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This study aims to propose a series of numerical and surrogate models to investigate the aerodynamic pressure inside cracks in high-speed railway tunnel linings and to predict the stress intensity factors (SIFs) at the crack tip.

A computational fluid dynamics (CFD) model is used to calculate the aerodynamic pressure exerted on two cracked surfaces. The simulation uses the viscous unsteady κ-ε turbulence model. Using this CFD model, the spatial and temporal distribution of aerodynamic pressure inside longitudinal, oblique and circumferential cracks are analyzed. The mechanism behind the pressure variation in tunnel lining cracks is revealed by the air density field. Furthermore, a response surface model (RSM) is proposed to predict the maximum SIF at the crack tip of circumferential cracks and analyze its influential parameters.

The initial compression wave amplifies and oscillates in cracks in tunnel linings, resulting from an increase in air density at the crack front. The maximum pressure in the circumferential crack is 2.27 and 1.76 times higher than that in the longitudinal and oblique cracks, respectively. The RSM accurately predicts the SIF at the crack tip of circumferential cracks. The SIF at the crack tip is most affected by variations in train velocities, followed by the depth and length of the cracks.

The mechanism behind the variation of aerodynamic pressure in tunnel lining cracks is revealed. In addition, a reliable surrogate model is proposed to predict the mechanical response of the crack tip under aerodynamic pressures.

This paper aims to explore the effects of normative and hedonic motivations on continuous knowledge contribution, and how past contribution experience moderates the effects of the motivations on continuous knowledge contribution.

Based on goal-framing theory, the present study proposes a comprehensive theoretical model by integrating normative and hedonic motivations, past contribution experience and continuous knowledge contribution. The data for virtual community members' activities were collected using the Python Scrapy crawler. Logit regression was used to validate the integrative model.

The results show that both normative motivation (reflected by generalized reciprocity and social learning) and hedonic motivation (reflected by peer recognition and online attractiveness) are positively associated with continuous knowledge contribution. Moreover, these effects are found to be significantly influenced by members' past knowledge contribution experience. Specifically, the results suggest that past knowledge contribution experience undermines the influence of generalized reciprocity on continuous knowledge contribution but strengthens the effect of peer recognition and online attractiveness.

Although the emerging literature on continuous knowledge contribution mainly focuses on motivations as antecedents that promote continuous knowledge contribution, most of these studies assume that the relationship between motivating mechanisms and continuous knowledge contribution does not change over time. The study is one of the initial studies to examine whether and how the influence of multiple motivations evolves relative to levels of past contribution experience.

This research aims to investigate the impact of the collaborative governance mechanism on the implementation of rural governance information systems in developing countries. By integrating institutional logic theory, affordance theory and social identity theory, the authors propose modeling grassroots officials' affordance perception process and exploring the importance of multi-identities’ information technology (IT) goals in affordance perception.

Through an exploratory case study, the authors identified three affordances of rural governance information systems and investigated the mechanisms influencing the perception of these affordances among grassroots officials. Next, the authors established a research model and collected 490 valid questionnaires from grassroots officials in China and analyzed the data using structural equation modeling (SEM).

The authors' study challenges previous assumptions by integrating institutional logic, affordance and social identity theories. The authors establish a perceived affordance path for rural governance information systems, recognize substitute effects among technological affordances and extend the theory to explain social factors influencing IT perception. The authors' findings suggest providing technical training for grassroots officials to enhance IT capabilities, and governments should prioritize essential functionalities in rural governance information systems to optimize resources. Training on collaborative governance mechanisms can improve IT affordance perception, enhancing digital platform utilization in governance processes.

The study was conducted mainly in China, and therefore, the findings may not be universal to other developing countries. Researchers are therefore encouraged to test the proposal in locations with different rural cultures.

The paper includes implications for the development of IT perception in rural governance, the development of affordance perception theory and studying the relationship between IT goals and affordance perception.

Overall, this paper addresses the need to understand how grassroots officials perceive IT affordances in rural governance and study the relationship between multi-identities’ goals and affordance perception.

The purpose of this paper is to design a multi-sensory anthropomorphic prosthetic hand and a grasping controller that can detect the slip and automatically adjust the grasping force to prevent the slip.

