Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

The Pan-STARRS Moving Object Processing System

We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern software package that produces automatic asteroid discoveries and identifications from catalogs of transient detections from next-generation astronomical survey telescopes. MOPS achieves >99.5% efficiency in producing orbits from a synthetic but realistic population of asteroids whose measurements were simulated for a Pan-STARRS4-class telescope. Additionally, using a nonphysical grid population, we demonstrate that MOPS can detect populations of currently unknown objects such as interstellar asteroids. MOPS has been adapted successfully to the prototype Pan-STARRS1 telescope despite differences in expected false detection rates, fill-factor loss, and relatively sparse observing cadence compared to a hypothetical Pan-STARRS4 telescope and survey. MOPS remains highly efficient at detecting objects but drops to 80% efficiency at producing orbits. This loss is primarily due to configurable MOPS processing limits that are not yet tuned for the Pan-STARRS1 mission. The core MOPS software package is the product of more than 15 person-years of software development and incorporates countless additional years of effort in third-party software to perform lower-level functions such as spatial searching or orbit determination. We describe the high-level design of MOPS and essential subcomponents, the suitability of MOPS for other survey programs, and suggest a road map for future MOPS development.

Main-belt Comet P/2012 T1 (PANSTARRS)

We present initial results from observations and numerical analyses aimed at characterizing the main-belt comet P/2012 T1 (PANSTARRS). Optical monitoring observations were made between 2012 October and 2013 February using the University of Hawaii 2.2 m telescope, the Keck I telescope, the Baade and Clay Magellan telescopes, Faulkes Telescope South, the Perkins Telescope at Lowell Observatory, and the Southern Astrophysical Research Telescope. The object's intrinsic brightness approximately doubles from the time of its discovery in early October until mid-November and then decreases by ~60% between late December and early February, similar to photometric behavior exhibited by several other main-belt comets and unlike that exhibited by disrupted asteroid (596) Scheila. We also used Keck to conduct spectroscopic searches for CN emission as well as absorption at 0.7 μm that could indicate the presence of hydrated minerals, finding an upper limit CN production rate of Q CN <1.5 × 1023 mol s-1, from which we infer a water production rate of Q_H_2O100 Myr and is unlikely to be a recently implanted interloper from the outer solar system, while a search for potential asteroid family associations reveals that it is dynamically linked to the ~155 Myr old Lixiaohua asteroid family. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration, and made possible by the generous financial support of the W. M. Keck Foundation, the Magellan Telescopes located at Las Campanas Observatory, Chile, and the Southern Astrophysical Research (SOAR) telescope, which is a joint project of the Ministério da Ciência, Tecnologia, e Inovação (MCTI) da República Federativa do Brasil, the U.S. National Optical Astronomy Observatory (NOAO), the University of North Carolina at Chapel Hill (UNC), and Michigan State University (MSU).

Outgassing Behavior of C/2012 S1 (ISON) from 2011 September to 2013 June

We report photometric observations for comet C/2012 S1 (ISON) obtained during the time period immediately after discovery (r = 6.28 AU) until it moved into solar conjunction in mid-2013 June using the UH2.2 m, and Gemini North 8 m telescopes on Mauna Kea, the Lowell 1.8 m in Flagstaff, the Calar Alto 1.2 m telescope in Spain, the VYSOS-5 telescopes on Mauna Loa Hawaii and data from the CARA network. Additional pre-discovery data from the Pan STARRS1 survey extends the light curve back to 2011 September 30 (r = 9.4 AU). The images showed a similar tail morphology due to small micron sized particles throughout 2013. Observations at submillimeter wavelengths using the James Clerk Maxwell Telescope on 15 nights between 2013 March 9 (r = 4.52 AU) and June 16 (r = 3.35 AU) were used to search for CO and HCN rotation lines. No gas was detected, with upper limits for CO ranging between 3.5-4.5 × 1027 molecules s-1. Combined with published water production rate estimates we have generated ice sublimation models consistent with the photometric light curve. The inbound light curve is likely controlled by sublimation of CO2. At these distances water is not a strong contributor to the outgassing. We also infer that there was a long slow outburst of activity beginning in late 2011 peaking in mid-2013 January (r ~ 5 AU) at which point the activity decreased again through 2013 June. We suggest that this outburst was driven by CO injecting large water ice grains into the coma. Observations as the comet came out of solar conjunction seem to confirm our models.

Laughter Type Recognition from Whole Body Motion

Despite the importance of laughter in social interactions it remains little studied in affective computing. Respiratory, auditory, and facial laughter signals have been investigated but laughter-related body movements have received almost no attention. The aim of this study is twofold: first an investigation into observers' perception of laughter states (hilarious, social, awkward, fake, and non-laughter) based on body movements alone, through their categorization of avatars animated with natural and acted motion capture data. Significant differences in torso and limb movements were found between animations perceived as containing laughter and those perceived as nonlaughter. Hilarious laughter also differed from social laughter in the amount of bending of the spine, the amount of shoulder rotation and the amount of hand movement. The body movement features indicative of laughter differed between sitting and standing avatar postures. Based on the positive findings in this perceptual study, the second aim is to investigate the possibility of automatically predicting the distributions of observer's ratings for the laughter states. The findings show that the automated laughter recognition rates approach human rating levels, with the Random Forest method yielding the best performance.