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| 1 | Allowance and allocation of industrial volatile organic compounds emission in China for year 2020 and 2030显示文摘As an effective pollution control method, emission allowance and allocation just implemented in volatile organic compounds(VOCs) control strategy of China in 2016. This article presents a possible way to set the emission allowance targets and establishes an allowance allocation model for the object year, 2020 and 2030, using 2010 as the reference year. On the basis of regression and scenario analysis method, the emission allowance targets were designed,which were 17.902 Tg and 18.224 Tg for 2020 and 2030, with an increasing rate of 28.75% and31.06% compared to 2010. From the perspective of industries, processes using VOCscontaining products, like machinery and equipment manufacturing, would continue to be the most significant industrial VOCs emission sources in the future of China. Four allocation indicators were selected, which are per capita GDP of each province, per capita industrial VOCs emission of each province, the economic contribution of industrial sector to regional economy of each province, and the emission intensity per land area of each province, respectively.Based on information entropy, the weights of the indicators were calculated and an emission allocation model was established, and the results showed that provinces like Shandong,Jiangsu, Guangdong, Zhejiang and Fujian were calculated to obtain more emission allowance while burden more reduction responsibility. Meanwhile, provinces like Guizhou, Ningxia,Hainan, Qinghai and Xizang were on the contrary. This paper suggests governments to enhance or ease to industrial VOCs reduction burden of each province in order to stimulate its economy or change its way of economy development. | Jiani Zhang Jingfang Xiao Xiaofang Chen Xiaoming Liang Liya Fan Daiqi Ye | 2018 | Journal of Environmental Sciences2018，30，7： | 13 |
| 2 | General Order Principle for Multi-Bennett Linkages显示文摘Order analysis for multi-Bennett linkages is a difficult topic in kinematics. Traditional methods fail to obtain the order of multi-Bennett linkages due to considering the special geometric distributions among joint axes. An order principle for multi-Bennett linkages is presented. For a summated multi-Bennett linkage, three procedures are included in the order principle. Firstly, a homogeneous screw equation is obtained by taking linear superposition operations and then the maximum order is determined according to linear dependency of all screws. Secondly, two theorems are employed to determine the maximum order, where the first is used to judge the linear independency of four-system screws and the second is fit for identifying the linear independency of five-system screws. Lastly, all possible cases in the order range are considered until the valid order is screened out. For a syncopated multi-Bennett linkage, an equivalent summated model is built and then the order analysis is the same as that of summated linkages. In order to verify the effectiveness of the presented order principle, the orders of summated 5R and 6R linkages as well as a syncopated 6R linkage are analyzed. The computed orders of the former two summated linkages are both 4 and the computed order of the last syncopated 6R linkage is 5. The results coincide with the prototype data. The advantage of the proposed principle is that it can get the correct order of a multi-Bennett linkage without solving the geometric conditions of joint axes and has wide application in variety of multi-Bennett linkages. | LIU Jingfang YU Yueqing HUANG Zhen HUANG Xiao'ou | 2013 | Chinese Journal of Mechanical Engineering2013，26，2： | 5 |
| 3 | A four-gene signature-derived risk score for glioblastoma:prospects for prognostic and response predictive analyses显示文摘Objective: Glioblastoma(GBM) is the most common primary malignant brain tumor regulated by numerous genes, with poor survival outcomes and unsatisfactory response to therapy.Therefore, a robust, multi-gene signature-derived model is required to predict the prognosis and treatment response in GBM.Methods: Gene expression data of GBM from TCGA and GEO datasets were used to identify differentially expressed genes(DEGs)through DESeq2 or LIMMA methods.The DEGs were then overlapped and used for survival analysis by univariate and multivariate COX regression.Based on the gene signature of multiple survival-associated DEGs, a risk score model was established,and its prognostic and predictive role was estimated through Kaplan–Meier analysis and log-rank test.Gene set enrichment analysis(GSEA) was conducted to explore high-risk score-associated pathways.Western blot was used for protein detection.Results: Four survival-associated DEGs of GBM were identified: OSMR, HOXC10, SCARA3, and SLC39A10.The four-gene signature-derived risk score was higher in GBM than in normal brain tissues.GBM patients with a high-risk score had poor survival outcomes.The high-risk group treated with temozolomide chemotherapy or radiotherapy survived for a shorter duration than the low-risk group.GSEA showed that the high-risk score was enriched with pathways such as vasculature development and cell adhesion.Western blot confirmed that the proteins of these four genes were differentially expressed in GBM cells.Conclusions: The four-gene signature-derived risk score functions well in predicting the prognosis and treatment response in GBM and will be useful for guiding therapeutic strategies for GBM patients. | Mianfu Cao Juan Cai Ye Yuan Yu Shi Hong Wu Qing Liu Yueliang Yao Lu Chen Weiqi Dang XiangZhang Jingfang Xiao Kaidi Yang Zhicheng He Xiaohong Yao Yonghong Cui Xia Zhang Xiuwu Bian | 2019 | Cancer Biology & Medicine2019，16，3： | 2 |
| 4 | Reinforcement learning based energy efficient robot relay for unmanned aerial vehicles against smart jamming显示文摘Unmanned aerial vehicles(UAVs)with limited energy resources,severe path loss,and shadowing to the ground base stations are vulnerable to smart jammers that aim to degrade the UAV communication performance and exhaust the UAV energy.The UAV anti-jamming communication performance,such as the outage probability,degrades if the robot relay is not aware of the jamming policies and the UAV network topology.In this paper,we propose a robot relay scheme for UAVs against smart jamming,which combines reinforcement learning with a function approximation approach named tile coding,to jointly optimize the robot moving distance and relay power with the unknown jamming channel states and locations.The robot mobility and relay policy are chosen based on the received jamming power,the robot received signal quality,location and energy consumption,and the bit error rate of the UAV messages.We also present a deep reinforcement learning version for the robot with sufficient computing resources.It uses three deep neural networks to choose the robot mobility and relay policy with reduced sample complexity,so as to avoid exploring dangerous policies that lead to the high outage probability of the UAV messages.The network architecture of the three networks is designed with fully connected layers instead of convolutional layers to reduce the computational complexity,which is analyzed by theoretical analyses.We provide the performance bound of the proposed schemes in terms of the bit error rate,robot energy consumption and utility based on a game-theoretic study.Simulation results show that the performance of our proposed relay schemes,including the bit error rate,the outage probability,and the robot energy consumption outperforms the existing schemes. | Xiaozhen LU Jingfang JIE Zihan LIN Liang XIAO Jin LI Yanyong ZHANG | 2022 | Science China(Information Sciences)2022，65，1： | 1 |
| 5 | My Impressions of Botswana Former President Mogae显示文摘Festus Mogae, the third president in the history of the Republic of Botswana, served between April 1998 and March 2008. Before that, he had been the Vice-President for 6 years. During his presidency, Mogae managed to maintain the stability and prosperity of Botswana, thanks to | Zhu Jingfang Xiao Lan | 2012 | International Understanding2012，，3： | 0 |
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