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作者： Chen, Mo Herbert, Sylvia L. Hu, Haimin Pu, Ye Fisac, Jaime Fernandez Bansal, Somil Han, Soojean Tomlin, Claire J. School of Computing Science Simon Fraser University BurnabyBCV5A 1S6 Canada Department of Mechanical and Aerospace Engineering University of California San Diego San DiegoCA92122 United States Department of Electrical Engineering Princeton University PrincetonNJ08536 United States Department of Electrical and Electronic Engineering University of Melbourne ParkvilleVIC3010 Australia Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA94704 United States Control and Dynamical Systems Program California Institute of Technology Los AngelesCA90019 United States

Real-time, guaranteed safe trajectory planning is vital for navigation in unknown environments. However, real-time navigation algorithms typically sacrifice robustness for computation speed. Alternatively, provably safe trajectory planning tends to be too computationally intensive for real-time replanning. We propose FaSTrack, Fast and Safe Tracking, a framework that achieves both real-time replanning and guaranteed safety. In this framework, real-time computation is achieved by allowing any trajectory planner to use a simplified planning model of the system. The plan is tracked by the system, represented by a more realistic, higher dimensional tracking model. We precompute the tracking error bound (TEB) due to mismatch between the two models and due to external disturbances. We also obtain the corresponding tracking controller used to stay within the TEB. The precomputation does not require prior knowledge of the environment. We demonstrate FaSTrack using Hamilton-Jacobi reachability for precomputation and three different real-time trajectory planners with three different tracking-planning model pairs. © 1963-2012 IEEE.

关键词： Real time systems

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First measurement of the strange axial coupling constant using neutral-current quasielastic interactions of atmospheric neutrinos at KamLAND

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Physical Review D 2023年第7期107卷 072006-072006页

作者： S. Abe S. Asami M. Eizuka S. Futagi A. Gando Y. Gando T. Gima A. Goto T. Hachiya K. Hata K. Ichimura S. Ieki H. Ikeda K. Inoue K. Ishidoshiro Y. Kamei N. Kawada Y. Kishimoto M. Koga M. Kurasawa T. Mitsui H. Miyake T. Nakahata K. Nakamura R. Nakamura H. Ozaki T. Sakai I. Shimizu J. Shirai K. Shiraishi A. Suzuki Y. Suzuki A. Takeuchi K. Tamae H. Watanabe Y. Yoshida S. Obara A. K. Ichikawa S. Yoshida S. Umehara K. Fushimi K. Kotera Y. Urano B. E. Berger B. K. Fujikawa J. G. Learned J. Maricic S. N. Axani Z. Fu J. Smolsky L. A. Winslow Y. Efremenko H. J. Karwowski D. M. Markoff W. Tornow J. A. Detwiler S. Enomoto M. P. Decowski C. Grant A. Li H. Song S. Dell’Oro T. O’Donnell Research Center for Neutrino Science Tohoku University Sendai 980-8578 Japan Department of Human Science Obihiro University of Agriculture and Veterinary Medicine Obihiro 080-8555 Japan Kavli Institute for the Physics and Mathematics of the Universe (WPI) The University of Tokyo Institutes for Advanced Study The University of Tokyo Kashiwa Chiba 277-8583 Japan Graduate Program on Physics for the Universe Tohoku University Sendai 980-8578 Japan Frontier Research Institute for Interdisciplinary Sciences Tohoku University Sendai 980-8578 Japan Department of Physics Tohoku University Sendai 980-8578 Japan Graduate School of Science Osaka University Toyonaka Osaka 560-0043 Japan Research Center for Nuclear Physics Osaka University Ibaraki Osaka 567-0047 Japan Department of Physics Tokushima University Tokushima 770-8506 Japan Graduate School of Integrated Arts and Sciences Tokushima University Tokushima 770-8502 Japan Nuclear Science Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Department of Physics and Astronomy University of Hawaii at Manoa Honolulu Hawaii 96822 USA University of Delaware Newark Delaware 19716 USA Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Physics and Astronomy University of Tennessee Knoxville Tennessee 37996 USA Triangle Universities Nuclear Laboratory Durham North Carolina 27708 USA Physics Departments at Duke University Durham North Carolina 27708 USA North Carolina Central University Durham North Carolina 27707 USA and The University of North Carolina at Chapel Hill Chapel Hill North Carolina 27599 USA Center for Experimental Nuclear Physics and Astrophysics University of Washington Seattle Washington 98195 USA Nikhef and the University of Amsterdam Science Park Amsterdam The Netherlands Boston University Boston Massachusetts 02215 USA Center for Neutrino Physics Virginia Polytechnic Institute and State University Blacksburg Virginia 24061 US

