Application of visual,statistical and artificial neural network methods in the differentiation of water from the exploited aquifers in Kuwait

The ability of artificial neural network to differentiate water samples from the two aquifers of Kuwait on the basis of their major ion chemistry has been demonstrated. The major ion concentration distribution in the groundwater of the Kuwait Group and the Dammam Formation aquifers of Kuwait appears very similar. Cross-plots, supported by the discriminant function analysis of the data, however, suggest that there are some subtle differences in the overall composition of the water from the two aquifers that make it possible to differentiate the water from the two aquifers in almost 80% of the cases. An artificial neural network improved the differentiation capability to 90% of the cases. It is also possible to estimate the fraction of Kuwait Group water in the flow stream of dually completed wells with the help of an artificial neural network developed for this purpose. Electronic Publication     

A coupled,dynamical and chemical model for the prestellar core L1544: Comparison of modeled and observed C<Superscript>18</Superscript>O,HCO<Superscript>+</Superscript>, and CS emission spectra

We consider radiative transfer in C¹⁸O, HCO⁺, and CS molecular lines in a spherically symmetrical, coupled, dynamical and chemical model of a prestellar core whose evolution is determined by ambipolar diffusion. Theoretical and observed line profiles are compared for the well-studied core L1544, which may be a collapsing protostellar cloud. We study the relationship between the line shapes and model parameters. The structure of the envelope and kinematic parameters of the cloud are the most important factors determining the shape of the lines. Varying the input model parameters for the radiative transfer—the kinetic temperature and microturbulent velocity—within the limits imposed by observations does not result in any substantial variations of the line profiles. The comparison between the model and observed spectra indicates that L1544 displays a flattened structure, and is viewed at an oblique angle. A two-dimensional model is needed to reproduce this structure.     

科尔沁沙地巴克窑地区近150年的环境演变*

在沉积和花粉分析的基础上,对科尔沁沙地东南部巴克窑地区过去150年的植被和环境演变进行了重建。巴克窑等湖泡的诞生时间是在上个世纪前期,约1837年前后。这个时间也正是科尔沁沙地东南部地区首次大规模人口移入和垦荒年代。突然增加的人类活动导致了沙丘植被的迅速破坏,而植被减少和沙丘活化引起区域水文循环的重新调整,即原来通过植物蒸腾作用输出的水量明显减弱,致使地下潜水位上升,形成一系列湖泡。以后,沙地系统的演化主要是在人类活动、气候和系统内部反馈机制的共同作用下完成的。     

开发利用地理信息系统(GIS)综合分析地学信息进行矿产预测

众所周知,矿产资源预测是综合地学信息,进行优选靶区的有效手段之一。随着地学工作的深入和勘探技术的发展,已获取了大量的多源地学信息,如地质、地球物理、地球化学和遥感等资料。怎样从这众多的资料中提取有用信息进行综合分析,达到矿产资源预测的目的,一直是地学界探索的课题。过去,应用人工的方法来进行此项工作,不但费力、投资大,而且难以达到预期的效果,方法技术也不利于推广。如今,高速、高质量的计算机已趋于普及,使应用计算机技术高效地处理堆积如山的资料成为可能,尤其是近些年发展起来的地理信息系统(GIS),为综合处理地学资料的矿产资源预测的方法技术,开拓了广阔的前景。地理信息系统是一种计算机系统的应用软件,它集数据库管理和图像分析技术为一体,以空间数据迭加分析为重要特征。地学工作者进行矿产资源预测时,通常是从多源地学资料中提取有用信息,再应用专家知识,结合数学方法,如逻辑运算、贝叶斯(Bayes)规则等,建立预测模型,以模型的推理网格为线索,利用地理信息系统有效的空间分析手段,把各种证据图层综合迭加,最终产生以概率为指标的矿产资源预测图,高概率指示有利的矿产资源远景区,可作为勘探者和决策者进行勘查规划的依据。     

Budd—Chiari综合征的CT评价

回顾性分析了５２例Ｂｕｄｄ－Ｃｈｉａｒｉ综合征的ＣＴ表现，ＣＴ显示肝尾叶增大５０例（９６％），肝脏呈低度密度或密度不均，４２例（８１％）肝静脉未明显，２２例（４２％）见有肝内侧枝血管，４９例（９４％）有肝外侧枝血管，作者认为ＣＴ检查对Ｂｕｄｄ－Ｃｈｉａｒｉ综合征有较高的诊断价值。