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Showing 1 - 20 results of 242,294 for search '(((( i values decrease ) OR ( i large decrease ))) OR ( a use increased ))', query time: 2.37s Refine Results
  1. 1
    Impact of large choroidal vessels (LCV) and topographical orientation on percentage of flow deficit (FD%) values.

    Impact of large choroidal vessels (LCV) and topographical orientation on percentage of flow deficit (FD%) values. by Valentin Hacker (9956024)

    Published 2021
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  2. 2
    Species occurrence along the NO₃¯ gradient (sorted by decreasing 25th percentile values).

    Species occurrence along the NO₃¯ gradient (sorted by decreasing 25th percentile values). by Willem Kaijser (12872371)

    Published 2022
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  3. 3
    Calculation of chl-a anomalies from <i>in situ</i> analog chl-a values.

    Calculation of chl-a anomalies from <i>in situ</i> analog chl-a values. by Benjamin M. Kraemer (7526225)

    Published 2022
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  4. 4
    Effect of parameter <i>a</i> on the model equations by increasing and decreasing value of <i>a</i> to 25%.

    Effect of parameter <i>a</i> on the model equations by increasing and decreasing value of <i>a</i> to 25%. by Shakoor Ahmad (168711)

    Published 2022
    “…<p><b>(a)</b> By increasing the value ‘<i>a</i>’ from 0.107 to 0.134. <b>(b)</b> By decreasing the value ‘<i>a</i>’ from 0.107 to 0.08.…”
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  5. 5
    Expression of NFATc1 is decreased in <i>Tcirg1</i>-knockdown osteoclasts.

    Expression of NFATc1 is decreased in <i>Tcirg1</i>-knockdown osteoclasts. by Dongyan Zhang (640677)

    Published 2020
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  6. 6
    Decrease of muscle weakness and degeneration with mutants of UPS components.

    Decrease of muscle weakness and degeneration with mutants of UPS components. by Cécile Ribot (11944875)

    Published 2022
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  7. 7
    FlexPepDock <i>ab-initio</i> recapitulates the native backbone structure of a glycosylated peptide and its unmodified counterpart, and correctly predicts a decrease in binding affinity after glycosylation.

    FlexPepDock <i>ab-initio</i> recapitulates the native backbone structure of a glycosylated peptide and its unmodified counterpart, and correctly predicts a decrease in binding affi... by Nathaniel Bloodworth (14253329)

    Published 2022
    “…<p>(A) Scheme for generating the NCAA for use in Rosetta. …”
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  8. 8
    Root Mean Square Error (RMSE) decreases with number of structures used.

    Root Mean Square Error (RMSE) decreases with number of structures used. by Samuel Coulbourn Flores (11636717)

    Published 2021
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  9. 9
    <i>Pax7</i> positive cells decrease during <i>in vitro</i> differentiation of myogenic progenitors.

    <i>Pax7</i> positive cells decrease during <i>in vitro</i> differentiation of myogenic progenitors. by Cécile Rallière (86527)

    Published 2024
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  10. 10
    Terminal objective values for the Gilets Jaunes dataset as a function of <i>ϵ</i> and <i>ω</i>.

    Terminal objective values for the Gilets Jaunes dataset as a function of <i>ϵ</i> and <i>ω</i>. by Yen-Shao Chen (18264587)

    Published 2024
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  11. 11
    Terminal objective values for the U.S. election dataset as a function of <i>ϵ</i> and <i>ω</i>.

    Terminal objective values for the U.S. election dataset as a function of <i>ϵ</i> and <i>ω</i>. by Yen-Shao Chen (18264587)

    Published 2024
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  12. 12
    GO analysis of stage-salient genes in the order of decreasing significance (i.e, increasing p–value).

    GO analysis of stage-salient genes in the order of decreasing significance (i.e, increasing p–value). by Sangeetha Muthamilselvan (8966006)

    Published 2022
    “…<p>GO analysis of stage-salient genes in the order of decreasing significance (i.e, increasing p–value).</p>…”
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  13. 13
    Terminal objective values for the Gilets Jaunes dataset as a function of <i>s</i><sub><i>network</i></sub> and <i>s</i><sub><i>edge</i></sub>.

    Terminal objective values for the Gilets Jaunes dataset as a function of <i>s</i><sub><i>network</i></sub> and <i>s</i><sub><i>edge</i></sub>. by Yen-Shao Chen (18264587)

    Published 2024
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  14. 14
    Terminal objective values for the U.S. election dataset as a function of <i>s</i><sub><i>network</i></sub> and <i>s</i><sub><i>edge</i></sub>.

    Terminal objective values for the U.S. election dataset as a function of <i>s</i><sub><i>network</i></sub> and <i>s</i><sub><i>edge</i></sub>. by Yen-Shao Chen (18264587)

    Published 2024
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  15. 15
    The proportion of lake area which exhibited decreases (blue bars) versus increases (green bars) in chl-a for the largest 18 lakes in the world.

    The proportion of lake area which exhibited decreases (blue bars) versus increases (green bars) in chl-a for the largest 18 lakes in the world. by Benjamin M. Kraemer (7526225)

    Published 2022
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  16. 16
    Costs and Benefits of Popular <i>P</i>‑Value Correction Methods in Three Models of Quantitative Omic Experiments

    Costs and Benefits of Popular <i>P</i>‑Value Correction Methods in Three Models of Quantitative Omic Experiments by Steven R. Shuken (14500192)

    Published 2023
    “…Overall, permutation had better FDR and sensitivity than BH. We show how increasing sample size, decreasing variability, or increasing effect size can enable the detection of all true changes while still correcting <i>p</i>-values, and we present basic guidelines for omic experimental design. …”
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  17. 17
    Bioclimatic variables used to predict the distribution of three Mexican <i>Atta</i> leaf-cutting ant species and their importance (%).

    Bioclimatic variables used to predict the distribution of three Mexican <i>Atta</i> leaf-cutting ant species and their importance (%). by Jorge A. Gómez-Díaz (17048305)

    Published 2023
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  18. 18
    WT host survival decreased with STAT6 KO-adapted <i>N</i>. <i>brasiliensis</i> infection.

    WT host survival decreased with STAT6 KO-adapted <i>N</i>. <i>brasiliensis</i> infection. by Annabel A. Ferguson (17616286)

    Published 2023
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  19. 19
    The terminal objective values as a function of <i>s</i><sub><i>network</i></sub> for the (left) U.S. election and (right) Gilets Jaunes datasets.

    The terminal objective values as a function of <i>s</i><sub><i>network</i></sub> for the (left) U.S. election and (right) Gilets Jaunes datasets. by Yen-Shao Chen (18264587)

    Published 2024
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  20. 20
    Knockout of <i>NbNBR1</i> decreases TYLCV-BJ infection.

    Knockout of <i>NbNBR1</i> decreases TYLCV-BJ infection. by Tingting Zhou (163678)

    Published 2021
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