面向小语种机器翻译的平行语料库构建方法

神经机器翻译模型的训练效果在很大程度上取决于平行语料库的规模和质量。除了一些常见语言外,汉语与小语种间高质量平行语料库的建设一直处于滞后状态。现有小语种平行语料库多采用自动句子对齐技术利用网络资源构建而成,在文本质量和领域等方面有诸多局限性。采用人工翻译的方式可以构建高质量平行语料库,但是缺乏相关经验和方法。文中从机器翻译实践者和研究者角度出发,介绍了经济高效的人工构建小语种平行语料库的工作,包括其总体目标、实施过程、流程细节和最后结果。在构建过程中尝试并积累了各种经验,形成了小语种到汉语平行语料库构建方法、建议的总结。最终,成功构建了波斯语到汉语、印地语到汉语、印度尼西亚语到汉语各50万条高质量平行语料。实验结果表明,所构建的平行语料库有较好的质量,提高了小语种神经机器翻译模型的训练效果。     

Sustainable phenolic thermosets coatings derived from urushiol

The over-exploitation of finite fossil resources and/or the increased environmental and sustainable awareness inspire scientists and technologists to search for inexpensive alternatives from renewable chemicals. Phenol formaldehyde (PF) resins, the oldest type of synthetic polymers with good mechanical properties and heat resistance, are widely used in the production of coatings, laminates, molding compositions, and glues. Here, biobased urushiol-derived PF resins were synthesized from the alkali-catalyzed reaction between urushiol and formaldehyde. The chemical compositions and molecular structures of resole resins were characterized by carbon-13 nuclear magnetic resonance and Fourier transform infrared spectroscopy, and their curing behaviors were studied by differential scanning calorimetry. The as-prepared urushiol-derived resole resins had methylol (Ph−CH₂OH), ortho- and para-hemiformal groups (Ph−CH₂OCH₂OH), and the para−para/ortho−para/ortho−ortho links of methylene groups (Ph−CH₂−Ph), whereas the resole resins had low curing temperatures at about 100–113°C. Additionally, given the long side alkyl group moiety on the aromatic rings of urushiol, the films of cured urushiol-derived resole resins had low glass transition temperatures of 132 ± 2°C. Furthermore, the as-prepared urushiol-derived coatings exhibited excellent physical and mechanical properties.     

中国传统饮食文化融入食育路径研究

为国民身体素质、探索具有中国特色的现代食育之路，必须深入分析与探索中国饮食文化中的食育理念。文章以传统饮食文化为出发点和落脚点，概括出医食同源、饮食有节、饮食有礼等先进的食育观点。分析传统饮食与现代食育的关系，认为食育是弘扬传统饮食文化的重要途径，传统饮食文化是发展现代食育的基础。但探索现代食育仍面临着西方快餐文化冲击和国民食育进程缓慢等困境，必须采取强化国民食育意识、加强食育法制建设、健全食育教育体系、推进食育试点工作等措施促进中国传统饮食文化融入食育体系建设，真正探索具有中国特色的食育之路。     

Korean automatic spacing using pretrained transformer encoder and analysis

Automatic spacing in Korean is used to correct spacing units in a given input sentence. The demand for automatic spacing has been increasing owing to frequent incorrect spacing in recent media, such as the Internet and mobile networks. Therefore, herein, we propose a transformer encoder that reads a sentence bidirectionally and can be pretrained using an out-of-task corpus. Notably, our model exhibited the highest character accuracy (98.42%) among the existing automatic spacing models for Korean. We experimentally validated the effectiveness of bidirectional encoding and pretraining for automatic spacing in Korean. Moreover, we conclude that pretraining is more important than fine-tuning and data size.     

中国传统白酒中微量成分的来源与作用

根据中国传统白酒微量成分研究取得的新成果,系统地总结了微量成分来源及其作用。主要来源有3条途径:发酵过程中微生物和酶的催化反应、贮存过程中的化学变化和生产原料特殊成分的化学反应,主要起到了呈香呈味、成格成型和生理功能三方面的作用。生产原料对中国传统白酒微量成分的影响、高产白酒主体风味成分的基因菌构建与应用和白酒功能因子的深入研究等方向是未来研究的重点。     

荸荠皮酚类物质超声波辅助提取工艺优化

采用超声波辅助提取荸荠皮中的酚类物质,考察溶剂种类、料液比、提取温度、超声功率及超声时间对酚类物质提取率的影响。在单因素试验的基础上,确定最佳提取溶剂,并利用响应面法优化工艺条件。结果表明,荸荠皮总酚的最佳提取工艺条件为:甲醇提取,料液比1:15 (g/mL),提取温度55℃,超声功率270 W,超声时间55 min,该条件下总酚含量的最大响应值为4. 42 mg/g;荸荠皮总黄酮最佳提取工艺条件为:甲醇提取,料液比1:20 (g/mL),提取温度60℃,超声功率240 W,超声时间55 min,该条件下总黄酮含量的最大响应值为15. 20 mg/g。     

结合预训练模型和语言知识库的文本匹配方法

针对文本匹配任务,该文提出一种大规模预训练模型融合外部语言知识库的方法。该方法在大规模预训练模型的基础上,通过生成基于WordNet的同义—反义词汇知识学习任务和词组—搭配知识学习任务引入外部语言学知识。进而,与MT-DNN多任务学习模型进行联合训练,以进一步提高模型性能。最后利用文本匹配标注数据进行微调。在MRPC和QQP两个公开数据集的实验结果显示,该方法可以在大规模预训练模型和微调的框架基础上,通过引入外部语言知识进行联合训练有效提升文本匹配性能。     

Applied data science in patient-centric healthcare: Adaptive analytic systems for empowering physicians and patients

We define the emerging research field of applied data science as the knowledge discovery process in which analytic systems are designed and evaluated to improve the daily practices of domain experts. We investigate adaptive analytic systems as a novel research perspective of the three intertwining aspects within the knowledge discovery process in healthcare: domain and data understanding for physician- and patient-centric healthcare, data preprocessing and modelling using natural language processing and (big) data analytic techniques, and model evaluation and knowledge deployment through information infrastructures. We align these knowledge discovery aspects with the design science research steps of problem investigation, treatment design, and treatment validation, respectively. We note that the adaptive component in healthcare system prototypes may translate to data-driven personalisation aspects including personalised medicine. We explore how applied data science for patient-centric healthcare can thus empower physicians and patients to more effectively and efficiently improve healthcare. We propose meta-algorithmic modelling as a solution-oriented design science research framework in alignment with the knowledge discovery process to address the three key dilemmas in the emerging “post-algorithmic era” of data science: depth versus breadth, selection versus configuration, and accuracy versus transparency.     

基于大数据的C语言程序设计

C语言作为一种程序设计语言,在大数据组成的物联网和云计算中应用广泛,具有强大的适应性和兼容性,是大数据时代下,在IT行业中起到关键作用的程序设计语言。文章分析了基于大数据的C语言程序设计的必然性和应用策略,为C语言在大数据上的应用方向提供了参考依据。以汉字的应用为例,提出了解决C语言应用问题的思路。