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| 1 | Three-dimensional crustal velocity structure model of the middle-eastern north China Craton (HBCrust1.0)显示文摘Lithosphere thinning and destruction in the middle-eastern North China Craton(NCC), a region susceptible to strong earthquakes, is one of the research hotspots in solid earth science. All 42 seismic wide-angle reflection/refraction profiles have been completed in the middle-eastern NCC. We collect all the 2-D profiling results and perform gridding of the velocity and interface depth data, building a 3-D crustal velocity structure model for the middle-eastern NCC, named HBCrust1.0, by using the Kriging interpolation method. Our result shows that the first-arrival times calculated by HBCust1.0 fit well with the observations. The result demonstrates that the upper crust is the main seismogenic layer, and the brittle-ductile transition occurs at depths near interface C(the interface between upper and lower crust). The depth of interface Moho varies beneath the source area of the Tangshan earthquake, and a low-velocity structure is found to extend from the source area to the lower crust. Based on these observations, it can be inferred that stress accumulation responsible for the Tangshan earthquake may have been closely related to the migration and deformation of the mantle materials. Comparisons of the average velocities of the whole crust, the upper and the lower crust show that the average velocity of the lower crust under the central part of the North China Basin(NCB) in the east of the craton is obviously higher than the regional average. This high-velocity probably results from long-term underplating of the mantle magma. | DUAN YongHong WANG FuYun ZHANG XianKang LIN JiYan LIU Zhi LIU BaoFeng YANG ZhuoXin GUO WenBin WEI YunHao | 2016 | Science China Earth Sciences2016，59，7： | 24 |
| 2 | A Simple Deep Learning Network for Classification of 3D Mobile LiDAR Point Clouds显示文摘Automatic and accurate classification is a fundamental problem to the analysis and modeling of LiDAR(Light Detection and Ranging)data.Recently,convolutional neural network(ConvNet or CNN)has achieved remarkable performance in image recognition and computer vision.While significant efforts have also been made to develop various deep networks for satellite image scene classification,it still needs to further investigate suitable deep learning network frameworks for 3D dense mobile laser scanning(MLS)data.In this paper,we present a simple deep CNN for multiple object classification based on multi-scale context representation.For the pointwise classification,we first extracted the neighboring points within spatial context and transformed them into a three-channel image for each point.Then,the classification task can be treated as the image recognition using CNN.The proposed CNN architecture adopted common convolution,maximum pooling and rectified linear unit(ReLU)layers,which combined multiple deeper network layers.After being trained and tested on approximately seven million labeled MLS points,the deep CNN model can classify accurately into nine classes.Comparing with the widely used ResNet algorithm,this model performs better precision and recall rates,and less processing time,which indicated the significant potential of deep-learning-based methods in MLS data classification. | Yanjun WANG Shaochun LI Mengjie WANG Yunhao LIN | 2021 | Journal of Geodesy and Geoinformation Science2021，4，3： | 8 |
| 3 | The construction of personalized virtual landslide disaster environments based on knowledge graphs and deep neural networks显示文摘Virtual Landslide Disaster environments are important for multilevel simulation,analysis and decision-making about Landslide Disasters.However,in the existing related studies,complex disaster scene objects and relationships are not deeply analyzed,and the scene contents are fixed,which is not conducive to meeting multilevel visualization task requirements for diverse users.To resolve the above issues,a construction method for Personalized Virtual Landslide Disaster Environments Based on Knowledge Graphs and Deep Neural networks is proposed in this paper.The characteristics of relationships among users,scenes and data were first discussed in detail;then,a knowledge graph of virtual Landslide Disaster environments was established to clarify the complex relationships among disaster scene objects,and a Deep Neural network was introduced to mine the user history information and the relationships among object entities in the knowledge graph.Therefore,a personalized Landslide Disaster scene data recommendation mechanism was proposed.Finally,a prototype system was developed,and an experimental analysis was conducted.The experimental results show that the method can be used to recommend intelligently appropriate disaster information and scene data to diverse users.The recommendation accuracy stabilizes above 80%–a level able to effectively support The Construction of Personalized Virtual Landslide Disaster environments. | Yunhao Zhang Jun Zhu Qing Zhu Yakun Xie Weilian Li Lin Fu Junxiao Zhang Jianmei Tan | 2020 | International Journal of Digital Earth2020，13，12： | 3 |
