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This study aims to the complex and unpredictable terrain environment of the Qinghai-Tibet Plateau scientific research station, such as cement road, wetland, gravel desert, snowfield, ice surface, grassland, slimy ground, steep slope, step, etc., a reconfigurable walking mechanism based on two movement modes of wheel and triangular crawler was proposed.

By analyzing the deformation mechanism of the walking mechanism, a reconfigurable wheel-crawler-integrated walking mechanism and the configuration scheme are designed. The analysis of the kinematics and mechanical properties of the swing arm system and the deformation mechanism of the walking mechanism.

The reconfigurable wheel-crawler-integrated walking mechanism can be switched between the wheel and triangular crawler modes by driving the deformation mechanism. Through the numerical simulation of its movement process, and the trial production and experiment of the prototype, indicates the validity of the reconfigurable wheel-crawler-integrated walking mechanism design.

The work of this paper provides a reconfigurable wheel-crawler-integrated-walking mechanism, which can be used by robots in the Qinghai-Tibet Plateau scientific research station. It has excellent reconfigurability and can effectively improve the robot’s adaptability to complex terrain.

According to Yubin et al. (2023), films serve as a medium for conveying visual representations of various elements such as landscapes, buildings, landmarks and monuments, which provide a contextual backdrop for the narrative. According to Vila et al. (2021), the number of global tourists visiting film locations exceeds 80 million. In addition, according to Yubin et al. (2023), the promotion of tourism is facilitated through the utilisation of films, which serve to create novel representations, counteract negative perceptions and enhance the portrayal of underdeveloped destinations. A significant number of individuals engage in the practise of visiting movie sets with the intention of re-experiencing the emotional impact of the film. The devaluation of film marketing has been observed. This method represents a highly indirect approach to enticing tourists. This chapter examines the comprehension of travellers' motivations and the perception of film-exposed locations in Bollywood films (Salnick, 2023). Film tourism provides a tailored and personalised experience for individuals. The difficulty in measuring this concept arises from factors such as the emotional responsiveness, personality traits, background and interpretive abilities of the viewers in relation to media images. According to Castro et al. (2023), the inclusion of a destination on a screen can serve as a means to enhance the diversity of a site's tourist offerings or mitigate the effects of seasonality by providing opportunities for experiential activities, showcasing notable landmarks or serving as a filming location. Film destinations have the potential to gain popularity and benefit from advertising and the perception of spectators.

Abundant studies of outpatient visits apply traditional recurrent neural network (RNN) approaches; more recent methods, such as the deep long short-term memory (DLSTM) model, have yet to be implemented in efforts to forecast key hospital data. Therefore, the current study aims to reports on an application of the DLSTM model to forecast multiple streams of healthcare data.

As the most advanced machine learning (ML) method, static and dynamic DLSTM models aim to forecast time-series data, such as daily patient visits. With a comparative analysis conducted in a high-level, urban Chinese hospital, this study tests the proposed DLSTM model against several widely used time-series analyses as reference models.

The empirical results show that the static DLSTM approach outperforms seasonal autoregressive integrated moving averages (SARIMA), single and multiple RNN, deep gated recurrent units (DGRU), traditional long short-term memory (LSTM) and dynamic DLSTM, with smaller mean absolute, root mean square, mean absolute percentage and root mean square percentage errors (RMSPE). In particular, static DLSTM outperforms all other models for predicting daily patient visits, the number of daily medical examinations and prescriptions.

With these results, hospitals can achieve more precise predictions of outpatient visits, medical examinations and prescriptions, which can inform hospitals' construction plans and increase the efficiency with which the hospitals manage relevant information.

To address a persistent gap in smart hospital and ML literature, this study offers evidence of the best forecasting models with a comparative analysis. The study extends predictive methods for forecasting patient visits, medical examinations and prescriptions and advances insights into smart hospitals by testing a state-of-the-art, deep learning neural network method.

