| 1. |
- Chen, Xi, et al.
(författare)
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Affinity conjugation for rapid and covalent labeling of proteins in live cells
- 2019
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Ingår i: Proximity labeling. - New York : Humana Press. - 9781493995363 - 9781493995394 - 9781493995370 ; , s. 191-202
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Bokkapitel (refereegranskat)abstract
- Protein labeling is enormously useful for characterization of protein function in live cells and study of the related cellular processes. Covalent labeling of protein using affinity conjugation confers stable and selective labeling of protein in cells. Affinity conjugation combines a specific ligand-protein interaction with a proximity-induced reaction to selectively label the protein of interest (POI) in the cell. Therefore, either a fluorogenic probe is directly introduced to the POI or a bioorthogonal group is incorporated to the POI, which is subsequently labeled with a fluorescent probe. Here, we describe a method for affinity conjugation of protein with a fluorogenic probe and a "tagging-then-labeling" approach by a combination of affinity conjugation with bioorthogonal reactions.
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| 2. |
- Edsjö, Joakim, et al.
(författare)
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WIMP searches with AMANDA-B10
- 2001
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Ingår i: The Identification Of Dark Matter. - : World Scientific. - 9789810246020 ; , s. 499-505
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 3. |
- Lv, Zhihan, et al.
(författare)
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Advanced Human–Computer Interaction Technology in Digital Twins
- 2023
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Ingår i: Studies in Computational Intelligence. - 1860-949X .- 1860-9503. ; , s. 99-123
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Bokkapitel (refereegranskat)abstract
- To explore the application of Human–Computer Interaction (HCI) in industrial Digital Twins (DTs), the current application status of DTs in Intelligent Manufacturing (IM) and the HCI problem in human–computer assembly are explored; aiming at the Human Action Recognition (HAR) of machine perspective in human–computer assembly, it proposes the Human Pose Estimation (HPE) method based on improved HRNet and inroduces the attention mechanism to establish the SE_NewHRNet model for the optimization of HPE; in addition, it points out Adaptive Architecture of Deep Learning Based on Confrontation (ADLC), and performs case analysis for the performance verification of the model. The accuracy of SE_NewHRNet in $$\mathrm{A}{P}:{pose}$$ indicator is 75.1%. Compared with other models, its network performance is improved to different extents, the number of parameters and calculation amount are lower, the Loss value decreases rapidly, and the decrease rate becomes slower after 40 iterations. In ADLC, the recognition accuracy of the branch model with three domain discrimination is the highest, reaching 86.50%; in most cases, ADLC performance is better in contrast to other models. Compared with the Wasserstein Generative Adversarial Networks (WGAN) model with the second comprehensive performance, the average accuracy of ADLC is 69.72, 9.24% higher than that of WGAN, and 27.67% higher than that of Source-only. Therefore, the proposed human recognition method performs better.
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| 4. |
- Lv, Zhihan, et al.
(författare)
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Distributed computing to blockchain: Architecture, technology, and applications
- 2023
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Ingår i: Distributed Computing to Blockchain: Architecture, Technology, and Applications. - 9780323961462 ; , s. 39-54
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Bokkapitel (refereegranskat)abstract
- This chapter aims to explore the correlation between distributed computing and blockchain technology and deeply investigate the architecture and application of blockchain technology. Mobile devices are taken as the research object, and blockchain technology is used to provide a distributed computing model for mobile terminals in the wireless communication scenario. Besides, deep learning is employed to classify tasks and enhance the analysis efficiency of multisource data. Finally, a distributed deep learning network model based on blockchain technology is constructed. In addition, the performance of the model is verified by simulation experiments. The experimental results demonstrate that through the comparative analysis of system performance, the computational overhead of the model constructed here is the lowest, maintained at about 0.12s, and the comprehensive income and system operation efficiency are the highest. In terms of the security performance of data transmission, the average delay of the distributed framework reported here is stable at about 250ms, and the identification accuracy of transmitted data reaches 92.40%. Therefore, the distributed deep learning model proposed here realizes splendid recognition accuracy, comprehensive income, and system operation efficiency and shows excellent system performance, which can provide a reference for the improvement of blockchain technology application in future.
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| 5. |
- Ren, Sa, et al.
(författare)
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Phaseoleae
- 2010
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Ingår i: Flora of China. - Beijing : Science Press. - 9781930723917 ; , s. 196-261
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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