Showing 1 - 4 results of 4 for search 'GMA Network', query time: 0.03s Refine Results
  1. 1

    Synergistic enhancement of hydrophobic dental adhesives: autonomous strengthening, polymerization kinetics, and hydrolytic resistance by Burak Korkmaz, Erhan Demirel, Qiang Ye, Qiang Ye, Anil Misra, Anil Misra, Candan Tamerler, Candan Tamerler, Candan Tamerler, Paulette Spencer, Paulette Spencer, Paulette Spencer

    Published 2024-04-01
    “…Hydrophobic resin formulation (NE1) was developed using HEMA/BisGMA 28/55w/w and 15 wt% MPS. Control (NC1) contained HEMA/BisGMA 28/55 w/w and 15 wt% MES. …”
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  2. 2

    Accurate recognition of micromorphology images of epoxy coatings for deep-sea environments based on a deep learning super-resolution method by JiaQi Pan, Furou Liu, Jia Feng, Fandi Meng, Yufan Chen, Jianning Chi, Zelan Li, Jie Li, Li Liu

    Published 2025-09-01
    “…To address the relatively blurred edges and unclear textures of SEM images, a crack image super-resolution network based on global mixed attention (GMA-net) is proposed for application to SEM images of organic coatings. …”
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  3. 3

    The members of zinc finger-homeodomain (ZF-HD) transcription factors are associated with abiotic stresses in soybean: insights from genomics and expression analysis by Hafiz Muhammad Rizwan, Jiayi He, Muhammad Nawaz, Keyu Lu, Mingfu Wang

    Published 2025-01-01
    “…The collinearity analysis revealed that GmZF-HD genes showed higher homology with dicot species, indicating common ancestors with close evolutionary relationships. A total of 94 gma-miRNAs from 41 diverse miRNA families were identified, targeting 40 GmZF-HD genes, with GmZF-HD6 being most targeted by 7 miRNAs, and gma-miR4993 emerging as the dominant miRNA family. …”
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  4. 4

    Deep learning empowered sensor fusion boosts infant movement classification by Tomas Kulvicius, Dajie Zhang, Luise Poustka, Sven Bölte, Lennart Jahn, Sarah Flügge, Marc Kraft, Markus Zweckstetter, Karin Nielsen-Saines, Florentin Wörgötter, Peter B. Marschik

    Published 2025-01-01
    “…Abstract Background To assess the integrity of the developing nervous system, the Prechtl general movement assessment (GMA) is recognized for its clinical value in diagnosing neurological impairments in early infancy. …”
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