Supermassive Binaries and Extragalactic Jets

Some quasars show Doppler shifted broad emission line peaks. I give new statistics of the occurrence of these peaks and show that, while the most spectacular cases are in quasars with strong radio jets inclined to the line of sight, they are also almost as common in radio-quiet quasars. Theories of the origin of the peaks are reviewed and it is argued that the displaced peaks are most likely produced by the supermassive binary model. The separations of the peaks in the 3C 390.3-type objects are consistent with orientation-dependent "unified models" of quasar activity. If the supermassive binary model is correct, all members of "the jet set" (astrophysical objects showing jets) could be binaries.Comment: 31 pages, PostScript, missing figure is in ApJ 464, L105 (see http://www.aas.org/ApJ/v464n2/5736/5736.html

Neural networks in petroleum geology as interpretation tools

Abstract Three examples of the use of neural networks in analyses of geologic data from hydrocarbon reservoirs are presented. All networks are trained with data originating from clastic reservoirs of Neogene age located in the Croatian part of the Pannonian Basin. Training always included similar reservoir variables, i.e. electric logs (resistivity, spontaneous potential) and lithology determined from cores or logs and described as sandstone or marl, with categorical values in intervals. Selected variables also include hydrocarbon saturation, also represented by a categorical variable, average reservoir porosity calculated from interpreted well logs, and seismic attributes. In all three neural models some of the mentioned inputs were used for analyzing data collected from three different oil fields in the Croatian part of the Pannonian Basin. It is shown that selection of geologically and physically linked variables play a key role in the process of network training, validating and processing. The aim of this study was to establish relationships between log-derived data, core data, and seismic attributes. Three case studies are described in this paper to illustrate the use of neural network prediction of sandstone-marl facies (Case Study # 1, Okoli Field), prediction of carbonate breccia porosity (Case Study # 2, Beničanci Field), and prediction of lithology and saturation (Case Study # 3, Kloštar Field). The results of these studies indicate that this method is capable of providing better understanding of some clastic Neogene reservoirs in the Croatian part of the Pannonian Basin

Toward a Multifaceted Heuristic of Digital Reading to Inform Assessment, Research, Practice, and Policy

In this commentary, the author explores the tension between almost 30 years of work that has embraced increasingly complex conceptions of digital reading and recent studies that risk oversimplifying digital reading as a singular entity analogous with reading text on a screen. The author begins by tracing a line of theoretical and empirical work that both informs and complicates our understanding of digital literacy and, more specifically, digital reading. Then, a heuristic is proposed to systematically organize, label, and define a multifaceted set of increasingly complex terms, concepts, and practices that characterize the spectrum of digital reading experiences. Research that informs this heuristic is used to illustrate how more precision in defining digital reading can promote greater clarity across research methods and advance a more systematic study of promising digital reading practices. Finally, the author discusses implications for assessment, research, practice, and policy