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arXiv 2020年

作者： Di Cairano, Loris Gori, Matteo Pettini, Giulio Pettini, Marco Institute of Neuroscience and Medicine INM-9 Institute for Advanced Simulation IAS-5 Forschungszentrum Jülich Jülich52428 Germany Department of Physics Faculty of Mathematics Computer Science and Natural Sciences Aachen University Aachen52062 Germany Physics and Materials Science Research Unit University of Luxembourg LuxembourgL-1511 Luxembourg Dipartimento di Fisica Università di Firenze I.N.F.N. Sezione di Firenze via G. Sansone 1 Sesto FiorentinoI-50019 Italy Aix-Marseille University Marseille France CNRS Centre de Physique Théorique UMR7332 Marseille13288 France

This paper tackles Hamiltonian chaos by means of elementary tools of Riemannian geometry. More precisely, a Hamiltonian flow is identified with a geodesic flow on configuration space-time endowed with a suitable metric due to Eisenhart. Until now, this framework has never been given attention to describe chaotic dynamics. A gap that is filled in the present work. In a Riemannian-geometric context, the stability/instability of the dynamics depends on the curvature properties of the ambient manifold and is investigated by means of the Jacobi–Levi-Civita (JLC) equation for geodesic spread. It is confirmed that the dominant mechanism at the ground of chaotic dynamics is parametric instability due to curvature variations along the geodesics. A comparison is reported of the outcomes of the JLC equation written also for the Jacobi metric on configuration space and for another metric due to Eisenhart on an extended configuration space-time. This has been applied to the Hénon-Heiles model, a two-degrees of freedom system. Then the study has been extended to the 1D classical Heisenberg XY model at a large number of degrees of freedom. Both the advantages and drawbacks of this geometrization of Hamiltonian dynamics are discussed. Finally, a quick hint is put forward concerning the possible extension of the differential-geometric investigation of chaos in generic dynamical systems, including dissipative ones, by resorting to Finsler manifolds. © 2020, CC BY.

关键词： Wave functions

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Performance Analysis of a Cloud Computing System using Queuing Model with Correlated Task Reneging

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Journal of Physics: Conference Series 2021年第1期2091卷

作者： Rakesh Kumar Bhavneet Singh Soodan Godlove Suila Kuaban Piotr Czekalski Sapana Sharma School of Mathematics Shri Mata Vaishno Devi University Katra Jammu and Kashmir 182320 India Department of Mathematics and Statistics Namibia University of Science and Technology Private Bag 13388 Windhoek Namibia 13 Jackson Kaujeua Street Windhoek Namibia Institute of Theoretical and Applied Informatics Polish Academy of Sciences Baltycka 5 44-100 Gliwice Poland Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Department of Mathematics Cluster University of Jammu Jammu and Kashmir

Queuing theory has been extensively used in the modelling and performance analysis of cloud computing systems. The phenomenon of the task (or request) reneging, that is, the dropping of requests from the request queue often occur in cloud computing systems, and it is important to consider it when developing performance evaluations models for cloud computing infrastructures. Majority of studies in the performance evaluation of cloud computing data centres with the use of queuing theory do not consider the fact that the tasks could be removed from queue without being serviced. The removal of tasks from the queue could be due to the user impatience, execution deadline expiration, security reasons, or as an active queue management strategy. The reneging could be correlated in nature, that is, if a request is dropped (or reneged) at any time epoch, and then there is a probability that a request may or may not be dropped at the next time epoch. This kind of dropping (or reneging) of requests is referred to as correlated request reneging. In this paper we have modelled a cloud computing infrastructure with correlated request reneging using queuing theory. An M/M/1/N queuing model with correlated reneging has been used to study the performance analysis of the load balancing server of a cloud computing system. The steady-state as well as the transient performance analyses have been carried out. Important measures of performance like average queue size, average delay, probability of task blocking, and the probability of no waiting in the queue are studied. Finally, some comparisons are performed which describe the effect of correlated task reneging over simple exponential reneging.

