3,588 research outputs found

    The interface between silicon and a high-k oxide

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    The ability to follow Moore's Law has been the basis of the tremendous success of the semiconductor industry in the past decades. To date, the greatest challenge for device scaling is the required replacement of silicon dioxide-based gate oxides by high-k oxides in transistors. Around 2010 high-k oxides are required to have an atomically defined interface with silicon without any interfacial SiO2 layer. The first clean interface between silicon and a high-K oxide has been demonstrated by McKee et al. Nevertheless, the interfacial structure is still under debate. Here we report on first-principles calculations of the formation of the interface between silicon and SrTiO3 and its atomic structure. Based on insights into how the chemical environment affects the interface, a way to engineer seemingly intangible electrical properties to meet technological requirements is outlined. The interface structure and its chemistry provide guidance for the selection process of other high-k gate oxides and for controlling their growth. Our study also shows that atomic control of the interfacial structure can dramatically improve the electronic properties of the interface. The interface presented here serves as a model for a variety of other interfaces between high-k oxides and silicon.Comment: 10 pages, 2 figures (one color

    Areas of natural occurrence of melipona scutellaris Latreille, 1811(Hymenoptera: Apidae) in the state of Bahia, Brazil.

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    The bee Melipona scutellaris is considered the reared meliponine species with the largest distribution in the North and Northeast regions of Brazil, with records from the state of Rio Grande do Norte down to the state of Bahia. Considering the importance of this species in the generation of income for family agriculture and in the preservation of areas with natural vegetation, this study aimed at providing knowledge on the distribution of natural colonies of M. scutellaris in the state of Bahia. Literature information, interviews with stinglessbee beekeepers, and expeditions were conducted to confirm the natural occurrence of the species. A total of 102 municipalities showed records for M. scutellaris, whose occurrence was observed in areas ranging from sea level up to 1,200-meter height. The occurrence of this species in the state of Bahia is considered to be restricted to municipalities on the coastal area and the Chapada Diamantina with its rainforests. Geographic coordinates, elevation, climate and vegetation data were obtained, which allowed a map to be prepared for the area of occurrence in order to support conservation and management policies for the species

    Atmospheric emissions from the deepwater Horizon spill constrain air-water partitioning, hydrocarbon fate, and leak rate

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    The fate of deepwater releases of gas and oil mixtures is initially determined by solubility and volatility of individual hydrocarbon species; these attributes determine partitioning between air and water. Quantifying this partitioning is necessary to constrain simulations of gas and oil transport, to predict marine bioavailability of different fractions of the gas-oil mixture, and to develop a comprehensive picture of the fate of leaked hydrocarbons in the marine environment. Analysis of airborne atmospheric data shows massive amounts (∼258,000 kg/day) of hydrocarbons evaporating promptly from the Deepwater Horizon spill; these data collected during two research flights constrain air-water partitioning, thus bioavailability and fate, of the leaked fluid. This analysis quantifies the fraction of surfacing hydrocarbons that dissolves in the water column (∼33% by mass), the fraction that does not dissolve, and the fraction that evaporates promptly after surfacing (∼14% by mass). We do not quantify the leaked fraction lacking a surface expression; therefore, calculation of atmospheric mass fluxes provides a lower limit to the total hydrocarbon leak rate of 32,600 to 47,700 barrels of fluid per day, depending on reservoir fluid composition information. This study demonstrates a new approach for rapid-response airborne assessment of future oil spills. Copyright 2011 by the American Geophysical Union

    Generalized quark-antiquark potential at weak and strong coupling

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    We study a two-parameter family of Wilson loop operators in N=4 supersymmetric Yang-Mills theory which interpolates smoothly between the 1/2 BPS line or circle and a pair of antiparallel lines. These observables capture a natural generalization of the quark-antiquark potential. We calculate these loops on the gauge theory side to second order in perturbation theory and in a semiclassical expansion in string theory to one-loop order. The resulting determinants are given in integral form and can be evaluated numerically for general values of the parameters or analytically in a systematic expansion around the 1/2 BPS configuration. We comment about the feasibility of deriving all-loop results for these Wilson loops.Comment: 43 pages: 15 comprising the main text and 25 for detailed appendice

