江苏省基层医务人员工作压力研究

对905名基层医务人员进行问卷调查,了解基层医务人员工作压力情况及其影响因素,为建立适合基层卫生机构的良性人才发展机制提供依据。基层医务人员整体工作压力得分为56.54分;单因素方差分析显示,不同性别、年龄、婚姻状况、学历、职称、机构类型、工作量、工作年数、受患者尊重程度和社会地位的医务人员工作压力得分差异具有统计学意义;多元线性回归分析结果显示,社会地位、工作量、工作年数、受患者尊重程度、最高学历和性别对基层医务人员工作压力的影响具有统计学意义。需要着重关注乡镇卫生院医生的工作压力情况,重点应放在提升基层医务人员社会地位、及时关注中坚力量等方面,从而减轻其工作压力,提高工作积极性。     

澳大利亚OESC保护中小学生上网安全的途径研究

随着网络技术的发展和社交软件使用的低龄化,发生在中小学校的网络欺凌现象越来越普遍。澳大利亚政府高度关注该问题,专门成立网络安全专员办公室（OESC）,用以支持和推动中小学生网络安全措施的实施。具体而言：（1）提供安全的网络使用指导,引导中小学生养成网络安全行为习惯;（2）为学校和家庭提供相关的教育资源,培养中小学生的网络安全意识和能力;（3）对网络服务供应商设立监管机制,确保中小学生网络安全措施的顺利实施。     

一种新的高分辨定位去噪方法

高分辨定位技术在近几年得到人们的广泛注意,在这方面的研究工作相当活跃。本文提出一种新的多目标阵列接收信号协方差矩阵的去噪方法,并对结果进行了计算机模拟。     

中小学教师依法治教的困境与对策

中小学教师是依法治教的实践者、宣讲者、推动者,是推动依法治教的关键因素之一。但是,在中小学教师依法治教的过程中,还存在着中小学教师法治素养良莠不齐,教育立法滞后、执法不严、司法不公以及中小学教师职前、职后法治教育缺失等现象。全面推进依法治国,实现教育治理体系和治理能力现代化,必须深刻把握和充分发挥中小学教师在依法治教中的价值和作用,增强其依法治教的自觉性;必须深刻分析中小学教师在依法治教中面临的各种困境与原因,采取针对性措施,做到有的放矢,综合施策。     

Multiscale Combined Forecast of Carbon PriceBased on Mixed Structure Data

Accurate forecast of the carbon trading price is of great significance in promoting the scientific and rational development of carbon trading market. Therefore, this paper proposes a multi-scale combined forecasting method for carbon price based on mixed structure data. First, the Google Index is used to extract the unstructured data related to the carbon price.The dimensions of unstructured data are reduced based on principal component analysis. Then, EMD is employedto the structured data,unstructured data and the carbon trading price to obtain different IMFs, which are reconstructed by the Fine-to-Coarse technique to get low, high frequency sequence and trend sequence. Furthermore, the three items are predicted respectively by using ARIMA, PLS and neural networks according to the features of each scale in time series. Finally, the forecasting results are summed to get the carbon price forecast sequence. The proposed method is used to forecast carbon price in EU. The empirical results show that the prediction accuracy of the model is higher than that of the single prediction method and the prediction method that time series aren’t decomposed by EMD, which is of great applicability.     

幼小衔接中儿童适应性问题探析

儿童结束幼儿园生活到小学生活的过渡阶段中普遍存在着学习环境、人际关系、行为要求、活动方式等方面的适应不良问题，往往造成儿童学习积极性差、注意力不集中、焦虑紧张等情况。对此从幼儿园、小学、家庭三方面提出了相应的建议与对策，希望帮助儿童顺利地适应小学生活，完成角色的转变。     

New calibration estimator based on two auxiliary variables in stratified sampling

In recent years, calibration estimation has become an important field of research in survey sampling. This paper proposes a new calibration estimator for the population mean in the presence of two auxiliary variables in stratified sampling. The theory of new calibration estimator is given and optimum calibration weights are derived. A simulation study is carried out to performance of the proposed calibration estimator over other existing calibration estimators. The results reveal that the proposed calibration estimators are more efficient than other existing calibration estimators in stratified sampling.     

Trend smoothness achieved by penalized least squares with the smoothing parameter chosen by optimality criteria

This work presents a study about the smoothness attained by the methods more frequently used to choose the smoothing parameter in the context of splines: Cross Validation, Generalized Cross Validation, and corrected Akaike and Bayesian Information Criteria, implemented with Penalized Least Squares. It is concluded that the amount of smoothness strongly depends on the length of the series and on the type of underlying trend, while the presence of seasonality even though statistically significant is less relevant. The intrinsic variability of the series is not statistically significant and its effect is taken into account only through the smoothing parameter.     

Local estimation for varying-coefficient models with longitudinal data

Varying-coefficient models are very useful for longitudinal data analysis. In this paper, we focus on varying-coefficient models for longitudinal data. We develop a new estimation procedure using Cholesky decomposition and profile least squares techniques. Asymptotic normality for the proposed estimators of varying-coefficient functions has been established. Monte Carlo simulation studies show excellent finite-sample performance. We illustrate our methods with a real data example.