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2017 IASTED International Conference on Modelling, Identification and Control, MIC 2017

作者： Liu, Fang Liu, Xin Liu, Jiaqi National Key Laboratory of Science and Technology On Test Physics and Numerical Mathematics Nandahongmen Road No.1 Beijing China

ISBN: (纸本)9780889869882

An observation model of unmanned aerial vehicle(UAV) infrared detector is developed. The visibility criterion is derived via geometric relationships between the infrared detector, target and earth, the constraint of the detector's frame angle, and the detection range of infrared detector. Because of the infrared sensor can only obtain the angular information of the target, so it is impossible for one detector to locate position of the target. The position of the target is obtained by two or more detectors. The least square method based multi-sensor target tracking method is introduced. It is important to set a filter before using the tracking data as there are observation errors caused by UAV position error, UAV attitude error, sensor pointing error and sensor image plane position error. The extend Kalman Filter (EKF) algorithm is used to smooth the tracking signals. Finally, two UAV infrared detectors observing a low-orbit target is simulated for their observation performance. The result shows that the infrared detectors can observe the target within the scope of the detection range. When the target flies off the top of the UAV, the detectors can't observe it because of the constraint of the frame angle. The observation error is reduced substantially after the EKF is used.

关键词： Infrared detectors

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Electronic Supplementary Material to:The Predictability of Ocean Environments that Contributed to the 2020/21 Extreme Cold Events in China: 2020/21 La Ni?a and 2020 Arctic Sea Ice Loss*

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大气科学进展（英文版） 2022年第4期39卷后插1-后插3页

作者： Fei ZHENG Ji-Ping LIU Xiang-Hui FANG Mi-Rong SONG Chao-Yuan YANG Yuan YUAN Ke-Xin LI Ji WANG Jiang ZHU International Center for Climate and Environment Science(ICCES) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science& TechnologyNanjing 210044China Department of Atmospheric and Environmental Sciences University at Albany State University of New YorkAlbanyNY 12222USA Department of Atmospheric and Oceanic Sciences& Institute of Atmospheric Sciences Fudan UniversityShanghai 200438China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China School of Atmospheric Sciences Sun Yat-sen UniversityZhuhai 519082China National Climate Center Beijing 100081China International Center for Climate and Environment Science(ICCES) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of Chinese Academy of Sciences Beijing 100049China Beijing Municipal Climate Center Beijing 100089China

Introduction:This file provides supplementary material on the brief descriptions of the IAP EPS and the pan-Arctic prediction sys-tems and components discussed in the main article. The additional figures comparing the...

Introduction: This file provides supplementary material on the brief descriptions of the IAP EPS and the pan-Arctic prediction sys-tems and components discussed in the main article. The additional figures comparing the best and worst Arctic sea-ice predic-tion members are also contained in the supplementary file.

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Determination of epsilon for Omega vortex identification method

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Journal of Hydrodynamics 2018年第4期30卷 541-548页

作者：董祥瑞王义乾陈小平 Yinlin Dong 张宇宁 Chaoqun Liu National Key Laboratory of Transient Physics Nanjing University of Science and Technology Department of Mathematics University of Texas at Arlington School of Aerospace Engineering Tsinghua University School of Mechanical Engineering Zhejiang Sci-Tech University Department of Mathematics University of Central Arkansas Key Laboratory of Condition Monitoring and Control for Power Plant Equipment (Ministry of Education) School of Energy Power and Mechanical Engineering North China Electric Power University Beijing Key Laboratory of Emission Surveillance and Control for Thermal Power Generation North China Electric Power University

In the present paper, epsilon（ε） in the Omega vortex identification criterion（ Ω method） is defined as an explicit function in order to apply the Ω method to different cases and even different time steps for the unsteady cases. In our method, e is defined as a function relating with the flow without any subjective adjustment on its coefficient. The newly proposed criteria for the determination of ε is tested in several typical flow cases and is proved to be effective in the current work. The test cases given in the present paper include boundary layer transition, shock wave and boundary layer interaction, and channel flow with different Reynolds numbers.

