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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.

The purpose of this paper is to present the latest sensing structure designs and principles of information detection of fiber Bragg grating (FBG) displacement sensors. Research advance and the future work in this field have been described, with the background that displacement and deformation measurements are universal and crucial for structural health monitoring.

This paper analyzes and summarizes the existing FBG displacement sensing technologies from two aspects principle of information detection (wavelength detection, spectral bandwidth detection, light intensity detection, among others) and principle of the sensing elastomer structure design (cantilever beam type, spring type, elastic ring type and other composite structures).

The current research on developing FBG displacement sensors is mainly focused on the sensing method, the construction and design of the elastic structure and the design of new information detection method. The authors hypothesize that the following research trends will be strengthened in future: temperature compensation technology for FBG displacement sensors based on wavelength detection; a study of more diverse elastic structures; and fiber gratings manufactured with special fibers will greatly improve the performance of sensors.

The latest sensing structure designs and principles of information detection of FBG displacement sensors have been proposed, which could provide important reference for research group.

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.

To realise the shared development of the digital economy, people need to transcend the capital logic and advocate the logic of cooperative development, i.e. “co-construction, benefit-sharing and co-governance”. This study aims to discuss the aforementioned statement.

Platform economy is a new economic form produced by the transformation of the social production patterns in the era of digital capitalism. In the neo-imperialist stage, a new stage of capitalist development, capital logic promotes the global expansion of the platform economy and influences its development process, organisational form, contradictions and dilemmas and internal transcendence. Having the spatiotemporal chain of capital circulation repaired, the globalisation of the platform economy is reshaping how the means of production are combined with labour, affecting the local changes in the general relations of production and “international relations of production”.

In the accumulation of digital capitalism, the social contradictions and fundamental contradictions in the capitalist world have been further intensified, making exploitation, income distribution gap, monopoly and other problems increasingly severe. The imbalance and inequality in the global development of the digital economy are increasingly prominent.

Regarding the global governance of the digital economy, China, as a major responsible country, will strive to encourage all countries to co-build a community with a shared future in cyberspace. In the new international development pattern of digital economy globalisation, China must take effective measures to actively safeguard its national security and development interests to meet specific challenges.

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.

The purpose of this paper is to investigate the cointegration and volatility spillover dynamics between the USA and South Asian stock markets, namely, India, Pakistan and Sri Lanka. The main objective of this study is to provide the knowledge about integration of financial market and volatility spillovers before, during and after global financial crisis to investors, fund managers and policy-makers.

The Johansen and Juselius cointegration test, Granger Causality test and bivaraite EGARCH model have been applied in this study to examine integration and volatility spillovers between selected stock markets.

The findings show that long-term integration between the USA market and South Asian emerging stock markets. It is found that USA stock market has causal relationship with emerging stock markets in short-term. The findings of EGARCH model reveal that asymmetric volatility spillover effects significant in all selected stock markets in pre, during and post-crisis periods. Furthermore, significant volatility spillover is found from stock markets of USA to all selected South Asian markets during and post-crisis periods. However, volatility spillovers from USA to India and Sri-Lanka markets are significant, while insignificant in case of Pakistani market in pre-crisis period. Overall, we find that returns and volatility spillover effects are higher in financial crisis period as compared to non-financial crisis period.

The findings of this paper have important implications for investors, portfolio managers and policy-makers. They can take potential benefits from international portfolio diversification by considering all these facts. The understanding and knowledge of across volatility transmission help them to maximize the gains from diversification and minimize the risk. Policy-makers can develop such strategies which protect the markets of these economies from future financial crisis.

Although in finance literature numerous studies have been conducted on integration between different stock markets, most of the studies investigated the integration and volatility spillovers between developed stock markets. However, many studies also analyzed the integration among emerging stock markets in literature review but it is hard to find studies in the context of South Asian stock markets on the effect of global financial crisis on stock markets. The main contribution of this study is to investigate the stock markets integration and volatility transmission between the USA and South Asia by considering the effect of recent 2007 US subprime financial crisis.

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.

To control one of the joints during the actual movement of the hydraulically driven quadruped robot, all the other joints in the leg need to be locked. Once the joints are unlocked, there is a coupling effect among the joints. Therefore, during the normal exercise of the robot, the movement of each joint is affected by the coupling of other joints. This brings great difficulties to the coordinated motion control of the multi-joints of the robot. Therefore, it is necessary to reduce the influence of the coupling of the hydraulically driven quadruped robot.

To solve the coupling problem with the joints of the hydraulic quadruped robot, based on the principle of mechanism dynamics and hydraulic control, the dynamic mathematical model of the single leg mechanism of the hydraulic quadruped robot is established. On this basis, the coupling dynamics model of the two joints of the thigh and the calf is derived. On the basis of the multivariable decoupling theory, a neural network (NN) model reference decoupling controller is designed.

The simulation and prototype experiment are carried out between the thigh joint and the calf joint of the hydraulic quadruped robot, and the results show that the proposed NN model reference decoupling control method is effective, and this method can reduce the cross-coupling between the thigh and the calf and improve the dynamic characteristics of the single joint of the leg.

The proposed method provides technical support for the mechanical–hydraulic cross-coupling among the joints of the hydraulic quadruped robot, achieving coordinated movement of multiple joints of the robot and promoting the performance and automation level of the hydraulic quadruped robot.

On the basis of the theory of multivariable decoupling, a new decoupling control method is proposed, in which the mechanical–hydraulic coupling is taken as the coupling behavior of the hydraulic foot robot. The method reduces the influence of coupling of system, improves the control precision, realizes the coordinated movement among multiple joints and promotes the popularization and use of the hydraulically driven quadruped robot.