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Showing 2,781 - 2,800 results of 9,249 for search 'significantly ((((((largest decrease) OR (larger decrease))) OR (mean decrease))) OR (we decrease))', query time: 0.52s Refine Results
  1. 2781
    A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets

    A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

    Published 2025
    “…To address the aforementioned challenges, we developed a bionic wedge-shaped track on the copper (Cu) substrate inspired by the cone-shaped thorn of cactus for liquid spontaneous transport. …”
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  2. 2782
    A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets

    A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

    Published 2025
    “…To address the aforementioned challenges, we developed a bionic wedge-shaped track on the copper (Cu) substrate inspired by the cone-shaped thorn of cactus for liquid spontaneous transport. …”
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  3. 2783
    A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets

    A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

    Published 2025
    “…To address the aforementioned challenges, we developed a bionic wedge-shaped track on the copper (Cu) substrate inspired by the cone-shaped thorn of cactus for liquid spontaneous transport. …”
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  4. 2784
    A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets

    A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

    Published 2025
    “…To address the aforementioned challenges, we developed a bionic wedge-shaped track on the copper (Cu) substrate inspired by the cone-shaped thorn of cactus for liquid spontaneous transport. …”
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  5. 2785
    A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets

    A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

    Published 2025
    “…To address the aforementioned challenges, we developed a bionic wedge-shaped track on the copper (Cu) substrate inspired by the cone-shaped thorn of cactus for liquid spontaneous transport. …”
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  6. 2786
    Schematic diagram of numerical simulation model.

    Schematic diagram of numerical simulation model. by Mengyun Li (7490870)

    Published 2025
    “…Finally, using the established prediction method, we calculated the limiting conditions for the existence of weak water-flushed zones in the X oil field test area. …”
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  7. 2787
    The result of molecular dynamics simulation.

    The result of molecular dynamics simulation. by Ashraf Attia Mahmoud (21262201)

    Published 2025
    “…The docking research indicated that these mutations decreased the binding affinity for DNA, with R273C, R280G, G266E, and G105C displaying the most significant differences. …”
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  8. 2788
    Result of the phenotypic analysis.

    Result of the phenotypic analysis. by Ashraf Attia Mahmoud (21262201)

    Published 2025
    “…The docking research indicated that these mutations decreased the binding affinity for DNA, with R273C, R280G, G266E, and G105C displaying the most significant differences. …”
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  9. 2789
    Type of Mutations.

    Type of Mutations. by Ashraf Attia Mahmoud (21262201)

    Published 2025
    “…The docking research indicated that these mutations decreased the binding affinity for DNA, with R273C, R280G, G266E, and G105C displaying the most significant differences. …”
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  10. 2790
    Algorithm training accuracy experiments.

    Algorithm training accuracy experiments. by Yingying Liu (360782)

    Published 2025
    “…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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  11. 2791
    Repeat the detection experiment.

    Repeat the detection experiment. by Yingying Liu (360782)

    Published 2025
    “…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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  12. 2792
    Detection network structure with IRAU [34].

    Detection network structure with IRAU [34]. by Yingying Liu (360782)

    Published 2025
    “…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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  13. 2793
    Ablation experiments of various block.

    Ablation experiments of various block. by Yingying Liu (360782)

    Published 2025
    “…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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  14. 2794
    Kappa coefficients for different algorithms.

    Kappa coefficients for different algorithms. by Yingying Liu (360782)

    Published 2025
    “…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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  15. 2795
    The structure of ASPP+ block.

    The structure of ASPP+ block. by Yingying Liu (360782)

    Published 2025
    “…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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  16. 2796
    The structure of attention gate block [31].

    The structure of attention gate block [31]. by Yingying Liu (360782)

    Published 2025
    “…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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  17. 2797
    DSC block and its application network structure.

    DSC block and its application network structure. by Yingying Liu (360782)

    Published 2025
    “…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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  18. 2798
    The structure of multi-scale residual block [30].

    The structure of multi-scale residual block [30]. by Yingying Liu (360782)

    Published 2025
    “…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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  19. 2799
    The structure of IRAU and Res2Net+ block [22].

    The structure of IRAU and Res2Net+ block [22]. by Yingying Liu (360782)

    Published 2025
    “…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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  20. 2800
    Loss of C1-FDX results in a reduction of the CI and CV activity.

    Loss of C1-FDX results in a reduction of the CI and CV activity. by Baoyin Chen (2635399)

    Published 2024
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