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Using a dynamic perspective this article examines, the general situation of the development of South Korean direct investment in China since 1992, when the two countries established diplomatic relations. It probes many characteristics of South Korean direct investment in China: its late start yet rapid rise; the smaller average value of Korean project investments; the accelerated process of localization by large South Korean enterprises in China; the diversified industrial distribution; and the wide-ranging geographical distribution. It analyses the reasons for the rapid increase in South Korean investment in China: the use of China's low-priced production factors, the direct entry of South Korean enterprises into the Chinese market, and the stable investment environment with fewer labor disputes that China provides. Finally, this article also proves that South Korean enterprises have achieved satisfactory results from their direct investment in China.

This paper aims to describe a three-dimensional mathematical and numerical model based on finite volume method to simulate the fluid dynamics in weld pool, droplet transfer and keyhole behaviors in the laser-MIG hybrid welding process of Fe36Ni Invar alloy.

Double-ellipsoidal heat source model and adaptive Gauss rotary body heat source model were used to describe electric arc and laser beam heat source, respectively. Besides, recoil pressure, electromagnetic force, Marangoni force, buoyancy as well as liquid material flow through a porous medium and the heat, mass, momentum transfer because of droplets were taken into consideration in the computational model.

The results of computer simulation, including temperature field in welded plate and velocity field in the fusion zone were presented in this article on the basis of the solution of mass, momentum and energy conservation equations. The correctness of elaborated models was validated by experimental results and this proposed model exhibited close correspondence with the experimental results with respect to weld geometry.

It lays foundation for understanding the physical phenomena accompanying hybrid welding and optimizing the process parameters for laser-MIG hybrid welding of Invar alloy.

The purpose of this paper is to establish a three-dimensional flow field model of the Invar alloy laser–metal inert gas (laser–MIG) hybrid welding process to investigate the influence of different heat sources between different layers and to analyze the flow field based on the two different heat source models for the multilayer welding.

The Invar steel plates with 19.5 mm thickness are welded into three layers’ seam using the hybrid laser–MIG welding technology. The flow field based on different heat source models is studied and then used to investigate the influence of different heat sources in different layers during the laser–MIG hybrid welding process. The simulation results of flow field using two different heat source models are compared with experiments.

The flow field simulations results show that using the Gaussian rotating body heat source model to simulate the temperature field is more consistent with the experiment of the hybrid laser–MIG welding where its flow field between different layers better reflects the characteristics of the hybrid laser–MIG welding.

The findings will be useful in the study of a variety of thick-plate laser–MIG hybrid welding process fluid flows.

The purpose of this paper is to make compliant training control of exoskeleton for ankle joint with electromyograph (EMG)-torque interface.

A virtual compliant mapping which is modeled by mass-spring-damper system is incorporated into the whole system at the reference input. The EMG-torque interface contains both data acquisition and torque estimator/predictor, and extreme learning machine is utilized for joint torque estimation/prediction from multiple channels of EMG signals.

The reference ankle joint angle to follow is produced from the compliance mapping whose input is the measured/predicted torque on healthy subjects. The control system works well with the desired angle to track. In the actuation level, the input torque to drive the ankle exoskeleton is less than the actual torque of the subject(s). This may have positive influence on diminishing overshoot of input torque from motors and protect the actuators. The torque prediction and final tracking control performance demonstrate the efficiency of the presented architecture.

This work can be beneficial to compliant training of ankle exoskeleton system for pilots and enhance current training control module in rehabilitation.

Digital transformation misalignment refers to disparities in digital transformation levels between suppliers and buyers across the production and operation process. It has negatively affected supply chain stability. However, the existing research concerning the economic consequences has not been adequately addressed. Therefore, this paper aims to investigate whether such digital transformation misalignment increases supplier financial risk and to identify the factors influencing this relationship.

This paper examines binary combinations of suppliers and buyers listed on China’s A-share market between 2011 and 2021. This group constitutes a sample to empirically test the influence of digital transformation misalignment on the supplier’s financial risk, as well as the moderating effect of the geographical and organizational distances.

The paper’s findings demonstrate that digital transformation misalignment has indeed a significant increase in the supplier’s financial risk. Moreover, the impact is more intense when the geographical or organizational distance between the supplier and the buyer is relatively large.

