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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.

The purpose of this paper is to investigate the effect of pulsed magnetic field (PMF) with different duty cycles on the melt flow and heat transfer behaviors during direct-chill (DC) casting of large-size magnesium alloy billet and find the appropriate range of duty cycle.

A transient two-dimensional mathematical model coupled electromagnetic field, flow field and thermal field, is conducted to study the melt flow and temperature field under PMF and compared with that under the harmonic magnetic field.

The results reveal that melt vibration and fluctuation are generated due to the instantaneous impact of repeated thrust and pull effects of Lorentz force under PMF. The peak of Lorentz force decreases greatly with the increasing duty cycle, but the melt fluctuation region is expanded with higher duty cycle, which accelerates the interior melt velocity and reduces the temperature gradient at the liquid-solid interface. However, PMF with overly high duty cycle has adverse effect on the melt convection and limited influence on the interior melt. A duty cycle of 20% to 50% is a reasonable range.

This paper can provide guiding significance for the setting of duty cycle parameters on DC casting under PMF.

There are few reports on the effect of PMF parameters during DC casting with applying PMF, especially for duty cycle, a parameter unique to PMF. The findings will be helpful for applying the external field of PMF on DC casting.

The purpose of this study is to prepare trivalent chromium conversion (TCC) film on the Zn-Ni electrodeposited film on the surface of 2024 aluminum alloy and to ensure that the TCC film has good corrosion resistance and electrical conductivity.

The morphology of the TCC film was studied by scanning electron microscopy, and the elemental composition of the TCC film was characterized by X-ray energy dispersive spectroscopy. The TCC film was tested and the roughness was analyzed by 3D morphology (white light interference). The electrochemical behavior and corrosion resistance of TCC films were studied by the Tafel polarization curve and electrochemical impedance spectroscopy, and the conductivity was tested.

The TCC films were uniformly black and bright in appearance and were mainly compounds of Zn, Ni and Cr with O. The electrochemical impedance of the TCC film is larger than that of the Zn-Ni film, the corrosion current (I_corr) is smaller than that of the Zn-Ni film and the corrosion potential (E_corr) is larger than that of the Zn-Ni film, which has excellent corrosion resistance. TCCs were performed on the appropriate size of the shell sample, and the resistance of the shells was 1.5 mVDC, which meets the total resistance requirements of the test standard for composite connector accessories.

In this study, TCC film was successfully prepared on the Zn-Ni coating on the surface of 2024 aluminum alloy. The TCC film has good corrosion resistance and electrical conductivity.

Despite the growing interest in the role of relation-specific investments (RSIs) in superior firm performance, their impact on sustainability performance remains unexplored, as do the underlying mechanisms of such effects. Drawing on the relational view and resource orchestration theory (ROT), the authors propose that supply chain learning (SCL) mediates the link between RSIs and sustainability performance.

A multi-method approach was adopted, combining a case study and survey. An exploratory case study of four Chinese manufacturing firms was first conducted to develop research hypotheses. A quantitative survey of data collected from 269 firms was then undertaken to test hypotheses.

Property-based, knowledge-based and personal-based RSIs positively impact firm sustainability performance and SCL. SCL fully mediates the relationship between knowledge-as well as personal-based RSIs and sustainability performance, and partially mediates the relationship between property-based RSIs and sustainability performance.

The study unveils important practical insights and approaches for firms endeavouring to achieve sustainability performance through RSIs and SCL.

The study extends the RSIs literature by linking RSIs and sustainability performance and differentiating the effects of different types of RSIs on sustainability performance. The theorized underlying mechanism advances the understanding of SCL in the link between RSIs and sustainability performance.

The carbon complementary supply chain (CCSC) is a collaborative framework that facilitates internal carbon credit trading agreements among supply chain agents in compliance with prevailing carbon regulations. Such agreements are highly beneficial, prompting agents to consider joint investment in emission reduction initiatives. However, capital investments come with inevitable opportunity costs, compelling agents to weigh the potential revenue from collaborative investments against these costs. Thus, this paper mainly explores carbon abatement strategies and operational decisions of the CCSC members and the influence of opportunity costs on the strategic choice of cooperative and noncooperative investment.

The authors propose a novel biform game-based theoretical framework that captures the interplay of pricing competition and investment cooperation among CCSC agents and assesses the impact of opportunity costs on CCSC profits and social welfare. Besides, the authors also compare the biform game-based collaborative scenario (Model B) to the noncooperative investment scenario (Model N) to investigate the conditions under which collaborative investment is most effective.

The biform game-based collaborative investment strategy enhances the economic performance of the traditional energy manufacturer, who bears the risk of opportunity costs, as well as the retailer. Additionally, it incentivizes the renewable energy manufacturer to improve environmental performance through renewable projects.

This research contributes significantly by establishing a theoretical framework that integrates the concepts of opportunity costs and biform game theory, offering new insights into the strategic management of carbon emissions within supply chains.

While top management teams (TMTs) play an important role in shaping firms’ strategic choices and performance outcomes, studies on green innovation have rarely considered the influence of the TMT demographics of firms and their suppliers. Drawing upon upper echelon theory, this study investigates the impact of buyer–supplier TMT misalignment on green innovation performance, along with potential moderators of this effect.

The empirical setting is Chinese-listed manufacturing firms that are present in both the Chinese Research Data Services Platform (CNRDS) database and the China Stock Market and Accounting Research (CSMAR) database. The study employs panel data regression methods on a dyadic dataset of 530 paired buyer–supplier firm-year observations over the period 2008–2019.

Buyer–supplier TMT misalignment in terms of functional background and educational level is negatively associated with buyer green innovation performance. This negative effect can, however, be mitigated by TMT tenure and long-term incentives in buyer firms.

By introducing the notion of TMT background misalignment to the supply chain, this study advances the understanding of relational TMT demographics in predicting organizational performance and extends upper echelon theory.