S1 Data - by George Mrema (19550255)

“…During this period, the point prevalence of leprosy declined from 0.32 to 0.25 per 10,000 people, and the new case detection rate decreased from 3.1 to 2.4 per 100,000 people; however, these changes were not statistically significant (p > 0.05). …”

(a) Molds; (b) Samples; (c)(d) Test devices. by Chenhao Li (822769)

“…<div><p>To solve the disposal of large quantities of construction waste clay, this study proposes a new method for preparing controlled low strength materials (CLSM). …”

CoA administration prevents ISC dysfunction through antioxidative ability and protects ISCs from stress-induced DNA damage. by Zhiming Liu (216751)

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

Minimal data set. by Zhaoping Meng (4875040)

“…Over-exploitation of wild resources led to the rise of cultivation, along with a decrease in quality. Exposure of plants to adversity must generate substantial quantities of reactive oxygen species (ROS) and result in cellular damage. …”

Image 2_Delineation of single-cell Altas provides new insights for development of coronary artery lesions in Kawasaki disease: bad and good signaling molecules.tif by Qiuping Lin (3091146)

Image 3_Delineation of single-cell Altas provides new insights for development of coronary artery lesions in Kawasaki disease: bad and good signaling molecules.tif by Qiuping Lin (3091146)

Image 1_Delineation of single-cell Altas provides new insights for development of coronary artery lesions in Kawasaki disease: bad and good signaling molecules.tif by Qiuping Lin (3091146)

SlABCG9 Functioning as a Jasmonic Acid Transporter Influences Tomato Resistance to Botrytis cinerea by Ning Tao (109880)

“…Assays using Xenopus oocytes, yeast cell sensitivity, and JA-inhibited primary root growth confirmed that SlABCG9 functions as a JA influx transporter. The knockout mutant lines of <i>SlABCG9</i> showed decreased JA contents, suppressed defense gene <i>PDF1.2</i>’s expression, reduced antioxidant enzyme activity, and severe disease symptoms compared to wild-type controls. …”

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)

(a) Cement; (b) SHMP; (c) Water glass; (d) PG. by Chenhao Li (822769)

“…<div><p>To solve the disposal of large quantities of construction waste clay, this study proposes a new method for preparing controlled low strength materials (CLSM). …”

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)

“…In fully adjusted models, each 10 ng/dL increase in testosterone was associated with a 3.0% decrease in ALI (OR=0.970, 95%CI: 0.962–0.978, P < 0.001), while each 1 pg/mL increase in estradiol was associated with a 60.3% increase in ALI (OR=1.603, 95%CI: 1.318–1.949, P < 0.001). …”

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

Overall model framework. by Ke Yan (331581)

“…On the other hand, taking English writing teaching as an example, the proposed method is further verified by designing a comparative experiment in groups. 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)

“…On the other hand, taking English writing teaching as an example, the proposed method is further verified by designing a comparative experiment in groups. 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)

“…On the other hand, taking English writing teaching as an example, the proposed method is further verified by designing a comparative experiment in groups. 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)

“…On the other hand, taking English writing teaching as an example, the proposed method is further verified by designing a comparative experiment in groups. 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)

“…On the other hand, taking English writing teaching as an example, the proposed method is further verified by designing a comparative experiment in groups. 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. …”