{"id":196,"date":"2022-07-17T00:07:11","date_gmt":"2022-07-16T16:07:11","guid":{"rendered":"https:\/\/www.corticalchip.com\/?p=196"},"modified":"2025-09-24T10:30:36","modified_gmt":"2025-09-24T02:30:36","slug":"%e7%94%b0%e6%95%8f%e8%80%81%e5%b8%88%e4%b8%aa%e4%ba%ba%e4%bb%8b%e7%bb%8d","status":"publish","type":"post","link":"https:\/\/www.corticalchip.com\/index.php\/2022\/07\/17\/%e7%94%b0%e6%95%8f%e8%80%81%e5%b8%88%e4%b8%aa%e4%ba%ba%e4%bb%8b%e7%bb%8d\/","title":{"rendered":"\u7530\u654f\u8001\u5e08\u4e2a\u4eba\u7b80\u4ecb"},"content":{"rendered":"\n

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1. \u5de5\u4f5c\u7ecf\u5386<\/p>\n\n\n\n

2024.12-\u81f3\u4eca\u3000\u3000\u91cd\u5e86\u8054\u5408\u5fae\u7535\u5b50\u516c\u53f8 \u5de5\u7a0b\u5e08
2020.09-2024.11 \u91cd\u5e86\u5927\u5b66 \u5fae\u7535\u5b50\u4e0e\u901a\u4fe1\u5de5\u7a0b\u5b66\u9662 \u52a9\u7406\u7814\u7a76\u5458
2019.07-2020.07 \u4e2d\u56fd\u5de5\u7a0b\u7269\u7406\u7814\u7a76\u9662\u7535\u5b50\u5de5\u7a0b\u7814\u7a76\u6240 \u52a9\u7406\u7814\u7a76\u5458<\/p>\n\n\n\n

2. \u6559\u80b2\u80cc\u666f<\/p>\n\n\n\n

2014.09-2019.06 \u4e2d\u79d1\u9662\u5fae\u7535\u5b50\u7814\u7a76\u6240 \u5fae\u7535\u5b50\u5b66\u4e0e\u56fa\u4f53\u7535\u5b50\u5b66 \u7855\u535a\u8fde\u8bfb
2010.09-2014.06 \u4e2d\u5c71\u5927\u5b66 \u5fae\u7535\u5b50\u4e0e\u56fa\u4f53\u7535\u5b50\u5b66 \u5b66\u58eb<\/p>\n\n\n\n

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3. \u5728\u7ec4\u671f\u95f4\u9879\u76ee\u7ecf\u5386<\/p>\n\n\n\n

    \n
  1. \u5b58\u5185\u7b97\u5b66\u4e00\u4f53\u5316\u7684\u7c7b\u8111\u82af\u7247\u8bbe\u8ba1\u7814\u7a76. \u4e2d\u56fd\u79d1\u5b66\u9662\u534a\u5bfc\u4f53\u7814\u7a76\u6240\u6a2a\u5411\u9879\u76ee\uff0c2024.1.1-2024.12.31\uff0c28\u4e07\uff0c\u4e3b\u6301<\/li>\n\n\n\n
  2. \u5168\u6570\u5b57\u5b58\u5185\u8ba1\u7b97\u52a0\u901f\u5668\u8bbe\u8ba1\u7814\u7a76. CCF-\u6d77\u5eb7\u5a01\u89c6\u6591\u5934\u96c1\u57fa\u91d1\uff0c2021-2022\uff0c27\u4e07\uff0c\u4e3b\u6301<\/li>\n\n\n\n
  3. \u57fa\u4e8e\u5fc6\u963b\u5668\u7684\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u7247\u4e0a\u5b66\u4e60\u7535\u8def\u8bbe\u8ba1\u7814\u7a76. \u91cd\u5e86\u5e02\u535a\u58eb\u540e\u79d1\u5b66\u57fa\u91d1\u9879\u76ee\uff0c2021-2023\uff0c\u4e3b\u6301<\/li>\n<\/ol>\n\n\n\n

