Belief-Rule-Based System with Self-organizing and Multi-temporal Modeling for Sensor-based Human Activity Recognition.

Smart environment is an efficient and cost- effective way to afford intelligent supports for the elderly people. Human activity recognition (HAR) is a crucial aspect of the research field of smart environments, and it has attracted widespread attention lately. The goal of this study is to develop an effective sensor-based HAR model based on the belief-rule-based system (BRBS), which is one of representative rule-based expert systems.

A novel data-driven decision model based on extended belief rule base to predict China's carbon emissions.

Global warming and climate change are gaining traction in recent years. As a major cause of global warming, carbon emissions were centered to China's climate change policy initiatives. Nevertheless, the existing policy discourse has yet reached a consensus on the optimal modeling method for carbon emissions prediction that is well-informed of both policy goals and the time-series pattern of carbon emissions.

Conjugated bile acids in gallbladder bile and serum as potential biomarkers for cholesterol polyps and adenomatous polyps.

Purpose: To identify conjugated bile acids in gallbladder bile and serum as possible biomarkers for cholesterol polyps (CPs) and adenomatous polyps (APs).

Methods: Gallbladder bile samples and serum samples were collected from 18 patients with CPs (CP group), 9 patients with APs (AP group), and 20 patients with gallstones (control group) from March to November, 2013. High performance liquid chromatography (HPLC) assay with ultraviolent detection was used to detect the concentration of 8 conjugated bile acids (glycocholic acid, GCA; taurocholic acid, TCA; glycochenodeoxycholic acid, GCDCA; taurochenodeoxycholic acid, TCDCA; glycodeoxycholic acid, GDCA; taurodeoxycholic acid, TDCA; taurolithocholic acid, TLCA; tauroursodeoxycholic acid, TUDCA) in bile samples and serum samples.