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4th International Conference of the Virtual and Augmented Reality in Education, VARE 2018

作者： Ginters, Egils Puspurs, Martins Griscenko, Igors Dumburs, Davis Sociotechnical Systems Engineering Group Department of Modelling and Simulation Faculty of Computer Science and Information Technology Riga Technical University 2 Daugavgrivas Street RigaLV-1048 Latvia

ISBN: (纸本)9788885741218

If we believe in statistical data, unless skilled labour resources in EC will not be updated on migration, the problems expect pension beneficiaries' and other socially protected groups that are jointly supported by workers. It is important to be aware of the challenges that are expected and to keep skilled professionals in the labour market as long as possible, compensating for loss of job capacity and enabling skills development through the use of ICTE and the global area of information. The study aims at establishing a conceptual set of requirements for augmented reality (AR) applications for the preservation and development of older communications capabilities. The human physical body is aging with time, i.e. worsening memory, perception and functionality. Virtual and augmented reality (VR/AR) applications are associated with the first two elements: memory and perception. Data search and recall functions are associated with memory, but with sensory organs - vision, hearing, touch and taste. The article looks at, above all, vision and memory related issues. Today, there is a diverse, complex and poorly adaptable, as well as functionally limited but relatively expensive VR/AR equipment, whose sustainability is debatable. The analysis of the situations covered by the article makes it possible to design a conceptual model for the logical structure of the application, which is the justification for further selection of technical equipment and the construction of the physical structure of the socio-technical system. Copyright © (2015) by CAL-TEK *** rights reserved. . All Rights Reserved.

关键词： Augmented reality

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“Rim-Differentiated” Pillararenes

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Angewandte Chemie 2022年第31期134卷

作者： Yang Chao Dr. Tushar Ulhas Thikekar Wangjian Fang Rong Chang Jiong Xu Nianfeng Ouyang Dr. Jun Xu Yan Gao Dr. Minjie Guo Prof. Han Zuilhof Prof. Andrew C.-H. Sue Institute for Molecular Design and Synthesis School of Pharmaceutical Science & Technology Tianjin University 92 Weijin Road Nankai District Tianjin 300072 P. R. China College of Chemistry and Chemical Engineering Xiamen University 422 Siming South Road Siming District Xiamen 361005 P. R. China Laboratory of Organic Chemistry Wageningen University Stippeneng 4 6708 WE Wageningen The Netherlands Department of Chemical and Materials Engineering Faculty of Engineering King Abdulaziz University Jeddah Saudi Arabia

A “rim-differentiated” pillar[6]arene (RD-P[6]) was obtained successfully, with the assistance of a dimeric silver trifluoroacetate template, among eight different constitutional isomers in a direct and regioselective manner. The solid-state conformation of this macrocycle could switch from the 1,3,5-alternate to a truly rim-differentiated one upon guest inclusion. This highly symmetric RD-P[6] not only hosts metal-containing molecules inside its cavity, but also can form a pillar[6]arene-C 60 adduct through co-crystallization on account of donor-acceptor interactions. The development of synthetic strategies to desymmetrize pillararenes offers new opportunities for engineering complex molecular architectures and organic electronic materials.

关键词： Co-Crystals Host–Guest Chemistry Macrocycles Pillar[n]arenes Tiara[n]arenes

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SleepEEGNet: Automated Sleep Stage Scoring with Sequence to Sequence Deep Learning Approach

arXiv

引用

arXiv 2019年

作者： Mousavi, Sajad Afghah, Fatemeh Rajendra Acharya, U. School of Informatics Computing and Cyber Systems Northern Arizona University Flagstaff United States Department of Electronics and Computer Engineering Ngee Ann Polytechnic Singapore Singapore Department of Biomedical Engineering School of Science and Technology Singapore University of Social Sciences Singapore Singapore Department of Biomedical Engineering Faculty of Engineering University of Malaya