We report a measurement of the strange axial coupling constant gAs using atmospheric neutrino data at KamLAND. This constant is a component of the axial form factor of the neutral-current quasielastic (NCQE) interaction. The value of gAs significantly changes the ratio of proton and neutron NCQE cross sections. KamLAND is suitable for measuring NCQE interactions as it can detect nucleon recoils with low-energy thresholds and measure neutron multiplicity with high efficiency. KamLAND data, including the information on neutron multiplicity associated with the NCQE interactions, makes it possible to measure gAs with a suppressed dependence on the axial mass MA, which has not yet been determined. For a comprehensive prediction of the neutron emission associated with neutrino interactions, we establish a simulation of particle emission via nuclear deexcitation of C12, a process not considered in existing neutrino Monte Carlo event generators. Energy spectrum fitting for each neutron multiplicity gives gAs=−0.14−0.26+0.25, which is the most stringent limit obtained using NCQE interactions without MA constraints. The two-body current contribution considered in this analysis relies on a theoretically effective model and electron scattering experiments and requires future verification by direct measurements and future model improvement.

关键词： Neutrinos

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HIGH ORDER CURVATURE FLOWS OF PLANE CURVES WITH GENERALISED NEUMANN BOUNDARY CONDITIONS

arXiv

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arXiv 2020年

作者： McCoy, James Wheeler, Glen Wu, Yuhan Priority Research Centre Computer Assisted Research Mathematics School of Mathematical and Physical Sciences University of Newcastle Australia Okinawa Institute for Science and Technology Graduate University Japan Institute for Mathematics and its Applications University of Wollongong

We consider the parabolic polyharmonic diffusion and L2-gradient flows of the m-th arclength derivative of curvature for regular closed curves evolving with generalised Neumann boundary conditions. In the polyharmonic case, we prove that if the curvature of the initial curve is small in L2, then the evolving curve converges exponentially in the C∞ topology to a straight horizontal line segment. The same behaviour is shown for the L2gradient flow provided the energy of the initial curve is sufficiently small. In each case the smallness conditions depend only on *** Codes 53C44, 35K25 Copyright © 2020, The Authors. All rights reserved.

关键词： Boundary conditions

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RESURGENCE, HABIRO ELEMENTS AND STRANGE IDENTITIES

arXiv

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arXiv 2023年

作者： Crew, Samuel Fantini, Veronica Goswami, Ankush Osburn, Robert Wheeler, Campbell Department of Mathematics Imperial College London South Kensington Campus LondonSW7 2AZ United Kingdom Laboratoire Mathématique Orsay Faculté des Sciences d’Orsay Université Paris-Saclay Building 307 rue Michel Magat OrsayF-91405 Cedex France School of Mathematical and Statistical Sciences the University of Texas Rio Grande Valley 1201 W. University Dr. EdinburgTX78539 United States School of Mathematics and Statistics University College Dublin Belfield Dublin 4 Ireland Theoretical Sciences Visiting Program Okinawa Institute of Science and Technology Graduate University Onna904-0495 Japan IHÉS Le Bois-Marie 35 route de Chartres Bures-sur-Yvette91440 France

We prove resurgence properties for the Borel transform of a formal power series associated to elements in the Habiro ring that come from radial limits of partial theta series via strange identities. As an application, we prove a conjecture in quantum topology due to Costin and Garoufalidis for two families of torus *** Codes 57K16, 11F37, 30B40, 40A05 Copyright © 2023, The Authors. All rights reserved.

关键词： Topology

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Unraveling the genetic mechanisms of UV radiation resistance in Bacillus through biofilm formation, sporulation, and carotenoid production

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Genomics 2025年第4期117卷 111066页

作者： Prasansah Shrestha Byeollee Kim So-Ra Han Hyun Lee Tae-Jin Oh Department of Life Science and Biochemical Engineering Graduate School SunMoon University Asan 31460 Republic of Korea Bio Big Data-based Chungnam Smart Clean Research Leader Training Program SunMoon University Asan 31460 Republic of Korea Genome-based BioIT Convergence Institute Asan 31460 Republic of Korea. Genome-based BioIT Convergence Institute Asan 31460 Republic of Korea Department of Life Science and Biochemical Engineering Graduate School SunMoon University Asan 31460 Republic of Korea. Division of Computer Science and Engineering SunMoon University Asan 31460 Republic of Korea. Department of Pharmaceutical Engineering and Biotechnology SunMoon University Asan 31460 Republic of Korea. Electronic address: tjoh3782@sunmoon.ac.kr.

