同位素中子源活化瞬发分析装置

一、基本原理自六十年代中期以来,中子活化瞬发γ射线元素分析技术(PNAA)得到人们广泛重视。与通常的中子活化分析(NAA)技术相比,它分析的是样品中的主要成分,若用同位素中子源,还可进行实时在线连续测定及现场分析。PNAA技术是用热中子与待测元素发生中子俘获反应,处于激发态的产物核在瞬间     

Physico-chemical properties of ceramic pigments for high-temperature application

Heat resistant coatings are required primarily for stacks, exhaust pipes, reactors, space crafts and similar equipments that are permanently or occasionally exposed to elevated temperatures. High-temperature coatings are generally based on silicone resin with ceramic and metallic pigments. In this study, iron oxide, cobalt oxide (thermo chromic compound) and aluminum oxide are used for the preparation of four new types of coloured pigments. The thermal resistant characteristics of these ceramic pigments were studied by differential thermal analysis, thermo gravimetric analysis and differential scanning calorimetric analysis. These ceramic pigments are found to be thermally stable up to 400 °C.     

Feasibility analysis of membrane reactors – discovery of reactive arheotropes

A feasibility analysis methodology adopted from reactive distillation is applied to membrane reactors. A model is formulated to depict the reactive liquid phase composition on the retentate side of a continuous type membrane reactor. The effects of both the chemical reaction kinetics and the membrane mass transfer kinetics on the feasible products are elucidated by means of retentate phase diagrams and bifurcation analysis. The proposed method can be applied to various membrane processes, independent of the specific structure of the membrane. Two quaternary reaction systems are considered to illustrate the methodology. In the first hypothetical system, it is shown how selective membranes can influence the sequence of effective volatilities which in turn affects the feasible products of the system. In the second example of practical importance, i.e. the heterogeneously catalysed synthesis of propyl acetate coupled with permeation through a porous polycarbonate membrane, the dusty gas model is applied to describe the component fluxes through the membrane. For the latter reaction system, the existence of reactive arheotrope is demonstrated. Arheotropes represent mass transfer controlled feasible products of membrane separation process.     

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。     

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.