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The purpose of this paper is to explore the basic loading state in local loading forming process of large-sized complicated rib-web component, which is important for understanding process characteristic, controlling metal flow and designing preformed geometry of the local loading forming process. Moreover the analytical models for different loading states are established to quickly predict the metal flow.

Through analysis of geometric characteristic of large-sized complicated rib-web component and the deformation characteristic on planes of metal flow by local loading method, a representative cross-section is put forward and designed, which could reflect the local loading forming characteristics of large-sized complicated rib-web component. Finite element method (FEM) is used to analyze the stress and metal flow, and the analytical models of metal flow are established by using slab method (SM).

Three local loading states and one whole loading state are found in the local loading forming process of representative cross-section. Further, four loading states also exist in local loading forming process of large-sized complicated rib-web components. With the metal distribution in the process, some local loading states may turn into whole loading state. For the representative cross-section, the relative error of metal distribution between SM and FEM results is less than 15 per cent, and the relative error of metal in the rib cavity between SM and FEM results is less than 10 per cent.

Metal flow can be controlled by adjusting the loading states in the process. According to the metal flow laws in different loading states, a simple unequal-thickness billet can be designed to achieve initial metal distribution, and then, the secondary metal distribution can be achieved in the process.

Path planning in unknown or partly unknown environment is a quite complex task, partly because it is an evolving globally optimal path affected by the motion of the robot and the changing of environmental information. The purpose of this paper is to propose an online path planning approach for a mobile robot, which aims to provide a better adaptability to the motion of the robot and the changing of environmental information.

This approach treats the globally optimal path as a changing state and estimates it online with two steps: prediction step, which predicts the globally optimal path based on the motion of the robot; and updating step, which uses the up‐to‐date environmental information to refine the prediction.

Simulations and experiments show that this approach needs less time to reach the destination than some classical algorithms, provides speedy convergence and can adapt to unexpected obstacles or very limited prior environmental information. The better performances of this approach have been proved in both field and indoor environments.

Compared with previous works, the paper's approach has three main contributions. First, it can reduce the time consumed in reaching the destination by adopting an online path planning strategy. Second, it can be applied in such environments as those with unexpected obstacles or with only limited prior environmental information. Third, both motion error of the robot and the changing of environmental information are considered, so that the global adaptability to them is improved.

The purpose of this paper is to find a novel optimization selection method for hyper‐parameter of support vector classification (SVC), responsible for the classification of datasets from the UCI machine learning database repository.

A novel two‐stage optimization selection method for hyper‐parameters is proposed. It makes use of explicit information derived from issues and implicit knowledge extracted from the evolution process so as to improve the performance of classifier. In the first stage, the search extent of each hyper‐parameter is determined according to the requirements of issues. In the second stage, optimal hyper‐parameters are obtained by adaptive chaotic culture algorithm in the above search extent. Adaptive chaotic cultural algorithm uses implicit knowledge extracted from the evolution process to control mutation scale of chaotic mutation operator. This algorithm can ensure the diversity of population and exploitation in the latter evolution.

The rationality of the above optimization selection method is proved by the binary classification problem. Final confirmation of this approach is the classification results compared with other methods.

This optimization selection method can effectively avoid premature convergence and lead to better computation stability and precision. It is not related on the structure of functions. SVC model corresponding to optimal hyper‐parameters by this method has better generalization.

Embodied intelligent robots are the iconic productivity of the Industry 4.0 era, and their potential to bring about a productivity surge mainly comes from the driving force of robots on innovation rather than efficiency. However, the dynamic impact of robots on the innovation capability of enterprises has not been empirically tested.

This study integrates panel vector autoregression and threshold effects to investigate this dynamic relationship by a multi-level analysis based on data of Chinese A-share manufacturing listed enterprises.

