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arXiv 2019年

作者： Dharmavarapu, Raghu Izumi, Ken-Ichi Katayama, Ikufumi Ng, Soon Hock Vongsvivut, Jitraporn Tobin, Mark J. Kuchmizhak, Aleksandr Nishijima, Yoshiaki Bhattacharya, Shanti Juodkazis, Saulius Department of Electrical Engineering Indian Institute of Technology Madras Chennai600036 India Centre for Micro-Photonics Faculty of Science Engineering and Technology Swinburne University of Technology HawthornVIC3122 Australia Melbourne Centre for Nanofabrication ANFF 151 Wellington Road ClaytonVIC3168 Australia Physics Department Yokohama National University 79-5 Tokiwadai Hodogaya-ku Yokohama240-8501 Japan Infrared Microspectroscopy Beamline Australian Synchrotron ClaytonVIC3168 Australia Institute of Automation and Control Processes Far Eastern Branch Russian Academy of Sciences Vladivostok690041 Russia Far Eastern Federal University Vladivostok690090 Russia Department of Electrical and Computer Engineering Graduate School of Engineering Yokohama National University 79-5 Tokiwadai Hodogaya-ku Yokohama240-8501 Japan Institute of Advanced Sciences Yokohama National University 79-5 Tokiwadai Hodogaya-ku Yokohama240-8501 Japan School of Materials and Chemical Technology Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo152-8550 Japan

Metasurfaces are engineered thin surfaces comprising two dimensional (2D) arrays of sub-wavelength spaced and sub-wavelength sized resonators. Metasurfaces can locally manipulate the amplitude, phase and polarization of light with high spatial resolution. In this study, we report numerical and experimental results of a vortex-beam-generating metasurface fabricated specifically for infrared (IR) and terahertz (THz) wavelengths. The designed metasurface consisted of a 2D array of dielectric cross-shaped resonators with spatially varying length, thereby providing desired spatially varying phase shift to the incident light. The metasurface was found to be insensitive to polarization of incident light. The dimensions of the cross-resonators were calculated using rigorous finite difference time domain (FDTD) analysis. The spectral scalability via physical scaling of meta resonators was demonstrated using two vortex generating optical elements operating at 8.8 μm (IR) and 0.78 THz (Terahertz). The vortex beam generated in the mid-IR spectral range was imaged using FTIR imaging miscroscope equipped with a focal plane array (FPA) detector. This design could be used for efficient wavefront shaping as well as various optical imaging applications in mid-IR spectral range, where polarization insensitivity is desired. Copyright © 2019, The Authors. All rights reserved.

关键词： Resonators

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The efficiency improving methods analyzing for the gasoil pump unit

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AIP Conference Proceedings 2019年第1期2141卷

作者： O. A. Lysenko A. V. Simakov M. Y. Chernev 1Department of Electrical Engineering Energy Institute Omsk State Technical University Mira Ave 11 Omsk 644050 Russia 2Department of Electrical Machines and General Electrical Engineering Electromechanical Faculty Omsk State Transport University Marx Ave 35 Omsk 644046 Russia 3Department of Theoretical Electrical Engineering and Electrification of Oil and Gas Industry Faculty of Automation and Computer Science Gubkin Russian State University of Oil and Gas (National Research University) Leninsky Prospekt Moscow 119991 Russia

In this article, the issues of improving the efficiency are considered. The aim of the work is to determine the benefits of using the PMSM-drive for the gasoil pump unit. Firstly, the object of study is selected. Secondly, the pump power consumption is analyzed. Then, energy optimization options are calculated. The method for determining power consumption parameters is a mathematical calculation. As a result, the object power characteristics are built. The pump energy consumption is calculated, the low efficiency of the pumping unit is determined. The efficiency may be increased by using PMSM-drive.

