The Transit Light Curve Project. IV. Five Transits of the Exoplanet OGLE-TR-10b

We present I and B photometry of five distinct transits of the exoplanet OGLE-TR-10b. By modeling the light curves, we find the planetary radius to be R_P = 1.06 +/- 0.08 R_Jup and the stellar radius to be R_S = 1.10 +/- 0.07 R_sun. The uncertainties are dominated by statistical errors in the photometry. Our estimate of the planetary radius is smaller than previous estimates that were based on lower-precision photometry, and hence the planet is not as anomalously large as was previously thought. We provide updated determinations of all the system parameters, including the transit ephemerides.Comment: Accepted in the Astrophysical Journal, 23 October 2006. Includes observations of additional transits to confirm earlier results. [15 pg, 6 figs

Getters for improved technetium containment in cementitious waste forms.

A cementitious waste form, Cast Stone, is a possible candidate technology for the immobilization of low activity nuclear waste (LAW) at the Hanford site. This work focuses on the addition of getter materials to Cast Stone that can sequester Tc from the LAW, and in turn, lower Tc release from the Cast Stone. Two getters which produce different products upon sequestering Tc from LAW were tested: Sn(II) apatite (Sn-A) that removes Tc as a Tc(IV)-oxide and potassium metal sulfide (KMS-2) that removes Tc as a Tc(IV)-sulfide species, allowing for a comparison of stability of the form of Tc upon entering the waste form. The Cast Stone with KMS-2 getter had the best performance with addition equivalent to ∼0.08wt% of the total waste form mass. The observed diffusion (Dobs) of Tc decreased from 4.6±0.2×10-12cm2/s for Cast Stone that did not contain a getter to 5.4±0.4×10-13cm2/s for KMS-2 containing Cast Stone. It was found that Tc-sulfide species are more stable against re-oxidation within getter containing Cast Stone compared with Tc-oxide and is the origin of the decrease in Tc Dobs when using the KMS-2

The Type Ic Supernova 1994I in M51: Detection of Helium and Spectral Evolution

We present a series of spectra of SN 1994I in M51, starting 1 week prior to maximum brightness. The nebular phase began about 2 months after the explosion; together with the rapid decline of the optical light, this suggests that the ejected mass was small. Although lines of He I in the optical region are weak or absent, consistent with the Type Ic classification, we detect strong He I λ10830 absorption during the first month past maximum. Thus, if SN 1994I is a typical Type Ic supernova, the atmospheres of these objects cannot be completely devoid of helium. The emission-line widths are smaller than predicted by the model of Nomoto and coworkers, in which the iron core of a low-mass carbon-oxygen star collapses. They are, however, larger than in Type Ib supernovae

Global Pattern Search at Scale

In recent years, data collection has far outpaced the tools for data analysis in the area of non-traditional GEOINT analysis. Traditional tools are designed to analyze small-scale numerical data, but there are few good interactive tools for processing large amounts of unstructured data such as raw text. In addition to the complexities of data processing, presenting the data in a way that is meaningful to the end user poses another challenge. In our work, we focused on analyzing a corpus of 35,000 news articles and creating an interactive geovisualization tool to reveal patterns to human analysts. Our comprehensive tool, Global Pattern Search at Scale (GPSS), addresses three major problems in data analysis: free text analysis, high volumes of data, and interactive visualization. GPSS uses an Accumulo database for high-volume data storage, and a matrix of word counts and event detection algorithms to process the free text. For visualization, the tool displays an interactive web application to the user, featuring a map overlaid with document clusters and events, search and filtering options, a timeline, and a word cloud. In addition, the GPSS tool can be easily adapted to process and understand other large free-text datasets