Summary
Blueberry anthocyanins are the major active ingredients of blueberry with a variety of biological activities. The scale extraction and separation of blueberry anthocyanins could contribute to their application in drugs, cosmetics, food additives and so on. In this study, using combined technologies to high‐efficient extraction and separation of blueberry anthocyanins was developed. Under the optimum extraction conditions of first 0.3% cellulose and pectinase with 2:1 (m/m) at 37 °C for 4 h and then 1% citric acid‐acidified 75% (v/v) ethanol at 37 °C for 6 h, as high as 25% extraction rate of blueberry anthocyanins was obtained. By ethyl acetate extraction in triplicate and then D101 resin column chromatography, up to 49.6% purity of blueberry anthocyanins was obtained based on UV–vis analysis. The scale‐up extraction and separation of blueberry anthocyanins were carried out. This method was simple but effective, and easy scalable at industrial purpose.
A new ultrafast all-optical solid-state framing camera (UASFC) capable of single-shot ultrafast imaging is proposed and experimentally demonstrated. It is composed of an ultrafast semiconductor chip (USC), an optical time-series system (TSS), and a spatial mapping device (SMD) with an USC to transform signal beam information to the probe beam, a TSS to convert the time axis to wavelength-polarization, and a SMD to map wavelength-polarization image to different spatial positions. In our recent proof-of-principle experiment, better performance than ever of this technique is confirmed by giving six frames with ~3 ps temporal resolution and ~30 lp/mm spatial resolution.
The spiculation sign is one of the main signs to distinguish benign and malignant pulmonary nodules. In order to effectively extract the image feature of a pulmonary nodule for the spiculation sign distinguishment, a new spiculation sign recognition model is proposed based on the doctors’ diagnosis process of pulmonary nodules. A maximum density projection model is established to fuse the local three-dimensional information into the two-dimensional image. The complete boundary of a pulmonary nodule is extracted by the improved Snake model, which can take full advantage of the parallel calculation of the Spike Neural P Systems to build a new neural network structure. In this paper, our experiments show that the proposed algorithm can accurately extract the boundary of a pulmonary nodule and effectively improve the recognition rate of the spiculation sign.
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