    <\/p>\n\n\n\n

    4. \u5728\u7ec4\u671f\u95f4\u53d1\u8868\u8bba\u6587<\/p>\n\n\n\n

      \n
    1. STOP: Spatiotemporal Orthogonal Propagation for Weight-Threshold-Leakage Synergistic Training of Deep Spiking Neural Networks<\/a><\/mark>
      \u00a0 \u00a0\u00a0Haoran Gao, Xichuan Zhou, Yingcheng Lin, Min Tian, Liyuan Liu, Cong Shi*<\/strong>. Neuromorphic Computing and Engineering<\/strong><\/em>, <\/strong>2025, doi: 10.1088\/2634-4386\/ae0a78. (Early Access)\uff08SCI\uff0c1\u533a\uff09<\/strong>

      <\/li>\n\n\n\n
    2. MorphBungee-Lite: An Edge Neuromorphic Architecture With Balanced Cross-Core Workloads Based on Layer-Wise Event-Batch Learning\/Inference<\/a><\/mark>
          Zhengqing Zhong, Haibing Wang, Mingju Chen, Yingcheng Lin, Min Tian<\/strong>, Tengxiao Wang, Liyuan Liu, <\/strong>Cong Shi*. IEEE Transactions On Circuits and Systems Part II: Express Briefs<\/em><\/strong>, 2024, 72(1), 293 – 297\uff08SCI, 2\u533a<\/strong>\uff09

      <\/li>\n\n\n\n
    3. A Visual Cortex-Inspired Edge Neuromorphic Hardware Architecture With On-Chip Multi-Layer STDP Learning<\/a><\/mark>
          Junxian He, Min Tian<\/strong>, Ying Jiang, Haibing Wang, Tengxiao Wang, Xichuan Zhou, Liyuan Liu, Nanjian Wu, Ying Wang, Cong Shi*. Computers and Electrical Engineering<\/em><\/strong>, 2024, 120:109806.\uff08SCI, 1\u533a\uff09<\/strong>

      <\/li>\n\n\n\n
    4. MorphBungee: A 65-nm 7.2-mm2<\/sup> 27-\u03bcJ\/image Digital Edge Neuromorphic Chip with On-Chip 802-frame\/s Multi-Layer Spiking Neural Network Learning<\/a><\/mark>
          Tengxiao Wang, Min Tian<\/strong>, Haibing Wang, Zhengqing Zhong, Junxian He, Fang Tang, Xichuan Zhou, Yingcheng Lin, Shuang-Ming Yu, Liyuan Liu, Cong Shi*. IEEE Transactions on Biomedical Circuits and Systems<\/strong><\/em>, <\/strong>2025, 19(1), 209-225. \uff08SCI\uff0c1\u533a\uff09<\/strong>

      <\/li>\n\n\n\n
    5. Ghost Reservoir: A Memory-Efficient Low-Power and Real-Time Neuromorphic Processor of Liquid State Machine with On-Chip Learning<\/a><\/mark>
          Cong Shi, Xiang Fu, Haibing Wang, Yingcheng Lin, Ying Jiang, Liyuan Liu, Nanjian Wu, Min Tian*<\/strong>. <\/strong>IEEE Transactions on Circuits and Systems II: Express Briefs<\/strong><\/em>:  2024, 71(10), 4526-4530.\uff08SCI\uff0c2\u533a\uff09<\/strong>

      <\/li>\n\n\n\n
    6. Learnable Leakage and Onset-Spiking Self-Attention in SNNs with Local Error Signals<\/a><\/mark>
           Cong Shi, Li Wang, Haoran Gao, Min Tian*<\/strong>. Sensors<\/em><\/strong>: 2023, 23(24), 9781. \uff08SCI\uff0c3\u533a\uff09<\/strong>

      <\/li>\n\n\n\n
    7. NORP: A Compact Neuromorphic Olfactory Recognition Processor with On-Chip Hybrid Learning<\/a><\/mark>
           Cong Shi, Yuxuan Wang, Fengchun Tian, Xiang Fu, Haibing Wang, Jingya Zhang, Haoran Gao, Shukai Duan, Lidan Wang, Min Tian*<\/strong>. IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA)<\/em><\/strong>, 2023, 31-32.

