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Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

This paper aims to determine the most practically applicable color-difference formula for yarn-dyed fabrics woven from warp and weft yarns in different color depths and to establish color-difference tolerance for perceptibility by evaluating yarn-dyed fabrics visually and instrumentally.

A total of 108 sample pairs were evaluated by a panel of 13 observers with perceptibility method under three typical light sources (A, D65 and cool white fluorescent). The data sets were statistically analyzed by the homogeneity of variance test (F-test), analysis of variance, standardized residual sum of squares and performance factor/3.

Light sources had a slight influence on the visual assessments of yarn-dyed fabrics. Among the eight color-difference formulae for measurements of yarn-dyed fabrics, CIEDE2000(2:1:1) outperformed all other tested formulae, and the color tolerance for the perceptibility of CIEDE2000(2:1:1) was 0.62. When the homochromy index (K) of warp and weft yarns of yarn-dyed fabric was lower than 1.25, the color difference based on ΔE*00(2:1:1) between the two samples was acceptable in terms of the color tolerance for perceptibility (i.e. 0.62).

The warp and weft yarns in different color depths could be woven in fabric with a relatively uniform color appearance.

This study could contribute to cost savings by reusing disqualified dyed yarns during the weaving manufacturing process.

Based on the theory of trust and cost-benefit perspective, this paper examines the relationship between citizens’ trust and their digital attitudes by considering the mediating effects of performance expectancy and perceived risk, as well as the moderating effect of media use.

The city digital transformation in Shanghai is chosen as the case in this study. 466 questionnaires were collected through a survey, with Structural Equation Modeling to test the hypotheses in AMOS.

Citizens’ trust of government and trust of technology has no significant direct effect on their digital attitudes. However, performance expectancy mediates between the trust of government and digital attitudes, and perceived risk mediates the effect of trust of technology on attitudes. The use of social media significantly moderates the association between trust of technology and citizens’ attitudes.

Exploring why citizens shape supportive attitudes toward digitalization is critical to achieving digital governance goals in developing countries, especially large cities where digital transformation is accelerating. The originality lies in using cost-benefit analysis as a perspective and media use as a moderator to examine the mechanisms of citizens’ trust and digital attitudes.

Auxetic sandwich structures are gaining attention because of the negative Poisson’s ratio effect offered by these structures. Re-entrant core was one configuration of the auxetic structures. There is a growing concern about the design and behavior of re-entrant cores in aerospace, marine and protection applications. Several researchers proposed various designs of re-entrant core sandwiches with various materials. The purpose of this study is to review the most recent advances in re-entrant core sandwich structures. This review serves as a guide for researchers conducting further research in this wide field of study.

The re-entrant core sandwich structures were reviewed in terms of their design improvements, impact and quasi-static crushing responses. Several design improvements were reviewed including 2D cell, 3D cell, gradient, hierarchical and hybrid configurations. Some common applications of the re-entrant core sandwiches were given at the end of this paper with suggestions for future developments in this field.

Generally, the re-entrant configuration showed improved energy absorption and impact response among auxetic structures. The main manufacturing method for re-entrant core manufacturing was additive manufacturing. The negative Poisson’s ratio effect of the re-entrant core provided a wide area of research.

Generally, re-entrant cores were mentioned in the review articles as part of other auxetic structures. However, in this review, the focus was solely made on the re-entrant core sandwiches with their mechanics.

Introduction: Skill development is crucial in developing economies by enhancing productivity and creating employment opportunities. At the macro level, it also leads to industrial development and economic growth.

Purpose: The research is to identify the types of skills required for increasing the probability of employability of labour. It also aims to define the challenges and opportunities in skill development to drive change.

Need of the Study: Studying opportunities and challenges for skill development in developing economies is essential for achieving sustainable economic growth, reducing poverty, increasing employment opportunities, and promoting global competitiveness.

Research Methodology: Some skills are recognised through research that has been published to determine the skill set needed to increase labour productivity. To draw lessons, some skill development initiatives by various companies are also identified and presented in case studies. Additionally, several government programs are available to assess the possibilities and prospects for skill development in the Indian market.

Practical Implications: The research will be valuable in micro and macro decision making. At the micro level, research is advantageous for a business person to initiate the skill development of its employees by using government schemes. Nations other than India can understand the policy framework for skill development.

Findings: The term ‘skilling’ has become fashionable. Due to the need for skill-based earnings data, only some studies examine the return on skill (ROS) of the labour market. Skill development plays a significant role in bringing change at the micro and macro levels. Hence it is necessary to exploit all opportunities for skill development.

This study aims to propose a more precise method for robust design optimization of mechanical structures with black-box problems, while also considering the efficiency of uncertainty analysis.

The method first introduces a dual adaptive chaotic flower pollination algorithm (DACFPA) to overcome the shortcomings of the original flower pollination algorithm (FPA), such as its susceptibility to poor accuracy and convergence efficiency when dealing with complex optimization problems. Furthermore, a DACFPA-Kriging model is developed by optimizing the relevant parameter of Kriging model via DACFPA. Finally, the dual Kriging model is constructed to improve the efficiency of uncertainty analysis, and a robust design optimization method based on DACFPA-Dual-Kriging is proposed.

