore Institute of Technology Chennai Tamil Nadu India 3Department of Electrical and Electronics Engineering SSM College of Engineering Komarapalayam Namakkal Tamil Nadu India 4Professor and Dean - Academic Affairs Chandigarh University Mohali Punjab India 5Program Director - Telecommunications University of Technology and Applied Sciences Higher College of Technology Muscat Sultanate of Oman

Medical information System provides the best way to collect patient’s medical information. It helps the doctors to retrieve the patient’s previous medical history very faster and able to provide suitable treatment quickly. To keep medical information of a patient securely is a difficult task. Many MQTT algorithms have been developed to provide security for the patients information. The sensitive medical information of a patient can also be protected by using biometric technology. Internet of Thing (IoT) technology used to send the medical information to the doctor like blood group, BP value, cholesterol level and heart rate level. The proposed system helps to provide the comorbidity details of the Covid-19 infected patient’s to doctors mobile phone. It also takes the current health details of the patients like temperature, respiratory rate and heart beat rate. By considering the past and present medical data of the Covid-19 patients , this system recommends the type of treatment to be given for Covid-19 infected patients.

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Nonreciprocal Willis Coupling in Zero-Index Moving Media

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Physical Review Letters 2019年第6期123卷 064301-064301页

作者： Li Quan Dimitrios L. Sounas Andrea Alù Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Department of Electrical and Computer Engineering Wayne State University Detroit Michigan 48202 USA Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Physics Program Graduate Center City University of New York New York New York 10016 USA Department of Electrical Engineering City College of The City University of New York New York 10031 USA

Mechanical motion can break the symmetry in which sound travels in a medium, but significant nonreciprocity is typically achieved only for large motion speeds. We combine moving media with zero-index acoustic propagation, yielding extreme nonreciprocity and induced bianisotropy for modest applied speeds. The metamaterial is formed by an array of waveguides loaded by Helmholtz resonators, and it exhibits opposite signs of the refractive index sustained by asymmetric Willis coupling for propagation in opposite directions. We use this response to induce nonreciprocal positive-to-negative sound refraction, and we propose a nonreciprocal metamaterial lens focusing only with excitation from one side based on asymmetric Willis coupling.

关键词： Acoustic metamaterials Acoustic wave phenomena Acoustics

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Two-dimensional pentagonal material Penta-PdPSe: A first-principle study

arXiv

引用

arXiv 2021年

作者： Bafekry, Asadolah Fadlallah, M.M. Faraji, M. Shafique, A. Jappor, H.R. Abdolhoseini Sarsari, I. Ang, Yee Sin Ghergherehchi, M. Department of Radiation Application Shahid Beheshti University Tehran*** Iran Department of Physics Faculty of Science Benha University Benha13518 Egypt Micro and Nanotechnology Graduate Program TOBB University of Economics and Technology Sogutozu Caddesi No 43 Sogutozu Ankara06560 Turkey Department of Physics Lahore University of Management Sciences Lahore Pakistan Department of Physics College of Education for Pure Sciences University of Babylon Hilla Iraq Department of Physics Isfahan University of Technology Isfahan84156-83111 Iran Cluster Singapore University of Technology and Design Singapore487372 Singapore Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Low-symmetry Penta-PdPSe with intrinsic in-plane anisotropy synthesized successfully [P. Li et al., Adv. Mater., 2102541 (2021)]. Motivated by this experimental discovery, we investigate the structural, mechanical, electronic, optical and thermoelectric properties of PdPSe monolayer via density functional theory calculations. The phonon dispersion, molecular dynamics simulation, the cohesive energy mechanical properties of the penta-PdPSe monolayer is verified to confirm its stability. The phonon spectrum represents a striking gap between the high-frequency and the low-frequency optical branches and an out-of-plane flexure mode with a quadratic dispersion in the long-wavelength limit. The Poisson’s ratio indicates that penta-PdPSe is a brittle monolayer. The pendaPdPSe monolayer is an indirect semiconductor with bandgap of 1.40 (2.07) eV using PBE (HSE06) functional. Optical properties simulation suggests that PdPSe is capable of absorbing a substantial range of visible to ultraviolet light. Band alignment analysis also reveals the compatibility of PdPSe for water splitting photocatalysis application. By combining the electrical and thermal transport properties of PdPSe, we show that a high PF is achievable at room temperature, thus making PdPSe a candidate material for thermoelectric application. Our findings reveal the strong potential of penta-PdPSe monolayer for a wide array of applications, including optoelectronic, water splitting and thermoelectric device applications. © 2021, CC BY.

关键词： Monolayers

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Exploring the effect of image enhancement techniques on COVID‐19 detection using chest X‐rays images

arXiv

引用

arXiv 2020年

作者： Rahman, Tawsifur Khandakar, Amith Qiblawey, Yazan Tahir, Anas Kiranyaz, Serkan Kashem, Saad Bin Abul Islam, Mohammad Tariqul Maadeed, Somaya Al Zughaier, Susu M. Khan, Muhammad Salman Chowdhury, Muhammad E.H. Department of Biomedical Physics & Technology University of Dhaka Dhaka 1000 Bangladesh Department of Electrical Engineering Qatar University Doha2713 Qatar Faculty of Robotics and Advanced Computing Qatar Armed Forces‐Academic Bridge Program Qatar Foundation Doha24404 Qatar Dept. of Electrical Electronics and Systems Engineering Universiti Kebangsaan Malaysia BangiSelangor43600 Malaysia Department of Computer Science and Engineering Qatar University Doha2713 Qatar Department of Basic Medical Sciences College of Medicine Biomedical and Pharmaceutical Research Unit QU Health Qatar University Doha2713 Qatar University of Engineering and Technology Peshawar Pakistan

The use of computer-aided diagnosis in the reliable and fast detection of corona virus disease (COVID-19) has become a necessity to prevent the spread of the virus during the pandemic to ease the burden on the medical infrastructure. Chest X-ray (CXR) imaging has several advantages over other imaging techniques as it is cheap, easily accessible, fast and portable. CXR images are sometimes of poor quality and so image enhancement techniques can help the machine learning models to extract valuable discriminating features from the image. Numerous works have been reported on COVID-19 detection from smaller set of original X-ray images. However, the effect of image enhancement in COVID-19 detection was not reported in the literature. This paper explores the effect of various popular image enhancement techniques and states the © 2020, CC BY.

