New approaches to object classification in synoptic sky surveys

Digital synoptic sky surveys pose several new object classification challenges. In surveys where real-time detection and classification of transient events is a science driver, there is a need for an effective elimination of instrument-related artifacts which can masquerade as transient sources in the detection pipeline, e.g., unremoved large cosmic rays, saturation trails, reflections, crosstalk artifacts, etc. We have implemented such an Artifact Filter, using a supervised neural network, for the real-time processing pipeline in the Palomar-Quest (PQ) survey. After the training phase, for each object it takes as input a set of measured morphological parameters and returns the probability of it being a real object. Despite the relatively low number of training cases for many kinds of artifacts, the overall artifact classification rate is around 90%, with no genuine transients misclassified during our real-time scans. Another question is how to assign an optimal star-galaxy classification in a multi-pass survey, where seeing and other conditions change between different epochs, potentially producing inconsistent classifications for the same object. We have implemented a star/galaxy multipass classifier that makes use of external and a priori knowledge to find the optimal classification from the individually derived ones. Both these techniques can be applied to other, similar surveys and data sets

Towards real-time classification of astronomical transients

Exploration of time domain is now a vibrant area of research in astronomy, driven by the advent of digital synoptic sky surveys. While panoramic surveys can detect variable or transient events, typically some follow-up observations are needed; for short-lived phenomena, a rapid response is essential. Ability to automatically classify and prioritize transient events for follow-up studies becomes critical as the data rates increase. We have been developing such methods using the data streams from the Palomar-Quest survey, the Catalina Sky Survey and others, using the VOEventNet framework. The goal is to automatically classify transient events, using the new measurements, combined with archival data (previous and multi-wavelength measurements), and contextual information (e.g., Galactic or ecliptic latitude, presence of a possible host galaxy nearby, etc.); and to iterate them dynamically as the follow-up data come in (e.g., light curves or colors). We have been investigating Bayesian methodologies for classification, as well as discriminated follow-up to optimize the use of available resources, including Naive Bayesian approach, and the non-parametric Gaussian process regression. We will also be deploying variants of the traditional machine learning techniques such as Neural Nets and Support Vector Machines on datasets of reliably classified transients as they build up

Traditional and Health-Related Philanthropy: The Role of Resources and Personality

I study the relationships of resources and personality characteristics to charitable giving, postmortem organ donation, and blood donation in a nationwide sample of persons in households in the Netherlands. I find that specific personality characteristics are related to specific types of giving: agreeableness to blood donation, empathic concern to charitable giving, and prosocial value orientation to postmortem organ donation. I find that giving has a consistently stronger relation to human and social capital than to personality. Human capital increases giving; social capital increases giving only when it is approved by others. Effects of prosocial personality characteristics decline at higher levels of these characteristics. Effects of empathic concern, helpfulness, and social value orientations on generosity are mediated by verbal proficiency and church attendance.

The Factory and the Beehive. IV. A Comprehensive Study of the Rotation X-Ray Activity Relation in Praesepe and the Hyades

X-ray observations of low-mass stars in open clusters are critical to understanding the dependence of magnetic activity on stellar properties and their evolution. Praesepe and the Hyades, two of the nearest, most-studied open clusters, are among the best available laboratories for examining the dependence of magnetic activity on rotation for stars with masses 21 M . We present an updated study of the rotation-X-ray activity relation in the two clusters. We updated membership catalogs that combine pre-Gaia catalogs with new catalogs based on Gaia Data Release 2. The resulting catalogs are the most inclusive ones for both clusters: 1739 Praesepe and 1315 Hyades stars. We collected X-ray detections for cluster members, for which we analyzed, re-analyzed, or collated data from ROSAT, the Chandra X-ray Observatory, the Neil Gehrels Swift Observatory, and XMM-Newton. We have detections for 326 Praesepe and 462 Hyades members, of which 273 and 164, respectively, have rotation periods - an increase of 6× relative to what was previously available. We find that at ≈700 Myr, only M dwarfs remain saturated in X-rays, with only tentative evidence for supersaturation. We also find a tight relation between the Rossby number and fractional X-ray luminosity L X/L bol in unsaturated single members, suggesting a power-law index between -3.2 and -3.9. Lastly, we find no difference in the coronal parameters between binary and single members. These results provide essential insight into the relative efficiency of magnetic heating of the stars' atmospheres, thereby informing the development of robust age-rotation-activity relations

An in-situ cell for characterization of solids by soft X-rayabsorption

An in-situ cell using ''lab-on-a-chip'' technologies has been designed and tested for characterization of catalysts and environmental materials using soft X-ray absorption spectroscopy and spectromicroscopy at photon energies above 250 eV. The sample compartment is 1.0 mm in diameter with a gas path length of 0.8 mm to minimize X-ray absorption in the gas phase. The sample compartment can be heated to 533 K by an Al resistive heater and gas flows up to 5.0 cm{sup 3} min{sup -1} can be supplied to the sample compartment through microchannels. The performance of the cell was tested by acquiring Cu L{sub 3}-edge XANES data during the reduction and oxidation of a silica-supported Cu catalyst using the beam line 11.0.2 Scanning Transmission X-ray Microscope (STXM) at the Advanced Light Source of LBNL. Two-dimensional images of individual catalyst particles were recorded at photon energies between 926 eV and 937 eV, the energy range in which the Cu(II) and Cu(I) L{sub 3} absorption edges are observed. Oxidation state specific images of the catalyst clearly show the disappearance of Cu(II) species during the exposure of the oxidized sample to 4% CO in He while increasing the temperature from 308 K to 473 K. Reoxidation restores the intensity of the image associated with Cu(II). L-edge XANES spectra obtained from stacks of STXM images show that with increasing temperature the Cu(II) peak intensity decreases as the Cu(I) peak intensity increases

Continental-scale geographic change across zealandia during paleogene subduction initiation

Data from International Ocean Discovery Program (IODP) Expedition 371 reveal vertical movements of 1-3 km in northern Zealandia during early Cenozoic subduction initiation in the western Pacific Ocean. Lord Howe Rise rose from deep (~1 km) water to sea level and subsided back, with peak uplift at 50 Ma in the north and between 41 and 32 Ma in the south. The New Caledonia Trough subsided 2-3 km between 55 and 45 Ma. We suggest these elevation changes resulted from crust delamination and mantle flow that led to slab formation. We propose a "subduction resurrection" model in which (1) a subduction rupture event activated lithospheric-scale faults across a broad region during less than ~5 m.y., and (2) tectonic forces evolved over a further 4-8 m.y. as subducted slabs grew in size and drove plate-motion change. Such a subduction rupture event may have involved nucleation and lateral propagation of slip-weakening rupture along an interconnected set of preexisting weaknesses adjacent to density anomalies

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Microflares and the Statistics of X-ray Flares

This review surveys the statistics of solar X-ray flares, emphasising the new views that RHESSI has given us of the weaker events (the microflares). The new data reveal that these microflares strongly resemble more energetic events in most respects; they occur solely within active regions and exhibit high-temperature/nonthermal emissions in approximately the same proportion as major events. We discuss the distributions of flare parameters (e.g., peak flux) and how these parameters correlate, for instance via the Neupert effect. We also highlight the systematic biases involved in intercomparing data representing many decades of event magnitude. The intermittency of the flare/microflare occurrence, both in space and in time, argues that these discrete events do not explain general coronal heating, either in active regions or in the quiet Sun.Comment: To be published in Space Science Reviews (2011