Adaptive Scalable SVD Unit for Fast Processing of Large LSE Problems

Singular Value Decomposition (SVD) is a key linear algebraic operation in many scientific and engineering applications. In particular, many computational intelligence systems rely on machine learning methods involving high dimensionality datasets that have to be fast processed for real-time adaptability. In this paper we describe a practical FPGA (Field Programmable Gate Array) implementation of a SVD processor for accelerating the solution of large LSE problems. The design approach has been comprehensive, from the algorithmic refinement to the numerical analysis to the customization for an efficient hardware realization. The processing scheme rests on an adaptive vector rotation evaluator for error regularization that enhances convergence speed with no penalty on the solution accuracy. The proposed architecture, which follows a data transfer scheme, is scalable and based on the interconnection of simple rotations units, which allows for a trade-off between occupied area and processing acceleration in the final implementation. This permits the SVD processor to be implemented both on low-cost and highend FPGAs, according to the final application requirements.

Managing and resisting ‘degeneration’ in employee-owned businesses: a comparative study of two large retailers in Spain and the UK

Employee-owned businesses have recently enjoyed a resurgence of interest as possible ‘alternatives’ to the somewhat tarnished image of conventional investor-owned capitalist firms. Within the context of global economic crisis, such alternatives seem newly attractive. This is somewhat ironic because, for more than a century, academic literature on employee-owned businesses has been dominated by the ‘degeneration thesis’. This suggested that these businesses tend towards failure – they either fail commercially, or they relinquish their democratic characters. Bucking this trend and offering a beacon - especially in the UK - has been the commercially successful, co-owned enterprise of the John Lewis Partnership (JLP) whose virtues have seemingly been rewarded with favourable and sustainable outcomes. This paper makes comparisons between JLP and its Spanish equivalent Eroski – the supermarket group which is part of the Mondragon cooperatives. The contribution of this paper is to examine in a comparative way how the managers in JLP and Eroski have constructed and accomplished their alternative scenarios. Using longitudinal data and detailed interviews with senior managers in both enterprises it explores the ways in which two large, employee-owned, enterprises reconcile apparently conflicting principles and objectives. The paper thus puts some new flesh on the ‘regeneration thesis’.

Energetics and Structural Characterization of the large-scale Functional Motion of Adenylate Kinase

Adenylate Kinase (AK) is a signal transducing protein that regulates cellular energy homeostasis balancing between different conformations. An alteration of its activity can lead to severe pathologies such as heart failure, cancer and neurodegenerative diseases. A comprehensive elucidation of the large-scale conformational motions that rule the functional mechanism of this enzyme is of great value to guide rationally the development of new medications. Here using a metadynamics-based computational protocol we elucidate the thermodynamics and structural properties underlying the AK functional transitions. The free energy estimation of the conformational motions of the enzyme allows characterizing the sequence of events that regulate its action. We reveal the atomistic details of the most relevant enzyme states, identifying residues such as Arg119 and Lys13, which play a key role during the conformational transitions and represent druggable spots to design enzyme inhibitors. Our study offers tools that open new areas of investigation on large-scale motion in proteins.