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The purpose of this research is to explore the effect of proactivity on work–family enrichment through thriving at work and the moderation of such mediation by immediate supervisor perspective-taking.

Research data consisting of two-wave lagged data (N = 470) were collected from 470 employees of 17 domestic Chinese firms to examine the proposed moderated mediation model.

The findings show that proactivity was positively related to work–family enrichment and that thriving at work partially mediated this relationship. Immediate supervisor perspective-taking strengthens the effect of proactivity on thriving at work, and a positive indirect relationship exists between proactivity and work–family enrichment through thriving at work when immediate supervisor perspective-taking is high.

Organizations should formulate policies to motivate employees to engage in proactive behavior and stimulate employees' thriving at work. Organizations should also select leaders who are good at perspective-taking and provide training to leaders to help them take others' perspectives.

These results deepen our theoretical understanding of the consequences of proactivity by demonstrating the positive associations between proactive behavior and work–family enrichment. The current study also contributes to the literature by identifying the mediating mechanism of thriving at work to explain the relationship between proactivity and work–family enrichment. Furthermore, the results show that supervisor perspective-taking moderates the above mediation.

The purpose of this paper is to study the microstructure and properties of Sn-3.5Ag and Sn-3.5Ag-0.5Sb lead-free solder alloys with and without a rotating magnetic field (RMF).

Optical microscopy, scanning electron microscopy and X-ray diffraction were used to analyze the effect of an RMF on the microstructure of the solders. Differential scanning calorimetry was used to study the influence of the RMF on the thermal characteristics of the solders. The mechanical properties of the alloys were determined by tensile measurements at different strain rates.

The ß-Sn grains and intermetallic compounds for the Sn-3.5Ag and Sn-3.5Ag-0.5Sb lead-free solder alloys were refined under an RMF, and the morphology of the ß-Sn grains changed from dendritic to equiaxed. The pasty range was significantly reduced under an RMF. The ultimate tensile strength (UTS) of Sn-3.5Ag improved under the RMF, whereas the UTS of Sn-3.5Ag-0.5Sb decreased slightly. The addition of Sb to the Sn-3.5Ag alloy significantly enhanced the UTS and elongation (El.%) of the samples. The UTS of the solder increased with increasing strain rate.

The results revealed that the application of RMF in the molten alloy had a significant effect on its microstructure and mechanical properties. The thermal characteristics of the Sn-3.5Ag and Sn-3.5Ag-0.5Sb solder alloys were improved under the RMF. This research is expected to fill a knowledge gap regarding the behaviour of Sn-Ag solder alloys under RMF.

With the promotion of lithium-ion battery, it is more and more important to ensure the safety usage of the battery. The purpose of this paper is to analyze the battery operation data and estimate the remaining life of the battery, and provide effective information to the user to avoid the risk of battery accidents.

The particle filter (PF) algorithm is taken as the core, and the double-exponential model is used as the state equation and the artificial neural network is used as the observation equation. After the importance resampling process, the battery degradation curve is obtained after getting the posterior parameter, and then the system could estimate remaining useful life (RUL).

Experiments were carried out by using the public data set. The results show that the Bayesian-based posterior estimation model has a good predictive effect and fits the degradation curve of the battery well, and the prediction accuracy will increase gradually as the cycle increases.

This paper combines the advantages of the data-driven method and PF algorithm. The proposed method has good prediction accuracy and has an uncertain expression on the RUL of the battery. Besides, the method proposed is relatively easy to implement in the battery management system, which has high practical value and can effectively avoid battery using risk for driver safety.