97 research outputs found
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy
The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing
reliable computer aided detection and diagnosis endoscopy systems and suggest a pathway for clinical translation
of technologies. Whilst endoscopy is a widely used diagnostic and treatment tool for hollow-organs, there are several core
challenges often faced by endoscopists, mainly: 1) presence of multi-class artefacts that hinder their visual interpretation, and
2) difficulty in identifying subtle precancerous precursors and cancer abnormalities. Artefacts often affect the robustness of
deep learning methods applied to the gastrointestinal tract organs as they can be confused with tissue of interest. EndoCV2020
challenges are designed to address research questions in these remits. In this paper, we present a summary of methods
developed by the top 17 teams and provide an objective comparison of state-of-the-art methods and methods designed by
the participants for two sub-challenges: i) artefact detection and segmentation (EAD2020), and ii) disease detection and
segmentation (EDD2020). Multi-center, multi-organ, multi-class, and multi-modal clinical endoscopy datasets were compiled
for both EAD2020 and EDD2020 sub-challenges. The out-of-sample generalization ability of detection algorithms was also
evaluated. Whilst most teams focused on accuracy improvements, only a few methods hold credibility for clinical usability. The
best performing teams provided solutions to tackle class imbalance, and variabilities in size, origin, modality and occurrences
by exploring data augmentation, data fusion, and optimal class thresholding techniques
Dependence of atmospheric muon flux on seawater depth measured with the first KM3NeT detection units: The KM3NeT Collaboration
KM3NeT is a research infrastructure located in the Mediterranean Sea, that will consist of two deep-sea Cherenkov neutrino detectors. With one detector (ARCA), the KM3NeT Collaboration aims at identifying and studying TeV–PeV astrophysical neutrino sources. With the other detector (ORCA), the neutrino mass ordering will be determined by studying GeV-scale atmospheric neutrino oscillations. The first KM3NeT detection units were deployed at the Italian and French sites between 2015 and 2017. In this paper, a description of the detector is presented, together with a summary of the procedures used to calibrate the detector in-situ. Finally, the measurement of the atmospheric muon flux between 2232–3386 m seawater depth is obtained
The Control Unit of the KM3NeT Data Acquisition System
The KM3NeT Collaboration runs a multi-site neutrino observatory in the Mediterranean Sea. Water Cherenkov particle detectors, deep in the sea and far off the coasts of France and Italy, are already taking data while incremental construction progresses. Data Acquisition Control software is operating off-shore detectors as well as testing and qualification stations for their components. The software, named Control Unit, is highly modular. It can undergo upgrades and reconfiguration with the acquisition running. Interplay with the central database of the Collaboration is obtained in a way that allows for data taking even if Internet links fail. In order to simplify the management of computing resources in the long term, and to cope with possible hardware failures of one or more computers, the KM3NeT Control Unit software features a custom dynamic resource provisioning and failover technology, which is especially important for ensuring continuity in case of rare transient events in multi-messenger astronomy. The software architecture relies on ubiquitous tools and broadly adopted technologies and has been successfully tested on several operating systems
Probing invisible neutrino decay with KM3NeT-ORCA
In the era of precision measurements of the neutrino oscillation parameters,
