Trends for nanotechnology development in China, Russia, and India

China, Russia, and India are playing an increasingly important role in global nanotechnology research and development (R&D). This paper comparatively inspects the paper and patent publications by these three countries in the Thomson Science Citation Index Expanded (SCI) database and United States Patent and Trademark Office (USPTO) database (1976–2007). Bibliographic, content map, and citation network analyses are used to evaluate country productivity, dominant research topics, and knowledge diffusion patterns. Significant and consistent growth in nanotechnology papers are noted in the three countries. Between 2000 and 2007, the average annual growth rate was 31.43% in China, 11.88% in Russia, and 33.51% in India. During the same time, the growth patterns were less consistent in patent publications: the corresponding average rates are 31.13, 10.41, and 5.96%. The three countries’ paper impact measured by the average number of citations has been lower than the world average. However, from 2000 to 2007, it experienced rapid increases of about 12.8 times in China, 8 times in India, and 1.6 times in Russia. The Chinese Academy of Sciences (CAS), the Russian Academy of Sciences (RAS), and the Indian Institutes of Technology (IIT) were the most productive institutions in paper publication, with 12,334, 6,773, and 1,831 papers, respectively. The three countries emphasized some common research topics such as “Quantum dots,” “Carbon nanotubes,” “Atomic force microscopy,” and “Scanning electron microscopy,” while Russia and India reported more research on nano-devices as compared with China. CAS, RAS, and IIT played key roles in the respective domestic knowledge diffusion

Developing nanotechnology in Latin America

This article investigates the development of nanotechnology in Latin America with a particular focus on Argentina, Brazil, Chile, and Uruguay. Based on data for nanotechnology research publications and patents and suggesting a framework for analyzing the development of R&D networks, we identify three potential strategies of nanotechnology research collaboration. Then, we seek to identify the balance of emphasis upon each of the three strategies by mapping the current research profile of those four countries. In general, we find that they are implementing policies and programs to develop nanotechnologies but differ in their collaboration strategies, institutional involvement, and level of development. On the other hand, we find that they coincide in having a modest industry participation in research and a low level of commercialization of nanotechnologies

COVID-19 therapy target discovery with context-aware literature mining

The abundance of literature related to the widespread COVID-19 pandemic is beyond manual inspection of a single expert. Development of systems, capable of automatically processing tens of thousands of scientific publications with the aim to enrich existing empirical evidence with literature-based associations is challenging and relevant. We propose a system for contextualization of empirical expression data by approximating relations between entities, for which representations were learned from one of the largest COVID-19-related literature corpora. In order to exploit a larger scientific context by transfer learning, we propose a novel embedding generation technique that leverages SciBERT language model pretrained on a large multi-domain corpus of scientific publications and fine-tuned for domain adaptation on the CORD-19 dataset. The conducted manual evaluation by the medical expert and the quantitative evaluation based on therapy targets identified in the related work suggest that the proposed method can be successfully employed for COVID-19 therapy target discovery and that it outperforms the baseline FastText method by a large margin.Comment: Accepted to the 23rd International Conference on Discovery Science (DS 2020

Measuring co-authorship and networking-adjusted scientific impact

Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I1 for a single scientist as the number of authors who appear in at least I1 papers of the specific scientist. For a group of scientists or institution, In is defined as the number of authors who appear in at least In papers that bear the affiliation of the group or institution. I1 depends on the number of papers authored Np. The power exponent R of the relationship between I1 and Np categorizes scientists as solitary (R>2.5), nuclear (R=2.25-2.5), networked (R=2-2.25), extensively networked (R=1.75-2) or collaborators (R<1.75). R may be used to adjust for co-authorship networking the citation impact of a scientist. In similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.Comment: 25 pages, 5 figure