Electroencephalogram (EEG) is a common base signal used to monitor brain activity and diagnose sleep disorders. Manual sleep stage scoring is a time-consuming task for sleep experts and is limited by inter-rater reliability. In this paper, we propose an automatic sleep stage annotation method called SleepEEGNet using a singlechannel EEG signal. The SleepEEGNet is composed of deep convolutional neural networks (CNNs) to extract timeinvariant features, frequency information, and a sequence to sequence model to capture the complex and long shortterm context dependencies between sleep epochs and scores. In addition, to reduce the effect of the class imbalance problem presented in the available sleep datasets, we applied novel loss functions to have an equal misclassified error for each sleep stage while training the network. We evaluated the proposed method on different single-EEG channels (i.e., Fpz-Cz and Pz-Oz EEG channels) from the Physionet Sleep-EDF datasets published in 2013 and 2018. The evaluation results demonstrate that the proposed method achieved the best annotation performance compared to current literature, with an overall accuracy of 84.26%, a macro F1-score of 79.66% and = 0.79. Our developed model is ready to test with more sleep EEG signals and aid the sleep specialists to arrive at an accurate diagnosis. The source code is available at https://***/SajadMo/SleepEEGNet1. Copyright © 2019, The Authors. All rights reserved.

关键词： Electroencephalography

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Measurement of the iron spectrum in cosmic rays from 10 GeV/n to 2.0 TeV/n with the calorimetric electron telescope on the international space station

arXiv

引用

arXiv 2021年

作者： Adriani, O. Akaike, Y. Asano, K. Asaoka, Y. Berti, E. Bigongiari, G. Binns, W.R. Bongi, M. Brogi, P. Bruno, A. Buckley, J.H. Cannady, N. Castellini, G. Checchia, Caterina Cherry, M.L. Collazuol, G. Ebisawa, K. Fuke, H. Gonzi, S. Guzik, T.G. Hams, T. Hibino, K. Ichimura, M. Ioka, K. Ishizaki, W. Israel, M.H. Kasahara, K. Kataoka, J. Kataoka, R. Katayose, Y. Kato, C. Kawanaka, N. Kawakubo, Y. Kobayashi, K. Kohri, K. Krawczynski, H.S. Krizmanic, J.F. Link, J. Maestro, P. Marrocchesi, P.S. Messineo, A.M. Mitchell, J.W. Miyake, S. Moiseev, A.A. Mori, M. Mori, N. Motz, H.M. Munakata, K. Nakahira, S. Nishimura, J. de Nolfo, G.A. Okuno, S. Ormes, J.F. Ospina, N. Ozawa, S. Pacini, L. Papini, P. Rauch, B.F. Ricciarini, S.B. Sakai, K. Sakamoto, T. Sasaki, M. Shimizu, Y. Shiomi, A. Spillantini, P. Stolzi, F. Sugita, S. Sulaj, A. Takita, M. Tamura, T. Terasawa, T. Torii, S. Tsunesada, Y. Uchihori, Y. Vannuccini, E. Wefel, J.P. Yamaoka, K. Yanagita, S. Yoshida, A. Yoshida, K. Department of Physics University of Florence Via Sansone 1 Sesto Fiorentino50019 Italy INFN Sezione di Florence Via Sansone 1 Sesto Fiorentino50019 Italy Waseda Research Institute for Science and Engineering Waseda University 17 Kikuicho Shinjuku Tokyo162-0044 Japan JEM Utilization Center Human Spaceflight Technology Directorate Japan Aerospace Exploration Agency 2-1-1 Sengen Ibaraki Tsukuba305-8505 Japan Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-Ha Chiba Kashiwa277-8582 Japan Department of Physical Sciences Earth and Environment University of Siena via Roma 56 Siena53100 Italy INFN Sezione di Pisa Polo Fibonacci Largo B. Pontecorvo Pisa3-56127 Italy Department of Physics McDonnell Center for the Space Sciences Washington University One Brookings Drive St. LouisMO63130-4899 United States Heliospheric Physics Laboratory NASA GSFC GreenbeltMD20771 United States Center for Space Sciences and Technology University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States Astroparticle Physics Laboratory NASA GSFC GreenbeltMD20771 United States Center for Research and Exploration in Space Sciences and Technology NASA GSFC GreenbeltMD20771 United States Via Madonna del Piano 10 Sesto Fiorentino50019 Italy Department of Physics and Astronomy Louisiana State University 202 Nicholson Hall Baton RougeLA70803 United States Department of Physics and Astronomy University of Padova Via Marzolo 8 Padova35131 Italy INFN Sezione di Padova Via Marzolo 8 Padova35131 Italy Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo Kanagawa Sagamihara252-5210 Japan Kanagawa University 3-27-1 Rokkakubashi Kanagawa Yokohama Kanagawa221-8686 Japan Faculty of Science and Technology Graduate School of Science and Technology Hirosaki University 3 Bunkyo Hirosaki Aomori036-8561 Japan Yukawa Institute for Theoretical Physics Kyoto

