Showing 8,141 - 8,160 results of 17,850 for search '(( significant decrease decrease ) OR ( significant a decrease ))~', query time: 0.41s Refine Results
  1. 8141

    Data Sheet 1_Pingers as a potential deterrent tool to mitigate Burmeister’s porpoise (Phocoena spinipinnis) bycatch while foraging nocturnally in the Humboldt Current System: a pil... by Diego Díaz (3286374)

    Published 2025
    “…For 27 days during austral summer, a full wave form capture porpoise detector was anchored 7 m above sea level in Mejillones Bay where Burmeister’s porpoises are frequently observed. …”
  2. 8142

    Data Sheet 1_Chinese patent medicine tongxinluo capsule as a supplement to treat chronic coronary syndromes: a GRADE-assessed systematic review and meta-analysis of randomized cont... by Shi-Bing Liang (10200806)

    Published 2025
    “…Adding TXL to WM showed a non-significant trend toward reducing myocardial infarction [RR 0.34, 95% CI (0.05, 2.12); NNT = 41] and sudden cardiac death [RR 0.34, 95% CI (0.01, 8.28); NNT = 65]. …”
  3. 8143

    Data Sheet 2_Chinese patent medicine tongxinluo capsule as a supplement to treat chronic coronary syndromes: a GRADE-assessed systematic review and meta-analysis of randomized cont... by Shi-Bing Liang (10200806)

    Published 2025
    “…Adding TXL to WM showed a non-significant trend toward reducing myocardial infarction [RR 0.34, 95% CI (0.05, 2.12); NNT = 41] and sudden cardiac death [RR 0.34, 95% CI (0.01, 8.28); NNT = 65]. …”
  4. 8144

    Data Sheet 3_Chinese patent medicine tongxinluo capsule as a supplement to treat chronic coronary syndromes: a GRADE-assessed systematic review and meta-analysis of randomized cont... by Shi-Bing Liang (10200806)

    Published 2025
    “…Adding TXL to WM showed a non-significant trend toward reducing myocardial infarction [RR 0.34, 95% CI (0.05, 2.12); NNT = 41] and sudden cardiac death [RR 0.34, 95% CI (0.01, 8.28); NNT = 65]. …”
  5. 8145

    Data Sheet 4_Chinese patent medicine tongxinluo capsule as a supplement to treat chronic coronary syndromes: a GRADE-assessed systematic review and meta-analysis of randomized cont... by Shi-Bing Liang (10200806)

    Published 2025
    “…Adding TXL to WM showed a non-significant trend toward reducing myocardial infarction [RR 0.34, 95% CI (0.05, 2.12); NNT = 41] and sudden cardiac death [RR 0.34, 95% CI (0.01, 8.28); NNT = 65]. …”
  6. 8146

    Citation patterns of Cochrane Reviews and other systematic reviews: a bibliometric analysis by Louise Olsbro Rosengaard (20439098)

    Published 2025
    “…The time window in which systematic reviews received citations has been progressively decreasing, possibly indicating a trend toward quicker recognition and uptake of these reviews within the academic community. …”
  7. 8147

    Supplementary file 1_Ivarmacitinib reduces the need for adding/escalating medications in moderate-to-severe rheumatoid arthritis patients: a post hoc analysis from a phase III tria... by Huaxiang Liu (322464)

    Published 2025
    “…</p>Conclusion<p>Ivarmacitinib significantly reduces the need for adding/escalating medications compared to placebo, thereby potentially decreasing treatment burden. …”
  8. 8148

    Table 1_Temporal trends of cervical cancer demographics: a CDC WONDER database study.docx by Grace Folino (21738503)

    Published 2025
    “…Between 2015 and 2023, there was a concerning positive change in AAMR [APC of 0.1272 (95% CI –0.3393 to 1.7502)], though not statistically significant. …”
  9. 8149

    Image 4_Temporal trends of cervical cancer demographics: a CDC WONDER database study.png by Grace Folino (21738503)

    Published 2025
    “…Between 2015 and 2023, there was a concerning positive change in AAMR [APC of 0.1272 (95% CI –0.3393 to 1.7502)], though not statistically significant. …”
  10. 8150

    Image 2_Temporal trends of cervical cancer demographics: a CDC WONDER database study.png by Grace Folino (21738503)

    Published 2025
    “…Between 2015 and 2023, there was a concerning positive change in AAMR [APC of 0.1272 (95% CI –0.3393 to 1.7502)], though not statistically significant. …”
  11. 8151

    Image 3_Temporal trends of cervical cancer demographics: a CDC WONDER database study.png by Grace Folino (21738503)

    Published 2025
    “…Between 2015 and 2023, there was a concerning positive change in AAMR [APC of 0.1272 (95% CI –0.3393 to 1.7502)], though not statistically significant. …”
  12. 8152

    Image 5_Temporal trends of cervical cancer demographics: a CDC WONDER database study.png by Grace Folino (21738503)

    Published 2025
    “…Between 2015 and 2023, there was a concerning positive change in AAMR [APC of 0.1272 (95% CI –0.3393 to 1.7502)], though not statistically significant. …”
  13. 8153

    Image 1_Temporal trends of cervical cancer demographics: a CDC WONDER database study.png by Grace Folino (21738503)

    Published 2025
    “…Between 2015 and 2023, there was a concerning positive change in AAMR [APC of 0.1272 (95% CI –0.3393 to 1.7502)], though not statistically significant. …”
  14. 8154

    The overall framework of CARAFE. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”
  15. 8155

    KPD-YOLOv7-GD network structure diagram. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”
  16. 8156

    Comparison experiment of accuracy improvement. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”
  17. 8157

    Comparison of different pruning rates. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”
  18. 8158

    Comparison of experimental results at ablation. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”
  19. 8159

    Result of comparison of different lightweight. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”
  20. 8160

    DyHead Structure. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”