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This paper aims to study the tribological characteristics of the electrical contact system under different displacement amplitudes.

First, the risk frequency of real nuclear safety distributed control system (DCS) equipment is evaluated. Subsequently, a reciprocating friction test device which is characterized by a ball-on-flat configuration is established, and a series of current-carrying tribological tests are carried out at this risk frequency.

At risk frequency and larger displacement amplitude, the friction coefficient visibly rises. The reliability of the electrical contact system declines as amplitude increases. The wear morphology analysis shows that the wear rate increases significantly and the degree of interface wear intensifies at a larger amplitude. The wear area occupied by the third body layer increases sharply, and the appearance of plateaus on the surface leads to the increase of friction coefficient and contact resistance. EDS analysis suggests that oxygen elements progressively arise in the third layer as a result of increased air exposure brought on by larger displacement amplitude.

Results are significant for recognizing the tribological properties of electrical connectors in nuclear power control systems.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0098/

Nowadays, more and more Chinese consumers purchase luxury goods on live streaming platforms. However, the existing literature rarely focuses on this emerging phenomenon. This article attempts to construct a theoretical model based on the perceived value theory to explain this phenomenon.

In total, 354 online questionnaires are collected, and the partial least square structural equation model is used to analyze the model empirically.

The results show that consumers' perceived luxury values (financial value, functional value, individual value and social value) have a significant and positive effect on customer engagement, which further leads to purchase intention.

In view of fact that there is a big difference between luxury goods and nonluxury goods, yet the existing literature rarely distinguishes between luxury goods and nonluxury goods in the context of live streaming shopping, this article attempts to use perceived value theory to examine consumers' luxury purchase intentions in live streaming shopping and explores whether customer engagement is a mediating mechanism of perceived luxury values that influences purchase intention in live streaming.

The aim of this paper is to solve the problem of low accuracy of traditional fatigue crack growth (FCG) prediction methods.

The GMSVR model was proposed by combining the grey modeling (GM) and the support vector regression (SVR). Meanwhile, the GMSVR model parameter optimal selection method based on the artificial bee colony (ABC) algorithm was presented. The FCG prediction of 7075 aluminum alloy under different conditions were taken as the study objects, and the performance of the genetic algorithm, the particle swarm optimization algorithm, the n-fold cross validation and the ABC algorithm were compared and analyzed.

The results show that the speed of the ABC algorithm is the fastest and the accuracy of the ABC algorithm is the highest too. The prediction performances of the GM (1, 1) model, the SVR model and the GMSVR model were compared, the results show that the GMSVR model has the best prediction ability, it can improve the FCG prediction accuracy of 7075 aluminum alloy greatly.

A new prediction model is proposed for FCG combined the non-equidistant grey model and the SVR model. Aiming at the problem of the model parameters are difficult to select, the GMSVR model parameter optimization method based on the ABC algorithm was presented. the results show that the GMSVR model has better prediction ability, which increase the FCG prediction accuracy of 7075 aluminum alloy greatly.