New data on the ophiolitic VMS deposits of Moeche (Cabo Ortegal Complex, NW Spain)

As a result of the variscan collision, several allochtonous complexes were emplaced on the Iberian margin in Devonian times, among them the Cabo Ortegal Complex comprising the Moeche ophiolitic sequence. Copper has been won from several mines (Piquitos I & II, Barqueira, Maruxa) from disseminated ores and thin massive sulphide layers in the Moeche Unit, a strongly deformed meta-volcanic sequence comprising mainly quartz-chlorite schists and mylonites, which defines the top of the ophiolite. The ores were metamorphosed and strongly deformed under brittle conditions (for pyrite), but their textures are often apparently post-deformational, due to very common solution-transfer processes; they are composed mostly of pyrite and chalcopyrite, with minor sphalerite, pyrrhotite, etc., and with traces of native gold and PGE. The geology, mineralogy, and geochemistry of the orebodies relate closely to VMS of the Cu-Zn (Cyprus) type. Fluid inclusion studies allowed an estimation of metamorphic conditions at pressures of 2/2’5 kb and T 325/350ºC. New determinations using the chlorite geothermometer yield temperatures around 320 ºC, corresponding to pressures near 2 kb according to the isochores deduced from the fluid inclusion study, although in the Barqueira mine higher temperatures, up to 350 ºC, are found, corresponding to presssures up to 2’5 kb. Pb isotopic compositions of pyrite point to a double source of Pb, i.e. a main mantle and a subordinate crustal source. The values for 87SR/86Sr in pyrite support this interpretation, but some results suggest later mobilization in an open system, corresponding to solution-transfer. Age determinations of pyrite deduced from the Pb isotope uranogenic graph, ≈ 480 Ma, do not fit with the metamorphic ages published for the Moeche Unit, and might point to the age of Pb extraction from the mantle.

Big Data : análisis y estudio de la plataforma Hadoop

Desde el inicio de los tiempos el ser humano ha tenido la necesidad de comprender y analizar todo lo que nos rodea, para ello se ha valido de diferentes herramientas como las pinturas rupestres, la biblioteca de Alejandría, bastas colecciones de libros y actualmente una enorme cantidad de información informatizada. Todo esto siempre se ha almacenado, según la tecnología de la época lo permitía, con la esperanza de que fuera útil mediante su consulta y análisis. En la actualidad continúa ocurriendo lo mismo. Hasta hace unos años se ha realizado el análisis de información manualmente o mediante bases de datos relacionales. Ahora ha llegado el momento de una nueva tecnología, Big Data, con la cual se puede realizar el análisis de extensas cantidades de datos de todo tipo en tiempos relativamente pequeños. A lo largo de este libro, se estudiarán las características y ventajas de Big Data, además de realizar un estudio de la plataforma Hadoop. Esta es una plataforma basada en Java y puede realizar el análisis de grandes cantidades de datos de diferentes formatos y procedencias. Durante la lectura de estas páginas se irá dotando al lector de los conocimientos previos necesarios para su mejor comprensión, así como de ubicarle temporalmente en el desarrollo de este concepto, de su uso, las previsiones y la evolución y desarrollo que se prevé tenga en los próximos años. ABSTRACT. Since the beginning of time, human being was in need of understanding and analyzing everything around him. In order to do that, he used different media as cave paintings, Alexandria library, big amount of book collections and nowadays massive amount of computerized information. All this information was stored, depending on the age and technology capability, with the expectation of being useful though it consulting and analysis. Nowadays they keep doing the same. In the last years, they have been processing the information manually or using relational databases. Now it is time for a new technology, Big Data, which is able to analyze huge amount of data in a, relatively, small time. Along this book, characteristics and advantages of Big Data will be detailed, so as an introduction to Hadoop platform. This platform is based on Java and can perform the analysis of massive amount of data in different formats and coming from different sources. During this reading, the reader will be provided with the prior knowledge needed to it understanding, so as the temporal location, uses, forecast, evolution and growth in the next years.

Pathways to quiescence: SHARDS view on the star formation histories of massive quiescent galaxies at 1.0 < z < 1.5

