A nanoporous carbon derived from an aluminumbased metal-organic framework was deposited on stainless steel wires in a sol-gel matrix. The resulting fibers were applied to the solid-phase microextraction of the polycyclic aromatic hydrocarbons (PAHs) naphthalene, acenaphthene, fluorene, phenanthrene and anthracene from water and soil samples. The fiber was then directly inserted into the GC injector and the PAHs were quantified by GC-MS. The effects of salt addition, extraction temperature, extraction time, sample volume and desorption conditions on the extraction efficiency were optimized. A linear response to the analytes was observed in the 0.1 to 12 μg L −1 range for water samples, and in the 0.6 to 30 μg kg −1 for soil samples, with the correlation coefficients ranging from 0.9934 to 0.9985. The limits of detection ranged from 5.0 to 20 ng L −1 for water samples, and from 30 to 90 ng kg −1 for soil samples. The recoveries of spiked samples were between 72.4 and 108.0 %, and the precision, expressed as the relative standard deviations, is <12.8 %.
The paper introduced the Bayesian networks briefly and discussed the algorithm of transforming fault tree into Bayesian networks at first, then regarded the structures impaired caused by tunnel blasting construction as a example, introduced the built and calculated method of the Bayesian networks by matlab. Then assumed the probabilities of essential events, calculated the probability of top event and the posterior probability of each essential events by the Bayesian networks. After that the paper contrast the characteristics of fault tree analysis and the Bayesian networks, Identified that the Bayesian networks is better than fault tree analysis in safety evaluation in some case, and provided a valid way to assess risk in metro construction.
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