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arXiv 2022年

作者： Payette, Kelly li, Hongwei de dumast, Priscille licandro, Roxane Ji, Hui Siddiquee, Md Mahfuzur Rahman Xu, daguang Myronenko, Andriy liu, Hao Pei, Yuchen Wang, lisheng Peng, Ying Xie, Juanying Zhang, Huiquan dong, Guiming Fu, Hao Wang, Guotai Rieu, ZunHyan Kim, donghyeon Kim, Hyun Gi Karimi, davood Gholipour, Ali Torres, Helena R. Oliveira, Bruno Vilaça, João l. lin, Yang Avisdris, Netanell Ben-Zvi, Ori Bashat, dafna Ben Fidon, lucas Aertsen, Michael Vercauteren, Tom Sobotka, daniel langs, Georg Alenyà, Mireia Villanueva, Maria Inmaculada Camara, Oscar Fadida, Bella Specktor Joskowicz, leo Weibin, liao Yi, lv Xuesong, li Mazher, Moona Qayyum, Abdul Puig, domenec Kebiri, Hamza Zhang, Zelin Xu, Xinyi Wu, dan liao, Kuanlun Wu, YiXuan Chen, JinTai Xu, Yunzhi Zhao, li Vasung, lana Menze, Bjoern Cuadra, Meritxell Bach Jakab, Andras Center for MR Research University Children's Hospital Zurich University of Zurich Zurich Switzerland Neuroscience Center Zurich University of Zurich Zurich Switzerland Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Informatics Technical University of Munich Munich Germany Medical Image Analysis Laboratory Department of Diagnostic and Interventional Radiology Lausanne University Hospital University of Lausanne Lausanne Switzerland CIBM Center for Biomedical Imaging Lausanne Switzerland Laboratory for Computational Neuroimaging Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Harvard Medical School CharlestownMA United States Medical University of Vienna Vienna Austria Arizona State University United States NVIDIA United States Shanghai Jiaotong University China School of Computer Science Shaanxi Normal University Xi'An710119 China Research Institute NEUROPHET Inc. Seoul06247 Korea Republic of Department of Radiology The Catholic University of Korea Eunpyeong St. Mary's Hospital Seoul06247 Korea Republic of Boston Children's Hospital Harvard Medical School BostonMA United States 2Ai - School of Technology IPCA Barcelos Portugal Algoritmi Center School of Engineering University of Minho Guimarães Portugal School of Medicine University of Minho Braga Portugal ICVS 3B's - PT Government Associate Laboratory Guimarães Braga Portugal School of Computer Science and Engineering The Hebrew University of Jerusalem Israel Sagol Brain Institute Tel Aviv Sourasky Medical Center Israel Sagol School of Neuroscience Tel Aviv University Israel Sackler Faculty of Medicine Tel Aviv University Israel School of Biomedical Engineering & Imaging Sciences King's College London LondonSE1 7EU United Kingdom Department of Radiology University Hospitals Leuven Leuven3000 Belgium Computational Imaging Research Lab Department of Biomedical Imaging and Image-guided Therapy Medical

In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research and clinical context. However, manual segmentation of cerebral structures is time-consuming and prone to error and inter-observer variability. Therefore, we organized the Fetal Tissue Annotation (FeTA) Challenge in 2021 in order to encourage the development of automatic segmentation algorithms on an international level. The challenge utilized FeTA dataset, an open dataset of fetal brain MRI reconstructions segmented into seven different tissues (external cerebrospinal fluid, grey matter, white matter, ventricles, cerebellum, brainstem, deep grey matter). 20 international teams participated in this challenge, submitting a total of 21 algorithms for evaluation. In this paper, we provide a detailed analysis of the results from both a technical and clinical perspective. All participants relied on deep learning methods, mainly U-Nets, with some variability present in the network architecture, optimization, and image pre- and post-processing. The majority of teams used existing medical imaging deep learning frameworks. The main differences between the submissions were the fine tuning done during training, and the specific pre- and post-processing steps performed. The challenge results showed that almost all submissions performed similarly. Four of the top five teams used ensemble learning methods. However, one team's algorithm performed significantly superior to the other submissions, and consisted of an asymmetrical U-Net network architecture. This paper provides a first of its kind benchmark for future automatic multi-tissue segmentation algorithms for the developing human brain in utero. © 2022, CC BY.

