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专色的准确预测是包装印刷领域的重要技术之一。为了得到更加准确的专色配方, 提高专色配色精度, 提出了一种结合最小二乘法和增强天牛须搜索算法的专色配方预测方法, 并利用吸光度来解决专色配方的预测问题。研究了高透光特性PET薄膜的光谱模型, 并构建了吸收光谱机理模型; 提出了增强天牛须搜索算法, 在传统天牛须搜索算法的基础上, 引入突变概率项和方向修正项, 提升算法的搜索能力和收敛速度; 利用最小二乘法优化配色色域空间, 降低基色搜索维度, 提高寻优效率。应用所提出的增强天牛须搜索算法求解各基色比例, 预测专色配方, 并与传统天牛须算法、粒子群算法和蚁群算法进行比较, 验证所提方法在专色预测方面的有效性和优越性。研究结果表明, 所提方法与现有的3种方法相比, 具有更高的精度, 原有专色和预测专色之间色差均小于3, 且90%的色差小于1, 40%的色差小于0.1, 所提方法对于提高专色油墨的配色精度具有显著效果, 可准确地预测专色配方。

Liver ischemia‐reperfusion (I/R) injury is a common cause of organ failure, developed by a sudden block in the blood and oxygen supply and subsequent restoration. I/R damage is responsible for acute and chronic rejection after organ transplantation, accounting for 10% of early graft failure. The study investigated the therapeutic properties of fangchinoline in liver injury‐induced rats. The rats were divided into three groups: Sham, I/R without pretreatment, and I/R + 10 mg/kg fangchinoline pretreatment. Blood and liver samples were collected for assays, and an in silico docking analysis was conducted to determine fangchinoline's inhibitory effect. The pretreatment with 10 mg/kg of fangchinoline effectively reduced hepatic marker enzymes such as AST, LDH, and ALT in the serum of rats with liver I/R damage. Fangchinoline treatment significantly reduced interleukin‐8 (IL‐8), IL‐6, and tumor necrosis factor‐α (TNF‐α) in I/R‐induced rats, boosting antioxidants and decreasing MDA. Histopathological studies showed liver injury protection, and fangchinoline inhibited TNF‐α and IL‐6 with improved binding affinity. Fangchinoline has hepatoprotective properties by reducing inflammation in rats with liver I/R damage, as demonstrated in the current study. Hence, it can be an effective salutary agent in preventing liver damage caused by I/R. [ABSTRACT FROM AUTHOR]

The slowly-stored and quickly-released system was studied to explore the method of optimizing the hydrodynamic force of rivers in arid regions and reveal its effect on water quality.The south-west tributary of Xi'an moat was defined as the study area.A hydrodynamic force-water quality coupling model of the moat was built based on the collected data of current water quality and hydrodynamic force by using MIKE21.In the coupling model,the impounding gate was designed based on the dam body of the moat to simulate the scouring and silting capacity of the lower reaches caused by rapid discharge from the upper reaches of the channel.The influence law of rapid discharge at different water levels and water quality conditions on hydrodynamics and water quality of the moat was studied.The numerical simulation results from MIKE21 show that water level has a significant influence on the hydrodynamic force,and water quality has a significant influence on the pollutant concentration.The simulation results of the hydrodynamic force-water quality coupling model of the moat show that the working condition with a 1-meter water level and class Ⅲ inlet water quality can greatly improve the water quality and hydrodynamic force of Xi'an moat.By using the water reaching the standard of the class Ⅲ inlet water quality as the supply source,the water quality of Xi'an moat can be effectively improved by enhancing the hydrodynamic force of the moat.

【Objective】 Water scarcity hinders agricultural production in many countries, and how to rationally allocate water resources for irrigation is hence important to make the most of the limited water resources in areas such as northern and northwest China where water is scarce. The purpose of this paper is to present an optimization method to rationalize regional water allocation for irrigation. 【Method】 We constructed a two-stage optimization model considering plant structure in one layer and plant irrigation in another layer. The principle of system decomposition and coordination were used to allocate the water resources to different irrigation areas. The first layer of the optimization model was to analyze the effect of irrigation time and irrigation scheduling on economic return, and the second layer was to calculate its consequence for the effect of ecological benefits. We applied the model to the Wuquan irrigation district at Baojixia in Shannxi province, with the optimization solved by the non-dominant genetic algorithm. 【Result】 ①The optimization model considering irrigation amount and irrigation time can improve the economic benefits. ②In the plant structure layer, adding the ecological benefits to the optimization objective reduced economic benefits but the overall optimized benefits were still significantly higher than the economic benefits obtained without considering the ecological benefits. ③Considering the improved ecological benefits, the optimized results considering the ecological benefits improved 23.5% of the overall return compared with those obtained without considering them. 【Conclusion】 Optimization of water resource allocation for irrigation should consider both economic and ecological benefits in the second layer, and the irrigation amount and irrigation time in the first layer. The optimization model we proposed in this paper can help make most of water resources for irrigation in regions where water is scarce such as northwestern China.

Spot color is widely applied to printing and packing in modern industry, which can satisfy the individualization requirements and express the emotion of products. Color prediction is the core technique for spot color restoration. In this paper, a method that combines the least squares method and gravitation search algorithm is proposed to address the color prediction by using the absorption spectrum. Firstly, the spectral transmittance of the thin film with high transmission and low reflectance characteristics is researched to find the absorbance. Secondly, the least squares method is used to ascertain the primary colors of the spot color. Thirdly, an enhanced quantum gravitation search algorithm is designed to predict the spot color. The predicted results on the 30 spot colors show that the proposed method has higher accuracy in comparison with the three existed methods. The color differences between the prepared spot colors and the reproduced spot colors are all less than 3, in which 75% of the color differences are less 1 and 35% of the color differences are less 0.1. All the results confirm that the proposed method can predict the spot color accurately. [ABSTRACT FROM AUTHOR]