Showing 781 - 800 results of 82,039 for search '(( 50 ((((mean decrease) OR (nn decrease))) OR (a decrease)) ) OR ( 2 we decrease ))', query time: 1.47s Refine Results
  1. 781
  2. 782

    Annual number of outpatient visits in recurrence and non-recurrence groups. by Yasuyuki Sotani (20114144)

    Published 2025
    “…<p>In the recurrence group, mean outpatient visits (± standard deviation) decreased from 13.6 ± 3.0 to 11.9 ± 5.0, 8.1 ± 3.9, and 7.8 ± 3.2 at 1, 2, and 3 years postoperatively, respectively (Kruskal-Wallis test, P < 0.001; Dunn’s test, **P < 0.01). …”
  3. 783

    Annual treatment frequencies in all eyes. by Yasuyuki Sotani (20114144)

    Published 2025
    “…<p>The number of anti-VEGF treatments, STTA, MA-PC, PPV, and total treatments (mean ± SD) significantly decreased from 2.6 ± 1.6, 0.3 ± 0.8, 0.6 ± 0.8, 0.1 ± 0.3, and 3.7 ± 1.7 preoperatively to 0.8 ± 1.9, 0.0 ± 0.2, 0.3 ± 1.0, 0.0, and 1.2 ± 2.2; at year 2 to 0.7 ± 2.0, 0.1 ± 0.6, 0.0 ± 0.2, 0.0 ± 0.2, and 1.0 ± 2.1; and at year 3 to 0.9 ± 2.2, 0.0, 0.2 ± 1.0, 0.0 ± 0.2, and 1.1 ± 3.1 (Kruskal–Wallis test, P < 0.001; Dunn’s test, **P < 0.01). …”
  4. 784

    Annual number of outpatient visits in all eyes. by Yasuyuki Sotani (20114144)

    Published 2025
    “…<p>Mean visit frequency (mean ± standard deviation) significantly decreased from 11.5 ± 4.3 preoperatively to 8.8 ± 4.1, 5.0 ± 3.4, and 4.4 ± 3.2 visits in the first, second, and third postoperative years, respectively (Kruskal–Wallis test, P < 0.001; Dunn’s test, **P < 0.01). …”
  5. 785

    Annual treatment frequencies in recurrence and non-recurrence groups. by Yasuyuki Sotani (20114144)

    Published 2025
    “…Mean outpatient visits in the recurrence group decreased from 13.6 ± 3.0 to 11.9 ± 5.0, 8.1 ± 3.9, and 7.8 ± 3.2 at 1, 2, and 3 years postoperatively, respectively (Kruskal-Wallis test, p < 0.001). …”
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  7. 787

    S1 File - by Yonghui Zhang (279832)

    Published 2024
    “…Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R<sup>2</sup>), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. …”
  8. 788

    Detailed information on field experiments. by Yonghui Zhang (279832)

    Published 2024
    “…Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R<sup>2</sup>), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. …”
  9. 789

    List of symbols used in this study. by Yonghui Zhang (279832)

    Published 2024
    “…Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R<sup>2</sup>), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. …”
  10. 790

    Data sources for calibration and evaluation. by Yonghui Zhang (279832)

    Published 2024
    “…Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R<sup>2</sup>), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. …”
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    Temporal profiles of the key BO-NN features. by Julia Berezutskaya (9080269)

    Published 2020
    “…Right plot show the gradual decrease in the TM tuning for the features highlighted in <b>c</b> as well as the gradual increase in the temporal response profile (i.e. optimal shifts for the prediction of the key BO-NN features using Praat features shown in <b>a</b>). …”
  14. 794
  15. 795

    Optical Phenomena and Antifrosting Property on Biomimetics Slippery Fluid-Infused Antireflective Films via Layer-by-Layer Comparison with Superhydrophobic and Antireflective Films by Kengo Manabe (1437730)

    Published 2014
    “…A slippery fluid-infused antireflective film composed of chitin nanofibers less than 50 nm in diameter prevented light scattering at the long-wavelength side by Rayleigh scattering to achieve 97.2% transmittance. …”
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    The mean <i>z</i>-coordinate error decreasing percentages (%) of SSI-RIK compared to EM-SFM, CSF and RIK, when the sequence sizes vary from 15 to 50 with an equal interval 5. by Ya-Ping Wang (44525)

    Published 2015
    “…<p>The mean <i>z</i>-coordinate error decreasing percentages (%) of SSI-RIK compared to EM-SFM, CSF and RIK, when the sequence sizes vary from 15 to 50 with an equal interval 5.…”