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In this study, we present an approach to create a visual research topic map for materials science researchers from a large collection of archived research papers using natural language processing (NLP). We apply this approach on SAMURAI, a directory service for the researchers of the National Institute for Materials Science (NIMS), Japan. Visualization of research content will support exploratory searches by maximizing the information absorbance and intuitively capturing the research characteristics of each materials science researcher. In addition, a research topic map can connect researchers with similar topics aiming to find potential collaborators. Collaboration can support the advance of scientific research. We analyze all available publications of a researcher using frequent term analysis. In addition, materials science knowledge resources were utilized including dictionaries and automatic extraction for the material names. Noise reduction was implemented using stop word filtering. The topics were then visualized using a word cloud technique for each researcher. An analysis of the topic similarity was conducted to find researchers that share similar topics leading to the creation of a topic map for each researcher. The approach aims at maximizing information absorbance for public knowledge by applying NLP approaches to information mining from materials science research papers. NLP analysis and visualization code are available . [ABSTRACT FROM AUTHOR]

This paper proposes a methodology which discriminates the articles by the target authors ('true' articles) from those by other homonymous authors ('false' articles). Author name searches for 2,595 'source' authors in six subject fields retrieved about 629,000 articles. In order to extract true articles from the large amount of the retrieved articles, including many false ones, two filtering stages were applied. At the first stage any retrieved article was eliminated as false if either its affiliation addresses had little similarity to those of its source article or there was no citation relationship between the journal of the retrieved article and that of its source article. At the second stage, a sample of retrieved articles was subjected to manual judgment, and utilizing the judgment results, discrimination functions based on logistic regression were defined. These discrimination functions demonstrated both the recall ratio and the precision of about 95% and the accuracy (correct answer ratio) of 90-95%. Existence of common coauthor(s), address similarity, title words similarity, and interjournal citation relationships between the retrieved and source articles were found to be the effective discrimination predictors. Whether or not the source author was from a specific country was also one of the important predictors. Furthermore, it was shown that a retrieved article is almost certainly true if it was cited by, or cocited with, its source article. The method proposed in this study would be effective when dealing with a large number of articles whose subject fields and affiliation addresses vary widely. [ABSTRACT FROM AUTHOR]

We applied the full-length eDNA Qvere~pressor (FOX) gene-hunting system for systematic and genome-wide functional analysis of rice genes. In this study, we constructed a novel binary vector carrying the Gateway site-specific recombination cassette and then constructed rice FOX libraries containing a maximum of 13,823 independent, full-length cDNAs (fl-cDNAs) that correspond to approximately half the total number of rice fl-cDNA clones. By introducing the FOX libraries via Agrobacterium, we generated 2,586 FOX-rice lines exhibiting various visible alterations (e.g., plant height, tillers, leaves, and heading dates). The introduced ficDNAs, integrated into individual transgenic rice genomes, were amplified by genomic PCR and identified using sequencing analysis. The fl-cDNAs were PCR-amplified in 2,251 (94.2%) of the 2,389 FOX-rice lines that were examined, identifying 1,920 independent fl-cDNAs in the FOX lines. In addition to the previously generated FOX-rice plants, our new collection of FOX-rice lines produced through the Gateway system should be a useful tool for the efficient identification of gene functions in rice. Moreover, this Gateway-based technology should be applicable to other species in which a collection of fl-eDNA clones is available. [ABSTRACT FROM AUTHOR]