Showing 19,921 - 19,940 results of 36,050 for search '(( significant decrease decrease ) OR ( significant ((levels increased) OR (teer decrease)) ))', query time: 0.76s Refine Results
  1. 19921

    Annual distribution of IG-ralated AE reports. by Shaozhi Liu (13720340)

    Published 2025
    “…In the overall population, the most significant signals included blood glucose abnormal (IC025 = 4.86), blood glucose fluctuation (IC025 = 4.69), blood glucose decreased (IC025 = 4.44), hypoglycaemic seizure (IC025 = 4.44) and hypoglycaemic unconsciousness (IC025 = 4.31). …”
  2. 19922

    Proportion of AEs by SOCs in pregnant women. by Shaozhi Liu (13720340)

    Published 2025
    “…In the overall population, the most significant signals included blood glucose abnormal (IC025 = 4.86), blood glucose fluctuation (IC025 = 4.69), blood glucose decreased (IC025 = 4.44), hypoglycaemic seizure (IC025 = 4.44) and hypoglycaemic unconsciousness (IC025 = 4.31). …”
  3. 19923

    Scheme of g-λ model with larger values λ. by Zhanfeng Fan (20390992)

    Published 2024
    “…The findings suggest that when λ is respectively equal to 4.19, 8.57, 10, and 12.15, the peak particle velocity (PPV) of the transmitted waves is significantly close to the incident wave amplitude. Furthermore, when λ is fixed, the energy transmission coefficient increases with the incident wave amplitude but decreases with the incident wave frequency. …”
  4. 19924

    Participants’ characteristics. by Aizhan Zabirova (21446781)

    Published 2025
    “…A logistic regression analysis indicated that acceptance of the facility and good mental health significantly increased the likelihood of trusting information provided by the public authorities, while concerns about genetic risks and negative images significantly decreased it. …”
  5. 19925

    Physics-Assisted Machine Learning for the Simulation of the Slurry Drying in the Manufacturing Process of Battery Electrodes: A Hybrid Time-Dependent VGG16-DEM Model by Diego E. Galvez-Aranda (9436672)

    Published 2025
    “…Furthermore, the integration of DL significantly reduced the computational cost versus the original DEM model simulation, decreasing the calculation time from 615 to 36 min for the whole slurry drying simulation process. …”
  6. 19926
  7. 19927

    Sketches of the two circuits used. by Lars-Olav Harnisch (22008639)

    Published 2025
    “…In the design of circuit-2, MP exceeded the 12 J/min threshold in both lung simulators at elevated RR and could only be decreased through valve closure followed by a consequential hypoventilation in one simulator.…”
  8. 19928

    Key Resources. by Jeffrey Chin (22538086)

    Published 2025
    “…These experiments revealed that Tax1bp1 protein abundance does not significantly change early after infection in AMs but does in BMDMs; moreover, early after infection, Tax1bp1-deficiency reduced necrotic-like cell death -- an outcome that favors <i>Mtb</i> replication -- in AMs but not BMDMs. …”
  9. 19929

    Tax1bp1-deficiency reduces autophagy flux. by Jeffrey Chin (22538086)

    Published 2025
    “…These experiments revealed that Tax1bp1 protein abundance does not significantly change early after infection in AMs but does in BMDMs; moreover, early after infection, Tax1bp1-deficiency reduced necrotic-like cell death -- an outcome that favors <i>Mtb</i> replication -- in AMs but not BMDMs. …”
  10. 19930

    Map showing the intervention and control LGAs. by Chinwe C. Eze (8787503)

    Published 2025
    “…However, post-intervention, the adjusted mean SARI Stigma Score significantly decreased in the intervention group compared to the control group, with an adjusted mean difference of 37.72 (95% CI: 36.01–39.43, p < 0.000).…”
  11. 19931

    Consort diagram. by Chinwe C. Eze (8787503)

    Published 2025
    “…However, post-intervention, the adjusted mean SARI Stigma Score significantly decreased in the intervention group compared to the control group, with an adjusted mean difference of 37.72 (95% CI: 36.01–39.43, p < 0.000).…”
  12. 19932

    The chain cable parameters. by Huiyuan Zheng (12889196)

