We report the identification of a cluster of galaxies around the high-redshift radio galaxy 3CR184 at z = 0.996. The identification is supported by an excess of galaxies observed in projection in I band images (both in ground-based and HST data), a peak in the redshift distribution comprising 11 galaxies (out of 56 with measured redshifts) in a ∼ 2000 km s −1 velocity interval, and the observation on HST WFPC2 frames of a gravitational arc seen projected at 42h −1 50 kpc away from the central radio galaxy. We thus have strong evidence for the presence of a massive cluster at z ≃ 1. The mass contained within the arc radius is in the range [1.20 × 10 13 h −1 50 M ⊙ , 2.78 × 10 13 h −1 50 M ⊙ ] for z arc within the interval 3-1.5; the corresponding mass to light ratio varies from 56h 50 to 140h 50 . The velocity dispersion deduced from the galaxy cluster redshifts is 634 +206 −102 km s −1 , leading to a virial mass M = 6.16 +3.94 −2.40 × 10 14 h −1 50 M ⊙ and a mass to light ratio 200h 50 < (M/L B ) 400h −1 50 < 500h 50 within a radius of 400h −1 50 kpc.

We report here the spectroscopic identification of galaxies in the neighborhood of the radio-galaxy MRC0316-257, at a redshift z ∼ 3.14. Candidate cluster galaxies were selected from deep V and I images combined with narrow band imaging at the wavelength of redshifted Lyα. Follow-up multi-slit spectroscopy has allowed confirmation of the redshift of the radio-galaxy, z = 3.1420 ± 0.0020, and identification of two associated galaxies at redshifts z = 3.1378 ± 0.0028 and z = 3.1351 ± 0.0028 respectively. The first galaxy is 0.3 h −1 50 Mpc from the radio-galaxy, is resolved with an intrinsic size 11.6 ± h −1 50 kpc, and shows Lyα in emission with rest W Lyα = 55 ± 14Å. In addition, its extremely blue V − I color might possibly indicate a proto-galaxy forming a first generation of stars in a low dust medium. The second galaxy is 1.3 h −1 50 Mpc away from the radio-galaxy, is marginally resolved and, in addition to Lyα in emission, shows CIV in emission with a broad component indicating the contribution from an AGN. The comoving density of galaxies with V < 23.8 and a Lyα flux > 10 −16 ergcm −2 sec −1 in the vicinity of MRC0316-257 is ∼ 2.5 × 10 −3 h 3 50 Mpc −3 , significantly higher than the expected background density of field galaxies with similar properties, and might indicate a rich cluster or proto-cluster environment. These observations indicate that the environment of high redshift radio-galaxies may provide significant numbers of galaxies from which to study the early stages of cluster formation and galaxy evolution.

We use data from the Hipparcos catalog and the Barbier-Brossat & Figon (2000) catalog of stellar radial velocities to test the hypothesis that the β Pic planetesimal disk was disrupted by a close stellar encounter. We trace the space motions of 21,497 stars and discover 18 that have passed within 5 pc of β Pic in the past 1 Myr. β Pic's closest encounter is with the K2III star HIP 27628 (∼0.6 pc), but dynamically the most important encounter is with the F7V star HIP 23693 (∼0.9 pc). We calculate the velocity and eccentricity changes induced by the 18 perturbations and conclude that they are dynamically significant if planetesimals exist in a β Pic Oort cloud. We provide a first-order estimate for the evolutionary state of a β Pic Oort cloud and conclude that the primary role of these stellar perturbations would be to help build a comet cloud rather than destroy a pre-existing structure. The stellar sample is ∼20% complete and motivates future work to identify less common close interactions that would significantly modify the observed circumstellar disk. For future radial velocity study we identify 6 stars in the Hipparcos catalog that may have approached β Pic to within 0.1 pc and therefore remain as candidate disk perturbers.

The rapid progress of deep neural network architectures is allowing both to automate the production of artworks and to extend the domain of creative expression. As such, it is opening new ground for professional and amateur artists alike. A major asset of these new computer processes is their capacity to derive, from a training phase, a generative model from which new artifacts can be produced. This attribute allows for a wide range of novel applications. New music or paintings in the style of famous artists can be produced at the click of a button, or combined to form new artworks. New graphical compositions can be "hallucinated" by the deep algorithmic models to produce striking, unexpected, visual forms. By the same token, the dependence on preexisting, protected, artworks lays the ground for potential zones of friction with the rights holders of the source data that helped shape the generative model. This articulation, between the popular creative movement initiated by the deep neural architectures and the preexisting rights of the authors, leads to a confrontation between the present legal framework for the protection of artistic creations and the new modalities offered by these new technological objects. The present work will address the conditions of protection of creations generated by deep neural networks under the main copyright regimes.

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Tablettes, smartphones, plateformes numériques, objets connectés avec ou sans Intelligence Artificielle (IA) envahissent désormais notre quotidien, transformant nos relations aux autres. Après leur entrée dans le champ du bien-être, depuis quelques années, c’est vers le champ de la santé que se tournent les attentes et les espoirs suscités par ces nouveaux dispositifs technologiques. C’est pourquoi, en 2019, la résolution du Parlement européen sur une politique industrielle européenne globale sur l’intelligence artificielle et la robotique 54 invite à la prudence quant à l’utilisation de procédés algorithmiques dans le champ médical, soulignant que «  le système actuel d’approbation des dispositifs médicaux numériques pourrait ne pas être adapté aux technologies de l’IA  ». En nous appuyant sur le cadre du traitement des apnées du sommeil par ventilation en pression positive continue (PPC), notre réflexion met en lumière le fait que l’augmentation de la masse de données, l’accélération de l’information, la disparité de l’attrait et des compétences en informatique et en IA des acteurs (médecins et patients), ainsi que les effets subjectifs que cela impose, conduisent à la recomposition de la relation médecin/patient et la transformation de la pratique médicale.