Industrial development has brought about not only rapid economic growth, but also serious environmental pollution in China, which has led to serious health problems and heavy economic burdens on healthcare. Therefore, the relationship between the industrial air pollution and health care expenditure (HCE) has attracted the attention of researchers, most of which used the traditional empirical methods, such as ordinary least squares (OLS), logistic and so on. By collecting the panel data of 30 provinces of China during 2005–2016, this paper attempts to use the Bayesian quantile regression (BQR) to reveal the impact of industrial air pollution represented by industrial waste gas emission (IWGE) on HCE in high-, middle-, low-income regions. It was found that double heterogeneity in the influence of IWGE on HCE was obvious, which revealed that people in high-, middle-, low-income regions have significantly different understandings of environmental pollution and health problems. In addition, the BQR method provided more information than the traditional empirical methods, which verified that the BQR method, as a new empirical method for previous studies, was applicable in this topic and expanded the discussion space of this research field.

Glutathione S-transferases (GSTs, EC 2.5.1.18) were isolated from the liver cytosolic fraction of 1 day old Leghorn chicks by S-hexylglutathione and glutathione affinity columns arranged in tandem. After sample loading, the affinity columns were detached from each other and developed separately. Four groups of GSTs (CL 1, 2, 3, and 4) were eluted from the hexylglutathione column, and an additional group of GSTs (CL 2 and 5) was eluted from the glutathione affinity column. CL 2, CL 3, and CL 5 were further purified to homogeneity by chromatofocusing, and the substrate specificities of each group were determined. Fractions from the chromatofocusing column were analyzed by native IEF electrophoresis. Protein bands were electroblotted onto PVDF membrane for N-terminal sequence analysis or extracted from IEF gel and rerun on SDS-PAGE to determine the subunit composition of each GST dimer. CL 2, CL 3, and CL 5 can form homodimers, whereas CL 1 and CL 4 exist only as CL 1-2 and CL 3-4 heterodimers. CL 2 and CL 5 have N-terminal amino acid sequences homologous to rat liver Yb and Ya GSTs, respectively. CL 1 has a unique N-terminal sequence that is not homologous to any known GSTs.

From the perspective of green growth, which seeks to coordinate and make sustainable the development of resources, the environment, and the economy, this study’s aim was to find out whether the high-tech industry along the Belt and Road (B&R) is sustainable and effective in using resources, reducing environmental pollution, and increasing performance. This study used panel data covering 16 provinces (municipalities) along the B&R in China between 2009 and 2016. This study used the directional distance function (DDF) and the global Malmquist–Luenberger (GML) index model to analyze the technological innovation efficiency (TIE) of the high-tech industry (HTI) while considering the undesirable output (environmental pollution). Further, supplemented by ArcGIS geographical analysis, this study carried out a comparative analysis of the TIE and its decomposition in the HTI along the B&R from geographical and time-series dimensions. Moreover, the panel Tobit regression model was used to analyze the influencing factors of TIE. The results show that the direct financial support of the government has no impact on the improvement of TIE in the HTI, the government’s regulation of environmental pollution can significantly affect the improvement of the TIE, the intensity of R&D has a significantly negative impact on the TIE, a higher level of R&D personnel in the HTI can be helpful in improving TIE, and increasing the import and export trade volumes of the HTI can promote TIE.

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This paper presents a general introduction to productivity measurement at the micro level. First, the concept of productivity is discussed and a mathematical definition is introduced. Next, various issues on productivity measurement, including index numbers, classification of inputs and outputs, and knowledge workers, are extensively discussed.