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Showing 821 - 840 results of 13,627 for search '(( significantly ((linked decrease) OR (linear decrease)) ) OR ( significant increase decrease ))', query time: 0.44s Refine Results
  1. 821

    Changes in total spillage during the first stage (pre-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  2. 822

    Changes in total spillage during the third stage (post epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  3. 823

    Dynamics of pairwise net spillovers between sectors in the second stage (in- epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  4. 824

    Sample stage division. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  5. 825

    First. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  6. 826

    Static spillovers in the first stage (pre-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  7. 827

    Changes in total spillage during the second stage (in-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  8. 828

    Dynamics of net spillage in the second stage (in-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  9. 829
  10. 830
  11. 831

    Detailed information of the observation datasets. by Weidong Ji (129916)

    Published 2025
    “…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”
  12. 832

    General technical specification for GW154/6700. by Weidong Ji (129916)

    Published 2025
    “…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”
  13. 833
  14. 834

    Fig 11 - by Naveed Arshad (19712985)

    Published 2024
    Subjects:
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