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arXiv 2019年

作者： Yang, Ki Youl Skarda, Jinhie Cotrufo, Michele Dutt, Avik Ahn, Geun Ho Vercruysse, Dries Fan, Shanhui Alù, Andrea Vucković, Jelena E. L. Ginzton Laboratory Stanford University StanfordCA94305 United States Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States Department of Electrical Engineering City University of New York New YorkNY10031 United States

Nonreciprocal devices such as isolators and circulators are key enabling technologies for communication systems, both at microwave and optical frequencies. While nonreciprocal devices based on magnetic effects are available for free-space and fibre-optic communication systems, their on-chip integration has been challenging, primarily due to the concomitant high insertion loss, weak magneto-optical effects, and material incompatibility. We show that Kerr nonlinear resonators can be used to achieve all-passive, low-loss, bias-free, broadband nonreciprocal transmission and routing for applications in photonic systems such as chip-scale LIDAR. A multi-port nonlinear Fano resonator is used as an on-chip, all-optical router for frequency comb based distance measurement. Since time-reversal symmetry imposes stringent limitations on the operating power range and transmission of a single nonlinear resonator, we implement a cascaded Fano-Lorentzian resonator system that overcomes these limitations and significantly improves the insertion loss, bandwidth and non-reciprocal power range of current state-of-the-art devices. This work provides a platform-independent design for nonreciprocal transmission and routing that are ideally suited for photonic integration. Copyright © 2019, The Authors. All rights reserved.

关键词： Insertion losses

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Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning

arXiv

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arXiv 2021年

作者： Hering, Alessa Hansen, Lasse Mok, Tony C.W. Chung, Albert C.S. Siebert, Hanna Häger, Stephanie Lange, Annkristin Kuckertz, Sven Heldmann, Stefan Shao, Wei Vesal, Sulaiman Rusu, Mirabela Sonn, Geoffrey Estienne, Théo Vakalopoulou, Maria Han, Luyi Huang, Yunzhi Yap, Pew-Thian Brudfors, Mikael Balbastre, Yaël Joutard, Samuel Modat, Marc Lifshitz, Gal Raviv, Dan Lv, Jinxin Li, Qiang Jaouen, Vincent Visvikis, Dimitris Fourcade, Constance Rubeaux, Mathieu Pan, Wentao Xu, Zhe Jian, Bailiang De Benetti, Francesca Wodzinski, Marek Gunnarsson, Niklas Sjölund, Jens Grzech, Daniel Qiu, Huaqi Li, Zeju Thorley, Alexander Duan, Jinming Großbröhmer, Christoph Hoopes, Andrew Reinertsen, Ingerid Xiao, Yiming Landman, Bennett Huo, Yuankai Murphy, Keelin Lessmann, Nikolas van Ginneken, Bram Dalca, Adrian V. Heinrich, Mattias P. Institute of Medical Informatics Universität zu Lübeck Ratzeburger Allee 160 Lübeck23562 Germany Fraunhofer MEVIS Institute for Digital Medicine Lübeck23562 Germany Department of Radiology and Nuclear Medicine Radboud University Medical Center GA Nijmegen6525 Netherlands The Institute of Medical Informatics Universität zu Lübeck Lübeck23562 Germany The Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong The Fraunhofer MEVIS Institute for Digital Medicine Lübeck23562 Germany The Department of Radiology Stanford University StanfordCA94305 United States The Department of Urology Stanford University StanfordCA94305 United States The Université Paris-Saclay CentraleSupélec Mathématiques et Informatique pour la Complexité et les Systèmes Inria Saclay Gif-sur-Yvette 91190 France Université Paris-Saclay Institut Gustave Roussy Inserm Radiothérapie Moléculaire et Innovation Thérapeutique Villejuif94800 France The Université Paris-Saclay CentraleSupélec Mathématiques et Informatique pour la Complexité et les Systèmes Inria Saclay Gif-sur-Yvette91190 France The Department of Radiology and Nuclear Medicine Radboud University Medical Center Nijmegen6525 GA Netherlands The School of Automation Nanjing University of Information Science and Technology Nanjing210044 China The School of Biomedical Engineering and Imaging Sciences King’s College London London United Kingdom The Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital United States Harvard Medical School Boston United States The King’s College London United Kingdom The Tel Aviv University The Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology Hubei Wuhan430074 China MoE Key Laboratory for Biomedical Photonics Collaborative Innovation Center for Biomedical Engineering School of Engineering Sciences Huazhong University of Sci

Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. However, only a few studies have comprehensively compared medical image registration approaches on a wide range of clinically relevant tasks. This limits the development of registration methods, the adoption of research advances into practice, and a fair benchmark across competing approaches. The Learn2Reg challenge addresses these limitations by providing a multi-task medical image registration data set for comprehensive characterisation of deformable registration algorithms. A continuous evaluation will be possible at https://***. Learn2Reg covers a wide range of anatomies (brain, abdomen, and thorax), modalities (ultrasound, CT, MR), availability of annotations, as well as intra- and inter-patient registration evaluation. We established an easily accessible framework for training and validation of 3D registration methods, which enabled the compilation of results of over 65 individual method submissions from more than 20 unique teams. We used a complementary set of metrics, including robustness, accuracy, plausibility, and runtime, enabling unique insight into the current state-of-the-art of medical image registration. This paper describes datasets, tasks, evaluation methods and results of the challenge, as well as results of further analysis of transferability to new datasets, the importance of label supervision, and resulting bias. While no single approach worked best across all tasks, many methodological aspects could be identified that push the performance of medical image registration to new state-of-the-art performance. Furthermore, we demystified the common belief that conventional registration methods have to be much slower than deep-learning-based methods. © 2021, CC BY.

关键词： Image registration

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Identification of gene expression signatures for psoriasis classification using machine learning techniques

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Medicine in Omics 2021年 1卷

作者： Nguyen Quoc Khanh Le Duyen Thi Do Trinh-Trung-Duong Nguyen Ngan Thi Kim Nguyen Truong Nguyen Khanh Hung Nguyen Thi Thu Trang Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei City 106 Taiwan Research Center for Artificial Intelligence in Medicine Taipei Medical University Taipei City 106 Taiwan Graduate Institute of Biomedical Informatics Taipei Medical University Taipei City 106 Taiwan Department of Computer Science and Engineering Yuan Ze University Chung-Li 32003 Taiwan School of Nutrition and Health Sciences Taipei Medical University Taipei City 110 Taiwan International Master/Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei City 110 Taiwan Orthopedic and Trauma Department Cho Ray Hospital Ho Chi Minh City Viet Nam International PhD Program for Cell Therapy and Regeneration Medicine College of Medicine Taipei Medical University Taipei City 110 Taiwan

Psoriasis classification requires the accurate identification of the lesional types for the early and effective diagnosis and it is worth interesting that the normal and psoriasis cell tissues exhibit different gene expression. Therefore, gene expression data is an effective source for psoriasis classification and there is a challenge regarding the selection of suitable gene signatures for its purpose. In this present study, the gene expression-based microarray data were used and 35 expression features linked with psoriasis were utilized to feed into our machine learning model. Overall, the performance of our model based on 35 mentioned-above features surpassed that of other state-of-the-art classifiers with an average accuracy of 98.3%, recall of 98.6%, and precision of 98% in 5-fold cross-validation tests. We also validate our model on two different sets of psoriasis and the performance results are significant. These results have suggested that our 35 expression signatures have been identified as key features for classifying samples between lesion and non-lesion. More specifically, the expression levels of few genes i.e., FABP5 , TGM1 , or BCAR3 are discovered as newly potential biomarkers for psoriasis classification and treatment with high confidence. This study, therefore, could shed light on developing the prediction models for psoriasis classification and treatment using gene expression profiles.

