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注意:仅列出部分参考文献,下载原文获取全部文献信息。Kinematics, triggers and mechanism of Majiagou landslide based on FBG real-time monitoring
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Faming Huang et al.
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Momo Zhi et al.
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Cheng Lian et al.
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Ling Peng et al.
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Hua-Fu Pei et al.
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