38,023 research outputs found

    Bearing detection in the presence of two sources of varying coherence using the complex cepstrum

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    The effect of the presence of two acoustic sources (one, the primary, whose location is to be detected) of varying coherence on a cepstral bearing finding procedure is experimentally studied. The coherence between the acoustic sources was altered by adding random noise of various SNR (signal-to-noise ratio) to the input signal of the primary source; the same base signal being fed to both sources. The results demonstrate that, when block liftering is used, the primary source bearing is reliably estimated for coherences as low as gamma sup 2 greater than or approx equal to 0.5. The results also imply that background noise (unreflected) of SNR greater than or approx equal to 10 dB will not markedly affect the accuracy of the bearing estimation algorithm

    Wearable technology in academia: the use of Google Glass in the life sciences

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    Crystal structure of Schmallenberg orthobunyavirus nucleoprotein-RNA complex reveals a novel RNA sequestration mechanism

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    Schmallenberg virus (SBV) is a newly emerged orthobunyavirus (family Bunyaviridae) that has caused severe disease in the offspring of farm animals across Europe. Like all orthobunyaviruses, SBV contains a tripartite negative-sense RNA genome that is encapsidated by the viral nucleocapsid (N) protein in the form of a ribonucleoprotein complex (RNP). We recently reported the three-dimensional structure of SBV N that revealed a novel fold. Here we report the crystal structure of the SBV N protein in complex with a 42-nt-long RNA to 2.16 Å resolution. The complex comprises a tetramer of N that encapsidates the RNA as a cross-shape inside the protein ring structure, with each protomer bound to 11 ribonucleotides. Eight bases are bound in the positively charged cleft between the N- and C-terminal domains of N, and three bases are shielded by the extended N-terminal arm. SBV N appears to sequester RNA using a different mechanism compared with the nucleoproteins of other negative-sense RNA viruses. Furthermore, the structure suggests that RNA binding results in conformational changes of some residues in the RNA-binding cleft and the N- and C-terminal arms. Our results provide new insights into the novel mechanism of RNA encapsidation by orthobunyaviruses

    Design and Construction of the 3.2 Mev High Voltage Column for Darht II

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    A 3.2 MeV injector has been designed and built for the Darht II Project at Los Alamos Lab. The installation of the complete injector system is nearing completion at this time. The requirements for the injector are to produce a 3.2 MeV, 2000 ampere electron pulse with a flattop width of at least 2-microseconds and emittance of less than 0.15 p cm-rad normalized. A large high voltage column has been built and installed. The column is vertically oriented, is 4.4 meters long, 1.2 meters in diameter, and weights 5700 kilograms. A novel method of construction has been employed which utilizes bonded mycalex insulating rings. This paper will describe the design, construction, and testing completed during construction. Mechanical aspects of the design will be emphasized.Comment: 3 pages, 4 figures, Linac 200

    Spatial reasoning to determine stream network from LANDSAT imagery

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    In LANDSAT imagery, spectral and spatial information can be used to detect the drainage network as well as the relative elevation model in mountainous terrain. To do this, mixed information of material reflectance in the original LANDSAT imagery must be separated. From the material reflectance information, big visible rivers can be detected. From the topographic modulation information, ridges and valleys can be detected and assigned relative elevations. A complete elevation model can be generated by interpolating values for nonridge and non-valley pixels. The small streams not detectable from material reflectance information can be located in the valleys with flow direction known from the elevation model. Finally, the flow directions of big visible rivers can be inferred by solving a consistent labeling problem based on a set of spatial reasoning constraints
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