4 resultados para Vehicle Side Structures.

em CentAUR: Central Archive University of Reading - UK


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This paper addresses the challenging domain of vehicle classification from pole-mounted roadway cameras, specifically from side-profile views. A new public vehicle dataset is made available consisting of over 10000 side profile images (86 make/model and 9 sub-type classes). 5 state-of-the-art classifiers are applied to the dataset, with the best achieving high classification rates of 98.7% for sub-type and 99.7- 99.9% for make and model recognition, confirming the assertion made that single vehicle side profile images can be used for robust classification.

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Hierarchical ordering in a side group liquid crystal block copolymer is investigated by differential scanning calorimetry, polarized optical microscopy, small-angle X-ray and neutron scattering (SAXS and SANS) and transmission electron microscopy (TEM). A series of block copolymers with a range of compositions was prepared by atom transfer radical polymerization, comprising a polystyrene block and a poly(methyl methacrylate) block bearing chiral cholesteryl mesogens. Smectic ordering is observed as well as microphase separation of the block copolymer. Lamellar structures were observed for far larger volume fractions than for coil-coil copolymers (up to a volume fraction of liquid crystal block, f(LC) = 0.8). A sample with f(LC) = 0.86 exhibited a hexagonal-packed cylinder morphology, as confirmed by SAXS and TEM. The matrix comprised the liquid crystal block, with the mesogens forming smectic layers. For the liquid crystal homopolymer and samples with high f(LC), a smectic-smectic phase transition was observed below the clearing point. At low temperature, the smectic phase comprises coexisting domains with monolayer S-A,S-1 coexisting with interdigitated S-A,S-d domains. At high temperature a SA,1 phase is observed. This is the only structure observed for samples with lower f(LC). These unprecedented results point to the influence of block copolymer microphase separation on the smectic ordering.

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The lithium salt of the anionic SPS pincer ligand composed of a central hypervalent lambda(4)-phosphinine ring bearing two ortho-positioned diphenylphosphine sulfide side arms reacts with [Mn(CO)(5)Br] to give fac-[Mn(SPS)(CO)(3)], This isomer can be converted photochemicaily to mer-[Mn(SPS)(CO)(3)], with a very high quantum yield (0.80 +/- 0.05). The thermal backreaction is slow (taking ca. 8 h at room temperature), in contrast to rapid electrodecatalyzed mer-to-fac isomerization triggered by electrochemical reduction of mer-[Mn(SPS)(CO)(3)]. Both geometric isomers of [Mn(SPS)(CO)(3)] have been characterized by X-ray crystallography. Both isomers show luminescence from a low-lying (IL)-I-3 (SPS-based) excited state. The light emission of fac-[Mn(SPS)(CO)(3)] is largely quenched by the efficient photoisomerization occurring probably from a low-lying Mn-CO dissociative excited state. Density functional theory (DFT) and time-dependent DFT calculations describe the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) of fac- and mer-[Mn(CO)(3)(SPS)] as ligand-centered orbitals, largely localized on the phosphinine ring of the SPS pincer ligand. In line with the ligand nature of its frontier orbitals, fac-[Mn(SPS)(CO)(3)] is electrochemically reversibly oxidized and reduced to the corresponding radical cation and anion, respectively. The spectroscopic (electron paramagnetic resonance, IR, and UV-vis) characterization of the radical species provides other evidence for the localization of the redox steps on the SIPS ligand. The smaller HOMO-LUMO energy difference in the case of mer-[Mn(CO)(3)(SPS)], reflected in the electronic absorption and emission spectra, corresponds with its lower oxidation potential compared to that of the fac isomer. The thermodynamic instability of mer-[Mn(CO)(3)(SPS)], confirmed by the DFT calculations, increases upon one-electron reduction and oxidation of the complex.

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World-wide structural genomics initiatives are rapidly accumulating structures for which limited functional information is available. Additionally, state-of-the art structural prediction programs are now capable of generating at least low resolution structural models of target proteins. Accurate detection and classification of functional sites within both solved and modelled protein structures therefore represents an important challenge. We present a fully automatic site detection method, FuncSite, that uses neural network classifiers to predict the location and type of functionally important sites in protein structures. The method is designed primarily to require only backbone residue positions without the need for specific side-chain atoms to be present. In order to highlight effective site detection in low resolution structural models FuncSite was used to screen model proteins generated using mGenTHREADER on a set of newly released structures. We found effective metal site detection even for moderate quality protein models illustrating the robustness of the method.