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This paper aims to conduct a comparative analysis of the scientific performance of distinguished young scholars in China during the pre-award and early stages of their research careers, aiming to provide insights into their growth pattern.

Spearman correlation was used to analyse the correlation between various academic ages and awarding age of the distinguished young scholars. The Wilcoxon matched pairs test was used to analyse variations in their scientific performance across different research stages.

The findings showed that: a) early successful research experiences significantly impact their emergence as outstanding scientists. While a low correlation exists between publication ages and awards, perseverance proves crucial for later-stage academic achievements; b) productivity increases before awards, with notable variations between first-author and non-first-authored publications; c) collaboration intensifies before awards, particularly in non-first author roles. However, discipline-specific variations highlight the importance of smaller teams and first-author roles, especially in the early career stage; d) the correlation between collaboration and productivity depends on research roles, emphasizing the evolving nature of collaboration dynamics as scholars progress in their careers.

This study could offer a reference for formulating well-founded talent training programs and reward mechanisms.

This study developed two presentation modes of scientific articles and evaluated their usability with user experiments.

Two presentation modes of scientific articles, simply referred to as “genre presentation mode” and “argument presentation mode”, were constructed based on their genre structure and argument structure respectively. Their usability was evaluated by being compared against the existing RichHTML presentation mode in the experiments using eye-tracking and questionnaire methods.

The participants who were going to find the specific information of scientific articles rated the genre presentation mode higher than they did with either the argument or the RichHTML presentation mode for effectiveness. In contrast, those who were going to understand the general idea of scientific articles rated both the genre and argument presentation mode higher than they did with the RichHTML mode. In terms of efficiency, the participants took less reading time when the articles of non-native language were presented with the genre mode than they did when the articles were presented with the argument mode. When reading the articles in native language to understand the general idea, the participants took less reading time for the articles presented with the argument mode than they did for the articles presented with the genre mode. In comparison, they took less reading time when the articles were presented with the argument mode if they were going to find specific information. For satisfaction, the genre presentation mode was more popular than the argument mode and the RichHTML mode. However, the participants were less satisfied with the argument presentation mode than the other two when reading in native language and intending to find specific information.

The two presentation modes of scientific articles are found to improve the accuracy of information acquisition, shorten the total reading time and be more acceptable by readers.

Driven by the rapid expansion of online retail and the surge in livestream commerce, the impact of different livestream mode on brand and platform performance has become a critical issue. This paper analyzes the impact of artificial intelligence (AI) and key opinion leader (KOL) livestream on the profitability of brands and the platform, incorporating the effects of horizontal interactions to identify the optimal livestream mode.

This paper develops a model of a platform supply chain involving two brands and a platform, where each brand independently decides whether to utilize KOL or AI livestream. Applying Stackelberg game approach, the study derives equilibria for various livestream scenarios, identifying the optimal livestream mode for both parties. Additionally, the model is extended to incorporate asymmetric market potential and network externality to evaluate their impact on a brand’s choice of livestream mode.

Several interesting and important results are derived in this paper. Firstly, it is found that AI livestream enables brands to leverage network externality and mitigate the market disadvantage, thereby gaining a competitive advantage. Secondly, while KOL livestream promotes trust, the medium KOL commission rates could cause brands to be trapped in a prisoner’s dilemma, and excessively high commission rates may render them less profitable. Thirdly, the KOL commission rate, network externality intensity, horizontal interactions and market disadvantage are critical determinants influencing a brand’s choice of livestream mode.

This study is the first to investigate the effects of horizontal interactions, asymmetric market potential and asymmetric network externality on livestream mode selection by brands within a platform supply chain. The research provides valuable insights into optimizing livestream strategies to enhance brand profitability.

This study aims to investigate the effect of vapor phase corrosion inhibitor (VCI) imidazoline, quinoline and urea on E36 ship steel in simulated marine atmospheric environment.

The inhibitive effect was investigated by weight loss, potentiodynamic polarization, electrochemical impedance and Raman spectroscopy.

The corrosion process was inhibited by adsorption of the three VCIs on the surface of ship steel. The corrosion inhibition mechanism is the adsorption film type. The corrosion inhibitor adsorbs on the metal surface to prevent Cl^- from reaching the surface of the substrate, so as to achieve the corrosion inhibition effect.

To the best of the authors’ knowledge, the work described was original research that has not been published previously and not under consideration for publication elsewhere, in whole or in part.

The purpose of this study is to investigate the dynamic behavior of the ball bearing with cage broken.

By analyzing the complicated relationship and interactions among the ball bearing elements, the dynamic modelling of the ball bearing with broken cage was established, and the dynamic simulations were conducted by solving the ball bearing dynamic equations using varying-step Runge–Kutta integration.

The computational results show that there is considerable distinguishment in the dynamic characteristics between the normal cage and the broken cage of the bears. The broken cage makes the trajectory of the cage erratic, and the vibration amplitude is much bigger than that of the normal cage, which makes the motion of the cage unstable. When one of the cage lintels breaks up, the two adjacent balls will collide with each other; what is worse, this may make the balls crush because of the high amplitude of the collision force. The broken cage makes the cage-race interaction force much larger than that of the normal cage, which could promote the guiding ring and quicken the cage wear-failure.

This study can provide important ideas for the fault identification of the ball bearing with cage broken.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2020-0042/