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Roadmap on Deep Learning for Microscopy

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arXiv 2023年

作者： Volpe, Giovanni Wählby, Carolina Tian, Lei Hecht, Michael Yakimovich, Artur Monakhova, Kristina Waller, Laura Sbalzarini, Ivo F. Metzler, Christopher A. Xie, Mingyang Zhang, Kevin Lenton, Isaac C.D. Rubinsztein-Dunlop, Halina Brunner, Daniel Bai, Bijie Ozcan, Aydogan Midtvedt, Daniel Wang, Hao Sladoje, Nataša Lindblad, Joakim Smith, Jason T. Ochoa, Marien Barroso, Margarida Intes, Xavier Qiu, Tong Yu, Li-Yu You, Sixian Liu, Yongtao Ziatdinov, Maxim A. Kalinin, Sergei V. Sheridan, Arlo Manor, Uri Nehme, Elias Goldenberg, Ofri Shechtman, Yoav Moberg, Henrik K. Langhammer, Christoph Špačková, Barbora Helgadottir, Saga Midtvedt, Benjamin Argun, Aykut Thalheim, Tobias Cichos, Frank Bo, Stefano Hubatsch, Lars Pineda, Jesus Manzo, Carlo Bachimanchi, Harshith Selander, Erik Homs-Corbera, Antoni Fränzl, Martin de Haan, Kevin Rivenson, Yair Korczak, Zofia Adiels, Caroline Beck Mijalkov, Mite Veréb, Dániel Chang, Yu-Wei Pereira, Joana B. Matuszewski, Damian Kylberg, Gustaf Sintorn, Ida-Maria Caicedo, Juan C. Cimini, Beth A. Bell, Muyinatu Lediju A. Saraiva, Bruno M. Jacquemet, Guillaume Henriques, Ricardo Ouyang, Wei Le, Trang Gómez-De-Mariscal, Estibaliz Sage, Daniel Muñoz-Barrutia, Arrate Lindqvist, Ebba Josefson Bergman, Johanna Department of Physics University of Gothenburg Gothenburg41296 Sweden Dept. IT and SciLifeLab Uppsala University Sweden Department of Electrical and Computer Engineering Boston University BostonMA02215 United States Department of Biomedical Engineering Boston University BostonMA02215 United States Görlitz Germany Department of Renal Medicine Division of Medicine University College London Royal Free Hospital Campus London United Kingdom Artificial Intelligence for Life Sciences CIC Dorset United Kingdom Roche Pharma International Informatics Roche Diagnostics GmbH Mannheim Germany Department of Electrical Engineering and Computer Sciences UC Berkeley United States Technische Universität Dresden Faculty of Computer Science Dresden Germany Max Planck Institute of Molecular Cell Biology and Genetics Center for Systems Biology Dresden Dresden Germany University of Maryland College Park United States Klosterneuburg3400 Austria School of Mathematics and Physics The University of Queensland Brisbane4072 Australia Australian Research Council Centre of Excellence for Engineered Quantum Systems The University of Queensland Brisbane4072 Australia Département d’Optique P. M. Duffieux Institut FEMTO-ST Université Franche-Comté CNRS UMR 6174 Besançon France Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA United States Department of Information Technology Uppsala University Sweden Department of Biomedical Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Elephas 1 Erdman Pl. Madison53705 United States University of Wisconsin–Madison Department of Medical Physics MadisonWI53705 United States Department of Molecular and Cellular Physiology Albany Medical College AlbanyNY12208 United States Research Laboratory of Electronics Electrical Engineering and Computer Science Massachusetts Institute of Technology BostonMA United States Center for Nanophase Materials Sciences Oak R

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences. Copyright © 2023, The Authors. All rights reserved.

