CEA Bolometer Arrays: the First Year in Space

The CEA/LETI and CEA/SAp started the development of far-infrared filled bolometer arrays for space applications over a decade ago. The unique design of these detectors makes possible the assembling of large focal planes comprising thousands of bolometers running at 300 mK with very low power dissipation. Ten arrays of 16x16 pixels were thoroughly tested on the ground, and integrated in the Herschel/PACS instrument before launch in May 2009. These detectors have been successfully commissioned and are now operating in their nominal environment at the second Lagrangian point of the Earth-Sun system. In this paper we briefly explain the functioning of CEA bolometer arrays, and we present the properties of the detectors focusing on their noise characteristics, the effect of cosmic rays on the signal, the repeatability of the measurements, and the stability of the system

Image synthesis with a convolutional capsule generative adversarial network

Machine learning for biomedical imaging often suffers from a lack of labelled training data. One solution is to use generative models to synthesise more data. To this end, we introduce CapsPix2Pix, which combines convolutional capsules with the pix2pix framework, to synthesise images conditioned on class segmentation labels. We apply our approach to a new biomedical dataset of cortical axons imaged by two-photon microscopy, as a method of data augmentation for small datasets. We evaluate performance both qualitatively and quantitatively. Quantitative evaluation is performed by using image data generated by either CapsPix2Pix or pix2pix to train a U-net on a segmentation task, then testing on real microscopy data. Our method quantitatively performs as well as pix2pix, with an order of magnitude fewer parameters. Additionally, CapsPix2Pix is far more capable at synthesising images of different appearance, but the same underlying geometry. Finally, qualitative analysis of the features learned by CapsPix2Pix suggests that individual capsules capture diverse and often semantically meaningful groups of features, covering structures such as synapses, axons and noise

A cluster of outflows in the Vulpecula Rift

We present $^{12}$CO, $^{13}$CO and C$^{18}$O (J=3$-$2) observations of a new cluster of outflows in the Vulpecula Rift with HARP-B on the JCMT. The mass associated with the outflows, measured using the $^{12}$CO HARP-B observations and assuming a distance to the region of 2.3 kpc, is 129 \msol{}, while the mass associated with the dense gas from C$^{18}$O observations is 458 \msol{} and the associated sub-millimeter core has a mass of 327 $\pm$ 112 \msol{} independently determined from Bolocam 1.1mm data. The outflow-to-core mass ratio is therefore $\sim$0.4, making this region one of the most efficient observed thus far with more than an order of magnitude more mass in the outflow than would be expected based on previous results. The kinetic energy associated with the flows, 94$\times10^{45}$ ergs, is enough to drive the turbulence in the local clump, and potentially unbind the local region altogether. The detection of SiO (J=8$-$7) emission toward the outflows indicates that the flow is still active, and not simply a fossil flow. We also model the SEDs of the four YSOs associated with the molecular material, finding them all to be of mid to early B spectral type. The energetic nature of the outflows and significant reservoir of cold dust detected in the sub-mm suggest that these intermediate mass YSOs will continue to accrete and become massive, rather than reach the main sequence at their current mass.Comment: 11 pages, 8 figures and 3 tables. Accepted to MNRAS. A higher-resolution version of figure 1 will be included in the published version and is available from the authors upon request. Updated with red and blue wings swapped to match doppler shif

Core Reference Sets Of Sorghum And Musa : From A Whole Collection To A Mini Core Collection And Back

The ‘core’ approach for investigating genetic diversity in a crop germplasm collection has proven merits, among which the possibility to choose a sample of manageable size (e.g. a ‘minicore’), so that it can be studied in details, be exchanged.....

Deep reinforcement learning for subpixel neural tracking

Automatically tracing elongated structures, such as axons and blood vessels, is a challenging problem in the field of biomedical imaging, but one with many downstream applications. Real, labelled data is sparse, and existing algorithms either lack robustness to different datasets, or otherwise require significant manual tuning. Here, we instead learn a tracking algorithm in a synthetic environment, and apply it to tracing axons. To do so, we formulate tracking as a reinforcement learning problem, and apply deep reinforcement learning techniques with a continuous action space to learn how to track at the subpixel level. We train our model on simple synthetic data and test it on mouse cortical two-photon microscopy images. Despite the domain gap, our model approaches the performance of a heavily engineered tracker from a standard analysis suite for neuronal microscopy. We show that fine-tuning on real data improves performance, allowing better transfer when real labelled data is available. Finally, we demonstrate that our model's uncertainty measure-a feature lacking in hand-engineered trackers-corresponds with how well it tracks the structure

Важлива складова національної безпеки (Проблеми захисту науково-технічної інформації)

У статті порушується проблема забезпечення захисту інформаційних ресурсів у науково- технічній сфері. Обґрунтовується значення науково-технологічного потенціалу для економічного і соціального розвитку України. Доводиться необхідність ґрунтовної розробки відповідної нормативно-правової бази.The article is dedicated to the problem of ensuring of protection of information resources in scientific-technical sphere, significance of the scientific-technological potential for economical and social growth of Ukraine is grounded. Necessity of well-founded development of correspondent normative and legal base is proved

