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This study aims to analyse the geographical distribution of global research activities and to investigate the knowledge diffusion embodied in scientific papers.

The geographical summary of Frontiers articles displays the number of visits and categorizes where the visitors hail from. This study uses the records of 23,798 articles published in 16 Frontiers journals from 2007 to 2015 to analyse the geographical distribution of article visits at both country and city levels. The process of knowledge diffusion is investigated on the basis of the different visiting patterns of new and old papers.

Most article visits are concentrated around major metropolitan areas and some high-tech clusters. The top “visiting countries” include both developed countries and developing countries, and the USA and China are two major players. Publishing cities dominate article visits for new papers; as time passes, there is diffusion from the publishing cities to a broader area.

The data on visiting for open access articles may be generated from various repositories besides the publishers’ websites; these data are ignored, as they are not significant enough to have much influence. There is also a lack of a basic theory in the data processing of outliers in the data set. In addition, only static results are given in this paper, as the data were collected on one day, for one time. A longer time period is necessary to track the dynamic diffusion process of the observations.

Introduction of usage data will propose a novel way to analyse research activities and track knowledge diffusion.

The visiting data of articles offer a new way to investigate research activities at the city level in a detailed and timely manner, for the geographical distribution of research activities and the research resource allocation of a specific country to be explored.

This study measured the research activities of scientific papers by examining the usage data. Compared with previous studies that focused on the geographical distribution of scientific activities using publication data, citation data and even altmetrics data, usage data are at the forefront of this research. Therefore, usage data offer a fresh perspective on methodology, providing more detailed and real-time information.

The purpose of this paper is to investigate the evolution of Gold open access (OA) rates in different countries and disciplines, as well as explore the influencing factors.

In this study, employing the OA filter option of Web of Science (WoS), the authors perform a large-scale evaluation of the OA state of countries and disciplines from 1990 to 2016. Particularly, the authors consider not only the absolute number of Gold OA literature but also the ratio of them among all literature.

Currently, one-quarter of the WoS articles is Gold OA articles. Brazil is the most active country in OA publishing, while Russia, India and China have the lowest OA ratios. The OA percentage of Brazil has been decreasing dramatically in recent years, while the OA percentages of China, UK and the Netherlands have been increasing. There also exist huge differences of OA percentages across different subject categories. The percentages of OA articles in biology, life, and health-related areas are high, while those in physics and chemistry-related subject categories are very low.

With the availability of large-scale data from WoS, this study conducts a comprehensive evaluation of the Gold OA state of major countries for the first time. The variation of OA percentages is considered in light of the research profiles. OA policies in different countries and funding organizations also have an influence on the OA development.

The purpose of this paper is to reveal a symbol – “however” that authors are very interested in, but few research studies pay attention to the existing literature. The authors aim to further insight its function.

In this research, the authors selected 3,329 valid comments on articles published in the British Medical Journal (BMJ) from 2015 to 2020 as the research objects. The authors showed the length distribution of reviewers' comments. In what follows, the authors analyzed the general distribution of words in comments and reviewer comments’ position to understand reviewers' comments qualitatively in word dimension. Specially, the authors analyzed functions of “however” and “but”, words that authors are most concerned with. In addition, the authors also discussed some factors, which may be related to “however,” that reflect reviewers' praise through regression analysis.

The authors found that there are marked differences in the length of reviewers' comments under different review rounds. By mapping the reviewers' comments to different sections, the authors found that reviewers are deeply concerned to methods section. Adjectives and adverbs in comments written in different sections of the manuscripts also have different characteristics. The authors tried to interpret the turning function of “however” in scientific communication. Its frequency of use is related to reviewers' identities, specifically academic status. More precisely, junior researchers use “however” in praise more frequently than senior researchers do.

The linguistic feature and function of “however” and “but” in the reviewers' comments of the rejected manuscripts may be different from accepted papers and also worth exploring. Regrettably, the authors cannot obtain the peer review comments of rejected manuscripts. This point may limit the conclusion of the investigation of this article.

Overall, the survey results revealed some language features of reviewers' comments, which could provide a basis of future endeavors for many reviewers in open peer review (OPR) field. Specially, the authors also put forward an interesting symbol to examine the review comments, “however”, for the first time.

The purpose of this paper is to analyze the network structure of technology in and between different fields, as well as the evolution of their relations.

Using the patent data in Derwent Innovation Index (DII) from 1991 to 2010, this paper analyzes the co-classification of Derwent Manual Code (DMC) of patents in all technology fields. Large-scaled co-classification matrices are employed to generate the DMC co-classification networks. In addition, analyses are pursued at different levels of aggregation in four five-year windows: 1991-1995, 1996-2000, 2001-2005 and 2006-2010. Using Girvan-Newman algorithm in the clustering process, the structure transformations over time are detected.

The paper identifies the key technological knowledge in certain fields and finds out how different technological fields are connected and integrated. What is more, the dynamic evolution between networks in different time periods reveals the trend of generic technology development in the macroscopic level.

The paper investigates a large quantity of data – all the patent data in DII from 1991 to 2010 in this paper. The paper applies Girvan-Newman algorithm in the co-classification analysis and uses co-classification networks to reveal technology network structures. Evolution coincident with the realistic technological shifts can be observed.

