HAL Université de Savoie
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Angular analysis of decays
No full textInternational audienceAn angular analysis of decays is presented using proton-proton collision data collected by the LHCb experiment at centre-of-mass energies of 7, 8 and 13 TeV, corresponding to an integrated luminosity of 9 fb. The analysis is performed in the region of the dilepton invariant mass squared of 1.1-6.0 GeV. In addition, a test of lepton flavour universality is performed by comparing the obtained angular observables with those measured in decays. In general, the angular observables are found to be consistent with the Standard Model expectations as well as with global analyses of other processes, where is either a muon or an electron. No sign of lepton-flavour-violating effects is observed
Stereograph: Stereoscopic event reconstruction using graph neural networks applied to CTAO
No full textInternational audienceThe CTAO (Cherenkov Telescope Array Observatory) is an international observatory currently under construction. With more than sixty telescopes, it will eventually be the largest and most sensitive ground-based gamma-ray observatory. CTAO studies the high-energy universe by observing gamma rays emitted by violent phenomena (supernovae, black hole environments, etc.). These gamma rays produce an atmospheric shower when entering the atmosphere, which emits faint blue light, observed by CTAO's highly sensitive cameras. The event reconstruction consists of analyzing the images produced by the telescopes to retrieve the physical properties of the incident particle (mainly direction, energy, and type). A standard method for performing this reconstruction consists of combining traditional image parameter calculations with machine learning algorithms, such as random forests, to estimate the particle's energy and class probability for each telescope. A second step, called stereoscopy, combines these monoscopic reconstructions into a global one using weighted averages. In this work, we explore the possibility of using Graph Neural Networks (GNNs) as a suitable solution for combining information from each telescope. The "graph" approach aims to link observations from different telescopes, allowing analysis of the shower from multiple angles and producing a stereoscopic reconstruction of the events. We apply GNNs to CTAO-simulated data from the Northern Hemisphere and show that they are a very promising approach to improving event reconstruction, providing a more performant stereoscopic reconstruction. In particular, we observe better energy and angular resolutions(before event selection) and better separation between gamma photons and protons compared to the Random Forest method
Continuous monitoring of partial discharge activities in power cables and their stimulation due to the temperature rise
No full textInternational audienceAbstract With the development of the power distribution systems demands, the grid reliability becomes a strategic issue. Continuous monitoring of power transmission networks is a key component in addressing this issue. Partial discharge (PD) characterisation instruments provide a reliable solution and an important indicator of the state of cable insulation. An increase in the PD level usually indicates the development of a fault that affects the integrity of the cable and can lead to various problems related to the quality and quantity of the transmitted energy. In this context, the use of Internet of Things (IoT) systems for power networks monitoring can provide a significant improvement to the localisation and detection of faults. In this paper, the authors show the advantages of continuous monitoring of power grid cables using a new IoT based framework using an advanced signal processing technique, namely the phase diagram. Also, the authors show that variations in temperature can impact the initiation and progression of PD, affecting the reliability and lifespan of electrical insulation systems. Understanding this temperature dependence is crucial for accurate PD detection and effective maintenance of power cables. Our results show that higher temperatures can accelerate the PD activity, while lower temperatures may suppress it
Engineering nanostructured electrodes for solid oxide cells (SOCs) via microstructural and electrochemical modelling
No full textInternational audienceThe design optimization of nanostructured-infiltrated electrodes for solid oxide cells was investigated by combining microstructural and electrochemical models. A large dataset of nanostructured electrodes (>70) was synthetically generated through an original approach, which combined validated random field and particle-based frameworks. The electrode microstructural correlations were studied by evaluating the impact of the nanoparticles size and loading on the resulting characteristics of the infiltrated phase (i.e. tortuosity factor, percolating fraction and density of active sites). Eventually, the microstructural properties of selected infiltrated microstructures, holding the highest density of triple phase boundary sites (16-112 μm−2), were used as inputs of a 1D electrochemical model tailored for Ni-YSZ electrodes. The simulated polarization resistances of optimized Ni-infiltrated YSZ backbones resulted to sweep in the 0.012–0.021 Ω⋅cm2 range at 750 °C, thus being considerably lower than the value measured for a classic Ni-YSZ composite cermet, 0.071 Ω⋅cm2. Infiltrated Ni-YSZ composites also resulted to potentially improve the reference electrochemical response, showing polarization resistances in the 0.23–0.32 Ω⋅cm2 range. Nonetheless, the integrated microstructural and electrochemical approach highlighted the crucial importance of the catalyst percolation. Significant performance limitations were evidenced when the percolation of Ni nanoparticles was lower than 50%, due to the insufficient effective transport properties
Evidence for discrete ochre exploitation 35,000 years ago in West Africa
