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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.

Audit trail cost management is crucial for ensuring accountability and enhancing quality assurance in construction management. Despite limited practical studies on audit trail management from a cost perspective; this study developed a lifecycle-based audit trail cost management framework. It used synchronized Building Information Modeling (BIM) cost models and Bills of Quantities (BoQs) to address the existing gap.

This study employed a descriptive case study approach of a real-life hospital project in China. Data triangulation was achieved through interviews, observations, documents, and relevant artifacts.

The study identified three key factors contributing to cost variances between BIM cost models and BoQs: differences in measurement rules, model precision, and professional errors, particularly evident during the preliminary estimate stage. Notably, significant cost savings of approximately RMB 5.811 million were achieved during the detailed estimate stage. During the construction phase, a synchronized approach was deployed to improve precise payment verification and modifications to the BIM model. In the post-construction phase, the synchronized as-built BIM models and BoQs served as primary references to facilitate the resolution of operational discrepancies.

The research contributes to the literature by proposing a synchronized approach of BIM cost models and BoQs. This approach enhances traceability and accountability of project information, catering to the digitalization needs of the construction industry.

This study unveils a pragmatic approach to enhancing transparency and accountability in audit-trail cost management by synchronizing BIM cost models and BoQs at various project stages. The synchronized approach offers a promising direction for future research and implementation of audit trail frameworks to enhance cost management in construction.

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.

The purpose of this paper is to develop a propeller performance measurement method for high-altitude platforms by analyzing of the propeller aerodynamic characteristics and application of a mobile testing system.

An experimental approach is adopted for this study. Considering the aerodynamic characteristics of the high-altitude propeller, the similitude of the scaled propeller model in the experiment is analyzed and determined. Then, the experimental method and procedure to obtain the propeller’s performance under different altitudes are presented, and the structure of hardware and software and the key techniques of the testing system are introduced in detail.

The applicability and effectiveness of the testing system is verified through comparison between experimental and numerical results. In addition, the performance of the 6.8-m propeller for a high-altitude airship is tested, which proves that the high-altitude propeller can meet the requirements of the propulsion system.

The testing methodology and the mobile testing system could be applied to aerodynamic performance evaluation of the high-altitude propellers under different altitudes.

This testing approach exhibits significant time and cost benefits over many other experimental methods to obtain the performance of the high-altitude propellers, which is important in the preliminary design of the propulsion system for high-altitude platforms.

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.

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.

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.

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.