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| 1 | Analysis of Policy of Investment in Science and Technology Based on CGE Model显示文摘 | Shiyun Zhang Hongfu Ni Yi Zheng Yuwei Ji | 2013 | Journal of US-China Public Administration2013，10，8： | 3 |
| 2 | HLA-DP Polymorphisms Affect the Outcomes of Chronic Hepatitis B Virus Infections, Possibly through Interacting with Viral Mutations显示文摘 | Qi Zhang Jianhua Yin Yuwei Zhang Yang Deng Xiaowei Ji Yan Du Rui Pu Yifang Han Jun Zhao Xue Han Hongwei Zhang Guangwen Cao | 2013 | Journal of Virology2013，，22： | 1 |
| 3 | Electrochemomechanical performance of porous electrode incorporating binder network显示文摘This paper proposes a theory for the random generation of porous electrodes to study the electrochemomechanical performance of Li-ion batteries. A new model is developed to explore the effects of the binder network and size polydispersity of electrode particles on the mechanical states under galvanostatic and potentiostatic charging. The quantity of binder, connecting position,contact area, and the angle between the binder and electrode particles exert considerable influence on the electrochemomechanical state of the electrode. Debonding at the interface between the binder and electrode particles is highly likely to occur under galvanostatic charging. Under potentiostatic charging, hoop stress experiences complex compressive-tensile conversion along the interface, which is prone to induce wrinkling and failure of the binder. The model and results are expected to be fundamental to studying real commercial porous electrodes in detail. | JI Liang GUO ZhanSheng ZHANG YuWei | 2019 | Science China(Technological Sciences)2019，62，8： | 1 |
| 4 | Motion direction prediction through spike timing based on micro Capsnet networks显示文摘Neural activity extraction and neural decoding from neural signals are an important part of critical components of brain-computer interface systems.With the development of brain-computer interface technology,the demand for precise external control and nervous activities in macaque monkey during unilateral hand grasp has increased the complexity of control and neural decoding,which puts forward higher requirements for the accuracy and stability of feature extraction and neural decoding.In this study,a micro Capsnet network architecture that consists of a few network layers,a vector feature structure,and optimization network parameters,is proposed to decrease the computing time and complexity,decrease artificial debugging,and improve the decoding accuracy.Compared with KNN,SVM,XGBOOST,CNN,Simple RNN,and LSTM,the algorithm in this study improves the decoding accuracy by 98.03%,and achieves state-of-the-art accuracy and stronger robustness.Furthermore,the proposed algorithm can further enhance the control accuracy in the brain-computer interface. | ZHANG HuaLiang LIU Ji WANG BaoZeng DAI Jun LIAN JinLing KE Ang ZHAO YuWei ZHOU Jin WANG ChangYong | 2022 | Science China(Technological Sciences)2022，65，11： | 1 |
| 5 | Response of Ruppia maritima to the reclaimed wastewater in coastal artificial landscape river显示文摘 | Weihong WANG Min JI Yuwei XUE | 2006 | Chinese Journal Of Geochemistry2006，25，B08： | 0 |
| 6 | Reactive Power Flow Convergence Adjustment Based on Deep Reinforcement Learning显示文摘Power flow calculation is the basis of power grid planning and many system analysis tasks require convergent power flow conditions.To address the unsolvable power flow problem caused by the reactive power imbalance,a method for adjusting reactive power flow convergence based on deep reinforcement learning is proposed.The deep reinforcement learning method takes switching parallel reactive compensation as the action space and sets the reward value based on the power flow convergence and reactive power adjustment.For the non-convergence power flow,the 500 kV nodes with reactive power compensation devices on the low-voltage side are converted into PV nodes by node type switching.And the quantified reactive power non-convergence index is acquired.Then,the action space and reward value of deep reinforcement learning are reasonably designed and the adjustment strategy is obtained by taking the reactive power non-convergence index as the algorithm state space.Finally,the effectiveness of the power flow convergence adjustment algorithm is verified by an actual power grid system in a province. | Wei Zhang Bin Ji Ping He Nanqin Wang Yuwei Wang Mengzhe Zhang | 2023 | Energy Engineering2023，120，9： | 0 |
| 7 | Antiviral Drugs(Synthetic Small Molecule Inhibitors and Nature Drugs)Against EV71 in Enteroviruses:Advances and Perspectives显示文摘Background:Enterovirus 71(EV71)is a major virus that causes hand-foot-mouth disease.In cases of infants and young children,EV71 infection has been associated with severe neurological disease and potentially fatal systemic complications.The sporadic outbreak worldwide is increasingly prevalent in the Asia-Pacific region,where it has become a major public health concern.Objective:No specific antiviral drugs are currently approved for the treatment of EV71 infection.The purpose of this study is to comprehensively review the research progress of anti-EV71 drugs(synthetic small molecule inhibitors and nature drugs)in the past twenty years,and further to promote the research and development of antiviral drugs against enterovirus infection.Methods:This study reviewed the drugs on anti EV71 in the past decades.The literature search in PubMed database was conducted for original studies and review articles on drugs against enterovirus 71.Related articles published in English were selected for study and discussion.Results:As reviewed in this paper,bioactive molecules include receptor analogues,protease inhibitors,natural drugs derived from traditional