10,018 research outputs found
Dimensional crossover of thermal conductance in graphene nanoribbons: A first-principles approach
First-principles density-functional calculations are performed to investigate
the thermal transport properties in graphene nanoribbons (GNRs). The
dimensional crossover of thermal conductance from one to two dimensions (2D) is
clearly demonstrated with increasing ribbon width. The thermal conductance of
GNRs in a few nanometer width already exhibits an approximate low-temperature
dependence of , like that of 2D graphene sheet which is attributed to
the quadratic nature of dispersion relation for the out-of-plane acoustic
phonon modes. Using a zone-folding method, we heuristically derive the
dimensional crossover of thermal conductance with the increase of ribbon width.
Combining our calculations with the experimental phonon mean-free path, some
typical values of thermal conductivity at room temperature are estimated for
GNRs and for 2D graphene sheet, respectively. Our findings clarify the issue of
low-temperature dependence of thermal transport in GNRs and suggest a
calibration range of thermal conductivity for experimental measurements in
graphene-based materials.Comment: 18 pages, 4 figure
Multi-stage learning for segmentation of aortic dissections using a prior aortic anatomy simplification
Aortic dissection (AD) is a life-threatening cardiovascular disease with a high mortality rate. The accurate and generalized 3-D reconstruction of AD from CT-angiography can effectively assist clinical procedures and surgery plans, however, is clinically unavaliable due to the lacking of efficient tools. In this study, we presented a novel multi-stage segmentation framework for type B AD to extract true lumen (TL), false lumen (FL) and all branches (BR) as different classes. Two cascaded neural networks were used to segment the aortic trunk and branches and to separate the dual lumen, respectively. An aortic straightening method was designed based on the prior vascular anatomy of AD, simplifying the curved aortic shape before the second network. The straightening-based method achieved the mean Dice scores of 0.96, 0.95 and 0.89 for TL, FL, and BR on a multi-center dataset involving 120 patients, outperforming the end-to-end multi-class methods and the multi-stage methods without straightening on the dual-lumen segmentation, even using different network architectures. Both the global volumetric features of the aorta and the local characteristics of the primary tear could be better identified and quantified based on the straightening. Comparing to previous deep learning methods dealing with AD segmentations, the proposed framework presented advantages in segmentation accuracy
Obvious enhancement of the total reaction cross sections for P with Si target and the possible relavent mechanisms
The reaction cross sections of P and the corresponding isotones on
Si target were measured at intermediate energies. The measured reaction cross
sections of the N=12 and 13 isotones show an abrupt increase at . The
experimental results for the isotones with as well as P can
be well described by the modified Glauber theory of the optical limit approach.
The enhancement of the reaction cross section for P could be explained
in the modified Glauber theory with an enlarged core. Theoretical analysis with
the modified Glauber theory of the optical limit and few-body approaches
underpredicted the experimental data of P. Our theoretical analysis
shows that an enlarged core together with proton halo are probably the
mechanism responsible for the enhancement of the cross sections for the
reaction of P+Si.Comment: 16 pages, 5 figures, to be published in Phys.Rev.
Upregulated sirtuin 1 by miRNA-34a is required for smooth muscle cell differentiation from pluripotent stem cells
© 2015 Macmillan Publishers Limited. All rights reserved. microRNA-34a (miR-34a) and sirtuin 1 (SirT1) have been extensively studied in tumour biology and longevityaging, but little is known about their functional roles in smooth muscle cell (SMC) differentiation from pluripotent stem cells. Using well-established SMC differentiation models, we have demonstrated that miR-34a has an important role in SMC differentiation from murine and human embryonic stem cells. Surprisingly, deacetylase sirtuin 1 (SirT1), one of the top predicted targets, was positively regulated by miR-34a during SMC differentiation. Mechanistically, we demonstrated that miR-34a promoted differentiating stem cells' arrest at G0G1 phase and observed a significantly decreased incorporation of miR-34a and SirT1 RNA into Ago2-RISC complex upon SMC differentiation. Importantly, we have identified SirT1 as a transcriptional activator in the regulation of SMC gene programme. Finally, our data showed that SirT1 modulated the enrichment of H3K9 tri-methylation around the SMC gene-promoter regions. Taken together, our data reveal a specific regulatory pathway that miR-34a positively regulates its target gene SirT1 in a cellular context-dependent and sequence-specific manner and suggest a functional role for this pathway in SMC differentiation from stem cells in vitro and in vivo
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