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A Temporally and Spatially Explicit, Mechanistic Estimation of Ragweed Pollen Concentrations Across Europe

SSRN

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SSRN 2023年

作者： Makra, László Matyasovszky, István Tusnády, Gábor Ziska, Lewis H. Hess, Jeremy J. Nyúl, László G. Chapman, Daniel S. Coviello, Luca Gobbi, Andrea Jurman, Giuseppe Furlanello, Cesare Brunato, Mauro Damialis, Athanasios Charalampopoulos, Athanasios Müller-Schärer, Heinz Schneider, Norbert Szabó, Bence Sümeghy, Zoltán Páldy, Anna Magyar, Donát Bergmann, Karl-Christian Deák, Áron József Mikó, Edit Thibaudon, Michel Oliver, Gilles Albertini, Roberto Bonini, Maira Šikoparija, Branko Radišić, Predrag Mitrović Josipović, Mirjana Gehrig, Regula Severova, Elena Rodinkova, Victoria Palamarchuk, Olena Stjepanović, Barbara Ianovici, Nicoleta Berger, Uwe Kofol Seliger, Andreja Rybníček, Ondřej Myszkowska, Dorota Dąbrowska-Zapart, Katarzyna Majkowska-Wojciechowska, Barbara Weryszko-Chmielewska, Elzbieta Grewling, Lukasz Rapiejko, Piotr Malkiewicz, Malgorzata Šaulienė, Ingrida Shalaboda, Valentina Prykhodo, Olexander Maleeva, Anna Ščevková, Jana Bullock, James M. Institute of Economics and Rural Development Faculty of Agriculture University of Szeged Andrássy út 15 Hódmezővásárhely6800 Hungary Department of Meteorology Eötvös Loránd University P.O.B. 32 Budapest1518 Hungary Alfréd Rényi Institute of Mathematics P.O.B 127 Budapest1364 Hungary Mailman School of Public Health Columbia University New YorkNY10032 United States Department of Global Health University of Washington SeattleWA98105 United States Department of Image Processing and Computer Graphics University of Szeged P.O.B. 652 Szeged6701 Hungary Biological and Environmental Sciences Faculty of Natural Sciences University of Stirling Scotland StirlingFK9 4LA United Kingdom University of Trento Enogis s.r.l. Trento Italy Bruno Kessler Foundation Trento Italy HK3 Lab Orobix Life Srl Rovereto Bergamo Italy Department of Information Engineering and Computer Science University of Trento Trento Italy Terrestrial Ecology and Climate Change Department of Ecology School of Biology Aristotle University of Thessaloniki ThessalonikiGR-54124 Greece Departement of Biology Unit of Ecology and Evolution University of Fribourg FribourgCH-1700 Switzerland National Institute of Environmental Health Albert Flórián út 2-6 Budapest1097 Hungary Institute of Allergology Charité Hindenburgdamm 30 Berlin12203 Germany Institute of Animal Science and Wildlife Management Faculty of Agriculture University of Szeged Andrássy út 15 Hódmezővásárhely6800 Hungary Réseau National de Surveillance Aérobiologique 11 chemin de la Creuzille Le Plat du Pin Brussieu696905 France Laboratory of Hygiene and Aerobiology Department of Medicine and Surgery University of Parma U.O. Medicina Interna di Continuità Azienda Ospedaliero-Universitaria di Parma Via Gramsci 14 Parma43126 Italy Hygiene and Public Health Service via Spagliardi 19 Parabiago Milan20015 Italy BioSensе Institute Research Institute for Information Technologies in Biosystems University of Novi Sad Dr

Ongoing and future climate change driven expansion of aeroallergen-producing plant species comprise a major human health problem across Europe and elsewhere. There is an urgent need to produce accurate, temporally dynamic maps at the continental level, especially in the context of climate uncertainty. This study aimed to restore missing daily ragweed pollen data sets for Europe, to produce phenological maps of ragweed pollen, resulting in the most complete and detailed high-resolution ragweed pollen concentration maps to date. To achieve this, we developed two statistical procedures, a Gaussian method (GM) and deep learning (DL) for restoring missing daily ragweed pollen data sets, based on the plant’s reproductive and growth (phenological, pollen production and frost-related) characteristics. DL model performances were consistently better for estimating annual total pollen concentrations than those of the GM approach. These are the first published modeled maps using altitude correction and phenology to recover missing pollen information. We created a web page (http://***/), including daily ragweed pollen concentration data sets of the stations examined and their restored daily data, allowing one to upload newly measured or recovered daily data. Generation of these maps provides a means to track pollen impacts in the context of climatic shifts, identify geographical regions with high pollen exposure, determine areas of future vulnerability, apply spatially-explicit mitigation measures and prioritize management interventions. © 2023, The Authors. All rights reserved.

关键词： Climate change

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The status of KAGRA underground cryogenic gravitational wave telescope 15

The status of KAGRA underground cryogenic gravitational wave...

