Assessment of cracks in power plant components by means of the HIDA knowledge-based system (KBS)

An important integrating task in the framework of the HIDA project was the development and application of the knowledge-based system (KBS). The system enables to assess/predict cracks in high-temperature components of power plants operating under creep and/or fatigue conditions, according to the HIDA procedure developed through the other tasks of the project. The system encompasses a comprehensive material database comprising the proprieties of the materials tested within the HIDA project and which are necessary for the analysis. It also includes a library of different component geometries. The system is built in such a way that the data (e.g. material data, component geometry, etc.) necessary for a high temperature crack assessment can be directly entered by the user or selected from the existing databases within the KBS.The HIDA procedure has been integrated in the KBS in a modular sequence, each module enabling to undertake a step of calculation and/or analysis. This structure allows the user to either run the whole procedure or just perform one single step (e.g. check C^* values). In addition, new or alternative procedures can be used, either for the assessment as a whole, or just for single steps (e.g. C^*, 2-criteria diagram, etc.). The system was developed by MPA Stuttgart, as the HIDA KBS task leader, using ALIAS shell (ALIAS — advanced life assessment system) as a basis, and then tested and applied by industrial partners in the HIDA project.The paper describes the functionality and use of the system through reporting selected application cases (CT probe, pipes, pipe bends), and demonstrates the benefits/advantage of such system within the industry.     

（2期下）基于改进型软件锁相环的正负序分量分离新方法研究

针对电网不平衡时传统正负序分离方法通用性不佳的缺点,提出了一种基于改进型软件锁相环的正负序分量分离的新方法,它利用二阶广义积分器较好的高次滤波效果、正负序级联的DSC谐波消除特性,通过αβ变换和dq变换,再利用软件锁相环原理来锁定电网的频率,并反馈给二阶广义积分器和正负序级联的DSC,从而分离出电网的正负序分量。由于本方法在电网电压平衡、不平衡以及电网电压频率变化等电网所有可能发生的故障情况下,都可以快速而准确的分离电网的正负序的基波分量,从而可为电力电子变流器的控制系统提供可靠的控制信号。最后MATLAB/Simulink软件仿真结果证明了所提出方法的可行性和有效性。     

Effective Classification of Synovial Sarcoma Cancer Using Structure Features and Support Vectors

In this research work, we proposed a medical image analysis framework with two separate releases whether or not Synovial Sarcoma (SS) is the cell structure for cancer. Within this framework the histopathology images are decomposed into a third-level sub-band using a two-dimensional Discrete Wavelet Transform. Subsequently, the structure features (SFs) such as Principal Components Analysis (PCA), Independent Components Analysis (ICA) and Linear Discriminant Analysis (LDA) were extracted from this sub-band image representation with the distribution of wavelet coefficients. These SFs are used as inputs of the Support Vector Machine (SVM) classifier. Also, classification of PCA + SVM, ICA + SVM, and LDA + SVM with Radial Basis Function (RBF) kernel the efficiency of the process is differentiated and compared with the best classification results. Furthermore, data collected on the internet from various histopathological centres via the Internet of Things (IoT) are stored and shared on blockchain technology across a wide range of image distribution across secure data IoT devices. Due to this, the minimum and maximum values of the kernel parameter are adjusted and updated periodically for the purpose of industrial application in device calibration. Consequently, these resolutions are presented with an excellent example of a technique for training and testing the cancer cell structure prognosis methods in spindle shaped cell (SSC) histopathological imaging databases. The performance characteristics of cross-validation are evaluated with the help of the receiver operating characteristics (ROC) curve, and significant differences in classification performance between the techniques are analyzed. The combination of LDA + SVM technique has been proven to be essential for intelligent SS cancer detection in the future, and it offers excellent classification accuracy, sensitivity, specificity.     

外源成分对肉制品中杂环胺抑制效果的研究进展

杂环胺是一类由高蛋白类食品在高温烹调加工时产生的具有致癌和致突变性的有机物。肉制品加工过程中烧烤、卤煮、煎炸和油炸等多种热加工方式均可导致杂环胺的生成,通过添加外源成分抑制肉制品加工过程中杂环胺的形成是当前研究热点。本文重点对外源添加成分对不同加工方式肉制品杂环胺形成的抑制研究进行综述,并对其研究现状进行简要总结。     

三种红花油茶花营养成分分析及氨基酸评价

为了解红花油茶花的营养价值,以目前主要推广种植的浙江、腾冲、广宁3个红花油茶品种的花为原料,测定蛋白质、粗脂肪、总糖、还原糖、多糖、氨基酸、黄酮、多酚、花青素和维生素C等主要营养成分,并进行评价。结果表明:红花油茶花营养成分丰富,其中总糖、还原糖和多糖含量较高,分别为31%³7%、17%²6%和7.1%⁸.2%,蛋白质含量在3.2%³.6%之间;抗氧化成分含量较高,黄酮和多酚含量高达3000 mg/100 g以上,花青素为251⁴16 mg/100 g,维生素C为10²1 mg/100 g;3种红花油茶花营养成分的主成分分析显示,浙江红花、腾冲红花和广宁红花油茶花中营养成分综合评分分别为2.630、-0.428和2.032,说明浙江红花油茶花的营养价值较好。3种红花油茶花的氨基酸种类齐全、含量丰富,总量介于145.65¹71.72 mg/100 g之间,均含有7种以上人体必需氨基酸;浙江红花油茶花的氨基酸比值得分最高;腾冲红花油茶花的蛋白质消化利用率最高,且其味觉氨基酸比例最优。在既定的测定范围内,综合分析表明浙江红花油茶花的营养价值最好。      