关键词： Vortex identification vorticity deformation turbulence

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AGN STORM 2: X. The origin of the interband continuum delays in Mrk 817∗

arXiv

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arXiv 2024年

作者： Netzer, Hagai Goad, Michael R. Barth, Aaron J. Cackett, Edward M. Horne, Keith Hu, Chen Kara, Erin Korista, Kirk T. Kriss, Gerard A. Lewin, Collin Montano, John Arav, Nahum Behar, Ehud Brotherton, Michael S. Chelouche, Doron De Rosa, Gisella Bontà, Elena Dalla Dehghanian, Maryam Ferland, Gary J. Fian, Carina Homayouni, Yasaman Ilić, Dragana Kaspi, Shai Kovačević, Andjelka B. Landt, Hermine Popović, Luka Č. Storchi-Bergmann, Thaisa Wang, Jian-Min Zaidouni, Fatima School of Physics and Astronomy Tel Aviv University Tel Aviv6997801 Israel School of Physics and Astronomy University of Leicester University Road LeicesterLE1 7RH United Kingdom Department of Physics and Astronomy 4129 Frederick Reines Hall University of California IrvineCA92697-4575 United States Department of Physics and Astronomy Wayne State University 666 W. Hancock St DetroitMI48201 United States SUPA School of Physics and Astronomy North Haugh St. AndrewsKY16 9SS United Kingdom Key Laboratory for Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences 19B Yuquan Road Beijing100049 China MIT Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Western Michigan University 1120 Everett Tower KalamazooMI49008-5252 United States Space Telescope Science Institute 3700 San Martin Drive BaltimoreMD21218 United States National Astronomical Observatories of China 20A Datun Road Beijing100020 China Department of Physics Virginia Tech BlacksburgVA24061 United States Department of Physics Technion Haifa32000 Israel Department of Physics and Astronomy University of Wyoming LaramieWY82071 United States Department of Physics Faculty of Natural Sciences University of Haifa Haifa3498838 Israel Haifa Research Center for Theoretical Physics and Astrophysics University of Haifa Haifa3498838 Israel Dipartimento di Fisica e Astronomia "G. Galilei " Università di Padova Vicolo dell’Osservatorio 3 PadovaI-35122 Italy INAF-Osservatorio Astronomico di Padova Vicolo dell’Osservatorio 5 PadovaI-35122 Italy Jeremiah Horrocks Institute University of Central Lancashire PrestonPR1 2HE United Kingdom Department of Physics and Astronomy The University of Kentucky LexingtonKY40506 United States Departamento de Astronomía y Astrofísica Universidad de Valencia Burjassot ValenciaE-46100 Spain Observatorio Astronómico Universidad de Va

The local (z=0.0315) AGN Mrk 817, was monitored over more than 500 days with space-borne and ground-based instruments as part of a large international campaign AGN STORM 2. Here, we present a comprehensive analysis of the broad-band continuum variations using detailed modeling of the broad line region (BLR), several types of disk winds classified by their optical depth, and new numerical simulations. We find that diffuse continuum (DC) emission, with additional contributions from strong and broad emission lines, can explain the continuum lags observed in this source during high and low luminosity phases. Disk illumination by the variable X-ray corona contributes only a small fraction of the observed continuum lags. Our BLR models assume radiation pressure-confined clouds distributed over a distance of 2-122 light days. We present calculated mean-emissivity radii of many emission lines, and DC emission, and suggest a simple, transfer-function-dependent method that ties them to cross-correlation lag determinations. We do not find clear indications for large optical depth winds but identify the signature of lower column density winds. In particular, we associate the shortest observed continuum lags with a combination of τ(1 Ryd)≈ 2 wind and a partly shielded BLR. Even smaller optical depth winds may be associated with X-ray absorption features and with noticeable variations in the width and lags of several high ionization lines like He ii and C iv. Finally, we demonstrate the effect of torus dust emission on the observed lags in the i and z bands. © 2024, CC BY.

关键词： X ray absorption

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The way from natural to artificial - The story of periodic electromagnetic structures

The way from natural to artificial - The story of periodic e...

