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In situations where the crew is reduced, the optimization of crew task allocation and sequencing (CTAS) can significantly enhance the operational efficiency of the man-machine system by rationally distributing workload and minimizing task completion time. Existing related studies exhibit a limited consideration of workload distribution and involve the violation of precedence constraints in the solution process. This study proposes a CTAS method to address these issues.

The method defines visual, auditory, cognitive and psychomotor (VACP) load balancing objectives and integrates them with workload balancing and minimum task completion time to ensure equitable workload distribution and task execution efficiency, and then a multi-objective optimization model for CTAS is constructed. Subsequently, it designs a population initialization strategy and a repair mechanism to maintain sequence feasibility, and utilizes them to improve the non-dominated sorting genetic algorithm III (NSGA-III) for solving the CTAS model.

The CTAS method is validated through a numerical example involving a mission with a specific type of armored vehicle. The results demonstrate that the method achieves equitable workload distribution by integrating VACP load balancing and workload balancing. Moreover, the improved NSGA-III maintains sequence feasibility and thus reduces computation time.

The study can achieve equitable workload distribution and enhance the search efficiency of the optimal CTAS scheme. It provides a novel perspective for task planners in objective determination and solution methodologies for CTAS.

Through the scientific and reasonable evaluation of the site selection of the emergency material reserve, the optimal site selection scheme is found, which provides reference for the future emergency decision-making research.

In this paper, we have chosen three primary indicators and twelve secondary indicators to construct an assessment framework for the determination of suitable locations for storing emergency material reserves. By mean of the improved entropy weight-order relationship weight determination method, the evaluation model of kullback leibler-technique for order preference by similarity to an ideal solution (KL-TOPSIS) emergency material reserve location based on relative entropy is established. On this basis, 10 regional storage sites in Beijing are selected for evaluation.

The results show that the evaluation model of the location of emergency material reserve not only respects the objective knowledge, but also considers the subjective information of the experts, which makes the ranking result of the location of the emergency material reserve more accurate and reliable.

Firstly, the modification factor is added to the calculation formula of traditional entropy weight method to complete the improvement of entropy weight method. Secondly, the order relation analysis method is used to assign subjective weights to the indicators. The principle of minimum information entropy is introduced to determine the comprehensive weight of the index. Finally, KL distance and TOPSIS method are combined to determine the relative entropy and proximity degree of alternative solutions and positive and negative ideal solutions, and the scientific and effective of the method is proved by case study.

Drawing on the job demands-resources theory (JD-R), this study aims to discuss the relationship between paradoxical leadership and job crafting (approach and avoidance), considering the moderating role of overwork climate and organisational identification in two cultural context (China and Poland).

The research was conducted on employees from diversified organisations in two different cultural context: China (N = 408) and Poland (N = 400). Statistical verifications of the three-way interaction effect were conducted with Jamovi version 2.3 and multigroup analysis with SPSS AMOS version 29.

The results showed that employees who perceive high levels of paradoxical leadership and overwork climate as well as possess a high level of organisational identification engage stronger in job crafting, both approach and avoidance. Moreover, the results demonstrated that the dimensions of culture: individualism-collectivism moderate the relationship between the variables tested, in such a way that the relationship is stronger with the lower level of individualism.

This study has two limitations: its cross-sectional design and the use of self-reported questionnaire data.

The study expands knowledge of the relationship between paradoxical leadership and job crafting in two different cultural contexts.

Drawing on the paradox perspective and the Job Demands-Resources Model (JD-R), we investigate how paradoxical leadership behavior (PLB) affects employee adaptive performance.

Conducted a multi-wave field study with a sample of 64 leaders and 224 subordinates (study 1), and a quasi-experiment involving 156 participants (study 2). The collected data were analyzed using ANOVA and HLM techniques.

Both studies reveal that (1) PLB exhibits a positive association with employee adaptive performance, (2) employee paradox mindset and role stress partly mediated the relationship between PLB and employee adaptive performance, (3) the indirect effects of PLB on employee adaptive performance through employee paradox mindset and role stress are moderated by employee gender-role identity (GRI).