upcoming neutrino experiments will also be sensitive to physics beyond the
Standard Model. KM3NeT/ORCA is a neutrino detector optimised for measuring
atmospheric neutrinos from a few GeV to around 100 GeV. In this paper, the
sensitivity of the KM3NeT/ORCA detector to neutrino decay has been explored. A
three-flavour neutrino oscillation scenario, where the third neutrino mass
state decays into an invisible state, e.g. a sterile neutrino, is
considered. We find that KM3NeT/ORCA would be sensitive to invisible neutrino
decays with ~ at confidence
level, assuming true normal ordering. Finally, the impact of neutrino decay on
the precision of KM3NeT/ORCA measurements for ,
and mass ordering have been studied. No significant effect of neutrino decay on
the sensitivity to these measurements has been found.Comment: 27 pages, 14 figures, bibliography updated, typos correcte
Characterisation of the Hamamatsu photomultipliers for the KM3NeT Neutrino Telescope
[EN] The Hamamatsu R12199-02 3-inch photomultiplier tube is the photodetector chosen for the first phase of the KM3NeT neutrino telescope. About 7000 photomultipliers have been characterised for dark count rate, timing spread and spurious pulses. The quantum eÿciency, the gain and the peak-to-valley ratio have also been measured for a sub-sample in order to determine parameter values needed as input to numerical simulations of the detector.The authors acknowledge the financial support of the funding agencies: Agence Nationale de la Recherche (contract ANR-15-CE31-0020), Centre National de la Recherche Scientifique (CNRS), Commission Europeenne (FEDER fund and Marie Curie Program), Institut Universitaire de France (IUF), IdEx program and UnivEarthS Labex program at Sorbonne Paris Cite (ANR-10-LABX-0023 and ANR-11-IDEX-0005-02), France; 'Helmholtz Alliance for Astroparticle Physics' funded by the Initiative and Networking Fund of the Helmholtz Association, Germany; The General Secretariat of Research and Technology (GSRT), Greece; Istituto Nazionale di Fisica Nucleare (INFN), Ministero dell'Istruzione, dell'Universita e della Ricerca (MIUR), Italy; Agence de l'Oriental and CNRST, Morocco; Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO), the Netherlands; National Authority for Scientific Research (ANCS), Romania; Plan Estatal de Investigacion (refs. FPA2015-65150-C3-1-P, -2-P and -3-P, (MINECO/FEDER)), Severo Ochoa Centre of Excellence and MultiDark Consolider (MINECO), and Prometeo and Grisolia programs (Generalitat Valenciana), Spain.Aiello, S.; Akrame, SE.; Ameli, F.; Anassontzis, EG.; Andre, M.; Androulakis, G.; Anghinolfi, M.... (2018). Characterisation of the Hamamatsu photomultipliers for the KM3NeT Neutrino Telescope. Journal of Instrumentation. 13:1-17. https://doi.org/10.1088/1748-0221/13/05/P05035S11713Adrián-Martínez, S., Ageron, M., Aharonian, F., Aiello, S., Albert, A., Ameli, F., … Anghinolfi, M. (2016). Letter of intent for KM3NeT 2.0. Journal of Physics G: Nuclear and Particle Physics, 43(8), 084001. doi:10.1088/0954-3899/43/8/084001Adrián-Martínez, S., Ageron, M., Aharonian, F., Aiello, S., Albert, A., Ameli, F., … Anvar, S. (2014). Deep sea tests of a prototype of the KM3NeT digital optical module. The European Physical Journal C, 74(9). doi:10.1140/epjc/s10052-014-3056-3Adrián-Martínez, S., Ageron, M., Aharonian, F., Aiello, S., Albert, A., Ameli, F., … Anton, G. (2016). The prototype detection unit of the KM3NeT detector. The European Physical Journal C, 76(2). doi:10.1140/epjc/s10052-015-3868-9Herold, B., Kalekin, O., & Reubelt, J. (2011). PMT characterisation for the KM3NeT project. