Search alternatives:
greatest decrease » treatment decreased (Expand Search), greater increase (Expand Search)
largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
set decrease » step decrease (Expand Search), sizes decrease (Expand Search), mean decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
Showing 1 - 20 results of 2,397 for search '(( values ((set decrease) OR (we decrease)) ) OR ( a ((greatest decrease) OR (largest decrease)) ))', query time: 0.59s Refine Results
  1. 1
    Differentially expressed genes (DEGs)<sup>a</sup> showing the greatest fold changes from each potato tissue: 10 with greatest increase in expression and 10 with greatest decrease in expression.

    Differentially expressed genes (DEGs)<sup>a</sup> showing the greatest fold changes from each potato tissue: 10 with greatest increase in expression and 10 with greatest decrease in expression. by Margaret A. Carpenter (6104180)

    Published 2025
    “…<p>Differentially expressed genes (DEGs)<sup>a</sup> showing the greatest fold changes from each potato tissue: 10 with greatest increase in expression and 10 with greatest decrease in expression.…”
    Save to List
    Saved in:
  2. 2
    iKIR score decreases protection associated with protective class II genotypes in T1D.

    iKIR score decreases protection associated with protective class II genotypes in T1D. by Laura Mora-Bitria (20477525)

    Published 2024
    Save to List
    Saved in:
  3. 3
    This is the data set that we used to reach the conclusions drawn in the manuscript with related metadata and methods.

    This is the data set that we used to reach the conclusions drawn in the manuscript with related metadata and methods. by Farayi Kaseke (19560197)

    Published 2024
    Save to List
    Saved in:
  4. 4
    An illustration for the lineages identification procedure. Left panel: Each leaf represents a cell, characterized by its measured set of barcodes, denoted as . Each individual barcode is identified and named by a unique integer number. A distance matrix <i>d</i> ( <i>X</i> , <i>Y</i> )  is computed for all cells to measure the dissimilarity between their barcode sets, see Eq. (6). This distance matrix is used to construct a dendrogram through agglomerative clustering. Right panel: We vary the threshold and count the number of inferred clusters. That value determines the required matching threshold for the lineages’ construction. Note that the data and threshold values shown in this illustration are for demonstration and visualization purposes only. The presented data set is truncated and small, whereas the actual systems examined in the manuscript involve thous

    An illustration for the lineages identification procedure. Left panel: Each leaf represents a cell, characterized by its measured set of barcodes, denoted as . Each individual barc... by Nava Leibovich (12908477)

    Published 2025
    Save to List
    Saved in:
  5. 5
    Simulated regional mean wetland seasons.

    Simulated regional mean wetland seasons. by Nic Gedney (19762301)

    Published 2024
    Save to List
    Saved in:
  6. 6
    Projected decadal changes in seasonality in the hydrological cycle over the wetland regions.

    Projected decadal changes in seasonality in the hydrological cycle over the wetland regions. by Nic Gedney (19762301)

    Published 2024
    Save to List
    Saved in:
  7. 7
    Contemporary mean inundation fraction in the Amazon basin.

    Contemporary mean inundation fraction in the Amazon basin. by Nic Gedney (19762301)

    Published 2024
    Save to List
    Saved in:
  8. 8
    Decadal mean regional hydrology.

    Decadal mean regional hydrology. by Nic Gedney (19762301)

    Published 2024
    Save to List
    Saved in:
  9. 9
    Regional contemporary (1990–1999 mean) precipitation and JULES inundation fraction over the Amazon basin.

    Regional contemporary (1990–1999 mean) precipitation and JULES inundation fraction over the Amazon basin. by Nic Gedney (19762301)

    Published 2024
    Save to List
    Saved in:
  10. 10
    Changes in decadal precipitation and JULES inundation between 1990–1999 and 2089–2098.

    Changes in decadal precipitation and JULES inundation between 1990–1999 and 2089–2098. by Nic Gedney (19762301)

    Published 2024
    Save to List
    Saved in:
  11. 11
    The contemporary, long-term seasonality in inundation over the whole of the Amazon basin.

    The contemporary, long-term seasonality in inundation over the whole of the Amazon basin. by Nic Gedney (19762301)

    Published 2024
    Save to List
    Saved in:
  12. 12
    Percentage regional changes in decadal regional hydrology.

    Percentage regional changes in decadal regional hydrology. by Nic Gedney (19762301)

    Published 2024
    Save to List
    Saved in:
  13. 13
    Wetland classification scheme for the contemporary period.

    Wetland classification scheme for the contemporary period. by Nic Gedney (19762301)

    Published 2024
    Save to List
    Saved in:
  14. 14
    Wetlands over the lowland Amazon basin from the Hess product [19,20].

    Wetlands over the lowland Amazon basin from the Hess product [19,20]. by Nic Gedney (19762301)

    Published 2024
    Save to List
    Saved in:
  15. 15
    Decadal seasonality of the hydrological cycle over the wetland regions.

    Decadal seasonality of the hydrological cycle over the wetland regions. by Nic Gedney (19762301)

    Published 2024
    Save to List
    Saved in:
  16. 16
    Wetland classification using the ensemble simulations.

    Wetland classification using the ensemble simulations. by Nic Gedney (19762301)

    Published 2024
    Save to List
    Saved in:
  17. 17
    Minimal data set.

    Minimal data set. by Wei Huang (36889)

    Published 2025
    “…Each10 units increase in BRI, ASM/ BMI decreased by 29% (β = −0.29,95% CI: −0.31, −0.28, <i><i>p</i></i> value < 0.0001). …”
    Save to List
    Saved in:
  18. 18
    Benchmarking DFT Accuracy in Predicting O 1s Binding Energies on Metals

    Benchmarking DFT Accuracy in Predicting O 1s Binding Energies on Metals by Elizabeth E. Happel (22391811)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  19. 19
    Benchmarking DFT Accuracy in Predicting O 1s Binding Energies on Metals

    Benchmarking DFT Accuracy in Predicting O 1s Binding Energies on Metals by Elizabeth E. Happel (22391811)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  20. 20
    Setting of experimental environment and model parameters.

    Setting of experimental environment and model parameters. by Guozhu Sui (21672798)

    Published 2025
    Save to List
    Saved in:

Search Tools: