Fiscal decentralization and regional disparities: The importance of good governance

In this paper we consider how government quality mediates the relationship between fiscal decentralization and regional disparities. Previous work has argued that fiscal decentralization has the potential to reduce income differences across regions but that this potential may not be realized because of governance problems associated with sub-national authorities. Our empirical evidence based on a sample of 24 OECD countries over the period 1984 to 2006 lends a measure of support to this idea. We find that fiscal decentralization promotes regional convergence in high government quality settings but, worryingly, it leads to wider regional disparities in countries with poor governance.     

Chemical characterisation of natural organic substrates for biological mitigation of acid mine drainage

The current approach of the biological treatment of acid mine drainage by means of a passive remediation system involves the choice of an appropriate organic substrate as electron donor for sulphate reducers. Nowadays this selection is one of the critical steps in the performance of such treatment, as this depends to a great extent on the degradability of the organic substrate. Thus, a prior characterisation of the organic substrate predicting its biodegradability would be desirable before embarking on an extensive large-scale application. The aim of this study was to correlate the chemical composition (lignin content) of four different natural organic substrates (compost, sheep and poultry manures, oak leaf) and their capacity to sustain bacterial activity in an attempt to predict biodegradation from chemical characterisation. The results showed that the lower the content of lignin in the organic substrate, the higher its biodegradability and capacity for developing bacterial activity. Of the four organic materials, sheep and poultry manures and oak leaf evolved reducing conditions and sustained active sulphidogenesis, which coupled with the decrease in sulphate concentration indicated bacterial activity. Sheep manure was clearly the most successful organic material as electron donor (sulphate removal >99%), followed by poultry manure and oak leaf (sulphate removal of 80%). Compost appeared to be too poor in carbon to promote sulphate-reducing bacteria activity by itself. Column experiments emphasised the importance of considering the residence time as a key factor in the performance of continuous systems. With a residence time of 0.73 days, sheep manure did not promote sulphidogenesis. However, extending residence time to 2.4 and 9.0 days resulted in an increase in the sulphate removal to 18% and 27%, respectively.     

Superconducting Proximity Effects in Ferromagnet/Superconductor Heterostructures

We consider in this paper superconducting proximity effects in clean Ferromagnet/Ferromagnet/Superconductor (F1/F2/S) heterostructures. We make use of a numerical self-consistent solution of the microscopic Bogoliubov?Cde Gennes equations to investigate the superconducting transition temperatures as a function of the angle ?? between the magnetizations in the ferromagnetic layers. Unlike in F1/S/F2 trilayers, we find that the superconducting transition temperature is a nonmonotonic function of ??.     

Power generation efficiency analysis of offshore wind farms connected to a SLPC (single large power converter) operated with variable frequencies considering wake effects

This paper deals with the power generation efficiency analysis of a proposed offshore wind farm topology, consisting of a SLPC (single large power converter) that simultaneously controls a group of generators. This common converter can operate at a VF (variable frequency) or at a CF (constant frequency). The results are compared with the conventional onshore wind farm scheme, where individual power converters are connected to each turbine, guaranteeing maximum power generation for the entire wind farm. A methodology to analyze different wind speed and direction scenarios, and to compute the optimal electrical frequency for each one, is presented and applied to different case studies depending on the wind farm size. In order to obtain more realistic values of wind speeds, the wake effect amongst wind turbines is considered. A wake model considering single, partial and multiple wakes inside a wind farm and taking into account different wind directions, is presented. Both wind farm topologies are analyzed by means of simulations, taking into account both wind speed variability in wind farms and the number of wind turbines. The possible resulting benefits of simplifying the MPCs (multiple power converters) of each turbine, namely saving costs, reducing losses and maintenance and increasing the reliability of the system, are analyzed, focusing on the total power extraction. The SLPC-VF scheme is also compared with a CF scheme SLPC-CF, and it is shown that a significant power increase of more than 33% can be obtained with SLPC-VF.     

Experimental and analytical study of the structural response of segmental tunnel linings based on an in situ loading test.: Part 1: Test configuration and execution

During the last years the use of segmental linings in tunnels bored with tunnel boring machines (TBMs) have increased considerably. Despite this, uncertainties remain on the structural behavior of segmental tunnel linings. To overcome them, a new methodology for an in situ real scale test on this kind of tunnels was developed and applied on an experimental section placed at the new Line 9 (L9) of the metro of Barcelona. The main particularity of this test falls on its performance in the definitive placement of the rings and, therefore, in the real work conditions of the tunnel. The main advantage to previous real scale test experiences was the consideration of the real ground–structure interaction. The experimental section was composed by 15 rings built using steel fibers as a unique reinforcement. Significant loads were applied to the tunnel crown (max 3000 kN) by means of three hydraulic flat jacks embedded at the extrados of the loaded ring. A complete set of internal and external instrumentation was placed on the experimental section to obtain the necessary measurements to characterize the lining behavior. Such measurements were intensively treated and its main results are presented and analyzed in detail in this paper. This in situ test provides significant evidences of the structural response of SFRC segmental tunnel linings in hard ground conditions.     

Online error correcting output codes

This article proposes a general extension of the error correcting output codes framework to the online learning scenario. As a result, the final classifier handles the addition of new classes independently of the base classifier used. In particular, this extension supports the use of both online example incremental and batch classifiers as base learners. The extension of the traditional problem independent codings one-versus-all and one-versus-one is introduced. Furthermore, two new codings are proposed, unbalanced online ECOC and a problem dependent online ECOC. This last online coding technique takes advantage of the problem data for minimizing the number of dichotomizers used in the ECOC framework while preserving a high accuracy. These techniques are validated on an online setting of 11 data sets from UCI database and applied to two real machine vision applications: traffic sign recognition and face recognition. As a result, the online ECOC techniques proposed provide a feasible and robust way for handling new classes using any base classifier.     

A Fittingness Factor-Based Spectrum Management Framework for Cognitive Radio Networks

In order to increase cognitive radios (CRs) operation efficiency, there has been an increasing interest in strengthening awareness level about spectrum utilisation. In this respect, this paper proposes to exploit the fittingness factor concept to capture the suitability of spectral resources exhibiting time-varying characteristics to support a set of heterogeneous CR applications. First, a new knowledge management functional architecture for optimizing spectrum management has been constructed. It integrates a set of advanced statistics capturing the influence of the dynamic radio environment on the fittingness factor. Then, a knowledge manager (KM) exploiting these statistics to monitor time-varying suitability of spectrum resources has been proposed to support the spectrum selection (SS) decision-making process. In particular, a new Fittingness Factor-based strategy combining two SS and spectrum mobility (SM) functionalities has been proposed, following either a greedy or a proactive approach. Results have shown that, with a proper fittingness factor function, the greedy approach efficiently exploits the KM support at low loads and the SM functionality at high loads to introduce significant gains in terms of the user dissatisfaction probability. The proactive approach has been shown to maintain the introduced performance gain while minimizing the signalling requirements in terms of spectrum handover rate.     

Intravascular Ultrasound Tissue Characterization with Sub-class Error-Correcting Output Codes

Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on radial frequency, texture-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this sense, error-correcting output codes (ECOC) show to robustly combine binary classifiers to solve multi-class problems. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different sub-sets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers. Furthermore, the combination of RF and texture-based features also shows improvements over the state-of-the-art approaches.