Search alternatives:
largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), teer decrease (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), gy decreased (Expand Search)
largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), teer decrease (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), gy decreased (Expand Search)
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2561
Targeted removal robustness analysis.
Published 2025“…Distance increased the relative abundance of Actinobacteria, Acidobacteria, and Chloroflexi, but significantly decreased the relative abundance of Proteobacteria and Firmicutes. …”
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2562
The network parameter at different distances.
Published 2025“…Distance increased the relative abundance of Actinobacteria, Acidobacteria, and Chloroflexi, but significantly decreased the relative abundance of Proteobacteria and Firmicutes. …”
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2563
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2564
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2565
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2566
A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets
Published 2025“…To address the aforementioned challenges, we developed a bionic wedge-shaped track on the copper (Cu) substrate inspired by the cone-shaped thorn of cactus for liquid spontaneous transport. …”
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2567
A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets
Published 2025“…To address the aforementioned challenges, we developed a bionic wedge-shaped track on the copper (Cu) substrate inspired by the cone-shaped thorn of cactus for liquid spontaneous transport. …”
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2568
A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets
Published 2025“…To address the aforementioned challenges, we developed a bionic wedge-shaped track on the copper (Cu) substrate inspired by the cone-shaped thorn of cactus for liquid spontaneous transport. …”
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2569
A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets
Published 2025“…To address the aforementioned challenges, we developed a bionic wedge-shaped track on the copper (Cu) substrate inspired by the cone-shaped thorn of cactus for liquid spontaneous transport. …”
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2570
A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets
Published 2025“…To address the aforementioned challenges, we developed a bionic wedge-shaped track on the copper (Cu) substrate inspired by the cone-shaped thorn of cactus for liquid spontaneous transport. …”
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2571
A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets
Published 2025“…To address the aforementioned challenges, we developed a bionic wedge-shaped track on the copper (Cu) substrate inspired by the cone-shaped thorn of cactus for liquid spontaneous transport. …”
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2572
Schematic diagram of numerical simulation model.
Published 2025“…Finally, using the established prediction method, we calculated the limiting conditions for the existence of weak water-flushed zones in the X oil field test area. …”
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2573
The result of molecular dynamics simulation.
Published 2025“…The docking research indicated that these mutations decreased the binding affinity for DNA, with R273C, R280G, G266E, and G105C displaying the most significant differences. …”
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2574
Result of the phenotypic analysis.
Published 2025“…The docking research indicated that these mutations decreased the binding affinity for DNA, with R273C, R280G, G266E, and G105C displaying the most significant differences. …”
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2575
Type of Mutations.
Published 2025“…The docking research indicated that these mutations decreased the binding affinity for DNA, with R273C, R280G, G266E, and G105C displaying the most significant differences. …”
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2576
Algorithm training accuracy experiments.
Published 2025“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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2577
Repeat the detection experiment.
Published 2025“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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2578
Detection network structure with IRAU [34].
Published 2025“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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2579
Ablation experiments of various block.
Published 2025“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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2580
Kappa coefficients for different algorithms.
Published 2025“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”