Labraunda 2018 : Étude d’un poids décoré et d’une couronne. Les apports de la conservation-restauration

International audienceUne unité de conservation-restauration a été intégrée à l’étude du mobilier métallique du site de Labraunda (Carie). Cette association poursuit deux objectifs : constituer un socle documentaire permettant l’exploitation scientifique d’un mobilier en partie inédit et mettre en œuvre les mesures de conservation des artefacts métalliques. Une méthodologie spécifique a été mise en place afin de conjuguer les apports des différentes spécialités. Les résultats de cette implication commune sont présentés à travers l’étude de deux objets exceptionnels issus de contextes de fouille différents : un poids en plomb décoré d’un motif de double hache (découvert en 2017 lors de la fouille menée à l’extérieur des bains Est) et une couronne hellénistique en os et alliage cuivreux dorés à la feuille (découverte anciennement, provenant de la maison terrasse)

Labraunda 2018 : étude d’un poids décoré et d’une couronne

Une unité de conservation-restauration a été intégrée à l’étude du mobilier métallique du site de Labraunda (Carie). Cette association poursuit deux objectifs : constituer un socle documentaire permettant l’exploitation scientifique d’un mobilier en partie inédit et mettre en œuvre les mesures de conservation des artefacts métalliques. Une méthodologie spécifique a été mise en place afin de conjuguer les apports des différentes spécialités. Les résultats de cette implication commune sont présentés à travers l’étude de deux objets exceptionnels issus de contextes de fouille différents : un poids en plomb décoré d’un motif de double hache (découvert en 2017 lors de la fouille menée à l’extérieur des bains Est) et une couronne hellénistique en os et alliage cuivreux dorés à la feuille (découverte anciennement, provenant de la maison terrasse). Labraunda, mobilier métallique, conservation-restauration, méthodologie, poids antique, couronne hellénistiqu

End-to-end P300 BCI using Bayesian accumulation of Riemannian probabilities

International audienceIn brain-computer interfaces (BCI), most of the approaches based on event-related potential (ERP) focus on the detection of P300, aiming for single trial classification for a speller task. While this is an important objective, existing P300 BCI still require several repetitions to achieve a correct classification accuracy. Signal processing and machine learning advances in P300 BCI mostly revolve around the P300 detection part, leaving the character classification out of the scope. To reduce the number of repetitions while maintaining a good character classification, it is critical to embrace the full classification problem. We introduce an end-to-end pipeline, starting from feature extraction, and composed of an ERP-level classification using probabilistic Riemannian MDM which feeds a character-level classification using Bayesian accumulation of confidence across trials. Whereas existing approaches only increase the confidence of a character when it is flashed, our new pipeline, called Bayesian accumulation of Riemannian probabilities (ASAP), update the confidence of each character after each flash. We provide the proper derivation and theoretical reformulation of this Bayesian approach for a seamless processing of information from signal to BCI characters. We demonstrate that our approach performs significantly better than standard methods on public P300 datasets

Spectroscopy of the superconducting proximity effect in nanowires using integrated quantum dots

The superconducting proximity effect has recently attracted a renewed interest as the basis of topologically nontrivial states in materials with a large spin–orbit interaction, with protected boundary states useful for quantum information technologies. However, spectroscopy of these states is challenging because of the limited control of conventional tunnel barriers. Here we report electronic spectroscopy measurements of the proximity gap in a semiconducting indium arsenide nanowire segment coupled to a superconductor, using quantum dots formed deterministically during the crystal growth. We extract characteristic parameters describing the proximity gap, which is suppressed for lower electron densities and fully developed for larger ones. This gate-tunable transition of the proximity effect can be understood as a transition from the long to the short junction regime of subgap bound states in the NW segment. Our device architecture opens up the way to systematic, quantitative spectroscopy studies of subgap states, such as Majorana-bound states

Labraunda 2018

1. Introduction La campagne 2018 des recherches à Labraunda (Fig. 1.1) s’est déroulée du 11 au 29 juin, pour la prospection, et du 15 juillet au 13 septembre pour la fouille. Nous tenons à remercier très chaleureusement les deux représentants du ministère de la Culture et du Tourisme turc, Murat Kaleağasıoğlu pour la prospection et Musa Ötenen pour la fouille. Leur efficacité et leur professionnalisme furent exceptionnels. Fig. 1.1 : Plan général du site de Labraunda O. Henry 2. Administrat..