No full textInternational audienceDespite new impetus for Late Pleistocene research in West Africa, little is known about the range of Middle Stone Age behaviours in this region. Yet, the multiplicity of Middle Stone Age lithic technologies testifies to significant behavioural and demographic dynamics, marked by innovation and adaptability. Here, we present the first indepth analysis of ochre remains in West Africa. New data from Toumboura III site, eastern Senegal, dated between 40 ± 3 and 30 ± 3 ka, point towards the use of ochre pieces as part of an occasional and specialized ochre crushing activity, probably dedicated to the production of powders, as well as the use of ochre sticks. Ochre pieces were studied at both macro and microscopic levels and while some of this iron-rich material likely accumulated in the deposits without anthropogenic intervention, another significant set of ochre pieces was found that was likely processed in situ. The impact scars on the pieces are not as striking as grinding traces for evidencing human exploitation. Nonetheless, they cannot be explained by natural phenomena. These remains could represent the earliest known evidence of ochre exploitation in Senegal. They potentially open new perspectives on symbolic behaviours in the Middle Stone Age of West Africa. They show that the full range of human behaviours in this region is yet far from being captured
Les règles de gestion des communautés foncières de montagne
No full textInternational audienceLes règles de gestion des propriétés collectives par les communautés foncières de montagne ont pour objet la préservation et la jouissance pérennes de ressources partagées. Ces règles découlent pour les unes d'usages ancestraux, pour les autres du droit administratif, certaines propriétés collectives étant prises dans un processus de municipalisation. L'étude de ces règles permet de mettre en exergue le rôle reconnu à chacun des protagonistes ainsi que la nécessité de leur évolution afin de répondre aux besoins et objectifs renouvelés de ces communautés
Observation of the and decays
No full textInternational audienceThe first observation of the decay and the most precise measurement of the branching fraction of the decay are reported, using proton-proton collision data from the LHCb experiment collected in 2016--2018 at a centre-of-mass energy of 13~TeV, corresponding to an integrated luminosity of 5.4~fb. Using the and decays as normalisation channels, the ratios of branching fractions are measured to be: where the first uncertainty is statistical and the second systematic
Quaternary landscape evolution of the river Seine (France): Synthesis and new results from ESR dating and magnetostratigraphy of fluvial and cave deposits
No full textInternational audienceIn this paper we present a detailed Quaternary evolution model of the Seine valley (France). The lower Seine valley contains very specific preserved morphological features (semi-entrenched meander cut-offs) and develops in a karstified chalky plateau (Normandy Chalk). Regional geomorphological features make it possible to combine geomorphological observations, petrological investigations as well as cross-dating analysis of fluvial sediments and karstic archives. We have reviewed former chronological data through a combination of different dating methods including ESR, U-series as well as palaeomagnetism. We also present here new dating results from both cave deposits and fluvial terrace sediments through the combined use of quartz ESR dating method and palaeomagnetism. The obtained results show river evolution extending over the entire Quaternary period. The gentle incision rate and its variations highlight the influence of climate and eustatic processes, hence a partially climate-induced uplift. Results also provide new chronological markers on the fluvial deposits for future archaeological research
Endogenous oscillatory rhythms and interactive contingencies jointly influence infant attention during early infant-caregiver interaction
No full textInternational audienceAlmost all early cognitive development takes place in social contexts. At the moment, however, we know little about the neural and cognitive mechanisms that drive infant attention during social interactions. Recording EEG during naturalistic caregiver-infant interactions (N=66), we compare two different accounts. Attentional scaffolding perspectives emphasise the role of the caregiver in structuring the child's behaviour, whilst active learning models focus on motivational factors, endogenous to the infant, that guide their attention. Our results show that, already by 12-months, intrinsic cognitive processes control infants' attention: fluctuations in endogenous oscillatory neural activity associated with changes in infant attentiveness, and predicted the length of infant attention episodes towards objects. In comparison, infant attention was not forwards-predicted by caregiver gaze, or modulations in the spectral and temporal properties of their caregiver's speech. Instead, caregivers rapidly modulated their behaviours in response to changes in infant attention and cognitive engagement, and greater reactive changes associated with longer infant attention. Our findings suggest that shared attention develops through interactive but asymmetric, infantled processes that operate across the caregiver-child dyad. eLife assessment This study reports important evidence that infants' internal factors guide children's attention and that caregivers respond to infants' attentional shifts during caregiverinfant interactions. The authors analyzed EEG data and multiple types of behaviors using solid methodologies that can guide future studies of neural responses during social interaction in infants. However, the analysis is incomplete, as several methodological choices need more adequate justification
Falafels: A tool for Estimating Federated Learning Energy Consumption via Discrete Simulation
No full textInternational audienceThe growth in computational power and data hungriness of Machine Learning has led to an important shift of research efforts towards the distribution of ML models on multiple machines, leading in even more powerful models. However, there exists many Distributed Artificial Intelligence paradigms and for each of them the platform and algorithm configurations play an important role in terms of training time and energy consumption. Many mathematical models and frameworks can respectively predict and benchmark this energy consumption, nonetheless, the former lacks of realism and extensibility while the latter suffers high run-times and actual power consumption. In this article, we introduce Falafels, an extensible tool that predicts the energy consumption and training time of -but not limited to -Federated Learning systems. It distinguishes itself with its discrete-simulatorbased solution leading to nearly instant run-time and fast development of new algorithms. Furthermore, we show this approach permits the use of an evolutionary algorithm providing the ability to optimize the system configuration for a given machine learning workload