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In order to improve the extraction rate of coal by solvent extraction, Lianhuatang lignite (LHT) was pretreated with 1‐butyl‐3‐methylimidazolium hexafluorophosphate ionic liquid([Bmim]PF6) firstly. Then, the Soxhlet extraction (SE), ultrasound‐assisted extraction (UAE), and microwave‐assisted extraction (MAE) were carried out to obtain extracts (ES1‐3, EU1‐3, and EM1‐3) and residues (RS1‐3, RU1‐3, and RM1‐3) from the Lianhuatang lignite pretreated with ionic liquid (BLHT), respectively, and CS2, acetone, and ethanol were used as solvents. The coal samples before and after the ionic liquid pretreatment were characterized by scanning electron microscope (SEM), Fourier‐transform infrared spectroscopy (FTIR), and thermogravimetric analyzer (TG). The residues were characterized by FTIR, and the extracts were characterized by a gas chromatograph/mass spectrometer (GC/MS). According to the results, ionic liquid can crack coal particles, increase the contact area of coal surface with solvent, and destroy part of the hydrogen bonds and intermolecular forces in coal, enabling easy extraction of the active small molecules. The macromolecular structure of coal is not destroyed in the three sequential extraction experiments. The types of extracts are similar under different methods, but the specific substances are very different. The total extraction rate by MAE was the highest, which was 48.70%. Microwave radiation can promote the extraction of oxygen‐containing substances, especially esters. [ABSTRACT FROM AUTHOR]

Real-time pedestrian volume data are becoming increasingly important to business strategy adjustment and guiding measures of shopping malls, tourist attractions, and transportation hubs. Wi-Fi probes are widely used to capture and study the media access control layer information of mobile devices but often with low detection and precision. This article mainly proposes an enhanced method to increase detection rate and precision under Wi-Fi-based system. Device test was first introduced to guarantee the performance of probes. Based on the theoretical analysis on the influences of probes’ relative locations, four layout schemes of multi-probes were compared, and the optimal one with the highest detection rate was identified experimentally. Based on the optimal layout, an estimation model between actual and detected volume was established after data cleaning. In total, two correction parameters were introduced to modify the model and shows a high estimation accuracy (root mean square error is 15.32 persons) in the experiment at Tongji University. The results of experiment proved that the proposed optimal layout scheme of multiple probes and estimation model can effectively improve the detection performance and precision of pedestrian volume and help increase the reliability and application value of Wi-Fi-based detection. [ABSTRACT FROM AUTHOR]