A large amount of (all-E)-lycopene was successfully purified from tomato paste using an improved method that included a procedure to wash crystalline powder with acetone. The total yield of the pure (all-E) form was at least 30%. The melting point of (all-E)-lycopene was determined to be 176.35 °C by differential scanning calorimetry (DSC) measurements. Bathochromic shifts were observed in the absorption maxima of all solvents tested (at most a 36 nm shift for λ2 in carbon disulfide, as was observed in hexane) and were accompanied by absorbance decreases, namely, a hypochromic effect, showing a higher correlation between the position and the intensity of the main absorption bands. This bathochromic shift was dependent upon the polarizability of the solvent rather than its polarity. The structure of (all-E)-lycopene in CDCl3 and C6D6 was identified on the basis of one- and two-dimensional nuclear magnetic resonance (NMR) spectra, including (1)H and (13)C NMR, homonuclear correlation spectroscopy ((1)H-(1)H COSY), heteronuclear multiple-quantum coherence (HMQC), and heteronuclear multiple-bond connectivity (HMBC). The rate constants of the decrease in (all-E)-lycopene with hexane and benzene were calculated to be 3.19 × 10(-5) and 3.55 × 10(-5) s(-1), respectively. The equilibrium constants between (all-E) and (13Z) isomers were estimated to be 0.29 in hexane and 0.31 in benzene, respectively, from the point at which the amount of (13Z)-lycopene reached its maximum.

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The paper briefly reviews certain aspects of the biological visual system and presents a smart vision sensor for the detection of higher-level features. The visual system processes information in a hierarchical manner starting from the retina up to the visual cortex. It decomposes the image in simple features (edges, orientation, line stops, corners, etc) using spatial and temporal information. At the higher level it integrates these primitive features, resulting in the recognition of complex objects. The sensor described in the paper is loosely modeled after the visual system and incorporates pixel level, programmable elements which extract orientation, end stops, corners and junctions from a line drawing. The architecture resembles a CNN-UM that can be programmed with a 30-bit word. The 16 x 16 pixels array detects these higher-level features in about 54 μseconds.