关键词： Image enhancement

A chirality-based quantum leap

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arXiv 2020年

作者： Aiello, Clarice D. Abbas, Muneer Abendroth, John M. Afanasev, Andrei Agarwal, Shivang Banerjee, Amartya S. Beratan, David N. Belling, Jason N. Berche, Bertrand Botana, Antia Caram, Justin R. Celardo, Giuseppe Luca Cuniberti, Gianaurelio Garcia-Etxarri, Aitzol Dianat, Arezoo Diez-Perez, Ismael Guo, Yuqi Gutierrez, Rafael Herrmann, Carmen Hihath, Joshua Kale, Suneet Kurian, Philip Lai, Ying-Cheng Lopez, Alexander Medina, Ernesto Mujica, Vladimiro Naaman, Ron Noormandipour, Mohammadreza Palma, Julio L. Paltiel, Yossi Petuskey, William T. Ribeiro-Silva, João Carlos Saenz, Juan José Santos, Elton J.G. Solyanik, Maria Sorger, Volker J. Stemer, Dominik M. Ugalde, Jesus M. Valdes-Curiel, Ana Varela, Solmar Waldeck, David H. Weiss, Paul S. Zacharias, Helmut Wang, Qing Hua California NanoSystems Institute University of California Los Angeles Los AngelesCA90095 United States Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA90095 United States Department of Microbiology Howard University WashingtonDC20059 United States Laboratory for Solid State Physics ETH Zürich Zürich8093 Switzerland George Washington University WashingtonDC20052 United States Department of Materials Science and Engineering University of California Los Angeles Los AngelesCA90095 United States Department of Chemistry Duke University DurhamNC27708 United States Department of Chemistry & Biochemistry University of California Los Angeles Los AngelesCA90095 United States Laboratoire de Physique et Chimie Théoriques UMR Université de Lorraine-CNRS Vandœuvre les Nancy 7019 54506 France Department of Physics Arizona State University TempeAZ85287 United States Institute of Physics IFUAP-BUAP Puebla72000 Mexico Institute for Materials Science Max Bergmann Center of Biomaterials Dresden University of Technology Dresden01062 Germany Donostia International Physics Center Euskal Herriko Unibertsitatea Euskadi Donostia20018 Spain Department of Chemistry Faculty of Natural and Mathematical Sciences King's College London 7 Trinity Street LondonSE1 1DB United Kingdom School for Engineering of Matter Transport and Energy Arizona State University TempeAZ85287 United States Department of Chemistry University of Hamburg Hamburg20146 Germany Department of Electrical and Computer Engineering University of California Davis DavisCA95616 United States School of Molecular Sciences Arizona State University TempeAZ85287 United States Quantum Biology Laboratory Graduate School Howard University WashingtonDC20059 United States School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Department of Chemical and Biological Physics Weizmann Institut

Chiral degrees of freedom occur in matter and in electromagnetic fields and constitute an area of research that is experiencing renewed interest driven by recent observations of the chiral-induced spin selectivity (CISS) effect in chiral molecules and engineered nanomaterials. The CISS effect underpins the fact that charge transport through nanoscopic chiral structures favors a particular electronic spin orientation, resulting in large room-temperature spin polarizations. Observations of the CISS effect suggest opportunities for spin control and for the design and fabrication of room-temperature quantum devices from the bottom up, with atomic-scale precision. Any technology that relies on optimal charge transport, including quantum devices for logic, sensing, and storage, may benefit from chiral quantum properties. These properties can be theoretically and experimentally investigated from a quantum information perspective, which is presently lacking. There are uncharted implications for the quantum sciences once chiral couplings can be engineered to control the storage, transduction, and manipulation of quantum information. This forward-looking perspective provides a survey of the experimental and theoretical fundamentals of chiral-influenced quantum effects, and presents a vision for their future roles in enabling room-temperature quantum technologies. Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum optics

Operational Research: Methods and Applications

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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

Cover Feature: Phosphorus-Doped MoS2Nanosheets Supported on Carbon Cloths as Efficient Hydrogen-Generation Electrocatalysts (ChemCatChem 7/2018)

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ChemCatChem 2018年第7期10卷 1477-1477页

