Wetlands play an important role in the feeding, breeding, and lives of birds. However, available habitats for bird species are changing due to intensifying human activity, especially in the context of China’s mass urbanization. Urban sprawl has taken over the wetlands along the lakes in the past decades, which places tremendous pressure on wetland ecosystems and, therefore, on bird communities. However, the ways urban land cover pattern along the urban-rural gradient affects bird communities is still unclear. To investigate the influence of land cover pattern on the α and β diversity of birds in the urban-rural gradient we chose 31 sites distributed within the wetlands around the Dianchi Lake in Yunnan, China. We calculated the species richness to indicate α diversity and used the Morisita–Horn index to indicate β diversity. Meanwhile, we assessed the land cover pattern of each site by measuring the proportion of emergent plants, floating plants, submerged plants, ponds, forests, lawns, roads, agricultural lands and built lands in a quadrat of 1 square kilometer. Simple linear regressions, model selection, and an averaging approach based on corrected Akaike information criterion (AICc) were used to test the effects of land cover pattern on bird diversity. Using one-way ANOVA and Tukey’s HSD (honestly significant difference) test, we compared the difference between α and β diversity, respectively, along the urban-rural gradient. Based on our analyses, urban and suburban wetland birds were significantly homogeneous. The community structure in rural wetlands, however, was significantly different from that of the suburban and urban areas. According to our research, the land cover patterns that influenced bird species richness were the built lands acreage, submerged plants acreage, ponds acreage, and the edge density of emergent plants. Meanwhile, of these variables, the built lands acreage, ponds acreage and edge density of emergent plants were significantly different in urban, suburban, and rural wetlands. Therefore, to maintain high biodiversity in wetlands affected by urbanization, we must pay more attention to the land cover patterns.

In this study, we conduct laboratory experiments on coal with liquid CO2 phase transition fracturing (L-CO2-PTF) treatment under the fracturing pressures of 120 and 185 MPa. The variations of structure and fractal characteristics for mesopores (2–50 nm) and micropores (<2 nm) are studied by employing the low-temperature N2/CO2 adsorption measurements and the fractal theory. The results indicate that the effects of pore enlarging and fractal dimension reducing of L-CO2-PTF are visible for mesopores, while these effects are underperformed for micropores. The connectivity of mesopores is improved due to the transformation of semi-open pores (type II) and thin-necked bottle pores (type III) into open pores (type I). The size of mesopores is increased, while the pore volume, pore specific area, and fractal dimension are reduced. All these performances are conducive to enhancing the capacity of coalbed methane (CBM) desorption and diffusion. It should adopt different fracturing pressures for coals with different metamorphic degrees. Primarily, it is significant to explore a novel L-CO2-PTF device with considerable energy, high fracturing pressure, and long action time for improving the nanoscale channel connectivity of CBM transport. This study further reveals the effects of L-CO2-PTF on mesopores, micropores, and CBM transport, which proposes theoretical guidance for the improvement and optimization of the L-CO2-PTF technique.

With the development of energy harvesting technologies and smart grid, the future trend of radio access networks will present a multi‐source power supply. In this article, joint renewable energy cooperation and resource allocation scheme of the fog radio access networks (F‐RANs) with hybrid power supplies (including both the conventional grid and renewable energy sources) is studied. In this article, our objective is to maximize the average throughput of F‐RAN architecture with hybrid energy sources while satisfying the constraints of signal to noise ratio (SNR), available bandwidth, and energy harvesting. To solve this problem, the dynamic power allocation scheme in the network is studied by using Q‐learning and Deep Q Network respectively. Simulation results show that the proposed two algorithms have low complexity and can improve the average throughput of the whole network compared with other traditional algorithms.

In this work, we have given an analogical method for estimating the fractal dimension for three-dimensional fracture tortuosity (3D-FT). The comparison and error analysis of analogical and rigorous methods on fractal dimension for 3D-FT were carried out in this work. The fractal dimension [Formula: see text] for 3D-FT from the proposed analogical method is the function of 3D fracture average tortuosity ([Formula: see text] and average fracture length ([Formula: see text]. The analogical method for estimating fractal dimension ([Formula: see text] with high accuracy indicates good consistency with the rigorous method ([Formula: see text]. The fractal dimension ([Formula: see text] from the rigorous method is the embodiment of the physical meaning of [Formula: see text]. The fractal dimension ([Formula: see text] from the analogical method is relatively convenient for calculating the premise of ensuring accuracy.

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