Diversité agro-morphologique des accessions de fonio [Digitaria exilis (Kippist.) Stapf.] au Niger

La variablité morphologique de 67 accessions de fonio [Digitaria exilis (Kippist.) Stapf.] collectées au Niger a été évaluée au cours de deux  années (2011 et 2012). Seize (16) caractères agro morphologiques (dont 14 caractères quantitatifs et 2 caractères qualitatifs) ont été évalués en station dans deux zones agroécologiques différentes (Tarna en zone sahélo-saharienne et Tara en zone soudanienne). La classification  acsendante hierarchique (CAH) et l’analyse factorielle discriminante (AFD) ont mis en évidence quatre groupes (GI, GII, GIII et GIV). Les accessions du groupe GIV ont en moyenne un cycle de maturité compris entre 85 et 90 jours tandis que les autres groupes présentent un cycle de maturité superieur à 90 jours dans nos conditions expérimentales. Les résultats montrent que les variables les plus discriminantes qui permettent de  décrire la variabilité entre les groupes identifiés sont la biomasse sèche (tige et feuille) par hectare, la longueur des entrenoeuds, le rendement en graine par hectare et dans une certaine mesure le cycle de la plante. L’observation des caractères qualitatifs a montré que cinq accessions (représentant 7% du total) ont des graines non decortiquées de couleur rouge et quatre accessions (6% du total), une tige de couleur rouge. Les caractères analysés peuvent ainsi constituer des critères de base pour différencier les accessions des autres régions de l’Afrique de l’Ouest et servir pour une étude de variabilité entre les restes des accessions de fonio collectées au Niger. Des possiblités d’amélioration peuvent  également être envisagées une fois que le regime de réproduction de l’espèce est bien identifié.Mots clés: Digitaria exilis, variabilité morphologique, accessions, diversité, fonio, Niger

A CHEOPS-enhanced view of the HD 3167 system

Much remains to be understood about the nature of exoplanets smaller than Neptune, most of which have been discovered in compact multi-planet systems. With its inner ultra-short period planet b aligned with the star and two larger outer planets d-c on polar orbits, the multi-planet system HD 3167 features a peculiar architecture and offers the possibility to investigate both dynamical and atmospheric evolution processes. To this purpose we combined multiple datasets of transit photometry and radial velocimetry (RV) to revise the properties of the system and inform models of its planets. This effort was spearheaded by CHEOPS observations of HD 3167b, which appear inconsistent with a purely rocky composition despite its extreme irradiation. Overall the precision on the planetary orbital periods are improved by an order of magnitude, and the uncertainties on the densities of the transiting planets b and c are decreased by a factor of 3. Internal structure and atmospheric simulations draw a contrasting picture between HD 3167d, likely a rocky super-Earth that lost its atmosphere through photo-evaporation, and HD 3167c, a mini-Neptune that kept a substantial primordial gaseous envelope. We detect a fourth, more massive planet on a larger orbit, likely coplanar with HD 3167d-c. Dynamical simulations indeed show that the outer planetary system d-c-e was tilted, as a whole, early in the system history, when HD 3167b was still dominated by the star influence and maintained its aligned orbit. RV data and direct imaging rule out that the companion that could be responsible for the present-day architecture is still bound to the HD 3167 system. Similar global studies of multi-planet systems will tell how many share the peculiar properties of the HD 3167 system, which remains a target of choice for follow-up observations and simulations

Star Formation in the Milky Way. The Infrared View

I present a brief review of some of the most recent and active topics of star formation process in the Milky Way using mid and far infrared observations, and motivated by the research being carried out by our science group using data gathered by the Spitzer and Herschel space telescopes. These topics include bringing together the scaling relationships found in extragalactic systems with that of the local nearby molecular clouds, the synthetic modeling of the Milky Way and estimates of its star formation rate.Comment: 12 pages, 9 figures. To apper in "Cosmic-ray induced phenomenology in star-forming environments: Proceedings of the 2nd Session of the Sant Cugat Forum of Astrophysics" (April 16-19, 2012), Olaf Reimer and Diego F. Torres (eds.

SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry

Every year, millions of brain magnetic resonance imaging (MRI) scans are acquired in hospitals across the world. These have the potential to revolutionize our understanding of many neurological diseases, but their morphometric analysis has not yet been possible due to their anisotropic resolution. We present an artificial intelligence technique, "SynthSR," that takes clinical brain MRI scans with any MR contrast (T1, T2, etc.), orientation (axial/coronal/sagittal), and resolution and turns them into high-resolution T1 scans that are usable by virtually all existing human neuroimaging tools. We present results on segmentation, registration, and atlasing of >10,000 scans of controls and patients with brain tumors, strokes, and Alzheimer's disease. SynthSR yields morphometric results that are very highly correlated with what one would have obtained with high-resolution T1 scans. SynthSR allows sample sizes that have the potential to overcome the power limitations of prospective research studies and shed new light on the healthy and diseased human brain