Multi-scenario & multi-task learning has been widely applied to many recommendation systems in industrial applications, wherein an effective and practical approach is to carry out multi-scenario transfer learning on the basis of the Mixture-of-Expert (MoE) architecture. However, the MoE-based method, which aims to project all information in the same feature space, cannot effectively deal with the complex relationships inherent among various scenarios and tasks, resulting in unsatisfactory performance. To tackle the problem, we propose a Hierarchical information extraction Network (HiNet) for multi-scenario and multi-task recommendation, which achieves hierarchical extraction based on coarse-to-fine knowledge transfer scheme. The multiple extraction layers of the hierarchical network enable the model to enhance the capability of transferring valuable information across scenarios while preserving specific features of scenarios and tasks. Furthermore, a novel scenario-aware attentive network module is proposed to model correlations between scenarios explicitly. Comprehensive experiments conducted on real-world industrial datasets from Meituan Meishi platform demonstrate that HiNet achieves a new state-of-the-art performance and significantly outperforms existing solutions. HiNet is currently fully deployed in two scenarios and has achieved 2.87% and 1.75% order quantity gain respectively.

The thermal efficiency limitation of the Flat-plate Micro Heat Pipe (FMHP) is a major challenge in the development of the FMHP, where the effect of wick structure and wettability on its thermal performance is studied to improve the thermal efficiency of the FMHP. In this work, a copper spiral woven mesh and copper foam Composite Wick FMHP (CW-FMHP) is designed based on the conventional Copper Foam Wick FMHP (CFW-FMHP), and its thermal performance is analyzed regarding the wick structure and internal gas–liquid two-phase flow characteristics. An oxidized copper spiral woven mesh and copper foam Composite Wick FMHP (OCW-FMHP) has been further developed through the modification of composite wick wettability. The performance tests are carried out with the thermal transfer characteristics of CW-FMHP, OCW-FMHP, and CFW-FMHP under different filling rates and different thermal powers. The experimental results show that the thermal transfer performance of CW-FMHP reaches the optimal under a liquid filling rate of 150%, where the maximum thermal power is 15.7 W, 35.3% higher than that of the CFW-FMHP under the same filling rate. Moreover, the dynamic response characteristics of the CW-FMHP are significantly improved. The thermal resistance of the CW-FMHP is 0.48 °C/W under the filling rate of 150% at the thermal power of 10 W with a reduction of 9.4% compared to the CFW-FMHP under the same condition. Furthermore, the optimal filling rate for OCW-FMHP is lower compared with the CW-FMHP. The maximum thermal power of OCW-FMHP increases to 17.8 W while the thermal resistance reduces to 0.34 °C/W under the liquid filling rate of 140%. This implies that the composite wick structure designed in this work can improve the thermal transfer performance of the FMHP, and the composite wick with wettability modification is more effective regarding both thermal resistance and maximum thermal power.

A double-thimble-type fiber Bragg grating (FBG) temperature sensor that isolates the stress strain is developed, and the three materials of air, grease, and copper thimble are employed for encapsulating. To investigate the effect of different encapsulation materials on the time constant of the sensors under dynamic conditions, the transient heat conduction mathematical model is built according to the lumped heat capacity (LHC) system and thermal equilibrium theory, and the time constant is solved by an analytical solution. Then, a proportional three-dimensional sensor simulation model is established and the transient heat transfer process is numerically solved by the finite element analysis method. To verify the models, an experimental system is established to test the response speed of the three-type sensor and the experimental data are compared with the analytical and numerical solution results. The results show that the dynamic response performance depends on the encapsulation material parameters; the response speed is faster than recovery speed; and the response speed of the air packaging sensor is more than 20% faster than that of the grease packaging sensor, and more than 30% faster than that of the copper packaging sensor. The smaller the heat storage capacity and the larger the heat transfer coefficient, the faster the sensor’s response speed.

The hot-spot temperature of a dry-type air-core reactor is a crucial factor that determines the service life of the reactor. Although the environment elevation has a significant influence on the reactor’s heat dissipation performance and hot-spot temperature, studies seldom focus on the temperature distribution for different altitude scenarios. To this end, this paper proposes a temperature field simulation model with multi-parameter coupling constraints based on the laminar–turbulent flow state. The calculation of the temperature field with the hot-spot temperature at different altitudes is finally achieved. The simulation results show that the hot-spot is located at 6.3% from the top of the sixth encapsulated-winding. It also shows that the hot-spot temperature of the reactor increases by 5 K–11 K with the altitude ascending by 1 km. Moreover, the hot-spot temperature of the reactor exceeds the temperature index at an altitude of 3.25 km, which will result in a shortened service life. Fiber Bragg grating temperature sensors are embedded in encapsulated-windings to detect the temperature for verifying the validity of the temperature field model, which could provide critical temperature rise evaluation rules for the operation safety of the dry-type air-core reactor.