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Author |
Super-Kamiokande Collaboration (Abe, K. et al); Molina Sedgwick, S. |
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Title |
Neutron tagging following atmospheric neutrino events in a water Cherenkov detector |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
17 |
Issue |
10 |
Pages |
P10029 - 41pp |
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Keywords |
Particle identification methods; Cherenkov detectors; Neutrino detectors; Large detector systems for particle and astroparticle physics |
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Abstract |
We present the development of neutron-tagging techniques in Super-Kamiokande IV using a neural network analysis. The detection efficiency of neutron capture on hydrogen is estimated to be 26%, with a mis-tag rate of 0.016 per neutrino event. The uncertainty of the tagging efficiency is estimated to be 9.0%. Measurement of the tagging efficiency with data from an Americium-Beryllium calibration agrees with this value within 10%. The tagging procedure was performed on 3,244.4 days of SK-IV atmospheric neutrino data, identifying 18,091 neutrons in 26,473 neutrino events. The fitted neutron capture lifetime was measured as 218 +/- 9 μs. |
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Address |
[Abe, K.; Haga, Y.; Hayato, Y.; Hiraide, K.; Ieki, K.; Ikeda, M.; Imaizumi, S.; Iyogi, K.; Kameda, J.; Kanemura, Y.; Kataoka, Y.; Kato, Y.; Kishimoto, Y.; Miki, S.; Mine, S.; Miura, M.; Mochizuki, T.; Moriyama, S.; Nagao, Y.; Nakahata, M.; Nakajima, T.; Nakano, Y.; Nakayama, S.; Okada, T.; Okamoto, K.; Orii, A.; Sato, K.; Sekiya, H.; Shiozawa, M.; Sonoda, Y.; Suzuki, Y.; Takeda, A.; Takemoto, Y.; Takenaka, A.; Tanaka, H.; Tasaka, S.; Tomura, T.; Ueno, K.; Watanabe, S.; Yano, T.; Yokozawa, T.] Univ Tokyo, Inst Cosm Ray Res, Kamioka Observ, Gifu, Akita 5061205, Japan, Email: hayato@icrr.u-tokyo.ac.jp |
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IOP Publishing Ltd |
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English |
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ISSN  |
1748-0221 |
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Conference |
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Notes |
WOS:000898723700008 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5441 |
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Author |
T2K Collaboration (Abe, K. et al); Antonova, M.; Cervera-Villanueva, A.; Molina Bueno, L.; Novella, P. |
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Title |
Scintillator ageing of the T2K near detectors fro 2010 to 2021 |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
17 |
Issue |
10 |
Pages |
P10028 - 36pp |
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Keywords |
Gamma detectors (scintillators, CZT, HPGe, HgI etc); Neutrino detectors; Performance of High Energy Physics Detectors; Scintillators; scintillation and light emission processes (solid, gas and liquid scintillators) |
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Abstract |
The T2K experiment widely uses plastic scintillator as a target for neutrino interactions and an active medium for the measurement of charged particles produced in neutrino interactions at its near detector complex. Over 10 years of operation the measured light yield recorded by the scintillator based subsystems has been observed to degrade by 0.9-2.2% per year. Extrapolation of the degradation rate through to 2040 indicates the recorded light yield should remain above the lower threshold used by the current reconstruction algorithms for all subsystems. This will allow the near detectors to continue contributing to important physics measurements during the T2K-II and Hyper-Kamiokande eras. Additionally, work to disentangle the degradation of the plastic scintillator and wavelength shifting fibres shows that the reduction in light yield can be attributed to the ageing of the plastic scintillator. The long component of the attenuation length of the wavelength shifting fibres was observed to degrade by 1.3-5.4% per year, while the short component of the attenuation length did not show any conclusive degradation. |
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Address |
[Labarga, L.] Univ Autonoma Madrid, Dept Theoret Phys, ES-28049 Madrid, Spain, Email: m.lawe@lancaster.ac.uk |
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IOP Publishing Ltd |
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English |
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1748-0221 |
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Notes |
WOS:000898723700007 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5442 |
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Author |
KM3NeT Collaboration (Aiello, S. et al); Alves Garre, S.; Calvo, D.; Carretero, V.; Colomer, M.; Garcia Soto, A.; Gozzini, S.R.; Hernandez-Rey, J.J.; Khan Chowdhury, N.R.; Lazo, A.; Manczak, J.; Palacios Gonzalez, J.; Pieterse, C.; Real, D.; Salesa Greus, F.; Sanchez Losa, A.; Zornoza, J.D.; Zuñiga, J. |
