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Antibiotic residues in the aquatic environment have become a global problem posing a serious threat to the environment and an inherent health risk to human beings. In this study, experiments were carried to investigate the use of carbon material modified by liquid nitrogen treatment (CM1) and carbon material unmodified by liquid nitrogen treatment (CM2) as adsorbents for the removal of the antibiotic ampicillin from aqueous solutions. The properties of the CMs (CM1 and CM2) and the effects of variations of the key operating parameters on the removal process were examined, and kinetic, isothermal and thermodynamic experimental data were studied. The results showed that CM1 had larger specific surface area and pore size than CM2. The ampicillin adsorption was more effective on CM1 than that on CM2, and the maximum adsorption capacity of ampicillin onto CM1 and CM2 was 206.002 and 178.423 mg/g, respectively. The kinetic data revealed that the pesudo-second order model was more suitable for the fitting of the experimental kinetic data and the isothermal data indicated that the Langmuir model was successfully correlated with the data. The adsorption of ampicillin was a spontaneous reaction dominated by thermodynamics. In synthetic wastewater, CM1 and CM2 showed different removal rates for ampicillin: 92.31% and 86.56%, respectively. For an adsorption-based approach, carbon material obtained by the liquid nitrogen treatment method has a stronger adsorption capacity, faster adsorption, and was non-toxic, therefore, it could be a promising adsorbent, with promising prospects in environmental pollution remediation applications.

The traditional particle swarm optimization algorithm (particle swarm optimization, PSO) was improved and a multiisland particle swarm optimization algorithm was proposed in this paper. The random values of weight coefficient were taken of the multi-island particle swarm optimization algorithm. It takes the harmonic distortion, capacity of reactive power compensation and the original investment as three objectives, and uses multiisland particle swarm optimization algorithm to design the PPF parameters of Hybrid active power filter. Simulation and experimental results verify the above mentioned theory and the design.

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