Hugely sensitive and speedy Icosabutate medchemexpress thiocyanate enrichment and detection.Table 7. Comparison on the present

Hugely sensitive and speedy Icosabutate medchemexpress thiocyanate enrichment and detection.Table 7. Comparison on the present system with other procedures for the analysis of thiocyanate. Detection Technique acetonitrile/(NH4 )2 SO4 ATPS-IC IC (UV) Ion Pair Chromatography High Efficiency Liquid Chromatography (UV) Colorimetric sensor Gold nanoparticles colorimetry Surface Enhanced Raman Spectroscopy Methyl Isobutyl Ketone Extraction-Atomic Fluorescence Spectrometry Spectrophotometry Electrode electrochemical process Sample Raw milk Emulsion Ionic liquid Emulsion Fossil and drill waters Saliva/environmental water Emulsion Seawater Blood Saliva LOD 0.20 /L 0.08 mg/L 0.96 mg/L 0.06 mg/L 0.60 mg/L 11.60 /L 0.04 mg/L 1.33 /L 1.80 mg/L 0.58 /L RSD 1.six 0.40 1.40 1.20 4.50 3.2 ten 2.10 7 2.20 Literature This study [32] [33] [34] [34] [35] [36] [8] [37] [38]4. Conclusions In this study, a highly sensitive and rapid determination of thiocyanate was accomplished by utilizing ATPE of acetonitrile/(NH4 )2 SO4 for the separation and enrichment of thiocyanate, combined with ion chromatography. Optimization in the extraction situations from the acetonitrile/(NH4 )two SO4 system by RSM resulted within a recovery of 107.24 0.50 and an enrichment multiple of ten.74 0.03 for thiocyanate. The extraction mechanism was initially explored by FTIR. The constructed acetonitrile/(NH4 )2 SO4 ATPS-IC technique showed the linear range of the approach was from 0.05 mg/L to 15 mg/L, and R2 = 0.998, the LOD was 0.2 /L, the LQD was 0.six /L, the intraday precision was 1.6 , the interday precision was 4.three , as well as the recovery prices of standard addition had been among 81 and 119 .Author Contributions: Information curation, S.Z., H.Y., and P.C.; formal evaluation, S.Z., P.C. and B.L.; funding acquisition, B.J., Z.F. and B.T.; investigation, S.Z. and H.Y.; methodology, B.J., D.L., C.L., Z.F. and B.T.; project administration, B.J., Z.F. and B.T.; writing–original draft, B.J., S.Z. and H.Y.; writing–review and editing, B.J., Z.F. and B.T. All authors have read and agreed to the published version on the manuscript. Funding: This analysis was funded National Important Study and Improvement System of China (2018YFC1604204). Conflicts of Interest: The authors declare that they’ve no recognized competing financial interest or personal relationships that could have appeared to influence the work reported in this paper.
applied sciencesArticleResearch on HC-LSSVM Model for Soft Soil Settlement Prediction Based on Homotopy GNE-371 Data Sheet Continuation MethodGuangjun Cui 1,2,3 , Shenghua Xiong 1,two,3 , Cuiying Zhou 1,2,3, and Zhen Liu 1,2,3, 2School of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, China; [email protected] (G.C.); [email protected] (S.X.) Guangdong Engineering Research Centre for Key Infrastructures Safety, Guangzhou 510275, China Investigation Center for Geotechnical Engineering and Facts Technology, Sun Yat-sen University, Guangzhou 510275, China Correspondence: [email protected] (C.Z.); [email protected] (Z.L.)Citation: Cui, G.; Xiong, S.; Zhou, C.; Liu, Z. Research on HC-LSSVM Model for Soft Soil Settlement Prediction Depending on Homotopy Continuation Approach. Appl. Sci. 2021, 11, 10666. https://doi.org/10.3390/ app112210666 Academic Editor: Theodore E. Matikas Received: 24 September 2021 Accepted: 2 November 2021 Published: 12 NovemberAbstract: Prediction of soft soil settlement is an critical study topic in the field of civil engineering, and the least square assistance vector machine is amongst the.