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Title |
The KM3NeT multi-PMT optical module |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
17 |
Issue |
7 |
Pages |
P07038 - 28pp |
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Keywords |
Cherenkov detectors; Large detector systems for particle and astroparticle physics; Neutrino detectors |
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Abstract |
The optical module of the KM3NeT neutrino telescope is an innovative multi-faceted large area photodetection module. It contains 31 three-inch photomultiplier tubes in a single 0.44 m diameter pressure-resistant glass sphere. The module is a sensory device also comprising calibration instruments and electronics for power, readout and data acquisition. It is capped with a breakout-box with electronics for connection to an electro-optical cable for power and long-distance communication to the onshore control station. The design of the module was qualified for the first time in the deep sea in 2013. Since then, the technology has been further improved to meet requirements of scalability, cost-effectiveness and high reliability. The module features a sub-nanosecond timing accuracy and a dynamic range allowing the measurement of a single photon up to a cascade of thousands of photons, suited for the measurement of the Cherenkov radiation induced in water by secondary particles from interactions of neutrinos with energies in the range of GeV to PeV. A distributed production model has been implemented for the delivery of more than 6000 modules in the coming few years with an average production rate of more than 100 modules per month. In this paper a review is presented of the design of the multi-PMT KM3NeT optical module with a proven effective background suppression and signal recognition and sensitivity to the incoming direction of photons. |
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Address |
[Aiello, S.; Bruno, R.; Leonora, E.; Longhitano, F.; Randazzo, N.] Ist Nazl Fis Nucl, Sez Catania, Via Santa Sofia 64, I-95123 Italy, Italy, Email: km3net-pc@km3net.de |
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IOP Publishing Ltd |
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English |
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ISSN |
1748-0221 |
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Conference |
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Notes |
WOS:000898568200003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5449 |
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Author |
Fioresi, R.; Lledo, M.A.; Razzaq, J. |
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Title |
N=2 quantum chiral superfields and quantum super bundles |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Physics A |
Abbreviated Journal |
J. Phys. A |
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Volume |
55 |
Issue |
38 |
Pages |
384012 - 19pp |
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Keywords |
supergeometry; supersymmetry; quantum groups; noncommutative geometry; Minkowski space |
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Abstract |
We give the superalgebra of N = 2 chiral (and antichiral) quantum superfields realized as a subalgebra of the quantum supergroup SL q (4|2). The multiplication law in the quantum supergroup induces a coaction on the set of chiral superfields. We also realize the quantum deformation of the chiral Minkowski superspace as a quantum principal bundle. |
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Address |
[Fioresi, R.] Univ Bologna, Fabit, Via San Donato 15, I-40126 Bologna, Italy, Email: rita.fioresi@unibo.it; |
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Corporate Author |
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Publisher |
IOP Publishing Ltd |
Place of Publication |
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English |
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ISSN |
1751-8113 |
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Conference |
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Notes |
WOS:000849946700001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5351 |
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Author |
Albiol, A.; Albiol, F.; Paredes, R.; Plasencia-Martinez, J.M.; Blanco Barrio, A.; Garcia Santos, J.M.; Tortajada, S.; Gonzalez Montano, V.M.; Rodriguez Godoy, C.E.; Fernandez Gomez, S.; Oliver-Garcia, E.; de la Iglesia Vaya, M.; Marquez Perez, F.L.; Rayo Madrid, J.I. |
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Title |
A comparison of Covid-19 early detection between convolutional neural networks and radiologists |
Type |
Journal Article |
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Year |
2022 |
Publication |
Insights into Imaging |
Abbreviated Journal |
Insights Imaging |
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Volume |
