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Author Mistry, A. K. et al; Tain, J.L.; Agramunt, J.; Algora, A.; Guadilla, V.; Morales, A.I.; Nacher, E.; Orrigo, S.E.A.; Rubio, B. doi  openurl
  Title The DESPEC setup for GSI and FAIR Type Journal Article
  Year 2022 Publication Nuclear Instruments & Methods in Physics Research A Abbreviated Journal Nucl. Instrum. Methods Phys. Res. A  
  Volume 1033 Issue Pages 166662 - 18pp  
  Keywords (up) alpha, beta, gamma spectroscopy; Digital electronics; Fast timing; FAIR; DESPEC; NuSTAR  
  Abstract The DEcay SPECtroscopy (DESPEC) setup for nuclear structure investigations was developed and commissioned at GSI, Germany in preparation for a full campaign of experiments at the FRS and Super-FRS. In this paper, we report on the first employment of the setup in the hybrid configuration with the AIDA implanter coupled to the FATIMA LaBr3(Ce) fast-timing array, and high-purity germanium detectors. Initial results are shown from the first experiments carried out with the setup. An overview of the setup and function is discussed, including technical advancements along the path.  
  Address  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0168-9002 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000794062100014 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5343  
Permanent link to this record
 

 
Author LHCb Collaboration (Aaij, R. et al); Jashal, B.K.; Martinez-Vidal, F.; Oyanguren, A.; Remon Alepuz, C.; Ruiz Vidal, J. url  doi
openurl 
  Title Identification of charm jets at LHCb Type Journal Article
  Year 2022 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.  
  Volume 17 Issue 2 Pages P02028 - 23pp  
  Keywords (up) Analysis and statistical methods; Pattern recognition; cluster finding; calibration and fitting methods; Performance of High Energy Physics Detectors  
  Abstract The identification of charm jets is achieved at LHCb for data collected in 2015-2018 using a method based on the properties of displaced vertices reconstructed and matched with jets. The performance of this method is determined using a dijet calibration dataset recorded by the LHCb detector and selected such that the jets are unbiased in quantities used in the tagging algorithm. The charm-tagging efficiency is reported as a function of the transverse momentum of the jet. The measured efficiencies are compared to those obtained from simulation and found to be in good agreement.  
  Address [Leite, J. Baptista; Bediaga, I; Torres, M. Cruz; De Miranda, J. M.; dos Reis, A. C.; Gomes, A.; Massafferri, A.; Machado, D. Torres] Ctr Brasileiro Pesquisas Fis CBPF, Rio De Janeiro, Brazil, Email: dcraik@cern.ch  
  Corporate Author Thesis  
  Publisher IOP Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1748-0221 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000770368300015 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5177  
Permanent link to this record
 

 
Author ANTARES Collaboration (Albert, A. et al); Alves, S.; Calvo, D.; Carretero, V.; Gozzini, R.; Hernandez-Rey, J.J.; Khan-Chowdhury, N.R.; Manczak, J.; Pieterse, C.; Sanchez-Losa, A.; Salesa Greus, F.; Zornoza, J.D.; Zuñiga, J. url  doi
openurl 
  Title Search for magnetic monopoles with ten years of the ANTARES neutrino telescope Type Journal Article
  Year 2022 Publication Journal of High Energy Astrophysics Abbreviated Journal J. High Energy Astrophys.  
  Volume 34 Issue Pages 1-8  
  Keywords (up) ANTARES telescope; Magnetic monopoles; Neutrino  
  Abstract This work presents a new search for magnetic monopoles using data taken with the ANTARES neutrino telescope over a period of 10 years (January 2008 to December 2017). Compared to previous ANTARES searches, this analysis uses a run-by-run simulation strategy, with a larger exposure as well as a new simulation of magnetic monopoles taking into account the Kasama, Yang and Goldhaber model for their interaction cross-section with matter. No signal compatible with the passage of relativistic magnetic monopoles is observed, and upper limits on the flux of magnetic monopoles with beta = v/c & nbsp;>=& nbsp;0.55, are presented. For ultra-relativistic magnetic monopoles the flux limit is similar to 7 x 10(-18) cm(-2) s(-1) sr(-1). (C)& nbsp;2022 Elsevier B.V. All rights reserved.  
  Address [Albert, A.; Pradier, T.] Univ Strasbourg, CNRS, UMR 7178, F-67000 Strasbourg, France, Email: boumaaza.jihad@gmail.com  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2214-4048 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000791701000001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5223  
Permanent link to this record
 

 
Author Hirn, J.; Garcia, J.E.; Montesinos-Navarro, A.; Sanchez-Martin, R.; Sanz, V.; Verdu, M. url  doi
openurl 
  Title A deep Generative Artificial Intelligence system to predict species coexistence patterns Type Journal Article
  Year 2022 Publication Methods in Ecology and Evolution Abbreviated Journal Methods Ecol. Evol.  
  Volume 13 Issue Pages 1052-1061  
  Keywords (up) artificial intelligence; direct interactions; generative adversarial networks; indirect interactions; species coexistence; variational AutoEncoders  
  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.  
  Address [Hirn, Johannes; Enrique Garcia, Jose; Sanz, Veronica] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: miguel.verdu@ext.uv.es  
  Corporate Author Thesis  
  Publisher Wiley Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2041-210x ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000765239700001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5155  
Permanent link to this record
 

 
Author Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Bhattacharyya, S.; Caron, S.; Johannesson, G.; Ruiz de Austri, R.; van den Oetelaar, C.; Zaharijas, G.; Groot, P.J.; Cator, E.; Nelemans, G. url  doi
openurl 
  Title AutoSourceID-Light Fast optical source localization via U-Net and Laplacian of Gaussian Type Journal Article
  Year 2022 Publication Astronomy & Astrophysics Abbreviated Journal Astron. Astrophys.  
  Volume 662 Issue Pages A109 - 8pp  
  Keywords (up) astronomical databases; miscellaneous; methods; data analysis; stars; imaging; techniques; image processing  
  Abstract Aims. With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. Methods. We show that the ASID-L algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter provides outstanding performance in the localization of sources. A U-Net network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location. Results. Using ASID-L on the optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with SExtractor and show that our method outperforms this more widely used method. ASID-L rapidly detects more sources not only in low- and mid-density fields, but particularly in areas with more than 150 sources per square arcminute. The training set and code used in this paper are publicly available.  
  Address [Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Groot, P. J.; Nelemans, G.] Radboud Univ Nijmegen, Dept Astrophys, IMAPP, POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: f.stoppa@astro.ru.nl  
  Corporate Author Thesis  
  Publisher Edp Sciences S A Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0004-6361 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000818665600009 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5291  
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