我国“十五“电力供需预测分析

分析“十五”期间我国电力需求预测和电力预测中的不确定因素,提出建议采取的措施。     

Investigation of the impact of changes in demand forecasting method on the financial performance of an electricity supply undertaking

Peak demand forecasts obtained from six different univariate forecasting methods, under a range of conditions, were used to drive a capacity acquisition model of a large electrical supply system; and the resulting physical and financial performance of the model was observed for each set of forecasts. The results obtained are discussed in the context of their implications for the choice of load forecasting method used in capacity acquisition planning by a power supply undertaking.     

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.     

未结盟大学的联盟

通过梳理管理学界对战略联盟的定义，发现价值链的鸸释同样适用于大学问的战略联盟。通过对已有的大学战略联盟的分析，提出了名校联盟与非名校联盟间的若干差异，最后提出了我国大学联盟战略的若干建议。     

Conceptual damage-sensitive features for structural health monitoring: Laboratory and field demonstrations

The use of damage-sensitive features to evaluate structural condition or health is a very critical aspect of structural health monitoring. The purpose of this paper is to investigate the potential of two different damage-sensitive features for detecting damage. Different damage scenarios are simulated on a large-scale laboratory structure and a three-span highway bridge for demonstration. The features presented in this paper are the modal flexibility-based deflection and curvature both of which are obtained directly from dynamic properties. In the literature, flexibility associated with mode shapes and mode shapes curvatures have been mostly explored. In this study, multi-input–multi-output dynamic data are used to obtain modal flexibility, which is a close approximation to the actual flexibility. A main novelty is that the curvature is calculated from the deflected shapes using the modal flexibility as opposed to using modal vectors. In this paper, the theory of the methodology is explained and then experimental studies and results are presented. For the experimental studies, the laboratory specimen and the three-span bridge were gradually damaged. It is shown that both deflection and curvature are conceptual and physically meaningful features for damage detection and localization. The issues and the requirements for these features to perform successfully are also presented.     

充分关注水质科学保障饮水安全

从我国饮水安全的现状入手，分析城乡饮水安全存在的问题，强调保障饮水安全是构建和谐社会的必然要求和水利工作的切实要务。从加强监测、科学规划，加强关键技术研究及推广应用，保护水源地、修复水环境，建立合理的体制与机制四个方面提出了做好保障饮水安全工作的建议。     

Heterogeneous chain propagation in low-pressure flames

An analysis of papers on hydrogen combustion at low pressures is performed, which refines the contribution of the catalytic reactions on the reactor wall to the gas-phase part of the process. A new model for the heterogeneous loss of active reaction centers was proposed and tested experimentally to explain inconsistencies that occur in some papers. In this model, the diffusion region of chain termination is formed under standard experimental conditions in vacuum oxyhydrogen flames at a reactor gas pressure a thousand times lower than the boundary pressure postulated by the previous models as the pressure below which the diffusion region of chain termination cannot be formed. __________ Translated from Fizika Goreniya i Vzryva, Vol. 42, No. 2, pp. 10–18, March–April, 2006.     

靶向抗癌药格列卫与其治疗白血病疗效监测

Gleevec是抑制致癌的融合蛋白BCR-ABL的一种分子靶向治疗药物,BCR-ABL是一种与慢性髓细胞性白血病(CML)有关的酪氨酸激酶抑制剂。用Gleevec选择性地抑制BCR-ABL活性在治疗CML中显示出很好的效果,特别是在CML慢性期,因此,监测疗效非常重要。现就Gleevec的研究进展及如何监测其在CML中的疗效作一简单综述。     

马尔可夫链在企业经济预测上的应用

为了科学的预测企业所关心的各项经济指标 ,以便为企业的未来做出正确的决策方案 ,需用适当的数学模型和方法对企业的经济活动进行定量的研究 .基于经济活动的复杂、多变性及带有许多随机性因素的特点 ,针对这两种常见的经济问题 ,分别建立了相应的马尔可夫链模型 .应用马尔可夫链的相关理论、巧妙的构造转移概率矩阵 ,只通过简单的矩阵运算 ,便迅速解决问题 .实例表明 ,马尔可夫链模型及方法在企业经济活动分析中是可行和适用的 ,可广泛用于解决企业中常见的预测及决策问题 .     

烧结成品运输自动控制系统的改进

对烧结成品运输自控系统不稳定性因素进行了分析，提出了采取优化硬件外围工作环境，完善软件保护程序等改进措施。改进后的自控系统稳定性明显提高。