The Calorimetric Electron Telescope (CALET), in operation on the International Space Station since 2015, collected a large sample of cosmic-ray iron over a wide energy interval. In this Letter a measurement of the iron spectrum is presented in the range of kinetic energy per nucleon from 10 GeV/n to 2.0 TeV/n allowing the inclusion of iron in the list of elements studied with unprecedented precision by space-borne instruments. The measurement is based on observations carried out from January 2016 to May 2020. The CALET instrument can identify individual nuclear species via a measurement of their electric charge with a dynamic range extending far beyond iron (up to atomic number Z = 40). The energy is measured by a homogeneous calorimeter with a total equivalent thickness of 1.2 proton interaction lengths preceded by a thin (3 radiation lengths) imaging section providing tracking and energy sampling. The analysis of the data and the detailed assessment of systematic uncertainties are described and results are compared with the findings of previous experiments. The observed differential spectrum is consistent within the errors with previous experiments. In the region from 50 GeV/n to 2 TeV/n our present data are compatible with a single power law with spectral index −2.60 ± 0.03. Copyright © 2021, The Authors. All rights reserved.

关键词： Iron

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Estimating Ecosystem Evaporation and Transpiration Using Soil Moisture Coupled Two-Source Energy Balance Model Across Fluxnet Sites

SSRN

引用

SSRN 2022年

作者： Xue, Kejia Song, Lisheng Xu, Yanhao Liu, Shaomin Zhao, Genle Tao, Sinuo Magliulo, Enzo Manco, Antonio Liddell, Michael Wohlfahrt, Georg Varlagin, Andrej Montagnani, Leonardo Woodgate, William Loubet, Benjamin Zhao, Long Anhui Province Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin School of Geography and Tourism Anhui Normal University Jinfo Mountain Chongqing241002 China Karst Ecosystem National Observation and Research Station School of Geographical Sciences Southwest University Chongqing400715 China State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical Sciences Beijing Normal University Beijing100875 China Institute for Agricultural and Forestry Systems in the Mediterranean National Research Council of Italy CNR-ISAFOM Piazzale Enrico Fermi 1 NA Portici Italy Centre for Tropical Environmental and Sustainability Science College of Science and Engineering James Cook University CairnsQLD4878 Australia Department of Ecology University of Innsbruck Sternwartestr. 15 Innsbruck6020 Austria A.N. Severtsov Institute of Ecology and Evolution Russian Academy of Sciences Leninsky pr.33 Moscow119071 Russia Forest Services Autonomous Province of Bolzano Bolzano Italy Faculty of Science and Technology Free University of Bozen-Bolzano Piazza Università Bolzano Italy Remote Sensing Research Centre School of Earth and Environmental Sciences The University of Queensland BrisbaneQLD4072 Australia Université Paris-Saclay UMR ECOSYS INRAE AgroParisTech Thiverval-Grignon78850 France

The two-source energy balance model coupled with soil moisture (TSEB-SM) was evaluated against observations from a global set of 57 sites, part of the FLUXNET2015 dataset. In addition, modeled soil evaporation (E) and transpiration (T) were compared with the values obtained from the Transpiration Estimation Algorithm (TEA) and underlying water use efficiency (uWUE) approaches. The TSEB-SM model framework using near-surface soil moisture improved the agreement between observed and modeled surface heat fluxes, reducing mean absolute percentage error (MAPE) by 30%-50% and root mean square error (RMSE) by about 100 W/m 2 across nearly all sites. The results show that the advantage of the TSEB-SM model, with respect to the original TSEB, becomes more evident as the ratio of actual to potential evapotranspiration (AET/PET) decreases. The E and T produced by TSEB-SM has better correlation with uWUE especially under low soil water content condition. Likewise, TSEB-SM is superior to TSEB in simulating T when compared with sap flow measurements derived from the SAPFLUXNET database. Overall, the patterns of surface heat flux and daily ET estimated by the TSEB-SM model are plausible. This implies that the initial application of the TSEB-SM has made significant advances in modeling surface water fluxes, even though uncertainties remain. The approach used in TSEB-SM provides valuable information on water use by driving the model with a parametric alternative to the complex interactions of ecosystems used in Global Climate Model. This provides a unique insight into the flow of energy and the role of surface fluxes in the global water cycle. © 2022, The Authors. All rights reserved.

