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The human health risk (HHR) assessment to dense non-aqueous phase liquids (DNAPLs) exposure has become an important part of groundwater environment management. Usually, DNAPL transport models are applied to simulate the concentration distribution of contaminant for HHR assessment. The present paper studied the influences of model uncertainties on the HHR assessment, and the metric of Incremental Lifetime Cancer Risk (ILCR) was used to quantify HHR. The impacts of permeability's heterogeneity and the structure of DNAPL transport model (e.g., the constitutive model) on HHR assessment were evaluated based on a synthetical DNAPL transport model. The results demonstrate that, compared with the low heterogeneity, the high heterogeneity leads to lower average ILCR value at the control planes near the source zone, and higher average ILCR value at the control planes far away from the source zone. In addition, the HHR assessments would be inconsistent for the two constitutive models, i.e., Stone-Parker (S-P) and Corey-van Genuchten (C-v) models. Compared with the HHR assessment depending on C-v model, the mean of ILCR's probability distribution produced by S-P model is larger at the control planes near the source zone, and smaller at the control planes far away from the source zone. Moreover, based on a sandbox experiment, the impact of parameter uncertainty of DNAPL transport model on HHR assessment was evaluated by Markov chain Monte Carlo (MCMC) simulation. The results show that it is infeasible and risky to assess HHR by the specific parameters of contaminant transport model and ignoring parameter uncertainty. The HHR assessment by incorporating Bayesian uncertainty analysis could provide more flexible information. In addition, the sparse grid (SG) surrogate is an effective way to reduce computation burden caused by the larger number of model executions in the MCMC based HHR assessment. [ABSTRACT FROM AUTHOR]

Fine-mineral separation has been a difficult problem in the mineral-processing field. A new cyclonic-flotation system was designed to solve the fine-mineral-recovery problem. Its design and operation are different from those of other cyclonic-flotation columns. In this study for the new cyclonic column, optimal reagent dosages, solid concentration, and aeration rate were determined. Many factors influence the operation of column flotation; however, in this study, mainly the effect of the circulation rate on the flotation behavior of the wide and narrow particle-size ranges of coal was investigated. The chosen circulation rates were 0.895, 1.044, 1.210, 1.369, 1.461, 1.578, 1.653, and 1.752 m/s. The wide particle size refers to a value of less than 0.5 mm. The narrow particle-size ranges refer to values from -250 to +75 μm, -75 to +45 µm, v45 µm, and +250 µm. The results showed that the combustible recovery of the narrow-size particles increased first and then decreased with the increasing circulation rate. The combustible recovery order of the narrow-size ranges in the same flotation time was as follows: -250 to +75 µm > -75 to +45 µm > -45 µm > +250 µm. [ABSTRACT FROM AUTHOR]

During the courses of the human history, several major influenza pandemics caused great disasters to human beings. In this paper, we choose all PA protein sequences of influenza A virus from 1933 to 2013, and these PA protein sequences are translated into chaos game representation walk sequences. For each CGR walk sequence we calculate 25 index values related to sequence structure characteristics, and principal component analysis method is used to study these values. Then we construct a principal component model to early-warn influenza A virus pandemic, compute the comprehensive index values CIV, and sort these values in descending order. Through computing the comprehensive index values based on the model and sorting, the comprehensive index value in 2009 is 30.274, ranked first; the comprehensive index value in 1969 is 8.383, ranked second; and the comprehensive index value in 1959 is 5.684, ranked third. And there were well-known influenza A virus pandemics in 2009, 1969, 1959. It is found that those influenza A virus pandemic years are almost at the top of the list, so we can draw a conclusion using the model that there maybe an influenza A virus pandemic when the CIV in the year is significantly bigger than that in the nearby years and the CIV in the year is more than 3. [ABSTRACT FROM AUTHOR]