Regional heterogeneity in wage distributions. Evidence from Spain.

Regional differences in real wages have been shown to be both large and persistent in the U.S. and the U.K., as well as in the economies of other countries. Empirical evidence suggests that wage differentials adjusted for the cost of living cannot only be explained by the unequal spatial distribution of characteristics determining earnings. Rather, average wage gap decomposition reveals the important contribution made by regional heterogeneity in the price assigned to these characteristics. This paper proposes a method for assessing regional disparities in the entire wage distribution and for decomposing the effect of differences across regions in the endowments and prices of the characteristics. The hypothesis forwarded is that the results from previous studies obtained by comparing average regional wages may be partial and non-robust. Empirical evidence from a matched employer-employee dataset for Spain confirms marked differences in wage distributions between regions, which do not result from worker and firm characteristics but from the increasing role of regional differences in the return to human capital.Regional Labour Markets, Human Capital, Wage Gap Decomposition, Counterfactual Distributions

Locally-adapted convolution-based super-resolution of irregularly-sampled ocean remote sensing data

Super-resolution is a classical problem in image processing, with numerous applications to remote sensing image enhancement. Here, we address the super-resolution of irregularly-sampled remote sensing images. Using an optimal interpolation as the low-resolution reconstruction, we explore locally-adapted multimodal convolutional models and investigate different dictionary-based decompositions, namely based on principal component analysis (PCA), sparse priors and non-negativity constraints. We consider an application to the reconstruction of sea surface height (SSH) fields from two information sources, along-track altimeter data and sea surface temperature (SST) data. The reported experiments demonstrate the relevance of the proposed model, especially locally-adapted parametrizations with non-negativity constraints, to outperform optimally-interpolated reconstructions.Comment: 4 pages, 3 figure

Chaos controller for switching regulators aiming enhanced design-space towards miniaturization

This paper tackles the control of fast-scale instabilities in a buck switching power converter aiming to expand its design-space towards miniaturization. After briefly revisiting the working principle of existing chaos controllers, the paper explores an alternative approach based on amplifying the harmonic at the switching frequency. Numerical simulations show that the proposed controller can concurrently improve both fast-scale and slow-scale stability margins. Finally, the paper proposes a chaos controller combined with an output ripple reduction network and studies their interaction with the aim of achieving both low-ripple and improved stability.Preprin

A convolve-and-MErge approach for exact computations on high-performance reconfigurable computers

This work presents an approach for accelerating arbitrary-precision arithmetic on high-performance reconfigurable computers (HPRCs). Although faster and smaller, fixed-precision arithmetic has inherent rounding and overflow problems that can cause errors in scientific or engineering applications. This recurring phenomenon is usually referred to as numerical nonrobustness. Therefore, there is an increasing interest in the paradigmof exact computation, based on arbitrary-precision arithmetic. There are a number of libraries and/or languages supporting this paradigm, for example, the GNUmultiprecision (GMP) library. However, the performance of computations is significantly reduced in comparison to that of fixed-precision arithmetic. In order to reduce this performance gap, this paper investigates the acceleration of arbitrary-precision arithmetic on HPRCs. A Convolve-And-MErge approach is proposed, that implements virtual convolution schedules derived from the formal representation of the arbitraryprecision multiplication problem. Additionally, dynamic (nonlinear) pipeline techniques are also exploited in order to achieve speedups ranging from 5x (addition) to 9x (multiplication), while keeping resource usage of the reconfigurable device low, ranging from 11% to 19%

