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Many Tibetan heritage buildings in China are opened to tourists recently. The crowd load has become a significantly concern to the structural safety of the structures. The beams of these wooden structures are easily deformed or cracked under the crowd load. The condition assessment of the timber beam in a Tibetan heritage building under crowd load has become a new challenge. Convention statistical evaluation method making use of monitored strain data require a threshold value which is determined with no physical meaning. This paper separates the monitored strain into temperature-induced strain and crowd-induced strain. An analytical model of the timber beam including the semi-rigid connections at its ends is formulated for the calculation of different material stresses under crowd load. The condition of the beam is then quantitatively evaluated against the residual strength of material. The shear stress at any point of the beam can then be calculated from limited number of sensors for evaluating the more popular shear crack damage which is not monitored in most existing ancient structures. [ABSTRACT FROM AUTHOR]

Previous studies reported regional variations in in-hospital acute coronary syndrome (ACS) mortality, but the reasons for that were not clearly defined. We explored whether differences in patient characteristics could explain regional variation. The Improving Care for Cardiovascular Disease in China (CCC)-ACS project is an ongoing national registry and quality improvement project, involving 150 tertiary hospitals from 30 provinces across China. We applied a prediction model that included patient-specific variables to calculate the expected in-hospital mortality. For each province, we reported the observed, expected in-hospital mortality and the risk-adjusted ratio which is based on the observed divided by the expected mortality. From 2014 to 2018, 79 585 ACS patients were enrolled. The average in-hospital mortality was 1.8%. There was a wide variation in the in-hospital mortality among different provinces (0.2-3.9%). Patient characteristics explained part of this variation because of differences in the expected in-hospital mortality (0.7-2.8%). There was a substantial variation in the risk-adjusted ratio among provinces (0.2-3.5), which suggests that the variations in the mortality cannot be completely explained by the differences in patient characteristics. In conclusion, we observed a wide regional variation in mortality for ACS, part of which could be explained by the difference in patient characteristics. [ABSTRACT FROM AUTHOR]