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This study explores whether and how Internet usage improves the subjective health of middle-aged and older adults by analyzing the mediating role of social engagement and heterogeneity of different living arrangements.

Based on data from the China Health and Retirement Longitudinal Study, the ordinary least squares (OLS) method is adopted to explore the relationship between Internet usage and the subjective health of middle-aged and older adults. Propensity score matching method (PSM) is used to alleviate self-selection bias in the samples. The bootstrap method is adopted to test the mediating role of social engagement, and generalized structural equation modeling (GSEM) is employed to resolve endogeneity. A permutation test is adopted to examine the heterogeneous effects of Internet usage on different living arrangements.

Internet access can help relieve depression among middle-aged and older adults and enhance their self-rated health, leading to perceived changes in health status. However, Internet usage is not directly associated with health satisfaction among middle-aged and older adults. Nevertheless, Internet usage can enhance middle-aged and older adults' subjective health by facilitating social engagement and significantly influences middle-aged and older adults living with their children.

This study reveals the underlying role of Internet usage among older adults and provides insights for governments and families to help middle-aged and older adults actively adapt to a digital society and improve their health.

Human capital is acquired not only through formal education (e.g. general skills) but also through training at the workplace. Prior studies have ignored the role of government subsidies explicitly for on-the-job training, which may influence firm training decisions and firm innovation performance. Hence, the authors establish a comprehensive theoretical framework to consider these issues and fill these gaps.

Considering the Chinese manufacturing firms listed in the Shanghai and Shenzhen Stock Exchange from 2010 to 2017, the authors investigate the influence of training investment on innovation performance by illustrating the role of human capital updating in enhancing firm innovation. The authors also explore serval mechanisms on how training investment influences innovation performance.

The authors propose that training investment promotes firm innovation performance, whereas government training subsidies negatively moderate this relationship. The authors also reveal how technicists' involvement and corporate culture mediate the relationship between training investment and innovation performance.

This study provides policy implications for stimulating firm innovation by improving learning and absorption ability, strengthening cultural identity and implementing system norms. Effective policies should be adopted to provide subsidies for on-the-job training of enterprises, particularly for firms with technical executives and firms in diversified life-cycle.

This work contributes to the literature on the role of on-the-job training in promoting firm innovation and reveals the crowding-out effect of subsidies. This study also shows the heterogeneous effects of training investment on firm innovation.

The purpose of this study is to reduce the cracks, pores and unfused defects in arc welding, improve the crystalline structure of the weld, refine its grains and improve the mechanical properties.

Taking E690 marine steel as the research object, the experiment adopts a new process method of laser forging coupled arc welding. Welding for comparative experiments. Experiments show that the “V”-shaped groove arc welding process has a larger fusion area, but has pores, the arc current is 168 A, the arc voltage is 28 V and the welding speed is 600 mm/min.

It can be seen from tensile tests that the coupling welding process has the highest tensile strength and yield strength, 872 MPa and 692 MPa, respectively, and the fracture elongation is 29.29%. The single-beam laser forging coupled arc welding process has a distance of laser and wire of 6–8 mm, a laser wavelength of 1,064 nm and the highest weld fusion ratio. The microhardness test shows that the average hardness of single-beam laser forging in the weld zone is 487.54 HV, which is 10.30% higher than that of arc welding. The average hardness in the fusion zone is 788.08 HV, which is 14.52% higher than that of the arc welding process.

The originality of the experiment: proposed a new process method of coupling arc repair for offshore steel forging; adopted a new process method of simultaneous coupling of single-beam short-pulse laser, double-beam short-pulse laser and arc welding; and obtained effect of pulsed laser and arc composite repair on porosity and fusion of E690 marine steel welds.

This study proposes a predictive neural network model reference decoupling control method for the coupling problem between the leg joints of hydraulic quadruped robots, and verifies its decoupling effect..

The machine–hydraulic cross-linking coupling is studied as the coupling behavior of the hydraulically driven quadruped robot, and the mechanical dynamics coupling force of the robot system is controlled as the disturbance force of the hydraulic system through the Jacobian matrix transformation. According to the principle of multivariable decoupling, a prediction-based neural network model reference decoupling control method is proposed; each module of the control algorithm is designed one by one, and the stability of the system is analyzed by the Lyapunov stability theorem.

