论非均匀断层滑动弱化速率的标定

尝试用二维断层模型来描述断层在不稳定开始时滑动弱化速率的定标律。断层由一系列受滑动摩擦力作用变弱的片区组成，这些片区被牢固的障碍体所分隔。第一组断层包含不同尺度总滑动长度相同的片区的平均分布，而第二组断层由各种分形康托尔集合组成。破裂的整体活动性质由指数增长率λ来描述。对无限均匀的断层，系数λ由摩擦定律的弱化速率控制。在非均匀断层系中我们估算每一个断层的弱化速率，因为一个断层系的指数增长率λ与均匀断层是一致的。利用这种均匀断层的破裂过程，我们根据不同尺度均匀性断层和给定的系数λ来计算弱片区上的弱化速率。对于大尺度的破裂，弱化速率与尺度无关，长片区的开始过程类似于无限断层的破裂情况。本文考虑的是小尺度和所有不同几何形状的破裂，弱化速率记为α=β0^*／a，其中a为破裂尺度或者单个断层长度的一半，β0^*≈1．158。本文计算了滑动弱化距离Dc的值，在此基础上讨论了计算结果的物理含义，并给出了这个参数与尺度相关的可能解释。     

由ODP Leg191布设的海底井下宽频带地震仪系统

名为WP-2的新井下地震观测站由ODP Leg191成功地布设在西北太平洋海盆的ODP1179E钻孔。为了研究地球构造，WP-2台站被安置在一个独特的点位。两套宽频带地震仪用水泥固定在玄武岩层内，通过ROV号潜艇来驱动系统并检查系统的工作状态。ROV也用于回收初始数据。WP-2台站的地震噪声水平对地震观测而言是足够低的。     

灌溉后的黄土剪切特征变化

在中国甘肃省的黑方台阶地上从上世纪60年代开始出现人类定居和开垦活动,并自1968年发展为灌溉农业。随着灌溉的进行地面已出现沉陷和滑坡。地表沉陷是由灌溉水的充填引起黄土结构崩塌造成的。然而崩塌和湿润化对剪切特征的影响目前还不清楚。为了研究湿化后的黄土剪切特征的变化,进行了对马兰黄土未经扰动和重塑土样的直接剪切盒测试。结果显示未扰动土样的粘合力和内摩擦角在湿润化后都下降了,而所观察到的重塑土的弹度参数只有少许变化。未扰动土的不饱合粘合力,据认为其受胶结物质的影响,在饱合后消失了。经灌溉的土的不饱合强度参数与未灌溉土相比表现出差异,它们可能受土壤水分的强烈影响。     

穿过俄勒冈州图拉丁山脉的重力研究：波特兰都市区地壳结构的解释和地震危险性

穿过波特兰市区西部图拉丁山脉（波特兰山）的高分辨率重力测量，展现出以前根据地表地质学和航磁测绘识别出的断层的证据。本次重力测量是在1996年沿着长4．5km的双孔隧道进行的，该隧道在当时的建设中及现在一直在波特兰市区与波特兰山以西的居民区之间通轻便火车。在隧道内的重力从西到东逐渐增加，这种情况反映了隧道位于西边的图拉丁盆地低密度沉积物与其东边高密度大部分隐蔽的始新世玄武岩之间。叠加在这一梯度之上的是几个阶梯状异常，我们将其解释为密度明显差异的岩石之间断续接触的证据。这些异常的最大值发生在西尔万克里克之下，这里存在一条以前测绘出的断层。另一异常发生在距西洞口1200m处，大约是隧道与航磁异常相交汇的部位，航磁异常与西尔万断层（原来称为奥特菲尔德断层）有关。以这些重力资料为依据的岩石学横剖面显示出阶梯状异常与陡倾逆断层相一致，虽然走滑位移也许同样重要。与上方地形洼地相对应的3个重力低异常可能反映存在着剪切带。几个中等地震（M≥3．5）1991年发生在隧道当前的位置，说明这些断层中的几条或波特兰山断层带的其他断层是地震活动断层。     

2004年12月26日苏门答腊—安达曼地震激发的地球自由振荡

根据300~500S的面波估计得到的哈佛大学矩心矩张量断层机制,当周期大于1000S时,地球的地震自由振荡的振幅将异常地大。我们对一个比较陡的断层应用根据地震的体波和面波得到的更真实的破裂模型,估计了自由振荡的振幅近似等于地震矩(6.5×1022N.M),这相当于矩震级为9.15。由于破裂的持续时间达600S,故断层破裂模型足以描述地震的观测结果,但却低估了大地测量位移,这些位移表明在尼科巴群岛和安达曼群岛下面发生了缓慢的断层运动。     

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.     

