441 research outputs found
Water extraction and implications on soil moisture sensor placement in the root zone of banana
Decepa de plantas jovens de eucalipto e manejo de brotaçÔes, em um sistema agroflorestal
Consumo e digestĂ”es totais e parciais em novilhos F1 Limousin x Nelore alimentados com dietas contendo cinco nĂveis de concentrado
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
gSeaGen: The KM3NeT GENIE-based code for neutrino telescopes
Program summary
Program Title: gSeaGen
CPC Library link to program files: http://dx.doi.org/10.17632/ymgxvy2br4.1
Licensing provisions: GPLv3
Programming language: C++
External routines/libraries: GENIE [1] and its external dependencies. Linkable to MUSIC [2] and PROPOSAL
[3].
Nature of problem: Development of a code to generate detectable events in neutrino telescopes, using
modern and maintained neutrino interaction simulation libraries which include the state-of-the-art
physics models. The default application is the simulation of neutrino interactions within KM3NeT [4].
Solution method: Neutrino interactions are simulated using GENIE, a modern framework for Monte
Carlo event generators. The GENIE framework, used by nearly all modern neutrino experiments, is
considered as a reference code within the neutrino community.
Additional comments including restrictions and unusual features: The code was tested with GENIE version
2.12.10 and it is linkable with release series 3. Presently valid up to 5 TeV. This limitation is not intrinsic
to the code but due to the present GENIE valid energy range.
References:
[1] C. Andreopoulos at al., Nucl. Instrum. Meth. A614 (2010) 87.
[2] P. Antonioli et al., Astropart. Phys. 7 (1997) 357.
[3] J. H. Koehne et al., Comput. Phys. Commun. 184 (2013) 2070.
[4] S. AdriĂĄn-MartĂnez et al., J. Phys. G: Nucl. Part. Phys. 43 (2016) 084001.The gSeaGen code is a GENIE-based application developed to efficiently generate high statistics samples
of events, induced by neutrino interactions, detectable in a neutrino telescope. The gSeaGen code is able
to generate events induced by all neutrino flavours, considering topological differences between tracktype
and shower-like events. Neutrino interactions are simulated taking into account the density and
the composition of the media surrounding the detector. The main features of gSeaGen are presented
together with some examples of its application within the KM3NeT project.French National Research Agency (ANR)
ANR-15-CE31-0020Centre National de la Recherche Scientifique (CNRS)European Union (EU)Institut Universitaire de France (IUF), FranceIdEx program, FranceUnivEarthS Labex program at Sorbonne Paris Cite
ANR-10-LABX-0023
ANR-11-IDEX-000502Paris Ile-de-France Region, FranceShota 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, MoroccoNetherlands 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 (MCIU/FEDER)
PGC2018-096663-B-C41
PGC2018-096663-A-C42
PGC2018-096663-BC43
PGC2018-096663-B-C44Severo Ochoa Centre of Excellence and MultiDark Consolider (MCIU), Junta de Andalucia, Spain
SOMM17/6104/UGRGeneralitat Valenciana: Grisolia, Spain
GRISOLIA/2018/119GenT, Spain
CIDEGENT/2018/034La Caixa Foundation
LCF/BQ/IN17/11620019EU: MSC program, Spain
71367
On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection
A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)
Body appreciation around the world: Measurement invariance of the Body Appreciation Scale-2 (BAS-2) across 65 nations, 40 languages, gender identities, and age.
The Body Appreciation Scale-2 (BAS-2) is a widely used measure of a core facet of the positive body image construct. However, extant research concerning measurement invariance of the BAS-2 across a large number of nations remains limited. Here, we utilised the Body Image in Nature (BINS) dataset - with data collected between 2020 and 2022 - to assess measurement invariance of the BAS-2 across 65 nations, 40 languages, gender identities, and age groups. Multi-group confirmatory factor analysis indicated that full scalar invariance was upheld across all nations, languages, gender identities, and age groups, suggesting that the unidimensional BAS-2 model has widespread applicability. There were large differences across nations and languages in latent body appreciation, while differences across gender identities and age groups were negligible-to-small. Additionally, greater body appreciation was significantly associated with higher life satisfaction, being single (versus being married or in a committed relationship), and greater rurality (versus urbanicity). Across a subset of nations where nation-level data were available, greater body appreciation was also significantly associated with greater cultural distance from the United States and greater relative income inequality. These findings suggest that the BAS-2 likely captures a near-universal conceptualisation of the body appreciation construct, which should facilitate further cross-cultural research. [Abstract copyright: Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.
Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET
The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR
Transitions of cardio-metabolic risk factors in the Americas between 1980 and 2014
Describing the prevalence and trends of cardiometabolic risk factors that are associated with non-communicable diseases (NCDs) is crucial for monitoring progress, planning prevention, and providing evidence to support policy efforts. We aimed to analyse the transition in body-mass index (BMI), obesity, blood pressure, raised blood pressure, and diabetes in the Americas, between 1980 and 2014
Measurement of nuclear modification factors of ΄(1S), ΄(2S), and ΄(3S) mesons in PbPb collisions at âsNN = 5.02 TeV
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