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The purpose of this paper is to investigate the growth behavior and mechanism of Sn whisker induced by RE addition in Sn‐Zn‐Ga‐Pr solder at ambient condition.

By means of aging treatment, FIB and SEM microstructure analysis, the whisker growth behavior was investigated.

It was found that the morphologies of tin whisker are changed during air exposure. After 60 days aging, the average length of the longest whiskers could reach up to 70 μm, some whiskers even can grow to a length of 100 μm. It was discussed that the oxidation of Pr‐Sn intermetallics provides driving force for whisker growth.

Tin whisker growth is a complex reliability issue for lead‐free solder. The current research can be helpful in re‐understanding the issue of tin whisker growth as well as an enriched understanding on the effects of REs on lead‐free solders.

The purpose of this paper is to explore the formation and growth mechanism of bulk Cu₆Sn₅ intermetallic compounds, selecting Sn‐Ag‐Cu‐Ce solders as specimens.

In order to further enhance the properties of SnAgCu solder, trace amount of rare earth Ce was selected as alloying addition into the alloy; in previous investigations, the enhancements include better wettability, physical properties, creep strength and tensile strength. In this paper, the microstructure of Sn‐Ag‐Cu‐Ce soldered joints and its interfacial intermetallic compounds were investigated. Moreover, different morphologies of Cu₆Sn₅ IMCs were enumerated and described, and Ostwald ripening theory was employed to interpret the formation mechanism of bulk Cu₆Sn₅ IMCs.

In addition, based on finite element simulation, it is found that the von Mises stress concentrate around the bulk Cu₆Sn₅ IMCs inside the Sn‐Ag‐Cu‐Ce soldered joints after three thermal cycling loading (−55‐125°C). From the stress distribution, the failure site was predicted to fracture near the bulk Cu₆Sn₅ IMCs interface. This coincides with the experimental findings significantly.

The results presented in this paper may provide a theory guide for developing novel lead‐free solders as well as reliability investigation of lead‐free soldered joints.

Path planning is an important part of UAV mission planning. The main purpose of this paper is to overcome the shortcomings of the standard particle swarm optimization (PSO) such as easy to fall into the local optimum, so that the improved PSO applied to the UAV path planning can enable the UAV to plan a better quality path.

Firstly, the adaptation function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself. Secondly, the standard PSO is improved, and the improved particle swarm optimization with multi-strategy fusion (MFIPSO) is proposed. The method introduces class sigmoid inertia weight, adaptively adjusts the learning factors and at the same time incorporates K-means clustering ideas and introduces the Cauchy perturbation factor. Finally, MFIPSO is applied to UAV path planning.

Simulation experiments are conducted in simple and complex scenarios, respectively, and the quality of the path is measured by the fitness value and straight line rate, and the experimental results show that MFIPSO enables the UAV to plan a path with better quality.

Aiming at the standard PSO is prone to problems such as premature convergence, MFIPSO is proposed, which introduces class sigmoid inertia weight and adaptively adjusts the learning factor, balancing the global search ability and local convergence ability of the algorithm. The idea of K-means clustering algorithm is also incorporated to reduce the complexity of the algorithm while maintaining the diversity of particle swarm. In addition, the Cauchy perturbation is used to avoid the algorithm from falling into local optimum. Finally, the adaptability function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself, which improves the accuracy of the evaluation model.

The purpose of this paper is to analyze the linear and nonlinear effects of market integration on carbon emissions and explore the direct and indirect paths of market integration on carbon emissions through path analysis.

The authors first conduct a measurement and contrastive study of the market integration and carbon emissions of China’s 28 provinces from year 1995 to 2015. Then, the linear effect of market integration on carbon emissions is analyzed by using the fixed-effect model. Next, based on the path analysis method, the direct and indirect paths of market integration’s impact on carbon emissions are explored. Finally, the panel threshold regression model is used to evaluate the effect of market integration on carbon emissions under different situations of geographic distance.

The results show that first, the improvement of market integration can increase carbon emissions in the form of a linear relationship. Second, market integration not only has a direct and positive impact on the carbon emissions, but also has an indirect and positive impact on carbon emissions through the level of economic development, and a negative impact on carbon emissions through technological level. Third, an increase in market integration can reduce its positive effect on carbon emissions, but the improvement of economic growth and technology level can both enhance the positive effect of market integration on carbon emissions.

This paper focuses on the impact of market integration on carbon emissions in 30 provinces in China, while, the authors do not conduct a comparative analysis of different regions, so there are certain limitations. In addition, policy interaction between regional governments is also a key factor affecting carbon emissions, but this paper does not consider the effect of policy interaction, future follow-up research will try to incorporate it into the analytical models.