Bacillus species are Gram-positive bacteria that are rod-shaped, endospore-forming, and aerobic or facultatively anaerobic. With over 300 recognized species, Bacillus subtilis stands out as a well-studied model organism. The genus's various species exhibit a wide range of physiological capabilities, allowing them to thrive in diverse environmental conditions. Each cell produces a single endospore, which is highly resistant to heat, cold, radiation, desiccation, and disinfectants. Among Bacillus strains, those capable of producing spores, biofilms, and carotenoids demonstrate significant resilience to UV light. This review examines the genes involved in spore formation, biofilm development, and carotenoid synthesis, emphasizing their roles in UV radiation survival. We explore the interconnections between these processes and their combined contribution to UV resistance, focusing on the underlying genetic mechanisms. These insights will benefit researchers studying the genetic basis of UV radiation resistance in Bacillus species. IMPORTANCE: Bacteria employ adaptive strategies in extreme environments through rapid changes in gene expression, altering their phenotype for survival. Bacillus species, for example, defend against UV radiation by making spores, creating biofilms, and producing pigments. During sporulation, sigma factors (σ, σ, σ, and σ) regulate gene expression to adapt to environmental shifts. It has been found that the spores of some species may contain pigments that strongly absorb UV radiation, playing a crucial role in spore UV resistance. UV light penetrates biofilm matrices minimally, mainly affecting surface cells, which produce compounds like mycosporine-like amino acids and carotenoids to shield against UV damage.

关键词： Bacillus Biofilm Carotenoid Spore UV-radiation resistance

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Performance and Optimization of Reconfigurable Intelligent Surface Aided THz Communications

arXiv

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arXiv 2020年

作者： Du, Hongyang Zhang, Jiayi Guan, Ke Niyato, Dusit Jiao, Huiying Wang, Zhiqin Kürner, Thomas The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The School of Computer Science and Engineering Nanyang Technological University Singapore China Academy of Information and Communications Technology Beijing100191 China Technische Universität Braunschweig Brunswick38106 Germany

TeraHertz (THz) communications can satisfy the high data rate demand with massive bandwidth. However, severe path attenuation and hardware imperfection greatly alleviate its performance. Therefore, we utilize the reconfigurable intelligent surface (RIS) technology and investigate the RIS-aided THz communications. We first prove that the small-scale amplitude fading of THz signals can be accurately modeled by the fluctuating two-ray distribution based on two THz signal measurement experiments conducted in a variety of different scenarios. To optimize the phase-shifts at the RIS elements, we propose a novel swarm intelligence-based method that does not require full channel estimation. We then derive exact statistical characterizations of end-to-end signal-to-noise plus distortion ratio (SNDR) and signal-to-noise ratio (SNR). Moreover, we present asymptotic analysis to obtain more insights when the SNDR or the number of RIS's elements is high. Finally, we derive analytical expressions for the outage probability and ergodic capacity. The tight upper bounds of ergodic capacity for both ideal and non-ideal radio frequency chains are obtained. It is interesting to find that increasing the number of RIS's elements can significantly improve the THz communications system performance. For example, the ergodic capacity can increase up to 25% when the number of elements increases from 40 to 80, which incurs only insignificant costs to the system. © 2020, CC BY.

关键词： Signal to noise ratio

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LearningEMS: A Unified Framework and Open-source Benchmark for Learning-based Energy Management of Electric Vehicles

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Engineering 2024年

作者： Yong Wang Hongwen He Yuankai Wu Pei Wang Haoyu Wang Renzong Lian Jingda Wu Qin Li Xiangfei Meng Yingjuan Tang Fengchun Sun Amir Khajepour School of Mechanical Engineering Beijing Institute of Technology Beijing 100081 China College of Computer Science Sichuan University Chengdu 100081 China Shenzhen International Graduate School Tsinghua University Shenzhen 518000 China The Hong Kong Polytechnic University Hong Kong 999077 China School of Mechanical Engineering Guangxi University Nanning 530000 China Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON N2L3G1 Canada