关键词： Psoriasis classification Random forest Gene expression Feature selection Machine learning FABP5 Dermatology

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Author Correction: Africa needs context-relevant evidence to shape its clean energy future

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Nature Energy 2024年 907页

作者： Yacob Mulugetta Lucas Somavilla Croxatto Meron Tesfamichael Abdulmutalib Yussuff Youba Sokona Philipp A. Trotter Samuel Fankhauser Jessica Omukuti Bjarne Steffen Edo Abraham Jean-Paul Adam Mekalia Paulos Aklilu Yohannes Hailu Linus Mofor S. Nadia Ouedraogo Lawrence Agbemabiese Churchill Agutu Florian Egli Abdulrasheed Isah Tobias S. Schmidt Olakunle Alao Wikus Kruger Peter Twesigye Bothwell Batidzirai Getachew Bekele Anteneh G. Dagnachew Ogunlade Davidson Fatima Denton E. Ogheneruona Diemuodeke Gebrekidan Gebresilassie Eshetu Mulualem Gebreslassie Mamadou Goundiam Haruna Kachalla Gujba Adam D. Hawkes Stephanie Hirmer Helen Hoka Mark Howells Daniel Kammen Francis Kemausuor Ismail Khennas Ifeoma Malo Minette Nago Destenie Nock Chukwumerije Okereke Benedict Probst Maria Schmidt Carlos Shenga Mohamed Sokona Jan Christoph Steckel Sebastian Sterl Bernard Tembo Julia Tomei Jim Watson Harald Winkler Department of Science Technology Engineering & Public Policy University College London London UK Responsible Technology Institute Department of Computer Science University of Oxford Oxford UK Groupe de Reflection et d’Initiatives Novatrices Bamako Mali Schumpeter School of Business and Economics University of Wuppertal Wuppertal Germany Smith School of Enterprise and the Environment University of Oxford Oxford UK Institute for Science Innovation and Society (INSIS) University of Oxford Oxford UK Climate Finance and Policy Group ETH Zurich Zurich Switzerland Department of Water Management Delft University of Technology Delft the Netherlands United Nations Economic Commission for Africa Addis Ababa Ethiopia Center for Energy & Environmental Policy University of Delaware Newark DE USA Energy and Technology Policy Group ETH Zurich Zurich Switzerland Kigali Collaborative Research Centre Kigali Rwanda IIPP Institute for Innovation and Public Purpose University College London London UK Institute of Science Technology and Policy ETH Zurich Zurich Switzerland Power Futures Lab Graduate School of Business University of Cape Town Cape Town South Africa African Union Development Agency (AUDA-NEPAD) Midrand Johannesburg South Africa School of Electrical and Computer Engineering Addis Ababa Institute of Technology Addis Ababa Ethiopia PBL Netherlands Environmental Assessment Agency the Hague the Netherlands Utrecht University Utrecht the Netherlands University of Sierra Leone Freetown Sierra Leone United Nations University–Institute for Natural Resources in Africa (UNU–INRA) Accra Ghana Department of Mechanical Engineering University of Port Harcourt Choba Nigeria Institute for Power Electronics and Electrical Drives RWTH Aachen University Aachen Germany Center of Energy Ethiopian Institute of Technology Mekelle University Mekelle Ethiopia Institute of Engineering University Grenoble Alpes Grenoble France GIZ — Africa–EU Energy Partnership (AEEP) Addis

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Metasurfaces: Coherent Perfect Diffraction in Metagratings (Adv. Mater. 36/2020)

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Advanced Materials 2020年第36期32卷

作者： Ziying Zhang Ming Kang Xueqian Zhang Xi Feng Yuehong Xu Xieyu Chen Huifang Zhang Quan Xu Zhen Tian Weili Zhang Alex Krasnok Jiaguang Han Andrea Alù Center for Terahertz Waves College of Precision Instrument and Optoelectronics Engineering Key Laboratory of Optoelectronics Information and Technology Tianjin University Tianjin 300072 P. R. China Department of Electrical and Computer Engineering The University of Texas at Austin Austin TX 78712 USA School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078 USA Photonics Initiative Advanced Science Research Center City University of New York New York NY 10031 USA Physics Program Graduate Center City University of New York New York NY 10016 USA