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15th International Conference on Topics in Astroparticle and Underground Physics, TAUP 2017

作者： Akutsu, T. Ando, M. Araya, A. Aritomi, N. Asada, H. Aso, Y. Atsuta, S. Awai, K. Barton, M.A. Cannon, K. Craig, K. Creus, W. Doi, K. Eda, K. Enomoto, Y. Flaminio, R. Fujii, Y. Fujimoto, M.-K. Furuhata, T. Haino, S. Hasegawa, K. Hashino, K. Hayama, K. Hirobayashi, S. Hirose, E. Hsieh, A.H. Inoue, Y. Ioka, K. Itoh, Y. Kaji, T. Kajita, T. Kakizaki, M. Kamiizumi, M. Kambara, S. Kanda, N. Kanemura, S. Kaneyama, M. Kang, G. Kasuya, J. Kataoka, Y. Kawai, N. Kawamura, S. Kim, C. Kim, H. Kim, J. Kim, Y. Kimura, N. Kinugawa, T. Kirii, S. Kitaoka, Y. Kojima, Y. Kokeyama, K. Komori, K. Kotake, K. Kumar, R. Lee, H. Lee, H. Liu, Y. Luca, N. Majorana, E. Mano, S. Marchio, M. Matsui, T. Matsushima, F. Michimura, Y. Miyakawa, O. Miyamoto, T. Miyamoto, A. Miyo, K. Miyoki, S. Morii, W. Morisaki, S. Moriwaki, Y. Morozumi, T. Musha, M. Nagano, S. Nagano, K. Nakamura, K. Nakamura, T. Nakano, H. Nakano, M. Nakao, K. Narikawa, T. Quynh, L.Nguyen Ni, W.-T. Ochi, T. Oh, J. Oh, S. Ohashi, M. Ohishi, N. Ohkawa, M. Okutomi, K. Oohara, K. Alleano, F.E.P. Pinto, I. Sago, N. Saijo, M. Saito, Y. Sakai, K. Sakai, Y. Sasaki, Y. Sasaki, M. Sato, S. Sato, T. Sekiguchi, Y. Seto, N. Shibata, M. Shimoda, T. Shinkai, H. Shoda, A. Somiya, K. Son, E. Suemasa, A. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H. Takahashi, R. Takamori, A. Takeda, H. Tanaka, H. Tanaka, K. Tanaka, T. Tatsumi, D. Tomaru, T. Tomura, T. Travasso, F. Tsubono, K. Tsuchida, S. Uchikata, N. Uchiyama, T. Uehara, T. Ueki, S. Ueno, K. Ushiba, T. Van Putten, M.H.P.M. Vocca, H. Wada, S. Wakamatsu, T. Yamada, T. Yamamoto, S. Yamamoto, T. Yamamoto, K. Yamamoto, A. Yokoyama, J. Yokozawa, T. Yoon, T.H. Yuzurihara, H. Zeidler, S. Zhu, Z.-H. National Astronomical Observatory of Japan Mitaka Tokyo181-8588 Japan Department of Physics University of Tokyo Bunkyo Tokyo113-0033 Japan Earthquake Research Institute University of Tokyo Bunkyo Tokyo113-0032 Japan Department of Advanced Physics Hirosaki University Aomori Hirosaki036-8561 Japan National Astronomical Observatory of Japan Hida Gifu506-1205 Japan Department of Physics Tokyo Institute of Technology Meguro Tokyo152-8551 Japan Institute for Cosmic Ray Research University of Tokyo Hida Gifu506-1205 Japan Research Center for the Early Universe University of Tokyo Bunkyo Tokyo113-0033 Japan Institute for Cosmic Ray Research University of Tokyo Chiba Kashiwa277-8582 Japan Institute of Physics Academia Sinica Nankang Taipei11529 Taiwan Department of Physics University of Toyama Toyama Toyama930-8555 Japan Faculty of Engineering University of Toyama Toyama Toyama930-8555 Japan Yukawa Institute for Theoretical Physics Kyoto University Sakyo Kyoto606-8502 Japan Department of Physics Osaka City University Sumiyosi Osaka558-8585 Japan Department of Physics Osaka University Osaka Toyonaka560-0043 Japan Korea Institute of Science and Technology Information Yuseong Daejeon 34141 Korea Republic of Yuseong Daejeon34055 Korea Republic of National Institute for Mathematical Sciences Daejeon34047 Korea Republic of Department of Computer Simulation Inje University Gimhae Gyeongsangnam50834 Korea Republic of Department of Physics and Astronomy Seoul National University Seoul151-742 Korea Republic of High Energy Accelerator Research Organization Ibaraki Tsukuba305-0801 Japan Department of Physical Science Hiroshima University Higashihiroshima Hiroshima903-0213 Japan Department of Applied Physics Fukuoka University Jonan Fukuoka814-0180 Japan Department of Advanced Materials Science University of Tokyo Chiba Kashiwa277-8582 Japan Istituto Nazionale di Fisica Nucleare Sapienza University Roma00185 Italy Department o