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 639(1), 70-72. doi:10.1016/j.nima.2010.09.018Timmer, P., Heine, E., & Peek, H. (2010). Very low power, high voltage base for a Photo Multiplier Tube for the KM3NeT deep sea neutrino telescope. Journal of Instrumentation, 5(12), C12049-C12049. doi:10.1088/1748-0221/5/12/c12049Mollo, C. M., Bozza, C., Chiarusi, T., Costa, M., Capua, F. D., Kulikovskiy, V., … Vivolo, D. (2016). A new instrument for high statistics measurement of photomultiplier characteristics. Journal of Instrumentation, 11(08), T08002-T08002. doi:10.1088/1748-0221/11/08/t08002Adrián-Martínez, S., Ageron, M., Aiello, S., Albert, A., Ameli, F., Anassontzis, E. G., … Anton, G. (2016). A method to stabilise the performance of negatively fed KM3NeT photomultipliers. Journal of Instrumentation, 11(12), P12014-P12014. doi:10.1088/1748-0221/11/12/p12014Lubsandorzhiev, B. K., Vasiliev, R. V., Vyatchin, Y. E., & Shaibonov, B. A. J. (2006). Photoelectron backscattering in vacuum phototubes. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 567(1), 12-16. doi:10.1016/j.nima.2006.05.04
Implementation and first results of the KM3NeT real-time core-collapse supernova neutrino search
The authors acknowledge the financial support of the funding agencies: Agence Nationale de la Recherche (contract ANR-15-CE31-0020), Centre National de la Recherche Scientifique (CNRS), Commission Europeenne (FEDER fund and Marie Curie Program), Institut Universitaire de France (IUF), LabEx UnivEarthS (ANR-10-LABX-0023 and ANR-18-IDEX-0001), Paris ile-de-France Region, France; Shota Rustaveli National Science Foundation of Georgia (SRNSFG, FR-18-1268), Georgia; Deutsche Forschungsgemeinschaft (DFG), Germany; The General Secretariat of Research and Technology (GSRT), Greece; Istituto Nazionale di Fisica Nucleare (INFN), Ministero dell'Universita e della Ricerca (MIUR), PRIN 2017 program (Grant NAT-NET 2017W4HA7S) Italy; Ministry of Higher Education Scientific Research and Professional Training, ICTP through Grant AF-13, Morocco; Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO), the Netherlands; The National Science Centre, Poland (2015/18/E/ST2/00758); National Authority for Scientific Research (ANCS), Romania; Ministerio de Ciencia, Innovacion, Investigacion y Universidades (MCIU): Programa Estatal de Generacion de Conocimiento (refs. PGC2018-096663-B-C41, -A-C42, -B-C43, -B-C44) (MCIU/FEDER), Generalitat Valenciana: Prometeo (PROMETEO/2020/019), Grisolia (ref. GRISOLIA/2018/119) and GenT (refs. CIDEGENT/2018/034, /2019/043, /2020/049) programs, Junta de Andalucia (ref. A-FQM-053-UGR18), La Caixa Foundation (ref. LCF/BQ/IN17/11620019), EU: MSC program (ref. 101025085), Spain.The KM3NeT research infrastructure is unconstruction
in the Mediterranean Sea. KM3NeT will study
atmospheric and astrophysical neutrinos with two multipurpose
neutrino detectors, ARCA and ORCA, primarily
aimed at GeV–PeV neutrinos. Thanks to the multiphotomultiplier
tube design of the digital optical modules,
KM3NeT is capable of detecting the neutrino burst from
a Galactic or near-Galactic core-collapse supernova. This potential is already exploitable with the first detection units
deployed in the sea. This paper describes the real-time implementation
of the supernova neutrino search, operating on the
two KM3NeT detectors since the first months of 2019. A
quasi-online astronomy analysis is introduced to study the
time profile of the detected neutrinos for especially significant
events. Themechanism of generation and distribution of
alerts, aswell as the integration into theSNEWSandSNEWS
2.0 global alert systems, are described. The approach for the
follow-up of external alerts with a search for a neutrino excess
in the archival data is defined. Finally, an overviewof the current
detector capabilities and a report after the first two years
of operation are given.French National Research Agency (ANR)European Commission ANR-15-CE31-0020Centre National de la Recherche Scientifique (CNRS)Commission EuropeenneInstitut Universitaire de France (IUF)LabEx UnivEarthS ANR-10-LABX-0023
