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arXiv 2021年

作者： Stangalini, Marco Jess, D.B. Verth, G. Fedun, V. Fleck, B. Jafarzadeh, S. Keys, P.H. Murabito, M. Calchetti, D. Aldhafeeri, A.A. Berrilli, F. Del Moro, D. Jefferies, S.M. Terradas, J. Soler, R. ASI Italian Space Agency Via del Politecnico snc Rome00133 Italy Astrophysics Research Centre School of Mathematics and Physics Queen’s University Belfast BelfastNorthern IrelandBT7 1NN United Kingdom Department of Physics and Astronomy California State University Northridge NorthridgeCA91330 United States Plasma Dynamics Group School of Mathematics and Statistics The University of Sheffield Hicks Building Hounsfield Road SheffieldS3 7RH United Kingdom Plasma Dynamics Group Department of Automatic Control and Systems Engineering The University of Sheffield SheffieldS1 3JD United Kingdom ESA Science and Operations Department NASA/GSFC Code 671 GreenbeltMD20771 United States Rosseland Centre for Solar Physics University of Oslo P.O. Box 1029 Blindern OsloNO-0315 Norway Institute of Theoretical Astrophysics University of Oslo P.O. Box 1029 Blindern OsloNO-0315 Norway INAF-OAR National Institute for Astrophysics Monte Porzio Catone RM00041 Italy Department of Physics University of Rome Tor Vergata Via della Ricerca Scientifica 1 Rome00133 Italy Mathematics and Statistic Department Faculty of Science King Faisal University Al-Hassa P.O. Box 400 Hofuf31982 Saudi Arabia Department of Physics and Astronomy Georgia State University GA30303 United States Institute for Astronomy University of Hawaii HI96768-8288 United States Departament de Física Universitat de les Illes Balears Palma de MallorcaE-07122 Spain Universitat de les Illes Balears Palma de MallorcaE-07122 Spain

The umbral regions of sunspots and pores in the solar photosphere are generally dominated by 3 mHz oscillations, which are due to p-modes penetrating the magnetic region. In these locations, wave power is also significantly reduced with respect to the quiet Sun. However, here we study a pore where the power of the oscillations in the umbra is not only comparable, or even larger than that of the quiet Sun, but the main dominant frequency is not 3 mHz as expected, but instead 5 mHz. By combining Doppler velocities and spectropolarimetry and analysing the relationship between magnetic field strength and frequency, the resultant B − ω diagram reveals distinct ridges which are remarkably clear signatures of resonant MHD oscillations confined within the pore umbra. In addition to velocity oscillations, we demonstrate that these modes are also accompanied by magnetic oscillations, as predicted from MHD theory. The novel technique of B − ω analysis, proposed in this Letter, opens an exciting new avenue for identifying MHD wave modes in the umbral regions of both pores and sunspots. Copyright © 2021, The Authors. All rights reserved.

关键词： Wave power

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A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge

arXiv

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arXiv 2024年

作者： de la Rosa, Ezequiel Reyes, Mauricio Liew, Sook-Lei Hutton, Alexandre Wiest, Roland Kaesmacher, Johannes Hanning, Uta Hakim, Arsany Zubal, Richard Valenzuela, Waldo Robben, David Sima, Diana M. Anania, Vincenzo Brys, Arne Meakin, James A. Mickan, Anne Broocks, Gabriel Heitkamp, Christian Gao, Shengbo Liang, Kongming Zhang, Ziji Siddiquee, Md Mahfuzur Rahman Myronenko, Andriy Ashtari, Pooya Van Huffel, Sabine Jeong, Hyun-Su Yoon, Chi-Ho Kim, Chulhong Huo, Jiayu Ourselin, Sebastien Sparks, Rachel Clèrigues, Albert Oliver, Arnau Lladó, Xavier Chalcroft, Liam Pappas, Ioannis Bertels, Jeroen Heylen, Ewout Moreau, Juliette Hatami, Nima Frindel, Carole Qayyum, Abdul Mazher, Moona Puig, Domenec Lin, Shao-Chieh Juan, Chun-Jung Hu, Tianxi Boone, Lyndon Goubran, Maged Liu, Yi-Jui Wegener, Susanne Kofler, Florian Ezhov, Ivan Shit, Suprosanna Hernandez Petzsche, Moritz R. Menze, Bjoern Kirschke, Jan S. Wiestler, Benedikt Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Informatics Technical University Munich Germany Icometrix Leuven Belgium ARTORG Center for Biomedical Research University of Bern Bern Switzerland Department of Radiation Oncology University Hospital Bern University of Bern Switzerland University of Bern Bern Switzerland Chan Division of Occupational Science and Occupational Therapy University of Southern California Los AngelesCA United States Stevens Neuroimaging and Informatics Institute Department of Neurology Keck School of Medicine University of Southern California United States University Institute of Diagnostic and Interventional Neuroradiology Inselspital Bern Switzerland University Institute of Diagnostic and Interventional Neuroradiology University Hospital Bern Inselspital University of Bern Bern Switzerland Department of Diagnostic and Interventional neuroradiology University Medical Center Hamburg-Eppendorf Hamburg Germany Department of Medical Imaging Radboud University Medical Center Institute for Health Sciences Nijmegen Netherlands Deepwise AI Lab Beijing China Beijing University of Posts and Telecommunications Bejing China School of Computing and Augmented Intelligence Arizona State University TempeAZ United States NVIDIA Santa ClaraCA United States STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Pohang Korea Republic of School of Biomedical Engineering & Imaging Sciences King’s College London United Kingdom Institute of Computer Vision and Robotics University of Girona Spain Wellcome Centre for Human Neuroimaging University College London London United Kingdom Laboratory of Neuro Imaging Stevens Institute for Neuroimaging and Informatics Keck School of Medicine University of Southern California Los Angeles United States KU Leuven Leuven Belgium CREATIS Université Lyon1 CNRS UMR5220 INSERM U1206 INSA-Lyon Villeurbanne696

Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable AI algorithms with clinical value. We address this gap by presenting a novel ensemble algorithm derived from the 2022 Ischemic Stroke Lesion Segmentation (ISLES) challenge. ISLES’22 provided 400 patient scans with ischemic stroke from various medical centers, facilitating the development of a wide range of cutting-edge segmentation algorithms by the research community. By assessing them against a hidden test set, we identified strengths, weaknesses, and potential biases. Through collaboration with leading teams, we combined top-performing algorithms into an ensemble model that overcomes the limitations of individual solutions. Our ensemble model combines the individual algorithms’ strengths and achieved superior ischemic lesion detection and segmentation accuracy (median Dice score: 0.82, median lesion-wise F1 score: 0.86) on our internal test set compared to individual algorithms. This accuracy generalized well across diverse image and disease variables. Furthermore, the model excelled in extracting clinical biomarkers like lesion types and affected vascular territories. Notably, in a Turing-like test, neuroradiologists consistently preferred the algorithm’s segmentations over manual expert efforts, highlighting increased comprehensiveness and precision. Validation using a real-world external dataset (N=1686) confirmed the model’s generalizability (median Dice score: 0.82, median lesion-wise F1 score: 0.86). The algorithm’s outputs also demonstrated strong correlations with clinical scores (admission NIHSS and 90-day mRS) on par with or exceeding expert-derived results, underlining its clinical relevance. This study offers two key findings. First, we present an ensemble algorithm that detects and segments ischemic stroke lesions on DWI across diverse scenarios on par with expert (neuro)rad

关键词： Diagnosis

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Sausage, kink, and fluting MHD wave modes identified in solar magnetic pores by Solar Orbiter/PHI

arXiv

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arXiv 2024年

作者： Jafarzadeh, S. Schiavo, L.A.C.A. Fedun, V. Solanki, S.K. Stangalini, M. Calchetti, D. Verth, G. Jess, D.B. Grant, S.D.T. Ballai, I. Gafeira, R. Keys, P.H. Fleck, B. Morton, R.J. Browning, P.K. Silva, S.S.A. Appourchaux, T. Gandorfer, A. Gizon, L. Hirzberger, J. Kahil, F. Suárez, D. Orozco Schou, J. Strecker, H. del Toro Iniesta, J.C. Valori, G. Volkmer, R. Woch, J. Max Planck Institute for Solar System Research Justus-von-Liebig-Weg 3 Göttingen37077 Germany School of Physics & Astronomy The University of Manchester Oxford Road ManchesterM13 9PL United Kingdom Department of Mathematics Physics and Electrical Engineering Northumbria University Newcastle upon TyneNE1 8ST United Kingdom Plasma Dynamics Group Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom ASI Italian Space Agency Via del Politecnico snc RomeI-00133 Italy Plasma Dynamics Group School of Mathematics and Statistics The University of Sheffield Hicks Building Hounsfield Road SheffieldS3 7RH United Kingdom Astrophysics Research Centre School of Mathematics and Physics Queen’s University Belfast BelfastBT7 1NN United Kingdom Department of Physics and Astronomy California State University Northridge NorthridgeCA91330 United States Instituto de Astrofísica e Ciências do Espaço Department of Physics University of Coimbra Coimbra3040-004 Portugal ESA Science and Operations Department c/o NASA Goddard Space Flight Center GreenbeltMD20771 United States Univ. Paris-Sud Institut d’Astrophysique Spatiale UMR 8617 CNRS Bâtiment 121 Orsay91405 Cedex France Apartado de Correos 3004 GranadaE-18080 Spain Leibniz-Institut für Sonnenphysik Schöneckstr. 6 FreiburgD-79104 Germany Institut für Astrophysik und Geophysik Georg-August-Universität Göttingen Friedrich-Hund-Platz 1 Göttingen37077 Germany