The effect of word sense disambiguation accuracy on literature based discovery

Background The volume of research published in the biomedical domain has increasingly lead to researchers focussing on specific areas of interest and connections between findings being missed. Literature based discovery (LBD) attempts to address this problem by searching for previously unnoticed connections between published information (also known as “hidden knowledge”). A common approach is to identify hidden knowledge via shared linking terms. However, biomedical documents are highly ambiguous which can lead LBD systems to over generate hidden knowledge by hypothesising connections through different meanings of linking terms. Word Sense Disambiguation (WSD) aims to resolve ambiguities in text by identifying the meaning of ambiguous terms. This study explores the effect of WSD accuracy on LBD performance. Methods An existing LBD system is employed and four approaches to WSD of biomedical documents integrated with it. The accuracy of each WSD approach is determined by comparing its output against a standard benchmark. Evaluation of the LBD output is carried out using timeslicing approach, where hidden knowledge is generated from articles published prior to a certain cutoff date and a gold standard extracted from publications after the cutoff date. Results WSD accuracy varies depending on the approach used. The connection between the performance of the LBD and WSD systems are analysed to reveal a correlation between WSD accuracy and LBD performance. Conclusion This study reveals that LBD performance is sensitive to WSD accuracy. It is therefore concluded that WSD has the potential to improve the output of LBD systems by reducing the amount of spurious hidden knowledge that is generated. It is also suggested that further improvements in WSD accuracy have the potential to improve LBD accuracy

Tracing the wider impacts of biomedical research: A literature search to develop a novel citation categorisation technique

There is an increasing need both to understand the translation of biomedical research into improved healthcare and to assess the range of wider impacts from health research such as improved health policies, health practices and healthcare. Conducting such assessments is complex and new methods are being sought. Our new approach involves several steps. First, we developed a qualitative citation analysis technique to apply to biomedical research in order to assess the contribution that individual papers made to further research. Second, using this method, we then proposed to trace the citations to the original research through a series of generations of citing papers. Third, we aimed eventually to assess the wider impacts of the various generations. This article describes our comprehensive literature search to inform the new technique. We searched various databases, specific bibliometrics journals and the bibliographies of key papers. After excluding irrelevant papers we reviewed those remaining for either general or specific details that could inform development of our new technique. Various characteristics of citations were identified that had been found to predict their importance to the citing paper including the citation’s location; number of citation occasions and whether the author(s) of the cited paper were named within the citing paper. We combined these objective characteristics with subjective approaches also identified from the literature search to develop a citation categorisation technique that would allow us to achieve the first of the steps above, i.e., being able routinely to assess the contribution that individual papers make to further research.Medical Research Council as part of the MRC-NIHR Methodology Research Programme, and Professor Martin Buxton

International ranking systems for universities and institutions: a critical appraisal

<p>Abstract</p> <p>Background</p> <p>Ranking of universities and institutions has attracted wide attention recently. Several systems have been proposed that attempt to rank academic institutions worldwide.</p> <p>Methods</p> <p>We review the two most publicly visible ranking systems, the Shanghai Jiao Tong University 'Academic Ranking of World Universities' and the Times Higher Education Supplement 'World University Rankings' and also briefly review other ranking systems that use different criteria. We assess the construct validity for educational and research excellence and the measurement validity of each of the proposed ranking criteria, and try to identify generic challenges in international ranking of universities and institutions.</p> <p>Results</p> <p>None of the reviewed criteria for international ranking seems to have very good construct validity for both educational and research excellence, and most don't have very good construct validity even for just one of these two aspects of excellence. Measurement error for many items is also considerable or is not possible to determine due to lack of publication of the relevant data and methodology details. The concordance between the 2006 rankings by Shanghai and Times is modest at best, with only 133 universities shared in their top 200 lists. The examination of the existing international ranking systems suggests that generic challenges include adjustment for institutional size, definition of institutions, implications of average measurements of excellence versus measurements of extremes, adjustments for scientific field, time frame of measurement and allocation of credit for excellence.</p> <p>Conclusion</p> <p>Naïve lists of international institutional rankings that do not address these fundamental challenges with transparent methods are misleading and should be abandoned. We make some suggestions on how focused and standardized evaluations of excellence could be improved and placed in proper context.</p