skip to main content

Search for: All records

Creators/Authors contains: "Castro, M."

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Different analytic techniques operate optimally with different types of data. As the use of EHR-based analytics expands to newer tasks, data will have to be transformed into different representations, so the tasks can be optimally solved. We classified representations into broad categories based on their characteristics and proposed a new knowledge-driven representation for clinical data mining as well as trajectory mining, called Severity Encoding Variables (SEVs). Additionally, we studied which characteristics make representations most suitable for particular clinical analytics tasks including trajectory mining. Our evaluation shows that, for regression, most data representations performed similarly, with SEV achieving a slight (albeitmore »statistically significant) advantage. For patients at high risk of diabetes, it outperformed the competing representation by (relative) 20%. For association mining, SEV achieved the highest performance. Its ability to constrain the search space of patterns through clinical knowledge was key to its success.« less
  2. Extensive development of shale gas has generated some concerns about environmental impacts such as the migration of natural gas into water resources. We studied high gas concentrations in waters at a site near Marcellus Shale gas wells to determine the geological explanations and geochemical implications. The local geology may explain why methane has discharged for 7 years into groundwater, a stream, and the atmosphere. Gas may migrate easily near the gas wells in this location where the Marcellus Shale dips significantly, is shallow (∼1 km), and is more fractured. Methane and ethane concentrations in local water wells increased after gasmore »development compared with predrilling concentrations reported in the region. Noble gas and isotopic evidence are consistent with the upward migration of gas from the Marcellus Formation in a free-gas phase. This upflow results in microbially mediated oxidation near the surface. Iron concentrations also increased following the increase of natural gas concentrations in domestic water wells. After several months, both iron and SO42−concentrations dropped. These observations are attributed to iron and SO42−reduction associated with newly elevated concentrations of methane. These temporal trends, as well as data from other areas with reported leaks, document a way to distinguish newly migrated methane from preexisting sources of gas. This study thus documents both geologically risky areas and geochemical signatures of iron and SO42−that could distinguish newly leaked methane from older methane sources in aquifers.

    « less
  3. Abstract The hybrid design of the Pierre Auger Observatory allows for the measurement of the properties of extensive air showers initiated by ultra-high energy cosmic rays with unprecedented precision. By using an array of prototype underground muon detectors, we have performed the first direct measurement, by the Auger Collaboration, of the muon content of air showers between $$2\times 10^{17}$$ 2 × 10 17 and $$2\times 10^{18}$$ 2 × 10 18 eV. We have studied the energy evolution of the attenuation-corrected muon density, and compared it to predictions from air shower simulations. The observed densities are found to be larger thanmore »those predicted by models. We quantify this discrepancy by combining the measurements from the muon detector with those from the Auger fluorescence detector at $$10^{{17.5}}\, {\mathrm{eV}} $$ 10 17.5 eV and $$10^{{18}}\, {\mathrm{eV}} $$ 10 18 eV . We find that, for the models to explain the data, an increase in the muon density of $$38\%$$ 38 % $$\pm 4\% (12\%)$$ ± 4 % ( 12 % ) $$\pm {}^{21\%}_{18\%}$$ ± 18 % 21 % for EPOS-LHC , and of $$50\% (53\%)$$ 50 % ( 53 % ) $$\pm 4\% (13\%)$$ ± 4 % ( 13 % ) $$\pm {}^{23\%}_{20\%}$$ ± 20 % 23 % for QGSJetII-04 , is respectively needed.« less