Scientometrics: State-of-the-art

In this presentation we argue that the core research activities of scientometries fall in four interrelated areas: science and technology indicators, information systems on science and technology, the interaction between science and technology, and cognitive as well as socioorganisational structures in science and technology. We emphasize that an essential condition for the healthy development of the field is a careful balance between application and basic work, in which the applied side is the driving force. In other words: scientometrics is primarily a field of applied science. This means that the interaction users' is at least as important as the interaction with colleague-scientists. We state that this situation is very stimulating, it strengthens methodology and it activates basic work. We consider idea of scientometrics lacking theoretical content or being otherwise in a 'crisis-like' situation groundless. Scientometrics is in a typical developmental stage in which the creativity of its individual researchers and the ‘climate’ and facilities of their institutional environments determine the Progress in the field and, particularly, its relation with other disciplines. These aspects also contribute substantially to the reputation of scientometrics as a research field respected by the broader scientific community. And this latter point is important, both to let quantitative studies of science and technology take more advantage of an academic environment, as well as to keep it innovative and thus attractive in terms of applications at the longer term.     

Accelerating materials discovery using machine learning

The discovery of new materials is one of the driving forces to promote the development of modern society and technology innovation,the traditional materials research mainly depended on the trial-and-error method,which is time-consuming and laborious.Recently,machine learning (ML) methods have made great progress in the researches of materials science with the arrival of the big-data era,which gives a deep revolution in human society and advance science greatly.However,there exist few systematic generalization and summaries about the applications of ML methods in materials science.In this review,we first provide a brief account of the progress of researches on materials science with ML employed,the main ideas and basic procedures of this method are emphatically introduced.Then the algorithms of ML which were frequently used in the researches of materials science are classified and compared.Finally,the recent meaningful applications of ML in metal materials,battery materials,photovoltaic materials and metallic glass are reviewed.     

基于科技感感知的电动汽车内饰设计要素研究

目的确定电动汽车内饰设计要素与科技感的关系,获取与科技感风格意象关联度较高的感性词汇,将研究成果应用于实际案例设计中。方法构建内饰科技感的意象认知层次模型,以量产车和概念车内饰为对象,以统计问卷调查的频数均值作为方法,获取设计要素、类型要素与科技感的关联度及科技感语义特征关联词汇,并探讨这种关联关系和关联词汇的设计应用意义。结论为电动汽车内饰科技风格主题设计和评价提供依据和支持。设计要素与科技感以及意象关联词汇的研究表明,风格要素是关联科技感的关键,关联内饰科技感要素层级中,风格要素高于品质感要素,品质感要素高于功能要素;词汇统计结果表明,科技感意象认知语汇为简洁、炫酷、未来感和智能;对于量产车和概念车,内饰科技感的设计要素及其关联度存在差异。     

Die Joule-Thomson-Experimente—Anmerkungen zur Materialität eines Experimentes

To analyze science as practice and culture has become, since the early 1970s, the object of the “new” history and sociology of science. Hence, historians and sociologists pay now more attention to the role of experiment in science. In order to study experiments we need to think more carefully about instruments, apparatus and their use. In this article I put forward a method which allows to do both, to study the “materiality” of experiment as well as the activities involved in the production of experimental results: The “replication” of an experiment, ie. the reworking of historical experiments with a replica as close to the original as possible. A study of the experiments jointly done by James Joule, and William Thomson in 1852 will demonstrate what might be learned by this method about an experiment. The origins of instruments and the apparatus used in these experiments, their historical context and use will be discussed in detail. With the help of this case study I will try to show that the replication of experiments has much to contribute to an enhanced understanding of experimental practices.      

Cyclotron production of radioactive CeO(2) nanoparticles and their application for in vitro uptake studies

Nowadays, a wide variety of nanoparticles (NPs) are applied in different fields such as medical science and industry. Due to their large commercial volume, the OECD Working Party on Manufactured Nanomaterials (NMs) has proposed to study a set of 14 nanomaterials, one of which being cerium oxide (CeO(2)). In particular, CeO(2) based NPs are widely used in automotive industry, healthcare, and cosmetics. In this paper, we propose a method for the production of radioactive CeO(2) NPs.We demonstrate that they maintain the same physicochemical characteristics as the “cold” ones in terms of size distribution and Zeta potential; we develop a new protocol to assess their cellular interaction in immortalized mouse fibroblast cell line Balb/3T3, a model for the study of basal cytotoxicity and carcinogenic potential induced by chemicals and in the present case by NPs. Experimental result of this work, which shows a quasi-linear concentration-uptake response of cells, can be useful as a reference dose-uptake curve for explaining effects following biological uptake after exposure to CeO(2) NPs.     

