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。     

Adaptive designs for best treatment identification with top-two Thompson sampling and acceleration

We consider outcome adaptive phase II or phase II/III trials to identify the best treatment for further development. Different from many other multi-arm multi-stage designs, we borrow approaches for the best arm identification in multi-armed bandit (MAB) approaches developed for machine learning and adapt them for clinical trial purposes. The best arm identification in MAB focuses on the error rate of identification at the end of the trial, but we are also interested in the cumulative benefit of trial patients, for example, the frequency of patients treated with the best treatment. In particular, we consider Top-Two Thompson Sampling (TTTS) and propose an acceleration approach for better performance in drug development scenarios in which the sample size is much smaller than that considered in machine learning applications. We also propose a variant of TTTS (TTTS2) which is simpler, easier for implementation, and has comparable performance in small sample settings. An extensive simulation study was conducted to evaluate the performance of the proposed approach in multiple typical scenarios in drug development.     

互联网的性质：与机器对比的视角

虽然互联网在各领域应用越来越普遍，但还笼罩着一层神秘的面纱，原因是人们对互联网性质的认识不够深刻。互联网的出现及影响与工业革命初期的机器具有高度相似性。借鉴《资本论》及其手稿中的机器思想及分析方法，将互联网与机器进行对比，可以发现：互联网是机器从动力革命、程序辅助、计算功能到对话需求发展的结果；互联网以机器作为连接的基础，具有无形客观、无限扩展和超脱的形式和快速、方便、大容量、交互性的特点；互联网能够改进生产和消费方式、提高机器的生产效率、提高社会的整体效率、创造信息财富；互联网表现和增强现有社会联系，增加新的社会联系；互联网通过增加休闲方式和劳动选择带来更多的剩余时间。此外，利用互联网需要注意其消极影响。     

机械制造技术基础课程教学方法改革研究

机械制造技术基础课程是一门综合性、实践性和应用性很强的机械类专业基础课。文章针对机械制造技术基础课程的教学特点,以创新能力培养为核心,从课程体系构建、理论和实践教学手段与方法的改革,教学效果评价等方面进行研究,多角度提高课程教学质量,以适应机械设计制造及其自动化专业人才培养的要求。