作者： Luozhen Bian Wei Gao Jiamin Sun Mingming Han Fulin Li Zhaofeng Gao Lei Shu Prof. Ning Han Prof. Zai-xing Yang Prof. Aimin Song Prof. Yongquan Qu Prof. Johnny C. Ho Shenzhen Research Institute Shandong University Shenzhen 518057 P.R. China Center of Nanoelectronics and School of Microelectronics Shandong University Jinan 250100 P.R. China Center for Applied Chemical Research Frontier Institute of Science and Technology Xi'an Jiaotong University Xi'an 710049 P.R. China Department of Materials Science and Engineering City University of Hong Kong 83 Tat Chee Avenue Kowloon Hong Kong P.R. China Shenzhen Research Institute City University of Hong Kong Shenzhen 518057 P.R. China State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing 100190 P.R. China

The Influence of the Dispersing Agent Nature on the Interaction of DNA Nucleotides With the Surface of YSZ Nanoparticles and the Homogeneity of Lyophilites Based on Them

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SSRN

SSRN 2022年

作者： Doroshkevich, Aleksander S. Doroshkevich, Viktor S. Zelenyak, Tatyana Yu. Doroshkevich, Nelya V. Lyubchyk, Andriy I. Lyubchyk, Sergiy I. Lyubchyk, Svitlana B. Tatarinova, Alisa A. Stanculescu, Anca Chicea, Dan Mita, Carmen Cornei, Nicoleta Mardare, Diana Oksengendler, Boris L. Nikiforova, Nadejda N. Mirzayev, Matlab N. Popov, Evgeni P. Donkov, Aleksandr A. Teofilović, Vesna Jasinska, Bozena Khiem, Le Hong Joint Institute for Nuclear Research Dubna Russia Donetsk Institute for Physics and Engineering named after O.O. Galkin Kiev Ukraine Donetsk National University Ukraine Donetsk National Vasyl Stus University Vinnitsa Ukraine Nanotechcenter LLC Krzhizhanovsky str. 3 Kyiv03680 Ukraine Research Centre in Industrial Engineering Management and Sustainability Lusófona University Campo Grande 376 Lisboa1749-024 Portugal REQUIMTE Faculdade de Ciências e Tecnologia Universidade Nova de Lisboa Quina de Torre Caparica2829-516 Portugal Optical Processes in Nanostructured Materials Laboratory National Institute of Materials Physics 405A Atomistilor Street P.O. Box MG-7 Magurele077125 Romania Research Center for Complex Physical Systems Faculty of Sciences "Lucian Blaga" University of Sibiu Dr. Ion Ratiu str. no. 5–7 Sibiu550012 Romania Faculty of Chemistry "Alexandru Ioan Cuza" University of Iasi Bld. Carol I No. 11 Iasi700506 Romania Faculty of Physics "Alexandru Ioan Cuza" University of Iasi Bld. Carol I No. 11 Iasi700506 Romania Ion-plasma and laser technologies Institute after U. Arifov Tashkent Uzbekistan Institute of Radiation Problems Azerbaijan National Academy of Sciences BakuАZ1143 Azerbaijan Institute of Solid-State Physics Bulgarian Academy of Sciences Sofia1784 Bulgaria Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia1784 Bulgaria Laboratory of Physics INN Vinča University of Belgrade M. Petrovica Alasa 12-14 Belgrade Serbia Institute of Physics Maria Curie-Sklodowska University Lublin Poland Graduate University of Science and Technology Vietnam Academy of Science and Technology 18 Hoang Quoc Viet Cau Giay Hanoi Viet Nam Institute of Physics 10 Dao Tan Ba Dinh Hanoi Viet Nam

A variational analysis of dispersion medium (electrolytes and surfactants) was carried out for the best nucleotide interactions with the presence of nanoparticles and the ability to formation of homogeneous coatings upon drying / lyophilization. Using UV-spectroscopy and transmission electron microscopy, the processes of immobilization of nucleotides on the surface of nanoparticles of the composition ZrO2-3mol% Y2O3 (YSZ) in the presence of various dispersing agents were investigated. Promising dispersing agents were established, the optimal composition of suspensions based on DNA nucleotides and YSZ nanoparticles, which is potentially suitable for adaptive technologies of bionanoelectronics, was *** aim of the work is to obtain and study functional media for molecular electronics based on heterojunctions biological molecule – wide-gap dielectric. © 2022, The Authors. All rights reserved.