关键词： Evapotranspiration

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Relationship analysis between puzzle-like programming game and achievement result after learning the basic of programming

Relationship analysis between puzzle-like programming game a...

引用

2018 International MultiConference of Engineers and Computer Scientists, IMECS 2018

作者： Matsumoto, Shimpei Yamagishi, Shuichi Kashima, Tomoko Department of Information Systems and Management Faculty of Applied Information Science Hiroshima Institute of Technology Graduate School of Engineering 2-1-1 Miyake Saeki-ku Hi-roshima731-5193 Japan Department of Information and Systems Engineering Faculty of Engineering Kindai University 1 Takaya Umenobe Higashi-Hiroshima City Hiroshima739-2116 Japan

ISBN: (纸本)9789881404886

Japan Electronics and Information technology Industries Association develops a puzzle-like programming game “Algologic” aiming to experience the concept of an algorithm for inexperienced programming learners. This is simple puzzle game aiming at solving a problem by automatically controlling a robot. The user designs an autonomous robot by selecting some of the instruction blocks, arranging the blocks in an appropriate order, and giving them to the robot. Before university students learn the basic of programming, with this programming puzzle game, we conducted a test to determine whether algorithms each student gave to the robot were correct or not. Likewise, after students have learned the basic of programming, we conducted a comprehension test to clarify the reachability. In this paper, we aim to investigate the relation between the comprehension of Algologic and the achievement degree of students after learning of programming and report the analysis result. Analysis results revealed that the results of Algologic test and the achievement results after learning programming were significantly in a positive relationship. © 2018 Newswood Limited. All rights reserved.

关键词： Robot programming

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AGlobal benchmark of algorithms for segmentinglate gadolinium-enhanced cardiac magnetic resonance imaging

arXiv

引用

arXiv 2020年

作者： Xiong, Zhaohan Xia, Qing Hu, Zhiqiang Huang, Ning Bian, Cheng Zheng, Yefeng Vesal, Sulaiman Ravikumar, Nishant Maier, Andreas Yang, Xin Heng, Pheng-Ann Ni, Dong Li, Caizi Tong, Qianqian Si, Weixin Puybareau, Elodie Khoudli, Younes Géraud, Thierry Chen, Chen Bai, Wenjia Rueckert, Daniel Xu, Lingchao Zhuang, Xiahai Luo, Xinzhe Jia, Shuman Sermesant, Maxime Liu, Yashu Wang, Kuanquan Borra, Davide Masci, Alessandro Corsi, Cristiana De Vente, Coen Veta, Mitko Karim, Rashed Preetha, Chandrakanth Jayachandran Engelhardt, Sandy Qiao, Menyun Wang, Yuanyuan Tao, Qian Nuñez-Garcia, Marta Camara, Oscar Savioli, Nicolo Lamata, Pablo Zhao, Jichao Auckland Bioengineering Institute University of Auckland Auckland New Zealand State Key Lab of Virtual Reality Technology and Systems Beihang University Beijing China School of Electronics Engineering and Computer Science Peking University Beijing China SenseTime Inc Shenzhen China Tencent Jarvis Laboratory Shenzhen China Pattern Recognition Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Shenzhen University Shenzhen China School of Computer Science Wuhan University Wuhan China Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Epita Research and Development Laboratory Paris France Department of Computing Imperial College London London United Kingdom School of Naval Architecture Shanghai Jiao Tong University Ocean & Civil Engineering Shanghai China School of Data Science Fudan University Shanghai China Epione Research Group Universite Cote d'Azur Inria Sophia Antipolis France Harbin Institute of Technology School of Computer Science and Technology Harbin China Department of Electric University of Bologna Electronic and Information Engineering Cesena Italy Department of Biomedical Engineering Eindhoven University of Technology Eindhoven Netherlands School of Biomedical Engineering and Imaging Sciences Kings College London London United Kingdom Faculty of Electrical Engineering and Information Technology University of Magdeburg Magdeburg Germany Heidelberg University Hospital Germany Biomedical Engineering Center Fudan University Shanghai China Department of Radiology Leiden University Medical Center Leiden Netherlands Department of Information and Communication Technologies Universitat Pompeu Fabra Barcelona Spain D