不同生态区沙姆逊香料烟品质差异分析

对不同生态区沙姆逊香料烟化学成分和感官质量进行了分析,以期为筛选适宜产区和工业合理应用提供依据。结果表明,不同生态区沙姆逊香料烟化学成分差异明显,云南和四川沙姆逊香料烟总糖和还原糖含量显著高于浙江和土耳其,烟碱含量显著低于浙江和土耳其,而且四川与云南沙姆逊香料烟糖和烟碱含量差异也达到显著水平;云南沙姆逊烟叶具有较高含量的苹果酸和柠檬酸,浙江沙姆逊具有较高的草酸含量;土耳其AB 级香料烟草酸含量明显高于国内香料烟,非挥发性有机酸总量生态区间和品种间差异较大。烟叶感官质量浙江沙姆逊最好,云南次之,四川最低;国内沙姆逊香料烟中、上部烟叶感官质量总体低于土耳其AB 级烟叶。     

基于基质需求特征确立脱氮假单胞杆菌产维生素B12的发酵原料

对于工业化发酵而言,选择一种适宜的发酵原料对提高微生物发酵产量及降低发酵成本显得尤为重要.该文首先在合成培养基中考察了氨基酸对脱氮假单胞杆菌合成维生素B12的影响,结果表明谷氨酸等氨基酸对菌体生长和维生素B12合成具有较大的促进作用.甜菜糖蜜作为制糖工业的副产物,其成本相对低廉,但营养组分检测显示,甜菜糖蜜含有丰富的碳源和有机氮类物质,其中有机氮类又以谷氨酸居多,而且还含有一定量的合成维生素B12所必需的甲基供体甜菜碱.基于此,最终确立了以甜菜糖蜜作为维生素B12发酵的主要原料.在该原料下,脱氮假单胞杆菌摇瓶发酵结束时(168h)的菌体量(光密度)和维生素B12产量分别达到37.3mg/L和108.37mg/L.     

甘肃省陇东地区小米营养成分分析与综合评价

目的 探究甘肃省陇东地区小米营养成分含量差异,并对其营养品质进行综合评价。方法 以不同地理来源的小米样品为研究对象,对其矿物元素、脂肪酸组分和常规营养成分进行测定,采用方差分析、相关性分析、主成分分析(principal component analysis, PCA)和聚类分析(hierarchical cluster analysis, HCA)对小米营养品质进行分析与评价。结果 小米矿物元素含量丰富,矿物元素总量范围为5284.45～7004.24 mg/kg, 4种常量元素和6种微量元素含量在不同产地小米间差异显著(P<0.05)。小米中不饱和脂肪酸(unsaturated fatty acid,UFA)与饱和脂肪酸(saturated fatty acid, SFA)的比值(UFA/SFA)在5.88～13.82之间,优质脂肪比例较高。蛋白质、粗淀粉和粗脂肪含量分别在10.79～12.90 g/100 g、71.56%～74.24%、4.48%～5.69%之间,变异系数均小于10%,地区间差异不大。通过PCA共提取5个主成分,累计方差贡献率为89.04%。PCA综合评价...     

不同氨基酸和糖对美拉德反应产物的影响

利用半胱氨酸、甘氨酸、谷氨酸3 种氨基酸和木糖、葡萄糖2 种还原糖作为反应底物,模拟美拉德反应制备香精,并对其香气成分和有害物质进行综合分析。结果表明：参与反应的氨基酸种类越多,所测得的挥发性物质种数也越多,反应产物的风味越丰富;甘氨酸参与的美拉德反应中丙烯酰胺的生成量较少,而谷氨酸的参与反应中丙烯酰胺的生成量较多;还原糖种类对丙烯酰胺的产生影响不大;谷氨酸参与的美拉德反应产物中,5-羟甲基糠醛（5-hydroxymethylfurfural,5-HMF）含量高,而半胱氨酸和甘氨酸参与的反应产物中,5-HMF的含量较低;木糖可减少产物中的5-HMF的含量。利用本实验条件制备香精,产物中的丙烯酰胺和5-HMF含量在安全范围内。     

黄芪渣中国拟青霉固体培养及发酵产物分析

以黄芪渣培养冬虫夏草菌——中国拟青霉,研究固体发酵条件及发酵产物成分含量变化。结果表明:固体发酵的温度为20℃,培养基含水量60%,pH自然,氧气充足,无需光照条件下适宜生长,发酵时间为45 d。虫草黄芪粉粗多糖含量为10.32%,比黄芪废弃物中粗多糖含量增加47%;甘露醇含量为2.38%,比黄芪废弃物中甘露醇含量提高11.5倍;水溶蛋白含量为1.72%,比黄芪废弃物高2.80倍。