关键词： Magnetic resonance imaging

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deePMd-kit v2: A software package for deep Potential models

arXiv

引用

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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Fully Passive Quantum Key distribution

引用

Physical Review letters 2023年第22期130卷 220801-220801页

作者： Wenyuan Wang Rong Wang Chengqiu Hu Victor Zapatero li Qian Bing Qi Marcos Curty Hoi-Kwong lo Department of Physics University of Hong Kong Pokfulam Road Hong Kong Vigo Quantum Communication Center University of Vigo Vigo E-36310 Spain Escuela de Ingeniería de Telecomunicación Department of Signal Theory and Communications University of Vigo Vigo E-36310 Spain AtlanTTic Research Center University of Vigo Vigo E-36310 Spain Department of Electrical and Computer Engineering University of Toronto Toronto Ontario M5S 3G4 Canada Centre for Quantum Information and Quantum Control (CQIQC) University of Toronto Toronto Ontario M5S 1A7 Canada Cisco Systems San Jose California 95134 USA Department of Physics University of Toronto Toronto Ontario M5S 1A7 Canada Quantum Bridge Technologies Inc. 100 College Street Toronto Ontario M5G 1L5 Canada

We propose a fully passive linear optical quantum key distribution (QKd) source that implements both random decoy-state and encoding choices with postselection only, thus eliminating all side channels in active modulators. Our source is general purpose and can be used in, e.g., BB84, the six-state protocol, and reference-frame-independent QKd. It can even potentially be combined with measurement-device-independent QKd to achieve robustness against side channels in both detectors and modulators. We also perform a proof-of-principle experimental source characterization to show its feasibility.

关键词： Optical quantum information processing Quantum communication Quantum cryptography Quantum optics Quantum protocols

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Perfect absorption in a metasurface-programmable complex scattering enclosure

arXiv

引用

arXiv 2020年

作者： Imani, Mohammadreza F. Smith, david R. del Hougne, Philipp Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Institut d'Electronique et de Télécommunications de Rennes CNRS UMR 6164 Université de Rennes 1 Rennes35000 France

Achieving the very special condition of perfect absorption (PA) in a complex scattering enclosure promises to enable a wealth of applications in secure communication, precision sensing, wireless power transfer, analog signal processing and random lasing. Consequently, a lot of recent research effort was dedicated to proposing wavefront shaping protocols to implement coherent PA in a complex scattering environment. Here, instead of shaping the impinging wave front and tuning the system's attenuation, we propose the conceptually different route of solely tweaking the randomness of the complex scattering environment in order to achieve PA. We provide an experimental proof-of-concept in the microwave domain where we tune the randomness of a three-dimensional chaotic cavity with a programmable metasurface. We systematically investigate the achievability and extreme sensitivity of the PA condition. Our technique can impose a PA condition at over hundred distinct frequencies within a small frequency band, which allows us to propose and experimentally demonstrate a concrete practical application: receiver-powered secure wireless communication in a complex scattering enclosure. Our fundamentally new perspective on PA is applicable to all types of wave phenomena and our results foreshadow the large potential of this novel tool for minute wave control in sensing, communication and energy transfer. Copyright © 2020, The Authors. All rights reserved.

关键词： Enclosures

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Maintaining a Resonance Condition of an RF Spin Rotator Through a Feedback loop in a Storage Ring

arXiv

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arXiv 2025年

作者： Hejny, V. Andres, A. Pretz, J. Abusaif, F. Aggarwal, A. Aksentev, A. Alberdi, B. Barion, l. Bekman, I. Beyß, M. Böhme, C. Breitkreutz, B. Canale, N. Ciullo, G. dymov, S. Fröhlich, N.-O. Gebel, R. Gaisser, M. Grigoryev, K. Grzonka, d. Hetzel, J. Javakhishvili, O. Kacharava, A. Kamerdzhiev, V. Karanth, S. Keshelashvili, I. Kononov, A. laihem, K. lehrach, A. lenisa, P. lomidze, N. lorentz, B. Macharashvili, G. Magiera, A. McHedlishvili, d. Melnikov, A. Müller, F. Nass, A. Nikolaev, N.N. Okropiridze, d. Pesce, A. Piccoli, A. Poncza, V. Prasuhn, d. Rathmann, F. Saleev, A. Shergelashvili, d. Shmakova, V. Shankar, R. Shurkhno, N. Siddique, S. Silenko, A. Slim, J. Soltner, H. Stassen, R. Stephenson, E.J. Ströher, H. Tabidze, M. Tagliente, G. Valdau, Y. Vitz, M. Wagner, T. Wirzba, A. Wrońska, A. Wüstner, P. Żurek, M. Institut für Kernphysik Forschungszentrum Jülich Jülich52425 Germany III. Physikalisches Institut B RWTH Aachen University Aachen52056 Germany Marian Smoluchowski Institute of Physics Jagiellonian University Cracow30348 Poland Institute for Nuclear Research Russian Academy of Sciences Moscow117312 Russia University of Ferrara Istituto Nazionale di Fisica Nucleare Ferrara44100 Italy Department of Electrical and Computer Engineering Agricultural University of Georgia Tbilisi0159 Georgia High Energy Physics Institute Tbilisi State University Tbilisi0186 Georgia GSI Helmholtzzentrum für Schwerionenforschung GmbH Planckstr. 1 Darmstadt64291 Germany L.D. Landau Institute for Theoretical Physics Chernogolovka142432 Russia Bogoliubov Laboratory of Theoretical Physics International Intergovernmental Organization Joint Institute for Nuclear Research Dubna141980 Russia Institute of Technology and Engineering Forschungszentrum Jülich Jülich52425 Germany Indiana University Department of Physics BloomingtonIN47405 United States Istituto Nazionale di Fisica Nucleare sez. Bari Bari70125 Italy Institute for Advanced Simulation Forschungszentrum Jülich Jülich52425 Germany

