A Framework for Building Hypercubes Using MapReduce

The European Space Agency's Gaia mission will create the largest and most precise three dimensional chart of our galaxy (the Milky Way), by providing unprecedented position, parallax, proper motion, and radial velocity measurements for about one billion stars. The resulting catalogue will be made available to the scientific community and will be analyzed in many different ways, including the production of a variety of statistics. The latter will often entail the generation of multidimensional histograms and hypercubes as part of the precomputed statistics for each data release, or for scientific analysis involving either the final data products or the raw data coming from the satellite instruments. In this paper we present and analyze a generic framework that allows the hypercube generation to be easily done within a MapReduce infrastructure, providing all the advantages of the new Big Data analysis paradigmbut without dealing with any specific interface to the lower level distributed system implementation (Hadoop). Furthermore, we show how executing the framework for different data storage model configurations (i.e. row or column oriented) and compression techniques can considerably improve the response time of this type of workload for the currently available simulated data of the mission. In addition, we put forward the advantages and shortcomings of the deployment of the framework on a public cloud provider, benchmark against other popular solutions available (that are not always the best for such ad-hoc applications), and describe some user experiences with the framework, which was employed for a number of dedicated astronomical data analysis techniques workshops.

A Framework for Building Hypercubes Using MapReduce

The European Space Agency's Gaia mission will create the largest and most precise three dimensional chart of our galaxy (the Milky Way), by providing unprecedented position, parallax, proper motion, and radial velocity measurements for about one billion stars. The resulting catalogue will be made available to the scientific community and will be analyzed in many different ways, including the production of a variety of statistics. The latter will often entail the generation of multidimensional histograms and hypercubes as part of the precomputed statistics for each data release, or for scientific analysis involving either the final data products or the raw data coming from the satellite instruments. In this paper we present and analyze a generic framework that allows the hypercube generation to be easily done within a MapReduce infrastructure, providing all the advantages of the new Big Data analysis paradigmbut without dealing with any specific interface to the lower level distributed system implementation (Hadoop). Furthermore, we show how executing the framework for different data storage model configurations (i.e. row or column oriented) and compression techniques can considerably improve the response time of this type of workload for the currently available simulated data of the mission. In addition, we put forward the advantages and shortcomings of the deployment of the framework on a public cloud provider, benchmark against other popular solutions available (that are not always the best for such ad-hoc applications), and describe some user experiences with the framework, which was employed for a number of dedicated astronomical data analysis techniques workshops.

Feasibility of direct mapping of cerebral fluorodeoxy-D-glucose metabolism in situ at subcellular resolution using soft X-ray fluorescence.

Glucose metabolism is difficult to image with cellular resolution in mammalian brain tissue, particularly with (18) fluorodeoxy-D-glucose (FDG) positron emission tomography (PET). To this end, we explored the potential of synchrotron-based low-energy X-ray fluorescence (LEXRF) to image the stable isotope of fluorine (F) in phosphorylated FDG (DG-6P) at 1 μm(2) spatial resolution in 3-μm-thick brain slices. The excitation-dependent fluorescence F signal at 676 eV varied linearly with FDG concentration between 0.5 and 10 mM, whereas the endogenous background F signal was undetectable in brain. To validate LEXRF mapping of fluorine, FDG was administered in vitro and in vivo, and the fluorine LEXRF signal from intracellular trapped FDG-6P over selected brain areas rich in radial glia was spectrally quantitated at 1 μm(2) resolution. The subsequent generation of spatial LEXRF maps of F reproduced the expected localization and gradients of glucose metabolism in retinal Müller glia. In addition, FDG uptake was localized to periventricular hypothalamic tanycytes, whose morphological features were imaged simultaneously by X-ray absorption. We conclude that the high specificity of photon emission from F and its spatial mapping at ≤1 μm resolution demonstrates the ability to identify glucose uptake at subcellular resolution and holds remarkable potential for imaging glucose metabolism in biological tissue. © 2012 Wiley Periodicals, Inc.

Comparative genome analysis of Pseudomonas knackmussii B13, the first bacterium known to degrade chloroaromatic compounds.

