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arXiv 2021年

作者： Sekimoto, Yutaro Ade, P.A.R. Adler, A. Allys, E. Arnold, K. Auguste, D. Aumont, J. Aurlien, R. Austermann, J. Baccigalupi, C. Banday, A.J. Banerji, R. Barreiro, R.B. Basak, S. Beall, J. Beck, D. Beckman, S. Bermejo, J. de Bernardis, P. Bersanelli, M. Bonis, J. Borrill, J. Boulanger, F. Bounissou, S. Brilenkov, M. Brown, M. Bucher, M. Calabrese, E. Campeti, P. Carones, A. Casas, F.J. Challinor, A. Chan, V. Cheung, K. Chinone, Y. Cliche, J.F. Colombo, L. Columbro, F. Cubas, J. Cukierman, A. Curtis, D. D’Alessandro, G. Dachlythra, N. de Petris, M. Dickinson, C. Diego-Palazuelos, P. Dobbs, M. Dotani, T. Duband, L. Duff, S. Duval, J.M. Ebisawa, K. Elleflot, T. Eriksen, H.K. Errard, J. Essinger-Hileman, T. Finelli, F. Flauger, R. Franceschet, C. Fuskeland, U. Galloway, M. Ganga, K. Gao, J.R. Genova-Santos, R. Gerbino, M. Gervasi, M. Ghigna, T. Gjerløw, E. Gradziel, M.L. Grain, J. Grupp, F. Gruppuso, A. Gudmundsson, J.E. de Haan, T. Halverson, N.W. Hargrave, P. Hasebe, T. Hasegawa, M. Hattori, M. Hazumi, M. Henrot-Versillé, S. Herman, D. Herranz, D. Hill, C.A. Hilton, G. Hirota, Y. Hivon, E. Hlozek, R.A. Hoshino, Y. de la Hoz, E. Hubmayr, J. Ichiki, K. Iida, T. Imada, H. Ishimura, K. Ishino, H. Jaehnig, G. Kaga, T. Kashima, S. Katayama, N. Kato, A. Kawasaki, T. Keskitalo, R. Kisner, T. Kobayashi, Y. Kogiso, N. Kogut, A. Kohri, K. Komatsu, E. Komatsu, K. Konishi, K. Krachmalnicoff, N. Kreykenbohm, I. Kuo, C.L. Kushino, A. Lamagna, L. Lanen, J.V. Lattanzi, M. Lee, A.T. Leloup, C. Levrier, F. Linder, E. Louis, T. Luzzi, G. Maciaszek, T. Maffei, B. Maino, D. Maki, M. Mandelli, S. Martinez-Gonzalez, E. Masi, S. Matsumura, T. Mennella, A. Migliaccio, M. Minami, Y. Mitsuda, K. Montgomery, J. Montier, L. Morgante, G. Mot, B. Murata, Y. Murphy, J.A. Nagai, M. Nagano, Y. Nagasaki, T. Nagata, R. Nakamura, S. Namikawa, T. Natoli, P. Nerval, S. Nishibori, T. Nishino, H. O’Sullivan, C. Ogawa, H. Ogawa, H. Oguri, S. Ohsaki, H. SagamiharaKanagawa252-5210 Japan The University of Tokyo Department of Astronomy Tokyo113-0033 Japan TsukubaIbaraki305-0801 Japan Cardiff University School of Physics and Astronomy CardiffCF10 3XQ United Kingdom Stockholm University Sweden Laboratoire de Physique de l’École Normale Supérieure ENS Université PSL CNRS Sorbonne Université Université de Paris Paris75005 France University of California San Diego Department of Physics San DiegoCA92093-0424 United States Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay91405 France IRAP Université de Toulouse CNRS CNES UPS Toulouse France University of Oslo Institute of Theoretical Astrophysics OsloNO-0315 Norway BoulderCO80305 United States Via Bonomea 265 Trieste34136 Italy Avenida los Castros SN Santander39005 Spain School of Physics Indian Institute of Science Education and Research Thiruvananthapuram Maruthamala PO Vithura ThiruvananthapuramKerala695551 India Stanford University Department of Physics CA94305-4060 United States University of California Berkeley Department of Physics BerkeleyCA94720 United States Plaza Cardenal Cisneros 3 Madrid28040 Spain Dipartimento di Fisica Università La Sapienza INFN Roma P. le A. Moro 2 Roma Italy Dipartimento di Fisica Università degli Studi di Milano INAF-IASF Milano Sezione INFN Milano Italy Computational Cosmology Center BerkeleyCA94720 United States University of California Berkeley Space Science Laboratory BerkeleyCA94720 United States CNRS UMR 8617 Université Paris-Sud 11 Bâtiment 121 Orsay91405 France University of Manchester ManchesterM13 9PL United Kingdom University Paris Diderot CNRS/IN2P3 CEA/Irfu Obs de Paris Sorbonne Paris Cité France Dipartimento di Fisica Università di Roma"Tor Vergata" Sezione INFN Roma2 Italy DAMTP Centre for Mathematical Sciences Wilberforce Road CambridgeCB3 0WA United Kingdom Institute of Astronomy Madingley Road CambridgeCB3 0HA United Kingdom Kavli Instit

