核技术应用企业研发骨干激励机制探究

核技术应用一般是指射线技术与射线装置在医疗、工农业、地质调查、研究与教育中的应用。我国核技术应用企业研发骨干激励存在着激励的创新导向不足、薪酬激励机制不合理、组织文化有欠缺等问题,需结合行业特点及核技术应用企业研发骨干激励的特殊要求,采取相应的激励对策,包括从核心能力出发研究激励问题、建立适于激励研发人员的能力工资制、注重职业发展激励、注重责任激励、建立激发创新活力的组织文化等。     

Factors associated with a positive childbirth experience in Brazilian women: A cross-sectional study

BackgroundHaving a positive childbirth experience is an increasingly valued outcome. Few studies evaluated the women’s satisfaction with childbirth through face-to-face interviews out of the health service environment. The objective of this study was to identify factors associated with a higher level of satisfaction with the childbirth experience among Brazilian women.MethodsThis cross-sectional study involved 287 women giving birth in two hospitals in southern Brazil. Women who gave birth to healthy newborns at term were randomly selected. Face-to-face interviews were conducted 31–37 days after delivery, at the mothers’ homes, using a structured questionnaire. Satisfaction with the childbirth experience was measured using a Likert-type scale ranging from very satisfied to very dissatisfied. Prevalence ratios (PR) were estimated using Poisson regression with robust variance.ResultsFollowing hierarchical multivariate analysis, the following factors remained associated with a higher level of satisfaction with the childbirth experience: being satisfied with antenatal care (PR = 1.30; 95% confidence interval [95%CI] = 1.06−1.59), understanding the information provided by health professionals during labor and delivery (PR = 1.40; 95%CI = 1.01−1.95), not having reported disrespect and abuse (PR = 1.53; 95%CI = 1.01−2.31), and having had the baby put to the breast within the first hour of life (PR = 1.63; 95%CI = 1.26−2.11). No association was observed with type of delivery or hospital status (public or private).ConclusionsA higher level of satisfaction with the childbirth experience is related to satisfactory antenatal care, a non-abusive, respectful, and informative environment during childbirth, and to the opportunity to breastfeed the baby within the first hour of life. In clinical practice, greater attention to these basic principles of care during pregnancy and delivery could provide more positive experiences during birth.     

Non-parametric estimation of reciprocal coordinate subtangent for right censored dependent scheme

The concept of reciprocal coordinate subtangent (RCST) has been used as a useful tool to study the monotone behavior of a continuous density function and for characterizing probability distributions. In this paper, we propose a non-parametric estimator for RCST based on the censored dependent data. Asymptotic properties of the estimator are established under suitable regularity conditions. A simulation study is carried out to examine the performance of the estimator. The usefulness of the estimator is also examined through a real data.     

丑角、看客与孤独者的悲喜剧 ——鲁迅与穆时英笔下的丑角形象之比较

鲁迅与穆时英笔下都塑造过一系列具有丑角特质的形象。不同的是,穆时英笔下的丑角具有自觉性,以小丑身份为面具,掩盖自己的孤独与恐惧；鲁迅笔下的丑角多是非自觉的,他们认真地践行着自己的人生理念,却因其与周遭环境格格不入,被人当作小丑、疯子。从中折射出两位作家迥异的生命观,穆时英从个体角度出发,写出了都市人在悲哀的脸上戴了快乐面具的无奈,对丑角表演持拥抱态度；鲁迅则从批判国民性的宏观角度出发,敏锐地意识到了丑角表演背后的隐忧,对其持拒斥的姿态。     

双循环新发展格局下中国双向直接投资研究

构建以国内大循环为主体、国内国际双循环相互促进的新发展格局,是对未来中国经济发展路径做出的重大战略部署,作为连接国内国际双循环的纽带,双向直接投资的发展战略和路径面临重塑和调整。研究认为,应当以推动新时代科技创新和产业升级为目标,提高双向直接投资的质量,畅通供应链和产业链; 以“一带一路”倡议为依托,通过更高水平的双向投资带动中国与沿线国家贸易水平的提高; 建设高水平自贸区和自贸港,提高对外开放标准,更高质量吸引外资,提升参与国际大循环的技术含量和自主性; 在畅通要素流动领域,建立更加完善的现代化物流体系,建设更高标准的要素流通市场体系,降低制度性交易费用,提高生产率和对高质量外资的吸引能力。     

嵌套并联结构两阶段DEA下科技创新效率测度与分解

目前有许多研究将两阶段DEA模型应用到科技创新活动当中，一般将创新活动分为研发和转化两个阶段，为了进一步探讨不同转移转化方式下科技成果的转化效率以获得更多的详细信息，本文拓展了传统的两阶段DEA模型，考虑了嵌套并联结构的两阶段网络DEA模型，将科技创新活动分为科技成果研发阶段和科技成果转化阶段，并将科技成果转化阶段分为内部转化和外部转化两个并联子系统。本文选取14家中科院院属单位作为被评价对象，应用加权加法分解方法计算整体效率和各阶段子效率。通过将本文模型与传统两阶段模型进行对比发现，传统模型会低估科技成果转化效率。结果表明：整体科技创新效率均值偏低，科技成果研发效率均值高于科技成果转化效率均值，科技成果转化效率仍有很大的提升空间。科技成果转化阶段中内部转化效率普遍较高但是外部转化效率普遍较低，较低的外部转化效率是导致科技成果转化效率低下的主要原因。最后，本文将所有被评价单位分为四类机构，分析提高科技创新效率的实现路径，可以通过重点突破模式和渐进突破模式来实现整体效率的提高。     

“百年未有之大变局”之哲学分析

当今世界正处于“百年未有之大变局”中。这是中国共产党对于世界新的时代特征的全新、科学和准确的研判。“百年未有之大变局”这一重大论断，具有深厚的马克思主义哲学的本体论基础、认识论基础、矛盾论基础和历史观基础。作为科学世界观与方法论，马克思主义哲学的辩证唯物主义和历史唯物主义为我们深刻认识和精准把握“百年未有之大变局”的深层本质和哲学依据提供了重要的认知性引导、方法论基础和实践智慧支撑。     

Recognizing Structural Nonidentifiability: When Experiments Do Not Provide Information About Important Parameters and Misleading Models Can Still Have Great Fit

In the quest to model various phenomena, the foundational importance of parameter identifiability to sound statistical modeling may be less well appreciated than goodness of fit. Identifiability concerns the quality of objective information in data to facilitate estimation of a parameter, while nonidentifiability means there are parameters in a model about which the data provide little or no information. In purely empirical models where parsimonious good fit is the chief concern, nonidentifiability (or parameter redundancy) implies overparameterization of the model. In contrast, nonidentifiability implies underinformativeness of available data in mechanistically derived models where parameters are interpreted as having strong practical meaning. This study explores illustrative examples of structural nonidentifiability and its implications using mechanistically derived models (for repeated presence/absence analyses and dose–response of Escherichia coli O157:H7 and norovirus) drawn from quantitative microbial risk assessment. Following algebraic proof of nonidentifiability in these examples, profile likelihood analysis and Bayesian Markov Chain Monte Carlo with uniform priors are illustrated as tools to help detect model parameters that are not strongly identifiable. It is shown that identifiability should be considered during experimental design and ethics approval to ensure generated data can yield strong objective information about all mechanistic parameters of interest. When Bayesian methods are applied to a nonidentifiable model, the subjective prior effectively fabricates information about any parameters about which the data carry no objective information. Finally, structural nonidentifiability can lead to spurious models that fit data well but can yield severely flawed inferences and predictions when they are interpreted or used inappropriately.