Master database baseline, 4 weeks and 1 year. حسب Jannet A. Tobon Ramos (20855642)

"…We compared the effectiveness of a single round of MDA with IDA or DA on hookworm and strongyloidiasis in PNG.…"

CTV p20 interacts with autophagy-related proteins NbATG8a and NbATG8f and induces autophagy. حسب Yongle Zhang (11355546)

Initial transport rate of [³H]-hypoxanthine of PhZ mutants (V%). حسب Mariana Barraco-Vega (19996318)

"…Different letters (a, b, c, d) represent significant differences at p < 0.05 probability level, according to ANOVA and Tukey´s test.…"

(A) Number of crossings, (B) Number of rearings, (C) Latency time for novel object, (D) Familiar object exploration time, (E) Novel object exploration time for novel object recogni... حسب Hammad Ismail (4227988)

Data_Sheet_2_Urolithin A alleviates cell senescence by inhibiting ferroptosis and enhances corneal epithelial wound healing.docx حسب Xiao-Xiao Guo (6092141)

"…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). …"

Data_Sheet_1_Urolithin A alleviates cell senescence by inhibiting ferroptosis and enhances corneal epithelial wound healing.zip حسب Xiao-Xiao Guo (6092141)

"…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). …"

Changes in the active H3K27ac and repressive H3K27me3 histone marks among Vasa2+/Piwi1+ and all cells in fed, starved, and refed juvenile polyps. حسب Eudald Pascual-Carreras (12115380)

"…Between fed, T_5ds and T_20ds timepoints, MFI levels of H3K27ac progressively and significantly decreased while levels H3K27me3 (M) did not change significantly (N). …"

Achieving Improved Ion Swarm Shaping Based on Ion Leakage Control in Ion Mobility Spectrometry حسب Jiyao Wang (2121157)

"…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>_p–<i>R</i>_p linear relationship. …"

Testing set error. حسب Xiangjuan Liu (618000)

"…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. …"

Internal structure of an LSTM cell. حسب Xiangjuan Liu (618000)

"…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. …"

Prediction effect of each model after STL. حسب Xiangjuan Liu (618000)

"…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. …"

The kernel density plot for data of each feature. حسب Xiangjuan Liu (618000)

"…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. …"

Analysis of raw data prediction results. حسب Xiangjuan Liu (618000)

"…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. …"

Flowchart of the STL. حسب Xiangjuan Liu (618000)

"…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. …"

SARIMA predicts season components. حسب Xiangjuan Liu (618000)

"…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. …"

BWO-BiLSTM model prediction results. حسب Xiangjuan Liu (618000)

"…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. …"

Bi-LSTM architecture diagram. حسب Xiangjuan Liu (618000)

"…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. …"

STL Linear Combination Forecast Graph. حسب Xiangjuan Liu (618000)

"…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. …"

LOSS curves for BWO-BiLSTM model training. حسب Xiangjuan Liu (618000)

"…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. …"

Analysis of STL-PCA prediction results. حسب Xiangjuan Liu (618000)

"…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. …"