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    Heat Transfer Dynamic Analyses for Recycled-Concrete Wall Combined with Expanded Polystyrene Template by Jianhua Li, Wenjing Chen

    Published 2018-01-01
    “…We put forth the suggestion for the use of corrected calculation method in the calculation and analysis of U of EPS template recycled-concrete composite shear wall in the climatic conditions of Beijing. The results revealed the fact that the U of EPS template recycled-concrete shear wall was dominantly controlled by the change of thermal conductivity changes of EPS template. …”
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    The Microbial Activity in PM2.5 in Indoor Air: As an Index of Air Quality Level by Hanlin Chen, Rui Du, Weishan Ren, Sujian Zhang, Pengrui Du, Yongtao Zhang

    Published 2020-08-01
    “…Thus, this study used a modified technique of fluorescein diacetate (FDA) hydrolysis to evaluate the activity of microorganisms in the PM2.5 during three seasons (summer, autumn and winter) in Beijing. 0.155–5.388 ng m−3 and 0.091–5.740 ng m−3 of sodium fluorescein, a marker of microbial activity, were measured indoors and outdoors, respectively; thus, no significant difference in concentration between the two environments was detected, but the indoor activity was affected by outdoor conditions to an extent. …”
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    Spatial association network structure of agricultural carbon emission efficiency in Chinese cities and its driving factors by Xu Wei, Bohong Chen

    Published 2024-12-01
    “…Central cities generally exhibit higher efficiency levels, while the surrounding cities tend to have lower efficiency. (2) The carbon emission efficiency of city agriculture in China displays multidimensional, complex, and organic characteristics, with potential for enhanced network stability. (3) Agricultural regions in central and southeastern China dominate the spatial network, while regions with weaker agricultural sectors, like Beijing, Shanghai, and Ningxia, occupy peripheral positions. (4) Within the spatial association network of city agricultural carbon emission efficiency in China, Intra block spatial correlations are low, while interblock spatial correlations are strong, exhibiting significant spillover effects. (5)Variations in agricultural development levels and mechanization significantly enhance the formation of networks related to city agricultural carbon emission efficiency in China. …”
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