Consolidation of Black-dyed Māori Textile Artefacts: Evaluating the Efficacy of Sodium Alginate

Black-dyed artefacts are found in museums worldwide, many produced using an iron-tannate compound. Deterioration of iron-tannate dyed artefacts is an international preservation issue: in New Zealand the deterioration of paru (iron-tannate) dyed Māori textiles is widespread. This article reports experimental work testing the efficacy of sodium alginate, a consolidant developed for deteriorated paru-dyed muka (fibre from harakeke; Phormium tenax). The colour stability, strength retention, and acidity of paru-dyed muka consolidated with sodium alginate (0.25, 0.5, and 1% w/v in water) was tested pre- and post-artificial light ageing. This study found that sodium alginate had no negative effect on paru-dyed muka and in some cases provided benefit. Interestingly, the colour of paru-dyed muka is substantially more stable in UV-filtered light than previously recognised. Also microfading results were in agreement with visual assessments of colour change at 1 Mlux hour exposure, providing confidence in this relatively new technique to assess colour change.     

基于读者属性分析的图书馆空间再造研究

[目的/意义]现阶段很多图书馆都出现了空间不足、环境老化的现象,空间再造成为图书馆的一个迫在眉睫、亟待解决的重大课题。[方法/过程]根据图书馆空间五要素要求原则,从读者属性角度分析图书馆空间短缺的原因是来自读者对图书馆空间的需求差异,把握读者属性的特点才能更好的进行空间再造。[结果/结论]针对不同类型的图书馆给出有效改善图书馆空间紧缩或阅读空间空置率高等现状的相应思路。     

基于SKOS的学术期刊文本资源多粒度语义标注方法研究

[目的/意义] 针对学术期刊文本资源语义标注仍存在的通用本体难以构建、标注粒度单一两大问题,提出基于SKOS的学术期刊多粒度语义标注方法,从而进一步推进语义标注的应用发展,更好满足用户的多粒度学术信息需求。[方法/过程] 在对《中国汉语主题词表》进行SKOS描述的基础上,以学术期刊文本资源为对象,实现其多粒度语义标注,并通过实证研究验证该方法的可行性。[结果/结论] 利用SKOS实现对学术期刊文本资源进行多粒度语义标注,较之当前学术检索系统中的标注结果,在"查全"查准"内部特征检索入口"检索结果反馈形式"4个方面具有一定优势。     

Google Scholar's Coverage of the Engineering Literature 10 years Later

In 2008 Meier and Conkling first tested Google Scholar's coverage of the engineering literature against citations gathered from the Compendex database. Since that time, other studies have used the same methodology and found improvement in Google Scholar's coverage. This study uses engineering dissertations from Proquest Dissertations & Theses to create a data set of citations for the comparison of fee-based databases, Compendex and Scopus, against Google Scholar. From 1950 to 2017 Google Scholar outperformed both Compendex and Scopus in discoverability of citations in nine engineering subjects. These results have implications for collection management and information literacy program planning for librarians.     

The Professional Career and Life of Valerie Bross

ABSTRACT

The career path and significant professional accomplishments of librarian Valerie Bross (1954–2016) are described in this article. The awards and recognition she received are recounted and the influence of outside activities on her career is assessed. An attempt is made to capture what she was like as a professional, as well as what her unique characteristics were. A bibliography of her writings and a photograph are included.     

基于知识治理的公共档案馆服务质量优化机制研究

[目的/意义] 在公共档案馆服务质量优化中引入知识治理理论,使得复杂的服务质量优化问题获得更本质的理解和更有效的解决途径,为公共档案馆服务质量和服务能力提升提供参考。[方法/过程] 以知识治理理论为支撑,对公共档案馆服务质量优化进行分析与探讨,设计公共档案馆服务质量优化机制。[结果/结论] 通过借鉴和探析知识治理机制,构建公共档案馆服务质量影响因素优化机制,主要包括优化的环境、优化的目标、优化内部动能（治理机制）、优化外部动力和优化过程五个部分。     

Online Celebrity Bashing: Wrecking Ball or Good for You? Adolescent Girls’ Attitudes Toward the Media and Public Bashing of Miley Cyrus and Selena Gomez

Journalists and readers of celebrity news regularly bash celebrities online, a behavior that is easily accepted among adolescents. This study investigates whether these attitudes of acceptance differ according to the perpetrator of the bashing (media versus public) and the likeability of the involved celebrity (liked versus disliked). Using a vignette study, we examine adolescent girls’ attitudes toward media (journalists’) and public (readers’) bashing of a generally disliked celebrity (Miley Cyrus) and a generally liked celebrity (Selena Gomez). All participants read an identical negative news story (media bashing) and two related negative reader comments (public bashing). Participants were randomly assigned to read this information about either Miley Cyrus or Selena Gomez. Results of a mixed-design ANOVA showed that the girls had less negative attitudes toward media bashing compared with public bashing. Moreover, they more easily accepted the bashing of a disliked celebrity than the bashing of a liked celebrity.     

Not All Perceptual Gaps Were Created Equal: Explicating the Third-Person Perception (TPP) as a Cognitive Fallacy

Explicating the third-person perception (TPP) as a cognitive fallacy in the process of comparative social judgment of media effects, we propose that not all self–other perceptual gaps in media effects should be considered as TPP. When there is reasonably valid and accurate information regarding self vis-à-vis others on media consumption and vulnerability to media influence, the associated self–other gaps in media effects are not exaggerations, hence, not TPP. TPP results from cognitive biases in information retrieval and application in the process of comparative social judgments. Such biases are in the forms of self-other information differential, assimilation, contrast, and anchoring effects. Caveats in interpretation of extant evidence and implications for future TPP research are discussed.     

Retrieving and classifying instances of source code plagiarism

Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents.     

The Suasory Force of Sticky Messages: An Application to the Application of Sunscreen

Stickiness refers to the set of persuasive message properties: simple, unexpected, concrete, credible, emotional, and stories (SUCCES). Heath and Heath (2007) argue that a sticky message is expected to be more memorable and hence more persuasive than a non-sticky message. A 2 (sticky v. non-sticky message) x 3 (pretest v. posttest v. delayed test) longitudinal experiment is employed to examine the persuasiveness of sticky messages on applying sunscreen. Results of a mixed model analysis of variance show that the sticky message produces attitudes and behaviors more favorable to the message recommendation than the non-sticky message. Specifically, a time × message induction non-additive effect was found, which sustained only in the sticky message condition across time. Despite this interesting effect, its explanation remains elusive.