Showing 741 - 760 results of 18,309 for search '(( a ((linear decrease) OR (larger decrease)) ) OR ( a ((latent decrease) OR (largest decrease)) ))', query time: 0.40s Refine Results
  1. 741

    “Surface Browsing” May Allow “Filter-Feeding” Protozoa to Exert Top-Down Control on Colony-Forming Toxic Cyanobacterial Blooms by Wenjie Xu (183092)

    Published 2023
    “…We show that this is not so: the model ciliate Paramecium has an impact on Microcystis populations through grazing, even when large colonies occur, and this leads to a corresponding decrease in toxic microcystins. …”
  2. 742

    “Surface Browsing” May Allow “Filter-Feeding” Protozoa to Exert Top-Down Control on Colony-Forming Toxic Cyanobacterial Blooms by Wenjie Xu (183092)

    Published 2023
    “…We show that this is not so: the model ciliate Paramecium has an impact on Microcystis populations through grazing, even when large colonies occur, and this leads to a corresponding decrease in toxic microcystins. …”
  3. 743

    “Surface Browsing” May Allow “Filter-Feeding” Protozoa to Exert Top-Down Control on Colony-Forming Toxic Cyanobacterial Blooms by Wenjie Xu (183092)

    Published 2023
    “…We show that this is not so: the model ciliate Paramecium has an impact on Microcystis populations through grazing, even when large colonies occur, and this leads to a corresponding decrease in toxic microcystins. …”
  4. 744
  5. 745
  6. 746
  7. 747
  8. 748
  9. 749
  10. 750
  11. 751
  12. 752
  13. 753
  14. 754
  15. 755
  16. 756
  17. 757
  18. 758

    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. …”
  19. 759

    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. …”
  20. 760

    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. …”