Extraction behavior of nickel(II) using some of the BTBP-class ligands

Recently the BTBP-family of solvating ligands have been studied for their ability to separate trivalent actinides from lanthanides. Five of the BTBPs were evaluated for their ability to extract nickel(II) from aqueous nitrate media into cyclohexanone. It was shown by both solvent extraction and X-ray diffraction experiments that the BTBPs are capable of forming both 1: 1 and 1:2 complexes with nickel(II). When the BTBP concentration is low the nickel distribution ratio is governed by the formation of the nickel/BTBP complex while at higher BTBP concentrations the partitioning of the nickel complex between the two phases dictates the nickel distribution ratio.

A new class of ammonium ylid for [2,3]-sigmatropic rearrangement reactions: ene-endo-spiro ylids

The first examples of sigmatropic rearrangements of ene-endo-spirocyclic, tetrahydropyridine-derived ammonium ylids are reported. Thus, spiro[6.7]-ylids rearrange primarily by a [2,3]-pathway, whereas the analogous [6.6]-ylids rearrange by [1,2]- and [2,3]-mechanisms in roughly equal proportions. This method serves as a rapid entry to the core of a range of alkaloids bearing a pyrrolo[1,2-a]azepine or octahydroindolizidine nucleus.

Synthesis of a novel class of chiral polyaromatic amide dendrimers bearing an amino acid derived C-3-symmetric core

Chiral polyaromatic amide dendrimers incorporating a C-3-core have been prepared as potential catalysts for asymmetric reactions. (C) 2002 Elsevier Science Ltd. All rights reserved.

Exploring the construction of social class in educational discourse: the rational order of the nation state versus global uncertainties

This article aims to create intellectual space in which issues of social inequality and education can be analyzed and discussed in relation to the multifaceted and multi-levelled complexities of the modern world. It is divided into three sections. Section One locates the concept of social class in the context of the modern nation state during the period after the Second World War. Focusing particularly on the impact of 'Fordism' on social organization and cultural relations, it revisits the articulation of social justice issues in the United Kingdom, and the structures put into place at the time to alleviate educational and social inequalities. Section Two problematizes the traditional concept of social class in relation to economic, technological and sociocultural changes that have taken place around the world since the mid-1980s. In particular, it charts some of the changes to the international labour market and global patterns of consumption, and their collective impact on the re-constitution of class boundaries in 'developed countries'. This is juxtaposed with some of the major social effects of neo-classical economic policies in recent years on the sociocultural base in developing countries. It discusses some of the ways these inequalities are reflected in education. Section Three explores tensions between the educational ideals of the 'knowledge economy' and the discursive range of social inequalities that are emerging within and beyond the nation state. Drawing on key motifs identified throughout, the article concludes with a reassessment of the concept of social class within the global cultural economy. This is discussed in relation to some of the major equity and human rights issues in education today.

Diheteroarylmethyl substituted titanocenes: a novel class of possible anti-cancer drugs

From the reaction of tert-butyl lithium or n-butyl lithium with N-methylpyrrole (1a), furan (1b) or 2-bromo-thiophen (1c), 2-N-methylpyrrolyl lithium (2a), 2-furyl lithium (2b) or 2-thiophenyl lithium (2c), respectively, was obtained. When reacted with 6-(2-N-methylpyrrolyl) fulvene (3a), 6-(2-furyl) fulvene (3b) or 6-(2-thiophenyl) fulvene (3c), the corresponding lithiated intermediates were formed (4a-c). Titanocenes (5a-c) were obtained through transmetallation with titanium tetrachloride. When these titanocenes were tested against pig kidney epithelial (LLC-PK) cells, inhibitory concentrations (IC50) of 32 mu M, 140 mu M, and 240 mu M, respectively, were observed. These values represent improved cytotoxicity against LLC-PK, compared to their ansa-analogues. (c) 2006 Elsevier B.V. All rights reserved.

Improvement of classification accuracy for stochastic discrimination - Multi-class classification

In this paper, an improved stochastic discrimination (SD) is introduced to reduce the error rate of the standard SD in the context of multi-class classification problem. The learning procedure of the improved SD consists of two stages. In the first stage, a standard SD, but with shorter learning period is carried out to identify an important space where all the misclassified samples are located. In the second stage, the standard SD is modified by (i) restricting sampling in the important space; and (ii) introducing a new discriminant function for samples in the important space. It is shown by mathematical derivation that the new discriminant function has the same mean, but smaller variance than that of standard SD for samples in the important space. It is also analyzed that the smaller the variance of the discriminant function, the lower the error rate of the classifier. Consequently, the proposed improved SD improves standard SD by its capability of achieving higher classification accuracy. Illustrative examples axe provided to demonstrate the effectiveness of the proposed improved SD.