This research developed a moderated mediation model to examine the potential impact of PLB on employee adaptive performance, which contributes to the literature by integrating the paradox perspective and emphasizing the effectiveness of combining “top-down” and “bottom-up” leadership approaches. Moreover, we elucidate the underlying mechanisms through which PLB facilitates employees in effectively managing work role tensions to enhance adaptive performance Finally, this study also extends the investigation of the contextual efficacy of PLB by incorporating GRI as a moderator.

The study investigates the motivations, learning experiences and impacts of Chilean student mobility in China, focusing on postgraduate students. It analyzes how this education has influenced their professional trajectories and Sino-Chilean relations.

The methodology employs a qualitative approach, based on 13 semi-structured interviews, with an analysis covering aspects such as the reasons for studying in China, the acquisition of Mandarin Chinese, the academic experience and professional projections.

The research concludes that these students, trained in China, significantly contribute to strengthening bilateral ties in various fields, highlighting cultural diplomacy as a key factor in expanding collaboration between the two countries.

Additionally, it underscores the need to consider student mobility as an essential component of relations between Chile and China, in particular, and among different Global South countries in general, transcending the limitations of financing criteria and the Eurocentric orientation that predominates in the internationalization policies of Chilean higher education.

The ionization of the air surrounding the phase conductor in high-voltage transmission lines results in a phenomenon known as the Corona effect. To avoid this, Corona rings are used to dampen the electric field imposed on the insulator. The purpose of this study is to present a fast and intelligent surrogate model for determination of the electric field imposed on the surface of a 120 kV composite insulator, in presence of the Corona ring.

Usually, the structural design parameters of the Corona ring are selected through an optimization procedure combined with some numerical simulations such as finite element method (FEM). These methods are slow and computationally expensive and thus, extremely reducing the speed of optimization problems. In this paper, a novel surrogate model was proposed that could calculate the maximum electric field imposed on a ceramic insulator in a 120 kV line. The surrogate model was created based on the different scenarios of height, radius and inner radius of the Corona ring, as the inputs of the model, while the maximum electric field on the body of the insulator was considered as the output.

The proposed model was based on artificial intelligence techniques that have high accuracy and low computational time. Three methods were used here to develop the AI-based surrogate model, namely, Cascade forward neural network (CFNN), support vector regression and K-nearest neighbors regression. The results indicated that the CFNN has the highest accuracy among these methods with 99.81% R-squared and only 0.045468 root mean squared error while the testing time is less than 10 ms.

To the best of the authors’ knowledge, for the first time, a surrogate method is proposed for the prediction of the maximum electric field imposed on the high voltage insulators in the presence Corona ring which is faster than any conventional finite element method.

This study aims to improve the Unified Theory of Acceptance and Use of Technology (UTAUT) model by examining technological anxiety and other influential factors on international students' adoption of mobile learning (m-learning) during COVID-19 emergency remote teaching (ERT).

This study utilized the modified UTAUT framework to test hypotheses through a cross-sectional survey method. Participants were university students studying Chinese as a foreign language who were selected using a convenience sampling approach. An online questionnaire was then administered. The data collected from the surveys were analyzed using the partial least squares method with SmartPLS 4 software.

The study examined 16 hypotheses and found support for six of them. The results confirmed that performance expectancy (PE) is a significant predictor of behavioral intention (BI), and anxiety influences both PE and effort expectancy. The negative effect of social influence on anxiety was found to be significant, while facilitating conditions had a negative impact on learners' self-efficacy. The model fit indices indicated a good overall fit for the model.

This study presents a valuable contribution to the literature on m-learning in emergency education by incorporating technological anxiety into the enhanced UTAUT model. Examining the relationships between the key factors of the model provides a better understanding of learners' intentions and can inspire researchers to establish new theoretical foundations to evaluate the roles of these factors in diverse educational settings.

The study found that performance expectations are linked to learners' intentions, and anxiety indirectly affects BIs to use mobile learning platforms. Thus, these platforms should be designed to meet learners' expectations with minimum effort and eliminate anxiety triggers to facilitate ease of use. Language curriculum developers and policymakers should incorporate mobile learning applications to support diverse language skills, address students' needs and encourage their use through professional development opportunities for instructors.

Social factors have been found to significantly influence anxiety levels among learners. Therefore, it is crucial for teachers and family members to play an essential role in mitigating anxiety's adverse effects. Discussing related issues can enhance the quality of mobile learning and stimulate social initiative by providers, ultimately improving the learning experience for all learners, regardless of their location or circumstances. This can also contribute to the growth and development of society.

