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https://www.selleckchem.com/products/pd0166285.html Furthermore, compared with simple linear ensemble learning, RF increases the generalization ability for robustness to achieve the final nonlinear output results. Two markets' real data of carbon trading in china are as the experiment cases to test the effectiveness of the above model. The final simulation results indicate that the proposed model performs better than the other four benchmark methods reflected by the smaller statistical errors. Overall, the developed approach provides an effective method for predicting carbon price.This paper presents a study on utilizing a novel BCP binder, basic oxygen furnace slag (BOFS) activated with mixed calcium carbide residue (CCR) and phosphogypsum (PG), to solidify/stabilize heavy metals in industrial contaminated site soil. The effects of curing time and binder dosage on the geoenvironmental properties of the solidified/stabilized soil including soil pH, electrical conductivity, unconfined compressive strength, and leachability were tested and discussed. Chemical speciation of target heavy metals, pore-size distribution of treated soil, and phase identification of reaction products were analyzed to understand the mechanisms leading to the change of geoenvironmental properties. The results demonstrated that the addition of the BCP binder yielded remarkable increase in soil pH, unconfined compressive strength, and relative binding intensity index (IR) of target heavy metals including nickel (Ni) and zinc (Zn), while significantly decreased the electrical conductivity and leachability of contaminated soil. The IR value of heavy metals had a good linear relationship with the leached concentrations on a semi-logarithmic scale. The formation of heavy metal-bearing precipitates, absorptivity of calcium silicate hydrate (C-S-H), heavy metals encapsulation by C-S-H, and ion-exchange of heavy metals with ettringite (AFt) contributed to the immobilization of heavy metals in the soli

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