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By comparing the original particle gradation of sediment from the Three Gorges Reservoir with the single particle gradation, the differences in these two particle gradations showed that there is sediment flocculation in the Three Gorges Reservoir, which can accelerate the sediment deposition rate in the reservoir. In order to determine the influence of flocculation on the sediment settling velocity, sediment was collected at the Three Gorges Reservoir, and the indoor quiescent settling experiment was performed to study the mechanism of sediment flocculation. The experimental results showed that sediments aggregated from single particles into floccules in the settling processes. The single particles smaller than 0.022 mm will participate in the formation of floccules, which accounts for 83% of the total amount of sediment in the Three Gorges Reservoir. Moreover, the degree of sediment flocculation and the increase in sediment settling velocity were directly proportional to the sediment concentration. Taking the average particle size and the median particle size as the representative particle size, respectively, the maximum flocculation factors were calculated to be 3.4 and 5.0. Due to the sediment flocculation, the volume of sediment deposition will increase by 66% when the mass settling flux factor of total sediment had a maximum value of 1.66, suggesting that flocculation has a significant influence on the sediment deposition rate in the Three Gorges Reservoir.

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a b s t r a c tWater resource shortage has become one of the main factors restricting the rapid economic and social development of mankind, how limited water resources reasonable allocation to various users, protection of life and production, ecological water safety is facing an important problem in various countries. Water resources optimal scheduling problem also has a wide range of application space, which involves cost control and optimization of design expertise. The shortest flow path problem, as a well-known NP-complete problem and one of famous water resources optimal scheduling problem, has attracted the attention of many scholars. In this paper, we use a new parallel algorithm to solve the problem by basic DNA molecular operations. We reasonably design DNA chains that characterize cities and paths, take appropriate biological operations and get solutions of the task scheduling problem in proper length range with O(n 2 ) time complexity. The ability of biological manipulation in the algorithm helps us better understand DNA computing, and can be widely used to solve more complex problems.

The maximal matching problem (MMP) is to find maximal edge subsets in a given undirected graph, that no pair of edges are adjacent in the subsets. It is a vitally important NP-complete problem in graph theory and applied mathematics, having numerous real life applications in optimal combination and linear programming fields. It can be difficultly solved by the electronic computer in exponential level time. Meanwhile in previous studies deoxyribonucleic acid (DNA) molecular operations usually were used to solve NP-complete continuous path search problems, e.g. HPP, traveling salesman problem, rarely for NP-hard problems with discrete vertices or edges solutions, such as the minimum vertex cover problem, graph coloring problem and so on. In this paper, we present a DNA algorithm for solving the MMP with DNA molecular operations. For an undirected graph with [Formula: see text] vertices and [Formula: see text] edges, we reasonably design fixed length DNA strands representing vertices and edges of the graph, take appropriate steps and get the solutions of the MMP in proper length range using [Formula: see text] time. We extend the application of DNA molecular operations and simultaneously simplify the complexity of the computation.

The shortage of freshwater resources is a serious problem in the process of urbanization in the world, and even become the main constraint factor in some areas. In order to solve the problem, it is imperative to develop an effective, flexible and low-cost water resources management plan. Water resources optimal allocation is one of the hot topics in the field of water resources at present, such as water resources optimal k-edge cover problem. The k-edge cover problem aims to find an edge cover set with k edges in a given undirected graph. The efficient solution of this problem can play an important role in planning and setting up urban water resources network sites. Based on DNA molecular computing, the paper use a new parallel algorithm to solve k-edge cover problem with O(n 2) time complexity, which greatly simplifies the computing complexity.

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