关键词： Electric fields

Steering self-organisation through confinement

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arXiv 2022年

作者： Araújo, Nuno A.M. Janssen, Liesbeth M.C. Barois, Thomas Boffetta, Guido Cohen, Itai Corbetta, Alessandro Dauchot, Olivier Dijkstra, Marjolein Durham, William M. Dussutour, Audrey Garnier, Simon Gelderblom, Hanneke Golestanian, Ramin Isa, Lucio Koenderink, Gijsje H. Löwen, Hartmut Metzler, Ralf Polin, Marco Royall, C. Patrick Šarić, Anđela Sengupta, Anupam Sykes, Cécile Trianni, Vito Tuval, Idan Vogel, Nicolas Yeomans, Julia M. Zuriguel, Iker Marin, Alvaro Volpe, Giorgio Departamento de Física Faculdade de Ciências Universidade de Lisboa Lisboa1749-016 Portugal Centro de Física Teórica e Computacional Faculdade de Ciências Universidade de Lisboa Lisboa1749-016 Portugal Department of Applied Physics Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands Institute for Complex Molecular Systems Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands University of Bordeaux CNRS LOMA UMR 5798 TalenceF-33400 France Department of Physics INFN University of Torino via Pietro Giuria 1 Torino10125 Italy Kavli Institute Cornell for Nanoscale Science Cornell University IthacaNY United States Laboratory of Atomic and Solid-State Physics Cornell University IthacaNY United States Gulliver UMR CNRS 7083 ESPCI Paris Université PSL Paris75005 France Soft condensed matter Department of Physics Debye institute for Nanomaterials Science Utrecht University Princetonplein 1 Utrecht3584 CC Netherlands Department of Physics and Astronomy University of Sheffield Hounsfield Road SheffieldS3 7RH United Kingdom Toulouse University CNRS UPS Toulouse31062 AD France Department of Biological Sciences New Jersey Institute of Technology NewarkNJ07102 United States Department of Applied Physics J.M. Burgers Center for Fluid Dynamics Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands Göttingen37077 Germany Rudolf Peierls Centre for Theoretical Physics University of Oxford OxfordOX1 3PU United Kingdom Laboratory for Soft Materials and Interfaces Department of Materials ETH Zürich Zürich8093 Switzerland Department of Bionanoscience Kavli Institute of Nanoscience Delft University of Technology Delft2629 HZ Netherlands Institut für Theoretische Physik II: Weiche Materie Heinrich-Heine-Universität Düsseldorf Universitätsstrasse 1 Düsseldorf40225 Germany Institute of Physics & Astronomy University of Potsdam Karl-Liebknecht-Str 24/25 Potsdam-Golm D-14

Self-organisation is the spontaneous emergence of spatio-temporal structures and patterns from the interaction of smaller individual units. Examples are found across many scales in very different systems and scientific disciplines, from physics, materials science and robotics to biology, geophysics and astronomy. Recent research has highlighted how self-organisation can be both mediated and controlled by confinement. Confinement occurs through interactions with boundaries, and can function as either a catalyst or inhibitor of self-organisation. It can then become a means to actively steer the emergence or suppression of collective phenomena in space and time. Here, to provide a common framework for future research, we examine the role of confinement in self-organisation and identify overarching scientific challenges across disciplines that need to be addressed to harness its full scientific and technological potential. This framework will not only accelerate the generation of a common deeper understanding of self-organisation but also trigger the development of innovative strategies to steer it through confinement, with impact, e.g., on the design of smarter materials, tissue engineering for biomedicine and crowd management. Copyright © 2022, The Authors. All rights reserved.

