“换词求雅”的修辞作用及衔接功能

“换词求雅”作为一种消极修辞手段,在避免重复、增加文章的文体色彩方面起到了积极的作用。不仅如此,作为一种衔接手段,“换词求雅”也在保证语篇的衔接与连贯上发挥着不可替代的作用。本文通过对这种辞手段的应用原则及分类方法的阐述,试图表明“换词求雅”并不是为了语言花哨的目的而存在的,无论从修辞还是语法意义角度上看,这一修辞方法的作用都是其他方法难以替代的。     

零售企业数字化转型对经营效率的影响研究——基于上市企业年报的文本挖掘分析

在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下,零售企业数字化转型具有重要的现实意义。基于2010—2019年中国实体上市零售企业的年报信息,采用文本挖掘法测算了零售企业的数字化转型水平,并实证检验了零售企业数字化转型对经营效率的影响机制与效应。实证结果表明,数字化转型显著促进了零售企业经营效率的提升。从影响机制来看,数字化转型通过扩大市场规模和改善管理效率对经营效率产生正向影响;从数字化转型的分维度来看,数字化技术的应用对经营效率的提升有显著促进作用,而数字化商业模式和数字化渠道的作用不显著。从异质性分析来看,数字化转型对零售企业经营效率的提升效应主要体现在国有企业当中;规模过大会抑制零售企业数字化转型对经营效率的提升作用;东中部地区零售企业数字化转型对提升经营效率的影响显著,但是这一影响在西部地区并不显著。因此,加快推进数字化转型升级,加大数字化技术应用力度,发挥国有企业示范作用,以及克服“大企业病”,均是促进零售企业经营效率提升的关键。     

翻译中心智距离存在的客观性

翻译难是一个众所周知的事实。难的原因有多种,涉及许多内在和外在诸因素,其中有一个不容忽视的成因是译者与原作者之间客观地存在着“心智距离”,即译者在语际传译过程中,受自身诸种内在因素的制约,不可能真正地深入到原作者的内心中去,与原作者同思维、共呼吸,与原作者的意旨彻底复合。当代西方流行的接受美学理论为这一现象作了很好的佐证。     

多重网络中的词学研究

近20年来,词学研究有所进展,但仍存在一些问题。词学研究应在多重网络中展开。首先,词学是专门之学,但研究者仍需建构开放的知识网络。词乐研究虽有不少成果,但仍处于相对低潮。这与研究者受限于音乐知识,无法有效介入有关。词谱、词律等专门之学亦是如此。其次,可以尝试词学研究的时空延展,打造通观的“全息网络”,通过长时段的、大量的文本分析发现新话题。同时,注意域外汉籍,因为它们可以提供新文献,启发新视角,丰富文本网络。最后,要注意数字人文的发展趋向,要建设词学检索库,善用新技术,更新研究理念,以便及时因应。但数字人文终究只是辅助研究手段,技术取代不了阅读与思考,只有在传统研究的基础上,技术才能发挥更大的作用。     

论晚明文人评点本的价值和传播机制

晚明是文学评点的鼎盛期和丰收期 ,不但汇评、集评的形式大量出现 ,而且形成了评点名篇为中心、各层次的作品均有评批的评点格局 ;这些文学评点具有很强的文本价值 ,一些重要的文艺理论都是在评点中形成、发展、流行起来的 ;同时它有一套调节接收者期待视界的传播机制 ,在提升传播速度、导引读者等方面起着重要的作用。     

文学语篇翻译中有标记主位的诗学价值再现

文学翻译的追求是思想信息和诗学价值兼得。有标记性主位的运用是文学作品诗学价值的重要表现手法。有标记主位的信息突出功能、信息对比功能、句法信息功能和文体信息功能在翻译中的再现是文学作品诗学价值再现的必由之路。     

Parameter identification for the discretely observed geometric fractional Brownian motion

This paper deals with the problem of estimating all the unknown parameters of geometric fractional Brownian processes from discrete observations. The estimation procedure is built upon the marriage of the quadratic variation and the maximum likelihood approach. The asymptotic properties of the estimators are provided. Moveover, we compare our derived method with the approach proposed by Misiran et al. [Fractional Black-Scholes models: complete MLE with application to fractional option pricing. In International conference on optimization and control; Guiyang, China; 2010. p. 573–586.], namely the complete maximum likelihood estimation. Simulation studies confirm theoretical findings and illustrate that our methodology is efficient and reliable. To show how to apply our approach in realistic contexts, an empirical study of Chinese financial market is also presented.     

Choosing Prior Hyperparameters: With Applications to Time-Varying Parameter Models

Time-varying parameter models with stochastic volatility are widely used to study macroeconomic and financial data. These models are almost exclusively estimated using Bayesian methods. A common practice is to focus on prior distributions that themselves depend on relatively few hyperparameters such as the scaling factor for the prior covariance matrix of the residuals governing time variation in the parameters. The choice of these hyperparameters is crucial because their influence is sizeable for standard sample sizes. In this article, we treat the hyperparameters as part of a hierarchical model and propose a fast, tractable, easy-to-implement, and fully Bayesian approach to estimate those hyperparameters jointly with all other parameters in the model. We show via Monte Carlo simulations that, in this class of models, our approach can drastically improve on using fixed hyperparameters previously proposed in the literature. Supplementary materials for this article are available online.     

COWORDS: a probabilistic model for multiple word clouds

Word clouds constitute one of the most popular statistical tools for the visual analysis of text documents because they provide users with a quick and intuitive understanding of the content. Despite their popularity for visualizing single documents, word clouds are not appropriate to compare different text documents. Independently generating word clouds for each document leads to configurations where the same word is typically located in widely different positions. This makes it very difficult to compare two or more word clouds. This paper introduces COWORDS, a new stochastic algorithm to create multiple word clouds, including one for each document. The shared words in multiple documents are placed in the same position in all clouds. Similar documents produce similar and compact clouds, making it easier to simultaneously compare and interpret several word clouds. The algorithm is based on a probability distribution in which the most probable configurations are those with a desirable visual aspect, such as a low value for the total distance between the words in all clouds. The algorithm output is a set of word clouds that are randomly selected from this probability distribution. The selection procedure uses a Markov chain Monte Carlo simulation method. We present several examples that illustrate the performance and visual results that can be obtained by our algorithm.     

Prevalence of Childhood Sexual Abuse in China: A Meta-Analysis

The objective of the current study was to explore the estimated prevalence of childhood sexual abuse in China. We conducted a meta-analysis that used the data from 36 articles. A total of 125 independent samples and 131,734 participants were included. The results revealed no significant difference in the prevalence of childhood sexual abuse between Chinese men (9.1%) and women (8.9%). The prevalence of childhood sexual abuse in studies from mainland areas was significantly higher than that from Hong Kong/Taiwan. The estimated prevalence of childhood sexual abuse in China also differed according to the definition of child sexual abuse, data collection method, year of data collection, and the mean age of participants at the time of assessment.