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In this paper, a dynamic projection scanning lithography (DPSL) technology and system is proposed to achieve cross-scale 3D printing, addressing the limitations of the traditional 3D printing methods that struggle to achieve both large build volumes and high precision. The method achieves a printing accuracy of 10 µm within a build volume of 100 × 100 × 100 mm, and successfully fabricates complex hollow structures and functional models.

DPSL uses a digital micromirror device (DMD)-based digital projector to generate light patterns for light-curing printing. The light patterns are created by sequentially loading the print design frame by frame, forming dynamic light patterns that are scanned line by line across the material surface for solidifying the printing materials. By controlling the scanning range of the digital projector, it is theoretically able to print models of any size. Additionally, by using DMD oblique scanning, the impact of the DMD micromirrors’ shape and arrangement on print accuracy is addressed by overlapping exposures along the scanning direction of the digital projector.

This study shows the printing system resolution of 1.3 µm, while the maximum size of the printing model depends on the system scanning range. Additionally, by using DMD oblique scanning, the impact of the DMD micromirrors’ shape and arrangement on print accuracy is addressed by overlapping exposures along the scanning direction of the digital projector.

This work demonstrates that DPSL based on oblique scanning technology is used to achieve 3D printing with high precision, large area and smoother surface. In addition, a rigid release method is used to achieve a precise printing layer thickness in the top-down printing process. By adhering the release film to the bottom surface of the glass and adjusting the descent distance of the stage for each layer, uniform layer thickness can be achieved for each exposure.

Merchant guild culture derives from business practices associated with medieval and early modern merchant guilds. This study aims to investigate the nexus between merchant guild culture and firm internationalization as well as the factors that moderate this nexus.

Based on the distribution of the ten merchant guilds in China and data on Chinese listed companies, this study uses the geographical proximity-based method to measure the intensity of merchant guild culture, which is the nearest distance between the ten merchant guilds’ origins and each firm’s registered address.

This study provides robust evidence that merchant guild culture positively relates to the degree of firm internationalization. It also documents that this nexus is stronger for firms with overseas background executives and those situated in highly marketized regions.

The findings of this study have valuable implications for both governments and firms. Governments can leverage local cultures to promote the internationalization of domestic firms, particularly in emerging economies with rich cultural heritage. Firms can further enhance their internationalization efforts by hiring more executives with overseas backgrounds.

This study advances the imprinting literature, provides a novel perspective on the antecedents of firm internationalization and expands research on the contemporary value of historical business culture.

Recently, many scholars have been paying more attention to studying the existence and application of multifractality. However, most researches concentrate on studying multifractal features of returns or volume separately, and ignore the correlation between them. The purpose of this paper, therefore, is to give an empirical test on multifractal features of price‐volume correlation in China metal futures market and then to conduct a comparative analysis from time and space dimensions, in order to better understand metals futures market behavior.

This paper gives an empirical test by means of multifractal detrended cross‐correlation analysis (MF‐DCCA) approach, which is a technique employed in statistical physics to detect multifractal features of two cross‐correlated nonstationary time series.

Empirical results show that the price‐volume correlation in China metal futures market is multifractal and that long range correlation and non‐Gaussian probability distribution are the main reasons for the existence of multifractality. Also, a comparative analysis is conducted and it is found that although China metal futures market is becoming more and more effective, the effectiveness is lower than that in mature LME metal futures markets. The futures market still needs further development.

The paper's conclusions would help to understand the nonlinear dependency relationship and potential dynamics mechanism in price‐volume correlation.

This study uses data from the Chinese banking sector to explore the relationship between green credit and risk-taking in commercial banks. It also examines whether the level of regional green development acts as a moderator regarding this relationship.

Using a dataset composed of annual observations from 57 Chinese commercial banks between 2008 and 2021, this study employs both piecewise and curvilinear models.

Our results indicate that when the scale of green credit is low (<0.164), it increases the risk-taking of commercial banks. Conversely, when the scale of green credit is high (>0.164), it reduces the risk-taking of commercial banks. Moreover, this nonlinear relationship impact exhibits bank heterogeneity. Furthermore, the results show that the level of regional green development and local government policy support negatively moderate the relationship between green credit and commercial bank risk-taking. Furthermore, we find that green credit can directly enhance the net interest margin of commercial banks.

This study is the first to provide evidence of a nonlinear relationship between green credit and risk-taking in commercial banks, and it identifies the significant roles of regional green development level and local government policy support in the Chinese context.

Today's logistics industry is facing severe challenges since global transportation demand increases substantially. Carriers are urged to reduce empty loads and CO2 emissions through collaboration. Therefore, the concept of Physical Internet (PI) came into being. However, PI is still in its infancy. It is difficult to understand its sophisticated coordination mechanism, which makes learning of the concept more complicated.

Gamification is an effective approach to help students improve their learning curve. At the same time, the psychological and behavioral changes in learning will also pose an impact on learning efficiency. This paper introduces a PI transportation game and designs a set of gamification teaching experiments. In the experiment, a control group and three experimental groups are set up, and the experiment was designed to respond to a plethora of research questions using the methods of T-test, correlation analysis and regression analysis. Experimental results were analyzed through the method of multivariate statistics.