We present star formation histories (SFHs) for a sample of 104 massive (stellar mass M > 10^10 M_⊙) quiescent galaxies (MQGs) at z = 1.0–1.5 from the analysis of spectrophotometric data from the Survey for High-z Absorption Red and Dead Sources (SHARDS) and HST/WFC3 G102 and G141 surveys of the GOODS-North field, jointly with broad-band observations from ultraviolet (UV) to far-infrared (far-IR). The sample is constructed on the basis of rest-frame UVJ colours and specific star formation rates (sSFRs = SFR/Mass). The spectral energy distributions (SEDs) of each galaxy are compared to models assuming a delayed exponentially declining SFH. A Monte Carlo algorithm characterizes the degeneracies, which we are able to break taking advantage of the SHARDS data resolution, by measuring indices such as MgUV and D4000. The population of MQGs shows a duality in their properties. The sample is dominated (85 per cent) by galaxies with young mass-weighted ages, t_M t_M < 2 Gyr, short star formation time-scales, 〈τ〉 ∼ 60–200 Myr, and masses log(M/M_⊙) ∼ 10.5. There is an older population (15 per cent) with t_M t_M = 2–4 Gyr, longer star formation time-scales, 〈τ〉∼ 400 Myr, and larger masses, log(M/M_⊙) ∼ 10.7. The SFHs of our MQGs are consistent with the slope and the location of the main sequence of star-forming galaxies at z > 1.0, when our galaxies were 0.5–1.0 Gyr old. According to these SFHs, all the MQGs experienced a luminous infrared galaxy phase that lasts for ∼500 Myr, and half of them an ultraluminous infrared galaxy phase for ∼100 Myr. We find that the MQG population is almost assembled at z ∼ 1, and continues evolving passively with few additions to the population.

A massive association around the obscured open cluster RSGC3

Context. Four clusters of red supergiants have been discovered in a region of the Milky Way close to base of the Scutum-Crux Arm and the tip of the Long Bar. Population synthesis models indicate that they must be very massive to harbour so many supergiants. If the clusters are physically connected, this Scutum Complex would be the largest and most massive star-forming region ever identified in the Milky Way. Aims. The spatial extent of one of these clusters, RSGC3, has not been investigated. In this paper we explore the possibility that a population of red supergiants could be located in its vicinity. Methods. We utilised 2MASS JHKS photometry to identify candidate obscured luminous red stars in the vicinity of RSGC3. We observed a sample of candidates with the TWIN spectrograph on the 3.5-m telescope at Calar Alto, obtaining intermediate-resolution spectroscopy in the 8000−9000 Å range. We re-evaluated a number of classification criteria proposed in the literature for this spectral range and found that we could use our spectra to derive spectral types and luminosity classes. Results. We measured the radial velocity of five members of RSGC3, finding velocities similar to the average for members of Stephenson 2. Among the candidates observed outside the cluster, our spectra revealed eight M-type supergiants at distances <18′ from the centre of RSGC3, distributed in two clumps. The southern clump is most likely another cluster of red supergiants, with reddening and age identical to RSGC3. From 2MASS photometry, we identified four likely supergiant members of the cluster in addition to the five spectroscopically observed. The northern clump may be a small cluster with similar parameters. Photometric analysis of the area around RSGC3 suggests the presence of a large (>30) population of red supergiants with similar colours. Conclusions. Our data suggest that the massive cluster RSGC3 is surrounded by an extended association, which may be very massive ( ≳ 105 M⊙). We also show that supergiants in the Scutum Complex may be characterised via a combination of 2MASS photometry and intermediate-to-high-resolution spectroscopy in the Z band.

A VLT/FLAMES survey for massive binaries in Westerlund 1. III. The WC9d binary W239 and implications for massive stellar evolution

Context. There is growing evidence that a treatment of binarity amongst OB stars is essential for a full theory of stellar evolution. However the binary properties of massive stars – frequency, mass ratio & orbital separation – are still poorly constrained. Aims. In order to address this shortcoming we have undertaken a multiepoch spectroscopic study of the stellar population of the young massive cluster Westerlund 1. In this paper we present an investigation into the nature of the dusty Wolf-Rayet star and candidate binary W239. Methods. To accomplish this we have utilised our spectroscopic data in conjunction with multi-year optical and near-IR photometric observations in order to search for binary signatures. Comparison of these data to synthetic non-LTE model atmosphere spectra were used to derive the fundamental properties of the WC9 primary. Results. We found W239 to have an orbital period of only ~5.05 days, making it one of the most compact WC binaries yet identified. Analysis of the long term near-IR lightcurve reveals a significant flare between 2004-6. We interpret this as evidence for a third massive stellar component in the system in a long period (>6 yr), eccentric orbit, with dust production occuring at periastron leading to the flare. The presence of a near-IR excess characteristic of hot (~1300 K) dust at every epoch is consistent with the expectation that the subset of persistent dust forming WC stars are short (<1 yr) period binaries, although confirmation will require further observations. Non-LTE model atmosphere analysis of the spectrum reveals the physical properties of the WC9 component to be fully consistent with other Galactic examples. Conclusions. The simultaneous presence of both short period Wolf-Rayet binaries and cool hypergiants within Wd 1 provides compelling evidence for a bifurcation in the post-Main Sequence evolution of massive stars due to binarity. Short period O+OB binaries will evolve directly to the Wolf-Rayet phase, either due to an episode of binary mediated mass loss – likely via case A mass transfer or a contact configuration – or via chemically homogenous evolution. Conversely, long period binaries and single stars will instead undergo a red loop across the HR diagram via a cool hypergiant phase. Future analysis of the full spectroscopic dataset for Wd 1 will constrain the proportion of massive stars experiencing each pathway; hence quantifying the importance of binarity in massive stellar evolution up to and beyond supernova and the resultant production of relativistic remnants.

