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In order to solve the problems faced by First Order Reliability Method (FORM) and First Order Saddlepoint Approximation (FOSA) in structural reliability optimization, this paper aims to propose a new Reliability-based Design Optimization (RBDO) strategy for offshore engineering structures based on Original Probabilistic Model (OPM) decoupling strategy. The application of this innovative technique to other maritime structures has the potential to substantially improve their design process by optimizing cost and enhancing structural reliability.

In the strategy proposed by this paper, sequential optimization and reliability assessment method and surrogate model are used to improve the efficiency for solving RBDO. The strategy is applied to the analysis of two marine engineering structure cases of ship cargo hold structure and frame ring of underwater skirt pile gripper. The effectiveness of the method is proved by comparing the original design and the optimized results.

In this paper, the proposed new RBDO strategy is used to optimize the design of the ship cargo hold structure and the frame ring of the underwater skirt pile gripper. According to the results obtained, compared with the original design, the structure of optimization design has better reliability and stability, and reduces the risk of failure. This optimization can also better balance the relationship between performance and cost. Therefore, it is recommended for related RBDO problems in the field of marine engineering.

In view of the limitations of FORM and FOSA that may produce multiple MPPs for a single performance function, the new RBDO strategy proposed in this study provides valuable insights and robust methods for the optimization design of offshore engineering structures. It emphasizes the importance of combining advanced MPP search technology and integrating SORA and surrogate models to achieve more economical and reliable design.

Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors.

We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis.

The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution.

Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.

The purpose is to explore the improvement mechanism of coating and laser micro-texture on the surface properties of cemented carbide, so as to give full play to the technical advantages of both and improve the overall surface properties of the material.

The surface hardness of the coating was measured by a microhardness tester, the surface element composition of the coating was tested by an energy spectrum analyzer and the phase was measured by an X-ray diffractometer to observe the surface morphology after the friction and wear experiment.

Laser will generate new oxide and nitride films on the surface of the coating, which will improve the hardness of the coating surface and the bonding strength between the coating and the substrate. The surface micro-texture can collect wear debris during the friction process, reduce abrasive wear and play a good role in inhibiting the expansion of the coating failure zone.

Most of the research on traditional laser coating is to process micro-texture first and then coating. This study is the opposite. In this paper, the modification effect of laser on the coating surface is explored, and the parameters of laser and coating are optimized, which paves the way for the subsequent milling experiments of textured coating tools.

The purpose of this study is to further improve the performance of surface texture, the chemical polishing method was introduced and the effect of it on the surface morphology and tribological properties of the surface texture was investigated.

The surface texture was processed on the surface of 304 stainless steel with laser technology in air medium. Hydrochloric acid solution (pH 2.4 ± 0.05) was selected and used to soak the prepared texture samples for 12 h. The surface morphology and elemental content of the samples were measured with the white light interferometry, SEM and EDS. To obtain the effect of acid corrosion on the tribological properties of textured surfaces, the samples were tested under dry friction and oil lubrication conditions.

The detailed study shows that the melt and burr of surface texture produced with laser processing was reduced due to the corrosion effect of hydrochloric acid. Therefore, the better interfacial tribological properties was obtained due to the improvement of surface-textured morphology.

The main contribution of this work is to provide a new reference for improving surface texture quality. It also lays a foundation for improving the tribological properties of the textured interface.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2023-0094/

The theoretical findings serve as a foundation for further research into understanding sulfide-based solid-state electrolytes, ultimately advancing the progress of all-solid-state batteries.

The electronic properties of Li₇P₃S₁₁ are thoroughly explored through first-principles calculations.

This investigation encompasses the intricate atom-dominated valence and conduction bands, spatial charge density distribution and the breakdown of atom and orbital contributions to van Hove singularities. Additionally, the compound’s wide and discrete energy spectra reflect the substantial variations in bond lengths and its highly anisotropic geometric structure. The complex and nonuniform chemical environment indicates the presence of intricate hopping integrals.

This study provides valuable insights into the critical multiorbital hybridizations occurring in the Li-S and P-S chemical bonds. To validate the theoretical predictions, experimental techniques can be employed. By combining theoretical predictions with experimental data, a comprehensive understanding of the geometric and electronic characteristics of Li₇P₃S₁₁ can be achieved.

This paper aims to conceptualize a framework drawn upon the self-regulation theory to study the effect of system quality features on the continuous usage intention of social network users. The study explores the relationship among the selected variables and identifies the determinants of continuous usage intention of social networks.

A survey method was used to collect data from 301 male and 311 female social network users to test the research model with the help of the structural equation modelling technique.

The results show a difference between male and female social media users for the continuous usage intention of social networks. A substantial difference in the relationship was seen between the attitude and continuous usage intention, where female social network users had a more robust and significant relationship than their male counterparts.

