Football is the most popular sport in the world, and one of the most interesting events is the transferring of football players among various clubs. Based on 470,792 transfer records among 23,605 football clubs in 206 countries and regions, we construct a mutual transfer network and investigate its basic topological characteristics related to node degree k, edge weight w and node strength s. We find that the distributions can be well fitted by bimodal distributions for k and s or a power-law tail distribution for w. By studying the features of neighbor nodes or edges, we find that the mutual transfer network exhibits assortative mixing for most nodes or clubs but disassortative for clubs with very large degrees. We also observe nonlinear correlations among the different types of measures. Our work sheds new lights into the investigation of the characteristics of football transfer activities.

Nighttime lights (NTLs) have been used as a proxy for economic growth in recent years. To verify the effectiveness of NTL in measuring regional economies, this article studies the regional economic convergence phenomenon in China’s provinces by a comparative analysis of NTL data and GDP data from 1992 to 2013. It is found that there is a significant difference between the results of club convergence between NTL and GDP; GDP high-growth clubs are mainly concentrated in the east and central areas, while NTL’s high-growth clubs are mostly concentrated in the central and west areas. Besides, the growth rate gaps between GDP clubs are relatively flat, while the growth rate gaps between NTL clubs are large. From the perspective of influencing, factors of the regional convergence, technological innovation, and industrial structure have a significant impact on GDP and NTL, and industrial structure has opposite effects on GDP clubs and NTL clubs. Besides the above factors, for NTL convergence clubs, population growth rate, economic openness, and resource consumption are also significant.

Ants are one of the important groups of venomous animals with about 14,000 described species. Studies so far focused on the discovery of venom proteins are only available for limited stinging ants, and the proteinaceous compositions of the stingless ants are completely unknown. Here, we used the transcriptomic approach to identify venom components from the yellow meadow ant, Lasius flavus, a stingless ant. The transcriptomic analysis yielded an extraordinary simplicity of the venom expression profile, with 17 venom proteins, such as phospholipase B, odorant binding protein, and apolipoprotein D. Ten of them were discovered as novel toxins for future functional investigations. Quantitative real time PCR analysis revealed that genes encoding the identified venom proteins display exclusively or highly expression profiles in venom glands, validating them as venom compositions. Our findings contribute to the understanding of the evolutional diversity of toxins between stinging and stingless ants.

The purpose of this paper is to clarify the convergence pattern of China’s regional economies, explore the driving force of their coordinated development, and provide policy suggestions for coordinated and high-quality development. We used nighttime light data from 1992 to 2020 and combined an exploratory spatial data analytical method and a log-t test of a nonlinear time-varying factor model to identify the spatial convergence clubs of regional economic growth and the economic growth drivers of different clubs based on a spatial econometric model. We found that the eastern region is strong while the development of the central, western, and northeastern regions follows China’s long-term trend. Three high-level economic clubs (Shanghai, Jiangsu, and Zhejiang belong to Club 1; Shandong, Hebei, Anhui, Henan, and Liaoning belong to Club 2; Hainan, Fujian, and Guangdong belong to Club 3) have formed in the eastern coastal and central regions, while a low-level one (Inner Mongolia, Hubei, Chongqing, Qinghai, Guizhou, Sichuan, Guangxi, Yunnan, Xizang, Shaanxi, Gansu, Hunan, Ningxia, Xinjiang, Jiangxi, Heilongjiang, and Jilin) has formed in the central, western, and northeastern regions. Beijing, Tianjin, and Shanxi are not convergent. The coordinated development of these regions requires improving the levels of economic growth in the western and northeastern regions to give full play to the role of the Yangtze River Delta as a growth pole and its economic radiation capacity. An analysis of the influence mechanism and spatial spillover effects shows that industrial development and market vitality are the most important driving forces for economic growth. For the low-level club, service industry development, human capital, and resource consumption are also key factors for achieving sustained and stable economic growth.