Showing 1 - 20 results of 81,684 for search '(( significant models based ) OR ( significant ((point decrease) OR (small decrease)) ))', query time: 4.00s Refine Results
  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7

    Response of small airway tissues infected with EV-D94 and decreasing doses of EV-D68. by Ines Cordeiro Filipe (5849144)

    Published 2022
    “…<p>Tissues were infected with 1E7 RNA copies of EV-D94 (equivalent to 2,46E4 TCID50) and 1E7 RNA copies of EV-D68 (3,3E5 TCID50) as well as decreasing doses of the latter. A and B: Viral loads were quantified by RT-PCR from apical wash samples collected at the indicated time points (A) or from tissues lysed at 2dpi (B). …”
  8. 8
  9. 9
  10. 10
  11. 11

    <i>BZP4</i> expression differs significantly between genotypes. by Thomas J. C. Sauters (17382864)

    Published 2023
    “…<p><b>A.</b> Points representing the difference in transcript abundance between conditions in transcript per million (TPM) in segregants with each parental allele under the chromosome 8 QTL. …”
  12. 12
  13. 13
  14. 14

    The strength of the commute time-functional connectivity relationship demonstrates weak pathological significance and weak dependency on age. by Rostam M. Razban (22232522)

    Published 2025
    “…</b> Strengthening commute time-FC correlations shown in <b>B</b> seem to be driven by a decrease in average commute time across age. Note that all reported correlations are calculated by considering all data points, i.e., they are not calculated for the binned data.…”
  15. 15
  16. 16

    Innovation and night light in large and small cities. by Saul Estrin (8629173)

    Published 2024
    “…The results from this construction are very similar to the ones obtained directly from logit models where the dependent variable is a dummy variable based on whether the innovation index is greater than 0. …”
  17. 17
  18. 18

    Residual test results based on FSAC model. by Jinxian Tang (15460795)

    Published 2023
    “…The FSAC model is more effective at fitting the concentration and dew point temperature of the Fenwei Plain in China because its mean square error (MSE) is significantly lower than that of the other models. …”
  19. 19
  20. 20