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Stakeholder Act as an IT and General Compliance Auditor

Stakeholder Act as an IT and General Compliance Auditor

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international Conference on Sustainable Information engineering and Technology (SIET)

作者： Surjandy Erick Fernando Meyliana Raymond Kosala Suhono Harso Supangkat Diani Dwiningrum Merry Marshela Angelica Renita Amalia Information Systems Audit Program Information Systems Department Bina Nusantara University Jakarta Indonesia Information Systems Departement Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9781538674086;9781538674079

Recently, the Indonesian government requires auditors, the need for auditors around 40,000 auditors in 2016, currently has only about 10,800 auditors, however, the lack of the auditors impacting the risk of financial loss for the state. Referring to the problem, this experimental research was conducted. The experiment of the research was conducted two times and the audit topic is a compliance audit in the year 2017 and year 2018. The goal of this research is to know, can the stakeholder act as an IT and general compliance auditor? The experiment was conducted by 8 university students in 2017 and 19 university students in 2018, and the supporting tools of audit activities the university student use the smartphone to capture the object as evidence. The experiment results with descriptive method show university students can act as an auditor and found several pieces of evidence that might cause future impact to the institution.

关键词： Regulation Stakeholders Companies Libraries Finance

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Universal research index: An inclusive metric to quantify scientific research output

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Journal of Academic Librarianship 2023年第3期49卷

作者： Keshavarz-Fathi, Mahsa Yazdanpanah, Niloufar Kolahchi, Sajad Ziaei, Heliya Darmstadt, Gary L. Dorigo, Tommaso Dochy, Filip Levin, Lisa Thongboonkerd, Visith Ogino, Shuji Chen, Wei-Hsin Perc, Matjaz Tremblay, Mark S. Olusanya, Bolajoko O. Rao, Idupulapati M. Hatziargyriou, Nikos Moradi-Lakeh, Maziar Bella, Federico Rosivall, Laszlo Gandomi, Amir H. Sorooshian, Armin Gupta, Manoj Gal, Ciprian Lozano, Andres M. Weaver, Connie Tanzer, Michael Poggi, Alessandro Sepanlou, Sadaf G. Weiskirchen, Ralf Jambrak, Anet Režek Torres, Pedro J. Capanoglu, Esra Barba, Francisco J. Ernest, Chua Kian Jon Sigman, Mariano Pluchino, Stefano Gharehpetian, Gevork B. Fereshtehnejad, Seyed-Mohammad Yang, Muh-Hwa Thomas, Sabu Cai, Wenju Comini, Elisabetta Scolding, Neil J. Myles, Paul S. Nieto, Juan J. Perry, George Sedikides, Constantine Rezaei, Nima School of Medicine Tehran University of Medical Sciences Tehran Iran Universal Scientific Education and Research Network (USERN) Iran Department of Pediatrics Stanford University School of Medicine Stanford CA United States Istituto Nazionale di Fisica Nucleare (INFN) Via Francesco Marzolo Sezione di Padova Italy High Impact Learning Academy Learning and Development Department Brussels Belgium Center for Marine Biodiversity and Conservation Integrative Oceanography Division Scripps Institution of Oceanography University of California San Diego San Diego CA United States Medical Proteomics Unit Office for Research and Development Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA United States Program in MPE Molecular Pathological Epidemiology Department of Pathology Brigham and Women's Hospital and Harvard Medical School Boston MA United States Broad Institute of MIT and Harvard Cambridge MA United States Department of Aeronautics and Astronautics National Cheng Kung University Tainan Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung 407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung 411 Taiwan Faculty of Natural Sciences and Mathematics University of Maribor Maribor Slovenia Department of Medical Research China Medical University Hospital China Medical University Taichung Taiwan Complexity Science Hub Vienna Vienna Austria Alma Mater Europaea Maribor Slovenia Children's Hospital of Eastern Ontario Research Institute Department of Pediatrics University of Ottawa Ottawa ON Canada Centre for Healthy Start Initiative Ikoyi Lagos Nigeria Alliance of Bioversity International International Center for Tropical Agriculture Cali Colombia International Centre of Insect Physiology and Ecology (ICIPE) Nairobi Kenya School of Electrical and Computer Engineering Natio