In the process of Renminbi (RMB) internationalization, the heterogeneity and complexity in knowledge under the multicultural contexts have been considered as important factors that can have profound impacts on the cross-border flow of the RMB currency. Moreover, COVID-19, an exogenous shock, also triggers more in-depth reflection on the relationship between cross-border knowledge management and the financial risk governance. In addition, the needs to effectively respond to global risks and crises prompt the necessity in systematically establishing an effective cross-border knowledge management mechanism and innovatively solidifying the knowledge bases needed for the further internationalization of the RMB.

Based on the analysis on the current status of the RMB internationalization, this paper qualitatively explores some major challenges and difficulties encountered in the process of RMB internationalization from the perspectives of knowledge management and cross-cultural theories. To effectively mitigate these challenges and difficulties, discussions and recommendations centered on three main aspects: cross-cultural management; cognition; and innovation for the further development of the RMB internationalization are also presented in this paper.

Based on the analysis on the cross-border knowledge management and cross-cultural perspectives, this paper identifies three major challenges and difficulties that the RMB internationalization is encountering, including: cultural heterogeneity and its adverse impacts on the communication amongst economic entities; the existence of knowledge iceberg; and the difficulty it presents to cognition and financial innovation. Meanwhile, the authors also present recommendations on the development of the cross-border knowledge management mechanism for furthering the progress of internationalizing the RMB currency.

From the perspective of cross-border knowledge management, this study not only elaborates on the recommendations aimed at further promoting the RMB internationalization but also provides reference and guidance for the state, central banks and commercial banks to play better roles in furthering the RMB internationalization.

This paper creatively integrates the micro knowledge management into the macro process of RMB internationalization, thoroughly discusses two main challenges and difficulties encountered in the process of RMB internationalization from the unique perspective of cross-border knowledge management under the multicultural contexts and provides relevant recommendations for RMB’s further internationalization. This study also enriches the exploration of knowledge management outcome variables and further expands the research field of knowledge management.

The purpose of this paper is to examine whether China is still a passive price taker from the US soybean futures, or instead domestic futures market has developed certain degrees of pricing power through time. The finding helps to identify the importance of China soybean futures in the perspective of portfolio selection for international futures traders. If China soybean futures market is no longer a price taker after the subprime crisis, traders need to include it as a separate category in their portfolio.

This paper uses exponential generalized autoregressive conditional heteroskedasticity-generalized error distribution (EGARCH-GED) and generalized autoregressive conditional heteroskedasticity-generalized error distribution (GARCH-GED) models to test spillover effects between Dalian Commodity Exchange (DCE) and Chicago Board of Trade (CBOT) soybean futures. The authors divide daily samples into three subperiods based on the subprime crisis. Three research questions – whether China is still the price taker, the importance of Chinese soybean futures in international futures portfolio selection, and the influences of subprime crisis on soybean futures volatility relationship – are examined by comparing estimation results through time and different contracts.

The spillover effect from CBOT soybean futures to DCE No. 1 soybean futures becomes weaker through time. China is no longer a soybean futures price taker after the subprime crisis. The authors also find the shocks of bearish news on DCE soybeans are greater than those of bullish news. Potential volatility of DCE in long positions is bigger than that in short positions.

China is the largest soybean importer. DCE is a very important futures market for non-genetically modified soybeans. It is necessary for both international and domestic futures traders to understand the changes in international soybean futures price relationship and take corresponding strategies. It is also important for market to realize that DCE soybean futures are to a less degree price taker after the subprime crisis.

The paper applies EGARCH-GED and GARCH-GED models to identify changes in spillover effects before, during, and after the subprime crisis. Different from other studies, this paper finds after the subprime crisis, China is no longer the soybean futures price taker. This paper also compares the spillover effects of non-genetically modified soybean futures (No. 1 soybean futures) with genetically modified soybean futures (No. 2 soybean futures).

This article examines the impact of different policy instruments on livestock farmers' willingness to recycle manure. The results shed light on the optimal policy combination.

A game theoretical framework is constructed to illustrate farmers' optimal strategies under different policies. Theoretical results are empirically tested by survey data from beef cattle farmers in Central China.

