Spectral Graph Convolutions for Population-based Disease Prediction

Exploiting the wealth of imaging and non-imaging information for disease prediction tasks requires models capable of representing, at the same time, individual features as well as data associations between subjects from potentially large populations. Graphs provide a natural framework for such tasks, yet previous graph-based approaches focus on pairwise similarities without modelling the subjects' individual characteristics and features. On the other hand, relying solely on subject-specific imaging feature vectors fails to model the interaction and similarity between subjects, which can reduce performance. In this paper, we introduce the novel concept of Graph Convolutional Networks (GCN) for brain analysis in populations, combining imaging and non-imaging data. We represent populations as a sparse graph where its vertices are associated with image-based feature vectors and the edges encode phenotypic information. This structure was used to train a GCN model on partially labelled graphs, aiming to infer the classes of unlabelled nodes from the node features and pairwise associations between subjects. We demonstrate the potential of the method on the challenging ADNI and ABIDE databases, as a proof of concept of the benefit from integrating contextual information in classification tasks. This has a clear impact on the quality of the predictions, leading to 69.5% accuracy for ABIDE (outperforming the current state of the art of 66.8%) and 77% for ADNI for prediction of MCI conversion, significantly outperforming standard linear classifiers where only individual features are considered.Comment: International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI) 201

Maximising the impact of careers services on career management skills: a review of the literature

The review identified an international body of work on the development and implementation of competency frameworks in reaction to CMS, including the ‘Blueprint’ frameworks, which are a series of inter-related national approaches to career management skills (originating in the USA and taken up subsequently, and with different emphases, by Canada, Australia, England and Scotland). There is, as yet, little empirical evidence to support the overall efficacy of CMS frameworks, but they have the advantage of setting out what needs to be learned (usually as a clear and identifiable list of skills, attributes and attitudes) and, often, how this learning is intended to happen. The international literature emphasised the iterative nature and mixture of formal and informal learning and life experiences that people needed to develop CMS. It suggested that, though there was no single intervention or group of interventions that appeared most effective in increasing CMS, there were five underpinning components of career guidance interventions that substantially increased effectiveness, particularly when combined. These included the use of narrative/writing approaches; the importance of providing a ‘safe’ environment; the quality of the adviser-client relationship; the need for flexibility in approach; the provision of specialist information and support; and clarity on the purpose and aims of action planning. The review also identified a possible emergent hierarchy around the efficacy of different modes of delivery of career guidance interventions on CMS development. Interventions involving practitioner contact and structured groups appeared more effective than self-directed interventions or unstructured groups. Computer-based interventions were found to work better when practitioner input was provided during the intervention or when they were followed up by a structured workshop session to discuss and review the results.Skills Funding Agenc

The hunt for submarines in classical art: mappings between scientific invention and artistic interpretation

This is a report to the AHRC's ICT in Arts and Humanities Research Programme. This report stems from a project which aimed to produce a series of mappings between advanced imaging information and communications technologies (ICT) and needs within visual arts research. A secondary aim was to demonstrate the feasibility of a structured approach to establishing such mappings. The project was carried out over 2006, from January to December, by the visual arts centre of the Arts and Humanities Data Service (AHDS Visual Arts).1 It was funded by the Arts and Humanities Research Council (AHRC) as one of the Strategy Projects run under the aegis of its ICT in Arts and Humanities Research programme. The programme, which runs from October 2003 until September 2008, aims ‘to develop, promote and monitor the AHRC’s ICT strategy, and to build capacity nation-wide in the use of ICT for arts and humanities research’.2 As part of this, the Strategy Projects were intended to contribute to the programme in two ways: knowledge-gathering projects would inform the programme’s Fundamental Strategic Review of ICT, conducted for the AHRC in the second half of 2006, focusing ‘on critical strategic issues such as e-science and peer-review of digital resources’. Resource-development projects would ‘build tools and resources of broad relevance across the range of the AHRC’s academic subject disciplines’.3 This project fell into the knowledge-gathering strand. The project ran under the leadership of Dr Mike Pringle, Director, AHDS Visual Arts, and the day-to-day management of Polly Christie, Projects Manager, AHDS Visual Arts. The research was carried out by Dr Rupert Shepherd