Pseudomonas knackmussii B13 was the first strain to be isolated in 1974 that could degrade chlorinated aromatic hydrocarbons. This discovery was the prologue for subsequent characterization of numerous bacterial metabolic pathways, for genetic and biochemical studies, and which spurred ideas for pollutant bioremediation. In this study, we determined the complete genome sequence of B13 using next generation sequencing technologies and optical mapping. Genome annotation indicated that B13 has a variety of metabolic pathways for degrading monoaromatic hydrocarbons including chlorobenzoate, aminophenol, anthranilate and hydroxyquinol, but not polyaromatic compounds. Comparative genome analysis revealed that B13 is closest to Pseudomonas denitrificans and Pseudomonas aeruginosa. The B13 genome contains at least eight genomic islands [prophages and integrative conjugative elements (ICEs)], which were absent in closely related pseudomonads. We confirm that two ICEs are identical copies of the 103 kb self-transmissible element ICEclc that carries the genes for chlorocatechol metabolism. Comparison of ICEclc showed that it is composed of a variable and a 'core' region, which is very conserved among proteobacterial genomes, suggesting a widely distributed family of so far uncharacterized ICE. Resequencing of two spontaneous B13 mutants revealed a number of single nucleotide substitutions, as well as excision of a large 220 kb region and a prophage that drastically change the host metabolic capacity and survivability.

Red blood cell-derived microparticles isolated from blood units initiate and propagate thrombin generation.

BACKGROUND: Red blood cell-derived microparticles (RMPs) are small phospholipid vesicles shed from RBCs in blood units, where they accumulate during storage. Because microparticles are bioactive, it could be suggested that RMPs are mediators of posttransfusion complications or, on the contrary, constitute a potential hemostatic agent. STUDY DESIGN AND METHODS: This study was performed to establish the impact on coagulation of RMPs isolated from blood units. Using calibrated automated thrombography, we investigated whether RMPs affect thrombin generation (TG) in plasma. RESULTS: We found that RMPs were not only able to increase TG in plasma in the presence of a low exogenous tissue factor (TF) concentration, but also to initiate TG in plasma in absence of exogenous TF. TG induced by RMPs in the absence of exogenous TF was neither affected by the presence of blocking anti-TF nor by the absence of Factor (F)VII. It was significantly reduced in plasma deficient in FVIII or F IX and abolished in FII-, FV-, FX-, or FXI-deficient plasma. TG was also totally abolished when anti-XI 01A6 was added in the sample. Finally, neither Western blotting, flow cytometry, nor immunogold labeling allowed the detection of traces of TF antigen. In addition, RMPs did not comprise polyphosphate, an important modulator of coagulation. CONCLUSIONS: Taken together, our data show that RMPs have FXI-dependent procoagulant properties and are able to initiate and propagate TG. The anionic surface of RMPs might be the site of FXI-mediated TG amplification and intrinsic tenase and prothrombinase complex assembly.

Chemical and isotopic equilibrium between CO2 and CH4 in fumarolic gas discharges: Generation of CH4 in arc magmatic-hydrothermal systems

The chemical and isotopic composition of fumarolic gases emitted from Nisyros Volcano, Greece, and of a single gas sample from Vesuvio, Italy, was investigated in order to determine the origin of methane (CH,) within two subduction-related magmatic-hydrothermal environments. Apparent temperatures derived from carbon isotope partitioning between CH4 and CO2 of around 340degreesC for Nisyros and 470degreesC for Vesuvio correlate well with aquifer temperatures as measured directly and/or inferred from compositional data using the H2O-H-2-CO2-CO-CH4 geothermometer. Thermodynamic modeling reveals chemical equilibrium between CH4, CO2 and H2O implying that carbon isotope partitioning between CO2 and CH, in both systems is controlled by aquifer temperature. N-2/(3) He and CH4/(3) He ratios of Nisyros fumarolic gases are unusually low for subduction zone gases and correspond to those of midoceanic ridge environments. Accordingly, CH4 may have been primarily generated through the reduction of CO, by H, in the absence of any organic matter following a Fischer-Tropsch-type reaction. However, primary occurrence of minor amounts of thermogenic CH4 and subsequent re-equilibration with co-existing CO2 cannot be ruled out entirely- CO2/He-3 ratios and delta(13)C(CO2) values imply that the evolved CO2 either derives from a metasomatized mantle or is a mixture between two components, one outgassing from an unaltered mantle and the other released by thermal breakdown of marine carbonates. The latter may contain traces of organic matter possibly decomposing to CH4 during thermometamorphism. Copyright (C) 2004 Elsevier Ltd.