    Published 2025
    “…Nevertheless, a 40% reduction in roll motion is achieved (3.36° in Condition 4 vs. 5.60° in Condition 1), along with a 24.5% reduction in yaw motion (39.22° in Condition 4 vs. 51.94° in Condition 1). (3) In irregular wave simulations, the ballast tanks effectively reduce the heave amplitude by up to 8.34% in sea state level 4 and 6.06% in sea state level 8, thereby enhancing its wave-following performance in the heave degree of freedom. (4) A CNN_BiLSTM_Attention algorithm is developed using hydrodynamic analysis generated datasets to predict the pitch motion time series of the platform under different ballast water conditions and sea states, while the model has a superior prediction performance (R² = 0.9658, RMSE = 0.5343, MAE = 0.3188, representing a 4.82% increase in R² and 30.31% reduction in RMSE compared to the original model). …”
  13. 19933

    Robustness optimization strategy. by Huiyuan Zheng (12889196)

    Published 2025
    “…Nevertheless, a 40% reduction in roll motion is achieved (3.36° in Condition 4 vs. 5.60° in Condition 1), along with a 24.5% reduction in yaw motion (39.22° in Condition 4 vs. 51.94° in Condition 1). (3) In irregular wave simulations, the ballast tanks effectively reduce the heave amplitude by up to 8.34% in sea state level 4 and 6.06% in sea state level 8, thereby enhancing its wave-following performance in the heave degree of freedom. (4) A CNN_BiLSTM_Attention algorithm is developed using hydrodynamic analysis generated datasets to predict the pitch motion time series of the platform under different ballast water conditions and sea states, while the model has a superior prediction performance (R² = 0.9658, RMSE = 0.5343, MAE = 0.3188, representing a 4.82% increase in R² and 30.31% reduction in RMSE compared to the original model). …”
  14. 19934

    Mooring system. by Huiyuan Zheng (12889196)

    Published 2025
    “…Nevertheless, a 40% reduction in roll motion is achieved (3.36° in Condition 4 vs. 5.60° in Condition 1), along with a 24.5% reduction in yaw motion (39.22° in Condition 4 vs. 51.94° in Condition 1). (3) In irregular wave simulations, the ballast tanks effectively reduce the heave amplitude by up to 8.34% in sea state level 4 and 6.06% in sea state level 8, thereby enhancing its wave-following performance in the heave degree of freedom. (4) A CNN_BiLSTM_Attention algorithm is developed using hydrodynamic analysis generated datasets to predict the pitch motion time series of the platform under different ballast water conditions and sea states, while the model has a superior prediction performance (R² = 0.9658, RMSE = 0.5343, MAE = 0.3188, representing a 4.82% increase in R² and 30.31% reduction in RMSE compared to the original model). …”
  15. 19935

    The “Guo Hai Shi 1” offshore test platform. by Huiyuan Zheng (12889196)

    Published 2025
    “…Nevertheless, a 40% reduction in roll motion is achieved (3.36° in Condition 4 vs. 5.60° in Condition 1), along with a 24.5% reduction in yaw motion (39.22° in Condition 4 vs. 51.94° in Condition 1). (3) In irregular wave simulations, the ballast tanks effectively reduce the heave amplitude by up to 8.34% in sea state level 4 and 6.06% in sea state level 8, thereby enhancing its wave-following performance in the heave degree of freedom. (4) A CNN_BiLSTM_Attention algorithm is developed using hydrodynamic analysis generated datasets to predict the pitch motion time series of the platform under different ballast water conditions and sea states, while the model has a superior prediction performance (R² = 0.9658, RMSE = 0.5343, MAE = 0.3188, representing a 4.82% increase in R² and 30.31% reduction in RMSE compared to the original model). …”
  16. 19936

    Difference comparison. by Huiyuan Zheng (12889196)

    Published 2025
    “…Nevertheless, a 40% reduction in roll motion is achieved (3.36° in Condition 4 vs. 5.60° in Condition 1), along with a 24.5% reduction in yaw motion (39.22° in Condition 4 vs. 51.94° in Condition 1). (3) In irregular wave simulations, the ballast tanks effectively reduce the heave amplitude by up to 8.34% in sea state level 4 and 6.06% in sea state level 8, thereby enhancing its wave-following performance in the heave degree of freedom. (4) A CNN_BiLSTM_Attention algorithm is developed using hydrodynamic analysis generated datasets to predict the pitch motion time series of the platform under different ballast water conditions and sea states, while the model has a superior prediction performance (R² = 0.9658, RMSE = 0.5343, MAE = 0.3188, representing a 4.82% increase in R² and 30.31% reduction in RMSE compared to the original model). …”
  17. 19937

