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Showing 5,061 - 5,080 results of 21,342 for search '(( significantly ((nn decrease) OR (linear decrease)) ) OR ( significant decrease decrease ))', query time: 0.43s Refine Results
  1. 5061
    Complete results of regression analyses of the candidate gene approach.

    Complete results of regression analyses of the candidate gene approach. by Dai Nogimura (21445649)

    Published 2025
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  2. 5062
    The comparison of ν<sub>s</sub> – DTs trends models with experimental measured values for RHOB = 2.33 g/cc and DTc = 118.67 us/ft.

    The comparison of ν<sub>s</sub> – DTs trends models with experimental measured values for RHOB = 2.33 g/cc and DTc = 118.67 us/ft. by Fahd Saeed Alakbari (10701871)

    Published 2025
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  3. 5063
    Distribution of continuous variables of all 3 visits (visit 1 = day 0, visit 2 = day 35, and visit 3 = day 70) of the PCSO-524 group and the placebo group. Results are shown as mean ± standard deviation (SD) for normally distributed variables and median with interquartile ranges for non-normally distributed.

    Distribution of continuous variables of all 3 visits (visit 1 = day 0, visit 2 = day 35, and visit 3 = day 70) of the PCSO-524 group and the placebo group. Results are shown as mea... by Nattapon Riengvirodkij (11268720)

    Published 2025
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  4. 5064
    eQTL analysis for proxy SNPs of <i>PRMT6</i>-<i>NTNG1</i> rs12028323.

    eQTL analysis for proxy SNPs of <i>PRMT6</i>-<i>NTNG1</i> rs12028323. by Dai Nogimura (21445649)

    Published 2025
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  5. 5065
    The optimized GPR approach’s cross-plotting for the training dataset.

    The optimized GPR approach’s cross-plotting for the training dataset. by Fahd Saeed Alakbari (10701871)

    Published 2025
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  6. 5066
    Methodology flowchart.

    Methodology flowchart. by Fahd Saeed Alakbari (10701871)

    Published 2025
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  7. 5067
    The most common machine learning methods to predict ν<sub>s</sub>.

    The most common machine learning methods to predict ν<sub>s</sub>. by Fahd Saeed Alakbari (10701871)

    Published 2025
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  8. 5068
    Tricuspid regurgitation pressure gradient of all 17 dogs.

    Tricuspid regurgitation pressure gradient of all 17 dogs. by Nattapon Riengvirodkij (11268720)

    Published 2025
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  9. 5069
    Trend analysis of the ν<sub>s</sub> – DTc in the range found in the dataset used for the optimized GPR.

    Trend analysis of the ν<sub>s</sub> – DTc in the range found in the dataset used for the optimized GPR. by Fahd Saeed Alakbari (10701871)

    Published 2025
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  10. 5070
    Statistical error analyses of the proposed or optimized GPR model.

    Statistical error analyses of the proposed or optimized GPR model. by Fahd Saeed Alakbari (10701871)

    Published 2025
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  11. 5071
    FT-IR results.

    FT-IR results. by Caglar Akcay (6910697)

    Published 2025
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  12. 5072
    Density differences between pre- and post-measurements for program completers (N = 160).

    Density differences between pre- and post-measurements for program completers (N = 160). by Anton Kurapov (11346019)

    Published 2025
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  13. 5073
    Fracture pressure based on proposed GPR Poisson’s ratio model.

    Fracture pressure based on proposed GPR Poisson’s ratio model. by Fahd Saeed Alakbari (10701871)

    Published 2025
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  14. 5074
    Tricuspid regurgitation pressure gradient in the PCSO-524 and placebo groups.

    Tricuspid regurgitation pressure gradient in the PCSO-524 and placebo groups. by Nattapon Riengvirodkij (11268720)

    Published 2025
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  15. 5075
    Baseline characteristics of participants (N = 2385) by UACR.

    Baseline characteristics of participants (N = 2385) by UACR. by Yubo Teng (21246745)

    Published 2025
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  16. 5076
    Comparison of ν<sub>s</sub> measured and predicted estimates of the optimized GPR approach for (a) training, (b) validation, and (c) testing datasets.

    Comparison of ν<sub>s</sub> measured and predicted estimates of the optimized GPR approach for (a) training, (b) validation, and (c) testing datasets. by Fahd Saeed Alakbari (10701871)

    Published 2025
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  17. 5077
    FT-IR results.

    FT-IR results. by Caglar Akcay (6910697)

    Published 2025
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  18. 5078
    GSEA and GSVA enrichment analysis.

    GSEA and GSVA enrichment analysis. by Wan-Jing Zhen (20427813)

    Published 2024
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  19. 5079
    Mean and standard error of pupil diameter in the dim states.

    Mean and standard error of pupil diameter in the dim states. by Tomoe Hayakawa (20978784)

    Published 2025
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  20. 5080
    Averaged pupillary responses in bright and dark conditions.

    Averaged pupillary responses in bright and dark conditions. by Tomoe Hayakawa (20978784)

    Published 2025
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