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Robotic arms play a crucial role in various industrial operations, such as sorting, assembly, handling and spraying. However, traditional robotic arm control algorithms often struggle to adapt when faced with the challenge of dynamic obstacles. This paper aims to propose a dynamic obstacle avoidance method based on reinforcement learning to address real-time processing of dynamic obstacles.

This paper introduces an innovative method that introduces a feature extraction network that integrates gating mechanisms on the basis of traditional reinforcement learning algorithms. Additionally, an adaptive dynamic reward mechanism is designed to optimize the obstacle avoidance strategy.

Validation through the CoppeliaSim simulation environment and on-site testing has demonstrated the method's capability to effectively evade randomly moving obstacles, with a significant improvement in the convergence speed compared to traditional algorithms.

The proposed dynamic obstacle avoidance method based on Reinforcement Learning not only accomplishes the task of dynamic obstacle avoidance efficiently but also offers a distinct advantage in terms of convergence speed. This approach provides a novel solution to the obstacle avoidance methods for robotic arms.

Coal is a critical global energy source, and fluctuations in its price significantly impact related enterprises' profitability. This study aims to develop a robust model for predicting the coal price index to enhance coal purchase strategies for coal-consuming enterprises and provide crucial information for global carbon emission reduction.

The proposed coal price forecasting system combines data decomposition, semi-supervised feature engineering, ensemble learning and deep learning. It addresses the challenge of merging low-resolution and high-resolution data by adaptively combining both types of data and filling in missing gaps through interpolation for internal missing data and self-supervision for initiate/terminal missing data. The system employs self-supervised learning to complete the filling of complex missing data.

The ensemble model, which combines long short-term memory, XGBoost and support vector regression, demonstrated the best prediction performance among the tested models. It exhibited superior accuracy and stability across multiple indices in two datasets, namely the Bohai-Rim steam-coal price index and coal daily settlement price.

The proposed coal price forecasting system stands out as it integrates data decomposition, semi-supervised feature engineering, ensemble learning and deep learning. Moreover, the system pioneers the use of self-supervised learning for filling in complex missing data, contributing to its originality and effectiveness.

China has experienced a fast economic growth and shown a significant rise in income inequality in the past decades. During the same period, fluid milk consumption in urban areas has rapidly expanded. The objective of this paper is to analyze and simulate the influence of income distribution changes on fluid milk consumption of households in urban China.

This study applies an inverse hyperbolic sine (IHS) double-hurdle model to modeling at-home fluid milk consumption of households across different income strata based on a sample of 11,861 urban households in five provinces in China, and simulating the impact of changing income distribution, including five income growth patterns, on fluid milk consumption of total households as well as specific household groups.

The fluid milk consumption in urban China will continue to increase, with the unconditional income elasticity being 0.334 for the full sample and 0.347, 0.335 and 0.162 for the low-, middle-, and high-income groups, respectively. The simulation results show an evidence that, compared with distribution-neutral and disparity-enlarging income growth patterns, a rising income equality would lead to a more significant increase in fluid milk consumption. And the inequality-reducing income growth pattern has a larger impact on fluid milk consumption of households with seniors and no children, as well as households having no local urban household registration (hukou).

The government should strengthen the supply measures of fluid milk in urban areas, enlarge domestic dairy production, and diversify the sources of milk imports. It is also necessary to subsidize low-income families, especially households with seniors or households migrated from other areas without getting local urban hukou, which could simultaneously improve nutritional benefits and alleviate financial pressures.

A simulation considering the evolution of income distribution as well as different household groups is conducted. Widely distributed data with a large sample size and detailed demographic information are used. The problems of zero consumption and non-normal distribution are addressed by the IHS double-hurdle model.

The purpose of this study is to improve the position and posture accuracy of posture alignment mechanism. The automatic drilling and riveting machine is an important equipment for aircraft assembly. The alignment accuracy of position and posture of the bracket type posture alignment mechanism has a great influence on the operation effect of the machine. Therefore, it is necessary to carry out the kinematic calibration.

Based on analysis of elastic deformation of the bracket and geometric errors of the posture alignment mechanism, an improved method of kinematic calibration was proposed. The position and posture errors of bracket caused by geometric errors were separated from those caused by gravity. The method of reduction of dimensions was applied to deal with the error coefficient matrix in error identification, and it did not change the coefficient of the error terms. The target position and its posture were corrected to improve the error compensation accuracy. Furthermore, numerical simulation and experimental verification were carried out.

