Composition and Self-Adaptation of Service-Based Systems with Feature Models

The adoption of mechanisms for reusing software in pervasive systems has not yet become standard practice. This is because the use of pre-existing software requires the selection, composition and adaptation of prefabricated software parts, as well as the management of some complex problems such as guaranteeing high levels of efficiency and safety in critical domains. In addition to the wide variety of services, pervasive systems are composed of many networked heterogeneous devices with embedded software. In this work, we promote the safe reuse of services in service-based systems using two complementary technologies, Service-Oriented Architecture and Software Product Lines. In order to do this, we extend both the service discovery and composition processes defined in the DAMASCo framework, which currently does not deal with the service variability that constitutes pervasive systems. We use feature models to represent the variability and to self-adapt the services during the composition in a safe way taking context changes into consideration. We illustrate our proposal with a case study related to the driving domain of an Intelligent Transportation System, handling the context information of the environment.Work partially supported by the projects TIN2008-05932, TIN2008-01942, TIN2012-35669, TIN2012-34840 and CSD2007-0004 funded by Spanish Ministry of Economy and Competitiveness and FEDER; P09-TIC-05231 and P11-TIC-7659 funded by Andalusian Government; and FP7-317731 funded by EU. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

The Redshift Evolution of the Relation between Stellar Mass, Star Formation Rate, and Gas Metallicity of Galaxies

We investigate the relation between stellar mass ($M_\star$), star formation rate (SFR), and metallicity ($Z$) of galaxies, so called the fundamental metallicity relation, in the galaxy sample of the Sloan Digital Sky Survey Data Release 7. We separate the galaxies into narrow redshift bins and compare the relation at different redshifts, and find statistically significant ($> 99$%) evolution. We test various observational effects that might cause seeming $Z$ evolution, and find it difficult to explain the evolution of the relation only by the observational effects. In the current sample of low redshift galaxies, galaxies with different $M_\star$ and SFR are sampled from different redshifts, and there is degeneracy between $M_\star$/SFR and redshift. Hence it is not straightforward to distinguish a relation between $Z$ and SFR from a relation between $Z$ and redshift. The separation of the intrinsic relation from the redshift evolution effect is a crucial issue to understand evolution of galaxies.Comment: 8 pages, 12 figures, 1 table, accepted for publication in ApJ, added discussions about the noise in the galaxy spectr

Forced Oscillations in Fluid Tori and Quasi-Periodic Oscillations

The kilo-Hertz Quasi--Periodic Oscillations in X-ray binaries could originate within the accretion flow, and be a signature of non--linear fluid oscillations and mode coupling in strong gravity. The possibility to decipher these systems will impact our knowledge of fundamental parameters such as the neutron star mass, radius, and spin. Thus they offer the possibility to constrain the nuclear equation of state and the rotation parameter of stellar--mass black holes. We review the general properties of these oscillations from a hydrodynamical point of view, when the accretion flow is subject to external perturbations and summarize recent results.Comment: Astronomische Nachrichten, in pres

Modelling long term trend and local spatial correlation: a mixed penalized spline and spatial econometrics approach

In this work we propose the combination of P-splines with traditional spatial econometric models in such a way that it allows for their representation as a mixed model. The advantages of combining these models include: (i) dealing with complex non-linear and non-separable trends, (ii) estimating short-range spatial correlation together with the large-scale spatial trend, (iii) decomposing the systematic spatial variation into those two components and (iv) estimating the smoothing parameters included in the penalized splines together with the other parameters of the model. The performance of the proposed spatial non-parametric models is checked by both simulation and a empirical study. More specifically, we simulate 3,600 datasets generated by those models (with both linear and non-linear-non-separable global spatial trends). As for the empirical case, we use the well-known Lucas county data on housing prices. Our results indicate that the proposed models have a better performance than the traditional spatial strategies, specially in the presence of nonlinear tren

Quantitative trait loci for a neurocranium deformity, lack of opercullum, in gilthead seabream (Sparus aurata L.)