关键词： Image enhancement

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Thermal properties of the binary-filler composites with few-layer graphene and copper nanoparticles

arXiv

引用

arXiv 2019年

作者： Barani, Zahra Mohammadzadeh, Amirmahdi Geremew, Adane Huang, Chun Yu Tammy Coleman, Devin Mangolini, Lorenzo Kargar, Fariborz Balandin, Alexander A. Department of Electrical and Computer Engineering Bourns College of Engineering University of California RiversideCA92521 United States Center University of California RiversideCA92521 United States Materials Science and Engineering Program Bourns College of Engineering University of California Riverside92521 United States Department of Mechanical Engineering Bourns College of Engineering University of California Riverside92521 United States

The thermal properties of an epoxy-based binary composites comprised of graphene and copper nanoparticles are reported. It is found that the gsynergistich filler effect, revealed as a strong enhancement of the thermal conductivity of composites with the size-dissimilar fillers, has a well-defined filler loading threshold. The thermal conductivity of composites with a moderate graphene concentration of fg=15 wt% exhibits an abrupt increase as the loading of copper nanoparticles approaches fg~40 wt%, followed by saturation. The effect is attributed to intercalation of spherical copper nanoparticles between the large graphene flakes, resulting in formation of the highly thermally conductive percolation network. In contrast, in composites with a high graphene concentration, fg=40 wt%, the thermal conductivity increases linearly with addition of copper nanoparticles. The electrical percolation is observed at low graphene loading, fg Copyright © 2019, The Authors. All rights reserved.

关键词： Thermal conductivity

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Machine Learning-Based Statistical Hypothesis Testing for Fault Detection

Machine Learning-Based Statistical Hypothesis Testing for Fa...

引用

Conference on Control and Fault-Tolerant Systems (SysTol)

作者： Radhia Fazai Majdi Mansouri Kamal Abodayeh Mohamed Trabelsi Hazem Nounou Mohamed Nounou Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Department of Mathematical Sciences Prince Sultan University Riyadh Saudi Arabia Department of Electronic and Communications Engineering Kuwait College of Science and Technology Kuwait Chemical Engineering Program Texas A&M University at Qatar Doha Qatar

ISBN: (纸本)9781728103815

This paper elaborates the development of machine learning approach merged with statistical hypothesis testing aimed at enhancing the operation of photovoltaic (PV) systems by developing intelligent PV fault detection framework. Fault detection in PV systems is important to ensure optimal energy harvesting and reliable power production because PV systems usually operate in a harsh outdoor environment and tend to suffer various faults. In this paper, therefore, special attention is paid to detection of various faults during different modes of operation. The proposed approach merges the benefits of machine learning technique (MLT) with statistical hypothesis testing to enhance the fault detection and monitoring of PV systems. The proposed technique will be effective in monitoring the PV faults under both normal and abnormal conditions. For the framework developed, the modeling phase is addressed using MLT and the faults are detected using the generalized likelihood ratio test (GLRT) chart. The MLT is used to compute the residuals monitored and the GLRT chart is applied to the monitored residuals evaluated for fault detection purposes. The developed MLT-based GLRT algorithm is implemented and validated using both simulated and real PV data. The results are evaluated in terms of false alarm rates (FAR), missed detection rates (MDR) and computation time.

关键词： Ground penetrating radar Monitoring Circuit faults Testing Photovoltaic systems Fault detection

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Author Correction: The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci

引用

Nature computational science 2023年第7期3卷 658页

作者： Gengjie Jia Yu Li Xue Zhong Kanix Wang Milton Pividori Rabab Alomairy Aniello Esposito Hatem Ltaief Chikashi Terao Masato Akiyama Koichi Matsuda David E Keyes Hae Kyung Im Takashi Gojobori Yoichiro Kamatani Michiaki Kubo Nancy J Cox James Evans Xin Gao Andrey Rzhetsky Shenzhen Branch Guangdong Laboratory of Lingnan Modern Agriculture Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China. jiagengjie@***. Computational Bioscience Research Center King Abdullah University of Science and Technology Thuwal Saudi Arabia. Computer Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong People's Republic of China. Department of Medicine and Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN US. Department of Medicine Institute of Genomics and Systems Biology Committee on Genomics Genetics and Systems Biology University of Chicago Chicago IL US. Department of Operations Business Analytics and Information Systems University of Cincinnati Cincinnati OH US. Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania Philadelphia PA US. Extreme Computing Research Center Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia. HPE HPC/AI EMEA Research Laboratory Bristol UK. RIKEN Center for Integrative Medical Sciences Yokohama Japan. Clinical Research Center Shizuoka General Hospital Shizuoka Japan. Department of Applied Genetics The School of Pharmaceutical Sciences University of Shizuoka Shizuoka Japan. Department of Ophthalmology Graduate School of Medical Sciences Kyushu University Fukuoka Japan. Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Tokyo Japan. Biological and Environmenta

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