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Colony size and morphology influence the vertical migration capacity of Microcystis and therewith the occurrence of surface accumulations or blooms. To explore the influence of wind-induced turbulence on the colony size and morphology of Microcystis in field conditions, a high-frequency field investigation was conducted in an enclosure in Meiliang Bay, Lake Taihu, China, from 26 August to 7 September 2012. A Pearson's correlation analysis indicated that the in situ growth rate of Microcystis was negatively related to surface cell density and positively related to wind speed. Strong wind speed stimulated Microcystis growth by enhancing light transmission due to the homodispersion of Microcystis in the water column. The Microcystis colony size was negatively correlated with wind speed, suggesting that wind-induced turbulence could break up colonies in shallow lakes. The results indicated that Microcystis colonies could be broken up by a turbulence intensity of 2.33×10-5 m2/s3, which corresponds to an average wind speed of 5.00 m/s in a reservoir with 30-m depth. Different Microcystis morphotypes were present and negative relationships were detected between the proportion of Microcystis ichthyoblabe and the proportion of Microcystis wesenbergii and between the proportion of Microcystis aeruginosa and the proportion of Microcystis wesenbergii out of all Microcystis throughout the water column, but more evidence is need to support the hypothesis that the morphology of Microcystis colonies changes over time. Altogether, the results suggest that declining wind speed, driven by climate change, will promote surface blooms of Microcystis due to the formation of larger colonies.

A real-time detection and tracking method of landmark based for UAV visual navigation and fixed landing was proposed. This method used the SVM classification algorithm to train the offline classifier based on SURF-BoW features extracted from samples, which can recognize the landing landmark accurately and complete the initialization of the tracker. Afterwards, tracked the landmark via the improved median flow algorithm to ensure the reliability and integrity of the tracking target. Finally, based on the classifier and the principle of similarity between two adjacent frames' target, this paper designed a target re-search algorithm to ensure that the target can be retrieved quickly even if the target is lost or the target tracking fails, which makes the entire set of algorithm track the target accurately for a long time. The experimental results show that the proposed algorithm has good tracking performance under the conditions of the change of target scale, illumination changes and motion blur.

Difficulties in advanced dewatering of dewatered sludge hinder sludge reduction and resource utilization. L-DME (liquified dimethyl ether) has been recently used for dewatering, but the effect of organic matter dissolution using L-DME during desorption and dehydration on water removal is not clear. In this study, dewatered sludge from urban sewage treatment plants was used to conduct experiments in sequencing dissolution-separation reactors. The changes in the dehydration rate, bound water and various organic matter levels at different times, L-DME additions, and the temperature were measured. The results show that L-DME can remove 90% of water, 100% of lipids, and 8-12% of organic matter in dewatered sludge. L-DME was mixed with the semi-like colloidal sludge, and high separation of water was achieved by mixing the L-DME with water and dissolving the hydrophilic organic matter to convert the solid-like into a two-phase (solid and liquid) substance, which can be easily separated. The dissolution of hydrophilic organic matter such as polysaccharides and proteins by L-DME promotes the conversion of bound water into free water, which is key to total water removal.