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The purpose of this paper is to investigate the hydrolytic stability of several S‐hydroxyethyl N,N‐dialkyl dithiocarbamate‐derived borates SNB1, SNB2, and SNB3, to evaluate their tribological performances used as additives in polyalpha olefins (PAO), and to explore the tribochemical action mechanism.

First, the three additives are synthesized and characterized. Second, the hydrolytic stabilities of the three compounds are investigated. As the third step, they are, respectively, added to PAO and a series of samples with different concentrations of the additives in PAO are prepared, respectively. Their tribological properties are evaluated with two types of four‐ball machines, and then the wear scars were observed using a JSM‐5600LV scanning electron microscope. Finally, the elements on the worn surface are analyzed with a X‐ray photoelectron spectroscope (XPS).

The three novel compounds possess relatively good hydrolytic stabilities, excellent anti‐wear (AW) performances, friction reduction properties, and load‐carrying capacity. There is an optimum concentration of each of the three additives for their AW properties. According to the XPS analytical results, a boundary lubrication protective film has formed during friction consisting of FeSO₄ film, Fe₂O₃ film, and the complicated adsorption film composed of N‐containing organic compounds. In the protective films, a large quantity of compounds containing element B is not found.

The antioxidation performances and the anticorrosion properties are not estimated.

Three novel AW/extreme pressure (EP) additives are synthesized, and may be they have the potential industrial application as AW/EP additives in lubricating oil.

The present work provides a research method of N,S‐containing organic borates as lubricating oil additives.

The purpose of this paper is to understand the effect of base media on the tribological performance and tribochemistry of bismuth thiophosphate additive.

The oil‐water double soluble additive bismuth dithiophosphate was prepared and identified. The contributions of the two base media on the additive tribological behavior and the tribofilm components were comparatively studied.

The extreme pressure (EP) and friction‐reducing properties are remarkably improved with water substituted for paraffin as the base medium. The EP performance of the lubricating media containing this additive mainly results from the tribochemical reaction film on the rubbing surface, not from the viscosity of the base media. In water or paraffin medium, the adsorption process of this additive from the lubricant bulk onto the rubbing surface and the components and the properties of the tribochemical reaction films formed are different, which have important effect on the tribological performance.

The paper mainly focuses on how the water medium with polarity and the liquid paraffin base medium with non‐polarity affect on the tribological performance of the bismuth thiophosphate additive.

The research has found a water‐oil double soluble lubrication additive with outstanding EP and friction‐reducing performance.

The designed experiment provides a new approach to further learn the action mechanism of thiophosphate additive.

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.

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.

This paper aims to present an unmarked method including entire two-dimensional (2D) and three-dimensional (3D) methods to recover absolute 3D humanoid robot poses from multiview images.

The method consists of two separate steps: estimating the 2D poses in multiview images and recovering the 3D poses from the multiview 2D heatmaps. The 2D one is conducted by High-Resolution Net with Epipolar (HRNet-Epipolar), and the Conditional Random Fields Humanoid Robot Pictorial Structure Model (CRF Robot Model) is proposed to recover 3D poses.

The performance of the algorithm is validated by experiments developed on data sets captured by four RGB cameras in Qualisys system. It illustrates that the algorithm has higher Mean Per Joint Position Error than Direct Linear Transformation and Recursive Pictorial Structure Model algorithms when estimating 14 joints of the humanoid robot.

A new unmarked method is proposed for 3D humanoid robot pose estimation. Experimental results show enhanced absolute accuracy, which holds important theoretical significance and application value for humanoid robot pose estimation and motion performance testing.

The authors explicitly evaluate the dynamic impact of five most concerned supply chain disruption scenarios, including: (1) a short-term shortage and price jump of corn supply in hog farms; (2) a shortage of market hogs to packing facilities; (3) disruption in breeding stock adjustments; (4) disruption in pork import; and (5) a combination of scenario (1)–(4).

The agricultural supply chain experienced tremendous disruptions from the COVID-19 pandemic. To evaluate the impact of disruptions, the authors employ a system dynamics model of hog market to simulate and project the impact of COVID-19 on China hog production and pork consumption. In the model the authors explicitly characterize the cyclical pattern of hog market. The hog cycle model is calibrated using market data from 2018–2019 to represent the market situation during an ongoing African swine fever.

The authors find that the impacts of supply chain disruption are generally short-lived. Market hog transportation disruption has immediate impact on price and consumption. But the impact is smoothed out in six months. Delay in import shipment temporarily reduces consumption and raises hog price. A temporary increase of corn price or delay in breeding stock acquisition does not produce significant impact on national hog market as a whole, despite mass media coverage on certain severely affected regions.

This is the first evaluation of short-term supply chain disruption on China hog market from COVID-19. The authors employ a system dynamics model of hog markets with an international trade component. The model allows for monthly time step analysis and projection of the COVID-19 impact over a five-year period. The results and discussion have far-reaching implications for agricultural markets around the world.

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.

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.

This study was designed to investigate how the material properties of the tea-drinking receptacle interact with a participant's motivation and preference for extracting and using information obtained via haptic perception, namely the need for touch (NFT), to influence his or her tea-drinking experience.

72 blindfolded participants were instructed to sample room temperature tea beverages served in a cup that was made of ceramic, glass, paper or plastic. They were then asked to rate how familiar they were with the taste of the beverage, to rate how pleasant the taste was and to specify how much they would like to pay for it (i.e. willingness-to-pay ratings).

The material of the receptacles used to serve the tea exerted a significant influence over the pleasantness ratings of the tea and interacted with the participants' NFT, exerting a significant influence over their willingness to pay for the tea. Specifically, high-NFT participants were willing to pay significantly more for the same cup of tea when it was served in a ceramic cup rather than in a paper cup, whereas the low-NFT participants' willingness to pay for the tea was unaffected by the material of the receptacles.

Our findings suggest that consumers may not be equally susceptible to the influence of the receptacle in which tea, or any other beverage, is served. Our findings also demonstrate how the physical properties of a receptacle interact with a consumer's motivation and preference to influence his or her behavior in the marketplace.