论普里什文哲理散文中的生态文学思想与猎人情结

普里什文哲理散文中所具有的预言式生态思想与环保理念备受当代“生态文学”理论家的青睐。但他热衷描写狩猎场景的猎人情结却又遭到新世纪中“生态伦理”理论的诟病。其实从文本的本体性观念来理解，普里什文的诗性自然情怀、生态观念与他的猎人情结并非只有冲突的一面，他所表达出的是人对大自然万物之本能与道义之间的尺度衡量，而这种衡量也可反观当代人与自然万物之间的关系的现状，实际上表达出一种更为深刻的天人关系的批判性。     

Reducing sample size needed for cox-proportional hazards model analysis using more efficient sampling method

Abstract

In general, survival data are time-to-event data, such as time to death, time to appearance of a tumor, or time to recurrence of a disease. Models for survival data have frequently been based on the proportional hazards model, proposed by Cox. The Cox model has intensive application in the field of social, medical, behavioral and public health sciences. In this paper we propose a more efficient sampling method of recruiting subjects for survival analysis. We propose using a Moving Extreme Ranked Set Sampling (MERSS) scheme with ranking based on an easy-to-evaluate baseline auxiliary variable known to be associated with survival time. This paper demonstrates that this approach provides a more powerful testing procedure as well as a more efficient estimate of hazard ratio than that based on simple random sampling (SRS). Theoretical derivation and simulation studies are provided. The Iowa 65+ Rural study data are used to illustrate the methods developed in this paper.     

自然科学与基督教的关系探讨——以自然科学的起源和前沿为视角

文章首先通过分析自然科学与基督教方法论发展上的相似,来说明近代自然科学在本源上与基督教的紧密联系,论证了近代自然科学在基督教欧洲发生的必然性.其次通过阐述当代自然科学一些前沿问题的研究进展来证明自然科学和基督教世界观的内在一致性.最后试图以基督教和近代自然科学的关系为先导,提出一些具有现实价值的、值得各领域一起合作探索的问题.同时也希望本文能够纠正一些长久以来存在于人们脑海中由于特定宗教、文化和意识形态下以偏概全的观念.     

模糊语言的独特功能

本文对模糊语言的独特功能从日常生活、文学作品、科学医学三方面进行了探讨 ,从而阐明在自然语言中 ,模糊语言是绝对的、普遍的。语言的模糊性缘于客观事物本身的模糊性及人们对客观世界认识的不确定性。     

由社会主体到自然主体——论宋代文人投身自然的几种表现形式

宋代文人投身自然 ,实质上是一种由社会主体向自然主体的角色转换 ,这种角色转换表现为 4个层面 :在行为上诗酒山林、随遇皆乐 ;在心理上“安于冲旷、不与众驱”;在思想上“无愧于中、无责于外”;在感情上“不以物喜、不以己悲”。这四个层面归结到一点 ,则是抒写山水 ,营造“心灵屋宇”。文人们在这些“心灵屋宇”中流泄的是真挚的情感 ,人生的顿悟和孤芳自赏的高洁品格     

长白山自然保护区科考旅游开发研究

本文根据长白山自然保护区的自然特点和开发优势,提出了开展科考旅游的设想,详细阐述了本区发展科考旅游的科学内涵,线路选择,标牌设计,导游培训与指南编制和环境管理.     

A simple estimator for a shared frailty regression model

Summary. We propose a simple estimation procedure for a proportional hazards frailty regression model for clustered survival data in which the dependence is generated by a positive stable distribution. Inferences for the frailty parameter can be obtained by using output from Cox regression analyses. The computational burden is substantially less than that of the other approaches to estimation. The large sample behaviour of the estimator is studied and simulations show that the approximations are appropriate for use with realistic sample sizes. The methods are motivated by studies of familial associations in the natural history of diseases. Their practical utility is illustrated with sib pair data from Beaver Dam, Wisconsin.     

A partial score test for difference among heterogeneous populations

In event time data analysis, comparisons between distributions are made by the logrank test. When the data appear to contain crossing hazards phenomena, nonparametric weighted logrank statistics are usually suggested to accommodate different-weighted functions to increase the power. However, the gain in power by imposing different weights has its limits since differences before and after the crossing point may balance each other out. In contrast to the weighted logrank tests, we propose a score-type statistic based on the semiparametric-, heteroscedastic-hazards regression model of Hsieh [2001. On heteroscedastic hazards regression models: theory and application. J. Roy. Statist. Soc. Ser. B 63, 63–79.], by which the nonproportionality is explicitly modeled. Our score test is based on estimating functions derived from partial likelihood under the heteroscedastic model considered herein. Simulation results show the benefit of modeling the heteroscedasticity and power of the proposed test to two classes of weighted logrank tests (including Fleming–Harrington's test and Moreau's locally most powerful test), a Renyi-type test, and the Breslow's test for acceleration. We also demonstrate the application of this test by analyzing actual data in clinical trials.     

Estimation of dependence between paired correlated failure times in the presence of covariate measurement error

Summary. In many biomedical studies, covariates are subject to measurement error. Although it is well known that the regression coefficients estimators can be substantially biased if the measurement error is not accommodated, there has been little study of the effect of covariate measurement error on the estimation of the dependence between bivariate failure times. We show that the dependence parameter estimator in the Clayton–Oakes model can be considerably biased if the measurement error in the covariate is not accommodated. In contrast with the typical bias towards the null for marginal regression coefficients, the dependence parameter can be biased in either direction. We introduce a bias reduction technique for the bivariate survival function in copula models while assuming an additive measurement error model and replicated measurement for the covariates, and we study the large and small sample properties of the dependence parameter estimator proposed.     

The 2003 Heat Wave in France: Dangerous Climate Change Here and Now

In an analysis of the French episode of heat wave in 2003, this article highlights how heat wave dangers result from the intricate association of natural and social factors. Unusually high temperatures, as well as socioeconomic vulnerability, along with social attenuation of hazards, in a general context where the anthropogenic contribution to climate change is becoming more plausible, led to an excess of 14,947 deaths in France, between August 4 and 18, 2003. The greatest increase in mortality was due to causes directly attributable to heat: dehydration, hyperthermia, heat stroke. In addition to age and gender, combinatorial factors included preexisting disease, medication, urban residence, isolation, poverty, and, probably, air pollution. Although diversely impacted or reported, many parts of Europe suffered human and other losses, such as farming and forestry through drought and fires. Summer 2003 was the hottest in Europe since 1500, very likely due in part to anthropogenic climate change. The French experience confirms research establishing that heat waves are a major mortal risk, number one among so-called natural hazards in postindustrial societies. Yet France had no policy in place, as if dangerous climate were restricted to a distant or uncertain future of climate change, or to preindustrial countries. We analyze the heat wave's profile as a strongly attenuated risk in the French context, as well as the causes and the effects of its sudden shift into amplification. Research and preparedness needs are highlighted.