Flowchart of the STL-PCA-BWO-BiLSTM model. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …”

Parameter optimization results of BiLSTM. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …”

Descriptive statistical analysis of data. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …”

The MAE value of the model under raw data. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …”

Three error values under raw data. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …”

Decomposition of time scries plot. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …”

Aging impairs renal mitochondrial function and antioxidant capacity. by Lihua Qiu (178071)

Aging enhances α-SMA expression and collagen accumulation in the kidney. by Lihua Qiu (178071)

Effect of aging on cellular senescence in the mouse kidney. by Lihua Qiu (178071)

Alterations in renal tubular morphology and renal interstitial collagen deposition were observed in aged mice. by Lihua Qiu (178071)

Aging regulates mRNA levels of renal fibrosis-related genes in mice across varying age cohort. by Lihua Qiu (178071)

Effect of isoarborinol on 3T3-L1 cell viability. by Yesenia Arcos-Reyes (22177391)

Error metric values i.e. MAPE and NMRE in JJA (main rainy season) rainfall between station data and CHIRPS data set before and after bias correction. by Asnake Adane (19935018)

S1 File - by Jure Brečko (20314959)

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Supplementary Figs 1–7. by Juliane F. Tampé (19976538)

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Supplementary Tables 1–8. by Juliane F. Tampé (19976538)

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Increased <i>Huwe1</i> after induction of Sox2 in mouse ES cells. by Yen-Fu Cheng (5819855)

“…<i>Atoh1</i> expression increased with <i>Sox2</i> at low levels but decreased at higher <i>Sox2</i> level. …”

The raw data for Fig 4. by Hongjoo An (21703199)

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Effects of compound 4f on neuroinflammation in mice with KA-induced neurodegeneration. by Naoto Arimura (416442)

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All data in the manuscript and supporting information. by Naoto Arimura (416442)

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