Conducción autónoma y calibración de dispositivos en un entorno Smart City/F2C

Durante estos últimos años se ha podido ver un gran avance en el ámbito de la tecnología. El continuo crecimiento y auge de esta hace que esté presente cada vez con más frecuencia en tareas del día a día de cualquier habitante de una sociedad moderna. Las ciudades son el lugar donde más impacto ha tenido este gran cambio, ya que es en estas donde la mayoría de sus ciudadanos realizan sus actividades diarias, como por ejemplo ir al trabajo, hacer la compra, etc. Todas estas actividades se ven afectadas directamente por la tecnología, y a partir de las diferentes necesidades que estas requieren, aparecen un gran número de servicios a disposición de los ciudadanos. Este gran incremento tecnológico requiere que estos servicios sean cada vez más eficientes con la finalidad de poder servir al mayor número de personas posibles. Para hacer esto posible, se requiere de un gran número de recursos, que gestionados de la manera conveniente faciliten el desarrollo de tales servicios. Basándonos en estas necesidades, aparece el concepto de Smart City. Una ciudad inteligente (Smart City en inglés) tiene como objetivo principal poder utilizar la tecnología de la información y comunicación (TIC) con la finalidad de mejorar el nivel de vida de los ciudadanos que habitan en esta. Para el correcto desarrollo de estos servicios que una ciudad inteligente debe proporcionar, se ha de introducir el concepto de Fog to Cloud (F2C). El F2C pretende acercar las capacidades de las cuales dispone el Cloud a los usuarios, con la finalidad de obtener un tiempo de comunicación mucho más reducido que el que habría en una comunicación directa con el Cloud. Con este tiempo de comunicación tan reducido, se puede incrementar el número de servicios que puede proporcionar una ciudad inteligente. En este proyecto, se pretende llevar a cabo el desarrollo de una conducción autónoma la cual utilice las diferentes características proporcionadas por F2C en un entorno de ciudad inteligente, es decir, un entorno donde el vehículo pueda realizar diferentes acciones en tiempo real dependiendo del estado de diferentes dispositivos de esta ciudad, como pueden ser semáforos, otros vehículos, etc. A parte, se pretende desarrollar un sistema de calibración de los diferentes dispositivos de esta ciudad inteligente, con la finalidad de cerciorarnos de que el funcionamiento de estos es el correcto, de una manera sencilla y eficaz.Over the last few years, there has been a breakthrough in the field of technology. The continued growth and boom of it makes it increasingly frequent in the day-to-day tasks of any inhabitant of a modern society. Cities are the place where this big change has had the most impact, as it is in these where most of their citizens carry out their daily activities, such as going to work, go shopping, etc. All these activities are directly affected by technology and based on the different needs that these require, a large number of services appear available to citizens. This great technological increase requires these services to be increasingly efficient in order to be able to serve as many people as possible. To make this possible, a large number of resources are required, which conveniently managed facilitate the development of such services. Based on these needs, the concept of Smart City appears. A smart city has as its main objective to be able to use information and communication technology (TIC) in order to improve the standard of living of the citizens who live in it. For the proper development of these services that a smart city must provide, the concept of Fog to Cloud (F2C) mus be introduced. F2C aims to bring the capabilities available on the Cloud to the users, in order to obtain a much shorter communication time than there would be in a direct communication with the Cloud. With this reduced communication time, we could increase the number of services that a smart city could provide. In this project, it is intended to carry out the development of an autonomous driving which uses the different features provided by F2C in a smart city environment, which is an environment where the car can perform different actions in real-time depending on the state of different devices of the city, such as traffic lights, other vehicles, etc. In addition, it is intended to deveop a calibration system of the different devices of this smart city, in order to make sure that the performance of these is correct, in a simple and effective way

Multiobjective electric vehicle charging station locations in a city scale area: Malaga study case.

This article presents a multiobjective variation of the problem of locating electric vehicle charging stations (EVCS) in a city known as the Multiobjective Electric Vehicle Charging Stations Locations (MO-EVCS-L) problem. MO-EVCS-L considers two conflicting objectives: maximizing the quality of service of the charging station network and minimizing the deployment cost when installing different types of charging stations. Two multiobjective metaheuristics are proposed to address MO-EVCS-L: the Non-dominated Sorting Genetic Algorithm, version II (NSGA-II) and the Strength Pareto Evolutionary Algorithm, version 2 (SPEA2). The experimental analysis is performed on a real-world case study defined in Malaga, Spain, and it compares the proposed approaches with a baseline algorithm. Results show that the SPEA2 computes the most competitive solutions, even though both metaheuristics found an accurate set of solutions that provide different trade-offs between the quality of service and the installation costs.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Regional heterogeneity in wage distributions. Evidence from Spain.

Regional differences in real wages have been shown to be both large and persistent in the U.S. and the U.K., as well as in the economies of other countries. Empirical evidence suggests that wage differentials adjusted for the cost of living cannot only be explained by the unequal spatial distribution of characteristics determining earnings. Rather, average wage gap decomposition reveals the important contribution made by regional heterogeneity in the price assigned to these characteristics. This paper proposes a method for assessing regional disparities in the entire wage distribution and for decomposing the effect of differences across regions in the endowments and prices of the characteristics. The hypothesis forwarded is that the results from previous studies obtained by comparing average regional wages may be partial and nonrobust. Empirical evidence from a matched employer-employee dataset for Spain confirms marked differences in wage distributions between regions, which do not result from worker and firm characteristics but from the increasing role of regional differences in the return to human capital

