The preparation and characterization of seven-coordinate tin(IV) complexes of the 2,6-diacetylpyridine Schiff bases of S-alkyl/aryl-dithiocarbazates and the X-ray crystal structure of the [Sn(dapsme)I-2] complex (dapsme=doubly deprotonated form of the 2,6

New tin(IV) complexes of empirical formula, Sn(SNNNS)I-2 (SNNNS = anionic form of the 2,6-diacetylpyridine Schiff bases of S-methyl- or S-benzyldithiocarbazate) have been prepared and characterized by a variety of physico-chemical techniques. The structure of Sn(dapsme)I-2 has been determined by single crystal X-ray crystallographic structural analysis. The complex has a seven-coordinate distorted pentagonal-bipyramidal geometry with the Schiff base coordinated to the tin(IV) ion as a dinegatively charged pentadentate chelating agent via the pyridine nitrogen atom, the two azomethine nitrogen atoms and the two thiolate sulfur atoms. The ligand occupies the equatorial plane and the iodo ligands are coordinated to the tin(IV) ion at axial positions. The distortion from an ideal pentagonal bipyramidal geometry is attributed to the restricted bite size of the pentadentate ligands. (C) 2004 Elsevier Ltd. All rights reserved.

A general-purpose tunable landscape generator

The research literature on metalieuristic and evolutionary computation has proposed a large number of algorithms for the solution of challenging real-world optimization problems. It is often not possible to study theoretically the performance of these algorithms unless significant assumptions are made on either the algorithm itself or the problems to which it is applied, or both. As a consequence, metalieuristics are typically evaluated empirically using a set of test problems. Unfortunately, relatively little attention has been given to the development of methodologies and tools for the large-scale empirical evaluation and/or comparison of metaheuristics. In this paper, we propose a landscape (test-problem) generator that can be used to generate optimization problem instances for continuous, bound-constrained optimization problems. The landscape generator is parameterized by a small number of parameters, and the values of these parameters have a direct and intuitive interpretation in terms of the geometric features of the landscapes that they produce. An experimental space is defined over algorithms and problems, via a tuple of parameters for any specified algorithm and problem class (here determined by the landscape generator). An experiment is then clearly specified as a point in this space, in a way that is analogous to other areas of experimental algorithmics, and more generally in experimental design. Experimental results are presented, demonstrating the use of the landscape generator. In particular, we analyze some simple, continuous estimation of distribution algorithms, and gain new insights into the behavior of these algorithms using the landscape generator.

Leading coordinate analysis of reaction pathways in proton chain transfer: Application to a two-proton transfer model for the green fluorescent protein

The ‘leading coordinate’ approach to computing an approximate reaction pathway, with subsequent determination of the true minimum energy profile, is applied to a two-proton chain transfer model based on the chromophore and its surrounding moieties within the green fluorescent protein (GFP). Using an ab initio quantum chemical method, a number of different relaxed energy profiles are found for several plausible guesses at leading coordinates. The results obtained for different trial leading coordinates are rationalized through the calculation of a two-dimensional relaxed potential energy surface (PES) for the system. Analysis of the 2-D relaxed PES reveals that two of the trial pathways are entirely spurious, while two others contain useful information and can be used to furnish starting points for successful saddle-point searches. Implications for selection of trial leading coordinates in this class of proton chain transfer reactions are discussed, and a simple diagnostic function is proposed for revealing whether or not a relaxed pathway based on a trial leading coordinate is likely to furnish useful information.

Coordinate activation of intracellular signaling pathways by insulin-like growth factor-1 and platelet-derived growth factor in rat hepatic stellate cells

Proliferation of activated hepatic stellate cells (HSC) is an important event in the development of hepatic fibrosis. Insulin-like growth factor-1 (IGF-1) has been shown to be mitogenic for HSC, but the intracellular signaling pathways involved have not been fully characterized. Thus, the aims of the current study were to examine the roles of the extracellular signal-regulated kinase (ERK), phosphatidylinositol 3-kinase (P13-K) and p70-S6 kinase (p70-S6-K) signaling pathways in IGF-1- and platelet-derived growth factor (PDGF)-induced mitogenic signaling of HSC and to examine the potential crosstalk between these pathways. Both IGF-1 and PDGF increased ERK, P13-K and p70-S6-K activity. When evaluating potential crosstalk between these signaling pathways, we observed that P13-K is required for p70-S6-K activation by IGF-1 and PDGF, and is partially responsible for PDGF-induced ERK activation. PDGF and IGF-1 also increased the levels of cyclin D1 and phospho-glycogen synthase kinase-30. Coordinate activation of ERK, P13-K and p70-S6-K is important for perpetuating the activated state of HSC during fibrogenesis.

On building a principled framework for evaluating and testing evolutionary algorithms: A continuous landscape generator

In this paper, we address some issue related to evaluating and testing evolutionary algorithms. A landscape generator based on Gaussian functions is proposed for generating a variety of continuous landscapes as fitness functions. Through some initial experiments, we illustrate the usefulness of this landscape generator in testing evolutionary algorithms.