An important practical implication of this research is that market integration should be regarded highly in China’s energy conservation and emission reduction efforts. The research results have important reference value for policy authorities to formulate relevant policies. That is, the government can play a more active role in the process of integration through breaking the regional blockade and interest barriers to comprehensively improve resource utilization efficiency and technical level, and ultimately achieve regional low-carbon development.

This paper explores the effects of market integration on China’s carbon emissions based on different methods and perspectives, and confirms that market integration plays a vital role in China’s carbon emissions through economic growth and technological progress. Notably, based on the studied results, some specific and practical suggestions are proposed in this paper so as to reduce carbon emission and realize the sustainable development of economy and society in China.

This paper aims to examine the influence of different self-presentation strategies (cultural, personal and informational posts) and interactivity on luxury brands’ social media advertising.

Three pre-tests and a main experiment collected responses from 459 Chinese participants in total.

Cultural posts significantly influenced brand attitudes, interest and purchase intention, and the effects were mediated by perceived reinforcement of the brand’s social media account. Informational posts added to perceived informativeness of the brand’s social media account, but were more likely to trigger a perception that the brand was conservative and distancing itself from consumers. Interactivity increased perceived closeness and reduced perceived inactiveness and conservativeness of the brand’s social media account and subsequently improved brand attitudes. Perception of brand’s social media accountfully mediated the effects of self-presentation strategies and interactivity on brand attitudes, interest and purchase intention.

Self-presentation transfers desirable brand associations to luxury brands, reinforces brand image, and subsequently influences responses to luxury brands. Interactivity largely influences relational perceptions and brand attitudes.

Curating content about brand heritage and culture creates a social media self-presentation that is effective and influential on consumers. Brand and product information satisfies informational needs. Interactivity maintains customer relationship.

A theoretical model of luxury brands’ advertising was generated from the findings.

Flexible pressure sensor arrays have promising applications in analog haptics, reconfiguration of sensory functions, artificial intelligence, wearable devices and human-computer interaction. The force disturbance generated by the connecting material between the sensor array units will reduce the detection accuracy of the unit. The purpose of this paper is to propose a flexible pressure sensor with interference immunity capability. A C-type bridge flexible piezoelectric structure is used to improve the pressure perturbation. The interference immunity capability of the sensor has been improved.

In this paper, a C-type pressure sensor array structure by rapid injection moulding is manufactured through the positive piezoelectric effect of a piezoelectric material. The feasibility of C-type interference immunity structure in a flexible sensor array is verified by further analysis and experiment. A flexible pressure sensor array with C-type interference immunity structure has been proposed.

In this paper, we present the results of the perturbation experiment results of the C-type pressure sensor array, showing that the perturbation error is less than 8%. The test of the flexible sensor array show that the sensor can identify the curved angle of up to 120 °, and the output sensitivity of the sensor in the horizontal state reaches 0.12 V/N, and the sensor can withstand the pressure of 80 N. The flexible sensor can work stably in the stretch rate range of 0–8.6% and the stretch length range of 0–6 mm.

In this paper, C-type pressure sensor array structure is fabricated by rapid injection moulding for the first time. The research in this paper can effectively reduce the disturbance of input pressure on the sensor’s internal array and improve the output accuracy. The sensor can intuitively reflect the number of fingers sliding on the sensor by the order in which the maximum voltage appears. Due to the strong interference immunity capability and flexibility of the flexible sensor array mechanism, it has a broad application prospect in the practical fields of haptic simulation, perceptual function reconstruction, artificial intelligence, wearable devices and human–computer interaction.

Coal and power generation are related upstream and downstream industries. Coal price marketization and electricity price regulation have caused the price of coal to be sensitive to the benefits of generators. The paper aims to discuss these issues.

As a financial tool, contracts for differences can both help balance interests and reduce risks caused by spot price fluctuation. This thesis regards coal demand as a triangular fuzzy stochastic variable while directing a levelling consideration towards risk returns for coal and power enterprises that are involved in coal generation contracts for differences. Risk and benefit measurement models were established between coal suppliers and power generators, and risk and benefit balance optimization models for contract negotiation were constructed.

A numerical example showed that the above models can be effectively used to avoid the risks of coal-electricity parties.

