Showing 561 - 580 results of 13,723 for search '(( a ((teer decrease) OR (linear decrease)) ) OR ( a ((largest decrease) OR (greatest decrease)) ))', query time: 0.56s Refine Results
  1. 561

    Baseline patient characteristics. by Oscar F. C. van den Bosch (22184246)

    Published 2025
    “…Changes during drug infusion were compared in a linear mixed model to assess the effects of s-ketamine and midazolam compared to saline. …”
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    Top Genes with Significantly Decreased Transcript Levels at the Site of SSTI<sup>1</sup>. by Rebecca A. Brady (408084)

    Published 2015
    “…<p><sup>1</sup>Top 50 genes with greatest negative change in LFC when comparing infected ears to uninfected ears from challenged mice for each time point represented</p><p><sup>2</sup>Function determined via Entrez (<a href="http://www.ncbi.nlm.nih.gov/" target="_blank">www.ncbi.nlm.nih.gov</a>) or Uniprot (<a href="http://www.uniprot.org/" target="_blank">www.uniprot.org</a>)</p><p><sup>3</sup>LFC = Log Fold Change</p><p>Italicized values indicate transcripts are significantly increased at the indicated time point.…”
  13. 573

    Data_Sheet_1_Reconstructing Global Chlorophyll-a Variations Using a Non-linear Statistical Approach.pdf by Elodie Martinez (9041420)

    Published 2020
    “…This paper investigates the ability of a machine learning approach (a non-linear statistical approach based on Support Vector Regression, hereafter SVR) to reconstruct global spatio-temporal Chl variations from selected surface oceanic and atmospheric physical parameters. …”
  14. 574

    Data_Sheet_1_Reconstructing Global Chlorophyll-a Variations Using a Non-linear Statistical Approach.pdf by Elodie Martinez (9041420)

    Published 2020
    “…This paper investigates the ability of a machine learning approach (a non-linear statistical approach based on Support Vector Regression, hereafter SVR) to reconstruct global spatio-temporal Chl variations from selected surface oceanic and atmospheric physical parameters. …”
  15. 575

    Data_Sheet_1_Reconstructing Global Chlorophyll-a Variations Using a Non-linear Statistical Approach.pdf by Elodie Martinez (9041420)

    Published 2024
    “…This paper investigates the ability of a machine learning approach (a non-linear statistical approach based on Support Vector Regression, hereafter SVR) to reconstruct global spatio-temporal Chl variations from selected surface oceanic and atmospheric physical parameters. …”
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    Response of a toggle-switch to pulse inputs. by Jaydeep K. Srimani (618692)

    Published 2014
    “…For sub-saturating durations, the dependence exhibits an approximately threshold-linear property: there is no activation until the pulse duration is above a threshold; then the activation probability increases linearly (as shown by solid lines, R<sup>2</sup>>0.9) until saturation. …”
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