Maximising the impact of careers services on career management skills: a review of the literature

The review identified an international body of work on the development and implementation of competency frameworks in reaction to CMS, including the ‘Blueprint’ frameworks, which are a series of inter-related national approaches to career management skills (originating in the USA and taken up subsequently, and with different emphases, by Canada, Australia, England and Scotland). There is, as yet, little empirical evidence to support the overall efficacy of CMS frameworks, but they have the advantage of setting out what needs to be learned (usually as a clear and identifiable list of skills, attributes and attitudes) and, often, how this learning is intended to happen. The international literature emphasised the iterative nature and mixture of formal and informal learning and life experiences that people needed to develop CMS. It suggested that, though there was no single intervention or group of interventions that appeared most effective in increasing CMS, there were five underpinning components of career guidance interventions that substantially increased effectiveness, particularly when combined. These included the use of narrative/writing approaches; the importance of providing a ‘safe’ environment; the quality of the adviser-client relationship; the need for flexibility in approach; the provision of specialist information and support; and clarity on the purpose and aims of action planning. The review also identified a possible emergent hierarchy around the efficacy of different modes of delivery of career guidance interventions on CMS development. Interventions involving practitioner contact and structured groups appeared more effective than self-directed interventions or unstructured groups. Computer-based interventions were found to work better when practitioner input was provided during the intervention or when they were followed up by a structured workshop session to discuss and review the results.Skills Funding Agenc

Challenges arising from alternative investment management.

Alternative investment management differs from traditional asset management in a number of respects. First, it is distinct in terms of both its targets – aiming to achieve an absolute performance, regardless of trends in underlying markets – and its strategies, in particular exploiting inefficiencies in the valuation of financial assets via opportunistic and discretionary positions. It also differs in terms of the financial techniques implemented, e.g. the extensive use made of leverage, derivatives and short selling, and the specific investment vehicles used (ad hoc structures such as hedge funds that are not bound by ordinary law in the way traditional investment vehicles are). These particularities, alongside the fact that the alternative investment universe is somewhat opaque, make it difficult to measure a fund’s risks or a fund manager’s performance. Specific measurement tools are therefore required, which differ from those commonly used in traditional asset management. Over the past few years, the alternative investment management, a diverse and rapidly-evolving universe, has enjoyed a spectacular development, which is illustrated by the sharp rise in the amounts under management and the proliferation of investment vehicles offered to an increasingly broad investor base. In view of the specific nature of alternative fund managers’ modus operandi, the flourishing of the alternative investment industry raises questions as to its implications in terms of financial stability. It also raises new issues regarding the division of roles between market participants and supervisory authorities in the organisation and monitoring of this asset management sector.

Case study based approach to integration of sustainable design analysis, performance and building information modelling

This paper presents a case study based research of both the method and technology for integration of sustainable design analysis (SDA) and building information modelling (BIM) within smart built environments (SBE). Level 3 BIM federation and integration challenges are recognised and improvements suggested, including issues with combining geometry and managing attribute data. The research defines SDA as rapid and quantifiable analysis of diverse sustainable alternatives and ‘what if’ scenarios posed by a design team and client during the early stages of the project, where the benefits of correct decisions can significantly exceed the actual investment required. The SDA concept and BIM integration findings are explained through a convergence from conceptualisation to calculation stages, emphasising the importance of an iterative over a linear approach. The approach allowed for a multitude of “what if” scenarios to be analysed, leading to more informed sustainable solutions at the right stages of the project development, with a generally lower level of detail (LOD) and computational/modelling effort required. In addition, the final stage of Building Regulations Part L compliance calculations was reached with a lot greater level of certainty, in terms of its requirements. Finally, a strategy for long term performance monitoring and evaluation of the building design in terms of its environmental sustainability is presented, via integration between BIM and SBE (Smart Built Environment) technologies