This thesis regards coal demand as a triangular fuzzy random variable while directing a levelling consideration towards the risk return to coal and power enterprises that are involved with coal generation contracts for differences. The features of this thesis are the following: demand information is regarded as a fuzzy random variable instead of a random variable. With historical data, sales experience and increasingly clear macro-economic conditions, coal and power enterprises are able to make a fuzzy decision – to a certain extent – when the transaction approaches. Accurate market information enables the supply chain system to satisfy the clients’ needs better, improve the profit level or avoid severe financial damages; by developing a feasible set of contracts for different parameters, it is possible to estimate whether the price difference enables supply chain coordination, requires changes or gives accounts to all involved parties of the supply chain; and without the assumption that the traditional M-V rule is unfavourable to decision makers, this thesis proposes the prospect M-V rule, which involves decision makers’ projections of future coal generation prices and enables wide applicability of the response method to contracts for differences.

To predict the passenger volume reasonably and accurately, this paper fills the gap in the research of quarterly data forecast of railway passenger volume. The research results can also provide references for railway departments to plan railway operation lines reasonably and efficiently.

This paper intends to establish a seasonal cycle first order univariate grey model (GM(1,1) model) combing with a seasonal index. GM (1,1) is termed as the trend equation to fit the railway passenger volume in China from 2014 to 2018. The railway passenger volume in 2019 is used as the experimental data to verify the forecasting effect of the proposed model. The forecasting results of the seasonal cycle GM (1,1) model are compared with the traditional GM (1,1) model, seasonal grey model (SGM(1,1)), Seasonal Autoregressive Integrated Moving Average (SARIMA) model, moving average method and exponential smoothing method. Finally, the authors forecast the railway passenger volume from 2020 to 2022.

The quarterly data of national railway passenger volume have a clear tendency of cyclical fluctuations and show an annual growth trend. According to the comparison of the modeling results, the authors know that the seasonal cycle GM (1,1) model has the best prediction effect with the mean absolute percentage error of 1.32%. It is much better than the other models, reflecting the feasibility of the proposed model.

As the previous grey prediction model could not solve the series prediction problem with seasonal fluctuation, and there are few research studies on quarterly railway passenger volume forecasting, GM (1,1) model is taken as the trend equation and combined with the seasonal index to construct a combination forecasting model for accurate forecasting results in this study. Besides, considering the impact of the epidemic on passenger volume, the authors introduce a disturbance factor to deal with the forecasting results in 2020, making the modeling results more scientific, practical and referential.

The purpose of this paper is to construct a dynamic information aggregation decision-making model based on variable precision rough set.

To deal with the dynamic decision-making problems, the grey relational analysis method, grey fixed weight clustering based on the centre triangle whitening weight function and maximum entropy principle is used to establish the dynamic information aggregation decision-making model based on variable precision rough set. The method, to begin with, the grey relational analysis method is used to determine the attributes weights of each stage; taking the proximity of the attribute measurement value and positive and negative desired effect value and the uncertainty of time weight into account, a multi-objective optimisation model based on maximum entropy principle is established to solve the model with Lagrange multiplier method, so that time weights expression are acquired; what is more, the decision-making attribute is obtained by grey fixed weight clustering based on the centre triangle whitening weight function, so that multi-decision-making table with dynamic characteristics is established, and then probabilistic decision rules from multi-criteria decision table are derived by applying variable precision rough set. Finally, a decision-making model validates the feasibility and effectiveness of the model.

The results show that it the proposed model can well aggregate the multi-stage dynamic decision-making information, realise the extraction of decision-making rules.

The method exposed in the paper can be used to deal with the decision-making problems with the multi-stage dynamic characteristics, and decision-making attributes contain noise data and the attribute values are interval grey numbers.

The paper succeeds in realising both the aggregation of dynamic decision-making information and the extraction of decision-making rules.

With the continuous change of research contents and methods of intelligence science, its integration with other disciplines is also deepening. The purpose of this paper is to further explore the interdisciplinary research characteristics of intelligence science in theoretical depth and application value.

This paper summarizes and explores in two aspects. The first is a large number of literature review, mainly combined with the historical characteristics of the development of intelligence science researches in China and international comparison. The second is to refine the discipline construction ideas suitable for the development of contemporary intelligence science.

From the perspective of the historical development of discipline relevance, the development characteristics and positioning of intelligence science in China are introduced, with the comparison of many disciplines including information technology, library science, information science, data science, management science and other disciplines. In order to better meet the practical needs of intelligence service in the new era, this paper mainly analyzes the construction method of intelligence science research system and the relocation of intelligence science research content.

This paper summarizes the historical characteristics and international comparison of the development of intelligence science in China. It proposes the development characteristics and orientation of intelligence science in China from the perspective of historical development of discipline relevance. It also proposes the discipline construction ideas suitable for the development of contemporary intelligence science.