      <\/li>\n\n\n\n
    8. An 8-T Processing-in-Memory SRAM Cell-Based Pixel-Parallel Array Processor for Vision Chips<\/a><\/mark>
           Leyi Chen, Cong Shi, Junxian He, Jianyi Yu, Haibing Wang, Jing Lu, Liyuan Liu, Nanjian Wu, Min Tian*<\/strong>. IEEE Transactions on Circuits and Systems I: Regular Papers<\/em><\/strong>: 2023, 70(11), 4249-4259.\uff08SCI\uff0c1\u533a\uff09<\/strong>

      <\/li>\n\n\n\n
    9. MorphBungee: A 65nm 7.2mm2<\/sup> 27\u03bcJ\/image Digital Edge Neuromorphic Chip with On-Chip 802 frame\/s Multi-layer Spiking Neural Network Learning<\/a><\/mark>
          Tengxiao Wang, Min Tian<\/strong>, Zhengqing Zhong, Haibing Wang, Junxian He, Fang Tang, Xichuan Zhou, Shuangming Yu, Nanjian Wu, Liyuan Liu, Cong Shi*<\/sup>, 2023 IEEE Asian Solid-State Circuits Conference (ASSCC)<\/em><\/strong>, 2023, 1-3.

      <\/li>\n\n\n\n
    10. Live Demonstration: Face Recognition at The Edge Using Fast On-Chip Deep Learning Neuromorphic Chip<\/a>
          Zhengqing Zhong, Tengxiao Wang, Haibing Wang, Zhihua Zhou, Junxian He, Fang Tang, Xichuan Zhou, Shuangming Yu, Liyuan Liu, Nanjian Wu, Min Tian<\/strong>, Cong Shi*. <\/strong>2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)<\/strong><\/em>, 2023, 1-2.

      <\/li>\n\n\n\n
    11. High-Accuracy Deep ANN-to-SNN Conversion Using Quantization-Aware Training Framework and Calcium-Gated Bipolar Leaky Integrate & Fire Neuron<\/a><\/mark>
           Haoran Gao, Junxian He, Haibing Wang, Tengxiao Wang, Zhengqing Zhong, Jianyi Yu, Ying Wang, Min Tian<\/strong>, Cong Shi*. Frontiers in Neuroscience<\/em><\/strong>: 2023, 17, 1141701.\uff08SCI\uff0c2\u533a\uff09<\/strong>

      <\/li>\n\n\n\n
    12. An Edge Neuromorphic Hardware with Fast On-Chip Error-Triggered Learning on Compressive Sensed Spikes<\/a>
      <\/mark>     Cong Shi, Jingya Zhang, Tengxiao Wang, Zhengqing Zhong, Junxian He, Haoran Gao, Jianyi Yu, Ping Li, Min Tian*<\/strong>. IEEE Transactions on Circuits and Systems II: Express Briefs<\/em><\/strong>: 2023<\/mark>, 70(7), 2665-2669.\uff08SCI\uff0c2\u533a\uff09<\/strong><\/mark>

      <\/li>\n\n\n\n
    13. A Configurable On-Chip Spike Encoding Network Based on Dual-Mode Integrate & Fire Neurons<\/a><\/mark>
           Zhengqing Zhong, Yunpeng Tuo*, Haibing Wang, Tengxiao Wang, Junxian He, Min Tian<\/strong>, Cong Shi. IEEE 6th Information Technology, Networking, Electronic and Automation Control Conference(ITNEC)<\/em><\/strong>: 2023, 1445-1449.