An effective energy management strategy (EMS) is essential to optimize the energy efficiency of electric vehicles (EVs). With the advent of advanced machine learning techniques, the focus on developing sophisticated EMS for EVs is increasing. Here, we introduce LearningEMS: a unified framework and open-source benchmark designed to facilitate rapid development and assessment of EMS. LearningEMS is distinguished by its ability to support a variety of EV configurations, including hybrid EVs, fuel cell EVs, and plug-in EVs, offering a general platform for the development of EMS. The framework enables detailed comparisons of several EMS algorithms, encompassing imitation learning, deep reinforcement learning (RL), offline RL, model predictive control, and dynamic programming. We rigorously evaluated these algorithms across multiple perspectives: energy efficiency, consistency, adaptability, and practicability. Furthermore, we discuss state, reward, and action settings for RL in EV energy management, introduce a policy extraction and reconstruction method for learning-based EMS deployment, and conduct hardware-in-the-loop experiments. In summary, we offer a unified and comprehensive framework that comes with three distinct EV platforms, over 10 000 km of EMS policy data set, ten state-of-the-art algorithms, and over 160 benchmark tasks, along with three learning libraries. Its flexible design allows easy expansion for additional tasks and applications. The open-source algorithms, models, data sets, and deployment processes foster additional research and innovation in EV and broader engineering domains.

关键词： Energy management Electric vehicles Reinforcement learning Machine learning Open-source benchmark

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Back Cover Image, Volume 7, Number 4, April 2025

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Carbon Energy 2025年第4期7卷

作者： Jiao Yang Xiaoyang Zheng Syed Shoaib Ahmad Shah Chao Wang Xueyao Li Zhishuo Yan Lishan Peng Key Laboratory of Rare Earths Ganjiang Innovation Academy Chinese Academy of Sciences Ganzhou China Institute of Applied Physics and Materials Engineering University of Macau Macao SAR China Department of Mechanical Engineering Graduate School of Engineering The University of Tokyo Tokyo Japan Department of Chemistry School of Natural Sciences National University of Sciences and Technology Islamabad Pakistan Department of Chemistry University of Connecticut Storrs Connecticut USA School of Rare Earths University of Science and Technology of China Hefei China Department of Electrical and Computer Engineering North Dakota State University Fargo USA

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Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients

IEEE Transactions on Technology and Society

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IEEE Transactions on technology and Society 2022年第4期3卷 272-289页

作者： Allahabadi, Himanshi Amann, Julia Balot, Isabelle Beretta, Andrea Binkley, Charles Bozenhard, Jonas Bruneault, Frederick Brusseau, James Candemir, Sema Cappellini, Luca Alessandro Chakraborty, Subrata Cherciu, Nicoleta Cociancig, Christina Coffee, Megan Ek, Irene Espinosa-Leal, Leonardo Farina, Davide Fieux-Castagnet, Genevieve Frauenfelder, Thomas Gallucci, Alessio Giuliani, Guya Golda, Adam Van Halem, Irmhild Hildt, Elisabeth Holm, Sune Kararigas, Georgios Krier, Sebastien A. Kuhne, Ulrich Lizzi, Francesca Madai, Vince I. Markus, Aniek F. Masis, Serg Mathez, Emilie Wiinblad Mureddu, Francesco Neri, Emanuele Osika, Walter Ozols, Matiss Panigutti, Cecilia Parent, Brendan Pratesi, Francesca Moreno-Sanchez, Pedro A. Sartor, Giovanni Savardi, Mattia Signoroni, Alberto Sormunen, Hanna-Maria Spezzatti, Andy Srivastava, Adarsh Stephansen, Annette F. Theng, Lau Bee Tithi, Jesmin Jahan Tuominen, Jarno Umbrello, Steven Vaccher, Filippo Vetter, Dennis Westerlund, Magnus Wurth, Renee Zicari, Roberto V. Ey Netherlands Enterprise Intelligence Department Amsterdam1083 HP Netherlands Eth Zurich Health Ethics and Policy Lab Department of Health Sciences and Technology Zürich8092 Switzerland Center for Diplomatic and Strategic Studies Postgraduate Studies in Diplomacy and International Relations Paris75015 France Pisa56124 Italy Hackensack Meridian Health Bioethics Center EdisonNJ08820 United States University of Oxford Faculty of Philosophy OxfordOX2 6GG United Kingdom Collège André- Laurendeau Philosophie Department MontrealQCH8N 2J4 Canada Université du Québec À Montréal École des Médias MontrealQCH2L 2C4 Canada Pace University Philosophy Department New YorkNY10038 United States The Ohio State University Wexner Medical Center Department of Radiology ColumbusOH43210 United States Humanitas Research Hospital Department of Radiology Milan20089 Italy Humanitas University Department of Biomedical Sciences Milan20089 Italy University of New England Faculty of Science Agriculture Business and Law ArmidaleNSW2351 Australia University of Technology Sydney Faculty of Engineering and Information Technology SydneyNSW2007 Australia Scuola Superiore Sant'Anna European Centre of Excellence on the Regulation of Robotics and Ai Pisa56127 Italy University of Bremen Group of Computer Architecture Bremen28359 Germany New York University Grossman School of Medicine Division of Infectious Diseases and Immunology Department of Medicine New YorkNY10016 United States Digital Institute Ai Research Section Stockholm16731 Sweden Arcada University of Applied Sciences Department of Business Management and Analytics Helsinki00550 Finland University of Brescia Radiological Sciences and Public Health Department of Medical and Surgical Specialties Brescia25121 Italy Sncf Reseau Sa Ethique Groupe La Plaine93418 France Institute of Diagnostic and Interventional Radiology University Hospital Zurich Zürich8091 Switzerland Eindhoven University of Tech

