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| 1 | Nanostructuring gold wires as highly durable nano- catalysts for selective reduction of nitro compounds and azides with organosilanes显示文摘一个一般方法被开发由 nanostructuring 准备持久的混合 nanocatalysts 经由简单 alloying 和 dealloying 的金电线的表面。产生 nanoporous gold/Au NPG/Au 电线催化剂在以一种高度可控制的方式指定的柔韧的金属电线上与他们的厚度拥有 nanoporous 皮肤。作为示范,同样获得的 NPG/Au 被显示是一高度活跃, chemo 选择,并且为把 organosilanes 用作减少代理人的 nitro 混合物和叠氮化物的减小的 recyclable 催化剂。 | Huifang Guo Xiulinq Yan Yun Zhi Zhiwen Li Cai Wu Chunliang Zhao Jing Wang Zhixin Yu Yi Ding Wei He Yadong Li | 2015 | Nano Research2015，8，4： | 8 |
| 2 | Mobile crowd sensing task optimal allocation: a mobility pattern matching perspective显示文摘 | Liang WANG Zhiwen YU Bin GUO Fei YI Fei XIONG | 2018 | Frontiers of Computer Science2018，12，2： | 7 |
| 3 | Event-triggered encirclement control of multi-agent systems with bearing rigidity显示文摘In recent years, the problem of multi-agent encirclement has attained much attention and was extensively studied. However, few work consider the factor that the on-board calculation as well as the communication capacity in the multi-agent system is limited. We investigate the encirclement control by employing the newly developed bearing rigidity theory and event-triggered mechanism. Firstly, in order to reduce the onboard loads,the event-triggered mechanism is considered in the framework and further an event-triggered control law based on bearing rigidity is proposed. The input-to-state stability(ISS) of networked agents is also analyzed by using the Lyapunov method and the cyclic-small-gain theory. In addition, the lower bound for the inter-event times is provided. Finally, to verify the efficiency and feasibility of the proposed encirclement control law, numerical experiments are investigated. | Yangguang YU Zhiwen ZENG Zhongkui LI Xiangke WANG Lincheng SHEN | 2017 | Science China(Information Sciences)2017，60，11： | 6 |
| 4 | Antibody drug conjugate:the“biological missile”for targeted cancer therapy显示文摘Antibody–drug conjugate(ADC)is typically composed of a monoclonal antibody(mAbs)covalently attached to a cytotoxic drug via a chemical linker.It combines both the advantages of highly specific targeting ability and highly potent killing effect to achieve accurate and efficient elimination of cancer cells,which has become one of the hotspots for the research and development of anticancer drugs.Since the first ADC,Mylotarg®(gemtuzumab ozogamicin),was approved in 2000 by the US Food and Drug Administration(FDA),there have been 14 ADCs received market approval so far worldwide.Moreover,over 100 ADC candidates have been investigated in clinical stages at present.This kind of new anti-cancer drugs,known as“biological missiles”,is leading a new era of targeted cancer therapy.Herein,we conducted a review of the history and general mechanism of action of ADCs,and then briefly discussed the molecular aspects of key components of ADCs and the mechanisms by which these key factors influence the activities of ADCs.Moreover,we also reviewed the approved ADCs and other promising candidates in phase-3 clinical trials and discuss the current challenges and future perspectives for the development of next generations,which provide insights for the research and development of novel cancer therapeutics using ADCs. | Zhiwen Fu Shijun Li Sifei Han Chen Shi Yu Zhang | 2022 | Signal Transduction and Targeted Therapy2022，7，4： | 5 |
| 5 | Holocene sea level trend on the west coast of Bohai Bay,China: reanalysis and standardization显示文摘Using 110 newly revised Holocene sea level indicators categorized into three types,sediments(67),shelly cheniers(27)and oyster reefs(16),this paper firstly provides a Holocene relative sea level curve,based on multiple approaches of litho-and biostratigraphies and sedimentary faces analysis,for the west coast of Bohai Bay,China.Following considerations,including indicative meaning,the paleo tidal pattern and range and conversion from mean tidal level to mean sea level,an apparent relative mean sea level(RMSL)curve was further reconstructed.After systematical calibration using CALIB,those of the 48 reworked samples were further corrected for the residence-time effect.Similarly,the younger ages for another 35 samples were chosen at the subsample level.These result in a younger-oriented shift for about 0.5 ka.Three