• A soft-sensing method based on GK-ARFNN is proposed. • The GK clustering algorithm is used to develop the initial fuzzy rule base. • The recursive link is introduced into the FNN to improve dynamic mapping ability. • A hierarchical adaptive second-order optimization algorithm is developed. To address the issue of soft-sensing of effluent total phosphorus in wastewater treatment processes (WWTPs), a soft-sensing system based on an adaptive recursive fuzzy neural network with Gustafson-Kessel (GK) clustering and hierarchical adaptive second-order optimization algorithm (HAS) is proposed in this paper. In GK-ARFNN, first, the GK clustering algorithm was utilized to cluster the input–output dataset. Thus, the establishment of the initial fuzzy rule base and the determination of the parameter value of the fuzzy set membership function was realized. Then, the recursive layer was added into FNN to improve the dynamic mapping ability of the system. Finally, the HAS algorithm was developed based on the improved Levenberg-Marquardt (LM) optimization algorithm, and all the free parameters of the GK-ARFNN were adjusted online using HAS to improve the generalization capability and prediction accuracy of the soft-sensing system. In addition, the convergence of the proposed GK-ARFNN algorithm was also analyzed in this paper, which can ensure the effectiveness of the solutions to modelling issues for practical industrial processes. The simulation results demonstrate that the GK-ARFNN-based soft-sensing system introduced in this paper achieved satisfactory accuracy in the prediction of effluent total phosphorus in WWTPs. The source codes of GK-ARFNN and some competitors can be downloaded from https://github.com/hyitzhb/GK-ARFNN . 

Soft-sensing of effluent total phosphorus using adaptive recurrent fuzzy neural network with Gustafson-Kessel clustering

Selection of microalgae strains for sustainable production of aviation biofuel.

A waste-to-wealth approach was adopted in this study to establish an efficient, economically viable, and environmentally sustainable process for producing biodiesel from Spent Vegetable Oil (SVO). This involved the synthesis and calcination at 800 °C of aluminum and iron oxide snail shell-based catalysts (F2O3-SS and Al2O3-SS) using the wet-impregnation method. The catalysts were characterized using FTIR, XRD, and SEM-EDS, and then used in the transesterification of SVO to produce biodiesel. Optimization was performed using three-factor Box-Behnken Design (BBD): reaction time, catalyst concentration, and temperature. After extensive physicochemical study, FTIR and GC–MS analyses were further carried out on the produced biodiesel. The XRD results showed crystalline composites with an average lattice parameter of 8.5583 Å (Fe2O3-SS) and 7.4813 Å (Al2O3-SS). EDX and FTIR confirmed surface modifications with the formation of metal oxide (Me-O) at 543 cm−1 (Al-O) and 613 cm−1 (Fe-O). SEM micrographs show flower-like and spherical-shaped nanocomposites of F2O3-SS (162 nm) and Al2O3-SS (660 nm), respectively. Under optimal transesterification conditions of 120 min, 1.0 wt%, and 90 °C, biodiesel yields of 94.23 ± 0.50 and 91.94 ± 0.21 % were recorded for both Al2O3-SS and F2O3-SS, respectively. FTIR analysis corroborated the biodiesel production, with a distinctive C-O-C ester stretch at 1021 cm−1 for both catalysts. The produced biodiesel recorded a low moisture content and specific gravity values of 0.03 % and 0.8011 kg/m3 for Al2O3-SS, 0.02 % and 0.8042 kg/m3 for Fe2O3-SS. GC–MS analysis shows hexadecanoic acid, 15-methyl-, methyl ester as the predominant component, constituting 29.87 % and 25.34 % for Al2O3-SS and F2O3-SS, respectively. Furthermore, activation energy (Ea) values of 50.42 and a pre-exponential factor (A) of 2.2 × 105 were recorded for Al2O3-SS while 45.94 kJ/mol and 6.2 × 104 were recorded for Ea and A, respectively for Fe2O3-SS. The outcomes of this research reveal the efficacy of utilizing aluminum and iron oxide snail shell-based nanocatalysts for biodiesel production from spent vegetable oil. However, future studies should focus on evaluating their long-term stability, assessing their environmental impact, and identifying potential applications in large-scale biodiesel production. 

Biodiesel production from spent vegetable oil with Al2O3 and Fe2O3-biobased heterogenous nanocatalysts: Comparative and optimization studies

Based on the panel data in China from 2010 to 2019, this study explores the role and mechanism of green finance in alleviating energy poverty and verifies the policy effects of green finance using the regression control method (RCM). The empirical results indicate that if the green finance index is increased by 1 unit, the regional energy poverty level will significantly reduce by 0.08–0.121 units. Green finance significantly suppresses energy poverty by restricting energy-intensive industrial development, improving energy efficiency, and promoting energy structure adjustment. The effectiveness of green finance pilot policy in different regions differs remarkably. The green finance pilot policy implementation in Guangdong and Xinjiang has significantly alleviated the local energy poverty, while the policy effect in Zhejiang, Jiangxi and Guizhou is insignificant. This study broadens the research paradigm of "finance and energy" in theory, and it provides a new idea for countries to explore the establishment of a green finance system and tap its value in promoting sustainable energy consumption. 

Natural resources policy making through finance? The role of green finance on energy resources poverty

Biodiesel degradation mechanism upon exposure of metal surfaces: A study on biodiesel sustainability

Effects of unsaturated fatty acid methyl esters on the oxidation stability of biodiesel determined by gas chromatography-mass spectrometry and information entropy methods

Determination of total phosphorus in biodiesel by ion chromatography

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Effects of unsaturated fatty acid methyl esters on the oxidation stability of biodiesel determined by gas chromatography-mass spectrometry and information entropy methods

Determination of total phosphorus in biodiesel by ion chromatography