This paper looks for superior pedagogical methods and procedures for students to learn PI while providing suggestions for PI's learning among undergraduates. The authors found (1) gamification teaching will make participants feel more satisfied and master more knowledge points; (2) the scores of logistics testing have been significantly improved after gamification teaching and (3) flow experience has a significant impact on game revenue.

This is the first study about the impact of gamification on teaching and learning PI. The authors apply the methods of T-test, correlation analysis and regression analysis to analyze the collected data. The paper proves that gamification can help students learn PI and that flow experience can improve the efficiency of students learning PI.

This study aims to propose a novel lightweight tendon-driven musculoskeletal arm (LTDM-arm) robot with a flexible series–parallel mixed skeletal joint structure and modularized artificial muscle system (MAMS). The proposed LTDM-arm exhibits human-like flexibility, safety and operational accuracy. In addition, to improve the safety and stability of the LTDM-arm, a control method is proposed to solve local artificial muscle overload accidents.

The proposed LTDM-arm comprises seven degrees of freedom skeletons, 15 MAMSs and various sensor systems (joint sensing, muscle tension sensing, visual sensing, etc.). It retains the morphology of a human skeleton (humerus, ulna and radius) and a simplified muscle configuration. This study proposes an input saturation control with full-state constraints to reduce local artificial muscle overload accidents caused by redundant muscle tension calculations.

3D circular trajectory experiments were conducted to verify the stability of the control method and the flexibility of the LTDM-arm. The results showed that the average error of the muscle length was approximately 0.35 mm (0.38%), which indicates that the proposed control scheme can make the output follow the target trajectory while ensuring constraint satisfaction.

The human arm is capable of performing compliant operations rapidly, flexibly and robustly in unstructured environments. Existing musculoskeletal arm robots lack simulations of the full morphology of the human arm and are insufficient in dexterity. However, the flexibility and safety features of the proposed LTDM-arm were consistent with that of the human arm. Therefore, this study offers a new approach for investigating the advantages of the musculoskeletal system and the concepts of muscle control.

The literature on corporate governance has experienced an explosive growth in the past decade and presented some new trends. One purpose of this paper is to make an exploratory survey of this. Since China is a typically emerging and transition economy, another purpose of this paper is to review some domestic studies with an intention to discover the evolution logic of corporate governance practices in China under a complicated and exclusive context, the third purpose is to provide future research directions.

This paper surveys recent literature in the field of corporate governance, intending to find out the development trends and extract the main line of literature on and practices of Chinese corporate governance.

In this paper, we find that recent literature on corporate governance provides some new insights into subtle characteristics of governance, governance effects of relational network, political connections, corporate governance evaluation and financial institutions governance. During the past decade, the literature on Chinese corporate governance has referred to some new areas during the transition process from administrative governance to economic governance. In addition to the above, we attempt to put forward an analytical framework and the proposition that Chinese corporate governance is in the transition process from administrative governance to economic governance.

The authors propose some research topics where future studies on corporate governance may prove valuable, especially putting forward an analytical framework which can be used for discussing and analyzing corporate governance in China.

This paper reviews some new trends of literature on corporate governance and makes a contribution to corporate governance studies by providing fruitful directions, extracting the main line and analytical framework for China's mode during the transition process from administrative governance to economic governance.

This study aims to improve the muscle model control performance of a tendon-driven musculoskeletal system (TDMS) to overcome disadvantages such as multisegmentation and strong coupling. An adaptive network controller (ANC) with a disturbance observer is established to reduce the modeling error of the musculoskeletal model and improve its antidisturbance ability.

In contrast to other control technologies adopted for musculoskeletal humanoids, which use geometric relationships and antagonist inhibition control, this study develops a method comprising of three parts. (1) First, a simplified musculoskeletal model is constructed based on the Taylor expansion, mean value theorem and Lagrange–d’Alembert principle to complete the decoupling of the muscle model. (2) Next, for this simplified musculoskeletal model, an adaptive neuromuscular controller is designed to acquire the muscle-activation signal and realize stable tracking of the endpoint of the muscle-driven robot relative to the desired trajectory in the TDMS. For the ANC, an adaptive neural network controller with a disturbance observer is used to approximate dynamical uncertainties. (3) Using the Lyapunov method, uniform boundedness of the signals in the closed-loop system is proved. In addition, a tracking experiment is performed to validate the effectiveness of the adaptive neuromuscular controller.

The experimental results reveal that compared with other control technologies, the proposed design techniques can effectively improve control accuracy. Moreover, the proposed controller does not require extensive considerations of the geometric and antagonistic inhibition relationships, and it demonstrates anti-interference ability.

Musculoskeletal robots with humanoid structures have attracted considerable attention from numerous researchers owing to their potential to avoid danger for humans and the environment. The controller based on bio-muscle models has shown great performance in coordinating the redundant internal forces of TDMS. Therefore, adaptive controllers with disturbance observers are designed to improve the immunity of the system and thus directly regulate the internal forces between the bio-muscle models.