local spatial factors,including neotectonic subsidence(average rate about 0.1 mm/a),self-compaction of unconsolidated sediments(between a few decimeters to about 6 m)and subsidence due to groundwater withdrawal(between a few centimeters to about 2.5 m),were quantitatively corrected.Finally,the amended RMSL curve after eliminating all these local temporo-spatial factors is very likely to show non-existence of mid-Holocene highstand and imply potential influences of both ice-volume equivalent sea level and regional glacial isostatic adjustment.Although it is still unable to divide both global and regional factors,the slowdown of sea level rise,in 7.5–6.8 ka with a maximum height less than+1 m,may constrain the model effort in the near future. | Jianfen Li Zhiwen Shang Fu Wang Yongsheng Chen Lizhu Tian Xingyu Jiang Qian Yu Hong Wang | 2021 | Acta Oceanologica Sinica2021，40，7： | 5 |
| 6 | Cyber-physical-social collaborative sensing: from single space to cross-space显示文摘 | Fei YI Zhiwen YU Huihui CHEN He DU Bin GUO | 2018 | Frontiers of Computer Science2018，12，4： | 5 |
| 7 | A survey on ensemble learning显示文摘Despite significant successes achieved in knowledge discovery,traditional machine learning methods may fail to obtain satisfactory performances when dealing with complex data,such as imbalanced,high-dimensional,noisy data,etc.The reason behind is that it is difficult for these methods to capture multiple characteristics and underlying structure of data.In this context,it becomes an important topic in the data mining field that how to effectively construct an efficient knowledge discovery and mining model.Ensemble learning,as one research hot spot,aims to integrate data fusion,data modeling,and data mining into a unified framework.Specifically,ensemble learning firstly extracts a set of features with a variety of transformations.Based on these learned features,multiple learning algorithms are utilized to produce weak predictive results.Finally,ensemble learning fuses the informative knowledge from the above results obtained to achieve knowledge discovery and better predictive performance via voting schemes in an adaptive way.In this paper,we review the research progress of the mainstream approaches of ensemble learning and classify them based on different characteristics.In addition,we present challenges and possible research directions for each mainstream approach of ensemble learning,and we also give an extra introduction for the combination of ensemble learning with other machine learning hot spots such as deep learning,reinforcement learning,etc. | Xibin DONG Zhiwen YU Wenming CAO Yifan SHI Qianli MA | 2020 | Frontiers of Computer Science2020，14，2： | 4 |
| 8 | Monolithic integration of MoS2-based visible detectors and GaN-based UV detectors显示文摘With the increasing demand for high integration and multi-color photodetection for both military and civilian applications, the research of multi-wavelength detectors has become a new research hotspot. However, current research has been mainly in visible dual-or multi-wavelength detectors, while integration of both visible light and ultraviolet(UV) dual-wavelength detectors has rarely been studied. In this work, large-scale and high-quality monolayer MoS2 was grown by the chemical vapor deposition method on transparent free-standing GaN substrate. Monolithic integration of MoS2-based visible detectors and GaN-based UV detectors was demonstrated using common semiconductor fabrication technologies such as photolithography, argon plasma etching, and metal deposition. High performance of a 280 nm and 405 nm dual-wavelength photodetector was realized.The responsivity of the UV detector reached 172.12 A/W, while that of the visible detector reached 17.5 A/W.Meanwhile, both photodetectors achieved high photocurrent gain, high external quantum efficiency, high normalized detection rate, and low noise equivalent power. Our study extends the future application of dual-wavelength detectors for image sensing and optical communication. | YOU WU ZHIWEN LI KAH-WEE ANG YUPING JIA ZHIMING SHI ZHI HUANG WENJIE YU XIAOJUAN SUN XINKE LIU DABING LI | 2019 | Photonics Research2019，7，10： | 4 |