This paper aims to assess the impact of research in the field of scientometrics by using the altmetrics (social media metrics) approach.

This is an applied study which uses scientometric and altmetrics methods. The research population consists of the studies and their citations published in the two core journals (Scientometrics and Journal of Informetrics) in a period of five years (included 1,738 papers and 11,504 citations). Collecting and extracting the studies directly was carried from Springer and ScienceDirect databases. The Altmetric Explorer, a service provided by Altmetric.com, was used to collect data on studies from various sources (www.altmetric.com/). The research studies with the altmetric scores were identified (included 830 papers). The altmetric scores represent the quantity and quality of attention that the study has received on social media. The association between altmetric scores and citation indicators was investigated by using correlation tests.

The findings indicated a significant, positive and weak statistical relationship between the number of citations of the studies published in the field of scientometrics and the altmetric scores of these studies, as well as the number of readers of these studies in the two social networks (Mendeley and Citeulike) with the number of their citations. In this study, there was no statistically significant relationship between the number of citations of the studies and the number of readers on Twitter. In sum, the above findings suggest that some social networks and their indices can be representations of the impact of scientific papers, similar citations. However, owing to the weakness of the correlation coefficients, the replacement of these two categories of indicators is not recommended, but it is possible to use the altmetrics indicators as complementary scientometrics indicators in evaluating the impact of research.

Investigating the impact of research on social media can reflect the social impact of research and can also be useful for libraries, universities, and research organizations in planning, budgeting, and resource allocation processes.

To ensure accurate position and force control of massage robot working on human body with unknown skin characteristics, this study aims to propose a novel intelligent impedance control system.

First, a skin dynamic model (SDM) is introduced to describe force-deformation on the human body as feed-forward for force control. Then a particle swarm optimization (PSO) method combined with graph-based knowledge transfer learning (GKT) is studied, which will effectively identify personalized skin parameters. Finally, a self-tuning impedance control strategy is designed to accommodate uncertainty of skin dynamics, system delay and signal noise exist in practical applications.

Compared with traditional least square method, genetic algorithm and other kinds of PSO methods, combination of PSO and GKT is validated using experimental data to improve the accuracy and convergence of identification results. The force control is effective, although there are contour errors, control delay and noise problems when the robot does massage on human body.

Integrating GKT into PSO identification algorithm, and designing an adaptive impedance control algorithm. As a result, the robot can understand textural and biological attributes of its surroundings and adapt its planning activities to carry out a stable and accurate force tracking control during dynamic contacts between a robot and a human.

The current student selection process for short-term mobility actions under the Erasmus + program (i.e. intensive programs and blended intensive programs) is based exclusively on the students' order of enrolment and their grades. This study offers an alternative approach using the analytic hierarchy process based on a four-layer model that collects information about the specificities of each project and the profile of the students and also promotes greater inclusion and homogenization of the project teams.

A decision support system was built by decomposing it into three stages: the predesign stage, in which the problem is characterized, and the user requirements are identified; the design stage, in which the models, the database and the interfaces are formulated; and the field stage, in which six test scenarios were built to validate the proposed solution.

The results show that this model can be applied with various selection criteria among students and consider both their hard and soft skills. It can also be applied to help build teams in which the students' knowledge is aligned with the technical skills required by the projects.

The proposed approach is innovative in that it responds to the emerging challenge of short-term European mobility programs that aim to involve students with multidisciplinary competencies. The solution considers both hard and soft skills in the selection of students, which allows changing the student selection paradigm and obtaining potentially more homogeneous multicultural teams with greater learning potential.

The purpose of this paper is to explore the effects of the camber on gliding and hovering performance of two-dimensional corrugated airfoils. While the flying mechanism of natural flyers remains a myth up to nowadays, the simulation serves as a minor step toward understanding the steady and unsteady aerodynamics of the dragonfly flight.

The lattice Boltzmann method is used to simulate the flow past the cambered corrugated dragonfly airfoil at low Reynolds numbers. For gliding flight, the maximum camber, the distance of the location of maximum camber point from the leading edge and Reynolds number are regarded as control variables; for hovering flight, the maximum camber, the flapping amplitude and trajectory are considered as control variables. Then corresponding simulations are performed to evaluate the implications of these factors.

Greater gliding ratio can be reached by increasing the maximum camber of the dragonfly wing section. When the location of the maximum camber moves backward along the wing chord, large scale flow separation can be delayed. These two effects result in better gliding performances. For hovering performances, it is found that for different flapping amplitudes along an inclined plane, the horizontal force exerted on the airfoils increases with the camber, and the drag growths first but then drops. It is also found that the elliptic flapping trajectory is most sensitive to the camber of the cambered corrugated dragonfly wing section.

The effects of the camber on gliding and hovering performance of the cambered dragonfly wing section are explored in detail. The data obtained can be helpful when designing micro aerial vehicles.

Could “Economic Man” and “Moral Man” be integrated? Could “Business” and “Morality” contain each other? An attempt is made to verify, from the theoretical formation, the value rationality of economic behaviour, to seek the value co‐structure of ethics and economics.