For the ASRS, a significant trend ( p < 0.01) was identified, whereby increasing pain intensity was associated with higher ADHD positivity rates.
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The tree species and season had a highly significant effect ( P < 0.01), age class had a significant effect ( P < 0.05), and the interaction between tree species and age class had a significant effect on δ 13 C ( P < 0.05).
From the ANOVA table, it can be seen that the model of seed conductivity, an indicator of experimental evaluation, was highly significant (P < 0.01), the misfit term was not significant (P > 0.05), and the regression equation was not misfit.
Statistical analysis confirmed that the differences between treated and control groups were highly significant ( p < 0.01), highlighting the potential of soil pollution exposure to induce metabolic stress and enzyme activation.
This difference was highly significant (p < 0.01) at DPO90 and DPO120, respectively.
The nozzle flow rate (X 1 ) was observed to be highly significant at p < 0.01 for all the responses i.e., Y 1 , Y 2 , Y 3 , Y 4 , Y 5 and Y 6 in orchard I.
Among them, the expression levels of Alox5ap , Chil1 , Clec7a , Fcgr3 , H2 − K1 , and Tnnt2 were extremely significantly different (p value < 0.001) between different groups (Normal/ARHL), and the expression levels of Il10ra and Rgs1 showed highly significant discrepancies (p value < 0.01).
Yield The interaction between fertigation regime and foliar treatments (NaHS or Cys, applied independently) had a highly significant effect on the yield of ‘Sabrina’ strawberry ( p < 0.01).
Highly significant (p < 0.01) correlation (r = 0.96; N = 270) was found between beat to beat fetal heart rate (FHR ECG ) from fECG and the same (FHR PCG ) from fetal PCG signals.
All tested factors exhibited a highly significant effect on protease activity, specifically in terms of their quadratic dependence, with p-values ranging from 0.001 to 0.002 ( p < 0.01), i.e., not all factors influence the response linearly nor through interactions, since all coefficients of linear terms and all interactions present a meager value (Table 3 ).
The effects of DO on plant height, stem thickness and LAI were highly significant (P < 0.01).
Statistical differences were designated as significant if p -values were less than 0.05 (* p ≤ 0.05), and highly significant if p-values were less than 0.01 (** p ≤ 0.01) or less than 0.001 (*** p ≤ 0.001).
Such spatial differences were highly significant ( P < 0.01 ), where site VI harboured the lowest abundance with an average value of 608 ± 344.90 individuals L -1 , while site III was the highest (1458 ± 594.61 individuals L -1 ).
Statistical analysis confirmed highly significant inter-district differences ( p < 0.01), as shown in Fig. 3 .
Differences were considered statistically significant with p < 0.05 (*) and highly significant at p < 0.01 (**) and p < 0.005 (***).
3 B indicates that Height displays significant positive correlations with NH 4 + and soil-TP content ( P < 0.05), and significant negative correlation with pH ( P < 0.01); Height also exhibits a negative correlation with EW ( P < 0.05) and positive correlations with DAT, ADP, TW, and NW at significant ( P < 0.05) or highly significant levels ( P < 0.01); furthermore, Height is significantly ( P < 0.05) or highly significantly ( P < 0.01) positively associated with seed-TP and seed-TK content.
In this study, highly significant correlations ( p < 0.01) were observed among all physico-chemical traits examined.
Statistical significance was set at p < 0.05, with highly significant differences defined as p < 0.01.
29 , using the following formula: Results Analysis of variance for the experimental design over the environments The mean sums of squares due to the genotype were highly significant ( p ≤ 0.01) for all studied traits in both the environments (Table 2 ); providing a perusal that there was sufficient variation present among the genotypes.
A, B, C Different superscript uppercase letters within a row indicated a highly significant difference (p < 0.01).
Analysis of variance revealed highly significant differences ( p ≤ 0.01) among genotypes for all the studied traits, indicating the presence of substantial genetic variability.
From the data presented in Table 3 , it is evident that the relationship between the monthly changes of Rs and the multiple linear regression of soil moisture and temperature in various areas is highly significant ( P < 0.01).
Results Non-structural carbohydrates (NSCs) Highly significant effects were found for treatment and the interaction between treatment and sampling period on leaf soluble sugar concentration (% DW) (p < 0.01, Table 1 ).
The improvements over traditional approaches like CNN and Decision Tree-Random Forest (DT-RF) are highly significant ( p < 0.01), while comparisons with more advanced models like transformer-based architectures (BERT, RoBERTa, DeBERTa) and Graph Neural Networks (GNN) also show statistically significant improvements ( p < 0.05).
Therefore, ANOVA revealed wheat genotypes, pathotypes, and their two-way interactions were highly significant ( p < 0.01) in Table 2 (Supplementary Materials Fig. 1).