Landslide susceptibility mapping is a crucial tool for disaster prevention and management.The performance of conventional data-driven model is greatly influenced by the quality of the samples data.The random selection...Landslide susceptibility mapping is a crucial tool for disaster prevention and management.The performance of conventional data-driven model is greatly influenced by the quality of the samples data.The random selection of negative samples results in the lack of interpretability throughout the assessment process.To address this limitation and construct a high-quality negative samples database,this study introduces a physics-informed machine learning approach,combining the random forest model with Scoops 3D,to optimize the negative samples selection strategy and assess the landslide susceptibility of the study area.The Scoops 3D is employed to determine the factor of safety value leveraging Bishop’s simplified method.Instead of conventional random selection,negative samples are extracted from the areas with a high factor of safety value.Subsequently,the results of conventional random forest model and physics-informed data-driven model are analyzed and discussed,focusing on model performance and prediction uncertainty.In comparison to conventional methods,the physics-informed model,set with a safety area threshold of 3,demonstrates a noteworthy improvement in the mean AUC value by 36.7%,coupled with a reduced prediction uncertainty.It is evident that the determination of the safety area threshold exerts an impact on both prediction uncertainty and model performance.展开更多
The leaching behaviour of Cu and Zn from contaminated soils at a copper mine was investigated using four extractants： citric acid （CA）, oxalic acid （OA）, ethylenediaminetetraacetic acid （EDTA） and nitrilotriace...The leaching behaviour of Cu and Zn from contaminated soils at a copper mine was investigated using four extractants： citric acid （CA）, oxalic acid （OA）, ethylenediaminetetraacetic acid （EDTA） and nitrilotriacetic acid （NTA）. Six soil samples were characterized for the distribution of four chemical fractions of Cu or Zn （acid-soluble, reducible, oxidizable and residual）. For the extraction of Cu, EDTA is more effective than other extmctants when the concentration is less than 0.02 mol/L. The leaching efficiency for Cu was at least 15% higher for EDTA than for the other extractants at the same concentrations. Similar leaching behaviour was observed in the extraction of Zn. After extraction by CA, OA, EDTA or NTA, the acid-soluble fractions and the reducible fractions of Cu were the main fractions extracted. The potential environmental risks related to speciation were evaluated, and after extraction these risks were reduced.展开更多
The heavy metal(such as Cr,Ni,Cu,Cd,Pb,and Zn)concentration,speciation,and pollution source in 43 sediment samples from the Xiangjiang River were investigated using sequential extraction combined with Pb isotope analy...The heavy metal(such as Cr,Ni,Cu,Cd,Pb,and Zn)concentration,speciation,and pollution source in 43 sediment samples from the Xiangjiang River were investigated using sequential extraction combined with Pb isotope analysis.Cu,Cd,Pb,and Zn concentrations are higher than their background values,while Cr and Ni concentrations are close to those.Sequential extraction demonstrates that heavy metals have different fractions,showing different bioavailabilities.The w(206Pb)/w(207Pb)ratio increases with decreasing bioavailability in the order of exchangeable<carbonate≈Fe-Mn oxides≈organic<residual(p<0.05).Wastewater,dust,and slag from mining and smelting areas,and the residual Pb are assumed to be the primary anthropogenic and natural sources of Pb,respectively.The percentages of anthropogenic Pb in the exchangeable,carbonate,Fe-Mn oxides,and organic fractions are(91.5±16.7)%,(61.1±13.9)%,(57.4±11.1)%,and(55.5±11.2)%,respectively,suggesting a significant input of anthropogenic Pb in these four fractions.展开更多
A new testing procedure to estimate the low-temperature stiffness of the reclaimed asphalt pavement （RAP） binder was developed. In the testing procedure, the SuperpaveTM Bending Beam Rheometer （BBR） with special m...A new testing procedure to estimate the low-temperature stiffness of the reclaimed asphalt pavement （RAP） binder was developed. In the testing procedure, the SuperpaveTM Bending Beam Rheometer （BBR） with special modifications and binder blending charts by Asphalt Institute were utilized. Modifications involved the development of a new kind of sample mold and different testing parameters were made to BBR testing procedure to capture the theological properties of bitumen mortars produced by mixing fresh binder with fine RAP materials or RAP aggregate. The stiffness relationship between binder and bitumen mortar was established based on the BBR test results. The blended binder stiffness in bitumen RAP mortar was estimated from the RAP mortar stiffness based on the binder-mortar relationship. And finally, the RAP binder stiffness was estimated from the blended binder and fresh binder stiffness based on the blending charts by Asphalt Institute. The results indicate that the new procedure can capture the rheological properties of bitumen mortar and can be used to estimate the low temperature stiffness of RAP binder without binder extraction and/or any chemical treatments.展开更多
基金Project(G2022165004L)supported by the High-end Foreign Expert Introduction Program,ChinaProject(2021XM3008)supported by the Special Foundation of Postdoctoral Support Program,Chongqing,China+1 种基金Project(2018-ZL-01)supported by the Sichuan Transportation Science and Technology Project,ChinaProject(HZ2021001)supported by the Chongqing Municipal Education Commission,China。
文摘Landslide susceptibility mapping is a crucial tool for disaster prevention and management.The performance of conventional data-driven model is greatly influenced by the quality of the samples data.The random selection of negative samples results in the lack of interpretability throughout the assessment process.To address this limitation and construct a high-quality negative samples database,this study introduces a physics-informed machine learning approach,combining the random forest model with Scoops 3D,to optimize the negative samples selection strategy and assess the landslide susceptibility of the study area.The Scoops 3D is employed to determine the factor of safety value leveraging Bishop’s simplified method.Instead of conventional random selection,negative samples are extracted from the areas with a high factor of safety value.Subsequently,the results of conventional random forest model and physics-informed data-driven model are analyzed and discussed,focusing on model performance and prediction uncertainty.In comparison to conventional methods,the physics-informed model,set with a safety area threshold of 3,demonstrates a noteworthy improvement in the mean AUC value by 36.7%,coupled with a reduced prediction uncertainty.It is evident that the determination of the safety area threshold exerts an impact on both prediction uncertainty and model performance.
