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The purpose of this article is the effect of doping minor Ni on the microstructure evolution of a Sn-xNi (x = 0, 0.05 and 0.1 wt.%)/Ni (Poly-crystal/Single-crystal abbreviated as PC Ni/SC Ni) solder joint during reflow and aging treatment. Results showed that the intermetallic compounds (IMCs) of the interfacial layer of Sn-xNi/PC Ni joints were Ni₃Sn₄ phase, while the IMCs of Sn-xNi/SC Ni joints were NiSn₄ phase. After the reflow process and thermal aging of different joints, the growth behavior of interfacial layer was different due to the different mechanism of element diffusion of the two substrates. The PC Ni substrate mainly provided Ni atoms through grain boundary diffusion. The Ni₃Sn₄ phase of the Sn0.05Ni/PC Ni joint was finer, and the diffusion flux of Sn and Ni elements increased, so the Ni₃Sn₄ layer of this joint was the thickest. The SC Ni substrate mainly provided Ni atoms through the lattice diffusion. The Sn0.1Ni/SC Ni joint increases the number of Ni atoms at the interface due to the doping of 0.1Ni (wt.%) elements, so the joint had the thickest NiSn₄ layer.

The effects of doping minor Ni on the microstructure evolution of an Sn-xNi (x = 0, 0.05 and 0.1 Wt.%)/Ni (Poly-crystal/Single-crystal abbreviated as PC Ni/SC Ni) solder joint during reflow and aging treatment was investigated in this study.

Results showed that the intermetallic compounds (IMCs) of the interfacial layer of Sn-xNi/PC Ni joints were Ni₃Sn₄ phase, while the IMCs of Sn-xNi/SC Ni joints were NiSn₄ phase. After the reflow process and thermal aging of different joints, the growth behavior of the interfacial layer was different due to the different mechanisms of element diffusion of the two substrates.

In this study, the effect of doping Ni on the growth and formation mechanism of IMCs of the Sn-xNi/Ni (single-crystal) solder joints (x = 0, 0.05 and 0.1 Wt.%) was investigated.

In this paper, the C80 special coal gondola car was taken as the subject, and the load test data of the car body at the center plate, side bearing and coupler measured on the dedicated line were broken down to generate the random load component spectrums of the car body under five working conditions, namely expansion, bouncing, rolling, torsion and pitching according to the typical motion attitude of the car body.

On the basis of processing the measured load data, the random load component spectrums were equivalently converted into sinusoidal load component spectrums for bench test based on the principle of pseudo-damage equivalence of load. Relying on the fatigue and vibration test bench of the whole railway wagon, by taking each sinusoidal load component spectrum as the simulation target, the time waveform replication (TWR) iteration technology was adopted to create the drive signal of each loading actuator required for the fatigue test of car body on the bench, and the drive signal was corrected based on the equivalence principle of measured stress fatigue damage to obtain the fatigue test loads of car body under various typical working conditions.

The fatigue test results on the test bench were substantially close to the measured test results on the line. According to the results, the relative error between the fatigue damage of the car body on the test bench and the measured damage on the line was within the range of −16.03%–27.14%.

The bench test results basically reproduced the fatigue damage of the key parts of the car body on the line.

Since the implementation of reform and opening up, China has made remarkable achievement in terms of economic reform and development. China’s path, as well as its experience, has simultaneously gained worldwide concerns. Developing the market economy against the backdrop of socialism brings conclusions from China’s achievement, deepens knowledge of China’s pathway and builds a socialist political economy with Chinese characteristics. That is the way to realise a basic socialist system, especially with regards to the organic integration of public ownership and market economy. This combination determines the future of socialism with Chinese characteristics and the success or failure of economic restructuring. Therefore, it requires consideration and in-depth study. The paper aims to discuss these issues.

The goal of economic restructuring is to establish and develop the socialist market economy. Its main content can be summarised in two parts. The first is the relationship between plan and market or government and market. The second is compatibility or combination of public ownership and market economy. The former is one of the superficial problems, relevant to resource allocation method or economic operation mechanism. The latter stems from deep-rooted problems, represented by ownership or the underlying economic system. These two work together to form the organic integrity of socialist market economy where both similarities and contrasts coexist.

The shared ideal of socialism with Chinese characteristics and the lofty goals of communism will then become empty words. In this sense we can say that, whether we can realise the unity and opposition between public ownership and market economy and better integrate advantages of socialist system with strengths of market economy, will to a large extent determine the future and destiny of the socialist market economy.

