黄土滑坡研究现状与设想

黄土滑坡因其危害大、分布广成为近年工程地质研究热点问题。首先对黄土滑坡类型划分进行了讨论,基于滑坡物质组成及主滑面发育位置的黄土滑坡分类方案反映了我国黄土滑坡的主控因素,各类滑坡活动特征明确,建议将其作为黄土滑坡分类的首选方案。对黄土滑坡的发生、滑动机制以及滑坡液化机制进行了评述,并就两类典型液化型黄土滑坡滑动模式、进一步研究思路进行了讨论。对地震诱发黄土滑坡进行了专门的述评。最后,对今后黄土滑坡研究提出了几点设想。     

基于LSB的遥感图像安全传输模型

互联网在方便人们交流、共享信息的同时,也带来了极大的安全问题.信息隐藏是解决信息安全的一种有效手段,研究采用LSB法实现重要目标遥感图像信息的隐藏,实验证明该方法可以有效地解决网上图像传输出现的安全问题.     

冬小麦夏玉米土壤水分预报及优化灌溉模型

利用土壤水分平衡方程，结合河南省冬小麦和夏玉米的生长规律和1994～2000年冬小麦、夏玉米田实测土壤湿度资料，建立了河南省冬小麦、夏玉米土壤水分预报及优化灌溉的计算机模型。用1998～1999年郑州市麦田实测土壤湿度资料验证该模型模拟结果，未来10、20、30天土壤湿度相对误差分别为-7．3％～7．7％、-8．3％～6．8％、-7．6％～7．7％，表明利用该模型，可以较为准确地预报未来1个月的土壤水分变化，并可根据小麦、玉米不同发育期特点，给出以最高产量和最佳经济效益为目标的灌溉建议。     

超级计算机上矩阵乘的并行计算与实现

数值预报系统中经常要用到矩阵乘运算。在分布式超级计算机 (如IBM-SP) 上, 矩阵乘的并行计算需要较多的数据移动, 有效的数据传输对矩阵乘的实现至关重要。该文讨论了两种矩阵乘的并行算法, 一种是基于矩阵的列-行划分方式, 一种是基于矩阵的网格划分方式。在IBM-SP计算机上的实验结果表明, 网格划分的矩阵乘并行算法通讯开销更小, 并行效率更高, 其并行加速比较列-行并行算法改善约10 %。     

山东平邑归来庄碲型金矿床中黄铁矿的矿物学特征研究

归来庄贫硫氧化型低温热液碲金矿床中黄铁矿形成于3个世代，不同世代黄铁矿的S／Fe均小于2，硫的质量分数平均值50．9％(小于标准值53．4％)，显示出明显的硫元素匮乏。不同时期的黄铁矿在晶形上有较明显的差异，并出现环带、环边及交代环边等结构构造。随着成矿作用的不断进行，从成矿早阶段到晚阶段成矿热液中的硫由于硫化物的不断结晶而消耗，成矿热液中硫逸度持续降低，可供进入黄铁矿品格的硫越来越少。成矿晚期，成矿热液中的砷替代硫大量进入黄铁矿的晶格中而形成与归来庄金矿床成矿作用密切相关的富砷黄铁矿，对该类型矿床具有找矿勘探的指示意义。     

基于强度折减概念的滑坡稳定性三维分析方法(Ⅱ):加固安全系数计算

结合乌江洪家渡1#塌滑体加固设计工程,探讨了滑动面已知的条件下滑坡稳定性的三维分析方法。首先,模拟了塌滑体在天然状态下处于极限平衡状态时的滑动方向,并使用其应力成果计算了塌滑体的三维安全系数;其次,建议了基于强度折减概念的三维加固安全系数计算方法:最后,提出了加固设计的进一步优化方案。计算结果表明,塌滑体的滑动方向与局部地形等高线近于垂直。主滑方向变化较大,自后缘的NE15°方向逐步过渡到中部的NS向,最终过渡到前缘的NE30°方向,以致很难作出能表征主滑方向的地质剖面。基于应力计算成果的安全系数计算公式不能充分考虑滑坡体的抗滑潜能,也不能充分反映滑坡体的滑动方向,安全系数偏大。基于强度折减概念的三维加固安全系数计算方法具有有限元等方法的优点,较好地克服了上述局限性,可以合理地评价加固后的滑坡稳定性。     

我国地震海浪初步分析

总结了我国地震海浪的25次记录,在做初步分析后认为我国的地震海浪多由近海海洋地震引起,其多发地区为渤海沿岸与东南沿海一带.随着对沿海地区开发的深入,这类记载逐渐增多,受灾程度加大.另外分析了在社会历史变迁中,国家对海洋的开发政策、沿海开发下城市近海地理位置、沿海港口及海洋贸易的规模与地震海浪受灾程度之间的关系.     

Experimental study on reduction of U (Ⅵ) by an anaerobic bacterium, Shewanella putrefaciens: Application to sandstone-hosted interlayer oxidation-zone type uranium deposits, China

An experimental study on reduction of U (Ⅵ) by anaerobic bacteria, Shewane//a putrefaciens, is first reported here in China. The experimental conditions were: 35℃ and pH =7.0-7.4, corresponding to a physicochemical environments in which the sandstone-hosted interlayer oxidation-zone type uranium deposit formed in Northwest China's Xinjiang. Bacteria adopted in the present experiment, Shewanella putrefaciens, occur extensively in natural environment. Our study shows that nano-crystal precipitates of uraninite quickly occurred on the surface of the cells within one week. It was found that the pitchblende was characterized by a random arrangement of uraninite nanocrystals (2-4 nm) in it, significantly different from natural pitchblende in which uraninite nanocrystals are arranged in order. Finally, a possible mechanism of uranium biomineralization by microorganisms in the deposits is discussed. Our investigation may supply a technical train of thoughts for bioremediation of nuclear-contaminated water environments and for underground dissolving extraction of the sandstone-hosted uranium ores.     

Biomineralization of Uranium: A Simulated Experiment and Its Significance

A simulated experimental reduction of U^v1 and the synthesis of uraninite by a sulfate-reducing bacteria,Desulfovibrio desulfuricans DSM 642, are first reported. The simulated physicochemical experimental conditions were:35℃, pH=7.0-7.4, corresponding to the environments of formation of the sandstone-hosted interlayer oxidation-zone type uranium deposits in Xinjiang, NW China. Uraninite was formed on the surface of the host bacteria after a one-week‘s incubation. Therefore, sulfate-reducing bacteria, which existed extensively in Jurassic sandstone-producing environments,might have participated in the biomineralization of this uranium deposit. There is an important difference in the orderdisorder of the crystalline structure between the uraninite produced by Desulfovibrio desulfuricans and naturally occurring uraninite. Long time and slow precipitation and growth of uraninite in the geological environment might have resulted in larger uraninite crystals, with uraninite nanocrystals arranged in order, whereas the experimentally produced uraninite is composed of unordered uraninite nanocrystals which, in contrast, result from the short time span of formation and rapid precipitation and growth of uraninite. The discovery has important implications for understanding genetic significance in mineralogy, and also indicates that in-situ bioremediation of U-contaminated environments and use of biotechnology in the treatment of radioactive liquid waste is being contemplated.