Low-pay higher pay and job satisfaction within the European Union: empirical evidence from fourteen countries

We examine differences in job satisfaction between low- and higher-paid workers within the European Union (EU). To do so The European Community Household Panel Data covering the period 1994-2001 is used. Then we test for differences in reported job satisfaction between low- and higher-paid workers. We also explain the existence of differences in the determinants of job satisfaction between these two types of workers and across countries. Our results indicate that low paid workers report a lower level of job satisfaction when compared with their higher paid counterparts in most countries, except in the UK. This supports the idea that low-wage employment in these countries mainly comprises low quality. The results also indicate that gap in average job satisfaction between low- and higher-paid workers is markedly wider in the Southern European countries than in the rest of EU. Finally, there are significant differences in the determinants of job satisfaction across countries. It seems then that a homogeneous policy may be inappropriate to increase satisfaction, and hence labour productivity, in the EU as a whole. Hence, an improvement of the quality of the jobs in the EU may require different policies. In particular, in some countries such as the United Kingdom removing low employment, namely through regulation, may worsen the workers’ well-being, although in other cases such a policy may lead to a totally different outcome.Job satisfaction,job quality,low-wage employment

RODRIGUEZ-SERRANO, PERRONNIN: LABEL EMBEDDING FOR TEXT RECOGNITION 1 Label embedding for text recognition

The standard approach to recognizing text in images consists in first classifying local image regions into candidate characters and then combining them with high-level word models such as conditional random fields (CRF). This paper explores a new paradigm that departs from this bottom-up view. We propose to embed word labels and word images into a common Euclidean space. Given a word image to be recognized, the text recognition problem is cast as one of retrieval: find the closest word label in this space. This common space is learned using the Structured SVM (SSVM) framework by enforcing matching label-image pairs to be closer than non-matching pairs. This method presents the following advantages: it does not require costly pre- or post-processing operations, it allows for the recognition of never-seen-before words and the recognition process is efficient. Experiments are performed on two challenging datasets (one of license plates and one of scene text) and show that the proposed method is competitive with standard bottom-up approaches to text recognition. 1 Introduction and related wor

El Proyecto fin de carrera como medio conductor para la iniciación a la investigación

Los proyectos fin de carrera son una herramienta útil para la atracción de estudiantes hacia las líneas de investigación de los distintos profesores. En base a la experiencia de los autores como profesores este artículo pretende presentar algunos de los principales errores que se comenten cuando se pretende utilizar los proyectos fin de carrera como mecanismo para introducir a los alumnos en el mundo de la investigación. De la misma manera se presentan algunas pautas para evitar caer en dichos errores.Peer Reviewe

Observations and Emerging Lessons from the 1998/99 High-Input Maize Program in Nampula Province, Mozambique

Research Results from the Department of Policy Analysis MARD-Directorate of Economicsfood security, food policy, Mozambique, maize, farmer associations, Crop Production/Industries, Q18,

Similarity-based Knowledge Transfer for Cross-Domain Reinforcement Learning

Transferring knowledge in cross-domain reinforcement learning is a challenging setting in which learning is accelerated by reusing knowledge from a task with different observation and/or action space. However, it is often necessary to carefully select the source of knowledge for the receiving end to benefit from the transfer process. In this article, we study how to measure the similarity between cross-domain reinforcement learning tasks to select a source of knowledge that will improve the performance of the learning agent. We developed a semi-supervised alignment loss to match different spaces with a set of encoder-decoders, and use them to measure similarity and transfer policies across tasks. In comparison to prior works, our method does not require data to be aligned, paired or collected by expert policies. Experimental results, on a set of varied Mujoco control tasks, show the robustness of our method in effectively selecting and transferring knowledge, without the supervision of a tailored set of source tasks.Comment: 30 pages, 7 figure

Modeling the external flow of a novel HorseShoe receiver and the evaluation of thermal performance

The linear receiver of a Parabolic Trough Collector is the most critical element in the entire system. The Universal Vacuum Air Collector concept is the most extended type of receiver in both experimental and industrial facilities. Besides their considerable cost, their efficiency usually drops as operation time passes. This is mainly due to a partial loss of vacuum in the evacuated annulus between the absorber and the glass cover. An alternative design called HorseShoe receiver is proposed in this work, whose main goal is to maintain the thermal performance throughout its entire lifespan. This innovative receiver is indicated for low-to-medium temperature ranges, which is particularly suitable for solar heat for industrial processes. It consists of a horseshoe-like cavity absorber having its upper border insulated. In addition, two main advantages can be taken by using two symmetric lenses as glass cover: reconcentrate solar radiation into the cavity (improvement of the intercept factor) and protect stratification conditions (reduction of thermal losses). A transient numerical model with customized boundary conditions has been implemented to evaluate both thermal performance and temperature difference in the absorber domain, which is critical for the thermal stress conditions. For that purpose and as a key contribution, not only the Heat Transfer Fluid (HTF) temperature but also the heat transfer coefficient in the duct are set. In particular, HTF temperature ranges from 80 °C to 220 °C and the inner heat transfer coefficient from 600 W/(mK) to 1800 W/(mK). Results show that numerical thermal performance is above 96%, which is mainly due to the reduction of thermal radiation losses, where the absorber active surface emittance is . (...)Second (corresponding) author J.J. Serrano-Aguilera acknowledges the support provided by Junta de Andalucía (Government of Andalusia) and Universidad de Málaga for the source of funding for the HERTERSOL project (UMA18-FEDERJA-195), as well as to Ministerio de Ciencia, Innovación Universidades (Spain) by means of the postdoc position: Ref No. FJCI-2017-32403 (Juan de la Cierva-Formación Postdoc Grant). Third author acknowledges the support of Universidad de Málaga, Spain through the Project WALICON, 2021. Authors also acknowledge funding for open access charge: Universidad de Málaga / CBUA

GoogleWave: Una herramienta para la evaluación de trabajos realizados fuera del aula

La evaluación de los trabajos en grupo es siempre difícil para el profesorado porque éste desconoce la cantidad de esfuerzo que ha dedicado cada alumno al trabajo asignado. Este artículo pretende presentar la herramienta Google Wave1 como una herramienta capaz de aportar una serie de funcionalidades no aportadas anteriormente por ninguna otra herramienta que facilitan al profesorado la evaluación del esfuerzo de cada alumno durante la realización de un trabajo en grupo.Peer Reviewe

Determinants of profitability in Spanish financial institutions. Comparing aided and non-aided entities

The last financial crisis has led to the greatest contribution of public funds ever made to Spanish banks. This paper studies why the need for support has been asymmetric, with not all of the institutions requiring aid. Based on profitability of assets (ROA), we determine using panel data econometric and logit response models the components of profit and loss accounts that generated profitability as well as the factors leading to some entities to ask for aid. The analyses show that before the beginning of the crisis there were significant differences between entities that needed aid and those that did not. The most profitable banks grounded their success in the traditional revenue components of financial institutions (such as margin on interest rates and commissions), as well as in revenues obtained from participated companies and extraordinary results. The model offers a tool to detect entities in difficulties in advance, reducing the financial and social costs of public interventions. The factors more impacting on profitability of Spanish institutions are also identifie