chinese medicine or natural medicine.These bioactive molecules have shown significant effectiveness in inhibiting the entry and replication of EV71 in vitro and in vivo experiments.Conclusion:This review demonstrated that the entry receptor of EV71 into host cells has been studied,and receptor drugs against enterovirus have been made some progress,but most receptor analogues have not been reported.Further research is needed in this area in the future.On the other hand,the protease inhibitors have always been a major aspect of anti-enterovirus research and can be developed as antiviral agents for clinical application.In terms of natural drugs,many monomers derived from traditional chinese medicine or natural medicine have good antiviral activity and little toxic and side effects on host cells,but in view of their multi-target properties,the mechanism of drug action needs to be further studied. | Yuwei Liu Yuan Xi Likai Ji Quan Shen Wen Zhang Mengzhu Xue | 2023 | Clinical Complementary Medicine and Pharmacology2023，3，4： | 0 |
| 8 | Wearable and interactive multicolored photochromic fiber display显示文摘Endowing flexible and adaptable fiber devices with light-emitting capabilities has the potential to revolutionize the current design philosophy of intelligent,wearable interactive devices.However,significant challenges remain in developing fiber devices when it comes to achieving uniform and customizable light effects while utilizing lightweight hardware.Here,we introduce a mass-produced,wearable,and interactive photochromic fiber that provides uniform multicolored light control.We designed independent waveguides inside the fiber to maintain total internal reflection of light as it traverses the fiber.The impact of excessive light leakage on the overall illuminance can be reduced by utilizing the saturable absorption effect of fluorescent materials to ensure light emission uniformity along the transmission direction.In addition,we coupled various fluorescent composite materials inside the fiber to achieve artificially controllable spectral radiation of multiple color systems in a single fiber.We prepared fibers on mass-produced kilometer-long using the thermal drawing method.The fibers can be directly integrated into daily wearable devices or clothing in various patterns and combined with other signal input components to control and display patterns as needed.This work provides a new perspective and inspiration to the existing field of fiber display interaction,paving the way for future human–machine integration. | Pan Li Yuwei Wang Xiaoxian He Yuyang Cui Jingyu Ouyang Ju Ouyang Zicheng He Jiayu Hu Xiaojuan Liu Hang Wei Yu Wang Xiaoling Lu Qian Ji Xinyuan Cai Li Liu Chong Hou Ning Zhou Shaowu Pan Xiangru Wang Huamin Zhou Cheng-Wei Qiu Yan-Qing Lu Guangming Tao | 2024 | Light(Science & Applications)2024，13，3： | 0 |
| 9 | Automatic classification of rural building characteristics using deep learning methods on oblique photography显示文摘Rural building is important to the well-being of rural residents,leading to a significant need to carry out extensive surveys and retrofits of many rural buildings.On-site surveys by expert surveyors are currently the main approach,but this traditional method is often expensive and laborious,especially for large-scale survey tasks.Therefore,this study explores an alternative workflow based on deep learning(DL)methods to apply automatic classification of rural building characteristics.Taking four villages in Jizhou District of Tianjin,China as research samples,we tested selected convolutional neural network(CNN)architectures through the establishment of the training database containing 3258 labeled images,under the performance metrics of accuracy,recall and F1 score.The results showed that ResNet50 is the CNN architecture with the best performance,with the comprehensive consideration of overall metrics.Taking accuracy as the performance metric to test the generalization ability of ResNet50,the prediction results for seven building characteristic indicators from low to high are as follows:building function(0.827);building style(0.863);building quality(0.871);building age(0.880);building structure(0.891);abandoned or not(0.959);the number of storeys(0.995).Due to simplicity,accuracy and effectiveness,this workflow is transferable and cost-effective to investigate large-scale villages. | Chengyu Meng Yuwei Song Jiaqi Ji Ziyu Jia Zhengxu Zhou Peng Gao Sunxiangyu Liu | 2022 | Building Simulation2022，15，6： | 0 |
| 10 | Education Platform of Congenital Heart Disease Based on Mixed Reality Technology显示文摘Recently the Mixed Reality (MR) technology has a rapid development and strong application prospect in various fields. This technology has been successfully applied in clinical work by means of surgical navigation and puncture positioning. However, there is few reports about MR technology’s applications in China. Therefore, based on the MR technology, a medical education platform was designed for related professions through the reconstruction of 3D heart model. Because of the various types of congenital heart diseases and the comprehensive medical knowledge system involved, it will start from congenital heart disease and expand to other organs later. The teaching mode was enriched and basic and clinical teaching materials were provided. And students’ interests were motivated and learning efficiency was strengthened. An equal communication mechanism between teachers and students was constructed. Experimental results show that both teachers and students benefit from this proposed platform. | Yuwei Ji Xiangjun Zhang Hanze Tang Hao Luo Shengwei Zhao Zhaowen Qiu Qinghua Zhang Kun Wang Liwei Diao | 2019 | 国际计算机前沿大会会议论文集2019，，2： | 0 |
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