LiteBIRD has been selected as JAXA’s strategic large mission in the 2020s, to observe the cosmic microwave background (CMB) B-mode polarization over the full sky at large angular scales. The challenges of LiteBIRD are the wide field-of-view (FoV) and broadband capabilities of millimeter-wave polarization measurements, which are derived from the system requirements. The possible paths of stray light increase with a wider FoV and the far sidelobe knowledge of −56 dB is a challenging optical requirement. A crossed-Dragone configuration was chosen for the low frequency telescope (LFT: 34–161 GHz), one of LiteBIRD’s onboard telescopes. It has a wide field-of-view (18◦ × 9◦) with an aperture of 400 mm in diameter, corresponding to an angular resolution of about 30 arcminutes around 100 GHz. The focal ratio f/3.0 and the crossing angle of the optical axes of 90◦ are chosen after an extensive study of the stray light. The primary and secondary reflectors have rectangular shapes with serrations to reduce the diffraction pattern from the edges of the mirrors. The reflectors and structure are made of aluminum to proportionally contract from warm down to the operating temperature at 5 K. A 1/4 scaled model of the LFT has been developed to validate the wide field-of-view design and to demonstrate the reduced far sidelobes. A polarization modulation unit (PMU), realized with a half-wave plate (HWP) is placed in front of the aperture stop, the entrance pupil of this system. A large focal plane with approximately 1000 AlMn TES detectors and frequency multiplexing SQUID amplifiers is cooled to 100 mK. The lens and sinuous antennas have broadband capability. Performance specifications of the LFT and an outline of the proposed verification plan are presented. © 2021, CC BY.

关键词： Millimeter waves

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A pragmatic approach to estimating average treatment effects from EHR data: The effect of prone positioning on mechanically ventilated COVID-19 patients

arXiv

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arXiv 2021年

作者： Izdebski, Adam Thoral, Patrick J. Lalisang, Robbert C.A. McHugh, Dean M. Gommers, Diederik Cremer, Olaf L. Bosman, Rob J. Rigter, Sander Wils, Evert-Jan Frenzel, Tim Dongelmans, Dave A. de Jong, Remko Peters, Marco A.A. Kamps, Marlijn J.A. Ramnarain, Dharmanand Nowitzky, Ralph Nooteboom, Fleur G.C.A. de Ruijter, Wouter Urlings-Strop, Louise C. Smit, Ellen G.M. Mehagnoul-Schipper, D. Jannet Dormans, Tom de Jager, Cornelis P.C. Hendriks, Stefaan H.A. Achterberg, Sefanja Oostdijk, Evelien Reidinga, Auke C. Festen-Spanjer, Barbara Brunnekreef, Gert B. Cornet, Alexander D. van den Tempel, Walter Boelens, Age D. Koetsier, Peter Lens, Judith Faber, Harald J. Karakus, A. Entjes, Robert de Jong, Paul Rettig, Thijs C.D. Arbous, Sesmu Fleuren, Lucas M. Dam, Tariq A. Tonutti, Michele de Bruin, Daan P. Elbers, Paul W.G. Cinà, Giovanni Pacmed Amsterdam Netherlands Department of Intensive Care Medicine Laboratory for Critical Care Computational Intelligence Amsterdam Medical Data Science Amsterdam UMC Vrije Universiteit Amsterdam Netherlands Institute of Logic Language and Computation University of Amsterdam Netherlands Department of Intensive Care Erasmus Medical Center Rotterdam Netherlands Intensive Care UMC Utrecht Utrecht Netherlands ICU OLVG Amsterdam Netherlands Department of Anesthesiology and Intensive Care St. Antonius Hospital Nieuwegein Netherlands Department of Intensive Care Franciscus Gasthuis & Vlietland Rotterdam Netherlands Department of Intensive Care Medicine Radboud University Medical Center Nijmegen Netherlands Department of Intensive Care Medicine Amsterdam UMC Amsterdam Netherlands Intensive Care Bovenij Ziekenhuis Amsterdam Netherlands Intensive Care Canisius Wilhelmina Ziekenhuis Nijmegen Netherlands Intensive Care Catharina Ziekenhuis Eindhoven Eindhoven Netherlands Department of Intensive Care ETZ Tilburg Tilburg Netherlands Intensive Care HagaZiekenhuis Den Haag Netherlands Intensive Care Laurentius Ziekenhuis Roermond Netherlands Department of Intensive Care Medicine Northwest Clinics Alkmaar Netherlands Intensive Care Reinier de Graaf Gasthuis Delft Netherlands Intensive Care Spaarne Gasthuis Haarlem en Hoofddorp Netherlands Intensive Care VieCuri Medisch Centrum Venlo Netherlands Intensive care Zuyderland MC Heerlen Netherlands Department of Intensive Care Jeroen Bosch Ziekenhuis Den Bosch Netherlands Intensive Care Albert Schweitzerziekenhuis Dordrecht Netherlands ICU Haaglanden Medisch Centrum Den Haag Netherlands ICU Maasstad Ziekenhuis Rotterdam Rotterdam Netherlands ICU SEH BWC Martiniziekenhuis Groningen Netherlands Intensive Care Ziekenhuis Gelderse Vallei Ede Netherlands Department of Intensive Care Ziekenhuisgroep Twente Almelo Netherlands FRCP Department of Intensive Care Medisch Spectrum Twente Enschede Netherla

