The Evolution of the Galaxy Cluster Luminosity-Temperature Relation

We analyzed the luminosity-temperature (L-T) relation for 2 samples of galaxy clusters which have all been observed by the ASCA satellite. We used 32 high redshift clusters (0.3<z<0.6), 53 low redshift clusters (z<0.3), and also the combination of the low and high redshift datasets. We assumed a power law relation between the bolometric luminosity of the galaxy cluster and its integrated temperature and redshift (L_{bol,44}=C*T^alpha*(1+z)^A). The results are consistent, independent of cosmology, with previous estimates of L$\sim$T$^3$ found by other authors. We observed weak or zero evolution.Comment: 20 pages, Latex, 11 figures, GIF forma

NSF Supported Socio-Environmental Research: How Do Crosscutting Programs Affect Research Funding, Publication, and Citation Patterns?

Recognizing the continued human domination of landscapes across the globe, social-ecological systems (SES) research has proliferated, necessitating interdisciplinary collaborations. Although interdisciplinary research started gaining traction in academic settings close to 50 years ago, formal frameworks for SES research did not develop until the late 1990s. The first National Science Foundation (NSF) funding mechanism specifically for interdisciplinary SES research began in 2001 and the SES-specific Coupled Natural Human (CNH) Systems program began in 2007. We used data on funded NSF projects from 2000 to 2015 to examine how SES research was funded, where the research is published, and the scholarly impact of SES research. Despite specific programs for funding SES research within the NSF, this type of research also received funding from non-SES mission programs (e.g., Ecosystem Science constituted 19% of grants in our study, and Hydrology constituted 16% of grants). Although NSF funding for SES research originates from across programs, the majority of products are published in journals with a focus on ecological sciences. Grants funded through the Coupled Natural Human Systems programs were more likely to publish at least one paper that was highly interdisciplinary (Biological Sciences [BE-CNH] constituted 70% of grants in program, and Geosciences [GEO-CNH] constituted 48% of grants) than the traditional disciplinary programs (Ecology [ES], 35% and Hydrology, 27%). This result highlights the utility of these cross-cutting programs in producing and widely disseminating SES research. We found that the number of citations was higher in BE-CNH and ES than other programs, pointing to greater scholarly impact of SES research in these NSF programs. Through our research, we identified the need for institutions to recognize research products and deliverables beyond the “standard” peer-reviewed manuscripts, as SES and interdisciplinary research and unconventional research products (e.g., popular press articles, online StoryMaps, workshops, white papers) continue to grow and are important to the broader societal impact of these types of research programs. This project demonstrates that the outcomes and products of grants awarded through the NSF CNH programs are important to furthering SES research and the programs should be valued and expanded in the future

Large-scale evaluation of automated clinical note de-identification and its impact on information extraction

Objective: (1) To evaluate a state-of-the-art natural language processing (NLP)-based approach to automatically de-identify a large set of diverse clinical notes. (2) To measure the impact of de-identification on the performance of information extraction algorithms on the de-identified documents. Material and methods A cross-sectional study that included 3503 stratified, randomly selected clinical notes (over 22 note types) from five million documents produced at one of the largest US pediatric hospitals. Sensitivity, precision, F value of two automated de-identification systems for removing all 18 HIPAA-defined protected health information elements were computed. Performance was assessed against a manually generated ‘gold standard’. Statistical significance was tested. The automated de-identification performance was also compared with that of two humans on a 10% subsample of the gold standard. The effect of de-identification on the performance of subsequent medication extraction was measured. Results: The gold standard included 30 815 protected health information elements and more than one million tokens. The most accurate NLP method had 91.92% sensitivity (R) and 95.08% precision (P) overall. The performance of the system was indistinguishable from that of human annotators (annotators' performance was 92.15%(R)/93.95%(P) and 94.55%(R)/88.45%(P) overall while the best system obtained 92.91%(R)/95.73%(P) on same text). The impact of automated de-identification was minimal on the utility of the narrative notes for subsequent information extraction as measured by the sensitivity and precision of medication name extraction. Discussion and conclusion NLP-based de-identification shows excellent performance that rivals the performance of human annotators. Furthermore, unlike manual de-identification, the automated approach scales up to millions of documents quickly and inexpensively

Automated detection of medication administration errors in neonatal intensive care

AbstractObjectiveTo improve neonatal patient safety through automated detection of medication administration errors (MAEs) in high alert medications including narcotics, vasoactive medication, intravenous fluids, parenteral nutrition, and insulin using the electronic health record (EHR); to evaluate rates of MAEs in neonatal care; and to compare the performance of computerized algorithms to traditional incident reporting for error detection.MethodsWe developed novel computerized algorithms to identify MAEs within the EHR of all neonatal patients treated in a level four neonatal intensive care unit (NICU) in 2011 and 2012. We evaluated the rates and types of MAEs identified by the automated algorithms and compared their performance to incident reporting. Performance was evaluated by physician chart review.ResultsIn the combined 2011 and 2012 NICU data sets, the automated algorithms identified MAEs at the following rates: fentanyl, 0.4% (4 errors/1005 fentanyl administration records); morphine, 0.3% (11/4009); dobutamine, 0 (0/10); and milrinone, 0.3% (5/1925). We found higher MAE rates for other vasoactive medications including: dopamine, 11.6% (5/43); epinephrine, 10.0% (289/2890); and vasopressin, 12.8% (54/421). Fluid administration error rates were similar: intravenous fluids, 3.2% (273/8567); parenteral nutrition, 3.2% (649/20124); and lipid administration, 1.3% (203/15227). We also found 13 insulin administration errors with a resulting rate of 2.9% (13/456). MAE rates were higher for medications that were adjusted frequently and fluids administered concurrently. The algorithms identified many previously unidentified errors, demonstrating significantly better sensitivity (82% vs. 5%) and precision (70% vs. 50%) than incident reporting for error recognition.ConclusionsAutomated detection of medication administration errors through the EHR is feasible and performs better than currently used incident reporting systems. Automated algorithms may be useful for real-time error identification and mitigation

