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This study aims to provide a comprehensive review and bibliometric analysis of the literature in the field of science, technology, engineering and mathematics (STEM) education over the past 15 years, with a specific focus on global distribution and research trends.

This study collected 1,718 documents from the Web of Science (WOS) database and analyzed their timeline distribution, geographical distribution, research topics, subject areas, learning stages and citation burst using a bibliometric approach with VOSviewer and Citespace.

Results indicated that: overall, STEM education has increasingly gained scholarly attention and is developing diversely by emphasizing interdisciplinary, cross-domain and regional collaboration. In terms of global collaboration, a collaborative network with the USA in the center is gradually expanding to a global scope. In terms of research themes, four key topics can be outlined including educational equity, pedagogy, empirical effects and career development. Social, cultural and economic factors influence the way STEM education is implemented across different countries. The developed Western countries highlighted educational equity and disciplinary integration, while the developing countries tend to focus more on pedagogical practices. As for research trends, eastern countries are emphasizing humanistic leadership and cultural integration in STEM education; in terms of teachers’ professional development, teachers’ abilities of interdisciplinary integration, technology adoption and pedagogy application are of the greatest importance. With regards to pedagogy, the main focus is for developing students’ higher-order abilities. In terms of education equity, issues of gender and ethnicity were still the hottest topics, while the unbalanced development of STEM education across regions needs further research.

This study provides a global landscape of STEM education along the timeline, which illustrates the yearly progressive development of STEM education and indicates the future trends.

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.

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.

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.

Under the carbon regulation mechanism, managing operational strategies is a challenging task. Green innovation is introduced into a hybrid system of manufacturing and remanufacturing to handle the carbon emission constraints in a dynamic market environment. This paper aims to investigate the joint dynamic green innovation policy and pricing strategies in a hybrid manufacturing and remanufacturing system.

This paper first considers a monopolistic manufacturer who offers brand-new products and remanufactured items at the same price to consumers. Subsequently, the authors extend their analyses to distinct pricing strategies for both newly manufactured products and refurnished ones in such a hybrid system. Two different cases are considered: a loose carbon emission constraint and a binding carbon emission constraint. By solving the dynamic optimization problem, the differential game and Pontryagin’s maximum principle are used to obtain the joint green innovation and pricing strategies.

The retail price first increases then declines over a single period. The green innovation diminishes in the same pricing decision model, while it first increases then declines in a distinct pricing decision model over a single planning horizon. The green innovation investment as well as the retail price are discouraged by an emission cap and recycling fraction. The distinct retail price fluctuates violently, and they are, in descending order of the highest peak price as follows: the newly manufactured product, the same pricing product and the repaired product. Carbon emission caps that are either too high or too low decrease the revenue of the manufacturer. A small emission constraint margin benefits the manufacturer. The recycling policy, as well as other parameters, affects whether the hybrid system attains the carbon emission constraint or not, which suggests that the recycling policy is complementary to the carbon emission constraint mechanism in the hybrid system.

These results offer managerial implications to the hybrid system in terms of green innovation, pricing strategies and recycling policy.

This paper is among the first papers to research the joint dynamic green innovation policy and pricing strategies with/without a carbon emission constraint in a hybrid manufacturing and remanufacturing system with a differential game. Moreover, this paper presents a potential way of investigating other common resource constraints by a differential game in a manufacturing/remanufacturing system or closed loop supply chain.

Due to the advantages of fast response, high positioning precision and large stiffness, the piezoelectric-actuated nanopositioning stage is widely used in the micro/nanomachining fields. However, due to the inherent nonlinear hysteresis of the piezoelectric-actuator, the positioning accuracy of nanopositioning stage is greatly degraded. Besides, the nanopositioning stage is always performed with repetitive trajectories as the reference signals in applications, which makes the hysteresis behavior periodic. To this end, an adaptive resonance suppression iterative learning control (ARS-ILC) is proposed to address the hysteresis effect. With this effort, the positioning accuracy of the nanopositioning stage is improved.

The hysteresis behavior is identified by the Prandtl–Ishlinskii model. By establishing a convergence function, it is demonstrated that the learnable band of ILC is restricted by the lightly damping resonance of nanopositioning stage. Then, an adaptive notch filter (ANF) with constrained poles and zeros is adopted to suppress the resonant peak. Finally, online stability supervision (OSS) is used to ensure that the estimated frequency converges to the resonant frequency.

A series of experiments were carried out in the nanopositioning stage, and the results validated that the OSS is available to ensure the convergence of the ANF. Furthermore, the learnable band was extended via ARS-ILC; thus, the hysteresis behavior of nanopositioning stage has been canceled.

Due to high accuracy and easy implementation, the ARS-ILC can be used in not only nanopositioning stage control but other fabrication process control with repetitive motion.

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 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.

With the rapid growth of the economy, people have increasingly higher living standards, and although people simply pursued material wealth in the past, they now pay more attention to material quality and safety and environmental protection. This paper discusses the lack of motivation for investing in fresh-keeping technology for agricultural products by individual members of an agricultural supply chain composed of a supplier and a retailer by means of mathematical models and data simulations and discuss the optimal price-invest strategies under different sales models.

First, based on the model of no investment by both sides (NN), this paper considers three models: supplier only (MN), retailer only (NR) and cooperative investment (MR). Then, the authors analyze the influence of consumer price sensitivity and freshness sensitivity on the investment motivation of agricultural products under four models. Subsequently, the paper makes a sensitivity analysis of the optimal strategies under several models, and makes a game analysis of the suppliers and retailers of agricultural products. Finally, we conduct an empirical analysis through specific values.

The results show that (a) when the two sides cooperate, the amount of investment is largest, the freshness of the agricultural products is highest, and the sales volume is greatest; however, when both sides do not invest, the freshness of agricultural products and sales volume are lowest. (b) The price and freshness sensitivity of the consumer have an impact on investment decisions. Greater freshness sensitivity corresponds to a higher investment, higher agricultural product price, greater sales volume, and greater supply chain member income and overall income; however, greater price sensitivity corresponds to a lower investment, lower agricultural product price, lower sales volume, fewer supply chain members and lower overall income. (c) The investment game between the supplier and retailer is not only related to the sensitivity to price and freshness but also to the coordination coefficients of interest. At the same time, the market position of agricultural products should be considered when making decisions. The market share of agricultural products will affect the final game equilibrium and then affect the final benefit of the supply chain and individual members.

These results provide managerial insights for enterprises preparing to invest in agricultural products preservation technology.

At present, the main problem is that member enterprises of agricultural supply chains operate based on their own benefits and are resistant to investing alone to improve the freshness of agricultural products. Instead, they would prefer that other members invest so that they may reap the benefits at no cost. Therefore, the enterprises in each node of the agricultural product supply chain are not motivated enough to invest, and competition and game states are observed among them, and such behavior is definitely not conducive to improving the freshness of agricultural products. However, the current research on agricultural products is more about price, quality and greenness, etc., and there are few studies on agricultural investment. Through the establishment of the model, this paper is expected to provide theoretical suggestions for the supply chain enterprises that plan to invest in agricultural products preservation technology.

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.