The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015–2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14 000 deg² of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance.

The practical deployment of wireless positioning systems requires minimizing the calibration procedures while improving the location estimation accuracy. Received Signal Strength localization techniques using propagation channel models are the simplest alternative, but they are usually designed under the assumption that the radio propagation model is to be perfectly characterized a priori. In practice, this assumption does not hold and the localization results are affected by the inaccuracies of the theoretical, roughly calibrated or just imperfect channel models used to compute location. In this paper, we propose the use of weighted multilateration techniques to gain robustness with respect to these inaccuracies, reducing the dependency of having an optimal channel model. In particular, we propose two weighted least squares techniques based on the standard hyperbolic and circular positioning algorithms that specifically consider the accuracies of the different measurements to obtain a better estimation of the position. These techniques are compared to the standard hyperbolic and circular positioning techniques through both numerical simulations and an exhaustive set of real experiments on different types of wireless networks (a wireless sensor network, a WiFi network and a Bluetooth network). The algorithms not only produce better localization results with a very limited overhead in terms of computational cost but also achieve a greater robustness to inaccuracies in channel modeling.

One of the most remarkable phenomena in loop quantum cosmology is that, at least for homogeneous cosmological models, the big bang is replaced with a big bounce that connects our Universe with a previous branch without passing through a cosmological singularity. The goal of this work is to study the existence of singularities in loop quantum cosmology, including inhomogeneities, and check whether the behavior obtained in the purely homogeneous setting continues to be valid. With this aim, we focus our attention on the three-torus Gowdy cosmologies with linearly polarized gravitational waves and use effective dynamics to carry out the analysis. For this model, we prove that all the potential cosmological singularities are avoided, generalizing the results about resolution of singularities to this scenario with inhomogeneities. We also demonstrate that, if a bounce in the (Bianchi background) volume occurs, the inhomogeneities increase the value of this volume at the bounce with respect to its counterpart in the homogeneous case.

We present the second release of the Meta-catalogue of X-ray detected Clusters of galaxies (hereafter MCXC-II). MCXC-II has been compiled from publicly available ROSAT All Sky Survey-based (NORAS, REFLEX, BCS, SGP, NEP, MACS, CIZA, and RXGCC) and serendipitous (160SD, 400SD, SHARC, WARPS, and EMSS) X-ray cluster catalogues. Redshifts were systematically checked and updated when necessary, with additional redshift information (type and origin) added. The X-ray data were standardised to an overdensity of 500, using a new procedure based on the use of the original flux and aperture measurements available in the input catalogues. MCXC-II contains 2221 entries, now including objects from the REFLEX-II and RXGCC surveys, in addition to providing a complete and fully-homogenised sub-catalogue of all published MACS clusters. Duplicate entries from overlaps between the survey areas of the individual input catalogues were carefully handled. For each cluster, the MCXC-II provides three identifiers: redshift, coordinates, and membership in the original catalogue, along with standardised [0.1–2.4] keV band luminosity, L₅₀₀, total mass, M₅₀₀, and radius, R₅₀₀. Uncertainties on L₅₀₀ were computed from the flux errors in the original catalogues. MCXC-II additionally provides information on overlaps between the input catalogues, reporting the luminosity and its uncertainty when measurements from different surveys are available, along with notes on individual objects.

We present a robust approach to estimating the redshift of galaxies using Pan-STARRS1 photometric data. Our approach is an application of the algorithm proposed for the SDSS Data Release 12. It uses a training set of 2 313 724 galaxies for which the spectroscopic redshift is obtained from SDSS, and magnitudes and colours are obtained from the Pan-STARRS1 Data Release 2 survey. The photometric redshift of a galaxy is then estimated by means of a local linear regression in a 5D magnitude and colour space. Our approach achieves an average bias of Δ̅z̅_n̅o̅r̅m̅ = −1.92 × 10⁻⁴, a standard deviation of σ(Δz_norm) = 0.0299, and an outlier rate of P_o = 4.30% when cross-validating the training set. Even though the relation between each of the Pan-STARRS1 colours and the spectroscopic redshifts is noisier than for SDSS colours, the results obtained by our approach are very close to those yielded by SDSS data. The proposed approach has the additional advantage of allowing the estimation of photometric redshifts on a larger portion of the sky (∼3/4 vs ∼1/3). The training set and the code implementing this approach are publicly available at the project website.

In the last few years, many health monitoring systems have been designed to fullfil the needs of a large range of scenarios. Although many of those systems provide good ad hoc solutions, most of them lack of mechanisms that allow them to be easily reused. This paper is focused on describing an open platform, the micro Web of Things Open Platform (µWoTOP), which has been conceived to improve the connectivity and reusability of context data to deliver different kinds of health, wellness and ambient home care services. µWoTOP is based on a resource-oriented architecture which may be embedded in mobile and resource constrained devices enabling access to biometric, ambient or activity sensors and actuator resources through uniform interfaces defined according to a RESTful fashion. Additionally, µWoTOP manages two communication modes which allow delivering user context information according to different methods, depending on the requirements of the consumer application. It also generates alert messages based on standards related to health care and risk management, such as the Common Alerting Protocol, in order to make its outputs compatible with existing systems.