[en] Guiyu is known as one of the largest e-waste disposal and recycling sites in China, which suffers greatly from heavy metal pollution. By evaluating the concentrations and distribution of 21 metal elements with Principal Component Analyses (PCA), five principal components were identified, which accounted for 70.4% of the information of the initial data matrix, including one e-waste recycling source, two geological sources, one source of human activities and one ocean aerosol source. Among them, the source of human activities cannot be detailed only by PCA. By using Pb isotope, the unexplained source was judged as battery sludge. Combining 21 metallic and metalloid element datasets with Pb isotope concentrations is more accurate and effective to identify uncertain sources in soil.

[en] Cardiovascular disease (CVD) is the most common cause of death in the world. Accurate coronary arteries segmentation is the basis for heart disease diagnose. But in coronary computed tomography angiography(CCTA) images, the complex structure of coronary vessels and the low contrast of thin vessels cause difficulty in coronary arteries segmentation. In this paper, an automatic segmentation algorithm is proposed to extract vessels from CCTA. Firstly, the hessian matrix is used to enhance vessels in CCTA images, and then, the moving sphere model we proposed is used to extract centerline of coronary arteries. Experimental results showed that the proposed model provides good-quality segmentation. (paper)