(1) The short-term momentum of industrial robot applications (IRA) on exploitative innovation (EII) is significant and the long-term momentum on exploratory innovation (ERI) is stronger. (2) EII affected by IRA is the main source of short-term total factor productivity (TFP) growth, while ERI is the driving factor for long-term TFP growth. (3) The impact of IRA on TFP exhibits a double-threshold effect based on ERI and follows a “stepped” incremental pattern. The promoting effect of IRA on TFP will significantly increase only when ERI surpasses certain thresholds.

Industrial robots accelerate the potential productivity growth in the long term, mainly coming from the augmented contribution of ERI, providing reference and inspiration for enterprises to fully utilize the endogenous growth potential of robots and implement innovation strategies. It also provides forward-looking guidance for organisations to undertake adaptive changes for the forthcoming AI economic revolution.

This paper provides an overview of the new Securities Law (“the Law”) of the People’s Republic of China, promulgated at the end of 1998. The analysis will be based on the objective of providing good quality control. The writer will ask whether the Law is sufficiently clear in setting up a securities law system in the PRC. The paper will conclude that the Law falls short of this goal by a considerable margin. This is mainly due to ambiguities in the Law. In addition, inherent characteristics of the PRC legal system also contribute towards this conclusion.

Neurotechnologies such as brain-computer interfaces (BCIs) are rapidly moving out of laboratories and onto frontline employees' (FLEs) heads. BCIs offer thought-controlled device operation and real-time adjustment of work tasks based on employees’ mental states, balancing the potential for optimal well-being with the risk of exploitative employee treatment. Despite its profound implications, a considerable gap exists in understanding how BCIs affect FLEs. This article’s purpose is to investigate BCIs’ impact on FLEs’ well-being.

This article uses a conceptual approach to synthesize interdisciplinary research from service marketing, neurotechnology and well-being.

This article highlights the expected impact from BCIs on the work environment and conceptualizes what BCIs entail for the service sector and the different BCI types that may be discerned. Second, a conceptual framework is introduced to explicate BCIs’ impact on FLEs’ well-being, identifying two mediating factors (i.e. BCI as a stressor versus BCI as a resource) and three categories of moderating factors that influence this relationship. Third, this article identifies areas for future research on this important topic.

Service firms can benefit from integrating BCIs to enhance efficiency and foster a healthy work environment. This article provides managers with an overview of BCI technology and key implementation considerations.

This article pioneers a systematic examination of BCIs as workplace technology, investigating their influence on FLEs’ well-being.

The commercial stainless steels have been used extensively in the biomedicine application and their electrochemical behaviour in the simulated body fluid (SBF) are not uncovered obviously. In this research, the corrosion resistance of the commercial stainless steel of Fe–17Cr–xNi alloys (x = 4, 8, 10 and 14) has been studied. This study aims to evaluate the rate of corrosion and corrosion resistance of some Fe–Cr–Ni alloys in SBF at 37°C.

In this research, the corrosion resistance of the commercial stainless steel of Fe–17Cr–xNi alloys has been studied using open circuit potential, electrochemical impedance spectroscopy and potentiodynamic polarization in the SBF at 37°C and pH 7.4 for a week. Also, the surface morphology of the four alloys was investigated using scanning electron microscopy, elemental composition was obtained via energy dispersive spectroscopy and the crystal lattice structure of Fe–17Cr–xNi alloys was obtained using X-ray diffraction technique. The chemical structure of the protective oxide film has been examined by X-ray photoelectron spectroscopy (XPS) and metals ions released into the solution have been detected after different immersion time using atomic absorption spectroscopy.

The results revealed that the increase of the Ni content leads to the formation of the stable protective film on the alloys such as the Fe–17Cr–10Ni and Fe–17Cr–14Ni alloys which possess solid solution properties. The Fe–17Cr–14Ni alloy displayed highest resistance of corrosion, notable resistance for localized corrosion and the low corrosion rate in SBF because of the formation of a homogenously protective oxide film on the surface. The XPS analysis showed that the elemental Fe, Cr and Ni react with the electrolyte medium and the passive film is mainly composed of Cr₂O₃ with some amounts of Fe(II) hydroxide at pH 7.4.

This work includes important investigation to use commercial stainless steel alloys for biomedical application.