Using machine learning to identify early predictors of adolescent emotion regulation development

As 20% of adolescents develop emotion regulation difficulties, it is important to identify important early predictors thereof. Using the machine learning algorithm SEM-forests, we ranked the importance of (87) candidate variables assessed at age 13 in predicting quadratic latent trajectory models of emotion regulation development from age 14 to 18. Participants were 497 Dutch families. Results indicated that the most important predictors were individual differences (e.g., in personality), aspects of relationship quality and conflict behaviors with parents and peers, and internalizing and externalizing problems. Relatively less important were demographics, bullying, delinquency, substance use, and specific parenting practices—although negative parenting practices ranked higher than positive ones. We discuss implications for theory and interventions, and present an open source risk assessment tool, ERRATA.     

TAUS指南在快速译后编辑（LPE）中的应用——以医学报告为例

随着互联网、大数据、云计算的飞速发展，机器翻译发生了巨大变化，机器翻译译后编辑（machine translation post-editing，MTPE）模式也应运而生，逐渐成为翻译服务业的主流模式。但若要进一步提高MTPE效率和质量，还需要相应的规范和准则加持，以帮助译后编辑者识别机器翻译错误并快速决策机器译文是否需要进行编辑。通过介绍翻译自动化用户协会（TAUS）的MTPE指南的相关实践准则，并根据文本性质和受众选取适用准则指导进行了医学报告的快速译后编辑（light post-editing, LPE）实践，对医学报告文本译后编辑实践中存在的词汇错译、分词短语错译、从句错译以及段落错译、漏译等问题进行了分析，并对该指南的实际指导意义进行了总结与评价。     

乡村农户贫困状态特征因子筛选与分析框架：兼论我国乡村振兴路径选择

本文构建了刻画乡村农户贫困状态的特征因子的提取算法和分析框架，旨在实现和帮助完善家庭农场的持续发展，尤其是由贫困农户组成或参与的家庭农场在发展需要的融资方面的乡村信用评估，推动有效地制订对应政策和落地方案，巩固脱贫攻坚成果和防止返贫。本文的最大亮点是以“分类与回归树”(CART)分析和“吉布斯抽样”(Gibbs Sampling)的人工智能算法为工具，对乡村农户贫困状态的特征因子提取建立了对应的框架和分析流程。基于国内某地区乡村建档立卡数据库的31,116个样本，实证研究筛选出12个刻画乡村农户贫困状态高度关联的特征因子，并进一步对特征因子的有效性进行了ROC曲线和AUC测试。结果表明以特征因子分析框架为基础，建设配套的乡村信用评估体系是支持乡村振兴的可持续性最佳解决途径之一，除了能够为乡村贫困户获得持续工作的基本技能或生产环境的改善提升上得到持续性的融资支持提供评估依据和数据支持，也能为乡村和城镇“传帮带”等生产和商务平台的建立提供可持续的基础性数据和信用分析的动态支持。     

Reliability analysis of man–machine systems using fuzzy cognitive mapping with genetic tuning

This article offers a method for analyzing the reliability of a man–machine system (MMS) and ranking of influencing factors based on a fuzzy cognitive map (FCM). The ranking of influencing factors is analogous to the ranking of system elements the probabilistic theory of reliability. To approximate the dependence of “influencing factors—reliability,” the relationship of variable increments is used, which ensures the sensitivity of the reliability level to variations in the levels of influencing factors. The novelty of the method lies in the fact that the expert values of the weights of the FCM graph edges (arcs) are adjusted based on the results of observations using a genetic algorithm. The algorithm's chromosomes are generated from the intervals of acceptable values of edge weights, and the selection criterion is the sum of squares of deviations of the reliability simulation results from observations. The method is illustrated by the example of a multifactor analysis of the reliability of the “driver–car–road” system. It is shown that the FCM adjustment reduces the discrepancy between the reliability forecast and observations almost in half. Possible applications of the method can be complex systems with vaguely defined structures whose reliability depends very much on interrelated factors measured expertly.     