This article's main contributions are twofold: 1) to demonstrate how to apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare and 2) to investigate the research question of what does 'trustworthy AI' mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multiregional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient's lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia, Italy, since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection®, uses sociotechnical scenarios to identify ethical, technical, and domain-specific issues in the use of the AI system in the context of the pandemic. © 2020 IEEE.

关键词： COVID-19

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Venous Air Embolism: A Systematic Review

CHEST Critical Care

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CHEST Critical Care 2024年第1期2卷 100049-100049页

作者： Alzghoul, Hamza Obeidat, Omar Abughazaleh, Saeed Al-Ani, Abdallah Al-Jabali, Ahmad Khrais, Mohammad Z. Tarawneh, Mohammed Al-Ani, Hashim Ismail, Mohamed F. De villa, Ariel Ruiz Haider, Asad Alzghoul, Bashar N. Samhouri, Bilal F. Graduate Medical Education University of Central Florida College of Medicine Orlando Internal Medicine Residency Program North Florida Regional Medical Center Gainesville FL United States Division of Pulmonary Critical Care and Sleep Medicine University of Florida Gainesville FL United States St. Elizabeth Medical Center Tufts University School of Medicine Brighton MA Department of Internal Medicine University of Arkansas for Medical Sciences Little Rock AR United States Division of Pulmonary and Critical Care Medicine Asante Health System Medford OR United States Office of Scientific Affairs and Research King Hussein Cancer Center Amman Jordan Faculty of Medicine Jordan University of Science and Technology Irbid Jordan

Background: Venous air embolism (VAE) is an understudied entity. Herein, we summarize VAE case reports and small case series reported in the literature. Research Question: What are the clinical features, diagnostic approaches, and clinical outcomes of VAE and how do surgery-related VAEs compare with non-surgery-related VAEs? Study Design and Methods: Using the search terms air, gas, venous, and embolism, 437 articles were identified. After applying predetermined exclusion criteria, we included the 164 articles describing cases of isolated VAE. We extracted data pertaining to patient demographics and clinical presentations;VAE characteristics, for example, cause and clinical context;diagnostic testing and time to diagnosis;and clinical management and outcomes. We used the Shapiro-Wilk test to assess data distribution (ie, normally vs nonnormally distributed), the Pearson χ² test for categorical variables, and the Mann-Whitney U test and t test for continuous variables. Results: We collated 174 patients;108 patients (62.1%) were male. Most VAE episodes (n = 160 [92%]) were iatrogenic. Eighty-two patients (47%) experienced respiratory, cardiac, or neurologic symptoms, or a combination thereof, whereas 15 patients (8.6%) were asymptomatic;the remaining patients (n = 77 [44.3%]) had collapsed or been intubated before VAE diagnosis. Most patients (56.9%) were hemodynamically unstable on presentation. Diagnostic and management approaches varied considerably across reports. Of management strategies, oxygen supplementation (FIO₂ = 1.0) and body repositioning were implemented most frequently. Seventy-nine patients (45%) received ICU level of care, 13 patients (7.5%) underwent endotracheal intubation, 39 patients (22.4%) received inotropic support, and 32 patients (18.4%) died. Compared with patients with non-surgery-related VAEs, those with surgery-related VAEs underwent end-tidal CO₂ measurement more frequently (50% vs 3%;P <.001) and showed

关键词： EtCO2 monitoring gas embolism venous air embolism

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