pKa values of aqua ligands of platinum (II) anticancer complexes: [1H, 15N] and 195Pt NMR Studies of cis- and trans- [PtCl2 (NH3) (Cyclohexylamine)]

Syntheses and NMR studies are reported of two 15N-labelled Pt(II) complexes of anticancer interest: cis-PtCl2(15NH3)(c-C6H1115NH2), a metabolite of the orally-active Pt(IV) complex cis,trans,cis-[PtCl2(acetate)2(c-C6H11NH2)(NH3), and trans-[PtCl2(15NH3)(c-C6H1115NH2), a reduction product of the active Pt(IV) complex trans,trans,trans-[PtCl2(OH)2(c-C6H11NH2). For cis-[PtCl2(15NH3)(c-C6H1115NH2), hydrolysis was faster for the chloride ligand trans to cyclohexylamine, and the pKa values determined by [1H, 15N NMR spectroscopy for the two cis monoaqua isomers were the same (6.73). The trans monoaqua complex was a stronger acid with pKa of 5.4 (determined by 195Pt NMR). For the cis diaqua complex, pKa values of 5.68 and 7.68 were determined.

Statistical analysis of extreme forest fires

Forest fires can cause extensive damage to natural resources and properties. They can also destroy wildlife habitat, affect the forest ecosystem and threaten human lives. In this paper extreme wildland fires are analysed using a point process model for extremes. The model based on a generalised Pareto distribution is used to model data on acres of wildland burnt by extreme fire in the US since 1825. A semi-parametric smoothing approach is adapted with maximum likelihood method to estimate model parameters.

Semi-Parametric Analysis of Extreme Forest Fires

Forest fires can cause extensive damage to natural resources and properties. They can also destroy wildlife habitat, affect the forest ecosystem and threaten human lives. In this paper incidences of extreme wildland fires are modelled by a point process model which incorporates time-trend. A model based on a generalised Pareto distribution is used to model data on acres of wildland burnt by extreme fire in the US since 1825. A semi-parametric smoothing approach, which is very useful in exploratory analysis of changes in extremes, is illustrated with the maximum likelihood method to estimate model parameters.

Case based adaptation using interpolation over nominal values

In this paper we propose a method for interpolation over a set of retrieved cases in the adaptation phase of the case-based reasoning cycle. The method has two advantages over traditional systems: the first is that it can predict “new” instances, not yet present in the case base; the second is that it can predict solutions not present in the retrieval set. The method is a generalisation of Shepard’s Interpolation method, formulated as the minimisation of an error function defined in terms of distance metrics in the solution and problem spaces. We term the retrieval algorithm the Generalised Shepard Nearest Neighbour (GSNN) method. A novel aspect of GSNN is that it provides a general method for interpolation over nominal solution domains. The method is illustrated in the paper with reference to the Irises classification problem. It is evaluated with reference to a simulated nominal value test problem, and to a benchmark case base from the travel domain. The algorithm is shown to out-perform conventional nearest neighbour methods on these problems. Finally, GSNN is shown to improve in efficiency when used in conjunction with a diverse retrieval algorithm.

Extreme weather events and business continuity planning

There is now a broad scientific consensus that the global climate is changing in ways that are likely to have a profound impact on human society and the natural environment over the coming decades. The challenge for Facilities Mangers is to ensure that business continuity plans acknowledge the potential for such events and have contingencies in place to ensure that their organisation can recover from an extreme weather event in a timely fashion. This paper will review current literature/theories pertinent to extreme weather events and business continuity planning; will consider issues of risk; identify the key drivers that need to be considered by Facilities Managers in preparing contingency/disaster recover plans; and identify gaps in knowledge (understanding and toolkits) that need to be addressed. The paper will also briefly outline a 3 year research project underway in the UK to address the issues