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The first three reports in this series (Parts I, II and III) deals with binders and technologies used in stabilisation/ solidification (S/S) practice and research in the UK. This first part covers 'basic principles'while the second covers 'research' and the third 'applications'. The purpose of this work, which forms part of the Network STARNET on stabilisation/solidification treatment and remediation, is to identify the knowledge gaps and future research needs in this field. This paper describes the details and basic principles of available binders and technologies in the UK. The introduction in the report includes background on S/S, legislation aspects, overview of STARNET and its activities and details of commonly used binder selection criteria. The report is then divided into two main sections. The first covers binders and includes cement, blastfurnace slag, pulverised fuel ash, lime, natural and organophilic clays, bitumen, waste binders and concludes with proprietary binders. The second part details implementation processes for S/S treatment systems starting with ex-situ treatment systems, such as plant processing, direct mixing and in-drum processing and finishes with in-situ treatment processes, such as mechanical mixing and pressure mixing. © 2005 Taylor & Francis Group.

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To maximize the utility of high land cost in urban development, underground space is commonly exploited, both to reduce the load acting on the ground and to increase the space available. The execution of underground constructions requires the use of appropriate retaining wall and bracing systems. Inadequate support systems have always been a major concern, as any excessive ground movement induced during excavation could cause damage to neighboring structures, resulting in delays, disputes and cost overruns. Experimental findings on the effect of wall stiffness, depth of the stiff stratum away from the wall toe and wall toe fixity condition are presented and discussed. © 2012 Taylor & Francis Group.

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In this paper, we adopt a differential-geometry viewpoint to tackle the problem of learning a distance online. As this problem can be cast into the estimation of a fixed-rank positive semidefinite (PSD) matrix, we develop algorithms that exploits the rich geometry structure of the set of fixed-rank PSD matrices. We propose a method which separately updates the subspace of the matrix and its projection onto that subspace. A proper weighting of the two iterations enables to continuously interpolate between the problem of learning a subspace and learning a distance when the subspace is fixed. © 2009 IEEE.

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Spatial normalisation is a key element of statistical parametric mapping and related techniques for analysing cohort statistics on voxel arrays and surfaces. The normalisation process involves aligning each individual specimen to a template using some sort of registration algorithm. Any misregistration will result in data being mapped onto the template at the wrong location. At best, this will introduce spatial imprecision into the subsequent statistical analysis. At worst, when the misregistration varies systematically with a covariate of interest, it may lead to false statistical inference. Since misregistration generally depends on the specimen's shape, we investigate here the effect of allowing for shape as a confound in the statistical analysis, with shape represented by the dominant modes of variation observed in the cohort. In a series of experiments on synthetic surface data, we demonstrate how allowing for shape can reveal true effects that were previously masked by systematic misregistration, and also guard against misinterpreting systematic misregistration as a true effect. We introduce some heuristics for disentangling misregistration effects from true effects, and demonstrate the approach's practical utility in a case study of the cortical bone distribution in 268 human femurs.