This study contributes to the originality of m-learning development by proposing an enhanced UTAUT model that considers anxiety and emphasizes the critical role of foreign learners' BIs. It provides fundamental guidelines for designing and evaluating m-learning in ERT contexts.

The purpose of this work is to optimize the monitoring of vibrations on dynamometric test rigs for railway brakes. This is a quite demanding application considering the continuous increase of performances of high-speed trains that involve higher testing specifications for brake pads and disks.

In this work, authors propose a mixed approach in which relatively simple finite element models are used to support the optimization of a diagnostic system that is used to monitor vibration levels and rotor-dynamical behavior of the machine. The model is calibrated with experimental data recorded on the same rig that must be identified and monitored. The whole process is optimized to not interfere with normal operations of the rig, using common inertial sensor and tools and are available as standard instrumentation for this kind of applications. So at the end all the calibration activities can be performed normally without interrupting the activities of the rig introducing additional costs due to system unavailability.

Proposed approach was able to identify in a very simple and fast way the vibrational behavior of the investigated rig, also giving precious information concerning the anisotropic behavior of supports and their damping. All these data are quite difficult to be found in technical literature because they are quite sensitive to assembly tolerances and to many other factors. Dynamometric test rigs are an important application widely diffused for both road and rail vehicles. Also proposed procedure can be easily extended and generalized to a wide value of machine with horizontal rotors.

Most of the studies in literature are referred to electrical motors or turbomachines operating with relatively slow transients and constant inertial properties. For investigated machines both these conditions are not verified, making the proposed application quite unusual and original with respect to current application. At the same time, there is a wide variety of special machines that are usually marginally covered by standard testing methodologies to which the proposed approach can be successfully extended.

Individuals show different environmental preferences, often influenced by their personality types. However, instances arise where the alignment of an individual’s personality and the architectural environment disappears, resulting in a mismatch. Consequently, the purpose of this study considers the urgent need to acknowledge and understand the complex interplay between architecture and individual personality traits.

The research method is based on the correlation between the variables, which is calculated by the significant assessment of the sample population and with SmartPLS. Finally, the findings and results of the research in relation to personality components and architectural aspects indicate the existence of a relationship. In the end, this study establishes correlations among variables and conclusions are drawn through systematic logical deductions.

The research findings underscore a compelling relationship between distinct personality components and various architectural facets. Furthermore, psychological cohesiveness within distinct social cohorts emerges as a pivotal factor influencing the relationship between individuals and architecture. In this regard, the main aspects of environmental preferences (surprise, cryptic, etc.) and personality types (neuroticism, extroversion, etc.) based on their significance and the factors affecting it in sub-components, create direct or indirect relationships. Additionally, the determination of the relationships created in each of these components is specified based on Image 12, and the path of creating architectural patterns can be considered according to that.

The results of the research show that the correlation between personality and physical components in different social groups is an effective issue in the relationship between human and the environment. It can also be considered as a factor for improving the quality of architectural design and creating a favorable cultural atmosphere in the environment. This issue has caused a connection between architecture and human personality, which creates the ground for improving the relationship between them. Also, architecture is placed by adapting to the personality and psychological needs of people and has an effective role in the quality of their relationships in organizing and expanding the environment.

This study examines whether Confucian culture can promote enterprise total factor productivity (TFP), and it also studies how transmission mechanism works on enterprise TFP.

Based on the data of A-share listed companies on Shanghai and Shenzhen stock markets from 2008 to 2019, this study measures the influence of Confucian culture on enterprise TFP by the number of Confucian academies and Confucian temples within three radius ranges of a company's registered address.

The empirical results show that Confucian culture has a positive effect on the enterprise TFP. The transmission mechanism test shows that Confucian culture can promote the TFP of Chinese enterprises through reducing agency cost, improving agency efficiency and enhancing innovation.

The findings in this study provide implications for policymakers, scholars and enterprises. The results show that Confucian culture can enhance the TFP of Chinese enterprises. Especially in emerging markets including China, the Confucian culture, as an informal institution, can effectively complement formal institutions, promoting enterprise TFP.

This study expands the literature on Confucian culture in two aspects: the influence of Confucian culture on TFP and its transmission mechanism. To the authors' knowledge, this is the first study to identify a link between Confucian culture and enterprise TFP.