PurposeBased on the theory of social identity mechanism, this study aimed to investigate the associations with millennial consumers' need for uniqueness (NFU), susceptibility to peer influence (SPI) and attitudes towards luxury brands (ALB) under the cross-cultural context. The mediating effect of fashion innovativeness (FI) and the moderating effect of culture were examined.Design/methodology/approachThe data for this study were collected through a survey from 217 millennials in Shanghai and 268 millennials in Tokyo. Moderation analysis and mediation analysis using Hayes PROCESS macro were applied to test proposed hypotheses.FindingsResults show that NFU and SPI have a significantly positive effect on millennials' ALB, and fashion innovativeness plays a mediating role in this process. Furthermore, the positive impact of NFU on millennials' ALB for relatively individualistic cities (Shanghai) is stronger than for relatively collectivist cities (Tokyo). The positive impact of susceptibility to informative influence (SII) on millennials' ALB for Tokyo is stronger than for Shanghai.Practical implicationsThe research results suggest how different cultures can support marketers in effectively carrying out their business strategy.Originality/valueUnder the cross-cultural background, the social identity mechanism behind the attitudes of millennials towards luxury brands has been widely recognised. However, little is known about how culture could moderate the social identity mechanism behind millennials' ALB. By analysing these mechanisms, this study compares the cultures of Shanghai and Tokyo and expands the previous research achievements.
Polyimide (PI) films with excellent heat resistance and outstanding mechanical properties have been widely researched in microelectronics and aerospace fields. However, most PI films can only be used under ordinary conditions due to their instability of dimension. The fabrication of multifunctional PI films for harsh conditions is still a challenge. Herein, flexible, low coefficient of thermal expansion (CTE) and improved mechanical properties films modified by carboxylated carbon nanotube (C-CNT) were fabricated. Acid treatment was adapted to adjust the surface characteristics by using a mixture of concentrated H2SO4/HNO3 solution to introduce carboxyl groups on the surface and improve the interfacial performance between the CNT and matrix. Moreover, different C-CNT concentrations of 0, 1, 3, 5, 7, and 9 wt.% were synthesized to use for the PI film fabrication. The results demonstrated that the 9 wt.% and 5 wt.% C-CNT/PI films possessed the lowest CTE value and the highest mechanical properties. In addition, the thermal stability of the C-CNT/PI films was improved, making them promising applications in precise and harsh environments.
In this study, the oxygen plasma and silane coupling agent composite treatment was used to modify the polyimide fiber surface to improve the interfacial properties. The oxygen plasma treatment introduced active groups on the fiber surface, which facilitated the grafting of silane coupling agent to the fiber surface. The surface morphology and chemical composition of fibers were characterized by scanning electron microscope and X-ray photoelectron spectroscopy. The results showed that after plasma treatment, the etching spots on the fiber surface increased with the plasma treatment time, and the surface O atom content, O/C ratio and C–O(H) bond ratio reached the highest value at 27 min plasma treatment. After the composite treatment, the surface Si atomic content reached the highest value after 27 min plasma pretreatment. Moreover, polyimide/polyamic acid unidirectional reinforced composites were prepared. In polyimide/polyamic acid composites, the interfacial shear strength of polyimide fibers first increased and then decreased with plasma treatment time, both in oxygen plasma treatment and in composite treatment, and increased by up to 36.98% and 61.68% respectively compared. In addition, the transverse tensile strength of polyimide/polyamic acid composites increased by 103.73% after composite treatment compared with the pristine specimens.
A new hydrodynamic artificial intelligence (AI) detection method is proposed to realize the accurate detection of internal solitary waves (ISWs) by the underwater vehicle. Two deep convolution neural network structures are established to predict the relative position between the underwater vehicle and ISW and the flow field around the underwater vehicle. By combining field observation data and the computational fluid dynamics (CFD) method, accurate numerical simulation of the motion of the underwater vehicle in a real ISW environment is achieved. The training process for the neural network is implemented by building a dataset from the above results. It is shown that the position prediction accuracy of the network for ISW is larger than 95%. For the prediction of the flow field around the underwater vehicle, it is found that the addition of the convolutional block attention module (CBAM) can increase the prediction accuracy. Moreover, the reduction of the number of sensors by the dynamic mode decomposition (DMD) method and k-means clustering method is realized. The accuracy can still reach 92% even when the number of sensors is reduced. This study is the first to use hydrodynamic signals for the detection of ISW, which can enhance the navigation safety of underwater vehicles.
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