| 4 | Tunnel vision optimization method for VR flood scenes based on Gaussian blur显示文摘The visualization of flood disasters in virtual reality(VR)scenes is useful for the representation and sharing of disaster knowledge and can effectively improve users’cognitive efficiency in comprehending disaster information.However,the existing VR methods of visualizing flood disaster scenes have some shortcomings,such as low rendering efficiency and poor user experience.In this paper,a tunnel vision optimization method for VR flood scenes based on Gaussian blur is proposed.The key techniques are studied,such as region of interest(ROI)calculation and tunnel vision optimization considering the characteristics of the human visual system.A prototype system has been developed and used to carry out an experimental case analysis.The experimental results show that the number of triangles drawn in a flood VR scene is reduced by approximately 30%–40%using this method and that the average frame rate is stable at approximately 90 frames per second(fps),significantly improving the efficiency of scene rendering and reducing motion sickness. | Lin Fu Jun Zhu Weilian Li Qing Zhu Bingli Xu Yakun Xie Yunhao Zhang Ya Hu Jingtao Lu Pei Dang Jigang You | 2021 | International Journal of Digital Earth2021，14，7： | 1 |
| 5 | Energy-efficient Wake-up Scheduling for Data Collection and Aggregation显示文摘 | Wu Yanwei Li Xiangyang Lin Yunhao | 2010 | IEEE Transactions on Parallel and Distributed Systems2010，21，2： | 1 |
| 6 | Zeolite-mediated hybrid Cu^(+)/Cu~0 interface for electrochemical nitrate reduction to ammonia显示文摘The electrocatalytic conversion of reactive nitrogen species to ammonia is a promising strategy for efficient NH_(3) synthesis.In this study,we reveal that the hybrid Cu^(+)/Cu~0 interface is catalytically active for electrochemical ammonia synthesis from nitrate reduction.To maintain the hybrid Cu^(+)/Cu~0 state at negative reaction potentials,hydrophilic zeolite is used to modify Cu/Cu_(2)O electrocatalyst,which demonstrates an impressive NH_(3) production rate of 41.65 mg h^(-1) cm^(-2)with ~100% Faradaic efficiency of ammonia synthesis at-0.6 V vs.RHE.In-situ Raman spectroscopy unveil the high activity originates from the zeolite reconstruction at the electrode–electrolyte interface,which protects the valence state of Cu~0/Cu^(+) site under negative potential and promotes electrochemical activity towards NH_(3) synthesis. | Jiabao Lv Angjian Wu Liang Wang Yunhao Zhong Zhihao Zeng Qunxing Huang Xiaoqing Lin Hao Zhang Shaojun Liu Qian Liu Songqiang Zhu Xiaodong Li Jianhua Yan Zhifu Qi Hao Bin Wu | 2023 | Journal of Energy Chemistry2023，，12： | 0 |
| 7 | Treatment Effects of Integrated TCM and Western Medicine Treatment Scheme on COVID-19: A Single-armed Clinical Trial显示文摘Backgroud:The outbreak of COVID-19 has brought unprecedented perils to human health and raised public health concerns in more than two hundred countries.Safe and effective treatment scheme is needed urgently.Objective:To evaluate the effects of integratedTCM and western medicine treatment scheme on COVID-19.Methods:A single-armed clinical trial was carried out in Hangzhou Xixi Hospital,an affiliated hospital with Zhejiang Chinese Medical University.102 confirmed cases were screened out from 725 suspected cases and 93 of them were treated with integrated TCM and western medicine treatment scheme.Results:83 cases were cured,5 cases deteriorated,and 5 cases withdrew from the study.No deaths were reported.The mean relief time of fever,cough,diarrhea,and fatigue were(4.78±4.61)days,(7.22±4.99)days,(5.28±3.39)days,and(5.28±3.39)days,respectively.It took(14.84±5.50)days for SARS-CoV-2 by nucleic acid amplification-based testing to turn negative.Multivariable cox regression analysis revealed that age,BMI,PISCT,BPC,AST,CK,BS,and UPRO were independent risk factors for COVID-19 treatment.Conclusion:Our study suggested that integrated TCM and western medicine treatment scheme was effective for COVID-19. | Jianfeng Bao Zhijun Xie Shourong Liu Lin Huang Jing Sun Yujun Tang Haiping Chen Jianjiang Qi Jianchun Guo Liangbin Miao Zhaoyi Li Hui Yang Yi Zhang Zhiyu Li Yuan Xu Shengyou Lin Yunhao Xun Li Zhang Jie Bao Zhaobin Cai Jinsong Huang Chengping Wen | 2021 | Clinical Complementary Medicine and Pharmacology2021，1，1： | 0 |