The existing literature rarely explores the potential risks arising from digital transformation misalignment between supply chain partners. Therefore, this paper fills a notable gap as it is the first to study the impact of digital transformation misalignment on the supplier’s financial risk and the specific applied mechanisms. The contribution significantly improves the field of corporate digital transformation, particularly, within the context of supply chain management.

This study aims to investigate the effect of coatings prepared by the addition of copper-aluminum alloy powder on the corrosion behavior of 90/10 copper-nickel alloy.

Coatings of copper-aluminum alloy powder at different contents (Wt.% = 50%, 60%, 70% and 80%) were prepared by the high-temperature heat treatment process. The microstructure and component of the coatings were characterized by scanning electron microscope, X-ray diffraction, energy dispersive spectrometer and X-ray photoelectron spectroscopy. The electrochemical properties of the coating were explored by electrochemical impedance spectroscopy.

The results show that the aluminized layer was successfully constructed on the surface of 90/10 copper-nickel alloy, the composition of the coating was composed of copper-aluminum phase and aluminum-nickel phase, the existence of the aluminum-nickel phase was formed by the diffusion of Ni elements within the substrate and because of the diffusion, the Al-Ni phase was distributed in the middle and bottom of the coating more. The Al-Ni phase is considered to be the enhanced phase for corrosion resistance. When the copper-aluminum alloy powder content is 70 Wt.%, the corrosion resistance is the best.

The enhancement of corrosion resistance of 90/10 copper-nickel alloy by the copper-aluminum alloy powder was revealed, the composition of the aluminized layer and the mechanism of corrosion resistance were discussed.

The purpose of this study is to bridge the gap in the literature on supply chain finance (SCF) by exploring the relationship between network capabilities and corporate financial performance (CFP) in financial supply chains (FSCs).

The authors collect panel data and adopt regression analysis to analyse the joint investment activities among 1359 manufacturing firms and 289 financial service providers in China to explore how network capabilities, both network power and network centrality, improve CFP in the FSCs.

Under the FSCs environments, network centrality (i.e. eigenvector centrality, closeness centrality and betweenness centrality) raises CFP (ROA, ROE and Tobin's Q) and network power (node degree, clustering coefficient) also improves CFP. However, node strength from the network power stream has a negative effect on Tobin's Q, indicating that when the partner of a firm has an extremely strong influence in FSCs; this weakens the bargaining ability and flexibility of the focal firm, thus reducing its long-term financial performance.

The joint investment activities among supply chain partners and financial service providers help managers understand the advanced financing solutions generated by internal and external network organisations as well as be aware of network capabilities' impact on CFP in FSCs.

This study answers the call for more empirical research on SCF to provide a broader sample to examine financial supply chain management. This is one of the earliest studies to shed light on a new perspective – how network capabilities improve CFP in the FSCs.

The purpose of this paper is to study the moderating role of corporate social responsibility (CSR) in the knowledge asset–firm financial performance relationship.

This paper first develops hypotheses based on multiple theoretical lenses and uses a sample of 3,030 US firms in 51 industries over 11 years to test these hypotheses.

It is found that CSR positively moderates the relationship between research and development (R&D) investments and the firm's financial performance, and the moderating effect declines when firms mistreat their employees.

This paper provides evidence that when firms allocate their resources, they should consider the synthetic effect among different activities such as R&D and CSR.

First, this study offers a new and alternate mechanism for the appropriability literature and also extends the boundary of CSR research. Second, this work shifts the CSR performance thought by considering CSR as an enabler rather than a driver for performance.

This paper aims at the problem of attaching the data of doctors, patients and the real-time sensor data of the exoskeleton to the cloud in intelligent rehabilitation applications. This study designed the exoskeleton cloud-brain platform and validated its safety assessment.

According to the dimension of data and the transmission speed, this paper implements a three-layer cloud-brain platform of exoskeleton based on Alibaba Cloud's Lambda-like architecture. At the same time, given the human–machine safety status detection problem of the exoskeleton, this paper built a personalized machine-learning safety detection module for users with the multi-dimensional sensor data cloned by the cloud-brain platform. This module includes an abnormality detection model, prediction model and state classification model of the human–machine state.

These functions of the exoskeleton cloud-brain and the algorithms based on it were validated by the experiments, they meet the needs of use.

This thesis innovatively proposes a cloud-brain platform for exoskeletons, beginning the digitalization and intelligence of the exoskeletal rehabilitation process and laying the foundation for future intelligent assistance systems.