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The ultra-high-energy event KM3-230213A within the global neutrino landscape

arXiv

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arXiv 2025年

作者： Adriani, O. Aiello, S. Albert, A. Alhebsi, A.R. Alshamsi, M. Garre, S. Alves Ambrosone, A. Ameli, F. Andre, M. Aphecetche, L. Ardid, M. Ardid, S. Argüelles, C. Aublin, J. Badaracco, F. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Becherini, Y. Bendahman, M. Gualandi, F. Benfenati Benhassi, M. Bennani, M. Benoit, D.M. Berbee, E. Berti, E. Bertin, V. Betti, P. Biagi, S. Boettcher, M. Bonanno, D. Bottai, S. Bouasla, A.B. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Breuhaus, M. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Clark, R. Cocimano, R. Coelho, J.A.B. Coleiro, A. Condorelli, A. Coniglione, R. Coyle, P. Creusot, A. Cuttone, G. Dallier, R. De Benedittis, A. De Wasseige, G. Decoene, V. Deguire, P. Del Rosso, I. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Drakopoulou, E. Drouhin, D. Ducoin, J.-G. Duverne, P. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. El Mentawi, S. Ellajosyula, V. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gal, T. Méndez, J. García Soto, A. Garcia Oliver, C. Gatius Geißelbrecht, N. Genton, E. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goswami, P. Gozzini, S.R. Gracia, R. Guidi, C. Guillon, B. Gutiérrez, M. Haack, C. van Haren, H. Heijboer, A. Hennig, L. Hernández-Rey, J.J. Idrissi, A. Ibnsalih, W. Idrissi Illuminati, G. Janik, O. Joly, D. de Jong, M. de Jong, P. Jung, B.J. Kalaczyński, P. Kamp, N. Keegans, J. Kikvadze, V. Kistauri, G. Kopper, C. Kouchner, A. Kovalev, Y.Y. Krupa, L. Kueviakoe, V. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. INFN Sezione di Firenze via Sansone 1 Sesto Fiorentino50019 Italy Università di Firenze Dipartimento di Fisica e Astronomia via Sansone 1 Sesto Fiorentino50019 Italy Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France Université de Haute Alsace rue des Frères Lumière Mulhouse68093 Cedex France Khalifa University of Science and Technology Department of Physics PO Box 127788 Abu Dhabi United Arab Emirates Aix Marseille Univ CNRS IN2P3 CPPM Marseille France c/Catedrático José Beltrán 2 Valencia Paterna46980 Spain Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain Subatech IMT Atlantique IN2P3-CNRS Nantes Université 4 rue Alfred Kastler - La Chantrerie BP Nantes20722 44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia46730 Spain Harvard University Department of Physics Laboratory for Particle Physics and Cosmology Lyman Laboratory 17 Oxford St. CambridgeMA02138 United States Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France INFN Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Università di Genova Via Dodecaneso 33 Genova16146 Italy LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava842 48 Slovakia Czech Technical University in Prague Institute of Experimen

On February 13th, 2023, the KM3NeT/ARCA telescope detected a neutrino candidate with an estimated energy in the hundreds of PeVs. In this article, the observation of this ultra-high-energy neutrino is discussed in light of null observations above tens of PeV from the IceCube and Pierre Auger observatories. Performing a joint fit of all experiments under the assumption of an isotropic E−2 flux, the best-fit single-flavour flux normalisation is E2Φ1fν+ν¯ = 7.5 × 10−10 GeVcm−2s−1sr−1 in the 90% energy range of the KM3NeT event. Furthermore, the ultra-high-energy data are then fit together with the IceCube measurements at lower energies, either with a single power law or with a broken power law, allowing for the presence of a new component in the spectrum. The joint fit including non-observations by other experiments in the ultra-high-energy region shows a slight preference for a break in the PeV regime if the "High-Energy Starting Events" sample is included, and no such preference for the other two IceCube samples investigated. A stronger preference for a break appears if only the KM3NeT data is considered in the ultra-high-energy region, though the flux resulting from such a fit would be inconsistent with null observations from IceCube and Pierre Auger. In all cases, the observed tension between KM3NeT and other datasets is of the order of 2.5σ − 3σ, and increased statistics are required to resolve this apparent tension and better characterise the neutrino landscape at ultra-high energies. Copyright © 2025, The Authors. All rights reserved.

关键词： Neutrons

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Peer-to-Peer Interpretability and Communication: Simple Language Design Using Model-Based Systems engineering with Lifecycle-Oriented Strategies and Innovative Practices for Career Readiness

Peer-to-Peer Interpretability and Communication: Simple Lang...