13 |
Issue |
1 |
Pages |
122 - 12pp |
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Keywords |
Deep learning; Covid-19; Radiology |
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Abstract |
Background The role of chest radiography in COVID-19 disease has changed since the beginning of the pandemic from a diagnostic tool when microbiological resources were scarce to a different one focused on detecting and monitoring COVID-19 lung involvement. Using chest radiographs, early detection of the disease is still helpful in resource-poor environments. However, the sensitivity of a chest radiograph for diagnosing COVID-19 is modest, even for expert radiologists. In this paper, the performance of a deep learning algorithm on the first clinical encounter is evaluated and compared with a group of radiologists with different years of experience. Methods The algorithm uses an ensemble of four deep convolutional networks, Ensemble4Covid, trained to detect COVID-19 on frontal chest radiographs. The algorithm was tested using images from the first clinical encounter of positive and negative cases. Its performance was compared with five radiologists on a smaller test subset of patients. The algorithm's performance was also validated using the public dataset COVIDx. Results Compared to the consensus of five radiologists, the Ensemble4Covid model achieved an AUC of 0.85, whereas the radiologists achieved an AUC of 0.71. Compared with other state-of-the-art models, the performance of a single model of our ensemble achieved nonsignificant differences in the public dataset COVIDx. Conclusion The results show that the use of images from the first clinical encounter significantly drops the detection performance of COVID-19. The performance of our Ensemble4Covid under these challenging conditions is considerably higher compared to a consensus of five radiologists. Artificial intelligence can be used for the fast diagnosis of COVID-19. |
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Address |
[Albiol, Alberto] Univ Politecn Valencia, iTeam Inst, ETSI Telecomunicac, Camino Vera S-N, Valencia 46022, Spain, Email: alalbiol@iteam.upv.es |
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Publisher |
Springer |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Edition |
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ISSN |
1869-4101 |
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Notes |
WOS:000832727200003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5302 |
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Author |
Capra, S. et al; Gadea, A. |
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Title |
GALTRACE: A highly segmented silicon detector array for charged particle spectroscopy and discrimination |
Type |
Journal Article |
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Year |
2022 |
Publication |
Nuovo Cimento C |
Abbreviated Journal |
Nuovo Cim. C |
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Volume |
45 |
Issue |
5 |
Pages |
98 - 4pp |
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Keywords |
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Abstract |
GALTRACE is an array of segmented silicon detectors specifically built to work as an ancillary of the GALILEO gamma-ray spectrometer at Legnaro National Laboratory of INFN. GALTRACE consists of four telescopic Delta E-Edetectors which allow discriminating light charged particles also via pulse-shape analysis techniques. The good angular and energy resolutions, together with particle discrimination capabilities, make GALTRACE suitable for experiments where coincidences with specific emitted particles allow for the selection of reaction channels with very low cross section. The first in-beam experiment is reported here, aiming at identifying a narrow resonance, near-proton-threshold state in B-11, currently under discussion. |
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Address |
[Capra, S.; Ziliani, S.; LEONI, S.; PULLIA, A.; BOTTONI, S.; CAMERA, F.; CRESPI, F. C. L.; GAMBA, E.; MILLION, B.; POLETTINI, M.] Univ Milan, Milan, Italy |
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Publisher |
Soc Italiana Fisica |
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English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2037-4909 |
ISBN |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000819587500001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5282 |
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Author |
HISPEC-DESPEC Collaboration (Polettini, M. et al); Algora, A.; Morales, A.I.; Orrigo, S.E.A. |
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Title |
Decay studies in the A similar to 225 Po-Fr region from the DESPEC campaign at GSI in 2021 |
Type |
Journal Article |
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Year |
2022 |
Publication |
Nuovo Cimento C |
Abbreviated Journal |
Nuovo Cim. C |
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Volume |
45 |