关键词： Tissue engineering

Erratum: On the nonlinear dynamics of electro-magnon excitations in the BaTiO3/Fe nanostructured multiferroic composite material

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欧洲物理快报 2018年第4期123卷

作者： P. A. Paglan J. P. Nguenang S. Ruffo Pure Physics Laboratory: Group of Nonlinear Physics and Complex Systems Department of Physics Faculty of Science University of Douala - P.O. Box 24157 Douala Cameroon National Committee for Technology Development (CNDT) Ministry of Scientific Research and Innovation P.O. Box 1457 Yaounde Cameroon The Abdus Salam ICTP - Strada Costiera 11 I-34151 Trieste Italy SISSA - Via Bonomea 265 I-34136 Trieste Italy INFN Sezione di Trieste - I-34151 Trieste Italy Istituto dei Sistemi Complessi Consiglio Nazionale delle Ricerche - Via Madonna del Piano 10 I-50019 Sesto Fiorentino Italy

Original article: EPL, 122 (2018) *** for HTML: https://***/10.1209/0295-5075/123/49901

关键词： Errata

The Effect of Relative Humidity on Eddy Covariance Latent Heat Flux Measurements and its Implication for Partitioning into Transpiration and Evaporation

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SSRN

SSRN 2022年

作者： Zhang, Weijie Jung, Martin Migliavacca, Mirco Poyatos, Rafael Miralles, Diego El-Madany, Tarek S. Galvagno, Marta Carrara, Arnaud Arriga, Nicola Ibrom, Andreas Mammarella, Ivan Papale, Dario Cleverly, Jamie Liddell, Michael J. Wohlfahrt, Georg Markwitz, Christian Mauder, Matthias Paul-Limoges, Eugenie Schmidt, Marius Wolf, Sebastian Brümmer, Christian Arain, M. Altaf Fares, Silvano Kato, Tomomichi Ardö, Jonas Oechel, Walter Hanson, Chad Korkiakoski, Mika Biraud, Sébastien Steinbrecher, Rainer Billesbach, Dave Montagnani, Leonardo Woodgate, William Shao, Changliang Carvalhais, Nuno Reichstein, Markus Nelson, Jacob A. Department of Biogeochemical Integration Max Planck Institute for Biogeochemistry Jena Germany Faculty of Bioscience Engineering Ghent University Ghent Belgium Italy CREAF Cerdanyola del Vallès Spain Universitat Autònoma de Barcelona Cerdanyola del Vallès Spain Climate Change Unit Environmental Protection Agency of Aosta Valley Aosta Italy Fundación Centro de Estudios Ambientales del Mediterráneo Valencia Paterna46980 Spain Technical University of Denmark Dept. of Environment and Resource Management Kgs. Lyngby Denmark Faculty of Science University of Helsinki P.O. Box 68 Helsinki00014 Finland University of Tuscia - DIBAF Viterbo01100 Italy IAFES Viterbo01100 Italy College of Science and Engineering James Cook University CairnsQLD4878 Australia Department of Ecology University of Innsbruck Innsbruck Austria Bioclimatology University of Göttingen Göttingen Germany Technische Universität Dresden Faculty of Environmental Sciences Dresden Germany Department of Geography University of Zurich Zurich8057 Switzerland Agrosphere Institute IBG-3 Forschungszentrum Jülich GmbH Jülich52425 Germany Department of Environmental Systems Science ETH Zurich Zurich8092 Switzerland Thünen Institute of Climate-Smart Agriculture Braunschweig Germany School of Earth Environment and Society McMaster University HamiltonON Canada National Research Council of Italy Institute of Bioeconomy Rome Italy Research Faculty of Agriculture Hokkaido University Sapporo Japan Department of Physical Geography and Ecosystem Science Lund University Sweden Global Change Research Group San Diego State University San DiegoCA United States Department of Geography University of Exeter Exeter United Kingdom Department of Forests Ecosystems and Society College of Forestry Oregon State University CorvallisOR United States Climate Sciences Department Lawrence Berkeley National Laboratory BerkeleyCA United States Garmisch-Partenkirchen Germany University of Nebraska

