The ‘Brain Drain’ Academic and Skilled Migration to the UK and its Impacts on Africa

In December 2004 the Association of University Teachers and the College and Lecturers Union NATFHE jointly commissioned research to review some of the literature on ‘the Brain Drain’ with a specific emphasis on developing countries in Africa and on academic labour in the UK. This report is the culmination of that research. The project aimed to review some of the available literature on the ‘Brain Drain’, to locate this in debates and contemporary approaches to international development and to consider especially the impact of the Brain Drain on Africa, where possible drawing reference to the impact on higher education. The report also considers the scale of migration to work in UK higher education and suggests ways in which AUT/NATFHE might work together and with others to offset the impact of Brain Drain factors and to build the capacity of higher education, and those working in it, in developing countries. Migration is an emotive issue and debate in this country is often shaped by populist and right-wing arguments, sometimes with racist and xenophobic undertones. This project aimed to develop a more progressive approach to the debate on migration, explicitly addressing the motivations behind migration decisions. This project was shaped by a background understanding that the UK undoubtedly benefits enormously from skilled labour migration, economically, socially and culturally. However, the project is also shaped by a concern to ensure that individual choices to migrate are taken freely, not as a result of political repression, a lack of life chances or vocational opportunities. The project also aimed to assess the extent to which skilled labour migration, and the unequal relationships between rich and developing countries which drives it, is further embedding that inequality. Failing to address these issues, risks leaving the debate on migration to those that seek to use the issue to generate a regressive and dangerous politics of fear and difference

Managing Development: EU and African Relations through the evolution of the Lomé and Cotonou Agreements

The relationship between the European Union 1 and Africa has been formalised since the beginning of the European integration project in the evolving Yaoundé, Lomé and now Cotonou Agreements. The relationship has shifted in line with the emerging global framework for neoliberal accumulation. This shift has involved the re-designing’ of developmental strategies and their ‘locking-in’ in the long term. Theoretically, this global shift in the organisation of both production and social relations (including popular understandings) has been well documented and the changing dominant patterns of production in advanced industrial economies has been highlighted at length. However, this article aims to develop further the idea of ‘locking-in’, outlined in the work of Stephen Gill, and to place an increased emphasis on the phenomena of both re-designing and locking-in as they apply to the alteration of developmental strategies in Less Developed Countries (LDCs), among which those in Africa have suffered from extreme marginalisation and exploitation. This article reveals the often ignored role of the EU in this process. It argues that the EU, through its institutionalised link with Africa, has played a key role in re-designing developmental strategies to complement the global shift to neoliberal accumulation which, in its latest phase, is aimed particularly at the complex, multifaceted and increasingly integrated project to ‘lock-in’ the gains of capital over labour on a global scale. The article begins with a brief introduction to the complementary projects of ‘re-designing’ and ‘locking-in’ before considering these against the historical evolution of the Lomé and Cotonou relationship

Constrained Hyperbolic Divergence Cleaning for Smoothed Particle Magnetohydrodynamics

We present a constrained formulation of Dedner et al's hyperbolic/parabolic divergence cleaning scheme for enforcing the \nabla\dot B = 0 constraint in Smoothed Particle Magnetohydrodynamics (SPMHD) simulations. The constraint we impose is that energy removed must either be conserved or dissipated, such that the scheme is guaranteed to decrease the overall magnetic energy. This is shown to require use of conjugate numerical operators for evaluating \nabla\dot B and \nabla{\psi} in the SPMHD cleaning equations. The resulting scheme is shown to be stable at density jumps and free boundaries, in contrast to an earlier implementation by Price & Monaghan (2005). Optimal values of the damping parameter are found to be {\sigma} = 0.2-0.3 in 2D and {\sigma} = 0.8-1.2 in 3D. With these parameters, our constrained Hamiltonian formulation is found to provide an effective means of enforcing the divergence constraint in SPMHD, typically maintaining average values of h |\nabla\dot B| / |B| to 0.1-1%, up to an order of magnitude better than artificial resistivity without the associated dissipation in the physical field. Furthermore, when applied to realistic, 3D simulations we find an improvement of up to two orders of magnitude in momentum conservation with a corresponding improvement in numerical stability at essentially zero additional computational expense.Comment: 28 pages, 25 figures, accepted to J. Comput. Phys. Movies at http://www.youtube.com/playlist?list=PL215D649FD0BDA466 v2: fixed inverted figs 1,4,6, and several color bar

Improving announcement media for technical reports

Computer and photographic printing and publishing methods for announcing technical report literatur

The introduction of microfiche for disseminating technical information in the United States

Development of microfiche for disseminating technical informatio

A Cluster Elastic Net for Multivariate Regression

We propose a method for estimating coefficients in multivariate regression when there is a clustering structure to the response variables. The proposed method includes a fusion penalty, to shrink the difference in fitted values from responses in the same cluster, and an L1 penalty for simultaneous variable selection and estimation. The method can be used when the grouping structure of the response variables is known or unknown. When the clustering structure is unknown the method will simultaneously estimate the clusters of the response and the regression coefficients. Theoretical results are presented for the penalized least squares case, including asymptotic results allowing for p >> n. We extend our method to the setting where the responses are binomial variables. We propose a coordinate descent algorithm for both the normal and binomial likelihood, which can easily be extended to other generalized linear model (GLM) settings. Simulations and data examples from business operations and genomics are presented to show the merits of both the least squares and binomial methods.Comment: 37 Pages, 11 Figure