Localized social media marketing of luxury fashion brands in China: impact on consumer perceptions

Objectives The first objective of this study was to examine the main motivations behind luxury consumption among Chinese consumers and whether these values have been addressed on social media marketing. The second objective was to explore their attitudes towards localized social media marketing of luxury brands. The final objective was to investigate how might localization on social media affect the purchase intention of Chinese luxury consumers. Summary The study finds that there are mainly five values driving Chinese consumers to purchase luxury: aestheticism and authenticity, long-term investment, snob and bandwagon effect, cost-effectiveness and self-realization. Yet, not all values are reflected and supported by current social media marketing of luxury brands. The study also shows that consumers in China are generally indifferent to localized marketing messages, which explains the little impact localization on social media has in terms of increasing purchase intention. However, it is suggested that appropriate localization could indeed increase brand awareness and visibility and could improve consumer’s perception about the luxury brands. Conclusions Although there is insufficient evidence supporting the positive impact localization might have on increasing purchase intention, luxury brands should update their understanding of the Chinese market, develop a sophisticated social media strategy and implement certain localization in order to reach wider audience. Meanwhile, luxury brands should avoid excessive social media presence and superficial localization attempts

A Natural Wind Defrosting, Nano-coated Antibacterial Self-cleaning Energy-saving Health Air-cooled Refrigerator

The air-cooled frost-free household refrigerator is popular in the market because of its large size and frost-free size. However, the evaporator defrost process consumes a large amount of electrical energy to limit the wide spread of this refrigerator, at the same time because of its structural problems, resulting in its evaporator, air duct can not be artificially cleaned, leading to the growth of bacteria, pollution of food storage. This research has developed a self-cleaning energy-saving health refrigerator that uses indoor natural wind defrosting, ultra-hydrophilic nano-titanium dioxide coating photocatalytic sterilization and sterilization. After experimental comparison, under the same operating time of the same operating conditions, the refrigeration mode saves 1.5%, the defrost process saves 95%, reduces the amount of frosting by 23%, the temperature changes of the freezer is less than 7 ℃ , and the desterilization rate of nano-coated reaches 80%

Emerging applications of integrated optical microcombs for analogue RF and microwave photonic signal processing

We review new applications of integrated microcombs in RF and microwave photonic systems. We demonstrate a wide range of powerful functions including a photonic intensity high order and fractional differentiators, optical true time delays, advanced filters, RF channelizer and other functions, based on a Kerr optical comb generated by a compact integrated microring resonator, or microcomb. The microcomb is CMOS compatible and contains a large number of comb lines, which can serve as a high performance multiwavelength source for the transversal filter, thus greatly reduce the cost, size, and complexity of the system. The operation principle of these functions is theoretically analyzed, and experimental demonstrations are presented.Comment: 16 pages, 8 figures, 136 References. Photonics West 2018 invited paper, expanded version. arXiv admin note: substantial text overlap with arXiv:1710.00678, arXiv:1710.0861

Detailed simulation of LOX/GCH4 flame-vortex interaction in supercritical Taylor-Green flows with machine learning

Accurate and affordable simulation of supercritical reacting flow is of practical importance for developing advanced engine systems for liquid rockets, heavy-duty powertrains, and next-generation gas turbines. In this work, we present detailed numerical simulations of LOX/GCH4 flame-vortex interaction under supercritical conditions. The well-established benchmark configuration of three-dimensional Taylor-Green vortex (TGV) embedded with a diffusion flame is modified for real fluid simulations. Both ideal gas and Peng-Robinson (PR) cubic equation of states are studied to reveal the real fluid effects on the TGV evolution and flame-vortex interaction. The results show intensified flame stretching and quenching arising from the intrinsic large density gradients of real gases, as compared to that for the idea gases. Furthermore, to reduce the computational cost associated with real fluid thermophysical property calculations, a machine learning-based strategy utilising deep neural networks (DNNs) is developed and then assessed using the three-dimensional reactive TGV. Generally good prediction accuracy is achieved by the DNN, meanwhile providing a computational speed-up of 13 times over the convectional approach. The profound physics involved in flame-vortex interaction under supercritical conditions demonstrated by this study provides a benchmark for future related studies, and the machine learning modelling approach proposed is promising for practical high-fidelity simulation of supercritical combustion