    Species Difference of CD137 Ligand Signaling in Human and Murine Monocytes

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    BACKGROUND: Stimulation of CD137 ligand on human monocytes has been shown to induce DC differentiation, and these CD137L-DCs are more potent than classical DCs, in stimulating T cell responses in vitro. To allow an in vivo evaluation of the potency of CD137L-DCs in murine models we aimed at generating murine CD137L-DCs. METHODOLOGY/PRINCIPAL FINDINGS: When stimulated through CD137 ligand murine monocytes responded just as human monocytes with an increased adherence, morphological changes, proliferation and an increase in viable cell numbers. But CD137 ligand signaling did not induce expression of inflammatory cytokines and costimulatory molecules in murine monocytes and these cells had no T cell stimulatory activity. Murine monocytes did not differentiate to inflammatory DCs upon CD137 ligand signaling. Furthermore, while CD137 ligand signaling induces maturation of human immature classical DCs it failed to do so with murine immature classical DCs. CONCLUSIONS/SIGNIFICANCE: These data demonstrate that both human and murine monocytes become activated by CD137 ligand signaling but only human and not murine monocytes differentiate to inflammatory DCs

    The identification of informative genes from multiple datasets with increasing complexity

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    Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

    The Role of the Mucus Barrier in Digestion

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    Mucus forms a protective layer across a variety of epithelial surfaces. In the gastrointestinal (GI) tract, the barrier has to permit the uptake of nutrients, while excluding potential hazards, such as pathogenic bacteria. In this short review article, we look at recent literature on the structure, location, and properties of the mammalian intestinal secreted mucins and the mucus layer they form over a wide range of length scales. In particular, we look at the structure of the gel-forming glycoprotein MUC2, the primary intestinal secreted mucin, and the influence this has on the properties of the mucus layer. We show that, even at the level of the protein backbone, MUC2 is highly heterogeneous and that this is reflected in the networks it forms. It is evident that a combination of charge and pore size determines what can diffuse through the layer to the underlying gut epithelium. This information is important for the targeted delivery of bioactive molecules, including nutrients and pharmaceuticals, and for understanding how GI health is maintained

    Factors associated with in-hospital mortality following intracerebral hemorrhage: a three-year study in Tehran, Iran

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    BACKGROUND: Primary intracerebral hemorrhage (ICH) is one of the common vascular insults with a relatively high rate of mortality. The aim of the current study was to determine the mortality rate and to evaluate the influence of various factors on the mortality of patients with intracerebral hemorrhage (ICH). Demographic characteristics along with clinical features and neuroimaging information on 122 patients with primary ICH admitted to Sina Hospital between 1999–2002 were assessed by multivariate analysis. RESULTS: Of 122 patients diagnosed with intracerebral hemorrhage, 70 were men and 52 were women. Sixtynine percent of subjects were between 60 to 80 years of age. A history of hypertension was the primary cause in 67.2% of participants and it was found more frequent compared to other cardiovascular risk factors such as a history of ischemic heart disease (17.2%), diabetes mellitus (18%) and cigarette smoking (13.1%). The overall mortality rate among ICH patients admitted to the hospital was 46.7%. About one third of the deaths occurred within the first two days after brain injury. Factor independently associated with in-hospital mortality were Glasgow Coma Scale (GCS) score (≤ 8), diabetes mellitus disease, volume of hematoma and and intraventricular hematoma. CONCLUSION: Higher rate of mortality were observed during the first two weeks of hospitalization following ICH. Neuroimaging features along with GCS score can help the clinicians in developing their prognosis
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