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Environmental Science and Pollution Research - Vegetated buffer strips (VBSs) are widely encouraged as a cost-effective strategy to address phosphorus (P) pollution associated with agricultural...  相似文献   
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Environmental Science and Pollution Research - Fruits are the valuable and important components of human diet. Among them, Prunus persica is a rich source of different minerals and dietary fibers....  相似文献   
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Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.  相似文献   
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Sampling of the offshore seabed sediments of southwestern part of the Caspian Sea was carried out by gravity corer in order to study heavy metal concentration and the physicochemical factors controlling their distribution in the fine-grained fraction. The grain size distribution, amount, and type of clay minerals, total organic carbon (TOC) content, and Eh–pH of the sediments were determined. The average concentrations of the heavy metals in ppm are Mn (563), Cu (207.5), Sr (187), Zn (94), Pb (26.3), Ni (14.5), Co (11.5), Cd (2.56), and Ag (1.04) in their order of abundances. Co and Zn mostly indicate increase in silt-size fraction of the sediments suggesting their probable detrital provenance but the Mn, Ni, Cu, Sr, Pb, Cd, and Ag concentrations show a similar trend to distribution of the clay-size fraction. The concentrations of Mn, Co, and Cd increase with increase in the TOC content but the Cu, Pb, Ni, Ag, and Sr concentrations decrease with increase of the TOC content. The amounts of Zn, Cu, Sr, Pb, Cd, and Ag increase with increase in the CaCO3 content. The calculated enrichment factor indicates that the sediments are very strong to extremely enriched in Ag, significantly enriched in Cu and Cd, and depleted to mineral for Pb, Sr, Co, Ni, and Zn. Variations of the Cu, Sr, Cd, Ag, and Pb concentrations are similar to the clay and CaCO3 distributions.  相似文献   
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The study was carried out to investigate the effects of filler content and two different compatibilizing agents (Eastman G-3003 and G-3216) on the mechanical properties of polypropylene reinforced with corn stalk and wood flour. In the sample preparation, three levels of filler loading (30, 40 and 50 wt%) and one level of compatibilizing agent content (2.5 wt%) were used. For overall trend, with addition of both grades of the compatibilizing agents, tensile and flexural properties of the composites significantly improved, as compared with the pure PP. Tensile and flexural properties reach a maximum at 40 wt% filler content and gradually decrease with a further increase in wood particle content. The composites treated with G-3003 gave better results in comparison with G-3216. This could be caused by the high melt viscosity of G-3003. In general, corn stalk flour filled composites showed superior mechanical properties.  相似文献   
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