Search alternatives:
step decrease » sizes decrease (Expand Search), teer decrease (Expand Search), we decrease (Expand Search)
nn decrease » _ decrease (Expand Search), mean decrease (Expand Search), gy decreased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
step decrease » sizes decrease (Expand Search), teer decrease (Expand Search), we decrease (Expand Search)
nn decrease » _ decrease (Expand Search), mean decrease (Expand Search), gy decreased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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5541
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5542
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5543
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5544
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5545
NIE ELISA results.
Published 2025“…We compared the effectiveness of a single round of MDA with IDA or DA on hookworm and strongyloidiasis in PNG.…”
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5546
Kato Katz and PCR database 12 months collection.
Published 2025“…We compared the effectiveness of a single round of MDA with IDA or DA on hookworm and strongyloidiasis in PNG.…”
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5547
Master database baseline, 4 weeks and 1 year.
Published 2025“…We compared the effectiveness of a single round of MDA with IDA or DA on hookworm and strongyloidiasis in PNG.…”
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5548
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5549
Initial transport rate of [<sup>3</sup>H]-hypoxanthine of PhZ mutants (V%).
Published 2024“…Different letters (a, b, c, d) represent significant differences at p < 0.05 probability level, according to ANOVA and Tukey´s test.…”
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5550
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5551
Data_Sheet_2_Urolithin A alleviates cell senescence by inhibiting ferroptosis and enhances corneal epithelial wound healing.docx
Published 2024“…The results of RNA-seq of HS-induced corneal epithelial cells showed that the ferroptosis pathway was significantly dysregulated. Further investigation revealed that UA decreased the level of oxidative stress in HCE-T cells, including the levels of LPO and MDA (p < 0.05). …”
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5552
Data_Sheet_1_Urolithin A alleviates cell senescence by inhibiting ferroptosis and enhances corneal epithelial wound healing.zip
Published 2024“…The results of RNA-seq of HS-induced corneal epithelial cells showed that the ferroptosis pathway was significantly dysregulated. Further investigation revealed that UA decreased the level of oxidative stress in HCE-T cells, including the levels of LPO and MDA (p < 0.05). …”
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5553
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). …”
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5554
Achieving Improved Ion Swarm Shaping Based on Ion Leakage Control in Ion Mobility Spectrometry
Published 2025“…Simulations and experiments demonstrate that precise voltage adjustments effectively minimize ion leakage, enhancing resolving power by 50% (reaching a maximum of 106), while the corresponding decrease in signal intensity follows the <i>I</i><sub>p</sub>–<i>R</i><sub>p</sub> linear relationship. …”
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5555
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. …”
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5556
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. …”
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5557
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. …”
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5558
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. …”
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5559
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. …”
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5560
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. …”