Both gestational diabetes mellitus (GDM) and pregnancy-induced hypertension (PIH) would influence the gestation significantly. However, the causation between these two symptoms remains speculative. 16,404 pregnant women were identified in Harbin, China, in this study. We investigated and evaluated the causal effect of GDM on PIH based on the Bayes conditional probability. The statistical results indicated that PIH might cause GDM, but not vice versa. Also, this case study demonstrated that the decrease temperature might also cause hypertension during pregnancy, and the prevalence rate of GDM increased with age. However, the prevalence of diabetes did not show a remarkable difference in varied areas and ages. This study could provide some essential information that will help to investigate the mechanism for GDM and PIH.
China is a world leader in capital construction. In the construction field, the shift toward prefabricated construction has become an important path for industrial transformation. This paper refers to the development of the prefabricated building industry in China, and uses input and output perspectives to examine its efficiency. It builds a data envelopment analysis model to evaluate the efficiency of the prefabricated building industry in China at both the micro and macro levels, and uses the Tobit model to empirically analyze the factors that influence this industry’s efficiency. It finds that the country’s prefabricated building industry has a moderate micro-level efficiency. This means that it is necessary to further rationalize industrial planning; strengthen technological innovation; and improve standardization, mechanization, and automation levels. At the macro level, China’s prefabricated buildings have a low industrial efficiency and remain at the initial stage of industrial development. A series of problems, such as small industrial scale and unsound policies, are restricting the industry’s rapid and efficient development. We propose several countermeasures and suggestions for the (micro- and macro-level) sustainable development of the prefabricated building industry in China, and anticipate that this will have implications for this industry’s worldwide development.
Analyzing monitoring data efficiently is a classic problem in structural health monitoring. A nonparametric test method, the Mann–Kendall (MK) method, was implemented in this study, which is commonly used to detect monotonic trends in a series of environmental data. Using the MK method, three types of time series were studied: the stress time series measured in the concrete prism compression test, the resultant force time series obtained from the pseudostatic test of a reinforced masonry shear wall, and the translation velocity time series detected in a high-rise building. The statistics calculated, as well as the intersections of curves, indicate the trend change in the time series. The results demonstrated that the MK method could efficiently analyze the trend in the engineering time series.
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