Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

The SPECTRA Barrax campaign (SPARC): Overview and first results from CHRIS data

In the framework of preparatory activities for the SPECTRA (Surface Processes and Ecosystems Changes Through Response Analysis) ESA Earth Explorer Core Mission, CHRIS/PROBA acquisitions over the Barrax Core Site in Spain were used to compile a reference dataset for future in-depth studies. Taking advantage of the possibility of consecutive days of acquisitions, multiple-angular acquisitions finally included 10 different view angles from CHRIS, in Mode 1 with 62 spectral, and a ground resolution of about 34 m. Additional ROSIS and HYMAP sensors, flying simultaneously with CHRIS overpass, provided detailed images for validation of CHRIS data, particularly in the spectral domain. Moreover, up to 3 angles per sample from airborne HYMAP data were acquired, with high spectral and spatial resolution, and then both spectral and angular domains can be exploited with the combined CHRIS/HYMAP/ROSIS dataset. Detailed soil/vegetation and atmospheric measurements complete the SPARC data, and data from other satellites (MERIS, SEVIRI, SPOT, Landsat) were collected as well, to address scaling issues. Methods for data analysis and exploitation have been developed in the context of SPARC activities, and preliminary results about retrievals of biophysical information from multi-angular hyperspectral data are already available. The whole SPARC dataset represents a reference for the exploitation of CHRIS data, allowing the development of new processing and retrieval algorithms, and the validation of such algorithms by means of ground measurements and complementary airborne and satellite data. More details on several processing aspects of the CHRIS/PROBA data acquired within the SPARC campaign are presented in other papers in this conference

Spatiotemporal Pattern of Urban Forest Leaf Area Index in Response to Rapid Urbanization and Urban Greening

Rapid urbanization and urban greening have caused great changes to urban forests in China. Understanding spatiotemporal patterns of urban forest leaf area index (LAI) under rapid urbanization and urban greening is important for urban forest planning and management. We evaluated the potential for estimating urban forest LAI spatiotemporally by using Landsat TM imagery. We collected three scenes of Landsat TM (thematic mapper) images acquired in 1997, 2004 and 2010 and conducted a field survey to collect urban forest LAI. Finally, spatiotemporal maps of the urban forest LAI were created using a NDVI-based urban forest LAI predictive model. Our results show that normalized differential vegetation index (NDVI) could be used as a predictor for urban forest LAI similar to natural forests. Both rapid urbanization and urban greening contribute to the changing process of urban forest LAI. The urban forest has changed considerably from 1997 to 2010. Urban vegetated pixels decreased gradually from 1997 to 2010 due to intensive urbanization. Leaf area for the study area was 216.4, 145.2 and 173.7 km2 in the years 1997, 2004 and 2010, respectively. Urban forest LAI decreased sharply from 1997 to 2004 and increased slightly from 2004 to 2010 because of numerous greening policies. The urban forest LAI class distributions were skewed toward low values in 1997 and 2004. Moreover, the LAI presented a decreasing trend from suburban to downtown areas. We demonstrate the usefulness of TM remote-sensing in understanding spatiotemporal changing patterns of urban forest LAI under rapid urbanization and urban greening