The simulation and experimental results show that considering the influence of the elastic deformation of the bracket on the calibration effect, the error identification accuracy and compensation accuracy can be improved. The maximum value of position error is reduced from 5.33 mm to 1.60 × 10⁻¹ mm and the maximum value of posture error is reduced from 1.07 × 10⁻³ rad to 6.02 × 10⁻⁴ rad, which is superior to the accuracy without considering the gravity factor.

This paper presents a calibration method considering the effects of geometric errors and gravity. By separating position and posture errors caused by different factors and correcting the target position and its posture, the results of the calibration method are greatly improved. The proposed method might be applied to any parallel mechanism based on the positioner.

This paper aims to examine whether managerial sentiment, extracted from annual reports, is associated with corporate risk-taking in the context of Chinese companies. This study expands the vein of literature on overconfidence theory.

By leveraging textual analysis on Chinese listed companies’ annual reports, the authors construct firm-level managerial sentiment during 2007 and 2021 to examine how managerial sentiment influences corporate risk-taking after control for firm characteristics. Corporate risk-taking is denoted by corporate investment engagements: capital expenditures and net fixed asset investment.

Results show that incentives for corporate risk-taking are likely to increase with the positive managerial sentiment and decrease with the negative sentiment in companies’ annual reports. Positive managerial sentiment is associated with over-/under-investment and low/high investment efficiency. Further additional tests show that the managerial sentiment effect only holds during low economic uncertain years and samples of private-owned firms. Furthermore, the robust tests indicate that there is no endogenous issue between managerial sentiment and corporate risk-taking.

Annual report textual-based managerial sentiment may not perfectly reflect managers’ lower frequency sentiment (e.g. weekly, monthly and quarterly sentiment). Future studies could attempt to capture managers’ on-time sentiment by using media sources and corporate disclosures.

To the best of the authors’ knowledge, this paper is the first research to provide insights into supervising managers’ corporate decisions by observing their textual information usage in corporate disclosure. Moreover, the approach of measuring managerial sentiment might be a solution to monitoring managerial class.

This paper contributes to the literature on accounting and finance studies, adding another piece of empirical evidence on content analysis by examining a unique language and institutional context (i.e. China). Besides, the paper notes that in line with the English version disclosure, based on Chinese semantic words, managerial sentiment in the Chinese-speaking world has magnitude on corporate decisions. The research provides insights into supervising managers’ corporate decisions by observing their textual information usage in corporate disclosure. Moreover, the approach to measuring managerial sentiment may be a practical solution to monitoring managerial class.

As innovative household products, social home robots have a significant impact on the interactive consumer experience. However, prior research on consumer intentions to use such robots has rarely considered the configuration perspective. The present study examines how consumers balance the key benefits and risks created by these robots and explores how key influential factors jointly influence usage intention from a configuration perspective.

We adopted a hybrid research design. In Study 1, a thematic analysis was conducted to derive a conceptual framework reflecting the interplay of key factors influencing usage intention. In Study 2, a fuzzy set qualitative comparative analysis (fsQCA) was applied to reveal how these factors jointly shape usage intention.

Equifinal configurations of antecedent conditions (i.e. emotional and instrumental support beliefs, concerns about informational and relational privacy risks, self-construal and anthropomorphic design) led to usage intention. Additionally, four distinct benefit-risk trade-off patterns emerged across individuals.

This study highlights the need to examine robot adoption in interactive marketing, particularly in the service domain. It has implications in the context of commercializing social home robots, emphasizing the potential of leveraging social home robots to enhance interactive consumer experiences and foster close connections with consumers.

We developed a neoconfigurational model to obtain a comprehensive understanding of social home robot acceptance in domestic settings, highlighting its implications for consumer–robot interactions and advancing research in interactive marketing.

The purpose of this paper is to analyze changes in consumers’ knowledge and acceptance of genetically modified (GM) foods over the past decade and identifies the determinants in the consumer attitudes toward GM foods in urban China.

The data used in this study were collected from 952 urban consumers in 2013 in 15 provinces. The ordinal logit model was chosen to identify the determinants in the consumers’ subjective knowledge and acceptance of GM foods.