ANR-18-IDEX-0001Shota Rustaveli National Science Foundation of Georgia (SRNSFG), Georgia FR-18-1268German Research Foundation (DFG)Greek Ministry of Development-GSRTIstituto Nazionale di Fisica Nucleare (INFN)Ministry of Education, Universities and Research (MIUR)PRIN 2017 program, Italy NAT-NET 2017W4HA7SMinistry of Higher Education Scientific Research and Professional Training, ICTP, Morocco AF-13Netherlands Organization for Scientific Research (NWO)
Netherlands GovernmentNational Science Centre, Poland 2015/18/E/ST2/00758National Authority for Scientific Research (ANCS), RomaniaMinisterio de Ciencia, Innovacion, Investigacion y Universidades (MCIU): Programa Estatal de Generacion de Conocimiento PGC2018-096663-B-C41
PGC2018-096663-A-C42
PGC2018-096663-B-C43
PGC2018-096663-B-C44Generalitat Valenciana PROMETEO/2020/019Grisolia program GRISOLIA/2018/119
CIDEGENT/2018/034Junta de Andalucia A-FQM-053-UGR18La Caixa Foundation LCF/BQ/IN17/11620019EU: MSC program 101025085Paris Ile-de-France Region, FranceGenT program CIDEGENT/2018/034
CIDEGENT/2019/043
CIDEGENT/2020/04
Embedded Software of the KM3NeT Central Logic Board
The KM3NeT Collaboration is building and operating two deep sea neutrino
telescopes at the bottom of the Mediterranean Sea. The telescopes consist of
latices of photomultiplier tubes housed in pressure-resistant glass spheres,
called digital optical modules and arranged in vertical detection units. The
two main scientific goals are the determination of the neutrino mass ordering
and the discovery and observation of high-energy neutrino sources in the
Universe. Neutrinos are detected via the Cherenkov light, which is induced by
charged particles originated in neutrino interactions. The photomultiplier
tubes convert the Cherenkov light into electrical signals that are acquired and
timestamped by the acquisition electronics. Each optical module houses the
acquisition electronics for collecting and timestamping the photomultiplier
signals with one nanosecond accuracy. Once finished, the two telescopes will
have installed more than six thousand optical acquisition nodes, completing one
of the more complex networks in the world in terms of operation and
synchronization. The embedded software running in the acquisition nodes has
been designed to provide a framework that will operate with different hardware
versions and functionalities. The hardware will not be accessible once in
operation, which complicates the embedded software architecture. The embedded
software provides a set of tools to facilitate remote manageability of the
deployed hardware, including safe reconfiguration of the firmware. This paper
presents the architecture and the techniques, methods and implementation of the
embedded software running in the acquisition nodes of the KM3NeT neutrino
telescopes
The KM3NeT potential for the next core-collapse supernova observation with neutrinos
The authors acknowledge the financial support of the funding agencies: Agence Nationale de la Recherche (contract ANR-15-CE31-0020), Centre National de la Recherche Scientifique (CNRS), Commission Europeenne (FEDER fund and Marie Curie Program), Institut Universitaire de France (IUF), LabEx UnivEarthS (ANR-10-LABX-0023 and ANR-18-IDEX-0001), Paris Ile-de-France Region, France; Shota Rustaveli National Science Foundation of Georgia (SRNSFG, FR-18-1268), Georgia; Deutsche Forschungsgemeinschaft (DFG), Germany; The General Secretariat of Research and Technology (GSRT), Greece; Istituto Nazionale di Fisica Nucleare (INFN), Ministero dell'Universita e della Ricerca (MIUR), PRIN 2017 program (Grant NAT-NET 2017W4HA7S) Italy; Ministry of Higher Education Scientific Research and Professional Training, ICTP through Grant AF-13, Morocco; Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO), the Netherlands; The National Science Centre, Poland (2015/18/E/ST2/00758); National Authority for Scientific Research (ANCS), Romania; Ministerio de Ciencia, Innovacion, Investigacion y Universidades (MCIU): Programa Estatal de Generacion de Conocimiento (refs. PGC2018-096663-B-C41, -A-C42, -B-C43, -B-C44) (MCIU/FEDER), Severo