Multiwavelength analysis of the Lyman alpha emitting galaxy Haro 2: relation between the diffuse Lyman alpha and soft X-ray emissions

In order to use Lyman alpha (Lya) emission as star formation tracer in cosmological studies, we must understand how the resonant scattering affects the escape fraction of the Lya photons. Thus, high spatial resolution multiwavelength studies of nearby Lya emitters, like Haro 2, are highly needed. For that purpose, we have used Chandra X-ray and HST (UV, optical and NIR) images of Haro 2, and STIS and ground-based spectral images along its major and minor axes, to characterize the Lya emission and the properties of the stellar population. The UV, Ha (Halpha) and FIR luminosities of the Haro 2 nuclear starburst are reproduced using evolutionary synthesis models assuming a young stellar population with ages ~3.5-5.0 Myr, affected by differential interstellar extinctions. The observed X-ray emission is attributed to gas heated by the mechanical energy released by the starburst (soft component) and a Ultra-Luminous X-ray source candidate (hard). Both compact and diffuse Lya components are observed. Whereas Lya is spatially decoupled from Balmer lines emission, Balmer decrement and UV continuum, the diffuse Lya component is spatially correlated with the diffuse soft X-ray emission. Moreover, unlike the compact one, diffuse Lya shows luminosities larger than predicted from Ha, assuming case B recombination and dust extinction as derived from Ha/Hbeta. We propose that, whereas the compact Lya emission is associated to the massive stellar clusters and is affected by outflows and dust extinction, the diffuse Lya originates in gas ionized by the hot plasma responsible for the soft X-ray radiation, as suggested by their spatial correlation and by the measured L(Ha)/LsoftX ratios. Calibration of Lya as star formation rate tracer should therefore include both effects (destruction vs. enhancement) to avoid biases in the study of galaxies at cosmological distances.Comment: Accepted for publication in A&A, 18 pages, 8 figures, 9 tables. If problems with quality of images, see http://www.cab.inta-csic.es/users/otih/haro2-v63.clean.pd

Physical properties and evolutionary state of the Lyman alpha emitting starburst galaxy IRAS 08339+6517

Though Lyman alpha emission (Lya) is one of the most used tracers of massive star formation at high redshift, a correct understanding of radiation transfer effects by neutral gas is required to properly quantify the star formation rate along the history of the Universe. We are embarked in a program to study the properties of the Lya emission (spectral profile, spatial distribution, relation to Balmer lines intensity,...) in several local starburst galaxies. We present here the results obtained for IRAS 08339+6517. Using evolutionary population synthesis models, we have characterized the properties of the starburst (UV continuum, Halpha, total infrared and X-ray emissions, etc.), which transformed 1.4e+8 Mo of gas into stars around 5-6 Myr ago. In addition to the central compact emission blob, we have identified a diffuse Lya emission component smoothly distributed over the whole central area of IRAS 08339+6517. This diffuse emission is spatially decoupled from the UV continuum, the Halpha emission or the Halpha/Hbeta ratio. Both locally and globally, the Lya/Halpha ratio is lower than the Case B predictions, even after reddening correction, with an overall Lya escape fraction of only 4%. We conclude that in IRAS 08339+6517 the resonant scattering of Lya photons by an outflowing shell of neutral gas causes their highly-efficient destruction by dust, which explains the low Lya escape fraction measured. These results stress again the importance of a proper correction of scattering and transfer effects when using Lya to derive the star formation rate in high-redshift galaxies.Comment: Accepted for publication in A&A, 17 pages, 13 figures, 8 tables. If problems with quality of images, see https://cloud.cab.inta-csic.es/public.php?service=files&file=%2Fotih%2Ffiles%2Foti_mas%2Firas%2Firas-v53.ack_referee.pd

A framework for the utilization of Building Management System data in building information models for building design and operation

