Predicted chronic activation of the cardiomyocyte signaling network during VO. by Johane H. Bracamonte (12883844)

Overall model framework. by Ke Yan (331581)

“…The results show that: (1) From the experimental data of word sense disambiguation, the accuracy of the SMOSS-LSTM model proposed in this paper is the lowest when the context range is "3+3", then it rises in turn at "5+5" and "7+7", reaches the highest at "7+7", and then begins to decrease at "10+10"; (2) Compared with the control group, the accuracy of syntactic analysis in the experimental group reached 89.5%, while that in the control group was only 73.2%. (3) In the aspect of English text error detection, the detection accuracy of the proposed model in the experimental group is as high as 94.8%, which is significantly better than the traditional SMOSS-based text error detection method, and its accuracy is only 68.3%. (4) Compared with other existing researches, although it is slightly inferior to Bidirectional Encoder Representations from Transformers (BERT) in word sense disambiguation, this proposed model performs well in syntactic analysis and English text error detection, and its comprehensive performance is excellent. …”

Key parameters of LSTM training model. by Ke Yan (331581)

“…The results show that: (1) From the experimental data of word sense disambiguation, the accuracy of the SMOSS-LSTM model proposed in this paper is the lowest when the context range is "3+3", then it rises in turn at "5+5" and "7+7", reaches the highest at "7+7", and then begins to decrease at "10+10"; (2) Compared with the control group, the accuracy of syntactic analysis in the experimental group reached 89.5%, while that in the control group was only 73.2%. (3) In the aspect of English text error detection, the detection accuracy of the proposed model in the experimental group is as high as 94.8%, which is significantly better than the traditional SMOSS-based text error detection method, and its accuracy is only 68.3%. (4) Compared with other existing researches, although it is slightly inferior to Bidirectional Encoder Representations from Transformers (BERT) in word sense disambiguation, this proposed model performs well in syntactic analysis and English text error detection, and its comprehensive performance is excellent. …”

Comparison chart of model evaluation results. by Ke Yan (331581)

“…The results show that: (1) From the experimental data of word sense disambiguation, the accuracy of the SMOSS-LSTM model proposed in this paper is the lowest when the context range is "3+3", then it rises in turn at "5+5" and "7+7", reaches the highest at "7+7", and then begins to decrease at "10+10"; (2) Compared with the control group, the accuracy of syntactic analysis in the experimental group reached 89.5%, while that in the control group was only 73.2%. (3) In the aspect of English text error detection, the detection accuracy of the proposed model in the experimental group is as high as 94.8%, which is significantly better than the traditional SMOSS-based text error detection method, and its accuracy is only 68.3%. (4) Compared with other existing researches, although it is slightly inferior to Bidirectional Encoder Representations from Transformers (BERT) in word sense disambiguation, this proposed model performs well in syntactic analysis and English text error detection, and its comprehensive performance is excellent. …”

Model performance evaluation results. by Ke Yan (331581)

“…The results show that: (1) From the experimental data of word sense disambiguation, the accuracy of the SMOSS-LSTM model proposed in this paper is the lowest when the context range is "3+3", then it rises in turn at "5+5" and "7+7", reaches the highest at "7+7", and then begins to decrease at "10+10"; (2) Compared with the control group, the accuracy of syntactic analysis in the experimental group reached 89.5%, while that in the control group was only 73.2%. (3) In the aspect of English text error detection, the detection accuracy of the proposed model in the experimental group is as high as 94.8%, which is significantly better than the traditional SMOSS-based text error detection method, and its accuracy is only 68.3%. (4) Compared with other existing researches, although it is slightly inferior to Bidirectional Encoder Representations from Transformers (BERT) in word sense disambiguation, this proposed model performs well in syntactic analysis and English text error detection, and its comprehensive performance is excellent. …”

The result compared with other existing methods. by Ke Yan (331581)

“…The results show that: (1) From the experimental data of word sense disambiguation, the accuracy of the SMOSS-LSTM model proposed in this paper is the lowest when the context range is "3+3", then it rises in turn at "5+5" and "7+7", reaches the highest at "7+7", and then begins to decrease at "10+10"; (2) Compared with the control group, the accuracy of syntactic analysis in the experimental group reached 89.5%, while that in the control group was only 73.2%. (3) In the aspect of English text error detection, the detection accuracy of the proposed model in the experimental group is as high as 94.8%, which is significantly better than the traditional SMOSS-based text error detection method, and its accuracy is only 68.3%. (4) Compared with other existing researches, although it is slightly inferior to Bidirectional Encoder Representations from Transformers (BERT) in word sense disambiguation, this proposed model performs well in syntactic analysis and English text error detection, and its comprehensive performance is excellent. …”

Results of MC simulations of VO and agonist infusion. by Johane H. Bracamonte (12883844)

Effects of receptor blockers on VO-induced hypertrophy in published experiments and the calibrated model. by Johane H. Bracamonte (12883844)

Ingenuity pathway analysis of tonic ISG subclasses. by Tyron Chang (9922533)

qPCR of vaccinia virus RNAs <i>IRF1</i> KO cells: glucose with and without IFN-γ priming. by Tyron Chang (9922533)

Analysis of host and interferon-induced responses in glucose/galactose infected with vaccinia virus. by Tyron Chang (9922533)

Glucose/galactose with extended interferon-priming does not impact levels of ISG RNAs or non-ISG proteins levels. by Tyron Chang (9922533)

Time course of IRF1 and IFITM3 RNA and protein expression across conditions. by Tyron Chang (9922533)

Vaccinia virus and VSV infections of <i>STAT1</i> and <i>IRF1</i> KO cells grown in glucose/galactose with and without IFN-γ priming. by Tyron Chang (9922533)

Vaccinia virus infection (MOI = 3) of A549 cells in media supplemented with glucose/galactose. by Tyron Chang (9922533)

Glucose/galactose regulation of IFN-γ induced IRF1 protein is conserved in mammals. by Tyron Chang (9922533)

Characterization of the impact of glucose/galactose on infection outcomes. by Tyron Chang (9922533)

Glucose/galactose selectively alters ISG protein not RNA levels in interferon-primed cells. by Tyron Chang (9922533)

Glucose but not galactose culturing of IFN-γ primed cells reduces VACV and HSV-1 replication. by Tyron Chang (9922533)

<i>IRF1</i> impacts VACV replication in glucose/IFN-γ primed but not galactose conditions. by Tyron Chang (9922533)