Despite the recent progress in the field of causal inference, to date there is no agreed upon methodology to glean treatment effect estimation from observational data. The consequence on clinical practice is that, when lacking results from a randomized trial, medical personnel is left without guidance on what seems to be effective in a real-world scenario. This article proposes a pragmatic methodology to obtain preliminary but robust estimation of treatment effect from observational studies, to provide front-line clinicians with a degree of confidence in their treatment strategy. Our study design is applied to an open problem, the estimation of treatment effect of the proning maneuver on COVID-19 Intensive Care patients. © 2021, CC BY.

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Towards the creation of the cardiovascular magnetic resonance quality assessment ontology (CMR-QA) 9

Towards the creation of the cardiovascular magnetic resonanc...

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9th International Conference Semantic Web Applications and Tools for Life sciences, SWAT4LS 2016

作者： Jiménez-Ruiz, Ernesto Carapella, Valentina Lukaschuk, Elena Aung, Nay Fung, Kenneth Paiva, Jose Sanghvi, Mihir Neubauer, Stefan Petersen, Steffen Horrocks, Ian Piechnik, Stefan Logic and Intelligent Data Group Department of Informatics University of Oslo Norway Radcliffe Department of Medicine University of Oxford United Kingdom William Harvey Research Institute NIHR Cardiovascular Biomedical Research Unit at Barts Queen Mary University of London United Kingdom Information Systems Group Department of Computer Science University of Oxford United Kingdom

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Societal impacts of big data: Challenges and opportunities in Europe

arXiv

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arXiv 2017年

作者： Cuquet, Martí Vega-Gorgojo, Guillermo Lammerant, Hans Finn, Rachel ul Hassan, Umair Semantic Technology Institute University of Innsbruck Technikerstraße 21a Innsbruck6020 Austria Logic and Intelligent Data Department of Informatics University of Oslo Ole-Johan Dahls Building Gaustadalléen 23 B OsloN-0373 Law Science Technology and Society Research Group Vrije Universiteit Brussel Pleinlaan 2 Brussels1050 Belgium Trilateral Research Ltd. Crown House 72 Hammersmith Road LondonW14 8TH United Kingdom The Insight Centre for Data Analytics National University of Ireland Galway DERI Building IDA Business Park Lower Dangan Galway Ireland

This paper presents the risks and opportunities of big data and the potential social benefits it can bring. The research is based on an analysis of the societal impacts observed in a set of six case studies across different European sectors. These impacts are divided into economic, social and ethical, legal and political impacts, and affect areas such as improved efficiency, innovation and decision making, changing business models, dependency on public funding, participation, equality, discrimination and trust, data protection and intellectual property rights, private and public tensions and losing control to actors abroad. A special focus is given to the risks and opportunities coming from the legal framework and how to counter the negative impacts of big data. Recommendations are presented for four specific legal frameworks: copyright and database protection, protection of trade secrets, privacy and data protection and anti-discrimination. In addition, the potential social benefits of big data are exemplified in six domains: improved decision making and event detection;data-driven innovations and new business models;direct social, environmental and other citizen benefits;citizen participation, transparency and public trust;privacy-aware data practices;and big data for identifying discrimination. Several best practices are suggested to capture these benefits. Copyright © 2017, The Authors. All rights reserved.