基金Project(2232013A3-08)supported by the Fundamental Research Funds for the Central Universities,ChinaProject supported by Shanghai Pujiang Program and DHU Distinguished Young Professor Program,China
文摘The leaching behaviour of Cu and Zn from contaminated soils at a copper mine was investigated using four extractants： citric acid （CA）, oxalic acid （OA）, ethylenediaminetetraacetic acid （EDTA） and nitrilotriacetic acid （NTA）. Six soil samples were characterized for the distribution of four chemical fractions of Cu or Zn （acid-soluble, reducible, oxidizable and residual）. For the extraction of Cu, EDTA is more effective than other extmctants when the concentration is less than 0.02 mol/L. The leaching efficiency for Cu was at least 15% higher for EDTA than for the other extractants at the same concentrations. Similar leaching behaviour was observed in the extraction of Zn. After extraction by CA, OA, EDTA or NTA, the acid-soluble fractions and the reducible fractions of Cu were the main fractions extracted. The potential environmental risks related to speciation were evaluated, and after extraction these risks were reduced.
基金Project(2009ZX07212-001)supported by the Major Science and Technology Program for Water Pollution Control and Treatment of ChinaProject(51079002)supported by the National Natural Science Foundation of China
文摘The heavy metal(such as Cr,Ni,Cu,Cd,Pb,and Zn)concentration,speciation,and pollution source in 43 sediment samples from the Xiangjiang River were investigated using sequential extraction combined with Pb isotope analysis.Cu,Cd,Pb,and Zn concentrations are higher than their background values,while Cr and Ni concentrations are close to those.Sequential extraction demonstrates that heavy metals have different fractions,showing different bioavailabilities.The w(206Pb)/w(207Pb)ratio increases with decreasing bioavailability in the order of exchangeable<carbonate≈Fe-Mn oxides≈organic<residual(p<0.05).Wastewater,dust,and slag from mining and smelting areas,and the residual Pb are assumed to be the primary anthropogenic and natural sources of Pb,respectively.The percentages of anthropogenic Pb in the exchangeable,carbonate,Fe-Mn oxides,and organic fractions are(91.5±16.7)%,(61.1±13.9)%,(57.4±11.1)%,and(55.5±11.2)%,respectively,suggesting a significant input of anthropogenic Pb in these four fractions.
基金Project(200831800044) supported by the Ministry of Communication of ChinaProject(50878054) supported by the National Natural Science Foundation of ChinaProject(06Y31) supported by the Department of Communication of Zhejiang Province,China
文摘A new testing procedure to estimate the low-temperature stiffness of the reclaimed asphalt pavement （RAP） binder was developed. In the testing procedure, the SuperpaveTM Bending Beam Rheometer （BBR） with special modifications and binder blending charts by Asphalt Institute were utilized. Modifications involved the development of a new kind of sample mold and different testing parameters were made to BBR testing procedure to capture the theological properties of bitumen mortars produced by mixing fresh binder with fine RAP materials or RAP aggregate. The stiffness relationship between binder and bitumen mortar was established based on the BBR test results. The blended binder stiffness in bitumen RAP mortar was estimated from the RAP mortar stiffness based on the binder-mortar relationship. And finally, the RAP binder stiffness was estimated from the blended binder and fresh binder stiffness based on the blending charts by Asphalt Institute. The results indicate that the new procedure can capture the rheological properties of bitumen mortar and can be used to estimate the low temperature stiffness of RAP binder without binder extraction and/or any chemical treatments.
