2026-06-20
06:01 |
Near-Infrared Light Attenuation Measurements of Radiophotoluminescence FD-7 Dosimeters Irradiated With
X-Rays at High Doses
/ Raj Mandal, A (Jean Monnet U.) ; Ferrari, M (Jean Monnet U.) ; Aguiar, Y Q (Jean Monnet U. ; CERN) ; Morana, A (Jean Monnet U.) ; García Alía, R (CERN) ; Marin, E (Jean Monnet U.) ; Ouerdane, Y (Jean Monnet U.) ; Boukenter, A (Jean Monnet U.) ; Girard, S (Jean Monnet U. ; IUF, Paris)
Dosimetry techniques at high dose levels in the
kGy–MGy range are challenging and still insufficiently explored.
One of the emerging candidates for high-level applications is
silver-doped metaphosphate glass, commercially known as FD-7
radiophotoluminescence (RPL) dosimeters. In this study, a free-
space optical setup is used to enable a dedicated study for
online (during irradiation) characterization of RPL dosimeters.
Transmission spectra are measured online as a function of
wavelength, dose, and dose rates, with additional monitoring
of post-irradiation recovery kinetics. [...]
2026 - 8 p.
- Published in : IEEE Trans. Nucl. Sci. 73 (2026) 2216-2223
Fulltext: PDF; External link: Fulltext
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2026-06-20
06:01 |
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2026-06-19
11:56 |
Data from Students’ Use of Generative AI in Innovation Education Programs at CERN IdeaSquare
/ Sairanen, Mikko (CERN) ; Poulaillon, Jimmy (CERN) ; Valtonen, Lauri ; Gaddi, Giulia (CERN) ; Batista, Catarina (CERN) ; Werner, Ole (CERN) ; Balocco, Matteo ; Bruno, Andrea ; Tandaypan, Diego Canova ; Costa-Perales, Ángel et al.
This article presents a dataset comprising Master-level students’ prompts and discussions with generative artificial intelligence (AI)as part of a challenge-based innovation problem-solving process. Openly accessible through Zenodo (https://doi.org/10.5281/zenodo.17857679), the data consists of 466pages of students’ conversations with generative AI tools and a 28-page extract comprising only the prompts.The data was collected through a survey for students participating in week-long intense innovation education programs at CERN IdeaSquare throughout2024.The data can be used to advance practice and theory regarding the use of generative AI in problem solving and innovation education.Scholars are encouraged to use the data in various forms of analysis,including thematic, content, and narrative analysis. [...]
Geneva : CERN, 2025 - 4 p.
- Published in : CERN IdeaSquare Journal of Experimental Innovation 9 (2025) 53-56
publication: PDF; External links: external link to the data paper; external link to the dataset
In : CERN IdeaSquare Journal of Experimental Innovation, pp.53-56
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2026-06-18
08:34 |
High Power Slow Extraction for BDF/SHiP at CERN SPS
/ Fraser, Matthew Alexander (CERN) ; Sota, Pablo Arrutia (CERN) ; Balhan, Bruno (CERN) ; Borburgh, Jan (CERN) ; Calviani, Marco (CERN) ; Esposito, Luigi (CERN) ; Goddard, Brennan (CERN) ; Kain, Verena (CERN) ; Lackner, Friedrich (CERN) ; Velotti, Francesco (CERN) et al.
The High Intensity ECN3 (HI-ECN3) project at CERN aims to increase the intensity to the SPS North Area’s only underground experimental area ECN3 by well over an order of magnitude to welcome the Search for Hidden Particles (SHiP) experiment at a new Beam Dump Facility (BDF). The project necessitates significant upgrades to the SPS slow extraction system to accommodate higher intensity proton beams while minimising beam loss and radio-activation. [...]
2026 - 10 p.
