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Search: WFRF:(Zhang Zuo Feng) > Research review

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1.
  • Huang, Hongyun, et al. (author)
  • Clinical Cell Therapy Guidelines for Neurorestoration (IANR/CANR 2017)
  • 2018
  • In: Cell Transplantation. - : SAGE Publications. - 0963-6897 .- 1555-3892. ; 27:2, s. 310-324
  • Research review (peer-reviewed)abstract
    • Cell therapy has been shown to be a key clinical therapeutic option for central nervous system diseases or damage. Standardization of clinical cell therapy procedures is an important task for professional associations devoted to cell therapy. The Chinese Branch of the International Association of Neurorestoratology (IANR) completed the first set of guidelines governing the clinical application of neurorestoration in 2011. The IANR and the Chinese Association of Neurorestoratology (CANR) collaborated to propose the current version "Clinical Cell Therapy Guidelines for Neurorestoration (IANR/CANR 2017)". The IANR council board members and CANR committee members approved this proposal on September 1, 2016, and recommend it to clinical practitioners of cellular therapy. These guidelines include items of cell type nomenclature, cell quality control, minimal suggested cell doses, patient-informed consent, indications for undergoing cell therapy, contraindications for undergoing cell therapy, documentation of procedure and therapy, safety evaluation, efficacy evaluation, policy of repeated treatments, do not charge patients for unproven therapies, basic principles of cell therapy, and publishing responsibility.
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2.
  • Tong, Yang, et al. (author)
  • Progress of the key materials for organic solar cells
  • 2020
  • In: Science in China Series B. - Beijing, China : SCIENCE PRESS. - 1674-7291 .- 1869-1870. ; 63:6, s. 758-765
  • Research review (peer-reviewed)abstract
    • Organic solar cells have attracted academic and industrial interests due to the advantages like lightweight, flexibility and roll-to-roll fabrication. Nowadays, 18% power conversion efficiency has been achieved in the state-of-the-art organic solar cells. The recent rapid progress in organic solar cells relies on the continuously emerging new materials and device fabrication technologies, and the deep understanding on film morphology, molecular packing and device physics. Donor and acceptor materials are the key materials for organic solar cells since they determine the device performance. The past 25 years have witnessed an odyssey in developing high-performance donors and acceptors. In this review, we focus on those star materials and milestone work, and introduce the molecular structure evolution of key materials. These key materials include homopolymer donors, D-A copolymer donors, A-D-A small molecular donors, fullerene acceptors and nonfullerene acceptors. At last, we outlook the challenges and very important directions in key materials development.
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3.
  • Zhang, Meng, et al. (author)
  • Top ten intelligent algorithms towards smart manufacturing
  • 2023
  • In: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 71, s. 158-171
  • Research review (peer-reviewed)abstract
    • Intelligent algorithms can empower the development of smart manufacturing, since they can provide optimal solutions for detection, analysis, prediction and optimization. In recent ten years, publications on intelligent algorithms in smart manufacturing have increased sharply, showing superior performance in solving problems such as shop-floor scheduling, equipment prognosis, product defect detection and manufacturing service composition, etc. In this context, this paper focuses on the selection of commonly used top ten algorithms by providing a sound understanding of how they contribute to improving manufacturing processes. First, it presents a comprehensive survey and bibliometric analysis according to relevant literature. On this basis, the top ten algorithms are highlighted and reviewed. Then three key issues concerning when to use these algorithms in smart manufacturing, how to use them, as well as why to use them are studied. Finally, the challenges for the ten algorithms are summarized.
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