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The purpose of this paper is to design a climbing robot connected by a connecting rod mechanism to achieve multi-functional tasks such as obstacles crossing and climbing of power transmission towers.

A connecting rod type gripper has been designed to achieve stable grasping of angle steel. Before grasping, use coordination between structures to achieve stable docking and grasping. By using the alternating movements of two claws and the middle climbing mechanism, the climbing and obstacle crossing of the angle steel were achieved.

Through a simple linkage mechanism, a climbing robot has been designed, greatly reducing the overall mass of the robot. It can also carry a load of 1 kg, and the climbing mechanism can perform stable climbing. The maximum step distance of the climbing robot is 543 mm, which can achieve the crossing of angle steel obstacles.

A transmission tower climbing mechanism was proposed by analyzing the working environment. Through the locking ability of the screw nut, stable clamping of the angle steel is achieved, and a pitch mechanism is designed to adjust the posture of the hand claw.

The purpose of the paper is to examine observed differences in China's ethnic majority and minority patterns of labor force participation and to decompose these differences into treatment and endowment effects.

Data from the three most recent population censuses of China are employed to explore differences in the labor force participation rates of a number of China's important ethnic groups. Gender‐separated urban labor force participation rates are estimated using logit regressions, controlling for educational attainment, marital status, pre‐school and school‐age children, household size, age, and measures of local economic conditions. The focus is on the experience of six minority groups (Hui, Koreans, Manchu, Mongolians, Uygurs, and Zhuang) in comparison to the majority Han. The technique developed by Borooah and Iyer is adopted to decompose the differences in labor force participation rates between pairs of ethnic groups into treatment and endowment effects.

Sizeable differences are found between the labor force participation rates of prime‐age urban women of particular ethnic groups and the majority Han. Men's participation rates are very high (above 95 percent) and exhibit little difference between Han and ethnic minorities. For almost all pairwise comparisons between Han and ethnic women, it is found that differences in coefficients account for more than 100 percent of the Han‐ethnic difference in labor force participation. Differences in endowments often have substantial effects in reducing this positive Han margin in labor force participation. Roughly speaking, treatment of women's characteristics, whether in the market or socially, tend to increase the Han advantage in labor force participation. The levels of these characteristics on average tend to reduce this Han advantage.

The paper analyses only one aspect of the economic status of China's ethnic minorities – labor force participation. It would be useful also to examine income, educational attainment, occupational attainment, and unemployment.

This paper contributes to and expands the scant literature on ethnicity in China's economic transition.

The purpose of this paper is to analyze the effects of public investment in agricultural R&D and extension on broadacre farming productivity in Australia.

An autoregressive integrated moving average (ARIMA) regression model is applied to estimate the effects of public investment in agricultural R&D and extension on Australian braodacre productivity.

The study reveals that public investment in agricultural R&D and extension has contributed almost two-thirds of average annual broadacre productivity growth between 1952-1953 and 2006-2007, the average internal rate of return to public investment in agricultural R&D and extension was 28.4 and 47.5 per cent a year, respectively, and overseas spill-ins is an important source of domestic agricultural productivity growth.

Policy implications: the findings suggest that increasing public investment in agricultural R&D and extension and maintaining agricultural R&D policy stability are equally important to have a sustained long-term agricultural productivity growth, and maintaining an open trade and investment regime is important to benefit from foreign knowledge spillovers which is especially important for developing countries.

This paper contributes to the existing literature by employing more sophisticated econometric techniques with an extended data set for the period from 1952-1953 to 2006-2007. The study separates the contribution of public R&D investment and the extension investment, and also takes into account the contribution of overseas public investment on the TFP growth in the Australian broadacre sector.

The minimum wage has been regarded as an important element of public policy for reducing poverty and inequality. Increasing the minimum wage is supposed to raise earnings for millions of low-wage workers and therefore lower earnings inequality. However, there is no consensus in the existing literature from industrialized countries regarding whether increasing the minimum wage has helped lower earnings inequality. China has recently exhibited rapid economic growth and widening earnings inequality. Since China promulgated new minimum wage regulations in 2004, the magnitude and frequency of changes in the minimum wage have been substantial, both over time and across jurisdictions. The growing importance of research on the relationship between the minimum wage and earnings inequality and its controversial nature have sparked heated debate in China, highlighting the importance of rigorous research to inform evidence-based policy making. We investigate the contribution of the minimum wage to the well-documented rise in earnings inequality in China from 2004 to 2009 by using city-level minimum wage panel data and a representative Chinese household survey, and we find that increasing the minimum wage reduces inequality – by decreasing the earnings gap between the median and the bottom decile – over the analysis period.