Lack of operculum, a neurocranial deformity, is the most common external abnormality to be found among industrially produced gilthead seabream (Sparus aurata L.), and this entails significant financial losses. This study conducts, for the first time in this species, a quantitative trait loci (QTL) analysis of the lack of operculum. A total of 142 individuals from a paternal half-sibling family (six full-sibling families) were selected for QTL mapping. They had previously shown a highly significant association with the prevalence of lack of operculum in a segregation analysis. All the fish were genotyped for 106 microsatellite markers using a set of multiplex PCRs (ReMsa1–ReMsa13). A linear regression methodology was used for the QTL analysis. Four QTL were detected for this deformity, two of which (QTLOP1 and QTLOP2) were significant. They were located at LG (linkage group) nine and LG10 respectively. Both QTL showed a large effect (about 27%), and furthermore, the association between lack of operculum and sire allelic segregation observed was statistically significant in the QTLOP1 analysis. These results represent a significant step towards including marker-assisted selection for this deformity in genetic breeding programmes to reduce the incidence of the deformity in the species

The surface chemistry of nanocrystalline MgO catalysts for FAME production:an in situ XPS study of H2O, CH3OH and CH3OAc adsorption

An in situ XPS study of water, methanol and methyl acetate adsorption over as-synthesised and calcined MgO nanocatalysts is reported with a view to gaining insight into the surface adsorption of key components relevant to fatty acid methyl esters (biodiesel) production during the transesterification of triglycerides with methanol. High temperature calcined NanoMgO-700 adsorbed all three species more readily than the parent material due to the higher density of electron-rich (111) and (110) facets exposed over the larger crystallites. Water and methanol chemisorb over the NanoMgO-700 through the conversion of surface O2 − sites to OH− and coincident creation of Mg-OH or Mg-OCH3 moieties respectively. A model is proposed in which the dissociative chemisorption of methanol occurs preferentially over defect and edge sites of NanoMgO-700, with higher methanol coverages resulting in physisorption over weakly basic (100) facets. Methyl acetate undergoes more complex surface chemistry over NanoMgO-700, with C–H dissociation and ester cleavage forming surface hydroxyl and acetate species even at extremely low coverages, indicative of preferential adsorption at defects. Comparison of C 1s spectra with spent catalysts from tributyrin transesterification suggest that ester hydrolysis plays a key factor in the deactivation of MgO catalysts for biodiesel production

Precision abundance analysis of bright HII galaxies

We present high signal-to-noise spectrophotometric observations of seven luminous HII galaxies. The observations have been made with the use of a double-arm spectrograph which provides spectra with a wide wavelength coverage, from 3400 to 10400\AA free of second order effects, of exactly the same region of a given galaxy. These observations are analysed applying a methodology designed to obtain accurate elemental abundances of oxygen, sulphur, nitrogen, neon, argon and iron in the ionized gas. Four electron temperatures and one electron density are derived from the observed forbidden line ratios using the five-level atom approximation. For our best objects errors of 1% in t_e([OIII]), 3% in t_e([OII]) and 5% in t_e([SIII]) are achieved with a resulting accuracy of 7% in total oxygen abundances, O/H. The ionisation structure of the nebulae can be mapped by the theoretical oxygen and sulphur ionic ratios, on the one side, and the corresponding observed emission line ratios, on the other -- the \eta and \eta' plots --. The combination of both is shown to provide a means to test photo-ionisation model sequences currently applied to derive elemental abundances in HII galaxies.Comment: 24 pages, 8 figures, accepted by MNRA

Neon and Argon optical emission lines in ionized gaseous nebulae: Implications and applications