Research on digitizing the various aspects of a typical building project has been on the increase since the advent of Building Information Modelling (BIM). Most efforts build on information technology capabilities already achieved in the various professional domains associated with different stages of the building life cycle. It is predicted that BIM will help to drastically reduce errors, fast-track project delivery time and save implementation costs. As such BIM is now being utilized in the various professional domains and project stages. However, research suggests that the building operation and management stage is being left behind despite the abundance of data collected using building management systems (BMS) of varying degrees of sophistication. It is therefore important to consider exploring BIM applications that encompasses the building operation phase. This will enhance the evaluation of building performance in use and provide feedback to the design stage which could help eliminate design-related performance issues. A framework for utilizing feedback loops from building energy consumption to inform and improve design and facility management in a BIM environment is therefore proposed. A prototype illustrating the framework is implemented in. NET framework interfaced with a BIM-enabled tool and tested in the refinement of a pre-designed school using data from the operations phase of another school delivered previously. We conclude that the framework developed in this research can contribute to bridging existing gaps between the design, construction and operation phases of a building's life-cycle

Coronagraphic mask design using Hermite functions

We introduce a stellar coronagraph that uses a coronagraphic mask described by a Hermite function or a combination of them. It allows the detection of exoplanets providing both deep starlight extinction and high angular resolution. This angular resolution depends on the order of the Hermite function used. An analysis of the coronagraph performance is carried out for different even order masks. Numerical simulations of the ideal case, with no phase errors and perfect telescope pointing, show that on-axis starlight is reduced to very low intensity levels corresponding to a gain of at least 25 magnitudes (10−10 light intensity reduction). The coronagraphic throughput depends on the Hermite function or combination selected. The proposed mask series presents the same advantages of band limited masks along with the benefit of reducing the light diffracted by the mask border thanks to its particular shape. Nevertheless, for direct detection of Earth-like exoplanets it requires the use of adaptive optics facilities for compensating the perturbations introduced by the atmosphere and by the optical system

DADA: Degree-Aware Algorithms for Network-Based Disease Gene Prioritization

<p>Abstract</p> <p>Background</p> <p>High-throughput molecular interaction data have been used effectively to prioritize candidate genes that are linked to a disease, based on the observation that the products of genes associated with similar diseases are likely to interact with each other heavily in a network of protein-protein interactions (PPIs). An important challenge for these applications, however, is the incomplete and noisy nature of PPI data. Information flow based methods alleviate these problems to a certain extent, by considering indirect interactions and multiplicity of paths.</p> <p>Results</p> <p>We demonstrate that existing methods are likely to favor highly connected genes, making prioritization sensitive to the skewed degree distribution of PPI networks, as well as ascertainment bias in available interaction and disease association data. Motivated by this observation, we propose several statistical adjustment methods to account for the degree distribution of known disease and candidate genes, using a PPI network with associated confidence scores for interactions. We show that the proposed methods can detect loosely connected disease genes that are missed by existing approaches, however, this improvement might come at the price of more false negatives for highly connected genes. Consequently, we develop a suite called D<smcaps>A</smcaps>D<smcaps>A</smcaps>, which includes different uniform prioritization methods that effectively integrate existing approaches with the proposed statistical adjustment strategies. Comprehensive experimental results on the Online Mendelian Inheritance in Man (OMIM) database show that D<smcaps>A</smcaps>D<smcaps>A</smcaps> outperforms existing methods in prioritizing candidate disease genes.</p> <p>Conclusions</p> <p>These results demonstrate the importance of employing accurate statistical models and associated adjustment methods in network-based disease gene prioritization, as well as other network-based functional inference applications. D<smcaps>A</smcaps>D<smcaps>A</smcaps> is implemented in Matlab and is freely available at <url>http://compbio.case.edu/dada/</url>.</p

Mortality from external causes in Africa and Asia: evidence from INDEPTH Health and Demographic Surveillance System Sites.

