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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 solidified/stabilized soil.Ultraviolet radiation (UVR) reaching the Earth surface is increasing and scarce information is available regarding effects of this stressor to early life stages of marine vertebrates. Therefore, this work aims to study the effects of UVR exposure during early development stages of the flatfish Solea senegalensis. Firstly, fish were exposed to UVR (six daily doses between 3.4 ± 0.08 and 8.6 ± 0.14 kJ m-2) at the following moments gastrula stage (24 h post fertilization, hpf), 1 and 2 days after hatching (dah, 48 and 72 hpf, respectively). In a second bioassay, fish at the beginning of metamorphosis were exposed to UVR (one or two daily doses of 7.2 ± 0.39 or 11.1 ± 0.49 kJ m-2) and then maintained until the end of metamorphosis. Mortality and effects on development, growth and behaviour were evaluated at the end of both bioassays (3 dah and 18 dah, respectively). Biomarkers of neurotransmission (acetylcholinesterase, AChE), oxidative stress (catalase, CAT) and biotransformation (glutathione S-transferase, GST) were also determined at the end of the early larvae bioassay, and metamorphosis progression was evaluated during the second bioassay. UVR exposure caused distinct effects depending on life stage. Altered pigmentation, decreased growth, impaired fish behaviour and AChE and GST inhibition were observed at the earlier larval phase. Whereas, decrease in growth was the main effect observed at the metamorphosis stage. In summary, the exposure of S. senegalensis early stages to environmentally relevant UVR doses led to adverse responses at different levels of biological organization, which might lead to implications in later life stages.The present research examines the landslide susceptibility in Rudraprayag district of Uttarakhand, India using the conditional probability (CP) statistical technique, the boost regression tree (BRT) machine learning algorithm, and the CP-BRT ensemble approach to improve the accuracy of the BRT model. Using the four fold of data, the models’ outcomes were cross-checked. The locations of existing landslides were detected by general field surveys and relevant records. 220 previous landslide locations were obtained, presented as an inventory map, and divided into four folds to calibrate and authenticate the models. For modelling the landslide susceptibility, twelve LCFs (landslide conditioning factors) were used. selleck chemical Two statistical methods, i.e. the mean absolute error (MAE) and the root mean square error (RMSE), one statistical test, i.e. the Freidman rank test, as well as the receiver operating characteristic (ROC), efficiency and precision were used for authenticating the produced landslide models. The results of the accuracy measures revealed that all models have good potential to recognize the landslide susceptibility in the Garhwal Himalayan region. Among these models, the ensemble model achieved a higher accuracy (precision 0.829, efficiency 0.833, AUC 89.460, RMSE 0.069 and MAE 0.141) than the individual models. According to the outcome of the ensemble simulations, the BRT model’s predictive accuracy was enhanced by integrating it with the statistical model (CP). The study showed that the areas of fallow land, plantation fields, and roadsides with elevations of more than 1500 m. with steep slopes of 24° to 87° and eroding hills are highly susceptible to landslides. The findings of this work could help in minimizing the landslides’ risk in the Western Himalaya and its adjoining areas with similar landscapes and geological characteristics.Producing a desirable adsorbent for removing endocrine disrupting compounds (EDCs) from aqueous solutions remains a major challenge. In this work, microporous-dominated nitrogen-doped framework carbons (MNFCs, s means the calcination temperature) with high specific surface area, ultra-microporous structure, and high nitrogen-doping can be obtained by a direct calcination of ethylene diamine tetraacetic acid tetrasodium (EDTA-4Na) without aid of any catalyst and nitrogen source. MNFCs were applied adsorbents to remove bisphenols from aqueous solution. Batch experiments showed MNFC-750 had a large adsorption capacity for bisphenols from aqueous solutions (409 mg/g for bisphenol A, 364 mg/g for bisphenol F, and 521 mg/g for bisphenol S) along with short equilibrium time (30 min), and good stability and reusability. Using multiple characterizations and comparative experiments along with theoretical calculations, we discovered that (1) nitrogen-doping can significantly boost the adsorption capacity; (2) adsorption sites are mainly the pyridinic-N instead of pyrrolic-N and graphitic-N; and (3) the adsorption mechanisms were mainly driven by Lewis acid-base interaction, hydrophobic interaction, π-π interaction and hydrogen bond interaction.