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arXiv 2024年

作者： Fraga-Lamas, Paula Lopes, Sérgio Ivan Fernández-Caramés, Tiago M. Dpt. of Computer Engineering Centro de investigación CITIC Faculty of Computer Science Universidade da Coruña A Coruña15071 Spain ADiT-Lab Instituto Politécnico de Viana do Castelo Viana do Castelo4900-348 Portugal CiTin Centro de Interface Tecnológico Industrial Arcos de Valdevez4970-786 Portugal IT—Instituto de Telecomunicações Campus Universitário de Santiago Aveiro3810-193 Portugal

Decentralized Metaverses, built on Web 3.0 and Web 4.0 technologies, have attracted significant attention across various fields. This innovation leverages blockchain, Decentralized Autonomous Organizations (DAOs), Extended Reality (XR) and advanced technologies to create immersive and interconnected digital environments that mirror the real world. This article delves into the Metaverse of Everything (MoE), a platform that fuses the Metaverse concept with the Internet of Everything (IoE), an advanced version of the Internet of Things (IoT) that connects not only physical devices but also people, data and processes within a networked environment. Thus, the MoE integrates generated data and virtual entities, creating an extensive network of interconnected components. This article seeks to advance current MoE, examining decentralization and the application of Opportunistic Edge Computing (OEC) for interactions with surrounding IoT devices and IoE entities. Moreover, it outlines the main challenges to guide researchers and businesses towards building a future cyber-resilient opportunistic MoE. © 2024, CC BY.

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BACH: grand challenge on breast cancer histology images

arXiv

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arXiv 2018年

作者： Aresta, Guilherme Araújo, Teresa Kwok, Scotty Chennamsetty, Sai Saketh Safwan, Mohammed Alex, Varghese Marami, Bahram Prastawa, Marcel Chan, Monica Donovan, Michael Fernandez, Gerardo Zeineh, Jack Kohl, Matthias Walz, Christoph Ludwig, Florian Braunewell, Stefan Baust, Maximilian Vu, Quoc Dang Nhat To, Minh Nguyen Kim, Eal Kwak, Jin Tae Galal, Sameh Sanchez-Freire, Veronica Brancati, Nadia Frucci, Maria Riccio, Daniel Wang, Yaqi Sun, Lingling Ma, Kaiqiang Fang, Jiannan Kone, Ismael Boulmane, Lahsen Campilho, Aurélio Eloy, Catarina Polónia, António Aguiar, Paulo INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal Faculty of Engineering of University of Porto Porto4200-465 Portugal Seek AI Limited Hong Kong Bangalore India Gurgaon India Chennai India Center for Computational and Systems Pathology Dpt. of Pathology Icahn School of Medicine at Mount Sinai Mount Sinai Hospital New York United States Konica Minolta Laboratory Europe Munich Germany Institute of Pathology Faculty of Medicine LMU Munich Munich Germany Department of Computer Science and Engineering Sejong University Seoul05006 Korea Republic of Chicago IL United States Naples Italy University of Naples "Federico II" Naples Italy Key Laboratory of RF Circuits and Systems Ministry of Education Hangzhou Dianzi University Hangzhou310018 China Zhejiang Provincial Laboratory of Integrated Circuits Design Hangzhou Dianzi University Hangzhou310018 China p2MIA Research Group LEM2A Lab Faculté des Sciences Université Moulay Ismail Meknes Morocco qLaboratório de Anatomia Patológica Ipatimup Diagnósticos Rua Júilio Amaral de Carvalho 45 Porto4200-135 Portugal Faculdade de Medicina Universidade do Porto Alameda Prof Hernâni Monteiro Porto4200-319 Portugal Universidade do Porto Rua Alfredo Allen 208 Porto4200-135 Portugal Universidade do Porto Rua Alfredo Allen 208 Porto4200-135 Portugal

