Examinando por Autor "Lopez, S."

Mostrando 1 - 2 de 2
  • Miniatura
    Ítem
    Heavy metal concentrations of two highly migratory sharks (Prionace glauca and Isurus oxyrinchus) in the southeastern Pacific waters: Comments on public health and conservation
    (SAGE Publishing, 2013) Lopez, S.; Abarca, N.; Meléndez, R.
    Despite the importance of sharks in structuring the marine food web, their biomass is declining dramatically throughout the world ́s oceans due to fishing pressures. Sharks caught as by-catch in long-line fisheries are sold for shark fins in the Asian fish market and secondarily as trunk sales for local consumption and fish meal. In order to determine the levels of heavy metals (mercury and lead) in oceanic shark populations in South Pacific waters, analyses of 39 Prionace glauca and 69 Isurus oxyrinchus were conducted. Mercury (Hg) and lead (Pb) were measured by cold vapor and via acetylene flame techniques, respectively. Mercury concentrations were similar in the studied sharks (p=0.1516), with 0.048 ± 0.03 μg·g-1 w/w for P. glauca and 0.034 ± 0.023 μg·g-1 w/w for I. oxyrinchus. P. glauca showed greater values of lead than I. oxyrinchus (p[removed]0.05). The metal concentrations reported in this work constitute a risk for human health, mainly from the high contributions of lead in tissues of P. glauca and I. oxyrinchus.
  • Miniatura
    Ítem
    Photometric classification of quasars from RCS-2 using Random Forest
    (EDP Sciences, 2015-12) Carrasco, D.; Barrientos L., F.; Pichara, K.; Anguita, T.; Murphy D., N.A.; Gilbank D., G.; Gladders M., D.; Yee H.K., C.; Hsieh B., C.; Lopez, S.
    The classification and identification of quasars is fundamental to many astronomical research areas. Given the large volume of photometric survey data available in the near future, automated methods for doing so are required. In this article, we present a new quasar candidate catalog from the Red-Sequence Cluster Survey 2 (RCS-2), identified solely from photometric information using an automated algorithm suitable for large surveys. The algorithm performance is tested using a well-defined SDSS spectroscopic sample of quasars and stars. The Random Forest algorithm constructs the catalog from RCS-2 point sources using SDSS spectroscopically-confirmed stars and quasars. The algorithm identifies putative quasars from broadband magnitudes (g, r, i, z) and colors. Exploiting NUV GALEX measurements for a subset of the objects, we refine the classifier by adding new information. An additional subset of the data with WISE W1 and W2 bands is also studied. Upon analyzing 542 897 RCS-2 point sources, the algorithm identified 21 501 quasar candidates with a training-set-derived precision (the fraction of true positives within the group assigned quasar status) of 89.5% and recall (the fraction of true positives relative to all sources that actually are quasars) of 88.4%. These performance metrics improve for the GALEX subset: 6529 quasar candidates are identified from 16 898 sources, with a precision and recall of 97.0% and 97.5%, respectively. Algorithm performance is further improved when WISE data are included, with precision and recall increasing to 99.3% and 99.1%, respectively, for 21 834 quasar candidates from 242 902 sources. We compiled our final catalog (38 257) by merging these samples and removing duplicates. An observational follow up of 17 bright (r < 19) candidates with long-slit spectroscopy at DuPont telescope (LCO) yields 14 confirmed quasars. The results signal encouraging progress in the classification of point sources with Random Forest algorithms to search for quasars within current and future large-area photometric surveys. © 2015 ESO.