864 research outputs found
Single wall carbon nanotube double quantum dot
We report on two top-gate defined, coupled quantum dots in a semiconducting
single wall carbon nanotube, constituting a tunable double quantum dot system.
The single wall carbon nanotubes are contacted by titanium electrodes, and
gated by three narrow top-gate electrodes as well as a back-gate. We show that
a bias spectroscopy plot on just one of the two quantum dots can be used to
extract the addition energy of both quantum dots. Furthermore, honeycomb charge
stability diagrams are analyzed by an electrostatic capacitor model that
includes cross capacitances, and we extract the coupling energy of the double
quantum dot.Comment: Published in Applied Physics Letters 4 December 2006.
http://link.aip.org/link/?APL/89/23211
Revealing the correlation between real-space structure and chiral magnetic order at the atomic scale
We image simultaneously the geometric, electronic and magnetic structure of a
buckled iron bilayer film that exhibits chiral magnetic order. We achieve this
by combining spin-polarized scanning tunneling microscopy and magnetic exchange
force microscopy (SPEX), to independently characterize the geometric as well as
the electronic and magnetic structure of non-flat surfaces. This new SPEX
imaging technique reveals the geometric height corrugation of the
reconstruction lines resulting from strong strain relaxation in the bilayer,
enabling the decomposition of the real-space from the eletronic structure at
the atomic level, and the correlation with the resultant spin spiral ground
state. By additionally utilizing adatom manipulation, we reveal the chiral
magnetic ground state of portions of the unit cell that were not previously
imaged with SP-STM alone. Using density functional theory (DFT), we investigate
the structural and electronic properties of the reconstructed bilayer and
identify the favorable stoichiometry regime in agreement with our experimental
result
A Systematic Development of Solid-Shell Element Formulations for Linear and Nonlinear Analyses Employing Only Displacement Degrees of Freedom
Glucose-Insulin-Potassium Therapy Guided by a Glucose-Controlled Insulin Infusion System in Acute Myocardinal Infarction
Unsupervised denoising for sparse multi-spectral computed tomography
Multi-energy computed tomography (CT) with photon counting detectors (PCDs)
enables spectral imaging as PCDs can assign the incoming photons to specific
energy channels. However, PCDs with many spectral channels drastically increase
the computational complexity of the CT reconstruction, and bespoke
reconstruction algorithms need fine-tuning to varying noise statistics.
\rev{Especially if many projections are taken, a large amount of data has to be
collected and stored. Sparse view CT is one solution for data reduction.
However, these issues are especially exacerbated when sparse imaging scenarios
are encountered due to a significant reduction in photon counts.} In this work,
we investigate the suitability of learning-based improvements to the
challenging task of obtaining high-quality reconstructions from sparse
measurements for a 64-channel PCD-CT. In particular, to overcome missing
reference data for the training procedure, we propose an unsupervised denoising
and artefact removal approach by exploiting different filter functions in the
reconstruction and an explicit coupling of spectral channels with the nuclear
norm. Performance is assessed on both simulated synthetic data and the openly
available experimental Multi-Spectral Imaging via Computed Tomography (MUSIC)
dataset. We compared the quality of our unsupervised method to iterative total
nuclear variation regularized reconstructions and a supervised denoiser trained
with reference data. We show that improved reconstruction quality can be
achieved with flexibility on noise statistics and effective suppression of
streaking artefacts when using unsupervised denoising with spectral coupling
Warfarin eller NOAC? Hva skal VI velge? Hvordan implementere brukermedvirkning ved oppstart av antikoagulasjonsbehandling hos pasienter med atrieflimmer.
How population-based data complement trial data in the adjuvant endocrine treatment of ER+/HER2+ breast cancers
Use of gene expression profiling to identify candidate genes for pretherapeutic patient classification in acute appendicitis
Background:
Phlegmonous and gangrenous appendicitis represent independent pathophysiological entities with different clinical courses ranging from spontaneous resolution to septic disease. However, reliable predictive methods for these clinical phenotypes have not yet been established. In an attempt to provide pathophysiological insights into the matter, a genomewide gene expression analysis was undertaken in patients with acute appendicitis.
Methods:
Peripheral blood mononuclear cells were isolated and, after histological confirmation of PA or GA, analysed for genomewide gene expression profiling using RNA microarray technology and subsequent pathway analysis.
Results:
Samples from 29 patients aged 7–17 years were included. Genomewide gene expression analysis was performed on 13 samples of phlegmonous and 16 of gangrenous appendicitis. From a total of 56 666 genes, 3594 were significantly differently expressed. Distinct interaction between T and B cells in the phlegmonous appendicitis group was suggested by overexpression of T cell receptor α and β subunits, CD2, CD3, MHC II, CD40L, and the B cell markers CD72 and CD79, indicating an antiviral mechanism. In the gangrenous appendicitis group, expression of genes delineating antibacterial mechanisms was found.
Conclusion:
These results provide evidence for different and independent gene expression in phlegmonous and gangrenous appendicitis in general, but also suggest distinct immunological patterns for the respective entities. In particular, the findings are compatible with previous evidence of spontaneous resolution in phlegmonous and progressive disease in gangrenous appendicitis
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