克隆人技术应用的“能做”与“应做”

本文基于哲学的维度 ,以对人的解读为切入点 ,在工具理性与价值理性的紧张中 ,分析克隆人技术应用的“能做”与“应做”,反思并祛魅工具理性 ,寻求价值理性与工具理性的统一。笔者认为 :在严格的意义上人是不可被复制的 ,克隆人技术至多只是开辟了人类繁衍、自身生命再生产的一个新途径 ;工具理性并不能从根本上解决人性与社会问题 ;试图在基因层次上确定“完人”终极标准的努力既不现实 ,又十分危险 ;克隆人技术及其应用作为一种工具理性 ,必须有其目的性价值 ;在对克隆人技术及其应用采取理性谨慎态度的同时 ,应当对探究科学未知活动给予社会宽容。     

考古材料所见生殖器崇拜考--以云南史前及青铜时代为例

文章以云南史前及青铜时代的考古发掘为主,结合各地考古资料,论述了生殖崇拜的宗教意义。     

故障诊断技术的应用

介绍了在工程界已广泛应用的信号分析诊断及尚停留在实验室探索的裂纹分析诊断,模糊分析诊断的工作原理和应用实例。     

Residual analysis for spatial point processes (with discussion)

Summary.  We define residuals for point process models fitted to spatial point pattern data, and we propose diagnostic plots based on them. The residuals apply to any point process model that has a conditional intensity; the model may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Some existing ad hoc methods for model checking (quadrat counts, scan statistic, kernel smoothed intensity and Berman's diagnostic) are recovered as special cases. Diagnostic tools are developed systematically, by using an analogy between our spatial residuals and the usual residuals for (non-spatial) generalized linear models. The conditional intensity λ plays the role of the mean response. This makes it possible to adapt existing knowledge about model validation for generalized linear models to the spatial point process context, giving recommendations for diagnostic plots. A plot of smoothed residuals against spatial location, or against a spatial covariate, is effective in diagnosing spatial trend or co-variate effects. Q – Q -plots of the residuals are effective in diagnosing interpoint interaction.     

Goodness‐of‐fit methods for matched case‐control studies

The authors propose graphical and numerical methods for checking the adequacy of the logistic regression model for matched case‐control data. Their approach is based on the cumulative sum of residuals over the covariate or linear predictor. Under the assumed model, the cumulative residual process converges weakly to a centered Gaussian limit whose distribution can be approximated via computer simulation. The observed cumulative residual pattern can then be compared both visually and analytically to a certain number of simulated realizations of the approximate limiting process under the null hypothesis. The proposed techniques allow one to check the functional form of each covariate, the logistic link function as well as the overall model adequacy. The authors assess the performance of the proposed methods through simulation studies and illustrate them using data from a cardiovascular study.     

Bayesian analysis of outlier problems using divergence measures

A Bayesian approach is presented for detecting influential observations using general divergence measures on the posterior distributions. A sampling-based approach using a Gibbs or Metropolis-within-Gibbs method is used to compute the posterior divergence measures. Four specific measures are proposed, which convey the effects of a single observation or covariate on the posterior. The technique is applied to a generalized linear model with binary response data, an overdispersed model and a nonlinear model. An asymptotic approximation using Laplace method to obtain the posterior divergence is also briefly discussed.     

The birds and the bees: interactive graphics and problem solving in the teaching of statistics

Software which allows interactive exploration of graphical displays is widely available. In addition there now exist sophisticated authoring tools which allow more general textual and graphical material to be presented in computer-based form. The role of an authoring tool in providing a graphical interface to a strategy for solving simple statistical problems in the context of teaching is discussed. This interface allows a variety of resources to be integrated. Specific examples, including the use of dynamic graphical displays in exploring data and in communicating the meaning of a model, are proposed. These ideas are illustrated by a problem involving the identification of the sex of a herring gull.     

On the effectiveness of cognitive feedback from an interface agent

The objective of this study was to determine the impact of task information (TI) provided by an interface agent during the idea evaluation and integration step of the problem formulation stage of the problem solving process. The effectiveness assessment was based on solving diagnostic decision problems in the domain of complex industrial machinery. Ten domain experts participated in this study. Decision support was provided by a case-based reasoning system. Findings suggest that TI provided by the interface agent had no effect on the decision maker's performance, nor on the associated cognitive effort. However, a verbal protocol analysis revealed that the ten subjects used the interface agent to verify their decision processes. The results and their implications are discussed with respect to current findings in the area of decision support systems.     

Comparing diagnostic tests: test of hypothesis for likelihood ratios

Likelihood ratios (LRs) are used to characterize the efficiency of diagnostic tests. In this paper, we use the classical weighted least squares (CWLS) test procedure, which was originally used for testing the homogeneity of relative risks, for comparing the LRs of two or more binary diagnostic tests. We compare the performance of this method with the relative diagnostic likelihood ratio (rDLR) method and the diagnostic likelihood ratio regression (DLRReg) approach in terms of size and power, and we observe that the performances of CWLS and rDLR are the same when used to compare two diagnostic tests, while DLRReg method has higher type I error rates and powers. We also examine the performances of the CWLS and DLRReg methods for comparing three diagnostic tests in various sample size and prevalence combinations. On the basis of Monte Carlo simulations, we conclude that all of the tests are generally conservative and have low power, especially in settings of small sample size and low prevalence.     

A log-Birnbaum–Saunders regression model with asymmetric errors

This paper introduces a skewed log-Birnbaum–Saunders regression model based on the skewed sinh-normal distribution proposed by Leiva et al. [A skewed sinh-normal distribution and its properties and application to air pollution, Comm. Statist. Theory Methods 39 (2010), pp. 426–443]. Some influence methods, such as the local influence and generalized leverage, are presented. Additionally, we derived the normal curvatures of local influence under some perturbation schemes. An empirical application to a real data set is presented in order to illustrate the usefulness of the proposed model.