Breast cancer is the most common invasive cancer in women, affecting more than 10% of women worldwide. Microscopic analysis of a biopsy remains one of the most important methods to diagnose the type of breast cancer. This requires specialized analysis by pathologists, in a task that i) is highly time- and cost-consuming and ii) often leads to nonconsensual results. The relevance and potential of automatic classification algorithms using hematoxylin-eosin stained histopathological images has already been demonstrated, but the reported results are still sub-optimal for clinical use. With the goal of advancing the state-of-the-art in automatic classification, the Grand Challenge on BreAst Cancer Histology images (BACH) was organized in conjunction with the 15th International Conference on Image Analysis and Recognition (ICIAR 2018). BACH aimed at the classification and localization of clinically relevant histopathological classes in microscopy and whole-slide images from a large annotated dataset, specifically compiled and made publicly available for the challenge. Following a positive response from the scientific community, a total of 64 submissions, out of 677 registrations, effectively entered the competition. The submitted algorithms improved the state-of-the-art in automatic classification of breast cancer with microscopy images to an accuracy of 87%. Convolutional neuronal networks were the most successful methodology in the BACH challenge. Detailed analysis of the collective results allowed the identification of remaining challenges in the field and recommendations for future developments. The BACH dataset remains publicly available as to promote further improvements to the field of automatic classification in digital pathology. Copyright © 2018, The Authors. All rights reserved.

关键词： Neurons

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Horizons: Nuclear Astrophysics in the 2020s and Beyond

arXiv

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arXiv 2022年

作者： Schatz, Hendrik Becerril Reyes, A.D. Best, A. Brown, E.F. Chatziioannou, K. Chipps, K.A. Deibel, C.M. Ezzeddine, R. Galloway, D.K. Hansen, C.J. Herwig, F. Ji, A.P. Lugaro, M. Meisel, Z. Norman, D. Read, J.S. Roberts, L.F. Spyrou, A. Tews, I. Timmes, F.X. Travaglio, C. Vassh, N. Abia, C. Adsley, P. Agarwal, S. Aliotta, M. Aoki, W. Arcones, A. Aryan, A. Bandyopadhyay, A. Banu, A. Bardayan, D.W. Barnes, J. Bauswein, A. Beers, T.C. Bishop, J. Boztepe, T. Côté, B. Caplan, M.E. Champagne, A.E. Clark, J.A. Couder, M. Couture, A. de Mink, S.E. Debnath, S. deBoer, R.J. den Hartogh, J. Denissenkov, P. Dexheimer, V. Dillmann, I. Escher, J.E. Famiano, M.A. Farmer, R. Fisher, R. Fröhlich, C. Frebel, A. Fryer, C. Fuller, G. Ganguly, A.K. Ghosh, S. Gibson, B.K. Gorda, T. Gourgouliatos, K.N. Graber, V. Gupta, M. Haxton, W. Heger, A. Hix, W.R. Ho, W.C.G. Holmbeck, E.M. Hood, A.A. Huth, S. Imbriani, G. Izzard, R.G. Jain, R. Jayatissa, H. Johnston, Z. Kajino, T. Kankainen, A. Kiss, G.G. Kwiatkowski, A. La