LED显示屏专用插件机的优化设计

为了提高LED显示屏的插装生产效率，提出了优化设计LED显示屏插件机的方案，采用锥形孔来校正LED管 脚，利用LED外形定位的方法来进行精准插件，省略LED管脚的裁剪环节和传输环节，使结构变得简洁，有效地节省产 品成本，通过对关键部件进行仿真分析，表明初步实现了目标。     

融通与互促——“翻译、科技与人文高端论坛”综述

“翻译、科技与人文高端论坛”综述探讨了翻译、科技与人文的融通路径和研究新方向：1）科技与人文的融合与赋能互促，可通过观念互启、方法互用和跨学科互构的路径实现；2）人文学科应发挥理论知识和外语人才的优势，积极应对机器翻译智能化带来的机遇与挑战；3）翻译专业人才培养既要满足新科技革命时代的新要求，也要立足学科本质，对接国家需求，在培养目标和培养方案等方面做出及时调整。     

Breakdowns and assemblages: Including machine-actants in sociolinguistic ethnographies of blue-collar work environments

A central concern in sociolinguistic ethnographies has been how people use language to make social distinctions. This article discusses the relevance of paying closer attention to the role of machines as actants in communication and social distinction-making processes. It analyses audio and video-recorded workplace interactions between humans and machines in a metal foundry in the Dutch-German borderland. Specifically, it focuses on several cases of a breakdown of a production process, a frequently observed phenomenon in the foundry. The cases show that: (1) the production work entails many improvised human–human and human–machine interactions as opposed to Taylorised working practices; (2) the machine-actants initiate and afford (re)negotiations of situated, hierarchical workplace relations through these interactions; and (3) the question whether these interactions should be considered ‘language-centred’ or ‘language-marginal’ partly depends on an ideological, conceptual distinction between what counts as ‘language’ and what not.     

可读性和吸引性对商品销量的影响——基于电影简介的文本分析

商品简介为企业提供着向消费者传递商品信息，并激起消费者购买欲的重要作用。但是鲜有研究对商品简介文本的营销效果进行分析。为了弥补上述研究缺陷，本文基于营销实践的特征和相关文献梳理，并采用机器学习的方式度量了中国大陆2018年上映264部电影简介文本的可读性和吸引性水平，并检验其对首周票房和总票房的影响。研究发现，简介文本的可读性和吸引性对首周票房和总票房有差异化的影响，可读性对于首周票房的影响较大，而吸引性对总票房的影响较大。此外，明星的存在削弱了文本可读性和吸引性对票房的影响；而且，在高电影评分组中，可读性和吸引性对首周票房及总票房的负向交互作用显著。本文基于启发式-系统式模型凝练出商品简介文本的可读性和吸引性两个特征并研究其对票房的影响，对丰富中国电影研究，指导中国电影营销实践具有重要参考价值。     

Social welfare in the light of topic modelling

With an increased focus on social well-being in response to a burgeoning global economy exposing the weaknesses of social welfare policies, research output in the field has grown exponentially. Keeping track of the evolving research themes proves difficult due to the steady rise in the number of studies published in the interdisciplinary field of social welfare. Therefore, researchers need a comprehensive overview to confirm the current shape of the field based on the published research. Using a latent Dirichlet allocation algorithm as a topic modelling technique, this study identified 12 prominent themes from more than 10,000 research outputs on social welfare published from 2000 to 2020 in Scopus-indexed journals. Such an exploratory text-mining approach to literature review provides broad insights into the diversity of research and may serve as a foundation for further in-depth studies. Identifying these 12 thematic areas and their sub-themes allows us to articulate the complexity and diversity of social welfare issues, which go far beyond the field of well-established welfare economics or social work. The study shows that the topic of ‘social welfare’ has not only evolved over time but has significantly broadened its meaning. It can no longer be solely synonymous with institutional social security. We contend that research in this area needs to take into account a broader and more systematic range of determinants constituting the dynamic character of social welfare.     

基于机器学习的小微企业信贷供给智能决策系统研究——以“银税互动”政策的共享纳税数据为例

随着金融科技的快速发展,如何融合现代信贷技术有效缓解小微企业的融资困境是当前金融市场亟待解决的关键问题。以“银税互动”政策作为切入点,深入挖掘小微企业纳税数据的信用特征,结合随机森林方法和深度神经网络方法对小微企业的信用违约概率和信贷风险等级进行评估,综合考虑银行的经营利润以及风险成本实现不同小微企业信贷利率和信贷额度的优化,以此构建小微企业信贷供给智能决策系统。研究结果表明,纳税数据能够准确识别小微企业的信贷风险,从而为银行信贷供给提供决策依据,并且纳税数据质量较高的小微企业无论是信贷额度还是信贷利率都能够获得银行层面更加有利的信贷支持。