The pH of the fish cakes was 7.09 in the control group and 6.87–7.04 in the garlic-powder groups, demonstrating a decreasing trend with increasing amounts of garlic powder (P < 0.001).
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A highly significant difference was seen between GP III (control) and the other groups (P-value < 0.001).
The infill pattern is also highly significant (F = 975.38, p < 0.001), confirming that the material’s internal structure directly affects its stress distribution and rigidity during three-point bending tests.
3 , there is a highly significant association of grass pollen concentration and the index physical symptoms ( β = 0.002; p < 0.001).
Conversely, the regression modeling for the TT model exhibited the best fit at a 0 MPa water potential of 0 MPa and a highly significant ( p < 0.001) R 2 = 0.939 after 4 h but displayed a non-significant ( p > 0.05) lowest fit (R 2 = 0.163) at a water potential of -6.0 MPa after 2 h (Fig. 7 ).
The Shannon–Weaver diversity index was very variable between samples and ranged from 0.93 to 5.07; the different sponges showed highly significant differences (ANOVA F 13, 14 = 7.03, p < 0.001; partial-η 2 = 0.87; 1-β = 0.999) (Fig. 3A ), whereas no additional factor significantly affected the alpha–diversity of the sponge microbiome ( p > 0.1).
There was a clear trend (Table 2 ) that height was greater with increasing degree of myopia, and the difference in height between all groups was highly statistically significant ( p < 0.001).
This increase became highly significant (p < 0.001) after 4 h of incubation with the dye (1.2 for 50 μM and 1.3 for 100 μM).
Nocturia showed a highly significant reduction (Hedges’ g = − 0.66, 95% CI − 0.91 to − 0.40, p < 0.001) with minimal heterogeneity (I 2 = 3.6%).
oleracea in reducing HeLa cell viability, with highly significant statistical differences ( p < 0.001) and a very large effect size.
10 B), revealing highly significant statistical differences in Gs between IDD and Control groups within the integrated GEO dataset (p-value < 0.001).
The difference between means is significant if p < 0.05 (*), very significant if p < 0.01 (**), and extremely significant if p < 0.001 (***).
Statistical analysis revealed highly significant differences (p < 0.001) between raw and boiled water samples, confirming the effect of repeated boiling.
4 , the association between SHR and mortality remains highly significant (1.90 (1.65–2.19), P < 0.001).
The differences in AUCs between the models were highly significant (P < 0.001), even after controlling for multiple comparisons.
In the monetary domain, the correlation between risk and ambiguity attitudes remained highly significant but slightly decreased in both phases (Phase 1: r = − 0.445, p < 0.001; Phase 2: r = − 0.394, p < 0.001).
However, data from movies acquired of the lymphatic contractility demonstrated highly significant correlations between the diameter measurements and the fluorescence data (n = 15 mice, p < 0.001 in each case) with a mean Pearson r correlation value of 0.902 ± 0.054.
Correlation analysis Pearson correlation analysis showed highly significant ( p < 0.001) relationships among traits across the locations (Tables 5 and 6 ).
T max effect was highly significant for both outcome categories, with both p < 0.001.
Kaplan-Meier survival analysis demonstrated a highly significant difference in survival rates between the two groups ( p < 0.001, Fig. 4 C).
The Friedman test indicated a highly significant difference among the three devices ( p < 0.001).
All of these correlations were highly significant ( p < 0.001).
The KMO measure of sampling adequacy was 0.873, and Bartlett’s test of sphericity was highly significant ( p < 0.001), indicating that the sampling of the variables was adequate.
Moreover, there was an evident trend to favour ICIs than control therapies for cancer patients in control group with placebo (OS: HR: 0.64, 95% CI: 0.53–0.77, P ≤ 0 . 001 ; PFS: HR: 0.55, 95% CI: 0.47–0.65; P ≤ 0 . 001 ) and chemotherapy (OS: HR: 0.74, 95% CI: 0.68–0.80, P ≤ 0 . 001 ; PFS: HR: 0.79, 95% CI: 0.69–0.90; P ≤ 0 . 001 ), but not with biologics (OS: HR: 0.93, 95% CI: 0.74–1.16, P = 0 . 496 PFS: HR: 0.97, 95% CI: 0.80–1.17; P = 0 . 730 ).
The ANOVA results for the effect of the independent parameters on the dependent parameters for the single flange rotary tiller experiment are shown in Table 3 . Effect of independent parameters on the power requirement It can be seen from the ANOVA results in Table 3 that the model for the power requirement was highly significant (P < 0.001).