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OBJECTIVE To explore the association between genetic polymorphisms of XRCC1 and susceptibility to acute childhood leukemia. METHODS A case-control study with 63 childhood leukemia patients and 66 control subjects was conducted to investigate the role of three XRCC1 polymorphisms (c. 194, c. 280 and c. 399 ) on susceptibility to childhood leukemia.(More)
With the motivation of lower recognition performance as the resolution of processed action videos decreases, this paper presents a robust action recognition approach based on Dempster-Shafer (DS) theory with assumption that single video frames are independent for action discrimination. By the use of artificial neural network (ANN) estimators trained using(More)
Alveolar macrophages (AMs) play a prominent role in influencing the development of lung inflammation and injury. The aim of this study is to investigate the roles of AMs response-related genes TNF-alpha, iNOS, and NRAMP1 (SLC11A1) in susceptibility to silicosis and pulmonary tuberculosis (PTB), and to analyze the interaction of dust exposure and genetic(More)
To accurately recognize human actions in less computational time is one important aspect for practical usage. This paper presents an efficient framework for recognizing actions by a RGB-D camera. The novel action patterns in the framework are extracted via computing position offset of 3D skeletal body joints locally in the temporal extent of video. Action(More)
Robust human pose estimation from the given visual observations has attracted many attentions in the past two decades. However, this problem is still challenging due to the suituation that observations are often corrupted with partial occlusions or noise pollutions or both in real-world applications. In this paper, we propose to estimate human pose by using(More)
Recent years have witnessed a dramatical growth of the deployment of vision-based surveillance in public spaces. Automatic summarization of surveillance videos (ASOSV) is hence becoming more and more desirable in many real-world applications. For this purpose, a novel frame-selection framework is proposed in the present paper, which has three properties: 1)(More)