Kernel classifier construction using orthogonal forward selection and boosting with Fisher ratio class separability measure

A greedy technique is proposed to construct parsimonious kernel classifiers using the orthogonal forward selection method and boosting based on Fisher ratio for class separability measure. Unlike most kernel classification methods, which restrict kernel means to the training input data and use a fixed common variance for all the kernel terms, the proposed technique can tune both the mean vector and diagonal covariance matrix of individual kernel by incrementally maximizing Fisher ratio for class separability measure. An efficient weighted optimization method is developed based on boosting to append kernels one by one in an orthogonal forward selection procedure. Experimental results obtained using this construction technique demonstrate that it offers a viable alternative to the existing state-of-the-art kernel modeling methods for constructing sparse Gaussian radial basis function network classifiers. that generalize well.

Complexity of Monte Carlo algorithms for a class of integral equations

In this work we study the computational complexity of a class of grid Monte Carlo algorithms for integral equations. The idea of the algorithms consists in an approximation of the integral equation by a system of algebraic equations. Then the Markov chain iterative Monte Carlo is used to solve the system. The assumption here is that the corresponding Neumann series for the iterative matrix does not necessarily converge or converges slowly. We use a special technique to accelerate the convergence. An estimate of the computational complexity of Monte Carlo algorithm using the considered approach is obtained. The estimate of the complexity is compared with the corresponding quantity for the complexity of the grid-free Monte Carlo algorithm. The conditions under which the class of grid Monte Carlo algorithms is more efficient are given.

A kernel-based two-class classifier for imbalanced data sets

Many kernel classifier construction algorithms adopt classification accuracy as performance metrics in model evaluation. Moreover, equal weighting is often applied to each data sample in parameter estimation. These modeling practices often become problematic if the data sets are imbalanced. We present a kernel classifier construction algorithm using orthogonal forward selection (OFS) in order to optimize the model generalization for imbalanced two-class data sets. This kernel classifier identification algorithm is based on a new regularized orthogonal weighted least squares (ROWLS) estimator and the model selection criterion of maximal leave-one-out area under curve (LOO-AUC) of the receiver operating characteristics (ROCs). It is shown that, owing to the orthogonalization procedure, the LOO-AUC can be calculated via an analytic formula based on the new regularized orthogonal weighted least squares parameter estimator, without actually splitting the estimation data set. The proposed algorithm can achieve minimal computational expense via a set of forward recursive updating formula in searching model terms with maximal incremental LOO-AUC value. Numerical examples are used to demonstrate the efficacy of the algorithm.

Global asymptotic stability in a class of Putnam-type equations

In this paper, we initiate the study of a class of Putnam-type equation of the form x(n-1) = A(1)x(n) + A(2)x(n-1) + A(3)x(n-2)x(n-3) + A(4)/B(1)x(n)x(n-1) + B(2)x(n-2) + B(3)x(n-3) + B-4 n = 0, 1, 2,..., where A(1), A(2), A(3), A(4), B-1, B-2, B-3, B-4 are positive constants with A(1) + A(2) + A(3) + A(4) = B-1 + B-2 + B-3 + B-4, x(-3), x(-2), x(-1), x(0) are positive numbers. A sufficient condition is given for the global asymptotic stability of the equilibrium point c = 1 of such equations. (c) 2005 Elsevier Ltd. All rights reserved.

Global exponential periodicity of a class of bidirectional associative memory networks with finite distributed delays

In this paper, we study the periodic oscillatory behavior of a class of bidirectional associative memory (BAM) networks with finite distributed delays. A set of criteria are proposed for determining global exponential periodicity of the proposed BAM networks, which assume neither differentiability nor monotonicity of the activation function of each neuron. In addition, our criteria are easily checkable. (c) 2005 Elsevier Inc. All rights reserved.

Global exponential periodicity of a class of neural networks with recent-history distributed delays

In this paper, we propose to study a class of neural networks with recent-history distributed delays. A sufficient condition is derived for the global exponential periodicity of the proposed neural networks, which has the advantage that it assumes neither the differentiability nor monotonicity of the activation function of each neuron nor the symmetry of the feedback matrix or delayed feedback matrix. Our criterion is shown to be valid by applying it to an illustrative system. (c) 2005 Elsevier Ltd. All rights reserved.