Issue |
5 |
Pages |
125 - 4pp |
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Keywords |
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Abstract |
The HISPEC-DESPEC collaboration aims at investigating the struc-ture of exotic nuclei formed in fragmentation reactions with decay spectroscopymeasurements, as part of the FAIR Phase-0 campaign at GSI. This paper reportson first results of an experiment performed in spring 2021, with a focus on beta-decaystudies in the Po-Fr nuclei in the 220 < A <230 island of octupole deformationexploiting the DESPEC setup. Ion-beta correlations and fast-timing techniques arebeing employed, giving an insight into this difficult-to-reach region. |
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Address |
[Polettini, M.; Benzoni, G.; Genna, D.; Bracco, A.; Bottoni, S.; Camera, F.; Crespi, F. C. L.; Gamba, E. R.; Leoni, S.; Million, B.; Porzio, C.; Wieland, O.; Ziliani, S.] Univ Milan, Dipartimento Fis, Milan, Italy |
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Soc Italiana Fisica |
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English |
Summary Language |
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Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2037-4909 |
ISBN |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000819174100001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5292 |
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Author |
Hirn, J.; Garcia, J.E.; Montesinos-Navarro, A.; Sanchez-Martin, R.; Sanz, V.; Verdu, M. |
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Title |
A deep Generative Artificial Intelligence system to predict species coexistence patterns |
Type |
Journal Article |
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Year |
2022 |
Publication |
Methods in Ecology and Evolution |
Abbreviated Journal |
Methods Ecol. Evol. |
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Volume |
13 |
Issue |
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Pages |
1052-1061 |
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Keywords |
artificial intelligence; direct interactions; generative adversarial networks; indirect interactions; species coexistence; variational AutoEncoders |
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Abstract |
Predicting coexistence patterns is a current challenge to understand diversity maintenance, especially in rich communities where these patterns' complexity is magnified through indirect interactions that prevent their approximation with classical experimental approaches. We explore cutting-edge Machine Learning techniques called Generative Artificial Intelligence (GenAI) to predict species coexistence patterns in vegetation patches, training generative adversarial networks (GAN) and variational AutoEncoders (VAE) that are then used to unravel some of the mechanisms behind community assemblage. The GAN accurately reproduces real patches' species composition and plant species' affinity to different soil types, and the VAE also reaches a high level of accuracy, above 99%. Using the artificially generated patches, we found that high-order interactions tend to suppress the positive effects of low-order interactions. Finally, by reconstructing successional trajectories, we could identify the pioneer species with larger potential to generate a high diversity of distinct patches in terms of species composition. Understanding the complexity of species coexistence patterns in diverse ecological communities requires new approaches beyond heuristic rules. Generative Artificial Intelligence can be a powerful tool to this end as it allows to overcome the inherent dimensionality of this challenge. |
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Address |
[Hirn, Johannes; Enrique Garcia, Jose; Sanz, Veronica] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: miguel.verdu@ext.uv.es |
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Thesis |
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Publisher |
Wiley |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2041-210x |
ISBN |
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Area |
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Notes |
WOS:000765239700001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5155 |
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Author |
Angles-Castillo, A.; Perez, A. |
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Title |
A quantum walk simulation of extra dimensions with warped geometry |
Type |
Journal Article |
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Year |
2022 |
Publication |
Scientific Reports |
Abbreviated Journal |
Sci Rep |
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Volume |
12 |
Issue |
1 |
Pages |
1926 - 12pp |
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Keywords |
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Abstract |