While the eddy covariance (EC) technique is a well-established method for measuring water fluxes (i.e., evaporation or 'evapotranspiration’, ET), the method is susceptible to many uncertainties. One such issue is the potential underestimation of ET when relative humidity (RH) is high (>70%), due to low-pass filtering with some EC systems. The influence of these errors for different types of EC systems (e.g. open- or closed-path sensors) has not been characterized for synthesis datasets such as the widely used FLUXNET2015 dataset. Here, we assess the RH-associated underestimation of ET from different EC systems for 163 sites in the FLUXNET2015 dataset. We found that high RH errors were most apparent during hours when RH was approximately 70% or higher. This underestimation was predominantly observed at sites using closed-path EC systems, with ET underestimations estimated at 58% when RH was higher than 90%. To assess the potential impact of high RH on ET and EC-based transpiration (T) estimates, ET was corrected using a machine learning based empirical approach and then partitioned into T and E using two different data-driven methods. Results showed opposite (increasing vs decreasing T-to-ET ratios, T/ET) responses owing to the contrasting ways the two methods model WUE. Analysis of T estimates based on three different ET correction approaches showed no clear improvement in correlation with independent sap flow based T. Overall, our results demonstrate the existence of high RH-related bias in water fluxes in the FLUXNET2015 dataset and suggest that the underestimation of ET is a significant source of uncertainty that must be reckoned with when estimating ecosystem T/ET and WUE. This work further demonstrates the need for high-quality, independent ecosystem water flux measurements to understand the uncertainties in EC-based ET and T estimates. © 2022, The Authors. All rights reserved.

关键词： Evapotranspiration

Input optics systems of the KAGRA detector during O3GK (vol 2023, 023F01, 2023)

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PROGRESS OF THEORETICAL AND EXPERIMENTAL PHYSICS 2023年第5期2023卷

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, Ws 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. Quynh, L. Nguyen Ni, W-T Nishizawa, A. Nozaki, S. Obuchi, Y. Ogaki, W. Oh, J. J. 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. Arellano, F. E. Pena Pinto, I. Sago, N. Saito, S. Saito, Y. Sakai, K. Sakai, Y. Sakuno, Y. Sato, S. Sato, T. Sawada, T. Sekiguchi, T. Sekiguchi, Y. Shao, L. Shibagaki, S. Shimizu, R. Shimoda, T. Shimode, K. Shinkai, H. Shishido, T. Shoda, A. Somiya, K. Son, E. J. Sotani, H. Sugimoto, R. Suresh, J. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H Gravitational Wave Science Project National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba 277-8582 Japan Accelerator Laboratory High Energy Accelerator Research Organization (KEK) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Graduate School of Science and Technology Hirosaki University 3 Bunkyo-cho Hirosaki Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan 238 Higashi-Mozumi Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information 245 Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea National Institute for Mathematical Sciences 70 Yuseong-daero 1689 Beon-gil Yuseong-gu Daejeon 34047 Republic of Korea International College Osaka University 1-1 Machikaneyama-cho Toyonaka City Osaka 560-0043 Japan School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University Xinjiekouwai Street 19 Haidian District Beijing 100875 China Department of Applied Physics Fukuoka University 8-19-1 Nanakuma Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University No. 151 Yingzhuan Road Danshui Dist. New Taipei City 25137 Taiwan Department of Physics

KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25 to March 10, 2020, and its first joint observation with the GEO 600 detector from April 7 to April 21, 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 kilohertz, whereas the laser intensity did not significantly limit the detector sensitivity.

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