The development of rural e-commerce has rapidly driven the development of rural logistics in China. Improving the service quality of the last mile delivery is an important measure to promote the sustainable development of rural e-commerce logistics. However, such work is challenging because the current rural last mile delivery is inefficient and unsustainable and is influenced by a set of interacting factors. It is necessary to explore the relationships among the sustainability influencing factors of rural last mile delivery. A total of 15 sustainability influencing factors are selected. The improved fuzzy analytic hierarchy process (FAHP) is used to assign the weights of the factors and then the interpretative structural model (ISM) is used to determine the hierarchical structure of each factor. The driving force-dependency quadrant graph is constructed by cross-impact matrix multiplication (MICMAC). The research results show that four factors, including “convenience of returning goods”, “integrity of goods”, “advance reservation of goods pickup”, and “delivery costs”, are the most basic factors affecting the sustainability of rural last mile delivery and are the deepest and most indispensable factors. This research provides valuable information for decision makers to develop proactive strategies and reinforcement policies to improve the service quality of rural last mile delivery, which could promote the sustainable development of rural logistics.

With the continuous improvement of the operation line network of urban rail transit, analyzing influencing factors of transfer passenger flow of urban rail transit is critical to improve the transfer demand analysis of urban rail transit. Using data collected from questionnaires, transfer passenger flow surveys and smart cards, this study proposes an approach base on nested logit passenger flow assignment model considering transfer choice behaviours of passengers. The transfer passenger flow at seven transfer stations in Nanjing is obtained. Subsequently, this study investigates the potential influencing factors of transfer passenger flow, including the node degree, geographic location (located in the city center, urban fringe, suburbs or suburban fringe), economic location (distance from the city center) and transportation locations (if it is close to a transportation hub or in combination with the hub) of rail transit transfer stations. The results indicate that a positive correlation between the transfer passenger flow and the node degrees of transfer stations. However, the relationship between transfer passenger flow and the economic, geographic, and transportation locations of transfer stations is not clear. The finding have reference value for the network design of rail transit transfer stations and transfer facilities, and provide reference for the analysis of passenger flow under network operation.

In modern engineering, electromagnetic induction quenching is usually adopted in improving the fatigue performance of steel engine parts such as crankshafts. In order to provide the theoretical basis for the design of the process, correct evaluation of the strengthening effect of this technique is necessary. In this paper, the research aim is the strengthening effect of this technique on a given type of steel crankshaft. First the magnetic-thermal coupling process was simulated by a 3D finite element model to obtain information on the temperature field during the heating and cooling stages. Then the residual stress field after cooling was simulated based on the same model. At last, the fatigue property of this crankshaft was predicted based on the combination of three parameters: the KBM (Kandil–Brown–Miller) multi-axial fatigue model, the residual stress field and the fatigue strength of the material. The experimental results showed that this method can achieve a much more reasonable prediction than the traditional strengthening factor, and thus can be applied in guiding the design of the quenching process.