    Comparison of model draft and actual draft. by Huiyuan Zheng (12889196)

    Published 2025
    “…Nevertheless, a 40% reduction in roll motion is achieved (3.36° in Condition 4 vs. 5.60° in Condition 1), along with a 24.5% reduction in yaw motion (39.22° in Condition 4 vs. 51.94° in Condition 1). (3) In irregular wave simulations, the ballast tanks effectively reduce the heave amplitude by up to 8.34% in sea state level 4 and 6.06% in sea state level 8, thereby enhancing its wave-following performance in the heave degree of freedom. (4) A CNN_BiLSTM_Attention algorithm is developed using hydrodynamic analysis generated datasets to predict the pitch motion time series of the platform under different ballast water conditions and sea states, while the model has a superior prediction performance (R² = 0.9658, RMSE = 0.5343, MAE = 0.3188, representing a 4.82% increase in R² and 30.31% reduction in RMSE compared to the original model). …”
  18. 19938

    Resultant moment diagram. by Huiyuan Zheng (12889196)

    Published 2025
    “…Nevertheless, a 40% reduction in roll motion is achieved (3.36° in Condition 4 vs. 5.60° in Condition 1), along with a 24.5% reduction in yaw motion (39.22° in Condition 4 vs. 51.94° in Condition 1). (3) In irregular wave simulations, the ballast tanks effectively reduce the heave amplitude by up to 8.34% in sea state level 4 and 6.06% in sea state level 8, thereby enhancing its wave-following performance in the heave degree of freedom. (4) A CNN_BiLSTM_Attention algorithm is developed using hydrodynamic analysis generated datasets to predict the pitch motion time series of the platform under different ballast water conditions and sea states, while the model has a superior prediction performance (R² = 0.9658, RMSE = 0.5343, MAE = 0.3188, representing a 4.82% increase in R² and 30.31% reduction in RMSE compared to the original model). …”
  19. 19939

    Regular wave condition combination. by Huiyuan Zheng (12889196)

    Published 2025
    “…Nevertheless, a 40% reduction in roll motion is achieved (3.36° in Condition 4 vs. 5.60° in Condition 1), along with a 24.5% reduction in yaw motion (39.22° in Condition 4 vs. 51.94° in Condition 1). (3) In irregular wave simulations, the ballast tanks effectively reduce the heave amplitude by up to 8.34% in sea state level 4 and 6.06% in sea state level 8, thereby enhancing its wave-following performance in the heave degree of freedom. (4) A CNN_BiLSTM_Attention algorithm is developed using hydrodynamic analysis generated datasets to predict the pitch motion time series of the platform under different ballast water conditions and sea states, while the model has a superior prediction performance (R² = 0.9658, RMSE = 0.5343, MAE = 0.3188, representing a 4.82% increase in R² and 30.31% reduction in RMSE compared to the original model). …”
  20. 19940

    Ballast tank water volume setting. by Huiyuan Zheng (12889196)

    Published 2025
    “…Nevertheless, a 40% reduction in roll motion is achieved (3.36° in Condition 4 vs. 5.60° in Condition 1), along with a 24.5% reduction in yaw motion (39.22° in Condition 4 vs. 51.94° in Condition 1). (3) In irregular wave simulations, the ballast tanks effectively reduce the heave amplitude by up to 8.34% in sea state level 4 and 6.06% in sea state level 8, thereby enhancing its wave-following performance in the heave degree of freedom. (4) A CNN_BiLSTM_Attention algorithm is developed using hydrodynamic analysis generated datasets to predict the pitch motion time series of the platform under different ballast water conditions and sea states, while the model has a superior prediction performance (R² = 0.9658, RMSE = 0.5343, MAE = 0.3188, representing a 4.82% increase in R² and 30.31% reduction in RMSE compared to the original model). …”