Down-regulation of VANGL2 in IBD patients triggers overt activation of NLRP3 inflammasome. حسب Huaji Jiang (16907514)

Lys823 in NLRP3 is essential for its K27-linked ubiquitination and autophagic degradation. حسب Huaji Jiang (16907514)

VANGL2 specifically inhibits the activation of NLRP3 inflammasome. حسب Huaji Jiang (16907514)

VANGL2 recruits NLRP3 to OPTN for selective autophagic degradation. حسب Huaji Jiang (16907514)

VANGL2 recruits MARCH8 to promote the K27-linked ubiquitination of NLRP3. حسب Huaji Jiang (16907514)

Complexity comparison of different models. حسب Li Yuan (102305)

"…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …"

Dynamic window based median filtering algorithm. حسب Li Yuan (102305)

"…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …"

Flow of operation of improved KMA. حسب Li Yuan (102305)

"…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …"

Improved DAE based on LSTM. حسب Li Yuan (102305)

"…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …"

Autoencoder structure. حسب Li Yuan (102305)

"…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …"

Podocyte numbers in control and iPLA₂γ KO mice (WT1-positive cells). حسب Andrey V. Cybulsky (4007012)

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

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

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. …"