女娲人首蛇身形象的结构分析

本文通过古籍中对女娲记载的分析,确定大约汉代时人们对女娲人首蛇身的形象已经形成相对一致的认识;并从野性的思维角度重新审视半人半兽形象的由来,认为人首蛇身是思维对自然—文化秩序进行调和的产物,并具体结合女娲神话分析了人首蛇身的来源和内涵,以及蛇身在大母神形象中的意义、蛇多样的象征意义对女娲神格的影响。     

东临碣石在绥中——《我从龙河走来》选载

读初中的时候就背诵过魏武帝曹操东临碣石,以观沧海这句脍炙人口的诗篇.那么,碣石究竟在哪里呢?我们到辽河流域采访时终于找到了答案: 碣石就在辽宁省绥中县.     

当代印度政坛中的雅利安人入侵理论争议初探

长期以来,由于受西方知识界对印欧文化百年研究积累的影响,＂雅利安人入侵理论＂始终位居学界主流,并进入印度与世界各国的教科书中,成为我们诠释印度古代历史的重要基础;时至今日,在后殖民学术批判风潮与印度教民族主义的推波助澜之下,此一理论却俨然成为具有高度政治争议性的论题。影响所及,不光是在印度国内的学界,更波及全世界的印度学研究社群。究竟对于＂雅利安人入侵理论＂的争论如何影响当代印度政治发展？此一理论为什么又能引起如此惊人的政治效应？各方对于此一理论的基本立场差异又是如何？透过本文的讨论,我们希望能针对这些问题提出回答。     

吸烟对免疫功能的影响

本文就烟草在吸燃过程中产生的有害物质对免疫功能的影响,并阐述吸烟对人体的危害。     

中国宏观经济对沪市的波动溢出效应研究——基于VAR（k）-MGARCH—BEKK（1，1）模型

本文基于VAR（k）-MGARCH—BEKK（1,1）模型和Wald检验探讨了2003—2008年期间的全国银行间同业拆借利率、汇率、企业商品价格指数、工业增加值增长率、M0、宏观景气指数和消费价格指数对沪市的波动溢出效应,结果表明,除了企业商品价格指数和M0之外,其它宏观经济指标的增长率（速度）均对沪市收益率产生显著的、直接的波动溢出效应。     

关于层次分析法的数值试验

通过对层次分析法进行数值模拟,证实了次序性程度不仅对评价结果存在着显著的影响,而且也与一致性指标存在着密切的关系,同时也证实了标度精度不足是导致多种标度并存的原因,并建议采用适当的标度精度,这一观点与Saaty是一致的。实验结果还清楚地表明,单纯使用一致性指标判定一个矩阵好坏是不够的,应该辅助以其它指标。     

Frequency of Selecting Noise Variables in Subset Regression Analysis: A Simulation Study

This article presents the results of a simulation study of variable selection in a multiple regression context that evaluates the frequency of selecting noise variables and the bias of the adjusted R ² of the selected variables when some of the candidate variables are authentic. It is demonstrated that for most samples a large percentage of the selected variables is noise, particularly when the number of candidate variables is large relative to the number of observations. The adjusted R ² of the selected variables is highly inflated.     

A Likelihood-Based Approximation to the Cumulative Distribution Function of the Noncentral t Distribution

Optimal designs for estimating the parameters and also the optimum factor combinations in multiresponse experiments have been considered by various authors. However, till date, in mixture experiments optimum designs have been studied only in the single response case. In this article, attempt has been made to investigate optimum designs for estimating optimum mixing proportions in a multiresponse mixture experiment.     

Multi-Step Classification Trees

Many algorithms originated from decision trees have been developed for classification problems. Although they are regarded as good algorithms, most of them suffer from loss of prediction accuracy, namely high misclassification rates when there are many irrelevant variables. We propose multi-step classification trees with adaptive variable selection (the multi-step GUIDE classification tree (MG) and the multi-step CRUISE classification tree (MC) to handle this problem. The variable selection step and the fitting step comprise the multi-step method.

We compare the performance of classification trees in the presence of irrelevant variables. MG and MC perform better than Random Forest and C4.5 with an extremely noisy dataset. Furthermore, the prediction accuracy of our proposed algorithm is relatively stable even when the number of irrelevant variables increases, while that of other algorithms worsens.     

Accuracy Analysis of the Percentile Method for Estimating Non Normal Manufacturing Quality

We consider asymmetric kernel estimates based on grouped data. We propose an iterated scheme for constructing such an estimator and apply an iterated smoothed bootstrap approach for bandwidth selection. We compare our approach with competing methods in estimating actuarial loss models using both simulations and data studies. The simulation results show that with this new method, the estimated density from grouped data matches the true density more closely than with competing approaches.