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Frontiers in Education (FIE) Conference

作者： Lena Spiller Etahe Johnson LaKeisha Harris Tiara Cornelius Bede Nnebedum Weiwei Zhu-Stone Theresa Queenan Marea De Koning Willie L. Brown Dinesha Sharma Urban Wiggins Roland Wescott Ibibia Dabipi Lanju Mei Jason Cornelius Enrique M. Jackson Lei Zhang Cynthia Cravens Rasheed Graham Laurence Price-Webb Department of Engineering and Aviation Sciences University of Maryland Eastern Shore Princess Anne Maryland USA Department of Computer Science and Engineering Technology University of Maryland Eastern Shore Princess Anne Maryland USA Dean of Graduate Studies University of Maryland Eastern Shore Princess Anne Maryland USA Department of Mathematics University of Maryland Eastern Shore Princess Anne Maryland USA Director of Career Services University of Maryland Eastern Shore Princess Anne Maryland USA Engineering and Natural Sciences Automation Technology and Mechanical Engineering Tampere University Tampere Finland Vice Provost for Faculty Affairs University of Maryland Eastern Shore Princess Anne Maryland USA Department of Business Management and Accounting University of Maryland Eastern Shore Princess Anne Maryland USA Vice Provost for Decision Science and Visualization University of Maryland Eastern Shore Princess Anne Maryland USA Wallops Flight Facility Goddard Space Flight Center National Aeronautics and Space Administration Wallops Island Virginia USA Marshall Space Flight Center National Aeronautics and Space Administration Huntsville Alabama USA Department of English and Modem Language University of Maryland Eastern Shore Princess Anne Maryland USA Chief Technology Officer Norsou360 Fort Lauderdale Florida USA

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This work in progress examines how outcomes and solutions from peer-to-peer engineering education can propel innovative practices to address gaps in industry requirements and design specifications with simple language. engineering education often grapples with understanding activities and their practical applications, prompting the need for innovative approaches. Peer-to-peer learning emerges as a solution, offering opportunities to apply model-based systems engineering (MBSE) concepts to environmental conditions and delve into relevant industry requirements and design specifications. These learning outcomes encompass the necessity to foster sustainability in innovation processes and collaborative team approaches for analysis. The framework considers functional outcomes, assessing environmental conditions, attributes, and lifecycle relationships while emphasizing innovative approaches. The peer-to-peer learning environment prioritizes engineering and educational outcomes, cultivating a mindset for setting requirement objectives and roadmaps, considering constraints and conditions, and evaluating peer-to-peer findings against established innovative practices. Consequently, implementing strategies to explain life cycle-oriented designed industry requirements can acknowledge norms, expectations, and formalities, ensuring effective functioning within a peer-to-peer learning context. Process communication design standards align with peer-to-peer workplaces' values, promoting learning and performance lifecycle-oriented designation through recommended analysis methodologies. In this study, a multidisciplinary team of STEM learners spanning engineering, aviation, aerospace, business, and non-STEM disciplines designed how relationships are determined by categorizing business and system use cases. By mapping out these relationships, learners gain enhanced insights into industry requirements for career development. The study focuses on developing career strategies for success

关键词： Industries Technological innovation engineering profession Collaboration Peer-to-peer computing Stakeholders engineering education Sustainable development Modeling Hip

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Complex Dynamical Behavior of a Two-Stage Colpitts Oscillator with Magnetically Coupled Inductors

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Journal of Chaos 2014年第1期2014卷

作者： V. Kamdoum Tamba H. B. Fotsin J. Kengne F. Kapche Tagne P. K. Talla Department of Physics Laboratory of Electronics and Signal Processing (LETS) Faculty of Science University of Dschang P.O. Box 67 Dschang *** Department of Telecommunication and Network Engineering IUT-Fotso Victor of Bandjoun University of Dschang P.O. Box 134 Bandjoun *** Department of Electrical Engineering Laboratory of Automation and Applied Computer (LAIA) IUT-Fotso Victor of Bandjoun University of Dschang P.O. Box 134 Bandjoun *** Department of Physics Laboratory of Mechanics and Modelling of Physical Systems (L2MPS) Faculty of Science University of Dschang P.O. Box 67 Dschang ***