A new network model for extracting text keywords

Text keywords are defined as meaningful and important words in a document, which provide a precise overview of its content and reflect the author’s writing intention. Keyword extraction methods have received a lot of attentions, among which is the network-based method. However, existing network-based keyword extraction methods only consider the connections between words in a document, while ignoring the impact of sentences. Since a sentence is made of many words, while words affect one another in a sentence, neglecting the influence of sentences will result in the loss of information. In this paper, we introduce a word network whose nodes represent words in a document, and define that any keyword extraction method based on a word network is called as a Word-net method. Then, we propose a new network model which considers the influence of sentences, and a new word-sentence method based on the new model. Experimental results demonstrate that our method outperforms the Word-net method, the classical term frequency-inverse document frequency (TF-IDF) method, most frequent method and TextRank method. The precision, recall, and F-measure of our result are respectively 7.95, 8.27 and 6.54% higher than the Word-net result, and the average precision of our result is 17.56% higher than the TF-IDF result. A two-way analysis of variance is employed to validate the empirical analysis, which indicates that keyword extraction methods and keyword numbers have statistically significant effects on the evaluation of metric values.     

Measuring the meaning of words in contexts: An automated analysis of controversies about 'Monarch butterflies,' 'Frankenfoods,' and 'stem cells'

Summary  Co-words have been considered as carriers of meaning across different domains in studies of science, technology, and society. Words and co-words, however, obtain meaning in sentences, and sentences obtain meaning in their contexts of use. At the science/society interface, words can be expected to have different meanings: the codes of communication that provide meaning to words differ on the varying sides of the interface. Furthermore, meanings and interfaces may change over time. Given this structuring of meaning across interfaces and over time, we distinguish between metaphors and diaphors as reflexive mechanisms that facilitate the translation between contexts. Our empirical focus is on three recent scientific controversies: Monarch butterflies, Frankenfoods, and stem-cell therapies. This study explores new avenues that relate the study of co-word analysis in context with the sociological quest for the analysis and processing of meaning.     

Modified Rule Ensemble Method for Binary Data and Its Applications

Ensemble learning, which combines multiple base learners to improve statistical prediction accuracy, is frequently used in statistical science and data mining. However, because of their “black box” nature, ensemble learning models are difficult to interpret. A recently proposed rule ensemble method known as RuleFit presents the base learner as a production rule and also generates a measure that influences the response variable. The RuleFit method for binary response applies a squared-error ramp loss function, and base learners are weighted by shrinkage regression using the lasso method. Thus, RuleFit is not constructed by a logistic regression model. Moreover, highly correlated pairs of base learners may be excessively pruned by the lasso method. In this study, we solved the excess pruning problem by constructing RuleFit within a logistic regression framework, weighting the base learners by elastic net. The effectiveness ofour proposed RuleFit model is illustrated through a real data set. In small-scale simulations, this method demonstrated higher predictive performance than the original RuleFit model.

     

On entropy research analysis: cross-disciplinary knowledge transfer

Our aim is to illustrate how the thermodynamics-based concept of entropy has spread across different areas of knowledge by analyzing the distribution of papers, citations and the use of words related to entropy in the predefined Scopus categories. To achieve this, we analyze the Scopus papers database related to entropy research during the last 20 years, collecting 750 K research papers which directly contain or mention the word entropy. First, some well-recognized works which introduced novel entropy-related definitions are monitored. Then we compare the hierarchical structure which emerges for the different cases of association, which can be in terms of citations among papers, classification of papers in categories or key words in abstracts and titles. Our study allowed us to evaluate, to some extent, the utility and versatility of concepts such as entropy to permeate in different areas of science. Furthermore, the use of specific terms (key words) in titles and abstracts provided a useful way to account for the interaction between areas in the category research space.     

New Generation Model of Word Vector Representation Based on CBOW or Skip-Gram

Word vector representation is widely used in natural language processing tasks. Most word vectors are generated based on probability model, its bag-of-words features have two major weaknesses: they lose the ordering of the words and they also ignore semantics of the words. Recently, neural-network language models CBOW and Skip-Gram are developed as continuous-space language models for words representation in high dimensional real-valued vectors. These vector representations have recently demonstrated promising results in various NLP tasks because of their superiority in capturing syntactic and contextual regularities in language. In this paper, we propose a new strategy based on optimization in contiguous subset of documents and regression method in combination of vectors, two of new models CBOW-OR and SkipGram-OR for word vector learning are established. Experimental results show that for some words-pair, the cosine distance obtained by the CBOW-OR (or SkipGram-OR) model is generally larger and is more reasonable than CBOW (or Skip-Gram), the vector space for Skip-Gram and SkipGram-OR keep the same structure property in Euclidean distance, and the model SkipGram-OR keeps higher performance for retrieval the relative words-pair as a whole. Both CBOW-OR and SkipGram-OR model are inherent parallel models and can be expected to apply in large-scale information processing.     

