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The purpose of the study is to obtain and analyze vibro-acoustic characteristics.

A unified analysis model for the rotary composite laminated plate and conical–cylindrical double cavities coupled system is established. The related parameters of the unified model are determined by isoparametric transformation. The modified Fourier series are applied to construct the admissible displacement function and the sound pressure tolerance function of the coupled systems. The energy functional of the structure domain and acoustic field domain is established, respectively, and the structure–acoustic coupling potential energy is introduced to obtain the energy functional. Rayleigh–Ritz method was used to solve the energy functional.

The displacement and sound pressure response of the coupled systems are acquired by introducing the internal point sound source excitation, and the influence of relevant parameters of the coupled systems is researched. Through research, it is found that the impedance wall can reduce the amplitude of the sound pressure response and suppress the resonance of the coupled systems. Besides, the composite laminated plate has a good noise reduction effect.

This study can provide the theoretical guidance for vibration and noise reduction.

The current studies on remaining useful life (RUL) prediction mainly rely on convolutional neural networks (CNNs) and long short-term memories (LSTMs) and do not take full advantage of the attention mechanism, resulting in lack of prediction accuracy. To further improve the performance of the above models, this study aims to propose a novel end-to-end RUL prediction framework, called convolutional recurrent attention network (CRAN) to achieve high accuracy.

The proposed CRAN is a CNN-LSTM-based model that effectively combines the powerful feature extraction ability of CNN and sequential processing capability of LSTM. The channel attention mechanism, spatial attention mechanism and LSTM attention mechanism are incorporated in CRAN, assigning different attention coefficients to CNN and LSTM. First, features of the bearing vibration data are extracted from both time and frequency domain. Next, the training and testing set are constructed. Then, the CRAN is trained offline using the training set. Finally, online RUL estimation is performed by applying data from the testing set to the trained CRAN.

CNN-LSTM-based models have higher RUL prediction accuracy than CNN-based and LSTM-based models. Using a combination of max pooling and average pooling can reduce the loss of feature information, and in addition, the structure of the serial attention mechanism is superior to the parallel attention structure. Comparing the proposed CRAN with six different state-of-the-art methods, for the predicted results of two testing bearings, the proposed CRAN has an average reduction in the root mean square error of 57.07/80.25%, an average reduction in the mean absolute error of 62.27/85.87% and an average improvement in score of 12.65/6.57%.

This article provides a novel end-to-end rolling bearing RUL prediction framework, which can provide a reference for the formulation of bearing maintenance programs in the industry.

The car-sharing market has entered the mature stage, and consumers' demand shows a diversified increasing trend. This paper considers two modes of operation and two pricing strategies, which are business-to-consumer and consumer-to-consumer modes, market pricing and platform pricing. Under these conditions, the platform's revenue-sharing ratio will be different. The purpose of this paper is to explore this research question, and seeks an optimal pricing mechanism that can achieve a win–win situation between platform and automobile manufacturer in the two market modes.

The authors design different profit functions for platform under the two contexts. Of course, the platform's function is constrained to the manufacturer's function. By introducing a revenue-sharing contract a Stackelberg game model dominated by the platform is established and the equilibrium solutions under the two pricing models are derived.

The study found that even if only market pricing is executed, the scale of the car-sharing market will continue to expand. As the car-sharing market becomes more saturated, platform pricing is better for the automobile manufacturer; in most cases, the platform prefers platform pricing, but when the number of private cars is relatively small, if the cost of car operation and maintenance for the automobile manufacturer is lower or the revenue-sharing ratio of private cars is high, then market pricing will be more favorable to the platform.

With the cross-border integration of car service platforms and the automobile manufacturing industry, the key to achieving win–win cooperation and sustainable development in the car-sharing market will converge on the question of how to design a suitable pricing mechanism and revenue-sharing method.

Authors have determined how a car-sharing platform achieves a win–win order pricing strategy with the manufacturer and private car owners, respectively. And authors combined the supply chain revenue-sharing contract with the car-sharing market to explore the application of the revenue-sharing contract in the sharing economy.

This study, a symposium, aims to explore the determinants of financial inclusion, impact of cross-country income-variations on financial inclusion, do high-income countries really uplift the financial inclusion and does the higher financial inclusion index indicate the larger economy?

This study adopts the panel data model to investigate the impact of high-income countries and low- and middle-income countries on financial inclusion. However, this study further adopts the principal component analysis rather than Sarma’s approach to calculate the financial inclusion index.

Based on the Data of World Bank, United Nations, International Monetary Fund, World Development Indicators, this study concludes that there is no nexus between income variations and financial inclusion, as the study reveals that some low- and middle-income countries have greater financial inclusion index such as Thailand (2.8538FII), Brazil (1.9526FII) and Turkey (0.8582FII). In low- and middle-income countries, the gross domestic product per capita, information technology and communication, the rule of law, age dependency ratio and urbanization have a noteworthy impact on financial inclusion that accumulatively describe the 83% of the model. Whereas, in high-income countries, merely, information technology and urbanization have a substantial influence on the growth of financial revolution and financial inclusion that describes the 70% of the total.

The biggest limitation is the availability of data from different countries.

The originality of this paper is its technique, which is used in this paper to calculate the financial inclusion index. Furthermore, this study contributes to 40 different countries based on income, which could help to boost financial inclusion, and ultimately, it leads them toward economic growth.

The purpose of this paper is to improve the corrosion resistance of the 6061-Al alloy as the battery pack material for electric vehicles, and the nano-SiC/MAO composite coating was prepared.

The corrosion resistance of coatings was evaluated by the global electrochemical test, and the local electrochemical impedance spectroscopy (LEIS) was used to study the local corrosion mechanism. The laser confocal microscope, scanning electron microscope and X-ray diffractometer (XRD) were used to characterise coatings.

Results showed that the impedance of nano-SiC/MAO coating was 1–2 times higher than MAO coating, and the main corrosion product was Al(OH)₃. LEIS results showed that the impedance of the nano-SiC/MAO coating was two times higher than the MAO coating. The defective SiC/Micro-arc oxidation coating still had high corrosion resistance compared to the MAO coating.

The physical model of the local corrosion mechanism for SiC/MAO composite coating in “cavity-fracture collapse” mode was proposed.