To improve the dexterity, sensing, controllability and practicability of a prosthetic hand, a modular and multi-sensory prosthetic hand was presented. In addition, a slip prevention control based on the tactile feedback was proposed to improve the grasp stability. The proposed controller identifies slippages through detecting the high-frequency vibration signal at the sliding surface in real time and the discrete wavelet transform (DWT) was used to extract the eigenvalues to identify slippages. Once the slip is detected, a direct-feedback method of adjusting the grasp force related with the sliding times was used to prevent it. Furthermore, the stiffness of different objects was estimated and used to improve the grasp force control. The performances of the stiffness estimation, slip detection and slip control are experimentally evaluated.

It was found from the experiment of stiffness estimation that the accuracy rate of identification of the hard metal bottle could reach to 90%, while the accuracy rate of identification of the plastic bottles could reach to 80%. There was a small misjudgment rate in the identification of hard and soft plastic bottles. The stiffness of soft plastic bottles, hard plastic bottles and metal bottles were 0.64 N/mm, 1.36 N/mm and 32.55 N/mm, respectively. The results of slip detection and control show that the proposed prosthetic hand with a slip prevention controller can fast and effectively detect and prevent the slip for different disturbances, which has a certain application prospect.

Due to the small size, low weight, high integration and modularity, the prosthetic hand is easily applied to upper-limb amputees. Meanwhile, the method of the slip prevention control can be used for upper-limb amputees to complete more tasks stably in daily lives.

A multi-sensory anthropomorphic prosthetic hand is designed, and a method of stable grasps control based on slip detection by a tactile sensor on the fingertip is proposed. The method combines the stiffness estimation of the object and the real-time slip detection based on DWT with the design of the proportion differentiation robust controller based on a disturbance observer and the force controller to achieve slip prevention and stable grasps. It is verified effectively by the experiments and is easy to be applied to commercial prostheses.

For privacy protection, federated learning based on data separation allows machine learning models to be trained on remote devices or in isolated data devices. However, due to the limited resources such as bandwidth and power of local devices, communication in federated learning can be much slower than in local computing. This study aims to improve communication efficiency by reducing the number of communication rounds and the size of information transmitted in each round.

This paper allows each user node to perform multiple local trainings, then upload the local model parameters to a central server. The central server updates the global model parameters by weighted averaging the parameter information. Based on this aggregation, user nodes first cluster the parameter information to be uploaded and then replace each value with the mean value of its cluster. Considering the asymmetry of the federated learning framework, adaptively select the optimal number of clusters required to compress the model information.

While maintaining the loss convergence rate similar to that of federated averaging, the test accuracy did not decrease significantly.

By compressing uplink traffic, the work can improve communication efficiency on dynamic networks with limited resources.

The purpose of this work is to bridge FL and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. FL is an emerging collaborative machine learning technique that trains a model across multiple devices or servers holding private data samples without exchanging their data. The locally trained results are aggregated by a centralized server in a privacy-preserving way. However, there is an assumption where the centralized server is trustworthy, which is impractical. Fortunately, blockchain technology has opened a new era of data exchange among trustless strangers because of its decentralized architecture and cryptography-supported techniques.

In this study, the author proposes a novel design of a smart agent inspired by the smart contract concept. Specifically, based on the proposed smart agent, a fully decentralized, privacy-preserving and fair deep learning blockchain-FL framework is designed, where the agent network is consistent with the blockchain network and each smart agent is a participant in the FL task. During the whole training process, both the data and the model are not at the risk of leakage.

A demonstration of the proposed architecture is designed to train a neural network. Finally, the implementation of the proposed architecture is conducted in the Ethereum development, showing the effectiveness and applicability of the design.

The author aims to investigate the feasibility and practicality of linking the three areas together, namely, multi-agent system, FL and blockchain. A blockchain-FL framework, which is based on a smart agent system, has been proposed. The author has made several contributions to the state-of-the-art. First of all, a concrete design of a smart agent model is proposed, inspired by the smart contract concept in blockchain. The smart agent is autonomous and is able to disseminate, verify the information and execute the supported protocols. Based on the proposed smart agent model, a new architecture composed by these agents is formed, which is a blockchain network. Then, a fully decentralized, privacy-preserving and smart agent blockchain-FL framework has been proposed, where a smart agent acts as both a peer in a blockchain network and a participant in a FL task at the same time. Finally, a demonstration to train an artificial neural network is implemented to prove the effectiveness of the proposed framework.