关键词： Big data

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Applying fuzzy functions and sequential coordination to optimization of machinery arrangement and pipe routing

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NAVAL ENGINEERS JOURNAL 1998年第6期110卷 43-54页

作者： Wu, BC Young, GS Schmidt, W Choppella, K Dr. Bi-Chu Wu:received a PhD in Mechanical Engineering from the University of Maryland College Park in 1991. She has worked on projects involving naval architecture design optimization solid mechanics and database development. Presently a senwr engineer with Angle Incorporated Dr Wu's research interests are in design optimization and fuzzy logic applications. Dr. Gin-Shu Young: a senior engineer with Angle Incorporated holds a PhD in Mechanical Engineering from the University of Maryland College Park. As a guest researcher with National Institute of Standards and Technologies from 1990 to 1993 he worked on vision-based navigation for autonomous vehicles. His experience also includes applications of optimization fuzzy logic neural network and genetic algorithm methods to engineering system design Mr. William Schmidt:co-founded Angle Incorporated in 1990 and has served as Vice PresidentlChiefScientist during this tame. He holds a B.Sc. in Applied Science from the Naval Acadt?my and an M.Sc. in Physics from the Naval Post Graduate School. He has cner 20 years experience in technical leadership material and personnel management. He has led the application of computer aided design (CAD) and Product Model Information Exchange to the shipbuilding industry. His experience also includes leading the amlication of model based operational analysis to support the Live Fire Test Program for DDG 51 Class Destroyers. Mr. Krishna M. Choppella:is a Sofware Engineer at Eidea Laboratories Incotporated where he works on componentbased distributed enterpvise frameworks. He has been involved in creating data analysis tools for the US Nay by integrating CAD modeis databases and graphical front ends. His work in the Masters degree program in Mechanical Engineering at the University of Texas at Austin was in di0ddase.r spectroscopy of combustion products in porous-matri burners. He received his Bachelors degree in Electrical Engineering in India. He was a Research Associate at the Centre for Laser Technology and Project Engi

Ship design is often multidisciplinary involving several design elements with various types of objectives and constraints (O/C) some easily described as mathematical formulas, others better modeled as descriptive assertions. This paper describes a method based on fuzzy functions and an integrated performance index to model O/C using descriptive assertions to be used with mathematical formulas in optimization. Another issue addressed in this paper concerns the coordination of design elements when sequentially coupled, that is, when one leads the other and the performance of the follower depends greatly on the design of the leader. Based on neuro-fuzzy techniques, the method described here coordinates and optimizes sequentially coupled elements. The two methods are applied to machinery arrangement (MA) and pipe routing (PR). Preliminary models for optimization of MA and PR are described considering convenience, producibility: engine room size, interference and location as factors in the O/C set. Some test results from MA/PR applications are presented and discussed. The methods are generic and can be extended to other elements in ship design. They are mutually independent and may be used separately Two advantages of their use are an improvement in overall performance and a reduction in the need for redesign of elements.

关键词： Optimization

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Target detection in radar: Current status and future possibilities

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JOURNAL OF NAVIGATION 1997年第2期50卷 303-313页

作者： Li, VYF Miller, KM [a1 ](Hong Kong University of Science and Technology)[a2 ](Institute of Marine Studies University of Plymouth)Most of the radar systems used in operating marine vessel traffic management services experience problems such as track loss and track swap which may cause confusion to the traffic regulators and lead to potential hazards in the harbour operation. The reason is mainly due to the limited adaptive capabilities of the algorithms used in the detection process. The decision on whether a target is present is usually based on the amplitude information of the returning echoes. Such method has a low efficiency in discriminating between the target and clutter especially when the signal-to-noise ratio is low. With modern signal processing techniques more information can be extracted from the radar return signals and the tracking parameters of the previous scan. The objectives of this paper are to review the methods which are currently adopted in radar target identification identify techniques for extracting additional information and consider means of data analysis for deciding the presence of a target. Instead of employing traditional two-state logic it is suggested that the radar signal should be allocated in terms of threshold levels into fuzzy sets with its membership functions being related to the information extracted and the environment. Additional signal processing techniques are also suggested to explore pattern recognition aspects and discriminate features which are associated with a return signal from those of clutter.

Most of the radar systems used in operating marine vessel traffic management services experience problems, such as track loss and track swap, which may cause confusion to the traffic regulators and lead to potential hazards in the harbour operation. The reason is mainly due to the limited adaptive capabilities of the algorithms used in the detection process. The decision on whether a target is present is usually based on the amplitude information of the returning echoes. Such method has a low efficiency in discriminating between the target and clutter, especially when the signal-to-noise ratio is low. With modern signal processing techniques more information can be extracted from the radar return signals and the tracking parameters of the previous scan. The objectives of this paper are to review the methods which are currently adopted in radar target identification, identify techniques for extracting additional information and consider means of data analysis for deciding the presence of a target. Instead of employing traditional two-state logic, it is suggested that the radar signal should be allocated in terms of threshold levels into fuzzy sets with its membership functions being related to the information extracted and the environment. Additional signal processing techniques are also suggested to explore pattern recognition aspects and discriminate features which are associated with a return signal from those of clutter.

关键词： radar signal processing target detection

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