In ecological studies, researchers often try to convey the analysis results to individual level based on aggregate data. In order to do this correctly, the possibility of ecological bias should be studied and addressed. One of the key ideas used to address the ecological bias issue is to derive the ecological model from the individual model and to check whether the parameter of interest in the individual model is identifiable in the ecological model. However, the procedure depends on unverifiable assumptions, and we recommend checking how sensitive the results are to these unverifiable assumptions. We analyzed the tuberculosis data that was collected in Seoul in 2005 using a spatial ecological regression model for the aggregate count data with spatial correlation, and found that the deprivation index is likely to have a small positive effect on the occurrence risk of tuberculosis in individual level in Seoul. We considered this finding in various aspects by performing in depth sensitivity analyses. In particular, our findings are shown to be robust to the distribution assumptions for the individual exposure and missing binary covariate across various scenarios. 相似文献
A series of Co-La catalysts were prepared using the wet impregnation method and the synthesis of catalysts were modified by controlling pH with the addition of ammonium hydroxide or oxalic solution. All the catalysts were systematically investigated for NO oxidation and SO2 resistance in a fixed bed reactor and were characterized by Brunanuer–Emmett–Teller (BET) method, Fourier Transform infrared spectroscopy (FTIR), X–ray diffraction (XRD), Thermogravimetric (TG) and Ion Chromatography (IC). Among the catalysts, the one synthesized at pH = 1 exhibited the maximum NO conversion of 43% at 180°C. The activity of the catalyst was significantly suppressed by the existence of SO2 (300 ppm) at 220°C. Deactivation may have been associated with the generation of cobalt sulfate, and the SO2 adsorption quantity of the catalyst might also have effected sulfur resistance. In the case of the compact selective catalytic reduction (SCR), the activity increased from 74% to 91% at the highest gas hourly space velocity (GHSV) of 300000 h–1 when the NO catalyst maintained the highest activity, in excess of 50% more than that of the standard SCR.
Nitrate analysis in water is one of the most frequently applied methods in environmental chemistry. Current methods for nitrate are generally based on toxic substances. Here, we show that a viable alternative method is to use the enzyme nitrate reductase. The key to applying this Green Chemistry solution for nitrate analysis is plentiful, inexpensive, analytical grade enzyme. We demonstrate that recombinant Arabidopsis nitrate reductase, expressed in the methylotrophic yeast Pichia pastoris, is a highly effective catalyst for nitrate analysis at 37°C. Recombinant production of enzyme ensures consistent quality and provides means to meet the needs of environmental chemistry. 相似文献