Segmentation of cardiac images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI)widely used for visualizing diseased cardiacstructures, is a crucial first step for clinical diagnosis and treatment. However, direct segmentation ofLGE-MRIsischallenging due to *** most clinical studies have relied on manual and labor-intensive approaches, automatic methods are of high interest, particularly optimized machine learning *** address this, we organized the "2018 Left Atrium Segmentation Challenge" using 154 3D LGE-MRIs, currently the world's largest cardiac LGE-MRI dataset, and associated labels of the left atriumsegmented by three medical experts,ultimately attractingthe participation of27 international teams. In this paper, extensive analysis of the submitted algorithms using technical and biological metrics was performed by undergoing subgroup analysis and conducting hyper-parameter analysis,offeringan overall picture ofthe major design choices of convolutional neural networks(CNNs) and practical considerations for achieving state-of-the-art left atrium segmentation. Results show the top methodachieved a dice score of 93.2%and a mean surface to a surface distance of 0.7mm, significantly outperforming prior state-of-the-art. Particularly, our analysisdemonstrated that double, sequentially usedCNNs, in which a first CNN is used for automatic region-of-interestlocalization and a subsequent CNN is used for refinedregional segmentation, achieved far superiorresults than traditional methods and pipelinescontaining *** findings from this study can potentially be extended to other imaging datasets and modalities, having an impact on the wider medical imaging *** large-scale benchmarking study makes a significant step towards much-improved segmentation methods for cardiac LGE-MRIs, and will serveas animportant benchmark for evaluating and comparing the future works in the field. Copyright © 2020, Th

关键词： Magnetic resonance imaging

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Assembly of Dynamic Supramolecular Polymers on a DNA Origami Platform

引用

Angewandte Chemie 2021年第14期133卷

作者： Dr. Jurgen Schill Dr. Bas J. H. M. Rosier Dr. Berta Gumí Audenis Dr. Eva Magdalena Estirado Prof. Dr. Tom F. A. de Greef Prof. Dr. Luc Brunsveld Institute for Complex Molecular Systems Eindhoven University of Technology P.O. Box 513 5600 MB Eindhoven The Netherlands Laboratory of Chemical Biology Department of Biomedical Engineering Eindhoven University of Technology The Netherlands Laboratory of Self-Organising Soft Matter and Laboratory of Macromolecular and Organic Chemistry Department of Chemical Engineering and Chemistry Eindhoven University of Technology The Netherlands Computational Biology group Department of Biomedical Engineering Eindhoven University of Technology The Netherlands Institute for Molecules and Materials Faculty of Science Radboud University Heyendaalseweg 135 6525 AJ Nijmegen The Netherlands

Biological processes rely on transient interactions that govern assembly of biomolecules into higher order, multi-component systems. A synthetic platform for the dynamic assembly of multicomponent complexes would provide novel entries to study and modulate the assembly of artificial systems into higher order topologies. Here, we establish a hybrid DNA origami-based approach as an assembly platform that enables dynamic templating of supramolecular architectures. It entails the site-selective recruitment of supramolecular polymers to the platform with preservation of the intrinsic dynamics and reversibility of the assembly process. The composition of the supramolecular assembly on the platform can be tuned dynamically, allowing for monomer rearrangement and inclusion of molecular cargo. This work should aid the study of supramolecular structures in their native environment in real-time and incites new strategies for controlled multicomponent self-assembly of synthetic building blocks.

