École Polytechnique Fédérale de Lausanne

About: École Polytechnique Fédérale de Lausanne is a facility organization based out in Lausanne, Switzerland. It is known for research contribution in the topics: Population & Catalysis. The organization has 44041 authors who have published 98296 publications receiving 4372092 citations. The organization is also known as: EPFL & ETHL.

Eemian interglacial reconstructed from a Greenland folded ice core

Abstract: Efforts to extract a Greenland ice core with a complete record of the Eemian interglacial (130,000 to 115,000 years ago) have until now been unsuccessful. The response of the Greenland ice sheet to the warmer-than-present climate of the Eemian has thus remained unclear. Here we present the new North Greenland Eemian Ice Drilling ('NEEM') ice core and show only a modest ice-sheet response to the strong warming in the early Eemian. We reconstructed the Eemian record from folded ice using globally homogeneous parameters known from dated Greenland and Antarctic ice-core records. On the basis of water stable isotopes, NEEM surface temperatures after the onset of the Eemian (126,000 years ago) peaked at 8 +/- 4 degrees Celsius above the mean of the past millennium, followed by a gradual cooling that was probably driven by the decreasing summer insolation. Between 128,000 and 122,000 years ago, the thickness of the northwest Greenland ice sheet decreased by 400 +/- 250 metres, reaching surface elevations 122,000 years ago of 130 +/- 300 metres lower than the present. Extensive surface melt occurred at the NEEM site during the Eemian, a phenomenon witnessed when melt layers formed again at NEEM during the exceptional heat of July 2012. With additional warming, surface melt might become more common in the future.

Intriguing aspects of lanthanide luminescence

Abstract: The enthralling properties of lanthanide luminescence have propelled luminescent probes, tags and materials based on these elements to the forefront of science and technology. In this minireview, attention is focused on the latest innovations and on less-known aspects of this field. Exciting new developments in bioimaging, therapy, drug delivery, security tags, luminescent sensors, and solar energy conversion are highlighted.

Planck 2013 results. XXIX. The Planck catalogue of Sunyaev-Zeldovich sources

Abstract: We describe the all-sky Planck catalogue of clusters and cluster candidates derived from Sunyaev-Zeldovich (SZ) effect detections using the first 15.5 months of Planck satellite observations. The catalogue contains 1227 entries, making it over six times the size of the Planck Early SZ (ESZ) sample and the largest SZ-selected catalogue to date. It contains 861 confirmed clusters, of which 178 have been confirmed as clusters, mostly through follow-up observations, and a further 683 are previously-known clusters. The remaining 366 have the status of cluster candidates, and we divide them into three classes according to the quality of evidence that they are likely to be true clusters. The Planck SZ catalogue is the deepest all-sky cluster catalogue, with redshifts up to about one, and spans the broadest cluster mass range from (0.1 to 1.6) x 10(15) M-circle dot. Confirmation of cluster candidates through comparison with existing surveys or cluster catalogues is extensively described, as is the statistical characterization of the catalogue in terms of completeness and statistical reliability. The outputs of the validation process are provided as additional information. This gives, in particular, an ensemble of 813 cluster redshifts, and for all these Planck clusters we also include a mass estimated from a newly-proposed SZ-mass proxy. A refined measure of the SZ Compton parameter for the clusters with X-ray counter-parts is provided, as is an X-ray flux for all the Planck clusters not previously detected in X-ray surveys.

Convolutional Neural Networks for Inverse Problems in Imaging: A Review

Abstract: In this article, we review recent uses of convolutional neural networks (CNNs) to solve inverse problems in imaging. It has recently become feasible to train deep CNNs on large databases of images, and they have shown outstanding performance on object classification and segmentation tasks. Motivated by these successes, researchers have begun to apply CNNs to the resolution of inverse problems such as denoising, deconvolution, superresolution, and medical image reconstruction, and they have started to report improvements over state-of-the-art methods, including sparsity-based techniques such as compressed sensing. Here, we review the recent experimental work in these areas, with a focus on the critical design decisions.