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larger decrease » marked decrease (Expand Search)
large decrease » marked decrease (Expand Search), large increases (Expand Search), large degree (Expand Search)
long decrease » point decrease (Expand Search), nn decrease (Expand Search), fold decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
larger decrease » marked decrease (Expand Search)
large decrease » marked decrease (Expand Search), large increases (Expand Search), large degree (Expand Search)
long decrease » point decrease (Expand Search), nn decrease (Expand Search), fold decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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The introduction of mutualisms into assembled communities increases their connectance and complexity while decreasing their richness.
Published 2025“…When they stop being introduced in further assembly events (i.e. introduced species do not carry any mutualistic interactions), their proportion slowly decreases with successive invasions. (B) Even though higher proportions of mutualism promote higher richness, introducing this type of interaction into already assembled large communities promotes a sudden drop in richness, while stopping mutualism promotes a slight boost in richness increase. …”
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<b>Supporting data for manuscript</b> "<b>Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins</b>"
Published 2025“…<p dir="ltr">The CSV file 'Eyreetal_DrainingVein_SourceData' contains the averaged time series traces and extracted metrics from individual experiments used across Figures 1-5 in the manuscript "Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins". The following acronyms included in the CSV file are defined as follows: Hbt is total hemoglobin, Art is artery region, DV is draining vein region, WV is whisker vein region, SEM is standard error mean, TS is time series, max peak is maximum peak, min peak is minima, AUC is area under the curve, WT is wild-type, AD is Alzheimer's disease, ATH is atherosclerosis and MIX is mixed AD/atherosclerosis. …”
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A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets
Published 2025“…Furthermore, a wettability gradient (water contact angle from 154.6° to 84.9°) was prepared on the wedge-shaped track to enhance the droplet motion. …”
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A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets
Published 2025“…Furthermore, a wettability gradient (water contact angle from 154.6° to 84.9°) was prepared on the wedge-shaped track to enhance the droplet motion. …”
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A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets
Published 2025“…Furthermore, a wettability gradient (water contact angle from 154.6° to 84.9°) was prepared on the wedge-shaped track to enhance the droplet motion. …”
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A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets
Published 2025“…Furthermore, a wettability gradient (water contact angle from 154.6° to 84.9°) was prepared on the wedge-shaped track to enhance the droplet motion. …”
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A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets
Published 2025“…Furthermore, a wettability gradient (water contact angle from 154.6° to 84.9°) was prepared on the wedge-shaped track to enhance the droplet motion. …”
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A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets
Published 2025“…Furthermore, a wettability gradient (water contact angle from 154.6° to 84.9°) was prepared on the wedge-shaped track to enhance the droplet motion. …”
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Experimental setup under ablation experiments.
Published 2025“…Simulation-based experimental results demonstrate that, under complex obstacle motion scenarios, the proposed method achieves a 55.8% reduction in trajectory tracking error compared with recently proposed improved APF methods and a 41.5% decrease relative to Dynamic Movement Primitives (DMP) baselines. …”
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Obstacle uniform linear motion scenarios.
Published 2025“…Simulation-based experimental results demonstrate that, under complex obstacle motion scenarios, the proposed method achieves a 55.8% reduction in trajectory tracking error compared with recently proposed improved APF methods and a 41.5% decrease relative to Dynamic Movement Primitives (DMP) baselines. …”
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Analysis of the tangential force of the obstacle.
Published 2025“…Simulation-based experimental results demonstrate that, under complex obstacle motion scenarios, the proposed method achieves a 55.8% reduction in trajectory tracking error compared with recently proposed improved APF methods and a 41.5% decrease relative to Dynamic Movement Primitives (DMP) baselines. …”
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Table of values for <i>p.</i>
Published 2025“…Simulation-based experimental results demonstrate that, under complex obstacle motion scenarios, the proposed method achieves a 55.8% reduction in trajectory tracking error compared with recently proposed improved APF methods and a 41.5% decrease relative to Dynamic Movement Primitives (DMP) baselines. …”
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Static obstacle avoidance scene setup.
Published 2025“…Simulation-based experimental results demonstrate that, under complex obstacle motion scenarios, the proposed method achieves a 55.8% reduction in trajectory tracking error compared with recently proposed improved APF methods and a 41.5% decrease relative to Dynamic Movement Primitives (DMP) baselines. …”
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The schematic diagram of the region <i>O</i><sub>1</sub>.
Published 2025“…Simulation-based experimental results demonstrate that, under complex obstacle motion scenarios, the proposed method achieves a 55.8% reduction in trajectory tracking error compared with recently proposed improved APF methods and a 41.5% decrease relative to Dynamic Movement Primitives (DMP) baselines. …”
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