      <\/li>\n\n\n\n
    14. \u7269\u7aef\u795e\u7ecf\u5f62\u6001\u7c7b\u8111\u82af\u7247\u8bbe\u8ba1\u7efc\u8ff0<\/a>
           \u949f\u6b63\u9752, \u738b\u817e\u9704, \u5218\u529b\u6e90, \u5434\u5357\u5065, \u7530\u654f<\/strong>, \u77f3\u5306*. \u5fae\u7eb3\u7535\u5b50\u4e0e\u667a\u80fd\u5236\u9020<\/em><\/strong>: 2022, 4(3), 19-30.

      <\/li>\n\n\n\n
    15. An 8-T Processing-in-Memory SRAM Cell-Based <\/mark>Pixel-Parallel Array Processor for Vision Chips<\/a><\/mark>
           Leyi Chen, Junxian He, Jianyi Yu, Haibing Wang, Jing Lu, Liyuan Liu, Nanjian Wu, Cong Shi, Min Tian*<\/strong>. IEEE Asia Pacific Conference on Circuits and Systems<\/strong><\/em> (APCCAS)<\/em><\/strong>: 2022, 1-5.(Best Paper Award)<\/strong>

      <\/li>\n\n\n\n
    16. TEDOP: a Tiny Event-Driven Neural Network Hardware Core Enabling On-Chip Spike-Driven Synaptic Plasticity<\/a><\/mark>
           Cong Shi, Sihao Chen, Haibing Wang, Zhengqing Zhong, Ping Li, Junxian He, Tengxiao Wang, Jianyi Yu, Min Tian*<\/strong>. IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA)<\/em><\/strong>: 2022, pp. 62-63.

      <\/li>\n\n\n\n
    17. MorphBungee: An Edge Neuromorphic Chip for High-Accuracy On-Chip Learning of Multiple-Layer Spiking Neural Networks<\/a><\/mark>
          Tengxiao Wang, Haibing Wang, Junxian He, Zhengqing Zhong, Fang Tang, Xichuan Zhou, Shuang-Ming Yu, Liyuan Liu, Nanjian Wu, Min Tian<\/strong>, Cong Shi*. IEEE Biomedical Circuits and Systems Conference (BioCAS)<\/em><\/strong>: 2022, 255-259.

      <\/li>\n\n\n\n
    18. TripleBrain: A Compact Neuromorphic Hardware Core with Fast On-Chip Self-Organizing and Reinforcement Spike-Timing Dependent Plasticity<\/a>
          Haibing Wang, Zhen He, Tengxiao Wang, Junxian He, Xichuan Zhou, Ying Wang, Liyuan Liu, Nanjian Wu, Min Tian<\/strong>, Cong Shi. IEEE Transactions on Biomedical Circuits and Systems<\/em><\/strong>. 2022, 16(4), 636-650.\uff08SCI\uff0c2\u533a\uff09<\/strong>

      <\/li>\n\n\n\n
    19. A Lightweight Spiking GAN Model for Memristor-Centric Silicon Circuit with On-Chip Reinforcement Adversarial Learning<\/a><\/mark>
          Min Tian<\/strong>, Jing Lu*, Haoran Gao, Haibing Wang, Jianyi Yu, Cong Shi. IEEE International Symposium on Circuits & Systems (ISCAS)<\/strong><\/em>: 2022, 3388-3392.

      <\/li>\n\n\n\n
    20.  A Low-cost FPGA Implementation of Spiking Extreme Learning Machine With On-chip Reward-Modulated STDP Learning<\/a>
          Zhen He, Cong Shi*, Tengxiao Wang, Ying Wang, Min Tian<\/strong>, Xichuan Zhou, Ping Li, Liyuan Liu, Nanjian Wu, Gang Luo. IEEE Transactions on Circuits and Systems II: Express Briefs<\/em><\/strong>: 2022, 69(3), 1657-1661.\uff08SCI\uff0c2\u533a\uff09<\/strong>

      <\/li>\n\n\n\n
    21. TripleBrain: An Edge Neuromorphic Architecture for High-accuracy Single-layer Spiking Neural Network with On-chip Self-organizing and Reinforcement Learning<\/a>
           Haibing Wang, Zhen He, Jinsong Rao, Tengxiao Wang, Junxian He, Min Tian<\/strong>, Xichuan Zhou, Liyuan Liu, Nanjian Wu, Cong Shi*. IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA)<\/em><\/strong>: 2021, 88-89.