This study uses the self-regulation theory to understand the continuous usage intention of social networks in the Indian context. This research study contributes to the existing literature on social networks/social media and the adoption intention.

The 21st century has brought the business model earth-shaking changes, especially since the Corona Virus Disease 2019 (COVID-19) epidemic at the end of 2019. Now, the epidemic normalization is slowing down China's rapid development. However, technological development, like artificial intelligence (AI), is unstoppable and is transforming China's economic growth modes from factor-driven to innovation-driven systems. Therefore, it is necessary to study further the new changes in labor entrepreneurship and innovation business models and their mechanism of action on economic growth.

This work studies how innovative human capital (IHC) uses AI and other scientific and technological (S&T) innovation technologies to promote China's innovation-driven economic growth model transformation from the labor entrepreneurship and innovation perspective.

The research shows that the entrepreneurial innovation ability of IHC can increase marginal return and output multiplier effect. It changes the traditional business model and promotes China's economic growth and innovation development. At the same time, this work analyzes China's inter-provincial panel data through the panel smooth transition regression (PSTR) model. It concludes that there is a nonlinear relationship between IHC and the output of innovative achievements. The main body presents three stages of nonlinear changes: first rising, then slightly declining, and rising so far.

The finding provides a direction for solving the problem of slow economic growth and accelerating the transformation of economic growth mode under epidemic normalization.

The purpose of this paper is to develop a novel recommendation method using online reviews with emotional preferences for facilitating online purchase decisions. This leads to better use of information-rich online reviews for providing users with personalized recommendations.

A novel method is developed for producing personalized recommendations in online purchase decision-making. Such a method fuses the belief structure and the Shapley function together to effectively deal with the emotional preferences in online reviews and adequately tackle the interaction existent between product criteria with the use of a modified combination rule for making better online recommendations for making online purchase decisions.

An example is presented for demonstrating the applicability of the method for facilitating online purchase. The results show that the recommendation using the proposed method can effectively improve customer satisfaction with better purchase decisions.

The proposed method can better utilize online reviews for satisfying personalized needs of consumers. The use of such a method can optimize interface design, refine customer needs, reduce recommendation errors and provide personalized recommendations.

The proposed method adequately considers the characteristics of online reviews and the personalized needs of customers for providing customers with appropriate recommendations. It can help businesses better manage online reviews for improving customer satisfaction and create greater value for both businesses and customers.

This study conducts a comparative study on the performance of reliability assessment methods based on adaptive surrogate models to accurately assess the reliability of automobile components, which is critical to the safe operation of vehicles.

In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components.

By comparing the reliability evaluation problems of four automobile components, the Kriging model and Polynomial Chaos-Kriging (PCK) have better robustness. Considering the trade-off between accuracy and efficiency, PCK is optimal. The Constrained Min-Max (CMM) learning function only depends on sample information, so it is suitable for most surrogate models. In the four calculation examples, the performance of the combination of CMM and PCK is relatively good. Thus, it is recommended for reliability evaluation problems of automobile components.

Although a lot of research has been conducted on adaptive surrogate-model-based reliability evaluation method, there are still relatively few studies on the comprehensive application of this method to the reliability evaluation of automobile component. In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components. Specially, a superior surrogate-model-based reliability evaluation method combination is illustrated in this study, which is instructive for adaptive surrogate-model-based reliability analysis in the reliability evaluation problem of automobile components.

Corporate social responsibility (CSR) and innovation are the two main approaches firms utilize to promote sustainable development. However, as yet, scholars have reached no consensus regarding their precise impact on construction firm performance (CFP), hindering efforts to implement effective sustainable development strategies that improve CFP. In view that a simple linear relationship may not be sufficient to capture their precise pattern, this study aims to unveil the nonlinear impact of CSR and innovation on CFP, especially when construction firms take up a distinct competitive position.

This study first proposed four hypotheses to establish a new theoretical model by incorporating CSR, innovation, CFP and construction firms' competitive position (CFCP). Then the model was tested by using 292 annual observations collected from 75 construction firms in China. A multiple regression model analysis was carried out to analyze the survey data and validate the hypotheses.

The results reveal that both CSR and innovation have a U-shaped impact on the price-to-book ratio of a construction firm, a specific CFP measure. CFCP negatively moderates the U-shaped relationship between CSR and CFP, but positively moderates the U-shaped relationship between innovation and CFP.

This study goes beyond a simple linear view, instead of unveiling the nonlinear U-shaped effects of CSR and innovation on CFP that deepen the understanding of their complex relationships in the construction industry and makes construction firms aware that CSR and innovation can only improve performance if they reach a certain level. The moderating role of CFCP provides important implications for construction firms seeking to adopt appropriate competitive strategies related to social responsibility and innovation that both promote CFP and achieve sustainable development.