Solar pores are intense concentrations of magnetic flux that emerge through the Sun’s photosphere. When compared to sunspots, they are much smaller in diameter and hence can be impacted and buffeted by neighbouring granular activity to generate significant magnetohydrodynamic (MHD) wave energy flux within their confines. However, observations of solar pores from ground-based telescope facilities may struggle to capture subtle motions synonymous with higher-order MHD wave signatures due to seeing effects produced in the Earth’s atmosphere. Hence, we have exploited timely seeing-free and high-quality observations of four small magnetic pores from the High Resolution Telescope (HRT) of the Polarimetric and Helioseismic Imager (PHI) on board the Solar Orbiter spacecraft, during its first close perihelion passage in March 2022 (at a distance of 0.5 au from the Sun). Through acquisition of data under stable observing conditions, we have been able to measure the area fluctuations and horizontal displacements of the solar pores. Cross correlations between perturbations in intensity, area, line-of-sight velocity, and magnetic fields, coupled with the first-time application of novel Proper Orthogonal Decomposition (POD) techniques on the boundary oscillations, provide a comprehensive diagnosis of the embedded MHD waves as sausage and kink modes. Additionally, the previously elusive m = 2 fluting mode is identified in the most magnetically isolated of the four pores. An important consideration lies in how the identified wave modes contribute towards the transfer of energy into the upper solar atmosphere. We find that the four pores examined have approximately 56%, 72%, 52%, and 34% of their total wave energy associated with the identified sausage modes, and around 23%, 17%, 39%, and 49% to their kink modes, respectively, while the first pore also has around an 11% contribution linked to the fluting mode. This study marks the first-time identification of concurrent sausage, kin

关键词： Magnetohydrodynamics

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MARKOV DECISION PROCESSES WITH UNCERTAIN TRANSITION RATES: SENSITIVITY AND MAX HYPHEN MIN control

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Asian Journal of control 2008年第2期6卷

作者： Suresh Kalyanasundaram Edwin K. P. Chong Ness B. Shroff Motorola India Electronics Limited No. 66/1 Plot 5 Bagmane Techpark C. V. Raman Nagar Post Bangalore 560 093 India. Department of Electrical and Computer Engineering Colorado State University Fort Collins CO 80523-1373 USA. Professor Edwin K. P. Chong received the B.E.(Hons.) degree with First Class Honors from the University of Adelaide South Australia in 1987 graduating top of his class and the M.A. and Ph.D. degrees in 1989 and 1991 respectively both from Princeton University where he held an IBM Fellowship. He joined the School of Electrical and Computer Engineering at Purdue University in 1991 where he was named a University Faculty Scholar in 1999 and promoted to Full Professor in 2001. Since August 2001 he has been a Professor of Electrical and Computer Engineering and Professor of Mathematics at Colorado State University. His current interests are in communication networks and optimization methods. He coauthored the best-selling book An Introduction to Optimization 2nd Edition Wiley-Interscience 2001. He received the NSF CAREER Award in 1995 and the ASEE Frederick Emmons Terman Award in 1998. He coauthored a paper that was awarded Best Paper in the journal Computer Networks 2003. Professor Chong is a Fellow of the IEEE. He was founding chairman of the IEEE Control Systems Society Technical Committee on Discrete Event Systems and until recently served as an IEEE Control Systems Society Distinguished Lecturer. He has been on the editorial board of the IEEE Transactions on Automatic Control. He is currently on the editorial board of the journal Computer Networks. He has also served on the organizing committees of several international conferences. He has been on the program committees for the IEEE Conference on Decision and Control the American Control Conference the IEEE International Symposium on Intelligent Control IEEE Symposium on Computers and Communications and the IEEE Global Telecommunications Conference. He has also served in the executive committees for the IEEE Co

Solution techniques for Markov decision problems rely on exact knowledge of the transition rates, which may be difficult or impossible to obtain. In this paper, we consider Markov decision problems with uncertain transition rates represented as compact sets. We first consider the problem of sensitivity analysis where the aim is to quantify the range of uncertainty of the average per-unit-time reward given the range of uncertainty of the transition rates. We then develop solution techniques for the problem of obtaining the max-min optimal policy, which maximizes the worst-case average per-unit-time reward. In each of these problems, we distinguish between systems that can have their transition rates chosen independently and those where the transition rates depend on each other. Our solution techniques are applicable to Markov decision processes with fixed but unknown transition rates and to those with time-varying transition rates.

