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The purpose of this study is to propose a precise and standardized strategy for numerically simulating vehicle aerodynamics.

Error sources in computational fluid dynamics were analyzed. Additionally, controllable experiential and discretization errors, which significantly influence the calculated results, are expounded upon. Considering the airflow mechanism around a vehicle, the computational efficiency and accuracy of each solution strategy were compared and analyzed through numerous computational cases. Finally, the most suitable numerical strategy, including the turbulence model, simplified vehicle model, calculation domain, boundary conditions, grids and discretization scheme, was identified. Two simplified vehicle models were introduced, and relevant wind tunnel tests were performed to validate the selected strategy.

Errors in vehicle computational aerodynamics mainly stem from the unreasonable simplification of the vehicle model, calculation domain, definite solution conditions, grid strategy and discretization schemes. Using the proposed standardized numerical strategy, the simulated steady and transient aerodynamic characteristics agreed well with the experimental results.

Building upon the modified Low-Reynolds Number k-e model and Scale Adaptive Simulation model, to the best of the authors’ knowledge, a precise and standardized numerical simulation strategy for vehicle aerodynamics is proposed for the first time, which can be integrated into vehicle research and design.

This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.

In the era of multiple global disruptions, firms are finding it to continue their business. MSMEs are impacted more as they have constrained resources. Organizational flexibility has emerged as an organizational and management principle that would help firms stay competitive even in volatile markets. This study aims to present a set of guidelines and insights for MSME managers to implement organizational flexibility in their organizations.

This study uses total interpretive structural modelling to study how the various factors contributing to organizational flexibility behave together. Behavioural theory is used to explain why organizations need to incorporate flexibility, and systems theory of organization is used to explain why an organization needs to have open boundaries.

Organizational flexibility is a principle that may be supported by the systems theory of organization. The study has shown that it is important for MSMEs to have supply chain collaborations to be more flexible. The study also shows pressure from competitors as the key driver that would make a firm more flexible, and that adequate support from management and technological skills are required to drive flexibility in an organization.

Single respondent bias may have occurred in this study. This can be eliminated by interviewing multiple people from the same organization. Further research around the reasoning for linkages can be explored with theory-driven grounded studies.

This study attempts to use a multi-criteria decision-making technique to present insights to managers to help them make their organizations flexible.

With the continuous development of the global COVID-19 epidemic, mobile learning has become one of the most significant learning approaches. The mobile learning resource is the basis of mobile learning; it may directly affect the effectiveness of mobile learning. However, the current learning resources cannot meet users' needs. This study aims to analyze the influencing factors of accepting open data as learning resources among users.

Based on the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT), this study proposed a comprehensive theoretical research model. Data were obtained from 398 postgraduates from several universities in central China. Confirmatory factor analysis was used to determine the reliability and validity of the measurement model. Data has been analyzed using SPSS and AMOS software.

The results suggested that perceived usefulness, performance expectancy, social influence and facilitating conditions have a positive influence on accepting open data as learning resources. Perceived ease of use was not found significant. Moreover, it was further shown in the study that behavioural intention significantly influenced the acceptance of open data as learning resources.

There is a lack of research on open data as learning resources in developing countries, especially in China. This study addresses the gap and helps us understand the acceptance of open data as learning resources in higher education. This study also pays attention to postgraduates' choice of learning resources, which has been little noticed before. Additionally, this study offers opportunities for further studies on the continuous usage of open data in higher education.

This study aims to fabricate a cool phthalocyanine green/TiO₂ composite pigment (PGT) with high near-infrared (NIR) reflectance, good color performance and good heat-shielding performance under sunlight and infrared irradiation.

With the help of anionic and cationic polyelectrolytes, the PGT composite pigment was prepared using a layer-by-layer assembly method under wet ball milling. Based on the light reflectance properties and color performance tested by ultraviolet-visible-NIR spectrophotometer and colorimeter, the preparation conditions were optimized and the properties of PGT pigment with different assembly layers (PGT-1, PGT-3, PGT-5 and PGT-7) were compared. In addition, their heat-shielding performance was evaluated and compared by temperature rise value for their coating under sunlight and infrared irradiation.

The PGT pigment had a core/shell structure, and the PG thickness increased with the self-assembly layers, which made the PGT-3 and PGT-7 pigment show higher color purity and saturation than PGT-1 pigment. In addition, the PGT-3 and PGT-7 pigment showed 11%–16% lower light reflectance in the visible region. However, their light reflectance in the NIR region was similar. Under infrared irradiation the PGT-5 and PGT-7 pigment coating showed 1.1°C–3.4°C and 1.3°C–4.7°C lower temperature rise value than PGT-1 pigment coating and physical mixture pigment coating, respectively. And under sunlight the PGT-3 pigment coating showed 1.5–2.6°C lower temperature rise value than the physical mixture pigment coating.

The layer-by-layer assembling makes the core/shell PGT composite pigment possess low visible light reflectance, high NIR reflectance and good heat-shielding performance.