Structure, diversity and spatial distribution pattern of significant tree species in Hefei city

In order to further tap the ecological potential of urban trees, improve the diversity of tree species in urban environment, and promote the sustainable development of urban trees, this paper further analyzes the structure, diversity and spatial distribution law of the prominent tree species in Hefei city on the basis of on–the–spot identification of the prominent trees distributed in the main city. The results show that: 1) 528 significant trees are identified in the three districts, belonging to 40 species, 36 genera and 27 families, with 23 trees evaluated by qualitative index and 505 trees by quantitative index. In quantity distribution, the number of significant trees in the three districts is ranked as Yaohai District> firstringroad City> Government Affairs District. The top four tree species in relative abundance are Platanus acerifolia, Cinnamomum camphora, Ginkgo biloba and Cedar. 2) In terms of the tree age structure, most trees are 20~40 years old, and only 22 trees are over 100 years old; the ratio of evergreen to deciduous tree species is 1: 3, and the ratio of plant to tree is about 7: 18; there are 23 native tree species accounting for 57.50%, but only 171 trees. 3) In terms of area distribution, the average tree height and crown area in Yaohai District are the largest, the average DBH, Shannon–Wiener index and Simpson index in the first–ring city area are the highest, and the species evenness index in Government District is the highest. 4) In terms of site types, most significant trees are distributed in urban streets, residential areas and parks, and only 11.74% of them are distributed in government organizations, schools, public facilities, scenic spots and religious land

Fast Adjustable NPN Classification Using Generalized Symmetries

NPN classification of Boolean functions is a powerful technique used in many logic synthesis and technology mapping tools in FPGA design flows. Computing the canonical form of a function is the most common approach of Boolean function classification. In this paper, a novel algorithm for computing NPN canonical form is proposed. By exploiting symmetries under different phase assignments and higher-order symmetries of Boolean functions, the search space of NPN canonical form computation is pruned and the runtime is dramatically reduced. The algorithm can be adjusted to be a slow exact algorithm or a fast heuristic algorithm with lower quality. For exact classification, the proposed algorithm achieves a 30× speedup compared to a state-of-the-art algorithm. For heuristic classification, the proposed algorithm has similar performance as the state-of-the-art algorithm with a possibility to trade runtime for quality