A five-dimensional (5D) controlled two-stage Colpitts oscillator is introduced and analyzed. This new electronic oscillator is constructed by considering the well-known two-stage Colpitts oscillator with two further elements (coupled inductors and variable resistor). In contrast to current approaches based on piecewise linear (PWL) model, we propose a smooth mathematical model (with exponential nonlinearity) to investigate the dynamics of the oscillator. Several issues, such as the basic dynamical behaviour, bifurcation diagrams, Lyapunov exponents, and frequency spectra of the oscillator, are investigated theoretically and numerically by varying a single control resistor. It is found that the oscillator moves from the state of fixed point motion to chaos via the usual paths of period-doubling and interior crisis routes as the single control resistor is monitored. Furthermore, an experimental study of controlled Colpitts oscillator is carried out. An appropriate electronic circuit is proposed for the investigations of the complex dynamics behaviour of the system. A very good qualitative agreement is obtained between the theoretical/numerical and experimental results.

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On the Potential Galactic Origin of the Ultra-High-Energy Event KM3-230213A

arXiv

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arXiv 2025年

作者： Adriani, O. Aiello, S. Albert, A. Alhebsi, A.R. Alshamsi, M. Garre, S. Alves Ambrosone, A. Ameli, F. Andre, M. Aphecetche, L. Ardid, M. Ardid, S. Aublin, J. Badaracco, F. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Becherini, Y. Bendahman, M. Gualandi, F. Benfenati Benhassi, M. Bennani, M. Benoit, D.M. Berbee, E. Berti, E. Bertin, V. Betti, P. Biagi, S. Boettcher, M. Bonanno, D. Bottai, S. Bouasla, A.B. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Breuhaus, M. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Clark, R. Cocimano, R. Coelho, J.A.B. Coleiro, A. Condorelli, A. Coniglione, R. Coyle, P. Creusot, A. Cuttone, G. Dallier, R. De Benedittis, A. De Wasseige, G. Decoene, V. Deguire, P. Del Rosso, I. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Drakopoulou, E. Drouhin, D. Ducoin, J.-G. Duverne, P. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. Bojaddaini, I.El. Hedri, S.El. Mentawi, S.El. Ellajosyula, V. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gal, T. Méndez, J. García Soto, A. Garcia Oliver, C. Gatius Geißelbrecht, N. Genton, E. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goswami, P. Gozzini, S.R. Gracia, R. Guidi, C. Guillon, B. Gutiérrez, M. Haack, C. van Haren, H. Heijboer, A. Hennig, L. Hernández-Rey, J.J. Idrissi, A. Ibnsalih, W. Idrissi Illuminati, G. Janik, O. Joly, D. de Jong, M. de Jong, P. Jung, B.J. Kalaczyński, P. Keegans, J. Kikvadze, V. Kistauri, G. Kopper, C. Kouchner, A. Kovalev, Y.Y. Krupa, L. Kueviakoe, V. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. INFN Sezione di Firenze via Sansone 1 Sesto Fiorentino50019 Italy Università di Firenze Dipartimento di Fisica e Astronomia via Sansone 1 Sesto Fiorentino50019 Italy Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France Université de Haute Alsace rue des Frères Lumière Mulhouse68093Cedex France Khalifa University of Science and Technology Department of Physics PO Box 127788 Abu Dhabi United Arab Emirates Aix Marseille Univ CNRS IN2P3 CPPM Marseille France c/Catedrático José Beltrán 2 Valencia Paterna46980 Spain Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain Subatech IMT Atlantique IN2P3 CNRS Nantes Université 4 rue Alfred Kastler - La Chantrerie BP Nantes20722 44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia46730 Spain Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France INFN Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Università di Genova Via Dodecaneso 33 Genova16146 Italy LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava842 48 Slovakia Czech Technical University in Prague Institute of Experimental and Applied Physics Husova 240/5 Prague110 00 Czech Republic Università di Bologna Dipartimento di Fisica e Astronomia v.le C. Berti-Pichat 6/2

The KM3NeT observatory detected the most energetic neutrino candidate ever observed, with an energy between 72 PeV and 2.6 EeV at the 90 % confidence level. The observed neutrino is likely of cosmic origin. In this article, it is investigated if the neutrino could have been produced within the Milky Way. Considering the low fluxes of the Galactic diffuse emission at these energies, the lack of a nearby potential Galactic particle accelerator in the direction of the event and the difficulty to accelerate particles to such high energies in Galactic systems, we conclude that if the event is indeed cosmic, it is most likely of extragalactic origin. Copyright © 2025, The Authors. All rights reserved.

