Measuring the Hole State Anisotropy in MgB2 by Electron Energy-Loss Spectroscopy

We have examined polycrystalline MgB2 by electron energy loss spectroscopy (EELS) and density of state calculations. In particular, we have studied two different crystal orientations, [110] and [001] with respect to the incident electron beam direction, and found significant changes in the near-edge fine-structure of the B K-edge. Density functional theory suggests that the pre-peak of the B K-edge core loss is composed of a mixture of pxy and pz hole states and we will show that these contributions can be distinguished only with an experimental energy resolution better than 0.5 eV. For conventional TEM/STEM instruments with an energy resolution of ~1.0 eV the pre-peak still contains valuable information about the local charge carrier concentration that can be probed by core-loss EELS. By considering the scattering momentum transfer for different crystal orientations, it is possible to analytically separate pxy and pz components from of the experimental spectra With careful experiments and analysis, EELS can be a unique tool measuring the superconducting properties of MgB2, doped with various elements for improved transport properties on a sub-nanometer scale.Comment: 26 Pages, 5 figures, 1 table. Submited to PR

Aluminum Oxide Layers as Possible Components for Layered Tunnel Barriers

We have studied transport properties of Nb/Al/AlOx/Nb tunnel junctions with ultrathin aluminum oxide layers formed by (i) thermal oxidation and (ii) plasma oxidation, before and after rapid thermal post-annealing of the completed structures at temperatures up to 550 deg C. Post-annealing at temperatures above 300 deg C results in a significant decrease of the tunneling conductance of thermally-grown barriers, while plasma-grown barriers start to change only at annealing temperatures above 450 deg C. Fitting the experimental I-V curves of the junctions using the results of the microscopic theory of direct tunneling shows that the annealing of thermally-grown oxides at temperatures above 300 deg C results in a substantial increase of their average tunnel barriers height, from ~1.8 eV to ~2.45 eV, versus the practically unchanged height of ~2.0 eV for plasma-grown layers. This difference, together with high endurance of annealed barriers under electric stress (breakdown field above 10 MV/cm) may enable all-AlOx and SiO2/AlOx layered "crested" barriers for advanced floating-gate memory applications.Comment: 7 pages, 6 figure

Disorder induced collapse of the electron phonon coupling in MgB2_{2} observed by Raman Spectroscopy

The Raman spectrum of the superconductor MgB$_{2}$ has been measured as a function of the Tc of the film. A striking correlation is observed between the $T_{c}$ onset and the frequency of the $E_{2g}$ mode. Analysis of the data with the McMillan formula provides clear experimental evidence for the collapse of the electron phonon coupling at the temperature predicted for the convergence of two superconducting gaps into one observable gap. This gives indirect evidence of the convergence of the two gaps and direct evidence of a transition to an isotropic state at 19 K. The value of the electron phonon coupling constant is found to be 1.22 for films with T$_{c}$ 39K and 0.80 for films with T$_{c}\leq$19K.Comment: 5 pages, 4 figure

Speeding up the Consensus Clustering methodology for microarray data analysis

<p>Abstract</p> <p>Background</p> <p>The inference of the number of clusters in a dataset, a fundamental problem in Statistics, Data Analysis and Classification, is usually addressed via internal validation measures. The stated problem is quite difficult, in particular for microarrays, since the inferred prediction must be sensible enough to capture the inherent biological structure in a dataset, e.g., functionally related genes. Despite the rich literature present in that area, the identification of an internal validation measure that is both fast and precise has proved to be elusive. In order to partially fill this gap, we propose a speed-up of <monospace>Consensus</monospace> (Consensus Clustering), a methodology whose purpose is the provision of a prediction of the number of clusters in a dataset, together with a dissimilarity matrix (the consensus matrix) that can be used by clustering algorithms. As detailed in the remainder of the paper, <monospace>Consensus</monospace> is a natural candidate for a speed-up.</p> <p>Results</p> <p>Since the time-precision performance of <monospace>Consensus</monospace> depends on two parameters, our first task is to show that a simple adjustment of the parameters is not enough to obtain a good precision-time trade-off. Our second task is to provide a fast approximation algorithm for <monospace>Consensus</monospace>. That is, the closely related algorithm <monospace>FC</monospace> (Fast Consensus) that would have the same precision as <monospace>Consensus</monospace> with a substantially better time performance. The performance of <monospace>FC</monospace> has been assessed via extensive experiments on twelve benchmark datasets that summarize key features of microarray applications, such as cancer studies, gene expression with up and down patterns, and a full spectrum of dimensionality up to over a thousand. Based on their outcome, compared with previous benchmarking results available in the literature, <monospace>FC</monospace> turns out to be among the fastest internal validation methods, while retaining the same outstanding precision of <monospace>Consensus</monospace>. Moreover, it also provides a consensus matrix that can be used as a dissimilarity matrix, guaranteeing the same performance as the corresponding matrix produced by <monospace>Consensus</monospace>. We have also experimented with the use of <monospace>Consensus</monospace> and <monospace>FC</monospace> in conjunction with <monospace>NMF</monospace> (Nonnegative Matrix Factorization), in order to identify the correct number of clusters in a dataset. Although <monospace>NMF</monospace> is an increasingly popular technique for biological data mining, our results are somewhat disappointing and complement quite well the state of the art about <monospace>NMF</monospace>, shedding further light on its merits and limitations.</p> <p>Conclusions</p> <p>In summary, <monospace>FC</monospace> with a parameter setting that makes it robust with respect to small and medium-sized datasets, i.e, number of items to cluster in the hundreds and number of conditions up to a thousand, seems to be the internal validation measure of choice. Moreover, the technique we have developed here can be used in other contexts, in particular for the speed-up of stability-based validation measures.</p

Status of Biodiversity in the Baltic Sea

The brackish Baltic Sea hosts species of various origins and environmental tolerances. These immigrated to the sea 10,000 to 15,000 years ago or have been introduced to the area over the relatively recent history of the system. The Baltic Sea has only one known endemic species. While information on some abiotic parameters extends back as long as five centuries and first quantitative snapshot data on biota (on exploited fish populations) originate generally from the same time, international coordination of research began in the early twentieth century. Continuous, annual Baltic Sea-wide long-term datasets on several organism groups (plankton, benthos, fish) are generally available since the mid-1950s. Based on a variety of available data sources (published papers, reports, grey literature, unpublished data), the Baltic Sea, incl. Kattegat, hosts altogether at least 6,065 species, including at least 1,700 phytoplankton, 442 phytobenthos, at least 1,199 zooplankton, at least 569 meiozoobenthos, 1,476 macrozoobenthos, at least 380 vertebrate parasites, about 200 fish, 3 seal, and 83 bird species. In general, but not in all organism groups, high sub-regional total species richness is associated with elevated salinity. Although in comparison with fully marine areas the Baltic Sea supports fewer species, several facets of the system's diversity remain underexplored to this day, such as micro-organisms, foraminiferans, meiobenthos and parasites. In the future, climate change and its interactions with multiple anthropogenic forcings are likely to have major impacts on the Baltic biodiversity