In large-scale galaxy surveys, particularly deep ground-based photometric studies, galaxy blending was inevitable. Such blending posed a potential primary systematic uncertainty for upcoming surveys. Current deblenders predominantly depended on analytical modelling of galaxy profiles, facing limitations due to inflexible and imprecise models. We presented a novel approach, using a U-net structured transformer-based network for deblending astronomical images, which we term the CAT-deblender. It was trained using both RGB and the grz-band images, spanning two distinct data formats present in the Dark Energy Camera Legacy Survey (DECaLS) database, including galaxies with diverse morphologies in the training dataset. Our method necessitated only the approximate central coordinates of each target galaxy, sourced from galaxy detection, bypassing assumptions on neighbouring source counts. Post-deblending, our RGB images retained a high signal-to-noise peak, consistently showing superior structural similarity against ground truth. For multi-band images, the ellipticity of central galaxies and median reconstruction error for r-band consistently lie within $\pm$0.025 to $\pm$0.25, revealing minimal pixel residuals. In our comparison of deblending capabilities focused on flux recovery, our model showed a mere 1% error in magnitude recovery for quadruply blended galaxies, significantly outperforming SExtractor’s higher error rate of 4.8%. Furthermore, by cross-matching with the publicly accessible overlapping galaxy catalogs from the DECaLS database, we successfully deblended 433 overlapping galaxies. Moreover, we have demonstrated effective deblending of 63 733 blended galaxy images, randomly chosen from the DECaLS database.

Soft magnetic robots have attracted tremendous interest owning to their controllability and manoeuvrability, demonstrating great prospects in a number of industrial areas. However, further explorations on the locomotion and corresponding deformation of magnetic robots with complex configurations are still challenging. In the present study, we analyse a series of soft magnetic robots with various geometric shapes under the action of the magnetic field. First, we prepared the matrix material for the robot, that is, the mixture of silicone and magnetic particles. Next, we fabricated a triangular robot whose locomotion speed and warping speed are approximately 1.5 and 9 mm/s, respectively. We then surveyed the generalised types of robots with other shapes, where the movement, grabbing, closure and flipping behaviours were fully demonstrated. The experiments show that the arching speed and grabbing speed of the cross-shaped robot are around 4.8 and 3.5 mm/s, the crawling speed of the pentagram-shaped robot is 3.5 mm/s, the pentahedron-shaped robot can finish its closure motion in 1 s and the arch-shaped robot can flip forward and backward in 0.5 s. The numerical simulation based on the finite element method has been compared with the experimental results, and they are in excellent agreement. The results are beneficial to engineer soft robots under the multi-fields, which can broaden the eyes on inventing intellectual devices and equipment.

To improve the corrosion resistance and to increase the hardness of copper substrate in marine environment, the Cu-Ni/Ni-P composite coatings were prepared on the copper substrate using the galvanostatic electrolytic deposition method. The deposition current densities were explored to find the optimized deposition conditions for forming the composite coatings. Corrosion resistance properties were analyzed using the polarization curves and electrochemical impedance spectroscopy (EIS). Considering the corrosion resistance and hardness, the −20 mA/cm2 was selected to deposit Cu-Ni coatings on copper substrate and the −30 mA/cm2 was selected to deposit Ni-P coating on the Cu-Ni layer. The Cu-Ni/Ni-P composite coatings not only exhibited superior corrosion resistance compared to single Cu-Ni coating in 3.5 wt.% NaCl solution, but also showed much better mechanical properties than single Cu-Ni coating.

In this paper, the design of a graded honeycomb radar absorbing structure (RAS) is presented to realize both a wide bandwidth and absorption over a wide range of angles. For both transverse-electric and transverse-magnetic polarization, a fractional bandwidth of more than 118.6% is achieved for at least a 10 dB reflectivity reduction when the incident angle is <45°, an 8 dB reduction when the incident angle is <55° and a 5 dB reduction when the incident angle is <70°. Meanwhile the 10 dB reduction upper angle limit is approximately 30° for the uniform coating honeycomb RAS in the literature, which loses its absorbing ability when the incident angle is larger than 55°. Furthermore, the total thickness of our design is 10.7 mm, which is only approximately 1.29 times that of the theoretical limitation. The good agreement between the calculated, simulated, and measured results demonstrates the validity of this optimization.

The optical emission spectra of the plasma generated by a 1.06-μm Nd:YAG laser irradiation of Al target in air was recorded and analyzed in a spatially resolved manner. Electron temperatures and densities in the plasma were obtained using the relative emission intensities and the Stark-broadened linewidths of Al(I) emission lines, respectively. The dependence of the electron density and temperature on the distance from the target surface and on the laser irradiance were manifested. We also discussed how the air takes part in the plasma evolution process and confirmed that the ignition of the air plasma was by the collisions between the energetic electrons and the nitrogen atoms through a cascade avalanche process.