甘三酯立体专一分析的研究：（Ⅱ）甘三酯立体专一分析方法初探

在第一部分综合讨论的基础上对甘三酯立体专一分析方法作了初步探讨。以液体油(菜油)及固体脂(猪脂)为基质,系统地研究了这一分析方法,取得了经验并补充了一些具体验证方法。分析液体油的结果与文献数据相一致,分析猪脂的结果欠佳,还存在一些问题需待进一步研究。     

地震勘探技术在焉耆盆地勘探开发中的合理应用探讨

地震勘探技术应用可以分为以二维地震研究构造为主的地震勘探初级阶段、以地震地层学为主的地震勘探中级阶段、以三维地震油藏静态描述为主的地震勘探高级阶段、以地震储层研究为主的开发地震妆级阶段和以四维地震进行油藏监测为主的开发地震高级阶段。针对5个不同阶段的地质条件和地质任务，选择使用合理的地震勘探技术是有效提高勘探开发效益的重要途径。焉耆盆地的勘探开发体现了以地震勘探为主的思路，在勘探开发过程中重视了针对不同勘探开发阶段和不同的地质 地震技术，因此，在早期勘探开发中取得了很好的经济效益。     

A comparative study of numerical solutions to non-linear discrete crack modelling of concrete beams involving sharp snap-back

Numerical problems are often encountered in modelling crack propagation in concrete beams using non-linear finite element (FE) analysis, especially when sharp snap-back behaviour in load-displacement relations occurs. This paper firstly identifies 16 arc-length control based numerical strategies based on extensive literature review. They are then used to carefully model the structural behaviour of a four-point single notched shear beam using discrete crack modelling approach in which cracks are represented by interface elements with bilinear softening constitutive laws. Based on extensive FE analyses, detailed comparisons of the merits and demerits of these numerical algorithms are then made. The results indicate that the effectiveness and efficiency of different algorithms may vary considerably from one to another, with the local arc-length based procedures in conjunction with tangential stiffness strategy and reversible unloading model being the most robust.     

降低发电装置CO2排放的对策初探

分析了老式与新式发电装置每度电产生CO_2的量,并提出了相应的对策。     

基于Multisim8的压控振荡电路仿真分析

介绍了Multisim8的仿真功能的特点，并通过实例说明了用Multisim8进行仿真分析的具体方法，简单介绍了如何设置参数和进行仿真操作。     

电容传感器在使用中存在的几个问题及处理方法

随着电容测量技术的迅速发展，电容传感器在非电量测量和自动检测中得到广泛应用，但它在使用过程中也存在一些问题，针对在使用电容传感器过程中存在的几个问题，从电容传感器的原理和工作过程两个方面进行了讨论，并提出行之有效的处理方法。     

Relating catalyst structure and composition to the water–gas shift activity of Cu–Zn-based mixed-oxide catalysts

In order to investigate the effect of cerium oxide on Cu–Zn-based mixed-oxide catalysts four catalyst samples were characterized by means of XRD, in situ XANES and thermogravimetric analysis. The activity of the catalyst samples was tested for the forward water–gas shift reaction. Cerium oxide was found to increase the crystallinity of the ZnO phase indicating a segregation of the Cu and ZnO phases. The TOF of the water–gas shift reaction based on chemisorption data was found to be independent of composition and preparation conditions of the four catalyst samples. In contrast, the catalyst stability depends on composition and preparation conditions. Cerium oxide impregnated before calcination of the hydrotalcite-based Cu–Zn precursors leads to a more stable water–gas shift catalyst.     

A Bayesian propensity score adjustment for latent variable modeling and MCMC algorithm

The estimation of the differences among groups in observational studies is frequently inaccurate owing to a bias caused by differences in the distributions of covariates. In order to estimate the average treatment effects when the treatment variable is binary, Rosenbaum and Rubin [1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41-55] proposed an adjustment method for pre-treatment variables using propensity scores. Imbens [2000. The role of the propensity score in estimating dose-response functions. Biometrika 87, 706-710] extended the propensity score methodology for estimation of average treatment effects with multivalued treatments.However, these studies focused only on estimating the marginal mean structure. In many substantive sciences such as the biological and social sciences, a general estimation method is required to deal with more complex analyses other than regression, such as testing group differences on latent variables. For latent variable models, the EM algorithm or the traditional Monte Carlo methods are necessary. However, in propensity score adjustment, these methods cannot be used because the full distribution is not specified.In this paper, we propose a quasi-Bayesian estimation method for general parametric models that integrate out the distributions of covariates using propensity scores. Although the proposed Bayes estimates are shown to be consistent, they can be calculated by existing Markov chain Monte Carlo methods such as Gibbs sampler. The proposed method is useful to estimate parameters in latent variable models, while the previous methods were unable to provide valid estimates for complex models such as latent variable models.We also illustrated the procedure using the data obtained from the US National Longitudinal Survey of Children and Youth (NLSY1979-2002) for estimating the effect of maternal smoking during pregnancy on the development of the child's cognitive functioning.     

Robustness of classification rules that incorporate additional information

The discrimination problem for two normal populations with the same covariance matrix when additional information on the population is available is considered. A study of the robustness properties against training sample contamination of classification rules that incorporate this additional information is performed. These rules have received recently attention where their total misclassification probability (TMP) is proved to be lower than Fisher's linear discriminant rule. The results of a simulation study on the TMP which compares the behaviour of the new rules against Fisher's rule and some of its robustified versions under different types of contamination are presented. These results show that the rules that incorporate the additional information not only have lower TMP, but they also prevent against some types of contamination. In order to achieve prevention from all types of contamination a robustifed version of these rules is recommended.     

比较法在房地产开发中的应用

对"比较法"原理和应用情况进行了分析,说明其在房地产开发中能够科学地预测房地产的价格和收益,从而提高财务分析的科学性和权威性,为项目决策提供科学依据,以促进"比较法"在房地产开发中的应用。