天然食用色素的多元线性模型和神经网络模型的配色效果比较

目的 探讨胸腹主动脉瘤(TAAA)患者行全胸腹主动脉替换术(tTAAAR)的临床疗效及术后并发症。方法 回顾性分析2010年4月至2019年4月期间本院收治的14例行开放手术治疗的TAAA患者,11例为Crawford Ⅱ型,3例为Crawford Ⅲ型。男12例,女2例,年龄28～54岁,平均(36.1±7.1)岁。手术方式4例采用传统深低温体外循环tTAAAR,10例采用改良常温非体外循环tTAAAR。传统方式于深低温体外循环下建立动静脉通路进行体外转流,改良方式在常温非体外循环下建立降主动脉-髂动脉旁路循环。结果 14例患者均完成手术。降主动脉阻断时间为(22.2±9.6)min；脊髓缺血时间为(23.0±7.3)min。术后早期死亡2例,急性肾功能不全4例,双下肢截瘫3例,肺部感染4例,一过性脑功能障碍4例。1例患者术中行脾切除术,1例患者术后行气管切开术。结论 开放性行tTAAAR是一种相对安全、有效的手术方式,是目前针对部分复杂TAAA的有效治疗手段。

Comparison of Color Matching Between Multivariate Linear Model and Neural Network Model of Natural Food Pigments

Natural food pigments are widely used, and trichromatic pigments can be mixed with different colors according to their concentrations. Traditional color matching methods are highly dependent on experience of color matching, which result in low production efficiency, big variation and poor product quality stability. In this study, according to the characteristic absorption peak of natural food pigments had no change during mixing, and based on the matching method of absorption spectrum, color matching models of multiple linear and neural network were established between the concentration of pigments and the absorption value of the characteristic absorption peak. And the optimal model was selected and tested by errors analysis. The results showed that the prediction accuracy and stability of neural network model were better than those in multivariate linear model, and the color differences between the prediction formula and the original formula were within 3, which could not be distinguished by naked eyes. Thus the neural network models were more suitable for color matching requirements. These results provided theoretical basis for the intelligent color matching of natural food pigments.