The little-studied cluster Berkeley 90 I. LS III +46 11: a very massive O3.5 If* + O3.5 If* binary

Context. It appears that most (if not all) massive stars are born in multiple systems. At the same time, the most massive binaries are hard to find owing to their low numbers throughout the Galaxy and the implied large distances and extinctions. Aims. We want to study LS III +46 11, identified in this paper as a very massive binary; another nearby massive system, LS III +46 12; and the surrounding stellar cluster, Berkeley 90. Methods. Most of the data used in this paper are multi-epoch high S/N optical spectra, although we also use Lucky Imaging and archival photometry. The spectra are reduced with dedicated pipelines and processed with our own software, such as a spectroscopic-orbit code, CHORIZOS, and MGB. Results. LS III +46 11 is identified as a new very early O-type spectroscopic binary [O3.5 If* + O3.5 If*] and LS III +46 12 as another early O-type system [O4.5 V((f))]. We measure a 97.2-day period for LS III +46 11 and derive minimum masses of 38.80 ± 0.83 M⊙ and 35.60 ± 0.77 M⊙ for its two stars. We measure the extinction to both stars, estimate the distance, search for optical companions, and study the surrounding cluster. In doing so, a variable extinction is found as well as discrepant results for the distance. We discuss possible explanations and suggest that LS III +46 12 may be a hidden binary system where the companion is currently undetected.

Radiocarbon data, oxygen isotopic composition in foraminifera, freshwater diatoms data, and salinity estimations from ODP Holes 167-1019C and 167-1019D

Massive discharges of freshwater from the glacial lake Missoula to the northeast Pacific Ocean are thought to have sculpted the Channeled Scablands of eastern Washington and debouched via the Columbia River near 46°N. The dynamics and timing of these events and their impact on northeast Pacific circulation remain uncertain. Here we date marine records of anomalous freshwater inputs to the ocean based on freshwater diatoms, oxygen isotopes in foraminifera, and radiocarbon data. Low-salinity plumes from the Columbia River reduced sea-surface salinities by as much as 6 psu (practical salinity units) more than 400 km away between 16 and 31 cal (calendar) ka B.P. Anomalously high abundances of freshwater diatoms in marine sediments from the region precede generally accepted dates for the existence of glacial Lake Missoula, implying that large flooding or freshwater routing events were common during the advance of the Cordilleran Ice Sheet and that such events require multiple sources.

Collaborative filtering on data streams

Collaborate Filtering is one of the most popular recommendation algorithms. Most Collaborative Filtering algorithms work with a static set of data. This paper introduces a novel approach to providing recommendations using Collaborative Filtering when user rating is received over an incoming data stream. In an incoming stream there are massive amounts of data arriving rapidly making it impossible to save all the records for later analysis. By dynamically building a decision tree for every item as data arrive, the incoming data stream is used effectively although an inevitable trade off between accuracy and amount of memory used is introduced. By adding a simple personalization step using a hierarchy of the items, it is possible to improve the predicted ratings made by each decision tree and generate recommendations in real-time. Empirical studies with the dynamically built decision trees show that the personalization step improves the overall predicted accuracy.

A Comparative Analysis of Predictive Learning Algorithms on High-Dimensional Microarray Cancer Data

This research evaluates pattern recognition techniques on a subclass of big data where the dimensionality of the input space (p) is much larger than the number of observations (n). Specifically, we evaluate massive gene expression microarray cancer data where the ratio κ is less than one. We explore the statistical and computational challenges inherent in these high dimensional low sample size (HDLSS) problems and present statistical machine learning methods used to tackle and circumvent these difficulties. Regularization and kernel algorithms were explored in this research using seven datasets where κ < 1. These techniques require special attention to tuning necessitating several extensions of cross-validation to be investigated to support better predictive performance. While no single algorithm was universally the best predictor, the regularization technique produced lower test errors in five of the seven datasets studied.

