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We present the analysis of ROSAT HRI and PSPC X-ray data on the compact cD type cluster Abell 4059. The central cD galaxy hosts the strong radio source PKS 2354[35. The central portion of the X-ray image shows two statistically signiÐcant X-ray emission minima and an orthogonal X-ray bar. As is the case in NGC 1275, the radio lobes in PKS 2354[35 lie perpendicularly to the X-ray bar and extend into the two X-ray minima. One suggestion is that the radio lobe plasma has displaced the X-ray plasma and created the X-ray holes. The radio plasma and the X-ray gas do have comparable pressures in the radio lobe area. However, the available radio images do not show radio emission that extends far enough to Ðll the two X-ray holes. An alternative scenario for the anticorrelated radio and X-ray structure is an rotating disk in the cooling Ñow region of Abell 4059.The ROSAT HRI surface brightness proÐle shows that there is a cooling Ñow around the central cD galaxy with a cooling rate of yr~1 within a radius of 156 kpc. However, the ROSAT M 0 \ 184~2 5 22 M _ PSPC spectrum of the central regions does not require a cooling Ñow and gives an upper limit to the cooling rate of yr~1 (90% conÐdence level). The X-ray spectra of the central region indicate M 0 \ 80 M _ very little intrinsic absorption in the cluster, with an upper limit of cm~2 for excess *N H ¹ 4.0 ] 1019 absorption in front of the cluster emission at the center of the cooling Ñow. On large scales, the cluster shows interesting spatial alignment between the major axes of the X-ray emission, cD galaxy, and the cluster potential. This is consistent with the anisotropic merger model for the formation of cD galaxies and the orientation of cD galaxy radio sources.

Wildfires have a profound impact upon the biosphere and our society in general. They cause loss of life, destruction of personal property and natural resources and alter the chemistry of the atmosphere. In response to the concern over the consequences of wildland fire and to support the fire management community, the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS) located in Camp Springs, Maryland gradually developed an operational system to routinely monitor wildland fire by satellite observations. The Hazard Mapping System, as it is known today, allows a team of trained fire analysts to examine and integrate, on a daily basis, remote sensing data from Geostationary Operational Environmental Satellite (GOES), Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors and generate a 24 hour fire product for the conterminous United States. Although assisted by automated fire detection algorithms, N O M has not been able to eliminate the human element from their fire detection procedures. As a consequence, the manually intensive effort has prevented NOAA from transitioning to a global fire product as urged particularly by climate modelers. NASA at Goddard Space Flight Center in Greenbelt, Maryland is helping N O M more fully automate the Hazard Mapping System by training neural networks to mimic the decision-making process of the frre analyst team as well as the automated algorithms.Two years ago, the Computing, Information and Communications Technology (CICT), Program operating out of the Ames Research Center in Moffett Field, California, provided fimding for the research effort to get underway. A team of government and (ultimately) University personnel were assembled with the intent of applying artificial intelligence techniques to NOAA's automation problem. NASA began archiving satellite imagery from GOES, AVHRR and MODIS satellite sensors in the summer of 2003. Three spectral channels for each of 3 science instruments were provided by NOAA NESDIS by uploading to a NASA computer within the Information Systems Division at Goddard Space Flight Center. The following spectral bands, being only a subset of those available from each instrument, were found to be the most useful in fire identification by NESDIS: MODIS channels 1 (0.66 pm), 2 (0.86 pm), 22 (3.96 pm); AVHRR channels 1 (0.66 pm), 2 (0.91 pm), 3b(3.7 pm), and GOES channels 1 (0.62 pm), 2 (3.9 pm), 4 (10.7 pm). Both reflectance and brightness temperature were scaled by NESDIS to a range of 0 -255.A good deal of thought, time and attention went into the composition of adequate neural https://ntrs.nasa.gov/search.jsp?R=20050180316 2018-05-12T15:13:20+00:00Z