Maps of science as interdisciplinary discourse: co-citation contexts and the role of analogy

Interdisciplinarity can be manifest in many forms: through collaboration or communication between scientists working in different fields or through the work of individual scientists who employ concepts or methods across disciplines. This latter form of interdisciplinarity is addressed here with the goal of understanding how ideas in different fields come together to create new opportunities for discovery. Maps of science are used to suggest possible interdisciplinary links which are then analyzed by co-citation context analysis. Interdisciplinary links are identified by juxtaposing a clustering and mapping of documents against a journal-based categorization of the same document clusters. Links between clusters are characterized as interdisciplinary based on the dissonance of their category assignments. To verify and probe more deeply into the meaning of interdisciplinary links, co-citation contexts for selected links from five separate cases are analyzed in terms of prominent cue words. This analysis reveals that interdisciplinary connections are often based on authors’ perceptions of analogous problems across scientific domains. Cue words drawn from the citation contexts also suggest that these connections are viewed as important and ripe with both opportunity and risk.     

Tracking the evolution of new and emerging S&;T via statement-linkages: Vision assessment in molecular machines

The past 10 years has seen an explosion of interest for the area of science and technology labelled “nanotechnology.” Although at an early stage, nanotechnology is providing a space for the creation of new alliances and the forging of new ties in many actor arenas, initiated based on promises and high expectations of the fruits that could be harvested from development and investment into nanotechnology. Those trying to characterise the dynamics of emerging ties and networks within this field are faced with a number of complexities which are characteristic of the nanotechnology umbrella term, which covers many technologies, various mixes of disciplines and actors, and ongoing debates about definitions of fields and terminology. In this paper we explore an approach for capturing dynamics of emergence of a particular area of nanotechnology by investigating visions of possible futures in relation to molecular mechanical systems (molecular machines). The focus of this text is to outline an approach used to map and analyse visions in an emerging field by taking as the unit of analysis linkages made in statements in texts, and the agglomeration of linkages around certain nodes. Taking the linkage, rather than node, allows one to probe deeper into the dynamics of emergence at early stages when definitions and meanings of certain words/nodes are in flux and patterns of their use change dramatically over short periods of time. As part of a larger project on single and macromolecular machines we explore the dynamics of visions in the field of molecular machines with the eventual aim to elucidate the shaping strength of visions within nanotechnology.     

Using an integrated ontology database to categorize web pages

As we know, current classification methods are mostly based on the vector space model, which only accounts for term frequency in the documents, and ignores important semantic relationships between key terms. We have proposed a system that uses integrated ontologies and natural language processing techniques to index texts. The traditional words matrix is replaced by a concepts-based matrix. For this purpose, we have developed fully automated methods for mapping keywords to their corresponding ontology concepts. Support vector machine, a successful machine learning technique, is used for classification. Experimental results show that the proposed method improves text classification performance significantly.     

Identifying research topics in marketing science along the past decade: a content analysis

In recent years, how marketing science is conceptualized has changed, as have the methods through which data are investigated. This reconceptualization is making a significant impact on the most important topics of this discipline. Here, a novel approach is used to analyse a collection of 1169 abstracts from articles published in the Journal of Marketing Research and the Journal of Marketing from 2005 to 2014. We apply statistical methods to answer the following questions: How is vocabulary commonly used in marketing science? What are the most relevant topics of these journals? Which articles are the most influential? What words do authors prefer? Is the consumer among the primary topics in marketing research? A set of easy-to-read visual representations are provided to answer these questions. We highlight two main findings: (i) consumers and customers are the main topics of these marketing research journals, which emphasizes the growing interest in consumers and consumer behaviour as the core of both brick-and-mortar and online businesses; and (ii) in contrast to previous periods, product has become an essential concept, perhaps due to the emergence of new product considerations and new and enhanced interrelations.     

Temperature-responsive chromatographic separation of amino acid phenylthiohydantions using aqueous media as the mobile phase

Recently, green chemistry has become one of the most important subjects of science for environmental pollution prevention. Here, we report development of a novel chromatographic technology for phenylthiohydantoin (PTH)-amino acid analyses in which only aqueous solution is used as the mobile phase. We have devised HPLC adsorbents (stationary phase) by modifying the surfaces of microparticulate silica gel using functional polymers. The thermoresponsive copolymer, poly(N-isopropylacrylamide-co-n-butyl methacrylate) (IBc) was used to modify the silica stationary phase surfaces. This polymer-grafted surface exhibits temperature-regulated hydrophilic/hydrophobic property changes in water. PTH-amino acid interactions with this surface are readily modulated by changing the column temperature using an isocratic aqueous mobile phase. Increasing hydrophobic interactions between more hydrophobic PTH-amino acids with hydrophobized polymer-grafted surfaces at elevated mobile phase temperatures is used for the effective separation of PTH-amino acids in aqueous solution. This study is aimed at the development of novel separation processes, which are also environmentally benign, for use with biochemical substances in order to meet the growing needs of the life sciences and biotechnology. The method is useful for various separations in life science so that proteins can maintain their biological activity and enzymes, their enzymatic activity.     

