CO map and steep Kennicutt-Schmidt relation in the extended UV disk of M63

Results from the UV satellite GALEX revealed large extensions of disks in some nearby spiral galaxies, extending out to 3 to 4 times the isophotal radius, r25. M63 is a remarkable example of a spiral galaxy with one of the most extended UV disks, so it offers the opportunity to search for the molecular gas and characterize the star formation in outer disk regions as revealed by the UV emission. We obtained deep CO(1-0) and CO(2-1) observations on the IRAM 30 m telescope along the major axis of the M63 disk from the center out to the galactocentric radius rgal = 1.6 r25 and over a bright UV region at rgal = 1.36 r25. CO(1-0) is detected all along the M63 major axis out to r25, and CO(2-1) is confined to rgal = 0.68 r25, which may betray lower excitation temperatures in the outer disk. CO(1-0) is also detected in the external bright UV region of M63. The radial profiles of the CO emission and of the Halpha, 24 micron, NUV and FUV star formation tracers and HI taken from the literature show a severe drop with the galactocentric radius, such that beyond r25 they are all absent with the exception of a faint UV emission and HI. The CO emission detection in the external UV region, where the UV flux is higher than the UV flux observed beyond r25, highlights a tight correlation between the CO and UV fluxes, namely the amount of molecular gas and the intensity of star formation. This external UV region is dominated by the atomic gas, suggesting that HI is more likely the precursor of H2 rather than the product of UV photodissociation. A broken power law needs to be invoked to describe the Kennicutt-Schmidt (K-S) relation of M63 from the center of the galaxy out to rgal = 1.36 r25. While all along the major axis out to r25 the K-S relation is almost linear, in the external UV region the SFR regime is highly nonlinear and characterized by a steep K-S relation and very low star formation efficiency.Comment: 12 pages, 8 figures, A&A accepte

Comparison of gene coverage of mouse oligonucleotide microarray platforms

BACKGROUND: The increasing use of DNA microarrays for genetical genomics studies generates a need for platforms with complete coverage of the genome. We have compared the effective gene coverage in the mouse genome of different commercial and noncommercial oligonucleotide microarray platforms by performing an in-house gene annotation of probes. We only used information about probes that is available from vendors and followed a process that any researcher may take to find the gene targeted by a given probe. In order to make consistent comparisons between platforms, probes in each microarray were annotated with an Entrez Gene id and the chromosomal position for each gene was obtained from the UCSC Genome Browser Database. Gene coverage was estimated as the percentage of Entrez Genes with a unique position in the UCSC Genome database that is tested by a given microarray platform. RESULTS: A MySQL relational database was created to store the mapping information for 25,416 mouse genes and for the probes in five microarray platforms (gene coverage level in parenthesis): Affymetrix430 2.0 (75.6%), ABI Genome Survey (81.24%), Agilent (79.33%), Codelink (78.09%), Sentrix (90.47%); and four array-ready oligosets: Sigma (47.95%), Operon v.3 (69.89%), Operon v.4 (84.03%), and MEEBO (84.03%). The differences in coverage between platforms were highly conserved across chromosomes. Differences in the number of redundant and unspecific probes were also found among arrays. The database can be queried to compare specific genomic regions using a web interface. The software used to create, update and query the database is freely available as a toolbox named ArrayGene. CONCLUSION: The software developed here allows researchers to create updated custom databases by using public or proprietary information on genes for any organisms. ArrayGene allows easy comparisons of gene coverage between microarray platforms for any region of the genome. The comparison presented here reveals that the commercial microarray Sentrix, which is based on the MEEBO public oligoset, showed the best mouse genome coverage currently available. We also suggest the creation of guidelines to standardize the minimum set of information that vendors should provide to allow researchers to accurately evaluate the advantages and disadvantages of using a given platform

Distributed-memory parallelization of the aggregated unfitted finite element method

