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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.

Members in a supply chain account for corporate social responsibility (CSR) in different ways. This paper considers a socially responsible supply chain in which the manufacturer innovates in a sustainable product while the retailer exhibits CSR concerns. This paper aims to investigate how socially responsible behavior, namely, sustainable innovations or CSR concerns, affects the pure profit, environmental impact and social welfare, in such a socially responsible supply chain.

This paper first constructs an integrated case as a benchmark and then develops a Manufacturer-Stackelberg game in a decentralized scenario. The pure profit, environmental impact and social welfare are confirmed and analyzed in centralized and decentralized cases. Moreover, two unique coordinating contracts, i.e. wholesale price discount contract and revenue-sharing contract, are used in this socially responsible supply chain.

Analytical analysis shows that, under certain conditions, the optimal CSR strategies hold for maximizing pure channel profit, minimizing environmental impact and maximizing social welfare. Whether the performance in a centralized case outnumbers that in a decentralized case depends on the CSR concerns level and environment-friendly degree of the product. In addition, it is found that a wholesale price discount contract is better for the retailer whereas a revenue-sharing contract is better for the manufacturer in pure profit to improve coordinating efficiency.

These results can offer managerial implications to the socially responsible supply chain in terms of pricing decisions, CSR strategies and sustainability innovations. Specifically, under certain conditions, placing more CSR concerns level increases pure channel profit and the social welfare. A balance between the pure profit and the social welfare is hereby achieved for the two socially responsible individuals by designing a proper contract.

To the best of the authors’ knowledge, this paper is among the first studies so far to combine the CSR concerns strategy and sustainability innovation into a socially responsible supply chain.

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.

Although leveraging social media to access healthcare information is nothing new, a boom in short video apps offers new potential for disseminating health-related information. However, it is still unclear how short video apps might facilitate and benefit users’ consumption of health information. Furthermore, the technology features of short video apps complicate attempts to conduct research about them; as a consequence, they have been understudied. For addressing these concerns, this study adopts an affordance perspective to investigate the relationship between affordances and user experience and to examine factors that contribute to users’ intention to continue using short video apps to obtain health information.

Drawing upon affordance theory, we constructed a research model that integrates four types of affordances (livestreaming, searching, meta-voicing and recommending), three types of user experience (immersion, social presence and credibility perception), and user’s intention to continue use. We employed an online survey and obtained a sample of 372 valid responses from TikTok (DouYin) users in China. The partial least squares (PLS) method was used to analyze the data.

The study found that the user experience, in terms of social presence, immersion and credibility perception, can significantly predict users’ intention to continue using short video apps to obtain health information. Furthermore, the user experience was positively associated with the different affordances provided by the short video apps.

The findings of this study have several implications. First, the study contributes to the health information behavior literature by incorporating the aspect of user experience. Moreover, the study extends the application of affordance theory to users’ health information acquisition, and it carries some practical implications on how to leverage the great potential of short video apps to serve public health communication better.

The purpose of the study is to investigate the financing channels and carbon emission abatement preferences of supply chain members, and further examine the optimal contract design of the retailer.

This paper develops a low-carbon supply chain composed of one retailer and one manufacturer, in which the retailer provides trade credit to the manufacturer. Considering the cap-and-trade regulation, the manufacturer with uncertain yield makes decision on whether to invest in emission abatement. There are bank loan and trade credit to finance production for the manufacturer and green credit to finance emission abatement investment. Meanwhile, the retailer may provide the manufacturer with three kinds of contracts to improve emission abatement efficiency, namely, revenue sharing, cost sharing or both sharing.

The results show that the retailer prefers to offer financing service at lower interest rate, but trade (and green) credit financing is always optimal for manufacturer and supply chain. The investment in emission abatement is value-added to all players. The sharing contracts offered by the retailer at lower sharing ratios can realize Pareto improvement of the system regardless of the financing scheme. However, comparing with the revenue or cost sharing contract, the existence of optimal sharing ratios makes the both sharing contract more favorable to the retailer.

The findings provide guidance for the emission-dependent manufacturer in financing and emission abatement decisions, as well as recommendations for the retailer to offer loan service and sharing contract.

This paper integrates green credit into bank loan or trade credit to analyze the financing decision of the manufacturer with uncertain yield and further considers the influence of three kinds of sharing contracts introduced by the retailer on improving operational performance.

The purpose of this paper is to report the design of a lightweight tree-shaped support structure for fused deposition modeling (FDM) three-dimensional (3D) printed models when the printing path is considered as a constraint.

A hybrid of genetic algorithm (GA) and particle swarm optimization (PSO) is proposed to address the topology optimization of the tree-shaped support structures, where GA optimizes the topologies of the trees and PSO optimizes the geometry of a fixed tree-topology. Creatively, this study transforms each tree into an approximate binary tree such that GA can be applied to evolve its topology efficiently. Unlike FEM-based methods, the growth of tree branches is based on a large set of FDM 3D printing experiments.

The hybrid of GA and PSO is effective in reducing the volume of the tree supports. It is shown that the results of the proposed method lead to up to 46.71% material savings in comparison with the state-of-the-art approaches.

The proposed approach requires a large number of printing experiments to determine the function of the yield length of a branch in terms of a set of critical parameters. For brevity, one can print a small set of tree branches (e.g. 30) on a single platform and evaluate the function, which can be used all the time after that. The steps of GA for topology optimization and those of PSO for geometry optimization are presented in detail.

The proposed approach is useful for the designers and manufacturers to save materials and printing time in fabricating complex models using the FDM technique. It can be adapted to the design of support structures for other additive manufacturing techniques such as Stereolithography and selective laser melting.

