12,997 research outputs found
MC-YOLOv5s training results.
No full textReal-time and accurate detection of ships plays a vital role in ensuring navigation safety and ship supervision. Aiming at the problems of large parameters, large computation quantity, poor real-time performance, and high requirements for memory and computing power of the current ship detection model, this paper proposes a ship target detection algorithm MC-YOLOv5s based on YOLOv5s. First, the MobileNetV3-Small lightweight network is used to replace the original feature extraction backbone network of YOLOv5s to improve the detection speed of the algorithm. And then, a more efficient CNeB is designed based on the ConvNeXt-Block module of the ConvNeXt network to replace the original feature fusion module of YOLOv5s, which improves the spatial interaction ability of feature information and further reduces the complexity of the model. The experimental results obtained from the training and verification of the MC-YOLOv5s algorithm show that, compared with the original YOLOv5s algorithm, MC-YOLOv5s reduces the number of parameters by 6.98 MB and increases the mAP by about 3.4%. Even compared with other lightweight detection models, the improved model proposed in this paper still has better detection performance. The MC-YOLOv5s has been verified in the ship visual inspection and has great application potential. The code and models are publicly available at https://github.com/sakura994479727/datas.</div
MC-YOLOv5s network structure.
No full textReal-time and accurate detection of ships plays a vital role in ensuring navigation safety and ship supervision. Aiming at the problems of large parameters, large computation quantity, poor real-time performance, and high requirements for memory and computing power of the current ship detection model, this paper proposes a ship target detection algorithm MC-YOLOv5s based on YOLOv5s. First, the MobileNetV3-Small lightweight network is used to replace the original feature extraction backbone network of YOLOv5s to improve the detection speed of the algorithm. And then, a more efficient CNeB is designed based on the ConvNeXt-Block module of the ConvNeXt network to replace the original feature fusion module of YOLOv5s, which improves the spatial interaction ability of feature information and further reduces the complexity of the model. The experimental results obtained from the training and verification of the MC-YOLOv5s algorithm show that, compared with the original YOLOv5s algorithm, MC-YOLOv5s reduces the number of parameters by 6.98 MB and increases the mAP by about 3.4%. Even compared with other lightweight detection models, the improved model proposed in this paper still has better detection performance. The MC-YOLOv5s has been verified in the ship visual inspection and has great application potential. The code and models are publicly available at https://github.com/sakura994479727/datas.</div
Inhibition of prostaglandin E2 production of a macrophage cell line by some phytochemicals.
No full textThe Abnormal Proliferation of Hepatocytes is Associated with MC-LR and C-Terminal Truncated HBX Synergistic Disturbance of the Redox Balance
No full textDong-Mei Cai,1,* Fan-Biao Mei,1,* Chao-Jun Zhang,1 San-Chun An,1 Rui-Bo Lv,1 Guan-Hua Ren,1 Chan-Chan Xiao,1 Long Long,1,2 Tian-Ren Huang,1,2 Wei Deng1,2 1Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, 530021, People’s Republic of China; 2Guangxi Cancer Molecular Medicine Engineering Research Center, Nanning, Guangxi, 530021, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wei Deng; Tianren Huang, Department of Experimental Research, Guangxi Medical University Cancer Hospital, No. 71, Hedi Road, Nanning, Guangxi, 530021, People’s Republic of China, Email [email protected]; [email protected]: Microcystin-LR (MC-LR) and hepatitis B virus (HBV) are associated with hepatocellular carcinoma (HCC). However, the concentrations of MC-LR in drinking water and the synergistic effect of MC-LR and HBV on hepatocellular carcinogenesis through their disturbance of redox balance have not been fully elucidated.Methods: We measured the MC-LR concentrations in 168 drinking water samples of areas with a high incidence of HCC. The relationships between MC-LR and both redox status and liver diseases in 177 local residents were analyzed. The hepatoma cell line HepG2 transfected with C-terminal truncated hepatitis B virus X gene (Ct-HBX) were treated with MC-LR. Reactive oxygen species (ROS), superoxide dismutase (SOD), glutathione (GSH) and malondialdehyde (MDA) were measured. Cell proliferation, migration, invasion, and apoptosis were assessed with cell activity assays, scratch and transwell assays, and flow cytometry, respectively. The mRNA and protein expression-related redox status genes were analyzed with qPCR and Western blotting.Results: The average concentration of MC-LR in well water, river water and reservoir water were 57.55 ng/L, 76.74 ng/L and 132.86 ng/L respectively, and the differences were statistically significant (P < 0.05). The MC-LR levels in drinking water were correlated with liver health status, including hepatitis, clonorchiasis, glutamic pyruvic transaminase abnormalities and hepatitis B surface antigen carriage (all P values < 0.05). The serum MDA increased in subjects who drank reservoir water and were infected with HBV (P < 0.05). In the cell experiment, ROS increased when Ct-HBX-transfected HepG2 cells were treated with MC-LR, followed by a decrease in SOD and GSH and an increase in MDA. MC-LR combined with Ct-HBX promoted the proliferation, migration and invasion of HepG2 cells, upregulated the mRNA and protein expression of MAOA gene, and downregulated UCP2 and GPX1 genes.Conclusion: MC-LR and HBV may synergistically affect redox status and play an important role in hepatocarcinoma genesis.Keywords: hepatocellular carcinoma, microcystins-LR, hepatitis B virus X gene, redox balanc
Examples of mapping of MC to their representative AlphaFold structure.
