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levels decrease » levels decreased (Expand Search), rivers decreased (Expand Search)
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20041
Effect of the Surface Peak–Valley Features on Droplet Impact Dynamics under Leidenfrost Temperature
Published 2024“…Specifically, the Leidenfrost temperature on micropit surfaces increases with greater micropit area occupancy, while it decreases on micropillar surfaces under similar conditions, which is mainly attributed to the differential impact of area occupancy on droplet heat transfer efficiency. …”
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20042
S6 File -
Published 2024“…</p><p>Results</p><p>CY and DEX significantly reduced the immune function in DNFB-induced sensitized mice, as indicated by decreased thymus and spleen indices, MLN enlargement, intestinal sIgA content, and ear swelling degree. …”
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20043
Schematic flowchart of the study.
Published 2025“…Factors such as individuals’ age (p = 0.029), underlying comorbid conditions (30.3%; p = 0.035), and longer employment duration (28%; p = 0.034) were significantly associated with IGRA positivity. Further, IGRA positivity was significantly associated with decreased RDW standard deviation (RDW-SD). …”
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20044
Comorbidities among LTBI-positive individuals.
Published 2025“…Factors such as individuals’ age (p = 0.029), underlying comorbid conditions (30.3%; p = 0.035), and longer employment duration (28%; p = 0.034) were significantly associated with IGRA positivity. Further, IGRA positivity was significantly associated with decreased RDW standard deviation (RDW-SD). …”
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20045
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20046
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20047
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20048
Scheme of g-λ model with larger values λ.
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. …”
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20049
Participants’ characteristics.
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. …”
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20050
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
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. …”
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20051
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20052
Key Resources.
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. …”
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20053
Tax1bp1-deficiency reduces autophagy flux.
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. …”
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20054
Map showing the intervention and control LGAs.
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).…”
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20055
Consort diagram.
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).…”
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20056
The chain cable parameters.
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). …”
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20057
Robustness optimization strategy.
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). …”
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20058
Mooring system.
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). …”
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20059
The “Guo Hai Shi 1” offshore test platform.
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). …”
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20060
Difference comparison.
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). …”