The simulation and experimental research on the robot joint decoupling control method is carried out, and the prediction-based neural network model reference decoupling control method is compared with the decoupling control method without any decoupling control method. The results show that taking the coupling effect experiment between the hip joint and knee joint as an example, after using the predictive neural network model reference decoupling control method, the phase lag of the hip joint response line was reduced from 20.3° to 14.8°, the amplitude attenuation was reduced from 1.82% to 0.21%, the maximum error of the knee joint coupling line was reduced from 0.67 mm to 0.16 mm and the coupling effect between the hip joint and knee joint was reduced from 1.9% to 0.48%, achieving good decoupling.

The prediction-based neural network model reference decoupling control method proposed in this paper can use the neural network model to predict the next output of the system according to the input and output. Finally, the weights of the neural network are corrected online according to the predicted output and the given reference output, so that the optimization index of the neural network decoupling controller is extremely small, and the purpose of decoupling control is achieved.

This study aims to address the challenge of automatic guided vehicle (AGV) scheduling for parcel storage and retrieval in an intelligent warehouse.

This study presents a scheduling solution that aims to minimize the maximum completion time for the AGV scheduling problem in an intelligent warehouse. First, a mixed-integer linear programming model is established, followed by the proposal of a novel genetic algorithm to solve the scheduling problem of multiple AGVs. The improved algorithm includes operations such as the initial population optimization of picking up goods based on the principle of the nearest distance, adaptive crossover operation evolving with iteration, mutation operation of equivalent exchange and an algorithm restart strategy to expand search ability and avoid falling into a local optimal solution. Moreover, the routing rules of AGV are described.

By conducting a series of comparative experiments based on the actual package flow situation of an intelligent warehouse, the results demonstrate that the proposed genetic algorithm in this study outperforms existing algorithms, and can produce better solutions for the AGV scheduling problem.

This paper optimizes the different iterative steps of the genetic algorithm and designs an improved genetic algorithm, which is more suitable for solving the AGV scheduling problem in the warehouse. In addition, a path collision avoidance strategy that matches the algorithm is proposed, making this research more applicable to real-world scheduling environments.

This study aims to solve the problem of job scheduling and multi automated guided vehicle (AGV) cooperation in intelligent manufacturing workshops.

In this study, an algorithm for job scheduling and cooperative work of multiple AGVs is designed. In the first part, with the goal of minimizing the total processing time and the total power consumption, the niche multi-objective evolutionary algorithm is used to determine the processing task arrangement on different machines. In the second part, AGV is called to transport workpieces, and an improved ant colony algorithm is used to generate the initial path of AGV. In the third part, to avoid path conflicts between running AGVs, the authors propose a simple priority-based waiting strategy to avoid collisions.

The experiment shows that the solution can effectively deal with job scheduling and multiple AGV operation problems in the workshop.

In this paper, a collaborative work algorithm is proposed, which combines the job scheduling and AGV running problem to make the research results adapt to the real job environment in the workshop.

This paper analyzes the existing body of work on the relationship between depression and social media use in the information system field, including the impact of social media use on depression, the effect of depression on social media use and the association and interaction between depression and social media use.

Using the systematic review method, this study selected the Web of Science, Emerald, Science Direct, JSTOR, Wiley Online Library and Taylor and Francis Online as search databases and ended up with 29 papers that met all the authors' requirements.

This study identified five possible reasons for the inconsistencies between the findings of the selected studies. First, uses and gratifications theory has different influence mechanisms in evaluating the relationship between social media use and depression. Second, gender can moderate the impact of social media use on depression. Third, age moderates the association between social media use and depression. Fourth, for adolescents, the time spent on social media has a critical effect on their depression. Fifth, negative personality traits (e.g. rumination, envy, etc.) can play a significant role in mediating the relationship between passive social media use and depression.

This study conducted an evaluation of the relationship between depression and social media use. First, the authors summarized the research framework and main body of work covering the relationship between depression and social media use. Second, the authors proposed possible explanations for the inconsistencies between the findings. Third, the authors discussed and explained the possible influence mechanisms of the existing results.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2021-0211.

