Search Results - "ZHU, Hanxi"

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  1. 1

    Research on Pore Structure of Foam Gypsum Modified by Portland–Sulphoaluminate Composite Cement (PSACC) by Yang, Jiansen, Zhu, Hanxi, Cao, Xiangyang

    Published in Modelling and simulation in engineering (29-07-2024)
    “…The pore structure of the modified foam gypsum and its thermal insulation performance were revealed through the integrated study of microscopic, macroscopic,…”
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    Journal Article
  2. 2

    Y-27632 preconditioning enhances transplantation of human-induced pluripotent stem cell-derived cardiomyocytes in myocardial infarction mice by Zhao, Meng, Fan, Chengming, Ernst, Patrick J, Tang, Yawen, Zhu, Hanxi, Mattapally, Saidulu, Oduk, Yasin, Borovjagin, Anton V, Zhou, Lufang, Zhang, Jianyi, Zhu, Wuqiang

    Published in Cardiovascular research (01-02-2019)
    “…Abstract Aims  The effectiveness of cell-based treatments for regenerative myocardial therapy is limited by low rates of cell engraftment. Y-27632 inhibits…”
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    Journal Article
  3. 3

    Application of Artificial Intelligence in Computer Network and Virtual Reality Technology by Zhu, Hanxi

    “…With the continuous improvement of China's scientific and technological level, computer network technology plays an important role in the guarantees of…”
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    Conference Proceeding
  4. 4

    Enhancing the Engraftment of Human Induced Pluripotent Stem Cell-derived Cardiomyocytes via a Transient Inhibition of Rho Kinase Activity by Zhao, Meng, Tang, Yawen, Ernst, Patrick J, Kahn-Krell, Asher, Fan, Chengming, Pretorius, Danielle, Zhu, Hanxi, Lou, Xi, Zhou, Lufang, Zhang, Jianyi, Zhu, Wuqiang

    Published in Journal of visualized experiments (10-07-2019)
    “…A crucial factor in improving cellular therapy effectiveness for myocardial regeneration is to safely and efficiently increase the cell engraftment rate…”
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    Journal Article
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    Forecasting of the chaos by iterations including multi-layer neural-network by Aoyama, T., Hanxi Zhu, Yoshihara, I.

    “…We discuss a general method to forecast movements of the chaos. The method is based on functions of multi layer neural networks and a recurrent representation…”
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    Conference Proceeding