The DACFPA outperforms the FPA, particle swarm optimization and gray wolf optimization algorithms in terms of solution accuracy, convergence speed and capacity to avoid local optimal solutions. Additionally, the DACFPA-Kriging model exhibits superior prediction accuracy and robustness contrasted with the original Kriging and FPA-Kriging. The proposed method for robust design optimization based on DACFPA-Dual-Kriging is applied to the motor hanger of the electric multiple units as an engineering case study, and the results confirm a significant reduction in the fluctuation of the maximum equivalent stress.

This study represents the initial attempt to enhance the prediction accuracy of the Kriging model using the improved FPA and to combine the dual Kriging model for uncertainty analysis, providing an idea for the robust optimization design of mechanical structure with black-box problem.

This study aims to evaluate performance and map the science of research on International Organization for Standardization (ISO) 31000 standard through published articles. Specifically, this study determines the current state of the art, identifies research gaps and guides future studies related to ISO 31000.

This work investigates and examines the research papers acquired from the Scopus and Web of Science databases. Inclusion and exclusion criteria were applied to obtain relevant papers. Bibliometric analysis using Biblioshiny was conducted to answer the research objectives.

The results show growing interest in ISO 31000 research but limited interconnectivity among articles. Influential journals have emerged, highlighting key research trends in risk management's (RM) practical application and its significance in organizational decision-making. Key research areas include risk assessment (RA) methods, enterprise RM and system integration, endorsing ISO 31000 as a valuable tool. Future research should prioritize longitudinal studies to track ISO 31000's impact, study effective risk communication strategies, explore sector-specific RM practices and assess ISO 31000's application in emerging technologies.

This research reveals key themes and diverse methods that aid practitioners in customizing industry risk strategies, adapting to emerging trends, engaging global collaboration and improving risk communication. Nevertheless, the study might overlook non-English contributions, urging broader language inclusion for ISO 31000's profundity.

This paper's originality lies in its comprehensive bibliometric analysis of ISO 31000 research, providing valuable insights into the standard's growing significance and global impact. The study identifies key research themes and influential authors, guiding future research and improving RM practices.

This paper aims to introduce the experience-dominant (Ex-D) logic model, which synthesizes the creation, perceptions and outcomes of Ex-D logic. It is designed to offer valuable insights for strategic managerial applications and future research directions.

Employing a qualitative approach by using eight selected product launch events from reviewed 100 event videos and 55 in-depth interviews with industrial managers to develop an Ex-D logic model, and data were coded and analysed via NVivo.

Results show that the firm’s Ex-D logic is operationalized as the mentalizing of the three types of customer needs (service competence, hedonic excitations and meaning making), the materializing of three types of customer experiences and customer journeys (service experience, hedonic experience and brand experience) and the moderating of three types of customer values (service values, hedonic values and brand values).

This study has implications for adding new insights into existing theory on dominant logic and customer experience management and also offers actionable recommendations for managerial applications.

This study sheds light on the importance of Ex-D logic from a strategic point of view and provides an organic view of the firm. It distinguishes firm perspective from customer perspective, firm experience from customer experience and firm journey from consumer journey.

This paper aims to explore the influence of corrosion-deformation interactions (CDI) on the corrosion behavior and mechanisms of 316LN under applied tensile stresses.

Corrosion of metals would be aggravated by CDI under applied stress. Notably, the presence of nitrogen in 316LN austenitic stainless steel (SS) would enhance the corrosion resistance compared to the nitrogen-absent 316L SS. To clarify the CDI behaviors, electrochemical corrosion experiments were performed on 316LN specimens under different applied stress levels. Complementary analyses, including three-dimensional morphological examinations by KH-7700 digital microscope and scanning electron microscopy coupled with energy dispersive spectroscopy, were conducted to investigate the macroscopic and microscopic corrosion morphology and to characterize the composition of corrosion products within pits. Furthermore, ion chromatography was used to analyze the solution composition variations after immersion corrosion tests of 316LN in a 6 wt.% FeCl₃ solution compared to original FeCl₃ solution. Electrochemical experiment results revealed the linear decrease in free corrosion potential with increasing applied stress. Electrochemical impedance spectroscopy results indicated that high tensile stress level damaged the integrity of passivation film, as evidenced by the remarkable reduction in electrochemical impedance. Ion chromatography analyses proved the concentrations increase of NO₃⁻ and NH₄⁺ ion concentrations in the corrosion media after corrosion tests.

The enhanced corrosion resistance of 316LN SS is attributable to the presence of nitrogen.

The scope of this study is confined to the influence of tensile stress on the electrochemical corrosion of 316LN at ambient temperatures; it does not encompass the potential effects of elevated temperatures or compressive stress.

The resistance to stress electrochemical corrosion in SS may be enhanced through nitrogen alloying.

This paper presents a systematic investigation into the stress electrochemical corrosion of 316LN, marking the inaugural study of its impact on corrosion behaviors and underlying mechanisms.

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.