Results show that the consumers’ awareness of GM foods, biotech knowledge, and subjective knowledge improved significantly, while the acceptance rate toward GM foods declined considerably from 2002 to 2013. Moreover, the consumers’ subjective knowledge of GM foods had a significantly negative impact on their acceptance rate of GM foods. Finally, the media coverage with the “event of Golden rice in 2012” as a proxy helped consumers in shaping their negative perceptions toward GM foods, suggesting that the media coverage was one of major factors in leading to the low acceptance rate of GM foods in urban China.

The findings of previous studies conducted in the early 2000s might not reflect current Chinese consumer attitudes because the public opinion toward GM foods in modern China has considerably changed. This study thus filled in the void by updating estimates on consumer attitudes toward GM foods and by underlining the factors that have led to the changes in consumer attitudes, using a mass survey covering Chinese urban consumers in 15 provinces in 2013.

The purpose of this paper is to investigate the determinants of pork consumption in urban western China and the different consumption patterns across income strata with respect to income elasticity and price elasticity of demand.

The double-hurdle model is fit to the household data of Sichuan and Xinjiang provinces which is from the National Bureau of Statistics urban household surveys.

The paper finds that consumers’ purchasing decisions regarding pork are related to both non-economic and economic factors. The results also indicate large differences among the determinants for decision of how much pork to buy across the three income strata. Low-income households have higher income elasticity than middle-income and high-income households. High-income and middle-income households’ level of pork consumption is more sensitive to pork price. High-income households have greater cross-price elasticity.

In the previous studies, the non-economic determinants of pork consumption have not been addressed, and neither does the issue of difference pork purchasing behavior across income strata for urban households in western China. So this study uses the double-hurdle model to investigate the determinants of pork consumption in urban western China.

This paper aims to examine the impact of visualization tools on the financing ratio of crowdfunding platforms projects of social enterprises, and to sort out personal quality signals and project quality signals based on signaling theory. This paper also divides the emotions and feelings brought by the visualization tools into persuasive and informative styles, showing the functions of different tools on the crowdfunding performance of social ventures.

Linear regression and binary regression are applied to analyze data on social entrepreneurship projects from two internationally authoritative crowdfunding platforms, Kickstarter and Indiegogo.

In social entrepreneurship projects, the number of emotionally persuasive images has a significant positive impact on the financing ratio. Among them, the financing target has a negative regulatory effect.

The study has not fully explored how different visual aspects (such as color and composition) impact investor perceptions. Future research should address these variables for a more accurate understanding of how visualization affects financing performance.

This paper summarizes the factors that affect the crowdfunding ratio and provides a visualization tool from an innovative perspective. The application provides reference value for all types of crowdfunding projects on the crowdfunding platforms.

Social entrepreneurs should use the crowdfunding model to raise funds and deepen their understanding of crowdfunding investors, so that more people can participate in social entrepreneurship and thereby generate greater social value.

This paper provides a new perspective for the classification of visualization tools. This paper divides the emotions and feelings brought by the visualization tools to the information recipients, and classifies them into persuasive and informative styles, showing the functions of different tools.

This study aims to study the influence of friction influencing factors between the wire rope and the liner on the safe use of the wire rope, which can provide guidance for the reliability design of the lifting system with strong dynamic response such as high speed, heavy load, etc., and improve the friction-driven stability of the system.

In this paper, the friction mechanism of wire rope and liner under the condition of excitation is investigated by means of wire rope-liner friction-vibration experimental platform and dynamic viscoelastic test of liner.

The results show that: With increasing excitation frequency, the friction between the three liner materials (G30, K25, PU) and the wire rope decreased, and the wear of the surface shape of the liners was greater. The dynamic thermomechanical analysis (DMA) test results showed that the viscoelasticity of the three liner materials increased when the frequency was increased.

Wire ropes are widely used in deep shaft hoisting and building elevators. Its operational reliability depends on whether there is sufficient friction between the wire rope and the friction liner, and whether the friction liner has good wear resistance. The study of the friction between the wire rope and the liner influencing factors is of great significance for the safe service of the wire rope.

The related results can provide guidance for the reliability design of lifting systems with strong dynamic response, such as high speed and heavy load, to improve the friction drive stability of the system.

With the increase of mining depth, to improve the transportation efficiency of the hoist used in deep and ultra-deep mines, as well as to ensure the safety and reliability of its operation, it is crucial that the large friction hoisting equipment has sufficient friction between the wire rope and the friction lining, as well as whether the friction lining has a good abrasion resistance.