| 9 | Multi-threshold second-order phase transition in laser显示文摘We present a theory of the multi-threshold second-order phase transition,and experimentally demonstrate the multi-threshold secondorder phase transition phenomenon.With carefully selected parameters,in an external cavity diode laser system,we observe secondorder phase transition with multiple(three or four) thresholds in the measured power-current-temperature three dimensional phase diagram.Such controlled death and revival of second-order phase transition sheds new insight into the nature of ubiquitous secondorder phase transition.Our theory and experiment show that the single threshold second-order phase transition is only a special case of the more general multi-threshold second-order phase transition,which is an even richer phenomenon. | ZHUANG Wei YU DeShui LIU ZhiWen CHEN JingBiao | 2011 | Chinese Science Bulletin2011，56，35： | 4 |
| 10 | Prophet model and Gaussian process regressionbased user traffic prediction in wireless networks显示文摘User traffic prediction is an important topic for wireless network operators.A user traffic prediction method based on Prophet and Gaussian process regression is proposed in this paper.The proposed method first employs discrete wavelet transform to decompose the user traffic time series to high-frequency component and low-frequency component.The low-frequency component bears the long-range dependence of user network traffic,while the high-frequency component reveals the gusty and irregular fluctuations of user network traffic.Then Prophet model and Gaussian process regression are applied to predict the two components respectively based on the characteristics of the two components.Experimental results demonstrate that the proposed model outperforms the existing time series prediction method. | Yu LI Ziang MA Zhiwen PAN Nan LIU Xiaohu YOU | 2020 | Science China(Information Sciences)2020，63，4： | 4 |
| 11 | Effect of water on extractive desulfurization of fuel oils using ionic liquids: A COSMO-RS and experimental study显示文摘When evaluating ionic liquids(ILs) for extractive desulfurization(EDS) of fuel oils, the inevitable presence of water in the system may have a significant and in many cases strongly negative effect. However, few studies have considered this particular issue and a promoted water effect on EDS is scarcely reported. In this work,COSMO-RS was firstly employed to calculate the capacity and selectivity for EDS of various IL/H_2 O mixtures,which cover different IL characters and a wide water concentration range. Experiments were then conducted with a representative IL [C_4MIM][H_2PO_4], whose stable and even promoted extraction performance with a small amount of water was suggested by COSMO-RS. Through analyses of the desulfurization ratio, the crosssolubility and the water content in the desulfurized fuel, the promoted effect of water within a certain range(b 10 wt%) was experimentally demonstrated. Moreover, such effect of water was explained combining the viscosity, the solvent–solute interactions and the COSMO-RS based analysis. | Zhen Song Dian Yu Qian Zeng Jingjing Zhang Hongye Cheng Lifang Chen Zhiwen Qi | 2017 | Chinese Journal of Chemical Engineering2017，25，2： | 3 |
| 12 | Model Warehouse显示文摘This paper puts forward a new conception:model warehouse,analyzes the reason why model warehouse appears and introduces the characteristics and architecture of model warehouse.Last,this paper points out that model warehouse is an important part of WebGIS. | YU Zhiwen | 2003 | Geo-Spatial Information Science2003，6，1： | 3 |
| 13 | Relative manifold based semi-supervised dimensionality reduction显示文摘 | Xianfa CAI Guihua WEN Jia WEI Zhiwen YU | 2014 | Frontiers of Computer Science2014，8，6： | 3 |
| 14 | The mass,fake news,and cognition security显示文摘The widespread fake news in social networks is posing threats to social stability,economic development,and political democracy,etc.Numerous studies have explored the effective detection approaches of online fake news,while few works study the intrinsic propagation and cognition mechanisms of fake news.Since the development of cognitive science paves a promising way for the prevention of fake news,we present a new research area called Cognition Security(CogSec),which studies the potential impacts of fake news on human cognition,ranging from misperception,untrusted knowledge acquisition,targeted opinion/attitude formation,to biased decision making,and investigates the effective ways for fake news debunking.CogSec is a multidisciplinary research