Global perspectives on science diplomacy: Exploring the diplomacy‐knowledge nexus in contemporary histories of science

Contemporary scholarship concerning science diplomacy is increasingly taking a historical approach. In our introduction to this special issue, we argue that this approach promises insight into science diplomacy because of the tools historians of science bring to their work. In particular, we observe that not only are historians of science currently poised to chart the diplomatic aspects involved in the transnational circulation of technoscientific knowledge, materials, and expertise. They are ready to bring critical global analysis to an important phenomenon that has too often been treated as a benign diplomacy device deployed by the Global North without equal reference to the Global South. Through cases discussed in the articles of the special issue, however, we see that historically, in the Global South as well as the Global North, science diplomacy has often functioned to mediate the circulation of technoscientific knowledge and materials, and its historical study helps to better illuminate the resulting knowledge‐power nexus.     

Artisanal culture in early modern Iberian and Atlantic worlds

For several decades, historians have realized the limitations of analysing the historical past of science as a mere succession of theories. One of the most stimulating messages that the reinvention of the discipline has launched is that although there are obvious intellectual elements that promote the development and progress of science, there are also social, economic, and institutional aspects to consider. The history of science is no longer just a history of scientific ideas and theories, but also a history of institutions, communities, spaces, objects, and practices as well as a history of the complex interaction among all these dimensions. Accompanying this new panorama is a broad consensus among scholars to accept that major social changes have inexorably some impact on scientific practice and vice versa. This premise, now widespread, is especially relevant to the history of early modern science and the question of its roots because it has allowed the introduction of new agents and spaces previously excluded from the domain of scientific development. In other words, this enriched perspective has multiplied both the processes of knowledge construction and the arenas in which these processes were undertaken. More specifically, historical research is no longer limited to spaces traditionally linked to the construction of science; it now embraces less orthodox ones. Within this broadened field of inquiry, practical knowledge and the objects of material culture have come to occupy a central place. This special issue explores how the new directions in which the history of science has expanded have a direct impact on the study of Iberian science in the Atlantic world.     

Language use reflects scientific methodology: A corpus-based study of peer-reviewed journal articles

Recently, philosophers of science have argued that the epistemological requirements of different scientific fields lead necessarily to differences in scientific method. In this paper, we examine possible variation in how language is used in peer-reviewed journal articles from various fields to see if features of such variation may help to elucidate and support claims of methodological variation among the sciences. We hypothesize that significant methodological differences will be reflected in related differences in scientists’ language style. This paper reports a corpus-based study of peer-reviewed articles from twelve separate journals in six fields of experimental and historical sciences. Machine learning methods were applied to compare the discourse styles of articles in different fields, based on easily-extracted linguistic features of the text. Features included function word frequencies, as used often in computational stylistics, as well as lexical features based on systemic functional linguistics, which affords rich resources for comparative textual analysis. We found that indeed the style of writing in the historical sciences is readily distinguishable from that of the experimental sciences. Furthermore, the most significant linguistic features of these distinctive styles are directly related to the methodological differences posited by philosophers of science between historical and experimental sciences, lending empirical weight to their contentions.     

An author co-citation analysis of information science in China with Chinese Google Scholar search engine, 2004–2006

Author co-citation analysis (ACA) is an important method for discovering the intellectual structure of a given scientific field. Since traditional ACA was confined to ISI Web of Knowledge (WoK), the co-citation counts of pairs of authors mainly depended on the data indexed in WoK. Fortunately, Google Scholar has integrated different academic databases from different publishers, providing an opportunity of conducting ACA in wider a range. In this paper, we conduct ACA of information science in China with the Chinese Google Scholar. Firstly, a brief introduction of Chinese Google Scholar is made, including retrieval principles and data formats. Secondly, the methods used in our paper are given. Thirdly, 31 most important authors of information science in China are selected as research objects. In the part of empirical study, factor analysis is used to find the main research directions of information science in China. Pajek, a powerful tool in social network analysis, is employed to visualize the author co-citation matrix as well. Finally, the resemblances and the differences between China and other countries in information science are pointed out.