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Optimal and pressure-independent L2 velocity error estimates for a modified Crouzeix-Raviart Stokes element with BDM reconstructions
Nearly all inf-sup stable mixed finite elements for the incompressible
Stokes equations relax the divergence constraint. The price to pay is that a
priori estimates for the velocity error become pressure-dependent, while
divergence-free mixed finite elements deliver pressure-independent estimates.
A recently introduced new variational crime using lowest-order Raviart-Thomas
velocity reconstructions delivers a much more robust modified
Crouzeix-Raviart element, obeying an optimal pressure-independent discrete H1
velocity estimate. Refining this approach, a more sophisticated variational
crime employing the lowest-order BDM element is proposed, which also allows
proving an optimal pressure-independent L2 velocity error. Numerical examples
confirm the analysis and demonstrate the improved robustness in the
Navier-Stokes case
Operator Norm Bounds on the Correlation Matrix of the SK Model at High Temperature
We prove that the two point correlation matrix of
the Sherrington-Kirkpatrick model has the property that for every
there exists , that is independent of , such that
for large enough, for suitable interaction and external
field parameters in the replica symmetric region. In other words,
the operator norm of is of order one with high probability. Our
results are in particular valid for all
and thus complement recently obtained results in \cite{EAG,BSXY} that imply the
operator norm boundedness of for all in the special case
of vanishing external field.Comment: 33 page
Optimal Rate for Bose-Einstein Condensation in the Gross-Pitaevskii Regime
We consider systems of bosons trapped in a box, in the Gross-Pitaevskii
regime. We show that low-energy states exhibit complete Bose-Einstein
condensation with an optimal bound on the number of orthogonal excitations.
This extends recent results obtained in \cite{BBCS1}, removing the assumption
of small interaction potential.Comment: 99 pages, typos correcte
Gene expression profiling in whole blood of patients with coronary artery disease
Owing to the dynamic nature of the transcriptome, gene expression profiling is a promising tool for discovery of disease-related genes and biological pathways. In the present study, we examined gene expression in whole blood of 12 patients with CAD (coronary artery disease) and 12 healthy control subjects. Furthermore, ten patients with CAD underwent whole-blood gene expression analysis before and after the completion of a cardiac rehabilitation programme following surgical coronary revascularization. mRNA and miRNA (microRNA) were isolated for expression profiling. Gene expression analysis identified 365 differentially expressed genes in patients with CAD compared with healthy controls (175 up- and 190 down-regulated in CAD), and 645 in CAD rehabilitation patients (196 up- and 449 down-regulated post-rehabilitation). Biological pathway analysis identified a number of canonical pathways, including oxidative phosphorylation and mitochondrial function, as being significantly and consistently modulated across the groups. Analysis of miRNA expression revealed a number of differentially expressed miRNAs, including hsa-miR-140-3p (control compared with CAD, P=0.017), hsa-miR-182 (control compared with CAD, P=0.093), hsa-miR-92a and hsa-miR-92b (post- compared with pre-exercise, P<0.01). Global analysis of predicted miRNA targets found significantly reduced expression of genes with target regions compared with those without: hsa-miR-140-3p (P=0.002), hsa-miR-182 (P=0.001), hsa-miR-92a and hsa-miR-92b (P=2.2Ă10â16). In conclusion, using whole blood as a âsurrogate tissueâ in patients with CAD, we have identified differentially expressed miRNAs, differentially regulated genes and modulated pathways which warrant further investigation in the setting of cardiovascular function. This approach may represent a novel non-invasive strategy to unravel potentially modifiable pathways and possible therapeutic targets in cardiovascular disease
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