Inferring the mode of origin of polyploid species from next-generation sequence data.

Many eukaryote organisms are polyploid. However, despite their importance, evolutionary inference of polyploid origins and modes of inheritance has been limited by a need for analyses of allele segregation at multiple loci using crosses. The increasing availability of sequence data for nonmodel species now allows the application of established approaches for the analysis of genomic data in polyploids. Here, we ask whether approximate Bayesian computation (ABC), applied to realistic traditional and next-generation sequence data, allows correct inference of the evolutionary and demographic history of polyploids. Using simulations, we evaluate the robustness of evolutionary inference by ABC for tetraploid species as a function of the number of individuals and loci sampled, and the presence or absence of an outgroup. We find that ABC adequately retrieves the recent evolutionary history of polyploid species on the basis of both old and new sequencing technologies. The application of ABC to sequence data from diploid and polyploid species of the plant genus Capsella confirms its utility. Our analysis strongly supports an allopolyploid origin of C. bursa-pastoris about 80 000 years ago. This conclusion runs contrary to previous findings based on the same data set but using an alternative approach and is in agreement with recent findings based on whole-genome sequencing. Our results indicate that ABC is a promising and powerful method for revealing the evolution of polyploid species, without the need to attribute alleles to a homeologous chromosome pair. The approach can readily be extended to more complex scenarios involving higher ploidy levels.

Yield QTL analysis of Oryza sativa x O. glumaepatula introgression lines

The objective of this work was to evaluate the yield performance of two generations (BC2F2 and BC2F9) of introgression lines developed from the interspecific cross between Oryza sativa and O. glumaepatula, and to identify the SSR markers associated to yield. The wild accession RS‑16 (O. glumaepatula) was used as donor parent in the backcross with the high yielding cultivar Cica‑8 (O. sativa). A set of 114 BC2F1 introgression lines was genotyped with 141 polymorphic SSR loci distributed across the whole rice genome. Molecular analysis showed that in average 22% of the O. glumaepatula genome was introgressed into BC2F1 generation. Nine BC2F9 introgression lines had a significantly higher yield than the genitor Cica‑8, thus showing a positive genome interaction among cultivated rice and the wild O. glumaepatula. Seven QTL were identified in the overall BC2F2, with one marker interval (4879‑EST20) of great effect on yield. The alleles with positive effect on yield came from the cultivated parent Cica‑8.

Beyond the Net Generation debate: A comparison between digital learners in face-to-face and virtual universities

This paper is based on the hypothesis that the use of technology to support learning is not related to whether a student belongs to the Net Generation, but that it is mainly influenced by the teaching model. The study compares behaviour and preferences towards ICT use in two groups of university students: face-to-face students and online students. A questionnaire was applied to asample of students from five universities with different characteristics (one offers online education and four offer face-to-face education with LMS teaching support).

Fully Distributed Cooperative Spectrum Sensing for Cognitive Radio Networks

Cognitive radio networks (CRN) sense spectrum occupancy and manage themselves to operate in unused bands without disturbing licensed users. The detection capability of a radio system can be enhanced if the sensing process is performed jointly by a group of nodes so that the effects of wireless fading and shadowing can be minimized. However, taking a collaborative approach poses new security threats to the system as nodes can report false sensing data to force a wrong decision. Providing security to the sensing process is also complex, as it usually involves introducing limitations to the CRN applications. The most common limitation is the need for a static trusted node that is able to authenticate and merge the reports of all CRN nodes. This paper overcomes this limitation by presenting a protocol that is suitable for fully distributed scenarios, where there is no static trusted node.