Considering the industrial site environment and installation requirements, the straight-beam ultrasound probe with easy installation and good coupling agent adaptability is adopted to replace the traditional water immersion focusing probe for film thickness measurement in cylindrical roller bearings. The straight-beam probe has a large echo receiving range, which will result in measurement regions overlapping and bring about large measurement errors. In this paper, an improved measurement method for film thickness of cylindrical roller bearing with the straight-beam probe is developed.

An improved method is proposed to enhance the spatial resolution of the straight-beam probe. By introducing a correction coefficient based on the percentage of the effective measurement area, the method improves the measuring accuracy successfully.

The experimental results demonstrate that the lubricant-film thickness can be measured to reasonable accuracy by this method and have a better agreement with the theoretical film thickness solutions.

This paper used analytical method and model that is helpful for the improvement of the spatial resolution, which has great influence on the measuring accuracy, is mainly determined by the echo reflection area size of the ultrasound transducer.

The purpose of this study is to reveal the underlying mechanism in film formation of oil-in-water (O/W) emulsion.

This study focuses on the film forming characteristics of O/W emulsion between the surface of a steel ball and a glass disc coated with chromium. The lubricant film thicknesses of O/W emulsion with various mechanical stirring strength were discussed, which were observed by technique of relative optical interference intensity.

The authors directly observed the oil pool in the contact area, finding the size of oil pool was closely related to the film-forming ability of emulsion. Enrichment phenomenon occurs in oil pool, which was caused by phase inversion. Further investigations revealed that the emulsion is stable with strong stirring strength, resulting in a smaller oil pool size and worse film forming ability.

With the wide usage of O/W emulsion in both biological and industrial systems, the ability of emulsion film formation is considered as an important factor to evaluate the lubrication effectiveness.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2022-0354/

The purpose of this paper is to estimate the real urbanization level in China so as to provide a measurement that can be compared with the international level.

Taking into consideration 300m residents living in the administrative towns (300m residents here are referred to the population in administrative towns, including those in all counties), the gap between the urbanization rate of China and that of the world average becomes much wider.

China, however, implements the administrative system of government at the central, provincial, municipal, county and township levels. By city, it means the jurisdiction at and above the level of county, which includes the municipality directly under the central government, prefecture-level municipal and county. By town, it means the jurisdiction below the level of county (including the Chengguan Town, or capital town, where the county government is located) and exclusive of rural townships.

China has witnessed rapid development for 40 years since the reform and opening up in 1978. Nowadays, China has already stepped into the period of post-industrialization, with its urbanization rate (UR) of permanent population reaching 58.58 percent. However, on the basis of registered population, the UR is 43.37 percent, which is not only far below the average level of 81.3 percent in high-income countries, but also lower than the average of 65.8 percent in upper middle-income countries which are comparable to China in terms of per capita income. (The classification of state income level is based on the data of national income per capita and division standards in 2016 from the World Bank, in which annual revenue per capita in high-income countries reaches over US$12,736 and that in upper middle-income countries between US$4,126 and US$12,735.)

To reconcile the mixed findings on commitment-oriented human resource management (HRM) on employee job performance, this study tests whether commitment-oriented HRM has a threshold effect on employee job performance and when this threshold effect matters. The authors further tested the role of employees' age in the relationships.

The authors conducted a survey and collected data from 601 employees in 32 firms in China, and used a multilevel approach to test the hypothesis.

The results showed that the association between commitment-oriented HRM and employee job performance was J-shaped, meaning that commitment-oriented HRM was positively related to job performance when the degree of commitment-oriented HRM exceeded a threshold. Moreover, the authors found that employee age moderated this J-shape relationship. Specifically, the curvilinear relationship between development commitment-oriented HRM and job performance was stronger in younger employees. Contrary to our prediction, the results showed that younger employees reacted more strongly to improve job performance than older employees when maintenance commitment-oriented HRM exceeded a moderate degree.

The findings on the J-shape effect and moderating role of employee age on the J-shape provided critical insights into understanding the mixed results of the effect of HRM. Additionally, this study provided new insight in the linkage between HRM practices and employee outcomes.