| 8 | A high-precision multi-dimensional microspectroscopic technique for morphological and properties analysis of cancer cell显示文摘Raman and Brillouin scattering are sensitive approaches to detect chemical composition and mechanical elasticity pathology of cells in cancer development and their medical treatment researches.The application is,however,suffering from the lack of ability to synchronously acquire the scattering signals following three-dimensional(3D)cell morphology with reasonable spatial resolution and signal-to-noise ratio.Herein,we propose a divided-aperture laser differential confocal 3D Geometry-Raman-Brillouin microscopic detection technology,by which reflection,Raman,and Brillouin scattering signals are simultaneously in situ collected in real time with an axial focusing accuracy up to 1 nm,in the height range of 200μm.The divided aperture improves the anti-noise capability of the system,and the noise influence depth of Raman detection reduces by 35.4%,and the Brillouin extinction ratio increases by 22 dB.A high-precision multichannel microspectroscopic system containing these functions is developed,which is utilized to study gastric cancer tissue.As a result,a 25%reduction of collagen concentration,42%increase of DNA substances,17%and 9%decrease in viscosity and elasticity are finely resolved from the 3D mappings.These findings indicate that our system can be a powerful tool to study cancer development new therapies at the sub-cell level. | Lirong Qiu Yunhao Su Ke-Mi Xu Han Cui Dezhi Zheng Yuanmin Zhu Lin Li Fang Li Weiqian Zhao | 2023 | Light(Science & Applications)2023，12，6： | 0 |
| 9 | Multiple unpinned Dirac points in group-Va single-layers with phosphorene structure显示文摘Emergent Dirac fermion states underlie many intriguing properties of graphene,and the search for them constitutes one strong motivation to explore two-dimensional(2D)allotropes of other elements.Phosphorene,the ultrathin layers of black phosphorous,has been a subject of intense investigations recently,and it was found that other group-Va elements could also form 2D layers with similar puckered lattice structure.Here,by a close examination of their electronic band structure evolution,we discover two types of Dirac fermion states emerging in the low-energy spectrum.One pair of(type-I)Dirac points is sitting on high-symmetry lines,while two pairs of(type-II)Dirac points are located at generic k-points,with different anisotropic dispersions determined by the reduced symmetries at their locations.Such fully-unpinned(type-II)2D Dirac points are discovered for the first time.In the absence of spin-orbit coupling(SOC),we find that each Dirac node is protected by the sublattice symmetry from gap opening,which is in turn ensured by any one of three point group symmetries.The SOC generally gaps the Dirac nodes,and for the type-I case,this drives the system into a quantum spin Hall insulator phase.We suggest possible ways to realise the unpinned Dirac points in strained phosphorene. | Yunhao Lu Di Zhou Guoqing Chang Shan Guan Weiguang Chen Yinzhu Jiang Jianzhong Jiang Xue-sen Wang Shengyuan A Yang Yuan Ping Feng Yoshiyuki Kawazoe Hsin Lin | 2016 | npj Computational Materials2016，，1： | 0 |
| 10 | A New Method for Converting T_(2) Spectrum into Pore Radius显示文摘In this paper,a new method for converting the T_(2)(relaxation time) of NMR(nuclear magnetic resonance) into the pore radius is proposed.Combined with NMR and centrifugation experiments,the relationship between pore radius and T_(2) of the sample was established.The results show that the new method is more reasonable than the traditional method.When the sample was denser and the mercury saturation was lower,the pore distribution curve was obtained by traditional method had a worse agreement with mercury injection experiment,while pore distribution curve of the new method had a better agreement with the mercury injection curve,which reflected the greater advantage of the new method as the reservoir becomes denser.The new method can obtain all the pore information in the sample.The results show that the pores in tight sandstone are mainly consisted with mesopore and macropore,and the connectivity of macropore is better than that of mesopore.The new method can effectively characterize the full pore distribution and the seepage characteristics in different pores interval of tight reservoirs,which had a great significance to evaluate the recoverable resources of tight reservoir. | Fan Zhang Zhenxue Jiang Yuanhao Zhang Bin Hu Zaiquan Yang Yuhua Yang Xianglu Tang Hanmin Xiao Lin Zhu Yunhao Han | 2023 | Journal of Earth Science2023，34，4： | 0 |
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