Substructure and Scatter in the Mass-Temperature Relations of Simulated Clusters

Galaxy clusters exhibit regular scaling relations among their bulk properties. These relations establish vital links between halo mass and cluster observables. Precision cosmology studies that depend on these links benefit from a better understanding of scatter in the mass-observable scaling relations. Here we study the role of merger processes in introducing scatter into the $M$-$T_{\rm X}$ relation, using a sample of 121 galaxy clusters simulated with radiative cooling and supernova feedback, along with three statistics previously proposed to measure X-ray surface brightness substructure. These are the centroid variation ($w$), the axial ratio ($\eta$), and the power ratios ($P_{20}$ and $P_{30}$). We find that in this set of simulated clusters, each substructure measure is correlated with a cluster's departures $\delta \ln T_{\rm X}$ and $\delta \ln M$ from the mean $M$-$T_{\rm X}$ relation, both for emission-weighted temperatures $T_{\rm EW}$ and for spectroscopic-like temperatures $T_{\rm SL}$, in the sense that clusters with more substructure tend to be cooler at a given halo mass. In all cases, a three-parameter fit to the $M$-$T_{\rm X}$ relation that includes substructure information has less scatter than a two-parameter fit to the basic $M$-$T_{\rm X}$ relation.Comment: Accepted by ApJ, 10 pages, 10 figure

Main-Belt Comet P/2012 T1 (PANSTARRS)

We present initial results from observations and numerical analyses aimed at characterizing main-belt comet P/2012 T1 (PANSTARRS). Optical monitoring observations were made between October 2012 and February 2013 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 (SOAR) 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 microns that could indicate the presence of hydrated minerals, finding an upper limit CN production rate of QCN<1.5x10^23 mol/s, from which we infer a water production rate of QH2O<5x10^25 mol/s, and no evidence of the presence of hydrated minerals. Numerical simulations indicate that P/2012 T1 is largely dynamically stable for >100 Myr and is unlikely to be a recently implanted interloper from the outer solar system, while a search for potential asteroid family associations reveal that it is dynamically linked to the ~155 Myr-old Lixiaohua asteroid family.Comment: 15 pages, 4 figures, accepted for publication in ApJ Letter

Prospecting in ultracool dwarfs : Measuring the metallicities of mid- and late-m dwarfs

© 2014. The American Astronomical Society. All rights reserved.Metallicity is a fundamental parameter that contributes to the physical characteristics of a star. The low temperatures and complex molecules present in M dwarf atmospheres make it difficult to measure their metallicities using techniques that have been commonly used for Sun-like stars. Although there has been significant progress in developing empirical methods to measure M dwarf metallicities over the last few years, these techniques have been developed primarily for early- to mid-M dwarfs. We present a method to measure the metallicity of mid- to late-M dwarfs from moderate resolution (R ∼ 2000) K-band (≃ 2.2 μm) spectra. We calibrate our formula using 44 wide binaries containing an F, G, K, or early-M primary of known metallicity and a mid- to late-M dwarf companion. We show that similar features and techniques used for early-M dwarfs are still effective for late-M dwarfs. Our revised calibration is accurate to ∼0.07 dex for M4.5-M9.5 dwarfs with -0.58 <[Fe/H] <+0.56 and shows no systematic trends with spectral type, metallicity, or the method used to determine the primary star metallicity. We show that our method gives consistent metallicities for the components of M+M wide binaries. We verify that our new formula works for unresolved binaries by combining spectra of single stars. Lastly, we show that our calibration gives consistent metallicities with the Mann et al. study for overlapping (M4-M5) stars, establishing that the two calibrations can be used in combination to determine metallicities across the entire M dwarf sequence.Peer reviewe

Multi-Messenger Gravitational Wave Searches with Pulsar Timing Arrays: Application to 3C66B Using the NANOGrav 11-year Data Set

When galaxies merge, the supermassive black holes in their centers may form binaries and, during the process of merger, emit low-frequency gravitational radiation in the process. In this paper we consider the galaxy 3C66B, which was used as the target of the first multi-messenger search for gravitational waves. Due to the observed periodicities present in the photometric and astrometric data of the source of the source, it has been theorized to contain a supermassive black hole binary. Its apparent 1.05-year orbital period would place the gravitational wave emission directly in the pulsar timing band. Since the first pulsar timing array study of 3C66B, revised models of the source have been published, and timing array sensitivities and techniques have improved dramatically. With these advances, we further constrain the chirp mass of the potential supermassive black hole binary in 3C66B to less than $(1.65\pm0.02) \times 10^9~{M_\odot}$ using data from the NANOGrav 11-year data set. This upper limit provides a factor of 1.6 improvement over previous limits, and a factor of 4.3 over the first search done. Nevertheless, the most recent orbital model for the source is still consistent with our limit from pulsar timing array data. In addition, we are able to quantify the improvement made by the inclusion of source properties gleaned from electromagnetic data to `blind' pulsar timing array searches. With these methods, it is apparent that it is not necessary to obtain exact a priori knowledge of the period of a binary to gain meaningful astrophysical inferences.Comment: 14 pages, 6 figures. Accepted by Ap