KAGRA is a 3-km interferometric gravitational wave telescope located in the Kamioka mine in Japan. It is the first km-class gravitational wave telescope constructed underground to reduce seismic noise, and the first km-class telescope to use cryogenic cooling of test masses to reduce thermal noise. The construction of the infrastructure to house the interferometer in the tunnel, and the initial phase operation of the interferometer with a simple 3-km Michelson configuration have been completed. The first cryogenic operation is expected in 2018, and the observing runs with a full interferometer are expected in 2020s. The basic interferometer configuration and the current status of KAGRA are described. © Published under licence by IOP Publishing Ltd.

关键词： Interferometers

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Quantum Yield Bias in Materials With Lower Absorptance

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Physical Review Applied 2019年第2期12卷 024022-024022页

作者： Bart van Dam Benjamin Bruhn Ivo Kondapaneni Gejza Dohnal Alexander Wilkie Jaroslav Křivánek Jan Valenta Yvo D. Mudde Peter Schall Kateřina Dohnalová Institute of Physics University of Amsterdam Science Park 904 1098 XH Amsterdam Netherlands Faculty of Mathematics and Physics Computer Graphics Group KSVI Charles University Malostranské náměstí 25 Prague 1 CZ-11800 Czech Republic Faculty of Mechanical Engineering Czech Technical University in Prague Karlovo náměstí 13 121 35 Prague 2 Czech Republic Department of Chemical Physics and Optics Faculty of Mathematics and Physics Charles University Ke Karlovu 3 Prague 2 CZ-121 16 Czech Republic

Photoluminescence (PL) quantum yield (QY), which is defined as the ratio of emitted to absorbed photons, is the central quantity that characterizes light-emitting materials. It is an important parameter to assess the light efficiency of new materials, as well as identify novel photophysical mechanisms. While QY measurements are performed as standard in research and industry, accurate measurements are challenging. Here, we show that, besides known inaccuracies, PL QY measurements exhibit a surprising systematic bias. QY values are underestimated by a factor of two or more for samples with lower absorption, which can even lead to misinterpretation of results. We combine PL QY measurements of diluted Rhodamine 6G and two different semiconductor quantum dot solutions, via the standard integrating sphere method, with analytical modeling and ray-tracing simulations and find that, independent of the setup and luminescence mechanism, all measurements suffer from the same systematic underestimation of the QY. Through statistical analysis of the measured emitted and absorbed photon numbers, we uncover the origin of this underestimation in the asymmetry of the ratio distribution for low absorption, together with setup-specific features, such as signal offsets and nonlinearities. We suggest a robust calibration procedure to correct for this bias for precise evaluation of the QY in materials used for bioimaging, biosensing, and optoelectronic or photovoltaic devices.

关键词： Light propagation, transmission & absorption Metrology Optoelectronics Semiconductor quantum optics Optical spectroscopy Optical techniques Photoluminescence Photon counting

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Noise subtraction from KAGRA O3GK data using Independent Component Analysis