Scientometrics and bibliometrics, the subfields of library and information science, deal with the quantity and quality of research outputs. Currently, various scientometric indices are being used to quantify and compare research outputs. The most widely known is the h-index. However, this index and its derivatives suffer from dependence on the mere count of a scholar's highly cited publications. To remedy this deficiency, we developed a novel index, the Universal Research Index (UR-Index) (https://***/UR-Index/) by which every single publication has its own impact on the total score. We developed this index by surveying international top 1 % cited scientists in various disciplines and included additional component variables such as publication type, leading role of a scholar, co-author count, and source metrics to this scientometric index. We acknowledge that unconscious biases built into the component variables included in the UR-Index might put research from specific groups at a disadvantage, thus continued efforts to improve equitable scholarly impact in science and academia are encouraged. © 2023 Elsevier Inc.

关键词： Citations CiteScore h-index Impact factor Leading author Research impact Scholarly impact Scholarly output Scientometrics UR-Index USERN

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Low-temperature electron-phonon interaction of quantum emitters in hexagonal boron nitride

arXiv

引用

arXiv 2019年

作者： Grosso, Gabriele Moon, Hyowon Ciccarino, Christopher J. Flick, Johannes Mendelson, Noah Toth, Milos Aharonovich, Igor Narang, Prineha Englund, Dirk R. Advanced Science Research Center City University of New York Photonics Initiative New YorkNY United States Physics Program Graduate Center City University of New York New YorkNY United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA United States School of Mathematical and Physical Sciences University of Technology Sydney UltimoNSW2007 Australia Center for Computational Quantum Physics Flatiron Institute New YorkNY United States

关键词： Electron-phonon interactions

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Generative Adversarial Networks Enable Cross-Modality Super-Resolution in Fluorescence Microscopy

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Microscopy and Microanalysis 2019年第S2期25卷 1228-1229页

作者： Hongda Wang Yair Rivenson Yiyin Jin Zhensong Wei Ronald Gao Harun Günaydın Laurent A. Bentolila Comert Kural Aydogan Ozcan Electrical & Computer Engineering Department University of California Los Angeles Los Angeles USA Bioengineering Department University of California Los Angeles Los Angeles USA California NanoSystems Institute University of California Los Angeles Los Angeles USA Computer Science Department University of California Los Angeles Los Angeles USA Department of Chemistry and Biochemistry University of California Los Angeles Los Angeles USA Department of Physics Ohio State University Columbus USA Biophysics Graduate Program Ohio State University Columbus USA Department of Surgery David Geffen School of Medicine University of California Los Angeles Los Angeles USA.

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Nonlinear Isolators and Circulators Based on Networks of Coupled Resonators 12

Nonlinear Isolators and Circulators Based on Networks of Cou...

引用

12th international Congress on Artificial Materials for Novel Wave Phenomena, METAMATERIALS 2018

作者： Sounas, D.L. Soric, J. Draguanno, G. Alu, A. University of Texas at Austin Department of Electrical and Computer Engineering AustinTX78712 United States Raytheon AndoverMA United States Johns Hopkins University Applied Physics Laboratory LaurelMD United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States Department of Electrical Engineering City College of New York New YorkNY10031 United States

ISBN: (纸本)9781538647028

We present our recent results in the area of nonlinear nonreciprocal devices, including isolators and circulators. We show that the nonlinear isolators based on single Fano resonators are subject to a fundamental trade-off between transmission and isolation intensity range or bandwidth, stemming from time reversal symmetry. We also show how we can overcome this limitation by using multiple nonlinear resonators. Finally, we show that networks with many nonlinear resonators can also be used to realize more advanced devices, such as circulators. © 2018 IEEE.

关键词： Resonators

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