With the development of the PCR technology, especially the improvement of its reagent and a method of pebrine detection by PCR in infected Bombyx mori eggs was established.With the 16sRNA gene of Nosema bombycis as target sequence, the results of extraction of genomic DNA from purified microspores showed that 1.3×10-7µg DNA can be extracted from each spore. The sensitivity detection showed the detection limit of Nosema bombycis DNA was 3.25×10-2pg, i.e. 4 spores. (PCR system volume is 25µl). The method of total DNA extraction from pebrine infected silkworm eggs just before hatching was created. The result showed that extracting total DNA from silkworm eggs after the eggs had been treated with 30% KOH met the PCR detection requirements. The result of application study showed the spores in the pebrine infected egg just before hatching can sensitively be found with PCR. The result of a group of eggs just before hatching detection showed that the maximum PCR detection level was of a pebrine infected eggs just before hatching in 300 healthy eggs when the total DNA extraction had been purified with Agarose electrophoresis. The probability of identifying groups of one pebrine spore in infected eggs just before hatching mixed with 100 healthy ones was about 80%.
Droplet size distribution of dispersed oil in deep-water is critical to the transport and biodegradation of spilled oil in deep-sea. Few studies have focused on the effects of pressure on chemically dispersed oil through experiments. This study thus simulated how the crude oil homogenously pre-dispersed by Corexit 9500A using baffled flasks would behave after being exposed to deep-water conditions. Key factors included dispersant-to-oil ratio (DOR), mixing energy (energy dissipation rate and Kolmogorov microscale), and pressure (up to 150 bar). The variations of pressure were demonstrated to have insignificant effects on the size distribution of pre-dispersed oil. Both the average and medium droplet sizes were correlated negatively with DOR and mixing energy in an established model with a p-value 0.0011. The log-normal and log-logistic distributions provided a reasonable fit to simulate the droplet size distribution. The two parameters of log-logistic distribution were dependent on DOR and mixing energy with a p-value < 0.005. The results would be valuable to advance the understanding of the behaviours and trajectories of chemically dispersed oil under deep-water conditions. The research helped provide more scientific evidence to improve the understanding of dispersed oil behaviours under high pressure and support deep-sea oil spill research and potential extension of the existing results from shallow water to deep water conditions.
Most existing real-time data compressing algorithms are focused on dynamic and inconstancy of the process data, but a basic observation is ignored with some unexpectedness: on condition that sampling interval is not large, difference between amplitudes of real-time process data from two neighboring samples is relatively small, and most of data amplitudes are in the same range. In this paper we propose a compression algorithm based on the observation and experimentally evaluate the proposed approach and demonstrate that our algorithm is promising and efficient.
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