关键词： Neutrons

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On the Potential Cosmogenic Origin of the Ultra-high-energy Event KM3-230213A

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Astrophysical Journal Letters 2025年第2期984卷 L41-L41页

作者： Adriani, O. Aiello, S. Albert, A. Alhebsi, A.R. Alshamsi, M. Alves Garre, S. Ambrosone, A. Ameli, F. Andre, M. Aphecetche, L. Ardid, M. Ardid, S. Argüelles, C. Aublin, J. Badaracco, F. Bailly-Salins, L. Bardacová, Z. Baret, B. Bariego-Quintana, A. Becherini, Y. Bendahman, M. Benfenati Gualandi, F. Benhassi, M. Bennani, M. Benoit, D.M. Berbee, E. Berti, E. Bertin, V. Betti, P. Biagi, S. Boettcher, M. Bonanno, D. Bottai, S. Bouasla, A.B. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzas, H. Bretaudeau, F. Breuhaus, M. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Clark, R. Cocimano, R. Coelho, J.A.B. Coleiro, A. Condorelli, A. Coniglione, R. Coyle, P. Creusot, A. Cuttone, G. Dallier, R. De Benedittis, A. De Wasseige, G. Decoene, V. Deguire, P. Del Rosso, I. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Drakopoulou, E. Drouhin, D. Ducoin, J.-G. Duverne, P. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. El Mentawi, S. Ellajosyula, V. Enzenhöfer, A. Ferrara, G. Filipovic, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geisselbrecht, N. Genton, E. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goswami, P. Gozzini, S.R. Gracia, R. Guidi, C. Guillon, B. Gutiérrez, M. Haack, C. van Haren, H. Heijboer, A. Hennig, L. Hernández-Rey, J.J. Idrissi, A. Idrissi Ibnsalih, W. Illuminati, G. Janik, O. Joly, D. de Jong, M. de Jong, P. Jung, B.J. Kalaczynski, P. Kamp, N. Keegans, J. Kikvadze, V. Kistauri, G. Kopper, C. Kouchner, A. Kovalev, Y.Y. Krupa, L. Kueviakoe, V. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Lamoureux, M. Larosa, G. Lastoria, C. Lazar, J. Lazo, A. Le Stum, S. Lehaut, G. Lemaître, V. Leonora, E. Le INFN Sezione di Firenze via Sansone 1 Sesto Fiorentino 50019 Italy Università di Firenze Dipartimento di Fisica e Astronomia via Sansone 1 Sesto Fiorentino 50019 Italy INFN Sezione di Catania (INFN-CT) Via Santa Sofia 64 Catania 95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 Strasbourg F-67000 France Université de Haute Alsace rue des Frères Lumière Mulhouse 68093 Cedex France Khalifa University of Science and Technology Department of Physics PO Box 127788 Abu Dhabi United Arab Emirates Aix Marseille Univ CNRS IN2P3 CPPM Marseille France IFIC-Instituto de Física Corpuscular CSIC Universitat de València c/Catedrático José Beltrán 2 Paterna Valencia 46980 Spain Università di Napoli 'Federico II' Dip. Scienze Fisiche 'E. Pancini' Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli 80126 Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli 80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma 00185 Italy Universitat Politècnica de Catalunya Laboratori d'Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú 08800 Spain Subatech IMT Atlantique IN2P3 CNRS Nantes Université 4rue Alfred Kastler-La Chantrerie BP *** Nantes France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia 46730 Spain Harvard University Department of Physics Laboratory for Particle Physics and Cosmology Lyman Laboratory 17Oxford St. Cambridge 02138 MA United States Université Paris Cité CNRS Astroparticule et Cosmologie Paris F-75013 France INFN Sezione di Genova Via Dodecaneso 33 Genova 16146 Italy Università di Genova Via Dodecaneso 33 Genova 16146 Italy LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6boulevard Maréchal Juin Caen 14050 France Comenius University in Bratislava Department of Nuclear Physics and Biophysics

