12至13世纪的蒙古人及其政权

地理环境在蒙古高原形成其独特的历史和文明方面非常重要。蒙古高原广阔的山地草原构成世界两大文明区,即中亚绿洲文明区和从多瑙河延伸至中国长城的欧亚草原文明带的一部分。很久以来,蒙古高原就处于世界交通的交叉口。两条大动脉,即伟大的丝绸之路和又叫草原丝绸之路的欧亚草原走廊,将蒙古高原与东西文明中心地区连接起来。游牧文明的出现是对中亚那个特殊地方自然地理挑战的合理回应。     

图像和原型与智能手机对生活世界的遮蔽

智能手机的图像制造能力给本真生活世界的表象造成了威胁。这种威胁被认为在全球出现并且无处不在,在视听和文本图像方面,它用数字生成的表象取代了本真生活世界的特有表象。对于这个问题,大约一百年前,胡塞尔就借助于形式化数学的概念进行了描绘,他认为这是对本真的非形式化的数学生活世界存在的遮蔽,并因此是对前形式化的数学生活世界存在的遮蔽。然而更早,柏拉图在《智者篇》中就对这个问题进行了经典阐述,他认为,真理问题与表象(幻象)问题是不可分割的,原型图像性的非表象和图像的表象之间的对立被原型和图像的表象之间的对立所取代,而存在与非存在多元化的显现排除了关于真假表象之区分的明证性知识。在展现和代现中,胡塞尔对客体的直接被给予性进行了开创性的洞察,在柏拉图对谬误之真的表象进行描述的基础上,对诸幻相和图像意识进行了补充性描述。在胡塞尔那里,现象学阐明了表象的根本性起源,以及在此基础上它是如何显现的。然而,智能手机的幻影给世界的真正表象带来了扰乱,致使在今天的技术干扰来临之际,现象学尽管拥有最为强大的能力,却中断了世界显现的道路,并且因此中断了它的表象自身。     

人口流动对基督教全球传播的影响

基督教流动人口是基督教在全球传播过程中的关键因素。在基督教存在的前五个世纪,广泛的人口流动将基督教变成了全球化的信仰。广泛的人口流动在其它主要的世界宗教在世界各地的传播过程中也发挥了重要作用,但是,就基督教来说,流动可能是这种信仰固有的因素。基督教超越罗马帝国成为全球性信仰是个非常复杂的过程,包含许多不同类型的人口流动。跨国界的领袖们、俘虏、难民和流浪者、商人是人口流动的四种主要类型。虽然,东部教会传教的成功是短暂的,但是东部教会在第一个千年形成的移民传教模式无疑为21世纪的基督教提供了典范。基督教在过去的两三个世纪里再次全球化,基督信仰作为新的中心在非洲、拉丁美洲和亚洲的某些地区出现,表明"人口流动"在基督教全球传播过程中的作用比以前更加明显。当代基督教的全球化与早期基督教的全球化在发展道路上有很大不同,但有一点是不变的,即基督教的全球化仍将主要依靠流动者的行动和决策。     

从国际关系社会学到世界政治社会学

形成于20世纪下半叶的国际关系社会学是社会学的研究方向之一.其实质是将社会学的研究方法应用于国际关系研究.然而,国际关系社会学却没能成为独立的社会学门类,很多国家仍将其归属于国际关系理论范畴.随着国际进程快速发展与科学知识不断激增,出现了世界政治社会学这一新的社会学方向,并有成为独立的社会学门类的趋势.     

Analysis of quality-of-life adjusted failure time data in the presence of competing, possibly informative, censoring mechanisms

We derive estimators of the mean of a function of a quality-of-life adjusted failure time, in the presence of competing right censoring mechanisms. Our approach allows for the possibility that some or all of the competing censoring mechanisms are associated with the endpoint, even after adjustment for recorded prognostic factors, with the degree of residual association possibly different for distinct censoring processes. Our methods generalize from a single to many censoring processes and from ignorable to non-ignorable censoring processes.     

A simple two-stage design for quantitative responses with application to a study in diabetic neuropathic pain

Two-stage designs offer substantial advantages for early phase II studies. The interim analysis following the first stage allows the study to be stopped for futility, or more positively, it might lead to early progression to the trials needed for late phase II and phase III. If the study is to continue to its second stage, then there is an opportunity for a revision of the total sample size. Two-stage designs have been implemented widely in oncology studies in which there is a single treatment arm and patient responses are binary. In this paper the case of two-arm comparative studies in which responses are quantitative is considered. This setting is common in therapeutic areas other than oncology. It will be assumed that observations are normally distributed, but that there is some doubt concerning their standard deviation, motivating the need for sample size review. The work reported has been motivated by a study in diabetic neuropathic pain, and the development of the design for that trial is described in detail.     

Models for the analysis of C-reactive protein in statin trials

Elevation in C-reactive protein (CRP) is an independent risk factor for cardiovascular disease progression and levels are reduced by treatment with statins. However, on-treatment CRP, given baseline CRP and treatment, is not normally distributed and outliers exist even when transformations are applied. Although classical non-parametric tests address some of these issues, they do not enable straightforward inclusion of covariate information. The aims of this study were to produce a model that improved efficiency and accuracy of analysis of CRP data. Estimation of treatment effects and identification of outliers were addressed using controlled trials of rosuvastatin. The robust statistical technique of MM-estimation was used to fit models to data in the presence of outliers and was compared with least-squares estimation. To develop the model, appropriate transformations of the response and baseline variables were selected. The model was used to investigate how on-treatment CRP related to baseline CRP and estimated treatment effects with rosuvastatin. On comparing least-squares and MM-estimation, MM-estimation was superior to least-squares estimation in that parameter estimates were more efficient and outliers were clearly identified. Relative reductions in CRP were higher at higher baseline CRP levels. There was also evidence of a dose-response relationship between CRP reductions from baseline and rosuvastatin. Several large outliers were identified, although there did not appear to be any relationships between the incidence of outliers and treatments. In conclusion, using robust estimation to model CRP data is superior to least-squares estimation and non-parametric tests in terms of efficiency, outlier identification and the ability to include covariate information.     

Missing item imputation for quality-of-life instruments with application to asthma quality-of-life questionnaires

There has been increasing use of quality-of-life (QoL) instruments in drug development. Missing item values often occur in QoL data. A common approach to solve this problem is to impute the missing values before scoring. Several imputation procedures, such as imputing with the most correlated item and imputing with a row/column model or an item response model, have been proposed. We examine these procedures using data from two clinical trials, in which the original asthma quality-of-life questionnaire (AQLQ) and the miniAQLQ were used. We propose two modifications to existing procedures: truncating the imputed values to eliminate outliers and using the proportional odds model as the item response model for imputation. We also propose a novel imputation method based on a semi-parametric beta regression so that the imputed value is always in the correct range and illustrate how this approach can easily be implemented in commonly used statistical software. To compare these approaches, we deleted 5% of item values in the data according to three different missingness mechanisms, imputed them using these approaches and compared the imputed values with the true values. Our comparison showed that the row/column-model-based imputation with truncation generally performed better, whereas our new approach had better performance under a number scenarios.