BACKGROUND: Mortality from external causes, of all kinds, is an important component of overall mortality on a global basis. However, these deaths, like others in Africa and Asia, are often not counted or documented on an individual basis. Overviews of the state of external cause mortality in Africa and Asia are therefore based on uncertain information. The INDEPTH Network maintains longitudinal surveillance, including cause of death, at population sites across Africa and Asia, which offers important opportunities to document external cause mortality at the population level across a range of settings. OBJECTIVE: To describe patterns of mortality from external causes at INDEPTH Network sites across Africa and Asia, according to the WHO 2012 verbal autopsy (VA) cause categories. DESIGN: All deaths at INDEPTH sites are routinely registered and followed up with VA interviews. For this study, VA archives were transformed into the WHO 2012 VA standard format and processed using the InterVA-4 model to assign cause of death. Routine surveillance data also provide person-time denominators for mortality rates. RESULTS: A total of 5,884 deaths due to external causes were documented over 11,828,253 person-years. Approximately one-quarter of those deaths were to children younger than 15 years. Causes of death were dominated by childhood drowning in Bangladesh, and by transport-related deaths and intentional injuries elsewhere. Detailed mortality rates are presented by cause of death, age group, and sex. CONCLUSIONS: The patterns of external cause mortality found here generally corresponded with expectations and other sources of information, but they fill some important gaps in population-based mortality data. They provide an important source of information to inform potentially preventive intervention designs

Adult non-communicable disease mortality in Africa and Asia: evidence from INDEPTH Health and Demographic Surveillance System sites.

BACKGROUND: Mortality from non-communicable diseases (NCDs) is a major global issue, as other categories of mortality have diminished and life expectancy has increased. The World Health Organization's Member States have called for a 25% reduction in premature NCD mortality by 2025, which can only be achieved by substantial reductions in risk factors and improvements in the management of chronic conditions. A high burden of NCD mortality among much older people, who have survived other hazards, is inevitable. The INDEPTH Network collects detailed individual data within defined Health and Demographic Surveillance sites. By registering deaths and carrying out verbal autopsies to determine cause of death across many such sites, using standardised methods, the Network seeks to generate population-based mortality statistics that are not otherwise available. OBJECTIVE: To describe patterns of adult NCD mortality from INDEPTH Network sites across Africa and Asia, according to the WHO 2012 verbal autopsy (VA) cause categories, with separate consideration of premature (15-64 years) and older (65+ years) NCD mortality. DESIGN: All adult deaths at INDEPTH sites are routinely registered and followed up with VA interviews. For this study, VA archives were transformed into the WHO 2012 VA standard format and processed using the InterVA-4 model to assign cause of death. Routine surveillance data also provide person-time denominators for mortality rates. RESULTS: A total of 80,726 adult (over 15 years) deaths were documented over 7,423,497 person-years of observation. NCDs were attributed as the cause for 35.6% of these deaths. Slightly less than half of adult NCD deaths occurred in the 15-64 age group. Detailed results are presented by age and sex for leading causes of NCD mortality. Per-site rates of NCD mortality were significantly correlated with rates of HIV/AIDS-related mortality. CONCLUSIONS: These findings present important evidence on the distribution of NCD mortality across a wide range of African and Asian settings. This comes against a background of global concern about the burden of NCD mortality, especially among adults aged under 70, and provides an important baseline for future work

Surfing a genetic association interaction network to identify modulators of antibody response to smallpox vaccine

The variation in antibody response to vaccination likely involves small contributions of numerous genetic variants, such as single-nucleotide polymorphisms (SNPs), which interact in gene networks and pathways. To accumulate the bits of genetic information relevant to the phenotype that are distributed throughout the interaction network, we develop a network eigenvector centrality algorithm (SNPrank) that is sensitive to the weak main effects, gene–gene interactions and small higher-order interactions through hub effects. Analogous to Google PageRank, we interpret the algorithm as the simulation of a random SNP surfer (RSS) that accumulates bits of information in the network through a dynamic probabilistic Markov chain. The transition matrix for the RSS is based on a data-driven genetic association interaction network (GAIN), the nodes of which are SNPs weighted by the main-effect strength and edges weighted by the gene–gene interaction strength. We apply SNPrank to a GAIN analysis of a candidate-gene association study on human immune response to smallpox vaccine. SNPrank implicates a SNP in the retinoid X receptor α (RXRA) gene through a network interaction effect on antibody response. This vitamin A- and D-signaling mediator has been previously implicated in human immune responses, although it would be neglected in a standard analysis because its significance is unremarkable outside the context of its network centrality. This work suggests SNPrank to be a powerful method for identifying network effects in genetic association data and reveals a potential vitamin regulation network association with antibody response