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In recent years, hydrophobic deep eutectic solvents as new generation of green solvents have attracted wide attention in liquid microextraction technique. In this article, four hydrophobic deep eutectic solvents composed of trioctylmethylammonium chloride and oleic acid were designed and prepared firstly. Combined with high‐performance liquid chromatography, these deep eutectic solvents were used as an extraction solvent in vortex‐assisted dispersive liquid–liquid microextraction for the selective enrichment and indirect determination of trace nitrite from real water and biological samples. This method is based on the diazotization‐coupling reaction of nitrite with p‐nitroaniline and diphenylamine in acidic water, and then the nitrite is quantified indirectly by measuring the obtained azo compounds. Some factors influencing the extraction efficiency, including the reaction and extraction conditions, were investigated. Under the optimized conditions, the method has a linear range of 1–300 μg/L with a correlation coefficient of 0.9924, limit of detection of 0.2 μg/L, limit of quantitation of 1 μg/L, intraday and interday relative standard deviations of 4.0 and 6.0%. This method was successfully applied in determination of nitrite from three environmental water and two biological samples with the recovery in the range of 90.5–115.2%. In addition, these results were well agreement with those obtained by the conventional Griess method. [ABSTRACT FROM AUTHOR]

In addressing the challenge of ships being prone to occlusion in multi‐target situations during ship target detection, leading to missed and false detections, this paper proposes an enhanced ship detection algorithm for YOLOv7‐tiny. The proposed method incorporates several key modifications. Firstly, it introduces the Convolutional Block Attention Module in the Backbone section of the original model, emphasizing position information while attending to channel features to enhance the network's ability to extract crucial information. Secondly, it replaces standard convolution with GSConv convolution in the Neck section, preserving detailed information and reducing computational load. Subsequently, the lightweight operator Content‐Aware ReAssembly of Features is employed to replace the original nearest‐neighbour interpolation, mitigating the loss of feature information during the up‐sampling process. Finally, the localization loss function, SIOU Loss, is utilized to calculate loss, expedite training convergence, and enhance detection accuracy. The research results indicate that the precision of the improved model is 91.2%, mAP@0.5 is 94.5%, and the F1‐score is 90.7%. These values are 3.7%, 5.5%, and 4.2% higher than those of the original YOLOv7‐tiny model, respectively. The improved model effectively enhances detection accuracy. Additionally, the improved model achieves an FPS of 145.4, meeting real‐time requirements. [ABSTRACT FROM AUTHOR]

A novel green hydrophilic levofloxacin imprinted polymer was presented via one‐step polymerization in water using ionic liquid 1,6‐hexa‐3,3′‐bis‐1‐vinylimidazolium bromine with multiple hydrophilic groups and 2‐hydroxyethyl methacrylate as a co‐functional monomer. Adsorption experiment revealed that the ionic liquid significantly improved the water compatible of imprinted polymer, and the excellent recognition of molecularly imprinted polymer for levofloxacin in water corresponds to the synergetic effect of H‐bonding and the electrostatic and π–π interactions between the levofloxacin and co‐functional monomer. Furthermore, the adsorption process of the imprinted material towards levofloxacin fitted the Langmuir model, and the maximum binding amount of levofloxacin onto the imprinted and corresponding non‐imprinted polymer were 16.45 and 6.82 mg/g at 25°C, respectively. After optimizing the parameters affecting solid phase extraction performance, an enrichment and determination system was achieved to separate and detect levofloxacin from water and sediment samples with recoveries that ranged from 83.67 to 101.33% and relative standard deviation of less than 5.59%. [ABSTRACT FROM AUTHOR]