This paper presents the successful application of a phase-lock feedback system to maintain the resonance condition of a radio frequency (rf) spin rotator (specifically, an rf Wien filter) with respect to a 120 kHz spin precession in the Cooler Synchrotron (COSY) storage ring. Real-time monitoring of the spin precession and the rf Wien filter signal allows the relative phase between the two to be stabilized at an arbitrary setpoint. The feedback system compensates for deviations in the relative phase by adjusting the frequency and/or phase of the rf device as needed. With this method, a variation in the phase relative to the demanded value with a standard deviation of σ∆φ ≈ 0.2 rad could be achieved. The system was implemented in two runs aiming at a first direct measurement of the deuteron electric dipole moment in 2018 and 2021. In addition, the difference between a single-bunch beam affected by the spin rotator and a two-bunch system in which only one bunch is exposed to the spin rotator fields is discussed. Both methods have been used during these beam times. The ability to keep the spin precession and the rf fields synchronized is crucial for future investigations of electric dipole moments of charged particles using storage rings. Copyright © 2025, The Authors. All rights reserved.

关键词： Storage rings

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Blockchain Confidence Protection and Cloud Chain Management Support

引用

Journal of Physics: Conference Series 2021年第4期1964卷

作者： M Nagalakshmi K Saravanan Mohammad Jabirullah T Rajesh Kumar Associate Professor Department of Computer Science and Engineering Marri Laxman Reddy Institute of Technology Dundigal Telangana India Associate Professor Department of Information Technology R.M.D Engineering College Kavaraipettai Tamil Nadu India Associate Professor Department of Electronics and Communication Engineering CMR Engineering College Hyderabad Telangana India Associate Professor Department of Computer Science and Engineering Koneru Lakshmaiah Deemed to be University Guntur Andhra Pradesh India

Verification and completeness are main challenges for today's ever more diverse supply chains. Even with the ability to counter blockchain technologies by offering a trail of manipulation-resistant audit It does not address the confidence issue associated with the source chain activities also information related to a produce life cycle Information itself. Reputation mechanisms are a promising solution for this faith problem. Yet existing structures of credibility are Not ideal for supply chain applications based on blockchain as centred on restricted findings, lack of granularity and their overhead was not discussed and automation. We recommend the system as a three-layer faith in this job. Management platform is using a blockchain consortium tracking relationships between actors in the supply chain and Assign trust and prestige dynamically dependent on these interactions. Its novelty is based on a Model for credibility assessing product quality and the trust of individuals based on many observations funding for credibility qualities in supply chain incidents separating the member in the supply chain from the goods, enables brand credibility to be reserved for smart contracts for straightforward use by the same participant, Effective, secure, and automatic credibility scoring measurement, and the latency and throughput minimum overhead as compared to a straightforward supply chain model based on blockchain.

关键词：

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Single-Shot diagnosis of Electron Energy Evolution via Streaked Betatron X Rays in a Curved laser Wakefield Accelerator

引用

Physical Review letters 2024年第22期132卷 225001-225001页

作者： Y. Ma J. A. Cardarelli P. T. Campbell S. Fourmaux R. Fitzgarrald M. d. Balcazar A. F. Antoine N. F. Beier Q. Qian A. E. Hussein B. Kettle S. R. Klein K. Krushelnick Y. F. li S. P. d. Mangles G. Sarri d. Seipt V. Senthilkumaran M. J. V. Streeter l. Willingale A. G. R. Thomas Gérard Mourou Center for Ultrafast Optical Science University of Michigan Ann Arbor Michigan 48109-2099 USA Institut National de la Recherche Scientifique - Énergie Matériaux et Télécommunications Université du Québec (INRS-EMT) 1650 Lionel Boulet Varennes Québec J3X 1P7 Canada Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta T6G 1H9 Canada The John Adams Institute for Accelerator Science Imperial College London London SW7 2AZ United Kingdom Institute of Physics Chinese Academy of Sciences Beijing 100190 China School of Mathematics and Physics Queen’s University Belfast Belfast BT7 1NN United Kingdom Helmholtz Institut Jena Fröbelstieg 3 Jena 07743 Germany GSI Helmholtzzentrum für Schwerionenforschung GmbH Planckstraße 1 64291 Darmstadt Germany

