BackgroundElectronic waste (e-waste) recycling has remained primitive in Guiyu, China, and thus may contribute to the elevation of blood lead levels (BLLs) in children living in the local environment.ObjectivesWe compared the BLLs in children living in the e-waste recycling town of Guiyu with those living in the neighboring town of Chendian.MethodsWe observed the processing of e-waste recycling in Guiyu and studied BLLs in a cluster sample of 226 children < 6 years of age who lived in Guiyu and Chendian. BLLs were determined with atomic absorption spectrophotometry. Hemoglobin (Hgb) and physical indexes (height and weight, head and chest circumferences) were also measured.ResultsBLLs in 165 children of Guiyu ranged from 4.40 to 32.67 μg/dL with a mean of 15.3 μg/dL, whereas BLLs in 61 children of Chendian were from 4.09 to 23.10 μg/dL with a mean of 9.94 μg/dL. Statistical analyses showed that children living in Guiyu had significantly higher BLLs compared with those living in Chendian (p < 0.01). Of children in Guiyu, 81.8% (135 of 165) had BLLs > 10 μg/dL, compared with 37.7% of children (23 of 61) in Chendian (p < 0.01). In addition, we observed a significant increasing trend in BLLs with increasing age in Guiyu (p < 0.01). It appeared that there was correlation between the BLLs in children and numbers of e-waste workshops. However, no significant difference in Hgb level or physical indexes was found between the two towns.ConclusionsThe primitive e-waste recycling activities may contribute to the elevated BLLs in children living in Guiyu.

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Parameter sensitivity analyses have been widely applied to industrial problems for evaluating parameter significance, effects on responses, uncertainty influence, and so forth. In the interest of simple implementation and computational efficiency, this study has developed two sensitivity analysis methods corresponding to the situations with or without sufficient probability information. The probabilistic method is established with the aid of the stochastic response surface and the mathematical derivation proves that the coefficients of first-order items embody the parameter main effects on the response. Simultaneously, a nonprobabilistic interval analysis based method is brought forward for the circumstance when the parameter probability distributions are unknown. The two methods have been verified against a numerical beam example with their accuracy compared to that of a traditional variance-based method. The analysis results have demonstrated the reliability and accuracy of the developed methods. And their suitability for different situations has also been discussed.

A damage assessment problem can be stated as a constraint satisfaction problem utilizing the translational and rotational displacements of a structure as measurements. By this means, usual numerical models are no longer required for a damage assessment, which considerably simplifies the solution process. In order to avoid the use of rotational displacements that are difficult to measure in practice, an improved analytical redundancy reduction method has been developed in which rotational displacements are replaced by translational ones. Moreover, some constraint equation positions in the decomposition of a static equilibrium matrix are exchanged according to their association with pre-assumed damaged elements. Then damage is located according to the changes in the relevant constraints of specific elements or substructures. Besides, the deviation increments of improved analytical redundancy reduction can embody the stiffness changes of the damaged elements. The proposed improved analytical redundancy reduction method was validated using both numerical and experimental steel box beams under static loads. The damage assessment results demonstrate the superiority of the improved analytical redundancy reduction method over the constraint satisfaction problem and analytical redundancy reduction methods.