1,574 research outputs found
Pressure dependence of the superconducting transition and electron correlations in Na_xCoO_2 \cdot 1.3H_2O
We report T_c and ^{59}Co nuclear quadrupole resonance (NQR) measurements on
the cobalt oxide superconductor Na_{x}CoO_{2}\cdot 1.3H_{2}O (T_c=4.8 K) under
hydrostatic pressure (P) up to 2.36 GPa. T_c decreases with increasing pressure
at an average rate of -0.49\pm0.09 K/GPa. At low pressures P\leq0.49 GPa, the
decrease of T_c is accompanied by a weakening of the spin correlations at a
finite wave vector and a reduction of the density of states (DOS) at the Fermi
level. At high pressures above 1.93 GPa, however, the decrease of T_c is mainly
due to a reduction of the DOS. These results indicate that the
electronic/magnetic state of Co is primarily responsible for the
superconductivity. The spin-lattice relaxation rate 1/T_1 at P=0.49 GPa shows a
T^3 variation below T_c down to T\sim 0.12T_c, which provides compelling
evidence for the presence of line nodes in the superconducting gap function.Comment: published on 19, Sept. 2007 on Phys. Rev.
Effects of H-NS and potassium glutamate on σ<SUP>S</SUP>- and σ<SUP>70</SUP>-directed transcription in vitro from osmotically regulated P1 and P2 promoters of proU in Escherichia coli
We have used supercoiled DNA templates in this study to demonstrate that transcription in vitro from the P1 and P2 promoters of the osmoresponsive proU operon of Escherichia coli is preferentially mediated by the σs and σ70-bearing RNA polymerase holoenzymes, respectively. Addition of potassium glutamate resulted in the activation of transcription from both P1 and P2 and also led to a pronounced enhancement of σs selectivity at the P1 promoter. Transcription from P2, and to a lesser extent from P1, was inhibited by the nucleoid protein H-NS but only in the absence of potassium glutamate. This study validates the existence of dual promoters with dual specificities for proU transcription. Our results also support the proposals that potassium, which is known to accumulate in cells grown at high osmolarity, is at least partially responsible for effecting the in vivo induction of proU transcription and that it does so through two mechanisms, directly by the activation of RNA polymerase and indirectly by the relief of repression imposed by H-NS
Existence of Dynamical Scaling in the Temporal Signal of Time Projection Chamber
The temporal signals from a large gas detector may show dynamical scaling due
to many correlated space points created by the charged particles while passing
through the tracking medium. This has been demonstrated through simulation
using realistic parameters of a Time Projection Chamber (TPC) being fabricated
to be used in ALICE collider experiment at CERN. An interesting aspect of this
dynamical behavior is the existence of an universal scaling which does not
depend on the multiplicity of the collision. This aspect can be utilised
further to study physics at the device level and also for the online monitoring
of certain physical observables including electronics noise which are a few
crucial parameters for the optimal TPC performance.Comment: 5 pages, 6 figure
Estimating Electric Fields from Vector Magnetogram Sequences
Determining the electric field (E-field) distribution on the Sun's
photosphere is essential for quantitative studies of how energy flows from the
Sun's photosphere, through the corona, and into the heliosphere. This E-field
also provides valuable input for data-driven models of the solar atmosphere and
the Sun-Earth system. We show how Faraday's Law can be used with observed
vector magnetogram time series to estimate the photospheric E-field, an
ill-posed inversion problem. Our method uses a "poloidal-toroidal
decomposition" (PTD) of the time derivative of the vector magnetic field. The
PTD solutions are not unique; the gradient of a scalar potential can be added
to the PTD E-field without affecting consistency with Faraday's Law. We present
an iterative technique to determine a potential function consistent with ideal
MHD evolution; but this E-field is also not a unique solution to Faraday's Law.
Finally, we explore a variational approach that minimizes an energy functional
to determine a unique E-field, similar to Longcope's "Minimum Energy Fit". The
PTD technique, the iterative technique, and the variational technique are used
to estimate E-fields from a pair of synthetic vector magnetograms taken from an
MHD simulation; and these E-fields are compared with the simulation's known
electric fields. These three techniques are then applied to a pair of vector
magnetograms of solar active region NOAA AR8210, to demonstrate the methods
with real data.Comment: 41 pages, 10 figure
TargetSearch - a Bioconductor package for the efficient preprocessing of GC-MS metabolite profiling data
Background: Metabolite profiling, the simultaneous quantification of multiple metabolites in an experiment, is becoming increasingly popular, particularly with the rise of systems-level biology. The workhorse in this field is gas-chromatography hyphenated with mass spectrometry (GC-MS). The high-throughput of this technology coupled with a demand for large experiments has led to data pre-processing, i.e. the quantification of metabolites across samples, becoming a major bottleneck. Existing software has several limitations, including restricted maximum sample size, systematic errors and low flexibility. However, the biggest limitation is that the resulting data usually require extensive hand-curation, which is subjective and can typically take several days to weeks. Results: We introduce the TargetSearch package, an open source tool which is a flexible and accurate method for pre-processing even very large numbers of GC-MS samples within hours. We developed a novel strategy to iteratively correct and update retention time indices for searching and identifying metabolites. The package is written in the R programming language with computationally intensive functions written in C for speed and performance. The package includes a graphical user interface to allow easy use by those unfamiliar with R. Conclusions: TargetSearch allows fast and accurate data pre-processing for GC-MS experiments and overcomes the sample number limitations and manual curation requirements of existing software. We validate our method by carrying out an analysis against both a set of known chemical standard mixtures and of a biological experiment. In addition we demonstrate its capabilities and speed by comparing it with other GC-MS pre-processing tools. We believe this package will greatly ease current bottlenecks and facilitate the analysis of metabolic profiling data
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