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.     

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.     

双抽机组工况图的画法分析

双抽机组热-电负荷关系非常复杂，运行人员难于分配。介绍一种较精确的工况图画法，可以为电厂运行人员提供可靠的基础。     

Interfacial activity and rate of palladium(II) extraction with decyl pyridine monocarboxylates

Decyl isonicotiniate and decyl nicotiniate permit a rapid extraction of palladium(II) from its hydrochloride solutions. Decyl picoliniate is not a suitable extractant. 4-Octylphenylamine can act as a phase transfer catalyst when its concentration in the organic phase is at least 2·5 × 10^?4 M . It seems that the interfacial adsorption of pyridine carboxylates and of 4-octylphenylamine is not the decisive phenomenon in palladium(II) extraction. The negligible protonation of the pyridine-type extractants and the phase transfer catalysis explains well the quick extraction of palladium(II) with the commercial and highly hydrophobic extractant ACORGA CLX-50.     

微波高压提取快速测定饲料含氟量的探讨

采用微波高压制样技术,快速提取饲料中的氟元素,结合氟离子选择性电极标准添加和电位极差测试方法,能够快速、准确地测试饲料中的含氟量     

Cyanex有机膦类萃取剂在贵金属溶剂萃取中的研究和应用

介绍了近年来Cyanex有机膦类萃取剂在贵金属溶剂萃取中的研究状况及应用进展，展望了该类萃取剂在贵金属分离提取中的应用前景。     

Influence of solvents on extraction of U(Ⅵ) by N,N'-didecanoylpiperazine

Extraction behavior of N, N'-didecanoylpiperazine (DDPEZ) for U(Ⅵ)in a series of solvents from aqueous nitric acid media was investigated for the first time.The dependence of distribution ratios on the concentration of aqueous nitric acid.extractant and temperature has been discussed. The increasing sequence of extractiveability of DDPEZ is given: chloroform, carbon tetrachloride, dimethylbenzene, toluene,benzene.``     

钇、钪分离工艺的新进展

本文简要介绍中国科学院长春应用化学研究所近年来在钇、钪分离工艺研究方面的新进展。     

On-Line Shape recognition with incremental training using binary synaptic weights algorithm

Recognition of hand drawn shapes is beneficial in drawing packages and automated sketch entry in handheld computers. In this paper, we propose a new approach to on-line geometric shape recognition with incremental training function, which utilizes a heuristic function to reduce noise and a neural network for classification and on-line training. Instead of recognizing segments of a drawing and then performing syntactical analysis to match with a predefined shape, which is weak in terms of generalization and dealing with noise, we examine the shape as a whole. The main concept of the recognition method is derived from the fact that internal angles are very important in the perceived shape of outlines. Our application's aim is to recognize elliptic, rectangular, and triangular shapes in a way similar to human cognition of these shapes. Human beings recognize such basic shapes regardless of the variations in size, noise on the shape border, rotation and in the case of triangles, regardless of the type of the triangle. The key concept is that the neural network learns the relationships between the internal angles of a shape and its classification, therefore only a few training samples which represent the class of the shape are sufficient. Fast meremental training, which is performed on-line, is accomplished by the use of the Binary Synaptic Weights algorithm, a one pass, feedforward neural network training algorithm. Incremental training offers the advantage of adjusting the recognition capability of the system to the user's drawings. the results are very successful, such that the neural network correctly classified shapes that did not have any resemblance to the shapes in the initial training set.