论邓小平教育思想的显著特征

邓小平教育思想是邓小平理论的重要组成部分,是毛泽东教育思想的继承和发展,其思想深邃,内容丰富,不仅是我国教育事业改革和发展的指南,而且也是建设中国特色社会主义现代化事业最宝贵的精神财富,具有显著的特征。     

福建省耕地流向及其与经济发展的关系

土地利用数量的净变化是土地双向变化的结果。在单一土地利用类型动态度模型基础上利用单一土地利用动态变化辅助方法:列表清单法和单一土地利用动态度双向模型,对福建省及各设区市耕地流向进行分析。并在此基础上,研究了福建省耕地的减少与经济发展的关系,提出福建省耕地保护的措施。     

论"中"

“中”的思想在中国历史渊源流长,成为中华民族人文精神的核心,也是中国哲学的精髓。《周易》倡导“中和”精神,儒家践行中庸之道,佛家崇尚以中观法,道家提倡守中致道,都从不同角度深刻地阐发了“中”的思想。万物皆有中,中是一切存在的根本属性,“中律”是宇宙万物运行的根本法则,中和是创新的灵魂。     

盗窃罪与诈骗罪的关系

虽然处分行为是区分盗窃与诈骗的关键性要素,但只需认识到财物外形上的占有转移即可,因而“处分意思不要说”相对合理;三角诈骗与盗窃罪间接正犯的根本区别在于,受骗者是否具有处分他人财产的权限和地位,此应以阵营说为基础,结合社会的一般观念进行判断;盗窃罪与诈骗罪不仅可能形成想象竞合,还可能存在法条竞合,同时符合两罪构成要件时,应以盗窃罪定罪处罚;承认二罪之间存在竞合关系,有助于认识错误和共犯问题的处理。     

孔子“道”范畴的哲学阐释

“道”是中国古代哲学的核心范畴之一,它在孔子思想中具有重要的地位及其意义。孔子的“道”范畴具有天道观与人道观的涵义,人道观是其重心。就人道观而言,孔子的“道”主要是指以“仁”为最高范畴的价值理论体系,它蕴涵了以“仁”为核心的道德目标;以“礼”为核心的价值准则;以“正名”为核心的政治理想;以“中庸”为核心的方法论和以“君子”为核心的理想人格。     

Analysis of a two incongruent arrivals and services M/G/1 queue with random feedback

A queuing system with two incongruent arrivals and services is considered. Two kinds of customers enter the system by Poisson process and the service times are assumed to have general distribution. After first kind service completion, it may feedback to repeat the first service, leave the system or go to give second service. The same policy is applied for the other kind of customer. All stochastic processes involved in this system are independent. We derive the probability generating function for each kind and for the system that yield the performance measures. Some numerical approaches examined the validity of the results.     

Penalized contrast estimation in functional linear models with circular data

Our aim is to estimate the unknown slope function in the functional linear model when the response Y is real and the random function X is a second-order stationary and periodic process. We obtain our estimator by minimizing a standard (and very simple) mean-square contrast on linear finite dimensional spaces spanned by trigonometric bases. Our approach provides a penalization procedure which allows to automatically select the adequate dimension, in a non-asymptotic point of view. In fact, we can show that our penalized estimator reaches the optimal (minimax) rate of convergence in the sense of the prediction error. We complete the theoretical results by a simulation study and a real example that illustrates how the procedure works in practice.     

Bias and precision of measures of survival gain from right‐censored data

In cost‐effectiveness analyses of drugs or health technologies, estimates of life years saved or quality‐adjusted life years saved are required. Randomised controlled trials can provide an estimate of the average treatment effect; for survival data, the treatment effect is the difference in mean survival. However, typically not all patients will have reached the endpoint of interest at the close‐out of a trial, making it difficult to estimate the difference in mean survival. In this situation, it is common to report the more readily estimable difference in median survival. Alternative approaches to estimating the mean have also been proposed. We conducted a simulation study to investigate the bias and precision of the three most commonly used sample measures of absolute survival gain – difference in median, restricted mean and extended mean survival – when used as estimates of the true mean difference, under different censoring proportions, while assuming a range of survival patterns, represented by Weibull survival distributions with constant, increasing and decreasing hazards. Our study showed that the three commonly used methods tended to underestimate the true treatment effect; consequently, the incremental cost‐effectiveness ratio (ICER) would be overestimated. Of the three methods, the least biased is the extended mean survival, which perhaps should be used as the point estimate of the treatment effect to be inputted into the ICER, while the other two approaches could be used in sensitivity analyses. More work on the trade‐offs between simple extrapolation using the exponential distribution and more complicated extrapolation using other methods would be valuable. Copyright © 2015 John Wiley & Sons, Ltd.     

Estimation of coefficient of dispersion using auxiliary information

In this note, we consider the problem of estimation of coefficient of dispersion of a study variable by making use of known value of the coefficient of dispersion of an auxiliary variable. We propose ratio and regression-type estimators. We derive expressions of bias and variance of the proposed estimators to the first order of approximation. The relative efficiencies of the ratio and regression-type estimators with respect to the naïve estimator are investigated through a simulation study.     

Measuring Nonlinear Granger Causality in Mean

We propose model-free measures for Granger causality in mean between random variables. Unlike the existing measures, ours are able to detect and quantify nonlinear causal effects. The new measures are based on nonparametric regressions and defined as logarithmic functions of restricted and unrestricted mean square forecast errors. They are easily and consistently estimated by replacing the unknown mean square forecast errors by their nonparametric kernel estimates. We derive the asymptotic normality of nonparametric estimator of causality measures, which we use to build tests for their statistical significance. We establish the validity of smoothed local bootstrap that one can use in finite sample settings to perform statistical tests. Monte Carlo simulations reveal that the proposed test has good finite sample size and power properties for a variety of data-generating processes and different sample sizes. Finally, the empirical importance of measuring nonlinear causality in mean is also illustrated. We quantify the degree of nonlinear predictability of equity risk premium using variance risk premium. Our empirical results show that the variance risk premium is a very good predictor of risk premium at horizons less than 6 months. We also find that there is a high degree of predictability at the 1-month horizon, that can be attributed to a nonlinear causal effect. Supplementary materials for this article are available online.