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https://www.selleckchem.com/products/scutellarin.html In the context of increasing pressure on water bodies, many fish-based indices have been developed to evaluate the ecological status of rivers. However, most of these indices suffer from several limitations, which hamper the capacity of water managers to select the most appropriate measures of restoration. Those limitations include (i) being dependent on reference conditions, (ii) not satisfactorily handling complex and non-linear biological responses to pressure gradients, and (iii) being unable to identify specific risks of stream degradation in a multi-pressure context. To tackle those issues, we developed a diagnosis-based approach using Random Forest models to predict the impairment probabilities of river fish communities by 28 pressure categories (chemical, hydromorphological and biological). In addition, the database includes the abundances of 72 fish species collected from 1527 sites in France, sampled between 2005 and 2015; and fish taxonomic and biological information. Twenty random forest models prents, resulting in an efficient assessment of ecological risks across various spatial and temporal scales.In this research, degradation of three sulfonamide antibiotic compounds (SNAs) such as Sulfasalazine (SSZ), Sulfamethoxazole (SMX) and Sulfamethazine (SMT) as well as Metronidazole (MNZ) were investigated for the first time using experimental, modeling and simulation data under O3, H2O2, and O3/H2O2 systems. The kinetic and synergistic study confirmed the pseudo-first-order reaction and highest performance of the O3/H2O2 process for the SNAs degradation process. Two modeling approach, central composite design (CCD) based on response surface methodology (RSM) and artificial neural network (ANN) were utilized to investigate the optimization and modeling of SSZ degradation as the response of O3/H2O2 system and results were compared. The individual and interactive effects of main operational parameters were a

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