“highly significant”

As shown in Table 6 , all 4 features showed highly significant group differences (all P <.001; df=235) with large effect sizes (Cohen d range: 1.11‐1.19).

It is important to note that adjustment for average daily screen time, as well as for levels of physical activity and sleep quality (as covariates in ANCOVA), did not alter the significance of the results: all between-group differences remained highly significant ( p < 0.001).

Bartlett’s test was also highly significant, χ 2 (45) = 1668.659, p < 0.001, rejecting the null hypothesis that the correlation matrix is an identity matrix and confirming that the inter-item correlations are sufficient to justify factor analysis.

Furthermore, the individual slopes relating autoMAPSE to MAP were highly significant ( P < 0.001) and markedly heterogeneous (both positive and negative), suggesting that ventriculoarterial coupling differs substantially in different individual patients.

The improvement was statistically highly significant in Group C as compared to group A ( P < 0.001) and group B ( P < 0.001).

300 μg/mL rutin revealed a non-significant 3.0 ± 1.2 h delay, while the positive control EGCG 100 μg/mL showed a highly significant 6.6 ± 0.3 h delay compared to untreated control ( p < 0.001) (Fig. 8 ).

The HTS data show a slightly higher standard deviation due to the lower number of analysed cells, but the differences in 1 μM AZT susceptibility between wild-type and mutant RT pseudotypes were highly significant (p <0.001).

At 3 months, the correlation coefficients became strong, with Menadione showing r = 0.468 and XELOX r = 0.519, both highly significant ( p < 0.001).

Asthma severity was also highly significant (χ 2 = 68.02, p < 0.001), with uncontrolled asthma reported in 42.91% of those with intermittent/mild persistent asthma (combined as “mild cases” for analysis) and 88.79% of those with moderate-to-severe persistent asthma (combined as “persistent cases”).

There was a highly significant correlation between T I and V T in all groups (p<0.001).

The difference in risk of relapse between the G2I-1 and G2I-2 tumors was borderline significant (Odd ratio: 0.16 [0.2-1.2] p = 0.08) whereas that between the G2I-2 and G2I-3 tumors was highly significant (odd ratio: 8.5 [3.2-22.6] p < 0.001) in univariate analysis.

saxicola with differences between the species being highly significant ( Fig. 3 , t-test: t = −22.0, d.f. = 24, P <0.001).

The mean score of teamwork perceptions increased from T0 (91.02 ± 31.10) to T1 (145.27 ± 12.87) and T2 (142.30 ± 15.74), with highly significant values in repeated measures two-way ANOVA (f = 307.06, p < 0.001) and paired t-tests results (p1 < 0.001, and p2 < 0.001).

The findings reveal highly significant effects ( p < 0.001) of both site and season on the physiological characteristics of young argan plants.

None of these controls enabled replication, a result that was highly significant ( p < 0.001, one-sided Fisher’s exact test), suggesting that OriGen learned to preserve essential functional elements even in a replication system highly sensitive to mutations.

Highly significant values ( p <0.001) are marked with an asterisk (*).

This shows a highly significant difference between continuous and intermittent infusion for both courses completed and change in antibiotic therapy (Fisher’s exact test p < 0.001 for both comparisons).

The loading coefficients for AHM (0.814), DD_5 (0.985), MCMT (0.906), and MWMT (0.958) were highly significant ( p < 0.001), with DD_5, MCMT, and MWMT exhibiting equivalent explanatory power.

The results revealed highly significant linear correlations ( p < 0.001) between the Cd concentrations in the edible parts of faba beans and those in the pods, stems, and leaves.

On the other hand, caterpillars occurred with a much higher frequency in deep chambers (15.8%) than in mid-depth (7.7%) or superficial (0.7%) chambers, differences that were highly significant (Pearson Chi-square= 14.86; d.f = 2; p < 0.001).

At 1 day of heat stress, genotype (G) had a highly significant ( p < 0.001) effect on photosynthetic rate (Pn), leaf conductance (Gs), transpiration (E), chlorophyll fluorescence traits (YII, NPQ, Fv/Fm), and carotenoid content (Cart), but not on chlorophyll-A (Chl-A), chlorophyll-B (Chl-B), or carotenoid (Cart).

Consistent with the MANOVA results, two-way ANOVA for each CIELab parameter ( Table 1 ; Supplementary Table S2 ) showed highly significant effects of population ( p < 0.001) and a population × salinity interaction ( p < 0.05), confirming that population identity was the main driver of colour variation.

While CSA exposure status was highly significant in this combined sample ( P <0.001), there was no indication of an additional effect attributable to the familial environment ( P = 0.406) based on results from generalized mixed-effect models.

Moreover, a highly significant correlation was observed between PB and PU, with a p-value of <0.001 and a Kendall’s Tau B coefficient of -0.402, indicating a moderate negative relationship.

Results The use of healthcare services by the street-dwellers increased at endline compared to baseline in both the model clinic areas, and the difference was highly significant ( p < 0.001).