Decelerating Airy pulse propagation in highly non-instantaneous cubic media

The propagation of decelerating Airy pulses in non-instantaneous cubic medium is investigated both theoretically and numerically. In a Debye model, at variance with the case of accelerating Airy and Gaussian pulses, a decelerating Airy pulse evolves into a single soliton for weak and general non- instantaneous response. Airy pulses can hence be used to control soliton generation by temporal shaping. The effect is critically dependent on the response time, and could be used as a way to measure the Debye type response function. For highly non- instantaneous response, we theoretically find a decelerating Airy pulse is still transformed into Airy wave packet with deceleration. The theoretical predictions are confirmed by numerical simulations

Highly efficient room-temperature nonvolatile magnetic switching by current in Fe3GaTe2 thin flakes

Effectively tuning magnetic state by using current is essential for novel spintronic devices. Magnetic van der Waals (vdW) materials have shown superior properties for the applications of magnetic information storage based on the efficient spin torque effect. However, for most of known vdW ferromagnets, the ferromagnetic transition temperatures lower than room temperature strongly impede their applications and the room-temperature vdW spintronic device with low energy consumption is still a long-sought goal. Here, we realize the highly efficient room-temperature nonvolatile magnetic switching by current in a single-material device based on vdW ferromagnet Fe3GaTe2. Moreover, the switching current density and power dissipation are about 300 and 60000 times smaller than conventional spin-orbit-torque devices of magnet/heavymetal heterostructures. These findings make an important progress on the applications of magnetic vdW materials in the fields of spintronics and magnetic information storage.Comment: 18 page2, 4 figure

RTSDM: A Real-Time Semantic Dense Mapping System for UAVs

Intelligent drones or flying robots play a significant role in serving our society in applications such as rescue, inspection, agriculture, etc. Understanding the scene of the surroundings is an essential capability for further autonomous tasks. Intuitively, knowing the self-location of the UAV and creating a semantic 3D map is significant for fully autonomous tasks. However, integrating simultaneous localization, 3D reconstruction, and semantic segmentation together is a huge challenge for power-limited systems such as UAVs. To address this, we propose a real-time semantic mapping system that can help a power-limited UAV system to understand its location and surroundings. The proposed approach includes a modified visual SLAM with the direct method to accelerate the computationally intensive feature matching process and a real-time semantic segmentation module at the back end. The semantic module runs a lightweight network, BiSeNetV2, and performs segmentation only at key frames from the front-end SLAM task. Considering fast navigation and the on-board memory resources, we provide a real-time dense-map-building module to generate an OctoMap with the segmented semantic map. The proposed system is verified in real-time experiments on a UAV platform with a Jetson TX2 as the computation unit. A frame rate of around 12 Hz, with a semantic segmentation accuracy of around 89% demonstrates that our proposed system is computationally efficient while providing sufficient information for fully autonomous tasks such as rescue, inspection, etc

A Hybrid Dynamic Probability Mutation Particle Swarm Optimization for Engineering Structure Design

Particle swarm optimization (PSO) is a common metaheuristic algorithm. However, when dealing with practical engineering structure optimization problems, it is prone to premature convergence during the search process and falls into a local optimum. To strengthen its performance, combining several ideas of the differential evolution algorithm (DE), a dynamic probability mutation particle swarm optimization with chaotic inertia weight (CWDEPSO) is proposed. The main improvements are achieved by improving the parameters and algorithm mechanism in this paper. The former proposes a novel inverse tangent chaotic inertia weight and sine learning factors. Besides, the scaling factor and crossover probability are improved by random distributions, respectively. The latter introduces a monitoring mechanism. By monitoring the convergence of PSO, a developed mutation operator with a more reliable local search capability is adopted and increases population diversity to help PSO escape from the local optimum effectively. To evaluate the effectiveness of the CWDEPSO algorithm, 24 benchmark functions and two groups of engineering optimization experiments are used for numerical and engineering optimization, respectively. The results indicate CWDEPSO offers better convergence accuracy and speed compared with some well-known metaheuristic algorithms

Recent Progress of Atomic Layer Technology in Spintronics: Mechanism, Materials and Prospects

