MOPSO Free Acid

Product Description

MOPSO Free Acid
Catalog number: B2015378
Lot number: Batch Dependent
Expiration Date: Batch dependent
Amount: 5 g
Molecular Weight or Concentration: 225.26 g/mol
Supplied as: Powder
Applications: a molecular tool for various biochemical applications
Storage: RT
Keywords: β-Hydroxy-4-morpholinepropanesulfonic acid; 3-Morpholino-2-hydroxypropanesulfonic acid;
Grade: Biotechnology grade. All products are highly pure. All solutions are made with Type I ultrapure water (resistivity >18 MΩ-cm) and are filtered through 0.22 um.

References:
1: Mansouri M, Safavi HR, Rezaei F. An improved MOPSO algorithm for multi-objective optimization of reservoir operation under climate change Environ Monit Assess. 2022 Mar 8;194(4):261.
2: Han HG, Liu Z, Lu W, Hou Y, Qiao JF. Dynamic MOPSO-Based Optimal Control for Wastewater Treatment Process IEEE Trans Cybern. 2021 May;51(5):2518-2528.
3: Wang S, Zhang T, Kong W, Wen G, Yu Y. An improved MOPSO approach with adaptive strategy for identifying biomarkers from gene expression dataset Math Biosci Eng. 2023 Jan;20(2):1580-1598.
4: Wang R, Wang H, Shi L, Han C, He Q, Che Y, Luo L. A novel framework of MOPSO-GDM in recognition of Alzheimer’s EEG-based functional network Front Aging Neurosci. 2023 Jun 29;15:1160534.
5: Rezaei F, Safavi HR. f-MOPSO/Div: an improved extreme-point-based multi-objective PSO algorithm applied to a socio-economic-environmental conjunctive water use problem Environ Monit Assess. 2020 Nov 19;192(12):767.
6: Yang Y, Han S, Sang H, Liu F. Preoperative planning method based on a MOPSO algorithm for robot-assisted cholecystectomy Int J Comput Assist Radiol Surg. 2022 Apr;17(4):731-744.
7: Rahimi MR, Makarem D, Sarspy S, Mahdavi SA, Albaghdadi MF, Armaghan SM. Classification of cancer cells and gene selection based on microarray data using MOPSO algorithm J Cancer Res Clin Oncol. 2023 Nov;149(16):15171-15184.
8: Goyal KK, Sharma N, Dev Gupta R, Singh G, Rani D, Banga HK, Kumar R, Pimenov DY, Giasin K. A Soft Computing-Based Analysis of Cutting Rate and Recast Layer Thickness for AZ31 Alloy on WEDM Using RSM-MOPSO Materials (Basel). 2022 Jan 15;15(2):635.
9: Taheri M, Alavi Moghaddam MR, Arami M. Techno-economical optimization of Reactive Blue 19 removal by combined electrocoagulation/coagulation process through MOPSO using RSM and ANFIS models J Environ Manage. 2013 Oct 15;128:798-806.
10: Hu C. A Comparative Study of Cultural and Traditional Education in Primary and Secondary Schools in Developed Countries Based on the MOPSO-CD-DNN Model Comput Intell Neurosci. 2022 Jul 12;2022:3973763.

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