Search alternatives:
greater decrease » greatest decrease (Expand Search), greater increase (Expand Search), greater disease (Expand Search)
linear decrease » linear increase (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
greater decrease » greatest decrease (Expand Search), greater increase (Expand Search), greater disease (Expand Search)
linear decrease » linear increase (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
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3281
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3282
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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3283
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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3284
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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3285
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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3286
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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3287
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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3288
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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3289
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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3290
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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3291
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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3292
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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3293
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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3294
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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3295
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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3296
Kappa coefficients for different algorithms.
Published 2025“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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3297
The structure of ASPP+ block.
Published 2025“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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3298
The structure of attention gate block [31].
Published 2025“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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3299
DSC block and its application network structure.
Published 2025“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”
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3300
The structure of multi-scale residual block [30].
Published 2025“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”