This study considered the possibility of using visible and near infrared(VNIR) spectral absorption feature parameters(SAFPs) in predicting the concentration and mapping the distribution of heavy metals in sediments of...This study considered the possibility of using visible and near infrared(VNIR) spectral absorption feature parameters(SAFPs) in predicting the concentration and mapping the distribution of heavy metals in sediments of the Takab area. In total, 60 sediment samples were collected along main streams draining from the mining districts and tailing sites, in order to measure the concentration of As, Co, V, Cu, Cr, Ni, Hg, Ti, Pb and Zn and the reflectance spectra(350–2500 nm). The quantitative relationship between SAFPs(Depth500 nm, R610/500 nm, R1344/778 nm, Area500 nm, Depth2200 nm, Area2200 nm, Asym2200 nm) and geochemical data were assessed using stepwise multiple linear regression(SMLR) and enter multiple linear regression(EMLR) methods. The results showed a strong negative correlation between Ni and Cr with Area2200 nm, a significant positive correlation between As and Asym2200 nm, Ni and Co with Depth2200 nm, as well as Co, V and total values with Depth500 nm. The EMLR method eventuated in a significant prediction result for Ni, Cr, Co and As concentrations based on spectral parameters, whereas the prediction for Zn, V and total value was relatively weak. The spatial distribution pattern of geochemical data showed that mining activities, along with the natural weathering of base metal occurrences and rock units, has caused high concentrations of heavy metals in sediments of the Sarough River tributaries.展开更多
We study an explicit exponential scheme for the time discretisation of stochastic SchrS- dinger Equations Driven by additive or Multiplicative It6 Noise. The numerical scheme is shown to converge with strong order 1 i...We study an explicit exponential scheme for the time discretisation of stochastic SchrS- dinger Equations Driven by additive or Multiplicative It6 Noise. The numerical scheme is shown to converge with strong order 1 if the noise is additive and with strong order 1/2 for multiplicative noise. In addition, if the noise is additive, we show that the exact solutions of the linear stochastic Sehr6dinger equations satisfy trace formulas for the expected mass, energy, and momentum （i. e., linear drifts in these quantities）. Furthermore, we inspect the behaviour of the numerical solutions with respect to these trace formulas. Several numerical simulations are presented and confirm our theoretical results.展开更多
文摘This study considered the possibility of using visible and near infrared(VNIR) spectral absorption feature parameters(SAFPs) in predicting the concentration and mapping the distribution of heavy metals in sediments of the Takab area. In total, 60 sediment samples were collected along main streams draining from the mining districts and tailing sites, in order to measure the concentration of As, Co, V, Cu, Cr, Ni, Hg, Ti, Pb and Zn and the reflectance spectra(350–2500 nm). The quantitative relationship between SAFPs(Depth500 nm, R610/500 nm, R1344/778 nm, Area500 nm, Depth2200 nm, Area2200 nm, Asym2200 nm) and geochemical data were assessed using stepwise multiple linear regression(SMLR) and enter multiple linear regression(EMLR) methods. The results showed a strong negative correlation between Ni and Cr with Area2200 nm, a significant positive correlation between As and Asym2200 nm, Ni and Co with Depth2200 nm, as well as Co, V and total values with Depth500 nm. The EMLR method eventuated in a significant prediction result for Ni, Cr, Co and As concentrations based on spectral parameters, whereas the prediction for Zn, V and total value was relatively weak. The spatial distribution pattern of geochemical data showed that mining activities, along with the natural weathering of base metal occurrences and rock units, has caused high concentrations of heavy metals in sediments of the Sarough River tributaries.
文摘We study an explicit exponential scheme for the time discretisation of stochastic SchrS- dinger Equations Driven by additive or Multiplicative It6 Noise. The numerical scheme is shown to converge with strong order 1 if the noise is additive and with strong order 1/2 for multiplicative noise. In addition, if the noise is additive, we show that the exact solutions of the linear stochastic Sehr6dinger equations satisfy trace formulas for the expected mass, energy, and momentum （i. e., linear drifts in these quantities）. Furthermore, we inspect the behaviour of the numerical solutions with respect to these trace formulas. Several numerical simulations are presented and confirm our theoretical results.
