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| 1 | Structure of the YTH domain of human YTHDF2 in complex with an m6A mononucleotide reveals an aromatic cage for m6A recognition显示文摘 | Fudong Li Debiao Zhao Jihui Wu Yunyu Shi | 2014 | Cell Research2014，24，12： | 16 |
| 2 | Discrete particle simulation of mixed sand transport显示文摘An Eulerian/Lagrangian numerical simulation is performed on mixed sand transport. Volume averaged Navier-Stokes equations are solved to calculate gas motion, and particle motion is calculated using Newton's equation, involving a hard sphere model to describe particle-to-particle and particle-to-wall collisions. The influence of wall characteristics, size distribution of sand particles and boundary layer depth on vertical distribution of sand mass flux and particle mean horizontal velocity is analyzed, suggesting that all these three factors affect sand transport at different levels. In all cases, for small size groups, sand mass flux first increases with height and then decreases while for large size groups, it decreases exponentially with height and for middle size groups the behavior is in-between. The mean horizontal velocity for all size groups well fits experimental data, that is, increasing logarithmically with height in the middle height region. Wall characteristics greatly affects particle to wall collision and makes the flat bed similar to a Gobi surface and the rough bed similar to a sandy surface. Particle size distribution largely affects the sand mass flux and the highest heights they can reach especially for larger particles. | Fengjiun Xiao Lieiin Guo Debiao Li Yueshe Wang | 2012 | Particuology2012，10，2： | 3 |
| 3 | Sand particle lift-off velocity measurements and numerical simulation of mass flux distributions in a wind tunnel显示文摘Lift-off velocity of saltating sand particles in wind-blown sand located at 1.0 mm above the sand bed surface was measured using a phase Doppler particle analyzer in a wind tunnel. The results show that the probability distribution of lift-off velocity can be expressed as a lognormal function, while that of lift-off angle follows an exponential function. The probability distribution of lift-off angle conditioned for each lift-off velocity also follows an exponential function, with a slope that becomes steeper with increasing lift-off velocity. This implies that the probability distribution of lift-off velocity is strongly dependent on the lift-off angle. However, these lift-off parameters are generally treated as an independent joint probability distribution in the literature. Numerical simulations were carried out to investigate the effects of conditional versus independent joint probability distributions on the vertical sand mass flux distribution. The simulation results derived from the conditional joint probability distribution agree much better with experimental data than those from the independent ones. Thus, it is better to describe the lift-off velocity of saltating sand particles using the conditional joint probability distribution. These results improve our understanding of saltation processes in wind-blown sand. | XIAO Fengjun DONG Zhibao GUO Liejin WANG Yueshe LI Debiao | 2017 | Journal of Arid Land2017，9，3： | 3 |
| 4 | Deep learning in hepatocellular carcinoma:Current status and future perspectives显示文摘Hepatocellular carcinoma(HCC)is among the leading causes of cancer incidence and death.Despite decades of research and development of new treatment options,the overall outcomes of patients with HCC continue to remain poor.There are areas of unmet need in risk prediction,early diagnosis,accurate prognostication,and individualized treatments for patients with HCC.Recent years have seen an explosive growth in the application of artificial intelligence(AI)technology in medical research,with the field of HCC being no exception.Among the various AI-based machine learning algorithms,deep learning algorithms are considered state-of-the-art techniques for handling and processing complex multimodal data ranging from routine clinical variables to high-resolution medical images.This article will provide a comprehensive review of the recently published studies that have applied deep learning for risk prediction,diagnosis,prognostication,and treatment planning for patients with HCC. | Joseph C Ahn Touseef Ahmad Qureshi Amit G Singal Debiao Li Ju-Dong Yang | 2021 | World Journal of Hepatology2021，13，12： | 2 |
| 5 | Coronary artery wall imaging:initial experience at 3 tesla显示文摘 | Ioannis Koktzoglou Orlando Simonetti Debiao Li | 2005 | J Magn Reson imaging2005，21，2： | 1 |
| 6 | Magnetic resonance imaging of the brain with Gd-DTPA: comparison of T1-weighted spin-echo and 3D gradient-echo seq uences显示文摘 | Rober TW Weili Li | 1996 | JMRI1996，6，3： | 1 |