arXiv

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arXiv 2022年

作者： Abe, H. Akutsu, T. Ando, M. Araya, A. Aritomi, N. Asada, H. Aso, Y. Bae, S. Bae, Y. Bajpai, R. Cannon, K. Cao, Z. Capocasa, E. Chan, M. Chen, C. Chen, D. Chen, K. Chen, Y. Chiang, C.-Y. Chu, Y.-K. Eguchi, S. Eisenmann, M. Enomoto, Y. Flaminio, R. Fong, H.K. Fujii, Y. Fujikawa, Y. Fujimoto, Y. Fukunaga, I. Gao, D. Ge, G.-G. Ha, S. Hadiputrawan, I.P.W. Haino, S. Han, W.-B. Hasegawa, K. Hattori, K. Hayakawa, H. Hayama, K. Himemoto, Y. Hirata, N. Hirose, C. Ho, T.-C. Hsieh, B.-H. Hsieh, H.-F. Hsiung, C. Huang, H.-Y. Huang, P. Huang, Y.-C. Huang, Y.-J. Hui, D.C.Y. Ide, S. Inayoshi, K. Inoue, Y. Ito, K. Itoh, Y. Jeon, C. Jin, H.-B. Jung, K. Jung, P. Kaihotsu, K. Kajita, T. Kakizaki, M. Kamiizumi, M. Kanda, N. Kato, T. Kawaguchi, K. Kim, C. Kim, J. Kim, J.C. Kim, Y.-M. Kimura, N. Kiyota, T. Kobayashi, Y. Kohri, K. Kokeyama, K. Kong, A.K.H. Koyama, N. Kozakai, C. Kume, J. Kuromiya, Y. Kuroyanagi, S. Kwak, K. Lee, E. Lee, H.W. Lee, R. Leonardi, M. Li, K.L. Li, P. Lin, L.C.-C. Lin, C.-Y. Lin, E.T. Lin, F.-K. Lin, F.-L. Lin, H.L. Liu, G.C. Luo, L.-W. Ma'arif, M. Majorana, E. Michimura, Y. Mio, N. Miyakawa, O. Miyo, K. Miyoki, S. Mori, Y. Morisaki, S. Morisue, N. Moriwaki, Y. Nagano, K. Nakamura, K. Nakano, H. Nakano, M. Nakayama, Y. Narikawa, T. Naticchioni, L. Nguyen Quynh, L. Ni, W.-T. Nishimoto, T. Nishizawa, A. Nozaki, S. Obayashi, Y. Ogaki, W. Oh, J.J. Oh, K. Ohashi, M. Ohashi, T. Ohkawa, M. Ohta, H. Okutani, Y. Oohara, K. Oshino, S. Otabe, S. Pan, K.-C. Parisi, A. Park, J. Peña Arellano, F.E. Saha, S. Saito, Y. Sakai, K. Sawada, T. Sekiguchi, Y. Shao, L. Shikano, Y. Shimizu, H. Shimode, K. Shinkai, H. Shishido, T. Shoda, A. Somiya, K. Song, I. Sugimoto, R. Suresh, J. Suzuki, T. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H. Takahashi, R. Takano, S. Takeda, H. Takeda, M. Tanaka, K. Tanaka, T. Tanaka, T. Tanioka, S. Taruya, A. Graduate School of Science Tokyo Institute of Technology Meguro-ku Tokyo152-8551 Japan Mitaka City Tokyo181-8588 Japan Mitaka City Tokyo181-8588 Japan Department of Physics The University of Tokyo Bunkyo-ku Tokyo113-0033 Japan The University of Tokyo Bunkyo-ku Tokyo113-0033 Japan Earthquake Research Institute The University of Tokyo Bunkyo-ku Tokyo113-0032 Japan Department of Mathematics and Physics Gravitational Wave Science Project Hirosaki University Aomori Hirosaki City036-8561 Japan Kamioka-cho Hida City Gifu506-1205 Japan Mitaka City Tokyo181-8588 Japan Yuseong-gu Daejeon34141 Korea Republic of National Institute for Mathematical Sciences Yuseong-gu Daejeon34047 Korea Republic of Ibaraki Tsukuba City305-0801 Japan Department of Astronomy Beijing Normal University Beijing100875 China Department of Applied Physics Fukuoka University Jonan Fukuoka Fukuoka City814-0180 Japan Department of Physics Tamkang University Danshui Dist. New Taipei City25137 Taiwan Department of Physics Institute of Astronomy National Tsing Hua University Hsinchu30013 Taiwan Department of Physics Center for High Energy and High Field Physics National Central University Zhongli District Taoyuan City32001 Taiwan Department of Physics National Tsing Hua University Hsinchu30013 Taiwan Institute of Physics Academia Sinica Nankang Taipei11529 Taiwan Université Savoie Mont Blanc CNRS IN2P3 AnnecyF-74941 France Department of Astronomy The University of Tokyo Mitaka City Tokyo181-8588 Japan Faculty of Engineering Niigata University Nishi-ku Niigata Niigata City950-2181 Japan Department of Physics Graduate School of Science Osaka City University Sumiyoshi-ku Osaka City Osaka558-8585 Japan Chinese Academy of Sciences Xiao Hong Shan Wuhan430071 China Ulju-gun Ulsan44919 Korea Republic of Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China KAGRA Observatory The University of Tok

