| 1. |
- Cao, Jian, et al.
(author)
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Heterogeneous consecutive reaction kinetics of direct oxidation of H2 to H2O2: Effect and regulation of confined mass transfer
- 2023
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In: Chemical Engineering Journal. - : Elsevier. - 1385-8947 .- 1873-3212. ; 455
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Journal article (peer-reviewed)abstract
- Porous catalysts in heterogeneous reactions have played an important role in the modern chemical industry, but it is still challenging to quantitatively describe mass transfer and surface reaction behaviors of reactants in nano-confined space. Direct synthesis of hydrogen peroxide (H2O2) is considered as an attractive alternative to anthraquinone oxidation process, while the confined mass transfer of H2O2 in porous catalysts limits the reactivity. In this work, taking the consecutive reaction of H2O2 synthesis as an example, a quantitative method in modeling the effects of confined mass transfer on the reactivity was studied. More specifically, calorimetry was developed to characterize the confined structures of porous carbon experimentally, the linear nonequilibrium thermodynamics and the statistical mechanics method were further combined. Then, the heterogeneous consecutive reaction kinetics and the Thiele modulus influenced by confined mass transfer were modeled. Consequently, regulation strategies were proposed with the help of theoretical models. The optimized catalyst with biological skeleton carbon support and 0.5 wt% palladium loading shows an excellent catalytic performance. Lastly, for the mesoscience in heterogeneous reaction, the resistance was explored as a quantitative descriptor to compromise in the competition between mass transfer and surface reaction. The mesoscale structures were considered as the dynamic spatiotemporal distribution of substance concentrations, and the resistance minimization multi-scale (RMMS) model was proposed.
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| 2. |
- Kristan, Matej, et al.
(author)
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The first visual object tracking segmentation VOTS2023 challenge results
- 2023
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In: 2023 IEEE/CVF International conference on computer vision workshops (ICCVW). - : Institute of Electrical and Electronics Engineers Inc.. - 9798350307443 - 9798350307450 ; , s. 1788-1810
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Conference paper (peer-reviewed)abstract
- The Visual Object Tracking Segmentation VOTS2023 challenge is the eleventh annual tracker benchmarking activity of the VOT initiative. This challenge is the first to merge short-term and long-term as well as single-target and multiple-target tracking with segmentation masks as the only target location specification. A new dataset was created; the ground truth has been withheld to prevent overfitting. New performance measures and evaluation protocols have been created along with a new toolkit and an evaluation server. Results of the presented 47 trackers indicate that modern tracking frameworks are well-suited to deal with convergence of short-term and long-term tracking and that multiple and single target tracking can be considered a single problem. A leaderboard, with participating trackers details, the source code, the datasets, and the evaluation kit are publicly available at the challenge website1
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| 3. |
- Cao, Danyang, et al.
(author)
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Biolubricant
- 2023
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In: Sustainable Production Innovations. - : John Wiley & Sons. ; , s. 1-56
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Book chapter (other academic/artistic)
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| 4. |
- Lensink, Marc F., et al.
(author)
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Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment
- 2023
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In: Proteins. - : WILEY. - 0887-3585 .- 1097-0134.
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Journal article (peer-reviewed)abstract
- We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average similar to 70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.
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