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We describe a general analysis package for supernova (SN) light curves, calledSNANA, that contains a simulation, a light-curve fitter, and a cosmology fitter. The software is designed with the primary goal of using SNe Ia as distance indicators for the determination of cosmological parameters, but it can also be used to study efficiencies for analyses of SN rates, estimate contamination from non-Ia SNe, and optimize future surveys. Several SN models are available within the same software architecture, allowing technical features such as K K -corrections to be consistently used among multiple models, and thus making it easier to make detailed comparisons between models. New and improved light-curve models can be easily added. The software works with arbitrary surveys and telescopes and has already been used by several collaborations, leading to more robust and easy-to-use code. This software is not intended as a final product release, but rather it is designed to undergo continual improvements from the community as more is learned about SNe. We give an overview of theSNANAcapabilities, as well as some of its limitations.

We report results from the Supernova Photometric Classification Challenge (SNPhotCC), a publicly released mix of simulated supernovae (SNe), with types (Ia, Ibc, and II) selected in proportion to their expected rates. The simulation was realized in the griz g r i z filters of the Dark Energy Survey (DES) with realistic observing conditions (sky noise, point-spread function, and atmospheric transparency) based on years of recorded conditions at the DES site. Simulations of non–Ia-type SNe are based on spectroscopically confirmed light curves that includeunpublishednon-Ia samples donated from the Carnegie Supernova Project (CSP), the Supernova Legacy Survey (SNLS), and the Sloan Digital Sky Survey-II (SDSS-II). A spectroscopically confirmed subset was provided for training. We challenged scientists to run their classification algorithms and report a type and photo- z z for each SN. Participants from 10 groups contributed 13 entries for the sample that included a host-galaxy photo- z z for each SN and nine entries for the sample that had no redshift information. Several different classification strategies resulted in similar performance, and for all entries the performance was significantly better for the training subset than for the unconfirmed sample. For the spectroscopically unconfirmed subset, the entry with the highest average figure of merit for classifying SNe Ia has an efficiency of 0.96 and an SN Ia purity of 0.79. As a public resource for the future development of photometric SN classification and photo- z z estimators, we have released updated simulations with improvements based on our experience from the SNPhotCC, added samples corresponding to the Large Synoptic Survey Telescope (LSST) and the SDSS-II, and provided the answer keys so that developers can evaluate their own analysis.

The DESGW group seeks to identify electromagnetic counterparts of gravitational wave events seen by the LIGO-VIRGO network, such as those expected from binary neutron star mergers or neutron star-black hole mergers. DESGW was active throughout the first two LIGO observing seasons, following up several binary black hole mergers and the first binary neutron star merger, GW170817. This work describes the modifications to the observing strategy generation and image processing pipeline between the second (ending in August 2017) and third (beginning in April 2019) LIGO observing seasons. The modifications include a more robust observing strategy generator, further parallelization of the image reduction software and difference imaging processing pipeline, data transfer streamlining, and a web page listing identified counterpart candidates that updates in real time. Taken together, the additional parallelization steps enable the identification of potential electromagnetic counterparts within fully calibrated search images in less than one hour, compared to the 3-5 hours it would typically take during the first two seasons. These performance improvements are critical to the entire EM follow-up community, as rapid identification (or rejection) of candidates enables detailed and rapid spectroscopic follow-up by multiple instruments, leading to more information about the environment immediately following such gravitational wave events.

