Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
i.e decrease » we decrease (Expand Search), sizes decrease (Expand Search), use decreased (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
i.e decrease » we decrease (Expand Search), sizes decrease (Expand Search), use decreased (Expand Search)
-
3301
-
3302
Study Data.
Published 2025“…It has also been hypothesized that the bradycardia and rare instances of cardiac arrest occurring after the use of sugammadex may be due to a transient decrease in circulating corticosteroids, causing a temporary ‘mini Addisonian crisis.’ …”
-
3303
Risk of bias summary.
Published 2025“…The observed decrease in body weight could be partially attributed to factors influencing energy balance, as evidenced by the significantly lower mean calorie intake at the end of the intervention (1694.71 kcal/day, 95% CI: 1498.57–1890.85) compared to the baseline intake (2000.64 kcal/day, 95% CI: 1830–2172.98), despite the absence of intentional efforts to restrict energy intake by the participants. …”
-
3304
Study outcomes.
Published 2025“…It has also been hypothesized that the bradycardia and rare instances of cardiac arrest occurring after the use of sugammadex may be due to a transient decrease in circulating corticosteroids, causing a temporary ‘mini Addisonian crisis.’ …”
-
3305
Criteria for study selection.
Published 2025“…The observed decrease in body weight could be partially attributed to factors influencing energy balance, as evidenced by the significantly lower mean calorie intake at the end of the intervention (1694.71 kcal/day, 95% CI: 1498.57–1890.85) compared to the baseline intake (2000.64 kcal/day, 95% CI: 1830–2172.98), despite the absence of intentional efforts to restrict energy intake by the participants. …”
-
3306
Number of visits per clinic type, 2013-2015.
Published 2025“…During PE, statistically significant longer waiting times were found for surgery (+1.0 day) and imaging (+1.1 days), while a 2.4 days decrease was noted in pediatrics, controlled for age, sex, ethnicity and the daily number of visits. …”
-
3307
Patient characteristics.
Published 2025“…It has also been hypothesized that the bradycardia and rare instances of cardiac arrest occurring after the use of sugammadex may be due to a transient decrease in circulating corticosteroids, causing a temporary ‘mini Addisonian crisis.’ …”
-
3308
-
3309
Changes in the active H3K27ac and repressive H3K27me3 histone marks among Vasa2+/Piwi1+ and all cells in fed, starved, and refed juvenile polyps.
Published 2025“…Between fed, T<sub>5ds</sub> and T<sub>20ds</sub> timepoints, MFI levels of H3K27ac progressively and significantly decreased while levels H3K27me3 (M) did not change significantly (N). …”
-
3310
-
3311
The TOR inhibitors Rapamycin and AZD-8055 strongly reduce RPS6 phosphorylation and cell proliferation in Vasa2+/Piwi1+ cells.
Published 2025“…<i>n</i> = 2–4 biological replicates per condition, with 15 individuals per replicate. Significance levels for Student <i>t</i> test are indicated for adjusted <i>p</i> values: *<i>p</i> < 0.05, ***<i>p</i> < 0.001, ***<i>p</i> < 0.0001. d: day(s), n.s.: non-significant. …”
-
3312
-
3313
Testing set error.
Published 2025“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”
-
3314
Internal structure of an LSTM cell.
Published 2025“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”
-
3315
Prediction effect of each model after STL.
Published 2025“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”
-
3316
Estimated results of the mediation effect.
Published 2024“…The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. …”
-
3317
The kernel density plot for data of each feature.
Published 2025“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”
-
3318
Panel unit root test result.
Published 2024“…The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. …”
-
3319
Analysis of raw data prediction results.
Published 2025“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”
-
3320
Flowchart of the STL.
Published 2025“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”