Ochoa Centre of Excellence and MultiDark Consolider (MCIU), Junta de Andalucia (ref. SOMM17/6104/UGR), Generalitat Valenciana: Grisolia (ref. GRISO-LIA/2018/119) and GenT (ref. CIDEGENT/2018/034 and CIDE-GENT/2019/043) programs, La Caixa Foundation (ref. LCF/BQ/IN17/11620019), EU: MSC program (ref. 713673), Spain. This work has also received funding from the European Union'sHorizon 2020 research and innovation program under Grant agreement no 739560.The KM3NeT research infrastructure is under construction in the Mediterranean Sea. It consists of two water Cherenkov neutrino detectors, ARCA and ORCA, aimed at neutrino astrophysics and oscillation research, respectively. Instrumenting a large volume of sea water with similar to 6200 optical modules comprising a total of similar to 200,000 photomultiplier tubes, KM3NeT will achieve sensitivity to similar to 10 MeV neutrinos from Galactic and near-Galactic core-collapse supernovae through the observation of coincident hits in photomultipliers above the background. In this paper, the sensitivity of KM3NeT to a supernova explosion is estimated from detailed analyses of background data from the first KM3NeT detection units and simulations of the neutrino signal. The KM3NeT observational horizon (for a 5 sigma discovery) covers essentially the Milky-Way and for the most optimistic model, extends to the Small Magellanic Cloud (similar to 60 kpc). Detailed studies of the time profile of the neutrino signal allow assessment of the KM3NeT capability to determine the arrival time of the neutrino burst with a few milliseconds precision for sources up to 5-8 kpc away, and detecting the peculiar signature of the standing accretion shock instability if the core-collapse supernova explosion happens closer than 3-5 kpc, depending on the progenitor mass. KM3NeT's capability to measure the neutrino flux spectral parameters is also presented.French National Research Agency (ANR) ANR-15-CE31-0020Centre National de la Recherche Scientifique (CNRS)Commission Europeenne, FranceInstitut Universitaire de France (IUF), FranceLabEx UnivEarthS, France ANR-10-LABX-0023
ANR-18-IDEX-0001Paris Ile-de-France Region, FranceShota Rustaveli National Science Foundation of Georgia (SRNSFG), Georgia FR-18-1268German Research Foundation (DFG)Greek Ministry of Development-GSRTGreek Ministry of Development-GSRTIstituto Nazionale di Fisica Nucleare (INFN)Ministry of Education, Universities and Research (MIUR)PRIN 2017 program, Italy NAT-NET 2017W4HA7SMinistry of Higher Education Scientific Research and Professional Training, ICTP, Morocco AF-13Netherlands Organization for Scientific Research (NWO)Netherlands GovernmentNational Science Centre, Poland 2015/18/E/ST2/00758National Authority for Scientific Research (ANCS), RomaniaMinisterio de Ciencia, Innovacion, Investigacion y Universidades (MCIU): Programa Estatal de Generacion de Conocimiento, Spain PGC2018-096663-B-C41
PGC2018-096663-A-C42
PGC2018-096663-B-C43
PGC2018-096663-B-C44Severo Ochoa Centre of Excellence and MultiDark Consolider (MCIU), SpainJunta de Andalucia
European Commission SOMM17/6104/UGRGeneralitat Valenciana: Grisolia, Spain GRISO-LIA/2018/119
GenT program, Spain CIDEGENT/2018/034
CIDE-GENT/2019/043La Caixa Foundation LCF/BQ/IN17/11620019
EU: MSC program, Spain 713673European Commission 73956
Prospects for combined analyses of hadronic emission from -ray sources in the Milky Way with CTA and KM3NeT
The Cherenkov Telescope Array and the KM3NeT neutrino telescopes are major
upcoming facilities in the fields of -ray and neutrino astronomy,
respectively. Possible simultaneous production of rays and neutrinos
in astrophysical accelerators of cosmic-ray nuclei motivates a combination of
their data. We assess the potential of a combined analysis of CTA and KM3NeT
data to determine the contribution of hadronic emission processes in known
Galactic -ray emitters, comparing this result to the cases of two