In this work we present a study of the strong optical collisional emission lines of Ne and Ar in an heterogeneous sample of ionized gaseous nebulae for which it is possible to derive directly the electron temperature and hence the chemical abundances of neon and argon. We calculate using a grid of photoionization models new ionization correction factors for these two elements and we study the behaviour of Ne/O and Ar/O abundance ratios with metallicity. We find a constant value for Ne/O, while there seems to be some evidence for the existence of negative radial gradients of Ar/O over the disks of some nearby spirals. We study the relation between the intensities of the emission lines of [NeIII] at 3869 \AA and [OIII] at 4959 \AA and 5007 \AA. This relation can be used in empirical calibrations and diagnostic ratios extending their applicability to bluer wavelengths and therefore to samples of objects at higher redshifts. Finally, we propose a new diagnostic using [OII], [NeIII] and Hdelta emission lines to derive metallicities for galaxies at high z.Comment: 12 pages, 12 figures, accepted for publication in Monthly Notices of the Royal Astronomical Societ

The impact of the nitrogen-to-oxygen ratio on ionized nebulae diagnostics based on [NII] emission lines

We study the relation between nitrogen and oxygen abundances as a function of metallicity for a sample of emission-line objects for which a direct measurement of the metallicity has been possible. This sample is representative of the very different conditions in ionization and chemical enrichement that we can find in the Universe. We first construct the N/O vs. O/H diagram and we discuss its large dispersion at all metallicity regimes. Using the same sample and a large grid of photoionization models covering very different values of the N/O ratio, we then study the most widely used strong-line calibrators of metallicity based on [NII] emission lines, such as N2 and O3N2. We demonstrate that these parameters underestimate the metallicity at low N/O ratios and viceversa. We investigate also the effect of the N/O ratio on different diagnostic diagrams used to discriminate narrow-line AGNs from star forming regions, such as the [OIII]/Hbeta vs. [NII}]/Halpha, and we show that a large fraction of the galaxies catalogued as composite in this diagram can be, in fact, star forming galaxies with a high value of the N/O ratio. Finally, using strong-line methods sensitive to the N/O abundance ratio, like N2O2 and N2S2, we investigate the relation between this ratio and the stellar mass for the galaxies of the SDSS. We find, as in the case of the mass-metallicity relation, a correlation between these two quantities and a flattening of the relation for the most massive galaxies, which could be a consequence of the enhancement of the dispersion of N/O in the high metallicity regime.Comment: 12 pages, 13 figures. Accepted for publication in Monthly Notices of the Royal Astronomical Societ

Can input reconstruction be used to directly estimate uncertainty of a regression U-Net model? -- Application to proton therapy dose prediction for head and neck cancer patients

Estimating the uncertainty of deep learning models in a reliable and efficient way has remained an open problem, where many different solutions have been proposed in the literature. Most common methods are based on Bayesian approximations, like Monte Carlo dropout (MCDO) or Deep ensembling (DE), but they have a high inference time (i.e. require multiple inference passes) and might not work for out-of-distribution detection (OOD) data (i.e. similar uncertainty for in-distribution (ID) and OOD). In safety critical environments, like medical applications, accurate and fast uncertainty estimation methods, able to detect OOD data, are crucial, since wrong predictions can jeopardize patients safety. In this study, we present an alternative direct uncertainty estimation method and apply it for a regression U-Net architecture. The method consists in the addition of a branch from the bottleneck which reconstructs the input. The input reconstruction error can be used as a surrogate of the model uncertainty. For the proof-of-concept, our method is applied to proton therapy dose prediction in head and neck cancer patients. Accuracy, time-gain, and OOD detection are analyzed for our method in this particular application and compared with the popular MCDO and DE. The input reconstruction method showed a higher Pearson correlation coefficient with the prediction error (0.620) than DE and MCDO (between 0.447 and 0.612). Moreover, our method allows an easier identification of OOD (Z-score of 34.05). It estimates the uncertainty simultaneously to the regression task, therefore requires less time or computational resources.Comment: 11 pages, 3 figures and 3 Table