青藏高原祖尔肯乌拉山地区火山岩Ar-Ar年代学初步研究

对祖尔肯乌拉山地区 4个火山岩样品进行了Ar -Ar年龄测定 ,其坪年龄分别为 (40 91± 1 18)Ma、(41 0 7± 0 80 )Ma、(42 0 0± 1 31)Ma、(39 0 0± 2 0 6 )Ma。它们代表了这些火山岩的形成时代 ,表明本区在古近纪始新世中期发生过大规模的火山活动     

沸石在水环境治理中的应用现状与前景

文章叙述了沸石的基本结构以及吸附、离子交换特性，总结了近年来国内外有关沸石在水环境保护方面的研究与应用成果，提出了沸石在今后的水环境保护和改善方面将具有广泛的应用前景。     

Impact of habitat heterogeneity on plant community pattern in Gurbantunggut Desert

1IntroductionStudy on the interrelationship between vegetation patterns and their habitat heterogeneity is important to recover and rehabilitate the desert vegetation, stabilize the desert ecosystem and prevent desert expansion. Domestic and foreign researchers have carried out many studies on this topic (Archer etal., 2002; Bolling etal., 2000; Chen etal., 2003; Dasti etal., 1994; Gu etal., 2002, Li etal., 2001; Li etal., 2001; Liang etal., 2003), which have used and refined statistic tech…     

亚、欧两大洲自然地理环境结构的整体性和差异性教学初探

地理环境的结构，是指地理环境各组成要素之间和各组成部分之间相互关系性质的组合，它包括既有联系、又有区别的两个方面，即地理环境结构的整体性和差异性。笔者在亚、欧两洲自然地理数年的教学实践中，从自然环境结构的整体性和差异性特征入手，得出分析、综合、概括归纳和对比研究等方法是学习世界区域地理的主要方法。     

世界政治新形势下的中国经济安全观

当前，世界政治形势处于动荡催生调整，调整蕴含机遇，在单极与多极矛盾的碰撞与互动中，正在形成某种更有效的机制，培育更为成熟、理性竞争的意识，促使各主要大国为世界的持久和平与繁荣共同担负起应有的责任。因此，国家经济安全是世界各国都普遍关注的战略问题。本文首先总结了就当今世界政治发展的四个特点，并在分析国际形势新变化对中国经济安全影响的基础上，提出了维护我国经济安全的六点思考。     

Wavelet analysis and interpretation of gravity data in Sichuan-Yunnan region, China

Introduction Sichuan-Yunnan region, located in the east margin of Qinghai-Xizang (Tibetean) Plateau, is a transitional zone between the rapidly upheaving Tibetean Plateau and relatively steady Yangtze Platform. Under the pressure exerted by the northward movement of Indian Plate, Sichuan-Yunnan region has been undergone strong deformation and regmagenesis, becoming one of the regions with the most intensive seismicity in the world. The research on the tectonics and seismicity there is alw…     

山西大同市农村民居震害特征及防震对策

1989年10月18日山西大同-阳高发生了6.1级地震,在这次地震中,倒塌房屋31 348间,其中,倒塌的大部分是土窑洞.可见,减轻地震灾害的关键是提高建筑物的抗震性能.     

Ruthenium-ion-catalyzed oxidation of asphaltenes and oil-source correlation of heavy oils from the Lunnan and Tahe oilfields in the Tarim Basin, NW China

The identification of marine source rocks in the Tarim Basin is debated vigorously. The intention of this paper is to investigate the asphahenes in heavy oils from the Lunnan and Tabe oilfields and Well TD2 with ruthenium-ions-catalyzed oxidation technique (RICO), in order to explore its role in oil-oil and oil-source correlations, The RICO products included n-alkanoic acids, α,ω-di-n-alkanoic acids, branched alkanoic acids, tricyclic terpanoic acids, hopanoic acids, gammacerane carboxylic acid , regular sterane carboxylic acids and 4-methylsterane carboxylic acids. The n-alkyl chains and biomarkers bounded on the asphaltenes were of unsusceptibility to biodegradation. The distribution and absolute concentrations of n-alkanoic acids in the RICO products of heavy oils from the Lunnan and Tabe oilfields are different from those of Well TD2. The biomarkers bounded on the asphahenes, especially steranes, have a distribution trend similar to that of the counterparts in saturates. The sterane carboxylic acids and 4-methylsterane carboxylic acids in the RICO products of heavy oils from the Lunnan and Tahe oilfields, dominated by C30 sterane and C31 4-methylsterane carboxylic acids, respectively, are significantly different from those of the heavy oils of Well TD2, whose dominating sterane and 4-methylsterane carboxylic acids are C28 sterane and C29 4-methylsterane acids, respectively. The RICO products of the asphaltenes further indicate that the Middle-Upper Ordovician may be the main source rocks for heavy oils from the Lunnan and Tabe oilfields.     

云南沿边境地带生态环境3S监测、 评价与调控研究

本文利用全球新千年整体生态系统评估的理论，以云南省沿边境地带生态系统变化跨境生态安全为研究对象，探寻并揭示我国陆疆系统的跨境生态系统变化监测、评价和生态安全综合调控的基础理论与信息机理；进而研究基于“3S”云南沿边境地带的生态环境监测、评价与综合调控的方法和关键技术，包括方法和技术体系的建立、指标体系的建立、多尺度效应和尺度转换、数学模型的建立、综合调控模式和决策方案的建立等；在案例研究部分，建立了背景数据库，然后选择大、中、小尺度进行了全区生态环境现状评价，重点河道、典型路段和重点口岸的影响评价和预测预报研究，最后进行了综合调控模式和方案的探讨，并对研究结果进行了动态仿真和虚拟表达研究。     

基于多模态感知的水下目标检测应用构想

水下目标检测在海洋生物研究、考古探索、军事防御等多领域广泛应用,随着人工智能快速发展,水下目标检测也朝着无人化、智能化发展。深度学习采用神经网络挖掘信息特征,在速度和精度上均表现出优异的性能,成为了计算机视觉技术的主流算法,然而水下环境复杂,将其应用于水下图像目标检测仍存在较大的挑战。水下目标各模态信息互补,特征丰富,有利于目标检测识别,因此结合应用场景调研现有技术,然后设计基于深度学习的多模态水下目标检测系统,同时对比分析了现有关键技术的优缺点,最后对多模态目标检测系统未来发展进行总结与展望,具有重要意义。