Cognata, M. Laird, A.M. Lamia, L. Landry, P. Laplace, E. Launey, K.D. Leahy, D. Leckenby, G. Lennarz, A. Longfellow, B. Lovell, A.E. Lynch, W.G. Lyons, S.M. Maeda, K. Masha, E. Matei, C. Merc, J. Messer, B. Montes, F. Mukherjee, A. Mumpower, M. Neto, D. Nevins, B. Newton, W.G. Nguyen, L.Q. Nishikawa, K. Nishimura, N. Nunes, F.M. O’Connor, E. O’Shea, B.W. Ong, W.-J. Pain, S.D. Pajkos, M.A. Pignatari, M. Pizzone, R.G. Placco, V.M. Plewa, T. Pritychenko, B. Psaltis, A. Puentes, D. Qian, Y.-Z. Radice, D. Rapagnani, D. Rebeiro, B.M. Reifarth, R. Richard, A.L. Rijal, N. Roederer, I.U. Rojo, J.S. Sk, J. Saito, Y. Schwenk, A. Sergi, M.L. Sidhu, R.S. Simon, A. Sivarani, T. Skúladóttir, Á. Smith, M.S. Spiridon, A. Sprouse, T.M. Starrfield, S. Steiner, A.W. Strieder, F. Sultana, I. Surman, R. Szücs, T. Tawfik, A. Thielemann, F. Trache, L. Trappitsch, R. Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Facility for Rare Isotope Beams Michigan State University East LansingMI48824 United States United States Department of Physics University of Naples"Federico II" Napoli80126 Italy INFN - Sezione di Napoli Napoli80126 Italy Department of Computational Mathematics Science and Engineering MichiganState University East LansingMI48824 United States Department of Physics California Institute of Technology PasadenaCA91125 United States LIGO Laboratory California Institute of Technology PasadenaCA91125 United States Physics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Physics and Astronomy University of Tennessee Knoxville KnoxvilleTN37996 United States Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States Department of Astronomy University of Florida GainesvilleFL32601 United States School of Physics and Astronomy Monash University VIC3800 Australia OzGRav-Monash School of Physics & Astronomy Monash University VIC3800 Australia Goethe University Frankfurt Institute for Applied Physics Max-von-Laue-Str. 12 Frankfurt am Main60438 Germany Technical University of Darmstadt Institute for Nuclear Physics Germany Max Planck Institute for Astronomy Heidelberg Germany Department of Physics and Astronomy University of Victoria VictoriaBCV8P 5C2 Canada Department of Astronomy & Astrophysics University of Chicago 5640 S Ellis Avenue ChicagoIL60637 United States Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Excellence Centre of the Hungarian Academy of Sciences Konkoly-Thege Miklós út 15-17 BudapestH-1121 Hungary ELTE Eötvös Loránd University Institute of Physics Pázmány Péter sétány 1/A Budapest1117 Hungary Institute of Nuclear & Particle Physics Department of Physics & Astronomy Ohio University AthensOH45701