In order to unravel the evolution of microstructure characteristics and the change of mechanical properties of bituminous mixture in the freezing and thawing environment in cold region, this study starts from macroscopic experiments and analyzes the changes in mechanical properties of asphalt mixtures before and after freezing and thawing in detail. On this basis, the displacement of key particles in the structure of asphalt mixture under the action of external forces (before and after freezing and thawing) is simulated through the combination macroscopic and microscopic methods.

The climate in China exhibits high complexity and diversity, divided into five zones based on the temperature difference from south to north. Considering that the significant effect of geography and natural climate on the design, construction and maintenance of asphalt pavement, the criterion for the road construction at different areas should be highly different.

The results show that the mechanical properties of asphalt mixture greatly decrease due to the influence of freeze-thaw, and the displacement of key particles in the structure of asphalt mixture (several representative particle sizes were selected through experiments) is obviously observed because of the action of external force. By analyzing the variation of several key particle sizes after freezing-thawing cycle, the gradation standard of asphalt mixture aggregate suitable for cold area was obtained. The research results have certain theoretical and practical value for the design and application of asphalt mixture in cold area.

The results show that the mechanical properties of asphalt mixture greatly decrease due to the influence of freeze-thaw, and the displacement of key particles in the structure of asphalt mixture (several representative particle sizes were selected through experiments) is obviously observed because of the action of external force. By analyzing the variation of several key particle sizes after freezing-thawing cycle, the gradation standard of asphalt mixture aggregate suitable for cold area was obtained. The research results have certain theoretical and practical value for the design and application of asphalt mixture in cold area.

Taking the COVID-19 as the background, this study aims to investigate the direct influencing factors regarding knowledge sharing behavior (KSB) on new media platforms and discuss how the characteristics of the users could enhance the KSB through moderation effect, and provide empirical evidences.

Based on the social exchange theory and after the text analysis of the data collected from the Tiktok platform in 2020, this paper uses the quantitative method to evaluate the factors influence KSB on short video social platform during the COVID-19 outbreak.

KSB on new media platform could be enhanced by richer knowledge content of the video posted and the attribute of the platform users directly. Platform users could affect the trustworthiness of the knowledge shared, thus influence the knowledge sharing. On the early stage of the COVID-19, the richer content of the knowledge released by users could effectively enhance the KSB. On the early stage of the emergency events, the official users could play a significant role on KS. During the mitigation stage of COVID-19, the KSB of the knowledge shared by unofficial users with richer content could be enhanced and the moderation effect is relatively stronger.

The research extends the social exchange theory to a disaster management context. The authors provide an effective reference for future governments to effectively cope with the epidemic and spread public knowledge in an emergency response context. By analyzing the influence of knowledge content and influencer characteristics, it could help the social media platform to improve content management and optimize resource allocation.

Traditional case-adaptation methods have poor accuracy, low efficiency and limited applicability, which cannot meet the needs of knowledge users. To address the shortcomings of the existing research in the industry, this paper proposes a case-adaptation optimization algorithm to support the effective application of tacit knowledge resources.

The attribute simplification algorithm based on the forward search strategy in the neighborhood decision information system is implemented to realize the vertical dimensionality reduction of the case base, and the fuzzy C-mean (FCM) clustering algorithm based on the simulated annealing genetic algorithm (SAGA) is implemented to compress the case base horizontally with multiple decision classes. Then, the subspace K-nearest neighbors (KNN) algorithm is used to induce the decision rules for the set of adapted cases to complete the optimization of the adaptation model.

The findings suggest the rapid enrichment of data, information and tacit knowledge in the field of practice has led to low efficiency and low utilization of knowledge dissemination, and this algorithm can effectively alleviate the problems of users falling into “knowledge disorientation” in the era of the knowledge economy.

This study provides a model with case knowledge that meets users’ needs, thereby effectively improving the application of the tacit knowledge in the explicit case base and the problem-solving efficiency of knowledge users.

The adaptation model can serve as a stable and efficient prediction model to make predictions for the effects of the many logistics and e-commerce enterprises' plans.

This study designs a multi-decision class case-adaptation optimization study based on forward attribute selection strategy-neighborhood rough sets (FASS-NRS) and simulated annealing genetic algorithm-fuzzy C-means (SAGA-FCM) for tacit knowledgeable exogenous cases. By effectively organizing and adjusting tacit knowledge resources, knowledge service organizations can maintain their competitive advantages. The algorithm models established in this study develop theoretical directions for a multi-decision class case-adaptation optimization study of tacit knowledge.

