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| 1 | Impulsive Phase He 10830 Spectra of a Large Solar Limb Flare of 16 August 1989*显示文摘 | You Jianqi Wang Chuanjin Fan Zhongyu Li Hui | 1998 | Solar Physics1998，，2： | 1 |
| 2 | Local engineering of topological phase in monolayer MoS2显示文摘Monolayer transition metal dichalcogenides(TMDCs) with the 1 T0 structure are a new class of large-gap two-dimensional(2 D) topological insulators, hosting topologically protected conduction channels on the edges. However, the 1 T0 phase is metastable compared to the 2 H phase for most of 2 D TMDCs, among which the 1 T0 phase is least favored in monolayer MoS2. Here we report a clean and controllable technique to locally induce nanometer-sized 1 T0 phase in monolayer 2 H-MoS2 via a weak Argon-plasma treatment,resulting in topological phase boundaries of high density. We found that the stabilization of 1 T0 phase arises from the concerted effects of S vacancies and the tensile strain. Scanning tunneling spectroscopy(STS) clearly reveals a spin-orbit band gap(~60 meV) and topologically protected in-gap states residing at the 1 T0-2 H phase boundary, which are corroborated by density-functional theory(DFT) calculations.The strategy developed in this work can be generalized to a large variety of TMDCs materials, with potentials to realize scalable electronics and spintronics with low dissipation. | Zhichang Wanga Xiaoqiang Liu Jianqi Zhu Sifan You Ke Bian Guangyu Zhang Ji Feng Ying Jiang | 2019 | Science Bulletin2019，64，23： | 1 |
| 3 | How Market-Guanxi Ambidexterity Affects Adaptive Capability in China's Transition Economy显示文摘 | Chengde You Jianqi Zhang Xi Li Wenwen An | 2013 | Frontiers of Business Research in China2013，7，4： | 0 |
| 4 | Improvement Up-conversion Luminescence Properties of SrIn_2O_04:Er^(3+) by Doping Yb^(3+) as Sensitizer显示文摘A series of Yb^(3+)/Er^(3+) or Er^(3+) doped SrIn_2O_4 were synthesized by a high temperature solid state method.The up-conversion luminescence property and the phase formation of SrIn_2O_4:Er^(3+) and SrIn_2O_4:Yb^(3+),Er^(3+) were investigated by X-ray diffraction(XRD) and spectral methods.The XRD pattern shows that incorporating different amounts of Yb^(3+)and Er^(3+) have no influence on the phase formation of SrIn_2O_4.The up-conversion luminescence spectrum of SrIn_2O_4:Er^(3+) presented a weak luminescence due to ground state absorption of Er^(3+).However,Yb^(3+)/Er^(3+) codoped SrIn_2O_4 depicted the green(525 and 551 run) and red(662 nm) up-conversion luminescence which were assigned to the energy transfer from the Yb^(3+) transition ~2F_(7/2)-~2F_(5/2) to the Er^(3+) transitions ~2H_(11/2)-~4I_(15/2) and ~4F_(9/2-~4I_(15/2),respectively.The possible up-conversion luminescence mechanism of SrIn_2O_4:Yb^(3+),Er^(3+) was analyzed.All results could be helpful to the development of up-conversion luminescence materials. | QI Shuai TIAN Yinghe LI Yong ZHANG Huan LI Xiang YOU Jianqi YUAN Xiaoxian WANG Zhijun LI Panlai LIU Haiyan | 2016 | Journal of the Chinese Ceramic Society2016，，2： | 0 |
| 5 | A novel fault-tolerant scheduling approach for collaborative workflows in an edge-IoT environment显示文摘As a newly emerging computing paradigm, edge computing shows great capability in supporting and boosting 5G and Internet-of-Things (IoT) oriented applications, e.g., scientific workflows with low-latency, elastic, and on-demand provisioning of computational resources. However, the geographically distributed IoT resources are usually interconnected with each other through unreliable communications and ever-changing contexts, which brings in strong heterogeneity, potential vulnerability, and instability of computing infrastructures at different levels. It thus remains a challenge to enforce high fault-tolerance of edge-IoT scientific computing task flows, especially when the supporting computing infrastructures are deployed in a collaborative, distributed, and dynamic environment that is prone to faults and failures. This work proposes a novel fault-tolerant scheduling approach for edge-IoT collaborative workflows. The proposed approach first conducts a dependency-based task allocation analysis, then leverages a Primary-Backup (PB) strategy for tolerating task failures that occur at edge nodes, and finally designs a deep Q-learning algorithm for identifying the near-optimal workflow task scheduling scheme. We conduct extensive simulative case studies on multiple randomly-generated workflow and real-world edge-IoT server position datasets. Results clearly suggest that our proposed method outperforms the state-of-the-art competitors in terms of task completion ratio, server active time, and resource utilization. | Tingyan Long Yong Ma Lei Wu Yunni Xia Ning Jiang Jianqi Li Xiaodong Fu Xiangmi You Bo Zhang | 2022 | Digital Communications and Networks2022，8，6： | 0 |
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