Expression profile heatmaps of key genes in gene sets. حسب Jiyong Zhang (2498740)

الموضوعات:

Influence of UHMWPE length on free swelling ratio. حسب Yonggang Huang (223155)

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Construction of the WGCNA Co-expression Network. حسب Jiyong Zhang (2498740)

الموضوعات:

Influence of UHMWPE content on free swelling ratio. حسب Yonggang Huang (223155)

الموضوعات:

Soil partice-size distribution. حسب Yonggang Huang (223155)

الموضوعات:

Differential Gene Expression Associated with Non-Alcoholic Fatty Liver Disease. حسب Jiyong Zhang (2498740)

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Interaction analysis of hub genes. حسب Jiyong Zhang (2498740)

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Change in temperature from baseline. حسب Katharyn L. Flickinger (4759323)

Hemodynamic and respiratory changes over time. حسب Katharyn L. Flickinger (4759323)

Linear association Between Vitamin D Concentration and Visceral Adiposity Index (VAI) and Lipid Accumulation Product (LAP). حسب Hyelim Lee (11286822)

الموضوعات:

Comparison of Visceral Adiposity Index (VAI), Lipid Accumulation Product (LAP), and Related Variables by Vitamin D Status (A) VAI, (B) LAP, (C) TG, (D) WC, (E) BMI, (F) HDL-C. حسب Hyelim Lee (11286822)

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Distribution of HWP by Criteria and Vitamin D Status (Three Groups). حسب Hyelim Lee (11286822)

الموضوعات:

Association Between Vitamin D Status and Hypertriglyceridemic Waist Phenotype (HWP). حسب Hyelim Lee (11286822)

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Distribution of Hypertriglyceridemic Waist Phenotype, abdominal obesity, and high triglyceride by serum vitamin D Status. حسب Hyelim Lee (11286822)

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Characteristics of Study Participants. حسب Hyelim Lee (11286822)

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Distribution of HWP by Criteria and Vitamin D Status (Two Groups). حسب Hyelim Lee (11286822)

الموضوعات:

The Efficacy of Taurolidine Lock Solution in Preventing Catheter-Related Bloodstream Infections in Pediatrics: A Systematic Review and Meta-Analysis حسب Congyu Qin (22386781)

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. …"