Satellite estimates and subpixel variability of rainfall in a semi-arid grassland

卫星估雨精度的不确定性受到当地降雨类型和像元内降雨非均匀性影响,而结合这两个关键因素开展半干旱草原卫星估雨的研究有限.2009年夏,我们在中国锡林郭勒半干旱草原用多部微雨雷达和雨量计构建了9 km卫星像元降雨观测网,观测了像元内降雨非均匀性(空间变异系数CV),并评估了卫星估雨精度.结果表明:(1)CV值受像元内平均降雨量,降雨类型,降雨云面积及移向等影响,如高Cv值的降雨过程大多为平均降雨量小,对流性降雨过程,降雨云边缘像元CV值较高;(2)TRMM 3B42V7卫星估雨产品适用性较好,CMORPH和PERSIANN次之,但TRMM 3B42V7易在半干旱草原湖泊处高估降雨.     

Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks

In recent years,landslide susceptibility mapping has substantially improved with advances in machine learning.However,there are still challenges remain in landslide mapping due to the availability of limited inventory data.In this paper,a novel method that improves the performance of machine learning techniques is presented.The proposed method creates synthetic inventory data using Generative Adversarial Networks(GANs)for improving the prediction of landslides.In this research,landslide inventory data of 156 landslide locations were identified in Cameron Highlands,Malaysia,taken from previous projects the authors worked on.Elevation,slope,aspect,plan curvature,profile curvature,total curvature,lithology,land use and land cover(LULC),distance to the road,distance to the river,stream power index(SPI),sediment transport index(STI),terrain roughness index(TRI),topographic wetness index(TWI)and vegetation density are geo-environmental factors considered in this study based on suggestions from previous works on Cameron Highlands.To show the capability of GANs in improving landslide prediction models,this study tests the proposed GAN model with benchmark models namely Artificial Neural Network(ANN),Support Vector Machine(SVM),Decision Trees(DT),Random Forest(RF)and Bagging ensemble models with ANN and SVM models.These models were validated using the area under the receiver operating characteristic curve(AUROC).The DT,RF,SVM,ANN and Bagging ensemble could achieve the AUROC values of(0.90,0.94,0.86,0.69 and 0.82)for the training;and the AUROC of(0.76,0.81,0.85,0.72 and 0.75)for the test,subsequently.When using additional samples,the same models achieved the AUROC values of(0.92,0.94,0.88,0.75 and 0.84)for the training and(0.78,0.82,0.82,0.78 and 0.80)for the test,respectively.Using the additional samples improved the test accuracy of all the models except SVM.As a result,in data-scarce environments,this research showed that utilizing GANs to generate supplementary samples is promising because it can improve the predictive capability of common landslide prediction models.     

Diagnosis of trace metal contamination in sediments: the example of Ensenada and El Sauzal, two harbors in Baja California, Mexico

Total metal concentrations in sediments from within Ensenada and El Sauzal Harbors are generally higher than at the mouths. Grain-size analyses suggested that this enrichment could be due to the presence of fine-grained sediments in the inner part of the harbors rather than to anthropogenic perturbations. The (Me/Al)(sample) ratios for Pb, Co, Ni and Fe were significantly higher for Ensenada Harbor relative to El Sauzal Harbor, whereas the ratios for Cd, Mn, Zn and Cu were statistically equivalent for both harbors. Calculated enrichment factors [EF(Me)=(Me/Al)(sample)/(Me/Al)(shale)] indicated that the metals showing slight enrichment were those associated with anthropogenic contamination (Pb, Zn), or probably related to primary productivity in the water column (Cd, Co). The levels of most of the metals were not greatly enriched, a consideration that is of the utmost importance when contamination issues are at stake.     

浅成磷钙土中的铀

磷钙土被广泛用于生产肥料的原料或直接用作肥料。对它的研究非常深入,包括分析微量元素组分。发现沉积岩中微量元素的一般分面规律和从磷钙土的实际农业化学应用观点出发是很重要的,因为在其组分中的部分微量元素是微量肥料,而部分（例如铀）则在生态上是危险的。磷钙土是获得铀的重要矿石,美国大部分铀正是从磷钙土中获取的。