      <\/li>\n\n\n\n
    22. Exploiting Memristors for Neuromorphic Reinforcement Learning<\/a>
           Cong Shi, Jing Lu, Ying Wang, Ping Li, Min Tian*<\/strong>. IEEE International Conference on Artificial Intelligence Circuits & Systems (AICAS)<\/strong><\/em><\/strong>: 2021: 2021, 1-4.

      <\/li>\n\n\n\n
    23. A Heterogeneous Spiking Neural Network for Computationally Efficient Face Recognition<\/a>
           Xichuan Zhou, Zhenghua Zhou, Zhengqing Zhong, Jianyi Yu, Tengxiao Wang, Min Tian<\/strong>, Ying Jiang, Cong Shi*. IEEE International Symposium on Circuits & Systems (ISCAS)<\/strong><\/em>: 2021, 1-5.<\/li>\n<\/ol>\n\n\n\n

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      5. \u5728\u7ec4\u671f\u95f4\u53d1\u660e\u4e13\u5229<\/p>\n\n\n\n

        \n
      1. \u7f51\u7edc\u7ed3\u6784\u53ef\u914d\u7f6e\u7684\u7c7b\u8111\u82af\u7247\u67b6\u6784.
        \u77f3\u5306*, \u738b\u817e\u9704, \u7530\u654f<\/strong>, \u738b\u6d77\u51b0, \u949f\u6b63\u9752, \u4f55\u4fca\u8d24, \u848b\u9896. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN117273100A\uff0c2023-12-22

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      2. \u4e8b\u4ef6\u9a71\u52a8\u7c7b\u578b\u82af\u7247\u4e2d\u7a81\u89e6\u6743\u91cd\u66f4\u65b0\u65b9\u6cd5\u3001\u82af\u7247\u3001\u7535\u5b50\u8bbe\u5907.
        \u77f3\u5306*, \u738b\u6d77\u51b0, \u7530\u654f<\/strong>, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u55bb\u5251\u4f9d, \u9ad8\u704f\u7136, \u5f20\u9756\u96c5, \u9648\u4e50\u6bc5, \u9648\u601d\u8c6a, \u5eb9\u4e91\u9e4f. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116629331A\uff0c2023-08-22

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      3. \u57fa\u4e8eCa-LIF\u795e\u7ecf\u5143\u6a21\u578b\u7684Spike-BP\u7247\u4e0a\u5b66\u4e60\u65b9\u6cd5\u3001\u7cfb\u7edf\u53ca\u5904\u7406\u5668.
        \u77f3\u5306*, \u9ad8\u704f\u7136, \u7530\u654f<\/strong>, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u55bb\u5251\u4f9d, \u738b\u6d77\u51b0, \u9648\u601d\u8c6a, \u5f20\u9756\u96c5, \u5eb9\u4e91\u9e4f, \u9648\u4e50\u6bc5. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116629344A\uff0c2023-08-22

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      4. \u4e00\u79cd\u57fa\u4e8e\u6db2\u4f53\u72b6\u6001\u673a\u7684\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u67b6\u6784.
        \u77f3\u5306*, \u9648\u4e50\u6bc5, \u7530\u654f<\/strong>, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u738b\u6d77\u51b0, \u55bb\u5251\u4f9d, \u9ad8\u704f\u7136. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116562354A\uff0c2023-08-08

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      5. \u6df1\u5c42\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u53ca\u6df1\u5c42SNN\u7247\u4e0a\u5b9e\u65f6\u5b66\u4e60\u5904\u7406\u5668.
        \u77f3\u5306*\uff0c\u5f20\u9756\u96c5, \u7530\u654f<\/strong>, \u738b\u817e\u9704, \u4f55\u4fca\u8d24, \u55bb\u5251\u4f9d, \u9ad8\u704f\u7136, \u738b\u6d77\u51b0, \u9648\u4e50\u6bc5, \u9648\u601d\u8c6a, \u5eb9\u4e91\u9e4f. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116562344A\uff0c2023-08-08