Tip leakage vortex flow (TLV) is a common flow phenomenon in the axial-flow hydraulic machinery. High-efficiency simulation of TLV is still not an easy task because of the complex turbulent vortex-cavitation interactions. As an important basis of CFD, turbulence model directly affects the efficient computation of TLV. The purpose of this paper is to evaluate the newly developed MST turbulence model in predicting the TLV flows.

By using the MST turbulence model and the ZGB cavitation model, numerical simulations of the TLV generated by a NACA0009 hydrofoil were performed under the cavitation-free and cavitation conditions, and the results were compared with the available experimental data.

The important features of TLV are well captured by the MST-based simulation scheme, and the problem of under-predicting the cavitating TLV tube is well solved. Turbulent viscosity is reasonably adjusted in the TLV core regions, and the LES-like mode is activated, which is beneficial to obtain more turbulent information on the same URANS grids. The requirements of grid size and time step of the MST model are much lower than that of the LES method, thereby weighing a good balance between the simulation accuracy and computation cost.

The MST turbulence model is suitable for the high-efficiency simulation of the TLV flows, which can lay a good foundation for efficient engineering computations of the cavitating TLV in the axial-flow hydraulic machinery.

Corporate social responsibility (CSR) has now been paid notable attention by a large number of firms. The aim of this paper is to investigate a better way to implement CSR in a socially responsible supply chain with different channel leaderships.

Started from measuring CSR by purely taking consumer surplus into account, a stylized centralized channel and two different decentralized channels are first developed and examined for equilibria in the socially responsible chain. Furthermore, this paper extends to a socially irresponsible supply chain and a broader practice of CSR by simultaneously incorporating environmental externality and consumer surplus into CSR.

With the analytical studies, several interesting and important results and managerial insights are clearly revealed. For example, but not limited to, it is found that: (1) Compared with the leader, the follower can effectively implement CSR for a better performance in both pure and socially responsible profits in the decentralized channel; (2) undertaking socially responsible concerns does not always mean reducing the economic profit and conversely being socially irresponsible does not always induce an increase in economic profit for the socially responsible member(s); (3) CSR concern level plays a key role in both the pure and socially responsible profit. An increase in CSR concern level clearly increases the socially responsible profit and poses an ambiguous impact on pure profit depending on different channel leaderships: it decreases the centralized channel in pure profit but increases the pure profit with the decentralized channel under certain conditions; and (4) interestingly, the authors find that decentralization can outperform centralization regarding on both pure and socially responsible channel profits by properly implementing CSR concern levels.

The results derived in this paper provide novel managerial implications to the socially responsible members in terms of pricing decisions, order quantity and CSR practice. In addition, this paper assists the socially responsible supply chain in determining the optimal channel leadership to undertake CSR. That is, decentralization may achieve a better performance than integration under certain market conditions.

To the best of the authors' knowledge, this paper is the first attempt to explore the interactive of the CSR practice and channel leadership in a socially responsible supply chain.

The objective of this paper is to provide a better understanding of the effect of irregular columnar jointed structure on the permeability and flow characteristics of rock masses.

An efficient numerical procedure is proposed to investigate the permeability and fluid flow in columnar jointed rock masses (CJRMs), of which the columnar jointed networks are generated by a modified constrained centroid Voronoi algorithm according to the field statistical results. The fractures are represented explicitly by using the lower-dimensional zero thickness elements. And the modeling scheme is validated by a benchmark test for flow in fractured porous media. The effective permeability and representative elementary volume (REV) size of CJRMs are estimated using finite element method (FEM). The influences of joint density and variation coefficient of columnar joint structure on the permeability of the rock mass are discussed.

The simulation results indicate that the permeability is scale-dependent and tends to be stable with increase of model size. The hydraulic REV size is determined as 3.5 m for CJRMs in the present study. Moreover, the joint density is a dominant factor affecting the permeability of CJRMs. The average permeability of columnar jointed structures increases linearly with the joint density under the same REV size, while the influence from the coefficient of variation can be neglected.

The present paper investigates the REV size of the CJRMs and the effect of joint parameters on the permeability. The proposed method and the results obtained are useful on understanding the hydraulic characteristic of the irregular CJRMs in engineering projects.

The purpose of this paper is to investigate the structural, electronic and optical properties of pure zinc oxide (ZnO) and transition metal (Tm)-doped ZnO using Tm elements from silver (Ag) and copper (Cu) by a first-principles study based on density functional theory (DFT) as implemented in the pseudo-potential plane wave in CASTEP computer code.

The calculations based on the generalized gradient approximation for Perdew-Burke-Ernzerhof for solids with Hubbard U (GGA-PBEsol+U) were performed by applying Hubbard corrections U_d = 5 eV for Zn 3d state, U_p = 9 eV for O 2p state, U_d = 6 eV for Ag 4d state and U_d = 9.5 eV for Cu 3d state. The crystal structure used in this calculation was hexagonal wurtzite ZnO with a space group of P63mc and supercell 2 × 2 × 2.

The total energy was calculated to determine the best position for Ag and Cu dopants. The band structures and density of states show that Tm-doped ZnO has a lower bandgaps value than pure ZnO because of impurity energy levels from Ag 4d and Cu 3d states. In addition, Ag-doped ZnO exhibits a remarkable enhancement in visible light absorption over pure ZnO and Cu-doped ZnO because of its lower energy region and extended wavelength spectrum.

The results of this paper are important for the basic understanding of the 3d and 4d Tm doping effect ZnO and have a wide range of applications in designing high-efficiency energy harvesting solar cells.