关键词： multicomponent assembly polymers self-assembly supramolecular synthesis

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Roadmap for Optical Tweezers

arXiv

引用

arXiv 2022年

作者： Volpe, Giovanni Maragò, Onofrio M. Rubinzstein-Dunlop, Halina Pesce, Giuseppe Stilgoe, Alexander B. Volpe, Giorgio Tkachenko, Georgiy Truong, Viet Giang Chormaic, Síle Nic Kalantarifard, Fatemeh Elahi, Parviz Käll, Mikael Callegari, Agnese Marqués, Manuel I. Neves, Antonio A.R. Moreira, Wendel L. Fontes, Adriana Cesar, Carlos L. Saija, Rosalba Saidi, Abir Beck, Paul Eismann, Jörg S. Banzer, Peter Fernandes, Thales F.D. Pedaci, Francesco Bowen, Warwick P. Vaippully, Rahul Lokesh, Muruga Roy, Basudev Thalhammer, Gregor Ritsch-Marte, Monika García, Laura Pérez Arzola, Alejandro V. Castillo, Isaac Pérez Argun, Aykut Muenker, Till M. Vos, Bart E. Betz, Timo Cristiani, Ilaria Minzioni, Paolo Reece, Peter J. Wang, Fan McGloin, David Ndukaife, Justus C. Quidant, Romain Roberts, Reece P. Laplane, Cyril Volz, Thomas Gordon, Reuven Hanstorp, Dag Marmolejo, Javier Tello Bruce, Graham D. Dholakia, Kishan Li, Tongcang Brzobohatý, Oto Simpson, Stephen H. Zemánek, Pavel Ritort, Felix Roichman, Yael Bobkova, Valeriia Wittkowski, Raphael Denz, Cornelia Kumar, G.V. Pavan Foti, Antonino Donato, Maria Grazia Gucciardi, Pietro G. Gardini, L. Bianchi, G. Kashchuk, A. Capitanio, M. Paterson, Lynn Jones, P.H. Berg-Sørensen, Kirstine Barooji, Younes F. Oddershede, Lene B. Pouladian, Pegah Preece, Daryl Adiels, Caroline Beck De Luca, Anna Chiara Magazzù, A. Ciriza, D. Bronte Iatì, M.A. Swartzlander, Grover A. Department of Physics University of Gothenburg Gothenburg41296 Sweden CNR IPCF Istituto per i Processi Chimico-Fisici Messina Italy ARC CoE for Engineered Quantum Systems School of Mathematics and Physics The University of Queensland Australia Department of Chemistry University College London 20 Gordon Street LondonWC1H 0AJ United Kingdom Dipartimento di Fisica Università degli studi di Napoli Federico II Italy Okinawa Institute of Science and Technology Graduate University Japan Department of Health Technology Technical University of Denmark Lyngby Denmark Physics Department Boğaziçi University Istanbul Turkey Chalmers University of Technology Gothenburg Sweden Departamento de Física de Materiales IFIMAC Instituto Nicolás Cabrera Universidad Autónoma de Madrid Spain Santo André São Paulo Brazil Tratamento de dados geofísicos Tecnologia e processamento de geologia e geofísica Exploração Petrobras - Petróleo Brasileiro S.A. Rio de Janeiro Rio de Janeiro Brazil Pernambuco Recife Brazil Ceará Fortaleza Brazil Campinas São Paulo Brazil Dipartimento di Scienze Matematiche e Informatiche Scienze Fisiche e Scienze della Terra Università di Messina Italy Institute of Optics Information and Photonics University Erlangen-Nuremberg Staudtstr. 7/B2 ErlangenD-91058 Germany Max Planck Institute for the Science of Light Staudtstr. 2 ErlangenD-91058 Germany Institute of Physics University of Graz NAWI Graz Universitätsplatz 5 Graz8010 Austria Centre de Biologie Structurale CNRS INSERM Univ.Montpellier France Indian Institute of Technology Madras India Institute for Biomedical Physics Medical University of Innsbruck Austria Instituto de Física Universidad Nacional Autónoma de México Ciudad de MéxicoC. P. 04510 Mexico Departamento de Física Universidad Autónoma Metropolitana-Iztapalapa San Rafael Atlixco 186 Ciudad de México09340 Mexico Third Institute of Physics - Biophysics Georg August University Göttingen Germany Department of Electrical

Optical tweezers are tools made of light that enable contactless pushing, trapping, and manipulation of objects ranging from atoms to space light sails. Since the pioneering work by Arthur Ashkin in the 1970s, optical tweezers have evolved into sophisticated instruments and have been employed in a broad range of applications in life sciences, physics, and engineering. These include accurate force and torque measurement at the femtonewton level, microrheology of complex fluids, single micro- and nanoparticle spectroscopy, single-cell analysis, and statistical-physics experiments. This roadmap provides insights into current investigations involving optical forces and optical tweezers from their theoretical foundations to designs and setups. It also offers perspectives for applications to a wide range of research fields, from biophysics to space exploration. Copyright © 2022, The Authors. All rights reserved.