| 7 | Magnetic Resonance Imaging of Coronary Arteries:Latest Technical Innovations and Clinical Experiences显示文摘Cardiovascular disease(CVD)is the leading cause of death and a major health care challenge globally.Coronary artery disease(CAD)is a primary underlying pathological process in the majority of cardiovascular disease cases.Magnetic resonance imaging(MRI)can play a potentially important role in the management of CAD as a noninvasive imaging modality without ionizing radiation,although its early promise has not been delivered because of several crucial technical limitations.However,recent innovations in MRI have reopened the door,with tremendous opportunities for multiparametric assessment of CAD including luminal stenosis,plaque burden and composition,and disease activities such as infl ammation and hemorrhage.Novel MRI acquisition and reconstruction strategies now offer much increased spatial resolution and image quality and shortened examination times compared with conventional approaches.Recent clinical experiences of coronary MRI indicated the potential to improve the current management of coronary atherosclerosis,such as identifying the patients at the highest risk and evaluating therapeutic responses.In this review we discuss the latest technical advances and clinical insights in coronary MRI. | Yibin Xie Jianing Pang Qi Yang Debiao Li | 2016 | Cardiovascular Innovations and Applications2016，，B12： | 1 |
| 8 | Three-Dimensional T2-Weighted MRI of the Human Femoral Arterial Vessel Wall at 3.0 Tesla显示文摘 | Zhuoli Zhang Zhaoyang Fan Timothy J. Carroll YiuCho Chung Peter Weale Renate Jerecic Debiao Li | 2009 | Investigative Radiology2009，，9： | 1 |
| 9 | Fiber-Optic Microstructure Sensors:A Review显示文摘This paper reviews a wide variety of fiber-optic microstructure(FOM)sensors,such as fiber Bragg grating(FBG)sensors,long-period fiber grating(LPFG)sensors,Fabry-Perot interferometer(FPI)sensors,Mach-Zchnder interferometer(MZI)sensors,Michelson interferometer(MI)sensors,and Sagnac interferometer(SI)sensors.Each FOM sensor has been introduced in the terms of structure types,fabrication methods,and their sensing applications.In addition,the sensing characteristics of different structures under the same type of FOM sensor are compared,and the sensing characteristics of the all FOM sensors,including advantages,disadvantages,and main sensing parameters,are summarized.We also discuss the future development of FOM sensors. | Zengling RAN Xiu HE Yunjiang RAO Dong SUN Xiaojuan QIN Debiao ZENG Wangwei CHU Xiankun LI Yabin WEI | 2021 | Photonic Sensors2021，11，2： | 1 |
| 10 | Makespan Minimization in Two-Machine Flow-Shop Scheduling under No-wait and Deterministic Unavailable Interval Constraints显示文摘This paper systematically studies the two machine flow-shop scheduling problems with no-wait and deterministic unavailable interval constraints.To minimize the makespan,three integer programming mathematical models are formulated for two-machine flow-shop with no-wait constraint,two-machine flow-shop with resumable unavailable interval constraint,and two-machine flow-shop with no-wait and non-resumable unavailable interval constraints problems,respectively.The optimal conditions of solv-ing the two-machine flow-shop with no-wait constraint problem by the permutation schedules,the two-machine flow-shop with resumable unavailable interval constraint problem by the Johnson algorithm,and two-machine flow-shop with no-wait and non-resumable unavailable interval constraints problem by the Gilmore and Gomory Algorithm(GGA)are presented,respectively.And the tight worst-case performance bounds of Johnson and GGA algorithms for these problems are also proved to be 2.Several instances are generated to demonstrate the proposed theorems.Based on the experimental results,GGA obtains the optimal solution for the two-machine flow-shop with no-wait constraint problem.Although it cannot reach the optimal solution for the two-machine flow-shop with resumable unavailable interval constraint problem,the optimal gap is 0.18%on average when the number of jobs is 100.Moreover,under some special conditions,it yields the optimal solution for the two-machine flow-shop with no-wait and non-resumable unavailable interval constraints problem.Therefore,GGA is an efficient heuristic to solve these problems. | Kejia Chen Debiao Li Xiao Wang | 2020 | Journal of Systems Science and Systems Engineering2020，29，4： | 0 |
| 11 | A BCH error correction scheme applied to FPGA with embedded memory显示文摘Given the potential for bit flipping of data on a memory medium,a high-speed parallel Bose-Chaudhuri-Hocquenghem(BCH)error correction scheme with modular characteristics,combining logic implementation and a look-up table,is proposed.It is suitable for data error correction on a modern field programmable gate array full with on-chip embedded memories.We elaborate on the optimization method for each part of the system and analyze the realization process of this scheme in the case of the BCH code with an information bit length of 1024 bits and a code length of 1068 bits that corrects the 4-bit error. | Yang LIU Jie LI Han WANG Debiao ZHANG Kaiqiang FENG Jinqiang LI | 2021 | Frontiers of Information Technology & Electronic Engineering2021，22，8： | 0 |
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