The atomic layer technique is generating a lot of excitement and study due to its profound physics and enormous potential in device fabrication. This article reviews current developments in atomic layer technology for spintronics, including atomic layer deposition (ALD) and atomic layer etching (ALE). To begin, we introduce the main atomic layer deposition techniques. Then, in a brief review, we discuss ALE technology for insulators, semiconductors, metals, and newly created two-dimensional van der Waals materials. Additionally, we compare the critical factors learned from ALD to constructing ALE technology. Finally, we discuss the future prospects and challenges of atomic layer technology in the field of spinronics

Structure and dynamics of the Tonga subduction zone: New insight from P-wave anisotropic tomography

he Tonga-Lau-Fiji region is important to study plate-plume and subduction-ridge interactions, but its deep mantle structure is still not very clear. Here we present high-resolution tomography of 3-D P-wave azimuthal anisotropy down to 400 km depth of the Tonga subduction zone derived from arrival-time data of local earthquakes recorded at seafloor and land seismometers. The subducting Tong slab is imaged as high-velocity anomalies at depths of 100-400 km, whereas large-scale low-velocity anomalies down to 400 km depth are revealed in the mantle wedge beneath the backarc basin and volcanic arc. Trench-parallel anisotropy beneath the Lau Basin extends southwards to ∼140 km depth at ∼20.5°S, representing the extent of both southward flow of the Samoan plume and toroidal flow by the slab rollback. At depths of 140-400 km, the Lau Basin and Fiji Plateau mainly exhibit plate-parallel fast-velocity directions (FVDs) north of ∼20.5°S, indicating strong corner flow in the mantle wedge driven by the slab subduction and dehydration. The Tonga slab exhibits trench-parallel FVDs at depths of <200 km, reflecting fossil fabric formed during the plate spreading stage, whereas, at greater depths, the slab mainly exhibits trench-normal FVDs, which may reflect complicated deformations within the slab. These results suggest that the Samoan plume has a significant impact on the Tonga-Lau-Fiji region, leading to variations in the scale and depth extent of mantle flows

Quality Evaluation of Wind Turbine Roller Bearing Profile in the Ultra-long Flexible Blade

In order to accurately measure and evaluate the quality of the roller profile of the ultra-long flexible blade bearing, an error evaluation model is established for the arc segment and the straight segment of the roller based on the least square method, and then an overall quality evaluation model is proposed based on these two error models. Through the simulation of a standard wind turbine cylindrical roller bearing, it is found that the quality evaluation model established in this work can effectively measure and evaluate the contour line of the wind turbine bearing’s roller. The overall absolute error is 0.0319 mm, which is consistent with the set random error. The overall quality evaluation model is also valid for other types of bearings commonly used in the wind turbine, which include arc and straight segments, and can be used to evaluate the error quality of the roller profile of wind turbine bearings

Development of Simulation Task Unit Model based on Role and State Mode

Currently, service-oriented model and simulation has become a main development direction for modeling and simulation. In order to separate the simulation service and state and effectively reuse simulation resources, this paper proposed a simulation task unit (STU) model method based on role and state mode, in which role could call the simulation service by simulation member and the state value of simulation service could be saved in the state of role. This paper also analyzed the relations among role, state and logic, and described the simulation member model and simulation task model in detail. Besides, an STU model tool was developed for effectively modeling for STU, and this tool was proved to be useful for saving simulation service state in service-oriented model and simulation

An Optimization Algorithm for Multipath Parallel Allocation for Service Resource in the Simulation Task Workflow

Service oriented modeling and simulation are hot issues in the field of modeling and simulation, and there is need to call service resources when simulation task workflow is running. How to optimize the service resource allocation to ensure that the task is complete effectively is an important issue in this area. In military modeling and simulation field, it is important to improve the probability of success and timeliness in simulation task workflow. Therefore, this paper proposes an optimization algorithm for multipath service resource parallel allocation, in which multipath service resource parallel allocation model is built and multiple chains coding scheme quantum optimization algorithm is used for optimization and solution. The multiple chains coding scheme quantum optimization algorithm is to extend parallel search space to improve search efficiency. Through the simulation experiment, this paper investigates the effect for the probability of success in simulation task workflow from different optimization algorithm, service allocation strategy, and path number, and the simulation result shows that the optimization algorithm for multipath service resource parallel allocation is an effective method to improve the probability of success and timeliness in simulation task workflow