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2017 International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2017

作者： Zhang, Shengjun Wang, Mingliang Ai, Xia Wang, Weidong Wu, Runhui Liu, Xin Liu, Jiaqi Meng, Gang Sun, Yuan National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China Institute of Effectiveness Evaluation of Flying Vehicle Beijing China

In this paper, the general of artificial electromagnetic structure with analog to the natural materials were briefly reviewed. The lattice theory of artificial structure was suggested to be built. © 2017 Applied ... 详细信息

ISBN: (纸本)9780996007856

关键词： Lattice theory

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Magnetic and topological transitions in three-dimensional topological Kondo insulator

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Chinese physics Letters 2018年第12期35卷 59-63页

作者：黎欢王志勇郑晓军刘瑜钟寅 College of Science Guilin University of Technology Institute of Applied Physics and Computational Mathematics Software Center for High Performance Numerical Simulation China Academy of Engineering Physics Center for Interdisciplinary Studies & Key Laboratory for Magnetism and Magnetic Materials of the MoE Lanzhou University

Using an extended slave-boson method,we draw a global phase diagram summarizing both magnetic phases and paramagnetic（PM） topological insulators（TIs） in a three-dimensional topological Kondo insulator（TKI）. By including electron hopping（EH） up to the third neighbors, we identify four strong TI（STI） phases and two weak TI（WTI） phases. Then, the PM phase diagrams characterizing topological transitions between these TIs are depicted as functions of EH,f-electron energy level,and hybridization constant. We also find an insulator-metal transition from an STI phase that has surface Fermi rings and spin textures in qualitative agreement with the TKI candidate SmBs. In the weak hybridization regime, antiferromagnetic（AF） order naturally arises in the phase diagrams. Depending on how the magnetic boundary crosses the PM topological transition lines,AF phases are classified into the AF topological insulator（AFTI） and the non-topological AF insulator, according to their Z2 indices. In two small regions of parameter space, two distinct topological transition processes between AF phases occur, leading to two types of AFTIs showing distinguishable surface dispersions around their Dirac points.

关键词： STI WTI TKI

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Co-Assembly Induced Solid-State Stacking Transformation in Amino Acid-Based Crystals with Enhanced Physical Properties

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Angewandte Chemie 2022年第17期134卷

作者： Prof. Wei Ji Hui Yuan Dr. Bin Xue Dr. Sarah Guerin Dr. Hui Li Dr. Lei Zhang Yanqing Liu Dr. Linda J. W. Shimon Prof. Mingsu Si Prof. Yi Cao Prof. Wei Wang Prof. Damien Thompson Prof. Kaiyong Cai Prof. Rusen Yang Prof. Ehud Gazit Key Laboratory of Biorheological Science and Technology Ministry of Education The National “111” Project for Biomechanics and Tissue Repair Engineering College of Bioengineering Chongqing University Chongqing 400044 P. R. China School of Molecular Cell Biology and Biotechnology George S. Wise Faculty of Life Sciences Tel Aviv University Tel Aviv 6997801 Israel School of Advanced Materials and Nanotechnology Xidian University Xi'an 710126 China National Laboratory of Solid State Microstructure Department of Physics Nanjing University Nanjing 210093 Jiangsu China Department of Physics Bernal Institute University of Limerick Limerick V94 T9PX Ireland Science and Technology on Combustion and Explosion Laboratory Xi'an Modern Chemistry Research Institute Xi'an 710065 China CAEP Software Center for High Performance Numerical Simulation Beijing 100088 China Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education Lanzhou University Lanzhou 730000 China Department of Chemical Research Support Weizmann Institute of Science Rehovot 7610001 Israel

The physical characteristics of supramolecular assemblies composed of small building blocks are dictated by molecular packing patterns in the solid-state. Yet, the structure–property correlation is still not fully understood. Herein, we report the unexpected cofacial to herringbone stacking transformation of a small aromatic bipyridine through co-assembly with acetylated glutamic acid. The unique solid-state structural transformation results in enhanced physical properties of the supramolecular organizations. The co-assembly methodology was further expanded to obtain diverse molecular packings by different bipyridine and acetylated amino acid derivatives. This study presents a feasible co-assembly approach to achieve the solid-state stacking transformation of supramolecular organization and opens up new opportunities to further explore the relationship between molecular arrangement and properties of supramolecular assemblies by crystal engineering.

