Since the operation of the Three Gorges Reservoir, its tributaries have been eutrophic and flooded many times, the prompt and accurate eutrophication assessment is the foundation of water environmental management for this area. To address the problems existing in the fuzzy comprehensive evaluation, a novel method is proposed to adjust the indicator weight by using the analytic hierarchy process–entropy weight method, improve the fuzzy operation method, and take the weighted average as the basis of comprehensive evaluation. Through this method, the information of each indicator can be comprehensively used, and the subjectivity and blindness of evaluation can be effectively reduced. Then the eutrophication status of Hanfeng Lake is analyzed by it, and compares the results with that of conventional methods. The results show that Hanfeng lake is greatly affected by TN and TP, and it is generally in mesotrophic to mildly eutrophication. Eutrophication degree is as follows: Nanhe River > Donghe River > Regulating dam, so the control measures should be strengthened in Nanhe area. Combined with the water pollution control measures proposed in this paper, it can provide guidance for the monitoring and treatment of eutrophication in the Three Gorges Reservoir area and ensure the safety of the water environment. Practitioner points This paper proposes to use the analytic hierarchy process–entropy weight method combined with the fuzzy operation method to assess the eutrophication status of tributaries of the Three Gorges Reservoir, in China. The results indicate that Hanfeng Lake is generally in a light eutrophication state, which is greatly affected by TN and TP, and the Nanhe River is in a relatively high degree of eutrophication, which need to be extra vigilant. The evaluation results are more conformable to reality than that of the traditional fuzzy comprehensive evaluation, which can provide guidance for comprehensive management of eutrophication.

Correlation filter (CF)-based tracking algorithms is most popular in recent years due to its high accuracy and impressive speed. However, it has some intrinsically drawbacks such as margin suppression, sensitive for disturbance, and partial occlusions. Contrasted with CF drawbacks, the advantages of particle filter (PF) tracking algorithm include robustness, motion prediction, and wide detection range. Therefore, it can amend some CF tracker drawbacks. On the other hand, the HOG feature is widely used in CF tracker because it can detect the target precision position.However, this kind of feature is rotation-variation, which is invalid for rotation transformation target. On the contrary, the tracker precision merely based on colour feature is rough, but colour feature is rotation invariation and is effective for rotating target; therefore, these two features are complementary. In this paper, we integrate both trackers (CF and PF) to learn the HOG and colour feature, respectively, experiments demonstrate this tracking algorithm is more robust, and the tracking precision is more accurate. This algorithm is integrated with some classic CF trackers (KCF, SAMF, and MOSSE) framework and benchmark them against their baseline. On the OTB2015 benchmark datasets, experiment result demonstrates OPE performance grades have improved from about 1% to 12%; SRE Performance grades have improved from about 1.3% to 5.8%.

Batch production of continuous and uniform graphene films is critical for the application of graphene. Chemical vapor deposition (CVD) has shown great promise for mass producing high-quality graphene films. However, the critical factors affected the uniformity of graphene films during the batch production need to be further studied. Herein, we propose a method for batch production of uniform graphene films by controlling the gaseous carbon source to be uniformly distributed near the substrate surface. By designing the growth space of graphene into a rectangular channel structure, we adjusted the velocity of feedstock gas flow to be uniformly distributed in the channel, which is critical for uniform graphene growth. The monolayer graphene film grown inside the rectangular channel structure shows high uniformity with average sheet resistance of 345 Ω sq−1 without doping. The experimental and simulation results show that the placement of the substrates during batch growth of graphene films will greatly affect the distribution of gas-phase dynamics near the substrate surface and the growth process of graphene. Uniform graphene films with large-scale can be prepared in batches by adjusting the distribution of gas-phase dynamics.

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