Urban Sewage Treatment Monitoring Based on 3DEEM Regional PCA

[1] Brereton R. G. Numerical introduction to principal components analysis. Journal of Chemometrics 2022:36(8):2–6. https://doi.org/10.1002/cem.3405 Search in Google Scholar

[2] Brereton R. G. Introduction to residuals and estimation by principal components analysis. Journal of Chemometrics 2022:36(10):2–7. https://doi.org/10.1002/cem.3407 Search in Google Scholar

[3] Ito A., Yanase E. Study into the chemical changes of tea leaf polyphenols during Japanese black tea processing. Food Research International 2022:160(10):2–9. https://doi.org/10.1016/j.foodres.2022.111731 Search in Google Scholar

[4] Gao S., Zhang H., Li H., Pei Y. Synthesis of sulfur-chlorine-doped fluorescent carbon quantum dots from leachate membrane concentrate as a selective probe for Pd²⁺ detection. Optical Materials 2023:139(5):2–10. https://doi.org/10.1016/j.optmat.2023.113746 Search in Google Scholar

[5] Shi J., Jiang G., Sun Z., Guo F., Wang Q., Liu F. Dissolved organic matter tracers reveal contrasting characteristics in the concentrated flow zone and matrix-with-fractures zone of a sulfate-contaminated karst aquifer in South China. Applied Geochemistry 2022:146(1):105–431. https://doi.org/10.1016/j.apgeochem.2022.105431 Search in Google Scholar

[6] Venturini F., Sperti M., Michelucci U., Gucciardi A., Martos V. M., Deriu M. A. Extraction of physicochemical properties from the fluorescence spectrum with 1D convolutional neural networks: Application to olive oil. Journal of Food Engineering 2023:336(1):2–8. https://doi.org/10.1016/j.jfoodeng.2022.111198 Search in Google Scholar

[7] Lee S. N., Ahn J., Joo T. Coherent Vibrational Spectrum via Time-Resolved Fluorescence for Molecular Dynamics and Identification of Emitting Species-Application to Excited-State Intramolecular Proton Transfer. The Journal of Physical Chemistry 2022:126(30):4962–4968. https://doi.org/10.1021/acs.jpca.2c03263 Search in Google Scholar

[8] Xu R. Z., Cao J. S., Feng G. Fast identification of fluorescent components in three-dimensional excitation-emission matrix fluorescence spectra via deep learning. Chemical Engineering Journal 2022:43(P2):132893. https://doi.org/10.1016/j.cej.2021.132893 Search in Google Scholar

[9] Tang J., Chen C., Shen X., Xiao F., Li X. A three-dimensional positivity-preserving and conservative multimoment finite-volume transport model on a cubed-sphere grid. Quarterly Journal of the Royal Meteorological Society 2022:148(749):3622–3638. https://doi.org/10.1002/qj.4377 Search in Google Scholar

[10] Cheng P., Tian H., Xiao X., Gai H., Zhou Q., Zhou L. Influence of Thermal Maturity on the Time-Resolved Emission Spectrum (TRES) Fluorescence Lifetime Characteristics of Crude Oils: A Preliminary Study Based on a Thermal Simulation Experiment of Crude Oils. Energy & Fuels 2023:37(7):5165–5178. https://doi.org/10.1021/acs.energyfuels.3c00474 Search in Google Scholar

[11] Han L., Chen Y., Zhang H., Li G., Jia Q., Zhang S. Low-temperature synthesis of six-principal-component high-entropy transition-metal carbide aerogel thermal insulator. Journal of the American Ceramic Society 2023:106(2):841–847. https://doi.org/10.1111/jace.18856 Search in Google Scholar

[12] Xue H., Cui P., Tan J., Zhang G., Ge S., Cai X. Separation of principal component dihydromyricetin from Ampelopsis grossedentata by high-speed counter-current chromatography and its interaction with corn starch. Journal of Food Science 2022:87(6):2350–2363. https://doi.org/10.1111/1750-3841.16128 Search in Google Scholar

[13] Kassinopoulos M., Mitsis G. D. A multi-measure approach for assessing the performance of fMRI preprocessing strategies in resting-state functional connectivity. Magnetic Resonance Imaging 2022:85(1):228–250. https://doi.org/10.1016/j.mri.2021.10.028 Search in Google Scholar

[14] Ameek S., Josh B., Els P., Jan C. A Principal Component Analysis of polycyclic aromatic hydrocarbon emission in NGC 7023. Monthly Notices of the Royal Astronomical Society 2022:511(2):2186–2200. https://doi.org/10.1093/mnras/stac157 Search in Google Scholar

[15] Moreno Y. S., Bournival G., Ata S. Classification of flotation frothers – A statistical approach. Chemical Engineering Science 2022:248(PB):2–12. https://doi.org/10.1016/j.ces.2021.117252 Search in Google Scholar

[16] Zhang T., Yang Y., Zhang M., Jiang H., Yan Z., Liu J., Liu X. Effect of soy lecithin concentration on physiochemical properties and rehydration behavior of egg white protein powder: Role of dry and wet mixing. Journal of Food Engineering 2022:328(9):2–10. https://doi.org/10.1016/j.jfoodeng.2022.111062 Search in Google Scholar

[17] Hou Z., Tian H., Wang J. S., Zhang X., Song Q., Zheng R., Chen H., Chen B., Bai X., Chen Y. Three-dimensional Propagation of the Global Extreme-ultraviolet Wave Associated with a Solar Eruption on 2021 October 28. The Astrophysical Journal 2022:928(2):97–98. https://doi.org/10.3847/1538-4357/ac590d Search in Google Scholar

[18] Tang W., Zhang L., Chen Q., Han M., Chen C., Liu W. Determination of monophenolase activity based on backpropagation neural network analysis of three-dimensional fluorescence spectroscopy. Journal of Biotechnology 2023:365(1):11–19. https://doi.org/10.1016/j.jbiotec.2023.02.001 Search in Google Scholar

[19] Brereton R. G. Introduction to statistical, algorithmic and theoretical basis of principal components analysis. Journal of Chemometrics 2022:36(9):2–9. https://doi.org/10.1002/cem.3406 Search in Google Scholar

[20] Shang L., Qiu A., Xu P., Yu F. Canonical Variate Nonlinear Principal Component Analysis for Monitoring Nonlinear Dynamic Processes. Journal of Chemical Engineering of Japan 2022:55(1):29–37. https://doi.org/10.1252/jcej.19we080 Search in Google Scholar

[21] Nsugbe E. Toward a Self-Supervised Architecture for Semen Quality Prediction Using Environmental and Lifestyle Factors. Artificial Intelligence and Applications 2023:1(1):35–42. https://doi.org/10.47852/bonviewAIA2202303 Search in Google Scholar