Foreground removal from CMB temperature maps using an MLP neural network

One of the main obstacles in extracting the Cosmic Microwave Background (CMB) signal from observations in the mm-submm range is the foreground contamination by emission from galactic components: mainly synchrotron, free-free and thermal dust emission. Due to the statistical nature of the intrinsic CMB signal it is essential to minimize the systematic errors in the CMB temperature determinations. Following the available knowledge of the spectral behavior of the galactic foregrounds simple, power law-like spectra have been assumed. The feasibility of using a simple neural network for extracting the CMB temperature signal from the combined CMB and foreground signals has been investigated. As a specific example, we have analysed simulated data, like that expected from the ESA Planck Surveyor mission. A simple multilayer perceptron neural network with 2 hidden layers can provide temperature estimates, over more than 80 percent of the sky, that are to a high degree uncorrelated with the foreground signals. A single network will be able to cover the dynamic range of the Planck noise level over the entire sky.Comment: Accepted for publication in Astrophysics and Space Scienc

Never mind the quality, take a seat!

This paper considers whether lecturers delivering Business Higher Education Programmes (BHEPs) in Further Education Colleges (FECs) in the UK see education to be a production industry, or a knowledge industry. It will consider the effects of managerialism and marketisation that the UK government (and others around the world), are applying to the education sector, and their possible effects. The study considers the narratives of twenty-six lecturers delivering BHEPs in FECs in relation to government intervention, and the impacts it may be having on their role as a lecturer. The research highlights that there may be a great deal of frustration and angst amongst these lecturers, and from this, suggests that colleges may be behaving more like production factories, rather than institutions of further and higher education

PEGASO: Towards a Life Companion

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Engaging patients, clinicians and health funders in weight management: the Counterweight Programme

Background. The Counterweight Programme provides an evidence based and effective approach for weight management in routine primary care. Uptake of the programme has been variable for practices and patients. Aim. To explore key barriers and facilitators of practice and patient engagement in the Counterweight Programme and to describe key strategies used to address barriers in the wider implementation of this weight management programme in UK primary care. Methods. All seven weight management advisers participated in a focus group. In-depth interviews were conducted with purposeful samples of GPs (n = 7) and practice nurses (n = 15) from 11 practices out of the 65 participating in the programme. A total of 37 patients participated through a mixture of in-depth interviews (n = 18) and three focus groups. Interviews and focus groups were analysed for key themes that emerged. Results. Engagement of practice staff was influenced by clinicians’ beliefs and attitudes, factors relating to the way the programme was initiated and implemented, the programme content and organizational/contextual factors. Patient engagement was influenced by practice endorsement of the programme, clear understanding of programme goals, structured proactive follow-up and perception of positive outcomes. Conclusions. Having a clear understanding of programme goals and expectations, enhancing self-efficacy in weight management and providing proactive follow-up is important for engaging both practices and patients. The widespread integration of weight management programmes into routine primary care is likely to require supportive public policy