- Published in : JPS Conf. Proc. 45 (2026) 011116
Fulltext: PDF;
In : J-PARC Symposium 2024: Futures of J-PARC, Futures by J-PARC, Ibaraki, Japan, 14 - 18 Oct 2024, pp.011116
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2026-06-18
08:34 |
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2026-06-18
08:34 |
Gain-Layer Project
/ Sorgenfrei, Niels G (CERN ; Freiburg U.) ; Altamura, Anna Rita (INFN, Turin ; Turin U.) ; Besleaga, Cristina (Bucharest, Inst. Space Science) ; Boni, Georgia Andra (Bucharest, Inst. Space Science) ; Ceponis, Tomas (Vilnius U.) ; Erberk, Paul (U. Hamburg, Dept. Phys.) ; Fretwurst, Eckhart (U. Hamburg, Dept. Phys.) ; Gurimskaya, Yana (CERN) ; Lauer, Kevin (CIS Inst. Micro., Erfurt) ; Massaccesi, Ludovico (INFN, Turin ; Turin U.) et al.
Gain-layer degradation from exposure to radiation limits the use of Low-Gain Avalanche Diodes (LGADs) in high energy particle physics detector experiments. Proper understanding of how the gain-layer is destroyed is not available on a defect level. [...]
arXiv:2601.16049.-
2026 - 16 p.
- Published in : Nucl. Instrum. Methods Phys. Res., A 1091 (2026) 171757
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2026-06-18
08:34 |
Improving timing resolution of BGO for TOF-PET : a comparative analysis with and without deep learning
/ Loignon-Houle, Francis (Valencia, Polytechnic U.) ; Kratochwil, Nicolaus (UC, Davis (main) ; CERN) ; Toussaint, Maxime (Sherbrooke U.) ; Lowis, Carsten (CERN ; RWTH Aachen U.) ; Ariño-Estrada, Gerard (UC, Davis (main) ; BIST, Barcelona) ; Gonzalez, Antonio J (Valencia, Polytechnic U.) ; Auffray, Etiennette (CERN) ; Lecomte, Roger (Sherbrooke U. ; Unlisted, CA)
Abstract
Background
The renewed interest in BGO scintillators for TOF-PET is driven by the improved Cherenkov photon detection with new blue-sensitive SiPMs. However, the slower scintillation light from BGO causes significant time walk with leading edge discrimination (LED), which degrades the coincidence time resolution (CTR) [...]
2025 - 15 p.
- Published in : EJNMMI Physics 12 (2025) 2
Fulltext: PDF; External link: Fulltext
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2026-06-17
11:21 |
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2026-06-16
06:20 |
A Novel Multi-Mode Resonator-Based Ultra-Wideband Bandpass Filter Topology
/ Rajender, Rathod (U. Pisa (main)) ; Barik, Rusan Kumar (Unlisted, IN) ; Ciarpi, Gabriele (CERN) ; Koziel, Slawomir (Reykjavik U. ; Gdansk Tech. U.) ; Genovesi, Simone (U. Pisa (main)) ; Rossi, Daniele (U. Pisa (main))
In this paper, a novel multi-mode resonator-based ultra-wideband bandpass filter topology is proposed, analyzed, and experimentally validated. The filter comprises a short shunt-stepped impedance resonator and shunt-open stubs. [...]
2025 - 15 p.
- Published in : Electronics 14 (2025) 3992
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2026-06-16
06:20 |
A Comparative Study Between Clinical Optical Coherence Tomography (OCT) Analysis and Artificial Intelligence-Based Quantitative Evaluation in the Diagnosis of Diabetic Macular Edema
/ Brandão Fantozzi, Camila (Unlisted, BR) ; Peres, Letícia Margaria (Unlisted, BR) ; Neto, Jogi Suda (CERN ; Unlisted, BR) ; Brandão, Cinara Cássia (Unlisted, BR) ; Guido, Rodrigo Capobianco (Unlisted, BR) ; Siqueira, Rubens Camargo (Unlisted, BR)
Recent advances in artificial intelligence (AI) have transformed ophthalmic diagnostics, particularly for retinal diseases. In this prospective, non-randomized study, we evaluated the performance of an AI-based software system against conventional clinical assessment—both quantitative and qualitative—of optical coherence tomography (OCT) images for diagnosing diabetic macular edema (DME). [...]
2025 - 12 p.
- Published in : Vision 9 (2025) 75
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