In April 2020, KAGRA conducted its first science observation in combination with the GEO 600 detector (O3GK) for two weeks. According to the noise budget estimation, suspension control noise in the low frequency band and acoustic noise in the middle frequency band are identified as the dominant contribution. In this study, we show that such noise can be reduced in offline data analysis by utilizing a method called Independent Component Analysis (ICA). Here the ICA model is extended from the one studied in iKAGRA data analysis by incorporating frequency dependence while linearity and stationarity of the couplings are still assumed. By using optimal witness sensors, those two dominant contributions are mitigated in the real observational data. We also analyze the stability of the transfer functions for whole two weeks data in order to investigate how the current subtraction method can be practically used in gravitational wave search. Copyright © 2022, The Authors. All rights reserved.

关键词： Data handling

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Identifying intracortical partial voluming effects using cortical surface normals in quantitative MRI T1 maps sensitive to microstructure

Identifying intracortical partial voluming effects using cor...

引用

Workshops on Image processing for the medicine, 2016

作者： Dinse, Juliane Schäfer, Andreas Bazin, Pierre-Louis Weiskopf, Nikolaus Max Planck Institute of Cognitive and Brain Science Leipzig Germany Simulation and Graphics Department Faculty of Computer Science Otto-von-Guericke University Magdeburg Germany Wellcome Trust Center for Neuroimaging Institute for Neurology University College London London United Kingdom

ISBN: (纸本)9783662494646

Partial voluming is a known problem in medical imaging. It occurs at high contrast edges between different structures. Image segmentation tasks can account for this type of effect to a certain degree, but residual intensity effects in structures located further away from affected edges remain. This paper focuses on partial volume (PV) effects at the interface between gray matter and cerebrospinal fluid in the brain when imaged using high-field magnetic resonance imaging (MRI). Here, we use cortical surface normals for spatially locating PV-induced effects on MRI measures of cortical microstructure. We demonstrate that especially in very narrow sulcal banks of the cortex, PV effects significantly influence cortical MRI intensities, but only up to a certain cortical depth. The method allows to investigate and better understand PV effects in the cortex to identify locations in which the MRI intensities can be fully trusted. The results may prove to be useful for future PV correction methods in brain segmentation. Also, cortical area studies may benefit from better PV estimation in order to yield more precise and confiding results on microstructure and areal extent. © Springer-Verlag Berlin Heidelberg 2016.

关键词： Magnetic resonance imaging

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Virtual and Augmented Reality Systems for Renal Interventions: A Systematic Review

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IEEE Reviews in Biomedical Engineering 2017年 10卷 78-94页

作者： Detmer, Felicitas J. Hettig, Julian Schindele, Daniel Schostak, Martin Hansen, Christian Institute for Simulation and Graphics Department of Computer Science Otto-von-Guericke University Magdeburg39106 Germany Department of Bioengineering George Mason University FairfaxVA22030 United States Clinic of Urology and Pediatric Urology University Hospital of Magdeburg Magdeburg39120 Germany

Purpose: Many virtual and augmented reality systems have been proposed to support renal interventions. This paper reviews such systems employed in the treatment of renal cell carcinoma and renal stones. Methods: A systematic literature search was performed. Inclusion criteria were virtual and augmented reality systems for radical or partial nephrectomy and renal stone treatment, excluding systems solely developed or evaluated for training purposes. Results: In total, 52 research papers were identified and analyzed. Most of the identified literature (87%) deals with systems for renal cell carcinoma treatment. About 44% of the systems have already been employed in clinical practice, but only 20% in studies with ten or more patients. Main challenges remaining for future research include the consideration of organ movement and deformation, human factor issues, and the conduction of large clinical studies. Conclusion: Augmented and virtual reality systems have the potential to improve safety and outcomes of renal interventions. In the last ten years, many technical advances have led to more sophisticated systems, which are already applied in clinical practice. Further research is required to cope with current limitations of virtual and augmented reality assistance in clinical environments. © 2017 IEEE.