No full textThe part of the sequence of the AlphaFold protein that aligns to the MC profile-HMM is shown in orange. Above each example we report the ID of the AlphaFold structure, the MC number, the Pfam family that was build from the MC (if any) and the position of the MC in the list of largest unknown MCs (S3 Table). Molecular graphics and analyses performed with UCSF Chimera (Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE. “UCSF Chimera–a visualization system for exploratory research and analysis.” J Comput Chem. 25 (2004):1605–12). (TIF)</p
Examples of mapping of MC to their representative AlphaFold structure.
No full textThe part of the sequence of the AlphaFold protein that aligns to the MC profile-HMM is shown in orange. Above each example we report the ID of the AlphaFold structure, the MC number, the Pfam family that was build from the MC (if any) and the position of the MC in the list of largest unknown MCs (S3 Table). Molecular graphics and analyses performed with UCSF Chimera (Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE. “UCSF Chimera–a visualization system for exploratory research and analysis.” J Comput Chem. 25 (2004):1605–12). (TIF)</p
Interactively using Semantic Web knowledge: Creating scalable abstractions with FacetOntology
No full textThe amount of knowledge accessible on the Semantic Web is growing, and there is a need for a scalable solution to facilitate exploring that data. Currently approaches to exploring Semantic Web data either focus on exploring resources individually, following links during exploration, and making little use of collated data, or take the approach of collating and aligning multiple sources into one store for one purpose, and hand-crafting a specific browsing interface onto it. We present an approach that provides a scalable browsing interface, which can browse knowledge from the Semantic Web at will. Our approach creates abstractions of knowledge, collated into facets, which are described using FacetOntology. FacetOntology facilitates describing facets from RDF data, suitable for use in creating datasets for faceted browsing
Examples of mapping of MC to their representative AlphaFold structure.
No full textThe part of the sequence of the AlphaFold protein that aligns to the MC profile-HMM is shown in orange. Above each example we report the ID of the AlphaFold structure, the MC number, the Pfam family that was build from the MC (if any) and the position of the MC in the list of largest unknown MCs (S3 Table). Molecular graphics and analyses performed with UCSF Chimera (Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE. “UCSF Chimera–a visualization system for exploratory research and analysis.” J Comput Chem. 25 (2004):1605–12). (TIF)</p
Examples of mapping of MC to their representative AlphaFold structure.
No full textThe part of the sequence of the AlphaFold protein that aligns to the MC profile-HMM is shown in orange. Above each example we report the ID of the AlphaFold structure, the MC number, the Pfam family that was build from the MC (if any) and the position of the MC in the list of largest unknown MCs (S3 Table). Molecular graphics and analyses performed with UCSF Chimera (Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE. “UCSF Chimera–a visualization system for exploratory research and analysis.” J Comput Chem. 25 (2004):1605–12). (TIF)</p
Health-Related Quality of Life and Medical Cost of Early-Stages Breast Cancer.Patients underwent Breast-Conserving Surgery versus Modified Radical Mastectomy.
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