关键词： Amino Acids Co-Assembly Stacking Modes Supramolecular Chemistry

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Measurement of the masses and widths of the Σc(2455)+ and Σc(2520)+ baryons

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Physical Review D 2021年第5期104卷 052003-052003页

作者： J. Yelton I. Adachi J. K. Ahn H. Aihara S. Al Said D. M. Asner H. Atmacan V. Aulchenko T. Aushev R. Ayad V. Babu S. Bahinipati P. Behera K. Belous J. Bennett M. Bessner V. Bhardwaj B. Bhuyan T. Bilka J. Biswal A. Bozek M. Bračko P. Branchini T. E. Browder A. Budano M. Campajola D. Červenkov M.-C. Chang P. Chang V. Chekelian A. Chen B. G. Cheon K. Chilikin H. E. Cho K. Cho S.-J. Cho S.-K. Choi Y. Choi S. Choudhury D. Cinabro S. Cunliffe S. Das N. Dash G. De Nardo G. De Pietro R. Dhamija F. Di Capua J. Dingfelder Z. Doležal T. V. Dong D. Epifanov T. Ferber D. Ferlewicz B. G. Fulsom R. Garg V. Gaur N. Gabyshev A. Garmash A. Giri P. Goldenzweig E. Graziani T. Gu K. Gudkova C. Hadjivasiliou T. Hara O. Hartbrich K. Hayasaka H. Hayashii W.-S. Hou C.-L. Hsu K. Inami A. Ishikawa R. Itoh M. Iwasaki Y. Iwasaki W. W. Jacobs S. Jia Y. Jin K. K. Joo A. B. Kaliyar K. H. Kang Y. Kato C. Kiesling C. H. Kim D. Y. Kim K.-H. Kim S. H. Kim Y.-K. Kim K. Kinoshita P. Kodyš T. Konno A. Korobov S. Korpar E. Kovalenko P. Križan R. Kroeger P. Krokovny T. Kuhr R. Kulasiri K. Kumara Y.-J. Kwon J. S. Lange M. Laurenza S. C. Lee J. Li L. K. Li Y. B. Li L. Li Gioi J. Libby K. Lieret D. Liventsev C. MacQueen M. Masuda T. Matsuda D. Matvienko J. T. McNeil M. Merola K. Miyabayashi R. Mizuk G. B. Mohanty T. J. Moon R. Mussa M. Nakao Z. Natkaniec A. Natochii L. Nayak M. Nayak M. Niiyama N. K. Nisar S. Nishida S. Ogawa H. Ono Y. Onuki P. Oskin P. Pakhlov G. Pakhlova S. Pardi H. Park S.-H. Park S. Paul T. K. Pedlar R. Pestotnik L. E. Piilonen T. Podobnik E. Prencipe M. T. Prim A. Rostomyan N. Rout G. Russo D. Sahoo Y. Sakai S. Sandilya A. Sangal L. Santelj T. Sanuki V. Savinov G. Schnell J. Schueler C. Schwanda Y. Seino K. Senyo M. E. Sevior M. Shapkin C. Sharma C. P. Shen J.-G. Shiu A. Sokolov E. Solovieva M. Starič Z. S. Stottler M. Sumihama K. Sumisawa T. Sumiyoshi M. Takizawa U. Tamponi K. Tanida Y. Tao F. Tenchini K. Trabelsi M. Uchida T. Uglov Y. Unno S. Uno P. Urquijo Y. Usov S. E. Vahsen R. Van Tonder G. Varner A. Vinokurova E. Waheed C. H. Wa University of Florida Gainesville Florida 32611 High Energy Accelerator Research Organization (KEK) Tsukuba 305-0801 SOKENDAI (The Graduate University for Advanced Studies) Hayama 240-0193 Korea University Seoul 02841 Department of Physics University of Tokyo Tokyo 113-0033 Department of Physics Faculty of Science University of Tabuk Tabuk 71451 Department of Physics Faculty of Science King Abdulaziz University Jeddah 21589 Brookhaven National Laboratory Upton New York 11973 University of Cincinnati Cincinnati Ohio 45221 Budker Institute of Nuclear Physics SB RAS Novosibirsk 630090 Novosibirsk State University Novosibirsk 630090 National Research University Higher School of Economics Moscow 101000 Deutsches Electronen-Synchrotron 22607 Hamburg Indian Institute of Technology Bhubaneswar Satya Nagar 751007 Indian Institute of Technology Madras Chennai 600036 Institute for High Energy Physics Protvino 142281 University of Mississippi University Mississippi 38677 University of Hawaii Honolulu Hawaii 96822 Indian Institute of Science Education and Research Mohali SAS Nagar 140306 Indian Institute of Technology Guwahati Assam 781039 Faculty of Mathematics and Physics Charles University 121 16 Prague J. Stefan Institute 1000 Ljubljana H. Niewodniczanski Institute of Nuclear Physics Krakow 31-342 Faculty of Chemistry and Chemical Engineering University of Maribor 2000 Maribor INFN—Sezione di Roma Tre I-00146 Roma INFN—Sezione di Napoli I-80126 Napoli Università di Napoli Federico II I-80126 Napoli Department of Physics Fu Jen Catholic University Taipei 24205 Department of Physics National Taiwan University Taipei 10617 Max-Planck-Institut für Physik 80805 München National Central University Chung-li 32054 Department of Physics and Institute of Natural Sciences Hanyang University Seoul 04763 P.N. Lebedev Physical Institute of the Russian Academy of Sciences Moscow 119991 Korea Institute of Science and Technology Information Daejeon 34141 Yonsei University Seoul 03722 Gyeo