关键词： Augmented reality

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Operational Research: Methods and Applications

arXiv

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arXiv 2023年

作者： Petropoulos, Fotios Laporte, Gilbert Aktas, Emel Alumur, Sibel A. Archetti, Claudia Ayhan, Hayriye Battarra, Maria Bennell, Julia A. Bourjolly, Jean-Marie Boylan, John E. Breton, Michèle Canca, David Charlin, Laurent Chen, Bo Cicek, Cihan Tugrul Cox, Louis Anthony Currie, Christine S.M. Demeulemeester, Erik Ding, Li Disney, Stephen M. Ehrgott, Matthias Eppler, Martin J. Erdogan, Güneş Fortz, Bernard Franco, L. Alberto Frische, Jens Greco, Salvatore Gregory, Amanda J. Hämäläinen, Raimo P. Herroelen, Willy Hewitt, Mike Holmström, Jan Hooker, John N. Işık, Tugçe Johnes, Jill Kara, Bahar Y. Karsu, Özlem Kent, Katherine Köhler, Charlotte Kunc, Martin Kuo, Yong-Hong Letchford, Adam N. Leung, Janny Li, Dong Li, Haitao Lienert, Judit Ljubić, Ivana Lodi, Andrea Lozano, Sebastián Lurkin, Virginie Martello, Silvano McHale, Ian G. Midgley, Gerald Morecroft, John D.W. Mutha, Akshay Oguz, Ceyda Petrovic, Sanja Pferschy, Ulrich Psaraftis, Harilaos N. Rose, Sam Saarinen, Lauri Salhi, Said Song, Jing-Sheng Sotiros, Dimitrios Stecke, Kathryn E. Strauss, Arne K. Tarhan, Istenç Thielen, Clemens Toth, Paolo Van Woensel, Tom Vanden Berghe, Greet Vasilakis, Christos Vaze, Vikrant Vigo, Daniele Virtanen, Kai Wang, Xun Weron, Rafal White, Leroy Yearworth, Mike Yıldırım, E. Alper Zaccour, Georges Zhao, Xuying School of Management University of Bath Bath United Kingdom Makridakis Open Forecasting Center University of Nicosia Nicosia Cyprus Department of Decision Sciences HEC Montréal Montreal Canada Molde University College Molde Norway Cranfield School of Management Cranfield University Cranfield United Kingdom Department of Management Sciences University of Waterloo Waterloo Canada ESSEC Business School in Paris Department of Information Systems Decision Sciences and Statistics Cergy France H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta United States Centre for Decision Research Leeds University Business School University of Leeds Leeds United Kingdom Université du Québec à Montréal Montreal Canada Centre for Marketing Analytics and Forecasting Lancaster University Management School Lancaster University Lancaster United Kingdom School of Engineering Department of Industrial Engineering and Management Science I University of Seville Seville Spain Mila-Quebec AI Institute Montreal Canada Warwick Business School University of Warwick Coventry United Kingdom Department of Industrial Engineering Atilim University Ankara Turkey Department of Business Analytics University of Colorado School of Business Denver United States Cox Associates Denver United States Mathematical Sciences University of Southampton Southampton United Kingdom Faculty of Economics and Business Research Center for Operations Management KU Leuven Leuven Belgium Durham University Business School Durham University Durham United Kingdom Center for Simulation Analytics and Modelling University of Exeter Business School Exeter United Kingdom Department of Management Science Lancaster University Management School Lancaster University Lancaster United Kingdom University of St. Gallen St. Gallen Switzerland HEC - Management School of the University of Liège Liège Belgium Département d'Informatique Université Libre de Bruxelles Bruss

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes. © 2023, CC BY.

关键词： Decision making

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Input optics systems of the KAGRA detector during O3GK