We report on an experimental observation of the streaking of betatron x rays in a curved laser wakefield accelerator. The streaking of the betatron x rays was realized by launching a laser pulse into a plasma with a transverse density gradient. By controlling the plasma density and the density gradient, we realized the steering of the laser driver, electron beam, and betatron x rays simultaneously. Moreover, we observed an energy-angle correlation of the streaked betatron x rays and utilized it in diagnosing the electron acceleration process in a single-shot mode. Our work could also find applications in advanced control of laser beam and particle propagation. More importantly, the angular streaked betatron x ray has an intrinsic spatiotemporal correlation, which makes it a promising tool for single-shot pump-probe applications.

关键词： laser wakefield acceleration Plasma acceleration & new acceleration techniques X-ray generation in plasmas X-ray techniques

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Methodology for Classification and Segmentation of Multiple Sclerosis Affected Brain MRI Images

Methodology for Classification and Segmentation of Multiple ...

引用

Bangalore Humanitarian Technology Conference (B-HTC), IEEE

作者： Prakash H. Unki B.L.D.E.A's V. P. Dr. P. G. Halakatti College of Engineering and Technology (Affiliated to Visvesvaraya Technological University Belgaum) Vijayapur Belgaum Karnataka India

ISBN: (数字)9781728187945

ISBN: (纸本)9781728187952

A methodology is developed for classification of brain MRI images as normal and affected by multiple sclerosis (MS). The classification of brain MR images into normal and MS using Back propagation neural network (BPNN) has given maximum accuracy of 96% for the combination of all the texture features. The segmentation of MS lesions is carried out using k-means segmentation with an accuracy of 86%. The k-means segmentation method has given more sensitivity, specificity and accuracy compared to Fuzzy-C-Means (FCM). The work carried out has given good classification & segmentation accuracy and has scope for further improvement.

关键词： lesions Magnetic resonance imaging Image segmentation Feature extraction Classification algorithms Clustering algorithms Sensitivity

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Modelling of Circuit Breaker using ATPdraw

Modelling of Circuit Breaker using ATPdraw

引用

International Conference for Convergence of Technology (I2CT)

作者： Viren Patel Krunal Kansara S.N. Shivani Electrical Engineering L D College of Engineering Ahmedabad India Power Grid High Voltage-TC ABB India Ltd Vadodara India

Here four mathematical models are modelled in ATPdraw. User defined model library block is programed to represent circuit breaker in ATPdraw. Circuit breaker model output is observed in diversified conditions. All fou... 详细信息

ISBN: (数字)9781538680759

ISBN: (纸本)9781538680766

关键词： Integrated circuit modeling Mathematical model Circuit breakers Cooling Numerical models Contacts Predictive models

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development of Computational Assessment Model of Fuzzy Rule Based Evaluation of Groundwater Quality Index: Comparison and Analysis with Conventional Index

SSRN

引用

SSRN 2019年

作者： Nigam, Utkarsh Yadav, S.M. Civil Engg. Department L.D. College of Engineering Gujarat Ahmedabad India Civil Engineering Department SVNIT Surat India

Fuzzy rule based technique and fuzzy logic has wide application in engineering fields. Fuzzy logic is not limited to any prescribed field of engineering it can be used in communication sectors as well as it can be used in core branches such as Civil and mechanical engineering. Fuzzy logic has also its application in the field of environmental and water resources. Fuzzy logic is a probabilistic approach which is used to demonstrate the partial truth and incorporate uncertain conditions to deal very important problems. Fuzzy logic has wide spread applications in environmental engineering and water quality. In the present study fuzzy rule based models have been developed for the assessment of groundwater quality index and the same has been compared with conventional groundwater quality index. The values of groundwater quality parameters for the development of model has been taken as per WHO (world health organization) and GPCB (Gujarat Pollution Control Board) standards. Both the quality index have been compared on the basis of development of framework and derived results from earlier researches shows that fuzzy rule based computational model gives prominent results when compared to conventional groundwater quality index. © 2019, The Authors. All rights reserved.

关键词： Water quality

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