Showing 3,641 - 3,660 results of 9,774 for search 'significantly ((((((larger decrease) OR (we decrease))) OR (linear decrease))) OR (mean decrease))', query time: 0.62s Refine Results
  1. 3641

    Raw data 6–9 and 15. by Fateme Khorramroo (18086501)

    Published 2025
    “…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”
  2. 3642

    Raw data 1–5. by Fateme Khorramroo (18086501)

    Published 2025
    “…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”
  3. 3643

    Raw data 10–14. by Fateme Khorramroo (18086501)

    Published 2025
    “…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”
  4. 3644

    Coordination angle during running. by Fateme Khorramroo (18086501)

    Published 2025
    “…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”
  5. 3645

    Gait retraining with biofeedback. by Fateme Khorramroo (18086501)

    Published 2025
    “…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”
  6. 3646

    Coordination angle during walking. by Fateme Khorramroo (18086501)

    Published 2025
    “…Wide running significantly decreased the coordination variability in the ankle-knee sagittal during LR (p<0.001) and knee-hip sagittal during LR (p=0.007) and push-off (p=0.016). …”
  7. 3647

    Primers for qPCR. by Xiaoyi Shi (3825754)

    Published 2024
    “…Our results indicated that PGAM5 was significantly elevated by I/R injury, and predominantly localized in the necrosis area. …”
  8. 3648

    Making Cells as a “Nirvana Phoenix”: Precise Coupling of Precursors Prior to ROS Bursts for Intracellular Synthesis of Quantum Dots by Juan Kong (2230867)

    Published 2025
    “…However, the introduced exogenous reactants and intracellularly produced species, e.g., reactive oxygen species (ROS), often cause cell damage, decreasing the fluorescence of the QDs. Herein, we have found that cell-adaptable selenocystine ((Cys-Se)<sub>2</sub>) can be reduced to biocompatible low-valence Se precursors, which could be subsequently hijacked by timely added Ag-glutathione (AgSG) to be transformed into NIR Ag<sub>2</sub>Se QDs. …”
  9. 3649

    Making Cells as a “Nirvana Phoenix”: Precise Coupling of Precursors Prior to ROS Bursts for Intracellular Synthesis of Quantum Dots by Juan Kong (2230867)

    Published 2025
    “…However, the introduced exogenous reactants and intracellularly produced species, e.g., reactive oxygen species (ROS), often cause cell damage, decreasing the fluorescence of the QDs. Herein, we have found that cell-adaptable selenocystine ((Cys-Se)<sub>2</sub>) can be reduced to biocompatible low-valence Se precursors, which could be subsequently hijacked by timely added Ag-glutathione (AgSG) to be transformed into NIR Ag<sub>2</sub>Se QDs. …”
  10. 3650

    S1 Raw data - by Xiaoyi Shi (3825754)

    Published 2024
    “…Our results indicated that PGAM5 was significantly elevated by I/R injury, and predominantly localized in the necrosis area. …”
  11. 3651

    Minimal data set. by Fu-Lin Yu (21446056)

    Published 2025
    “…However, the metabolic mechanisms underlying arsenic’s effects on muscle function and pathogenesis remain incompletely understood. In this study, we investigated the role of mitochondrial fatty acid oxidation in arsenic-induced muscular damage using mouse skeletal muscle C2C12 cells. …”
  12. 3652

    Making Cells as a “Nirvana Phoenix”: Precise Coupling of Precursors Prior to ROS Bursts for Intracellular Synthesis of Quantum Dots by Juan Kong (2230867)

    Published 2025
    “…However, the introduced exogenous reactants and intracellularly produced species, e.g., reactive oxygen species (ROS), often cause cell damage, decreasing the fluorescence of the QDs. Herein, we have found that cell-adaptable selenocystine ((Cys-Se)<sub>2</sub>) can be reduced to biocompatible low-valence Se precursors, which could be subsequently hijacked by timely added Ag-glutathione (AgSG) to be transformed into NIR Ag<sub>2</sub>Se QDs. …”
  13. 3653

    Making Cells as a “Nirvana Phoenix”: Precise Coupling of Precursors Prior to ROS Bursts for Intracellular Synthesis of Quantum Dots by Juan Kong (2230867)

    Published 2025
    “…However, the introduced exogenous reactants and intracellularly produced species, e.g., reactive oxygen species (ROS), often cause cell damage, decreasing the fluorescence of the QDs. Herein, we have found that cell-adaptable selenocystine ((Cys-Se)<sub>2</sub>) can be reduced to biocompatible low-valence Se precursors, which could be subsequently hijacked by timely added Ag-glutathione (AgSG) to be transformed into NIR Ag<sub>2</sub>Se QDs. …”
  14. 3654

    The chemical structure of melatonin. by Xiaoyi Shi (3825754)

    Published 2024
    “…Our results indicated that PGAM5 was significantly elevated by I/R injury, and predominantly localized in the necrosis area. …”
  15. 3655

    Regulation of Rice Grain Weight by Fatty Acid Composition: Unveiling the Mechanistic Roles of <i>OsLIN6</i> by OsARF12 by Haoran Tian (6706925)

    Published 2024
    “…However, the inner mechanism is still unclear and needs to be further studied. In this study, we identified that oleic acid (C18:1) negatively correlates while linoleic acid (C18:2) positively correlates with rice grain weight. …”
  16. 3656

    Modulating the Coordination Environment of Cu-Embedded Mo<i>X</i><sub>2</sub> (<i>X</i> = S, Se, and Te) Monolayers for Electrocatalytic Reduction of CO<sub>2</sub> to CH<sub>4</su... by Thamarainathan Doulassiramane (17382128)

    Published 2024
    “…We found that the catalytic activity is mainly due to the level of antibonding states filling between the Cu atom and *OCHOH intermediate. …”
  17. 3657

    Analysis of differential microbiome and classification prediction model between case and control groups. by Chuan Zhang (187157)

    Published 2025
    “…The relative importance of each genus in the predictive model was evaluated using the mean decreasing accuracy and the Gini coefficient.…”
  18. 3658

    PCA-CGAN model parameter settings. by Chao Tang (10925)

    Published 2025
    “…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”
  19. 3659

    MIT-BIH dataset proportion analysis chart. by Chao Tang (10925)

    Published 2025
    “…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”
  20. 3660

    Wavelet transform preprocessing results. by Chao Tang (10925)

    Published 2025
    “…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”