field that leverages the knowledge from social science,psychology,cognition science,neuroscience,AI and computer science.We first propose related definitions to characterize CogSec and review the literature history.We further investigate the key research challenges and techniques of CogSec,including human-content cognition mechanism,social influence and opinion dif-fusion,fake news detection,and malicious bot detection.Finally,we summarize the open issues and future research directions,such as the cognition mechanism of fake news,influence maximization of fact-checking information,early detection of fake news,fast refutation of fake news,and so on. | Bin GUO Yasan DING Yueheng SUN Shuai MA Ke LI Zhiwen YU | 2021 | Frontiers of Computer Science2021，15，3： | 2 |
| 15 | Real-world gaseous emission characteristics of natural gas heavy-duty sanitation trucks显示文摘As compared to conventional diesel heavy-duty vehicles,natural gas vehicles have been proved to be more eco-friendly due to their lower production of greenhouse gas and pollu-tant emissions,which are causing enormous adverse effects on global warming and air pol-lution.However,natural gas vehicles were rarely studied before,especially through on-road measurements.In this study,a portable emission measurement system(PEMS)was em-ployed to investigate the real-world emissions of nitrogen oxides(NO_(x))(nitrogen monoxide(NO),nitrogen dioxide(NO_(2))),total hydrocarbons(THC),carbon monoxide(CO),and carbon dioxide(CO_(2))from two liquified natural gas(LNG)China V heavy-duty cleaning sanitation trucks with different weight.Associated with the more aggressive driving behaviors,the ve-hicle with lower weight exhibited higher CO_(2)(3%)but lower NO_(x)(48.3%)(NO_(2)(78.2%)and NO(29.4%)),CO(44.8%),and THC(3.7%)emission factors.Aggressive driving behaviors were also favorable to the production of THC,especially those in the medium-speed range but sig-nificantly negative to the production of CO and NO_(2),especially those in the low-speed range with high engine load.In particular,the emission rate ratio of NO_(2)/NO decreased with the increase of speed/scaled tractive power in different speed ranges. | Jiguang Wang Huaqiao Gui Zhiwen Yang Tongzhu Yu Xiaowen Zhang Jianguo Liu | 2022 | Journal of Environmental Sciences2022，34，5： | 2 |
| 16 | Numerical Hydrodynamics Study Around Turbine Array of Tidal Stream Farm in Zhoushan, China显示文摘In recent decades,great efforts have been made to efficiently explore tidal stream energy due to its unique advantages of easy prediction and great potential.China recently launched a national tidal stream farm demonstration project in the waterway between Putuoshan and Hulu Islands in the Zhoushan area.Before deployment of the turbine array,it is necessary to understand the hydrodynamic changes associated with the construction of a turbine array.In this study,we developed a depth-averaged hydrodynamics model that solves the shallow water governing equations to simulate the tidal hydrodynamics around the Zhoushan Archipelago.The simulation results agree with field data in terms of the water elevation and stream velocity.We considered two types of turbine arrays in this study and investigated their impacts on the local hydrodynamics.In general,the stream velocity in the northern and southern areas is reduced due to the power take-off of the turbine array,whereas stream velocity in the western and eastern areas is slightly increased due to the blockage impact of the turbine array. | YU Zhiwen ZHANG Jisheng ZHAI Yanyan ZHANG Tiantian ZHENG Jinhai | 2017 | Journal of Ocean University of China2017，16，4： | 1 |
| 17 | Graph-based consensus clustering for class discovery from gene expression data显示文摘 | YU Zhiwen WONG H S WANG Hongqiang | 2007 | Bioinformatics2007，23，21： | 1 |
| 18 | Class discovery from gene expression data based on perturbation and cluster ensemble显示文摘 | YU Zhiwen WONG H S | 2009 | IEEE Trans Nanobioscience2009，8，2： | 1 |
| 19 | Preparation and characterization of nano-Ni O fibers显示文摘 | YUAN Yanlin WANG Zhiwen YU Jinshan | 2009 | Journal of Northeast Dianli Unversity2009，29，2： | 1 |
| 20 | A Rule Based Technique for Extraction of Visual Attention Regions Based on Real-Time Clustering显示文摘 | Zhiwen Yu Hausan Wong | 2007 | IEEE TRANSACTIONS ON MULTIMEDIA2007，9，4： | 1 |
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