运动疗法治疗颈痛的中国专家共识

颈痛(neck pain)是成年人慢性病中最常见的健康问题之一,发病率高达71%。《"健康中国2030"规划纲要》要求:广泛开展全民健身运动,加强体医融合和非医疗健康干预。为进一步加强体医融合,提高运动疗法改善颈痛的治疗水平,来自中国康复科学、骨科以及运动科学等领域的专家组制定了"运动疗法治疗颈痛的中国专家共识"。经检索国内外常用电子数据库,参考国际常用的证据水平进行分级,结合中国正积极倡导的"非医疗健康干预"和"体医融合",该专家共识提出了符合中国特色的运动疗法治疗颈痛的规范和推荐建议,指导物理治疗实践和推行体医融合理念。     

Computing semantic similarity based on novel models of semantic representation using Wikipedia

Computing Semantic Similarity (SS) between concepts is one of the most critical issues in many domains such as Natural Language Processing and Artificial Intelligence. Over the years, several SS measurement methods have been proposed by exploiting different knowledge resources. Wikipedia provides a large domain-independent encyclopedic repository and a semantic network for computing SS between concepts. Traditional feature-based measures rely on linear combinations of different properties with two main limitations, the insufficient information and the loss of semantic information. In this paper, we propose several hybrid SS measurement approaches by using the Information Content (IC) and features of concepts, which avoid the limitations introduced above. Considering integrating discrete properties into one component, we present two models of semantic representation, called CORM and CARM. Then, we compute SS based on these models and take the IC of categories as a supplement of SS measurement. The evaluation, based on several widely used benchmarks and a benchmark developed by ourselves, sustains the intuitions with respect to human judgments. In summary, our approaches are more efficient in determining SS between concepts and have a better human correlation than previous methods such as Word2Vec and NASARI.     

A novel reasoning mechanism for multi-label text classification

The aim in multi-label text classification is to assign a set of labels to a given document. Previous classifier-chain and sequence-to-sequence models have been shown to have a powerful ability to capture label correlations. However, they rely heavily on the label order, while labels in multi-label data are essentially an unordered set. The performance of these approaches is therefore highly variable depending on the order in which the labels are arranged. To avoid being dependent on label order, we design a reasoning-based algorithm named Multi-Label Reasoner (ML-Reasoner) for multi-label classification. ML-Reasoner employs a binary classifier to predict all labels simultaneously and applies a novel iterative reasoning mechanism to effectively utilize the inter-label information, where each instance of reasoning takes the previously predicted likelihoods for all labels as additional input. This approach is able to utilize information between labels, while avoiding the issue of label-order sensitivity. Extensive experiments demonstrate that our method outperforms state-of-the art approaches on the challenging AAPD dataset. We also apply our reasoning module to a variety of strong neural-based base models and show that it is able to boost performance significantly in each case.     

Countering Youth's Negative Stereotypes of Teens Fosters Constructive Behavior

Adolescence can be a time of unconstructive behavior for many youth. This research examined if an intervention countering youth's stereotypes of teens as irresponsible fosters their constructive behavior. In two experimental intervention studies (Ns = 124 and 319) with seventh graders, stereotypes of teens as irresponsible were described as inaccurate portrayals; youth then provided their own observations of teens acting responsibly. Youth in this counterstereotyping intervention (vs. the control) held higher intentions for academic engagement and performed better on an academic task (i.e., a word-search puzzle). Over the 3 days following the intervention, their academic engagement was higher. Youth's risk taking was also reduced. Redirecting youth to see teens as responsible has the potential to provide a foundation for flourishing.     

多媒体环境下的英语词汇教学模式探索

随着计算机技术的普及和多媒体技术应用的优势变得更加显著,传统英语词汇教学模式已无法满足当前英语教学发展的需要。在建构主义学习理论的指导下,从英语教学实践出发,在多媒体技术提供的仿真学习环境中,改变了传统的英语教学模式,实现了学生主动探究学习词汇和完成意义的重新构建的目标,有利于提高英语教学的效率。     

德育生态化视角下高职学生思政教育“主渠道、主阵地”生态系统的创建

在德育生态化视角下,探寻德育生态化与高职学生思政教育“主渠道、主阵地”的契合点,充分体现思想政治教育理论课教学、形势课教学、专业课教学、校园文化建设、心理健康教育、就业指导工作、社会实践、学生资助工作、学生社团建设、学生行为修养、学生自我成长等的生态化并提高其生态效应,努力构建高职学生思想政治教育“主渠道、主阵地”的生态系统,进一步增强高职学生思想政治教育的针对性、实效性,最终实现学生的和谐、全面发展.     

论白居易和杜甫对石川啄木诗作的影响

文章选取了日本近代浪漫主义诗人石川啄木代表作《一握砂》中的四首短歌,结合其随笔与日记,探讨了白居易和杜甫对啄木的影响.     

Non-destructive Analysis and Deterioration Study of a Decorated Famille Rose Porcelain Bowl of Qianlong Reign from the Forbidden City

ABSTRACT

In August 2014, a pit containing more than 10000 porcelain shards was excavated in the southwestern area of the Palace Museum. Reign marks and other stylistic criteria dated the manufacture of these fragments from the reign of Hongwu in the Ming Dynasty (1368–98 CE) to the Guangxu reign in the Qing Dynasty (1875–1908 CE). A famille rose (fencai, 粉彩) bowl decorated with a red-ground peony pattern and having the reign mark of Qianlong (1736–96 CE) on the base was studied using several non-destructive analytical methods to determine the variation in overglaze compositions, the colorants, the application sequences, the thickness of the colored layers and the high-temperature porcelain glaze, and the identification of the surface weathering products that formed during burial. The methods include non-destructive X-ray fluorescence, Raman spectroscopy, optical stereomicroscopy, and laser confocal microscopy, as well as X-ray diffraction.     

中国机器人产业发展现状与展望

文章分析了国内外机器人产业发展现状,介绍了新松机器人产业布局,并对机器人与工业4.0、互联网+融合产生的影响进行了展望。     

中小学英语校本课程开发的与思考

在当今如火如荼的进行的课程改革之中,基于学校的具体形式和英语教学的特殊性,在强调交际拓展、文化传播的指导下,中小学英语校本课程的开发代表了一种新的课程理念和课程形态。校本课程的开发本身就具有了一定深度的探究性质,文章从英语校本课程开发的基本原则、可能遇见的问题以及相应解决对策,对中小学英语校本课程开发进行了一定的思索以及探究。