As previously mentioned, the relationship between plan and market or government and market are part of resource allocation methods or economic operation mechanism. Compatibility and combination, however, with public ownership and market economy are part of an ownership or basic economic system. Science reveals the nature and developmental law of the socialist market economy. An in-depth study must be conducted on the relationship between public ownership and market economy.

Scholars and practitioners increasingly recognize data as an important source of business opportunities, but research on the effect on small and medium-sized enterprises (SMEs) is limited. This paper empirically examines the complementary impact of SMEs' data capability and supply chain capability (SCC) and further tests the mediation effect of SCC between data capability and operational performance. The mediated effect of data capability is also moderated by competition.

This paper analyzes longitudinal data collected from 122 manufacturing SMEs in Finland. Hypotheses were tested by using structural equation modeling (SEM).

The results show that to benefit from the data capability, SMEs require a certain level of SCC to extract the value from the SMEs' data capability and support operational performance. Additionally, competition affects how SMEs benefit from data capability, as competitor turbulence moderates the complementary effect of data capability and SCC on operational performance.

This is one of the first studies examining the longitudinal effect of SMEs' data and SCC on operational performance in the current competitive environment.

The authors explore the impact of an emerging technology, blockchain technology, on diverse governance mechanisms and sustainable supply chain practices and how its relationships with the linkage of these elements.

The methodology incorporates a literature review and a qualitative empirical analysis of the Electronic Product Environmental Assessment Tool (EPEAT) standards. Expert opinions from various firms and organizations within the electronics sector are assessed. Through a thematic analysis, the relationships are identified and examined.

Data immutability, transparency and traceability capabilities of blockchain technology enhance the relationship between environmental standards and ecological supply chain sustainability practices. Although immature, the blockchain can influence the governance of supply chain sustainability practices. Immaturity of technology, lack of expertise, sharing information and trust have delayed adoption.

There is limited empirical evidence regarding blockchain's impact on governance mechanisms, specifically hybrid public-private mechanisms and sustainable supply chain practices. The study further evaluates how particular blockchain features may exert varying influences on these aspects and different sustainable supply chain traits. As an exploratory study, it proposes new areas for further research, including how blockchain's traceability function can improve sustainability standard adoption. Additionally, there is a call for integrating blockchain with technologies like IoT and sensors which may influence supply chain governance mechanisms, standards and sustainability practices.

The objectives of this study were to evaluate knowledge on the coronavirus disease 2019 (COVID-19) transmission, attitude toward the measures of COVID-19 prevention and control, explore social responsibility behaviors and test for the association between variables and social responsibility among university students.

It was a cross-sectional study. The population was 7,754 students from a university in Yala province. The sample size was 370 students according to Krejcie and Morgan table. Google form was introduced to make the self-administered questionnaires. Content validity was evaluated by three experts, and for reliability of knowledge and attitude, the coefficient was 0.707 and 0.702. Data collection was done in the early April 2020. Descriptive statistics and χ² were used to analyze the data. Ethical approval number 095–63.

The results found that students' knowledge on COVID-19 transmission was in a moderate level, attitude toward the state measures for COVID-19 prevention and control was at a high level. Their social responsibility behaviors were at a high level. Their knowledge, attitude and payment were significant association with social responsibility behaviors among university students (p < 0.05).

University students' knowledge on disease transmission as well as positive attitude toward the measures of regulation led them to have cooperation. Social distancing and lockdown measures affected their lifestyle. However, they have responsibility behaviors to the society, especially in the pandemic situation.

Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present study, the authors assess the forecast problem for the weekly wholesale price index of yellow corn in China during January 1, 2010–January 10, 2020 period.

The authors employ the nonlinear auto-regressive neural network as the forecast tool and evaluate forecast performance of different model settings over algorithms, delays, hidden neurons and data splitting ratios in arriving at the final model.

The final model is relatively simple and leads to accurate and stable results. Particularly, it generates relative root mean square errors of 1.05%, 1.08% and 1.03% for training, validation and testing, respectively.

Through the analysis, the study shows usefulness of the neural network technique for commodity price forecasts. The results might serve as technical forecasts on a standalone basis or be combined with other fundamental forecasts for perspectives of price trends and corresponding policy analysis.