Showing 621 - 640 results of 99,609 for search '(( 2 a decrease ) OR ( 5 ((((ng decrease) OR (nn decrease))) OR (mean decrease)) ))', query time: 1.77s Refine Results
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    Supplementary Material for: Enhanced Recovery after Surgery for Radical Cystectomy Decreases Postoperative Complications at Different Times by Lannes F. (11465377)

    Published 2021
    “…There was no significant difference between groups for 90-day readmission (<i>p</i> = 0.349). Mean length of stay did not differ significantly between ERAS and non-ERAS groups (12.7 ± 6.2 and 13.1 ± 5.7 days, respectively; <i>p</i> = 0.743). …”
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    Pep4 overexpression decreased APCs in Vps21- and ESCRT-mutant cells after nitrogen starvation. by Zulin Wu (4451572)

    Published 2022
    “…<p><b>A.</b> The accumulation of GFP-Atg8-labeled APCs in mutant cells (<i>vps21Δ</i>, <i>snf7Δ</i>, and <i>vps4Δ</i>) slightly decreased with Pep4 overexpression. …”
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    Overexpression of <i>RECQL4</i> results in increased RAD51 foci and decreased tail moment. by Thong T. Luong (13833935)

    Published 2022
    “…U2OS cells were transfected with an empty plasmid or a plasmid expressing RECQL4 or RECQL4-K508A under a CMV promoter. …”
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    NgR1 KO mice exhibited an increase in excitatory synapses and a decrease in inhibitory synapses, indicating an imbalance of synaptic transmission. by Jinwei Zhang (462455)

    Published 2025
    “…The inhibitory synaptic density of NgR1 mice showed a significant decrease when compared to WT mice (***P <  0.001). …”
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    Model performance with different sparsity rates. by Zhongjian Xie (4633099)

    Published 2024
    “…The experimental results showed that P-YOLOv5s-GRNF increased the mAP(mean average precision) by 0.8%, 4.3%, 3.2%, 0.7%, 19.3%, 9.8%, 3.1% compared to mainstream object detection algorithms YOLOv5s, YOLOv6s, YOLOv7-tiny, YOLOv8s, YOLOv5s-Shufflenetv2, YOLOv5s-Mobilenetv3, YOLOv5s-Ghost, respectively. …”
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    Comparison of different lightweight models. by Zhongjian Xie (4633099)

    Published 2024
    “…The experimental results showed that P-YOLOv5s-GRNF increased the mAP(mean average precision) by 0.8%, 4.3%, 3.2%, 0.7%, 19.3%, 9.8%, 3.1% compared to mainstream object detection algorithms YOLOv5s, YOLOv6s, YOLOv7-tiny, YOLOv8s, YOLOv5s-Shufflenetv2, YOLOv5s-Mobilenetv3, YOLOv5s-Ghost, respectively. …”