习近平关于青年工作重要论述的科学指引与实践要求

习近平关于青年工作重要论述既是对马克思主义青年观一脉相承的理论发展,也是结合中华民族优秀传统文化和中国青年工作的特点所形成的实践创新。通过习近平关于青年工作重要论述理论来源和基本内涵提供的科学指引,从历史维度明确了强化青年时代责任的要求是增强对中国道路、中国理论和中国制度的认同感和责任感,与时代同向同行;从现实维度明确了提升社会适应能力的要求是构建全员全程全方位的育人格局,增强意识形态建设;从青年成长个人维度明确了完善综合素质的要求是在对青年特性和社会地位正确认识的基础上激发其奋斗热情。由此形成进一步发展青年事业的实践路径,即通过筑牢意识形态防线,增强新时代青年的使命担当;优化青年人才培养和选拔模式,提高青年适应社会发展的能力;提升青年综合素质,实现人的全面发展。     

基于ECA规则的工作流时间约束分析

本文着重研究了工作流中各活动间的定量时序关系,提出了一种分析工作流中时间约束的方法。该方法针对基于ECA规则的工作流,通过建立及分析工作流的约束图,对工作流中活动间定量时序约束的一致性进行了分析,从而保证了工作流的正常运行。     

自由知识分子对西安事变的态度浅析——兼与“福建事件”的一个比较

自由知识分子大都认为“西安事变”是“叛乱”，要求武力“勘平叛乱”。“九一八”以来，知识分子对国事的基本态度是，对日本的入侵要求和平谈判方式解决，对内部的军阀“兵变”却要求武力镇压。同“福建事变”时相比，国民党在1936年中，已经逐渐得到知识分子的普遍支持。他们认为中国政治秩序基本稳定，因此张学良以“逼蒋抗日”为由发动的“西安事变”，破坏了知识界所看重的“统一”局面。     

Handling Missing Values in Longitudinal Panel Data With Multiple Imputation

This article offers an applied review of key issues and methods for the analysis of longitudinal panel data in the presence of missing values. The authors consider the unique challenges associated with attrition (survey dropout), incomplete repeated measures, and unknown observations of time. Using simulated data based on 4 waves of the Marital Instability Over the Life Course Study (n = 2,034), they applied a fixed effect regression model and an event‐history analysis with time‐varying covariates. They then compared results for analyses with nonimputed missing data and with imputed data both in long and in wide structures. Imputation produced improved estimates in the event‐history analysis but only modest improvements in the estimates and standard errors of the fixed effects analysis. Factors responsible for differences in the value of imputation are examined, and recommendations for handling missing values in panel data are presented.     

从传统走向现代:近代传奇杂剧的舞台艺术变革

大量的剧本材料表明 ,近代传奇杂剧在服装、道具、烟火、灯光、场幕、布景等方面发生了根本性的变化 ,旋转舞台也开始出现。这些舞台艺术变革与创新是中国戏曲传统的扬弃 ,更是在外国戏剧文化影响下发生发展的。近代传奇杂剧的舞台艺术转变与其他方面的重要变革共同促进了近代戏曲的发展 ,同时也加速了传奇杂剧的式微与消亡。这种深刻的历史转变是古典戏曲向现代戏剧转变的一道津梁 ,对中国传统戏曲格局的终结和现代戏剧格局的建立也起了重要作用。     

社会发展和变革的先导——学习党的十六大报告

实践基础上的理论创新是社会发展和变革的前导 ,是整个人类社会历史经验、特别是世界社会主义运动历史经验的科学总结。党的十六大把“三个代表”重要思想写入党章是我们党在实践基础上进行理论创新的最新成果 ,成为引导全国人民全面建设小康社会 ,建设中国特色社会主义 ,实现中华民族伟大复兴的旗帜     

A seasonal mixed-POT model to estimate high flood quantiles from different event types and seasons

Flood events can be caused by several different meteorological circumstances. For example, heavy rain events often lead to short flood events with high peaks, whereas snowmelt normally results in events of very long duration with a high volume. Both event types have to be considered in the design of flood protection systems. Unfortunately, all these different event types are often included in annual maximum series (AMS) leading to inhomogeneous samples. Moreover, certain event types are underrepresented in the AMS. This is especially unsatisfactory if the most extreme events result from such an event type. Therefore, monthly maximum data are used to enlarge the information spectrum on the different event types. Of course, not all events can be included in the flood statistics because not every monthly maximum can be declared as a flood. To take this into account, a mixture Peak-over-threshold model is applied, with thresholds specifying flood events of several types that occur in a season of the year. This model is then extended to cover the seasonal type of the data. The applicability is shown in a German case study, where the impact of the single event types in different parts of a year is evaluated.     

Estimation of discrete survival function for error‐prone diagnostic tests

The product limit or Kaplan‐Meier (KM) estimator is commonly used to estimate the survival function in the presence of incomplete time to event. Application of this method assumes inherently that the occurrence of an event is known with certainty. However, the clinical diagnosis of an event is often subject to misclassification due to assay error or adjudication error, by which the event is assessed with some uncertainty. In the presence of such errors, the true distribution of the time to first event would not be estimated accurately using the KM method. We develop a method to estimate the true survival distribution by incorporating negative predictive values and positive predictive values, into a KM‐like method of estimation. This allows us to quantify the bias in the KM survival estimates due to the presence of misclassified events in the observed data. We present an unbiased estimator of the true survival function and its variance. Asymptotic properties of the proposed estimators are provided, and these properties are examined through simulations. We demonstrate our methods using data from the Viral Resistance to Antiviral Therapy of Hepatitis C study.     

Left truncation in linked data: A practical guide to understanding left truncation and applying it using SAS and R

Time-to-event data such as time to death are broadly used in medical research and drug development to understand the efficacy of a therapeutic. For time-to-event data, right censoring (data only observed up to a certain point of time) is common and easy to recognize. Methods that use right censored data, such as the Kaplan–Meier estimator and the Cox proportional hazard model, are well established. Time-to-event data can also be left truncated, which arises when patients are excluded from the sample because their events occur before a specific milestone, potentially resulting in an immortal time bias. For example, in a study evaluating the association between biomarker status and overall survival, patients who did not live long enough to receive a genomic test were not observed in the study. Left truncation causes selection bias and often leads to an overestimate of survival time. In this tutorial, we used a nationwide electronic health record-derived de-identified database to demonstrate how to analyze left truncated and right censored data without bias using example code from SAS and R.