This paper describes the data release of the Sloan Digital Sky Survey-II (SDSS-II) Supernova Survey conducted between 2005 and 2007. Light curves, spectra, classifications, and ancillary data are presented for 10,258 variable and transient sources discovered through repeat ugriz imaging of SDSS Stripe 82, a 300 deg2 area along the celestial equator. This data release is comprised of all transient sources brighter than r 22.5 mag with no history of variability prior to 2004. Dedicated spectroscopic observations were performed on a subset of 889 transients, as well as spectra for thousands of transient host galaxies using the SDSS-III BOSS spectrographs. Photometric classifications are provided for the candidates with good multi-color light curves that were not observed spectroscopically, using host galaxy redshift information when available. From these observations, 4607 transients are either spectroscopically confirmed, or likely to be, supernovae, making this the largest sample of supernova candidates ever compiled. We present a new method for SN host-galaxy identification and derive host-galaxy properties including stellar masses, star formation rates, and the average stellar population ages from our SDSS multi-band photometry. We derive SALT2 distance moduli for a total of 1364 SN Ia with spectroscopic redshifts as well as photometric redshifts for a further 624 purely photometric SN Ia candidates. Using the spectroscopically confirmed subset of the three-year SDSS-II SN Ia sample and assuming a flat ΛCDM cosmology, we determine M = 0.315 0.093 (statistical error only) and detect a non-zero cosmological constant at 5.7 .

Despite the efficacy of electroconvulsive therapy for the treatment of affective disorders there are no systematic studies of its effectiveness or safety in the mentally retarded population. A literature search revealed 16 case reports that suggests that it is both as effective and safe with mentally retarded persons as in the general population. Four additional clinical vignettes, with extensive follow-up observation from four to eleven years, are presented in an effort to enrich the literature on this subject. They include patients with rapid cycling bipolar disorder, bipolar disorder, manic phase, major depression with psychotic features and schizoaffective disorder. Issues of diagnostic difficulty and pharmacologic prophylaxis are addressed.

The Handbook of Composites From Renewable Materials comprises a set of 8 individual volumes that brings an interdisciplinary perspective to accomplish a more detailed understanding of the interplay between the synthesis, structure, characterization, processing, applications and performance of these advanced materials. The handbook covers a multitude of natural polymers/ reinforcement/ fillers and biodegradable materials. Together, the 8 volumes total at least 5000 pages and offers a unique publication. Volume 1 is solely focused on the Structure and Chemistry of renewable materials. Some of the important topics include but not limited to: carbon fibers from sustainable resources; polylactic acid composites and composite foams based on natural fibres; composites materials from other than cellulosic resources; microcrystalline cellulose and related polymer composites; tannin-based foam; renewable feedstock vanillin derived polymer and composites; silk biocomposites; bio-derived adhesives and matrix polymers; biomass based formaldehyde-free bio-resin ; isolation and characterization of water soluble polysaccharide; bio-based fillers; keratin based materials in biotechnology; structure of proteins adsorbed onto bioactive glasses for sustainable composite; effect of filler properties on the antioxidant response of starch composites; composite of chitosan and its derivate; magnetic biochar from discarded agricultural biomass; biodegradable polymers for protein and peptide conjugation; polyurethanes and polyurethane composites from bio-based / recycled components.

Keeping in mind the advantages of bio-based materials, this book focuses on the potential efficacy of different biocomposites procured from diverse natural resources and the preparation and processing of the biocomposites to be used for a variety of applications. Each chapter gives an overview on a particular biocomposite material and its processing and successful utilization for selected applications.

A continuous demanding in raw chemicals cost reduction and processing simplification facilitates the exploration and development of new materials in current plastics industries. In this study, a novel carbonaceous filler material “asphaltene” extracted from inexpensive and abundant asphalt is blended into a thermoplastic elastomer poly(styrene–butadiene–styrene) copolymer (SBS) for the fabrication of hybrid composites at different loadings via melt-compounding. Due to its intrinsic molecular rigidness and desirable compatibility with SBS, the prepared asphaltene/SBS composites displays excellent thermo-mechanical properties by improving the storage modulus in the glassy region by 19 % and in the rubbery region by 305 %, as well as increasing the thermal stability by up to 20 °C. The overall mechanical properties are also enhanced substantially by incorporation of asphaltene into the SBS matrix according to the filler loading in SBS: the tensile strength increased by 2.2 MPa, the maximum elongation by 268 %, Young’s modulus by 214 %, and toughness by 100.4 %. Although the introduced asphaltene inevitably led to a gradual increment in the viscosity of polymer melts from the filler–filler and filler–polymer interactions, homogeneous dispersion of the reinforcing fillers at optimum loading (20–30 wt%) in SBS matrix is still sustained.