关键词： Optical tweezers

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Label-free chemical imaging flow cytometry by high-speed multicolor stimulated Raman scattering

引用

PROCEEDINGS OF THE NATIONAL ACADEMY OF scienceS OF THE UNITED STATES OF AMERICA 2019年第32期116卷 15842-15848页

作者： Suzuki, Yuta Kobayashi, Koya Wakisaka, Yoshifumi Deng, Dinghuan Tanaka, Shunji Huang, Chun-Jung Lei, Cheng Sun, Chia-Wei Liu, Hanqin Fujiwaki, Yasuhiro Lee, Sangwook Isozaki, Akihiro Kasai, Yusuke Hayakawa, Takeshi Sakuma, Shinya Arai, Fumihito Koizumi, Kenichi Tezuka, Hiroshi Inaba, Mary Hiraki, Kei Ito, Takuro Hase, Misa Matsusaka, Satoshi Shiba, Kiyotaka Suga, Kanako Nishikawa, Masako Jona, Masahiro Yatomi, Yutaka Yalikun, Yaxiaer Tanaka, Yo Sugimura, Takeaki Nitta, Nao Goda, Keisuke Ozeki, Yasuyuki Department of Electrical Engineering and Information Systems The University of Tokyo 113-8656 Tokyo Japan. Department of Chemistry The University of Tokyo 113-0033 Tokyo Japan. Department of Photonics National Chiao Tung University 300 Hsinchu Taiwan. Institute of Technological Sciences Wuhan University 430072 Wuhan China. Department of Micro-Nano Mechanical Science and Engineering Nagoya University 464-8601 Nagoya Japan. Department of Precision Mechanics Chuo University 112-8551 Tokyo Japan. Department of Creative Informatics The University of Tokyo 113-0033 Tokyo Japan. Japan Science and Technology Agency 332-0012 Saitama Japan. Department of Gastroenterology Cancer Institute Hospital Japanese Foundation for Cancer Research 135-8550 Tokyo Japan. Clinical Research and Regional Innovation Faculty of Medicine University of Tsukuba 305-8575 Ibaraki Japan. Division of Protein Engineering Cancer Institute Japanese Foundation for Cancer Research 135-8550 Tokyo Japan. Department of Clinical Laboratory Medicine Graduate School of Medicine The University of Tokyo 113-0033 Tokyo Japan. Center for Biosystems Dynamics Research RIKEN 565-0871 Osaka Japan. Department of Bioengineering University of California Los Angeles CA 90095. Department of Electrical Engineering and Information Systems The University of Tokyo 113-8656 Tokyo Japan ozeki@ee.t.u-tokyo.ac.jp.

Combining the strength of flow cytometry with fluorescence imaging and digital image analysis, imaging flow cytometry is a powerful tool in diverse fields including cancer biology, immunology, drug discovery, microbiology, and metabolic engineering. It enables measurements and statistical analyses of chemical, structural, and morphological phenotypes of numerous living cells to provide systematic insights into biological processes. However, its utility is constrained by its requirement of fluorescent labeling for phenotyping. Here we present label-free chemical imaging flow cytometry to overcome the issue. It builds on a pulse pair-resolved wavelength-switchable Stokes laser for the fastest-to-date multicolor stimulated Raman scattering (SRS) microscopy of fast flowing cells on a 3D acoustic focusing microfluidic chip, enabling an unprecedented throughput of up to similar to 140 cells/s. To show its broad utility, we use the SRS imaging flow cytometry with the aid of deep learning to study the metabolic heterogeneity of microalgal cells and perform marker-free cancer detection in blood.

关键词： imaging flow cytometry stimulated Raman scattering metabolite imaging microalgae cancer cells

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