Comparative study of crude oils from the Machete area in the Eastern Venezuelan Basin by pyrolysis of asphaltenes

This work is an analysis of crude oil samples from the two most recent producing wells in the Machete area (Orinoco Tar Belt, Venezuela). The aim is to determine the type of environment in which the precursor organic materials were deposited. In spite of the fact that the degree of maturity and the biodegradation of the two crude oils are similar, their characterization leads us to conclude that they have very distinctive and different origins. The comparative study was performed by separating their main fractions, pyrolysis of asphaltenes, and further identification of several indicators (aromatic, polar and sulfur compounds, linear aliphatic hydrocarbons, and cadalene). Moreover, several biomarkers (terpanes, hopanoids and steranes) present in the saturated fractions obtained from the two crude oils were analyzed by using gas chromatography combined with mass spectrometry (GC–MS). The statistical study of geochemical indicator values and relative proportions of lipid and lipid-like biomarkers present in products from asphaltene pyrolysis shows a high probability of there being two distinct crude oil families from the Machete area.     

Encapsulation of Bromocresol Green pH Indicator into a Sol‐Gel Matrix

The bromocresol green pH indicator was encapsulated into transparent monolithic silica matrices using acid catalyzed sol‐gel reaction. Tetraethylorthosilicate was used for the entrapment of the bromocresol green indicator. The immobilized bromocresol green shows behavior similar to its solution counterpart. It retains its structure during the sol‐gel reactions in terms of response to pH and albumine. The polarized light microscopy has indicated that the bromocresol green molecules are strongly interacted within the host silica network.     

Program Fullerene: A software package for constructing and analyzing structures of regular fullerenes

Fullerene (Version 4.4) is a general purpose open‐source program that can generate any fullerene isomer, perform topological and graph theoretical analysis, as well as calculate a number of physical and chemical properties. The program creates symmetric planar drawings of the fullerene graph and generates accurate molecular 3D geometries by way of force‐field optimization, serving as a good starting point for further quantum theoretical treatments. It includes a number of fullerene‐to‐fullerene transformations, such as Goldberg–Coxeter transforms, Stone–Wales transforms, Endo–Kroto, Yoshida–Fowler, and Brinkmann–Fowler vertex insertions. The program is written in standard Fortran and C++ and can easily be installed in a Linux or UNIX environment. © 2013 Wiley Periodicals, Inc.     

两不同部件并联可修系统动态解的最优控制

针对修复时间服从任意分布的两不同部件并联可修系统的模型,把系统方程的解转化为Volterra积分方程的形式,用范数指标函数作为衡量控制变量的标准,以及系统在某一时刻T的最优控制问题.     

关于C题四个质量指标之间关系的研究

对C题四个指标数据之间数量关系进行多角度的探讨,获得一些较好的结果.     

复合油藏试井分析解的相似结构

针对复合油藏,建立了考虑井筒储集和表皮效应和三种外边界(无穷大、定压、封闭)条件下的试井分析模型;利用Laplace变换,在Laplace空间中得到了储层压力和井底压力分布的精确解;经全面和深入的分析,发现了描述该类油藏在三种外边界条件下的渗流特征的解式之间具有的相似结构,并作了进一步的讨论.这项研究,极大地方便了试井分析软件的编制,对油气藏渗流规律的理论研究也具有深远的意义.     

Bifurcation indicator based on meshless and asymptotic numerical methods for nonlinear poisson problems

We propose in this work new algorithms associating asymptotic numerical method and meshless discretization (MFS‐MPS: Method of fundamental solutions‐Method of particular solutions) to compute branch solutions of nonlinear Poisson problems. To detect singular points on these branches, geometrical indicator, Padé approximants, and analytical bifurcation indicator are proposed. Numerical applications show the robustness and the effectiveness of the proposed algorithms. © 2014 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 30: 978–993, 2014     

Prediction of financial distress: An empirical study of listed Chinese companies using data mining

The deterioration in profitability of listed companies not only threatens the interests of the enterprise and internal staff, but also makes investors face significant financial loss. It is important to establish an effective early warning system for prediction of financial crisis for better corporate governance. This paper studies the phenomenon of financial distress for 107 Chinese companies that received the label ‘special treatment’ from 2001 to 2008 by the Shanghai Stock Exchange and the Shenzhen Stock Exchange. We use data mining techniques to build financial distress warning models based on 31 financial indicators and three different time windows by comparing these 107 firms to a control group of firms. We observe that the performance of neural networks is more accurate than other classifiers, such as decision trees and support vector machines, as well as an ensemble of multiple classifiers combined using majority voting. An important contribution of the paper is to discover that financial indicators, such as net profit margin of total assets, return on total assets, earnings per share, and cash flow per share, play an important role in prediction of deterioration in profitability. This paper provides a suitable method for prediction of financial distress for listed companies in China.     

基于k-means聚类与粗糙集算法的指标筛选方法研究

针对多属性决策中指标的信息重复和不确定性问题,提出了一种基于改进的k-means聚类与粗糙集算法相结合的指标筛选方法。首先,定义样本的空间分布密度,实现初始聚类中心优化的k-means算法,对连续型指标进行离散化处理;然后利用粗糙集的相对约简原理进行指标约简,删除存在信息重复的冗余指标,并结合绿色经济指标体系构建的案例验证了该方法的合理性和有效性。