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      6. \u57fa\u4e8e\u53cc\u6a21\u5f0f\u79ef\u5206\u70b9\u706b\u795e\u7ecf\u5143\u7684\u7247\u4e0a\u8109\u51b2\u7f16\u7801\u5668.
        \u77f3\u5306*, \u5eb9\u4e91\u9e4f, \u949f\u6b63\u9752, \u7530\u654f<\/strong>, \u738b\u6d77\u51b0, \u738b\u817e\u9704, \u4f55\u4fca\u8d24, \u9648\u4e50\u6bc5, \u5f20\u9756\u96c5, \u738b\u4e3d, \u9648\u601d\u8c6a, \u9ad8\u704f\u7136. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116050487A\uff0c2023-05-02

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      7. \u8f7b\u91cf\u7ea7\u7247\u4e0a\u5b66\u4e60FPGA\u786c\u4ef6\u67b6\u6784\u53ca\u5176\u8bbe\u8ba1\u65b9\u6cd5.
        \u77f3\u5306*, \u5f20\u9756\u96c5, \u7530\u654f<\/strong>, \u738b\u817e\u9704, \u738b\u6d77\u51b0, \u4f55\u4fca\u8d24, \u5362\u9756, \u9ad8\u704f\u7136. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN115115039A\uff0c2022-09-27

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      8. \u5b58\u5185\u8ba1\u7b97\u88c5\u7f6e\u53ca\u5176\u63a7\u5236\u65b9\u6cd5.
        \u77f3\u5306*, \u9648\u4e50\u6bc5, \u7530\u654f<\/strong>, \u738b\u6d77\u51b0, \u55bb\u5251\u4f9d, \u4f55\u4fca\u8d24. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN115064197A\uff0c2022-09-16

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      9. \u57fa\u4e8e\u7b80\u5316SDSP\u7b97\u6cd5\u7684\u8f7b\u91cf\u7ea7\u7247\u4e0a\u5b66\u4e60\u65b9\u6cd5\u3001\u7cfb\u7edf\u53ca\u5904\u7406\u5668. 
        \u9648\u601d\u8c6a, \u77f3\u5306*, \u7530\u654f<\/strong>, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u738b\u6d77\u51b0, \u9ad8\u704f\u7136, \u5eb9\u4e91\u9e4f. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN115018058A\uff0c2022-09-06

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      10. \u57fa\u4e8e\u5fc6\u963b\u5668\u7684\u53ef\u7247\u4e0a\u5f3a\u5316\u5b66\u4e60\u8109\u51b2GAN\u6a21\u578b\u53ca\u8bbe\u8ba1\u65b9\u6cd5.
        \u77f3\u5306*, \u5362\u9756, \u7530\u654f<\/strong>, \u738b\u6d77\u51b0, \u55bb\u5251\u4f9d, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u9ad8\u704f\u7136. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN114943329A\uff0c2022-08-25

        <\/li>\n\n\n\n
      11. \u57fa\u4e8e\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u7684\u8f7b\u91cf\u7ea7\u7247\u4e0a\u5b66\u4e60\u65b9\u6cd5\u3001\u7cfb\u7edf\u53ca\u5904\u7406\u5668.
        \u738b\u6d77\u51b0, \u77f3\u5306*, \u7530\u654f<\/strong>, \u738b\u817e\u9704, \u4f55\u4fca\u8d24, \u4f55\u796f. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN114091663A\uff0c2022-2-25

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      12. \u57fa\u4e8e\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u7684\u5b9e\u65f6\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u3001\u7cfb\u7edf\u53ca\u5904\u7406\u5668.
        \u738b\u817e\u9704, \u77f3\u5306*, \u7530\u654f<\/strong>, \u4f55\u4fca\u8d24, \u738b\u6d77\u51b0, \u55bb\u5251\u4f9d. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN114065922A\uff0c2022-2-18<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

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