On 2023 February 13, the KM3NeT/ARCA telescope observed a track-like event compatible with a ultra-highenergy muon with an estimated energy of 120 PeV, produced by a neutrino with an even higher energy, making it the most energetic neutrino event ever detected. A diffuse cosmogenic component is expected to originate from the interactions of ultra-high-energy cosmic rays with ambient photon and matter fields. The flux level required by the KM3NeT/ARCA event is, however, in tension with the standard cosmogenic neutrino predictions based on the observations collected by the Pierre Auger Observatory and Telescope Array over the last decade of the ultra-highenergy cosmic rays above the ankle (hence from the local Universe, z ≲ 1). We show here that both observations can be reconciled by extending the integration of the equivalent cosmogenic neutrino flux up to a redshift of z_max = 6 and considering either source evolution effects or the presence of a subdominant independent proton component in the ultra-high-energy cosmic-ray flux, thus placing constraints on known cosmic accelerators. © 2025. The Author(s). Published by the American Astronomical Society.

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CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

arXiv

引用

arXiv 2023年

作者： Graham, Simon Vu, Quoc Dang Jahanifar, Mostafa Weigert, Martin Schmidt, Uwe Zhang, Wenhua Zhang, Jun Yang, Sen Xiang, Jinxi Wang, Xiyue Rumberger, Josef Lorenz Baumann, Elias Hirsch, Peter Liu, Lihao Hong, Chenyang Aviles-Rivero, Angelica I. Jain, Ayushi Ahn, Heeyoung Hong, Yiyu Azzuni, Hussam Xu, Min Yaqub, Mohammad Blache, Marie-Claire Piégu, Benoît Vernay, Bertrand Scherr, Tim Böhland, Moritz Löffler, Katharina Li, Jiachen Ying, Weiqin Wang, Chixin Snead, David Raza, Shan E. Ahmed Minhas, Fayyaz Rajpoot, Nasir M. Tissue Image Analytics Centre University of Warwick Coventry United Kingdom Histofy Ltd Birmingham United Kingdom Institute of Bioengineering School of Life Sciences Epfl Lausanne Switzerland Dresden Germany The Department of Computer Science The University of Hong Kong Hong Kong Tencent Ai Lab Shenzhen China College of Biomedical Engineering Sichuan University Chengdu China Department of Precision Instruments Tsinghua University Beijing China College of Computer Science Sichuan University Chengdu China Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association Berlin Germany Humboldt University of Berlin Faculty of Mathematics and Natural Sciences Berlin Germany Charité University Medicine Berlin Germany University of Bern Bern Switzerland Department of Applied Mathematics and Theoretical Physics University of Cambridge United Kingdom Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Softsensor.ai BridgewaterNJ United States PRR.ai TX United States Department of R&d Center Arontier Co. Ltd Seoul Korea Republic of Computer Vision Department Mohamed Bin Zayed University of Artificial Intelligence Abu Dhabi United Arab Emirates Cnrs Ifce Inrae Université de Tours Prc Nouzilly3780 France Institut de Génétique et de Biologie Moléculaire et Cellulaire Illkirch France Centre National de la Recherche Scientifique UMR7104 Illkirch France Institut National de la Santé et de la Recherche Médicale Inserm U1258 Illkirch France Université de Strasbourg Strasbourg France Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Germany School of Software Engineering South China University of Technology Guangzhou China Department of Pathology University Hospitals Coventry Warwickshire Nhs Trust Coventry United Kingdom Division of Biomedical Sciences Warwick Medical School University of Warwick Coventry United Kingdom

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge, named CoNIC, stimulated the development of reproducible algorithms for cellular recognition with real-time result inspection on public leaderboards. We conducted an extensive post-challenge analysis based on the top-performing models using 1,658 whole-slide images of colon tissue. With around 700 million detected nuclei per model, associated features were used for dysplasia grading and survival analysis, where we demonstrated that the challenge's improvement over the previous state-of-the-art led to significant boosts in downstream performance. Our findings also suggest that eosinophils and neutrophils play an important role in the tumour microevironment. We release challenge models and WSI-level results to foster the development of further methods for biomarker discovery. © 2023, CC BY-NC-SA.

