Bioactive compounds in rye flours with different extraction rates

Rye flours with extraction rate of 100% (wholemeal flour), 95% (brown flour), 90% (brown flour) and 70% (light flour) were prepared in order to study the relation between flour extraction rates and content of bioactive compounds. The following compounds were analysed: total phenolic compounds (TPC), total flavonoids (TF), inositol hexaphosphate (IP6), reduced (GSH) and oxidized (GSSG) glutathione, tocopherols (T) and tocotrienols (T3). The reduced/oxidized glutathione status (GSH/GSSG) of the flours was examined as a potential index of flour resistance against oxidative stress. The following observations were made in relation to the flour extraction rates and bioactive compounds contents: (a) milling process caused decrease in content in TPC, TF, IP6, GSH and GSSG, T and T3, (b) the most resistant against oxidation processes were suggested a brown flours, then light and finally wholemeal flour, (c) the ratio of tocotrienols to tocopherols (T3/T) was the highest in rye flours with extraction rate of 100–90% whereas light flour was the poorest source of tocopherols and tocotrienols. The provided data support current trend to increase number of rye products from wholemeal or brown flours.     

大豆蛋白分离工艺研究

阐述了大豆蛋白质的分离原理,分析了运用“碱提酸沉”分离法提取大豆蛋白质过程中,豆粕的粉碎方式、浸提温度、浸提时间、浸提液的pH值以及离心工艺对提取效果的影响,为大豆蛋白／聚丙烯腈纤维的工业化生产提供了依据。     

炼厂碱渣处理工艺及设计优化

针对催化裂化装置汽油和液态烃精制产生的含硫废弃物的碱渣处理，讨论了碱渣提酚、碱渣湿式氧化脱臭两种处理工艺的环境治理效果，并就碱渣湿式氧化脱臭工艺如何降低运行成本、减少污水排放等内容进行了探讨。     

应用溶剂萃取处理金泥的新技术

用溶剂萃取法代替目前广泛使用的金泥处理方法，可以节约资源，降低成本，提高金的回收率，还能回收金泥中的银，产品金的纯度在９９．９％以上；连续作业，操作方便，大大减轻劳动强度和改善工作条件，而且便于自动化操作管理，是一种社会，环境，经济三种效益都佳的成熟技术，应大力推广应用。     

闪光X光噪声图象的局部统计滤波

本文介绍一种噪声图象的滤波方法 ,它不需要先验的图象模型 ,而且也不会损伤边界和细小的细节 ,在相加性和相乘性噪声的情况下 ,计算与边界方向有关的子集的局部平均值和方差 ,相应地沿着边界方向的噪声就被去掉 ,同时对边界有一定的增强效果     

超临界流体络合萃取镧系和锕系元素的研究进展

超临界流体络合萃取是1种可用于萃取金属离子的新型分离技术，它应用于乏燃料后处理和核废物处理中的最大优点是能大幅减少二次废物的产生。文章主要介绍超临界流体的特点、超临界流体络合萃取的基本原理及其影响因素，并对超临界流体络合萃取镧系和锕系元素的研究进展及其在乏燃料后处理工艺研究中的应用进行综述。     

Target differentiation with simple infrared sensors using statistical pattern recognition techniques

This study compares the performances of various statistical pattern recognition techniques for the differentiation of commonly encountered features in indoor environments, possibly with different surface properties, using simple infrared (IR) sensors. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting feature in a way that cannot be represented by a simple analytical relationship, therefore complicating the differentiation process. We construct feature vectors based on the parameters of angular IR intensity scans from different targets to determine their geometry and/or surface type. Mixture of normals classifier with three components correctly differentiates three types of geometries with different surface properties, resulting in the best performance (100%) in geometry differentiation. Parametric differentiation correctly identifies six different surface types of the same planar geometry, resulting in the best surface differentiation rate (100%). However, this rate is not maintained with the inclusion of more surfaces. The results indicate that the geometrical properties of the targets are more distinctive than their surface properties, and surface recognition is the limiting factor in differentiation. The results demonstrate that simple IR sensors, when coupled with appropriate processing and recognition techniques, can be used to extract substantially more information than such devices are commonly employed for.     

The S-kernel: A measure of symmetry of objects

In this paper we introduce a new symmetry feature named “symmetry kernel” (SK) to support a measure of symmetry. Given any symmetry transform S, SK of a pattern P is the maximal included symmetric sub-set of P for all directions and shifts. We provide a first algorithm to exhibit this kernel where the centre of symmetry is assumed to be the centre of mass. Then we prove that, in any direction, the optimal axis corresponds to the maximal correlation of a pattern with its symmetric version. That leads to a second algorithm. The associated symmetry measure is a modified difference between the respective surfaces of a pattern and its kernel. A series of experiments supports the actual algorithm validation.     

Comparison among feature extraction methods for HIV-1 protease cleavage site prediction

Recently, several works have approached the HIV-1 protease specificity problem by applying a number of methods from the field of machine learning. However, it is still difficult for researchers to choose the best method due to the lack of an effective comparison. For the first time we have made an extensive study on methods for feature extraction for the problem of HIV-1 protease. We show that a fusion of classifiers trained in different feature spaces permits to obtain a drastically error reduction with respect to the performance of the state-of-the-art.