Coal gangue, sandy soil and clay (mass ratio 45: 4: 1) as goaf filling materials acquired from coal mining processes were applied to remove Fe and Mn effectively from mining drainage. The results of an adsorption kine...
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Coal gangue, sandy soil and clay (mass ratio 45: 4: 1) as goaf filling materials acquired from coal mining processes were applied to remove Fe and Mn effectively from mining drainage. The results of an adsorption kinetic study showed that the Fe adsorption equation was y = 21.454y + 8.4712, R-2 = 0.9924 and the Mn adsorption equation was y = 7.5409x + 0.905, R-2 = 0.9957. Meanwhile, the goaf filling materials had low desorption capacity (Fe 6.765 mu g/g, Mn 1.52 mu g/g) and desorption ratio (Fe 8.98%, Mn 11.04%). Experiments demonstrated that Fe and Mn from mining drainage could be removed stably at a flow rate of 1.2 L/min, Fe inlet concentration of less than 40 mg/L, Mn inlet concentration of less than 2 mg/L and neutral or alkaline conditions. During a procedure of continuous experiments, the effluent quality could meet the requirement of the 'Code for Engineering Design of Sewage Regeneration-GB503352-2002'. A real-application project using goaf filling materials to treat mining drainage in Shendong coal mine showed that the average cost per ton of mining drainage was about 0.55 RMB, which could bring about considerable economic benefit for coal mining enterprises.
With the development of the Low Earth Orbit (LEO) satellite communication technology, highlydependable wireless communication using LEO satellites has been getting much attention for emergency, marine research, and fo...
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Provided are a series of BTK inhibitors, and specifically disclosed are a compound, pharmaceutically acceptable salt thereof, tautomer thereof or prodrug thereof represented by formula (I), (II), (III) or (IV).
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US2017313683(A1)
Provided are a series of BTK inhibitors, and specifically disclosed are a compound, pharmaceutically acceptable salt thereof, tautomer thereof or prodrug thereof represented by formula (I), (II), (III) or (IV).
The Artificial Bee Colony (ABC) algorithm is one of the most recent swarm intelligence based algorithms which simulates the foraging behavior of honey bee colonies. In this work, a particle swarm inspired multi-elitis...
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The Artificial Bee Colony (ABC) algorithm is one of the most recent swarm intelligence based algorithms which simulates the foraging behavior of honey bee colonies. In this work, a particle swarm inspired multi-elitist ABC algorithm named PS-MEABC is proposed and applied for real-parameter optimization. In this modified version, the global best solution and an elitist randomly selected from the elitist archive are used to modify parameters of each food source in either onlooker bees or employed bees phases. PS-MEABC is compared with 5 state-of-the-art swarm based algorithms on CEC05 and BBOB12 benchmark functions in terms of four metrics: the mean error, the best error, the success rate (SR) and the expected running time (ERT). Wilcoxon signed ranks test results on the mean and the best error show that the performance of PS-MEABC is significantly better than or at least similar to these algorithms, and PS-MEABC has wider application range in terms of the success rate and faster convergence speed in terms of the expected running time. Our algorithm is comparable to its competitors with a fewer control parameters to be tuned.
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