5 resultados para Missing values

em Greenwich Academic Literature Archive - UK


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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.

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The Symposium, “Towards the sustainable use of Europe’s forests”, with sub-title “Forest ecosystem and landscape research: scientific challenges and opportunities” lists three fundamental substantive areas of research that are involved: Forest management and practices, Ecosystem processes and functional ecology, and Environmental economics and sociology. This paper argues that there are essential catalytic elements missing! Without these elements there is great danger that the aimed-for world leadership in the forest sciences will not materialize. What are the missing elements? All the sciences, and in particular biology, environmental sciences, sociology, economics, and forestry have evolved so that they include good scientific methodology. Good methodology is imperative in both the design and analysis of research studies, the management of research data, and in the interpretation of research finding. The methodological disciplines of Statistics, Modelling and Informatics (“SMI”) are crucial elements in a proposed Centre of European Forest Science, and the full involvement of professionals in these methodological disciplines is needed if the research of the Centre is to be world-class. Distributed Virtual Institute (DVI) for Statistics, Modelling and Informatics in Forestry and the Environment (SMIFE) is a consortium with the aim of providing world-class methodological support and collaboration to European research in the areas of Forestry and the Environment. It is suggested that DVI: SMIFE should be a formal partner in the proposed Centre for European Forest Science.

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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.

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This chapter focuses on what the key decision makers in organizations decide after having received information on the current state of the organizational performance. Because of strong attributions to success and failure, it is impossible to predict in advance which concrete actions will occur. We can however find out what kinds of actions are decided upon by means of an organizational learning model that focuses on the hastenings and delays after performance feedback. As an illustration, the responses to performance signals by trainers and club owners in Dutch soccer clubs are analyzed.