Chemical structure of a lignan. by Zhaoping Meng (4875040)

“…The combination of exogenous NO with high-temperature enhances secondary metabolism of <i>Schisandra chinensis</i> fruit, which opens new avenues for production of high-quality Schisandra chinensis fructus.…”

Table 1_Association of brain-derived neurotrophic factor levels at different trimesters and new-onset depressive symptom in the third trimester among pregnant women: a longitudinal... by Yue-rong Zhang (21838784)

Heatmap comparison of the highest fractional inhibitory concentration index (FICI) values and fold change (FC) reductions in colistin MIC across all tested bacterial strains. by Marian Klose (22190299)

Different agronomic traits associated with pod dehiscence. by JaeBuhm Chun (20958047)

Knockdown of <i>fhplk1</i> disrupts growth and cell proliferation in juvenile <i>Fasciola hepatica in vitro.</i> by Paul McCusker (634425)

Boxplots of food security metrics by income equivalence indices. by Daniel Fobi (13607663)

Boxplots of food-security metrics by household asset categories. by Daniel Fobi (13607663)

Fig 2 - by Nathalie Lavenne-Collot (11262998)

Primers for qPCR. by Xiaoyi Shi (3825754)

“…These results established a new paradigm in melatonin-mediated hepatocyte protection under the burden of I/R attack.…”

S1 Raw data - by Xiaoyi Shi (3825754)

“…These results established a new paradigm in melatonin-mediated hepatocyte protection under the burden of I/R attack.…”

The chemical structure of melatonin. by Xiaoyi Shi (3825754)

“…These results established a new paradigm in melatonin-mediated hepatocyte protection under the burden of I/R attack.…”

MO-SAM segmentation performance using the Grid method in the forested landscape. by Qitong Wang (15279695)

Flow chart of research object screening. by Wenyao Xie (21567889)

“…These findings suggest cancer may fundamentally alter sex hormone-inflammation relationships, providing new insights into hormone-mediated inflammatory regulation in health and disease.…”

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. …”

Effects of the presence of stabilimentum concerning prey vibration acting in the direction tangent to the spiral threads. by G. Greco (7636232)

Sequence composition analysis identifies distinct A + U and C + G base frequencies within subregions of mRNA transcripts – with effects on protein coding potential. by Benjamin S. Pickard (21276556)