Star Formation Properties in Barred Galaxies(SFB). III. Statistical Study of Bar-driven Secular Evolution using a sample of nearby barred spirals

Stellar bars are important internal drivers of secular evolution in disk galaxies. Using a sample of nearby spiral galaxies with weak and strong bars, we explore the relationships between the star formation feature and stellar bars in galaxies. We find that galaxies with weak bars tend to be coincide with low concentrical star formation activity, while those with strong bars show a large scatter in the distribution of star formation activity. We find enhanced star formation activity in bulges towards stronger bars, although not predominantly, consistent with previous studies. Our results suggest that different stages of the secular process and many other factors may contribute to the complexity of the secular evolution. In addition, barred galaxies with intense star formation in bars tend to have active star formation in their bulges and disks, and bulges have higher star formation densities than bars and disks, indicating the evolutionary effects of bars. We then derived a possible criterion to quantify the different stages of bar-driven physical process, while future work is needed because of the uncertainties.Comment: 30 single-column pages, 9 figures, accepted for publication in A

Utility-maximization Resource Allocation for Device-to-Device Communication Underlaying Cellular Networks

Device-to-device(D2D) underlaying communication brings great benefits to the cellular networks from the improvement of coverage and spectral efficiency at the expense of complicated transceiver design. With frequency spectrum sharing mode, the D2D user generates interference to the existing cellular networks either in downlink or uplink. Thus the resource allocation for D2D pairs should be designed properly in order to reduce possible interference, in particular for uplink. In this paper, we introduce a novel bandwidth allocation scheme to maximize the utilities of both D2D users and cellular users. Since the allocation problem is strongly NP-hard, we apply a relaxation to the association indicators. We propose a low-complexity distributed algorithm and prove the convergence in a static environment. The numerical result shows that the proposed scheme can significant improve the performance in terms of utilities.The performance of D2D communications depends on D2D user locations, the number of D2D users and QoS(Quality of Service) parameters

Artifi cial Intelligence Generated Content for Language Teaching and Learning Reform

Artifi cial Intelligence Generated Content (AIGC) is a generative method that matches language patterns with existing data and thus provides relevant content with appropriate generalization capabilities. The educational demand is to combine AIGC with teaching resources, expanding traditional monomodal language teaching modes with Digital Multimodal Composing(DMC), so as to carry out language teaching and learning reform. As a new Artifi cial Intelligence involved practice, language teachers lack technological experiences to ensure class performance. In the process of creating DMC, learners pay more attention to entertainment rather than the practicability of its content. AIGC can facilitate teaching with feasible methods to improve learning effi ciency and promote outcome