Multi-Observation Thematic Assembly: existing products and future evolutions

International audience<div> <p><span data-contrast="none">Producing comprehensive information about the ocean has become a top priority to monitor and predict the ocean and climate change.</span><span data-contrast="none"> Complementary to ocean state estimate provided by modelling/assimilation systems, a multi observations-based approach is developed thought the Copernicus Marine Service MultiOBservation Thematic Assembly (</span><span data-contrast="auto">MOB TAC). Recent advances in data fusion techniques and use of machine-learning approach open the possibility of producing estimators of ocean physic and biogeochemistry (BGC) operationally, using input data from diverse sensors, satellites and in-situ programs.</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":160,"335559740":259}"> </span></p> </div> <div> <p><span data-contrast="auto">MOB TAC provides the following multi observations products at global scale: </span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":60,"335559740":259}"> </span></p> </div> <div> <p><span data-contrast="auto">Blue ocean</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":60,"335559740":259}"> </span></p> </div> <div> <div> <ul> <li data-leveltext="" data-font="Wingdings" data-listid="1" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Wingdings","469769242":[9642],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="1" data-aria-level="1"><span data-contrast="auto">3D temperature, salinity, geopotential height and geostrophic current fields, both in near-real-time (NRT) and as long time series (REP=Reprocessing) in delayed-mode;</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":200,"335559740":276}"> </span></li> <li data-leveltext="" data-font="Wingdings" data-listid="1" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Wingdings","469769242":[9642],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="2" data-aria-level="1"><span data-contrast="auto">2D sea surface salinity and sea surface density fields, both in NRT and as REP;</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":200,"335559740":276}"> </span></li> <li data-leveltext="" data-font="Wingdings" data-listid="1" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Wingdings","469769242":[9642],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="3" data-aria-level="1"><span data-contrast="auto">2D total surface and near-surface currents, both in NRT and as REP;</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":200,"335559740":276}"> </span></li> <li data-leveltext="" data-font="Wingdings" data-listid="1" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Wingdings","469769242":[9642],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="4" data-aria-level="1"><span data-contrast="auto">3D Vertical velocity fields as REP;</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":200,"335559740":276}"> </span></li> <li data-leveltext="" data-font="Wingdings" data-listid="1" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Wingdings","469769242":[9642],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="5" data-aria-level="1"><span data-contrast="auto">L2Q and L4 sea surface salinity from SMOS in REP and NRT (only L2Q)</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":200,"335559740":276}"> </span></li> </ul> </div> </div> <div> <div> <p><span data-contrast="auto">Green ocean</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559685":0,"335559739":200,"335559740":276}"> </span></p> </div> <div> <ul> <li data-leveltext="" data-font="Wingdings" data-listid="1" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Wingdings","469769242":[9642],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="1" data-aria-level="1"><span data-contrast="auto">2D surface carbon data sets of FCO2, pCO2, DIC, Alkalinity, saturation states of surface waters with respect to calcite and aragonite as REP;</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":200,"335559740":276}"> </span></li> <li data-leveltext="" data-font="Wingdings" data-listid="1" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Wingdings","469769242":[9642],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="2" data-aria-level="1"><span data-contrast="auto">Nutrient and Carbon vertical distribution (including Nitrates, Phosphates, Silicates, pH, pCO2, Alkalinity, DIC) profiles as REP and NRT;</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":200,"335559740":276}"> </span></li> <li data-leveltext="" data-font="Wingdings" data-listid="1" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Wingdings","469769242":[9642],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="3" data-aria-level="1"><span data-contrast="auto">3D Particulate Organic Carbon (POC), particulate backscattering coefficient (bbp) and Chlorophyll a (Chl-a) fields as REP.</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":200,"335559740":276}"> </span></li> </ul> </div> <div> <p><span data-contrast="auto">Parallel to its portfolio, MOB TAC has and will further develop specific expertise about the integration of multiple satellites and in-situ based observations coming from the other CMEMS TACs and projects. </span><span data-contrast="none">Furthermore, MOB TAC provides specific Ocean Monitoring Indicators (OMIs), based on the above products, to monitor and the global ocean carbon sink. </span></p> </div> </div&gt