Nuclear Astrophysics is a field at the intersection of nuclear physics and astrophysics, which seeks to understand the nuclear engines of astronomical objects and the origin of the chemical elements. This white paper summarizes progress and status of the field, the new open questions that have emerged, and the tremendous scientific opportunities that have opened up with major advances in capabilities across an ever growing number of disciplines and subfields that need to be integrated. We take a holistic view of the field discussing the unique challenges and opportunities in nuclear astrophysics in regards to science, diversity, education, and the interdisciplinarity and breadth of the field. Clearly nuclear astrophysics is a dynamic field with a bright future that is entering a new era of discovery opportunities. © 2022, CC BY-NC-SA.

关键词： Astrophysics

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18th European Symposium on Radiopharmacy and Radiopharmaceuticals Salzburg, Austria. 7-10 April 2016

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EJNMMI RADIOPHARMACY AND CHEMISTRY 2016年第1期1卷 1-37页

作者： [Anonymous] Los Alamos National Laboratory Los Alamos USA Oak Ridge National Laboratory Oak Ridge USA Department of Nuclear Medicine Medical University Innsbruck Innsbruck Austria Department of Radiology & Nuclear Medicine Radboud University Medical Center Nijmegen The Netherlands Institute of Molecular and Translational Medicine Faculty of Medicine and Dentistry Palacky University Olomouc Czech Republic Département de Médecine Nucléaire et Radiobiologie Faculté de Médecine et Sciences de la Santé Université de Sherbrooke Sherbrooke Canada Centre d’Imagerie Moléculaire de Sherbrooke (CIMS) CR-CHUS Sherbrooke Canada Division of Molecular Biology/Biocenter Medical University Innsbruck Innsbruck Austria Department of Nuclear Medicine Radboud University Medical Center Nijmegen The Netherlands IENI-CNR Padua Italy DiSCOG-University of Padua Padua Italy IOV Padua Padua Italy IC-CNR Bari Italy IBB-CNR Naples Italy Laboratory of Radiopharmacy KU Leuven Leuven Belgium Micro Flow Chemistry & Process Technology Chemical Engineering and Chemistry Department TU Eindhoven Eindhoven The Netherlands Laboratory for Radiopharmacy University of Leuven Leuven Belgium Department of Nuclear Medicine and Molecular Imaging University of Leuven Leuven Belgium Department of Medicine and Surgery Tecnomed Foundation University of Milano-Bicocca Milan Italy Dipartimento di Biotecnologie Mediche e Medicina Traslazionale Università degli Studi di Milano Milan Italy Department of Radiology & Nuclear Medicine VU University Medical Center Amsterdam The Netherlands Department of Clinical Pharmacology & Pharmacy VU University Medical Center Amsterdam The Netherlands Université de Lorraine Vandoeuvre les Nancy France NancycloTEP Plateforme d’imagerie expérimentale Vandoeuvre les Nancy France CNRS UMR 7565 SRSMC Vandoeuvre les Nancy France CHU de Nancy-Brabois Vandoeuvre les Nancy France Department of Biomedical Imaging and Image-guided Therapy Division of Nuclear Medicine Medical Univers

Table of contents OP03 Selective extraction of medically-related radionuclides from proton-irradiated thorium targets V. Radchenko, J.W. Engle, C. Roy, J. Griswold, M.F. Nortier, E.R. Birnbaum, M. Brugh, S. Mirzadeh, K. D. John, M.E. Fassbender OP04 Comparison of [68Ga]FSC(succ-RGD)3 and [68Ga]NODAGA-RGD for PET imaging of alpha v beta 3 integrin expression Chuangyan Zhai, Gerben M. Franssen, Milos Petrik, Peter Laverman, Clemens Decristoforo OP05 A new NPY-Y1R targeting peptide for breast cancer PET imaging Ait-Mohand Samia, Dumulon-Perreault Veronique, Guerin Brigitte OP06 The influence of multivalency on CCK 2 receptor targeting D. Summer, A. Kroess, C. Rangger, H. Haas, P. Laverman, F. Gerben, E. von Guggenberg, *** OP07 SPECT Imaging of alpha v beta 3 Expression by [99mTc(N)PNP43]- Bifunctional Chimeric RGD Peptide not Cross-Reacting with alpha v beta 5 Cristina Bolzati, Nicola Salvarese, Fiorenzo Refosco, Laura Melendez-Alafort, Debora Carpanese, Antonio Rosato, Michele Saviano, Annarita Del Gatto, Daniela Comegna, Laura Zaccaro OP09 New dienophiles for the inverse-electron-demand Diels-Alder reaction and for pretargeted PET imaging Emilie Billaud, Muneer Ahamed, Frederik Cleeren, Elnaz Shahbazali, Tim Noel, Volker Hessel, Alfons Verbruggen and Guy Bormans OP10 New complexing agent for Al18F-labelling of heat-sensitive biomolecules: Synthesis and preclinical evaluation of Al18F-RESCA1-HAS Cleeren F, Lecina J, Koole M, Verbruggen A and Bormans G OP11 A novel versatile precursor efficient for F-18 radiolabelling via click-chemistry B. Lugatoa, S. Stucchia, E.A. Turollaa, L. Giulianoa, ***, P. Ferraboschib OP12 A general applicable method to quantify unidentified UV impurities in radiopharmaceuticals R.P. Klok, M.P.J. Mooijer, N.H. Hendrikse, A.D. Windhorst OP13 Development of [F-18]Fluoro-C-glycosides to radiolabel peptides Collet C., Petry N., Chretien F., Karcher G., Pellegrini-Moise N., Lamande-Langle S. OP14 A Microfluidic Approach for the 68

关键词： Positron Emission Tomography Single Photon Emission Compute Tomography Standard Uptake Value Positron Emission Tomography Imaging High Pressure Liquid Chromatography

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