RESUMEN
Powerful relativistic jets are one of the ubiquitous features of accreting black holes in all scales1-3. GRS 1915 + 105 is a well-known fast-spinning black-hole X-ray binary4 with a relativistic jet, termed a 'microquasar', as indicated by its superluminal motion of radio emission5,6. It has exhibited persistent X-ray activity over the last 30 years, with quasiperiodic oscillations of approximately 1-10 Hz (refs. 7-9) and 34 and 67 Hz in the X-ray band10. These oscillations probably originate in the inner accretion disk, but other origins have been considered11. Radio observations found variable light curves with quasiperiodic flares or oscillations with periods of approximately 20-50 min (refs. 12-14). Here we report two instances of approximately 5-Hz transient periodic oscillation features from the source detected in the 1.05- to 1.45-GHz radio band that occurred in January 2021 and June 2022. Circular polarization was also observed during the oscillation phase.
RESUMEN
FAST is the largest single-dish radio telescope in the world. The characteristics of FAST are presented and analyzed in the context of the parameter space to show how FAST science achievements are affected. We summarize the scientific achievements of FAST and discuss its future science based on the new parts of the parameter space that can be explored by FAST.
RESUMEN
Map building and map-based relocalization techniques are important for unmanned vehicles operating in urban environments. The existing approaches require expensive high-density laser range finders and suffer from relocalization problems in long-term applications. This study proposes a novel map format called the ClusterMap, on the basis of which an approach to achieving relocalization is developed. The ClusterMap is generated by segmenting the perceived point clouds into different point clusters and filtering out clusters belonging to dynamic objects. A location descriptor associated with each cluster is designed for differentiation. The relocalization in the global map is achieved by matching cluster descriptors between local and global maps. The solution does not require high-density point clouds and high-precision segmentation algorithms. In addition, it prevents the effects of environmental changes on illumination intensity, object appearance, and observation direction. A consistent ClusterMap without any scale problem is built by utilizing a 3D visual-LIDAR simultaneous localization and mapping solution by fusing LIDAR and visual information. Experiments on the KITTI dataset and our mobile vehicle illustrates the effectiveness of the proposed approach.