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- Kristanl, Matej, et al.
(författare)
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The Seventh Visual Object Tracking VOT2019 Challenge Results
- 2019
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Ingår i: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE COMPUTER SOC. - 9781728150239 ; , s. 2206-2241
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website(1).
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- Chen, Song, et al.
(författare)
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Early osteoimmunomodulation by mucin hydrogels augments the healing and revascularization of rat critical-size calvarial bone defects
- 2023
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Ingår i: BIOACTIVE MATERIALS. - : Elsevier BV. - 2452-199X. ; 25, s. 176-188
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Tidskriftsartikel (refereegranskat)abstract
- The design principle of osteogenic bone grafts has shifted from immunological inertness to limiting foreign body response to combined osteoimmunomodulatory activity to promote high-quality endogenous bone regeneration. Recently developed immunomodulatory mucin hydrogels have been shown to elicit very low complement activation and suppress macrophage release and activation after implantation in vivo. However, their immunoregulatory activity has not yet been studied in the context of tissue repair. Herein, we synthesized mucinmonetite composite materials and investigated their early osteoimmunomodulation using a critical-size rat bone defect model. We demonstrated that the composites can polarize macrophages towards the M2 phenotype at weeks 1 and 2. The early osteoimmunomodulation enhanced early osteogenesis and angiogenesis and ultimately promoted fracture healing and engraftment (revascularization of the host vasculature) at weeks 6 and 12. Overall, we demonstrated the applicability of mucin-based immunomodulatory biomaterials to enhance tissue repair in tissue engineering and regenerative medicine.
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- Cheng, Jie, et al.
(författare)
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Interactions in Composite Film Formation of Mefp-1/graphene on Carbon Steel
- 2021
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Ingår i: Coatings. - : MDPI AG. - 2079-6412. ; 11:10
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Tidskriftsartikel (refereegranskat)abstract
- Mefp-1 adhesive protein derived from marine blue mussels, together with the 2D material graphene, was used to build the green composite film with enhanced anti-corrosion property and mechanical strength. The corrosion inhibition of the composite film, formed by different methods, was evaluated by using electrochemical impedance spectroscopy. The non-degraded adhesion of the composite film to the carbon steel substrate was proved by nano-scratch tests. Infrared spectroscopy was utilized to investigate the film formation process and "three-body interactions " between Mefp-1, graphene and carbon steel surface. The results show that the Mefp-1 adsorbs on the carbon steel surface mainly through the covalent bond between catechols and Fe(III). Meanwhile, Mefp-1 can bond to non-adhesive graphene by forming hydrogen bonds and pi-pi interaction non-covalent bonds, which facilitate the formation of a robust Mefp-1/graphene composite film on the carbon steel surface.
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- Gu, Qiang, et al.
(författare)
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VKORC1-1639G>A, CYP2C9, EPHX1691A>G genotype, body weight, and age are important predictors for warfarin maintenance doses in patients with mechanical heart valve prostheses in southwest China
- 2010
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Ingår i: European Journal of Clinical Pharmacology. - : Springer Science and Business Media LLC. - 0031-6970 .- 1432-1041. ; 66:12, s. 1217-1227
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Tidskriftsartikel (refereegranskat)abstract
- There were great interindividual differences in warfarin maintenance dosage (ranging from 0.6 to 8.4 mg/day) among the 127 patients with mechanical heart valve prostheses. VKORC1-1639G>A, CYP2C9, EPHX1691A>G polymorphism, body weight, and age were found to affect the dose demands. Multiple linear regression models incorporating genetic polymorphisms of VKORC1, CYP2C9, EPHX1691A>G, and the nongenetic factors of age and body weight were developed, and explained up to 76.8% of the total variation (adjusted R (2) of 0.743) in warfarin maintenance doses in southwest Chinese patients with mechanical heart valve prostheses.
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- Huang, He, et al.
(författare)
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Material informatics for uranium-bearing equiatomic disordered solid solution alloys
- 2021
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Ingår i: Materials Today Communications. - : Elsevier BV. - 2352-4928. ; 29
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Tidskriftsartikel (refereegranskat)abstract
- Near-equiatomic, multi-component alloys with disordered solid solution phase (DSSP) are associated with outstanding performance in phase stability, mechanical properties and irradiation resistance, and may provide a feasible solution for developing novel uranium-based alloys with better fuel capacity. In this work, we build a machine learning (ML) model of disordered solid solution alloys (DSSAs) based on about 6000 known multicomponent alloys and several materials descriptors to efficiently predict the DSSAs formation ability. To fully optimize the ML model, we develop a multi-algorithm cross-verification approach in combination with the SHapley Additive exPlanations value (SHAP value). We find that the Delta S-C, Lambda, Phi(s), gamma and 1/Omega, corresponding to the former two Hume - Rothery (H - R) rules, are the most important materials descriptors affecting DSSAs formation ability. When the ML model is applied to the 375 uranium-bearing DSSAs, 190 of them are predicted to be the DSSAs never known before. 20 of these alloys were randomly synthesized and characterized. Our predictions are in-line with experiments with 3 inconsistent cases, suggesting that our strategy offers a fast and accurate way to predict novel multi-component alloys with high DSSAs formation ability. These findings shed considerable light on the mapping between the material descriptors and DSSAs formation ability.
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