Diabetes problems can lead to an eye disease called Diabetic Retinopathy(DR),which permanently damages the blood vessels in the retina.If not treated early,DR becomes a significant reason for blindness.To identify the...Diabetes problems can lead to an eye disease called Diabetic Retinopathy(DR),which permanently damages the blood vessels in the retina.If not treated early,DR becomes a significant reason for blindness.To identify the DR and determine the stages,medical tests are very labor-intensive,expensive,and timeconsuming.To address the issue,a hybrid deep and machine learning techniquebased autonomous diagnostic system is provided in this paper.Our proposal is based on lesion segmentation of the fundus images based on the LuNet network.Then a Refined Attention Pyramid Network(RAPNet)is used for extracting global and local features.To increase the performance of the classifier,the unique features are selected from the extracted feature set using Aquila Optimizer(AO)algorithm.Finally,the LightGBM model is applied to classify the input image based on the severity.Several investigations have been done to analyze the performance of the proposed framework on three publically available datasets(MESSIDOR,APTOS,and IDRiD)using several performance metrics such as accuracy,precision,recall,and f1-score.The proposed classifier achieves 99.29%,99.35%,and 99.31%accuracy for these three datasets respectively.The outcomes of the experiments demonstrate that the suggested technique is effective for disease identification and reliable DR grading.展开更多
The construction of the first infectious clone JFH-1 speeds up the research on hepatitis C virus (HCV). However, Huh7 cell line was the only highly permissive cell line for HCV infection and only a few clones were ful...The construction of the first infectious clone JFH-1 speeds up the research on hepatitis C virus (HCV). However, Huh7 cell line was the only highly permissive cell line for HCV infection and only a few clones were fully permissive. In this study, two different fully permissive clones of Huh7 cells, Huh7.5.1 and Huh7-Lunet-CD81 (Lunet-CD81) cells were compared for their responses upon HCV infection. The virus replication level was found slightly higher in Huh7.5.1 cells than that in Lunet-CD81 cells. Viability of Huh7.5.1 cells but not of Lunet-CD81 cells was reduced significantly after HCV infection. Further analysis showed that the cell cycle of infected Huh7.5.1 cells was arrested at G1 phase. The G1/S transition was blocked by HCV infection in Huh7.5.1 cells as shown by the cell cycle synchronization analysis. Genes related to cell cycle regulation was modified by HCV infection and gene interaction analysis in GeneSpring GX in Direct Interactions mode highlighted 31 genes. In conclusion, the responses of those two cell lines were different upon HCV infection. HCV infection blocked G1/S transition and cell cycle progress, thus reduced the cell viability in Huh7.5.1 cells but not in Lunet-CD81 cells. Lunet-CD81 cells might be suitable for long term infection studies of HCV.展开更多
The operators on the n-complex unit sphere under study have three forms: the singular integrals with holomorphic kernels, the bounded and holomorphic Fourier multipliers, and the Cauchy-Dunford bounded and holomorphic...The operators on the n-complex unit sphere under study have three forms: the singular integrals with holomorphic kernels, the bounded and holomorphic Fourier multipliers, and the Cauchy-Dunford bounded and holomorphic functional calculus of the radial Dirac operator. The equivalence between the three forms and the strong-type (p, p), 1【p【∞, and weak-type (1,1)-boundedness of the operators is proved. The results generalise the work of L. K. Hua, A. Korányli and S. Vagi, W. Rudin and S. Gong on the Cauchy-Szeg(?) kernel and the Cauchy singular integral operator.展开更多
文摘Diabetes problems can lead to an eye disease called Diabetic Retinopathy(DR),which permanently damages the blood vessels in the retina.If not treated early,DR becomes a significant reason for blindness.To identify the DR and determine the stages,medical tests are very labor-intensive,expensive,and timeconsuming.To address the issue,a hybrid deep and machine learning techniquebased autonomous diagnostic system is provided in this paper.Our proposal is based on lesion segmentation of the fundus images based on the LuNet network.Then a Refined Attention Pyramid Network(RAPNet)is used for extracting global and local features.To increase the performance of the classifier,the unique features are selected from the extracted feature set using Aquila Optimizer(AO)algorithm.Finally,the LightGBM model is applied to classify the input image based on the severity.Several investigations have been done to analyze the performance of the proposed framework on three publically available datasets(MESSIDOR,APTOS,and IDRiD)using several performance metrics such as accuracy,precision,recall,and f1-score.The proposed classifier achieves 99.29%,99.35%,and 99.31%accuracy for these three datasets respectively.The outcomes of the experiments demonstrate that the suggested technique is effective for disease identification and reliable DR grading.
基金supported partly by grants of National Nature Science Foundation of China (grant 31200135)
文摘The construction of the first infectious clone JFH-1 speeds up the research on hepatitis C virus (HCV). However, Huh7 cell line was the only highly permissive cell line for HCV infection and only a few clones were fully permissive. In this study, two different fully permissive clones of Huh7 cells, Huh7.5.1 and Huh7-Lunet-CD81 (Lunet-CD81) cells were compared for their responses upon HCV infection. The virus replication level was found slightly higher in Huh7.5.1 cells than that in Lunet-CD81 cells. Viability of Huh7.5.1 cells but not of Lunet-CD81 cells was reduced significantly after HCV infection. Further analysis showed that the cell cycle of infected Huh7.5.1 cells was arrested at G1 phase. The G1/S transition was blocked by HCV infection in Huh7.5.1 cells as shown by the cell cycle synchronization analysis. Genes related to cell cycle regulation was modified by HCV infection and gene interaction analysis in GeneSpring GX in Direct Interactions mode highlighted 31 genes. In conclusion, the responses of those two cell lines were different upon HCV infection. HCV infection blocked G1/S transition and cell cycle progress, thus reduced the cell viability in Huh7.5.1 cells but not in Lunet-CD81 cells. Lunet-CD81 cells might be suitable for long term infection studies of HCV.
文摘The operators on the n-complex unit sphere under study have three forms: the singular integrals with holomorphic kernels, the bounded and holomorphic Fourier multipliers, and the Cauchy-Dunford bounded and holomorphic functional calculus of the radial Dirac operator. The equivalence between the three forms and the strong-type (p, p), 1【p【∞, and weak-type (1,1)-boundedness of the operators is proved. The results generalise the work of L. K. Hua, A. Korányli and S. Vagi, W. Rudin and S. Gong on the Cauchy-Szeg(?) kernel and the Cauchy singular integral operator.