The aggregated unfitted finite element method (AgFEM) is a methodology recently introduced in order to address conditioning and stability problems associated with embedded, unfitted, or extended finite element methods. The method is based on removal of basis functions associated with badly cut cells by introducing carefully designed constraints, which results in well-posed systems of linear algebraic equations, while preserving the optimal approximation order of the underlying finite element spaces. The specific goal of this work is to present the implementation and performance of the method on distributed-memory platforms aiming at the efficient solution of large-scale problems. In particular, we show that, by considering AgFEM, the resulting systems of linear algebraic equations can be effectively solved using standard algebraic multigrid preconditioners. This is in contrast with previous works that consider highly customized preconditioners in order to allow one the usage of iterative solvers in combination with unfitted techniques. Another novelty with respect to the methods available in the literature is the problem sizes that can be handled with the proposed approach. While most of previous references discussing linear solvers for unfitted methods are based on serial non-scalable algorithms, we propose a parallel distributed-memory method able to efficiently solve problems at large scales. This is demonstrated by means of a weak scaling test defined on complex 3D domains up to 300M degrees of freedom and one billion cells on 16K CPU cores in the Marenostrum-IV platform. The parallel implementation of the AgFEM method is available in the large-scale finite element package FEMPAR

Distributed-memory parallelization of the aggregated unfitted finite element method

The aggregated unfitted finite element method (AgFEM) is a methodology recently introduced in order to address conditioning and stability problems associated with embedded, unfitted, or extended finite element methods. The method is based on removal of basis functions associated with badly cut cells by introducing carefully designed constraints, which results in well-posed systems of linear algebraic equations, while preserving the optimal approximation order of the underlying finite element spaces. The specific goal of this work is to present the implementation and performance of the method on distributed-memory platforms aiming at the efficient solution of large-scale problems. In particular, we show that, by considering AgFEM, the resulting systems of linear algebraic equations can be effectively solved using standard algebraic multigrid preconditioners. This is in contrast with previous works that consider highly customized preconditioners in order to allow one the usage of iterative solvers in combination with unfitted techniques. Another novelty with respect to the methods available in the literature is the problem sizes that can be handled with the proposed approach. While most of previous references discussing linear solvers for unfitted methods are based on serial non-scalable algorithms, we propose a parallel distributed-memory method able to efficiently solve problems at large scales. This is demonstrated by means of a weak scaling test defined on complex 3D domains up to 300M degrees of freedom and one billion cells on 16K CPU cores in the Marenostrum-IV platform. The parallel implementation of the AgFEM method is available in the large-scale finite element package FEMPAR

Situación Actual del Empleo con Apoyo en España

The article presents a study on the quantitative status of Supported Employment in Spain. It has been developed by the Institute for Community Integration (INICO) of the University of Salamanca in collaboration with Spanish Association for Supported Employment (AESE). Every known program was contacted and relevant information was gathered using a questionnaire. The results of the study show that there are 35 programs in the whole of Spain which have supported 1,389 individuals. In the study, some other factors are analysed: evolution, autonomous community distribution, maintained jobs, persons integrated by type of disability, continuance in the job, support needs, job coaches per post, and participation in European Community funding. Eventually, the study is drawn to an end by a critical analysis of gathered data and some conclusions and suggestions are put forward so as to guide the development of Supported Employment programs

A generic finite element framework on parallel tree-based adaptive meshes

We present highly scalable parallel distributed-memory algorithms and associated data structures for a generic finite element framework that supports h-adaptivity on computational domains represented as multiple connected adaptive trees—forest-of-trees—, thus providing multi-scale resolution on problems governed by partial differential equations.The framework is grounded on a rich representation of the adaptive mesh suitable for generic finite elements that is built on top of a low-level, light-weight forest-oftrees data structure handled by a specialized, highly parallel adaptive meshing engine. Along the way, we have identified the requirements that the forest-of-trees layer must fulfill to be coupled into our framework. Essentially, it must be able to describe neighboring relationships between cells in the adapted mesh (apart from hierarchical relationships) across the lower-dimensional objects at the boundary of the cells. Atop this two-layered mesh representation, we build the rest of data structures required for the numerical integration and assembly of the discrete system of linear equations.We consider algorithms that are suitable for both subassembled and fully-assembled distributed data layouts of linear system matrices. The proposed framework has been implemented within the FEMPAR scientific software library, using p4est as a practical forest-of-octrees demonstrator. A comprehensive strong scaling study of this implementation when applied to Poisson and Maxwell problems reveals remarkable scalability up to 32.2K CPU cores and 482.2M degrees of freedom. Besides, the implementation in FEMPAR of the proposed approach is up to 2.6 and 3.4 times faster than the state-of-the-art deal.II finite element software in the h-adaptive approximation of a Poisson problem with firstand second-order Lagrangian finite elements, respectively (excluding the linear solver step from the comparison)