The highly integrated and miniaturized next-generation electronic products call for high-performance electromagnetic interfer?ence (EMI) shielding materials to ... 相似文献
As promising anodes for sodium-ion batteries, metal sulfides ubiquitously suffer from low-rate and high-plateau issues, greatly hindering their application in f... 相似文献
InAs/GaAs quantum dot(QD)lasers were grown on silicon substrates using a thin Ge buffer and three-step growth method in the molecular beam epitaxy(MBE)system.In addition,strained superlattices were used to prevent threading disloca-tions from propagating to the active region of the laser.The as-grown material quality was characterized by the transmission electron microscope,scanning electron microscope,X-ray diffraction,atomic force microscope,and photoluminescence spectro-scopy.The results show that a high-quality GaAs buffer with few dislocations was obtained by the growth scheme we de-veloped.A broad-area edge-emitting laser was also fabricated.The O-band laser exhibited a threshold current density of 540 A/cm2 at room temperature under continuous wave conditions.This work demonstrates the potential of large-scale and low-cost manufacturing of the O-band InAs/GaAs quantum dot lasers on silicon substrates. 相似文献
Parking in a small parking lot within limited space poses a difficult task. It often leads to deviations between the final parking posture and the target posture. These deviations can lead to partial occupancy of adjacent parking lots, which poses a safety threat to vehicles parked in these parking lots. However, previous studies have not addressed this issue. In this paper, we aim to evaluate the impact of parking deviation of existing vehicles next to the target parking lot(PDEVNTPL) on the au... 相似文献
Goal-conditioned reinforcement learning (RL) is an interesting extension of the traditional RL framework, where the dynamic environment and reward sparsity can cause conventional learning algorithms to fail. Reward shaping is a practical approach to improving sample efficiency by embedding human domain knowledge into the learning process. Existing reward shaping methods for goal-conditioned RL are typically built on distance metrics with a linear and isotropic distribution, which may fail to provide sufficient information about the ever-changing environment with high complexity. This paper proposes a novel magnetic field-based reward shaping (MFRS) method for goal-conditioned RL tasks with dynamic target and obstacles. Inspired by the physical properties of magnets, we consider the target and obstacles as permanent magnets and establish the reward function according to the intensity values of the magnetic field generated by these magnets. The nonlinear and anisotropic distribution of the magnetic field intensity can provide more accessible and conducive information about the optimization landscape, thus introducing a more sophisticated magnetic reward compared to the distance-based setting. Further, we transform our magnetic reward to the form of potential-based reward shaping by learning a secondary potential function concurrently to ensure the optimal policy invariance of our method. Experiments results in both simulated and real-world robotic manipulation tasks demonstrate that MFRS outperforms relevant existing methods and effectively improves the sample efficiency of RL algorithms in goal-conditioned tasks with various dynamics of the target and obstacles.
Based on the experimental results and analysis of the cyclic deformation, there is an obvious yield stage on the cyclic stress-strain curve at the stage of small plastic deformation (in room or low temperatures). This phenomenon is similar to that of monotonic tensile curve case. But for the former the deformation amount at which the yield begins is much smaller than that for the latter. The cyclic stress-strain constitutive relation needs to be further studied according to the actual cyclic stress-strain curve. The conventional constitutive equation σ=Aεn is based on the results only corresponding to the cyclic strengthening stage. It is not appropriate for the stage of the small plastic deformation and the stage of yield. 相似文献