陕西凤太矿集区多金属成矿作用的构造控制

陕西凤县-太白(简称凤太)矿集区铅、锌、金、银、铜多金属资源丰富,已发现二十余个大中小型矿床。在大地构造位置上,凤太矿集区位于南秦岭造山带北缘,紧邻商丹缝合带。以往的工作缺乏对矿集区整体的构造研究,本次工作通过比较系统的构造测量和解析,提出在南秦岭晚三叠世碰撞造山过程中,凤太矿集区南北两条边界断裂带的左行走滑运动导致在区内衍生了NNE向主压应力场,从而形成了NWW向复式褶皱、脆韧性剪切带、断裂和节理(纵向破裂)、B型线理,以及NNE向断裂和节理(横向破裂)、劈理、张裂隙等一系列构造组合,所有构造形迹都是在统一构造应力场下随着构造层次不断抬升,脆韧性和脆性递进变形叠加的产物,共同构成了一个大型压扭性走滑双重构造变形系统。在构造几何学上,凤太矿集区整体上表现为一个隔档式复式褶皱,由一组NWW向紧闭复背斜和一组相对宽缓复向斜组成。区内的多金属成矿作用、岩浆活动、动力变质变形作用的同位素年龄数据集中于230~190Ma。综合地质演化和成矿作用的研究成果,提出在南秦岭碰撞造山过程中引发的动力变质变形作用和岩浆活动提供了成矿元素和成矿流体,在温压梯度以及浮力效应的驱动下向上运移至走滑双重构造变形系统中的有利扩容空间中发生充填型和交代型矿化,即凤太矿集区多金属矿床是区域大规模变形变质-岩浆活动-流体作用的产物,是在构造作用这一主导因素控制下形成的一个多金属后生热液成矿系统。     

The digital ‘connected’ earth: open technology for providing location-based services on degraded communication environments

In the current world, it is easy to listen that everybody and everything is connected. Over this connected world, the concept of location-based services has grown in order to provide digital services in everyplace and at every time. Nevertheless, this is not 100% true because the connection is not guaranteed for many people and in many places. These are the Degraded Communications Environments (DCE), environments where the availability of high-speed communications is not guaranteed in at least the 75% of the time. This paper works over the experience of a previous work in developing light protocols that do not need broadband for communication. This work provides an extension of these protocols for the inclusion of mobile devices as elements of the communication process and a set of libraries to allow the development of applications in DCE. The work done has involved the development of two frameworks: an Android framework that makes the incorporation of Android devices easier and a server-based framework that provides the server side for the development of the referred applications. A use case that uses these two frameworks has been developed. Finally, all technology developed is available throw a public Git repository.     

Supervised classification of electric power transmission line nominal voltage from high-resolution aerial imagery

For many researchers, government agencies, and emergency responders, access to the geospatial data of US electric power infrastructure is invaluable for analysis, planning, and disaster recovery. Historically, however, access to high quality geospatial energy data has been limited to few agencies because of commercial licenses restrictions, and those resources which are widely accessible have been of poor quality, particularly with respect to reliability. Recent efforts to develop a highly reliable and publicly accessible alternative to the existing datasets were met with numerous challenges – not the least of which was filling the gaps in power transmission line voltage ratings. To address the line voltage rating problem, we developed and tested a basic methodology that fuses knowledge and techniques from power systems, geography, and machine learning domains. Specifically, we identified predictors of nominal voltage that could be extracted from aerial imagery and developed a tree-based classifier to classify nominal line voltage ratings. Overall, we found that line support height, support span, and conductor spacing are the best predictors of voltage ratings, and that the classifier built with these predictors had a reliable predictive accuracy (that is, within one voltage class for four out of the five classes sampled). We applied our approach to a study area in Minnesota.     

渤海湾盆地庙西中南洼围区原油成因类型及分布主控因素

通过原油生物标志化合物参数聚类分析,在对比沙河街组不同层系烃源岩地化特征的基础上,分析了渤海海域庙西中南洼已发现原油的成因类型、来源及其分布规律。结果表明,研究区目前已发现的原油主要有Ⅰ型、Ⅱ型和Ⅲ型3种成因类型,其中：Ⅰ型原油来源于沙三段烃源岩,主要分布在垦利6-4区和蓬莱25区,其进一步可分为Ⅰ₁和Ⅰ₂两个亚类,分别对应中高熟沙三型原油和中低熟沙三型原油;Ⅱ型原油来源于沙三段和沙四段烃源岩,主要分布在蓬莱31区;Ⅲ型原油主要来源于沙四段烃源岩,可能有少量的沙三段烃源岩贡献,主要分布在渤中36区。原油地化特征及分布规律指示研究区为近源成藏特征。综合烃源岩分布特征及断层活动性分析认为蓬莱25区和垦利6-4区原油类型主要受烃源岩控制,而蓬莱31区和渤中36区原油类型和分布受断裂和烃源岩联合控制。     

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.     

