再谈汉日翻译中的几个问题——再与迟军先生商榷

针对迟军先生于1990年在《日语学习与研究》第3期上发表的“试析《试析〈汉译日基础教程〉的误译》”一文，从如下几个方面与迟军先生再商榷：一、译文要符合语言的规范和表达习惯；二、译文不应使用过于陈旧的词汇或表达方式；三、译文的句组、语段脉络要清楚易懂；四、译文要符合日语语法规范。     

卫星信道基带残留误码分布特性拟合与模拟

卫星通信信道的基带残留误码特性直接影响上层通信协议的性能。通过对卫星通信系统仿真,提取基带误码图案,将基带误码分布图案通过误码持续期发生概率密度分布、误码持续期长度概率密度分布来表征。在典型的卫星通信系统参数条件下,拟合表明经过有噪莱斯衰落信道的误码持续期发生概率接近广义极值分布;经过高斯噪声信道的误码持续期发生概率密度、误码持续期长度概率密度接近负二项式分布。在此基础上完成的卫星基带信道硬件模拟器能够为通信协议的测试提供方便、可信的信道基带特性模拟。     

农业生产与经济增长关系的均衡分析

为探讨我国农业生产与经济增长之间的关系,选取1978-2006年我国历年农业产值和国内生产总值序列进行协整检验,结果表明我国农业生产与经济增长之间存在着长期稳定的动态均衡关系,农业产值每增加1%,将促进经济增长2.12%;误差修正模型表明,农业生产的短期变化对经济增长有显著的正效应,如果本期的经济增长偏离长期均衡值,那么到下一时期这一偏离度将有8%得以纠正;Granger因果关系检验表明,农业生产对经济增长具有短期效应,经济增长对农业生产具有长期促进作用;脉冲响应函数分析和方差分解的结果进一步表明,农业生产对经济增长的贡献较显著。     

Linear Discriminant Analysis of Multivariate Spatial–Temporal Regressions

Abstract.  We consider classification of the realization of a multivariate spatial–temporal Gaussian random field into one of two populations with different regression mean models and factorized covariance matrices. Unknown means and common feature vector covariance matrix are estimated from training samples with observations correlated in space and time, assuming spatial–temporal correlations to be known. We present the first-order asymptotic expansion of the expected error rate associated with a linear plug-in discriminant function. Our results are applied to ecological data collected from the Lithuanian Economic Zone in the Baltic Sea.     

公司对外担保的效力认定——以意思表示规则为核心

从法律行为构成要件的角度入手,《公司法》16条第1款规定的公司对外担保问题不是当事人行为能力、标的问题。因此,判断对外担保的效力应遵循意思表示规则。公司对外担保的意思表示过程是：公司董事会或股东会做出决议,形成对外担保意思,由法定代表人向外做出意思表示。无意思形成的对外担保效力,应据动机错误的效力规则确定其效力。有意思形成的对外担保效力,属于典型当事人错误,可纳入表示内容错误。由于界定赔偿责任时,须考虑相对人的过错,相对人过错取决于其审查义务,应限制相对人只是形式审查公司章程与担保决议。     

工程更改研究进展

在产品的生命周期里,多元化的客户需求、生产制造技术工艺的改进等,不断对企业提出新设计更改的要求。在 现有的产品设计信息基础上对产品进行工程更改,是满足复杂多变的市场的重要方法。在研读国内外文献基础上,根据 工程更改中的研究对象不同,从工程更改的过程管理和更改传播技术2个方面对工程更改理论进行归纳概括。从工程 更改的定义、原因、管理原则、产品的生命周期和计算机支持下环境的更改管理系统、更改机制、更改经验,利用零部件间 参数关系、多层网络模型和设计结构矩阵等更改传播的技术等多方面总结了工程更改的理论研究。最后提出未来工程 更改的研究重点是更改管理系统和传播技术与实际应用的结合,在不断应用过程中完善理论。     

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.     

To adjust or not to adjust for baseline when analyzing repeated binary responses? The case of complete data when treatment comparison at study end is of interest

The benefits of adjusting for baseline covariates are not as straightforward with repeated binary responses as with continuous response variables. Therefore, in this study, we compared different methods for analyzing repeated binary data through simulations when the outcome at the study endpoint is of interest. Methods compared included chi‐square, Fisher's exact test, covariate adjusted/unadjusted logistic regression (Adj.logit/Unadj.logit), covariate adjusted/unadjusted generalized estimating equations (Adj.GEE/Unadj.GEE), covariate adjusted/unadjusted generalized linear mixed model (Adj.GLMM/Unadj.GLMM). All these methods preserved the type I error close to the nominal level. Covariate adjusted methods improved power compared with the unadjusted methods because of the increased treatment effect estimates, especially when the correlation between the baseline and outcome was strong, even though there was an apparent increase in standard errors. Results of the Chi‐squared test were identical to those for the unadjusted logistic regression. Fisher's exact test was the most conservative test regarding the type I error rate and also with the lowest power. Without missing data, there was no gain in using a repeated measures approach over a simple logistic regression at the final time point. Analysis of results from five phase III diabetes trials of the same compound was consistent with the simulation findings. Therefore, covariate adjusted analysis is recommended for repeated binary data when the study endpoint is of interest. Copyright © 2015 John Wiley & Sons, Ltd.     

Notes on estimation of the intraclass correlation under the AB/BA crossover trial

Under the AB/BA crossover trial, we focus our attention on estimation of the intraclass correlation in normal data. We develop both point and interval estimators in closed form for the intraclass correlation. We employ Monte Carlo simulation to study the performance of these estimators in a variety of situations. We note that the estimators developed here for the intraclass correlation remain valid even when there are possibly unexpected carry-over effects.