济阳坳陷CO2气藏同位素地球化学特征及成因

济阳坳陷CO2气藏主要发育在高青-平南深断裂中南段和阳信次级凹陷西北缘及商店火山岩穹隆构造内。气藏中CO2气体浓度为69％～97％，δ^13CCO2值为-5．67‰～-3．35‰，CH4／^3He值为（1．01～5．65）×10^8，^3He／^1He值为（2．80～4．49）×10^-6，即R／Ra为2．00～3．21，^40Ar／^36Ar值为317～1791，CO2/^3He值为（0．25～2．61）×10^9。以上地球化学数据表明，济阳坳陷气藏中CO2主要来源于地慢，且慢源CO2在成藏过程中有损失，或者有壳源CO2的加入，特别是部分碳酸盐岩变质成因CO2的加入。在对CO2气来源定性分析的基础上，还需要在各来源的定量区分和CO2气藏的成藏及其与岩浆活动的时空匹配关系等方面作进一步的研究.

Graphitic nanofilaments as novel support of Ru-Ba catalysts for ammonia synthesis

A novel graphitic-nanofilament-(GNF-) supported Ru-Ba catalyst is prepared and used in ammonia synthesis reaction. The Ru-Ba/GNFs catalyst shows remarkably high activity and stability for ammonia synthesis, which can be attributed to high purity and graphitization of GNFs with unique structure. TEM micrographs of the Ru-Ba/GNFs catalysts show that Ru metal particles uniformly disperse on the outer wall of GNFs, and the particles become bigger than that before ammonia synthesis reaction after 50 h of operation at 500degreesC and 7.0 MPa, probably due to the Ru crystals covered by promoter and support materials and/or sintering of Ru crystals. (C) 2002 Elsevier Science (USA).

Computer System for Visual Recognition Using Active Knowledge

A system for visual recognition is described, with implications for the general problem of representation of knowledge to assist control. The immediate objective is a computer system that will recognize objects in a visual scene, specifically hammers. The computer receives an array of light intensities from a device like a television camera. It is to locate and identify the hammer if one is present. The computer must produce from the numerical "sensory data" a symbolic description that constitutes its perception of the scene. Of primary concern is the control of the recognition process. Control decisions should be guided by the partial results obtained on the scene. If a hammer handle is observed this should suggest that the handle is part of a hammer and advise where to look for the hammer head. The particular knowledge that a handle has been found combines with general knowledge about hammers to influence the recognition process. This use of knowledge to direct control is denoted here by the term "active knowledge". A descriptive formalism is presented for visual knowledge which identifies the relationships relevant to the active use of the knowledge. A control structure is provided which can apply knowledge organized in this fashion actively to the processing of a given scene.