用工业CT技术测量储层岩芯饱和度分布

认识储层岩石中含油饱和度及饱和度分布,对驱替机理的深入研究是非常重要的。为了搞清储层岩石在驱替过程中的饱和度分布情况,应用工业CT技术,提出了一种储层含油岩芯被驱替后的饱和度分布的CT密度差测量方法。在岩样的同一断面,分别对干岩样、饱和岩样及在驱替后的岩样进行CT扫描,重建相应的断层图象,测量所建图象的灰度值,计算出相应的密度值,用密度差法计算出饱和度及其分布值。在γ射线工业CT机“CD-300BG”上对某油田岩样进行了实际测量,获得的结果说明,采用CT密度差法测量饱和度分布是有效的。该方法与常规驱替法相比较,具有快速、精度高、无损岩样和能模拟地层状态测量等特点,是油田开发、油藏描述和地层评价的一种新的有效方法。     

Complete moment convergence and Lr convergence for asymptotically almost negatively associated random variables

In this paper, we investigate the complete moment convergence and L_r convergence for maximal partial sums of asymptotically almost negatively associated random variables under some general conditions. The results obtained in the paper generalize some corresponding ones for negatively associated random variables.     

高职院校工学结合教学中的困境与对策

工学结合是高职院校提高人才培养质量的重要途径,是学生尽早胜任岗位需求的必要环节。目前,许多院校在工学结合实施的过程中遇到诸多困难,文章首先分析了工学结合实施中的困境,比如经费不足、企业参与度不高、学生缺乏认同感、师资队伍紧缺等等,其次就如何面对困境提出相应的对策。     

集体行动的村庄有组织建设模式探讨——以花都区毕村为例

农用地被征收,村庄建设用地开发权被压制,征用制度的缺陷以及村庄引导政策的缺失,往往容易导致城市边缘的村庄无序及低效开发,从而形成环境恶劣、效益低下的城边村或城中村,导致集体土地与土地开发权的矛盾日益明显。本文以广州东风日产边上的毕村为例,在保留村民宅基地的前提下,通过宅基地置换、多余用地集中建设以及增益公共还原等政策,探讨村庄的有组织建设模式并以此推动村集体行动,形成良好的村庄形态,以及高效的集体资产建设。     

美国BIT范本的环境政策考量与变迁及其对中国的启示

美国从1981年启用第一个BIT范本,之后历经数次修订,形成不同版本。其中的环境保护条款从无到有、从简到繁,2012年版本对环境保护又有大力强化。虽然环境例外条款具有法律形态,但因其为缔约方保留环境规制的空间,没有消极影响,其他环境条款尤其专门环境条款则只具有政策形态,对缔约方只有倡导和督促作用,因而也不具有负面意义。基于此,对于中美BIT谈判,中国应该持有像实践WTO规则一样的心态,研究它、接受它,为投身国际实践走出第一步,为将来参与更大范围的规则制定做好准备。     

大学生心理危机的识别与预警

心理危机的识别与预警既是预防心理危机发生的重要策略，也是对危机当事人和相关人进行生命教育和促进生命成长的重要机会。心理危机产生的原因具有复杂性，发生过程具有阶段性，危机现象具有特殊性，危机爆发具有极端性，危机发生也具有一定规律性。因此，在进行生命教育过程中，需要关注不同类别的生命个体、不同阶段的生命现象、处在规律中的独特生命个体，同时要注意识别生命危机信号和生命求救信号。     

上党神话与长治旅游业之间的共生关系研究

一个地区的旅游业发展与该地的人文、地理、环境等有很大联系。近年来，随着长治旅游业的不断发展，上党神话作为长治地区特有的人文内涵与长治旅游业之间逐渐形成了相互影响、相互促进、相互合作和相互依赖的共生关系。上党神话在长治旅游业的旅游景区方面赋予了神秘的色彩，在旅游产品方面丰富了本地旅游产品的内涵，在旅游需求方面扩展了长治旅游消费市场；同时，长治旅游业对上党神话的普及、发展及延伸也发挥了补充作用。     

A robust and efficient estimation method for nonparametric models with jump points

Nonparametric models with jump points have been considered by many researchers. However, most existing methods based on least squares or likelihood are sensitive when there are outliers or the error distribution is heavy tailed. In this article, a local piecewise-modal method is proposed to estimate the regression function with jump points in nonparametric models, and a piecewise-modal EM algorithm is introduced to estimate the proposed estimator. Under some regular conditions, the large-sample theory is established for the proposed estimators. Several simulations are presented to evaluate the performances of the proposed method, which shows that the proposed estimator is more efficient than the local piecewise-polynomial regression estimator in the presence of outliers or heavy tail error distribution. What is more, the proposed procedure is asymptotically equivalent to the local piecewise-polynomial regression estimator under the assumption that the error distribution is a Gaussian distribution. The proposed method is further illustrated via the sea-level pressures.     

Outlier detection in high-dimensional regression model

An outlier is defined as an observation that is significantly different from the others in its dataset. In high-dimensional regression analysis, datasets often contain a portion of outliers. It is important to identify and eliminate the outliers for fitting a model to a dataset. In this paper, a novel outlier detection method is proposed for high-dimensional regression problems. The leave-one-out idea is utilized to construct a novel outlier detection measure based on distance correlation, and then an outlier detection procedure is proposed. The proposed method enjoys several advantages. First, the outlier detection measure can be simply calculated, and the detection procedure works efficiently even for high-dimensional regression data. Moreover, it can deal with a general regression, which does not require specification of a linear regression model. Finally, simulation studies show that the proposed method behaves well for detecting outliers in high-dimensional regression model and performs better than some other competing methods.     

基于“重要性-影响力”框架的非首都功能疏解路径研究——以北京市动物园服装批发市场搬迁为例

利益相关者分析法是分析复杂管理问题的重要方法,广泛应用于企业管理、项目管理及公共政策领域。随着北京市非首都核心功能的疏解思路的提出,作为低端产业代表的动物园批发市场的外迁势在必行。运用"重要性-影响力"利益相关者分析框架,对动批搬迁政策中涉及的利益相关者进行界定,分别分析其利益诉求并进行合理划分,依据各利益相关者对政策的重要性程度和影响力大小以及各相关者之间的利益冲突分别制定解决对策,同时将各种外部阻力纳入考虑范围,为北京市动物园批发市场搬迁提出可行路径,以期为其他类似公共政策制定问题提供参考。