Using 980 fb−1 of data collected with the Belle detector operating at the KEKB asymmetric-energy e+e− collider, we report the measurements of the masses, and the first measurements of the instrinsic widths, of the Σc(2455)+ and Σc(2520)+ charmed baryons. We find M(Σc(2455)+)−M(Λc+)=166.17±0.05−0.07+0.16 MeV/c2, Γ(Σc(2455)+)=2.3±0.3±0.3 MeV/c2, M(Σc(2520)+)−M(Λc+)=230.9±0.5−0.1+0.5 MeV/c2, and Γ(Σc(2520)+)=17.2−2.1−0.7+2.3+3.1 MeV/c2, where the uncertainties are statistical and systematic, respectively. These measurements can be used to test models of the underlying quark structure of the Σc states.

关键词： Particle decays

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A Novel Gcv-Based Criterion for Parameter Selection In Image Deconvolution

A Novel Gcv-Based Criterion for Parameter Selection In Image...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Feng Xue Thierry Blu Jiaqi Liu Xia Ai National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing 100076 China Dept. of Electronic Engineering The Chinese University of Hong Kong Shatin N.T. Hong Kong

ISBN: (纸本)9781538646595

A proper selection of regularization parameter is essential for regularization-based image deconvolution. The main contribution of this paper is to propose a new form of generalized cross validation (GCV) as a criterion for this optimal selection. Incorporating a nil-trace non-linear estimate, we develop this new GCV based on Stein's unbiased risk estimate (SURE)-an unbiased estimate of mean squared error (MSE). The key advantage of this GCV over SURE is that it does not require the knowledge of noise variance. We exemplify this criterion with both Tikhonov regularization and l_1-based sparse deconvolution. In particular, we develop a recursive evaluation of GCV for the l_1-estimate based on iterative soft-thresholding (IST) algorithm. numerical experiments demonstrate the nearly optimal parameter selection and negligible loss of its resultant deconvolution quality.

关键词： Image deconvolution regularization parameter generalized cross validation (GCV) Stein's unbiased risk estimate (SURE) deconvolution Mean square error optimal selection optimal parameter Imagery (Psychotherapy) Image images

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The Probability Density Function for Network Coding with Three Input Flows

The Probability Density Function for Network Coding with Thr...

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International Conference on Computers, Communications, and Systems (ICCCS)

作者： Xiangrong Liu Yaping Liang Qing Chang Xianxu Li National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China School of Electronic Information Engineering Beihang University Beijing China State grid information & communication branch Beijing China

ISBN: (纸本)9781538663516

Now many researches have been studying the optimization between throughput/energy consuming and delay with a couple of independent input flows in network coding (NC). However, the implementation of network coding (NC) requires a thorough investigation of its impact on relevant queueing systems which little work focuses on. In this paper, the scenario with three independent Poisson input flows based on our previous work about the pdf with two independent Poisson input flows., and one output flow is considered. The asynchronous NC-based strategy is that a new arrival evicts a head packet holding in its queue when waiting for another packet from the other flow to encode. The three flows are divided into two parts for getting the probability density function (pdf) of the output flow. The pdf for the output flow which contains both coded and uncoded packets is derived. Besides, the statistic characteristics of this strategy are analyzed. These results are verified by numerical simulations.

关键词： Probability density function Network coding Encoding Relays Merging Simulation numerical simulation

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