Empirical results show that penalties work better than subsidies if each type of policy is implemented separately. The authors also find a positive interaction between subsidy and penalty policies, suggesting that a combination of subsidy and penalty policies produces the best outcome in incentivizing livestock farmers to recycle manure. Furthermore, planting and breeding simultaneously have the strongest effect on increasing livestock farmers' willingness to recycle manure, suggesting that the combination of planting and breeding can be an optimal strategy for manure management.

This study is based on firsthand survey data and provides new evidence on the effectiveness of alternative environmental policies on manure recycling.

Considering the small sample size and non-linear characteristics of historical energy consumption data from certain provinces in Southwest China, the authors propose a hybrid accumulation operator and a hybrid accumulation grey univariate model as a more accurate and reliable methodology for forecasting energy consumption. This method can provide valuable decision-making support for policy makers involved in energy management and planning.

The hybrid accumulation operator is proposed by linearly combining the fractional-order accumulation operator and the new information priority accumulation. The new operator is then used to build a new grey system model, named the hybrid accumulation grey model (HAGM). An optimization algorithm based on the JAYA optimizer is then designed to solve the non-linear parameters θ, r, and γ of the proposed model. Four different types of curves are used to verify the prediction performance of the model for data series with completely different trends. Finally, the prediction performance of the model is applied to forecast the total energy consumption of Southwest Provinces in China using the real world data sets from 2010 to 2020.

The proposed HAGM is a general formulation of existing grey system models, including the fractional-order accumulation and new information priority accumulation. Results from the validation cases and real-world cases on forecasting the total energy consumption of Southwest Provinces in China illustrate that the proposed model outperforms the other seven models based on different modelling methods.

The HAGM is used to forecast the total energy consumption of the Southwest Provinces of China from 2010 to 2020. The results indicate that the HAGM with HA has higher prediction accuracy and broader applicability than the seven comparative models, demonstrating its potential for use in the energy field.

The HAGM(1,1) is used to predict energy consumption of Southwest Provinces in China with the raw data from 2010 to 2020. The HAGM(1,1) with HA has higher prediction accuracy and wider applicability compared with some existing models, implying its high potential to be used in energy field.

Theoretically, this paper presents, for the first time, a hybrid accumulation grey univariate model based on a new hybrid accumulation operator. In terms of application, this work provides a new method for accurate forecasting of the total energy consumption for southwest provinces in China.

The purpose of this paper is to study the influences of recess configurations on the performances of high-speed hybrid journal bearing. Hybrid journal bearing earns increasing attention in high-speed machine tool spindle owing to its intrinsic outstanding performances of low temperature rise and high stability.

To investigate the coupled effects of temperature, turbulence and the interaction between lubricant and journal/bearing bush, a thermal fluid-structure interaction approach is presented and validated by the experimental results.

Ladder-type recess has excellent tribological characteristics in decreasing temperature rise, improving stability and inhibiting cavitation, which are all beneficial to improve the performances of high-speed spindle system.

This work can be a valuable guide for the future high-speed hybrid journal bearing design.

Existing research has examined the results of women’s political leadership participation (WPLP) and the reasons for the lack of advancement of women to management positions. However, little research has been adopting a more comprehensive framework and configuration perspective to investigate the determinants of WPLP. By integrating institutional theory and institutional complementarities theory, this study aims to construct an institution–culture–structure framework to investigate the multiple driving mechanisms of WPLP.

Drawing on the fuzzy set qualitative comparative analysis method and a sample of 66 countries, the authors identify multiple equifinal combinations of conditions related to high and not-high levels of WPLP.

According to the results, the authors summarize five pathways influencing WPLP. These pathways include education and culture-driven pattern, political institutions-driven pattern, political institutions and structure-driven pattern, integrated-driven pattern and political institutions and culture restrictive pattern.

The authors shed new light on the driving mechanism of WPLP and contribute to research on making full out of women’s leadership.