132 research outputs found

    Quasi-Freestanding Multilayer Graphene Films on the Carbon Face of SiC

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    The electronic band structure of as-grown and doped graphene grown on the carbon face of SiC is studied by high-resolution angle-resolved photoemission spectroscopy, where we observe both rotations between adjacent layers and AB-stacking. The band structure of quasi-freestanding AB- bilayers is directly compared with bilayer graphene grown on the Si-face of SiC to study the impact of the substrate on the electronic properties of epitaxial graphene. Our results show that the C-face films are nearly freestanding from an electronic point of view, due to the rotations between graphene layers.Comment: http://link.aps.org/doi/10.1103/PhysRevB.81.24141

    Evaluation of conduction eigenchannels of an adatom probed by an STM tip

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    Ballistic conductance through a single atom adsorbed on a metallic surface and probed by a scanning tunneling microscope (STM) tip can be decomposed into eigenchannel contributions, which can be potentially obtained from shot noise measurements. Our density functional theory calculations provide evidence that transmission probabilities of these eigenchannels encode information on the modifications of the adatom's local density of states caused by its interaction with the STM tip. In the case of open shell atoms, this can be revealed in nonmonotonic behavior of the eigenchannel's transmissions as a function of the tip-adatom separation.Comment: 4.5 pages, 5 figures, REVTe

    End-to-end learning of brain tissue segmentation from imperfect labeling

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    Segmenting a structural magnetic resonance imaging (MRI) scan is an important pre-processing step for analytic procedures and subsequent inferences about longitudinal tissue changes. Manual segmentation defines the current gold standard in quality but is prohibitively expensive. Automatic approaches are computationally intensive, incredibly slow at scale, and error prone due to usually involving many potentially faulty intermediate steps. In order to streamline the segmentation, we introduce a deep learning model that is based on volumetric dilated convolutions, subsequently reducing both processing time and errors. Compared to its competitors, the model has a reduced set of parameters and thus is easier to train and much faster to execute. The contrast in performance between the dilated network and its competitors becomes obvious when both are tested on a large dataset of unprocessed human brain volumes. The dilated network consistently outperforms not only another state-of-the-art deep learning approach, the up convolutional network, but also the ground truth on which it was trained. Not only can the incredible speed of our model make large scale analyses much easier but we also believe it has great potential in a clinical setting where, with little to no substantial delay, a patient and provider can go over test results.Comment: Published as a conference paper at IJCNN 2017 Preprint versio

    The Peculiarities of Large Intron Splicing in Animals

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    In mammals a considerable 92% of genes contain introns, with hundreds and hundreds of these introns reaching the incredible size of over 50,000 nucleotides. These “large introns” must be spliced out of the pre-mRNA in a timely fashion, which involves bringing together distant 5′ and 3′ acceptor and donor splice sites. In invertebrates, especially Drosophila, it has been shown that larger introns can be spliced efficiently through a process known as recursive splicing—a consecutive splicing from the 5′-end at a series of combined donor-acceptor splice sites called RP-sites. Using a computational analysis of the genomic sequences, we show that vertebrates lack the proper enrichment of RP-sites in their large introns, and, therefore, require some other method to aid splicing. We analyzed over 15,000 non-redundant, large introns from six mammals, 1,600 from chicken and zebrafish, and 560 non-redundant large introns from five invertebrates. Our bioinformatic investigation demonstrates that, unlike the studied invertebrates, the studied vertebrate genomes contain consistently abundant amounts of direct and complementary strand interspersed repetitive elements (mainly SINEs and LINEs) that may form stems with each other in large introns. This examination showed that predicted stems are indeed abundant and stable in the large introns of mammals. We hypothesize that such stems with long loops within large introns allow intron splice sites to find each other more quickly by folding the intronic RNA upon itself at smaller intervals and, thus, reducing the distance between donor and acceptor sites

    Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA

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    Non-coding genomic regions in complex eukaryotes, including intergenic areas, introns, and untranslated segments of exons, are profoundly non-random in their nucleotide composition and consist of a complex mosaic of sequence patterns. These patterns include so-called Mid-Range Inhomogeneity (MRI) regions -- sequences 30-10000 nucleotides in length that are enriched by a particular base or combination of bases (e.g. (G+T)-rich, purine-rich, etc.). MRI regions are associated with unusual (non-B-form) DNA structures that are often involved in regulation of gene expression, recombination, and other genetic processes (Fedorova & Fedorov 2010). The existence of a strong fixation bias within MRI regions against mutations that tend to reduce their sequence inhomogeneity additionally supports the functionality and importance of these genomic sequences (Prakash et al. 2009)

    Many-body interactions in quasi-freestanding graphene

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    The Landau-Fermi liquid picture for quasiparticles assumes that charge carriers are dressed by many-body interactions, forming one of the fundamental theories of solids. Whether this picture still holds for a semimetal like graphene at the neutrality point, i.e., when the chemical potential coincides with the Dirac point energy, is one of the long-standing puzzles in this field. Here we present such a study in quasi-freestanding graphene by using high-resolution angle-resolved photoemission spectroscopy. We see the electron-electron and electron-phonon interactions go through substantial changes when the semimetallic regime is approached, including renormalizations due to strong electron-electron interactions with similarities to marginal Fermi liquid behavior. These findings set a new benchmark in our understanding of many-body physics in graphene and a variety of novel materials with Dirac fermions.Comment: PNAS 2011 ; published ahead of print June 27, 201
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