关键词： Grading

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Metrics Reloaded: Recommendations for image analysis validation

arXiv

引用

arXiv 2022年

作者： Maier-Hein, Lena Reinke, Annika Godau, Patrick Tizabi, Minu D. Buettner, Florian Christodoulou, Evangelia Glocker, Ben Isensee, Fabian Kleesiek, Jens Kozubek, Michal Reyes, Mauricio Riegler, Michael A. Wiesenfarth, Manuel Emre Kavur, A. Sudre, Carole H. Baumgartner, Michael Eisenmann, Matthias Heckmann-Nötzel, Doreen Rädsch, Tim Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Benis, Arriel Blaschko, Matthew B. Jorge Cardoso, M. Cheplygina, Veronika Cimini, Beth A. Collins, Gary S. Farahani, Keyvan Ferrer, Luciana Galdran, Adrian Ginneken, Bram Van Haase, Robert Hashimoto, Daniel A. Hoffman, Michael M. Huisman, Merel Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kenngott, Hannes Kofler, Florian Kopp-Schneider, Annette Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Petersen, Jens Rajpoot, Nasir Rieke, Nicola Saez-Rodriguez, Julio Sánchez, Clara I. Shetty, Shravya Smeden, Maarten Van Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben Van Varoquaux, Gaël Jäger, Paul F. Heidelberg Division of Intelligent Medical Systems and HI Helmholtz Imaging Germany Faculty of Mathematics and Computer Science and Medical Faculty Heidelberg University Heidelberg Germany NCT Heidelberg a partnership between DKFZ University Medical Center Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Intelligent Medical Systems Germany partner site Frankfurt/Mainz a partnership between DKFZ and UCT Frankfurt-Marburg Germany Heidelberg Goethe University Frankfurt Germany Department of Medicine Goethe University Frankfurt Germany Department of Informatics Frankfurt Cancer Insititute Germany Department of Computing Imperial College London London United Kingdom Heidelberg Division of Medical Image Computing and HI Applied Computer Vision Lab Germany Institute for AI in Medicine University Medicine Essen Essen Germany Centre for Biomedical Image Analysis Faculty of Informatics Masaryk University Brno Czech Republic ARTORG Center for Biomedical Engineering Research University of Bern Bern Switzerland Department of Radiation Oncology University Hospital Bern University of Bern Bern Switzerland Simula Metropolitan Center for Digital Engineering Oslo Norway UiT The Arctic University of Norway Romsø Norway Heidelberg Division of Biostatistics Germany Heidelberg Division of Intelligent Medical Systems Division of Medical Image Computing HI Applied Computer Vision Lab Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Heidelberg Division of Medical Image Computing Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen performance metrics often do not reflect the domain interest, thus failing to adequately measure scientific progress and hindering translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. It was developed by a large international consortium in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint – a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output. Based on the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as a classification task at image, object or pixel level, namely image-level classification, object detection, semantic segmentation, and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases. © 2022, CC BY.

关键词： Semantic Segmentation

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Preface

Lecture Notes in Networks and Systems

引用

Lecture Notes in Networks and Systems 2023年 764 LNNS卷 v-vi页

作者： Milrad, Marcelo Otero, Nuno Sánchez-Gómez, María Cruz Mena, Juan José Durães, Dalila Sciarrone, Filippo Alvarez-Gómez, Claudio Rodrigues, Manuel Vittorini, Pierpaolo Gennari, Rosella Di Mascio, Tania Temperini, Marco De la Prieta, Fernando Linnaeus University Växjö Sweden University of Greenwich London United Kingdom Department of Didactics Organization and Research Method University of Salamanca Salamanca Spain University of Minho Braga Portugal Mercatorum University Rome Italy Facultad de Ingeniería y Ciencias Aplicadas Universidad de los Andes Santiago Chile Department of Life Health and Environmental Sciences University of L’Aquila L’Aquila Italy Faculty of Computer Science Free University of Bozen-Bolzano Bolzano Italy Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Dipartimento di Ingegneria Informatica Sapienza Universita’ di Roma Rome Italy Department of Computer Science and Automation Control University of Salamanca Salamanca Spain

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