We investigate the properties of a quantum walk which can simulate the behavior of a spin 1/2 particle in a model with an ordinary spatial dimension, and one extra dimension with warped geometry between two branes. Such a setup constitutes a 1+ 1 dimensional version of the Randall-Sundrum model, which plays an important role in high energy physics. In the continuum spacetime limit, the quantum walk reproduces the Dirac equation corresponding to the model, which allows to anticipate some of the properties that can be reproduced by the quantum walk. In particular, we observe that the probability distribution becomes, at large time steps, concentrated near the “low energy” brane, and can be approximated as the lowest eigenstate of the continuum Hamiltonian that is compatible with the symmetries of the model. In this way, we obtain a localization effect whose strength is controlled by a warp coefficient. In other words, here localization arises from the geometry of the model, at variance with the usual effect that is originated from random irregularities, as in Anderson localization. In summary, we establish an interesting correspondence between a high energy physics model and localization in quantum walks. |
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Address |
[Angles-Castillo, Andreu] Univ Valencia, CSIC, Dept Fis Teor, Valencia 46100, Spain, Email: andreu.angles@ific.uv.es |
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Publisher |
Nature Portfolio |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2045-2322 |
ISBN |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000751472600024 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5107 |
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Author |
Lerendegui-Marco, J.; Balibrea-Correa, J.; Babiano-Suarez, V.; Ladarescu, I.; Domingo-Pardo, C. |
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Title |
Towards machine learning aided real-time range imaging in proton therapy |
Type |
Journal Article |
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Year |
2022 |
Publication |
Scientific Reports |
Abbreviated Journal |
Sci Rep |
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Volume |
12 |
Issue |
1 |
Pages |
2735 - 17pp |
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Keywords |
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Abstract |
Compton imaging represents a promising technique for range verification in proton therapy treatments. In this work, we report on the advantageous aspects of the i-TED detector for proton-range monitoring, based on the results of the first Monte Carlo study of its applicability to this field. i-TED is an array of Compton cameras, that have been specifically designed for neutron-capture nuclear physics experiments, which are characterized by gamma-ray energies spanning up to 5-6 MeV, rather low gamma-ray emission yields and very intense neutron induced gamma-ray backgrounds. Our developments to cope with these three aspects are concomitant with those required in the field of hadron therapy, especially in terms of high efficiency for real-time monitoring, low sensitivity to neutron backgrounds and reliable performance at the high gamma-ray energies. We find that signal-to-background ratios can be appreciably improved with i-TED thanks to its light-weight design and the low neutron-capture cross sections of its LaCl3 crystals, when compared to other similar systems based on LYSO, CdZnTe or LaBr3. Its high time-resolution (CRT similar to 500 ps) represents an additional advantage for background suppression when operated in pulsed HT mode. Each i-TED Compton module features two detection planes of very large LaCl3 monolithic crystals, thereby achieving a high efficiency in coincidence of 0.2% for a point-like 1 MeV gamma-ray source at 5 cm distance. This leads to sufficient statistics for reliable image reconstruction with an array of four i-TED detectors assuming clinical intensities of 10(8) protons per treatment point. The use of a two-plane design instead of three-planes has been preferred owing to the higher attainable efficiency for double time-coincidences than for threefold events. The loss of full-energy events for high energy gamma-rays is compensated by means of machine-learning based algorithms, which allow one to enhance the signal-to-total ratio up to a factor of 2. |
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Address |
[Lerendegui-Marco, Jorge; Balibrea-Correa, Javier; Babiano-Suarez, Victor; Ladarescu, Ion; Domingo-Pardo, Cesar] Univ Valencia, CSIC, Inst Fis Corpuscular, Valencia, Spain, Email: jorge.lerendegui@ific.uv.es |
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Corporate Author |
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Thesis |
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Publisher |
Nature Portfolio |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2045-2322 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000757537100018 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5136 |
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