This study aims to focus on the impact of multi-level knowledge sharing between and within organizations on the risk control of rural inclusive finance. The paper presents a synergistic risk control system integrating external and internal factors for rural inclusive finance by constructing different knowledge-sharing platforms in an environment, which is full of many uncertainties.

This study is based on survey methods. To achieve the research objectives, the authors adopt a single case study approach. For data collection, the authors apply a wide variety of methods such as semi-structured interviews, field visits, second-hand databases and official websites.

The results emphasize that using multi-level knowledge sharing such as the inter- and intra-organizational level, can facilitate the risk control of rural inclusive finance during the post-COVID-19 era. Furthermore, it is also noted that achieving knowledge sharing at different levels by building diverse knowledge-sharing platforms can promote the risk control of rural inclusive finance from the individual-organization level to the chain level of multi-organization collaboration, which contributes to the formation of symbiotic risk control ecology.

The authors have formed the “Chinese wisdom” to deal with inclusive financial risks and to promote in-depth development in relation to the “last mile” practice of inclusive finance, which means the final and the most important phase of a project. The conclusions contribute to enriching the outcomes regarding the risk control of rural inclusive finance, provide experiences to its sustainable development and offer a reference to other countries with their risk control of rural inclusive finance.

Drawing on the knowledge-sharing approach, this study creatively resolves the persistent problems in the risk control of rural inclusive finance, which forms a powerful supplement to the extant literature. Meanwhile, the paper combines the two contextual factors of the post-COVID-19 era and emerging economies, which can be deemed as a novel attempt.

It was verified that the micro-texture in the front and back of the tool at the same time had a positive effect on improving the milling behavior and surface quality of the tool. The purpose of this study is to explore the rationality of simultaneous placement of micro-textures on the front and rear surfaces of ball-end milling cutters, analyze the influence of micro-texture parameters on tool milling behavior and workpiece surface quality, reveal its internal mechanism, and obtain the best micro-texture parameters by optimization.

First, the mechanism of micro-texture is studied based on the energy loss model. Second, the orthogonal experiment is designed to analyze the influence of micro-texture parameters on tool milling behavior and reveal its mechanism by combining simulation technology and cutting experiment. Finally, the parameters are optimized based on the artificial bee colony algorithm.

The results show that the simultaneous placement of micro-texture on the rake face and flank face of the tool has a positive effect on improving the milling behavior and surface quality of the tool. Taking milling force, tool wear and surface roughness as the evaluation criteria, the optimal parameter combination is obtained: the rake face micro-texture diameter is 50 µm, the distance from the micro-texture is 200 µm and the distance from the cutting edge is 110 µm; the diameter of the micro-textured flank is 40 µm, the distance from the micro-texture is 170 µm and the distance from the cutting edge is 130 µm.

Taking milling force, tool wear and surface roughness as the evaluation criteria, the optimal parameter combination is obtained: the rake face micro-texture diameter is 50 µm, the distance from the micro-texture is 200 µm and the distance from the cutting edge is 110 µm; the diameter of the micro-textured flank is 40 µm, the distance from the micro-texture is 170 µm and the distance from the cutting edge is 130 µm, which provides theoretical support for the further study of the micro-textured tool.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2023-0022/

This study aims to investigate the surface modification on 20CrMnTi gear steel individually treated by diamond-like carbon films and nitride coatings.

For this purpose, the mechanical properties of a-C:H, ta-C and AlCrSiN coatings are characterized by nano-indentation and scratch tests. The friction and wear behaviors of these three coatings are evaluated by ball-on-disc tribological experiments under dry contact conditions.

The results show that the a-C:H coating has the highest coating-substrate adhesion strength (495 mN) and the smoothest surface (Ra is about 0.045 µm) compared with the other two coatings. The AlCrSiN coating shows the highest mean coefficient of friction (COF), whereas the ta-C coating exhibits the lowest one (steady at about 0.16). The carbon-based coatings possess excellent self-lubricating properties compared with nitride ceramic ones, which effectively reduce the COF by about 64%. The major failure mode of carbon-based coatings in dry contact is slight abrasive wear. The damage of AlCrSiN coating is mainly adhesive wear and abrasive wear.

It is suggested that the carbon-based film can effectively improve the friction-reducing and wear resistance performance of the gear steel surface, which has a promising application prospect in the mechanical transmission field.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0129/