We introduce the Automatic Learning for the Rapid Classification of Events (ALeRCE) broker, an astronomical alert broker designed to provide a rapid and self-consistent classification of large etendue telescope alert streams, such as that provided by the Zwicky Transient Facility (ZTF) and, in the future, the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). ALeRCE is a Chilean-led broker run by an interdisciplinary team of astronomers and engineers working to become intermediaries between survey and follow-up facilities. ALeRCE uses a pipeline that includes the real-time ingestion, aggregation, cross-matching, machine-learning (ML) classification, and visualization of the ZTF alert stream. We use two classifiers: a stamp-based classifier, designed for rapid classification, and a light curve-based classifier, which uses the multiband flux evolution to achieve a more refined classification. We describe in detail our pipeline, data products, tools, and services, which are made public for the community (see https://alerce.science). Since we began operating our real-time ML classification of the ZTF alert stream in early 2019, we have grown a large community of active users around the globe. We describe our results to date, including the real-time processing of 1.5 × 10 8 alerts, the stamp classification of 3.4 × 10 7 objects, the light-curve classification of 1.1 × 10 6 objects, the report of 6162 supernova candidates, and different experiments using LSST-like alert streams. Finally, we discuss the challenges ahead in going from a single stream of alerts such as ZTF to a multistream ecosystem dominated by LSST.

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A high percentage of patients with CF also present with IGT. This increases with age and is more common among patients homozygous for the deltaF508 mutation and is not related to clinical status. Alterations in the kinetics of insulin secretion play an important role in the appearance of IGT and CF. We suggest that the OGTT is a more sensitive method than IVGTT for identifying early alterations in CF-related diabetes mellitus.

Although the use of RGB photometry has exploded in the last decades due to the advent of high-quality and inexpensive digital cameras equipped with Bayer-like color filter systems, there is surprisingly no catalogue of bright stars that can be used for calibration purposes. Since due to their excessive brightness, accurate enough spectrophotometric measurements of bright stars typically cannot be performed with modern large telescopes, we have employed historical 13-color medium-narrow-band photometric data, gathered with quite reliable photomultipliers, to fit the spectrum of 1346 bright stars using stellar atmosphere models. This not only constitutes a useful compilation of bright spectrophotometric standards well spread in the celestial sphere, the UCM library of spectrophotometric spectra, but allows the generation of a catalogue of reference RGB magnitudes, with typical random uncertainties ∼0.01 mag. For that purpose, we have defined a new set of spectral sensitivity curves, computed as the median of 28 sets of empirical sensitivity curves from the literature, that can be used to establish a standard RGB photometric system. Conversions between RGB magnitudes computed with any of these sets of empirical RGB curves and those determined with the new standard photometric system are provided. Even though particular RGB measurements from single cameras are not expected to provide extremely accurate photometric data, the repeatability and multiplicity of observations will allow access to a large amount of exploitable data in many astronomical fields, such as the detailed monitoring of light pollution and its impact on the night sky brightness, or the study of meteors, solar system bodies, variable stars, and transient objects. In addition, the RGB magnitudes presented here make the sky an accessible and free laboratory for the calibration of the cameras themselves.

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MEGARA is an IFU & MOS medium-resolution spectrograph that finished its commissioning at the GTC 10m telescope on August 2017. MEGARA is a fiber-fed high-resolution spectrograph with two major units, Fiber-MOS & Spectrograph, that are now located at the Folded-Cass F and Nasmyth-A foci of GTC respectively. These are linked by more than 1200 fibers 44.5m-length split between two observing modes, the LCB (Integral Field Unit, IFU) and a Multi-Object (MOS) capability with 92 robotic positioners each one provided with a mini-bundle of 7 fibers. The spectrograph can accommodate 18 VPHs (11 of them can be simultaneously mounted) covering the visible wavelength range at Resolving Powers between R=6000-20000. This paper presents the sequence of tasks carried out after Laboratory Acceptance at the Universidad Complutense de Madrid to move the whole instrument to the GTC. A detailed day-to-day plan was followed to disassemble, pack, transport, reintegrate the full instrument at the GTC and to verify performance to ensure the instrument was ready for commissioning. The lessons learnt are relevant to other double-focus instruments being developed such as WEAVE@WHT or PFS@Subaru.

This study evaluated the waste generated by a Spanish marble-producing company as adsorbent for the removal of copper (Cu [II]) from aqueous media. Six marble waste sludge samples were studied, and the following operational parameters were analyzed in discontinuous regime, including pollutant concentration, pH, temperature, nature of aqueous medium, and ionic strength. The applicability of the adsorbent material was assessed with experiments in both continuous and discontinuous regimes under close-to-real-life conditions. A pseudo-second order model yielded a better fit to the kinetic data. Application of the intraparticle diffusion model revealed two well-differentiated adsorption stages, in which the external material transfer is negligible and intraparticle diffusion is the controlling stage. The equilibrium study was better fitted to a Freundlich-type isotherm, predicting elevated maximum adsorption values (22.7 mg g−1) at a relatively low initial Cu (II) concentration (25 ppm), yielding a highly favorable chemisorption process (n >> 1). X-ray fluorescence study identified calcite (CaCO3) as the main component of marble waste sludges. According to X-ray diffraction analysis, Cu (II) ion adsorption occurred by intercalation of the metallic cation between CaCO3 layers and by the formation of surface complexes such as CaCO3 and Cu2(CO3)(OH)2. Cu (II) was more effectively removed at medium pH, lower temperature, and lower ionic strength of the aqueous medium. The salinity and dissolved organic matter in surface, ground-, and waste-waters negatively affected the Cu (II) removal process in both continuous and discontinuous regimes by competing for active adsorption sites. These findings demonstrate the applicability and effectiveness of marble-derived waste sludges as low-cost and readily available adsorbents for the treatment of waters polluted by Cu (II) under close-to-real-life conditions.

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