Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
significantly a » significantly _ (Expand Search), significantly i (Expand Search), significantly vary (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
significantly a » significantly _ (Expand Search), significantly i (Expand Search), significantly vary (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
-
5941
ASP protects the AC16 cells from DOX-induced cardiotoxicity via Nrf2 activation.
Published 2025“…<p>(A) Representative images of protein expression detected by Western blot of p-PI3K,p-AKT, AKT, and the Nrf2 downstream signaling pathways in AC16 cells; (B, C) ML385 does not affect PI3K/AKT (n = 3); (D-F) The statistical results show that ML385 significantly represses NRF2 activation, leading to a decrease in its downstream gene expression (n = 3); (G, H) Lipid ROS levels (n = 3); (I, J) Quantitative q-PCR analysis of relative ANP and BNP mRNA expression (n = 3); (K, L) Representative images (Scale bar = 100 μm) and statistical analysis of JC-1 (n = 150); One-way ANOVA (Tukey post-test), means ± SD. …”
-
5942
-
5943
Example of sample data.
Published 2025“…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”
-
5944
Mean parameter values for the selected crops.
Published 2025“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”
-
5945
Performance comparison of ML models.
Published 2025“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”
-
5946
Comparative data of different soil samples.
Published 2025“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”
-
5947
Confusion matrix of random forest model.
Published 2025“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”
-
5948
Structure of BPNN.
Published 2025“…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”
-
5949
The workflow of EGA-BPNN.
Published 2025“…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”
-
5950
S1 Data -
Published 2025“…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”
-
5951
Sensor value scenario for fuzzy logic algorithm.
Published 2025“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”
-
5952
Algorithm flow of the GA-BPNN model.
Published 2025“…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”
-
5953
Evaluation metrics of selected ML models.
Published 2025“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”
-
5954
Block diagram of the proposed system.
Published 2025“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”
-
5955
Chart for applicable amount of fertilizers.
Published 2025“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”
-
5956
Cost analysis of irrigation controller unit.
Published 2025“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”
-
5957
Run times of two algorithms.
Published 2025“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”
-
5958
-
5959
Modeling method used.
Published 2025“…The most influential variables for predicting larval presence were the mean of Normalized Difference Vegetation Index (NDVI), texture indices from both NDVI, brightness index (BI), and the panchromatic image. Urban vegetation significantly influences larval presence, although higher vegetation index values correlate with a decreased probability of larval occurrence. …”
-
5960
Flow chart of Fuzzy Logic based control system.
Published 2025“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”