Cambios en la distribución salarial en españa, 1995-2002. efectos a través del tipo de contrato

En este trabajo analizamos los cambios en la distribución salarial en España entre 1995 y 2002, utilizando la información contenida en la Encuesta de Estructura Salarial. El análisis revela un notable cambio en la distribución salarial que afecta, básicamente, a los niveles salariales bajos y medios, mientras que los correspondientes a los elevados permanecen inalterados entre ambos años. El análisis detallado de las distribuciones salariales para trabajadores con contrato indefinido y temporal muestra como estos últimos son los protagonistas de las mejoras salariales, mientras que los cambios en los niveles salariales intermedios son causados principalmente por los cambios producidos en la distribución de los trabajadores indefinidos. Empleando una técnica semi-paramétrica que permite considerar los efectos en el conjunto de la distribución salarial, encontramos que las variaciones observadas en las distribuciones salariales son consecuencia de cambios en la estructura retributiva, que han afectado de forma distinta a los trabajadores temporales (mejoras salariales homogéneas) y a los indefinidos, (reducción de los salarios intermedios)

Simultaneous Effect of Temperature and Irradiance on Growth and Okadaic Acid Production from the Marine Dinoflagellate Prorocentrum belizeanum

Benthic marine dioflagellate microalgae belonging to the genus Prorocentrum are a major source of okadaic acid (OA), OA analogues and polyketides. However, dinoflagellates produce these valuable toxins and bioactives in tiny quantities, and they grow slowly compared to other commercially used microalgae. This hinders evaluation in possible large-scale applications. The careful selection of producer species is therefore crucial for success in a hypothetical scale-up of culture, as are appropriate environmental conditions for optimal growth. A clone of the marine toxic dinoflagellate P. belizeanum was studied in vitro to evaluate its capacities to grow and produce OA as an indicator of general polyketide toxin production under the simultaneous influence of temperature (T) and irradiance (I0). Three temperatures and four irradiance levels were tested (18, 25 and 28 °C; 20, 40, 80 and 120 µE·m−2·s−1), and the response variables measured were concentration of cells, maximum photochemical yield of photosystem II (PSII), pigments and OA. Experiments were conducted in T-flasks, since their parallelepipedal geometry proved ideal to ensure optically thin cultures, which are essential for reliable modeling of growth-irradiance curves. The net maximum specific growth rate (µm) was 0.204 day−1 at 25 °C and 40 µE·m−2·s−1. Photo-inhibition was observed at I0 > 40 μEm−2s−1, leading to culture death at 120 µE·m−2·s−1 and 28 °C. Cells at I0 ≥ 80 µE·m−2·s−1 were photoinhibited irrespective of the temperature assayed. A mechanistic model for µm-I0 curves and another empirical model for relating µm-T satisfactorily interpreted the growth kinetics obtained. ANOVA for responses of PSII maximum photochemical yield and pigment profile has demonstrated that P. belizeanum is extremely light sensitive. The pool of photoprotective pigments (diadinoxanthin and dinoxanthin) and peridinin was not able to regulate the excessive light-absorption at high I0-T. OA synthesis in cells was decoupled from optimal growth conditions, as OA overproduction was observed at high temperatures and when both temperature and irradiance were low. T-flask culture observations were consistent with preliminary assays outdoors

GPT-3.5, GPT-4, or BARD? Evaluating LLMs Reasoning Ability in Zero-Shot Setting and Performance Boosting Through Prompts

Large Language Models (LLMs) have exhibited remarkable performance on various Natural Language Processing (NLP) tasks. However, there is a current hot debate regarding their reasoning capacity. In this paper, we examine the performance of GPT-3.5, GPT-4, and BARD models, by performing a thorough technical evaluation on different reasoning tasks across eleven distinct datasets. Our paper provides empirical evidence showcasing the superior performance of ChatGPT-4 in comparison to both ChatGPT-3.5 and BARD in zero-shot setting throughout almost all evaluated tasks. While the superiority of GPT-4 compared to GPT-3.5 might be explained by its larger size and NLP efficiency, this was not evident for BARD. We also demonstrate that the three models show limited proficiency in Inductive, Mathematical, and Multi-hop Reasoning Tasks. To bolster our findings, we present a detailed and comprehensive analysis of the results from these three models. Furthermore, we propose a set of engineered prompts that enhances the zero-shot setting performance of all three models.Comment: Accepted for publication at Elsevier's Natural Language Processing Journa