In situ epitaxial engineering of graphene and h-BN lateral heterostructure with a tunable morphology comprising h-BN domains

Graphene and hexagonal boron nitride (h-BN), as typical two-dimensional (2D) materials, have long attracted substantial attention due to their unique properties and promise in a wide range of applications. Although they have a rather large difference in their intrinsic bandgaps, they share a very similar atomic lattice; thus, there is great potential in constructing heterostructures by lateral stitching. Herein, we present the in situ growth of graphene and h-BN lateral heterostructures with tunable morphologies that range from a regular hexagon to highly symmetrical star-like structure on the surface of liquid Cu. The chemical vapor deposition (CVD) method is used, where the growth of the h-BN is demonstrated to be highly templated by the graphene. Furthermore, large-area production of lateral G-h-BN heterostructures at the centimeter scale with uniform orientation is realized by precisely tuning the CVD conditions. We found that the growth of h-BN is determined by the initial graphene and symmetrical features are produced that demonstrate heteroepitaxy. Simulations based on the phase field and density functional theories are carried out to elucidate the growth processes of G-h-BN flakes with various morphologies, and they have a striking consistency with experimental observations. The growth of a lateral G-h-BN heterostructure and an understanding of the growth mechanism can accelerate the construction of various heterostructures based on 2D materials

Measurement of the Branching Fraction of J/psi --> pi+ pi- pi0

Using 58 million J/psi and 14 million psi' decays obtained by the BESII experiment, the branching fraction of J/psi --> pi+ pi- pi0 is determined. The result is (2.10+/-0.12)X10^{-2}, which is significantly higher than previous measurements.Comment: 9 pages, 8 figures, RevTex

First observation of psi(2S)-->K_S K_L

The decay psi(2S)-->K_S K_L is observed for the first time using psi(2S) data collected with the Beijing Spectrometer (BESII) at the Beijing Electron Positron Collider (BEPC); the branching ratio is determined to be B(psi(2S)-->K_S K_L) = (5.24\pm 0.47 \pm 0.48)\times 10^{-5}. Compared with J/psi-->K_S K_L, the psi(2S) branching ratio is enhanced relative to the prediction of the perturbative QCD ``12%'' rule. The result, together with the branching ratios of psi(2S) decays to other pseudoscalar meson pairs (\pi^+\pi^- and K^+K^-), is used to investigate the relative phase between the three-gluon and the one-photon annihilation amplitudes of psi(2S) decays.Comment: 5 pages, 4 figures, 2 tables, submitted to Phys. Rev. Let

Identification of Combinatorial Patterns of Post-Translational Modifications on Individual Histones in the Mouse Brain

Post-translational modifications (PTMs) of proteins are biochemical processes required for cellular functions and signalling that occur in every sub-cellular compartment. Multiple protein PTMs exist, and are established by specific enzymes that can act in basal conditions and upon cellular activity. In the nucleus, histone proteins are subjected to numerous PTMs that together form a histone code that contributes to regulate transcriptional activity and gene expression. Despite their importance however, histone PTMs have remained poorly characterised in most tissues, in particular the brain where they are thought to be required for complex functions such as learning and memory formation. Here, we report the comprehensive identification of histone PTMs, of their combinatorial patterns, and of the rules that govern these patterns in the adult mouse brain. Based on liquid chromatography, electron transfer, and collision-induced dissociation mass spectrometry, we generated a dataset containing a total of 10,646 peptides from H1, H2A, H2B, H3, H4, and variants in the adult brain. 1475 of these peptides carried one or more PTMs, including 141 unique sites and a total of 58 novel sites not described before. We observed that these PTMs are not only classical modifications such as serine/threonine (Ser/Thr) phosphorylation, lysine (Lys) acetylation, and Lys/arginine (Arg) methylation, but also include several atypical modifications such as Ser/Thr acetylation, and Lys butyrylation, crotonylation, and propionylation. Using synthetic peptides, we validated the presence of these atypical novel PTMs in the mouse brain. The application of data-mining algorithms further revealed that histone PTMs occur in specific combinations with different ratios. Overall, the present data newly identify a specific histone code in the mouse brain and reveal its level of complexity, suggesting its potential relevance for higher-order brain functions

Interleukin-17 Contributes to the Pathogenesis of Autoimmune Hepatitis through Inducing Hepatic Interleukin-6 Expression

T helper cells that produce IL-17 (Th17 cells) have recently been identified as the third distinct subset of effector T cells. Emerging data suggests that Th17 cells play an important role in the pathogenesis of many liver diseases by regulating innate immunity, adaptive immunity, and autoimmunity. In this study, we examine the role and mechanism of Th17 cells in the pathogenesis of autoimmune hepatitis (AIH). The serum levels of IL-17 and IL-23, as well as the frequency of IL-17+ cells in the liver, were significantly elevated in patients with AIH, compared to other chronic hepatitis and healthy controls. The hepatic expressions of IL-17, IL-23, ROR-γt, IL-6 and IL-1β in patients with AIH were also significantly increased and were associated with increased inflammation and fibrosis. IL-17 induces IL-6 expression via the MAPK signaling pathway in hepatocytes, which, in turn, may further stimulate Th17 cells and forms a positive feedback loop. In conclusion, Th17 cells are key effector T cells that regulate the pathogenesis of AIH, via induction of MAPK dependent hepatic IL-6 expression. Blocking the signaling pathway and interrupting the positive feedback loop are potential therapeutic targets for autoimmune hepatitis