Continuous knowledge contribution behaviors (CKCB) are critical for the healthy development of online medical communities (OMCs). However, it is unclear that if and how contributors' prior actions and the responses they received from the community influence the nature of their future contributions. Drawing upon the Information Systems Continuance theory and Service Feedback theory, the purpose of the study is to examine the impact of knowledge contribution performance (KCP) on doctors' CKCB. Evaluation of social motivation, financial incentive and the moderating influence of expertise level (EL) provided further insight into the pathways that motivate various forms of CKCB.

In order to better understand the CKCB of physicians in OMCs, the authors divided it into two categories: A_CKCB (active CKCB) and P_CKCB (passive CKCB). Information Systems Continuance theory and Service Feedback theory are adapted and integrated with empirical findings from previous research on OMCs to develop a model of CKCB. This study used ordinary least squares (OLS) regression to test hypotheses in the preexisting research model based on data collected from a Chinese OMC platform.

The results show that KCP helps develop several facets of CKCB. According to the findings, doctors' CKCB improved dramatically after receiving feedback from A_CKCB and P_CKCB, but feedback from peers did not promote CKCB. This study found that financial rewards only have a significant positive effect on P_CKCB, and that the level of expertise has a negative effect on the effect. The findings also demonstrated that doctors' level of expertise moderates the relationship between fA_CKCB (a comprehensive evaluation of doctors' A_CKCB) and A_CKCB.

Future studies should look at the role of self-efficacy as a mediator and attitudes as a moderator in the link between KCP and various forms of CKCB. This will help authors figure out how important KCP is for physicians' CKCB. And future research should use more than one way to gather data to prove the above roles.

This study makes a significant contribution to understanding the association between CKCB and KCP by highlighting the significance of distinguishing between the various forms of CKCB and their underlying causes.

This research has advanced both the theory and practice of OMCs' user management by illuminating the central role of KCP in this context.

The purpose of this study is to investigate the application of non-destructive testing methods in measuring bearing oil film thickness to ensure that bearings are in a normal lubrication state. The oil film thickness is a crucial parameter reflecting the lubrication status of bearings, directly influencing the operational state of bearing transmission systems. However, it is challenging to accurately measure the oil film thickness under traditional disassembly conditions due to factors such as bearing structure and working conditions. Therefore, there is an urgent need for a nondestructive testing method to measure the oil film thickness and its status.

This paper introduces methods for optically, electrically and acoustically measuring the oil film thickness and status of bearings. It discusses the adaptability and measurement accuracy of different bearing oil film measurement methods and the impact of varying measurement conditions on accuracy. In addition, it compares the application scenarios of other techniques and the influence of the environment on detection results.

Ultrasonic measurement stands out due to its widespread adaptability, making it suitable for oil film thickness detection in various states and monitoring continuous changes in oil film thickness. Different methods can be selected depending on the measurement environment to compensate for measurement accuracy and enhance detection effectiveness.

This paper reviews the basic principles and latest applications of optical, electrical and acoustic measurement of oil film thickness and status. It analyzes applicable measurement methods for oil film under different conditions. It discusses the future trends of detection methods, providing possible solutions for bearing oil film thickness detection in complex engineering environments.

This paper aims to correct the existing mixed integer programming (MIP) model proposed by Yadav et al. (2019) [“Bi-objective optimization for sustainable supply chain network design in omnichannel.”, Journal of Manufacturing Technology Management, Vol. 30 No. 6, pp. 972–986].

This paper first presents a counterexample to show that the existing MIP model is incorrect and then proposes an improved mixed integer linear programming (MILP) model for the considered problem. Last, a numerical experiment is conducted to test our improved MILP model.

This paper demonstrates that the formulations of the facility capacity constraints and the product flow balance constraints in the existing MIP model are incorrect and incomplete. Due to this reason, infeasible solutions could be identified as feasible ones by the existing MIP model. Hence, the optimal solution obtained with the existing MIP model could be infeasible. A counter-example is used to verify our observations. Computational results verify the effectiveness of our improved MILP model.

This paper gives a complete and correct formulation of the facility capacity constraints and the product flow balance constraints, and conducts other improvements on the existing MIP model. The improved MILP model can be easily implemented and would help companies to have more effective distribution networks under the omnichannel environment.