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| 1 | Environmental impact and health risk assessment of volatile organic compound emissions during different seasons in Beijing显示文摘Volatile organic compounds(VOCs)are major contributors to air pollution.Based on the emission characteristics of 99 VOCs that daily measured at 10 am in winter from 15 December 2015 to 17 January 2016 and in summer from 21 July to 25 August 2016 in Beijing,the environmental impact and health risk of VOC were assessed.In the winter polluted days,the secondary organic aerosol formation potential(SOAP)of VOC(199.70±15.05 mg/m^3)was significantly higher than that on other days.And aromatics were the primary contributor(98.03%)to the SOAP during the observation period.Additionally,the result of the ozone formation potential(OFP)showed that ethylene contributed the most to OFP in winter(26.00%and 27.64%on the normal and polluted days).In summer,however,acetaldehyde was the primary contributor to OFP(22.00%and 21.61%on the normal and polluted days).Simultaneously,study showed that hazard ratios and lifetime cancer risk values of acrolein,chloroform,benzene,1,2-dichloroethane,acetaldehyde and 1,3-butadiene exceeded the thresholds established by USEPA,thereby presenting a health risk to the residents.Besides,the ratio of toluene-to-benzene indicated that vehicle exhausts were the main source of VOC pollution in Beijing.The ratio of m-/p-xylene-toethylbenzene demonstrated that there were more prominent atmospheric photochemical reactions in summer than that in winter.Finally,according to the potential source contribution function(PSCF)results,compared with local pollution sources,the spread of pollution from long-distance VOCs had a greater impact on Beijing. | Chuanqi Li Qianqian Li Dongge Tong Qingliang Wang Mingge Wu Bohua Sun Guijin Su Li Tan | 2020 | Journal of Environmental Sciences2020，32，7： | 10 |
| 2 | Asynchronous Brain-Computer Interface Shared Control of Robotic Grasping显示文摘The control of a high Degree of Freedom(DoF) robot to grasp a target in three-dimensional space using Brain-Computer Interface(BCI) remains a very difficult problem to solve. Design of synchronous BCI requires the user perform the brain activity task all the time according to the predefined paradigm; such a process is boring and fatiguing. Furthermore, the strategy of switching between robotic auto-control and BCI control is not very reliable because the accuracy of Motor Imagery(MI) pattern recognition rarely reaches 100%. In this paper, an asynchronous BCI shared control method is proposed for the high DoF robotic grasping task. The proposed method combines BCI control and automatic robotic control to simultaneously consider the robotic vision feedback and revise the unreasonable control commands. The user can easily mentally control the system and is only required to intervene and send brain commands to the automatic control system at the appropriate time according to the experience of the user. Two experiments are designed to validate our method: one aims to illustrate the accuracy of MI pattern recognition of our asynchronous BCI system; the other is the online practical experiment that controls the robot to grasp a target while avoiding an obstacle using the asynchronous BCI shared control method that can improve the safety and robustness of our system. | Wenchang Zhang Fuchun Sun Hang Wu Chuanqi Tan Yuzhen Ma | 2019 | Tsinghua Science and Technology2019，24，3： | 8 |
| 3 | A review of EEG-based brain-computer interface systems design显示文摘A brain-computer interface(BCI) system can recognize the mental activities pattern by computer algorithms to control the external devices. Electroencephalogram(EEG) is one of the most common used approach for BCI due to the convenience and non-invasive implement. Therefore, more and more BCIs have been designed for the disabled people that suffer from stroke or spinal cord injury to help them for rehabilitation and life. We introduce the common BCI paradigms, the signal processing, and feature extraction methods. Then, we survey the different combined modes of hybrids BCIs and review the design of the synchronous/asynchronous BCIs.Finally, the shared control methods are discussed. | Wenchang Zhang Chuanqi Tan Fuchun Sun Hang Wu Bo Zhang | 2018 | Translational Neuroscience and Clinics2018，4，2： | 5 |
| 4 | A glove-based system for object recognition via visual-tactile fusion显示文摘Dear editor,In our daily life,information such as tactile and visual information is widely used to recognize objects when we manipulate them.Research has shown that the human brain makes use of multisensory models of objects(1)However,the issue of how to combine visual and tactile information for classification. | Bin FANG Fuchun SUN Huaping LIU Chuanqi TAN Di GUO | 2019 | Science China(Information Sciences)2019，62，5： | 2 |
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