Actions of the main intrinsic laryngeal muscles and the laryngeal abnormalities in Parkinson’s disease. حسب Andrew Ma (4532494)

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The laryngeal measures. حسب Andrew Ma (4532494)

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Change in laryngeal measures with disease duration and UPDRS part III scores. حسب Andrew Ma (4532494)

الموضوعات:

Comparison of the laryngeal measures during vocalization between pwPD and controls. حسب Andrew Ma (4532494)

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Demographic details. حسب Andrew Ma (4532494)

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Table_1_Decreased Serum Brain-Derived Neurotrophic Factor Concentrations 72 Hours Following Marathon Running.DOCX حسب Astrid Roeh (11136600)

"…</p><p>Conclusion: Prolonged exercise induces a significant decrease in serum BDNF concentration 72 h post-exercise. …"

Fig 4 - حسب Thiago Bezerra Wanderley e Lima (14232350)

Fig 5 - حسب Thiago Bezerra Wanderley e Lima (14232350)

Fig 7 - حسب Thiago Bezerra Wanderley e Lima (14232350)

Fig 6 - حسب Thiago Bezerra Wanderley e Lima (14232350)

DataSheet_1_Decrease in Serum Urate Level Is Associated With Loss of Visceral Fat in Male Gout Patients.docx حسب Zijing Ran (11429935)

"…By multiple regression model, ΔSU was identified to be a significant determinant variable of decrease in VFA (beta, 0.302; p = 0.001).…"

Transcriptomic analysis of the long-lived and short-lived Atg1 over-expressing flies reveals decreased lipid metabolism. حسب Ivana Bjedov (75652)

nsP4-C483Y or Q192L mutations decrease sensitivity to 4′-FlU. حسب Peiqi Yin (6533747)

Response to NLC for 1 122 native plant species with significant null models. حسب Kaixuan Pan (11714457)

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

"…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. 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)

"…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. 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)

"…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. 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)

"…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. 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)

"…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. 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)

"…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. 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. …"