arXiv

引用

arXiv 2022年

作者： Akutsu, T. Ando, M. Arai, K. Arai, Y. Araki, S. Araya, A. Aritomi, N. Asada, H. Aso, Y. Bae, S. Bae, Y. Baiotti, L. Bajpai, R. Barton, M.A. Cannon, K. Cao, Z. Capocasa, E. Chan, M. Chen, C. Chen, K. Chen, Y. Chiang, C.-I. Chu, H. Chu, Y.-K. Eguchi, S. Enomoto, Y. Flaminio, R. Fujii, Y. Fujikawa, Y. Fukunaga, M. Fukushima, M. Furuhata, T. Gao, D. Ge, G.-G. Ha, S. Hagiwara, A. Haino, S. Han, W.-B. Hasegawa, K. Hattori, K. Hayakawa, H. Hayama, K. Himemoto, Y. Hiranuma, Y. Hirata, N. Hirose, E. Hong, Z. Hsieh, B.-H. Huang, G.-Z. Huang, H.-Y. Huang, P. Huang, Y.-C. Huang, Y.-J. Hui, D.C.Y. Ide, S. Ikenoue, B. Imam, S. Inayoshi, K. Inoue, Y. Ioka, K. Ito, K. Itoh, Y. Izumi, K. Jeon, C. Jin, H.-B. Jung, K. Jung, P. Kaihotsu, K. Kajita, T. Kakizaki, M. Kamiizumi, M. Kanbara, S. Kanda, N. Kang, G. Kataoka, Y. Kawaguchi, K. Kawai, N. Kawasaki, T. Kim, C. Kim, J. Kim, J.C. Kim, W.S. Kim, Y.-M. Kimura, N. Kita, N. Kitazawa, H. Kojima, Y. Kokeyama, K. Komori, K. Kong, A.K.H. Kotake, K. Kozakai, C. Kozu, R. Kumar, R. Kume, J. Kuo, C. Kuo, H.-S. Kuromiya, Y. Kuroyanagi, S. Kusayanagi, K. Kwak, K. Lee, H.K. Lee, H.W. Lee, R. Leonardi, M. Li, K.L. Lin, L.C.-C. Lin, C.-Y. Lin, F.-K. Lin, F.-L. Lin, H.L. Liu, G.C. Luo, L.-W. Majorana, E. Marchio, M. Michimura, Y. Mio, N. Miyakawa, O. Miyamoto, A. Miyazaki, Y. Miyo, K. Miyoki, S. Mori, Y. Morisaki, S. Moriwaki, Y. Nagano, K. Nagano, S. Nakamura, K. Nakano, H. Nakano, M. Nakashima, R. Nakayama, Y. Narikawa, T. Naticchioni, L. Negishi, R. Nguyen Quynh, L. Ni, W.-T. Nishizawa, A. Nozaki, S. Obuchi, Y. Ogaki, W. Oh, J.J. Oh, K. Oh, S.H. Ohashi, M. Ohishi, N. Ohkawa, M. Ohta, H. Okutani, Y. Okutomi, K. Oohara, K. Ooi, C. Oshino, S. Otabe, S. Pan, K.-C. Pang, H. Parisi, A. Park, J. Pena Arellano, F.E. Pinto, I. Sago, N. Saito, S. Saito, Y. Sakai, K. Sakai, Y. Sakuno, Y. Sato, S. Sato, T. Gravitational Wave Science Project National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo181-8588 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Research Center for the Early Universe The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba277-8582 Japan 1-1 Oho Tsukuba City Ibaraki305-0801 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo113-0032 Japan Department of Mathematics and Physics Graduate School of Science and Technology Hirosaki University 3 Bunkyo-cho Aomori Hirosaki036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan 238 Higashi-Mozumi Kamioka-cho Gifu Hida City506-1205 Japan 2-21-1 Osawa Mitaka City Tokyo181-8588 Japan Korea Institute of Science and Technology Information 245 Daehak-ro Yuseong-gu Daejeon34141 Korea Republic of National Institute for Mathematical Sciences 70 Yuseong-daero 1689 Beon-gil Yuseong-gu Daejeon34047 Korea Republic of International College Osaka University 1-1 Machikaneyama-cho Toyonaka City Osaka560-0043 Japan 1-1 Oho Tsukuba City Ibaraki305-0801 Japan Department of Astronomy Beijing Normal University Xinjiekouwai Street 19 Haidian District Beijing100875 China Department of Applied Physics Fukuoka University 8-19-1 Nanakuma Jonan Fukuoka Fukuoka City814-0180 Japan Department of Physics Tamkang University No. 151 Yingzhuan Rd. Danshui Dist. New Taipei City25137 Taiwan Department of Physics Institute of Astronomy National Tsing Hua University No. 101 Section 2 Kuang-Fu Road Hsinchu30013 Taiwan Department of Physics Center for High Energy and High Field Physics National Central University No.300 Zhongda

KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25th to March 10th, 2020, and its first joint observation with the GEO 600 detector from April 7th - 21st, 2020 (O3GK). This study presents an overview of the input optics systems of the KAGRA detector, which consist of various optical systems, such as a laser source, its intensity and frequency stabilization systems, modulators, a Faraday isolator, mode-matching telescopes, and a high-power beam dump. These optics were successfully delivered to the KAGRA interferometer and operated stably during the observations. The laser frequency noise was observed to limit the detector sensitivity above a few kHz, whereas the laser intensity did not significantly limit the detector sensitivity. © 2022, CC BY.

关键词： Gravity waves

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