Soil conditioning under London

The CTRL Contract 220 covered 7.5km twin-bore tunnels excavated between late 2002 and early 2004 from Stratford Box to St Pancras station in Central London. To ensure efficient machine operation as well as the transport and disposal of soil, soil conditioning treatments were applied. Specifically, the foam injection ratio (FIR) and the polymer injection ratio (PIR) (injected volume of foam and polymer solution expressed as a percentage of the excavated soil volume) were employed. It was found that carefully selected soil conditioning allowed chamber pressures of 200kPa or more to be accurately controlled in the stiff London Clay and to an extent, in the very stiff clays of the Lambeth Group. Average FIRs of 50% and PIRs of 7 and 9% were used in the Thanet Sand and in the Lambeth Group Clays. In contrast, much lower quantities of foam were used in the London Clay.

The role of adaptive thermal comfort in the prediction of the thermal performance of a modern mixed-mode office building in the UK under climate change

Climate change is becoming a serious issue for the construction industry, since the time scales at which climate change takes place can be expected to show a true impact on the thermal performance of buildings and HVAC systems. In predicting this future building performance by means of building simulation, the underlying assumptions regarding thermal comfort conditions and the related heating, ventilating and air conditioning (HVAC) control set points become important. This article studies the thermal performance of a reference office building with mixedmode ventilation in the UK, using static and adaptive thermal approaches, for a series of time horizons (2020, 2050 and 2080). Results demonstrate the importance of the implementation of adaptive thermal comfort models, and underpin the case for its use in climate change impact studies. Adaptive thermal comfort can also be used by building designers to make buildings more resilient towards change. © 2010 International Building Performance Simulation Association (IBPSA).

The Place of Philosophy in Management

Our purpose is to not to define a particular philosophy of management, but rather to demonstrate some of the ways in which philosophy – ethics, metaphysics, epistemology, logic and æsthetics – contributes to the practice of management. We identify a number of contemporary management questions, procedures or issues where the application of philosophical approaches are relevant, and show how philosophical skills, an understanding of philosophical principles or exposure to philosophical discussion can contribute to improved management practice. In some ways the paper is a report on progress in the quest begun by Nigel Laurie and Christopher Cherry in the first issue of Philosophy of Management, formerly Reason in Practice (2001) when they asked why philosophers have interested themselves so little in the entire field of management. We include some examples where philosophers have written about management, some where managers have shown the direct impact of philosophy on management effectiveness and some where potential remains. In much we see links to process philosophy, and to the need for conversation and reflection by and between managers and philosophers. This does not of itself show how philosophy can contribute to management education. A brief final section discusses the way in which moral creativity skills can be developed through reflection, and describes how this has been done in the Manufacturing Leaders’ Programme at the Institute for Manufacturing at Cambridge and in the International Management Ethics & Values course taught to undergraduate management students in Adelaide, Singapore and Hong Kong. This will be taken up in a subsequent paper.

Bayesian Active Learning for Classification and Preference Learning

Information theoretic active learning has been widely studied for probabilistic models. For simple regression an optimal myopic policy is easily tractable. However, for other tasks and with more complex models, such as classification with nonparametric models, the optimal solution is harder to compute. Current approaches make approximations to achieve tractability. We propose an approach that expresses information gain in terms of predictive entropies, and apply this method to the Gaussian Process Classifier (GPC). Our approach makes minimal approximations to the full information theoretic objective. Our experimental performance compares favourably to many popular active learning algorithms, and has equal or lower computational complexity. We compare well to decision theoretic approaches also, which are privy to more information and require much more computational time. Secondly, by developing further a reformulation of binary preference learning to a classification problem, we extend our algorithm to Gaussian Process preference learning.

Contingency awareness in human aversive conditioning involves the middle frontal gyrus.

In contrast to the wealth of data describing the neural mechanisms underlying classical conditioning, we know remarkably little about the mechanisms involved in acquisition of explicit contingency awareness. Subjects variably acquire contingency awareness in classical conditioning paradigms, in which they are able to describe the temporal relationship between a conditioned cue and its outcome. Previous studies have implicated the hippocampus and prefrontal cortex in the acquisition of explicit knowledge, although their specific roles remain unclear. We used functional magnetic resonance imaging to track the trial-by-trial acquisition of explicit knowledge in a concurrent trace and delay conditioning paradigm. We show that activity in bilateral middle frontal gyrus and parahippocampal gyrus correlates with the accuracy of explicit contingency awareness on each trial. In contrast, amygdala activation correlates with conditioned responses indexed by skin conductance responses (SCRs). These results demonstrate that brain regions known to be involved in other aspects of learning and memory also play a specific role, reflecting on each trial the acquisition and representation of contingency awareness.

Slowness and sparseness lead to place, head-direction, and spatial-view cells.

We present a model for the self-organized formation of place cells, head-direction cells, and spatial-view cells in the hippocampal formation based on unsupervised learning on quasi-natural visual stimuli. The model comprises a hierarchy of Slow Feature Analysis (SFA) nodes, which were recently shown to reproduce many properties of complex cells in the early visual system []. The system extracts a distributed grid-like representation of position and orientation, which is transcoded into a localized place-field, head-direction, or view representation, by sparse coding. The type of cells that develops depends solely on the relevant input statistics, i.e., the movement pattern of the simulated animal. The numerical simulations are complemented by a mathematical analysis that allows us to accurately predict the output of the top SFA layer.