基于DBSCAN与网格搜索的雷电定位算法

定位精度是评价雷电定位网络的重要指标之一,定位算法直接影响雷电探测结果的精度。雷电监测系统探测数据误差不可避免,传统定位算法不具备抗误差干扰能力,迭代计算易发散,定位结果精度不高。为了满足实际应用需求,提出一种新的雷电定位算法DG-LLA（DBSCAN and grid-search lighting location algorithm）,在定位计算中引入DBSCAN（density-based spatial clustering of applications with noise）方法与网格搜索方法。通过仿真与国家雷电监测网实际定位结果对比分析定位算法性能。结果表明:到达时间差（time difference of arrival,TDOA）法和Taylor级数展开法定位误差较大,仿真区域的均方根误差分别为982 m和668 m;定位中引入DBSCAN方法后,均方根误差明显减小为406 m,引入DBSCAN方法和网格搜索方法后,均方根误差减小为349 m;在相同回击数据条件下,算法DG-LLA与国家雷电监测网相比定位数量更多,回击数据的利用率从43.4%提升到51.5%,新增定位结果周围雷达回波特征较强,定位精度更高。     

地震工程研究的科学大平台

始于十九世纪末的地震工程研究,在其100多年的历史中积累了大量的理论和实践经验,随之而建设起来的各类地震工程实验设施分布于世界各地。近20年来,信息技术的飞速发展使得分布于世界各地的实验设施通过网络实现协同实验和资源共享。基于以上的信息,为了更好更快地和国际接轨,本文提出了建设一个地震工程研究领域的科学大平台设想。这个大平台包括三个方面的内容:数值模拟,网络协同实验系统和基础信息系统,将形成本领域开放性的综合科学平台。在数值模拟方面,这个科学平台将利用最新的信息技术将本领域的科学研究结果和方法集成起来,形成一个模块式的科学研究平台系统。在网络协同实验方面,将采纳美国NEES的思路,并对其改进和提高之后应用于中国。在基础数据方面,将利用最为先进的数据仓储技术,建设一个可以服务于地震工程科学研究的数据平台。最后,文章给出了建设这个科学平台的规划,以及目前的进展和资金支持等情况。     

制造业活动地理转移视角下的中国产业集群问题

在简要回顾产业集群理论的基础上,在制造业活动地理转移的视角下,结合案例重新审视了我国劳动密集型产业集群的形成及发展.作者认为,一些锁定在低成本竞争的集群正在或已经老化,甚至衰亡.另一些集群中的企业有过度集聚的问题,还有一些中小企业集聚的区域根据产业特征需要增加产业集中度.因为集群的这些问题,随成本上升,出现了集群中企业的加工制造环节外移的现象.这种现象挑战了新产业区理论中集群是"在流动的全球空间中的粘结的区位"的观点.根据集群中企业外移现象,就产业承接地的规划和发展,以及转出地那些正在升级的集群的地理稳定性和生产者服务业的发展问题,提出了几点看法.     

区域产业升级理论评价和升级目标层次论建构

产业升级相关文献综述表明,区域产业升级具有丰富的理论含义.产业结构升级研究寻求对产业宏观结构比例的统计学意义上的优化;产业地域分工思路则考察产业分布演进的空间格局及其升级含义;企业升级思路则细化到产业内部,指出企业创新以获得更高附加值是产业升级的根本;集群研究则注意到区域产业发展的整体特征,并指出了推动产业集聚、产业联系与创新等升级含义.中国集群实践更进一步验证了集群层面集体效率的提升以及企业发展环境的和谐共进(区域发展目标)也是影响产业升级的重要方面.在讨论产业升级的经济维度与空间维度、个体层面与系统层面的基础上重新构建区域产业发展的理论框架,认为企业升级、集群升级和区域和谐3个层次构成了区域产业升级的3个目标层次,其相互衔接与互动对于区域产业发展具有重要意义.     

多元统计分析在金川铜镍矿床两类矿石中的应用

应用聚类分析和因子分析对金川铜镍硫化物矿床样品及其微量元素进行了分析和科学分类,并对分类的样品进行R型因子分析,找寻在成矿作用过程中对成矿贡献起关键性作用的因子。因子分析结果表明,富矿类型的网状矿石与贫矿类型的星点状矿石的Ni,Cu矿化期存在着明显的差异性;网状矿石在成矿作用过程中,经受了晚期晚阶段的中、低温热液作用,使矿石中的主要成矿元素Cu产生了进一步的叠加和富集,并伴有Bi,Se,Te及贵金属元素的富集。因子分析的研究为脉动式多期多阶段的成矿机制模式提供了新的依据,同时,也为矿床中有用伴生元素的赋存状态及找寻提供了有用的成因信息。