Exploring the integration of data mining and data visualization

Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being generated everyday in various applications. The integration of data mining and data visualization has been widely used to analyze these massive and complex data sets to discover hidden patterns. For both data mining and visualization to be effective, it is important to include the visualization techniques in the mining process and to generate the discovered patterns for a more comprehensive visual view. In this dissertation, four related problems: dimensionality reduction for visualizing high dimensional datasets, visualization-based clustering evaluation, interactive document mining, and multiple clusterings exploration are studied to explore the integration of data mining and data visualization. In particular, we 1) propose an efficient feature selection method (reliefF + mRMR) for preprocessing high dimensional datasets; 2) present DClusterE to integrate cluster validation with user interaction and provide rich visualization tools for users to examine document clustering results from multiple perspectives; 3) design two interactive document summarization systems to involve users efforts and generate customized summaries from 2D sentence layouts; and 4) propose a new framework which organizes the different input clusterings into a hierarchical tree structure and allows for interactive exploration of multiple clustering solutions.

Data compilation on the biological response to ocean acidification: environmental and experimental context of data sets and related literature

The exponential growth of studies on the biological response to ocean acidification over the last few decades has generated a large amount of data. To facilitate data comparison, a data compilation hosted at the data publisher PANGAEA was initiated in 2008 and is updated on a regular basis (doi:10.1594/PANGAEA.149999). By January 2015, a total of 581 data sets (over 4 000 000 data points) from 539 papers had been archived. Here we present the developments of this data compilation five years since its first description by Nisumaa et al. (2010). Most of study sites from which data archived are still in the Northern Hemisphere and the number of archived data from studies from the Southern Hemisphere and polar oceans are still relatively low. Data from 60 studies that investigated the response of a mix of organisms or natural communities were all added after 2010, indicating a welcomed shift from the study of individual organisms to communities and ecosystems. The initial imbalance of considerably more data archived on calcification and primary production than on other processes has improved. There is also a clear tendency towards more data archived from multifactorial studies after 2010. For easier and more effective access to ocean acidification data, the ocean acidification community is strongly encouraged to contribute to the data archiving effort, and help develop standard vocabularies describing the variables and define best practices for archiving ocean acidification data.

Measuring star formation in high-z massive galaxies: a mid-infrared to submillimetre study of the GOODS NICMOS Survey sample

We present measurements of the mean mid-infrared to submillimetre flux densities of massive (M_*≳ 10^11 M_⊙) galaxies at redshifts 1.7 < z < 2.9, obtained by stacking positions of known objects taken from the GOODS NICMOS Survey (GNS) catalogue on maps at 24 μm (Spitzer/MIPS); 70, 100 and 160 μm (Herschel/PACS); 250, 350 and 500 μm (BLAST); and 870 μm (LABOCA). A modified blackbody spectrum fit to the stacked flux densities indicates a median [interquartile] star formation rate (SFR) of SFR = 63[48, 81] M_⊙ yr^−1. We note that not properly accounting for correlations between bands when fitting stacked data can significantly bias the result. The galaxies are divided into two groups, disc-like and spheroid-like, according to their Sérsic indices, n. We find evidence that most of the star formation is occurring in n≤ 2 (disc-like) galaxies, with median [interquartile] SFR = 122[100, 150] M_⊙ yr^−1, while there are indications that the n > 2 (spheroid-like) population may be forming stars at a median [interquartile] SFR = 14[9, 20] M_⊙ yr^−1, if at all. Finally, we show that star formation is a plausible mechanism for size evolution in this population as a whole, but find only marginal evidence that it is what drives the expansion of the spheroid-like galaxies.

Oceanographic data, oxygen and methane concentrations, and C-CH4 isotope ratios measured at Jaco Scar

Methane (CH4) concentrations and CH4 stable carbon isotopic composition (d13CCH4) were investigated in the water column within Jaco Scar. It is one of several scars formed by massive slides resulting from the subduction of seamounts offshore Costa Rica, a process that can open up structural and stratigraphical pathways for migrating CH4. The release of large amounts of CH4 into the adjacent water column was discovered at the outcropping lowermost sedimentary sequence of the hanging wall in the northwest corner of Jaco Scar, where concentrations reached up to 1,500 nmol L-1. There CH4-rich fluids seeping from the sedimentary sequence stimulate both growth and activity of a dense chemosynthetic community. Additional point sources supplying CH4 at lower concentrations were identified in density layers above and below the main plume from light carbon isotope ratios. The injected CH4 is most likely a mixture of microbial and thermogenic CH4 as suggested by d13CCH4 values between -50 and -62 per mil Vienna Pee Dee Belemnite. This CH4 spreads along isopycnal surfaces throughout the whole area of the scar, and the concentrations decrease due to mixing with ocean water and microbial oxidation. The supply of CH4 appears to be persistent as repeatedly high CH4 concentrations were found within the scar over 6 years. The maximum CH4 concentration and average excess CH4 concentration at Jaco Scar indicate that CH4 seepage from scars might be as significant as seepage from other tectonic structures in the marine realm. Hence, taking into account the global abundance of scars, such structures might constitute a substantial, hitherto unconsidered contribution to natural CH4 sources at the seafloor.