separate analyses. In doing so, we demonstrate the capability of Gammapy, an
open-source software package for the analysis of -ray data, to also
process data from neutrino telescopes. For a selection of prototypical
-ray sources within our Galaxy, we obtain models for primary proton and
electron spectra in the hadronic and leptonic emission scenario, respectively,
by fitting published -ray spectra. Using these models and instrument
response functions for both detectors, we employ the Gammapy package to
generate pseudo data sets, where we assume 200 hours of CTA observations and 10
years of KM3NeT detector operation. We then apply a three-dimensional binned
likelihood analysis to these data sets, separately for each instrument and
jointly for both. We find that the largest benefit of the combined analysis
lies in the possibility of a consistent modelling of the -ray and
neutrino emission. Assuming a purely leptonic scenario as input, we obtain, for
the most favourable source, an average expected 68% credible interval that
constrains the contribution of hadronic processes to the observed -ray
emission to below 15%.Comment: 18 pages, 15 figures. Submitted to journa
Event reconstruction for KM3NeT/ORCA using convolutional neural networks
The authors acknowledge the financial support of the funding agencies: Agence Nationale de la Recherche (contract ANR-15-CE31-0020), Centre National de la Recherche Scientifique (CNRS), Commission Europeenne (FEDER fund and Marie Curie Program), Institut Universitaire de France (IUF), LabEx UnivEarthS (ANR-10-LABX-0023 and ANR-18-IDEX-0001), Paris Ile-de-France Region, France; Shota Rustaveli National Science Foundation of Georgia (SRNSFG, FR-18-1268), Georgia; Deutsche Forschungsgemeinschaft (DFG), Germany; The General Secretariat of Research and Technology (GSRT), Greece; Istituto Nazionale di Fisica Nucleare (INFN), Ministero dell'Universita e della Ricerca (MUR), PRIN 2017 program (Grant NAT-NET 2017W4HA7S) Italy; Ministry of Higher Education, Scientific Research and Professional Training, Morocco; Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO), the Netherlands; The National Science Centre, Poland (2015/18/E/ST2/00758); National Authority for Scientific Research (ANCS), Romania; Ministerio de Ciencia, Innovacion, Investigacion y Universidades (MCIU): Programa Estatal de Generacion de Conocimiento (refs. PGC2018-096663-B-C41, -A-C42, -B-C43, -B-C44) (MCIU/FEDER), Severo Ochoa Centre of Excellence and MultiDark Consolider (MCIU), Junta de Andalucia (ref. SOMM17/6104/UGR), Generalitat Valenciana: Grisolia (ref. GRISOLIA/2018/119) and GenT (ref. CIDEGENT/2018/034) programs, La Caixa Foundation (ref. LCF/BQ/IN17/11620019), EU: MSC program (ref. 713673), Spain.The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches.French National Research Agency (ANR)
ANR-15-CE31-0020Centre National de la Recherche Scientifique (CNRS), Commission Europeenne (FEDER fund)European Union (EU)Institut Universitaire de France (IUF)LabEx UnivEarthS
ANR-10-LABX-0023
ANR-18-IDEX-0001Shota Rustaveli National Science Foundation of Georgia
FR-18-1268German Research Foundation (DFG)Greek Ministry of Development-GSRTIstituto Nazionale di Fisica Nucleare (INFN)Ministry of Education, Universities and Research (MIUR)
Research Projects of National Relevance (PRIN)Ministry of Higher Education, Scientific Research and Professional Training, MoroccoNetherlands Organization for Scientific Research (NWO)National Science Centre, Poland
2015/18/E/ST2/00758National Authority for Scientific Research (ANCS), RomaniaMinisterio de Ciencia, Innovacion, Investigacion y Universidades
PGC2018-096663-B-C41
A-C42
B-C43
B-C44Severo Ochoa Centre of ExcellenceJunta de Andalucia
SOMM17/6104/UGRGeneralitat Valenciana: Grisolia
GRISOLIA/2018/119
CIDEGENT/2018/034La Caixa Foundation
LCF/BQ/IN17/11620019EU: MSC program
71367
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