关键词： Markov decision processes sensitivity max-min control call admission control policy iteration

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Critical science plan for the Daniel K. Inouye Solar Telescope (DKIST)

arXiv

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arXiv 2020年

作者： Rast, Mark P. Bello González, Nazaret Bellot Rubio, Luis Cao, Wenda Cauzzi, Gianna DeLuca, Edward de Pontieu, Bart Fletcher, Lyndsay Gibson, Sarah E. Judge, Philip G. Katsukawa, Yukio Kazachenko, Maria D. Khomenko, Elena Landi, Enrico Martínez Pillet, Valentin Petrie, Gordon J.D. Qiu, Jiong Rachmeler, Laurel A. Rempel, Matthias Schmidt, Wolfgang Scullion, Eamon Sun, Xudong Welsch, Brian T. Andretta, Vincenzo Antolin, Patrick Ayres, Thomas R. Balasubramaniam, K.S. Ballai, Istvan Berger, Thomas E. Bradshaw, Stephen J. Carlsson, Mats Casini, Roberto Centeno, Rebecca Cranmer, Steven DeForest, Craig Deng, Yuanyong Erdélyi, Robertus Fedun, Viktor Fischer, Catherine E. González Manrique, Sergio J. Hahn, Michael Harra, Louise Henriques, Vasco M.J. Hurlburt, Neal E. Jaeggli, Sarah Jafarzadeh, Shahin Jain, Rekha Jefferies, Stuart M. Keys, Peter H. Kowalski, Adam F. Kuckein, Christoph Kuhn, Jeffrey R. Liu, Jiajia Liu, Wei Longcope, Dana James McAteer, R.T. McIntosh, Scott W. McKenzie, David E. Paz Miralles, Mari Morton, Richard J. Muglach, Karin Nelson, Chris J. Panesar, Navdeep K. Parenti, Susanna Parnell, Clare E. Poduval, Bala Reardon, Kevin P. Reep, Jeffrey W. Schad, Thomas A. Schmit, Donald Sharma, Rahul Socas-Navarro, Hector Srivastava, Abhishek K. Sterling, Alphonse C. Suematsu, Yoshinori Tarr, Lucas A. Tiwari, Sanjiv Alexandra, Tritschler Verth, Gary Vourlidas, Angelos Wang, Haimin Wang, Yi-Ming Department of Astrophysical and Planetary Sciences University of Colorado BoulderCO80309 United States Laboratory for Atmospheric and Space Physics University of Colorado BoulderCO80303 United States Kiepenheuer-Institut für Sonnenphysik Freiburg79104 Germany GranadaE-18080 Spain Big Bear Solar Observatory New Jersey Institute of Technology Big Bear CityCA92314 United States National Solar Observatory BoulderCO80303 United States Harvard-Smithsonian Center for Astrophysics CambridgeMA02138 United States Lockheed Martin Solar & Astrophysics Laboratory Palo AltoCA94304 United States Institute of Theoretical Astrophysics Rosseland Centre for Solar Physics University of Oslo OsloN-0315 Norway School of Physics and Astronomy University of Glasgow GlasgowG12 8QQ United Kingdom High Altitude Observatory National Center for Atmospheric Research BoulderCO80307 United States Department of Astronomical Science School of Physical Sciences The Graduate University for Advanced Studies SOKENDAI Tokyo181-8588 Japan National Astronomical Observatory of Japan National Institutes of Natural Science Tokyo181-8588 Japan Instituto de Astrofísica de Canarias La Laguna Tenerife38205 Spain Department of Climate and Space Sciences and Engineering University of Michigan Ann ArborMI48109 United States Department of Physics Montana State University BozemanMT59717 United States NOAA National Centers for Environmental Information BoulderCO80305 United States Department of Mathematics Physics and Electrical Engineering Northumbria University Newcastle upon TyneNE1 8ST United Kingdom Institute for Astronomy University of Hawaii PukalaniHI96768 United States Department of Natural and Applied Sciences University of Wisconsin Green BayWI54311 United States INAF Osservatorio Astronomico di Capodimonte Naples80131 Italy Center for Astrophysics and Space Astronomy University of Colorado BoulderCO80309 United States AFRL Battlespace Environment Division

The Daniel K. Inouye Solar Telescope (DKIST) will revolutionize our ability to measure, understand and model the basic physical processes that control the structure and dynamics of the Sun and its atmosphere. The first-light DKIST images, released publicly on 29 January 2020, only hint at the extraordinary capabilities which will accompany full commissioning of the five facility instruments. With this Critical Science Plan (CSP) we attempt to anticipate some of what those capabilities will enable, providing a snapshot of some of the scientific pursuits that the Daniel K. Inouye Solar Telescope hopes to engage as start-of-operations nears. The work builds on the combined contributions of the DKIST Science Working Group (SWG) and CSP Community members46, who generously shared their experiences, plans, knowledge and dreams. Discussion is primarily focused on those issues to which DKIST will uniquely contribute. Copyright © 2020, The Authors. All rights reserved.

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