Neural coding in a single sensory neuron controlling opposite seeking behaviours in Caenorhabditis elegans

Unveiling the neural codes for intricate behaviours is a major challenge in neuroscience. The neural circuit for the temperature-seeking behaviour of Caenorhabditis elegans is an ideal system to dissect how neurons encode sensory information for the execution of behavioural output. Here we show that the temperature-sensing neuron AFD transmits both stimulatory and inhibitory neural signals to a single interneuron AIY. In this circuit, a calcium concentration threshold in AFD acts as a switch for opposing neural signals that direct the opposite behaviours. Remote control of AFD activity, using a light-driven ion pump and channel, reveals that diverse reduction levels of AFD activity can generate warm- or cold-seeking behaviour. Calcium imaging shows that AFD uses either stimulatory or inhibitory neuronal signalling onto AIY, depending on the calcium concentration threshold in AFD. Thus, dual neural regulation in opposite directions is directly coupled to behavioural inversion in the simple neural circuit

Properties of Graphene: A Theoretical Perspective

In this review, we provide an in-depth description of the physics of monolayer and bilayer graphene from a theorist's perspective. We discuss the physical properties of graphene in an external magnetic field, reflecting the chiral nature of the quasiparticles near the Dirac point with a Landau level at zero energy. We address the unique integer quantum Hall effects, the role of electron correlations, and the recent observation of the fractional quantum Hall effect in the monolayer graphene. The quantum Hall effect in bilayer graphene is fundamentally different from that of a monolayer, reflecting the unique band structure of this system. The theory of transport in the absence of an external magnetic field is discussed in detail, along with the role of disorder studied in various theoretical models. We highlight the differences and similarities between monolayer and bilayer graphene, and focus on thermodynamic properties such as the compressibility, the plasmon spectra, the weak localization correction, quantum Hall effect, and optical properties. Confinement of electrons in graphene is nontrivial due to Klein tunneling. We review various theoretical and experimental studies of quantum confined structures made from graphene. The band structure of graphene nanoribbons and the role of the sublattice symmetry, edge geometry and the size of the nanoribbon on the electronic and magnetic properties are very active areas of research, and a detailed review of these topics is presented. Also, the effects of substrate interactions, adsorbed atoms, lattice defects and doping on the band structure of finite-sized graphene systems are discussed. We also include a brief description of graphane -- gapped material obtained from graphene by attaching hydrogen atoms to each carbon atom in the lattice.Comment: 189 pages. submitted in Advances in Physic

Probabilistic change detection and visualization methods for the assessment of temporal stability in biomedical data quality

The final publication is available at Springer via http://dx.doi.org/DOI 10.1007/s10618-014-0378-6. Published online.Knowledge discovery on biomedical data can be based on on-line, data-stream analyses, or using retrospective, timestamped, off-line datasets. In both cases, changes in the processes that generate data or in their quality features through time may hinder either the knowledge discovery process or the generalization of past knowledge. These problems can be seen as a lack of data temporal stability. This work establishes the temporal stability as a data quality dimension and proposes new methods for its assessment based on a probabilistic framework. Concretely, methods are proposed for (1) monitoring changes, and (2) characterizing changes, trends and detecting temporal subgroups. First, a probabilistic change detection algorithm is proposed based on the Statistical Process Control of the posterior Beta distribution of the Jensen–Shannon distance, with a memoryless forgetting mechanism. This algorithm (PDF-SPC) classifies the degree of current change in three states: In-Control, Warning, and Out-of-Control. Second, a novel method is proposed to visualize and characterize the temporal changes of data based on the projection of a non-parametric information-geometric statistical manifold of time windows. This projection facilitates the exploration of temporal trends using the proposed IGT-plot and, by means of unsupervised learning methods, discovering conceptually-related temporal subgroups. Methods are evaluated using real and simulated data based on the National Hospital Discharge Survey (NHDS) dataset.The work by C Saez has been supported by an Erasmus Lifelong Learning Programme 2013 Grant. This work has been supported by own IBIME funds. 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Production Scheduling Requirements to Smart Manufacturing

The production scheduling has attracted a lot of researchers for many years, however most of the approaches are not targeted to deal with real manufacturing environments, and those that are, are very particular for the case study. It is crucial to consider important features related with the factories, such as products and machines characteristics and unexpected disturbances, but also information such as when the parts arrive to the factory and when should be delivered. So, the purpose of this paper is to identify some important characteristics that have been considered independently in a lot of studies and that should be considered together to develop a generic scheduling framework to be used in a real manufacturing environment.authorsversionpublishe