Trends of the temperature, precipitation, and TVDI in the Santun River Irrigation Area, Xinjiang, during 2005–2023. حسب Yuxin Wei (11510974)

Conceptual diagram of survival curve and loss of life expectancy. حسب Hiroaki Saito (24514)

This figure is the PRISMA used in synthesis of the systematic review. حسب Aahan Arif (20189512)

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Characteristics of included studies, mental health outcomes recorded, and study tools used. حسب Aahan Arif (20189512)

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Relationship between <i>β</i>₁ and <i>β</i>₂ and compressive strength. حسب YongHe Liu (20477123)

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Porosity changes in concrete after F–T under three curing conditions. حسب YongHe Liu (20477123)

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The association of cybervictimization with mental health outcomes. حسب Aahan Arif (20189512)

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This file includes the data availability tables that are relevant to data curation in the systematic review. حسب Aahan Arif (20189512)

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Fitting equation of material parameters <i>β</i>₁ and <i>β</i>₂ and compressive strength in Pei model. حسب YongHe Liu (20477123)

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IRE1 depletion increases chromosome instability. حسب Iratxe Zuazo-Gaztelu (21071939)

(a, b). The statistical error analyses for the models using the same dataset. حسب Fahd Saeed Alakbari (10701871)

Coal seam combustion (a), (c) and infrared thermometry map (b), (d) in Fire Zone 1 and 3 (Republished from Desheng Xie under a CC BY license, with permission from Desheng Xie, orig... حسب Desheng Xie (21439869)

The restoration effect carried out in the early stage of (a) Fire Zone 1 and (b) Fire Zone 3 (Republished from Desheng Xie under a CC BY license, with permission from Desheng Xie,... حسب Desheng Xie (21439869)

Structure diagram of ensemble model. حسب Hongqi Wang (2208238)

"…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"

Fitting formula parameter table. حسب Hongqi Wang (2208238)

"…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"

Test plan. حسب Hongqi Wang (2208238)

"…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"

Fitting surface parameters. حسب Hongqi Wang (2208238)

"…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"

Model generalisation validation error analysis. حسب Hongqi Wang (2208238)

"…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"

Empirical model prediction error analysis. حسب Hongqi Wang (2208238)

"…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"

Fitting curve parameters. حسب Hongqi Wang (2208238)

"…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"